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Damage-Associated Molecular Patterns in Human Diseases Volume 3: Antigen-Related Disorders Walter Gottlieb Land
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Damage-Associated Molecular Patterns in Human Diseases
Walter Gottlieb Land
Damage-Associated Molecular Patterns in Human Diseases Volume 3: Antigen-Related Disorders
Walter Gottlieb Land German Academy for Transplantation Medicine Munich, Bayern, Germany Laboratoire d’ImmunoRhumatologie Moléculaire INSERM U1109, FHU OMICARE, ITI TRANSPLANTEX NG Faculté de Médecine, Université de Strasbourg Strasbourg, France
ISBN 978-3-031-21775-3 ISBN 978-3-031-21776-0 (eBook) https://doi.org/10.1007/978-3-031-21776-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Foreword I
DAMPs in Allograft and Tumor Rejection: The Early Engagement of the Başkent University. When searching for the authorial origin of Chap. 9 of the book on “DAMPs in Human Diseases—Antigen-Related Disorders,” one inevitably comes across the publication of the book on Innate Alloimmunity that was first published by the Başkent University Publisher in 2009/2011 [1, 2]. Indeed, in Part 2 of the two-part monograph, the emerging role of “Innate Alloimmunity” in organ transplantation was comprehensively presented and described for the first time worldwide. In my foreword of Part 2 in 2011, I wrote: “In the light of new insights into the mechanisms of innate immunity and innate alloimmunity, Baskent University in Ankara, Turkey, committed itself to support the development of this exciting new field of immunology. The Society of Innate Immunity (“SII”) was founded and officially registered in Ankara, and the first congress of this society was held at Baskent University in May 2007. This book, Innate Alloimmunity, reflects Baskent University’s ongoing commitment to contribute to the progress of this nascent field of modern immunology. We are confident that this book will change the scientific and practical viewpoints of transplantologists in their day-to-day work.” Today, I am pleased to see that I was right and that further progress in this emerging field of immunology has been made. Damage-associated molecular patterns are now generally accepted to operate as potent triggers of sterile inflammation. The unique molecules are released explicitly in response to tissue injury and cell death. DAMPs have a distinctly critical role in carcinogenesis and responses to tumor treatment. The presence of DAMPs is like a double-edged sword for the host regarding tumor development and allograft rejection. DAMPs alert the immune system to dying tumor cells and thus enable the host immune system to destroy them. However, since DAMPs can give rise to chronic inflammation, they can also trigger tumor development and progression. Recent evidence suggests—as already predicted by us in 2011—that DAMPs may also have a vital role in organ transplantation. Inflammation secondary to the release of DAMPs following solid organ transplantation can lead to acute allograft rejection, hinder transplant tolerance, and enhance the development of chronic allograft rejection. The release of DAMPs due to ischemia-reperfusion injury leads
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to the migration of innate immune cells to allografts. This process precedes T cell recruitment and eventually initiates allograft rejection. This book chapter provides essential insights into our understanding of how DAMPs are induced by and induce further allograft injury while providing a different perspective on the similarities and differences between allograft and tumor rejection. Thorough knowledge and study of the roles of DAMPs are necessary to understand the importance of using DAMPs as therapeutic targets to prevent allograft rejection and as therapeutics to prevent tumor growth. On a final note, I would like to congratulate Professor Walter Gottlieb Land for introducing such significant and valuable work again to the medical community and for his dedication to the field over these many years. References 1. Land WG. Innate alloimmunity - part 1: innate immunity and host defense [Internet]. 1st ed. Baskent University Publisher, Ankara; Pabst Science Publishers, Lengerich; 2011. https://www.amazon.com/Innate-Alloimmunity- Part-Immunity-Defense-ebook/dp/B00W6PJ97M. 2. Land WG. Innate alloimmunity. Part 2. Innate immunity and allograft rejection [Internet]. Baskent University Publisher, Ankara; Pabst Science Publishers, Lengerich; 2011. https://www.amazon.de/Innate-Alloimmunity-Immunity- Allograft-Rejection-ebook/. Mehmet Haberal Baskent University (Founder and Founder President) Ankara, Turkey Baskent University Division of Transplantation and Burns (Chair) Ankara, Turkey The Transplantation Society (Past President) Montréal, QC, Canada International Society for Burn Injuries (Past President) Floresville, TX, USA Royal Society of Medicine (Distinguished Fellow) London, UK Middle East Society for Organ Transplantation (Founder and Past President) Ankara, Turkey Turkish Transplantation Society (Founder and President) Ankara, Turkey Turkish World Transplantation Society (Founder and President) Ankara, Turkey
Foreword II
I have had the pleasure of knowing Dr. Walter Land since 2016 in a deep friendship that has gone from an initial contact during a meeting on “DAMPs across the Tree of Life” in Guanajuato, Mexico, to his visit to the Wide River Institute of Immunology, Seoul National University in 2017, to my visit to his home in Germany in 2019 on the occasion of a Council Meeting of the International DAMPs Association, up to a Scientific Advisory Board Meeting of Shaperon Inc. in 2021. During all those events, the discussion on the “Role of DAMPs in Human Diseases” was the driving momentum that brought us closer together. Indeed, since the first description of DAMPs by both of us [1, 2], the DAMPs have taken center stage in the pathogenesis of inflammatory diseases of various etiology. Volume 3 of his book on this emerging topic in biomedicine and practicing medicine includes the role of DAMPs in infections and autoimmune diseases. Dr. Land has masterfully succeeded in describing the outstanding role of DAMPs in these diseases in a didactically understandable way. For example, as described, it is the pathogen-induced emission of DAMPs in excess that leads to the life-threatening outcome in sepsis patients; and it is the DAMPs that mediate environmental factortriggered autoimmune disorders in genetically predisposed individuals. And as a consequence: it is the current development of novel inhibitors for DAMPs or DAMPs-initiated signaling cascade such as inflammasome that are expected to alleviate the outcome of these serious disorders. Finally, I am confident that this volume, like the previous two volumes, will help to critically raise awareness in the medical and paramedical community of the pathogenetic role of DAMPs and DAMPs-initiated signaling pathways in human diseases.
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References 1. Seong S-Y, Matzinger P. Hydrophobicity: an ancient damage-associated molecular pattern that initiates innate immune responses. Nat Rev Immunol. 2004;4:469–78. http://www.nature.com/articles/nri1372. 2. Land W. Allograft injury mediated by reactive oxygen species: from conserved proteins of Drosophila to acute and chronic rejection of human transplants. Part III: interaction of (oxidative) stress-induced heat shock proteins with toll-like receptor-bearing cells. Transplant Rev. 2003;17:67–86. https://linkinghub.elsevier.com/retrieve/pii/S0955470X02000095. S. Y. Seong Department of Microbiology and Immunology Seoul National University College of Medicine Seoul, Korea Department of Biomedical Sciences Seoul National University College of Medicine Seoul, Korea Wide River Institute of Immunology Seoul, Korea
Preface
This book is the continuation of the monograph on DAMPs in Human Diseases, whose Volume 1 has already been published in Springer International Publishing AG, part of Springer Nature 2018, and Volume 2 in Springer Nature Switzerland AG 2020. Volume 3 of the book, which you now have in your hands, is again written for professionals from all medical and paramedical disciplines who are interested in the emerging and ambitious biomedical field of cell stress/tissue injury-induced inflammation and immunity in human diseases. Hence, again, it goes without saying that the book has not been written for experts in the field of innate immunity and related disciplines. In keeping with the title of the book, Volume 3 covers, in an appropriate manner and adequate length, the practical and clinical aspects of DAMP-promoted human diseases, here, infectious and autoimmune diseases. However, the topic of DAMP- promoted transplant and tumor rejection, which was originally intended to be addressed in a similar appropriate manner, had to be shortened to a brief overview in nutshell form—given the renewed enormous increase in the number of incoming publications on DAMPs in human diseases, which exceeded the allotted scope of the book. Accordingly, the book is designed didactically and thematically divided into five parts, which cover ten chapters altogether. Chapter 1, the prologue in Part I, begins with an update on the classification of activating DAMPs and suppressing DAMPs (SAMPs), followed by a short overview of principles of the action of DAMPs in shaping antigen-related disorders. Then, the prologue addresses some perspectives of the danger/injury model of immunology as they have emerged with respect to antigen-related human disorders, for example, the topic of cytotoxic T lymphocyteand antibody-driven induction of regulated cell death leading to the emission of DAMPs; according to the motto: “The adaptive immune system calls in the cavalry.” Part II on “Infections” is divided into four chapters. In Chap. 2—besides discussing the pathogenetic actions on both the side of the infectious agent and the host and reviewing some characteristics of pathogens—emphasis is put on the possible integration of DAMPs into the “Red Queen Paradigm” as posed in relation to the host↔ pathogen interaction: A tentative model is being sketched for an evolutionary arms race between pathogens evolving virulence factors to invade and infect a host to survive and replicate, and the host evolving DAMPs and DAMP-mediated defense responses to overcome the infection. Chapter 3 describes then in more detail the ix
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various damaging virulence factors of pathogens and the counteracting defense responses of the host against them. These defensive processes consist of DAMP- promoted cell-autonomous stress responses and, when they fail, induction of subroutines of regulated cell death, which serve as prolific sources of DAMPs. This momentum of defense is intended to restore systemic organismal homeostasis via the creation of DAMP-driven inflammation-promoting and inflammation-resolving responses. Chapter 4 of Part II then elaborates on this DAMP-driven host immune defense program against pathogens. Here, I describe the role of the various pattern recognition receptors (PRRs) on/in cells of the innate immune system in triggering innate and adaptive immune pathways in infections by sensing DAMPs along with microbe-associated molecular patterns (MAMPs). In particular, the interplay between MAMPs, constitutive DAMPs, and inducible DAMPs in infections is addressed by discussing the concept that the recognition of MAMPs alone (plus microbial antigen) is not responsible for eliciting innate and adaptive immune responses to defend against pathogens. Instead, the action of MAMPs and DAMPs appears to be required in terms of an interplay to precipitate an effective and robust antimicrobial defense response via activation of innate immune cells, including dendritic cells. Chapter 5 then presents current knowledge on the pathogenetic role of DAMPs and SAMPs in severe infectious diseases. Focus is directed on the hyperinflammatory response triggered by the emission of DAMPs in excess and the inflammation-hyperresolving response driven by counterbalancing SAMPs. Here, three clinical examples are presented: (1) severe virus-induced pneumonia-related acute respiratory distress syndrome (ARDS), (2) life-threatening bacterium-induced sepsis, and (3) devastating protozoan-induced malaria. In particular, the concept is discussed that the well-known cytokine storm observed in ARDS is consistent with a dysregulated exaggerated hyperinflammatory response executed by DAMP- activated mobile and sessile PRR-bearing cells of the innate immune system. In this context, a conceptual model of a positive feed-forward loop is proposed, fired by DAMPs released by cells succumbing to regulated cell death: the initiation of an “avalanche of DAMPs.” Part III on “Autoimmunity” begins with Chap. 6, which focuses on some basic trajectories in autoimmunity. Specifically, it is stressed—as also impressively emphasized by Polly Matzinger elsewhere—that it is the responsibility of the peripheral bodily tissue cells equipped with a plethora of perceptive PRRs, rather than the innate or adaptive immune system, to take control over immunity, that is, to decide whether protective peripheral tolerance or dangerous immune responses to self are ultimately induced. The major mechanistic difference here is that, in immune tolerance, there are no DAMP-induced costimulatory molecules expressed either by tissue cells or antigen-presenting cells, but by contrast, coinhibitory molecules, whereas in immunity, the phenomenon of costimulation promoted by DAMPs and mediated by activated immunostimulatory antigen-presenting cells is operative. In Chaps. 7 and 8, then, the role of DAMPs and SAMPs in autoimmune diseases is comprehensively outlined by selecting for diseases: systemic lupus erythematosus and rheumatoid arthritis out of the group of systemic disorders and multiple sclerosis and type 1 diabetes mellitus out of the group of organ-specific disorders.
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Emphasis will be put on the role of DAMPs and SAMPs in the pathogenesis of these diseases, their use as biomarkers in diagnosis and prognosis, as well as their exploitation as targets and compounds for future therapeutic strategies. Since the publication of clinical data in these fields has just started, data from appropriate animal (rodent) studies are very often presented instead to stress their future importance for the clinic. When it comes to clinical trials, they are usually specially marked. Part IV “Transplants and Cancer” deals with the undesirable, therapeutic-to- combat, and desirable, therapeutic-to-promote functions of DAMPs in allograft and tumor rejection. Reports from the international literature, collected and presented in this ultrashort chapter written in the form of an abstract, provide compelling evidence for the notion that injury to cells, be they allograft cells or tumor cells, though different in nature, induces DAMPs that, by using similar innate immune trajectories, promote either adaptive alloimmunity or antitumor immunity. Finally, Part V, the epilogue (Chap. 10), presents some insinuations on the future role of the “DAMPome” in the pathogenesis and treatment of human diseases. Of note, all figures presented in this book are consciously oversimplified to spare the reader the burden of spending too much time deciphering all the molecules and pathways involved. My sources in writing this book mainly stem from the daily exploration of the MEDLINE database, especially PubMed (until September 2022). If not available online as a full-text article, I used the reprints requested by e-mail and sent by the corresponding authors in a thankful way. I want to use this opportunity to thank all these colleagues for their generosity. Certainly, as already stressed in Volumes 1 and 2, this book reflects just the beginning of a new era in medical/clinical practice that is rapidly growing. In particular, the phenomenon of regulated cell death has taken center stage as a prolific source of DAMPs emissions. In fact, the intersection between cell death and the immune system is currently regarded as one of the hottest topics in modern biomedical research; it is this scenario that is central to homeostatic healing responses, critical human pathologies, and the development of novel therapeutics. Also, it can be noticed that researchers in the field of DAMPs are still successfully trying to extend and re-classify the DAMPs and SAMPs according to their personal viewpoints, knowledge, and area of interest, a policy that results in many stimulating proposals for proper DAMPs classification. On the horizon, one can already see the contours of a “DAMPome,” which—as the final result of international DAMP research—is on track to being defined more stringently in the near future. Accordingly, many topics covered here have to be rewritten, modified, and amended in the near future. A veritable flood of new publications from this emerging research field awaits us. Finally, having researched, written, and illustrated the book entirely on my own, I cannot blame others for its imperfections. Any errors or omissions have been made in good faith, and I plead for the reader’s indulgence. Munich, Germany
Walter Gottlieb Land, Ancien Prof. Conv. Univ. Strasbourg; Prof. em. Dr. med.
Acknowledgments
First and foremost, I would like to once again thank my loving and supportive wife Veronika for her constant patience and inspiration throughout the process of writing and illustrating this Volume 3 of the book. Also, I would like to thank our children Olrik, Jochen, Eva, Oliver, and Michael for their continuous support and helpfulness. This publishing endeavor would certainly not have been possible without the continuous moral and financial support of the German Academy for Transplantation Medicine, represented by the Council Members Prof. Dr. mult. Nikolaus Knoepffler (President), Prof. Dr. med. Bernhard Banas (Vice President), and Prof. Dr. med. Helmut Arbogast (Secretary-General and Treasurer). Also, I am especially indebted to the distinguished members of the University of Strasbourg, Professor Seiamak Bahram and Professor Jean Sibilia (Dean of the Medical Faculty), who supported my project and managed to have granted a position as a “Professeur Conventionné” at the University of Strasbourg, France. Writing the third volume could not have been completed without the continuous support from some of my friends, to whom I am grateful for various reasons related to this project: Mr. Hildebrecht Braun, Dr. Peter Schmidt, Wolfgang Linss, Josef Griesbeck, Mary Walther, Emilija Schuhmacher, and Gudrun Krienke. Finally, I would also like to extend my thanks and appreciation to the whole Springer Nature staff, who edited my original prose and produced a high-quality product.
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Part I Prologue 1
Perspectives of the Danger/Injury Model of Immunology as Applied to Antigen-Related Human Disorders ���������������������������������� 3 1.1 Introduction���������������������������������������������������������������������������������������� 3 1.1.1 The Danger/Injury Model of Immunology ���������������������������� 3 1.1.2 DAMPs in Their Role as Friend and Foe�������������������������������� 4 1.1.3 The Four Described Antigen-Related Disorders in Light of the Action of DAMPs�������������������������������������������� 5 1.2 Classification of DAMPs: An Update ������������������������������������������������ 6 1.2.1 Introductory Remarks ������������������������������������������������������������ 6 1.2.2 Endogenous Constitutively Expressed DAMPs (Cat. I DAMPs)���������������������������������������������������������������������������������� 6 1.2.3 Endogenous Constitutively Expressed Injury-Modified Molecules (Cat. II DAMPs)���������������������������������������������������� 12 1.2.4 Endogenous Inducible DAMPs (Cat. III DAMPs) ���������������� 15 1.2.5 Exogenous DAMPs (Cat. IV DAMPs) ���������������������������������� 18 1.2.6 Résumé������������������������������������������������������������������������������������ 20 1.3 Some Principles of the Action of DAMPs in Shaping Antigen-Related Disorders������������������������������������������������������������������ 21 1.3.1 Emission of Three Signals by Activated Antigen-Presenting Cells�������������������������������������������������������� 21 1.3.2 History of Costimulation: The Signal 2���������������������������������� 21 1.3.3 The Concept of DAMP-Promoted Activation of APCs���������� 22 1.4 Cytotoxic T Lymphocyte- and Antibody-Driven Induction of Regulated Cell Death Leading to Emission of DAMPs: “The Adaptive Immune System Calls in the Cavalry”�������������������������������� 24 1.4.1 Introductory Remarks ������������������������������������������������������������ 24 1.4.2 Antibodies ������������������������������������������������������������������������������ 24 1.4.3 Cytotoxic CD8+ T Lymphocytes �������������������������������������������� 25 1.4.4 Cytotoxic B Lymphocytes������������������������������������������������������ 26 1.4.5 The Hypothetical Model of a DAMP-Driven Positive Feed- Forward Loop in Adaptive Immune Responses���������������������� 26
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1.5 DAMPs and SAMPs in Diagnosis and Prognosis������������������������������ 27 1.5.1 Introductory Remarks ������������������������������������������������������������ 27 1.5.2 DAMPs and SAMPs as Prognostic and Predictive Biomarkers������������������������������������������������������������������������������ 28 1.5.3 Résumé������������������������������������������������������������������������������������ 28 1.6 Use of DAMPs and SAMPs as Therapeutic Targets or Therapeutics 29 1.6.1 Introductory Remarks ������������������������������������������������������������ 29 1.6.2 DAMPs and SAMPs as Therapeutic Targets�������������������������� 29 1.6.3 SAMPs as Therapeutics in Chronic Inflammatory Processes 30 1.6.4 DAMPs as Therapeutics to Boost Innate Resistance�������������� 31 1.6.5 Résumé������������������������������������������������������������������������������������ 32 References���������������������������������������������������������������������������������������������������� 33 Part II Infections 2
Infectious Agents: From the Red Queen Paradigm to Some of Their Genuine Traits�������������������������������������������������������������������������������������������� 47 2.1 Introduction���������������������������������������������������������������������������������������� 47 2.2 To Start with Some Infection Enigmas ���������������������������������������������� 48 2.3 Pathogenetic Actions on the Side of the Infectious Agent: The Capacity of a Pathogen to Induce DAMPs in the Host as a Conceptual Definition of Virulence�������������������������������������������������� 49 2.3.1 Pathogenicity: Virulence in Light of Major Paradigms in Microbiology and Immunology���������������������������������������������� 49 2.3.2 Concepts of Pathogenicity and Virulence as a Consequence of Infectious Agent-Induced Damage to Host Cells: A Unifying Approach?������������������������������������������������������������ 50 2.3.3 The Role of Virulence Factors: Serving the Fitness of Pathogens but, Simultaneously, Evoking DAMP- Promoted Host Defense Responses���������������������������������������� 51 2.3.4 Some Thoughts on the Evolutionary Role of DAMPs and Innate Immune Recognition Receptors���������������������������� 53 2.3.5 The Red Queen Paradigm ������������������������������������������������������ 54 2.4 Pathogenetic Actions on the Side of the Host: Quality and Quantity of Innate/Adaptive Immune Defense Responses to Infectious Agent-Induced Damage���������������������������������������������������������������������� 55 2.5 The Pathogenesis of Infectious Diseases: A Brief Synopsis Ahead�������������������������������������������������������������������������������������������������� 57 2.5.1 Introductory Remarks ������������������������������������������������������������ 57 2.5.2 The Early Begin of the Disease: Recognition of Pathogens and the Harm They Induce������������������������������������������������������������ 57 2.5.3 Infectious Diseases as Clinical Manifestation of the Innate Immune Defense Program of the Host Against the Pathogenic Invaders���������������������������������������������������������������� 58
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2.5.4 Model Integration of DAMPs and SAMPs in Regulated and Dysregulated Inflammatory Defense Responses Determining the Pattern of Infectious Diseases���������������������� 60 2.5.5 Résumé������������������������������������������������������������������������������������ 62 2.6 Some Characteristics of Bacteria�������������������������������������������������������� 63 2.6.1 Introductory Remarks ������������������������������������������������������������ 63 2.6.2 Only a Brief Excerpt from the Fascinating History of Microbiology�������������������������������������������������������������������������� 64 2.6.3 The Continuous Fight Against Pathogenic Members of the Immense Bacterial World �������������������������������������������� 65 2.6.4 Structure of Bacteria �������������������������������������������������������������� 66 2.6.5 Bacterial Taxonomy���������������������������������������������������������������� 68 2.6.6 Bacterial Cell Division������������������������������������������������������������ 71 2.7 Some Characteristics of Viruses���������������������������������������������������������� 73 2.7.1 A Few Historical Remarks������������������������������������������������������ 73 2.7.2 Viral Infections: From a Simple Common Cold to Fatal Sepsis�������������������������������������������������������������������������������������� 74 2.7.3 Some Features of Viruses�������������������������������������������������������� 75 2.7.4 Structure and Taxonomy of Viruses (in Brief)������������������������ 75 2.7.5 Replication Cycle of Viruses: The Seed for the Generation of DAMPs������������������������������������������������������������ 78 2.8 Fungal Infections�������������������������������������������������������������������������������� 87 2.8.1 Introductory Remarks ������������������������������������������������������������ 87 2.8.2 Structure of Fungi ������������������������������������������������������������������ 88 2.8.3 Classification of Fungi������������������������������������������������������������ 89 2.8.4 Reproduction of Fungi������������������������������������������������������������ 89 2.9 Parasitic Infections������������������������������������������������������������������������������ 90 2.9.1 Introductory Remarks ������������������������������������������������������������ 90 2.9.2 Protozoans������������������������������������������������������������������������������ 90 2.9.3 Helminths�������������������������������������������������������������������������������� 92 2.10 Outlook ���������������������������������������������������������������������������������������������� 93 References���������������������������������������������������������������������������������������������������� 93 3
Virulence of Pathogens and the Counteracting Responses of the Host�������������������������������������������������������������������������������������������������� 109 3.1 Introduction���������������������������������������������������������������������������������������� 109 3.2 Bacterial Virulence������������������������������������������������������������������������������ 110 3.2.1 Introductory Remarks ������������������������������������������������������������ 110 3.2.2 Nondamaging Bacterial Virulence Factors Paving the Way to Induce Injury�������������������������������������������������������� 110 3.2.3 Indirectly Damaging Bacterial Virulence Factors������������������ 112 3.2.4 Directly Damaging Bacterial Virulence Factors of Extracellular Bacteria �������������������������������������������������������� 117 3.2.5 Intracellular Bacteria: Production of Indirectly and Directly Damaging Virulence Factors������������������������������ 123
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3.2.6 Mechanisms of Bacteria to Subvert Host Defense Responses�������������������������������������������������������������������������������� 125 3.2.7 Résumé������������������������������������������������������������������������������������ 126 3.3 Viral Virulence������������������������������������������������������������������������������������ 126 3.3.1 The Virulence Program of Viruses������������������������������������������ 126 3.3.2 Virulence Factors in Terms of Molecular Perturbations in Viral Replication Cycle������������������������������������������������������ 127 3.3.3 Viroporins: A Peculiar Viral Virulence Factor������������������������ 127 3.3.4 Virulence Secondary to Viral Invasion: Mechanisms to Subvert Host Defense Responses�������������������������������������� 129 3.3.5 Résumé������������������������������������������������������������������������������������ 129 3.4 Fungal Virulence �������������������������������������������������������������������������������� 129 3.4.1 Introductory Remarks ������������������������������������������������������������ 129 3.4.2 Host Membrane Distension and Disruption by Mechanical Forces������������������������������������������������������������������ 130 3.4.3 Fungal Toxins�������������������������������������������������������������������������� 130 3.4.4 Fungal Extracellular Vesicles�������������������������������������������������� 131 3.4.5 Résumé������������������������������������������������������������������������������������ 131 3.5 Parasitic Virulence������������������������������������������������������������������������������ 131 3.5.1 Protozoan Virulence���������������������������������������������������������������� 131 3.5.2 Helminthic Virulence�������������������������������������������������������������� 132 3.6 Cell-Autonomous Stress Responses During Infections���������������������� 133 3.6.1 Introductory Remarks ������������������������������������������������������������ 133 3.6.2 Extracellular Vesicle Formation upon PathogenMediated Cell Stress �������������������������������������������������������������� 134 3.6.3 Autophagy in Defense Against Pathogens������������������������������ 135 3.6.4 Oxidative Stress and Antioxidative Stress Responses������������ 137 3.6.5 The Heat Shock Response������������������������������������������������������ 138 3.6.6 Endoplasmic Reticulum Stress and the Unfolded Protein Response�������������������������������������������������������������������� 139 3.6.7 DNA Damage Response �������������������������������������������������������� 142 3.6.8 Résumé������������������������������������������������������������������������������������ 143 3.7 Regulated Cell Death as Prolific Sources of DAMPs: A Powerful Host Defense Program Against Infection������������������������ 143 3.7.1 Introductory Remarks ������������������������������������������������������������ 143 3.7.2 Subroutines of Regulated Cell Death�������������������������������������� 144 3.7.3 Apoptosis→Secondary Necrosis: The Failure to Clear a Dying Cell������������������������������������������������������������������ 145 3.7.4 Necroptosis: A Cellular Suicide for Host Defense ���������������� 146 3.7.5 Pyroptosis: The Result of Pathogen-Induced Activation of Inflammasomes������������������������������������������������������������������ 153 3.7.6 PANoptosis: A Unique Inflammatory Cell Death Pathway Integrating Other Cell Death Trajectories������������������������������ 164 3.7.7 Formation of NETs and NETosis�������������������������������������������� 165
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3.7.8 Ferroptosis: An Iron-Dependent, Oxidative Form of Regulated Necrosis ������������������������������������������������������������ 171 3.7.9 Parthanatos������������������������������������������������������������������������������ 173 3.8 Outlook and Future Perspectives�������������������������������������������������������� 173 References���������������������������������������������������������������������������������������������������� 174 4
The DAMP-Driven Host Immune Defense Program Against Pathogens���������������������������������������������������������������������������������������������������� 203 4.1 Introduction���������������������������������������������������������������������������������������� 203 4.2 MAMPs and DAMPs as Key Players in Defense Responses to Pathogens�������������������������������������������������������������������������������������������� 204 4.2.1 Introductory Remarks ������������������������������������������������������������ 204 4.2.2 Microbe-Associated Molecular Patterns�������������������������������� 205 4.2.3 Damage-Associated Molecular Patterns �������������������������������� 206 4.2.4 Résumé������������������������������������������������������������������������������������ 206 4.3 Sensing of MAMPs and DAMPs by Pattern Recognition Molecules Triggering Innate Immune Pathways in Infections ���������� 207 4.3.1 Introductory Remarks ������������������������������������������������������������ 207 4.3.2 Cellular Pattern Recognition Molecules and Signaling Pathways Used to Sense Pathogens and to Cope with Stress and Injury Caused by Them: An Overview������������������ 209 4.3.3 Detection of Invading Bacteria: Receptor Molecules and their Helpers �������������������������������������������������������������������� 221 4.3.4 Detection of Viruses: The Impressive Arsenal of Different Receptors Implicated in Antiviral Defense ���������������������������� 221 4.3.5 Production of Inducible DAMPs Upon Bacteria and Virus Detection: The Type I Interferon and Tumor Necrosis Factor Systems������������������������������������������������������������������������ 226 4.3.6 Detection of Fungi by Cellular Pattern Recognition Molecules�������������������������������������������������������������������������������� 228 4.3.7 Detection of Parasites by Cellular Pattern Recognition Molecules�������������������������������������������������������������������������������� 228 4.3.8 Humoral Innate Immune Sensing of Pathogens���������������������� 229 4.3.9 Epigenetic Regulation of Innate Immune Responses to Infections�������������������������������������������������������������������������������� 230 4.4 MAMP/DAMP-Mediated Regulation of Defense Responses to Pathogens�������������������������������������������������������������������������������������������� 231 4.4.1 Introductory Remarks ������������������������������������������������������������ 231 4.4.2 Multiple-Level Mechanisms to Regulate Infectious Inflammation �������������������������������������������������������������������������� 232 4.4.3 MAMP/DAMP-Triggered Initiation and Promotion of Infectious Inflammation������������������������������������������������������ 233 4.4.4 The Model of SAMP-Driven Resolution of Inflammation ���� 235 4.5 Innate Lymphoid Cells and Unconventional T Cells in Infections ���� 237 4.5.1 Introductory Remarks ������������������������������������������������������������ 237
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4.5.2 Innate Lymphoid Cells������������������������������������������������������������ 238 4.5.3 Unconventional T Cells���������������������������������������������������������� 240 4.6 DAMP-Shaped Adaptive Immune Responses to Pathogens �������������� 242 4.6.1 Introductory Remarks ������������������������������������������������������������ 242 4.6.2 Pathogen-Derived Antigens���������������������������������������������������� 242 4.6.3 Uptake, Processing, and Presentation of Bacterial and Viral Antigens by Dendritic Cells������������������������������������ 243 4.6.4 Maturation of Immunostimulatory Dendritic Cells in Infection���������������������������������������������������������������������������������� 244 4.6.5 Cellular Adaptive Immune Responses������������������������������������ 247 4.6.6 Humoral Adaptive Immune Responses���������������������������������� 248 4.6.7 Immune Complexes Triggering NET Formation and NETosis in Infections: An Emerging Concept ���������������� 249 4.6.8 Innate and Adaptive Immune Memory ���������������������������������� 254 4.7 Conclusions and Future Perspectives�������������������������������������������������� 254 4.7.1 Introductory Remarks ������������������������������������������������������������ 254 4.7.2 Interplay Between MAMPs and DAMPs�������������������������������� 255 4.7.3 The Changing Role of MAMPs in Pathogen-Induced Inflammation/Immunity���������������������������������������������������������� 255 4.7.4 Recognition of MAMPs and DAMPs in Infections: Simultaneously or Sequentially?�������������������������������������������� 257 4.7.5 Résumé������������������������������������������������������������������������������������ 259 References���������������������������������������������������������������������������������������������������� 261 5
The Pathogenetic Role of DAMPs in Severe Infectious Diseases���������� 285 5.1 Introduction���������������������������������������������������������������������������������������� 285 5.2 MAMP/DAMP-Triggered Dysregulation of Defense Responses to Pathogens�������������������������������������������������������������������������������������������� 286 5.2.1 Introductory Remarks ������������������������������������������������������������ 286 5.2.2 Chronic/Persistent Inflammatory Responses to Infections ���� 286 5.2.3 Hyperinflammatory Syndrome Associated with Infections: The Case of Sepsis������������������������������������������������ 288 5.3 Exploring DAMPs in Clinical Practice: An Emerging Area of Research in Infectious Diseases�������������������������������������������� 290 5.3.1 Introductory Remarks ������������������������������������������������������������ 290 5.3.2 High Mobility Group Box 1���������������������������������������������������� 291 5.3.3 S100A Proteins (Calgranulins) ���������������������������������������������� 293 5.3.4 Extracellular Nucleic Acids, Histones, and Nucleosomes������ 294 5.3.5 SAMPs������������������������������������������������������������������������������������ 297 5.3.6 Résumé������������������������������������������������������������������������������������ 297 5.4 Pathogenetic Impact of MAMPs and DAMPs on Viral Diseases: The Example of Pneumonia-Related Acute Respiratory Distress Syndrome�������������������������������������������������������������������������������������������� 298 5.4.1 Introductory Remarks ������������������������������������������������������������ 298
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5.4.2 Demonstration of MAMPs, DAMPs, and SAMPs in Respiratory Virus Infections ���������������������������������������������� 300 5.4.3 Change of Viewpoints in the Pathogenesis of ALI → ARDS���������������������������������������������������������������������� 303 5.4.4 Cellular Events in ARDS�������������������������������������������������������� 303 5.4.5 MAMP/DAMP/SAMP-Driven Dysregulated Innate Immune Responses in ARDS�������������������������������������������������� 305 5.4.6 The Cytokine Storm as a DAMP-Driven Dysregulated Hyperinflammatory Response������������������������������������������������ 308 5.4.7 Pathogenetic Role of Nonviral-Induced DAMPs in Respiratory Virus Infection: A Theory�������������������������������� 309 5.4.8 DAMPs and SAMPs as Diagnostics and Prognostics in Respiratory Virus Infection ���������������������������������������������������� 312 5.4.9 DAMPs and SAMPs as Therapeutic Targets or Therapeutics in Respiratory Virus Infection �������������������������� 314 5.4.10 Résumé and Future Perspectives�������������������������������������������� 314 5.5 Pathogenetic Impact of MAMPs and DAMPs on Bacterial Diseases: The Example of Sepsis������������������������������������������������������� 315 5.5.1 Introductory Remarks ������������������������������������������������������������ 315 5.5.2 Experimental Sepsis Models�������������������������������������������������� 317 5.5.3 Demonstration of DAMPs������������������������������������������������������ 318 5.5.4 Demonstration of SAMPs ������������������������������������������������������ 323 5.5.5 Pathophysiology-Pathogenesis of Sepsis�������������������������������� 328 5.5.6 Epigenetics in Sepsis�������������������������������������������������������������� 338 5.5.7 DAMPs and SAMPs as Biomarkers �������������������������������������� 338 5.5.8 DAMPs and SAMPs as Therapeutic Targets and Therapeutics���������������������������������������������������������������������������� 340 5.5.9 Résumé and Future Perspectives�������������������������������������������� 343 5.6 Pathogenetic Impact of MAMPs and DAMPs on Protozoan Diseases: The Example of Malaria ���������������������������������������������������� 344 5.6.1 Introductory Remarks ������������������������������������������������������������ 344 5.6.2 Demonstration of DAMPs������������������������������������������������������ 344 5.6.3 Demonstration of SAMPs ������������������������������������������������������ 346 5.6.4 Pathogenesis of Malaria���������������������������������������������������������� 347 5.6.5 Résumé������������������������������������������������������������������������������������ 348 5.7 DAMP/SAMP-Dependent Clinical Outcomes of Infectious Diseases: Sketching a Narrative Summing-Up Model����������������������� 348 5.7.1 The Different Clinical Facets of an Infection ������������������������ 349 5.7.2 Integration of DAMP/SAMP-Driven Immune Responses in Different Clinical Courses of Infections (Exemplified in Part by COVID-19 Pneumonia): A Tentative Proposal������ 349 5.7.3 The Future of DAMPs and SAMPs in Improving Outcomes of Infectious Diseases�������������������������������������������� 351 References���������������������������������������������������������������������������������������������������� 352
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Part III Autoimmunity 6
Basic Trajectories in Autoimmunity�������������������������������������������������������� 383 6.1 Introduction���������������������������������������������������������������������������������������� 383 6.2 Some Basic Principles in the Development of Autoimmune Diseases���������������������������������������������������������������������������������������������� 385 6.2.1 Introductory Remarks: What Is Known Today ���������������������� 385 6.2.2 The Concept of T Cell and B Cell Tolerance to Self at a Glance ������������������������������������������������������������������������������������ 386 6.2.3 Development of Autoimmunity in Light of the Danger/Injury Model�������������������������������������������������������������� 395 6.2.4 Immune Complexes Triggering NETosis as a Pivotal Source of DAMPs Emission in Autoimmune Diseases���������� 401 6.2.5 Autoimmune Mechanisms of Tissue Destruction: Another Source of DAMPs Emission �������������������������������������������������� 405 6.2.6 Résumé������������������������������������������������������������������������������������ 408 6.3 The Role of the Environment in the Etiopathogenesis of Autoimmune Diseases�������������������������������������������������������������������� 409 6.3.1 Introductory Remarks ������������������������������������������������������������ 409 6.3.2 Models of Environmental Factor-Promoted Generation of Autoantigens���������������������������������������������������� 410 6.3.3 Environmental Factors Promoting the Emission of DAMPs Through Induction of Regulated Cell Death�������� 417 6.3.4 Role of the Microbiota in the Pathogenesis of Autoimmune Diseases�������������������������������������������������������� 423 6.3.5 Résumé������������������������������������������������������������������������������������ 425 6.4 Hereditary Factors in the Etiopathogenesis of Autoimmune Diseases���������������������������������������������������������������������������������������������� 426 6.4.1 Introductory Remarks ������������������������������������������������������������ 426 6.4.2 Genetics���������������������������������������������������������������������������������� 426 6.4.3 Epigenetics������������������������������������������������������������������������������ 429 6.4.4 Résumé������������������������������������������������������������������������������������ 435 6.5 Outlook and Future Perspectives�������������������������������������������������������� 435 References���������������������������������������������������������������������������������������������������� 436
7
DAMPs in Systemic Autoimmune Diseases �������������������������������������������� 457 7.1 Introduction���������������������������������������������������������������������������������������� 457 7.2 Systemic Lupus Erythematosus���������������������������������������������������������� 457 7.2.1 Introductory Remarks ������������������������������������������������������������ 457 7.2.2 Experimental Animal Models ������������������������������������������������ 458 7.2.3 Pathogenesis-Orchestrating Interrelationship Between Environmental Triggers, Genetic Predisposition, and Epigenetic Modifications ������������������������������������������������ 459 7.2.4 Pathogenetic Principles of Autoantigen Formation and Emission of DAMPs�������������������������������������������������������� 469
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7.2.5 DAMP-Promoted, Pattern Recognition MoleculeMediated Autoinflammatory Pathways���������������������������������� 471 7.2.6 Is There an Insufficient Inflammation-Resolving Role of SAMPs in SLE? �������������������������������������������������������� 474 7.2.7 DAMPs and Their Cognate Pattern Recognition Receptors Triggering Maturation of Dendritic Cells, Production of Type 1 Interferons, and Activation of B Cells�������������������������������������������������������������������������������� 475 7.2.8 The Autoreactive T Cell Response������������������������������������������ 487 7.2.9 The Autoreactive B Cell Response ���������������������������������������� 489 7.2.10 Organ-Specific Tissue Injury�������������������������������������������������� 495 7.2.11 Summarizing Hypothetical Model to SLE Pathogenesis: Immune Complex-Induced NETs and NETosis and the DAMP-Promoted Positive Feed-Forward Loop as Drivers of Type I Interferon Secretion by Plasmacytoid Dendritic Cells������������������������������������������������������������������������ 497 7.3 Rheumatoid Arthritis�������������������������������������������������������������������������� 499 7.3.1 Introductory Remarks ������������������������������������������������������������ 499 7.3.2 Experimental Animal Models ������������������������������������������������ 500 7.3.3 The Pathogenesis of Rheumatoid Arthritis: Cellular Events�������������������������������������������������������������������������������������� 500 7.3.4 Pathogenesis-Orchestrating Interrelationship Between Environmental Triggers, Genetic Predisposition, and Epigenetic Modifications ������������������������������������������������ 502 7.3.5 Pathogenetic Principles of Autoantigen Formation and Emission of DAMPs�������������������������������������������������������� 508 7.3.6 DAMPs Triggering Synovial Autoinflammatory Responses�������������������������������������������������������������������������������� 512 7.3.7 Evidence for SAMPs to Drive Synovial InflammationResolving Responses�������������������������������������������������������������� 515 7.3.8 DAMPs Promoting Maturation of Antigen-Presenting Cells���������������������������������������������������������������������������������������� 516 7.3.9 The Autoreactive T Cell Response������������������������������������������ 518 7.3.10 The Autoreactive B Cell Response ���������������������������������������� 519 7.3.11 Summarizing Hypothetical Model to Rheumatoid Arthritis Pathogenesis: The DAMP-Driven Positive Feed-Forward Loop of Innate/Adaptive Autoimmune Responses ���������������� 525 7.4 DAMPs and SAMPs as Biomarkers, Therapeutic Targets, and Therapeutics in Systemic Autoimmune Disorders������������������������������ 527 7.4.1 Introductory Remarks ������������������������������������������������������������ 527 7.4.2 DAMPs and SAMPs as Diagnostic and Prognostic Biomarkers in Systemic Lupus Erythematosus���������������������� 528 7.4.3 Avoidance, Blockade, or Removal of DAMPs and Administration of SAMPs as Therapeutic Options in Systemic Lupus Erythematosus������������������������������������������ 530
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7.4.4 DAMPs and SAMPs as Diagnostic and Prognostic Biomarkers in Rheumatoid Arthritis�������������������������������������� 532 7.4.5 Avoidance, Blockade, or Removal of DAMPs and Administration of SAMPs as Therapeutic Options in Rheumatoid Arthritis�������������������������������������������������������������� 534 7.4.6 Résumé������������������������������������������������������������������������������������ 536 7.5 Outlook and Future Directions������������������������������������������������������������ 536 References���������������������������������������������������������������������������������������������������� 537 8
DAMPs in Organ-Specific Autoimmune Diseases���������������������������������� 569 8.1 Introduction���������������������������������������������������������������������������������������� 569 8.2 Multiple Sclerosis ������������������������������������������������������������������������������ 569 8.2.1 Introductory Remarks ������������������������������������������������������������ 569 8.2.2 Experimental Animal Models ������������������������������������������������ 571 8.2.3 Pathogenesis-Orchestrating Interrelationship Between Environmental Triggers, Genetic Predisposition, and Epigenetic Modifications ������������������������������������������������ 573 8.2.4 A Special Note to the Role of the Microbiota in Multiple Sclerosis �������������������������������������������������������������� 581 8.2.5 Pathogenetic Principles of Autoantigen Formation and Emission of DAMPs�������������������������������������������������������� 582 8.2.6 DAMPs and Their Cognate Pattern Recognition Receptors Triggering Neuroinflammatory Responses ���������������������������� 587 8.2.7 DAMPs and Their Cognate Pattern Recognition Receptors Triggering Activation of Antigen-Presenting Cells���������������� 591 8.2.8 The Autoreactive T Cell and B Cell Responses���������������������� 597 8.2.9 Hypothetical Model to Reconcile the “Inside-Out” and the “Outside-In” Paradigms in Multiple Sclerosis Pathogenesis: The DAMP-Driven Positive Feed-Forward Loop of Chronic Inflammatory Demyelinating Processes�������������������������������������������������������� 600 8.3 Type 1 Diabetes Mellitus�������������������������������������������������������������������� 603 8.3.1 Introductory Remarks ������������������������������������������������������������ 603 8.3.2 Experimental Animal Models ������������������������������������������������ 604 8.3.3 Pathogenesis-Orchestrating Interrelationship Between Environmental Triggers, Genetic Predisposition, and Epigenetic Modifications ������������������������������������������������ 605 8.3.4 Pathogenetic Principles of Autoantigen Formation and Emission of DAMPs�������������������������������������������������������� 614 8.3.5 DAMPs and Their Cognate Pattern Recognition Receptors Triggering Islet Inflammation�������������������������������� 619 8.3.6 DAMP/PRR-Activated Antigen-Presenting Cells Promoting Activation of T and B Cells�������������������������� 620
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8.3.7 The Autoreactive T Cell and B Cell Responses���������������������� 622 8.3.8 Insulitis and Islet β-Cell Destruction�������������������������������������� 625 8.3.9 Summarizing Hypothetical Model to T1DM Pathogenesis: Is the End-Stage Diabetes the Result of a DAMP-Driven Positive Feed-Forward Loop? ���������������� 626 8.4 DAMPs and SAMPs as Biomarkers, Therapeutic Targets, and Therapeutics in Organ-Specific Autoimmune Disorders ������������ 626 8.4.1 Introductory Remarks ������������������������������������������������������������ 626 8.4.2 DAMPs and SAMPs as Diagnostic and Prognostic Biomarkers in Multiple Sclerosis�������������������������������������������� 628 8.4.3 Avoidance, Blockade, or Removal of DAMPs and Administration of SAMPs as Therapeutic Options in Multiple Sclerosis �������������������������������������������������������������� 629 8.4.4 DAMPs and SAMPs as Diagnostic and Prognostic Biomarkers in Islet Transplantation (as a Substitute for Type 1 Diabetes Mellitus) ������������������������������������������������ 631 8.4.5 Blockade or Removal of DAMPs and Administration of SAMPs as Therapeutic Options in Islet Transplantation (as a Substitute for Type 1 Diabetes Mellitus)���������������������������������������������������������������������������������� 633 8.4.6 Résumé������������������������������������������������������������������������������������ 634 8.5 Outlook and Future Directions������������������������������������������������������������ 635 References���������������������������������������������������������������������������������������������������� 635 Part IV Transplants and Cancer 9
The Undesirable and Desirable Functions of DAMPs in Allograft and Tumor Rejection���������������������������������������������������������������� 659 9.1 Introduction���������������������������������������������������������������������������������������� 659 9.2 Allograft Rejection������������������������������������������������������������������������������ 660 9.2.1 Introductory Remarks ������������������������������������������������������������ 660 9.2.2 Allograft Injury-Induced DAMPs as Main Players in Triggering Innate Alloimmune Responses�������������������������� 660 9.2.3 Chronic Allograft Dysfunction - Chronic Allograft Rejection �������������������������������������������������������������������������������� 664 9.2.4 DAMPs as Biomarkers and Therapeutic Targets�������������������� 664 9.3 Tumor Rejection��������������������������������������������������������������������������������� 665 9.3.1 Introductory Remarks ������������������������������������������������������������ 665 9.3.2 Immunogenic Cell Death and the Secretion/Release of DAMPs ������������������������������������������������������������������������������ 665
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9.3.3 ICD-Associated Secretion and Release of DAMPs Triggering Antitumor Immune Response ������������������������������ 667 9.3.4 Immunogenic Cell Death-Induced DAMPs for Future Cancer Therapy ���������������������������������������������������������������������� 667 9.4 Outlook ���������������������������������������������������������������������������������������������� 668 References���������������������������������������������������������������������������������������������������� 669 Part V Epilogue 10 Approaching the DAMPome: Evolution in Medicine? �������������������������� 677
Abbreviations
AA AAA ACD ACE ACPA ACR ADs ADAM(s) ADCC ADCP ADP-ribosyl-EF-2 AECI/II AGER AHR AIA AIDS AIM2 AIRE AITD AKI ALI ALOX ALRs Alum ALX ALX/FPR2 AMR ANAs Ang (1-7) Ang II AnxA1 AOP APN
Arachidonic acid ATPases associated with diverse cellular activities Accidental cell death Angiotensin-converting enzyme Anti-citrullinated proteins/peptide antibodies American College of Rheumatology Autoimmune diseases A disintegrin and metalloproteinase domain-containing protein(s) Antibody-dependent cell-mediated cytotoxicity Antibody-dependent cellular phagocytosis ADP-ribosylated elongation factor 2 Alveolar epithelial cells type I/II Advanced glycosylation end product-specific receptor Aryl hydrocarbon receptor Antigen-induced arthritis Acquired immune deficiency syndrome Absent in melanoma 2 Autoimmune regulator Autoimmune thyroid disease Acute kidney injury Acute lung injury Arachidonic acid-lipoxygenase Absent in melanoma 2 (AIM2)-like receptors Aluminum hydroxide Lipoxin A4 Lipoxin receptor/N-formyl peptide receptor-2 Antimicrobial resistance Antinuclear antibodies Angiotensin (1-7) Angiotensin II Annexin A1 Adverse outcome pathway Aminopeptidase N xxvii
xxviii
AP-1 APCs APECED
Abbreviations
Activator protein-1 Antigen-presenting cells Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (also known as APS-1) ARDS Acute respiratory distress syndrome ARE Antioxidant response element AREG Amphiregulin AS Ankylosing spondylitis ASC Apoptosis-associated speck-like protein containing a caspase recruitment domain ASCs Antibody-secreting cells Ascl2 Achaete-scute homolog 2 ASIA Autoimmune syndrome induced by adjuvants ATFs Activating transcription factors ATG Autophagy-related ATIs α-amylase/trypsin inhibitors ATM Ataxia telangiectasia mutated ATP Adenosine 5′-triphosphate ATR Ataxia telangiectasia and Rad3 related AutoAg(s) Abbreviation for autoantigen(s) as used, e.g., in figures (in SLE, standing for autoantigenic native or modified molecules, such as NAs [DNA, RNA] complexed with nuclear proteins like chromatin/chromatin fragments and ribonucleoproteins/ribonucleoprotein fragments) A1/2/3AR A1/2/3 adenosine receptor BAFF B cell-activating factor BALF Bronchoalveolar lavage fluid BBB Blood–brain barrier BCs Baltimore classes Bcl6 B cell lymphoma 6 protein BCR B cell receptor BD Brain death BIM Bcl-2 interacting mediator of cell death BiP Binding immunoglobulin protein BIR Baculovirus inhibitor of apoptosis repeat BMSCs Bone marrow stromal cells BSA Bovine serum albumin bZip Basic region-leucine zipper Cs Complement components CAE Cuprizone autoimmune encephalitis CAIA Collagen antibody-induced arthritis CALR Calreticulin cAMP Cyclic adenosine monophosphate CARD Caspase-activating and recruiting domain CARS Compensatory anti-inflammatory response syndrome
Abbreviations
xxix
CASP(S) Caspase(s) CASP Colon ascendens stent peritonitis CAT Category CBP CREB binding protein CCAAT Cytidine-cytidine-adenosine-adenosine-thymidine CCLs Chemokine (C-C motif) ligands CDC Complement-dependent cytotoxicity cDCs Conventional or myeloid dendritic cells CEACAM1 Carcinoembryonic antigen-related cell adhesion molecule 1 CeD Celiac disease cf. Compare figure CFA Complete Freund’s adjuvant cGAMB Cyclic GMP-AMP cGAS Cyclic GMP-AMP synthase Chap. Chapter ChgA Chromogranin A CHGA Chromogranin A CHOP Cytidine-cytidine-adenosine-adenosine-thymidine- enhancer-binding homologous protein CIA Collagen type I-induced arthritis CLP Cecal ligation and puncture CLRs C-type lectin-like receptors cMSAg Candidate MS-associated CNS autoantigens CNS Central nervous system COPD Chronic obstructive pulmonary disease COVID-19 Coronavirus disease of 2019 COX Cyclooxygenases CpG Unmethylated cytosine phospho-bound guanosine CPZ Cuprizone CRs Complement receptors CRD Carbohydrate recognition domain, also known as the CTLD CREB cAMP response element-binding protein cRNA Complementary RNA CRP C-reactive protein CSF Cerebrospinal fluid CSR Class switch recombination CTD Carboxyl(C)-terminal domain CTGF Connective tissue growth factor CTLA-4 Cytotoxic T lymphocyte-associated antigen-4 CTLD C-type lectin-like domain CTLs CD8+ cytotoxic T lymphocytes (=T cells) CTS-B or L Cysteine proteases cathepsins B and L CVD(s) Cardiovascular disease(s) CXCLs Chemokine (C-X-C motif) ligands C1q Complement component 1q
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C3a, C5a DAI DAMPs DCs DC-SIGN
Abbreviations
Complement fragments 3a and 5a (anaphylatoxins) DNA-dependent activator of IFN regulatory factors Damage (or danger)-associated molecular patterns Dendritic cells Dendritic cell-specific intercellular adhesion molecule-3- grabbing non-integrin DDR DNA damage response DDX3X DEAD-box helicase 3 X-linked DIA Drug-induced autoimmunity DIC Disseminated intravascular coagulation DM Dermatomyositis DMARDs Disease-modifying anti-rheumatic drugs DMVs Double-membrane vesicles DNA Deoxyribonucleic acid DNA-ICs Self DNA-autoantibodies immune complexes DNA-PK DNA-dependent protein kinase DNAse1 Deoxyribonuclease I DPP4 Dipeptidyl peptidase 4 DSBs Double-strand DNA breaks dsDNA Double-stranded DNA dsRNA Double-stranded RNA DT Diphtheria toxin dTGN Dispersed trans-Golgi network DV Dengue virus dysDAMPs Dyshomeostatic DAMPs (i.e., change of a homeostatic molecular pattern) E Envelope protein (coronavirus structural protein) EAE Experimental autoimmune encephalomyelitis eATP Extracellular adenosine 5′-triphosphate EBNA1 Epstein–Barr nuclear antigen 1 EBV Epstein–Barr Virus EC(s) Endothelial cell(s) eCIRP Extracellular cold-inducible RNA-binding protein ECM Extracellular matrix EF Edema factor EF Extrafollicular eIF2α Eukaryotic translation initiation factor 2 ELSs Ectopic lymphoid structures EMCV Encephalomyocarditis virus eQTL Expression of quantitative trait loci ER Endoplasmic reticulum ERAD Endoplasmic reticulum-associated protein degradation ERGIC Endoplasmic reticulum-Golgi intermediate compartment ERK Extracellular signal-regulated protein kinase ERO Endoplasmic reticulum oxidoreductin
Abbreviations
xxxi
ESCRT Endosomal sorting complexes required for transport ET-1,2,3 Endothelin-1,2,3 EULAR European League Against Rheumatism EVs Extracellular vesicles FAK Focal adhesion kinase FasL Fas ligand Fc Fragment crystallizable (region) FcRs Fragment crystallizable receptors FCN-A72 Ficolin-A/2 FDCs Follicular dendritic cells FeTPPS Fe(III)5,10,15,20-tetrakis(4-sulfonatophenyl)porphyrinato chloride FLSs Fibroblast-like synoviocytes Foxp3 Forkhead box protein 3 FP Formyl peptides FPRs Formyl peptide receptors FRET Fluorescence resonance energy transfer FtsZ Filamenting temperature-sensitive mutant Z GAD Glutamic acid decarboxylase GADA GAD autoantibodies GAL(s) Galectin(s) γδ T cells Gamma delta T cells GATA1/2/3 GATA-binding protein 1/2/3 GC Germinal center GDP Guanosine diphosphate GM-CSF Granulocyte-macrophage colony-stimulating factor GPCRs G protein-coupled receptors GPR32 G protein-coupled receptor 32 GPI Glycosylphosphatidylinositol GPX(s) Glutathione peroxidase(s) GRP78 Glucose-regulated protein 78 GSDMB Gasdermin B GSDMD Gasdermin D GSDME Gasdermin E GSH Glutathione GSSG Glutathione (GSH)/glutathione disulfide GTP Guanosine-5′-triphosphate GWAS Genome-wide association studies GzmA/B Granzyme A/B HA Hyaluronan HA Hemagglutinin HAdV Human adenovirus HB-EGF Heparin-binding epidermal growth factor-like growth factor HBV Hepatitis B virus HCMV Human cytomegalovirus
xxxii
Abbreviations
HCV Hepatitis C virus HHV Human herpes virus HIF1α Hypoxia-inducible factor 1-alpha HIN Hematopoietic interferon-inducible nuclear protein HIP Hybrid insulin peptides HIV Human immunodeficiency virus Hla Hemolysin-α HLA Human leukocyte antigen HMGB1 High mobility group box 1 protein HMTs Histone methyltransferases hnRNPL Heterogenous nuclear ribonucleoprotein L HPV(s) Human papillomavirus(es) HS Heparan sulfate HSCs Hepatic stellate cells HSF(s) Heat shock transcription factor(s) HSP(s) Heat shock protein(s) HspB5 Heat shock protein B5 = alpha B-crystallin HSR Heat shock response HSVs Herpesviruses HTNV Hantaan virus H2O2 Hydrogen peroxide IAA Autoantibodies to insulin IAPP Islet amyloid polypeptide IA-2 Insulinoma antigen-2 IAV(s) Influenza A virus(es) IBD Inflammatory bowel disease IC(s) Immune complex(es) ICA Islet cell autoantigens ICD Immunogenic cell death ICM Inflachromene ICOS Inducible T cell costimulator ICOSL Inducible T cell costimulator ligand ICU Intensive care unit iDCs Immature dendritic cells IECs Intestinal epithelial cells IFIH1 Interferon induced with helicase C domain 1 IFI16 Interferon-inducible protein 16 IFNs Interferons IFNAR1 Interferon alpha and beta receptor subunit 1 Ig Immunoglobulin IGRP Islet-specific glucose-6-phosphatase catalytic subunit related protein IgSF Immunoglobulin superfamily IKKs Inhibitors of nuclear factor-kappa B (NF-κB) kinases IL(s) Interleukin(s)
Abbreviations
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ILCs Innate lymphoid cells IL-1→x Interleukin-1→x iNKT cells Invariant natural killer T cells IRAK Interleukin-1-receptor-associated kinase IRF(s) Interferon regulatory factor(s) IRGs Interferon (IFN)-gamma immunity-related guanosine-5′triphosphate hydrolase enzymes (GTPases) IRI Postischemic reperfusion injury ISG Interferon-stimulated gene ISGF3 Interferon-stimulated gene factor 3 ISRE Interferon-stimulated response element ITAM Immunoreceptor tyrosine-based activation motifs ITIM Immunoreceptor tyrosine-based inhibitory motifs iTregs Inducible Foxp3+ regulatory T cells IVIG Intravenous immunoglobulins JAK Janus kinase JNK C-Jun-N-terminal protein kinase KEAP1 Kelch-like erythroid cell-derived protein with CNC homology (ECH)-associated protein 1 KO Knockout (also denoted as “deficient” or −/−) Ku Ku70–Ku80 complex LADA Latent autoimmune diabetes in adults LAP Latency-associated protein LAP Light chain 3 (LC3)-associated phagocytosis LBP LPS-binding protein LCMV Lymphocytic choriomeningitis virus LCMV-GP/NP Lymphocytic choriomeningitis virus-glycoprotein/ nucleoprotein LDGs Low-density granulocytes LF Lethal factor LFA-1 Lymphocyte function-associated antigen-1 LGP2 Laboratory of genetics and physiology 2 lncRNAs Long noncoding RNAs LNPs Lipid nanoparticles LoM Lung-only mice LOX Lipoxygenases LPLs Lysophospholipids LPS Lipopolysaccharide LRRs Leucine-rich repeats LTA Lipoteichoic acid LTB4 Leukotriene B4 LXs Lipoxins LXA4 Lipoxin A4 MAA Malondialdehyde-acetaldehyde mAbs Monoclonal antibodies
xxxiv
Abbreviations
MAC Membrane attack complex MAG Myelin-associated glycoprotein MAIT cells Mucosal-associated invariant T cells MAL Myd88-adapter-like MAM Mitochondrial-associated membranes MAMPs Microbe-associated molecular patterns MAPKs Mitogen-activated protein kinases MaRs Maresins, for macrophage mediators in resolving inflammation MAVS Mitochondrial antiviral signaling proteins MBL Mannose-binding lectin MBP Myelin basic protein MDA Malondialdehyde MDA5 Melanoma differentiation-associated gene 5 MD-2 Myeloid differentiation protein 2 MDR Multidrug-resistant MDSCs Myeloid-derived suppressor cells MERS Middle East respiratory syndrome METs Macrophage extracellular traps MG Myasthenia gravis MHC Major histocompatibility complex MHC-I/II Major histocompatibility complex class I/class II molecules MICA MHC Class I polypeptide-related sequence A MICB MHC Class I polypeptide-related sequence B MICs MHC class I chain-related proteins Mincle Macrophage-inducible C-type lectin or CLEC4E miRNA MicroRNA (small noncoding RNA) MLKL Mixed lineage kinase domain-like protein MLSs Macrophage-like synoviocytes MMPs Matrix metalloproteinases mNGS Metagenomic NGS MODS Multiple organ dysfunction syndrome MOF Multiple organ failure MOG Myelin oligodendrocyte glycoprotein MPO Myeloperoxidase MR1 MHC-I-related molecule 1 MRN Mre11–RAD50–NBS1 mRNA Messenger RNA MS Multiple sclerosis MSCs Mesenchymal stem cells MSU Monosodium urate crystals mTECs Medullary thymic epithelial cells mtDNA Mitochondrial DNA mtFPs Mitochondrial formyl peptides
Abbreviations
mTOR MVs MyD88 M1/M2 M1 or M1-like N NA(s) naDAMPs NA NACHT
NAD+ NADPH NAIP
NAMPs nauAgs NCRs ncRNA nDNA NDV NE NEK7 NEMO NET(s) NETosis NFAT(1/2) NF-κB NGS nIgM NIEHS NK cells NKG2D NKT cells NLRs
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Mechanistic target of rapamycin (previously referred to as the mammalian target of rapamycin) Membrane vesicles Myeloid differentiation primary response gene 88 Membrane or matrix protein 1/2 from influenza A virus Macrophages with predominantly proinflammatory activities Nucleocapsid (coronavirus structural protein) Nucleic acid(s) Nucleic acid DAMPs (i.e., endogenous DNA and RNA acting as DAMPs) Neuraminidase (e.g., of influenza A virus) Neuronal apoptosis inhibitor protein (NAIP), MHC Class II transactivator/transcription activator (CIITA), plant het product (HET-E), and telomerase-associated protein 1 (TP1) protein Nicotinamide adenine dinucleotide Nicotinamide adenine dinucleotide phosphate NLR-family caspase activation and recruitment domain (CARD)-containing protein 4 (NLRC4), NLR-family apoptosis inhibitory protein; also called neuronal apoptosis inhibitor protein Nanoparticle-associated molecular patterns Nuclear autoantigens Natural cytotoxicity receptors Noncoding RNAs Nuclear DNA Newcastle disease virus Neutrophil elastase Never in mitosis A (NIMA)-related kinase 7 NF-kappa-B essential modulator, also known as inhibitor of nuclear factor-kappa B kinase subunit gamma (IKK-γ) Neutrophil extracellular trap(s) Neutrophil extracellular trap (NET)-associated cell death Nuclear factor of activated T cells 1 (member 1/2) Nuclear factor-kappa B Next-generation sequencing Natural immunoglobulin M National Institute of Environmental Health Sciences Natural killer cells Natural killer group 2 D Natural killer T cells Nucleotide-binding oligomerization domain (NOD)-like receptors
xxxvi
NLRC4
Abbreviations
NLR-family caspase activation and recruitment domain (CARD)-containing protein 4 NLRP3 Nucleotide-binding and oligomerization domain (NOD, “NACHT”)-leucine-rich repeat (LRR) receptor (NLR)family, pyrin domain (PYD)-containing 3 NMDA N-methyl-D-aspartate • NO Nitric oxide NOD Nucleotide-binding oligomerization domain NOD mice Non-obese diabetic mice NOX Nicotinamide adenine dinucleotide phosphate- dependent oxidase NP Nucleoprotein NPD1 Neuroprotectin D1 NPR NADPH-P450 reductase Nrf1/Nrf2 Nuclear factor-erythroid 2 p45-related factors 1/2 Nsps Nonstructural proteins (e.g., coronavirus) nuDAMPs Nuclear DAMPs NZB mouse New Zealand black mouse O2− Superoxide • OH Hydroxyl radical Omega-3 LC-PUFAs Omega-3 long-chain polyunsaturated fatty acids OMVs Outer membrane vesicles OMR Osmotic membrane rupture ONOO− Peroxynitrite OPN Osteopontin ORFs Open reading frames OSEs Oxidation-specific epitopes OxCL Oxidized cardiolipin OxLDLs Oxidized low-density lipoproteins OXPHOS Oxidative phosphorylation OxPLs Oxidized phospholipids PA Polymerase acidic protein PAD(s) Peptidyl arginine deiminase(s) PAMPs Pathogen-associated molecular patterns PARP-1 Poly (ADP-ribose) synthetase-1 Parthanatos Poly ADP-ribose polymer PB1/2 Polymerase basic protein 1/2 PC Phosphatidylcholine PCR Polymerase chain reaction PD-1 Programmed cell death protein-1 pDCs Plasmacytoid dendritic cells PD-1 Programmed cell death protein 1 PD-L1/2 Programmed cell death protein ligand 1/2
Abbreviations
xxxvii
PDs Protectins PDCD1 Programmed cell death 1 PDI Protein disulfide isomerase PDX1 Pancreatic duodenal homeobox factor 1 PE Phosphatidylethanolamine PERK Protein kinase RNA-like endoplasmic reticulum kinase PGs Proteoglycans PGE2 Prostaglandin E2 PGF2α Prostaglandin F2α PGN Peptidoglycan PICS Persistent inflammation, immunosuppression, and catabolism syndrome PI3K Phosphatidylinositol 3 kinase PIKKs Phosphatidylinositol 3 kinase-related kinases PIP Phosphatidylinositol phosphate PKC Protein kinase C PKR Protein kinase, regulated by dsRNA PLP (Myelin) proteolipid protein pLxIS motif p, hydrophilic residue, x, any residue, S, phosphorylation site PM Particulate matter pMHC-I/II Peptide/major histocompatibility complex class/class II molecules PMNs Polymorphonuclear neutrophils pol III Polymerase III (holoenzyme) poly (I:C) Polyinosinic:polycytidylic acid PRAT4A Protein associated with Toll-like receptor 4 PRDXs Peroxiredoxins PRMs Pattern recognition molecules proTα Prothymosin alpha PRRs Pattern recognition receptors PS Phosphatidylserine PtdIns4P Phosphatidylinositol-4-phosphate PtdSer Phosphatidylserine PtdSer-lysoPS Phosphatidylserine-lysophosphatidylserine PTGR2 Prostaglandin reductase 2 PTMs Posttranslational modifications pTregs Peripherally derived Tregs (also called iTregs) PTX3 Pentraxin 3 PUFA-PLs Polyunsaturated fatty acids-containing phospholipids PYD Pyrin domain (also abbreviated as NLRP) P2XRs P2X purinoceptors qSOFA Quick sequential organ failure assessment
xxxviii
RA RAS RAGE RAMPs RANK RANKL RBCs RBD RCD RdRp REDD1 RF RHIM RhoA RIG-I RIP(s) RIPK(1-3) RIP-GP RLRs RN RNA RNPs RNS RORγt ROS RPA rRNA RSV RTC RT-PCR Rvs S SA SAA SAFA SAMPs SAP SARS-CoV SARS 3a Sec SF
Abbreviations
Rheumatoid arthritis Renin-angiotensin system Receptor for advanced glycation end products Resolution-associated molecular patterns Receptor activator of NF-κB Ligand of receptor activator of NF-κB Red blood cells Receptor-binding domain Regulated cell death RNA-dependent RNA polymerase Regulated in development and DNA damage responses 1 Rheumatoid factor Receptor-interacting protein homotypic interaction motif Ras homolog gene family, member A Retinoic acid-inducible gene (protein) I Receptor-interacting protein(s) Receptor-interacting serine/threonine-protein kinase (1-3) Rat insulin promoter-glycoprotein Rig I-like receptors; also referred to helicase retinoic acid- inducible gene I-like receptors Regulated necrosis Ribonucleic acid Ribonucleoprotein particles, i.e., RNA-binding proteins Reactive nitrogen species Retinoic acid receptor-related orphan receptor-gamma t Reactive oxygen species Replication protein A Ribosomal RNA Respiratory syncytial virus Replication-transcription complex Reverse transcription-polymerase chain reaction Resolvins, for: resolution phase interaction products Spike glycoprotein (Coronavirus structural protein) Sialic acid Serum amyloid A Scaffold attachment factor A Suppressing/inhibiting DAMPs SLAM (signaling lymphocytic activation molecule)-associated protein Severe acute respiratory syndrome coronavirus SARS-coronavirus ORF3a (Bacterial) secretion pathway Synovial fluid
Abbreviations
xxxix
SHM Somatic hypermutation siRNA Small interfering RNA SIRS Systemic inflammatory response syndrome SKIV2L Super viralicidic activity 2-like gene SLAM Signaling lymphocytic activation molecule SLE Systemic lupus erythematosus SLOs Secondary lymphoid organs Sm Smith antigen SMART A sensor for MLKL activation by RIPK3 based on FRET SMCs Smooth muscle cells SMOCs Supramolecular organizing centers SNPs Single nucleotide polymorphisms SOD Superoxide dismutase SOFA Sequential organ failure assessment SopB Salmonella outer protein B SPA4 Surfactant protein-A-derived peptide 4 SPMs Specialized proresolving mediators sRNA(s) Small noncoding RNA(s) SS Secretion systems SS Sjögren’s syndrome SSBs Single-strand DNA breaks SSc Systemic sclerosis, also called scleroderma ssDNA Single-stranded DNA ssRNA Single-stranded RNA STAT 1/2/3/4 Signal transducer and activator of transcription 1/2/3/4 STING Stimulator of interferon genes Syk A member of the Syk family of tyrosine kinases S1PR5 Sphingosine-1 phosphate receptor 5 TA Teichoic acid TAAs Tumor-associated antigens TAK1 Transforming growth factor-β-activated kinase 1 Tat (Bacterial) Twin-arginine translocation pathway TB Tuberculosis TBK1 TANK-binding kinase 1 TCR T cell receptor TD T cell-dependent TEDDY The environmental determinants of diabetes in the young TF Tissue factor TFAM Transfactor A, mitochondrial Tfh cells Follicular helper T cells TGF-β Transforming growth factor-beta TGN Trans Golgi network TG2 Tissue transglutaminase
xl
Abbreviations
Th1/Th2 T helper cell type 1/2 THP-1 A human monocyte/macrophage cell line TI T cell-independent TIR Toll-interleukin-1 receptor TIRAP TIR domain-containing adapter protein TLOs Tertiary lymphoid organs TLRs Toll-like receptors TLTs Tertiary lymphoid tissues TM Transmembrane TME Tumor microenvironment TMEV-IDD Theiler’s murine encephalitis virus-induced demyelinating disease TMPRSS2 Transmembrane serine protease 2 TNC Tenascin-C TNF Tumor necrosis factor TNFAIP3 Tumor necrosis factor (TNF) alpha induced protein 3 TNFR1/2 Tumor necrosis factor receptor 1/2 tNGS Targeted next-generation sequencing TNT Tuberculosis necrotizing toxin tolDCs Tolerogenic dendritic cells TPE Tuberculous pleural effusion TRAs Tissue-restricted antigens (also denoted as tissue-specific antigens—TSAs) TRAF Tumor necrosis factor-receptor-associated factor TRAIL Tumor necrosis factor-related apoptosis-inducing ligand TRAILR1/2 Tumor necrosis factors-related apoptosis-inducing ligand receptor 1/2 TRAM TRIF-related adaptor molecule Tregs Regulatory T cells TREX1 Exonuclease 1 TRIF Toll/IL-1(TIR) domain-containing adaptor inducing interferon-β tRNA(s) Transfer RNA(s) TSAs Tissue-specific antigens tsRNA Transfer RNA-derived small noncoding RNA tTregs Thymus regulatory T cells TXNIP Thioredoxin-interacting protein TYK2 Tyrosine kinase 2 T1DM Type 1 diabetes mellitus ULBP 1-6 UL16-binding protein 1-6 Unc93B Unc-93 homolog B1 UPR Unfolded protein response UVR Ultraviolet radiation
Abbreviations
U11snRNA Small nuclear RNA U11 VACV Vaccinia virus VAL Venom allergen-like vmRNA Viral mRNA vRNA Viral RNA (viral RNA genome segment) vRNP Viral ribonucleoprotein VZV Varicella-zoster virus WGS Whole-genome sequencing WHO World Health Organization Wnt Wingless-type ZBP1 Z-DNA-binding protein 1 ZNT8 Zinc transporter-8
xli
Part I Prologue
1
Perspectives of the Danger/Injury Model of Immunology as Applied to Antigen-Related Human Disorders
1.1 Introduction As with volumes 1 and 2 of the book [1, 2], the preparation of this volume is again a continuing attempt to view human diseases through the “lens of the danger/injury model of Immunity.” The core of this model suggests that stressed/injured cells generate “danger signals,” also known as damage-associated molecular patterns (DAMPs) [3, 4], or “alarmins” [5] that activate pattern recognition molecule (PRM)bearing cells of the innate immune system and shape T/B cell-mediated adaptive immune responses. (Note, PRM is interchangeably and synonymously used with pattern recognition receptor (PRR) throughout the book). As disorders, infections, autoimmune diseases, and allograft rejection have been chosen. In addition, rejection of tumors is addressed, which precisely does not occur in the case of tumor growth, but which—as a future therapeutic target—is intended to be triggered by the administration of DAMPs.
1.1.1 The Danger/Injury Model of Immunology The model was formulated and published in 1994 as the third major paradigm in Immunology, holding that the host immune system does not care about self vs. nonself but rather that any form of cell stress/tissue injury is the critical feature that initiates an immune response. In other words, the danger/injury model held and still holds that the key triggers in instigating an innate/adaptive immune response are primarily not foreign, altered-self, or self antigenic stimuli but are endogenous molecules derived from damaged body cells and/or tissues, which interact with immune cells together with antigens. The model emerged from two sources: (1) its description by Polly Matzinger in the form of an ingenious, extremely plausible, self- coherent chain of argumentation on theoretical grounds, resulting in the stringent
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 W. G. Land, Damage-Associated Molecular Patterns in Human Diseases, https://doi.org/10.1007/978-3-031-21776-0_1
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conclusion that Burnet’s self/nonself discrimination theory of immune responses is inappropriate [6]; and (2) its publication by Walter Land and the Munich transplant group on the basis of significant data from a clinical trial in transplant patients, providing compelling evidence that tissue injury induces immunity [7] (more details of the three major paradigms developed in immunology are described in Vol. 1 [1], chapter (Chap.) 2, pp. 13–23). This is now 29 years ago. In the meantime, multiple articles of both groups have been published, and many dedicated and encouraged colleagues all over the world have joined the new stream in immunology described in 1994. Consequently, scientific research in this field has always been continuing to advance, especially in the fields of immunology, biomedicine, and clinical medicine. At this point, writing an up-to-date report on the DAMPs with respect to their role in antigen-related human diseases is a difficult task as it requires adjustments and changes when new emerging information about previously described facts, thoughts, and dogmas steadily has been come and still comes in. And, indeed, new information on the universal role of DAMPs, including their role in antigen-related human diseases, is being published continuously, week after week and month after month, and recently even at an accelerating pace. Thus, on September 30, 2022, at the date of submission of the manuscript, a search for “DAMPs” in PubMed retrieved 2431 results.
1.1.2 DAMPs in Their Role as Friend and Foe Before going into more detail, an important point should be made that was already addressed in Vol. 1 [1], Sect. 4.4, Fig. 4.1, pp. 39/40: DAMPs can behave as friend or foe—and this not only to humans but probably to all organisms living on our planet. First of all, their evolutionarily determined function is to promote injury- induced defense responses; the aim always being to repair damaged tissue—that is, to restore and maintain homeostasis. To fulfill these tasks, DAMPs elicit various innate immune responses, which drive the execution of inflammation, proliferation, and regulated cell death (RCD) in a context-dependent manner. In fact, it currently appears that all organisms on our planet use DAMPs to signal that cell stress and tissue injury have occurred, be it of sterile or infectious nature [8, 9]. Typical examples of such defensive responses across the tree of life are (1) volatile DAMP- promoted indirect defense responses of plants against insect herbivores [10, 11]; (2) a Toll-mediated antimicrobial defense pathway in Drosophila that is triggered by a yet-unidentified DAMP [12]; (3) a danger signal—activated broad antimicrobial innate immune defense response in Caenorhabditis elegans, triggered by the microbe-induced bloating of the intestinal lumen triggers [13]; (4) the innate immune response of shrimps to infections that is presaged by the release of high mobility group box 1 (HMGB1) [14]; and (5) an L-HMGB1-mediated or -initiated pathogen defense in fish/lampreys [15]. This is good news.
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However, there is also another side of the coin: emerging evidence from a growing number of experimental and clinical studies suggests that uncontrolled emission of DAMPs plays a crucial role in the promotion of pathologies and disorders, again, a phenomenon that can be observed across the tree of life. Thus, dysregulated production of DAMPs can drive such pathologies/disorders as demonstrated in plants by the hypersensitive response, death of individual cells, and reduced growth of the entire organism [16]; as shown in corals by enhanced heat stress-driven coral bleaching [17]; and as exemplified in humans by hyperinflammation as a classical feature of infection-associated sepsis such as seen in coronavirus disease 2019 (COVID-19) patients in the intensive care unit [18], or chronic or acute-repetitive inflammatory immune responses in autoimmune diseases, or acute and chronic inflammatory immune response in allograft rejection [19]. These three DAMP- driven antigen-related disorders are the subject of this volume 3, along with the fourth group of diseases that exhibit an opposite pathogenetic principle of DAMPs: namely, their failure to combat cancer. In fact, these disorders develop for a very simple and plausible reason: The tumors usually do not emit danger signals (i.e., DAMPs) and thus escape surveillance by the host's immune defense.
1.1.3 The Four Described Antigen-Related Disorders in Light of the Action of DAMPs While the antigens involved in the above-mentioned four categories of disease intrinsically determine the specificity of the immune response, the DAMPs—by upregulating the expression of costimulatory molecules on activated antigen- presenting cells (APCs) such as dendritic cells (DCs), simply summed up as “costimulation”—ensure that naïve T cells are activated to actually elicit an immune response. In other words, the role of DAMPs in all these diseases is similar in that they act as the igniting spark that triggers an immune response in the first place, whereas the specificity-determining nature of the antigens is different. In infectious diseases, nonself bacterial, viral, fungal, or parasitic antigens determine the specific nature of the adaptive anti-pathogen immune responses; in autoimmune diseases, autoantigens (self or altered-self antigens) trigger the immune responses against the patient’s body cells and tissue; and in organ transplantation, donor alloantigens determine the nature and intensity of allograft rejections in the recipient. In tumor growth, the scenario is different, even inverse. Tumors are not rejected but grow despite expression of (”foreign”) tumor-associated antigens (TAAs) because, as mentioned, the tumor does not emit danger signals, that is, the DAMPs are not present/absent or do not work efficiently. In contrast, in the presence of DAMPs, which can be therapeutically released from tumor cells by inducing immunogenic cell death (ICD), tumors are likely to be rejected (details of ICD will be described in Sect. 9.3).
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1.2 Classification of DAMPs: An Update 1.2.1 Introductory Remarks For those readers who are holding this book on DAMPs in Human Diseases in their hands for the first time, a classifying definition of these molecules is briefly repeated here (also see Tables 1.1, 1.2, and 1.3). More details on the definition and function of DAMPs and their counterparts, the suppressing/inhibiting DAMPs (“SAMPs”), with respect to their use throughout the work are described and illustrated in Vol. 1 [1], Part IV, pp. 191–370 and Vol. 2 [2], Chap. 3, pp. 67–102. Notably, the classification used in the two volumes is maintained and only slightly amended. In an overview, DAMPs that operate in the commission of our immune defense system are ordered in four major categories (Cat. I–IV), by defining them roughly as endogenous and exogenous DAMPs, whereby the exogenous DAMPs (Cat. IV DAMPs) should refer to molecules administered to or invading a host from outside. Endogenous DAMPs are then further subdivided into constitutive and inducible DAMPs.
1.2.2 Endogenous Constitutively Expressed DAMPs (Cat. I DAMPs) Endogenous DAMPs that are constitutively expressed in their native state and ad hoc, that is, immediately emitted are denoted as Cat. I DAMPs. Depending on their mode of emission, they comprise molecules passively released from necrotic cells (Cat. IA DAMPs) or actively exposed at the surface of stressed (or dying) cells (Cat. IB DAMPs). This category of danger signals includes molecules that are regarded as the “prototypical” or “historical” DAMPs, which marked the start of the era of DAMPs. High mobility group box 1 and heat shock proteins (HSPs) can be found among these molecules but also proteins of entirely different nature, structure, and function such as major histocompatibility complex (MHC) class I chain-related proteins (MICs).
1.2.2.1 Constitutively Expressed Native DAMPs, Passively Released from Necrotic Cells (IA DAMPs) The endogenous constitutively expressed Cat. IA DAMPs are divided into (1) DAMPs except for indirectly NLRP3-activating molecules (Subclass IA-1 DAMPs) and (2) DAMPs indirectly activating the NLRP3 inflammasome (Subclass IA-2 DAMPs) (NLRP3 stands for nucleotide binding and oligomerization domain (NOD, [“NACHT”])-like receptor family, pyrin domain (PYD)-containing 3). These DAMPs can be released passively by cell membrane rupture as observed in accidental cell death (ACD) or regulated necrosis (RN) as a form of RCD. As a new DAMP not mentioned in this book, prothymosin alpha (proTα) may be added here. This DAMP/alarmin is a nuclear protein that is released by necrotic neurons upon cerebral ischemic stress via a unique nonclassical pathway and has been shown to
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Table 1.1 Classification of DAMPs: endogenous constitutively expressed molecules Category I: Endogenous DAMPs: Constitutively Expressed Native Molecules (Cat. I DAMPs)
Class A: DAMPs passively released from necrotic cells
Class B: DAMPs exposed on the cell surface
Subclass 1: DAMPs except for indirectly NLRP3activating molecules Subclass 2: DAMPs indirectly activating the NLRP3 inflammasome Subclass 1: Phagocytosis-facilitating molecules (“chaperones”) Subclass 2: MHC class I chain-related molecules
Category II: Endogenous DAMPs: Constitutively Expressed, Injury-Modified Molecules (Cat. II DAMPs) Class A: DAMPs released from the extracellular matrix
Class B: Cell-extrinsic modified DAMPs
Subclass 1: Proteoglycans Subclass 2: Glycosaminoglycans Subclass 3: Glycoproteins Subclass 1: Oxidation-specific epitopes (membranebound) Subclass 2: Distinct structural sugar patterns (membrane-bound) Subclass 3: Cell-extrinsic dyshomeostasis-associated molecular patterns (dys DAMPs) Subclass 4: Plasma-derived modified soluble molecules Subclass 1: Nuclear DNA breaks Subclass 2: Cytosolic DNA (nuclear and mitochondrial)
Class C: Cell-intrinsic modified DAMPs
Subclass 3: Cytosolic RNA (accumulated, processed) Subclass 4: Cell-intrinsic dyshomeostasis-associated molecular patterns (dysDAMPs) Subclass 5: Abnormally accumulating metabolic molecules
MHC major histocompatibility complex, NLRP3 nucleotide binding and oligomerization domainlike receptor family, pyrin domain-containing 3
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Table 1.2 Classification of DAMPs: endogenous inducible molecules Category III: Endogenous DAMPs: Inducible DAMPs (Cat. III DAMPs)
Class A: Native molecules acting as inducible DAMPs
Class B: Modified molecules acting as inducible DAMPs
Class C: Suppressing/inhibiting DAMPs (“SAMPs”)
Class D: Humoral pattern recognitionmolecules
Subclass 1: Actively secreted molecules (also passively released) Subclass 2: Cytokines secreted by (DAMP-) activated cells Subclass 3: Members of full-length Interleukin-1family Subclass 4: Complement-related and vascular molecules Subclass 5: Galectins Subclass 6: NF-kB signaling in cross-priming Subclass 7: Eicosanoids Subclass 8: Vasoactive catecholamines, Angiotensin II,ET-1 Subclass 9: Lactoferrin Subclass 10: RANKL, GM-CSF Subclass 11: eCIRP Subclass 1: Processed interleukin-1 family members Subclass 2: Processed HMGB1 secreted by activated immune cells Subclass 3: Anaphylatoxins C3a and C5a Subclass 4: “Prion-like” polymers (“Specks”) Subclass 5: Lysophospholipids Subclass 6: Peroxiredoxins Subclass 7: Wnt Proteins Subclass 1: Prostaglandin E2 Subclass 2: Adenosine (extracellular adenosine, cyclic AMP) Subclass 3: Annexin A1 Subclass 4: Specialized proresolving mediators Subclass 5: Lysophosphatidylserine, Lysophosphatidylethanolamine Subclass 6: Angiotensin (1-7) Subclass 7: Alpha B-crystallin (HspB5) Subclass 8: Cardiolipin Subclass 1: Pentraxins Subclass 2: Collectins Subclass 3: Ficolins Subclass 4: Serum amyloid A
eCIRP1 extracellular cold-inducible RNA-binding protein, ET-1 endothelin-1, GM-CSF granulocyte-macrophage colony-stimulating factor, NF-κB nuclear factor-kappa B, RANKL receptor activator of NF-kB ligand, Wnt wingless-type
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Table 1.3 Classification of DAMPs: exogenous molecules Category IV: Exogenous DAMPs (Cat. IV DAMPs) Class A: Exogenous DAMPs indirectly sensed by NLRP3
Class B: Exogenous DAMPs sensed by nociceptors
Subclass 1: Aluminium salt Subclass 2: Asbestos fibres Subclass 3: Silica particles Subclass 1: Noxious stimuli involved in thermosensation Subclass 2: Non-reactive compounds Subclass 3: Reactive electrophilic compounds Subclass 4: Vanilloids- capsaicin
Class C: Allergens
Subclass 1: Metal Allergens
Class D: Vaccines
Subclass 1: Viral Vector-Based Vaccines (DNA, RNA) Subclass 2: DNA Plasmid Vaccines Subclass 3: RNA (e.g., messenger RNA) Vaccines Subclass 4: Nanoparticles
Class E: Airborne Particulate Matter
Subclass 1: Inhalable particles, diameters: £ 10 µm Subclass 2 : Fine inhalable particles,diameters: £ 2,5 µm
activate the Toll-like receptor 4 (TLR4) → Toll/IL-1(TIR)-domain containing adaptor inducing interferon-β (TRIF) signaling pathway in the microglia [20–22]. The category of IA DAMPs is of particular importance because they play a key role in the promotion of necroinflammatory responses as a common consequence of necrosis, either in the form of ACD or subroutines of RN such as apoptosis leading to secondary necrosis, necroptosis, pyroptosis, ferroptosis, and NETosis (for neutrophil extracellular trap(NET)-associated cell death) (reviewed by Sarhan et al. [23]; for the different subroutines of RCD, see Vol. 1 [1], Chap. 19, Figs. 19.1–19.8, pp. 427-469 and Vol. 2 [2], Sect. 4.3, Figs. 4.2 and 4.3, pp. 127–139; for more recently reported details of subroutines of RCD, see Sect. 3.8). As pointed out in detail in Vol. 1 and Vol. 2 of this book, the various forms of RCD are triggered when cellular stress responses such as endoplasmic reticulum (ER) stress fail to cope with stress and injury, and are thought, via intrinsic release of DAMPs, to promote and ensure robust host defenses at the organismal level (for the nature and mechanisms of stress responses, see Vol. 1 [1], Chap. 18 plus Figs. 18.1–18.7, pp. 377–426); and Vol. 2 [2], Sect. 4.2, Fig. 4.1, pp. 117–127). Indeed, the remarkable “clou” of these cell death events is that bacterial/viral infection-caused RN—via emission of endogenous Cat. IA DAMPs—promotes robust host defense against the virus or the bacterium concerned (that is not mainly triggered by the pathogen per se!). On the other hand, it should also be reiterated here that the different forms of RCD can serve as very prolific sources of DAMPs, that
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is, a momentum that explains the unique ability of these molecules to drive antigenrelated human diseases very effectively. Indeed, as noted by Tonnus and Linkermann [24, 25], growing evidence suggests a significant in vivo impact of RN on human diseases: a topic that emerges throughout this book. Worthwhile to mention is also that some DAMPs can be exported actively from stressed but living cells via exocytosis of secretory lysosomes or exosomes, ectosomes, and activation of cell membrane channel pores (Fig. 1.1). The topic has recently been reviewed by Murao et al. [26] and will be resumed in the following chapters, in particular, in Sect. 3.8.
Ferroptosis
Necroptosis
Pyroptosis
DAMPs
DAMPs DAMPs
DAMPs
Pore
Pore
P
Exosomes
PO
L
S RO Fe
MLKL
GSDMD
RIPK3 P RIPK1 P
RCD
Inflammasome 4
MPO
NE
D PA
s
u cle
Nu Lysosomes
NETosis
Fig. 1.1 Simplified scheme of various mechanisms of DAMP release. Subroutines of regulated cell death such as ferroptosis, necroptosis, pyroptosis, and NETosis (not shown: apoptosis → secondary necrosis) serve as major sources of DAMPs, with their release occurring through either the rupture of the plasma membrane or pore formation or even both mechanisms. It is thought that larger DAMPs exit the cell through the ruptured membrane while smaller molecules pass through the pores. However, the precise mechanisms are still not clear. In addition, secretory lysosomes and exosomes have been reported to function as carriers of DAMPs. Note: This is just a rough overview of the release of DAMPs from dying cells, and mechanistic details of the various forms of cell death are not explained here. Instead, the topic will be described with careful reference to competent articles in Sect. 3.8. DAMPs damage-associated molecular patterns, Fe iron, LPO lipid peroxidation, GSDMD gasdermin D, MLKL mixed lineage kinase domain-like protein, MPO myeloperoxidase, NE neutrophil elastase, NET neutrophil extracellular trap, PAD4 peptidyl arginine deiminase 4, RIPK1/3 receptor-interacting serine/threonine-protein kinase 1/3, RCD regulated cell death, ROS reactive oxygen species. (Sources: [26]; other sources used for this figure are cited in the legends of Figs. 3.6, 3.8, 3.10, and 3.11)
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1.2.2.2 Constitutive DAMPs, Exposed at the Cell Surface of Stressed or Dying Cells (Cat. IB DAMPs) DAMPs exposed at the cell surface of stressed or dying cells denoted as Cat. IB DAMPs have been described in detail in Vol. 1 [1], Sect. 12.3, Fig. 12.5, pp. 245–251. They are divided into phagocytosis-facilitating molecules such as calreticulin (CALR) (Subclass IB-1 DAMPs), and MICs such as MHC class I polypeptiderelated sequence A and B (MICA/MICB) (Subclass IB-2 DAMPs), which have gained center stage as bona fide transplantation antigens [27]. The critical role of phagocytosis-promoting IB-1 DAMPs is that they emit an “eat-me” signal to facilitate antigen uptake. For example, CALR has a vital impact on the engulfment of TAAs by phagocytosing DCs to increase the immunogenicity of cancer cells via the phenomenon of ICD. However, it should be noted here that CALR does not only have an immunogenicity-increasing function acting as a DAMP but also exert an opposing immunosuppressive effect through its capability to promote phagocytosis of apoptotic cells by macrophages, a process called efferocytosis (compare Vol. 1 [1], Sect. 22.6.3.3, pp. 562/563). Importantly, this process is a vital prerequisite for the resolution of inflammation (reviewed in [28–30]). One explanation for these two obviously contradictory effects may be that CALR, exposed on dying tumor cells, facilitates engulfment, processing, and presentation of nonself TAAs by DCs such as conventional DCs (cDCs; also called myeloid DCs) that initiate an adaptive anti-cancer immune response. On the other hand, CALR exposed on dying “self cells” does not lead to the presentation of nonself antigens to instigate an adaptive immune response (see also similar discussion of this topic in [31]). The MICs have recently been reviewed [32]. Expression of these DAMPs was shown to be regulated by a variety of stress pathways via different mechanisms (reviewed in [33]) (for stress responses, see Vol. 1 [1], Chap. 18, Figs. 18.1–18.7, pp. 377–412). For example, oxidative stress leads to accumulation of H2O2, which reportedly induces MICA and MICB and UL16-binding proteins (ULBPs) 1–4 via activation of the mitogen-activated protein kinase (MAPK) pathway. In contrast, heat shock can transcriptionally regulate MICA and MICB, as the promoter regions of the MIC genes have heat shock elements that can be recognized by heat shock factor 1 (HSF1). Also, the unfolded protein response (UPR) pathways during ER stress were demonstrated to result in upregulation of ULBP-related protein via the protein kinase RNA-like endoplasmic reticulum kinase (PERK) → activating transcription factor 4 (ATF4) → CHOP pathway (CHOP stands for cytidine-cytidine- adenosine-adenosine-thymidine (CCAAT)-enhancer-binding homologous protein) (reviewed in [33]; for PERK-ATF4-CHOP pathway, also compare Vol. 1 [1], Fig. 18.6, p. 402). Importantly, compared to damage-modified molecules (Cat. II DAMPs), Cat. IB DAMPs have now taken over a similar crucial innate immune defending function in moderately stressful situations, which can be often observed in clinical situations.
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1.2.3 Endogenous Constitutively Expressed Injury-Modified Molecules (Cat. II DAMPs) As described and illustrated in Vol. 1 [1], Chap. 13, Figs. 13.1–13.3, pp. 269–294, and Vol. 2 [2], Sect 3.4, Fig. 3.3, pp. 71–81, the category of II DAMPs encompasses various endogenous molecules that undergo different modifications in their constitutional molecular structure upon cell stress and tissue injury, reflected by extra- or intracellular, biochemical, and/or spatially intercompartmental alterations. Such stress/injury-induced modification of endogenous DAMPs can occur via conventional or unconventional types of posttranslational modifications (PTMs) of native molecules, for example, induced by oxidative or proteolytic processes. Moreover, the alteration can be reflected not only by modification of a given molecule but also by changes of a molecular pattern, whereby the molecules per se are not biochemically modified. This category of DAMPs is characterized by different structures, localization, way of emission, and function and, consequently, is sensed by various pattern recognition molecules (PRMs). The molecules can be sorted into (1) two cell- extrinsically modified classes of molecules, encompassing DAMPs (i.e., IIA DAMPs) derived from the extracellular matrix (ECM) as well as cell-extrinsic modified DAMPs (IIB DAMPs) such as oxidation-specific epitopes (OSEs) and cell- extrinsic dyshomeostasis-associated molecular patterns (detailed below); and (2) one cell-intrinsically modified class of molecule (IIC DAMPs). This last class of DAMPs plays a critical role in infectious and autoimmune diseases and, thus, deserves a few more words.
1.2.3.1 Cell-Intrinsic Modified Molecules (IIC DAMPs) Endogenous cell-intrinsic modified molecules refer to DAMPs that are not passively released from necrotic cells but emerge within cells upon cell stress or damage. As described and illustrated in Vol. 1 [1], Sect. 13.4, Figs.13.2 and 13.3, pp. 284–294, this class of DAMPs is denoted as IIC DAMPs that encompass all forms of nuclear or cytosolic, constitutive, or modified molecules, including cell organelles. Doubtlessly, apart from intracellularly located exogenous nucleic acids (NAs) derived from viruses or bacteria, self NAs can be regarded as the most critical endogenous cell-intrinsic endogenous DAMPs. Accumulation, Dislocation, and Translocation of Nucleic Acids Intracellular dyshomeostatic “pathological” accumulation of NAs can induce an innate immune response, whereas physiological amounts of endogenous NAs can be tolerated by a sensing PRM and at least not induce a signaling pathway. Moreover, the sensing threshold of a PRM and its signaling cascade can also be subject to modulation [34]. Slight lesions, for example, in the form of discontinuation of intracellular molecules, can also lead to their recognition by PRMs. For example, in the nucleus, double-stranded DNA breaks (DSBs) and single-stranded DNA (ssDNA) generated upon DNA damage may act as DAMPs (denoted as IIC-1 DAMPs) to be sensed by special receptors located in the nucleus [35] (see Vol. 1 [1], Sect. 18.6.3,
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Fig. 18.7, pp. 408/409). Also, dyshomeostatically accumulated RNA/RNA fragments in the cytosol may operate as DAMPs (i.e., IIC-3 DAMPs) to be sensed by cytosolic PRRs. Besides abnormally accumulated NAs such as RNA, pathologically accumulated or processed in the cytosol, intracellular molecules can dislocate/mislocate or translocate to be recognized as DAMPs. An example of dislocated molecules refers to DNA (IIC-2 DAMPs) leaked from mitochondria (denoted as mtDNA) or the nucleus (denoted as nDNA) upon cellular damage (described in Vol. 1 [1], Sects. 13.4.3 and 13.4.4, pp. 286–288). Indeed, our innate immune system notices every molecule that has left its “homeostatic location” (“breaching of compartmentalization”). Thus, the appearance of NAs in the cytosol signals danger because they should not be there under homeostatic conditions! A typical example of translocation refers to the pre-apoptotic trafficking of the chaperone CALR from the ER toward the plasma membrane to get exposed at the cell surface during ICD [36]. Another similar example may be reflected by the upregulation of MICs in the ER during stress that are translocated to the cell surface to be exposed at the cell membrane [33, 37, 38]. Intracellular Endogenous Host Nucleic Acids and Exogenous Bacterial/ Viral Nucleic Acids: Is There a Difference for Cells of the Innate Immune System? In reading the literature on innate immune responses to NAs, it is noticeable that host NAs, DNA and RNA, are referred to as endogenous DAMPs, whereas exogenous bacterial or viral NAs are termed pathogen-associated molecular patterns (PAMPs) or microbe-associated molecular patterns (MAMPs). (At this point, it should already be noted that the phrase MAMPs is mostly used throughout this book, whereby the term is applied synonymously to all pathogens.) (also compare Vol. 1 [1], Sect. 11.3, pp. 201–204). This is an interesting topic that will be briefly examined here. Intracellular Endogenous DNA and Exogenous Bacterial/Viral DNA Endogenous DNA or DNA fragments that are dislocated in the host cytosol are referred to as (endogenous) DAMPs, which are sensed by cytosolic PRRs that trigger an innate immune response. On the other hand, exogenous viral or bacterial DNA that is located in the host cytosol is used to be referred to as nonself PAMPs that are sensed by cytosolic PRRs that also trigger an innate immune response. Obviously, in both cases, the cells know that neither endogenous nor exogenous DNA belong in the cytoplasm, and, consequently, they treat them as danger signals and respond. In addition, it can also be assumed that cells of the innate immune system have no tools at all to distinguish endogenous and exogenous DNA precisely. So, the question that arises here is: Is the innate immune response directed at one time against self/altered-self and at another time against bacterial/viral nonself?—Or is the response in both situations directed principally against dislocated DNA, regardless of their origin? If the last assumption is correct, it would make sense to refer to viral/bacterial DNA as exogenous DAMPs rather than PAMPs.
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Intracellular Endogenous RNA and Exogenous Bacterial/Viral RNA There seems to be general agreement that endogenous RNA or RNA fragments that are dyshomeostatically accumulated in the host cytosol are referred to as (endogenous) DAMPs, which are recognized by cytosolic PRRs and elicit an innate immune response. On the other hand, the bacterial/viral RNA present in the host cytosol are used to be termed exogenous nonself PAMPs, which are sensed by cytosolic PRRs that also trigger an innate immune response. Again, obviously, in both cases, the cells know that neither endogenous nor exogenous RNA present in abnormal concentrations belong in the cytoplasm, and consequently, they treat them as danger signals and respond. And also again, it can be assumed that cells of the innate immune system have no tools at all to distinguish endogenous and exogenous RNA precisely. So, the question that arises here again is: Is the innate immune response directed at one time against self/altered-self and at another time against bacterial/ viral nonself?—Or is the response in both situations directed principally against dyshomeostatically accumulated RNA, regardless of their origin? If the last assumption is correct, it would make sense to refer to viral/bacterial RNA as exogenous DAMPs rather than PAMPs. Conclusion This interesting aspect about the denotation of viral/bacterial DNA and RNA as exogenous DAMPs has been tentatively adopted in Table 1.3. Also, in the following sections of this book, this topic is sometimes referenced when appropriate. It would indeed be worthwhile to discuss this issue with experts in the field in the near future to eventually reach a consensus on it. Intracellular Dyshomeostasis-Associated Molecular Patterns As mentioned, stress/injury-induced extra- or intracellular, biochemical, and/or spatially intercompartmental alterations can be reflected not only by modification of a given molecule but also by changes of a molecular pattern, whereby the molecules per se are not biochemically modified. Such molecular perturbations reflect homeostatic danger signals [39] or homeostasis-altering molecular processes [40], or dyshomeostasis–associated molecular patterns [41]. Here, these dyshomeostasis-indicating danger signals are denoted throughout the book as “dyshomeostatic DAMPs” (whereby DAMPs stand for dyshomeostasis–associated molecular patterns), newly abbreviated throughout this book as “dysDAMPs.” Accordingly, as mentioned above, such disruption of molecular homeostasis reflecting DAMPs may be associated, for instance, with extracellular cell-extrinsic acidosis or disturbed osmolarity [42] (denoted as cell-extrinsic IIB-3 DAMPs). On the other hand—here with respect to cell-intrinsically modified molecules—intracellular molecular perturbations indicating disruption of molecular homeostasis of a cell may be caused by cell-intrinsic intercompartmental dislocation of molecules, unusual accumulation/ aggregation of molecules, or intracellular perturbation of molecular patterns. These endogenous modified/native DAMPs—denoted as cell-intrinsic IIC-4 DAMPs— may directly or indirectly induce an inflammatory response.
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1.2.4 Endogenous Inducible DAMPs (Cat. III DAMPs) Endogenous inducible DAMPs (Cat. III DAMPs) are molecules that are “newly made” by (DAMP)-activated cells upon cellular stress or tissue injury or even by cells undergoing (DAMP-promoted) RCD. Inducible DAMPs are generated via neo-transcription in terms of native proteins but also via neotranslation, or PTMs in terms of modified proteins. As expected, reports of newly discovered DAMPs in this category are published on an ongoing basis. Some of them are briefly described here.
1.2.4.1 Native Molecules Operating as Inducible DAMPs (IIIA DAMPs) The category of inducible activating DAMPs includes key molecules operating in infections, such as members of the interleukin (IL)-1 family, tumor necrosis factor (TNF), and type I interferons (IFNs) [43]. They are considered molecules that mainly enhance and amplify inflammatory responses. Notably, these DAMPs have recently been proposed to be critical for the generation of immunostimulatory DCs capable of cross-presenting exogenous antigens [44] (for DC cross-presentation, see Vol. 1 [1], Sect. 31.3.5, Fig. 31.5, pp. 740–743). Here, it should be recalled again that this classification policy is not generally accepted and only reflects the author's view. Anyway, via their receptors, that is, type I interferon receptor (IFNAR) and tumor necrosis factor receptor (TNFR), they activate proinflammatory transcription factors such as nuclear factor-kappa B (NF-κB) to elicit strong proinflammatory pathways. Another inducible DAMP not previously mentioned in this book is lactoferrin (LTF). Lactoferrin is an iron-binding glycoprotein typically detected in human milk, saliva, and other mucosal secretions and is produced by multiple cells, including neutrophils, during inflammation [45, 46]. This inducible DAMP may also directly regulate innate immunity by interacting with intracellular signaling pathways, including NF-κB [47, 48]. In addition, the ligand for receptor activator of NF-kB (RANK), RANKL, can be considered an inducible DAMP. RANKL is defined as a cytokine belonging to the TNF superfamily and is expressed by activated resident bone cells such as osteoblasts, osteoclasts, and osteocytes [49, 50] and also by different activated T cells [51], indicating the active influence of the immune system in osteoclastogenesis. Both the formation and activity of mature osteoclasts are stimulated by ligation of RANKL to RANK in vitro [52, 53]. Further, another DAMP not mentioned in the book yet is extracellular cold- inducible RNA-binding protein (eCIRP) that is secreted by stress-activated macrophages and has been shown to exaggerate inflammation under shock conditions and induce NETs in the lungs during sepsis via upregulating expression of peptidylarginine deiminase 4 (PAD4) [54, 55] (for details of NET formation, see Sect. 3.7.7). 1.2.4.2 Modified Molecules Operating as Inducible DAMPs (IIIB DAMPs) The subclasses sorted into this class, so far published and described in Vol. 1 [1], Sect. 14.3, Fig. 14.4, pp. 322–330, and Vol. 2 [2], Sect. 3.5.4, pp. 89–91, refer to
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processed IL-1 family members IL-1α and IL-1β (IIIB-1 DAMPs); secreted HMGB1 (IIIB-2 DAMP) (compare Fig. 14.4, in Vol. 1 [1], Sect. 14.3.3.2, p. 326); anaphylatoxins (= complement fragments 3a and 5a, = C3a and C5a = IIIB-3 DAMPs); “prion-like” polymers (IIIB-4 DAMPs); the lysophospholipids (LPLs, IIIB-5 DAMPs); peroxiredoxin-1 (PRDX1, IIIB-6 DAMP); and Wnt (denoted as IIIB-7 DAMPs). They will all not be taken up further here.
1.2.4.3 Native Molecules Operating as Inducible Suppressing DAMPs (IIIC DAMPs) Growing attention is being paid to inducible SAMPs, which were first described as resolution-associated molecular patterns (RAMPs) [56]) or inhibitory DAMPs [57]. These molecules, which counteract/counterbalance the action of activating DAMPs, have already been cursorily presented in separate sections in Vol. 1 [1], Sect. 14.4, p. 330 and Sect. 22.2.3, p. 480, as well as in Vol. 2 [2], Sect. 5.3.3.2, p. 157 (for more information, also see [58]). They include but are not limited to prostaglandin E2 (PGE2) [57, 59–61], cyclic adenosine monophosphate (cAMP) [62–64], extracellular adenosine [65, 66], annexin A1 (AnxA1) [67–70], specialized proresolving mediators (SPMs) grouped into four structurally distinct chemical families—the lipoxins (LXs); resolvins (Rvs, for resolution phase interaction products); protectins (Pds), including neuroprotectin D1 (NPd1); and maresins (MaRs) [71–74]—and phosphatidylserine-lysophosphatidylserine (PtdSer-lysoPS) [75–81]. As a new molecule, angiotensin-(1-7) (Ang-(1–7)) can be included in the SAMP list. Ang(1-7) is converted from angiotensin-II (Ang-II) by angiotensin-converting enzyme 2 (ACE2). The molecule has tissue-protective actions that are generally opposite to the unwanted chronic effects of excessive Ang-II that has been denoted in this book as an inducible IIIA-8 DAMP. Among the various actions of Ang-(1-7), inhibition of inflammatory responses is one of the most prominent (for further reading, see [74, 82–84]). Thus, in this sense, Ang-(1-7) can really be regarded as a bona fide SAMP. A SAMP that appears to act preferentially in neuroinflammation is alpha B-crystallin (HspB5). The glial heat shock protein B5 (HspB5) is secreted by stressed oligodendrocytes and operates as a molecular chaperone and endogenous agonist of TLR2. Studies on primary human microglial cultures indicated that HspB5 induces an immunoregulatory and antiviral microglial response in pre-active multiple sclerosis (MS) lesions [85]. Following systemic administration, HspB5 was shown to act as a potent inhibitor of neuroinflammation in animal models and reduce lesion development in MS patients. As targets for this SAMP, peripheral monocytes and macrophages, as well as the microglia, were identified [86]. Another SAMP that appears to function predominantly in neuroinflammation is cardiolipin. Recent studies with murine and human microglia indicate that this phospholipid may inhibit the inflammatory activity of these cells by downregulating the release of cytotoxins and inflammatory mediators, such as TNF, nitric oxide (˙NO), and reactive oxygen species (ROS). Extracellular cardiolipin was also shown to upregulate phagocytic activity of murine microglia in vitro [87].
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Regarding their function, it must be emphasized here that the SAMPs such as SPMs, AnxA1, PGE2, and HspB5 are required not only for optimal inflammation- resolving processes but are also essential for tissue regeneration and restoration of homeostasis [85, 88–92].
1.2.4.4 Humoral Pattern Recognition Molecules Operating as Inducible DAMPs or SAMPs (IIID DAMPs) Here, a new class of DAMPs is introduced in this book as IIID DAMPs: humoral pattern recognition molecules (humoral PRMs). Humoral or soluble PRMs are a group of evolutionarily ancient molecules that are heterogeneous in terms of structure, expression, and specificity and function as vital players of the humoral arm of the innate immune defense system across the tree of life [93–95]. The molecules include a group of receptors produced by MAMP/DAMP-activated innate immune cells, including collectins, ficolins, and pentraxins [93, 96] (for details, see Vol. 1 [1], Sect. 5.4, pp. 89–94). These soluble PRMs can be regarded as “hybrid proteins,” which, on the one hand, are able to recognize certain MAMPs and DAMPs, but on the contrary, when expressed and secreted upon infectious or sterile injury by a variety of MAMP/DAMP-activated innate immune cells, can operate in terms of inducible DAMPs to trigger innate immune responses. The molecules are qualified as inducible DAMPs/SAMPs because they have been shown to trigger TLR4- dependent pro- or anti-inflammatory innate immune responses. For example, the long pentraxin 3 (PTX3) as a DAMP was found to (1) exert its protective antifungal activity in vivo through TLR4/myeloid differentiation protein 2 (MD-2)-mediated signaling [97]; and (2) promote melanoma migration through a TLR4 → NF-κB signaling pathway [98]. The prototypical pentraxin C-reactive protein (CRP) was shown to promote inflammation through TLR4 → NF-κB → tumor growth factor-β (TGF-β) pathway in HL-1 cardiac muscle cell line [99]. Moreover, the mouse ficolin FCN-A/2 was shown to exacerbate the inflammatory pathogenesis of experimental mouse colitis by stimulating M1-like macrophage polarization through the TLR4 → myeloid differentiation primary response gene 88 (MyD88) → MAPK/NF-κB signaling pathway in macrophages [100]. On the other hand, the collectin surfactant protein-A-derived peptide 4 (SPA4) was demonstrated to interact with and bind to TLR4 ↔ MD-2 [101, 102] to promote anti-inflammatory responses by suppressing secretion of cytokines and chemokines, thereby qualifying this molecule as a SAMP. Another humoral PRM is serum amyloid A (SAA), which drives type 2 immunity [103]. The SAA proteins comprise a family of molecules that are instrumental in host defense (reviewed by Sack [104]). This humoral PRM, produced, for example, by macrophages and hepatic cells, qualifies as an inducible DAMP as it was shown to be sensed by multiple receptors, including TLR4, TLR2, and the ATP receptor P2X purinoreceptor 7 (P2XR7) [105]. The DAMP appears to be important in neuroinflammation.
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1.2.4.5 Damage-Associated Molecules Operating Context-Dependently as SAMPs or DAMPs In the course of an increasing interest in research on DAMPs, the puzzling finding was made that some injury-induced molecules can function context-dependently either as SAMPs or DAMPs. As briefly mentioned in Vol. 1 [1], Sect. 3.5.6, pp. 95–98, such molecules include HSPs, TGF-β, IL-33, and some ECM components such as biglycan and versican. Here, another such molecule should be added: PGE2, which is described above as a SAMP. Indeed, this stress/injury-induced molecule has been observed to exert both pro- and anti-inflammatory/resolving actions and, thus, operates context- dependently. For example, adequate formation of PGE2 is required to mount an optimal level of inflammation, which in turn activates the arachidonic acid 12/15-lipoxygenase (ALOX12/15) enzyme to enhance the production of inflammation resolving lipoxin 4 (LXA4) [106]. Once shifted to resolution, the inflammation- resolving effect of PGE2 then is remarkable. For instance, produced at sites of tissue injury, the SAMP has been shown to promote an anti-inflammatory neutrophil phenotype and determines the outcome of inflammation resolution in vivo [107]. The existence of molecules that may function context-dependently as both DAMPs and SAMPs is still an unsolved problem. And the list of molecules mentioned here is certainly not complete. Future studies should be envisaged to reveal the mechanisms that enable these injury-induced molecules to trigger either proinflammatory or anti-inflammatory/resolving immune responses, depending on given circumstances. One may think of the involvement of different types of innate immune cells or interaction with different PRMs, or distinctive effects on different cell types.
1.2.5 Exogenous DAMPs (Cat. IV DAMPs) As another category, exogenous DAMPs, which refer to molecules invading a host from outside or being administered as adjuvants in vaccines (“vaccinology” [108]), have been included in this monograph. According to the perspective of the book, these Cat. IV DAMPs include various exogenous molecules, for example, aluminum hydroxide (alum), asbestos fibers, and silica; noxious stimuli; some nonreactive compounds; reactive electrophilic compounds; vanilloids; some allergens; viral vector-based vaccines, NA vaccines, nanoparticles, and airborne particulate matter (PM) (also compare Vol. 1 [1], Chap. 15, pp. 353–364). The vaccines, nanoparticles, and airborne PM, which are currently of great interest, will be briefly touched upon here.
1.2.5.1 Viral Vector-Based Vaccines Recombinant viral vector-based vaccines deliver antigens encoded in the context of an unrelated, modified virus. A wide range of different viruses has been used as the basis for the development of viral vector-based vaccines, including adenoviruses consisting of a single-stranded DNA and the vesicular stomatitis virus, which is a
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single-stranded, negative-sense RNA virus. The vectors have been employed pre- clinically and clinically as vaccines against a variety of infectious diseases, such as acquired immunodeficiency syndrome (AIDS), Ebola, and, more recently, COVID-19 (for details, see [109]). As exogenous DAMPs, they are sensed by cognate DNA and RNA receptors (for DNA and RNA signaling, see Sect. 4.3.2.3, and Figs. 4.5, 4.6, and 4.7).
1.2.5.2 Nucleic Acid Vaccines Nucleic acid-based technologies use either antigen encoding plasmid DNA or RNA as messenger RNA (mRNA) or viral replicons. Upon their cellular uptake and expression, NA-encoded antigens can elicit humoral as well as cell-mediated immune responses (reviewed in [110]). DNA Vaccines DNA vaccines are usually based on bacterial DNA plasmids and a strong eukaryotic promoter that enhances the expression of the antigenic protein, inducing immune responses [111, 112]. They can be termed exogenous DAMPs, deduced from the fact that DNA is thought to be sensed by a variety of cytosolic DNA receptors [113]. However, vaccination with a DNA vector alone was observed to lead to relatively low immunogenicity, prompting additional methods to enhance DNA uptake, expression, and immunogenicity, such as developing special delivery devices [110]. RNA Vaccines Two major types of RNA have been utilized as prophylactic vaccines against pathogens that cause infectious diseases, nonreplicating mRNA and self-amplifying mRNA [110]. Indeed, mRNA vaccines were found to elicit robust immune responses against various viruses, especially in recent years, using lipid-encapsulated or naked forms of sequence-optimized mRNA [114]. At the time being, in vitro modified/ transcribed RNA injected intramuscularly is used in modern vaccines to code a distinct antigen in question, for example, the spike protein of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). Thus, as reviewed by Park et al. [115], in vitro transcribed/synthesized mRNA vaccines are thought to be recognized by PRRs, including the endosomal TLR3, -7, and -8, and cytoplasmic innate immune receptors, retinoic acid-inducible gene (protein) I (RIG-I) and melanoma differentiation-associated gene 5 (MDA5), whereas double-stranded RNA (dsRNA), produced by inaccurate T7 polymerase activity, to be recognized by TLR8 and RIG-I (for these PRRs, see below, Sect. 4.3.2.3 and Figs. 4.5–4.7).
1.2.5.3 Nanoparticles Interestingly, nanoparticles have already been recognized as DAMPs and termed nanoparticle-associated molecular patterns (NAMPs) as early as 2012 by Fadeel [116]. In fact, there is growing evidence that nanoparticles operate as potent exogenous DAMPs and, when added as adjuvants to mRNA vaccines, seem to be even more potent than the RNA itself. For example, acute iron oxide nanoparticles exposure has been shown to induce murine eosinophilic airway inflammation via TLR2
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and TLR4 signaling [117]. Also, there is first evidence suggesting that lipid nanoparticles (LNPs) may activate TLR4/2-bearing macrophages [118]. In addition, several studies indicate that different nanoparticles (e.g., liposomes, polymer-based nanoparticles) can induce NLRP3 inflammasome activation (reviewed in [119]). Remarkably, there is also first evidence suggesting that LNPs formulated with ionizable lipids are potent activators of the inflammasome pathway [120]. These findings are of great interest in view of other lines of studies showing that lipids regulate NLRP3 inflammasome activity through organelle stress (i.e., stress of mitochondria, lysosomes, and ER [121]).
1.2.5.4 Airborne Particulate Matter The airborne PM is becoming increasingly important in its function as exogenous DAMPs, as they have been shown to activate the NLRP3 inflammasome. Indeed, evidence is discussed in [122], suggesting that environment-derived exogenous DAMPs may operate as an essential integrating element of both environmental health research paradigms, that is, the “exposome” concept and the “adverse outcome pathway” (AOP) concept. On the one hand, as further argued [122], DAMP- promoted controlled/uncontrolled innate/adaptive immune responses reflect the key events of the AOP concept. On the other hand, the whole process starting from exposure to a distinct environmental stress/injury—associated with the presence/ emission of DAMPs—up to the manifestation of a disease may be regarded as an exposome. An urgent clinical example of such a scenario refers to the emerging COVID-19 pandemic, where the interaction of noninfectious environmental factors (e.g., PM) and infectious factors (SARS CoV-2) may promote SARS case fatality via superimposition of both exogenous and endogenous DAMPs (the topic is resumed below in Sect. 5.4.7).
1.2.6 Résumé The spectrum of the various DAMPs discovered and described so far is impressive. Given the enormous amount of various DAMPs generated and emitted in the course of injury, in particular, in injury-induced subroutines of RCD (see below), and sensed by a variety of PRMs, it becomes clear that the initiation and propagation of sterile inflammatory and fibrogenic responses is never the work of one DAMP alone. In fact, it can be hypothesized that for each given injury and each given context, a certain pattern of DAMPs is required to mount an effective inflammatory and/or profibrotic response. Likewise, as already discussed by us elsewhere [123], the ratio of DAMPs and SAMPs must be carefully determined in each case to assess the cutting point, where a beneficial homeostatic defense response transitions to a deleterious pathological process clinically manifesting as a severe or life-threatening disease. Accordingly, future research work must be tackled, focusing on the precise definition and identification of a given pattern of DAMPs that drives a specific clinically relevant inflammatory and/or regenerative response.
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1.3 Some Principles of the Action of DAMPs in Shaping Antigen-Related Disorders 1.3.1 Emission of Three Signals by Activated Antigen-Presenting Cells Injury-induced activation of APCs such as immature DCs (iDCs) into mature immunostimulatory APCs can be regarded as the key event in instigating and maintaining an adaptive immune response. Following activation through DAMP-triggered, PRM-mediated signaling pathways, DCs undergo a metamorphotic process that is characterized by upregulation of MHC molecules (signal 1), upregulation of costimulatory molecule expression at their surface (signal 2), and secretion of T cell- polarizing cytokines (signal 3). Matured DCs, then, have acquired the ability to migrate from the periphery through the lymph to draining lymph nodes. In the secondary lymphoid organs, mature DCs function as the prototype of professional APCs able to efficiently present antigens captured at the time of activation and to activate naïve T cells [124–128] (for detailed information, see Vol. 1 [1], Sect. 32.2, Fig. 32.1, pp. 750–756). In the following, the scenario of providing signal 2 is decorated with some more details.
1.3.2 History of Costimulation: The Signal 2 The history of inducing an antigen-dependent adaptive immune response is exciting to read and was briefly described in Vol. 1 [1], Chap. 2, pp. 13–23. And it was the self/nonself discrimination model proposed by Burnet and Medawar that was highly appreciated as the first solid concept in the immunological world (Vol. 1 [1], Sect. 2.2, pp. 13–15). The paradigm was first modified in 1969 after the discovery that activated B lymphocytes hypermutate, creating new, potentially self-reactive cells. Then, Bretscher and Cohn [129], recognizing that autoimmunity would be rare if immunity did not require the cooperation of two cells, added a new cell (the helper cell, which later turned out to be a T cell) and a new signal (help!) by proposing that the B cell would die if it recognized the antigen out of help. In 1975, Lafferty and Cunningham [130] focused on the finding that T cells respond more strongly to foreign cells of their own species than to cells of another species by adding another cell and another signal. They proposed that T cells also require a second signal (signal 2, called “costimulation”), which they receive from “stimulator” cells (now called APCs), and suggested that this signal is species-specific. In 1989, Janeway offered an ingenious solution [131], suggesting that APCs have their own form of self/nonself discrimination and can recognize evolutionarily distant pathogens. He specifically proposed that APCs are quiescent until they are activated via a set of PRRs that recognize conserved PAMPs on bacteria. Janeway further proposed that, on activation, APCs upregulate costimulatory signals, process
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the bacterial antigens, and present them to passing T cells. The PRRs, he wrote, allow APCs to discriminate between “infectious-nonself ” and “noninfectious-self” [132]. In other words, he placed the activation of APCs as cells of the more recently evolved adaptive immunity under the control of ancient pathogen-sensing mechanisms. Matzinger’s ingenious danger model published in 1994 added another layer of cells and signals [6], proposing that APCs are activated by danger/alarm signals from injured cells in terms of signal 2, such as those exposed to pathogens, toxins, and mechanical/physical damage. In the same year, Land et al. [7]—on the basis of significant clinical data obtained from a clinical trial on kidney transplant patients— proposed that the activity of APCs is upregulated by ROS-mediated reperfusion injury, leading to increased graft immunogenicity. In 1999, in the context of T cell alloactivation, Land highlighted the impact of costimulation on alloactivation [133, 134]: We proposed that postischemic reperfusion injury to allografts promotes T cell alloactivation via upregulation on DCs of MHC products (signal 1) and costimulatory molecules, thereby providing signal 2. Matzinger then refined her danger model in 2002 [135] by arguing that endogenous danger signals like exogenous PAMPs can be sensed by PRR-bearing APCs, thereby providing signal 2. In the same year (2002) [136], we discussed and illustrated in a review article that postischemic reperfusion injury to an allograft leads to induction of endogenous ligands on damaged allogeneic cells that, as danger signals, may interact with and activate TLRs on resting DCs. As an example, HSP60 interaction with TLR4 was quoted. The concept that an adaptive immune response against an antigen requires not only stimulation of naïve T cells by antigen recognition but also their costimulation provided by defined DAMPs (i.e., HSPs) was formulated by us in 2003 [3]: In relation to induction of acute allograft rejection and coining the term DAMPs for the first time, we wrote anecdotally: …HSPs may function in 2 ways: (1) by a contribution to the increased and efficient alloantigen- presenting capacity of DCs, in terms of re-presenting and cross-presenting HSP-chaperoned alloantigenic peptides to naive T lymphocytes, with the provision of signal 1 … and (2) by induction of DC maturation via stimulation of and signalling by TLRs, resulting in the induction of costimulatory molecules that interact with corresponding molecules of naïve T cells, with the provision of signal 2…
1.3.3 The Concept of DAMP-Promoted Activation of APCs Today, the concept of DAMP-promoted activation of APCs as cursorily described here has gained general acceptance, and the framework of events is sketched in Fig. 1.2: Antigen-presenting cells such as DCs stimulate naïve T cells by presenting processed antigenic peptides (e.g., bacterial and viral antigens, autoantigens,
1.3 Some Principles of the Action of DAMPs in Shaping Antigen-Related Disorders
Infectious or sterile stress/injury
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Regulated Cell Death
Antigen
DAMPs
Pathogen-derived Ags, AutoAgs, AlloAgs , TAAs PRM
DC T cellpolarizing cytokines
(Signal 3)
Costimul.m.
pMHC
(Signal 2)
(Signal 1)
Cogn.Cost.m.
TCR
Antigen recognition
Naive T cell
Adaptive immune response
Fig. 1.2 Highly simplified diagram of the principal action of DAMPs in shaping adaptive immune responses by activating antigen-presenting cells such as DCs. The cells engulf antigens and present them as processed peptides by MHC molecules to naïve T cells (signal 1). DAMPs derived from injury-induced cell death interact with PRM-bearing DCs by upregulating the expression of costimulatory molecules (signal 2) required for full activation of naïve T cells. Along with the secretion of T cell-polarizing cytokines by DCs (signal 3), which determine subsequent distinct functions of T cells, an antigen-specific adaptive immune response is instigated. Ags antigens, AlloAgs alloantigens, AuAgs autoantigens, Cogn.Cost.m. cognate costimulatory molecules, Costimul.m. costimulatory molecules, DC dendritic cell, pMHC peptide/major histocompatibility complex, PRM pattern recognition molecule, TAAs tumor-associated antigens
alloantigens, TAAs) on MHC class I (MHC-I) and MHC-II molecules. In addition, stress/injury-induced DAMPs interact with these PRM-bearing cells of the innate immune system by upregulating the expression of costimulatory molecules required for full activation of naïve T cells and, subsequently, B cells. Along with the secretion of T cell-polarizing cytokines by DCs, which determine subsequent distinct functions of T cells, an antigen-specific adaptive immune response is instigated. This scenario—here roughly sketched—applies to infectious and autoimmune diseases as well as allograft rejection. In cancer, the opposite scenario takes place: the absence of RCD-associated DAMPs precludes the initiation of a robust anti-tumor immune response allowing tumor cells to grow.
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1.4 Cytotoxic T Lymphocyte- and Antibody-Driven Induction of Regulated Cell Death Leading to Emission of DAMPs: “The Adaptive Immune System Calls in the Cavalry” 1.4.1 Introductory Remarks As emphasized in the previous section, it is the cell stress and/or tissue injury that— if not overcome by stress responses—triggers the various forms of RCD associated with release of DAMPs. In this context, we argued in Vol. 2 [2], Sect. 4.3.1, p. 128: Of utmost importance with respect to the emission of DAMPs is the event of RN: during this RN-associated dying process, a cell can initially continue with transcriptional activities, which include the capability to generate further DAMPs in terms of inducible DAMPs. At the end of the process, when the plasma membrane has definitely ruptured, constitutive DAMPs are passively released in large amounts. In this situation, both constitutive and inducible DAMPs, via activation of innate immune cells, evoke cell-extrinsic efferent defense responses in terms of inflammation and inflammation-related events such as phagocytosis. Accordingly, in the context of stress/injury ↔ host interactions, the induction of RCD can be seen as a continuation of a cell's desperate defensive efforts to save the life of the individual it harbors. Intriguingly, however, if this first wave of a DAMP-driven host immune defense response at the organismal level is not successful enough, the resulting specific products of the adaptive immune response may harness the same mechanism of RN-mediated emission of DAMPs to fortify and enforce the host defense. Indeed, there is growing evidence from targeted studies, preferentially on cancer and infection models, demonstrating that antibodies and cytotoxic CD8+ T lymphocytes can trigger subroutines of RN, including NETosis, pyroptosis, efferocytosis, and necroptosis. The issue, which is strongly consistent with the danger/injury model in immunity, is briefly presented here.
1.4.2 Antibodies Antibodies, as products of an adaptive immune response, elicit effector functions via the fragment crystallizable (Fc) domain by interaction with Fc receptors (FcRs) on innate immune cells as well as activation of complement proteins in circulation [137]. These processes promote induction of cell death by mechanisms such as antibody-dependent cellular phagocytosis (ADCP), antibody-dependent cell- mediated cytotoxicity (ADCC), and complement-dependent cytotoxicity (CDC) [138], as well as formation of NETs transitioning into NETosis [139] (for details of NET formation and NETosis, see Sect. 3.8.7). However, while the process of DAMPs release in ADCC and CDC has not been systematically investigated, this has been done in studies on NET formation and NETosis. Indeed, as will be
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described in Sect. 4.6.7 in more detail, there is emerging evidence suggesting that antibodies complexed with antigens (i.e., immune complexes [ICs]) can promote FcR-mediated induction of NET formation/NETosis. Notably, first and preliminary findings of this scenario have been observed in bacterial [139–141] and viral infections, for example, in COVID-19 [142, 143]).
1.4.3 Cytotoxic CD8+ T Lymphocytes Besides antibodies and antibody/antigen complexes, respectively, there is increasing evidence suggesting that cytotoxic CD8+ T lymphocytes (CTLs)—through T cell receptor (TCR) ↔ peptide/major histocompatibility complex class I molecules (pMHC-I) interaction, forming the immunological synapse—can also induce various subroutines of RCD such as pyroptosis, ferroptosis, and necroptosis (for the concept of TCR ↔ pMHC interaction-mediated cytotoxicity, see [144–147]; for induction of RCD, see review in [148]). This connotes that these cytotoxic cells are dependent upon the target cells’ machinery to sense and integrate the cell death signals into their pro-death pathways and then to ultimately execute the sophistically RCD process. Thus, CTLs were recently reported to kill gasdermin B (GSDMB)-positive cells through pyroptosis, a form of RN executed by the gasdermin family of pore-forming proteins [149] (for details of pyroptosis, see below Sect. 3.8.5). Mechanistically, killing was shown to result from the cleavage of GSDMB by lymphocyte-derived granzyme A (GzmA), which releases its pore-forming activity. In support of these findings are studies on leukemic cells showing that chimeric antigen receptor (CAR) T cells, by virtue of their release of a large amount of perforin and granzyme B, activate the caspase 3-gasdermin E (GSDME) pathways, resulting in cell pyroptosis [150]. Cytotoxic CD8+ T cells, more precisely, T cell-derived IFN γ, in combination with arachidonic acid (AA), were also recently discovered to induce ferroptosis in tumor cells, serving as a mode of action for CTL-mediated tumor killing [151]. In contrast to a demonstrated, albeit still vague, effect of CTLs on promoting pyroptosis and ferroptosis induction, there are no firm data published on their role in triggering necroptosis. On the other hand, however, there are findings from studies conducted in other research areas suggesting that this effect may well exist. Thus, it is known that target cells succumb to necroptotic death by death ligands that bind to cognate death receptors on their surface (including FAS (CD95), TNFR1, and TNFR2, and TNF-related apoptosis-inducing ligand receptor 1 (TRAILR1, DR4) and TRAILR2 (DR5)). Cognate death ligands of these receptors refer to FAS ligand (FasL), TNF, and TRAIL that are also expressed or secreted by cytotoxic T lymphocytes (for further detailed information, see [152–156]). Anyway, regardless of the mechanisms of CTL-induced cell death, every necrotic cell death is notoriously associated with the release of DAMPs. Thus, CTLs are predistined to sustain an immune response from which they have originated.
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1.4.4 Cytotoxic B Lymphocytes Interestingly, as reviewed by Janjic et al. [157], activated B cells reportedly also express several TNF superfamily (TNFSF) ligands, including TNF, FasL, TRAIL, OX40L, CD30L, CD40L, CD70, LIGHT, GITRL, BAFF, and APRIL. Therefore, they are thought to be able to execute various innate immune functions, including the ability to kill cancer cells. This notion is supported by earlier studies that have suggested that activated B cells possess tumoricidal potential, which might be mediated by a number of mechanisms, including TNFSF ligands and granzyme B (GzmB). In addition, as observed in other lines of studies by Hagn et al. [158], human B cells may differentiate into GzmB-secreting cytotoxic B lymphocytes upon incomplete T cell help and, therefore, were suggested to have a role in early cellular immune responses, including tumor immunosurveillance, before fully activated, antigen-specific cytotoxic T cells are on the spot.
1.4.5 The Hypothetical Model of a DAMP-Driven Positive Feed-Forward Loop in Adaptive Immune Responses Overall, preliminary evidence for a role of specific humoral and cellular products of adaptive immune responses in triggering subroutines of RCD is intriguing and points to an emerging conceptual model of an enforced host defense program in terms of a positive feed-forward loop. The tentatively designed loop encompasses the following sequelae of events (Fig. 1.3): stress/injury → RCD → DAMPs (+ antigen) → innate/adaptive immune responses → (antigen/antibody) ICs and CTLs → RCD → DAMPs (+ antigen) → innate/adaptive immune responses. This model gains credibility when considering that the various subroutines of the RCD are interconnected [159]. Unfortunately, the same mechanism that obviously evolved to boost efficient host immune defense against pathogens and tumors can turn into pathologies, for example, autoimmune disorders, where (AuAg/AuAb) ICs can induce NET formation and NETosis, for example, as reported in rheumatoid arthritis (see [139, 160, 161]). The release of large amounts of DAMPs from this specific form of RN may hypothetically elicit a positive feed-forward loop of innate immune (inflammatory) and adaptive immune responses, which may fuel the chronicity of these diseases. Certainly, the evolving model of adaptive immunity-mediated enforcement of host defense is still in an immature state and needs to be further confirmed by future targeted studies, in particular, as it relates to the role of cytotoxic CD8+ T cells. On the other hand, the principle of (antigen/ antibody) IC-promoted formation of NETs and NETosis as a productive source of DAMPs emission has meanwhile acquired considerable validity and will be addressed and resumed later on in Sects. 4.4.8 and 6.2.4.
1.5 DAMPs and SAMPs in Diagnosis and Prognosis Infectious or sterile stress/injury
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Regulated cell Death DAMPs + Antigen
controlled t iv e
Regulated cell death
o op
Disease
(Ag/Ab) ICs, CD8+ T cells,
feed-forward l
Adaptive immune response uncontrolled
si Po
Activation of APCs Host defense
DAMPs
Fig. 1.3 Simplified line of drawing of a hypothetical model of a DAMP-driven positive feed- forward loop in adaptive immune responses. The tentatively designed loop encompasses the following sequelae of events: stress/injury → RCD → DAMPs (+ antigen) → innate/adaptive immune responses → (antigen/antibody) ICs and CTLs → RCD → DAMPs (+ antigen) → innate/adaptive immune responses. When controlled, the innate/immune response governs a host defense program; when uncontrolled, it causes hyperinflammatory (e.g., sepsis) or chronic inflammatory diseases (e.g., autoimmune disorders). Note that the figure should be read clockwise, starting from top to bottom and back to top. Ab antibodies, Ag antigen, APCs antigen-presenting cells, ICs immune complexes
1.5 DAMPs and SAMPs in Diagnosis and Prognosis 1.5.1 Introductory Remarks The use of DAMPs and SAMPs as diagnostic and prognostic biomarkers has been described in Vol. 2 [2], Chap. 7, pp. 264/265. Indeed, the use of DAMPs and SAMPs as biological markers is increasingly being seen as a valuable enrichment of modern diagnostic modalities; not least due to the fact that biomarkers are meanwhile considered as part of modern medicine [162]. The background of their use is clear: Levels of DAMPs and SAMPs can be measured in body fluids (e.g., HMGB1 [163], S100B proteins [164], SPMs [165]). Accordingly, from the perspective of this book, DAMPs and SAMPs appear to be of high value in their function as diagnostic markers, because they contribute clinically relevant information in many medical disciplines beyond what has been available as stress/injury-induced biomarkers to clinicians in the past. In particular, acutely high
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or chronically persistent plasma levels of DAMPs associated with insufficient levels of SAMPs will serve as sensitive disease biomarkers and may guide clinicians and practitioners in their daily decision making. Moreover, determining the levels and distribution of DAMPs in target tissues and in the circulation might represent novel biomarkers for quantitating and monitoring fibrotic diseases, in particular, for identifying patient subpopulations likely to benefit from interventions targeting the innate immune branch of fibrogenesis. Plausibly, such a procedure will allow designing small molecules and antibodies to selectively interrupt and disrupt fibrotic responses without interfering with antimicrobial immunity.
1.5.2 DAMPs and SAMPs as Prognostic and Predictive Biomarkers From the perspective of this book, DAMPs and SAMPs may be both prognostic and predictive. For example, in their function as prognostic biomarkers, extremely high levels of DAMPs in sepsis patients measured immediately after onset of this infection complication may announce the development of a threatening multiple organ dysfunction syndrome (MODS) or even multiple organ failure (MOF); rapid reduction of these blood levels during subsequent appropriate treatment may predict a positive treatment effect leading to a beneficial outcome. On the other hand, too long periods of SAMPs in high concentrations may indicate a dangerous immunosuppressive phase following trauma. Hence, their use in therapeutic monitoring is taking several forms; besides predicting treatment responses, they may be harnessed to monitor for side effects and applied as surrogate endpoints in clinical trials.
1.5.3 Résumé In the following chapters on clinical aspects of the diseases covered, the use of DAMPs and SAMPs as biomarkers will be discussed separately. However, in the future, it may turn out that the measurement of DAMPs alone does not fulfill the expectations of physicians to obtain the diagnostic and prognostic information they requested and needed. Probably more exact information will be provided by targeted exploration, definition, and interpretation of distinct disease-specific “DAMPs pattern” and “SAMPs pattern” and/or even by a distinct DAMPs:SAMPs ratio. Indeed, the measurement and interpretation of “DAMPs and SAMPs patterns” and a “DAMPs:SAMPs ratio” may ultimately become a standard routine procedure for physicians in their daily diagnostic, prognostic, and predictive decision-making processes.
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1.6 Use of DAMPs and SAMPs as Therapeutic Targets or Therapeutics 1.6.1 Introductory Remarks The use of DAMPs as therapeutic targets or therapeutics has been described in Vol. 2 [2], Chap. 7, pp. 265–275. In particular, the various aspects of therapeutic caveats in harnessing DAMPs and SAMPs as therapeutic options were highlighted. Indeed, both the constitutive DAMPs and inducible DAMPs/SAMPs appear to be highly suitable to serve as future ideal diagnostic and prognostic biomarkers as well as therapeutic targets or therapeutics in daily clinical practice. Here, a few key aspects of the various options in practice will be recapitulated. Further details will be added as the various diseases are treated.
1.6.2 DAMPs and SAMPs as Therapeutic Targets For choosing DAMPs as therapeutic targets, DAMPs should be druggable molecules. Druggability is the property of a druggable molecule, that is, a biological target such as proteins and NA, by virtue of which they elicit a favorable clinical response when they contact a drug or a drug-like compound. Ideal drug targets should possess specific properties, including (1) binding with high affinity to a drug that must alter the function of the target with a therapeutic benefit to the patient, (2) differential expression across the body for specific targeting, (3) the quality of a biomarker to monitor its efficacy, and (4) freedom to operate, that is, lack of competitive binding [166–169]. DAMPs appear to fulfill these criteria. The idea of choosing DAMPs, for example, HMGB1 as therapeutic targets to inhibit innate immune responses with the use of monoclonal antibodies (mAbs) or biologicals, has already been proposed by Land in 2012 [170]. Today, several strategies are being discussed and applied to prevent DAMPs release or inhibiting their activities. Such therapeutic maneuvers are, for example, worth to consider in hyperinflammation as observed in systemic inflammatory response syndrome (SIRS) and certain chronic inflammatory/autoimmune diseases. Current pharmacological strategies include the use of mAbs, peptides, decoy receptors, and small molecules, but also absorption/adsorption procedures [171]. Indications to choose SAMPs as therapeutic targets may refer to situations of unwanted hyperresolution and/or immunosuppression, such as observed in compensatory anti-inflammatory response syndrome (CARS). Again, for choosing SAMPs as therapeutics targets in such cases, they should be druggable molecules.
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1.6.3 SAMPs as Therapeutics in Chronic Inflammatory Processes The concept of impaired resolution leading to chronic inflammatory disorders, autoimmune diseases like rheumatoid arthritis, and Crohn’s disease, as well as contributing to allergic diseases such as asthma, has paved the way to consider SAMPs as therapeutics in activating inflammation-resolving processes. In principle, potential therapeutics include adenosine, AnxA1, and SPMs, but also SPM derivatives, other synthetic small molecule agonists of SPM receptors, inhibitors of SPM-degrading enzymes (e.g., soluble epoxide hydrolase inhibitors), and modifiers of the SPM synthesis pathways. With the indications mentioned, SPMs have already proven potent proresolving actions in a range of disease models. Given their potency, many drug development opportunities are possible. As outlined by Serhan [172], aspirin and statins have a positive impact on these resolution pathways, producing epimeric forms of specific SPMs, whereas other drugs can disrupt timely resolution. As further outlined by this investigator [172], evidence from recent human and preclinical animal studies indicates that SPMs are physiologic mediators and pharmacologic agonists that stimulate resolution of inflammation and infection. This observation is reason enough to use them clinically as inhibitors and antagonists alone—and to develop immunoresolvents as agonists to test resolution pharmacology and their role in catabasis for their therapeutic potential [172]. Dalli [173] argues similarly when discussing the potential of resolution pharmacology-based approaches in developing new therapeutics for combatting infections that do not interfere with the immune response. This issue is also raised by Schett and Neurath [174], who discuss potential intervention strategies for fostering the resolution process and their implications for the therapy of inflammatory diseases. Indeed, given the new concept of inflammation resolution as an essential part of inflammation biology and pathology, the development of SAMPs for clinical use is a dictate of the hour. As stated by Serhan in this context [172], The available evidence from extensive preclinical animal models, human SPM production in vivo, and the limited results of randomized clinical trials in humans suggest that it is indeed time to consider stimulating resolution in the 21st century as a new therapeutic direction for managing unwanted excessive inflammation and infection. Proresolution pharmacology can enhance the host innate response to expedite microbial clearance, limit collateral tissue damage, and stimulate tissue regeneration by enhancing endogenous resolution mechanisms that are programmed into the resolving exudates of the acute inflammatory response. Of note, the concept has recently been echoed by Perez-Hernandez et al. [175] in their review on “Regulation of T-Cell Immune Responses by Pro-Resolving Lipid Mediators”: Therefore, these experimental data support SPM-based therapy as a promising avenue for the treatment of a wide range of T-cell-mediated immune and autoimmune diseases. …Building on the potent immunoresolvent properties of SPMs and their multiple targets, these findings open a new field of investigations that may provide a better understanding of the physiological regulation of adaptive immune response and its failure in pathophysiological contexts. SPM lipidomic analyses are indeed performed in the frame of several clinical studies as a read-out
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of disease diagnosis and progression, inflammatory profile (for instance in COVID19 patients [176]), as well as response to therapeutic interventions (NCT04698291, NCT04452942, NCT04697719, NCT01865448, NCT04308889, NCT04377334, and NCT02719665) [177]. Indeed, not only SPMs but also other SAMPs could stimulate the development of novel therapeutic strategies encompassing a novel “resolution pharmacology” approach. The emerging topic will be sustainably resumed in the following chapters when and if appropriate.
1.6.4 DAMPs as Therapeutics to Boost Innate Resistance 1.6.4.1 General Remarks The intrinsic evolution-determined nature of DAMPs is to promote adaptive immune defense responses via activation of antigen-presenting DCs. This implies that they can be used as therapeutics in situations in which a robust immune defense response is desired, that is, to promote anti-pathogen-directed immune processes aimed at conferring strong vaccination effects and to induce an ICD in cancer cells sought to instigate a potent antitumor immune response. 1.6.4.2 Administration of DAMPs in Vaccination Procedures There is a wide indication field for the administration of DAMPs to boost short- and long-term innate resistance against pathogens and cancer cells. To remember: for a long time, adjuvants have been used in vaccine formulations to induce potent adaptive (humoral!) immune responses that cannot be achieved with antigen alone [178]. Aluminum hydroxide (alum) is the most common adjuvant currently in clinical use [179, 180] that has been denoted as an exogenous DAMP (IVA-1 DAMP) in this book. Of note, in studies in mice, alum was found to cause cell death associated with the subsequent release of host cell DNA identified by the authors as a DAMP [181]. However, one has to realize that—according to current knowledge—cell death leads to large amounts of other DAMPs as well, which all mediate adjuvanticity. Thus, it is not a surprise that the ongoing development of novel vaccines intends to incorporate the combination of DAMP-inducing adjuvants and PAMP adjuvants [182]. Of note, a new dimension to the application of such exogenous DAMPs in vaccines, as touched above, is the recognition that nanoparticles such as LNPs, originally used only as delivery vehicles for vaccine antigens, have been proven to operate as potent DAMPs (newly termed IVD-4 DAMPs). 1.6.4.3 Induction of DAMPs in Antitumor Therapy The induction of an ICD aimed at promoting a robust antitumor immune response is currently an emerging topic in oncology. Fired by the danger/injury model in immunology, a conceptual revolution in oncology has emerged in that cancer is considered an entity that can be detected and destroyed by the immune system under certain circumstances. The core of this new concept refers to the phenomenon of ICD. Of note, however, only a few lethal stimuli are intrinsically endowed with
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the ability to instigate ICD, including certain chemotherapeutics, radiotherapy, certain oncolytic viruses, and photodynamic therapy [183]. They are called “ICD inducers” [184]. There is accumulating evidence indicating that these therapeutic inducers cause ICD through ER stress associated with or induced by ROS [185]. Typically, ICD is associated with emission of a series of DAMPs that are generated in a precise spatiotemporally defined configuration. This coordinated emission of DAMPs then allows elicitation of a robust antitumor immune response that is associated with the establishment of immunological memory.
1.6.4.4 Concluding Remark The clinical use of DAMPs as therapeutics aimed at promoting adaptive immune responses is emerging but probably not restricted to vaccination and antitumor therapy. Other fields of indication may be considered. For example, it may be imaginable to add certain DAMPs to antibiotic treatment in case of intractable infections, such as those observed in infectious disorders caused by antibiotic-resistant pathogens.
1.6.5 Résumé Here, some principles of DAMPs and SAMPs as therapeutic targets and therapeutics have been tentatively introduced. To implement these tasks clinically in the future, agonists to these molecules have to be developed, knowing that some are already available. For example, as reviewed by Venereau et al. [186] and Andersson et al. [187], there are reports on the successful use of polyclonal or mouse/rat anti- HMGB1 mAbs in a number of experimental inflammatory models. To enable development of HMGB1-targeted therapy for clinical use, humanized anti-HMGB1 mAbs have been worked out, for example, a partly humanized, chimeric mAb targeting HMGB1 with preserved functionality compared to the parental mouse anti- HMGB1 mAb [188]. Thus, removing or neutralizing extracellular HMGB1 in infectious or sterile inflammation would be a plausible approach to ameliorating human diseases concerned. However, up to now, there is only limited clinical evidence for therapeutic agents that target extracellular HMGB1, but several promising candidates are in preclinical or clinical development. As concluded in this context by Andersson et al. [187]: Blocking excessive amounts of extracellular HMGB1, particularly the disulfide isoform, offers an attractive clinical opportunity to ameliorate systemic inflammatory diseases. Therapeutic interventions to regulate intracellular HMGB1 biology must still await a deeper understanding of intracellular HMGB1 functions. Future work is needed to create more robust assays to evaluate functional bioactivity of HMGB1 antagonists. Forthcoming clinical studies would also greatly benefit from a development of antibody-based assays to quantify HMGB1 redox isoforms, presently assessed by mass spectrometry methods…. Together, we believe that HMGB1-specific antagonists should be tested in multiple parallel clinical studies of inflammatory disease syndromes to reveal whether blocking extracellular HMGB1 will benefit patients.
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Certainly, such opinions, statements, and conclusions must be uttered for antagonists of all the other critical DAMPs and SAMPs. As imaginable, this research field—including the activities of the pharmaceutical industry—is currently in full swing, and many highly exciting reports can be expected in the near future, providing a promising expansion of the therapeutic spectrum to treat human diseases. However, with all the optimistic reports currently being published about the promising therapeutic use of DAMPs and SAMPs in human diseases, a note of caution should be sounded, as we have recently articulated [123]: “The introduction of DAMPs and SAMPs as therapeutic targets and therapeutics will certainly enrich the therapeutic options of clinicians and physicians and may allow new sophisticated and efficient treatment modalities indicated for all those disorders that are characterized by currently untreatable, dysregulated inflammatory responses, including inflammatory diseases caused by environmental exposure.” In all these therapeutic efforts, however, it should not be forgotten that these molecules are responsible for the daily defense against any stress or injury. Also, here, the “Hippocratic oath” counts: “Primum non nocere.” Thus, for future optimal treatment modalities, the exact status of the DAMP/SAMP ratio should be determined in each patient. This concept would allow precise and timely intervention during infectious sepsis, either by inhibiting DAMPs (e.g., in the initial phase of SIRS) or blocking SAMPs (e.g., in the subsequent stage of CARS) to rebalance the immune response. However—as warned in Vol. 2 [2], Sect. 7.3.3.3, pp. 667/678—before any considerations to choose DAMPs or SAMPs as therapeutic targets to be inhibited, their homeostatic concentrations (e.g., in body fluids) that are required to establish a restitutio ad integrum following injury have to be a priori identified aimed at defining a homeostatic DAMPs:SAMPs ratio in a given situation. More precisely, and for safety reasons, a “homeostatic window” for DAMPs and SAMPs concentrations must be worked out in orientating clinical trials. The homeostatic window for DAMPs should not be exceeded because of increased risk of hyperinflammation and organ dysfunction but also not be undercut (deceeded) because of increased risk of compromised defensive repairing, that is, healing processes. On the other hand, the homeostatic window for SAMPs should not be exceeded because of increased risk of hyperresolution and immunosuppression and not be deceeded because of increased risk of hyperinflammation and organ dysfunction.
References 1. Land WG. Damage-associated molecular patterns in human diseases. Volume 1: injury-induced innate immune responses. Cham: Springer; 2018. https://doi.org/10.1007/978-3-319-78655-1. 2. Land WG. Damage-associated molecular patterns in human diseases. Vol. 2: danger signals as diagnostics, prognostics, and therapeutic targets. Cham: Springer; 2020. https://doi. org/10.1007/978-3-030-53868-2. 3. Land W. Allograft injury mediated by reactive oxygen species: from conserved proteins of Drosophila to acute and chronic rejection of human transplants. Part III: interaction of (oxidative) stress-induced heat shock proteins with toll-like receptor-bearing cells. Transplant Rev. 2003;17:67–86. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0955470X02000095.
34
1 Perspectives of the Danger/Injury Model of Immunology as Applied…
4. Seong S-Y, Matzinger P. Hydrophobicity: an ancient damage-associated molecular pattern that initiates innate immune responses. Nat Rev Immunol. 2004;4:469–78. Available from http://www.nature.com/articles/nri1372. 5. Yang D, de la Rosa G, Tewary P, Oppenheim JJ. Alarmins link neutrophils and dendritic cells. Trends Immunol. 2009;30:531–7. Available from: http://linkinghub.elsevier.com/retrieve/pii/ S1471490609001422. 6. Matzinger P. Tolerance, danger, and the extended family. Annu Rev Immunol. 1994;12:991–1045. Available from http://www.annualreviews.org/doi/10.1146/annurev. iy.12.040194.005015. 7. Land W, Schneeberger H, Schleibner S, Illner W-D, Abendroth D, Rutili G, et al. The beneficial effect of human recombinant superoxide dismutase on acute and chronic rejection events in recipients of cadaveric renal transplants. Transplantation. 1994;57:211–7. Available from http://journals.lww.com/00007890-199401001-00010. 8. Heil M, Land WG. Danger signals - damaged-self recognition across the tree of life. Front Plant Sci. 2014;5:578. Available from http://journal.frontiersin.org/article/10.3389/ fpls.2014.00578/abstract. 9. De Lorenzo G, Ferrari S, Cervone F, Okun E. Extracellular DAMPs in plants and mammals: immunity, tissue damage and repair. Trends Immunol. 2018;39:937–50. Available from https://linkinghub.elsevier.com/retrieve/pii/S1471490618301716. 10. Duran-Flores D, Heil M. Sources of specificity in plant damaged-self recognition. Curr Opin Plant Biol. 2016;32:77–87. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1369526616301029. 11. Meents AK, Mithöfer A. Plant–plant communication: is there a role for volatile damage- associated molecular patterns? Front Plant Sci. 2020;11:583275. Available from: https:// www.frontiersin.org/article/10.3389/fpls.2020.583275/full. 12. Kanoh H, Kuraishi T, Tong L-L, Watanabe R, Nagata S, Kurata S. Ex vivo genome-wide RNAi screening of the drosophila toll signaling pathway elicited by a larva-derived tissue extract. Biochem Biophys Res Commun. 2015;467:400–6. Available from https://linkinghub. elsevier.com/retrieve/pii/S0006291X15306549. 13. Singh J, Aballay A. Microbial colonization activates an immune fight-and-flight response via neuroendocrine signaling. Dev Cell. 2019;49:89–99. Available from https://linkinghub. elsevier.com/retrieve/pii/S1534580719300565. 14. Soo TCC, Devadas S, Mohamed Din MS, Bhassu S. Differential transcriptome analysis of the disease tolerant Madagascar–Malaysia crossbred black tiger shrimp, Penaeus monodon hepatopancreas in response to acute hepatopancreatic necrosis disease (AHPND) infection: inference on immune gene response and in. Gut Pathog. 2019;11:39. https://doi.org/10.1186/ s13099-019-0319-4. 15. Li C, Wang D, Guan X, Liu S, Su P, Li Q, et al. HMGB1 from Lampetra japonica promotes inflammatory activation in supraneural body cells. Dev Comp Immunol. 2019;92:50–9. Available from https://linkinghub.elsevier.com/retrieve/pii/S0145305X18303690. 16. Benedetti M, Pontiggia D, Raggi S, Cheng Z, Scaloni F, Ferrari S, et al. Plant immunity triggered by engineered in vivo release of oligogalacturonides, damage-associated molecular patterns. Proc Natl Acad Sci. 2015;112:5533–8. Available from http://www.pnas.org/lookup/ doi/10.1073/pnas.1504154112. 17. Cleves PA, Krediet CJ, Lehnert EM, Onishi M, Pringle JR. Insights into coral bleaching under heat stress from analysis of gene expression in a sea anemone model system. Proc Natl Acad Sci. 2020;117:28906–17. Available from: http://www.pnas.org/lookup/doi/10.1073/ pnas.2015737117. 18. Land WG. Role of DAMPs in respiratory virus-induced acute respiratory distress syndrome— with a preliminary reference to SARS-CoV-2 pneumonia. Genes Immun. 2021;22:141–60. Available from http://www.nature.com/articles/s41435-021-00140-w. 19. Land WG, Agostinis P, Gasser S, Garg AD, Linkermann A. Transplantation and damage- associated molecular patterns (DAMPs). Am J Transplant. 2016;16:3338–61. https://doi. org/10.1111/ajt.13963.
References
35
20. Halder SK, Matsunaga H, Ueda H. Neuron-specific non-classical release of prothymosin alpha: a novel neuroprotective damage-associated molecular patterns. J Neurochem. 2012;123:262–75. https://doi.org/10.1111/j.1471-4159.2012.07897.x. 21. Halder SK, Matsunaga H, Ishii KJ, Ueda H. Prothymosin-alpha preconditioning activates TLR4-TRIF signaling to induce protection of ischemic retina. J Neurochem. 2015;135:1161–77. https://doi.org/10.1111/jnc.13356. 22. Samara P, Karachaliou C-E, Ioannou K, Papaioannou N, Voutsas F, Zikos C, et al. Prothymosin alpha: an alarmin and more. Curr Med Chem. 2017;24:152541. Available from http://www. eurekaselect.com/152541/article. 23. Sarhan M, Land WG, Tonnus W, Hugo CP, Linkermann A. Origin and consequences of necroinflammation. Physiol Rev. 2018;98:727–80. https://doi.org/10.1152/physrev.00041.2016. 24. Tonnus W, Linkermann A. “Death is my Heir”–ferroptosis connects cancer pharmacogenomics and ischemia-reperfusion injury. Cell Chem Biol. 2016;23:202–3. Available from http:// www.ncbi.nlm.nih.gov/pubmed/26971867. 25. Tonnus W, Linkermann A. The in vivo evidence for regulated necrosis. Immunol Rev. 2017;277:128–49. Available from http://www.ncbi.nlm.nih.gov/pubmed/28462528. 26. Murao A, Aziz M, Wang H, Brenner M, Wang P. Release mechanisms of major DAMPs. Apoptosis. 2021;26:152–62. https://doi.org/10.1007/s10495-021-01663-3. 27. Carapito R, Jung N, Kwemou M, Untrau M, Michel S, Pichot A, et al. Matching for the nonconventional MHC-I MICA gene significantly reduces the incidence of acute and chronic GVHD. Blood. 2016;128:1979–86. Available from http://www.ncbi.nlm.nih.gov/ pubmed/27549307. 28. Green DR, Oguin TH, Martinez J. The clearance of dying cells: table for two. Cell Death Differ. 2016;23:915–26. Available from http://www.nature.com/articles/cdd2015172. 29. Elliott MR, Koster KM, Murphy PS. Efferocytosis signaling in the regulation of macrophage inflammatory responses. J Immunol. 2017;198:1387–94. Available from http://www.ncbi. nlm.nih.gov/pubmed/28167649. 30. Greenlee-Wacker MC. Clearance of apoptotic neutrophils and resolution of inflammation. Immunol Rev. 2016;273:357–70. Available from http://www.ncbi.nlm.nih.gov/ pubmed/27558346. 31. Schcolnik-Cabrera A, Oldak B, Juárez M, Cruz-Rivera M, Flisser A, Mendlovic F. Calreticulin in phagocytosis and cancer: opposite roles in immune response outcomes. Apoptosis. 2019;24:245–55. https://doi.org/10.1007/s10495-019-01532-0. 32. Zingoni A, Molfetta R, Fionda C, Soriani A, Paolini R, Cippitelli M, et al. NKG2D and its ligands: “one for all, all for one”. Front Immunol. 2018;9:476. Available from http://www. ncbi.nlm.nih.gov/pubmed/29662484. 33. Hosomi S, Grootjans J, Huang Y-H, Kaser A, Blumberg RS. New insights into the regulation of natural-killer group 2 member D (NKG2D) and NKG2D-ligands: endoplasmic reticulum stress and CEA-related cell adhesion molecule 1. Front Immunol. 2018;9:1324. https://doi. org/10.3389/fimmu.2018.01324/full. 34. Roers A, Hiller B, Hornung V. Recognition of endogenous nucleic acids by the innate immune system. Immunity. 2016;44:739–54. Available from http://linkinghub.elsevier.com/ retrieve/pii/S1074761316301078. 35. Mavragani I, Nikitaki Z, Souli M, Aziz A, Nowsheen S, Aziz K, et al. Complex DNA damage: a route to radiation-induced genomic instability and carcinogenesis. Cancer. 2017;9:91. Available from http://www.ncbi.nlm.nih.gov/pubmed/28718816. 36. van Vliet AR, Agostinis P. When under pressure, get closer: PERKing up membrane contact sites during ER stress. Biochem Soc Trans. 2016;44:499–504. Available from http://www. ncbi.nlm.nih.gov/pubmed/27068961. 37. Carapito R, Bahram S. Genetics, genomics, and evolutionary biology of NKG2D ligands. Immunol Rev. 2015;267:88–116. Available from http://www.ncbi.nlm.nih.gov/ pubmed/26284473 38. Carapito R. Personal communication.
36
1 Perspectives of the Danger/Injury Model of Immunology as Applied…
39. Gallo PM, Gallucci S. The dendritic cell response to classic, emerging, and homeostatic danger signals. Implications for autoimmunity. Front Immunol. 2013;4:138. Available from http://www.ncbi.nlm.nih.gov/pubmed/23772226. 40. Liston A, Masters SL. Homeostasis-altering molecular processes as mechanisms of inflammasome activation. Nat Rev Immunol. 2017;17:208–14. Available from http://www.nature. com/doifinder/10.1038/nri.2016.151. 41. Land WG. Emerging role of innate immunity in organ transplantation part II: potential of damage- associated molecular patterns to generate immunostimulatory dendritic cells. Transplant Rev. 2012;26:73–87. Available from http://www.ncbi.nlm.nih.gov/ pubmed/22074784. 42. Danziger J, Zeidel ML. Osmotic homeostasis. Clin J Am Soc Nephrol. 2015;10:852–62. https://doi.org/10.2215/CJN.10741013. 43. Sprooten J, Garg AD. Type I interferons and endoplasmic reticulum stress in health and disease. Int Rev Cell Mol Biol. 2020;350:63–118. Available from https://pubmed.ncbi.nlm.nih. gov/32138904/. 44. Yatim N, Cullen S, Albert ML. Dying cells actively regulate adaptive immune responses. Nat Rev Immunol. 2017;17:262–75. Available from http://www.nature.com/articles/nri.2017.9. 45. Valenti P, Antonini G. Lactoferrin. Cell Mol Life Sci. 2005;62:2576–87. Available from http://link.springer.com/10.1007/s00018-005-5372-0. 46. Sharma D, Murki A, Murki S, Pratap OT. Use of lactoferrin in the newborn: where do we stand? J Matern Neonatal Med. 2015;28:1774–8. https://doi.org/10.3109/1476705 8.2014.968548. 47. Latorre D, Puddu P, Valenti P, Gessani S. Reciprocal interactions between lactoferrin and bacterial endotoxins and their role in the regulation of the immune response. Toxins. 2010;2:54–68. Available from http://www.mdpi.com/2072-6651/2/1/54. 48. Hwang S-A, Kruzel ML, Actor JK. Recombinant human lactoferrin modulates human PBMC derived macrophage responses to BCG and LPS. Tuberculosis. 2016;101:53–62. Available from https://linkinghub.elsevier.com/retrieve/pii/S147297921630395X. 49. Souza PPC, Lerner UH. The role of cytokines in inflammatory bone loss. Immunol Investig. 2013;42:555–622. https://doi.org/10.3109/08820139.2013.822766. 50. Souza PPC, Lerner UH. Finding a toll on the route: the fate of osteoclast progenitors after toll-like receptor activation. Front Immunol. 2019;10:e01663. Available from https://www. frontiersin.org/article/10.3389/fimmu.2019.01663/full. 51. Theill LE, Boyle WJ, Penninger JM. RANK-L and RANK: T cells, bone loss, and mammalian evolution. Annu Rev Immunol. 2002;20:795–823. https://doi.org/10.1146/annurev. immunol.20.100301.064753. 52. Nakagawa N, Kinosaki M, Yamaguchi K, Shima N, Yasuda H, Yano K, et al. RANK is the essential signaling receptor for osteoclast differentiation factor in osteoclastogenesis. Biochem Biophys Res Commun. 1998;253:395–400. Available from https://pubmed.ncbi. nlm.nih.gov/9878548/. 53. Hsu H, Lacey DL, Dunstan CR, Solovyev I, Colombero A, Timms E, et al. Tumor necrosis factor receptor family member RANK mediates osteoclast differentiation and activation induced by osteoprotegerin ligand. Proc Natl Acad Sci. 1999;96:3540–5. https://doi. org/10.1073/pnas.96.7.3540. 54. Qiang X, Yang W-L, Wu R, Zhou M, Jacob A, Dong W, et al. Cold-inducible RNA-binding protein (CIRP) triggers inflammatory responses in hemorrhagic shock and sepsis. Nat Med. 2013;19:1489–95. Available from http://www.nature.com/articles/nm.3368. 55. Ode Y, Aziz M, Jin H, Arif A, Nicastro JG, Wang P. Cold-inducible RNA-binding protein induces neutrophil extracellular traps in the lungs during sepsis. Sci Rep. 2019;9:6252. Available from http://www.nature.com/articles/s41598-019-42762-1. 56. Shields AM, Thompson SJ, Panayi GS, Corrigall VM. Pro-resolution immunological networks: binding immunoglobulin protein and other resolution-associated molecular patterns. Rheumatology. 2012;51:780–8. Available from https://academic.oup.com/rheumatology/ article-lookup/doi/10.1093/rheumatology/ker412.
References
37
57. Hangai S, Ao T, Kimura Y, Matsuki K, Kawamura T, Negishi H, et al. PGE2 induced in and released by dying cells functions as an inhibitory DAMP. Proc Natl Acad Sci. 2016;113:3844–9. Available from http://www.pnas.org/lookup/doi/10.1073/pnas.1602023113. 58. Serhan CN, Levy BD. Resolvins in inflammation: emergence of the pro-resolving superfamily of mediators. J Clin Invest. 2018;128:2657–69. Available from http://www.ncbi.nlm.nih. gov/pubmed/29757195. 59. O’Callaghan G, Houston A. Prostaglandin E2 and the EP receptors in malignancy: possible therapeutic targets? Br J Pharmacol. 2015;172:5239–50. Available from http://www.ncbi. nlm.nih.gov/pubmed/26377664. 60. Kawahara K, Hohjoh H, Inazumi T, Tsuchiya S, Sugimoto Y. Prostaglandin E2-induced inflammation: relevance of prostaglandin E receptors. Biochim Biophys Acta Mol Cell Biol Lipids. 2015;1851:414–21. Available from http://www.ncbi.nlm.nih.gov/pubmed/25038274. 61. Hangai S, Ao T, Kimura Y, Matsuki K, Kawamura T, Negishi H, et al. PGE2 induced in and released by dying cells functions as an inhibitory DAMP. Proc Natl Acad Sci U S A. 2016;113:3844–9. Available from http://www.pnas.org/lookup/doi/10.1073/ pnas.1602023113. 62. Koga K, Takaesu G, Yoshida R, Nakaya M, Kobayashi T, Kinjyo I, et al. Cyclic adenosine monophosphate suppresses the transcription of proinflammatory cytokines via the phosphorylated c-Fos protein. Immunity. 2009;30:372–83. Available from http://www.ncbi.nlm.nih. gov/pubmed/19285436. 63. Sokolowska M, Chen L-Y, Liu Y, Martinez-Anton A, Qi H-Y, Logun C, et al. Prostaglandin E2 inhibits NLRP3 inflammasome activation through EP4 receptor and intracellular cyclic AMP in human macrophages. J Immunol. 2015;194:5472–87. https://doi.org/10.4049/ jimmunol.1401343. 64. Lima KM, Vago JP, Caux TR, Negreiros-Lima GL, Sugimoto MA, Tavares LP, et al. The resolution of acute inflammation induced by cyclic AMP is dependent on annexin A1. J Biol Chem. 2017;292(33):13758–73. Available from http://www.ncbi.nlm.nih.gov/ pubmed/28655761. 65. Vourch M, Roquilly A, Asehnoune K. Trauma-induced damage-associated molecular patterns-mediated remote organ injury and immunosuppression in the acutely ill patient. Front Immunol. 2018;9:1330. Available from https://www.frontiersin.org/article/10.3389/ fimmu.2018.01330/full. 66. Antonioli L, Fornai M, Blandizzi C, Pacher P, Haskó G. Adenosine signaling and the immune system: when a lot could be too much. Immunol Lett. 2019;205:9–15. Available from http:// www.ncbi.nlm.nih.gov/pubmed/29702147. 67. Perretti M, D’Acquisto F. Annexin A1 and glucocorticoids as effectors of the resolution of inflammation. Nat Rev Immunol. 2009;9:62–70. Available from http://www.nature.com/ doifinder/10.1038/nri2470. 68. Gavins FNE, Hickey MJ. Annexin A1 and the regulation of innate and adaptive immunity. Front Immunol. 2012;3:354. Available from http://www.ncbi.nlm.nih.gov/pubmed/23230437. 69. Sousa LP, Alessandri AL, Pinho V, Teixeira MM. Pharmacological strategies to resolve acute inflammation. Curr Opin Pharmacol. 2013;13:625–31. Available from http://linkinghub.elsevier.com/retrieve/pii/S1471489213000416. 70. Sugimoto MA, Vago JP, Teixeira MM, Sousa LP. Annexin A1 and the resolution of inflammation: modulation of neutrophil recruitment, apoptosis, and clearance. J Immunol Res. 2016;2016:1–13. Available from http://www.ncbi.nlm.nih.gov/pubmed/26885535. 71. Serhan CN. Pro-resolving lipid mediators are leads for resolution physiology. Nature. 2014;510:92–101. Available from http://www.nature.com/doifinder/10.1038/nature13479. 72. Basil MC, Levy BD. Specialized pro-resolving mediators: endogenous regulators of infection and inflammation. Nat Rev Immunol. 2016;16:51–67. Available from http://www.nature. com/articles/nri.2015.4. 73. Serhan CN, Chiang N, Dalli J, Levy BD. Lipid mediators in the resolution of inflammation. Cold Spring Harb Perspect Biol. 2014;7:a016311. https://doi.org/10.1101/cshperspect. a016311.
38
1 Perspectives of the Danger/Injury Model of Immunology as Applied…
74. McKinney CA, Fattah C, Loughrey CM, Milligan G, Nicklin SA. Angiotensin-(1–7) and angiotensin-(1–9): function in cardiac and vascular remodelling. Clin Sci. 2014;126:815–27. Available from https://portlandpress.com/clinsci/article/126/12/815/69167/ Angiotensin17-and-angiotensin19-function-in. 75. Anderson HA, Maylock CA, Williams JA, Paweletz CP, Shu H, Shacter E. Serum-derived protein S binds to phosphatidylserine and stimulates the phagocytosis of apoptotic cells. Nat Immunol. 2003;4:87–91. Available from http://www.nature.com/doifinder/10.1038/ni871. 76. Frasch SC, Bratton DL. Emerging roles for lysophosphatidylserine in resolution of inflammation. Prog Lipid Res. 2012;51:199–207. Available from http://www.ncbi.nlm.nih.gov/ pubmed/22465125. 77. Frasch SC, Fernandez-Boyanapalli RF, Berry KAZ, Murphy RC, Leslie CC, Nick JA, et al. Neutrophils regulate tissue neutrophilia in inflammation via the oxidant-modified lipid lysophosphatidylserine. J Biol Chem. 2013;288:4583–93. Available from http://www.ncbi.nlm. nih.gov/pubmed/23293064. 78. Zagórska A, Través PG, Lew ED, Dransfield I, Lemke G. Diversification of TAM receptor tyrosine kinase function. Nat Immunol. 2014;15:920–8. Available from: http://www.ncbi. nlm.nih.gov/pubmed/25194421. 79. Franz S, Muñoz LE, Heyder P, Herrmann M, Schiller M. Unconventional apoptosis of polymorphonuclear neutrophils (PMN): staurosporine delays exposure of phosphatidylserine and prevents phagocytosis by MΦ-2 macrophages of PMN. Clin Exp Immunol. 2015;179:75–84. Available from http://www.ncbi.nlm.nih.gov/pubmed/24995908. 80. Griffiths HR, Gao D, Pararasa C. Redox regulation in metabolic programming and inflammation. Redox Biol. 2017;12:50–7. Available from http://www.ncbi.nlm.nih.gov/ pubmed/28212523. 81. Lemke G. Phosphatidylserine is the signal for TAM receptors and their ligands. Trends Biochem Sci. 2017;42:738–48. Available from http://www.ncbi.nlm.nih.gov/pubmed/28734578. 82. Zhang Y-H, Zhang Y, Dong X-F, Hao Q-Q, Zhou X-M, Yu Q-T, et al. ACE2 and Ang-(1–7) protect endothelial cell function and prevent early atherosclerosis by inhibiting inflammatory response. Inflamm Res. 2015;64:253–60. Available from http://link.springer.com/10.1007/ s00011-015-0805-1. 83. Serfozo P, Wysocki J, Gulua G, Schulze A, Ye M, Liu P, et al. Ang II (angiotensin II) conversion to angiotensin-(1-7) in the circulation is POP (prolyloligopeptidase)-dependent and ACE2 (angiotensin-converting enzyme 2)-independent. Hypertens NLM. 2020;75:173–82. https://doi.org/10.1161/HYPERTENSIONAHA.119.14071. 84. Guo L, Yin A, Zhang Q, Zhong T, O’Rourke ST, Sun C. Angiotensin-(1–7) attenuates angiotensin II-induced cardiac hypertrophy via a Sirt3-dependent mechanism. Am J Physiol Circ Physiol. 2017;312:980–91. https://doi.org/10.1152/ajpheart.00768.2016. 85. Bsibsi M, Holtman IR, Gerritsen WH, Eggen BJL, Boddeke E, van der Valk P, et al. Alpha-B- crystallin induces an immune-regulatory and antiviral microglial response in preactive multiple sclerosis lesions. J Neuropathol Exp Neurol. 2013;72:970–9. https://doi.org/10.1097/ NEN.0b013e3182a776bf. 86. Holtman IR, Bsibsi M, Gerritsen WH, Boddeke HWGM, Eggen BJL, van der Valk P, et al. Identification of highly connected hub genes in the protective response program of human macrophages and microglia activated by alpha B-crystallin. Glia. 2017;65:460–73. https:// doi.org/10.1002/glia.23104. 87. Pointer CB, Wenzel TJ, Klegeris A. Extracellular cardiolipin regulates select immune functions of microglia and microglia-like cells. Brain Res Bull. 2019;146:153–63. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0361923018306816. 88. Leoni G, Nusrat A. Annexin A1: shifting the balance towards resolution and repair. Biol Chem. 2016;397:971–9. Available from https://www.degruyter.com/document/doi/10.1515/ hsz-2016-0180/html. 89. Serhan CN, Chiang N, Dalli J. New pro-resolving n-3 mediators bridge resolution of infectious inflammation to tissue regeneration. Mol Asp Med. 2018;64:1–17. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0098299717300912.
References
39
90. Chiang N, Serhan CN. Specialized pro-resolving mediator network: an update on production and actions. Essays Biochem. 2020;64:443–62. Available from https://portlandpress.com/ essaysbiochem/article/64/3/443/226308/Specialized-pro-resolving-mediator-network-an. 91. McArthur S, Juban G, Gobbetti T, Desgeorges T, Theret M, Gondin J, et al. Annexin A1 drives macrophage skewing to accelerate muscle regeneration through AMPK activation. J Clin Invest. 2020;130:1156–67. Available from https://www.jci.org/articles/view/124635. 92. Cheng H, Huang H, Guo Z, Chang Y, Li Z. Role of prostaglandin E2 in tissue repair and regeneration. Theranostics. 2021;11:8836–54. Available from https://www.thno.org/ v11p8836.htm. 93. Bottazzi B, Doni A, Garlanda C, Mantovani A. An integrated view of humoral innate immunity: pentraxins as a paradigm. Annu Rev Immunol. 2010;28:157–83. https://doi.org/10.1146/ annurev-immunol-030409-101305. 94. Mantovani A, Valentino S, Gentile S, Inforzato A, Bottazzi B, Garlanda C. The long pentraxin PTX3: a paradigm for humoral pattern recognition molecules. Ann N Y Acad Sci. 2013;1285:1–14. https://doi.org/10.1111/nyas.12043. 95. Pathak A, Agrawal A. Evolution of C-reactive protein. Front Immunol. 2019;10:943. https:// doi.org/10.3389/fimmu.2019.00943/full. 96. Jaillon S, Ponzetta A, Magrini E, Barajon I, Barbagallo M, Garlanda C, et al. Fluid phase recognition molecules in neutrophil-dependent immune responses. Semin Immunol. 2016;28:109–18. Available from http://www.ncbi.nlm.nih.gov/pubmed/27021644. 97. Bozza S, Campo S, Arseni B, Inforzato A, Ragnar L, Bottazzi B, et al. PTX3 binds MD-2 and promotes TRIF-dependent immune protection in aspergillosis. J Immunol. 2014;193:2340–8. Available from http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.1400814. 98. Rathore M, Girard C, Ohanna M, Tichet M, Ben Jouira R, Garcia E, et al. Cancer cell- derived long pentraxin 3 (PTX3) promotes melanoma migration through a toll-like receptor 4 (TLR4)/NF-κB signaling pathway. Oncogene. 2019;38:5873–89. Available from http://www. nature.com/articles/s41388-019-0848-9. 99. Sun W, Wu Y, Gao M, Tian Y, Qi P, Shen Y, et al. C-reactive protein promotes inflammation through TLR4/NF-κB/TGF-β pathway in HL-1 cells. Biosci Rep. 2019;39:8. Available from https://portlandpress.com/bioscirep/article/39/8/ BSR20190888/219383/C-reactive-protein-promotes-inflammation-through. 100. Yang Y-F, Zhou Y-D, Hu J-C, Luo F-L, Xie Y, Shen Y-Y, et al. Ficolin-A/2, acting as a new regulator of macrophage polarization, mediates the inflammatory response in experimental mouse colitis. Immunology. 2017;151:433–50. https://doi.org/10.1111/imm.12741. 101. Ramani V, Madhusoodhanan R, Kosanke S, Awasthi S. A TLR4-interacting SPA4 peptide inhibits LPS-induced lung inflammation. Innate Immun. 2013;19:596–610. https://doi. org/10.1177/1753425912474851. 102. Awasthi S, Kumar G, Ramani V, Awasthi V, Rodgers KK, Xie J, et al. Mechanism of anti- inflammatory activity of TLR4-interacting SPA4 peptide. Immunohorizons. 2021;5:659–74. https://doi.org/10.4049/immunohorizons.2100067. 103. Smole U, Gour N, Phelan J, Hofer G, Köhler C, Kratzer B, et al. Serum amyloid A is a soluble pattern recognition receptor that drives type 2 immunity. Nat Immunol. 2020;21:756–65. Available from http://www.nature.com/articles/s41590-020-0698-1. 104. Sack GH. Serum amyloid A (SAA) proteins. Subcell Biochem. 2020;94:421–36. https://doi. org/10.1007/978-3-030-41769-7_17. 105. Ye RD, Sun L. Emerging functions of serum amyloid A in inflammation. J Leukoc Biol. 2015;98:923–9. https://doi.org/10.1189/jlb.3VMR0315-080R. 106. Das UN. Essential fatty acids and their metabolites in the pathobiology of inflammation and its resolution. Biomol Ther. 2021;11:1873. Available from https://www.mdpi.com/2218- 273X/11/12/1873. 107. Loynes CA, Lee JA, Robertson AL, Steel MJG, Ellett F, Feng Y, et al. PGE 2 production at sites of tissue injury promotes an anti-inflammatory neutrophil phenotype and determines the outcome of inflammation resolution in vivo. Sci Adv. 2018;4:8320. Available from https:// www.science.org/doi/10.1126/sciadv.aar8320.
40
1 Perspectives of the Danger/Injury Model of Immunology as Applied…
108. Pulendran B, Arunachalam S, O’Hagan DT. Emerging concepts in the science of vaccine adjuvants. Nat Rev Drug Discov. 2021;20:454–75. Available from http://www.nature.com/ articles/s41573-021-00163-y. 109. Travieso T, Li J, Mahesh S, Mello JDFRE, Blasi M. The use of viral vectors in vaccine development. NPJ Vaccines. 2022;7:75. Available from https://www.nature.com/articles/ s41541-022-00503-y. 110. Rauch S, Jasny E, Schmidt KE, Petsch B. New vaccine technologies to combat outbreak situations. Front Immunol. 2018;9:e01963. Available from: https://www.frontiersin.org/ article/10.3389/fimmu.2018.01963/full. 111. Ghaffarifar F. Plasmid DNA vaccines: where are we now? Drugs Today. 2018;54:315. Available from http://journals.prous.com/journals/servlet/xmlxsl/pk_journals. xml_summary_pr?p_JournalId=4&p_RefId=2807864&p_IsPs=N. 112. Gary EN, Weiner DB. DNA vaccines: prime time is now. Curr Opin Immunol. 2020;65:21–7. Available from https://linkinghub.elsevier.com/retrieve/pii/S095279152030008X. 113. Li L, Petrovsky N. Molecular mechanisms for enhanced DNA vaccine immunogenicity. Expert Rev Vaccines. 2016;15:313–29. https://doi.org/10.1586/14760584.2016.1124762. 114. Pardi N, Hogan MJ, Porter FW, Weissman D. mRNA vaccines — a new era in vaccinology. Nat Rev Drug Discov. 2018;17:261–79. Available from https://www.nature.com/articles/ nrd.2017.243. 115. Park JW, Lagniton PNP, Liu Y, Xu R-H. mRNA vaccines for COVID-19: what, why and how. Int J Biol Sci. 2021;17:1446–60. Available from https://www.ijbs.com/v17p1446.htm. 116. Fadeel B. Clear and present danger? Engineered nanoparticles and the immune system. Swiss Med Wkly. 2012;142:13609. Available from http://doi.emh.ch/smw.2012.13609. 117. Yue L, Qidian L, Jiawei W, Rou X, Miao H. Acute iron oxide nanoparticles exposure induced murine eosinophilic airway inflammation via TLR2 and TLR4 signaling. Environ Toxicol. 2022;37:925–35. https://doi.org/10.1002/tox.23455. 118. Parhiz H, Brenner JS, Patel PN, Papp TE, Shahnawaz H, Li Q, et al. Added to pre-existing inflammation, mRNA-lipid nanoparticles induce inflammation exacerbation (IE). J Control Release. 2022;344:50–61. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0168365921006805. 119. Sharma B, McLeland CB, Potter TM, Stern ST, Adiseshaiah PP. Assessing NLRP3 inflammasome activation by nanoparticles. Methods Mol Biol. 2018;1682:135–47. https://doi. org/10.1007/978-1-4939-7352-1_12. 120. Tahtinen S, Tong A-J, Himmels P, Oh J, Paler-Martinez A, Kim L, et al. IL-1 and IL-1ra are key regulators of the inflammatory response to RNA vaccines. Nat Immunol. 2022;23:532–42. Available from https://www.nature.com/articles/s41590-022-01160-y. 121. Liang JJ, Fraser IDC, Bryant CE. Lipid regulation of NLRP3 inflammasome activity through organelle stress. Trends Immunol. 2021;42:807–23. Available from https://linkinghub.elsevier.com/retrieve/pii/S147149062100140X. 122. Land WG. Role of damage-associated molecular patterns in light of modern environmental research: a tautological approach. Int J Environ Res. 2020;14:583–604. https://doi. org/10.1007/s41742-020-00276-z. 123. Land WG. Use of DAMPs and SAMPs as therapeutic targets or therapeutics: a note of caution. Mol Diagn Ther. 2020;24:251–62. https://doi.org/10.1007/s40291-020-00460-z. 124. Banchereau J, Briere F, Caux C, Davoust J, Lebecque S, Liu YJ, et al. Immunobiology of dendritic cells. Annu Rev Immunol. 2000;18:767–811. https://doi.org/10.1146/annurev. immunol.18.1.767. 125. Shortman K, Naik SH. Steady-state and inflammatory dendritic-cell development. Nat Rev Immunol. 2007;7:19–30. Available from http://www.ncbi.nlm.nih.gov/pubmed/17170756. 126. Hammer GE, Ma A. Molecular control of steady-state dendritic cell maturation and immune homeostasis. Annu Rev Immunol. 2013;31:743–91. https://doi.org/10.1146/ annurev-immunol-020711-074929.
References
41
127. Dalod M, Chelbi R, Malissen B, Lawrence T. Dendritic cell maturation: functional specialization through signaling specificity and transcriptional programming. EMBO J. 2014;33:1104–16. https://doi.org/10.1002/embj.201488027. 128. Vega-Ramos J, Roquilly A, Zhan Y, Young LJ, Mintern JD, Villadangos JA. Inflammation conditions mature dendritic cells to retain the capacity to present new antigens but with altered cytokine secretion function. J Immunol. 2014;193:3851–9. https://doi.org/10.4049/ jimmunol.1303215. 129. Bretscher P, Cohn M. A theory of self-nonself discrimination. Science. 1970;169:1042–9. https://doi.org/10.1126/science.169.3950.1042. 130. Lafferty K, Cunningham A. A new analysis of allogeneic interactions. Aust J Exp Biol Med Sci. 1975;53:27–42. https://doi.org/10.1038/icb.1975.3. 131. Janeway CA. Approaching the asymptote? Evolution and revolution in immunology. Cold Spring Harb Symp Quant Biol. 1989;54:1–13. Available from http://www.ncbi.nlm.nih.gov/ pubmed/2700931. 132. Janeway CA. The immune system evolved to discriminate infectious nonself from noninfectious self. Immunol Today. 1992;13:11–6. Available from https://linkinghub.elsevier.com/ retrieve/pii/016756999290198G. 133. Land W. Postischemic reperfusion injury to allografts: its impact on T-cell alloactivation via upregulation of dendritic cell-mediated stimulation, co-stimulation, and adhesion. Curr Opin Organ Transplant. 1999;4:118–24.Available from https://journals.lww.com/co-transplantation/ Abstract/1999/06000/Postischemic_reperfusion_injury_to_allografts__its.3.aspx. 134. Land W. Postischemic reperfusion injury and allograft dysfunction: is allograft rejection the result of a fateful confusion by the immune system of danger and benefit? Transplant Proc. 1999;31:332–6. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0041134598016510. 135. Matzinger P. The danger model: a renewed sense of self. Science. 2002;296:301–5. Available from https://www.science.org/doi/10.1126/science.1071059. 136. Land W. Postischemic reperfusion injury to allografts – a case for ‘innate immunity’? Eur Surg Res. 2002;34:160–9. Available from https://www.karger.com/Article/FullText/48904. 137. Bournazos S, Ravetch JV. Diversification of IgG effector functions. Int Immunol. 2017;29:303–10. Available from https://academic.oup.com/intimm/article/29/7/303/3787477. 138. Wang X, Mathieu M, Brezski RJ. IgG Fc engineering to modulate antibody effector functions. Protein Cell. 2018;9:63–73. https://doi.org/10.1007/s13238-017-0473-8. 139. Chen T, Li Y, Sun R, Hu H, Liu Y, Herrmann M, et al. Receptor-mediated NETosis on neutrophils. Front Immunol. 2021;12:775267. https://doi.org/10.3389/fimmu.2021.775267/full. 140. Palmer LJ, Damgaard C, Holmstrup P, Nielsen CH. Influence of complement on neutrophil extracellular trap release induced by bacteria. J Periodontal Res. 2016;51:70–6. https://doi. org/10.1111/jre.12284. 141. Diago-Navarro E, Calatayud-Baselga I, Sun D, Khairallah C, Mann I, Ulacia-Hernando A, et al. Antibody-based immunotherapy to treat and prevent infection with hypervirulent klebsiella pneumoniae. Clin Vaccine Immunol. 2017;24:16. https://doi.org/10.1128/CVI.00456-16. 142. Stacey HD, Golubeva D, Posca A, Ang JC, Novakowski KE, Zahoor MA, et al. IgA potentiates NETosis in response to viral infection. Proc Natl Acad Sci. 2021;118:e2101497118. https://doi.org/10.1073/pnas.2101497118. 143. Boribong BP, LaSalle TJ, Bartsch YC, Ellett F, Loiselle ME, Davis JP, et al. Neutrophil profiles of pediatric COVID-19 and multisystem inflammatory syndrome in children. Prepr Serv Biol. 2021. Available from http://www.pubmedcentral.nih.gov/articlerender. fcgi?artid=PMC8722589. 144. Wooldridge L, Ekeruche-Makinde J, van den Berg HA, Skowera A, Miles JJ, Tan MP, et al. A single autoimmune T cell receptor recognizes more than a million different peptides. J Biol Chem. 2012;287:1168–77. Available from https://linkinghub.elsevier.com/retrieve/pii/ S002192582053353X.
42
1 Perspectives of the Danger/Injury Model of Immunology as Applied…
145. Golstein P, Griffiths GM. An early history of T cell-mediated cytotoxicity. Nat Rev Immunol. 2018;18:527–35. Available from http://www.nature.com/articles/s41577-018-0009-3. 146. Gálvez J, Gálvez JJ, García-Peñarrubia P. Is TCR/pMHC affinity a good estimate of the T-cell response? An answer based on predictions from 12 phenotypic models. Front Immunol. 2019;10:349. Available from https://www.frontiersin.org/article/10.3389/ fimmu.2019.00349/full. 147. Raskov H, Orhan A, Christensen JP, Gögenur I. Cytotoxic CD8+ T cells in cancer and cancer immunotherapy. Br J Cancer. 2021;124:359–67. Available from https://www.nature.com/ articles/s41416-020-01048-4. 148. Miguel D, Ramirez-Labrada A, Uranga I, Hidalgo S, Santiago L, Galvez EM, et al. Inflammatory cell death induced by cytotoxic lymphocytes: a dangerous but necessary liaison. FEBS J. 2021;2021:16093. https://doi.org/10.1111/febs.16093. 149. Zhou Z, He H, Wang K, Shi X, Wang Y, Su Y, et al. Granzyme A from cytotoxic lymphocytes cleaves GSDMB to trigger pyroptosis in target cells. Science. 2020;368:7548. https://doi. org/10.1126/science.aaz7548. 150. Liu Y, Fang Y, Chen X, Wang Z, Liang X, Zhang T, et al. Gasdermin E–mediated target cell pyroptosis by CAR T cells triggers cytokine release syndrome. Sci Immunol. 2020;5:7969. https://doi.org/10.1126/sciimmunol.aax7969. 151. Liao P, Wang W, Wang W, Kryczek I, Li X, Bian Y, et al. CD8+ T cells and fatty acids orchestrate tumor ferroptosis and immunity via ACSL4. Cancer Cell. 2022;40:365–78. Available from https://linkinghub.elsevier.com/retrieve/pii/S1535610822000368. 152. Pobezinskaya YL, Liu Z. The role of TRADD in death receptor signaling. Cell Cycle. 2012;11:871–6. Available from http://www.tandfonline.com/doi/abs/10.4161/cc.11.5.19300. 153. Walczak H. Death receptor-ligand systems in cancer, cell death, and inflammation, vol. 5. Cold Spring Harb Perspect Biol; 2013. p. a008698. https://doi.org/10.1101/cshperspect. a008698. 154. Mehta AK, Gracias DT, Croft M. TNF activity and T cells. Cytokine. 2018;101:14–8. Available from https://linkinghub.elsevier.com/retrieve/pii/S1043466616304501. 155. Rossin A, Miloro G, Hueber A-O. TRAIL and FasL functions in cancer and autoimmune diseases: towards an increasing complexity. Cancer. 2019;11:639. Available from https://www. mdpi.com/2072-6694/11/5/639. 156. Gong Y, Fan Z, Luo G, Yang C, Huang Q, Fan K, et al. The role of necroptosis in cancer biology and therapy. Mol Cancer. 2019;18:100. Available from https://molecular-cancer.biomedcentral.com/articles/10.1186/s12943-019-1029-8. 157. Janjic BM, Kulkarni A, Ferris RL, Vujanovic L, Vujanovic NL. Human B cells mediate innate anti-cancer cytotoxicity through concurrent engagement of multiple TNF superfamily ligands. Front Immunol. 2022;13:837842. https://doi.org/10.3389/fimmu.2022.837842/full. 158. Hagn M, Sontheimer K, Dahlke K, Brueggemann S, Kaltenmeier C, Beyer T, et al. Human B cells differentiate into granzyme B-secreting cytotoxic B lymphocytes upon incomplete T-cell help. Immunol Cell Biol. 2012;90:457–67. https://doi.org/10.1038/icb.2011.64. 159. Bedoui S, Herold MJ, Strasser A. Emerging connectivity of programmed cell death pathways and its physiological implications. Nat Rev Mol Cell Biol. 2020;21:678–95. Available from https://www.nature.com/articles/s41580-020-0270-8. 160. Aleyd E, Al M, Tuk CW, van der Laken CJ, van Egmond M. IgA complexes in plasma and synovial fluid of patients with rheumatoid arthritis induce neutrophil extracellular traps via FcαRI. J Immunol. 2016;197:4552–9. https://doi.org/10.4049/jimmunol.1502353. 161. Granger V, Peyneau M, Chollet-Martin S, de Chaisemartin L. Neutrophil extracellular traps in autoimmunity and allergy: immune complexes at work. Front Immunol. 2019;10:e02824. https://doi.org/10.3389/fimmu.2019.02824/full. 162. Foroutan B. Personalized medicine: a review with regard to biomarkers. J Bioequiv Availab. 2015;7:60613. Available from https://www.omicsonline.org/open-access/personalized- medicine-a-review-with-regard-to-biomarkers-jbb-1000248.php?aid=60613.
References
43
163. Lehner J, Wittwer C, Fersching D, Siegele B, Holdenrieder S, Stoetzer OJ. Methodological and preanalytical evaluation of an HMGB1 immunoassay. Anticancer Res. 2012;32:2059–62. Available from http://www.ncbi.nlm.nih.gov/pubmed/22593488. 164. Heizmann CW. S100B protein in clinical diagnostics: assay specificity. Clin Chem. 2004;50:249–51. Available from http://www.ncbi.nlm.nih.gov/pubmed/14709667. 165. Kutzner L, Rund KM, Ostermann AI, Hartung NM, Galano J-M, Balas L, et al. Development of an optimized LC-MS method for the detection of specialized pro-resolving mediators in biological samples. Front Pharmacol. 2019;10:169. Available from http://www.ncbi.nlm.nih. gov/pubmed/30899221. 166. Imming P, Sinning C, Meyer A. Drugs, their targets and the nature and number of drug targets. Nat Rev Drug Discov. 2006;5:821–34. Available from http://www.nature.com/articles/ nrd2132. 167. Davidson BL, McCray PB. Current prospects for RNA interference-based therapies. Nat Rev Genet. 2011;12:329–40. Available from http://www.nature.com/articles/nrg2968. 168. Gashaw I, Ellinghaus P, Sommer A, Asadullah K. What makes a good drug target? Drug Discov Today. 2012;17:24–30. Available from http://www.ncbi.nlm.nih.gov/pubmed/22155646. 169. Zheng CJ, Han LY, Yap CW, Ji ZL, Cao ZW, Chen YZ. Therapeutic targets: progress of their exploration and investigation of their characteristics. Pharmacol Rev. 2006;58:259–79. Available from: http://pharmrev.aspetjournals.org/cgi/doi/10.1124/pr.58.2.4 170. Land WG. Emerging role of innate immunity in organ transplantation part III: the quest for transplant tolerance via prevention of oxidative allograft injury and its consequences. Transplant Rev. 2012;26:88–102. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0955470X11000565. 171. Gruda MC, Ruggeberg K-G, O’Sullivan P, Guliashvili T, Scheirer AR, Golobish TD, et al. Broad adsorption of sepsis-related PAMP and DAMP molecules, mycotoxins, and cytokines from whole blood using CytoSorb® sorbent porous polymer beads. PLoS One. 2018;13:e0191676. Available from http://www.ncbi.nlm.nih.gov/pubmed/29370247. 172. Serhan CN. Treating inflammation and infection in the 21st century: new hints from decoding resolution mediators and mechanisms. FASEB J. 2017;31:1273–88. Available from http:// www.fasebj.org/doi/10.1096/fj.201601222R. 173. Dalli J. Does promoting resolution instead of inhibiting inflammation represent the new paradigm in treating infections? Mol Asp Med. 2017;58:12–20. Available from http://linkinghub. elsevier.com/retrieve/pii/S0098299717300213. 174. Schett G, Neurath MF. Resolution of chronic inflammatory disease: universal and tissue- specific concepts. Nat Commun. 2018;9:3261. Available from http://www.nature.com/ articles/s41467-018-05800-6. 175. Perez-Hernandez J, Chiurchiù V, Perruche S, You S. Regulation of T-cell immune responses by pro-resolving lipid mediators. Front Immunol. 2021;12:768133. Available from https:// www.frontiersin.org/articles/10.3389/fimmu.2021.768133/full. 176. Archambault A, Zaid Y, Rakotoarivelo V, Turcotte C, Doré É, Dubuc I, et al. High levels of eicosanoids and docosanoids in the lungs of intubated COVID-19 patients. FASEB J. 2021;35:540. https://doi.org/10.1096/fj.202100540R. 177. Schaller MS, Chen M, Colas RA, Sorrentino TA, Lazar AA, Grenon SM, et al. Treatment with a marine oil supplement alters lipid mediators and leukocyte phenotype in healthy patients and those with peripheral artery disease. J Am Heart Assoc. 2020;9:e016113. https:// doi.org/10.1161/JAHA.120.016113. 178. Desmet CJ, Ishii KJ. Nucleic acid sensing at the interface between innate and adaptive immunity in vaccination. Nat Rev Immunol. 2012;12:479–91. Available from http://www.nature. com/articles/nri3247. 179. He P, Zou Y, Hu Z. Advances in aluminum hydroxide-based adjuvant research and its mechanism. Hum Vaccin Immunother. 2015;11:477–88. Available from http://www.ncbi.nlm.nih. gov/pubmed/25692535.
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1 Perspectives of the Danger/Injury Model of Immunology as Applied…
180. Powell BS, Andrianov AK, Fusco PC. Polyionic vaccine adjuvants: another look at aluminum salts and polyelectrolytes. Clin Exp Vaccine Res. 2015;4:23. Available from http://www.ncbi. nlm.nih.gov/pubmed/25648619. 181. Marichal T, Ohata K, Bedoret D, Mesnil C, Sabatel C, Kobiyama K, et al. DNA released from dying host cells mediates aluminum adjuvant activity. Nat Med. 2011;17:996–1002. Available from http://www.nature.com/articles/nm.2403. 182. Hayashi T, Momota M, Kuroda E, Kusakabe T, Kobari S, Makisaka K, et al. DAMP-inducing adjuvant and PAMP adjuvants parallelly enhance protective type-2 and type-1 immune responses to influenza split vaccination. Front Immunol. 2018;9:2619. Available from http:// www.ncbi.nlm.nih.gov/pubmed/30515151. 183. Garg AD, Galluzzi L, Apetoh L, Baert T, Birge RB, Bravo-San Pedro JM, et al. Molecular and translational classifications of DAMPs in immunogenic cell death. Front Immunol. 2015;6:588. https://doi.org/10.3389/fimmu.2015.00588/abstract. 184. Garg AD, Dudek-Peric AM, Romano E, Agostinis P. Immunogenic cell death. Int J Dev Biol. 2015;59:131–40. Available from http://www.ncbi.nlm.nih.gov/pubmed/26374534. 185. Garg AD, Krysko DV, Vandenabeele P, Agostinis P. The emergence of phox-ER stress induced immunogenic apoptosis. Onco Targets Ther. 2012;1:786–8. Available from http:// www.ncbi.nlm.nih.gov/pubmed/22934283. 186. Venereau E, De Leo F, Mezzapelle R, Careccia G, Musco G, Bianchi ME. HMGB1 as biomarker and drug target. Pharmacol Res. 2016;111:534–44. Available from https://linkinghub. elsevier.com/retrieve/pii/S104366181630487X. 187. Andersson U, Yang H, Harris H. Extracellular HMGB1 as a therapeutic target in inflammatory diseases. Expert Opin Ther Targets. 2018;22:263–77. https://doi.org/10.1080/1472822 2.2018.1439924. 188. Lundbäck P, Lea JD, Sowinska A, Ottosson L, Fürst CM, Steen J, et al. A novel high mobility group box 1 neutralizing chimeric antibody attenuates drug-induced liver injury and postinjury inflammation in mice. Hepatology. 2016;64:1699–710. https://doi.org/10.1002/ hep.28736.
Part II Infections
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Infectious Agents: From the Red Queen Paradigm to Some of Their Genuine Traits
2.1 Introduction The intention of this second part of the book, “Infections,” is to describe the current state of the emerging role of DAMPs in the pathogenesis of infectious diseases. However, instead of presenting just dry and themata-related stuff about DAMPs in infectiology, we will first take the opportunity to decorate this traditional, extensive, and sometimes still enigmatic field of medicine with some narratives about the characteristics of infectious agents (generally called pathogens), on one hand, and principles of host immune responses against damage induced by them, on the other hand. In fact, it is the interaction between an infectious agent (i.e., its virulence program) and a host (i.e., its susceptibility attributes) that governs the pathogenesis of infectious diseases. Excitingly, this interaction between coevolving pathogens and their hosts is often interpreted as an evolutionary arms race between two organisms, both claiming the right to survive on our planet––a scenario that is aptly symbolized by the “Red Queen” Hypothesis. The first part of the chapter will be closed by briefly sketching the modern notions on the pathogenesis of infectious diseases in light of the danger/injury model in immunology––as it will be presented to the reader in the following chapters in more detail. The second part of the chapter reflects the transition from some theme-related conceptual considerations to the realistic world of pathogens by describing some of their genuine characteristics, which may also contribute to a better understanding of the pathogenetic role of damage-associated molecular patterns (DAMPs) in these diseases. Indeed, understanding which characteristics of an infectious agent contribute most to disease is a major area of research in microbiology and infection biology. Accordingly, this section will focus on some traits of infectious agents that are typical for a genus, such as structure and reproduction mechanisms. The most important features, however, are the damaging virulence
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 W. G. Land, Damage-Associated Molecular Patterns in Human Diseases, https://doi.org/10.1007/978-3-031-21776-0_2
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factors because they provoke emission of DAMPs in the host. For this reason, they are described separately in Chap. 3, together with the presentation of counteracting host stress responses and with respect to their ability to induce host cell death. Here, however, a brief introduction to the classification and identification of infectious agents will wrap up this topic.
2.2 To Start with Some Infection Enigmas The vast field of infections and infectious diseases was always and still is surrounded by enigmas. For example, the observation that some nonpathogenic microbes (e.g., commensals) compose useful and beneficial microbiomes while other pathogenic microbes can cause severe diseases was mechanistically an unsolved problem for a long time and is still not completely elucidated today (for the microbiome, also see Vol. 1 [1], Chap. 34, pp. 829–835, for a recent topic- related review, see [2]). Also, the knowledge about the great diversity of infectious diseases caused by different pathogenic infectious agents––though partially and approximatively explained by different virulence programs of the various agents–– awaits complete mechanistic clarification. Finally, the interindividual variability of the clinical manifestation of an infection caused by one and the same bacterium or virus––reflecting a different susceptibility of individuals to infection––is challenging to understand. For example, in the recent SARS-CoV-2-induced COVID-19 pandemic, as in every epidemic, one can observe that some positively tested individuals remain asymptomatic, some become more or less sick but stay at home, some require urgent hospitalization, and some of them die there despite intensive medical care and therapy. In fact, for almost all human-tropic infectious agents, the clinical outcome of primary infection varies enormously, as said, from asymptomatic infection to fatal infectious disease. Moreover, on top of this, the various clinical outcomes of an infection are unexplained in most cases. As an explanation for these puzzling observations, the idea was slowly developed and accepted that two momenta essentially govern the pathogenesis of infection: (1) the different interaction between the infectious agent and the host that determines those various outcomes, and (2) this interaction mirrors the continuously evolving battle between the infecting agent and the human host. These insights have naturally aroused interdisciplinary interests. Accordingly, for a long time, infectiologists have tried to solve these enigmas by exploring infectious agents’ characteristics, while immunologists explored the immune responses of a host against these pathogenic foreign invaders intensively. The two groups were joined by geneticists who studied the genetically determined host susceptibility to infection. More recently, DAMPs researchers have entered the scene and contributed to the understanding of induction mechanisms involved in both strong immune defense responses against pathogens and pathological disorders caused by them. During the past decade, interdisciplinary efforts have brought a burst of insights into the molecular mechanisms of innate immune responses of the host to bacterial and viral pathogens. In parallel, multiple specific mechanisms by which microorganisms subvert these host responses have been
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uncovered. It is this phenomenal scenario of pathogen ↔ host interaction that will guide us through the following sections.
2.3 Pathogenetic Actions on the Side of the Infectious Agent: The Capacity of a Pathogen to Induce DAMPs in the Host as a Conceptual Definition of Virulence 2.3.1 Pathogenicity and Virulence in Light of Major Paradigms in Microbiology and Immunology The pathogenetic action of infectious agents (= pathogenicity) is generally attributed to the phenomenon of virulence. Notably, however, the term virulence, as used in infectiology, has different meanings depending on context and, thus, attempts to define “virulence of infections agents” have been difficult and complicated [3, 4]. Historically, in earlier times, microbiologists considered virulence in the context of pathogenicity to be primarily pathogen oriented, assuming that these characteristics are purely intrinsic properties of microorganisms, which cause an infection and finally determine––via pathogenetic pathways––its outcome. The classical highlight of this concept refers to Koch’s postulates for the definition of microbial pathogens, which placed the entire responsibility for the pathogenesis of an infection on the microbe. (The postulates were partly derived from earlier concepts of Jacob Henle (Koch’s teacher), who had previously proposed microbes as the cause of infectious diseases.) Koch’s paradigmatic fulfillment of the postulates for tuberculosis is outlined in an article published in Berliner klinische Wochenschrift, 1882, where he concluded [5]: “Alle diese Tatsachen zusammengenommen berechtigen zu dem Ausspruch, daß die in den tuberkulösen Substanzen vorkommenden Bazillen nicht nur Begleiter des tuberkulösen Prozesses, sondern die Ursache desselben sind, und daß wir in den Bazillen das eigentliche Tuberkelvirus vor uns haben.” (translated by Kaufmann and Schaible in [6]: “All these factors together allow me to conclude that the bacilli present in the tuberculous lesions do not only accompany tuberculosis but rather cause it. These bacilli are the true agents of tuberculosis.”). With the emerging field of Immunology, more host-oriented views were developed to explain the origin, nature, and strength of infections. However, seen as a too rigid concept, this idea was also questioned. Thus, over time, the notion gained acceptance that infection and its outcome are not only determined by the virulence of a microbe nor originated purely by the host but rather the result of a complex interaction between the microbe and the host. Indeed, microbiologists now understood that the clinical course of a disease depends on the interaction of a given microbe’s virulence factors with the host's response, in particular, immune response. Historically, the modern concept of host immune responses to microbes evolved on the basis of the three paradigms in Immunology, which were already cursorily mentioned in the context of costimulation in the previous chapter (for details of the three paradigms and related references, see Vol. 1 [1], Chap. 2, incl. Fig. 2.1, pp. 13–28).
