Dendritic Cells: Methods and Protocols 1071629379, 9781071629376
This detailed volume provides methods that can be used to study dendritic cell (DC) ontogeny, isolation, migration, and
250 24 11MB
English Pages 383 [384] Year 2023
Preface
Contents
Contributors
Part I: Overview on Mouse and Human Dendritic Cells
Chapter 1: Origin, Phenotype, and Function of Mouse Dendritic Cell Subsets
1 Introduction
2 Ontogeny of Mouse Dendritic Cells
2.1 Conventional DC Development
2.2 Plasmacytoid DC Development
2.3 Contraction of the DC Family
3 The Mouse DC Subsets and Their Functional Specialization
3.1 Conventional DCs
3.1.1 cDC1s
3.1.2 cDC2s
3.2 Plasmacytoid DCs
4 Conclusion
References
Chapter 2: Phenotypes and Functions of Human Dendritic Cell Subsets in the Tumor Microenvironment
1 Introduction
2 Identification and Functions of Human DC Subsets
2.1 Conventional Dendritic Cells
2.1.1 cDC1
2.1.2 cDC2 and LC
2.2 Plasmacytoid Dendritic Cells
2.3 Mature DC
2.4 Other DC Subsets
2.4.1 MoDCs and InfDC
2.4.2 AS-DC, Axl-DC, or DC5
3 Role of DC Subsets in Antitumor Immune Response and on the Overall Clinical Impact
3.1 Sc-RNA seq Studies of Tumor-Associated DC Populations Reveal Five Subsets
3.2 The Antitumor Function of cDC1: Antigen Cross-Presentation, IFN-λ Secretion, and Cross Talk with NK Cells
3.3 The Antitumor Properties of Tumor-associated cDC2
3.4 Inhibition of IFN-I Production by Tumor-Associated pDCs and Their Specific Interaction with Treg
3.5 Mature DC Have an Antitumor Function and Likely Contribute to TLS Formation
3.6 MoDC and LC Roles Are Poorly Characterized in Antitumor Immune Responses
4 In Situ Visualization of Tumor Associated DCs and Prognosis Impact
5 Conclusion
References
Part II: In Vivo Study of Dendritic Cells
Chapter 3: In Vivo Tracking of Dendritic Cell Migration
1 Introduction
2 Materials
2.1 KikGR Mice (See Note 1)
2.2 Light Source and Protective Glasses
2.3 Anesthesia, Flow Cytometry, and Other Instruments and Reagents
2.4 Skin DCs and Lymph Node Cell Purification
3 Methods
3.1 Photoconversion of Skin
3.2 Photoconversion of Proximal Colon or Jejunum and Ileum Excluding the Terminal Ileum
3.3 Purification of Cells from the Skin
3.4 Purification of Cells from LN
3.5 Staining Samples for Flow Cytometric Analysis
3.6 Flow Cytometric Analysis
4 Notes
References
Chapter 4: In Vivo Analysis of Dendritic Cell Clonality
1 Introduction
2 Materials
2.1 Mice
2.2 Reagents
2.3 Equipment
2.4 Instruments
3 Methods
3.1 Tissue Isolation from Clec9aConfetti Mice
3.2 Tissue Processing for Imaging
3.3 (Optional) Fluorescence Antibody Staining for cDC Subsets
3.4 Image Acquisition
4 Notes
References
Chapter 5: Monitoring the Interaction Between Dendritic Cells and T Cells In Vivo with LIPSTIC
1 Introduction
2 Materials
2.1 Mouse Strains and Animal Procedures
2.2 Isolation and Transfer of Naïve CD4+ T Cells
2.3 Immunization
2.4 In Vivo LIPSTIC Labeling and Analysis of LIPSTIC-Labeled Cells by Flow Cytometry
3 Methods
3.1 Adoptive Transfer of Ovalbumin-Specific Naïve Cd40lgSrtA/SrtA CD45.1/1 CD4-Cre OT-II CD4+ T Cells into Cd40G5/G5 Hosts (Se...
3.2 Immunization of Cd40G5/G5 Hosts (See Note 8)
3.3 Injection of SrtA Substrate to Achieve In Vivo LIPSTIC Labeling (See Note 9)
3.4 Analysis of LIPSTIC-Labeled Cells by Flow Cytometry
4 Notes
References
Part III: In Vitro Differentiation of Dendritic Cells
Chapter 6: In Vitro Generation of Murine Bone Marrow-Derived Dendritic Cells
1 Introduction
1.1 GM-CSF-Derived BMDC: A Model for Migratory DCs
1.2 FLT3L-Derived BMDC: A Model for Conventional DC Subsets
2 Materials
3 Methods
3.1 Bone Marrow Cell Preparation
3.2 GM-CSF (+/- IL-4) Cultures
3.3 FLT3L Alone Culture
3.4 FLT3L + GM-CSF Culture
3.5 Summary
4 Notes
References
Chapter 7: In Vitro Generation of Murine Dendritic Cells from Hoxb8-Immortalized Hematopoietic Progenitors
1 Introduction
2 Materials
3 Methods
3.1 Generation and Titration of Hoxb8-ERHBD-Expressing MSCV
3.1.1 Generation of Hoxb8-ERHBD-Expressing MSCV
3.1.2 MSCV Titration (See Note 4)
3.2 Preparation of BM Cells and Generation of Hoxb8-FL Cells
3.2.1 Preparation of BM Cells
3.2.2 Infection of BM Cells and Expansion of Hoxb8-FL Cells
3.2.3 Cell Differentiation and Generation of DC
3.2.4 CRISPR/Cas9-Mediated Gene Deletion Using Lentiviral Vectors
4 Notes
References
Chapter 8: In Vitro Generation of Murine CD8α+ DEC205+ XCR1+ Cross-Presenting Dendritic Cells from Bone Marrow-Derived Hematop...
1 Introduction
2 Materials
2.1 Cell Lines and Cell Culture
2.2 Isolation and Culture of Primary BM-Derived Hematopoietic Progenitors
2.3 Harvesting, Staining, and Flow Cytometric Analysis of Culture-Derived DCs
3 Methods
3.1 Generation of Mitomycin C (MMC)-Treated OP9 Cells
3.2 Production of Flt3L Supernatant for Cell Culture
3.3 Isolation of Hematopoietic Progenitors from BM
3.4 Differentiation of Notch DCs from BM Hematopoietic Progenitors
3.5 Phenotypic Characterization of Culture-Derived DCs
4 Notes
References
Chapter 9: In Vitro Generation of Human Dendritic Cell Subsets from CD34+ Cord Blood Progenitors
1 Introduction
2 Materials
3 Methods
3.1 MS5 and eMS5 Culture
3.2 Generation of the Engineered (e) MS5 for the Growth Factor Production by Retroviral Transduction
3.3 CD34+ Cell Isolation from Cord Blood
3.4 In Vitro eMSC and CD34+ Cell Coculture
4 Notes
References
Chapter 10: In Vitro Generation of Human Cross-Presenting Type 1 Conventional Dendritic Cells (cDC1s) and Plasmacytoid Dendrit...
1 Introduction
2 Materials
2.1 Cell Lines and Feeder Layer Preparation
2.2 Expansion of CD34+ CB Cells
2.3 Cryopreservation and Revival of Expanded CD34+ CB Cells
2.4 Differentiation of DCs from Expanded CD34+ CB Cells
2.5 Staining for Flow Cytometry Analysis
3 Methods
3.1 Maintenance of Cell Lines and Preparation of the Feeder Layers
3.2 Expansion of CD34+ CB Cells
3.3 Cryopreservation of Expanded CD34+ CB Cells
3.4 Revival of Frozen Expanded CD34+ CB Cells
3.5 Preparation of the Feeder Layer for CD34+ Cell Coculture
3.6 Seeding of Expanded CD34+ Cells on Feeder Layer Cells for Differentiation
3.7 Phenotypic Identification of the DC Populations at the End of the Culture
4 Notes
References
Chapter 11: Culture System Allowing the Simultaneous Differentiation of Human Monocytes into Dendritic Cells and Macrophages U...