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Fig. 2.1 The Red Queen hypothesis proposed by Van Valen [7] to explain the scenario of an evolutionary arms race between two species: despite continued evolution and adaptations, none of the interacting species (here the pathogens and their mammalian hosts) gain a sustained fitness advance––their fitness remains constant and unchanged: evolution is a zero-sum game. The scenario has been analogized by Van Valen to the character of the Red Queen in Lewis Carroll’s [8] “Through the Looking Glass,” who said: “…it takes all the running you can do, to keep in the same place…” (Sources: [7, 8], drawing from Sir John Tenniel [1820–1914])
2.3.2 Concepts of Pathogenicity and Virulence as a Consequence of Infectious Agent-Induced Damage to Host Cells: A Unifying Approach? Remarkably, only 1 year later, following the publication of the danger/injury model, the concept of host–pathogen interaction in the context of the requirement of cell damage for pathogenicity was insinuated by Hibbs et al. [9] in an article on viruses, virulence, and pathogenicity, published in 1995. In the summary of the article, the authors concluded that “Pathogenicity is a complex process with stringent requirements of both the host cell and the infecting virion. Among these requirements are a port of entry into host cells, a means of replication for the virus, and a means by which infection damages host cells. Damage to the host can result from multiple mechanisms, including transformation, suppression of cellular metabolism, apoptosis, autoimmune responses directed against infected or uninfected tissues, or by molecular mimicry. In the attempt to identify new associations between viral infection and disease, investigators should be mindful that variable host factors, as well as viral infection, may be required for pathogenesis. Efforts to associate specific viral infections with specific diseases may be obscured by final common pathways
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through which multiple agents damage host cells in similar ways.” Subsequently, the concept of host ↔ pathogen interaction was redefined by Casadevall and Pirofski [10–13], who proposed and described the Damage–Response Framework (1999–2003), a groundbreaking concept that is very similar to the danger/injury model. It holds that virulence can be defined as “the relative capacity of a microorganism to cause damage in a host” [10]. As later concluded by the authors [12], The damage–response framework is based on three tenets that are both self-evident and incontrovertible: (1) microbial pathogenesis is the outcome of the interaction between two entities, namely a host and a microbe; (2) the relevant outcome of host- microbe interaction in a given host is damage in the host and (3) host damage can reflect the action of microbial factors, the host response, or both. And further, The focus of the damage–response framework on host damage provides a new set of definitions that permit a different approach to the problem of virulence and, by extension, to virulence factors. In the damage–response framework, a pathogen is a microbe capable of causing host damage, virulence is the relative capacity of a microbe to cause damage in a susceptible host and a virulence factor is a microbial component that can damage a susceptible host. At least from the perspective of this book, the action of DAMPs is currently setting up the point of closure of this exciting (hi)story. On one hand, these molecules are generated upon pathogen-induced injury in the infected host and, on the other hand, govern and orchestrate the nature and the extent of subsequent innate immune (inflammatory)/adaptive immune responses. In other words, the degree of generated and emitted DAMPs inflicted during infection is directly proportional to the pathogen’s virulence. Indeed, apart from mirroring the pathogenetically significant host ↔ pathogen interaction, the measurement of quality and quantity of these molecules as phenotypic biomarkers would allow assessing the virulence of a given infectious agent rather precisely. Moreover, this policy would allow refraining from the performance of experimental assay systems, ranging from in vitro growth assays to tissue culture and animal infection models, as well as conduction of human volunteer studies. And interestingly, in terms of a similar argumentation, already in 1999, Casadevall and Pirofski [10] concluded that existing concepts of virulence and pathogenicity are inadequate because they do not account for the full complexity of microbial pathogenesis in hosts with and without impaired immunity. Thus, the authors proposed that host-pathogen interactions can be analyzed using host damage as the common denominator for characterizing microbial pathogenicity and can provide a conceptual framework for incorporating the importance of the host response into the outcome of the host-microbe interaction….
2.3.3 The Role of Virulence Factors: Serving the Fitness of Pathogens but, Simultaneously, Evoking DAMP-Promoted Host Defense Responses Notably, the issue of virulence is intrinsically linked to the concept of virulence factors in terms of specific determinants of pathogenicity. However, the definition of
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what constitutes a virulence factor is not limited to the proposal that it causes damage but is challenging, varied, and controversially discussed in the literature (e.g., see [14]). And to cite Casadevall and Pirofski again [12], The microbial attributes that confer the potential for virulence fall primarily within several categories, including the ability to enter a host; the ability to evade host defenses; the ability to grow in a host environment; the ability to counteract host immune responses; the ability to acquire iron and nutrients from the environment and the ability to sense environmental change. In other words, virulence factors, as seen from infectious agents’ viewpoints, primarily evolved to serve their survival and reproduction in a host. If these virulence factors do not do any harm and thus do not evoke innate immune responses, microbes may behave as commensals, establish a microbiota, and thus have fulfilled the infectious agent’s intention. However, if they damage, microbes act as pathogens to elicit DAMP-promoted innate immune/inflammatory and adaptive immune defense responses, which may lead to their elimination when efficient and robust enough (what happens mostly)––or may successfully be counteracted and evaded by the pathogen. Such surviving mechanisms of pathogens include, for example, the ability to blunt host defenses via capsules [15] or inhibit innate immune responses by injection of effector proteins [16, 17] (for capsules and injected effector proteins acting as virulence factors, see next chapter, Sects. 3.2.2.4 and 3.2.3.4). Hence, in the context of the danger/injury model, the topic of infectious agent- caused pathogenicity should be addressed by focusing on those damaging virulence factors that operate at the beginning of the pathogenesis of infectious diseases. They can be roughly divided into three categories: (1) nondamaging virulence factors such as adhesins that, however, pave the way to induce cell stress and tissue injury finally; (2) indirectly damaging bacterial virulence factors such as siderophores; and (3) directly damaging bacterial virulence factors that cause real stress and damage to the host's cells and tissues (detailed in next chapter). Speaking in the language of the danger/injury model: Virulence factors are factors that, in a graduated manner according to their nature, quality, and quantity, provoke generation and emission of various subclasses of DAMPs. At this place, however, an important point should already be added that was already insinuated by Hibbs et al. [9]: Among the category of damaging virulence factors, one must even include intracellular perturbating mechanisms caused by intracellular infectious agents (viruses, intracellular bacteria), such as cell invasion, intracellular migration/trafficking, and replication maneuvers. These molecular scenarios cause cellular stress, such as cytoskeletal dysfunction associated with perturbations of cellular molecules, that is, processes that are characterized by the generation of dysDAMPs. As mentioned previously, these DAMPs induce various stress responses that, when unsuccessful, can result in subroutines of regulated cell death (RCD). Doubtlessly, in this scenario, the most severely damaging virulence factors refer to bacterial toxins, viral viroporins, and fungal mycotoxins. To cope with these inciting, possibly life-threatening insults and restore cellular homeostasis, the infected host cell at first reacts with an above-mentioned defensive stress response.
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However, when the toxin-mediated perturbations of the intracellular and extracellular microenvironment are too intense or prolonged, that is, when severe cellular damage occurs, the host cells are “forced to decide” to initiate pathways resulting in various subroutines of RCD. In other words, when defense against infectious agents at the cellular level fails, the infected/stressed cell has no other chance than to commit suicide in the form of an RCD that can be considered the culmination of innate host defense mechanisms. This event is then associated with emission of large amounts of DAMPs that directly operate at the whole organism's level, aimed at restoring organismal homeostasis. (Spoken in metaphor: The host cell argues, “if I have no chance to survive, then at least the organism that I derive from should survive”). Indeed, RCD of infected cells functions as perhaps the most ancient firewall against fatal injury caused by pathogens by limiting their replication and dissemination. This most effective defense weapon out of the host’s arsenal of innate immune defensive tools operating in the battle against invading pathogens is discussed in detail in Chap. 3 (for stress responses, see Vol. 1 [1], Chaps. 17 and 18, pp. 373–412, and Vol. 2 [18], Chap. 4, pp. 117–140; for the description of the classification of DAMPs in this book, see above Tables 1.1–1.3, also Vol. 1 [1], Chaps. 11–15, pp. 191–364 and Vol. 2 [18], Chap. 3, pp. 67–102).
2.3.4 Some Thoughts on the Evolutionary Role of DAMPs and Innate Immune Recognition Receptors Theodor Dobzhansky wrote that nothing in biology makes sense except in the light of evolution [19], and this may also be true for the evolution of virulence factors on the pathogen side and the evolutionary development of DAMPs on the side of their hosts. Thus, the damaging virulence factors that intentionally serve the infectious agents to replicate, survive, and disseminate in the host simultaneously evoke the emission of DAMPs, which in turn boost host immune defense responses aimed at killing the pathogens. In light of evolution, this conclusion may also be turned around: In early evolution, there was at first the generation and emission of DAMPs upon infectious injury to initiate and orchestrate a host immune defense response to the injury-causing pathogens. And although evidence has been provided suggesting that injuries derived from the hostile pathogenic environment are the predominant driver of local adaptation in humans [20], the conceptual thread can be spun further: generation and emission of DAMPs upon any injury, including sterile environmental injuries evolved to initiate and orchestrate a host immune defense response. Such a discussion raises the question as to what role DAMPs play during the evolution of our immune defense system. And what came the first––generation of DAMPs upon infectious or sterile injury? Or did DAMPs evolve from the very beginning against any injury, regardless of whether infectious or sterile? Notwithstanding, a paradigmatic example of DAMPs evolutionarily involved in host immune defense responses is the heat shock proteins (HSPs). These very ancient and evolutionary, highly conserved DAMPs have been identified in virtually all metazoan taxa and are known to be among the key players in host defense for
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billions of years. The HSPs have been shown to be rapidly upregulated by microbial and viral infections––and various other perturbations and stress challenges––to initiate innate/adaptive immune responses (for further reading, see [21–24]). Also, as another example, evidence suggests that the canonical HMGB proteins are present in multicellular animals, from sponges onwards, and appear to have arisen through the fusion of two different genes, each coding for one of the boxes. Moreover, the organization of HMGB genes was reportedly very conserved during Metazoan evolution, with the only deviations appearing in Caenorhabditis and Dipteran (Drosophila and Anopheles) species [25]. Also, the action of the DAMPs in plant innate immune responses underlines their role as evolutionarily highly conserved molecules in host defense [26, 27]. On the other hand, innate pattern recognition molecules (PRMs) that sense DAMPs are also evolutionarily highly conserved. For example, canonical Toll-like receptors (TLRs), regarded as the most ancient innate immune receptors across a wide range of invertebrate and vertebrate species, have already been detected within the phylum of Cnidaria, Toll-like molecules even earlier in Porifera (reviewed in [28–30]). Of note, as concluded by Leulier and Lemaitre [28], these observations point to an origin of TLRs in the eumetazoan ancestor more than 600 million years ago––before the separation of bilaterians and cnidarians. Certainly, in the context of the topic discussed here, one might discuss the possibility that infectious or sterile stress/injury conditions are the driving force of TLR evolution. And interestingly enough, this topic is also discussed in the literature. For example, Nie et al. [30] argued: “We believe that stress may be one of the main driving forces in the development of TLRs. The stress conditions, especially challenges to the immune system, such as pathogen, temperature, salinity, and prolonged desiccation, are highly variable and change rapidly. As mentioned …, the pathogen stress may play positive selection roles during TLR evolution.” In line with such considerations are other recently performed studies, including comparative evolutionary analyses of pattern recognition receptor (PRR)-related genes from mammals, which provided convincing evidence for PRRs to be under particularly high evolutionary selection pressure from a wide diversity of coevolving pathogens. Indeed, the extensive positive selection of PRRs across the mammalian phylogeny suggests an enhancement of their host’s defense capacity against invading pathogens during mammalian evolution [31, 32].
2.3.5 The Red Queen Paradigm The role of virulence factors in serving the fitness of pathogens but simultaneously evoking host DAMP-promoted, PRM-mediated defense responses undoubtedly reflects the scenario of an evolutionary arms race between coevolving pathogens and their hosts. And at this point, the Red Queen Hypothesis comes into play, which was proposed by Leigh Van Valen [7] after the character in Lewis Carroll’s novel “Through the Looking-Glass” [8]. In this novel, the Red Queen speaks to Alice, Now, here, you see, it takes all the running you can do, to keep in the same place. If
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you want to get somewhere else, you must run at least twice as fast as that! (Fig. 2.1). The words reflect the need for species to continually evolve in the face of lifethreatening biotic insults derived from competing organisms (e.g., bacteria, viruses, fungi, parasites, predators), yet on average, their fitness remains unchanged. Thus, the key principle of the Red Queen dynamics is that organisms must continually adapt to survive and reproduce in the face of continually evolving opposing counteradapting organisms (for further reading, see [33, 34]). The Red Queen hypothesis also applies to host ↔ pathogen interactions as briefly touched on above: as hosts, such as humans––being under constant selective pressure to resist pathogens––evolve innate/adaptive immune defense responses against infections, infectious agents must evolve counteracting virulence factors to overcome those defensive processes and achieve successful infection (also see [31, 35]). In light of the danger/injury theory, a speculative and tentative model can be sketched for an evolutionary arms race between pathogens (evolving virulence factors to invade and infect a host to survive and replicate) and the host (evolving DAMPs and DAMP-mediated defense responses to overcome the infection): The more potent and thus life threatening the damage induced by the pathogen's virulence factor, the stronger the emission of DAMPs, and the more robust is the immune defense response triggered by DAMPs. The culmination of DAMPs emission in this scenario can be seen in the event of RCD, as also elegantly discussed by Lacey and Miao [35]. And further, one may discuss whether such an escalation in the competing host DAMPs and pathogen virulence factors is a consequence of selection. Typically, pathogens are able to keep up in the evolutionary race with DAMP- induced promoting and resolving innate/adaptive immune responses but usually lose this race within one week (clinically manifest as mild/moderate infection followed by full resolution)––but not before the pathogen transmits to a new host. However, one has to admit here that sometimes, for example, when a new pandemics such as COVID-19 threatens mankind, the therapeutic application of DAMPs is necessary to let the pathogen (here the virus) not win the race. In the case of COVID-19, the LNP/in vitro modified mRNA vaccine was and still is successfully used: both operating as exogenous DAMPs, whereby the mRNA encodes the viral antigen.
2.4 Pathogenetic Actions on the Side of the Host: Quality and Quantity of Innate/Adaptive Immune Defense Responses to Infectious Agent-Induced Damage Susceptibility to a given infection does not only depend on the virulence factors of the pathogen but also on the status of the host’s existing defense mechanisms. Attributes of individual susceptibility have been exhaustively described by Casadevall and Pirofsky [36] and include critical phenotypes, such as immunity and environment, as well as genetics and epigenetics. Doubtlessly, an effectively functioning innate/adaptive immune system of the host is essential for a successful defense against pathogens. This unshakeable fact,
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well known not only to professionals but also to the public, implies that a defective or functionally impaired system increases the individual susceptibility to many infectious diseases. This rationale was first formally recognized in immunocompromised patients with the emergence of opportunistic infections [37], which sometimes manifest as severe life-threatening diseases––as I have personally experienced (as a former transplant surgeon) in immunosuppressed organ recipients. For example, fungal pneumonia, often diagnosed in immunocompromised patients [38], is considerably feared by physicians. Since immune defense responses to pathogenic invaders are dealt with in Chap. 4, the topic is not pursued further here. The environment's attribute includes all conditions that may influence host ↔ pathogen interaction, such as climate changes and the presence of environmental toxins (reviewed in [39, 40]). A good example is epidemics that are caused by viruses, such as SARS-CoV and the newly emerging SARS-CoV-2, which preferentially occur during the winter months. Indeed, as reviewed [41], the major contributing factor (besides human behavior) to respiratory virus outbreaks are the changes in environmental parameters. In this context of considerable interest are observations from a study on adult New York State residents revealing that increased concentrations of fine PM air pollution of 2.5 mm or less in diameter (denoted as exogenous DAMPs in this book, see Table 1.3) are associated with increased rates of respiratory infections, including influenza [42]. Even of intriguing interest are earlier reports of Chinese groups on a possible link between environmental factors and SARS case fatality [43–45]. Studying the genetic factors of susceptibility to infectious diseases has become a fundamental issue for our understanding of infections’ pathogenesis and its clinical variability between individuals infected with the same pathogen. In fact, the idea that infectious diseases have a strong host genetic component dates back to the start of the twentieth century. At that time, classical genetics studies were performed; for example, twin studies showed that concordance for some infectious diseases is much greater for monozygotic than for dizygotic twins. Other studies provided strong evidence for the host genetic make-up to be an additional mechanism contributing to interindividual variability in response to primary infection. In addition, and of note, there is also accumulating evidence suggesting a strong effect of germline genetic variation on innate and adaptive immune responses to infection (for reviews, see Casanova and Casanova and Abel [46–49], as well as Nashef et al. [50] and Mozzi et al. [51]). Indeed, immunopolymorphism is considered an essential aspect behind the host’s resistance or susceptibility to an infectious disease. For example, in a recent review by Mukherjee et al. [52] on polymorphic residues in TLRs shaping immunity to pathogenic infections, the authors presented as the major influential single nucleotide polymorphisms (SNPs) I602S (TLR1), R677W (TLR2), P554S (TLR3), D299G (TLR4), F616L (TLR5), S249P (TLR6), Q11L (TLR7), M1V (TLR8), G1174A (TLR9), and G1031T (TLR10). However, according to the authors’ conclusion, the contribution of these SNPs in the structure–function relationship of TLRs is not yet clear. While the important role of genetics in host susceptibility to infections has been known for decades, studies on epigenetics that may influence host susceptibility
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have only recently been started. Thus, accumulating evidence suggests that, in viral infections, epigenetic-sensitive mechanisms, including DNA methylation, histone tail modifications, and noncoding RNA (ncRNA), may lead to perturbations of the host immune-related transcriptional programs by regulating chromatin structure and gene expression patterns. Similarly, in bacterial infections, the interaction of multidrug-resistant bacteria with host cells can guide molecular perturbations of host transcriptional programs and noncoding RNAs leading to pathogen survival (for details, see Crimi et al. [53, 54]; for epigenetic control of immunity and inflammation, see also [55, 56]; and Vol. 1 [1], Sect. 24.2, pp. 636–646, and Vol. 2 [18], Sect. 5.6, pp. 169–194). Of note, an emerging variant of epigenetic regulation of infection is the phenomenon of trained immunity, de facto, an innate immune memory. The concept was developed by the Radboud University group around Netea [57–61]. The topic that has already been addressed in Vol. 1 [1], Sect. 24.2.4, pp. 642-645; and Vol. 2 [18], Sect. 3.7, pp. 100/101, and Sect. 5.6.2.3, pp. 174–175. The model holds that cells of the innate immune system can establish a memory of past stimulation via a process of metabolic and epigenetic reprogramming that allows modifying their response upon secondary challenges with an infectious insult similar or unrelated to the first one. This process results in enhanced cytokine production and provides more effective protection against reinfection.
2.5 The Pathogenesis of Infectious Diseases: A Brief Synopsis Ahead 2.5.1 Introductory Remarks There is a wealth of literature about the pathogenesis of infectious diseases that is conceptually characterized by transmission of the infectious agent, portal of entry into the body, routes of spreading within the body, targeting organs or cells, and mechanisms of inducing damage to the cells, tissues, and organs. In this part “Infections” of the book, an attempt is made to explore and understand the role of infection-induced DAMPs as the main players in the pathogenetic mechanisms that characterize these disorders. To prepare the reader for this new field of infection research––and as a concise guide for the following chapters––a brief synopsis of this topic is given here, which will be covered in depth in the following chapters.
2.5.2 The Early Begin of the Disease: Recognition of Pathogens and the Harm They Induce The process of infection begins with the transmission of an infectious agent (e.g., direct/indirect contact, blood borne, air borne) that is associated with contact, attachment, and contamination to a surface, followed by an invasion of host cells and tissues. Local defense mechanisms may ward off the potential pathogen before
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it can induce any cell stress or tissue injury, a scenario that may correspond with the term “asymptomatic infection.” The invasion by these pathogens of the host then fulfills the criterium of infection, whereby the invaders replicate and propagate in close association with the host’s tissues. Pathogenetically, an infectious disease begins with the recognition by the host’s innate immune system of both the pathogens and the cell stress/tissue injury caused by them. More precisely, the pathogens are sensed by germline-encoded PRMs located on or in cells of the innate immune system. These sensors recognize distinct conserved molecular structures derived from the pathogens, the PAMPs [62], that is, molecules that are vital for the life cycle of the pathogen. The history and discovery of these molecules are described in more detail in [63, 64]. Of note, however, since nonpathogenic invaders do not cause harm but express those conserved molecules as well, the term microbe-associated molecular patterns (MAMPs) was introduced later on. Almost in parallel with the detection of MAMPs, recognition of DAMPs occurs, which are generated and emitted as a result of pathogen-induced cell and tissue damage. Like MAMPs, the DAMPs are also sensed by a large variety of PRMs (a property that has led to denoting them as “promiscuous” recognition receptors). The nature and intensity of such “infectious” cell stress/tissue injury depend on the virulent factors of the pathogen concerned, mainly, however, on the injurious factors (touched on above and detailed below and in the next chapter). In turn, the nature and the intensity of the innate immune defense response of the host against pathogen- induced “infectious” harm are thought to depend on several factors, including (1) the generation, nature, amount, and emission of DAMPs that originates from the pathogen-induced stress/injury; (2) the genetically determined susceptibility of the host, including immunopolymorphisms; and (3) other host attributes (e.g., age, temperature, pathogen inoculum).
2.5.3 Infectious Diseases as Clinical Manifestation of the Innate Immune Defense Program of the Host Against the Pathogenic Invaders As outlined above, the emergence of infection reflects a continuously evolving battle between the infecting agent and the human host. While infectious agents, such as viruses and bacteria, evolve primarily to survive and reproduce in a host and not to cause disease, it is the MAMP/DAMP-elicited inflammatory/immune defense response of the host against stress and damage they provoke that ultimately causes the disorder. In other words, infectious diseases are a clinical manifestation of the innate immune defense responses of the host against infectious agents. This defense program––already partially touched on above––includes (Fig. 2.2) 1. generation of constitutive DAMPs upon pathogen-caused primary RCD; 2. dysDAMP-promoted cell-intrinsic stress responses, such as autophagy, the endoplasmic reticulum (ER) stress-triggered UPR, and the DNA damage
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Fig. 2.2 Graphical synopsis of the DAMP-orchestrated defense program of the host to pathogens as the pathogenetic basis of infectious diseases. Various defense pathways that will be described in the following chapters are sketched: (I) generation of constitutive DAMPs upon pathogen-induced primary RCD; (II) cell-intrinsic stress responses upon pathogen-caused cell insults that, when failed to save the cell, can result in RCD; (III) MAMP/ DAMP- or DAMP-triggered, PRM- mediated signaling pathways that lead to production of cytokines and other inflammatory mediator substances, resulting in a robust proinflammatory innate immune response; (IV) induction of PRM-triggered cell death pathways leading to RCD; (V) production of inducible DAMPs (e.g., type I IFN, TNF) secreted by activated innate immune cells promoting induction of RCD (e.g., necroptosis, pyroptosis). Occurrence of variously induced subroutines of RCD is notoriously associated with emission of constitutive DAMPs. DAMPs damage-associated molecular patterns, ER endoplasmic reticulum, IFN interferon, MAMPs microbe-associated molecular patterns, NLRP3 nucleotide binding and oligomerization domain (NOD, “NACHT”)-leucine-rich repeat (LRR) receptor (NLR)—family, pyrin domain (PYD)-containing 3, RCD regulated cell death, TNF tumor necrosis factor, UPR unfolded protein response, ZBP1 Z-DNA-binding protein 1. (Sources: [1, 18, 65–68])
response (DDR) (covered in Vol. 1 [1], Chap. 17/18, pp. 373–412; and Vol. 2 [18], Sects. 4.2.1–4.2.7, pp. 117–127); 3. MAMP/DAMP- or DAMP-triggered, PRM-mediated signaling pathways that lead to production of cytokines and other inflammatory mediator substances, resulting in a proinflammatory innate immune response (compare Vol. 1 [1], Sects. 22.2–22.5, pp. 485–556); and Vol. 2 [18], Chap. 2, pp. 13–49); and 4. induction of secondary RCD, particularly regulated necrosis (RN), aimed at preserving organismal homeostasis by using two simultaneously operating mechanisms: first, elimination of unwanted dangerous cells such as infected cells, and second, the release of constitutive DAMPs, which are capable of promoting lifesaving immune defense responses against infectious/sterile injuries. In principle, there are three mechanisms with which a host cell commits suicidal RCD to combat infections, via (1) unsuccessful stress responses that fail to restore cellular homeostasis [65]; (2) induction of cell death pathways triggered by PRMs [66, 67]; and (3) production of cytokines (denoted as inducible DAMPs, such as
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tumor necrosis factor (TNF) and interferons IFNs) secreted by MAMPs/DAMPsactivated, PRM-bearing cells [68] (Fig. 2.2). Of note, RCD represents an umbrella term that includes several subroutines of cell death, which will be described in detail in the following chapter. Together, when looking at this scenario, it becomes obvious that it is the DAMPs that dominate the pathogenesis of infectious diseases by driving innate immune inflammatory and cell death effector pathways as well as––via activation of PRM-expressing dendritic cells (DCs)––shaping a specific, anti-pathogen adaptive immune response.
2.5.4 Model Integration of DAMPs and SAMPs in Regulated and Dysregulated Inflammatory Defense Responses Determining the Pattern of Infectious Diseases Today, when discussing the function of DAMPs in infectious inflammation, one must mention in one breath the modern concept of inflammation as a two-phase, self-limited, protective innate immune defense response of the host (described in Vol. 1 [1], Sect. 22.2, pp. 476–484; and Vol. 2 [18], Chap. 5, pp. 151–194). The sequelae of this defense process consist of both strictly controlled inflammation- initiating/promoting responses, governed by activating DAMPs, and tightly regulated inflammation-resolving responses, driven by counterbalancing SAMPs (Fig. 2.3; also see Fig. 2.4). These processes are fortified by DAMP-shaped specific adaptive immune responses against the pathogen concerned. Accordingly, a conceptual model of a controlled innate/adaptive immune defense response can be proposed encompassing an initiating DAMP-promoted proinflammatory crescendo → decrescendo that proceeds––slightly shifted but nearly in parallel––to a SAMP- driven proresolving “reversed” crescendo → decrescendo, resulting in restitutio ad integrum (Fig. 2.4). However, under uncontrolled and dysregulated infection conditions, for example, when DAMPs are emitted in excess or over a prolonged period of time, or when the production of counterbalancing SAMPs is suboptimal, the DAMPtriggered, PRM-mediated responses can result in severe pathologies such as the development of chronic nonresolving inflammation or local and systemic hyperinflammation. Typically, this DAMP-induced hyperinflammatory response may proceed to a long-lasting mirror-imaged counterbalancing hyperresolution response that––following this conceptual model––is induced by production of SAMPs in excess (Fig. 2.5). These various types of DAMP/SAMP-driven, regulated, and dysregulated defense responses can translate into different disease outcomes in patients diagnosed by physicians as asymptomatic, mild/moderate, severe, or life-threatening/ fatal courses. With respect to nature and strength, they can be divided into • an inapparent/subclinical infection (e.g., in case of a controlled MAMP/DAMP- promoted memory immune response [in terms of “trained immunity”]);
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Infectious/sterile cell/tissue injury
DAMPs PRMs Proinflammatory cells e.g., M1-like macrophages, N1 PMNs
PRMs Phenotype switch
Proresolving cells e.g., M2-like macrophages, N2 PMNs
(DAMP - driven?) epigenetic modifications
Inducible DAMPs Promotion of inflammation
SAMPs Resolution of inflammation
Fig. 2.3 Schematic conceptual model of injury-induced inflammation that is regulated by DAMP- triggered proinflammatory and SAMP-driven counterbalancing proresolving responses aimed at returning to homeostasis. Increasing evidence suggests that DAMPs do not only activate PRM- bearing innate immune cells, such as M1-like macrophages and N1 neutrophils to promote inflammation, but also modulate activated innate immune cells to change their phenotype to inflammation-resolving traits. These transdifferentiated PRM-bearing cells, such as M2-like macrophages and N2 neutrophils, possess proresolving properties, including production of SAMPs, which in turn produce further SAMPs. Epigenetic modifications occurring during cell activation by various environmental stimuli (and triggered by DAMPs?) drive this phenotype switch. DAMPs damage-associated molecular patterns, PMNs polymorphonuclear leukocytes, PRMs pattern recognition molecules, SAMPs suppressing DAMPs. (Source: identical to Fig. 1.2, p. 7, Vol. 2 [18])
• a transient acute inflammatory disease characterized by a controlled DAMP- driven proinflammatory response followed by a controlled SAMP-promoted inflammation-resolving response. These processes are paralleled by a controlled MAMP/DAMP/SAMP-shaped specific adaptive immune response leading to the elimination of the pathogen (e.g., clinically familiar as the common cold); • a chronic nonresolving inflammatory disease (in terms of a dysregulated ongoing MAMP/DAMP-promoted inflammatory/immune response with persistence of the pathogen); or • a hyperacute hyperinflammatory disease (e.g., SIRS) associated with MOF, in terms of a dysregulated exaggerated (MAMP)/DAMP-promoted hyperinflammatory response. Typically, this clinical picture of SIRS is accompanied by an inflammation-hyperresolving response (e.g., manifested as a counterbalancing CARS (in terms of a dysregulated SAMP-driven hyperresolving response), resulting in a state of immunosuppression. Which of these clinical manifestations pathogenetically develops depends on the constellation of the given host ↔ pathogen interaction. As a multifactorial process, this interplay is mainly determined by the nature and the strength of the host’s
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Sterile/infectious insults
DAMP-promoted proinflammatory program
e.g., Recruitment and activation of neutrophils; prn, induction of TH1/TH17 cells
Antiinflammatory events: e.g., stop of neutrophil recruitment
Restitutio ad integrum
DAMP-activated PRM-bearing cells
homeostasis SAMP-promoted proresolving program e.g., Efferocytosis/phagocytosis; differentiation of M2-like MØ; prn, induction of Tregs
Fig. 2.4 Schematic diagram of a conceptual model illustrating an injury-induced controlled homeostatic inflammatory response leading to restitutio ad integrum. The initiating DAMP- promoted proinflammatory crescendo → decrescendo proceeds––slightly shifted but nearly in parallel––to a SAMP-promoted proresolving “reversed” crescendo → decrescendo. The short delay of the beginning of the proresolving response (estimated about 3–6 h post-trauma) may be explained by the fact that SAMPs, in terms of inducible suppressing DAMPs, are secreted by DAMP- activated innate immune cells. DAMPs damage-associated molecular patterns, MØ macrophages, nrp pro re nata, PRM pattern recognition molecule, Tregs T regulatory cells, Th1/17 cells T helper cells type 1/17. (Source: identical to Fig. 5.1, p. 152, Vol. 2 [18])
orchestrated immune defense response. But other factors count as well, including the complex virulence program executed by pathogens, on one hand, and host genetic-driven susceptibility and resistance, on the other hand.
2.5.5 Résumé Certainly, from the perspective of the danger/injury model in Immunology, the topic of the Red Queen paradigm in relation to host ↔ pathogen interaction and its impact on the pathogenesis of infectious diseases is a burning research field. In fact, the intense study of coevolution of the generation of DAMPs in mammals and virulence factors in pathogens is of high interest. However, evolutionary biologists tend to work at the population levels, whereas microbiologists, virologists, and immunologists tend to work at the molecular and cellular levels. Also, the research field on DAMPs is just at the beginning but is increasingly flourishing. Together, a more precise understanding of the biological and biomedical implications of coevolution between DAMPs in host defense and the pathogens’ virulence factors obviously demands closer links between those disciplines. And here, we should take this conclusion as a sharp cut by leaving the touched future project and moving to the more real world of pathogens, as depicted in the following.
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63
DAMP - promoted Hyperinflammation (ARDS, SIRS, MOF)
controlled inflammation
DAMP-activated PRM-bearing cells
homeostasis controlled inflammation resolution
susceptibility of infections immunosuppression
SAMP - driven hyperresolution (CARS)
Fig. 2.5 Schematic diagram of a conceptual model illustrating the hyperinflammatory response in SIRS induced by excessive production of DAMPs that proceeds in parallel to a long-lasting hyperresolution response in CARS, caused by counterregulating production of SAMPs in excess (the controlled homeostatic proinflammatory and resolving responses are faded in, separated by dotted lines). Clinically, the long-lasting hyperresolution phase is characterized by a state of immunosuppression. ARDS acute respiratory distress syndrome, CARS compensatory anti-inflammatory response syndrome, MOF multiple organ failure, PRM pattern recognition molecule, SIRS systemic inflammatory response syndrome. (Source: identical to Fig. 5.2, p. 161, Vol. 2 [18])
2.6 Some Characteristics of Bacteria 2.6.1 Introductory Remarks There is evidence supposing bacterial life on Earth before 3.8 billion years ago [69], compared to eukaryotes, which were calculated to arise after the oxygenation of the Earth’s atmosphere (“Great Oxygenation Event”) about 2.4 billion years ago [70]. Together with archaea, protists, and fungi, bacteria remained free-living single cells, whereas some became host associated, forming microbial communities in terms of microbiomes (also called microbiota). Such host ↔ microbiome interactions have evolved to the hologenome concept, which considers the holobiont with its hologenome as an independent level of selection in evolution. The term holobiont now refers to a host (human, animal, plant) together with all associated microorganisms living on or in it, exosymbionts and endosymbionts, respectively (for further reading, see [71–73]). Bacteria do not only live as commensals in microbiota but can cause a wide range of human diseases, and the typical clinical picture of infection is known to every physician. Besides the diagnoses of acute, subacute, chronic, and hyperacute disorders, their severity ranges from mild/moderate diseases such as harmless soft throat, soft tissue infection/infected wounds, to more severe diseases such as upper
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airway inflammation/pneumonia (not requiring ventilatory support), osteomyelitis, and meningitis, up to life-threatening/fatal diseases culminating in sepsis → septic shock, associated with MOF. Certainly, although the simplest among living organisms, bacteria are much more complex than viruses. Before beginning with the description of some selected features, a brief glance at the history of their discovery may be allowed that simultaneously reflects the history of Microbiology.
2.6.2 Only a Brief Excerpt from the Fascinating History of Microbiology Indeed, the history of microbiology is fascinating [74]. It was the Dutch scientist Antoni van Leeuwenhoek who discovered both bacteria and protists in 1676, using his own deceptively simple, single-lensed microscopes, with a resolution of fewer than 1 μm only [75] (Fig. 2.6). For this discovery, he is universally acknowledged as the father of microbiology [76]. The critical relevance of these “little animals” (as
Fig. 2.6 Antony van Leeuwenhoek (Rijksmuseum, The Netherlands): the discovery of bacteria. (Source: Copied from Opal SM. A Brief History of Microbiology and Immunology. Vaccines A Biogr. New York, NY: Springer New York; 2010. p. 31–56. Available from https://link.springer. com/chapter/10.1007/978-1-4419-1108-7_3)
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Leeuwenhoek called the tiny forms observed through his microscope) to human health was not completely appreciated until almost 200 years later when Louis Pasteur (1822–1895) in Paris, France, and Robert Koch (1843–1910) in Berlin, Germany first successfully cultured bacterial organisms from diseased tissues. Indeed, the most important step toward the new discipline of Bacteriology was the work of Pasteur, who had proven that life is not generated spontaneously and that microorganisms cause fermentation and putrefaction (for his seminal work, also see [77–79]). Koch in Berlin developed the criteria and procedures, allowing to conclude that it is the particular microbe that causes a particular infectious disease. As already touched on in the previous chapter, Koch’s postulates, described by Robert Koch and Friedrich Löffler in 1882–1984 in relation to tuberculosis and cholera, can be regarded as the foundation of microbial etiology of infectious diseases [5, 6, 79]. The history of microbiology proceeded with great speed and, in the twentieth century, was dominated by research discoveries and remarkable achievements in genetics, NA biochemistry, and molecular biology. The foundation of several scientific journals on this subject bears witness to this development (e.g., also discussed in [80]). Recent progress in Microbiology, such as the development of recombinant DNA technology, polymerase chain reaction (PCR), and monoclonal antibodies, have revolutionized clinical microbiology. And last but not least, the introduction of MAMPs and DAMPs in the pathogenesis of infectious diseases can be regarded as a further important step in this advancing research field but is certainly not the end of the fascinating story of microbiology (for further reading, also see [81]).
2.6.3 The Continuous Fight Against Pathogenic Members of the Immense Bacterial World Bacteria and Archaea have a vital role in the earth’s ecosystem processes. They are ubiquitous, possess enormous metabolic versatility by catalyzing unique and indispensable transformations in the biogeochemical cycles of the biosphere, and produce critical components of the earth’s atmosphere. Moreover, as reviewed by Whitman et al. [82], the number of prokaryotes and the total amount of their cellular carbon on earth are estimated to be 4–6 × 1030 cells and 350–550 pg of carbon (1 pg = 1015 g), respectively. The authors continued [82]: Thus, the total amount of prokaryotic carbon is 60–100% of the estimated total carbon in plants, and inclusion of prokaryotic carbon in global models will almost double estimates of the amount of carbon stored in living organisms. In addition, the earth’s prokaryotes contain 85–130 pg of nitrogen and 9–14 pg of phosphorus, or about tenfold more of these nutrients than do plants, and represent the largest pool of these nutrients in living organisms. Most of the earth’s prokaryotes occur in the open ocean, in soil, and in oceanic and terrestrial subsurfaces, where the numbers of cells are 1.2 3 1029, 2.6 3 1029, 3.5 3 1030, and 0.25–2.5 3 1030, respectively. Bacterial infections, such as syphilis, gangrene, and tuberculosis, that scourged mankind from ancient times up to the twentieth century have lost their horror with the serendipitous discovery of penicillin by Alexander Fleming in 1928 [83–85].
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With this event and the following golden era of antibiotics discovery, it was generally thought that bacterial diseases would be easily controlled. However, this era of discovery, in particular, the discovery of broad-spectrum antibiotics, ended rather abruptly in the late 1950s/early 1960s, just as knowledge on mechanisms of antibiotic action and the nature of resistance began to accumulate [86]. Although impressive improvements had been made to limit the burden of healthcare-associated infections, outbreaks of multidrug-resistant (MDR) bacteria still present a considerable threat to vulnerable patient populations in hospitals around the world [87]. Indeed, the emergence of resistance among bacterial pathogens is recognized as a major public health threat worldwide. As warned by Munita and Arias [88], multidrug-resistant organisms have not only emerged in the hospital environment but are now often identified in community settings, suggesting that reservoirs of antibiotic-resistant bacteria are present outside the hospital. Further, medical communities have been facing emerging and reemerging microbial infectious diseases, and emerging pathogenic microbes are now considered to be another paramount microbiologic public health threat. Most of these diseases originated either from an animal and are considered to be zoonoses or from water sources. As outlined by Vouga and Greub [89], major contributing factors in the emergence of these disorders include an increase in human exposure to bacterial pathogens as a result of sociodemographic and environmental changes, and the emergence of more virulent bacterial strains and opportunistic infections, especially affecting immunocompromised populations. These scenarios alone make it already crystal clear that the future clinical use of DAMPs as biomarkers and their administration as therapeutics in patients with bacterial infections will represent a step forward.
2.6.4 Structure of Bacteria All bacteria are unicellular organisms that, defined as prokaryotes, are distinguished from eukaryotes by their smaller size and their lack of some internal organelles (e.g., mitochondria, ER, lysosomes, and Golgi apparatus). Structurally, a bacterial cell consists of three architectural regions: (1) appendages, (2) a cell envelope, and (3) a cytoplasmic region (Fig. 2.7). Surface appendages, such as flagella, pili, curli, and spinae, are filamentous structures attached to cell envelopes. They provide bacteria with a link to their external environments and are involved in various cellular functions, such as motility, attachment, secretion, and cell-to-cell interactions [90–92]. The cell envelope encompasses a capsule, cell wall, and plasma membrane. Gram-positive organisms have dynamic cell envelopes consisting of the main component peptidoglycan (PGN) and secondary cell wall polymers, such as lipoteichoic acid (LTA), teichoic acid (TA), surface proteins, phospholipids, and capsular polysaccharides. In addition, some species of Gram-positive bacteria, most notably the Mycobacteria, contain a cell wall heavily modified by lipids called a mycomembrane. These components mediate interactions with the environment and serve as
2.6 Some Characteristics of Bacteria
Periplasmic space
Cell membrane
67 Cell wall (MAMPs)
Capsule (virulence fact.)
Plasmid DNA (MAMPs)
Cytoplasm Nucleotid DNA (MAMPs)
Ribosomes
Flagellum (Virulence factors)
Pili (Virulence factors)
Curli (Virulence factors)
Fig. 2.7 Simplified schematic diagram of cellular structures of a bacterial cell. Fact. factors, MAMPs microbe-associated molecular patterns. (Sources: [90–97])
the first line of defense against toxic molecules [93–95]. Gram-negative bacteria possess a cell envelope that consists of an inner, cytoplasmic membrane, a PGN/ lipoprotein cell wall, and an outer membrane containing lipopolysaccharide (LPS). The envelope serves as a selective chemical permeability barrier that defines cell shape and allows the cell to sustain large mechanical loads [93, 96, 97]. From the perspective of this book, these structural envelope components are important because they provide the MAMPs, which, together with DAMPs, drive antimicrobial innate immune responses (Fig. 2.8) (see next chapter, Sect. 3.2). The bacterial cytoplasmic region usually comprises DNA, ribosomes, RNA, and most globular proteins. In fact, prokaryotes have a free-floating chromosome that is not surrounded by a nucleus membrane. Thus, their genetic material is not segregated from the cytoplasm and, instead, the chromosomal genomic DNA is typically condensed in a region of the cell called the nucleoid [98, 99]. Notably, besides chromosomal DNA, there is extrachromosomal DNA, called plasmids; the structure of them is made of circular double chains of DNA molecules which are replicated autonomously in a host cell (Fig. 2.7) (for further reading, see [100, 101]). Besides the nucleoid and plasmids, the bacterial ribosomes are localized in the cytoplasmic region. In prokaryotes, as in all cells, this large ribonucleoprotein complex synthesizes proteins using mRNA as the template and aminoacyl-transfer RNAs (tRNAs) as substrates. Ribosomes from bacteria consist of a large (50S) and a small (30S) subunit, which together compose the 2.5-megadalton 70S ribosome. In addition, several protein factors act on the ribosome at various stages of translation (reviewed in [102]). Mechanistically, these large complex machines translate
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Bacterium LTA TA (MAMP) (MAMP)
Surface proteins
Cell wall, Cell membrane
LPS (MAMP) Outer Membrane Lipoprotein PGN (MAMP)
Cell membrane Cytoplasm
Gram-positive bacteria
Cytoplasm
Gram-negative bacteria
Fig. 2.8 Simplified schematic illustration of the cell envelope of Gram-negative and Gram- positive bacteria, expressing various MAMPs. LPS lipopolysaccharide, LTA lipoteichoic acid, MAMPs microbe-associated molecular patterns, PGN peptidoglycan, TA teichoic acid. (Sources: [93–97])
mRNAs into proteins via the four translation phases: initiation, elongation, termination, and ribosome recycling [103]. In fact, as reviewed elsewhere [104], the assembly of ribosomes from a discrete set of components is a key aspect of the highly coordinated process of ribosome biogenesis in microbes. As said already, only a few points of the bacterial structure have been addressed here. Interested readers are referred to textbooks on Microbiology, such as quoted in [105].
2.6.5 Bacterial Taxonomy 2.6.5.1 General Remarks Taxonomy is the scientific discipline of classifying living entities. Over a long time, bacterial taxonomy has been dominated by the use of phenotypic markers, such as morphological, developmental, physiological, and, later on, biochemical properties. In subsequent periods, the bacterial enzymes were studied, and metabolic pathways were explored [106]. However, in the recent past, that is, over the past 30 years, the rapid expansion of sequenced bacterial and archaeal genomes has strongly influenced bacterial identification, classification, and nomenclature [107, 108]. Indeed, with the rapid advancements in DNA sequencing techniques, genome-based methods now allow to delineate the bacterial species at the genome level and thus provide valuable clues toward their identification [109]. Moreover, metabarcoding and metagenomics have recently been developed, enabling researchers to explore
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robustly bacterial and archaeal diversity by comparative genomic analysis [110, 111]. To review all these wonderful past and recent achievements of microbiology are beyond the scope of this book. Instead, here, only a few remarks on those topics are made that appear to be related to the topic of innate immune responses upon cell stress/tissue injury caused by bacteria. Interested readers are referred to the corresponding chapter in textbooks on Microbiology, such as quoted in [112–114].
2.6.5.2 Phenotypic Classification of Bacteria From the various phenotypic markers, the chemical composition of cell constituents has been recognized as a useful property for optimizing the classification and identification of prokaryotes. Among the various chemotaxonomic methods, the traditional Gram stain is an important classification system, as several cell properties can be correlated with the cell envelope of Gram-positive and Gram-negative bacteria (reviewed in [93, 106]). One such feature is the different expression of cell envelope- associated MAMPs that serve as molecules to be recognized by PRRs of innate immune cells, a most important MAMP being LPS in Gram-negative bacteria (as briefly touched on above and illustrated in Fig. 2.8). From the perspective of the book, the classification of bacteria according to the degree of their intrinsic pathogenicity would be of major interest, an approach that has already been addressed by de la Cal et al. [115]. The authors concluded that at least some characteristics in terms of certain virulence factors determine the different pathogenicity (discussed in more detail in the next chapter). In this context, it appears reasonable to distinguish extracellular and intracellular pathogenic microbes in the approach of phenotypic classification. Of note, however, such a classification must be flexibly handled as there are variations in that bacteria can be divided into extracellular (Staphylococcus aureus, Streptococcus pyogenes, Pseudomonas aeruginosa, Escherichia coli), extra-/intracellular (e.g., Yersinia pestis, Francisella tularensis, Burkholderia pseudomallei, Salmonella enterica serovar Typhimurium, M. tuberculosis), or intracellular microbes (Brucella abortus, Listeria monocytogenes, Chlamydia trachomatis, Coxiella burnetii, Mycobacterium tuberculosis, Salmonella enterica) [116, 117]. The point regarding pathogenicity here is that intracellular bacteria can cause additional cell stress arising during their invasion and replication processes (see Chap. 5). 2.6.5.3 Genotypic Classification of Bacteria The era of genome-based classification of bacteria (and archaea) originated from the work of Woese et al. [118, 119]. In a phylogenetic analysis based upon ribosomal RNA (rRNA) sequence characterization, the authors could show that the phylogenetic relationships of bacteria could be determined by comparing a stable part of the genetic code. As candidates for this genetic area in bacteria, they identified genes that code for the small ribosomal subunits 5S, 16S, and 23S rRNA. Moreover, on the basis of these earlier studies, Woese et al. [120] proposed a natural system for classifying Bacteria, Archaea, and Eukarya based on comparisons of gene sequences of the small ribosomal subunit. In the ensuing years, this method has become a
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standard for identifying Bacteria and Archaea [121]. Today, the part of the DNA most commonly used for taxonomic purposes for bacteria is the 16S rRNA gene. Indeed, the contribution of 16S rRNA gene sequences to the classification and identification of the Bacteria and Archaea has turned out to be immense. Thus, data from its use have revolutionized the understanding of the microbial world and led to a rapid increase in the number of descriptions of novel taxa, especially at the species level (for further reading, e.g., see [122–125]). Of note, although 16S rRNA-based taxonomy has been successfully employed in clinical microbiology and still serves as the primary basis for microbial taxonomy, scientific progress of bacterial classification schemes during the last decade has moved to more sophisticated methods such as whole-genome sequencing (WGS) and high-throughput DNA sequencing, known as next-generation sequencing (NGS). Indeed, the potential use of genomics-driven taxonomy determines current classification and identification of microorganisms (for further reading, e.g., see [109, 126–135]). Historically, the development of DNA sequencing technologies is a unique story characterized by many highlights, such as the development by Sanger et al. [136] and Maxam and Gilbert [137] of two methods that could decode hundreds of bases within several hours. The first complete genome of a free-living microorganism, Haemophilus influenza, published in 1995, was sequenced using the Sanger method [138]. Subsequently, progressively more efficient technologies characterized by increased accuracy, throughput, and sequencing speed have been developed, allowing to address larger genomes in the process of WGS. It was now possible to harness WGS to determine the complete nucleotide sequence of an organism’s and a cell’s genome. Applied to microbiology, WGS explores the entire genetic material of a bacterium and therefore provides maximal distinguishing power for a discrimination among closely related endemic strains. Continuous progress in sequencing technologies then resulted in the establishment of WGS in research laboratories, qualifying this method as one of the most promising techniques in clinical microbiology [126, 127]. But not least, because of being expensive, cumbersome, and time consuming, this technology, based on Sanger sequencing, was then replaced by whole-genome NGS methods that were shown to reduce these disadvantages dramatically. NGS is a genre of technology that allows for high-throughput, massively parallel sequencing of thousands to billions of DNA fragments independently and simultaneously. The applications of NGS in clinical microbiological testing are manifold and include metagenomic NGS (mNGS), which allows for an unbiased approach to the detection of pathogens [132]. For example, NGS allows sequencing of the whole genome of numerous pathogens in one single efficient WGS workflow, either from bacterial isolates of (different) patients or from multiple species present in patient material from one individual (i.e., metagenomics). Thus, apart from the improvement of taxonomic classification, WGS of cultured microbial isolates applying NGS has now facilitated the use of this technology for microorganism typing, epidemiology, susceptibility prediction, and virulence factor determination. A variant of NSG is targeted next-generation sequencing (tNGS) that focuses on sequencing specific regions of the genome (for more detailed information, see [139–142]).
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Over the last 10 years, NGS applications have been increasingly established as diagnostic tools in clinical microbiology laboratories. These applications include WGS, tNGS methods, and mNGS, all of which are described in detail in the excellent article of Mitchell and Simner [133]. In short, WGS is used for precise strain typing and characterization, for example, for pathogen monitoring during outbreaks; testing of strain properties such as antimicrobial resistance (AMR) profiling and pathogen virulence factors; and establishing sources of (recurrent) infections by providing entire genome and plasmid sequences. For clinical applications of tNGS, the main goal is to identify the microbial pathogen or pathogens in patient samples, whereas mNGS has proven successful as diagnostics in detecting infections in various organs, such as the central nervous system (CNS), respiratory airways, and urinary tract.
2.6.5.4 Concluding Remarks Certainly, during the past years, tools to improve the quality of bacterial taxonomy have made incredible progress, moving from phenotypic to genotypic methodology. Thus, WGS has been identified as one of the most promising techniques in clinical microbiology, and its clinical application is discussed for topics, such as typing and outbreak and antimicrobial susceptibility prediction. Also, at least from the perspective of the book, with the use of WGS for typing bacterial strains in combination with the determination of their capability to induce in vitro typical key DAMPs (reflecting virulence-associated genes), it would be of interest to explore the possible use of WGS in predicting disease-causing pathotypes with more accuracy (also compare in this context [131]). Indeed, with such a use of WGS data in combination with in vitro measured DAMPs, clinical application of WGS-based individualized antimicrobial treatments may already be imaginable. However, despite its obvious successes, it is difficult to predict if and when WGS technology will completely fully replace current standards in clinical microbiology. Indeed, WGS diagnostics have not yet been widely adopted in this area of clinical research. Major hints include current high costs, a lack of the necessary computational infrastructure in most hospitals, and the inadequacy of existing reference microbial genomics databases necessary for reliable AMR and virulence profiling (see for details Balloux et al. [143]). Nevertheless, as concluded by Michell and Simner [133], There is great momentum for the introduction of NGS applications in clinical microbiology laboratories. Over the next 5 to 10 years, although it is unlikely to see NGS completely supplant traditional identification and AST methods, a wealth of applications must be acquired that is continually improved over time, providing enhanced diagnostic capabilities for patients.
2.6.6 Bacterial Cell Division 2.6.6.1 General Remarks The core machinery that copies DNA is conserved in all three domains of life: Eukarya, Archaea, and Bacteria [144]. However, research in bacterial cell division
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(mostly done on model organisms such as the Gram-negative Escherichia coli and Gram-positive Bacillus subtilis) revealed that there are differences. For example, bacteria do not usually undergo sexual reproduction in the eukaryotic sense. As unicellular organisms, they mainly reproduce by so-called binary fission rather than mitosis, a process that follows a copy of their genetic material (i.e., DNA) and is based on the interaction between the so-called filamenting temperature-sensitive mutant Z (FtsZ) protein and PGN biosynthesis machinery [145]. Regardless of this peculiarity, the conserved biochemical pathway of DNA replication in bacteria proceeds in the same way as in all other organisms, namely, divided into three stages: initiation, elongation, and termination.
2.6.6.2 Principles of Bacterial DNA Replication As in all cells, initiation of genome replication relies on the activity of AAA+ initiator proteins that form complexes with replication origin DNA (AAA, for ATPases Associated with diverse cellular Activities). In bacteria, the conserved adenosine triphosphate (ATP)-regulated initiator protein “DnaA” forms a complex with the origin that mediates DNA strand separation and recruitment of replication machinery. The molecular processes within the three phases of genomic DNA replication are governed by the ATP-DnaA-driven nanomachines [146, 147]. In the DnaA-dependent initiation phase of genomic DNA replication, the origin of DNA replication is unwound by the replicative DNA helicase (for details, see [148, 149]). This is followed by the DNA polymerase III holoenzyme (pol III)driven elongation phase, in which forks copy the chromosome using semi- conservative DNA synthesis (for further reading, see [150, 151]). The process of DNA replication is finalized when the converging replication forks meet. During this process, called replication termination, DNA synthesis is completed, the replication machinery is unassembled, and daughter molecules are resolved (for more information, see [152, 153]). Bacteria have the capacity to adhere, replicate, and proliferate at the surface of host cells and tissues, while some are able to enter and proliferate inside host cells. These processes will be briefly touched on in the following. 2.6.6.3 Extracellular and Intracellular Bacterial Replication: The Cradle of DAMPs Emission As mentioned above, bacteria, with the help of adhesive virulence factors, adhere to respiratory, digestive, and urogenital mucosa, which are all composed of three layers representing suitable surfaces for adhesions: (1) an epithelium, (2) a lamina propria, and (3) smooth muscle cells (SMCs). It is these surfaces that form superior replicative niches, where bacteria can replicate and proliferate in extracellular spaces (reviewed in [154]). In turn, some pathogenic bacteria multiply intracellularly. After internalization, for example, via endocytosis, intracellular bacteria can replicate in the vacuolar systems or the cytosol, dividing them as vacuolar or cytosolic pathogens (see also next chapter, Sect. 3.2.5). However, the invading bacteria are able to change these two replicative niches: thus, intravacuolar pathogens, at least to some extent, can get
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access to the host cytosol by crossing their vacuolar membranes, while cytosolic bacteria have been observed to spend their intracellular life cycle partially, for example, via autophagic processes, within membrane-bound compartments [155– 157]. In this context, it should be noted that intracellular pathogens usually must reprogram the metabolism of their host cells to proliferate or persist in these infection niches (reviewed by Eisenreich et al. [158]). The authors discussed that the replication rate of cytosolic pathogenic bacteria is usually higher than that of vacuolar pathogens, suggesting easier access to essential nutrients by cytosolic bacteria compared to vacuolar bacteria. Independently from this difference, exhaustion of essential nutrients in the host cells by cytosolic or vacuolar bacteria is associated with negative effects for the infected cells. However, the point to make here is that these various processes of nutrient exhaustion associated with intracellular bacterial DNA replication evoke molecular perturbations reflecting generation of dysDAMPs. And as described several times in this book, these danger signals may lead to stress responses, which can result in the induction of subroutines of RCD as another source of DAMPs emission.
2.7 Some Characteristics of Viruses 2.7.1 A Few Historical Remarks As often noticed in the history of discoveries of a novel biological/biomedical principle, the scientific observation of several researchers resulted in the final definition of a principle. The discovery of contagious viruses followed this rule as well. It was the Russian researcher Ivanovsky who, in 1892, working on tobacco mosaic disease, presented a paper in which he stated that “the sap of leaves infected with tobacco mosaic disease retains its infectious properties even after filtration through Chamberland filter candles” [159]. But falsely, he still thought of small bacteria being involved. A few years later, in 1898, the Dutch Martinus Willem Beijerinck, working on a potential causative agent of tobacco mosaic disease, concluded from his work that the infection is not caused by a corpuscular entity but by a solubilized substance denoted as contagium vivum fluidum that he called––for the first time––“virus” (the Latin word for the German word “Gift” (Engl.: poison) [160] (Fig. 2.9). It was his credit to propose that this entity can only multiply in a living cell. In fact, Beijerinck clearly indicated that the virus became part of the cell’s metabolism: Without being able to grow independently, it is drawn into the growth of the dividing cells and here increased to a great degree without losing in any way its own individuality in the process [161]. Also, in 1898, Friedrich Loeffler and Paul Frosch, from their work on the etiology of foot-and-mouth disease, concluded that the infectious agent is not a solubilized substance but must be of a corpuscular structure [162]. The proposal of a corpuscular structure was then confirmed by Wendell Meredith Stanley, who, using an electron microscope, demonstrated viruses to be particles rather than a fluid [163].
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Fig. 2.9 First coining of the term: “virus.” The figure shows a section of the publication of the Dutch Martinus Willem Beijerinck who worked on a potential causative agent of tobacco mosaic disease. Explanation of the text: He concluded from his work that the infection is not caused by a corpuscular entity but by a solubilized substance denoted as contagium vivum fluidum that he called––for the first time––“virus” (virus is the Latin word for the German word “Gift,” in English: poison). (Source: Beijerinck MW: Ueber ein Contagium vivum fluidum als Ursache der Fleckenkrankheit der Tabaksblätter [160])
Today, a wealth of information has been published about these particles by researchers of different disciplines worldwide. In fact, viruses are now recognized as the most abundant and the most diverse life form and appear to be the dominant biological entities on our planet. Some details will be presented in the following.
2.7.2 Viral Infections: From a Simple Common Cold to Fatal Sepsis Viral infectious diseases belong to the major causes of human and animal morbidity and mortality, leading to significant healthcare expenditure worldwide. Indeed, the world has experienced outbreaks, epidemics, and pandemics of severe viral diseases, most recently COVID-19, declared by the World Health Organization (WHO) a global pandemic on March 11, 2020 [164]. As known to every physician, viruses can cause a wide range of human diseases, ranging from acute (symptomatic or asymptomatic) disorders such as harmless rhinitis that resolve in about a week to chronic diseases, up to acute fatal diseases characterized by sepsis and MOF. Notably, pathogenic RNA viruses are potentially the most important group involved in zoonotic disease transmission. As reviewed by Carrasco-Hernandez et al. [165], studies from the last decades have placed RNA viruses as primary etiological agents of human emerging pathogens, occupying up to 44% of all emerging infectious diseases (ranging from 25% to 44% in different studies), which, along with bacteria (10–49%), overshadow other parasite groups such as fungi (7–9%), protozoans (11–25%), and helminths (3–6%). Moreover, RNA viruses are known to induce emerging infectious diseases, which are both transmissible from patient to patient and virulent with high mortality. These viruses and associated disorders include––as reviewed by Weber et al. [166]––hemorrhagic
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fever viruses (Lassa, Ebola), SARS-CoV (the Middle East respiratory syndrome, MERS), and highly pathogenic influenza A viruses (IAVs), A(H5N1), and A(H7N9). Likewise, DNA viruses can lead to acute mild diseases that may heal up within a week but may also result in fatal diseases, in particular, in immunosuppressed patients and children, whereas other DNA viruses are known to create chronic persistent and/or latent infections in the host, which are usually lifelong and hard to eradicate. Besides diagnosing acute, chronic, and fatal courses, there are other ways how to categorize viral infections, for example, and clinically useful, by the organ system most commonly affected (e.g., lungs, gastrointestinal tract, skin, liver, CNS, the immune system, and mucous membranes).
2.7.3 Some Features of Viruses Virome studies consistently show that, in marine, soil, and animal-associated environments, the number of virus particles typically is 10–100 times greater than the number of cells [167]. Viruses do not only function as pathogens to cause severe, potentially deadly diseases but are also a driver of global geochemical cycles and a reservoir of the greatest genetic diversity on Earth. As impressively described by Suttle [168], in the oceans alone, viruses probably infect all living things, from bacteria to whales. Most interesting is the fact that the ocean waters are estimated to contain ~4 × 1030 viruses. Also, according to a meta-analysis reported by Cobián Güemes et al. [169], there are, as estimated, 4.80 × 1031 phages on Earth. Further, 97% of viruses are in soil and sediment, that is, two underinvestigated biomes that combined account for only ∼2.5% of publicly available viral metagenomes. Impressed by these and other figures not cited here, the authors conclude: Viruses are the winners in the game of life: the most numerous and genetically diverse life forms on Earth [169]. In fact, the discovery of unforeseen diversity of viruses in the ways of storage and transfer of genetic information is considered one of the most fundamental achievements of virology today. This abundance and diversity of viruses prompted Koonin et al. [170] recently to describe the global organization of the virus world and propose a comprehensive hierarchical taxonomy of viruses based on the Baltimore classification (for details of the description and proposal, see [170]). Here, only a brief description of the structure, classification, and replication cycle of viruses is presented by focusing on the Baltimore classification scheme.
2.7.4 Structure and Taxonomy of Viruses (in Brief) 2.7.4.1 General Remarks Viruses can be considered very small obligate intracellular parasites, which by definition contain either an RNA or DNA genome, surrounded by a protective, virus- coded protein coat. For propagation as a complete virus particle, namely, the
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infectious virion, viruses depend on specialized host cells, which provide the complex metabolic and biosynthetic machinery of eukaryotic or prokaryotic cells. The crucial function of the virion is to deliver its DNA or RNA genome into the host cell so that the genome can be expressed, that is, transcribed and translated by the host cell.
2.7.4.2 The Infectious Particle: Viral Genome and Associated Proteins The viral genome does not always exist alone but is often associated with basic proteins. Thus, the genome, together with the NA-associated protein, denoted as nucleoprotein, forms the nucleocapsid. For some viruses, the capsid is surrounded by a lipid bilayer derived from the modified host cell membrane and riddled with an outer layer of virus envelope glycoproteins. They are called enveloped viruses, while viruses that lack this bilayer are denoted nonenveloped viruses (for further reading, see [171, 172]). Notably, the route of virus replication and protein expression is determined by the viral genome type and property, whereby every family of viruses employs unique replication strategies. And it is the comparison of these genome-determined routes that had led to the classification of viruses into seven “Baltimore classes” (BCs) that characterize the major features of virus reproduction. 2.7.4.3 The Baltimore Classification Scheme In a seminal article published by Baltimore in 1971 [173], all then-known viruses were classified into six distinct BCs; a seventh class was introduced later [174]. The classification is based on the structure of the virion’s genome NAs as well as on how the critical viral mRNA is finally produced. Accordingly, viruses can be placed in one of the seven following groups: • BC I, double-stranded DNA (dsDNA) viruses, such as Herpesviruses (HSVs), Human cytomegalovirus (HCMV), Adenoviruses, Papillomaviruses, and Poxviruses; • BC II, single-stranded DNA (ssDNA) viruses, such as Parvoviruses; • BC III, double-stranded RNA (dsRNA) viruses, such as Reoviruses; • BC IV, positive-sense single-stranded RNA (ssRNA) viruses, such as hepatitis C virus (HCV), coronaviruses (e.g., SARS-CoV-2, Fig. 2.10), Flaviviruses, and Astroviruses; • BC V, negative-sense ssRNA viruses, such as orthomyxoviruses (e.g., IAV, Fig. 2.11), rhabdoviruses, and paramyxoviruses; • BC VI, positive-sense ssRNA reverse-transcriptase viruses (i.e., with DNA intermediates), commonly known as retroviruses; and • BC VII, DNA reverse-transcriptase viruses, also known as the dsDNA retroviruses.
2.7.4.4 Concluding Remarks In view of this classification, viral diversity is enormous and, obviously, far greater than that of other organisms, given alone these major differences in virus
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a Nucleocapsid
Mature virus
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Fig. 2.10 Simplified schematic presentation of the SARS-CoV-2 genome organization and the viral structure. (a) Overview of the viral positive-sense single-stranded RNA and the nucleoprotein (N) as well as the three major structural SARS-CoV-2 proteins [spike protein (S), envelope protein (E), and membrane protein (M)]. The spike protein consists of three spike monomers, which form a homotrimeric structure (spike trimer) on the SARS-CoV-2. (b) From the full-length genomic RNA (29,813 bases) that also serves as an mRNA, ORF1a, and ORF1b are translated (the genome shown with ORFs below the nucleotide numbering). The region from ORF1a to ORF1b encodes 16 different nonstructural proteins (nsp1–nsp16) involved in the replication–transcription complex. Structural proteins are encoded by the four structural genes, including S, E, M, and N genes. The accessory genes are distributed among the structural genes (not annotated). It is noted that the figure was prepared during the pandemic with the delta variant of SARS-CoV-2. kb kilobases, nsps nonstructural proteins, ORF open reading frame, ssRNA single-stranded RNA. (Sources: (a) [175– 177]; original Figure of (b) in [178]: Ellis P, Somogyvári F, Virok DP, Noseda M, McLean GR. Decoding Covid-19 with the SARS-CoV-2 Genome. Curr Genet Med Rep. 2021 Jan 9:1-12)
genetic material (RNA or DNA) and configurations (double stranded or single stranded). However, this is certainly not the end result of virus classifications. In the context of their article on “Global Organization and Proposed Megataxonomy of the Virus World,” Koonin et al. [170] concluded: The principal and, in our view, striking conclusion of this work is that the global organization of the virus world is becoming transparent. Evidently, there are numerous, sometimes vast, white spots on the map of the virosphere. These gaps are being gradually filled thanks to increasingly sensitive analyses of genomic and metagenomic data coupled with comparisons of virus protein structures. A comprehensive, internally consistent, and stable hierarchical taxonomy of viruses seems to be within the reach of the current generation of virologists. We find it unexpected and remarkable that, notwithstanding the enormous diversity of viruses that is rapidly expanding through the advances of metaviromics, the contours of such a hierarchical virus taxonomy appear to be solidifying.
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HA
PA
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PB2 3' PB1 5' Negative-sense single-stranded RNA IAV
PA
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M2 Positive-sense single-stranded RNA IAV
Fig. 2.11 Diagram of the structure of influenza A virus that contains eight negative-sense, single- stranded viral RNA gene segments, and the viral membrane proteins HA, NA, M1, and M2 (left side of the figure). On the right side, a single viral RNA gene segment is shown wrapped around multiple nucleoprotein copies with the conserved promoter regions in the 5′ and 3′ untranslated regions, forming a helical hairpin, which is bound by a single heterotrimeric viral RNA-dependent RNA polymerase, denoted as PB1, PB2, and PA. The negative-sense single-stranded RNA is the transcribed complementary positive-sense single-stranded RNA. HA hemagglutinin, IAV influenza A virus, NA neuraminidase, M1/M2 matrix proteins, NP nucleoprotein, PA polymerase acidic protein, PB1 polymerase basic protein 1, PB2 polymerase basic protein 2. (Sources: [179–183])
2.7.5 Replication Cycle of Viruses: The Seed for the Generation of DAMPs 2.7.5.1 General Remarks To be able to continue the chain of infection, a virus must undergo the process of replication to produce new, infectious virions that can execute infection to other cells of the host’s organism or subsequent other hosts. According to the international literature, this process encompasses seven stages: (1) attachment, (2) penetration (cell entry), (3) uncoating, (4) replication, (5) assembly, (6) maturation, and (7) release (also compare [184, 185]). In general, viral genomes are replicated, expressed, and assembled in association with intracellular structures that are formed by viral and cellular macromolecules. The resulting molecular complexes occupy either cytoplasmic or nuclear sites, where the viral genome and viral and cellular molecules accumulate. There are diverse molecules and activities that are associated with these compartments but invariably include components that direct viral genome replication and expression (reviewed in [186]). But why did mention the replication cycle in a book on DAMPs? The answer to this question is plausible: the replication cycle causes considerable stress and molecular perturbation to the infected cell associated with generation of dysDAMPs. And this process is the beginning of triggering inflammatory pathways.
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2.7.5.2 Attachment → Penetration/Fusion → Uncoating Once the virus has entered the body, it docks physically on and then crosses the plasma membrane of a target cell. Indeed, attachment to the host cell plasma membrane is the key to instigating viruses’ infectious cycle. For the majority of viruses, this initial stage of the entry process is the binding of a viral attachment protein (either membrane glycoproteins or sites on a viral capsid) to a generalized receptor (mostly salicylic acid [SA] receptors) on the host target cell surface, more commonly known as attachment factors (e.g., glycolipids and/or glycoproteins, such as heparan sulfate proteoglycans). Attachment proteins of enveloped viruses are usually spike-like and extend from the surface of the virion allowing the attachment protein to serve as the first point of contact with the receptor on the plasma membrane [187]. The negative-sense ssRNA IAV is a prototype example of a virus that––via its expressed envelope protein hemagglutinin (HA)––interacts with SA to mediate host cell invasion, and SA expression within the host regulates tissue tropism and host range specificity [179, 188, 189] (cf. Fig. 2.11). Herpes simplex virus reportedly mediates cell entry via the envelope glycoproteins gB and gD [190]. The initial capture of HCV particles is executed by glycosaminoglycans and/or lipoprotein receptors, while subsequent coordinated interactions with host cell receptors are mediated by the scavenger receptor class B type I, the CD81 tetraspanin, and the tight junction proteins Claudin-1 and Occludin [191]. In coronaviruses, the spike protein (S) mediates virus entry into the host cell via binding to several host cell receptors, including ACE2, aminopeptidase N (APN), dipeptidyl peptidase 4 (DPP4), and carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) [192]. These first interactions provide a virus an initial “handhold,” from which it can then recruit specific receptors that drive the reactions resulting in final entry (for more details, see [187, 193, 194]). In fact, interactions between the incoming virus and host receptors and co- receptors in the plasma membrane are of critical importance for proper cellular invasion. As touched on above, some of the contacts provide attachment only, while others trigger signaling, induce plasma membrane ruffling, activate endocytosis, and provoke changes in the viral particle. Such non-SA viral receptors include immunoglobulin superfamily (IgSF) receptors, integrins, selectins, cadherins, and viral phosphatidylserine (PtdSer) receptors. For example, integrins serve as receptors for HSV [195], whereas IgSF members have emerged as receptors for enveloped and nonenveloped viruses with either DNA or RNA genomes, including reovirus, adenovirus, coxsackievirus, and HIV, as well as PtdSer receptors for enveloped viruses, including Dengue virus and Zika virus (for reviews, see [187, 194, 196]). In animal cells, viruses achieve entry in two principal ways, which may occur in parallel: (1) by an internalization process into endosomes (endocytosis), or (2)––as applicable for some enveloped viruses––by direct fusion with the plasma membrane. The majority of viruses, however, prefer to enter cells via endocytosis by penetrating or fusing with the endosomal membrane, where receptor-binding and/or the acidic pH trigger conformational modifications or disassembly of the shell,
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allowing the NAs to be released into the cytoplasm (for further reading, see [187, 193, 197–200]). Multiple endocytic pathways operate at the plasma membrane and are utilized in viral entry, such as macropinocytosis, micropinocytosis, clathrin- mediated endocytosis, caveolin-dependent endocytosis, or alternative, less- characterized uptake pathways. The clathrin-coated pit pathway is the best-characterized endocytic pathway and is used for entry by many viruses, including IAV [201, 202] and HCV [191] (cf. Fig. 3.4 in Chap. 3). Interestingly, there is also first evidence from in vitro studies that human coronavirus enters the cell by clathrin-mediated endocytosis, though the pathway may be bypassed to some extent during infection ex vivo [203]. Following penetration through the plasma membrane, enveloped and nonenveloped animal viruses deliver their genome to the replication site, which can be in the cytosol, on cytoplasmic membranes, or in the nucleus. This maneuver is a complex, tightly regulated, multistep process termed uncoating, whereby the majority of viruses link their uncoating program to the endocytic machinery. These processes have been studied in detail for just a few viruses and turned out to be highly variable and complicated, depending on the nature of the virus and the cell. For detailed information, the reader is referred to excellent articles listed under [196, 204–206].
2.7.5.3 Replication Strategies of DNA Viruses All viruses, regardless of their type of neuraminidase (NA) genome, that is, DNA viruses briefly described here and RNA viruses touched upon below, must copy/ replicate the genome and translate/express their viral proteins in order to assemble/ create new infectious virions. Viral DNA genomes have restricted coding capabilities and, thus, use cellular factors to enhance replication of their genomes and generate progeny virions. In the following, a few aspects of function and replication mechanisms are cursorily outlined (for in-depth information, also see [184, 185, 207]). BCI, Double-Stranded DNA Viruses All dsDNA viruses that infect humans (with the exception of poxviruses) enter the nucleus of the cell, using various mechanisms of entry and uncoating, and use a broad diversity of DNA replication machinery. Viruses differ greatly in both completeness and composition of their sets of DNA replication proteins. In principle, viruses with dsDNA genomes often harness the enzymes and proteins that the host cell normally uses for DNA replication and transcription, including its nucleus- located DNA polymerases and RNA polymerases. Of note, the process of transcription of viral mRNA (vmRNA) must take place before genome replication in case the viral proteins are involved in replicating the virus genome. Moreover, some translated viral proteins operate as transcription factors to orchestrate the transcription of other genes (for details, also see [184, 186, 207, 208]). For example, replication of herpesviruses, such as HSV, in the cell nucleus is a complex process involving at least seven viral DNA replication proteins and possibly several host proteins. Six of the viral replication proteins play “core” replication roles at the replication fork and are conserved in all known herpesviruses: a single-strand DNA-binding protein, a
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two-subunit DNA polymerase, and a three-subunit helicase/primase complex (reviewed in [209]). BCII, Single-Stranded DNA Viruses Single-stranded DNA viruses are extremely widespread, infect diverse hosts from all three domains of life, and include important pathogens, amongst them Parvoviruses, Circoviruses, Anelloviruses, and Geminiviruses (reviewed in [185, 210, 211]). The genomes of ssDNA viruses can be linear or circular, multi- or single component, and they have evolved diverse mechanisms to invade cellular genomes. Notably, during replication, the ssDNA genome enters the nucleus of the host cell, where the ssDNA is converted to dsDNA by host DNA polymerase. The DNA polymerase synthesizes the virion sense strand using a negative strand as a template. A typical example is the Protoparvoviruses, which replicate within the nucleus harnessing the transport, transcription, and replication machinery of the host cells. In order to reach the nucleus, Protoparvoviruses need to cross over several intracellular barriers and traffic through different cell compartments, which limit their infection efficiency (for details, see [212]).
2.7.5.4 Replication Strategies of RNA Viruses RNA viruses are unique in that their genetic information is encoded using RNA instead of DNA. Accordingly, transcription of RNA from an RNA template is a phenomenon unique to these viruses and needs an RNA-dependent RNA polymerase (RdRp). Notably, the replication of viral RNA (vRNA) requires first the synthesis of complementary RNA that, in turn, serves as a template for the synthesis of additional copies of vRNA. As touched on above, RNA viruses can have a genetic material consisting of ssRNA or dsRNA. Moreover, there are positive-sense and negative-sense RNA viruses. For both RNA virus types, the replication process proceeds through a complementary RNA strand intermediate. Here, a few aspects of replication mechanisms in negative-sense and positive-sense ssRNAs viruses are presented, which have necessarily evolved different routes to the production of mRNA (for in-depth information, also see [184, 185, 207]; for a review on RNA viruses, also see [213]). BCIV, Negative-Sense Single-Stranded RNA Viruses Negative-sense ssRNA viruses have genomes that do not operate as mRNA. Therefore, like their dsRNA counterparts, they carry an RdRp in the virion, originating from the preceding round of infection in hosts. Accordingly, for negative-sense ssRNA viruses, the complementary RNA is of positive sense, and the RNA polymerase involved performs the same function as the virion-associated transcriptase used for the primary transcription of mRNAs. Influenza A virus, as a typical negative-sense ssRNA virus, should serve here again as an example (Fig. 2.12) (reviewed in depth in [179, 180]). The eight viral ssRNA genome segments (vRNA) are packaged inside the virus in distinct ribonucleoprotein particles (RNPs). Each RNP comprises the viral RdRp bound to its promoter, which consists of the conserved and quasi-complementary 5′ and 3′
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Fig. 2.12 Simplified schematic diagram of a narrative model of the influenza A virus (IAV) replication cycle. The receptor-mediated endocytotic entry of the influenza A virus and hemifusion of the viral envelope with the endosomal membrane are illustrated. Following this process, the viral ribonucleoprotein (vRNP), together with viral RNA-dependent RNA polymerase complex PB1/ PB/PA, is released from the endosome and transported through the cytosol into the nucleus. Upon entry into the host cell nucleus, the vRNP-associated viral polymerase transcribes the viral mRNAs. Also, the heterotrimeric viral RNA-dependent RNA polymerase (marked in blue, red, and green) initiates transcription of the positive-sense complementary RNA (cRNA, marked in red). Nucleoprotein (NP) molecules (symbolized by the dotted green arrow) bind to the cRNA, promoting cRNP assembly. Upon termination of transcription, cRNP formation is completed with the binding of a newly synthesized viral polymerase (PB1, PB2, PA, symbolized by the dotted green arrow). Subsequently, transcription of the negative-sense viral RNA (vRNA, marked in blue) proceeds in a similar way as cRNA synthesis. Similar to the formation of cRNP, multiple NPs and a viral polymerase (again symbolized by the dotted green arrow) bind to the newly transcribed vRNA to produce a new viral ribonucleoprotein (vRNP). Further, newly synthesized NPs and viral polymerase, imported back to the nucleus (again symbolized by a dotted green arrow), are encoded by IAV mRNA (exported for translation by cytosolic ribosomes), which is transcribed by the viral polymerase. On the other hand, viral mRNAs encoding the membrane proteins NA, HA, and M2 are exported for translation by ER-associated ribosomes. Once synthesized, these membrane proteins are transported from the ER via the TGN to the apical plasma membrane and ultimately assembled together with vRNP into virus particles. The transport of the vRNP to the plasma membrane for budding occurs, at least in part, through Rab11 protein that is located in the modified endoplasmic reticulum membranes. The subsequent processes of budding and release provide the final exit of the infectious virion from the cell. Note: Assistance of viral mRNA transcription by the association of the viral polymerase (PA subunit) with the cellular RNA polymerase II C-terminal domain is not shown. cRNA(+) positive-sense complementary RNA, cRNP complementary ribonucleoprotein, ER endoplasmic reticulum, HA hemagglutinin, mRNA messenger RNA, moER modified endoplasmic reticulum, M2 matrix 2, NA neuraminidase, NP nucleoprotein, PA polymerase acidic protein, PB1/2 polymerase basic protein 1/2, Rib. ribosome, TGN trans-Golgi Network, tr. transcription, vRNA(-) negative-sense viral RNA, vRNP viral ribonucleoprotein. (Sources: [179, 180, 189, 214])
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extremities of the vRNA [181, 182]. Following SA-containing receptor-mediated endocytotic entry of the virus and hemifusion of the viral envelope with the endosomal membrane, the viral ribonucleoprotein (vRNP) is released from the endosome into the cytosol to be transported into the host cell nucleus. The vRNP is composed of vRNA associated with the nucleoprotein (NP) and viral RdRp. Arrived in the nucleus, the heterotrimeric viral NA-dependent RdRp executes the transcription and replication of the vRNAs that involves two steps: at first, transcription of positive-sense complementary RNA (cRNA), followed by transcription of new negative-sense vRNA copies by newly synthesized viral polymerase, using the cRNAs as templates. The whole process then starts again from the beginning: replication. In addition, the viral RNP-associated viral polymerase transcribes the viral mRNAs from the vRNA templates when it reaches the host cell nucleus, the process being assisted by the cellular RNA polymerase. Notably, during the course of infection, mRNA synthesis occurs before cRNA and vRNA transcription is initiated. Subsequent IAV protein synthesis is dependent on the translation machinery of the host cell. The vRNPs are trafficking within the cytoplasm toward the plasma membrane for viral assembly by Rab11 protein, budding, and final release as infectious virions (also see next section). Notably, recent evidence suggests that the vRNP components and the Rab11 protein are present at the membrane of a modified, tubulated ER that extends all throughout the cell, and on irregularly coated vesicles [215]. BCIV, Positive-Sense Single-Stranded RNA Viruses In contrast to negative-sense ssRNA viruses, positive-sense ssRNA viruses have genomes that do operate as mRNA. Since the genome of positive-sense ssRNA viruses, such as coronaviruses, operates as mRNA, these viruses have genetic information that is infectious. The viral genome of these viruses is used to create a complementary negative strand, the antigenomic RNA, that is used as a template for the synthesis of many copies of the positive-sense ssRNA genome. The production of replication proteins by positive-sense ssRNA viruses is different from the production by DNA viruses. Thus, the incoming RNA genome can bind directly to ribosomes and be translated in full or in part without the need for any prior transcription. Interestingly, coronaviruses have been shown to possess an exceptionally large genome and employ a complex genome expression strategy (reviewed in [216]). Thus, many of the coronavirus proteins expressed in the infected cell contribute to the coronavirus–host interplay, for example, by interacting with the host cell to establish an optimal environment for coronavirus replication.
2.7.5.5 Assembly, Maturation, and Release After de novo synthesis of the viral genome and viral proteins, formation of an infectious virion develops that requires assembly of the capsid, envelopment by a membrane (if enveloped), and packaging of the NA genome within. The location of virion assembly can occur within the nucleus of the cell, at the plasma membrane,
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or at a variety of cellular organelle membranes, such as the Golgi complex. Most nonenveloped DNA viruses assemble their nucleocapsid in the nucleus, whereby viral proteins are imported through nuclear pores to reach the site of assembly. Intranuclearly localized and accumulated viruses are usually released only when the cell eventually lyses (see below). On the other hand, enveloped viruses derived from the plasma membrane usually assemble at this location again (for further reading, also see [184, 207, 217, 218]). After the NA genome and viral proteins are packaged within the assembled capsid, virus replication proceeds to maturation of an infectious virus particle that is finally released as a virion into the extracellular environment, where it resumes its infectious replication cycle in new cells. Mechanistically, there are two methods of virions’ release: budding or lysis. Viruses can bud from any of the membrane systems within the cell, including the rough ER, Golgi apparatus, or even the nuclear envelope. In this case, the virions leave the cell by exocytosis. However, enveloped viruses, which usually assemble on the inside layer of the plasma membrane, most often embed their envelope proteins into and bud at the plasma membrane. Conceptually, virus budding can be divided into two stages: (1) membrane deformation, when the membrane is “wrapped” around the assembling virion, and (2) membrane fission, when the bud neck is severed, allowing the virus to leave the cell. Of note, many viruses harness the cellular endosomal sorting complexes required for transport (ESCRT) machinery to effect membrane fission during egress (reviewed in [184, 207, 219, 220]). Nonenveloped viruses can also leave the cell via exocytosis; however, many such human viruses are released through cell lysis. Indeed, release by lysis is the result of RCD of an infected host cell. This cell death is executed by the so-called lytic viruses, which disrupt the plasma membrane and cause lysis or bursting of the cell (for further reading, also see [184, 207, 220]). As will be outlined in the following chapters several times, such virus-induced subroutines of RCD serve as major sources of DAMPs in viral infections (as also in infections in general). A good example of mechanisms of assembly → budding → release is again the IAV (for reviews, see [179, 183, 189, 214]). As mentioned, the protein synthesis of IAV depends on the translation machinery of the host cell. Following nuclear export, the translation of the viral mRNAs is divided between cytosolic ribosomes (for polymerase acidic protein [PA], polymerase basic protein 1 [PB1], PB2, NP, and matrix protein 1 [M1]) and ER-associated ribosomes for the membrane proteins (HA, neuraminidase [NA], and M2), which ultimately compose the viral envelope. Once synthesized, the membrane proteins oligomerize and are transported from the ER via the trans-Golgi network (TGN) to the apical plasma membrane and ultimately assembled into virus particles. The subsequent processes of budding and release provide the final exit of the infectious virion from the cell.
2.7.5.6 Life Cycle of the SARS-CoV-2 (here, Delta Variant) Of note, the current highly actual SARS-CoV-2 virus is a typical enveloped positive- sense ssRNA betacoronavirus that is briefly highlighted here (reviewed in depth in [175, 176, 178, 221–224]). The coronavirus virion is composed of four structural
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proteins referred to as nucleocapsid (N), S, envelope (E), membrane (M) (Fig. 2.10), and 16 nonstructural proteins (Nsps) required for viral replication, whereby Nsp1 mediates RNA processing and replication, Nsp2 modulates the survival signaling transcriptional pathway of host cell, and Nsp3 is believed to separate the translated protein. Attachment → Penetration/Fusion → Uncoating of SARS-CoV-2 Notably, the transmembrane trimeric spike (S) glycoprotein (a typical example of a viral adhesin) protrudes from the host-derived viral surface envelope and provides specificity for cellular entry receptors. The receptor-binding domain (RBD) of the spike glycoprotein of SARS-CoV-2 is recognized by and binds specifically to the cell surface receptor ACE2, thereby mediating virus entry into human cells (Figs. 2.10 and 2.13). Consequently, RBD has been recognized as an attractive antiviral key target for vaccines, antiviral agents, and monoclonal antibodies. Importantly, the S protein is subsequently cleaved by host proteases to produce two functional subunits responsible for binding to the host cell receptor (N-terminal S1 subunit) and fusion of the viral and cellular membranes (C-terminal S2 subunit). In the pre-fusion state, the S1 subunit stabilizes the entire S protein trimer and protects the S2 protein from undergoing conformational change in advance. After binding to ACE2, the S2 subunit is exposed and undergoes a conformational change from a pre-fusion to a post-fusion state. Therefore, binding to the ACE2 receptor is essential for viral infection [222, 223]. More precisely, a 3.5-angstrom-resolution cryo-electron microscopy study revealed that RBD, to engage a host cell receptor, undergoes conformational movements like a hinge, resulting in the hide or exposure of the determinants of receptor binding [225]. As outlined by the authors [225], these two states are referred to as the “down” conformation and the “up” conformation, where “down” corresponds to the receptor-inaccessible state and “up” corresponds to the receptor-accessible state. Because of the indispensable function of the S protein, it represents a target for antibody-mediated neutralization, and characterization of the prefusion S structure would provide atomic-level information to guide vaccine design and development. As a consequence of ACE2 binding, proteolytic cleavage of the viral S glycoprotein by the host cellular serine transmembrane serine protease 2 (TMPRSS2) [226] or endosomal cysteine proteases cathepsins B and L (CTS-B or L) [175], or the calcium-dependent protease furin [227] has been recognized as a vital step to induce or promote host cellular or endosomal membrane fusion and virus infection (Fig. 2.13). Of note, studies on SARS-CoV have shown that TMPRSS2 acts by facilitating the fusion of viral and cell membranes at the target cell surface, whereas endosomal CTS-B/L operates after the virus has been endocytosed, facilitating the fusion of viral and endosomal membranes. However, well-defined endocytic pathways (such as clathrin-dependent endocytosis) for SARS-CoV-2 cell entry have not been described so far (for reviews, see [176, 224, 228, 229]). Following, internalization of SARS-CoV-2 results in uncoating of incoming genomic vRNA and release into the cytoplasm.
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Fig. 2.13 Simplified schematic diagram of a narrative model of SARS-CoV-2 life cycle. The life cycle of SARS-CoV-2 particles begins with the binding of the spike (S) glycoprotein to the cell surface receptor ACE2. Viral entry is promoted within acidified endosomes via the endocytic pathway, which is mediated by conformational changes in the S glycoprotein triggered by ACE2 binding or by membrane fusion of the S glycoprotein after proteolytic processing at the plasma membrane by TMPRSS2. Following viral entry, the release of the incoming genomic RNA into the host cell cytoplasm proceeds to translation of two large open reading frames, ORF1a and ORF1b, which results––via cleavage processes––in generation of nonstructural proteins (nsps, including RdRp). A replication–transcription complex (RTC) is formed based on many of these nsps and anchored in double-membrane vesicles. The complex drives synthesis of the negative-sense genomic RNA that is used as a template to produce positive-sense genomic RNA and subgenomic RNAs. The viral genomic RNA and the nucleocapsid protein are replicated, transcribed, and synthesized in the cytoplasm, while the other viral structural proteins (S, M, and E protein) are transcribed, translated, and then translocated into the rough endoplasmic reticulum membranes, from where they transit through the ER-to-Golgi intermediate compartment. Within this compartment, the S, M, and E proteins interact with the nucleoprotein complex (N-encapsidated, newly produced genomic RNA), leading to assembly and budding into the lumen of secretory vesicular compartments. Finally, the mature virions are released from the host cell into the extracellular space. It is noted that the figure was prepared during the pandemic with the delta variant of SARS-CoV-2. ACE2 angiotensin-converting enzyme 2, DMVs double-membrane vesicles, E envelope protein, ERGIC ER–Golgi intermediate compartment, g genomic, M membrane glycoprotein, N nucleocapsid, nsps nonstructural proteins, ORF open reading frame, RER rough endoplasmic reticulum, RdRps RNA-dependent RNA polymerases, RTC replication–transcription complex, S spike glycoprotein, sg subgenomic, TMPRSS2 transmembrane protease serine subtype 2, + sense positive- sense, − sense negative-sense. (Sources: [176, 177, 221, 224])
Replication, Maturation, and Egress of SARS-CoV-2 In today’s world, the replication strategy of SARS-CoV-2 is of major interest (Fig. 2.13) (reviewed in [176, 177, 221, 224]). After release into the host cell cytoplasm, the positive-sense ssRNA is first translated in host ribosomes (i.e., translation of open reading frames [ORFs], ORF1a and ORF1b) to generate viral replicase polyproteins (pp1a and pp1ab), which are further cleaved by virus-encoded viral
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proteases into a total of 16 small Nsps. Most of these Nsps form a membrane- anchored, highly dynamic protein–RNA machinery, the replication–transcription complex (RTC), residing in double-membrane vesicles (DMVs) within the cell. The RTC includes, as a hallmark, RdRp (Nsp12) that drives SARS-CoV-2 RNA polymerization and other enzymes responsible for vRNA modification and proofreading, whereas the DMVs––reflecting remodeled host ER––serve as replication organelles to produce viral genomic RNA. In the continuous process of genome replication and transcription mediated by RTC, negative-sense RNA intermediates are generated that serve as the templates for the synthesis of positive-sense genomic RNA and an array of subgenomic mRNAs, which encompasses sequences arising from discontinuous transcription and comprises the characteristic nested set of coronavirus mRNAs. Indeed, these newly synthesized genomes are used for translation to generate more Nsps and RTCs or are packaged into new virions. Thus, the nucleocapsid and positive-sense genome RNA are replicated, transcribed, and synthesized in the cytoplasm to become a nucleoprotein complex that is delivered to budding compartments. The structural S, M, and E proteins that are essential for the assembly and release of SARS-CoV-2 are transcribed, then translated, and finally inserted in the rough ER and translocated to the budding sites at the ER–Golgi intermediate compartment (ERGIC) and Golgi region. There, the proteins assemble with N-encapsidated, newly produced genomic RNA resulting in budding into the lumen of secretory vesicular compartments to form mature virions. Finally, the mature virions are secreted from the infected host cell by exocytosis (Fig. 2.13).
2.7.5.7 Concluding Remarks Certainly, in the era of COVID-19, a considerable re-interest in replication cycles of viruses can be noticed. Thus, every step, from initial cell attachment to virion assembly to final maturation and release, has been considered as a specific momentum that potentially could be therapeutically tackled by existing or novel compounds. Plausibly, current research will find out that the machinery of viral replication is much more complex than hitherto assumed. It remains to hope that as targeted research progresses, the mechanisms of replication-triggered DAMP generation will also be elucidated.
2.8 Fungal Infections 2.8.1 Introductory Remarks Fungal infections or mycoses can be regarded as largely neglected diseases of medical history [230]. On the other hand, the story of fungal infections goes back to antiquity. Thus, Hippocrates seemingly wrote already on “aphthae” in 500 BC, which modern mycologists have identified as thrush [231]. Today, ranging from harmless tinea pedis (e.g., the “athlete’s foot”) [232] up to serious life-threatening disorders (e.g., invasive aspergillosis), fungal diseases are known to every physician, whereby the life-threatening form is recognized as a severe clinical problem
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that is predominantly observed in the increasing number of immunocompromised patients [233] (e.g., extensive development of organ transplantation, and the wide use of immunosuppressants and antibiotics in cancer chemotherapy). Indeed, invasive fungal infections represent a significant cause of human diseases that affect over a billion people, with an estimated 1.5 million people dying each year [234]. Notably, fungi are literally everywhere, and their world is diverse, encompassing about 3–6 million species. But only a very few of them (about 150–300) are known to cause disease in humans (reviewed in [235, 236]). A few aspects of their structure, classification, and reproduction are briefly touched on here.
2.8.2 Structure of Fungi Human pathogenic fungi produce a wide range of different types of hyphae, spores, and single-cell yeasts. The filamentous fungi are the most widespread form of growth in fungi, whereby the vegetative unit refers to tube-like hyphae that are capable of differentiating into more complex morphological structures and distinct cell types. When hyphae come together and fuse, they branch into a complicated and expanding patchwork called a mycelium. Hyphae grow at the tip with the help of an organelle called the “Spitzenkörper” (the German word for pointed body), usually associated with the creation of individual cells by forming walls called septa. New hyphae derive from spores on the mycelia. Of note, for a variety of fungi, the phenomenon of dimorphism (a shift between hyphae and unicellular yeast) is critical for the pathogenesis of infectious fungal diseases. Candida is an example of such a dimorphic fungus. It can undergo rapid transformation from the yeast to the hyphal phase in vivo, which partly contributes to its success in invading host tissue (for a comprehensive review, see Riquelme et al. [237]). Importantly, not all species of fungi have cell walls, but in those that do, synthesis and molecular composition of the cell wall are critical for determining the final morphology of fungal elements and, thus, the biology and ecology of each fungal species. Fungal walls are composed of matrix components that are embedded and linked to scaffolds of fibrous load-bearing polysaccharides. Notably, in most fungal species, the inner cell wall consists of a core of polysaccharides, the covalently attached branched β-(1,3) glucan with 3–4% interchain and chitin. Some other fungi have an outer layer of proteins that are highly glycosylated with α and β-linked oligomannosyl residues by mannosyltransferases that use guanosine diphosphate (GDP) mannose as a substrate. These conserved wall structures provide the MAMPs that are critical for recognition of pathogenic fungi by PRMs (see below) (for review, see Gow et al. [238]). Interestingly, another fungal cell wall component, melanin, has been found to play a modulatory role by impeding the capability of host immune cells to respond to specific ligands on A. fumigatus [239].
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2.8.3 Classification of Fungi The classification of fungi has been comprehensively reviewed by Naranjo-Ortiz and Gabaldón [236]. In brief, in general, true fungi share some characteristic traits: (1) the presence of a β-glucan and (generally) chitin cell wall, at least in their spores; (2) existence as a (usually) unicellular organism or grown as a mycelium; (3) the presence of the amino adipic pathway for the biosynthesis of lysine; and (4) the manifestation of flattened mitochondrial cristae. In an earlier time, four major phyla were defined (Chytridiomycota, Zygomycota, Ascomycota, and Basidiomycota), followed by the definition of fungal-like organisms (Rozellidea, Rozellomycota, and Cryptomycota) and Aphelidea, a clade of amoeboid parasitoids of unicellular algae. The updated taxonomy comprises the diversity of known true fungi, divided into nine major lineages: Opisthosporidia, Chytridiomycota, Neocallimastigomycota, Blastocladiomycota, Zoopagomycota, Mucoromycota, Glomeromycota, Ascomycota, and Basidiomycota. For example, from the well-known opportunists causing fungal infection, Aspergillus is a representative of the clade Eurotiomycetes of the phylum of Ascomycota; Candida is a representative of the class Saccharomycotina of the phylum Ascomycota; and Cryptococcus is a representative of the class Tremellomycetes of the phylum Basidiomycota (for more information, see [236]).
2.8.4 Reproduction of Fungi A vital aspect of the success of many fungal pathogens in provoking a disease is their capability to produce infectious propagules by which they can enter and colonize a human host. Usually, such a reproductive process refers to sexual reproduction in which genomes from two organisms are melded into a single cell through the procedure of mating, and then the zygote genomes are divided into progeny cells through the event of meiosis. On the other hand, given the processes of mating and meiosis do not take place, reproduction is termed asexual or clonal reproduction. Interestingly, both processes, asexual and sexual reproduction, are found in fungi. Many filamentous fungi are predominantly haploid throughout their life and begin their life cycle by germination of a meiotic haploid spore to form a mycelium by three integrated processes, including hyphal extension, branching, and vegetative hyphal fusion (also known as anastomosis) [240–242]. In fact, the majority of fungi are believed to reproduce asexually by mitosis via formation of spores called conidia, although fragmentation, fission, and budding are also methods of asexual reproduction in a number of fungi. Spores that are produced asexually (i.e., initiation of the so-called conidiation) are often termed mitospores (spores produced by mitosis). Hence, in the absence of meiosis, other mechanisms associated with the nuclear cycle result in recombination of hereditary properties and genetic variation (for further reading, see [243, 244]).
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Sexual reproduction in fungal pathogens that commonly infect humans, including Aspergillus fumigatus, Candida albicans, and Cryptococcus neoformans/gattii. In general, sexual reproduction occurs by the fusion of two haploid nuclei (karyogamy, i.e., two nuclei of opposite mating types compartmentalized in the penultimate cell). This is followed by meiotic division of the diploid nucleus, which occurs at a different point in the reproductive lifecycle than in other higher eukaryotes. Indeed, the process of fungal reproduction is much more complex, and thus, for further details, the reader is referred to articles cited in [245–247]. Finally, it is further worthwhile to briefly touch here that fungi were observed to reproduce both sexually and asexually as well as parasexually. Parasex is thought to involve chromosome nondisjunction events during mitotic divisions, and the products of parasex are, therefore, aneuploid cells that exhibit a wide variety of ploidies (reviewed in [246]).
2.9 Parasitic Infections 2.9.1 Introductory Remarks Parasites that cause infectious diseases encompass unicellular protozoa and multicellular helminths. The Protozoa are considered to be a subkingdom of the kingdom Protista. More than 50,000 species have been described, most of which are free- living organisms; indeed, protozoa are found in almost every possible habitat. Helminths (or worms), on the other hand, are invertebrate animals that comprise a broad spectrum of different pathogens able to affect human health by causing acute and chronic infections. Here, a few introductory aspects with a focus on damage- inducing properties are briefly touched on.
2.9.2 Protozoans 2.9.2.1 General Remarks Protozoan parasitic infections continue to be an extensive global health concern, causing significant morbidity and mortality worldwide, in particular, fatal diseases, such as malaria [248], visceral leishmaniasis [249], toxoplasmic encephalitis [250], and trypanosomiasis [251]. Indeed, according to recent WHO estimates, protozoan infections cause the second largest number of infectious disease-related deaths. Notably, in developing countries, the lack of vaccination strategies, on one hand, and an increase in drug-resistant parasites, on the other hand, have rendered these infections into a major socio-economic issue. The topic (comprehensively described by Yaeger [252]) is summarized in shortened form in the following by focusing a bit more on the pathogen Plasmodium species, the etiological agents of malaria tropica, the leading cause of death due to the vector-borne infectious disease, claiming 0.5 million lives every year [253] (also addressed in Chap. 5, Sect. 5.6). Indeed, out of more than 120 Plasmodium species
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known to exist, only five cause malarial infections in human beings: Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, and Plasmodium knowlesi [254, 255]. And it is P. falciparum that accounts for the overwhelming majority of mortality, accounting for over 99% of all malaria-associated deaths globally [256].
2.9.2.2 Structure and Classification Protozoa are microscopic unicellular eukaryotes that consist of a nucleus, cytoplasm, and organelles, including the Golgi apparatus, mitochondria, and lysosomes. Possessing a complex internal structure, they perform complex metabolic activities. Some protozoa have structures for propulsion or other types of movement. Malaria is initiated and spread by the injection of Plasmodium sporozoites into the dermis through the bite of infectious Anopheles’ female mosquito during their blood meal [253]. Interestingly, from the point of view of functional and physiologic complexity, a protozoan is more like an animal than a single cell [252]. Based on morphology as revealed by light, electron, and scanning microscopy, the protozoa are currently classified into six phyla. Most species causing human diseases are members of the phyla Sarcomastigophora and Apicomplexa. For example, Trichomonas and Leishmania are members of the phyla Sarcomastigophora, whereas Plasmodium falciparum belongs to the phyla of Apicomplexa (i.e., in the order Haemosporida). Worthwhile to mention here is––as outlined by Yaeger [252]––that, eventually, molecular taxonomy may prove to be a more reliable basis than morphology for protozoan taxonomy. 2.9.2.3 Life Cycle Stages and Reproduction During a protozoan’s life cycle, it usually runs through several stages that differ in structure and activity. The stage of parasitic protozoa that actively feed and reproduce is often called trophozoite, that is, the stage which is usually associated with pathogenesis. A variety of terms are employed for stages in the Apicomplexa. Thus, some stages in the complex asexual and sexual life cycles seen in this phylum are the merozoite (the asexual form resulting from fission of a multinucleate schizont) and sexual stages, such as gametocytes and gametes [252]. For example, the single-cell eukaryote Plasmodium undergoes a complex life cycle that begins when an infected female Anopheles mosquito bites the intermediate host, injecting sporozoites into the host's blood circulation via the mosquito's saliva. The life cycle relies on sophisticated molecular strategies to both survive transmission in mosquito vectors and access the immunoprotective environment of host cells. Thus, Plasmodium is an obligate intracellular parasite of hepatocytes (clinically silent) and erythrocytes (disease causing). It is also worth noting here that the Plasmodium falciparum behaves differently from other human malarial species in that infected red blood cells (RBCs) do not stay in the circulating blood for their entire life cycle. Instead, when young parasites mature from the ring to the trophozoite stage, parasitized RBCs adhere to endothelial cells (ECs) in the microcirculation of various organs (termed sequestration). Hence, for the Plasmodium species, the sporozoites injected into the dermis enter the vasculature and are then
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transported to the liver, where they invade a hepatocyte. They form a so-called parasitophorous vacuole membrane and undergo schizogony; that is, they form trophozoites that mature into schizonts. The schizonts eventually rupture and release tens of thousands of merozoites, which are liberated in packets of merosomes into the vasculature, where they encounter erythrocytes and begin a chronic cycle of asexual schizogony in the bloodstream. Also, a proportion of asexually reproducing merozoites is reprogrammed to undergo (sexual) gametocytogenesis, while in the erythrocyte, the merozoite forms a ring-like structure, becoming a trophozoite (reviewed and illustrated in [253, 257, 258]). The life cycle of P. falciparum is pathogenetically involved in the development of malaria and thus will be addressed again in Chap. 5, Sect. 5.6.
2.9.3 Helminths 2.9.3.1 General Remarks Helminths are the most common parasites infecting humans, usually affecting the poorest and most deprived communities. According to the WHO report 2020, more than 1.5 billion people, or 24% of the world’s population, are infected with soil-transmitted helminth infections, in particular, in tropical and subtropical areas. The main species that infect people are the roundworm (Ascaris lumbricoides), the whipworm (Trichuris trichiura), and hookworms (Necator americanus and Ancylostoma duodenale), with some of these producing chronic infections that can last up to 20 years (see WHO report 2020 [259]). Helminths are transmitted to humans through food, water, soil, arthropod, and molluscan vectors. Helminths can infect every organ and organ system. Prevalent in the intestines, they are found in the liver, lungs, blood, and occasionally the brain and other organs. 2.9.3.2 Structure and Classification Structure and classification of helminths have been comprehensively described by Castro [260] and are summarized in the shortened form here. The clinically relevant groups of these worm-like parasites are separated according to their general external shape and the host organ they inhabit. There are both hermaphroditic and bisexual species. The definitive classification is based on the external and internal morphology of egg, larval, and adult stages. There are two major phyla: the Nematodes (or roundworms) and the Platyhelminthes (or flatworms), subdivided into Trematodes (flukes) and Cestodes (tapeworms). Some additional features can be distinguished: adult and larval roundworms are cylindrical worms; they inhabit intestinal and extraintestinal sites. Adult flukes are leaf-shaped flatworms, while prominent oral and ventral suckers help maintain position in situ. Adult tapeworms are elongated, segmented, hermaphroditic flatworms that inhabit the intestinal lumen. Larval forms, which are cystic or solid, inhabit extraintestinal tissues.
References
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2.9.3.3 Life Cycle Stages and Reproduction Life cycle stages and reproduction processes of helminths vary among the species and are complex, involving different life stages and infecting different host species in a particular order to complete a single generation (for reviews, see [260, 261]). In brief, Nematodes are usually bisexual, and copulation between a female and a male nematode is usually necessary for fertilization. Trematodes are hermaphroditic, with both male and female reproductive organs in the same individual. The schistosomes are bisexual flukes that infect humans. Flukes pass through several larval stages (e.g., eggs → larvae) before attaining adulthood. Tapeworms are also hermaphroditic; however, they differ from flukes in the mechanism of egg deposition.
2.10 Outlook This chapter reflects a rough and short introductory run through some aspects of the broad spectrum of infections by first focusing on some modern notions on the pathogenesis of infectious diseases, followed by a cursory description of some genuine characteristics of pathogens. In light of the danger/injury model and in the “spirit” of the Red Queen paradigm, a speculative and tentative model is presented, suggesting an evolutionary arms race between pathogens that have evolved virulence factors to infect a host and survive and replicate in it, and the host that has evolved DAMPs and DAMP-mediated defense responses to overcome the infection caused by pathogens. Accordingly, in the subsequent chapters, the pathogenesis of infectious diseases is mainly seen “through the glasses of the danger/injury model in Immunology” by focusing on the pathogenetic role of DAMPs in those disorders. For in-depth information on infections and infectious diseases, the reader is referred to the relevant respective handbooks, such as Bergey’s Manual of Systematic Bacteriology, Vols. 1–5 (Vol. 1 [262–266]), and other competent articles, e.g., cited in [112–114, 267–271].
References 1. Land WG. Damage-associated molecular patterns in human diseases. Volume 1: injury-induced innate immune responses. Cham: Springer; 2018. https://doi. org/10.1007/978-3-319-78655-1. 2. Vonaesch P, Anderson M, Sansonetti PJ. Pathogens, microbiome and the host: emergence of the ecological Koch’s postulates. FEMS Microbiol Rev. 2018;42:273–92. Available from https://academic.oup.com/femsre/article/42/3/273/4794944. 3. Bull JJ, Lauring AS. Theory and empiricism in virulence evolution. PLoS Pathog. 2014;10:e1004387. https://doi.org/10.1371/journal.ppat.1004387. 4. Geoghegan JL, Holmes EC. The phylogenomics of evolving virus virulence. Nat Rev Genet. 2018;19:756–69. Available from http://www.nature.com/articles/s41576-018-0055-5. 5. Koch RI. Die Aetiologie der Tuberculose. (Nach einem in der physiologischen Gesellschaft zu Berlin am 24. März er, gehaltenen Vortrage). Fortschr Med. 1982;100:539. Available from https://edoc.rki.de/handle/176904/5163.
94
2 Infectious Agents: From the Red Queen Paradigm to Some of Their Genuine Traits
6. Kaufmann SHE, Schaible UE. 100th anniversary of Robert Koch’s nobel prize for the discovery of the tubercle bacillus. Trends Microbiol. 2005;13:469–75. Available from https:// linkinghub.elsevier.com/retrieve/pii/S0966842X05002027. 7. Van Valen L. A new evolutionary law. Evolv Theory. 1973;1:1–30. Available from https:// www.mn.uio.no/cees/english/services/van-valen/evolutionary-theory/volume-1/vol-1-no-1- pages-1-30-l-van-valen-a-new-evolutionary-law.pdf. 8. Carroll L. Through the looking-glass. 1872. Available from https://www.amazon.de/ Through-Looking-Glass-Illustrated-Facsimile-Omegadoc/dp/B088NXZD37. 9. Hibbs J, Young NS. 1 Viruses, virulence and pathogenicity. Baillieres Clin Haematol. 1995;8:1–23. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0950353605802306. 10. Casadevall A, Pirofski L. Host-pathogen interactions: redefining the basic concepts of virulence and pathogenicity. Infect Immun. 1999;67:3703–13. Available from https://iai.asm.org/ content/67/8/3703. 11. Casadevall A, Pirofski L. The damage-response framework of microbial pathogenesis. Nat Rev Microbiol. 2003;1:17–24. Available from http://www.nature.com/articles/nrmicro732. 12. Casadevall A, Pirofski L. Virulence factors and their mechanisms of action: the view from a damage–response framework. J Water Health. 2009;7:2–18. Available from https://iwaponline.com/jwh/article/7/S1/S2/2047/Virulence-factors-and-their-mechanisms-of-action 13. Casadevall A, Pirofski L. Microbiology: ditch the term pathogen. Nature. 2014;516:165–6. Available from http://www.nature.com/articles/516165a. 14. Diard M, Hardt W-D. Evolution of bacterial virulence. FEMS Microbiol Rev. 2017;23:679–97. Available from https://academic.oup.com/femsre/article-abstract/41/5/679/3844166. 15. Cress BF, Englaender JA, He W, Kasper D, Linhardt RJ, Koffas MAG. Masquerading microbial pathogens: capsular polysaccharides mimic host-tissue molecules. FEMS Microbiol Rev. 2014;38:660–97. https://doi.org/10.1111/1574-6976.12056. 16. Figueira R, Holden DW. Functions of the Salmonella pathogenicity island 2 (SPI-2) type III secretion system effectors. Microbiology. 2012;158:1147–61. https://doi.org/10.1099/ mic.0.058115-0. 17. Sun H, Kamanova J, Lara-Tejero M, Galán JE. A family of salmonella type III secretion effector proteins selectively targets the NF-κB signaling pathway to preserve host homeostasis. PLoS Pathog. 2016;12:e1005484. https://doi.org/10.1371/journal.ppat.1005484. 18. Land WG. Damage-associated molecular patterns in human diseases. Vol. 2: danger signals as diagnostics, prognostics, and therapeutic targets. Cham: Springer; 2020. https://doi. org/10.1007/978-3-030-53868-2. 19. Dobzhansky T. Nothing in biology makes sense except in the light of evolution. Am Biol Teach. 1973;35:125–9. Available from https://online.ucpress.edu/abt/article/35/3/125/9833/ Nothing-in-Biology-Makes-Sense-except-in-the-Light. 20. Fumagalli M, Sironi M, Pozzoli U, Ferrer-Admetlla A, Pattini L, Nielsen R. Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution. PLoS Genet. 2011;7:11. https://doi.org/10.1371/annotation/ ca428083-dbcb-476a-956c-d7bb6e317cf7. 21. Srivastava P. Interaction of heat shock proteins with peptides and antigen presenting cells: chaperoning of the innate and adaptive immune responses. Annu Rev Immunol. 2002;20:395–425. https://doi.org/10.1146/annurev.immunol.20.100301.064801. 22. Wallin RPA, Lundqvist A, Moré SH, von Bonin A, Kiessling R, Ljunggren H-G. Heatshock proteins as activators of the innate immune system. Trends Immunol. 2002;23:130–5. Available from https://linkinghub.elsevier.com/retrieve/pii/S1471490601021688. 23. Robert J. Evolution of heat shock protein and immunity. Dev Comp Immunol. 2003;27:449–64. Available from https://linkinghub.elsevier.com/retrieve/pii/S0145305X0200160X. 24. Chen B, Feder ME, Kang L. Evolution of heat-shock protein expression underlying adaptive responses to environmental stress. Mol Ecol. 2018;27:3040–54. https://doi.org/10.1111/ mec.14769.
References
95
25. Sessa L, Bianchi ME. The evolution of High Mobility Group Box (HMGB) chromatin proteins in multicellular animals. Gene. 2007;387:133–40. Available from https://linkinghub. elsevier.com/retrieve/pii/S0378111906005853. 26. Heil M, Land WG. Danger signals - damaged-self recognition across the tree of life. Front Plant Sci. 2014;5:578. https://doi.org/10.3389/fpls.2014.00578/abstract. 27. Heil M, Land WG, Tör M. Editorial: wound recognition across the tree of life. Front Plant Sci. 2016;7:1319. https://doi.org/10.3389/fpls.2016.01319. 28. Leulier F, Lemaitre B. Toll-like receptors — taking an evolutionary approach. Nat Rev Genet. 2008;9:165–78. Available from http://www.nature.com/articles/nrg2303. 29. Brennan JJ, Gilmore TD. Evolutionary origins of toll-like receptor signaling. Mol Biol Evol. 2018;35:1576–87. Available from https://academic.oup.com/mbe/ article/35/7/1576/4953722. 30. Nie L, Cai S-Y, Shao J-Z, Chen J. Toll-like receptors, associated biological roles, and signaling networks in non-mammals. Front Immunol. 2018;9:e01523. https://doi.org/10.3389/ fimmu.2018.01523/full. 31. Sironi M, Cagliani R, Forni D, Clerici M. Evolutionary insights into host–pathogen interactions from mammalian sequence data. Nat Rev Genet. 2015;16:224–36. Available from http://www.nature.com/articles/nrg3905. 32. Tian R, Chen M, Chai S, Rong X, Chen B, Ren W, et al. Divergent selection of pattern recognition receptors in mammals with different ecological characteristics. J Mol Evol. 2018;86:138–49. https://doi.org/10.1007/s00239-018-9832-1. 33. Brockhurst MA, Chapman T, King KC, Mank JE, Paterson S, Hurst GDD. Running with the red queen: the role of biotic conflicts in evolution. Proc R Soc B Biol Sci. 2014;281:20141382. https://doi.org/10.1098/rspb.2014.1382. 34. Strotz LC, Simões M, Girard MG, Breitkreuz L, Kimmig J, Lieberman BS. Getting somewhere with the red queen: chasing a biologically modern definition of the hypothesis. Biol Lett. 2018;14:20170734. https://doi.org/10.1098/rsbl.2017.0734. 35. Lacey CA, Miao EA. Programmed cell death in the evolutionary race against bacterial virulence factors. Cold Spring Harb Perspect Biol. 2020;12:a036459. https://doi.org/10.1101/ cshperspect.a036459. 36. Casadevall A, Pirofski L. What is a host? Attributes of individual susceptibility. Infect Immun. 2017;86:17. https://doi.org/10.1128/IAI.00636-17. 37. Armstrong D. History of opportunistic infection in the immunocompromised host. Clin Infect Dis. 1993;17:318–21. Available from http://academic.oup.com/cid/article/17/Supplement_2/ S318/307260/History-of-Opportunistic-Infection-in-the. 38. Roden AC, Schuetz AN. Histopathology of fungal diseases of the lung. Semin Diagn Pathol. 2017;34:530–49. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0740257017300862. 39. Land WG. Role of damage-associated molecular patterns in light of modern environmental research: a tautological approach. Int J Environ Res. 2020;14:583–604. https://doi. org/10.1007/s41742-020-00276-z. 40. Land WG. Role of DAMPs in respiratory virus-induced acute respiratory distress syndrome— with a preliminary reference to SARS-CoV-2 pneumonia. Genes Immun. 2021;22:141–60. Available from http://www.nature.com/articles/s41435-021-00140-w. 41. Moriyama M, Hugentobler WJ, Iwasaki A. Seasonality of respiratory viral infections. Annu Rev Virol. 2020. Available from http://www.ncbi.nlm.nih.gov/pubmed/32196426 42. Croft DP, Zhang W, Lin S, Thurston SW, Hopke PK, Masiol M, et al. The association between respiratory infection and air pollution in the setting of air quality policy and economic change. Ann Am Thorac Soc. 2019;16:321–30. Available from http://www.ncbi.nlm. nih.gov/pubmed/30398895. 43. Kan HD, Chen BH, Fu CW, Yu SZ, Mu L. Relationship between ambient air pollution and daily mortality of SARS in Beijing. Biomed Environ Sci. 2005;18(1):1–4. Available from https://www.ncbi.nlm.nih.gov/pubmed/?term=Relationship+between+ambient+air+pollutio n+and+daily+mortality+of+SARS+in+Beijing.
96
2 Infectious Agents: From the Red Queen Paradigm to Some of Their Genuine Traits
44. Cui Y, Zhang Z-F, Froines J, Zhao J, Wang H, Yu S-Z, et al. Air pollution and case fatality of SARS in the People’s Republic of China: an ecologic study. Environ Health. 2003;2:15. https://doi.org/10.1186/1476-069X-2-15. 45. Sun Z, Thilakavathy K, Kumar SS, He G, Liu SV. Potential factors influencing repeated SARS outbreaks in China. Int J Environ Res Public Health. 2020;17:1633. Available from https://www.mdpi.com/1660-4601/17/5/1633. 46. Casanova J-L, Abel L. The genetic theory of infectious diseases: a brief history and selected illustrations. Annu Rev Genomics Hum Genet. 2013;14:215–43. https://doi.org/10.1146/ annurev-genom-091212-153448. 47. Casanova J-L. Severe infectious diseases of childhood as monogenic inborn errors of immunity. Proc Natl Acad Sci. 2015;112:7128–37. https://doi.org/10.1073/pnas.1521651112. 48. Casanova J-L. Human genetic basis of interindividual variability in the course of infection. Proc Natl Acad Sci. 2015;112:7118–27. https://doi.org/10.1073/pnas.1521644112. 49. Casanova J-L, Abel L. Human genetics of infectious diseases: unique insights into immunological redundancy. Semin Immunol. 2018;36:1–12. Available from https://linkinghub.elsevier.com/retrieve/pii/S1044532317301239 50. Nashef A, Agbaria M, Shusterman A, Lorè NI, Bragonzi A, Wiess E, et al. Dissection of host susceptibility to bacterial infections and its toxins. Methods Mol Biol. 2017;7:551–78. https://doi.org/10.1007/978-1-4939-6427-7_27. 51. Mozzi A, Pontremoli C, Sironi M. Genetic susceptibility to infectious diseases: current status and future perspectives from genome-wide approaches. Infect Genet Evol. 2018;66:286–307. Available from https://linkinghub.elsevier.com/retrieve/pii/S1567134817303349. 52. Mukherjee S, Huda S, Sinha Babu SP. Toll-like receptor polymorphism in host immune response to infectious diseases: a review. Scand J Immunol. 2019;90:12771. https://doi. org/10.1111/sji.12771. 53. Crimi E, Benincasa G, Figueroa-Marrero N, Galdiero M, Napoli C. Epigenetic susceptibility to severe respiratory viral infections: pathogenic and therapeutic implications: a narrative review. Br J Anaesth. 2020. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0007091220305638. 54. Crimi E, Benincasa G, Cirri S, Mutesi R, Faenza M, Napoli C. Clinical epigenetics and multidrug-resistant bacterial infections: host remodelling in critical illness. Epigenetics. 2020;15:1021–34. https://doi.org/10.1080/15592294.2020.1748918. 55. Busslinger M, Tarakhovsky A. Epigenetic control of immunity. Cold Spring Harb Perspect Biol. 2014;6:a019307. https://doi.org/10.1101/cshperspect.a019307. 56. Zhang Q, Cao X. Epigenetic regulation of the innate immune response to infection. Nat Rev Immunol. 2019;19:417–32. Available from http://www.nature.com/articles/ s41577-019-0151-6. 57. Netea MG, Quintin J, van der Meer JWM. Trained immunity: a memory for innate host defense. Cell Host Microbe. 2011;9:355–61. Available from http://linkinghub.elsevier.com/ retrieve/pii/S1931312811001284. 58. Netea MG, Latz E, Mills KHG, O’Neill LAJ. Innate immune memory: a paradigm shift in understanding host defense. Nat Immunol. 2015;16:675–9. 59. Netea MG, Joosten LAB, Latz E, Mills KHG, Natoli G, Stunnenberg HG, et al. Trained immunity: a program of innate immune memory in health and disease. Science. 2016;352:1098. https://doi.org/10.1126/science.aaf1098. 60. Netea MG, Schlitzer A, Placek K, Joosten LAB, Schultze JL. Innate and adaptive immune memory: an evolutionary continuum in the host’s response to pathogens. Cell Host Microbe. 2019;25:13–26. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1931312818306334. 61. Netea MG, Domínguez-Andrés J, Barreiro LB, Chavakis T, Divangahi M, Fuchs E, et al. Defining trained immunity and its role in health and disease. Nat Rev Immunol. 2020;20:375–88. Available from http://www.nature.com/articles/s41577-020-0285-6. 62. Janeway CA, Medzhitov R. Innate immune recognition. Annu Rev Immunol. 2002;20:197–216. https://doi.org/10.1146/annurev.immunol.20.083001.084359.
References
97
63. Land WG. Innate alloimmunity - part 1: innate immunity and host defense. 1st ed. Ankara: Baskent University; 2011. Available from https://www.amazon.com/ Innate-Alloimmunity-Part-Immunity-Defense-ebook/dp/B00W6PJ97M. 64. Silva-Gomes S, Decout A, Nigou J. Pathogen-associated molecular patterns (PAMPs). Encycl Inflamm Dis. 2014;35:1–16. https://doi.org/10.1007/978-3-0348-0620-6_35-1. 65. Mehrbod P, Ande SR, Alizadeh J, Rahimizadeh S, Shariati A, Malek H, et al. The roles of apoptosis, autophagy and unfolded protein response in arbovirus, influenza virus, and HIV infections. Virulence. 2019;10:376–413. https://doi.org/10.1080/21505594.2019.1605803. 66. Maelfait J, Liverpool L, Bridgeman A, Ragan KB, Upton JW, Rehwinkel J. Sensing of viral and endogenous RNA by ZBP1/DAI induces necroptosis. EMBO J. 2017;36:2529–43. https://doi.org/10.15252/embj.201796476. 67. Kanneganti T. Intracellular innate immune receptors: life inside the cell. Immunol Rev. 2020;297:5–12. https://doi.org/10.1111/imr.12912. 68. Fujikura D, Miyazaki T. Programmed cell death in the pathogenesis of influenza. Int J Mol Sci. 2018;19:2065. Available from http://www.mdpi.com/1422-0067/19/7/2065. 69. Mojzsis SJ, Arrhenius G, McKeegan KD, Harrison TM, Nutman AP, Friend CRL. Evidence for life on Earth before 3,800 million years ago. Nature. 1996;384:55–9. Available from http://www.nature.com/articles/384055a0. 70. Knoll AH, Nowak MA. The timetable of evolution. Sci Adv. 2017;3:e1603076. https://doi. org/10.1126/sciadv.1603076. 71. Richardson LA. Evolving as a holobiont. PLoS Biol. 2017;15:e2002168. https://doi. org/10.1371/journal.pbio.2002168. 72. Rosenberg E, Zilber-Rosenberg I. The hologenome concept of evolution after 10 years. Microbiome. 2018;6:78. https://doi.org/10.1186/s40168-018-0457-9. 73. Dominguez-Bello MG, Godoy-Vitorino F, Knight R, Blaser MJ. Role of the microbiome in human development. Gut. 2019;68:1108–14. https://doi.org/10.1136/gutjnl-2018-317503. 74. Opal SM. A brief history of microbiology and immunology. Vaccines A Biogr. 2010;10:31–56. https://doi.org/10.1007/978-1-4419-1108-7_3. 75. Leeuwenhoek A. Observations, communicated to the publisher by Mr. Antony van Leewenhoeck, in a dutch letter of the 9th Octob. 1676. here English’d: concerning little animals by him observed in rain-well-sea- and snow water; as also in water wherein pepper had lain infus. Philos Trans R Soc Lond. 1677;12:821–31. https://doi.org/10.1098/ rstl.1677.0003. 76. Lane N. The unseen world: reflections on Leeuwenhoek (1677) ‘Concerning little animals’. Philos Trans R Soc B Biol Sci. 2015;370:20140344. Available from https://pubmed.ncbi.nlm. nih.gov/25750239/. 77. Smith KA. Louis Pasteur, the father of immunology? Front Immunol. 2012;3:68. https://doi. org/10.3389/fimmu.2012.00068/abstract. 78. Berche P. Louis Pasteur, from crystals of life to vaccination. Clin Microbiol Infect. 2012;18:1–6. Available from https://linkinghub.elsevier.com/retrieve/pii/S1198743X14613550. 79. Amsterdamska O. Bacteriology, historical. Int Encycl Publ Health. 2017;2017:206–9. Available from https://linkinghub.elsevier.com/retrieve/pii/B978012803678500031X. 80. Woese CR, Goldenfeld N. How the microbial world saved evolution from the scylla of molecular biology and the charybdis of the modern synthesis. Microbiol Mol Biol Rev. 2009;73:14–21. Available from https://mmbr.asm.org/content/73/1/14. 81. Fauci AS, Morens DM. The perpetual challenge of infectious diseases. N Engl J Med. 2012;366:454–61. https://doi.org/10.1056/NEJMra1108296. 82. Whitman WB, Coleman DC, Wiebe WJ. Prokaryotes: the unseen majority. Proc Natl Acad Sci. 1998;95:6578–83. https://doi.org/10.1073/pnas.95.12.6578. 83. Fleming A. On the antibacterial action of cultures of a penicillium, with special reference to their use in the isolation of B. influenzae. Clin Infect Dis. 1980;2:129–39. Available from https://academic.oup.com/cid/article-lookup/doi/10.1093/clinids/2.1.129. 84. Lewis K. Platforms for antibiotic discovery. Nat Rev Drug Discov. 2013;12:371–87. Available from http://www.nature.com/articles/nrd3975.
98
2 Infectious Agents: From the Red Queen Paradigm to Some of Their Genuine Traits
85. Tan S, Tatsumura Y. Alexander Fleming (1881–1955): Discoverer of penicillin. Singap Med J. 2015;56:366–7. Available from http://www.smj.org.sg/article/ alexander-fleming-1881-1955-discoverer-penicillin. 86. Lewis K. The science of antibiotic discovery. Cell. 2020;181:29–45. Available from https:// linkinghub.elsevier.com/retrieve/pii/S0092867420302336. 87. Wong H, Eso K, Ip A, Jones J, Kwon Y, Powelson S, et al. Use of ward closure to control outbreaks among hospitalized patients in acute care settings: a systematic review. Syst Rev. 2015;4:152. Available from http://systematicreviewsjournal.biomedcentral.com/ articles/10.1186/s13643-015-0131-2. 88. Munita JM, Arias CA. Mechanisms of antibiotic resistance. Microbiol Spectr. 2016;4:2. Available from https://pubmed.ncbi.nlm.nih.gov/27227291/. 89. Vouga M, Greub G. Emerging bacterial pathogens: the past and beyond. Clin Microbiol Infect. 2016;22:12–21. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1198743X1500909X. 90. Jarrell KF, McBride MJ. The surprisingly diverse ways that prokaryotes move. Nat Rev Microbiol. 2008;6:466–76. Available from http://www.nature.com/articles/nrmicro1900. 91. Hospenthal MK, Costa TRD, Waksman G. A comprehensive guide to pilus biogenesis in Gram-negative bacteria. Nat Rev Microbiol. 2017;15:365–79. Available from http://www. nature.com/articles/nrmicro.2017.40. 92. Kim KW. Electron microscopic observations of prokaryotic surface appendages. J Microbiol. 2017;55:919–26. https://doi.org/10.1007/s12275-017-7369-4. 93. Silhavy TJ, Kahne D, Walker S. The bacterial cell envelope. Cold Spring Harb Perspect Biol. 2010;2:a000414. Available from http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect.a000414. 94. Rajagopal M, Walker S. Envelope structures of gram-positive bacteria. Curr Top Microbiol Immunol. 2015;404:1–44. https://doi.org/10.1007/82_2015_5021. 95. Dörr T, Moynihan PJ, Mayer C. Bacterial cell wall structure and dynamics. Front Microbiol. 2019;10:e02051. https://doi.org/10.3389/fmicb.2019.02051/full. 96. Huang KC, Mukhopadhyay R, Wen B, Gitai Z, Wingreen NS. Cell shape and cell-wall organization in Gram-negative bacteria. Proc Natl Acad Sci. 2008;105:19282–7. https://doi. org/10.1073/pnas.0805309105. 97. Rojas ER, Billings G, Odermatt PD, Auer GK, Zhu L, Miguel A, et al. The outer membrane is an essential load-bearing element in Gram-negative bacteria. Nature. 2018;559:617–21. Available from http://www.nature.com/articles/s41586-018-0344-3. 98. Badrinarayanan A, Le TBK, Laub MT. Bacterial chromosome organization and segregation. Annu Rev Cell Dev Biol. 2015;31:171–99. Available from http://www.annualreviews.org/ doi/10.1146/annurev-cellbio-100814-125211. 99. Joyeux M. Preferential localization of the bacterial nucleoid. Microorganisms. 2019;7:204. Available from https://www.mdpi.com/2076-2607/7/7/204. 100. CLowes RC. Molecular structure of bacterial plasmids. Bacteriol Rev. 1972;36:361–405. Available from https://pubmed.ncbi.nlm.nih.gov/4345849/. 101. di Cenzo GC, Finan TM. The divided bacterial genome: structure, function, and evolution. Microbiol Mol Biol Rev. 2017;81:17. https://doi.org/10.1128/MMBR.00019-17. 102. Schmeing TM, Ramakrishnan V. What recent ribosome structures have revealed about the mechanism of translation. Nature. 2009;461:1234–42. Available from http://www.nature. com/articles/nature08403. 103. Rodnina MV. Translation in prokaryotes. Cold Spring Harb Perspect Biol. 2018;10:a032664. https://doi.org/10.1101/cshperspect.a032664. 104. Shajani Z, Sykes MT, Williamson JR. Assembly of Bacterial Ribosomes. Annu Rev Biochem. 2011;80:501–26. https://doi.org/10.1146/annurev-biochem-062608-160432. 105. Salton MRJ, Kim K. Structure. In: Baron S, editor. Medical microbiology. 4th ed. Galveston: University of Texas Medical Branch at Galveston; 1996. Available from https://www.ncbi. nlm.nih.gov/books/NBK8477/.
References
99
106. Schleifer KH. Classification of bacteria and archaea: past, present and future. Syst Appl Microbiol. 2009;32:533–42. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0723202009001258. 107. Parks DH, Chuvochina M, Waite DW, Rinke C, Skarshewski A, Chaumeil P-A, et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat Biotechnol. 2018;36:996–1004. Available from http://www.nature.com/articles/ nbt.4229. 108. Paul B, Dixit G, Murali TS, Satyamoorthy K. Genome-based taxonomic classification. Genome. 2019;62:45–52. https://doi.org/10.1139/gen-2018-0072. 109. Hugenholtz P, Skarshewski A, Parks DH. Genome-based microbial taxonomy coming of age. Cold Spring Harb Perspect Biol. 2016;8:a018085. https://doi.org/10.1101/cshperspect. a018085. 110. Srivathsan A, Sha JCM, Vogler AP, Meier R. Comparing the effectiveness of metagenomics and metabarcoding for diet analysis of a leaf-feeding monkey (Pygathrix nemaeus). Mol Ecol Resour. 2015;15:250–61. https://doi.org/10.1111/1755-0998.12302. 111. Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy TBK, et al. Minimum information about a single amplified genome (MISAG) and a metagenome- assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol. 2017;35:725–31. Available from http://www.nature.com/articles/nbt.3893. 112. Baron S. Medical microbiology - NCBI bookshelf. 1996. Available from https://www.ncbi. nlm.nih.gov/books/NBK7627/. 113. Bisen P, Debnath M, Prasad G. Microbes: concepts and applications. New York: Wiley- Blackwell; 2012. Available from https://www.wiley.com/en-us/Microbes%3A+Concepts+a nd+Applications-p-9780470905944. 114. Murray P, Rosenthal K, Pfaller M. Medical microbiology. 9th ed. Amsterdam: Elsevier; 2020. Available from https://www.elsevier.com/books/medical-microbiology/murray/978-032367322-8. 115. De La Cal MA, Cerdà E, Abella A, Garcia-Hierro P. Classification of microorganisms according to their pathogenicity. Infect Control Intensive Care Unit. 2012;37:29–40. https://doi. org/10.1007/978-88-470-1601-9_3. 116. Silva MT. Classical labeling of bacterial pathogens according to their lifestyle in the host: inconsistencies and alternatives. Front Microbiol. 2012;3:71. https://doi.org/10.3389/ fmicb.2012.00071/abstract. 117. Casadevall A, Fang FC. The intracellular pathogen concept. Mol Microbiol. 2020;113:541–5. https://doi.org/10.1111/mmi.14421. 118. Woese CR, Fox GE. Phylogenetic structure of the prokaryotic domain: the primary kingdoms. Proc Natl Acad Sci U S A. 1977;74:5088–90. https://doi.org/10.1073/pnas.74.11.5088. 119. Woese CR, Stackebrandt E, Macke TJ, Fox GE. A phylogenetic definition of the major eubacterial taxa. Syst Appl Microbiol. 1985;6:143–51. Available from https://linkinghub. elsevier.com/retrieve/pii/S0723202085800473. 120. Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains archaea, bacteria, and eucarya. Proc Natl Acad Sci U S A. 1990;87:4576–9. https:// doi.org/10.1073/pnas.87.12.4576. 121. Stackebrandt E, Frederiksen W, Garrity GM, Grimont PAD, Kämpfer P, Maiden MCJ, et al. Report of the ad hoc committee for the re-evaluation of the species definition in bacteriology. Int J Syst Evol Microbiol. 2002;52:1043–7. https://doi.org/10.1099/00207713-52-3-1043. 122. Rosselló-Mora R, Amann R. The species concept for prokaryotes. FEMS Microbiol Rev. 2001;25:39–67. https://doi.org/10.1111/j.1574-6976.2001.tb00571.x. 123. Clarridge JE. Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases. Clin Microbiol Rev. 2004;17:840–62. Available from https://cmr.asm.org/content/17/4/840. 124. Yarza P, Yilmaz P, Pruesse E, Glöckner FO, Ludwig W, Schleifer K-H, et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences.
100
2 Infectious Agents: From the Red Queen Paradigm to Some of Their Genuine Traits
Nat Rev Microbiol. 2014;12:635–45. Available from http://www.nature.com/articles/ nrmicro3330. 125. Church DL, Cerutti L, Gürtler A, Griener T, Zelazny A, Emler S. Performance and application of 16S rRNA gene cycle sequencing for routine identification of bacteria in the clinical microbiology laboratory. Clin Microbiol Rev. 2020;33:1–74. Available from https://cmr.asm. org/content/33/4/e00053-19. 126. Didelot X, Bowden R, Wilson DJ, Peto TEA, Crook DW. Transforming clinical microbiology with bacterial genome sequencing. Nat Rev Genet. 2012;13:601–12. Available from http:// www.nature.com/articles/nrg3226. 127. Bertelli C, Greub G. Rapid bacterial genome sequencing: methods and applications in clinical microbiology. Clin Microbiol Infect. 2013;19:803–13. Available from https://linkinghub. elsevier.com/retrieve/pii/S1198743X14631979. 128. Fricke WF, Rasko DA. Bacterial genome sequencing in the clinic: bioinformatic challenges and solutions. Nat Rev Genet Nat Rev Genet. 2014;15:49–55. Available from http://www. nature.com/articles/nrg3624. 129. Chun J, Rainey FA. Integrating genomics into the taxonomy and systematics of the Bacteria and Archaea. Int J Syst Evol Microbiol. 2014;64:316–24. https://doi.org/10.1099/ ijs.0.054171-0. 130. Garrity GM. A New genomics-driven taxonomy of bacteria and archaea: are we there yet? J Clin Microbiol. 2016;54:1956–63. Available from https://jcm.asm.org/content/54/8/1956. 131. Tagini F, Greub G. Bacterial genome sequencing in clinical microbiology: a pathogen- oriented review. Eur J Clin Microbiol Infect Dis. 2017;36:2007–20. https://doi.org/10.1007/ s10096-017-3024-6. 132. Gu W, Miller S, Chiu CY. Clinical metagenomic next-generation sequencing for pathogen detection. Annu Rev Pathol Mech Dis. 2019;14:319–38. Available from https://www.annualreviews.org/doi/10.1146/annurev-pathmechdis-012418-012751. 133. Mitchell SL, Simner PJ. Next-generation sequencing in clinical microbiology: are we there yet? Clin Lab Med. 2019;39:405–18. Available from https://linkinghub.elsevier.com/retrieve/ pii/S0272271219300307. 134. Gołębiewski M, Tretyn A. Generating amplicon reads for microbial community assessment with next-generation sequencing. J Appl Microbiol. 2020;128:330–54. https://doi. org/10.1111/jam.14380. 135. Janda JM. Proposed nomenclature or classification changes for bacteria of medical importance: taxonomic update 4. Diagn Microbiol Infect Dis. 2019;94:205–8. Available from https://linkinghub.elsevier.com/retrieve/pii/S0732889318306837. 136. Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci U S A. 1977;74:5463–7. https://doi.org/10.1073/pnas.74.12.5463. 137. Maxam AM, Gilbert W. A new method for sequencing DNA. Proc Natl Acad Sci U S A. 1977;74:560–4. https://doi.org/10.1073/pnas.74.2.560. 138. Fleischmann R, Adams M, White O, Clayton R, Kirkness E, Kerlavage A, et al. Whole- genome random sequencing and assembly of Haemophilus influenzae Rd. Science. 1995;269:496–512. https://doi.org/10.1126/science.7542800. 139. Deurenberg RH, Bathoorn E, Chlebowicz MA, Couto N, Ferdous M, García-Cobos S, et al. Application of next generation sequencing in clinical microbiology and infection prevention. J Biotechnol. 2017;243:16–24. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0168165616316686. 140. Popovich KJ, Snitkin ES. Whole genome sequencing—implications for infection prevention and outbreak investigations. Curr Infect Dis Rep. 2017;19:15. https://doi.org/10.1007/ s11908-017-0570-0. 141. Ellington MJ, Ekelund O, Aarestrup FM, Canton R, Doumith M, Giske C, et al. The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee. Clin Microbiol Infect. 2017;23:2–22. Available from https://linkinghub.elsevier.com/retrieve/pii/S1198743X16305687
References
101
142. Rossen JWA, Friedrich AW, Moran-Gilad J. Practical issues in implementing whole-genome- sequencing in routine diagnostic microbiology. Clin Microbiol Infect. 2018;2018:355–60. Available from https://pubmed.ncbi.nlm.nih.gov/29117578/. 143. Balloux F, Brønstad Brynildsrud O, van Dorp L, Shaw LP, Chen H, Harris KA, et al. From theory to practice: translating whole-genome sequencing (WGS) into the clinic. Trends Microbiol. 2018;26:1035–48. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0966842X18301768. 144. O’Donnell M, Langston L, Stillman B. Principles and concepts of DNA replication in bacteria, archaea, and eukarya. Cold Spring Harb Perspect Biol. 2013;5:a010108. Available from http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect.a010108. 145. Haeusser DP, Margolin W. Splitsville: structural and functional insights into the dynamic bacterial Z ring. Nat Rev Microbiol. 2016;14:305–19. Available from http://www.nature. com/articles/nrmicro.2016.26. 146. Skarstad K, Katayama T. Regulating DNA replication in bacteria. Cold Spring Harb Perspect Biol. 2013;5:a012922. https://doi.org/10.1101/cshperspect.a012922. 147. Oakley AJ. A structural view of bacterial DNA replication. Protein Sci. 2019;28:990–1004. https://doi.org/10.1002/pro.3615. 148. Chodavarapu S, Kaguni JM. Replication initiation in bacteria. Enzyme. 2016;2016:1–30. Available from https://linkinghub.elsevier.com/retrieve/pii/S1874604716300038. 149. Bleichert F, Botchan MR, Berger JM. Mechanisms for initiating cellular DNA replication. Science. 2017;355:6317. https://doi.org/10.1126/science.aah6317. 150. Gowrishankar J. End of the beginning: elongation and termination features of alternative modes of chromosomal replication initiation in bacteria. PLoS Genet. 2015;11:e1004909. https://doi.org/10.1371/journal.pgen.1004909. 151. Lewis JS, Jergic S, Dixon NE. The E. coli DNA replication fork. Enzymes. New York: Academic; 2016. p. 31–88. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1874604716300099. 152. Dimude J, Midgley-Smith S, Stein M, Rudolph C. Replication termination: containing fork fusion-mediated pathologies in Escherichia coli. Gene. 2016;7:40. Available from http:// www.mdpi.com/2073-4425/7/8/40. 153. Dewar JM, Walter JC. Mechanisms of DNA replication termination. Nat Rev Mol Cell Biol. 2017;18:507–16. Available from http://www.nature.com/articles/nrm.2017.42. 154. Ribet D, Cossart P. How bacterial pathogens colonize their hosts and invade deeper tissues. Microbes Infect. 2015;17:173–83. Available from https://linkinghub.elsevier.com/retrieve/ pii/S1286457915000179. 155. Checroun C, Wehrly TD, Fischer ER, Hayes SF, Celli J. Autophagy-mediated reentry of Francisella tularensis into the endocytic compartment after cytoplasmic replication. Proc Natl Acad Sci U S A. 2006;103:14578–83. https://doi.org/10.1073/pnas.0601838103. 156. Fredlund J, Enninga J. Cytoplasmic access by intracellular bacterial pathogens. Trends Microbiol. 2014;22:128–37. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0966842X14000043. 157. Knodler LA. Salmonella enterica: living a double life in epithelial cells. Curr Opin Microbiol. 2015;23:23–31. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1369527414001581. 158. Eisenreich W, Rudel T, Heesemann J, Goebel W. How viral and intracellular bacterial pathogens reprogram the metabolism of host cells to allow their intracellular replication. Front Cell Infect Microbiol. 2019;9:42. https://doi.org/10.3389/fcimb.2019.00042/full. 159. Ivanovsky D. Ueber die Mosaikkrankheit der Tabakspflanze. 35, 67–70 English translation: Ivanovsky, D. (1942) Concerning the mosaic disease of tobacco. Phytopathol. Classics 7, 25–30. St Petersb Acad Imp Sci Bull. 1892;35:67–70. 160. Beijerinck M. Ueber ein Contagium vivum fluidum als Ursache der Fleckenkrankheit der Tabaksblätter. Amsterdam: Johannes Müller; 1898. Available from https://www.dwc.knaw. nl/DL/publications/PU00011860.
102
2 Infectious Agents: From the Red Queen Paradigm to Some of Their Genuine Traits
161. Beijerinck M. Über ein contagium vivum fluidum als Ursache der Fleckenkrankheit der Tabaksblätter. (Eng. translation: Concerning a contagium vivum fluidum as cause of the spot disease of tobacco leaves. Phytopath Classics 7 (1942): 33–54). Verh Kon Akad Wetensch. 1898;65:3–21. 162. Loeffler F, Frosch P. Berichte (I–III) der Kommission zur Erforschung der Maul-und Klauenseuche bei dem Institut für Infektionkrankheiten in Berlin. Centrbl Bakt Parasitenk. 1898;23:371–91. 163. Stanley WM. Isolation of a crystalline protein possessing the properties of tobacco-mosaic virus. Science. 1935;81:644–5. Available from https://www.sciencemag.org/lookup/doi/1. 164. WHO Director-General’s opening remarks at the media briefing on COVID-19 11 March 2020. Available from https://www.who.int/dg/speeches/detail/ who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19-11-march-2020. 165. Carrasco-Hernandez R, Jácome R, López Vidal Y, Ponce de León S. Are RNA viruses candidate agents for the next global pandemic? A review. ILAR J. 2017;58:343–58. Available from https://academic.oup.com/ilarjournal/article/58/3/343/4107390. 166. Weber DJ, Rutala WA, Fischer WA, Kanamori H, Sickbert-Bennett EE. Emerging infectious diseases: focus on infection control issues for novel coronaviruses (severe acute respiratory syndrome-CoV and middle east respiratory syndrome-CoV), hemorrhagic fever viruses (Lassa and Ebola), and highly pathogenic avian influenza vi. Am J Infect Control. 2016;44:91–100. https://doi.org/10.1016/j.ajic.2015.11.018. 167. Koonin EV, Krupovic M, Yutin N. Evolution of double-stranded DNA viruses of eukaryotes: from bacteriophages to transposons to giant viruses. Ann N Y Acad Sci. 2015;1341:10–24. https://doi.org/10.1111/nyas.12728. 168. Suttle CA. Viruses in the sea. Nature. 2005;437:356–61. Available from http://www.nature. com/articles/nature04160. 169. Cobián Güemes AG, Youle M, Cantú VA, Felts B, Nulton J, Rohwer F. Viruses as winners in the game of life. Annu Rev Virol. 2016;3:197–214. https://doi.org/10.1146/ annurev-virology-100114-054952. 170. Koonin EV, Dolja VV, Krupovic M, Varsani A, Wolf YI, Yutin N, et al. Global organization and proposed megataxonomy of the virus world. Microbiol Mol Biol Rev. 2020;84:19. Available from https://mmbr.asm.org/content/84/2/e00061-19. 171. Rossmann MG. Structure of viruses: a short history. Q Rev Biophys. 2013;46:133–80. Available from https://www.cambridge.org/core/product/identifier/S0033583513000012/ type/journal_article. 172. Spriggs CC, Harwood MC, Tsai B. How non-enveloped viruses hijack host machineries to cause infection. Adv Virus Res. 2019;104:97–122. Available from https://linkinghub.elsevier. com/retrieve/pii/S0065352719300120. 173. Baltimore D. Expression of animal virus genomes. Bacteriol Rev. 1971;35:235–41. https:// doi.org/10.1128/mmbr.35.3.235-241.1971. 174. Agol VI. Towards the system of viruses. Biosystems. 1974;6:113–32. Available from https:// linkinghub.elsevier.com/retrieve/pii/0303264774900033. 175. Ou X, Liu Y, Lei X, Li P, Mi D, Ren L, et al. Characterization of spike glycoprotein of SARS-CoV-2 on virus entry and its immune cross-reactivity with SARS-CoV. Nat Commun. 2020;11:1620. Available from http://www.nature.com/articles/s41467-020-15562-9. 176. Duan L, Zheng Q, Zhang H, Niu Y, Lou Y, Wang H. The SARS-CoV-2 spike glycoprotein biosynthesis, structure, function, and antigenicity: implications for the design of spike- based vaccine immunogens. Front Immunol. 2020;11:576622. https://doi.org/10.3389/ fimmu.2020.576622/full. 177. Romano M, Ruggiero A, Squeglia F, Maga G, Berisio R. A structural view of SARS- CoV-2 RNA replication machinery: RNA synthesis, proofreading and final capping. Cell. 2020;9:1267. Available from https://www.mdpi.com/2073-4409/9/5/1267. 178. Ellis P, Somogyvári F, Virok DP, Noseda M, McLean GR. Decoding Covid-19 with the SARS-CoV-2 genome. Curr Genet Med Rep. 2021;9:1–12. https://doi.org/10.1007/ s40142-020-00197-5.
References
103
179. Dou D, Revol R, Östbye H, Wang H, Daniels R. Influenza A virus cell entry, replication, virion assembly and movement. Front Immunol. 2018;9:e01581. https://doi.org/10.3389/ fimmu.2018.01581/full. 180. Pflug A, Lukarska M, Resa-Infante P, Reich S, Cusack S. Structural insights into RNA synthesis by the influenza virus transcription-replication machine. Virus Res. 2017;234:103–17. Available from https://linkinghub.elsevier.com/retrieve/pii/S0168170216307821. 181. McGeoch D, Fellner P, Newton C. Influenza virus genome consists of eight distinct RNA species. Proc Natl Acad Sci U S A. 1976;73:3045–9. https://doi.org/10.1073/pnas.73.9.3045. 182. Palese P, Schulman JL. Mapping of the influenza virus genome: identification of the hemagglutinin and the neuraminidase genes. Proc Natl Acad Sci U S A. 1976;73:2142–6. https:// doi.org/10.1073/pnas.73.6.2142. 183. Ritchey MB, Palese P, Schulman JL. Mapping of the influenza virus genome. III. Identification of genes coding for nucleoprotein, membrane protein, and nonstructural protein. J Virol. 1976;20:307–13. Available from http://www.ncbi.nlm.nih.gov/pubmed/985644. 184. Louten J. Virus replication. Essent Hum Virol. 2016;2016:49–70. Available from https://linkinghub.elsevier.com/retrieve/pii/B9780128009475000041. 185. Ryu WS. Molecular virology of human pathogenic viruses; DNA viruses. In: Molecular virology of human pathogenic viruses. Amsterdam: Elsevier; 2016. https://doi.org/10.1016/ c2013-0-15172-0. 186. Schmid M, Speiseder T, Dobner T, Gonzalez RA. DNA virus replication compartments. J Virol. 2014;88:1404–20. Available from https://jvi.asm.org/content/88/3/1404. 187. Grove J, Marsh M. The cell biology of receptor-mediated virus entry. J Cell Biol. 2011;195:1071–82. Available from https://rupress.org/jcb/article/195/7/1071/54877/ The-cell-biology-of-receptormediated-virus. 188. de Graaf M, Fouchier RAM. Role of receptor binding specificity in influenza A virus transmission and pathogenesis. EMBO J. 2014;33:823–41. https://doi.org/10.1002/embj.201387442. 189. Sato R, Okura T, Kawahara M, Takizawa N, Momose F, Morikawa Y. Apical trafficking pathways of influenza A virus HA and NA via Rab17- and Rab23-positive compartments. Front Microbiol. 2019;10:e01857. https://doi.org/10.3389/fmicb.2019.01857/full. 190. Komala Sari T, Gianopulos KA, Weed DJ, Schneider SM, Pritchard SM, Nicola AV. Herpes simplex virus glycoprotein C regulates low-pH entry. mSphere. 2020;5:e00826. Available from https://msphere.asm.org/content/5/1/e00826-19. 191. Douam F, Lavillette D, Cosset F-L. The mechanism of HCV entry into host cells. Prog Mol Biol Transl Sci. 2015;129:63–107. Available from https://linkinghub.elsevier.com/retrieve/ pii/S1877117314000040. 192. Li F. Structure, function, and evolution of coronavirus spike proteins. Annu Rev Virol. 2016;3:237–61. https://doi.org/10.1146/annurev-virology-110615-042301. 193. Marsh M, Helenius A. Virus entry: open sesame. Cell. 2006;124:729–40. Available from https://linkinghub.elsevier.com/retrieve/pii/S0092867406001826. 194. Maginnis MS. Virus-receptor interactions: the key to cellular invasion. J Mol Biol. 2018;430:2590–611. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0022283618306302. 195. Gianni T, Cerretani A, DuBois R, Salvioli S, Blystone SS, Rey F, et al. Herpes simplex virus glycoproteins H/L bind to cells independently of αVβ3 integrin and inhibit virus entry, and their constitutive expression restricts infection. J Virol. 2010;84:4013–25. Available from https://jvi.asm.org/content/84/8/4013. 196. Yamauchi Y, Greber UF. Principles of virus uncoating: cues and the snooker ball. Traffic. 2016;17:569–92. Available from http://doi.wiley.com/10.1111/tra.12387. 197. Dimitrov DS. Virus entry: molecular mechanisms and biomedical applications. Nat Rev Microbiol. 2004;2:109–22. Available from http://www.nature.com/articles/nrmicro817. 198. Mercer J, Schelhaas M, Helenius A. Virus entry by endocytosis. Annu Rev Biochem. 2010;79:803–33. https://doi.org/10.1146/annurev-biochem-060208-104626. 199. Kalia M, Jameel S. Virus entry paradigms. Amino Acids. 2011;41:1147–57. https://doi. org/10.1007/s00726-009-0363-3.
104
2 Infectious Agents: From the Red Queen Paradigm to Some of Their Genuine Traits
200. Helenius A. Virus entry: looking back and moving forward. J Mol Biol. 2018;430:1853–62. Available from https://linkinghub.elsevier.com/retrieve/pii/S0022283618303097. 201. Rust MJ, Lakadamyali M, Zhang F, Zhuang X. Assembly of endocytic machinery around individual influenza viruses during viral entry. Nat Struct Mol Biol. 2004;11:567–73. Available from http://www.nature.com/articles/nsmb769. 202. Fujioka Y, Tsuda M, Nanbo A, Hattori T, Sasaki J, Sasaki T, et al. A Ca2+-dependent signalling circuit regulates influenza A virus internalization and infection. Nat Commun. 2013;4:2763. Available from http://www.nature.com/articles/ncomms3763. 203. Milewska A, Nowak P, Owczarek K, Szczepanski A, Zarebski M, Hoang A, et al. Entry of human coronavirus NL63 into the cell. J Virol. 2017;92:17. Available from https://jvi.asm. org/content/92/3/e01933-17. 204. Banerjee I, Miyake Y, Nobs SP, Schneider C, Horvath P, Kopf M, et al. Influenza A virus uses the aggresome processing machinery for host cell entry. Science. 2014;346:473–7. https:// doi.org/10.1126/science.1257037. 205. Kilcher S, Mercer J. DNA virus uncoating. Virology. 2015;479–480:578–90. Available from https://linkinghub.elsevier.com/retrieve/pii/S0042682215000367. 206. Harutyunyan S, Kumar M, Sedivy A, Subirats X, Kowalski H, Köhler G, et al. Viral uncoating is directional: exit of the genomic RNA in a common cold virus starts with the poly-(A) tail at the 3′-end. PLoS Pathog. 2013;9:e1003270. https://doi.org/10.1371/journal.ppat.1003270. 207. Burrell CJ, Howard CR, Murphy FA. Virus replication. Med Virol. 2017;2017:39–55. Available from https://linkinghub.elsevier.com/retrieve/pii/B9780123751560000047. 208. Weitzman MD, Fradet-Turcotte A. Virus DNA replication and the host DNA damage response. Annu Rev Virol. 2018;5:141–64. https://doi.org/10.1146/annurev-virology-092917-043534. 209. Weller SK, Coen DM. Herpes simplex viruses: mechanisms of DNA replication. Cold Spring Harb Perspect Biol. 2012;4:a013011. https://doi.org/10.1101/cshperspect.a013011. 210. Modrow S, Falke D, Truyen U, Schätzl H. Viruses with a single-stranded DNA genome. Mol Virol. 2013;2013:875–918. https://doi.org/10.1007/978-3-642-20718-1_20. 211. Malathi VG, Renuka DP. ssDNA viruses: key players in global virome. Virus Dis. 2019;30:3–12. https://doi.org/10.1007/s13337-019-00519-4. 212. Ros C, Bayat N, Wolfisberg R, Almendral J. Protoparvovirus cell entry. Viruses. 2017;9:313. Available from http://www.mdpi.com/1999-4915/9/11/313. 213. Poltronieri P, Sun B, Mallardo M. RNA viruses: RNA roles in pathogenesis, coreplication and viral load. Curr Genomics. 2015;16:327–35. Available from http://www.eurekaselect.com/ openurl/content.php?genre=article&issn=1389-2029&volume=16&issue=5&spage=327. 214. Amorim MJ. A comprehensive review on the interaction between the host GTPase Rab11 and influenza A virus. Front Cell Dev Biol. 2019;6:176. https://doi.org/10.3389/ fcell.2018.00176/full. 215. de Castro Martin IF, Fournier G, Sachse M, Pizarro-Cerda J, Risco C, Naffakh N. Influenza virus genome reaches the plasma membrane via a modified endoplasmic reticulum and Rab11-dependent vesicles. Nat Commun. 2017;8:1396. Available from http://www.nature. com/articles/s41467-017-01557-6. 216. de Wilde AH, Snijder EJ, Kikkert M, van Hemert MJ. Host factors in coronavirus replication. Curr Top Microbiol Immunol. 2017;2017:1–42. https://doi.org/10.1007/82_2017_25. 217. Perlmutter JD, Hagan MF. Mechanisms of virus assembly. Annu Rev Phys Chem. 2015;66:217–39. https://doi.org/10.1146/annurev-physchem-040214-121637. 218. Chelikani V, Ranjan T, Kondabagil K. Revisiting the genome packaging in viruses with lessons from the “giants”. Virology. 2014;466–467:15–26. Available from https://linkinghub. elsevier.com/retrieve/pii/S0042682214002839. 219. Votteler J, Sundquist WI. Virus budding and the ESCRT pathway. Cell Host Microbe. 2013;14:232–41. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1931312813002941. 220. Payne S. Virus interactions with the cell. Viruses. 2017;2017:23–35. https://doi.org/10.1016/ C2014-0-03894-4.
References
105
221. Kumar S, Nyodu R, Maurya VK, Saxena SK. Morphology, genome organization, replication, and pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Singapore: Springer; 2020. p. 23–31. https://doi.org/10.1007/978-981-15-4814-7_3. 222. Wang M-Y, Zhao R, Gao L-J, Gao X-F, Wang D-P, Cao J-M. SARS-CoV-2: structure, biology, and structure-based therapeutics development. Front Cell Infect Microbiol. 2020;10:58269. https://doi.org/10.3389/fcimb.2020.587269/full. 223. Zhu G, Zhu C, Zhu Y, Sun F. Minireview of progress in the structural study of SARS-CoV-2 proteins. Curr Res Microb Sci. 2020;1:53–61. Available from https://linkinghub.elsevier. com/retrieve/pii/S2666517420300079. 224. V’kovski P, Kratzel A, Steiner S, Stalder H, Thiel V. Coronavirus biology and replication: implications for SARS-CoV-2. Nat Rev Microbiol. 2021;19:155–70. Available from http:// www.nature.com/articles/s41579-020-00468-6. 225. Wrapp D, Wang N, Corbett KS, Goldsmith JA, Hsieh CL, Abiona O, et al. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. bioRxiv. bioRxiv. 2020. https://doi. org/10.1126/science.abb2507. 226. Hoffmann M, Kleine-Weber H, Schroeder S, Krüger N, Herrler T, Erichsen S, et al. SARS- CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020;181:271–80. Available from https://linkinghub.elsevier.com/ retrieve/pii/S0092867420302294. 227. Papa G, Mallery DL, Albecka A, Welch LG, Cattin-Ortolá J, Luptak J, et al. Furin cleavage of SARS-CoV-2 spike promotes but is not essential for infection and cell-cell fusion. PLoS Pathog. 2021;17:e1009246. https://doi.org/10.1371/journal.ppat.1009246. 228. Kumar A, Prasoon P, Kumari C, Pareek V, Faiq MA, Narayan RK, et al. SARS-CoV-2-specific virulence factors in COVID-19. J Med Virol. 2021;93:1343–50. https://doi.org/10.1002/ jmv.26615. 229. Glebov OO. Understanding SARS-CoV-2 endocytosis for COVID-19 drug repurposing. FEBS J. 2020;287:3664–71. https://doi.org/10.1111/febs.15369. 230. Rodrigues ML, Nosanchuk JD. Fungal diseases as neglected pathogens: a wake-up call to public health officials. PLoS Negl Trop Dis. 2020;14:e0007964. https://doi.org/10.1371/journal.pntd.0007964. 231. Ainsworth GC. Introduction to the history of medical and veterinary. Mycology. 1986;1986:244. Available from https://books.google.de/books/about/Introduction_to_the_ History_of_Medical_a.html?id=j2adikTWFRMC&redir_esc=y. 232. Ilkit M, Durdu M. Tinea pedis: the etiology and global epidemiology of a common fungal infection. Crit Rev Microbiol. 2015;41:374–88. https://doi.org/10.3109/1040841X.2013.856853. 233. Vallabhaneni S, Mody RK, Walker T, Chiller T. The global burden of fungal diseases. Infect Dis Clin N Am. 2016;30:1–11. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0891552015000938. 234. Bongomin F, Gago S, Oladele R, Denning D. Global and multi-national prevalence of fungal diseases—estimate precision. J Fungi. 2017;3:57. Available from http://www.mdpi. com/2309-608X/3/4/57. 235. Brown GD, Denning DW, Gow NAR, Levitz SM, Netea MG, White TC. Hidden killers: human fungal infections. Sci Transl Med. 2012;4:165. Available from https://stm.sciencemag. org/content/4/165/165rv13. 236. Naranjo-Ortiz MA, Gabaldón T. Fungal evolution: diversity, taxonomy and phylogeny of the fungi. Biol Rev. 2019;94:2101–37. https://doi.org/10.1111/brv.12550. 237. Riquelme M, Aguirre J, Bartnicki-García S, Braus GH, Feldbrügge M, Fleig U, et al. Fungal morphogenesis, from the polarized growth of hyphae to complex reproduction and infection structures. Microbiol Mol Biol Rev. 2018;82:e00068. Available from https://mmbr.asm.org/ content/82/2/e00068-17. 238. Gow NA, et al. The fungal cell wall: structure, biosynthesis, and function. The fungal kingdom. Washington: American Society of Microbiology; 2017. p. 267–92. Available from http://www.asmscience.org/content/book/10.1128/9781555819583.chap12.
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239. Chai LYA, Netea MG, Sugui J, Vonk AG, van de Sande WWJ, Warris A, et al. Aspergillus fumigatus conidial melanin modulates host cytokine response. Immunobiology. 2010;215:915–20. Available from https://linkinghub.elsevier.com/retrieve/pii/S0171298509001661. 240. Glass NL, Jacobson DJ, Shiu PKT. The genetics of hyphal fusion and vegetative incompatibility in filamentous ascomycete fungi. Annu Rev Genet. 2000;34:165–86. https://doi. org/10.1146/annurev.genet.34.1.165. 241. Taylor J, Jacobson D, Fisher M. The evolution of asexual fungi: reproduction, speciation and classification. Annu Rev Phytopathol. 1999;37:197–246. https://doi.org/10.1146/annurev. phyto.37.1.197. 242. Nieuwenhuis BPS, James TY. The frequency of sex in fungi. Philos Trans R Soc B Biol Sci. 2016;371:20150540. https://doi.org/10.1098/rstb.2015.0540. 243. Ojeda-López M, Chen W, Eagle CE, Gutiérrez G, Jia WL, Swilaiman SS, et al. Evolution of asexual and sexual reproduction in the aspergilli. Stud Mycol. 2018;91:37–59. Available from https://linkinghub.elsevier.com/retrieve/pii/S0166061618300344. 244. Gusa A, Jinks-Robertson S. Mitotic recombination and adaptive genomic changes in human pathogenic fungi. Gene. 2019;10:901. Available from https://www.mdpi. com/2073-4425/10/11/901. 245. Heitman J, Carter DA, Dyer PS, Soll DR. Sexual reproduction of human fungal pathogens. Cold Spring Harb Perspect Med. 2014;4:a019281. https://doi.org/10.1101/cshperspect. a019281. 246. Bennett R, Turgeon BG. Fungal sex: the ascomycota. the fungal kingdom. Washington: American Society of Microbiology; 2017. p. 117–45. https://doi. org/10.1128/9781555819583.chap6. 247. Usher J. The mechanisms of mating in pathogenic fungi—a plastic trait. Gene. 2019;10:831. Available from https://www.mdpi.com/2073-4425/10/10/831. 248. Gowda DC, Wu X. Parasite recognition and signaling mechanisms in innate immune responses to malaria. Front Immunol. 2018;9:3006. https://doi.org/10.3389/fimmu.2018.03006/full. 249. Rodrigues V, Cordeiro-da-Silva A, Laforge M, Silvestre R, Estaquier J. Regulation of immunity during visceral Leishmania infection. Parasit Vectors. 2016;9:118. Available from http:// www.parasitesandvectors.com/content/9/1/118. 250. Sasai M, Pradipta A, Yamamoto M. Host immune responses to Toxoplasma gondii. Int Immunol. 2018;30:113–9. Available from https://academic.oup.com/intimm/ article/30/3/113/4835044. 251. Dos-Santos ALA, Carvalho-Kelly LF, Dick CF, Meyer-Fernandes JR. Innate immunomodulation to trypanosomatid parasite infections. Exp Parasitol. 2016;167:67–75. Available from https://linkinghub.elsevier.com/retrieve/pii/S0014489416300959. 252. Yaeger RG. Chap. 77. Protozoa: structure, classification, growth, and development. In: Baron S, editor. Medical microbiology. 4th ed. Galveston: University of Texas Medical Branch at Galveston; 1996. Available from https://www.ncbi.nlm.nih.gov/books/NBK8325/. 253. Cowman AF, Healer J, Marapana D, Marsh K. Malaria: biology and disease. Cell. 2016;167:610–24. Available from https://linkinghub.elsevier.com/retrieve/pii/ S009286741631008X. 254. White NJ. Plasmodium knowlesi: the fifth human malaria parasite. Clin Infect Dis. 2008;46:172–3. 255. Sutherland CJ, Tanomsing N, Nolder D, Oguike M, Jennison C, Pukrittayakamee S, et al. Two nonrecombining sympatric forms of the human malaria parasite plasmodium ovale occur globally. J Infect Dis. 2010;201:1544–50. Available from https://academic.oup.com/ jid/article-lookup/doi/10.1086/652240. 256. Wassmer SC, Grau GER. Severe malaria: what’s new on the pathogenesis front? Int J Parasitol. 2017;47:145–52. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0020751916302107. 257. Miller LH, Ackerman HC, Su X, Wellems TE. Malaria biology and disease pathogenesis: insights for new treatments. Nat Med. 2013;19:156–67. Available from http://www.nature. com/articles/nm.3073.
References
107
258. Maier AG, Matuschewski K, Zhang M, Rug M. Plasmodium falciparum. Trends Parasitol. 2019;35:481–2. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1471492218302484. 259. WHO R. Soil-transmitted helminth infections. 2020. Available from https://www.who.int/ news-room/fact-sheets/detail/soil-transmitted-helminth-infections. 260. Castro GA. Chap. 86. Helminths: structure, classification, growth, and development. In: Baron S, editor. Medical microbiology. 4th ed. Galveston: University of Texas Medical Branch at Galveston; 1996. Available from http://www.ncbi.nlm.nih.gov/pubmed/21413320. 261. Blasco-Costa I, Poulin R. Parasite life-cycle studies: a plea to resurrect an old parasitological tradition. J Helminthol. 2017;91:647–56. Available from https://www.cambridge.org/core/ product/identifier/S0022149X16000924/type/journal_article. 262. Garrity G, Boone DR, Castenholz RW. Bergey’s manual of systematic bacteriology - volume one : the archaea and the deeply branching and phototrophic bacteria. 2nd ed. New York: Springer; 2001. Available from https://www.springer.com/gp/book/9780387987712. 263. Garrity G, Brenner DJ, Krieg NR, Staley JR. Bergey’s manual® of systematic bacteriology volume 2: the proteobacteria. 2nd ed. New York: Springer; 2005. Available from https:// www.springer.com/de/book/9780387241449. 264. Vos P, Garrity G, Jones D, Krieg NR. Bergey’s manual of systematic bacteriology - volume 3: the firmicutes. 2nd ed. New York: Springer; 2009. Available from https://www.springer. com/de/book/9780387950419. 265. Krieg NR, Ludwig W, Whitman W, Hedlund BP. Bergey’s manual of systematic bacteriology—volume 4: the bacteroidetes, spirochaetes, tenericutes (mollicutes), acidobacteria, fibrobacteres, fusobacteria, dictyoglomi, gemmatimonadetes, lentisphaerae, verrucomicrobia, chlamydiae, and planctomycetes. 2nd ed. New York: Springer; 2010. Available from https://www.springer.com/gp/book/9780387950426. 266. Whitman W, Goodfellow M, Kämpfer P, Busse H-J. Bergey’s manual of systematic bacteriology - volume 5: the actinobacteria. 2nd ed. New York: Springer; 2012. Available from https:// www.springer.com/gp/book/9780387950433. 267. Specter S, Hodinka RL, Young SA, Wiedbrauk DL. Clinical virology manual. Washington: American Society of Microbiology; 2009. https://doi.org/10.1128/9781555815974. 268. van Saene HKF, Silvestri L, de la Cal MA, Gullo A. Infection control in the intensive care unit. In: Infect control intensive care unit. 3rd ed. Milano: Springer; 2012. https://doi. org/10.1007/978-88-470-1601-9. 269. Trujillo ME, Dedysh S, DeVos P, Hedlund B, Kämpfer P, Rainey FA, et al. Bergey’s manual of systematics of archaea and bacteria. New York: Wiley; 2015. https://doi. org/10.1002/9781118960608. 270. Tang Y-W, Sails A. Molecular medical microbiology. 2nd ed. New York: Academic Press; 2015. Available from https://www.elsevier.com/books/molecular-medical-microbiology/tan g/978-0-12-397169-2. 271. Flint J, Racaniello J, Rall G, Skalka A, Hatziioannon T. Principles of virology, volume 1: molecular biology. 5th ed. New York: Wiley; 2020. Available from https://www.wiley.com/ en-us/Principles+of+Virology%2C+Volume+1%3A+Molecular+Biology%2C+5th+Edit ion-p-9781683672845.
3
Virulence of Pathogens and the Counteracting Responses of the Host
3.1 Introduction As briefly portrayed in the previous chapter, host–pathogen interactions reflect the classical Red Queen paradigm, in which pathogens are continually evolving new virulence strategies while the host responds with counteracting immune defense mechanisms. In light of the danger/injury theory – and apart from an explanation on genetics ground, a tentative model was insinuated for an evolutionary arms race between pathogens (evolving virulence factors to infect a host) and the host (evolving DAMPs and DAMP-mediated defense responses to overcome the infection). In the following, a closer look should be taken at the virulence factors of the pathogens, on the one hand, and the host defense responses, on the other hand, with the aim of giving more plausibility and credibility to the insinuated analogy between this unique biotic cross-species interaction and the Red Queen hypothesis. Indeed, the motto here is: “From virulence of pathogens to counteracting responses of the host.” Accordingly, the first part of this chapter (Sects. 3.2, 3.3, 3.4, and 3.5) will cover the virulence factors comprising (1) nondamaging molecules such as surface structures (adhesins, invasins, and capsules), which facilitate attachment to host cells, (2) indirectly damaging molecules such as siderophores, which scavenge iron from the host, as well as (3) directly damaging, secreted products such as toxin and enzymes, which degrade host cells or tissues. Intracellular perturbations such as changes in metabolic networks or the molecular pattern caused, for example, by intracellular bacteria and viruses, can also contribute to virulence – as already discussed in the previous chapter. In the second part (Sects. 3.6 and 3.7), the counterbalancing host defense responses are briefly reviewed by focusing on cell-autonomous stress responses and the incidence of RCD as prolific sources of DAMPs emission.
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 W. G. Land, Damage-Associated Molecular Patterns in Human Diseases, https://doi.org/10.1007/978-3-031-21776-0_3
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3.2 Bacterial Virulence 3.2.1 Introductory Remarks Virulence factors are essential tools of pathogenic bacteria for invading the host, causing disease, and evading and subverting the host’s innate/adaptive immune defense responses. Bacterial invaders possess several factors that enable them to enhance their virulence by using a combination of mainly two properties to cause illness: invasiveness, that is, the capability to penetrate into the host and spread, and (2) toxicity, that is, the degree to which they cause cell stress and tissue damage in the host. Here, these various virulence factors are briefly discussed, focusing on their ability to promote the emission of DAMPs.
3.2.2 Nondamaging Bacterial Virulence Factors Paving the Way to Induce Injury 3.2.2.1 General Remarks Nondamaging factors operate particularly during the initiation of bacterial infection. Processes such as adherence, colonization, and biofilm formation are classically promoted by those factors. Typically, however, the host does not perceive these processes as a disease yet. As preparing steps for pathogen-mediated cell stress and tissue injury associated with the emission of DAMPs, these processes are of considerable importance for the virulence potency of bacteria in general. 3.2.2.2 Bacterial Adherence and Host Colonization Upon contaminating the host, bacteria must move to their appropriate site of infection and colonize there. Following this, the bacteria remain adherent at the site of colonization and now begin invading the host system in order to initiate the disease process. To reach this goal, pathogenic bacteria have evolved various molecular strategies to adhere to epithelia of the respiratory, intestinal, and urogenital mucosa, as well as to proliferate at their surface to colonize these organs successfully. Indeed, the adhesion of bacteria to host surfaces is a critical step of host colonization as it prevents the mechanical clearance of pathogens. Typically, most bacteria express adhesive surface structures that promote interaction with host cells. Such adhesive proteins include different types of pili, fimbrial adhesions, curli, trimeric autotransporter adhesins, and outer membrane proteins (cf. Fig. 2.7). Notably, pili and other organelles can be regarded as the functional end products of bacterial secretion systems; that is, they are assembled by critical secretion systems to function in adherence (for secretion systems, see below). The process of adhesion reflects a crucial step for extracellular bacteria that facilitates their colonization and biofilm formation by withstanding host mechanical and immunological clearance. These maneuvers allow persistence in the host. For intracellular bacteria, it is an initial crucial step that precedes their internalization within host cells. On the other hand, adhesion may become detrimental to bacteria
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themselves because their attachment can also stimulate phagocytosis by macrophages and DCs, which favors bacterial clearing via both innate and adaptive immune processes (for phagocytosis, see Vol. 1 [1], Sect. 22.6, pp. 556–563; for further reading, see [2–9]).
3.2.2.3 Biofilm Formation Bacterial biofilms refer to complex sessile communities of microbes that may be found attached to a solid surface or may form aggregates without adhering to a surface [10]. Biofilm formation is commonly considered to occur in four main stages: (1) bacterial attachment to a surface (pili commonly necessary), (2) assembly of the cells to form microcolonies, (3) final biofilm differentiation into a mature structure, and (4) detachment (also termed disassembly or dispersal) of bacteria which may then colonize new areas [11, 12]. During the formation of biofilm, several species of bacteria communicate with one another, employing so-called “quorum sensing.” Quorum sensing acts by monitoring cell density through chemical signals that allow communication among and between bacterial species in order to trigger and coordinate changes in their behavior and regulate—besides others—the expression of genes involved in virulence and pathogenicity (for reviews, see [13, 14]). By withstanding hostile environmental conditions such as desiccation, biofilms take over a crucial role in virulence, favoring the persistence and chronicity of infection as well as acting as an important source of bacterial dissemination. In addition, as reviewed by Roy and colleagues [15], biofilms protect the invading bacteria against the immune system of the host via impaired activation of phagocytes and the complement system and, importantly, also increase their resistance against conventional antibiotics by around 1000-fold. Given these properties, microbial biofilm can be considered a potent virulence factor (for the complement system, see Vol. 1 [1], Sect. 23.2, pp. 591–614). Of note, more than 65–80% of all microbial infectious diseases, including both device- and non-device-associated infections, involve the formation of biofilms. Biofilms are usually observed on or within indwelling medical devices such as contact lenses, central venous catheters, mechanical heart valves, peritoneal dialysis catheters, prosthetic joints, pacemakers, urinary catheters, and voice prostheses. Regarding the potential to generate DAMPs, antibacterial antibodies were found to form ICs at the biofilm surface, which may mediate collateral damage to adjacent tissues (reviewed in [16, 17]). 3.2.2.4 Capsules Many Gram-negative and Gram-positive bacteria produce capsules that are the outermost layer of bacterial cells and, with a few exceptions, are all composed of polysaccharides (also see Fig. 2.7). In their capacity as essential virulence factors during infection and invasion processes in mammalian hosts, capsules have been demonstrated to possess several functions that serve survival and immune evasion of encapsulated bacterial pathogens (reviewed in [18]). They include prevention of desiccation [19] and protection from/evasion of immune recognition and
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phagocytic elimination, including complement-mediated opsonophagocytosis [20, 21]. For example, capsules, besides other various surface structures, were recently shown to contribute—by interfering with multiple steps of the complement cascade—to evasion of complement-mediated immune clearance of the systemic pathogens Yersiniae and Salmonellae [22].
3.2.2.5 Concluding Remarks These brief remarks on some typical processes initiated in the early phase of infection already guess that bacteria possess sophisticated intra- and intercellular regulatory networks controlling the expression of nondamaging virulence factors, which subsequently may lead to processes associated with the emission of DAMPs. Certainly, these networks may vary between different species, a fact that does not allow to make general assumptions regarding their precise role in driving the pathogenesis of bacterial infectious diseases.
3.2.3 Indirectly Damaging Bacterial Virulence Factors 3.2.3.1 General Remarks From the perspective of this book, this section addressing indirectly damaging bacterial virulence factors is of particular importance because such molecules produced by pathogenic bacteria are known to cause secondarily, via various mechanisms, cell stress, and/or tissue injury: the sources of DAMPs generation and emission. Here, this characteristic capability of pathogenic bacteria to initiate a sequela of virulence factors that subsequently results in host cell stress/tissue damage will be briefly sketched, using the examples of small ncRNA, siderophores, secretion systems, and membrane extracellular vesicles (EVs). 3.2.3.2 RNA-Dependent Regulation of Bacterial Virulence The tools of bacterial virulence for successful host invasion, colonization, and proliferation, in spite of the host’s innate/adaptive immune defense responses and antimicrobial therapy, must be properly and well-timed orchestrated by the pathogenic bacterium at all phases during infection. This can be achieved by optimal coordination of epigenetically regulated gene expression. Indeed, there is accumulating evidence implicating the productive roles played by bacterial regulatory RNAs in mediating gene expression both at the transcriptional and post-transcriptional levels. In fact, small noncoding RNAs (sRNAs) are emerging as an important, distinct class of virulence factors in both Gram-positive and Gram-negative bacteria, usually by promoting other virulence factors mentioned above. As reviewed by Chakravarty and Massé, 2019 [23], among those sRNAs are RNAIII in Staphylococcus aureus that, for example, activates the synthesis of secreted exotoxins; RsaA, which promotes chronic persistence biofilm formation; LhrC/lapB in Listeria monocytogenes that encodes a cell wall-tethered adhesin; and sRNA RyhB that triggers, through multiple molecular mechanisms, siderophore production ([24], also addressed in [25]).
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Also, bacterial sRNA—either intracellular, secreted, or packaged in vesicles (see below)—has gained increasing attention as a potential virulence factor involved in host–pathogen interactions. However, the exact mechanisms promoting pathogenicity within ongoing antimicrobial innate immune responses remain to be explored (for more details, see [26–28]; for sRNA-based epigenetic modifications in inflammatory responses, see also Vol. 2 [29], Sect. 5.6.5, pp. 188–193). This emerging topic of manipulation of host immune responses by microbial RNA is resumed in the next chapter, Sect. 4.3.4.5.
3.2.3.3 Siderophores: Molecules Damaging Host Cells by Iron Deprivation Nearly all pathogenic bacteria require iron as an essential trace element for fundamental cellular processes such as DNA synthesis, in particular, for replication during colonization and proliferation processes [30]. This iron dependency means that they have to compete with the host for iron (e.g., bound to hemoglobin, ferritin, transferrin, and lactoferrin). The iron, however, is tightly regulated by the host. To overcome this problem, many bacteria secrete siderophores, of which about 500 have been identified (such as enterobactin, mycobactin, lidobactin, and pyoverdine). These ferric ion chelating molecules are low molecular weight, high-affinity Fe3+binding compounds actively taken up (as siderophore-Fe3+ complex) by bacteria for iron acquisition via specific receptors and transport system. Such receptors include outer membrane receptors like FepA, FecA, and FhuA, which bind to their cognate ferrisiderophore complex. Indeed, the high-iron binding affinity allows siderophores to steal iron from host proteins (for reviews, see [31–34]). Of note, many siderophores have been recognized to be important virulence factors, particularly in pathogens that encode multiple siderophores, due to the acquisition of siderophore synthesis systems by horizontal gene transfer. Siderophores execute their virulence power via chelation of iron involved in host cellular processes. Depending on the cellular response, siderophores can secondarily act as toxins causing cell death (e.g., apoptosis in cancer cells) (for further reading, see [31–36]). Moreover, other mechanisms of potential damage to host cells have been described. For example, the siderophore pyoverdine in P. aeruginosa was shown to regulate the production of other virulence factors, such as exotoxin A and endoprotease [37, 38]. 3.2.3.4 Secretion Systems Contributing to Bacterial Virulence Bacterial pathogens utilize various tools to invade mammalian hosts, evade host immune defense responses, and, most important from the perspective of the book, cause tissue damage in the host as potential sources of DAMPs. One vital component of these strategies for many bacterial pathogens is the secretion of proteins across phospholipid membranes. Secreted proteins can function as bacterial virulence factors in many ways, from facilitating adhesion to host cells (as briefly touched on above); scavenging resources such as iron in an environmental niche (compare the previous section); up to directly intoxicating host target cells, manifested by cellular stress, damage, and even death.
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Such secretion systems are, for example, the highly conserved general secretion (Sec) and twin-arginine translocation (Tat) pathways, which are most commonly used to transport proteins across the cytoplasmic membrane (for reviews, see [39– 41]). For example, Gram-positive bacteria employ both the Tat and Sec pathways to transport proteins across the cytoplasmic membrane and will eventually be released into the extracellular environment, often through passive diffusion through the PGN layer. Additionally, to date, eight different types (T1–T9) of dedicated secretion systems (SS) have been identified: T1SS, T2SS, T3SS, T4SS, T5SS, T6SS, T7SS, and T9SS (Fig. 3.1). The systems are characteristic for Gram-negative bacteria where they are numbered T1SS through T6SS, with each system transporting a specific subset of proteins. In contrast, Gram-positive bacteria lack these sophisticated systems and, instead, secrete virulence factors in their soluble form or encapsulated in extracellular membrane vesicles (see next section). Nevertheless, some Grampositive organisms utilize T7SS to export certain proteins across the cytoplasmic membrane and, potentially, through the cell wall. Moreover, certain Gram-positive organisms, such as species of Mycobacteria and Corynebacteria, contain—as mentioned above—a heavily lipidated cell wall layer called a mycomembrane. These systems can differ based on whether their protein substrates cross a single phospholipid membrane, two membranes, or even three membranes, where two are bacterial, and one is a host membrane, allowing for direct transfer of substrates into the cytoplasm of the recipient cell (Fig. 3.1; for details, see reviews such as in [39, 42–48]). As nanomachines, the secretion systems have global but different functions that all can contribute to virulence. These functions include the transport of adhesins, DNA-protein complexes, enzymes, effector proteins, and toxins. Of note, some very virulent Gram-negative bacteria such as Salmonella, Shigella, Francisella, Legionella, Burkholderia, Pseudomonas, and Yersinia possess T3SS, T4SS, and T6SS that are capable of injecting effector proteins to alter normal cellular processes involved, for example, in innate immune responses and the cytoskeleton machinery, manifested by cytoskeleton rearrangement (Fig. 3.1 [49, 50]). The T3SS is one of the most studied secretion systems due to its striking correlation with bacterial pathogenesis. Indeed, some enzymes secreted via T3SS are strong virulence factors, such as proteases, sphingomyelinases, and phospholipases (reviewed in [51–53]). These enzymes reportedly damage cells by multiple mechanisms, including degradation of host ECM components; altering host cellular receptors in a manner that can subvert the binding of their usual ligands, such as complement; modulating the pathways of the host’s signaling machinery; changing microbial behavior via phagosomal escape or prevention of phagosomal maturation; and, last but not least, promoting invasiveness, serum resistance and evasion of host immune mechanisms. Via all those mechanisms, these secreted proteins promote dissemination and spreading of the infection, modify receptors involved in host signaling and, most important from the perspective of the book, elicit stress responses and, thus, contribute not only to the generation of dysDAMPs but also emission of other subclasses of DAMPs (Fig. 3.1).
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Consequences: generation and emission of DAMPs (e.g., IA-1; IA-2, IIC-4 DAMPs)
Proteins, Proteins, e.g., causing Proteins, Adhesins, Proteins, phagosomal Enzymes, Toxins, Adhesins, damage Enzymes Enzymes Toxins
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Effector proteins, DNA
HM
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LPS
MM
OM PGN, Peripl. IM
Sec Cytoplasm
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Type I
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Type II Type V
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Cytoplasm
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Type VI
Fig. 3.1 Simplified schematic diagram of a model illustrating the structure of bacterial secretion systems: type I (T1SS), type II (T2SS), type V (T5SS), type IX (T9SS), type III (T3SS), type IV (T4SS), type VI (T6SS), and type VII (T7SS). As indirectly damaging virulence factors, they provide a way for the transportation of various molecules (e.g., toxins, enzymes, and effector proteins) across bacterial and host membranes. The processes ultimately contribute to causing cell stress and/or tissue injury leading to generation and emission of DAMPs by the host. Notably, as illustrated in the middle of the figure, some Gram-negative bacteria transport and secret proteins across the inner membrane with the help of either the Sec or Tat secretion pathways, which are then transported across the outer membrane using a second secretion system. The T2SSs and T5SSs secrete proteins in this manner. In addition, other Gram-negative protein secretion systems such as T1SSs can transport their substrates across both bacterial membranes in one step. Notably, the secretion systems T3SS, T4SS, and T6SS (right side of the figure) can also transport proteins across an additional host cell membrane, injecting effector proteins directly into the cytosol of a target cell. Moreover, as shown on the far left of the figure, some Gram-positive bacteria, such as species of Mycobacteria, use the Type VII secretion machinery, responsible for the secretion of proteins across the outer mycomembrane of the mycobacteria. IM inner membrane, HM host membrane, LPS lipopolysaccharide, MM mycomembrane, OM outer membrane, Peripl. periplasmic space, PGN peptidoglycan, Sec general secretion, Tat twin-arginine translocation (sources: [39, 42–50])
3.2.3.5 Bacterial Extracellular Membrane Vesicles Encapsulating Virulence Factors In infections, EVs are generally considered to contribute to the virulence of bacteria, viruses, fungi, and parasites. For example, bacterial virulence factors are delivered either in the extracellular environment or directly into host cells not only through the dedicated and sophisticated secretion systems (T1SS–T7SS) but also via vesicles derived from bacterial membranes. Such vesicles are referred to as outer membrane vesicles (OMVs) originating from Gram-negative bacteria or membrane vesicles (MVs) deriving from Gram-positive bacteria, lacking an outer
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Early endosome
Host cell Endocytosis
OMVs Clathrin
Lysosome
Virulence factors Gram-neg. Bacterium
Fusion
Virulence factors such as Toxins, enzymes, DNA
Virulence factors interfering with ribosomes, mitochondria, DNA → Regulated cell death
IM PGN OM LPS Nascent OMV
Consequence: generation and emission of DAMPs
membrane. Interestingly, some authors have proposed the OMVs to be considered as an additional and independent secretion system [54] (Fig. 3.2). Hereafter, the term “MVs” will usually be used to refer to both types of vesicles together [55, 60]. Most bacteria produce, secret, and release MVs that contain specific cargo molecules, including the transport of virulence factors such as proteins with adhesin activity, NAs, components for biofilm formation, siderophores, enzymes such as proteases, and active toxins (reviewed in [55–59]). And it is this discovery of the ability of MVs to carry dangerous molecules into host cells that has garnered increasing interest from researchers as this function allows bacteria to interfere with the host’s defense responses against them (Fig. 3.2). For example, Staphylococcus aureus-derived MVs were shown to contain many extracellular and membrane-associated virulence factors, including toxins, adhesins, and several enzymes, such as coagulase, which execute crucial pathological functions for systemic infections. In targeted proteomic analyses of Gram-positive bacteria, Staphylococcus-derived MVs were found to harbor, besides those mentioned, the α-toxin [61]. In other lines of studies on the MV of pathogens of the
Fig. 3.2 Simplified schematic diagram of a model illustrating transportation of virulence factors of Gram-negative bacteria via an extracellular membrane vesicle-based secretion system. The processes ultimately contribute to causing cell stress and cell death leading to generation and emission of DAMPs by the host. At first, nascent OMVs form as a constriction of the outermost membrane leading to a blebbing structure that contains membrane, periplasmic proteins, and virulence factors that are encapsulated as cargo. Entrance and delivery of virulence factors into the host cell are exemplified by clathrin-mediated endocytosis proceeding to an endolysosomal pathway and a membrane fusion process, respectively. This is followed by intracellular trafficking of bacterial virulence factors such as toxins, enzymes, and DNA, which proceed (by escaping the endosome and migrating to the Golgi and endoplasmic reticulum: here not shown) to their cellular targets such as ribosomes, mitochondria, and host DNA. IM inner membrane, LPS lipopolysaccharide, OM outer membrane, OMV outer membrane vesicle, PGN peptidoglycan, R receptor (sources: [55–59])
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gastrointestinal tract, the vesicles were shown to contain toxins leading to cell damage or cell death, such as Shiga toxin [62], hemolysin [58], and cholera toxin [63]. Also, the oral pathogen Porphyromonas gingivalis was shown to secret the virulence factor gingipain in its MVs, which induces detachment of cultured oral epithelial cells [64]. The authors of this finding suggested, that the gingipain-laden OMVs may contribute to tissue destruction in periodontal diseases by serving as a vehicle for the antigens and active proteases. Typically, the MVs enter host cells to release their cargo, such as toxins leading to cellular stress or damage. Mechanistically, five different endocytic pathways are discussed by which MVs can be engulfed by host cells: macropinocytosis, clathrin- mediated endocytosis, caveolin-mediated endocytosis, lipid raft-mediated endocytosis, and direct membrane fusion. For example, multiple bacterial virulence factors, such as Shiga toxin, cholera toxin, cytolethal distending toxin V of Escherichia coli, and the gingipain of Porphyromonas gingivalis have been shown to utilize clathrin- mediated endocytosis to enter host cells during infection [65] (cf. Fig. 3.2; for details, see Caruana and Walper [57]); for engulfment of exogenous proteins, also compare Vol. 1 [1], Sect. 31.2, pp. 724–728). More precisely: MVs, that is, OMVs (from Gram-negative bacteria) that are engulfed in endocytic vesicles proceed through the endolysosomal pathway and are eventually processed in lysosomes, whereas caveolae-derived vesicles travel to so-called caveosomes (which are distinct from endosomes in content and pH). In caveosomes, internalized MVs can reside to be delivered to the ER–Golgi complex [66–68] (for processing of exogenous proteins via the endolysosomal pathway, also compare Vol. 1 [1], Sect. 31.3.3, pp. 730–733).
3.2.3.6 Concluding Remarks To sum up, bacterial virulence factors, as they are tentatively defined in this section as indirectly damaging molecules, are gaining importance with regard to the fact that they initiate processes that ultimately may result in the emission of DAMPs. In this regard, these molecules should not be underestimated in their pathogenetic role in bacterial infections. In describing and illustrating the function of these virulence factors by appropriate figures (cf. Figs. 3.1 and 3.2), one is once again fascinated by the tools that bacteria have developed in the course of evolution to evade their host's immune defense response.
3.2.4 Directly Damaging Bacterial Virulence Factors of Extracellular Bacteria 3.2.4.1 General Remarks Pathogenic bacteria use toxins (exotoxins and endotoxins) and enzymes to cause cell stress associated with molecular perturbations, tissue injury, and, in the worst case, RCD. These toxic proteins can act in various ways to trigger the emission of DAMPs: They are injected from the bacterial cytoplasm directly into the adherent host cell; they are secreted to act at sites within the host that are distant from the
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pathogen, and; they can be released upon bacterial lysis. The outcome of infection can be markedly influenced by these processes. So, the various modes of action of the different protein toxins – via elicitation of different classes of constitutive and inducible DAMPs and, thus, via different pathways – result in gradual adaptation of the host's innate/adaptive immune response to a given infection. For example, induction by a bacterial exotoxin of subroutines of RCD associated with the release of large amounts of various DAMPs may transform a local inflammatory response into a life-threatening SIRS. In the following, these characteristic injury-promoting abilities of pathogenic bacteria are briefly sketched using some typical examples (for further reading, also see [69–76]).
3.2.4.2 Bacterial Exotoxins Exotoxins are several types of protein toxins and enzymes (usually single polypeptides or heteromeric protein complexes) secreted by both Gram-positive and Gram- negative bacteria in a soluble form or partially packed in extracellular MVs [77] and also, but rarely, released from lysed bacteria [78]. Notably, bacterial pathogens are capable of simultaneously producing more than a dozen exotoxins with various structures, translocation mechanisms, and biological-toxic effects. As secreted proteins, they can operate on host cells located at remote sites. According to Lemichez and Barbieri [79], bacterial exotoxins can be mainly classified into four groups according to their modes of action, including (1) sophisticated protein toxins that bind to cell cytoplasmic membranes and disrupt the membrane lipid bilayer through pore formation or expression of phospholipase activity; (2) so-called AB toxins that are composed of two distinct molecular components, A and B (the B component binding to a specific receptor of the target cell and allowing the component A—usually an enzyme that acts on a specific cytosolic target—to translocate into the cytoplasm); (3) toxins with an enzymatic activity, also called effector proteins, which are delivered into the cytosol of the target cell via an injection apparatus that is a component of the bacterial pathogens (i.e., T3SS, T4SS, and T6SS secretion systems; see above, and Fig. 3.1), and; (4) toxins that bind to surface membrane receptors to trigger intracellular signaling, thereby modifying host cell physiology. The four classes are briefly touched on in the following. Pore-Forming Toxins: Sophisticated and Largely Spread Virulence Factors Causing Cell Disruption Some bacteria employ those pore-forming exotoxins that are the most common bacterial proteins (reviewed in [80, 81]). Pore-forming toxins are required for virulence in a large number of important pathogens, including Streptococcus pneumoniae, group A and B streptococci, Staphylococcus aureus, Escherichia coli, and Mycobacterium tuberculosis [82]. For example, one such prototypic pore-forming exotoxin is the S. aureus alpha-toxin (α-toxin, also called hemolysin-α, Hla), which causes lysis of many different cell types, including erythrocytes, platelets, ECs, epithelial cells, brain cells, and certain leukocytes [83–86]. Mechanistically, the α-toxin, secreted in a soluble form or in MVs, binds to its cellular transmembrane
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receptor, a disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) to start an oligomerization process that finally leads to transmembrane pore formation, resulting in cell lysis [84, 87] (Fig. 3.3). There is growing evidence suggesting that this process kills host cells via induction of subroutines of RCD, for example, NLRP3 inflammasome-dependent pyroptosis in macrophages and necroptosis [88–90]. Other such toxins attacking host cell membranes refer to the surfactant-like phenol-soluble modulins, that is, small peptides with an amphipathic α-helical structure, which have been found to be expressed by staphylococcal species. Their mode of action is to aggregate in the lipid bilayer of host cell membranes, leading to their lytic disintegration [91] (presumably a subroutine of RCD again). Together, bacterial pore-forming exotoxins can be considered strong virulence factors as they apparently serve, by the induction of RCD subroutines, as prolific sources of DAMPs. Activation of necroptosis and, in particular, inflammasome- associated pyroptotic cell death by pore-induced K+ efflux appear to be a typical feature of pore-forming bacterial toxins to promote the emission of DAMPs [92] (the topic is resumed below in Sects. 3.7.4.4 and 3.7.5.4). AB Toxins Causing Stress Responses and Cell Death Other exotoxins refer to the AB toxins, which differ in their biological effects. AB toxins consist of two non-linked proteins: an A domain that possesses enzymatic
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Fig. 3.3 Simplified schematic diagram of a model illustrating roughly the mechanism of action of Staphylococcus aureus pore-forming alpha-toxin. Mechanistically, the α-toxin, here shown as secreted as a monomer in a soluble form, binds to its cellular transmembrane receptor ADAM10 to start an oligomerization process that finally leads to transmembrane pore formation of a heptamer resulting in cell lysis. Evidence suggests that cell lysis is the result of toxin-induced RCD (such as pyroptosis and necroptosis), which serve as sources of DAMPs release. ADAM10 a disintegrin and metalloproteinase domain-containing protein 10, RCD regulated cell death (sources: [80–83, 85, 86, 88–90])
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Diphtheria toxin
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activity and a separate B domain that binds to cellular membranes and—via receptor-mediated endocytosis—serves for efficient transport of the A subunit into the host cell’s cytosol. Thus, transported by the B components and arrived in the cytosol, the A subunits, acting as enzymes, exert their characteristic cytotoxic effects, which differ depending upon the individual toxin (for more detailed information about these processes, also see [75, 93, 94]). Notably, the AB toxins are among the most potent bacterial toxins produced by Gram-positive bacteria (Fig. 3.4). For instance, Corynebacterium diphtheriae, a nonmotile, nonencapsulated, Gram-positive bacterium, secrets the Diptheria toxin (DT) that kills susceptible cells via inhibition of protein synthesis [104, 105]. The DT consists of three independent domains: (1) C-terminal receptor-binding domain (R-domain), which interacts with the DT receptor (i.e., the host cell surface heparin- binding epidermal growth factor-like growth factor [HB-EGF] precursor) to enter the cell via clathrin-mediated endocytosis followed by initiation of the endosomal pathway; (2) the translocation domain (T-domain), which—via acidification- promoted conformational changes—is responsible for bridging the endosomal
Release of C-Domain
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Fig. 3.4 Simplified schematic diagram of a model illustrating the mechanism of diphtheria toxin entry into a host cell, exemplified by clathrin-mediated endocytosis. Diphtheria toxin (consisting of the C-, T-, and R-domain) binds—via its R-domain - to its cell surface receptor (precursor HB-EGF) to become endocytosed into early endosomal vesicles. Upon acidification-promoted conformational changes, the T-domain of the toxin bridges the endosomal membrane to initiate the translocation process, allowing the C-domain to translocate through endosomal membrane pores and be delivered into the cell cytosol. Following, the C-domain is proteolyzed from the R- and T-domain and catalyzes the ADP-ribosylation of elongation factor 2 (EF-2). The ADP-ribosylated EF-2 is now irreversibly inactivated, leading to the inhibition of protein synthesis. The halt of vital protein synthesis causes cell death resulting in the final release of DAMPs. ADP adenosine 5′-diphosphate, EF-2 elongation factor 2, C catalytic, HB-EGF heparin-binding epidermal growth factor-like growth factor, NAD+ nicotinamide adenine dinucleotide, R receptor-binding, T translocation (sources: [95–103])
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membrane, that is, the transmembrane translocation process; and (3) the N-terminal catalytic domain (C-domain) that, following translocation through endosomal membrane pores into the cell cytosol, is proteolyzed from the R and T domains and proceeds to ADP-ribosylated elongation factor 2 (ADP-ribosyl-EF-2), thereby inhibiting protein synthesis and causing cell death (Fig. 3.4; for reviews, see [95– 98], for more details see [99–103, 106]). Also, the tripartite anthrax toxin of Bacillus anthracis encompasses a receptor- binding moiety and two different enzymatically active components, lethal factor (LF, a metalloprotease) and edema factor (EF), that can lead to apoptotic and NLRP1 inflammasome-mediated pyroptotic cell death of macrophages and DCs [107–109]. Similarly, the binary clostridial toxins produced by Clostridium spp., such as C. perfringens, were shown to induce subroutines of RCD, including apoptosis and necroptosis [76, 110]. In addition, the typhoid toxin, a unique AB exotoxin produced by Salmonella typhi, reportedly exerts cytotoxic effects, typically via induction of a DDR that can lead to apoptosis [74, 111] (for DDR, see Vol. 1 [1], Sect. 18.6, p. 408; for a review on DDR in prokaryotes, see [112]). Likewise, Shiga toxins were found to induce ER stress→UPR, apoptotic, and pyroptotic cell death [113–117]. Taken together, processes induced by AB toxins are associated with severe cell damage associated with stress responses and subroutines of RCD. Typically, and by definition, it can be anticipated that these AB toxin-mediated innate immune defense processes are associated with the emission of various subclasses of DAMPs, including IA-1 DAMPs (e.g., as shown for Shiga toxin, HMGB1) and extracellular histones [118]), IA-2 and IIC-4 DAMPs. Bacterial Effector Proteins Causing Intracellular Dyshomeostasis and Regulated Cell Death Still, other exotoxins refer to effector proteins, which can be directly injected from the pathogen into the cytoplasm of host cells by specialized nanomachines, that is, the above-mentioned T3SS, T4SS, and T6SS (cf. Fig. 3.1). These effectors are unique in that the bacterium delivers a large number of molecules over a short period of time to interfere effectively with the physiological processes of the host cell. Typically, effector proteins exert their specific function in concert with the activities of multiple other bacterial effectors delivered by the same machine. In the cells, effector proteins reportedly execute specialized functions in terms of enzymes that use host components as substrates or proteins that structurally or functionally mimic eukaryotic proteins and thus interfere with cellular mechanisms. Such complex biochemical activities include modulation of actin cytoskeleton dynamics, covalent modification of host target molecules through a PTM, or disruption of signaling pathways; that is, processes that result in intracellular molecular perturbations (for further reading, see [119–124]). Interestingly, although all these processes serve pathogens to subvert host defense functions, simultaneously, they are associated with the generation of cell-intrinsic dysDAMPs that are able to initiate and promote potent innate immune responses (for dysDAMPs, see Table 1.1, and Vol. 1 [1], Sect. 13.4.5, p. 289 and Vol. 2 [29], Sect. 3.4.4, p. 78).
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Of note, however, bacterial effector proteins do not only induce molecular perturbations; they have also been demonstrated to promote the induction of RCD. For example, Yersinia and Shigella effector proteins were found to elicit PRR-mediated pathways, which subsequently results in cell death with features of both apoptosis and pyroptosis [125–127]. Receptor-Triggered Intracellular Signaling Leading to Cellular Dyshomeostasis Other exotoxins, such as enterotoxins, bind to the surface of target cell membrane receptors, thereby corrupting the host intracellular signaling network [75, 79]. For example, Escherichia coli strains have been shown to secrete enterotoxins that activate signaling pathways in the small intestinal epithelial cells (IECs), leading to the disruption of electrolyte homeostasis [128, 129]. Although further studies are needed to specify the mode of action of these exotoxins, one may discuss that enterotoxin-mediated disturbance of intracellular homeostasis reflects the emission of cell-intrinsic dysDAMPs as well. In addition, this group of toxins, in their role as virulence factors, may induce host damage by other mechanisms such as induction of RCD. Still, other bacterial virulence factors that are reportedly included in this group of toxins refer to as so-called staphylococcal superantigens [79]. These secreted toxins are a family of secreted toxins that bypass antigen processing and presentation and, nevertheless, stimulate T cell activation. Mechanistically, these molecules can bridge nonspecifically MHC-II molecules at the surface of APCs with the TCR, leading to uncontrolled nonclonal T cell activation and proliferation, resulting in an inflammatory response. Via subversion of the T cell-mediated effector processes, the superantigens are suggested to alter the course of the immune response in a way that benefits S. aureus persistence [130, 131] (for details of the adaptive immune responses in light of the danger/injury model, also see Vol. 1 [1], Chaps. 31 and 32, pp. 723–781).
3.2.4.3 Bacterial Endotoxins Unlike the classical exotoxins of bacteria, endotoxins are essential complex components of the outer membrane of Gram-negative bacteria (Fig. 2.8). They are associated with LPS, which—as a MAMP—is composed of three components: the toxic lipid A, that is, the hydrophobic domain, which is widely accepted as the main virulence factor; the cell wall antigen (O-antigen) representing the repeating hydrophilic distal oligosaccharide; and the hydrophilic core polysaccharide. Besides its toxic function, LPS operates as an exogenous DAMP that is recognized by TLR4 to activate powerful innate immune responses (for reviews, see [132–135]). Of note, the cytotoxic effect of LPS has recently been shown to lead to RCD in the form of pyroptosis and necroptosis known to be associated with the release of DAMPs [136–139] (for non-canonical LPS–CASP11-mediated activation of NLRP3 inflammasome and pyroptosis, also compare Vol. 1 [1], Sect. 22.4.2.3, p. 519; for a recent overview, see [139]). Interestingly, a study on murine macrophages identified OMVs as the vehicle that, via clathrin-mediated endocytosis, delivers LPS into the
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cytosol during extracellular Gram-negative bacterial infections [140] (cf. Fig. 3.2), demonstrating impressively the function of OMVs as an indirectly damaging virulence factor.
3.2.4.4 Concluding Remarks It is intriguing to note that extracellular bacteria have evolved such highly sophisticated and “tricky” tools to plant toxic molecules into a host cell aimed at killing it. And it is equally fascinating to see how humans (as all mammals) counteracted this threat by evolving DAMPs as effective tools of defense against this deadly threat: an admirable example of the evolutionary arms race between pathogens and the host. However, this inflammatory, primarily beneficial defense response intrinsically and notoriously affects the infected person: disease is a result, which can even lead to death in case the DAMPs are produced in excess. If one understands this scenario, the indispensable involvement of DAMPs in the pathogenesis of bacterial infectious diseases is not a surprise anymore.
3.2.5 Intracellular Bacteria: Production of Indirectly and Directly Damaging Virulence Factors 3.2.5.1 General Remarks The topic of virulence of pathogens that have evolutionarily adapted to an intracellular lifestyle presents some peculiarities and thus deserves a separate section. Usually, intracellular bacteria reside, replicate, or persist in myeloid cells, especially in macrophages, but some also reside in nonphagocytic cells such as epithelial cells, fibroblasts, and ECs. The intracellular lifecycle of a bacterium begins with its entry into a host cell that is initiated by adhesion virulence factors such as the above-mentioned adhesins. Once inside a cell, bacteria can live in three main categories of compartments. The first category is set up by phagolysosomal or endolysosome- like vacuoles, which have an acidic pH and contain hydrolytic enzymes. The second complies with nonacidic vacuoles that do not fuse to lysosomes and are usually remodeled by the pathogen. The third compartment is the cytosol, in which some pathogens can reside after escaping from their internalization vacuole. Accordingly, intracellular bacteria are divided into intravacuolar and cytosolic bacteria [8]. 3.2.5.2 Production of Virulence Factors by Bacteria Inside Nonphagocytic Cells Uptake of bacteria by nonphagocytic cells occurs by two processes known as zipper and trigger mechanisms, which both depend on the activation of signaling pathways leading to the reorganization of the actin cytoskeleton at the level of the host plasma membrane. In the “zipper” mechanism, bacterial surface effector proteins, such as mimicking components, engage with host proteins to induce cytoskeleton and membrane rearrangements, culminating in endocytosis. In the “trigger” mechanism, injection of the above-mentioned effector proteins by the bacterium (e.g., T3SS and
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T6SS) in the host cell cytoplasm triggers the formation of large-scale cytoskeletal rearrangements and ruffles. In both cases, the bacterium is internalized and replicates in a remodeled membrane-bound vacuole that is destined to traffic—as an intravacuolar bacterium along the endocytic pathway (called “internalization” or “bacterial-induced phagocytosis”). Also, some pathogens, such as Listeria, which have escaped internalization vacuoles, are able to replicate and move in the cytosol using actin-based motility. This intracellular motility leads to the formation of bacteria-containing protrusions, a process that is associated with plasma membrane damage (for detailed information, see reviews cited in [8, 141, 142]). It is not difficult to imagine the unproven possibility that all these processes are associated with cellular stress reflecting generation and the presence of cell-intrinsic dysDAMPs.
3.2.5.3 Production of Virulence Factors by Bacteria Inside Phagocytes Uptake of invading bacteria can be a host-induced defense process in terms of phagocytosis by professional phagocytes such as macrophages, polymorphonuclear neutrophils (PMNs), DCs, or M cells of the intestinal Peyer's patches. Like nonphagocytic cells, these cells also constitute a niche for bacteria with an intracellular lifestyle, as they naturally internalize foreign particles. Indeed, representing a frontline defense against pathogens, these cells capture, phagocytose, and engulf bacteria into phagosomes. Following, a dynamic pathway is initiated, characterized by phagosome maturation via sequential fusion with endocytic and lysosomal compartments. This leads to the formation of a secondary acidic and oxidative phagolysosome that is dedicated to degrading and finally digesting bacteria (for detailed information, see [8, 141–143]; for mechanisms of phagocytosis and endocytosis, including the various endocytic pathways, also see Vol. 1 [1], Sect. 22.6, Figs. 22.14 and 22.15, pp. 556–563). Of note, however, pathogenic microbes manipulate host macrophages to reside and replicate in these cells. In fact, for survival and replication in phagocytes, bacteria have evolved the production of nondamaging, indirectly damaging, and directly damaging virulence factors. For example, to avoid digestion, pathogenic bacteria can avoid vacuole-lysosome fusion or convert the phagolysosomal environment into one permissive to bacterial survival. In both instances, bacteria are referred to as vacuolar pathogens [8, 142]. Another example refers to bacteria such as Mycobacterium tuberculosis, the agent of tuberculosis, or Legionella pneumophila, the bacterium responsible for Legionnaire's disease, which, after being phagocytosed by macrophages, block the acidification of the phagosome and its fusion to lysosomes, thereby avoiding killing and allowing sustained survival in these cells [144, 145]. The ability of some of these phagocytes to migrate through tissues furthermore provides an interesting way for pathogens to disseminate inside their host. Here, the indirectly and directly damaging virulence factors are of major interest (e.g., reviewed by Mitchell et al. [143]). Thus, intravacuolar Gram-negative bacteria use the secretion systems T3SS, T4SS, and T6SS to inject effector proteins through the bacterial surface and the host vacuole membrane into the host cell cytosol,
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causing intracellular molecular perturbations, for example, via remodeling of the cytoskeleton network associated with the generation of dysDAMPs (cf. Fig. 3.1). Likewise, cytosolic bacteria were observed to use distinct sets of virulence determinants at different stages of their intracellular life cycle, mainly aimed at escaping from phagosomes. For successful escape, they rely on distinct specialized secretion systems (e.g., T3SS and T6SS). Mechanistically, however, details of this phagosomal escape process are still elusive (for more information, see [143]).
3.2.5.4 Concluding Remarks In sum, like extracellular pathogens, intracellular bacteria have evolved virulence factors to guarantee to reside, replicate, and survive within protecting compartments of host cells for transmission to other hosts. In nonphagocytic cells, invasive intracellular bacteria inject effector proteins into the cytosol of host cells to initiate endocytosis machinery and other changes, thereby escaping extracellular immune defense mechanisms. In macrophages, the phagocytosed bacteria use their virulence effector arsenal to escape the various host innate immune defense mechanisms executed by these professional phagocytes. In light of the scenario of an evolutionary arms race between hundreds of millions of years-coexisting bacterial pathogens and their hosts [40], one has to stress again that the ability of intracellular bacteria to subvert these defense mechanisms provokes host stress responses such as autophagy and UPR as well as cell death pathways leading to RCD, both processes associated with the generation and emission of DAMPs. In Chap. 5, this topic will be resumed.
3.2.6 Mechanisms of Bacteria to Subvert Host Defense Responses As already briefly introduced above, a variety of virulence factors are essential tools of pathogenic bacteria for invading the host, causing disease, and evading and subverting the host innate/adaptive immune defense responses, respectively. On the other hand, as also already emphasized previously, virulence factors do not only serve the fitness of pathogens but, simultaneously, evoke DAMP-promoted host defense responses: an evolutionary narrative that is wonderfully illuminated by the Red Queen paradigm (see Sect. 2.3.5). In this sense, this topic has indirectly already been covered previously and does not deserve its own section anymore. Nevertheless, a few more points should be added here but only in keywords. Thus, typical mechanisms by which pathogenic bacteria avoid killing by innate host responses include—besides the mentioned use of specialized secretion systems to subvert host functions and the manipulation of vesicular trafficking to escape phagosomal and lysosomal enzymes—(1) evasion of autophagy pathways; (2) interference with induction of a proinflammatory cytokine transcriptional response; (3) subversion of antimicrobial peptides; (4) camouflage of MAMPs; (5) targeting PRR-mediated signaling pathways, and; (6) subversion of host cell apoptosis (for more information, see [146–149]).
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Finally, and of major interest, recent emerging studies have provided evidence suggesting that bacteria may evade clearance by the host innate/adaptive immune responses via the use of their virulence factors (i.e., effector proteins) that epigenetically manipulate host gene expression [150, 151]. Indeed, this is exciting progress in the research field of bacterial evasion mechanisms and highlights—as concluded by Denzer et al. [151]—the importance of further research on bacterial subversion of the host immune response considering each level of gene expression, as new promising targets for successful bacterial clearance during medical therapy might emerge.
3.2.7 Résumé Bacterial virulence in relation to DAMP-driven immune defense responses is an ongoing story. It would be of interest in the future to try to correlate and relate the various virulence factors mentioned here with their differential power to trigger specific patterns of DAMPs. If this endeavor would yield significant results, it could be reasonable to administer targeted DAMPs inhibitors in addition to antibiotic therapy. But this is indeed still a long way off.
3.3 Viral Virulence 3.3.1 The Virulence Program of Viruses First, it is worth mentioning here that the phenomenon described for microbial virulence factors can be applied for viral virulence factors in a similar way: serving the fitness of pathogens but, simultaneously, evoking DAMP-promoted host defense responses. Viral virulence and pathogenicity can be estimated in a variety of ways, based, for example, on mortality, the strength of disease, or pathological lesions, each of which can be quantified. More precisely formulated, it is the virulence phenotype that can be found at any step during the course of infection: from initial entry (e.g., attachment and fusion mechanisms through envelope proteins) to invasion, replication, spread, involvement of target organs, or, finally, shedding. For example, the spike protein of SARS-CoV-2 is currently considered a strong virulence factor [152]. Notably, however, viral virulence factors, for example influenza viruses, particularly operate at levels of evading host antiviral immunity, or manipulating/dysregulating host cell’s immune signaling pathways, or driving host cell protein machinery in favor of viral replication, or causing direct cytotoxicity. Also, the virulence of a virus depends upon factors encoded by specific viral genes (for further reading on this topic, also see [153–160]). From the perspective of the book, induction by the virus of molecular and/or cellular perturbations and stress is of special importance. For example, as already touched on above, the processes of entrance and the different levels of viral invasion and replication in host cells, serving the virus to survive and multiply, are already
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intrinsically associated with molecular perturbations in cells, that is, the generation of dysDAMPs. Accordingly, here, the focus is mainly directed to those virulence factors that cause such perturbation and/or cell stress and damage.
3.3.2 Virulence Factors in Terms of Molecular Perturbations in Viral Replication Cycle Although the structure of pathogenic viruses is different from the molecular makeup of bacteria, a few properties that determine their virulence are similar. As mentioned in the previous chapter, viruses use adhesive capsid or envelope proteins that bind to specific receptors on the surface of host cells. The interaction of such viral adhesive proteins with specific cell receptors defines the tropism of viruses for specific cells, tissues, and organs in the body, thereby reflecting a certain way of virulence. More important, however, is the nature and strength of virulence in terms of DAMPs generation associated with the viral replication process. The replication cycle of viruses has been exemplified by the influenza virus and SARS-CoV-2 in the previous chapter (Figs. 2.12 and 2.13). The example is used here again to stress that the whole life cycle is accompanied by the induction of dysDAMPs. The correctness of this concept is impressively supported by affinity- purification mass spectrometry studies published by Gordon et al. [161], in which 332 high-confidence SARS-CoV-2 protein–human protein interactions were identified that are connected with multiple biological processes, including protein trafficking, translation, transcription, and regulation of ubiquitination (Fig. 3.5). The derangement of the molecular homeostasis caused by these interactions within the cell is easily imaginable: the seed of DAMPs generation! The concept is fortified by similar studies on perturbations in protein abundance and phosphorylation during SARS-CoV-2 infection using a mass spectrometry-based approach, in which the group of investigators found viral proteins to be increased starting 8 h after infection, indicative of viral replication [162]. Also, these studies provided evidence suggesting virus-induced changes in cytoskeleton organization, which again reflect the generation of perturbation-induced dysDAMPs.
3.3.3 Viroporins: A Peculiar Viral Virulence Factor Such virus-induced molecular perturbation can also be caused by viroporins, which are known to contribute to the activation of the NLRP3 inflammasome [163]. Viroporins are small proteins that form ion channels that increase membrane permeability in virus-infected cells via transmembrane formation of hydrophilic pores [164, 165]. Examples include the encephalomyocarditis virus viroporin 2B [166], IAV virulence protein PB1-F2 [167], and the influenza virus M2 protein [168]. As reviewed [169], the M2 protein is present in all influenza types. In influenza A and B, AM2 and BM2 are predominantly proton channels; by contrast, M2 proteins in influenza C and D, CM2 and DM2, are thought to be especially selective for
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Fig. 3.5 Symbolization of the generation of dyshomeostatic DAMPs during the process of intracellular virus replication by a figure published by Gordon et al. [161]. The correctness of this DAMPs-generation-concept is impressively supported by the SARS-CoV-2 protein-protein interaction network shown in this figure, which is derived from data from affinity-purification mass spectrometry studies. In these studies, 332 high-confidence SARS-CoV-2 protein–human protein interactions were identified that are connected with multiple biological processes, including protein trafficking, translation, transcription, and regulation of ubiquitination. The derangement of the molecular homeostasis caused by these interactions within the cell is easily imaginable: the seed of DAMPs generation (source: Fig. 3.3 from an article published by Gordon et al. Nature Research; 2020;583:459–68 [161])
chloride ions. Finally, and of high interest are the experiments unearthing that SARS-CoV viroporins, that is, the three envelope proteins 3a, E, and 8a, can also activate the NLRP3 inflammasome via disturbance of the intracellular molecular
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homeostasis [170, 171]. Although the precise underlying mechanisms in viroporininduced inflammasome activation are not yet fully understood, some interesting evidence has already been reported, which is outlined below.
3.3.4 Virulence Secondary to Viral Invasion: Mechanisms to Subvert Host Defense Responses Several mechanisms have been uncovered by which viruses subvert cellular intrinsic and innate immune responses. As reviewed by Crow et al. with reference to DNA viruses [172], they include (1) manipulation of host defense protein levels by either transcriptional regulation or protein degradation; (2) repurposing or inhibiting these cellular immune factors by molecular hijacking or by regulating their PTM status; and (3) induction by infection of temporal modulation of apoptosis to facilitate viral replication and spread. In addition, if one accepts that the ability of a pathogen to induce subroutines of RN is a hallmark of its virulence, then the property of a virus to trigger cellular pro-death pathways should also be seen as a strong virulence factor. In fact, as already touched upon and discussed in Sect. 2.5.3 and Fig. 2.2, there are three possible mechanisms of a pathogen to induce RCD: via (1) unsuccessful stress responses, (2) PRM-triggered death pathways, and (3) secondary secretion by PRM-activated cells of inducible DAMPs (e.g., TNF and IFNs) (for more details see Sects. 3.7.4.5, 3.7.5.5, and 3.7.6).
3.3.5 Résumé This brief description of viral virulence factors makes it clear that even the initial infection of a cell with a virus initiates already an antiviral DAMP-induced inflammatory defense response. Certainly, viral replication-induced molecular perturbations and viroporins operating as virulence factors do not appear to constitute strong DAMPs inducers. Instead, it is apparently the ability of viruses to trigger stress responses and, in particular, various subroutines of RCD that can be considered the most prolific sources of DAMPs emission.
3.4 Fungal Virulence 3.4.1 Introductory Remarks Virulence, defined as the ability of a pathogen to cause stress and damage in a host leading to a disease, is also a typical characteristic of fungi (reviewed by Brunke et al. [173]). As described above for bacteria and/or viruses, fungal virulence also includes nondamaging factors such as adhesion properties, immune evasion strategies, and manipulation of effector molecules of innate immune signaling pathways, as well as indirectly damaging factors such as siderophores. Although these factors
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pave the way to induce cell stress and tissue damage to the host [174, 175], they are not addressed here further. Instead, the focus is directed on those virulence factors that are known to cause cell stress and tissue injury directly.
3.4.2 Host Membrane Distension and Disruption by Mechanical Forces Like intracellular bacteria, fungi can cause stress and damage via various physical and biochemical ways occurring during cell entry and replication in phagosomes (reviewed in [176]). Thus, membrane distension and disruption by mechanical forces are reportedly generated by expanding/protruding fungal cells. A typical example refers to C. albicans, which mediates membrane distension and remodeling. After adhesion to epithelial cells, C. albicans was shown to be either wholly endocytosed as true hypha or remain partially attached to the surface of the cell. In both cases, the hyphal expansion exerts mechanical forces toward the host membrane, leading to membrane remodeling and membrane damage [176].
3.4.3 Fungal Toxins Fungal toxins refer preferentially to mycotoxins, which are natural secondary metabolites produced by fungi, which grow on a variety of agricultural products. Dietary, respiratory, dermal, and other exposures to these metabolites produce disorders collectively called mycotoxicoses, whereas the growth of fungi on hosts produces diseases collectively called mycoses. Of note, recent research work revealed that some mycotoxins and, more recently, peptide toxins are also produced during active fungal infection in humans to cause diseases (for reviews, see Bennett and Klich [177] and, recently, Brown et al. [178]). As the term “toxin” tells us, these fungal metabolites can cause various forms of cell stress/damage and tissue injury and thus serve as typical inducers of DAMPs emissions. Without going into detail, here, a few aspects of those mycoses that are of interest to clinicians are briefly touched on. A classical mycotoxin is a gliotoxin that is produced by Aspergillus fumigatus and was shown to promote cytoskeleton remodeling of human alveolar epithelial cells and induce apoptosis of macrophages and DCs. Aflatoxins, produced by many Aspergillus species, are another group of mycotoxins that have been detected in patients with fungal infections and were found to exert various cytotoxic effects. For example, Aflatoxin B1 was observed to induce an autophagic response and release of macrophage extracellular traps (METs). Other mycotoxins detected in animal studies, such as ochratoxin, fumonisins, T-2 toxin, deoxynivalenol, zearalenone, and patulin, were also shown to have a broad pattern of various immunotoxic effects (not pursued any further here, for detailed reading, see [178]). A special note has to be made to the fungal cytolytic peptide toxin candidalysin. The toxin that is secreted from C. albicans hyphae was recently discovered and found to drive epithelial damage through destabilization of the integrity of plasma
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membranes and activation of epithelial immunity. Hence, the process was identified to be vital for C. albicans pathogenicity at mucosal surfaces [179]. Notably, in other lines of studies, candidalysin could be identified as a potent inducer of the DAMPs S100A8 and ATP in epithelial cells [180].
3.4.4 Fungal Extracellular Vesicles Some aspects of EVs have already been outlined above in the context of bacterial virulence. Fungal EVs contain many constituents of a cell, including NAs, proteins, toxins, lipids, and cytosolic and cell-surface proteins, some of them serving as potent virulence factors (for reviews, see [181, 182]). However, how fungal EVs can act in virulence transfer in many different contexts is still not understood and needs further investigation.
3.4.5 Résumé The recent discovery of a fungal hyphae-secreted peptide toxin, candidalysin, is of considerable importance for our understanding of the ability of mucosal surfaces to discriminate between commensal and pathogenic fungi. Thus, the fungus C. albicans is normally a commensal member of the human microbiota but, on the other hand, can cause severe and life-threatening mucosal infections in immunosuppressed hosts [183]. Indeed, as mentioned in Sect. 2.8.2, for a variety of fungi, the phenomenon of dimorphism is critical for the pathogenesis of infectious fungal diseases. Hence, the ability of C. albicans to shift from yeast to invasive filamentous hyphae, associated with secretion of the peptide toxin, appears to be a key step in gaining virulence, that is, by acting as a damaging-inducing pathogen to contribute to infectious pathogenesis (also compare here [184]). Contrary to toxins, the virulence capacity of EV formation is still less explored. Together, as can be seen from the brief summary, research on fungal toxin evoking emission of DAMPs in the host is in its infancy. Nevertheless, given the considerable biological impact of mycotoxins, peptide toxins, and EVs on fungus-mediated pathologies, and given the first reports on the emission of DAMPs in oropharyngeal candidiasis [185], an increase in research activities in this field can be expected in the near future.
3.5 Parasitic Virulence 3.5.1 Protozoan Virulence Protozoan pathogens have several virulence factors that are analogous to bacterial and viral pathogens, including adhesins, toxins, and subversion mechanisms that allow them to survive and grow inside phagocytic vesicles in phagocytes. Again,
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from der perspective of this chapter, stress/damage-inducing virulence factors are of major interest. In protozoa, proteases belong to this group of molecules. For example, Plasmodium spp. and Trypanosoma cruzi express high levels of protease activity to efficiently degrade host proteins like hemoglobin. On the other hand, Entamoeba histolytica, the causative agent of amebiasis, releases proteases, which can damage host cells and tissues, contributing to host tissue damage (reviewed in [186]). Of note, in malaria pathogenesis, malaria parasites enter and infect RBCs resulting in their sequestration, cytoadherence, as well as schizont rupture→cell lysis [187]. The parasite egression process can be considered a potent damaging virulence factor that is associated with the release of large amounts of DAMPs such as heme, uric acid, host NAs, and molecules encapsulated in EVs (reviewed in [188, 189]) (the topic is resumed and reviewed in Sect. 5.6). Similarly, Toxoplasma gondii was shown to leave the infected host cell upon a tightly controlled process of parasitophorous vacuole and host membrane rupture associated with subsequent cell lysis [190], again serving as a productive source of DAMPs emission. In other parasites, damaging virulence factors have been less well studied. In Leishmaniasis, GP63, also called leishmanolysin, has been reportedly found to be involved in pathogenesis. The protein is a zinc-dependent metalloprotease that has been shown to cleave a rather wide array of proteins and degrade components of the ECM, such as collagen IV and fibronectin. Together with other subversion mechanisms, such as modulation of signaling pathways in macrophages, GP63 has been identified as a potent virulence factor (reviewed in [191]). For virulence factors of T. cruzi, cysteine peptidases such cruzi, phospholipases, and activation of the lectin complement pathway have been discussed [192]. T. gondii virulence has been mainly investigated in mice, and proteases were suggested to operate as strong virulence factors [193]. However, little is known about virulence factors concerning human infection, in particular concerning damaging virulence factors (described in [194]). Last but not least, it should not go unmentioned here that intracellular protozoan pathogens—like bacteria, viruses, and fungi—can exploit exosomes to transfer some pathogen-derived molecules into host cells, where they act as virulence factors. However, not only parasite-derived exosomes but also host-derived exosomes released from host cells after parasite invasion are implicated in the pathogenic mechanisms of parasitic diseases (reviewed in [195]). This has been shown for Plasmodium, Leishmania, Toxoplasma, and Trypanosoma.
3.5.2 Helminthic Virulence Helminths do not replicate in the mammalian host as microbes do, so thus far, purposeful damaging factors have not been explicitly and precisely defined as virulence factors. Nevertheless, it is clear that helminths produce “virulence factor-like” proteins that facilitate immunoevasion and manipulation of the host immune defense
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response, aimed at living longer inside the host to cause long-term infections. They are not covered here. On the other hand, distinct damaging factors have been described, such as enzymes, although they have not been explicitly identified as typical virulence factors. For example, Nematodes produce a variety of enzymes for host tissue digestion and feeding. In addition, venom allergen-like (VAL) proteins are suspected of mediating damage as they are homologs of vespid venom proteins, the latter of which is locally toxic. Interestingly, VAL proteins were shown to be highly immunogenic, promoting both cellular and humoral adaptive immune responses in humans (reviewed in [196]). Similarly, Trematodes, mainly by the early intra-mammalian life stages of liver and blood flukes, secret proteases, in particular, cathepsins, which are thought to be responsible for the digestion of host tissue and blood during migration and feeding as the parasite’s gut begins to develop (reviewed in [197]). Also, Schistosomes are known to deliberately expose proteins and glycoproteins on their surface or release them into their host environment. Proteins secreted and needed for digestion include hydrolytic enzymes such as cathepsins (reviewed in [198]). Like other pathogens, helminths release protein/lipid/NA-containing EVs, which may provide widespread effects (e.g., immunomodulatory/immunoprotective effects) on host cells (for further reading, see [199, 200]). However, reports of targeted investigations for distinct damaging virulence factors such as toxins are apparently scarce. Thus, the topic will not be pursued further here.
3.6 Cell-Autonomous Stress Responses During Infections 3.6.1 Introductory Remarks Clearly, as outlined in the first part of this chapter, pathogens have various facilities to evoke cellular stress, culminating in their ability to cause the host’s cell death. What does the infected host have to counter this? Notably, as the first line of defense, it is the cell-autonomous stress responses. In fact, an increasing amount of publications in the international literature provides convincing evidence that cell-autonomous, cell-intrinsic stress responses are initiated not only by sterile but also by infection-mediated stress. (For the nature and mechanisms of stress responses, also see Vol. 1 [1], Chap. 18 plus Figs. 18.1–18.7, pp. 377–426). The ultimate goal of those responses, which are all highly conserved among eukaryotic species, is to maintain cellular homeostasis and ensure cell integrity. As concluded in Vol. 1 [1], Sect. 18.7, p. 412, one of the characteristic features of cell-autonomous stress responses is their interconnectivity and interdependency. Strikingly, this kind of interconnectedness is not restricted to a collaboration between the stress responses but expands to the elicitation of innate and adaptive immune processes. Again, the DAMPs, in terms of a particular hierarchy in their emission, appear to take center stage in this scenario—a topic that is briefly highlighted in the following.
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3.6.2 Extracellular Vesicle Formation upon Pathogen-Mediated Cell Stress Although generally not included in the spectrum of classical cell-autonomous stress responses, the formation of EVs upon stress should serve as the beginning of this topic. And there is another reason for this action: the formation of EVs amazingly reflects the evolutionary arms race between bacteria and mammals, whereby both rivals use them as the same weapons for their mutual defense! Indeed, in mammals, EVs can be released from both stressed living cells and dying apoptotic cells. Extracellular vesicles are usually divided into two distinct types, the ectosomes originating from the plasma membrane and the exosomes from endocytic/endosomal membranes. Ectosomes are vesicles that bud outward from the surface of the plasma membrane and consist of microvesicles, microparticles, and large vesicles in the size range of ~50–500 nm in diameter. Exosomes are EVs with a size of ~50–150 nm in diameter and, via sequential invagination of the plasma membrane, ultimately lead to the formation of multivesicular bodies (MVBs), which are later destined to undergo regulated exocytosis, leading to the extracellular release of exosomes (Fig. 3.6; for exosomes, also see Vol. 2 [29], Sect. 3.6.3.2, p. 83).
Endocytosis
Late sorting endosome
MAMPs/ DAMPs Early sorting endosome
MVB
Exosomes
Early sorting endosome
Secretion into the cytosol
Disintegration
e.g., DAMPs/ MAMPs Ectosomes Lysosome
Stressed cell
Nucleus
Nucleus
Endosome rupture
Target cell
Fig. 3.6 Simplified schematic representation of a model roughly illustrating the intercellular journey of extracellular vesicles known to be critical nanocarriers of biomolecules. The two major types, the ectosomes, and exosomes, shown here, are induced, for example, by pathogen-mediated cell stress and are known to be critical carriers of both MAMPs and DAMPs. Ectosomes are generated by plasma membrane outward budding and then released extracellularly. Exosomes originate from the endosomal pathway to form multivesicular bodies, which fuse with the plasma membrane to get released. Following uptake by target cells, the molecular cargo of the vesicles (e.g., DAMPs) is suggested to be secreted/released into the cytosol to induce a cascade of innate immune signal transduction events in those cells (e.g., DAMP-triggered proinflammatory pathways) (not shown). MVB multivesicular body (sources: [201–206])
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The EVs usually contain pathogen-derived molecules (i.e., MAMPs) but also many constituents of a cell, including NAs, proteins, toxins, lipids, and cytosolic and cell-surface (antigenic) proteins. Of note, however, and important from the perspective of the book, EVs were found to contain DAMPs amongst those other host molecules. Thus, exosomal DAMPs include, but are not limited to, HMGB1, histones, HSPs, extracellular adenosine 5′-triphosphate (eATP), and NAs. Upon release, exosomes and ectosomes navigate through extracellular fluid for varying times and distances. Subsequently, they interact with host cells and undergo fusion with endocytic or plasma membranes. Following this, the vesicle membranes integrate into their fusion membranes and release their luminal cargoes, such as DAMPs, into the cytosol (Fig. 3.6). In other words, we are dealing here with an important secretion pathway of peculiar inducible DAMPs (compare Vol. 2 [29], Sect. 1.2 and Fig. 1.1, pp. 3–5; for further reading, see [201–206]). Although, in general, the physiological purpose of generating EVs remains elusive, there might be a plausible explanation in view of the Red Queen paradigm: with reference to a modern holistic view of the intrinsic nature of the universal defense system, one may discuss that generation of EVs reflects a response upon any stress and/or injury. More specifically denoted for EVs in infections: the process of EV biogenesis, in a way, mirrors the cell’s defense response to pathogen- induced cell stress and damage in the sense of proving and delivering DAMPs in a sophisticated way, a process aimed at restoring homeostasis. Indeed, mammalian EVs—reminiscent of bacterial MVs/OMVs mentioned above in Sect. 3.2.3.5— clearly represent a unique secretory defense mechanism: an evolutionary arms race between mammals and bacteria using the same weapons.
3.6.3 Autophagy in Defense Against Pathogens 3.6.3.1 General Remarks The topic of autophagy as a process induced by MAMPs and DAMPs but also serving as a source of DAMPs emission has been discussed and illustrated in Vol. 1 [1], Sect. 18.2 and Fig. 18.1., pp. 377–388, as well as Vol. 2 [29], Sect. 4.2.2, p. 118 (for more recent information on Autophagy Regulation in Innate Immunity, see [207]). As outlined in Vol. 1 and Vol. 2 in detail (together with a quotation of competent articles), autophagy is a lysosome-mediated degradation and recycling pathway that involves the formation of multiple membrane structures ranging from phagophores to autophagosomes and autophagolysosomes. The autophagosomes need the intervention of autophagy-regulated (ATG) proteins to develop into autolysophagosomes through docking and fusion with lysosomes. Internalized material includes all kinds of cell components and organelles, which are degraded by lysosomal enzymes for recycling. A specialized form of selected autophagy, known as xenophagy, serves as an innate immune defense response against pathogens. Of note, however, autophagy/xenophagy of pathogens can be considered a double-edged sword: According to the previously often cited evolutionary arms race, this stress response does not only represent a defense mechanism of the host but also, on the other hand, is hijacked and used by bacteria and viruses for their own benefit.
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3.6.3.2 Xenophagy of Intracellular Bacteria and Viruses During bacterial or viral infection, the innate immune system induces an autophagic/xenophagic machinery to provide a series of barriers against those invading pathogens (for reviews, see [208, 209]). Xenophagy of bacteria consists of mechanistic procedures similar to those mentioned above for canonical autophagy. Invasive intracellular bacteria are firstly tagged by ubiquitin, whereby this process can be regarded as the key event in triggering antibacterial xenophagy (for ubiquitination, also compare Vol. 1 [1], Box 18.2, p. 379). Subsequently, ubiquitinated bacteria are captured by and interact with ubiquitin-binding protein adaptors (i.e., autophagy adaptors such as p62, NDP52, and optineurin) to be recruited to the autophagosome→autophagolysosomes, where they are degraded by lysosomal hydrolases (compare Vol. 1 [1], Fig. 18.1, p. 381; for more details, see [210, 211]). Also, xenophagy is a potent weapon of host cells to defend against viral infection. In fact, multiple mechanisms during virus infection, such as cellular stress during replication or even the viral protein itself, can activate autophagy, whereby the autophagosomes deliver trapped viral components/particles to the lysosome for degradation; that is, degradation of viral components, viral particles, and host factors needed for viral replication (the process called virophagy). Specifically, the autophagic machinery can initiate antiviral innate immune responses via PRM- triggered signaling pathways to induce type I IFN production (for PRM signaling, see next chapter). Also, following degradation, autophagy has been shown to contribute to adaptive immunity by generating viral antigens for presentation to T cells. In fact, as outlined in Vol. 1 [1], Sect. 31.3.5, p. 740, in specialized/ committed APCs like DCs, the presentation of peptides derived from viral antigens on MHC-I molecules is essential for the initiation of CD8+ T cell responses against these extracellular antigens. This process in which exogenous antigens are presented on MHC-I molecules is referred to as cross-presentation, that is, a non-canonical MHC-I presentation that is crucial for the generation of CD8+ CTL responses (for further reading, see reviews under [209, 212]). At this point, it should not go unmentioned that both bacteria and viruses have evolutionarily developed a variety of strategies to disarm xenophagy/autophagy, leading to a persistent intracellular survival, colonization, and replication of the pathogens. On the bacterial side, such strategies to escape the host-executed autophagic machinery include specialized SSs (e.g., T3SS and T4SS, see Sect. 3.2.3.4) to transport effectors for disabling autophagy, such as disarming the PRMs sensing, blocking autophagosome formation, suppressing autophagosome and autophagolysosome formation, as well as harnessing autophagy as a platform for bacterial replication [211]. On the viral side, the specific molecular mechanisms that various viruses utilize to repurpose autophagy for their life cycle and pathogenesis include evasion of autophagic degradation, manipulation of autophagosomes for replication, as well as interference with autophagosome formation and fusion with the lysosome, which benefits viral replication and virion production.
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3.6.3.3 Concluding Remarks Taking together the description of autophagy as outlined here as well as in Vol. 1 [1] and Vol. 2 [29], this classical cell-autonomous stress response in infections can be appreciated again in light of the Red Queen principle: On the arms race side at the host, DAMPs, in interaction with PRMs, elicit autophagic defense responses as efficient weapons of the innate immune system to cope with infection (for a comprehensive review, see Zhu et al. [213] who also discussed this topic intensely). On the other arms race side, pathogens have evolved mechanisms to counteract the effects of DAMPs. Thus, bacterial species use unique strategies to manipulate the host autophagic machinery aimed at providing both resources and nutrients for their replication as well as mitigating host defense responses. Viruses, on the other hand, manipulate autophagy for their immune evasion, replication, and release from infected cells, whereby the repertoire of mechanisms used by them to interfere with the autophagic machinery is amazing.
3.6.4 Oxidative Stress and Antioxidative Stress Responses There is increasing evidence of a role of oxidative stress in infections, in particular, viral infections, less so in bacterial infections, as indicated by the production of ROS and reactive nitrogen species (RNS). The increase in oxidants is mainly produced by activated phagocytic cells of the host in terms of an anti-pathogen immune defense response: a critical process for the clearance of pathogens. Moreover, various viruses on their own induce oxidative stress that, in turn, enhances specific mechanistic steps of their intracellular replication, that is, lifecycle. Typically, the infection-associated, primarily pathogen-directed oxidative stress creates a highly cytotoxic milieu that contributes to collateral damage to target organs. This deleterious effect to host cells, as caused by the excess of oxidants, is countervailed by the oxidative stress response encompassing three main tiers as described in Vol. 1 [1], Sect. 18.3.3.2, pp. 393–395: (1) antioxidant enzymes including superoxide dismutase (SOD), catalase, and glutathione (GSH); (2) detoxifying enzymes such as glutathione peroxidase (GPX), glutathione S-transferase, aldo-keto reductase, and aldehyde dehydrogenase; and (3) energy-dependent efflux pumps. As a fourth defense system, the antioxidant nutrients, such as vitamins E and C, as well as carotenoids, were appreciated. Notably, most genes coding for detoxifying and cytoprotective enzymes are regulated by the oxidant-promoted Kelch-like ECH-associated protein 1 (Keap1) – nuclear factor erythroid 2 p45-related factor 2 (Nrf2)-triggered antioxidant response element (ARE) pathway as described and illustrated in Vol. 1 [1], Sect. 18.3.3.3, pp. 395–398 as well as in Vol. 2 [29], Sect. 4.2.3. pp. 119–121. Of note, recent studies on multiple Keap1-mutant mice lines performed by Suzuki et al. [214] revealed that Keap1 uses the cysteine residues redundantly to set up an elaborate fail-safe mechanism in which specific combinations of these four cysteine residues can form
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a disulfide bond to sense hydrogen peroxide (H2O2), the central redox signaling metabolite [214]. Thus, intracellular, pathologically accumulated H2O2 reflects a redox change that is consistent with the presence of dysDAMPs (i.e., IIC-4DAMPs), which in turn are sensed by Keap1. This scenario then lends support to the concept that, during infections, the antioxidative Keap1 – Nrf2-triggered ARE pathway is initiated by oxidative stress-induced dysDAMPs. In fact, this pathway is a robust oxidative stress response. Its regulatory mechanisms, for example, stress-sensing mechanism, proteasome-based regulation of Nrf2 activity, and selection of target genes, have been elucidated mainly in mammals. Nevertheless, the pathway is now regarded as an evolutionarily conserved, efficient antioxidant defense mechanism against oxidative and xenobiotic stress across the tree of life (for further reading in the field of this section topic, see [158, 215–217]). Finally, it is worth noting that evidence is emerging that when antioxidative mechanisms fail, excessive production of ROS may lead to lipid peroxidation resulting in ferroptosis [218] (for further information on ferroptosis, see below).
3.6.5 The Heat Shock Response The heat shock response (HSR)—one of the most ancient and evolutionarily conserved cytoprotective mechanisms found in nature—is induced upon exposure of living cells to sterile and pathogen-mediated stress conditions (described and illustrated in Vol. 1 [1], Sect. 18.4 and Fig. 18.5, pp. 398–401). Induction of the HSR by putative DAMPs is apparently not yet explored and remains to be elucidated. Current notions hold that stress-induced intracellular perturbations reflected by protein aggregates operate as molecular signals that activate HSF1, which serves as a kind of recognition receptor [219]. This defensive HSR is characterized by the expression of a group of phylogenetically conserved intracellular HSPs, which possess the capacity to protect cells from high temperature and other forms of stress, thereby maintaining cellular homeostasis. Via activation of TLR-expressing cells of the innate immune system, HSPs, in their function as inducible IIIA-1 DAMPs, can induce strong innate and adaptive immune defense responses, including responses against invading pathogens. In addition, via activation of TLR-bearing DCs, HSPs possess a crucial role in MHC-antigen processing and presentation (for reviews, see [220, 221]). As comprehensively reviewed by Bolhassani and Agi [221], HSPs have been detected in bacterial, viral, fungal, and parasitic infections, clearly indicating the ability of pathogens to induce this class of inducible DAMPs. For example, bacterial infections were reported to promote the induction of the HSR [222, 223]. Also, in studies on H. pylori and E. coli infection models, the initiation of an HSP70 stress response could be demonstrated [224, 225]. On the other side and again, pathogens use HSPs for their own benefit. For example, a number of HSPs such as HSP70 and HSP90 have been reported to be supportive factors in the process of hepatitis B virus (HBV) replication, and selective inhibition of these HSPs was proposed to be host-based anti-HBV strategies [226– 228]. Certainly, as also concluded by Bolhassani and Agi [221], further studies are
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needed to evaluate the induction and regulation of HSPs during different infections and determine the specificity of HSP responses in a variety of infectious diseases and their use as biomarkers.
3.6.6 Endoplasmic Reticulum Stress and the Unfolded Protein Response 3.6.6.1 General Remarks Mounting evidence is coming to light, clearly indicating that viruses and bacteria also induce ER stress, thereby activating a robust UPR. In fact, the constitution of cellular stress responses is meanwhile regarded as the first line of defense against both viral and bacterial infection. However, as with other stress responses, the outcome is not always in favor of the host; the pathogen may also profit from this stress response, at least under certain circumstances. Some aspects of ER stress and the UPR have been described and illustrated in Vol. 1 [1], Sect. 18.5 and Fig. 18.6, pp. 401–408, as well as in Vol. 2 [29], Sect. 4.2.5 and Fig. 4.1, pp. 122–126. In brief: The ER is mainly responsible for the correct folding and PTM-driven maturation of proteins destined for other organelles. As a subcellular organelle in the control of proteostasis, it is also accountable for calcium storage, detoxification of chemical compounds, and lipid biosynthesis, as well as for the orchestration of the protein transport along the classical/ conventional secretory pathway. Perturbation of ER-associated functions such as accumulation of unfolded/misfolded proteins requiring increased correct folding, mutations in specific proteins, excessive ROS production, hypoxia, as well as calcium and glucose depletion induce stress of the organelle and result in activation of an ER stress-coping response, the evolutionarily conserved UPR. Of note—as already highlighted in Vol. 2 [29], Sect. 4.2.5.2, pp. 123–125—there is convincing evidence indicating that ER stress, the autophagic machinery, and ROS-mediated oxidative stress typically interact and interfere with each other [229, 230]. 3.6.6.2 Dyshomeostatic DAMP-Triggered Pro-Death Pathways of the Unfolded Protein Response In line with the tenor of the book, the ER stress-associated molecular perturbations reflect the generation of dysDAMPs, which are sensed by three stress sensors of the UPR embedded in the ER membrane: the PERK, inositol-requiring protein 1α (IRE-1α), and activating transcription factor 6 (ATF6) (illustrated in Vol. 1 [1], Fig. 18.6, p. 402). Under remediable ER stress conditions, the three sensors trigger signaling pathways to resolve ER stress aiming at maintaining cellular integrity and cell survival. In cases of severe irremediable ER stress, however, the pro-survival pathways fail, and the balance is tipped in favor of pro-death pathways, resulting in subroutines of RCD (reviewed in [231, 232]) such as apoptosis [233], necroptosis [234, 235], inflammasome-mediated pyroptosis [236, 237], and ferroptosis [238], known to be associated with the release of DAMPs. And interestingly enough, there is evidence for a striking interconnectedness of the ER stress-promoted UPR with the diverse subroutines of RCD signaling [232] (Fig. 3.7).
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Bacterial, Viral Infections ER stress ↔ Oxidative Stress (dysDAMPs) UPR
Stress Sensors --- Signaling --U P R
e.g., TXNIP RIPK1 Casp. 8
Autophagy
Cell survival
NRF2? ATF4
NLRP3
Casp.3/7
MLKL
GSDMD
Apoptosis
Necroptosis
Pyroptosis
?
Ferroptosis
Release of DAMPs
Fig. 3.7 Simplified schematic diagram of ER stress—UPR-promoted pro-death signaling pathways in bacterial/viral infections, that is, induction of subroutines of RCD, serving as sources of DAMPs in defense against infections. Of interest here is the evidence for a striking interconnectedness of the ER stress-promoted UPR with the diverse subroutines of RCD signaling. Note: details of the signaling pathways resulting in necroptosis and pyroptosis are shown in the subsequent figures. ATF4 activating transcription factor 4, Casp caspase, dysDAMPs dyshomeostatic DAMPs, ER endoplasmic reticulum, GSDMD gasdermin D, MLKL mixed lineage kinase domain-like protein, NRF2 nuclear factor-erythroid 2 p45-related factors 2, RIPK1 receptor-interacting serine/ threonine-protein kinase 1, TXNIP thioredoxin-interacting protein, UPR unfolded protein response (sources: [231–238])
3.6.6.3 Bacterium-Induced ER Stress→Unfolded Protein Response Accumulating evidence indicates that ER Stress→UPR plays multiple roles during bacterial infections. Thus, as comprehensively reviewed by Celli and Tsolis [239] and Choi and Song [240], the UPR has been shown to be induced in murine lungs by M. tuberculosis (associated with apoptotic events) and also be correlated with Helicobacter-induced gastric carcinogenesis. Similarly, in vitro infectious models have revealed UPR induction in macrophages and epithelial cells infected with either Brucella melitensis and B. abortus or Listeria monocytogenes. Notably, diverse extracellular bacteria induce this stress response by various virulence factors such as exotoxins and endotoxin, whereas intracellular bacterial pathogens promote it via other mechanisms; for example, by upregulation of the molecular chaperone binding protein (BiP), as shown for Chlamydia. On the other hand, there is evidence suggesting that bacteria can subvert the UPR for their own advantage. Nevertheless, indications that bacteria can modulate this response are still somewhat sparse. One example refers to L. pneumophila, which recruits components of the ER-associated protein degradation (ERAD) on its
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vacuole to mediate turnover of bacterial effectors on the vacuolar surface and uses the proteasome to generate amino acids necessary for its intracellular growth (for ERAD, also see Vol. 1 [1], Sect. 18.5.2.2, p. 403).
3.6.6.4 Virus-Induced ER Stress→Unfolded Protein Response There are several mechanisms that describe how a virus can induce ER stress. The central mechanisms of perturbation of the ER during virus infection can be seen in the production of large amounts of viral proteins by the virus concerned (e.g., exemplified by the intracellular SARS-CoV-2 life cycle described and illustrated in Sect. 3.3.2 and Fig. 3.5). Such accumulation of viral proteins in the ER implies a challenge to the protein folding machinery, which may cause ER stress and, in turn, activate the UPR resulting in restoration of the ER homeostasis or apoptosis. So far, at least 36 viruses have been found to be able to induce ER stress and activate the three UPR stress signaling pathways [241]. Moreover, ER stress can be caused by viruses via other mechanisms, for example, as a result of ER membrane exploitation, imbalance of calcium concentration, or sabotage/depletion of the ER membrane during virion release (for further reading, also see [242, 243]). Finally, the viroporins as briefly described above in Sect. 3.3.3 have to be stressed here again, as they were shown to mediate virus-induced ER stress in a typical fashion [244] (also see below, Sect. 3.7.5.5). Intriguingly, as discussed [245], many viruses have evolved strategies aimed at continuing the replication cycle. Thus, viruses were shown to manipulate the host UPR in various ways to stimulate protein synthesis capacity and to improve cell survival by inhibiting cellular apoptosis. In particular, the link between UPR and autophagy is intensely discussed to be involved in this scenario. These two systems may act dependently, or the induction of one system may interfere with the other [246]. 3.6.6.5 The Integrated Stress Response Of note, in relation to the HSR and UPR, the integrated stress response (ISR) has gained increasing attention as recently reviewed by Costa-Mattioli and Walter [247]. This stress response refers to a central and evolutionarily conserved signaling network that responds to stress perturbations from both the lumen of the ER and the cytosol. As discussed by the authors, induction of ISR can be coupled to UPR and HSR activation in that ISR signaling nucleates diverse stressors, including proteostasis defects, nutrient deprivation, viral infection, and oxidative stress. Accordingly, the various stresses are sensed by four specialized kinases including PERK and protein kinase, regulated by dsRNA (PKR), which converge on phosphorylation of a single serine on the eukaryotic translation initiation factor eIF2α (for eIF2α, also compare Vol. 1 [1], Sect. 18.5.2, Fig. 18.6, pp. 401–406). Recent genetic and pharmacological evidence suggests that targeting ISR reverses cognitive dysfunction as well as neurodegeneration in a variety of memory disorders that result from disturbances in protein homeostasis. Costa-Mattioli and Walter [247] further outlined that the ISR is involved in the pathogenesis of a plethora of complex diseases, including cancer (e.g., induction of ICD, see Sect. 9.3), diabetes, and metabolic disorders.
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3.6.7 DNA Damage Response 3.6.7.1 General Remarks The DDR has been covered in Vol. 1 [1], Sect. 18.6 and Fig 18.7, pp. 408–412 and is not resumed here. In sum, this stress response is controlled by three PI3K-related kinases (PIKKs): the ataxia telangiectasia mutated (ATM), the DNA-dependent protein kinase (DNA-PK), and the ataxia telangiectasia and Rad3 related (ATR) kinases. Various exogenous and endogenous factors, including ionizing radiation, chemical reactions, oxidative stress, and replication stress, are known to induce diverse lesions in the DNA, such as bulky adducts, collapsed DNA replication forks, single-strand DNA breaks (SSBs), and DSBs acting as cell-intrinsic modified DAMPs (IIC-1 DAMPs). Two highly intranuclear multiprotein complexes, Mre11– RAD50–NBS1 (MRN) and Ku70–Ku80 (Ku), are considered the primary sensors of DSBs to activate ATM and DNA-PK subsequently. Also, there is the first evidence suggesting that the replication protein A (RPA) is a recognition molecule that can sense ssDNA as well as PRP19, which is thought to act as a sensor of RPA- ssDNA; both sensors were shown to activate ATR downstream. These recognition receptors enable cells in response to those DNA damages to initiate and activate a complex network of cellular signaling cascades that cooperate to sense and repair lesions in DNA. Indeed, the DDR orchestrates many cell-surviving processes, including the execution of DNA repair, regulation of cell-cycle checkpoints, and commencement of protective transcriptional programs. However, when the damage is too severe, the stress response can fail and, in turn, drives the initiation of cellular senescence and RCD (apoptosis, necroptosis, parthanatos [248–250]). 3.6.7.2 Activation of the DNA Damage Response by Infections Maintaining genome integrity and transmission of intact genomes is a condition sine qua non for cellular, organismal, and species survival. This homeostatic integrity is also threatened by DNA damage associated with the generation of cell- intrinsic modified DAMPs such as DNA breaks that occurs in infections, which reportedly can provoke a DDR via various mechanisms. Here, only a few aspects of this emerging topic are addressed. Viral Activation of the DDR Many DNA and RNA viruses and viral gene products are known to provoke activation of the DDR during their replication, whereby the activation process can be broad, including the involvement of ATM, ATR, or DNA-PK. Successful activation of the DDR can promote efficient prevention of viral replication. Mechanistically, activation of the DDR can be induced directly by viral replication proteins that cause DNA lesions, for example, DNA breaks [251], or indirectly by oxidative stress (e.g., ROS) or “misrecognition” of viral DNA and viral replication intermediates as damaged nuclear self-DNA (for further reading, see [252–255]). Nevertheless, the precise molecular mechanisms for virus infection-induced DDR activation remain poorly understood. Finally, and worth noting again, viruses have, in return, evolved counterstrategical mechanisms to evade the DDR for the
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benefit of replication and thereby successfully maintain themselves in the host cell [252, 253, 255]. Bacterial Activation of the DDR As reviewed by Chumduri et al. [256], bacterial infections can induce various types of DNA damage. For example, bacteria-induced ROS and RNS can directly provoke SSB. In addition, bacteria-caused DNA damage can be mediated either directly through the formation of toxins with genotoxic activities or indirectly as a result of immune defense mechanisms against the pathogen. Among bacterial genotoxins, three have been identified so far: the cytolethal distending toxin produced by Gram- negative bacteria, the typhoid toxin, and colibactin produced by strains of Escherichia coli (reviewed in [254, 257, 258]).
3.6.7.3 Concluding Remarks Of note, as shown for other DNA damaging agents, severe pathogen-induced DNA damage beyond repair might induce a DDR that drives initiation of RCD, that is, apoptosis and, still unproven, necroptosis and parthanatos [248–250]. Thus, future studies are needed to explore whether this possibility may represent another source of infection-triggered production of DAMPs.
3.6.8 Résumé The cursory presentation of the role of cell-autonomous stress responses in infections should make clear that every cell of mammalian organisms intrinsically possesses such powerful tools to react to pathogen-provoked cellular perturbations and injuries. From the tenor of this book, the focus is directed on mounting evidence indicating that the adaptive stress responses are instigated by stress-induced DAMPs (e.g., dysDAMPs and cell-intrinsic modified DAMPs) aimed at restoring cellular homeostasis. If these DAMP-promoted innate immune responses fail, the cell switches the lever by now envisaging RCD associated with the emission of DAMPs, intended to restore systemic organismal homeostasis via the creation of an inflammation-promoting and inflammation-resolving defense response (compare Sect. 2.5.3 and Figs. 2.2 and 2.4).
3.7 Regulated Cell Death as Prolific Sources of DAMPs: A Powerful Host Defense Program Against Infection 3.7.1 Introductory Remarks The thread of the Red Queen paradigm can be spun further with reference to the phenomenon of RCD induced by the host upon severe insults caused by the pathogen. As already outlined in the previous chapter, on the host side, RCD is an effort of the host to cope with the pathogen by the provision of DAMPs able to drive
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controlled effective immune defense response and restore organismal homeostasis; on the pathogen side, RCD is an effort to manipulate this host response to maintain and promote fitness of the pathogenic invader. In fact, the topic of RCD appears to be the most critical part of Part II (Infections) because it supports the concept of the danger/injury model in Immunity, holding that it is the infectious stress/injury mediated by pathogens—and not the infectious agents per se—that provokes and promotes the robust inflammatory defense response of the host against the pathogen substantially; a response that, simultaneously, governs and orchestrates the pathogenesis of infectious diseases (cf. Fig. 2.2)! Indeed, today, subtypes of RCD are generally recognized as a powerful well- controlled cell defense response against infections, mainly for two reasons: First, and most importantly, the cell death process leads to the release of constitutive DAMPs via membrane rupture, although the mechanisms of release appear to differ between the DAMPs [204] (compare Fig. 1.1). Subsequently, these DAMPs, via activation of neighboring innate immune cells, promote the production of inducible DAMPs. Both classes of DAMPs, in interaction with MAMPs, then promote and shape robust antimicrobial and antiviral innate/adaptive immune responses, thereby extending the host's defense, initially limited to the cell, to efficient protection of the whole organism against the pathogenic invaders. Second, and not to neglect, death of the infected cell implies the removal of a source of replication used by intracellular infectious agents, thereby exposing the freed pathogens to other immune killing mechanisms such as the cytotoxic action of natural killer (NK) cells and CD8+ T cells. In addition, and in accordance with new research data, there is a striking interconnectedness between the diverse subroutines of RCD signaling [259] (Fig. 3.7). Notably, however, besides the beneficial and protective defense responses to pathogenic invaders mediated by those DAMP-producing RCD processes, the cell death program may turn out to become detrimental by (1) a nonresolving inflammatory response as seen, for example, in chronic inflammatory diseases, or (2) a dangerous, life-threatening hyperinflammatory response associated with a severe acute disorder or even fatal outcome of the patient: The tenor of this book! In the following, this emerging topic in infectiology is presented with two restrictions: first, not all aspects of RCD, but only those of interest for infections are discussed; second, details of RCD as described in Vols. 1 and 2 have meanwhile been modified and corrected in an increasing number of recently published articles, reflecting the dynamic development in this emerging field of biomedicine (therefore, for more recent in-depth information, the reader is referred to competent reviews, for example, quoted under [260–264]).
3.7.2 Subroutines of Regulated Cell Death The various subroutines of RCD, initiated by a variety of sensors in the innate immune system, have been addressed in Vol. 1 [1] of the book, Chap. 19, pp. 427–469, and Vol. 2 [29], Sect. 4.3, pp. 127–139. In infections, the RCD spectrum
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preferentially refers to apoptosis and subtypes of RN such as necroptosis, pyroptosis, ferroptosis, and NETosis (for the definition and classification of cell death subroutines, see [264]: The Nomenclature Committee on Cell Death 2018; also see Box 4.1 in Vol. 2 [29], pp. 129/130). Since, per definition, RN is associated with an inevitable rupture of the plasma membrane, it is consequently associated with the release of large amounts of constitutive DAMPs that confer high immunogenicity to necrotic cells induced during infections [261, 265–267]. Apoptosis, known as a prototypical form of RCD and described in Vol. 1 [1], Sect. 19.2 as an immunologically silent form of cell death, has long been considered to eliminate harmful virus- infected cells (besides senescent and cancer cells) [268–270]. However, intense research in the field of infectiology has recently disclosed other subroutines of RN, which are critically involved in the pathogenesis of infectious diseases. As a consequence of RN, all necrotic cells release DAMPs, which promote a vigorous necroinflammatory response. Of note, while all RN pathways share the release of DAMPs in general, most of them actively regulate the immune system by the additional expression and/or maturation of either pro- or antiinflammatory cytokines and chemokines (reviewed in [265, 266]). Here, the topic is briefly discussed in relation to pathogen-induced necroinflammation.
3.7.3 Apoptosis→Secondary Necrosis: The Failure to Clear a Dying Cell Apoptosis is a suicidal response of the host to severe insults initiated by two major cellular signaling pathways, the intrinsic and extrinsic pathways. Some details of these death pathways have been presented in this book in Vol. 1 [1], Sect. 19.2 and Figs. 19.2/19.3, pp. 429–435 and Vol. 2 [29], Sect. 4.3.2, p. 131 (for recent reviews, see [263, 271]). Apoptosis, in contrast to the immunogenic RN of a cell, is a low degree-immunogenic form of cell death because the plasma membrane integrity remains preserved. Indeed, apoptotic cells are cleared by phagocytes; that is, they are engulfed before they leak their contents such as DAMPs, the phenomenon called efferocytosis (also compare Vol. 1 [1], Sect. 22.6.3.3, p. 562 and Vol. 2 [29], Sect. 5.3.2.2, p. 154; for review, see [272]). Expectedly, therefore, the emission of DAMPs by apoptotic cells is weak or even null. As will be discussed in the next chapter, the process of efferocytosis is promoted by SAMPs and represents an important mechanism in inflammation resolution. When, however, the process of efferocytosis is impaired, that is, when apoptotic cells are not efficiently engulfed by macrophages, they undergo secondary necrosis and can now release DAMPs [272–274]. Such DAMPs were shown to trigger usually proinflammatory pathways. However, other molecular patterns on the surface of secondarily necrotic cells have also been described to share similarities to apoptotic cells and promote a switch of phagocytes to an antiinflammatory phenotype [274]. In infections, the intrinsic mitochondria- or extrinsic cell death receptor-mediated apoptotic pathways are initiated by the host in response to cell stress and tissue
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injury caused by the pathogen. Accordingly, and very frequently, apoptosis—in particular, when induced via the intrinsic pathway—is the result of failed stress responses such as the ER stress→UPR response [275]. Activation of both pathways is mediated by MAMPs/DAMPs interacting with PRMs or by mitochondrial damage, respectively. In addition, the extrinsic pathway can be activated by cytokines (TNF, type I IFN) secreted by MAMP/DAMP-activated, PRM-bearing innate immune cells (for further reading, also see [262, 276]). The apoptotic cell death serves as a defense tool of the host against intracellular pathogens by removing their replicative niche and thus contributing to the resolution of infections. And in the case of secondary necrosis, the emission of DAMPs may contribute to the propagation of infectious inflammation. But again: pathogens have evolved a variety of mechanisms to subvert and also counter this type of RCD- mediated host defense (not discussed here, for further reading, see [262, 277, 278]). Altogether, one may insinuate that apoptosis in infections does not represent a strong tool to combat pathogens and is certainly overshadowed by other subroutines of RCD (e.g., necroptosis and pyroptosis) with respect to its anti-pathogen potency.
3.7.4 Necroptosis: A Cellular Suicide for Host Defense 3.7.4.1 General Remarks The biochemical processes in necroptosis are distinct from those found in apoptosis; in particular, there is no caspase activation. As such, necroptosis is a kinase- mediated cell death that relies on receptor-interacting serine/threonine-protein kinase 3 (RIPK3)-mediated phosphorylation of the pseudokinase mixed lineage kinase domain-like protein (MLKL). The topic was reviewed by us in [266], Sect. B and Fig. 2, and, in this book, in Vol. 1 [1], Sect. 19.3.2 and Fig. 19.4/Fig. 19.5, pp. 436–442, and Vol. 2 [29], Sect. 4.3.3, pp. 131–133 (for a more recent review, see [263]). Necroptosis has now been recognized as a robust DAMP-based cell death program that promotes defense against pathogens, in particular, viruses. 3.7.4.2 Activation of the Necroptotic Program and Cell Lysis Necroptosis, early recognized as a source of DAMPs [279], can be instigated (i.e., induced or at least sensitized to get induced) by a variety of triggers, including TNF↔TNFRI, DNA, dsRNA, TLR (e.g., TLR3 and TLR4) agonists, type I IFNs↔IFNAR, ER stress, as well as bacterial and viral stimuli. These triggers may be distinct exogenous MAMPs or molecules secondarily induced by pathogens, typically including endogenous constitutive and inducible DAMPs (e.g., full-length biologically active IL-33 [280], TNF (when CASP8 activation fails [281], and type I IFNs [282, 283] secreted by activated cells). The stimuli mediate their efferent functions via complex signaling pathways as well as direct and indirect formation of necrosomes. In brief: the RIPK1/RIPK3 complex recruits and phosphorylates MLKL; under the involvement of highly phosphorylated inositol phosphate, phosphorylated MLKL oligomerizes, thereby forming the necrosome. Then, MLKL oligomers translocate to phosphatidylinositol phosphate (PIP)-rich patches in the
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plasma membrane and form large pores. Ultimately, these pores result in necroptotic cell death by allowing ion influx, cell swelling, and membrane lysis, followed by the uncontrollable release of intracellular molecules, including DAMPs [263, 266].
3.7.4.3 The Release of DAMPs in Necroptosis Notably, the precise mechanism by which MLKL permeabilizes membranes to regulate the emission of DAMPs is by far not clear and still debated in the literature and will rely on future structural studies for resolution [284]. In this context, a recent report by Nakano et al. [267] on monitoring necroptosis and the release of DAMPs at the single-cell resolution is of interest. First observations from this study revealed unexpectedly that the duration of the release of HMGB1 is divided into two modes: a burst-mode and a sustained-mode. The authors described and discussed [267]: “In a sustained mode cell, the release of HMGB1 continued more than 100 min, whereas the release of HMBG1 terminated within 10 min in a burst-mode cell. At this moment, the biological significance of two different modes of the release of HMGB1is unclear, one might surmise that a burst-mode cell might elicit strong immune responses to the surrounding micro-environment. Alternatively, sustained release of HMGB1 might induce another cellular response, such as recruitment of immune cells.” Indeed, such studies will become most important in attempts to elucidate the dynamics of DAMPs released from various forms of RN, in particular, when induced by bacterial and viral infections. 3.7.4.4 Necroptosis in Bacterial Infections The phenomenon of necroptosis has been shown to play a pathogenetic role in some bacterial diseases such as P. gingivalis-induced periodontitis, pneumonia, and sepsis (for informative articles, see [285–292]). Notably, the vast majority of studies have produced supportive data favoring a protective role for necroptosis via inhibition of bacterial load, elimination of pathogens, and inflammation [293, 294]. Hence, the most burning question to be raised here is obviously: how can bacteria trigger necroptosis? Theoretically, many stimuli can elicit necroptosis in a direct and indirect way. Thus, necroptosis is initiated in response to TLR3, TLR4, and death receptors in the TNFR superfamily. Indeed, several ligands to these receptors have been shown to operate, including LPS, TNF, interferon-gamma (IFN-γ), and dsRNA [295]. One may add that any MAMP or DAMP involved in bacterial infection and sensed by these receptors is able to induce necroptosis. Damaging Bacterial Virulence Factors as Inducers of Necroptosis Plausibly, efficient inducers of the necroptotic pathway besides TLR agonists have to be sought among the cell-damaging exotoxins. Indeed, this mechanism has already been described. Thus, earlier reports indicated already that pore-forming toxins trigger necroptosis of alveolar macrophages during acute pneumonia caused by various bacteria (Serratia marcescens or Staphylococcal pneumonia) [88, 296]. In other lines of studies on a bacteremia/heart model in mice, Gilley et al. [297] could demonstrate that a strain-dependent pneumolysin – a cholesterol-dependent
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pore-forming toxin that kills cardiomyocytes in vitro – mediates necroptosis of myocardium-infiltrating macrophages following Streptococcus pneumoniae. Importantly, in these studies, pneumolysin was found to elicit a cytokine and chemokine response from the heart, including TNF. (This is also known from other lines of studies [295, 298] aimed to trigger the necroptotic pathway via interaction with TNFR1.) In a subsequent study, this group of researchers could show that pore- forming toxin-producing bacteria and purified exotoxin can induce necroptosis of respiratory epithelial cells [287]. Interestingly, however, the authors reported that receptor-interacting protein 1 (RIP1)→RIP3→MLKL activation following exposure to the pore-forming toxin is not death receptor-dependent but instead the result of ion dysregulation following exotoxin-induced membrane damage. Given their results, they suggested that “necroptosis may occur under a broader context of cellular insults, expand our molecular understanding of bacterial pathogenesis and programmed cell death, and add to the existing body of evidence that suggest blocking necroptosis is a way to protect against injury during bacterial infection.” Yet another mechanism of exotoxin-induced necroptosis was unearthed in studies on a human macrophage cell line (THP-1) as an infection model, used to examine the molecular mechanism of tuberculosis necrotizing toxin (TNT)-induced cell death. TNT is a nicotinamide adenine dinucleotide (NAD+) glycohydrolase secreted by Mycobacterium tuberculosis [299]. Depletion of NAD+ by TNT was found to activate the key mediators of necroptosis, RIPK3, and MLKL. However, Mycobacterium tuberculosis was observed to bypass the canonical necroptosis pathway since neither TNF nor RIPK1 was found to be required for macrophage death. The authors discussed several possible mechanisms of necroptosis activation; however, they concluded that further experiments are needed to identify the precise underlying molecular mechanisms of this phenomenon. Of interest in this context are also studies on a Salmonella typhimurium infection model in mice showing that this intracellular pathogen can induce necroptosis in macrophages [300]. In these experiments, evidence was provided revealing that type I IFN signaling through the activation of RIP kinases exacerbates necroptosis in Salmonella typhimurium-infected macrophages. Indeed, indirect evidence suggests that exotoxin-induced cytokines such as type I IFN and TNF may serve as critical necroptosis inducers in bacterial infections. For example, as shown by other sets of studies, type I IFN is able to activate necroptosis [301]. Also, streptolysin O, Clostridium difficile toxin A and B, and the cholera toxin have been reported to produce TNF; quite admittedly, however, without referring to necroptosis (reviewed in [302]). Interestingly, a recent study provided the first direct evidence suggesting that the process of necroptosis may drive antibacterial defense programs [303]). In this study, necroptosis was found to be triggered through TLR4→TRIF→RIPK3 signaling by a complex consisting of bacterial lipids (lipid IVa or lipid A; i.e., microbial lipids in Gram-negative bacteria, cf. Fig. 2.8) and HMGB1, released by activated immune cells or damaged tissue during bacterial infection (see also next chapter, Sect. 4.3.2.3 and Fig. 4.3). In fact, this study supports the concept that both MAMPs and DAMPs work in concert to orchestrate host defense responses against pathogens, a model that has been and still is being used throughout this part of the book.
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In sum, although the role of bacterial exotoxins in the activation of necroptosis appears to be proven, the precise mechanisms of how these toxins generate ligands for the death receptors triggering this form of RN await further clarifications via targeted studies. The Red Queen Paradigm in Necroptosis In view of the Red Queen hypothesis, it is not surprising that some bacteria have evolved mechanisms to interfere with and thus evade the host's necroptotic pathway for their own benefit [287, 304]. Here is just one example [305]: In studies on a Salmonella colitis model using sopB- and MLKL-deficient mice, evidence was provided suggesting that the Salmonella outer protein B (SopB) protein, a strong, via T3SS-secreted virulence factor, prevents goblet cell necroptosis. Moreover, in these studies, the downregulation of SopB expression was observed to represent a mechanism used by Salmonella to manipulate the onset of epithelial cell death to establish infection [305].
3.7.4.5 Necroptosis in Viral Infections with Reference to Influenza A Virus There is emerging evidence for the role of necroptosis in promoting inflammation and immunity in viral infections (already addressed in Vol. 1 [1] Sect. 19.3.2.3 and Fig. 19.5, pp. 439, 440, and Vol. 2, Sect. 4.3.3.3, p. 132; also see [292, 306–309]). For example, necroptotic processes have been shown to be activated by DNA virus family members such as HSV (e.g., HCMV) [310–313], HIV (RNA virus) [314, 315], respiratory syncytial virus (RSV) (RNA virus) [316], and influenza virus [317–319], in particular, IAV [320, 321]. Indeed, a distinct IAV-induced cell death pathway has been explored that is active in lung epithelial cells, and that has been demonstrated to occur in most cell death, triggered by replicating IAV in these and other primary cell types. This pathway is triggered by the IAV-perceiving sensor, ZBP1 (for Z-DNA binding protein 1, also known as DNA-dependent activator of IFN regulatory factors [DAI]). The sensor is a host protein harboring the RHIM domain, enabling its physical interaction with other RHIM-containing proteins [322–324] (for RHIM, receptor-interacting protein (RIP) homotypic interaction motif). Activation of ZBP1 obviously requires upstream activation by necroptosis inducers such as type I/II IFNs, TNF, and TLR3/4 agonists [325, 326], as well as other NA sensors. For example, recent studies suggest that recognition of IAV RNA by the RIG-I receptor initiates type I IFN– IFNAR signaling to license ZBP1 upregulation and activation [301, 327]. Recent pivotal studies over the past four years have begun to shed light on the signaling pathways underlying IAV-induced necroptotic pathway [322, 323, 328–330]. Notably, whereas observations from earlier experiments were in favor of an activation of ZBP1 outside the nucleus, a recent study provided evidence indicating activation in the nucleus of virus-infected cells [323]. ZBP1 detects so-called Z-RNAs that are dsRNAs (RNA duplexes), which are suggested to be produced during nuclear virus replication (although Z-RNA formation and ZBP1 activation outside the nucleus cannot be ruled out [323]); for Z-RNAs, see also [331–333]). Z-RNA is generally referred to as a PAMP, but according to the new definition proposed in
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Sect. 1.2.3.1 may act here as an exogenous DAMP. Activated ZBP1 then—via RHIM domains—associates with RIPK3, which phosphorylates and activates MLKL in the nucleus. Activated MLKL then triggers disruption of the nuclear envelope but also transits through the nucleus to the plasma membrane to mediate, via pore-formation, necroptotic cell death, allowing the passive release of constitutive DAMPs. Interestingly, studies on a fluorescence resonance energy transfer (FRET) biosensor, termed SMART (a sensor for MLKL activation by RIPK3 based on FRET), showed that loss of HMGB1 from the nucleus occurred rapidly and corresponded only with a short-lived increase in cytosolic HMGB1, indicating rapid release of HMGB1 via the ruptured plasma membrane into the extracellular space [334]. Emission of DAMPs in IAV-Induced Necroptosis: A Paradigm for Host Immune Defense Responses Against Pathogens Of note, induction of the IAV-triggered necroptotic cell death pathway resulting in the release of DAMPs can be considered a paradigm for the initiation of robust host immune defense responses against pathogens. Indeed, the emission of constitutive DAMPs, including NAs, results in the activation of local and distant PRR-bearing host innate immune cells such as macrophages, which in turn produce proinflammatory cytokines (including inducible DAMPs such as TNF and type I IFNs) and chemokines (Fig. 3.8a). This leads to the subsequent recruitment of neutrophils,
Fig. 3.8 (a) Simplified schematic diagram of a narrative model illustrating the release of DAMPs from influenza virus-induced necroptotic cells. Z-RNA produced by influenza viruses in the nucleus of infected cells (here symbolized by a lung epithelial cell) is sensed by host ZBP1, which activates RIPK3 and MLKL in the necrosome to lead to nuclear envelope rupture and necroptosis. Passive release of constitutive DAMPs, including nucleic acids, results in the activation of PRR- bearing innate immune cells (here symbolized by an alveolar macrophage), which produce proinflammatory cytokines (including inducible DAMPs) and chemokines. This leads to the subsequent recruitment of macrophages, neutrophils, and dendritic cells, which may be activated by inducible DAMPs to amplify the inflammatory response (not shown). cGas cyclic GMP-AMP synthase, dsRNA double-stranded RNA, HMGB1 high mobility group box 1, IFN interferon, MLKL mixed lineage kinase domain-like protein, PRRs pattern recognition receptors, RHIM RIP homotypic interaction motif, RIG-I retinoic acid-inducible gene (protein) I, RIPK3 receptor-interacting serine/threonine-protein kinase 3, ssRNA single-stranded RNA, Zα1/2 Z-form nucleic acid-binding domain1/2, TLR Toll-like receptor, TNF tumor necrosis factor, ZBP1 Z-DNA binding protein 1 (sources: [266, 292, 322, 323, 328–330]). (b) Simplified schematic diagram of a narrative model illustrating the post-IAV-triggered generation of necroptosis in lung epithelial cells via the action of inducible DAMPs such as TNF and type I IFNs secreted by DAMP-activated macrophages, as well as DAMPs such as HMGB1, to promote the second round of necroptosis induction. The repeated release of DAMPs then amplifies the innate and adaptive anti-IAV immune defense response. Note: This figure is a continuation of part (a) and should be read from the top left –(I)– (II)–(III) to the bottom right. Ag antigen, DC dendritic cell, HMGB1 high mobility group box 1, iDAMPs- inducible DAMPs, IFN-I type I interferon, IFNAR1 interferon alpha and beta receptor subunit 1, M membrane, MLKL mixed lineage kinase domain-like protein, NAs nucleic acids, PRRs pattern recognition receptors, RHIM RIP homotypic interaction motif, RIPK1/3 receptor- interacting serine/threonine-protein kinase 1/3, Zα1/2 Z-form nucleic acid-binding domain1/2, TLR Toll-like receptor, TNF tumor necrosis factor, TNFR1 tumor necrosis factor receptor 1, ZBP1 Z-DNA binding protein 1 (sources: [266, 292, 301, 303, 322, 323, 328–330, 335])
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macrophages, and DCs, which may be activated by inducible DAMPs to amplify the inflammatory defense response. In addition, inducible DAMPs such as TNF and type I IFNs, as well as DAMPs such as HMGB1, may promote the second round of necroptosis. Indeed, there is mounting evidence that these DAMPs activate the key mediators of necroptosis, RIPK3 and MLKL: TNF through TNFR1 signaling [335]; IFNs through interferon alpha and beta receptor subunit 1 (IFNAR1)→ZBP1 signaling [301], and HMGB1 through TLR4→TRIF signaling [303]). This repeated RN is again associated with the release of DAMPs that may fortify the adaptive antiviral immune defense response (Fig. 3.8b). We will face a similar scenario when discussing the pathogen-triggered pyroptotic cell death below.
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3.7.4.6 First Hints of Necroptosis Induction in Coronavirus Infection The first evidence for the development of necroptosis in SARS-CoV was provided by Meessen-Pinard et al. in studies on HCoV-OC43-induced neuronal cell death [336]. In view of their findings, the authors concluded: As necroptosis disrupts cellular membranes and allows the release of damage-associated molecular patterns (DAMP), and possibly induces the production of proinflammatory cytokines, it may represent a proinflammatory cell death mechanism that contributes to excessive neuroinflammation and neurodegeneration and eventually to neurological disorders after a coronavirus infection. Similar observations were made in other lines of in vitro studies [337], demonstrating that SARS-coronavirus ORF3a (SARS 3a) interacts with RIPK3, which augments the oligomerization of SARS 3a, helping drive necroptotic cell death. Also, and imaginable, virus-induced RN such as pyroptosis (see below) can lead to the release of constitutive DAMPs such as HMGB1 and DNA that activate PRR-bearing phagocytes, which in turn secrete cytokines such as TNF and type I IFNs. These cytokines then operate as inducible DAMPs to induce necroptosis. Of note, there are first reports on the role of necroptosis in COVID-19, and this, notably, in the context of PANoptosis [338, 339]. This burning topic will be described below in Sect. 3.7.6. 3.7.4.7 Necroptosis in Fungal Infections Host necroptotic cell death has also been observed to play a vital role in innate immune defense against fungi (reviewed in [340, 341]). For example, in response to C. albicans infection, the β-glucan receptor dectin-1, a member of C-type lectin-like receptors (CLRs) (see Vol. 1 [1], Sect. 5.2.7.2, Fig. 5.6, pp. 60–62 and Sect. 22.3.8.2, Fig. 22.9, p. 510), was recently identified as an inducer of necroptosis in host myeloid cells through the RIPK1→RIPK3→MLKL cascade [342]. More recently, the sensor ZBP1, like its action in IAV-induced cell death, was shown to induce necroptosis in the fungal pathogens C. albicans and A. fumigatus (see Banoth et al. [343]; for the role of ZBP1 in PANoptosis in response to fungal pathogens, see below Sect. 3.7.6). 3.7.4.8 Concluding Remarks Collectively, necroptotic cell death is being recognized as a potent immunogenic mechanism, enabling the host to limit infected cells and mount robust innate and adaptive immune defense responses against infectious agents (Fig. 3.8b). Typically, pathogens counteract this attack in favor of their own fitness by evolutionarily developing multiple mechanisms to manipulate this host's necroptotic cell death and survival pathways. But again, and from the perspective of this review, the benefits of necroptosis to the host should not be overestimated. Given the death of too many cells (e.g., in SARS CoV infection due to a too heavy viral load in alveolar epithelial cells), DAMPs are released in excess and can elicit a hyperinflammatory response resulting in life-threatening acute lung injury–acute respiratory distress syndrome (ALI–ARDS). As a classical DAMP-triggered life-threatening disease, the disorder will be discussed in detail in Sect. 5.4.
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3.7.5 Pyroptosis: The Result of Pathogen-Induced Activation of Inflammasomes 3.7.5.1 General Remarks Inflammatory processes caused by infections are predominantly executed by canonical and noncanonical inflammasomes. These cytosolic molecular machines are sizeable multi-molecular-weight signaling protein complexes that contribute substantially to the establishment and regulation of a pathogen-induced inflammatory milieu by producing the key inflammatory cytokines IL-1β and IL-18. As molecular platforms, they are formed in the cytosolic compartment in response to MAMPs and DAMPs or DAMPs alone. Of note, beyond the secretion of proinflammatory cytokines, pathogen-induced activation of inflammasomes plays another particularly critical role in infections by initiating pyroptotic cell death. Indeed, this subroutine of RN, occurring in multiple cell types including monocytes, macrophages, DCs, lymphocytes, epithelial cells, and ECs, and mediated by canonical and non- canonical pathways, is considered to play an essential role in the control and clearance of various infections. Activation mechanisms of the inflammasome, the inflammasome-initiated pyroptotic machinery, and the inflammasome-dependent inflammatory response have already previously been described in this book (Vol. 1 [1], Sect. 19.3.4 and Figs. 19.7/19.8, pp. 447–450, Sect. 22.4 and Fig. 22.11, pp. 514–526, as well as Vol. 2 [29], Sect. 2.2.5, Fig. 2.1. pp. 17–21 and Sect. 2.2.8, Fig. 2.2, p. 25, and Sect. 4.3.5, p. 138; for reviews, see [344–351]). Here, the topic is briefly resumed and updated by focusing on some specifics observed in infections. Indeed, inflammatory cell-death pathways leading to pyroptosis have been shown to be triggered by bacteria, viruses, and fungi (for recent reviews, see [262, 352–355]). 3.7.5.2 Types of Inflammasomes During the past three decades, several types of these molecular machines operating in the commission of the innate immune system have been discovered. They are characterized by a number of innate immune receptors, which have been reported to serve as so-called inflammasome sensors (note: these receptors, together with other innate sensors and their signaling, are described in more detail in the next chapter). The various sensors differ in their structural features and, typically, determine the name of the respective inflammasome complexes. They include the NLRP1, NLRP2, NLRP3, NLRP6, NLRP7, NLRP9, and NLRP12), NLR-family caspase activation and recruitment domain (CARD)-containing protein 4 (NLRC4), NLR-family apoptosis inhibitory protein (NAIP), absent in melanoma 2 (AIM2), and interferon- gamma inducible protein 16 (IFI16), both characterized by a PYD and hematopoietic interferon-inducible nuclear protein (HIN) domains. Of note, each inflammasome senses and becomes triggered in response to unique signals. For instance, some of these sensors, such as AIM2 and NAIP, can directly recognize and bind to cognate MAMPs or DAMPs, while expression of NLRP3 requires priming (=signal 1) via stimulation of TLRs, TNFR, or IL-1R, followed by NF-κB activation. Upregulated NLRP3 and others such as NLRP1 and pyrin
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indirectly then sense and respond to DAMPs through changes in the homeostatic environment of the cell (=signal 2 in terms of cellular molecular perturbations, i.e., presence of dysDAMPs) (for “priming” in NLRP3 activation, see Vol. 1 [1], Sect. 22.4 and Fig. 22.11; for dysDAMPs, also see Vol. 1 [1], Sect. 5.2.3, Fig. 5.3, pp. 50–55; and Sect. 5.2.5, Fig. 5.5, pp. 57–59). In contrast, the noncanonical NLRP3 inflammasome is activated by intracellular LPS derived from Gram-negative bacterial membranes (see Fig. 2.8).
3.7.5.3 Activation of the Inflammasome-Mediated Pyroptotic Program and Cell Lysis Assembly of an inflammasome complex is initiated by the interaction of a range of MAMPs and/or DAMPs with a PYD-containing inflammasome sensor such as NLRP3 (by activating signal 2) or NLRP1or AIM2 resulting in its activation, oligomerization, and the recruitment of the adaptor protein apoptosis-associated speck- like protein containing a caspase recruitment domain (ASC), which consists of a PYD and CARD domain. Importantly, the recruitment of ASC is crucial for the activation of pro-caspase-1 (containing a CARD domain) into its cleaved form, CASP1, to activate the downstream signaling cascade, while the mitotic NIMA- related kinase 7 (NEK7), a homeostatic regulator of cell division, licenses the assembly and activation of the NLRP3 inflammasome in interphase (more information, incl. references reviewed and illustrated in [1], Sect. 22.4.2.2. p. 516 and Fig. 22.11, p. 517). This process is unequivocally required for the proteolytic processing of pro-IL-1β and pro-IL-18 into the mature signaling IL-1β and IL-18 (=inflammatory path) in response to inflammasome activators. Additionally, CASP1 cleaves the protein gasdermin D (GSDMD). After cleavage, the N-terminal fragment of GSDMD (N-term GSDMD) oligomerizes to form plasma membrane pores, allowing mature IL-1β and IL-18 to leave the cell and effectively executing the pyroptotic cell death pathway via membrane destabilization. Finally, this leads to membrane rupture and cell lysis, enabling the release of DAMPs such as HMGB1 that are too large to escape the cell through the pores (Fig. 3.9) (for further reading, see [362–369]). Alternatively, a CARD-containing inflammasome sensor such as NLRC4 may directly interact with CASP1 via their respective CARDs. Indeed, the current understanding of the NLRC4 inflammasome has been proposed to be perhaps the most comprehensive illustration of the inflammasome paradigm: trigger (e.g., cytosolic flagellin), sensor (NAIP), nucleator (NLRC4), adaptor (ASC), and effector (CASP1) [370]. Taken together, the activation and regulation of inflammasomes are delicate processes that are much more complex and complicated than those touched on here in this brief overview. Thus, these cell-death processes are mediated and regulated by a wide number of transcription factors, upstream and downstream regulatory molecules such as interferon regulatory factor 1 (IRF1) and ZBP1, PTMs (e.g., a combination of ubiquitination and phosphorylation), and cellular pathways. These themes are not further pursued here; instead, the reader is referred to competent and informative articles cited at [263, 322, 350, 371–375].
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Fig. 3.9 Simplified schematic diagram of a conceptual narrative model illustrating release of DAMPs from SARS-CoV/viroporin-induced, NLRP3 inflammasome-mediated pyroptotic cells (note, read from left to right). The first priming step is exemplified by IFN receptor-triggered transcriptional pathways (NF-κB activation) to promote the upregulation of NLRP3 and pro-IL-1β/ pro-IL18 expression. The activation step is proposed to be triggered by SARS CoV viroporins via recruitment of NLRP3 to dTGN in the form of an early and common cellular event caused, for example, by virus-induced ER stress, ER stress-induced mitochondrial ROS production, calcium mobilization, and enhanced potassium efflux (marked by purple arrows). Activation and assembly of the inflammasome results in activation of Gasdermin D, whereby the CASP1-cleaved N-terminal of GSDMs oligomerizes in membranes to form pre-pores, proceeding to final pores. Via these pores, cytosolic contents, including small DAMPs and proteolytically processed matured IL-1β and IL-18, are released, leading to osmotic membrane rupture and pyroptotic cell lysis, enabling the release of DAMPs such as HMGB1 that are too large to escape the cell through the pores (Note: also cf. Fig. 4.4 in the next chapter.) ASC apoptosis-associated speck-like protein containing a caspase recruitment domain, C C-terminal domain, CARD caspase-activating and recruiting domain, dTGN dispersed trans-Golgi network, ER endoplasmic reticulum, GSDMD gasdermin D, IFN-I type I interferons, IFNAR interferon-α/β receptor, K+ potassium, NF-κB nuclear factor kappa B, IL interleukin, LRR leucine-rich repeats, N N-terminal domain, NACHT (domain), neuronal apoptosis inhibitor protein (NAIP), MHC-Class II transactivator/transcription activator (CIITA), plant het product (HET-E), and telomerase-associated protein 1 (TP1) protein, NLRP3 nucleotidebinding oligomerization domain-like receptor family pyrin domain-containing 3, OMR osmotic membrane rupture, PI phosphatidylinositol-4-phosphate, PYD pyrin domain, ROS reactive oxygen species. Note: This figure is modified from Fig. 2.1 (including the legend with Refs. and based on findings of Chen and Chen [356]) published in Vol. 2 [29] (Sect. 2.2.5.3, p. 20): Land WG. DamageAssociated Molecular Patterns in Human Diseases. Vol. 2: Danger Signals as Diagnostics, Prognostics, and Therapeutic Targets. Cham, Springer International Publishing AG, 2020. Available from http://link.springer.com/10.1007/978-3-030-53868-2; and republished in [357]) (further sources: [166, 168–170, 337, 358–361])
3.7.5.4 Bacterium-Triggered Activation of Pyroptosis Activation of pyroptosis as a powerful tool to fight pathogenic bacteria during extracellular and intracellular phases of infection begins with perception by inflammasome sensors of bacterial MAMPs (cell wall components, NAs) and virulence
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factors (toxins) as well as DAMPs induced by them. In addition, to come back to the Red Queen paradigm, several pathogenic bacteria have developed strategies to evade such inflammasome activation mechanisms. Here, however, only the host side of the continuous arms race will be addressed (for further reading, see [92, 259, 262, 348, 352–355, 376]). Canonical Activation of NLRP3 Inflammasome-Driven Pyroptosis Among the various inflammasomes, the NLRP3 inflammasome plays several crucial roles in antibacterial host defense. Signal 1 is usually believed to be provided by a MAMP derived from the pathogenic bacterium in question. Nevertheless, IA-1 DAMPs such as HMGB1, induced by global infectious injury, may also be involved. Signal 2 is considered an indirect activation process triggered by NLRP3 that operates as a sensor of various stress-induced molecular perturbations, which are reflected by the presence of dysDAMPs. Notably, these perturbations are partially emitted by preceding DAMP↔PRM interactions. Indeed, in bacterial infections, it is imaginable that the NLRP3 inflammasome is indirectly activated by the generation of dysDAMPs reflecting changes of the molecular pattern induced, for example, by various stress mechanisms, including indirect action of eATP (operating as an IA-2 DAMP and channeling K+ efflux; lysosomal disruption by crystalline particulates/misfolded protein aggregates combined with cathepsin B release; and mitochondrial damage/dysfunction associated with the production of ROS (i.e., oxidative stress) and oxidized mtDNA generation [158, 344, 345, 350, 377]. In support of the concept of bacterial stress-induced IIC-4 DAMPs as a potentially common trigger of NRLP3 inflammasome activation are three recently published studies: First, one line of studies showed that NLRP3 activators induce the disassembly of the TGN and that NLRP3 is targeted for activation at the dispersed TGN (dTGN) by ionic bonding between its conserved polybasic region and phosphatidylinositol-4-phosphates on the dTGN [356, 378] (discussed in Vol. 2 [29], Sect. 2.2.5.3 and Fig. 2.1, pp. 18–21). Second, another line of studies revealed a novel regulator of NLRP3 activation, DEAD-box helicase 3 X-linked (DDX3X), a protein normally involved in stress granule formation [379]. Finally, the third line of studies could demonstrate that NEK7 operates downstream of K+ efflux (reflecting dysDAMPs) to mediate NLRP3 inflammasome assembly and activation [380]. However, the most important and the best-studied example of indirect inflammasome activation by bacteria is the action of the membrane pore-forming exotoxins, which lead to perception by NLRP3 of intracellular ion perturbations such as K+ efflux, reflecting the presence of dysDAMPs (reviewed in [92, 348, 353, 381]; for pore-forming exotoxins and bacterial enzymatic toxins, see above Sect. 3.2.4.2). Indeed, early studies using aerolysin purified from Aeromonas hydrophila could already demonstrate that NLRP3- and ASC-dependent inflammasome formation occurs in response to a purified pore-forming bacterial toxin [382]. The link between pore-based lowered intracellular K+ and NLRP3 activation was later confirmed by multiple other groups [383, 384]. Notably, other pore-forming toxins such as
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Tetanolysin O from Clostridium tetani, Listeriolysin from Listeria monocytogenes, pneumolysin from Streptococcus pneumoniae, and other streptococcal lysins have meanwhile also been recognized to activate the inflammasome by K+ efflux induction or other mechanisms (reviewed in [353, 385]). Moreover, the Gram-positive Staphylococcus aureus was found to complement the line of NLRP3 inflammasome- activating bacteria via the action of multiple pore-forming toxins and hemolysins [353, 385–387]. Worthwhile to mention further is that Gram-negative bacteria such as Escherichia coli, Vibrio vulnificus, and Vibrio cholerae were also observed to produce a variety of hemolysins that have been implicated in the activation of the NLRP3 inflammasome [388–390]. Also, Yersinia T3SS effector protein, YopJ, was recently shown to activate NLRP3 via a novel pathway resulting in GSDMD activation and subsequent K+ efflux [125]. Of note, apart from pore-forming mechanisms, NLRP3 inflammasome activation can also occur by other mechanisms of indirect sensing of bacterial effectors. For example, intracellularly delivered RNA derived from both Gram-positive and Gram- negative bacteria was shown to activate the NLRP3 inflammasome in mouse macrophages [391, 392]. Moreover, bacterial RNA: DNA hybrids, which are formed during bacterial DNA replication and transcription, were observed to act as activators of the NLRP3 inflammasome [393]. Again other lines of studies reportedly indicate that bacterial mRNA, tRNA, and rRNA are all capable of activating NLRP3 in human macrophages [394]. The mechanism of NLRP3 inflammasome activation by RNA is not clear, and further studies are therefore needed to clarify these interesting observations. Of special interest in this context is also the observation that simultaneous engagement of TLRs and NLRP3 can promptly lead to the assembly of the NLRP3 inflammasome [395, 396]. This immediately activated pyroptosis is dependent on the myddosome components, which will be described in more detail in the next chapter (Sect. 4.3.2.2). Noncanonical Activation of NLRP3 Inflammasome Besides canonical NLRP3 inflammasome activation, a noncanonical cytosolic bacterial endotoxin/LPS-triggered, CASP11-dependent (in humans, CASP4-/CASP5- dependent) NLRP3 activation has been identified (for LPS operating as an exogenous DAMP, see above Sect. 3.2.4.3). This process consists of pyroptotic cell death that is independent of the canonical NLRP3 inflammasome components, that is, independent of NLRP3-, ASC-, and CASP1-dependent IL-1β/IL-18 processing and release (reviewed in [348, 397–399]; also see Vol. 1 [1], Sect. 11.2.6, p. 200, Sect. 22.4.2.3, p. 519, and Vol. 2 [29], Sect. 3.2.2, p. 71). The entry of LPS—operating as an exogenous DAMP—into the cytosol appears to be a critical activation step, and several mechanisms have been discussed by Hayward et al. [348] to explain how LPS might reach the cytosol of the host cell for perception by CASP11. Thus, bacteria, such as Burkholderia thailandensis and Burkholderia pseudomallei, were found to introduce LPS into the cytosol while escaping the pathogen-containing vacuole, thereby driving rapid CASP11 activation. However, there is also evidence suggesting alternative routes by which LPS can enter the cytoplasm.
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AIM2 Inflammasome The inflammasome-forming cytosolic DNA sensor AIM2 is flexible in its recognition capabilities and, thus, not only binds to host dsDNA (= endogenous DAMP) and viral dsDNA (=exogenous DAMP) but also bacterial dsDNA (=exogenous DAMP) (for details of AIM2 inflammasome, see Vol. 1 [1], Sect. 5.2.5.2, p. 58, Fig. 19.5, p. 449, and Sect. 22.4.4, p. 522, as well as Vol. 2 [29], Sect. 2.2.8 and Fig. 2.2, pp. 24/25). The AIM2-activating bacteria encompass a range of Gram- negative, Gram-positive, and Gram-variable bacteria, including Francisella tularensis, Francisella novicida, Listeria monocytogenes, and Legionella pneumophila (reviewed in [348, 400, 401]). Notably, before binding to bacterial dsDNA, activation of AIM2 in response to intracellular bacteria was shown to require IFN- inducible guanosine-5′-triphosphate (GTP)ases, including guanylate-binding proteins and the immunity-related GTPase family member b10 (IRGB10) [375]. These proteins target intracellular bacteria, leading to bacteriolysis and the liberation of dsDNA into the cytosol for sensing by AIM2. Notably, the final activation of AIM2 depends on direct binding to dsDNA mediated through interactions between the DNA and the HIN domain of the AIM2, whereby non-sequence-specific DNA recognition is accomplished through electrostatic attraction between the positively charged HIN domain residues and the dsDNA sugar-phosphate backbone [402]. The mechanism by which DNA becomes exposed in the cytoplasm of an infected host cell for inflammasome sensing is discussed by Hayward et al. [348] to be a consequence of escaping from the bacterium-containing vacuole via a T6SS and invading the cytoplasm with subsequent bacteriolysis. The NAIP-NLRC4 Inflammasome The NAIP–NLRC4 inflammasome in human and murine macrophages is reportedly activated by flagellated bacteria (e.g., S. Typhimurium and L. pneumophila) and effector components (“inner rod, needle”) of the T3SS secretion system. Mechanistically, cytoplasmic flagellin monomers are initially perceived by murine NAIP5 (or NAIP6) proteins and the single human NAIP protein, which work cooperatively to mediate inflammasome activation whereby NAIPs are responsible for directly sensing bacterial ligands. Activated NAIP proteins then bind NLRC4 to initiate inflammasome assembly (also see Vol. 1 [1], Sect. 22.4.3.3, p. 521; for details of activation, see [348, 355, 403]). For example, the human NAIP was found to detect both flagellin and the T3SS needle protein [403] as well as—as shown more recently—the Salmonella Typhimurium T3SS inner rod protein PrgJ and T3SS inner rod proteins from other bacterial species [404]. From their findings, the authors concluded that, like murine cells, human macrophages sense multiple bacterial ligands from the T3SS and flagellar apparatus. In addition to the T3SS needle and flagellin, T3SS inner rod proteins from multiple bacterial species activate the human NAIP inflammasome [404]. In fact, the NLRC4 inflammasome plays a critical role in host defense against many bacterial pathogens, as, for example, shown by BALB/c mice deficient in NLRC4, which were found to exhibit increased susceptibility to oralgastric infection with Salmonella typhimurium [405].
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NLRP1 and Pyrin Inflammasome Similar to NLRP3, but in contrast to the AIM2 and NAIP-NLRC4 inflammasomes, NLRP1 and Pyrin respond to bacteria-provoked conformational changes in terms of intracellular molecular perturbations (i.e., dysDAMPs) rather than to direct binding to a specific MAMP or DAMP. The mechanism of NLRP1 activation is cleavage dependent; for example, the human NLRP1 is activated by any protein capable of inducing N-terminal proteolytic cleavage of NLRP1 (N-terminal degradation), indicating that this inflammasome sensor is not specific to any single ligand. However, how human NLRP1 is precisely regulated is still elusive (for more details, see [348, 350, 355]). Compared to the NLRP1 inflammasome, the activation of the Pyrin inflammasome by bacteria is similar but more complex, and details of the molecular mechanisms can be found in [406]. In brief: The Pyrin sensor was shown not to directly interact with MAMPs, but rather indirectly perceive bacterial modifications in the activity of the small GTPase Ras homolog gene family, member A (RhoA). Various bacterial toxins, for example, derived from Clostridium difficile, Vibrio parahaemolyticus, and Clostridium botulinum, were shown to mediate these molecular changes (described in [407]). As discussed in Vol. 2 [29], Sect. 6.3.3.3, p. 221, RhoA has several vital roles in cell behavior, including regulation of cell shape, transformation of cellular phenotypes, and actin cytoskeleton reorganization, that is, functions, which may lead to the generation of dysDAMPs sensed by Pyrin (for RhoA, also see [408–411]). This indirect mechanism again represents a paradigm shift for the sensing of pathogens indicating that subsequent pathogen-triggered emission of DAMPs promotes the real antimicrobial innate immune defense response.
3.7.5.5 Virus-Triggered Activation of Pyroptosis Activation of the inflammasome–pyroptosis pathway that contributes robustly to anti-pathogen innate and adaptive immunity is not only a powerful tool of host defense to fight bacterial pathogens but also intracellular viruses. At the time of writing, this subroutine of RN is even excitingly discussed by many researchers to operate in COVID-19 (e.g., [412], also cited in [357]). As will be described in the next chapter, viral MAMPs can trigger innate immune pathways either on the host cell surface, within the endolysosome, in the cytosol, or even in the nucleus. However, it is the inflammasome sensors (NLRP3, AIM2, NLRP1), activated in response to various viral DNA and RNA operating as exogenous DAMPs, which is thought to guarantee robust and efficient immunosurveillance and elimination of different families of viruses, not least because of their ability to trigger pyroptotic cell death that is associated with the release of large amounts of DAMPs. Among the various inflammasomes, the NLRP3 inflammasome [348, 413–417] and AIM2 inflammasome [348, 417–419] play the most crucial roles. Overall, activation of the pyroptotic pathway usually begins with perception by inflammasome sensors of viral-triggered generation/emission of DAMPs, such as dysDAMPs evoked by viroporins and NAs operating as exogenous DAMPs. Nonetheless, to come back again to the Red Queen paradigm, several viruses have developed strategies to evade such inflammasome activation mechanisms. In the
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following, however, only the host side of the continuous arms race will be addressed (for further reading, also see [259, 262, 376, 420]). Activation of the NLRP3 Inflammasome The diverse array of viruses that activate the NLRP3 inflammasome via various mechanisms includes RNA viruses of the families Orthomyxoviridae (e.g., influenza virus [A, B, C], Paramyxoviridae (e.g., RSV), Picornaviridae (e.g., poliovirus, and encephalomyocarditis virus [EMCV]), Flaviviridae (e.g., HCV and dengue virus), and others (for reviews, see [348, 413, 415, 421–423]). Mechanistically, the NLRP3 sensor can be activated by viral components (signal 1) as well as molecular perturbations reflecting cell-intrinsic dysDAMPs (signal 2). Such perturbations are caused by processes of viral cell entry, replication, and budding/release (e.g., mitochondrial ROS, ion perturbations, and misfolded protein aggregates) (also see above, Sect. 2.7.5; for reviews, see [350, 413, 417]). A special role in causing ionic perturbations—as mentioned—play viroporins (for viroporins, see above, Sect. 3.3.3). Signal 1 leading to the activation of NF-κB is provided in part by viral RNA- sensing RIG I-like receptors (RLRs), for example, RIG-I (described in the next chapter, Sect. 4.3.2.3 and Fig. 4.6). Additionally, IA-1DAMPs such as HMGB1 or S100 proteins (released from virus-induced cell death) as well as type I IFN and TNF can trigger the TLR→NF-κB pathway and the IFNAR→NF-κB and TNFR→NF-κB path, respectively, thereby amplifying NLRP3 inflammasome activation processes (compare next chapter, Sect. 4.3.5 and Fig. 4.8). Of note, some DNA viruses have been demonstrated to activate the NLRP3 inflammasome over AIM2 (reviewed in [350, 413]). Viruses using this pathway include HSV-1, adenovirus, and varicella-zoster virus (VZV). Signal 1 leading to the activation of NF-κB is provided in part by viral DNA-sensing through the cGAS/ STING pathway (for cyclic GMP-AMP [cGAMP] synthase/stimulator of interferon genes; see next chapter, Sect. 4.3.2.3 and Fig. 4.7) (partially reviewed in [413]). Additionally, constitutive DAMPs, as well as inducible DAMPs, as mentioned above for RNA viruses, may provide signal 1 to amplify NLRP3 inflammasome activation processes. Signal 2 is suggested to be triggered by DNA virus-induced molecular perturbations reflecting cell-intrinsic dysDAMPs. The NLRP3 Inflammasome→Pyroptosis Pathway in Influenza A Virus and COVID-19 Infection There is emerging evidence for the role of the activated NLRP3–pyroptosis pathway in promoting inflammation and immunity in influenza [417] and, recently, also COVID-19 infection [424, 425]. Mechanistically, most information was collected from studies on the influenza virus, a long-recognized potent activator of the NLRP3 inflammasome. Observations from murine influenza virus infection models made by the Kanneganti group [330, 371, 422, 426, 427] revealed a pivotal role of the cytosolic innate immune receptor ZBP1 in NLRP3 inflammasome activation (for a role of ZBP1 in necroptosis, see above Sect. 3.7.4.5). In fact, ZBP1, in terms of signal 2, was found to activate assembly of the NLRP3 inflammasome through a ZBP1/RIPK3/ CASP8 complex, thereby executing pyroptosis in response to influenza infection.
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Another proposal for (signal 2) NLRP3 activation mechanism refers to virus- provoked cytosolic molecular perturbations caused by viroporins, which—as mentioned above—are known to activate the NLRP3 inflammasome [163]. As reviewed [169], the M2 protein is present in all influenza types. In influenza A and B, AM2 and BM2 are predominantly proton channels; by contrast, M2 proteins in influenza C and D, CM2, and DM2, are thought to be especially selective for chloride ions. Plausibly, the discoveries of viroporin properties to activate the NLRP3 inflammasome have stimulated experiments to study the underlying mechanisms. Previous preclinical studies had already shown that the influenza virus M2 protein triggers activation of the NLRP3 inflammasome pathway via the involvement of the proton-selective M2 ion channel in the acidic TGN [168]. The investigators observed that M2 channel activity was sufficient to activate inflammasomes in primed macrophages and DCs. As two striking findings, the authors noted that M2-induced inflammasome activation requires its localization to the Golgi apparatus and is dependent on disturbances in intracellular ionic concentrations. Similar observations were made in subsequent studies on other RNA viruses [166, 358]. Of actual interest in this context are experiments revealing that SARS-CoV viroporins, that is, the three envelope proteins 3a, E, and 8a, can also activate the NLRP3 inflammasome via disturbance of the intracellular molecular homeostasis [170, 171, 337, 359]. Although the precise underlying mechanisms are not yet fully understood, some exciting pathways have already been reported that are briefly cited here: In pioneering investigations on coronaviruses, Nieto-Torres et al. [170, 428] demonstrated that SARS-CoV E protein forms protein-lipid channels in the ERGIC/ Golgi membranes that are permeable to calcium ions, which, together with pH, modulate E protein pore charge and selectivity. Calcium transport through the E protein ion channel was found to be the main trigger of this process. Subsequent studies on coronaviruses revealed that SARS-CoV 3a—which had previously been found to induce Golgi fragmentation [360]—activates CASP1 either directly or via an enhanced K+ efflux, which triggers NLRP3 inflammasome assembly [337]. In similar lines of studies on murine bone marrow-derived, LPS-primed macrophages, Chen et al. [359] found that the ion channel activity of SARS-CoV 3a protein is essential for NLRP3 inflammasome activation. In addition, both K+ efflux and mitochondrial mtROS production were observed to be required for SARS-CoV 3a-mediated IL-1β secretion. Given these findings, previous studies are important, showing that the 3a protein of SARS-CoV moves from the Golgi apparatus to the plasma membrane [429] and, there, forms a potassium-sensitive channel [430], thereby (presumably) stimulating the K+ efflux at the plasma membrane. In more recent studies on macrophages conducted by Shi et al. [361], evidence was provided indicating that SARS-coronavirus ORF8b (SARS CoV 8b) triggers ER stress pathways upon forming insoluble aggregates, which activate the inflammasome- pyroptotic cell death pathway (for K+ efflux, ER stress, and mtROS involved in canonical NLRP3 activation, also see Vol. 1 [1], Sect. 22.4.2.2. p. 516 and Fig. 22.11, p. 517).
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Perspectives of Pyroptosis for the Pathogenesis of COVID-19 Infection Indeed, it is amazing to note that respiratory viruses, including SARS CoV, can be involved in viral pathogenicity via induction of pyroptotic cell deaths. In this regard, these first reports on viroporin-mediated activation of the NLRP3 inflammasome- driven pyroptosis pathway are of high interest. To sum up: The activation mechanisms so far reported refer to (1) location of viroporins at the intermediate between ER and Golgi apparatus, (2) ER stress, (3) Golgi fragmentation, (4) K+ efflux, and (5) involvement of mtROS. In fact, these five processes are out of several—still complicated and partially controversial—models that have been proposed to explain NLRP3 inflammasome activation (reviewed in [413, 431]). On the other hand, the five mechanisms described fit the concept proposed by Chen and Chen [356], which refers to the possibility that diverse activating NLRP3 stimuli (e.g., K+ efflux) result in the disassembly/fragmentation of the TGN. According to this model, NLRP3 is recruited to the dispersed TGN through ionic bonding between its conserved polybasic region and negatively charged phosphatidylinositol-4-phosphate (PtdIns4P) on the dispersed TGN. The dispersed TGN then serves as a scaffold for NLRP3 aggregation into multiple puncta, leading to polymerization of the adaptor protein ASC, thereby activating the downstream signaling cascade (Fig. 3.9). In this model, mtROS, like ER stress that is known to contribute to Golgi fragmentation [432], may derive from dysfunctional mitochondria induced in the course of ER stress [433, 434]. Given the existing experimental data in favor of the role of SARS-CoV in NLRP3 inflammasome activation, together with studies showing increased IL-1β in the serum of patients infected with SARS-CoV-2 [435], one may discuss a pathogenetic role of pyroptosis in COVID-19. In this context, Yang et al. [436] discuss that cell pyroptotic activity is likely to be activated and involved in the pathogenesis of COVID-19 patients. Nevertheless, as both classical and nonclassical pyroptosis signaling can induce the release of IL-1β, it is unclear which pathway is involved in COVID-19. The AIM2-Driven Pyroptosis Pathway The AIM2 inflammasome is preferentially activated by DNA viruses, whereby the sensor binds exclusively to cytosolic dsDNA acting as an exogenous DAMP, independent of the sequence of the dsDNA. Mechanistically, binding of DNA to the HIN domain of AIM2 induces a conformational change that leads to AIM2 oligomerization (for reviews, see [348, 418, 419], also see Vol. 2 [29], Sect. 2.2.8, Fig. 2.2, pp. 23–26). The AIM2 inflammasome is reportedly activated by many DNA viruses, including HCMV, Human Papillomavirus16 (HPV16), Epstein-Barr virus (EBV), and HBV (for HCMV-triggered AIM2, compare Vol. 1 [1], Fig. 19.8, p. 449). Similar to sensing by AIM2, the nuclear sensing of viral DNA by IFI16 activates the inflammasome pathway through ASC and Casp1, leading to IL-1β release [437, 438]. Of note, there is evidence that the RNA virus IAV can activate the AIM2 inflammasome as well [439]. The researchers speculated on two mechanisms: (1) Uptake by macrophages of damaged alveolar epithelial cells (AECs) to transfer genomic
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dsDNA from epithelial cells into the cytosol of macrophages, which is then sensed by intracellular AIM2; (2) IAV-caused mitochondrial damage and release of mtDNA into the cytosol, which directly triggers the AIM2 inflammasome. This concept is supported by findings from studies in mice showing that the influenza virus stimulates oxidized DNA release from macrophages and stimulates IL-1β production from these phagocytes in an AIM2-dependent manner [440].
3.7.5.6 Fungal-Triggered Activation of Pyroptosis Inflammasomes also have a critical role in promoting antifungal host defense at the level of the mucosa. This is essential during the later stages of disseminated fungal infection by potentiating the protective Th17 and Th1 responses. Indeed, accumulating evidence suggests that fungal MAMPs (e.g., derived from Candida, Aspergillus, Cryptococcus, and Paracoccidioides) such as DNA, spores, and cell wall-associated polysaccharides are recognized by inflammasome sensors (reviewed in [350, 441, 442]). For example, fungal cell wall components such as fungal β-glucan, zymosan, and mannan have been proposed to operate as inducers of NLRP3 inflammasome activation [443]. Also, and interestingly, transfection studies in mice revealed that AIM2 and NLRP3 form a dual surveillance system within the cytosol to orchestrate a strong inflammasome-mediated response against Aspergillus fumigatus infection [444]. The AIM2 inflammasome has also been observed to be activated by fungal DNA. However, the mechanism by which fungal DNA enters the cytoplasm for sensing by AIM2 remains unknown. One may discuss that endogenous mtDNA derived from fungus-induced cell damage operates as a DAMP (for more information, see [350, 441, 442]). In another study on the activation of the NLRP3 and AIM2 inflammasomes upon Aspergillus fumigatus infection (without referring to pyroptosis), IRGB10, under the regulation of IRF1, was identified to play a critical role in promoting inflammasome activation by releasing fungal MAMPs [445]. Again in other lines of studies on murine macrophages, phagosomal neutralization by the fungal pathogen Candida albicans was found to induce macrophage pyroptosis [446]. Further investigations on this emerging topic can be expected. 3.7.5.7 Pyroptosis in Parasitic Infections There are first reports on inflammasome activation in protozoan and helminthic diseases. For example, in malaria, the danger signal hemozoin, an inorganic crystal that is generated by detoxification of heme after hemoglobin degradation in infected RBCs, was reported to act as an activator of NLRP3, inducing IL-1β release and contributing to a strong innate immune response [447, 448]. Additionally, hemozoin has been found to induce AIM2 inflammasome assembly, probably, because this danger signal is often associated with DNA [449]. The topic is brought up again in Sect. 5.6, when discussing the pathogenetic role of DAMPs in malaria. Also, helminthic pathogens have been reported to trigger inflammasome assembly. For example, the soluble egg antigens from S. mansoni were found to trigger the NLRP3 inflammasome-driven pyroptotic pathway in non-parenchymal liver cells, such as hepatic stellate cells (HSCs). These antigens interact with the Dectin-1
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receptor, which in turn induces Syk activation. Interaction between Syk and ASC appeared to be one of the mechanisms by which this kinase influences NLRP3 inflammasome assembly and the subsequent caspase-1 activation [450]. The topic is not further pursued here; instead, the reader is referred to recent review articles such as those quoted in [450–452].
3.7.6 PANoptosis: A Unique Inflammatory Cell Death Pathway Integrating Other Cell Death Trajectories It has been known for some time that the pyroptotic, apoptotic, and necroptotic death pathways are tightly interconnected forms of RN. Thus, it is now reasonable to consider these subroutines of RN signaling as a network of connected programs capable of compensating for the inhibition of one [259]. But this is not the end of the story. Excitingly, a recent platform of the inflammatory RCD pathway was identified by the Kanneganti group [453, 454] that reportedly operates in terms of extensive crosstalk between apoptosis, necroptosis, and pyroptosis. Termed PANoptosis, this inflammatory RCD integrates components from other cell death pathways and is regulated by PANoptosomes in terms of multifaceted macromolecular complexes. The PANoptosis is activated by sensors that detect cellular perturbations caused by sterile or infection-mediated stress/injury and is characterized by the formation of membrane pores, which execute the cell death to release DAMPs and cytokines such as IL-1β and IL-18. As recently reviewed by Gullett et al. [455], PANoptosis conceptually involves the activation of several molecules that were previously characterized as mediators of independent cell death pathways, including ZBP1 mentioned above, to interact with the necroptotic molecules RIPK1 and RIPK3, or to operate as a cytosolic innate immune sensor for endogenous NAs during IAV infection to execute NLRP3mediated pyroptosis. Given this “crosstalk, plasticity, redundancies, switches, and interconnectedness encompassed by PANoptosis underlying the totality of cell death associated biological effects” [455], it is tempting to insinuate that various classes of endogenous constitutive expressed DAMPs (e.g., dysDAMPs, DNA, and RNA), inducible DAMPs (e.g., TNF and type I IFN), and/or exogenous DAMPs (e.g., viral RNA) are perceived by these sensors to promote the formation of PANoptosomes, which have the potential to bring together distinct components from previously segregated cell death pathways. These pathways then lead to the formation of pores through cell membranes associated with the release of DAMPs (Fig. 3.10). PANoptosis has been implicated in several disorders, including microbial/viral infectious diseases. For example, Yersinia infection was shown to activate PANoptosis, with infection inducing the formation of a PANoptosome containing molecules including RIPK1, RIPK3, AIM2, ASC, and NLRP3 [456]. In IAV- infected cells, ZBP1 was found to be a key master regulator of PANoptosis. Activation of this sensor results in its interaction with molecules such as RIPK3, RIPK1, and CASP8 to assemble as the PANoptosome [453, 454]. During HSV1 infection, AIM2 was found to regulate pyrin and ZBP1 expression and form a PANoptosome complex along with these two sensors and other molecules, such as ASC and RIPK3/RIPK1 to drive PANoptosis [457]. Since SARS-CoV-2 has been
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shown to trigger apoptosis, necroptosis, and pyroptosis, the virus is discussed to promote the formation of PANoptosis [338, 339]. The possible impact of this phenomenon on the cytokine storm in COVID-19 patients in this context is discussed in Chap. 5 (Sect. 5.4.5.4).
3.7.7 Formation of NETs and NETosis 3.7.7.1 General Remarks Neutrophils belong to the most powerful cells in innate immune host defense. They execute their defensive work using several tools such as neutralization of infectious agents via release of their granules by degranulation, internalization of and degradation of pathogens by phagocytosis, and release of NETs; a process that is often associated with neutrophil death, that is, NETosis. Accordingly, we must distinguish between NET formation, where NETs are released from living cells, and NETosis, which is characterized by suicidal cell death, and is generally regarded as a true subroutine of RCD. Consequently, mainly two models for NET formation are being discussed to date: nonlytic vital NET formation that takes place within minutes after
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neutrophilic stimulation and lytic NET formation in terms of suicidal NETosis that occurs within several hours after neutrophilic stimulation (as cursorily described in Vol. 1 [1], Sect. 19.3.6, pp. 452–454 and Vol. 2 [29], Sect. 436, p. 139). The formation of NETs and NETotic cell death is not restricted to neutrophils but has been detected in other innate immune cells such as macrophages/monocytes, mast cells, basophils, eosinophils, and DCs. Pathways involved in the NET formation and NETosis have been comprehensively described in recent reviews published by Burgener and Schroder [458], Thiam et al. [459], Chen et al. [460], Chen et al. [461], Wang et al. [462], Tan et al. [463], and Huang and O’Sullivan [464]. Here, the key aspects described in these papers are briefly presented.
3.7.7.2 Pathways in Lytic and Nonlytic NET Formation Based on the reviews cited here, a model of NET formation is sketched in the form of a brief excerpt of pathways involved in lytic and nonlytic NET formation (Fig. 3.11a, b). It should be emphasized, however, that some controversial data have
Fig. 3.11 (a) Simplified schematic diagram of a model illustrating proposed pathways involved in lytic NET formation (suicidal NETosis). The lytic NET formation is triggered by various infectious stimuli (pathogen-derived MAMPs) or sterile impulses (stress/injury-induced DAMPs such as HMGB or mtDNA) that are recognized by different recognition receptors such as TLRs located at the cell surface or the endosomal membrane. Another trigger molecule refers to ICs that bind to Fc receptors. Activated receptors instigate signaling through MAPKs leading to NOX-mediated production of ROS, which in turn activate MPO and NE (translocating to the nucleus) as well as PAD4. The synergistic effect between this enzyme, NE, and MPO then drives nuclear membrane disruption, chromatin depolymerization/decondensation, and plasma membrane rupture. This results in the final extrusion of NETs as characterized by the release into the extracellular space of a meshwork of chromatin-containing and histone-containing fibers (reflecting nuclear DAMPs), imposing as web-like DNA structures. In addition, recent evidence suggests that PAD4 is involved in the assembly of the NLRP3 inflammasome associated with the activation of GSDMD, resulting in pore formation and plasma membrane rupture, which allows the release of cytoplasmic DAMPs. Note, for the NLRP3 inflammasome-driven pore formation and membrane rupture, cf. previous Fig. 3.9 and its legend. FcR fragment crystallizable receptor, GSDMD gasdermin D, HMGB1 high mobility group box 1, ICs immune complexes, MAPKs mitogen-activated protein kinases, MPO myeloperoxidase, mtDNA mitochondrial DNA, NE neutrophil elastase, NET neutrophil extracellular trap, NLRP3 nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3, NOX nicotinamide adenine dinucleotide phosphate (NADPH) oxidase, PAD4 peptidyl arginine deiminase 4, PKC protein kinase C, ROS reactive oxygen species, TLRs Toll-like receptors (sources: [458–467]). (b) Simplified schematic diagram of a model illustrating proposed pathways involved in nonlytic NET formation (vital NETosis). The nonlytic NET formation is triggered by various infectious stimuli (pathogen-derived MAMPs) or sterile impulses (stress/injury-induced DAMPs) that are recognized by different cell recognition receptors, such as TLRs. Another trigger molecule refers to ICs that bind to Fc receptors. Activated receptor-triggered pathways signaling through MAPKs lead to activation of PAD4 that, in conjunction with NE and MPO, drives NET formation by citrullination of histones, thereby mediating chromatin decondensation. The decondensed chromatin, containing nuclear DAMPs, is expelled via vesicles without nuclear and plasma membrane disruption. After the release of NETs, neutrophils are still alive and possess the ability to function. Cit citrullination of histones, FcR fragment crystallizable receptor, ICs immune complexes, MAPKs mitogen-activated protein kinases, MPO myeloperoxidase, NE neutrophil elastase, PAD4 peptidyl arginine deiminase 4, PKC protein kinase C, TLRs Toll-like receptors (sources: [459–465])
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been reported on the underlying mechanisms of formation as presented here. For example, unsolved questions about precise mechanisms of intracellular signaling pathways still exist. Accordingly, the following can only be considered a snapshot taken in the summer of 2022. Lytic NET Formation (Suicidal NETosis) Lytic NET formation takes place within some hours of stimulation of neutrophils. The process of neutrophilic death involves a sequence of pathways that begins with neutrophil activation triggered by various neutrophil PRMs interacting with different infectious or sterile stimuli (Fig. 3.11a). As PRMs, receptors such as TLRs (TLR2/4/6), CLRs), nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs), FcRs, and complement receptors (CRs) have been
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demonstrated, whereas as agonistic stimuli, MAMPs, DAMPs such as HMGB1, mtDNA, oxidized low-density lipoproteins (OxLDL), soluble ICs, or complement fragments have been detected. Some activated PRMs trigger pathways (e.g., through protein kinase C [PKC]→SYK→MAPK or SYK→MAPK signaling), leading to the production of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (NOX)-mediated production of ROS. On the other hand, some PRMs, such as TLR7/8/9, directly promote the NOX-mediated production of ROS [461]. Also, it should be added here that ROS has been shown to be primarily produced by the mitochondria, a process called NOX-independent NETosis [465]. Following this, the release of ROS triggers the liberation of myeloperoxidase (MPO) from azurophilic granules into the cytoplasm. This peroxidase enzyme then activates neutrophil proteases, including neutrophil elastase (NE), that subsequently translocates from the cytoplasm to the nucleus. Interestingly, during these processes, ROS also activates the PAD4 enzyme. The synergistic effect between this enzyme and NE and MPO, both released from the neutrophilic granules, then drives actin degradation, nuclear membrane disruption, chromatin depolymerization/decondensation, and plasma membrane rupture. Interestingly, there is growing recent evidence indicating a role of the NLRP3 inflammasome-mediated downstream pathways in promoting NETosis. A first study could demonstrate that PAD4 is needed for optimal NLRP3 inflammasome assembly by regulating NLRP3 and ASC protein levels posttranscriptionally [466]. Also, in other lines of studies, NE was found to cleave and activate GSDMD (mentioned above in the context of pyroptosis), resulting in nuclear and plasma membrane rupture and neutrophil cell lysis by NETosis ([467], also reviewed in [460]). Finally, this extrusion of NETs from the dying cells is characterized by the release into the extracellular space of a meshwork of chromatin-containing and histone-containing fibers bound to granular and cytoplasmic proteins imposing as web-like DNA structures. Plausibly, as is typical for all forms of RN, numerous nuclear and cytosolic DAMPs are released into the extracellular space during this cell death process. Nonlytic (Vital) NET Formation In contrast to lytic NET formation, neutrophils can also release NETs in a NOX/ ROS- and cell death-independent manner (Fig. 3.11b). Neutrophil activation in this nonlytic NET formation has been shown to be elicited by numerous stimuli, including many of those involved in lytic NET formation. Also, in this nonlytic pathway, PAD4 has been shown to be activated by PRM-triggered signaling as similarly proposed for the production of ROS. Moreover, in biochemical studies on murine and human necroptotic neutrophils, the RIPK1/3→MLKL pathway was recently proposed to contribute to the activation of PAD4 [468]. Overall, however, the exact mechanisms that govern PAD4 activation and regulation are still not completely understood. Nonetheless, according to the current model, the action of Ca2+ -activated PAD4—likely in conjunction with NE and MPO—drives NET formation by
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citrullination of histones H3, H2A, and H4, thereby mediating subsequent loss of the compacted chromatin structure associated with chromatin decondensation. The decondensed chromatin is expelled without disruption of the nuclear membrane that is thought, however, to vesiculate. The formation and extrinsic distribution of vesicles allow the release of cytosol-derived granular proteins as well as nuclear molecules such as DNA, RNA, and histones, which are thought to be finally expelled extracellularly via exocytosis. Under these conditions, the cell is still alive and has the capacity to perform cellular functions. In conclusion, research on pathways involved in lytic and nonlytic NET formation is in full swing, but, as concluded by Thiam et al. [459], “the molecular, cellular, and biophysical mechanisms driving this process have just begun to be revealed.”
3.7.7.3 NETs and NETosis in Bacterial Infections Various bacteria can reportedly induce the formation of NETs by suicidal and vital NETosis (reviewed by Burgener and Schroder [458]). In brief: Bacteria identified to induce NETosis, include S. flexneri, E. coli, Streptococcus pneumoniae, Streptococcus pyogenes, and Mycobacterium tuberculosis. Notably, several PRRs, such as TLR2 and TLR4, for example, expressed on platelets, appear to be required for the initiation of NETosis. However, the distinct bacterial stimulators that trigger the formation of NETs are still not fully identified. Further research to elucidate the molecular and cellular mechanisms by which activated neutrophils promote and shape their NETs will be vital for understanding this important host defense program against bacteria. 3.7.7.4 NETs and NETosis in Viral Infections The formation of NETs in acute viral infections has recently been reviewed by Sung and Hsieh [469]. In brief: NETs have been shown to be induced in vitro and/or in vivo by viruses such as IAV, HIV-1, RSV, and hantaan virus (HTNV). The RSV- induced NET formation was even observed to be involved in the pathogenesis of this viral infection. In addition, the dengue virus (DV)-induced NET formation was demonstrated to be induced via platelet-derived EVs [470]. Recently, and reviewed elsewhere [471], the NET formation was also identified in critically ill COVID-19 patients within airways and alveoli in lung parenchyma of 40% of SARS-CoV-2 infected lungs. As reported in other studies, the NET formation was observed to contribute to the pathogenesis of SARS-CoV-2 infection and mediate COVID-19 pathology (reviewed in [469]). Mechanistically, the formation of virus-induced NETs as a crucial source of DAMPs release is far from being clarified. However, in this context, the observations of Sung and Hsieth [469] are of interest, demonstrating that DV promotes NET formation by inducing platelet-derived EVs containing cytoskeleton components, whereby some of them, for example, F-actin, are identified as DAMPs (for F-actin operating as an IIB-2 DAMP, see Vol. 1 [1], Sect. 5.2.7.3, p. 62 and Sect. 12.2.4.7, p. 237). In other words: One may discuss that the formation of virus-induced NETs is a result of the primary action of virus-induced EV in
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terms of a host stress response associated with the generation of encapsulated DAMPs (Sect. 3.6.2 with reference to the Red Queen paradigm) [43, 46, 58, 87, 115, 126].
3.7.7.5 NETs and NETosis in Protozoan Infections The NET formation has also been reported to occur in protozoan infections. For example, Knackstedt et al. [472] showed that heme-induced NETs are essential for malaria pathogenesis. The investigators, using patient samples and a mouse model, were able to define two mechanisms of NET-mediated inflammation of the vasculature: activation of emergency granulopoiesis via the production of granulocyte- colony stimulating factor (GCSF) and induction of the endothelial cytoadhesion receptor intercellular adhesion molecule1 (ICAM-1). The authors concluded that their findings point to a key role of neutrophils in malaria immunopathology and suggested inhibiting NETs as a treatment strategy in vascular infections. 3.7.7.6 NETs and NETosis Induced by Immune Complexes Of note, in addition to their defensive role played during infection, growing evidence has been reported showing that NET formation and the NETotic cell death also occur in a large number of noninfectious chronic inflammation-associated disorders, including various lung diseases, thrombosis, cancer, and autoimmune diseases [473]. Indeed, as already touched on in Sect 1.4.2, there is emerging evidence indicating that the formation of NETs/NETosis is not only induced by injurious stimuli but also by ICs in terms of antibodies complexed with antigens. As will be described in Sect. 4.6.7 in more detail, mechanistically, it is the soluble ICs interacting with Fc receptors on neutrophils that trigger this process. The first and preliminary findings of this scenario have been observed in bacterial infections [461, 474, 475] and viral infections (e.g., COVID-19) [476, 477]. The same topic will be resumed in Sect. 6.2.4.4 when discussing IC-induced NET formation/NETosis and subsequent initiation of a DAMP-promoted positive feed-forward loop that orchestrates autoimmune responses. 3.7.7.7 Concluding Remarks Both events, the formation of NETs and the NETotic cell death, are considered another tool for robust host defense against any type of pathogens. For example, the formation of NETosis has also been reported as a strategy by the host to defend against fungal infection caused by Candida albicans [478]. The effectiveness of NETs in promoting host defense is underlined by the observation that many pathogens have developed NET-evasion mechanisms. In further reading of the following chapters on autoimmune diseases and cancer, we will again encounter this form of cell death. However, cellular and molecular mechanisms that regulate the key morphological changes of neutrophils during NET formation have not yet been well understood.
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3.7.8 Ferroptosis: An Iron-Dependent, Oxidative Form of Regulated Necrosis 3.7.8.1 General Remarks The ferroptotic cascade has been described and illustrated by us in [266], Fig. 3, and Vol. 1 [1], Sect. 19.3.3, pp. 442–446 and Vol. 2 [29], Sect. 4.3.4 and Figs. 4.2/4.3, pp. 133–138 (for recent reviews, see [218, 479, 480]). In recent times, the role of ferroptosis as an iron-dependent, oxidative form of RN has become an exciting research hotspot and is associated with an increasing number of diseases. In principle, activation of the ferroptotic pathway is involved in the pathogenesis of those diseases, which are associated with oxidative stress, that is, disorders such as atherosclerosis, cardiovascular diseases (CVD), acute allograft rejection, and neurodegenerative diseases. Accordingly, the activation of ferroptosis can be considered as another host defense strategy in those infections which are associated with increased oxidative stress caused by the accumulation of excessive ROS. In other words: The ferroptotic cell death is implicated in those infectious disorders in which heavy oxidative stress surmounts the antioxidative defense system of the host. Indeed, as already discussed above in Sect. 3.6.4, there is increasing evidence of a role of oxidative stress in infections, in particular, viral infections, as indicated by the production of ROS and RNS. The increase in oxidants is mainly produced by activated phagocytic cells of the host in terms of an anti-pathogen immune defense response: a critical process for the clearance of pathogens. To reiterate the weight of ferroptosis in host defenses against infection, the scenario of defense responses to growing oxidative stress, as formulated and illustrated in Vol. 2 [29], Sect. 4.3.4.5 and Fig. 4.3 should be referred to once again. 3.7.8.2 The Defense Response to Oxidative Stress Depending on Increasing Stress Intensity Indeed, our innate defense system operates against oxidative stress/injury on three levels, in each case adapted to the increasing intensity of oxidative insults. All three levels have been addressed in this book: (1) the Keap1→Nrf2-initiated antioxidative response as the first attempt to restore and maintain homeostasis upon oxidative stress (see above, Sect. 3.6.4 as well as Vol. 2 [29], Sect. 4.2.3.2, pp. 119–121); (2) as an adjunct to the antioxidative response, the emission of OSEs during the process of lipid peroxidation (see Vol. 2 [29], Sect. 3.4.3.2, p. 76, Sect. 4.3.4.2, p. 134), which represent a powerful subclass of DAMPs (IIB-1 DAMPs) capable of triggering robust innate defense pathways; and (3)—as a culmination of defense against heavy and/or persistent oxidative stress, and when the two previous defensive tools fail— induction of ferroptosis associated with the release of large amounts of DAMPs aimed at rescuing at least the organism that may be exposed to a severe oxidative injury-mediated threat (as described here and in Vol. 1 [1], Sect. 19.3.3, pp. 442–446). Again, this scenario shows the highly sophisticated, evolutionarily developed action of our defense system that always responds in a tailor-made fashion.
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3.7.8.3 Update of Ferroptosis Activation Mechanisms As briefly outlined and illustrated in Vol. 2 [29], Sect. 4.3.4.2 and Fig. 4.2, pp. 134/135, ferroptosis is executed by lipid peroxidation, which relies on ROS generation and transition metal iron availability. Indeed, lipid peroxidation is generally considered as a process under which oxidants such as ROS attack lipids containing carbon-carbon double bond(s), especially phospholipid-containing polyunsaturated fatty acids (PUFAs-PLs) that involve hydrogen abstraction from carbon, with oxygen insertion resulting in lipid peroxyl radicals and hydroperoxides. This oxidative process of lipids can occur via three distinct mechanisms: (1) enzymatic oxidation by enzymes such as lipoxygenases (LOX), cyclooxygenases (COX), and cytochrome P450; (2) non-enzymatic, ROS-mediated oxidation that requires catalysis by transition metals or hemin, and; (3) non-enzymatic, non-ROS- mediated oxidation. Each lipid oxidation mechanism finally leads to the generation of various highly reactive terminal degradation products with high stereospecificity, which include phosphatidylserine (PS), oxidized phospholipids (OxPLs) containing oxidized cardiolipin (OxCL), phosphatidylcholine (PC), or phosphatidylethanolamine (PE) headgroups, as well as fragments such as reactive aldehydes. The activation mechanisms of ferroptosis have recently been updated by Jiang et al. [481] and Tang et al. [479], where more and more recent information on this emerging subroutine of RN is being presented. However, it is important to note here that the exact mechanisms of ferroptosis-dependent membrane rupture are still not clear. To cite here Jiang et al. [481]: “Despite significant progress in understanding the mechanisms regulating ferroptosis, we still do not know how cells ultimately die. Uncontrolled peroxidation of PUFA-PLs is the most downstream step identified; it may be that peroxidized phospholipids cause membrane damage or even pore formation, compromising membrane integrity.” 3.7.8.4 Ferroptosis in Infections: First Reports Research on the role of ferroptosis in infections is still in its infancy, but review articles have already discussed this emerging topic in modern infectiology [291, 482–484], and the first intriguing data have already been published. For example, Amaral et al. [485], in studies on macrophages infected with virulent Mycobacterium tuberculosis both in vitro and in vivo, have reported on a major role of ferroptosis in cell death and tissue necrosis induced by this pathogen. The investigators observed that Mycobacterium tuberculosis-promoted macrophage necrosis is associated with reduced levels of glutathione and GPX4, along with elevated free iron, mitochondrial superoxide, and lipid peroxidation; that is, findings that are consistent with the definition of ferroptosis. In other lines of studies on the bacterium P. aeruginosa, Dar et al. [486] demonstrated that lipoxygenase, expressed by the pathogen, can selectively and specifically oxidize host membrane phospholipids, particularly arachidonoyl-phosphatidylethanoamine (an arachidonic acid) to 15-hydroperoxy- arachidonoyl-phosphatidylethanoamine, and trigger—acting as a proferroptotic signal and in the absence of GPX4—ferroptotic death in human bronchial epithelial cells. In viral infections, including COVID-19, the pathogenetic role of ferroptosis is increasingly discussed, as reflected, for example, by the publication of recent review
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articles [487, 488]. This is not a surprise since viral infections are known to be associated with oxidative stress. Indeed, as argued by Camini et al. [489], in general, viruses cause an imbalance in the cellular redox environment, which, depending on the virus and the cell, can result in different responses, for example, cell signaling, antioxidant defenses, ROS, and other processes.
3.7.9 Parthanatos Parthanatos (poly ADP-ribose polymer) is a unique and highly choreographed form of cell death, which occurs through injury-induced overactivation of the nuclear enzyme, poly (ADP-ribose) synthetase-1 (PARP-1), also known as poly (ADP- ribose) glycohydrolase or poly (ADP-ribose) transferase-1. The topic that has been briefly addressed in Vol. 1 [1], Sect. 19.3.5.3, p. 451, is not further pursued here (for a recent review, see [490]).
3.8 Outlook and Future Perspectives As mentioned in part one of this chapter, a variety of virulence factors are essential tools of pathogenic bacteria for escaping host innate/adaptive immune defense responses, including (1) the use of specialized secretion systems to subvert host functions; (2) evasion of autophagy pathways; (3) interference with induction of a proinflammatory cytokine transcriptional response; (4) camouflage of MAMPs, and; (5) targeting PRR-mediated signaling pathways. Viruses, for example, DNA viruses, use similar tools for escape, including (1) manipulation of host defense protein levels by either transcriptional regulation or protein degradation; (2) repurposing or inhibiting these cellular immune factors by molecular hijacking or by regulating their PTM status, and; (3) induction by infection of temporal modulation of apoptosis to facilitate viral replication and spread. In addition, if one accepts that the ability of a pathogen to induce subroutines of RN is a hallmark of its virulence, then the property of a virus to trigger cellular pro-death pathways should also be seen as a strong virulence factor. On the other hand, however, microbes are known to have evolved strategies to interfere with the pathways of RCD to circumvent eradication by the host; that is, strategies that can be regarded as a real hallmark of their virulence. In fact, the observation that human bacteria and viruses continuously and consistently spark new infections should actually be testimony that their tools to escape host immune defense responses are effective. On the other hand, as outlined in part two of this chapter, the development of multiple host defense responses on the cellular and organismal level, driven and orchestrated by an amazing arsenal of DAMPs, provides witness to the fact that throughout evolution, mammals have successfully warded off the attacks of pathogens. Indeed, the complexity of the various DAMP-triggered signaling pathways discovered to drive the different subroutines of RCD, including recently PANoptosis, together with the evolvement of crosstalks and interconnectedness between RCD
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resulting in DAMP-promoted positive feed-forward loops, reflects the relevance of a continuously running evolutionary arms race between the pathogens and their hosts. And the current discovery of PANoptosis, tentatively proposed here to promote DAMP-driven positive feed-forward loops that amplify host defenses against pathogens, may reflect the current culmination on the host side to develop novel arms to combat pathogens: “a self-fulfilling prophecy of the Red Queen paradigm.” Mankind can obviously be confident in this paradigm that promises the establishment of new successful immune defense responses against newly emerging weapons on the side of pathogens. But we should not forget here the tenor of the book: the massive induction of forms of RCD associated with the generation and emission of DAMPs in excess leads to uncontrolled and dysregulated defense responses, manifested, for example, in the creation of local and systemic hyperinflammatory and hypercoagulative processes. With this respect, the release of excessive DAMPs from pathogen-induced RCD can be considered a strong pathogenetic factor in severe/fatal courses of infectious diseases such as currently observed in sepsis and COVID-19 patients (the topic will be discussed in more detail in Sects. 5.4 and 5.5). This means, however, that the medical community has to be alert to develop innovative therapeutics, which can interfere with the various pro-death pathways driving the different forms of RCD.
References 1. Land WG. Damage-associated molecular patterns in human diseases. Volume 1: injury- induced innate immune responses. Cham: Springer International Publishing; 2018. Available from http://link.springer.com/10.1007/978-3-319-78655-1. 2. Hospenthal MK, Costa TRD, Waksman G. A comprehensive guide to pilus biogenesis in Gram-negative bacteria. Nat Rev Microbiol. 2017;15:365–79. Available from http://www. nature.com/articles/nrmicro.2017.40. 3. Isenberg HD. Pathogenicity and virulence: another view. Clin Microbiol Rev. 1988;1:40–53. Available from http://cmr.asm.org/lookup/doi/10.1128/CMR.1.1.40. 4. Cambronne ED, Schneewind O. Bacterial invasins: molecular systems dedicated to the invasion of host tissues. Concepts Bact Virulence. 2004;2004:181–209. Available from https:// www.karger.com/Article/FullText/81696. 5. Kline KA, Fälker S, Dahlberg S, Normark S, Henriques-Normark B. Bacterial adhesins in host-microbe interactions. Cell Host Microbe. 2009;5:580–92. Available from https://linkinghub.elsevier.com/retrieve/pii/S1931312809001784. 6. Thanassi DG, Bliska JB, Christie PJ. Surface organelles assembled by secretion systems of Gram-negative bacteria: diversity in structure and function. FEMS Microbiol Rev. 2012;36:1046–82. Available from https://academic.oup.com/femsre/article-lookup/ doi/10.1111/j.1574-6976.2012.00342.x. 7. Mühlen S, Dersch P. Anti-virulence strategies to target bacterial infections. Curr Top Microbiol Immunol. 2015;2015:147–83. Available from http://link.springer.com/10.1007/82_2015_490. 8. Ribet D, Cossart P. How bacterial pathogens colonize their hosts and invade deeper tissues. Microbes Infect. 2015;17:173–83. Available from https://linkinghub.elsevier.com/retrieve/ pii/S1286457915000179. 9. Leitão JH. Microbial virulence factors. Int J Mol Sci. 2020;21:5320. Available from https:// www.mdpi.com/1422-0067/21/15/5320.
References
175
10. Costerton JW, Lewandowski Z, Caldwell DE, Korber DR, Lappin-Scott HM. Microbial biofilms. Annu Rev Microbiol. 1995;49:711–45. Available from http://www.annualreviews.org/ doi/10.1146/annurev.mi.49.100195.003431. 11. Boles BR, Horswill AR. AGR-mediated dispersal of Staphylococcus aureus biofilms. PLoS Pathog. 2008;4:e1000052. Available from https://dx.plos.org/10.1371/journal.ppat.1000052. 12. Landini P, Antoniani D, Burgess JG, Nijland R. Molecular mechanisms of compounds affecting bacterial biofilm formation and dispersal. Appl Microbiol Biotechnol. 2010;86:813–23. Available from https://pubmed.ncbi.nlm.nih.gov/20165945/. 13. Paul D, Gopal J, Kumar M, Manikandan M. Nature to the natural rescue: Silencing microbial chats. Chem Biol Interact. 2018;280:86–98. Available from https://linkinghub.elsevier.com/ retrieve/pii/S0009279717309742. 14. Abisado RG, Benomar S, Klaus JR, Dandekar AA, Chandler JR. Bacterial quorum sensing and microbial community interactions. MBio. 2018;9:e02331. Available from https://mbio. asm.org/content/9/3/e02331-17. 15. Roy R, Tiwari M, Donelli G, Tiwari V. Strategies for combating bacterial biofilms: a focus on anti-biofilm agents and their mechanisms of action. Virulence. 2018;9:522–54. Available from https://www.tandfonline.com/doi/full/10.1080/21505594.2017.1313372. 16. Del Pozo JL. Biofilm-related disease. Expert Rev Anti-Infect Ther. 2018;16:51–65. Available from https://www.tandfonline.com/doi/full/10.1080/14787210.2018.1417036. 17. Jamal M, Ahmad W, Andleeb S, Jalil F, Imran M, Nawaz MA, et al. Bacterial biofilm and associated infections. J Chin Med Assoc. 2018;81:7–11. Available from https://linkinghub. elsevier.com/retrieve/pii/S1726490117302587. 18. Wen Z, Zhang J-R. Bacterial capsules. In: Tang Y, Sails A, editors. Mol med microbiol. 2nd ed. Academic: New York; 2015. p. 33–52. Available from https://www.elsevier.com/books/ molecular-medical-microbiology/tang/978-0-12-397169-2. 19. Ophir T, Gutnick DL. A role for exopolysaccharides in the protection of microorganisms from desiccation. Appl Environ Microbiol. 1994;60:740–5. Available from https://aem.asm. org/content/60/2/740. 20. Moxon ER, Kroll JS. The role of bacterial polysaccharide capsules as virulence factors. Curr Top Microbiol Immunol. 1990;1990:65–85. Available from http://link.springer. com/10.1007/978-3-642-74694-9_4. 21. Nahm MH, Katz J. Immunity to extracellular bacteria. In: Paul WE, editor. Fundam immunol. 7th ed. Philadelphia: Lippincott Williams & Wilkins; 2013. Available from https://www. worldcat.org/title/fundamental-immunology/oclc/856655285. 22. Krukonis ES, Thomson JJ. Complement evasion mechanisms of the systemic pathogens yersiniae and salmonellae. FEBS Lett. 2020;594:2598–620. Available from https://onlinelibrary. wiley.com/doi/abs/10.1002/1873-3468.13771. 23. Chakravarty S, Massé E. RNA-dependent regulation of virulence in pathogenic bacteria. Front Cell Infect Microbiol. 2019;9:337. Available from https://www.frontiersin.org/ article/10.3389/fcimb.2019.00337/full. 24. Porcheron G, Habib R, Houle S, Caza M, Lépine F, Daigle F, et al. The small RNA RyhB contributes to siderophore production and virulence of uropathogenic Escherichia coli. Infect Immun. 2014;82:5056–68. Available from https://iai.asm.org/content/82/12/5056. 25. Chareyre S, Mandin P. Bacterial iron homeostasis regulation by sRNAs. Microbiol Spectr. 2018. Available from http://www.asmscience.org/content/ book/10.1128/9781683670247.chap16. 26. Tsatsaronis JA, Franch-Arroyo S, Resch U, Charpentier E. Extracellular vesicle RNA: a universal mediator of microbial communication? Trends Microbiol. 2018;26:401–10. Available from https://linkinghub.elsevier.com/retrieve/pii/S0966842X18300453. 27. Diallo I, Provost P. RNA-sequencing analyses of small bacterial rnas and their emergence as virulence factors in host-pathogen interactions. Int J Mol Sci. 2020;21:1627. Available from https://www.mdpi.com/1422-0067/21/5/1627. 28. Lécrivain A-L, Beckmann BM. Bacterial RNA in extracellular vesicles: a new regulator of host-pathogen interactions? Biochim Biophys Acta Gene Regul Mech. 2020;1863:194519. Available from https://linkinghub.elsevier.com/retrieve/pii/S1874939919302706.
176
3 Virulence of Pathogens and the Counteracting Responses of the Host
29. Land WG. Damage-associated molecular patterns in human diseases. Vol. 2: danger signals as diagnostics, prognostics, and therapeutic targets. Cham: Springer International Publishing; 2020. Available from http://link.springer.com/10.1007/978-3-030-53868-2. 30. Andrews SC, Robinson AK, Rodríguez-Quiñones F. Bacterial iron homeostasis. FEMS Microbiol Rev. 2003;27:215–37. Available from https://academic.oup.com/femsre/ article-lookup/doi/10.1016/S0168-6445(03)00055-X. 31. Saha R, Saha N, Donofrio RS, Bestervelt LL. Microbial siderophores: a mini review. J Basic Microbiol. 2013;53:303–17. Available from http://doi.wiley.com/10.1002/jobm.201100552. 32. Holden VI, Bachman MA. Diverging roles of bacterial siderophores during infection. Metallomics. 2015;7:986–95. Available from http://xlink.rsc.org/?DOI=C4MT00333K. 33. Khan A, Singh P, Srivastava A. Synthesis, nature and utility of universal iron chelator – siderophore: a review. Microbiol Res. 2018;212–213:103–11. Available from https://linkinghub. elsevier.com/retrieve/pii/S0944501317306730. 34. Kramer J, Özkaya Ö, Kümmerli R. Bacterial siderophores in community and host interactions. Nat Rev Microbiol. 2020;18:152–63. Available from http://www.nature.com/articles/ s41579-019-0284-4. 35. Miethke M, Marahiel MA. Siderophore-based iron acquisition and pathogen control. Microbiol Mol Biol Rev. 2007;71:413–51. Available from https://mmbr.asm.org/content/71/3/413. 36. Palmer LD, Skaar EP. Transition metals and virulence in bacteria. Annu Rev Genet. 2016;50:67–91. Available from http://www.annualreviews.org/doi/10.1146/ annurev-genet-120215-035146. 37. Wilderman PJ, Vasil AI, Johnson Z, Wilson MJ, Cunliffe HE, Lamont IL, et al. Characterization of an endoprotease (PrpL) encoded by a PvdS-regulated gene in Pseudomonas aeruginosa. Infect Immun. 2001;69:5385–94. Available from https://iai.asm.org/content/69/9/5385. 38. Lamont IL, Beare PA, Ochsner U, Vasil AI, Vasil ML. Siderophore-mediated signaling regulates virulence factor production in Pseudomonas aeruginosa. Proc Natl Acad Sci. 2002;99:7072–7. Available from http://www.pnas.org/cgi/doi/10.1073/pnas.092016999. 39. Green ER, Mecsas J. Bacterial secretion systems: an overview. Microbiol Spectr. 2016;4:12. Available from http://www.asmscience.org/content/journal/microbiolspec/10.1128/microbiolspec.VMBF-0012-2015. 40. Tsirigotaki A, De Geyter J, Šoštaric N, Economou A, Karamanou S. Protein export through the bacterial Sec pathway. Nat Rev Microbiol. 2017;15:21–36. Available from http://www. nature.com/articles/nrmicro.2016.161. 41. Frain KM, Robinson C, van Dijl JM. Transport of folded proteins by the tat system. Protein J. 2019;38:377–88. Available from http://link.springer.com/10.1007/s10930-019-09859-y. 42. Tseng T-T, Tyler BM, Setubal JC. Protein secretion systems in bacterial-host associations, and their description in the gene ontology. BMC Microbiol. 2009;9:2. Available from http:// bmcmicrobiol.biomedcentral.com/articles/10.1186/1471-2180-9-S1-S2. 43. Simeone R, Bobard A, Lippmann J, Bitter W, Majlessi L, Brosch R, et al. Phagosomal rupture by mycobacterium tuberculosis results in toxicity and host cell death. PLoS Pathog. 2012;8:e1002507. Available from https://dx.plos.org/10.1371/journal.ppat.1002507. 44. Gunasinghe SD, Webb CT, Elgass KD, Hay ID, Lithgow T. Super-resolution imaging of protein secretion systems and the cell surface of gram-negative bacteria. Front Cell Infect Microbiol. 2017;7:220. Available from http://journal.frontiersin.org/article/10.3389/ fcimb.2017.00220/full. 45. Pena RT, Blasco L, Ambroa A, González-Pedrajo B, Fernández-García L, López M, et al. Relationship between quorum sensing and secretion systems. Front Microbiol. 2019;10:1100. Available from https://www.frontiersin.org/article/10.3389/fmicb.2019.01100/full. 46. Tiwari S, Casey R, Goulding CW, Hingley-Wilson S, Jacobs WR. Infect and inject: how mycobacterium tuberculosis exploits its major virulence-associated type VII secretion system, ESX-1. Bact Intracell. 2019;2019:113–26. Available from http://www.asmscience.org/ content/book/10.1128/9781683670261.chap8. 47. Vaziri F, Brosch R. ESX/type VII secretion systems—an important way out for mycobacterial proteins. Protein Secret Bact. 2019;2019:351–62. Available from http://www.asmscience. org/content/book/10.1128/9781683670285.chap28.
References
177
48. Denise R, Abby SS, Rocha EPC. The evolution of protein secretion systems by co-option and tinkering of cellular machineries. Trends Microbiol. 2020;28:372–86. Available from https:// linkinghub.elsevier.com/retrieve/pii/S0966842X2030007X. 49. Ratner D, Orning MPA, Lien E. Bacterial secretion systems and regulation of inflammasome activation. J Leukoc Biol. 2017;101:165–81. Available from http://doi.wiley.com/10.1189/ jlb.4MR0716-330R. 50. An Y, Wang J, Li C, Leier A, Marquez-Lago T, Wilksch J, et al. Comprehensive assessment and performance improvement of effector protein predictors for bacterial secretion systems III, IV and VI. Brief Bioinform. 2016;19:100. Available from https://academic.oup.com/bib/ article-lookup/doi/10.1093/bib/bbw100. 51. Frees D, Brøndsted L, Ingmer H. Bacterial proteases and virulence. In: Subcell biochem. New York: Springer; 2013. p. 161–92. Available from http://link.springer. com/10.1007/978-94-007-5940-4_7. 52. Flores-Díaz M, Monturiol-Gross L, Naylor C, Alape-Girón A, Flieger A. Bacterial sphingomyelinases and phospholipases as virulence factors. Microbiol Mol Biol Rev. 2016;80:597–628. Available from https://mmbr.asm.org/content/80/3/597. 53. Lebrun I, Marques-Porto R, Pereira A, Pereira A, Perpetuo E. Bacterial toxins: an overview on bacterial proteases and their action as virulence factors. Mini-Rev Med Chem. 2009;9:820–8. Available from http://www.eurekaselect.com/openurl/content. php?genre=article&issn=1389-5575&volume=9&issue=7&spage=820. 54. Guerrero-Mandujano A, Hernández-Cortez C, Ibarra JA, Castro-Escarpulli G. The outer membrane vesicles: secretion system type zero. Traffic. 2017;18:425–32. Available from http://doi.wiley.com/10.1111/tra.12488. 55. Toyofuku M, Nomura N, Eberl L. Types and origins of bacterial membrane vesicles. Nat Rev Microbiol. 2019;17:13–24. Available from http://www.nature.com/articles/ s41579-018-0112-2. 56. Dineshkumar K, Aparna V, Wu L, Wan J, Abdelaziz MH, Su Z, et al. Bacterial bug-out bags: outer membrane vesicles and their proteins and functions. J Microbiol. 2020;58:531–42. Available from http://link.springer.com/10.1007/s12275-020-0026-3. 57. Caruana JC, Walper SA. Bacterial membrane vesicles as mediators of microbe – microbe and microbe – host community interactions. Front Microbiol. 2020;11:432. Available from https://www.frontiersin.org/article/10.3389/fmicb.2020.00432/full. 58. Bielaszewska M, Rüter C, Kunsmann L, Greune L, Bauwens A, Zhang W, et al. Enterohemorrhagic Escherichia coli hemolysin employs outer membrane vesicles to target mitochondria and cause endothelial and epithelial apoptosis. PLoS Pathog. 2013;9:e1003797. Available from https://dx.plos.org/10.1371/journal.ppat.1003797. 59. Bielaszewska M, Rüter C, Bauwens A, Greune L, Jarosch K-A, Steil D, et al. Host cell interactions of outer membrane vesicle-associated virulence factors of enterohemorrhagic Escherichia coli O157: intracellular delivery, trafficking and mechanisms of cell injury. PLoS Pathog. 2017;13:e1006159. Available from https://dx.plos.org/10.1371/journal. ppat.1006159. 60. Jan AT. Outer membrane vesicles (OMVs) of gram-negative bacteria: a perspective update. Front Microbiol. 2017;8:e01053. Available from http://journal.frontiersin.org/article/10.3389/ fmicb.2017.01053/full. 61. Lee E-Y, Choi D-Y, Kim D-K, Kim J-W, Park JO, Kim S, et al. Gram-positive bacteria produce membrane vesicles: proteomics-based characterization of Staphylococcus aureus- derived membrane vesicles. Proteomics. 2009;9:5425–36. Available from http://doi.wiley. com/10.1002/pmic.200900338. 62. Dutta S, Iida K, Takade A, Meno Y, Nair GB, Yoshida S. Release of shiga toxin by membrane vesicles in shigella dysenteriae serotype 1 strains and in vitro effects of antimicrobials on toxin production and release. Microbiol Immunol. 2004;48:965–9. Available from http://doi. wiley.com/10.1111/j.1348-0421.2004.tb03626.x. 63. Chatterjee D, Chaudhuri K. Association of cholera toxin with Vibrio cholerae outer membrane vesicles which are internalized by human intestinal epithelial cells. FEBS Lett. 2011;585:1357–62. Available from http://doi.wiley.com/10.1016/j.febslet.2011.04.017.
178
3 Virulence of Pathogens and the Counteracting Responses of the Host
64. Nakao R, Takashiba S, Kosono S, Yoshida M, Watanabe H, Ohnishi M, et al. Effect of Porphyromonas gingivalis outer membrane vesicles on gingipain-mediated detachment of cultured oral epithelial cells and immune responses. Microbes Infect. 2014;16:6–16. Available from https://linkinghub.elsevier.com/retrieve/pii/S1286457913001974. 65. Boisvert H, Duncan MJ. Clathrin-dependent entry of a gingipain adhesin peptide and Porphyromonas gingivalis into host cells. Cell Microbiol. 2008;10:2538–52. Available from http://doi.wiley.com/10.1111/j.1462-5822.2008.01228.x. 66. Pelkmans L, Helenius A. Endocytosis via caveolae. Traffic. 2002;3:311–20. Available from http://doi.wiley.com/10.1034/j.1600-0854.2002.30501.x. 67. Ewers H, Helenius A. Lipid-mediated endocytosis. Cold Spring Harb Perspect Biol. 2011;3:a004721. Available from http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect.a004721. 68. O’Donoghue EJ, Krachler AM. Mechanisms of outer membrane vesicle entry into host cells. Cell Microbiol. 2016;18:1508–17. Available from http://doi.wiley.com/10.1111/cmi.12655. 69. Gonzalez MR, Bischofberger M, Pernot L, van der Goot FG, Frêche B. Bacterial pore- forming toxins: the (w)hole story? Cell Mol Life Sci. 2008;65:493–507. Available from http://link.springer.com/10.1007/s00018-007-7434-y. 70. Sastalla I, Monack DM, Kubatzky KF. Editorial: Bacterial exotoxins: how bacteria fight the immune system. Front Immunol. 2016;7:300. Available from http://journal.frontiersin.org/ Article/10.3389/fimmu.2016.00300/abstract. 71. do Vale A, Cabanes D, Sousa S. Bacterial toxins as pathogen weapons against phagocytes. Front Microbiol. 2016;7:42. Available from http://journal.frontiersin.org/article/10.3389/ fmicb.2016.00042. 72. Rudkin JK, McLoughlin RM, Preston A, Massey RC. Bacterial toxins: offensive, defensive, or something else altogether? PLoS Pathog. 2017;13:e1006452. Available from https:// dx.plos.org/10.1371/journal.ppat.1006452. 73. Carbonetti NH. Contribution of pertussis toxin to the pathogenesis of pertussis disease: graphical abstract figure. Pathog Dis. 2015;73:73. Available from https://academic.oup.com/ femspd/article-lookup/doi/10.1093/femspd/ftv073. 74. Fowler CC, Chang S-J, Gao X, Geiger T, Stack G, Galán JE. Emerging insights into the biology of typhoid toxin. Curr Opin Microbiol. 2017;35:70–7. Available from https://linkinghub. elsevier.com/retrieve/pii/S1369527417300176. 75. Duport A-B, Armengaud. Advanced proteomics as a powerful tool for studying toxins of human bacterial pathogens. Toxins. 2019;11:576. Available from https://www.mdpi. com/2072-6651/11/10/576. 76. Navarro M, McClane B, Uzal F. Mechanisms of action and cell death associated with Clostridium perfringens toxins. Toxins. 2018;10:212. Available from http://www.mdpi. com/2072-6651/10/5/212. 77. Coelho C, Brown L, Maryam M, Vij R, Smith DFQ, Burnet MC, et al. Listeria monocytogenes virulence factors, including listeriolysin O, are secreted in biologically active extracellular vesicles. J Biol Chem. 2019;294:1202–17. Available from http://www.jbc.org/lookup/ doi/10.1074/jbc.RA118.006472. 78. Popoff MR. Bacterial exotoxins. Concepts bact virulence. Basel: Karger; 2004. p. 28–54. Available from https://www.karger.com/Article/FullText/81688. 79. Lemichez E, Barbieri JT. General aspects and recent advances on bacterial protein toxins. Cold Spring Harb Perspect Med. 2013;3:a013573. Available from http://perspectivesinmedicine.cshlp.org/lookup/doi/10.1101/cshperspect.a013573. 80. Peraro MD, van der Goot FG. Pore-forming toxins: ancient, but never really out of fashion. Nat Rev Microbiol. 2016;14:77–92. Available from http://www.nature.com/articles/ nrmicro.2015.3. 81. Mondal AK, Sreekumar A, Kundu N, Kathuria R, Verma P, Gandhi S, et al. Structural basis and functional implications of the membrane pore-formation mechanisms of bacterial pore- forming toxins. Adv Exp Med Biol. 2018;2018:281–91. Available from http://link.springer. com/10.1007/978-981-13-3065-0_19.
References
179
82. Los FCO, Randis TM, Aroian RV, Ratner AJ. Role of pore-forming toxins in bacterial infectious diseases. Microbiol Mol Biol Rev. 2013;77:173–207. Available from https://mmbr.asm. org/content/77/2/173. 83. Dahlberg D, Mariussen E, Goverud IL, Tønjum T, Mæhlen J, Antal E-A, et al. Staphylococcal α-hemolysin is neurotoxic and causes lysis of brain cells in vivo and in vitro. Neurotoxicology. 2015;48:61–7. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0161813X15000285. 84. Reyes-Robles T, Torres VJ. Staphylococcus aureus pore-forming toxins. Curr Top Microbiol Immunol. 2016;2016:121–44. Available from http://link.springer.com/10.1007/82_2016_16. 85. Oliveira D, Borges A, Simões M. Staphylococcus aureus toxins and their molecular activity in infectious diseases. Toxins. 2018;10:252. Available from http://www.mdpi. com/2072-6651/10/6/252. 86. Tam K, Torres VJ. Staphylococcus aureus secreted toxins and extracellular enzymes. Microbiol Spectr. 2019;7:39. Available from http://www.asmscience.org/content/journal/ microbiolspec/10.1128/microbiolspec.GPP3-0039-2018. 87. von Hoven G, Qin Q, Neukirch C, Husmann M, Hellmann N. Staphylococcus aureus α-toxin: small pore, large consequences. Biol Chem. 2019;400:1261–76. Available from http://www. degruyter.com/view/j/bchm.2019.400.issue-10/hsz-2018-0472/hsz-2018-0472.xml. 88. Kitur K, Parker D, Nieto P, Ahn DS, Cohen TS, Chung S, et al. Toxin-induced necroptosis is a major mechanism of Staphylococcus aureus lung damage. PLoS Pathog. 2015;11:e1004820. Available from https://dx.plos.org/10.1371/journal.ppat.1004820. 89. Guo N, Liu Z, Yan Z, Liu Z, Hao K, Liu C, et al. Subinhibitory concentrations of Honokiol reduce α-Hemolysin (Hla) secretion by Staphylococcus aureus and the Hla-induced inflammatory response by inactivating the NLRP3 inflammasome. Emerg Microbes Infect. 2019;8:707–16. Available from https://www.tandfonline.com/doi/full/10.1080/2222175 1.2019.1617643. 90. Wang X, Eagen WJ, Lee JC. Orchestration of human macrophage NLRP3 inflammasome activation by Staphylococcus aureus extracellular vesicles. Proc Natl Acad Sci. 2020;117:3174–84. Available from http://www.pnas.org/lookup/doi/10.1073/ pnas.1915829117. 91. Li S, Huang H, Rao X, Chen W, Wang Z, Hu X. Phenol-soluble modulins: novel virulence- associated peptides of staphylococci. Future Microbiol. 2014;9:203–16. Available from https://www.futuremedicine.com/doi/10.2217/fmb.13.153. 92. Jing W, Lo Pilato J, Kay C, Man SM. Activation mechanisms of inflammasomes by bacterial toxins. Cell Microbiol. 2021;23:13309. Available from https://onlinelibrary.wiley.com/ doi/10.1111/cmi.13309. 93. Odumosu O, Nicholas D, Yano H, Langridge W. AB toxins: a paradigm switch from deadly to desirable. Toxins. 2010;2:1612–45. Available from http://www.mdpi. com/2072-6651/2/7/1612. 94. Benz R, Barth H. Toxin transport by A-B type of toxins in eukaryotic target cells and its inhibition by positively charged heterocyclic molecules. Curr Top Microbiol Immunol. 2017;2017:229–56. Available from http://link.springer.com/10.1007/82_2017_17. 95. Falnes PØ, Sandvig K. Penetration of protein toxins into cells. Curr Opin Cell Biol. 2000;12:407–13. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0955067400001095. 96. Collier R. Understanding the mode of action of diphtheria toxin: a perspective on progress during the 20th century. Toxicon. 2001;39:1793–803. Available from https://linkinghub.elsevier.com/retrieve/pii/S0041010101001659. 97. Shafiee F, Aucoin MG, Jahanian-Najafabadi A. Targeted diphtheria toxin-based therapy: a review article. Front Microbiol. 2019;10:2340. Available from https://www.frontiersin.org/ article/10.3389/fmicb.2019.02340/full. 98. Rodnin MV, Kashipathy MM, Kyrychenko A, Battaile KP, Lovell S, Ladokhin AS. Structure of the diphtheria toxin at acidic pH: implications for the conformational switching
180
3 Virulence of Pathogens and the Counteracting Responses of the Host
of the translocation domain. Toxins. 2020;12:704. Available from https://www.mdpi. com/2072-6651/12/11/704. 99. Murphy JR. Mechanism of diphtheria toxin catalytic domain delivery to the eukaryotic cell cytosol and the cellular factors that directly participate in the process. Toxins. 2011;3:294–308. Available from http://www.mdpi.com/2072-6651/3/3/294. 100. Morris RE, Gerstein AS, Bonventre PF, Saelinger CB. Receptor-mediated entry of diphtheria toxin into monkey kidney (Vero) cells: electron microscopic evaluation. Infect Immun. 1985;50:721–7. Available from https://iai.asm.org/content/50/3/721. 101. Hoch DH, Romero-Mira M, Ehrlich BE, Finkelstein A, DasGupta BR, Simpson LL. Channels formed by botulinum, tetanus, and diphtheria toxins in planar lipid bilayers: relevance to translocation of proteins across membranes. Proc Natl Acad Sci. 1985;82:1692–6. Available from http://www.pnas.org/cgi/doi/10.1073/pnas.82.6.1692. 102. Moya M, Dautry-Varsat A, Goud B, Louvard D, Boquet P. Inhibition of coated pit formation in Hep2 cells blocks the cytotoxicity of diphtheria toxin but not that of ricin toxin. J Cell Biol. 1985;101:548–59. Available from https://rupress.org/jcb/article/101/2/548/28126/ Inhibition-of-coated-pit-formation-in-Hep2-cells. 103. Ratts R, Zeng H, Berg EA, Blue C, McComb ME, Costello CE, et al. The cytosolic entry of diphtheria toxin catalytic domain requires a host cell cytosolic translocation factor complex. J Cell Biol. 2003;160:1139–50. Available from https://rupress.org/jcb/ article/160/7/1139/33190/The-cytosolic-entry-of-diphtheria-toxin-catalytic. 104. Bennett MJ, Eisenberg D. Refined structure of monomelic diphtheria toxin at 2.3 Å resolution. Protein Sci. 1994;3:1464–75. Available from http://doi.wiley.com/10.1002/ pro.5560030912. 105. Holmes RK. Biology and molecular epidemiology of diphtheria toxin and the tox gene. J Infect Dis. 2000;181:S156–67. Available from https://academic.oup.com/jid/article-lookup/ doi/10.1086/315554. 106. Zahaf NI, Schmidt G. Bacterial toxins for cancer therapy. Toxins. 2017;9:236. Available from http://www.mdpi.com/2072-6651/9/8/236. 107. Popov SG, Villasmil R, Bernardi J, Grene E, Cardwell J, Wu A, et al. Lethal toxin of Bacillus anthracis causes apoptosis of macrophages. Biochem Biophys Res Commun. 2002;293:349–55. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0006291X02002279. 108. Agrawal A, Pulendran B. Anthrax lethal toxin: a weapon of multisystem destruction. Cell Mol Life Sci. 2004;61:2859–65. Available from http://link.springer.com/10.1007/ s00018-004-4251-4. 109. Moayeri M, Sastalla I, Leppla SH. Anthrax and the inflammasome. Microbes Infect. 2012;14:392–400. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1286457911003091. 110. McClane B, Shrestha A. Using more than 1 (path)way to kill a host cell: lessons from Clostridium perfringens enterotoxin. Microbiol Insights. 2020;13:117863612093151. Available from http://journals.sagepub.com/doi/10.1177/1178636120931518. 111. Martin OCB, Frisan T. Bacterial genotoxin-induced DNA damage and modulation of the host immune microenvironment. Toxins. 2020;12:63. Available from https://www.mdpi. com/2072-6651/12/2/63. 112. Kreuzer KN. DNA damage responses in prokaryotes: regulating gene expression, modulating growth patterns, and manipulating replication forks. Cold Spring Harb Perspect Biol. 2013;5:a012674. Available from http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect.a012674. 113. Tesh VL. Induction of apoptosis by Shiga toxins. Future Microbiol. 2010;5:431–53. Available from https://www.futuremedicine.com/doi/10.2217/fmb.10.4. 114. Tesh VL. Activation of cell stress response pathways by Shiga toxins. Cell Microbiol. 2012;14:1–9. Available from http://doi.wiley.com/10.1111/j.1462-5822.2011.01684.x. 115. Lee M-S, Kwon H, Lee E-Y, Kim D-J, Park J-H, Tesh VL, et al. Shiga toxins activate the NLRP3 inflammasome pathway to promote both production of the proinflammatory cyto-
References
181
kine interleukin-1β and apoptotic cell death. Infect Immun. 2016;84:172–86. Available from https://iai.asm.org/content/84/1/172. 116. Lee M-S, Koo S, Jeong D, Tesh V. Shiga toxins as multi-functional proteins: induction of host cellular stress responses, role in pathogenesis and therapeutic applications. Toxins. 2016;8:77. Available from http://www.mdpi.com/2072-6651/8/3/77. 117. Park J-Y, Jeong Y-J, Park S-K, Yoon S-J, Choi S, Jeong D, et al. Shiga toxins induce apoptosis and ER stress in human retinal pigment epithelial cells. Toxins. 2017;9:319. Available from http://www.mdpi.com/2072-6651/9/10/319. 118. Mayer CL, Parello CSL, Lee BC, Itagaki K, Kurosawa S, Stearns-Kurosawa DJ. Pro- coagulant endothelial dysfunction results from EHEC shiga toxins and host damage- associated molecular patterns. Front Immunol. 2015;6:155. Available from http://journal. frontiersin.org/article/10.3389/fimmu.2015.00155/abstract 119. Galán JE. Common themes in the design and function of bacterial effectors. Cell Host Microbe. 2009;5:571–9. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1931312809001103. 120. Ribet D, Cossart P. Post-translational modifications in host cells during bacterial infection. FEBS Lett. 2010;584:2748–58. Available from http://doi.wiley.com/10.1016/j. febslet.2010.05.012. 121. Costa TRD, Felisberto-Rodrigues C, Meir A, Prevost MS, Redzej A, Trokter M, et al. Secretion systems in Gram-negative bacteria: structural and mechanistic insights. Nat Rev Microbiol. 2015;13:343–59. Available from http://www.nature.com/articles/nrmicro3456. 122. Jennings E, Thurston TLM, Holden DW. Salmonella SPI-2 type III secretion system effectors: molecular mechanisms and physiological consequences. Cell Host Microbe. 2017;22:217–31. Available from https://linkinghub.elsevier.com/retrieve/pii/S1931312817302925. 123. Galán JE, Waksman G. Protein-injection machines in bacteria. Cell. 2018;172:1306–18. Available from https://linkinghub.elsevier.com/retrieve/pii/S0092867418301119. 124. Allgood SC, Neunuebel MR. The recycling endosome and bacterial pathogens. Cell Microbiol. 2018;20:e12857. Available from http://doi.wiley.com/10.1111/cmi.12857. 125. Orning P, Weng D, Starheim K, Ratner D, Best Z, Lee B, et al. Pathogen blockade of TAK1 triggers caspase-8–dependent cleavage of gasdermin D and cell death. Science. 2018;362:1064–9. Available from https://www.sciencemag.org/lookup/doi/10.1126/science. aau2818. 126. Zhang L, Mei M, Yu C, Shen W, Ma L, He J, et al. The functions of effector proteins in yersinia virulence. Pol J Microbiol. 2016;65:5–12. Available from http://www.pjmonline.org/ the-functions-of-effector-proteins-in-yersinia-virulence/. 127. Ashida H, Suzuki T, Sasakawa C. Shigella infection and host cell death: a double-edged sword for the host and pathogen survival. Curr Opin Microbiol. 2021;59:1–7. Available from https://linkinghub.elsevier.com/retrieve/pii/S1369527420300886. 128. Kaper JB, Nataro JP, Mobley HLT. Pathogenic Escherichia coli. Nat Rev Microbiol. 2004;2:123–40. Available from http://www.nature.com/articles/nrmicro818. 129. Wang H, Zhong Z, Luo Y, Cox E, Devriendt B. Heat-stable enterotoxins of enterotoxigenic Escherichia coli and their impact on host immunity. Toxins. 2019;11:24. Available from https://www.mdpi.com/2072-6651/11/1/24. 130. Tuffs S, Haeryfar S, McCormick J. Manipulation of innate and adaptive immunity by staphylococcal superantigens. Pathogens. 2018;7:53. Available from https://www.mdpi. com/2076-0817/7/2/53. 131. Vrieling M, Tuffs SW, Yebra G, van Smoorenburg MY, Alves J, Pickering AC, et al. Population analysis of Staphylococcus aureus reveals a cryptic, highly prevalent superantigen SElW that contributes to the pathogenesis of bacteremia. MBio. 2020;11:1–13. Available from https:// mbio.asm.org/content/11/5/e02082-20. 132. Lu Y-C, Yeh W-C, Ohashi PS. LPS/TLR4 signal transduction pathway. Cytokine. 2008;42:145–51. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1043466608000070.
182
3 Virulence of Pathogens and the Counteracting Responses of the Host
133. Casadevall A, Pirofski L. Virulence factors and their mechanisms of action: the view from a damage–response framework. J Water Health. 2009;7:2–18. Available from https://iwaponline.com/jwh/article/7/S1/S2/2047/Virulence-factors-and-their-mechanisms-of-action. 134. Molinaro A, Holst O, Di Lorenzo F, Callaghan M, Nurisso A, D’Errico G, et al. Chemistry of lipid A: at the heart of innate immunity. Chem Eur J. 2015;21:500–19. Available from http:// doi.wiley.com/10.1002/chem.201403923. 135. Farhana A, Khan YS. Biochemistry, lipopolysaccharide. In: StatPearls. Treasure Island: StatPearls Publishing; 2020. Available from http://www.ncbi.nlm.nih.gov/ pubmed/32119301. 136. Du X, Ge W, Jing R, Pan L. Necroptosis in pulmonary macrophages mediates lipopolysaccharide- induced lung inflammatory injury by activating ZBP-1. Int Immunopharmacol. 2019;77:105944. Available from https://linkinghub.elsevier.com/ retrieve/pii/S1567576919314316. 137. Rathinam VAK, Zhao Y, Shao F. Innate immunity to intracellular LPS. Nat Immunol. 2019;20:527–33. Available from http://www.nature.com/articles/s41590-019-0368-3. 138. Tamada N, Tojo K, Yazawa T, Goto T. Necrosis rather than apoptosis is the dominant form of alveolar epithelial cell death in lipopolysaccharide-induced experimental acute respiratory distress syndrome model. Shock. 2020;54:128–39. Available from https://journals.lww. com/10.1097/SHK.0000000000001425. 139. Downs KP, Nguyen H, Dorfleutner A, Stehlik C. An overview of the non-canonical inflammasome. Mol Asp Med. 2020;76:100924. Available from https://linkinghub.elsevier.com/ retrieve/pii/S0098299720301266. 140. Vanaja SK, Russo AJ, Behl B, Banerjee I, Yankova M, Deshmukh SD, et al. Bacterial outer membrane vesicles mediate cytosolic localization of LPS and caspase-11 activation. Cell. 2016;165:1106–19. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0092867416304068. 141. Cossart P, Helenius A. Endocytosis of viruses and bacteria. Cold Spring Harb Perspect Biol. 2014;6:a016972. Available from http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect.a016972. 142. Ray K, Marteyn B, Sansonetti PJ, Tang CM. Life on the inside: the intracellular lifestyle of cytosolic bacteria. Nat Rev Microbiol. 2009;7:333–40. Available from http://www.nature. com/articles/nrmicro2112. 143. Mitchell G, Chen C, Portnoy DA. Strategies used by bacteria to grow in macrophages. Microbiol Spectr. 2016;4:12. Available from 10.1128/microbiolspec.mchd-0012-2015. 144. Sharma AK, Dhasmana N, Dubey N, Kumar N, Gangwal A, Gupta M, et al. Bacterial virulence factors: secreted for survival. Indian J Microbiol. 2017;57:1–10. Available from http:// link.springer.com/10.1007/s12088-016-0625-1. 145. Misch EA. Legionella: virulence factors and host response. Curr Opin Infect Dis. 2016;29:280–6. Available from http://journals.lww.com/00001432-201606000-00009. 146. Webb SAR, Kahler CM. Bench-to-bedside review: bacterial virulence and subversion of host defences. Crit Care. 2008;12:234. Available from http://ccforum.biomedcentral.com/ articles/10.1186/cc7091. 147. Baxt LA, Garza-Mayers AC, Goldberg MB. Bacterial subversion of host innate immune pathways. Science. 2013;340:697–701. Available from https://www.sciencemag.org/lookup/ doi/10.1126/science.1235771. 148. Rapisarda C, Fronzes R. Secretion systems used by bacteria to subvert host functions. Curr Issues Mol Biol. 2018;25:1–42. Available from https://www.caister.com/cimb/abstracts/ v25/1.html. 149. Reddick LE, Alto NM. Bacteria fighting back: how pathogens target and subvert the host innate immune system. Mol Cell. 2014;54:321–8. Available from https://linkinghub.elsevier. com/retrieve/pii/S1097276514002159. 150. Grabiec AM, Potempa J. Epigenetic regulation in bacterial infections: targeting histone deacetylases. Crit Rev Microbiol. 2018;44:336–50. Available from https://www.tandfonline. com/doi/full/10.1080/1040841X.2017.1373063.
References
183
151. Denzer L, Schroten H, Schwerk C. From gene to protein—how bacterial virulence factors manipulate host gene expression during infection. Int J Mol Sci. 2020;21:3730. Available from https://www.mdpi.com/1422-0067/21/10/3730. 152. Mohammadi E, Shafiee F, Shahzamani K, Ranjbar MM, Alibakhshi A, Ahangarzadeh S, et al. Novel and emerging mutations of SARS-CoV-2: biomedical implications. Biomed Pharmacother. 2021;139:111599. Available from https://pubmed.ncbi.nlm.nih. gov/33915502/. 153. Schrauwen EJA, Graaf M, Herfst S, Rimmelzwaan GF, Osterhaus ADME, Fouchier RAM. Determinants of virulence of influenza A virus. Eur J Clin Microbiol Infect Dis. 2014;33:479–90. Available from http://link.springer.com/10.1007/s10096-013-1984-8. 154. Ciancanelli MJ, Abel L, Zhang S-Y, Casanova J-L. Host genetics of severe influenza: from mouse Mx1 to human IRF7. Curr Opin Immunol. 2016;38:109–20. Available from https:// linkinghub.elsevier.com/retrieve/pii/S0952791515001685. 155. Baron S, Fons M, Albrecht T. Viral pathogenesis. In: Baron S, editor. Med. microbiol. 4th ed. Galveston: University of Texas Medical Branch at Galveston; 1996. Available from https:// pubmed.ncbi.nlm.nih.gov/21413306/. 156. He B. Viruses, endoplasmic reticulum stress, and interferon responses. Cell Death Differ. 2006;13:393–403. Available from http://www.nature.com/articles/4401833. 157. Muralidharan S, Mandrekar P. Cellular stress response and innate immune signaling: integrating pathways in host defense and inflammation. J Leukoc Biol. 2013;94:1167–84. Available from http://doi.wiley.com/10.1189/jlb.0313153. 158. Ivanov AV, Bartosch B, Isaguliants MG. Oxidative stress in infection and consequent disease. Oxidative Med Cell Longev. 2017;2017:1–3. Available from https://www.hindawi.com/ journals/omcl/2017/3496043/. 159. Eisenreich W, Rudel T, Heesemann J, Goebel W. How viral and intracellular bacterial pathogens reprogram the metabolism of host cells to allow their intracellular replication. Front Cell Infect Microbiol. 2019;9:42. Available from https://www.frontiersin.org/article/10.3389/ fcimb.2019.00042/full. 160. Kikkert M. Innate immune evasion by human respiratory RNA viruses. J Innate Immun. 2020;12:4–20. Available from https://www.karger.com/Article/FullText/503030. 161. Gordon DE, Jang GM, Bouhaddou M, Xu J, Obernier K, White KM, et al. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature. 2020;583:459–68. Available from http://www.nature.com/articles/s41586-020-2286-9. 162. Bouhaddou M, Memon D, Meyer B, White KM, Rezelj VV, Correa Marrero M, et al. The global phosphorylation landscape of SARS-CoV-2 infection. Cell. 2020;182:685–712. Available from https://linkinghub.elsevier.com/retrieve/pii/S0092867420308114. 163. Farag NS, Breitinger U, Breitinger HG, El Azizi MA. Viroporins and inflammasomes: a key to understand virus-induced inflammation. Int J Biochem Cell Biol. 2020;122:105738. Available from https://linkinghub.elsevier.com/retrieve/pii/S1357272520300558. 164. Gonzalez ME, Carrasco L. Viroporins. FEBS Lett. 2003;552:28–34. Available from http:// doi.wiley.com/10.1016/S0014-5793%2803%2900780-4. 165. Nieva JL, Madan V, Carrasco L. Viroporins: structure and biological functions. Nat Rev Microbiol. 2012;10:563–74. Available from http://www.nature.com/articles/nrmicro2820. 166. Ito M, Yanagi Y, Ichinohe T. Encephalomyocarditis virus viroporin 2B activates NLRP3 inflammasome. PLoS Pathog. 2012;8:e1002857. Available from https://dx.plos.org/10.1371/ journal.ppat.1002857. 167. McAuley JL, Tate MD, MacKenzie-Kludas CJ, Pinar A, Zeng W, Stutz A, et al. Activation of the NLRP3 inflammasome by IAV virulence protein PB1-F2 contributes to severe pathophysiology and disease. PLoS Pathog. 2013;9:e1003392. Available from https://dx.plos. org/10.1371/journal.ppat.1003392 168. Ichinohe T, Pang IK, Iwasaki A. Influenza virus activates inflammasomes via its intracellular M2 ion channel. Nat Immunol. 2010;11:404–10. Available from http://www.nature.com/ articles/ni.1861.
184
3 Virulence of Pathogens and the Counteracting Responses of the Host
169. To J, Torres J. Viroporins in the influenza virus. Cell. 2019;8:654. Available from https:// www.mdpi.com/2073-4409/8/7/654. 170. Nieto-Torres JL, Verdiá-Báguena C, Jimenez-Guardeño JM, Regla-Nava JA, Castaño- Rodriguez C, Fernandez-Delgado R, et al. Severe acute respiratory syndrome coronavirus E protein transports calcium ions and activates the NLRP3 inflammasome. Virology. 2015;485:330–9. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0042682215003566. 171. Castaño-Rodriguez C, Honrubia JM, Gutiérrez-Álvarez J, DeDiego ML, Nieto-Torres JL, Jimenez-Guardeño JM, et al. Role of severe acute respiratory syndrome coronavirus viroporins E, 3a, and 8a in replication and pathogenesis. MBio. 2018;9:e02325. Available from https://mbio.asm.org/content/9/3/e02325-17. 172. Crow MS, Lum KK, Sheng X, Song B, Cristea IM. Diverse mechanisms evolved by DNA viruses to inhibit early host defenses. Crit Rev Biochem Mol Biol. 2016;51:452–81. Available from https://www.tandfonline.com/doi/full/10.1080/10409238.2016.1226250. 173. Brunke S, Mogavero S, Kasper L, Hube B. Virulence factors in fungal pathogens of man. Curr Opin Microbiol. 2016;32:89–95. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1369527416300650 174. Richardson MD. Opportunistic and pathogenic fungi. J Antimicrob Chemother. 1991;28:1–11. Available from https://academic.oup.com/jac/article-lookup/doi/10.1093/jac/28.suppl_A.1. 175. Haas H, Eisendle M, Turgeon BG. Siderophores in fungal physiology and virulence. Annu Rev Phytopathol. 2008;46:149–87. Available from http://www.annualreviews.org/ doi/10.1146/annurev.phyto.45.062806.094338. 176. Westman J, Hube B, Fairn GD. Integrity under stress: host membrane remodelling and damage by fungal pathogens. Cell Microbiol. 2019;21:e13016. Available from https://onlinelibrary.wiley.com/doi/abs/10.1111/cmi.13016. 177. Bennett JW, Klich M. Mycotoxins. Clin Microbiol Rev. 2003;16:497–516. Available from https://cmr.asm.org/content/16/3/497. 178. Brown R, Priest E, Naglik JR, Richardson JP. Fungal toxins and host immune responses. Front Microbiol. 2021;12:697. Available from https://www.frontiersin.org/articles/10.3389/ fmicb.2021.643639/full. 179. Richardson JP, Mogavero S, Moyes DL, Blagojevic M, Krüger T, Verma AH, et al. Processing of Candida albicans Ece1p is critical for candidalysin maturation and fungal virulence. MBio. 2018;9:e02178. Available from https://mbio.asm.org/content/9/1/e02178-17. 180. Ho J, Wickramasinghe DN, Nikou S-A, Hube B, Richardson JP, Naglik JR. Candidalysin is a potent trigger of alarmin and antimicrobial peptide release in epithelial cells. Cell. 2020;9:699. Available from https://www.mdpi.com/2073-4409/9/3/699. 181. de Toledo MS, Szwarc P, Goldenberg S, Alves LR. Extracellular vesicles in fungi: composition and functions. Curr Top Microbiol Immunol. 2018;141:45–59. Available from http:// link.springer.com/10.1007/82_2018_141. 182. Rizzo J, Rodrigues ML, Janbon G. Extracellular vesicles in fungi: past, present, and future perspectives. Front Cell Infect Microbiol. 2020;10:32760680. Available from https://pubmed. ncbi.nlm.nih.gov/32760680/. 183. Brown GD, Denning DW, Gow NAR, Levitz SM, Netea MG, White TC. Hidden killers: human fungal infections. Sci Transl Med. 2012;4:165. Available from https://stm.sciencemag. org/content/4/165/165rv13. 184. Moyes DL, Wilson D, Richardson JP, Mogavero S, Tang SX, Wernecke J, et al. Candidalysin is a fungal peptide toxin critical for mucosal infection. Nature. 2016;532:64–8. Available from http://www.nature.com/articles/nature17625. 185. Kay JG, Kramer JM, Visser MB. Danger signals in oral cavity-related diseases. J Leukoc Biol. 2019;106:193–200. Available from http://doi.wiley.com/10.1002/JLB.4MIR1118-439R. 186. McKerrow JH, Sun E, Rosenthal PJ, Bouvier J. The proteases and pathogenicity of parasitic protozoa. Annu Rev Microbiol. 1993;47:821–53. Available from http://www.annualreviews. org/doi/10.1146/annurev.mi.47.100193.004133.
References
185
187. Haldar K, Murphy SC, Milner DA, Taylor TE. Malaria: mechanisms of erythrocytic infection and pathological correlates of severe disease. Annu Rev Pathol Mech Dis. 2007;2:217–49. Available from http://www.annualreviews.org/doi/10.1146/annurev. pathol.2.010506.091913. 188. Gazzinelli RT, Kalantari P, Fitzgerald KA, Golenbock DT. Innate sensing of malaria parasites. Nat Rev Immunol. 2014;14:744–57. Available from http://www.nature.com/articles/ nri3742. 189. Gowda DC, Wu X. Parasite recognition and signaling mechanisms in innate immune responses to malaria. Front Immunol. 2018;9:3006. Available from https://www.frontiersin. org/article/10.3389/fimmu.2018.03006/full. 190. Melzer T, Duffy A, Weiss LM, Halonen SK. The gamma interferon (IFN-γ)-inducible GTP- binding protein IGTP is necessary for toxoplasma vacuolar disruption and induces parasite egression in IFN-γ-stimulated astrocytes. Infect Immun. 2008;76:4883–94. Available from https://iai.asm.org/content/76/11/4883. 191. Atayde VD, Hassani K, da Silva Lira Filho A, Borges AR, Adhikari A, Martel C, et al. Leishmania exosomes and other virulence factors: impact on innate immune response and macrophage functions. Cell Immunol. 2016;309:7–18. Available from https://linkinghub. elsevier.com/retrieve/pii/S0008874916300624. 192. Osorio L, Ríos I, Gutiérrez B, González J. Virulence factors of Trypanosoma cruzi: who is who? Microbes Infect. 2012;14:1390–402. Available from https://linkinghub.elsevier.com/ retrieve/pii/S1286457912002201. 193. Ramírez-Flores CJ, Cruz-Mirón R, Arroyo R, Mondragón-Castelán ME, Nopal-Guerrero T, González-Pozos S, et al. Characterization of metalloproteases and serine proteases of Toxoplasma gondii tachyzoites and their effect on epithelial cells. Parasitol Res. 2019;118:289–306. Available from http://link.springer.com/10.1007/s00436-018-6163-5. 194. Dubremetz JF, Lebrun M. Virulence factors of Toxoplasma gondii. Microbes Infect. 2012;14:1403–10. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1286457912002225. 195. Wu Z, Wang L, Li J, Wang L, Wu Z, Sun X. Extracellular vesicle-mediated communication within host-parasite interactions. Front Immunol. 2019;9:e03066. Available from https:// www.frontiersin.org/article/10.3389/fimmu.2018.03066/full. 196. Bobardt SD, Dillman AR, Nair MG. The two faces of nematode infection: virulence and immunomodulatory molecules from nematode parasites of mammals, insects and plants. Front Microbiol. 2020;11:577846. Available from https://www.frontiersin.org/articles/10.3389/ fmicb.2020.577846/full. 197. Bennett APS, Robinson MW. Trematode proteomics: recent advances and future directions. Pathogens. 2021;10:348. Available from https://www.mdpi.com/2076-0817/10/3/348. 198. Wilson RA. Virulence factors of schistosomes. Microbes Infect. 2012;14:1442–50. Available from https://linkinghub.elsevier.com/retrieve/pii/S1286457912002183. 199. Mardahl M, Borup A, Nejsum P. A new level of complexity in parasite-host interaction: the role of extracellular vesicles. Adv Parasitol. 2019;2019:39–112. Available from https://linkinghub.elsevier.com/retrieve/pii/S0065308X19300041. 200. Bennett APS, de la Torre-Escudero E, Oliver NAM, Huson KM, Robinson MW. The cellular and molecular origins of extracellular vesicles released by the helminth pathogen, Fasciola hepatica. Int J Parasitol. 2020;50:671–83. Available from https://linkinghub.elsevier.com/ retrieve/pii/S0020751920301478. 201. Murao A, Brenner M, Aziz M, Wang P. Exosomes in sepsis. Front Immunol. 2020;11:e02140. Available from https://www.frontiersin.org/article/10.3389/fimmu.2020.02140/full. 202. Meldolesi J. Exosomes and ectosomes in intercellular communication. Curr Biol. 2018;28:435–44. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0960982218300927. 203. Kalluri R, LeBleu VS. The biology, function, and biomedical applications of exosomes. Science. 2020;367:6977. Available from https://www.sciencemag.org/lookup/doi/10.1126/ science.aau6977.
186
3 Virulence of Pathogens and the Counteracting Responses of the Host
204. Murao A, Aziz M, Wang H, Brenner M, Wang P. Release mechanisms of major DAMPs. Apoptosis. 2021;26:152–62. Available from http://link.springer.com/10.1007/ s10495-021-01663-3. 205. Qiu P, Zhou J, Zhang J, Dong Y, Liu Y. Exosome: the regulator of the immune system in sepsis. Front Pharmacol. 2021;12:671164. Available from https://www.frontiersin.org/ articles/10.3389/fphar.2021.671164/full. 206. Fonseka P, Marzan AL, Mathivanan S. Introduction to the community of extracellular vesicles. Subcell Biochem. 2021;2021:3–18. Available from http://link.springer. com/10.1007/978-3-030-67171-6_1. 207. Cui J. Autophagy regulation of innate immunity. Singapore: Springer; 2019. p. 55–78. Available from http://link.springer.com/10.1007/978-981-15-0606-2. 208. Lei Y, Li H, Lu K. Autophagy regulation of bacterial pathogen invasion. Singapore: Springer; 2019. p. 43–54. Available from http://link.springer.com/10.1007/978-981-15-0606-2_4. 209. Mao J, Lin E, He L, Yu J, Tan P, Zhou Y. Autophagy and viral infection. Singapore: Springer; 2019. p. 55–78. Available from http://link.springer.com/10.1007/978-981-15-0606-2_5. 210. Sharma V, Verma S, Seranova E, Sarkar S, Kumar D. Selective autophagy and xenophagy in infection and disease. Front Cell Dev Biol. 2018;6:e00147. Available from https://www. frontiersin.org/article/10.3389/fcell.2018.00147/full. 211. Hu W, Chan H, Lu L, Wong KT, Wong SH, Li MX, et al. Autophagy in intracellular bacterial infection. Semin Cell Dev Biol. 2020;101:41–50. Available from https://linkinghub.elsevier. com/retrieve/pii/S1084952119300540. 212. Choi Y, Bowman JW, Jung JU. Autophagy during viral infection — a double-edged sword. Nat Rev Microbiol. 2018;16:341–54. Available from http://www.nature.com/articles/ s41579-018-0003-6. 213. Zhu Y, Deng J, Nan M-L, Zhang J, Okekunle A, Li J-Y, et al. The interplay between pattern recognition receptors and autophagy in inflammation. Adv Exp Med Biol. 2019;2019:79–108. Available from http://link.springer.com/10.1007/978-981-15-0606-2_6. 214. Suzuki T, Muramatsu A, Saito R, Iso T, Shibata T, Kuwata K, et al. Molecular mechanism of cellular oxidative stress sensing by Keap1. Cell Rep. 2019;28:746–58. Available from https:// linkinghub.elsevier.com/retrieve/pii/S2211124719308204. 215. Deramaudt TB, Dill C, Bonay M. Regulation of oxidative stress by Nrf2 in the pathophysiology of infectious diseases. Méd Mal Infect. 2013;43:100–7. Available from https://linkinghub.elsevier.com/retrieve/pii/S0399077X13000504. 216. Lee C. Therapeutic modulation of virus-induced oxidative stress via the Nrf2-dependent antioxidative pathway. Oxidative Med Cell Longev. 2018;2018:1–26. Available from https:// www.hindawi.com/journals/omcl/2018/6208067/. 217. Bender H. Effect of hepatitis viruses on the Nrf2/Keap1-signaling pathway and its impact on viral replication and pathogenesis. Int J Mol Sci. 2019;20:4659. Available from https://www. mdpi.com/1422-0067/20/18/4659. 218. Mao H, Zhao Y, Li H, Lei L. Ferroptosis as an emerging target in inflammatory diseases. Prog Biophys Mol Biol. 2020;155:20–8. Available from https://linkinghub.elsevier.com/retrieve/ pii/S0079610720300250. 219. Pincus D. Regulation of Hsf1 and the heat shock response. Adv Exp Med Biol. 2020;2020:41–50. Available from http://link.springer.com/10.1007/978-3-030-40204-4_3. 220. Land W. Allograft injury mediated by reactive oxygen species: from conserved proteins of Drosophila to acute and chronic rejection of human transplants. Part II: role of reactive oxygen species in the induction of the heat shock response as a regulator of innate. Transplant Rev. 2003;17:31–44. Available from http://linkinghub.elsevier.com/retrieve/pii/ S0955470X0380006X. 221. Bolhassani A, Agi E. Heat shock proteins in infection. Clin Chim Acta. 2019;498:90–100. Available from https://linkinghub.elsevier.com/retrieve/pii/S0009898119320030. 222. Hasday JD, Thompson C, Singh IS. Fever, immunity, and molecular adaptations. Compr Physiol. 2014;2014:109–48. Available from http://www.ncbi.nlm.nih.gov/pubmed/24692136.
References
187
223. Shekhawat SD, Jain RK, Gaherwar HM, Purohit HJ, Taori GM, Daginawala HF, et al. Heat shock proteins: possible biomarkers in pulmonary and extrapulmonary tuberculosis. Hum Immunol. 2014;75:151–8. Available from http://www.ncbi.nlm.nih.gov/pubmed/24269695. 224. Pierzchalski P, Jastrzebska M, Link-Lenczowski P, Leja-Szpak A, Bonior J, Jaworek J, et al. The dynamics of heat shock system activation in Monomac-6 cells upon Helicobacter pylori infection. J Physiol Pharmacol. 2014;65:791–800. Available from http://www.ncbi.nlm.nih. gov/pubmed/25554983. 225. Klingspor S, Bondzio A, Martens H, Aschenbach JR, Bratz K, Tedin K, et al. Enterococcus faecium NCIMB 10415 modulates epithelial integrity, heat shock protein, and proinflammatory cytokine response in intestinal cells. Mediat Inflamm. 2015;2015:1–11. Available from http://www.ncbi.nlm.nih.gov/pubmed/25948884. 226. Hu J, Flores D, Toft D, Wang X, Nguyen D. Requirement of heat shock protein 90 for human hepatitis B virus reverse transcriptase function. J Virol. 2004;78:13122–31. Available from http://jvi.asm.org/cgi/doi/10.1128/JVI.78.23.13122-13131.2004. 227. Wang Y-P, Liu F, He H-W, Han Y-X, Peng Z-G, Li B-W, et al. Heat stress cognate 70 host protein as a potential drug target against drug resistance in hepatitis B virus. Antimicrob Agents Chemother. 2010;54:2070–7. Available from http://aac.asm.org/cgi/doi/10.1128/ AAC.01764-09. 228. Zhou Y-B, Wang Y-F, Zhang Y, Zheng L-Y, Yang X-A, Wang N, et al. In vitro activity of cepharanthine hydrochloride against clinical wild-type and lamivudine-resistant hepatitis B virus isolates. Eur J Pharmacol. 2012;683:10–5. Available from http://linkinghub.elsevier. com/retrieve/pii/S0014299912001665. 229. Bhattarai KR, Riaz TA, Kim H-R, Chae H-J. The aftermath of the interplay between the endoplasmic reticulum stress response and redox signaling. Exp Mol Med. 2021;53:151–67. Available from http://www.nature.com/articles/s12276-021-00560-8. 230. Lee J, Song C-H. Effect of reactive oxygen species on the endoplasmic reticulum and mitochondria during intracellular pathogen infection of mammalian cells. Antioxidants. 2021;10:872. Available from https://www.mdpi.com/2076-3921/10/6/872. 231. Zhang Z, Zhang L, Zhou L, Lei Y, Zhang Y, Huang C. Redox signaling and unfolded protein response coordinate cell fate decisions under ER stress. Redox Biol. 2019;25:101047. Available from https://linkinghub.elsevier.com/retrieve/pii/S2213231718308954. 232. McGrath EP, Centonze FG, Chevet E, Avril T, Lafont E. Death sentence: the tale of a fallen endoplasmic reticulum. Biochim Biophys Acta, Mol Cell Res. 2021;1868:119001. Available from https://linkinghub.elsevier.com/retrieve/pii/S0167488921000550. 233. Lam M, Marsters SA, Ashkenazi A, Walter P. Misfolded proteins bind and activate death receptor 5 to trigger apoptosis during unresolved endoplasmic reticulum stress. elife. 2020;9:52291. Available from https://elifesciences.org/articles/52291. 234. Saveljeva S, Mc Laughlin SL, Vandenabeele P, Samali A, Bertrand MJM. Endoplasmic reticulum stress induces ligand-independent TNFR1-mediated necroptosis in L929 cells. Cell Death Dis. 2015;6:e1587. Available from http://www.nature.com/articles/cddis2014548. 235. Kishino H, Maeda J, Hidai N, et al. Caspase-8 regulates endoplasmic reticulum stress- induced necroptosis independent of the apoptosis pathway in auditory cells. Int J Mol Sci. 2019;20:5896. Available from https://www.mdpi.com/1422-0067/20/23/5896. 236. Menu P, Mayor A, Zhou R, Tardivel A, Ichijo H, Mori K, et al. ER stress activates the NLRP3 inflammasome via an UPR-independent pathway. Cell Death Dis. 2012;3:e261. Available from http://www.nature.com/articles/cddis2011132. 237. Lerner AG, Upton J-P, Praveen PVK, Ghosh R, Nakagawa Y, Igbaria A, et al. IRE1α induces thioredoxin-interacting protein to activate the NLRP3 inflammasome and promote programmed cell death under irremediable ER stress. Cell Metab. 2012;16:250–64. Available from https://linkinghub.elsevier.com/retrieve/pii/S1550413112002847. 238. Park E-J, Park Y-J, Lee SJ, Lee K, Yoon C. Whole cigarette smoke condensates induce ferroptosis in human bronchial epithelial cells. Toxicol Lett. 2019;303:55–66. Available from https://linkinghub.elsevier.com/retrieve/pii/S0378427418317557.
188
3 Virulence of Pathogens and the Counteracting Responses of the Host
239. Celli J, Tsolis RM. Bacteria, the endoplasmic reticulum and the unfolded protein response: friends or foes? Nat Rev Microbiol. 2014;13:71–82. Available from http://www.nature.com/ doifinder/10.1038/nrmicro3393. 240. Choi J-A, Song C-H. Insights into the role of endoplasmic reticulum stress in infectious diseases. Front Immunol. 2020;10:e03147. Available from https://www.frontiersin.org/ article/10.3389/fimmu.2019.03147/full. 241. Li S, Kong L, Yu X. The expanding roles of endoplasmic reticulum stress in virus replication and pathogenesis. Crit Rev Microbiol. 2015;41:150–64. Available from http://www.tandfonline.com/doi/full/10.3109/1040841X.2013.813899. 242. Iurlaro R, Muñoz-Pinedo C. Cell death induced by endoplasmic reticulum stress. FEBS J. 2016;283:2640–52. Available from http://doi.wiley.com/10.1111/febs.13598. 243. Carletti T, Zakaria MK, Faoro V, Reale L, Kazungu Y, Licastro D, et al. Viral priming of cell intrinsic innate antiviral signaling by the unfolded protein response. Nat Commun. 2019;10:3889. Available from http://www.nature.com/articles/s41467-019-11663-2. 244. Fung T, Torres J, Liu D. The emerging roles of viroporins in ER stress response and autophagy induction during virus infection. Viruses. 2015;7:2834–57. Available from http://www. mdpi.com/1999-4915/7/6/2749. 245. Dash S, Chava S, Aydin Y, Chandra P, Ferraris P, Chen W, et al. Hepatitis C virus infection induces autophagy as a prosurvival mechanism to alleviate hepatic ER-stress response. Viruses. 2016;8:150. Available from http://www.ncbi.nlm.nih.gov/pubmed/27223299. 246. Jheng J-R, Ho J-Y, Horng J-T. ER stress, autophagy, and RNA viruses. Front Microbiol. 2014;5:388. Available from http://www.ncbi.nlm.nih.gov/pubmed/25140166. 247. Costa-Mattioli M, Walter P. The integrated stress response: from mechanism to disease. Science. 2020;2020:368. Available from https://www.science.org/doi/10.1126/science. aat5314. 248. Roos WP, Kaina B. DNA damage-induced cell death: from specific DNA lesions to the DNA damage response and apoptosis. Cancer Lett. 2013;332:237–48. Available from https://linkinghub.elsevier.com/retrieve/pii/S0304383512000328. 249. Wang JV. Cell death response to DNA damage. Yale J Biol Med. 2019;92:771–9. Available from https://pubmed.ncbi.nlm.nih.gov/31866794/. 250. Wang Y, Luo W, Wang Y. PARP-1 and its associated nucleases in DNA damage response. DNA Repair. 2019;81:102651. Available from https://linkinghub.elsevier.com/retrieve/pii/ S1568786419302046. 251. Shah GA, O’Shea CC. Viral and cellular genomes activate distinct DNA damage responses. Cell. 2015;162:987–1002. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0092867415009745. 252. Turnell AS, Grand RJ. DNA viruses and the cellular DNA-damage response. J Gen Virol. 2012;93:2076–97. Available from https://www.microbiologyresearch.org/content/journal/ jgv/10.1099/vir.0.044412-0. 253. Luftig MA. Viruses and the DNA damage response: activation and antagonism. Annu Rev Virol. 2014;1:605–25. Available from http://www.annualreviews.org/doi/10.1146/ annurev-virology-031413-085548. 254. Weitzman MD, Weitzman JB. What’s the damage? The impact of pathogens on pathways that maintain host genome integrity. Cell Host Microbe. 2014;15:283–94. Available from https:// linkinghub.elsevier.com/retrieve/pii/S1931312814000687. 255. Ryan E, Hollingworth R, Grand R. Activation of the DNA damage response by RNA viruses. Biomol Ther. 2016;6:2. Available from http://www.mdpi.com/2218-273X/6/1/2. 256. Chumduri C, Gurumurthy RK, Zietlow R, Meyer TF. Subversion of host genome integrity by bacterial pathogens. Nat Rev Mol Cell Biol. 2016;17:659–73. Available from http://www. nature.com/articles/nrm.2016.100. 257. Grasso F, Frisan T. Bacterial genotoxins: merging the DNA damage response into infection biology. Biomol Ther. 2015;5:1762–82. Available from http://www.mdpi. com/2218-273X/5/3/1762.
References
189
258. Teshima R. Investigation of DNA double-strand breaks induced in host cells following infection with genotoxic bacteria. Methods Mol Biol. 2020;2020:111–22. Available from http:// link.springer.com/10.1007/978-1-0716-0323-9_10. 259. Snyder AG, Oberst A. The antisocial network: cross talk between cell death programs in host defense. Annu Rev Immunol. 2021;39:77–101. Available from https://www.annualreviews. org/doi/10.1146/annurev-immunol-112019-072301. 260. Jorgensen I, Rayamajhi M, Miao EA. Programmed cell death as a defence against infection. Nat Rev Immunol. 2017;17:151–64. Available from http://www.ncbi.nlm.nih.gov/ pubmed/28138137. 261. Tang D, Kang R, Vanden BT, Vandenabeele P, Kroemer G. The molecular machinery of regulated cell death. Cell Res. 2019;29:347–64. Available from http://www.nature.com/articles/ s41422-019-0164-5. 262. Imre G. The involvement of regulated cell death forms in modulating the bacterial and viral pathogenesis. Int Rev Cell Mol Biol. 2020;353:211–53. Available from https://linkinghub. elsevier.com/retrieve/pii/S1937644819301273. 263. Bertheloot D, Latz E, Franklin BS. Necroptosis, pyroptosis and apoptosis: an intricate game of cell death. Cell Mol Immunol. 2021;18:1106–21. Available from http://www.nature.com/ articles/s41423-020-00630-3. 264. Galluzzi L, Vitale I, Aaronson SA, Abrams JM, Adam D, Agostinis P, et al. Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018. Cell Death Differ. 2018;25:486–541. Available from http://www.nature.com/articles/ s41418-017-0012-4. 265. Land WG, Agostinis P, Gasser S, Garg AD, Linkermann A. Transplantation and damage- associated molecular patterns (DAMPs). Am J Transplant. 2016;16:3338–61. Available from https://onlinelibrary.wiley.com/doi/10.1111/ajt.13963. 266. Sarhan M, Land WG, Tonnus W, Hugo CP, Linkermann A. Origin and consequences of necroinflammation. Physiol Rev. 2018;98:727–80. Available from http://www.physiology. org/doi/10.1152/physrev.00041.2016. 267. Nakano H, Murai S, Yamaguchi Y, Shirasaki Y, Nakabayashi O, Yamazaki S. Development of novel methods that monitor necroptosis and the release of DAMPs at the single cell resolution. Cell Stress. 2019;3:66–9. Available from http://www.cell-stress.com/ researcharticles/2019a-nakano-cell-stress/. 268. Baar MP, Brandt RMC, Putavet DA, Klein JDD, Derks KWJ, Bourgeois BRM, et al. Targeted apoptosis of senescent cells restores tissue homeostasis in response to chemotoxicity and aging. Cell. 2017;169:132–47. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0092867417302465. 269. Green DR. Cancer and apoptosis: who is built to last? Cancer Cell. 2017;31:2–4. Available from http://www.ncbi.nlm.nih.gov/pubmed/28073002. 270. Atkin-Smith GK, Duan M, Chen W, Poon IKH. The induction and consequences of Influenza A virus-induced cell death. Cell Death Dis. 2018;9:1002. Available from http://www.nature. com/articles/s41419-018-1035-6. 271. Obeng E. Apoptosis (programmed cell death) and its signals - a review. Braz J Biol. 2021;81:1133–43. Available from http://www.scielo.br/scielo.php?script=sci_arttext&pid =S1519-69842021000401133&tlng=en. 272. Nagata S. Apoptosis and clearance of apoptotic cells. Annu Rev Immunol. 2018;36:489–517. Available from http://www.ncbi.nlm.nih.gov/pubmed/29400998. 273. Poon IKH, Lucas CD, Rossi AG, Ravichandran KS. Apoptotic cell clearance: basic biology and therapeutic potential. Nat Rev Immunol. 2014;14:166–80. Available from http://www. nature.com/articles/nri3607. 274. Sachet M, Liang YY, Oehler R. The immune response to secondary necrotic cells. Apoptosis. 2017;22:1189–204. Available from http://link.springer.com/10.1007/s10495-017-1413-z. 275. Tabas I, Ron D. Integrating the mechanisms of apoptosis induced by endoplasmic reticulum stress. Nat Cell Biol. 2011;13:184–90. Available from http://www.nature.com/articles/ ncb0311-184.