1 Introduction
2 Materials
2.1 Blood Monocyte Isolation
2.1.1 PBMC Purification
2.1.2 Monocyte Isolation
2.2 Monocyte Culture
2.3 Quantification of Differentiated Cells by Flow Cytometry
3 Methods
3.1 Blood Monocyte Isolation
3.1.1 PBMC Purification
3.1.2 Monocyte Isolation
3.2 Monocyte Culture
3.3 Quantification of Differentiated Cells by Flow Cytometry
4 Notes
References
Chapter 12: Clonal Analysis of Human Dendritic Cell Progenitors Using a Stromal Cell Culture
1 Introduction
2 Materials
3 Methods
3.1 Culture of Stromal Cells (Day 4 to Day 0)
3.1.1 Passaging Stromal Cells
3.1.2 Treating Stromal Cells with Mitomycin C
3.1.3 Plating Mitomycin C-Treated Stromal Cells
3.2 Purification of CD34+ HSPC from Human Cord Blood (Day 0)
3.2.1 Isolation of Cord Blood Mononuclear Cells Using Ficoll-Paque (See Note 8)
3.2.2 Enrichment of CD34+ Cells
3.3 Culture of Purified Cells in Single-Cell Environment (Day 0-7)
3.3.1 Single-Cell Sorting and Plating
3.3.2 Cell Culture Over Time
3.4 Harvest and Analyze CD34+ Cells´ Output (Day 7-21)
3.4.1 Read Cells via Flow Cytometry
4 Notes
References
Part IV: Enrichment of Dendritic Cells
Chapter 13: Enrichment of Large Numbers of Splenic Mouse Dendritic Cells After Injection of Flt3L-Producing Tumor Cells
1 Introduction
2 Materials
2.1 Injection of B16-Flt3L Tumor Cells In Vivo
2.2 Preparation of Single-Cell Suspensions of Splenocytes
2.3 Depletion of T cells, B cells, and Macrophages
2.4 Positive Selection of DCs
3 Methods
3.1 Implantation of B16-Flt3L Tumors in Mice
3.2 Preparation of Single-Cell Suspensions of Splenocytes
3.3 Depletion of T cells, B cells, and Macrophages
3.4 Positive Selection of DC Cells
3.4.1 Protocol A (Positive Selection of CD11c+ Cells)
3.4.2 Protocol B (Positive Selection of CD11c+ mPDCA1+ Cells)
3.4.3 Magnetic Positive Isolation
3.4.4 Verification of Cell Purity by Flow Cytometry
4 Notes
References
Chapter 14: Isolation and Identification of Dendritic Cell Subsets from Human and Mouse Tumors
1 Introduction
2 Materials
2.1 Human Tumor Processing
2.1.1 Mechanical and Enzymatic Tumor Digestion
2.1.2 DC Enrichment
2.1.3 Cell Sorting
2.2 Mouse Tumor Processing
3 Methods
3.1 Human Tumor Processing
3.1.1 Mechanical and Enzymatic Tissue Digestion
3.1.2 Dendritic Cell Enrichment (See Note 8)
3.1.3 Cell Staining and Dendritic Cell Sorting
3.2 Mouse Tumor Processing
3.2.1 Mouse Mammary Tumor Processing
3.2.2 Cell Preparation for FACS Analysis of Murine DCs
4 Notes
References
Part V: Functional Characterization of Dendritic Cells
Chapter 15: Optimized Nonviral Gene Disruption in Primary Murine and Human Myeloid Cells
1 Introduction
2 Materials
2.1 Human Monocyte Preps and Myeloid Cell Culturing
2.2 Mouse BMDM and BMDC Preps and Culturing
2.3 Cas9-RNA Complex Formation
2.4 Monocyte Nucleofection
2.5 Flow Cytometric Analysis of Target Gene Disruption
3 Methods
3.1 Isolation of Human Monocytes
3.1.1 Isolation of Human Peripheral Blood Mononuclear Cells (PBMCs)
3.1.2 Isolation of Human Monocytes
3.2 Murine Bone Marrow Isolation and BMDM Culture
3.2.1 Isolate Bone Marrow from Tibias and Femurs of Mice
3.2.2 BMDM Culture
3.3 Cas9-RNP Complex Formation
3.4 Monocyte Nucleofection
3.4.1 Preparing Cells and Reagents for Electroporation
3.4.2 Electroporation of Cas9-RNP Complexes Produced in Subheading 3.3
3.5 Human Myeloid Cell Culturing Post Nucleofection
3.5.1 Human Monocyte-Derived Dendritic Cell Culturing
3.5.2 Human Monocyte-Derived Macrophage Culturing
3.6 Mouse BMDC and BMDM Culturing Post Nucleofection
3.6.1 BMDC Culturing
3.6.2 BMDM Culturing
3.7 Flow Cytometry Analysis of Knockout Frequency
4 Notes
References
Chapter 16: Characterization of Dendritic Cell Metabolism by Flow Cytometry
1 Introduction
2 Materials
2.1 Cellular Systems
2.2 Flow Cytometry Reagents and Equipment
2.3 Intracellular Staining for Metabolic Phosphorylated Proteins
2.4 Metabolic Dyes
3 Methods
3.1 Intracellular Staining of Phosphorylated Metabolic Proteins
3.1.1 Fixation
Fixation Prior to Tissue Processing
Fixation of Single-Cell Suspensions After Tissue or Blood Processing
Fixation of In Vitro-Cultured DCs
3.1.2 Staining Procedure
3.2 Glucose and Lipid Metabolism
3.2.1 Staining Procedure
3.3 Mitochondrial Metabolism
3.3.1 Staining Procedure
3.4 ROS Staining
3.4.1 Staining Procedure
3.5 Metabolic Panel Tested on Cytek Spectral Flow Cytometer
4 Notes
References
Chapter 17: In Vivo and In Vitro Assay to Address Dendritic Cell Antigen Cross-Presenting Capacity
1 Introduction
2 Materials
2.1 Reagents and Plasticware
2.2 Gamma Irradiation Source
2.3 Transgenic Mice
3 Methods
3.1 In Vitro Assay to Address DC Cross-Presenting Capacity
3.1.1 Preparation of Single-Cell Suspensions
3.1.2 Preparation of Labeled OT-I Cells
3.1.3 Antigen (OVA) Loading of Cells by Osmotic Shock
3.1.4 Cross-Priming of OT-I by DCs
3.2 In Vivo Assay to Address DC Cross-Presenting Capacity
3.2.1 Preparation of OT-I Cells at Day 0
3.2.2 Preparation of Labeled OT-I Cells at Day 0
3.2.3 Injections of Labeled OT-I Cells at Day 0
3.2.4 Preparation of Antigen-Loaded Cells at Day 1
3.2.5 Injection of Antigen-Loaded Cells at Day 1
4 Notes
References
Chapter 18: Assays to Detect Cross-Dressing by Dendritic Cells In Vivo and In Vitro
1 Introduction
2 Materials
2.1 In Vitro Assay for Cross-Dressing
2.2 In Vivo Assay for Cross-Dressing
3 Methods
3.1 Assays to Study Cross-Dressing In Vitro (See Fig. 1)
3.1.1 Culture of Bone Marrow-Derived Dendritic Cells (BMDCs)
3.1.2 Culture of EL4 and EG7 Cells and Pulsing of EG7 Cells with SIINFEKL
3.1.3 Detection of Cross-Dressing of BALB/c BMDCs with SIINFEKL-Kb Complexes
3.1.4 Labeling of OT-I Cells with CFSE
3.1.5 FACS Sorting of BMDCs After Co-Culture with Tumor Cells
3.1.6 Functional Validation of Cross-Dressing by Co-Culturing Sorted BMDCs with CFSE-Labeled OT-I Cells
3.2 Assays to Study Cross-Dressing In Vivo (See Fig. 2)
3.2.1 Injection of SIINFEKL-Pulsed EL4 Tumor Cells into H2Kbm1 Mice
3.2.2 Preparation of Single-Cell Suspension from Draining Lymph Nodes
3.2.3 Staining of the Dendritic Cells in the Single-Cell Suspension
3.2.4 Sorting and Co-Culture of DCs with CFSE-Labeled OT-I Cells
4 Notes
References
Chapter 19: Assessing the Ability of Human Dendritic Cells to Stimulate Naive CD4+ and CD8+ T Cells
1 Introduction
2 Materials
2.1 Polarization of Blood Naive CD4+ T Cells
2.1.1 Blood Naive CD4+ T Cell Isolation
2.1.2 Staining CD4+ T Cells with a Proliferation Dye
2.1.3 CD4+ T Cells and DC Co-Culture
2.1.4 Detection of Cytokines by Intracellular Flow Cytometry
2.2 Differentiation of Blood Naive CD8+ T Cells into Effector Cells
2.2.1 Blood Naive CD8+ T Cell Isolation
2.2.2 Staining CD8+ T Cells with a Proliferation Dye
2.2.3 T Cells and DC Co-Culture
2.2.4 Detection of Effector Molecules by Intracellular Flow Cytometry
3 Methods
3.1 Polarization of Blood Naive CD4+ T Cells
3.1.1 Blood Naive CD4+ T Cell Isolation
3.1.2 Staining of Naive CD4+ T Cells with a Proliferation Dye
3.1.3 Allogeneic Co-Culture with DC
3.1.4 Detection of Cytokines by Intracellular Flow Cytometry
3.2 Differentiation of Blood Naive CD8+ T Cells into Effector Cells
3.2.1 Blood Naive T Cell Isolation
3.2.2 Staining of Naive CD8+ T Cells with a Proliferation Dye
3.2.3 Allogeneic Co-Culture with DC
3.2.4 Detection of Effector Molecules by Intracellular Flow Cytometry
4 Notes
References
Chapter 20: In Vitro and In Vivo Assays to Evaluate Dendritic Cell Phagocytic Capacity
1 Introduction
2 Materials
2.1 In Vitro Generation of Bone-Marrow-Derived Dendritic Cells (BMDCs)
2.2 In Vitro Generation of Conventional Dendritic Cells Type 1 (cDC1)
2.3 Ex Vivo Purification of Conventional Dendritic Cells Type 1 (cDC1)
2.4 Phagocytosis Assay
3 Methods
3.1 Generating BM-DCs and cDC1
3.1.1 Day 0: Collection of Bone Marrow from the Femur and Tibia
3.1.2 Generation of BMDCs
3.1.3 Generation of cDC1
Preparation of the OP9-DL1 Feeder Cell Line
Differentiation of BM Cells into cDC1
3.2 Ex Vivo cDC1 Purified from the Spleen
3.3 Preparation of NH2 Beads
3.4 Phagocytosis Assay
3.4.1 In Vitro Phagocytosis Assay
3.4.2 Ex Vivo Phagocytosis Assay
4 Notes
References
Chapter 21: Tracking Plasmacytoid Dendritic Cell Response to Physical Contact with Infected Cells
1 Introduction
2 Materials
2.1 Isolation of pDCs from Peripheral Blood Mononuclear Cells (PBMCs)
2.2 Biological Reagents: Infected Cells
2.3 Enzyme-Linked Immunosorbent Assay (ELISA)
2.4 Flow Cytometry Analysis for the Profiling of pDC Activation
2.5 Imaging Combined with Flow Cytometry Analysis of the Frequency of pDC/Infected Cell Conjugates (Image Stream X Technology)
2.6 Antiviral Activity of pDCs Defined by Flow Cytometry Analysis of Viral Spread
2.7 Imaging of the Cell-Cell Contacts by Confocal Microscopy
2.8 Live Imaging of the Cell Contacts by Spinning-Disk Confocal Microscopy
3 Methods
3.1 Isolation of PBMCs from the Blood of Healthy Adult Human Volunteers
3.2 Isolation of pDCs from PBMCs
3.3 Infection of the Cells and Coculture with Isolated pDCs for the Analysis of Cytokine Production
3.4 Flow Cytometry Analysis of the Activation Profile of pDCs Induced by Contact with Infected Cells
3.5 Quantification of pDC/Infected Cell Conjugates and Its Molecular Regulation by a Technology Combining Imaging and Flow Cyt...
3.6 Antiviral Activity of pDCs Defined by Flow Cytometry
3.7 Analysis of Cell-Cell Contacts at Subcellular Level by Immunofluorescence and Confocal Microscopy Analysis
3.8 Imaging of the Cell-Cell Contacts at Single-Cell Level by Spinning-Disk Confocal Microscopy
4 Notes
References
Untitled
Part VI: Omic Approaches to Study Dendritic Cells
Chapter 22: Harnessing Single-Cell RNA Sequencing to Identify Dendritic Cell Types, Characterize Their Biological States, and ...
1 Introduction
2 Materials
2.1 List of Files to Download
2.2 Download the Input Files
2.3 Download the Files for the Signature Generation
2.4 Download the .R Scripts to Run Single-Cell CMAP
2.5 Download the Docker File
2.6 Programs and Packages Used in This Workflow
3 Methods
3.1 Running the Seurat Workflow on All the Cells from the Original Data File
3.2 Running the Seurat Workflow on the Selected cDC1s
3.3 Trajectory Inference Using Monocle
3.4 Trajectory Inference Based on Velocity Analysis
3.5 Analysis of Mature cDC1s
3.6 Analyzing the Transcriptional Differences between Clusters of Interest
4 Notes
References
Chapter 23: Characterization of Developmental Trajectories of Dendritic Cell Hematopoiesis Through Single-Cell RNA Sequencing ...
1 Introduction
2 Materials
2.1 Mouse Bone Marrow Processing
2.2 Datasets
2.3 Software for Processing and Analyses of scRNA-seq Data
2.4 Packages for Trajectory Analyses of scRNA-seq Bone Marrow Data
3 Methods
3.1 Processing of Mouse Bone Marrow
3.2 Enrichment of Bone Marrow Progenitors
3.3 Staining of Mouse Bone Marrow Progenitors for Cell Sorting
3.3.1 If Progenitor Cells Were Not Enriched
3.3.2 If Progenitor Cells Were Enriched
3.4 ScRNA-seq Analyses of DC Progenitor Trajectories
3.4.1 Analyses of scRNA-seq Data Using the Seurat Pipeline
3.4.2 Analyses of Developmental Trajectories Using mpath
3.4.3 Employing cMap to Identify Gene Enrichment for pDC Versus cDC Lineage Commitment
3.4.4 Analyses of Developmental Trajectories Using Slingshot
4 Notes
References
Index
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Methods in Molecular Biology 2618
Vanja Sisirak Editor
Dendritic Cells Methods and Protocols
METHODS
IN
MOLECULAR BIOLOGY
Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, UK
For further volumes: http://www.springer.com/series/7651
For over 35 years, biological scientists have come to rely on the research protocols and methodologies in the critically acclaimed Methods in Molecular Biology series. The series was the first to introduce the step-by-step protocols approach that has become the standard in all biomedical protocol publishing. Each protocol is provided in readily-reproducible step-by step fashion, opening with an introductory overview, a list of the materials and reagents needed to complete the experiment, and followed by a detailed procedure that is supported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitute the key ingredient in each and every volume of the Methods in Molecular Biology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexed in PubMed.
Dendritic Cells Methods and Protocols
Edited by
Vanja Sisirak UMR CNRS 5164 – Immunoconcept, Université de Bordeaux, Bordeaux, France
Editor Vanja Sisirak UMR CNRS 5164 – Immunoconcept Universite´ de Bordeaux Bordeaux, France
ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-2937-6 ISBN 978-1-0716-2938-3 (eBook) https://doi.org/10.1007/978-1-0716-2938-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 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 Humana imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.
Preface This edition of dendritic cell protocols is aimed at providing researchers with an overview of methods that can be used to study dendritic cell (DC) ontogeny, isolation, migration, and functions. An introductory review on murine and human DC subsets and their unique transcriptional, phenotypic, and functional properties will familiarize the readers with the current state of the art. Then, novel murine models to characterize in vivo each DC subset developmental paths and functional properties are described. In vitro methods to generate DCs and decipher their ontogeny are addressed next. Protocols to isolate DCs from multiple tissues and assess their unique functional properties are then detailed. Finally, novel omic approaches to elucidate DC heterogeneity, ontogeny, and activation states are provided. Each chapter was written by experts in the field and includes introductions to the relevant topic, the list of necessary materials/reagents, and a step-by-step protocol. In addition, each experts provides tips on troubleshooting to avoid common pitfalls as well as pro and cons of certain methods over others. Vanja Sisirak
Bordeaux, France
v
Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
PART I
OVERVIEW ON MOUSE AND HUMAN DENDRITIC CELLS
1 Origin, Phenotype, and Function of Mouse Dendritic Cell Subsets . . . . . . . . . . . Dorothe´e Duluc and Vanja Sisirak 2 Phenotypes and Functions of Human Dendritic Cell Subsets in the Tumor Microenvironment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Candice Sakref, Nathalie Bendriss-Vermare, and Jenny Valladeau-Guilemond
PART II
3
17
IN VIVO STUDY OF DENDRITIC CELLS
3 In Vivo Tracking of Dendritic Cell Migration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michio Tomura 4 In Vivo Analysis of Dendritic Cell Clonality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mar Cabeza-Cabrerizo 5 Monitoring the Interaction Between Dendritic Cells and T Cells In Vivo with LIPSTIC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Giulia Pasqual, Aleksey Chudnovskiy, and Gabriel D. Victora
PART III
v xi
39 55
71
IN VITRO DIFFERENTIATION OF DENDRITIC CELLS
6 In Vitro Generation of Murine Bone Marrow–Derived Dendritic Cells . . . . . . . . 83 Yohan Gerber-Ferder, Pierre Bourdely, Mathias Vetillard, Pierre Guermonprez, and Julie Helft 7 In Vitro Generation of Murine Dendritic Cells from Hoxb8-Immortalized Hematopoietic Progenitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Hans H€ a cker 8 In Vitro Generation of Murine CD8α+ DEC205+ XCR1+ Cross-Presenting Dendritic Cells from Bone Marrow–Derived Hematopoietic Progenitors . . . . . . 109 Margaret E. Kirkling and Boris Reizis 9 In Vitro Generation of Human Dendritic Cell Subsets from CD34+ Cord Blood Progenitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Pierre Bourdely, Roberto Savoldelli, Mathias Vetillard, Giorgio Anselmi, Julie Helft, and Pierre Guermonprez 10 In Vitro Generation of Human Cross-Presenting Type 1 Conventional Dendritic Cells (cDC1s) and Plasmacytoid Dendritic Cells (pDCs) . . . . . . . . . . . 133 Xinlong Luo, Sreekumar Balan, Catharina Arnold-Schrauf, and Marc Dalod
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Contents
Culture System Allowing the Simultaneous Differentiation of Human Monocytes into Dendritic Cells and Macrophages Using M-CSF, IL-4, and TNF-α. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 Javiera Villar, Alice Coillard, Corne´ van Roessel, and Elodie Segura Clonal Analysis of Human Dendritic Cell Progenitors Using a Stromal Cell Culture. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Kang Liu, Jaeyop Lee, and Thomas Luh
PART IV 13
14
Enrichment of Large Numbers of Splenic Mouse Dendritic Cells After Injection of Flt3L-Producing Tumor Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Pauline Santa, Anaı¨s Roubertie, Se´verine Loizon, Anne Garreau, Amandine Ferriere, Dorothe´e Duluc, and Vanja Sisirak Isolation and Identification of Dendritic Cell Subsets from Human and Mouse Tumors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Yamila Rocca, Aure´lien Voissie`re, Jenny Valladeau-Guilemond, and Nathalie Bendriss-Vermare
PART V 15
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ENRICHMENT OF DENDRITIC CELLS
FUNCTIONAL CHARACTERIZATION OF DENDRITIC CELLS
Optimized Nonviral Gene Disruption in Primary Murine and Human Myeloid Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emily C. Freund, Simone M. Haag, Benjamin Haley, and Aditya Murthy Characterization of Dendritic Cell Metabolism by Flow Cytometry . . . . . . . . . . . Eline C. Brombacher, Thiago A. Patente, Marjolein Quik, and Bart Everts In Vivo and In Vitro Assay to Address Dendritic Cell Antigen Cross-Presenting Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pengju Ou, Lifen Wen, Hai Ni, and Cliff Y. Yang Assays to Detect Cross-Dressing by Dendritic Cells In Vivo and In Vitro. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alok Das Mohapatra and Pramod K. Srivastava Assessing the Ability of Human Dendritic Cells to Stimulate Naive CD4+ and CD8+ T Cells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alice Coillard, Tsing-Lee Tang-Huau, and Elodie Segura In Vitro and In Vivo Assays to Evaluate Dendritic Cell Phagocytic Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lucie Maisonneuve and Be´ne´dicte Manoury Tracking Plasmacytoid Dendritic Cell Response to Physical Contact with Infected Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Margarida Sa´ Ribeiro, Garima Joshi, Elodie De´cembre, Ce´lia Nuovo, Adrien Bosseboeuf, Alicia Bellomo, Manon Venet, Sonia Assil, and Marle`ne Dreux
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PART VI
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OMIC APPROACHES TO STUDY DENDRITIC CELLS
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Harnessing Single-Cell RNA Sequencing to Identify Dendritic Cell Types, Characterize Their Biological States, and Infer Their Activation Trajectory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 Ammar Sabir Cheema, Kaibo Duan, Marc Dalod, and Thien-Phong Vu Manh 23 Characterization of Developmental Trajectories of Dendritic Cell Hematopoiesis Through Single-Cell RNA Sequencing Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Regine J. Dress and Florent Ginhoux Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Contributors GIORGIO ANSELMI • King’s College London, Centre for Inflammation Biology and Cancer Immunology, London, UK; Oxford University, Radcliffe Department of Medicine, Oxford, UK CATHARINA ARNOLD-SCHRAUF • Aix Marseille Univ, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France; Celgene Austria GmbH, Vienna, Austria SONIA ASSIL • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France SREEKUMAR BALAN • Aix Marseille Univ, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France; The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA ALICIA BELLOMO • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France NATHALIE BENDRISS-VERMARE • Univ Lyon, Universite´ Claude Bernard Lyon 1, INSERM U1052, CNRS 5286, Centre de Recherche en Cance´rologie de Lyon, Lyon, France; LabEx DEVweCAN, Lyon, France; Laboratoire d’Immunothe´rapie des Cancers de Lyon (LICL), Lyon, France ADRIEN BOSSEBOEUF • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France PIERRE BOURDELY • Universite´ de Paris, Centre for Inflammation Research, CNRS ERL8252, INSERM1149, Paris, France; Institut Cochin, INSERM U1016, CNRS UMR8104, Universite´ de Paris Cite´, Paris, France ELINE C. BROMBACHER • Department of Parasitology, Leiden University Medical Centre, Leiden, Netherlands MAR CABEZA-CABRERIZO • Immunobiology Laboratory, The Francis Crick Institute, London, UK; Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, Cambridge, UK AMMAR SABIR CHEEMA • Aix Marseille Univ, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France ALEKSEY CHUDNOVSKIY • Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA ALICE COILLARD • Institut Curie, INSERM, U932, Paris, France MARC DALOD • Aix Marseille Univ, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France ELODIE DE´CEMBRE • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France REGINE J. DRESS • Institute of Systems Immunology, Hamburg Center for Translational Immunology (HCTI), University Medical Center Hamburg-Eppendorf, Hamburg, Germany MARLE`NE DREUX • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France KAIBO DUAN • Singapore Immunology Network (SIgN), A*STAR, Singapore, Singapore
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xii
Contributors