190
3 Virulence of Pathogens and the Counteracting Responses of the Host
276. Krakauer T. Inflammasomes, autophagy, and cell death: the trinity of innate host defense against intracellular bacteria. Mediat Inflamm. 2019;2019:1–10. Available from https://www. hindawi.com/journals/mi/2019/2471215/. 277. Häcker G. Apoptosis in infection. Microbes Infect. 2018;20:552–9. Available from https:// linkinghub.elsevier.com/retrieve/pii/S1286457917301818. 278. Naderer T, Fulcher MC. Targeting apoptosis pathways in infections. J Leukoc Biol. 2018;103:275–85. Available from https://pubmed.ncbi.nlm.nih.gov/29372933/. 279. Kaczmarek A, Vandenabeele P, Krysko DV. Necroptosis: the release of damage-associated molecular patterns and its physiological relevance. Immunity. 2013;38:209–23. Available from http://www.ncbi.nlm.nih.gov/pubmed/23438821 280. Shlomovitz I, Erlich Z, Speir M, Zargarian S, Baram N, Engler M, et al. Necroptosis directly induces the release of full-length biologically active IL-33 in vitro and in an inflammatory disease model. FEBS J. 2019;286:507–22. Available from https://onlinelibrary.wiley.com/ doi/abs/10.1111/febs.14738. 281. Wajant H, Siegmund D. TNFR1 and TNFR2 in the control of the life and death balance of macrophages. Front Cell Dev Biol. 2019;7:91. Available from https://www.frontiersin.org/ article/10.3389/fcell.2019.00091/full. 282. Robinson N, McComb S, Mulligan R, Dudani R, Krishnan L, Sad S. Type I interferon induces necroptosis in macrophages during infection with Salmonella enterica serovar Typhimurium. Nat Immunol. 2012;13:954–62. Available from http://www.nature.com/articles/ni.2397. 283. Brault M, Olsen TM, Martinez J, Stetson DB, Oberst A. Intracellular nucleic acid sensing triggers necroptosis through synergistic type I IFN and TNF signaling. J Immunol. 2018;200:2748–56. Available from http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1701492. 284. Petrie EJ, Czabotar PE, Murphy JM. The structural basis of necroptotic cell death signaling. Trends Biochem Sci. 2019;44:53–63. Available from https://linkinghub.elsevier.com/ retrieve/pii/S0968000418302299. 285. Ke X, Lei L, Li H, Li H, Yan F. Manipulation of necroptosis by Porphyromonas gingivalis in periodontitis development. Mol Immunol. 2016;77:8–13. Available from http://www.ncbi. nlm.nih.gov/pubmed/27449906. 286. Ahn D, Prince A. Participation of necroptosis in the host response to acute bacterial pneumonia. J Innate Immun. 2017;9:262–70. Available from https://www.karger.com/Article/ FullText/455100. 287. González-Juarbe N, Bradley KM, Shenoy AT, Gilley RP, Reyes LF, Hinojosa CA, et al. Pore- forming toxin-mediated ion dysregulation leads to death receptor-independent necroptosis of lung epithelial cells during bacterial pneumonia. Cell Death Differ. 2017;24:917–28. Available from http://www.ncbi.nlm.nih.gov/pubmed/28387756. 288. Shrestha A, Mehdizadeh Gohari I, McClane BA. RIP1, RIP3, and MLKL contribute to cell death caused by clostridium perfringens enterotoxin. MBio. 2019;10:31848291. Available from http://www.ncbi.nlm.nih.gov/pubmed/31848291. 289. Parker D, Prince A. Immunoregulatory effects of necroptosis in bacterial infections. Cytokine. 2016;88:274–5. Available from http://www.ncbi.nlm.nih.gov/pubmed/27710879. 290. Faust H, Mangalmurti NS. Collateral damage: necroptosis in the development of lung injury. Am J Physiol Cell Mol Physiol. 2019;318:215–25. Available from http://www.ncbi.nlm.nih. gov/pubmed/31774305. 291. Minagawa S, Yoshida M, Araya J, Hara H, Imai H, Kuwano K. Regulated necrosis in pulmonary disease: a focus on necroptosis and ferroptosis. Am J Respir Cell Mol Biol. 2020. Available from http://www.ncbi.nlm.nih.gov/pubmed/32017592. 292. Xia X, Lei L, Wang S, Hu J, Zhang G. Necroptosis and its role in infectious diseases. Apoptosis. 2020;25:169–78. Available from http://link.springer.com/10.1007/s10495-019-01589-x. 293. Weng D, Marty-Roix R, Ganesan S, Proulx MK, Vladimer GI, Kaiser WJ, et al. Caspase-8 and RIP kinases regulate bacteria-induced innate immune responses and cell death. Proc Natl Acad Sci U S A. 2014;111:7391–6. Available from http://www.ncbi.nlm.nih.gov/ pubmed/24799678.
References
191
294. Kitur K, Wachtel S, Brown A, Wickersham M, Paulino F, Peñaloza HF, et al. Necroptosis promotes Staphylococcus aureus clearance by inhibiting excessive inflammatory signaling. Cell Rep. 2016;16:2219–30. Available from http://www.ncbi.nlm.nih.gov/pubmed/27524612. 295. Grootjans S, Vanden Berghe T, Vandenabeele P. Initiation and execution mechanisms of necroptosis: an overview. Cell Death Differ. 2017;24:1184–95. Available from http://www. nature.com/doifinder/10.1038/cdd.2017.65. 296. González-Juarbe N, Gilley RP, Hinojosa CA, Bradley KM, Kamei A, Gao G, et al. Pore- forming toxins induce macrophage necroptosis during acute bacterial pneumonia. PLoS Pathog. 2015;11:e1005337. Available from http://www.ncbi.nlm.nih.gov/ pubmed/26659062. 297. Gilley RP, González-Juarbe N, Shenoy AT, Reyes LF, Dube PH, Restrepo MI, et al. Infiltrated macrophages die of pneumolysin-mediated necroptosis following pneumococcal myocardial invasion. Infect Immun. 2016;84:1457–69. Available from http://www.ncbi.nlm.nih.gov/ pubmed/26930705. 298. He S, Wang L, Miao L, Wang T, Du F, Zhao L, et al. Receptor interacting protein kinase-3 determines cellular necrotic response to TNF-α. Cell. 2009;137:1100–11. Available from http://www.ncbi.nlm.nih.gov/pubmed/19524512. 299. Pajuelo D, Gonzalez-Juarbe N, Tak U, Sun J, Orihuela CJ, Niederweis M. NAD+ depletion triggers macrophage necroptosis, a cell death pathway exploited by Mycobacterium tuberculosis. Cell Rep. 2018;24:429–40. Available from http://www.ncbi.nlm.nih.gov/ pubmed/29996103. 300. Robinson N. Salmonella Typhimurium infection: type I interferons integrate cellular networks to disintegrate macrophages. Cell Stress. 2018;2:37–9. Available from http://www. cell-s tress.com/researcharticles/salmonella-t yphimurium-i nfection-t ype-i -i nterferons- integrate-cellular-networks-to-disintegrate-macrophages/. 301. Yang D, Liang Y, Zhao S, Ding Y, Zhuang Q, Shi Q, et al. ZBP1 mediates interferon-induced necroptosis. Cell Mol Immunol. 2020;17:356–68. Available from https://www.nature.com/ articles/s41423-019-0237-x. 302. Cavaillon J-M. Exotoxins and endotoxins: Inducers of inflammatory cytokines. Toxicon. 2018;149:45–53. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0041010117303136. 303. Meng R, Gu L, Lu Y, Zhao K, Wu J, Wang H, et al. High mobility group box 1 enables bacterial lipids to trigger receptor-interacting protein kinase 3 (RIPK3)-mediated necroptosis and apoptosis in mice. J Biol Chem. 2019;294:8872–84. Available from http://www.jbc.org/ lookup/doi/10.1074/jbc.RA118.007040. 304. Jondle CN, Gupta K, Mishra BB, Sharma J. Klebsiella pneumoniae infection of murine neutrophils impairs their efferocytic clearance by modulating cell death machinery. PLoS Pathog. 2018;14:e1007338. Available from https://dx.plos.org/10.1371/journal.ppat.1007338. 305. Hu G-Q, Yang Y-J, Qin X-X, Qi S, Zhang J, Yu S-X, et al. Salmonella outer protein B suppresses colitis development via protecting cell from necroptosis. Front Cell Infect Microbiol. 2019;9:87. Available from https://www.frontiersin.org/article/10.3389/ fcimb.2019.00087/full. 306. Upton JW, Shubina M, Balachandran S. RIPK3-driven cell death during virus infections. Immunol Rev. 2017;277:90–101. Available from http://doi.wiley.com/10.1111/imr.12539. 307. Nailwal H, Chan FK-M. Necroptosis in anti-viral inflammation. Cell Death Differ. 2019;26:4–13. Available from http://www.nature.com/articles/s41418-018-0172-x. 308. Frank D, Vince JE. Pyroptosis versus necroptosis: similarities, differences, and crosstalk. Cell Death Differ. 2019;26:99–114. Available from http://www.nature.com/articles/ s41418-018-0212-6. 309. Gaba A, Xu F, Lu Y, Park H-S, Liu G, Zhou Y. The NS1 protein of influenza A virus participates in necroptosis by interacting with MLKL and increasing its oligomerization and membrane translocation. J Virol. 2019;93:18. Available from http://jvi.asm.org/lookup/ doi/10.1128/JVI.01835-18.
192
3 Virulence of Pathogens and the Counteracting Responses of the Host
310. Upton JW, Kaiser WJ, Mocarski ES. DAI/ZBP1/DLM-1 complexes with RIP3 to mediate virus-induced programmed necrosis that is targeted by murine cytomegalovirus vIRA. Cell Host Microbe. 2012;11:290–7. Available from http://www.ncbi.nlm.nih.gov/ pubmed/22423968. 311. Maelfait J, Liverpool L, Bridgeman A, Ragan KB, Upton JW, Rehwinkel J. Sensing of viral and endogenous RNA by ZBP1/DAI induces necroptosis. EMBO J. 2017;36:2529–43. Available from https://onlinelibrary.wiley.com/doi/10.15252/embj.201796476. 312. Sridharan H, Ragan KB, Guo H, Gilley RP, Landsteiner VJ, Kaiser WJ, et al. Murine cytomegalovirus IE3-dependent transcription is required for DAI/ZBP1-mediated necroptosis. EMBO Rep. 2017;18:1429–41. Available from http://www.ncbi.nlm.nih.gov/pubmed/28607035. 313. He S, Han J. Manipulation of host cell death pathways by herpes simplex virus. Curr Top Microbiol Immunol. 2020. Available from http://www.ncbi.nlm.nih.gov/pubmed/32060646. 314. Paim AC, Badley AD, Cummins NW. Mechanisms of human immunodeficiency virus- associated lymphocyte regulated cell death. AIDS Res Hum Retrovir. 2020;36:101–15. Available from http://www.ncbi.nlm.nih.gov/pubmed/31659912. 315. Pan T, Wu S, He X, Luo H, Zhang Y, Fan M, et al. Necroptosis takes place in human immunodeficiency virus type-1 (HIV-1)-infected CD4+ T lymphocytes. PLoS One. 2014;9:e93944. Available from http://www.ncbi.nlm.nih.gov/pubmed/24714696. 316. Harker JA, Snelgrove RJ. A not-so-good way to die? Respiratory syncytial virus-induced necroptotic cell death promotes inflammation and type 2–mediated pathology. Am J Respir Crit Care Med. 2020;201:1321–3. Available from https://www.atsjournals.org/doi/10.1164/ rccm.202003-0533ED. 317. Orzalli MH, Kagan JC. Apoptosis and necroptosis as host defense strategies to prevent viral infection. Trends Cell Biol. 2017;27:800–9. Available from https://linkinghub.elsevier.com/ retrieve/pii/S0962892417300867. 318. Downey J, Pernet E, Coulombe F, Divangahi M. Dissecting host cell death programs in the pathogenesis of influenza. Microbes Infect. 2018;20:560–9. Available from http://www.ncbi. nlm.nih.gov/pubmed/29679740. 319. Balachandran S, Rall GF. Benefits and perils of necroptosis in influenza virus infection. J Virol. 2020;94:19. Available from http://jvi.asm.org/lookup/doi/10.1128/JVI.01101-19. 320. Thapa RJ, Nogusa S, Balachandran S. Analysis of cytokine- and influenza A virus-driven RIPK3 necrosome formation. Methods Mol Biol. 2018;2018:93–9. Available from http:// www.ncbi.nlm.nih.gov/pubmed/30136233. 321. Lee ACY, Zhang AJX, Chu H, Li C, Zhu H, Mak WWN, et al. H7N9 influenza A virus activation of necroptosis in human monocytes links innate and adaptive immune responses. Cell Death Dis. 2019;10:442. Available from http://www.nature.com/articles/s41419-019-1684-0. 322. Thomas PG, Shubina M, Balachandran S. ZBP1/DAI-dependent cell death pathways in influenza A virus immunity and pathogenesis. Curr Top Microbiol Immunol. 2019. Available from https://link.springer.com/10.1007/82_2019_190. 323. Zhang T, Yin C, Boyd DF, Quarato G, Ingram JP, Shubina M, et al. Influenza virus Z-RNAs induce ZBP1-mediated necroptosis. Cell. 2020;180:1115–29. Available from https://linkinghub.elsevier.com/retrieve/pii/S0092867420302270. 324. Maelfait J, Liverpool L, Rehwinkel J. Nucleic acid sensors and programmed cell death. J Mol Biol. 2020;2020:552–68. Available from http://www.ncbi.nlm.nih.gov/pubmed/31786265. 325. Wang Y, Hao Q, Florence JM, Jung B-G, Kurdowska AK, Samten B, et al. Influenza virus infection induces ZBP1 expression and necroptosis in mouse lungs. Front Cell Infect Microbiol. 2019;9:286. Available from http://www.ncbi.nlm.nih.gov/pubmed/31440477. 326. Ingram JP, Thapa RJ, Fisher A, Tummers B, Zhang T, Yin C, et al. ZBP1/DAI drives RIPK3- mediated cell death induced by IFNs in the absence of RIPK1. J Immunol. 2019;203:1348–55. Available from http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.1900216. 327. Kesavardhana S, Kuriakose T, Guy CS, Samir P, Malireddi RKS, Mishra A, et al. ZBP1/ DAI ubiquitination and sensing of influenza vRNPs activate programmed cell death. J Exp Med. 2017;214:2217–29. Available from https://rupress.org/jem/article/214/8/2217/42511/ ZBP1DAI-ubiquitination-and-sensing-of-influenza.
References
193
328. Nogusa S, Thapa RJ, Dillon CP, Liedmann S, Oguin TH, Ingram JP, et al. RIPK3 activates parallel pathways of MLKL-driven necroptosis and FADD-mediated apoptosis to protect against influenza A virus. Cell Host Microbe. 2016;20:13–24. Available from http://www. ncbi.nlm.nih.gov/pubmed/27321907. 329. Thapa RJ, Ingram JP, Ragan KB, Nogusa S, Boyd DF, Benitez AA, et al. DAI senses influenza A virus genomic RNA and activates RIPK3-dependent cell death. Cell Host Microbe. 2016;20:674–81. Available from http://linkinghub.elsevier.com/retrieve/pii/ S1931312816303924. 330. Kuriakose T, Man SM, Subbarao Malireddi RK, Karki R, Kesavardhana S, Place DE, et al. ZBP1/DAI is an innate sensor of influenza virus triggering the NLRP3 inflammasome and programmed cell death pathways. Sci Immunol. 2016;1:2045. Available from https://immunology.sciencemag.org/lookup/doi/10.1126/sciimmunol.aag2045. 331. Placido D, Brown BA, Lowenhaupt K, Rich A, Athanasiadis A. A left-handed RNA double helix bound by the Zα domain of the RNA-editing enzyme ADAR1. Structure. 2007;15:395–404. Available from https://linkinghub.elsevier.com/retrieve/pii/S0969212607001074. 332. Herbert A, Karapetyan S, Poptsova M, Vasquez KM, Vicens Q, Vögeli B. Special issue: A, B and Z: The structure, function and genetics of Z-DNA and Z-RNA. Int J Mol Sci. 2021;22:7686. Available from https://www.mdpi.com/1422-0067/22/14/7686. 333. Basavaraju S, Mishra S, Jindal R, Kesavardhana S. Emerging role of ZBP1 in Z-RNA sensing, influenza virus-induced cell death, and pulmonary inflammation. MBio. 2022;13:22. Available from https://journals.asm.org/doi/10.1128/mbio.00401-22. 334. Murai S, Yamaguchi Y, Shirasaki Y, Yamagishi M, Shindo R, Hildebrand JM, et al. A FRET biosensor for necroptosis uncovers two different modes of the release of DAMPs. Nat Commun. 2018;9:4457. Available from http://www.ncbi.nlm.nih.gov/pubmed/30367066. 335. Santos LD, Antunes KH, Muraro SP, de Souza GF, da Silva AG, de Felipe JS, et al. TNF- mediated alveolar macrophage necroptosis drives disease pathogenesis during respiratory syncytial virus infection. Eur Respir J. 2021;57:2003764. Available from http://erj.ersjournals.com/lookup/doi/10.1183/13993003.03764-2020. 336. Meessen-Pinard M, Le Coupanec A, Desforges M, Talbot PJ. Pivotal role of receptor- interacting protein kinase 1 and mixed lineage kinase domain-like in neuronal cell death induced by the human neuroinvasive coronavirus OC43. J Virol. 2017;2017:91. Available from https://journals.asm.org/doi/10.1128/JVI.01513-16. 337. Yue Y, Nabar NR, Shi C-S, Kamenyeva O, Xiao X, Hwang I-Y, et al. SARS-coronavirus open reading frame-3a drives multimodal necrotic cell death. Cell Death Dis. 2018;9:904. Available from http://www.nature.com/articles/s41419-018-0917-y. 338. Karki R, Sharma BR, Tuladhar S, Williams EP, Zalduondo L, Samir P, et al. Synergism of TNF-α and IFN-γ triggers inflammatory cell death, tissue damage, and mortality in SARS- CoV-2 infection and cytokine shock syndromes. Cell. 2021;184:149–68. Available from https://linkinghub.elsevier.com/retrieve/pii/S0092867420315427. 339. Paolini A, Borella R, De Biasi S, Neroni A, Mattioli M, Lo Tartaro D, et al. Cell death in coronavirus infections: uncovering its role during COVID-19. Cell. 2021;10:1585. Available from https://www.mdpi.com/2073-4409/10/7/1585. 340. Camilli G, Blagojevic M, Naglik JR, Richardson JP. Programmed cell death: central player in fungal infections. Trends Cell Biol. 2021;31:179–96. Available from https://linkinghub. elsevier.com/retrieve/pii/S0962892420302300. 341. Williams TJ, Gonzales-Huerta LE, Armstrong-James D. Fungal-induced programmed cell death. J Fungi. 2021;7:231. Available from https://www.mdpi.com/2309-608X/7/3/231. 342. Cao M, Wu Z, Lou Q, Lu W, Zhang J, Li Q, et al. Dectin-1-induced RIPK1 and RIPK3 activation protects host against Candida albicans infection. Cell Death Differ. 2019;26:2622–36. Available from http://www.nature.com/articles/s41418-019-0323-8. 343. Banoth B, Tuladhar S, Karki R, Sharma BR, Briard B, Kesavardhana S, et al. ZBP1 promotes fungi-induced inflammasome activation and pyroptosis, apoptosis, and necroptosis (PANoptosis). J Biol Chem. 2020;295:18276–83. Available from https://linkinghub.elsevier. com/retrieve/pii/S0021925817506985.
194
3 Virulence of Pathogens and the Counteracting Responses of the Host
344. Latz E, Xiao TS, Stutz A. Activation and regulation of the inflammasomes. Nat Rev Immunol. 2013;13:397–411. Available from http://www.nature.com/doifinder/10.1038/ nri3452. 345. Lamkanfi M, Dixit VM. Mechanisms and functions of inflammasomes. Cell. 2014;157:1013–22. Available from http://linkinghub.elsevier.com/retrieve/pii/ S0092867414004759. 346. Mathur A, Hayward JA, Man SM. Molecular mechanisms of inflammasome signaling. J Leukoc Biol. 2017;103:250. Available from http://www.ncbi.nlm.nih.gov/pubmed/28855232. 347. Place DE, Kanneganti T-D. Recent advances in inflammasome biology. Curr Opin Immunol. 2018;50:32–8. Available from http://www.ncbi.nlm.nih.gov/pubmed/29128729. 348. Hayward JA, Mathur A, Ngo C, Man SM. Cytosolic recognition of microbes and pathogens: inflammasomes in action. Microbiol Mol Biol Rev. 2018;82:1–40. Available from https:// mmbr.asm.org/content/82/4/e00015-18. 349. Yang Y, Wang H, Kouadir M, Song H, Shi F. Recent advances in the mechanisms of NLRP3 inflammasome activation and its inhibitors. Cell Death Dis. 2019;10:128. Available from http://www.nature.com/articles/s41419-019-1413-8. 350. Christgen S, Place DE, Kanneganti T-D. Toward targeting inflammasomes: insights into their regulation and activation. Cell Res. 2020;30:315–27. Available from http://www.nature.com/ articles/s41422-020-0295-8. 351. Wang B, Bhattacharya M, Roy S, Tian Y, Yin Q. Immunobiology and structural biology of AIM2 inflammasome. Mol Asp Med. 2020;2020:100869. Available from https://linkinghub. elsevier.com/retrieve/pii/S0098299720300510. 352. Lacey CA, Miao EA. Programmed cell death in the evolutionary race against bacterial virulence factors. Cold Spring Harb Perspect Biol. 2020;12:a036459. Available from http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect.a036459. 353. Greaney AJ, Leppla SH, Moayeri M. Bacterial exotoxins and the inflammasome. Front Immunol. 2015;2015:570. Available from http://www.ncbi.nlm.nih.gov/pubmed/26617605. 354. Liang F, Zhang F, Zhang L, Wei W. The advances in pyroptosis initiated by inflammasome in inflammatory and immune diseases. Inflamm Res. 2020;69:159–66. Available from http:// www.ncbi.nlm.nih.gov/pubmed/31932850. 355. Xue Y, Enosi Tuipulotu D, Tan WH, Kay C, Man SM. Emerging activators and regulators of inflammasomes and pyroptosis. Trends Immunol. 2019;40:1035–52. Available from https:// linkinghub.elsevier.com/retrieve/pii/S1471490619301930. 356. Chen J, Chen ZJ. PtdIns4P on dispersed trans-Golgi network mediates NLRP3 inflammasome activation. Nature. 2018;564:71–6. Available from http://www.nature.com/articles/ s41586-018-0761-3. 357. Land WG. Role of DAMPs in respiratory virus-induced acute respiratory distress syndrome— with a preliminary reference to SARS-CoV-2 pneumonia. Genes Immun. 2021;2021:141–60. Available from http://www.nature.com/articles/s41435-021-00140-w. 358. Triantafilou K, Kar S, van Kuppeveld FJM, Triantafilou M. Rhinovirus-induced calcium flux triggers NLRP3 and NLRC5 activation in bronchial cells. Am J Respir Cell Mol Biol. 2013;49:923–34. Available from https://www.atsjournals.org/doi/10.1165/ rcmb.2013-0032OC. 359. Chen I-Y, Moriyama M, Chang M-F, Ichinohe T. Severe acute respiratory syndrome coronavirus viroporin 3a activates the NLRP3 inflammasome. Front Microbiol. 2019;10:50. Available from https://www.frontiersin.org/article/10.3389/fmicb.2019.00050/full. 360. Freundt EC, Yu L, Goldsmith CS, Welsh S, Cheng A, Yount B, et al. The open reading frame 3a protein of severe acute respiratory syndrome-associated coronavirus promotes membrane rearrangement and cell death. J Virol. 2010;84:1097–109. Available from https://journals. asm.org/doi/10.1128/JVI.01662-09. 361. Shi C-S, Nabar NR, Huang N-N, Kehrl JH. SARS-Coronavirus Open Reading Frame-8b triggers intracellular stress pathways and activates NLRP3 inflammasomes. Cell Death Dis. 2019;5:101. Available from http://www.ncbi.nlm.nih.gov/pubmed/31231549.
References
195
362. He W, Wan H, Hu L, Chen P, Wang X, Huang Z, et al. Gasdermin D is an executor of pyroptosis and required for interleukin-1β secretion. Cell Res. 2015;25:1285–98. Available from http://www.ncbi.nlm.nih.gov/pubmed/26611636. 363. Shi J, Zhao Y, Wang K, Shi X, Wang Y, Huang H, et al. Cleavage of GSDMD by inflammatory caspases determines pyroptotic cell death. Nature. 2015;526:660–5. Available from http:// www.ncbi.nlm.nih.gov/pubmed/26375003. 364. Vince JE, Silke J. The intersection of cell death and inflammasome activation. Cell Mol Life Sci. 2016;73:2349–67. Available from http://www.ncbi.nlm.nih.gov/ pubmed/27066895. 365. Man SM, Kanneganti T-D. Gasdermin D: the long-awaited executioner of pyroptosis. Cell Res. 2015;25:1183–4. Available from http://www.ncbi.nlm.nih.gov/pubmed/26482951. 366. Shi J, Gao W, Shao F. Pyroptosis: gasdermin-mediated programmed necrotic cell death. Trends Biochem Sci. 2017;42:245–54. Available from https://linkinghub.elsevier.com/ retrieve/pii/S0968000416301827. 367. Sborgi L, Rühl S, Mulvihill E, Pipercevic J, Heilig R, Stahlberg H, et al. GSDMD membrane pore formation constitutes the mechanism of pyroptotic cell death. EMBO J. 2016;35:1766–78. Available from http://emboj.embopress.org/lookup/doi/10.15252/embj.201694696. 368. Qiu S, Liu J, Xing F. ‘Hints’ in the killer protein gasdermin D: unveiling the secrets of gasdermins driving cell death. Cell Death Differ. 2017;24:588–96. Available from http://www. ncbi.nlm.nih.gov/pubmed/28362726. 369. Volchuk A, Ye A, Chi L, Steinberg BE, Goldenberg NM. Indirect regulation of HMGB1 release by gasdermin D. Nat Commun. 2020;11:4561. Available from http://www.nature. com/articles/s41467-020-18443-3. 370. Duncan JA, Canna SW. The NLRC4 inflammasome. Immunol Rev. 2018;281:115–23. Available from https://onlinelibrary.wiley.com/doi/10.1111/imr.12607. 371. Kuriakose T, Kanneganti T-D. ZBP1: innate sensor regulating cell death and inflammation. Trends Immunol. 2018;39:123–34. Available from https://linkinghub.elsevier.com/retrieve/ pii/S1471490617302120. 372. Praefcke GJK. Regulation of innate immune functions by guanylate-binding proteins. Int J Med Microbiol. 2018;308:237–45. Available from https://linkinghub.elsevier.com/retrieve/ pii/S1438422117304253. 373. Tretina K, Park E-S, Maminska A, MacMicking JD. Interferon-induced guanylate- binding proteins: guardians of host defense in health and disease. J Exp Med. 2019;216:482–500. Available from https://rupress.org/jem/article/216/3/482/120360/ Interferoninduced-guanylatebinding-proteins. 374. Meunier E, Wallet P, Dreier RF, Costanzo S, Anton L, Rühl S, et al. Guanylate-binding proteins promote activation of the AIM2 inflammasome during infection with Francisella novicida. Nat Immunol. 2015;16:476–84. Available from http://www.nature.com/articles/ni.3119. 375. Man SM, Karki R, Sasai M, Place DE, Kesavardhana S, Temirov J, et al. IRGB10 liberates bacterial ligands for sensing by the AIM2 and caspase-11-NLRP3 inflammasomes. Cell. 2016;167:382–96. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0092867416312454. 376. Ta A, Vanaja SK. Inflammasome activation and evasion by bacterial pathogens. Curr Opin Immunol. 2021;68:125–33. Available from https://linkinghub.elsevier.com/retrieve/pii/ S0952791520301321. 377. Wang F, Gómez-Sintes R, Boya P. Lysosomal membrane permeabilization and cell death. Traffic. 2018;2018:918–31. Available from http://www.ncbi.nlm.nih.gov/pubmed/30125440. 378. Chen KW, Boucher D, Broz P. Divide to conquer: NLRP3 is activated on dispersed trans- Golgi network. Cell Res. 2019;29:181–2. Available from http://www.nature.com/articles/ s41422-018-0138-z. 379. Samir P, Kesavardhana S, Patmore DM, Gingras S, Malireddi RKS, Karki R, et al. DDX3X acts as a live-or-die checkpoint in stressed cells by regulating NLRP3 inflammasome. Nature. 2019;573:590–4. Available from http://www.nature.com/articles/s41586-019-1551-2.
196
3 Virulence of Pathogens and the Counteracting Responses of the Host
380. He Y, Zeng MY, Yang D, Motro B, Núñez G. NEK7 is an essential mediator of NLRP3 activation downstream of potassium efflux. Nature. 2016;530:354–7. Available from http:// www.nature.com/articles/nature16959. 381. Brito C, Cabanes D, Sarmento Mesquita F, Sousa S. Mechanisms protecting host cells against bacterial pore-forming toxins. Cell Mol Life Sci. 2019;76:1319–39. Available from http:// link.springer.com/10.1007/s00018-018-2992-8. 382. Gurcel L, Abrami L, Girardin S, Tschopp J, van der Goot FG. Caspase-1 activation of lipid metabolic pathways in response to bacterial pore-forming toxins promotes cell survival. Cell. 2006;126:1135–45. Available from http://www.ncbi.nlm.nih.gov/pubmed/16990137. 383. Pétrilli V, Papin S, Dostert C, Mayor A, Martinon F, Tschopp J. Activation of the NALP3 inflammasome is triggered by low intracellular potassium concentration. Cell Death Differ. 2007;14:1583–9. Available from http://www.ncbi.nlm.nih.gov/pubmed/17599094. 384. Muñoz-Planillo R, Kuffa P, Martínez-Colón G, Smith BL, Rajendiran TM, Núñez G. K+ efflux is the common trigger of NLRP3 inflammasome activation by bacterial toxins and particulate matter. Immunity. 2013;38:1142–53. Available from http://www.ncbi.nlm.nih.gov/ pubmed/23809161. 385. Mathur A, Feng S, Hayward JA, Ngo C, Fox D, Atmosukarto II, et al. A multicomponent toxin from Bacillus cereus incites inflammation and shapes host outcome via the NLRP3 inflammasome. Nat Microbiol. 2019;4:362–74. Available from http://www.nature.com/ articles/s41564-018-0318-0. 386. Craven RR, Gao X, Allen IC, Gris D, Wardenburg JB, McElvania-TeKippe E, et al. Staphylococcus aureus α-hemolysin activates the NLRP3-inflammasome in human and mouse monocytic cells. PLoS One. 2009;4:e7446. Available from https://dx.plos.org/10.1371/journal.pone.0007446. 387. Kebaier C, Chamberland RR, Allen IC, Gao X, Broglie PM, Hall JD, et al. Staphylococcus aureus α-hemolysin mediates virulence in a murine model of severe pneumonia through activation of the NLRP3 inflammasome. J Infect Dis. 2012;205:807–17. Available from http:// www.ncbi.nlm.nih.gov/pubmed/22279123. 388. Zhang X, Cheng Y, Xiong Y, Ye C, Zheng H, Sun H, et al. Enterohemorrhagic Escherichia coli specific enterohemolysin induced IL-1β in human macrophages and EHEC-induced IL-1β required activation of NLRP3 inflammasome. PLoS One. 2012;7:e50288. Available from http://www.ncbi.nlm.nih.gov/pubmed/23209696. 389. Schaale K, Peters KM, Murthy AM, Fritzsche AK, Phan M-D, Totsika M, et al. Strain- and host species-specific inflammasome activation, IL-1β release, and cell death in macrophages infected with uropathogenic Escherichia coli. Mucosal Immunol. 2016;9:124–36. Available from http://www.ncbi.nlm.nih.gov/pubmed/25993444. 390. Toma C, Higa N, Koizumi Y, Nakasone N, Ogura Y, McCoy AJ, et al. Pathogenic vibrio activate NLRP3 inflammasome via cytotoxins and TLR/nucleotide-binding oligomerization domain-mediated NF-kappa B signaling. J Immunol. 2010;184:5287–97. Available from http://www.ncbi.nlm.nih.gov/pubmed/20348425. 391. Gupta R, Ghosh S, Monks B, DeOliveira RB, Tzeng T-C, Kalantari P, et al. RNA and β-hemolysin of group B Streptococcus induce interleukin-1β (IL-1β) by activating NLRP3 inflammasomes in mouse macrophages. J Biol Chem. 2014;289:13701–5. Available from http://www.ncbi.nlm.nih.gov/pubmed/24692555. 392. Eigenbrod T, Dalpke AH. Bacterial RNA: an underestimated stimulus for innate immune responses. J Immunol. 2015;195:411–8. Available from http://www.ncbi.nlm.nih.gov/ pubmed/26138638. 393. Vanaja SK, Rathinam VAK, Atianand MK, Kalantari P, Skehan B, Fitzgerald KA, et al. Bacterial RNA:DNA hybrids are activators of the NLRP3 inflammasome. Proc Natl Acad Sci U S A. 2014;111:7765–70. Available from http://www.ncbi.nlm.nih.gov/pubmed/24828532. 394. Sha W, Mitoma H, Hanabuchi S, Bao M, Weng L, Sugimoto N, et al. Human NLRP3 inflammasome senses multiple types of bacterial RNAs. Proc Natl Acad Sci U S A. 2014;111:16059–64. Available from http://www.ncbi.nlm.nih.gov/pubmed/25355909.
References
197
395. Fitzgerald KA, Kagan JC. Toll-like receptors and the control of immunity. Cell. 2020;180:1044–66. Available from https://linkinghub.elsevier.com/retrieve/pii/ S009286742030218X. 396. Lin K-M, Hu W, Troutman TD, Jennings M, Brewer T, Li X, et al. IRAK-1 bypasses priming and directly links TLRs to rapid NLRP3 inflammasome activation. Proc Natl Acad Sci. 2014;111:775–80. Available from http://www.pnas.org/cgi/doi/10.1073/pnas.1320294111. 397. Mortellaro A, Diamond C, Khameneh HJ, Brough D. Novel perspectives on non-canonical inflammasome activation. ImmunoTargets Ther. 2015;4:131. Available from http://www. dovepress.com/novel-p erspectives-o n-n on-c anonical-i nflammasome-a ctivation-p eer- reviewed-article-ITT. 398. Broz P. Recognition of intracellular bacteria by inflammasomes. Bact Intracell. 2019;2019:301–13. Available from http://www.asmscience.org/content/ book/10.1128/9781683670261.chap20. 399. Rathinam VAK, Zhao Y, Shao F. Innate immunity to intracellular LPS. Nat Immunol. 2019;2019:527–33. Available from http://www.ncbi.nlm.nih.gov/pubmed/30962589. 400. Jones JW, Kayagaki N, Broz P, Henry T, Newton K, O’Rourke K, et al. Absent in melanoma 2 is required for innate immune recognition of Francisella tularensis. Proc Natl Acad Sci. 2010;107:9771–6. Available from http://www.pnas.org/cgi/doi/10.1073/pnas.1003738107. 401. Kim S, Bauernfeind F, Ablasser A, Hartmann G, Fitzgerald KA, Latz E, et al. Listeria monocytogenes is sensed by the NLRP3 and AIM2 inflammasome. Eur J Immunol. 2010;40:1545–51. Available from http://doi.wiley.com/10.1002/eji.201040425. 402. Jin T, Perry A, Jiang J, Smith P, Curry JA, Unterholzner L, et al. Structures of the HIN domain: DNA complexes reveal ligand binding and activation mechanisms of the AIM2 inflammasome and IFI16 receptor. Immunity. 2012;36:561–71. Available from https://linkinghub.elsevier.com/retrieve/pii/S1074761312001240. 403. Zhao Y, Shao F. The NAIP-NLRC4 inflammasome in innate immune detection of bacterial flagellin and type III secretion apparatus. Immunol Rev. 2015;265:85–102. Available from http://www.ncbi.nlm.nih.gov/pubmed/25879286. 404. Reyes Ruiz VM, Ramirez J, Naseer N, Palacio NM, Siddarthan IJ, Yan BM, et al. Broad detection of bacterial type III secretion system and flagellin proteins by the human NAIP/ NLRC4 inflammasome. Proc Natl Acad Sci. 2017;114:13242–7. Available from http://www. pnas.org/lookup/doi/10.1073/pnas.1710433114. 405. Franchi L, Kamada N, Nakamura Y, Burberry A, Kuffa P, Suzuki S, et al. NLRC4-driven production of IL-1β discriminates between pathogenic and commensal bacteria and promotes host intestinal defense. Nat Immunol. 2012;13:449–56. Available from http://www.nature. com/articles/ni.2263. 406. Schnappauf O, Chae JJ, Kastner DL, Aksentijevich I. The pyrin inflammasome in health and disease. Front Immunol. 2019;10:1745. Available from http://www.ncbi.nlm.nih.gov/ pubmed/31456795. 407. Gao W, Yang J, Liu W, Wang Y, Shao F. Site-specific phosphorylation and microtubule dynamics control Pyrin inflammasome activation. Proc Natl Acad Sci U S A. 2016;113:4857–66. Available from http://www.ncbi.nlm.nih.gov/pubmed/27482109. 408. Julian L, Olson MF. Rho-associated coiled-coil containing kinases (ROCK). Small. 2014;5:e29846. Available from http://www.ncbi.nlm.nih.gov/pubmed/25010901. 409. Narumiya S, Thumkeo D. Rho signaling research: history, current status and future directions. FEBS Lett. 2018;592:1763–76. Available from http://doi.wiley. com/10.1002/1873-3468.13087. 410. Boyle ST, Kular J, Nobis M, Ruszkiewicz A, Timpson P, Samuel MS. Acute compressive stress activates RHO/ROCK-mediated cellular processes. Small. 2018;2018:1–17. Available from http://www.ncbi.nlm.nih.gov/pubmed/29455593. 411. Yuan Y, Li M, To CH, Lam TC, Wang P, Yu Y, et al. The role of the RhoA/ROCK signaling pathway in mechanical strain-induced scleral myofibroblast differentiation. Investig Opthalmol Vis Sci. 2018;59:3619. Available from http://www.ncbi.nlm.nih.gov/ pubmed/30029249.
198
3 Virulence of Pathogens and the Counteracting Responses of the Host
412. Bittner ZA, Schrader M, George SE, Amann R. Pyroptosis and its role in SARS-CoV-2 infection. Cell. 2022;11:1717. Available from https://www.mdpi.com/2073-4409/11/10/1717. 413. Zhao C, Zhao W. NLRP3 inflammasome—a key player in antiviral responses. Front Immunol. 2020;11:211. Available from https://www.frontiersin.org/articles/10.3389/ fimmu.2020.00211?utm_source=researcher_app&utm_medium=referral&utm_ campaign=RESR_MRKT_Researcher_inbound. 414. Shimada K, Crother TR, Karlin J, Dagvadorj J, Chiba N, Chen S, et al. Oxidized mitochondrial DNA activates the NLRP3 inflammasome during apoptosis. Immunity. 2012;36:401–14. Available from https://linkinghub.elsevier.com/retrieve/pii/S1074761312000441. 415. Sarvestani ST, McAuley JL. The role of the NLRP3 inflammasome in regulation of antiviral responses to influenza A virus infection. Antivir Res. 2017;2017:32–42. Available from http://www.ncbi.nlm.nih.gov/pubmed/29097227. 416. da Costa LS, Outlioua A, Anginot A, Akarid K, Arnoult D. RNA viruses promote activation of the NLRP3 inflammasome through cytopathogenic effect-induced potassium efflux. Cell Death Dis. 2019;10:346. Available from http://www.nature.com/articles/s41419-019-1579-0. 417. Shrivastava G, León-Juárez M, García-Cordero J, Meza-Sánchez DE, Cedillo-Barrón L. Inflammasomes and its importance in viral infections. Immunol Res. 2016;64:1101–17. Available from http://link.springer.com/10.1007/s12026-016-8873-z. 418. Ma Z, Ni G, Damania B. Innate sensing of DNA virus genomes. Annu Rev Virol. 2018;5:341–62. Available from https://www.annualreviews.org/doi/10.1146/ annurev-virology-092917-043244. 419. Sharma BR, Karki R, Kanneganti T. Role of AIM2 inflammasome in inflammatory diseases, cancer and infection. Eur J Immunol. 2019;49:1998–2011. Available from https://onlinelibrary.wiley.com/doi/abs/10.1002/eji.201848070. 420. Imre G. Cell death signalling in virus infection. Cell Signal. 2020;76:109772. Available from https://linkinghub.elsevier.com/retrieve/pii/S0898656820302497. 421. Lupfer C, Malik A, Kanneganti T-D. Inflammasome control of viral infection. Curr Opin Virol. 2015;12:38–46. Available from http://www.ncbi.nlm.nih.gov/pubmed/25771504. 422. Kuriakose T, Kanneganti T-D. Regulation and functions of NLRP3 inflammasome during influenza virus infection. Mol Immunol. 2017;86:56–64. Available from https://linkinghub. elsevier.com/retrieve/pii/S0161589017300299. 423. Kuriakose T, Kanneganti T-D. Pyroptosis in antiviral immunity. Curr Top Microbiol Immunol. 2019. Available from https://link.springer.com/10.1007/82_2019_189. 424. Rodrigues TS, de Sá KSG, Ishimoto AY, Becerra A, Oliveira S, Almeida L, et al. Inflammasomes are activated in response to SARS-CoV-2 infection and are associated with COVID-19 severity in patients. J Exp Med. 2021;218:211560. Available from https://rupress.org/jem/article/doi/10.1084/jem.20201707/211560/ Inflammasomes-are-activated-in-response-to. 425. Ferreira AC, Soares VC, de Azevedo-Quintanilha IG, da Dias SS, Fintelman-Rodrigues N, Sacramento CQ, et al. SARS-CoV-2 engages inflammasome and pyroptosis in human primary monocytes. Cell Death Dis. 2021;7:43. Available from http://www.nature.com/articles/ s41420-021-00428-w. 426. Malireddi RKS, Kesavardhana S, Kanneganti T-D. ZBP1 and TAK1: master regulators of NLRP3 inflammasome/pyroptosis, apoptosis, and necroptosis (PAN-optosis). Front Cell Infect Microbiol. 2019;9:406. Available from https://www.frontiersin.org/article/10.3389/ fcimb.2019.00406/full. 427. Zheng M, Kanneganti T. The regulation of the ZBP1-NLRP3 inflammasome and its implications in pyroptosis, apoptosis, and necroptosis (PANoptosis). Immunol Rev. 2020;297:26–38. Available from https://onlinelibrary.wiley.com/doi/abs/10.1111/imr.12909. 428. Nieto-Torres JL, DeDiego ML, Verdiá-Báguena C, Jimenez-Guardeño JM, Regla-Nava JA, Fernandez-Delgado R, et al. Severe acute respiratory syndrome coronavirus envelope protein ion channel activity promotes virus fitness and pathogenesis. PLoS Pathog. 2014;10:e1004077. Available from https://dx.plos.org/10.1371/journal.ppat.1004077.
References
199
429. Minakshi R, Padhan K. The YXXΦ motif within the severe acute respiratory syndrome coronavirus (SARS-CoV) 3a protein is crucial for its intracellular transport. Virol J. 2014;11:75. Available from https://virologyj.biomedcentral.com/articles/10.1186/1743-422X-11-75. 430. Lu W, Zheng B-J, Xu K, Schwarz W, Du L, Wong CKL, et al. Severe acute respiratory syndrome-associated coronavirus 3a protein forms an ion channel and modulates virus release. Proc Natl Acad Sci. 2006;103:12540–5. Available from https://pnas.org/doi/ full/10.1073/pnas.0605402103. 431. Kelley N, Jeltema D, Duan Y, He Y. The NLRP3 inflammasome: an overview of mechanisms of activation and regulation. Int J Mol Sci. 2019;20:3328. Available from https://www.mdpi. com/1422-0067/20/13/3328. 432. Machamer CE. The Golgi complex in stress and death. Front Neurosci. 2015;9:421. Available from http://journal.frontiersin.org/Article/10.3389/fnins.2015.00421/abstract. 433. Cao SS, Kaufman RJ. Endoplasmic reticulum stress and oxidative stress in cell fate decision and human disease. Antioxid Redox Signal. 2014;21:396–413. Available from http://www. ncbi.nlm.nih.gov/pubmed/24702237. 434. Bronner DN, Abuaita BH, Chen X, Fitzgerald KA, Nuñez G, He Y, et al. Endoplasmic reticulum stress activates the inflammasome via NLRP3- and caspase-2-driven mitochondrial damage. Immunity. 2015;43:451–62. Available from http://www.ncbi.nlm.nih.gov/ pubmed/26341399. 435. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497–506. Available from https:// linkinghub.elsevier.com/retrieve/pii/S0140673620301835. 436. Yang Y, Peng F, Wang R, Guan K, Jiang T, Xu G, et al. The deadly coronaviruses: the 2003 SARS pandemic and the 2020 novel coronavirus epidemic in China. J Autoimmun. 2020;2020:102434. Available from http://www.ncbi.nlm.nih.gov/pubmed/32143990. 437. Briard B, Place DE, Kanneganti T-D. DNA sensing in the innate immune response. Physiology. 2020;35:112–24. Available from https://www.physiology.org/doi/10.1152/ physiol.00022.2019. 438. Diner BA, Lum KK, Cristea IM. The emerging role of nuclear viral DNA sensors. J Biol Chem. 2015;290:26412–21. Available from http://www.jbc.org/lookup/doi/10.1074/jbc. R115.652289. 439. Zhang H, Luo J, Alcorn JF, Chen K, Fan S, Pilewski J, et al. AIM2 inflammasome is critical for influenza-induced lung injury and mortality. J Immunol. 2017;198:4383–93. Available from http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.1600714. 440. Moriyama M, Nagai M, Maruzuru Y, Koshiba T, Kawaguchi Y, Ichinohe T. Influenza virus- induced oxidized DNA activates inflammasomes. Science. 2020;23:101270. Available from https://linkinghub.elsevier.com/retrieve/pii/S2589004220304569. 441. van de Veerdonk FL, Joosten LAB, Netea MG. The interplay between inflammasome activation and antifungal host defense. Immunol Rev. 2015;265:172–80. Available from http://doi. wiley.com/10.1111/imr.12280. 442. Tavares AH, Bürgel PH, Bocca AL. Turning up the heat: inflammasome activation by fungal pathogens. PLoS Pathog. 2015;11:e1004948. Available from https://dx.plos.org/10.1371/ journal.ppat.1004948. 443. Li Z, Lu G, Meng G. Pathogenic fungal infection in the lung. Front Immunol. 2019;10:e01524. Available from https://www.frontiersin.org/article/10.3389/fimmu.2019.01524/full. 444. Karki R, Man SM, Malireddi RKS, Gurung P, Vogel P, Lamkanfi M, et al. Concerted activation of the AIM2 and NLRP3 inflammasomes orchestrates host protection against aspergillus infection. Cell Host Microbe. 2015;17:357–68. Available from https://linkinghub.elsevier. com/retrieve/pii/S1931312815000268. 445. Briard B, Karki R, Malireddi RKS, Bhattacharya A, Place DE, Mavuluri J, et al. Fungal ligands released by innate immune effectors promote inflammasome activation during Aspergillus fumigatus infection. Nat Microbiol. 2019;4:316–27. Available from http://www. nature.com/articles/s41564-018-0298-0.
200
3 Virulence of Pathogens and the Counteracting Responses of the Host
446. Vylkova S, Lorenz MC. Phagosomal neutralization by the fungal pathogen candida albicans induces macrophage pyroptosis. Infect Immun. 2017;85:16. Available from https://iai.asm. org/lookup/doi/10.1128/IAI.00832-16. 447. Shio MT, Eisenbarth SC, Savaria M, Vinet AF, Bellemare M-J, Harder KW, et al. Malarial hemozoin activates the NLRP3 inflammasome through Lyn and Syk kinases. PLoS Pathog. 2009;5:e1000559. Available from https://dx.plos.org/10.1371/journal.ppat.1000559. 448. Olivier M, Van Den Ham K, Shio MT, Kassa FA, Fougeray S. Malarial pigment hemozoin and the innate inflammatory response. Front Immunol. 2014;5:25. Available from http://journal.frontiersin.org/article/10.3389/fimmu.2014.00025/abstract. 449. Kalantari P, DeOliveira RB, Chan J, Corbett Y, Rathinam V, Stutz A, et al. Dual engagement of the NLRP3 and AIM2 inflammasomes by plasmodium-derived hemozoin and DNA during malaria. Cell Rep. 2014;6:196–210. Available from https://linkinghub.elsevier.com/retrieve/ pii/S2211124713007596. 450. Sanches RCO, Souza C, Oliveira SC. Schistosoma antigens as activators of inflammasome pathway: from an unexpected stimulus to an intriguing role. Microbes Infect. 2020;22:534–9. Available from https://linkinghub.elsevier.com/retrieve/pii/S1286457920301489. 451. de Carvalho RVH, Zamboni DS. Inflammasome activation in response to intracellular protozoan parasites. Trends Parasitol. 2020;36:459–72. Available from https://linkinghub.elsevier. com/retrieve/pii/S147149222030043X. 452. Celias DP, Motrán CC, Cervi L. Helminths turning on the NLRP3 inflammasome: pros and cons. Trends Parasitol. 2020;36:87–90. Available from https://linkinghub.elsevier.com/ retrieve/pii/S1471492219302715. 453. Christgen S, Zheng M, Kesavardhana S, Karki R, Malireddi RKS, Banoth B, et al. Identification of the PANoptosome: a molecular platform triggering pyroptosis, apoptosis, and necroptosis (PANoptosis). Front Cell Infect Microbiol. 2020;10:237. Available from https://www.frontiersin.org/article/10.3389/fcimb.2020.00237/full. 454. Place DE, Lee S, Kanneganti T-D. PANoptosis in microbial infection. Curr Opin Microbiol. 2021;59:42–9. Available from https://linkinghub.elsevier.com/retrieve/pii/ S136952742030093X. 455. Gullett JM, Tweedell RE, Kanneganti T-D. It’s All in the PAN: crosstalk, plasticity, redundancies, switches, and interconnectedness encompassed by PANoptosis underlying the totality of cell death-associated biological effects. Cell. 2022;11:1495. Available from https://www. mdpi.com/2073-4409/11/9/1495. 456. Malireddi RKS, Kesavardhana S, Karki R, Kancharana B, Burton AR, Kanneganti T-D. RIPK1 distinctly regulates yersinia-induced inflammatory cell death, PANoptosis. ImmunoHorizons. 2020;4:789–96. Available from http://www.immunohorizons.org/lookup/ doi/10.4049/immunohorizons.2000097. 457. Nguyen LN, Kanneganti T-D. PANoptosis in viral infection: the missing puzzle piece in the cell death field. J Mol Biol. 2022;434:167249. Available from https://linkinghub.elsevier. com/retrieve/pii/S0022283621004824. 458. Burgener SS, Schroder K. Neutrophil extracellular traps in host defense. Cold Spring Harb Perspect Biol. 2020;12:a037028. Available from http://cshperspectives.cshlp.org/lookup/ doi/10.1101/cshperspect.a037028. 459. Thiam HR, Wong SL, Wagner DD, Waterman CM. Cellular mechanisms of NETosis. Annu Rev Cell Dev Biol. 2020;36:191–218. Available from https://www.annualreviews.org/ doi/10.1146/annurev-cellbio-020520-111016. 460. Chen KW, Demarco B, Broz P. Beyond inflammasomes: emerging function of gasdermins during apoptosis and NETosis. EMBO J. 2020;39:103397. Available from https://onlinelibrary.wiley.com/doi/10.15252/embj.2019103397. 461. Chen T, Li Y, Sun R, Hu H, Liu Y, Herrmann M, et al. Receptor-mediated NETosis on neutrophils. Front Immunol. 2021;12:775267. Available from https://www.frontiersin.org/ articles/10.3389/fimmu.2021.775267/full.
References
201
462. Wang H, Zhang Y, Wang Q, Wei X, Wang H, Gu K. The regulatory mechanism of neutrophil extracellular traps in cancer biological behavior. Cell Biosci. 2021;11:193. Available from https://cellandbioscience.biomedcentral.com/articles/10.1186/s13578-021-00708-z. 463. Tan C, Aziz M, Wang P. The vitals of NETs. J Leukoc Biol. 2021;110:797–808. Available from https://onlinelibrary.wiley.com/doi/10.1002/JLB.3RU0620-375R. 464. Huang SU-S, O’Sullivan KM. The expanding role of extracellular traps in inflammation and autoimmunity: the new players in casting dark webs. Int J Mol Sci. 2022;23:3793. Available from https://www.mdpi.com/1422-0067/23/7/3793. 465. Douda DN, Khan MA, Grasemann H, Palaniyar N. SK3 channel and mitochondrial ROS mediate NADPH oxidase-independent NETosis induced by calcium influx. Proc Natl Acad Sci. 2015;112:2817–22. Available from https://pnas.org/doi/full/10.1073/ pnas.1414055112. 466. Münzer P, Negro R, Fukui S, di Meglio L, Aymonnier K, Chu L, et al. NLRP3 inflammasome assembly in neutrophils is supported by PAD4 and promotes NETosis under sterile conditions. Front Immunol. 2021;12:683803. Available from https://www.frontiersin.org/ articles/10.3389/fimmu.2021.683803/full. 467. Sollberger G, Choidas A, Burn GL, Habenberger P, Di Lucrezia R, Kordes S, et al. Gasdermin D plays a vital role in the generation of neutrophil extracellular traps. Sci Immunol. 2018;3:6689. Available from http://immunology.sciencemag.org/lookup/doi/10.1126/sciimmunol.aar6689. 468. D’Cruz AA, Speir M, Bliss-Moreau M, Dietrich S, Wang S, Chen AA, et al. The pseudokinase MLKL activates PAD4-dependent NET formation in necroptotic neutrophils. Sci Signal. 2018;11:1716. Available from https://www.science.org/doi/10.1126/scisignal.aao1716. 469. Sung P-S, Hsieh S-L. C-type lectins and extracellular vesicles in virus-induced NETosis. J Biomed Sci. 2021;28:46. Available from https://jbiomedsci.biomedcentral.com/ articles/10.1186/s12929-021-00741-7. 470. Sung P-S, Huang T-F, Hsieh S-L. Extracellular vesicles from CLEC2-activated platelets enhance dengue virus-induced lethality via CLEC5A/TLR2. Nat Commun. 2019;10:2402. Available from http://www.nature.com/articles/s41467-019-10360-4. 471. Masso-Silva JA, Moshensky A, Lam MTY, Odish MF, Patel A, Xu L, et al. Increased peripheral blood neutrophil activation phenotypes and neutrophil extracellular trap formation in critically ill coronavirus disease 2019 (COVID-19) patients: a case series and review of the literature. Clin Infect Dis. 2021. Available from https://academic.oup.com/cid/advance-article/ doi/10.1093/cid/ciab437/6275596. 472. Knackstedt SL, Georgiadou A, Apel F, Abu-Abed U, Moxon CA, Cunnington AJ, et al. Neutrophil extracellular traps drive inflammatory pathogenesis in malaria. Sci Immunol. 2019;4:eaaw0336. Available from https://immunology.sciencemag.org/lookup/doi/10.1126/ sciimmunol.aaw0336. 473. Castanheira FVS, Kubes P. Neutrophils and NETs in modulating acute and chronic inflammation. Blood. 2019;133:2178–85. Available from https://ashpublications.org/blood/ article/133/20/2178/273824/Neutrophils-and-NETs-in-modulating-acute-and. 474. Palmer LJ, Damgaard C, Holmstrup P, Nielsen CH. Influence of complement on neutrophil extracellular trap release induced by bacteria. J Periodontal Res. 2016;51:70–6. Available from https://onlinelibrary.wiley.com/doi/10.1111/jre.12284. 475. Diago-Navarro E, Calatayud-Baselga I, Sun D, Khairallah C, Mann I, Ulacia-Hernando A, et al. Antibody-based immunotherapy to treat and prevent infection with hypervirulent klebsiella pneumoniae. Clin Vaccine Immunol. 2017;24:16. Available from https://journals.asm. org/doi/10.1128/CVI.00456-16. 476. Stacey HD, Golubeva D, Posca A, Ang JC, Novakowski KE, Zahoor MA, et al. IgA potentiates NETosis in response to viral infection. Proc Natl Acad Sci. 2021;118:e2101497118. Available from https://pnas.org/doi/full/10.1073/pnas.2101497118. 477. Boribong BP, LaSalle TJ, Bartsch YC, Ellett F, Loiselle ME, Davis JP, et al. Neutrophil profiles of pediatric COVID-19 and multisystem inflammatory syndrome in children. bioRxiv
202
3 Virulence of Pathogens and the Counteracting Responses of the Host
Prepr Serv Biol. 2021. Available from http://www.pubmedcentral.nih.gov/articlerender. fcgi?artid=PMC8722589. 478. Smolarz M, Zawrotniak M, Satala D, Rapala-Kozik M. Extracellular nucleic acids present in the candida albicans biofilm trigger the release of neutrophil extracellular traps. Front Cell Infect Microbiol. 2021;11:681030. Available from https://www.frontiersin.org/ articles/10.3389/fcimb.2021.681030/full. 479. Tang D, Chen X, Kang R, Kroemer G. Ferroptosis: molecular mechanisms and health implications. Cell Res. 2021;31:107–25. Available from http://www.nature.com/articles/ s41422-020-00441-1. 480. Liu J, Kang R, Tang D. Signaling pathways and defense mechanisms of ferroptosis. FEBS J. 2021;2021:16059. Available from https://onlinelibrary.wiley.com/doi/10.1111/febs.16059. 481. Jiang X, Stockwell BR, Conrad M. Ferroptosis: mechanisms, biology and role in disease. Nat Rev Mol Cell Biol. 2021;22:266–82. Available from http://www.nature.com/articles/ s41580-020-00324-8. 482. Meunier E, Neyrolles O. Die another way: ferroptosis drives tuberculosis pathology. J Exp Med. 2019;216:471–3. Available from https://rupress.org/jem/article/216/3/471/120336/ Die-another-way-Ferroptosis-drives-tuberculosis. 483. Toyokuni S, Yanatori I, Kong Y, Zheng H, Motooka Y, Jiang L. Ferroptosis at the crossroads of infection, aging and cancer. Cancer Sci. 2020. Available from https://onlinelibrary.wiley. com/doi/abs/10.1111/cas.14496. 484. Xu X, Lin D, Tu S, Gao S, Shao A, Sheng J. Is ferroptosis a future direction in exploring cryptococcal meningitis? Front Immunol. 2021;12:598601. Available from https://www.frontiersin.org/articles/10.3389/fimmu.2021.598601/full. 485. Amaral EP, Costa DL, Namasivayam S, Riteau N, Kamenyeva O, Mittereder L, et al. A major role for ferroptosis in Mycobacterium tuberculosis–induced cell death and tissue necrosis. J Exp Med. 2019;216:556–70. Available from https://rupress.org/jem/ article/216/3/556/120345/A-major-role-for-ferroptosis-in-Mycobacterium. 486. Dar HH, Tyurina YY, Mikulska-Ruminska K, Shrivastava I, Ting H-C, Tyurin VA, et al. Pseudomonas aeruginosa utilizes host polyunsaturated phosphatidylethanolamines to trigger theft-ferroptosis in bronchial epithelium. J Clin Invest. 2018;128:4639–53. Available from https://www.jci.org/articles/view/99490. 487. Muhoberac BB. What can cellular redox, iron, and reactive oxygen species suggest about the mechanisms and potential therapy of COVID-19? Front Cell Infect Microbiol. 2020;10:569709. Available from https://www.frontiersin.org/articles/10.3389/ fcimb.2020.569709/full. 488. Edeas M, Saleh J, Peyssonnaux C. Iron: innocent bystander or vicious culprit in COVID-19 pathogenesis? Int J Infect Dis. 2020;97:303–5. Available from https://linkinghub.elsevier. com/retrieve/pii/S1201971220304173. 489. Camini FC, da Silva Caetano CC, Almeida LT, de Brito Magalhães CL. Implications of oxidative stress on viral pathogenesis. Arch Virol. 2017;162:907–17. Available from http://link. springer.com/10.1007/s00705-016-3187-y. 490. Huang P, Chen G, Jin W, Mao K, Wan H, He Y. Molecular mechanisms of parthanatos and its role in diverse diseases. Int J Mol Sci. 2022;23:7292. Available from https://www.mdpi. com/1422-0067/23/13/7292.
4
The DAMP-Driven Host Immune Defense Program Against Pathogens
4.1 Introduction Humans—together with a variety of other mammals—live on this planet that is incredibly inhabited by about a trillion species of microorganisms and viruses that are pathogens, threatening our normal homeostasis and causing disorders. On the contrary, there are nonpathogenic beneficial commensal microbes that serve our health, reproduction, and survival. Given this scenario, the ambitious task of our immune system is clear: On the one hand, it has to eliminate that universe of pathogenic microbes that are themselves constantly evolving, and, on the other hand, it must tolerate and even farm the billions of commensals in order to support normal tissue and organ function. It is not surprising, therefore, that our innate/adaptive immune defense system uses a sophisticated and complex array of mechanisms to fulfill these challenging tasks, including special tools to recognize structural features of the microbes; and to realize and appropriately react to the dangerous cell stress/tissue injury caused by the pathogens amongst them, and to call immune killer cells on the scene to eradicate invading pathogens. The most powerful tools brought into place for the defensive part of these tasks have been presented in Sects. 3.6 and 3.7 with the description of cell-autonomous stress responses and induction of various subroutines of RCD. However, with the execution of these events that were outlined under the parable of the Red Queen paradigm, the work of the system is not finished. In addition, the defense system is able to install an immune memory, allowing it to contribute vigorously to a more effective host response against specific pathogens when they are encountered later a second time. From this background, it is easy to understand that our immune system always faces difficult and complicated decisions in accomplishing all these tasks. In the past, this topic has been comprehensively presented countless times in the international literature. Here, it is again resumed by focusing on DAMPs, that is, on
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 W. G. Land, Damage-Associated Molecular Patterns in Human Diseases, https://doi.org/10.1007/978-3-031-21776-0_4
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some aspects that have emerged in recent times with the increasing knowledge about their defensive role in infectious diseases caused by microorganisms such as bacteria, viruses, fungi, and parasites.
4.2 MAMPs and DAMPs as Key Players in Defense Responses to Pathogens 4.2.1 Introductory Remarks As often quoted in this book, the primary goal of any immune defense response is to detect and eliminate factors that interfere with homeostasis. Accordingly, the immune defense response to pathogenic invaders—mainly consisting of innate immune inflammatory and adaptive immune processes—is to recognize and eliminate them and repair the damage they have caused. Plausibly, restoration of homeostasis includes the imperative to resolve the inflammatory response and terminate the immune processes in a timely manner. Hence, a typical regulated immune defense response to pathogens is thought to consist of five key components: 1. Inflammatory inducers that are MAMPs derived from pathogenic invaders plus DAMPs emitted primarily and directly by cellular stress such as ER stress during pathogen entry and replication or, subsequently and indirectly, via pathogen- induced RCD; 2. MAMP/DAMP-detecting sensors, that is, PRMs on/in cells of the innate immune system, which trigger downstream signaling pathways to activate inflammation- promoting and inflammation-resolving transcription factors, resulting in the activation of hundreds of corresponding genes; 3. Downstream efferent inflammation-promoting and inflammation-resolving mediator substances secreted by MAMP/DAMP-activated innate immune cells, which target the affected/infected tissues; 4. The generation of an innate immune memory (trained immunity); 5. Innate lymphoid cells (ILCs) and unconventional T cells that assist context- dependently humoral innate immune mediator substances in attacking pathogens; 6. MAMP/DAMP-activated APCs of the innate immune system, in particular, DCs, which initiate the specific adaptive immune response characterized by clonal gene rearrangements from a broad repertoire of microbial antigen-specific receptors on T and B lymphocytes. The type and the degree of inflammatory responses reflecting the first line of defense are dependent on the nature of the infectious agent (bacterial, viral, fungal, or parasitic), its virulence, and its persistence. The second line of defense, the adaptive immune system, then, is committed to executing the elimination of pathogens in the late phase of infection and is responsible for the generation of adaptive immunological memory. The six steps are briefly addressed in this and the following sections.
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4.2.2 Microbe-Associated Molecular Patterns 4.2.2.1 General Remarks Host ↔ pathogen interactions are traditionally instigated via host recognition of MAMPs, that is, molecules that are indispensable for the pathogen’s life cycle. Numerous MAMPs sensed by various PRMs have been described as conserved molecular motifs for many classes of nonpathogenic and pathogenic bacteria, viruses, fungi, and parasites. Given their many precise descriptions in the international literature and the concise outline of their structure in the second part of Chap. 2, they are only briefly resumed here. 4.2.2.2 Pathogen Membrane Components Acting as MAMPs The MAMPs detected on pathogens consist mainly of membrane proteins such as bacterial wall components and viral fusion envelope proteins. The discovery of bacterial MAMPs (traditionally denoted as PAMPs in those days) dominated early research activities in the field of innate immunity. As already briefly touched on in Sect. 2.6.4 (Figs. 2.7 and 2.8), the walls of Gram-positive bacteria consist mainly of PGN and LTA, whereas the Gram-negative bacterial cell wall is more complex and contains a thin layer of PGN adjacent to the cytoplasmic membrane and an outer membrane consisting of LPS, phospholipids, and other membrane proteins. Another MAMP, flagellin, derives from both Gram-positive and Gram-negative bacteria [1, 2]. Also, viral envelope proteins, such as the spike protein of SARS-CoV-2, can operate as MAMPs (cf. Fig. 2.10) [3]. The major components of the fungal cell wall are beta-glucan, mannan, and chitin [4, 5]. Several protozoan MAMPs have been described as well. For example, MAMPs common amongst protozoans are some glycolipids, including glycophosphatidylinositol (GPI), alkylacylglycerol, lipophosphoglycan, and glycoinositolphospholipids, which can be attached to the C-terminus of proteins in the cell membrane. These MAMPs coat the surface of protozoan parasites, for example, as studied on Plasmodium spp., Trypanosoma spp., and Leishmania (for further reading, see [6–10]). MAMPs derived from helminths have also been outlined. For example, in studies on mice, helminth carbohydrate, lacto-N-fucopentaose III, was found to drive activation/maturation of DCs [11]. In other lines of studies on knockout (KO) mice, ES-62, a filarial nematode phosphorylcholine-containing secreted product, was found to be sensed by TLR4 on macrophages and DCs to modulate an innate immune response [12]. 4.2.2.3 Pathogen-Derived Nucleic Acids Acting as MAMPs: Or Better—Exogenous DAMPs Moreover, bacterial, viral, fungal, and parasitic NAs are generally considered to operate as MAMPs or PAMPs, such as DNA (e.g., unmethylated cytosine phospho- bound guanosine [CpG] motifs), dsRNA, ssRNA, and 5′-triphosphate RNA. Notably, the unmethylated CpG motif is a typical feature of many lower microorganisms but is not a component of mammalian DNA [5, 10, 13–17]. Of note, however, these exogenous NA-MAMPs have been re-designated as exogenous DAMPs in Sect.
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1.2.4.3 and Table 1.3 because they act intracellularly as mis-/dislocated and/or pathologically accumulated NAs, that is, just precisely like endogenous NAs that are designated as DAMPs. Actually, looking at the international literature, NAs are currently weighted even more heavily in their function as potent danger signals. More details of them are outlined contextually in the following sections when needed.
4.2.3 Damage-Associated Molecular Patterns The classification of DAMPs, as currently used in the literature, has been updated in Sect. 1.2 and Tables 1.1, 1.2, and 1.3, in accordance with previous classification attempts as presented in Vols. 1 and 2 of this book [18, 19]. Indeed, interest in the role of these unique molecules in infections has become a burning field of biomedical research and is noticeably growing, in particular, in relation to the phenomena of both pathogen-induced, cell-autonomous stress responses and—when these responses fail—subtypes of RCD. The scenario has been highlighted in the previous chapter (Sects. 3.6 and 3.7) by stressing that both events doubtlessly serve as the most prolific sources of DAMPs in infectious diseases. A wealth of DAMPs is believed to have evolutionarily evolved in the course of the arms race between coevolving pathogens and their natural hosts to protect mammals from dangerous infectious stress and injury. A growing number of those molecules have been reported including IA-1 DAMPs such as the prototype HMGB1 [20–28]; HSPs [29, 30]; S100 proteins [31–33], and extracellular nucleus-derived histones and NAs [34–36], as well as IA-2 DAMPs such as eATP. Notably, the molecules are not only released from cells undergoing RCD but are also directly or indirectly involved in the initiation of pathogen-triggered pro-death pathways leading to RCD. Needless to mention in this context are some IL-1 family members (e.g., IL-1β), type I IFNs, and TNF, which are secreted by DAMP-activated innate immune cells during infection (cf. Fig. 3.8b). “Needless to mention” here means that two of these inflammatory mediators (type I IFNs and TNF) are commonly well known as cytokines in clinical and research settings of infectious inflammation, whereas, in this book, they are referred to as inducible DAMPs. As typical DAMPs, all these molecules activate cells of the innate immune system in concert with MAMPs. According to current knowledge, however, the pathogenetic—obviously context-dependent—mechanisms of the various subclasses of DAMPs in infectious diseases have not been systematically examined yet. In particular, the precise interplay of DAMPs and MAMPs in the activation process of innate immune cells is still largely unexplored. We discuss this point below.
4.2.4 Résumé Over a long period of time, DAMPs were not recognized as crucial players in infections. However, the tide seems to have turned recently. The fact that pathogens can trigger various forms of RCD known to be notoriously associated with the release
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of DAMPs can probably be considered the spark for this evolution. A recent highlight of this development is the publication of an increasing number of articles describing the role of DAMPs in COVID-19. We will come back to this encouraging development in the next chapter.
4.3 Sensing of MAMPs and DAMPs by Pattern Recognition Molecules Triggering Innate Immune Pathways in Infections 4.3.1 Introductory Remarks Traditional views on innate immune defense against pathogens are based on the pattern recognition theory proposed by Charles Janeway Jr. in 1989. His ingenious theory has revolutionized our understanding of the immune system and is considered the cornerstone of modern immunology. The model held that germline-encoded PRRs expressed by innate immune cells exist, which are responsible for detecting conserved products of microbial origin [37, 38]. Interaction of these cell-intrinsic PRRs with MAMPs endows the innate immune system with the ability to distinguish effectively between host cells and pathogens, providing initial defense and also contributing to the activation of adaptive immunity (also see articles of Janeway and Medzhitov in [39–44] as well as Refs. [45, 46]). Janeway’s model has led to tremendous progress in the research field of innate immune signaling, and a wealth of knowledge on PRMs has been (and still is) published. These perceiving sensors are expressed on/in cells of the innate immune system, including mobile cells (also denoted as professional immune cells [such as PMNs, macrophages, monocytes, DCs]) and sessile cells (i.e., nonimmune cells such as ECs and epithelial cells). The PRMs are localized at the cellular surface, in the cytoplasm, and in the nucleus of all innate immune cells. Of note, with the introduction and acceptance of the danger/injury model in Immunology, it became obvious that these unique sensors of the innate immune system function as “promiscuous” recognition receptors; that is, they do perceive not only pathogen-derived MAMPs but also DAMPs, induced by cell stress/tissue injury caused by pathogens (Fig. 4.1). The very initial detection of MAMPs by PRM-bearing innate immune cells (professional phagocytes and nonphagocytosing resident cells) is thought to lead to their primary activation resulting in secretion of inflammatory mediators such as cytokines, chemokines, and adhesion molecules (although the last definite proof is still missing that, at least in vivo, MAMPs can induce an effective inflammatory response in the absence of DAMPs). In addition, the cells respond by initiating cell- autonomous stress responses and inducing various subroutines of RCD, that is, processes associated with the generation and emission of various DAMPs, including (1) cell-extrinsic and cell-intrinsic dysDAMPs (IIB-3 and IIC-4 DAMPs), (2) DAMPs exposed at the cell membrane (IB-1 DAMPs) such as eat-me-signals, as well as (3) DAMPs passively released from dying cells (IA DAMPs) (see Tables 1.1, 1.2, and 1.3). It is thought that the interactions between MAMPs/DAMPs and PRMs on/in mobile phagocytes present momentarily, and specific tissue-resident
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Cell wall components
Pathogen
Cell stress, tissue injury
MAMPs
Cell of the innate immune system
DAMPs
PRMs
PRMs
Infective inflammatory response
in collaboration with the adaptive immune system controlled/regulated response Initiation and resolution of Inflammation (mild/moderate infectious disease)
uncontrolled/dysregulated response Hyperinflammation (SIRS, MOF), persistent inflammation (chronic infectious disease)
Fig. 4.1 Oversimplified diagram of a model sketching pathogen-induced, MAMP/DAMP- triggered innate immune (inflammatory) → adaptive immune pathways, leading to controlled host defense responses (manifested as mild/moderate transient infectious diseases that end with full recovery) or uncontrolled/dysregulated host defense responses (manifested as a hyperinflammatory syndrome (SIRS, MOF)) or persistent inflammation (chronic infectious disorders). DAMPs damage-associated molecular patterns, MAMPs microbe-associated molecular patterns, MOF multiple organ failure, PRMs pattern recognition molecules, SIRS systemic inflammatory response syndrome
cells localized at the site of invasion initiate the earliest immune pathways in defense against pathogenic invaders. And it is this process that is critical for pathogen containment and subsequent amplification of the full repertoire of the immune defense response. Indeed, upon MAMP/DAMP recognition, cellular PRMs located at the plasma membrane, endosomal membrane, or in the cytosol continue to trigger innate immune proinflammatory and antimicrobial signaling pathways to activate—via adaptor molecules and distal kinases—transcription factors that regulate genes involved in inflammatory responses and antipathogen immunity. Via translational processes, this is followed by the synthesis of a broad range of further molecules such as cytokines (including inducible DAMPs), chemokines, and cell adhesion molecules, which together orchestrate the early host defense response to infection. At the same time, PRR-expressing, MAMP/DAMP-activated APCs such as DCs initiate—via the presentation of microbial antigens and costimulatory signals to host naïve T cells—an adaptive immune response (for further reading on PAMPs interacting with PRRs, see [15, 47–50]). Notably, the critical ability of the cellular innate immune system to recognize and tackle microbes early during infection is based on additional mechanisms such
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as autophagy [51, 52] and phagocytosis [53] (for details, see Vol. 1 [18], Sect. 18.2, p. 377 and Sect. 22.6, p. 556, as well as Refs. [54, 55]). Moreover, the cellular defense mechanisms are fortified by humoral innate immune responses, including activation of the complement system that operates together with its coplayers collectins, ficolins, and pentraxins, as well as antimicrobial peptides such as defensins, cathelicidins, and histatins [56]. Together, the PRM-triggered processes can benefit the host in two ways. First, they can instigate innate immune effector responses aimed at killing the foreign invaders directly, and second, if those responses are not sufficient to eliminate the pathogens, they can initiate microbial antigen-specific adaptive immune responses in terms of a second line of highly specific defense. As a side note for the reader: The various PRM-driven cellular and humoral effector responses have been more comprehensively outlined in Vol. 1 [18], Chap. 5, p. 43, Chaps. 22 and 23, pp. 475–634, as well as Vol. 2 [19], Chap. 2, p. 13, Chap. 5, p. 151, and Chap. 6, p. 211; (also compare [57], Chap. 5, pp. 219–429). Notably, these innate immune responses are context-dependently assisted by defense functions of ILCs and unconventional T cells with partial innate function (see Vol. 1 [18], Chaps. 27 and 28, pp. 665–711; for more recent reviews, see [58–62]). Here, rather than revisiting the various responses in detail, some remarks on their role in the course of detection of pathogens and cell stress/tissue injury caused by them are briefly sketched, with attention to critical new data. While doing so, different PRMs are distinguished depending on whether extracellular or intracellular pathogens are involved.
4.3.2 Cellular Pattern Recognition Molecules and Signaling Pathways Used to Sense Pathogens and to Cope with Stress and Injury Caused by Them: An Overview 4.3.2.1 General Remarks As the first line of defense against invading pathogens, the innate immune system relies mainly on physical and chemical barriers against infection. Physical and chemical defense mechanisms are represented by epithelial, mucociliary, mucosal, and endothelial surfaces [63–66]. However, when pathogens have successfully passed through these barriers, they are sensed by host PRMs. Remarkably, in the last decade, the focus of research has shifted from extracellular to intracellular pathogen recognition systems. Indeed, among a variety of MAMPs, pathogen- derived NAs have emerged as a critical target for intracellular innate immune sensing. Both topics are briefly touched on here. 4.3.2.2 Cell Surface Toll-Like Receptors In earlier times, most studies focused on the role of cell surface PRMs in the detection of pathogens. In particular, the family of membrane-bound TLRs was the major and most extensively studied class of PRRs at that time. In Vol. 1 [18], Sect. 5.2.2 and Figs. 5.1 and 5.2, pp. 44–50, they were presented in more detail. In mammals, TLRs are synthesized in the ER and transported to their ultimate locations in the
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cell, that is, the plasma or endosomal membranes. Among the cell surface TLRs (TLRs 1, 2, 4, and 5), TLR4 detects LPS, TLRs 1, 2, and 6 bind to lipoproteins (e.g., TLR2 binds to PGN and LTA), and TLR5 senses flagellin. The endosomal membrane-bound TLRs (TLRs 3, 7, 8, 9) are discussed below (for an excellent recent review on TLRs and the control of immunity, see Fitzgerald and Kagan [67]). Signaling Pathways and the Supramolecular Organizing Centers The process of MAMP/DAMP-mediated dimerization of TLR ectodomains is a key feature of signaling, as ectodomain dimerization results in the coordinate dimerization of the cytosolic Toll-interleukin-1 receptor (TIR) domains of these PRRs [68]. As a next step, the adapter protein MyD88-adapter-like (MAL) (also called TIR domain-containing adapter protein [TIRAP]) recognizes the dimerized TIR domain and triggers the assembly of a large oligomeric scaffold of cytosolic proteins, denoted as a supramolecular organizing center (SMOC). As outlined in Vol. 2 [19], Sect. 2.2.2, p. 14, the SMOCs [69] are considered the principal subcellular sites of signal transduction in terms of signaling organelles, which drive innate immune cellular responses, for example, to microbial detection. Typically, these machines of the innate immune system allow for an all-or-none response that is only triggered once a threshold is exceeded. In other words, this molecular machinery allows efficient signal amplification, preceding enzyme activation that enables a response threshold to be reached. Indeed, this phenomenon of nucleated polymerization ensures that a small number of sensor proteins can activate many downstream signaling proteins (for key articles, see [70–72]). Up to date, four such SMOCs have been proposed: as here applicable, the TLR → MAL/TIRAP-triggered myddosome [72–74] and the adaptor protein TRIF-related adaptor molecule (TRAM)-triggered putative triffosome [67, 72, 75]. Further, the polymerization of inflammasome- associated ASC, visible as so-called ASC specks (discussed in Sect. 3.7.5.3), as well as the RLR-promoted polymerization of mitochondrial antiviral signaling protein (MAVS) (outlined below) have been proposed as such organelles [71, 72, 76]. The Myddosome The core of the hetero-oligomeric structure of the myddosome comprises multiple copies of MyD88 and members of the interleukin-1-receptor-associated kinase (IRAK) family of serine–threonine kinases. Specifically, in cell-free systems using recombinant proteins, six to eight molecules of MyD88 interact with four molecules each of IRAK4 and IRAK2. The complex-recruited enzyme tumor necrosis factor- receptor-associated factor 6 (TRAF6) is also present in the myddosome (Fig. 4.2). Signaling via cell surface TLR (e.g., TLR4) → myddosome triggers activation of the transforming growth factor-β (TGF-β)-activated kinase 1 (TAK1), resulting in activation of the IκB kinase (IKK) complex consisting of the IKKα and IKKβ kinases, scaffolded by nuclear factor kappa B (NF-κB) essential modulator (NEMO), also known as IKK-γ. The activation of the IKK complex promotes the phosphorylation and proteosomic degradation of IκB, which leads to its ubiquitylation and subsequent degradation. This allows the transcription factor NF-κB to translocate to the nucleus. The NF-κB heterodimers typically consist of RelA (p65)
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Fig. 4.2 Simplified schematic diagram of TLR signaling through the myddosome and triffosome. TLR receptors are composed of an extracellular leucine-rich repeat domain, a transmembrane domain, and a cytosolic TIR domain. Upon activation by agonists, for example, MAMPs or DAMPs, all TLRs, except TLR3, form the myddosome complex (left side of the figure). Myddosome assembly occurs around the cytosolic tail of dimerized TLRs present at the plasma membrane or endosomal membrane (not shown). Initially, 6 (-8) molecules of MyD88 are recruited to dimeric TLR-TIRs via homotypic TIR domain interactions (for simplicity, only 2 MyD88 TIR domains are shown). Dimerized TIR domains are recognized by the adaptor protein MAL, which is required for signaling by a subset of TLRs. Six MyD88 DDs provide a platform for the recruitment of 4 IRAK4 and 4 IRAK1/2 DDs. The myddosome is completed by TRAF 6 (recruited by putative binding motifs of IRAK1 and IRAK2), which functions to stimulate downstream IKKand MAPK-dependent transcription factors (see Fig. 4.3). On endosomes, TLR4 (also TLR3 not shown here) has the capacity to associate with the triffosome (right side of the figure). This protein complex is still incompletely defined but is believed to be organized and act according to the model shown here. Notably, the protein axis TRAM → TRIF → TRAF3 is discussed to operate in analogy to MAL → MyD88 → TRAF6 of the myddosome. Similar to MAL, TRAM is a peripheral membrane adaptor protein that scans the plasma and endosomal membranes for dimerized TLR4. In addition, TRIF contains a pLxIS motif that promotes TBK1-dependent gene expression and an RHIM domain to drive RIPK1-mediated activation of NF-κB as well as RIPK3-dependent execution of necroptosis (see Fig. 4.3). DD death domain, IKK IκB kinase, IRAK1/2/4 interleukin-1- receptor-associated kinase1/2/4, LRR extracellular leucine-rich repeat, MAL Myd88-adapter-like, MAPK mitogen-activated protein kinase, Myd88 myeloid differentiation primary response gene 88, RIPK1/3 receptor-interacting serine/threonine-protein kinase 1/3, TBK1 TANK-binding kinase1, TIR Toll/interleukin-1 receptor, TM transmembrane, TLRs Toll-like receptors, TRAF3/6 tumor necrosis factor receptor-associated factor 3/6, TRAM TRIF-related adaptor molecule, TRIF Toll/IL-1(TIR)-domain-containing adaptor inducing interferon–β. (Sources: [67, 72–75])
and p50, which bind to NF-κB target sites in the promoters and enhancers of immune response genes. Concurrently, TAK1 induces activation of members of the MAPK family, such as extracellular signal-regulated protein kinase1 (ERK1)/ERK2, p38, and c-Jun-N-terminal protein kinase (JNK). These kinases mediate activation of further transcription factors such as activator protein-1 (AP-1), cAMP response
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element-binding protein (CREB), and Akt → mechanistic target of rapamycin (mTOR). Collectively, these signaling cascades induce strong transcriptional responses and gene expression of proinflammatory cytokines, chemokines, and other inflammatory mediators (cf. Fig. 4.3; for more details, including literature references, also see Vol. 1 [18], Sect. 22.3.3, Fig. 22.3 and Box 22.1, pp. 488–491, as well as Sect. 22.3.4, Fig. 22.5, p. 494; for further reading, also see [14–16, 77–80]). The Putative Triffosome The core of the hetero-oligomeric structure of the putative triffosome comprises— in analogy to MAL ↔ Myd88 ↔ TRAF6—, TRAM ↔ TRIF ↔ TRAF3 (Fig. 4.2). Of note, in macrophages and conventional DCs, TLR3- or TLR4-induced IFN expression is proposed to be driven by these proteins TRAM, TRIF, and TRAF3 (for TLR3 not proven). For example, upon detection of endosomal dimerized TLR4, TRAM is suggested to interact with TRIF and drive TRAF3-dependent activation of the kinase TBK1. TBK1 then triggers the induction of IFN and interferon-stimulated gene (ISG) expression. Notably, however, the feature of TRAM to promote triffosome-dependent responses is restricted to TLR4 [67]. It should be added here that the mechanisms involved in TRIF-driven IFN responses are not quite clear. Nevertheless, there is evidence suggesting that the conserved pLxIS motif (p, hydrophilic residue; x, any residue; S, phosphorylation site) within TRIF (Fig. 4.2) promotes activation of the IFN-inducing transcription factor IRF3 upon phosphorylation by TANK-binding kinase 1 (TBK1). In turn, then, IRF3 dimerizes and translocates to the nucleus (Fig. 4.3) [81, 82]. Hence, TRIF has the capability to recruit the TBK1 → IRF3 enzyme–substrate pair, leading to IRF3 activation and IFN expression. Finally, it should not be unmentioned that the pLxIS motif has been shown to also play a critical role in mediating the recruitment and activation of IRF-3 in the cGAS- and RLR-triggered signaling pathways [82]. Another impressive feature of the triffosome refers to the ability to induce late activation of NF-κB via recruitment and activation of TRAF6. Thus, upon TLR3 or TLR4 dimerization, the RHIM domain of TRIF (Fig. 4.2) binds to RIPK1, which was shown to activate TAK1, leading to IKK activation [83, 84]. In addition, as briefly addressed already in Sect. 3.7.4.4, TLR3 and TLR4 were found to engage RIPK3 via the noncanonical TRIF ↔ RHIM-based pathway, thereby triggering MLKL-dependent necroptosis (Fig. 4.3) [85] (for details of necroptosis, see Sect. 3.7.4). Prompt Induction of the Pyroptotic Pathway by Simultaneous Engagement of TLRs and NLRP3 Last but not least, it is the function of pathogen-detecting TLRs to contribute to the induction of NLRP3 inflammasome-mediated pyroptosis. Indeed, as outlined in Sect. 3.7.5 and previously in Vol. 1 [18], Sect. 22.4.2 and Fig. 22.11, pp. 515–519, simultaneous exposure of cells to MAMPs (acting as TLR agonists to trigger the priming signal 1) and microbial toxin-induced DAMPs such as eATP (evoking ion
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Fig. 4.3 Simplified schematic diagram of a narrative model illustrating TLR4-triggered signaling via the myddosome and triffosome. The scenario is exemplified by TLR4 recognition of LPS from Gram-negative bacteria (operating as an exogenous DAMP) as well as endogenous DAMPs (e.g., HMGB1, S100 protein). Serum protein LBP binds LPS and delivers it to a CD14 molecule that transfers LPS to the ectodomain of the TLR4/MD-2 receptor complex, which leads to homodimerization of TLR4. Likewise, TLR4 can detect DAMPs such as HMGB1 and S100 proteins released from bacteria-induced regulated cell death. Activation of TLR4 nucleates assembly of the myddosome that triggers a signaling cascade involving the TAK1 complex that in turn results in activation of two pathways, the IKK complex-NF-κB pathway and the MAPK pathway. The IKK complex phosphorylates IκB, which undergoes proteasomal degradation to release NF-κB (i.e., its subunits p65 and p50) for further translocation to the nucleus and subsequent regulation of cytokine genes followed by induction of proinflammatory cytokines. MAP kinases phosphorylate JNK to activate AP-1; both proteins translocate to the nucleus to contribute to induction of proinflammatory cytokines via cytokine gene expression. In addition, MAP kinases (JNK, ERKs, p38) are phosphorylated to activate transcription factors AP-1 and CREB; both proteins translocate to the nucleus to contribute to induction of proinflammatory cytokines via cytokine gene expression. In addition, after translocation to the endosome, the LPS-TLR4/MD-2 complex (or HMGB1-TLR4/MD-2 complex) leads to the triffosome-dependent signaling pathway that mediates the induction of IRF3 and production of type-1 interferons. Moreover, evidence suggests that TRIF, via the triffosome and RIPK1, induces late activation of NF-κB. Accumulating evidence also suggests that, under certain conditions, endosomal TLR4 can promote triffosome-triggered, RIPK3-mediated, MLKL- dependent necroptosis. AP-1 activator protein-1, CREB cAMP response element-binding protein, ERK1/2 extracellular signal-regulated protein kinase 1/2, HMGB1 high mobility group box 1, IκB inhibitor of nuclear factor-kappa B, IKK IκB kinase, IRAK2/4 interleukin-1-receptor-associated kinase 2/4, IRF3 interferon regulatory factor 3, JNK c-Jun-N-terminal protein kinase, LBP LPS- binding protein, MAPKs mitogen-activated protein kinases; MLKL mixed lineage kinase domain- like protein, NEMO NF-κB essential modulator, NF-κB nuclear factor–kappa B, RCD regulated cell death, RIPK1/3 receptor-interacting serine/threonine-protein kinase 1/3, TAB 2/3 transforming growth factor-β-activated kinase1 (TAK1)-binding protein 2/3, TAK1 transforming growth factor- β-activated kinase 1, TBK1 TANK-binding kinase 1, TRAF 3/6 tumor necrosis factor (TNF)receptor-associated factor 3/6. (Sources: [67, 77–85])
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perturbations in terms of activation signal 2) promote assembly of the inflammasome, resulting in pyroptotic cell death. However, of even more interest in this context, the simultaneous engagement of TLRs and NLRP3 was found to lead promptly to the assembly of the NLRP3 inflammasome resulting in pyroptosis. This rapid response pathway (e.g., rapid CASP1 activation within 30–45 min after Listeria infection without prior TLR priming [86]) is dependent on IRAK1, which directly links MyD88-dependent TLR ligation to rapid NLRP3 inflammasome assembly. In fact, this immediately developing pyroptosis is dependent on the myddosome (Myd88 → IRAK4 → IRAK1)-signaling pathway but is independent of any TLRtriggered transcriptional pathways induced in the cell [67, 86, 87] (Fig. 4.4). In fact, these experimental observations of dual signals from TLRs and NLRP3, which synergistically provoke inflammasome-mediated pyroptosis, mirrors again the tenor of this book: A robust and early innate immune defense response against invading pathogens involves not only the action of MAMPs but also additional immediate (!) emission of DAMPs—even before the transcriptional induction of inflammatory cytokines and chemokines.
Fig. 4.4 Simplified schematic diagram of a narrative model illustrating rapid induction of pyroptosis via myddosome-dependent, IRAK1-mediated, non-transcriptional priming of the NLRP3 inflammasome. Simultaneous exposure of cells to TLR ligands and stimuli that promote inflammasome assembly lead to immediate pyroptosis. Of note, this rapid response pathway (e.g., rapid CASP1 activation within 30–45 min after Listeria infection without prior TLR priming [86]) is dependent on the myddosome component IRAK1, which directly links MyD88-dependent TLR ligation to rapid NLRP3 inflammasome assembly. In fact, this immediately developing pyroptosis is dependent on the myddosome (Myd88-IRAK4-IRAK1) signaling pathway but is independent of any TLR-triggered transcriptional pathways induced in the cell. Note: more details of pathways leading to activation of the NLRP3 inflammasome and execution of pyroptosis are shown above in Fig. 3.9. CASP1 caspase 1, CM cell membrane, GSDMD gasdermin D, IL-1β interleukin-1 beta, IRAK1 interleukin-1-receptor-associated kinase 1, NLRP3 nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3, TLR Toll-like receptor, TRAF6 tumor necrosis factor (TNF)-receptor-associated factor 6. (Sources: [67, 86, 87])
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4.3.2.3 Nucleic Acid Sensors As described in the second part of Chap. 2, all pathogens rely on their DNA for replication. Among others, this means that host cells are inescapably confronted with pathogen-derived NAs, either they are derived from extracellular pathogens and endocytosed from outside or released by intracellular pathogens inside the cell. Hence, the consequent atypical aberrant localization of bacterial, viral, fungal, or parasitic NAs within the endosomal compartments or the cell cytosol or the pathological accumulation of NAs in the cytosol signal a cell that its integrity is disturbed and perturbed. In other words, as already proposed in Sect. 1.2.4.3 and above, intracellular pathogen-derived NAs are “(mis)recognized” by the cell as danger-signaling exogenous DAMPs. In addition, simultaneously with sensing pathogen-derived NAs by TLRs, RLRs, or DNA receptors, the concomitant molecular perturbations evoked by the pathogen’s life cycle and reflecting the presence of dysDAMPs, are sensed by receptors such as PERK or NLRP3 (cf. Fig. 3.5). To add here also is the fact that innate immune cells are equipped with various categories of PRMs that can sense intracellular NAs differently. Thus, most NA-sensing endosomal TLRs are expressed predominantly in mobile innate immune cells (e.g., macrophages and DCs), whereas the major cytosolic DNA and RNA sensors are expressed at various levels in most cell types of the innate immune system (compare Vol. 1 [18], Chap. 8, p. 115 and Chap. 9, p. 159). Consequently, the diverse PRMs involved in the detection of infections trigger various signaling pathways that are briefly described here (for more information, see Vol. 1 [18], Sect. 5.2, pp. 44–60; for more recent reviews, see [88–94]). Endolysosomally Localized Transmembrane Toll-Like Receptors The endolysosomally localized transmembrane TLRs include TLR3, TLR7, TLR8, TLR9, and TLR13 (not found in humans), which detect various exogenous (e.g., viral, bacterial) and endogenous (host) RNA and DNA in the lumen of endolysosomes. Notably, these TLRs are synthesized in the ER and—escorted by trafficking chaperones such as Unc93B, gp96, and PRAT4A—translocate from the ER through the Golgi apparatus to endolysosomes, where they are further processed by proteolysis via cathepsins. TLR3 recognizes and binds to dsRNA, TLR7/8 senses and binds to ssRNA, and TLR9 detects and binds to single-stranded CpG DNA (Fig. 4.5) [93, 94, 96, 97]. TLR3, like endocytosed TLR4, is suggested to lead to the TRIF → putative triffosome (without TRAM)-dependent signaling pathway that mediates the induction of IRF3 and production of type-I IFNs as well as—via RIPK1—induces late activation of NF-κB. All other TLRs use MyD88 as their adaptor protein to form the assembly of the myddosome that triggers signaling pathways to elicit vital proinflammatory immune responses, here: NF-κB, IRF5, and IRF7 (Fig. 4.5) [67, 72, 73, 83, 95, 98]. TLR13 recognizes a conserved 10-nucleotide sequence from bacterial 23S ribosomal RNA (described and illustrated in Vol. 1 [18], Sect. 22.3.3, p. 488 and Fig. 22.4, p. 490, as well as Vol. 2 [19], Sect. 2.2.3, p. 15; for recent reviews with more details, see [89, 93, 94]). Of note, among endogenous self-NAs involved in various diseases such as autoimmune disorders, ssRNA, dsRNA, and mtDNA (hypomethylated at CpG motifs)
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Fig. 4.5 Simplified schematic diagram of a narrative model illustrating endosomal nucleic acid sensing by TLRs followed by TLR signaling through the myddosome and triffosome. Various endocytosed nucleic acids (RNA, CPG DNA) derived from bacteria, viruses, and/or dying infected host cells are sensed by TLR3, 7, 8, 9, and 13, which are transmembrane proteins synthesized in the ER. The TLR trafficking chaperone Unc93B1 escorts TLRs from the ER through the Golgi apparatus to endolysosomes, where TLRs are further processed by proteolysis. Binding to their specific nucleic acid ligands leads to formation of TLR dimers and oligomerization of their cytoplasmic TIR domains, which recruit signaling adaptors through TIR ↔ TIR interaction. TLR3 recruits the adaptor protein TRIF, which in turn recruits TRAF3 for formation of the triffosome complex, resulting in activation of the TBK1 → IRF3 cascade for transcriptional upregulation of type I interferons. TRIF also recruits RIPK1 to activate the IKK complex, leading to NF-κB- mediated transcription of proinflammatory cytokines. Ubiquitination controls the activation of both TBK1 and IKK (not shown). In the case of TLR7/8/9 and likely TLR13, recruitment of MyD88 leads to oligomerization of its death domain, which in turn triggers the formation of the myddosome complex containing MyD88, IRAK4, IRAK1, and IRAK2. Formation of the myddosome results in activation of the IRAKs and the ubiquitin E3 ligase TRAF6, which in turn activates NF-κB, IRF5, and IRF7. Note: for simplicity, MD-2 and MAL/Tirap are not shown. CM cell membrane, CpG unmethylated cytosine phospho-bound guanosine, dsRNA double-stranded RNA, ER endoplasmic reticulum, DD death domain, IFNs interferons, IκB inhibitor of nuclear factor- kappa B, IKK IκB kinase, IRF3/5/7 interferon regulatory factor3/5/7, NAs nucleic acids, NEMO NF-κB essential modulator, NF-κB nuclear factor-kappaB, P phosphoryl group, Ubn polyubiquitin chain, RHIM receptor-interacting protein 1 homotypic interaction motif, RIPK1 receptor- interacting serine/threonine-protein kinase 1, ssRNA single-stranded RNA, TBK1 TANK-binding kinase 1, TIR Toll/IL-1 receptor domain, TLR Toll-like receptor. (Sources: [72, 73, 88–95])
have been shown to be potent activators of endosomal TLRs [99, 100] (for further details of self NAs in autoimmune diseases, see Chap. 7). Cytosolic RNA Sensors Cytosolic RNA sensors, the RLRs, are a family of DExD/H box RNA helicases that function as cytoplasmic sensors of RNAs derived from exogenous (e.g., viral,
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bacterial) and endogenous origins. The protein family comprises three members: RIG-I, MDA5, and laboratory of genetics and physiology 2 (LGP2). All proteins have a central helicase domain and a carboxyl(C)-terminal domain (CTD). These two domains work together to recognize RNAs. RIG-I and MDA5 additionally contain tandem CARDs at their N-termini, which are critical for interactions with mitochondrial antiviral signaling proteins to promote downstream signaling. LGP2 lacks the CARDs and does not function as a signaling molecule, and thus is generally believed to regulate RIG-I and MDA5 (described and illustrated in Vol. 1 [18], Sect. 5.2.4, and Fig. 5.4, pp. 55–57; for more detailed information, see recent reviews [89, 101–103]). All RLRs detect pathogen-derived dsRNA, with some differences in ligand preference. For example, RIG-I typically senses blunt-end short dsRNA bearing 5′-triphosphate or 5′-diphosphate, a process involving both the CTD and helicase domain. MDA5 recognizes relatively long dsRNAs. Upon RNA binding and oligomerization, both RLRs undergo homotypic CARD ↔ CARD interactions with the essential adaptor protein for RLR signal transduction, the MAVS protein that is anchored with its transmembrane (TM) into mitochondria, mitochondrial-associated membranes (MAM), and peroxisomes. Notably, through these interactions, RLRs activate MAVS to oligomerize into larger filaments. It is also worth noting—without going into detail—that the activities of RIG-I and MDA5, as well as MAVS, are controlled by several types of PTM, including ubiquitylation, phosphorylation, acetylation, and deamidation [104]. For example, K63-linked ubiquitylation of RIG-I at the CARDs is important for MAVS binding and has a central function in regulating the activity of MAVS. Recent studies have demonstrated that a mitochondria-localized deubiquitinase USP18 specifically interacts with MAVS to promote K63-linked polyubiquitination and subsequent aggregation of MAVS [105]. Recruitment of members of the TRAF family (e.g., TRAF3, TRAF6), TBK1, and IKKε to MAVS filaments results in the assembly of a complex that is reminiscent of the formation of the myddosome and triffosome in terms of SMOCs. Indeed, this signalosome complex serves as an essential platform that triggers two downstream pathways resulting in the activation of IRF3 and IRF7 to induce expression of type I IFNs genes and NF-κB activation to induce expression of proinflammatory genes, respectively (Fig. 4.6; also described and illustrated in part in Vol. 1 [18], Sect. 22.3.6, p. 501 and Fig. 22.7, p. 502, as well as Vol. 2 [19], Sects. 2.2.6 and 2.2.7, pp. 21–25; for recent reviews with more details, see [89, 90, 101–103]). Cytosolic DNA Sensors with Special Attention to Cyclic GMP-AMP Synthase Sensing pathogen-derived DNA in the cytosol, where it does not normally reside, is a potent strategy to perceive infection. Multiple cytosolic DNA sensors have been identified during the past years, including absent in melanoma 2 [AIM2]-like receptors (ALRs), cGAS, ZBP1, the DExD/H-box helicases DHX36 and DHX9, RNA pol III, and others. It should be stressed again that all these receptors trigger signaling pathways resulting in type I IFN production by converging at a common pathway, the STING-pathway (see Vol. 1 [18], Sects. 5.2.5 and 5.2.6 and Fig. 5.5, pp. 57–60; for a recent review, see [91]). One of the most prominent receptors that
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Fig. 4.6 Simplified schematic diagram of a narrative model illustrating the cytosolic RNA- sensing pathway. After entry into the cell cytosol, RNA from viruses and bacteria (thought to act as exogenous DAMPs) or dead cells (i.e., endogenous DAMPs) can bind to RIG-I, sensing 5′-triphosphate (ppp)-containing dsRNA, or MDA5 recognizing long dsRNA, respectively. Activation of RLRs relies on the oligomer formation of RNA-induced filaments and CARD tetramerization. Through CARD ↔ CARD interactions, RLRs activate MAVS at the outer mitochondrial membrane to oligomerize into larger filaments. Binding of K63-linked polyubiquitin chains to CARDs of either RIG-I or MDA5 triggers their oligomerization. Through recruitment of TRAF proteins, MAVS activates TBK1 and IKKs, resulting in the assembly of a complex, which in turn activates IRF3 and IRF7 as well as NF-κB. These transcription factors induce the expression of type I INFs and other proinflammatory genes, resulting in production of type I IFNs and proinflammatory cytokines, chemokines, and other inflammatory mediator substances. CARD caspase-activating and recruiting domain, CM cell membrane, dsRNA double-stranded RNA, endog endogenous, exog exogenous, IFNs interferons, IFR3/7 interferon regulatory factor 3/7, IKKs IκB kinases, MAVS mitochondrial antiviral signaling proteins, MDA5 melanoma differentiation-associated gene 5, NEMO NF-κB essential modulator, NF-κB nuclear factor-kappa B, P phosphoryl group, RCD regulated cell death, RIG-I retinoic acid-inducible gene (protein) I, TBK1 TANK-binding kinase 1, TRAFs tumor necrosis factor (TNF) receptor-associated factors, Ub polyubiquitin chain. (Sources: [89, 101–104])
sense cytosolic DNA originated from various sources (viruses, bacteria, stressed or dying host cells) is cGAS, which should be briefly addressed here (Fig. 4.7, for recent reviews, see [106–109]). Cytosolic DNA binds to cGAS, which subsequently triggers cGAS dimerization and production of a special dinucleotide messenger, 2′3′-cGAMP (from ATP and GTP) that binds STING dimers localized at the ER membranes. Following, STING translocates from the ER via the ERGIC to Golgi compartments to serve there as a signaling platform for TBK1 and IKK. TBK1 phosphorylates STING, which in turn recruits IRF3 for phosphorylation by TBK1. Phosphorylated IRF3 dimerizes and translocates to the nucleus. Another major signaling module used by STING is NF-κB-mediated transcriptional activation. Recent studies revealed that this way of
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Fig. 4.7 Simplified schematic diagram of a narrative model illustrating the cytosolic DNA- sensing pathway via cGAS-STING. After entry into the cell cytosol, DNA derived from DNA viruses (also DNA after reversed transcription of RNA from retroviruses, all thought to operate as exogenous DAMPs), bacteria (acting as exogenous DAMPs), or dead cells (i.e., endogenous DAMPs) is sensed by and binds to cytosolic DNA sensor cGAS that subsequently dimers assemble on dsDNA, leading to enzymatic activation of cGAS and production of a special dinucleotide messenger, 2′3′-cGAMP from ATP and GTP. 2′3′-cGAMP binds STING dimers localized on ER, through trafficking to Golgi, to recruit and activate IKK and TBK1. TBK1 phosphorylates dimerized STING, which in turn recruits IRF3 for phosphorylation by TBK1. Phosphorylated IRF3 dimerizes and enters the nucleus, where it cooperates with NF-κB signaling to turn on transcription of type I IFNs and other immunomodulatory genes. Notably, not shown here: regulation of cGAS by various posttranslational modifications upon DNA insults such as monoubiquitination, polyubiquitination, SUMOylation, glutamylation, phosphorylation, acetylation, and deamidation in cells. cGAS cyclic GMP-AMP synthase, endog endogenous, exog exogenous, IFNs interferons, IKKs IκB kinases, NEMO NF-κB essential modulator, NF-κB nuclear factor-kappaB, RCD regulated cell death, STING stimulator of interferon genes, TAK1 transforming growth factor-β- activated kinase 1, TBK1 TANK-binding kinase 1. (Sources: [106, 107])
STING-dependent NF-κB activation is not only dependent on TBK1 but that TBK1 and IKKε—at least in certain cell types—act redundantly to mediate this response [110]. Finally, the genes are transcribed, which encode type I IFNs and proinflammatory cytokines such as IL-6 and TNF resulting in their secretion (Fig. 4.7; also described and illustrated in Vol. 1 [18], Sect. 22.3.7, p. 505 and Fig. 22.8, p. 508, as well as Vol. 2 [19], Sect. 2.2.7.2, p. 23; for detailed information, see again [106–109]). As with all MAMP/DAMP-triggered homeostatic innate immune responses, cGAS-elicited pathways are tightly controlled through a plethora of regulatory mechanisms that are crucial for balancing the activity of NA sensors for the maintenance of overall cellular homeostasis. They include PTMs such as polyubiquitination, SUMOylation, glutamylation, phosphorylation, and acetylation, as well as intracellular nucleases DNase II, located inside the lysosomal compartment, and TREX1, positioned at the membrane of the ER (for PTMs, see Vol. 1 [18], Sect.
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24.3, Fig. 24.2, pp. 646–649). These enzymes are critical in degrading self-DNA that originates from endogenous sources or exogenous sources (for further information, see [102, 107]).
4.3.2.4 NOD-Like Receptors Besides intracellular PRMs that detect pathogen-derived NAs, another important class of cytoplasmic recognition receptors refers to members of the NLR family, which have already been touched on above in Sect. 3.7.5.2 but intensely addressed and illustrated in Vol. 1 [18], Sect. 5.2.3 and Fig. 5.3, pp. 50–55 (reviewed in [111]). Like the other receptors, NLRs recognize both MAMPs and DAMPs and thus play a crucial role in the innate immune response to pathogens. The NLR family is divided into four subgroups, NLRA, NLRB, NLRC, and NLRP, based on the nature of the N-terminal domain consisting, respectively, of an acidic transactivation domain, a baculovirus inhibitor of apoptosis repeat (BIR), a CARD, and a PYD (see Fig. 5.3 in Vol. 1 [18], p. 50). Alternatively, NLRs can be subdivided into four broad functional categories: signaling transduction, transcription activation, inflammasome assembly, and autophagy. To trigger these categories, the NLRs recognize various MAMPs and numerous DAMPs. For example, NOD1/NOD2 was shown to sense bacterial PGN components and viral RNA to elicit activation of the NF-κB and MAPK signaling pathways. Given these properties, there are significant pathogenic associations between NLRs and various diseases, including infections. In particular, their unique capability to drive the assembly of inflammasomes confers to them a special function in the pathogenesis of infectious diseases. (For this reason, the topic has been separately discussed previously in Sect. 3.7.5.) 4.3.2.5 C-Type Lectin Receptors The C-type lectin receptor superfamily is the largest and most diverse lectin family in animals and has been classified into 17 groups based on phylogeny, structural, and functional properties. The CLRs are soluble and transmembrane PRMs that recognize a diverse range of MAMPs and DAMPs and are defined by the presence of at least one C-type lectin-like domain (CTLD). The CTLDs are critical for the recognition of specific carbohydrate structures, that is, glycolipids and glycoproteins present in bacterial, viral, and fungal components or derived from damaged self or altered-self components. Some special features of these sensors are introduced (inclusive references) and illustrated in Vol. 1 [18], Sect. 5.2.7 and Fig. 5.6, pp. 60–66, as well as Sect. 22.3.8 and Fig. 22.9, pp. 509–512 (also see the eBook: “Lectin in Host Defense Against Microbial Infections” [112]). The CLRs have traditionally been associated with the recognition of fungal MAMPs [113], but recent reports also provided evidence for their role in antiviral [114] and antibacterial host defense [115]. In addition, increasing attention is paid to their ability to promote sterile inflammatory responses [116], indicating that they are involved in amplifying PRM–driven anti-pathogen innate/adaptive immune responses via the detection of DAMPs derived from pathogeninduced RCD.
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4.3.3 Detection of Invading Bacteria: Receptor Molecules and their Helpers Detection of extracellular bacterial MAMPs through cell surface TLRs has already been briefly touched on above. As a general rule, LPS on Gram-negative bacteria is primarily sensed by TLR4, while PGN, LTA, and lipoproteins as essential major components of Gram-positive bacteria are recognized by TLR2 [79, 80]. In fact, LPS—which can also be regarded as an exogenous DAMP—is a prominent microbial component that triggers myddosome-dependent proinflammatory signaling. Targeted studies revealed that TLR4 binds LPS with the help of LPS-binding protein (LBP) and CD14, and an indispensable contribution of the MD-2 protein stably associated with the extracellular fragment of the receptor (Fig. 4.3) Interestingly, the process of TLR4 internalization mentioned above is not provoked by TLR4 itself. Rather, TLR4 is cargo for an LPS-induced endocytosis response mediated by CD14, independent from signaling. Indeed, in most cases, the LPS-induced internalization of TLR4 is controlled by CD14 (outlined in [67, 117]). Like TLR4 in defense against Gram-negative bacteria, TLR2 is critical in host defense against Gram-positive bacteria. This was, for example, evidenced by studies in TLR2-deficient mice, which display increased susceptibility to challenge with Streptococcus pneumoniae and Staphylococcus aureus compared to wild-type mice (cited in [15]). Bacterial pathogens enter the host cell via phagocytosis and can then be recognized by endosomal TLR9 and TLR13 (not found in humans) in immune cells. Whereas mouse TLR13 recognizes bacterial 23S ribosomal RNA [118], TLR9 identifies bacterial unmethylated CpG DNA that represents a potent danger signal [119]. TLR9 → myddosome triggers downstream signaling to lead to IRF and NF-κB activation (Fig. 4.5), resulting in the production of cytokines, chemokines, and interferons, in particular by plasmacytoid DCs (pDCs) [119, 120] (for pDCs, see Vol. 1 [18], Sect. 8.3, p. 129). Bacteria can also be sensed by cytosolic DNA sensors. For example, cGAS reportedly detects a variety of intracellular bacteria, including Chlamydia trachomatis, Listeria monocytogenes, and Francisella tularensis (reviewed by Tan et al. [89]; also cf. Fig. 4.7). Taken together, this brief overview illustrates that the world of bacteria is confronted with an effective arsenal of innate immune recognition molecules, which are used daily by mammals in the evolutionary arms race with pathogenic bacteria. The same scenario is found when observing the detection of viruses—as briefly discussed in the following.
4.3.4 Detection of Viruses: The Impressive Arsenal of Different Receptors Implicated in Antiviral Defense 4.3.4.1 General Remarks Innate immune sensing of viral NAs is vital for early defense against virus infections. Upon initial viral attachment, PRMs on the host cell surface recognize viral invaders from their MAMPs, such as viral capsid proteins and surface
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glycoproteins. Regarding recognition of viral NAs, one has to differentiate between (1) recognition by endolysosomal PRMs of NAs released from dying virus-infected cells and then engulfed by cells to become localized in endolysosomal compartments (requiring internalization of NAs for sensing through an endocytic pathway), and (2) sensing by cytosolic PRMs of the viral genome (DNA or RNA) within the cytoplasm of cells after entry and uncoating of the virus (see Figs. 2.12 and 2.13, exemplifying IAV and SARS-CoV-2 replication; also see review in [121]; further cf. Fig. 12.3 in Vol. 1 [18], p. 231). Impressively, a considerable arsenal of PRMs is alert to trigger host antiviral defense responses, including TLRs, RLRs, ALRs, and CLRs. This network of cellular PRRs plays an essential role in the immune defense response by initiating interferon and other proinflammatory signaling pathways upon detection of viral MAMPs (for earlier classical articles, see [43, 122, 123], for more recent reviews, see [108, 124–134]). In general, they are divided into PRMs sensing extracellular or intracellular viral MAMPs.
4.3.4.2 Detection of Viruses Before Cell Entry As touched on in Sect. 2.7.5.2 attachment is the first step that initiates viral infection. The process relies on the binding of a viral attachment protein (either membrane glycoproteins or sites on a viral capsid) to a generalized receptor on the host target cell surface, more commonly known as attachment factors. Typically, these structural proteins function as viral antigens to induce a specific antiviral adaptive immune response. However, they may also initiate or at least contribute to an inflammatory response prior to viral entry via interaction with cell surface PRRs on innate immune cells, the most well characterized being TLRs. For example, the Ebola virus shed envelope glycoprotein was demonstrated to contribute to the inflammatory response through stimulation of the TLR4 pathway [135] (compare this with Fig. 4.3). Other lines of studies have provided evidence suggesting that TLR2 may recognize the repeating pattern of viral multi-subunit glycoproteins [136]. For instance, it could be shown that two entry-mediating envelope glycoproteins of HCMV, gp, gp B (gB), and gp H (gH), display determinants recognized by TLR2 to initiate inflammatory cytokine secretion in response to HCMV infection [137]. Also, in investigations on human monocyte-derived macrophages and HSCs, evidence was observed to suggest an interplay between host TLR4 and envelope glycoprotein gp120 on the surface of the HIV envelope, leading to intracellular signaling pathways and biologic activities, thereby mediating proinflammatory and profibrogenic signals [138]. Moreover, in recent studies on murine peritoneal exudate macrophages and human THP-1 cell-derived macrophages, data were obtained suggesting that the SARS-CoV-2 spike protein S1 subunit activates TLR4 signaling to induce proinflammatory responses in these cells [139]. As a conclusion of data from other lines of studies, SARS-CoV-2 spike glycoprotein was proposed to bind TLR4 and activate TLR4 signaling to increase cell surface expression of ACE2, facilitating entry and causing hyperinflammation [140]. Nevertheless, the recognition of viral structural proteins by surface PRMs is likely to be negligible
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compared to the intense sensing of viral NAs when considering the strength of an invoked efficient defense response.
4.3.4.3 Detection of Intracellular Viral Nucleic Acids The two ways in which viral NAs enter and reside in a cell have a historical background: In earlier times, viral NAs, released from virus-induced cells succumbing from RCD and then endocytosed, were shown to be sensed by transmembrane endolysosomal TLRs. In recent years, these earlier observations were supplemented by the discovery of the cytosolic NA-sensing PRRs. Since most sessile cells of the innate immune system do not possess NA-sensing TLRs, the cytosolic recognition process is of particular importance for those viruses. This discovery—together with recent notions about the concomitant virus- induced generation of DAMPs—has led to the understanding of how cells of the innate immune defense system elicit powerful innate immune responses against incoming viruses carrying DNA or RNA genomes. The signaling pathways stimulated by DNA and RNA sensors and enabling the expression of antiviral proteins have been previously described and illustrated in Vol. 1 [18], Sect. 22.3.6, Fig. 22.7, and Sect. 22.3.7, Fig. 22.8, pp. 501–509 (for updated illustrations, see Figs. 4.5, 4.6, and 4.7, and for a collection of articles on NA sensing, see again [89–110]). Here, the topic is briefly resumed and updated. RNA Virus-Triggered Signaling Pathways Endosomal and cytosolic PRMs are involved in sensing viral RNA, for example, derived from the influenza virus (Figs. 4.5 and 4.6). Like engulfment of extracellular viral DNA through an endocytic pathway, uptake of extracellular viral RNA through this pathway is also the critical step in recognition by endolysosomal TLRs. Notably, positive-stranded RNA viruses and dsDNA viruses produce dsRNA. These RNA intermediate products but also genomic RNA accumulate in the cytosol of infected cells and can then be passively released from infected cells dying from virus-induced RN into the extracellular space. Subsequently, dsRNA and structured RNA (containing a partial stem in secondary structures of ssRNA, originating from viruses or from stressed or necrotic cells) are sensed by TLR3. On the other hand, endocytosed and phagocytosed ssRNA are sensed by TLR7 and TLR8 (also see Vol. 1 [18], Sect. 5.2.2.4, pp. 47–48; for further reading, see [141]). The elicited signaling is illustrated in Fig. 4.5: recognition process → TLR3 triggers triffosome-dependent pathways, leading—via IRF3 and NF-κB activation—to the secretion of type I IFN and proinflammatory cytokines, whereas TLR7/8 drive myddosome-dependent paths resulting—via NF-κB and IRF7—in secretion of type I IFN and proinflammatory cytokines as well (also see Vol. 1 [18], Sect. 22.3.3, pp. 488–494; for more details, see [141]). Of note, viral endosomal RNA may also be transported to the cytosol for innate immune sensing. Thus, studies on the mammalian orthologs of the Caenorhabditis elegans SID-1 dsRNA transporter, that is, SIDT1 and SIDT2 (localized to late endosomes and lysosomes), provided the first evidence indicating that both promote the
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endosomal escape of long dsRNA to the cytosol, thereby influencing the production of type I IFN following HSV-1 infection [142]. Apart from TLR-triggered pathways involved in perceiving endosomal RNA, RLR-initiated signaling mediates critical and well-established major pathways for sensing viral RNA in the cytosol (Fig. 4.6; also described in Vol. 1 [18], Sect. 22.3.6, and Fig. 22.7, pp. 501–505 as well as Vol. 2 [19], Sect. 2.2.6, pp. 21–23; for more detailed information, see [143–146]). As described above, RIG-I and MDA5 play nonredundant roles in cytosolic RNA sensing by recognizing different groups of exogenous RNAs. Accordingly, the involvement of the two receptors in different virus infections is variable. Viral RNAs, broken down and generated by RNase L cleavage, can also serve as ligands for RIG-I. Further, RLR signaling is regulated by PTMs [145, 147]. In this context, it should not remain unmentioned that there is emerging evidence for an involvement of the cGAS → STING pathway in restricting RNA virus infection, suggesting that there exists crosstalk between the innate sensing of cytosolic RNA and DNA [148]. In the context of RNA virus detection, sensing of the positive-sense ssRNA SARS-CoV-2 has attracted the attention of those researchers working in the field of COVID-19. Thus, in such a recent study, both RIG-I and MDA5 were shown to recognize viral RNAs in the cytoplasm, whereby two viral RNA regions were preferentially sensed by these receptors [149]. Surprisingly, however, SARS-CoV-2 proteins were found to suppress RIG-I and MDA5-mediated type I IFN expression, indicating viral escape from the host’s innate immune response. Notably, a prototypical MAMP relevant for coronaviruses is not its genome, the ssRNA itself, but a dsRNA. This puzzling finding is due to the fact that dsRNA is a by-product of ssRNA genome translation, RNA replication, and transcription following the entrance of the virus into a cell (cf. Fig. 2.13; also see [150, 151]; for reviews, see [130, 152]). Double-stranded RNA can be sensed by TLR3 in the endosome [153] and in the cytoplasm by RIG-I and MDA5, as well as by the kinase PKR (for further reading, see [154–156]). DNA Virus-Triggered Signaling Pathways Endosomal and cytosolic PRMs are involved in sensing viral DNA (Figs. 4.5 and 4.7). Notably, the endosomal TLR9 expressed in pDCs has been shown to induce type I IFN production in response to DNA viruses, including HPV and EBV [157, 158] (for details of signaling, cf. Fig. 22.4 in Vol. 1 [18], p. 490). However, a large variety of DNA viruses reportedly activate the cytosolic STING pathway, including HPV, HSV-1, Adenovirus, and Vaccinia Virus (VACV) [159]. Indeed, cytosolic viral DNA is mainly sensed by cGAS but potentially also by other putative DNA sensors such as IFI16, which are all proposed to activate STING. This observation has contributed to the increased awareness among virologists of the dominant role of DNA → STING sensing in viral DNA perception. Interestingly, the RIG-I receptor, typically recognizing RNA virus infection (see below), has also been shown to sense several DNA viruses, including HSV-1 and EBV. Mechanistically, RNA pol III was found to transcribe adenine (A)–thymine
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(T)-rich dsDNA into dsRNA containing a 5′-triphosphate-moiety, which, as noted above, is a known ligand of RIG-I. Activation of RIG-I by this dsRNA then induces the production of type I IFN and activation of NF-κB [160, 161]. Thus, as discussed by Ma et al. [108], recognition of cytoplasmic A–T-rich dsDNA through the RNA pol III → RIG-I → MAVS axis represents possible crosstalk between innate sensing of RNA viruses and DNA viruses.
4.3.4.4 Nuclear Innate Sensors Detecting Viral DNA Although the engagement of cytosolic NA sensors with viral DNA or RNA results in a robust host antiviral defense, multiple viruses replicate in the nucleus and release their genome DNA there. This means much less or no opportunities for cytosolic receptors to sense viral NAs. However, evolution has taken care of this deficit. Thus, emerging evidence shows that nDNA sensors such as IFI16, heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNPA2B1), scaffold attachment factor A (SAFA), and nuclear cGAS take over this task. Amazingly, also RIG-I has recently been found to locate in the nucleus and was observed, upon IAV infection, to sense IAV replication and oligomerizes with activated cytoplasmic RIG-I to trigger the RIG-I-MAVS signaling cascade (for IAV replication, cf. Fig. 2.12). The spectrum of functions of these evolutionarily conserved sensors includes potentiation of antiviral innate immune responses, showing an impressive crosstalk with cytoplasmic sensors and signaling molecules to create a sophisticated innate signaling network between nucleus and cytoplasm—again, typically regulated by PTMs. The best-investigated receptor is IFI16 which, upon detecting nuclear viral DNA, translocates to the cytoplasm to activate the STING signaling cascade. It is further worth noting that these innate nuclear sensors evolved varied mechanisms for discriminating self from nonself NAs to maintain immune homeostasis and avoid autoinflammatory immune response (for recent reviews, see [162, 163]). In this context, the nuclear protein Ku70 is also of considerable interest. The sensor was reported to translocate, upon transfection with DNA or infection with DNA virus, from the nucleus into the cytoplasm and induce IFN-λ1 rather than IFN-α or IFN-β through a STING-dependent signaling pathway. Recent studies demonstrated Ku70’s cytoplasmic translocation as an early and required event for its cytosolic DNA sensing to trigger a DNA ↔ Ku70-mediated type III IFN response [164] (regarding Ku70, also compare the DDR, presented in Vol. 1 [18], Sect. 18.6 and Fig. 18.7, pp. 408–412). 4.3.4.5 Concluding Remarks This brief overview of the detection of viruses by cellular PRMs reflects the enormous evolutionary achievements of mammals in combating viral infections. But again, it should not go unmentioned at the end that viruses can effectively evade recognition by the innate immune system. Indeed, the coevolution of viruses in the course of the arms race with their hosts has led to the development of viral pathogens that cleverly evade or actively suppress host immunity (as discussed in Sect. 3.3.4). Such strategies used by viruses to escape immune surveillance include the sequestration or modification of viral NAs, interference with specific PTMs of
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PRMs or their adaptors, the degradation or cleavage of PRMs or their adaptor proteins, and the sequestration or relocalization of PRMs. The recent report on the ability of SARS-CoV-2 to suppress RIG-I and MDA5-mediated type I IFN expression provides another highly actual testimony about this phenomenon [149] (for more detailed information, see [165]).
4.3.5 Production of Inducible DAMPs Upon Bacteria and Virus Detection: The Type I Interferon and Tumor Necrosis Factor Systems In view of the here-presented limited description of bacteria and virus detection through PRMs, it is easy to imagine the uniqueness of the innate immune defense system in sensing these pathogens. Thus, upon their detection, cell surface and endosomal TLRs, together with cytosolic RNA and DNA sensors, create a multilayer surveillance system that triggers a variety of cytokines and chemokines upon their detection. Among these proinflammatory mediators, and besides members of the IL-1 family, type I IFNs and TNF, denoted endogenous inducible DAMPs in this book, play an essential role in antibacterial/antiviral defense, and their absence may lead to lethal infections in mammals—a reason enough to say a few words here. Type I IFNs operate in an autocrine and paracrine fashion by binding to their heterodimeric transmembrane receptor, IFNAR1/2, that activates the Janus kinases (JAKs), which in turn activate the transcription factors signal transducer and activator of transcription 1 (STAT1) and STAT2 (for more information on type I IFNs and JAK/STAT signaling, see Vol. 1 [18], Sect. 22.3.4.3, Fig. 22.6, pp. 497–499 as well as Sect. 22.5.5, Fig. 22.12, pp. 527–539). Phosphorylated STAT1 and STAT2 assemble with IRF9 to form interferon-stimulated gene factor 3 (ISGF3). ISGF3 translocates into the nucleus and binds to the specific promoter elements known as IFN-stimulated response elements (ISREs), thereby driving the expression of hundreds of ISGs, which then mediate the effects of type I IFNs (Fig. 4.8). For example, some proteins encoded by these ISGs work in concert to promote the cellular state for antiviral defense, such as stimulating and shaping innate and adaptive immune responses and inducing expression of restriction factors, thereby orchestrating viral clearance in infected and neighboring cells. A culmination of the robust antiviral defense provided by type I IFN has been shown in studies on IAV infection. As outlined in Sect. 3.7.4.5 and illustrated in Fig. 3.8b, type I IFN has been revealed to trigger necroptosis via activation of ZBP1. Also, type I IFNs, their signaling pathways, and ISGs play important roles in bacterial infections (for more information, see [166–168]). Another quality of a robust antibacterial/antiviral defense is provided by the release of constitutive DAMPs in terms of endogenous DNA and RNA from pathogen-induced RCD, which contribute to and overlap with these IFNdriven signaling pathways (Fig. 4.8; for type I IFNs, also compare Vol. 1 [18], Sect. 22.5.5.2, p. 535). Tumor necrosis factor also operates in an autocrine and paracrine fashion and triggers pleiotropic signaling by binding to its two receptors: TNFR1 and TNFR2.
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Fig. 4.8 Simplified schematic diagram of the promotion of a type I interferon-driven anti- pathogen defense response (exemplified by viral infections). On the left side of the figure: Cytosolic nucleic acid sensors (cGAS and RIG-I) recognize viral genomic DNA and RNA molecules (thought to operate as exogenous DAMPs) to trigger intracellular signaling cascades which transcriptionally induce the genes encoding type I IFNs. Denoted as endogenous inducible DAMPs, the type I IFNs act in an autocrine (not shown) and paracrine fashion by binding to their receptor IFNAR1/2. This results in activation of JAKs, which in turn activate STAT 1 and STAT2 to form a STAT1/2-IRF9 complex called ISGF3. Translocation of this complex in the nucleus leads to activation of expression of ISGs. Several ISGs have direct antiviral effects. Type I IFNs and ISGs are also involved in promoting defense responses against invading bacteria (on the center of the illustration). The same scenario can occur after recognition by cGAS and RIG-I of endogenous DNA and RNA in terms of constitutive DAMPs released from virus-induced host cell death (on the right side of the figure). cGAS cyclic GMP-AMP synthase, exog exogenous, IFNs interferons, IFNAR interferon-α/β receptor, IRF9 interferon regulatory factors 9, ISGs interferon-stimulated genes, ISRE interferon-stimulated response element, JAKs Janus kinases, MAVS mitochondrial antiviral signaling proteins, RIG-I retinoic acid-inducible gene (protein) I, STAT1/2 transcription factors signal transducer and activator of transcription1/2, STING stimulator of interferon genes, TYK2 tyrosine kinase 2. (Sources: [101, 166, 167])
Indeed, these receptor-triggered signaling pathways result in each potential cellular response, that is, canonical and non-canonical NF-κB activation as well as apoptosis and necroptosis as an additional source of DAMPs emission (compare Sect. 3.7.4.5 and Fig. 3.8b, as well as Vol. 1 [18], Sect. 19.2 and Figs. 19.2 and 19.3, pp. 429–435, and Sect. 19.3.2 and Figs. 19.4 and 19.5, pp. 436–442, and Sect. 22.5.7, pp. 544–546, as well as Vol. 2 [19], Sect. 4.3.3, pp. 131–133; for reviews, see [169–172]). Given these scenarios, it is easy to imagine that the production of both inducible DAMPs reflects a potential mechanism that can explain the development of infection into a life-threatening hyperinflammatory syndrome such as ARDS and sepsis (this emerging topic is presented in Sects. 5.4.6 and 5.5.5.2).
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4.3.6 Detection of Fungi by Cellular Pattern Recognition Molecules The innate and adaptive immune defense apparatus against invasive fungal infections—as against all other pathogens—is flexible and multifaceted and ranges from first-line nonspecific protective to sophisticated adaptive immune mechanisms [173]. And again, when these pathogens have successfully passed the physical/ chemical barriers, they are sensed by host PRMs. Depending on whether extracellular or intracellular fungi are involved, different PRMs get engaged. Detection of fungal pathogens has also been shown to be mediated by cell surface PRMs, including TLRs (TLR2, TLR4), and CLRs such as dectin-1 and DC-SIGN (for, dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin). These receptors sense fungal MAMPs such as β-glucans and mannose (N-mannan and O-mannan) respectively, located in the fungal cell wall to trigger downstream innate immune signaling pathways [174, 175]. In addition, CRs and FcRs were shown to assist in fungal sensing by detecting complement or antibody-bound fungal cells [175]. Also, there is already evidence (though sparse) that fungal NAs are sensed to trigger immune defense responses. For example, TLR9 was found to sense cryptococcal DNA to initiate the host defense against this infection [176, 177]. Notably, and again, like other pathogens that have survived the evolutionary arms race with mammals, C. Albicans was shown to have a remarkable capacity to adapt to the host environment and subsequently evade clearance by the immune system [178].
4.3.7 Detection of Parasites by Cellular Pattern Recognition Molecules The diagnosis of parasitic infections clearly shows that mammals sense these organisms via PRMs to trigger innate immune defense responses. Although such infections are usually harmless, some of them, for example, protozoan infections such as malaria, can be life-threatening for humans. Indeed, MAMPs coating the surface of protozoan parasites, for example, as studied on Plasmodium spp., Trypanosoma spp., and Leishmania, have been shown to be sensed by PRMs such as TLRs (TLR 2/1, TLR2/6), NLRs, and NA receptors (for further reading, see [6–10, 179, 180]). As a typical example of protozoal infections, a few aspects of malaria are touched on here. Three MAMPs derived from P. falciparum, namely GPI anchors, hemozoin (also called a danger signal because of its pathogen/host hybrid nature), and immunostimulatory NA motifs, are reportedly sensed by various PRMs, including TLRs (TLR2/1, TLR4), NLRs, and RLRs. In addition, the immunostimulatory CpG motifs of plasmodial DNA were found to be perceived by TLR9. Moreover, hemozoin crystals were demonstrated to activate the assembly of the NLRP3 inflammasome, while the parasite dsDNA reportedly activates the AIM2 inflammasome (reviewed in [8, 10]).
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Unlike other infectious agents, helminths are macropathogens, a condition that changes innate immune processes, such as altering sensing mechanisms and preventing them from being ingested by phagocytic cells. Helminth-derived MAMPs, like the other pathogen-associated MAMPs, are reportedly recognized by PRMs such as TLRs, CLRs, and NLRs. The topic has recently been thoroughly reviewed by Motran et al. [181]. In brief: Host DCs are involved in the recognition of helminths or their products and the subsequent initiation of T helper cell type 2 (Th2) development. Indeed, DCs are able to sense multiple so-called excretory/secretory antigens released by the parasites by expressing different PRRs (TLRs, CLRs, NLRs) involved in recognition of MAMPs (for further reading, see [181]). Indeed, these few examples impressively reflect the ability of mammals to perceive different infectious agents across the tree of life through specific PRMs that have emerged during evolution. The special role of malaria as a life-threatening, in Africa frequently fatal disease, has been taken as an impulse to take a closer look at this disorder in a separate section (Sect. 5.6).
4.3.8 Humoral Innate Immune Sensing of Pathogens Humoral innate immune sensing of pathogens is executed by soluble or fluid phase PRMs, which are heterogeneous in terms of structure, expression, and specificity. They can be subdivided into one pre-existing receptor, that is, natural immunoglobulin M (nIGM) antibodies [182], and a group of receptors produced by MAMP/DAMPactivated innate immune cells, including the complement component C1q, pentraxins, and collectins/ficolins. These soluble PRMs can be regarded as “hybrid proteins,” which, on the one hand, are able to recognize certain MAMPs and DAMPs, but on the contrary, when expressed and secreted upon infectious or sterile injury by a variety of MAMP/DAMP-activated innate immune cells, can operate in terms of inducible DAMPs to trigger innate immune responses. More specifically, they can act in terms of effectors and modulators of innate immune responses, such as regulation of complement activation, phagocytosis/opsonization of pathogens and apoptotic cells, and regulation of inflammation. These molecules are essential in pathogen recognition but also identification of nonself or altered-self molecular patterns on dying cells. Denoted as IIID DAMPs in this book (see Table 1.2), the crucial antimicrobial defense proteins are only briefly touched on here; for more information, compare Vol. 1 [18], Sect. 5.4, pp. 89–94, and Chap. 23, pp. 591–618; also see reviews, quoted in [183–187]. The recognition molecule C1q possesses the recognition motif for the Fc portion of antimicrobial IgM and IgG antibodies. However, evidence has also accumulated of antibody-independent activation of C1 via C1q binding to other exogenous molecules such as lipid A (of Gram-negative bacteria) and other constituents of bacteria and viruses, indicating a primary role of C1 in the detection of pathogens (discussed in [188, 189]). The pentraxin family encompasses three major members, CRP, PTX3, and serum-amyloid P component (SAP). The pentraxins recognize a wide spectrum of
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microbial moieties, including fungi, bacteria, and viruses, thereby mediating a number of antimicrobial effector mechanisms (e.g., opsonophagocytosis) (reviewed in [186, 190–193]). Collectins are a family of collagenous Ca2+-dependent CLRs such as mannose- binding lectins (MBL) and surfactant proteins A, B, C, and D (SP-A, SP-B, SP-C, and SP-D). These typical soluble PRMs are characterized by their inclusion of a collagen-like region linked to a Ca2+-dependent C-terminal carbohydrate recognition domain (CRD), also known as the CTLD, which recognizes structural sugar patterns. Collectins have the capacity to interact with carbohydrates and lipids exposed on pathogen surfaces, that is, bacteria, fungi, viruses, and parasites (for reviews, see [186, 190, 194]). Ficolins are a class of collagenous defense proteins containing collagen-like domains and fibrinogen-like domains. Three members of this family have been identified in humans: ficolin-1 (also called M-ficolin), ficolin-2 (also known as L-ficolin), and ficolin-3 (also known as H-ficolin or Hakata antigen). Through their fibrinogen-like domain, ficolins can recognize carbohydrates that are located on the surface of a wide spectrum of different types of microorganisms (reviewed in [186, 195, 196]). The humoral PRMs have recently gained attention as they have been shown to interact with SARS-CoV-2 [197]. In this study, of 12 PRMs tested, PTX3 and MBL were found to bind the viral nucleocapsid and spike proteins, respectively.
4.3.9 Epigenetic Regulation of Innate Immune Responses to Infections The topic of regulation of innate inflammatory responses has been covered in Vol. 1 [18], Chap. 24, pp. 635–653, and resumed with respect to inflammation and fibrosis in Vol. 2 [19], Sect. 5.6, Figs. 5.4, 5.5, 5.6, pp. 169–193 and Sect. 6.6, Fig. 6.4, pp. 237–245. In infections, an important point has to be added: we must distinguish between epigenetic dysregulation of host chromatin induced by the pathogen in favor of evasion of the immune system, on the one hand, and epigenetic counteraction/counterregulation of the host against these modifications, on the other side. For example, viruses use epigenetic reprogramming to complete their life cycles and evade host innate immune responses. In other words: the evolutionary arms race between mammals and pathogens goes on at the level of epigenetics as well. On the host side, as reviewed by Zhang and Cao [198], four epigenetic principles are involved in regulating the host innate immune response during infection: DNA methylation, histone modifications, chromatin structure and remodeling, and ncRNAs. The various epigenetic mechanisms operate and are tightly regulated throughout the course of an anti-pathogen cellular immune defense response after the detection of pathogens: at the level of PRR-triggered innate immune signaling pathways, the level of innate effectors, and, finally, the level of trained immunity (for in-depth information, see again [198]; for further reading, also see [199–205]).
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4.3.9.1 Trained Immunity in Infections A special form of epigenetic modifications, including DNA methylation and histone modifications that affect long-term transcriptional regulation, refers to the phenomenon of trained immunity that has already been briefly addressed in Vol. 1 [18], Sects. 24.2.4, pp. 642–645, and Vol. 2 [19], Sect. 3.7, pp. 100–102 and Sect. 10.5.2, pp. 478–479. The model holds that cells of the innate immune system such as monocytes, macrophages, DCs, and NK cells can establish a memory of past stimulation via a process of metabolic and epigenetic reprogramming that allows modifying their response (either hyperresponsive or hyporesponsive) upon secondary challenges with an infectious or sterile insult similar or unrelated to the first one [206, 207]. Of note, there is growing evidence suggesting that not only MAMPs such as those derived from microorganisms as contained in the BCG vaccine but also DAMPs such as oxLDL and OSE OxPLs are involved in the phenomenon of this emerging concept. Hence, the relevance of the model for infectious diseases lies in the proposal that its induction by whole-microorganism vaccines may represent an important tool for reducing susceptibility to infection. Accordingly, Netea et al. [208, 209] had proposed induction of trained immunity as an important host-directed approach in COVID-19 patients, which might lead to improved antiviral host defense as well as decreased systemic inflammation, ultimately leading to a better chance of a favorable outcome. Based on this proposal, a double-blind, randomized trial of BCG vaccination against COVID-19 in individuals at risk was conducted, indicating that BCG vaccination confers some protection against possible COVID-19 among patients older than 50 years with comorbidities [210]. Given their findings, the investigators concluded that BCG vaccination may be a promising approach against the COVID-19 pandemic. The topic of epigenetics will be resumed in the context of ADs in Chap. 7, Sect. 7.2.3.4.
4.4 MAMP/DAMP-Mediated Regulation of Defense Responses to Pathogens 4.4.1 Introductory Remarks Over a long period of time, infection-induced inflammation was thought to be solely due to the recognition of pathogen-derived MAMPs by PRR-bearing cells of our innate immune defense system. Current notions now hold that a vigorous innate immune response to an infectious insult is promoted by the detection of both conserved MAMPs derived from invading pathogens and DAMPs emitted and generated during pathogen-induced host cell stress/tissue damage. This and other achievements that emerged in the recent past have turned the scenario of infection into a sophisticated many-faceted event. Indeed, as can be easily understood from the two previous volumes of the book [18, 19], the MAMP/DAMP- triggered initiation and promotion of inflammatory responses, as well as the SAMP- driven resolution of inflammation, followed by DAMP-promoted repairing healing
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processes, reflect a complex network of interactions and interconnections among and between the various cellular, humoral, and molecular components of the innate immune system, acting in crosstalk with the different tissues. Moreover, there is growing support for the idea that DAMPs do not only participate in those complex inflammatory and adaptive immune defense responses but are even the key players in shaping the clinical outcome of infectious diseases. More precisely and as repeatedly mentioned throughout the tenor of the book: The primary, evolutionarily determined role of DAMPs (here: DAMPs + MAMPs)—in concert with the timely and adequate generation of SAMPs—is to elicit an adequate, controlled, and beneficially robust innate inflammatory defense response, aimed at eliminating the pathogens and restoring tissue homeostasis (described in this section). However, when DAMPs are generated and emitted uncontrolled, that is, acute repetitively or continuously, or in excess, they lead to infectious pathologies in the form of chronic inflammatory (e.g., autoimmune) or hyperinflammatory acute diseases.
4.4.2 Multiple-Level Mechanisms to Regulate Infectious Inflammation To prevent those potentially life-threatening pathological processes, the innate immune responses to pathogens are tightly regulated at multiple cellular and molecular levels. Gene-specific but epigenetically controlled transcriptional regulation of the inflammatory response begins at the level of PRM-expressing innate immune cells (see Vol. 1, [18], Sect. 24.2, Fig. 24.1, pp. 636–649; and Vol. 2 [19], Sect. 5.6, Figs. 5.4, 5.5, and 5.6, pp. 169–193 and Sects. 6.6.2 and 6.6.3, Fig. 6.4, pp. 238–244). In fact, accumulating evidence has shown that innate immune cells, such as monocytes, macrophages, DCs, and NK cells, can be influenced by encounters with injurious → inflammatory stimuli, undergoing functional reprogramming, and developing changed responses to subsequent challenges [211]. And excitingly, increasing evidence suggests that DAMPs may drive epigenetic modifications [212–214]. Following recognition of MAMPs and DAMPs, the cells—via PRM-triggered, PTM-regulated molecular signaling pathways (exerting complex interplay among each other)—secret cytokines, chemokines, proinflammatory lipid mediators, and adhesion molecules to orchestrate robust inflammatory processes (for PTMs influencing PRM-triggered signaling, see Vol. 1, [18], Sect. 24.3, Fig. 24.2, pp. 646–649; also compare the review of Liu and Cao [215]). The scenario is accompanied by further defense mechanisms such as complement activation, phagocytotic activities, and secretion of AMPs, as well as activation of ILCs, unconventional T cells, and DCs translating innate immune to adaptive immune events: all processes dedicated to the clearance of the pathogens. Given the comprehensive description of this whole scenario in Vols. 1 and 2 of the book, only a few more points on this topic are resumed in a condensed form in the following sections.
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4.4.3 MAMP/DAMP-Triggered Initiation and Promotion of Infectious Inflammation 4.4.3.1 General Remarks The modern fundamentals of MAMP/DAMP-initiated promotion of pathogen- induced inflammation and their regulation have already been covered in Vol. 1 [18], Chaps. 21–28, pp. 473–706, and Vol. 2 [19], Sect. 5.2, p. 152. As outlined there, the dynamics of the infectious inflammatory response begin with the recognition by PRMs (located on/in innate immune cells) of both the MAMPs derived from the invading pathogens and the DAMPs whose emission is provoked by them. The unique scenario here is that DAMPs, like MAMPs, are also recognized by cellular and humoral PRMs, and, to a great extent, utilize the same signaling pathways to activate the innate immune system. This implies that the main players in mounting an infectious inflammatory milieu, that is, the PRM-expressing cells of our innate immune system that are initially localized at the site of primary infection, possess the unique capacity to sense simultaneously—and thereby getting activated by— both pathogen-derived exogenous molecules and host-generated endogenous molecules. 4.4.3.2 PRM-Bearing Cells Regulating Proinflammatory Responses to Pathogens Indeed, the family of mobile and sessile cells of the innate immune system can be regarded as a unique organ of perception that is alert in all types of infections (for a comprehensive description of innate immune cells, see Vol. 1 [18], Part III, pp. 113–187; also compare [122, 216–218]). In brief, the PRM-bearing mobile cells include leukocytes, macrophages, mast cells, and DCs, as well as ILCs such as NK cells, and unconventional T cells such as natural killer T cells (NKT) cells, mucosal- associated invariant T (MAIT) cells, and gamma delta T cells (γδ T cells). The PRM-bearing sessile tissue-resident cells encompass a variety of somatic cells, including epithelial cells, ECs, fibroblasts and myofibroblasts, vascular cells, chondrocytes, osteoblasts, osteoclasts, and adipocytes. Macrophages (in their polarization to M1- or M1-like macrophages) and PMNs (in analogy to macrophages, also sometimes called N1- or N1-like neutrophils [219, 220]) have been identified as the main players of mobile cells during infectious inflammation (for more information on M1-like macrophages, see Vol. 1 [18], Sect. 8.2.2.2, Fig. 8.2, pp. 117–119; and some more recent reviews [221– 224]). In fact, PMNs are regarded as the body’s first line of defense against invading pathogens, which they fight by using an array of diverse antimicrobial effector mechanisms ranging from phagocytosis, the release of both granules and NADPH-dependent ROS, up to the formation of NETs. Leukocyte recruitment in postcapillary venules in many tissues generally follows a multistep pathway: rolling, arrest, firm attachment, and transmigration, known as the process of leukocyte-endothelial interaction (described and illustrated in Vol. 1 [18], Sect. 22.2.2 and Fig. 22.2, pp. 477–480; for a recent review see [225]). Like neutrophils, macrophages, in their polarization to proinflammatory M1-like
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macrophages, possess diverse functions including phagocytosis of pathogens, infected debris, and dead cells; production of different proinflammatory cytokines; and microbial antigen presentation (see Vol. 2 [19], Sect. 5.3.2.3, pp. 155–156). Sessile cells, such as epithelial cells and ECs execute defense responses to pathogens as well. For example, respiratory epithelial cells were shown not only to serve as a physical and chemical barrier to influenza virus infection but also to produce type I IFNs and proinflammatory cytokines [226]. Likewise, to cite just one example out of many, human brain microvascular ECs, stimulated by a Streptococcus species, were found to release proinflammatory cytokines and chemokines [227]. The broad range of cytokines exerts distinct functions that confer the typical clinical features of inflammation. For example, proinflammatory cytokines such as IL-1β, TNF, and IL-6 operate as endogenous pyrogens by increasing the hypothalamic thermoregulatory set-point (“fever”) [228]. The cytokine IL-1β has been shown to provoke inflammatory hyperalgesia (“dolor”) [229], whereas TNF was found to mediate multiple hallmark signs of inflammation by inducing local vasodilation (“rubor,” “calor”) and vascular leakage associated with tissue swelling (“tumor”) [230, 231]. Moreover, depending on the nature of the invading pathogen, the PRMtriggered cytokine pattern varies. Thus, bacterial and fungal infections induce the production of proinflammatory cytokines such as TNF, IL-1, IL-6, and IL-8 predominantly; viruses evoke predominantly the generation of type I IFNs, whereas parasites (e.g., helminths) result in the production of IL-4, IL-5, and IL-13 by mast cells, basophils, and eosinophils (for details of inflammatory mediator substances of the innate immune system, see Vol. 1 [18], Sect. 22.5 and Fig. 22.12, pp. 527–556).
4.4.3.3 Impact of Phagocytosis on Pathogen Elimination The topic of phagocytosis has been addressed in Vol. 1 [18], Sect. 22.6.3, Fig. 22.15, pp. 560–563. Phagocytosis is defined as the ingestion by cells of large (>0.5 μm) particles. Foreign bodies such as bacteria or fungi are cleared from infectiously damaged tissue by professional phagocytes. Notably, phagocytosis is a receptor- mediated event. Thus, in parallel to the PRM-triggered signaling machinery, which may initiate or at least promote and enhance their phagocytic activities, phagocytes use other sets of “entry receptors” for the engulfment of material. In infections, microbial bodies, via direct binding of MAMPs, are predominantly taken up by members of the CLR family, including Dectin-1/2, Mincle (for macrophage- inducible C-type lectin or CLEC4E), and DC-SIGN (for these receptors, see Vol. 1 [18], Sect. 5.2.7 and Fig. 5.6, pp. 60–66; for a recent review, see [232]). For example, Dectin-2, which recognizes high-mannose polysaccharides, was recently shown to be involved in phagocytosis by DCs of the fungus Cryptococcus neoformans [233]. However, it is worth noting that this is just one example of many other mechanisms involved in the phagocytosis of microbial pathogens. For more information, in particular, on the action of other phagocytic receptors used by professional phagocytes, see, for instance, Ref. [232].
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4.4.3.4 Humoral Innate Immune Effector Responses: The Complement System Humoral innate immune effector responses play an integral part in antimicrobial defense. Given their description in Vol. 1 [18], Chap. 23, Fig. 23.1, pp. 591–634, the topic is resumed here only in keywords. This crucial defense system is dominated by the function of the complement system—a considerably complex fluid-phase and membrane-bound system of proteins—that is activated upon recognition of “activators” in terms of MAMPs expressed on invading pathogens, as well as DAMPs either associated with ICs (Subclass IIB-1 DAMPs = neoantigens/neoepitopes) or emitted by damaged/dying cells in the extracellular environment (e.g., Subclass IIB-4 DAMPs). Activation of the complement system is instigated via three convergent pathways, the classical pathway, the lectin pathway, and the alternative pathway. The resulting terminal proteolytic cascade tags those complement “activators” for elimination (i.e., removal of pathogens or dying cells) and promotes an innate proinflammatory response via various mechanisms, including the elaboration of the complement peptides, the anaphylatoxins C3a and C5a, denoted as inducible DAMPs in this book, as well as the activation of the terminal C5b-9 complement complex, which forms the membrane attack complex (MAC) if inserted into a membrane. The classical pathway is initiated by C1q binding to antigen-antibody complexes on the surface of pathogenic microbes or by direct binding of C1q to the microbial protein or to the virion itself. Notably, C1q binding to neoantigen/nIgM antibody complexes instigates this pathway during scenarios of non-infectious, sterile cell stress/tissue injury. The lectin pathway is triggered by collectins, in particular, by their member MBL, as well as ficolins which recognize carbohydrates on cell surfaces. Certainly, both pathways have a critical role in pathogen recognition and initiation of the complement cascade. However, due to a usual lack of complement regulators on microbes, the response is rapidly amplified by the alternative pathway and results in opsonization, proinflammatory signaling, mobilization of immune cells, phagocytosis, and, on specific pathogens such as Gram-negative bacteria or parasites, the formation of the terminal complement complex and subsequent cell lysis. In fact, in this way, the alternative pathway assures more than 80% of the terminal complement activity during pathogen recognition (for further reading, see [234–240]).
4.4.4 The Model of SAMP-Driven Resolution of Inflammation 4.4.4.1 General Remarks Current notions from modern inflammation research hold that resolution of inflammation is a tightly regulated multifactorial event that is characterized by the involvement of phenotypic, functional, regulatory, and epigenetic mechanisms. Unique regulating molecules, the SAMPs, convey, in parallel to DAMP-triggered proinflammatory responses, antiinflammatory/proresolving processes, and shape
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immunosuppressive responses. The molecules include—as listed in Sect. 1.2.4.3 and Table 1.2—but are not limited to AnxA1, SPMs, PGE2, cAMP, extracellular adenosine, and Ang(1-7) (for more information, see Vol. 1 [18], Sect. 14.4, pp. 330–338, and Sect. 22.2.3, pp. 480–482, and Vol. 2 [19], Sect. 5.3, Fig. 5.1, pp. 152–160; as well as [241–244]). Here, in a nutshell, a few typical aspects of this emerging topic are briefly resumed.
4.4.4.2 Death of Inflammatory Cells and the Process of Efferocytosis After the recruitment of inflammatory innate immune cells into pathogen-injured tissue, a peak of influx will be reached that is followed by the clearance of these cells: the start of resolution resulting in the final restoration of functional homeostasis. Under normal physiological, that is, homeostatic conditions, inflammatory cell clearance is initiated by apoptosis as a form of “noninflammatory” RCD that avoids the release of DAMPs (reviewed in [245, 246]; also see Vol. 1 [18], Sect. 19.2, Fig. 19.3, pp. 429–435). Apoptotic cells then are finally cleared by phagocytosing cells in a process known as efferocytosis (for additional information also compare Vol. 1 [18], Sect. 22.6.3.3, p. 562 and Vol. 2 [19], Sect. 5.3.2.2, pp. 154–155; for reviews, also see [247–252]). This scenario is thought to apply most often to mild/ moderate-running infectious diseases that heal promptly up in a timely manner. 4.4.4.3 Participation of M2 Macrophages and N2 Neutrophils in Inflammation Resolution Neutrophils and macrophages are not only PRM-bearing innate immune cells to promote inflammation but are also involved in its resolution, resulting in tissue repair. Thus, the appearance of “antiinflammatory proresolving M2-like macrophages” is a characteristic sign of resolution. This transition from proinflammatory (classically activated) M1-like macrophages to antiinflammatory (alternatively activated) M2-like macrophages is a unique feature of macrophage plasticity that is transcriptionally [253], immunometabolically [254], and epigenetically [255, 256] regulated. M2-like macrophages—under epigenetic control, e.g., by histone methyltransferases (HMTs)—respond to IL-4/IL13 and IL-10 and are mainly characterized by secretion of a variety of antiinflammatory mediators such as IL-10 and TGF-β1 [257] as well as chemokines such as chemokine C-X-C motif ligand 10 (CXCL10), CXCL16, and chemokine (C-C motif) ligand 5 (CCL5) [258] (for chemokines and their receptors, see Vol. 1 [18], Sect. 22.5.11 and Table 22.1, pp. 552–555). Also, they express cell-surface receptors like programmed death- ligand 1 (PD-L1) and PD-L2 that play significant roles in suppressing the immune system and quieting the inflammation (for additional information, see also Vol. 1 [18], Sect. 33.3.5.4, p. 807 and Vol. 2 [19], Sect. 5.3.2.3, pp. 155–156). Similar to the scenario of M1-like to M2-like polarization, the transition of proinflammatory N1-like neutrophils into inflammation-resolving N2-like neutrophils has gained increasing attention in the research field of inflammation resolution [259]. In fact, N2-like neutrophils—in analogy to M2-like macrophages—are believed to exert inflammation-resolving and immunosuppressive capabilities (also compare [260]) and have recently been shown to operate in preclinical infection and tumor models [261–263].
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4.4.4.4 SAMP-Driven Resolution of Inflammation in Infectious Disorders Notably, this principle of SAMPs-driven regulation of innate immune responses to restore and maintain homeostasis has also been shown to the resolution of pathogen- induced inflammation [15, 264–266]. Indeed, SAMPs such as AnxA1 [267] and SPMs [268] have been successfully tested for inflammation-resolving properties in several models of infections. A comprehensive review of the role of SPMs in this field has recently been published by Sandhaus and Swick [269]. In bacterial infections, the implication of SPMs has been intensely examined in periodontitis [270, 271]. Thus, in pre-clinical studies on models of experimental periodontitis, the exogenous application of SPMs could be shown to prevent and regenerate significantly alveolar bone loss. Moreover, in two studies, the positive shift in microbial composition, in line with a positive shift in inflammatory status, could be demonstrated (reviewed in [272]). The SPMs have also been studied in various preclinical models of viral infection, including influenza virus infection [273], HSV-induced keratitis [274], and RSV infection [275] (for reviews, see [269, 276]). Overall, this family of SAMP was found to exert strong protective and inflammation-resolving effects. In Chap. 5, Sects. 5.4.2.4 and 5.5.4 the topic will be resumed by focusing on the role of SPMs in COVID-19 and bacterial sepsis. 4.4.4.5 Concluding Remarks Research on SAMP-driven resolution of inflammation in infectious disorders is in full swing, as documented by recent reviews on the role of SPMs and SPM mimetics as agonists of SPM receptors in bacterial and viral infections [276, 277]. Indeed, there is mounting evidence from preclinical studies with various bacterial and viral pathogens that SAMPs, in particular, SPMs, were demonstrated to facilitate pathogen contamination, lower antibiotic requirement, prevent complications such as SARS-CoV-2 cytokine storm, and increase survival in life-threatening infectious diseases. Further significant findings can be expected from ongoing studies which promise new insights into this emerging topic in infection research. For example, recent studies from inflammation research suggest that the process of inflammation resolution is not the end of innate immune responses to infection but that there is further immunological activity during the phase following the resolution cascade (for detailed information, see review under [242]).
4.5 Innate Lymphoid Cells and Unconventional T Cells in Infections 4.5.1 Introductory Remarks Innate lymphoid cells have been covered in Vol. 1 [18], Sect. 8.4, pp. 134–140, and the activation and function of these “ready-to-go” cells, including their activation by DCs—in terms of a bi-directional crosstalk with MAMP/DAMP-activated DCs—, has been extensively described and illustrated in Vol. 1 [18], Sect. 27.2. Figs. 27.1 and 27.2, pp. 665–680. The unconventional T cells have been covered in Vol. 1 [18],
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Sect. 8.5 and Fig. 8.4, pp. 141–148, and their activation and function have been described in Vol. 1 [18], Chap. 28, pp. 693–706. Here, and in a nutshell only, the role of some ILC subsets, NKT cells, MAIT cells, and γδ T cells in infections should be resumed and addressed.
4.5.2 Innate Lymphoid Cells 4.5.2.1 General Remark The ILCs have recently been proposed by Vivier et al. [278] to reclassify into five subsets: NK cells, ILC1s, ILC2s, ILC3s, and LTi, which has now been approved by the International Union of Immunological Societies [278]. The NK cells are the oldest member of the ILC family and represent the only cytotoxic ILCs. The unique cells are crucial for defense against a wide variety of pathogens. Non-cytotoxic ILCs refer to ILC1, ILC2, and ILC3 in general. Similar to NK cells, ILC1s promote type 1 immune responses against intracellular pathogens (viruses, certain bacteria) via the production of IFN-γ and TNF. However, ILC1s lack perforin-dependent cytotoxicity, but they are able to kill target cells via alternative pathways, such as TNF receptor-mediated induction of apoptosis. The ILC2s, regulated by SPMs such as MaRs or LXA4, which are secreted to resolve inflammation, secrete cytokines, such as IL-4, IL-5, and IL-13 and are involved in the innate immune defense response to parasites, such as the helminth. After resolving the infection, ILC2s help to repair damaged tissues by producing amphiregulin (AREG). ILC3s combat extracellular microbes, such as bacteria and fungi (reviewed in [278, 279]). As said, NK cells are critical for defense against a wide variety of pathogens by cytotoxicity and cytokine-mediated effector functions. The immune recognition properties of NK cells within the innate immune defense system depend to a large extent on the interaction between immunoreceptors (including, among others, the natural cytotoxicity receptors (NCRs) and natural killer group 2D (NKG2D); for recognition receptors of ILCs, see Vol. 1 [18], Sect. 5.3.7 and Figs. 5.12 and 5.13, pp. 82–87). These receptors recognize corresponding ligands, including host cell stress-induced IB-2 DAMPs (MICA/B and ULBP 1-6) (see Vol. 1 [18], Sect. 12.3.3, pp. 249–251; also compare [280]). 4.5.2.2 Natural Killer Cells in Viral Infections Natural killer cells represent the first line of defense against viral infections. Activated by virus-induced IB-2 DAMPs (besides other mechanisms not alluded to here), they convey unique mechanisms to restrict the distribution of viruses, including lysis of virus-infected cells, releasing them, and exposing them to an adaptive immune response. In addition, NK cells were shown to produce inflammatory cytokines, such as IFN-γ, to slow down viral growth (described in Vol. 1 [18], Sect. 27.2.3.3, p. 672, for further information, see [281–284]). Notably, evidence of virus-induced IB-2 DAMPs has been reported. For example, HCMV infection was shown to lead to the upregulation of these DAMPs (MICA, MICB, and ULBPs) on human cells [285, 286]. Also, in studies on an in vitro model for the early activation
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of human NK cells during the innate immune response to influenza infection, NK cell activation was demonstrated to rely on influenza-induced IB-2 DAMPs (ULBP1-3) expressed on infected DCs and recognized by NKG2D (besides other activating signals not mentioned here) [287] (for NK cell-DC crosstalk in viral infection, see also [288]).
4.5.2.3 Natural Killer Cells in Bacterial Infections In the last decade, an increasing amount of evidence has been accumulated in support of the notion that NK cells are major players in the host response to bacterial infections as well (also briefly described in Vol. 1 [18], Sect. 27.2.3.6, p. 676). Indeed, NK cells were shown not only to inhibit the spreading of viruses but also some species of intracellular bacteria by lysing those infected cells and hindering their growth by secretion of cytokines such as IFN-γ and TNF (reviewed in [281, 289]). For example, NK cells were shown to kill Burkholderia cepacia complex via a contact-dependent and cytolytic mechanism [290]. Also of considerable importance are the observations that NK cells fight against bacteria by releasing and exposing them to adaptive cell-mediated immune attacks [291]. Indeed, as stressed elsewhere [292], emerging data have shown that this capability to mount a potent adaptive immune response against invading bacterial pathogens is a critical maneuver to prevent the development of bacterial sepsis. 4.5.2.4 Natural Killer Cells in Fungal Infections It has been known for several years that patients with well-controlled invasive aspergillosis show significantly higher NK cell counts compared to patients with poor outcomes [281, 293]. This clinical data supported the experimental findings of NK cells to exert both direct and indirect antifungal activity through (1) cytotoxic molecules, cytokines, and interferons; (2) phagocytosis; as well as (3) modulating an antifungal host adaptive immune response (reviewed in [294]). For example, there is increasing evidence from animal studies and clinical data indicating that NK cells play an important role in the host response to Aspergillus spp. (reviewed in [295]). 4.5.2.5 Innate Lymphoid Cells Group 2 in Parasite Infections The role of inflammatory ILC2s in antihelminth immunity has recently been comprehensively reviewed by Miller and Reinhard [296]. As known, repeated infections and chronic colonization by these large extracellular worms in mammals led to the evolution of type 2 immunity characterized by the production of distinct cytokines (IL-4, IL-5, and IL-13). Besides the action of ILC2s contributing to parasite resistance, adaptive immunity is necessary for completely expelling most helminths and for preventing reinfection. By contrast, the activation of Treg cells promotes tolerance against the parasite, preventing overt host pathology (reviewed in [297]). For example, in Nippostrongylus brasiliensis infection in mice, it is the subset of inflammatory ILC2s that has been shown to migrate to the lungs early after the infection and to be potent early producers of type 2 cytokines (for further in-depth information, see [296]).
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While the role of inflammatory ILC2s in helminth infection is clear, there have been few studies demonstrating their appearance in other infection or disease models. Nevertheless, further studies in this interesting field of infection can be expected.
4.5.2.6 Concluding Remarks Together, there is a clear role of NK cells in combatting human infectious diseases, in particular, protection against virus infection. But here again, it is timely to point out a topic that is not the subject of this part of the volume: the mechanisms by which pathogens escape NK cell attack. For example, viruses have evolved numerous strategies to evade NK cell effector functions. One of these evasion strategies is the manipulation of NK cells through direct infection [298]. Another example refers to HCMV, which expresses several proteins that downregulate the expression of NKG2D ligands, including UL16, UL142, and several additional proteins (reviewed in [285]). That this phenomenon appears to be distributed across all pathogens is indicated by other lines of in vitro coculture studies with NK cells and A. fumigatus, suggesting that A. fumigatus-mediated NK cell immunoparesis may represent an important mechanism of immune evasion during pulmonary aspergillosis [299].
4.5.3 Unconventional T Cells 4.5.3.1 General Remarks These innate-like T cells include (1) CD1-restricted αβ T cells, known as NKT cells, divided into type I NKT cells, sometimes referred to as invariant NKT (iNKT) cells, and type II NKT cells, also known as “diverse NKT cells”; (2) MHC-I-related molecule 1 (MR1)-restricted MAIT cells; (3) MHC class Ib-restricted T cells such as Qa-1-, Qa-2-, and M3-restricted T cells; and (4) γδ T cells. The characteristic feature of some of these TCR-bearing T cell subsets assigning them to the family of innate immune cells is their equipment with NK markers, for example, the activating receptor NKG2D. As mentioned, this receptor can sense DAMPs such as MICA and MICB exposed on stressed or altered cells (cf. Fig. 8.4 in Vol. 1 [18], p. 142). 4.5.3.2 Invariant Natural Killer T Cells Invariant NKT cells, their activation, and function have been addressed in Vol. 1 [18], Sect. 8.5.2.2, p. 142 and Sect. 28.2, pp. 694–698. These CD1-restricted αβ T cells play an important role in the detection of various pathogens, including Pseudomonas aeruginosa, Streptococcus pneumoniae, Salmonella typhimurium, Mycobacterium tuberculosis, Listeria monocytogenes, and Borrelia burgdorferi. Thanks to their capability to produce large quantities of cytokines, they can augment both innate and adaptive immune responses, thereby providing protection against disparate microbial pathogens (reviewed in [300–302]). Several activation mechanisms of iNKT cells by microbial pathogens have been reported, including microbial glycolipid-mediated TCR activation, endogenous antigen-mediated weak TCR stimulation with concomitant inflammatory cytokine-mediated stimulation, and activation solely by inflammatory cytokines (reviewed in [302]). Hence, in
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infections, cytokines produced by MAMP/DAMP-activated innate cells may be critical players in NKT cell activation. From the perspective of this book, however, one should not forget another pathway, namely, the direct IB-2 DAMP-induced, TCR-independent activation of NK-like cytolysis and costimulation of activation by CD1d performed by the NKG2D receptor (see [303], also quoted in [304]).
4.5.3.3 Mucosa-Associated Invariant T Cells The MAIT cells, their activation, and function have been briefly addressed in Vol. 1 [18], Sect. 8.5.3, p. 144, and Sect. 28.3, pp. 698–700. These innate-like T cells are involved in antibacterial immunity. A large variety of bacterial, mycobacterial, and fungal (but not viral) pathogens have been shown to activate MAIT cells in vitro. Activation of MAIT cells is usually provided by recognition of riboflavin derivatives/intermediates presented by MR1-expressing APCs, in conjunction with costimulatory signals from specific cytokines or TLRs. Alternatively, MAIT cells have also been demonstrated to be activated TCR-independently by cytokines and type-I IFNs, assuming that MAIT cells can also respond to viruses (for reviews, see [300, 305]). Also, and interestingly, the first evidence has been reported suggesting that IB-2 DAMPs such as MICA, via recognition by NKG2D, might provide a signal sufficient to activate MAIT cells and increase their function [306]. Typically, in infectious diseases, they promote a more rapid response to pathogens and shorter time to effector function in vivo than conventional MHC-restricted T cells (for reviews, see [300, 305]). 4.5.3.4 Gammadelta T Cells The γδ T cells, their activation, and function have been addressed in Vol. 1 [18], Sect. 8.5.4, p. 145 and Sect. 28.4, pp. 701–705. The cells have been shown to have diverse functions in various infectious diseases (reviewed in [300, 307]). Characteristically, these cells—via their γδ TCR and without restrictive MHC molecules—recognize various types of antigens, including microbial phosphoantigens and stress-related self-phosphoantigens. Interestingly, recent studies on a subset of human γδ T cells (V9γ/Vδ2 T cells) identified butyrophilin 2A1 as a direct ligand for V9γ/Vδ2 TCR and critical mediator/potentiator of phosphoantigen sensing (for detailed information, see the two seminal articles cited at [308, 309]). Another possibility of γδ T cell activation that cannot be ruled out is the recognition of infectious cell stress-induced IB-2 DAMPs via the NKG2D receptor (also expressed on these unconventional T cells). For example, MICA/B and ULBPs expressed on stressed cancer cells were shown to be sensed by Vδ1 T cells, Vδ2 T cells, or Vγ9Vδ2 T cells in an NKG2D-dependent manner [310–312]. Thus, one may think of the unproven possibility that virus-induced cell stress, via this mechanism, may alert γδ T cells to fight against viral infections. Notably, increasing evidence indicates that γδ T cells operate as a link to connection innate with adaptive immune responses, whereby, remarkably, they can function as APC to present pathogen infection-associated antigen to CD4+ and CD8+ T cells. In addition, γδ T cells contribute to the fight against infections via the elimination of pathogenic invaders, on the one hand, and tissue repair, on the other hand, in
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terms of producing cytokines, chemokines, and conveying other antimicrobial/antiviral activities (reviewed in [307]).
4.6 DAMP-Shaped Adaptive Immune Responses to Pathogens 4.6.1 Introductory Remarks The recognition process of the first pathogenetic momentum in the development of infectious diseases includes the concept that the interplay between MAMPs and DAMPs also shapes and controls protective, pathogen antigen-specific adaptive immune responses. Such a model includes the notion that MAMPs, constitutive DAMPs, and inducible DAMPs, on the level of their recognition by PRMs expressed on/in host DCs, closely and intensely interact and collaborate with each other; a concept that has already been alluded to above in Sect. 4.4.4. In fact, DCs are located at strategic positions at sites of pathogen entry, where they continuously sample the environment for invading pathogens (for function and subsets of DCs such as cDCs and pDCs, see Vol. 1 [18], Sect. 8.3, pp. 129–134, for a recent review, see [313]). Engulfment of antigens in combination with the recognition of MAMPs and DAMPs is thought to trigger the maturation of PRM-bearing immature DCs (iDCs) into immunostimulatory APCs that continue the innate immune defense program against pathogens by orchestrating responses in the adaptive arm of our immune system. The unique role of DCs in innate immune pathway-driven adaptive immune responses, in general, has been comprehensively described and illustrated in Vol. 1 [18], Chaps. 30–32, pp. 717–781, by focusing on antigen uptake, processing, and presentation as well as DAMP-induced maturation of immunostimulatory DCs (for reviews, also see [314–316]). Here, only a few aspects in relation to pathogen- induced adaptive immunity are briefly resumed.
4.6.2 Pathogen-Derived Antigens The specificity of adaptive immune responses to human pathogens is determined by antigens inherent and unique to each pathogenic invader. Bacterial antigens can be divided into protein and polysaccharide antigens. Proteins, in most instances, are defined as T-cell-dependent antigens, that is, antigens that activate B cells with the need for cognate T-cell help. Polysaccharides such as glycoproteins or glycolipids are usually T-cell-independent antigens, that is, antigens that directly activate B cells, without the need for cognate T-cell help (also see [317, 318] and compare Vol. 1 [18], Sect. 32.6, p. 775). Viral antigens refer to envelope proteins such as the spike protein of SARS- CoV-2 and the surface glycoproteins, HA and NA, of IAV (cf. Figs. 2.10 and 2.11). Viral antigens have considerable implications for viral virulence and vaccination procedures because they can change. For example, Influenza viruses are known to
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undergo antigenic evolution through antigenic drift and shift in their surface glycoproteins (further reading, see [319]). A comprehensive description of antigens derived from pathogens is beyond the scope of this book. Instead, the reader is referred to review articles in textbooks such as listed in Sect. 2.10.
4.6.3 Uptake, Processing, and Presentation of Bacterial and Viral Antigens by Dendritic Cells 4.6.3.1 General Remarks Antigen uptake, processing, and presentation by DCs have been outlined and illustrated in Vol. 1 [18], Chap. 31, and Figs. 31.1, 31.2, 31.3, 31.4, and 31.5, pp. 723–748. In particular, presentation and cross-presentation of both exogenous and endogenous antigens were highlighted. Here, a few remarks on this topic, as presented in Vol. 1, are repeated by focusing on bacterial and viral antigens as typical exogenous antigens. 4.6.3.2 Bacterial Antigens Extracellular bacterial antigens are internalized by pathways such as receptor- mediated endocytosis, phagocytosis, and macropinocytosis. Following, they are processed by DCs into peptides and then primarily and typically presented in the form of antigenic peptides on major MHC-II (i.e., pMHC-II) molecules to be recognized by antigen-specific CD4+ T cells. In fact, MHC-II-restricted antigen presentation is essential for CD4+ T cell-dependent immune responses. Thus, recognition of pMHC-II by CD4+ T cells stimulates their activation and differentiation into CD4+ Th cell subsets and also mediates interactions between antigen-specific B cells and Th cells [320]. However, the presentation of exogenous peptides derived from bacterial antigens on MHC-I molecules is also essential, namely, for the initiation of CD8+ T cell responses against these extracellular bacteria. This is usually executed by specialized/committed APCs like DCs. The process is referred to as cross- presentation, that is, a noncanonical MHC-I presentation that is crucial for the generation of CTL responses (also see [321, 322]). Mechanistically, two main pathways of antigen cross-presentation in DCs have been proposed: the cytosolic pathway and the vacuolar pathway (for details, see Vol. 1 [18], Sect. 31.3.5 and Figs. 31.5, pp. 740–743). 4.6.3.3 Viral Antigens Exogenous viral antigens engulfed by noninfected bystander DCs are, like exogenous bacteria, also presented in the form of viral peptides on MHC-II molecules to be recognized by antigen-specific CD4+ T cells and cross-presented on MHC-I to be recognized by antigen-specific CD8+ T cells. On the contrary, DCs infected themselves with a virus use endogenously synthesized viral proteins/peptides as antigens for presentation in MHC class I to promote a robust CD8+ CTL response, crucial for effective viral clearance (also see [322–324]).
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4.6.4 Maturation of Immunostimulatory Dendritic Cells in Infection 4.6.4.1 General Remarks In Vol. 1 [18], Chap. 32, and Figs. 32.1, 32.2, 32.3, 32.4, 32.5, 32.6, and 32.7, pp. 749–781, the scenario that antigens in the presence of DAMPs trigger the development of immunostimulatory DCs to promote destructive adaptive immune responses was comprehensively presented. In a nutshell: A conceptual model was presented proposing that the generation of immunostimulatory DCs is the work of collaborating DAMPs: (1) DAMPs triggering PRM-mediated pathways to induce DC maturation directly; (2) DAMPs facilitating antigen engulfment to promote DC maturation; (3) DAMPs providing the second signal for NLRP3 inflammasome activation to contribute to inflammation-dependent DC maturation; (4) DAMPs activating NK cells that assist in DC maturation; and (5) DAMPs binding to natural IgM antibodies to activate complement. As already introductively outlined and illustrated in Sect. 1.3 and Fig. 1.2, immunostimulatory DCs are characterized by (1) transient upregulation of MHC-II synthesis (signal 1) followed by its near shutdown; (2) upregulation of T cell costimulatory molecule expression at their surface (the most important signal 2); and (3) secretion of proinflammatory T cell-polarizing cytokines (signal 3) and chemokines. It is worth noting here that this metamorphosis of iDCs into immunostimulatory DCs is accompanied by profound changes in cellular metabolism that are integral and essential to the activation process. Thus, as outlined in Vol. 1 [18], Sect. 35.2, and Fig. 35.1, pp. 837–840, the metabolism of activated DCs changes from mitochondrial oxidative phosphorylation (OXPHOS) fueled by the β-oxidation of lipids to aerobic glycolysis, the “Warburg metabolism.” 4.6.4.2 The Professional Properties of Matured Dendritic Cells The matured DCs now have the ability to migrate from the periphery through the lymph to draining lymph nodes. In the secondary lymphoid organs, mature DCs function as the prototype of professional APCs able to efficiently present and cross- present (!) exogenous antigens captured at the time of activation and to activate naïve T cells (also see [325]). Induction of generation and emission of immunostimulatory DCs by antigens in the presence of DAMPs to promote adaptive immune responses has been documented in many studies. In particular, in oncoimmunological studies on ICD, the powerful capacity of constitutively expressed and inducible DAMPs (e.g., HMGB1, CALR, eATP, and type I IFN) to induce immunostimulatory DCs could be impressively documented (reviewed in [326]). Notably, accumulating evidence collected from a survey of the literature gives rise to designing a model showing the collaboration of various subclasses of DAMPs in the generation of immunogenic DCs, including IA-1/2 DAMPs, IB-2 DAMPs, and IIC-4 DAMPs (see Fig. 32.3 in Vol. 1 [18], Sect. 32.3.2, p. 758). Given the various scenarios in the release of DAMPs from cells succumbing to different subroutines of pathogen-induced RN (Fig. 1.1), the role of these molecules
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such as HMGB1, S100 proteins, eATP, DNA, and RNA in promoting immunostimulatory DCs in infection—this time in collaboration and interplay with MAMPs [327]—can be firmly assumed (also discussed in [328]). Moreover, inducible DAMPs such as TNF and type I IFN secreted by MAMP/DAMP-activated cells during infection have been shown in other lines of studies to promote DC maturation [329, 330]. A few examples should underscore these modern notions in infectiology.
4.6.4.3 Bacterial Infections In bacterial infection, maturation of DCs via activation of the NLRP3 inflammasome is a good example. Thus, the Mycobacterium tuberculosis “PPE60” antigen has been found to drive Th1/Th17 responses via TLR2-dependent maturation of DCs [331]. “PPE60” as a MAMP was found to act as the priming signal 1, whereas K+ efflux, indicating the presence of dysDAMPs, was suggested to operate as the inflammasome-assembling activating signal. And it can be firmly assumed that these dyshomeostasis-reflecting DAMPs are always generated in pathogen-induced injury. In fact, a generally participating role of dysDAMPs in the activation of DCs in defense responses against pathogens can be reasonably presumed due to the fact that has already been outlined above in Sects. 3.6.4 and 3.6.6 and Sect. 3.7.5.4, namely that invading pathogens promote notoriously stress responses such as ER stress/UPR and antioxidative stress response (e.g., as a result of membrane damage, access to the cytosol, disruption of the cytoskeleton, and protein aggregation) (also see [332–337]). On the other hand, and in support of this concept, maturation of immunostimulatory DCs has been shown to be generally induced by stress responses [338–340]. 4.6.4.4 Viral Infections and Viral Vaccines Virus-induced maturation of DCs associated with the induction of strong T-cell immunity has already been reported in 2003 [341]. During the past decade, several viruses have been described to promote DC maturation, including IAV, HPV, and Adenovirus (reviewed by Soto et al. [328]). Recognition of MAMPs (viral envelope proteins, viral DNA, or RNA) and/or DAMPs by multiple transmembrane and cytosolic PRMs is thought to trigger pathways resulting in DC maturation. This new knowledge and the increasing understanding of the role of MAMPs and DAMPs in triggering signaling pathways in antiviral defense have stimulated novel strategies in the development of vaccination procedures (particularly RIG-I → MAVS path [Fig. 4.6] and cGAS → STING path [Fig. 4.7]; also compare [342]). Such efforts culminated in the development of vaccines in the form of modified viral vector DNA or in vitro transcribed modified viral mRNA, which, for example, are currently used in vaccination against SARS-CoV-2. Such vaccines, at first, encode the desired viral antigen, but, in addition, as modified vector DNA or modified mRNA, they function as exogenous DAMPs to promote induction of immunostimulatory DCs. Indeed, as modified DNA or RNA, they do not function as MAMPs “sue generis” anymore (also denoted elsewhere as “ a self-adjuvant effect” [343]).
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Viral Vector DNA Vaccine and Dendritic Cell Maturation For example, modified Vaccinia virus Ankara is reportedly an attenuated strain of vaccinia virus and is currently under investigation as a promising vaccine vector against infectious diseases and cancer [344]. The authors conclude in their abstract: Our results show that STING has an impact on the antigen processing and presentation capacity of conventional DCs and played a crucial role for DC maturation and type I interferon production. mRNA Vaccine and Dendritic Cell Maturation As already introduced in Sects. 1.2.5.3 and 1.6.4.2, another technology refers to the use of in vitro transcribed mRNA-based vaccine such as LNPs/RNA that has been shown in COVID-19 vaccination trials to elicit robust CD4+ and CD8+ T cell and strong antibody responses ([343, 345]; for a review on mRNA-based drug technologies, see Sahin et al. [346]). Interestingly, already in 2000, mRNA transfection of DCs with mRNA encoding the HIV core protein “gag” was shown to deliver encoded antigen to MHC-I and MHC-II molecules and cause DC maturation [347]. Of note, in 2004, in vitro transcribed mRNA was already described by Karikó et al. [348] as an endogenous ligand of TLR3 in terms of a danger signal that was able to induce DC maturation. Later on, further PRRs that were detected to sense in vitro- transcribed mRNA with modified nucleotides include TLR3, TLR7/8, RIG-I, and MDA5 (reviewed by Weissman [349]). The potency of RNA-loaded LNPs vaccine in promoting DC maturation and inducing CTLs to kill tumor cells could recently be confirmed in in vitro studies on liver cancer cells [350].
4.6.4.5 Fungal and Protozoan Infections In fungal infections, MAMP-induced DC maturation has been reported as well. For example, in in vitro studies on the effects of C. albicans and A. fumigatus infection on human DCs, β-glucan was observed to promote activation and maturation of DCs [351]. The use of in vitro cultured DCs, that is, stressed cells, let suggest that the presence of dysDAMPs may have contributed to the process of DC maturation. Finally, DC maturation has also been observed in protozoan infection. For example, in interesting studies on an in vitro model using primary DCs incubated with intact P. falciparum-infected RBC and autologous naive CD4+ T cell, oxidative stress—known to be associated with malaria—was demonstrated to promote DC maturation in response to the parasite [340]. In these studies, the investigators used xanthine oxidase, a ROS-producing enzyme that is increased during malaria and observed that exposure to extracellular ROS potentiated DC maturation in response to the parasite. Hence, one might speculate again that the presence of dysDAMPs reflecting oxidative stress/ER stress has contributed to this kind of DC activation. 4.6.4.6 Concluding Remarks The findings and observations from studies in infection and vaccine settings presented here support the concept that DAMPs are essentially involved in DC maturation, a process that is essential for eliciting effective and robust T-/B-cell-mediated immune responses against pathogens. Here, it is reiterated that DAMPs are the key
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players in providing upregulation of costimulatory molecules on DCs, which are absolutely required for their metamorphosis into immunostimulatory DCs needed for full activation of T cells. One would wish that this process—along with the specific action of microbial or viral antigens in providing signal 1 for T cell activation—would be expressive verbis emphasized in all the excellent publications on DC maturation in infection and vaccination settings.
4.6.5 Cellular Adaptive Immune Responses 4.6.5.1 General Remarks Whereas the innate immune system provides a first-line, immediate, and rapid but non-specific response to foreign pathogens, the adaptive immune responses are generally seen to be slower but specific to the pathogenic invader. Typically, when the innate immune system fails to clear the bacteria or the viruses, the adaptive immune system is immediately alert to pick up the slack. The scenario is well known: Arrived from the periphery in the interfollicular areas of secondary lymphoid organs, immunostimulatory DCs present pathogen-derived antigenic peptides to uncommitted naïve CD4+ T cells and polarize them under control and orchestration by PRMs in different ways that are characteristic for a given class of pathogens. 4.6.5.2 CD4+ T Cell Immune Responses As described and illustrated in detail in Vol. 1 [18] (Sect. 32.4, Figs. 32.4 and 32.5, pp. 765–772), various adaptive CD4+ T cell responses are induced, depending on the T cell-priming and polarizing cytokines secreted by DCs. In brief, IL-12 promotes Th1 differentiation by driving T-bet expression, IL-4 drives Th2 differentiation in both a paracrine and autocrine manner, and the combination of IL-6 and TGF-β promotes Th17 differentiation. Also, concomitantly with effector CD4+ Th1, Th2, and Th17 cells, which support cellular immunity, follicular CD4+ helper T (Tfh) cells can develop, which promote humoral immunity. The prevailing paradigm in interpreting this scenario is that there is a relationship between the collaborating MAMPs and DAMPs, on the one hand, and the class of T cell effector response elicited, on the other hand [352]. The importance of eliciting the appropriate class of Th cell response to a given microbial infection has been evident since the discovery of Th1 and Th2 cells by Mosmann and Coffman [353]. The authors wrote: Because the appropriate response (i.e., the response that eliminates the infection) can be either Th1 or Th2, depending on the infectious agent, it is obviously important to consider the interregulation of these types of cell when inducing therapeutic immune responses. 4.6.5.3 Function of CD4+ Th1 Cells Interferon gamma-producing CD4+ Th1 cells have typically been associated with immune response to viruses, intracellular bacteria, and fungi, whereby the different pathogens are believed to induce distinct types of Th1. The Th17 subset is reportedly specialized in eliminating extracellular bacterial and fungal pathogens. The
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primary function of Tfh cells is to provide protection from infectious diseases by facilitating antibody responses to viral, bacterial, and fungal infections. The role of Th2 cells in infections is unclear. Although a Th2 response to helminths has been stressed, there are no reports describing a heterogeneity of helminth-specific human Th2 cells (for further reading, see [352, 354–357]).
4.6.5.4 Efferent Arm of the Adaptive Immune Response The efferent arm of the cell-mediated adaptive immune response is represented by CTLs, which respond to viral infections but also participate in defense against bacterial and protozoal infections (see Vol. 1 [18], Sect. 32.5 and Fig. 32.6, pp. 772–774). The CTLs eliminate intracellular bacterial/viral pathogens by various mechanisms, including induction of apoptotic cell death of infected target cells via recognition of pathogen-derived peptides complexed with MHC-I on the cell surface (for reviews, see [358–360]). Plausibly, such an immune destruction of virus-infected cells can result in further emission of DAMPs when apoptosis proceeds to secondary necrosis. However, as already discussed in Sect. 1.4.3 there is emerging evidence from targeted studies, preferentially on cancer models, demonstrating that cytotoxic CD8+ T lymphocytes can trigger subroutines of RN, including NETosis, pyroptosis, efferocytosis, and necroptosis. As touched above, the Tfh CD4+ T cells are the specialized providers of help for B cells which promote the development of long-lived humoral immunity. The differentiation of these cells depends on the expression of the master regulator transcription factor “Bcl6.” The next section has more of this.
4.6.6 Humoral Adaptive Immune Responses The humoral antibody-mediated response is a biological system in which innate immune factors such as complement, collectins, ficolins, and pentraxins (see above and, Vol. 1 [18], Chap. 23, pp. 591–626) along with soluble specific products of the adaptive immune response, the antigen-specific anti-pathogen antibodies, form a defense scenario that is characterized by tight regulation of progression from a small number of antigen-specific B cells to the production of a large number of antibodysecreting plasma cells and memory B cells. Humoral adaptive immune responses are vital for protection against invading pathogens and serve as a guideline for the development of vaccines since successful vaccination strategies against pathogens depend upon the humoral immune response (for more information, see Vol. 1 [18] Sect. 32.6, including Fig. 32.7, pp. 775–781; for a recent review, see [361]). The key component of the humoral response is the antibodies, which can exert their protective functions (but also detrimental functions) via a multitude of mechanisms. Such effector functions include neutralization, ADCP, ADCC, and CDC (for more information, see [361, 362]). For example, upon recognition of viruses, antibodies are produced that can neutralize viruses and induce the elimination of viruses through the recruitment of other immune effector cells or activation of the complement cascade, an innate immune process that results in the lysis of virus-infected cells [363].
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4.6.7 Immune Complexes Triggering NET Formation and NETosis in Infections: An Emerging Concept 4.6.7.1 General Remarks As already touched on in Sect. 1.4.2, antibodies as products of an adaptive immune response can lead to cell death using mainly three mechanisms: ADCC, CDC, and IC-promoted NET formation and NETosis. All three mechanisms of cell death induction are thought to be associated with the release of DAMPs, whereby the formation of NETs and NETosis has been systemically studied in their role as productive sources of nuclear and cytosolic DAMPs (for pathways involved in vital NET formation and lytic NETosis, see earlier, Sect. 3.7.7 and Fig. 3.10a, b). Taken as a whole, these results give rise to propose the emerging concept that antibody (or better: antigen/antibody IC)-induced formation of NETs and NETosis contribute to a robust immune defense response against pathogenic invaders, according to the motto: “The adaptive immune system calls in the cavalry for help.” Findings in support of this concept will be discussed in the following. 4.6.7.2 Immune Complexes and Their Interaction with Fc Gamma Receptors on Neutrophils Antigen/antibody ICs are produced whenever there is an antibody response to a soluble antigen. This applies to anti-pathogen antibodies and soluble pathogen- derived antigens as well. Interaction of ICs with neutrophils is accomplished by special receptors on the surface of neutrophils: the FcRs, that is, receptors expressed on innate immune effector cells such as neutrophils, macrophages, mast cells, and NK cells (for FcRs, also see Vol. 1 [18], Sect. 5.3.8, pp. 87–88). The FcRs are membrane molecules that bind to the Fc region of several immunoglobulin (Ig) classes and subclasses. They can be divided into FcR for IgG (FcγRI/CD64, FcγRII/CD32, and FcγRIII/CD16), IgE (FcεRI), IgA (FcαRI/CD89), IgM (FcμR), and IgA/IgM (Fcα/μR) [364]. Of special importance are FcγRs. These receptors allow neutrophils to bind to antigen-antibody complexes, conferring on these sentinel cells the ability to respond in an antigen-specific manner, thereby gaining a hallmark of the adaptive immune response [365, 366]. Humans express six classical FcγRs: FcγRI, FcγRIIA, FcγRIIB, FcγRIIC, FcγRIIIA, and FcγRIIIB, whereby all FcγRs, except for FcγRIIB and FcγRIIIB that function as inhibiting sensors, are classical activating receptors. All these FcγRs bind at least two of the four different human IgG subclasses, whereby IgG1 and IgG3 were found to bind to all FcγRs, IgG2 to 3 hFcγRs, and IgG4 to 6 [367]. However, human neutrophils express not only FcγRs but also the FcR for IgA, the FcαRI, and can thus be activated by both IgG and IgA complexes [368, 369]. Upon binding to neutrophil FcγRs, FcγRs-triggered cross-linking and signaling pathways in now activated neutrophils mediate various efferent functions. Activating FcγR signal through their immunoreceptor tyrosine-based activation motifs (ITAMs) while inhibitory FcγR signal via their immunoreceptor tyrosine-based inhibitory motifs (ITIMs) [370, 371].
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4.6.7.3 Functional Diversification of Immunoglobulin G Through Fc Glycosylation Neutrophil FcR expression was found to change dramatically in the context of sterile or infectious inflammatory conditions. Out of the Ig classes (IgG, IgA, IgM, IgE, and IgD) [372], the IgG isotype as the most abundant antibody in circulation is of special interest here. Contained in ICs, these antibodies are critically involved in the modulation of neutrophil activity that depends on both their IgG subclass and Fc glycosylations. The IgGs are divided into four subclasses, that is, IgG1–4, in humans, with IgG1 and IgG3 having superior affinity for activating type I FcγRs. Aside from subclass, the activity of IgG antibodies relies on Fc glycosylation as one of the most common PTMs in mammalian cells that significantly modifies their affinity for FcγRs [373]. More precisely, the activity of IgGs is reportedly influenced by a structural variability in Fc structure that is composed of a complex, biantennary N-linked glycan present at Asp297 of each CH2 domain in the antibody Fc portion, reflecting considerable functional diversification of IgG effector function (reviewed by Wang and Ravetch [374]). Several structural modifications in these Fc domains resulting in variable affinities expressed by variable neutrophil functions have been described: core-fucosylation, galactosylation, sialylation, mannosylation, or bisecting GlcNAcylation [375] (for the structure of IgG, see [376] and Fig. 4.9). For example, withdrawal of the core glycan decreases the affinity of Fc for FcγRs, resulting in the loss of FcγR-mediated effector functions in vivo. On the other hand, IgG-Fc glycans deficient in fucose (“afucosylation”) exhibit substantially increased affinity for FcγRs, FcγRIIIA, and Fcγ RIIIB compared with fucosylated IgG, resulting in enhanced IgG-dependent effector functions. Similarly, reduced sialylation of the Fc promotes increased activating FcγR signaling and, in turn, enhances inflammatory effector cell activity. Similarly again, low levels of galactosylated IgG have been considered by researchers as proinflammatory, for example, manifested in some ADs as disease progression and flare; however, there are also contradictory reports showing that agalactosylation decreases affinity for FcγRIII (for detailed information, see Dekkers et al. [377]). By contrast, sialylation of Fc glycan domains switches the binding specificity from the canonical activating FcRs type II FcRs, resulting in impaired IgG- dependent effector functions (reviewed by Wang and Ravetch [374] and Kaneko et al. [378]). In sum, there is growing evidence suggesting that lower Fc glycoforms promote an increase in inflammation, whereas increased Fc glycoforms, such as sialic acid moieties, tend to confer antiinflammatory properties [379]. 4.6.7.4 Impact of Changes in IgG Fc Glycosylation State on Neutrophil Effector Functions in Infections Based on what has been briefly touched on here, IgG molecules can exert neutrophil activity-promoting functions (e.g., in the absence of fucose) and neutrophil activity- decreasing functions (e.g., by addition of sialic acid), each driven by the variable carbohydrates in the sugar (N-linked glycan) moiety attached to the IgG Fc domain.
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Fig. 4.9 Schematic and simplified-sketched structure of IgG antibody consisting of two heavy chains and two light chains linked by disulfide bridges (called hinge region). The variable part of a heavy chain, along with the variable part of a light chain, represents the antigen-binding site. The binding site for Fc receptors is located near the hinge region and the Fc fragment (CH2/CH3 domain) interface. The Fab region is a region that binds to antigens. It is composed of one constant and one variable domain of each of the heavy and the light chain. Fab fragment antigen-binding, Fc fragment crystallizable, FcR CL constant light, CH constant heavy, VL variable light, S disulfide, VH variable heavy, VL variable light, CH: constant heavy. (Sources: [364, 376])
This phenomenon is also reflected in the property of IgG molecules to exert either proinflammatory or antiinflammatory effector functions of neutrophils. For example, low galactosylation and low fucosylation levels, mostly mediated by FcγRIII, promote proinflammatory processes such as ADCC [380]. Thus, defucosylation was demonstrated to consistently induce efficient ADCC [381]. These findings are consistent with reports on the role of defucosylation of IgG/IgG ↔ ICs in some infections caused by enveloped viruses. Thus, defucosylation (i.e., low Fc fucosylation) has been shown to be pathogenetically involved in HIV infections [382], secondary Dengue virus infection [383], and COVID-19 [384–386]. A typical observation in these clinical studies was the correlation of afucosylated IgGs/IgG ICs with the severity of the disease as mediated by the proinflammatory cytokine storm.
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On the other hand, evidence has been accumulated indicating that sialylation of IgG Fc domains confers antiinflammatory properties of neutrophils [378], qualifying IgG sialylation as a key checkpoint that determines the engagement of pro- or antiinflammatory FcγR. Mechanistically, sialylated IgG is supposed to increase the activation threshold of innate effector cells to ICs by promoting the upregulation of the inhibitory FcγRIIB [387] (for a review of this topic, also see [388]). Further support for this concept of antiinflammatory activity of IgG was provided by other lines of studies demonstrating that sialylation of IgG Fc significantly decreases ADCC in vivo [389] and impairs CDC [390]. Of note, it is worth mentioning in this context that the knowledge about FcR-driven antiinflammatory properties of neutrophils partially stems from findings that the antiinflammatory activity of i.v. Immunoglobulins (IVIG) in various murine inflammatory disease models could be recapitulated using a sialylated recombinant human IgG1 Fc fragment at a much- reduced dose [378, 391, 392]. Taken together, IgGs as pure antibodies or as part of ICs, render neutrophils capable through FcγRs to react to threats against the host in a balanced antigen- specific manner by initiating various innate immune defense responses such as ADCP, ADCC, and CDC (for more in-depth information on expression, role, and regulation of neutrophil FcγRs, see the review of Wang and Jönsson [366]). Among these processes, the induction of NET formation and NETosis by ICs via FcγRs has recently attracted increasing attention, particularly with respect to their pathogenetic role in autoimmunity, a topic discussed in Sect. 6.2.4.
4.6.7.5 Immune Complexes Interacting with FcRs as Powerful Inducers of NET Formation and NETosis As touched on in Sect. 3.7.7.6, there is accumulating evidence suggesting that antigen/antibody ICs (including mixed IgG/IgA ICs) can induce the formation of NETs and NETosis by interacting with FcRs [393–399]. Interestingly, in one study [399], evidence was provided showing that IgA is much more effective in inducing NET formation compared to IgG (for details of NETs and NETosis, see the previous chapter, Sect. 3.7.7 and Fig. 3.11a, b). Remarkably, this mechanism of NET formation/NETosis has also recently been observed in bacterial and viral infections. To date, only two studies have documented the mechanism of antibody ↔ FcR- mediated NET release in bacterial infections [400, 401]. The findings reported for neutrophils in contact with complement-mediated opsonization of S. aureus or monoclonal antibody-mediated opsonization of hypervirulent Klebsiella pneumoniae suggest that activation of FcRs could enhance the release of NETs. In viral infections, the data are documented more clearly. For example, Stacey et al. [402] observed that virus—IgA/ICs could potentiate NETosis through FcαRI signaling on human neutrophils. This effect could be observed for IAV, HIV, and SARS-CoV-2 spike-pseudo-typed lentiviruses. Moreover, recent studies on children with multisystem inflammatory syndrome reported by Boribong et al. [403] revealed high rates of spontaneous NETosis in neutrophils. Mechanistically, the investigators could demonstrate that SARS-CoV-2 antigen/antibody ICs derived from patient- derived plasma are capable of triggering NETosis in healthy donor neutrophils. This
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observation goes in line with other studies on sera from COVID-19 patients showing that the sera can trigger NET release from control neutrophils in vitro [404]. These findings were specified by other sets of studies on COVID-19 patients, demonstrating that virus-specific IgA, but not IgG, is obviously associated with increased NET formation markers, whereby virus-specific IgA was observed to be associated with a more severe disease course and fatal outcome [405].
4.6.7.6 Immune Complex-Triggered NETs/NETosis in Infections: From Facts to a Preliminary Working Hypothesis Given the various findings and observations outlined in this section and considering that formation of NETs and NETosis serve as potent sources for the release of nuclear and cytosolic DAMPs, it is tempting to propose a preliminary working hypothesis as follows (Fig. 4.10): Pathogen antigens elicit an anti-pathogen humoral immune response characterized by the action of anti-pathogen IgG/IgA antibodies that form ICs together with their cognate pathogen antigens. Deglycosylated (e.g., degalactosylated, defucosylated) Fc Igs (e.g., IgA > IgG) ICs—via increasing the stimulation of neutrophil FcRs such FcγRIII—trigger formation of NETs and NETosis as a prolific source for release of DAMPs, which contribute robustly to host defense. The motto is: “The immune system calls for the cavalry!” However, there is another side of the coin: Dysregulated DAMPs release may activate
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Fig. 4.10 Schematic diagram of a working hypothesis: Pathogen-derived antigens elicit a humoral immune response against the pathogen characterized by the action of anti-pathogen IgG/IgA antibodies that form ICs together with their corresponding soluble antigens. Deglycosylated (e.g., degalactosylated, defucosylated) Fc Igs (e.g., IgA > IgG) ICs—via enhancing the stimulation of neutrophil FcRs such FcγRIII—trigger formation of NETs and NETosis as a prolific source of DAMPs. The DAMPs, in turn, activate innate immune cells, including DCs, which drive an innate/ adaptive immune response that, when regulated, leads to a robust host defense but, when dysregulated, may end up with a severe disease course, eventually partly caused by a DAMP-induced cytokine storm. Note: start reading the figure on the left and continue clockwise. Ab antibody, Ag antigen, FcRs Fc receptors, ICs immune complexes, Ig immunoglobulin, NET neutrophil extracellular trap
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PRR-bearing innate immune cells to secrete large amounts of cytokines (“cytokine storm”) that can lead to severe disease course and fatal outcome (for DAMP-induced cytokine storm, also see Sect. 5.4.6 in the next chapter).
4.6.8 Innate and Adaptive Immune Memory Immunological memory is an important evolutionary trait that enhances host survival in the event of reinfection. Memory is a feature recognized in both the innate and adaptive arms of the immune system. The adaptive immune memory, well known to the medical community, is an evolutionary adaptation of the immune system that executes more rapid and effective defense responses to previously encountered bacterial or viral antigens. For a long time, this type of immune memory was thought to be mediated by adaptive cells, that is, B cells and T cells that have differentiated into subsets of “memory” cells. In particular, B cells, through the production of antibodies, and T cells through a variety of mechanisms have been recognized as critical mediators of protection. The adaptive immune memory collaborates with the innate immune memory to enhance the host defense against pathogens, although the mechanisms and properties by which the adaptive innate and adaptive immune memory are triggered are distinct. As several times cited in this book, trained immunity has been defined as one form of adaptation of innate host defense mechanisms or a de facto innate immune memory [208, 209]. In a recent excellent comment written by multiple authors [406], a paper that is definitely worth reading, a common framework was established that describes the experimental standards for defining trained immunity. The authors concluded: Understanding innate immune memory is critical for deciphering new approaches to vaccine development. By dissecting the cellular and molecular mechanisms of trained immunity, we hope to develop new vaccine strategies with cross-protective efficacy against a range of infections. In addition, we can envisage more effective vaccines that combine the induction of trained immunity with adaptive immune memory. While we have made enormous progress in our fundamental understanding of trained immunity in health and diseases, accurate nomenclature and experimental standardization are important and would encourage progress in the field. By doing this work, we hope scientists who are new to trained immunity will establish accurate experimental models to close the knowledge gap in this field. Furthermore, as a more precise mechanistic description of trained immunity is developed, we will need to formulate updated recommendations on trained immunity.
4.7 Conclusions and Future Perspectives 4.7.1 Introductory Remarks The danger/injury model holds that, in the presence of nonself antigens plus cell stress/tissue injury-induced DAMPs, the innate immune system elicits an innate immune (inflammatory) → specific adaptive immune response. Consequently, the
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model precludes that nonself antigens per se—in the absence of stress/injury- induced DAMPs—can instigate an inflammatory/adaptive immune response but rather induces protective immune tolerance. This concept can be transferred to the field of microbiology, where it can be modified, for instance, like: “In the presence of microbe-derived MAMPs and (nonself) microbial antigens plus (microbe-caused) cell stress/tissue injury-induced DAMPs, the innate immune system elicits an innate immune (inflammatory) → adaptive antimicrobial immune response”. Consequently, the model precludes that microbe-derived MAMPs and microbial nonself antigens per se—in the absence of cell stress/tissue injury-induced DAMPs—can instigate an inflammatory/immune response but rather induces antiinflammation and protective immune tolerance to microbes, in this case resulting in the formation of microbiomes.
4.7.2 Interplay Between MAMPs and DAMPs Based on these introductory words, it can be argued that an effective inflammatory defense response to infectious agents is not triggered by MAMPs alone but in the form of an interplay between the two inducers, the MAMPs and DAMPs. The additional action of microbial antigens then results in the establishment of a specific adaptive antimicrobial immune response. This implies, as outlined above, that PRMs on/in cells of the innate immune system (including APCs, see below) sense both the MAMPs derived from pathogenic invaders and the DAMPs induced by them. However, the question of the exact chronological sequence of the two key recognition processes could still not be answered satisfactorily. In other words, it is still unclear how MAMPs and DAMPs as inducers of an infective inflammatory response co-vary and what relative contribution they each make, in particular, how they have to be in order to mount an effective and robust immune defense response to pathogenic invaders. In addition, there is another level of complexity when assessing the impact of inducible DAMPs, such as type I IFNs and TNF, on the amplification of the MAMP/DAMP-triggered inflammatory processes. In such a situation, it may be allowed to discuss some possible mechanisms. However, before discussing this still unclear interplay, some evidence in support of the emerging notion is presented, proposing that MAMPs per se (plus microbial antigens) are not involved in mounting an effective inflammatory/immune defense response to pathogens. Clearly, this new concept has led to a change of views on the role of MAMPs in pathogen-induced inflammation/immunity.
4.7.3 The Changing Role of MAMPs in Pathogen-Induced Inflammation/Immunity As mentioned already above, at the beginning of the new era of modern immunology, introduced by Janeway and Medzhitov [37, 40–44], PRRs were considered to mediate the recognition of microbes by binding to highly conserved, invariant motifs, the PAMPs, to trigger an inflammatory response. However, the use of the
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term “PAMPs” for molecules derived from all microbes posed a puzzling paradox because harmless commensal microorganisms are no pathogens and, thus, do not trigger inflammatory responses. Given this conundrum, it seems appropriate and sound to resume at first a few aspects of the microbiota already briefly touched previously, albeit at the risk of having to repeat some inevitable facts.
4.7.3.1 The Microbiota The commensal microorganisms, collectively termed the microbiome, including bacteria, viruses, fungi, and parasites [407, 408], do not trigger inflammatory responses but, in contrast, are preserved, protected, and even farmed. For example, a typical feature of the intestinal innate/adaptive immune system is its capacity to establish immunological tolerance towards this huge and permanently changing wealth of harmless microorganisms while, at the same time, promoting protective inflammatory and immune defense responses against pathogens intruding into the sterile body milieu [409] (for immunotolerance against commensal microbes, i.e., nonself (!), also compare Vol. 1 [18], Chap. 34, pp. 829–835). For example, every abdominal surgeon is familiar with the puzzling observation that harmless bacteria from the gut cause severe systemic peritonitis when intruding—as the same but now harmful bacteria—into the unprotected sterile peritoneal cavity due to gut (e.g., appendix!) perforation. In fact, it was the recognition of these features that has led to the more precise acronym “MAMPs” in terms of molecules derived from all microbes, including nonpathogenic commensals (also compare [410]). However, this proposal raises another puzzle: Given that all microbes possess MAMPs, how can PRR-bearing cells of the innate immune system distinctly discriminate between the myriads of non-pathogenic commensals within the gut microbiota to establish symbiosis and those that operate as injuring pathogenic microbes to promote inflammatory/ immune defense responses? 4.7.3.2 MAMPs in the Absence of Injury-Induced DAMPs: Promotion of Intestinal Homeostasis and Tolerance Instead of Inflammation The answer to this question above is grounded on the general notion that, in gut homeostasis, the host’s innate/adaptive immune response to the intestinal microbiota is strictly compartmentalized to the mucosal surface. Indeed, a single layer of epithelium separates the intestinal lumen from the underlying tissues. Many mechanisms are operating to establish efficient microbiota compartmentalization aimed at preventing microbes from conveying stress and injury; the first place to mention is a dense mucus layer separating the intestinal epithelium from resident microbes. This monolayer of intestinal epithelial cells (IECs) is attached to each other via tight junctions that serve to limit diffusion via intercellular gaps. Of note, all these compartmentalization-achieving mechanisms prevent harmless but still potentially harmful (!) microorganisms from crossing the mucosal barrier function and, thus, from causing stress and injury to underlying cells and tissue; that is, DAMPs are thus not emitted or generated: consequently, an inflammatory response remains absent.