DOROTHE´E DULUC • Universite´ de Bordeaux, CNRS, ImmunoConcEpT, UMR 5164, Bordeaux, France BART EVERTS • Department of Parasitology, Leiden University Medical Centre, Leiden, Netherlands AMANDINE FERRIERE • Universite´ de Bordeaux, CNRS, ImmunoConcEpT, UMR 5164, Bordeaux, France EMILY C. FREUND • Department of Molecular Biology, Genentech, South San Francisco, CA, USA ANNE GARREAU • Universite´ de Bordeaux, CNRS, ImmunoConcEpT, UMR 5164, Bordeaux, France YOHAN GERBER-FERDER • PSL University, Institut Curie Research Center, INSERM U932, Center for Cancers Immunotherapy, Paris, France FLORENT GINHOUX • Singapore Immunology Network (SIgN), Agency for Science, Technology and Research, Singapore, Singapore; Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore; Gustave Roussy Cancer Campus, Villejuif, France; Institut National de la Sante´ et de la Recherche Me´dicale (INSERM) U1015, Equipe Labellise´e - Ligue Nationale contre le Cancer, Villejuif, France PIERRE GUERMONPREZ • Universite´ de Paris, Centre for Inflammation Research, CNRS ERL8252, INSERM1149, Paris, France SIMONE M. HAAG • Department of Cancer Immunology, Genentech, South San Francisco, CA, USA HANS HA€ CKER • Laboratory of Innate Immunity and Signal Transduction, Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT, USA BENJAMIN HALEY • Department of Molecular Biology, Genentech, South San Francisco, CA, USA JULIE HELFT • PSL University, Institut Curie Research Center, INSERM U932, Center for Cancers Immunotherapy, Paris, France; Universite´ de Paris, Centre for Inflammation Research, CNRS ERL8252, INSERM1149, Paris, France; Universite´ de Paris - Inserm Cnrs, Institut Cochin, Paris, France; Institut Cochin, Paris, France GARIMA JOSHI • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France MARGARET E. KIRKLING • Genomic Sciences- R&D, GSK, Collegeville, PA, USA JAEYOP LEE • Memorial Sloan Kettering Cancer Center, New York, NY, USA KANG LIU • Cancer Immunology and Immune Modulation, Boehringer Ingelheim, Ridgefield, CT, USA SE´VERINE LOIZON • Universite´ de Bordeaux, CNRS, ImmunoConcEpT, UMR 5164, Bordeaux, France THOMAS LUH • University of California San Francisco, School of Medicine, San Francisco, CA, USA XINLONG LUO • Aix Marseille Univ, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France LUCIE MAISONNEUVE • Institut Necker Enfants Malades, INSERM U1151-CNRS UMR 8253, Universite´ de Paris, Faculte´ de Me´decine Necker, Paris, France THIEN-PHONG VU MANH • Aix Marseille Univ, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France
Contributors
xiii
BE´NE´DICTE MANOURY • Institut Necker Enfants Malades, INSERM U1151-CNRS UMR 8253, Universite´ de Paris, Faculte´ de Me´decine Necker, Paris, France ALOK DAS MOHAPATRA • Department of Immunology and Carole and Ray Neag Comprehensive Cancer Center, University of Connecticut School of Medicine, Farmington, CT, USA; TScan Therapeutics, Preclinical In Vivo Pharmacology Division, Waltham, MA, USA ADITYA MURTHY • Department of Cancer Immunology, Genentech, South San Francisco, CA, USA; Gilead Sciences, Foster City, CA, USA HAI NI • Department of Immunology, Sun Yat-sen University Zhongshan School of Medicine, Guangzhou, Guangdong, China CE´LIA NUOVO • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France PENGJU OU • Department of Immunology, Sun Yat-sen University Zhongshan School of Medicine, Guangzhou, Guangdong, China GIULIA PASQUAL • Laboratory of Synthetic Immunology, Department of Surgery Oncology and Gastroenterology, University of Padova, Padova, Italy; Veneto Institute of Oncology IOV-IRCCS, Padova, Italy THIAGO A. PATENTE • Department of Parasitology, Leiden University Medical Centre, Leiden, Netherlands MARJOLEIN QUIK • Department of Parasitology, Leiden University Medical Centre, Leiden, Netherlands BORIS REIZIS • Department of Pathology, New York University School of Medicine, New York, NY, USA MARGARIDA SA´ RIBEIRO • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France YAMILA ROCCA • Centre de Recherche en Cance´rologie de Lyon, INSERM U1052, CNRS UMR5286, Universite´ de Lyon, Universite´ Lyon 1, Centre Le´on Be´rard, Lyon, France ANAI¨S ROUBERTIE • Universite´ de Bordeaux, CNRS, ImmunoConcEpT, UMR 5164, Bordeaux, France CANDICE SAKREF • Univ Lyon, Universite´ Claude Bernard Lyon 1, INSERM U1052, CNRS 5286, Centre de Recherche en Cance´rologie de Lyon, Lyon, France; LabEx DEVweCAN, Lyon, France PAULINE SANTA • Universite´ de Bordeaux, CNRS, ImmunoConcEpT, UMR 5164, Bordeaux, France ROBERTO SAVOLDELLI • King’s College London, Centre for Inflammation Biology and Cancer Immunology, London, UK; Universite´ de Paris, INSERM U1149, CNRS erl8252, Centre for Inflammation Research, Universite´ de Paris Cite´, Paris, France ELODIE SEGURA • Institut Curie, INSERM, U932, Paris, France VANJA SISIRAK • UMR CNRS 5164 – Immunoconcept, Universite´ de Bordeaux, Bordeaux, France PRAMOD K. SRIVASTAVA • Department of Immunology and Carole and Ray Neag Comprehensive Cancer Center, University of Connecticut School of Medicine, Farmington, CT, USA TSING-LEE TANG-HUAU • Institut Curie, INSERM, Paris, France MICHIO TOMURA • Laboratory of Immunology, Faculty of Pharmacy, Osaka Ohtani University, Tondabayashi, Osaka, Japan
xiv
Contributors
JENNY VALLADEAU-GUILEMOND • Univ Lyon, Universite´ Claude Bernard Lyon 1, INSERM U1052, CNRS 5286, Centre de Recherche en Cance´rologie de Lyon, Lyon, France; LabEx DEVweCAN, Lyon, France CORNE´ VAN ROESSEL • Institut Curie, INSERM, U932, Paris, France MANON VENET • CIRI, Inserm, U1111, Universite´ Claude Bernard Lyon 1, CNRS, UMR5308, E´cole Normale Supe´rieure de Lyon, Univ Lyon, Lyon, France MATHIAS VETILLARD • Universite´ de Paris, Centre for Inflammation Research, CNRS ERL8252, INSERM1149, Paris, France GABRIEL D. VICTORA • Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA JAVIERA VILLAR • Institut Curie, INSERM, U932, Paris, France AURE´LIEN VOISSIE`RE • Centre de Recherche en Cance´rologie de Lyon, INSERM U1052, CNRS UMR5286, Universite´ de Lyon, Universite´ Lyon 1, Centre Le´on Be´rard, Lyon, France LIFEN WEN • Department of Immunology, Sun Yat-sen University Zhongshan School of Medicine, Guangzhou, Guangdong, China CLIFF Y. YANG • Department of Immunology, Sun Yat-sen University Zhongshan School of Medicine, Guangzhou, Guangdong, China
Part I Overview on Mouse and Human Dendritic Cells
Chapter 1 Origin, Phenotype, and Function of Mouse Dendritic Cell Subsets Dorothe´e Duluc and Vanja Sisirak Abstract Dendritic cells are cells of hematopoietic origin that are specialized in antigen presentation and instruction of innate and adaptive immune responses. They are a heterogenous group of cells populating lymphoid organs and most tissues. Dendritic cells are commonly separated in three main subsets that differ in their developmental paths, phenotype, and functions. Most studies on dendritic cells were done primarily in mice; therefore, in this chapter, we propose to summarize the current knowledge and recent progress on mouse dendritic cell subsets’ development, phenotype, and functions. Key words Conventional dendritic cells, Plasmacytoid dendritic cells, DC ontogeny, DC subsets
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Introduction Dendritic cells (DCs) were first identified ~50 years ago by Ralph Steinman and Zanvil Cohn as crucial cells required for the activation of T cells, thus bridging innate and adaptive immunity [1]. Due to their ability to capture and present antigens to T cells through major histocompatibility complex (MHC) molecules, DCs were classified as professional antigen-presenting cells (APCs) [2]. DCs develop in the bone marrow (BM) from hematopoietic stem cells (HSCs) and then populate most tissues [2]. DCs are indeed found in the circulation, primary and secondary lymphoid organs, mucosal surfaces, and multiple organs such as the liver and the kidney [3]. This strategic location across the organism allows DCs to play a role of sentinel by patrolling their surroundings via their protrusions (dendrites). DCs express multiple pathogen recognition receptors (PRRs) enabling them to sense microbial infections and tissue damage [3, 4]. Upon pathogen encounter and/or tissue damage, DCs become activated (upregulate costimulatory (CD80/86) and MHC-II molecules) and secrete inflammatory cytokines to alert the immune system of a potential threat
Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_1, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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[3, 4]. The activation of DCs also induces the upregulation of chemokine receptors on their surface, most notably CCR7, which allows their migration into T cell areas of secondary lymphoid organs [5]. There, DCs present antigens (Ag) from the periphery in the context of MHC-I and MHC-II molecules to naı¨ve CD8 and CD4 T cells, respectively [3, 4]. The presentation of Ag to T cells when associated with costimulatory signals (surface molecules and cytokines) leads to an effective T cell activation and their specific instruction in order to generate T cell responses adapted to the types of threats encountered [3, 4]. In addition, DCs continually and constitutively present tissue-derived self-antigens to T cells, ultimately leading to tolerance against those self-antigens [6, 7]. This constitutes the life cycle of DCs that was initially characterized using Langerhans cells (LCs) as an archetypal DCs. With these initial observations, multiple studies have revealed crucial updates to this DC life cycle [4]. It is now admitted that DCs are a heterogenous group of cells with distinct functions. Not only multiple DC subsets display unique functions, but their development from HSCs (ontogeny) is unique and require specific transcription factors directing their faith [2]. There are two main subsets of conventional DCs (cDCs), including cDC1 and cDC2, which mostly differ in their ability to activate T cell responses [2]. cDC1 presents exogenous cell-associated Ag to cytotoxic CD8 T lymphocytes (CTLs), and cDC2 presents exogenous soluble Ag to helper CD4 T cells [2–4]. Plasmacytoid DCs (pDCs) are an unconventional subset of DCs due to their lack of dendritic morphology and their poor ability to activate T cell responses. They are rather involved in the production of type I interferons (IFN-I) in response to viral infections [8, 9]. The discovery of DC heterogeneity has also shown that DCs divide their labor. Those present in tissues are capable of transferring antigens to secondary lymphoid organ resident DCs to enhance T cell activation [10, 11]. In addition, resident DCs can acquire soluble and particulate antigens that directly reach in secondary lymphoid organs through passive drainage [12, 13]. Therefore, the life cycle of DCs has evolved over the past 2 decades, most notably thanks to a better characterization of the three main DC subsets in mice. In this review chapter, we will provide an overview of the recent studies related to the development of mouse cDCs and pDCs and their functional specialization.
2
Ontogeny of Mouse Dendritic Cells All DCs originate from BM-derived HSCs [2]. Their half-life is rather short, that is, ~7–14 days for cDCs and pDCs, and they require the contribution BM-derived HSCs for their replenishment [14]. The development of DCs is dependent on the cytokine
Overview on Mouse Dendritic Cell Subsets
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FMS-like tyrosine kinase 3 ligand (FLT3L). Mice deficient in Flt3l constitutively lack all cDCs as well as pDCs [15, 16]. In addition, supplementation with FLT3L in mice expands cDCs and pDCs in vivo [17, 18], and cultures of BM cells in the presence of FLT3L in vitro allow the differentiation of both cDCs and pDCs [19]. Here, we describe the specific developmental routes of cDCs and pDCs and the transcriptional control of their fates. 2.1 Conventional DC Development
As indicated above, cDCs originate from BM-derived HSCs. It is thought that HSCs give rise to multipotent progenitors (MPPs), which are highly proliferative cells that contribute to most of the blood lineages [2]. The specification of the cDC lineage was suggested to occur early in the development at the level of HSCs and/or MPPs that express high levels of the interferon regulatory factor (IRF)-8 [20, 21]. Even though cell fates may be locked early in development, it is admitted that MPPs give rise to intermediate progenitors including common lymphoid progenitors (CLPs) and common myeloid progenitors (CMPs). All lymphoid lineages including T cells and B cells originate from CLPs, and CMPs differentiate into myeloid lineages including granulocytes, monocytes, and cDCs [2]. A common DC precursor (CDP) was shown to develop from CMPs [22, 23] and to give rise to cDC1 and cDC2 precursors called pre-cDC1 and pre-cDC2 [24, 25]. Such pre-cDCs then leave the BM in an immature state and seed different tissues where they terminate their differentiation by integrating local cues [2]. Multiple recent studies have identified the genetic determinants for cDC differentiation. The expression of Irf8, Batf3, Id2, and Nfil3 is required for the development of cDC1 [2]. Individual deficiencies in Batf3 [26], Id2 [27], and Nfil3 [28] lead to the depletion of cDC1; however, over time, cDC1 re-appear [29, 30]. On the other hand, Irf8 deficiency causes an irreversible loss of cDC1 indicating its nonredundant function [31, 32]. It was also recently suggested that IRF8 is required for cDC1 maintenance and that its deletion in mature/terminally differentiated cDC1 leads to their conversion into cDC2-like cells [33]. The expression of Irf8 was shown to be regulated by three enhancers. The one located at +32 kb from the transcription start site is required for cDC1 maintenance, while the one located at +41 kb is active early in development in CDP and required for pre-cDC1 differentiation [32]. The third enhancer of Irf8 located at -50 kb does not regulate cDC1 development but rather regulates Irf8 expression in monocyte and macrophages [32]. The genetic determinants for cDC2 commitment from CDP are less understood. It was initially thought that the transcription factor IRF4 is crucial for the development of cDC2. However, Irf4-deficient mice still develop a small population of cDC2 [34], and IRF4 controls a limited number of genes specifically associated with cDC2-specific
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function [35]. A very recent study has shown that Zeb2 expression is required for cDC2 development and that the deletion of the specific enhancers at –165 kb prior the transcription start site regulating Zeb2 expression abrogated pre-cDC2 specification and mature cDC2 development in vivo [36]. These enhancers are bound by NFIL3 and C/EBP proteins, which are respectively repressing and enhancing Zeb2 expression, suggesting that CDP divergence into cDC1 or cDC2 is controlled by competition between NFIL3 and C/EBPs at this Zeb2 enhancer [36]. Finally, cDC2 show further heterogeneity, including two distinct subsets requiring either NOTCH2 receptor [34, 37, 38] or KLF4 transcription factor for their development [30]. The NOTCH2 receptor is required for the development of ESAM+ cDC2 present in the spleen and CD11b+ and CD103+ intestinal cDCs [38], while KLF4 mostly regulates the development of CD11b- cDC2 [30]. Another recent study has found heterogeneity in the cDC2 compartment based on the expression of the Tbet and Rorγt that show distinct metabolic and inflammatory programs [39]. Nevertheless, how these cDC2 subsets are affiliated to NOTCH2- or KLF4-dependent cDC2 previously described remains to be elucidated. 2.2 Plasmacytoid DC Development
The development of pDCs remains unclear and currently debated. It is established that pDCs originate from BM-derived HSCs and that their development is dependent on the FLT3L as for cDCs [15, 16]. Unlike cDCs, which exit the BM at a precursor state and terminate their specification in tissues, pDCs fully differentiate in the BM and then emigrate into peripheral sites [8, 9]. Given their requirement for FLT3L, pDCs were thought to share ancestry with cDCs. In addition, CDP that were initially shown to exhibit a dual pDC and cDC differentiation potential in vivo and in vitro [22, 23]. The development of pDCs requires the expression of the transcription factor E2-2 (encoded by the Tcf4 gene), and the loss of Tcf4 was reported to induce pDC depletion [40] in part due to their conversion into cDC-like cells [41]. TCF4 acts jointly with its protein cofactor MTG16 [42] and additional factors such as BCL11A [43] to promote pDC development. The expression of E2-2 is regulated by the transcriptional repressor ID2, which is required for the specification of pre-cDC1 from CDP, further indicating an intricate connection between cDC and pDC lineages [44]. This common developmental pathway of cDCs and pDCs was also supported by recent lineage tracing studies combined with clonal DNA barcoding, which have revealed a common and clonal origin of cDCs and pDCs from progenitors expressing CX3CR1 [45]. This common developmental path between cDCs and pDCs was challenged by observations indicating that pDCs originate from lymphoid progenitors (CLP), which do not give rise to
Overview on Mouse Dendritic Cell Subsets
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cDCs [46, 47]. Indeed, lineage- CD127+ CD135+ CD117int/low Ly6D+ SiglecH+ pre-pDC progenitors were identified as differentiating uniquely into pDCs and traced back to a CLP origin [46]. Due to these finding indicating a distinct developmental path of pDCs from cDC, the authors suggested to rename pDCs as innate lymphoid cells specialized in IFN-I production [46]. This lymphoid origin of pDCs is in accordance with studies that indicated that pDCs are transcriptionally divergent from cDCs and express multiple genes related to the lymphoid lineage [48]. Nevertheless, a recent study has shown that similar BM-derived precursor cells expressing Ly6D and Siglec H exhibit the potential to give rise to both pDCs and cDCs [49]. Therefore, the development of pDC requires further studies to delineate their lymphoid and myeloid origins and to assess whether heterogeneity may exist within this particular DC subset with distinct functional features according to their origin. 2.3 Contraction of the DC Family
As mentioned in the introduction, the archetypal DCs that were used to initially delineate DC function were LCs. However, multiple recent studies indicated that LCs have a unique developmental path closely resembling tissues macrophages [50]. LCs originate from fetal liver monocyte that differentiate in the skin to give rise to LCs during embryogenesis [51, 52]. LCs are long-lived radioresistant and maintain themselves by local proliferation in response to macrophage colony stimulator factor (M-CSF) and interleukin (IL)-34 [53] and develop normally in Flt3l-deficient mice [54]. Together with data indicating that LCs are transcriptionally distinct from cDCs and pDCs, these observations pinpoint that LC are not bona fide DCs but rather correspond to skin resident macrophages [55]. Monocyte-derived DCs (MO-DCs) correspond to another unconventional DC population that is commonly included in DC subsets. As their name indicate, these cells do not share the same origin as cDCs and pDCs. Commonly, they are not detected at steady state and were reported to differentiate in vivo in inflammatory conditions [56]. Lineage tracing studies that label cDC progeny using Clec9aCre-Rosa26-Rosa26-STOPfl/fl-EYFP mice did not lead to the labeling of Mo-DC [57]. Conversely, lineage tracing of monocyte and granulocyte progenitors using the Ms4a3 CreERT2 fate-mapping line did not lead to DC labeling [58]. Due to these developmental considerations, it was suggested that monocytederived cells should be cells independent of DCs [55]. Therefore, in this review, we will now mostly focus on the phenotypic and functional characterization of cDCs and pDCs (see Fig. 1).
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Fig. 1 Main features of murine DC subsets. Three major subsets of DCs are described. Each subset possesses unique phenotypical and functional characteristics. The main features of each subset are highlighted in this schematic view. The markers in ( ) are expressed differentially in tissues, under certain pathological/inflammatory conditions or only by a subgroup of the DC subset as described in the text. The function of the three main DCs is also indicated
3
The Mouse DC Subsets and Their Functional Specialization
3.1 Conventional DCs
Conventional MHC-II+ CD11c+ DCs are potent Ag-presenting cells that are developmentally separated into two main subsets, the cDC1s and cDC2s, found throughout the body [2]. Each subset comprises resident DCs found in both lymphoid organs and nonlymphoid organs and migratory DCs trafficking from nonlymphoid organs into draining-lymphoid organs [59]. A population of cDC expressing CD64, in particular in inflammatory conditions such as viral infections [60], has been described [61–63]. Whether these cells are a type of cDC1c and/or cDC2s or are a new cDC subset is still an open question [60–63].
3.1.1
cDC1s represent about 30% of total cDCs in the periphery and 40% of cDCs in the lymphoid organs. All cDC1s are XCR1+ DNGR1 (Clec9A)+ and CD205+ [2, 4]. Resident cDC1 in the spleen and lymph nodes (LNs) are CD8α+, while migratory cDC1 are CD103+. In nonlymphoid tissue, cDC1 do not express CD8α, but they express CD103 and CD24 [2–4]. It is well established that cDC1s are specialized in Ag crosspresentation and therefore are potent inducers of CD8 T cell activation [26]. Numerous studies have highlighted the pivotal role of
cDC1s
Overview on Mouse Dendritic Cell Subsets
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cDC1s in antitumor immunity, since cDC1 depletion results in impaired tumor immune rejection or decreased responses to immunotherapies [64]. The cDC1 can cross-present tumor Ag to CTLs in draining (d)LN [65, 66] and maintain Ag-specific T cells in dLN [67], and intratumor cDC1s were also reported to directly recruit CD8 T cells in the tumor through CXCL9 and CXCL10 production [68]. Moreover, it was recently described that cDC1 can also prime CD4 T cells against tumor Ag and that such priming is crucial to help antitumor CD8 responses [69] suggesting a key function of cDC1 in T cell activation beyond Ag cross-presentation. cDC1s are also important in directing responses against intracellular pathogens such as Listeria [70, 71], Leishmania major [72], and viruses [73, 74]. They express high levels of Toll-like receptor (TLR)-3 [75], an endosomal TLR sensing double-stranded RNA and thus allowing the recognition of viruses [76, 77]. A recent study demonstrated that cDC1s limit the exhaustion of T cells in chronic viral infection by maintaining the precursors of exhausted T cells [78]. Finally, their expression of TLR11 allows cDC1s to recognize the Toxoplasma gondii profilin inducing their production of IL-12, a cytokine that orchestrates both innate and adaptive immunity against this parasite [79, 80]. 3.1.2
cDC2s
The cDC2 population was first identified by the expression of CD4, but only a fraction of this subset expresses this marker. Therefore, cDC2s are better defined by the expression of CD11b and signal regulatory protein α (Sirpα) and may express CD301b in tissues [4]. cDC2s form a heterogenous population, and different subgroups have been proposed. For instance, a subgroup dependent on Notch2 and expressing ESAM has been described by opposition to a subgroup dependent on Klf4, which is CD11b- [2]. Recently, two additional populations of cDC2 have been uncovered, the cDC2A expressing Tbet and the cDC2B expressing Rorγt [39]. The cDC2A mainly overlap with the ESAM+ cDC2s, while the cDC2B comprise both ESAM+ and ESAM- cells [39]. Finally, cDC2 phenotype can be modified in pathological conditions [81], and cells at different maturation stages should not be considered as bona fide subgroups of cDC2s. These different subgroups also harbor functional specificities as described below. cDC2s are specialized in Ag presentation via MHC-II and therefore are able to prime and activate helper CD4 T cells [2]. They have a pivotal role in immunity against allergens, parasites, and extracellular pathogens or even blood Ag and induce either Th2, Th17, and/or Tfh cells [2]. For instance, Notch 2dependent ESAM+ cDC2s orchestrate the immune response against the extracellular bacteria Citrobacter rodentium via the production of IL-23, which induces type III immunity [34]. ESAM+ cDC2s are also required for Tfh induction and therefore humoral responses after immunization with sheep red blood