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Moreover, other mechanisms to prevent intestinal, potentially harmful microorganisms from causing injury are provided by the innate/adaptive immune system. They include secretion of antiinflammatory cytokines (IL-10) and AMPs; function of γδ T cells; as well as—via involvement of tolerogenic DCs (tolDCs), i.e., intestinal CD103+ DCs and commensal-derived antigens—production by B cells of IgA antibodies [411] and generation of regulatory T cells (Tregs) [412–414]. The mechanisms are not quite clear. But there is first evidence suggesting an involvement of coinhibitory immune pathways [415, 416] (see Vol. 1 [18], Sect. 33.3.5, pp. 805–807; for intestinal CD103+ DCs, see Sect. 34.3, p. 831). Of note, initiation of all these mechanisms is triggered by innate immune recognition of MAMPs derived from commensals. In fact, PRRs such as TLR, CLRs, NLRs, RLRs, and ALRs on innate immune cells, including IECs and subepithelially located intestinal macrophages and DCs, have been reported to interact with those MAMPs to regulate host-microbiome symbiosis (for more information, again see Vol. 1 [18], Chap. 34, pp. 829–835; for further reading, see reviews of Mowat [409], Zheng et al. [417], and Srinivasan [418]). An impressive example of this phenomenon refers to the intestinal and systemic impact of the MAMP PGN, as recently reported by Wolf and Underhill [79]. The authors provided increasing evidence demonstrating that PGN from gut microbiota not only affects gut homeostasis but also possesses substantial systemic effects. The investigators reviewed that bacteria-derived PGN can activate Paneth cells in the intestinal crypts to secrete defensins that assist in regulating the gut microbiota and protecting the host from pathogenic bacteria. Moreover, they described that IECs produce distinct PGN recognition proteins (PGLYRPs) to maintain a healthy gut microbiome. It is worth adding here some other studies in support of the concept that the action of MAMPs per se is not sufficient to trigger effective PRR-mediated innate (inflammatory) and—together with microbial antigen—adaptive immune responses. These studies refer to observations on the role of distinct TLR signaling in IECs that, in the absence of injury, is involved in controlling crypt dynamics, enhancing epithelial barrier integrity, and promoting immune tolerance towards the gut microbiota. However, in the presence of injury, for example, induced by pathogenic microorganisms, the tolerant state may be disrupted and converted to a DAMP- promoted innate (inflammatory)/adaptive immune response, as seen, for example, in patients with inflammatory bowel disease (IBD) (for further reading, see [419–421]).
4.7.4 Recognition of MAMPs and DAMPs in Infections: Simultaneously or Sequentially? All of the findings cited here make it difficult to hold that the recognition of MAMPs alone (plus microbial antigen) is responsible for the initiation of innate and adaptive immune responses to defend against pathogens. Instead, the action of MAMPs and DAMPs (i.e., constitutive DAMPs) in terms of an interplay appears to be required
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to precipitate an effective and robust antimicrobial defense response via activation of innate immune cells, including DCs. Regarding such an interplay between MAMPs and constitutive DAMPs—and if we anticipate that inducible DAMPs operate in a delayed way—two extreme scenarios may be discussed. One extreme scene would refer to a nearly parallel, simultaneous detection by PRM-bearing cells of both MAMPs and DAMPs—even by the same recognition receptor-, for example, by cell stress associated with invasion of harmful pathogens. In this case, both molecules are needed to mount an efficient antimicrobial immune defense response. Such a prompt, nearly simultaneous perception of MAMPs and DAMPs by PRM-bearing cells may occur, for example, when intracellular bacteria penetrate the cell and replicate, thereby evoking cell stress associated with molecular perturbations (reflecting IIC-4 DAMPs). The other extreme scene would refer to a two-step mechanism: initial interaction of PRMs with MAMPs triggering an initial subclinical inflammatory response, followed by induction of different subroutines of RN (via pathways outlined in Sect. 2.5.3 and Fig. 2.2), leading to release of IA-1/IA2 DAMPs. Subsequently, MAMPs plus DAMPs sensed by PRM-bearing cells contribute to a robust antimicrobial immune defense response and potentially—when too exaggerated—cause severe infectious disease (e.g., sepsis). Nonetheless, in the end, it is still unclear how MAMPs and DAMPs co-vary and cooperate as triggers of an infectious inflammatory/immune response to mount a robust defense against pathogenic invaders. In this situation, it is of interest to look at first reports on this topic in the international literature to see how this burning issue is being discussed elsewhere.
4.7.4.1 Discussion of the Topic in the International Literature Indeed, the role of DAMPs in infections is increasingly discussed by mainly focusing on their role in amplification and aggravation of inflammatory/immune responses. For example, in an earlier article on “The interplay between pathogen- associated and danger-associated molecular patterns: an inflammatory code in cancer?”, Escamilla-Tilch et al. [422] summarized remarkably in their abstract: Microorganisms harbor molecules structurally conserved within groups called PAMPs that are recognized by specific receptors present on immune cells, such as monocytes and dendritic cells (DCs); these are the pattern recognition receptors (PRRs). Activation through different PRRs leads to production of pro-inflammatory cytokines. A robust immune response also requires the presence of endogenous molecules that pose ‘danger’ to self-tissues and are produced by damaged or stressed cells; these are the DAMPs, which act also as inducers of inflammation. PAMPs and DAMPs are each recognized by a limited set of receptors that in number probably do not exceed 100. PAMPs and DAMPs interact with each other, and a single PRR can bind to a PAMP as well as a DAMP. Within this framework, we propose that PAMPs and DAMPs act in synchrony, modifying the activation threshold of one another. Thus, the range of PAMP–DAMP partnerships defines the course of inflammation, in a predictable manner, in an ‘inflammatory code’. Further, Hayward et al., in a review on Cytosolic Recognition of Microbes and Pathogens: Inflammasomes
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in Action [423], stated: Recognition of PAMPs and DAMPs by inflammasome sensors, …, initiates a cascade of events that culminate in inflammation and cell death. Also, in an article on Pattern Recognition Receptors and the Host Cell Death Molecular Machinery, Amarante-Mendes et al. [424] conclude in the context of PRR-triggered RN: These forms of cell death release larger amounts of DAMPs, which in turn, stimulate surrounding cells via PRRs, thus constituting a positive feedback loop capable of amplifying host defense mechanisms. The authors illustrate the interaction between PRRs and cell death mechanisms in a figure by explaining in its legend: The engagement of PRRs in response to PAMPs induces the activation of different cell death machineries in order to promote tissue homeostasis and host-defense against pathogens. Importantly, cell death products known collectively as DAMPs forms a feedback loop that stimulate PRRs to induce inflammatory/immune responses. And they concluded further: Therefore, recognition of PAMPs and DAMPs by the same set of PRRs is a powerful strategy that bridges intrinsic cell death programs and complex immune cell interactions to preserve homeostasis and at the same time protects the organism against infection and cellular transformation. De Lorenzo and Cervone [425], in their article on: Plant immunity by damage-associated molecular patterns (DAMPs), conclude in the abstract: “It is conceivable that DAMPs and MAMPs act in synergy to activate a stronger plant immunity and that MAMPs exploit the mechanisms and transduction pathways traced by DAMPs.”
4.7.5 Résumé Together, the role of MAMPs by themselves as well as the interplay between MAMPs, constitutive DAMPs, and inducible DAMPs in infections, has emerged as a hot topic in immunity-oriented infectiology. With respect to viral and bacterial NAs, the case for a cautious interpretation appears to be clearer: If we accept that they are (mis)recognized by cytosolic PRRs as molecules that are mis-/dislocated or pathologically accumulated in the cytosol, they should function as exogenous DAMPs and be able to induce a robust antiviral immune defense response. But what about the other non-nucleic acid MAMPs? Indeed, there is increasing evidence suggesting that, in this case, it is the interplay of MAMPs and DAMPs which promotes robust inflammatory/immune responses to defend against pathogens, whereas the action of MAMPs alone drives immune tolerance processes to maintain host- microbiome homeostasis. Under the impression of current reports from this research field, the evolutionary role of PRMs is gaining center stage. Thus, it is tantalizing to speculate on the model holding that the primary role of mammalian PRMs in sensing non-nucleic acid MAMPs is to discriminate between self and nonself/foreign: they recognize all foreign microorganisms from their MAMPs to signal their presence in terms of “nonself” to the host. Following recognition of MAMPs, the PRM-bearing cells then decide what to do (Fig. 4.11): In case the nonself microorganism does not cause cell stress/tissue injury, that is, when DAMPs are absent, the cell initiates a program that promotes an intestinal
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MHC-II
coinhibitory molecules
Signal 2
Ps
M DA
immunogenic DC
Signal 3
helper/effector T cell differentiation -immunity-
Immunity Infection
Fig. 4.11 Simplified schematic diagram of a narrative hypothetical scenario model of the dichotomous function of DCs to maintain the intricate balance between tolerance and immunity in the gut. In the presence of MAMPs and microbial antigens derived from harmless commensals, DCs acquire tolerogenic properties to promote an intestinal immunological tolerance to microbes leading to gut homeostasis (host ↔ microbial symbiosis → microbiome). In the presence of MAMPs and microbial antigens derived from pathogens as well as DAMPs that are generated and emitted due to pathogen-induced stress/injury, DCs develop into immunogenic antigen-presenting cells to promote adaptive immune immunity resulting in a defensive response manifested by infection. In both scenarios, DCs’ three signals are involved. Induction of immunity by immunogenic DCs strictly depends on provision of costimulation provided by DAMPs. Ag microbial antigens, DC dendritic cell, MHC-I/II major histocompatibility complex class I/II. Note that this figure is modified from Fig. 30.2 published in Vol. 1 [18], Sect. 30.2, p. 721. (Sources: [411–416])
immunological tolerance leading to gut homeostasis (host-microbial symbiosis); in case the microbe causes stress/injury, that is when DAMPs are generated and emitted, the cell is licensed to start a defense program, aimed at eliminating the foreign invader. Simultaneous recognition, uptake, transportation, and presentation of foreign organism-derived antigenic material by PRR-bearing APCs, in particular, DCs, then initiate the adaptive arm of the immune defense program, which specifically assists in either tolerating (even farming!) or destroying the nonself invader in the course of infection. The exciting question is whether this model of tolerance or immunity to nonself can be applied to all potentially infectious agents such as viruses and fungi. Here, however, a note of caution must be added: The role of MAMPs, as discussed in this model, is much more complex and complicated. Let’s take, for example, the MAMP LPS derived from Gram-negative bacteria (Fig. 2.8). As outlined and illustrated in Sect. 3.2.4.3 and Fig. 4.3, LPS by itself—designated as an exogenous DAMP—has been shown to promote strong proinflammatory responses. On the other hand, as reviewed by Gnauck et al. [426], LPS, in a context-dependent
References
261
way, for example, in low doses or in a deacetylated or tetra-acetylated structural form or via other mechanisms, has been observed to trigger less inflammatory, pro- tolerance pathways, for example, via promotion of pro-tolerant macrophage maturation. Thus, one could speculate that high doses of LPS operate as DAMPs while low doses function as SAMPs.
References 1. Chandler CE, Ernst RK. Bacterial lipids: powerful modifiers of the innate immune response. F1000Research. 2017;6:1334. https://f1000research.com/articles/6-1334/v1. 2. Hajam IA, Dar PA, Shahnawaz I, Jaume JC, Lee JH. Bacterial flagellin—a potent immunomodulatory agent. Exp Mol Med. 2017;49:e373. http://www.nature.com/articles/ emm2017172. 3. Rey FA, Lok S-M. Common features of enveloped viruses and implications for immunogen design for next-generation vaccines. Cell. 2018;172:1319–34. https://linkinghub.elsevier. com/retrieve/pii/S0092867418302319. 4. Arana DM, Prieto D, Román E, Nombela C, Alonso-Monge R, Pla J. The role of the cell wall in fungal pathogenesis. Microb Biotechnol. 2009;2:308–20. http://doi.wiley. com/10.1111/j.1751-7915.2008.00070.x. 5. Taghavi M, Khosravi A, Mortaz E, Nikaein D, Athari SS. Role of pathogen-associated molecular patterns (PAMPS) in immune responses to fungal infections. Eur J Pharmacol. 2017;808:8–13. https://linkinghub.elsevier.com/retrieve/pii/S0014299916307063. 6. Schofield L, Hackett F. Signal transduction in host cells by a glycosylphosphatidylinositol toxin of malaria parasites. J Exp Med. 1993;177:145–53. https://rupress.org/jem/ article/177/1/145/24652/Signal-transduction-in-host-cells-by-a. 7. Gowda DC. TLR-mediated cell signaling by malaria GPIs. Trends Parasitol. 2007;23:596–604. https://linkinghub.elsevier.com/retrieve/pii/S1471492207002565. 8. Gazzinelli RT, Kalantari P, Fitzgerald KA, Golenbock DT. Innate sensing of malaria parasites. Nat Rev Immunol. 2014;14:744–57. http://www.nature.com/articles/nri3742. 9. Dos-Santos ALA, Carvalho-Kelly LF, Dick CF, Meyer-Fernandes JR. Innate immunomodulation to trypanosomatid parasite infections. Exp Parasitol. 2016;167:67–75. https://linkinghub.elsevier.com/retrieve/pii/S0014489416300959. 10. Gowda DC, Wu X. Parasite recognition and signaling mechanisms in innate immune responses to malaria. Front Immunol. 2018;9:3006. https://www.frontiersin.org/article/10.3389/ fimmu.2018.03006/full. 11. Thomas PG, Carter MR, Atochina O, Da’Dara AA, Piskorska D, McGuire E, et al. Maturation of dendritic cell 2 phenotype by a helminth glycan uses a toll-like receptor 4-dependent mechanism. J Immunol. 2003;171:5837–41. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.171.11.5837. 12. Goodridge HS, Marshall FA, Else KJ, Houston KM, Egan C, Al-Riyami L, et al. Immunomodulation via novel use of TLR4 by the filarial nematode phosphorylcholine- containing secreted product, ES-62. J Immunol. 2005;174:284–93. http://www.jimmunol. org/lookup/doi/10.4049/jimmunol.174.1.284. 13. Albiger B, Dahlberg S, Henriques-Normark B, Normark S. Role of the innate immune system in host defence against bacterial infections: focus on the Toll-like receptors. J Intern Med. 2007;261:511–28. http://doi.wiley.com/10.1111/j.1365-2796.2007.01821.x. 14. Akira S. Innate immunity to pathogens: diversity in receptors for microbial recognition. Immunol Rev. 2009;227:5–8. http://doi.wiley.com/10.1111/j.1600-065X.2008.00739.x. 15. Mogensen TH. Pathogen recognition and inflammatory signaling in innate immune defenses. Clin Microbiol Rev. 2009;22:240–73, Table of Contents. http://cmr.asm.org/cgi/doi/10.1128/ CMR.00046-08.
262
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
16. Kumar H, Kawai T, Akira S. Pathogen recognition by the innate immune system. Int Rev Immunol. 2011;30:16–34. http://www.tandfonline.com/doi/full/10.3109/0883018 5.2010.529976. 17. Eigenbrod T, Dalpke AH. Bacterial RNA: an underestimated stimulus for innate immune responses. J Immunol. 2015;195:411–8. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1500530. 18. Land WG. Damage-associated molecular patterns in human diseases. Volume 1: Injury- induced innate immune responses. Cham: Springer International Publishing; 2018. http:// link.springer.com/10.1007/978-3-319-78655-1. 19. Land WG. Damage-associated molecular patterns in human diseases. Vol. 2: Danger signals as diagnostics, prognostics, and therapeutic targets. Cham: Springer International Publishing; 2020. http://link.springer.com/10.1007/978-3-030-53868-2. 20. Qu Y, Zhan Y, Yang S, Ren S, Qiu X, Rehamn ZU, et al. Newcastle disease virus infection triggers HMGB1 release to promote the inflammatory response. Virology. 2018;525:19–31. https://linkinghub.elsevier.com/retrieve/pii/S0042682218302721. 21. Tang Z, Zang N, Fu Y, Ye Z, Chen S, Mo S, et al. HMGB1 mediates HAdV-7 infection- induced pulmonary inflammation in mice. Biochem Biophys Res Commun. 2018;501:1–8. 22. Zhang P, Xin X, Fang L, Jiang H, Xu X, Su X, et al. HMGB1 mediates Aspergillus fumigatus -induced inflammatory response in alveolar macrophages of COPD mice via activating MyD88/NF-κB and syk/PI3K signalings. Int Immunopharmacol. 2017;53:125–32. https:// linkinghub.elsevier.com/retrieve/pii/S1567576917303764. 23. Masouris I, Klein M, Dyckhoff S, Angele B, Pfister HW, Koedel U. Inhibition of DAMP signaling as an effective adjunctive treatment strategy in pneumococcal meningitis. J Neuroinflammation. 2017;14:214. http://jneuroinflammation.biomedcentral.com/ articles/10.1186/s12974-017-0989-0. 24. Tasaka S, Kobayashi S, Kamata H, Kimizuka Y, Fujiwara H, Funatsu Y, et al. Cytokine profiles of bronchoalveolar lavage fluid in patients with pneumocystis pneumonia. Microbiol Immunol. 2010;54:425–33. http://doi.wiley.com/10.1111/j.1348-0421.2010.00229.x. 25. Higa F, Furugen M, Koide M, Karimata Y, Nabeya D, Iha Y, et al. Clinical evaluation of high mobility group box 1 protein in Legionella pneumophila pneumonia. J Infect Chemother. 2014;20:289–92. https://linkinghub.elsevier.com/retrieve/pii/S1341321X13000536. 26. Wu X, Mi Y, Yang H, Hu A, Zhang Q, Shang C. The activation of HMGB1 as a progression factor on inflammation response in normal human bronchial epithelial cells through RAGE/JNK/NF-κB pathway. Mol Cell Biochem. 2013;380:249–57. http://link.springer. com/10.1007/s11010-013-1680-0. 27. Wang H-L, Tsao S-M, Yeh C-B, Chou Y-E, Yang S-F. Circulating level of high mobility group box-1 predicts the severity of community-acquired pneumonia: regulation of inflammatory responses via the c-Jun N-terminal signaling pathway in macrophages. Mol Med Rep. 2017;16:2361–6. https://www.spandidos-publications.com/10.3892/mmr.2017.6892. 28. Alpkvist H, Athlin S, Mölling P, Norrby-Teglund A, Strålin K. High HMGB1 levels in sputum are related to pneumococcal bacteraemia but not to disease severity in community-acquired pneumonia. Sci Rep. 2018;8:13428. http://www.nature.com/articles/s41598-018-31504-4. 29. Zuo D, Subjeck J, Wang XY. Unfolding the role of large heat shock proteins: new insights and therapeutic implications. Front Immunol. 2016;7:75. http://journal.frontiersin.org/ article/10.3389/fimmu.2016.00075. 30. Bolhassani A, Agi E. Heat shock proteins in infection. Clin Chim Acta. 2019;498:90–100. https://linkinghub.elsevier.com/retrieve/pii/S0009898119320030. 31. Sutherland AD, Gearry RB, Frizelle FA. Review of fecal biomarkers in inflammatory bowel disease. Dis Colon Rectum. 2008;51:1283–91. http://journals.lww. com/00003453-200851080-00017. 32. van Rheenen PF, Van de Vijver E, Fidler V. Faecal calprotectin for screening of patients with suspected inflammatory bowel disease: diagnostic meta-analysis. BMJ. 2010;341:c3369. http://www.bmj.com/cgi/doi/10.1136/bmj.c3369.
References
263
33. Zackular JP, Chazin WJ, Skaar EP. Nutritional immunity: S100 proteins at the host-pathogen interface. J Biol Chem. 2015;290:18991–8. http://www.jbc.org/lookup/doi/10.1074/jbc. R115.645085. 34. Jiang X, Hao X, Wen T, Jin Y, Sun M, Yang H, et al. Increased concentrations of extracellular histones in patients with tuberculous pleural effusion. Med Sci Monit. 2018;24:5713–8. https://www.medscimonit.com/abstract/index/idArt/910431. 35. Ashar HK, Mueller NC, Rudd JM, Snider TA, Achanta M, Prasanthi M, et al. The role of extracellular histones in influenza virus pathogenesis. Am J Pathol. 2018;188:135–48. https:// linkinghub.elsevier.com/retrieve/pii/S0002944017304121. 36. Gómez RM, López Ortiz AO, Schattner M. Platelets and extracellular traps in infections. Platelets. 2020;28:1–9. https://www.tandfonline.com/doi/full/10.1080/09537104.202 0.1718631. 37. Janeway CA. Approaching the asymptote? Evolution and revolution in immunology. Cold Spring Harb Symp Quant Biol. 1989;54(Pt 1):1–13. http://www.ncbi.nlm.nih.gov/ pubmed/2700931. 38. Janeway CA. Pillars article: approaching the asymptote? Evolution and revolution in immunology. Cold spring harb symp quant biol. 1989. 54: 1-13. J Immunol. 2013;191:4475–87. http://www.ncbi.nlm.nih.gov/pubmed/24141854. 39. Medzhitov R. Approaching the asymptote: 20 years later. Immunity. 2009;30:766–75. http:// www.ncbi.nlm.nih.gov/pubmed/19538928. 40. Medzhitov R. Pattern recognition theory and the launch of modern innate immunity. J Immunol. 2013;191:4473–4. http://www.ncbi.nlm.nih.gov/pubmed/24141853. 41. Medzhitov R, Janeway CA. Innate immunity: the virtues of a nonclonal system of recognition. Cell. 1997;91:295–8. 42. Medzhitov R, Janeway CA. Innate immune recognition and control of adaptive immune responses. Semin Immunol. 1998;10:351–3. http://www.ncbi.nlm.nih.gov/pubmed/9799709. 43. Janeway CA, Medzhitov R. Innate immune recognition. Annu Rev Immunol. 2002;20:197–216. http://www.annualreviews.org/doi/10.1146/annurev.immunol.2 0.083001.084359. 44. Medzhitov R. Recognition of microorganisms and activation of the immune response. Nature. 2007;449:819–26. 45. Takeuchi O, Akira S. Pattern recognition receptors and inflammation. Cell. 2010;140:805–20. http://www.ncbi.nlm.nih.gov/pubmed/20303872. 46. Chen H, Jiang Z. The essential adaptors of innate immune signaling. Protein Cell. 2013;4:27–39. http://link.springer.com/10.1007/s13238-012-2063-0. 47. Akira S, Uematsu S, Takeuchi O. Pathogen recognition and innate immunity. Cell. 2006;124:783–801. https://linkinghub.elsevier.com/retrieve/pii/S0092867406001905. 48. Kawai T, Akira S. The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors. Nat Immunol. 2010;11:373–84. http://www.ncbi.nlm.nih.gov/ pubmed/20404851. 49. Zhai Y, Wang C, Jiang Z. Cross-talk between bacterial PAMPs and host PRRs. Natl Sci Rev. 2018;5:791–2. https://academic.oup.com/nsr/article/5/6/791/5154946. 50. Rosadini CV, Kagan JC. Early innate immune responses to bacterial LPS. Curr Opin Immunol. 2017;44:14–9. http://www.ncbi.nlm.nih.gov/pubmed/27842237. 51. Bah A, Vergne I. Macrophage autophagy and bacterial infections. Front Immunol. 2017;8:1483. http://journal.frontiersin.org/article/10.3389/fimmu.2017.01483/full. 52. Siqueira MS, Ribeiro RM, Travassos LH. Autophagy and its interaction with intracellular bacterial pathogens. Front Immunol. 2018;9:935. http://www.ncbi.nlm.nih.gov/ pubmed/29875765. 53. Uribe-Querol E, Rosales C. Control of phagocytosis by microbial pathogens. Front Immunol. 2017;8:1368. http://www.ncbi.nlm.nih.gov/pubmed/29114249. 54. Beltrame MH, Boldt ABW, Catarino SJ, Mendes HC, Boschmann SE, Goeldner I, et al. MBL- associated serine proteases (MASPs) and infectious diseases. Mol Immunol. 2015;67:85–100. https://linkinghub.elsevier.com/retrieve/pii/S0161589015003491.
264
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
55. Haapasalo K, Meri S. Regulation of the complement system by pentraxins. Front Immunol. 2019;10:1750. http://www.ncbi.nlm.nih.gov/pubmed/31428091. 56. Sierra JM, Fusté E, Rabanal F, Vinuesa T, Viñas M. An overview of antimicrobial peptides and the latest advances in their development. Expert Opin Biol Ther. 2017;17:663–76. http:// www.ncbi.nlm.nih.gov/pubmed/28368216. 57. Land WG. Innate alloimmunity - Part 1: Innate immunity and host defense. 1st ed; 2011. https://www.amazon.com/Innate-A lloimmunity-P art-I mmunity-D efense-e book/dp/ B00W6PJ97M. 58. Cruz-Adalia A, Veiga E. Close encounters of lymphoid cells and bacteria. Front Immunol. 2016;7:405. http://journal.frontiersin.org/article/10.3389/fimmu.2016.00405/full. 59. Schmidt S, Ullrich E, Bochennek K, Zimmermann SY, Lehrnbecher T. Role of natural killer cells in antibacterial immunity. Expert Rev Hematol. 2016;9:1119–27. http://www.ncbi.nlm. nih.gov/pubmed/27791439. 60. Dantzler KW, Parte L, Jagannathan P. Emerging role of γδ T cells in vaccine‐mediated protection from infectious diseases. Clin Transl Immunol. 2019;8:e1072. http://www.ncbi.nlm. nih.gov/pubmed/31485329. 61. Meermeier EW, Harriff MJ, Karamooz E, Lewinsohn DM. MAIT cells and microbial immunity. Immunol Cell Biol. 2018;96:607–17. http://www.ncbi.nlm.nih.gov/pubmed/29451704. 62. Paget C, Trottein F. Mechanisms of bacterial superinfection post-influenza: a role for unconventional T cells. Front Immunol. 2019;10:336. http://www.ncbi.nlm.nih.gov/ pubmed/30881357. 63. Basset C, Holton J, O’Mahony R, Roitt I. Innate immunity and pathogen–host interaction. Vaccine. 2003;21:S12–23. https://linkinghub.elsevier.com/retrieve/pii/S0264410X03001956. 64. Stannard W, O’Callaghan C. Ciliary function and the role of cilia in clearance. J Aerosol Med. 2006;19:110–5. http://www.liebertpub.com/doi/10.1089/jam.2006.19.110. 65. Sperandio B, Fischer N, Sansonetti PJ. Mucosal physical and chemical innate barriers: lessons from microbial evasion strategies. Semin Immunol. 2015;27:111–8. https://linkinghub. elsevier.com/retrieve/pii/S1044532315000196. 66. Eyerich S, Eyerich K, Traidl-Hoffmann C, Biedermann T. Cutaneous barriers and skin immunity: differentiating a connected network. Trends Immunol. 2018;39:315–27. https://linkinghub.elsevier.com/retrieve/pii/S1471490618300280. 67. Fitzgerald KA, Kagan JC. Toll-like receptors and the control of immunity. Cell. 2020;180:1044–66. https://linkinghub.elsevier.com/retrieve/pii/S009286742030218X. 68. Latz E, Verma A, Visintin A, Gong M, Sirois CM, Klein DCG, et al. Ligand-induced conformational changes allosterically activate Toll-like receptor 9. Nat Immunol. 2007;8:772–9. http://www.nature.com/articles/ni1479. 69. Qiao Q, Wu H. Supramolecular organizing centers (SMOCs) as signaling machines in innate immune activation. Sci China Life Sci. 2015;58:1067–72. http://www.ncbi.nlm.nih.gov/ pubmed/26511517. 70. Wu H. Higher-order assemblies in a new paradigm of signal transduction. Cell. 2013;153:287–92. https://linkinghub.elsevier.com/retrieve/pii/S0092867413003358. 71. Kagan JC, Magupalli VG, Wu H. SMOCs: supramolecular organizing centres that control innate immunity. Nat Rev Immunol. 2014;14:821–6. http://www.nature.com/articles/ nri3757. 72. Tan Y, Kagan JC. Innate immune signaling organelles display natural and programmable signaling flexibility. Cell. 2019;177:384–398.e11. http://www.ncbi.nlm.nih.gov/ pubmed/30853218. 73. Balka KR, Nardo D. Understanding early TLR signaling through the Myddosome. J Leukoc Biol. 2019;105:339–51. https://onlinelibrary.wiley.com/doi/abs/10.1002/JLB. MR0318-096R. 74. Li X, Zhong C-Q, Yin Z, Qi H, Xu F, He Q, et al. Data-driven modeling identifies TIRAP- independent MyD88 activation complex and myddosome assembly strategy in LPS/TLR4 signaling. Int J Mol Sci. 2020;21:3061. https://www.mdpi.com/1422-0067/21/9/3061.
References
265
75. Gay NJ, Symmons MF, Gangloff M, Bryant CE. Assembly and localization of Toll-like receptor signalling complexes. Nat Rev Immunol. 2014;14:546–58. http://www.nature.com/ articles/nri3713. 76. Franklin BS, Latz E, Schmidt FI. The intra- and extracellular functions of ASC specks. Immunol Rev. 2018;281:74–87. http://www.ncbi.nlm.nih.gov/pubmed/29247990. 77. Whitmarsh AJ, Davis RJ. Transcription factor AP-1 regulation by mitogen-activated protein kinase signal transduction pathways. J Mol Med. 1996;74:589–607. http://link.springer. com/10.1007/s001090050063. 78. Mukherjee S, Karmakar S, Babu SPS. TLR2 and TLR4 mediated host immune responses in major infectious diseases: a review. Braz J Infect Dis. 2016;20:193–204. http://linkinghub. elsevier.com/retrieve/pii/S141386701500224X. 79. Wolf AJ, Underhill DM. Peptidoglycan recognition by the innate immune system. Nat Rev Immunol. 2018;18:243–54. http://www.nature.com/articles/nri.2017.136. 80. Mazgaeen L, Gurung P. Recent advances in lipopolysaccharide recognition systems. Int J Mol Sci. 2020;21:379. https://www.mdpi.com/1422-0067/21/2/379. 81. Jing T, Zhao B, Xu P, Gao X, Chi L, Han H, et al. The structural basis of IRF-3 Activation upon phosphorylation. J Immunol. 2020;205:1886–96. http://www.jimmunol.org/lookup/ doi/10.4049/jimmunol.2000026. 82. Zhao B, Shu C, Gao X, Sankaran B, Du F, Shelton CL, et al. Structural basis for concerted recruitment and activation of IRF-3 by innate immune adaptor proteins. Proc Natl Acad Sci. 2016;113:E3403–12. http://www.pnas.org/lookup/doi/10.1073/pnas.1603269113. 83. Cusson-Hermance N, Khurana S, Lee TH, Fitzgerald KA, Kelliher MA. Rip1 mediates the trif-dependent Toll-like receptor 3- and 4-induced NF-κB activation but does not contribute to interferon regulatory factor 3 activation. J Biol Chem. 2005;280:36560–6. https://doi. org/10.1074/jbc.M506831200. 84. Najjar M, Saleh D, Zelic M, Nogusa S, Shah S, Tai A, et al. RIPK1 and RIPK3 Kinases promote cell-death-independent inflammation by toll-like receptor 4. Immunity. 2016;45:46–59. https://linkinghub.elsevier.com/retrieve/pii/S1074761316302102. 85. Grootjans S, Vanden Berghe T, Vandenabeele P. Initiation and execution mechanisms of necroptosis: an overview. Cell Death Differ. 2017;24:1184–95. http://www.nature.com/ doifinder/10.1038/cdd.2017.65. 86. Fernandes-Alnemri T, Kang S, Anderson C, Sagara J, Fitzgerald KA, Alnemri ES. Cutting edge: TLR signaling licenses IRAK1 for rapid activation of the NLRP3 inflammasome. J Immunol. 2013;191:3995–9. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1301681. 87. Lin K-M, Hu W, Troutman TD, Jennings M, Brewer T, Li X, et al. IRAK-1 bypasses priming and directly links TLRs to rapid NLRP3 inflammasome activation. Proc Natl Acad Sci. 2014;111:775–80. http://www.pnas.org/cgi/doi/10.1073/pnas.1320294111. 88. Newton K, Dixit VM. Signaling in innate immunity and inflammation. Cold Spring Harb Perspect Biol. 2012;4:a006049. http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect.a006049. 89. Tan X, Sun L, Chen J, Chen ZJ. Detection of microbial infections through innate immune sensing of nucleic acids. Annu Rev Microbiol. 2018;72:447–78. https://www.annualreviews. org/doi/10.1146/annurev-micro-102215-095605. 90. Yang Q, Shu H-B. Deciphering the pathways to antiviral innate immunity and inflammation. Adv Immunol. 2020;145:1–36. https://linkinghub.elsevier.com/retrieve/pii/ S0065277619300677. 91. Zahid A, Ismail H, Li B, Jin T. Molecular and structural basis of DNA sensors in antiviral innate immunity. Front Immunol. 2020;11:613039. https://www.frontiersin.org/ articles/10.3389/fimmu.2020.613039/full. 92. Andreou AZ. DDX41: a multifunctional DEAD-box protein involved in pre-mRNA splicing and innate immunity. Biol Chem. 2021;402:645–51. https://www.degruyter.com/document/ doi/10.1515/hsz-2020-0367/html.
266
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
93. Miyake K, Shibata T, Ohto U, Shimizu T, Saitoh S-I, Fukui R, et al. Mechanisms controlling nucleic acid-sensing Toll-like receptors. Int Immunol. 2018;30:43–51. https://academic.oup. com/intimm/article/30/2/43/4857348. 94. Almuttaqi H, Udalova IA. Advances and challenges in targeting IRF5, a key regulator of inflammation. FEBS J. 2019;286:1624–37. https://febs.onlinelibrary.wiley.com/doi/ full/10.1111/febs.14654. 95. O’Neill LAJ, Bowie AG. The family of five: TIR-domain-containing adaptors in Toll-like receptor signalling. Nat Rev Immunol. 2007;7:353–64. http://www.ncbi.nlm.nih.gov/ pubmed/17457343. 96. McGettrick AF, O’Neill LA. Localisation and trafficking of Toll-like receptors: an important mode of regulation. Curr Opin Immunol. 2010;22:20–7. https://linkinghub.elsevier.com/ retrieve/pii/S0952791509002258. 97. Lee BL, Moon JE, Shu JH, Yuan L, Newman ZR, Schekman R, et al. UNC93B1 mediates differential trafficking of endosomal TLRs. elife. 2013;2:e00291. https://elifesciences.org/ articles/00291. 98. Meylan E, Burns K, Hofmann K, Blancheteau V, Martinon F, Kelliher M, et al. RIP1 is an essential mediator of Toll-like receptor 3–induced NF-κB activation. Nat Immunol. 2004;5:503–7. http://www.nature.com/articles/ni1061. 99. Riley JS, Tait SW. Mitochondrial DNA in inflammation and immunity. EMBO Rep. 2020;21:e49799. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132203/. 100. Vierbuchen T, Stein K, Heine H. RNA is taking its toll: impact of RNA-specific toll-like receptors on health and disease. Allergy Eur. J Allergy Clin Immunol. 2019;74:223–35. https://onlinelibrary.wiley.com/doi/full/10.1111/all.13680. 101. Rehwinkel J, Gack MU. RIG-I-like receptors: their regulation and roles in RNA sensing. Nat Rev Immunol. 2020;20:537–51. http://www.nature.com/articles/s41577-020-0288-3. 102. Ablasser A, Hur S. Regulation of cGAS- and RLR-mediated immunity to nucleic acids. Nat Immunol. 2020;21:17–29. http://www.nature.com/articles/s41590-019-0556-1. 103. Onomoto K, Onoguchi K, Yoneyama M. Regulation of RIG-I-like receptor-mediated signaling: interaction between host and viral factors. Cell Mol Immunol. 2021;18:539–55. http:// www.nature.com/articles/s41423-020-00602-7. 104. Uehata T, Takeuchi O. RNA recognition and immunity—innate immune sensing and its posttranscriptional regulation mechanisms. Cells. 2020;9:1701. https://www.mdpi. com/2073-4409/9/7/1701. 105. Hou J, Han L, Zhao Z, Liu H, Zhang L, Ma C, et al. USP18 positively regulates innate antiviral immunity by promoting K63-linked polyubiquitination of MAVS. Nat Commun. 2021;12:2970. http://www.nature.com/articles/s41467-021-23219-4. 106. Decout A, Katz JD, Venkatraman S, Ablasser A. The cGAS–STING pathway as a therapeutic target in inflammatory diseases. Nat Rev Immunol. 2021;21:548. http://www.nature.com/ articles/s41577-021-00524-z. 107. Yu L, Liu P. Cytosolic DNA sensing by cGAS: regulation, function, and human diseases. Signal Transduct Target Ther. 2021;6:170. http://www.nature.com/articles/s41392-021-00554-y. 108. Ma Z, Ni G, Damania B. Innate sensing of DNA virus genomes. Annu Rev Virol. 2018;5: 341–62. https://www.annualreviews.org/doi/10.1146/annurev-virology-092917-043244. 109. Briard B, Place DE, Kanneganti T-D. DNA sensing in the innate immune response. Physiology. 2020;35:112–24. https://www.physiology.org/doi/10.1152/physiol.00022.2019. 110. Balka KR, Louis C, Saunders TL, Smith AM, Calleja DJ, D’Silva DB, et al. TBK1 and IKKε Act redundantly to mediate STING-induced NF-κB responses in myeloid cells. Cell Rep. 2020;31:107492. https://linkinghub.elsevier.com/retrieve/pii/S2211124720303703. 111. Kim YK, Shin J-S, Nahm MH. NOD-like receptors in infection, immunity, and diseases. Yonsei Med J. 2016;57:5. https://eymj.org/DOIx.php?id=10.3349/ymj.2016.57.1.5. 112. Hsieh S-L, editor. Lectin in host defense against microbial infections. Cham: Springer; 2021. https://www.springer.com/gp/book/9789811515798. 113. Nikolakopoulou C, Willment JA, Brown GD. C-type lectin receptors in antifungal immunity. Adv Exp Med Biol. 2020;1204:1–30. http://link.springer.com/10.1007/978-981-15-1580-4_1.
References
267
114. Bermejo-Jambrina M, Eder J, Helgers LC, Hertoghs N, Nijmeijer BM, Stunnenberg M, et al. C-type lectin receptors in antiviral immunity and viral escape. Front Immunol. 2018;9:590. http://journal.frontiersin.org/article/10.3389/fimmu.2018.00590/full. 115. Mnich ME, van Dalen R, van Sorge NM. C-type lectin receptors in host defense against bacterial pathogens. Front Cell Infect Microbiol. 2020;10:309. https://www.frontiersin.org/ article/10.3389/fcimb.2020.00309/full. 116. Chiffoleau E. C-type lectin-like receptors as emerging orchestrators of sterile inflammation represent potential therapeutic targets. Front Immunol. 2018;9:227. http://journal.frontiersin. org/article/10.3389/fimmu.2018.00227/full. 117. Ciesielska A, Matyjek M, Kwiatkowska K. TLR4 and CD14 trafficking and its influence on LPS-induced pro-inflammatory signaling. Cell Mol Life Sci. 2021;78:1233–61. http://link. springer.com/10.1007/s00018-020-03656-y. 118. Oldenburg M, Kruger A, Ferstl R, Kaufmann A, Nees G, Sigmund A, et al. TLR13 Recognizes bacterial 23S rRNA devoid of erythromycin resistance-forming modification. Science. 2012;337:1111–5. https://www.sciencemag.org/lookup/doi/10.1126/science.1220363. 119. Krieg AM. CpG motifs in bacterial DNA and their immune effects. Annu Rev Immunol. 2002;20:709–60. http://www.annualreviews.org/doi/10.1146/annurev. immunol.20.100301.064842. 120. Osawa Y, Iho S, Takauji R, Takatsuka H, Yamamoto S, Takahashi T, et al. Collaborative action of NF-κB and p38 MAPK is involved in CpG DNA-induced IFN-α and chemokine production in human plasmacytoid dendritic cells. J Immunol. 2006;177:4841–52. http:// www.jimmunol.org/lookup/doi/10.4049/jimmunol.177.7.4841. 121. Lee H-C, Chathuranga K, Lee J-S. Intracellular sensing of viral genomes and viral evasion. Exp Mol Med. 2019;51:1–13. http://www.nature.com/articles/s12276-019-0299-y. 122. Koyama S, Ishii KJ, Coban C, Akira S. Innate immune response to viral infection. Cytokine. 2008;43:336–41. https://linkinghub.elsevier.com/retrieve/pii/S1043466608002214. 123. Kawai T, Akira S. Toll-like receptors and their crosstalk with other innate receptors in infection and immunity. Immunity. 2011;34:637–50. http://www.ncbi.nlm.nih.gov/ pubmed/21616434. 124. Maelfait J, Liverpool L, Rehwinkel J. Nucleic acid sensors and programmed cell death. J Mol Biol. 2020;432:552–68. http://www.ncbi.nlm.nih.gov/pubmed/31786265. 125. Koehler HS, Feng Y, Mandal P, Mocarski ES. Recognizing limits of Z-nucleic acid binding protein (ZBP1/DAI/DLM1) function. FEBS J. 2020;287:4362. 126. Okamoto M, Tsukamoto H, Kouwaki T, Seya T, Oshiumi H. Recognition of viral RNA by pattern recognition receptors in the induction of innate immunity and excessive inflammation during respiratory viral infections. Viral Immunol. 2017;30:408–20. http://www.ncbi.nlm. nih.gov/pubmed/28609250. 127. Almine JF, O’Hare CAJ, Dunphy G, Haga IR, Naik RJ, Atrih A, et al. IFI16 and cGAS cooperate in the activation of STING during DNA sensing in human keratinocytes. Nat Commun. 2017;8:14392. http://www.nature.com/articles/ncomms14392. 128. Hartmann G. Nucleic acid immunity. Adv Immunol. 2017;133:121–69. http://www.ncbi.nlm. nih.gov/pubmed/28215278. 129. Chen N, Xia P, Li S, Zhang T, Wang TT, Zhu J. RNA sensors of the innate immune system and their detection of pathogens. IUBMB Life. 2017;69:297–304. http://doi.wiley.com/10.1002/ iub.1625. 130. Banerjee A, Baid K, Mossman K. Molecular pathogenesis of middle east respiratory syndrome (MERS) coronavirus. Curr Clin Microb Rep. 2019;6:139–47. http://link.springer. com/10.1007/s40588-019-00122-7. 131. Lee J, Ghonime MG, Wang R, Cassady KA. The antiviral apparatus: STING and oncolytic virus restriction. Mol Ther Oncolytics. 2019;13:7–13. http://www.ncbi.nlm.nih.gov/ pubmed/30989105. 132. Heil M, Vega-Muñoz I. Nucleic acid sensing in mammals and plants: facts and caveats. Int Rev Cell Mol Biol. 2019;345:225–85. https://linkinghub.elsevier.com/retrieve/pii/ S1937644818301114.
268
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
133. Prompetchara E, Ketloy C, Palaga T. Immune responses in COVID-19 and potential vaccines: lessons learned from SARS and MERS epidemic. Asian Pac J Allergy Immunol. 2020;38:1–9. http://www.ncbi.nlm.nih.gov/pubmed/32105090. 134. Li G, Fan Y, Lai Y, Han T, Li Z, Zhou P, et al. Coronavirus infections and immune responses. J Med Virol. 2020;92:424–32. http://www.ncbi.nlm.nih.gov/pubmed/31981224. 135. Iampietro M, Younan P, Nishida A, Dutta M, Lubaki NM, Santos RI, et al. Ebola virus glycoprotein directly triggers T lymphocyte death despite of the lack of infection. PLoS Pathog. 2017;13:e1006397. http://www.ncbi.nlm.nih.gov/pubmed/28542576. 136. Shepardson KM, Schwarz B, Larson K, Morton RV, Avera J, McCoy K, et al. Induction of antiviral immune response through recognition of the repeating subunit pattern of viral capsids is toll-like receptor 2 dependent. MBio. 2017;8:e01356. https://mbio.asm.org/ content/8/6/e01356-17. 137. Boehme KW, Guerrero M, Compton T. Human cytomegalovirus envelope glycoproteins B and H are necessary for TLR2 activation in permissive cells. J Immunol. 2006;177:7094–102. http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.177.10.7094. 138. Del Cornò M, Cappon A, Donninelli G, Varano B, Marra F, Gessani S. HIV-1 gp120 signaling through TLR4 modulates innate immune activation in human macrophages and the biology of hepatic stellate cells. J Leukoc Biol. 2016;100:599–606. http://doi.wiley.com/10.1189/ jlb.4A1215-534R. 139. Shirato K, Kizaki T. SARS-CoV-2 spike protein S1 subunit induces pro-inflammatory responses via toll-like receptor 4 signaling in murine and human macrophages. Heliyon. 2021;7:e06187. https://linkinghub.elsevier.com/retrieve/pii/S2405844021002929. 140. Aboudounya MM, Heads RJ. COVID-19 and toll-like receptor 4 (TLR4): SARS-CoV-2 may bind and activate TLR4 to increase ACE2 expression, facilitating entry and causing hyperinflammation. Mediat Inflamm. 2021;2021:1–18. https://www.hindawi.com/journals/ mi/2021/8874339/. 141. Tatematsu M, Funami K, Seya T, Matsumoto M. Extracellular RNA sensing by pattern recognition receptors. J Innate Immun. 2018;10:398–406. https://www.karger.com/Article/ FullText/494034. 142. Nguyen TA, Smith BRC, Elgass KD, Creed SJ, Cheung S, Tate MD, et al. SIDT1 localizes to endolysosomes and mediates double-stranded RNA transport into the cytoplasm. J Immunol. 2019;202:3483–92. http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.1801369. 143. Yoneyama M, Kikuchi M, Natsukawa T, Shinobu N, Imaizumi T, Miyagishi M, et al. The RNA helicase RIG-I has an essential function in double-stranded RNA-induced innate antiviral responses. Nat Immunol. 2004;5:730–7. http://www.nature.com/articles/ni1087. 144. Wu J, Chen ZJ. Innate immune sensing and signaling of cytosolic nucleic acids. Annu Rev Immunol. 2014;32:461–88. http://www.annualreviews.org/doi/10.1146/ annurev-immunol-032713-120156. 145. Chow KT, Gale M, Loo Y-M. RIG-I and other RNA sensors in antiviral immunity. Annu Rev Immunol. 2018;36:667–94. http://www.annualreviews.org/doi/10.1146/ annurev-immunol-042617-053309. 146. Esser-Nobis K, Hatfield LD, Gale M. Spatiotemporal dynamics of innate immune signaling via RIG-I–like receptors. Proc Natl Acad Sci. 2020;117:15778–88. http://www.pnas.org/ lookup/doi/10.1073/pnas.1921861117. 147. Ren Z, Ding T, Zuo Z, Xu Z, Deng J, Wei Z. Regulation of MAVS expression and signaling function in the antiviral innate immune response. Front Immunol. 2020;11:1030. https:// www.frontiersin.org/article/10.3389/fimmu.2020.01030/full. 148. Ni G, Ma Z, Damania B. cGAS and STING: at the intersection of DNA and RNA virus- sensing networks. PLoS Pathog. 2018;14:e1007148. https://dx.plos.org/10.1371/journal. ppat.1007148. 149. Kouwaki T, Nishimura T, Wang G, Oshiumi H. RIG-I-like receptor-mediated recognition of viral genomic RNA of severe acute respiratory syndrome coronavirus-2 and viral escape from the host innate immune responses. Front Immunol. 2021;12:700926. https://www.frontiersin.org/articles/10.3389/fimmu.2021.700926/full.
References
269
150. Weber F, Wagner V, Rasmussen SB, Hartmann R, Paludan SR. Double-stranded RNA is produced by positive-strand RNA viruses and DNA viruses but not in detectable amounts by negative-strand RNA viruses. J Virol. 2006;80:5059–64. 151. Li SF, Gong MJ, Zhao FR, Shao JJ, Xie YL, Zhang YG, et al. Type I interferons: distinct biological activities and current applications for viral infection. Cell Physiol Biochem. 2018;51:2377–96. http://www.ncbi.nlm.nih.gov/pubmed/30537741. 152. Kindler E, Thiel V, Weber F. Interaction of SARS and MERS coronaviruses with the antiviral interferon response. Adv Virus Res. 2016;96:219–43. http://www.ncbi.nlm.nih.gov/ pubmed/27712625. 153. Totura AL, Whitmore A, Agnihothram S, Schäfer A, Katze MG, Heise MT, et al. Toll-like receptor 3 signaling via TRIF contributes to a protective innate immune response to severe acute respiratory syndrome coronavirus infection. MBio. 2015;6:e00638–15. http://www. ncbi.nlm.nih.gov/pubmed/26015500. 154. Kell AM, Gale M. RIG-I in RNA virus recognition. Virology. 2015;479–480:110–21. http:// www.ncbi.nlm.nih.gov/pubmed/25749629. 155. Zhao X, Chu H, Wong BH-Y, Chiu MC, Wang D, Li C, et al. Activation of C-type lectin receptor and (RIG)-I-like receptors contributes to proinflammatory response in middle east respiratory syndrome coronavirus-infected macrophages. J Infect Dis. 2020;221:647–59. http://www.ncbi.nlm.nih.gov/pubmed/31562757. 156. Lee JY, Kim SJ, Myoung J. Middle East respiratory syndrome coronavirus-encoded ORF8B inhibits RIG-I-like receptors by a differential mechanism. J Microbiol Biotechnol. 2019;29:2014–21. http://www.ncbi.nlm.nih.gov/pubmed/31838791. 157. Hasan UA, Bates E, Takeshita F, Biliato A, Accardi R, Bouvard V, et al. TLR9 Expression and function is abolished by the cervical cancer-associated human papillomavirus type 16. J Immunol. 2007;178:3186–97. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.178.5.3186. 158. Fiola S, Gosselin D, Takada K, Gosselin J. TLR9 contributes to the recognition of EBV by primary monocytes and plasmacytoid dendritic cells. J Immunol. 2010;185:3620–31. http:// www.jimmunol.org/lookup/doi/10.4049/jimmunol.0903736. 159. Ma Z, Damania B. The cGAS-STING defense pathway and its counteraction by viruses. Cell Host Microbe. 2016;19:150–8. https://linkinghub.elsevier.com/retrieve/pii/ S1931312816300099. 160. Ablasser A, Bauernfeind F, Hartmann G, Latz E, Fitzgerald KA, Hornung V. RIG-Idependent sensing of poly(dA:dT) through the induction of an RNA polymerase III–transcribed RNA intermediate. Nat Immunol. 2009;10:1065–72. http://www.nature.com/ articles/ni.1779. 161. Chiu Y-H, MacMillan JB, Chen ZJ. RNA polymerase III detects cytosolic DNA and induces type I interferons through the RIG-I pathway. Cell. 2009;138:576–91. https://linkinghub.elsevier.com/retrieve/pii/S0092867409007144. 162. Lin H, Cao X. Nuclear innate sensors for nucleic acids in immunity and inflammation. Immunol Rev. 2020;297:162–73. https://onlinelibrary.wiley.com/doi/abs/10.1111/imr.12893. 163. Zhang F, Yuan Y, Ma F. Function and regulation of nuclear DNA sensors during viral infection and tumorigenesis. Front Immunol. 2021;11:624556. https://www.frontiersin.org/ articles/10.3389/fimmu.2020.624556/full. 164. Sui H, Chen Q, Imamichi T. Cytoplasmic‐translocated Ku70 senses intracellular DNA and mediates interferon‐lambda1 induction. Immunology. 2021;163:323. https://onlinelibrary. wiley.com/doi/10.1111/imm.13318. 165. Chan YK, Gack MU. Viral evasion of intracellular DNA and RNA sensing. Nat Rev Microbiol. 2016;14:360–73. http://www.nature.com/articles/nrmicro.2016.45. 166. Platanitis E, Demiroz D, Schneller A, Fischer K, Capelle C, Hartl M, et al. A molecular switch from STAT2-IRF9 to ISGF3 underlies interferon-induced gene transcription. Nat Commun. 2019;10:2921. http://www.nature.com/articles/s41467-019-10970-y. 167. Schoggins JW. Interferon-stimulated genes: what do they all do? Annu Rev Virol. 2019;6: 567–84. https://www.annualreviews.org/doi/10.1146/annurev-virology-092818-015756.
270
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
168. Boxx GM, Cheng G. The roles of type I interferon in bacterial infection. Cell Host Microbe. 2016;19:760–9. http://linkinghub.elsevier.com/retrieve/pii/S1931312816302128. 169. Liu T, Zhang L, Joo D, Sun S-C. NF-κB signaling in inflammation. Signal Transduct Target Ther. 2017;2:17023. http://www.nature.com/articles/sigtrans201723. 170. Dorrington MG, Fraser IDC. NF-κB Signaling in macrophages: dynamics, crosstalk, and signal integration. Front Immunol. 2019;10:705. https://www.frontiersin.org/article/10.3389/ fimmu.2019.00705/full. 171. Holbrook J, Lara-Reyna S, Jarosz-Griffiths H, McDermott MF. Tumour necrosis factor signalling in health and disease. F1000Research. 2019;8:111. https://f1000research.com/ articles/8-111/v1. 172. Gough P, Myles IA. Tumor necrosis factor receptors: pleiotropic signaling complexes and their differential effects. Front Immunol. 2020;11:585880. https://www.frontiersin.org/ articles/10.3389/fimmu.2020.585880/full. 173. Shoham S, Levitz SM. The immune response to fungal infections. Br J Haematol. 2005;129:569–82. http://doi.wiley.com/10.1111/j.1365-2141.2005.05397.x. 174. Lionakis MS, Iliev ID, Hohl TM. Immunity against fungi. JCI Insight. 2017;2:e93156. https://insight.jci.org/articles/view/93156. 175. Erwig LP, Gow NAR. Interactions of fungal pathogens with phagocytes. Nat Rev Microbiol. 2016;14:163–76. http://www.nature.com/articles/nrmicro.2015.21. 176. Kawakami K. Immune response and its clinical significance in fungal infection. Nihon Rinsho. 2008;66:2245–53. https://pubmed.ncbi.nlm.nih.gov/19069087/. 177. Ishii K, Kawakami K. Pattern recognition and host defense response to Cryptococcus neoformans. Med Mycol J. 2012;53:247–54. https://www.jstage.jst.go.jp/article/ mmj/53/4/53_247/_article/-char/ja/. 178. Bojang E, Ghuman H, Kumwenda P, Hall RA. Immune sensing of Candida albicans. J Fungi. 2021;7:119. https://www.mdpi.com/2309-608X/7/2/119. 179. Ghosh D, Stumhofer J. Do you see what I see: recognition of protozoan parasites by toll-like receptors. Curr Immunol Rev. 2014;9:129–40. http://www.eurekaselect.com/openurl/content.php?genre=article&issn=1573-3955&volume=9&issue=3&spage=129. 180. Gurung P, Kanneganti T-D. Immune responses against protozoan parasites: a focus on the emerging role of Nod-like receptors. Cell Mol Life Sci. 2016;73:3035–51. http://link. springer.com/10.1007/s00018-016-2212-3. 181. Motran CC, Silvane L, Chiapello LS, Theumer MG, Ambrosio LF, Volpini X, et al. Helminth infections: recognition and modulation of the immune response by innate immune cells. Front Immunol. 2018;9:664. http://journal.frontiersin.org/article/10.3389/ fimmu.2018.00664/full. 182. Lobo PI. Role of natural autoantibodies and natural IgM anti-leucocyte autoantibodies in health and disease. Front Immunol. 2016;7:198. http://www.ncbi.nlm.nih.gov/pubmed/27375614. 183. Bottazzi B, Doni A, Garlanda C, Mantovani A. An integrated view of humoral innate immunity: pentraxins as a paradigm. Annu Rev Immunol. 2010;28:157–83. https://www.annualreviews.org/doi/10.1146/annurev-immunol-030409-101305. 184. Jaillon S, Ponzetta A, Magrini E, Barajon I, Barbagallo M, Garlanda C, et al. Fluid phase recognition molecules in neutrophil-dependent immune responses. Semin Immunol. 2016;28:109–18. http://www.ncbi.nlm.nih.gov/pubmed/27021644. 185. Litvack ML, Palaniyar N. Review: Soluble innate immune pattern-recognition proteins for clearing dying cells and cellular components: implications on exacerbating or resolving inflammation. Innate Immun. 2010;16:191–200. http://www.ncbi.nlm.nih.gov/ pubmed/20529971. 186. Ma YJ, Lee BL, Garred P. An overview of the synergy and crosstalk between pentraxins and collectins/ficolins: their functional relevance in complement activation. Exp Mol Med. 2017;49:e320. http://www.nature.com/articles/emm201751. 187. Smole U, Kratzer B, Pickl WF. Soluble pattern recognition molecules: guardians and regulators of homeostasis at airway mucosal surfaces. Eur J Immunol. 2020;50:624–42. https:// onlinelibrary.wiley.com/doi/abs/10.1002/eji.201847811.
References
271
188. Thielens NM, Tedesco F, Bohlson SS, Gaboriaud C, Tenner AJ. C1q: a fresh look upon an old molecule. Mol Immunol. 2017;89:73–83. https://linkinghub.elsevier.com/retrieve/pii/ S0161589017301591. 189. Reid KBM. Complement component C1q: historical perspective of a functionally versatile, and structurally unusual, serum protein. Front Immunol. 2018;9:764. http://journal.frontiersin.org/article/10.3389/fimmu.2018.00764/full. 190. Foo S-S, Reading PC, Jaillon S, Mantovani A, Mahalingam S. Pentraxins and collectins: friend or foe during pathogen invasion? Trends Microbiol. 2015;23:799–811. https://linkinghub.elsevier.com/retrieve/pii/S0966842X15002243. 191. Porte R, Davoudian S, Asgari F, Parente R, Mantovani A, Garlanda C, et al. The long pentraxin PTX3 as a humoral innate immunity functional player and biomarker of infections and sepsis. Front Immunol. 2019;10:794. https://www.frontiersin.org/article/10.3389/ fimmu.2019.00794/full. 192. Ma YJ, Garred P. Pentraxins in complement activation and regulation. Front Immunol. 2018;9:3046. https://www.frontiersin.org/article/10.3389/fimmu.2018.03046/full. 193. Perez L. Acute phase protein response to viral infection and vaccination. Arch Biochem Biophys. 2019;671:196–202. https://linkinghub.elsevier.com/retrieve/pii/ S0003986119303212. 194. Gupta G, Surolia A. Collectins: sentinels of innate immunity. BioEssays. 2007;29:452–64. http://www.ncbi.nlm.nih.gov/pubmed/17450595. 195. Ren Y, Ding Q, Zhang X. Ficolins and infectious diseases. Virol Sin. 2014;29:25–32. http:// www.ncbi.nlm.nih.gov/pubmed/24452543. 196. Endo Y, Matsushita M, Fujita T. New insights into the role of ficolins in the lectin pathway of innate immunity. Int Rev Cell Mol Biol. 2015;316:49–110. http://www.ncbi.nlm.nih.gov/ pubmed/25805122. 197. Stravalaci M, Pagani I, Paraboschi EM, Pedotti M, Doni A, Scavello F, et al. Recognition and inhibition of SARS-CoV-2 by humoral innate immunity pattern recognition molecules. Nat Immunol. 2022;23:275–86. https://www.nature.com/articles/s41590-021-01114-w. 198. Zhang Q, Cao X. Epigenetic regulation of the innate immune response to infection. Nat Rev Immunol. 2019;19:417–32. http://www.nature.com/articles/s41577-019-0151-6. 199. Casanova J-L, Abel L. The genetic theory of infectious diseases: a brief history and selected illustrations. Annu Rev Genomics Hum Genet. 2013;14:215–43. http://www.annualreviews. org/doi/10.1146/annurev-genom-091212-153448. 200. Casanova J-L. Severe infectious diseases of childhood as monogenic inborn errors of immunity. Proc Natl Acad Sci. 2015;112:E7128–37. http://www.pnas.org/lookup/doi/10.1073/ pnas.1521651112. 201. Casanova J-L. Human genetic basis of interindividual variability in the course of infection. Proc Natl Acad Sci. 2015;112:E7118–27. http://www.pnas.org/lookup/doi/10.1073/ pnas.1521644112. 202. Casanova J-L, Abel L. Human genetics of infectious diseases: unique insights into immunological redundancy. Semin Immunol. 2018;36:1–12. https://linkinghub.elsevier.com/retrieve/ pii/S1044532317301239. 203. Nashef A, Agbaria M, Shusterman A, Lorè NI, Bragonzi A, Wiess E, et al. Dissection of host susceptibility to bacterial infections and its toxins. Methods Mol Biol. 2017;1488:551–78. http://link.springer.com/10.1007/978-1-4939-6427-7_27. 204. Mozzi A, Pontremoli C, Sironi M. Genetic susceptibility to infectious diseases: current status and future perspectives from genome-wide approaches. Infect Genet Evol. 2018;66:286–307. https://linkinghub.elsevier.com/retrieve/pii/S1567134817303349. 205. Mukherjee S, Huda S, Sinha Babu SP. Toll‐like receptor polymorphism in host immune response to infectious diseases: a review. Scand J Immunol. 2019;90:e12771. https://onlinelibrary.wiley.com/doi/abs/10.1111/sji.12771. 206. Netea MG, Domínguez-Andrés J, Barreiro LB, Chavakis T, Divangahi M, Fuchs E, et al. Defining trained immunity and its role in health and disease. Nat Rev Immunol. 2020;20:375–88. http://www.nature.com/articles/s41577-020-0285-6.
272
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
207. Koeken VACM, Crevel R, Netea MG, Li Y. Resolving trained immunity with systems biology. Eur J Immunol. 2021;51:773–84. https://onlinelibrary.wiley.com/doi/10.1002/eji.202048882. 208. Netea MG, Schlitzer A, Placek K, Joosten LAB, Schultze JL. Innate and adaptive immune memory: an evolutionary continuum in the host’s response to pathogens. Cell Host Microbe. 2019;25:13–26. https://linkinghub.elsevier.com/retrieve/pii/S1931312818306334. 209. Netea MG, Giamarellos-Bourboulis EJ, Domínguez-Andrés J, Curtis N, van Crevel R, van de Veerdonk FL, et al. Trained immunity: a tool for reducing susceptibility to and the severity of SARS-CoV-2 infection. Cell. 2020;181:969–77. https://linkinghub.elsevier.com/retrieve/ pii/S0092867420305079. 210. Tsilika M, Taks E, Dolianitis K, Kotsaki A, Leventogiannis K, Damoulari C, et al. ACTIVATE-2: a double-blind randomized trial of BCG vaccination against COVID-19 in individuals at risk. Front Immunol. 2022;13:873067. https://www.frontiersin.org/ articles/10.3389/fimmu.2022.873067/full. 211. Dominguez-Andres J, Netea MG. Long-term reprogramming of the innate immune system. J Leukoc Biol. 2019;105:329–38. https://onlinelibrary.wiley.com/doi/abs/10.1002/JLB. MR0318-104R. 212. Bekkering S, Quintin J, Joosten LAB, van der Meer JWM, Netea MG, Riksen NP. Oxidized low-density lipoprotein induces long-term proinflammatory cytokine production and foam cell formation via epigenetic reprogramming of monocytes. Arterioscler Thromb Vasc Biol. 2014;34:1731–8. http://atvb.ahajournals.org/cgi/doi/10.1161/ATVBAHA.114.303887. 213. van der Valk FM, Bekkering S, Kroon J, Yeang C, Van den Bossche J, van Buul JD, et al. Oxidized phospholipids on lipoprotein(a) elicit arterial wall inflammation and an inflammatory monocyte response in humans. Circulation. 2016;134:611–24. https://www.ahajournals. org/doi/10.1161/CIRCULATIONAHA.116.020838. 214. Neidhart M, Pajak A, Laskari K, Riksen NP, Joosten LAB, Netea MG, et al. Oligomeric S100A4 is associated with monocyte innate immune memory and bypass of tolerance to subsequent stimulation with lipopolysaccharides. Front Immunol. 2019;10:791. http://www. ncbi.nlm.nih.gov/pubmed/31037071. 215. Liu J, Cao X. Cellular and molecular regulation of innate inflammatory responses. Cell Mol Immunol. 2016;13:711–21. http://www.nature.com/doifinder/10.1038/cmi.2016.58. 216. Li Z, Lu G, Meng G. Pathogenic fungal infection in the lung. Front Immunol. 2019;10:1524. https://www.frontiersin.org/article/10.3389/fimmu.2019.01524/full. 217. Kumar S, Ingle H, Prasad DVR, Kumar H. Recognition of bacterial infection by innate immune sensors. Crit Rev Microbiol. 2013;39:229–46. http://www.tandfonline.com/doi/ful l/10.3109/1040841X.2012.706249. 218. Heung LJ. Monocytes and the host response to fungal pathogens. Front Cell Infect Microbiol. 2020;10:34. https://www.frontiersin.org/article/10.3389/fcimb.2020.00034/full. 219. Shaul ME, Fridlender ZG. Neutrophils as active regulators of the immune system in the tumor microenvironment. J Leukoc Biol. 2017;102:343–9. http://doi.wiley.com/10.1189/ jlb.5MR1216-508R. 220. Ohms M, Möller S, Laskay T. An attempt to polarize human neutrophils toward N1 and N2 Phenotypes in vitro. Front Immunol. 2020;11:532. https://www.frontiersin.org/ article/10.3389/fimmu.2020.00532/full. 221. Benoit M, Desnues B, Mege J-L. Macrophage polarization in bacterial infections. J Immunol. 2008;181:3733–9. http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.181.6.3733. 222. Atri C, Guerfali F, Laouini D. Role of human macrophage polarization in inflammation during infectious diseases. Int J Mol Sci. 2018;19:1801. http://www.mdpi.com/1422-0067/19/6/1801. 223. Orecchioni M, Ghosheh Y, Pramod AB, Ley K. Macrophage polarization: different gene signatures in M1(LPS+) vs. classically and M2(LPS–) vs. alternatively activated macrophages. Front Immunol. 2019;10:1084. https://www.frontiersin.org/article/10.3389/ fimmu.2019.01084/full. 224. Lee KY. M1 and M2 polarization of macrophages: a mini-review. Med Biol Sci Eng. 2019;2:1–5. http://www.embse.org/journal/view.html?doi=10.30579/mbse.2019.2.1.1.
References
273
225. Liew PX, Kubes P. The neutrophil’s role during health and disease. Physiol Rev. 2019;99:1223–48. https://www.physiology.org/doi/10.1152/physrev.00012.2018. 226. Sanders CJ, Doherty PC, Thomas PG. Respiratory epithelial cells in innate immunity to influenza virus infection. Cell Tissue Res. 2011;343:13–21. http://link.springer.com/10.1007/ s00441-010-1043-z. 227. Vadeboncoeur N, Segura M, Al-Numani D, Vanier G, Gottschalk M. Pro-inflammatory cytokine and chemokine release by human brain microvascular endothelial cells stimulated by Streptococcus suis serotype 2. FEMS Immunol Med Microbiol. 2003;35:49–58. https://academic.oup.com/femspd/article-lookup/doi/10.1111/j.1574-695X.2003.tb00648.x. 228. Netea MG, Kullberg BJ, Van der Meer JWM. Circulating cytokines as mediators of fever. Clin Infect Dis. 2000;31:S178–84. http://academic.oup.com/cid/article/31/Supplement_5/ S178/333323/Circulating-Cytokines-as-Mediators-of-Fever. 229. Samad TA, Moore KA, Sapirstein A, Billet S, Allchorne A, Poole S, et al. Interleukin-1β- mediated induction of Cox-2 in the CNS contributes to inflammatory pain hypersensitivity. Nature. 2001;410:471–5. http://www.nature.com/articles/35068566. 230. Hollenberg SM, Cunnion RE, Parrillo JE. The effect of tumor necrosis factor on vascular smooth muscle. Chest. 1991;100:1133–7. https://linkinghub.elsevier.com/retrieve/pii/ S0012369216325235. 231. Hofmann S, Grasberger H, Jung P, Bidlingmaier M, Vlotides J, Janssen OE, et al. The tumour necrosis factor-alpha induced vascular permeability is associated with a reduction of VE-cadherin expression. Eur J Med Res. 2002;7:171–6. https://pubmed.ncbi.nlm.nih. gov/12010652/. 232. Uribe-Querol E, Rosales C. Phagocytosis: our current understanding of a universal biological process. Front Immunol. 2020;11:1066. https://www.frontiersin.org/article/10.3389/ fimmu.2020.01066/full. 233. Kitai Y, Sato K, Tanno D, Yuan X, Umeki A, Kasamatsu J, et al. Role of dectin-2 in the phagocytosis of Cryptococcus neoformans by dendritic cells. Infect Immun. 2021;89:e0033021. https://journals.asm.org/doi/10.1128/IAI.00330-21. 234. Merle NS, Church SE, Fremeaux-Bacchi V, Roumenina LT. Complement system Part I Molecular mechanisms of activation and regulation. Front Immunol. 2015;6:262. http:// www.ncbi.nlm.nih.gov/pubmed/26082779. 235. Bajic G, Degn SE, Thiel S, Andersen GR. Complement activation, regulation, and molecular basis for complement-related diseases. EMBO J. 2015;34:2735–57. http://emboj.embopress. org/cgi/doi/10.15252/embj.201591881. 236. Ricklin D, Hajishengallis G, Yang K, Lambris JD. Complement: a key system for immune surveillance and homeostasis. Nat Immunol. 2010;11:785–97. http://www.nature.com/ doifinder/10.1038/ni.1923. 237. Harboe M, Mollnes TE. The alternative complement pathway revisited. J Cell Mol Med. 2008;12:1074–84. http://doi.wiley.com/10.1111/j.1582-4934.2008.00350.x. 238. Lachmann PJ. The amplification loop of the complement pathways. Adv Immunol. 2009;104:115–49. http://linkinghub.elsevier.com/retrieve/pii/S0065277608040042. 239. Heesterbeek DAC, Angelier ML, Harrison RA, Rooijakkers SHM. Complement and bacterial infections: from molecular mechanisms to therapeutic applications. J Innate Immun. 2018;10:455–64. https://www.karger.com/Article/FullText/491439. 240. van den Broek B, van der Flier M, de Groot R, de Jonge MI, Langereis JD. Common genetic variants in the complement system and their potential link with disease susceptibility and outcome of invasive bacterial infection. J Innate Immun. 2020;12:131–41. https://www.karger. com/Article/FullText/500545. 241. Serhan CN, Levy BD. Resolvins in inflammation: emergence of the pro-resolving superfamily of mediators. J Clin Invest. 2018;128:2657–69. http://www.ncbi.nlm.nih.gov/ pubmed/29757195. 242. Feehan KT, Gilroy DW. Is resolution the end of inflammation? Trends Mol Med. 2019;25:198–214. http://www.cell.com/article/S1471491419300176/fulltext.
274
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
243. Chiang N, Serhan CN. Specialized pro-resolving mediator network: an update on production and actions. Essays Biochem. 2020;64:443–62. https://portlandpress.com/essaysbiochem/ article/64/3/443/226308/Specialized-pro-resolving-mediator-network-an. 244. Serhan CN, Gupta SK, Perretti M, Godson C, Brennan E, Li Y, et al. The atlas of inflammation resolution (AIR). Mol Asp Med. 2020;74:100894. https://linkinghub.elsevier.com/ retrieve/pii/S0098299720300960. 245. Savill J. Apoptosis in resolution of inflammation. J Leukoc Biol. 1997;61:375–80. http:// www.ncbi.nlm.nih.gov/pubmed/9103222. 246. Fullerton JN, Gilroy DW. Resolution of inflammation: a new therapeutic frontier. Nat Rev Drug Discov. 2016;15:551–67. http://www.ncbi.nlm.nih.gov/pubmed/27020098. 247. Green DR, Oguin TH, Martinez J. The clearance of dying cells: table for two. Cell Death Differ. 2016;23:915–26. http://www.nature.com/articles/cdd2015172. 248. Elliott MR, Koster KM, Murphy PS. Efferocytosis signaling in the regulation of macrophage inflammatory responses. J Immunol. 2017;198:1387–94. http://www.ncbi.nlm.nih.gov/ pubmed/28167649. 249. Greenlee-Wacker MC. Clearance of apoptotic neutrophils and resolution of inflammation. Immunol Rev. 2016;273:357–70. http://www.ncbi.nlm.nih.gov/pubmed/27558346. 250. Freeman GJ, Casasnovas JM, Umetsu DT, DeKruyff RH. TIM genes: a family of cell surface phosphatidylserine receptors that regulate innate and adaptive immunity. Immunol Rev. 2010;235:172–89. http://www.ncbi.nlm.nih.gov/pubmed/20536563. 251. Rothlin CV, Carrera-Silva EA, Bosurgi L, Ghosh S. TAM receptor signaling in immune homeostasis. Annu Rev Immunol. 2015;33:355–91. http://www.ncbi.nlm.nih.gov/ pubmed/25594431. 252. Doran AC, Yurdagul A, Tabas I. Efferocytosis in health and disease. Nat Rev Immunol. 2020;20:254–67. http://www.nature.com/articles/s41577-019-0240-6. 253. Murray PJ. Macrophage polarization. Annu Rev Physiol. 2017;79:541–66. http://www.annualreviews.org/doi/10.1146/annurev-physiol-022516-034339. 254. O’Neill LAJ, Artyomov MN. Itaconate: the poster child of metabolic reprogramming in macrophage function. Nat Rev Immunol. 2019;19:273. http://www.ncbi.nlm.nih.gov/ pubmed/30705422. 255. Patel U, Rajasingh S, Samanta S, Cao T, Dawn B, Rajasingh J. Macrophage polarization in response to epigenetic modifiers during infection and inflammation. Drug Discov Today. 2017;22:186–93. http://www.ncbi.nlm.nih.gov/pubmed/27554801. 256. Zhou D, Yang K, Chen L, Zhang W, Xu Z, Zuo J, et al. Promising landscape for regulating macrophage polarization: epigenetic viewpoint. Oncotarget. 2017;8:57693–706. http://www. ncbi.nlm.nih.gov/pubmed/28915705. 257. Hallowell RW, Collins SL, Craig JM, Zhang Y, Oh M, Illei PB, et al. mTORC2 signalling regulates M2 macrophage differentiation in response to helminth infection and adaptive thermogenesis. Nat Commun. 2017;8:14208. http://www.nature.com/doifinder/10.1038/ ncomms14208. 258. Biswas SK, Gangi L, Paul S, Schioppa T, Saccani A, Sironi M, et al. A distinct and unique transcriptional program expressed by tumor-associated macrophages (defective NF-kappaB and enhanced IRF-3/STAT1 activation). Blood. 2006;107:2112–22. http://www.bloodjournal. org/cgi/doi/10.1182/blood-2005-01-0428. 259. Fridlender ZG, Sun J, Kim S, Kapoor V, Cheng G, Ling L, et al. Polarization of tumor- associated neutrophil phenotype by TGF-β: “N1” versus “N2” TAN. Cancer Cell. 2009;16:183–94. https://linkinghub.elsevier.com/retrieve/pii/S1535610809002153. 260. Prame Kumar K, Nicholls AJ, Wong CHY. Partners in crime: neutrophils and monocytes/ macrophages in inflammation and disease. Cell Tissue Res. 2018;371:551–65. http://link. springer.com/10.1007/s00441-017-2753-2. 261. Scalerandi MV, Peinetti N, Leimgruber C, Cuello Rubio MM, Nicola JP, Menezes GB, et al. Inefficient N2-like neutrophils are promoted by androgens during infection. Front Immunol. 2018;9:1980. https://www.frontiersin.org/article/10.3389/fimmu.2018.01980/full.
References
275
262. Wang X, Qiu L, Li Z, Wang X-Y, Yi H. Understanding the multifaceted role of neutrophils in cancer and autoimmune diseases. Front Immunol. 2018;9:2456. https://www.frontiersin.org/ article/10.3389/fimmu.2018.02456/full. 263. Giese MA, Hind LE, Huttenlocher A. Neutrophil plasticity in the tumor microenvironment. Blood. 2019;133:2159–67. https://ashpublications.org/blood/article/133/20/2159/273823/ Neutrophil-plasticity-in-the-tumor. 264. Dalli J. Does promoting resolution instead of inhibiting inflammation represent the new paradigm in treating infections? Mol Asp Med. 2017;58:12–20. http://linkinghub.elsevier.com/ retrieve/pii/S0098299717300213. 265. Lee S, Nakahira K, Dalli J, Siempos II, Norris PC, Colas RA, et al. NLRP3 inflammasome deficiency protects against microbial sepsis via increased lipoxin B 4 synthesis. Am J Respir Crit Care Med. 2017;196:713–26. http://www.atsjournals.org/doi/10.1164/ rccm.201604-0892OC. 266. Lopategi A, Flores-Costa R, Rius B, López-Vicario C, Alcaraz-Quiles J, Titos E, et al. Frontline science: specialized proresolving lipid mediators inhibit the priming and activation of the macrophage NLRP3 inflammasome. J Leukoc Biol. 2019;105:25–36. http://doi.wiley. com/10.1002/JLB.3HI0517-206RR. 267. Machado MG, Tavares LP, Souza GVS, Queiroz‐Junior CM, Ascenção FR, Lopes ME, et al. The Annexin A1/FPR2 pathway controls the inflammatory response and bacterial dissemination in experimental pneumococcal pneumonia. FASEB J. 2020;34:2749–64. https://onlinelibrary.wiley.com/doi/10.1096/fj.201902172R. 268. Basil MC, Levy BD. Specialized pro-resolving mediators: endogenous regulators of infection and inflammation. Nat Rev Immunol. 2016;16:51–67. http://www.nature.com/articles/ nri.2015.4. 269. Sandhaus S, Swick AG. Specialized proresolving mediators in infection and lung injury. Biofactors. 2021;47:6–18. https://onlinelibrary.wiley.com/doi/10.1002/biof.1691. 270. Van Dyke TE. Shifting the paradigm from inhibitors of inflammation to resolvers of inflammation in periodontitis. J Periodontol. 2020;91:S19–25. https://onlinelibrary.wiley.com/ doi/10.1002/JPER.20-0088. 271. Aubeux D, Peters OA, Hosseinpour S, Tessier S, Geoffroy V, Pérez F, et al. Specialized pro- resolving lipid mediators in endodontics: a narrative review. BMC Oral Health. 2021;21:276. https://bmcoralhealth.biomedcentral.com/articles/10.1186/s12903-021-01619-8. 272. Osorio Parra MM, Elangovan S, Lee C. Specialized pro‐resolving lipid mediators in experimental periodontitis: a systematic review. Oral Dis. 2019;25:1265–76. https://onlinelibrary. wiley.com/doi/10.1111/odi.12979. 273. Morita M, Kuba K, Ichikawa A, Nakayama M, Katahira J, Iwamoto R, et al. The lipid mediator protectin D1 inhibits influenza virus replication and improves severe influenza. Cell. 2013;153:112–25. https://linkinghub.elsevier.com/retrieve/pii/S009286741300216X. 274. Rajasagi NK, Reddy PBJ, Mulik S, Gjorstrup P, Rouse BT. Neuroprotectin D1 reduces the severity of herpes simplex virus–induced corneal immunopathology. Investig Ophthalmol Vis Sci. 2013;54:6269. http://iovs.arvojournals.org/article.aspx?doi=10.1167/iovs.13-12152. 275. Shirey KA, Lai W, Pletneva LM, Karp CL, Divanovic S, Blanco JCG, et al. Role of the lipoxygenase pathway in RSV-induced alternatively activated macrophages leading to resolution of lung pathology. Mucosal Immunol. 2014;7:549–57. http://www.nature.com/articles/ mi201371. 276. Lee CH. Role of specialized pro-resolving lipid mediators and their receptors in virus infection: a promising therapeutic strategy for SARS-CoV-2 cytokine storm. Arch Pharm Res. 2021;44:84–98. http://link.springer.com/10.1007/s12272-020-01299-y. 277. Jordan PM, Werz O. Specialized pro‐resolving mediators: biosynthesis and biological role in bacterial infections. FEBS J. 2022;289:4212–27. https://onlinelibrary.wiley.com/ doi/10.1111/febs.16266. 278. Vivier E, Artis D, Colonna M, Diefenbach A, Di Santo JP, Eberl G, et al. Innate lymphoid cells: 10 years on. Cell. 2018;174:1054–66. https://linkinghub.elsevier.com/retrieve/pii/ S0092867418309115.
276
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
279. Klose CSN, Artis D. Innate lymphoid cells control signaling circuits to regulate tissue-specific immunity. Cell Res. 2020;30:475–91. http://www.nature.com/articles/s41422-020-0323-8. 280. Kim Y, Born C, Bléry M, Steinle A. MICAgen mice recapitulate the highly restricted but activation-inducible expression of the paradigmatic human NKG2D ligand MICA. Front Immunol. 2020;11:960. https://www.frontiersin.org/article/10.3389/fimmu.2020.00960/full. 281. Abel AM, Yang C, Thakar MS, Malarkannan S. Natural killer cells: development, maturation, and clinical utilization. Front Immunol. 2018;9:1869. https://www.frontiersin.org/ article/10.3389/fimmu.2018.01869/full. 282. Vivier E, Tomasello E, Baratin M, Walzer T, Ugolini S. Functions of natural killer cells. Nat Immunol. 2008;9:503–10. http://www.nature.com/articles/ni1582. 283. Lanier LL. NKG2D receptor and its ligands in host defense. Cancer Immunol Res. 2015;3:575–82. http://cancerimmunolres.aacrjournals.org/cgi/doi/10.1158/2326-6066. CIR-15-0098. 284. Jost S, Altfeld M. Control of human viral infections by natural killer cells. Annu Rev Immunol. 2013;31:163–94. http://www.annualreviews.org/doi/10.1146/ annurev-immunol-032712-100001. 285. Sun J, Lanier L. The natural selection of herpesviruses and virus-specific NK cell receptors. Viruses. 2009;1:362–82. http://www.mdpi.com/1999-4915/1/3/362. 286. Loewendorf A, Benedict CA. Modulation of host innate and adaptive immune defenses by cytomegalovirus: timing is everything. J Intern Med. 2010;267:483–501. http://doi.wiley. com/10.1111/j.1365-2796.2010.02220.x. 287. Draghi M, Pashine A, Sanjanwala B, Gendzekhadze K, Cantoni C, Cosman D, et al. NKp46 and NKG2D recognition of infected dendritic cells is necessary for NK cell activation in the human response to influenza infection. J Immunol. 2007;178:2688–98. http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.178.5.2688. 288. Thomas R, Yang X. NK-DC Crosstalk in immunity to microbial infection. J Immunol Res. 2016;2016:1–7. https://www.hindawi.com/journals/jir/2016/6374379/. 289. Guo Y, Patil NK, Luan L, Bohannon JK, Sherwood ER. The biology of natural killer cells during sepsis. Immunology. 2018;153:190–202. http://doi.wiley.com/10.1111/imm.12854. 290. Li SS, Saleh M, Xiang RF, Ogbomo H, Stack D, Huston SH, et al. Natural killer cells kill Burkholderia cepacia complex via a contact-dependent and cytolytic mechanism. Int Immunol. 2019;31:385–96. https://academic.oup.com/intimm/article/31/6/385/5485419. 291. Wang H, Li J, Dong X, Zhou X, Zhao L, Wang X, et al. NK cells contribute to protective memory T cell mediated immunity to Chlamydia muridarum infection. Front Cell Infect Microbiol. 2020;10:296. https://www.frontiersin.org/article/10.3389/fcimb.2020.00296/full. 292. Kumar V. Natural killer cells in sepsis: underprivileged innate immune cells. Eur J Cell Biol. 2019;98:81–93. https://linkinghub.elsevier.com/retrieve/pii/S0171933518302723. 293. Stuehler C, Kuenzli E, Jaeger VK, Baettig V, Ferracin F, Rajacic Z, et al. Immune reconstitution after allogeneic hematopoietic stem cell transplantation and association with occurrence and outcome of invasive aspergillosis. J Infect Dis. 2015;212:959–67. https://academic.oup. com/jid/article-lookup/doi/10.1093/infdis/jiv143. 294. Schmidt S, Zimmermann S-Y, Tramsen L, Koehl U, Lehrnbecher T. Natural killer cells and antifungal host response. Clin Vaccine Immunol. 2013;20:452–8. https://cvi.asm.org/ content/20/4/452. 295. Lehrnbecher T, Schmidt S. Why are natural killer cells important for defense against Aspergillus ? Med Mycol. 2019;57:S206–10. https://academic.oup.com/mmy/article/57/ Supplement_2/S206/5366886. 296. Miller MM, Reinhardt RL. The heterogeneity, origins, and impact of migratory iILC2 cells in anti-helminth immunity. Front Immunol. 2020;11:1594. https://www.frontiersin.org/ article/10.3389/fimmu.2020.01594/full. 297. Harris NL, Loke P. Recent advances in type-2-cell-mediated immunity: insights from helminth infection. Immunity. 2017;47:1024–36. https://linkinghub.elsevier.com/retrieve/pii/ S1074761317305162.
References
277
298. van Erp E, van Kampen M, van Kasteren P, de Wit J. Viral infection of human natural killer cells. Viruses. 2019;11:243. https://www.mdpi.com/1999-4915/11/3/243. 299. Santiago V, Rezvani K, Sekine T, Stebbing J, Kelleher P, Armstrong-James D. Human NK cells develop an exhaustion phenotype during polar degranulation at the aspergillus fumigatus hyphal synapse. Front Immunol. 2018;9:2344. https://www.frontiersin.org/article/10.3389/ fimmu.2018.02344/full. 300. Godfrey DI, Uldrich AP, McCluskey J, Rossjohn J, Moody DB. The burgeoning family of unconventional T cells. Nat Immunol. 2015;16:1114–23. http://www.nature.com/articles/ ni.3298. 301. Gao Y, Williams AP. Role of innate T cells in anti-bacterial immunity. Front Immunol. 2015;6:302. http://journal.frontiersin.org/Article/10.3389/fimmu.2015.00302/abstract. 302. Kinjo Y, Takatsuka S, Kitano N, Kawakubo S, Abe M, Ueno K, et al. Functions of CD1d- restricted invariant natural killer T cells in antimicrobial immunity and potential applications for infection control. Front Immunol. 2018;9:1266. https://www.frontiersin.org/ article/10.3389/fimmu.2018.01266/full. 303. Kuylenstierna C, Björkström NK, Andersson SK, Sahlström P, Bosnjak L, Paquin-Proulx D, et al. NKG2D performs two functions in invariant NKT cells: direct TCR-independent activation of NK-like cytolysis and co-stimulation of activation by CD1d. Eur J Immunol. 2011;41:1913–23. http://doi.wiley.com/10.1002/eji.200940278. 304. Stojanovic A, Correia MP, Cerwenka A. The NKG2D/NKG2DL axis in the crosstalk between lymphoid and myeloid cells in health and disease. Front Immunol. 2018;9:827. http://journal. frontiersin.org/article/10.3389/fimmu.2018.00827/full. 305. Hinks TSC, Zhang X-W. MAIT cell activation and functions. Front Immunol. 2020;11:1014. https://www.frontiersin.org/article/10.3389/fimmu.2020.01014/full. 306. Serriari N-E, Eoche M, Lamotte L, Lion J, Fumery M, Marcelo P, et al. Innate mucosal- associated invariant T (MAIT) cells are activated in inflammatory bowel diseases. Clin Exp Immunol. 2014;176:266–74. http://doi.wiley.com/10.1111/cei.12277. 307. Zhao Y, Lin L, Xiao Z, Li M, Wu X, Li W, et al. Protective role of γδ T cells in different pathogen infections and its potential clinical application. J Immunol Res. 2018;2018:1–15. https://www.hindawi.com/journals/jir/2018/5081634/. 308. Rigau M, Ostrouska S, Fulford TS, Johnson DN, Woods K, Ruan Z, et al. Butyrophilin 2A1 is essential for phosphoantigen reactivity by γδ T cells. Science. 2020;367:eaay5516. https:// www.sciencemag.org/lookup/doi/10.1126/science.aay5516. 309. Karunakaran MM, Willcox CR, Salim M, Paletta D, Fichtner AS, Noll A, et al. Butyrophilin-2A1 directly binds germline-encoded regions of the Vγ9Vδ2 TCR and is essential for phosphoantigen sensing. Immunity. 2020;52:487–498.e6. https://linkinghub.elsevier. com/retrieve/pii/S1074761320300856. 310. Poggi A, Venturino C, Catellani S, Clavio M, Miglino M, Gobbi M, et al. Vδ1 T lymphocytes from B-CLL patients recognize ULBP3 expressed on leukemic B cells and up-regulated by trans -retinoic acid. Cancer Res. 2004;64:9172–9. http://cancerres.aacrjournals.org/lookup/ doi/10.1158/0008-5472.CAN-04-2417. 311. Catellani S, Poggi A, Bruzzone A, Dadati P, Ravetti JL, Gobbi M, et al. Expansion of Vδ1 T lymphocytes producing IL-4 in low-grade non-Hodgkin lymphomas expressing UL-16–binding proteins. Blood. 2007;109:2078–85. https://ashpublications.org/blood/ article/109/5/2078/23248/Expansion-of-Vδ1-T-lymphocytes-producing-IL4-in. 312. Mao T, Miao C, Liao Y, Chen Y, Yeh C, Liu C. Ex vivo expanded human Vγ9Vδ2 T-cells can suppress epithelial ovarian cancer cell growth. Int J Mol Sci. 2019;20:1139. https://www. mdpi.com/1422-0067/20/5/1139. 313. Balan S, Saxena M, Bhardwaj N. Dendritic cell subsets and locations. Int Rev Cell Mol Biol. 2019;348:1–68. https://linkinghub.elsevier.com/retrieve/pii/S193764481930067X. 314. Cui B, Lin H, Yu J, Yu J, Hu Z. Autophagy and the immune response. Adv Exp Med Biol. 2019;1206:595–634. http://link.springer.com/10.1007/978-981-15-0602-4_27.
278
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
315. Dolasia K, Bisht MK, Pradhan G, Udgata A, Mukhopadhyay S. TLRs/NLRs: shaping the landscape of host immunity. Int Rev Immunol. 2018;37:3–19. https://www.tandfonline.com/ doi/full/10.1080/08830185.2017.1397656. 316. Cruz MT, Ferreira I, Liberal J, Martins JD, Silva A, Neves BM. Inflammasome in dendritic cells immunobiology: implications to diseases and therapeutic strategies. Curr Drug Targets. 2017;18:1003. http://www.eurekaselect.com/145693/article. 317. Weintraub A. Immunology of bacterial polysaccharide antigens. Carbohydr Res. 2003;338:2539–47. https://linkinghub.elsevier.com/retrieve/pii/S000862150300449X. 318. Avci FY, Kasper DL. How bacterial carbohydrates influence the adaptive immune system. Annu Rev Immunol. 2010;28:107–30. http://www.annualreviews.org/doi/10.1146/ annurev-immunol-030409-101159. 319. Kim H, Webster RG, Webby RJ. Influenza virus: dealing with a drifting and shifting pathogen. Viral Immunol. 2018;31:174–83. https://www.liebertpub.com/doi/10.1089/vim.2017.0141. 320. Trombetta ES, Mellman I. Cell biology of antigen processing in vitro and in vivo. Annu Rev Immunol. 2005;23:975–1028. http://www.annualreviews.org/doi/10.1146/annurev. immunol.22.012703.104538. 321. Joffre OP, Segura E, Savina A, Amigorena S. Cross-presentation by dendritic cells. Nat Rev Immunol. 2012;12:557–69. http://www.nature.com/doifinder/10.1038/nri3254. 322. Embgenbroich M, Burgdorf S. Current concepts of antigen cross-presentation. Front Immunol. 2018;9:1643. https://www.frontiersin.org/article/10.3389/fimmu.2018.01643/full. 323. van Montfoort N, van der Aa E, Woltman AM. Understanding MHC class I presentation of viral antigens by human dendritic cells as a basis for rational design of therapeutic vaccines. Front Immunol. 2014;5:182. http://journal.frontiersin.org/article/10.3389/ fimmu.2014.00182/abstract. 324. Woon AP, Purcell AW. The use of proteomics to understand antiviral immunity. Semin Cell Dev Biol. 2018;84:22–9. https://linkinghub.elsevier.com/retrieve/pii/S1084952116304517. 325. Jain A, Pasare C. Innate control of adaptive immunity: beyond the three-signal paradigm. J Immunol. 2017;198:3791–800. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1602000. 326. Fucikova J, Kepp O, Kasikova L, Petroni G, Yamazaki T, Liu P, et al. Detection of immunogenic cell death and its relevance for cancer therapy. Cell Death Dis. 2020;11:1013. http:// www.nature.com/articles/s41419-020-03221-2. 327. Granucci F, Foti M, Ricciardi‐Castagnoli P. Dendritic cell biology. Adv Immunol. 2005;88:193–233. https://linkinghub.elsevier.com/retrieve/pii/S006527760588006X. 328. Soto JA, Gálvez NMS, Andrade CA, Pacheco GA, Bohmwald K, Berrios RV, et al. The role of dendritic cells during infections caused by highly prevalent viruses. Front Immunol. 2020;11:1513. https://www.frontiersin.org/article/10.3389/fimmu.2020.01513/full. 329. Brunner C, Seiderer J, Schlamp A, Bidlingmaier M, Eigler A, Haimerl W, et al. Enhanced dendritic cell maturation by TNF-α or cytidine-phosphate-guanosine DNA drives T cell activation in vitro and therapeutic anti-tumor immune responses in vivo. J Immunol. 2000;165:6278–86. http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.165.11.6278. 330. Pantel A, Teixeira A, Haddad E, Wood EG, Steinman RM, Longhi MP. Direct type I IFN but not MDA5/TLR3 activation of dendritic cells is required for maturation and metabolic shift to glycolysis after poly IC stimulation. PLoS Biol. 2014;12:e1001759. https://dx.plos. org/10.1371/journal.pbio.1001759. 331. Su H, Zhang Z, Liu Z, Peng B, Kong C, Wang H, et al. Mycobacterium tuberculosis PPE60 antigen drives Th1/Th17 responses via Toll-like receptor 2–dependent maturation of dendritic cells. J Biol Chem. 2018;293:10287–302. http://www.jbc.org/lookup/doi/10.1074/jbc. RA118.001696. 332. Sano R, Reed JC. ER stress-induced cell death mechanisms. Biochim Biophys Acta, Mol Cell Res. 2013;1833:3460–70. https://linkinghub.elsevier.com/retrieve/pii/S0167488913002516. 333. Fang FC, Frawley ER, Tapscott T, Vázquez-Torres A. Bacterial stress responses during host infection. Cell Host Microbe. 2016;20:133–43. https://linkinghub.elsevier.com/retrieve/pii/ S1931312816303080.
References
279
334. Rodrigues LOCP, Graça RSF, Carneiro LAM. Integrated stress responses to bacterial pathogenesis patterns. Front Immunol. 2018;9:1306. https://www.frontiersin.org/article/10.3389/ fimmu.2018.01306/full. 335. Chamberlain N, Anathy V. Pathological consequences of the unfolded protein response and downstream protein disulphide isomerases in pulmonary viral infection and disease. J Biochem. 2020;167:173–84. https://academic.oup.com/jb/article/167/2/173/5650410. 336. Carletti T, Zakaria MK, Faoro V, Reale L, Kazungu Y, Licastro D, et al. Viral priming of cell intrinsic innate antiviral signaling by the unfolded protein response. Nat Commun. 2019;10:3889. http://www.nature.com/articles/s41467-019-11663-2. 337. Choi J-A, Song C-H. Insights into the role of endoplasmic reticulum stress in infectious diseases. Front Immunol. 2020;10:3147. https://www.frontiersin.org/article/10.3389/ fimmu.2019.03147/full. 338. Knippertz I, Stein MF, Dörrie J, Schaft N, Müller I, Deinzer A, et al. Mild hyperthermia enhances human monocyte-derived dendritic cell functions and offers potential for applications in vaccination strategies. Int J Hyperth. 2011;27:591–603. http://www.tandfonline.com/ doi/full/10.3109/02656736.2011.589234. 339. Zhu X, Yao F, Yao Y, Dong N, Yu Y, Sheng Z. Endoplasmic reticulum stress and its regulator XBP-1 contributes to dendritic cell maturation and activation induced by high mobility group box-1 protein. Int J Biochem Cell Biol. 2012;44:1097–105. https://linkinghub.elsevier.com/ retrieve/pii/S1357272512001100. 340. Götz A, Ty MC, Rodriguez A. Oxidative stress enhances dendritic cell responses to Plasmodium falciparum. ImmunoHorizons. 2019;3:511–8. http://www.immunohorizons.org/ lookup/doi/10.4049/immunohorizons.1900076. 341. Brimnes MK, Bonifaz L, Steinman RM, Moran TM. Influenza virus–induced dendritic cell maturation is associated with the induction of strong T cell immunity to a coadministered, normally nonimmunogenic protein. J Exp Med. 2003;198:133–44. https://rupress.org/jem/ article/198/1/133/39827/Influenza-Virusinduced-Dendritic-Cell-Maturation. 342. Laursen MF, Christensen E, Degn LLT, Jønsson K, Jakobsen MR, Agger R, et al. CD11c- targeted delivery of DNA to dendritic cells leads to cGAS- and STING-dependent maturation. J Immunother. 2018;41:9–18. https://journals.lww.com/00002371-201801000-00002. 343. Chakraborty C, Sharma AR, Bhattacharya M, Lee S-S. From COVID-19 to cancer mRNA vaccines: moving from bench to clinic in the vaccine landscape. Front Immunol. 2021;12:679344. https://www.frontiersin.org/articles/10.3389/fimmu.2021.679344/full. 344. Barnowski C, Ciupka G, Tao R, Jin L, Busch DH, Tao S, et al. Efficient induction of cytotoxic T cells by viral vector vaccination requires STING-dependent DC functions. Front Immunol. 2020;11:1458. https://www.frontiersin.org/article/10.3389/fimmu.2020.01458/full. 345. Sahin U, Muik A, Derhovanessian E, Vogler I, Kranz LM, Vormehr M, et al. COVID-19 vaccine BNT162b1 elicits human antibody and TH1 T cell responses. Nature. 2020;586:594–9. http://www.nature.com/articles/s41586-020-2814-7. 346. Sahin U, Karikó K, Türeci Ö. mRNA-based therapeutics — developing a new class of drugs. Nat Rev Drug Discov. 2014;13:759–80. http://www.nature.com/articles/nrd4278. 347. Weissman D, Ni H, Scales D, Dude A, Capodici J, McGibney K, et al. HIV gag mRNA transfection of dendritic cells (DC) delivers encoded antigen to MHC class I and II molecules, causes DC maturation, and induces a potent human in vitro primary immune response. J Immunol. 2000;165:4710–7. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.165.8.4710. 348. Karikó K, Ni H, Capodici J, Lamphier M, Weissman D. mRNA is an endogenous ligand for toll-like receptor 3. J Biol Chem. 2004;279:12542–50. https://linkinghub.elsevier.com/ retrieve/pii/S0021925819641931. 349. Weissman D. mRNA transcript therapy. Expert Rev Vaccines. 2015;14:265–81. http://www. tandfonline.com/doi/full/10.1586/14760584.2015.973859. 350. Zhang Y, Xie F, Yin Y, Zhang Q, Jin H, Wu Y, et al. Immunotherapy of tumor RNA-loaded lipid nanoparticles against hepatocellular carcinoma. Int J Nanomedicine. 2021;16:1553–64.
280
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
https://www.dovepress.com/immunotherapy-o f-t umor-r na-l oaded-l ipid-n anoparticles- against-hepatoce-peer-reviewed-article-IJN. 351. Fidan I, Kalkanci A, Yesilyurt E, Erdal B. In vitro effects of Candida albicans and Aspergillus fumigatus on dendritic cells and the role of beta glucan in this effect. Adv Clin Exp Med. 2014;23:17–24. http://www.advances.umed.wroc.pl/en/article/2014/23/1/17/. 352. Sallusto F. Heterogeneity of human CD4+ T cells against microbes. Annu Rev Immunol. 2016;34:317–34. http://www.annualreviews.org/doi/10.1146/ annurev-immunol-032414-112056. 353. Mosmann TR, Coffman RL. TH1 and TH2 cells: different patterns of lymphokine secretion lead to different functional properties. Annu Rev Immunol. 1989;7:145–73. http://www. annualreviews.org/doi/10.1146/annurev.iy.07.040189.001045. 354. Kaiko GE, Horvat JC, Beagley KW, Hansbro PM. Immunological decision-making: how does the immune system decide to mount a helper T-cell response? Immunology. 2008;123:326–38. http://doi.wiley.com/10.1111/j.1365-2567.2007.02719.x. 355. Iwasaki A, Medzhitov R. Control of adaptive immunity by the innate immune system. Nat Immunol. 2015;16:343–53. http://www.ncbi.nlm.nih.gov/pubmed/25789684. 356. Crotty S. T follicular helper cell biology: a decade of discovery and diseases. Immunity. 2019;50:1132–48. https://linkinghub.elsevier.com/retrieve/pii/S1074761319301918. 357. Richardson JP, Moyes DL. Adaptive immune responses to Candida albicans infection. Virulence. 2015;6:327–37. http://www.tandfonline.com/doi/full/10.1080/21505594.201 5.1004977. 358. Wong P, Pamer EG. CD8 T cell responses to infectious pathogens. Annu Rev Immunol. 2003;21:29–70. http://www.annualreviews.org/doi/10.1146/annurev. immunol.21.120601.141114. 359. Andersen MH, Schrama D, Thor Straten P, Becker JC. Cytotoxic T cells. J Invest Dermatol. 2006;126:32–41. https://linkinghub.elsevier.com/retrieve/pii/S0022202X1532621X. 360. Upton JW, Shubina M, Balachandran S. RIPK3-driven cell death during virus infections. Immunol Rev. 2017;277:90–101. http://doi.wiley.com/10.1111/imr.12539. 361. Sebina I, Pepper M. Humoral immune responses to infection: common mechanisms and unique strategies to combat pathogen immune evasion tactics. Curr Opin Immunol. 2018;51:46–54. https://linkinghub.elsevier.com/retrieve/pii/S0952791518300049. 362. Kenneth M, Janeway CA Jr, Travers P, Walport M. Immunobiology. 8th ed. New York, NY: Garland, Science, Taylor and Francis Group, LLC; 2012. isbn: 978-0-8153-4243-4. 363. Dörner T, Radbruch A. Antibodies and B cell memory in viral immunity. Immunity. 2007;27:384–92. https://linkinghub.elsevier.com/retrieve/pii/S1074761307004207. 364. Ben Mkaddem S, Benhamou M, Monteiro RC. Understanding Fc receptor involvement in inflammatory diseases: from mechanisms to new therapeutic tools. Front Immunol. 2019;10:811. https://www.frontiersin.org/article/10.3389/fimmu.2019.00811/full. 365. Nimmerjahn F, Ravetch JV. Fcγ receptors as regulators of immune responses. Nat Rev Immunol. 2008;8:34–47. http://www.nature.com/articles/nri2206. 366. WangY, Jönsson F. Expression, role, and regulation of neutrophil Fcγ receptors. Front Immunol. 2019;10:1958. https://www.frontiersin.org/article/10.3389/fimmu.2019.01958/full. 367. Bruhns P, Iannascoli B, England P, Mancardi DA, Fernandez N, Jorieux S, et al. Specificity and affinity of human Fcγ receptors and their polymorphic variants for human IgG subclasses. Blood. 2009;113:3716–25. https://ashpublications.org/blood/article/113/16/3716/25117/ Specificity-and-affinity-of-human-Fcγ-receptors. 368. Monteiro RC, Kubagawa H, Cooper MD. Cellular distribution, regulation, and biochemical nature of an Fc alpha receptor in humans. J Exp Med. 1990;171:597–613. https://rupress.org/ jem/article/171/3/597/50101/Cellular-distribution-regulation-and-biochemical. 369. Brandsma AM, Bondza S, Evers M, Koutstaal R, Nederend M, Jansen JHM, et al. Potent Fc receptor signaling by IgA leads to superior killing of cancer cells by neutrophils compared to IgG. Front Immunol. 2019;10:704. https://www.frontiersin.org/article/10.3389/ fimmu.2019.00704/full.
References
281
370. Getahun A, Cambier JC. Of ITIMs, ITAMs, and ITAMis: revisiting immunoglobulin Fc receptor signaling. Immunol Rev. 2015;268:66–73. https://pubmed.ncbi.nlm.nih.gov/26497513/. 371. Ravetch JV, Clynes RA. Divergent roles for Fc receptors and complement in vivo. Annu Rev Immunol. 1998;16:421–32. https://www.annualreviews.org/doi/10.1146/annurev. immunol.16.1.421. 372. Schroeder HW, Cavacini L. Structure and function of immunoglobulins. J Allergy Clin Immunol. 2010;125:S41–52. https://linkinghub.elsevier.com/retrieve/pii/ S0091674909014651. 373. Subedi GP, Barb AW. The immunoglobulin G1 N-glycan composition affects binding to each low affinity Fc γ receptor. MAbs. 2016;8:1512–24. https://www.tandfonline.com/doi/full/1 0.1080/19420862.2016.1218586. 374. Wang TT, Ravetch JV. Functional diversification of IgGs through Fc glycosylation. J Clin Invest. 2019;129:3492–8. https://www.jci.org/articles/view/130029. 375. Liu S, Liu X. IgG N-glycans. Adv Clin Chem. 2021;105:1–47. https://linkinghub.elsevier. com/retrieve/pii/S0065242321000123. 376. Maibom-Thomsen SL, Trier NH, Holm BE, Hansen KB, Rasmussen MI, Chailyan A, et al. Immunoglobulin G structure and rheumatoid factor epitopes. PLoS One. 2019;14:e0217624. https://dx.plos.org/10.1371/journal.pone.0217624. 377. Dekkers G, Rispens T, Vidarsson G. Novel concepts of altered immunoglobulin G galactosylation in autoimmune diseases. Front Immunol. 2018;9:553. http://journal.frontiersin.org/ article/10.3389/fimmu.2018.00553/full. 378. Kaneko Y, Nimmerjahn F, Ravetch JV. Anti-inflammatory activity of immunoglobulin G resulting from Fc sialylation. Science. 2006;313:670–3. https://www.science.org/ doi/10.1126/science.1129594. 379. Ahmed AA, Giddens J, Pincetic A, Lomino JV, Ravetch JV, Wang L-X, et al. Structural characterization of anti-inflammatory immunoglobulin G Fc proteins. J Mol Biol. 2014;426:3166–79. https://linkinghub.elsevier.com/retrieve/pii/S0022283614003404. 380. Niwa R, Sakurada M, Kobayashi Y, Uehara A, Matsushima K, Ueda R, et al. Enhanced natural killer cell binding and activation by low-fucose IgG1 antibody results in potent antibody-dependent cellular cytotoxicity induction at lower antigen density. Clin Cancer Res. 2005;11:2327–36. http://clincancerres.aacrjournals.org/lookup/doi/10.1158/1078-0432. CCR-04-2263. 381. Temming AR, de Taeye SW, de Graaf EL, de Neef LA, Dekkers G, Bruggeman CW, et al. Functional attributes of antibodies, effector cells, and target cells affecting NK cell–mediated antibody-dependent cellular cytotoxicity. J Immunol. 2019;203:3126–35. http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.1900985. 382. Ackerman ME, Crispin M, Yu X, Baruah K, Boesch AW, Harvey DJ, et al. Natural variation in Fc glycosylation of HIV-specific antibodies impacts antiviral activity. J Clin Invest. 2013;123:2183–92. http://www.jci.org/articles/view/65708. 383. Bournazos S, Vo HTM, Duong V, Auerswald H, Ly S, Sakuntabhai A, et al. Antibody fucosylation predicts disease severity in secondary dengue infection. Science. 2021;372:1102–5. https://www.science.org/doi/10.1126/science.abc7303. 384. Hoepel W, Chen H-J, Geyer CE, Allahverdiyeva S, Manz XD, de Taeye SW, et al. High titers and low fucosylation of early human anti–SARS-CoV-2 IgG promote inflammation by alveolar macrophages. Sci Transl Med. 2021;13:eabf8654. https://www.science.org/doi/10.1126/ scitranslmed.abf8654. 385. Larsen MD, de Graaf EL, Sonneveld ME, Plomp HR, Nouta J, Hoepel W, et al. Afucosylated IgG characterizes enveloped viral responses and correlates with COVID-19 severity. Science. 2021;371:eabc8378. https://www.science.org/doi/10.1126/science.abc8378. 386. Chakraborty S, Gonzalez JC, Sievers BL, Mallajosyula V, Chakraborty S, Dubey M, et al. Early non-neutralizing, afucosylated antibody responses are associated with COVID-19 severity. Sci Transl Med. 2022;14:eabm7853. https://www.science.org/doi/10.1126/scitranslmed.abm7853.
282
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
387. Anthony RM, Kobayashi T, Wermeling F, Ravetch JV. Intravenous gammaglobulin suppresses inflammation through a novel TH2 pathway. Nature. 2011;475:110–3. http://www. nature.com/articles/nature10134. 388. Böhm S, Schwab I, Lux A, Nimmerjahn F. The role of sialic acid as a modulator of the anti- inflammatory activity of IgG. Semin Immunopathol. 2012;34:443–53. http://link.springer. com/10.1007/s00281-012-0308-x. 389. Li T, DiLillo DJ, Bournazos S, Giddens JP, Ravetch JV, Wang L-X. Modulating IgG effector function by Fc glycan engineering. Proc Natl Acad Sci. 2017;114:3485–90. https://pnas.org/ doi/full/10.1073/pnas.1702173114. 390. Quast I, Keller CW, Maurer MA, Giddens JP, Tackenberg B, Wang L-X, et al. Sialylation of IgG Fc domain impairs complement-dependent cytotoxicity. J Clin Invest. 2015;125:4160–70. https://www.jci.org/articles/view/82695. 391. Anthony RM, Nimmerjahn F, Ashline DJ, Reinhold VN, Paulson JC, Ravetch JV. Recapitulation of IVIG anti-inflammatory activity with a recombinant IgG Fc. Science. 2008;320:373–6. https://www.science.org/doi/10.1126/science.1154315. 392. Anthony RM, Wermeling F, Karlsson MCI, Ravetch JV. Identification of a receptor required for the anti-inflammatory activity of IVIG. Proc Natl Acad Sci. 2008;105:19571–8. https:// pnas.org/doi/full/10.1073/pnas.0810163105. 393. Aleyd E, Al M, Tuk CW, van der Laken CJ, van Egmond M. IgA complexes in plasma and synovial fluid of patients with rheumatoid arthritis induce neutrophil extracellular traps via FcαRI. J Immunol. 2016;197:4552–9. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1502353. 394. Behnen M, Leschczyk C, Möller S, Batel T, Klinger M, Solbach W, et al. Immobilized immune complexes induce neutrophil extracellular trap release by human neutrophil granulocytes via FcγRIIIB and Mac-1. J Immunol. 2014;193:1954–65. http://www.jimmunol.org/ lookup/doi/10.4049/jimmunol.1400478. 395. Alemán OR, Mora N, Cortes-Vieyra R, Uribe-Querol E, Rosales C. Differential use of human neutrophil Fc γ receptors for inducing neutrophil extracellular trap formation. J Immunol Res. 2016;2016:1–17. http://www.hindawi.com/journals/jir/2016/2908034/. 396. Chen K, Nishi H, Travers R, Tsuboi N, Martinod K, Wagner DD, et al. Endocytosis of soluble immune complexes leads to their clearance by FcγRIIIB but induces neutrophil extracellular traps via FcγRIIA in vivo. Blood. 2012;120:4421–31. https://ashpublications.org/blood/ article/120/22/4421/73051/Endocytosis-of-soluble-immune-complexes-leads-to. 397. Granger V, Peyneau M, Chollet-Martin S, de Chaisemartin L. Neutrophil extracellular traps in autoimmunity and allergy: immune complexes at work. Front Immunol. 2019;10:2824. https://www.frontiersin.org/article/10.3389/fimmu.2019.02824/full. 398. Chen T, Li Y, Sun R, Hu H, Liu Y, Herrmann M, et al. Receptor-mediated NETosis on neutrophils. Front Immunol. 2021;12:775267. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.775267/full. 399. Gimpel A-K, Maccataio A, Unterweger H, Sokolova MV, Schett G, Steffen U. IgA Complexes Induce Neutrophil Extracellular Trap Formation More Potently Than IgG Complexes. Front Immunol. 2022;12:761816. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.761816/full. 400. Palmer LJ, Damgaard C, Holmstrup P, Nielsen CH. Influence of complement on neutrophil extracellular trap release induced by bacteria. J Periodontal Res. 2016;51:70–6. https:// onlinelibrary.wiley.com/doi/10.1111/jre.12284. 401. Diago-Navarro E, Calatayud-Baselga I, Sun D, Khairallah C, Mann I, Ulacia-Hernando A, et al. Antibody-based immunotherapy to treat and prevent infection with hypervirulent klebsiella pneumoniae. Clin Vaccine Immunol. 2017;24:e00456. https://journals.asm.org/ doi/10.1128/CVI.00456-16. 402. Stacey HD, Golubeva D, Posca A, Ang JC, Novakowski KE, Zahoor MA, et al. IgA potentiates NETosis in response to viral infection. Proc Natl Acad Sci. 2021;118:e2101497118. https://pnas.org/doi/full/10.1073/pnas.2101497118.
References
283
403. Boribong BP, LaSalle TJ, Bartsch YC, Ellett F, Loiselle ME, Davis JP, et al. Neutrophil profiles of pediatric COVID-19 and multisystem inflammatory syndrome in children. bioRxiv. 2021. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC8722589. 404. Zuo Y, Yalavarthi S, Shi H, Gockman K, Zuo M, Madison JA, et al. Neutrophil extracellular traps in COVID-19. JCI Insight. 2020;5:e138999. http://insight.jci.org/articles/view/138999. 405. Staats LAN, Pfeiffer H, Knopf J, Lindemann A, Fürst J, Kremer AE, et al. IgA2 Antibodies against SARS-CoV-2 correlate with NET formation and fatal outcome in severely diseased COVID-19 patients. Cells. 2020;9:2676. https://www.mdpi.com/2073-4409/9/12/2676. 406. Divangahi M, Aaby P, Khader SA, Barreiro LB, Bekkering S, Chavakis T, et al. Trained immunity, tolerance, priming and differentiation: distinct immunological processes. Nat Immunol. 2021;22:2–6. http://www.nature.com/articles/s41590-020-00845-6. 407. Sender R, Fuchs S, Milo R. Are we really vastly outnumbered? Revisiting the ratio of bacterial to host cells in humans. Cell. 2016;164:337–40. https://linkinghub.elsevier.com/retrieve/ pii/S0092867416000532. 408. Proctor LM, Creasy HH, Fettweis JM, Lloyd-Price J, Mahurkar A, Zhou W, et al. The Integrative human microbiome project. Nature. 2019;569:641–8. http://www.nature.com/ articles/s41586-019-1238-8. 409. Mowat AM. To respond or not to respond — a personal perspective of intestinal tolerance. Nat Rev Immunol. 2018;18:405–15. http://www.nature.com/articles/s41577-018-0002-x. 410. Chu H, Mazmanian SK. Innate immune recognition of the microbiota promotes host- microbial symbiosis. Nat Immunol. 2013;14:668–75. http://www.nature.com/articles/ ni.2635. 411. Tezuka H, Ohteki T. Regulation of IgA production by intestinal dendritic cells and related cells. Front Immunol. 2019;10:1891. https://www.frontiersin.org/article/10.3389/ fimmu.2019.01891/full. 412. Bakdash G, Vogelpoel LTC, van Capel TMM, Kapsenberg ML, de Jong EC. Retinoic acid primes human dendritic cells to induce gut-homing, IL-10-producing regulatory T cells. Mucosal Immunol. 2015;8:265–78. http://www.nature.com/doifinder/10.1038/mi.2014.64. 413. Tanoue T, Atarashi K, Honda K. Development and maintenance of intestinal regulatory T cells. Nat Rev Immunol. 2016;16:295–309. http://www.nature.com/doifinder/10.1038/ nri.2016.36. 414. Tordesillas L, Berin MC. Mechanisms of oral tolerance. Clin Rev Allergy Immunol. 2018;55:107–17. http://link.springer.com/10.1007/s12016-018-8680-5. 415. Chulkina M, Beswick EJ, Pinchuk IV. Role of PD-L1 in gut mucosa tolerance and chronic inflammation. Int J Mol Sci. 2020;21:9165. https://www.mdpi.com/1422-0067/21/23/9165. 416. Garo LP, Ajay AK, Fujiwara M, Beynon V, Kuhn C, Gabriely G, et al. Smad7 Controls immunoregulatory PDL2/1-PD1 signaling in intestinal inflammation and autoimmunity. Cell Rep. 2019;28:3353–3366.e5. https://linkinghub.elsevier.com/retrieve/pii/ S2211124719309696. 417. Zheng D, Liwinski T, Elinav E. Interaction between microbiota and immunity in health and disease. Cell Res. 2020;30:492–506. http://www.nature.com/articles/s41422-020-0332-7. 418. Srinivasan N. Telling apart friend from foe: discriminating between commensals and pathogens at mucosal sites. Innate Immun. 2010;16:391–404. http://www.ncbi.nlm.nih.gov/ pubmed/20083498. 419. Baumgart DC, Carding SR. Inflammatory bowel disease: cause and immunobiology. Lancet. 2007;369:1627–40. https://linkinghub.elsevier.com/retrieve/pii/S0140673607607508. 420. Boyapati RK, Rossi AG, Satsangi J, Ho G-T. Gut mucosal DAMPs in IBD: from mechanisms to therapeutic implications. Mucosal Immunol. 2016;9:567–82. http://www.nature. com/articles/mi201614. 421. Burgueño JF, Abreu MT. Epithelial Toll-like receptors and their role in gut homeostasis and disease. Nat Rev Gastroenterol Hepatol. 2020;17:263–78. http://www.nature.com/articles/ s41575-019-0261-4. 422. Escamilla-Tilch M, Filio-Rodríguez G, García-Rocha R, Mancilla-Herrera I, Mitchison NA, Ruiz-Pacheco JA, et al. The interplay between pathogen-associated and danger-associated
284
4 The DAMP-Driven Host Immune Defense Program Against Pathogens
molecular patterns: an inflammatory code in cancer? Immunol Cell Biol. 2013;91:601–10. http://www.ncbi.nlm.nih.gov/pubmed/24100386. 423. Hayward JA, Mathur A, Ngo C, Man SM. Cytosolic recognition of microbes and pathogens: inflammasomes in action. Microbiol Mol Biol Rev. 2018;82:1–40. https://mmbr.asm.org/ content/82/4/e00015-18. 424. Amarante-Mendes GP, Adjemian S, Branco LM, Zanetti LC, Weinlich R, Bortoluci KR. Pattern recognition receptors and the host cell death molecular machinery. Front Immunol. 2018;9:2379. https://www.frontiersin.org/article/10.3389/fimmu.2018.02379/full. 425. De Lorenzo G, Cervone F. Plant immunity by damage-associated molecular patterns (DAMPs). Essays Biochem. 2022;30;66(5):459−69. https://doi.org/10.1042/EBC20210087. 426. Gnauck A, Lentle RG, Kruger MC. The characteristics and function of bacterial lipopolysaccharides and their endotoxic potential in humans. Int Rev Immunol. 2016;35:189–218. https://www.tandfonline.com/doi/full/10.3109/08830185.2015.1087518.
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5.1 Introduction In the previous chapters of this “Infection” Part of Vol. 3 of the book, the DAMPs were examined in perspective from three key viewpoints: (1) their putative role in the evolutionary arms race between pathogens and mammals; (2) their sources in pathogen-induced inflammation/immunity, and (3) their beneficial role in controlled and regulated defense responses against pathogens, which manifest clinically as mild/moderate infectious diseases, usually lasting about 1–2 weeks. Indeed, inflammatory immune defense responses to pathogens serve our health and survival and are usually temporary in nature, always directed toward the ultimate goal of leading to homeostasis and full recovery. Yet, they are called diseases, a term connoting unhealthiness, concern, and danger. This paradox is based on the fact that any inflammation of our body is perceived by us as a disturbance of our well-being, usually associated with pain and discomfort. On the other hand, immune responses must be, however, considered truly dangerous and serious diseases when they develop into disastrously uncontrolled and dysregulated defense responses against pathogens, which are the leading subject of this chapter. In particular, the hyperinflammatory response triggered by the emission of DAMPs in excess will be highlighted by reference to three clinical examples: severe virus-induced ARDS, life-threatening bacteria-induced sepsis, and devastating protozoan-induced malaria. The chapter ends with a proposal to use DAMPs and SAMPs as (1) biomarkers in diagnosis and prognosis and (2) novel therapeutic targets or therapeutics in the treatment and prophylaxis of infectious diseases.
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5.2 MAMP/DAMP-Triggered Dysregulation of Defense Responses to Pathogens 5.2.1 Introductory Remarks The growing awareness in the medical community of the essential role of DAMPs and SAMPs in dysregulated inflammatory defense responses that determine the pattern of infectious diseases has already been introduced in Sect. 2.5.4. As stressed there, the metaphor for DAMPs as a double-edge sword can be reused in relation to infections: Under uncontrolled and dysregulated conditions, the beneficial defense response against pathogens can run out of control and result in the development of a hyperinflammatory life-threatening syndrome or chronic infectious disease (Fig. 5.1). Here, some principles of both complications are briefly described by focusing—as usual from the perspective of this book—on the deleterious role of DAMPs.
5.2.2 Chronic/Persistent Inflammatory Responses to Infections 5.2.2.1 General Remarks Recent achievements in modern inflammation research have led to a paradigm shift in our understanding of the nature of chronic inflammatory diseases. Thus, as Transmission Æ Entry of Pathogens Invasion of Pathogens Pathogen-induced cell stress/tissue injury Æ Subroutines of RCD
MAMPs + DAMPs/SAMPs Homeostatic emission: Controlled/Regulated host responses - Inflammation-promoting responses - Inflammation-resolving responses - Appropriate adaptive immune responses
Host Defense (transient mild/moderate disorder) Regeneration Æ healing
Excessive/persistent emission: Uncontrolled/Dysregulated host responses - Hyperinflammatory response - Non-resolving chronic responses - Aberrant adaptive immune responses
Life-threatening pathologies (e.g., ARDS, SIRS), Chronic inflammatory diseases
Fig. 5.1 Simplified schematic presentation of the double-edged sword function of DAMPs in infections. Homeostatic emission of DAMPs leads to controlled host defense responses clinically diagnosed as transient mild/moderate disorder, and emission of excessive or persistent DAMPs results in hyperinflammatory or chronic inflammation-nonresolving responses clinically diagnosed as ARDS, SIRS, or chronic, devastating inflammatory diseases. ARDS acute respiratory distress syndrome, RCD regulated cell death, SIRS systemic inflammatory response syndrome
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outlined and illustrated in Vol. 1 [1], Sect. 22.2.4, pp. 483–484 and Vol. 2 [2], Sect. 5.5 and Fig. 5.3, pp. 166–168, modern notions in inflammation research now hold that chronic inflammation reflects a state of nonresolving inflammation fired and sustained by sterile or infectious insults. A typical example is atherosclerosis, which has been described in Vol. 2 [2], Chap. 10, pp. 413–441. In general, the nature of these insults (notoriously associated with the generation/emission of various DAMPs) can vary depending on different causes, such as: –– Disturbed metabolism, for example, due to chronic stress of the ER induced by accumulation of proinsulin. –– Adaptive autoimmunity, as a result of the action of cytotoxic autoantibodies and autoreactive CTLs. –– Exposure to environmental chemicals/toxins (i.e., exogenous DAMPs, such as silica particles, air pollution particles, asbestos fibers, and allergens). –– Continuous physical/traumatic forces, for example, tendonitis due to repetitive use or overuse of a certain area of the body. –– The action of toxic ROS that may be secondarily generated in the course of inflammation. –– Finally, and applicable here, the presence of chronic infection in case of persistence of pathogens as a result of incomplete elimination of pathogens for various reasons, for example, compromised immune defense.
5.2.2.2 Nonresolving Persisting Infections A severe and feared complication of infections is their chronic course, causing a great burden of morbidity and mortality in human diseases associated with significant public health and economic costs. For example, Mycobacterium tuberculosis, an infectious Lymphocytic choriomeningitis virus, or Salmonella Typhi bacteria may be produced continuously or acutely repetitively for months or years [3, 4]. Of note, persistent infections can be classified into chronic infections if they are eventually cleared from the host, and latent or slow infections, if they last during the life of the host. In contrast to an acute infection, chronic persistent infection is not cleared in an appropriate time, and the pathogen, pathogenic genome, or pathogen-derived proteins continue to be produced for long periods. The incomplete elimination of pathogens is complex and can have several reasons, including, on the pathogen side: (1) a high level of replication or high burden of the pathogen during its persistence, (2) high virulence factors, for example, biofilm formation, and (3) successful immune evasion procedure or interactions with the host cell metabolism; including, on the patient side: older age, immunosuppression, genetically determined susceptibility, ineffective elimination of the pathogen by antibiotics/antiviral drugs (for further reading, also see [5–7]). Of note, an important further causal contribution to the development of chronic infectious diseases has been recently recognized in the generation and action of Tregs (for reviews, see [8–11]; for more information on Tregs in general, see Vol. 1 [1], Sect. 33.4, pp. 809–818). Indeed, Tregs are induced by a wide range of pathogens, but distinct effects of Tregs have been demonstrated
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for different pathogens and in different stages of infection. Moreover, Tregs that are induced by a specific pathogen may non-specifically suppress immunity against other microbes and parasites. Mechanistically, Tregs—suggested to be induced by tolDCs via the CTLA-4 ↔ CD80/CD86 and the PD-1↔PD-L1 axis (i.e., immune checkpoints)-mediate their suppressive action by direct cell↔cell contact with effector T cells; to produce immunosuppressive cytokines; and to kill anti-pathogen-directed effector T cells (for CTLA-4, i.e., cytotoxic T lymphocyte-associated antigen-4 and PD-1, i.e., programmed cell death protein1), also see Vol. 1 [1], Sect. 33.3.5, pp. 805–807, and Fig. 33.3, p. 800). The persistence of all the pathogen-induced insults is intrinsically associated with the permanent generation/emission of more or fewer amounts of various classes of DAMPs whereby, due to the nature of the infection, the presence of MAMPs joins this scenario. Accordingly, and in principle, chronic infections can be caused—besides the persistence of MAMPs—by two constellations: (1) persistent or acute/chronic repetitive generation/emission of such high amounts of DAMPs that surpass the “normal (homeostasis-striving)” production of counterregulatory SAMPs, (2) a (genetically determined) incompleteness or failure of the inflammation-resolution program, for example, due to defective SAMPs emission, or (3) even by both scenarios. A characteristic example refers to chronic viral diseases, which reflect a severe complication of a viral infection and can be due to several conditions (reviewed in [12, 13]). The dilemma here is that, due to incomplete elimination, the same acutely involved virus may cause a long-term or persistent infection (typically in immunocompromised hosts). This implies that the virus is still able to promote the emission of DAMPs, which, along with viral MAMPs, continue to promote antiviral inflammatory and antigen-specific immune responses in order to limit viral replication to an acceptable level without damaging collaterally the permanently infected tissues. According to current notions, the scenario has reached another level of complexity as the inferior and insufficient production of SAMPs is believed to contribute to the chronic course of an infection. Last but not least, the ongoing emission of virus-induced DAMPs, together with persistent induction of RCD, may lead to continued cell demise associated with DAMP-promoted overshooting repairing responses. The result is dysfunction and tumorigenesis of infected organs, typically seen, for example, in hepatitis virus infection-associated continuous inflammation leading to hepatic fibrosis that frequently brings about cirrhosis and ultimately hepatocellular carcinoma (for DAMPpromoted fibrogenesis → fibrosis, see Vol. 2 [2], Chap. 6, pp. 211–245).
5.2.3 Hyperinflammatory Syndrome Associated with Infections: The Case of Sepsis 5.2.3.1 General Remarks The development of a dysregulated hyperinflammatory syndrome during infection is diagnosed by intensive care physicians in their daily work as the clinical picture
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of sepsis. This life-threatening disorder is recognized as a major killer across all ages and countries and remains the most common cause of admission and death in the Intensive Care Unit (ICU) [14]. Notably, the World Health Assembly of WHO 2018 passed a resolution on better prevention, diagnosis, and management of sepsis [15]. The pathogenesis of sepsis has been described in Vol. 2 [2] (Sect 8.3, Fig. 8.1, pp. 290–307) in relation to the sepsis-like clinical picture seen in polytrauma—as briefly repeated in the following.
5.2.3.2 Causes of Sepsis Development Similar to the incidence of chronic infections, the development of sepsis is complex and affected by a variety of factors. The disastrous disease begins when pathogens can escape locally controlled innate immune defense responses that can occur for a variety of reasons. They include, on the pathogen side, high infectious agent load, effective virulence-associated factors, and antibiotic resistance genes; on the patient side, site of infection, decreased immune resistance, for example, due to chemotherapy or immunosuppressive treatment, high age, a variety of comorbid medical conditions such as diabetes and malignancies, post-trauma, and, last but not least, genetic predisposition influenced, for example, by the epigenetic control of gene transcription, and genetic polymorphisms of sepsis-associated genes (also see [16– 19]). Hence, once the initial innate immune defense has failed to clear the source of the infection, the pathogens now cross mucosal barriers, disseminate to remote organs, and replicate there [20]. 5.2.3.3 Systemic Hyperinflammatory Response Syndrome and Coagulation Activation Current notions in agreement with the danger/injury theory hold that sepsis is an uncontrolled exaggerated systemic innate immune response triggered by pathogen-caused systemic cell and tissue injuries. These infectious insults lead multilocularly to the emission of large amounts of DAMPs [21], which enter the systemic circulation to affect each system and organ of the patient. And it is this systemic emission of DAMPs in excess, which is believed to turn an initially localized infection into the catastrophe of the typical infectious SIRS, potentially leading to septic shock, MODS, or MOF as the major complications of sepsis [16] (compare Sect. 2.5.4, and Fig. 2.5; for a new definition of sepsis according to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) [22], see below Sect. 5.5.1.2). Also, in severe courses of sepsis, the coagulation system becomes diffusely activated, with the consumption of multiple clotting factors resulting in immunothrombosis that can develop into disseminated intravascular coagulation (DIC). In earlier reports, this scenario has already been proposed to be driven by the systemic spreading of DAMPs together with MAMPs [23–25]. Mechanistically, DAMPs were shown to trigger an intravascular thrombus formation, possibly by inducing tissue factor (TF) expression on PRR-expressing monocytes, upregulating TF procoagulant activity, and promoting activation and aggregation of PRRbearing platelets [23, 26]. Notably, TF, also known as coagulation factor III, F3,
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is a cell-surface transmembrane glycoprotein that, upon vascular damage, is exposed to plasma to operate as a receptor for factor (F) VII by binding to its activated form FVIIa. The TF/FVIIa complex is a potent primary activator of the coagulation protease cascade. Once formed, the TF/FVIIa complex triggers the activation of two downstream substrates in the coagulation cascade via limited proteolysis: the zymogens factor IX (FIX) converted to FIXa, and factor X (FX) converted to FXa. Downstream proteolytic reactions then result in thrombin generation and fibrin clot formation (for further reading, see [27–29]; for more details on immunothrombosis in sepsis, see below, Sect. 5.5.5.2).
5.2.3.4 Induction of Regulated Cell Death by Pathogens Also, as already detailed in Sect. 3.7, there is accumulating evidence suggesting that the emission of DAMPs in excess can be due to the intense capability of a pathogen to induce the formation of various subroutines of RCD. In case of hematogenous spreading of pathogens during sepsis, DAMPs will be emitted systemically throughout the body. Furthermore, at least under certain circumstances, a superimposition of DAMPs derived from other sources, for example, the environment, may contribute to the development of a fulminant course of an infection [30]. 5.2.3.5 Compensatory Anti-inflammatory Response Syndrome Typically, this DAMP-promoted hyperinflammatory response to severe infection is accompanied/followed by intense and long-lasting counterbalancing inflammationhyperresolving → immunosuppressive pathways known as CARS, often associated with late infections and long-term mortality [31–34] (introduced in Sect. 2.5.4, and Fig. 2.5). Of note, accumulating evidence suggests that this greatly feared complication—also denoted as “hyperresolution” in this book—associated with high susceptibility of the patient to secondary bacterial, fungal, and viral infection, is mediated by SAMPs, which control homeostasis following injury (see [35, 36] and Table 1.2; also compare Vol. 1 [1], Sect. 14.4, pp. 330–339, and Vol. 2 [2], Sect. 3.5.5, pp. 91–98).
5.3 Exploring DAMPs in Clinical Practice: An Emerging Area of Research in Infectious Diseases 5.3.1 Introductory Remarks In August 2022, when searching in PubMed for publications on DAMPs in infections (inserting the two keywords DAMPs and infections), respectable 615 results were received. Indeed, growing and compelling evidence from studies on infectious diseases has been and still is reported indicating that, along with well-established MAMPs, endogenous DAMPs and SAMPs also drive inflammatory/immune
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responses in infectious diseases. In principle, the sources of extracellularly acting DAMPs in infections are pathogen-induced subroutines of RN [37] or EVs secreted by infected cells [38]. As an introduction to this chapter, only a brief but not complete overview of some selected DAMPs and SAMPs as reported to play a role in infections is provided. In this brief survey, these molecules will not be considered if they are involved in viral respiratory infections, bacterial sepsis, and malaria, as these three topics are discussed in more detail below. For an initial “warming up,” the reader is referred to articles cited under [21, 39–47].
5.3.2 High Mobility Group Box 1 5.3.2.1 General Remarks The nature and function of HMGB1 have been addressed in Vol. 1 [1], Sect. 12.2.2, pp. 220–226. As could be expected, most reports on the role of DAMPs in infections refer to this prototype HMGB1. Interestingly, some of those publications already stressed the possibility of using this DAMP in the future as an essential biomarker in diagnosis and prognosis of infectious diseases as well as therapeutic targets in these disorders. 5.3.2.2 Bacterial Infections Clinical observations on the pathogenetic role of HMGB1 in pneumonia were already supported by earlier in vitro studies conducted in 2013, showing that the inflammation response in normal human bronchial epithelial cells, as indicated by the release of proinflammatory cytokines, can be stimulated by the application of HMGB1 [48]. During this time period, clinical evaluation of HMGB1 blood levels in the sera and bronchoalveolar lavage fluid (BALF) of patients with Legionella pneumophila pneumonia were also reported, which revealed findings suggesting that intrapulmonary HMGB1 may be involved in the pathophysiology of this respiratory disease [49]. The authors of this study concluded that their findings suggest that intrapulmonary HMGB1 may be involved in the pathophysiology of pneumonia caused by L. pneumophila. Subsequent studies on patients with pneumonia showed conflicting results. Thus, in a study on patients with suspected community-acquired pneumonia [50], the levels of plasma HMGB1 were found to be significantly elevated compared with the controls, and plasma HMGB1 correlated with the pneumonia severity. By contrast, in a study on patients with pneumococcal pneumonia [42], the HMGB1 levels, measured in plasma and sputum of patients, were shown to be related only to bacteremia but not correlated to disease severity. Yet, the role of HMGB1 in infections has also been explored in extrapulmonary organ systems. For example, investigations on a pneumococcal meningitis mouse model revealed that adjunctive inhibition of HMGB1 can reduce mortality in diseased mice [51]. Similarly, in other lines of various studies, including in vitro
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experiments and investigations on a model of intestinal epithelial HMGB1-KO mice with Salmonella-colitis, as well as human samples, intestinal HMGB1 was found to operate as an important contributor to host protection from inflammation and infection [52].
5.3.2.3 Viral Infections The protective → pathological action of the prototypic DAMP has also been explored in viral infections. For example, in preclinical studies, HMGB1 was shown to operate as a significant inflammation factor in Newcastle disease virus (NDV) infection [53]. The experiments revealed that HMGB1 promotes inflammatory cytokine production through the receptor for advanced glycation end products (RAGE), TLR2, and TLR4 receptors. HMGB1↔RAGE interaction was also shown to take part in the activation of ERK1/2 and JNK induced by NDV infection. In studies on mice, HMGB1 was found to mediate human adenovirus (HAdV) type 7—infection-induced pulmonary inflammation in mice [54]. The authors concluded from their findings that HMGB1 promotes HAdV-7 replication and signals through TLR4, TLR9, and RAGE receptors to activate NF-κB, stimulating the release of inflammatory mediators and contributing to adenoviral pathology. Interestingly, as outlined by Gougeon [55], HMGB1 has been identified as a specific biomarker in cerebrospinal fluid from patients with HIV-1-associated neurocognitive disorders. In fact, HMGB1 was shown to correlate with immune activation and identify a very early stage of neurocognitive impairment that precedes changes in metabolites detected by magnetic resonance spectroscopy. 5.3.2.4 Fungal Infections First clinical observations on the role of HMGB1 in fungal infections have been reported as well. For example, already in 2010, the concentrations of HMGB1 measured in the BALF of patients with pneumocystis pneumonia (caused by the fungus Pneumocystis jirovecii) were found to be positively correlated with the proportion of neutrophils in the fluid and inversely with the oxygenation index [56]. In later years conducted studies on a chronic obstructive pulmonary disease (COPD) model in mice, HMGB1 was demonstrated to mediate Aspergillus fumigatus-induced inflammatory response in alveolar macrophages via activating MyD88/NF-κB and Syk/PI3K signalings [57]. In other lines of experimental studies on the role of autophagy in the innate immune response to mice with A. fumigatus keratitis, treatment with autophagy inhibitors was shown to be associated with upregulation of HMGB1 (besides clinical scores and besides inflammatory cytokines) [58]. Notably, in recent clinical studies on the role of HMGB1 in invasive Candida albicans infection, the researchers found that HMGB1 levels are significantly increased in patients suffering from this fungal disease [59]. Moreover, in parallel studies in mice, the investigators showed that administration of ethyl pyruvate, an HMGB1 inhibitor, can prevent C. albicans lethality by decreasing HMGB1 expression and release. In view of their findings, the authors concluded that HMGB1 may provide an effective diagnostic and therapeutic target for invasive C. albicans infections [59].
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5.3.3 S100A Proteins (Calgranulins) 5.3.3.1 General Remarks The nature and function of S100 proteins, or calgranulins, in particular, S100A8/ S100A9 (calprotectin) and S100A12, have been addressed in Vol. 1 [1], Sect. 12.2.4.2, pp. 229–230 and Sect. 14.2.2.4, p. 310. These molecules, released from necrotic cells as IA-1-DAMPs and secreted as IIIA-1 DAMPs by activated innate immune cells (e.g., neutrophils and macrophages), have also been reported to be pathogenetically involved in infections. As reviewed earlier by Hsu et al. [60], the calgranulins possess a variety of properties to protect the host against pathogens. These DAMPs serve as leukocyte chemoattractants, and their protective functions include oxidant scavenging, antimicrobial activity, and chemokine-like activities. The authors concluded that these molecules are remarkable as multifunctional proteins dedicated to protecting the intra- and extracellular environments during infection and inflammation. From the mechanism of action point of view, a report is of interest showing that S100 proteins exhibit antimicrobial properties through the process of metal limitation, termed nutritional immunity (discussed in [61]). In a more recent review, Wang et al. [62] stressed that these DAMPs can serve as valuable candidate biomarkers for diagnosis and prognosis of inflammation-associated disorders and that they have the potential as therapeutic targets. 5.3.3.2 Bacterial Infections Several earlier studies have already shown that the concentration of S100A8/ S100A9 in the stool correlates with intestinal inflammation, as particularly demonstrated in IBD (reviewed in [63, 64]). Of interest is an investigation from this time period in a model of streptococcal pneumonia demonstrating that the blockade of antimicrobial proteins S100A8 and S100A9 inhibits phagocyte migration to the alveoli in streptococcal pneumonia [65]. The researchers emphasized that the blockade of S100A8 and S100A9 activity is also associated with an accumulation of neutrophils and monocytes in lung tissue. In more recent studies, the level of fecal S100A8/S100A9 proteins was found to correlate significantly with Clostridium difficile infection severity, qualifying this DAMP as a predictive marker for assessing this disease severity [66]. Yet, the role of S100 proteins in infections, especially in their use as biomarkers, has also been explored in extraintestinal and extrapulmonary organ systems. For example, a recent systematic review on the diagnostic accuracy of ascitic calprotectin for the early diagnosis of spontaneous bacterial peritonitis revealed ascitic calprotectin to be an excellent alternative to PMN leukocyte count of ≥250 cells/mm3 for the diagnosis of spontaneous bacterial peritonitis, with much faster time to diagnosis [67]. The investigators concluded that owing to its substantially high negative predictive value, the test for these molecules can accurately exclude this disorder, avoiding unnecessary antibiotics in suspected patients. Moreover, in other lines of studies on the well-established mouse model of tuberculosis (TB), evidence was provided that S100A8/A9 promotes neutrophil accumulation during the progression to chronic disease [68]. In addition, the researchers could demonstrate that S100A8/
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A9 serum levels, along with chemokines, are useful in distinguishing between active tuberculosis and asymptomatic Mycobacterium tuberculosis-infected latent individuals. In fact, the idea of using these DAMPs in distinguishing different disorders has also been demonstrated in the diagnosis of arthritis. Thus, it could be shown in a clinical study that the determination of S100A8/A9 proteins in the synovial fluid of patients can discriminate septic arthritis from pseudogout and rheumatoid arthritis, whereby these DAMPs were significantly increased in patients with septic arthritis [69].
5.3.3.3 Viral Infections In the field of viral infections, S100A and S100A9 proteins have recently received much attention as DAMPs to promote COVID-19-associated hyperinflammation [70, 71] (also see below, Sect. 5.4.2.3). Yet, these molecules have already been reported to be elevated in the serum of HIV-infected patients and suggested to reflect immune activation before the DAMPs were described [72]. That these DAMPs can exacerbate viral diseases has been demonstrated in studies on their role in Coxsackievirus B3 (CVB3)-induced myocarditis [73]. In investigations on endomyocardial biopsies of patients with myocarditis, as well as on experimental CVB3 models, including S100A8/S100A9 KO animals and under cell culture conditions, the researchers revealed a pronounced pathogenetic role of these DAMPs in this myocardial infectious disease; demonstrated that cardiac decrease of S100A8 and S100A9 expression in CVB3-positive patients is associated with an improved clinical course, and showed that loss of S100A9 and S100A8 rescues CVB3-infected myocarditis mice from cardiac inflammation and oxidative stress [73]. 5.3.3.4 Concluding Remarks Indeed, S100 proteins, in particular, S100A8/A9, have evolved as strong DAMPs implicated in the pathogenesis of infectious diseases, including fungal infections [74, 75] (not further discussed here). Given the importance of the complexed S100A8/A9 in biological functions of inflammation-associated disorders in general, the exact mechanisms of action in defense and pathologies are still not very clear. In this context, Wang et al. [62] concluded: With respect to functional studies, only a few detailed characterizations exist related to S100A8/A9, while there are adequate studies on S100A8 and S100A9 separately. This condition requires researchers to carry out more experiments in the future to facilitate our understanding of the S100A8/A9 heterodimer.
5.3.4 Extracellular Nucleic Acids, Histones, and Nucleosomes 5.3.4.1 General Remarks When exploring endogenous NAs in their role as DAMPs in infections, one has to differentiate between extracellular NAs, passively released from pathogen-induced subroutines of RN [37] or secreted within EVs [38] as inducible DAMPs, as well as
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cytosolic NAs generated in the course of a stressed infected host cell (for passively released NAs, see Vol. 1 [1], Sect. 12.2.4.3, Fig. 12.3, pp. 230–232; for cytosolic NAs, see Sects. 13.4.3 and 13.4.4, pp. 286–289). Theoretically, however, every extracellular unmodified and modified host NA (sensed by endosomal TLRs, cf. Fig. 4.5) or intracellularly mislocalized host NA (sensed, e.g., by RIG-I, MDA5, or cGAS → STING, cf. Figs. 4.6 and 4.7), or bacterial/viral/fungal NA may operate either as an endogenous or an exogenous DAMP during an infection. In particular, NAs such as mtDNA containing CpG-DNA repeats and nDNA, as well as cytosolic accumulated RNA, appear to convey potent immunostimulatory capabilities in host defense against infections. Like NAs, histones have been recognized as powerful DAMPs to trigger innate immune responses in infections. When released from dying cells (e.g., succumbing to RCD such as NETosis) into the extracellular space, histones (i.e., free histones), DNA-bound histones (nucleosomes), or part of NETs, have been recognized as candidates of the DAMP family, and as such all three can be detected in serum after significant cellular death such as occurring in infective or sterile SIRS. The impact of histones on triggering innate immune responses has gained even more importance in light of studies showing that they can activate the NLRP3 inflammasome [76], associated with the pyroptosis-mediated release of another round of DAMPs. A few examples are given in the following by focusing on extracellular NAs.
5.3.4.2 Bacterial Infections Investigations on the role of NAs in bacterial infections have already been reported. For example, in a study on patients with bacterial meningitis, levels of plasma nDNA and mtDNA were shown to be significantly increased initially and substantially decreased thereafter [77]. Interestingly, in this clinical investigation, higher plasma levels of both DAMPs at presentation were found to be associated with poor outcomes in this patient cohort. In this context, an isolated rat lung perfusion model is of considerable interest, aimed at testing the hypothesis that bacteria might be a stimulus for mtDNA release [78]. In this experimental study, the researchers measured mtDNA abundance in the medium of perfused rat lungs challenged with intratracheal instillation of Pseudomonas aeruginosa. And indeed, they found that this pathogen causes oxidative mtDNA damage leading to a feed-forward cycle of mtDNA formation and TLR9-dependent mtDNA damage, culminating in acute kidney injury (AKI). Extracellular RNAs—mainly exported and transported to the extracellular medium through EVs such as exosomes—have also been identified in bacterial infections as potent inducible DAMPs involved in host ↔ pathogen interactions (reviewed in [79]; also compare Sect. 3.6.2). In particular, microRNAs (miRNAs) are increasingly implicated in defense responses to bacterial pathogens, including Helicobacter pylori, Salmonella enterica, and Listeria monocytogenes (for review, see [80]). For example, in studies about the impact of miR-155 (a prototypical miRNA operating as a putative inducible DAMP), loaded in exosomes derived from
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macrophages upon the inflammatory response of Helicobacter pylori-infected macrophages, miR-155 was found to promote the expression of inflammatory cytokines [81]. Extracellular histones—mainly derived from infection-induced NETosis (see Sect. 3.7.7)—have also been found to operate as DAMPs in bacterial infections. For example, in studies on samples of tuberculous pleural effusion (TPE) and peripheral blood from patients with tuberculosis, extracellular histones were found to be significantly elevated compared to controls [82]. In light of their observations, the authors concluded that extracellular histones may aggravate the inflammatory processes involved with TPE. Extracellular histones may be considered as a potential biomarker for TPE, and could be used to diagnose, monitor or improve the prognosis of TPE.
5.3.4.3 Viral Infections Notably, endogenous NAs have been reported to be implicated in viral infections as well. For instance, mtDNA was shown to be increased in acute HIV infection [83]. Given viroimmunological parameters obtained from a study in patients with acute HIV infection (not quoted here), the authors concluded that the immunological response is likely to also depend upon other crucial factors that are able to trigger and drive inflammation, such as mtDNA. These observations were supported by another study on HIV patients showing that in acute HIV infection and late presenters taking antiretroviral therapy for the first time, mtDNA plasma levels are significantly higher than in healthy individuals [84]. Notably, the authors also found that the plasma mtDNA levels had a significant correlation with plasma viral load, revealing a possible role for mtDNA in inflammation or as a biomarker of virusinduced damage. Extracellular RNAs, released from virus-infected cells and shuttled to the extracellular medium by EVs such as exosomes—have not only been demonstrated in bacterial but also viral infections, although it appears not always trivial to understand whether the up- or down-regulation of a given miRNA upon infection is driven by a viral or host mechanism (reviewed in [85, 86]). Thus, cellular host miRNAs have been reported to be implicated in viral infection through various targets, whereby their function may be proviral or antiviral. Indeed, several studies have revealed that virus-infected cells release higher levels of specific host miRNAs in EVs. For example, in studies on an in vitro model of intercellular communications between human macrophages and hepatocytes, TLR3-activated macrophages were demonstrated to release exosomes that contain anti-HCV miRNA-29 family members, which were observed to inhibit viral replication in host hepatocytes: a nice example of a mechanism, by which macrophages can confer antiviral immune protection to hepatocytes [87]. Extracellular histones derived from NETs and acting as DAMPs in viral infections have recently received considerable attention in their use as prognostic biomarkers for COVID-19 patients and will be further discussed below.
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5.3.5 SAMPs The inflammation-resolving properties of SAMPs have been described in Vol. 1 [1], Sect. 14.4, pp. 330–338, and Sect. 22.2.3, pp. 480–482, and Vol. 2 [2], Sect. 5.3, Fig. 5.1, pp. 152–160 (also see Sect. 4.4.4). As expected, there is also increasing evidence for their inflammation-resolving role in infections. Indeed, already a decade ago, the administration of SPMs (RvD1, RvD5, and PD1) was shown to enhance the phagocytosis of bacteria and lower the required antibiotic doses for bacterial clearance [88]. Also, other sets of studies revealed PD1 to be able to suppress influenza virus replication, thereby protecting against lethal influenza virus infection [89]. Another potent SAMP, AnxA1, was also shown to be endowed with inflammation/immunity-resolving capacities in preclinical models of infections [90]. For example, experiments in chimeric mice lacking AnxA1 in T cells revealed that this SAMP mediates the power of DC efferocytosis and cross-presentation during Mycobacterium tuberculosis infection [91]. Also, in experimental studies on pneumococcal pneumonia in mice, the AnxA1/FPR2 pathway was found to control the inflammatory response and bacterial dissemination [92]. Moreover, working on a murine model of Streptococcus suis-induced meningitis, researchers could demonstrate that AnxA1 attenuates neutrophil migration and IL-6 expression through the FPR2 receptor [93] (for AnxA1 and its binding to FPR2, see Vol. 1 [1], Sect. 4.4.3, and Fig. 14.5, pp. 333–335). Another SAMP, PGE2 (now denoted as a molecule acting context-dependently as a DAMP or SAMP, see Sect. 1.2.4.5), was also shown to be implicated in bacterial and viral infections, although—quod erat demonstrandum—varying effects (inflammation-promoting and/or -suppressing) were described [94, 95]. On the other hand, when looking into the majority of those studies on the effect of PGE2 in infectious inflammation, the primary objective of the experiments was not directed to inflammation-resolving properties. Thus, future studies in this area will hopefully clarify the role of this molecule in infections. As a whole, the initiation of targeted studies on the potential inflammationresolving role of SAMPs in infections is a worthwhile and emerging starting platform for future research work in infectious diseases.
5.3.6 Résumé In this section, only a brief selection of articles and reviews on DAMPs and SAMPs has been covered. Furthermore, the inducible DAMPs, such as TNF and type I IFNs, known to play a pivotal role in infections, were not mentioned at all. However, also in the light of what has been presented in the preceding chapters, this version, condensed to a few examples, is a clear indication of the enormous progress made in this modern research field of infectious injury-induced immunity over the past
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two decades. To deepen this topic, three diseases are presented in the following, which appear to exemplify the pathogenetic impact of these infectious injuryinduced molecules impressively.
5.4 Pathogenetic Impact of MAMPs and DAMPs on Viral Diseases: The Example of Pneumonia-Related Acute Respiratory Distress Syndrome 5.4.1 Introductory Remarks 5.4.1.1 General Remarks In humans, not surprisingly, the most common types of infection are respiratory tract infections, among which viral infections predominate. And it is the lower respiratory tract infections that are responsible for the most deaths from an infectious disease worldwide and thus have a considerable economic and personal burden [96]. The list of viruses that can cause respiratory tract infection is rather long. According to a systematic review and a meta-analysis, the most commonly identified pathogenic viruses in community-acquired pneumonia include influenza viruses, rhinovirus, syncytial respiratory virus, and coronaviruses [97]. The influenza virus causes the most recurring respiratory disease in humans, with outbreaks likely occurring since at least the Middle Ages [98]. Present estimates indicate that each year, seasonal influenza affects 5–10% of the world’s population, resulting in 3–5 million cases of critical illness and between 250,000 and 500,000 deaths [99]. In past years, besides influenza viruses [100], SARS coronaviruses, SARS-CoV [101, 102], MERS [103], and recently, SARS-CoV-2 [104], have come into the spotlight as causative agents of severe pneumonia. Indeed, at the time of writing, that is, in 2020–2022, the SARS-CoV-2 pandemic raised considerable interest in the media and among the general public. 5.4.1.2 Symptomatology and Clinical Picture of Respiratory Tract Infection → Pneumonia In general, an acute viral infection is characterized by rapid onset of the inflammatory disease, a relatively brief period of symptoms, and, within days, inflammation-resolution associated with the elimination of a given virus and tissue repair (i.e., restoration of homeostasis). In the end, the acute viral disease is the work of a perfectly functioning MAMP/DAMP-orchestrated innate/adaptive immune defense system, whereby inflammation and immunity are considered robust protective responses in all mammals. Elimination of the virus, clearance of damaged cells and the viral antigens, effector cells, and cytokines allow both the innate and adaptive immune system to reset to an uninfected but memoryarmed state that includes trained immunity as a memory for innate host defense, memory B and T cells, as well as plasma cells that continuously produce antibodies, when homed to their bone marrow niche (compare Chap. 4; for more information about innate/adaptive immune effector responses and innate and adaptive
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immune memory, also see Vol. 1 [1], Part VI, pp. 473–659 and Part VIII, pp. 717–869). Doubtlessly, any acute virus-induced organ injury must be assessed as the first pathophysiological momentum in the development of viral diseases. To come to the theme, in respiratory virus-induced pneumonia, it is the ALI that is clinically defined as an acute inflammatory disorder with substantial morbidity. If pulmonary inflammation, that is, pneumonia, does not resolve, ALI can progress to a fulminant lifethreatening, and complex pulmonary process, first officially described as ARDS in 1967 [105]. Extreme high viral load, strong virulence in terms of the powerful capability of a virus to induce RCD, the way of virus entrance, and genetic polymorphisms predisposing individuals to the injurious effects of specific viruses may contribute to the culmination of initially mild pneumonia to such a life-threatening syndrome. As a characteristic complication of severe pneumonia, ARDS is a complex and cascading process. Both ALI and ARDS are considered as common lifethreatening critical illnesses with substantial morbidity and mortality of about 40% [106–108]. This life-threatening and lethal disorder develops in most cases within 2–5 days of hospitalization and is usually diagnosed clinico-radiographically. Of note, ALI → ARDS, characterized by overwhelming inflammation, that is, hyperinflammation can develop not only upon viral infections but also various other pulmonary injurious conditions such as major trauma without or with shock, burns, aspiration, mechanical ventilation, and bacterial infection (compare Vol. 2 [2], Sect. 9.3, pp. 347–359). It is worth adding here that ALI-induced pulmonary inflammation has primarily to be considered a beneficial immune response in terms of protective inflammation that is characterized by an initiation/promotion phase and subsequent resolution phase aimed at fighting respiratory infections successfully. However, progression to aberrant exaggerated hyperinflammatory responses in ARDS patients caused by events mentioned above can result in fatal outcomes such as progressive respiratory failure and, when spreading systemically, sepsis, septic shock, and MODS (for competent papers, see [109–114]; also compare Vol. 2 [2], Sect. 8.3, pp. 290–307).
5.4.1.3 Classification of ALI → ARDS Notably, the classification of ALI → ARDS is differently understood. In 2012, the complex of symptoms observed in ARDS had been assessed by the Berlin Definition, which specifies three severity classifications based on the intensity of hypoxemia: mild, moderate, and severe ARDS, whereby the mild course (“ALI non-ARDS”) is equivalent to the earlier definition of ALI (among others corresponding to mild pneumonia) [107]. Today, however, many reports on SARS-CoV-2 infection deviate from this definition and rather rely on the WHO classification of COVID-19 disease severity [115, 116]: (1) mild disease (symptoms without pneumonia); (2) moderate disease (moderate pneumonia); (3) severe disease (severe pneumonia); (4) critical disease (ARDS—sepsis—septic shock). In other words, the WHO classification refers mainly to infectious inflammatory criteria. In good line with this guideline are reports of Chinese investigators. They observed that COVID-19 could lead to mild pneumonia symptomatology but also—like other viral respiratory
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diseases—to critical illnesses such as ALI → ARDS, septic shock associated with MODS, and resultant death [117–120]. As of February 2020, the case fatality rate of COVID-19 infections has reportedly been approximately 2.2%, compared to 9.6% in the SARS-CoV epidemic and 34.4% in the MERS-CoV outbreak since 2012 [121]. As of June 2021, the mortality rate for COVID-19 infection was 2.17% worldwide, according to information available online [122]. As of 8 May 2022, over 514 million confirmed cases and over six million deaths had been reported globally by the WHO [123].
5.4.2 Demonstration of MAMPs, DAMPs, and SAMPs in Respiratory Virus Infections 5.4.2.1 General Remarks Over a long period of time, infection-induced inflammation was thought to be solely due to recognition of and response to pathogen-derived MAMPs by PRR-bearing cells of our defense system. As outlined in the previous chapters, these views have changed, in particular, as a consequence of accumulating reports on pathogens, including respiratory viruses, to induce various subroutines of RCD (outlined in Sect. 3.7). On the other hand, a growing number of studies have shown that the event of RCD is associated with the release of constitutive DAMPs and secretion of inducible DAMPs capable of promoting inflammatory responses [124–127] (for the definition of the various subclasses, nature, and function of DAMPs and SAMPs, see Tables 1.1, 1.2, and 1.3; Vol. 1 [1], Chaps. 12–14. pp. 219–369; and Vol. 2 [2], Chap. 3, pp. 66–102). Collectively, it is now widely accepted that DAMPs—together with MAMPs— play a crucial pathogenetic role in infectious inflammatory disorders. Indeed, as discussed above in Sect. 4.7.2, there is increasing evidence suggesting that it is this interplay between MAMPs, constitutive DAMPs, and inducible DAMPs which promotes robust inflammatory/immune responses to defend against pathogens. And according to current knowledge, this interplay scenario between exogenous and endogenous pathogenesis-causing molecules matches respiratory virus infections in patients as well. Some information on this currently hot topic in infectiology with a focus on influenza virus and coronavirus should be added here. 5.4.2.2 MAMPs Here, the recognition of MAMPs derived from respiratory viruses such as influenza virus and coronavirus is of particular importance. Hence, a few facts, as outlined in Sects. 2.7.4 and 4.2.2, are repeated in the following. The influenza virus is a negative-sense ssRNA recognized by several PRRs, including TLRs, RIG-I, and NLRP3 [128]. Given that coronaviruses, like influenza viruses, are RNA viruses, it is important to know that, in principle, upon RNA virus infection, viral RNA genomes are recognized by RLRs [129]. Notably, however, the prototypical MAMP relevant for coronaviruses is not its genome, the ssRNA itself, but a dsRNA. This puzzling finding is due to the fact that dsRNA is a by-product of ssRNA genome translation,
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RNA replication, and transcription following the entrance of the virus into a cell (cf. Fig. 2.13; also see [130, 131]; for reviews, see [132, 133]). Double-stranded RNA can be sensed by TLR3 in the endosome [134] and in the cytoplasm by RIG-I and MDA5 as well as by the kinase PKR (for further reading, see [135–137]).
5.4.2.3 DAMPs DAMPs may already be generated during processes associated with virus entry in the cell and subsequent intracellular replication and processing of viral proteins, that is, processes that cause molecular perturbations (e.g., acidosis during clathrinmediated endocytosis of coronaviruses [138], as it does the generation of ER stress during coronaviral protein processing [139]; also compare stress as exemplified by the intracellular SARS-CoV-2 life cycle, described and illustrated in Sect. 3.3.2 and Fig. 3.5). These cell-intrinsic perturbations reflect the generation of dysDAMPs. As mentioned in Sect. 3.6.6.2 these ER stress-associated DAMPs are sensed by UPRassociated receptors such as PERK. Moreover, cells that undergo episodes of ER stress, including pathogen-induced stress, can not only express those dysDAMPs but were also shown to expose DAMPs on their surface and release them into the extracellular space, respectively [140–142]. On the other hand, as recently reviewed [143], human CoV infections (SARS CoV and MERS CoV)—in the course of replication process-associated drastic alterations in cellular structure—were demonstrated to activate cell-intrinsic ER stress as well [144]. In fact, earlier studies had already provided evidence showing that coronavirus infection causes ER stress and induces a UPR in infected cells [139, 145]). Moreover, a number of LPLs, believed to promote efficient coronavirus replication, were shown to be upregulated upon HCoV-229E infection [146]. Here, LPLs are denoted as endogenous modified molecules acting as inducible DAMPs (i.e., IIIB-5 DAMPs, see Table 1.2; elsewhere, also called conditional DAMPs [147]). Also, the cytokines Il-1β (released from pyroptotic cells), TNF, and type I IFNs (secreted from activated cells such as leukocytes and macrophages and both denoted as inducible DAMPs) can be discussed to contribute to the promotion of respiratory virus-mediated inflammation. Moreover, IA-1 DAMPs have also been observed in respiratory viral infections. And remarkably, a possible pathogenic role of the prototypic DAMP HMGB1 in severe SARS-CoV-induced pulmonary inflammation has already been suggested by Chen et al. in 2004 [148]. First experimental studies on DAMPs in respiratory viral infections were reported in 2008 when Imai et al. [149] showed that host OxPLs (i.e., DAMPs out of the subclass of OSEs) mediate influenza virus H5N1-induced ALI in mice. Subsequent preclinical studies on mouse models of pneumonia following infection with the H5N1 strain of influenza virus already provided the first evidence indicating that HMGB1 can drive inflammatory pathways [150–152]. In more recent studies on influenza-infected rats, HMGB1 was identified as a potential biomarker of infection severity, qualifying this DAMP as a potentially useful therapeutic target in influenza virus-induced ALI [153]. Another DAMP shown to regulate inflammation during IAV infection is S100A9, which, released from IAV-infected cells, exaggerates reportedly proinflammatory response, cell death, and virus pathogenesis [154]. As mentioned above, this DAMP in the form of its heterodimer
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S100A8/A9 (i.e., calprotectin) has recently received increasing attention in COVID-19 as a molecule to promote disease-associated hyperinflammation, such as occurs in ARDS. Moreover, the DAMP has also been identified as a valuable biomarker since its serum levels, like HMGB1 serum levels, were found to be strongly correlated with the severity of clinical manifestations in COVID-19 patients and with significant predictive power for the risk of ICU admission and death [70, 155, 156]. Also, recently, high circulating mtDNA levels have been detected in COVID-19 patients and found to be a potential early indicator for poor outcomes [157]. Given the discovery of subroutines of RCD in influenza infection as productive sources of DAMPs, it can be anticipated that, in a short time, further DAMPs involved in triggering inflammatory responses in influenza infection and COVID-19 will be reported.
5.4.2.4 SAMPs The recovery rate of COVID-19 patients is about 80% [158], implying that strong inflammation-resolving forces are involved. Indeed, viral pathogens appear to interact with the host in a way that is modifiable by proresolving factors. Some preclinical evidence in support of this concept has already been published. For example, in studies on a murine IAV infection model, AnxA1-treated mice were shown to display significantly attenuated pathology upon a subsequent IAV infection with significantly improved survival, impaired viral replication in the respiratory tract, and less severe lung damage [159]. In other lines of studies on several in vivo models of lung inflammation and infection (reviewed in [159]), inflammatory lung injury was observed to be exacerbated in AnxA1-deficient mice, suggesting that this SAMP has a general protective role in the lung. Of note, in a recent case-control study of COVID-19 patients, AnxA1 serum levels were found to be significantly lower in the severe/critical disease group compared with the control and moderate disease groups [160]. Given their observations, the authors concluded: AnxA1 levels may be a beneficial biomarker in the diagnosis of COVID-19 pneumonia and in predicting the need for ICU treatment in patients with COVID-19 pneumonia at the time of admission to the emergency department. The inflammation-resolving role of SPMs in lung infection and inflammation is well documented and has been reviewed by Basil and Levy [161]. For example, in elegant studies on PD1 in several murine influenza models, Morita et al. [89] observed that treatment of influenza virus-infected mice with this SPM improves their survival, even when administered as late as 48 h after infection, that is, at a time when current antiviral therapies are no longer significantly effective [162]. In other lines of studies, virulent strains of influenza were demonstrated to lead to suppression of LX accompanied by inhibition of anti-inflammatory responses, a scenario that is associated with enhanced viral dissemination [163]. In addition, the SPM 17-HDHA was shown to enhance virus-specific humoral immunity in a preclinical influenza vaccination model, proving a link between proresolution pathways and adaptive immunity [164]. It is also noteworthy that, in the first study on
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SAMPs in COVID-19, PGE2 and RvE3 could be measured in the patients’ serum and were found to be decreased in severe cases [165].
5.4.3 Change of Viewpoints in the Pathogenesis of ALI → ARDS The change of viewpoints, as touched above, is also equally applicable to infectionassociated ALI → ARDS. In fact, these new views on the dominant role of DAMPs in triggering inflammatory pathways have also contributed to a better understanding of the exact molecular mechanisms governing the pathogenesis of ALI → ARDS in general, which had remained elusive despite many years of experimental and clinical studies. Thus, in the end, it is obviously the DAMPs, which, when emitted in a controlled or uncontrolled and excessive way—by what mechanism whatsoever— drive robust proinflammatory → hyperinflammatory responses, clinically then manifested in the lung as ALI → ARDS and, when spreading, sepsis/SIRS (for further reading, see [21, 166–171]). Accordingly, here, MAMP/DAMP/SAMP-driven inflammation-promoting and inflammation-resolving responses, as described in Sect. 4.3, are tentatively projected onto respiratory virus-induced mild ALI non-ARDS [107] (WHO: “moderate pneumonia” [116]), progressing to severe ARDS [107] (WHO: “critical disease” [116]). To understand these inflammatory responses in ARDS, a brief “a priori” look at cellular events is useful. And as a note for the reader: the cellular events have already been mentioned in Vol. 2 [2], Sect. 9.3, pp. 347–359, in which the pathogenesis of sterile injury-induced ALI-ARDS is described in more detail.
5.4.4 Cellular Events in ARDS Typically, in virus-induced ARDS, the alveolar epithelium can be regarded as a critical target of innate immune attacks. It is composed of two types of cells, which, under homeostatic conditions, form a natural barrier. PRR-bearing AECI are flat cells that mediate the gas exchange. These cells compose 90% of the alveolar epithelium and are sensitive to toxins and stress (e.g., oxidative stress), and are prone to necrosis (Fig. 5.2). PRR-bearing AECII, which make up 10% of the alveolar surface area, are a key structure of the distal lung epithelium, where they exert their innate immune function and serve as progenitors of AECI. As a defender of the alveolus, AECII are involved in the secretion of surfactant proteins, which are important in lung protection against pathogen exposure. Also, they may contribute to fibroproliferation and differentiation to AECI, contributing to alveolar epithelial repair and regeneration upon damage (Fig. 5.2). In ARDS, AECII injury results in a decreased production of surfactant, interfering with the normal lung repair processes and eventually leading to diffuse lung fibrosis [172, 173]. Of note, preclinical studies and experiments on the in vivo human lung-only mice (LoM) model provided first evidence that ACE2-expressing AECII (but less AECI) are infected by SARS-CoV-2 [174–176]. Moreover, in other sets of studies
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Fig. 5.2 Simplified schematic diagram of a narrative model of the action of DAMPs and SAMPs in respiratory virus-induced acute lung injury. Injury-induced DAMPs (e.g., released from type 1 alveolar epithelial cells succumbing to RCD) activate PRR-bearing innate immune cells such as alveolar epithelial cells and resident alveolar macrophages, which secrete the first wave of cytokines. Subsequently, these inflammatory mediators amplify the inflammatory response via recruitment of further innate immune/proinflammatory cells such as PMNs and M1-like macrophages, which in turn intensify acute pulmonary inflammation via the secretion of further proinflammatory mediator substances (e.g., cytokines). Pulmonary inflammation resolution is initiated by a switch of the PMN phenotype and shift of M1-like to M2-like macrophages, whereby SAMPs, mainly secreted by injury-activated M2-like macrophages, fewer neutrophils, contribute to resolution via promotion of anti-inflammatory mechanisms (e.g., production of IL-10), efferocytosis, and reepithelialization—the end result being the repair of the alveolar barrier. Note: Co-activating virusassociated MAMPs are not shown. Also note: injured alveolar epithelial type I cells are representative of other injured cells such as alveolar epithelial type II cells and ECs. In particular, the target role of the endothelium is not shown. AECI alveolar epithelial type I cells, AECII alveolar epithelial type II cells, ECM extracellular matrix, MØ macrophage, PMN polymorphonuclear leukocytes, RCD regulated cell death (Sources: The figure is slightly modified from Vol. 2 [2], Danger Signals as Diagnostics, Prognostics, and Therapeutics; also re-published in Genes & Immunity 2021 [235]; further Refs. [191, 204–209])
on COVID-19, infected AECII were found to transmit the virus to AECI with the rapid spread of viral replication that can turn this type of injury explosive, creating a diffuse injury. Also, in COVID-19, loss of AECII was observed, implying loss of progenitors for AECI, thus interfering with the regenerative capacity of AECI and possibly resulting in progressive deterioration of respiratory function [173, 177]. The interaction between the epithelial barrier and the other barrier, the microvascular endothelium, plays a crucial role in controlling fluid accumulation in the alveolar space. In ARDS, this process becomes out of control via virus-induced RCD of ECs (such as apoptosis and necroptosis) that is promoted by various inflammatory and cytotoxic mediators. This leads to disruption of the alveolar-capillary barrier associated with hyperpermeability and the consequent influx of fluid into the alveoli, resulting in pulmonary edema, intrapulmonary hemorrhage, severely impaired
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gas exchange, decreased lung compliance, and increased pulmonary arterial pressure. Further, the injury of alveolar epithelium impairs active fluid transport mechanisms in the lung, preventing the reabsorption of edema fluid from the alveolar space, which is a key step in the resolution of ARDS (reviewed in [109, 178–181]). Interestingly, some of these findings have recently been reviewed for COVID-19 ARDS [182]. Whereas the exudative stage is characterized by diffuse alveolar damage, a subsequent second stage of fibroproliferation is manifested by the resolution of pulmonary edema and hyperplastic proliferation of AECII, which contribute to alveolar epithelial repair and regeneration [178, 183]. Of note, in studies on transbronchial lung cryobiopsy carried out in COVID-19 patients, AECII hyperplasia was found to be a prominent event in the majority of cases [184].
5.4.5 MAMP/DAMP/SAMP-Driven Dysregulated Innate Immune Responses in ARDS 5.4.5.1 General Remarks A growing number of articles have been published discussing the pathogenetic action of DAMPs in ALI → ARDS, including sepsis-induced ARDS (reviewed in [185, 186]). Thus, as recently reported by Li et al. [187], there is increasing evidence from various noninfectious and infectious ARDS models showing that the pulmonary inflammatory pathways are induced by DAMPs, including HMGB1, histones, and S100A8/9 proteins. These observations are supported by other lines of studies in mice showing that extracellular mtDNA and eATP are also able to contribute to the induction of ALI → ARDS [188, 189]. Again, in another set of studies on a bromine gas inhalation-induced ALI model in mice, attenuation of the DAMP heme was shown to improve survival after bromine gas exposure [190]. It goes without saying that in the respiratory virus-triggered pneumonia scenario, DAMPs work in concert with MAMPs acting as exogenous DAMPs (i.e., viral RNA) to elicit robust innate immune responses. 5.4.5.2 Initiation of Lung Inflammation In accordance with the conceptual model outlined here, current notions hold that, in respiratory virus-induced pneumonia (i.e., ALI non-ARDS/moderate ARDS), the initial proinflammatory response is mediated by a first wave of cytokines (e.g., type I IFNs, TNF, IL-6, and granulocyte-macrophage colony-stimulating factor [GM-CSF]) and chemokines (e.g., IL-8/CXCL8, IP-10/CXCL10, and CCL5/ RANTES), secreted by MAMP/DAMP-activated, PRR-bearing AECI and AECII, alveolar macrophages, ILCs, and ECs [191] (Fig. 5.2). This concept is supported by reports from noninfectious lung injury models showing that these pulmonary innate immune cells are activated by DAMPs [109, 192, 193], while, in lung injury mediated by respiratory viruses including IAV and SARS-CoV-2, other reports still focus expressively on viral RNA and inducible DAMPs (e.g., type I IFNs) to interact with PRRs [194–197] (considering viral RNA as exogenous
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DAMPs, probably, all three molecules are operating as DAMPs in concert). In mild cases, the inflammatory response, at this stage, might already transit to an inflammation-resolving process. Otherwise, these inflammatory mediators may continue to promote amplification of the inflammatory response, including increased vascular permeability, via recruitment of further PRR-expressing mobile cells such as PMNs, monocytes, M1-like macrophages, platelets, and DCs to the lung. Arrived in the lung, the mobile immune cells, in turn, get activated to produce a second wave of cytokines and chemokines as well as cytotoxic mediators such as ROS and proteolytic enzymes (proteases) and granular enzymes (Fig. 5.2). Additionally, recruited dying neutrophils produce NETs as additional DAMPs sources. These products at the efferent arm of the innate immune response mediate vascular endothelial and alveolar epithelial cell damage that leads to disruption of the alveolar endothelial and epithelial barriers (for in-depth articles, see [110, 114, 178, 180, 195, 198–201]). Nearly in parallel, that is, in response to the first wave of cytokines, pulmonary MAMP/DAMP-activated PRR-bearing DCs migrate to regional lymph nodes to mount virus-specific adaptive T and B cell responses [202, 203]. (This topic is not further covered here.)
5.4.5.3 Resolution of Lung Inflammation In those patients with mild or moderate ARDS who do not proceed to or survive the severe course of ARDS, a resolution of inflammation can be observed, characterized by fluid clearance and solute reabsorption from the alveolus [204, 205]. SAMPs such as AnxA1 [206] and SPMs [207] have already been reported to be involved in these processes. Several mechanisms central to controlling the resolution of lung inflammation have been discussed, including enhanced efferocytosis of apoptotic neutrophils/eosinophils performed by anti-inflammatory and/or proresolving macrophages. In particular, a shift from M1-like to M2-like macrophages appears to be the principal mechanism involved in this resolution of the inflammation stage [200] (Fig. 5.2). The M2-like macrophages promote alveolar epithelial cell transition and fibrosis formation mainly by the release of transforming TGF-β and IL-10 [204, 208, 209]. In respiratory viral infections, the process of SAMPdriven resolution of lung inflammation has also been already documented. For example, as mentioned above, the lipid mediator PD1 was shown to inhibit influenza virus replication and improve severe influenza [89]. Similarly, as also mentioned earlier, PGE2 and RvE3 were found to have a protective effect on COVID-19, as revealed by their decrease in the progression from moderate to severe disease [165]. In most patients suffering from respiratory virus-induced mild/moderate pneumonia, the combined MAMP/DAMP/SAMP-driven innate/adaptive immune response, as only briefly outlined here, will result in successful clearance of viruses from the lung, associated with complete resolution of pulmonary inflammation. However, respiratory virus infection can progress to severe disease, a feared outcome that has recently been extensively reported with respect to COVID-19.
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5.4.5.4 Hallmarks of Dysregulated Innate Immune Responses in ARDS Hyperinflammation: The “Cytokine Storm” Patients who develop a severe life-threatening, sometimes a deadly clinical picture of ARDS reportedly have markedly elevated levels of circulating proinflammatory cytokines and chemokines, significantly correlating to disease severity and mortality [180]. This “cytokine storm” phenomenon, reflecting increased promotion but the impaired resolution of inflammation, has also been described as a key feature in patients with influenza [210] and, recently, COVID-19 (the inflammatory mediators including types I and III IFNs, TNF, IL-1β, IL-6, IL-12, IL-18, IL-33, TGF-β, CCL2, CCL3, CCL5, CXCL8, CXCL9, and CXCL10) [117, 211–213]; also cf. Fig. 2.5). Counterbalancing Inflammation-Hyperresolution → Immunosuppression Moreover, the dysregulated hyperinflammatory/immune response in COVID-19 patients has been observed to be associated with a state of delayed immunosuppression (a phenomenon that, as mentioned above, is particularly seen in polytrauma patients). Typically, this syndrome is indicated by pronounced lymphopenia [214] and reduced monocytic human leukocyte antigen (HLA)-DR expression [215]. Notably, a substantial reduction in peripheral lymphocyte counts was reportedly identified as a high-risk factor for secondary bacterial infection [216] and, in another study, found to correlate with the severity of COVID-19 [217]. Given these early observations, it is tantalizing to speculate that the DAMP-promoted hyperinflammatory response—as reflected by the cytokine storm—may transit into a SAMP-driven counterbalancing hyperresolution response prone to increased susceptibility of secondary bacterial infection/sepsis (cf. Fig. 2.5). Immunothrombosis → Disseminated Intravascular Coagulation Another pathogenetic hallmark of severe ARDS refers to the complex process of immunothrombosis that has already been briefly introduced above in Sect. 5.2.3.3. The event, feared by intensivists, is known to lead to thromboembolic complications during the course of ARDS as, for example, observed in SARS-CoV, MERS CoV, and, recently, COVID-19 patients [218–220]. The process is orchestrated by the action of activated platelets, PMNs, ECs, NETs, microparticles, and coagulation proteases [221]. Notably, DAMPs may also be involved in this complication. Thus, as mentioned, DAMPs were shown to trigger such an intravascular thrombus formation, possibly by inducing TF expression on monocytes, elevating TF procoagulant activity, and promoting platelet aggregation. In fact, as recently reported [222], neutrophils of COVID-19 patients were found to yield high TF expression and released NETs carrying active TF. As also mentioned earlier, this immunothrombotic process can evolve into DIC that can contribute to—or even cause— a fatal outcome, a scenario that has been proposed to be due to the systemic spreading of MAMPs and DAMPs (for more details of immunothrombosis in sepsis, see below, Sect. 5.5.5.2).
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5.4.5.5 Systemic and Remote Organ-Specific Inflammation A distinctive feature of SARS-CoV-2 is that it spreads from the respiratory tract and invades and damages various distant organs, including the kidney, liver, gastrointestinal tract, and nervous system. The underlying mechanistic pathways leading to such extrapulmonary clinical manifestations are still elusive. As a causative process, the cytokine storm has been and still is often discussed, but another concept has recently gained center stage: the infection of human cells by SARS-CoV-2 via binding of the “spike” glycoprotein to ACE2 (see Sect. 2.7.5.6 and Fig. 2.13). This receptor is widely distributed and expressed across multiple organs, including the gastrointestinal system, bone marrow, brain, liver, heart, and kidney [223]. According to this concept and from the perspective of this article, the dissemination of COVID-19 to cause extrapulmonary pathologies may be discussed by sketching three possible mechanistic pathways: 1. Systemic spreading of SARS-CoV-2 with ACE2-mediated entry into cells of remote organs to activate PRR-bearing cells and promote MAMP-triggered (infectious) proinflammatory responses; 2. Systemic spreading of intrapulmonary emitted DAMPs with entry into remote organs to activate PRR-bearing cells and promote DAMP-triggered (“sterile”) proinflammatory responses; 3. Systemic spreading of SARS-CoV-2 with entry into remote organs to induce cytotoxic effects associated with the emission of DAMPs. This process would activate PRR-bearing cells and promote MAMP/DAMP-triggered proinflammatory responses. Theoretically, all three pathways might work together context-dependently. Given the topic of this review, and in view of poor evidence for intracellular SARSCoV-2 demonstration in non-lung organs (except for organoids), the second pathway, that is, DAMP-triggered inflammatory responses are of major interest here. In fact, there is accumulating evidence for the action of DAMPs to trigger an exaggerated systemic and remote organ-specific inflammatory response, contributing to organ injury [224–227]. These data are in support of the concept that, in COVID-19, DAMPs are involved in the promotion of remote organ-specific inflammation.
5.4.6 The Cytokine Storm as a DAMP-Driven Dysregulated Hyperinflammatory Response There is an increasing number of researchers discussing the concept that the cytokine storm in ARDS is consistent with a dysregulated exaggerated hyperinflammatory response executed by DAMP-activated mobile and sessile PRR-bearing cells of the innate immune system [109, 110, 114, 161, 170, 177, 186, 207, 212, 228–230]. Intriguingly, the first clues in support of this concept were recently provided by studies in COVID-19 patients showing that serum levels of the DAMPs S100A8/ A9, HMGB1, and mtDNA are correlated with both the concentrations of a spectrum
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of proinflammatory cytokines [156] and the severity of clinical manifestations [156, 157]. Considering these first clues on the role of DAMPs in respiratory virus-induced ARDS, it is still unclear what factors influence/determine the progression from regulated protective inflammatory defense response to pathogenic hyperinflammatory destructive response. Among currently discussed theories, here, the concept of a positive feed-forward loop of RCD → DAMPs → RCD → DAMPs → RCD → DA MPs, leading to an “avalanche of DAMPs” is proposed—as already discussed by us in the context of SIRS (see Vol. 1 [1], Chap. 20, and Fig. 20.1, pp. 467–469). According to such a conceptual model, the sequelae of processes can be sketched as follows: Initial viral injury-induced RN such as necroptosis and pyroptosis results in the release of the first line of constitutive DAMPs including HMGB1, eATP, and NAs, which can lead directly [231, 232] or indirectly—via inducible DAMPs such as TNF and type I IFN secreted by innate immune cells activated by them [233, 234]—to further pyroptotic and necroptotic cell death. A vicious circle may develop [235] (Fig. 5.3). Emerging evidence in support of this model is provided by a recent study by Karki et al. [236] on multiple inflammatory cytokines produced by innate immune cells during SARS-CoV-2 infection showing that the combined production of TNF-α and IFN-γ specifically induces PANoptosis. This data let the authors conclude that TNF-α and IFN-γ play a prominent role in damaging vital organs by inducing inflammatory cell death. In other words, one may argue that these two cytokines of the cytokine storm operating as inducible DAMPs are key players in the RCD-related production of large amounts of DAMPs that ultimately may lead to severe and fatal outcomes of COVID-19. It is tempting to extend this concept with the hypothetical model of a DAMPdriven positive feed-forward loop triggered by the adaptive immune response as proposed in Sect. 1.4.5: IC (viral antigen/antiviral antibody)-promoted formation of NETs and NETosis as a prolific source of DAMPs that join the loop. As described in Sect. 3.7.7.4 NETs have been detected in COVID-19 [237].
5.4.7 Pathogenetic Role of Nonviral-Induced DAMPs in Respiratory Virus Infection: A Theory As known from the literature, several factors and conditions have been observed as contributing to severe and life-threatening courses of respiratory virus infections, including coronavirus infections (SARS-CoV, MERS-CoV, and SARS-CoV-2). Such factors contributing to life-threatening courses of respiratory virus infections include high age [238–240], environmental impacts [241–243], and co-morbidities such as diabetes [244, 245] and CVDs [246]. On the other hand, these conditions have been described to be associated—more or less—with endogenous and exogenous DAMPs, respectively. For example, DAMPs have been proposed to contribute to aging via the promotion of sterile inflammation (“inflammaging”) [247–250]. In atherosclerosis associated with CVDs, the OSEs have been shown to operate as powerful DAMPs, which trigger innate/adaptive immune responses, initiating and
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Fig. 5.3 Simplified schematic diagram of a conceptual “positive feed-forward loop” model of DAMP-induced cytokine storm in respiratory viral infection. Virus-induced RN (necroptosis and pyroptosis) leads to release of constitutive DAMPs such as HMGB1 and DNA that activate PRRbearing alveolar macrophages, which in turn secrete cytokines such as TNF and type I IFNs. These cytokines operate as inducible DAMPs to induce necroptosis. The release of constitutive DAMPs such as HMGB1 and eATP induces pyroptosis, which again is associated with the release of the constitutive DAMPs and IL-1β. The constitutive DAMPs such as HMGB1 and DNA activate recruited PRR-bearing neutrophils, which contribute to further cytokine production such as TNF and type I IFNs. The sequelae of processes are repeated in terms of a positive feed-forward loop and might proceed to a vicious circle. Note: the oversimplified figure shows only one example out of various possible scenarios regarding the release of DAMPs, expression of pattern recognition receptors, secretion of cytokines (iDAMPs), type of cells involved, and sequelae of processes. Also note: injured alveolar epithelial type I cells are representative of other injured cells such as alveolar epithelial type II cells and ECs. In particular, the target role of the endothelium is not shown. AECI alveolar epithelial type I cells, cDAMPs constitutive DAMPs, eATP extracellular ATP, HMGB1 high mobility group box 1, iDAMPs inducible DAMPs, IFN interferon, IFNAR type I interferon receptor, IL interleukin, MØ macrophage, P2XR7 purinergic receptor P2X7, RN regulated necrosis, TLR Toll-like receptor, TNF tumor necrosis factor, TNFR1 tumor necrosis factor receptor 1, vc vicious circle (Sources: The figure has already been published in, Genes & Immunity 2021 [235], further Refs. [193, 195, 197])
propagating chronic nonresolving vessel wall inflammation [251–253] (for OSEs in atherosclerosis, compare Vol. 2 [2], Sect. 10.4.2.3, and Fig. 10.3, pp. 457–458). Another interesting risk factor refers to damaging environmental impacts, which are selected here as an example for a closer look at this topic. Accordingly, a theory is presented here which holds that it is the superimposition of coronavirus-induced DAMPs with non-virus-induced DAMPs of any origin that at least contributes to severe and fatal courses of coronavirus pneumonia (Fig. 5.4). Notably, as recently reviewed [254], the major contributing factor (besides human behavior) to respiratory virus outbreaks is the changes in environmental parameters. On the other hand, however, thermal stress/injury, either cold or heat,
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Respiratory Virus Infections (incl. SARS Coronavirus Infections)
Nonviral risk factors (high age, environmental impacts, cardiovascular diseases, others)
MAMPs/DAMPs/SAMPs
DAMPs
Activation of PRR-bearing mobile and sessile cells of the innate immune system
Activation of PRR-bearing mobile and sessile cells of the innate immune system superimposition
Controlled inflammation-promoting Æ inflammation-resolving responses
Uncontrolled hyperinflammatory / procoagulative responses Contribution
Mild pneumonia prompt healing
Fatalities (SIRS, DIC, MODS)
Fig. 5.4 Proposal of a theory. The superimposition of respiratory virus-induced DAMPs with non-virus-induced DAMPs derived from conditions known to be associated with the emission of DAMPs (e.g., high age and air pollution) contributes—via the promotion of hyperinflammatory pathways—to severe and fatal courses of pneumonia, as observed in COVID-19 (Source: The figure has already been published in Genes & Immunity 2021 [235])
has been experimentally shown to be associated with the emission of endogenous DAMPs [255, 256]. Likewise, other environmental factors may operate directly as exogenous DAMPs in respiratory tract inflammation, such as inhaled airborne PM/ pathogenic pollutants (classified as exogenous IVE-1/2 DAMPs, see Table 1.3). Some molecules of this DAMP class were shown to trigger activation of the NLRP3 inflammasome associated with inflammasome-dependent proinflammatory processes as well as, even more important, regulated necrosis in the form of pyroptosis as a critical source of subsequent endogenous DAMPs emission [257–260]. In this context of special importance are two earlier studies, which had already demonstrated a positive association between pollutants and SARS case fatality in Chinese populations [241, 242]. With this background, Qu et al. [261] recently argued: The high levels of PM pollution in China may increase the susceptibility of the population to more serious symptoms and respiratory complications of the disease. … The simultaneous inhalation of chemical pollutants in PM alongside COVID-19 virus may also exacerbate the level of COVID-19 infection. Pro-inflammation, injury, and fibrosis from inhaled PM combined with an immune response or cytokine storm induced by COVID-19 infection could enhance the infection severity. Recent studies confirm these observations: A Harvard University environmental research study could demonstrate that a small increase in long-term exposure to fine PM (PM2.5) results in a large increase in COVID-19 death rate, with the magnitude of increase 20 times that observed for PM2.5 and all-cause mortality [262]. In accordance with these reports is a more recent multicenter, time-series study performed in 235
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Chinese cities demonstrating a statistically significant association between ambient air pollution (pollutants: NO2, PM2.5, PM10) and the spread of COVID-19 [263]. Finally, it appears worth discussing, in light of this topic, the mechanical ventilation of critically ill ARDS patients in the ICU. Indeed, in studies on preclinical ARDS models and ARDS patients, the release of DAMPs during mechanical ventilation, such as HMGB1, eATP, hyaluronan, and S100 proteins, has been clearly demonstrated. For example, in investigations on BALF of trauma patients during mechanical ventilation and ventilator-associated pneumonia, long-term mechanical ventilation was shown to be associated with increased HMGB1 levels [264]. In a subsequent study on patients with severe pneumonia and ARDS requiring mechanical ventilation, the investigators remarkably observed the day 1 HMGB1 concentration to be a critical, independent biomarker for ICU mortality [167] (for reviews, see [265, 266]; for further details on DAMPs emission during mechanical ventilation, see Vol. 2 [2], Sect. 9.3.5, pp. 351–357). With respect to optimal treatment of ARDS patients in the ICU, these data should be brought into the discussion on a maximum possible continuation of standard intensive care treatment (eventually together with nasal high-flow, noninvasive ventilation), aimed at delaying or even preventing the need for invasive mechanical ventilation with intubation. It is about weighing the risk of increasing the DAMP-induced hyperinflammatory, potentially fatal process with the use of invasive mechanical ventilation against the risk of dying from the consequences of hypoxemia/hypoxia due to insufficient noninvasive nasal ventilation. Clearly, future, more targeted studies on the emerging pathogenetic role of nonviral-induced DAMPs in respiratory virus infection may help clarify this proposal.
5.4.8 DAMPs and SAMPs as Diagnostics and Prognostics in Respiratory Virus Infection 5.4.8.1 General Remarks The measurement of biomarkers in respiratory virus infections is of utmost importance with respect to early diagnosis of potential complications. For example, severe COVID-19 often develops cardiac, liver, and kidney failure; hence biomarkers serve as helpful warning signals in one such instance. In addition, this methodology may be helpful in differentiating viral versus bacterial pneumonia etiology [267]. There has been an encouraging development in the exploitation of DAMPs and SAMPs as biomarkers in viral infections, culminating in their recent use in COVID-19 patients. In fact, recent reports indicate that these unique molecules will slowly but inevitably take center stage in modern diagnostic strategies for those diseases. 5.4.8.2 DAMPs As described in Vol. 2 [2], Sect. 9.9.2.3, pp. 396/397, in a study on patients with severe pneumonia and ARDS requiring mechanical ventilation, the investigators remarkably observed day 1 HMGB1 concentration to be a critical, independent biomarker for ICU mortality. As was to be expected, HMGB1 has once again
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come out on top regarding its role as a biomarker in respiratory viral diseases. Interestingly, some of those publications described above in Sect. 5.3.2 already stressed the possibility of using HMGB1 in the future as an essential biomarker in diagnosis and prognosis of infectious diseases. These early proposals soon found their way into research on respiratory viral diseases. For example, in a recent study on COVID-19 patients reported by Chen et al. [268], the average serum HMGB1 level in the severe patient group was found to be significantly higher than that observed in the non-severe group. The authors concluded that these findings indicate that serum HMGB1 in COVID-19 patients positively correlated with disease severity. Also, as mentioned above, the heterodimer S100A8/A9 has been identified as a valuable biomarker in respiratory virus diseases since its serum levels, like HMGB1 serum levels, were found to be strongly correlated with the severity of clinical manifestations in COVID-19 patients and with significant predictive power for the risk of ICU admission and death [70, 71, 155, 156]. Moreover, mtDNA has revealed itself to be a strong biomarker in respiratory diseases. As described in Vol. 2 [2], Sect. 9.9.2.3, p. 397, in a clinical study on patients with suspected ventilator-associated pneumonia, higher levels of mtDNA were detected in the BALF. Thus, it did not take long for this DAMP to be measured in COVID-19 patients. Accordingly, high circulating mitochondrial DNA levels have recently been detected in these patients and found to be a potential early indicator of poor outcomes [157].
5.4.8.3 SAMPs As already touched on above, in the first study on SAMPs in COVID-19, PGE2 and RvE3 could be measured in the patients’ serum and were found to be decreased in severe cases [165]. Moreover, in a recent case-control study of COVID-19 patients reported by Canacik et al. [160], AnxA1 serum levels were shown to be significantly lower in the severe/critical disease group compared with the control and moderate disease groups [160]. Given their observations, the authors concluded: AnxA1 levels may be a beneficial biomarker in the diagnosis of COVID-19 pneumonia and in predicting the need for ICU treatment in patients with COVID-19 pneumonia at the time of admission to the emergency department. 5.4.8.4 Concluding Remarks Doubtlessly, the detection of DAMPs and SAMPs offers considerable opportunities for personalized medicine applied to emerging diseases such as COVID-19. Indeed, the measurement of these molecules—even better, a certain “COVID-19typical” DAMPs/SAMPs pattern—would allow a more accurate diagnosis of patients with low viral load and provide novel opportunities for prognosis of the severity of the disease, and—consequently—encourage new treatment options. In this sense, detection and measurement of DAMPs and SAMPs represent the initial step to achieving precision medicine for the management of COVID-19 patients.
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5.4.9 DAMPs and SAMPs as Therapeutic Targets or Therapeutics in Respiratory Virus Infection One of the most important lessons learned during the current COVID-19 pandemic is that no effective drugs are available to efficiently treat or even cure the severe/ life-threatening complications of respiratory viral diseases, such as ARDS [269] and sepsis [270]. Thus, the therapeutic aim is clear: to inhibit these DAMP-promoted hyperinflammatory complications resulting in MOF, as well as to prevent the development of the SAMP-driven immunosuppressive phase associated with increased susceptibility to infections. In view of the actuality of the pandemic, we will focus here on these complications as seen in COVID-19. As was to be expected, HMGB1 as a potential target for considering the treatment of COVID-19 has once again come out on top (see, e.g., [271–274]). In a recent study on patients with confirmed COVID-19, reported by Chen et al. [268], genetic (using advanced glycosylation end-product specific receptor [AGER] siRNA) or pharmacological (using glycyrrhizin, chloroquine, and hydroxychloroquine) inhibition of the HMGB1-AGER pathway has been shown to block ACE2 expression. The findings led the researchers to suggest that HMGB1 inhibitors are promising drug candidates for the treatment of patients suffering from COVID-19. Other DAMPs, such as S100A8/A9 proteins, have also recently been discussed as potential therapeutic targets in COVID-19 [275]. Thus, reports on appropriate studies are to be expected in the near future. The administration of SAMPs to promote the resolution of inflammation in COVID-19 is another treatment option. With this indication, the SPMs have gained increasing attention [276]. Appropriate control studies using these SPMs have not been published so far; however, at least metabolic precursors of these SAMPs, the omega-3 long-chain polyunsaturated fatty acids (omega-3 LC-PUFAs), are being discussed to be able to improve the resolution of the inflammatory balance, limiting, therefore, the level and duration of the critical inflammatory period of COVID-19 [277]. Overall, reports on studies on DAMPs and SAMPs as potential therapeutic targets in COVID-19 are still meager; however, they are obviously already being discussed heavily.
5.4.10 Résumé and Future Perspectives Twenty years after their first description [278], the DAMPS have been recognized not only to mount effective defense responses against infections but also to jeopardize the infected host itself by inducing dysregulated exaggerated life-threatening hyperinflammatory responses. Indeed, in analogy to their reported action in bacterial sepsis ([21, 279], also see next section), these molecules are now suggested to play a critical pathogenetic role in the development of severe/fateful processes as observed in respiratory viral infections including COVID-19. Future emphasis should be focused on exploring the key DAMPs involved, as well as their
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interaction with viral MAMPs. Specification and quantification of DAMPs, for example, in COVID-19 patients, will serve as valuable diagnostic and prognostic biomarkers to monitor and evaluate the course of the viral disorder, in particular, to grasp the eventual transition precociously from a controlled defense response as observed in mild/moderate cases to a dysregulated life-threatening hyperinflammatory response as seen in severe/fatal cases. Such a diagnostic stratification strategy then would pave the path to new therapeutic opportunities aimed at preventing progression to severe diseases and potentially reducing mortality, such as seen in severe COVID-19 pneumonia.
5.5 Pathogenetic Impact of MAMPs and DAMPs on Bacterial Diseases: The Example of Sepsis 5.5.1 Introductory Remarks 5.5.1.1 General Remarks Some introductory remarks on sepsis have already been briefly made above in Sect. 5.2.3: this life-threatening disease is characterized by an initial hyperinflammatory state promoted by the emission of DAMPs in excess, followed, nearly in parallel, by the development of an inflammation hyperresolution-immunosuppression state driven by the overproduction of SAMPs. Sepsis is the leading cause of mortality and critical illness in the world, especially in low- and middle-income countries. The estimated worldwide incidence of sepsis admissions is reportedly 31.5 million cases per year, leading to 5.3 million deaths [280]. Another study on sepsis incidence and mortality across 195 countries and territories for the years 1990–2017 showed that there were even an estimated 48.9 million incident cases of sepsis and 11.0 million sepsis-related deaths in 2017 [281]. The study further revealed that sepsis incidence and mortality varied substantially across regions, with the highest burden in sub-Saharan Africa, Oceania, South Asia, East Asia, and Southeast Asia. Hence, the cost of treatment for sepsis is considered the highest among all disease treatments, as, for example, shown by a retrospective observational study conducted in the USA [282]. Clearly, these data demonstrate that research into new, promising developments in modern immunology-oriented infectiology, including work on the pathogenetic role of DAMPs, is absolutely necessary to effectively curb the incidence of this disorder. 5.5.1.2 History of Classification/Definition of Sepsis: A Few Remarks The term “sepsis” dates back over 2700 years ago when it was first articulated, with respect to a medical context, in the ancient Greek poems of Homer. The word itself means “decomposition of animal, or vegetable or organic matter in the presence of bacteria” [283]. In the medical context, the term “sepsis” derives directly from the Greek word “sepo,” which means “I rotted” or “to make rotten.” In later centuries, the term is found in the writings of Hippocrates (circa 400 bc) in his Corpus Hippocraticum as well as the work of Galen. In the nineteenth century, it was Lister
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(England), Semmelweiss (Hungary), Pasteur (France), and Koch (Germany) who contributed seminal advancements in the origin of sepsis (reviewed in [284]). The beginning of modern definitions of sepsis can be dated back three decades when continuous elucidation and expansion of knowledge about the complex pathophysiologic response involved in sepsis had culminated in the creation of the term SIRS (reviewed in [285–288]). Indeed, the SIRS concept derives from a 1991 consensus conference in Chicago charged with the task of developing an easy-to-apply set of clinical parameters to aid in the early identification of potential candidates for entrance into clinical trials aimed at evaluating new treatments for sepsis. In this conference, broad definitions of sepsis and SIRS were proposed, along with detailed physiologic parameters by which a patient may be categorized. The combination of SIRS with a confirmed infectious process was then denoted sepsis [289, 290]. For years, it was believed that high morbidity and mortality were due to SIRS, but disappointingly, many clinical trials to inhibit inflammation failed to improve survival. In 2016, then, at the third International Consensus Definitions for Sepsis, sepsis was redefined and named Sepsis-3, and now described as “life-threatening organ dysfunction caused by a dysregulated host response to infection” [22]. Notably, the new definition proposed at this meeting skipped the routine use of the term “SIRS” in the identification of sepsis (although the task force wished to stress that SIRS criteria may still remain useful for the identification of infection [22]). Instead, the authors recommended the use of Sequential Organ Failure Assessment (SOFA) scoring to assess the severity of organ dysfunction and failure in a potentially septic patient [291]. (Due to its complexity, however, it is sometimes reduced to the so-called “quick (q)SOFA” score.) Organ dysfunction is now defined by an increase in the SOFA score of 2 points or more, which reflects an overall mortality risk of approximately 10% in a general hospital population with suspected infection. In addition, septic shock is now defined as a subset of sepsis in which underlying circulatory and cellular/metabolic abnormalities are profound enough to substantially increase mortality. Patients with septic shock can be identified with presenting hypotension requiring vasopressors to maintain a mean arterial pressure of 65 mmHg or greater and having a serum lactate level greater than 2 mmol/L (18 mg/dL) despite adequate volume resuscitation. With these criteria, in-hospital mortality is in excess of 40% [22]. Nevertheless, these new scores have some limitations as well. For example, as reported from a retrospective cohort analysis of patients with suspected infection admitted to an ICU, an increase in SOFA score of 2 or more had greater prognostic accuracy for in-hospital mortality than SIRS criteria or the qSOFA score [292]. According to the authors’ conclusion, these findings suggest that SIRS criteria and qSOFA may have limited utility for predicting mortality in an ICU setting.
5.5.1.3 Clinical Picture of Sepsis at a Glance As every physician is aware, sepsis encompasses a spectrum of illnesses ranging from mild signs and symptoms to organ dysfunction and shock [293]. Originally defined as a SIRS to a source of infection consisting of symptoms such as tachypnoea, tachycardia, pyrexia or hypothermia, and leukocytosis, leukopenia, or
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neutrophilia [294], sepsis is now defined as an infection associated with organ injury distant from the site of infection. Septic shock remains defined as a subset of sepsis in which the risk of mortality is substantially increased, and is characterized by hypotension that persists during volume resuscitation and requires the use of vasopressors (quoted from [295]). In addition to this classical acute clinical picture of sepsis, the disease reportedly presents with chronic clinical manifestations in the form of chronic critical illness, manifested by long-lasting immunosuppression associated with persistent, low-grade inflammation and catabolism syndrome [296]. Of particular importance is the post-sepsis immunosuppressive phase, associated with a high susceptibility to secondary nosocomial infections, typically caused by opportunistic pathogens [297].
5.5.2 Experimental Sepsis Models Given the complex pathophysiology of clinical sepsis, which is associated with many unresolved problems, the development of experimental sepsis models over the past nine decades is not a surprise. Guided by the review of Mai et al. [298], some aspects are briefly addressed here. The gold standard model of infectious disease is the cecal ligation and puncture (CLP) model, mostly used in rats and mice. This experimental setting models polymicrobial sepsis that appears to mimic events occurring in septic humans satisfactorily (which is what I, as a surgeon, was frequently confronted with during surgery for acute perforated appendicitis). Originally described in 1980 [299], the technique involves initial ligation of the cecum distal to the ileocecal valve, once or twice punctures from the mesenteric to the antimesenteric direction (by controlling the intensity of sepsis via the numbers of punctures and the size of the needle), and aspiration for trapped gasses. This is followed by the extrusion of small amounts of fecal content into the peritoneal cavity. Notably, this model induces polymicrobial infection, defined as the presence of both aerobic and anaerobic bacteria in the peritoneal cavity and in blood, leading to a 70% mortality rate in septic animals. Recently, however, there has been criticism that the model does not adequately reflect the relevance of human disease; and proposals have been made to repurpose the model to better inform therapy in human sepsis [300]. Another polymicrobial peritonitis sepsis model refers to the colon ascendens stent peritonitis (CASP) [301]. This setting is characterized by the maneuver of inserting a stent into the ascending colon, which generates a septic focus by providing an open link between the gut lumen and the abdominal cavity. By using stents of different diameters ranging from 14G to 22G, the intensity of the pathophysiology of abdominal sepsis (e.g., the incidence of mortality) can be exactly controlled. The use of CASP is supposed to increase in prevalence along with further elucidation of mechanisms governing the complex pathogenesis of the disease. In particular, CASP models with the use of small stent sizes are reportedly suitable for long-term studies and studies with mild/moderate sepsis severity [302].
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Sepsis models in larger animals have been developed in rabbits, dogs, pigs, sheep, and non-human primates [298]. In general, models of endotoxemia and bacteremia via continuous infusion of endotoxin or live bacteria have been used to induce sepsis, that is, to study extensively systemic and/or organ dysfunction during sepsis, as well as to explore therapeutic agents for improving dysfunction. For example, in recent studies on a piglet model of LPS-induced sepsis, it was shown that necroptosis (associated with the demonstration of HMGB1) occurs in the liver during sepsis and contributes to septic hepatic injury [303]. Certainly, there are limitations to the use of these animals. Due to their large size, they are also more difficult to handle, house, and anesthetize and, in the case of primates, pose risks of cross-transmissible diseases [298]. Nevertheless, it is anticipated that research on these models will contribute to future advances in understanding the pathogenetic role of DAMPs and SAMPs in patients suffering from sepsis.