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cells or Listeria monocytogenes [82]. Conversely, Klf4-dependent cDC2s induce Th2 responses against parasites such as Schistosoma or house dust mite allergens [30]. The induction of Th2 or Th17 responses by lung cDC2 in response to house dust mite Ag seems to be dependent on the maturation stage of this DC subset [81]. The recently described cDC2B express higher levels of TLR6, TLR8, and TLR9 than cDC2A and accordingly produce more IL-6 and TNFα in response to CpG [39]. cDC2B are also more potent in inducing Th1 and Th17 differentiation than cDC2A [39]. Recently, a novel mouse model targeting three enhancers regulating Zeb2 expression was generated and shown to constitutively lack all cDC2 [36]. Using this mouse model, the authors have shown the crucial role of cDC2 in generating Th2 type immunity in response to helminth infections [36]. Furthermore, the involvement of cDC2s in tumor immunity is now starting to be recognized [83]. cDC2s may exhibit both pro-tumor [84] and antitumor properties as they can activate antitumor CD4 T cells upon Treg depletion [85]. Moreover, a recent study showed that, in the absence of cDC1s, part of cDC2s responds to IFN-I stimulation and can then promote CD8 T cell activation and antitumor immunity [86]. Finally, the importance of cDC2 in tolerance has been recently uncovered. First, Gargaro et al. showed the cross talk between cDC1s and cDC2s via the IDO1-Kyn-AHR axis is important to maintain self-tolerance [87], and then Breed et al. demonstrated a role for cDC2 in central tolerance as ablation of these cells impaired clonal T cell deletion in the thymus [88]. 3.2 Plasmacytoid DCs
The pDCs express low levels of CD11c and MHC-II molecules and high levels of B220, mPDCA1, and Siglec H [8, 9]. They are found in primary and secondary lymphoid organs, in the circulation, and in multiple tissues including the lung and the liver [8, 9]. They are potent producers of IFN-I and play a major role in immune responses against viral infections [8, 9]. Indeed, pDCs express TLR7 and TLR9 in their endosomal compartment, which are specialized in the recognition of single-stranded RNA and CpG oligodeoxynucleotides (ODN), respectively, making them poised for the recognition of viruses [8, 9]. Multiple cell types express those TLRs and can produce IFN-I; however, conditional Tfc4 deficiency using the CD11c (Itgax)-Cre-deleter line, which causes pDC depletion, abrogated IFN-α production in response to CpG-ODN injection, making them a predominant source of IFN-α in response to infection [40]. Accordingly, such pDC targeting was also reported to impair the control of an acute infection induced by the murine hepatitis virus (MHV) and of a chronic viral infection induced by the lymphocytic choriomeningitis virus (LCMV) [89]. In the context of chronic LCMV infection, pDCs were shown to play an important role in the expansion and/or maintenance of LCMV-specific CD4 and CD8 T cells mostly
Overview on Mouse Dendritic Cell Subsets
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through their production of IFN-I but not through Ag presentation [89]. The ablation of pDCs in vivo can also be achieved by the treatment of mice that express the diphtheria toxin receptor (DTR) under a pDC-specific promoter of the human gene encoding CLEC4C (BDCA2) by DT [90]. Using this model, multiple studies have also shown the relevance of pDCs in controlling immune response to murine cytomegalovirus (mCMV) [90], vesicular stomatitis virus (VSV) [90], systemic herpes simplex virus (HSV) [91], and vaccinia virus [92]. These studies have also revealed that pDCs contribute not only to the maintenance and expansion of antiviral CD8 T cells [90] but also to the expansion of natural killer (NK) cells [90] and the activation of cDC1 through their production of IFN-I [92]. In addition to their role in antiviral immunity, the aforementioned models inducing the depletion of pDCs have shown their critical role in the development of autoimmune syndromes, including systemic lupus erythematosus [93–95] and systemic sclerosis [96]. The contribution of pDCs to autoimmunity was associated to their ability to produce IFN-I in response to TLR7 and/or TLR9 stimulation by endogenous (self) nucleic acids [8, 9]. The role of pDCs in antigen presentation was also described [97]; however, this function is likely redundant with other cDC subsets. Genetic depletion of pDCs does not affect the priming of CD8 and CD4 T cells in response to viral infection but rather their expansion [89, 90]. A recent study has followed pDC activation states during the course of mCMV infection and has shown that pDCs, which initially responded to infection by IFN-I production acquired overtime an activated phenotype, migrated to T cell areas and activated antiviral T cell responses [98]. These data indicate that pDCs multitask during infection and opened novel perspectives in pDC functional characterization.
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Conclusion Recent advances in fate mapping, lineage tracing, and single-cell RNA sequencing approaches have greatly contributed to a better knowledge of DC development. These advances have led to a contraction of the DC family, leading to the exclusion of LCs and Mo-DCs based on their distinct ontogeny. In addition, studies of the development of DCs have also permitted to precisely characterize genetic determinants that are required for the development of the main three DC subsets including cDC1, cDC2, and pDCs. As a consequence, these studies contributed to the generation of multiple mouse lines lacking individual DC subsets that have allowed to attribute specific functions to individual DC subsets. While results from mice lacking individual DCs should be taken with caution, since they mostly tell us what nontargeted DCs or other cells cannot do, they open multiple perspectives in further characterizing
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previously unappreciated functions of individual DC subsets such as mediating neutrophil recruitment [99] and activating sensory neurons [100]. These mouse studies are also critical in further delineating human DC development and functions in order to be able to harness their potential to fight infectious diseases and cancer.
Acknowledgments Figures were created with Biorender.com. The work in our laboratory is supported by research grant from the IdEx junior chair program from the University of Bordeaux, the Agence Nationale de la Recherche (ANR JCJC DOMINOS), the Institut National du Cancer (INCa-PLBIO22-124) and the SIRIC Brio. References 1. Steinman RM, Cohn ZA (1973) Identification of a novel cell type in peripheral lymphoid organs of mice. I. Morphology, quantitation, tissue distribution. J Exp Med 137(5): 1142–1162 2. Anderson DA, Dutertre CA, Ginhoux F, Murphy KM (2021) Genetic models of human and mouse dendritic cell development and function. Nat Rev Immunol 21(2): 101–115 3. Merad M, Sathe P, Helft J, Miller J, Mortha A (2013) The dendritic cell lineage: ontogeny and function of dendritic cells and their subsets in the steady state and the inflamed setting. Annu Rev Immunol 31:563. h t t p s : // d o i . o r g / 1 0 . 1 1 4 6 / a n n u r e v immunol-020711-74950 4. Cabeza-Cabrerizo M, Cardoso A, Minutti CM, Pereira da Costa M, Reis e Sousa C. (2021) Dendritic cells revisited. Annu Rev Immunol 39(1):131–166 5. Worbs T, Hammerschmidt SI, Fo¨rster R (2017) Dendritic cell migration in health and disease. Nat Rev Immunol 17(1):30–48 6. Kurts C, Cannarile M, Klebba I, Brocker T (2001) Dendritic cells are sufficient to crosspresent self-antigens to CD8 T cells in vivo. J Immunol Baltim, MD 1950 166(3): 1439–1442 7. Probst HC, Lagnel J, Kollias G, van den Broek M (2003) Inducible transgenic mice reveal resting dendritic cells as potent inducers of CD8+ T cell tolerance. Immunity 18(5):713–720 8. Reizis B, Bunin A, Ghosh HS, Lewis KL, Sisirak V (2011) Plasmacytoid dendritic cells: recent progress and open questions. Annu Rev Immunol 29:163–183
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cell ablation impacts early interferon responses and antiviral NK and CD8(+) T cell accrual. Immunity 33(6):955–966 91. Swiecki M, Wang Y, Gilfillan S, Colonna M (2013) Plasmacytoid dendritic cells contribute to systemic but not local antiviral responses to HSV infections. PLoS Pathog 9(10):e1003728 92. Brewitz A, Eickhoff S, D€ahling S, Quast T, Bedoui S, Kroczek RA et al (2017) CD8+ T cells orchestrate pDC-XCR1+ dendritic cell spatial and functional cooperativity to optimize priming. Immunity 46(2):205–219 93. Sisirak V, Ganguly D, Lewis KL, Couillault C, Tanaka L, Bolland S et al (2014) Genetic evidence for the role of plasmacytoid dendritic cells in systemic lupus erythematosus. J Exp Med 211(10):1969–1976 94. Soni C, Perez OA, Voss WN, Pucella JN, Serpas L, Mehl J et al (2020) Plasmacytoid dendritic cells and type I interferon promote extrafollicular B cell responses to extracellular self-DNA. Immunity [Internet]. [cite´ 16 juin 2020]. Disponible sur: http://www.cell. com/immunity/abstract/S1074-7613(20) 30173-4 95. Rowland SL, Riggs JM, Gilfillan S, Bugatti M, Vermi W, Kolbeck R et al (2014) Early, transient depletion of plasmacytoid dendritic cells ameliorates autoimmunity in a lupus model. J Exp Med 211(10):1977–1991 96. Kioon MDA, Tripodo C, Fernandez D, Kirou KA, Spiera RF, Crow MK et al (2018) Plasmacytoid dendritic cells promote systemic sclerosis with a key role for TLR8. Sci Transl Med 10(423):eaam8458 97. Villadangos JA, Young L (2008) Antigenpresentation properties of plasmacytoid dendritic cells. Immunity 29(3):352–361 98. Abbas A, Manh TPV, Valente M, Collinet N, Attaf N, Dong C et al (2020) The activation trajectory of plasmacytoid dendritic cells in vivo during a viral infection. Nat Immunol 21(9):983–997 99. Janela B, Patel AA, Lau MC, Goh CC, Msallam R, Kong WT et al (2019) A subset of type I conventional dendritic cells controls cutaneous bacterial infections through VEGFα-mediated recruitment of neutrophils. Immunity 50(4):1069–1083.e8 100. Xu J, Zanvit P, Hu L, Tseng PY, Liu N, Wang F et al (2020) The cytokine TGF-β induces interleukin-31 expression from dermal dendritic cells to activate sensory neurons and stimulate wound itching. Immunity 53(2): 371–383.e5
Chapter 2 Phenotypes and Functions of Human Dendritic Cell Subsets in the Tumor Microenvironment Candice Sakref, Nathalie Bendriss-Vermare, and Jenny Valladeau-Guilemond Abstract Dendritic cells (DCs) play a key role in the antitumor immunity, as they are at the interface of innate and adaptive immunity. This important task can only be performed thanks to the broad range of mechanisms that DCs can perform to activate other immune cells. As DCs are well known for their outstanding capacity to prime and activate T cells through antigen presentation, DCs were intensively investigated during the past decades. Numerous studies have identified new DC subsets, leading to a large variety of subsets commonly separated into cDC1, cDC2, pDCs, mature DCs, Langerhans cells, monocyte-derived DCs, Axl-DCs, and several other subsets. Here, we review the specific phenotypes, functions, and localization within the tumor microenvironment (TME) of human DC subsets thanks to flow cytometry and immunofluorescence but also with the help of high-output technologies such as single-cell RNA sequencing and imaging mass cytometry (IMC). Key words Human dendritic cells, Conventional dendritic cells, Plasmacytoid dendritic cells, Monocyte-derived dendritic cells, Cancer, Tumor, Antitumor immunity, Single-cell RNA sequencing
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Introduction Dendritic cells (DCs) were first identified in human in the early 1980s by the team of R. Steinman and G. Kaplan [1]. Their high expression of pattern recognition receptors (PRRs) [2] and their secretion of a wide range of cytokines [3] give them a central role at the interface between innate and adaptive immune responses [4]. DCs are also the most efficient antigen-presenting cells (APC). Due to this antigenpresenting ability, DCs were intensively investigated during the past 50 years using flow cytometry, in situ hybridization, immunofluorescence, and (single-cell) RNA sequencing methods. These approaches helped to understand how DCs orchestrate adaptive immune responses against infectious diseases and tumors [5] but also helped to appreciate the diversity of DC subsets from which a universal
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consensus has emerged about their classification in both human and mice. DCs are indeed commonly separated into Langerhans cells (LC), plasmacytoid dendritic cells (pDCs), and conventional dendritic cells (cDCs), the latter including type 1 cDCs (cDC1) and type 2 cDCs (cDC2). Additional DC subsets were recently described such as DC3, DC4, and DC5 [6], but their functions are not yet fully characterized nor understood. It is known that cDCs as well as pDCs differentiate from the common DC progenitor (CDP) even though there are recent evidences showing that pDCs could also derive from the common lymphoid progenitor (CLP) [7, 8]. Coming from another differentiation pathway, we should also consider the family of monocytederived DCs (moDCs), which are generated from monocytes under inflammatory conditions [9]. The high heterogeneity among the DC family makes the concomitant analysis of all DC subsets difficult, especially due to their low numbers within complex tissues like tumors. Here, we discuss human DC heterogeneity as well as their counterparts in human tumors based on their phenotypes, functions, and localization.