5.5.3 Demonstration of DAMPs 5.5.3.1 General Remarks The role of MAMPs by themselves as well as the interplay between MAMPs, constitutive DAMPs, and inducible DAMPs in infections, has been described and discussed earlier in Sect. 4.7.2. In particular, the general consensus of the research community on the role of DAMPs in amplifying, aggravating, and exacerbating inflammatory/immune responses to defend against pathogens has been highlighted. Therefore, we will focus here on reports of the detection of DAMPs in bacterial sepsis, neglecting the role of MAMPs. Theoretically, as with “sterile SIRS” observed in polytrauma, all subclasses of constitutive and inducible DAMPs may be induced by pathogen-induced cell stress/tissue injury. But it is the IA-1 and IA-2 DAMPs released from necrotic cells undergoing RCD, as well as inducible DAMPs actively secreted/released from stressed or dying cells, which can be regarded as the critical danger signals in sepsis/“infectious SIRS” (for the definition of the various subclasses, nature, and function of DAMPs and SAMPs, see Tables 1.1, 1.2, and 1.3; Vol. 1 [1], Chaps. 12–14. pp. 219–369; and Vol. 2 [2], Chap. 3, pp. 66–102). In principle, in sepsis patients, RCD is primarily induced by pathogens but can also be triggered by tissue hypoperfusion in case of septic shock. Furthermore, the cytokine storm itself elicited via inducible DAMPs such as TNF, type I IFN, and IL-1β results in further RCD in terms of a vicious circle. Hence, sources of DAMPs in sepsis are well established with an increasing demonstration of various subroutines of RCD as observed in experimental septic models and sepsis patients, including pyroptosis [35, 304–307], necroptosis [303, 306, 308, 309], ferroptosis [310, 311], and parthanatos [312] (compare Sect. 3.7). The detection of the stress/injury-induced danger signals has been shown experimentally in studies using the above-mentioned sepsis model in mice, the CLP model [300], but also increasingly in sepsis patients in the ICU [313].
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5.5.3.2 High Mobility Group Box 1, Heat Shock Proteins, and S100 Proteins As could be expected, the well-known “classical” DAMPs, such as HMGB1 and S100 proteins, but fewer HSPs, have been measured in critically ill patients as well as in experimental sepsis models. Indeed, their current and future use as diagnostic/ prognostic markers and therapeutic targets represents an attractive goal of sepsis research. In the following, a brief overview of observational human studies and animal intervention studies relevant to intensive care-related conditions is neatly provided, without claiming to be complete. High Mobility Group Box 1 Remarkably, already in 1999, HMGB1 levels were already described to be increased in the serum of septic patients succumbing to infection [314]. Today, HMGB1— sensed by TLR4 and RAGE as its dominant receptors—is one of the best-studied DAMPs in the pathogenesis of sepsis. Indeed, numerous studies on experimental lethal sepsis models have convincingly demonstrated that HMGB1 is pathogenically involved in fatal pathways defined in these models (e.g., published in [314– 317]). Clinically, the pathogenetic role of HMGB1 is also well documented in sepsis patients. Thus, it has been reported that circulating HMGB1 levels are consistently elevated and, importantly, that the concentration of circulating HMGB1 correlates positively with the severity and mortality attributed to the septic disease [309, 318– 320]. Of note, these observations on a correlation of HMGB1 with mortality of sepsis patients were recently confirmed and extended by two meta-analyses [321, 322] (see also below Sect. 5.5.7.2 on biomarkers). Heat Shock Proteins Heat shock proteins using their surface receptors TLR4 and TLR2 have a role in the pathophysiology of sepsis as well. However, while studies on the cytoprotective function of intracellularly generated HSPs in sepsis are frequently reported, there is obviously only one clinical study published on HSPs detected in the extracellular space. And it is the extracellular HSPs that are involved in triggering inflammatory responses and are therefore of interest here. In this particular study on sepsis patients, HSP70 levels were shown to be elevated compared to controls [323]. Detailed analysis of data from this study according to survival outcome also indicated that patients with increased HSP70 serum levels presented increased mortality. S100A Proteins The S100 proteins S100A8/A9 interacting both with TLR4 and RAGE are reportedly also implicated in the pathogenesis of sepsis and, interestingly, in sepsis-associated neuroinflammation. In earlier studies, the role of these DAMPs in sepsis was documented in S100A8/A9-deficient mice that showed a reduced systemic inflammatory response after endotoxin administration [324]. In more recent clinical investigations, S100A8/A9 proteins were found to be increased in the brains of patients who died of sepsis, and S100A8 was expressed in astrocytes and myeloid cells, indicating neuroinflammation [325]. In further studies on a mouse model of sepsis
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survival in mice, the investigators could demonstrate that the expression of S100A8/ A9 in the brain after sepsis is needed for the recruitment of neutrophils to the brain and for priming production of ROS and TNF secretion in microglia and macrophages. In another clinical study on S100A8/A9 in patients with bacterial sepsis, the two DAMPs were found to be significantly higher than those measured in patients with viral infections and healthy controls [326]. Moreover, in this analysis, the level of S100A8/A9 was demonstrated to be the best predictor of bacterial sepsis compared to other routine biomarkers, such as the neutrophil-lymphocyte count ratio and procalcitonin. Indeed, not least because of the observed increase in their mRNA expression in septic shock [327, 328], this subclass of DAMPs has been intensively investigated for its use as reliable diagnostic and prognostic biomarkers to improve the prediction of death in patients with septic shock [329–331]. For example, high plasma levels of S100A8/ S100A9 and S100A12 at admission were observed to indicate such a higher risk of death [330]. Given this observation, the authors concluded that these markers could indicate a higher risk of death when SOFA scores are similar and help the stratification of patients for improved care and therapy selection.
5.5.3.3 Mitochondria-Derived DAMPs Mitochondria-derived DAMPs have always attracted the interest of DAMPs researchers, in particular, researchers of the Hauser group at Harvard University [332], because all mitochondria derive from endosymbiotic bacteria, more precisely, from a common ancestral organelle that originated from the integration of an endosymbiotic alphaproteobacterium into a host cell related to Asgard Archaea [333]. This narrative insinuates that these DAMPs are, in reality, PAMPs derived from bacteria. In fact, several components of mitochondria have been reported to act as DAMPs, including mtDNA, mitochondrial N-formyl peptides (mtFPs), transfactor A, mitochondrial (TFAM), ATP, cardiolipin, cytochrome C, succinate, and mtRNA (for comprehensive reviews, see Itagaki et al. [332] and Li et al. [334]). In the following, some of these DAMPs will be addressed, which are believed to be emitted during sepsis/septic shock-induced tissue hypoperfusion. Mitochondrial DNA Mitochondrial DNA, which has been best investigated by mitochondria-derived DAMP so far, triggers the activation of multiple PRMs, including TLR9-, NLRP3-, and cGAS → STING-triggered pathways. This molecule has meanwhile been recognized as a strong DAMP that is pathogenetically involved in many diseases, in particular, life-threatening disorders. Already a decade ago, some clinical studies in sepsis patients provided the first evidence indicating that mtDNA (like nDNA) contributes to the hyperinflammatory response and is critical for the prognosis of the disease [335, 336]. Subsequent studies in sepsis patients shortly thereafter confirmed these observations and demonstrated that similar to HMGB1 levels, plasma levels of circulating mtDNA are significantly increased in severe sepsis/septic shock patients and correlate with mortality [337–340]. Interestingly, the recent study, in terms of a secondary analysis of data from a previous control study [340], revealed
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the NADH dehydrogenase 1 mtDNA as a potential biomarker for the discrimination of septic shock and postsurgical systemic inflammation. Moreover, the authors provided evince for an association between the levels of this mtDNA and a fibrinogendependent pro-coagulatory shift in cardiac surgical patients. Mitochondrial N-Formyl Peptides Mitochondrial N-formyl peptides, operating as IA-1 DAMPs, are recognized by formyl peptide receptors (FPRs), which—as described in Vol. 1 [1], Sect. 5.3.5.3, p. 80 and Sect. 12.2.4.6, p. 235—belong to the family of G protein-coupled receptors (GPCRs). In contrast to mtDNA, few reports have been published on the role of mtFPs in sepsis. In earlier studies, Wenceslau et al. [341] suggested a role of mtFPs in the promotion of inflammation and vascular dysfunction, contributing to the development of sepsis, by discussing a link between trauma, vascular collapse, and sepsis. In further studies on a rat model of hemorrhagic shock, the authors could demonstrate that mtFPs (N-formyl-Met-Met-Tyr-Ala-Leu-Phe) elicit a sepsis-like syndrome characterized by severe hypotension, hyperthermia, lung injury, microvascular thrombosis, and vascular leakage [342]. However, more recent studies by Kwon et al. [343] in patients with septic shock revealed that a relatively high plasma level of the most potent human mtFP (nicotinamide adenine dinucleotide dehydrogenase subunit-6) is independently associated with the development of secondary infection. The group observed that the increased susceptibility to secondary infection was partly attributed to the suppression of PMN chemotaxis by mtFP occupancy of FPR1 [343]. In other words, given the results from this study, this member of mtFPs obviously operates as a SAMP rather than a DAMP. Future studies will certainly clarify whether different members of the mtFPs group act differently in sepsis, that is, either as DAMPs or SAMPs.
5.5.3.4 Histones As briefly outlined in Vol. 1 [1], Sect. 12.2.4.4, pp. 233/234, histones and nucleosomes are critical nuclear proteins that contribute to the structural organization and stability of chromatin. As potent DAMPs involved in the pathogenesis of infections, they have already been briefly touched on above in Sect. 5.3.4.1. Since their description as critical mediators of death in sepsis in 2009 [344], extracellular histones have attracted more and more attention. In fact, in the setting of sepsis, many of the proinflammatory and thrombogenic/prothrombotic events affecting cells and organs can be attributed to these DAMPs. For example, and of note, the interaction of histones with TLR2 and TLR4 was shown to induce expression of the TF in vascular ECs, resulting in activation of the clotting system with thrombus formation [345, 346]. The impact of these DAMPs on sepsis has been impressively demonstrated by the administration of inhibiting agents. Indeed, as reviewed by Cheng et al. [347], anti-histone antibodies and non-anticoagulant heparin were shown to neutralize extracellular histones and improve survival in sepsis. Also, and of note, ex-vivo administration of serum from septic patients was found to directly induce histone-specific cardiomyocyte death, which was abrogated by anti-histone antibodies [348].
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5.5.3.5 DAMPs Derived from the Degraded Endothelial Glycocalyx in Sepsis Every cell in the human body exhibit a glycocalyx. “Glycocalyx” literarily translates to “sweet husk.” As explained by Möckl [349], “sweet” indicates its key building units—various sugars (or monosaccharides) like glucose, mannose, galactose, and many others. “Husk” points toward the location of these sugars—they reside extracellularly on the cell membrane, surrounding the cell like a cloak. In sepsis, the endothelial glycocalyx that plays a critical role in maintaining vascular homeostasis is of special importance. Thus, during the initial onset of sepsis, the glycocalyx is injured and degraded, and circulating levels of glycocalyx components, including proteoglycans (PGs), heparan sulfate (HS), and hyaluronan (HA), can be measured (for a review on the derangement of the endothelial glycocalyx in sepsis, see [350]). On the other hand, in DAMPs research, these components are defined as ECMderived class IIA DAMPs that signal through TLRs such as TLR4 and TLR2 (see Table 1.1 and Vol. 1 [1], Sect. 13.2, pp. 269–277). Although the mechanisms of degradation are not fully understood, the increased plasma and urine levels of these glycocalyx components have been proposed to using as diagnostic and prognostic biomarkers as well as therapeutic targets in sepsis [351]. Moreover, the role of these DAMPs in contributing to septic hyperinflammation is also not clear, and conflicting findings have been reported. While, on the one hand, HS fragments and HA were shown to trigger proinflammatory responses [352, 353], on the other hand, circulating HS has been reported to reduce inflammation during sepsis [354]. Together, given the emerging role of the glycocalyx as a central part of sepsis pathophysiology (dysfunction of the endothelial barrier, see below), further studies are needed to define and specify the pathogenetic role of this class of DAMPs in the course of the disease. 5.5.3.6 The Inducible DAMPs C3a and C5a (Anaphylatoxins) The complement system and its co-players in inflammation have been exhaustively covered in Vol. 1 [1], Sect. 23.2, pp. 591–615, and summed up in Sect. 4.4.3.4. In particular, and according to the tenor of this book, the role of anaphylatoxins C3a and C5a, denoted as inducible DAMPs, is highlighted in that section. To repeat: These small peptides originating from the three pathways of complement activation exert multiple and profound regulatory effects on innate immune responses, thereby shaping inflammatory reactions in response to both infectious and sterile triggering insults. Of note, C3a and C5a mediate their biological effector function, for instance, the promotion of inflammation at the site of complement activation through binding to and activation of seven cognate transmembrane domain (7TM) receptors in the membranes of host cells. Two of these receptors, C3aR and C5aR1 (CD88), belong to the large family of GPCRs that contain transmembrane domains capable of interacting with C3a and C5a (compare Vol. 1 [1], Sect. 5.3.5.2, p. 80, Sect. 14.3.4, p. 328, and Sect. 23.2.5, pp. 604/605). The third receptor, C5aR2 (previously known as C5L2), is structurally similar to C5aR1 but does not couple to heterotrimeric G proteins (more information about the role of C3a and C5a acting as inducible DAMPs in sepsis is described below).
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5.5.3.7 Extracellular Vesicles (e.g., Exosomes) in Sepsis As already briefly thematized in Sects. 3.2.3.5 and 3.6.2, the formation of EVs such as exosomes amazingly reflects the evolutionary arms race between bacteria and mammals, whereby both rivals use them as the same weapons for their mutual defense. These extracellular organelles have also been shown to be involved in the pathogenesis of experimental and clinical sepsis [355, 356]. In this disease, their key function is to shuttle DAMPs via the systemic circulation from the local site of infection to distant organs such as the lungs, kidneys, liver, cardiovascular system, and CNS, where they immediately begin to activate PRR-bearing cells, contributing to MODS. Constitutive DAMPs contained in exosomes of septic mice and/or patients were found to include HMGB1, HSP70, histones, eATP, and extracellular RNA. Inducible DAMPs detected to be encapsulated by exosomes from septic mice include TNF and IL-1β [356]. 5.5.3.8 Concluding Remarks The spectrum of DAMPs involved in sepsis, as listed here, is not complete and should just mediate an impression of the strong pathogenetic role of these molecules in this life-threatening disease. In fact, other DAMPs, such as DNA, RNA, and eATP, released from RCD in sepsis, can be assumed to be involved in sepsis as well. Looking at PubMed in August 2022, a brisk activity can be noticed (e.g., [357–359]).
5.5.4 Demonstration of SAMPs 5.5.4.1 General Remarks As highlighted in Sect. 4.4.4 the production of SAMPs during infection is imperative to regulate the innate immune defense through their inflammation-resolving capabilities, aimed at restoring homeostasis upon pathogen-induced injury. However, as frequently mentioned in this book, this primarily beneficial response can turn into a dysregulated harmful process in case the original injury is too excessive. Thus, as with the polytrauma-induced sterile SIRS, infective SIRS/sepsis is typically characterized by the development of an immunosuppressive phase that is described in more detail below. Accordingly, in keeping with the model of SAMPdriven resolution of inflammation, as discussed in Sect. 4.4.4 the phenomenon of immunosuppression in sepsis is interpreted here as a SAMP-driven compensatory/ counterbalancing inflammation hyperresolution response. Indeed, there are already some first reports in the international literature dedicated to this hot topic. Thus, SAMPs such as AnxA1, cAMP, extracellular adenosine, and, most importantly, SPMs have already been reported to be involved in bacterial infection and sepsis, respectively. 5.5.4.2 Annexin A1 Experimental evidence for AnxA1 to act as a SAMP in the setting of sepsis comes from earlier studies on a murine model of LPS-induced cerebral inflammation,
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demonstrating that the AnxA1/FPR2 system has a critical role in effecting the resolution of cerebral inflammation in sepsis [360]. These findings are supported by experiments with a Chinese herbal medicine (“Xuebijing”) that is known to induce an increase in the expression of AnxA1. In a sepsis model of A. baumannii infection, prophylactic administration of this substance to rats was shown to effectively alleviate the symptoms and tissue injury, thereby preventing the development of severe sepsis in these animals [361]. Further experimental evidence for a beneficial effect of AnxA1 in sepsis settings came from studies in a sepsis-induced cardiomyocyte apoptosis model, suggesting that application of the AnxA1 mimetic peptide AC2-26 may successfully alleviate the sepsis-induced cardiomyocyte apoptosis in vitro and in vivo through the LXA4/PI3K/AKT signaling pathway [362] (PI3K for phosphatidylinositol 3 kinase). Of note, some data on this SAMP from critically ill patients suffering from infectious sepsis are also available. Thus, in a Chinese study on a relatively small number of sepsis patients, the AnxA1 level was found to be elevated in 56% of patients over the 7-day observation period. However, the daily levels of the patients over time were not significantly different from the levels of the control individuals [363, 364]. The authors discussed that the observed elevation of AnxA1 level in their patients is likely due to the release of AnxA1—in either free form or wrapped in microparticles—by activated neutrophils or monocytes/macrophages in response to the infectious insults as reported from other studies [365–368]. Nevertheless, though the data is still sparse, an immunosuppressive effect of this SAMP is understandable as AnxA1 has been proposed to interact with GATA-protein binding 3 (GATA3) to influence T-cell differentiation in CD4+ T cells [369] (Fig. 5.5; for GATA3, compare Vol. 1 [1], Sect. 32.4.4, p. 768). Of interest in this context mentioning are two studies: In in vitro and in vivo cancer-related studies, AnxA1 was shown to enhance the function of Tregs [370]; in a murine model of endotoxemia, AnxA1 and FPR2 were demonstrated to have a critical role in the manifestation of adrenal insufficiency known to contribute to morbidity and mortality in a high proportion of patients with sepsis [371].
5.5.4.3 Extracellular Adenosine Extracellular adenosine (its major source being ATP hydrolysis by ectonucleotidases such as CD39 and CD73) is another SAMP that has been experimentally and clinically demonstrated to be involved in sepsis. As known, adenosine signals through adenosine A2A receptors (A2AR) suppress anti-tumor and anti-pathogen immune responses [372]. Indeed, adenosine plasma levels are well known to be elevated in patients during the acute phase of sepsis and septic shock [373, 374]. Experiments support these clinical observations. For example, in studies on the murine CLP model aimed at determining CD39 ectonucleotidase activity and its role in sepsis-induced liver injury, the authors provided evidence indicating that the functionality of CD39 is crucial for the generation of adenosine, which conveys anti-inflammatory, immunosuppressive, and protective effects in sepsis-associated liver injury [375]. Other lines of studies using in vivo and in vitro models of
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Fig. 5.5 Schematic diagram of a model illustrating the role of SAMPs in suppressing destructive Th1 and Th17 adaptive immune responses but promoting a protective Th2 response. SPMs, in their function as SAMPs, reduce lineage-specific cytokine production by activating Th1 (i.e., IFN-γ) and Th17 cells (i.e., IL-17) by downregulating their signature transcription factors T-bet and RORγt. By contrast, adenosine, in its function as a SAMP, is suggested to activate DCs to promote the production of the anti-inflammatory cytokines IL-4 by Th2 cells, and AnxA1 has been proposed to interact with the transcription factor GATA3 to influence T cell differentiation in CD4+ T cells. DC dendritic cell, GATA3 GATA-protein binding 3, IFNγ interferon-gamma, IL interleukin, pMHC peptide/major histocompatibility complex molecule, RORγt retinoic acid receptor-related orphan receptor gamma t, STAT signal transducer and activator of transcription, TCR T cell receptor, TGF-β transforming growth factor-beta, TNF tumor necrosis factor, UCM up-regulated costimulatory molecules (Sources: the figure corresponds to Fig. 8.2, Sect. 8.3.4, p. 304; in Vol. 2. [2], Danger Signals as Diagnostics, Prognostics, and Therapeutic Targets. In: Springer International Publishing AG, 2020; available from http://www.springer.com/978-3-030-53868-2, for further references, see there)
endotoxemia yielded evidence that extracellular adenosine acts on its corresponding receptor A1R to suppress endotoxemia-induced inflammation by inhibiting neutrophil overactivation [376] (for purinergic receptors, see Vol. 1 [1], Sect. 5.3.4, pp. 75–78 and Vol. 2 [2], Sect. 2.3.3, p. 29). In addition, in recent studies on the CLP sepsis model in mice, extracellular adenosine derived from CD39hiCD138hi plasmablasts was found to operate as an important driver of sepsis-induced immunosuppression [377]. Remarkably, in these studies, Nascimento et al. [377] could show that sepsis promotes the expansion of splenic CD39hiCD138hi plasmablasts, which generate elevated extracellular adenosine in sepsis survivors. The SAMP was found to drive suppression of the immune response by hampering the microbicidal activity of macrophages via A2AR activation, leaving sepsis-surviving mice highly susceptible to secondary infections. The increasing knowledge of the immunosuppressive role of extracellular adenosine in sepsis culminates, however, in studies on the CLP model demonstrating that this SAMP promotes Foxp3 expression in Tregs [378].
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5.5.4.4 Specialized Proresolving Mediators The emerging topic of SPMs in posttraumatic immunosuppression has been sketched in Vol. 2 [2], Sect. 8.3.4.6, pp. 304/305 and briefly resumed in Sect. 4.4.4.4. In support of this concept are earlier clinical findings reported by Dalli et al. [379] showing that the lipid mediator profiles in human septic patients are correlated with outcome. Intriguingly, in sepsis non-survivors, the authors found significantly higher inflammation-initiating mediators, including prostaglandin F2α (PGF2α) and chemoattractant leukotriene B4 (LTB4, an inducible DAMP), as well as higher SPMs including RvE1, RvD5, and 17R-PdD1 than was observed in surviving sepsis subjects. In other words: the higher state of inflammation-initiating (i.e., hyperinflammatory) mediators in septic patients was observed to be associated with a higher state of resolving (i.e., hyperresolving) molecules. However, since the primary objective of this study was not to correlate SPMs levels with infections, a possible immunosuppressive effect was not investigated. On the other hand, the first evidence from other lines of studies has already been published reporting an effect of several SPMs in shaping, that is, suppressing adaptive immune responses. For example, in a series of in vitro experiments performed by Chiurchiu et al. [380], the SPMs RvD1, RvD2, and MaR1 were shown to modulate adaptive immune responses in human peripheral blood lymphocytes (see also [381]). For example, the SPMs reportedly regulate DC activation markers, including suppression of cytokine production and expression of MHC molecules and costimulatory markers that promote a return to homeostasis following an acute inflammatory response. Moreover, these lipid mediators were found to sharply reduce lineage-specific cytokine production by activated CD4+ Th1 (i.e., IFN-γ) and CD4+ Th17 cells (i.e., IL-17) as well as CD8+ T cells (i.e., TNF, IFNγ), but not to modulate T-cell inhibitory receptors (e.g., PD-1 and CTLA-4) or abrogate their capacity to proliferate (for PD-1 and CTLA-4, compare Vol. 1 [1], Sect. 33.3.5 and Fig. 33.3, pp. 805–807). Further targeted in vitro experiments revealed that the tested SPMs can prevent naïve CD4+ T-cell differentiation into Th1 and Th17 by downregulating their signature transcription factors, T-bet and retinoic acid receptor-related orphan receptor-gamma t (RORγt) [380] (see Fig. 5.5 for these transcription factors, for additional information see also Vol. 1 [1], Sect. 32.4, p. 765). This mechanism was found to be mediated by members of the GPCR family, namely, G protein-coupled receptor 32 (GPR32) and lipoxin A4 (ALX)/FPR2 (for GPCRs and GPCR signaling, for additional information, compare Vol. 1 [1], Sect. 5.3.5.3, p. 80, Fig. 5.11, p. 79, and Vol. 2 [2], Sect. 22.3.10, p. 513). In these studies reported by Chiurchiu et al. [380], the authors could also show that SPMs—concomitantly with Th1 and Th17 downregulation—enhance de novo generation and function of inducible Foxp3+ regulatory T cells (iTregs) via the GPR32 receptor (for additional information about iTregs, see Vol. 1 [1], Sect. 33.4.3.3, p. 813 and Fig. 33.4, p. 801). These findings are supported by another study on the property of the SPM MaR1 [382]. In these in vitro experiments, MaR1—together with TGF-β—was found to promote the generation of iTregs.
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Doubtlessly, research on the critical role of SPMs in sepsis is currently a hot topic. In earlier studies on the CLP sepsis model, LXA4 alone was already found to be effective at reducing systemic inflammation and bacterial load as well as improving survival [383]. In subsequently conducted experiments using this model in mice, treatment with RvD1 revealed (1) improved survival of the septic animals, (2) enhanced organism bacterial clearance, (3) suppressed the increase of the numbers of neutrophils in peritoneal lavage fluid, (4) reduced the release of inflammatory cytokines, and (5) decreased the apoptosis rate of CD3+ T cells of the thymus [384]. In more recent studies on the CLP model, the SAMP RvE1 was demonstrated to ameliorate cardiac dysfunction in septic mice [385]. Moreover, treatment with this SPM was shown to reduce the peritoneal bacterial load and promote the phagocytosis activity of bone marrow-derived macrophages. The authors concluded that cardiac SPMs, particularly RvE1, are substantially reduced in mice with polymicrobial sepsis. And again, in investigations on the murine CLP sepsis model, the SPM MaR1 has also been demonstrated to improve survival in septic mice, ameliorate vital organ function, inhibit inflammation response, and reduce the bacterial burden in serum [386]. One can imagine that these protectively acting SAMPs, when produced in excess under hyperinflammatory septic conditions, may contribute to a counterbalancing hyperresolving response. But this has still to be proven.
5.5.4.5 Prostaglandin E2 There is at least some indirect evidence that PGE2 acts as a SAMP in septic settings. Thus, in in vivo studies on the CLP model in mice [387], administration of bone marrow stromal cells (BMSCs) was found to attenuate sepsis, as indicated by reduced mortality and improved organ function. The combination of further in vitro and in vivo experiments then revealed that the beneficial effect of the BMSCs was probably due to an increased release of PGE2 from the BMSCs, acting on the corresponding receptors of macrophages and stimulating the production and release of IL-10 [305]. These observations are consistent with subsequent studies on the murine inflammatory model of LPS-induced acute (septic) liver injury showing that injection of BMSCs ameliorates acute liver injury, interpreted by the authors as mediated via PGE2-dependent repression of the NLRP3 inflammasome in Kupffer cells [388]. Again, other sets of studies on experimental sepsis models provided further corroborative evidence for the role of PGE2 in sepsis-induced immunosuppression [389–392]. In one such experimental series [390], ketoprofen treatment was found to inhibit PGE2 production, thereby qualifying this agent as an attractive target to prevent secondary infections in immunocompromised septic patients. In another model of sepsis-induced AKI in mice [391], tenuigenin, a natural product isolated from Polygala tenuifolia root, was also found to inhibit the production of PGE2. In more recent experiments, targeting the 15-keto-PGE2-prostaglandin reductase 2 (PTGR2) axis was demonstrated to mitigate systemic inflammation and improve survival of septic mice (15-keto-PGE2 is a PGE2 metabolite, whose further processing is catalyzed by PTGR2).
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5.5.4.6 Concluding Remarks The narrative of SAMPs in impacting infectious diseases is currently an exciting and emerging topic. In the near future, knowledge about the function of these molecules in infections will certainly be expanded, especially about their ability to control innate immune defense responses against infectious invaders, but also—in the sense of a double-edged sword—to contribute to the aggravation of infectious disorders via promotion of increased susceptibility to additional nosocomial infections.
5.5.5 Pathophysiology-Pathogenesis of Sepsis 5.5.5.1 General Remarks As with the change of viewpoints in the pathogenesis of ARDS, there has also been a marked rethinking in our understanding of the molecular pathogenesis of sepsis. Originally believed that the typical hemodynamic manifestations of sepsis are primarily related to the hyperimmune host response against a distinct pathogen, current notions now focus on the scenario that has already been discussed above in Sect. 4.7.2: namely, a complex interplay between the infectious agent and the host, that is, on the molecular level, between MAMPs (whereby NAs act as exogenous DAMPs) and DAMPs. This time, however, this complex interplay derails into a multifaceted, dysregulated, systemic innate immune (i.e., hyperinflammatory/ hyperresolving) response that is driven and orchestrated by the emission of DAMPs and SAMPs in excess; a scenario that is comparable to the above-described development of ARDS (see Sect. 5.4.5). At this point, it is also worth recalling again the danger/injury model stating that excessive emission of DAMPs can result from any severe injury, whether infectious or sterile in nature. Accordingly, the clinical picture, as well as many DAMP/ SAMP-triggered, PRR-mediated innate immune hyperinflammatory/hyperresolving pathways observed and described in sepsis (i.e., “infectious SIRS”), are similar though not identical to those seen in polytrauma-associated “sterile SIRS” (outlined in Vol. 2 [2], Sect. 8.3.3, pp. 294–308). This fact gives reason to insinuate that the DAMPs and SAMPs, rather than the non NA-MAMPs, are the major players in sepsis, shaping the clinical picture and governing the interconnecting cellular and molecular pathways involved in the pathogenesis of the disease. Accordingly, and with reference to the description of DAMPs and SAMPs as described above, here, DAMP-triggered inflammation-promoting and SAMPdriven inflammation-resolving responses are tentatively projected onto a bacterial infection progressing to sepsis with the potentially fatal outcome as characterized by hyperinflammation → immune coagulation → septic shock → immunosuppression → MODS → patient’s death (cf. Fig. 2.5). 5.5.5.2 The Systemic Hyperinflammatory State: Sketching a Scenario Model The breach of the controlled local-regional innate immune defense response against bacteria is the beginning of the septic scenario: the pathogens now cross mucosal
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barriers, disseminate to remote organs throughout the body and replicate there [20]. Arrived at each body system and various organs, the infectious agents (but perhaps also their toxins secreted by them at the original site of infection) are supposed to do what they have been shown to do in vitro and in vivo studies: to induce various subroutines of RCD as pivotal sources of DAMPs (see above [35, 303–312]; also compare Sect. 3.7). The simultaneous abundant release of constitutional DAMPs throughout the body may result in an overall activation of PRM-bearing cells of the innate immune system, that is, mobile cells such as PMNs, macrophages, DCs, but also platelets, as well as sessile cells such as endothelial and epithelial cells (for the whole family of mammalian PRM-expressing innate immune cells, see Vol. 1 [1], Part III, pp. 113–177). Notably, some cells, in particular, phagocytes, following activation by DAMPs, secrete inducible DAMPs such as TNF and type I IFNs, as well as IL-1β released from cells succumbing from inflammasome-mediated pyroptosis. (Needless to stress here again the critical role of inflammasomes in amplifying the inflammatory pathways, compare [393, 394].) However, this is not the end of the dynamic systemic MAMP/DAMP-triggered innate immune responses. As demonstrated by their detection in the serum of sepsis patients, both constitutive and inducible DAMPs may leave the site of their origin in cells and tissues throughout the body and—via “DAMPemia”—may systemically activate further mobile PRMbearing cells in the circulation and sessile PRM-bearing cells in various other organs. Given that all activated cells of the innate immune system are programmed to secrete inflammatory mediator substances such as cytokines, chemokines, and adhesion molecules, the demonstration of the cytokine storm as a typical feature in sepsis patients [288] is easy to explain in light of this conceptual scenario (cf. Fig. 5.3; for more information of DAMP-triggered cellular inflammatory responses, see Vol. 1 [1], Chap. 22, pp. 475–564). Moreover, within this “DAMPome”-elicited hyperinflammatory “hurricane,” further cells, as well as cellular and humoral pathways, are activated, including PMNs and ECs as well as the complement system and coagulation cascade (Fig. 5.6): a complex scenario that deserves a few more words. DAMP-Promoted Activation of Polymorphonuclear Neutrophils During the development and progression of sepsis, PMNs are the most abundantly recruited innate immune cells at the multilocular sites of infection, dedicated to playing crucial roles in the containment of local infection. As already mentioned in Sect. 4.4.3.2, PMNs are regarded as the body’s first line of defense against invading pathogens, which they fight by using an array of diverse antimicrobial effector mechanisms ranging from phagocytosis, the release of both granules, and NADPHdependent ROS, up to the formation of NETs. Leukocyte recruitment in postcapillary venules in many tissues generally follows a multistep pathway: rolling, arrest, firm attachment, and transmigration, known as the process of leukocyte-endothelial interaction (described and illustrated in Vol. 1 [1], Sect. 22.2.2 and Fig. 22.2, pp. 477–480; for a recent review, see [395]). Of peculiar importance—as also stressed by Bosman and Ward in their review on The Inflammatory Response in Sepsis [287]—is the ability of activated neutrophils to generate large amounts of
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Pathogen-induced injury (Sepsis)
RCD
Sterile injury (e.g., Polytrauma - SIRS)
MAMPs Cytok. storm→ Hyperinflammation
cDAMPs, iDAMPs
DAMPome
cDAMPs, iDAMPs
Endothelial barrier dysfunction
Complement fragments SAMPs, e.g., Histones, HMGB1, DNA, act. Inflammasome Æ TF iDAMPs: C5a, C3a e.g., SPMs, AnxA1 Potentiation of Thromboinflammation Hyperresolution Immunosuppression
Immunothrombosis DIC
Fatal Outcomes
Fig. 5.6 Simplified schematic diagram of a model illustrating the DAMPome—elicited complex pathogenetic scenario in sepsis (in comparison to polytrauma) that can lead to fatal outcomes such as septic shock or multiple organ failure. AnxA1 annexin A1, cDAMPs constitutive DAMPs, iDAMPs inducible DAMPs, RCD regulated cell death, SIRS systemic inflammatory response syndrome, SPMs specific proresolving mediators, TF tissue factor (Sources: [370, 378, 380, 396–398, 404, 406, 407, 419–421])
ROS, and in some situations RNS, including H2O2, hydroxyl radical (•OH), •NO, and peroxynitrite (ONOO−). It is this imbalance in the redox system during sepsis that leads to the formation of an oxidant state, which appears to intensify SIRS and the downstream events. Of particular note in this context are studies on models of sterile injury suggesting that PMNs activated by mitochondria-derived DAMP are pathogenetically involved in sepsis-like symptoms [332]. DAMP-Triggered Activation of Endothelial Cells Leading to Endothelial Barrier Dysfunction A marked dysfunction of PRM-bearing ECs is a typical pathological feature during sepsis that manifests as several pathological processes, including barrier hyperpermeability in terms of inappropriate barrier function, inappropriate leukocyte adhesion, and microvascular thrombosis. In fact, it is the disruption of vascular endothelial barrier function associated with derangement of the endothelial glycocalyx, which is considered central to the pathogenesis of sepsis and highly integrated into the host systemic inflammatory and coagulopathic response [396]. This severe complication leads to massive loss of plasma volume, circulatory collapse, shock, and/or MODS [350, 396–398]. Notably, already a decade ago, the first evidence was reported suggesting a pathogenetic role of DAMPs such as HMGB1, HA, and HSP in this scenario [399, 400]. Further support for an implication of DAMPs in endothelial barrier dysfunction was provided by in vitro studies on EA.
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hy926 ECs, a cell line derived from the human umbilical cord ECs, demonstrating that mitochondrial DAMPs increased the permeability of these cells [401]. Also, and confirming the function of these DAMPs, Wencelau et al. [402], in reviewing relevant data from their own group and from the literature, proposed that mtFPssensing endothelial FPR is a key contributor to impaired barrier function in SIRS and sepsis patients following trauma. Moreover, other lines of experimental studies on human umbilical vein ECs provided evidence for the role of inducible DAMPs such as TNF and IL-1β in this pathogenetic feature that drives the septic process at the level of the endothelium [403]. In fact, in recent years, the interest in DAMPs implicated in septic endothelial barrier dysfunction has been growing (cf. Fig. 5.6). Thus, as discussed by Opal and van der Poll [396] with reference to HMGB1: HMGB1 disrupts endothelial barriers, alters the actin filament cytoskeleton, impairs tight junctions, promotes the release of large quantities of IL-1a as well as an array of other cytokines and chemokines, and stimulates enhanced expression of cell surface adhesion components such as ICAM1 and VCAM1 on endothelial membranes…. Antibodies directed against HMGB1 can reverse many of these changes seen in experimental animal models of sepsis, indicating that clinical development of HMGB1 inhibitors should be considered. And Joffre et al. recently noted [398]: In response to DAMPs or PAMPs, the vascular barrier is impaired … owing to glycocalyx breakdown, EC apoptosis, and junction protein dysregulation (Compare: DAMPs derived from the degraded endothelial glycocalyx, in Sect. 5.5.3.5). Again, the concept of the aberrant and dysfunctional endothelial barrier is considered the central pathophysiological process in septic shock [396]. Complement Activation: The Work of the Inducible DAMPs C3a and C5a The humoral innate immune defense response against bacteria is best and impressively reflected by the activation of complement that contributes to their elimination. Notably, however, in addition to this historical view as a tool to defend against bacteria, the complement system is now recognized to play a crucial homeostatic role by sensing damaged or altered-self components. But again, its dysregulated exaggerated function in sepsis is harmful and potentiates the thromboinflammatory and hyperinflammatory state, leads to severe organ damage, and may even be lethal for the host in case of septic shock (for a recent review, see [404]). The complement system, its recognition receptors, its activation, and its co-players have been comprehensively described in Vol. 1 [1], Sect. 5.4.3, p. 90 and Chap. 23, Fig. 23.1, pp. 591–626 (briefly resumed in Sect. 4.4.3.4). During sepsis, especially in the early phase, it is the adverse and harmful function of the terminal C5b-9 complement complex (the MAC) and—even more important—the inducible DAMPs C3a, particularly C5a at high concentrations that, along with engagement of corresponding receptors (C3aR and C5aR1/C5aR2), contribute significantly to the hyperinflammatory state (cf. Fig. 5.6). In fact, C5a is considered one of the most active inflammatory peptides produced during sepsis [405]. Mechanistically, these inducible DAMPs operate on several levels. As reported in reviews of findings and observations mainly from studies on the CLP model [287, 295, 346, 406–408], C5a acts as a most potent chemotactic factor for neutrophils
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that can shift the EC from anti-adhesiveness to pro-adhesiveness by upregulation of various selectins, allowing early adhesive interactions between recruited neutrophils and ECs in the acute inflammatory response. Also, C5a was found to drive an oxidative burst in neutrophils resulting in the generation of ROS and the release of granular enzymes, which are believed to contribute to oxidative tissue damage. In addition, C5a, as a powerful activator of cytokine and chemokine synthesis/release, was shown to amplify sepsis-associated inflammatory responses, which are believed to contribute to vasodilation, tissue damage, and MOF in settings of acute inflammation. Such an amplifying effect may stem from the ability of complement and C5a and its receptors (1) to activate PMNs forming NETs and macrophages forming METs and (2) to activate the NLRP3 inflammasome. Moreover, as published elsewhere [409], C5b-9, as the final product of the three activation pathways of the complement system, also has been reported to activate the NLRP3 inflammasome. Similar events have been observed to occur in patients with sepsis, especially with severe septic courses: In fact, in the clinical studies, a robust complement activation including generation of C3a and C5a was reported, whereby the anaphylatoxin production appeared to be associated with a poor prognosis ([410], reviewed in [407]). Interestingly, high levels of C3a and C5a, as observed in critically ill patients, were found to be higher in sepsis than in trauma-associated sterile SIRS [411]. Contribution of DAMPs to Immunothrombosis: Hypercoagulability Another hallmark observed in patients with severe sepsis and septic shock, in tandem with the activation of the complement system, is the activation of the coagulation system. Of note, as outlined already by us in the book Innate Alloimmunity, Part 2, Innate Immunity and Allograft Rejection in 2011 [412], simultaneous activation of the inflammatory response and clotting cascade following tissue injury is a phylogenetically ancient survival strategy. As reviewed by Opal and Esmon [413], the linkage between inflammation and coagulation in terms of two defense systems can be traced back to the earliest events in eukaryotic evolution before the separation of plants and invertebrate animals from the evolutionary pathway that led toward vertebrate animal development. The evolutionary linkage between coagulation and inflammation is perhaps best exemplified by the study of the host defenses of the Atlantic horseshoe crab, Limulus Polyphemus, a living fossil that dates back to the Jurassic Period 250 million to 146 million years ago. As further outlined by Opal and Esmon [413], any injury to the exoskeleton of the crab immediately jeopardizes the integrity of the internal milieu of the organism. Not only is there a real threat of loss of internal contents of the crab to the external environment, but there is also an omnipresent risk for entry of pathogens from the marine environment through the damaged protective crab shell. Both the loss of the internal milieu through the crab’s open circulatory system and contamination of its vital structures by microbial invaders threaten the survival of the entire arthropod organism. In response to this threat, the horseshoe crab has evolved a rapid defense response system that leads, besides others, to the release of a complex series of soluble proteins, which work as a cascade system that terminates in the formation of an
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insoluble extracellular clot. Today, this defense response is called “immunothrombosis” [414]. In sepsis patients, we meet this evolutionary developed defense mechanism again; unfortunately, however, from its dark side: in its dysregulated, exaggerated, and thus, life-threatening version. Sepsis promotes a hypercoagulable state that is characterized by endothelial injury, microvascular thrombi, fibrin deposition, and NET formation. The process is orchestrated by the action/interaction of activated PRR-bearing platelets, neutrophils, ECs, and coagulation proteases [415]. In the worst case, the hemostatic changes can result in generalized thrombosis in the microvasculature, platelet consumption, and subsequent clotting factor exhaustion, characterizing the life-threatening picture of DIC that can lead to MODS, hemorrhage, and death [416, 417]. Notably, in addition to the involvement of MAMPs, there is growing evidence for a pivotal prothrombotic/procoagulant role of systemically spreading DAMPs in the development of DIC (cf. Fig. 5.6). This emerging notion is mainly based on the finding that DAMPs are involved in other pathophysiological conditions known to cause DIC, such as polytrauma, well-noting conditions where MAMPs are absent. Thus, DAMPs such as extracellular DNA, histones, HMGB1, and others released from cells undergoing NETosis and other forms of RN, but also as contents of EVs, are thought to contribute to DIC [417–420]. Mechanistically, DAMPs have already previously been proposed to trigger an intravascular thrombus formation, possibly by inducing TF expression on PRR-expressing monocytes, upregulating TF procoagulant activity, and promoting activation and aggregation of PRR-bearing platelets [23, 26]. Of particular note, recent studies now emphasize that the MAMP/DAMPinduced activation of inflammasome-associated pyroptosis not only leads to the release of constitutive and inducible DAMPs but also triggers the release of the TF in activated macrophages and monocytes (reviewed by Wu et al. [421]). And it is this TF that initiates and promotes the blood clotting cascade [27, 422] (see Figs. 5.7 and 5.8). In fact, TF is a key link between inflammation and coagulation and has been identified as a critical initiator of the extrinsic coagulation pathway in sepsis, together with the clotting factors, factor VIIa, factor Xa, thrombin, and fibrin [295, 423, 424]. It is worth adding here that the inducible DAMP C5a has been shown to induce TF expression on ECs [425].
5.5.5.3 Immunosuppression Reflecting “Inflammation Hyperresolution”: Continuation of the Scenario Model Over the past decade, stringent experimental and clinical studies have been published indicating that sepsis may evoke an immunosuppressive state that confers increased susceptibility to secondary, mostly opportunistic infections. In fact, intensivists have long observed that patients who successfully survive the hyperinflammatory episode of sepsis suffer from a long-term immunosuppressive state, making them vulnerable to secondary infections [297, 426–428]. The clinical picture of sepsis-associated immunosuppression is associated with marked changes in innate immune responses. Thus, the function of non-matured
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Fig. 5.7 Simplified schematic diagram of a narrative model of MAMP/DAMP-induced inflammasome-associated pyroptosis (here exemplified by NLRP3 inflammasome-associated pyroptosis), leading to release of tissue factor from the ruptured cell membrane of activated macrophages and monocytes, promoting sepsis-induced blood coagulation. MAMP/DAMP-induced ion perturbations reflecting the presence of dyshomeostatic DAMPs are mainly caused by K + efflux and Ca2+ influx. Note: More informative illustrations about the activation of the NLRP3 inflammasome → pyroptosis are presented in Vol. 1 [1], Injury-Induced Innate Immune Responses. In: Cham, Springer International Publishing; 2018; available from: http://link.springer. com/10.1007/978-3-319-78655-1, Fig. 22.11, p. 517; and Vol. 2 [2], Danger Signals as Diagnostics, Prognostics, and Therapeutic Targets. In: Springer International Publishing AG, 2020; available from http://www.springer.com/978-3-030-53868-2, Fig. 2.1, p. 20; also compare the previous Sect. 3.7.5.4, Figs. 3.9 and 4.4. dysDAMPs dyshomeostatic DAMPs, GSDMD gasdermin D, IL-1β interleukin-1 beta, NF-κB nuclear factor-kappa B, NLRP3 nucleotide-binding oligomerization domainlike receptor family pyrin domain-containing 3, RCD regulated cell death, TF tissue factor, TLRs Toll-like receptors, TRAF6 tumor necrosis factor (TNF)-receptor-associated factor 6 (Source: [421])
neutrophils is reportedly impaired, as evidenced, for example, by decreased chemotaxis and oxidative burst [429]. Moreover, as observed in experimental sepsis models, especially in CLP, myeloid-derived suppressor cells (MDSCs), characterized by their immunosuppressive functions, are activated by MAMPs and DAMPs to proliferate and expand massively (reviewed in [430]; for MDSCs, also see Vol. 1 [1], Sect. 33.4.8, p. 817). Both immature neutrophils and MDSCs secrete multiple antiinflammatory cytokines, including IL-10 and TGF-β, which further suppress immune function. As another class of innate immune cells, DCs, translating innate immune events into adaptive immune processes, have been shown not only to decrease in number but also to exhibit decreased functionality. In addition, these professionals among the APCs were observed to lose expression of the activating MHC-II molecule (HLA-DR), whereby antigen presentation is compromised [295, 431].
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Fig. 5.8 Simplified schematic diagram of a narrative model showing the sepsis-induced blood clotting cascade with a focus on the activation of the tissue factor (TF) pathway (i.e., the extrinsic pathway of coagulation) via MAMP/DAMP-induced inflammasome-associated pyroptosis, (note: the figure is a continuation of Fig. 5.7, inserted, start reading at the top left). The TF is released from ruptured membranes of pyroptotic cells (e.g., monocytes and macrophages) and exposed to blood to be complexed with FVIIa. The TF-FVIIa complex (anchored to the cell surface because TF is a transmembrane protein) functions as the primary activator of the coagulation protease cascade by activating its major substrates: FIX → converting to FIXa, and FX → converting to FXa by limited proteolysis. Both of these active enzymes must assemble on appropriate membrane surfaces together with their own protein cofactors (FVIIIa in the case of FIXa; or FVa in the case of FXa) in order to propagate the clotting cascade. The final FXa-triggered pathway results in the generation of thrombin, which converts fibrinogen to fibrin and activates platelets. Note: The clotting proteins (both zymogens and procofactors) are represented by Roman numerals, with a lowercase “a” appended to the numeral, once the protein has been proteolytically converted to the active form. FVa factor Va, FVII factor II, FIX factor IX, FX factor X, TF tissue factor (Sources: [27–29, 295, 422–424])
Of particular significance, however, are alterations involving the adaptive immune system, characterized by a significant apoptotic depletion of B cells, CD4+ T cells, and CD8+ T cells. Additionally, as reviewed by Martin et al. [432], there is a marked sepsis-associated disruption of representation and function of CD4+ T cell subsets, including Th1, Th2, Th17, Tfh, and Treg subsets (for details of these subsets, see Vol. 1[1], Sect. 32.4, pp. 765–772). As further reviewed [432], several studies in septic patients revealed an increased frequency of Tregs cells in the circulation, an observation that was later found to be due to preferential loss of other subsets (i.e., Th1, Th2, Th17, and Tfh) (for Tregs, also see Vol. 1 [1], Sect. 33.4, pp. 809–815). SAMP-Driven “Hyperresolution” in Sepsis-Associated Immunosuppression According to the model of SAMP-driven resolution of inflammation (Sect. 4.4.4), the inflammation-resolving properties of these molecules are thought to get exaggerated under septic conditions to counteract the DAMP-promoted
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hyperinflammatory response. In fact, and intriguingly, the features of a dysregulated adaptive immune response observed in sepsis are reminiscent of the function of SAMPs. As mentioned already above, SPMs were shown to downregulate Th1 and Th17 cells and, concomitantly, enhance the de novo generation and function of Tregs [380]. Also, another SAMP, extracellular adenosine, was demonstrated to promote Foxp3 expression in Tregs [378], while the SAMP AnxA1 reportedly reveals the property of enhancing the function of Tregs [370]. Of particular note at this point is that evidence has been provided supporting a new pro-resolution vagal reflex where vagal stimulation produces SPMs that stimulate the resolution of inflammation and infections [433]. On the other hand, as shown, for example, in studies on the CLP model in mice, the vagus nerve is constitutively active in sepsis survivors and modulates immunosuppression [434]. These exciting findings from two different lines of studies may allow considering the possibility that the vagal production of SPMs in the setting of sepsis contributes to the well-known immunosuppressive state. Overall, the observations on sepsis-associated disruption of representation and function of CD4+ T cell subsets appear to be at least partially congruent with the function of SAMPs as reported from SPMs and adenosine. In other words: there is growing evidence for a model holding that SAMPs drive the counterbalancing inflammation“hyperresolving” responses in sepsis-associated immunosuppression (cf. Fig. 5.6). Typically, depending on the severity of the septic process, both the innate and adaptive immune systems may remain dysfunctional for weeks or even months, exposing patients to further risks of infections [428, 435]. Of note, the long-lasting immune disturbances in terms of an immunosuppressive state were found to be often accompanied by persistent low-grade inflammation associated with long-term catabolism and malnutrition. As “chronic critical illness,” the clinical picture then was termed Persistent Inflammation, Immunosuppression, and Catabolism Syndrome (PICS) [436]. Interestingly, the persistent inflammation in patients developing the syndrome has been proposed to be a result of DAMPs released from damaged organs and loss of muscle mass [437]. A modification of this concept has been proposed with respect to polytrauma-associated immunosuppression (Ref. [438] and Vol. 2 [2], Fig. 8.1, p. 292 and Sect. 8.3.5, p. 306) and is—slightly modified— resumed here (Fig. 5.9): Due to the overlapping trajectories of DAMP-promoted proinflammatory crescendo → decrescendo response and SAMP-driven proresolving “reversed” crescendo → decrescendo response, the action of DAMPs (promoting persistent low-grade inflammation) is still demonstrable during the phase of SAMP-driven inflammation “hyperresolution”/immunosuppression.
5.5.5.4 Remote Organ-Specific Dysfunction Sepsis, as a systemic disorder, can affect all organs of the body. The clinical manifestations, symptoms, and syndromes are variable and depend on the organ systems affected in each case. Intensivists can identify mainly six types of organ dysfunction [439]: (1) neurological involvement presented as confusion, agitation, coma, or “sepsis-associated delirium”; (2) pulmonary disorder culminating in ARDS; (3) cardiovascular disturbances diagnosed as myocardium dysfunction and/or shock; (4)
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Fig. 5.9 Schematic diagram of a conceptual model illustrating the dysregulated hyperinflammatory response observed in sepsis that is induced by excessive production of DAMPs in interaction with MAMPs. This DAMP/MAMP-induced hyperinflammatory response proceeds in parallel to a hyperresolution response observed as CARS/immunosuppression that is induced by the production of counterbalancing SAMPs in excess (the controlled homeostatic proinflammatory and resolving responses are faded in, separated by dotted lines). The short delay of the beginning of the hyperresolving response should symbolize that SAMPs, in terms of inducible suppressing DAMPs, are secreted by MAMP/DAMP-activated PRM-expressing innate immune cells. The initial hyperinflammatory phase is associated with an increased risk of MOF, whereas the long-lasting hyperresolution phase is characterized by a state of immunosuppression that is associated with increased susceptibility of patients to secondary, mostly opportunistic infections. Note: The overlapping hyperinflammatory and hyperresolution responses allow DAMPs to still be measured in the hyperresolving phase. CARS compensatory anti-inflammatory response syndrome, MOF multiple organ failure, SIRS systemic inflammatory response syndrome. Note: This figure is slightly modified from Fig. 1 published in Ref. [438] and Fig. 8.1, shown in Vol. 2 [2], Danger Signals as Diagnostics, Prognostics, and Therapeutic Targets. In: Springer International Publishing AG, 2020; available from http://www.springer.com/978-3-030-53868-2, p. 292; for further references, see there
renal disorder manifested as AKI; (5) hepatic dysfunction manifested, for example, by hepatitis and cholestasis; and (6) hematological symptomatology (dominated by DIC). Pathologically, inflammation is common to all different organ dysfunctions as, for example, documented by the demonstration of cytokines and other inflammatory mediators. Three possible mechanistic pathways leading to sepsis-associated remote organ inflammatory dysfunction have been discussed above in the context of SARSCoV-2-associated sepsis and are repeated here: 1. Systemic spreading of the bacterium concerned into cells of remote organs to activate PRM-bearing cells and promote MAMP-triggered (infectious) proinflammatory responses;
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2. Systemic spreading of locally emitted DAMPs with entry into remote organs to activate PRM-bearing cells and promote DAMP-triggered (“sterile”) proinflammatory responses; 3. Systemic spreading of the bacterium into remote organs to induce cytotoxic effects associated with the emission of DAMPs. This process would activate PRM-bearing cells and promote MAMP/DAMP-triggered proinflammatory responses. Theoretically, in sepsis, all three pathways might work together context-dependently.
5.5.6 Epigenetics in Sepsis The emerging impact of epigenetic regulations on innate immune events—that is, on acute/chronic inflammatory processes—has briefly been outlined and illustrated in Vol. 1 [1], Sect. 24.2, pp. 636–645, as well as Vol. 2 [2], Sect. 5.6, pp. 169–194. In these sections, epigenetic regulation of innate immune inflammatory responses by DNA methylation, histone modifications, long noncoding RNAs, and small noncoding RNAs (miRNAs) were concisely presented. In sepsis, epigenetic regulation has been shown to be a key determinant of gene expression (for recent reviews, see [440, 441]). At the onset of infection, hostpathogen interactions often lead to epigenetic alterations in host cells, whereas epigenetic mechanisms are significantly perturbed during the progression of the septic process. Interestingly, studies of human endotoxemia, established by intravenous administration of bacterial endotoxin to healthy human subjects, revealed changes in the expression of 3714 genes as early as 2 h after exposure [442]. According to current knowledge, the epigenetic mechanisms so far explored play a significant role in sepsis-associated endothelial dysfunction and immunosuppression. Overall, however, most solid evidence for epigenetic mechanisms operating in sepsis derives from in vitro and animal studies, whilst studies in patients are still scarce. In particular, exploration of the possible involvement of MAMPs and DAMPs in the induction of epigenetic modifications would be an interesting future research field for sepsis researchers.
5.5.7 DAMPs and SAMPs as Biomarkers 5.5.7.1 General Remarks Measurement of biomarkers in septic patients is a valuable aid to intensivists in many ways: diagnostically, to differentiate between viral/bacterial/fungal infections and noninfectious conditions such as polytrauma-associated SIRS; prognostically, to establish risk profiles and predict the outcome; and, theranostically, to stratify the patient at admission in ICU for the appropriate targeted treatment at the right time. In this way, the measurement and assessment of DAMPs and SAMPs improve sepsis management and can make a significant contribution to personalized precision medicine.
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From the various DAMPs investigated as biomarkers, here, the focus is directed on HMGB1, S100A8/A9 proteins, and mtDNA.
5.5.7.2 DAMPs HMGB1 The pathogenetic role of HMGB1 in sepsis patients is well documented; accordingly, the levels of HMGB1 in the circulation of these patients were reported to be consistently elevated, and the concentration of circulating HMGB1 positively correlated with the severity and mortality attributed to the septic disease [309, 318– 320]. Of note, these observations on a correlation of HMGB1 with mortality of sepsis patients were recently confirmed and extended by two meta-analyses [321, 322]. Thus, in these analyses, initial high blood HMGB1 levels were found to be significantly associated with short-term mortality of septic patients, whereas subsequently monitored HMGB1 levels on the third and seventh day after admission is encouraged for better evaluation of HMGB1 as a prognostic marker of mortality in sepsis. S100A8/A9 Proteins (Calprotectin) Like HMGB1, S100A8/A9 proteins have also emerged as valuable candidate diagnostic and prognostic biomarkers in sepsis patients [62]. For example, in a recent study, the level of fecal S100A8/A9 proteins was found to correlate significantly with Clostridium difficile infection severity, qualifying this DAMP as a predictive marker for assessing this disease severity [66]. In another clinical study on S100A8/ A9 in patients with bacterial sepsis, the two DAMPs were found to be significantly higher than those measured in patients with viral infections and healthy controls [326]. Moreover, in this analysis, the level of S100A8/A9 was found to be the best predictor of bacterial sepsis compared to other routine biomarkers. Similar observations have been made in other studies on septic shock patients, in which these DAMPs were found to improve the prediction of death [330, 331]. In more recent investigations on ICU patients reported by Larsson et al. [443], the concentrations of S100A8/A9 proteins at admission were shown to be higher in non-survivors than in survivors at day 30. The researchers observed in their studies that these DAMPs were superior to procalcitonin for distinguishing between ICU patients with sepsis and non-sepsis patients. The proteins also revealed higher predictive ability regarding 30-day mortality. Mitochondrial DNA As reported by Itagaki et al. [332], mtDNA and mtFPs can be measured and used as valuable biomarkers in sepsis. In line with this report are studies on septic patients with ARDS, which showed that mtDNA copies are significantly associated with 28-day survival in ARDS patients but not in non-ARDS patients [444]. The authors proposed that mtDNA copies at sepsis diagnosis could be considered an early prognostic biomarker in sepsis-associated ARDS patients. Also, by measuring plasma mtDNA levels in critically ill patients with trauma and sepsis, the researchers found
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that mtDNA concentrations were associated with the incidence of ARDS in the two critically ill populations, suggesting a possible link between circulating mtDNA and lung injury [445]. In support of these observations is a recent clinical study on patients with sepsis and septic shock revealing that a higher plasma mtDNA level is associated with a poor prognosis of sepsis in the emergency room [446]—suggesting to the investigators that this DAMP may serve as a predictor of sepsis for 28-day mortality.
5.5.7.3 SAMPs SAMPs have also already been used as biomarkers in sepsis. For example, reviewing the studies on SPMs, Padovan, and Norling [36] concluded that “monitoring plasma SPM profiles can predict patient outcomes in sepsis, indicating their utility as new early biomarkers that may help stratify patients upon ICU admission.” Also, AnxA1, whose plasma levels were found to be decreased in sepsis patients, may be exploited as a prognostic biomarker. The list could be extended by PGE2, which was shown to decrease in patients with major burns or sepsis, even to a level lower than that in normal control [447]. 5.5.7.4 Concluding Remarks Overall, the use of DAMPs and SAMPs as biomarkers in septic patients can be considered valuable for facilitating diagnosis and prognosis of this life-threatening disease. Indeed, continuous measurement of both DAMPs and SAMPs may be a new avenue to timely detect and recognize the critical phase when the hyperinflammatory response pattern transitions to an immunosuppressive phase, during which MODS occurs.
5.5.8 DAMPs and SAMPs as Therapeutic Targets and Therapeutics 5.5.8.1 General Remarks All kinds of infectious diseases continue to pose myriad threats to mankind. The increasing resistance of the causative organisms against available therapeutics is also an emerging problem. Yet all these troubles may culminate in the development of life-threatening, sometimes fatal, sepsis. Indeed, it remains a huge clinical challenge, and hence, there is an unmet need to identify new therapeutic opportunities to combat this fatal condition. Thus, the therapeutic exploitation of DAMPs and SAMPs in sepsis is of particular importance. Strategically, inhibiting, blocking, or eliminating DAMPs [272] or administration of SAMPs [207, 448] have to be seriously considered and actually were already proposed. However, given the fact that controlled emission of both DAMPs and SAMPs is vital for successful host defense and that it is critical for restoring homeostasis, therapeutic inhibition of DAMPs and/or substitution of SAMPs should be performed under strict caveats and precautions [449].
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5.5.8.2 DAMPs as Therapeutic Targets Given the detrimental role of excessive emission of DAMPs in amplifying infectious inflammation to levels of hyperinflammation, the development of strategies to specifically inhibit or at least mitigate the DAMP-mediated hyperinflammatory response without compromising the innate/adaptive immune response directed against pathogens is the imperative need of the hour. Such pharmacological strategies to inhibit the action of DAMPs currently include the use of mAbs, peptides, decoy receptors, and small molecules but also absorption/adsorption procedures. Some examples of these strategies investigated in preclinical sepsis models are briefly outlined in the following. High Mobility Group Box 1 A glance at the international literature shows that, as expected, the selection of HMGB1 as a therapeutic target is the most popular in diseases, especially sepsis (for recent articles and reviews, see [450–453]). Small Molecules Small molecules in their function as HMGB1 antagonists have been successfully applied in inhibiting HMGB1. For example, earlier studies on the CLP model showed that candidate small-molecule modulators such as inflachromene (a benzopyran-embedded tetracyclic compound that directly binds to HMGB proteins) were able to successfully ameliorate sepsis pathogenesis [450]. Another small molecule, Fe(III)5,10,15,20-tetrakis(4-sulfonatophenyl)porphyrinato chloride (FeTPPS), a small molecule that selectively inhibits HMGB1-mediated CASP11 activation, was also recently reported to significantly attenuate HMGB1- and CASP11-mediated lethality in endotoxemia and bacterial sepsis [454]. Monoclonal Antibodies Using the same experimental model, similar observations were made with the application of polyclonal or monoclonal anti-HMGB1 antibodies. For instance, as reported by Andersson et al. [451], administration of polyclonal or monoclonal anti-HMGB1 antibodies or anti-RAGE monoclonal antibodies was found to significantly improve survival of the animals, even when the first HMGB1antagonist dose is administered up to 24 h after the onset of infection. Glycyrrhizin and Inhibition of CREB Binding Protein (CBP) Bromodomain Glycyrrhizin, the main active ingredient of the traditional Chinese medicine Glycyrrhiza glabra, has also been shown to attenuate sepsis-associated complications. For example, in studies on the CLP model in mice, this substance was observed to ameliorate sepsis-induced ARDS and reduce the NETs formation in lung tissues, which may be associated with the inhibition of the HMGB1/TLR9 pathway [455]. Similarly, in the models of murine LPS-induced endotoxemia and CLP-induced sepsis, selective inhibition of CBP bromodomain by SGC-CBP30 (a molecule that has been shown to bind with low nanomolar affinity to the bromodomains of CBP)
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was found to rescue mice from lethal sepsis through blocking HMGB1-mediated inflammatory responses [456]. S100A8/A9 Proteins S100A8/A9 proteins have also been recognized and selected as substantial therapeutic targets in sepsis. For example, in studies on neonatal sepsis rat models, narciclasine (a natural product present in Amaryllidaceae family of flowering plants) was found to significantly reduce the plasma levels of S100A8/A9 and also suppressed its expression in the liver and lung. The histopathological studies showed that narciclasine prevents organ damage associated with sepsis and improves the survival of neonatal rats [457]. In other lines of studies on the murine CLP model, targeting S100A9 function was shown to decrease the formation of CXC chemokines in circulation and lungs and attenuate sepsis-induced lung damage [458].
5.5.8.3 Blood Purification Techniques: A New Approach to Eliminating DAMPs on the Horizon With the development of extracorporeal blood purification techniques, it is now possible to eliminate DAMPs under septic conditions in the same ways as inflammatory mediators such as cytokines. And indeed, this new avenue to get rid of DAMPs is already much discussed. Thus, Köhler et al. [459] state in their abstract: Under pathologic conditions, the massive elevation of cytokine levels (“cytokine storm”) could not be controlled until the recent development of hemoadsorption devices that are able to extract a variety of different DAMPs, PAMPs, and metabolic products from the blood. CytoSorb® has been approved for adjunctive sepsis therapy since 2011. And Moriyama and Nishida [460] argue: Considering the pathogenesis of sepsis, the targets of blood purification are considered to be LPS and immune cells, cytokines, and DAMPs. However, science moves fast: these reasonable predictions have already been caught up by the first step toward reality: Burow et al. [461] recently reported on an observational case series showing that six neurosurgical patients with septic shock demonstrated clinical improvement after a combination of standard care and blood purification—albeit without measuring DAMPs in this study. 5.5.8.4 SAMPs as Therapeutics and Therapeutic Targets in Sepsis SAMPs as Therapeutics in the Early Hyperinflammatory Phase SAMPs may be applied as therapeutics in the early hyperinflammatory phase of sepsis. In this context, Padovan and Norling argue [36]: Given their potent biological actions in promoting bacterial clearance, and also organ protection in animal models of sepsis, respiratory distress, and heart failure, SPMs offer promising new therapeutics for critical illness. Indeed, development and testing of stable analogues and mimetics of SPMs with enhanced pharmacokinetics and pharmacodynamics is ongoing, and initial clinical evidence of protective actions of SPMs in human diseases is emerging.
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Blockade of SAMPs in the Late Sepsis-Associated Immunosuppressive Phase If the model of “hyperresolution”/immunosuppression in sepsis as an expression of overshooting SAMPs is correct, blockade or elimination of SAMPs, especially SMPs, under strict observance of the DAMP/SAMP ratio in relation to the homeostatic window could theoretically be considered. However, such clinical trials have not been designed so far, but they may become a clinical reality in the near future. Nevertheless, in this context, it appears at least worth mentioning that, in one experimental series on a murine CLP model [390], ketoprofen treatment was found to inhibit the production of the SAMP PGE2, thereby qualifying this agent as an attractive target to prevent secondary infections in the immunocompromised septic patients. In another model of sepsis-induced AKI in mice [391], tenuigenin, a natural product isolated from Polygala tenuifolia root, was also shown to inhibit the production of PGE2. In more recent experiments, targeting the 15-ketoPGE2—prostaglandin reductase 2 axis was demonstrated to mitigate systemic inflammation and improve the survival of septic mice (nota bene: 15-keto-PGE2 is a PGE2 metabolite whose further processing is catalyzed by prostaglandin reductase 2).
5.5.8.5 Concluding Remarks Implementation of treatment of septic patients taking advantage of DAMPs and SAMPs as therapeutic targets and therapeutics may prove complicated and is probably feasible only with strict daily measurement of the DAMP:SAMP ratio. Theoretically, such as regimen would depend on the respective phase of the disease: initial hyperinflammatory stage (DAMPs:SAMPs ratio >1): Blocking/elimination of DAMPs as therapeutic targets and administration of SAMPs as therapeutics; subsequent immunosuppressive stage (DAMPs:SAMPs ratio 400 endogenously modified proteins was established. Remarkably, >20 residue sites with endogenous lipid-derived electrophile modifications were identified in ferroptotic cells, specifically, a novel cysteine site of modification on the voltage-dependent anion-selective channel protein 2 [197]. In sum, here we have the constellation that injury-induced subroutines of RCD simultaneously promote the development of autoantigens and emission of Class IA DAMPs, which are capable of generating autoimmunostimulatory DCs to activate autoreactive T cells resulting in an autoimmune response.
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Principles of Autoantigen Release from Necrotic Cells and the Role of Posttranslational Modifications Accordingly, and in principle, there are at least three possible ways through which cellular components released from cells succumbing to RN may act as autoantigens (Fig. 6.6a–c). 1. Released native proteins such as native DNA are engulfed by APCs and presented as bona fide self antigenic peptides on MHC molecules to naïve bona fide autoreactive T cells which have escaped central and peripheral self tolerance mechanisms or whose TCR/TCR signaling may be normal or aberrant in terms of genetically/epigenetically (?) altered (Fig. 6.6a) [198, 199] (true breakdown of self tolerance). Of note, here, it is the initial cell injury (e.g., leading to RCD) that induces autoimmunity. 2. Released native proteins are engulfed by APCs but modified (e.g., by intracellular proteases) during (genetically/epigenetically?) antigen processing and thus presented as altered-self antigenic peptides on MHC molecules to altered-self- reactive T cells (which—as positively selected thymocytes—were allowed to leave the thymus like nonself-reactive T cells) (Fig. 6.6b). Of note, such a scenario is exemplified by islet proteins which can be deamidated by tissue transglutaminase during antigen processing within the APC to be presented as an altered-self antigen [200]. 3. Proteins released, for example, from RN, such as NETosis [201] or ferroptosis [202], are already (genetically/epigenetically-mediated?) PTM-proteins which are engulfed by APCs and presented as altered-self antigens on MHC molecules to altered-self-reactive T cells (which were allowed to leave the thymus like nonself-reactive T cells) (Fig. 6.6c). The increasingly appreciated role of PTMs in the context of RCD for the development of autoimmune diseases deserves some more remarks. In fact, as mentioned already above and to stress again here, there is accumulating evidence indicating a central role of PTMs in the generation of autoantigens in terms of altered-self antigens or neoepitopes, a concept previously described as “autoantigenesis” [94, 203– 205]. For example, during the last years, considerable attention has been paid to citrullination because of its role in inducing anti-citrullinated proteins/peptide antibodies (ACPA), a class of autoantibodies with diagnostic, predictive, and prognostic value for RA. Moreover, and typically, as recently reviewed [206], oxidative stress to cells and tissues may provoke PTMs of proteins, both directly and indirectly, as well as may potentially lead to aberrant gene expression. An impressive example refers to ROS–facilitated carbonyl protein modifications. In addition, oxidative stress reportedly leads to a number of non-enzymatic spontaneous modifications, including deamidation and isoaspartate modification, as well as enzyme-mediated citrullination of self-proteins. As also pointed out [206], ROS were demonstrated to have direct effects on epigenetic changes such as DNA methylation, leading to influences in gene expression, chromosome inactivation, and the silencing of genetic elements (see also below).
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a
Fig. 6.6 (a) Simplified schematic diagram of a narrative model of “autoantigenesis” illustrating signal 1 (self peptide/MHC) and signal 2 (DAMP-upregulated costimulatory molecules) to trigger activation of naïve autoreactive T cells expressing normal or (epigenetically induced) aberrant TCR/TCR-signaling. Released native proteins are engulfed by APCs and presented as bona fide self antigenic peptides on MHC molecules to naïve bona fide autoreactive T cells which have escaped central and peripheral self tolerance mechanisms or whose TCR/TCR signaling may be normal or aberrant in terms of genetically/epigenetically (?) altered (true breakdown of self tolerance). Of note, here, it is the initial cell injury (e.g., leading to RCD) that induces autoimmunity. mDC mature dendritic cell, MHC major histocompatibility complex, P peptide, PRM pattern recognition molecule, RCD regulated cell death, TCR T cell receptor, Th1/Th17 T helper type 1/17 cells. (Sources: [198, 199]). Note: This figure corresponds to Fig. 2 published in: Land WG. Role of DAMPs and cell death in autoimmune diseases: The example of multiple sclerosis. Genes&Immunity 2023, in press; https://doi.org/10.1038/s41435-023-00198-8. (b) Simplified schematic diagram of a narrative model of “autoantigenesis” illustrating signal 1 (altered-self peptide/MHC) and signal 2 (DAMP-upregulated costimulatory molecules) to trigger activation of naïve altered-self reactive T cells expressing normal TCR/TCR-signaling. Released native proteins are engulfed by APCs but then modified (e.g., by intracellular proteases) during (genetically/epigenetically?) antigen processing and presented as altered-self antigenic peptides on MHC molecules to altered-self-reactive T cells (which—as positively selected thymocytes—were allowed to leave the thymus like nonself-reactive T cells). Of note, such a scenario is exemplified by islet proteins which can be deamidated by tissue transglutaminase during antigen processing within the APC to be presented as an altered-self antigen. Ag antigen, a-sp altered-self peptide, mDC mature dendritic cell, MHC major histocompatibility complex, P peptide, PRM pattern recognition molecule, RCD regulated cell death, TCR T cell receptor, Th1/Th17 T helper type 1/17 cells. (Source: [200]). (c) Simplified schematic diagram of a narrative model of “autoantigenesis” illustrating signal 1 (RCD-modified altered-self peptide/MHC) and signal 2 (DAMP-upregulated costimulatory molecules) to trigger activation of naïve altered-self reactive T cells expressing normal TCR/ TCR-signaling. Proteins released, for example, from RN such as NETosis or ferroptosis, are already (genetically/epigenetically-mediated?) PTM-proteins which are engulfed by APCs and presented as altered-self antigens on MHC molecules to altered-self-reactive T cells (which were allowed to leave the thymus like nonself-reactive T cells). Ag antigen, mDC mature dendritic cell, MHC major histocompatibility complex, P peptide, PRM pattern recognition molecule, RCD regulated cell death, TCR T cell receptor, Th1/Th17 T helper type 1/17 cells. (Sources: [201, 202])
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b
c
Fig. 6.6 Continued)
Notably, there is increasing evidence suggesting that oxidative stress-elicited PTMs of proteins cause them to function as altered-self antigens, which, together with DAMPs released from oxidative stress-induced, lipid peroxidation-mediated ferroptosis, may represent a powerful mechanism to induce autoimmune diseases [206–210] (Fig. 6.7). (It is worth noting here—as described in Vol. 1 [24], Sect. 13.3.2, pp. 277–282—that oxidative PTMs of proteins and lipids result in the development of OSEs, which represent a powerful subclass of DAMPs [Subclass IIB-1 DAMPs], capable of instigating and maintaining efficiently innate immune efferent and adaptive autoimmune responses.)
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ROS production (in excess)
Lipid peroxidation
Oxidation-induced PTMs of proteins (Altered-self antigens)
Oxidation-induced Ferroptosis (Release of Class IA DAMPs)
autoimmunostimulatory DCs (upregulated signal 1, 2, 3)
activation of “altered-self “- reactive T cells
autoimmune response Æ autoimmune disease
Fig. 6.7 Schematic diagram of a conceptual model of oxidative stress-induced autoimmunity. Increasing evidence suggests that oxidative stress-elicited PTMs of proteins cause them to function as altered-self antigens, which, together with DAMPs released from oxidative stress-induced, lipid peroxidation-mediated ferroptosis, may represent a powerful mechanism to induce autoimmune diseases. DCs dendritic cells, PTMs post-translational modifications. (Sources: [206, 208, 209])
As also outlined previously and above, a critical role of PTMs in the generation of autoantigens in terms of altered-self antigens or neoepitopes can be assumed to occur during RN [201, 202, 211]. The underlying mechanism can be clearly argued: At first, cell/tissue injury leads to a certain subroutine of RN that is associated with PTMs to proteins. Since these PTMs arise in the periphery, they may not occur in an identical manner in the thymus or the bone marrow and, thus, these proteins never tolerize developing thymocytes or developing B cells [94]. Consequently, when PTMs arise during various infectious or sterile injury-induced innate cellular effector responses associated with any RN subroutine, these altered-self proteins are engulfed and processed by APC, which then present the altered-self peptides on MHC molecules to autoreactive = altered-self-reactive T and B cells. The interesting question here is whether or not the appearance of PTMs during RN is directly an action of DAMPs known to induce RN (cf. Fig. 6.6c).
6.3.2.7 Concluding Remarks According to the danger/injury model, autoimmunity can be induced by self antigens in the presence of DAMPs. To be distinguished from this concept, there is the proposal of various models of “autoantigenesis” that refer to the action of altered self antigens. As curtly touched on here, the majority of altered-self antigens are post-translationally modified proteins, indicating that T cells specific for those PTM-induced altered-self antigens do their normal job in recognizing nonself
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antigens. However, to induce an autoimmune response, these altered-self antigens also need the presence and action of DAMPs. Apart from this, another, more important momentum needs to be highlighted in the context of the danger/injury model: The original idea that environmental factors are mainly responsible for the generation and action of autoimmunity-inducing autoantigens is slowly condensing into the notion that stress/injury-induced emission of DAMPs is the true “autoimmunity-promoting” factor, irrespective of—and to reiterate—whether a self or nonself antigen acts specifically as an autoantigen.
6.3.3 Environmental Factors Promoting the Emission of DAMPs Through Induction of Regulated Cell Death 6.3.3.1 General Remarks As published so far, environmental factors account for up to 70% of all ADs [212]. Conceptually and in view of the danger/injury model and in close adherence to a tautological approach [11], environmental factors are defined as agents which produce endogenous DAMPs or act themselves as exogenous DAMPs. And as already stressed repeatedly, the ad hoc presence and action of DAMPs is mandatory to turn iDCs into autoimmunostimulatory DCs capable of activating autoreactive T cells (cf. Fig. 1.2). Thus, the ability of DAMPs to shape adaptive immunity has already been documented in some human ADs. For example, DAMPs emitted in the course of RCD (e.g., apoptosis, necroptosis, pyroptosis, and NETosis) were shown to be involved in the pathogenesis of systemic autoimmune manifestations such as SLE and RA as well as organ-specific autoimmune disorders such as MS and T1DM [110, 213–221] The emerging pathogenetic key topic will be resumed in the sections concerned. Here, some selected environmental factors are examined in regard to their potential role in acting as exogenous DAMPs and provoking the emission of endogenous DAMPs (cf. Fig. 6.5). 6.3.3.2 Infections Infectious agents and infections have long been the most well-studied environmental factors involved in the pathogenesis of ADs [222–224]. One of the best-studied examples of infection-induced autoimmunity is that of acute rheumatic fever presenting several weeks after infection with Streptococcus pyogenes [225]. Other examples include the associations between Helicobacter pylori and autoimmune gastritis [226], as well as between Trypanosoma cruzi and Chagas’ cardiomyopathy [227]. Notably, the general opinion is that not a single pathogen per se but the sum of all infections from birth onwards contributes to the induction of autoimmunity. Moreover, viral infections such as EBV infection have been documented as risk factors for some ADs [228]. Per definition, however, any pathogen in question causes infectious cell stress and/or tissue injury associated with the emission of DAMPs, very often associated with the event of RCD as a further potent event of DAMPs release. This issue has been comprehensively dealt with in Sects. 3.6 and 3.7. Of note, reports on COVID-19 infection to trigger autoimmune disorders such as SLE, Guillain–Barré syndrome, antiphospholipid Syndrome, and Kawasaki disease
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in genetically predisposed individuals have received considerable attention during the writing of this book [229–232]. Also, and remarkably, there is increasing evidence suggesting that the long COVID-19 syndrome reflects autoreactive → autoimmune phenomena [233]. The background of these serious post-COVID-complications seems to be clear with respect to reports about the emission of large amounts of DAMPs. Both DAMPs and SARS-CoV-2 antigenic proteins together trigger activation of immunostimulatory DCs to initiate an adaptive immune response (compare Sects. 3.7.4.6, 3.7.5.5, and 5.4.2.3; and [234]). On the other hand, the transformation of SARS- CoV-2 viral antigens into autoantigens is still not fully understood. The currently ongoing debate includes the discussion of molecular mimicry [232, 235], epitope spreading [236], and bystander activation [237].
6.3.3.3 Xenobiotics Of major interest to clinicians is the appearance of ADs following exposure to pharmaceutical agents. Notably, this subject has been extensively reviewed by Xiao and Chang [238]. Since sulfadiazine-associated lupus-like symptoms were first described in 1945, certain drugs have been reported to interfere with the immune system and induce a series of ADs (named drug-induced autoimmunity [DIA]). In addition to lupus, other major ADs, including vasculitis and arthritis, have also been associated with drugs. Among those drugs, procainamide and hydralazine are considered to be associated with the highest risk of developing lupus, while quinidine has a moderate risk, and all other drugs have a low or very low risk [238]. Concerning their “autoimmune disease-mediating effect,” one should cautiously realize that, basically, all these drugs are more or less associated with the induction of cell and/ or tissue damage; that is, they possess potential DAMP-inducing capacities. As an example of many and representative of many drugs prone to induce autoimmunity, the effect of hydralazine, known to be associated with the highest risk for developing lupus, is briefly examined here. For a long time, it has been known that the cytotoxic effect of hydralazine is associated with necrosis such as myocardial necrosis [239, 240]. In addition, recent studies on human leukemic T cells revealed that hydralazine can induce caspase-dependent apoptosis and trigger the intrinsic mitochondrial apoptotic pathway [241] (for this pathway, also compare Vol. 1 [24], Sect. 19.2.2.2, Fig. 19.3, pp. 431/432). In these studies, it was also demonstrated that hydralazine treatment can trigger DNA damage. Remarkably, in other lines of studies, the generation of free radicals derived from the oxidation of hydralazine was reported to directly induce DNA cleavage [242]. Together, these studies are in support of the notion that hydralazine may cause cellular DNA damage associated with the generation of DNA fragments acting as both autoantigens and DAMPs sensed by DNA receptors such as cGAS—a scenario that might induce autoimmune responses (for cGAS signaling, see Fig. 4.7) Moreover, secondary defective clearance of hydralazine-induced apoptotic cells (see also below) may also contribute to emission of DAMPs.
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6.3.3.4 Vaccines Vaccines and autoimmunity have been suggested to be linked in genetically predisposed individuals. Although the described side effects thus far have been mostly transient and acute, vaccines have been shown to elicit autoimmune responses in rare instances—in regard to the formation of autoantigens, likely via the mechanisms of molecular mimicry [243]. Activation of autoreactive DCs under these circumstances appears plausible in view of the notion that vaccines, at any rate, contain adjuvants, and adjuvants act as DAMPs, thereby promoting innate immune and adaptive immune responses [244]. This implies that, in the presence of a mimicry- induced autoantigen or an otherwise generated altered-self or self antigen, immunogenic DCs may be activated to trigger autoimmune responses and ADs. In this context of interest is a recently published new autoinflammatory/autoimmune syndrome induced by adjuvants (ASIA) that includes post-vaccination phenomena, macrophagic myofasciitis, Gulf War syndrome, and siliconosis [245]. This syndrome is characterized by nonspecific and specific manifestations of autoimmune disease. The main substances associated with ASIA are squalene (Gulf War syndrome), alum (post-vaccination phenomena, macrophagic myofasciitis), and silicone with siliconosis. Mineral oil, guaiacol, and iodine gadital are also associated with ASIA. One may speculate that all those rare circumstances, besides the formation of autoantigens, are probably associated with the emission of DAMPs. Notable, similar to COVID-19 infection (see above), the potential role of mRNA vaccines against SARS-CoV-2 in triggering autoimmune disorders in genetically predisposed individuals has received considerable attention during the writing of this book [246–249]. The background of this phenomenon seems to be clear: as is well known, mRNA vaccines against viruses promote a robust antiviral innate/adaptive immune response because they exert a dual function: (1) the mRNA encodes the viral antigenic protein of interest, and (2) operates—together with LNPs—as a potent exogenous DAMP that is sensed by various endosomal and cytosolic PRRs (see Sects. 1.2.5.2/1.2.5.3 and Table 1.3). The two functions of mRNA plus the action of LNPs together activate PRR-bearing immunostimulatory DCs, which initiate and propagate an adaptive immune response. However, as discussed for the disease, the transformation of the viral antigen into an autoantigen is not entirely clear and is still debated. In particular, molecular mimicry, epitope spreading, and bystander activation are currently discussed [248, 250–252]. 6.3.3.5 Heavy Metals Heavy metals, reportedly known to contribute to the development of ADs [253], may operate as toxic substances to induce DAMPs able to activate DCs. For example, transition metal ion sensing by TLR4, including nickel, cobalt, and palladium, has been shown to effectively stimulate human DCs [254]. As depicted in Table 1.3, these heavy metals are defined as exogenous IVC-1 DAMPs because they are known to promote allergic diseases.
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6.3.3.6 Lifestyle Habits, for Example, Cigarette Smoking The association between smoke habit and autoimmunity was hypothesized a long time ago. In fact, the smoke has been found to play a pathogenic role in certain ADs and is regarded as the most well-recognized risk factor for RA and SLE [255]. Several pathways of autoimmunogenicity of smoke have been discussed. For example, smoking, by provoking oxidative stress, may contribute to lupus disease by dysregulating DNA demethylation and upregulating immune genes, thereby leading to autoreactivity [255]. In addition, smoke such as cigarette smoke contains several TLR-stimulating DAMPs such as LPS [256] and S100A8/A9 proteins [257, 258] which are known to elicit an innate immune response and activate iDCs. (By the way, and again, one may argue here that LPS does not act as a PAMP but as an exogenous DAMP, also compare Vol. 1 [24], Sect. 11.3, pp. 201–204.) In addition, recent studies demonstrated that cigarette smoke induces dysfunction of both intrinsic and extrinsic apoptotic programs in neutrophils, leading to the subsequent release of DAMPs to activate proinflammatory responses of the airway epithelium and promote neutrophilic airway inflammation in a self-augmenting process [259]. Moreover, more recent in vitro studies on differentiated primary bronchial epithelial cells provided evidence indicating that cigarette smoke induces DAMPs such as extracellular dsDNA and RNA [260]. 6.3.3.7 Ultraviolet Radiation Finally, ultraviolet radiation (UVR) wave lengths of sunlight have also been observed to trigger or exacerbate a number of ADs, including SLE [261, 262]. Ultraviolet radiation is known to lead to DNA damage often associated with cell death, thereby promoting the generation of autoantigens and the release of DAMPs. Thus, UVR-induced emission of DNA and HMGB1 was shown to trigger innate immune/inflammatory pathways, respectively [262, 263]. 6.3.3.8 Nutrition (Gluten, Iodine, and Vitamin D) A good example of the importance of non-infectious environmental agents is the relationship between gluten ingestion and CeD, an autoimmune disorder triggered by gluten ingestion in genetically predisposed individuals. Gluten is a protein part of wheat flour consisting of (non-digestible) gliadins (α-, β-, γ-, and ω-gliadins) and glutenin. Pathogenetically, involvement of a genetic constellation (HLA)-DQ2 and HLA-DQ8), the action of an autoantigen (tissue transglutaminase [TG2]), and the environmental trigger (gluten) have meanwhile been defined. Other environmental factors such as enteric infection and dysbiosis may contribute to the elicitation of the autoimmune disease (for further reading, see [264–267]). A few pathogenetic key events of this scenario should be concisely addressed: The binding of gliadin fragments in terms of non-digestible peptides on enterocytes allows them to transit from the lumen to the lamina propria to trigger apoptosis of intestinal cells associated with the release of intracellular contents, including the enzyme TG2 and gliadin peptides. These peptides are in part posttranslationally modified, that is, deaminated by and complexed with TG2 in order to be engulfed and processed by
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APCs such as DCs. The processed antigenic molecules are then presented on MHC II—HLA-DQ2 and -DQ8 molecules to CD4+ T cells, which, in turn, drive activation and maturation of B cells, producing IgM, IgG, and IgA antibodies against TG2 (for further reading, see [264–267]). The relationship of gluten to a potential generation of DAMPs needed to activate DCs is not quite clear. In one study on macrophages, the 33-mer gliadin peptide, an unprocessed peptide of gliadin, was demonstrated to interact with TLR2 and TLR4 to promote the secretion of proinflammatory cytokines [268]. This observation would suggest that 33-mer gliadin peptide—and probably other gliadin fragments?—may operate as exogenous DAMPs. In this context, other lines of recent studies are of interest, revealing that the α-amylase/trypsin inhibitors (ATIs) CM3 and 0.19, known as pest-resistance molecules in wheat, act as strong activators of innate immune responses in monocytes, macrophages, and DCs [269]. ATIs were shown to engage the TLR4-MD2-CD14 complex leading to the upregulation of maturation markers and to elicit the release of proinflammatory cytokines in cells from celiac and non-celiac patients and in celiac patients’ biopsies. Mice deficient in TLR4 or TLR4 signaling were found to be protected from intestinal and systemic immune responses upon oral challenge with ATIs. According to the authors’ conclusion, these findings define cereal ATIs as novel contributors to CeD [269]. In other words, ATIs may also be defined as a member of exogenous nutritional DAMPs. In this context, it is also interesting to note that higher dietary iodine consumption was shown to increase the incidence and severity of autoimmune thyroid disease (AITD). In this disorder, thyroid self antigens such as thyroid peroxidase, thyroglobulin, sodium (natrium) iodide symporter, and Pendred syndrome gene have been detected to provoke autoantibodies in patients suffering from AITD [270, 271]. Interestingly, iodine incorporation in thyroglobulin was demonstrated to augment the antigenicity of this molecule (better: immunogenicity?) by increasing the affinity of its determinants for the TCR or the MHC-presenting molecule, either altering antigen processing or by affecting antigen presentation [272]. Other lines of recent in vitro studies demonstrated that PRR-bearing thyroid cells can respond to MAMPs and DAMPs such as dsDNA, thereby launching innate immune responses [273]. On the other hand, it is known that high concentrations of dietary iodine cause thyroid cell injury [274]. These observations lent support to the notion that iodine-mediated injury leads to the emission of DAMPs that, in turn, may activate thyroid-invading DCs—defining iodide in access as an indirectly operating DAMP. However, what exact classes of DAMPs are induced by iodine has to be explored in further studies. Also of interest to the clinician is the relationship between vitamin D levels and the immune response. Epidemiological studies have demonstrated that reduced levels of vitamin D lead to an increased risk for loss of tolerance. In fact, reduced vitamin D has been suggested to be involved in the development of ADs such as RA, MS, SLE, asthma, and IBD. Nevertheless, the mechanism for this association has yet to be elucidated [275, 276].
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To approach a possible mechanistic explanation, one may refer to emerging evidence that supports the notion that vitamin D enhances immunity, providing protection against pathogens, while, concomitantly, it exerts immunosuppressive effects by preventing the detrimental effects of prolonged inflammatory responses to the host [277]. In addition, one might interpret studies showing that 1,25(OH)2D3, the most active metabolite of vitamin D, and its receptor can regulate human DC maturation [278]. In fact, exposure of differentiating human and mouse monocytes to 1,25(OH)2D3 was found to increase the expression of molecules involved in antigen capture and inhibit DC differentiation and maturation, thereby impairing stimulatory capacity for CD8+ T cells. Furthermore, these tolDCs were shown to stimulate an increase in the number of Tregs, directly affect CD4+ T cells, upregulate IL-10, as well as to reduce TNF- and IFN levels. As discussed by the authors [278], these molecular changes may play a role in the inhibition and interaction between DCs and T cells in mice and humans. On the other side, murine vitamin D deficiency reportedly results in the overproduction of Th1 and Th17 immune responses and a reduction in the amount of tolDCs and Tregs [278]. In view of these data, it is tempting to speculate—in terms of an argumentum e contrario—that reduced levels of vitamin D are associated with the decreased potential of tolDCs to maintain self tolerance and, thus, may allow even the lowest suboptimal levels of emitted DAMPs to activate DCs to present autoantigens to autoreactive T cells. In other words: lack of 1,25(OH)2D3 may markedly reduce activation of signaling programs in DCs that yield in priming of regulatory and antiinflammatory T cell responses to “self.” Consequently, murine vitamin D deficiency will result in a reduction in the amount of tolDCs and Tregs to “self,” thereby allowing the instigation of Th1 and Th17 autoimmune responses.
6.3.3.9 Oral Contraceptives and Postmenopausal Hormone Therapy Oral contraceptives and postmenopausal hormone therapy reportedly promote the development of ADs [279–281]. The relationship to the potential emission of DAMPs is also not quite clear. However, one should keep in mind that oral contraceptive use reportedly induces many changes in hematological and plasmatic markers, modifying hormonal levels, endothelial function, inflammation index, and some redox state parameters, producing a perturbation of the internal milieu that impacts macrophagic function [282]. Thus, one may argue that all these activities may be theoretically linked to the emission of various members of DAMP classes. Regarding postmenopausal hormone therapy, one may discuss whether estrogens could contribute to the emission of DAMPs via the promotion of DNA damage associated with a defective DDR [283, 284]. 6.3.3.10 Air Pollution The pathogenic role of airborne PM/pollution in diseases exemplified by respiratory virus infection has already been outlined in Sect. 5.4.7. Airborne PM/pathogenic pollutants, as well as asbestos and crystalline silica, are classified as exogenous IVA and IVE DAMPs, respectively (Table 1.3). They have been shown to trigger activation of the NLRP3 inflammasome, associated with inflammasome-dependent proinflammatory processes, as well as, even more important, regulated necrosis in the
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form of pyroptosis as a critical source of subsequent endogenous DAMPs emission. There is also an emerging role of air pollution in ADs [285, 286]. Interestingly, in contrast to the concept of exogenous DAMP-induced activation of the NLRP3 inflammasome, current research on this topic has followed another approach that focuses on the role of the aryl hydrocarbon receptor (AHR). The AHR is a ligand- activated transcription factor that responds to toxicants present in PM. Once activated by these ligands, the receptor triggers signaling pathways that are involved in inflammatory processes and adaptive immune responses and drives the balance between effector Th17 cells and Tregs, ultimately participating in the pathogenesis of ADs. Polluted air can cause a T cell imbalance, production of proinflammatory cytokines, airway damage, oxidative stress, and epigenetic changes to instigate and exacerbate ADs (for further reading, see [285, 286]).
6.3.3.11 Concluding Remarks In attempting to investigate and define the role of DAMPs in environmental factors known to be implicated in the development of ADs, it is evident that only insufficient data exist to provide comprehensive information. On the other side, the topic is especially important because it is generally believed that environmental factors not only promote the emission of DAMPs but also cause epigenetic changes, as, for example, shown for air pollution [287] (see below for more details). Certainly, further larger prospective studies are needed to establish a more solid basis for this concept.
6.3.4 Role of the Microbiota in the Pathogenesis of Autoimmune Diseases 6.3.4.1 General Remarks The gut microbiota is permanently exposed to environmental forces and has been considered part of the exposome [288] (for the microbiota, compare Sect. 4.7.3.1). It can, for example, be influenced by the motility of the gastrointestinal tract, smoking, and intake of alcohol, coffee, and pharmaceutical medications. On the other hand, the gut microbiome interacts not only with environmental factors but also with the host and other organisms. Such emerging relationships between the microbiota, host immune responses and ADs (including but not limited to T1DM, RA, and MS) have given rise to becoming a subject of intense attention [289–298]. This issue is generally dealt with under the topic of environmental factors. In regard to its peculiar role, however, its discussion deserves a separate section (for the microbiota, including more references, see Vol. 1 [24], Chap. 34, pp. 829–835). Indeed, with improved methods, including sophisticated sequencing and high-throughput technology, it has been demonstrated that changes in the microbiota, even in normal hosts, are pivotal to normal immune development and homeostasis. In view of this recent knowledge, it has become obvious that pathologies such as ADs can reflect the compromise of the normal composition of the commensal community. In strong support of this assumption are studies on multiple animal models of human ADs suggesting the direct involvement of commensal microbiota in disease
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development. For example, under germ-free conditions, no such disease is developing in the animal models of RA, MS, and IBD, supporting the notion that the presence of commensals is a condition sine qua non for the manifestation of the disease. On the other hand, under such conditions, some disorders are only attenuated. As reviewed [299], in some models of human ADs, causality is reinforced by the reintroduction of specific microbes restoring the disease severity. Intriguingly, some members of the gut microbiota have been directly linked to autoimmune disorders. In addition, changing a single bacterial species and/or the entire commensal community has been demonstrated to alter the outcome of a specific AD due to the imbalance of pathological/protective immune responses.
6.3.4.2 Changes in the Composition of the Commensal Community Preceding the Onset of Disease As reviewed [84], changes in the gut microbiome were observed to precede the onset of certain autoimmune disorders. For example, at the taxonomic level, Bacteroides is associated positively with islet autoimmunity for T1DM, while Firmicutes is associated negatively. Butyrate-producing bacteria may be protective, while those that produce other short-chain fatty acids may lead to autoimmunity. These observations may relate to the effects of bacterial fermentation products on gut epithelial integrity. Other lines of studies revealed changes in Firmicutes and Bacteroidetes in the upper small bowel mucosal and fecal flora to be particularly associated with Crohn’s disease. Interestingly, the oral commensals Porphyromonas gingivalis and Prevotella nigrescens, as well as the intestinal microbiota-associated microbes Bacteroidetes and Bifidobacterium, have been correlated with the onset and course of RA. In addition, recent data have demonstrated that changes in the neonatal gut colonization of segmented filamentous bacteria influence generalized autoimmunity even into adult life. 6.3.4.3 Mechanisms of Commensal Involvement in the Promotion of Autoimmunity In regard to mechanisms of the involvement of the microbiota in the promotion of autoimmunity, the focus is here directed on the model that an altered-self antigen in the presence of injury-induced DAMPs activates host DCs that interact with naïve altered-self-reactive T cells to elicit an autoimmune response. Of note, however, the exact role of the microbiota in regard to this scenario is still elusive. Several mechanisms have been suggested to operate, including the proposal that aberrant/abnormal innate sensing of the gut microbiota through TLRs and inflammasomes may contribute to intestinal dyshomeostasis by stimulating the development/function of both regulatory and inflammatory cells; a scenario that evokes disturbances in the finetuning that governs host-microbiota interactions leading to both local and systemic inflammatory and ADs [297]. Another unproven possibility would be that harmless commensal that do not induce DAMPs to transform into harmful pathogens that do induce DAMPs, which then promote autoimmunity along with altered-self proteins. Of high interest in the field of mechanistic explanations of the phenomenon is a review by Lerner et al. [292] pointing to a role of the microbial enzymatic
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machinery that is involved in the PTM of proteins [292]. Thus, the authors hypothesize that the enzymes produced by the dysbiotic microbial community may process luminal proteins differently than that of the normal community. Such an abnormal PTM of proteins may produce neoepitopes in the sense of altered-self antigens that are autoantigenic and may induce systemic autoimmune responses resulting in ADs. Such a mechanistic, dysbiosis-based explanation may be offered for alcohol- or coffee-promoted development of ADs which are suspected to occur but not confirmed by large studies [107, 109]. As reported, intestinal microbiota signatures change in alcoholic patients [300]. On the other hand, the toxic effect of alcohol is well known and has been shown to induce the emission of DAMPs such as uric acid and ATP [301]. Again, a similar explanation may be applied to high coffee consumption discussed to increase the susceptibility to developing AD. Thus, as demonstrated in experiments on high-fat-fed rats, coffee consumption is also able to alter the composition of the gut microbiota [302]. Furthermore, in experiments on rats, the capacity of coffee to induce DAMPs could be demonstrated with the proof of HMGB1in the lungs, as demonstrated by an up-regulation of HMGB1 mRNA [303]. Nevertheless, as concluded by Anaya et al. [107, 109], further studies from the perspective of metabolomics, proteomics, and genomics are needed to clarify the effect of these environmental factors on autoimmune diseases.
6.3.4.4 Concluding Remarks Together, the few studies cited here lend growing credence to the notion that the microbiota, via its interaction with environmental factors on one side and the host’s immune system, on the other side, plays a participating role in the development of ADs. The question then is: would it be possible to treat or prevent ADs by conversion of a given dysbiosis into a normal healthy microbiota, for example, through the application of a special “probiotic” diet. To efficiently realize such a therapeutic strategy, however, much more work is needed to fully understand the complex mechanisms of those disturbed interactions between the microbiota, the environment, and the host (for recent reviews, see [304, 305]).
6.3.5 Résumé In sum, this patchy collection of data provides new perspectives on how environmental factors may impact autoimmunity in genetically susceptible individuals. Even at first glance, it becomes already obvious that recent research has unearthed a considerable variety of environmental factors of different origins. However, by applying the tautological approach to the role of these triggers in AD pathogenesis, it is possible to identify and define a common mode of action among these agents when interpreting all environmental factors as DAMPs or DAMP-inducing agents. Needed for activation of DCs to initiate an autoimmune response, they may operate intrinsically as exogenous DAMPs or elicit endogenous DAMPs in the host. It is hoped that this new view on the pathogenesis of ADs will stimulate further progress
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in the research field that can be translated into preventive and intervention strategies to counter autoimmune diseases.
6.4 Hereditary Factors in the Etiopathogenesis of Autoimmune Diseases 6.4.1 Introductory Remarks Though the environmental factor-associated generation of a bona fide self antigen or an altered-self antigen together with simultaneous emission of DAMPs represent the very first mandatory stimulus for instigation of ADs, there must be a genetic susceptibility that turns this stimulus—that is normally harmless and non-pathogenic for most people on our planet—into an autoimmune response. However, the incomplete concordance rate of the autoimmune disease in monozygotic twins ranging between 12 and 67% and the presence of a strong genetic association in some patients only have convinced researchers in the field of ADs to assume that a third factor must operate. This momentum has been identified as epigenetic modifications, which appear to represent the link between genetic and environmental factors (DAMPs?) influencing the onset and the evolution of autoimmune diseases. In fact, experimental data strongly suggests a complex interaction between the exposome (or environmental influences) and genome (genetic material) to produce epigenetic changes (epigenome) that can alter the expression of genetic material and lead to the development of disease in the susceptible individual [106, 306–310]. Having outlined the environmental scenario above, genetics and epigenetics should be briefly examined in this section.
6.4.2 Genetics 6.4.2.1 General Remarks In the field of genetics, recent progress has been mostly due to GWAS, which has become a standard approach to the identification of susceptibility genes for complex traits. Thus, in the past decade, genome-wide strategies have driven the discovery of more than 300 susceptibility loci—also denoted as risk loci—associated with ADs, including ankylosing spondylitis, autoimmune thyroid disease, Crohn’s disease, MS, psoriasis, RA, T1DM, and ulcerative colitis (reviewed in [311]). Of special importance are the single nucleotide polymorphisms (SNPs) that produce forms with loss of function or markedly reduced activity, thereby being substantially responsible for the genetic background determining susceptibility to certain ADs through failure in innate and/or adaptive immune processes. However, for almost all loci, understanding of the mechanisms leading to autoimmunity remains limited, and most genetic variants (>80%) that are likely to be causal are localized in noncoding regions of the genome. In addition, despite this progress, less than half of the heritability of most ADs can be explained, and nearly
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half of this identified genetic risk is due to variations within the MHC/HLA system as, for example, seen in CeD (for reviews, [84, 309, 310, 312]). Notably, as outlined by Suzuki et al. [313], the abilities of next-generation sequencing techniques for analyzing the functions of noncoding regions have progressed recently advanced, allowing extensive analysis of enhancers, promoters, histone modifications, and chromatin structures. Analysis of the so-called expression of quantitative trait loci (eQTL) is used to explore how particular variants lead to intermediate phenotypes such as epigenetics. The eQTL are DNA markers on a chromosome that allude to genes implicated in a quantitative trait. Remarkably, eQTL analysis has been exploited to identify loci that are associated with a particular quantitative phenotypic trait or disease and can be caused to polygenic effects. In fact, novel types of QTL have been discovered, spanning the epigenome, transcriptome, and proteome to the metabolome and microbiome to link the genotype and phenotype [314].
6.4.2.2 Genetic Factors Associated with Autoimmune Diseases For understanding convenience, this section is divided into MHC/HLA and non- MHC/HLA loci associated with autoimmune diseases. The MHC/HLA System Clearly, the strongest component for genetic bias in human autoimmunity was and still remains the MHC/HLA system. It is believed to play a central role in the genetic predisposition to ADs [315, 316]. In fact, considerable genetic similarity is found among autoimmune disorders, and they are frequently associated with MHC genes. A number of linkage studies have identified genetic variants associated with ADs. Still, many diseases demonstrate multiple MHC associations. For instance, diseases like T1DM and autoimmune thyroid diseases are associated with the HLA-DR3-DQ2 haplotype yet also have associations with the class I alleles encoding HLA-B8 and HLA-A1, which are part of an extended, conserved haplotype. Of interest is that ADs with characteristic autoantibodies are typically associated with MHC class II alleles, whereas seronegative diseases most often are associated with MHC class I alleles [315, 316]. Nevertheless, despite a massive effort to identify the genetic basis of a number of ADs through GWAS, the results have failed to have major predictive value. One of the most interesting—and challenging—questions is what mechanisms for the contribution of MHC molecules to the induction of autoimmunity are operating. In fact, significant progress has been made in delineating several important molecular mechanisms. As reviewed [316], there are several examples of how PTMs can be involved, the most straightforward mechanism for them to explain MHC association with the disease being to act by the creation of neoepitopes which only bind to the susceptibility alleles, and to which T cell have not been negatively selected against in the thymus. The Non-MHC/HLA System Of note, over the past ten years, hundreds of non-HLA loci have been reported to be also associated with ADs [317]. These risk factors appear to be associated with gene products involved in both innate and adaptive immune responses. One typical
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example refers to the transcription factors Bach1 and Bach2, which belong to a basic region-leucine zipper (bZip) family [318, 319]. Bach2 is a transcription repressor that belongs to the basic-region leucine zipper family and binds to Maf recognition elements. It participates in oxidative stress-mediated apoptosis and is involved in macrophage-mediated innate immunity as well as the adaptive immune response. Furthermore, Bach2 maintains T cell homeostasis, influences the function of macrophages, and plays a role in autoimmunity. In fact, GWAS combined with a meta-analysis of genome-wide analysis has been conducted, and results indicate that Bach2 is associated with numerous ADs. However, in spite of new research, the role of Bach2 in immune responses, in particular with regard to the clinical phenotypes of ADs, is not completely clear [318, 319]. In addition, such studies to identify genetic risk loci are also complemented by progress in gene expression studies, including, as mentioned above, the definition of eQTL (for further reading, see [309, 313, 314]).
6.4.2.3 Genetic Defects in Insufficient Clearance of Dying Cells and NETs A relationship between genetics and the development of ADs can also be found elsewhere, that is, in the field of RCD research. Human bodies collectively turn over about 200 billion to 300 billion cells every day. Consequently, phagocytic cells of the immune system must constantly survey for, recognize, and efficiently clear the billions of cellular corpses that arise as a result of development, stress, infection, or normal homeostasis. This process, termed efferocytosis, is critical for the prevention of inflammatory and autoimmune disorders, and the persistence of dead cells in tissue is characteristic of many human ADs, notably SLE (for efferocytosis, see Vol.1 [24] Sect. 22.6.3.3, pp. 562/563). The most notable characteristic of the efferocytosis of apoptotic cells is its “immunologically silent” response aimed at maintaining homeostasis [320–322]. If dead cells are not engulfed efficiently and swiftly due to a defective apoptotic machinery, they undergo secondary RN associated with the release of (auto)antigens and a plethora of DAMPs [102, 320, 323–325] (compare Vol.1 [24], Fig. 19.2, p. 429, Sects. 19.2.3, p. 435 and Sect. 19.3.7, p. 454). Such defects in apoptosis have been reported in several human ADs. In other words, inefficient clearance of apoptotic cells leads to high immunogenicity of dying cells, thereby eliciting adaptive immune responses. In this scenario, the modified autoantigens (altered-self antigens) are presented by FDCs to autoreactive B cells in GCs of secondary lymphoid organs [102, 325]. This results in the loss of self tolerance and the production of autoantibodies. In addition, the first evidence has been published that FDCs are activated by DAMPs [103]. Likewise, another alteration of cell death pathways, NETosis, can represent another potential source of autoantigens and DAMPs involved in autoimmune processes though the genetic background of susceptibility is not yet clear [326] (for NETosis, see Sect. 6.2.4). Enhanced/persisting NETosis in terms of impaired NET clearance may contribute to immunogenicity in SLE and other ADs by promoting
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the externalization of modified chromatin-associated self antigens and emission of DAMPs such as DNA and histones (see Table 1.1) [326–328]. Interestingly, one of the potential genetic defects refers to DNase1, which is also essential to degrade chromatin—besides other forms of cell death—within NETs [329].
6.4.2.4 Concluding Remarks Together, in regard to environmental and genetic factors, one is inclined to discuss the following two pathogenetic scenarios: (1) injury → DAMPs → apoptosis → genetics-related insufficient apoptotic cell clearance → necrosis → genetics- related insufficient clearance of cell debris clearance → generation/presentation of chromatin-associated autoantigens and emission of DAMPs → activation of autoreactive DCs → autoimmune response; (2) injury → DAMPs → NETosis → genetics- related insufficient clearance of NETs → generation/presentation of chromatin-associated autoantigen and emission of DAMPs → activation of autoreactive DCs → autoimmune response. The next steps in research would include experiments to identify candidate genes contributing to these abnormalities that will provide a new understanding of the complex genetic interactions leading to the development of ADs such as SLE. In this context, Ding et al. [330] concluded: Understanding the genetic mechanisms underlying autoimmune diseases is still a major challenge. Appropriately characterizing GWAS SNPs in different cell types and contexts can assist in defining relevant genes and pathways. Advances in screening techniques of high-throughput perturbation and genome editing have allowed examination of noncoding autoimmune-associated SNPs and immune-related pathways at scale, prioritizing certain SNPs that can then be studied thoroughly, including at the single base pair level in order to establish causative variants and genes (in this context, also see the related editorial [331]).
6.4.3 Epigenetics 6.4.3.1 General Remarks Epigenetics is defined as stable, potentially inheritable, and reversible changes occurring in the genome in DNA and chromatin that regulate gene expression without altering the original DNA sequence. Moreover, epigenetics can be induced by environmental exposures, which in theory, may be relatively easier to change or reverse than genetic hardwiring. In fact, accumulating results have indicated that not only environmental factors play a critical role in autoimmune diseases in genetically predisposed individuals but also additional epigenetic mechanisms. However, it is not yet fully clarified whether all of these modifications are caused by disease or are actually causally involved in the disease. Without discussing in-depth, a few more words on the role of epigenetics in autoimmune disorders are added here. (For more information, the reader is referred to recent reviews listed under [16, 332–337].)
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6.4.3.2 Epigenetics: The Link Between Environmental and Genetic Factors Epigenetic mechanisms transduce the inheritance of gene expression patterns without altering the underlying DNA sequence but by adapting chromatin, which is the physiological form of our genetic information (for epigenetics in inflammation, see Vol. 1 [24], Sect. 24.2 and Fig. 24.1, pp. 636–645, and Vol. 2 [47], Sect. 5.6, Figs. 5.4, 5.5, and 5.6, pp. 169–193). In fact, epigenetic mechanisms work in addition to the DNA template to stabilize gene expression programs (activation or repression), thereby canalizing cell-type identities [333]. In the field of ADs, there is growing evidence in support of the notion that epigenetic modifications represent a link between genetic and environmental factors—here tentatively interpreted as the action of DAMPs—and, thus, may contribute to a better understanding of possible mechanisms involved in the pathogenesis of these diseases. In fact, epigenetic dysregulation may result in either overexpression or underexpression of certain genes on the level of damaged somatic cells of the target organ and/or distinct key cells of the innate/adaptive immune system implicated in ADs. Moreover, as comprehensively reviewed by Wu et al. [332], besides control of gene expression by epigenetics, a special set of master transcription factors participates in directly shaping cell type-specific gene expression programs, which include genes implicated in ADs. Finally, the normal execution of biological events is controlled by a combination of epigenetic modifications and transcription factors. It is also worth briefly noting here that epigenetic modifications may also occur on the gene loci that encode certain transcription factors, thereby serving as an additional regulatory factor for biological processes and cellular function. In fact, the interaction between epigenetic modifications and key transcription factors in regulating the immune system and their roles in the pathogenesis of some ADs are critical areas of research [332]. Chromatin Architecture To understand the mechanisms of epigenetics in gene regulation, one has to remember the chromatin architecture (see Fig. 24.1, in Vol.1 [24], Part VI, p. 637) and [338–340]). Chromatin is the assembly of DNA and proteins, that is, histones and non-histones, which collectively make up the contents of a cell nucleus. The function of chromatin is connected to DNA packaging, gene expression, and DNA replication. Of note, the genome does not just function in a sequential fashion but is folded in three-dimensional (3D) space, thereby allowing genomic elements located very remotely to contact and regulate each other (hierarchical genome organization). One hundred and forty-six base pairs (bp), or two turns, of DNA, are wrapped around a histone core octamers (containing two copies each of H2A, H2B, H3, and H4), thereby forming the nucleosome as the basic unit of chromatin. The histones present small protein tails that protrude from the nucleosome and are accessible to PTMs, including but not limited to methylation, acetylation, citrullination, and ubiquitination. Each modification can regulate gene expression by allowing DNA to condense into heterochromatin or open up into euchromatin. The genomic regions within heterochromatin primarily consist of repetitive sequences; it has been demonstrated that alterations in this region result in repressed genes
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associated with morphogenesis or differentiation (imprinting or X chromosome inactivation). Epigenetic Mechanisms Regulate Gene Expression Epigenetic mechanisms control eukaryotic development beyond DNA-stored information, that is, without a change in the nucleotide sequence. The primary mechanisms of epigenetic regulation of gene expression (activation or repression) include (1) DNA methylation, (2) nucleosome remodeling, (3) histone PTM (in particular, methylation, acetylation, citrullination), (4) histone variants, as well as (5) miRNAand long noncoding RNA (lncRNA) interference [332, 333]. It is important to mention that all these epigenetic mechanisms act together at the same time, not separately, to regulate gene expression, thereby contributing to differences in the chromatin template. As pointedly argued [332, 341], epigenetics has become a popular and important area of investigation in the pathogenesis of AD by focusing on the importance of aberrant epigenetic modifications. Indeed, it is generally agreed that aberrant epigenetic regulations play an important role in the pathogenesis of autoimmune disorders in terms of providing mechanistic links between “pathological” epigenetic marks and the onset of an AD. In principle, the epigenetics-mediated defect may operate either at the level of the antigen or the function of innate immune cells, including DCs, or at the level of adaptive immune T and B cells. Here, some general aspects of this emerging topic are being discussed. Crosstalk Between Epigenetic Modifications and Metabolism in Autoimmune Diseases Interestingly, as reviewed by Wang et al. [342], epigenetic changes such as the methylation/demethylation of DNA and histone proteins as well as histone acetylation/deacetylation can be dynamically produced and eliminated by a group of enzymes that consume several metabolites derived from various physiological pathways. Metabolites such as S-adenosylmethionine, acetyl-CoA, nicotinamide adenine dinucleotide, α-ketoglutarate, and ATP serve as cofactors for chromatin-modifying enzymes, such as methyltransferases, deacetylases, and kinases, which are responsible for chromatin remodeling (for more detailed information, see the comprehensive review [342]).
6.4.3.3 Epigenetics at the Level of Altered-Self Antigen Formation (“Autoantigenesis”) First of all—and similar to PTM as discussed above—epigenetic changes may lead to the generation of an altered-self antigen in cells of the target organ, a scenario that has been widely observed. In fact, such an interpretation of the initiation of an autoimmune response sounds plausible, and recent discoveries of autoimmunity- inducing stimuli revealed that epigenetic marks of autoantigens presented by DCs are recognized by autoreactive B and T cell receptors. A prerequisite of this notion is that these epigenetic marks should not have occurred during the process of central tolerance mechanisms and host development and, thus, were chosen for negative selection (compare above, Sect. 6.2.2.3).
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An excellent example of such epigenetic modifications is provided by the large number of PTMs in histones. As reviewed by Radic and Muller [343], over 100 different self molecules derived from cell components act as autoantigens in different autoimmune disorders. Many or even most of these combine a number of different epigenetic marks. Examples are PARP that, in addition to auto-polyADP- ribosylation, can be phosphorylated, acetylated, ubiquitinylated, and sumoylated, HSPs-DAMPs such as HSP90 that can be phosphorylated, acetylated, or citrullinated, and the HSPA8/HSC70 that can be acetylated and tyrosinephosphorylated. Many of these modifications are recognized by autoantibodies occurring in ADs. If one accepts such a scenario, the question here is: (1) do environmental triggers (here in terms of injury-induced DAMPs) activate PRR-bearing DCs, which— together with engulfment of altered-self antigen resulting from pre-existing epigenetic modifications—elicit an autoimmune response; or (2) do environmental triggers in terms of injury-induced DAMPs primarily induce epigenetic changes in distinct target cells (e.g., fibroblasts in RA), resulting in the generation of an altered-self antigen that is engulfed by PRR-bearing DCs that are simultaneously activated by those DAMPs to elicit an autoimmune response?
6.4.3.4 Impact on the Innate Immune Arc Epigenetically caused defects in ADs could also be searched on the side of innate immune cells (also see [337]). In fact, perturbations of epigenetic mechanisms of macrophages and DCs have recently been discussed to affect normal macrophage or DC tissue function, thereby contributing to autoimmune pathologies [344, 345]. An exciting, supportive contribution to such a model refers to recent studies showing that MAMPs and DAMPs can induce epigenetic changes (for example, histone modifications), leading to an innate immune memory, also defined as “trained immunity” (also see Vol. 1 [24], Sect. 24.2.4, pp. 642–646, and [18, 346– 348]). As recently reviewed by Bekkering et al. [349], DAMPs as inducers of trained immunity include activators of the liver X receptor pathways, uric acid, catecholamines, aldosterone, S100 proteins, and type I IFNs. Trained Immunity Reprogramming Innate Immunity in Health and Disease Trained immunity is non-specific and mediated through epigenetic reprogramming in innate immune cells, including myeloid cells and NK cells, but also stromal and epithelial cells [350]. This kind of “memory” immunity evolved to lead to adaptive states that protect the host during microbial colonization or after infections. However, in certain situations, trained immunity may result in maladaptive states such as post-sepsis immune paralysis or hyperinflammation or, as recently proposed by Arts et al. [351], an autoimmune response (Fig. 6.8). In fact, there is accumulating evidence to suggest that, in such DAMP-induced epigenetic changes, rewiring of cellular metabolism (a shift from oxidative phosphorylation toward aerobic glycolysis) is involved, with a role for metabolites as cofactors for enzymes involved in epigenetic modulation of gene transcription. Thus, it is tempting to speculate that the maladaptive state of innate immune cells based on DAMP-induced epigenetic modifications would change—besides generating an autoantigen—the local immune
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Environmental factors DAMPs Trained immunity (Myeloid cells)
Beneficial adaptive effects
Maladaptive detrimental effects
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(And other disorders)
Fig. 6.8 Simplified diagram of a tentatively designed conceptual model of the Janus-faced, DAMP-promoted trained immunity in health and diseases. This kind of “memory” immunity evolved to lead to adaptive states that protect the host during microbial colonization or after infections. However, in certain situations, trained immunity may result in maladaptive states, such as seen in autoimmune responses. (Sources: [349–351])
responsiveness of immune cells, in particular, the maturation process of autoreactive DCs under the involvement of modified transcriptional processes. As hypothesized in this context by Arts et al. [351], trained immunity may play a deleterious role in the induction and/or maintenance of autoimmune and autoinflammatory diseases if inappropriately activated. In support of such a concept are data presented showing that monocytes from patients with several autoimmune and autoinflammatory diseases display features that are consistent with a trained immunity phenotype. Thus, the authors argue that … Trained immunity could serve a role in the initiation of the disease and in the maintenance or aggravation of the symptoms. In the case of disease initiation, a genetic or environmental factor (or combinations of both) would induce trained monocytes/macrophages that initiate the disease. In the case of disease progression, monocytes/macrophages become trained and are therefore easier activated, which would result in the maintenance or deterioration of disease symptoms [351]. Additional evidence for the role of a metabolic intermediate such as the DAMP succinate in activation of epigenetic changes comes from studies recently reviewed by Nieborak and Schneider [352]. These exciting observations have been recently echoed by Bekkering et al. [349]: Trained immunity can induce increased protection against reinfection, which can be used to optimize vaccination strategies or for protection against, for example, COVID-19. It is important in the induction of mucosal tolerance, and it is already being used to treat bladder cancer. On the other hand, several chronic inflammatory diseases are characterized by an inappropriately trained immunity phenotype, such as cardiovascular diseases, allergies, transplantation rejection, and autoinflammatory diseases. In patients with SLE, for example, hematopoietic stem and progenitor cells reportedly show transcriptomic reprogramming and myeloid skewing similar to what has been portrayed in trained immunity, leading to enhanced activation and differentiation of neutrophils, thereby contributing to persistent inflammation and risk of flare once the disease is in remission [353].
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6.4.3.5 Impact on the Adaptive Immune Arc As briefly mentioned in Vol. 1 [24], Sect. 32.4.1, pp. 765–767, epigenetic reprogramming is normally implicated in T cell activation, T cell subset differentiation, and development, thus defining cell identity and function to environmental challenges (see also [354, 355]). Such homeostatic epigenetic reprogramming can be subjected to aberrant modifications. Hence, and not surprisingly, a pathogenetic role of epigenetic changes implicated in the pathogenesis of ADs has also been described for cells of the adaptive immune system [356, 357]. Indeed, a dysregulated adaptive immune system—may it be the consequence of epigenetics-induced dysfunction/ hyperactivation of the innate immune response or a de novo-occurring malfunction caused by aberrant epigenetic modifications—is characteristic of the pathogenesis of many ADs, including SLE, RA, MS, T1DM, and IBD [358]. Specific alterations of epigenetic mechanisms in immune cells, such as Th cells, may represent the trigger for self tolerance loss and for cell and/or tissue destruction [356]. 6.4.3.6 The Model of DAMP-Triggered Epigenetic Changes in Autoimmune Diseases Epigenetics is increasingly appreciated to be a crucial mechanism in the pathogenesis of ADs. Epigenetic alterations can operate as integrators of environmental and genetic factors to promote activated states in innate and adaptive immune cells. In view of the danger/injury model in Immunology, and in accordance with the tautological approach that environmental factors operate as exogenous DAMPs or induce endogenous DAMPs, the unproven tenet here would be: DAMPs trigger epigenetic changes at genetic loci in predisposed individuals resulting in the development of in ADs (Fig. 6.9). According to this hypothetical interpretation that is currently going Fig. 6.9 Simplified presentation of a hypothetical model proposing that environmental factor- promoted generation and emission of DAMPs trigger epigenetic changes at predisposing genes in susceptible individuals, resulting in the initiation of an autoimmune assault against target cells as the basis for the development of autoimmune diseases
Environmental factors
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to gain credibility, the DAMPs could play an integral key role in the initiation and perpetuation of ADs. Overall, studies on the key conceptual role of DAMPs in autoimmune disease pathogenesis are rapidly increasing. However, in-depth studies of the impact of DAMPs on epigenetic alterations are still needed to draw valid conclusions.
6.4.4 Résumé Heritable genes and their modifications by epigenetic modifications are currently a burning issue in the research field of etiopathogenesis of ADs autoimmunity. As briefly addressed in this section, epigenetic features such as DNA methylation and hydroxymethylation, as well as histone modifications, all contribute to playing a role in the development of autoimmunity. Compared to numerous studies that have focused on the field of genetics, research on epigenetics is still in its infancy. In this context, Surace et al. [337] conclude: Completely deciphering epigenetic contributors to disease is complicated by the fact that epigenetic events are highly complex and work in combination with other epigenetic marks, they are reversible and depend on multiple variables, including cell cycle, and external factors including the immunological micro-environment. While for some epigenetic modifications underlying causes and their involvement in the pathophysiology have been accepted, other modifications may be the result of ongoing inflammation and a secondary event in systemic autoimmune/inflammatory disease.
6.5 Outlook and Future Perspectives The exact etiopathogenetic pathways involved in ADs are still not fully understood. In light of the danger/injury model, the pathogenetic concept—as already outlined above—pragmatically condenses to the tenet: autoantigenic stimulus (i.e., bone fide self antigens or altered self antigens) (signal 1) in the absence of DAMPs promotes immune tolerance; and autantigenic stimulus (i.e., bone fide self antigens or altered self antigens) in the presence of DAMPs, that is, DAMP-induced costimulation (signal 2), induces immunostimulatory DCs to promote destructive adaptive autoimmune responses (cf. Fig. 6.2). As discussed in this chapter, a growing mountain of evidence suggests a complex involvement of environmental and genetic factors, whereby epigenetic alterations function as links. Tentatively interpreted in light of the danger/injury model, the scenario may be outlined as follows: “A growing mountain of evidence suggests a complex involvement of environmental factors (acting as exogenous DAMPs or inducing endogenous DAMPs) and genetic factors, whereby DAMP-promoted epigenetic alterations function as links.” Harmful environmental factors definitely play a critical triggering role; however, evidently, not everybody who is exposed to those environmental factors does acquire an AD. Instead, she or he may just transiently respond to exogenous DAMPs or endogenous DAMPs, eventually associated with some degree of necro- autoinflammation. In other words: Environmental exposures of genetically
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predisposed individuals may epigenetically modify AD-associated risk genes, resulting in the development of AD manifestations. Notably, a true clearcut interrelationship between these three factors has still not been proven. Nevertheless, the critical event causing an AD in genetically susceptible individuals—in addition to the action of DAMPs—must be searched in a perturbation at any point of the sequelae: environmental factor-induced generation of an autoantigen in target cells → processing/presentation of autoantigen by DCs → recognition of autoantigen/autoepitope by autoreactive TCR on T cells and/ or autoreactive BCR on B cells. When hypothesizing a scenario in which DAMPs, in the presence of bona fide self antigens or altered-self antigens, instigate innate immune pathways leading to an adaptive autoimmune response, the following three DAMP-based scenarios may be discussed—by focusing on epigenetic modifications that need a genetically inherited predisposition (see also Fig. 6.6a–c): 1. Native proteins released from subroutines of RCD are engulfed by APCs (e.g., DCs) that get activated by DAMPs and present self antigenic peptides on MHC molecules (signal 1) and express costimulatory molecules (signal 2). Both signals trigger the activation of naïve autoreactive T cells that express normal or (epigenetically induced) aberrant TCR/TCR signaling (Fig. 6.6a). Here, it is the initial cell injury (e.g., leading to RCD) that promotes autoimmunity. 2. Native self proteins released from subroutines of RCD are engulfed by APCs (e.g., DCs) and (epigenetically?) modified (e.g., by intracellular proteases) to altered-self peptides during antigen processing. Activated by DAMPs, the APCs present altered-self antigenic peptides on MHC molecules (signal 1) and express costimulatory molecules (signal 2). Both signals trigger activation of altered-self reactive T cells that express normal TCR/TCR signaling (Fig. 6.6b). 3. Proteins released, for example, from RN, are already (epigenetically modified?) PTM-proteins that are engulfed by APCs (e.g., DCs) and get activated by DAMPs and present altered-self antigenic peptides on MHC molecules (signal 1) and express costimulatory molecules (signal 2). Both signals trigger activation of altered-self reactive T cells that express normal TCR/TCR signaling (Fig. 6.6c). After having sketched some pathways involved in the etiopathogenesis of ADs, we will describe the four most prominent disorders in more detail in the following two chapters.
References 1. Woodruff MC, Ramonell RP, Saini AS, Haddad NS, Anam FA, Rudolph ME, et al. Relaxed peripheral tolerance drives broad de novo autoreactivity in severe COVID-19. medRxiv Prepr Serv Heal Sci. 2021. https://pubmed.ncbi.nlm.nih.gov/33106819/. 2. Theofilopoulos AN, Kono DH, Baccala R. The multiple pathways to autoimmunity. Nat Immunol. 2017;18:716–24. http://www.nature.com/articles/ni.3731.
References
437
3. Jacobson DL, Gange SJ, Rose NR, Graham NM. Epidemiology and estimated population burden of selected autoimmune diseases in the United States. Clin Immunol Immunopathol. 1997;84:223–43. http://www.ncbi.nlm.nih.gov/pubmed/9281381. 4. Eaton WW, Rose NR, Kalaydjian A, Pedersen MG, Mortensen PB. Epidemiology of autoimmune diseases in Denmark. J Autoimmun. 2007;29:1–9. https://linkinghub.elsevier.com/ retrieve/pii/S0896841107000650. 5. Cooper GS, Bynum MLK, Somers EC. Recent insights in the epidemiology of autoimmune diseases: improved prevalence estimates and understanding of clustering of diseases. J Autoimmun. 2009;33:197–207. https://linkinghub.elsevier.com/retrieve/pii/ S089684110900122X. 6. Lerner A, Jeremias P, Matthias T. The World incidence and prevalence of autoimmune diseases is increasing. Int J Celiac Dis. 2016;3:151–5. http://pubs.sciepub.com/ijcd/3/4/8/ index.html. 7. Lahita RG, Chiorazzi N, Reeves WH. Textbook of the autoimmune diseases. Philadelphia: Lippincott Williams & Wilkins; 2000. ISBN-13: 978-0781715058. 8. Niaid. Progress in autoimmune diseases research. 2005. https://www.niaid.nih.gov/sites/ default/files/adccfinal.pdf. 9. NIAD. NIH Autoimmune Diseases Coordinating Committee | NIH: National Institute of Allergy and Infectious Diseases. 2005. https://www.niaid.nih.gov/about/ autoimmune-diseases-committee. 10. Harris JE. Cellular stress and innate inflammation in organ-specific autoimmunity: lessons learned from vitiligo. Immunol Rev. 2016;269:11–25. https://onlinelibrary.wiley.com/ doi/10.1111/imr.12369. 11. Land WG. Role of damage-associated molecular patterns in light of modern environmental research: a tautological approach. Int J Environ Res. 2020;14:583–604. http://link.springer. com/10.1007/s41742-020-00276-z. 12. Cotsapas C, Hafler DA. Immune-mediated disease genetics: the shared basis of pathogenesis. Trends Immunol. 2013;34:22–6. https://linkinghub.elsevier.com/retrieve/pii/ S1471490612001573. 13. Goris A, Liston A. The immunogenetic architecture of autoimmune disease. Cold Spring Harb Perspect Biol. 2012;4:a007260. http://cshperspectives.cshlp.org/lookup/doi/10.1101/ cshperspect.a007260. 14. Ma Y, Shi N, Li M, Chen F, Niu H. Applications of next-generation sequencing in systemic autoimmune diseases. Genomics Proteomics Bioinformatics. 2015;13:242–9. https://linkinghub.elsevier.com/retrieve/pii/S1672022915001126. 15. Miller FW, Pollard KM, Parks CG, Germolec DR, Leung PSC, Selmi C, et al. Criteria for environmentally associated autoimmune diseases. J Autoimmun. 2012;39:253–8. https:// linkinghub.elsevier.com/retrieve/pii/S0896841112000583. 16. Jeffries MA. Epigenetic editing: how cutting-edge targeted epigenetic modification might provide novel avenues for autoimmune disease therapy. Clin Immunol. 2018;196:49–58. http://linkinghub.elsevier.com/retrieve/pii/S1521661618300159. 17. Morandini AC, Santos CF, Yilmaz Ö. Role of epigenetics in modulation of immune response at the junction of host–pathogen interaction and danger molecule signaling. Pathog Dis. 2016;74:ftw082. https://academic.oup.com/femspd/article-lookup/doi/10.1093/ femspd/ftw082. 18. Crișan TO, Netea MG, Joosten LAB. Innate immune memory: implications for host responses to damage-associated molecular patterns. Eur J Immunol. 2016;46:817–28. https:// onlinelibrary.wiley.com/doi/10.1002/eji.201545497. 19. Starr TK, Jameson SC, Hogquist KA. Positive and negative selection of T cells. Annu Rev Immunol. 2003;21:139–76. http://www.annualreviews.org/doi/10.1146/annurev. immunol.21.120601.141107. 20. Bour-Jordan H, Esensten JH, Martinez-Llordella M, Penaranda C, Stumpf M, Bluestone JA. Intrinsic and extrinsic control of peripheral T-cell tolerance by costimulatory mol-
438
6 Basic Trajectories in Autoimmunity
ecules of the CD28/ B7 family. Immunol Rev. 2011;241:180–205. http://doi.wiley. com/10.1111/j.1600-065X.2011.01011.x. 21. Xing Y, Hogquist KA. T-cell tolerance: central and peripheral. Cold Spring Harb Perspect Biol. 2012;4:a006957. http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect. a006957. 22. Richards DM, Delacher M, Goldfarb Y, Kägebein D, Hofer A-C, Abramson J, et al. Treg cell differentiation: from thymus to peripheral tissue. Prog Mol Biol Transl Sci. 2015;136:175–205. https://linkinghub.elsevier.com/retrieve/pii/S1877117315001465. 23. Yang S-H, Gao C, Li L, Chang C, Leung PSC, Gershwin ME, et al. The molecular basis of immune regulation in autoimmunity. Clin Sci. 2018;132:43–67. https://portlandpress.com/ clinsci/article/132/1/43/71684/The-molecular-basis-of-immune-regulation-in. 24. Land WG. Damage-associated molecular patterns in human diseases. Volume 1: Injury- induced innate immune responses. Cham: Springer International Publishing; 2018. http:// link.springer.com/10.1007/978-3-319-78655-1. 25. Hodgkin PD, Heath WR, Baxter AG. The clonal selection theory: 50 years since the revolution. Nat Immunol. 2007;8:1019–26. http://www.nature.com/articles/ni1007-1019. 26. Brent L. Transplantation tolerance—a historical introduction. Immunology. 2016;147:267–8. https://onlinelibrary.wiley.com/doi/10.1111/imm.12567. 27. Ring GH, Lakkis FG. Breakdown of self-tolerance and the pathogenesis of autoimmunity. Semin Nephrol. 1999;19:25–33. http://www.ncbi.nlm.nih.gov/pubmed/9952278. 28. Silverstein AM. Paul Ehrlich, archives and the history of immunology. Nat Immunol. 2005;6:639. http://www.nature.com/articles/ni0705-639. 29. Borchers A, Ansari AA, Hsu T, Kono DH, Gershwin ME. The pathogenesis of autoimmunity in New Zealand mice. Semin Arthritis Rheum. 2000;29:385–99. http://www.ncbi.nlm.nih. gov/pubmed/10924025. 30. Rose NR, Witebsky E. Studies on organ specificity. V. Changes in the thyroid glands of rabbits following active immunization with rabbit thyroid extracts. J Immunol. 1956;76:417–27. http://www.ncbi.nlm.nih.gov/pubmed/13332243. 31. Passos GA, Speck-Hernandez CA, Assis AF, Mendes-da-Cruz DA. Update on Aire and thymic negative selection. Immunology. 2018;153:10–20. https://onlinelibrary.wiley.com/ doi/10.1111/imm.12831. 32. Takaba H, Morishita Y, Tomofuji Y, Danks L, Nitta T, Komatsu N, et al. Fezf2 orchestrates a thymic program of self-antigen expression for immune tolerance. Cell. 2015;163:975–87. https://linkinghub.elsevier.com/retrieve/pii/S0092867415013264. 33. Klein L, Kyewski B, Allen PM, Hogquist KA. Positive and negative selection of the T cell repertoire: what thymocytes see (and don’t see). Nat Rev Immunol. 2014;14:377–91. http:// www.nature.com/articles/nri3667. 34. Waisman A, Lukas D, Clausen BE, Yogev N. Dendritic cells as gatekeepers of tolerance. Semin Immunopathol. 2017;39:153–63. http://link.springer.com/10.1007/ s00281-016-0583-z. 35. Cowan JE, Parnell SM, Nakamura K, Caamano JH, Lane PJL, Jenkinson EJ, et al. The thymic medulla is required for Foxp3+ regulatory but not conventional CD4+ thymocyte development. J Exp Med. 2013;210:675–81. https://rupress.org/jem/article/210/4/675/41522/ The-thymic-medulla-is-required-for-Foxp3. 36. Perry JSA, Lio C-WJ, Kau AL, Nutsch K, Yang Z, Gordon JI, et al. Distinct contributions of aire and antigen-presenting-cell subsets to the generation of self-tolerance in the thymus. Immunity. 2014;41:414–26. https://linkinghub.elsevier.com/retrieve/pii/ S107476131400301X. 37. Inglesfield S, Cosway EJ, Jenkinson WE, Anderson G. Rethinking thymic tolerance: lessons from mice. Trends Immunol. 2019;40:279–91. https://linkinghub.elsevier.com/retrieve/pii/ S1471490619300225. 38. Klein L, Robey EA, Hsieh C-S. Central CD4+ T cell tolerance: deletion versus regulatory T cell differentiation. Nat Rev Immunol. 2019;19:7–18. http://www.nature.com/articles/ s41577-018-0083-6.
References
439
39. Tao Z, Jiang Y, Xia S. Regulation of thymic T regulatory cell differentiation by TECs in health and disease. Scand J Immunol. 2021;94(4):e13094. https://onlinelibrary.wiley.com/ doi/10.1111/sji.13094. 40. Herppich S, Beckstette M, Huehn J. The thymic microenvironment gradually modulates the phenotype of thymus-homing peripheral conventional dendritic cells. Immun Inflamm Dis. 2022;10(2):175–88. https://onlinelibrary.wiley.com/doi/10.1002/iid3.559. 41. Zehn D, Bevan MJ. T cells with low avidity for a tissue-restricted antigen routinely evade central and peripheral tolerance and cause autoimmunity. Immunity. 2006;25:261–70. https:// linkinghub.elsevier.com/retrieve/pii/S1074761306003426. 42. Yu W, Jiang N, Ebert PJR, Kidd BA, Müller S, Lund PJ, et al. Clonal deletion prunes but does not eliminate self-specific αβ CD8(+) T lymphocytes. Immunity. 2015;42:929–41. http:// linkinghub.elsevier.com/retrieve/pii/S1074761315001818. 43. Legoux FP, Lim J-B, Cauley AW, Dikiy S, Ertelt J, Mariani TJ, et al. CD4+ T cell tolerance to tissue-restricted self antigens is mediated by antigen-specific regulatory T cells rather than deletion. Immunity. 2015;43:896–908. http://linkinghub.elsevier.com/retrieve/pii/ S1074761315004367. 44. Malhotra D, Linehan JL, Dileepan T, Lee YJ, Purtha WE, Lu JV, et al. Tolerance is established in polyclonal CD4(+) T cells by distinct mechanisms, according to self-peptide expression patterns. Nat Immunol. 2016;17:187–95. http://www.nature.com/doifinder/10.1038/ ni.3327. 45. Gutierrez MJ, Gilson J, Zacharias J, Ishmael F, Bingham CA. Childhood polyarthritis as early manifestation of autoimmune polyendocrinopathy with candidiasis and ectodermal dystrophy syndrome. Front Immunol. 2017;8:377. http://journal.frontiersin.org/article/10.3389/ fimmu.2017.00377/full. 46. Perniola R. Twenty years of AIRE. Front Immunol. 2018;9:98. http://journal.frontiersin.org/ article/10.3389/fimmu.2018.00098/full. 47. Land WG. Damage-associated molecular patterns in human diseases. Vol. 2: Danger signals as diagnostics, prognostics, and therapeutic targets. Cham: Springer International Publishing; 2020. http://link.springer.com/10.1007/978-3-030-53868-2. 48. Pinto S, Sommermeyer D, Michel C, Wilde S, Schendel D, Uckert W, et al. Misinitiation of intrathymic MART-1 transcription and biased TCR usage explain the high frequency of MART-1-specific T cells. Eur J Immunol. 2014;44:2811–21. http://doi.wiley.com/10.1002/ eji.201444499. 49. Marx A, Yamada Y, Simon-Keller K, Schalke B, Willcox N, Ströbel P, et al. Thymus and autoimmunity. Semin Immunopathol. 2021;43:45–64. http://link.springer.com/10.1007/ s00281-021-00842-3. 50. Richards DM, Ruggiero E, Hofer A-C, Sefrin JP, Schmidt M, von Kalle C, et al. The contained self-reactive peripheral T cell repertoire: size, diversity, and cellular composition. J Immunol. 2015;195:2067–79. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1500880. 51. Matzinger P, Kamala T. Tissue-based class control: the other side of tolerance. Nat Rev Immunol. 2011;11:221–30. http://www.nature.com/doifinder/10.1038/nri2940. 52. Matzinger P. Autoimmunity: are we asking the right question? Front Immunol [Internet]. 2022; 13: 864633 Available from: https://doi.org/10.3389/fimmu.2022.864633. 53. Matzinger P. Autoimmunity: are we asking the right question? Res Online. 2022. https:// www.researchgate.net/project/autoimmunity-are-we-asking-the-right-question. 54. Khan U, Ghazanfar H. T lymphocytes and autoimmunity. Int Rev Cell Mol Biol. 2018;341:125–68. https://linkinghub.elsevier.com/retrieve/pii/S1937644818300583. 55. Land W. Allograft injury mediated by reactive oxygen species: from conserved proteins of Drosophila to acute and chronic rejection of human transplants. Part III: interaction of (oxidative) stress-induced heat shock proteins with toll-like receptor-bearing cells. Transplant Rev. 2003;17:67–86. https://linkinghub.elsevier.com/retrieve/pii/S0955470X02000095. 56. ElTanbouly MA, Noelle RJ. Rethinking peripheral T cell tolerance: checkpoints across a T cell’s journey. Nat Rev Immunol. 2021;21:257–67. https://www.nature.com/articles/ s41577-020-00454-2.
440
6 Basic Trajectories in Autoimmunity
57. Anderson CC, Sinclair NRSS. FcR-mediated inhibition of cell activation and other forms of coinhibition. Crit Rev Immunol. 1998;18:525–44. http://www.dl.begellhouse.com/journals/2 ff21abf44b19838,390d3fc461d10f95,673576f31674bd3d.html. 58. Davey GM, Kurts C, Miller JFAP, Bouillet P, Strasser A, Brooks AG, et al. Peripheral deletion of autoreactive CD8 T cells by cross presentation of self-antigen occurs by a Bcl-2– inhibitable pathway mediated by bim. J Exp Med. 2002;196:947–55. https://rupress.org/jem/ article/196/7/947/8411/Peripheral-Deletion-of-Autoreactive-CD8-T-Cells-by. 59. Hildeman DA, Zhu Y, Mitchell TC, Kappler J, Marrack P. Molecular mechanisms of activated T cell death in vivo. Curr Opin Immunol. 2002;14:354–9. https://linkinghub.elsevier.com/ retrieve/pii/S0952791502003357. 60. Hawiger D, Inaba K, Dorsett Y, Guo M, Mahnke K, Rivera M, et al. Dendritic cells induce peripheral T cell unresponsiveness under steady state conditions in vivo. J Exp Med. 2001;194:769–79. http://www.ncbi.nlm.nih.gov/pubmed/11560993. 61. Mueller DL. Mechanisms maintaining peripheral tolerance. Nat Immunol. 2010;11:21–7. http://www.nature.com/articles/ni.1817. 62. Kurts C, Kosaka H, Carbone FR, Miller JFAP, Heath WR. Class I–restricted cross- presentation of exogenous self-antigens leads to deletion of autoreactive CD8+ T cells. J Exp Med. 1997;186:239–45. https://rupress.org/jem/article/186/2/239/7241/ Class-Irestricted-CrossPresentation-of-Exogenous. 63. Hasegawa H, Matsumoto T. Mechanisms of tolerance induction by dendritic cells in vivo. Front Immunol. 2018;9:350. http://journal.frontiersin.org/article/10.3389/fimmu.2018.00350/full. 64. Fife BT, Bluestone JA. Control of peripheral T-cell tolerance and autoimmunity via the CTLA-4 and PD-1 pathways. Immunol Rev. 2008;224:166–82. https://onlinelibrary.wiley. com/doi/10.1111/j.1600-065X.2008.00662.x. 65. Francisco LM, Sage PT, Sharpe AH. The PD-1 pathway in tolerance and autoimmunity. Immunol Rev. 2010;236:219–42. https://onlinelibrary.wiley.com/doi/10.1111/j.1600-065X .2010.00923.x. 66. Paterson AM, Sharpe AH. Taming tissue-specific T cells: CTLA-4 reins in self-reactive T cells. Nat Immunol. 2010;11:109–11. http://www.nature.com/articles/ni0210-109. 67. Oyewole-Said D, Konduri V, Vazquez-Perez J, Weldon SA, Levitt JM, Decker WK. Beyond T-cells: functional characterization of CTLA-4 expression in immune and non-immune cell types. Front Immunol. 2020;11:608024. https://www.frontiersin.org/articles/10.3389/ fimmu.2020.608024/full. 68. Sakaguchi S, Yamaguchi T, Nomura T, Ono M. Regulatory T cells and immune tolerance. Cell. 2008;133:775–87. http://linkinghub.elsevier.com/retrieve/pii/S0092867408006247. 69. Iberg CA, Jones A, Hawiger D. Dendritic cells as inducers of peripheral tolerance. Trends Immunol. 2017;38:793–804. https://linkinghub.elsevier.com/retrieve/pii/ S147149061730145X. 70. Saligrama N, Zhao F, Sikora MJ, Serratelli WS, Fernandes RA, Louis DM, et al. Opposing T cell responses in experimental autoimmune encephalomyelitis. Nature. 2019;572:481–7. http://www.nature.com/articles/s41586-019-1467-x. 71. Grover P, Goel PN, Greene MI. Regulatory T cells: regulation of identity and function. Front Immunol. 2021;12:750542. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.750542/full. 72. Li S, Tajiri K, Murakoshi N, Xu D, Yonebayashi S, Okabe Y, et al. Programmed death-ligand 2 deficiency exacerbates experimental autoimmune myocarditis in mice. Int J Mol Sci. 2021;22:1426. https://www.mdpi.com/1422-0067/22/3/1426. 73. Franks SE, Getahun A, Hogarth PM, Cambier JC. Targeting B cells in treatment of autoimmunity. Curr Opin Immunol. 2016;43:39–45. http://linkinghub.elsevier.com/retrieve/pii/ S0952791516300929. 74. Nemazee D. Mechanisms of central tolerance for B cells. Nat Rev Immunol. 2017;17:281–94. http://www.nature.com/articles/nri.2017.19. 75. Salinas GF, Braza F, Brouard S, Tak P-P, Baeten D. The role of B lymphocytes in the progression from autoimmunity to autoimmune disease. Clin Immunol. 2013;146:34–45. https:// linkinghub.elsevier.com/retrieve/pii/S1521661612002604.
References
441
76. Castañeda J, Hidalgo Y, Sauma D, Rosemblatt M, Bono MR, Núñez S. The multifaceted roles of B cells in the thymus: from immune tolerance to autoimmunity. Front Immunol. 2021:12. https://www.frontiersin.org/articles/10.3389/fimmu.2021.766698/full. 77. Xu Z, Zan H, Pone EJ, Mai T, Casali P. Immunoglobulin class-switch DNA recombination: induction, targeting and beyond. Nat Rev Immunol. 2012;12:517–31. http://www.nature. com/articles/nri3216. 78. Martin A, Chahwan R, Parsa JY, Scharff MD. Somatic hypermutation. In: Molecular biology of B cells. Amsterdam: Elsevier; 2015. p. 363–88. http://linkinghub.elsevier.com/retrieve/pii/ B9780123979339000205. 79. Sheppard EC, Morrish RB, Dillon MJ, Leyland R, Chahwan R. Epigenomic modifications mediating antibody maturation. Front Immunol. 2018;9:355. http://journal.frontiersin.org/ article/10.3389/fimmu.2018.00355/full. 80. Meffre E, Wardemann H. B-cell tolerance checkpoints in health and autoimmunity. Curr Opin Immunol. 2008;20:632–8. http://linkinghub.elsevier.com/retrieve/pii/S0952791508001775. 81. Meffre E. The establishment of early B cell tolerance in humans: lessons from primary immunodeficiency diseases. Ann N Y Acad Sci. 2011;1246:1–10. http://doi.wiley. com/10.1111/j.1749-6632.2011.06347.x. 82. Brink R. The imperfect control of self-reactive germinal center B cells. Curr Opin Immunol. 2014;28:97–101. https://linkinghub.elsevier.com/retrieve/pii/S0952791514000399. 83. Chen JW, Schickel J-N, Tsakiris N, Sng J, Arbogast F, Bouis D, et al. Positive and negative selection shape the human naïve B cell repertoire. J Clin Invest. 2022;132(2):e150985. http:// www.jci.org/articles/view/150985. 84. Wang L, Wang F-S, Gershwin ME. Human autoimmune diseases: a comprehensive update. J Intern Med. 2015;278:369–95. https://onlinelibrary.wiley.com/doi/10.1111/joim.12395. 85. Rojas M, Restrepo-Jiménez P, Monsalve DM, Pacheco Y, Acosta-Ampudia Y, Ramírez- Santana C, et al. Molecular mimicry and autoimmunity. J Autoimmun. 2018;95:100–23. https://linkinghub.elsevier.com/retrieve/pii/S0896841118305365. 86. Vanderlugt CL, Miller SD. Epitope spreading in immune-mediated diseases: implications for immunotherapy. Nat Rev Immunol. 2002;2:85–95. http://www.nature.com/articles/nri724. 87. Pacheco Y, Acosta-Ampudia Y, Monsalve DM, Chang C, Gershwin ME, Anaya J-M. Bystander activation and autoimmunity. J Autoimmun. 2019;103:102301. https://linkinghub.elsevier.com/retrieve/pii/S0896841119303142. 88. Moulton VR, Tsokos GC. T cell signaling abnormalities contribute to aberrant immune cell function and autoimmunity. J Clin Invest. 2015;125:2220–7. http://www.jci.org/articles/ view/78087. 89. Rawlings DJ, Metzler G, Wray-Dutra M, Jackson SW. Altered B cell signalling in autoimmunity. Nat Rev Immunol. 2017;17:421–36. http://www.nature.com/articles/nri.2017.24. 90. Luchicchi A, Preziosa P, ‘t Hart B. Editorial: “Inside-out” vs “outside-in” paradigms in multiple sclerosis etiopathogenesis. Front Cell Neurosci. 2021;15:666529. https://www.frontiersin.org/articles/10.3389/fncel.2021.666529/full. 91. Lanzavecchia A. How can cryptic epitopes trigger autoimmunity? J Exp Med. 1995;181:1945–8. https://rupress.org/jem/article/181/6/1945/57581/ How-can-cryptic-epitopes-trigger-autoimmunity. 92. Warnock MG, Goodacre JA. Cryptic T-cell epitopes and their role in the pathogenesis of autoimmune diseases. Rheumatology. 1997;36:1144–50. https://academic.oup.com/ rheumatology/article-lookup/doi/10.1093/rheumatology/36.11.1144. 93. Moudgil KD. Viewing autoimmune pathogenesis from the perspective of antigen processing and determinant hierarchy. Crit Rev Immunol. 2020;40:329–39. http://www.dl.begellhouse. com/journals/2ff21abf44b19838,0060188a5a3e46cd,0b22cf7f7b8cc340.html. 94. Doyle HA, Mamula MJ. Autoantigenesis: the evolution of protein modifications in autoimmune disease. Curr Opin Immunol. 2012;24:112–8. http://linkinghub.elsevier.com/retrieve/ pii/S0952791511001786. 95. Doyle HA, Yang M-L, Raycroft MT, Gee RJ, Mamula MJ. Autoantigens: novel forms and presentation to the immune system. Autoimmunity. 2014;47:220–33. http://www.tandfonline.com/doi/full/10.3109/08916934.2013.850495.
442
6 Basic Trajectories in Autoimmunity
96. Yin L, Dai S, Clayton G, Gao W, Wang Y, Kappler J, et al. Recognition of self and altered self by T cells in autoimmunity and allergy. Protein Cell. 2013;4:8–16. http://link.springer. com/10.1007/s13238-012-2077-7. 97. Yang M-L, Doyle HA, Clarke SG, Herold KC, Mamula MJ. Oxidative modifications in tissue pathology and autoimmune disease. Antioxid Redox Signal. 2018;29:1415–31. https://www. liebertpub.com/doi/10.1089/ars.2017.7382. 98. Liu J, Qian C, Cao X. Post-translational modification control of innate immunity. Immunity. 2016;45:15–30. http://linkinghub.elsevier.com/retrieve/pii/S1074761316302424. 99. Clemen R, Bekeschus S. Oxidatively modified proteins: cause and control of diseases. Appl Sci. 2020;10:6419. https://www.mdpi.com/2076-3417/10/18/6419/htm. 100. Rubtsov AV, Rubtsova K, Kappler JW, Jacobelli J, Friedman RS, Marrack P. CD11cexpressing B cells are located at the T cell/B cell border in spleen and are potent APCs. J Immunol. 2015;195:71–9. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1500055. 101. Rubtsova K, Rubtsov AV, Thurman JM, Mennona JM, Kappler JW, Marrack P. B cells expressing the transcription factor T-bet drive lupus-like autoimmunity. J Clin Invest. 2017;127:1392–404. https://www.jci.org/articles/view/91250. 102. Mahajan A, Herrmann M, Muñoz LE. Clearance deficiency and cell death pathways: a model for the pathogenesis of SLE. Front Immunol. 2016;7:35. http://journal.frontiersin.org/ Article/10.3389/fimmu.2016.00035/abstract. 103. Das A, Heesters BA, Bialas A, O’Flynn J, Rifkin IR, Ochando J, et al. Follicular dendritic cell activation by TLR ligands promotes autoreactive B cell responses. Immunity. 2017;46:106–19. http://linkinghub.elsevier.com/retrieve/pii/S1074761316305209. 104. Abd El-Aleem SA, Saber EA, Aziz NM, El-Sherif H, Abdelraof AM, Djouhri L. Follicular dendritic cells. J Cell Physiol. 2022;237(4):2019–33. https://onlinelibrary.wiley.com/ doi/10.1002/jcp.30662. 105. Parks C, Miller F, Pollard K, Selmi C, Germolec D, Joyce K, et al. Expert panel workshop consensus statement on the role of the environment in the development of autoimmune disease. Int J Mol Sci. 2014;15:14269–97. http://www.mdpi.com/1422-0067/15/8/14269. 106. Vojdani A. A potential link between environmental triggers and autoimmunity. Autoimmune Dis. 2014;2014:437231. http://www.hindawi.com/journals/ad/2014/437231/. 107. Anaya J-M, Ramirez-Santana C, Alzate MA, Molano-Gonzalez N, Rojas-Villarraga A. The autoimmune ecology. Front Immunol. 2016;7:139. http://journal.frontiersin.org/ Article/10.3389/fimmu.2016.00139/abstract. 108. Anaya J-M. The autoimmune tautology. A summary of evidence. Joint Bone Spine. 2017;84:251–3. http://linkinghub.elsevier.com/retrieve/pii/S1297319X16302184. 109. Anaya J-M, Restrepo-Jiménez P, Ramírez-Santana C. The autoimmune ecology: an update. Curr Opin Rheumatol. 2018;30:350–60. https://journals.lww. com/00002281-201807000-00010. 110. Land WG. The role of damage-associated molecular patterns in human diseases: Part I— promoting inflammation and immunity. Sultan Qaboos Univ Med J. 2015;15:9–21. https:// pubmed.ncbi.nlm.nih.gov/25685392/. 111. Pollard KM, Christy JM, Cauvi DM, Kono DH. Environmental xenobiotic exposure and autoimmunity. Curr Opin Toxicol. 2018;10:15–22. https://linkinghub.elsevier.com/retrieve/ pii/S2468202017301213. 112. Zhao T, Ren H, Wang X, Liu P, Yan F, Jiang W, et al. Rituximab-induced HMGB1 release is associated with inhibition of STAT3 activity in human diffuse large B-cell lymphoma. Oncotarget. 2015;6:27816–31. https://www.oncotarget.com/lookup/doi/10.18632/ oncotarget.4816. 113. Ivanova OK, Sharapova TN, Romanova EA, Soshnikova NV, Sashchenko LP, Yashin DV. CD3 + CD8 + NKG2D + T lymphocytes induce apoptosis and necroptosis in HLA- negative cells via FasL–Fas interaction. J Cell Biochem. 2017;118:3359–66. https://onlinelibrary.wiley.com/doi/10.1002/jcb.25990. 114. Parodi M, Pedrazzi M, Cantoni C, Averna M, Patrone M, Cavaletto M, et al. Natural killer (NK)/melanoma cell interaction induces NK-mediated release of chemotactic high mobil-
References
443
ity group box-1 (HMGB1) capable of amplifying NK cell recruitment. Oncoimmunology. 2015;4:e1052353. http://www.tandfonline.com/doi/full/10.1080/2162402X.2015.1052353. 115. Wu H, Chen Z, Xie J, Kang L-N, Wang L, Xu B. High mobility group box-1: a missing link between diabetes and its complications. Mediators Inflamm. 2016;2016:1–11. https://www. hindawi.com/journals/mi/2016/3896147/. 116. Han J, Zhong J, Wei W, Wang Y, Huang Y, Yang P, et al. Extracellular high-mobility group box 1 acts as an innate immune mediator to enhance autoimmune progression and diabetes onset in NOD mice. Diabetes. 2008;57:2118–27. http://diabetes.diabetesjournals.org/cgi/ doi/10.2337/db07-1499. 117. Jung SM, Lee J, Baek SY, Lee J, Jang SG, Hong S-M, et al. Ethyl pyruvate ameliorates inflammatory arthritis in mice. Int Immunopharmacol. 2017;52:333–41. http://linkinghub. elsevier.com/retrieve/pii/S156757691730365X. 118. Mohammad Hosseini A, Majidi J, Baradaran B, Yousefi M. Toll-like receptors in the pathogenesis of autoimmune diseases. Adv Pharm Bull. 2015;5:605–14. http://journals.tbzmed. ac.ir/APB/Abstract/APB_1811_20140524173829. 119. Joffre OP, Segura E, Savina A, Amigorena S. Cross-presentation by dendritic cells. Nat Rev Immunol. 2012;12:557–69. http://www.nature.com/doifinder/10.1038/nri3254. 120. Lapaquette P, Guzzo J, Bretillon L, Bringer M-A. Cellular and molecular connections between autophagy and inflammation. Mediators Inflamm. 2015;2015:398483. http://www. hindawi.com/journals/mi/2015/398483/. 121. Hetz C. The unfolded protein response: controlling cell fate decisions under ER stress and beyond. Nat Rev Mol Cell Biol. 2012;13:89–102. http://www.nature.com/articles/nrm3270. 122. Malhotra JD, Kaufman RJ. Endoplasmic reticulum stress and oxidative stress: a vicious cycle or a double-edged sword? Antioxid Redox Signal. 2007;9:2277–94. http://www.liebertpub. com/doi/10.1089/ars.2007.1782. 123. Martinon F, Glimcher LH. Regulation of innate immunity by signaling pathways emerging from the endoplasmic reticulum. Curr Opin Immunol. 2011;23:35–40. https://linkinghub. elsevier.com/retrieve/pii/S095279151000169X. 124. Fousert E, Toes R, Desai J. Neutrophil extracellular traps (NETs) take the central stage in driving autoimmune responses. Cells. 2020;9:915. https://www.mdpi.com/2073-4409/9/4/915. 125. Goel RR, Kaplan MJ. Deadliest catch: neutrophil extracellular traps in autoimmunity. Curr Opin Rheumatol. 2020;32:64–70. https://journals.lww.com/10.1097/ BOR.0000000000000667. 126. Nimmerjahn F, Ravetch JV. Fcγ receptors as regulators of immune responses. Nat Rev Immunol. 2008;8:34–47. http://www.nature.com/articles/nri2206 127. WangY, Jönsson F. Expression, role, and regulation of neutrophil Fcγ receptors. Front Immunol. 2019;10:1958. https://www.frontiersin.org/article/10.3389/fimmu.2019.01958/full. 128. Monteiro RC, Kubagawa H, Cooper MD. Cellular distribution, regulation, and biochemical nature of an Fc alpha receptor in humans. J Exp Med. 1990;171:597–613. https://rupress.org/ jem/article/171/3/597/50101/Cellular-distribution-regulation-and-biochemical. 129. Brandsma AM, Bondza S, Evers M, Koutstaal R, Nederend M, Jansen JHM, et al. Potent Fc receptor signaling by IgA leads to superior killing of cancer cells by neutrophils compared to IgG. Front Immunol. 2019;10:704. https://www.frontiersin.org/article/10.3389/ fimmu.2019.00704/full. 130. Wang TT, Ravetch JV. Functional diversification of IgGs through Fc glycosylation. J Clin Invest. 2019;129:3492–8. https://www.jci.org/articles/view/130029. 131. Liu S, Liu X. IgG N-glycans. Adv Clin Chem. 2021;105:1–47. https://linkinghub.elsevier. com/retrieve/pii/S0065242321000123. 132. Cobb BA. The history of IgG glycosylation and where we are now. Glycobiology. 2020;30:202–13. https://academic.oup.com/glycob/article/30/4/202/5554875. 133. Niwa R, Sakurada M, Kobayashi Y, Uehara A, Matsushima K, Ueda R, et al. Enhanced natural killer cell binding and activation by low-fucose IgG1 antibody results in potent antibody-dependent cellular cytotoxicity induction at lower antigen density. Clin Cancer Res. 2005;11:2327–36. http://clincancerres.aacrjournals.org/lookup/doi/10.1158/1078-0432. CCR-04-2263.
444
6 Basic Trajectories in Autoimmunity
134. Scherer HU, van der Woude D, Ioan-Facsinay A, el Bannoudi H, Trouw LA, Wang J, et al. Glycan profiling of anti-citrullinated protein antibodies isolated from human serum and synovial fluid. Arthritis Rheum. 2010;62:1620–9. https://onlinelibrary.wiley.com/doi/10.1002/ art.27414. 135. Wuhrer M, Selman MHJ, McDonnell LA, Kümpfel T, Derfuss T, Khademi M, et al. Pro-inflammatory pattern of IgG1 Fc glycosylation in multiple sclerosis cerebrospinal fluid. J Neuroinflammation. 2015;12:235. http://www.jneuroinflammation.com/ content/12/1/235. 136. Wong AHY, Fukami Y, Sudo M, Kokubun N, Hamada S, Yuki N. Sialylated IgG-Fc: a novel biomarker of chronic inflammatory demyelinating polyneuropathy. J Neurol Neurosurg Psychiatry. 2016;87:275–9. https://jnnp.bmj.com/lookup/doi/10.1136/ jnnp-2014-309964. 137. Kaneko Y, Nimmerjahn F, Ravetch JV. Anti-inflammatory activity of immunoglobulin G resulting from Fc sialylation. Science. 2006;313:670–3. https://www.science.org/ doi/10.1126/science.1129594. 138. Aleyd E, Al M, Tuk CW, van der Laken CJ, van Egmond M. IgA complexes in plasma and synovial fluid of patients with rheumatoid arthritis induce neutrophil extracellular traps via FcαRI. J Immunol. 2016;197:4552–9. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1502353. 139. Behnen M, Leschczyk C, Möller S, Batel T, Klinger M, Solbach W, et al. Immobilized immune complexes induce neutrophil extracellular trap release by human neutrophil granulocytes via FcγRIIIB and Mac-1. J Immunol. 2014;193:1954–65. http://www.jimmunol.org/ lookup/doi/10.4049/jimmunol.1400478. 140. Alemán OR, Mora N, Cortes-Vieyra R, Uribe-Querol E, Rosales C. Differential use of human neutrophil Fc γ receptors for inducing neutrophil extracellular trap formation. J Immunol Res. 2016;2016:1–17. http://www.hindawi.com/journals/jir/2016/2908034/. 141. Chen K, Nishi H, Travers R, Tsuboi N, Martinod K, Wagner DD, et al. Endocytosis of soluble immune complexes leads to their clearance by FcγRIIIB but induces neutrophil extracellular traps via FcγRIIA in vivo. Blood. 2012;120:4421–31. https://ashpublications.org/blood/ article/120/22/4421/73051/Endocytosis-of-soluble-immune-complexes-leads-to. 142. Granger V, Peyneau M, Chollet-Martin S, de Chaisemartin L. Neutrophil extracellular traps in autoimmunity and allergy: immune complexes at work. Front Immunol. 2019;10:2824. https://www.frontiersin.org/article/10.3389/fimmu.2019.02824/full. 143. Chen T, Li Y, Sun R, Hu H, Liu Y, Herrmann M, et al. Receptor-mediated NETosis on neutrophils. Front Immunol. 2021;12:775267. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.775267/full. 144. Gimpel A-K, Maccataio A, Unterweger H, Sokolova MV, Schett G, Steffen U. IgA complexes induce neutrophil extracellular trap formation more potently than IgG complexes. Front Immunol. 2022;12:761816. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.761816/full. 145. Castanheira FVS, Kubes P. Neutrophils and NETs in modulating acute and chronic inflammation. Blood. 2019;133:2178–85. https://ashpublications.org/blood/ article/133/20/2178/273824/Neutrophils-and-NETs-in-modulating-acute-and. 146. Kelley JM, Monach PA, Ji C, Zhou Y, Wu J, Tanaka S, et al. IgA and IgG antineutrophil cytoplasmic antibody engagement of Fc receptor genetic variants influences granulomatosis with polyangiitis. Proc Natl Acad Sci. 2011;108:20736–41. https://pnas.org/doi/full/10.1073/ pnas.1109227109. 147. Khandpur R, Carmona-Rivera C, Vivekanandan-Giri A, Gizinski A, Yalavarthi S, Knight JS, et al. NETs are a source of citrullinated autoantigens and stimulate inflammatory responses in rheumatoid arthritis. Sci Transl Med. 2013;5:178ra40. https://www.science.org/doi/10.1126/ scitranslmed.3005580. 148. Huang H, Tohme S, Al-Khafaji AB, Tai S, Loughran P, Chen L, et al. Damage-associated molecular pattern-activated neutrophil extracellular trap exacerbates sterile inflammatory liver injury. Hepatology. 2015;62:600–14. https://onlinelibrary.wiley.com/doi/10.1002/ hep.27841.
References
445
149. Awasthi D, Nagarkoti S, Kumar A, Dubey M, Singh AK, Pathak P, et al. Oxidized LDL induced extracellular trap formation in human neutrophils via TLR-PKC-IRAK-MAPK and NADPH-oxidase activation. Free Radic Biol Med. 2016;93:190–203. https://linkinghub.elsevier.com/retrieve/pii/S0891584916000058. 150. Liu L, Mao Y, Xu B, Zhang X, Fang C, Ma Y, et al. Induction of neutrophil extracellular traps during tissue injury: involvement of STING and Toll-like receptor 9 pathways. Cell Prolif. 2019;52:e12579. https://onlinelibrary.wiley.com/doi/10.1111/cpr.12579. 151. Grootjans S, Vanden Berghe T, Vandenabeele P. Initiation and execution mechanisms of necroptosis: an overview. Cell Death Differ. 2017;24:1184–95. http://www.nature.com/ doifinder/10.1038/cdd.2017.65. 152. Zhang X, Wu J, Liu Q, Li X, Li S, Chen J, et al. mtDNA-STING pathway promotes necroptosis-dependent enterocyte injury in intestinal ischemia reperfusion. Cell Death Dis. 2020;11:1050. http://www.nature.com/articles/s41419-020-03239-6. 153. Jiao H, Wachsmuth L, Kumari S, Schwarzer R, Lin J, Eren RO, et al. Z-nucleic-acid sensing triggers ZBP1-dependent necroptosis and inflammation. Nature. 2020;580:391–5. http:// www.nature.com/articles/s41586-020-2129-8. 154. Yang D, Liang Y, Zhao S, Ding Y, Zhuang Q, Shi Q, et al. ZBP1 mediates interferon- induced necroptosis. Cell Mol Immunol. 2020;17:356–68. https://www.nature.com/articles/ s41423-019-0237-x. 155. Malireddi RKS, Kanneganti T-D. Role of type I interferons in inflammasome activation, cell death, and disease during microbial infection. Front Cell Infect Microbiol. 2013;3:77. http:// journal.frontiersin.org/article/10.3389/fcimb.2013.00077/abstract. 156. Yang Y, Wang H, Kouadir M, Song H, Shi F. Recent advances in the mechanisms of NLRP3 inflammasome activation and its inhibitors. Cell Death Dis. 2019;10:128. http://www.nature. com/articles/s41419-019-1413-8. 157. Burdette BE, Esparza AN, Zhu H, Wang S. Gasdermin D in pyroptosis. Acta Pharm Sin B. 2021;11:2768–82. https://linkinghub.elsevier.com/retrieve/pii/S2211383521000447. 158. Anthony RM, Nimmerjahn F, Ashline DJ, Reinhold VN, Paulson JC, Ravetch JV. Recapitulation of IVIG anti-inflammatory activity with a recombinant IgG Fc. Science. 2008;320:373–6. https://www.science.org/doi/10.1126/science.1154315. 159. Harre U, Lang SC, Pfeifle R, Rombouts Y, Frühbeißer S, Amara K, et al. Glycosylation of immunoglobulin G determines osteoclast differentiation and bone loss. Nat Commun. 2015;6:6651. http://www.nature.com/articles/ncomms7651. 160. Pagan JD, Kitaoka M, Anthony RM. Engineered sialylation of pathogenic antibodies in vivo attenuates autoimmune disease. Cell. 2018;172:564–577.e13. https://linkinghub.elsevier. com/retrieve/pii/S0092867417314319. 161. Wooldridge L, Ekeruche-Makinde J, van den Berg HA, Skowera A, Miles JJ, Tan MP, et al. A single autoimmune T cell receptor recognizes more than a million different peptides. J Biol Chem. 2012;287:1168–77. https://linkinghub.elsevier.com/retrieve/pii/ S002192582053353X. 162. Golstein P, Griffiths GM. An early history of T cell-mediated cytotoxicity. Nat Rev Immunol. 2018;18:527–35. http://www.nature.com/articles/s41577-018-0009-3. 163. Gálvez J, Gálvez JJ, García-Peñarrubia P. Is TCR/pMHC affinity a good estimate of the T-cell response? An answer based on predictions from 12 phenotypic models. Front Immunol. 2019;10:349. https://www.frontiersin.org/article/10.3389/fimmu.2019.00349/full. 164. Raskov H, Orhan A, Christensen JP, Gögenur I. Cytotoxic CD8+ T cells in cancer and cancer immunotherapy. Br J Cancer. 2021;124:359–67. https://www.nature.com/articles/ s41416-020-01048-4. 165. Walter U, Santamaria P. CD8+ T cells in autoimmunity. Curr Opin Immunol. 2005;17:624–31. http://linkinghub.elsevier.com/retrieve/pii/S0952791505001597. 166. Blanco P, Viallard J-F, Pellegrin J-L, Moreau J-F. Cytotoxic T lymphocytes and autoimmunity. Curr Opin Rheumatol. 2005;17:731–4. http://www.ncbi.nlm.nih.gov/pubmed/16224251. 167. Teillaud J-L, Teillaud J. Antibody-dependent cellular cytotoxicity (ADCC). eLS. Chichester: John Wiley & Sons, Ltd; 2012. http://doi.wiley.com/10.1002/9780470015902. a0000498.pub2.
446
6 Basic Trajectories in Autoimmunity
168. Lintner KE, Wu YL, Yang Y, Spencer CH, Hauptmann G, Hebert LA, et al. Early components of the complement classical activation pathway in human systemic autoimmune diseases. Front Immunol. 2016;7:36. http://journal.frontiersin.org/Article/10.3389/fimmu.2016.00036/ abstract. 169. Mayadas TN, Tsokos GC, Tsuboi N. Mechanisms of immune complex-mediated neutrophil recruitment and tissue injury. Circulation. 2009;120:2012–24. http://circ.ahajournals.org/cgi/ doi/10.1161/CIRCULATIONAHA.108.771170. 170. Wang T, Liu M, Zheng S-J, Bian D-D, Zhang J-Y, Yao J, et al. Tumor-associated autoantibodies are useful biomarkers in immunodiagnosis of α-fetoprotein-negative hepatocellular carcinoma. World J Gastroenterol. 2017;23:3496–504. http://www.wjgnet.com/1007-9327/ full/v23/i19/3496.htm. 171. Castiblanco J, Anaya J-M. The nature and nurture of common autoimmunity. Ann N Y Acad Sci. 2007;1109:1–8. http://doi.wiley.com/10.1196/annals.1398.001. 172. Brodin P, Jojic V, Gao T, Bhattacharya S, Angel CJL, Furman D, et al. Variation in the human immune system is largely driven by non-heritable influences. Cell. 2015;160:37–47. http:// www.ncbi.nlm.nih.gov/pubmed/25594173. 173. Pollard KM. Environment, autoantibodies, and autoimmunity. Front Immunol. 2015;6:60. http://journal.frontiersin.org/Article/10.3389/fimmu.2015.00060/abstract. 174. Pollard KM, Cauvi DM, Mayeux JM, Toomey CB, Peiss AK, Hultman P, et al. Mechanisms of environment-induced autoimmunity. Annu Rev Pharmacol Toxicol. 2021;61:135–57. https://www.annualreviews.org/doi/10.1146/annurev-pharmtox-031320-111453. 175. Baxter AG. Modelling the effects of genetic and environmental factors on the risk of autoimmune disease. J Autoimmun. 2001;16:331–5. http://www.ncbi.nlm.nih.gov/ pubmed/11334500. 176. Floreani A, Leung PSC, Gershwin ME. Environmental basis of autoimmunity. Clin Rev Allergy Immunol. 2016;50:287–300. http://www.ncbi.nlm.nih.gov/pubmed/25998909. 177. Parks CG, de Souza Espindola Santos A, Barbhaiya M, Costenbader KH. Understanding the role of environmental factors in the development of systemic lupus erythematosus. Best Pract Res Clin Rheumatol. 2017;31:306–20. http://www.ncbi.nlm.nih.gov/ pubmed/29224673. 178. Rosser EC, Mauri C. A clinical update on the significance of the gut microbiota in systemic autoimmunity. J Autoimmun. 2016;74:85–93. http://linkinghub.elsevier.com/retrieve/pii/ S0896841116300877. 179. Generali E, Ceribelli A, Stazi MA, Selmi C. Lessons learned from twins in autoimmune and chronic inflammatory diseases. J Autoimmun. 2017;83:51–61. http://linkinghub.elsevier. com/retrieve/pii/S0896841117302469. 180. Khan MF, Wang H. Environmental exposures and autoimmune diseases: contribution of gut microbiome. Front Immunol. 2020;10:3094. https://www.frontiersin.org/article/10.3389/ fimmu.2019.03094/full. 181. Marshak-Rothstein A. Autoimmunity-promoting and stabilizing innate immunity “UNWUCHT”. Immunol Rev. 2016;269:7–10. http://www.ncbi.nlm.nih.gov/ pubmed/26683141. 182. Sarhan M, von Mässenhausen A, Hugo C, Oberbauer R, Linkermann A. Immunological consequences of kidney cell death. Cell Death Dis. 2018;9:114. http://www.nature.com/articles/ s41419-017-0057-9. 183. Prasad S, Starck SR, Shastri N. Presentation of cryptic peptides by MHC class I is enhanced by inflammatory stimuli. J Immunol. 2016;197:2981–91. http://www.jimmunol.org/lookup/ doi/10.4049/jimmunol.1502045. 184. Damian RT. Molecular mimicry in biological adaptation. Science. 1965;147:824. http:// www.ncbi.nlm.nih.gov/pubmed/17793550. 185. Blank M, Barzilai O, Shoenfeld Y. Molecular mimicry and auto-immunity. Clin Rev Allergy Immunol. 2007;32:111–8. http://www.ncbi.nlm.nih.gov/pubmed/17426366. 186. Cusick MF, Libbey JE, Fujinami RS. Molecular mimicry as a mechanism of autoimmune disease. Clin Rev Allergy Immunol. 2012;42:102–11. http://www.ncbi.nlm.nih.gov/ pubmed/22095454.
References
447
187. Jara LJ, Medina G, Saavedra MA. Autoimmune manifestations of infections. Curr Opin Rheumatol. 2018;30(4):373–9. http://www.ncbi.nlm.nih.gov/pubmed/29528865. 188. Lehmann PV, Forsthuber T, Miller A, Sercarz EE. Spreading of T-cell autoimmunity to cryptic determinants of an autoantigen. Nature. 1992;358:155–7. http://www.nature.com/ articles/358155a0. 189. Cornaby C, Gibbons L, Mayhew V, Sloan CS, Welling A, Poole BD. B cell epitope spreading: mechanisms and contribution to autoimmune diseases. Immunol Lett. 2015;163:56–68. https://linkinghub.elsevier.com/retrieve/pii/S0165247814002557. 190. Mackay IR, Rowley MJ. Autoimmune epitopes: autoepitopes. Autoimmun Rev. 2004;3:487–92. https://linkinghub.elsevier.com/retrieve/pii/S1568997204001077. 191. Darrah E, Andrade F. NETs: the missing link between cell death and systemic autoimmune diseases? Front Immunol. 2012;3:428. http://journal.frontiersin.org/article/10.3389/ fimmu.2012.00428/abstract. 192. Kumar S, Calianese D, Birge RB. Efferocytosis of dying cells differentially modulate immunological outcomes in tumor microenvironment. Immunol Rev. 2017;280:149–64. http:// www.ncbi.nlm.nih.gov/pubmed/29027226. 193. Mistry P, Kaplan MJ. Cell death in the pathogenesis of systemic lupus erythematosus and lupus nephritis. Clin Immunol. 2017;185:59–73. http://www.ncbi.nlm.nih.gov/pubmed/27519955. 194. Bonaventura A, Liberale L, Carbone F, Vecchié A, Diaz-Cañestro C, Camici G, et al. The pathophysiological role of neutrophil extracellular traps in inflammatory diseases. Thromb Haemost. 2018;118:6–27. http://www.ncbi.nlm.nih.gov/pubmed/29304522. 195. Urban CF, Ermert D, Schmid M, Abu-Abed U, Goosmann C, Nacken W, et al. Neutrophil extracellular traps contain calprotectin, a cytosolic protein complex involved in host defense against Candida albicans. PLoS Pathog. 2009;5:e1000639. http://dx.plos.org/10.1371/journal.ppat.1000639. 196. Saffarzadeh M, Juenemann C, Queisser MA, Lochnit G, Barreto G, Galuska SP, et al. Neutrophil extracellular traps directly induce epithelial and endothelial cell death: a predominant role of histones. PLoS One. 2012;7:e32366. http://dx.plos.org/10.1371/journal. pone.0032366. 197. Chen Y, Liu Y, Lan T, Qin W, Zhu Y, Qin K, et al. Quantitative profiling of protein carbonylations in ferroptosis by an aniline-derived probe. J Am Chem Soc. 2018;140(13):4712–20. http://www.ncbi.nlm.nih.gov/pubmed/29569437. 198. Kay RA. TCR Gene polymorphisms and autoimmune disease. Eur J Immunogenet. 1996;23:161–77. https://onlinelibrary.wiley.com/doi/10.1111/j.1744-313X.1996.tb00279.x. 199. Sogkas G, Atschekzei F, Adriawan IR, Dubrowinskaja N, Witte T, Schmidt RE. Cellular and molecular mechanisms breaking immune tolerance in inborn errors of immunity. Cell Mol Immunol. 2021;18:1122–40. http://www.nature.com/articles/s41423-020-00626-z. 200. Vomund AN, Zinselmeyer BH, Hughes J, Calderon B, Valderrama C, Ferris ST, et al. Beta cells transfer vesicles containing insulin to phagocytes for presentation to T cells. Proc Natl Acad Sci U S A. 2015;112:E5496–502. http://www.pnas.org/lookup/doi/10.1073/ pnas.1515954112. 201. Hamam HJ, Palaniyar N. Post-translational modifications in NETosis and NETs-mediated diseases. Biomolecules. 2019;9:369. https://pubmed.ncbi.nlm.nih.gov/31416265/. 202. Wei X, Yi X, Zhu X-H, Jiang D-S. Posttranslational modifications in ferroptosis. Oxid Med Cell Longev. 2020;2020:1–12. https://www.hindawi.com/journals/omcl/2020/8832043/. 203. Romero V, Fert-Bober J, Nigrovic PA, Darrah E, Haque UJ, Lee DM, et al. Immune-mediated pore-forming pathways induce cellular hypercitrullination and generate citrullinated autoantigens in rheumatoid arthritis. Sci Transl Med. 2013;5:209ra150. http://stm.sciencemag.org/ cgi/doi/10.1126/scitranslmed.3006869. 204. Valesini G, Gerardi MC, Iannuccelli C, Pacucci VA, Pendolino M, Shoenfeld Y. Citrullination and autoimmunity. Autoimmun Rev. 2015;14:490–7. http://www.ncbi.nlm.nih.gov/ pubmed/25636595. 205. Raposo B, Merky P, Lundqvist C, Yamada H, Urbonaviciute V, Niaudet C, et al. T cells specific for post-translational modifications escape intrathymic tolerance induction. Nat Commun. 2018;9:353. http://www.ncbi.nlm.nih.gov/pubmed/29367624.
448
6 Basic Trajectories in Autoimmunity
206. Yang M-L, Doyle HA, Clarke SG, Herold KC, Mamula MJ. Oxidative modifications in tissue pathology and autoimmune disease. Antioxid Redox Signal. 2018;29(14):1415–31. http:// www.ncbi.nlm.nih.gov/pubmed/29088923. 207. Ramani S, Pathak A, Dalal V, Paul A, Biswas S. Oxidative stress in autoimmune diseases: an under dealt malice. Curr Protein Pept Sci. 2020;21:611–21. https://www.eurekaselect. com/179361/article. 208. Tonnus W, Belavgeni A, Beuschlein F, Eisenhofer G, Fassnacht M, Kroiss M, et al. The role of regulated necrosis in endocrine diseases. Nat Rev Endocrinol. 2021;17:497–510. http:// www.nature.com/articles/s41574-021-00499-w. 209. Li P, Jiang M, Li K, Li H, Zhou Y, Xiao X, et al. Glutathione peroxidase 4–regulated neutrophil ferroptosis induces systemic autoimmunity. Nat Immunol. 2021;22:1107–17. https:// www.nature.com/articles/s41590-021-00993-3. 210. Lin W, Shen P, Song Y, Huang Y, Tu S. Reactive oxygen species in autoimmune cells: function, differentiation, and metabolism. Front Immunol. 2021;12:635021. https://www.frontiersin.org/articles/10.3389/fimmu.2021.635021/full. 211. Kang K, Lee S-R, Piao X, Hur GM. Post-translational modification of the death receptor complex as a potential therapeutic target in cancer. Arch Pharm Res. 2019;42:76–87. http:// link.springer.com/10.1007/s12272-018-01107-8. 212. Vojdani A. A potential link between environmental triggers and autoimmunity. Autoimmune Dis. 2014;2014:1–18. http://www.hindawi.com/journals/ad/2014/437231/. 213. Land WG. The role of damage-associated molecular patterns (DAMPs) in human diseases: part II: DAMPs as diagnostics, prognostics and therapeutics in clinical medicine. Sultan Qaboos Univ Med J. 2015;15:e157–70. http://www.ncbi.nlm.nih.gov/pubmed/26052447. 214. He S, Mao X, Sun H, Shirakawa T, Zhang H, Wang X. Potential therapeutic targets in the process of nucleic acid recognition: opportunities and challenges. Trends Pharmacol Sci. 2015;36:51–64. http://www.ncbi.nlm.nih.gov/pubmed/25479797. 215. Magna M, Pisetsky DS. The role of cell death in the pathogenesis of SLE: is pyroptosis the missing link? Scand J Immunol. 2015;82:218–24. http://www.ncbi.nlm.nih.gov/ pubmed/26118732. 216. Maverakis E, Kim K, Shimoda M, Gershwin ME, Patel F, Wilken R, et al. Glycans in the immune system and the altered glycan theory of autoimmunity: a critical review. J Autoimmun. 2015;57:1–13. http://www.ncbi.nlm.nih.gov/pubmed/25578468. 217. O’Reilly S. Pound the alarm: danger signals in rheumatic diseases. Clin Sci (Lond). 2015;128:297–305. http://www.ncbi.nlm.nih.gov/pubmed/25394289. 218. Shin JJ, Lee EK, Park TJ, Kim W. Damage-associated molecular patterns and their pathological relevance in diabetes mellitus. Ageing Res Rev. 2015;24:66–76. http://www.ncbi.nlm.nih. gov/pubmed/26197086. 219. Man SM, Karki R, Kanneganti T-D. AIM2 inflammasome in infection, cancer, and autoimmunity: role in DNA sensing, inflammation, and innate immunity. Eur J Immunol. 2016;46:269–80. https://onlinelibrary.wiley.com/doi/10.1002/eji.201545839. 220. Liu L, Tang Z, Zeng Y, Liu Y, Zhou L, Yang S, et al. Role of necroptosis in infection-related, immune-mediated, and autoimmune skin diseases. J Dermatol. 2021;48:1129–38. https:// onlinelibrary.wiley.com/doi/10.1111/1346-8138.15929. 221. Wu J, Sun J, Meng X. Pyroptosis by caspase-11 inflammasome-Gasdermin D pathway in autoimmune diseases. Pharmacol Res. 2021;165:105408. https://linkinghub.elsevier.com/ retrieve/pii/S1043661820317163. 222. Bogdanos DP, Smyk DS, Invernizzi P, Rigopoulou EI, Blank M, Pouria S, et al. Infectome: a platform to trace infectious triggers of autoimmunity. Autoimmun Rev. 2013;12:726–40. http://www.ncbi.nlm.nih.gov/pubmed/23266520. 223. Arango M-T, Shoenfeld Y, Cervera R, Anaya J-M. Infection and autoimmune diseases. Bogota: El Rosario University Press; 2013. https://www.ncbi.nlm.nih.gov/books/NBK459437/. 224. Shamriz O, Shoenfeld Y. Infections: a double-edge sword in autoimmunity. Curr Opin Rheumatol. 2018;30:365–72. https://journals.lww.com/00002281-201807000-00012.
References
449
225. Karthikeyan G, Guilherme L. Acute rheumatic fever. Lancet. 2018;392:161–74. https://linkinghub.elsevier.com/retrieve/pii/S0140673618309991. 226. Conti L, Annibale B, Lahner E. Autoimmune gastritis and gastric microbiota. Microorganisms. 2020;8:1827. https://www.mdpi.com/2076-2607/8/11/1827. 227. De Bona E, Lidani KCF, Bavia L, Omidian Z, Gremski LH, Sandri TL, et al. Autoimmunity in chronic chagas disease: a road of multiple pathways to cardiomyopathy? Front Immunol. 2018;9:1842. https://www.frontiersin.org/article/10.3389/fimmu.2018.01842/full. 228. Getts DR, Chastain EML, Terry RL, Miller SD. Virus infection, antiviral immunity, and autoimmunity. Immunol Rev. 2013;255:197–209. http://www.ncbi.nlm.nih.gov/ pubmed/23947356. 229. Galeotti C, Bayry J. Autoimmune and inflammatory diseases following COVID-19. Nat Rev Rheumatol. 2020;16:413–4. http://www.nature.com/articles/s41584-020-0448-7. 230. Saad MA, Alfishawy M, Nassar M, Mohamed M, Esene IN, Elbendary A. COVID-19 and autoimmune diseases: a systematic review of reported cases. Curr Rheumatol Rev. 2021;17:193–204. https://www.eurekaselect.com/187380/article. 231. Ehrenfeld M, Tincani A, Andreoli L, Cattalini M, Greenbaum A, Kanduc D, et al. Covid-19 and autoimmunity. Autoimmun Rev. 2020;19:102597. https://linkinghub.elsevier.com/ retrieve/pii/S1568997220301610. 232. Liu Y, Sawalha AH, Lu Q. COVID-19 and autoimmune diseases. Curr Opin Rheumatol. 2021;33:155–62. https://journals.lww.com/10.1097/BOR.0000000000000776. 233. Yong SJ. Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments. Infect Dis (Auckl). 2021;53:737–54. https://www.tandfonline.com/doi/full/1 0.1080/23744235.2021.1924397. 234. Land WG. Role of DAMPs in respiratory virus-induced acute respiratory distress syndrome— with a preliminary reference to SARS-CoV-2 pneumonia. Genes Immun. 2021;22(3):141–60. http://www.nature.com/articles/s41435-021-00140-w. 235. Angileri F, Legare S, Marino Gammazza A, Conway de Macario E, Macario AJ, Cappello F. Molecular mimicry may explain multi-organ damage in COVID-19. Autoimmun Rev. 2020;19:102591. https://linkinghub.elsevier.com/retrieve/pii/S1568997220301555. 236. Novelli L, Motta F, De Santis M, Ansari AA, Gershwin ME, Selmi C. The JANUS of chronic inflammatory and autoimmune diseases onset during COVID-19—a systematic review of the literature. J Autoimmun. 2021;117:102592. https://linkinghub.elsevier.com/retrieve/pii/ S0896841120302274. 237. Shah S, Danda D, Kavadichanda C, Das S, Adarsh MB, Negi VS. Autoimmune and rheumatic musculoskeletal diseases as a consequence of SARS-CoV-2 infection and its treatment. Rheumatol Int. 2020;40:1539–54. https://link.springer.com/10.1007/s00296-020-04639-9. 238. Xiao X, Chang C. Diagnosis and classification of drug-induced autoimmunity (DIA). J Autoimmun. 2014;48–49:66–72. https://linkinghub.elsevier.com/retrieve/pii/ S0896841114000079. 239. Feld LG, Van Liew JB, Brentjens JR, Boylan JW. Renal lesions and proteinuria in the spontaneously hypertensive rat made normotensive by treatment. Kidney Int. 1981;20:606–14. http://www.ncbi.nlm.nih.gov/pubmed/7343711. 240. Handler J. Hydralazine-induced lupus erythematosis. J Clin Hypertens (Greenwich). 2012;14:133–6. http://www.ncbi.nlm.nih.gov/pubmed/22277146. 241. Ruiz-Magaña MJ, Martínez-Aguilar R, Lucendo E, Campillo-Davo D, Schulze-Osthoff K, Ruiz-Ruiz C. The antihypertensive drug hydralazine activates the intrinsic pathway of apoptosis and causes DNA damage in leukemic T cells. Oncotarget. 2016;7(16):21875–86. http:// www.ncbi.nlm.nih.gov/pubmed/26942461. 242. Sinha BK, Leinisch F, Bhattacharjee S, Mason RP. DNA cleavage and detection of DNA radicals formed from hydralazine and copper (II) by ESR and immuno-spin trapping. Chem Res Toxicol. 2014;27:674–82. http://www.ncbi.nlm.nih.gov/pubmed/24502259. 243. Guimarães LE, Baker B, Perricone C, Shoenfeld Y. Vaccines, adjuvants and autoimmunity. Pharmacol Res. 2015;100:190–209. http://www.ncbi.nlm.nih.gov/pubmed/26275795.
450
6 Basic Trajectories in Autoimmunity
244. Jounai N, Kobiyama K, Takeshita F, Ishii KJ. Recognition of damage-associated molecular patterns related to nucleic acids during inflammation and vaccination. Front Cell Infect Microbiol. 2012;2:168. http://www.ncbi.nlm.nih.gov/pubmed/23316484. 245. Vera-Lastra O, Medina G, Cruz-Dominguez MDP, Jara LJ, Shoenfeld Y. Autoimmune/ inflammatory syndrome induced by adjuvants (Shoenfeld’s syndrome): clinical and immunological spectrum. Expert Rev Clin Immunol. 2013;9:361–73. http://www.ncbi.nlm.nih.gov/ pubmed/23557271. 246. Krajewski PK, Szepietowski JC. Immune thrombocytopenic purpura associated with COVID-19 Pfizer-BioNTech BNT16B2b2 mRNA vaccine. J Eur Acad Dermatology Venereol. 2021;35:e626–7. https://onlinelibrary.wiley.com/doi/10.1111/jdv.17444. 247. Jacobs JW, Booth GS. COVID-19 and immune-mediated RBC destruction. Am J Clin Pathol. 2022;157(6):844–51. https://academic.oup.com/ajcp/advance-article/doi/10.1093/ajcp/ aqab210/6468807. 248. Avci E, Abasiyanik F. Autoimmune hepatitis after SARS-CoV-2 vaccine: new-onset or flare-up? J Autoimmun. 2021;125:102745. https://linkinghub.elsevier.com/retrieve/pii/ S0896841121001530. 249. Weintraub MA, Ameer B, Sinha GN. Graves disease following the SARS-CoV-2 vaccine: case series. J Investig Med High Impact Case Rep. 2021;9:232470962110633. http://journals. sagepub.com/doi/10.1177/23247096211063356. 250. Kanduc D, Shoenfeld Y. Molecular mimicry between SARS-CoV-2 spike glycoprotein and mammalian proteomes: implications for the vaccine. Immunol Res. 2020;68:310–3. https:// link.springer.com/10.1007/s12026-020-09152-6. 251. Caso F, Costa L, Ruscitti P, Navarini L, Del Puente A, Giacomelli R, et al. Could Sars- coronavirus- 2 trigger autoimmune and/or autoinflammatory mechanisms in genetically predisposed subjects? Autoimmun Rev. 2020;19:102524. https://linkinghub.elsevier.com/ retrieve/pii/S1568997220300793. 252. Velikova T, Georgiev T. SARS-CoV-2 vaccines and autoimmune diseases amidst the COVID-19 crisis. Rheumatol Int. 2021;41:509–18. http://link.springer.com/10.1007/ s00296-021-04792-9. 253. Rowley B, Monestier M. Mechanisms of heavy metal-induced autoimmunity. Mol Immunol. 2005;42:833–8. https://linkinghub.elsevier.com/retrieve/pii/S0161589004004146. 254. Rachmawati D, Bontkes HJ, Verstege MI, Muris J, von Blomberg BME, Scheper RJ, et al. Transition metal sensing by Toll-like receptor-4: next to nickel, cobalt and palladium are potent human dendritic cell stimulators. Contact Dermatitis. 2013;68:331–8. http://doi.wiley. com/10.1111/cod.12042. 255. Perricone C, Versini M, Ben-Ami D, Gertel S, Watad A, Segel MJ, et al. Smoke and autoimmunity: the fire behind the disease. Autoimmun Rev. 2016;15:354–74. http://www.ncbi.nlm. nih.gov/pubmed/26772647. 256. Hasday JD, Bascom R, Costa JJ, Fitzgerald T, Dubin W. Bacterial endotoxin is an active component of cigarette smoke. Chest. 1999;115:829–35. http://www.ncbi.nlm.nih.gov/ pubmed/10084499. 257. Schiopu A, Cotoi OS. S100A8 and S100A9: DAMPs at the crossroads between innate immunity, traditional risk factors, and cardiovascular disease. Mediators Inflamm. 2013;2013:828354. http://www.hindawi.com/journals/mi/2013/828354/. 258. Cotoi OS, Dunér P, Ko N, Hedblad B, Nilsson J, Björkbacka H, et al. Plasma S100A8/A9 correlates with blood neutrophil counts, traditional risk factors, and cardiovascular disease in middle-aged healthy individuals. Arterioscler Thromb Vasc Biol. 2014;34:202–10. http:// www.ncbi.nlm.nih.gov/pubmed/24202303. 259. Heijink IH, Pouwels SD, Leijendekker C, de Bruin HG, Zijlstra GJ, van der Vaart H, et al. Cigarette smoke-induced damage-associated molecular pattern release from necrotic neutrophils triggers proinflammatory mediator release. Am J Respir Cell Mol Biol. 2015;52:554–62. http://www.ncbi.nlm.nih.gov/pubmed/25192219. 260. Faiz A, Heijink IH, Vermeulen CJ, Guryev V, van den Berge M, Nawijn MC, et al. Cigarette smoke exposure decreases CFLAR expression in the bronchial epithelium, augmenting sus-
References
451
ceptibility for lung epithelial cell death and DAMP release. Sci Rep. 2018;8:12426. http:// www.nature.com/articles/s41598-018-30602-7. 261. Barbhaiya M, Costenbader K. Ultraviolet radiation and systemic lupus erythematosus. Lupus. 2014;23:588–95. http://www.ncbi.nlm.nih.gov/pubmed/24763542. 262. Kemp MG, Lindsey-Boltz LA, Sancar A. UV light potentiates STING (stimulator of interferon genes)-dependent innate immune signaling through deregulation of ULK1 (Unc51-like Kinase 1). J Biol Chem. 2015;290:12184–94. http://www.ncbi.nlm.nih.gov/ pubmed/25792739. 263. Johnson KE, Wulff BC, Oberyszyn TM, Wilgus TA. Ultraviolet light exposure stimulates HMGB1 release by keratinocytes. Arch Dermatol Res. 2013;305:805–15. http://www.ncbi. nlm.nih.gov/pubmed/23942756. 264. Sollid LM. The roles of MHC class II genes and post-translational modification in celiac disease. Immunogenetics. 2017;69:605–16. http://link.springer.com/10.1007/ s00251-017-0985-7. 265. Shewry P. What is gluten—why is it special? Front Nutr. 2019;6:101. https://www.frontiersin.org/article/10.3389/fnut.2019.00101/full. 266. Caio G, Volta U, Sapone A, Leffler DA, De Giorgio R, Catassi C, et al. Celiac disease: a comprehensive current review. BMC Med. 2019;17:142. https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-019-1380-z. 267. Gandini A, Gededzha MP, De Maayer T, Barrow P, Mayne E. Diagnosing coeliac disease: a literature review. Hum Immunol. 2021;82:930–6. https://linkinghub.elsevier.com/retrieve/ pii/S019888592100197X. 268. Herrera MG, Pizzuto M, Lonez C, Rott K, Hütten A, Sewald N, et al. Large supramolecular structures of 33-mer gliadin peptide activate toll-like receptors in macrophages. Nanomedicine. 2018;14:1417–27. https://linkinghub.elsevier.com/retrieve/pii/S1549963418300868. 269. Junker Y, Zeissig S, Kim S-J, Barisani D, Wieser H, Leffler DA, et al. Wheat amylase trypsin inhibitors drive intestinal inflammation via activation of toll-like receptor 4. J Exp Med. 2012;209:2395–408. http://www.ncbi.nlm.nih.gov/pubmed/23209313. 270. Raspé E, Costagliola S, Ruf J, Mariotti S, Dumont JE, Ludgate M. Identification of the thyroid Na+/I- cotransporter as a potential autoantigen in thyroid autoimmune disease. Eur J Endocrinol. 1995;132:399–405. http://www.ncbi.nlm.nih.gov/pubmed/7711875. 271. Yoshida A, Hisatome I, Taniguchi S, Shirayoshi Y, Yamamoto Y, Miake J, et al. Pendrin is a novel autoantigen recognized by patients with autoimmune thyroid diseases. J Clin Endocrinol Metab. 2009;94:442–8. http://www.ncbi.nlm.nih.gov/pubmed/19050049. 272. Rose NR, Bonita R, Burek CL. Iodine: an environmental trigger of thyroiditis. Autoimmun Rev. 2002;1:97–103. http://www.ncbi.nlm.nih.gov/pubmed/12849065. 273. Kawashima A, Yamazaki K, Hara T, Akama T, Yoshihara A, Sue M, et al. Demonstration of innate immune responses in the thyroid gland: potential to sense danger and a possible trigger for autoimmune reactions. Thyroid. 2013;23:477–87. http://www.ncbi.nlm.nih.gov/ pubmed/23234343. 274. Many MC, Maniratunga S, Varis I, Dardenne M, Drexhage HA, Denef JF. Two-step development of Hashimoto-like thyroiditis in genetically autoimmune prone non-obese diabetic mice: effects of iodine-induced cell necrosis. J Endocrinol. 1995;147:311–20. http://www. ncbi.nlm.nih.gov/pubmed/7490561. 275. Watad A, Neumann SG, Soriano A, Amital H, Shoenfeld Y. Vitamin D and systemic lupus erythematosus: myth or reality? Isr Med Assoc J. 2016;18:177–82. http://www.ncbi.nlm.nih. gov/pubmed/27228639. 276. Rosen Y, Daich J, Soliman I, Brathwaite E, Shoenfeld Y. Vitamin D and autoimmunity. Scand J Rheumatol. 2016;45(6):439–47. http://www.ncbi.nlm.nih.gov/pubmed/27191042. 277. Trochoutsou AI, Kloukina V, Samitas K, Xanthou G. Vitamin-D in the immune system: genomic and non-genomic actions. Mini Rev Med Chem. 2015;15:953–63. http://www.ncbi. nlm.nih.gov/pubmed/25985946. 278. Barragan M, Good M, Kolls JK. Regulation of dendritic cell function by vitamin D. Nutrients. 2015;7:8127–51. http://www.ncbi.nlm.nih.gov/pubmed/26402698.
452
6 Basic Trajectories in Autoimmunity
279. Mackay L, Kilbride L, Adamson KA, Chisholm J. Hormone replacement therapy for women with type 1 diabetes mellitus. Cochrane Database Syst Rev. 2013;(6):CD008613. http://www. ncbi.nlm.nih.gov/pubmed/23744560. 280. Khafagy AM, Stewart KI, Christianson MS, Tao Y, Blanck JF, Shen W. Effect of menopause hormone therapy on disease progression in systemic lupus erythematosus: a systematic review. Maturitas. 2015;81:276–81. http://www.ncbi.nlm.nih.gov/pubmed/25882762. 281. Williams WV. Hormonal contraception and the development of autoimmunity: a review of the literature. Linacre Q. 2017;84:275–95. http://www.ncbi.nlm.nih.gov/pubmed/28912620. 282. Campesi I, Sanna M, Zinellu A, Carru C, Rubattu L, Bulzomi P, et al. Oral contraceptives modify DNA methylation and monocyte-derived macrophage function. Biol Sex Differ. 2012;3:4. http://bsd.biomedcentral.com/articles/10.1186/2042-6410-3-4. 283. Pedram A, Razandi M, Evinger AJ, Lee E, Levin ER. Estrogen inhibits ATR signaling to cell cycle checkpoints and DNA repair. Mol Biol Cell. 2009;20:3374–89. http://www.molbiolcell.org/cgi/doi/10.1091/mbc.E09-01-0085. 284. Caldon CE. Estrogen signaling and the DNA damage response in hormone dependent breast cancers. Front Oncol. 2014;4:106. http://journal.frontiersin.org/article/10.3389/ fonc.2014.00106/abstract. 285. O’Driscoll CA, Mezrich JD. The aryl hydrocarbon receptor as an immune-modulator of atmospheric particulate matter-mediated autoimmunity. Front Immunol. 2018;9:2833. https://www.frontiersin.org/article/10.3389/fimmu.2018.02833/full. 286. Zhao C-N, Xu Z, Wu G-C, Mao Y-M, Liu L-N, Qian-Wu, et al. Emerging role of air pollution in autoimmune diseases. Autoimmun Rev. 2019;18:607–14. https://linkinghub.elsevier.com/ retrieve/pii/S1568997219300886. 287. Shukla A, Bunkar N, Kumar R, Bhargava A, Tiwari R, Chaudhury K, et al. Air pollution associated epigenetic modifications: transgenerational inheritance and underlying molecular mechanisms. Sci Total Environ. 2019;656:760–77. https://linkinghub.elsevier.com/retrieve/ pii/S0048969718347375. 288. Moon Y. Microbiome-linked crosstalk in the gastrointestinal exposome towards host health and disease. Pediatr Gastroenterol Hepatol Nutr. 2016;19:221. http://www.ncbi.nlm.nih.gov/ pubmed/28090466. 289. Kau AL, Ahern PP, Griffin NW, Goodman AL, Gordon JI. Human nutrition, the gut microbiome and the immune system. Nature. 2011;474:327–36. http://www.nature.com/articles/ nature10213. 290. Chervonsky AV. Microbiota and autoimmunity. Cold Spring Harb Perspect Biol. 2013;5:a007294. http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect.a007294. 291. Kuhn KA, Pedraza I, Demoruelle MK. Mucosal immune responses to microbiota in the development of autoimmune disease. Rheum Dis Clin North Am. 2014;40:711–25. https:// linkinghub.elsevier.com/retrieve/pii/S0889857X1400074X. 292. Lerner A, Aminov R, Matthias T. Dysbiosis may trigger autoimmune diseases via inappropriate post-translational modification of host proteins. Front Microbiol. 2016;7:84. http:// journal.frontiersin.org/Article/10.3389/fmicb.2016.00084/abstract. 293. Mu Q, Zhang H, Luo XM. SLE: another autoimmune disorder influenced by microbes and diet? Front Immunol. 2015;6:608. http://journal.frontiersin.org/Article/10.3389/ fimmu.2015.00608/abstract. 294. Wu X, He B, Liu J, Feng H, Ma Y, Li D, et al. Molecular insight into gut microbiota and rheumatoid arthritis. Int J Mol Sci. 2016;17:431. http://www.mdpi.com/1422-0067/17/3/431. 295. Knip M, Siljander H. The role of the intestinal microbiota in type 1 diabetes mellitus. Nat Rev Endocrinol. 2016;12:154–67. http://www.nature.com/articles/nrendo.2015.218. 296. Chen J, Chia N, Kalari KR, Yao JZ, Novotna M, Paz Soldan MM, et al. Multiple sclerosis patients have a distinct gut microbiota compared to healthy controls. Sci Rep. 2016;6:28484. http://www.nature.com/articles/srep28484. 297. Ignacio A, Morales CI, Câmara NOS, Almeida RR. Innate sensing of the gut microbiota: modulation of inflammatory and autoimmune diseases. Front Immunol. 2016;7:54. http:// journal.frontiersin.org/Article/10.3389/fimmu.2016.00054/abstract.