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Identification and Functions of Human DC Subsets
2.1 Conventional Dendritic Cells
Conventional DCs (cDCs), also known as myeloid DCs (mDCs), are identified by flow cytometry in the fraction of lineage-negative (CD3, CD14, CD20, CD15, CD56) cells expressing CD11c as well as high levels of major histocompatibility complex (MHC) class II molecules (HLA-DR) at steady state. In peripheral blood, cDCs only represent a small fraction of immune cells (1 year) at 80 °C. We typically use freshly prepared or freshly thawed virus and avoid storage at 4 °C. 4. For labs performing MSCV production routinely, virus titration may not be necessary as typical titers obtained for MSCVERHBD-Hoxb8 are in the range of 10e6–10e7 infectious virus particles/mL. For labs with less experience, it is advantageous to determine the virus titer to avoid ineffective Hoxb8-FL generation. 5. Other cell types, for example, immortalized 3T3 fibroblasts can also be used for virus titration. However, the G418 concentration may need to be adjusted. 6. The concentration of G418 needs to be adjusted to the specific cell type used. Ideally, titration experiments are performed to determine the proper G148 concentration in non-transduced cells, that is, a concentration of G418, which leads to quantitative cell death after 5 days of cell culture. 7. We have established successfully many Hoxb8-FL cell lines starting from frozen BM. To freeze BM, follow standard procedures, that is, resuspend pelleted BM cells in freezing medium (10% DMSO, 90% FBS), aliquot in 1 mL N2-resistant tubes and freeze by standard procedure, that is, in -80 °C freezer overnight, followed by transfer to N2-tank. Cells can be shipped on dry ice. For virus transduction, thaw these cells quickly in 37 °C water bath, transfer to 15 mL tube
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containing 6 mL RP-10, spin down (5 min, 450 g) and resuspend in 4 mL PBS-FBS. Continue with Ficoll-Paque centrifugation as described above. 8. The main purpose of the Ficoll-Paque-step is to remove neutrophils and red blood cells. The majority of those cells are found in the cell pellet, while progenitor cells scatter throughout the Ficoll gradient along with lymphocytes. 9. The purpose of the brief cell culture period in SCM is to induce cells entering the cell cycle, which is required for efficient transduction with MSCV. Extended periods of BM cell culture in SCM (>3 days) are discouraged to avoid cell differentiation and loss of lineage potential. 10. Other compounds, such as Polybrene (6 μg/mL), can likely also be used. However, we have seen better results with Lipofectamine, which may be related to less cytotoxicity. 11. Initially, for maintenance of cell cultures, remove 1 mL of medium, resuspend cells gently, and transfer to new wells containing 1 mL of fresh POM. We recommend to use 1000 μL filter tips for this purpose to prevent cell contamination during multiple resuspensions. During the initial cell culture period (~10 days), most BM cells will die or differentiate and stop growing. Cells transduced with MSCV-ERHBD-Hoxb8 will express activated Hoxb8 in the presence of β-estrogen, preventing cell differentiation. FLT3L will provide survival and proliferation signals to some of these cells expressing FLT3, allowing these cells to expand and ultimately form homogenous Hoxb8-FL progenitor cell populations. Although we have not determined how many of the originally infected cells are able to expand, we do find that increased cellularity begins to become microscopically apparent (7-) 10–14 days after viral transduction. In these early stages, it is very useful to compare transduced cells with mock-transduced cells, which facilitates identification of Hoxb8-FL cells. Hoxb8-FL cells, which divide ~1×/day, appear microscopically as round, refractile cell cluster, initially often growing at the edge of the wells (Fig. 2). 12. Cell viability of Hoxb8-FL cells immediately after thawing is more variable than viability of classic tumor cell lines and ranges from 10% to 90%. This variability is usually not problematic due to the strong proliferative capacity of Hoxb8-FL cells, which compensates for cell loss rapidly. Although we undertook considerable effort, we have not been able to identify the specific reason for this variability. One observation related to this is that Hoxb8-FL cells do not tolerate low temperature, for example, incubation on ice, which will lead to quantitative cells death. Thus, we perform all procedures with pre-warmed medium not below RT.
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13. When handling multiple Hoxb8-FL cell populations, we routinely do not resuspend cells, but simply add 4 mL PBS-FBS, followed by gently vortexing the cells three times for 1–2 s. 14. We typically recover 1–2 × 10e6 cells/mL after 7–9 (10) days. In case the cells appear too dense during the first 5 days after estrogen withdrawal, dilute the cells further with RP-10 containing FLT3L. Cells differentiated for 7 days are less mature than cells differentiated for 9 (to 10) days as apparent by reduced expression of B220 and MHC class II molecules. 15. GM-CSF-driven cells display a remarkable proliferative capacity, which can make it difficult to seed the cells at the right concentration avoiding overcrowding at later stages. Thus, it can be useful to count the cells on day 4 and re-seed the cells at lower concentration, for example, 2 × 10e5 cells/mL. Some trial and error may be required to find the optimal cell concentration. 16. Hoxb8-FL cells are immature progenitor cells and not yet fully GM-CSF responsive. As such, if FLT3L is replaced by GM-CSF alone, more than 80% of the cells may die. One possibility to address this issue is to add a small amount of FLT3L during the early stage of cell differentiation as described above. This allows the cells to become responsive for GM-CSF, which then mediates cell survival, proliferation, and differentiation. Another option is to culture the cells for 1 day with FLT3L after estrogen withdrawal (allowing the cells to become GM-CSF-responsive), followed by removal of FLT3L and continued cell culture with GM-CSF alone. 17. While both ecotropic MSCV and VSV-G-pseudotyped lentiviral vectors can be used to transduce Hoxb8-FL cells, the titers required for infection are ~10–100× higher than those required for other cell lines, such as NIH3T3 or HEK293T cells. We have not been successful with transfection procedures, for example, Lipofectamine 2000 or Nucleofection. 18. Standard procedures based on transiently transfected HEK293T cells are used to generate VSV-G pseudotyped lentiviral particles. For low-titer viruses, such as LentiCrisprV2, it is advisable, although not absolutely required, to concentrate the virus to obtain higher infectious titers. An alternative possibility is to transduce Hoxb8-FL cells first with a Cas9expressing virus, for example, lentiCas9-blast (Addgene Plasmid #52962) [10], followed by transduction with a sgRNAexpressing virus, both of which can typically be produced at higher titers. A third alternative is to establish Hoxb8-FL cells based on BM from mice expressing Cas9 constitutively in various organs, such as “Rosa26-Cas9 knockin” mice, available through The Jackson Laboratory [11]. The latter approach
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simplifies the procedure and avoids multiple viral infections, which we believe can affect cell performance and differentiation potential, particularly when performed with inferior virus titers extending cell selection. 19. Volume of added virus depends on the virus titer. If concentrated virus is used, the total volume in wells should be adjusted with POM to 1.5 mL. 20. The level of protection depends on the virus titer. Lower virus titers may protect only a fraction of the cells, requiring longer periods of time to establish stably growing cell populations. In general, we advise against low virus titers to avoid lengthy selection of potentially inferior cells.