References
453
298. Opazo MC, Ortega-Rocha EM, Coronado-Arrázola I, Bonifaz LC, Boudin H, Neunlist M, et al. Intestinal microbiota influences non-intestinal related autoimmune diseases. Front Microbiol. 2018;9:432. http://www.ncbi.nlm.nih.gov/pubmed/29593681. 299. Wu HJ, Wu E. The role of gut microbiota in immune homeostasis and autoimmunity. Gut Microbes. 2012;3(1):4–14. http://www.ncbi.nlm.nih.gov/pubmed/22356853. 300. Ciocan D, Rebours V, Voican CS, Wrzosek L, Puchois V, Cassard A-M, et al. Characterization of intestinal microbiota in alcoholic patients with and without alcoholic hepatitis or chronic alcoholic pancreatitis. Sci Rep. 2018;8:4822. http://www.ncbi.nlm.nih.gov/ pubmed/29555983. 301. Petrasek J, Iracheta-Vellve A, Saha B, Satishchandran A, Kodys K, Fitzgerald KA, et al. Metabolic danger signals, uric acid and ATP, mediate inflammatory cross-talk between hepatocytes and immune cells in alcoholic liver disease. J Leukoc Biol. 2015;98:249–56. http:// www.ncbi.nlm.nih.gov/pubmed/25934928. 302. Cowan TE, Palmnäs MSA, Yang J, Bomhof MR, Ardell KL, Reimer RA, et al. Chronic coffee consumption in the diet-induced obese rat: impact on gut microbiota and serum metabolomics. J Nutr Biochem. 2014;25:489–95. http://www.ncbi.nlm.nih.gov/pubmed/24629912. 303. Bartling B, Fuchs C, Somoza V, Niemann B, Silber R-E, Simm A. Lung level of HMBG1 is elevated in response to advanced glycation end product-enriched food in vivo. Mol Nutr Food Res. 2007;51:479–87. http://doi.wiley.com/10.1002/mnfr.200600223. 304. Brown EM, Kenny DJ, Xavier RJ. Gut microbiota regulation of T cells during inflammation and autoimmunity. Annu Rev Immunol. 2019;37:599–624. https://www.annualreviews.org/ doi/10.1146/annurev-immunol-042718-041841. 305. Gomaa EZ. Human gut microbiota/microbiome in health and diseases: a review. Antonie Van Leeuwenhoek. 2020;113:2019–40. http://link.springer.com/10.1007/s10482-020-01474-7. 306. Hewagama A, Richardson B. The genetics and epigenetics of autoimmune diseases. J Autoimmun. 2009;33:3–11. http://linkinghub.elsevier.com/retrieve/pii/S0896841109000523. 307. Meda F, Folci M, Baccarelli A, Selmi C. The epigenetics of autoimmunity. Cell Mol Immunol. 2011;8:226–36. http://www.nature.com/articles/cmi201078. 308. Selmi C, Lu Q, Humble MC. Heritability versus the role of the environment in autoimmunity. J Autoimmun. 2012;39:249–52. http://linkinghub.elsevier.com/retrieve/pii/ S0896841112001072. 309. Seldin MF. The genetics of human autoimmune disease: a perspective on progress in the field and future directions. J Autoimmun. 2015;64:1–12. http://www.ncbi.nlm.nih.gov/ pubmed/26343334. 310. Ramos PS, Shedlock AM, Langefeld CD. Genetics of autoimmune diseases: insights from population genetics. J Hum Genet. 2015;60:657–64. http://www.nature.com/articles/ jhg201594. 311. Ding J, Frantzeskos A, Orozco G. Functional genomics in autoimmune diseases. Hum Mol Genet. 2020;29:R59–65. https://academic.oup.com/hmg/article/29/R1/R59/5838120. 312. Invernizzi P, Gershwin ME. The genetics of human autoimmune disease. J Autoimmun. 2009;33:290–9. http://www.ncbi.nlm.nih.gov/pubmed/19682858. 313. Suzuki A, Guerrini MM, Yamamoto K. Functional genomics of autoimmune diseases. Ann Rheum Dis. 2021;80:689–97. https://ard.bmj.com/lookup/doi/10.1136/ annrheumdis-2019-216794. 314. Ye Y, Zhang Z, Liu Y, Diao L, Han L. A multi-omics perspective of quantitative trait loci in precision medicine. Trends Genet. 2020;36:318–36. https://linkinghub.elsevier.com/retrieve/ pii/S0168952520300251. 315. Deitiker P, Atassi MZ. MHC genes linked to autoimmune disease. Crit Rev Immunol. 2015;35:203–51. http://www.ncbi.nlm.nih.gov/pubmed/26559228. 316. Sollid LM, Pos W, Wucherpfennig KW. Molecular mechanisms for contribution of MHC molecules to autoimmune diseases. Curr Opin Immunol. 2014;31:24–30. https://linkinghub. elsevier.com/retrieve/pii/S095279151400106X. 317. Deitiker P, Atassi MZ. Non-MHC genes linked to autoimmune disease. Crit Rev Immunol. 2012;32:193–285. http://www.ncbi.nlm.nih.gov/pubmed/23176726.
454
6 Basic Trajectories in Autoimmunity
318. So AY-L, Garcia-Flores Y, Minisandram A, Martin A, Taganov K, Boldin M, et al. Regulation of APC development, immune response, and autoimmunity by Bach1/HO-1 pathway in mice. Blood. 2012;120:2428–37. https://ashpublications.org/blood/article/120/12/2428/30556/ Regulation-of-APC-development-immune-response-and. 319. Zhou Y, Wu H, Zhao M, Chang C, Lu Q. The bach family of transcription factors: a comprehensive review. Clin Rev Allergy Immunol. 2016;50:345–56. https://link.springer. com/10.1007/s12016-016-8538-7. 320. Green DR, Oguin TH, Martinez J. The clearance of dying cells: table for two. Cell Death Differ. 2016;23:915–26. http://www.nature.com/articles/cdd2015172. 321. Arandjelovic S, Ravichandran KS. Phagocytosis of apoptotic cells in homeostasis. Nat Immunol. 2015;16:907–17. https://www.nature.com/articles/ni.3253. 322. Kumar S, Birge RB. Efferocytosis. Curr Biol. 2016;26:R558–9. https://linkinghub.elsevier. com/retrieve/pii/S0960982216300069. 323. Grabiec AM, Hussell T. The role of airway macrophages in apoptotic cell clearance following acute and chronic lung inflammation. Semin Immunopathol. 2016;38:409–23. http://link. springer.com/10.1007/s00281-016-0555-3. 324. McGaha TL, Karlsson MCI. Apoptotic cell responses in the splenic marginal zone: a paradigm for immunologic reactions to apoptotic antigens with implications for autoimmunity. Immunol Rev. 2016;269:26–43. https://onlinelibrary.wiley.com/doi/10.1111/imr.12382. 325. Biermann MH, Veissi S, Maueröder C, Chaurio R, Berens C, Herrmann M, et al. The role of dead cell clearance in the etiology and pathogenesis of systemic lupus erythematosus: dendritic cells as potential targets. Expert Rev Clin Immunol. 2014;10:1151–64. http://www. tandfonline.com/doi/full/10.1586/1744666X.2014.944162. 326. Grayson PC, Kaplan MJ. At the bench: neutrophil extracellular traps (NETs) highlight novel aspects of innate immune system involvement in autoimmune diseases. J Leukoc Biol. 2016;99:253–64. http://doi.wiley.com/10.1189/jlb.5BT0615-247R. 327. Chen R, Kang R, Fan X-G, Tang D. Release and activity of histone in diseases. Cell Death Dis. 2014;5:e1370. http://www.nature.com/articles/cddis2014337. 328. Gupta S, Kaplan MJ. The role of neutrophils and NETosis in autoimmune and renal diseases. Nat Rev Nephrol. 2016;12:402–13. http://www.nature.com/articles/nrneph.2016.71. 329. Hakkim A, Fürnrohr BG, Amann K, Laube B, Abed UA, Brinkmann V, et al. Impairment of neutrophil extracellular trap degradation is associated with lupus nephritis. Proc Natl Acad Sci U S A. 2010;107:9813–8. http://www.ncbi.nlm.nih.gov/pubmed/20439745. 330. Ding J, Frantzeskos A, Orozco G. Functional interrogation of autoimmune disease genetics using CRISPR/Cas9 technologies and massively parallel reporter assays. Semin Immunopathol. 2022;44(1):137–47. https://link.springer.com/10.1007/s00281-021-00887-4. 331. Dolcino M, Friso S, Selmi C, Lunardi C. Editorial: role of epigenetics in autoimmune diseases. Front Immunol. 2020;11:1284. https://doi.org/10.3389/FIMMU.2020.01284/BIBTEX. 332. Wu H, Zhao M, Yoshimura A, Chang C, Lu Q. Critical link between epigenetics and transcription factors in the induction of autoimmunity: a comprehensive review. Clin Rev Allergy Immunol. 2016;50:333–44. http://link.springer.com/10.1007/s12016-016-8534-y. 333. Allis CD, Jenuwein T. The molecular hallmarks of epigenetic control. Nat Rev Genet. 2016;17:487–500. http://www.nature.com/doifinder/10.1038/nrg.2016.59. 334. Araki Y, Mimura T. The histone modification code in the pathogenesis of autoimmune diseases. Mediators Inflamm. 2017;2017:1–12. http://www.ncbi.nlm.nih.gov/ pubmed/28127155. 335. Carnero-Montoro E, Alarcón-Riquelme ME. Epigenome-wide association studies for systemic autoimmune diseases: the road behind and the road ahead. Clin Immunol. 2018;196:21–33. http://www.ncbi.nlm.nih.gov/pubmed/29605707. 336. Wu H, Chen Y, Zhu H, Zhao M, Lu Q. The pathogenic role of dysregulated epigenetic modifications in autoimmune diseases. Front Immunol. 2019;10:2305. https://www.frontiersin.org/ article/10.3389/fimmu.2019.02305/full. 337. Surace AEA, Hedrich CM. The role of epigenetics in autoimmune/inflammatory disease. Front Immunol. 2019;10:1525. https://www.frontiersin.org/article/10.3389/ fimmu.2019.01525/full.
References
455
338. Rothbart SB, Strahl BD. Interpreting the language of histone and DNA modifications. Biochim Biophys Acta. 2014;1839:627–43. http://linkinghub.elsevier.com/retrieve/pii/ S1874939914000522. 339. Denker A, de Laat W. The second decade of 3C technologies: detailed insights into nuclear organization. Genes Dev. 2016;30:1357–82. http://genesdev.cshlp.org/lookup/doi/10.1101/ gad.281964.116. 340. Spielmann M, Mundlos S. Looking beyond the genes: the role of non-coding variants in human disease. Hum Mol Genet. 2016;25:R157–65. https://academic.oup.com/hmg/ article-lookup/doi/10.1093/hmg/ddw205. 341. Mazzone R, Zwergel C, Artico M, Taurone S, Ralli M, Greco A, et al. The emerging role of epigenetics in human autoimmune disorders. Clin Epigenetics. 2019;11:34. https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0632-2. 342. Wang Z, Long H, Chang C, Zhao M, Lu Q. Crosstalk between metabolism and epigenetic modifications in autoimmune diseases: a comprehensive overview. Cell Mol Life Sci. 2018;75(18):3353–69. http://www.ncbi.nlm.nih.gov/pubmed/29974127. 343. Radic M, Muller S. Epigenetics of autoantigens: new opportunities for therapy of autoimmune diseases. Genet Epigenet. 2013;5:63–70. http://www.ncbi.nlm.nih.gov/ pubmed/25512708. 344. Amit I, Winter DR, Jung S. The role of the local environment and epigenetics in shaping macrophage identity and their effect on tissue homeostasis. Nat Immunol. 2015;17:18–25. http://www.ncbi.nlm.nih.gov/pubmed/26681458. 345. Hu Y, Yan F, Ying L, Xu D. Emerging roles for epigenetic programming in the control of inflammatory signaling integration in heath and disease. Adv Exp Med Biol. 2017;1024:63–90. http://www.ncbi.nlm.nih.gov/pubmed/28921465. 346. Cheng S-C, Quintin J, Cramer RA, Shepardson KM, Saeed S, Kumar V, et al. mTOR- and HIF-1α–mediated aerobic glycolysis as metabolic basis for trained immunity. Science. 2014;345:1250684. https://www.science.org/doi/10.1126/science.1250684. 347. Saeed S, Quintin J, Kerstens HHD, Rao NA, Aghajanirefah A, Matarese F, et al. Epigenetic programming of monocyte-to-macrophage differentiation and trained innate immunity. Science. 2014;345:1251086. https://www.science.org/doi/10.1126/science.1251086. 348. Netea MG, Joosten LAB, Latz E, Mills KHG, Natoli G, Stunnenberg HG, et al. Trained immunity: a program of innate immune memory in health and disease. Science. 2016;352:aaf1098. https://www.science.org/doi/10.1126/science.aaf1098. 349. Bekkering S, Domínguez-Andrés J, Joosten LAB, Riksen NP, Netea MG. Trained immunity: reprogramming innate immunity in health and disease. Annu Rev Immunol. 2021;39:667–93. https://www.annualreviews.org/doi/10.1146/annurev-immunol-102119-073855. 350. Netea MG, Domínguez-Andrés J, Barreiro LB, Chavakis T, Divangahi M, Fuchs E, et al. Defining trained immunity and its role in health and disease. Nat Rev Immunol. 2020;20:375–88. http://www.nature.com/articles/s41577-020-0285-6. 351. Arts RJW, Joosten LAB, Netea MG. The potential role of trained immunity in autoimmune and autoinflammatory disorders. Front Immunol. 2018;9:298. http://journal.frontiersin.org/ article/10.3389/fimmu.2018.00298/full. 352. Nieborak A, Schneider R. Metabolic intermediates – cellular messengers talking to chromatin modifiers. Mol Metab. 2018;14:39–52. http://www.ncbi.nlm.nih.gov/ pubmed/29397344. 353. Grigoriou M, Banos A, Filia A, Pavlidis P, Giannouli S, Karali V, et al. Transcriptome reprogramming and myeloid skewing in haematopoietic stem and progenitor cells in systemic lupus erythematosus. Ann Rheum Dis. 2020;79:242–53. https://ard.bmj.com/lookup/ doi/10.1136/annrheumdis-2019-215782. 354. Busslinger M, Tarakhovsky A. Epigenetic control of immunity. Cold Spring Harb Perspect Biol. 2014;6:a019307. http://cshperspectives.cshlp.org/lookup/doi/10.1101/cshperspect. a019307. 355. Zhao M, Wang Z, Yung S, Lu Q. Epigenetic dynamics in immunity and autoimmunity. Int J Biochem Cell Biol. 2015;67:65–74. http://linkinghub.elsevier.com/retrieve/pii/ S1357272515001430.
456
6 Basic Trajectories in Autoimmunity
356. Nielsen HM, Tost J. Epigenetic changes in inflammatory and autoimmune diseases. Subcell Biochem. 2013;61:455–78. http://www.springerlink.com/ index/10.1007/978-94-007-4525-4_20. 357. Wang Z, Lu Q, Wang Z. Epigenetic alterations in cellular immunity: new insights into autoimmune diseases. Cell Physiol Biochem. 2017;41:645–60. http://www.ncbi.nlm.nih.gov/ pubmed/28214857. 358. Picascia A, Grimaldi V, Pignalosa O, De Pascale MR, Schiano C, Napoli C. Epigenetic control of autoimmune diseases: from bench to bedside. Clin Immunol. 2015;157:1–15. http:// linkinghub.elsevier.com/retrieve/pii/S1521661615000029.
7
DAMPs in Systemic Autoimmune Diseases
7.1 Introduction Systemic autoimmune diseases are a broad spectrum of autoantigen-related disorders that depend on the development of an autoimmune response to antigens that can be detected in almost any type of cell in the body. Consequently, pathological damage involves many different organs and tissues. The diseases are—not least because of their complexity—an impressive and fascinating but poorly understood group of disorders that include but are not limited to SLE, RA, SS, SSc, DM, AS, and antiphospholipid syndrome. Typically, these disorders often involve vital organs such as the lungs and kidneys, which can lead to life-threatening, sometimes fatal, outcomes. Moreover, mechanistically, the development of these diseases is still not very clear. It is now thought that environmental exposure to infectious or sterile injury or hormones and genetic/epigenetic factors are pathogenetically involved. A description of the entire clinical, biochemical, and immunological spectrum of these diseases is beyond the scope of this chapter. Instead, exemplary for the other systemic autoimmune diseases, only two prototypical disorders, SLE and RA, will be presented, focusing on the pathogenetic role of DAMPs and SAMPs.
7.2 Systemic Lupus Erythematosus 7.2.1 Introductory Remarks 7.2.1.1 General Remarks Systemic lupus erythematosus is a complex chronic autoimmune disorder with a variable clinical presentation commonly affecting skin, lungs, kidneys, and the CNS, classifying SLE as a typical systemic autoimmune disease. The disorder is highly heterogeneous, with different patients exhibiting different combinations of symptoms and laboratory features, affecting women (before menopause) nine times © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 W. G. Land, Damage-Associated Molecular Patterns in Human Diseases, https://doi.org/10.1007/978-3-031-21776-0_7
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more often than men. It is characterized by the action of autoreactive T and B cells and the presence of circulating antinuclear antibodies (ANAs), including autoantibodies with specificity for ssDNA and dsDNA and the Smith antigen (Sm), a non- histone nuclear RNA complex with ribonucleoprotein (RNP), present in spliceosomes. (The spliceosome is a large RNP complex primarily located within the nucleus of eukaryotic cells. The function of the spliceosome is to remove introns from messenger RNA precursors (pre-mRNA), for a recent review, see Wilkinson et al. [1].) Moreover, other autoantibodies interact with various NA constituents, nucleosomes, ribosomes, and RNA-binding proteins, that is, RNPs such as Ro60 La. These antibodies bind to NAs (DNA or RNA), proteins, and complexes of DNA or RNA with proteins [2, 3].
7.2.1.2 Clinical Picture and Classification Once becoming pathogenic, the autoantibodies are generally thought to trigger inflammation (mediated in part by ICs) that results in organ damage associated with a plethora of different clinical and immunological abnormalities, characterized by a relapsing and remitting clinical course. The immunological abnormalities that occur in SLE lead to multi-systemic involvement with many different possible clinical manifestations, including malar rash, discoid and subacute cutaneous lesions, photosensitivity, oral ulcers, constitutional symptoms (fever, weight loss, or fatigue), arthritis, serositis, myositis, nephropathy, cardiovascular changes, abdominal pain, hepatosplenomegaly, normochromic normocytic or hemolytic anemia, leukopenia, and thrombocytopenia. Neurologic or psychiatric manifestations, ranging from mild cognitive impairment to severe involvement, such as psychosis, seizures, and stroke, may also occur. Recently, the European League Against Rheumatism (EULAR), jointly with the American College of Rheumatology (ACR), has proposed new classification criteria, introducing the ANA positivity as an obligatory entry criterion and the additive, weighted multicriteria system. Over the past year, several studies evaluated the accuracy of the new criteria among broader and diversified populations (for further information, see [4–6]). The pathogenesis of SLE is still poorly understood, and multiple factors interplay in the development of the disorder, including—typical for a systemic AD—environmental, genetic, epigenetic, immunoregulatory, ethnic, and hormonal factors. Here, we will mainly focus on environmental, genetic, and epigenetic factors. For the other topics, as well as recent progress in other aspects of this disease during 2016–2021 not covered here, the reader is referred to reviews listed under [6–11].
7.2.2 Experimental Animal Models The use of experimental murine SLE models has considerably contributed to progress in the understanding of pathogenetic mechanisms involved in this autoimmune disease and how to treat them. For example, the genetically determined MRL/lpr
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and NZB/W mice serve as models for both systemic and neurological manifestations of SLE [12]. Such models encompass a spectrum ranging from inbred strains developing spontaneous diseases to experimentally induced, sometimes genetically manipulated animals [13]. Nearly all the models share in common the development of glomerulonephritis and autoantibodies, including antinuclear and DNA specificities. Li et al. [14] have recently reviewed this important topic and concluded: The use of murine models has led to discovery of potential therapeutic targets in diverse signaling pathways dysregulated in SLE. Immune cells including T cells, B cells, antigen-presenting cells, and macrophages, are all potential targets in different models of SLE. Clinical lupus is an extremely complex and diverse disease, and establishment of a mouse model with all features of the disease is very difficult. Various mouse models of SLE, spontaneous, induced or genetically engineered, have been used during the past 30 years, to answer the question of how the alteration of the immune system and target organs leads to break of tolerance to self.
7.2.3 Pathogenesis-Orchestrating Interrelationship Between Environmental Triggers, Genetic Predisposition, and Epigenetic Modifications 7.2.3.1 General Remarks Multifactorial environmental, pathogen-mediated, or sterile injurious stimuli are considered to promote and precipitate SLE in a genetically predisposed individual. Many of those insults are mediated by uncontrolled oxidative stress that contributes to functional oxidative epigenetic modifications of cellular protein, lipid, and DNA ([15, 16], also compare Fig. 6.7). Of note, oxidative stress and infection-mediated tissue damage—as any tissue injury in general—can be accompanied by massive cellular demise, mostly—if not exclusively—in the form of epigenetically regulated RCD. It is this occurrence of the RCD that is suspected of stimulating the generation of self and/or altered-self antigens on the one hand, but on the other hand, is recognized to serve as a prolific source for the emission of costimulation-mediating DAMPs. As discussed and shown by several studies, defects in the clearance of dying cells favor the development of autoimmunity [17, 18]. In addition, in view of the danger/injury model and in close adherence to a tautological approach as discussed in Sect. 6.2.3.6 and outlined in [19], environmental factors are defined here as agents that act themselves as exogenous DAMPs or produce (e.g., via induction of RCD) endogenous DAMPs in the host. And indeed, according to current knowledge, DAMPs—which also occasionally cause epigenetic changes—are involved at the beginning and at the end of the scenario of initiation and perpetuation of SLE and seem to play a crucial pathogenetic role in patients genetically predisposed to develop SLE (Fig. 7.1).
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7 DAMPs in Systemic Autoimmune Diseases Scenario Model: Pathogenesis of Systemic Lupus Erythematosus
Environmental factors e.g., UVR Smoking Infections Drugs
Regulated cell death
itive feed-forward-loop Pos nauAgs
e.g., NETosis, Pyroptosis Necroptosis
+ nuclear DAMPs Exog. DAMPs ?
activation
PRRexpressing APCs (cDCs, pDCs, FDCs, B cells)
AutoAbs + autoAgs / immune complexes
I nt er play e.g., HLA-II IRFs DNase I
e.g., Aberrant DNA methyl, Histone acetyl.
Genetic risk factors
Epigenetic modifications
Processed nauAg/MHC DAMP-induced costimulatory molecules T cell-polarizing cytokines → naive T cell activation
Innate immune response
AutoAbs T cells Tfh Th1,Th17
SLE disease
Adaptive immune response
Fig. 7.1 Simplified scheme of a tentatively designed scenario model of the pathogenesis of SLE. The scenario involves a complex interplay of factors and processes, including environmental factors, genetic risk factors, epigenetic modifications, induction of regulated cell death associated with defective clearance of dying cells as potent sources of autoantigens and DAMPs, DAMP-promoted innate and adaptive immune responses, generation of autoantigen/autoantibody immune complexes driving, via induction of NETosis, a DAMP-promoted positive feed-forward-loop in DAMPs emission, orchestrating continuously the autoimmune response. acetyl acetylation, APCs antigen-presenting cells, autoAbs autoantibodies, autoAgs autoantigens, cDCs conventional dendritic cells, Exog exogenous, FDCs follicular dendritic cells, HLA human leukocyte antigen, IRFs interferon regulatory factors, methyl methylation, MHC major histocompatibility complex, nauAgs nuclear autoantigens, pDCs plasmacytoid dendritic cells, PRR pattern recognition receptor, SLE systemic lupus erythematosus, Tfh follicular helper T cells, Th1/17 T helper cell type 1/17, UVR ultraviolet radiation
7.2.3.2 Environmental Factors and the Role of Regulated Cell Death Environmental factors that account for up to 70% of all ADs have already been briefly presented in Sect. 6.3.3 by referring to their role in inducing various subroutines of RCD. Their involvement in the pathogenesis of SLE has been comprehensively reviewed elsewhere [20–22]. Such factors include smoking [23, 24], exposure to silica [25], exposure to UVR [22, 26], viral infection by certain viruses (such as EBV, HCMV, CVB, IAV, HSVs, rotavirus, and human endogenous retroviruses) [27, 28], drug- and chemical-mediated insults (e.g., via hydralazine, procainamide, isoniazid, minocycline, diltiazem, and TNF inhibitors) [22, 29], and—though here difficult to integrate into this context—hormonal influence (estrogens and hormone therapy). Together, all these environment-mediated events act themselves as exogenous DAMPs (e.g., silica particles = Subclass IVA-3, see Vol. 1 [30], Sect. 15.2.4, p. 355) or reportedly induce severe cellular stress leading to subroutines of RCD including secondary necrosis after apoptosis, necroptosis, pyroptosis, ferroptosis, and NETosis, all known to be associated with the release of large amounts of nuclear and cytosolic DAMPs [17, 18, 31–33] (for RCD, see also Vol. 1 [30], Chap. 19, pp. 427–456, and Vol. 2 [34], Sect. 4.3, pp. 127–140; for RCD as sources of DAMPs in infections, see Sect. 3.7).
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The formation of vital NETs and lytic NETosis, whose triggering pathways have already been briefly described and illustrated in Sect. 3.7.7.2, Fig. 3.11a, b deserves a special note. Indeed, NETs and NETosis have been identified as key events in orchestrating autoimmune responses in SLE [35, 36]. As reported by Frangou et al. [37], NETosis in SLE neutrophils correlated with increased expression of the stress-response protein regulated in development and DNA damage responses 1 (REDD1). Endothelin-1 (ET-1)—denoted here as an inducible DAMP—and hypoxia-inducible factor-1α (HIF-1α) were found to be critical mediators of REDD1-driven NETs. In addition, SLE NETs were shown to be decorated with TF and IL-17A, which promote thrombosis (including atherothrombosis), inflammation, and fibrosis. And there is another important point that should be mentioned here: NET formation and NETosis in SLE are triggered not only by environmental factors but also by autoantigen/autoantibody ICs. This emerging issue has already been addressed in Sect. 6.2.4 and is discussed below in Sect. 7.2.9.4 with a focus on SLE. Among the various environmental factors, cigarette smoking is of particular importance. This unhealthy lifestyle habit has been reported to cause oxidative stress [38], necroptosis [39], and NETosis [40]. Likewise, UVR was shown to promote the generation of ROS that is associated with various forms of RCD, including necroptosis, ferroptosis, and NETosis [41–43]. Viral infections—as described in Sect. 3.7—were also recently discovered to be associated with forms of RN, such as necroptosis [44, 45], pyroptosis [46, 47], and NETosis [45, 48]. There is also evidence for drug-induced RN, for example, acetaminopheninduced necroptosis [49], chemotherapy drug-induced pyroptosis [50], and hydralazine- and tunicamycin-induced NETosis [51, 52]. Regarding the function of hormones in this context, one could discuss the unproven possibility that dysDAMPs in the form of hormonal modulation in DCs, for example, in terms of profound metabolic alterations, may promote the maturation of immunostimulatory DCs [53, 54]. Notably, there is increasing evidence suggesting that less apoptosis (although it is most often the subject of investigations related to SLE pathogenesis) but subroutines of RN are predominantly involved in SLE pathogenesis. Such a scenario would stress that—besides the potential generation of self and/or altered-self antigens— DAMPs are the key pathogenetic triggers of SLE. This is a plausible argumentation because—as described in Vol. 1 [30], Sect. 19.2.3, pp. 434/435, and Fig. 19.2— apoptotic cell death is far less a source of DAMPs in comparison to subroutines of RN. Nevertheless, it should not be ignored that apoptosis can progress to secondary necrosis [55], a process typically associated with the secretion of inducible DAMPs and the release of constitutive DAMPs. Taken together, environmental factors, representing an integral part of the pathogenesis of ADs (here, mainly triggering the initiation of SLE and subsequent flares), appear to exert their pathogenic effect by promotion of RCD in conjunction with the release of DAMPs. And to reiterate: all of these environmental events, in their role as sources of DAMPs, provide costimulation (signal 2) required for autoantigens (signal 1) to elicit robust autoimmune responses (cf. Fig. 6.2).
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7.2.3.3 Genetics It can be assumed that anyone who is extremely exposed to the environmental factors described here will emit DAMPs transiently to a greater or lesser extent during the course of RCD and thus suffer from transient mild, usually unnoticed, necroinflammation [32]; however, none of these individuals will develop SLE, even in the future. In fact, as many times stressed earlier, a pathogenetic effect of DAMPs in autoimmune diseases requires a genetic predisposition of individuals, and this is also true for SLE (for reviews, see [56–58]). In fact, numerous GWAS have been performed in patients with SLE across various ethnic populations, and currently, more than 40 common risk loci have been definitively linked to SLE susceptibility in case-control genetic studies. Environmental exposures of genetically predisposed individuals are thought to modify these SLE risk genes epigenetically, resulting in the development of clinical SLE manifestations. Typically, the most crucial association signal among the common genetic variants was found to be located in the HLA region, while many other non-HLA SLE susceptibility loci were detected within or near genes of functional relevance to the immune system. However, some other genetic loci associated with SLE susceptibility have been discovered that may not function within innate/adaptive immune system pathways and are obviously not related to the pathogenesis of SLE. In the following, several genes associated with SLE will be presented, including (1) genes related to clearance of cellular debris; (2) overrepresented genes involved in signaling, production, and response of type I IFN, that is, a cytokine that functions as an inducible DAMP and is capable of activating APCs after uptake of self or altered-self antigens; and (3) genes related to T cell and B cell signaling [15, 59–61]. HLA Region in Relation to SLE Susceptibility Among HLA regions, genes in MHC-II are dominantly represented as SLE susceptibility loci, in particular, HLA-DRB1 [62, 63]. These MHC-II alleles (specifically HLA-DR and HLA-DQ alleles) are discussed to be important in promoting autoantibody responses in SLE patients [62]. In addition, the MHC-III gene, super viralicidic activity 2-like (SKIV2L) encoding RNA helicase SKI2W enzyme, was identified as an SLE susceptibility risk gene independent of class II loci [64]. These and other studies not mentioned here highlight the crucial influence of MHC-HLA genes in SLE pathogenesis. Polygenic Influences on Type I IFN As thoroughly reviewed by Ghodke-Puranik and Niewold [57], genetic variations in three of the nine IRFs (IRF5, IRF7, and IRF8) associated with greater IFN-α in circulation (mostly produced by pDCs) have been linked to SLE susceptibility, supporting a key role for this family of proteins in SLE pathogenesis. As further reviewed by the authors, multiple studies have demonstrated a strong association between SLE and STAT4, interferon induced with helicase C domain 1 (IFIH1), and osteopontin (OPN) genes associated with increased sensitivity to IFN-α signaling. The gene STAT4 encodes STAT4, which plays an important role in downstream
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responses to type I IFN and other cytokines. Functionally, activation and phosphorylation of STAT4 are induced by IL-12, IL-23, and IFN-α, which then promotes Th1 as well as Th17 responses (for type I IFN, compare Vol. 1 [30], Sect. 14.2.3.3, p. 311, for JAK → STAT signaling, see Sect. 22.3.4.3 and Fig. 22.6, pp. 497–499, and again for type I IFN, see Sect. 22.5.5.2, pp. 535–538). Polygenic Influences on the Nuclear Factor-Kappa B Pathway As reviewed by Deng and Tsao [56], genes that function in the NF-κB pathway downstream of TLR engagement have been associated with increased SLE risk in multiple ancestries. For example, the gene tumor necrosis factor alpha-induced protein 3 (TNFAIP3) encodes a deubiquitinating enzyme (A20) that participates in the termination of NF-κB signaling. The authors outline that … A pair of tandem polymorphic dinucleotides (TT > A), downstream of the TNFAIP3 promoter, have been nominated as causal variants responsible for disease association with TNFAIP3…. The SLE-associated TT > A risk alleles with inefficient delivery of NFκB to the TNFAIP3 promoter via long-range DNA looping attenuate A20 expression, leading to enhanced NF-κB pathway activity that contributes to SLE. Monogenic Deficiencies in SLE As comprehensively reviewed by Ghodke-Puranik and Niewold [57], monogenic causes refer to complement components (C1q, C1r/s, C2, C4A, and C4B) which are strongly associated with increased susceptibility to SLE (for complement, see Sect. 4.4.3.4 and compare Vol. 1 [30], Sect. 23.2.2 and Fig. 23.1, pp. 593–598). Another monogenic cause can be seen in deoxyribonuclease I (DNase I, encoded by DNASE1), which is a specific endonuclease essential during the clearance of dying cells such as apoptotic and NETotic cells. The fact that incomplete apoptosis leads to secondary necrosis and NETosis associated with the release of cell contents, including chromatin-associated self-antigens and DAMPs, identifies DNAse I as a critical gene involved in SLE. Interestingly, the identification of the functional alleles of the nonsynonymous SNP is reportedly implicated in SLE in the human DNASE1 gene [15, 65, 66]. In this context, it is of interest that defects in phagocytosis have long been suggested to be inherited in patients suffering from SLE, a suggestion that has recently been experimentally confirmed [16]. Remarkably, in these studies on lupus-prone NZB mice with a non-autoimmune B6 genetic background (B6.NZBc13), a novel lupus susceptibility locus on NZB chromosome 13 was identified that impairs clearance of apoptotic debris. As stretches of dsRNA are found in mammalian apoptotic debris, the authors discussed that this clearance defect may interact directly with this B cell defect located within the c13 to augment the autoimmune phenotype by providing a source of endogenous TLR3 ligands. Gene Loci Mediating T and B Cell Signaling As also reviewed by Deng and Tsao [56], multiple loci that mediate signaling pathways in T and B cells are associated with SLE, supporting a central role of dysregulated adaptive immune lymphocytes in the pathogenesis of SLE. For example, the R620W SNP of PTPN22 is a well-characterized functional variant associated with
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multiple autoimmune diseases, including SLE. Both humans carrying the risk 620W allele and knock-in mice expressing the analogous 619W mutation show altered TCR and BCR signaling as well as enhanced B cell autoreactivity, demonstrating the consequences of the risk variant in modulating T and B cell autoimmunity. In addition, other genes encoding distinct functional proteins in BCR signaling, such as CSK, BANK1, and IKZF1, have also been identified as risk genes for lupus [56]. Programmed Cell Death 1 Gene Polymorphisms Mounting evidence demonstrates that impaired PD-1 ↔ PD-L function plays an important role in SLE and other ADs. By investigating the candidate genes, it was demonstrated that there is a higher risk of relevant genetic associations with developing ADs in certain ethnic groups [67] (for PD-1 ↔ PD-L, see Vol. 1. [30], Fig. 33.3, p. 800 and Sect. 33.3.5.4, p. 807). For example, a study of the association between programmed cell death 1 (PDCD1) and SLE susceptibility in the Malaysian population revealed the PD1.5 variant to be significantly associated with SLE susceptibility. In conclusion, these and other studies not mentioned here illustrate the wide diversity of molecular genetic mechanisms involved in SLE pathogenesis. The question is, however, what risk genes are responsible for the initiation of SLE and what risk genes are involved at the efferent arc in autoreactive CTL- and autoantibody- mediated tissue destruction. Moreover, though many SLE- predisposing genes have been identified, they cannot fully explain the SLE susceptibility associated with these genetic variations, and epigenetics may account for some of this unexplained heritability. Furthermore, the incomplete disease concordance rates in monozygotic twin studies in SLE (as low as 24%) would suggest epigenetic influences on SLE development. Thus, differences in epigenetic modifications such as DNA methylation, histone modifications, and noncoding RNA are now believed to affect the expression and function of genes involved in SLE pathogenesis [56, 57]. Accordingly, experimental data strongly suggests a complex interaction between the exposome (or environmental influences) and genome (genetic material) to produce epigenetic changes (epigenome) that can alter the expression of genetic material and lead to the development of disease in the susceptible individual.
7.2.3.4 Epigenetics The basics of epigenetic modifications in inflammation and fibrosis have been pointed out in Vol. 2, Sect. 5.6, Figs. 5.4, 5.5, and 5.6, pp. 169–194; and Sect. 6.6, Fig. 6.4, pp. 237–244. In a nutshell: All innate and adaptive immune cells involved in the regulation of inflammatory processes are confronted with the problem of controlling the requirement-dependent amounts and timing of expression of their various genes. Depending on the environmental circumstances, this control involves very short-term or relatively long-term but heritable modifications to the chromatin, albeit nonpermanent. Such modifications that do not change the DNA sequence are referred to as “epigenetic.” The resulting epigenetic effects maintain the various patterns of gene expression in different cell types. Hence, the expression of genes
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regulating innate immune processes such as pro-/antiinflammatory responses is not only controlled by MAMP-/DAMP-triggered transcriptional pathways but also by epigenetic modifications. Such epigenetic changes can generally be categorized into several major biochemical mechanisms, including changes in (1) DNA methylation (primarily CpG cytosine-5 methylation); (2) covalent histone PTMs such as histone acetylation-deacetylation, methylation-demethylation, phosphorylation, and ubiquitination; and (3) RNA-based mechanisms (action of lncRNAs and miRNAs; (for PTMs, also see Vol. 1 [30], Sect. 24.3, Fig. 24.2, pp. 646–649). Trained Immunity: An Example of Epigenetic Modifications The issue of trained immunity in the context of infection has been addressed in Sect. 4.3.9. One of the hallmarks of this emerging model is the growing evidence suggesting that not only MAMPs but also DAMPs such as oxLDL and OSE OxPLs are involved in triggering this concept in innate immunity. In a discussion of the pathogenetic role of epigenetics in SLE, the concept of innate immune memory comes up again. So far, there are no hard data from targeted studies available. But Badii et al. [68] have argued: Finally, transcriptomic profiling in patients with the disease reveals no differences when comparing active and inactive SLE. These results suggest that immune cells from inactive SLE patients maintain a transcriptomic profile resembling that of active SLE, despite favorable treatment [69]. Based on these results, it is tempting to speculate that these effects could be mediated by persistent epigenetic changes in trained immune cells. Epigenetic Modifications in Adaptive Immunity Epigenetic modifications have not only been detected in innate immune cells but also in T and B cells of the adaptive immune system [70, 71]. Thus, DNA methylation and histone modifications were shown to play a critical role in enabling T cells to acquire long-lived gene expression programs that allow a cellular adaptive immune response to form immunological memory. In B cell biology, epigenetic changes such as DNA methylation, histone PTMs, and ncRNAs, particularly miRNAs, were found to be critical in modulating B cell differentiation processes which are central to the maturation of the antibody and autoantibody response. The Lesson from the Basics of Epigenetics As with all efferent innate and adaptive immune responses, although beneficial in the context of host defense, epigenetically modified processes, including trained immunity and adaptive immunity—when uncontrolled—may eventually contribute to chronic immune-mediated diseases such as ADs. This dangerous development may be at least in part due to the fact that one epigenetic mechanism can affect another one, and feed-forward loops can and do exist. Epigenetic Modifications in SLE Epigenetic modifications, thought to bridge the gap between genetic background and environmental factors, are critically involved in the pathogenesis of SLE. Given the danger/injury model and under the tautological notion that environmental
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factors can equal exogenous or endogenous DAMPs [19], it can be tentatively considered that epigenetic changes can be influenced by DAMPs (cf. Fig. 6.9). In principle, as briefly outlined in Sect. 6.4.3, epigenetic modifications can be localized at the level of autoantigenesis, innate immune cells (e.g., DCs), and adaptive T and B cells (cf. Fig. 6.6a–c). Theoretically, the critical event triggering this autoimmune disease should be sought (1) in the generation of an altered-self antigen in the course of RCD; or, in case such an epigenetically modified self antigen is not generated, in (2) dysregulated APCs presenting original self antigens as epigenetically modified self antigens during protein processing into peptides; and/or (3) in the TCR or BCR function of autoreactive T and B cells that have either escaped central tolerance mechanisms or may be epigenetically modified in the periphery. In fact, most current research focuses on B and T cells and, to a much lesser extent, DCs and their involvement in the pathogenesis of SLE. However, the main source of self antigens is thought to be apoptotic or necrotic material that is not disposed of by SLE patients, such as NETs and delayed clearance of NETosis remnants. Interestingly, there is already evidence for such scenarios, as briefly touched on in this section. Epigenetic Modification at the Level of Altered-Self Antigens The majority of environmental factors (for example, certain types of drugs, including 5-azacytidine and procainamide [72]) known to trigger SLE in individuals with genetic susceptibility may induce excessive RCD such as apoptosis (leading to secondary necrosis) and NETosis in an epigenetically regulated fashion. This can lead to increased release/exposure and availability of intracellular self and/or altered-self antigens as well as constitutive and inducible DAMPs (reviewed by Wu et al. [18]). On the other hand, both subroutines of RCD have been shown to be induced by constitutive and inducible DAMPs [73, 74]. Interestingly, several lines of evidence have now documented the involvement of epigenetic alterations such as miRNA- mediated regulation and DNA methylation in the process of apoptosis [18]. Intriguingly, it has been demonstrated that many of the nuclear autoantigens targeted in SLE are concentrated within apoptotic blebs and nucleosomes [75–78]. In addition, as reviewed elsewhere [79–81], there is accumulating evidence suggesting insufficient clearance of NETs in SLE, thereby providing another source of nuclear autoantigens that induce the production of anti-NET antibodies. Clearly, both subroutines of RCD, apoptosis → secondary necrosis and NETosis, which are excessively frequent in SLE patients, are associated with the release of self proteins that may act as bona fide autoantigens in their unchanged state, provided there is autopathogenic dysregulation at the level of innate immune cells and/ or B and T cells. However, if the autopathogenic principle is established at the level of autoantigenesis, autoimmunity cannot be explained by the release of unmodified nuclear self antigens because apoptosis and NETosis, in their role as physiological forms of cell death, lead only to inflammation. Therefore, it should be concluded that additional epigenetically operating factors are required to turn apoptotic or NETotic material into autopathogenic antigens able to trigger autoimmunity. Excitingly, this conclusion is supported by elegant studies performed by the van der Vlag group, which demonstrated the generation of altered-self antigens via histone
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PTMs [82–84]. And it is noteworthy to remind here that histones in their unmodified form can simultaneously operate as DAMPs, that is, Subclass IA-1 DAMPs (see Table 1.1). Thus, characteristic PTMs during apoptosis include the acetylation of lysine 12 in the H2B core histone, a PTM that was shown to enhance the binding of lupus autoantibodies [82]. For example, lysine 12 acetylation was found to occur in NETosis; moreover, tri-acetylated histone H4, a specific target of the KM-2 murine lupus autoantibody, was demonstrated to be more abundant in NETs from SLE patients than in controls [83]. Therefore, the group concluded [84] …. Despite the heterogeneity in the underlying (molecular) defects and pathways that cause SLE, it appears that accumulation of apoptotic material and NETs in tissues is the common denominator between all patients with SLE. Enrichment of protein modifications, and in particular specific histone modifications, in not efficiently cleared apoptotic cells or NETs may generate neoantigens/danger signals with an increased antigenic and immunogenic potential. In addition to PTMs, another process to be considered in the generation of neoantigens/danger signals is proteolytic cleavage of histones and other chromatin-associated proteins by for example caspases, neutrophil elastase, and/or cathepsins. It is conceivable that chromatin-derived PTMs and/or cleavage products, related to apoptosis and/or NETosis, specifically ligate to receptors on antigen-presenting cells, thereby activating these cells and resulting in their immunogenic presentation. Epigenetic Modification at the Level of Innate Immune Cells (Macrophages and Dendritic Cells) The emerging topic of epigenetic modifications in SLE, that is, changes at the level of APCs, has recently been reviewed by Wu et al. [18, 85]. Indeed, the development of autoimmunity may theoretically also result from abnormal processing of bona fide self antigens and subsequent presentation of altered-self antigens by DAMP- activated APCs under upregulated costimulation to T cells. However, currently, there is poor evidence revealing a link between epigenetic changes and DC and/or macrophage functions. As discussed by Wu et al. [18], DNA demethylation is reportedly detected in the sphingosine-1 phosphate receptor 5 (S1PR5), suggesting a role in the observed defects in the S1P system and phagocytic ability in macrophages [86]. Thus, an increased sera level of S1P has been found in juvenile-onset SLE [87], pointing to a link between DNA methylation-mediated macrophage function and the pathogenesis of SLE. In fact, recent studies provided evidence for robust epigenetic dynamics of monocyte-to-macrophage differentiation by discovering a phagocytic gene network that is repressed by DNA methylation in monocytes and rapidly de-repressed after the onset of macrophage differentiation [88]. In addition, dysfunctional antigen processing and presentation by DCs might promote the breakdown of T cell and B cell tolerance in SLE. Of note, epigenetics regulate the development and function of DCs [89]; why should they not be involved in the alteration of processing and presentation of antigens. Intriguingly, in studies on mice, the DAMPs HSPs were shown to drive divergent DNA methylation programs in cDCs and pDCs via activation of DNA methyltransferases resulting in
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dichotomous T cell immune responses [90]. Indeed, patients with SLE show multiple DC abnormalities, including a reduced number of circulating cDCs, but increased numbers of pDCs [91], as well as alterations in DC function stemming from either DC-intrinsic abnormalities or DC-extrinsic regulators of function [92]. Regarding epigenetically induced alterations, increased levels of miR-29b and miR-29c were found to be involved in TLR control of glucocorticoid-induced apoptosis in human pDCs [93]. Experimental support for this clinical observation comes from studies in mice showing that miR-155 mediates augmented CD40 expression in bone marrow-derived pDCs in symptomatic lupus-prone NZB/W F1 mice [94]. Overall, these observations are of great interest; however, more targeted studies need to be done to identify exactly the role of epigenetically modified DCs in SLE. Epigenetic Modification at the Level of Adaptive Immune T Cells and B Cells Environmental factor-induced epigenetic modification observed in SLE at the level of adaptive immune T cells and B cells has been thoroughly outlined in several reviews [85, 95–98]. In fact, studies on a wide range of hypomethylated/demethylated genes in T lymphocytes have been reported showing that the methylation- sensitive genes concerned (such as CD11a, cytotoxic molecule perforin, and the B cell costimulators CD70 and CD40LG) are significantly increased. Indeed, as stressed by Richardson [96], the demethylation and overexpression of CD11a appear to be the cardinal epigenetic principle resulting in T cell autoreactivity. This molecule is a subunit of the lymphocyte function-associated antigen-1 (LFA-1) adhesion molecule that surrounds the TCR/MHC-II complex to form the immunologic synapse (for immunological synapse, see Vol. 1 [30], Sect. 32.2.3.1 and Fig. 32.1, pp. 750/751). Together, these changes convert normal, antigen-specific CD4+ Th cells into autoreactive, cytotoxic, proinflammatory cells that are capable of inducing a lupus-like disease [99]. As further reviewed [96], environmental factors known to trigger lupus flares are believed to act as T cell DNA methylation inhibitors; they include the drugs procainamide and hydralazine, UVR light (via oxidative stress), diet, and estrogens. Moreover, as could be expected, histone modifications and ncRNAs were also shown to play a role in the pathogenesis of SLE. For example, as reviewed by Wu et al. [85], global histone H3 and H4 hypoacetylation have been demonstrated in lupus CD4+ T cells.
7.2.3.5 Concluding Remarks The etiopathogenesis of SLE, as with all ADs, is complex and determined by an interrelationship between environmental triggers, genetic predisposition, and epigenetic modifications. From the four theoretically discussed scenarios outlined earlier in Sects. 6.3 and 6.4, and illustrated in Fig. 6.1, the most plausible event in the instigation of SLE appears to be the environmental factor-induced generation of self and/or altered-self nuclear antigens, which, together with various DAMPs, lead to innate immune pathway-mediated adaptive autoimmune processes. Both innate immune pathways and adaptive autoimmune processes may be influenced by epigenetic dysregulation. However, whilst epigenetic modifications of autoreactive T
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cells are mostly investigated, studies on potential epigenetically modified altered- self antigens and potential epigenetically modified DC processing and presentation of bona fide antigenic self proteins are still lacking. Further studies on these topics are needed, eventually combined with other lines of studies on the exploration of the emission of distinct DAMPs associated with environmental risk factors known (and not known yet) to trigger the development of SLE. Such studies will advance our understanding of SLE pathogenesis and could lead to strategies to prevent the disease.
7.2.4 Pathogenetic Principles of Autoantigen Formation and Emission of DAMPs 7.2.4.1 General Remarks Target cell stress/tissue injury-induced emission of DAMPs in the presence of disease-typical autoantigens marks the beginning of the development of SLE, which is characterized by a type I IFN signature. And it is the genetically predisposed, insufficient clearance of dying cells emanating from subroutines of RCD that is thought to serve as a long-lasting prolific source of both autoantigens and DAMPs. Nucleic Acids and Nuclear Proteins in SLE Acting as Autoantigens and Endogenous Nuclear DAMPs To provide a proper understanding of the information presented here, the definition of autoantigens in SLE that operate simultaneously as DAMPs, as used in this section, should be placed at the beginning. These molecules are homeostatically inaccessible to the immune system, but in the course of dysregulated RCD, they are released into the extracellular space as fragmented cellular material. According to growing evidence in the international literature, nuclear autoantigens in SLE may be interpreted and discussed as native (“naked”) or modified (e.g., oxidized) NAs (DNA, RNA), complexed with nuclear proteins such as chromatin or chromatin fragments and RNPs or RNP fragments. During SLE pathogenesis, these molecules may operate context-dependently, for example, as autoantigens recognized by TCR and BCR and as endogenous DAMPs, that is, endogenous DNA and RNA (i.e., nucleic acid DAMPs = naDAMPs), sensed by endosomal TLR7 and TLR9 or cytosolic DNA receptors such as cGAS-STING as well as RLRs (for more information, also see [2, 3, 100, 101]). (To repeat for the reader: In the following, the broad panoply of nuclear autoantigens acting in SLE/lupus are sometimes, e.g., in the figures, abbreviated simply as nauAgs.)
7.2.4.2 Defective Clearance of Dying Cells: A Source of Autoantigens in SLE Persistence of dead cells in tissue associated with dysregulated efferocytosis is characteristic of many human autoimmune diseases, notably SLE [102]. Accordingly, insufficiently cleared nuclear cell debris derived from subroutines of RCD, in particular, apoptosis and NETosis [103–105], which have been discovered to act as
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nuclear autoantigens and endogenous DAMPs in SLE, include HMGB1, chromatin proteins such as RNPs, nucleosomes, and histones [17, 106, 107] as well as cytosolic self dsDNA (i.e., nDNA and mtDNA) [106]. For example, a few NET proteins have recently been discovered to be oxidized by ROS and undergo a process of PTM by which they are transformed into potential new autoantigens [108]. Notably, these autoantigenic molecules are often incorporated in microparticles/EVs. Indeed, chromatin carried by and exposed on circulating microparticles has been shown to represent a productive source of potentially antigenic DNA that is frequently targeted by autoantibodies in SLE [109]. Moreover, it has been suggested that the excessive release of intact nucleosomes could be a major source of those autoantigenic (neo)epitopes. For instance, with the demonstration of anti-HMGB1 antibodies in SLE correlating with disease activity variables, the action of HMGB1 as an autoantigen could be confirmed [110]. Also, it has been shown that the action of HMGB1 as an autoantigen is determined in part by the complexes it forms with other molecules [111], qualifying this molecule as an altered-self antigen. Most importantly, self DNA and self RNA have been demonstrated to operate as typical DNA- and RNA-associated autoantigens involved in SLE [78, 112, 113]. The crucial question here is whether the capability of dsDNA to act as an autoantigen is brought about in terms of a bona fide self dsDNA or results from an epigenetic modification of self dsDNA that transforms it into an altered-self dsDNA. Nevertheless, the generation of both native and modified NAs in the context of genetics/epigenetics-related autoimmunity are well conceivable.
7.2.4.3 Defective Clearance of Dying Cells: A Prolific Source of Costimulation-Mediating DAMPs Typically, nuclear molecules, as defined to be derived from dysregulated clearance of cell debris released during subroutines of RCD (Fig. 7.1), do not only function as autoantigens recognized by autoantibodies in SLE but they also represent endogenous DAMPs (or PAMPs in terms of exogenous DAMPs in case of infection) (reviewed by Qiu et al. [114]). (To remember: The compartmentalization of endogenous NAs and PRRs usually prevents the inappropriate stimulation of the immune system by these potent danger signals in the absence of infection-mediated injury.) To repeat in excerpts: These nuclear molecules, here collectively referred to as nuclear DAMPs, include dsDNA and ssRNA such as small nuclear RNA U11 (U11snRNA) as well as endogenous HMGB1, histones, and nucleosomes which— as cell-extrinsic nuclear DAMPs—are passively released from dying cells or—as cell-intrinsic NAs (nDNA and mtDNA)—are generated within stressed/damaged cells. The final activity of these nuclear DAMPs may depend on epigenetic modifications, redox changes, and/or the binding of other molecules such as HSPs [17, 31, 32, 106, 107, 115–121]. For example, subroutines of RN, in particular, NETosis, are especially immunogenic because they appear to be often associated with the release of long DNA stretches and histones that are released from the nuclei. Notably, as discussed in more detail, stressed or “netting” lupus neutrophils termed low-density granulocytes (LDGs) have been shown to release oxidized mtDNA, which typically operates as “interferogenic” DNA in SLE; that is, it triggers production by activated
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cells of the innate immune system of type I IFNs in their role as inducible DAMPs [122, 123] (for inducible DAMPs, see Table 1.2 and Vol. 2 [34], Sect. 3.5.3 and Fig. 3.4, pp. 82/83). Again, the crucial question here is whether the capability of these molecules to operate as DAMPs in SLE is brought about in terms of endogenous constitutively expressed native molecules or results from endogenous constitutively expressed molecules modified by injury (e.g., epigenetically)—as is the case, for example, with oxidized mtDNA.
7.2.4.4 Concluding Remarks The critical impact of environmental factors on the development of SLE can be seen in the event of RCD and its various subroutines. This process is associated with the generation of autoantigens, either in terms of bona fide self antigens or altered-self antigens, as well as emission of nuclear DAMPs either as endogenous, constitutively expressed native or injury-modified molecules. It can be suspected that the excessive release of DAMPs during an actual event of RCD—including probably not only nuclear but also cytosolic DAMPs—triggers the feared clinical flares as observed in SLE, which can result in permanent organ damage, increased morbidity, and early mortality [124] (see also below: biomarkers in SLE). The central question posed above is repeated here: Do the autoantigens—that together with costimulation-providing DAMPs promote activation of PRR-bearing autoreactive DCs—operate as self/native molecules to elicit a disease-specific autoimmune response, or must they be modified? Based on current knowledge, this question cannot be answered correctly and satisfactorily. What is better understood is what is known about DAMP ↔ PRR-triggered autoinflammatory pathways leading to an autoimmune response: the topic of the next section.
7.2.5 DAMP-Promoted, Pattern Recognition Molecule-Mediated Autoinflammatory Pathways 7.2.5.1 General Remarks The release of DAMPs as a consequence of any environmentally induced RCD in the presence of an autoantigen is thought to be the key trigger for the onset of SLE and subsequent acute SLE flares. Plausibly, this pathogenic function of DAMPs has to be mediated by their cognate PRMs on/in cells of the innate immune system, for example, neutrophils recognized as central cellular elements of SLE pathogenesis [125]; (for PRMs, see Sect. 4.3 and Vol. 1 [30], Chap. 5, pp. 43–94). Indeed, numerous studies, including experiments on cell lines and in mouse knockout systems, have shown that various receptors of the TLR, NLR, RLR, and ALR families are pathogenetically implicated in SLE by sensing key SLE-eliciting DAMPs (e.g., self NAs and HMGB1). These studies demonstrate that interaction between DAMPs and PRMs triggers signaling pathways leading to necro-autoinflammation and maturation of autoreactive DCs, a scenario required to elicit the full spectrum of an autoimmune response. In this context, it seems useful to point out that both nuclear and
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cytosolic DAMPs are involved in mounting autoinflammation, although the cytosolic DAMPs are less explored; on the other hand, there are numerous studies on nuclear DAMPs, which appear to play a dominant role in eliciting the adaptive autoimmune response. Some key aspects are described below, for more detailed information, see [115, 120, 126–132].
7.2.5.2 DAMP-Triggered, Endosomal Toll-Like Receptor-Mediated Signaling DAMP-triggered, endosomal TLR-mediated signaling pathways in the context of infections have been sketched in Sect. 4.3.2.3 and illustrated in Fig. 4.5. Indeed, recognition of self NAs by endosomal TLRs in B cells and pDCs is also thought to be an important step in the pathogenesis of SLE, producing type I IFN and generating ANAs (reviewed in [133, 134]). For example, recognition of ssRNA by TLR7 triggers the myddosome → NF-κB signaling complex required for proinflammatory cytokine production, whereas recognition of dsDNA (unmethylated CPG-DNA) by TLR9—in addition to stimulating this pathway—triggers the myddosome → IRF7 pathway required for type I IFN production in pDCs [135]. Interestingly, there is evidence for TLR9-mediated signaling in B cells to be protective against SLE, even though it is required for the production of autoantibodies interacting with dsDNA-associated antigens. More recently, TLR7 expression was shown to be increased in lysosomes of pDCs from SLE patients, suggesting the importance of the TLR7 pathway also in IFN-α-mediated SLE pathogenesis [136] (for more detailed information about these pathways, see Vol. 1 [30], Sect. 22.3.3 and Fig. 22.4, pp. 488–494). As emphasized [137], these trajectories normally are under the control of the negative TLR regulator TNFAIP3, also known as A20, and mutations in this gene increase the risk for SLE development. Indeed, as recently reported, the dysregulation of TNFAIP3 in CD4+ T cells may contribute to the pathogenesis of SLE by overproduction of inflammatory cytokine IFN-γ and IL-17 [138]. 7.2.5.3 Cytosolic DNA → cGAS → STING-Mediated Signaling Cytosolic DNA-induced, cGAS → STING-triggered pathways in the context of infections have been sketched in Sect. 4.3.2.3 and illustrated in Fig. 4.7. The path has also received a great deal of attention in SLE. In fact, increased cGAS expression and cGAMP in a proportion of SLE patients reportedly indicates that the cGAS pathway should be considered as a contributor to type I IFN production [139] (for cGAS → STING-induced signaling, also see Vol. 1 [30], Sect. 22.3.7.3 and Fig. 22.8, pp. 507–509). Also, as reviewed by Ablasser and Gulen [140], in humans, mutations within exonuclease 1 (TREX1) are associated with SLE, suggesting that cGAS— via recognition of self dsDNA—may be a critical component for the development of these particular human autoimmune syndromes. In agreement with this, a recent study demonstrated that a mutation in RNaseH2 led to increased type I IFN production in mice via cGAS → STING signaling. As further reviewed [140], another nuclease involved in the degradation of intracellular DNA is DNase II which is
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expressed in lysosomes. The enzyme was found to act on either extrinsic DNA (= Subclass IA-1DAMPs), derived from engulfed cell debris, or on intrinsic, damaged DNA (= Subclass IIC-2 DAMPs), which originates from the nucleus or mitochondria. Typically, mice lacking DNase II die in utero because of excessive type I IFN production. The authors conclude that … these experiments (and others not cited here) implicate cGAS as a major initiator of self-DNA-triggered autoinflammatory syndromes. Furthermore, compartmentalized DNA could also serve as a trigger for cGAS and eventually contribute to the development of autoimmunity. Thus, as already quoted above [123], SLE patients were observed to spontaneously release oxidized mtDNA to the extracellular space, which activates STING-dependent type I IFNs production. In this context, studies on an acute murine model of UVB-triggered inflammation are of interest showing that a single UV exposure triggered a striking IFN-I signature not only in the skin but also in the blood and kidneys. The early type I IFN response in the skin was almost entirely, and in the blood partly, dependent on the presence of cGAS, as was skin inflammatory cell infiltration [141]. Of note, not only production of type I IFNs is promoted by dsDNA-triggered cGAS → STING signaling; recent studies suggest that this pathway is also involved in the maturation process of human myeloid cDCs [142]. However, in contrast to these observations, in recent studies on a chronic murine model of SLE induced by the i.p. injection of pristane, it could be demonstrated that the cGAS → STING pathway does not promote systemic autoimmunity in murine models of SLE [143]. The authors concluded that their conflicting data provide a cautionary note for the use of cGAS → STING targeted therapies for the treatment of SLE in patients.
7.2.5.4 DAMPs Involved in Activation of the NLRP3-Mediated Pyroptotic Pathway Remarkably, recent findings from several studies, including those on humans and various animal models, have provided evidence indicating a role of the inflammasome-forming → pyroptosis-triggering cytosolic receptor NLRP3 in the pathogenesis of SLE (reviewed in [144, 145]; for NLRP3 inflammasome, cf. Sect. 3.7.5, also see Vol. 1 [30], Sect. 19.3.4, Fig. 19.7, pp. 447–449, and Sect. 22.4.2, Fig. 22.11, pp. 515–520). For example, in macrophages and peripheral blood mononuclear cells of SLE patients, NLRP3 and IL-1β were found to be upregulated. Similar observations were also made in tubular cells and podocytes from SLE patients, and they were found to be associated with the disease activity. Of note, it has been particularly demonstrated that self dsDNA, together with its anti-dsDNA autoantibodies, upregulate NLRP3 in monocytes of SLE patients, promoting the production of IL-1β (for more details, see [146–150]). Further support for a pathogenetic role of the NLRP3 inflammasome on SLE stems from other lines of genetic studies showing a remarkable influence of NLRP3 inflammasome polymorphisms in lupus nephritis, with studies demonstrating a significantly higher risk of nephritis in SLE patients with NLRP3 genetic variants (reviewed in [151]).
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7.2.5.5 Evidence for a Role of DNA-Activated AIM2-Mediated Pathway The inflammasome-forming, pyroptosis-triggering cytosolic DNA sensor AIM2 has been alluded to in the context of bacterial and viral infections in Sect. 3.7.5. Interestingly, as reviewed by Zhu et al. [152], an altered AIM2 inflammasome system, together with other IFN-inducible protein-promoted responses, appears to be involved in the pathogenesis of SLE. In support of this concept are, for example, studies in mice showing that AIM2 stimulates type I IFN production. Further support comes from findings from MRL/lpr mice model and SLE patients, suggesting that organ-, cell type- and sex-dependent expression and epigenetic changes in AIM2 are related to the occurrence of SLE. Interestingly, in more recent investigations on AIM2 KO mice, AIM2 was identified to play a role in promoting the Tfh cell response in lupus pathogenesis [153]. Certainly, further studies are needed to elucidate the precise mechanism by which self DNA promotes AIM2 activation and to clarify the interactions of AIM2 with other sensor pathways in SLE.
7.2.6 Is There an Insufficient Inflammation-Resolving Role of SAMPs in SLE? The inhibiting/suppressing DAMPs, the SAMPs, have been demonstrated to contribute to post-inflammation homeostasis through their marked ability to promote inflammation-resolving processes. These molecules include but are not limited to AnxA1, SPMs, PGE2, cAMP, extracellular adenosine, and Ang (1–7) (for more information on SAMPs and SAMP-driven resolution of inflammation, see Sect. 4.4.4 as well as Vol. 1 [30], Sect. 14.4, pp. 330–338, and Sect. 22.2.3, pp. 480–482, and Vol. 2 [34], Sect. 5.3, Fig. 5.1, pp. 152–160; as well as Refs. [154–157]). It is worth mentioning here that the action of SAMPs in SLE may be observed in the case of recovery from flares. On the other hand, considering chronic non-resolving inflammation as a hallmark of AD, the inflammation-resolving capacity of SAMPs is expected to be insufficient and defective. Indeed, the first reports of the inferior function of SPMs and AnxA1 in autoimmunity have already been published recently [158–161]. For example, in a study on patients with SLE aimed at evaluating plasma levels of RvD1 and investigating its potential role as a biomarker of SLE as well as assessing its relationship with disease activity and laboratory parameters, the investigators found lower levels of RvD1 as compared to healthy controls [158]. From their findings, they concluded: The present preliminary study allows hypothesizing a dysregulation of RvD1 in patients with SLE, confirming the emerging role of bioactive lipids in this disease. Of note, stark support of this concept is the recent report by Cheng et al. [162]. The researchers explored the effect of the SPM RvD1 on SLE and investigated the correlation between RvD1 and Treg/Th17 imbalance, which is one of the major factors contributing to the pathogenesis of the disease. The researchers found that the RvD1 level was significantly lower in active SLE patients compared with inactive status and controls. Moreover, the results of the study revealed that the SLE disease
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activity index score had a significant negative correlation with the RvD1 level. In other parallel investigations in MRL/lpr mice, RvD1 treatment was shown to ameliorate disease phenotype and inflammatory response and improve the imbalanced Treg/Th17 ratio. Moreover, RvD1 was observed to increase Treg while reduce Th17 differentiation in vitro. Last but not least, and highly interesting, miR-30e-5p (a microRNA that is induced by DAMPs and has an integrated role in the regulation of the innate immune response during SLE [163]) was detected to modulate the Treg/ Th17 differentiation from naïve CD4+ T cells as RvD1 downstream microRNA [162]. The authors concluded from their findings that RvD1 effectively ameliorates SLE progression through upregulating Treg and downregulating Th17 cells via miR-30e-5p. In this context, it is worth also mentioning that, in earlier studies, production of another SAMP, that is, PGE2, was shown to be decreased in SLE, whereby the functional alteration was more pronounced in clinically active than in inactive disease [164]. Regarding another SAMP, AnxA1, known to operate as a potent inflammation- resolving molecule in acute and chronic inflammation settings, its role in adaptive immunity is far from understood, perhaps in part due to its lower expression on adaptive immune cells. This may be the reason why its inflammation-resolving function in SLE is not clear (for detailed information, see [165, 166]). Together, given the optimistic reports in support of an insufficient inflammation- resolving effect of SAMPs in ADs, their administration to SLE patients still seems warranted as a potential therapeutic option, at least under the impression of the beneficial therapeutic efficacy of SPMs demonstrated in many preclinical models of chronic inflammation [167].
7.2.7 DAMPs and Their Cognate Pattern Recognition Receptors Triggering Maturation of Dendritic Cells, Production of Type 1 Interferons, and Activation of B Cells 7.2.7.1 General Remarks The scenario that antigens in the presence of DAMPs trigger the development of immunostimulatory DCs to promote destructive adaptive immune responses was comprehensively presented in Vol. 1 [30], Chap. 32, and Figs. 32.1, 32.2, 32.3, 32.4, 32.5, 32.6, and 32.7, pp. 749–781. In a nutshell: The conceptual model was sketched proposing that the generation of immunostimulatory DCs is the work of collaborating DAMPs: (1) DAMPs triggering PRM-mediated pathways to induce DC maturation directly; (2) DAMPs facilitating antigen engulfment to promote DC maturation; (3) DAMPs providing the second signal for NLRP3 inflammasome activation to contribute to inflammation-dependent DC maturation; (4) DAMPs activating NK cells that assist in DC maturation; and (5) DAMPs binding to natural IgM antibodies to activate complement. And as a reminder: Immunostimulatory DCs are characterized by (1) transient upregulation of MHC-II synthesis (signal 1) followed by its near shutdown; (2) upregulation of T cell costimulatory molecule expression at their surface (signal 2); and (3) secretion of proinflammatory T cell polarizing
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cytokines (signal 3) and chemokines. It is worth noting here that this metamorphosis of iDCs into immunostimulatory DCs is accompanied by profound changes in cellular metabolism that are integral and essential to the activation process. Since the formal demonstration that DCs can prime autoreactive naïve T cells, a full body of evidence has implicated DCs in virtually all manifestations of autoimmunity, although their exact pathogenic role often remains poorly characterized [168] (for a recent review, see Kaewraemruaen et al. [169]). It has already earlier been shown that costimulation-mediating DAMPs involved in SLE, such as dsDNA or circulating DNA/ICs, but also RNA and HMGB1, in conjunction with PRR-triggered signaling pathways leading to NF-κB activation, generate potent immunostimulatory human DCs that elicit strong adaptive immune responses [170, 171]. In fact, innate immune events in SLE induced by the aforementioned DAMPs are translated by PRR-bearing DCs into the adaptive autoimmune response that is typical for this disease. However, in SLE, we have strictly to differentiate between cDCs and pDCs (for DCs, including their dichotomic function and subsets, see Vol. 1 [30], Sect. 8.3, pp. 129–134, for a recent review, see [172]). Notably, self NA-activated cDCs not only produce proinflammatory cytokines and chemokines but also possess a potent ability to present antigens to autoreactive CD4+ and CD8+ T cells, thereby initiating and expanding adaptive autoimmune processes, including autoantibody production by B cells [171, 173– 175]. On the other hand, pDCs, after sensing self NA by TLR7 and TLR9, promote the production of type I IFNs and participate in the secretion of ANAs, which are both correlated with the severity of SLE. In fact, increasing evidence suggests that pDCs are essential for the initiation of the abnormal innate immune responses that lead to systemic SLE autoimmunity. It is likely that this occurs through the promotion of cDC maturation and high production of type I IFNs (Fig. 7.2; also see [172, 174–178, 184, 185]).
7.2.7.2 Activation of Conventional Dendritic Cells Conventional DCs can be further subdivided into two subsets based on ontogeny, cDC1 and cDC2, that differ in cell surface marker expression, cytokine production, and antigen processing and reside in distinct locations at steady state [186]. As discussed in Sect. 6.2.2.4 and illustrated in Fig. 6.2, PRM-bearing iDCs are activated in the presence of autoantigens by costimulation-triggering DAMPs and mature into immunostimulatory DCs that elicit—via signal 1/2/3-activated T cells—destructive adaptive autoimmune responses. Indeed, as competently discussed earlier by Wu et al. [18] and Fransen et al. [179], this scenario model is thought to also take place in the initial phase of SLE, whereby DAMP-activated auto-immunostimulatory cDCs present bona fide self or altered-self antigens in the form of pMHCs such as MHC/histone peptide epitopes [187] to naïve self-reactive or altered-self-reactive T cells (Fig. 7.2). Surprisingly, however, a review of the international literature reveals that studies on the role of uptake, processing, and presentation of nuclear autoantigens by cDCs have not been reported so far. In other words, the mechanism of how the cDC-emitted signal 1 contributes to the production of anti-nauAgs antibodies in SLE patients remains elusive. Irrespective of this, it can be assumed that these
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Fig. 7.2 Simplified model of distinct roles of plasmacytoid DCs (pDCs) and conventional DCs (cDCs) in SLE focusing on the action of nuclear DAMPs. Current notions hold that cDCs are activated and mature via various nuclear DAMPs, including HMGB1, histones, DNA, and RNA, which signal through different TLRs-, RIG-I-, cGAS → STING-, and JAK → STAT-triggered pathways. Mature cDCs then promote activation of naïve T cells via upregulation of the three signals (presentation of autoantigens, costimulation, and secretion of T cell-polarizing cytokines). In parallel, immune complexes containing nuclear autoantigens, NAs, and autoantibodies bind to FcγRIIa and FcεRI receptors on pDCs and are endocytosed through phagocytosis and delivered into phagosomal/endosomal compartments, where the released oxDNA triggers TLR9-mediated signaling through IRF7. OxDNA released from the endosome into the cytosol is sensed by cGAS → STING. Finally, this results in the production of large amounts of IFN-α (and other proinflammatory cytokines, not shown). IFN-α plays a central role in the pathogenesis of SLE, in particular, via contribution to cDC maturation and promotion of autoreactive B cell differentiation. Note, details of TLRs-, RIG-I-, cGAS → STING-, and JAK → STAT-triggered signaling pathways are not shown here but are illustrated above in Figs. 4.2, 4.3, 4.4, 4.5, 4.6, and 4.7. Also, potential pathways of uptake, processing, and presentation of nuclear autoantigens by cDCs to naïve T cells are not mentioned. cDCs conventional dendritic cells, cGAS cyclic GMP-AMP synthase, dsDNA double-stranded DNA, dsRNA double-stranded RNA, FcRs fragment crystallizable receptors, FcεRI IgE-Fc receptor I, FcγRIIa IgG-Fc receptor IIa, HMGB1 high mobility group box 1, IC immune complex, IFN-α interferon alpha, IFNAR1 type I interferon receptor 1, IRF7 interferon regulator factor 7, JAK Janus kinase, NAs nucleic acids, oxDNA oxidized DNA, pDCs plasmacytoid dendritic cells, RIG-I retinoic acid-inducible gene (protein) I, ssRNA single-stranded RNA, STAT signal transducer and activator of transcription, STING stimulator of interferon genes, TLR Toll-like receptor. (Sources: [61, 172, 176–183])
professional APCs are also likely to contribute to the amplification and perpetuation of the disease. Interestingly, as argued by Soni and Reizis [109], it does not appear to be primarily the antigenicity of the naked DNA that is recognized by T cells as signal 1 but rather chromatin fragments that contain abundant proteins, which may produce substantial epitopes for Th cells. Although cDCs in SLE patients have been shown to overexpress costimulatory molecules such as CD86 and secrete proinflammatory cytokines [176], and although in vitro studies suggest that cDCs can promote T cell activation, there is limited
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information on DAMPs involved in SLE pathogenesis, nor is there clear evidence that they activate immature cDCs by providing costimulation. At the very least, earlier in vitro studies have already shown that purified nucleosomes obtained from SLE patients induce direct DC activation via a MyD88-independent pathway [188]. Also, there is evidence from in vitro studies suggesting that self DNA and/or self RNA could activate cDCs, signaling via TLR7/8 and TLR9, respectively (reviewed by Liao et al. [180]). Moreover, in a study on mice, RNA sensing by TLR7 in cDCs was found to be central to the development of lupus nephritis [181]. In support of these findings are in vitro and in vivo experiments in mice showing that an anti- TLR7 mAb inhibits TLR7 responses in cDCs [189], suggesting that cDCs are activated by RNA via TLR7. Also, in a study on detecting alterations in DCs at the cellular and molecular levels in patients with treated SLE [190], the cDCs (besides pDCs) were found to be characterized by changes in the expression of genes associated with their maturation, functioning, and signaling. In addition, in more recent studies on an autoimmune lupus mouse model, STING was found to mediate activation of cDCs maturation, thereby promoting T cell differentiation [191]. Overall, however, there was no reference to potential nuclear DAMPs involved in DC maturation. Finally, as reviewed by Gessani et al. [192], type I IFNs have been shown in different experimental settings to promote activation of cDCs associated with the induction of potent Th1 responses, CD8+ T cell cross-priming, and peculiar transcriptional signatures, suggesting that they may contribute to cDC activation in SLE as well. Indeed, it should be reminded that type I IFNs produced by pDCs and acting as inducible DAMPs have been reported already 20 years ago to stimulate cDCs to initiate and maintain their maturation, which is essential for their ability to elicit adaptive immune responses in SLE [61] (Fig. 7.2). Other DAMPs such as histones or nucleosomes known to activate DCs and thus promote adaptive immune responses have not been intensely investigated, at least to our knowledge. On the other hand, there is some evidence suggesting that DAMP- triggered pathways involved in SLE, such as dsDNA → cGAS → STING and RNA fragment signaling are capable of activating iDCs [142, 193]. Moreover, as reviewed by Sozzani et al. [168], other molecules such as the adapter protein MyD88, sex hormone 17b estradiol, and complement factor C1q were shown to contribute to the activation of cDCs in SLE. Conventional Dendritic Cell-Promoted Priming of Follicular Helper T Cells Importantly, it has to be added here that cDCs (cDC1 and cDC2)—by interaction with naïve CD4+ T cells via pMHC and costimulatory molecules (CD80/86 ↔ CD28, ICOSL ↔ ICOS, OX40L ↔ OX40)—have been shown to prime pre-Tfh cells [186, 194], which in other lines of studies were found to contribute to the induction of B cell maturation and which play a crucial role in the production of diverse autoantibodies detected in SLE [195] (ICOSL ↔ ICOS stands for inducible T cell costimulatory ligand ↔ inducible T cell costimulatory; for details of Tfh cells, see below Sect. 7.2.8.3 and Fig. 7.3a–c).
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a
Fig. 7.3 (a) Simplified schematic diagram of a tentative model illustrating the narrative of nuclear autoantigen/nucleic acid DAMP (DNA, RNA)-promoted activation and maturation of B cells to autoantibody-producing plasma cells and memory B cells in SLE. The scenario model is presented in the form of a multi-step process that is orchestrated by trajectories that are initiated by cDC ↔ CD4+ T cell, Tfh ↔ B cell, and FDC ↔ B cell interactions. In the T cell zones of secondary lymphoid organs, nuclear proteins and nucleic acids released from dying cells and acting as nuclear autoantigens (nauAgs) and endogenous nucleic acid DAMPs (naDAMPs, such as DNA and RNA) activate cDCs that prime naïve CD4+ T cells via signal 1 (presentation of autopeptides by MHC-II molecules to cognate TCR), signal 2 (costimulation) and signal 3 (secretion of T cell-polarizing cytokines) to generate Tfh cells. Differentiated Tfh cells migrate to the T:B border, where they interact in a cognate manner with primed B cells that have taken up nauAgs and naDAMPs via their BCR. At this stage, Tfh cells are called “pre-Tfh” cells. After this cellular engagement, some of the interacting T and B cells migrate to the B cell follicle to form GCs. There, mature Tfh cells continue to interact in a cognate autoantigen-specific fashion with B cells that additionally interact with FDCs, which have taken up nauAg and naDAMPs via the CR2 receptor. Finally, interaction with Tfh cells and FDCs promote proliferation, affinity maturation, and class switch recombination leading to the generation of long-lived plasma cells that find their niche in the bone marrow and memory B cells, which recirculate in the blood. Note: this figure shows an overview of the scenario, while more details are illustrated in the subsequent Fig. 7.3b, c. BCR B cell receptor, cDCs conventional dendritic cells, CR2 complement receptor type 2, FDC follicular dendritic cells, GC germinal center, IL interleukin, nauAgs nuclear autoantigens, naDAMPs nucleic acid DAMPs, Tfh follicular helper T cells. (Sources used for this figure and subsequent Fig. 7.3b, c: [134, 180, 181, 186, 187, 190–194, 196–208]). (b) Simplified schematically designed scenario model showing—as a continuation of Fig. 7.3a—some details of the cDC ↔ CD4+ T cell and pre- Tfh cell ↔ B cell interaction occurring initially in the course of B cell activation. In the T cell zone, cDCs engulf nauAgs and naDAMPs released from cells succumbing to regulated cell death and shuttle them via the endolysosomal pathway. Via the exogenous pathway (not shown), nauAGs are processed to autopeptides to be presented in the context of MHC-II molecules to the TCR (signal 1). In parallel, naDAMPs such as ssRNA bind to TLR7 at the endosomal membrane, while naDAMPs such as dsDNA are sensed by the cytosolic DNA receptor cGAS. Following, TLR7- and cGAS → STING-triggered pathways drive upregulation of costimulatory molecule expression (e.g., CD80/86, ICOSL, OX40L9; i.e., signal 2) that interact with cognate receptors on T cells. In (continued)
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addition, cDC-secreted T cell-polarizing cytokines (signal 3) include IL-6, IL-12, and IL-27. Activated by the three signals, T cells then migrate to the T:B zone border to interact with primed B cells. This traveling is dependent, besides others, on upregulation of CXCR5 as well as expression of Bcl6 and Ascl2, in conjunction with downregulation of CCR7. At this stage, activated T cells are called pre-Tfh cells that now interact with primed B cells. Priming of B cells is initiated by binding of the BCR to nauAgs/naDAMPs with subsequent clathrin-promoted internalization of the complex into the endolysosomal compartment. While naDAMPs such as ssRNA are sensed by TLR7 to drive costimulation, nauAGs are processed to autoantigenic peptides (e.g., histone peptide epitopes) to be presented in the frame of MHC-II molecules to the TCR of pre-Tfh cells. Critical upregulated costimulatory molecules on B cells in their role as major APCs include OX40L and ICOSL that interact with cognate receptors on the T cells. Note: for details of TLR7and cGAS-triggered signaling pathways, see Figs. 4.5 and 4.7. Ascl2 achaete-scute homolog 2, Bcl6 B-cell lymphoma 6 protein, BCR B cell receptor, CCR7 C-C motif receptor type 7, cDCs conventional dendritic cells, cGAS cyclic GMP-AMP synthase, chrom chromatin, Cl clathrin, CR2 complement receptor type 2, CXCR5 C-X-C motif chemokine receptor type 5, GC germinal center, ICOS inducible T cell costimulator, ICOSL inducible T cell costimulator ligand, IL interleukin, nauAgs nuclear autoantigens, naDAMPs nucleic acid DAMPs, pMHC-II peptide/major histocompatibility complex class II molecules, RCD regulated cell death, ssRNA single-stranded RNA, STING stimulator of interferon genes, TCR T cell receptor, Tfh follicular helper T cells, TLR Toll- like receptor, Unc93B1 Unc-93 homolog B1 (Sources: [134, 186, 194, 200], for further sources, see Fig. 7.3a). (c) Simplified schematically designed scenario model showing, —as a continuation of Fig. 7.3a, b—on the right side of the figure, some details of the GC Tfh cell ↔ GC B cell interaction occurring in the GC during the course of B cell activation (the interaction of pre-Tfh cells and primed B cells as shown in Fig. 7.3b is displayed on the left side). Some activated B cells with high affinity and some primed Tfh cells, showing increased expression of Bcl6 and other transcription factors, migrate to the center of the B cell follicle and form nascent GCs. The continued interaction between these two cell types is executed in an antigen-specific (pMHCII ↔ TCR) and costimulation- providing fashion that progresses to final differentiation of both cell types. Crucial costimulatory molecules involved in this interaction include CD40L ↔ CD40 and SAP ↔ CD 84. Among the cytokines involved, secretion of IL-21 and IL-4 by Tfh cells is critical and required for B cell proliferation and full differentiation towards GC B cells. In addition, GC B cells interact with FDCs, which are suggested to bind to nauAGs/naDAMPs/IC complexes via surface-exposed receptors such as CR1 and CR2 and internalize them into a cycling endosomal compartment. The complex is cycled to the cell surface and thus allows accessibility of nauAGs/naDAMPs for binding by the BCR of cognate B cells. In addition, naDAMPs such as RNA may be sensed by endosomal TLR7 that may trigger signaling pathways leading to secretion of type I IFN-α and enhancement of antigen presentation by FDCs. Then, GC B cells, having obtained nauAgs by BCR-mediated endocytosis, process them into autoantigenic peptides for surface presentation in pMHC-II complexes to Tfh cells. In parallel, naDAMP (ssRNA)-triggered, TLR7-mediated signaling may promote costimulation. Bcl6 B-cell lymphoma 6 protein, BCR B cell receptor, Cl clathrin, CR1/2 complement receptor type 1/2, FDC follicular dendritic cells, GC germinal center, IC immune complexes, ICOS inducible T cell costimulator, ICOSL inducible T cell costimulator ligand, IL interleukin, IFNα interferon alpha, nauAgs nuclear autoantigens, naDAMPs nucleic acid DAMPs, pMHC-II peptide/major histocompatibility complex class II molecules, SAP SLAM associated protein, ssRNA single-stranded RNA, TCR T cell receptor, TFs transcription factors, Tfh follicular helper T cells, TLR Toll-like receptor, Unc93B1 Unc-93 homolog B1. (Sources: [134, 186, 194, 197, 198, 200, 209–211], for further sources, see Fig. 7.3a)
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Fig. 7.3 (continued)
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7.2.7.3 Activation of Plasmacytoid Dendritic Cells Besides neutrophils, pDCs are regarded as highly critical key cells of the innate immune system involved in the SLE pathogenesis, in particular, regarding the progression phase (for review, see Swiecki et al. [212]). Indeed, pDCs are activated in SLE and characterized by increased production of type I IFNs and upregulation of IRGs. In other words: pDCs display an increased expression of IFN-regulated genes, the so-called “type I IFN signature” [213] (for type I IFNs, see next section and also Vol. 1 [30], Sect. 22.5.5.2 and Fig. 22.6, pp. 535–537). Activation of pDCs is predominantly induced by nuclear DAMPs in terms of native self NAs (e.g., self DNA) or modified altered-self NAs (e.g., oxidized mtDNA) released as cell-extrinsic DAMPs from insufficiently cleared cell debris derived from RCD, especially NETosis (Fig. 7.2). The function of pDCs is linked to their expression of endosomal TLR9 and TLR7, which sense self DNA (unmethylated CpG DNA) and self RNA (i.e., ssRNA), respectively (Fig. 7.2); (for TLR9 and TLR7 and their downstream signaling, also cf. Sect. 4.3.2.3 and Fig. 4.5, also see Vol. 1. [30], Sect. 5.2.2.4, pp. 47–49 and Sect. 22.3.3.3, p. 492). Importantly, human pDCs were found to sense the NAs as ICs formed with autoantibodies and mediated by the FcγRIIa, or the high-affinity FcεRI expressed at the plasma membrane (for FcRs, see earlier Sects. 4.6.7.2 and 6.2.4.2). The ICs are then endocytosed through phagocytosis and delivered into phagosomal/endosomal compartments, where TLR7 and/or TLR9 signaling is triggered, finally resulting in the production of IFN- α. Also, self DNA/autoantibodies ICs were reportedly shown to lead to IFN-α production, depending upon the convergence of the phagocytic and autophagic pathways, a process called microtubule-associated protein 1A/1B-light chain 3 (LC3)-associated phagocytosis (LAP) (for competent articles, see [174, 177, 178, 182, 183, 214, 215]; also see Vol. 1 [30], Sect. 5.3.8.3, p. 88 and for autophagosome, see Sect. 18.2.3.2, Fig. 18.1, pp. 380–382). Indeed, autoantibodies from patients suffering from SLE (as with all diseases) displaying an IFN signature can generate ICs capable of triggering the production of type I IFNs (IFN-α) by pDCs [216–218]. Last but not least, it should be mentioned that pDCs as APCs have also been shown to shape adaptive immune responses. Thus, as outlined by Liao et al. [180], MHC-II and costimulatory molecules are increased on pDC of both SLE patients and lupus- prone mice, suggesting an increased ability to present self-antigens and activate autoreactive T cells. 7.2.7.4 Production of Type I Interferons: Powerful Inducible DAMPs in SLE Many MAMP/DAMP-activated cells have been shown to produce type I IFNs, which have been classified as inducible DAMPs (see Table 1.2 and Vol. 1 [30], Sect. 14.2.3.3, p. 312). Doubtlessly, however, the principal type of cell producing large amounts of type I IFNs—besides monocytes and B cells [219]—is the pDC (Fig. 7.2) [213, 220–222]. In fact, the continuous secretion of type I IFNs derived from MAMP/DAMP- activated pDCs via “interferogenic” ICs and the migration of these cells into tissues play a critical role in the etiopathogenesis of SLE disease. For example, IC-induced
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NETS (and NETosis), known to be associated with the release of large amounts of nuclear DAMPs such as DNA (detailed below), have been observed to lead to type I IFN production by pDCs [223]. As mentioned above, the interferogenic DNA operating as a DAMP was further characterized and found to be oxidized mtDNA, which was shown to promote cGAS → STING signaling or the TLR9-triggered pathway [122, 123] (Fig. 7.2). At this point, it is also worth mentioning that some other IFN-inducing innate immune sensors are reportedly involved in promoting IFN production, including RLR-MAVS, or TLRs such as TLRs 3, 4, and 7/8 [224]. However, whether all of these receptors, besides TLR7, interact with naDAMPs in SLE has not been documented so far. Signaling Through Type I IFN Receptor All type I IFNs, in their function as inducible DAMPs, bind, albeit with slightly different affinities, to the same IFNAR1 expressed on the cell surface of most cell types, including cDCs [225] (cf. Fig. 7.2; also see Vol. 1 [30], Sect. 22.5.5.2, pp. 535–537). The binding of type I IFNs to IFNAR1 instigates multiple signaling pathways, the best-characterized path being the JAK → STAT pathway involving phosphorylation of cytoplasmic JAK1 and tyrosine kinase 2 (TYK2) and subsequently downstream STAT1 and 2. A complex consisting of activated STAT1, STAT2, and IRF9 translocates to the nucleus, where it binds to IFN regulatory elements and triggers the transcription of hundreds of ISGs. In this complex, STAT1 and IRF9 are required for sequence- specific recognition and stable binding with DNA, whereas STAT2 provides transcriptional modulation but is unable to interact with DNA directly [226–229]. Other members of the STAT family (e.g., STAT3, 4, and 5) can also be activated by type I IFNs. In addition, other pathways such as MAPK signaling, PI3K → AKT → mTOR, and PKC pathways can be activated by IFNAR engagement and either cooperate with the JAK → STAT pathway or act independently to trigger the expression of ISGs [230, 231] (note, the various signaling pathways are outlined and illustrated in Vol. 1 [30], Sect. 4.3.2.2, Fig. 4.3; Sect. 4.3.5, Fig. 4.8; Sect. 22.3.3, Fig. 22.3, pp. 488–491; Sect. 22.3.4.2, Fig. 22.5, pp. 494–497, and Sect. 22.3.4.3, Fig. 22.6, pp. 497–499). Effects of Type I IFN on the Immune System As reviewed by Bengtsson and Rönnblom [220], type I IFNs have a broad spectrum of effects on innate and adaptive immune responses, whereby the actual mode of action is dependent on the responding cell type and cellular and genetic context. Moreover, the efferent action of IFN subsets also varies, probably due to differential binding to the IFNAR1 and IFNAR2 subunits (cf. Vol. 1 [30], Sect. 22.5.5.2, pp. 535–537). Thus, both IFN-α and IFN-β efficiently facilitate the effector capacities of NK cells and macrophages, thereby fortifying the rapid first-line immune defense (for NK cell function, see Vol. 1 [30], Sect. 28.2.3, pp. 696–698). Also, the expression of MHC-I molecules is upregulated by type I IFN on several cell types, which promotes the cross-presentation of exogenous antigens and detection of virus-infected cells and cancer cells by CTLs (for cross-presentation, see Vol. 1
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[30], Sect. 31.3.5, pp. 740–743). Moreover, IFN-α was found to promote the expression of MHC-II and costimulatory molecules, as well as the production of several cytokines that promote the differentiation of iDCs into immunostimulatory APCs [232]. Regarding adaptive/acquired immunity, type I IFNs were shown to prolong the survival of activated T lymphocytes and stimulate the development of CD4+ and CD8+ memory T cells. Furthermore, type I IFNs increase the differentiation of Th17 cells and suppress Treg functions, which all can lead to an expansion of autoreactive T cells and enhanced inflammatory responses [233, 234]. Also, regarding the pronounced effects on B cells, type I IFNs reportedly increase the production of B cell stimulators, stimulate B lymphocyte proliferation, enhance the survival of transitional B cells, and reduce the threshold required for activation through the BCR. In addition, type I IFNs were also shown to promote Ig isotype class switching, differentiation of B cells into plasma cells, and the synthesis of antibody production [235–238]. All these experimental and clinical observations underscore the critical role of inducible DAMPs in augmenting not only host defense responses but also in exacerbating interferonopathies such as SLE [239]—echoing the title of the Epilogue in Vol. 1 [30], Chap. 20, pp. 467–470: The horror of an injury-induced avalanche of DAMPs. Accordingly, Bengtsson and Rönnblom [220] conclude: Clearly, the persistent synthesis of type IFNs have many crucial effects on the immune system that can contribute to the loss of tolerance and exacerbate the immune pathology in individuals prone to autoimmune disorders.
7.2.7.5 Activation of Follicular Dendritic Cells Follicular dendritic cells were briefly addressed in the context of humoral immunity in Vol. 1 [30], Sect. 32.6.2, and Fig. 32.7, pp. 775/776. These cells organize the microanatomic structure of GCs and have been shown to bind ICs coated with complement C3 via their surface-exposed CD21 receptors and internalize them into a cycling endosomal compartment. This periodic cycling of antigen complexes to the cell surface is thought to retain antigens for long periods and allows accessibility of the antigen on the cell surface for acquisition by cognate B cells (for more information, see Heesters et al. [196, 197, 240, 241]). Indeed, B cells obtain intact antigen from the surface of FDCs by BCR-mediated internalization and process the antigen into peptides for surface presentation in pMHC-II complexes (Fig. 7.3a–c). The involvement of this special subset of APCs in the pathogenesis of autoimmune disorders has become a hot research area in the last couple of decades [242]. Thus, recent studies on a murine SLE model have shed some more light on mechanisms of B cell peripheral tolerance breakdown [198]. In these studies, FDCs were found to take up and retain self ICs composed of RNPs (acting as both self antigen and DAMPs), autoantibody, and complement. This uptake, mediated through the complement receptor CR2, was shown to trigger activation of endosomal TLR7—qualifying RNPs as DAMPs (!)—and to lead to the secretion of type I IFN-α via an IRF5-dependent pathway; type I IFN, thereby enhancing autoreactive GCs and antinuclear autoantibody formation (for CR2, see Vol. 1 [30], Sect. 23.2.6.4, p. 607).
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Overall, however, the role of FDCs in contributing to B cell activation in SLE has not been thoroughly explored so far. In general, it is accepted that FDCs function as storage of native antigens for a long period of time. Antigens are distributed mainly in the form of ICs nonuniformly on FDC processes, whereby they are bound to CR1, CR2, and/or FcγRIIB, depending on activation and availability of complement proteins. There is evidence suggesting that these receptors—besides antigen retention—are also responsible for antigen presentation to B cells. Moreover, FDCs are equipped with many TLRs, including TLR7. Although FDCs were found to sense RNA during autoreactive responses and produce type I IFN in response, whether this interaction also contributes to upregulation of costimulation in SLE— allowing activation of T cells—has not been investigated so far (for further information, see [197, 209–211]). Together, there is growing evidence supporting the concept that FDCs have the machinery to contribute to B cell activation and GC regulation in SLE. However, further studies are needed to elucidate the underlying mechanisms, particularly the mode and action of NA-related DAMPs in activating FDCs and, in turn, FDC- triggered activation of T cells.
7.2.7.6 Activation of Autoantigen-Presenting B Cells: The Begin of B Cell Pathobiology The topic of B cell pathobiology will be outlined below in detail. Here, only the first steps of their activation are briefly examined: Within the peripheral lymphoid organs, bone marrow-derived immature B cells migrate toward the lymphoid follicles, where the complex B cell activation process begins. B Cell Receptor-Mediated, Autoantigen-Triggered Activation of B Cells At the entry of the GC reaction, autoantigen-specific B cells capture T-dependent soluble antigens via the BCR, a process that depends mostly on BCR signaling- dependent, clathrin-independent internalization. Following engulfment, antigens are processed and presented as autoantigenic peptides on pMHC-II to pre-Tfh cells to get help from them for further development (Fig. 7.3a; for peptide-processing and loading and presentation on MHC-II molecules, see Vol. 1 [30], Sects. 31.3.3 and 31.3.4, and Fig. 31.3, pp. 730–740; for details of B cells as APCs in general, see reviews of Ghosh et al. [199] and McShane and Malinova [243]). Note that the Tfh cells are primed by cDCs, which present the cognate autoantigen and provide costimulation. Also, of note, only B cells with sufficiently high-density pMHC-II interact efficiently with cognate pre-Tfh cells at the T:B border of lymphoid follicles or with cognate Tfh cells at the border of GC. And for achieving a high density of antigen-derived pMHC-II, the BCR requires high affinity for the antigen [199] (for further details of the Tfh cell response, see next section). Nuclear DAMP (RNA)-Triggered, Toll-Like Receptor-Promoted Activation of B Cells As pointed out in Vol. 1 [30], Sect. 32.6.5, p. 778, although TLR signals are not essential for B cell activation, B cell-intrinsic signaling pathways triggered by
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TLRs promote B cell activation, and this, in combination with other T celldependent (TD) and T cell-independent (TI), BCR-mediated intracellular pathways. In addition, TLR signaling has been shown to drive cell proliferation and differentiation, amplify autoantibody and cytokine production, antigen presentation, Ig isotype switching, and cell survival for long-lived plasma cells and memory B cells [244, 245]. Interestingly, there is already the first evidence suggesting a role for nuclear DAMPs in B cell activation. For example, RNA operating as a DAMP was shown to trigger the activation of autoreactive B cells by TLR7 and TLR3 [246]. These early reports have been confirmed by more recent studies. Thus, in vitro and in vivo studies have shown that TLR9 and TLR7 are implicated in the activation of the corresponding autoantibody-producing B cells. Specifically, TLR9/TLR7- deficiency results in the inability of autoreactive B cells to proliferate in response to DNA/RNA-associated autoantigens in vitro and leads to marked changes in the autoantibody repertoire of autoimmune-prone mice [247]. Moreover, in studies on double-KO mice, B cells were demonstrated to respond only to RNA-associated ligands, as DNase II-mediated degradation of self DNA is required for TLR9 activation [117]. This observation indicates that self DNA is operating in this scenario as a modified DAMP to be recognized by TLR9. Interestingly, in more recent studies, evidence was provided suggesting a unique link between neutrophils and B cells in which NETs trigger a concerted activation of TLR9 and BCR, leading to anti-NET autoantibody production in lupus [248]. Of note, this critical topic has more recently been revisited in a review paper by Fillatreau et al. [134]. In brief: The naDAMPs unmethylated CpG DNA and ssRNA can be sensed by the BCR at the surface of B cells to be internalized and delivered as BCR/NA complex into the endosomal compartment of B cells, where DNA is recognized by TLR9 and ssRNA by TLR7, respectively.
7.2.7.7 Concluding Remarks In summary, nuclear DAMPs are critically involved in the onset and progression of SLE at multiple levels. As constitutive native DAMPs, passively released from environmental factor-induced RCD, they promote the maturation of auto- immunostimulatory cDCs as a necessary step to instigate an autoimmune T and B cell response; in the form of constitutive modified DAMPs, they contribute to the activation of pDCs; and as inducible DAMPs (type I IFNs), they contribute to various innate and adaptive autoimmune responses that are heavily involved in SLE. Notably, given the discovery of various subroutines of RCD involved in the SLE pathogenesis, further non-nuclear DAMPs are certainly operating in the pathogenesis of SLE and await exploration soon. In addition, the precise determination of the various dysregulated DAMP-triggered innate immune pathways and their signaling molecules—evaluated by taking into consideration the genetic/epigenetic background involved in SLE—will certainly be helpful in further elucidating the pathogenesis of this complex and heterogeneous disease, which causes important social and public health problems.
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7.2.8 The Autoreactive T Cell Response 7.2.8.1 General Remarks As a reminder: under DC-elicited specific antigen stimulation (signal 1), DAMP- triggered costimulation (signal 2), and T cell-polarizing cytokine (signal 3), naïve T cells differentiate, determined by the expression of specific transcription factors in response to these cytokines, into various subsets (Th1-, Th2-, Th17-, Tfh-, Treg cells; and compare Vol. 1 [30], Sect. 32.4, Figs. 32.4, and 32.5 pp. 765–772; Sect. 33.3.2, Fig. 33.3, pp. 799–802 and Sect. 33.4, pp. 809–818). Abnormalities of these T cell-related pathways have long been observed in SLE [249]. Thus, CD4+ T cells comprise a considerable proportion of the inflammatory cells invading affected tissues. In fact, the T cells are generally believed to be central to the etiopathogenesis of SLE because of their close relationship to the recognition of pMHC complexes and because adoptive transfer of these cells confers lupus-like disease in some mouse models. As discussed above, the development of autoimmunity is implied in autoimmune diseases that can conceptually occur when potential bona fide self- reactive T cells have escaped central tolerance mechanisms or when altered-self- reactive T cells (i.e., T cells which have not “seen” altered-self in the thymus during development) get activated in the periphery (i.e., “the tissue controls escaped autoreactive T cells” [Sect. 6.2.2.4]). 7.2.8.2 CD4+ Th1 and CD4+ Th17 Cells In recent years, increasing attention has been paid to the role of T cell subsets in SLE pathology (for a review, see Moulton et al. [250]). In brief: In SLE, CD4+ Th subsets have been shown to display aberrant cytokine production, a profound defect in IL-2 production, and impaired effector and regulatory capacities. Typically, Th1 cells are reduced in favor of Th17 cells that produce high levels of IL-17 to amplify the inflammatory response. Indeed, in patients with SLE, increased numbers of autoreactive Th17 cells have been documented, and Th17 cells appear to be responsible for tissue inflammation and damage. Interestingly, the ICs + terminal complement complex C5b-9 were shown to act as a costimulator of naïve CD4+ T cells [251]. The authors reported that IC/C5b-9 generates a costimulatory signal that is mediated via FcγRIIIA-Syk phosphorylation and replaces the costimulatory molecule CD28 requirement for the development of CD4+ IFN-γ and a Th17-like population (note, the tyrosine kinase Syk is a member of the Syk family of tyrosine kinases). 7.2.8.3 Follicular CD4+ Helper T Cell Responses: The Help for B Cell Activation Follicular CD4+ helper T cells have already been briefly alluded to above. These cells are peculiarly highly differentiated CD4+ T cells that are the specialized providers of help for B cells that promote the development of long-lived humoral immunity, including autoimmune responses. As described and illustrated in Vol. 1 of the book, the provision of help by Tfh in SLE is a complex process (see Vol. 1
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[30], Sect. 32.4.5, Fig. 32.5, Box 32.1, pp. 769/770, and Sect. 32.6, Fig. 32.7, pp. 775–780). The Tfh cells develop concomitantly with effector Th1, Th2, and Th17 cells, which support cellular immunity. The cells are rich in plasticity and diversity of differentiation and function [195]. The development and differentiation of Tfh cells is a multifactorial process that progresses through several stages (Fig. 7.3a–c; reviewed by Crotty [194] and Qin et al. [200]). As discussed above, their initial priming is executed by nauAg/DAMP- activated matured cDCs [186, 194]. This leads to the generation of CXCR5+ Bcl6lo pre-Tfh cells with increased activity of transcriptional factors such as Achaete-scute homolog 2 (Ascl2), STAT1, STAT3, and IRF4. It is the expression of Ascl2 in these activated T cells that promote their migration toward B cell follicles by upregulation of CXCR5 expression and other mechanisms. Upon interaction with cognate B cells via nauAg/MHC-II ↔ TCR and costimulatory molecules (e.g., ICOSL ↔ ICOS, CD80/86 ↔ CD28) at the T:B border, CXCR5+ T cells begin to upregulate the transcription factors B-cell lymphoma 6 protein (Bcl6) expression, which in cooperation with other transcription factors determines the final differentiation state of Tfh cells within GCs. On the whole, Tfh cell differentiation and function are variably supported and regulated by certain cytokines such as IL-6, IL-21, and IL-27; costimulatory molecules (including ICOS and CD40L), and intracellular signals (e.g., JAK-STAT) [195]. The subset of T cells is involved in the pathogenesis of SLE based on their plasticity and diversity. Indeed, multiple lines of evidence demonstrate that aberrant Tfh cell responses are also associated with human SLE [195, 252]. Thus, as will be outlined below in more detail, Tfh cells are crucial for the formation of GCs, B cell differentiation into plasma cells and memory B cells, and finally, affinity maturation and Ig class switching as an indispensable part of adaptive immunity. Indeed, their critical contribution to autoantibody production by providing help to GC B cells enhances the development of long-lived humoral autoimmunity in this disease. In particular, Tfh cells are essential for the generation of high-affinity memory B cells through the GC reaction.
7.2.8.4 Regulatory T Cells The role of Tregs in central and peripheral T cell tolerance has been comprehensively presented in Vol. 1 [30], Sects. 33.2.3 and 33.2.4, pp. 796–798, and Sect. 33.4, Figs. 33.3 and 33.4, pp. 800–818. The imbalance of Th cell and Treg cell subsets is thought to contribute to the pathogenesis of SLE (for a review, see Ohl and Tenbrock [253]). Defects in Peripheral Tolerance Mouse models support the importance of defects in peripheral tolerance, and deficient or defective Treg cells have been identified both in mouse models and human studies. Moreover, GWAS has also identified defects in lymphocyte signaling that could centrally alter thymic deletion of autoreactive cells [9]. Notably, several
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pathways were described to exist by which T cell tolerance could be defective in SLE (reviewed in [254, 255]). For example, aberrant TCR signaling has reportedly been observed in patients with SLE, which leads to hyperresponsiveness of T cells. Moreover, changes have been found in the expression of TCRζ, the activation of intracellular spleen tyrosine kinase Syk, calcium signaling, and various other kinase pathways. (For details, the reader is referred to the comprehensive review by Rother and van der Vlag [254]). In addition, reduced numbers of Tregs, as well as Tregs with impaired regulatory function, have been associated with SLE. The altered balance between the number of Tregs and Th17 cells in SLE may result from changes in the cytokine milieu that favors the development of Th17 cells over Tregs (for Th1 and Th17 cells and Tregs, see Vol. 1 [30], Sects. 32.4.2 and 32.4.3, pp. 767/768 and Sect. 33.4, pp. 809–818). As concluded by Rother and van der Vlag [254], So, not all aberrancies in T cell signaling and disturbances in Th17 cell/Tregs …. are present in all patients with SLE. Nevertheless, the signaling cascades emerging from the TCR and ultimately leading to changes in the expression of numerous genes play a key role in the phenotype of T cells in SLE. In general, aberrancies in TCR signaling lead to a hyperresponsive state of T cells in SLE. Moreover, aberrancies in TCR signaling may affect selection processes in the thymus, thereby impairing central tolerance (cf. Fig. 6.6a). Follicular Regulatory T Cells FoxP3+ follicular Treg cells have recently been identified as important regulators of the humoral immune response in GCs. Similar to Tfh cells, this Treg-cell population localizes to GCs and suppresses B cell antibody production there, thereby limiting the magnitude of the GC response. In addition, Treg suppression is not restricted to GC B cells and occurs at various steps during B cell differentiation, from B cell activation to class-switched B cells and plasma cells (for detailed information, see [194, 200, 253]).
7.2.9 The Autoreactive B Cell Response 7.2.9.1 General Remarks Doubtlessly, the dominant cells operating within the adaptive autoimmune processes in SLE are the autoreactive B cells, which in their function as APCs and autoantibody-producing cells play crucial roles during disease progression and target organ damage. As mentioned above, B cell activation is considered a complex process that is mainly regulated by (1) BCRs that bind to autoantigens, (2) naDAMPs (e.g., RNA)-triggered PRRs such as TLR7, and (3) interactions between CD4+ T cells and B cells. In the following, the scenario will be discussed in form of a multi-step, multisignal process of B cell activation, whereby the trajectories described above are resumed (e.g., cDC ↔ CD4+ T cell, Tfh ↔ B cell, and FDC ↔ B cell interactions). Before, however, a quick glance at B cell pathobiology should be allowed.
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7.2.9.2 B Cell Pathobiology at a Glance The scenario of B cell activation within the adaptive branch of humoral immunity has been covered in Vol. 1 [30], Sect. 32.4.5, Box 32.1, and Fig. 32.5, pp. 765–770, as well as Sect. 32.6, including Fig. 32.7, pp. 775–780. In brief: The humoral process is orchestrated by tight regulation of progression from a small number of antigen-specific B cells to the production of a large number of antibody-secreting plasma cells and memory B cells. The process takes place within the GC, that is, the transient structures that form within peripheral secondary lymphoid organs (SLOs) or tertiary lymphoid organs (TLOs) in response to either TD or TI pathways. As briefly outlined above, B cells, following antigen stimulation, receive help for final differentiation from Tfh cells and FDCs. Arrived in the GC and having received this help, B cells will undergo SHM and CSR to facilitate the affinity of immunoglobulins (CSR for class-switch recombination: a biological mechanism that changes a B cell’s production of Ig antibodies from one type to another). Finally, they differentiate into memory B cells that recirculate in the blood and long-lived antibody- secreting plasma cells, which home to and survive in unique bone marrow niches as mediators of humoral immunity through the secretion of high-affinity antibodies (Fig. 7.3a). 7.2.9.3 A Model of B Cell Activation as an Interplay Between DCs, T Cells, and B Cells Here, with the use of data obtained also from other lines of studies as well as with the assistance of reports from the international literature [134, 180, 181, 186, 187, 190–194, 196–208], the following tentative model of an interplay between cDCs, Tfh cells, FDCs, and B cells in B cell activation in SLE is sketched and may be discussed: The multi-step, multi-signal process begins in the T cell zones of SLOs such as the spleen or lymph nodes. There, naïve CD4+ T cells are primed by cDCs that present their processed autoantigenic peptides in the context of MHC molecules (e.g., pMHC-II) to the cognate TCR and provide naDAMPs- and type I IFN-triggered costimulatory signals such as CD80/86, ICOSL, and Ox40L through their cognate receptors on T cells, such as CD28, ICOS, and Ox40 (compare Vol. 1 [30], Fig. 32.1, p. 751). T cell-polarizing cytokines involved in this cDC ↔ T cell interaction include IL-6, IL-12, and IL-27 (Fig. 7.3b). This early DC priming in the T cell zone is generally required for Tfh differentiation but is not sufficient. It is worth mentioning here one more word about signal 1, the presentation of autoantigens to CD4+ T cells, and signal 2, the provision of costimulation in SLE: Since there is no clearcut evidence-based definition of anti-dsDNA autoantibodies in the literature, here, the cognate nauAGs are interpreted as discussed above (i.e., interpreted in terms of autologous native or RCD-modified chromatin/chromatin fragments (e.g., DNA, RNA)-associated/derived proteins like histones). Costimulation may be provided by TLR7-, TLR9-, and STING-mediated pathways, whereby RNA- and DNA operating as naDAMPs are supposed to be involved in cDC activation. Upregulation of the chemokine receptor CXCR5 as well as expression of Bcl6 and Ascl2, in conjunction with downregulation of CCR7, allows the
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activated T cells (now called pre-Tfh cells) to migrate to the T/B zone border and interfollicular regions of SLOs. Once arrived and settled in follicular areas of lymphoid tissue, the pre-Tfh cells interact with antigen-primed B cells in a cognate fashion leading to further B cell activation and differentiation. In fact, this B cell activation → differentiation process appears to be complicated for me as a clinician (Fig. 7.3b): At first, it is to note that, in B cells, binding of chromatin-associated proteins and nucleoproteins—eventually complexed with IC—by the BCR is the key process to permit entry of these molecules into cells. And to emphasize again: these molecules act as nauAgs and operate as naDAMPs (RNA, DNA)! After the engagement, the BCR is internalized with the bound molecules and delivered to endolysosomal compartments, in which chromatin- associated DNA and nucleoprotein-associated RNA operate as nuclear DAMPs to be sensed by TLR7 (ssRNA) and TLR9 (dsDNA). Trafficking of TLR7 and TLR9 to and from the endolysosomes is controlled by the chaperone UNC93B1. TLR7 and TLR9 trigger downstream pathways via the myddosome, resulting in the upregulation of costimulatory molecules such as ICOSL interacting with ICOS expressed on Tfh cells (i.e., the B cell-dependent phase of Tfh differentiation; here, also cf. Fig. 4.5). Of note, recently reported evidence suggests that TLR7-mediated promotion of SLE development is restrained by TLR9-mediated protection of SLE development [134]. Further costimulatory molecules upregulated on B cells during this phase of B cell ↔ pre-Tfh cell interaction include CD80/86 interacting with CD28 and OX40L interacting with OX40. In addition, B cells show upregulation of the coinhibitory molecule PD-1L expression that interacts with PD-1 on Tfh cells. Simultaneously, BCR-captured nauAgs are endocytosed and processed to be presented as peptides (e.g., nucleosomal peptides [187]) on MHC-II to Tfh cells that show increased Bcl6 expression, which is essential for Tfh formation and further differentiation, B cell help, and GC formation. Such nauAg uptake and presentation allow cognate interaction with Tfh cells in proportion to pMHC-II levels. After this cellular interaction, some activated antigen-specific B cells proliferate extensively, forming extrafollicular foci, and differentiate into short-lived plasma cells that secrete antibodies with low affinity. Moreover, some activated B cells with high affinity, which are destined for the GC pathway, migrate to the center of the follicle and form nascent GCs. Also, following priming by cDCs and exposure to B cell-presented autoantigenic peptides as well as provision of costimulation by cognate B cells, some pre-Tfh cells transit into the B cell follicles and contribute to the formation of GCs, while their terminal differentiation into GC Tfh cells depends on signals from cognate B cells. Indeed, in these highly specialized microanatomical structures of the GC, GC Tfh and GC B cells continue to interact in a TCR ↔ pMHCII- and ICOS ↔ ICOSL-dependent fashion to progress to final differentiation. In addition, in the course of this interaction, Tfh cells provide further costimulation in form of SLAM-associated protein (SAP), CD40L, and CD28, as well as secret cytokines such as IL-21 and IL-4, required for B cell proliferation and full differentiation toward GC B cells (Fig. 7.3c). Also, as mentioned above, there are FDCs that have been shown to contribute to B cell activation. In fact, FDCs are equipped with the receptors CR1, CR2, and/or
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FcγRIIB which are generally thought to be responsible for antigen/IC retention and presentation to B cells [209–211]. Interestingly, recent studies on murine and human FDCs reported by Heesters et al. [197] revealed that this subset of DCs is equipped with multiple TLRs, including TLR4 and TLR7, which can sense MAMPs. Moreover, in these studies, TLR signaling was shown to enhance antigen presentation by FDCs [197]. The findings suggest that not only MAMPs but also DAMPs— for example, through TLR7 signaling—may activate FDCs, thereby contributing to autoantigen presentation (Fig. 7.3c). Finally, the interaction between GC Tfh cells, GC B cells and FDCs regulates the humoral autoimmune response by orchestrating—as already mentioned—the differentiation of B cells into plasmablasts developing to high-affinity antibody- secreting plasma cells (located in niches of the bone marrow) and memory B precursors developing into peripherally circulating memory B cells (Fig. 7.3a).
7.2.9.4 B Cell-Derived Production of Autoantibodies in SLE Although SLE is a clinically heterogeneous disease, patients are near-universally characterized by the production of pathogenic autoantibodies that target a variety of nuclear self antigens, some of which cross-react with tissue antigens. These autoantibodies are generally high-affinity, somatically mutated IgG, which suggests that they have arisen in GCs, where T cells provide help for class switching (see also Vol. 1 [30], Sect. 32.4.5, pp. 769–771). Among the various autoantibodies, anti- dsDNA antibodies are considered the most important. Interestingly, however, the mechanism of how an anti-dsDNA antibody is produced in SLE patients remains elusive. Also, as discussed above, the mechanism of how the cDC-emitted signal 1 contributes to the production of anti-nauAgs antibodies in SLE patients remains unclear. Notwithstanding, a few more words are added to this topic in the following. Indeed, as outlined in Vol. 1 [30], Sect. 32.6 and Fig. 32.7, pp. 775–780, antibodies are produced by rare populations of terminally differentiated B cells, that is, plasmablasts and plasma cells, the formation of which—compared with their B cell precursors—is associated with marked alterations in the morphology, gene expression profile, and lifespan of the differentiated antibody-secreting cells (ASCs). These cells also produce autoantibodies, which are often found elevated in the circulation of patients with SLE [256, 257]. The production of ASCs in response to TD antigens occurs in the GCs. As mentioned, the GC ultimately produces high-affinity, long-lived plasma cells that are capable of sustaining a high level of antibody secretion. In addition, the GC generates memory B cells that maintain a B cell phenotype but that seem to be epigenetically programmed to rapidly differentiate into ASCs following re-exposure to antigen. As also already outlined above and also described in Vol. 1 [30], Sect. 32.6, pp. 775–780, differentiation of naïve B cells to ASCs requires multiple B cell activation pathways, that is, with and without T cell help, as well as through TLRs. Loss of tolerance and altered B cell differentiation in SLE has been discussed to be probably genetically determined by variants present from birth or acquired as part of the disease process [258]. Other lines of studies provided evidence suggesting that proinflammatory factors, in particular, type I IFNs, modulate B cell function
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in SLE in a way that could contribute to the breach of tolerance in this condition [259]. Again other sets of experiments lent support to the notion that activation of B cells and class switching to pathogenic autoantibodies through TLR pathways promotes loss of tolerance [260, 261]. In addition, tolerance was also supposed to be broken by B cell stimulation via cytokines. For example, the B cell-activating factor (BAFF) complexed with IgG was demonstrated to strongly correlate with overall disease activity, low complement levels, and a history of lupus nephritis [262]. Independent from the ongoing discussion, it should be reiterated here again that, in light of the danger/injury model, the nature of immunological tolerance vs. immunity can be summarized as already outlined in Sect. 6.2.2.4 and Vol. 1 of the book ([30], Chap. 33, pp. 791–819): At a simplistic level, the pragmatic conceptual model proposes that antigen (self or nonself) in the absence of DAMPs promotes immunological tolerance, whereas antigen—regardless of whether it is self or nonself—in the presence of any DAMPs induces immunity. Extrafollicular Pathway of Autoantibody Production in SLE As mentioned, the key antibody-producing cells are the plasma cells and high- affinity IgG autoantibodies that are thought to arise through GC responses. And this scenario is also true for the production of pathogenic autoantibodies in SLE. However, as reviewed by Malkiel et al. [263], CSR and SHM can occur in extrafollicular (EF) locations as well, and this pathway has also been implicated in SLE. Though the exact pathogenic pathway is not quite clear, the authors propose some mechanisms by which extrafollicular plasma cell responses in SLE may be altered, including expansion of marginal zone B cells, enhanced TLR (TLR7!) signaling, B cell hyperresponsiveness that causes increased signaling upon BCR ligation by antigen, and increased CSR in EF responses. As further reviewed [263], SLE patients have increased numbers of circulating pre-GC B cells and switched memory B cells and Tfh cells, which lent support for the notion of enhanced GC responses. Given that potential pathogenic IgG anti- DNA autoantibodies in SLE show evidence of SHM, the production of autoreactive plasma cells by SHM of non-autoreactive naïve B cells within the GC has been considered an important contributor to the development of SLE in both mice [264] and humans [265]. Plausibly, it is the influence of genetic risk factors that are proposed to cause susceptibility to pathogenically altered extrafollicular and GC pathways leading to autoantibody production. As proposed by Malkiel et al. [263], these risk factors that can alter B cell responses and, subsequently, PC differentiation may cause a dominance of either of these pathways in individual patients. The authors emphasize: These risk alleles can function in a B cell-intrinsic or -extrinsic manner. We propose that some risk alleles, such as TLR7, FAS, IRF5, TNFAIP3, and TNIP1, can modify both EF and GC responses. Certain risk alleles, such as HLA class II genes, FCGR2B, STAT4, CD80, IRF8, and PRDM1, most likely drive GC responses, whereas other risk alleles, such as ETS1, LYN, BACH2, and BLK, may preferentially drive EF responses in SLE, although this pathway has not been extensively explored. Further understanding of the exact role of each risk allele in plasma cell
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differentiation pathways may enhance our insight into patient heterogeneity (for all abbreviations used in this statement, see the original paper [263]). Aberrant Glycosylation of Autoantibodies in SLE The impact of aberrant glycosylation of IgG and IgA antibodies on their pro-and anti-inflammatory function on neutrophils has been cursorily covered in Sect. 6.2.4.2. Thus, depending on changes in IgG Fc glycosylation state, IgG molecules can exert neutrophil activity-promoting functions (e.g., in the absence of fucose, galactose, sialic acid) and neutrophil activity-decreasing functions (e.g., by addition of sialic acid), each driven by the variable carbohydrates in the sugar (N-linked glycan) moiety attached to the IgG Fc domain. This scenario can also be found in SLE, where low- or non-galactosylated (agalactosylated; G0) IgG autoantibodies in the serum of patients reflect severity of the disease, and sialylated IgG autoantibodies fail to induce inflammation and lupus nephritis in a BCR transgenic lupus model, but instead are associated with lower frequencies of pathogenic Th1, Th17 and B cell responses [266]. Of note, the impact of glycosylation of IgG autoantibodies on neutrophil function is also seen in RA patients and is described below. Induction of NET Formation and NETosis by Autoantibodies and Associated Immune Complexes As already touched on above, it should not remain unmentioned that IgG autoantibodies have been reported to promote induction of RCD such as necroptosis and NETosis, thereby contributing to emission of DAMPs. For example, in in vitro studies on serum from SLE patients, autoantibodies were shown to induce necroptosis in murine fibroblast cells through interaction with the TNFR1 receptor [267]. Looking back on what has been outlined in Sects. 6.2.4.3 and 6.2.4.4, IC-induced, FcR-mediated NET formation, and NETosis are of particular interest here. The emerging concept in autoimmunity has been incorporated here into a hypothetical scenario postulating that autoantigen/autoantibody IC-induced NET formation/NETosis subsequently initiate a DAMP-promoted positive feed-forward loop that amplifies innate and adaptive autoimmune responses (cf. Fig. 6.4). In fact, there is compelling evidence in support of this tentative concept in SLE (reviewed by Goel and Kaplan [36] and Granger et al. [268]). Observation and findings from earlier studies on sera and neutrophils of SLE patients have already led investigators to propose that autoantibodies ICs (e.g., anti-RNP ICs) may elicit FcR-dependent formation of NETs and NETosis [269, 270]. Garcia-Romo et al. [270] remarkably concluded already from their findings: Furthermore, they explain how anti-RNP antibodies might contribute to the production of IFN via induction of a peculiar form of neutrophil death that represents source of highly immunogenic DNA. There, all the necessary ingredients converge to trigger the adaptive immune system through a self-amplifying pathogenic loop. Consistent with these reports were subsequent studies showing, besides others, that mitochondrial ROS are able to drive NETosis following RNP IC stimulation in vitro [123]. In more recent in vitro studies on serum of SLE patients, ICs were found to induce NET formation in a FcγR- depending manner, associated with the presence of DAMPs such as HMGB1 and
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oxidized mtDNA [271]. Convincing support for the correctness of the concept of IC-induced NETs and NETosis in autoimmunity comes from investigations on immobilized ICs (i.e., hallmarks of several autoimmune diseases), revealing that antibody-containing ICs induce ROS-dependent, FcγRIIIB-mediated NETosis of human neutrophils [272]. Of note, as pointed out already above, a distinct subset of proinflammatory neutrophils, the LDGs, has been described that are elevated in SLE and possess an increased capability for NET formation. The NETs are enriched in oxidized mtDNA, thereby enhancing type I IFN production by human peripheral blood cells and pDCs through STING- and/or TLR9-dependent pathways [123, 273]. And it is the type I IFNs and their signaling, mostly IFNα and IFNβ, and the type I IFN signature that is critical in the pathogenesis of SLE. This is the more of note as type I IFNs reportedly induce chromatin remodeling and, as noted above, SLE patients have increased global and gene-specific epigenetic modifications, such as hypomethylation of DNA and histone acetylation (reviewed by Stefania Gallucci et al. in [274]).
7.2.9.5 Concluding Remarks The autoreactive T and B cell responses in SLE can be rightly regarded as a highly complex scenario. Generation of bona fide self antigens or altered-self antigens in the course of DAMP-induced RCD, activation of three types of DCs, the function of aberrant T and B cells, and production of autoantibodies are important pathogenic mechanisms of development and progression of SLE disease in patients. A complicated interaction of environmental factors with certain genetic risk alleles and their potential (DAMP-induced?) epigenetic modifications may contribute to the complexity of the disease and, thus, to patient heterogeneity as seen by the treating physicians. The interplay of constitutive/modified DAMPs (nuclear DAMPs) and inducible DAMPs (type I IFNs!) may reflect the molecular machinery that sustains the aberrant function of T cell subsets, B cells, and plasma cells, as well as subsequent autoantibody production (cf. Fig. 7.1).
7.2.10 Organ-Specific Tissue Injury 7.2.10.1 General Remarks Disease heterogeneity in patients suffering from SLE remains a major challenge for physicians to make a proper prima vista diagnosis. Of note, mechanistically, the development of autoimmunity and local tissue injury are two distinct independently regulated processes and emerge in two phases [9, 275]. The first phase refers to the development of a chronic autoimmune response manifested by the presence of autoantibodies and activated T and B cells, whereas the second stage represents the clinically overt immune-mediated tissue inflammation of target organs. (Note: this characteristic feature is also observed in RA and will be discussed in more detail there.) As target organs for damaging insults, kidneys, skin, joints, as well as the hematopoietic, nervous, and cardiovascular systems, are most commonly involved. To
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outline details of the full spectrum of end-organ injury in SLE is beyond the scope of this section. Here, some destructive autoimmune effects on the kidney, skin, and CNS are briefly outlined.
7.2.10.2 Lupus Nephritis Lupus nephritis is a major cause of morbidity and mortality in patients with SLE. The disorder occurs in approximately 50% of lupus patients, but rates vary significantly between genders. Nephritis in SLE patients is characterized by immune complex deposition and immune-mediated injury to the kidney parenchyma. Clinically, the disease manifests as periods of remission infiltrated with episodes of acute flares. If these inflammatory processes are not efficiently treated, glomerulosclerosis, interstitial fibrosis, tubular atrophy, and chronically progressive kidney failure will follow, leading to end-stage renal failure requiring renal replacement therapy, for example, kidney transplantation [276, 277]. Notably, the accumulation/deposition of ICs in the renal glomeruli is necessary, but not sufficient, to trigger glomerulonephritis resulting in renal end-stage failure. Moreover, various intrarenal resident/sessile and mobile/infiltrating, nuclear DAMP-activated PRR-bearing cells of the innate immune system promote tubulo- interstitial inflammatory responses, known to contribute to this disease. For example, in murine and human lupus nephritis, pDCs were found to recognize ssRNA and CpG DNA derived from endogenous NAs through TLR3, TLR7/8, and TLR9. In addition, IC-mediated activation of complement has been suggested to be involved in lupus renal disease. Surprisingly, however, only a few autoantibodies have been found to specifically contribute to the kidney-related injury seen in mice and humans, including anti-dsDNA antibodies (for reviews, see [137, 275, 277– 281]). On the other hand, as demonstrated by other lines of studies, SLE patients in clinical remission continue to produce elevated levels of self-reactive and polyreactive antibodies [282]. These findings suggest that autoimmunity and local renal tissue damage are independent processes. In fact, in regard to this scenario, lupus nephritis represents an example of the discrepancy between autoantibody production and end-organ damage (for more detailed information, see the excellent review of Anders et al. [283]). 7.2.10.3 Skin Injury The pathogenesis of skin injury of SLE has recently been reviewed [284–286]. Cutaneous lesions include a broad range of dermatologic manifestations and— though seldom life-threatening—are common in SLE. The pathogenesis is multifactorial and includes genetic contributions as well as effects of UV light that is a typical precipitant of an SLE flare as a result of keratinocyte apoptosis. Immune dysregulation and aberrant cell signaling pathways through cytokine cascades are implicated, and ICs, as seen in skin biopsies from patients with SLE, are, in fact, a typical diagnostic finding of SLE. Indeed, as reviewed by Deng et al. [286], skin- deposited IgG is a typical pathologic factor in the development of skin damage.
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Moreover, macrophages and signaling of TNFα ↔ TNFR1 and IFN ↔ IFNR were found to play a critically important role in the skin injury of SLE.
7.2.10.4 Attribution of Neuropsychiatric Manifestations Neuropsychiatric involvement in SLE is one of the most severe manifestations of the disease that has a heavy impact on a patient’s functioning, quality of life, and disease outcome. Its prevalence is highly variable, ranging from 14% to 75% (reviewed by Tsokos et al. [9] and Bortoluzzi et al. [287]). Its occurrence may be the result of a primary manifestation of SLE, secondary to other conditions, or the effect of concomitant comorbidities that often complicate the disease course. The disease remains one of the most troubling and puzzling clinical features of SLE. A meta-analysis indicated that polymorphisms in genes associated with IC clearance are potential susceptibility genes for the disease [288]. Dysfunction of the blood- brain barrier (BBB) and abnormal function of the blood-cerebrospinal fluid barrier have been proposed to allow autoantibodies, immunoglobulins, cytokines, and immune cells to infiltrate the brain tissue reflecting a central mechanism of neuropsychiatric lupus [289]. Evidently, the complement system has a key role in disrupting the integrity of the BBB [290]. Certain autoantibodies, including anti-phospholipid antibodies, anti-DNA antibodies, and anti-N-methyl-d-aspartate (NMDA) receptor antibodies, have been suggested to be involved in the pathogenesis of this neuropsychiatric disease through multiple mechanisms [291, 292]. 7.2.10.5 Concluding Remarks Today’s increased longevity of patients suffering from SLE leads to chronic organ damage accrual, which reduces the possibility of further survival improvement in patients with the disease. Besides the involvement of renal, cutaneous, and neuropsychiatric systems, other systems, such as the cardiovascular system, have also increased over the past decades and remain major factors that limit survival improvement in patients with this disease. Thus, there may be some hope that both improved diagnostic modalities based on measuring DAMPs as biomarkers and therapeutic strategies in administration of SAMPs involved in SLE may mitigate the course of illness, a topic that will be addressed below.
7.2.11 Summarizing Hypothetical Model to SLE Pathogenesis: Immune Complex-Induced NETs and NETosis and the DAMP-Promoted Positive Feed-Forward Loop as Drivers of Type I Interferon Secretion by Plasmacytoid Dendritic Cells In Sect. 6.2.4.4 and Fig. 6.4, a model scenario was sketched hypothesizing that IC-induced NET formation/NETosis and subsequent initiation of a DAMP-promoted positive feed-forward loop may orchestrate autoimmune responses in terms of a
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Fig. 7.4 Schematic diagram of a hypothesis-based narrative model applied to SLE illustrating pDCs activation by NETosis-derived “interferogenic” DNA (i.e., oxidized DNA, eventually bound to ICs) leading via TLR9 and cGAS-STING signaling to secretion of INF-α. This type I IFN promotes induction of NETosis, necroptosis, and pyroptosis associated with release of nuclear and cytosolic DAMPs. A DAMP-driven positive feed-forward loop is established that activates PRR- bearing cells of the innate immune system, such as neutrophils and cDCs, which are involved in driving innate/inflammatory and adaptive autoimmune responses. Finally, the generation of ICs complexed with NAs may activate pDCs again: a vitious circle. Note, details of the DAMP-driven positive feed-forward loop are not shown here but illustrated in Fig. 6.4. Also, details of TLR9- and cGAS → STING-triggered signaling pathways are not shown here but are illustrated above in Figs. 4.5 and 4.7. cDC conventional dendritic cell, cGAS cyclic GMP-AMP synthase, FcγRIIa IgG-Fc receptor IIa, IC immune complex, IFN-α interferon alpha, IFNAR1 type I interferon receptor 1, NAs nucleic acids, oxDNA oxidized DNA, pDCs plasmacytoid dendritic cells, PMN polymorphonuclear leukocyte, STING stimulator of interferon genes, TLR9 Toll-like receptor 9. (Sources: [122, 123, 223, 293–296])
vitious circle. In light of what has been discussed above, particularly in Sects. 7.2.7.4 and 7.2.9.4, the hypothetical model can be applied again in SLE, this time with relation to the pronounced impact of type I IFNs on the development of a broad spectrum of innate and adaptive autoimmune responses as observed in SLE. The sequelae of cellular interactions and pathways in illustrated in Fig. 7.4: IC/ NA-induced formation of NETs/NETosis → release of nuclear DAMPs (e.g., oxidized DNA) → endocytosis by pDCs and recognition by TLR9 and cGAS → STING → signaling through cGAS → STING- and TLR9-triggered transcriptional pathways → secretion of type I IFNs → (1) type I IFN-driven contribution to activation of NETosis [293], necroptosis [294], and pyroptosis [295, 296] and → (2)—via type I IFN-promoted maturation of cDCs—re-activation of the ongoing adaptive autoimmune response, leading to the new formation of IC/ NAs → IC/NA-triggered formation of NETs/NETosis. Future targeted studies will have to show how close this hypothesis has come to the genuine pathogenetic trajectories that will eventually be firmly discovered in SLE.
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7.3 Rheumatoid Arthritis 7.3.1 Introductory Remarks 7.3.1.1 General Remarks Rheumatoid arthritis is a complex crippling autoimmune disease characterized by chronic inflammation of small synovial joints in which cartilage, tendons, and bone of the affected subjects are progressively destroyed in multiple joints (most commonly in the hands, wrists, and knees), thereby classifying RA as a systemic autoimmune disease. According to reports from the literature, RA affects 0.5–1% of the population by showing regional variation and arises more frequently in females than males and is predominantly observed in the elderly. In a recent meta-analysis based on a systematic review, the global RA prevalence estimate was calculated to be 0.46%. The activity and detrimental effects of RA have diminished over time, in conjunction with novel therapeutic interventions. However, there seems to be no decrease in the frequency of RA, which continues to induce considerable mortality [297–299]. 7.3.1.2 Clinical Picture and Classification Early in the disorder, tender and painful joints and joint stiffness dominate the clinical manifestations. Eventual functional loss due to structural injuries becomes the major problem, as reflected by progressive disability, premature death, and socioeconomic burdens. The clinical picture is an expression of inflammatory processes that include a cascade of events inducing synovitis with consequent destructive arthritis characterized by the proliferation of synovia and cartilage and subchondral bone destruction. The disease emerges in fictional phases. A pre–RA phase, also termed Preclinical RA, refers to a period during which elevated systemic innate and adaptive immune mediators (e.g., several types of circulating autoantibodies such as ACPAs, rheumatoid factor [RF], and antibodies to other posttranslationally modified proteins [e.g., carbamylated proteins] as well as cytokines) can usually be detected. Immunologically, patients with RA can be divided into two major subsets: seropositive and seronegative RA, based on the presence (~2/3) or absence (~1/3) of ACPAs and RF [300]. Notably, seropositive RA is associated with worse clinical outcomes, exemplified, for example, by the increased risk of cardiovascular mortality [301]. The distinction between these two disease entities is stressed by differences in underlying environmental and genetic risk factors, reflecting a different etiology and pathophysiology between ACPA-positive and ACPA-negative RA disease. The Pre-RA phase is followed by the true onset of clinically evident articular joint disease during the early RA phase, which is characterized by acute articular inflammation and symmetric polyarthritis. This usually evolves into established RA that is hallmarked by chronic inflammatory arthritis and associated tissue remodeling in terms of hyperplastic synovial pannus tissue and damage. Of note, the disorder also affects a variety of extraarticular organs such as peripheral nerves, muscles, lungs, and especially the arterial walls resulting in rheumatoid vasculitis, which may cause infarction and hemorrhage (for further reading, see [302–304]).
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The classification criteria of RA refer to those as published by the ACR and the EULAR established in 2010 [305] (for more information, see Box 1 in Ref. [303]). The criteria have been developed for a target population of patients presenting with at least one clinically swollen joint that cannot be clearly explained by another disease.
7.3.2 Experimental Animal Models Animal models have been used extensively in studies on the pathogenesis of RA. These models, with a proven track record of predictability for efficacy in humans, include collagen type II-induced arthritis (CIA), collagen antibody-induced arthritis (CAIA), zymosan-induced arthritis, and antigen-induced arthritis (AIA) (e.g., methylated bovine serum albumin [BSA]), as well as the genetically manipulated or spontaneous arthritis models such as the TNF-transgenic mouse, K/BxN mouse, and the Skg mouse (reviewed [306, 307]). Although none of these models entirely reflect clinical pathology, they have contributed to a better understanding of those processes believed to be involved in RA development and progression and provided valuable information relating to the pathogenesis of RA. In fact, as with SLE, the pathogenesis of RA is complex, as documented in numerous reviews, some of which have been published very recently (see [308– 314]). In the following sections, some aspects from all of these reports will be highlighted, again by focusing primarily on the role of DAMPs.
7.3.3 The Pathogenesis of Rheumatoid Arthritis: Cellular Events Typically, RA pathogenesis is the result of an orchestrated action of various cell types with highly specific intracellular cross-talks, which create the typical symptomatology and clinical signs of the disease. These cells include innate immune PRM-bearing resident cells such as fibroblast-like synoviocytes (FLSs), macrophage- like cells, chondrocytes, and ECs, as well as PRM-bearing mobile cells such as macrophages, neutrophils, DCs, mast cells, and NK cells. Cells of the adaptive immune system, such as T and B cells, plasmablasts, and plasma cells, join the multicellular orchestra [303, 315]. It is the FLSs that deserve a special note, as they have been identified as the main effector cells in RA. Fibroblast-like synoviocytes, also known as synovial fibroblasts or type B synoviocytes (vs. A-type synoviocytes [macrophage-like synoviocytes, MLSs]), are the predominant cell type comprising the structure of the synovial intima in healthy joints. They are structured and organized in two to three layers of cells and account for 75–80% of all synoviocytes in normal human synovium. In a normal physiological state, FLSs have been found to play an essential homeostatic role in the formation of a normally organized synovial lining and the production of synovial fluid (SF) constituents [316–319].
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Of note, during the past years, FLSs have been recognized as the key players in the RA synovium and are considered a productive source of cartilage and bone degradation factors (e.g., enzymes) and inflammation [316, 319, 320]. The prominent role as key cells in the pathogenesis of RA is underlined by the fact that these so-to- speak sentinel cells of the innate immune system are endowed with multiple PRRs that allow the regulation of immune responses and chronic inflammation [321]. In view of the danger/injury model, the sentence may be modified to: “The prominent role as key cells in the pathogenesis in RA is underlined by the fact that these so-to- speak sentinel cells of the innate immune system are endowed with multiple PRRs that allow—via interaction with DAMPs—regulation (but also dysregulation!) of multiple DAMP-driven innate immune and DAMP-shaped adaptive immune responses.” Notably, during the pathogenesis of RA, FLSs have been observed to undergo a transformation in which their phenotype changes, now exhibiting invasive “cancer-like” aggressive properties similar to that observed in tumor conditions (for more in-depth information, see reviews of Nygaard and Firestein [322], Masoumi et al. [323], and Mousavi et al. [324]). In brief: The transformation process of these cells as seen in RA is amazing: Their number increases sharply and, as overproliferating innate immune cells, they contribute to synovial inflammatory processes and remodeling of the synovial lining from a tenuous structure into an invasive hyperplastic tissue mass, called “pannus.” This hypertrophied synovial tissue that is composed of cells such as macrophages, osteoclasts, and invasive FLSs covers the cartilage and behaves like a locally invasive tumor by eroding the cartilage toward the bone. The “malign” process finally results in a perpetuation of destructive joint inflammation, characterized by severe bone and cartilage degradation/destruction associated with osteoclastogenesis and synovial neoangiogenesis. Another typical hallmark of FLSs is their ability to crosstalk with various cells; for example, • with B cells, contributing to their clonal expansion and differentiation associated with the production of a variety of autoantibodies; • with T cells, by serving as APCs to drive adaptive autoimmune responses; • with macrophages, promoting their function to produce inducible DAMPs (TNF and IL-1β) in the rheumatoid synovium; and • with ECs, thereby regulating the influx of further inflammatory cells. The vital pathogenetic role of these DAMP-activated innate immune cells in RA will be recaptured and expanded below. Together, the pathogenic potential of FLS in RA is thought to stem from their unique capability to express immunomodulating cytokines and chemokines as well as a wide array of adhesion molecules and matrix-modeling enzymes such as proteases. The FLS have been proposed to be considered as “passive responders” to the immunoreactive process in RA, their activated phenotype reflecting the proinflammatory milieu. However, as further reviewed [319], FLS from patients with RA also display unique aggressive features that are autonomous and vertically transmitted,
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and these cells can invade articular cartilage and operate as primary promoters of inflammation.
7.3.4 Pathogenesis-Orchestrating Interrelationship Between Environmental Triggers, Genetic Predisposition, and Epigenetic Modifications 7.3.4.1 General Remarks As with SLE, multifactorial environmental, pathogen-mediated or sterile injurious stimuli are considered to promote and precipitate RA in a genetically susceptible individual. Moreover, there is increasing evidence indicating a pathogenetic role of aberrant epigenetic modifications in RA, such as DNA methylation, histone marks, and noncoding RNA. In addition, according to current knowledge, DAMPs are involved at the beginning and the end of this scenario and seem to play a crucial pathogenetic role in patients genetically predisposed to develop RA (Fig. 7.5).
Scenario Model: Pathogenesis of Rheumatiod Arthritis Regulated cell death
Generation of AutoAgs+DAMPs
Activation of APCs
e.g., Smoking (!), Air pollutans, Atmosp. agents, Diet, Infections
e.g., NETosis, Pyroptosis, Necroptosis
Auto-/alter-selfAgs + endog. DAMPs exog. DAMPs
APCs (cDCs, pDCs, FDCs, FLSs, B cells)
I nt er play e.g., HLA-II, STAT-4, MIR146A, PTPN2
e.g., Aberrant DNA methyl, Histone modif., ncRNA
Genetic risk factors
Epigenetic modifications
Processed auto-/alterd-selfAg/MHC DAMP-induced costimulatory molecules T cell polarizing cytokines → naive T cell activation
Innate immune response
Pos itiv ef ee
loop ard rw fo d-
Environment. factors
AutoAbs + autoAgs/ Immune complexes ACPA, ICs/ ACPAs T cells (Tfh Th1,Th17)
RA
Adaptive immune response
Fig. 7.5 Simplified scheme of a tentatively designed scenario model of the pathogenesis of rheumatoid arthritis. The scenario involves a complex interplay of factors and processes, including environmental factors, genetic risk factors, epigenetic modifications, induction of regulated cell death as potent sources of autoantigens and DAMPs, autoantigen/DAMP-promoted innate and adaptive immune responses, generation of autoantigen/autoantibody immune complexes driving, via induction of NETosis, a DAMP-promoted positive feed-forward-loop in DAMPs emission, orchestrating continuously the autoimmune response acetyl acetylation, ACPA anti-citrullinated protein antibodies, APCs antigen-presenting cells, autoAbs autoantibodies, autoAgs autoantigens, cDCs conventional dendritic cells, Exog exogenous, FDCs follicular dendritic cells, HLA human leukocyte antigen, IRFs interferon regulatory factors, methyl methylation, MHC major histocompatibility complex, nauAgs nuclear autoantigens, pDCs plasmacytoid dendritic cells, PRR pattern recognition receptor, SLE systemic lupus erythematosus, Tfh follicular helper T cells, Th1/17 T helper cell type 1/17, UVR ultraviolet radiation
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The exact etiopathogenesis of the disease remains still unclear, but the irreversible breakdown in immunologic self tolerance is generally seen in a complex interplay among multiple environmental influences and genetic risk factors in combination with epigenetic modifications, which differently influence each of the three periods of the disease [325]. Currently, the understanding by rheumatologists of the role of innate and adaptive autoimmune processes in the pathogenesis of RA is expanding—as coherently summarized in this and the following sections.
7.3.4.2 Environmental Factors and the Role of Regulated Cell Death Many environmental factors, including cigarette smoking, air pollutants and occupational and atmospheric agents, diet, obesity, and the microbiome, as well as certain previous infections, have been identified to act as trigger stimuli for the development of RA, some of them known to be also involved in the pathogenesis of SLE such as cigarette smoking and silica (for elaborative articles, see [308, 309, 326–328]). Together, as already mentioned in the context of SLE, all these environment-mediated events act themselves intrinsically as exogenous DAMPs (e.g., silica particles, see Vol. 1 [30], Sect. 15.2.4, p. 355) or reportedly induce severe cellular stress leading to subroutines of RCD, including secondary necrosis after apoptosis, necroptosis, pyroptosis, ferroptosis, and NETosis [17, 18, 31–33]— all defined to be associated with the release of large amounts of endogenous DAMPs. In fact, the conceptual sequelae of stress/injury → RCD → DAMPs that govern the pathogenesis of antigen-dependent human diseases can be encountered again here (cf. Fig. 1.3). Subroutines of RCD so far described to occur in RA include necroptosis [329], pyroptosis (e.g., via Gasdermin-E) [330, 331], and NETosis [332, 333]. Of note, however, current notions hold that environmental factor-induced RCD (e.g., smoking-induced RCD) are preferentially implicated in the initial extraarticular pre-RA phase of the disease (and possibly also in subsequent relapses), whereas, during clinical onset and progression of the disease, ACPAs and ACPA-ICs take over to promote predominantly induction of cell death in the synovium (the emerging topic will be detailed below). Of interest in this context are experiments showing the role of environmental factors in RA pathogenesis. For example, in studies on a mouse model, nicotine was demonstrated to drive the NET formation and accelerate CIA [334] (Fig. 7.5). Notably, it is worthwhile to mention here that some of these factors, such as smoking, are known to induce NETosis as a special subroutine of RN [334, 335]. And it is this process of NETosis that—like in SLE—is regarded as a key feature in the pathogenesis of RA, mostly in relation to generation and release of modified altered- self (e.g., citrullinated) antigens (signal 1) [336, 337]. However, as emphasized in previous sections, NETosis must also be considered a critical source of both nuclear and cytoplasmic DAMPs to provide obligate costimulation (signal 2). Exposure to cigarette smoke is probably one of the strongest environmental risk factors associated with the disease [338]. Interestingly, it is epidemiological studies have remarkably revealed the association between cigarette smoking and RA. For example, as observed in a historical cohort study on twins born from 1920 to 1982,
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the risk of developing RA was found to be more than doubled after 20 years of smoking in both sexes, whereby smoking duration, but not intensity, mattered [339]. Also, several pieces of evidence reportedly suggest a possible correlation between the development of RA and exposure to occupational and atmospheric agents such as silica/dust. Thus, already in 1953, the occurrence of multiple peripheral lung nodules was found in coal workers that had RA [340]. More recently, a high risk of developing ACPA-positive RA was observed among silica-exposed smokers in a small Swedish cohort [341]. Moreover, there have also been findings linking increased exposure to inhaled particulate air pollution and increased risk for RA [342]. The association between viral and bacterial infections and RA development has also been investigated. Thus, a growing number of studies reportedly underline the association between the development of RA and periodontitis caused by Porphyromonas Gingivalis infection [343, 344]. Interestingly, P. gingivalis was shown to play its detrimental role not only by inducing citrullination but also NETosis [345]. Also, studies of RA after viral exposures are in progress. Thus, as recently reviewed [328], there is a risk of RA after Parvo B19, HCV, and possibly EBV infection, whereas Chikungunya Virus is associated with persistent inflammatory arthritis. By contrast, CMV and HBV infections are not associated with RA. Interestingly, respiratory virus infections, including COVID-19, have recently been found to be associated with an increased number of incidents of RA, especially in women and the elderly, suggesting that respiratory viral infections can operate as environmental risk factors for the development of this disease [346, 347]. In background that these infections promote the emission of DAMPs derived from RCD, these findings are not surprising (see Sect. 3.7 and Figs. 3.8a/b, 3.9, and 3.11a/b). The same scenario can be discussed for obesity as another risk factor for RA development as this metabolic disease has also been shown to contribute to metabolic stress-triggered emission of DAMPs [348]. Overall, it can be cautiously concluded that environmental risk factors, as an integral part of the pathogenesis of RA, especially in the initial developmental phase and in subsequent relapses, exert their pathogenic effect via RCD-provoked emission of DAMPs.
7.3.4.3 Genetics Genetics have definitely a major influence on the development of RA. Human genetic studies into RA have uncovered more than 100 genetic loci associated with susceptibility to RA and have refined the RA-association model for HLA variants. As reported by Kim et al. [349], … The majority of RA-risk variants are highly shared across multiple ancestral populations and are located in noncoding elements that might have allele-specific regulatory effects in relevant tissues. Emerging multi-omics data, high-density genotype data, and bioinformatic approaches are enabling researchers to use RA-risk variants to identify functionally relevant cell types and biological pathways that are involved in impaired immune processes and disease phenotypes. Genetic factors so far identified include the generally increased prevalence of RA within families, leading to estimations of familial risk contribution of ~40–50% of
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seropositive RA, with the strongest risks seen in first-degree relatives [350]. In addition, multiple specific genetic loci have been identified that are associated with increased risk for RA and, in some cases, decreased risk. In particular, recent advances in GWAS and subsequent meta-analyses have revealed many alleles that govern RA susceptibility [351]. Certainly, as also reviewed by Kampstra and Toes [310], for ACPA-positive RA disease, the genetic factors associated with the disease mainly comprise MHC-II (HLA-II) molecules supporting the impact of autoreactive Th cells on the development of this disorder. Indeed, GWAS have identified 101 SNPs in total, emphasizing the highest contribution of the hla-drb1 gene to the development of RA. Notably, Hla-drb1-encoded proteins are components of HLA-DR molecules, and, together with HLA-DQ and HLA-DP, they represent the major determinants in antigen presentation-mediated induction of adaptive immune responses. In fact, genetic variants affecting the structure of epitope-binding sites of pMHC-II molecules expressed on APCs exhibit the strongest contributions to RA development (compare Vol. 1 [30], Sects. 31.3.4 and 31.3.6; Figs. 31.2 and 32.3, pp. 735–743). The authors summarize in their abstract [310]: The predisposing HLA-DR alleles have been depicted as the “HLA Shared Epitope (SE) alleles”, as these alleles encode a similar sequence, the shared epitope sequence, within the beta chain of the HLA-DR molecule. In addition to the involvement of the HLA-SE alleles in the development of ACPA-positive RA disease, other HLA-DR molecules have been shown to confer protection against this disease entity. Nevertheless, as discussed by Kim et al. [349], the amino acid-based HLADRB1-association model for ACPA-positive RA explains some of the RA-risk HLADRB1 alleles that cannot be explained by the shared epitope model and accounts for RA-risk associations of other functional HLA-DRB genes. Moreover, as further pointed out by the authors [349], as compared with ACPA-positive RA, ACPA-negative RA is relatively poorly studied. The association of MHC variants (e.g., shared epitope alleles) with ACPA-negative RA is inconsistent among published studies. In addition to the MHC-HLA loci, more than 100 common variants in non- MHC-HLA loci have been implicated in RA susceptibility, whereby most of the reported non-MHC RA-risk variants are also shared with other autoimmune diseases [352]. For example, polymorphisms in STAT-4 and IL-10 genes were found to confer susceptibility to RA [353]. Moreover, the authors of this study on an Italian population described that SNPs in PSORS1C1, PTPN2, and MIR146A genes were associated differently with a severe disease phenotype in terms of autoantibody status and radiographic damage. In addition, other lines of studies in terms of a meta- analysis showed associations between circulating IL-17 levels and RA and between IL-17 gene polymorphisms and disease susceptibility [354]. In addition, several studies report that RA-associated genes or variants implicate T cells (i.e., CD4+ T cells) in RA pathogenesis. In fact, 13 RA-risk loci gene products are mapped to simplified signaling pathways involved in T cell differentiation. In a more recent study on three large case-control collections consisting of 311,292 individuals of Korean, Japanese, and European populations, 11 new RA susceptibility loci were identified that explained 6.9% and 1.8% of the SNP-based heritability in East Asians and Europeans, respectively, and confirmed 71 known non-HLA susceptibility loci, identifying 90 independent association signals [355].
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Of major interest in this context are somatic mutations in a variety of genes that could contribute to the altered “cancer-like” phenotype of FLS in RA. For example, as argued and discussed by Nygaard and Firestein [322], transition mutations could be caused by ROS and RNS in the highly inflamed joint. Thus, mutations in TP53 have reportedly been identified, which encodes cellular tumor antigen p53 in RA. And it is p53, also called “the guardian of the genome,” that was shown to maintain genome integrity and prevent the proliferation of cells with damaged DNA. Together, research in the genetics of RA is flourishing but still not completely understood. Thus, Kim et al. conclude [349]: Despite successes within RA genetic research, a large proportion of RA heritability remains unexplained, and our understanding of the biological effects driven by identified RA-risk variants is far from complete. The identification of more RA-risk loci will be necessary for the development of future therapies. Multiple mechanisms of cellular regulation associated with genetic RA-risk variants operate in a cell-specific manner. Functional studies of genetic variants in cell types relevant to RA pathogenesis are required to demonstrate the effect of RA-risk variants at a cellular level. In addition, cutting-edge genomic technologies (such as next-generation sequencing and high-coverage genetic arrays) and various statistical approaches should be actively deployed to investigate RA-risk variants.
7.3.4.4 Epigenetics Again, as with SLE, the development of RA cannot be explained by genetic susceptibility alone. Epigenetic variations, including DNA methylation, histone modifications, miRNA, and lncRNA, may also be involved in representing the link between environmental and genetic factors and are discussed to be eventually triggered by DAMPs. In order to echo the remark from Sect. 7.2.3.4 above: theoretically, the critical event causing RA should be searched in (1) the generation of an altered-self antigen in the course of RCD; or—in case such an epigenetically modified self antigen is not created—(2) dysregulated APCs presenting original self antigens as altered-self antigens epigenetically modified during protein processing to peptides; and/or (3) in the TCR/BCR signaling of autoreactive T and B cells, which either have escaped central tolerance mechanisms or may be epigenetically modified. Indeed, targeted RA-related epigenetic studies have revealed stable epigenetic marks, which lead to changes in cellular functionality, thereby further increasing the well-known complexity of RA. Here, their results are briefly discussed (for reviews, see [72, 356–359]). Posttranslational Modifications at the Level of Altered-Self Antigens: Citrullination Posttranslational modifications such as citrullination, carbamylation, and acetylation are correlated with the pathogenesis of RA. The characteristic PTM of altered- self antigens in RA is citrullination, that is, conversion of an arginine residue into citrulline in proteins and peptides, a modification that is also observed in normal physiological processes but obviously dysregulated in RA. In fact, a unique set of
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intra- and extracellular citrullinated proteins are highly enriched in the rheumatoid joint (reviewed in [360–363]). The reaction is catalyzed by the Ca2+-dependent PAD family of enzymes, whereas five PADs have been identified in humans (PAD1–4 and 6). With regard to RA, PAD2 and PAD4 are the most relevant because they are predominantly overexpressed in immune cells, including macrophages and neutrophils. Pathways that promote the concentration of intracellular calcium in excess, such as host (i.e., MAC and perforin) and bacterial (i.e., toxins) pore-forming proteins, are potent activators of PADs and inducers of hypercitrullination [361] (for MAC and perforin, see Vol. 1 [30], Sect. 23.2.4, p. 603 and Sect. 27.2.3.2 and Fig. 27.2, pp. 669–672). Once released from (DAMP ?-) activated stressed and/or dying cells, these enzymes citrullinate numerous different proteins, including vimentin, fibrinogen, alpha-enolase, filaggrin, and keratin, whereby PAD 1, 2, and 4 citrullinate various histones as well. Interestingly, PADs have been shown to be released by a form of regulated cell pore-forming neutrophilic cell death resembling NETosis [361, 364] (compare Fig. 3.11a). In addition to citrullination, acetylation and carbamylation are also involved in autoimmunogenicity in RA, a topic that will not be pursued further here. Epigenetic Modifications at the Level of Fibroblast-Like Synoviocytes A majority of data about the role of epigenetics in RA disease come from studies on synovial tissue and innate immune cells such as FLSs. Epigenetic mechanisms associated with FLS imprinting in RA include alterations in DNA methylation, histone modifications, and miRNA expression. A first comprehensive epigenomic characterization of RA FLS, including six histone modifications (H3K27ac, H3K4me1, H3K4me3, H3K36me3, H3K27me3, and H3K9me3), open chromatin regions, RNA expression, and whole-genome DNA methylation was recently published by Ai et al. [365] and Karami et al. [366]. Notably, these modifications reportedly convert a normal FLS into an aggressive and hyperplastic phenotype associated with the production of several proinflammatory cytokines that are supposed to result in bone and cartilage destruction. Trained Immunity in Rheumatoid Arthritis As with SLE, in a discussion of the pathogenetic role of epigenetics in RA, the issue of trained immunity comes up again. And Badii et al. [68] argue here: “Interestingly, monocytes from a subset of patients with active RA were shown to have altered epigenetic states which made them resistant to the homeostatic pathway of TNF- dependent inhibition of osteoclast differentiation. This suggests that previous epigenetic processes could aggravate erosive processes in different subsets of patients and that alternative mechanisms may be at play in the progression of RA. The cause of such initial epigenetic reprogramming is yet unknown but addressing the possibility of trained immunity occurring and contributing to the pathogenesis and response to therapy in RA is worthwhile.”
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7.3.4.5 Concluding Remarks Understanding the pathogenetic relationship between environmental factors, genetics, and epigenetics in the development of RA is still in its infancy. A major goal of future studies will be to identify environmentally derived DAMPs and their impact on disease genes and epigenetic modifications that may lead to new insights into the pathogenesis of RA.
7.3.5 Pathogenetic Principles of Autoantigen Formation and Emission of DAMPs 7.3.5.1 General Remarks The very initial environment-mediated damaging trigger of the RA pathogenesis in genetically susceptible hosts is still elusive. Nevertheless, there is accumulating evidence suggesting that initial autoantigen formation and putative DAMP emission instigating an innate/adaptive autoimmune response (e.g., autoantibody production such as ACPAs) occur extraarticularily (e.g., at mucosal sites of the lung and intestine) at the early stage of RA when clinical symptoms are still absent (asymptomatic autoimmunity). As will be described in more detail below, subsequently, these early responses can lead to a more substantiated secondary autoimmune reaction targeting the joints and precipitating the clinical onset of RA (established autoimmune disease). Both innate and adaptive mechanisms will then locally, that is, intraarticularly, interplay to promote chronic DAMP-mediated joint inflammation. In fact, since all synovial cells, including FLS, are equipped with PRRs, the final execution of destructive synovitis can be assumed to be the work of various DAMPs demonstrated in the RA synovia. 7.3.5.2 Autoantigens As briefly outlined above, the key autoantigens which fuel the autoimmune processes in the pathogenesis of RA are citrullinated altered-self proteins/peptides that are neither tissue nor organ-specific. Notably, autophagy and NETosis reportedly appear to be key cellular events involved in the generation of citrullinated peptides [336, 367]. Intriguingly, careful analysis of the cellular and soluble components in RA serum, SF, and synovial tissue samples have identified more than 150 novel citrullinated proteins, which include both intra- and extracellular substrates and together comprise the RA citrullinome. As mentioned above, they include alpha- enolase, fibrin, vimentin, keratin, and filaggrin which are catalyzed by PADs and released during neutrophilic RCD [360–362, 368]. Besides citrullinated altered-self proteins, other modified altered-self antigens proposed to be involved in RA have been described, including N-acetylglucosamine-6-sulfatase, filamin A [369], carbamylated vimentin [370], and malondialdehyde (MDA)-adducts in a variety of proteins including albumin, histone 2B, fibrinogen and vimentin [371]. Besides altered-self antigens, however, several native autoantigens have also been identified that are recognized by autoantibodies in both ACPA-positive and anti-ACPA-negative RA [372]. Accordingly, the authors concluded that
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autoimmunity in RA is not restricted to posttranslationally modified altered-self epitopes.
7.3.5.3 DAMPs Notably, when describing the role of DAMPs in the pathogenesis of RA, we must differentiate between extraarticularly operating DAMPs (induced, for example, by environmental factors such as cigarette smoke in the lung [39]) and intraarticularly operating DAMPs emitted in the synovium. It is quite conceivable that extraarticular emission of DAMPs is involved in the preclinical RA phase, where together with autoantigens, they initiate first autoimmune responses resulting in the production of autoantibodies (e.g., ACPAs, see below). And we should not forget that DAMPs can exert a remote effect far from their original site of emission, that is, in this case, effects on RA joints [373]. Later on, in case of overt synovitis, they operate in the synovium. Indeed, the demonstration of various subroutines of RCD, such as NETosis, pyroptosis, and necroptosis in synovial cells, as revealed in RA, provides a plausible basis for explaining the substantial synovial release of DAMPs. Accordingly, the marked synovial inflammation and proliferation in joints reflect the executive work of DAMPs—or DAMPs together with MAMPs in case of infection-triggered disease. Indeed, expression/emission of DAMPs in serum, SF, and cells in RA has impressively been demonstrated (for reviews, see [374–376]). Some key molecules are cursorily listed here before their role in promoting synovial autoinflammatory processes is described in more detail in the next section. HMGB1, S100A Proteins (Calgranulins), Heat Shock Proteins Let’s start with HMGB1, whose nature and function of HMGB1 have been addressed in Vol. 1 [30], Sect. 12.2.2, Figs. 12.1 and 12.2, pp. 220–226. The direct arthritis- inducing function of this prototypic DAMP has been extensively studied in RA models and shown to be released locally at the site of joint inflammation. Clinically, expression of HMGB1 was found locally in SF and serum of patients with RA. The nature and function of S100 proteins, or calgranulins, in particular, S100A8/ A9 (calprotectin) and S100A12, have been described and illustrated in Vol. 1 [30], Sect. 12.2.4.2, pp. 229–230 and Sect. 14.2.2.4, pp. 310/311. The important pathogenetic role of the S100 protein family in RA has recently been reviewed by Wu et al. [377]. Indeed, S100A proteins have been demonstrated to be expressed in the synovial tissue of RA patients [378, 379], and their direct synovitis-inducing role has been documented in several RA models in mice. Interestingly, HSPs have also been identified as DAMPs involved in RA. However, as reviewed by Nefla et al. [375], these DAMPs seem to be associated with resolution rather than induction of inflammation (pointing again to HSPs operating context-dependently as SAMPs or DAMPs, compare Sect. 1.2.4.5). Extracellular Endogenous Histones, Nucleosomes, and Nucleic Acids Given the marked impact of NETosis on the pathogenesis of RA [333], it can be assumed that nuclear DAMPs are substantially involved in promoting synovial inflammatory responses. And indeed, there are already reports on this topic.
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Histones, for example, which are known for their ability to exert proinflammatory functions upon their release from the nucleus into the extracellular environment [380], have been demonstrated to be pathogenetically implicated in RA in form of epigenetically modified histones [366]. On the other hand, histones in their function as DAMPs reportedly interact with TLRs (TLR2/TLR4/TLR9) to trigger proinflammatory cytokine/chemokine release via MyD88, NF-κB, and NLRP3 inflammasome- dependent pathways [381]. Consistent with the notion that NETosis-derived NAs may also operate as nuclear DAMPs in RA, an increase in extracellular DNA in peripheral blood and SF has been demonstrated in both arthritis models and RA patients and observed to be associated with disease activity [382, 383]. Moreover, in studies on cell-free DNA isolated from the SF obtained from RA patients, dsDNA was found to induce joint inflammation in vivo [384]. More recent studies of the group revealed that cytosolic dsDNA-induced cGAS → STING activation could promote the in vitro migration and invasion of human RA FLSs [385]. In other lines of studies on samples obtained from joint replacement surgery, the presence of extracellular RNA (and RNase) within RA joints could be detected, localized in the synovial lining layer and in the intercellular synovial compartments of the lining layer [386]. In accompanying in vitro studies, the investigators could further show that this nuclear DAMP can be released by FLSs under hypoxic conditions. Extracellular Matrix Compounds and Molecules Acting as Altered-Self Antigens and Qualifying as DAMPs Besides the prominent DAMPs HMGB1, S100A proteins, and nuclear molecules, citrullinated tenascin-C (TNC) was also reported to act as a DAMP in RA [387, 388]. Tenascin-C was found in persistently high levels of expression occurring in the inflamed synovium of joints from RA patients. The TNC levels were found to correlate with disease markers in RA and to be expressed by myeloid cells. Similarly, PAD2-mediated citrullinated fibrinogen reportedly induces high proinflammatory mediators in FLSs via TLR4 ligation, qualifying this citrullinated protein as a DAMP as well [389]. It is worthwhile to mention in this context another citrullinated altered-self antigen in RA, that is, alpha-enolase. In its soluble form, this protein was also qualified as a DAMP able to activate monocytes by CD14- dependent TLR4 signaling pathway to trigger inflammation firstly, through the production of proinflammatory cytokines such as TNF and IL-1β, and chemokines, as well as then a delayed and extended anti-inflammatory effect, with IL-10 production [390]. Interestingly, in an analysis of human atherosclerotic lesions, vimentin—also known to function as an altered-self antigen in RA in its citrullinated form—was also identified as a DAMP to be sensed by the PRR Dectin-1 [391]. Another DAMP that has been identified to play a crucial role in the pathogenesis of RA is synovial galectin-3 (Gal-3) [392]. Acting as an inducible DAMP, Gal-3 was also recently shown to induce inflammatory fibroblast activation and osteoclastogenesis in patients with RA [393] (for galectins in their role as inducible DAMPs, see Vol. 1 [30], Sect. 14.2.6 and Fig. 14.3, pp. 319–321).
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The list of DAMPs implicated in the pathogenesis of RA should be closed by briefly touching LTF. Lactoferrin has been identified as an inducible DAMP that binds to TLR4 to trigger inflammatory pathways. In in vitro studies on FLSs, neutrophil-derived LTF was demonstrated to induce inflammatory responses of FLSs via TLR4 [394]. Moreover, in other lines of studies, a positive correlation between the prevalence of circulating anti-LTF/IgG autoantibodies and RA in humans was shown, thereby qualifying LTF/IgG ICs as another DAMP involved in the pathogenesis of RA [395]. Inducible DAMPs (TNF, IL-1β) The inducible DAMPs TNF and IL-1β have been detected in the serum and SF of RA patients and proposed to use as biomarkers [396]. Tumor necrosis factor is of great importance because it could be shown to induce necroptosis in synovial macrophages [329] and NETosis in RA neutrophils [397], thereby contributing to the release of various DAMPs in the synovium. Of equal importance is the detection of elevated IL-1β as this indicates the occurrence of pyroptosis as another critical source of DAMPs in the synovium.
7.3.5.4 SAMPs As already outlined in Sect. 1.2.4.3 and above in the context of SLE, the SAMPs represent key injury-induced molecules that counteract the action of activating DAMPs. As suppressing/inhibiting DAMPs, they can contribute to homeostatic healing processes in inflammatory diseases through their marked ability to drive inflammation-resolving responses. However, like SLE, RA is a chronic autoimmune disorder that is characterized by a failure of spontaneous resolution of inflammation. This suggests that the overall inflammation-resolving capacity of SAMPs is insufficient and impaired in RA. Nevertheless, spontaneous remissions in RA have been described and are not uncommon in patients who present with very early arthritis, some of whom may meet the criteria for RA over less than a few months [398]. This means that SAMPs, at least in part, may very well become active under certain operating conditions. However, this also implies that new insights into SAMP-driven inflammation-resolving pathways are clinically relevant in RA. In fact, there are already the first reports on SAMPs describing their antiinflammatory/inflammation-resolving properties in RA. Among those molecules, AnxA1 [399, 400], PGE2 [401–403], and, in particular, SPMs [404] are of major interest. Their distinct action as SAMPs in experimental arthritis models and patients with RA will be described in more detail below. 7.3.5.5 Concluding Remarks This section of DAMPs and SAMPs gives an inkling that this emerging topic is still in its infancy. Nevertheless, the research field about the pathogenetic role of these unique counterbalancing molecules in RA is currently growing: reason enough to resume this topic succinctly in the next section by focusing on some DAMP-/ SAMP-triggered pathways promoting or resolving synovial autoinflammatory processes.
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7.3.6 DAMPs Triggering Synovial Autoinflammatory Responses 7.3.6.1 General Remarks The spectrum of DAMPs discovered so far in RA animal models and patients suffering from this autoimmune disease is remarkable as of now and will certainly be extended in the future. On the other hand, various PRM-bearing cells of the innate immune system are pathogenetically involved in RA, including resident cells such as FLSs and chondrocytes, as well as mobile cells such as macrophages, neutrophils, and DCs. And it no longer takes much fantasy to imagine that the different cell types are activated by DAMPs to produce inflammatory mediator substances such as cytokines and chemokines and interact with T and B cells of the adaptive immune system. And in fact: there is now compelling evidence suggesting— although still not fully understood—that complex DAMP-promoted processes mediated by the various PRM-bearing innate immune cells, including APCs, are involved in joint inflammation and the formation of RA-specific autoantibodies. Depending on localization and distribution patterns of PRMs and their associated signaling pathways, various receptors appear to be critical in different stages of disease (for PRMs, see Sect. 4.3 and Vol. 1 [30], Chap. 5, pp. 43–94). The following is an attempt to outline this scenario using references from the literature as available to date. 7.3.6.2 Synovial Membrane Inflammation The documentation of synovial innate immune cells that are equipped with various PRRs is the prerequisite for DAMPs to orchestrate the scenario of joint inflammation. An array of soluble mediators is secreted by these cells that orchestrate the inflammatory processes characteristic of RA, the most relevant components being the inducible DAMPs TNF and Il-1β but also IL-6 and GM-CSF. Typically, TNF is the main cytokine involved in the inflammatory response of RA, whereas cartilage and bone destruction are mostly directed by IL-1 [303, 308]. Notably, convincing experimental and clinical evidence has been published pointing to a critical role of TLRs in contributing to the dysregulated inflammatory response observed in RA associated with ultimate cartilage and bone destruction. In particular, immunohistochemical and immunofluorescence analysis of synovial cells and tissue obtained from RA patients during surgery (at the time of joint replacement) documented expression of TLR2 and TLR4 as well as TLR3, TLR7, and TLR9 (for reviews, see [405, 406]). Numerous studies have shown and confirmed that the activation of a number of TLRs expressed on/in various intraarticular cells drives persistent inflammation in RA [407, 408]. And there is growing evidence indicating that this activation of TLRs is triggered by DAMPs which—as touched above—are emitted in the destructive environment of the RA joints. For example, HMGB1 has been proposed to promote synovitis by activating various intraarticular PRR (TLR4, RAGE)-bearing cells (for HMGB1- triggered signaling, cf. Fig. 4.3 and see Vol. 1 [30], Sect. 2.2.3.9 and Fig. 22.10, pp. 512/513). For example, HMGB1 was shown to stimulate macrophages derived from SF to release proinflammatory cytokines such as TNF, IL-1β, and IL-6 [409].
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Also, studies on HMGB1 in rodent RA models revealed interesting insights into the site of action of this DAMP. Thus, in investigations on a murine CIA model, aberrant HMGB1 expression was seen in areas of pannus lesions [410]. Another line of studies in rats using the same model showed similar findings [411]: cytoplasmic HMGB1 expression was observed in synoviocytes within the non-proliferative lining layer, whereby marked HMGB1 expression coincided with the progression of clinical disease. Additionally, the experiments revealed upregulation of HMGB1 mRNA to be restricted mainly to areas of cartilage and bone destruction. Given these and other findings not cited here, the authors concluded their data [411]: … these new findings implicate a role for HMGB1 in both inducing and perpetuating inflammatory events of significant importance in the destructive processes in chronic arthritis. Of note, these experimental findings are in line with clinical studies showing enhanced extracellular HMGB1 expression in both SF and synovial tissue, that is, clinical results that support a role for HMGB1 in the pathogenesis of RA (reviewed by Andersson et al. [412]). Similar to HMGB1, S100 proteins (S100A4, S100A8, s100A9, S100A11, S100A12, and S100B) have been found to be associated with inflammatory responses in RA [377]. Depending on the type of S100 DAMPs released from RCD or secreted by activated neutrophils or monocytes, TLR4- or RAGE-mediated innate immune pathways are triggered, resulting in secretion of inducible DAMPs such as TNF and IL-1β (and other cytokines such as IL-6), which in turn activate other innate immune cells to create a vitious circle of synovial inflammation (for TLR4- triggered signaling, see Fig. 4.3, and for RAGE-triggered signaling, see Vol. 1 [30], Sect. 2.2.3.9 and Fig. 22.10, pp. 512/513; for inducible DAMPs, see Vol. 2 [34], Sect. 3.5.3 and Fig. 3.4, pp. 82/83). Moreover, supportive evidence comes from studies showing that some other DAMPs that are not as in the spotlight as HMGB1, such as TNC, enhance spontaneous cytokine synthesis upon addition to human RA cell populations, as well as being essential for the progression of disease in murine models of RA [406]. DAMPs Activating the NLRP3 Inflammasome In exploring the role of DAMPs in synovial inflammation, one must imperatively look for a possible contribution of DAMP-promoted activation of inflammasomes. And indeed, compelling evidence has accumulated in recent years that the NLRP3 inflammasome plays a critical role in the pathogenesis of RA. Among various findings, NLRP3 inflammasome has been demonstrated to be highly activated in synovial tissues and peripheral blood mononuclear cells from RA patients. As operating DAMPs, numerous DAMPs released from cells succumbing to NETosis or necroptosis may be discussed (for recent reviews, see [413, 414]; for NLRP3 inflammasome, compare Sect. 3.7.5 and Fig. 3.9, also see Vol. 1 [30], Sect. 19.3.4, Fig. 19.7, pp. 447–449, and Sect. 22.4.2, Fig. 22.11, pp. 515–520). Typically, as in other inflammatory conditions, the NLRP3 inflammasome itself serves as another source for the emission of additional DAMPs and the production of IL-1β via the induction of pyroptotic cell death.
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7.3.6.3 Synovial Tissue Proliferation (Pannus) and Destructive Joint Inflammation As mentioned, a hallmark of RA refers to pannus formation in terms of synovial tissue proliferation which has been considered a late and irreversible manifestation of RA. At the pannus-cartilage intersection of the rheumatoid joint, activated PRR- bearing FLSs produce matrix metalloproteinases (MMPs) and other enzymes (cathepsins and collagenases), which are released into the SF, enable their invasion and cause cartilage destruction. Another vital function of FLS (similar to T lymphocytes) refers to the promotion of osteoclastogenesis, that is, activation of PRR- bearing osteoclasts as specialized bone-absorbing cells, which is also involved in joint destruction. Mechanistically, (DAMP?)-activated TLR-bearing FLSs secrete the cytokine RANKL and GM-CSF to induce osteoclast differentiation (for more in-depth information, see reviews of Nygaard and Firestein [322], Masoumi et al. [323] and Mousavi et al. [324]). With this respect, RANKL and GM-CSF may be regarded as inducible DAMPs (Table 1.2). Thus, it is the TLR-bearing FLSs that are responsible for these severe lesions leading to progressive disability in patients. And it should be emphasized here that the FLSs were conceptually proposed to be activated by DAMPs [405, 415, 416]. The concept is supported, for example, by studies on FLSs suggesting that HMGB1 may stimulate migration and invasiveness of FLSs via interaction with the RAGE receptor [417, 418]. Given the documented function of HMGB1 to promote tissue repair and regeneration [419], its involvement in pannus formation can be fairly safely assumed. In this context, Andersson et al. [412]argued: This aberrant HMGB1 expression has been reported to be particularly evident in the pannus tissue representing the aggressive and destructive synovitis at the cartilage–bone interface. Similar to HMGB1, S100 proteins have been found to be associated with proliferative responses in RA [377]. Moreover, S100A8/S100A9 DAMPs have been shown to contribute to bone erosion in this disease. Thus, as reviewed by Di Ceglie et al. [420], mechanistically, these DAMPs can promote a shift toward the expression of activating FcγRs on innate immune cells, osteoclast precursors, and mature osteoclasts, thereby rendering them more sensitive to IC stimulation. This scenario qualifies both ICs and S100A8/A9 and ICs as key inducers of bone erosion in RA, indirectly—as concluded by the authors—via the stimulation of immune cells and via the direct stimulation of osteoclast differentiation and function. Another DAMP shown to contribute to joint destruction in RA is Gal-3. Interestingly, in recent clinical studies on patients with RA, Nielsen et al. [393] could demonstrate that patients with early and chronic RA had persistently increased plasma levels of Gal-3 compared with controls. In patients with chronic RA, Gal-3 levels in SF were markedly elevated. Moreover, changes in plasma Gal-3 at the level of individuals were observed to be associated with long-term disease activity. In seropositive early RA patients, a decrease in plasma Gal-3 during the first 3 months of treatment selectively correlated with favorable treatment response after 2 years. In parallel in vitro experiments with a Gal-3 inhibitor, the researchers could show that this inducible DAMP may promote the secretion of TNF and IL-1β by FLSs and increase monocyte-derived osteoclastogenesis, underscoring the role this molecule regarding disease activity and tissue destruction in RA. From their findings,
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the investigators concluded [393]: Our findings underscore the role of Gal-3 regarding disease activity and tissue destruction in seropositive RA… Collectively, these findings provide mechanistic insights into the role of Gal-3 regarding the functions of inflammatory FLSs and osteoclasts in RA.
7.3.6.4 Concluding Remarks The scenario of a role for DAMPs in triggering synovial autoinflammatory responses is certainly incomplete and not fully understood. However, given the current intensive research in the field of RA, further progress can be expected soon. Also, it can be speculated that further insights into a potential DAMP-driven positive feed- forward loop of innate immune responses will be involved in this ongoing synovial inflammation (see below Sect. 7.3.11: the design of a tentative conceptual model of this loop).
7.3.7 Evidence for SAMPs to Drive Synovial Inflammation-Resolving Responses The model of SAMP-driven resolution of inflammation was introduced in Sect. 4.4.4. In RA, inflammation-resolving processes are suppressed and impaired [421], although periods of remission have been observed in certain circumstances [422], and the contribution of SAMPs to this clinical picture has been reported, as touched on above. Here, some further details should be added. Thus, AnxA1, for example, in studies on a rat AIA model, was shown to inhibit synovial inflammation [399]. In a clinical study, a significant decrease in the level of AnxA1 was noticed in RA patients compared to healthy controls, wherein remission cases of serum AnxA1 were significantly high [400]. Also, the SAMP PGE2 that may context-dependently also exert proinflammatory effects was shown to play a beneficial role in the pathogenesis of RA [401]. In studies on a murine CIA model, this molecule was observed to restore the resolution of inflammation by mediating LXA4 production [402]. In other lines of cell culture experiments, PGE2 was found to attenuate cytokine-induced inflammatory responses in FLSs via regulation of the localization of specific NF-κB family dimers [403]. At present, studies on the inflammation-resolving role of SPMs in RA have attracted great attention, especially since experiments in RA models, including the murine self-resolving arthritis model, have convincingly demonstrated endogenous SPMs and their pathways to be able to protectively modulate inflammatory arthritis [423–425]. New insights into the resolution-promoting properties of SPMs in RA stem from findings of several clinical studies that have provided compelling evidence that there is a stringent association between arthritis disease status and SPMs levels [424, 426–429]. For example, compared with controls, plasma levels of MaR1 were shown to be higher in patients with inactive RA and lower in patients with active RA. Also, the intervention of this SPM in the CIA model was found to reduce joint inflammation and damage and improve the imbalanced Th17/Treg ratio [427] (for Th17/Treg imbalance, also see Sect. 7.3.9.2 below). Other lines of studies
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in RA patients revealed similar findings in that the RvD1 levels were found to be decreased in the serum of RA patients and inversely correlated with the connective tissue growth factor (CTGF) [429]. This factor, known to be elevated in RA patients, contributes to disease progression by promoting FLS proliferation, pannus formation, and cartilage, as well as bone damage. In in vitro experiments conducted in parallel [429], the authors further demonstrated that RvD1 could inhibit angiogenesis. Moreover, they demonstrated that RvD1 could inhibit pannus formation and decrease the levels of proinflammation cytokines and CTGF in CIA mice. Overall, there is remarkable progress in the field of SAMP-driven inflammation- resolving responses in RA. Consistent with new notions about the efficacy of SAMPs to resolve inflammation, pre-clinical and clinical evidence is growing, indicating that these molecules, counterbalancing the proinflammatory action of DAMPs, are also active, or better said, inactive, in RA. Indeed, the observations are striking that arthritis onset, symptoms development, and its resolution correspond well with fluctuations in SAMP levels, such that low levels correlate with disease severity. Accordingly, as with DAMPs, their clinical use as biomarkers in monitoring the disease and therapeutic options in curing the disease has already begun, a topic that will be addressed below.
7.3.8 DAMPs Promoting Maturation of Antigen-Presenting Cells 7.3.8.1 General Remarks In principle, DCs, FDCs, FLSs, and B cells have been shown to function as APCs in RA, whereby DCs operate as professional APCs. And again: according to the danger/injury model, the development of autoimmune diseases depends not only on the action of an autoantigen but requires DAMP-induced costimulation to activate (auto)immunostimulatory DCs, which interact with naïve autoreactive T cells. This interaction results in subsequent differentiation of naïve autoantigen-specific CD4+ T cells (including Tfh cells) to effector CD4+ Th cells, cross-priming of CD8+ T cells, promotion of B cell-mediated autoantibody responses, and generation of adaptive immunological memory. This dogma also applies to autoimmune T and B cell responses involved in the pathogenesis of RA. However, although experimental and clinical studies provide compelling evidence for the implication of DCs in triggering adaptive autoimmune processes in the pathogenesis of RA, relatively little is known about the mechanisms of their maturation to immunostimulatory professional APCs. Accordingly, most current notions derive from experimental arthritis mouse models. In the following, a few points are addressed, guided by recently published articles by Yu and Langridge [430] and Wehr et al. [431]. 7.3.8.2 Synovial Dendritic Cells as Antigen-Presenting Cells In RA patients, DCs, including cDCs and pDCs, infiltrate the joint SF and tissues and account for 5–7% of SF mononuclear cells. Studies on the CIA model have revealed that of the various subsets of these cells, cDC1 operates as the main subset
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in orchestrating the initiation of cell-mediated immunity in arthritis [432, 433] (for DC subsets, also see Vol. 1 [30], Sect. 8.3.3, pp. 130–134). There are a number of excellent studies that have firmly elucidated the presentation of autoantigens by DCs, including PTM-modified altered-self peptides. Also, there is evidence that synovial DCs are generally mature, indicating that they exert immunostimulatory properties. On the other hand, the DC maturation process is less clear. Nevertheless, there are already clues for their activation in vitro and in vivo, such as upregulation of MHC-II and costimulatory molecules (CD40, CD80, CD86) as well as increased production of T cell-polarizing cytokines (e.g., IL-12, IL-6) (described in [430, 431, 433, 434]). This data is supported by other lines of studies using the CIA model, showing that CIA-derived NETs are capable of directly activating DCs, as documented by the induction of costimulatory molecules and proinflammatory cytokine [435]. These observations give rise to the as-yet unproven possibility that synovial DCs in RA are activated by DAMPs, including nuclear DAMPs (or DAMPs and MAMPs in case of infections). Activation of Synovial Dendritic Cells There is the first experimental evidence suggesting a crucial role of matured immunostimulatory DCs in initiating an adaptive T cell autoimmune response in RA. Thus, in experiments on the model of AIA, DC ↔ T cell interactions were imaged in the joint [436]. Intriguingly, these studies demonstrated stable interactions between DCs and endogenous CD4+ T cells in the inflamed joint consistent with the recognition of specific antigens. In addition, as shown in the experiments already mentioned, CIA-derived NETs are capable of directly activating DCs that, in turn, promote induction and expansion of Th1 pathogenic cells [435]. Also to note are reports that synovial DCs secrete T cell-polarizing cytokines known to induce CD4+ T cell differentiation into activated Th1 (e.g., IL-12) and Th17 (e.g., IL-6) cells, that is, T cells which are crucial players in RA pathogenesis (reviewed in [431]; for DC-secreted T cell polarizing cytokines and CD4+ Th cell differentiation, see below). Last but not least, it should not remain unmentioned that synovial DCs from patients with RA were found to show a defective capability to induce the generation of Foxp3+ Tregs in the periphery [437]. The authors concluded that this aberrant function of RA DCs may have an important role in the pathogenesis of this condition (for extrathymic generation of Foxp3+ Tregs at peripheral sites, see Vol. 1 [30], Sect. 33.4.2.2., p. 810).
7.3.8.3 Fibroblast-Like Synoviocytes and B Cells as Nonprofessional Antigen-Presenting Cells Besides the professional APCs, the DCs, FDCs, and B cells have also been identified to present antigens to naïve CD4+ T cells. For example, FLSs exposed to NETs were found to acquire APC capabilities when they internalize NET-associated citrullinated peptides and present them to antigen-specific CD4+ T cells [438, 439]. In view of the danger/injury model, it can be assumed that mandatory costimulation is provided by NET-associated nuclear DAMPs.
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Also, in addition to their traditional role in producing autoantibodies, B cells have been identified to act as APCs as well (reviewed in [199]). For example, as demonstrated in studies on human B cell subsets, a B cell subset with a peculiar range of surface markers was identified in RA patients that were able to strongly stimulate T lymphocytes [440]. As will be outlined in more detail in Sect. 7.3.10.2. below, B cells, as APCs, mainly present their own cognate antigens to CD4+ Tfh cells.
7.3.8.4 Concluding Remarks Together, several types of APC have been detected in RA and are supposed to be activated by DAMPs. However, as mentioned in the introduction, little is known about the mechanisms of upregulation of costimulatory molecules during the maturation process involved in the pathogenesis of RA. With the growing interest in the costimulation-driving function of DAMPs in ADs, further progress in this research field can be expected.
7.3.9 The Autoreactive T Cell Response 7.3.9.1 General Remarks Adaptive autoimmune pathways play a central role in the pathogenesis of RA. Clinical detection of circulating autoantibodies and investigations on B cells infiltrating the synovium and other typical immune features provide evidence of this. It is beyond the scope of this section to describe the autoreactive T and B cell responses in RA in full detail. Instead, only some aspects that seem to be relevant in a chapter mainly dedicated to the role of DAMPs in this disease will be addressed. We will begin with a short description of T cells whose pathogenetic role is obviously less relevant compared to B cells. 7.3.9.2 T Cell Pathobiology The critical role of T cells in the pathogenesis of RA has been well appreciated. In fact, CD4+ T cells comprise a considerable proportion of the inflammatory cells invading the synovial tissue. Under DC-elicited autoantigen stimulation (signal 1), DAMP-mediated costimulation (signal 2), and T cell-polarizing cytokine (signal 3), they differentiate, determined by the expression of specific transcription factors in response to these cytokines, into various subsets (Th1-, Th2-, Th17-, Tfh-, Treg cells; compare Vol. 1 [30], Sect. 32.4, Figs. 32.4, and 32.5 pp. 765–772; and Sect. 33.3.2, Fig. 33.3, pp. 799–802). The pivotal role of CD4+ T cells in RA and experimentally induced arthritis with respect to their transcriptionally regulated differentiation has recently been reviewed by Kondo et al. [441]. In brief: Historically, Th1 cells, characterized by T-bet as a master transcription factor, have been regarded to play an important role in inflammatory RA because most synovium-infiltrating CD4+ T cells secret IFN-γ and TNF. However, more recently performed studies suggest that this T cell subset does not explain all of the mechanisms encountered during the various stages of the
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disease. In contrast to Th1 cells, IL-17-producing CD4+ T cells, characterized by RORγt as a master transcription factor, are considered to be more important in RA and experimental RA models. Supportive evidence for the pathogenic effects of Th17 cells in RA has been provided by recent studies showing (1) the association of IL-17 and intraarticular IgA secretion, (2) the capability of Th17 cells to promote specific B lymphocyte clones to secret autoantibodies in the preclinical RA phase, (3) the vital role of IL-21 in orchestrating bone damage together with TNF, and (4) the IL-17-induced mitochondrial dysfunction in FLSs (reviewed by Calabresi et al. [309]). The role of Th2 T cells, characterized by GATA3 as a master transcription factor, has been less investigated in RA and RA animal models. According to current knowledge, this T cell subset appears to exert more protective functions in RA by operating antagonistically to Th1 and Th17 cells. Follicular helper T cells, which have already been discussed above in the context of SLE, are also involved in RA pathogenesis (cf. Fig. 7.3a–c). Indeed, evidence has been provided suggesting a critical role of Tfh cells in B cell help because of several findings: besides others, the large number of Tfh cells in the synovial tissue of RA patients and the increased frequency of circulating Tfh-like cells (cTfh-like cells) among peripheral blood mononuclear cells (reviewed in [442]). The function and role of Tregs in RA are not quite clear. Indeed, as recently reviewed by Jiang et al. [443], many studies have reported contradictory results. The number of Treg cells in the peripheral blood of patients with RA has been reported to be either increased, unchanged, or decreased. Notably, contradictory results were also published for the functional characteristics of Tregs from RA patients, namely enhancement or attenuation. Overall, the suppressive function of Tregs may be impaired by the inflammatory conditions occurring in RA (the topic is not further pursued here, for an extensive description of Tregs in inducing peripheral tolerance, see Vol. 1 [30], Sect. 33.4, pp. 809–818). Of note, an imbalance of immunosuppressive Tregs and proinflammatory Th17 cells in multi-staging RA has been demonstrated to play a role in RA pathogenesis. Interestingly, as shown in recent studies on RA patients, aberrant DNA methylation patterns may contribute to this observation [444]. Collectively, emerging data have revealed that Th17 cells, but less Th1 cells, are of the most critical T cell subsets during the disease course, whereby an imbalance between Th17 cells and Tregs commitment seems to contribute to inflammatory/ autoimmune processes. Nevertheless, the precise role of CD4+ T cell subsets and their secreting cytokines in RA remains unclear.
7.3.10 The Autoreactive B Cell Response 7.3.10.1 General Remark One of the hallmarks of RA is the presence of B cell-derived ACPA and RF autoantibodies which defines the seropositive subset of the disease [300]. As outlined in Vol. 1 [30], Sect. 32.6, pp. 775–780, antibodies are produced by rare populations of terminally differentiated B cells, known as plasmablasts and plasma cells, the
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formation of which—compared with their B cell precursors—is associated with marked alterations in the morphology, gene expression profile, and lifespan of the differentiated ASCs. The pathogenetic mechanisms of B cells in seropositive RA have recently been comprehensively reviewed by Wu et al. [445]. Using this article as a guide, some key aspects will be presented in a condensed form in the following.
7.3.10.2 The Pathogenetic Role of B Cell in the Synovium In RA patients, B cells are preferentially located in the synovial tissue that can be regarded as TLOs, also known as tertiary lymphoid tissues (TLT) or ectopic lymphoid structures (ELSs). These structures are similar to SLOs, with (1) segregation of T cells and B cells into separate areas (T cell zone, B cell follicles); (2) differentiation of networks of FDCs that are capable of retaining intact antigen for extended periods by trapping ICs, thereby protecting the antigen from degradation; and (3) differentiation of hypermutated and class-switched autoantibody-producing plasma blasts and long-lived plasma cells. (Note, the TLOs can also be found at extraarticular sites, including the lung and bone marrow.) The TLTs are correlated with autoantibody titers, inflammatory cytokine levels (such as IL-23 and IL-17), and disease severity in RA patients (although conflicting results have been published; for more in-depth information, see Bombardieri et al. [446]). According to currently published evidence, activation of the molecular machinery required for synovial B cells to undergo immunoglobulin SHM, CSR, and development into autoantibody-producing plasmablasts and long-lived memory B cells in RA TLOs is similar to the conceptual scenario described above in Sect. 7.2.7.5 for SLE (in general outlined in Vol. 1 [30], Sect. 32.4.5, Fig. 32.5, Box 32.1, pp. 769/770, and Sect. 32.6, Fig. 32.7, pp. 775–780). Given the evidence for DC maturation in RA as described and repeating some points touched on above, a tentative scenario model can be outlined that is similar to that developed for B cell pathobiology in SLE (cf. Fig. 7.3a–c): Interaction of cDC ↔ Tfh ↔ B cell ↔ FDC in Synovial B Cell Activation DAMP-activated mature synovial APCs, e.g., cDCs or FLSs, interact with CD4+ T cells in the T cell zone of RA TLOs, leading to activation of Tfh cells, which migrate to B cell follicles. There, via secretion of cytokines such as IL-21 and expression of CD40L, they provide cognate antigen-specific additional help for activation, proliferation, and differentiation of B cells, which, at first, have captured autoantigenic peptides (e.g., citrullinated peptides) via the BCR to present—in their role as APCs—the processed peptide on MHC-II molecules to Tfh cells. Also, besides providing help in B cell activation, Tfh cells are committed to controlling B cell isotype CSR, whereby activation-induced cytidine deaminase plays a major role (for further reading, see [445, 446]). Of note, besides help from Tfh cells, B cells require further assistance from FDCs, which have already been addressed with respect to their role in SLE. This special subset of APCs is rare stroma-derived, enigmatic cells whose role in contributing to B cell activation in RA, as in SLE, has not been thoroughly explored so far, particularly with regard to putative activation by DAMPs.
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The FDCs present autoantigens in the form of ICs to B cells, whereby they are bound to CR1, CR2, and/or FcγRIIB. This interaction of B cells with FDCs promotes their activation and affinity maturation during the GC reaction. Moreover, FDCs are equipped with many TLRs, including TLR2, TLR4, and TLR7, enabling them principally, like cDCs and pDCs, to respond to DAMPs. Although FDCs were found to sense RNA during autoreactive responses and produce type I IFN in response, whether similar interactions also contribute to the upregulation of costimulation in RA has not been investigated so far. Hence, while MAMPs such as LPS, which acts as an exogenous DAMP, have been shown to activate FDCs, no endogenous DAMPs have been studied in this function to date. Nevertheless, given the growing evidence that DAMPs are pathogenetically involved in RA, it is to be supposed that they also interact with TLRs on FDCs (for further information, see [197, 209–211, 447, 448]). Overall, evidence is growing in support of the concept that FDCs have the machinery to contribute to B cell activation and regulation of the GC in RA. However, further studies are needed to clarify the underlying mechanisms, in particular, the mode and action of DAMPs in activating FDCs and, in turn, FDC-triggered activation of B cells.
7.3.10.3 Autoantibodies in Seropositive Rheumatoid Arthritis The most prominent RA-specific autoantibodies are RF and ACPA, but others such as anti-carbamylated protein antibodies, anti-acetylated protein antibodies, anti- MDA, and anti-malondialdehyde-acetaldehyde (MAA) antibodies contribute to RA pathogenesis. (Interestingly, MDA and MAA are highly immunogenic because they act as both (auto)antigens and (IIB-1) DAMPs in their function as OSEs; see Table 1.1; also compare Vol. 1 [30], Sect. 13.3.2 and Fig. 13.1, pp. 277–282.) Here, only ACPA and RF will be briefly described (for in-depth information, see the reviews of England et al. [449] and Volkov et al. [450]). Anti-Citrullinated Protein Antibodies Anti-citrullinated protein antibodies are directed against citrulline residues on proteins or peptides. As mentioned in Sect. 7.3.4.4, citrullination (or deimination) is an irreversible PTM of arginine mediated by PADs (e.g., PAD4). As reviewed [449, 450], ACPAs can be detected in about 50–60% of early RA patients and 60–90% of patients with established disease. Of note, on the one hand, autoantibodies can be found in asymptomatic patients in advance of RA outbreak and do not necessarily lead to RA development. On the other hand, ACPAs are a typical feature of seropositive RA, which is associated with higher disease severity and the occurrence of extraarticular manifestations such as cardiovascular and pulmonary disorders. The robust proinflammatory effects of ACPAs and ACPA ICs are reportedly due to their ability to directly activate innate immune cells such as neutrophils, macrophages, mast cells, and osteoclasts. Also, direct binding of ACPAs to osteoclasts was shown to result in osteoclastogenesis [449, 451], whereby recent evidence suggests that interaction with FcγRI may be required for RANKL-induced proinflammatory osteoclastogenesis [452]. Of interest in this context is that there is evidence
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suggesting that TLR-expressing osteoclasts can also be activated by the DAMP HMGB1 [453]. On the other hand, osteoclastogenesis, when regarded as a consecution of osteocyte death, is reportedly associated with the emission of DAMPs [454]. Origin and Role of ACPAs As a result of Tfh ↔ B cell ↔ FDC interaction, ACPAs are produced within or directly in the synovium years before the onset of RA, making the synovial microenvironment in RA uniquely qualified to support ongoing ACPA production. Even earlier, however, the question arose as to whether the synovium is the only site where ACPAs are formed. Indeed, identifying where and when citrullination of antigenic proteins occurs and ACPAs are produced is critical to clarifying the early events resulting in RA. Thus, the fact that ACPAs are present in the circulation of asymptomatic patients years before the onset of symptoms [455] has lent support to the concept that autoantibody production does not only take place in the synovial TLOs but can also originate at extraarticular sites. Supported by compelling studies documenting the association between cigarette smoking and RA risk (e.g., [456]), increasing attention has focused on the mucosal surfaces of the lungs as a possible site of early ACPA production [457]. Further support for this concept was provided by studies on seropositive RA patients demonstrating enrichment of ACPAs in bronchoalveolar fluid as signs of local autoantibody production [457]. Additional confirmation of the correctness of the concept that the lungs can serve as the initiating site of ACPA production is based on studies demonstrating that IgA antibodies against citrullinated peptides are produced at mucosal surfaces of airways, and both circulatory and secretory IgA ACPAs in early RA are associated with smoking [458, 459]. The model is of even greater importance because smoking has been shown to induce NETosis that serves, as mentioned above [334, 335], as the production of both citrullinated autoantigens and DAMPs. Aberrant Glycosylation of ACPAs Another interesting observation regarding ACPAs is that they have a larger molecular weight as compared to most antibodies due to the fact that they carry N-linked glycans in their variable domains. Thus, circulating and SF ACPA-IgG have been found to be extensively N-glycosylated in their Fc domain [449, 450]. Of note, as already mentioned earlier in Sects. 4.6.7.4 and 6.2.4.2 the effector functions of IgG antibodies rely on a given Fc glycosylation as one of the most common PTMs in mammalian cells that significantly modify their affinity for FcγRs. Several structural modifications in these Fc domains resulting in variable functions have been described: mannosylation, core fucosylation, galactosylation, bisecting GlcNAcylation, or sialylation [460–462]. Notably, these modifications in the Fc portion of IgG autoantibodies were observed to also alter FcγR signaling and proinflammatory cytokine release in RA. For example, low galactosylation (i.e., agalactosylated IgG antibodies) and low sialylation are generally thought to promote proinflammatory processes. Consistent with these findings are reports showing that low galactosylation in RA is observed some time prior to the onset of arthritis symptoms skewing toward more
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inflammation and that it correlates with duration, relapses, and progression of the disease. Similar results were found regarding decreased IgG sialylation. In support of these findings is a recent clinical study showing that both galactosylation and sialylation levels of ACPA-IgG negatively correlate with inflammation-related clinical parameters such as CRP, ESR, and RF [463] (for more detailed information, see [464–467]). Of interest in this context are experimental studies in mice on random IgG and specific IgG autoantibodies showing that low- or non-sialylated ICs drive inflammatory osteoclastogenesis in vitro as well as in vivo [468]. In parallel clinical studies on RA patients, the investigators found that individuals exhibiting IgG with low-sialylated or low-galactosylated Fc domains displayed a significantly decreased bone volume compared with patients with high levels of IgG Fc sialylation or galactosylation. Similar results were obtained for disease-specific ACPA. In accordance with these findings were experimental studies of the group, demonstrating that mice with increased sialylated IgG are less susceptible to inflammatory bone loss [468]. On the other hand, it has been shown that ACPA-IgG1-Fc fucosylation increases immediately after the onset of RA, reflecting a proinflammatory phenotype, in contrast to the proinflammatory activity of decreased galactosylation and sialylation levels [467]. This observation is in stark contrast to the function of antiviral antibodies in viral infections, including COVID-19, where decreased fucosylation IgG Fc has been observed to promote inflammation (described in Sect. 4.6.7.4). Continuous Induction of Net Formation and NETosis by Autoantibodies-ICs As outlined above, environmental factors are thought to promote NETosis by instigating the pre-RA phase. But this does not explain why induction of NET formation and NETosis reportedly also play a critical role in perpetuating a variety of autoimmune diseases, including RA [35, 36]. Indeed, this event has to occur in order for the disease to progress: namely, ongoing production of ACPAs in the synovium requires, after their initial generation, a regenerating supply of autoantigens and costimulation-providing DAMPs. And it could well be these NETosis-derived ACPAs/ACPAICs, originating from extraarticular sites and traveling through the circulation to the synovium—and/or ACPAs and ACPA-ICs produced locally in the synovium—which might provide this supply via induction of NETosis of synovial neutrophils (Fig. 7.6). And indeed, there is some early evidence suggesting that this is the case: Typically, for example, circulating NETs and netting neutrophils in joints are found in patients with RA, demonstrating productive and widespread NETosis. Also, in vitro studies on neutrophils from RA patients have revealed that RA SF and peripheral blood neutrophils display an enhanced capacity to form NETs. In fact, evidence is accumulating suggesting that ACPAs as autoantibodies can also induce NETs in the synovium and SF (Fig. 7.6) (for further information, see [332, 333, 397, 469, 470]). Mechanistically, as already discussed and illustrated earlier (Sect. 6.2.4.3 and Fig. 6.4) and also outlined above for SLE, autoantibodies-ICs are suggested to enhance NET formation in an FcγR-depending manner (reviewed in [268, 471]). Preliminary evidence in support of this concept was provided, showing that ACPA/IgG-ICs can bind to FcγRI on activated RA neutrophils [472] and RF/IgA-ICs contribute to NET release that is dependent on FcαRI [473].
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Fig. 7.6 Simplified diagram of a conceptual model illustrating the role of DAMPs in activating various RA synovial cells involved in autoinflammatory, tissue-proliferating (i.e., pannus formation), and destructive processes. ACPA-IC-induced NETosis—in the synovium or the synovial fluid—serves as the source of DAMPs. Note that the arrows are to symbolize the DAMP-promoted migration and invasion function of fibroblast-like synoviocytes. ACPA anti-citrullinated protein antibodies, Cartil cartilage, FLSs fibroblast-like synoviocytes, ICs immune complexes, Inflamm inflammatory, MØ macrophage, PRRs pattern recognition molecules, RA rheumatoid arthritis, SF synovial fluid. (Sources: [268, 332, 333, 397, 469–471])
Rheumatoid Factor The RF, defined as a class of Igs directed against the Fc region of IgG, is the most well-known and most-studied autoantibody in RA. The estimation of RF is routinely used in clinical settings to differentiate RA from other diseases with similar symptoms. Several isotypes of RF have been described to play a role in the disease, of which IgM is the most abundant. Interestingly, similar to ACPA, targeted studies on the serum of RA patients provided evidence suggesting that total IgG shows significantly lower galactosylation, lower sialylation, and higher fucosylation levels compared with healthy controls [474]. Although the role of RF in RA pathogenesis is still elusive, its pathogenic properties are supposed to be mediated via IC formation [450]. This notion lets us think of the unproven possibility that RF, like ACPAs, may be involved in the induction of NETosis as a source of autoantigen and DAMPs (as discussed in the next section). Overall, as concluded by Volkov et al. [450], the exact role of RF in RA development appears to be enigmatic, and its presence in other diseases highlights RF as a rather general autoimmunity-related phenomenon. Despite this, RF remains a useful diagnostic marker of RA used in daily clinical practice. Complement Activation The complement system as a crucial defense system against pathogens has been briefly outlined in Sect. 4.4.3.4. The defense system is a considerably complex
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fluid-phase and membrane-bound system of proteins—that is activated upon recognition of “activators” in terms of MAMPs expressed on invading pathogens, as well as DAMPs either associated with ICs or emitted by damaged/dying cells in the extracellular environment. Activation of the complement system is instigated via three major convergent pathways, the classical pathway, the lectin pathway, and the alternative pathway, each leading to a common terminal pathway, that is, activation of the central C3 and C5 convertases and final formation of the terminal C5b-9 complement complex (MAC) (for detailed information about the complement system and its co-players, see Vol. 1 [30], Sect. 23.2 and Fig. 23.1, pp. 591–614). The role of complement in the initiation and evolution of RA has recently been reviewed by Holers and Banda [475] and Dijkstra et al. [476]. In brief: Several studies in animal models of arthritis, such as the CAIA model, revealed that each of the three major complement activation pathways apparently plays a crucial role in the recognition of injured joint tissue but that the alternative pathway is markedly essential for disease development. Typically, as with other ICs, the autoantigen/ autoantibody complexes present in RA patients are supposed to activate complement, which may promote chronic destruction of the joint, for example, via the initiation of innate and adaptive immune responses. Indeed, serum ACPAs were already found to recruit both the classical and alternative complement pathways in vitro, and serum ACPA titers were shown to correlate with complement activation in ACPA-positive patients [477].
7.3.10.4 Concluding Remarks Research on the complex processes of the autoreactive B cell response in RA is growing. Thus, circulating ACPAs were found to appear prior to the clinical onset of RA, with aberrant glycosylation changes of autoantibodies occurring near clinical onset. Importantly, the growing evidence for ACPA/ICs to induce NET formation and NETosis of synovial FcR-expressing neutrophils as sources for altered (e.g., citrullinated)-self antigens and costimulation-providing DAMPs may explain the continuous activation of synovial innate immune cells such as FLSs, neutrophils, and macrophages to mount synovial acute/chronic inflammatory and hyperplastic responses leading to pannus formation and RANKL-mediated osteoclastogenesis (Fig. 7.6). Moreover, these trajectories may also provide a plausible explanation for the scenario of ongoing autoimmune processes as typical for this disease.
7.3.11 Summarizing Hypothetical Model to Rheumatoid Arthritis Pathogenesis: The DAMP-Driven Positive Feed-Forward Loop of Innate/Adaptive Autoimmune Responses Based on what has been briefly described in this section about the origin, nature, and role of ACPAs in RA (again compare [268, 334, 335, 397, 464–467, 472, 473, 478]), a DAMP-centric model for the pathogenesis of RA in genetically susceptible patients can be tentatively proposed as grounded in the danger/injury theory
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Fig. 7.7 Tentatively designed hypothetical model of the pathogenetic role of a DAMP-triggered positive feed-forward loop in seropositive rheumatoid arthritis. Environmental factors interacting with susceptibility genes operate as initial inducers of RCD at extraarticular sites such as the lungs. The programmed cell death serves as a source of both citrullinated autoantigens and costimulation- providing DAMPs that activate APCs to mount an autoreactive T cell → B cell autoimmune response, leading production of ACPAs/ACPA-ICs. After release into the circulation, ACPA/ICs shift speculatively to low galactosylation and sialylation but increased fucosylation of IgG Fc domain in the autoantibodies, which allows them—after having reached the joints—higher affinity binding to FcγRs on synovial neutrophils, thereby causing NETosis, associated with the release of citrullinated autoantigens and DAMPs. Via a vitious circle, DAMPs may induce further subroutines of RCD (for details of this circle, see Fig. 6.4). The positive feedback loop progresses with citrullinated autoantigen/DAMP-triggered activation of synovial APCs that drive an autoimmune response associated with the production of ACPA-containing ICs, which enter the loop to cause NETosis again. In addition, DAMPs activate synovial effector cells that convey chronic perpetuating autoinflammatory, proliferating, and destructive synovial processes (cf. Fig. 7.6). ACPA anti- citrullinated protein antibodies, APCs antigen-presenting cells, citPeptides citrullinated peptides, DCs dendritic cells, FcR Fc receptor, FLSs fibroblast-like synoviocytes, MØ macrophage, PMNs polymorphonuclear neutrophils, RA rheumatoid arthritis, RCD regulated cell death, SF synovial fluid. (Sources: [268, 334, 335, 397, 464, 465, 467, 472, 473, 478–486])
(Fig. 7.7): Environmental factors such as smoking, interacting with susceptibility genes, operate as initial inducers of RCD (especially NETosis) at extraarticular sites such as the lungs. The programmed cell death serves as a source of both citrullinated autoantigens (i.e., altered-self proteins) and costimulation-providing DAMPs that activate APCs/MHC-II (e.g., from HLA-DRB1) to mount an autoreactive T cell → B cell autoimmune response. Finally, differentiated plasmablasts and plasma cells produce extraarticular ACPAs. Once produced extraarticularly, ACPAs, ACPA/ ICs are released into the circulation and reach the joints where they interact with shared citrullinated proteins/peptides in the synovium. Accumulated there, ACPAs— preferentially as ACPA/IgG- and RF IgA-ICs—bind to FcγRs and FcαRI on synovial FcR-expressing neutrophils to induce NETosis, which again is associated with
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generation of citrullinated peptides and release of DAMPs within the synovium. The fact that ACPAs/ACPA/ICs are present in the circulation of asymptomatic patients years before the onset of symptoms might be due to the unproven possibility that the observed shift to low galactosylation and sialylation but increased fucosylation of Fc Igs in the ICs promotes higher affinity binding to FcγRs on neutrophils, thereby causing NET formation and NETosis associated with release of DAMPs. Released DAMPs and inducible DAMPs (e.g., TNF [397]) secreted by DAMP- activated cells, in turn, may induce further subroutines of RCD (e.g., necroptosis, pyroptosis, and NETosis [479–486]). Cells observed to succumb to RCD include FLSs, synovial macrophages and monocytes, neutrophils, T and B cells, osteoblasts/chondrocytes, and osteoclasts (also compare [487]). All in all: The various subroutines of RCD are again associated with the release of DAMPs and autoantigens such as citrullinated peptides: a vitious circle. Thus, it is the continuous emission of DAMPs that activate synovial innate immune cells such as FLSs, neutrophils, and macrophages to mount synovial acute/chronic inflammatory and hyperplastic responses leading to pannus formation and RANKL-mediated osteoclastogenesis. In addition, DAMPs, along with citrullinated autoantigens, enter a positive feed- forward loop and fuel permanently—via activation of APCs—the adaptive autoimmune response, which will, in turn, produce ACPAs and ACPA/ICs. Overall, a disastrous pathogenetic DAMP-driven positive feed-forward loop of innate and adaptive autoimmune processes in genetically predisposed RA patients can be insinuated starting in the lung from an initial environmental injury (cigarette smoke)-induced, NETosis-mediated, citrullinated autoantigen/DAMP-driven autoimmune response with subsequent production of autoantibodies and autoantibody- containing ICs. The loop proceeds intraarticularly with autoantibodies/ autoantibody-containing ICs to NET formation and NETosis, associated with the release of DAMPs—through induction of further subroutines of RCD associated with the release of additional DAMPs—up to chronic perpetuating destructive synovial autoinflammation and (together with citrullinated autoantigens) ongoing autoimmune processes. Speculatively, this concept might serve as a blueprint for other environmental factors, such as periodontitis, known to be pathogenetically involved in RA.
7.4 DAMPs and SAMPs as Biomarkers, Therapeutic Targets, and Therapeutics in Systemic Autoimmune Disorders 7.4.1 Introductory Remarks The emerging use of DAMPs and SAMPs as biomarkers, therapeutic targets, and therapeutics in the management of systemic ADs is outlined here, using SLE and RA as examples. Though not generally accepted in the current routine management of both diseases, the exploitation of these molecules should be seriously considered a valuable enrichment of modern diagnostic and therapeutic modalities. This is all
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the more as modern medicine includes the application of criteria of personalized medicine that strives for improvements in tailoring and timing of diagnostic, prognostic, preventive, and therapeutic measures. Indeed, personalized medicine most frequently refers to a “medical model” using biomarker profiling for tailoring the right therapeutic strategy for the right patient, the correct dose, and at the right time and/or to determine the predisposition to disease and/or to deliver timely and stratified prevention [488, 489]. DAMPs and SAMPs appear to meet these criteria. New treatment options in ADs are also warranted since the standard treatment for them had long been immunosuppressive agents, and recent therapy with immunomodulatory biologic drugs aimed at blocking inflammatory mediators was shown to have limitations, including adverse safety risk and lack of efficacy in many autoimmune diseases. They will not be covered here, nor are T cell therapies using Tregs to achieve active dominant immune tolerance or T cells (engineered to express chimeric antigen receptors) to eliminate pathogenetically involved immune cells.
7.4.2 DAMPs and SAMPs as Diagnostic and Prognostic Biomarkers in Systemic Lupus Erythematosus 7.4.2.1 General Remarks As with other human diseases, biomarkers in SLE include tools and technologies that help make a proper diagnosis and classification of complications as well as understand the prediction, progression, regression, or outcome of therapeutic interventions (see also the introduction of this topic in Vol. 2 [34], Sect. 7.1, p. 261). In fact, a considerable spectrum of traditional and novel clinical and immunological biomarkers in SLE has been published and recently been reviewed by Capecchi et al. [490] and Yu et al. [491]. Here, only DAMPs and SAMPs are of main interest. Indeed, the measurement of DAMPs as biomarkers is very helpful in the management of the disease. In particular, the identification of patients at risk of impeding flare could instigate tight clinical monitoring and allow preemptive treatment. Determination of nuclear DAMPs (including non-nuclear DAMPs in case of suspected RCD as an underlying triggering event) could improve the ability to predict clinical flare beyond traditional clinical and serological markers. Indeed, such a novel DAMP-oriented tool could provide a better understanding of SLE disease activity and clinical flare and contribute to the appropriate management of the individual patient. 7.4.2.2 DAMPs Certainly, the inducible DAMP type I IFN that appears to correlate with SLE disease activity and possibly associate with certain disease manifestations would be a valuable biomarker. However, circulating levels of type I IFN in SLE are often below the detection limit of immunoassays, and thus, the development of surrogate markers for this inducible DAMP disease activity has recently been discussed [492]. On the other hand, there is a growing interest in using RNA (sensed by TLR7) such as circular RNA and exosomal miRNA as biomarkers in diagnosis,
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follow-up, and therapeutic monitoring for SLE (particularly for renal injury of SLE) [493, 494]. For example, Yang et al. [495], in studies on patients with lupus nephritis, recently analyzed tRNA-derived small noncoding RNA (tsRNA) signatures in the serum of these patients and controls and identified that tRF-His-anticodon GTG-1 was significantly upregulated in SLE serum. They further showed that a combination of tRF-His-GTG-1 (the most significantly elevated tsRNA) and anti-dsDNA could serve as biomarkers for diagnosing SLE and that the noninvasive serum tRFHis-GTG-1 could also be used to distinguish SLE with lupus nephritis or SLE without lupus nephritis. The authors concluded from their findings that serum tsRNAs (here denoted as an endogenous DAMP) could be employed as noninvasive biomarkers for the efficient diagnosis and prediction of nephritis in SLE. Also, in a recent study on patients with lupus nephritis, Yu et al. [496] observed that syndecan-1 and HA levels (here, both denoted as ECM-associated DAMPs) were significantly higher during active lupus nephritis compared with remission and correlated with the level of proteinuria, estimated glomerular filtration rate, anti- dsDNA antibodies, complement 3 and serum creatinine. Also, the researchers found that syndecan-1 levels increased prior to clinical renal flare by 3.6 months, while HA levels increased at the time of nephritic flare, and the levels decreased in parallel with treatment response. They further observed that syndecan-1 levels correlated with the severity of interstitial inflammation, while HA levels correlated with chronicity grading in kidney biopsies of active lupus nephritis. These and other findings led the investigators to suggest that serum syndecan-1 and HA levels can be potentially utilized in clinical management. Last but not least, in a controlled cross-sectional study that comprised children and adolescents with SLE [497], serum HMGB1 was shown to be a reliable biomarker for diagnosis of pediatric SLE and monitoring disease status, especially in lupus nephritis, suggesting this DAMP as a potential therapeutic target in this disease.
7.4.2.3 SAMPs An even more emerging concept refers to the use of SAMPs as valuable diagnostic and prognostic biomarkers in autoimmune diseases such as SLE. Interestingly, this idea has already been published in a paper by Das in 2011 [498] (“Lipoxins as biomarkers of lupus and other inflammatory conditions”). Das wrote: It is likely that progression and flares of lupus and lupus nephritis are due to decreased formation and release of LXA4. Hence, administration of LXA4 and its analogues could be of benefit in lupus. Furthermore, plasma and urinary measurement of lipoxins may be used to predict prognosis and response to therapy. It is likely that lipoxins and other bioactive anti-inflammatory lipids such as resolvins, protectins, maresins and nitrolipids play a significant role in other auto-immune diseases. Of note, the proposal that SAMPs can be utilized as ideal biomarkers in SLE has received convincing traction from the above-mentioned reports on the RvD1, showing that the level of this SPM was significantly lower in active SLE patients compared with inactive status and controls [162]. Experimentally, the property of RvD1 to ameliorate the
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clinical features of SLE was found to be due to its ability to increase Treg differentiation [162, 163]. The emerging topic has also recently been resumed and impressively discussed by Perez-Hernandez et al. [161].
7.4.2.4 Concluding Remarks Targeted research on the use of DAMPs and SAMPs in their role as biomarkers in SLE is still in its infancy. On the other hand, more robust immunological biomarkers are demanded by clinicians needed to better understand disease progression in individuals with SLE, including non-organ-specific SLE biomarkers and organ- specific SLE biomarkers. However, given current worldwide-growing research activities on DAMPs and SAMPs, one can be confident that such studies will be published soon.
7.4.3 Avoidance, Blockade, or Removal of DAMPs and Administration of SAMPs as Therapeutic Options in Systemic Lupus Erythematosus 7.4.3.1 General Remarks In light of the danger/injury model, successful treatment of ADs is completely different from traditional therapy and consists of the strategy to avoid, block, or eliminate DAMPs, aimed at preserving the presentation of autoantigens by DCs in the absence of DAMPs, that is, absence of costimulation; in one word: to induce peripheral self tolerance. At the cellular level and mechanistically, the goal is to induce tolerogenic DCs that present the autoantigen to naïve T cells in the absence of costimulatory but in the presence of co-inhibitory molecules (see Sect. 6.2.2.4 and Fig. 6.2). The three possibilities are briefly discussed in the following. 7.4.3.2 Administration of Autoantigen in the Absence of DAMPs The key tenet of the danger/injury paradigm in Immunity includes the proposal that antigens in the absence of DAMPs, that is, the absence of costimulatory signal 2, induce antigen-specific tolerance (see Sect. 1.3 and Fig. 1.2 and Sect. 6.2.2.4 and Fig. 6.2). This concept also applies to autoantigens and is not brand new. Indeed, earlier autoantigen-specific approaches using peptides or whole antigens have evolved into strategies aimed at delivering these molecules to autoreactive T cells either indirectly, via APCs such as tolDCs, or directly via MHC molecules, more recently via DNA or mRNA vaccines, in a manner intended to drive clonal deletion and/or immunoregulation. These various antigen-specific therapeutic approaches for autoimmunity have recently been comprehensively reviewed by Serra and Santamaria [499] and discussed for SLE by Robinson and Thomas [500]. For allotolerance, this principle was reviewed by Land [501]. Notably, this highly interesting antigen-specific approach to breaking autoimmunity has not yet been explored in SLE but has been investigated in other ADs. Thus, the topic will be addressed for RA (below) and for MS and T1DM in the next chapter, where such approaches have already been pursued.
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7.4.3.3 DAMPs as Therapeutic Targets First and foremost, therapeutic strategies to downregulate/inhibit directly/indirectly type I IFNs (denoted as inducible DAMPs in this book) and IFN receptors, respectively, should be mentioned here. Indeed, clinical trials have already been successfully conducted with respect to these important options. Since a number of reports have already been published in this field, this topic will not be pursued further here; instead, the reader is referred to relevant articles, such as those published in Refs. [220, 221, 502–504]. Instead, HMGB1 and the most relevant naDAMPs, DNA and RNA, will be discussed next, although there have been few published reports on therapeutic interventions with these DAMPs. High Mobility Group Box 1 There are only a few published reports on therapeutic intervention with HMGB1 antagonists in experimental lupus models (reviewed by Andersson et al. [412]). For example, in earlier investigations on a lupus-prone model, inhibition of HMGB1 using neutralizing anti-HMGB1mAB was found to improve lupus-like disease in BXSB mice [505]. In later studies on MRL/lpr mice, ethyl pyruvate was demonstrated to alleviate the clinical aspects of lupus nephritis and prolong the survival of animals [506]. Interventions with Nucleic Acid Hydroxychloroquine should be mentioned here. This antimalarial drug, like chloroquine, belongs to the group of disease-modifying anti-rheumatic drugs (DMARDs) and is used as part of current treatment guidelines for SLE (and RA, too). Its mechanism of action has been recently reviewed by Schrezenmeier and Dörner [507] and is summarized in the following in a staggered abbreviated form. Hydroxychloroquine, besides others, accumulates in endosomes and binds to the minor groove of dsDNA. Moreover, the drug was shown to inhibit TLR signaling by changing the pH of endosomes and/or preventing TLR7 and TLR9 from binding their ligands RNA and DNA, respectively (here denoted as endogenous DAMPs). Hydroxychloroquine was found to also inhibit the activity of the cGAS by interfering with its binding to cytosolic DNA. Hence, by preventing TLR and STING signaling, hydroxychloroquine can reduce the production of proinflammatory cytokines, including type I IFNs. Moreover, in cDCs, pDCs, and B cells, hydroxychloroquine is supposed to interfere with TLR7/TLR9-binding to DNA and RNA, thereby inhibiting autoantigen processing and subsequent MHC-II presentation and upregulation of costimulatory molecules; the result is the prevention of T cell activation. However, the role of this drug in inhibiting DNA and RNA in their function as DAMPs was not mentioned expressis verbis by the investigators (for TLR- and STING-mediated signaling, see Sect. 4.3.2.3 and Figs. 4.5 and 4.7). There is some evidence from clinical studies that hydroxychloroquine exerts beneficial effects in form of alleviating mild symptoms of SLE, such as arthralgia, fatigue, fever, and rash, as well as preventing disease flares (reviewed by Ponticelli and Moroni [508]). Dima et al. [509], in a more recent review, outlined that this drug also has a significant favorable impact on long-term outcomes such as damage
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accrual and mortality in SLE. The authors stated that, based on these impressive benefits, hydroxychloroquine is now the mainstay long-term treatment in SLE, recommended by current guidelines in all patients unless contraindications or side effects. Nucleic Acid Scavenging Nucleic-acid scavenging polymers (NASPs) have been shown to neutralize the proinflammatory effects of NAs and therefore have been proposed to be used as a promising therapeutic option in SLE [510]. Hence, it remains to be seen when such emerging investigations will be carried out and published.
7.4.3.4 SAMPs as Therapeutics An even more emerging concept is coming up in using SAMPs as putative therapeutic tools to regulate the development and magnitude of SLE. The proposal is supported by the above-mentioned experiments suggesting that RvD1 treatment ameliorates disease phenotype and inflammatory response through upregulating Treg and downregulating Th17 cells [162]. Hence, it is expected that clinical trials with the use SPMs applying this approach will be conducted in the near future. 7.4.3.5 Concluding Remarks Overall, there are still few reports on interventions for SLE with the use of DAMPs as therapeutic targets and application of SAMPs as therapeutics in efforts to treat this disease. But it is in the air that extensive research and the initiation of clinical trials in this new therapeutic terrain will soon be initiated and published.
7.4.4 DAMPs and SAMPs as Diagnostic and Prognostic Biomarkers in Rheumatoid Arthritis 7.4.4.1 General Remarks Biomarkers in RA are relevant for guiding the clinical and therapeutic management of all phases of this disease. As reviewed by Atzeni et al. [511], they can assist in predicting disease development in individuals at risk, facilitating diagnosis by closing the serological gap, providing prognostic information that is useful for making therapeutic choices and assessing treatment responses and outcomes, and allowing disease activity and progression to be monitored. DAMPs appear to ideally fulfill these tasks; accordingly, their level in serum and SF can be useful diagnostic and prognostic biomarkers of arthritis as well as could serve as promising biomarkers for predicting responses to biological therapies in this disease [375]. Leaving aside the inducible DAMPs TNF and IL-1β, which have been detected in the serum and SF of RA patients and proposed to use as biomarkers [396], some aspects of the use of constitutive DAMPs are outlined in this section.
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7.4.4.2 DAMPs Interestingly, S100A8/A9 proteins, whose concentrations strongly correlate with synovitis activity, are at the forefront of using DAMPs to monitor RA status and progression of RA (for a systemic review, see Abildtrup et al. [512]). By collecting data from studies searched in Medline, Scopus, and the Cochrane Library, the authors could show that S100A8/A9 protein levels are high in active disease, particularly in RF-positive patients. Further, they demonstrated that levels fell with effective treatment. Moreover, longitudinal data analyzed by the authors showed that this DAMP is a significant and independent predictor of erosive progression and therapeutic responses, particularly in patients who received effective biological treatments. The data were extended by other lines of studies showing that measurement of S100A8/A9 proteins in the SF of patients serves as a tool to discriminate septic arthritis from pseudogout and RA arthritis [513]. High mobility group box 1 appears to join S100A8/A9 proteins as a valuable diagnostic and prognostic biomarker. Evidence for this property was provided by a study in children with juvenile idiopathic arthritis showing that this DAMP is a good prognostic marker for structural joint damage in a 10-year follow-up of these little patients [514]. In a more recent study, HMGB1 was found to be higher in serum and joint SF of RA patients than in healthy controls [515]. Extracellular cell-free DNA also seems to be a good biomarker in RA. For example, in a study on patients with RA who started biological DMARDs therapy, an increase in circulating cell-free DNA at 8 weeks after introducing biological DMARDs was found to be associated with an improvement in disease activities [516]. The authors concluded that, compared with traditional biomarkers, circulating cell-free DNA is able to predict the early therapeutic effects of biological DMARDs in RA patients. 7.4.4.3 SAMPs The role of SAMPs as valuable biomarkers must certainly be highly appreciated, although there is little evidence to date to support this assumption. The article of Gomez et al. [517] is an important exception. The investigators studied plasma levels of SMPs as potential biomarkers for DMARD responsiveness in patients with early RA. Using supervised machine-learning methodologies, the researchers found that increased levels of SPMs such as RvD4, 15R-LXA4, and MaR1 are predictive of DMARD responsiveness at 6 months. Evaluation of circulating SPM concentrations 6 months after treatment initiation revealed that differences between responders and non-responders persist, with SPM concentrations decreasing in patients resistant to DMARD therapy. The authors summed up: Thus, these biomarkers may be clinically useful in identifying patients who are unlikely to respond to conventional DMARD therapy and would benefit from being fast-tracked to the next level of RA therapeutics. This would in turn help minimise or even prevent further structural damage to the joints together with disease progression and disability, thereby improving quality of life.
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7.4.5 Avoidance, Blockade, or Removal of DAMPs and Administration of SAMPs as Therapeutic Options in Rheumatoid Arthritis 7.4.5.1 General Remarks Modern treatment of RA consists of the optional use of various drugs that are currently available, including non-steroidal anti-inflammatory drugs, glucocorticoids, and DMARDs of synthetic origin (conventional DMARDs, such as methotrexate or targeted DMARDs, such as JAK-inhibitors or biological DMARDs, such as B celldepleting drugs) [518]. In light of the danger/injury model, treatment of this disease is different and would consist of strategies to avoid, block, or eliminate DAMPs. Leaving aside the use of TNF inhibitors (seen here as inhibitors against an inducible DAMP), several such approaches have already been proposed and are briefly discussed in the following. 7.4.5.2 Administration of Autoantigen in the Absence of DAMPs From the different autoantigen-specific approaches mentioned above in the description of SLE, a few that have already proven successful experimentally have already been tested in RA patients (reviewed by Page et al. [519]). For example, several self antigens/self peptides administered for restoration of tolerance in RA have been investigated using oral ingestion, gastric application, or nasal application routes. However, they have so far been quite disappointing and resulted in only minor improvements in rheumatic scores as compared to control or placebo treatment. A bit more promising, albeit moderate, results were observed with the use of tolDCs. Administration of Tolerogenic Dendritic Cells For example, in a controlled open-label Phase I trial, patients received autologous DCs modified with an NF-κB inhibitor exposed to four citrullinated peptide antigens (designated “Rheumavax”). Rheumavax was administered once intradermally at two progressive dose levels to 18 RA patients [520]. The peptide antigen proved to be well tolerated; moreover, at 1 month after treatment, the researchers observed a reduction in effector T cells and an increased ratio of Tregs, also a significant reduction in some RA-typical cytokines and chemokines. In a more recently conducted controlled Phase I trial, patients with inflammatory arthritis and an inflamed knee received arthroscopically tolDCs following saline irrigation of the target knee [521]. The tolDC were differentiated from CD14+ monocytes and loaded with autologous SF as a source of autoantigens. The investigators found that tolDC therapy appears safe, feasible, and acceptable. Knee symptoms stabilized in two of three patients who received 10 × 106 tolDC, but no systemic clinical or immunomodulatory effects were detectable. Certainly, observations made in such studies encourage for further studies on RA patients to assess the clinical efficacy and autoantigen-specific effects in the absence of DAMPs.
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DNA Vaccines and Application of Regulatory T Cells: Not Yet Clinically Realized Although DNA vaccines showed beneficial effects in experimental RA models, to date, the clinical use cannot be widely developed for RA, especially because the PTMs of self peptides, such as citrullination, cannot be coded genetically. As argued by Page et al. [519]: Consequently, these peptides need to be exogenously produced with the correct modifications and then infused. Before infusion, these self-peptides can also be engineered to enhance their tolerogenic properties or to promote their delivery to the right cells and at the right place. Similarly, based on promising results obtained from experiments on RA models, adoptive transfer of Tregs has been considered to restore tolerance in RA. However, as also discussed by Page et al. [519]: The clinical efficacy of Tregs transfer has been hampered by the high amount of pro-inflammatory cytokines in the joints, which could not be counterbalanced by the infused cells. Another limitation of Tregs lies in the difficulty to characterise and expand these cells.
7.4.5.3 DAMPs as Therapeutic Targets High Mobility Group Box 1 A number of experimental studies in arthritis models have shown that inhibition of HMGB1 by application of specific antagonists of this DAMP, such as the use of monoclonal anti-HMGB1 antibodies, improves arthritis, in particular, protects against the devastating destruction of cartilage and bone (reviewed by Andersson et al. [412] and more recently Kaur et al. [522]). Given the promising results from these studies, Andersson et al. [412] proposed that HMGB1-specific antagonists should be tested in multiple parallel clinical studies of inflammatory disease syndromes to reveal whether blocking extracellular HMGB1 will benefit patients. S100A8/A9 Proteins There are no targeted experimental studies on experimental RA models showing that blocking S100A8A9 protein expression ameliorates this disease. On the other hand, in view of numerous indirect pieces of evidence from other experimental settings, Austermann et al. [523] have suggested these DAMPs as potential therapeutic targets for arthritis. They concluded: Taken together, there has been emerging evidence in recent years that modulation of alarmin functions could be an innovative and successful strategy in local anti-inflammatory therapy.
7.4.5.4 SAMPs as Therapeutics To date, there have been no reports about the investigation of SAMPs as therapeutics in experimental RA models. However, given the growing preclinical and clinical evidence indicating that these DAMP-counterbalancing molecules are active in RA (see above Sect. 7.3.7), the initiation of such experiments seems “just around the corner.”
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7.4.6 Résumé Intensive characterization and exploration of the nature and function of DAMPs and SAMPs is an emerging area of research in SLE and RA that can be expected to contribute to further elucidation of the complex and heterogenous pathogenesis of these disorders. But one point should be emphasized: Given that subroutines of RCD have been proven to occur in both diseases and considering that more than the above-mentioned DAMPs are released, it can be definitely assumed that activation of innate immune cells, including DCs, is also promoted by other DAMPs not yet identified. To accurately arrange them in order in their role as diagnostic and prognostic biomarkers, such studies can be eagerly awaited. This is all the more so as it may become apparent in the future that the measurement of a few DAMPs does not fulfill the expectations of physicians to obtain the diagnostic and prognostic information they requested and needed. Probably more exact information will be provided by targeted exploration, definition, and interpretation of distinct disease-specific “DAMPs pattern” and “SAMPs pattern” and/or even a distinct DAMPs:SAMPs ratio. Harnessing DAMPs and SAMPs as therapeutic targets and therapeutics—eventually under consideration of a given DAMPs:SAMPs ratio—appears to be emerging as attractive novel therapeutic options in both SLE and RA. Nevertheless, one has again to realize that the intrinsic nature of DAMPs and SAMPs is to maintain and restore homeostasis upon cell stress and tissue injury. A too-drastic therapeutic manipulation of these molecules can result in dyshomeostasis, that is, pathologies and disorders. Thus, strict monitoring of the DAMPs/SAMPs pattern within defined homeostatic windows during the whole course of the disease appears to be recommendable.
7.5 Outlook and Future Directions Systemic autoimmune diseases such as SLE and RA have complex pathogenesis and a multifactorial etiology. As outlined and illustrated in this chapter, it is the interrelationship between environmental factors to which an individual is exposed, his or her genetic predisposition, and epigenetic modifications that are thought to trigger the development and progression of both disorders. And there is emerging evidence indicating that different subclasses of DAMPs—originating as constitutive DAMPs from subroutines of RCD and secreted as inducible DAMPs by DAMP- activated innate immune cells—are pathogenetically involved in all stages of the diseases. In view of the growing evidence collected in the research area of RCD as prolific sources of DAMPs emission, a tentative model scenario for the pathogenesis of SLE and RA in genetically susceptible patients has been tentatively proposed holding that IC-induced NET formation/NETosis, associated with the release of DAMPs, and further subsequent DAMP-triggered forms of RCD, in turn, associated with the release of additional DAMPs, initiate an autoantigen-specific, DAMP-driven
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positive feed-forward loop that could orchestrate innate and adaptive autoimmune responses in both diseases in terms of a vitious circle. With further experience with intervention modalities such as extracorporeal hemoadsorption and moAB-mediated inhibition of DAMPs or scavenging of naDAMPs, possibly in conjunction with the administration of SAMPs as therapeutics, there is hope that this feed-forward loop can be broken, contributing to the alleviation of the devastating diseases.
References 1. Wilkinson ME, Charenton C, Nagai K. RNA splicing by the spliceosome. Annu Rev Biochem. 2020;89:359–88. https://www.annualreviews.org/doi/10.1146/ annurev-biochem-091719-064225. 2. Riemekasten G, Hahn BH. Key autoantigens in SLE. Rheumatology. 2005;44:975–82. http:// academic.oup.com/rheumatology/article/44/8/975/1772091/Key-autoantigens-in-SLE. 3. Didier K, Bolko L, Giusti D, Toquet S, Robbins A, Antonicelli F, et al. Autoantibodies associated with connective tissue diseases: what meaning for clinicians? Front Immunol. 2018;9:541. http://journal.frontiersin.org/article/10.3389/fimmu.2018.00541/full. 4. Aringer M, Costenbader K, Daikh D, Brinks R, Mosca M, Ramsey-Goldman R, et al. 2019 European League Against Rheumatism/American College of Rheumatology classification criteria for systemic lupus erythematosus. Ann Rheum Dis. 2019;78:1151–9. https://ard.bmj. com/lookup/doi/10.1136/annrheumdis-2018-214819. 5. Fanouriakis A, Kostopoulou M, Alunno A, Aringer M, Bajema I, Boletis JN, et al. 2019 update of the EULAR recommendations for the management of systemic lupus erythematosus. Ann Rheum Dis. 2019;78:736–45. https://ard.bmj.com/lookup/doi/10.1136/annrheumd is-2019-215089. 6. Fan Y, Hao Y-J, Zhang Z-L. Systemic lupus erythematosus: year in review 2019. Chin Med J. 2020;133:2189–96. https://journals.lww.com/10.1097/CM9.0000000000000983. 7. Trentin F, Zucchi D, Signorini V, Elefante E, Bortoluzzi A, Tani C. One year in review 2021: systemic lupus erythematosus. Clin Exp Rheumatol. 2021;39:231–41. http://www.ncbi.nlm. nih.gov/pubmed/33843578. 8. Kaul A, Gordon C, Crow MK, Touma Z, Urowitz MB, van Vollenhoven R, et al. Systemic lupus erythematosus. Nat Rev Dis Prim. 2016;2:16039. http://www.nature.com/articles/ nrdp201639. 9. Tsokos GC, Lo MS, Reis PC, Sullivan KE. New insights into the immunopathogenesis of systemic lupus erythematosus. Nat Rev Rheumatol. 2016;12:716–30. http://www.nature. com/articles/nrrheum.2016.186. 10. Pisetsky DS, Lipsky PE. New insights into the role of antinuclear antibodies in systemic lupus erythematosus. Nat Rev Rheumatol. 2020;16:565–79. https://www.nature.com/articles/ s41584-020-0480-7. 11. Signorini V, Elefante E, Zucchi D, Trentin F, Bortoluzzi A, Tani C. One year in review 2020: systemic lupus erythematosus. Clin Exp Rheumatol. 2020;38:592–601. https://pubmed.ncbi. nlm.nih.gov/32662410/. 12. Katzav A, Kloog Y, Korczyn AD, Niv H, Karussis DM, Wang N, et al. Treatment of MRL/lpr mice, a genetic autoimmune model, with the Ras inhibitor, farnesylthiosalicylate (FTS). Clin Exp Immunol. 2002;126:570–7. https://academic.oup.com/cei/article/126/3/570/6478297. 13. Peng SL. Experimental use of mouse models of systemic lupus erythematosus. Methods Mol Biol. 2012;900:135–68. http://www.ncbi.nlm.nih.gov/pubmed/22933068. 14. Li W, Titov AA, Morel L. An update on lupus animal models. Curr Opin Rheumatol. 2017;29:434–41. https://journals.lww.com/00002281-201709000-00003.
538
7 DAMPs in Systemic Autoimmune Diseases
15. Fujihara J, Ueki M, Kimura-Kataoka K, Iida R, Takeshita H, Yasuda T. Functional single nucleotide polymorphisms (SNPs) in the genes encoding the human deoxyribonuclease (DNase) family potentially relevant to autoimmunity. Immunol Investig. 2016;45:406–19. https://www.tandfonline.com/doi/full/10.3109/08820139.2016.1157813. 16. Pau E, Loh C, Minty GES, Chang N-H, Wither JE. Identification of a lupus-susceptibility locus leading to impaired clearance of apoptotic debris on New Zealand Black chromosome 13. Genes Immun. 2013;14:154–61. http://www.nature.com/articles/gene201264. 17. Herrmann M, Podolska M, Biermann M, Maueröder C, Hahn J. Inflammatory etiopathogenesis of systemic lupus erythematosus: an update. J Inflamm Res. 2015;8:161. http://www. dovepress.com/inflammatory-etiopathogenesis-of-systemic-lupus-erythematosus-an-updat- peer-reviewed-article-JIR. 18. Wu H, Fu S, Zhao M, Lu L, Lu Q. Dysregulation of cell death and its epigenetic mechanisms in systemic lupus erythematosus. Molecules. 2016;22:30. http://www.ncbi.nlm.nih. gov/pubmed/28035990. 19. Land WG. Role of damage-associated molecular patterns in light of modern environmental research: a tautological approach. Int J Environ Res. 2020;14:583–604. http://link.springer. com/10.1007/s41742-020-00276-z. 20. Parks CG, de Souza Espindola Santos A, Barbhaiya M, Costenbader KH. Understanding the role of environmental factors in the development of systemic lupus erythematosus. Best Pract Res Clin Rheumatol. 2017;31:306–20. http://www.ncbi.nlm.nih.gov/pubmed/29224673. 21. Gulati G, Brunner HI. Environmental triggers in systemic lupus erythematosus. Semin Arthritis Rheum. 2018;47:710–7. http://linkinghub.elsevier.com/retrieve/pii/S0049017217304699. 22. Pan Q, Guo Y, Guo L, Liao S, Zhao C, Wang S, et al. Mechanistic insights of chemicals and drugs as risk factors for systemic lupus erythematosus. Curr Med Chem. 2020;27:5175–88. https://www.eurekaselect.com/171277/article. 23. Barbhaiya M, Tedeschi SK, Lu B, Malspeis S, Kreps D, Sparks JA, et al. Cigarette smoking and the risk of systemic lupus erythematosus, overall and by anti-double stranded DNA antibody subtype, in the Nurses’ Health Study cohorts. Ann Rheum Dis. 2018;77:196–202. http://www.ncbi.nlm.nih.gov/pubmed/28988206. 24. Speyer CB, Costenbader KH. Cigarette smoking and the pathogenesis of systemic lupus erythematosus. Expert Rev Clin Immunol. 2018;14:481–7. https://www.tandfonline.com/doi/ful l/10.1080/1744666X.2018.1473035. 25. Finckh A, Cooper GS, Chibnik LB, Costenbader KH, Watts J, Pankey H, et al. Occupational silica and solvent exposures and risk of systemic lupus erythematosus in urban women. Arthritis Rheum. 2006;54:3648–54. http://doi.wiley.com/10.1002/art.22210. 26. Barbhaiya M, Costenbader K. Ultraviolet radiation and systemic lupus erythematosus. Lupus. 2014;23:588–95. http://www.ncbi.nlm.nih.gov/pubmed/24763542. 27. Doaty S, Agrawal H, Bauer E, Furst DE. Infection and lupus: which causes which? Curr Rheumatol Rep. 2016;18:13. http://www.ncbi.nlm.nih.gov/pubmed/26951251. 28. Smatti MK, Cyprian FS, Nasrallah GK, Al Thani AA, Almishal RO, Yassine HM. Viruses and autoimmunity: a review on the potential interaction and molecular mechanisms. Viruses. 2019;11:762. https://www.mdpi.com/1999-4915/11/8/762. 29. Ho CH, Chauhan K. Lupus erythematosus, drug-induced. Treasure Island, FL: StatPearls; 2018. http://www.ncbi.nlm.nih.gov/pubmed/28722919. 30. Land WG. Damage-associated molecular patterns in human diseases. Volume 1: Injury- induced innate immune responses. Cham: Springer International Publishing; 2018. http:// link.springer.com/10.1007/978-3-319-78655-1. 31. Magna M, Pisetsky DS. The role of cell death in the pathogenesis of SLE: is pyroptosis the missing link? Scand J Immunol. 2015;82:218–24. http://www.ncbi.nlm.nih.gov/ pubmed/26118732. 32. Sarhan M, Land WG, Tonnus W, Hugo CP, Linkermann A. Origin and consequences of necroinflammation. Physiol Rev. 2018;98:727–80. http://www.physiology.org/doi/10.1152/ physrev.00041.2016.
References
539
33. Yang F, He Y, Zhai Z, Sun E. Programmed cell death pathways in the pathogenesis of systemic lupus erythematosus. J Immunol Res. 2019;2019:1–13. https://www.hindawi.com/ journals/jir/2019/3638562/. 34. Land WG. Damage-associated molecular patterns in human diseases. Vol. 2: Danger signals as diagnostics, prognostics, and therapeutic targets. Cham: Springer International Publishing; 2020. http://link.springer.com/10.1007/978-3-030-53868-2. 35. Fousert E, Toes R, Desai J. Neutrophil extracellular traps (NETs) take the central stage in driving autoimmune responses. Cells. 2020;9:915. https://www.mdpi.com/2073-4409/9/4/915. 36. Goel RR, Kaplan MJ. Deadliest catch: neutrophil extracellular traps in autoimmunity. Curr Opin Rheumatol. 2020;32:64–70. https://journals.lww.com/10.1097/BOR.0000000000000667. 37. Frangou E, Chrysanthopoulou A, Mitsios A, Kambas K, Arelaki S, Angelidou I, et al. REDD1/ autophagy pathway promotes thromboinflammation and fibrosis in human systemic lupus erythematosus (SLE) through NETs decorated with tissue factor (TF) and interleukin-17A (IL-17A). Ann Rheum Dis. 2019;78:238–48. https://ard.bmj.com/lookup/doi/10.1136/annrh eumdis-2018-213181. 38. Faux SP, Tai T, Thorne D, Xu Y, Breheny D, Gaca M. The role of oxidative stress in the biological responses of lung epithelial cells to cigarette smoke. Biomarkers. 2009;14:90–6. http://www.ncbi.nlm.nih.gov/pubmed/19604067. 39. Pouwels SD, Zijlstra GJ, van der Toorn M, Hesse L, Gras R, ten Hacken NHT, et al. Cigarette smoke-induced necroptosis and DAMP release trigger neutrophilic airway inflammation in mice. Am J Physiol Cell Mol Physiol. 2016;310:L377–86. http://www.physiology.org/ doi/10.1152/ajplung.00174.2015. 40. Bokaba RP, Anderson R, Theron AJ, Tintinger GR. Cigarette smoke condensate attenuates phorbol ester-mediated neutrophil extracellular trap formation. Afr Health Sci. 2017;17:896. http://www.ncbi.nlm.nih.gov/pubmed/29085418. 41. Yang M-L, Doyle HA, Clarke SG, Herold KC, Mamula MJ. Oxidative modifications in tissue pathology and autoimmune disease. Antioxid Redox Signal. 2017;29:1415. http://www.ncbi. nlm.nih.gov/pubmed/29088923. 42. Harberts E, Fishelevich R, Liu J, Atamas SP, Gaspari AA. MyD88 mediates the decision to die by apoptosis or necroptosis after UV irradiation. Innate Immun. 2014;20:529–39. http:// journals.sagepub.com/doi/10.1177/1753425913501706. 43. de Jager TL, Cockrell AE, Du Plessis SS. Ultraviolet light induced generation of reactive oxygen species. Adv Exp Med Biol. 2017;996:15–23. http://www.ncbi.nlm.nih.gov/ pubmed/29124687. 44. Orzalli MH, Kagan JC. Apoptosis and necroptosis as host defense strategies to prevent viral infection. Trends Cell Biol. 2017;27:800–9. http://www.ncbi.nlm.nih.gov/pubmed/28642032. 45. Jorgensen I, Rayamajhi M, Miao EA. Programmed cell death as a defence against infection. Nat Rev Immunol. 2017;17:151–64. http://www.ncbi.nlm.nih.gov/pubmed/28138137. 46. Jorgensen I, Miao EA. Pyroptotic cell death defends against intracellular pathogens. Immunol Rev. 2015;265:130–42. http://doi.wiley.com/10.1111/imr.12287. 47. Wang Y, Qin Y, Wang T, Chen Y, Lang X, Zheng J, et al. Pyroptosis induced by enterovirus 71 and coxsackievirus B3 infection affects viral replication and host response. Sci Rep. 2018;8:2887. http://www.ncbi.nlm.nih.gov/pubmed/29440739. 48. Schönrich G, Raftery MJ. Neutrophil extracellular traps go viral. Front Immunol. 2016;7:366. http://www.ncbi.nlm.nih.gov/pubmed/27698656. 49. Yang X, Chao X, Wang Z-T, Ding W-X. The end of RIPK1-RIPK3-MLKL-mediated necroptosis in acetaminophen-induced hepatotoxicity? Hepatology. 2016;64:311–2. http://www. ncbi.nlm.nih.gov/pubmed/26418225. 50. Wang Y, Gao W, Shi X, Ding J, Liu W, He H, et al. Chemotherapy drugs induce pyroptosis through caspase-3 cleavage of a gasdermin. Nature. 2017;547:99–103. http://www.ncbi.nlm. nih.gov/pubmed/28459430. 51. Magro CM, Momtahen S, Harp J. The distinctive histopathology of hydralazine-associated ANCA positive vasculitis: in vivo demonstration of NETosis. Eur J Dermatol. 2017;27:91–2. http://www.ncbi.nlm.nih.gov/pubmed/27748260.
540
7 DAMPs in Systemic Autoimmune Diseases
52. Nakayama T, Saitoh N, Morotomi-Yano K, Yano K, Nakao M, Saitoh H. Nuclear extrusion precedes discharge of genomic DNA fibers during tunicamycin-induced neutrophil extracellular trap-osis (NETosis)-like cell death in cultured human leukemia cells. Cell Biol Int. 2016;40:597–602. http://www.ncbi.nlm.nih.gov/pubmed/26888435. 53. Mackern-Oberti JP, Jara EL, Riedel CA, Kalergis AM. Hormonal modulation of dendritic cells differentiation, maturation and function: implications for the initiation and progress of systemic autoimmunity. Arch Immunol Ther Exp (Warsz). 2017;65:123–36. http://www. ncbi.nlm.nih.gov/pubmed/27585815. 54. Zhang S, Liu S, Hong L, Wang X, Diao L, Cai S, et al. Identification of profound metabolic alterations in human dendritic cells by progesterone through integrated bioinformatics analysis. Front Immunol. 2021;12:806110. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.806110/full. 55. De Schutter E, Ramon J, Pfeuty B, De Tender C, Stremersch S, Raemdonck K, et al. Plasma membrane perforation by GSDME during apoptosis-driven secondary necrosis. Cell Mol Life Sci. 2022;79:19. https://link.springer.com/10.1007/s00018-021-04078-0. 56. Deng Y, Tsao BP. Advances in lupus genetics and epigenetics. Curr Opin Rheumatol. 2014;26:482–92. https://insights.ovid.com/crossref?an=00002281-201409000-00005. 57. Ghodke-Puranik Y, Niewold TB. Immunogenetics of systemic lupus erythematosus: a comprehensive review. J Autoimmun. 2015;64:125–36. http://linkinghub.elsevier.com/retrieve/ pii/S0896841115300226. 58. Mohan C, Putterman C. Genetics and pathogenesis of systemic lupus erythematosus and lupus nephritis. Nat Rev Nephrol. 2015;11:329–41. http://www.ncbi.nlm.nih.gov/ pubmed/25825084. 59. Ghodke-Puranik Y, Niewold TB. Genetics of the type I interferon pathway in systemic lupus erythematosus. Int J Clin Rheumtol. 2013;8:657–69. http://www.ncbi.nlm.nih.gov/ pubmed/24416080. 60. Crow MK. Advances in understanding the role of type I interferons in systemic lupus erythematosus. Curr Opin Rheumatol. 2014;26:467–74. https://insights.ovid.com/ crossref?an=00002281-201409000-00003. 61. Blanco P, Palucka AK, Gill M, Pascual V, Banchereau J. Induction of dendritic cell differentiation by IFN-alpha in systemic lupus erythematosus. Science. 2001;294:1540–3. http:// www.sciencemag.org/cgi/doi/10.1126/science.1064890. 62. Fernando MMA, Stevens CR, Walsh EC, De Jager PL, Goyette P, Plenge RM, et al. Defining the role of the MHC in autoimmunity: a review and pooled analysis. PLoS Genet. 2008;4:e1000024. http://dx.plos.org/10.1371/journal.pgen.1000024. 63. Connolly JJ, Hakonarson H. Role of cytokines in systemic lupus erythematosus: recent progress from GWAS and sequencing. J Biomed Biotechnol. 2012;2012:798924. http://www. hindawi.com/journals/bmri/2012/798924/. 64. Fernando MMA, Stevens CR, Sabeti PC, Walsh EC, McWhinnie AJM, Shah A, et al. Identification of two independent risk factors for lupus within the MHC in United Kingdom families. PLoS Genet. 2007;3:e192. http://dx.plos.org/10.1371/journal.pgen.0030192. 65. Napirei M, Gültekin A, Kloeckl T, Möröy T, Frostegård J, Mannherz HG. Systemic lupus- erythematosus: deoxyribonuclease 1 in necrotic chromatin disposal. Int J Biochem Cell Biol. 2006;38:297–306. http://www.ncbi.nlm.nih.gov/pubmed/16352456. 66. Kimura-Kataoka K, Ueki M, Takeshita H, Fujihara J, Iida R, Kawai Y, et al. Identification of the functional alleles of the nonsynonymous single-nucleotide polymorphisms potentially implicated in systemic lupus erythematosus in the human deoxyribonuclease I gene. DNA Cell Biol. 2014;33:492–502. http://www.ncbi.nlm.nih.gov/pubmed/24819173. 67. Zamani MR, Aslani S, Salmaninejad A, Javan MR, Rezaei N. PD-1/PD-L and autoimmunity: a growing relationship. Cell Immunol. 2016;310:27–41. http://www.ncbi.nlm.nih.gov/ pubmed/27660198. 68. Badii M, Gaal O, Popp RA, Crișan TO, Joosten LAB. Trained immunity and inflammation in rheumatic diseases. Jt Bone Spine. 2022;89:105364. https://linkinghub.elsevier.com/retrieve/ pii/S1297319X22000239.
References
541
69. Panousis NI, Bertsias GK, Ongen H, Gergianaki I, Tektonidou MG, Trachana M, et al. Combined genetic and transcriptome analysis of patients with SLE: distinct, targetable signatures for susceptibility and severity. Ann Rheum Dis. 2019;78:1079–89. https://ard.bmj.com/ lookup/doi/10.1136/annrheumdis-2018-214379. 70. Moroney JB, Chupp DP, Xu Z, Zan H, Casali P. Epigenetics of the antibody and autoantibody response. Curr Opin Immunol. 2020;67:75–86. https://linkinghub.elsevier.com/retrieve/pii/ S0952791520300893. 71. Frias AB, Boi SK, Lan X, Youngblood B. Epigenetic regulation of T cell adaptive immunity. Immunol Rev. 2021;300:9–21. https://onlinelibrary.wiley.com/doi/10.1111/imr.12943. 72. Wu H, Zhao M, Yoshimura A, Chang C, Lu Q. Critical link between epigenetics and transcription factors in the induction of autoimmunity: a comprehensive review. Clin Rev Allergy Immunol. 2016;50:333–44. http://link.springer.com/10.1007/s12016-016-8534-y. 73. Kiraz Y, Adan A, Kartal Yandim M, Baran Y. Major apoptotic mechanisms and genes involved in apoptosis. Tumor Biol. 2016;37:8471–86. http://www.ncbi.nlm.nih.gov/ pubmed/27059734. 74. Goldmann O, Medina E. The expanding world of extracellular traps: not only neutrophils but much more. Front Immunol. 2012;3:420. http://journal.frontiersin.org/article/10.3389/ fimmu.2012.00420/abstract. 75. Rosen A, Casciola-Rosen L, Ahearn J. Novel packages of viral and self-antigens are generated during apoptosis. J Exp Med. 1995;181:1557–61. http://www.ncbi.nlm.nih.gov/ pubmed/7699336. 76. Casciola-Rosen LA, Anhalt G, Rosen A. Autoantigens targeted in systemic lupus erythematosus are clustered in two populations of surface structures on apoptotic keratinocytes. J Exp Med. 1994;179:1317–30. http://www.ncbi.nlm.nih.gov/pubmed/7511686. 77. Kang S, Rogers JL, Monteith AJ, Jiang C, Schmitz J, Clarke SH, et al. Apoptotic debris accumulates on hematopoietic cells and promotes disease in murine and human systemic lupus erythematosus. J Immunol. 2016;196:4030–9. http://www.ncbi.nlm.nih.gov/pubmed/27059595. 78. Bai Y, Tong Y, Liu Y, Hu H. Self-dsDNA in the pathogenesis of systemic lupus erythematosus. Clin Exp Immunol. 2018;191:1–10. http://www.ncbi.nlm.nih.gov/pubmed/28836661. 79. Mahajan A, Herrmann M, Muñoz LE. Clearance deficiency and cell death pathways: a model for the pathogenesis of SLE. Front Immunol. 2016;7:35. http://journal.frontiersin.org/ Article/10.3389/fimmu.2016.00035/abstract. 80. Mistry P, Kaplan MJ. Cell death in the pathogenesis of systemic lupus erythematosus and lupus nephritis. Clin Immunol. 2017;185:59–73. http://www.ncbi.nlm.nih.gov/pubmed/27519955. 81. Radic M. Clearance of apoptotic bodies, NETs, and biofilm DNA: implications for autoimmunity. Front Immunol. 2014;5:365. http://journal.frontiersin.org/article/10.3389/ fimmu.2014.00365/abstract. 82. van Bavel CC, Dieker J, Muller S, Briand J-P, Monestier M, Berden JH, et al. Apoptosis- associated acetylation on histone H2B is an epitope for lupus autoantibodies. Mol Immunol. 2009;47:511–6. http://www.ncbi.nlm.nih.gov/pubmed/19747733. 83. Pieterse E, Hofstra J, Berden J, Herrmann M, Dieker J, van der Vlag J. Acetylated histones contribute to the immunostimulatory potential of neutrophil extracellular traps in systemic lupus erythematosus. Clin Exp Immunol. 2015;179:68–74. http://doi.wiley.com/10.1111/ cei.12359. 84. Pieterse E, van der Vlag J. Breaking immunological tolerance in systemic lupus erythematosus. Front Immunol. 2014;5:164. http://www.ncbi.nlm.nih.gov/pubmed/24782867. 85. Wu H, Chang C, Lu Q. The epigenetics of lupus erythematosus. Adv Exp Med Biol. 2020;1253:185–207. http://link.springer.com/10.1007/978-981-15-3449-2_7. 86. Barnawi J, Jersmann H, Haberberger R, Hodge S, Meech R. Reduced DNA methylation of sphingosine-1 phosphate receptor 5 in alveolar macrophages in COPD: a potential link to failed efferocytosis. Respirology. 2017;22:315–21. http://doi.wiley.com/10.1111/resp.12949. 87. Watson L, Tullus K, Marks SD, Holt RCL, Pilkington C, Beresford MW. Increased serum concentration of sphingosine-1-phosphate in juvenile-onset systemic lupus erythematosus. J Clin Immunol. 2012;32:1019–25. http://link.springer.com/10.1007/s10875-012-9710-3.
542
7 DAMPs in Systemic Autoimmune Diseases
88. Wallner S, Schröder C, Leitão E, Berulava T, Haak C, Beißer D, et al. Epigenetic dynamics of monocyte-to-macrophage differentiation. Epigenetics Chromatin. 2016;9:33. http://epigeneticsandchromatin.biomedcentral.com/articles/10.1186/s13072-016-0079-z. 89. Tian Y, Meng L, Zhang Y. Epigenetic regulation of dendritic cell development and function. Cancer J. 2017;23:302–7. http://insights.ovid.com/ crossref?an=00130404-201709000-00008. 90. Kinner-Bibeau LB, Sedlacek AL, Messmer MN, Watkins SC, Binder RJ. HSPs drive dichotomous T-cell immune responses via DNA methylome remodelling in antigen presenting cells. Nat Commun. 2017;8:15648. http://www.nature.com/doifinder/10.1038/ncomms15648. 91. Jin O, Kavikondala S, Sun L, Fu R, Mok M-Y, Chan A, et al. Systemic lupus erythematosus patients have increased number of circulating plasmacytoid dendritic cells, but decreased myeloid dendritic cells with deficient CD83 expression. Lupus. 2008;17:654–62. http://journals.sagepub.com/doi/10.1177/0961203308089410. 92. Son M, Kim SJ, Diamond B. SLE-associated risk factors affect DC function. Immunol Rev. 2016;269:100–17. http://www.ncbi.nlm.nih.gov/pubmed/26683148. 93. Hong Y, Wu J, Zhao J, Wang H, Liu Y, Chen T, et al. miR-29b and miR-29c are involved in Toll-like receptor control of glucocorticoid-induced apoptosis in human plasmacytoid dendritic cells. PLoS One. 2013;8:e69926. http://dx.plos.org/10.1371/journal.pone.0069926. 94. Yan S, Yim L, Tam R, Chan A, Lu L, Lau C, et al. MicroRNA-155 mediates augmented CD40 expression in bone marrow derived plasmacytoid dendritic cells in symptomatic lupus-prone NZB/W F1 mice. Int J Mol Sci. 2016;17:1282. http://www.ncbi.nlm.nih.gov/ pubmed/27509492. 95. Wang Z, Lu Q, Wang Z. Epigenetic alterations in cellular immunity: new insights into autoimmune diseases. Cell Physiol Biochem. 2017;41:645–60. http://www.ncbi.nlm.nih.gov/ pubmed/28214857. 96. Richardson B. The interaction between environmental triggers and epigenetics in autoimmunity. Clin Immunol. 2018;192:1–5. http://www.ncbi.nlm.nih.gov/pubmed/29649575. 97. Foma AM, Aslani S, Karami J, Jamshidi A, Mahmoudi M. Epigenetic involvement in etiopathogenesis and implications in treatment of systemic lupus erythematous. Inflamm Res. 2017;66:1057–73. http://www.ncbi.nlm.nih.gov/pubmed/28741130. 98. Yang F, Lin J, Chen W. Post-translational modifications in T cells in systemic erythematosus lupus. Rheumatology. 2021;60:2502–16. https://academic.oup.com/rheumatology/ article/60/6/2502/6123790. 99. Quddus J, Johnson KJ, Gavalchin J, Amento EP, Chrisp CE, Yung RL, et al. Treating activated CD4+ T cells with either of two distinct DNA methyltransferase inhibitors, 5-azacytidine or procainamide, is sufficient to cause a lupus-like disease in syngeneic mice. J Clin Invest. 1993;92:38–53. http://www.jci.org/articles/view/116576. 100. Onishi S, Adnan E, Ishizaki J, Miyazaki T, Tanaka Y, Matsumoto T, et al. Novel autoantigens associated with lupus nephritis. PLoS One. 2015;10:e0126564. https://dx.plos.org/10.1371/ journal.pone.0126564. 101. Rekvig OP. The anti-DNA antibodies: their specificities for unique DNA structures and their unresolved clinical impact—a system criticism and a hypothesis. Front Immunol. 2022;12:808008. https://www.frontiersin.org/articles/10.3389/fimmu.2021.808008/full. 102. Green DR, Oguin TH, Martinez J. The clearance of dying cells: table for two. Cell Death Differ. 2016;23:915–26. http://www.nature.com/articles/cdd2015172. 103. Wang H, Zhang Y, Wang Q, Wei X, Wang H, Gu K. The regulatory mechanism of neutrophil extracellular traps in cancer biological behavior. Cell Biosci. 2021;11:193. https://cellandbioscience.biomedcentral.com/articles/10.1186/s13578-021-00708-z. 104. Gupta S, Kaplan MJ. Bite of the wolf: innate immune responses propagate autoimmunity in lupus. J Clin Invest. 2021;131:e144918. https://www.jci.org/articles/view/144918. 105. Bruschi M, Moroni G, Sinico RA, Franceschini F, Fredi M, Vaglio A, et al. Neutrophil extracellular traps in the autoimmunity context. Front Med. 2021;8:614829. https://www.frontiersin.org/articles/10.3389/fmed.2021.614829/full.
References
543
106. Wang H, Li T, Chen S, Gu Y, Ye S. Neutrophil extracellular trap mitochondrial DNA and its autoantibody in systemic lupus erythematosus and a proof-of-concept trial of metformin. Arthritis Rheumatol. 2015;67:3190–200. http://doi.wiley.com/10.1002/art.39296. 107. Pisetsky DS. The complex role of DNA, histones and HMGB1 in the pathogenesis of SLE. Autoimmunity. 2014;47:487–93. http://www.ncbi.nlm.nih.gov/pubmed/24916843. 108. Bruschi M, Petretto A, Santucci L, Vaglio A, Pratesi F, Migliorini P, et al. Neutrophil Extracellular Traps protein composition is specific for patients with Lupus nephritis and includes methyl-oxidized αenolase (methionine sulfoxide 93). Sci Rep. 2019;9:7934. http:// www.nature.com/articles/s41598-019-44379-w. 109. Soni C, Reizis B. DNA as a self-antigen: nature and regulation. Curr Opin Immunol. 2018;55:31–7. https://linkinghub.elsevier.com/retrieve/pii/S0952791518300475. 110. Wirestam L, Schierbeck H, Skogh T, Gunnarsson I, Ottosson L, Erlandsson-Harris H, et al. Antibodies against High Mobility Group Box protein-1 (HMGB1) versus other anti-nuclear antibody fine-specificities and disease activity in systemic lupus erythematosus. Arthritis Res Ther. 2015;17:338. http://www.ncbi.nlm.nih.gov/pubmed/26596890. 111. Willis WL, Wang L, Wada TT, Gardner M, Abdouni O, Hampton J, et al. The proinflammatory protein HMGB1 is a substrate of transglutaminase-2 and forms high-molecular weight complexes with autoantigens. J Biol Chem. 2018;293:8394. http://www.ncbi.nlm.nih.gov/ pubmed/29618516 112. Lau CM, Broughton C, Tabor AS, Akira S, Flavell RA, Mamula MJ, et al. RNA-associated autoantigens activate B cells by combined B cell antigen receptor/Toll-like receptor 7 engagement. J Exp Med. 2005;202:1171–7. http://www.jem.org/lookup/doi/10.1084/ jem.20050630. 113. Lou H, Pickering MC. Extracellular DNA and autoimmune diseases. Cell Mol Immunol. 2018;15:746. http://www.ncbi.nlm.nih.gov/pubmed/29553134 114. Qiu CC, Caricchio R, Gallucci S. Triggers of autoimmunity: the role of bacterial infections in the extracellular exposure of lupus nuclear autoantigens. Front Immunol. 2019;10:2608. https://www.frontiersin.org/article/10.3389/fimmu.2019.02608/full. 115. Schaper F, Westra J, Bijl M. Recent developments in the role of high-mobility group box 1 in systemic lupus erythematosus. Mol Med. 2014;20:72–9. http://www.ncbi.nlm.nih.gov/ pubmed/24531837. 116. Magna M, Pisetsky DS. The role of HMGB1 in the pathogenesis of inflammatory and autoimmune diseases. Mol Med. 2014;20:138–46. http://www.molmed.org/content/pdfstore/13_164_Magna.pdf. 117. Pawaria S, Moody K, Busto P, Nündel K, Choi C-H, Ghayur T, et al. Cutting edge: DNase II deficiency prevents activation of autoreactive B cells by double-stranded DNA endogenous ligands. J Immunol. 2015;194:1403–7. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1402893. 118. Tamura Y, Yoneda A, Takei N, Sawada K. Spatiotemporal regulation of Hsp90–ligand complex leads to immune activation. Front Immunol. 2016;7:1–8. http://journal.frontiersin.org/ Article/10.3389/fimmu.2016.00201/abstract. 119. Pelka K, Shibata T, Miyake K, Latz E. Nucleic acid-sensing TLRs and autoimmunity: novel insights from structural and cell biology. Immunol Rev. 2016;269:60–75. http://www.ncbi. nlm.nih.gov/pubmed/26683145. 120. Magna M, Pisetsky DS. The alarmin properties of DNA and DNA-associated nuclear proteins. Clin Ther. 2016;38:1029–41. https://linkinghub.elsevier.com/retrieve/pii/ S0149291816301266. 121. Negishi H, Endo N, Nakajima Y, Nishiyama T, Tabunoki Y, Nishio J, et al. Identification of U11snRNA as an endogenous agonist of TLR7-mediated immune pathogenesis. Proc Natl Acad Sci U S A. 2019;116:23653–61. https://pubmed.ncbi.nlm.nih.gov/31694883/. 122. Caielli S, Athale S, Domic B, Murat E, Chandra M, Banchereau R, et al. Oxidized mitochondrial nucleoids released by neutrophils drive type I interferon production in human lupus. J Exp Med. 2016;213:697–713. http://www.jem.org/lookup/doi/10.1084/ jem.20151876.
544
7 DAMPs in Systemic Autoimmune Diseases
123. Lood C, Blanco LP, Purmalek MM, Carmona-Rivera C, De Ravin SS, Smith CK, et al. Neutrophil extracellular traps enriched in oxidized mitochondrial DNA are interferogenic and contribute to lupus-like disease. Nat Med. 2016;22:146–53. http://www.nature.com/ doifinder/10.1038/nm.4027. 124. Thanou A, Jupe E, Purushothaman M, Niewold TB, Munroe ME. Clinical disease activity and flare in SLE: current concepts and novel biomarkers. J Autoimmun. 2021;119:102615. https://linkinghub.elsevier.com/retrieve/pii/S0896841121000238. 125. Bosch X. Systemic lupus erythematosus and the neutrophil. N Engl J Med. 2011;365:758–60. http://www.nejm.org/doi/abs/10.1056/NEJMcibr1107085. 126. Jounai N, Kobiyama K, Takeshita F, Ishii KJ. Recognition of damage-associated molecular patterns related to nucleic acids during inflammation and vaccination. Front Cell Infect Microbiol. 2012;2:168. http://www.ncbi.nlm.nih.gov/pubmed/23316484. 127. Vollmer J, Tluk S, Schmitz C, Hamm S, Jurk M, Forsbach A, et al. Immune stimulation mediated by autoantigen binding sites within small nuclear RNAs involves Toll-like r eceptors 7 and 8. J Exp Med. 2005;202:1575–85. http://www.jem.org/lookup/doi/10.1084/jem.20051696. 128. Shrivastav M, Niewold TB. Nucleic Acid sensors and type I interferon production in systemic lupus erythematosus. Front Immunol. 2013;4:319. http://journal.frontiersin.org/ article/10.3389/fimmu.2013.00319/abstract. 129. Funabiki M, Kato H, Miyachi Y, Toki H, Motegi H, Inoue M, et al. Autoimmune disorders associated with gain of function of the intracellular sensor MDA5. Immunity. 2014;40:199–212. http://linkinghub.elsevier.com/retrieve/pii/S1074761314000326. 130. Wu J, Chen ZJ. Innate immune sensing and signaling of cytosolic nucleic acids. Annu Rev Immunol. 2014;32:461–88. http://www.annualreviews.org/doi/10.1146/ annurev-immunol-032713-120156. 131. Unterholzner L. The interferon response to intracellular DNA: why so many receptors? Immunobiology. 2013;218:1312–21. http://www.ncbi.nlm.nih.gov/pubmed/23962476. 132. Zhang W, Cai Y, Xu W, Yin Z, Gao X, Xiong S. AIM2 facilitates the apoptotic DNA-induced systemic lupus erythematosus via arbitrating macrophage functional maturation. J Clin Immunol. 2013;33:925–37. http://link.springer.com/10.1007/s10875-013-9881-6. 133. Clancy RM, Markham AJ, Buyon JP. Endosomal Toll-like receptors in clinically overt and silent autoimmunity. Immunol Rev. 2016;269:76–84. http://www.ncbi.nlm.nih.gov/ pubmed/26683146. 134. Fillatreau S, Manfroi B, Dörner T. Toll-like receptor signalling in B cells during systemic lupus erythematosus. Nat Rev Rheumatol. 2021;17:98–108. http://www.nature.com/articles/ s41584-020-00544-4. 135. Sasai M, Linehan MM, Iwasaki A. Bifurcation of Toll-like receptor 9 signaling by adaptor protein 3. Science. 2010;329:1530–4. http://www.sciencemag.org/cgi/doi/10.1126/ science.1187029. 136. Murayama G, Furusawa N, Chiba A, Yamaji K, Tamura N, Miyake S. Enhanced IFN-α production is associated with increased TLR7 retention in the lysosomes of palasmacytoid dendritic cells in systemic lupus erythematosus. Arthritis Res Ther. 2017;19:234. https:// arthritis-research.biomedcentral.com/articles/10.1186/s13075-017-1441-7. 137. Weidenbusch M, Kulkarni OP, Anders H-J. The innate immune system in human systemic lupus erythematosus. Clin Sci (Lond). 2017;131:625–34. http://clinsci.org/lookup/ doi/10.1042/CS20160415. 138. Zhao H, Wang L, Luo H, Li Q-Z, Zuo X. TNFAIP3 downregulation mediated by histone modification contributes to T-cell dysfunction in systemic lupus erythematosus. Rheumatology. 2017;56:835–43. http://www.ncbi.nlm.nih.gov/pubmed/28158872. 139. An J, Durcan L, Karr RM, Briggs TA, Rice GI, Teal TH, et al. Expression of Cyclic GMP-AMP synthase in patients with systemic lupus erythematosus. Arthritis Rheum. 2017;69:800–7. http://www.ncbi.nlm.nih.gov/pubmed/27863149. 140. Ablasser A, Gulen MF. The role of cGAS in innate immunity and beyond. J Mol Med. 2016;94:1085–93. http://link.springer.com/10.1007/s00109-016-1423-2.
References
545
141. Skopelja-Gardner S, An J, Tai J, Tanaka L, Sun X, Hermanson P, et al. The early local and systemic Type I interferon responses to ultraviolet B light exposure are cGAS dependent. Sci Rep. 2020;10:7908. http://www.nature.com/articles/s41598-020-64865-w 142. Laursen MF, Christensen E, Degn LLT, Jønsson K, Jakobsen MR, Agger R, et al. CD11c- targeted delivery of dna to dendritic cells leads to cGAS- and STING-dependent maturation. J Immunother. 2018;41:9–18. http://www.ncbi.nlm.nih.gov/pubmed/29189388. 143. Motwani M, McGowan J, Antonovitch J, Gao KM, Jiang Z, Sharma S, et al. cGAS-STING pathway does not promote autoimmunity in murine models of SLE. Front Immunol. 2021;12:605930. https://www.frontiersin.org/articles/10.3389/fimmu.2021.605930/full 144. Land WG. The role of damage-associated molecular patterns in human diseases: Part I Promoting inflammation and immunity. Sultan Qaboos Univ Med J. 2015;15:9–21. https:// pubmed.ncbi.nlm.nih.gov/25685392/. 145. Li Z, Guo J, Bi L. Role of the NLRP3 inflammasome in autoimmune diseases. Biomed Pharmacother. 2020;130:110542. https://linkinghub.elsevier.com/retrieve/pii/ S0753332220307356. 146. Zhao J, Wang H, Dai C, Wang H, Zhang H, Huang Y, et al. P2X7 blockade attenuates murine lupus nephritis by inhibiting activation of the NLRP3/ASC/caspase 1 pathway. Arthritis Rheum. 2013;65:3176–85. http://doi.wiley.com/10.1002/art.38174. 147. Shin MS, Kang Y, Lee N, Wahl ER, Kim SH, Kang KS, et al. Self double-stranded (ds)DNA induces IL-1β production from human monocytes by activating NLRP3 inflammasome in the presence of anti-dsDNA antibodies. J Immunol. 2013;190:1407–15. http://www.jimmunol. org/cgi/doi/10.4049/jimmunol.1201195. 148. Yang Q, Yu C, Yang Z, Wei Q, Mu K, Zhang Y, et al. Deregulated NLRP3 and NLRP1 inflammasomes and their correlations with disease activity in systemic lupus erythematosus. J Rheumatol. 2014;41:444–52. http://www.jrheum.org/cgi/doi/10.3899/jrheum.130310. 149. Fu R, Guo C, Wang S, Huang Y, Jin O, Hu H, et al. Podocyte activation of NLRP3 inflammasomes contributes to the development of proteinuria in lupus nephritis. Arthritis Rheum. 2017;69:1636–46. http://www.ncbi.nlm.nih.gov/pubmed/28544564. 150. Carney EF. Lupus nephritis: role of NLRP3 inflammasomes in podocyte injury. Nat Rev Nephrol. 2017;13:444. http://www.ncbi.nlm.nih.gov/pubmed/28603274. 151. Oliveira CB, Lima CAD, Vajgel G, Sandrin-Garcia P. The role of NLRP3 inflammasome in lupus nephritis. Int J Mol Sci. 2021;22:12476. https://www.mdpi. com/1422-0067/22/22/12476. 152. Zhu H, Zhao M, Chang C, Chan V, Lu Q, Wu H. The complex role of AIM2 in autoimmune diseases and cancers. Immun Inflamm Dis. 2021;9:649–65. https://onlinelibrary.wiley.com/ doi/10.1002/iid3.443. 153. Wu H, Deng Y, Long D, Yang M, Li Q, Feng Y, et al. The IL-21-TET2-AIM2-c-MAF pathway drives the T follicular helper cell response in lupus-like disease. Clin Transl Med. 2022;12:e781. https://onlinelibrary.wiley.com/doi/10.1002/ctm2.781. 154. Serhan CN, Levy BD. Resolvins in inflammation: emergence of the pro-resolving superfamily of mediators. J Clin Invest. 2018;128:2657–69. http://www.ncbi.nlm.nih.gov/pubmed/29757195. 155. Feehan KT, Gilroy DW. Is resolution the end of inflammation? Trends Mol Med. 2019;25:198–214. http://www.cell.com/article/S1471491419300176/fulltext. 156. Chiang N, Serhan CN. Specialized pro-resolving mediator network: an update on production and actions. Essays Biochem. 2020;64:443–62. https://portlandpress.com/essaysbiochem/ article/64/3/443/226308/Specialized-pro-resolving-mediator-network-an. 157. Serhan CN, Gupta SK, Perretti M, Godson C, Brennan E, Li Y, et al. The atlas of inflammation resolution (AIR). Mol Asp Med. 2020;74:100894. https://linkinghub.elsevier.com/ retrieve/pii/S0098299720300960. 158. Navarini L, Bisogno T, Margiotta DPE, Piccoli A, Angeletti S, Laudisio A, et al. Role of the specialized proresolving mediator resolvin D1 in systemic lupus erythematosus: preliminary results. J Immunol Res. 2018;2018:1–6. https://www.hindawi.com/journals/ jir/2018/5264195/.
546
7 DAMPs in Systemic Autoimmune Diseases
159. Chiurchiù V, Leuti A, Maccarrone M. Bioactive lipids and chronic inflammation: managing the fire within. Front Immunol. 2018;9:38. http://journal.frontiersin.org/article/10.3389/ fimmu.2018.00038/full. 160. Abdolmaleki F, Kovanen PT, Mardani R, Gheibi-Hayat SM, Bo S, Sahebkar A. Resolvins: emerging players in autoimmune and inflammatory diseases. Clin Rev Allergy Immunol. 2019;58:82. http://link.springer.com/10.1007/s12016-019-08754-9 161. Perez-Hernandez J, Chiurchiù V, Perruche S, You S. Regulation of T-cell immune responses by pro-resolving lipid mediators. Front Immunol. 2021;12:768133. https://www.frontiersin. org/articles/10.3389/fimmu.2021.768133/full. 162. Cheng T, Ding S, Liu S, Li X, Tang X, Sun L. Resolvin D1 improves the Treg/Th17 imbalance in systemic lupus erythematosus through miR-30e-5p. Front Immunol. 2021;12:668760. https://www.frontiersin.org/articles/10.3389/fimmu.2021.668760/full. 163. Mishra R, Bhattacharya S, Rawat BS, Kumar A, Kumar A, Niraj K, et al. MicroRNA-30e-5p has an integrated role in the regulation of the innate immune response during virus infection and systemic lupus erythematosus. iScience. 2020;23:101322. https://linkinghub.elsevier. com/retrieve/pii/S2589004220305095. 164. Cruchaud A, Despont JP, Roth A, Dayer JM. Phagocytosis, bactericidal capacity, and PGE2 production of monocytes in systemic lupus erythematosus and rheumatoid arthritis. Diagn Immunol. 1984;2:203–12. https://pubmed.ncbi.nlm.nih.gov/6597049/. 165. Bruschi M, Petretto A, Vaglio A, Santucci L, Candiano G, Ghiggeri G. Annexin A1 and autoimmunity: from basic science to clinical applications. Int J Mol Sci. 2018;19:1348. http:// www.mdpi.com/1422-0067/19/5/1348. 166. Kelly L, McGrath S, Rodgers L, McCall K, Tulunay Virlan A, Dempsey F, et al. Annexin-A1; the culprit or the solution? Immunology. 2022;166:2. https://onlinelibrary.wiley.com/ doi/10.1111/imm.13455 167. Panigrahy D, Gilligan MM, Serhan CN, Kashfi K. Resolution of inflammation: an organizing principle in biology and medicine. Pharmacol Ther. 2021;227:107879. https://linkinghub. elsevier.com/retrieve/pii/S0163725821000814. 168. Sozzani S, Del Prete A, Bosisio D. Dendritic cell recruitment and activation in autoimmunity. J Autoimmun. 2017;85:126–40. http://www.ncbi.nlm.nih.gov/pubmed/28774715. 169. Kaewraemruaen C, Ritprajak P, Hirankarn N. Dendritic cells as key players in systemic lupus erythematosus. Asian Pac J Allergy Immunol. 2020;38:225–32. https://apjai-journal.org/wp- content/uploads/2020/12/2.pdf. 170. Kis-Toth K, Tsokos GC. Dendritic cell function in lupus: independent contributors or victims of aberrant immune regulation. Autoimmunity. 2010;43:121–30. http://www.ncbi.nlm.nih. gov/pubmed/20102311. 171. Kis-Toth K, Szanto A, Thai T-H, Tsokos GC. Cytosolic DNA-activated human dendritic cells are potent activators of the adaptive immune response. J Immunol. 2011;187:1222–34. http:// www.ncbi.nlm.nih.gov/pubmed/21709148. 172. Balan S, Saxena M, Bhardwaj N. Dendritic cell subsets and locations. Int Rev Cell Mol Biol. 2019;348:1–68. https://linkinghub.elsevier.com/retrieve/pii/S193764481930067X. 173. Guiducci C, Coffman RL, Barrat FJ. Signalling pathways leading to IFN-α production in human plasmacytoid dendritic cell and the possible use of agonists or antagonists of TLR7 and TLR9 in clinical indications. J Intern Med. 2009;265:43–57. http://www.ncbi.nlm.nih. gov/pubmed/19093959. 174. Chan VS-F, Nie Y-J, Shen N, Yan S, Mok M-Y, Lau C-S. Distinct roles of myeloid and plasmacytoid dendritic cells in systemic lupus erythematosus. Autoimmun Rev. 2012;11:890–7. http://linkinghub.elsevier.com/retrieve/pii/S156899721200064X. 175. Guéry L, Hugues S. Tolerogenic and activatory plasmacytoid dendritic cells in autoimmunity. Front Immunol. 2013;4:59. http://journal.frontiersin.org/article/10.3389/fimmu.2013.00059/ abstract. 176. Ding D, Mehta H, McCune WJ, Kaplan MJ. Aberrant phenotype and function of myeloid dendritic cells in systemic lupus erythematosus. J Immunol. 2006;177:5878–89. http://www. jimmunol.org/lookup/doi/10.4049/jimmunol.177.9.5878.
References
547
177. Kim J-M, Park S-H, Kim H-Y, Kwok S-K. A plasmacytoid dendritic cells-type I interferon axis is critically implicated in the pathogenesis of systemic lupus erythematosus. Int J Mol Sci. 2015;16:14158–70. http://www.mdpi.com/1422-0067/16/6/14158. 178. Ye Y, Gaugler B, Mohty M, Malard F. Plasmacytoid dendritic cell biology and its role in immune-mediated diseases. Clin Transl Immunol. 2020;9:e1139. https://onlinelibrary.wiley. com/doi/10.1002/cti2.1139. 179. Fransen JH, Vlag J, Ruben J, Adema GJ, Berden JH, Hilbrands LB. The role of dendritic cells in the pathogenesis of systemic lupus erythematosus. Arthritis Res Ther. 2010;12:207. http:// www.ncbi.nlm.nih.gov/pubmed/20423534. 180. Liao X, Reihl AM, Luo XM. Breakdown of immune tolerance in systemic lupus erythematosus by dendritic cells. J Immunol Res. 2016;2016:1–15. http://www.hindawi.com/journals/ jir/2016/6269157/. 181. Celhar T, Hopkins R, Thornhill SI, De Magalhaes R, Hwang S-H, Lee H-Y, et al. RNA sensing by conventional dendritic cells is central to the development of lupus nephritis. Proc Natl Acad Sci U S A. 2015;112:E6195–204. http://www.pnas.org/lookup/doi/10.1073/ pnas.1507052112. 182. Means TK, Latz E, Hayashi F, Murali MR, Golenbock DT, Luster AD. Human lupus autoantibody-DNA complexes activate DCs through cooperation of CD32 and TLR9. J Clin Invest. 2005;115:407–17. http://www.jci.org/articles/view/23025. 183. Henault J, Martinez J, Riggs JM, Tian J, Mehta P, Clarke L, et al. Noncanonical autophagy is required for type I interferon secretion in response to DNA-immune complexes. Immunity. 2012;37:986–97. http://linkinghub.elsevier.com/retrieve/pii/S1074761312005079. 184. Guiducci C, Gong M, Xu Z, Gill M, Chaussabel D, Meeker T, et al. TLR recognition of self nucleic acids hampers glucocorticoid activity in lupus. Nature. 2010;465:937–41. http:// www.nature.com/articles/nature09102. 185. Baccala R, Gonzalez-Quintial R, Blasius AL, Rimann I, Ozato K, Kono DH, et al. Essential requirement for IRF8 and SLC15A4 implicates plasmacytoid dendritic cells in the pathogenesis of lupus. Proc Natl Acad Sci U S A. 2013;110:2940–5. http://www.pnas.org/cgi/ doi/10.1073/pnas.1222798110. 186. Krishnaswamy JK, Alsén S, Yrlid U, Eisenbarth SC, Williams A. Determination of T follicular helper cell fate by dendritic cells. Front Immunol. 2018;9:2169. https://www.frontiersin. org/article/10.3389/fimmu.2018.02169/full. 187. Datta SK. Harnessing tolerogenic histone peptide epitopes from nucleosomes for selective down-regulation of pathogenic autoimmune response in lupus (past, present, and future). Front Immunol. 2021;12:629807. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.629807/full. 188. Decker P, Singh-Jasuja H, Haager S, Kötter I, Rammensee H-G. Nucleosome, the main autoantigen in systemic lupus erythematosus, induces direct dendritic cell activation via a MyD88- independent pathway: consequences on inflammation. J Immunol. 2005;174:3326–34. http:// www.ncbi.nlm.nih.gov/pubmed/15749864. 189. Kanno A, Tanimura N, Ishizaki M, Ohko K, Motoi Y, Onji M, et al. Targeting cell surface TLR7 for therapeutic intervention in autoimmune diseases. Nat Commun. 2015;6:6119. http://www.nature.com/articles/ncomms7119. 190. Wardowska A, Smoleńska Ż, Lisowska KA, Zdrojewski Z, Pikuła M. Dendritic cells’ characteristics in patients with treated systemic lupus erythematosus. Acta Biochim Pol. 2020;67:417. https://ojs.ptbioch.edu.pl/index.php/abp/article/view/5416. 191. Thim-uam A, Prabakaran T, Tansakul M, Makjaroen J, Wongkongkathep P, Chantaravisoot N, et al. STING mediates lupus via the activation of conventional dendritic cell maturation and plasmacytoid dendritic cell differentiation. iScience. 2020;23:101530. https://linkinghub. elsevier.com/retrieve/pii/S2589004220307227. 192. Gessani S, Conti L, Del Cornò M, Belardelli F. Type I interferons as regulators of human antigen presenting cell functions. Toxins. 2014;6:1696–723. http://www.mdpi. com/2072-6651/6/6/1696.
548
7 DAMPs in Systemic Autoimmune Diseases
193. Kelly KM, Zhuang H, Nacionales DC, Scumpia PO, Lyons R, Akaogi J, et al. “Endogenous adjuvant” activity of the RNA components of lupus autoantigens Sm/ RNP and Ro 60. Arthritis Rheum. 2006;54:1557–67. https://onlinelibrary.wiley.com/ doi/10.1002/art.21819. 194. Crotty S. T Follicular helper cell biology: a decade of discovery and diseases. Immunity. 2019;50:1132–48. https://linkinghub.elsevier.com/retrieve/pii/S1074761319301918. 195. Nakayamada S, Tanaka Y. Clinical relevance of T follicular helper cells in systemic lupus erythematosus. Expert Rev Clin Immunol. 2021;17:1143–50. https://www.tandfonline.com/ doi/full/10.1080/1744666X.2021.1976146. 196. Heesters BA, van der Poel CE, Das A, Carroll MC. Antigen presentation to B cells. Trends Immunol. 2016;37:844–54. https://linkinghub.elsevier.com/retrieve/pii/ S147149061630151X. 197. Heesters BA, van Megesen K, Tomris I, de Vries RP, Magri G, Spits H. Characterization of human FDCs reveals regulation of T cells and antigen presentation to B cells. J Exp Med. 2021;218:e20210790. https://rupress.org/jem/article/218/10/e20210790/212590/ Characterization-of-human-FDCs-reveals-regulation. 198. Das A, Heesters BA, Bialas A, O’Flynn J, Rifkin IR, Ochando J, et al. Follicular dendritic cell activation by TLR ligands promotes autoreactive B cell responses. Immunity. 2017;46:106–19. http://linkinghub.elsevier.com/retrieve/pii/S1074761316305209. 199. Ghosh D, Jiang W, Mukhopadhyay D, Mellins ED. New insights into B cells as antigen presenting cells. Curr Opin Immunol. 2021;70:129–37. https://linkinghub.elsevier.com/retrieve/ pii/S0952791521000716. 200. Qin L, Waseem TC, Sahoo A, Bieerkehazhi S, Zhou H, Galkina EV, et al. Insights into the molecular mechanisms of T follicular helper-mediated immunity and pathology. Front Immunol. 2018;9:1884. https://www.frontiersin.org/article/10.3389/ fimmu.2018.01884/full 201. Scherm MG, Ott VB, Daniel C. Follicular helper T cells in autoimmunity. Curr Diab Rep. 2016;16:75. http://link.springer.com/10.1007/s11892-016-0770-2. 202. Qiu H, Wu H, Chan V, Lau C-S, Lu Q. Transcriptional and epigenetic regulation of follicular T-helper cells and their role in autoimmunity. Autoimmunity. 2017;50:71–81. https://www. tandfonline.com/doi/full/10.1080/08916934.2017.1284821. 203. Adler LN, Jiang W, Bhamidipati K, Millican M, Macaubas C, Hung S, et al. The other function: class II-restricted antigen presentation by B cells. Front Immunol. 2017;8:319. http:// journal.frontiersin.org/article/10.3389/fimmu.2017.00319/full. 204. Jackson SW, Scharping NE, Kolhatkar NS, Khim S, Schwartz MA, Li Q-Z, et al. Opposing impact of B cell–intrinsic TLR7 and TLR9 signals on autoantibody repertoire and systemic inflammation. J Immunol. 2014;192:4525–32. http://www.jimmunol.org/lookup/ doi/10.4049/jimmunol.1400098. 205. Heath WR, Kato Y, Steiner TM, Caminschi I. Antigen presentation by dendritic cells for B cell activation. Curr Opin Immunol. 2019;58:44–52. https://linkinghub.elsevier.com/retrieve/ pii/S0952791518301572. 206. Wang X, Xia Y. Anti-double stranded DNA antibodies: origin, pathogenicity, and targeted therapies. Front Immunol. 2019;10:1667. https://www.frontiersin.org/article/10.3389/ fimmu.2019.01667/full. 207. Hua Z, Hou B. The role of B cell antigen presentation in the initiation of CD4+ T cell response. Immunol Rev. 2020;296:24–35. https://onlinelibrary.wiley.com/doi/10.1111/imr.12859. 208. Fu N, Xie F, Sun Z, Wang Q. The OX40/OX40L axis regulates T Follicular helper cell differentiation: implications for autoimmune diseases. Front Immunol. 2021;12:670637. https:// www.frontiersin.org/articles/10.3389/fimmu.2021.670637/full. 209. El Shikh MEM, El Sayed RM, Sukumar S, Szakal AK, Tew JG. Activation of B cells by antigens on follicular dendritic cells. Trends Immunol. 2010;31:205–11. https://linkinghub. elsevier.com/retrieve/pii/S1471490610000517.
References
549
210. van der Poel CE, Bajic G, Macaulay CW, van den Broek T, Ellson CD, Bouma G, et al. Follicular dendritic cells modulate germinal center B cell diversity through FcγRIIB. Cell Rep. 2019;29:2745–2755.e4. https://linkinghub.elsevier.com/retrieve/pii/S2211124719314081. 211. Arulraj T, Binder SC, Meyer-Hermann M. Rate of immune complex cycling in follicular dendritic cells determines the extent of protecting antigen integrity and availability to germinal center B cells. J Immunol. 2021;206:1436–42. http://www.jimmunol.org/lookup/ doi/10.4049/jimmunol.2001355. 212. Swiecki M, Colonna M. The multifaceted biology of plasmacytoid dendritic cells. Nat Rev Immunol. 2015;15:471–85. http://www.nature.com/articles/nri3865. 213. Rönnblom L, Eloranta M-L. The interferon signature in autoimmune diseases. Curr Opin Rheumatol. 2013;25:248–53. http://www.ncbi.nlm.nih.gov/pubmed/23249830. 214. Lövgren T, Eloranta M-L, Båve U, Alm GV, Rönnblom L. Induction of interferon-alpha production in plasmacytoid dendritic cells by immune complexes containing nucleic acid released by necrotic or late apoptotic cells and lupus IgG. Arthritis Rheum. 2004;50:1861–72. http://doi.wiley.com/10.1002/art.20254. 215. Barrat FJ, Meeker T, Gregorio J, Chan JH, Uematsu S, Akira S, et al. Nucleic acids of mammalian origin can act as endogenous ligands for Toll-like receptors and may promote systemic lupus erythematosus. J Exp Med. 2005;202:1131–9. http://www.jem.org/lookup/ doi/10.1084/jem.20050914. 216. Båve U, Nordmark G, Lövgren T, Rönnelid J, Cajander S, Eloranta M-L, et al. Activation of the type I interferon system in primary Sjögren’s syndrome: a possible etiopathogenic mechanism. Arthritis Rheum. 2005;52:1185–95. http://doi.wiley.com/10.1002/art.20998. 217. Eloranta M-L, Barbasso Helmers S, Ulfgren A-K, Rönnblom L, Alm GV, Lundberg IE. A possible mechanism for endogenous activation of the type I interferon system in myositis patients with anti-Jo-1 or anti-Ro 52/anti-Ro 60 autoantibodies. Arthritis Rheum. 2007;56:3112–24. http://doi.wiley.com/10.1002/art.22860. 218. Eloranta M-L, Franck-Larsson K, Lövgren T, Kalamajski S, Rönnblom A, Rubin K, et al. Type I interferon system activation and association with disease manifestations in systemic sclerosis. Ann Rheum Dis. 2010;69:1396–402. http://ard.bmj.com/cgi/doi/10.1136/ ard.2009.121400. 219. Hamilton JA, Hsu H-C, Mountz JD. Role of production of type I interferons by B cells in the mechanisms and pathogenesis of systemic lupus erythematosus. Discov Med. 2018;25:21–9. http://www.ncbi.nlm.nih.gov/pubmed/29466691. 220. Bengtsson AA, Rönnblom L. Role of interferons in SLE. Best Pract Res Clin Rheumatol. 2017;31:415–28. https://linkinghub.elsevier.com/retrieve/pii/S1521694217300360. 221. Chasset F, Arnaud L. Targeting interferons and their pathways in systemic lupus erythematosus. Autoimmun Rev. 2018;17:44–52. http://linkinghub.elsevier.com/retrieve/pii/ S1568997217302823. 222. Postal M, Vivaldo JF, Fernandez-Ruiz R, Paredes JL, Appenzeller S, Niewold TB. Type I interferon in the pathogenesis of systemic lupus erythematosus. Curr Opin Immunol. 2020;67:87–94. https://linkinghub.elsevier.com/retrieve/pii/S095279152030114X. 223. Pinegin B, Vorobjeva N, Pinegin V. Neutrophil extracellular traps and their role in the development of chronic inflammation and autoimmunity. Autoimmun Rev. 2015;14:633–40. http://linkinghub.elsevier.com/retrieve/pii/S1568997215000646. 224. Crowl JT, Gray EE, Pestal K, Volkman HE, Stetson DB. Intracellular nucleic acid detection in autoimmunity. Annu Rev Immunol. 2017;35:313–36. https://www.annualreviews.org/ doi/10.1146/annurev-immunol-051116-052331. 225. Schreiber G. The molecular basis for differential type I interferon signaling. J Biol Chem. 2017;292:7285–94. http://www.ncbi.nlm.nih.gov/pubmed/28289098. 226. Bluyssen HA, Levy DE. Stat2 is a transcriptional activator that requires sequence- specific contacts provided by stat1 and p48 for stable interaction with DNA. J Biol Chem. 1997;272:4600–5. http://www.ncbi.nlm.nih.gov/pubmed/9020188.
550
7 DAMPs in Systemic Autoimmune Diseases
227. Schneider WM, Chevillotte MD, Rice CM. Interferon-stimulated genes: a complex web of host defenses. Annu Rev Immunol. 2014;32:513–45. http://www.annualreviews.org/ doi/10.1146/annurev-immunol-032713-120231. 228. Hoffmann H-H, Schneider WM, Rice CM. Interferons and viruses: an evolutionary arms race of molecular interactions. Trends Immunol. 2015;36:124–38. http://linkinghub.elsevier.com/ retrieve/pii/S1471490615000150. 229. Schoggins JW. Recent advances in antiviral interferon-stimulated gene biology. F1000Research. 2018;7:309. http://www.ncbi.nlm.nih.gov/pubmed/29568506. 230. Platanias LC. Mechanisms of type-I- and type-II-interferon-mediated signalling. Nat Rev Immunol. 2005;5:375–86. http://www.nature.com/articles/nri1604. 231. Fish EN, Platanias LC. Interferon receptor signaling in malignancy: a network of cellular pathways defining biological outcomes. Mol Cancer Res. 2014;12:1691–703. http://www. ncbi.nlm.nih.gov/pubmed/25217450. 232. McNab F, Mayer-Barber K, Sher A, Wack A, O’Garra A. Type I interferons in infectious disease. Nat Rev Immunol. 2015;15:87–103. http://www.nature.com/articles/nri3787. 233. Huber JP, Farrar JD. Regulation of effector and memory T-cell functions by type I interferon. Immunology. 2011;132:466–74. http://www.ncbi.nlm.nih.gov/pubmed/21320124. 234. Alunno A, Bartoloni E, Bistoni O, Nocentini G, Ronchetti S, Caterbi S, et al. Balance between regulatory T and Th17 cells in systemic lupus erythematosus: the old and the new. Clin Dev Immunol. 2012;2012:823085. http://www.hindawi.com/journals/jir/2012/823085/. 235. Jackson SW, Kolhatkar NS, Rawlings DJ. B cells take the front seat: dysregulated B cell signals orchestrate loss of tolerance and autoantibody production. Curr Opin Immunol. 2015;33:70–7. http://linkinghub.elsevier.com/retrieve/pii/S0952791515000199. 236. Vazquez MI, Catalan-Dibene J, Zlotnik A. B cells responses and cytokine production are regulated by their immune microenvironment. Cytokine. 2015;74:318–26. http://linkinghub. elsevier.com/retrieve/pii/S1043466615000666. 237. López P, Rodríguez-Carrio J, Caminal-Montero L, Mozo L, Suárez A. A pathogenic IFNα, BLyS and IL-17 axis in systemic lupus erythematosus patients. Sci Rep. 2016;6:20651. http://www.nature.com/articles/srep20651. 238. Liu M, Guo Q, Wu C, Sterlin D, Goswami S, Zhang Y, et al. Type I interferons promote the survival and proinflammatory properties of transitional B cells in systemic lupus erythematosus patients. Cell Mol Immunol. 2018;16:367. http://www.ncbi.nlm.nih.gov/ pubmed/29563616 239. Lee-Kirsch MA. The type I interferonopathies. Annu Rev Med. 2017;68:297–315. http:// www.ncbi.nlm.nih.gov/pubmed/27813875. 240. Heesters BA, Chatterjee P, Kim Y-A, Gonzalez SF, Kuligowski MP, Kirchhausen T, et al. Endocytosis and recycling of immune complexes by follicular dendritic cells enhances B cell antigen binding and activation. Immunity. 2013;38:1164–75. https://linkinghub.elsevier.com/ retrieve/pii/S1074761313002367. 241. Heesters BA, Myers RC, Carroll MC. Follicular dendritic cells: dynamic antigen libraries. Nat Rev Immunol. 2014;14:495–504. http://www.nature.com/doifinder/10.1038/nri3689. 242. Abd El-Aleem SA, Saber EA, Aziz NM, El-Sherif H, Abdelraof AM, Djouhri L. Follicular dendritic cells. J Cell Physiol. 2021;44:937. https://onlinelibrary.wiley.com/doi/10.1002/ jcp.30662 243. McShane AN, Malinova D. The ins and outs of antigen uptake in B cells. Front Immunol. 2022;13:892169. https://www.frontiersin.org/articles/10.3389/fimmu.2022.892169/full. 244. Marshak-Rothstein A. Toll-like receptors in systemic autoimmune disease. Nat Rev Immunol. 2006;6:823–35. http://www.ncbi.nlm.nih.gov/pubmed/17063184. 245. Hua Z, Hou B. TLR signaling in B-cell development and activation. Cell Mol Immunol. 2013;10:103–6. http://www.nature.com/doifinder/10.1038/cmi.2012.61. 246. Green NM, Moody K-S, Debatis M, Marshak-Rothstein A. Activation of autoreactive B cells by endogenous TLR7 and TLR3 RNA ligands. J Biol Chem. 2012;287:39789–99. http:// www.jbc.org/lookup/doi/10.1074/jbc.M112.383000.
References
551
247. Moody KL, Uccellini MB, Avalos AM, Marshak-Rothstein A, Viglianti GA. Toll-like receptor-dependent immune complex activation of B cells and dendritic cells. Methods Mol Biol. 2016;1390:249–72. http://www.ncbi.nlm.nih.gov/pubmed/26803634. 248. Gestermann N, Di Domizio J, Lande R, Demaria O, Frasca L, Feldmeyer L, et al. Netting neutrophils activate autoreactive B cells in lupus. J Immunol. 2018;200:3364. http://www. ncbi.nlm.nih.gov/pubmed/29632142 249. Nagy G, Koncz A, Perl A. T- and B-cell abnormalities in systemic lupus erythematosus. Crit Rev Immunol. 2005;25:123–40. http://www.ncbi.nlm.nih.gov/pubmed/15952933. 250. Moulton VR, Suarez-Fueyo A, Meidan E, Li H, Mizui M, Tsokos GC. Pathogenesis of human systemic lupus erythematosus: a cellular perspective. Trends Mol Med. 2017;23:615–35. https://linkinghub.elsevier.com/retrieve/pii/S1471491417300849. 251. Chauhan AK, Moore TL, Bi Y, Chen C. FcγRIIIa-Syk co-signal modulates CD4+ T-cell response and up-regulates toll-like receptor (TLR) expression. J Biol Chem. 2016;291:1368–86. https://linkinghub.elsevier.com/retrieve/pii/S002192582036169X. 252. Blanco P, Ueno H, Schmitt N. T follicular helper (Tfh) cells in lupus: activation and involvement in SLE pathogenesis. Eur J Immunol. 2016;46:281–90. http://www.ncbi.nlm.nih.gov/ pubmed/26614103. 253. Ohl K, Tenbrock K. Regulatory T cells in systemic lupus erythematosus. Eur J Immunol. 2015;45:344–55. https://onlinelibrary.wiley.com/doi/10.1002/eji.201344280. 254. Rother N, van der Vlag J. Disturbed T cell signaling and altered Th17 and regulatory T cell subsets in the pathogenesis of systemic lupus erythematosus. Front Immunol. 2015;6:610. http://www.ncbi.nlm.nih.gov/pubmed/26648939. 255. Crispin JC, Hedrich CM, Suárez-Fueyo A, Comte D, Tsokos GC. SLE-associated defects promote altered T cell function. Crit Rev Immunol. 2017;37:39–58. http://www.dl.begellhouse. com/journals/2ff21abf44b19838,7906ba2402487331,4cda3c1037fb3a8c.html. 256. Dörner T, Giesecke C, Lipsky PE. Mechanisms of B cell autoimmunity in SLE. Arthritis Res Ther. 2011;13:243. http://arthritis-research.biomedcentral.com/articles/10.1186/ar3433. 257. Nutt SL, Hodgkin PD, Tarlinton DM, Corcoran LM. The generation of antibody-secreting plasma cells. Nat Rev Immunol. 2015;15:160–71. http://www.ncbi.nlm.nih.gov/ pubmed/25698678. 258. Dörner T, Jacobi AM, Lee J, Lipsky PE. Abnormalities of B cell subsets in patients with systemic lupus erythematosus. J Immunol Methods. 2011;363:187–97. http://linkinghub. elsevier.com/retrieve/pii/S0022175910001742. 259. Chang N-H, Li TT, Kim JJ, Landolt-Marticorena C, Fortin PR, Gladman DD, et al. Interferon-α induces altered transitional B cell signaling and function in Systemic Lupus Erythematosus. J Autoimmun. 2015;58:100–10. http://linkinghub.elsevier.com/retrieve/pii/ S0896841115000104. 260. Ehlers M, Fukuyama H, McGaha TL, Aderem A, Ravetch JV. TLR9/MyD88 signaling is required for class switching to pathogenic IgG2a and 2b autoantibodies in SLE. J Exp Med. 2006;203:553–61. http://www.ncbi.nlm.nih.gov/pubmed/16492804. 261. Guerrier T, Youinou P, Pers J-O, Jamin C. TLR9 drives the development of transitional B cells towards the marginal zone pathway and promotes autoimmunity. J Autoimmun. 2012;39:173–9. http://www.ncbi.nlm.nih.gov/pubmed/22695187. 262. Friebus-Kardash J, Branco L, Ribi C, Chizzolini C, Huynh-Do U, Dubler D, et al. Immune complexes containing serum B-cell activating factor and immunoglobulin G correlate with disease activity in systemic lupus erythematosus. Nephrol Dial Transplant. 2018;33:54–64. http://www.ncbi.nlm.nih.gov/pubmed/28992184. 263. Malkiel S, Barlev AN, Atisha-Fregoso Y, Suurmond J, Diamond B. Plasma cell differentiation pathways in systemic lupus erythematosus. Front Immunol. 2018;9:427. http://journal. frontiersin.org/article/10.3389/fimmu.2018.00427/full. 264. Guo W, Smith D, Aviszus K, Detanico T, Heiser RA, Wysocki LJ. Somatic hypermutation as a generator of antinuclear antibodies in a murine model of systemic autoimmunity. J Exp Med. 2010;207:2225–37. http://www.jem.org/lookup/doi/10.1084/jem.20092712.
552
7 DAMPs in Systemic Autoimmune Diseases
265. Mietzner B, Tsuiji M, Scheid J, Velinzon K, Tiller T, Abraham K, et al. Autoreactive IgG memory antibodies in patients with systemic lupus erythematosus arise from nonreactive and polyreactive precursors. Proc Natl Acad Sci U S A. 2008;105:9727–32. http://www.pnas.org/ cgi/doi/10.1073/pnas.0803644105. 266. Bartsch YC, Rahmöller J, Mertes MMM, Eiglmeier S, Lorenz FKM, Stoehr AD, et al. Sialylated autoantigen-reactive IgG antibodies attenuate disease development in autoimmune mouse models of lupus nephritis and rheumatoid arthritis. Front Immunol. 2018;9:1183. https://www.frontiersin.org/article/10.3389/fimmu.2018.01183/full. 267. Sharapova TN, Romanova EA, Soshnikova NV, Belogurov AA, Lomakin YA, Sashchenko LP, et al. Autoantibodies from SLE patients induce programmed cell death in murine fibroblast cells through interaction with TNFR1 receptor. Sci Rep. 2020;10:11144. http://www. nature.com/articles/s41598-020-68088-x. 268. Granger V, Peyneau M, Chollet-Martin S, de Chaisemartin L. Neutrophil extracellular traps in autoimmunity and allergy: immune complexes at work. Front Immunol. 2019;10:2824. https://www.frontiersin.org/article/10.3389/fimmu.2019.02824/full. 269. Lande R, Ganguly D, Facchinetti V, Frasca L, Conrad C, Gregorio J, et al. Neutrophils activate plasmacytoid dendritic cells by releasing Self-DNA–peptide complexes in systemic lupus erythematosus. Sci Transl Med. 2011;3:73ra19. https://www.science.org/doi/10.1126/ scitranslmed.3001180. 270. Garcia-Romo GS, Caielli S, Vega B, Connolly J, Allantaz F, Xu Z, et al. Netting neutrophils are major inducers of type I IFN production in pediatric systemic lupus erythematosus. Sci Transl Med. 2011;3:73ra20. https://www.science.org/doi/10.1126/ scitranslmed.3001201. 271. Dam LS, Kraaij T, Kamerling SWA, Bakker JA, Scherer UH, Rabelink TJ, et al. Intrinsically distinct role of neutrophil extracellular trap formation in antineutrophil cytoplasmic antibody–associated vasculitis compared to systemic lupus erythematosus. Arthritis Rheum. 2019;71:2047–58. https://onlinelibrary.wiley.com/doi/10.1002/art.41047. 272. Behnen M, Leschczyk C, Möller S, Batel T, Klinger M, Solbach W, et al. Immobilized immune complexes induce neutrophil extracellular trap release by human neutrophil granulocytes via FcγRIIIB and Mac-1. J Immunol. 2014;193:1954–65. http://www.jimmunol.org/ lookup/doi/10.4049/jimmunol.1400478. 273. Carmona-Rivera C, Kaplan MJ. Low-density granulocytes: a distinct class of neutrophils in systemic autoimmunity. Semin Immunopathol. 2013;35:455–63. http://link.springer. com/10.1007/s00281-013-0375-7. 274. Gallucci S, Meka S, Gamero AM. Abnormalities of the type I interferon signaling pathway in lupus autoimmunity. Cytokine. 2021;146:155633. https://linkinghub.elsevier.com/retrieve/ pii/S1043466621002192. 275. Flores-Mendoza G, Sansón SP, Rodríguez-Castro S, Crispín JC, Rosetti F. Mechanisms of tissue injury in lupus nephritis. Trends Mol Med. 2018;24:364–78. http://www.ncbi.nlm.nih. gov/pubmed/29526595. 276. Saxena R, Mahajan T, Mohan C. Lupus nephritis: current update. Arthritis Res Ther. 2011;13:240. http://arthritis-research.biomedcentral.com/articles/10.1186/ar3378. 277. Yung S, Yap DY, Chan TM. Recent advances in the understanding of renal inflammation and fibrosis in lupus nephritis. F1000Research. 2017;6:874. http://www.ncbi.nlm.nih.gov/ pubmed/28663794. 278. Bao L, Cunningham PN, Quigg RJ. Complement in lupus nephritis: new perspectives. Kidney Dis. 2015;1:91–9. http://www.ncbi.nlm.nih.gov/pubmed/27536669. 279. Devarapu SK, Anders H-J. Toll-like receptors in lupus nephritis. J Biomed Sci. 2018;25:35. http://www.ncbi.nlm.nih.gov/pubmed/29650017. 280. Marshak-Rothstein A, Rifkin IR. Immunologically active autoantigens: the role of toll-like receptors in the development of chronic inflammatory disease. Annu Rev Immunol. 2007;25:419–41. http://www.annualreviews.org/doi/10.1146/annurev. immunol.22.012703.104514.
References
553
281. Kwok S-K, Tsokos GC. New insights into the role of renal resident cells in the pathogenesis of lupus nephritis. Korean J Intern Med. 2018;33:284–9. http://www.ncbi.nlm.nih.gov/ pubmed/29320847. 282. Yurasov S, Tiller T, Tsuiji M, Velinzon K, Pascual V, Wardemann H, et al. Persistent expression of autoantibodies in SLE patients in remission. J Exp Med. 2006;203:2255–61. http:// www.jem.org/lookup/doi/10.1084/jem.20061446. 283. Anders H-J, Saxena R, Zhao M, Parodis I, Salmon JE, Mohan C. Lupus nephritis. Nat Rev Dis Prim. 2020;6:7. http://www.nature.com/articles/s41572-019-0141-9. 284. Grönhagen CM, Nyberg F. Cutaneous lupus erythematosus: an update. Indian Dermatol Online J. 2014;5:7–13. http://www.idoj.in/text.asp?2014/5/1/7/126020. 285. Hejazi EZ, Werth VP. Cutaneous lupus erythematosus: an update on pathogenesis, diagnosis and treatment. Am J Clin Dermatol. 2016;17:135–46. http://www.ncbi.nlm.nih.gov/ pubmed/26872954. 286. Deng G-M. Pathogenesis of skin injury of systemic lupus erythematosus. Curr Rheumatol Rep. 2018;20:5. http://www.ncbi.nlm.nih.gov/pubmed/29464447. 287. Bortoluzzi A, Scirè CA, Govoni M. Attribution of neuropsychiatric manifestations to systemic lupus erythematosus. Front Med. 2018;5:68. http://www.ncbi.nlm.nih.gov/ pubmed/29594125. 288. Ho RC, Ong H, Thiaghu C, Lu Y, Ho CS, Zhang MW. Genetic variants that are associated with neuropsychiatric systemic lupus erythematosus. J Rheumatol. 2016;43:541–51. http:// www.jrheum.org/cgi/doi/10.3899/jrheum.150884. 289. Gelb S, Stock AD, Anzi S, Putterman C, Ben-Zvi A. Mechanisms of neuropsychiatric lupus: the relative roles of the blood-cerebrospinal fluid barrier versus blood-brain barrier. J Autoimmun. 2018;91:34. http://www.ncbi.nlm.nih.gov/pubmed/29627289 290. Jacob A, Hack B, Chiang E, Garcia JGN, Quigg RJ, Alexander JJ. C5a alters blood-brain barrier integrity in experimental lupus. FASEB J. 2010;24:1682–8. http://www.ncbi.nlm.nih. gov/pubmed/20065106. 291. Ho RC, Thiaghu C, Ong H, Lu Y, Ho CS, Tam WW, et al. A meta-analysis of serum and cerebrospinal fluid autoantibodies in neuropsychiatric systemic lupus erythematosus. Autoimmun Rev. 2016;15:124–38. http://linkinghub.elsevier.com/retrieve/pii/S156899721500213X. 292. Arinuma Y. Antibodies and the brain. Curr Opin Neurol. 2018;31:1. http://www.ncbi.nlm. nih.gov/pubmed/29474315. 293. Pylaeva E, Bordbari S, Spyra I, Decker AS, Häussler S, Vybornov V, et al. Detrimental effect of type I IFNs during acute lung infection with pseudomonas aeruginosa is mediated through the stimulation of neutrophil NETosis. Front Immunol. 2019;10:2190. https://www.frontiersin.org/article/10.3389/fimmu.2019.02190/full. 294. Yang D, Liang Y, Zhao S, Ding Y, Zhuang Q, Shi Q, et al. ZBP1 mediates interferon- induced necroptosis. Cell Mol Immunol. 2020;17:356–68. https://www.nature.com/articles/ s41423-019-0237-x. 295. Malireddi RKS, Kanneganti T-D. Role of type I interferons in inflammasome activation, cell death, and disease during microbial infection. Front Cell Infect Microbiol. 2013;3:77. http:// journal.frontiersin.org/article/10.3389/fcimb.2013.00077/abstract. 296. Labzin LI, Lauterbach MAR, Latz E. Interferons and inflammasomes: cooperation and counterregulation in disease. J Allergy Clin Immunol. 2016;138:37–46. https://linkinghub.elsevier.com/retrieve/pii/S0091674916303591. 297. Minichiello E, Semerano L, Boissier M-C. Time trends in the incidence, prevalence, and severity of rheumatoid arthritis: a systematic literature review. Jt Bone Spine. 2016;83:625–30. https://linkinghub.elsevier.com/retrieve/pii/S1297319X16301294. 298. van der Woude D, van der Helm-van Mil AHM. Update on the epidemiology, risk factors, and disease outcomes of rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2018;32:174–87. https://linkinghub.elsevier.com/retrieve/pii/S1521694218300688. 299. Almutairi K, Nossent J, Preen D, Keen H, Inderjeeth C. The global prevalence of rheumatoid arthritis: a meta-analysis based on a systematic review. Rheumatol Int. 2021;41:863–77. http://link.springer.com/10.1007/s00296-020-04731-0.
554
7 DAMPs in Systemic Autoimmune Diseases
300. Malmström V, Catrina AI, Klareskog L. The immunopathogenesis of seropositive rheumatoid arthritis: from triggering to targeting. Nat Rev Immunol. 2017;17:60–75. http://www.nature. com/articles/nri.2016.124. 301. Goodson NJ, Wiles NJ, Lunt M, Barrett EM, Silman AJ, Symmons DPM. Mortality in early inflammatory polyarthritis: cardiovascular mortality is increased in seropositive patients. Arthritis Rheum. 2002;46:2010–9. https://onlinelibrary.wiley.com/doi/10.1002/art.10419. 302. Bugatti S, Sakellariou G, Luvaro T, Greco MI, Manzo A. Clinical, imaging, and pathological suppression of synovitis in rheumatoid arthritis: is the disease curable? Front Med. 2018;5:140. http://journal.frontiersin.org/article/10.3389/fmed.2018.00140/full. 303. Smolen JS, Aletaha D, Barton A, Burmester GR, Emery P, Firestein GS, et al. Rheumatoid arthritis. Nat Rev Dis Prim. 2018;4:18001. http://www.ncbi.nlm.nih.gov/pubmed/29417936. 304. Figus FA, Piga M, Azzolin I, McConnell R, Iagnocco A. Rheumatoid arthritis: extra-articular manifestations and comorbidities. Autoimmun Rev. 2021;20:102776. https://linkinghub.elsevier.com/retrieve/pii/S1568997221000392. 305. Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO, et al. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Ann Rheum Dis. 2010;69:1580–8. https://ard. bmj.com/lookup/doi/10.1136/ard.2010.138461. 306. Asquith DL, Miller AM, McInnes IB, Liew FY. Animal models of rheumatoid arthritis. Eur J Immunol. 2009;39:2040–4. http://www.ncbi.nlm.nih.gov/pubmed/19672892. 307. Choudhary N, Bhatt LK, Prabhavalkar KS. Experimental animal models for rheumatoid arthritis. Immunopharmacol Immunotoxicol. 2018;40:193–200. https://www.tandfonline. com/doi/full/10.1080/08923973.2018.1434793. 308. Angelotti F, Parma A, Cafaro G, Capecchi R, Alunno A, Puxeddu I. One year in review 2017: pathogenesis of rheumatoid arthritis. Clin Exp Rheumatol. 2017;35:368–78. http://www. ncbi.nlm.nih.gov/pubmed/28631608. 309. Calabresi E, Petrelli F, Bonifacio AF, Puxeddu I, Alunno A. One year in review 2018: pathogenesis of rheumatoid arthritis. Clin Exp Rheumatol. 2018;36:175–84. http://www.ncbi.nlm. nih.gov/pubmed/29716677. 310. Kampstra ASB, Toes REM. HLA class II and rheumatoid arthritis: the bumpy road of revelation. Immunogenetics. 2017;69:597–603. http://www.ncbi.nlm.nih.gov/pubmed/28695293. 311. Guo Q, Wang Y, Xu D, Nossent J, Pavlos NJ, Xu J. Rheumatoid arthritis: pathological mechanisms and modern pharmacologic therapies. Bone Res. 2018;6:15. http://www.ncbi.nlm.nih. gov/pubmed/29736302. 312. Croia C, Bursi R, Sutera D, Petrelli F, Alunno A, Puxeddu I. One year in review 2019: pathogenesis of rheumatoid arthritis. Clin Exp Rheumatol. 2019;37:347–57. https://pubmed.ncbi. nlm.nih.gov/31111823/. 313. Giannini D, Antonucci M, Petrelli F, Bilia S, Alunno A, Puxeddu I. One year in review 2020: pathogenesis of rheumatoid arthritis. Clin Exp Rheumatol. 2020;38:387–97. https://pubmed. ncbi.nlm.nih.gov/32324123/. 314. Testa D, Calvacchi S, Petrelli F, Giannini D, Bilia S, Alunno A, et al. One year in review 2021: pathogenesis of rheumatoid arthritis. Clin Exp Rheumatol. 2021;39:445–52. https:// pubmed.ncbi.nlm.nih.gov/34018918/. 315. Zhang F, Wei K, Slowikowski K, Fonseka CY, Rao DA, Kelly S, et al. Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry. Nat Immunol. 2019;20:928–42. http://www.nature.com/articles/ s41590-019-0378-1. 316. Bartok B, Firestein GS. Fibroblast-like synoviocytes: key effector cells in rheumatoid arthritis. Immunol Rev. 2010;233:233–55. https://onlinelibrary.wiley.com/doi/10.1111/j.0105-289 6.2009.00859.x. 317. Kiener HP, Watts GFM, Cui Y, Wright J, Thornhill TS, Sköld M, et al. Synovial fibroblasts self-direct multicellular lining architecture and synthetic function in three-dimensional organ culture. Arthritis Rheum. 2010;62:742–52. https://onlinelibrary.wiley.com/doi/10.1002/ art.27285.
References
555
318. Smith MD. The normal synovium. Open Rheumatol J. 2011;5:100–6. http://benthamopen. com/ABSTRACT/TORJ-5-100. 319. Bottini N, Firestein GS. Duality of fibroblast-like synoviocytes in RA: passive responders and imprinted aggressors. Nat Rev Rheumatol. 2013;9:24–33. http://www.nature.com/ articles/nrrheum.2012.190. 320. Ganesan R, Rasool M. Fibroblast-like synoviocytes-dependent effector molecules as a critical mediator for rheumatoid arthritis: current status and future directions. Int Rev Immunol. 2017;36:20–30. https://www.tandfonline.com/doi/full/10.1080/08830185.2016.1269175. 321. Yoshitomi H. Regulation of immune responses and chronic inflammation by fibroblast-like synoviocytes. Front Immunol. 2019;10:1395. https://www.frontiersin.org/article/10.3389/ fimmu.2019.01395/full. 322. Nygaard G, Firestein GS. Restoring synovial homeostasis in rheumatoid arthritis by targeting fibroblast-like synoviocytes. Nat Rev Rheumatol. 2020;16:316–33. http://www.nature.com/ articles/s41584-020-0413-5. 323. Masoumi M, Bashiri H, Khorramdelazad H, Barzaman K, Hashemi N, Sereshki HA, et al. Destructive roles of fibroblast-like synoviocytes in chronic inflammation and joint damage in rheumatoid arthritis. Inflammation. 2021;44:466–79. https://link.springer.com/10.1007/ s10753-020-01371-1. 324. Mousavi MJ, Karami J, Aslani S, Tahmasebi MN, Vaziri AS, Jamshidi A, et al. Transformation of fibroblast-like synoviocytes in rheumatoid arthritis; from a friend to foe. Autoimmun Highlights. 2021;12:3. https://autoimmunhighlights.biomedcentral.com/articles/10.1186/ s13317-020-00145-x. 325. Scherer HU, Häupl T, Burmester GR. The etiology of rheumatoid arthritis. J Autoimmun. 2020;110:102400. https://linkinghub.elsevier.com/retrieve/pii/S0896841119308431. 326. Radić M. Role of Helicobacter pylori infection in autoimmune systemic rheumatic diseases. World J Gastroenterol. 2014;20:12839–46. http://www.wjgnet.com/1007-9327/full/v20/ i36/12839.htm. 327. Deane KD, Demoruelle MK, Kelmenson LB, Kuhn KA, Norris JM, Holers VM. Genetic and environmental risk factors for rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2017;31:3–18. http://www.ncbi.nlm.nih.gov/pubmed/29221595. 328. Kudaeva FM, Speechley MR, Pope JE. A systematic review of viral exposures as a risk for rheumatoid arthritis. Semin Arthritis Rheum. 2018;48:487. http://www.ncbi.nlm.nih.gov/ pubmed/29747994 329. Trimova G, Yamagata K, Iwata S, Hirata S, Zhang T, Uemura F, et al. Tumour necrosis factor alpha promotes secretion of 14-3-3η by inducing necroptosis in macrophages. Arthritis Res Ther. 2020;22:24. http://www.ncbi.nlm.nih.gov/pubmed/32051018. 330. Chen S, Luo Z, Chen X. Hsa_circ_0044235 regulates the pyroptosis of rheumatoid arthritis via MiR-135b-5p-SIRT1 axis. Cell Cycle. 2021;20:1107–21. https://www.tandfonline.com/ doi/full/10.1080/15384101.2021.1916272. 331. Wu T, Zhang X-P, Zhang Q, Zou Y-Y, Ma J-D, Chen L-F, et al. Gasdermin-E mediated pyroptosis—a novel mechanism regulating migration, invasion and release of inflammatory cytokines in rheumatoid arthritis fibroblast-like synoviocytes. Front Cell Dev Biol. 2022;9:810635. https://www.frontiersin.org/articles/10.3389/fcell.2021.810635/full. 332. O’Neil LJ, Kaplan MJ. Neutrophils in rheumatoid arthritis: breaking immune tolerance and fueling disease. Trends Mol Med. 2019;25:215–27. https://linkinghub.elsevier.com/retrieve/ pii/S1471491418302429. 333. Song W, Ye J, Pan N, Tan C, Herrmann M. Neutrophil extracellular traps tied to rheumatoid arthritis: points to ponder. Front Immunol. 2021;11:578129. https://www.frontiersin.org/ articles/10.3389/fimmu.2020.578129/full. 334. Lee J, Luria A, Rhodes C, Raghu H, Lingampalli N, Sharpe O, et al. Nicotine drives neutrophil extracellular traps formation and accelerates collagen-induced arthritis. Rheumatology (Oxford). 2017;56:644–53. https://academic.oup.com/rheumatology/article-lookup/ doi/10.1093/rheumatology/kew449.
556
7 DAMPs in Systemic Autoimmune Diseases
335. Anaya J-M, Restrepo-Jiménez P, Ramírez-Santana C. The autoimmune ecology: an update. Curr Opin Rheumatol. 2018;30:350–60. https://journals.lww.com/00002281-20180700000010. 336. Corsiero E, Pratesi F, Prediletto E, Bombardieri M, Migliorini P. NETosis as source of autoantigens in rheumatoid arthritis. Front Immunol. 2016;7:485. http://www.ncbi.nlm.nih.gov/ pubmed/27895639. 337. Lightfoot YL, Kaplan MJ. Disentangling the role of neutrophil extracellular traps in rheumatic diseases. Curr Opin Rheumatol. 2017;29:65–70. http://www.ncbi.nlm.nih.gov/ pubmed/27755122. 338. Hedström AK, Stawiarz L, Klareskog L, Alfredsson L. Smoking and susceptibility to rheumatoid arthritis in a Swedish population-based case–control study. Eur J Epidemiol. 2018;33:415–23. http://www.ncbi.nlm.nih.gov/pubmed/29387991. 339. Svendsen AJ, Junker P, Houen G, Kyvik KO, Nielsen C, Skytthe A, et al. Incidence of chronic persistent rheumatoid arthritis and the impact of smoking: a historical twin cohort study. Arthritis Care Res. 2017;69:616–24. http://doi.wiley.com/10.1002/acr.22987. 340. Speck-Hernandez CA, Montoya-Ortiz G. Silicon, a possible link between environmental exposure and autoimmune diseases: the case of rheumatoid arthritis. Arthritis. 2012;2012:1–11. http://www.ncbi.nlm.nih.gov/pubmed/23119159. 341. Zeng P, Chen Z, Klareskog L, Alfredsson L, Bengtsson C, Jiang X. Amount of smoking, duration of smoking cessation and their interaction with silica exposure in the risk of rheumatoid arthritis among males: results from the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study. Ann Rheum Dis. 2017;77:1238. http://ard.bmj.com/ lookup/doi/10.1136/annrheumdis-2017-212145. 342. Bernatsky S, Smargiassi A, Joseph L, Awadalla P, Colmegna I, Hudson M, et al. Industrial air emissions, and proximity to major industrial emitters, are associated with anti-citrullinated protein antibodies. Environ Res. 2017;157:60–3. http://linkinghub.elsevier.com/retrieve/pii/ S0013935117303560. 343. Schmickler J, Rupprecht A, Patschan S, Patschan D, Müller GA, Haak R, et al. Cross- sectional evaluation of periodontal status and microbiologic and rheumatoid parameters in a large cohort of patients with rheumatoid arthritis. J Periodontol. 2017;88:368–79. http://doi. wiley.com/10.1902/jop.2016.160355. 344. Sakkas LI, Bogdanos DP. Multiple hit infection and autoimmunity: the dysbiotic microbiota- ACPA connection in rheumatoid arthritis. Curr Opin Rheumatol. 2018;30:403. http://www. ncbi.nlm.nih.gov/pubmed/29538012. 345. Perricone C, Ceccarelli F, Matteo S, Di Carlo G, Bogdanos DP, Lucchetti R, et al. Porphyromonas gingivalis and rheumatoid arthritis. Curr Opin Rheumatol. 2019;31:517–24. https://journals.lww.com/10.1097/BOR.0000000000000638. 346. Bin JY, Lim Y-H, Kim K-J, Park K-S, Park Y-J. Respiratory viral infections and the risk of rheumatoid arthritis. Arthritis Res Ther. 2019;21:199. https://arthritis-research.biomedcentral.com/articles/10.1186/s13075-019-1977-9. 347. Roongta R, Ghosh A. Managing rheumatoid arthritis during COVID-19. Clin Rheumatol. 2020;39:3237–44. https://link.springer.com/10.1007/s10067-020-05358-z. 348. Barra NG, Henriksbo BD, Anhê FF, Schertzer JD. The NLRP3 inflammasome regulates adipose tissue metabolism. Biochem J. 2020;477:1089–107. https://portlandpress.com/ biochemj/article/477/6/1089/222425/The-NLRP3-inflammasome-regulates-adipose-tissue. 349. Kim K, Bang S-Y, Lee H-S, Bae S-C. Update on the genetic architecture of rheumatoid arthritis. Nat Rev Rheumatol. 2017;13:13–24. http://www.ncbi.nlm.nih.gov/ pubmed/27811914. 350. Frisell T, Saevarsdottir S, Askling J. Family history of rheumatoid arthritis: an old concept with new developments. Nat Rev Rheumatol. 2016;12:335–43. http://www.nature.com/ articles/nrrheum.2016.52. 351. Suzuki A, Yamamoto K. From genetics to functional insights into rheumatoid arthritis. Clin Exp Rheumatol. 2015;33:40–3. https://pubmed.ncbi.nlm.nih.gov/26457422/.
References
557
352. Fortune MD, Guo H, Burren O, Schofield E, Walker NM, Ban M, et al. Statistical colocalization of genetic risk variants for related autoimmune diseases in the context of common controls. Nat Genet. 2015;47:839–46. http://www.ncbi.nlm.nih.gov/ pubmed/26053495. 353. Ciccacci C, Conigliaro P, Perricone C, Rufini S, Triggianese P, Politi C, et al. Polymorphisms in STAT-4, IL-10, PSORS1C1, PTPN2 and MIR146A genes are associated differently with prognostic factors in Italian patients affected by rheumatoid arthritis. Clin Exp Immunol. 2016;186:157–63. http://doi.wiley.com/10.1111/cei.12831. 354. Lee YH, Bae S-C. Associations between circulating IL-17 levels and rheumatoid arthritis and between IL-17 gene polymorphisms and disease susceptibility: a meta-analysis. Postgrad Med J. 2017;93:465–71. http://www.ncbi.nlm.nih.gov/pubmed/28069745. 355. Ha E, Bae S-C, Kim K. Large-scale meta-analysis across East Asian and European populations updated genetic architecture and variant-driven biology of rheumatoid arthritis, identifying 11 novel susceptibility loci. Ann Rheum Dis. 2021;80:558–65. https://ard.bmj.com/ lookup/doi/10.1136/annrheumdis-2020-219065. 356. Ospelt C, Gay S, Klein K. Epigenetics in the pathogenesis of RA. Semin Immunopathol. 2017;39:409–19. http://link.springer.com/10.1007/s00281-017-0621-5. 357. Zhang P, Lu Q. Genetic and epigenetic influences on the loss of tolerance in autoimmunity. Cell Mol Immunol. 2018;15:575. http://www.ncbi.nlm.nih.gov/pubmed/29503444 358. Hammaker D, Firestein GS. Epigenetics of inflammatory arthritis. Curr Opin Rheumatol. 2018;30:188–96. http://www.ncbi.nlm.nih.gov/pubmed/29194108. 359. Nemtsova MV, Zaletaev DV, Bure IV, Mikhaylenko DS, Kuznetsova EB, Alekseeva EA, et al. Epigenetic changes in the pathogenesis of rheumatoid arthritis. Front Genet. 2019;10:570. https://www.frontiersin.org/article/10.3389/fgene.2019.00570/full. 360. Nguyen H, James EA. Immune recognition of citrullinated epitopes. Immunology. 2016;149:131–8. http://doi.wiley.com/10.1111/imm.12640. 361. Darrah E, Andrade F. Rheumatoid arthritis and citrullination. Curr Opin Rheumatol. 2018;30:72–8. http://www.ncbi.nlm.nih.gov/pubmed/28937414. 362. Tilvawala R, Nguyen SH, Maurais AJ, Nemmara VV, Nagar M, Salinger AJ, et al. The rheumatoid arthritis-associated citrullinome. Cell Chem Biol. 2018;25:691. http://linkinghub. elsevier.com/retrieve/pii/S2451945618300813 363. Kwon E-J, Ju JH. Impact of posttranslational modification in pathogenesis of rheumatoid arthritis: focusing on citrullination, carbamylation, and acetylation. Int J Mol Sci. 2021;22:10576. https://www.mdpi.com/1422-0067/22/19/10576. 364. Konig MF, Andrade F. A critical reappraisal of neutrophil extracellular traps and NETosis mimics based on differential requirements for protein citrullination. Front Immunol. 2016;7:461. http://journal.frontiersin.org/article/10.3389/fimmu.2016.00461/full. 365. Ai R, Laragione T, Hammaker D, Boyle DL, Wildberg A, Maeshima K, et al. Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes. Nat Commun. 2018;9:1921. http://www.ncbi.nlm.nih.gov/pubmed/29765031. 366. Karami J, Aslani S, Tahmasebi MN, Mousavi MJ, Sharafat Vaziri A, Jamshidi A, et al. Epigenetics in rheumatoid arthritis; fibroblast-like synoviocytes as an emerging paradigm in the pathogenesis of the disease. Immunol Cell Biol. 2020;98:171–86. https://onlinelibrary. wiley.com/doi/10.1111/imcb.12311. 367. Sorice M, Iannuccelli C, Manganelli V, Capozzi A, Alessandri C, Lococo E, et al. Autophagy generates citrullinated peptides in human synoviocytes: a possible trigger for anti- citrullinated peptide antibodies. Rheumatology. 2016;55:1374–85. http://www.ncbi.nlm.nih. gov/pubmed/27074807. 368. Catrina AI, Joshua V, Klareskog L, Malmström V. Mechanisms involved in triggering rheumatoid arthritis. Immunol Rev. 2016;269:162–74. http://doi.wiley.com/10.1111/imr.12379. 369. Pianta A, Arvikar SL, Strle K, Drouin EE, Wang Q, Costello CE, et al. Two rheumatoid arthritis–specific autoantigens correlate microbial immunity with autoimmune responses in joints. J Clin Invest. 2017;127:2946–56. http://www.ncbi.nlm.nih.gov/pubmed/28650341.
558
7 DAMPs in Systemic Autoimmune Diseases
370. Ospelt C, Bang H, Feist E, Camici G, Keller S, Detert J, et al. Carbamylation of vimentin is inducible by smoking and represents an independent autoantigen in rheumatoid arthritis. Ann Rheum Dis. 2017;76:1176–83. http://www.ncbi.nlm.nih.gov/pubmed/28183721. 371. Grönwall C, Amara K, Hardt U, Krishnamurthy A, Steen J, Engström M, et al. Autoreactivity to malondialdehyde-modifications in rheumatoid arthritis is linked to disease activity and synovial pathogenesis. J Autoimmun. 2017;84:29–45. http://linkinghub.elsevier.com/ retrieve/pii/S0896841117302834. 372. Poulsen TBG, Damgaard D, Jørgensen MM, Senolt L, Blackburn JM, Nielsen CH, et al. Identification of novel native autoantigens in rheumatoid arthritis. Biomedicines. 2020;8:141. https://www.mdpi.com/2227-9059/8/6/141. 373. Pottecher J, Meyer A, Wenceslau CF, Timmermans K, Hauser CJ, Land WG. Editorial: Trauma-induced, DAMP-mediated remote organ injury, and immunosuppression in the acutely Ill patient. Front Immunol. 2019;10:1971. https://doi.org/10.3389/ FIMMU.2019.01971/BIBTEX. 374. O’Reilly S. Pound the alarm: danger signals in rheumatic diseases. Clin Sci (Lond). 2015;128:297–305. http://www.ncbi.nlm.nih.gov/pubmed/25394289. 375. Nefla M, Holzinger D, Berenbaum F, Jacques C. The danger from within: alarmins in arthritis. Nat Rev Rheumatol. 2016;12:669–83. http://www.nature.com/articles/nrrheum.2016.162. 376. Roh JS, Sohn DH. Damage-associated molecular patterns in inflammatory diseases. Immune Netw. 2018;18:e27. https://immunenetwork.org/DOIx.php?id=10.4110/in.2018.18.e27. 377. Wu Y, Li X, Wu S, Niu X, Yin S, Huang C, et al. Role of the S100 protein family in rheumatoid arthritis. Arthritis Res Ther. 2022;24:35. https://arthritis-research.biomedcentral.com/ articles/10.1186/s13075-022-02727-8. 378. Youssef P, Roth J, Frosch M, Costello P, Fitzgerald O, Sorg C, et al. Expression of myeloid related proteins (MRP) 8 and 14 and the MRP8/14 heterodimer in rheumatoid arthritis synovial membrane. J Rheumatol. 1999;26:2523–8. http://www.ncbi.nlm.nih. gov/pubmed/10606357. 379. Foell D, Kane D, Bresnihan B, Vogl T, Nacken W, Sorg C, et al. Expression of the pro- inflammatory protein S100A12 (EN-RAGE) in rheumatoid and psoriatic arthritis. Rheumatology (Oxford). 2003;42:1383–9. https://academic.oup.com/rheumatology/ article-lookup/doi/10.1093/rheumatology/keg385. 380. Marsman G, Zeerleder S, Luken BM. Extracellular histones, cell-free DNA, or nucleosomes: differences in immunostimulation. Cell Death Dis. 2016;7:e2518. http://www.nature.com/ articles/cddis2016410. 381. Silk E, Zhao H, Weng H, Ma D. The role of extracellular histone in organ injury. Cell Death Dis. 2017;8:e2812. http://www.nature.com/articles/cddis201752. 382. Neumann E, Hasseli R, Lange U, Müller-Ladner U. The role of extracellular nucleic acids in rheumatoid arthritis. Curr Pharm Biotechnol. 2019;19:1182–8. http://www.eurekaselect. com/168717/article. 383. Hashimoto T, Yoshida K, Hashiramoto A, Matsui K. Cell-free DNA in rheumatoid arthritis. Int J Mol Sci. 2021;22:8941. https://www.mdpi.com/1422-0067/22/16/8941. 384. Dong C, Liu Y, Sun C, Liang H, Dai L, Shen J, et al. Identification of specific joint- inflammatogenic cell-free DNA molecules from synovial fluids of patients with rheumatoid arthritis. Front Immunol. 2020;11:662. https://www.frontiersin.org/article/10.3389/ fimmu.2020.00662/full. 385. Li R, Lin W, Kuang Y, Wang J, Xu S, Shen C, et al. cGAS/STING signaling in the regulation of rheumatoid synovial aggression. Ann Transl Med. 2022;10:431. https://atm.amegroups. com/article/view/91059/html. 386. Zimmermann-Geller B, Köppert S, Fischer S, Cabrera-Fuentes HA, Lefèvre S, Rickert M, et al. Influence of extracellular RNAs, released by rheumatoid arthritis synovial fibroblasts, on their adhesive and invasive properties. J Immunol. 2016;197:2589–97. http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.1501580. 387. Goh FG, Piccinini AM, Krausgruber T, Udalova IA, Midwood KS. Transcriptional regulation of the endogenous danger signal tenascin-C: a novel autocrine loop in inflam-
References
559
mation. J Immunol. 2010;184:2655–62. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.0903359. 388. Raza K, Schwenzer A, Juarez M, Venables P, Filer A, Buckley CD, et al. Detection of antibodies to citrullinated tenascin-C in patients with early synovitis is associated with the development of rheumatoid arthritis. RMD Open. 2016;2:e000318. http://www.ncbi.nlm.nih.gov/ pubmed/27933208. 389. Sanchez-Pernaute O, Filkova M, Gabucio A, Klein M, Maciejewska-Rodrigues H, Ospelt C, et al. Citrullination enhances the pro-inflammatory response to fibrin in rheumatoid arthritis synovial fibroblasts. Ann Rheum Dis. 2013;72:1400–6. http://ard.bmj.com/lookup/ doi/10.1136/annrheumdis-2012-201906. 390. Guillou C, Fréret M, Fondard E, Derambure C, Avenel G, Golinski M-L, et al. Soluble alpha- enolase activates monocytes by CD14-dependent TLR4 signalling pathway and exhibits a dual function. Sci Rep. 2016;6:23796. http://www.ncbi.nlm.nih.gov/pubmed/27025255. 391. Thiagarajan PS, Yakubenko VP, Elsori DH, Yadav SP, Willard B, Tan CD, et al. Vimentin is an endogenous ligand for the pattern recognition receptor Dectin-1. Cardiovasc Res. 2013;99:494–504. http://www.ncbi.nlm.nih.gov/pubmed/23674515. 392. Forsman H, Islander U, Andréasson E, Andersson A, Önnheim K, Karlström A, et al. Galectin 3 aggravates joint inflammation and destruction in antigen-induced arthritis. Arthritis Rheum. 2011;63:445–54. https://onlinelibrary.wiley.com/doi/10.1002/art.30118. 393. Nielsen M, Køster D, Greisen S, Troldborg A, Stengaard-Pedersen K, Junker P, et al. Increased synovial galectin-3 induce inflammatory fibroblast activation and osteoclastogenesis in patients with rheumatoid arthritis. Scand J Rheumatol. 2022:1–9. https://www.tandfonline.com/doi/full/10.1080/03009742.2021.1992860. 394. Umekita K, Miyauchi S, Nomura H, Umeki K, Okayama A. Neutrophil-derived lactoferrin induces the inflammatory responses of rheumatoid arthritis synovial fibroblasts via Toll-like receptor 4. Clin Exp Rheumatol. 2019;37:834–41. https://pubmed.ncbi.nlm.nih. gov/30767875/. 395. Hu L, Hu X, Long K, Gao C, Dong H-L, Zhong Q, et al. Extraordinarily potent proinflammatory properties of lactoferrin-containing immunocomplexes against human monocytes and macrophages. Sci Rep. 2017;7:4230. http://www.nature.com/articles/s41598-017-04275-7. 396. Burska A, Boissinot M, Ponchel F. Cytokines as biomarkers in rheumatoid arthritis. Mediat Inflamm. 2014;2014:1–24. http://www.hindawi.com/journals/mi/2014/545493/. 397. Khandpur R, Carmona-Rivera C, Vivekanandan-Giri A, Gizinski A, Yalavarthi S, Knight JS, et al. NETs are a source of citrullinated autoantigens and stimulate inflammatory responses in rheumatoid arthritis. Sci Transl Med. 2013;5:178ra40. https://www.science.org/doi/10.1126/ scitranslmed.3005580. 398. Shammas RM, Ranganath VK, Paulus HE. Remission in rheumatoid arthritis. Curr Rheumatol Rep. 2010;12:355–62. http://link.springer.com/10.1007/s11926-010-0121-2. 399. Yang Y, Hutchinson P, Morand EF. Inhibitory effect of annexin I on synovial inflammation in rat adjuvant arthritis. Arthritis Rheum. 1999;42:1538–44. https://pubmed.ncbi.nlm.nih. gov/10403283/. 400. Haridas V, Shetty P, Sarathkumar E, Bargale A, Vishwanatha JK, Patil V, et al. Reciprocal regulation of pro-inflammatory Annexin A2 and anti-inflammatory Annexin A1 in the pathogenesis of rheumatoid arthritis. Mol Biol Rep. 2019;46:83–95. http://link.springer.com/10.1007/ s11033-018-4448-5. 401. Akaogi J, Nozaki T, Satoh M, Yamada H. Role of PGE2 and EP receptors in the pathogenesis of rheumatoid arthritis and as a novel therapeutic strategy. Endocr Metab Immune Disord Drug Targets. 2006;6:383–94. http://www.eurekaselect.com/openurl/content.php?genre=art icle&issn=1871-5303&volume=6&issue=4&spage=383. 402. Chan MM-Y, Moore AR. Resolution of inflammation in murine autoimmune arthritis is disrupted by cyclooxygenase-2 inhibition and restored by prostaglandin E2-mediated lipoxin A4 production. J Immunol. 2010;184:6418–26. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.0903816. 403. Gomez PF, Pillinger MH, Attur M, Marjanovic N, Dave M, Park J, et al. Resolution of inflammation: prostaglandin E 2 dissociates nuclear trafficking of individual NF-κB subunits (p65,
560
7 DAMPs in Systemic Autoimmune Diseases
p50) in stimulated rheumatoid synovial fibroblasts. J Immunol. 2005;175:6924–30. http:// www.jimmunol.org/lookup/doi/10.4049/jimmunol.175.10.6924. 404. Zaninelli TH, Fattori V, Verri WA. Harnessing inflammation resolution in arthritis: current understanding of specialized pro-resolving lipid mediators’ contribution to arthritis physiopathology and future perspectives. Front Physiol. 2021;12:729134. https://www.frontiersin. org/articles/10.3389/fphys.2021.729134/full. 405. Elshabrawy HA, Essani AE, Szekanecz Z, Fox DA, Shahrara S. TLRs, future potential therapeutic targets for RA. Autoimmun Rev. 2017;16:103–13. http://www.ncbi.nlm.nih.gov/ pubmed/27988432. 406. Piccinini AM, Williams L, McCann FE, Midwood KS. Investigating the role of toll-like receptors in models of arthritis. Methods Mol Biol. 2016;1390:351–81. http://link.springer. com/10.1007/978-1-4939-3335-8_22. 407. Midwood KS, Piccinini AM, Sacre S. Targeting toll-like receptors in autoimmunity. Curr Drug Targets. 2009;10:1139–55. http://www.ncbi.nlm.nih.gov/pubmed/19715534. 408. Huang Q-Q, Pope RM. The role of toll-like receptors in rheumatoid arthritis. Curr Rheumatol Rep. 2009;11:357–64. http://www.ncbi.nlm.nih.gov/pubmed/19772831. 409. Taniguchi N, Kawahara K, Yone K, Hashiguchi T, Yamakuchi M, Goto M, et al. High mobility group box chromosomal protein 1 plays a role in the pathogenesis of rheumatoid arthritis as a novel cytokine. Arthritis Rheum. 2003;48:971–81. http://doi.wiley.com/10.1002/art.10859. 410. Hamada T, Torikai M, Kuwazuru A, Tanaka M, Horai N, Fukuda T, et al. Extracellular high mobility group box chromosomal protein 1 is a coupling factor for hypoxia and inflammation in arthritis. Arthritis Rheum. 2008;58:2675–85. http://doi.wiley.com/10.1002/art.23729. 411. Palmblad K, Sundberg E, Diez M, Söderling R, Aveberger A-C, Andersson U, et al. Morphological characterization of intra-articular HMGB1 expression during the course of collagen-induced arthritis. Arthritis Res Ther. 2007;9:R35. http://arthritis-research.biomedcentral.com/articles/10.1186/ar2155. 412. Andersson U, Yang H, Harris H. Extracellular HMGB1 as a therapeutic target in inflammatory diseases. Expert Opin Ther Targets. 2018;22:263–77. https://www.tandfonline.com/doi/ full/10.1080/14728222.2018.1439924. 413. Unterberger S, Davies KA, Rambhatla SB, Sacre S. Contribution of Toll-Like Receptors and the NLRP3 Inflammasome in Rheumatoid Arthritis Pathophysiology. ImmunoTargets Ther. 2021;10:285–98. https://www.dovepress.com/contribution-of-toll-like-receptors-and- the-nlrp3-inflammasome-in-rheu-peer-reviewed-fulltext-article-ITT. 414. Kong R, Sun L, Li H, Wang D. The role of NLRP3 inflammasome in the pathogenesis of rheumatic disease. Autoimmunity. 2022;55:1–7. https://www.tandfonline.com/doi/full/1 0.1080/08916934.2021.1995860. 415. Ospelt C, Brentano F, Rengel Y, Stanczyk J, Kolling C, Tak PP, et al. Overexpression of toll- like receptors 3 and 4 in synovial tissue from patients with early rheumatoid arthritis: toll-like receptor expression in early and longstanding arthritis. Arthritis Rheum. 2008;58:3684–92. http://doi.wiley.com/10.1002/art.24140. 416. de Seny D, Cobraiville G, Charlier E, Neuville S, Lutteri L, Le Goff C, et al. Apolipoprotein-A1 as a damage-associated molecular patterns protein in osteoarthritis: ex vivo and in vitro pro-inflammatory properties. PLoS One. 2015;10:e0122904. http://www.ncbi.nlm.nih.gov/ pubmed/25849372. 417. Steenvoorden MMC, Toes REM, Ronday HK, Huizinga TWJ, DeGroot J. RAGE activation induces invasiveness of RA fibroblast-like synoviocytes in vitro. Clin Exp Rheumatol. 2007;25:740–2. https://pubmed.ncbi.nlm.nih.gov/18078623/. 418. Li Y, Xu P, Xu K, Cai Y-S, Sun M, Yang L, et al. Methotrexate affects HMGB1 expression in rheumatoid arthritis, and the downregulation of HMGB1 prevents rheumatoid arthritis progression. Mol Cell Biochem. 2016;420:161–70. http://link.springer.com/10.1007/ s11010-016-2783-1. 419. Tirone M, Tran NL, Ceriotti C, Gorzanelli A, Canepari M, Bottinelli R, et al. High mobility group box 1 orchestrates tissue regeneration via CXCR4. J Exp Med. 2018;215:303–18. https:// rupress.org/jem/article/215/1/303/42473/High-mobility-group-box-1-orchestrates-tissue.
References
561
420. Di Ceglie I, Kruisbergen NNL, van den Bosch MHJ, van Lent PLEM. Fc-gamma receptors and S100A8/A9 cause bone erosion during rheumatoid arthritis. Do they act as partners in crime? Rheumatology. 2019;58:1331–43. https://academic.oup.com/rheumatology/ article/58/8/1331/5513254. 421. Schett G. Resolution of inflammation in arthritis. Semin Immunopathol. 2019;41:675–9. http://link.springer.com/10.1007/s00281-019-00768-x. 422. Pincus T, Kavanaugh A, Aletaha D, Smolen J. Complexities in defining remission in rheumatic diseases. Clin Exp Rheumatol. 2006;24:S1. https://pubmed.ncbi.nlm.nih.gov/17083755/. 423. Perretti M, Norling LV. Actions of SPM in regulating host responses in arthritis. Mol Asp Med. 2017;58:57–64. https://linkinghub.elsevier.com/retrieve/pii/S0098299717300249. 424. Arnardottir HH, Dalli J, Norling LV, Colas RA, Perretti M, Serhan CN. Resolvin D3 is dysregulated in arthritis and reduces arthritic inflammation. J Immunol. 2016;197:2362–8. http:// www.jimmunol.org/lookup/doi/10.4049/jimmunol.1502268. 425. Norling LV, Headland SE, Dalli J, Arnardottir HH, Haworth O, Jones HR, et al. Proresolving and cartilage-protective actions of resolvin D1 in inflammatory arthritis. JCI Insight. 2016;1:e85922. https://insight.jci.org/articles/view/85922. 426. Hashimoto A, Hayashi I, Murakami Y, Sato Y, Kitasato H, Matsushita R, et al. Antiinflammatory mediator lipoxin A4 and its receptor in synovitis of patients with rheumatoid arthritis. J Rheumatol. 2007;34:2144. https://pubmed.ncbi.nlm.nih.gov/17918787/. 427. Jin S, Chen H, Li Y, Zhong H, Sun W, Wang J, et al. Maresin 1 improves the Treg/Th17 imbalance in rheumatoid arthritis through miR-21. Ann Rheum Dis. 2018;77:1644–52. https://ard. bmj.com/lookup/doi/10.1136/annrheumdis-2018-213511. 428. Sano Y, Toyoshima S, Miki Y, Taketomi Y, Ito M, Lee H, et al. Activation of inflammation and resolution pathways of lipid mediators in synovial fluid from patients with severe rheumatoid arthritis compared with severe osteoarthritis. Asia Pac Allergy. 2020;10:e21. https:// apallergy.org/DOIx.php?id=10.5415/apallergy.2020.10.e21 429. Sun W, Ma J, Zhao H, Xiao C, Zhong H, Ling H, et al. Resolvin D1 suppresses pannus formation via decreasing connective tissue growth factor caused by upregulation of miRNA-146a-5p in rheumatoid arthritis. Arthritis Res Ther. 2020;22:61. https://arthritis-research.biomedcentral.com/articles/10.1186/s13075-020-2133-2. 430. Yu MB, Langridge WHR. The function of myeloid dendritic cells in rheumatoid arthritis. Rheumatol Int. 2017;37:1043–51. http://www.ncbi.nlm.nih.gov/pubmed/28236220. 431. Wehr P, Purvis H, Law S-C, Thomas R. Dendritic cells, T cells and their interaction in rheumatoid arthritis. Clin Exp Immunol. 2019;196:12–27. https://academic.oup.com/cei/ article/196/1/12/6403584. 432. Lebre MC, Jongbloed SL, Tas SW, Smeets TJM, McInnes IB, Tak PP. Rheumatoid arthritis synovium contains two subsets of CD83–DC-LAMP– dendritic cells with distinct cytokine profiles. Am J Pathol. 2008;172:940–50. https://linkinghub.elsevier.com/retrieve/pii/ S0002944010618561 433. Ramos MI, Garcia S, Helder B, Aarrass S, Reedquist KA, Jacobsen SE, et al. cDC1 are required for the initiation of collagen-induced arthritis. J Transl Autoimmun. 2020;3:100066. https://linkinghub.elsevier.com/retrieve/pii/S2589909020300332. 434. Moret FM, Hack CE, van der Wurff-Jacobs KM, de Jager W, Radstake TRDJ, Lafeber FPJG, et al. Intra-articular CD1c-expressing myeloid dendritic cells from rheumatoid arthritis patients express a unique set of T cell-attracting chemokines and spontaneously induce Th1, Th17 and Th2 cell activity. Arthritis Res Ther. 2013;15:R155. http://arthritis-research. biomedcentral.com/articles/10.1186/ar4338. 435. Papadaki G, Kambas K, Choulaki C, Vlachou K, Drakos E, Bertsias G, et al. Neutrophil extracellular traps exacerbate Th1-mediated autoimmune responses in rheumatoid arthritis by promoting DC maturation. Eur J Immunol. 2016;46:2542–54. http://doi.wiley.com/10.1002/ eji.201646542. 436. Prendergast CT, Patakas A, Al-Khabouri S, McIntyre CL, McInnes IB, Brewer JM, et al. Visualising the interaction of CD4 T cells and DCs in the evolution of inflamma-
562
7 DAMPs in Systemic Autoimmune Diseases
tory arthritis. Ann Rheum Dis. 2018;77:579–88. http://ard.bmj.com/lookup/doi/10.1136/ annrheumdis-2017-212279. 437. Estrada-Capetillo L, Hernández-Castro B, Monsiváis-Urenda A, Alvarez-Quiroga C, Layseca-Espinosa E, Abud-Mendoza C, et al. Induction of Th17 lymphocytes and treg cells by monocyte-derived dendritic cells in patients with rheumatoid arthritis and systemic lupus erythematosus. Clin Dev Immunol. 2013;2013:1–9. https://www.hindawi.com/journals/ jir/2013/584303/. 438. Tran CN, Davis MJ, Tesmer LA, Endres JL, Motyl CD, Smuda C, et al. Presentation of arthritogenic peptide to antigen-specific T cells by fibroblast-like synoviocytes. Arthritis Rheum. 2007;56:1497–506. https://onlinelibrary.wiley.com/doi/10.1002/art.22573. 439. Carmona-Rivera C, Carlucci PM, Moore E, Lingampalli N, Uchtenhagen H, James E, et al. Synovial fibroblast-neutrophil interactions promote pathogenic adaptive immunity in rheumatoid arthritis. Sci Immunol. 2017;2:eaag3358. https://www.science.org/doi/10.1126/sciimmunol.aag3358. 440. Shimabukuro-Vornhagen A, García-Márquez M, Fischer RN, Iltgen-Breburda J, Fiedler A, Wennhold K, et al. Antigen-presenting human B cells are expanded in inflammatory conditions. J Leukoc Biol. 2017;101:577–87. http://doi.wiley.com/10.1189/ jlb.5A0416-182R. 441. Kondo Y, Yokosawa M, Kaneko S, Furuyama K, Segawa S, Tsuboi H, et al. Review: transcriptional regulation of CD4+ T cell differentiation in experimentally induced arthritis and rheumatoid arthritis. Arthritis Rheum. 2018;70:653–61. https://onlinelibrary.wiley.com/ doi/10.1002/art.40398. 442. Lu J, Wu J, Xia X, Peng H, Wang S. Follicular helper T cells: potential therapeutic targets in rheumatoid arthritis. Cell Mol Life Sci. 2021;78:5095–106. https://link.springer. com/10.1007/s00018-021-03839-1. 443. Jiang Q, Yang G, Liu Q, Wang S, Cui D. Function and role of regulatory T cells in rheumatoid arthritis. Front Immunol. 2021;12:626193. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.626193/full. 444. Huang Y, Wang H, Ba X, Chen Z, Wang Y, Qin K, et al. Decipher manifestations and Treg /Th17 imbalance in multi-staging rheumatoid arthritis and correlation with TSDR/RORC methylation. Mol Immunol. 2020;127:1–11. https://linkinghub.elsevier.com/retrieve/pii/ S0161589020304454. 445. Wu F, Gao J, Kang J, Wang X, Niu Q, Liu J, et al. B cells in rheumatoid arthritis: pathogenic mechanisms and treatment prospects. Front Immunol. 2021;12:750753. https://www.frontiersin.org/articles/10.3389/fimmu.2021.750753/full. 446. Bombardieri M, Lewis M, Pitzalis C. Ectopic lymphoid neogenesis in rheumatic autoimmune diseases. Nat Rev Rheumatol. 2017;13:141–54. http://www.nature.com/articles/ nrrheum.2016.217. 447. Suzuki K, Maruya M, Kawamoto S, Sitnik K, Kitamura H, Agace WW, et al. The sensing of environmental stimuli by follicular dendritic cells promotes immunoglobulin A generation in the gut. Immunity. 2010;33:71–83. https://linkinghub.elsevier.com/retrieve/pii/ S1074761310002451. 448. El Shikh MEM, El Sayed RM, Wu Y, Szakal AK, Tew JG. TLR4 on Follicular dendritic cells: an activation pathway that promotes accessory activity. J Immunol. 2007;179:4444–50. http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.179.7.4444. 449. England BR, Thiele GM, Mikuls TR. Anticitrullinated protein antibodies: origin and role in the pathogenesis of rheumatoid arthritis. Curr Opin Rheumatol. 2017;29:57–64. http:// content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00002281-201701 000-00011. 450. Volkov M, Schie KA, Woude D. Autoantibodies and B cells: the ABC of rheumatoid arthritis pathophysiology. Immunol Rev. 2020;294:148–63. https://onlinelibrary.wiley.com/ doi/10.1111/imr.12829. 451. Harre U, Georgess D, Bang H, Bozec A, Axmann R, Ossipova E, et al. Induction of osteoclastogenesis and bone loss by human autoantibodies against citrullinated vimentin. J Clin Invest. 2012;122:1791–802. http://www.jci.org/articles/view/60975.
References
563
452. Zuo Y, Deng G-M. Fc gamma receptors as regulators of bone destruction in inflammatory arthritis. Front Immunol. 2021;12:688201. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.688201/full. 453. Bidwell JP, Yang J, Robling AG. Is HMGB1 an osteocyte alarmin? J Cell Biochem. 2008;103:1671–80. https://onlinelibrary.wiley.com/doi/10.1002/jcb.21572. 454. Komori T. Cell death in chondrocytes, osteoblasts, and osteocytes. Int J Mol Sci. 2016;17:2045. http://www.ncbi.nlm.nih.gov/pubmed/27929439. 455. Nielen MMJ, Van Schaardenburg D, Reesink HW, Van De Stadt RJ, Van Der Horst-Bruinsma IE, De Koning MHMT, et al. Specific autoantibodies precede the symptoms of rheumatoid arthritis: a study of serial measurements in blood donors. Arthritis Rheum. 2004;50:380–6. https://pubmed.ncbi.nlm.nih.gov/14872479/. 456. Sparks JA, Karlson EW. The roles of cigarette smoking and the lung in the transitions between phases of preclinical rheumatoid arthritis. Curr Rheumatol Rep. 2016;18:15. https:// www.ncbi.nlm.nih.gov/pmc/articles/PMC4941234/ 457. Reynisdottir G, Karimi R, Joshua V, Olsen H, Hensvold AH, Harju A, et al. Structural changes and antibody enrichment in the lungs are early features of anti-citrullinated protein antibody-positive rheumatoid arthritis. Arthritis Rheumatol. 2014;66:31–9. https://pubmed. ncbi.nlm.nih.gov/24449573/. 458. Roos K, Martinsson K, Ziegelasch M, Sommarin Y, Svärd A, Skogh T, et al. Circulating secretory IgA antibodies against cyclic citrullinated peptides in early rheumatoid arthritis associate with inflammatory activity and smoking. Arthritis Res Ther. 2016;18:119. https:// pubmed.ncbi.nlm.nih.gov/27215344/. 459. Svärd A, Skogh T, Alfredsson L, Ilar A, Klareskog L, Bengtsson C, et al. Associations with smoking and shared epitope differ between IgA- and IgG-class antibodies to cyclic citrullinated peptides in early rheumatoid arthritis. Arthritis Rheumatol. 2015;67:2032–7. https:// pubmed.ncbi.nlm.nih.gov/25916813/. 460. Wang TT, Ravetch JV. Functional diversification of IgGs through Fc glycosylation. J Clin Invest. 2019;129:3492–8. https://www.jci.org/articles/view/130029. 461. Subedi GP, Barb AW. The immunoglobulin G1 N-glycan composition affects binding to each low affinity Fc γ receptor. MAbs. 2016;8:1512–24. https://www.tandfonline.com/doi/full/1 0.1080/19420862.2016.1218586. 462. Liu S, Liu X. IgG N-glycans. Adv Clin Chem. 2021;105:1–47. https://linkinghub.elsevier. com/retrieve/pii/S0065242321000123. 463. Gyebrovszki B, Ács A, Szabó D, Auer F, Novozánszki S, Rojkovich B, et al. The role of IgG Fc region N-glycosylation in the pathomechanism of rheumatoid arthritis. Int J Mol Sci. 2022;23:5828. https://www.mdpi.com/1422-0067/23/10/5828. 464. Albrecht S, Unwin L, Muniyappa M, Rudd PM. Glycosylation as a marker for inflammatory arthritis. Cancer Biomark. 2014;14:17–28. https://www.medra.org/servlet/aliasResolver?alia s=iospress&doi=10.3233/CBM-130373. 465. Gudelj I, Salo PP, Trbojević-Akmačić I, Albers M, Primorac D, Perola M, et al. Low galactosylation of IgG associates with higher risk for future diagnosis of rheumatoid arthritis during 10 years of follow-up. Biochim Biophys Acta Mol basis Dis. 2018;1864:2034–9. https:// linkinghub.elsevier.com/retrieve/pii/S092544391830098X. 466. Ząbczyńska M, Link-Lenczowski P, Pocheć E. Glycosylation in autoimmune diseases. Adv Exp Med Biol. 2021;1325:205–18. https://link.springer.com/10.1007/978-3-030-70115-4_10. 467. Rombouts Y, Ewing E, van de Stadt LA, Selman MHJ, Trouw LA, Deelder AM, et al. Anti- citrullinated protein antibodies acquire a pro-inflammatory Fc glycosylation phenotype prior to the onset of rheumatoid arthritis. Ann Rheum Dis. 2015;74:234–41. https://ard.bmj.com/ lookup/doi/10.1136/annrheumdis-2013-203565. 468. Harre U, Lang SC, Pfeifle R, Rombouts Y, Frühbeißer S, Amara K, et al. Glycosylation of immunoglobulin G determines osteoclast differentiation and bone loss. Nat Commun. 2015;6:6651. http://www.nature.com/articles/ncomms7651. 469. Sur Chowdhury C, Giaglis S, Walker UA, Buser A, Hahn S, Hasler P. Enhanced neutrophil extracellular trap generation in rheumatoid arthritis: analysis of underlying signal trans-
564
7 DAMPs in Systemic Autoimmune Diseases
duction pathways and potential diagnostic utility. Arthritis Res Ther. 2014;16:R122. http:// arthritis-research.biomedcentral.com/articles/10.1186/ar4579. 470. Wu S, Peng W, Liang X, Wang W. Anti-citrullinated protein antibodies are associated with neutrophil extracellular trap formation in rheumatoid arthritis. J Clin Lab Anal. 2021;35:e23662. https://onlinelibrary.wiley.com/doi/10.1002/jcla.23662. 471. Chen T, Li Y, Sun R, Hu H, Liu Y, Herrmann M, et al. Receptor-mediated NETosis on neutrophils. Front Immunol. 2021;12:775267. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.775267/full. 472. Kempers AC, Nejadnik MR, Rombouts Y, Ioan-Facsinay A, van Oosterhout M, Jiskoot W, et al. Fc gamma receptor binding profile of anti-citrullinated protein antibodies in immune complexes suggests a role for FcγRI in the pathogenesis of synovial inflammation. Clin Exp Rheumatol. 2018;36:284–93. http://www.ncbi.nlm.nih.gov/pubmed/29352854. 473. Aleyd E, Al M, Tuk CW, van der Laken CJ, van Egmond M. IgA complexes in plasma and synovial fluid of patients with rheumatoid arthritis induce neutrophil extracellular traps via FcαRI. J Immunol. 2016;197:4552–9. http://www.jimmunol.org/lookup/doi/10.4049/ jimmunol.1502353. 474. Su Z, Xie Q, Wang Y, Li Y. Abberant immunoglobulin G glycosylation in rheumatoid arthritis by LTQ-ESI-MS. Int J Mol Sci. 2020;21:2045. https://www.mdpi.com/1422-0067/21/6/2045. 475. Holers VM, Banda NK. Complement in the initiation and evolution of rheumatoid arthritis. Front Immunol. 2018;9:1057. https://www.frontiersin.org/article/10.3389/ fimmu.2018.01057/full. 476. Dijkstra DJ, Joeloemsingh JV, Bajema IM, Trouw LA. Complement activation and regulation in rheumatic disease. Semin Immunol. 2019;45:101339. https://linkinghub.elsevier.com/ retrieve/pii/S1044532319300181. 477. Trouw LA, Haisma EM, Levarht EWN, van der Woude D, Ioan-Facsinay A, Daha MR, et al. Anti-cyclic citrullinated peptide antibodies from rheumatoid arthritis patients activate complement via both the classical and alternative pathways. Arthritis Rheum. 2009;60:1923–31. https://onlinelibrary.wiley.com/doi/10.1002/art.24622. 478. Ribon M, Seninet S, Mussard J, Sebbag M, Clavel C, Serre G, et al. Neutrophil extracellular traps exert both pro- and anti-inflammatory actions in rheumatoid arthritis that are modulated by C1q and LL-37. J Autoimmun. 2019;98:122–31. https://linkinghub.elsevier.com/retrieve/ pii/S0896841118306036. 479. Huang H, Tohme S, Al-Khafaji AB, Tai S, Loughran P, Chen L, et al. Damage-associated molecular pattern-activated neutrophil extracellular trap exacerbates sterile inflammatory liver injury. Hepatology. 2015;62:600–14. http://doi.wiley.com/10.1002/hep.27841. 480. Awasthi D, Nagarkoti S, Kumar A, Dubey M, Singh AK, Pathak P, et al. Oxidized LDL induced extracellular trap formation in human neutrophils via TLR-PKC-IRAK-MAPK and NADPH-oxidase activation. Free Radic Biol Med. 2016;93:190–203. https://linkinghub.elsevier.com/retrieve/pii/S0891584916000058. 481. Liu L, Mao Y, Xu B, Zhang X, Fang C, Ma Y, et al. Induction of neutrophil extracellular traps during tissue injury: involvement of STING and Toll-like receptor 9 pathways. Cell Prolif. 2019;52:e12579. https://onlinelibrary.wiley.com/doi/10.1111/cpr.12579. 482. Grootjans S, Vanden Berghe T, Vandenabeele P. Initiation and execution mechanisms of necroptosis: an overview. Cell Death Differ. 2017;24:1184–95. http://www.nature.com/ doifinder/10.1038/cdd.2017.65. 483. Zhang X, Wu J, Liu Q, Li X, Li S, Chen J, et al. mtDNA-STING pathway promotes necroptosis-dependent enterocyte injury in intestinal ischemia reperfusion. Cell Death Dis. 2020;11:1050. http://www.nature.com/articles/s41419-020-03239-6. 484. Jiao H, Wachsmuth L, Kumari S, Schwarzer R, Lin J, Eren RO, et al. Z-nucleic-acid sensing triggers ZBP1-dependent necroptosis and inflammation. Nature. 2020;580:391–5. http:// www.nature.com/articles/s41586-020-2129-8. 485. Yang Y, Wang H, Kouadir M, Song H, Shi F. Recent advances in the mechanisms of NLRP3 inflammasome activation and its inhibitors. Cell Death Dis. 2019;10:128. http://www.nature. com/articles/s41419-019-1413-8.
References
565
486. Burdette BE, Esparza AN, Zhu H, Wang S. Gasdermin D in pyroptosis. Acta Pharm Sin B. 2021;11:2768–82. https://linkinghub.elsevier.com/retrieve/pii/S2211383521000447. 487. Zhao J, Jiang P, Guo S, Schrodi SJ, He D. Apoptosis, autophagy, NETosis, necroptosis, and pyroptosis mediated programmed cell death as targets for innovative therapy in rheumatoid arthritis. Front Immunol. 2021;12:809806. https://www.frontiersin.org/articles/10.3389/ fimmu.2021.809806/full. 488. The Academy of Medical Sciences. Realising the potential of stratified medicine. London: The Academy of Medical Sciences; 2013. https://acmedsci.ac.uk/ viewFile/51e915f9f09fb.pdf. 489. Seyhan AA, Carini C. Are innovation and new technologies in precision medicine paving a new era in patients centric care? J Transl Med. 2019;17:114. https://translational-medicine. biomedcentral.com/articles/10.1186/s12967-019-1864-9. 490. Capecchi R, Puxeddu I, Pratesi F, Migliorini P. New biomarkers in SLE: from bench to bedside. Rheumatology. 2020;59:v12–8. https://academic.oup.com/rheumatology/article/59/ Supplement_5/v12/5903868. 491. Yu H, Nagafuchi Y, Fujio K. Clinical and immunological biomarkers for systemic lupus erythematosus. Biomolecules. 2021;11:928. https://www.mdpi.com/2218-273X/11/7/928. 492. Enocsson H, Wetterö J, Eloranta M-L, Gullstrand B, Svanberg C, Larsson M, et al. Comparison of surrogate markers of the type I interferon response and their ability to mirror disease activity in systemic lupus erythematosus. Front Immunol. 2021;12:688753. https:// www.frontiersin.org/articles/10.3389/fimmu.2021.688753/full. 493. Liu H, Zou Y, Chen C, Tang Y, Guo J. Current understanding of circular RNAs in systemic lupus erythematosus. Front Immunol. 2021;12:628872. https://www.frontiersin.org/ articles/10.3389/fimmu.2021.628872/full. 494. Wang W, Yue C, Gao S, Li S, Zhou J, Chen J, et al. Promising roles of exosomal microRNAs in systemic lupus erythematosus. Front Immunol. 2021;12:757096. https://www.frontiersin. org/articles/10.3389/fimmu.2021.757096/full. 495. Yang P, Zhang X, Chen S, Tao Y, Ning M, Zhu Y, et al. A novel serum tsRNA for diagnosis and prediction of nephritis in SLE. Front Immunol. 2021;12:735105. https://www.frontiersin. org/articles/10.3389/fimmu.2021.735105/full. 496. Yu KYC, Yung S, Chau MKM, Tang CSO, Yap DYH, Tang AHN, et al. Serum syndecan-1, hyaluronan and thrombomodulin levels in patients with lupus nephritis. Rheumatology. 2021;60:737–50. https://academic.oup.com/rheumatology/article/60/2/737/5892439. 497. Hossny E, El-Ghoneimy D, Soliman DA, Ashour A. Diagnostic value of serum high-mobility group box-1 in pediatric systemic lupus erythematosus. Int J Rheum Dis. 2019;22:1402. https://onlinelibrary.wiley.com/doi/10.1111/1756-185X.13556. 498. Das UN. Lipoxins as biomarkers of lupus and other inflammatory conditions. Lipids Health Dis. 2011;10:76. http://lipidworld.biomedcentral.com/articles/10.1186/1476-511X-10-76. 499. Serra P, Santamaria P. Antigen-specific therapeutic approaches for autoimmunity. Nat Biotechnol. 2019;37:238–51. http://www.nature.com/articles/s41587-019-0015-4. 500. Robinson S, Thomas R. Potential for antigen-specific tolerizing immunotherapy in systematic lupus erythematosus. Front Immunol. 2021;12:654701. https://www.frontiersin.org/ articles/10.3389/fimmu.2021.654701/full. 501. Land WG. How evolution tells us to induce allotolerance. Exp Clin Transplant. 2015;13(Suppl 1):46–54. http://www.ncbi.nlm.nih.gov/pubmed/25894127. 502. Carreira PL, Isenberg DA. Recent developments in biologic therapies for the treatment of patients with systemic lupus erythematosus. Rheumatology. 2018;58:382. https://academic. oup.com/rheumatology/advance-article/doi/10.1093/rheumatology/key064/4962137 503. Loncharich MF, Anderson CW. Interferon inhibition for lupus with anifrolumab: critical appraisal of the evidence leading to FDA approval. ACR Open Rheumatol. 2022;4:486–91. https://onlinelibrary.wiley.com/doi/10.1002/acr2.11414. 504. Dörner T, van Vollenhoven RF, Doria A, Jia B, Ross Terres JA, Silk ME, et al. Baricitinib decreases anti-dsDNA in patients with systemic lupus erythematosus: results from a phase II
566
7 DAMPs in Systemic Autoimmune Diseases
double-blind, randomized, placebo-controlled trial. Arthritis Res Ther. 2022;24:112. https:// arthritis-research.biomedcentral.com/articles/10.1186/s13075-022-02794-x. 505. Zhang C, Li C, Jia S, Yao P, Yang Q, Zhang Y. High-mobility group box 1 inhibition alleviates lupus-like disease in BXSB mice. Scand J Immunol. 2014;79:333–7. https://onlinelibrary. wiley.com/doi/10.1111/sji.12165. 506. Ji J, Fu T, Dong C, Zhu W, Yang J, Kong X, et al. Targeting HMGB1 by ethyl pyruvate ameliorates systemic lupus erythematosus and reverses the senescent phenotype of bone marrow- mesenchymal stem cells. Aging (Albany NY). 2019;11:4338–53. https://www.aging-us.com/ lookup/doi/10.18632/aging.102052. 507. Schrezenmeier E, Dörner T. Mechanisms of action of hydroxychloroquine and chloroquine: implications for rheumatology. Nat Rev Rheumatol. 2020;16:155–66. http://www.nature. com/articles/s41584-020-0372-x. 508. Ponticelli C, Moroni G. Hydroxychloroquine in systemic lupus erythematosus (SLE). Expert Opin Drug Saf. 2017;16:411–9. https://www.tandfonline.com/doi/full/10.1080/1474033 8.2017.1269168. 509. Dima A, Jurcut C, Chasset F, Felten R, Arnaud L. Hydroxychloroquine in systemic lupus erythematosus: overview of current knowledge. Ther Adv Musculoskelet Dis. 2022;14:1759720X2110730. http://journals.sagepub.com/doi/10.117 7/1759720X211073001. 510. Olson LB, Hunter NI, Rempel RE, Sullenger BA. Targeting DAMPs with nucleic acid scavengers to treat lupus. Transl Res. 2022;245:30. https://linkinghub.elsevier.com/retrieve/pii/ S193152442200041X 511. Atzeni F, Talotta R, Masala I, Sarz-Puttini P. Biomarkers in rheumatoid arthritis. IMAJ. 2017;19:512–6. https://www.ima.org.il/MedicineIMAJ/viewarticle.aspx?year=2017 &month=08&page=512. 512. Abildtrup M, Kingsley GH, Scott DL. Calprotectin as a biomarker for rheumatoid arthritis: a systematic review. J Rheumatol. 2015;42:760–70. http://www.jrheum.org/lookup/ doi/10.3899/jrheum.140628. 513. Baillet A, Trocmé C, Romand X, Nguyen CMV, Courtier A, Toussaint B, et al. Calprotectin discriminates septic arthritis from pseudogout and rheumatoid arthritis. Rheumatology. 2019;58:1644–8. https://pubmed.ncbi.nlm.nih.gov/30919904/. 514. Pullerits R, Schierbeck H, Uibo K, Liivamägi H, Tarraste S, Talvik T, et al. High mobility group box protein 1—a prognostic marker for structural joint damage in 10-year follow-up of patients with juvenile idiopathic arthritis. Semin Arthritis Rheum. 2017;46:444–50. http:// www.ncbi.nlm.nih.gov/pubmed/27756498. 515. Huang J, Zeng T, Zhang X, Tian Y, Wu Y, Yu J, et al. Clinical diagnostic significance of 14-3-3η protein, high-mobility group box-1, anti-cyclic citrullinated peptide antibodies, anti- mutated citrullinated vimentin antibodies and rheumatoid factor in rheumatoid arthritis. Br J Biomed Sci. 2020;77:19–23. https://www.tandfonline.com/doi/full/10.1080/09674845.201 9.1658425. 516. Hashimoto T, Yoshida K, Hashimoto N, Nakai A, Kaneshiro K, Suzuki K, et al. Circulating cell free DNA: a marker to predict the therapeutic response for biological DMARDs in rheumatoid arthritis. Int J Rheum Dis. 2017;20:722–30. https://onlinelibrary.wiley.com/doi/1 0.1111/1756-185X.12959. 517. Gomez EA, Colas RA, Souza PR, Hands R, Lewis MJ, Bessant C, et al. Blood pro-resolving mediators are linked with synovial pathology and are predictive of DMARD responsiveness in rheumatoid arthritis. Nat Commun. 2020;11:5420. https://www.nature.com/articles/ s41467-020-19176-z. 518. Burmester GR, Pope JE. Novel treatment strategies in rheumatoid arthritis. Lancet. 2017;389:2338–48. https://linkinghub.elsevier.com/retrieve/pii/S0140673617314915. 519. Page A, Fusil F, Cosset F-L. Antigen-specific tolerance approach for rheumatoid arthritis: past, present and future. Jt Bone Spine. 2021;88:105164. https://linkinghub.elsevier.com/ retrieve/pii/S1297319X21000361.
References
567
520. Benham H, Nel HJ, Law SC, Mehdi AM, Street S, Ramnoruth N, et al. Citrullinated peptide dendritic cell immunotherapy in HLA risk genotype–positive rheumatoid arthritis patients. Sci Transl Med. 2015;7:290ra87. https://www.science.org/doi/10.1126/scitranslmed. aaa9301. 521. Bell GM, Anderson AE, Diboll J, Reece R, Eltherington O, Harry RA, et al. Autologous tolerogenic dendritic cells for rheumatoid and inflammatory arthritis. Ann Rheum Dis. 2017;76:227–34. https://ard.bmj.com/lookup/doi/10.1136/annrheumdis-2015-208456. 522. Kaur I, Behl T, Bungau S, Kumar A, Mehta V, Setia D, et al. Exploring the therapeutic promise of targeting HMGB1 in rheumatoid arthritis. Life Sci. 2020;258:118164. https://linkinghub.elsevier.com/retrieve/pii/S0024320520309164. 523. Austermann J, Zenker S, Roth J. S100-alarmins: potential therapeutic targets for arthritis. Expert Opin Ther Targets. 2017;21:738–50. https://www.tandfonline.com/doi/full/10.108 0/14728222.2017.1330411.
8
DAMPs in Organ-Specific Autoimmune Diseases
8.1
Introduction
Organ-specific autoimmune diseases, as the term says, involve specific organs of the body in which the target autoantigen is found. Target tissues include the thyroid (thyroiditis), the islets of Langerhans (diabetes), gastric parietal cells (gastritis), and steroid-producing cells in the adrenal and ovary (Addison’s disease). As with systemic ADs, the etiopathogenesis of organ-specific ADs is enigmatic and complex and still not fully understood. Moreover, as with systemic ADs, it is generally agreed that an interplay between infectious/sterile environmental triggers, genetic risk factors, epigenetic modifications, and stochastic dynamics of the immune response results in the development of these organ-restricted autoimmune disorders (cf. Fig. 6.1). Of note, a detailed description of the entire clinical, biochemical, and immunological spectrum of these diseases has again been omitted. Moreover, in order not to exceed the scope of the book, the format of their presentation has been shortened compared with the presentation of SLE and RA in Chap. 7. Accordingly, exemplary for the other organ-specific autoimmune diseases, only two prototypical disorders, MS and T1DM, will be presented, focusing on the pathogenetic role of stress/ injury-induced DAMPs, while parts of the adaptive autoimmune response are partially abridged.
This chapter is based on an article by the same author previously published in the Nature Journal: Genes and Immunity and titled “Role of DAMPs and Cell Death in Autoimmune Diseases: The Example of Multiple Sclerosis”. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 W. G. Land, Damage-Associated Molecular Patterns in Human Diseases, https://doi.org/10.1007/978-3-031-21776-0_8
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8.2 Multiple Sclerosis 8.2.1 Introductory Remarks 8.2.1.1 General Remarks Multiple Sclerosis is a chronic neuroinflammatory demyelinating disease of the CNS of unknown etiology and still incompletely clarified pathogenesis. Autoimmune processes are thought to be pathogenetically involved, although the exact nature of this disease is still a matter of debate. In any way, the etiopathogenesis of the disorder is complex. Interestingly, two complementary paradigms indicated as “outside-in” and “inside-out” are discussed about the MS origin. The “outside-in” paradigm postulates a peripherally triggered autoimmune attack against (“mimic”) autoantigenic myelin as the cause of MS, whilst “inside-out” implies a primary cytodegenerative process in the CNS that drives secondary autoimmune responses against myelin debris [1]. In other words: the “inside-out” paradigm is akin to the d anger/injury model of Immunity, holding that the peripheral bodily tissue cells equipped with a plethora of perceptive PRMs, rather than the innate or adaptive immune system take control over immunity, that is, to decide—as” healthy” cells—to induce protective peripheral tolerance to self or—as “unhealthy” stressed/damaged cells—to drive dangerous immune responses to self (compare Sects. 6.2.2.4 and 6.2.3.1; also see [2, 3]). 8.2.1.2 Clinical Picture, Classification, and Prevalence The disease accounts for functional deterioration and lasting disability among young adults. Twice as many women are affected as men, and persons of Northern European descent appear to be at the highest risk for MS. The major clinical symptoms of MS are cognitive disabilities, abnormal sensation, paralysis, and ocular symptoms associated with relapses and remissions. However, the symptoms vary depending on which part of the CNS is involved. In fact, the variation in clinical manifestations correlates with the spatiotemporal dissemination of lesional sites, the lesions being caused by inflammatory/immune cell infiltration across the disintegrated BBB, destruction of the myelin layer, and axonal damage (for reviews and competent papers, see [4–7]). Neurologists agree that patients may be grouped into four major categories based on the course of the disease: relapsing-remitting MS; secondary progressive MS; primary progressive MS; and progressive-relapsing MS [8, 9]. In 2013, the disease affected about 2.3 million people and with a global prevalence ranging from 5 to >100 patients with MS per 100,000 people, according to the Atlas of MS published in 2013 by the World Health Organization [10]. According to a recent survey conducted between September 2019 and March 2020, a total of 2.8 million people are estimated to live with MS worldwide (35.9 per 100,000 population). MS prevalence has increased in every world region since 2013, but gaps in prevalence estimates persist. The pooled incidence rate across 75 reporting countries is 2.1 per 100,000 persons/year, and the mean age of diagnosis is 32 years. Females are twice as likely to live with MS as males [11]. 8.2.1.3 Neuroimmunology and Neuropathology Although the etiology of the disease and the pathogenic trajectories involved remain enigmatic, the autoimmune in nature is generally accepted. Current notions hold
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that defects of central and peripheral tolerance permit the existence of autoreactive T cells, which are activated by APCs, including microglia that, in the CNS, are considered professional macrophages/APCs. Regarding pathomechanisms, autoimmune inflammation in early MS is thought to be primarily mediated by adaptive immune responses and involves autoreactive T cells, B cells, and autoantibodies, while the later, chronic stages of MS are characterized by a compartmentalized immune response in the CNS (i.e., innate vs. adaptive immune processes). Thus, infiltrating CD4+ T cells is less apparent as MS progresses, while microglial and astrocyte activation persists as the typical lesional feature in progressive MS. Of note, although most of the research on MS pathogenesis has centered on the role of effector CD4+ T cells, growing evidence suggests that CD8+ T cells (along with B cells) may also play a significant role in the disease. In fact, in contrast to most animal models, the primary T cell found in the CNS in patients with MS is the CD8+ T cell (for reviews, see [12–14]). The characteristic neuropathological features of MS include demyelination in the form of progressive destruction of the myelin sheath surrounding axons, chronic inflammation, gliosis, and consequent neurodegeneration and axonal transection/ loss (i.e., axonal degeneration) in the white and gray matter of the CNS, leading to disruption of neuronal signaling. Accordingly, the pathological hallmark of all MS phenotypes is focal plaques, which are areas of demyelination that are typically located around postcapillary venules and are characterized by the breakdown of the BBB. A key mechanism, finally leading to demyelination and neurodegeneration, is seen in a cascade of oxidative stress/injury and mitochondrial damage, reflecting a state of “virtual hypoxia”, a mechanism that is pronounced in patients with progressive MS. The major pathogenetic event appears to be the death of myelin-producing oligodendrocytes which is sufficient to trigger an innate and adaptive autoimmune response against myelin. Of note, although the oligodendrocyte and the myelin sheath are considered the main target of the pathological process, any cellular element of the CNS can be affected by MS (for reviews, see [15, 16]). Notably, MS immunopathology has been widely studied in experimental animal models, mainly murine models, which recapitulate pathological features such as demyelination, axonal pathology, and immune cell infiltration. Given the ongoing debate about the two complementary paradigms explaining the origin of the disease, two different groups of models are utilized, one recapitulating the “outside-in” and another one the “inside-out” concept. In the following, only the experimental autoimmune encephalomyelitis (EAE) animal model will be briefly described, which is representative of the “outside-in” concept model, as well as the cuprizone autoimmune encephalitis (CAE) model that is typical for the “inside-out” idea.
8.2.2 Experimental Animal Models 8.2.2.1 General Remarks As said, in MS, two different kinds of experimental animal models have been developed to study the etiopathogenesis of the disease, supporting either the “outside-in” concept or the “inside-out” idea (reviewed by Sen et al. [17] and Titus et al. [18]).
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Models supporting the “outside-in” paradigm include the traditional EAE and Theiler’s murine encephalitis virus-induced demyelinating disease (TMEV-IDD), while models supporting the “inside-out” concept comprise approaches such as the epsilon toxin model, the diphtheria toxin A chain model, and the cuprizone (CPZ) model for toxic demyelination. Experimental autoimmune encephalomyelitis is among the most clinically relevant mouse models of MS and, in particular, has been used to mirror autoimmune demyelination in response to a peripheral immunostimulatory event. It is characterized by mononuclear cell infiltration within the CNS, represented primarily by T cells, B cells, and macrophages, which can induce demyelination and axonal loss (for a recent review, see Glatigny and Bettelli [19]). On the “inside-out” concept side, the model of toxic demyelination induced by CPZ has recently become more and more popular and has contributed substantially to an understanding of primary cell damage as an important etiopathogenetic event in MS pathology (for review, see Zirngibl et al. [20]). These two prototypical models will be briefly touched upon here.
8.2.2.2 Experimental Autoimmune Encephalomyelitis Supporting the “Outside-In” Paradigm Experimental autoimmune encephalomyelitis is the most commonly used experimental model for human MS that can be induced in rats, mice, rabbits, guinea pigs, and monkeys. The model is induced by immunization of susceptible animal strains with spinal cord homogenate or with candidate MS-associated CNS autoantigens (cMSAg) in adjuvant, that is, myelin proteins or immunodominant peptide epitopes from these proteins such as myelin basic protein (MBP), myelin proteolipid protein (PLP), and myelin oligodendrocyte glycoprotein (MOG), emulsified in complete Freund’s adjuvant (CFA = containing DAMPs and/or potentially releasing DAMPs via local necrosis [21]). In addition, the experimental disorder can be induced by the adoptive transfer of cMSAg-specific CD4+ T cells. These studies reinforced the idea that MS is an autoimmune disease mediated by cMSAg-specific CD4+ Th1/Th17 cells (for reviews, see [22–25]). The experimentally induced disorder is a complex condition in which the interaction between a variety of immunopathological and neuropathological mechanisms leads to an approximation of the key pathological features of MS: inflammation, demyelination, axonal loss, and gliosis. The counter-regulatory mechanisms of resolution of inflammation and remyelination also occur in EAE, which, therefore, can also serve as a model for these processes. Moreover, EAE is often used as a model of T cell/B cell-mediated organ-specific autoimmune conditions in general. The EAE has complex neuropharmacology, and many of the drugs that are in current or imminent use in MS have been developed, tested, or validated on the basis of EAE studies. But, over time, growing inherent weaknesses of this model of MS have been noted in straightforward translation from EAE to the human disease, in particular, with respect to the inability of EAE to address the initial, underlying etiopathology of MS. This has motivated researchers to focus in their studies on the “inside-out” hypothesis of MS.
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8.2.2.3 Cuprizone Model of Toxic Demyelination Supporting the “Inside-Out” Paradigm Cuprizone is a copper chelator that, when long-term fed to rodents, leads to oligodendrocyte death, demyelination, and, in specific brain regions, gliosis with limited infiltration of peripheral immune cells [17]. Of note, besides the promotion of many findings typical for MS, such as demyelination, CPZ was evidenced to contribute to the induction of subroutines of RCD such as ferroptosis, pyroptosis, and necroptosis (reviewed in [20]). Jhelum et al. [26], for example, could demonstrate that CPZ given to mice induces rapid loss of oligodendrocytes in the corpus callosum, accompanied by the expression of several markers for ferroptosis. In other lines of studies, CPZ was shown to upregulate the expression of NLRP3 by week 3, remaining high through week 5. Further observations from this study suggested that a CASP1/ NLRP3-dependent but IL-1β-independent mechanism leads to increased demyelination and the loss of mature oligodendrocytes, although a clearcut transition to pyroptosis was not assessed [27]. Also, Zirngibel et al. [20] reviewed findings from other lines of studies, suggesting that oligodendrocytes are prone to undergo necroptosis. Consistent with those findings were studies by Ofengeim et al. [28], who showed that necroptosis mediates oligodendrocyte degeneration induced by TNF and that inhibition of RIPK1 protects against oligodendrocyte cell death in two animal models of MS, including the CPZ model and in culture. The researchers further demonstrated that necroptosis is involved in MS and suggested that targeting RIPK1 may represent a therapeutic strategy for MS.
8.2.3 Pathogenesis-Orchestrating Interrelationship Between Environmental Triggers, Genetic Predisposition, and Epigenetic Modifications 8.2.3.1 General Remarks As mentioned, the causes of MS development remain unknown, but it is considered a chronic disease resulting from a complex interplay between environmental risk factors and predisposing causal genetic variants, together with stochastic factors causing subsequent dysregulation of key genes in innate/adaptive immune and nervous system processes. As with other ADs such as SLE and RA, an increasing body of evidence has accumulated suggesting the involvement of epigenetic mechanisms at various stages in the pathogenesis of this disorder. 8.2.3.2 Environmental Factors and the Role of Regulated Cell Death Regarding the role of environmental risk factors in ADs, recent research has intriguingly focused on secondary events in terms of induced subroutines of RCD caused by environmental triggers. These studies examine issues such as (1) cell death- associated modifications of self components that—besides bona fide self—operate as altered-self antigens; (2) the distinct pattern of constitutive /inducible DAMPs emitted in the course of given environment-induced cell death; and (3) the
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imbalance of regulatory pathways in a given autoantigen/DAMPs constellation which can provoke the innate immune system to promote overt autoimmune disorder [29, 30]. This scenario can also be applied to MS, in which subroutines of RCD, such as apoptosis [31], ferroptosis [32], pyroptosis [33, 34], and necroptosis [35], have been described. Indeed, there is ample and strong evidence suggesting that environmental factors and lifestyle are involved in the pathogenesis of MS by serving as triggers of
Infectious and Sterile Environmental risk factors Oxidative stress
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CNS PRR-bearing cells (e.g., microglia, astrocytes, endothelial cells)
Cytokines, chemokines, adhesion molecules
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Infections (EBV!), smoking, low UVR, low vitamin D levels, air pollutants, childhood/adolescent obesity, antibiotics, others
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Fig. 8.1 Simplified schematic overview of a tentative conceptual model proposing the role of DAMPs in the pathogenesis of multiple sclerosis (MS) as seen in the light of the danger/injury model. Environmental risk factors (shown on the top left of the figure) for MS contribute to the triggering of various subroutines of RCD in genetically predisposed individuals that serve as sources of both generation of altered-self antigens and release of DAMPs. The figure shows only some key events of the hypothetical model, holding that those environmental factors which induce oxidative stress/injury-driven ferroptosis of oligodendrocytes may be primarily responsible for the onset of MS and subsequent disease relapses. Downstream ferroptosis-derived DAMPs (e.g., HMGB1, eATP, DNA, or RNA, here, not shown) promote activation of NLRP3/AIM2 inflammasome-mediated pyroptosis, whereas other ferroptosis-derived DAMPs activate PRR- expressing microglial cells and astrocytes to secrete TNF for activation of necroptosis as well as other inflammatory mediators to promote neuroinflammation. The DAMP-driven neuroinflammatory milieu, in turn, allows enhanced recruitment of PRR-bearing DCs from the peripheral circulation to the CNS, which are then activated by DAMPs. Subsequently, DCs are thought to travel to the peripheral lymph nodes and trigger activation of naïve T cells through presentation of autoantigens and provision of costimulation. Products of the adaptive autoimmune response (e.g., cytotoxic CD4+Th17 cells, CD8+ T cells, and B cells) migrate into the CNS via a disturbed BBB, are reactivated by CNS APCs (e.g., microglial cells, DCs), and then presumably promote elicitation of RCD in conjunction with release of DAMPs, thereby causing autoimmune processes to relapse or sustain in the sense of a self-perpetuating, positive feed-forward loop. This momentum may be responsible for the chronicity of the disease. APCs antigen-presenting cells, AuAgs autoantigens in terms of bona fide self antigens or altered-self antigens, CNS central nervous system, CTLs cytotoxic T lymphocytes, EBV Epstein-Barr virus, ii cells innate immune cells, mDCs mature dendritic cells, MS multiple sclerosis, OLs oligodendrocytes, PRR pattern recognition receptor, RCD regulated cell death, UV ultraviolet
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onset, relapse, and progression of the disorder. Among those risk factors so far described are infections, particularly viral infections such as EBV infection (thought to play a critical role in the development of MS); smoking (associated with increased risk of secondary progressive disease; low vitamin D levels (lack of sun exposure/ vitamin D, typically observed at a time of relapse) and low exposure to UVR; exposure to airborne biological pollutants including PMs; childhood/adolescent obesity; exposure to heavy metals and antibiotics; ethanol abuse; vaccination; and gut microbiota changes (Fig. 8.1) (for reviews, see [36–43]). And to echo sources of DAMPs emission via release from RCD as outlined already in Sect. 6.3.3: EBV infections have been reported to cause inflammasome-mediated pyroptosis [44]. Likewise, smoking has been reported to cause ferroptosis [45], necroptosis [46], and NETosis [47], and UVR was demonstrated to promote various forms of RCD, including necroptosis, ferroptosis, and NETosis [48–50]. Other viral infections are also recently discovered to be associated with forms of RN, such as necroptosis [51, 52], inflammasome-mediated pyroptosis [53, 54], and NETosis [52, 55]. Of special note here is that EBV has been shown to promote AIM2 inflammasome activation in human monocytes [44]. Activation of this inflammasome then leads—as shown in other sets of studies—to the pyroptosis-associated release of DAMPs [56–58] (Fig. 8.1). In fact, this interesting finding might explain the potential impact of EBV on MS etiopathogenesis. (Note that the issue of RCD has also been comprehensively dealt with in the context of infections in Sects. 3.6 and 3.7).
8.2.3.3 Environmental Factors in Multiple Sclerosis Promoting Oxidative Stress The molecular mechanisms underlying the relationship between environmental risk factors and MS pathogenesis are of utmost importance for the development of future therapeutic strategies. Viewed through the lens of the danger/injury model, the first question here would be what pathways these risk factors use preferentially to trigger CNS injury leading to forms of RCD as potential sources of DAMPs emission. And the amazing answer would be that there is evidence that almost all of the aforementioned environmental risk factors share a common characteristic, namely the ability to promote oxidative stress/damage (i.e., as oxidative stressors) [59], including, for example, smoking [60, 61]; UVR [50]; air pollution [62]; virus (e.g., EBV) infections [63]; vitamin D deficiency [64]; childhood/adolescent obesity [65]; ethanol abuse [66]; as well as heavy metals, chemotherapy, and drugs/xenobiotics (reviewed in [67]) (Fig. 8.1). And these observations are of particular relevance since oxidative stress in the brain is all the more severe because oligodendrocytes are known to be highly susceptible to the attack of ROS compared to astrocytes and microglia, due to their weak antioxidant defense system [68]. The concept that environmental factors contribute to MS pathogenesis via mediating oxidative injury directly to the CNS is supported by further findings observed in other lines of studies. For example, for smoking, compounds found in tobacco have been proposed to affect the viability of cells at the BBB (reviewed in [69]); for exposure to air pollutants, inhaled particles have been suggested to increase the epithelial wall’s permeability and oxidative stress or to directly enter the CNS by crossing the BBB through the olfactory system (reviewed in [70]).
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Of course, it is not only oxidative stress that has to be discussed here. In viral infections of the CNS, for instance, the local damaging effects of viruses on the CNS could also be considered. Indeed, herpes viruses have long been described as potential triggers. In particular, these viruses are known to be associated with MS; thus, EBV, human herpes virus 6 (HHV6), and VZV have consistently been thought to play an etiological role in the disease [39]. In support of this notion are studies showing, for example, that there is a correlation between EBV antibody titers and the risk of developing MS. Also, in other lines of studies, EBV has been shown to infiltrate the brain [71]. Further, anti-Epstein–Barr nuclear antigen 1 (EBNA1) antibodies were demonstrated to be present in patients with MS up to 5 years before the diagnosis of the disease [72]. Of note, these early observations were recently supported by a longitudinal analysis that revealed a high prevalence of EBV associated with multiple sclerosis [73]. Impressed by their findings, the authors suggested in their conclusion that EBV is the leading cause of MS. On the other hand, EBV has been shown to be associated with the emission of DAMPs such as HMGB1 [74]. In addition, three EBV latency proteins have been shown to independently promote genomic instability by inducing DNA damage [75], thereby inducing a DDR regarded as a source of DAMPs, including class I DAMPs (e.g., endogenous DNA) and class III DAMPs (see Tables 1.1 and 1.2). In this context, it is also interesting to note that HHV7, a virus found in the blood of MS patients [76], has been shown to mediate increased ROS production leading to ferroptosis in HHV7-infected Schwann cells [77]. Of note, besides environmental risk factors, other nonenvironmental factors related to neurons or cytotoxic autoreactive T lymphocytes may also cause RCD in MS—indeed, an emerging topic that will be addressed below.
8.2.3.4 Induction of Regulated Cell Death in the CNS: What Evidence Exists to Date for Multiple Sclerosis? To put it bluntly, direct, convincing evidence for the induction of RCD in the CNS of patients with MS has not been reported yet. Nevertheless, findings from other experimental and clinical settings suggest the unproven but thoughtful possibility that induction of subroutines of RCD, especially in oligodendrocytes, may also occur in MS. These are: (1) the ability of environmental risk factors typical for MS to trigger various forms of RCD, and (2) the growing evidence that the human MS symptoms-mirroring CPZ promotes the induction of subroutines of RCD. This proposal seems justifiably posed on the basis of the fact that RCD in the CNS has been identified as a major driver of the pathogenesis of neuroinflammatory and neurodegenerative diseases [78]. Indeed, preventing RCD in oligodendrocytes and other cells of the CNS is of paramount importance from a therapeutic perspective, as hindering the death of these cells may halt myelin loss and inhibit axonal degeneration, the major cause of irreversible neurological disability in MS patients. Non-Immune-Mediated Induction of Regulated Cell Death In the first place, ferroptosis can be discussed here as a classical form of RCD (also see Sect. 3.7.8). This is even more so since Jhelum et al. [26] were able to demonstrate that administration of CPZ in mice induces rapid loss of oligodendrocytes in the corpus callosum by 2 days, accompanied by the expression of several markers
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for ferroptosis. In support of this proposal are also the above-mentioned studies on environmental risk factors for MS, sharing a common characteristic, namely the ability to promote oxidative stress/damage. And it is the oxidative stress that is known to trigger lipid peroxidation, which is responsible for ferroptotic cell death. (Note, details of lipid peroxidation, ferroptotic cascade, and activation mechanisms of ferroptosis have been described and illustrated in our contributions in [79], Fig. 3, and Vol. 1 [80], Sect. 19.3.3, pp. 442–446 and Vol. 2 [81], Sect. 4.3.4 and Figs. 4.2 and 4.3, pp. 133–138; for recent reviews, see [82–84]). In a nutshell: Lipid peroxidation with the generation of the first line of DAMPs (i.e., OSEs) mirrors a defense response against oxidative stress at the cellular level aimed at restoring cellular homeostasis. However, when this stress response fails as a consequence of excessive oxidative stress or a too-weak antioxidative defense response, the cell proceeds to RCD in the form of ferroptosis associated with the release of large amounts of DAMPs, which operate at the level of the organism to restore organismal homeostasis. And that a deficient antioxidative defense may be one of the causes of the development of ferroptosis development in MS was impressively documented by Hu et al. [85] in studies on MS brain and EAE spinal cord in mice. The authors revealed that mRNA expression for all three isoforms of the ferroptosis inhibitor GPX4 declined in MS gray matter and in the spinal cord of EAE animals. The amount of GPX4 protein was found to be also reduced in EAE. In light of their findings, the authors [85] argued that the deficiency of the ferroptosis inhibitor GPX4, specifically in neurons, may be the cause of neuronal damage in these disorders. And they speculated that neurons are being damaged by ferroptosis. The question then would be whether or not the deficiency in this enzyme reflects a genetic defect common to all MS patients. A more recently conducted study published by Louqian et al. [32] supported these assumptions by showing that critical ferroptosis proteins are altered in an existing genomic database of MS patients and that biochemical features of ferroptosis, including lipid ROS accumulation and mitochondrial shrinkage, do occur in the EAE mouse model. Interestingly, in parallel experiments of this study [32], targeting ferroptosis with ferroptosis inhibitors or reducing a ferroptosis protein expression was found to improve the behavioral phenotypes of EAE mice, reduce neuroinflammation, and prevent neuronal death. In contrast to the role of oxidative stress-triggered pathways resulting in ferroptosis, paths that are thought to link distinct injuries causatively to microglia- or oligodendrocytes-specific activation of pyroptosis has not yet been demonstrated in MS. On the other hand, this subroutine of RCD has recently been identified as a major contributor to pathogenesis in MS [33, 34, 86]. Indeed, in earlier studies, CPZ was already shown to upregulate the expression of NLRP3 by week 3, remaining high through week 5. Further observations from this study suggested that a CASP1/ NLRP3-dependent but IL-1β-independent mechanism leads to increased demyelination and the loss of mature oligodendrocytes, although a clearcut transition to pyroptosis was not assessed [27]. In a more recent paper, McKenzie et al. [87] presented evidence showing that the activation of the executioner CASP3 and CASP7 promotes microglial pyroptosis in models of MS, thus providing unprecedented insight into the molecular mechanisms governing pyroptosis in the CNS. Interestingly, the authors also discussed in their article that widespread cell death may release
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DAMPs, which trigger pyroptosis in macrophages and microglia (for details of the pyroptotic pathway and activation of inflammasome-mediated pyroptosis, see Sect. 3.7.5 with citation references [88-96]; also see our contributions in Vol. 1 [80], Sect. 19.3.4 and Figs. 19.7 and 19.8, pp. 447–450, Sect. 22.4 and Fig. 22.11, pp. 514–526, as well as Vol. 2 [81], Sect. 2.2.5, Fig. 2.1. pp. 17–21 and Sect. 2.2.8, Fig. 2.2, p. 25, and Sect. 4.3.5, p. 138; for reviews, see [97–104]). Similarly to pyroptosis, there are as yet no pathways reported linking distinct injuries causatively to neuron- or oligodendrocyte-specific activation of RIPK1/RIPK3promoted necroptosis, although RIPK1 has been shown to mediate neuroinflammation and disease progression in MS [35], and TNF-mediated necroptosis has been evidenced in the disease. Indeed, remarkable studies reported by Ofgenheim et al. [28] already cited above provided substantial evidence for the activation of the necroptotic cell death in MS, including the oligomerization/aggregation and phosphorylation of RIPK1, RIPK3, and MLKL in post-mortem brain tissues from MS patients. The investigators, in the course of their investigations, discovered a defective CASP8 activation in MS cortical lesions. Because CASP8 is critical for suppressing the activation of necroptosis, these data suggest that defective activation of CASP8 might be involved in the pathogenesis of MS, according to the researchers. Also, in further parallel studies on the EAE and CPZ model of MS, the researcher group [28] could first show that TNF mediates necroptosis. They further demonstrated that necroptosis mediates oligodendrocyte loss in the corpus callosum occurring in the third and fourth weeks following CPZ treatment and that inhibition of RIPK1 by administration of 7 N-1, an analog of necrostatin-1, to CPZ-fed mice protects against oligodendrocyte cell death and increases motor function in these animals after 5 weeks. In more recent studies on cortical grey matter tissue blocks from post-mortem brains of secondary progressive MS subjects, Picon et al. [105] confirmed these findings and additionally found an increase in the expression of multiple steps in the TNF → TNFR1 signaling pathway leading to necroptosis, including the key proteins TNFR1, RIPK1, RIPK3, and MLKL. The authors further showed that primary cortical neurons in vitro undergo TNF-induced and RIPK1/RIPK3 → MLKL-dependent necroptosis (for details of the necroptotic pathway and activation mechanisms of necroptosis, see Sect. 3.7.4.2 and our contributions in Ref. [79], Sect. B and Fig. 2, and, in this book, in Vol. 1 [80], Sect. 19.3.2 and Figs. 19.4 and 19.5, pp. 436–442) and Vol. 2 [81], Sect. 4.3.3, pp. 131–133; for a more recent review, see [106]). T Cell- and B Cell-Mediated Induction of Regulated Cell Death Another completely different cause of injury-triggered RCD observed in MS patients could be mediated by neurodegeneration-promoting factors of the autoimmune response, that is, cytotoxic autoreactive T and B cells. This connotes that these cytotoxic cells are dependent upon the machinery of the target cells, such as oligodendrocytes, to sense and integrate the cell death signals into their pro-death pathways and then ultimately execute the sophistically regulated cell death process (compare Sect. 1.4.3 and Fig. 1.3). In view of the “outside-in” paradigm, they are the primary players and promote, after migration into the CNS, secondary inflammatory immune process. In light of the “inside-out” idea, they amplify, as peripherally derived autoreactive T cells, secondarily inflammatory immune processes in the
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CNS. In this context, Dendrou et al. argued [16], “… it has been suggested that autoimmune response-instigated neuroaxonal injury triggers a potentially self- sustaining chronic neurodegenerative process. This proceeds even in the absence of continued immune cell infiltration from the periphery, which eventually wanes regardless of therapy, possibly due to immune cell exhaustion associated with chronic antigenic exposure ….”. The concept that T and B cells confer cytotoxicity in MS through the promotion of subroutines of RCD can be discussed for two reasons: First, immune cell- mediated cytotoxicity has already been shown for Th17 cells in studies on EAE [107]), for autoreactive CD8+ T cells (i.e., CTLs) in MS relapses [108], and for B cells in relapsing-remitting MS, whereby CD19+ GzmB+ B cells are thought to exhibit cytotoxic behavior resembling CD8+ T cells [109] (for review, see also [110]). Second, in other lines of studies, preferentially on cancer models, evidence has been provided demonstrating that cytotoxic CD8+ T cells can induce forms of RCD such as pyroptosis, ferroptosis, and (though less proven) necroptosis (for recent reviews, see [111, 112]). Ferroptosis, for example, has been demonstrated to participate in neuron damage in experimental cerebral malaria and be partially induced by activated CD8+ T cells [113]. Pyroptosis was reportedly shown to be responsible for the CTL-mediated death of GSDMB-positive cells, and inflammasome (→ pyroptosis) was found to occur in patients with cutaneous leishmaniasis [114]. Necroptosis is thought to be secondarily activated by TNF that is secreted by DAMP-activated innate immune cells (cf. Fig. 3.8b), whereby the DAMPs are derived from the other forms of RCD. Activation of these highly inflammatory types of RCD, which even can crosstalk via DAMPs with each other, appears to be critical in activating successful antitumor immune responses. In MS, such injuries mediated by cytotoxic T and B cells appear to be equally responsible for relapses [108, 109] and progression and perpetuation of the disease. However, this assumption remains to be proven by future targeted experiments.
8.2.3.5 Genetic Factors Genome-wide association studies identified over 230 MS risk loci in terms of susceptibility variants, many of which overlap with those identified from other autoimmune diseases. The majority of these loci regulate or encode genes that control immune cell functions. Thus, both innate and adaptive immune response-related genes are involved in MS susceptibility, but the HLA-DR and -DQ alleles within the MHC-II region confer the most important contribution, specifically the HLA-DR15 haplotype (HLA-DRB1*15:01) exerting the strongest influence [13, 115–121]. Again, however, the exact functional interpretation of these results remains a challenge, and translation to an understanding of pathobiology will remain a major target for the immediate future. Last but not least, a special reference to evidence that patients with MS display low levels of antioxidant enzymes: Is this a genetic defect of individuals with a predisposition to MS? And indeed, in a recent study on the identification of the potential association of SNPs in nitrative and oxidative stress-related genes, Wigner et al. [122] found that genetic variants in the antioxidant enzymes SOD2, GPX4, catalase, and nitric oxide synthase 2 genes may modulate the risk of MS occurrence.
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8.2.3.6 Epigenetic Factors A low concordance rate of MS in monozygotic twins, the fact that in a disease with estimated heritability above 50%, all identified risk genes jointly explain