Acknowledgments The CD18-sgRNA vector was generously provided by M. Sixt. This work was supported by NIH grant R01 AI145877 to H.H. References 1. Wang GG, Calvo KR, Pasillas MP, Sykes DB, Hacker H, Kamps MP (2006) Quantitative production of macrophages or neutrophils ex vivo using conditional Hoxb8. Nat Methods 3(4):287–293. https://doi.org/10.1038/ nmeth865 2. Tora L, Mullick A, Metzger D, Ponglikitmongkol M, Park I, Chambon P (1989) The cloned human oestrogen receptor contains a mutation which alters its hormone binding properties. EMBO J 8(7):1981–1986 3. Redecke V, Wu R, Zhou J, Finkelstein D, Chaturvedi V, High AA, Hacker H (2013) Hematopoietic progenitor cell lines with myeloid and lymphoid potential. Nat Methods 10(8):795–803. https://doi.org/10.1038/ nmeth.2510 4. Guo X, Zhou Y, Wu T, Zhu X, Lai W, Wu L (2016) Generation of mouse and human dendritic cells in vitro. J Immunol Methods 432: 24–29. https://doi.org/10.1016/j.jim.2016. 02.011 5. Anderson DA 3rd, Dutertre CA, Ginhoux F, Murphy KM (2021) Genetic models of human and mouse dendritic cell development and function. Nat Rev Immunol 21(2):101–115. https://doi.org/10.1038/s41577-02000413-x 6. Bunin A, Sisirak V, Ghosh HS, Grajkowska LT, Hou ZE, Miron M, Yang C, Ceribelli M, Uetani N, Chaperot L, Plumas J, Hendriks W,
Tremblay ML, Hacker H, Staudt LM, Green PH, Bhagat G, Reizis B (2015) Protein tyrosine phosphatase PTPRS is an inhibitory receptor on human and murine plasmacytoid dendritic cells. Immunity 43(2):277–288. https://doi.org/10.1016/j.immuni.2015. 07.009 7. Grajkowska LT, Ceribelli M, Lau CM, Warren ME, Tiniakou I, Nakandakari Higa S, Bunin A, Haecker H, Mirny LA, Staudt LM, Reizis B (2017) Isoform-specific expression and feedback regulation of E protein TCF4 control dendritic cell lineage specification. Immunity 46(1):65–77. https://doi.org/10.1016/j. immuni.2016.11.006 8. Leithner A, Renkawitz J, De Vries I, Hauschild R, Hacker H, Sixt M (2018) Fast and efficient genetic engineering of hematopoietic precursor cells for the study of dendritic cell migration. Eur J Immunol 48(6): 1074–1077. https://doi.org/10.1002/eji. 201747358 9. Kopf A, Renkawitz J, Hauschild R, Girkontaite I, Tedford K, Merrin J, ThornSeshold O, Trauner D, Hacker H, Fischer KD, Kiermaier E, Sixt M (2020) Microtubules control cellular shape and coherence in amoeboid migrating cells. J Cell Biol 219(6):1–41. https://doi.org/10.1083/jcb.201907154 10. Sanjana NE, Shalem O, Zhang F (2014) Improved vectors and genome-wide libraries
DC Generation Using Hoxb8-Immortalized Progenitors for CRISPR screening. Nat Methods 11(8): 783–784. https://doi.org/10.1038/nmeth. 3047 11. Platt RJ, Chen S, Zhou Y, Yim MJ, Swiech L, Kempton HR, Dahlman JE, Parnas O, Eisenhaure TM, Jovanovic M, Graham DB, Jhunjhunwala S, Heidenreich M, Xavier RJ,
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Chapter 8 In Vitro Generation of Murine CD8α+ DEC205+ XCR1+ Cross-Presenting Dendritic Cells from Bone Marrow– Derived Hematopoietic Progenitors Margaret E. Kirkling and Boris Reizis Abstract Dendritic cells (DCs) comprise a heterogeneous population of antigen (Ag)-presenting cells that play a critical role in both innate and adaptive immunity. DCs orchestrate protective responses against pathogens and tumors while mediating tolerance to host tissues. Evolutionary conservation between species has allowed the successful use of murine models to identify and characterize DC types and functions relevant to human health. Among DCs, type 1 classical DCs (cDC1) are uniquely capable of inducing antitumor responses and therefore present a promising therapeutic target. However, the rarity of DCs, particularly cDC1, limits the number of cells that can be isolated for study. Despite significant effort, progress in the field has been hampered by inadequate methods to produce large quantities of functionally mature DCs in vitro. To overcome this challenge, we developed a culture system in which mouse primary bone marrow cells are cocultured with OP9 stromal cells expressing Notch ligand Delta-like 1 (OP9-DL1) to produce CD8α+ DEC205+ XCR1+ cDC1 (Notch cDC1). This novel method provides a valuable tool to facilitate the generation of unlimited cDC1 for functional studies and translational applications such as antitumor vaccination and immunotherapy. Key words Classical dendritic cells, Adaptive immunity, Innate immunity, cDC1, Antigen crosspresentation, CD8α+ dendritic cells, Antitumor, Notch signaling, Immunotherapy, Antigen presentation, BMDC, OP9-DL1
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Introduction Dendritic cells (DCs) are sentinels of the immune system, linking innate and adaptive immunity by recognizing pathogens through pattern recognition receptors, such as Toll-like receptors (TLRs), and recruiting diverse effector cells to orchestrate antigen (Ag)specific responses [1, 2]. Murine DCs can be divided into two main types: plasmacytoid DCs (pDCs) that secrete type I interferons (IFN-α/β) in response to viruses and conventional dendritic cells (cDCs), often referred to as professional Ag presenting cells [3]. There are two functionally distinct subsets of cDCs: CD11b+
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CD8α- cDCs, which present exogenous Ag to CD4+ T cells on major histocompatibility complex (MHC) class II, and CD8α+ CD103+ cDCs capable of cross-presenting exogenous Ag to naı¨ve CD8+ T cells via MHCI [3–6]. Both subsets are conserved in humans and have been designated as cDC2 and cDC1, respectively [7, 8]. Notably, CD8α+ cDC1 are required for the cross-priming of cytotoxic T lymphocytes against tumors [9–13]. Although murine models have been widely used to characterize DC types and functions, the paucity of DCs present in tissues limits the number of cells that can be isolated. Efforts to advance our knowledge and clinical use of DCs have been hindered by inadequate methods to generate large quantities of functionally mature cells in vitro. Commonly used cultures of primary bone marrow (BM) with the cytokine FMS-like tyrosine kinase 3 ligand (Flt3L) or granulocytemonocyte colony-stimulating factor (GM-CSF) produce a mixture of pDC, cDC2 and cDC1-like cells, or cDC2-like cells and macrophages, respectively [8, 14–16]. These cell types possess aberrant expression of nonspecific surface markers and lack the characteristic functions that define them in vivo. Thus, innovative approaches are needed to enhance cellular output and phenotype, particularly those of cDC1. Here, we describe a novel method to generate CD8α-expressing cDC1 that transcriptionally and functionally represent their ex vivo counterparts. Based on previously published findings from our laboratory and others demonstrating a role for Notch signaling in cDC differentiation, we developed a culture system to induce Notch signaling in BM progenitors [17– 21]. Since Delta-like 1 (DL1) was identified as the relevant ligand of the NOTCH2 receptor on splenic DCs, we incorporated OP9 stromal cells expressing DL1 (OP9-DL1) into Flt3L-driven BM cultures [22, 23]. Coculture of primary BM with OP9-DL1 cells facilitated the generation IRF8-dependent CD8α+ cDC1 that express DEC205, XCR1, and CLEC9A (Notch cDC1) [24– 28]. Notch cDC1 possessed an expression profile aligned with splenic cDC1 and displayed enhanced functional capacity in vitro and in vivo. This method provides a valuable tool to generate unlimited DCs for developmental and functional studies [29, 30]. Moreover, it supports the advancement of their use in translational and therapeutic applications such as cellular vaccination and immunotherapy [31, 32].
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Materials
2.1 Cell Lines and Cell Culture
1. OP9-DL1 cell line transduced with retroviruses encoding GFP and Notch ligand DL1. 2. Flt3L-secreting B16 melanoma cell line (B16-Flt3L).
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3. OP9-DL1 medium: minimum essential medium-α (MEM-α), 20% fetal calf serum (FCS). 4. B16-Flt3L medium: DMEM, 10% FCS, 100 IU/mL penicillin/streptomycin, 1 mM L-glutamine, 1 mM sodium pyruvate, 1 mM nonessential amino acids (MEM-NEAA). 5. Mitomycin C from Streptomyces caespitosus (MMC). 6. Phosphate-buffered saline (PBS). 7. Trypsin-EDTA 0.05%, phenol red. 8. Disposable vacuum filter unit (sterile, cellulose acetate, 0.2 μm). 9. 50 and 15 mL conical sterile polypropylene tubes. 10. Sterile T75 cm2 flask, tissue culture treated, vented cap. 11. 10 cm cell culture-treated dish. 2.2 Isolation and Culture of Primary BMDerived Hematopoietic Progenitors
1. Femurs and tibias of wild-type C57BL/6 mice to obtain BM cells (see Note 1). 2. BM flushing solution: PBS, 2% FCS. 3. 70 μm strainers. 4. 50 and 15 mL conical sterile polypropylene tubes. 5. 27-gauge needles. 6. 10 mL syringes. 7. 10 mL serological pipettes. 8. Sterile red blood cell (RBC) lysis solution: 155 mM NH4Cl, 10 mM NaHCO3, 0.1 mM EDTA. 9. Sterile tweezers and straight-edge blade. 10. Sterile 1.5 mL Eppendorf tubes. 11. DC medium: DMEM, 10% FCS, 1 mM L-glutamine, 1 mM sodium pyruvate, 1 mM MEM-NEAA and 100 IU/mL penicillin/streptomycin, 55 μM 2-mercaptoethanol, and 10% supernatant from cultured B16-FLT3L cell line. 12. 24-well tissue culture-treated plates.
2.3 Harvesting, Staining, and Flow Cytometric Analysis of Culture-Derived DCs
1. 70 and 40 μm strainers. 2. FACS buffer: PBS, 1% FCS, 0.02% NaN3. 3. Fluorochrome-conjugated antibodies (see Table 1). 4. 10 mL serological pipettes. 5. 50 and 15 mL conical sterile polypropylene tubes. 6. Flow cytometers equipped with lasers and emission filters suitable for the analysis of cells stained with the dyes listed in the antibody panel (see Table 1). 7. FlowJo software for flow cytometry data analysis.
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Table 1 List of fluorochrome-conjugated anti-mouse antibodies used for phenotypic characterization of cultured DCs Surface marker
Fluorochrome
Clone
Source
CD45
APC
30-F11
BD Biosciences
CD205 (DEC205)
PerCP-Cy5.5, PE-Cy7
NLDC-145
BioLegend
CD45R (B220)
FITC, AF700
RA3-6B2
BioLegend
CD11c
APC-Cy7
N418
eBioscience
CD8a
APC, FITC
53-6.7
eBioscience
CD11b
PE-Texas red, FITC
M1/70
eBioscience
CD24
PE-Cy7
M1/69
eBioscience
CD103
PE
2E7
eBioscience
MHC class II (I-A/I-E)
Pacific blue
M5/114.15.2
eBioscience
CD172a (Sirpa)
AF700, PE
P84
BD Biosciences
Clec9a
PE
42D2
eBioscience
Xcr1
PerCP-Cy5.5
ZET
BioLegend
Live/dead
DAPI
3
Sigma-Aldrich
Methods In vitro generation of Notch cDC1 (CD8α+ DEC205+ XCR1+ CLEC9A cDC1) requires a two-step culture lasting a period of 7 days. The first 3 days of differentiation is a monoculture of freshly isolated BM cells in medium supplemented with Flt3L (DC medium). The second step entails the coculture of differentiating BM cells with OP9 cells initiated on day 3, when the cells are transferred to OP9 monolayers in 24-well plates. Flt3L cultures performed in parallel produce a CD24+ cDC1-like population that lacks CD8α but expresses the cDC2 marker CD11b. All experimental procedures should be performed under sterile conditions while implementing the appropriate safety measures for handling murine tissues and potentially harmful chemicals.
3.1 Generation of Mitomycin C (MMC)Treated OP9 Cells
1. Thaw vial of OP9-DL1 cells in 37 °C bath and remove when a small piece of ice remains. 2. Add 1 mL of pre-warmed to 37 °C OP9-DL1 medium and gently transfer cells to a 15 mL conical tube containing 10 mL of OP9 medium pre-warmed to 37 °C. 3. Centrifuge cells at 450 g for 5 min. 4. Resuspend cell pellet in 10 mL of OP9-DL1 medium and transfer entire volume to a 10 cm cell culture-treated dish.
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5. Incubate at 37 °C in a humidified atmosphere at 5% CO2. 6. When cells reach 90% confluency, aspirate medium and treat cells with 4 mL of pre-warmed to 37 °C OP9-DL1 medium supplemented with 10 μg/mL of MMC for 2–3 h. 7. Aspirate MMC-containing medium and gently rinse cells with 8 mL of room temperature (RT) PBS. 8. Add 5 mL of 0.05% trypsin to cells and return to the incubator. 9. Once cells detach from dish surface (after ~5 min), add 10 mL of OP9-DL1 medium pre-warmed to 37 °C, pipette vigorously using a 10 mL serological pipette and transfer cell suspension to a 15 mL conical tube. 10. Centrifuge cells at 450 g for 5 min. 11. Aspirate and wash cells three times with PBS. After the last wash, resuspend in desired volume of OP9-DL1 medium pre-warmed to 37 °C for cell counting (see Note 2). 3.2 Production of Flt3L Supernatant for Cell Culture
1. Thaw vial of B16-Flt3L cells in 37 °C bath and remove when a small piece of ice remains. 2. Add 1 mL of pre-warmed to 37 °C B16-Flt3L medium and gently transfer cells to a 15 mL conical tube containing 10 mL of pre-warmed to 37 °C B16-Flt3L medium. 3. Centrifuge cells at 450 g for 5 min. 4. Resuspend cell pellet in 10 mL of pre-warmed to 37 °C B16-Flt3L medium and transfer entire volume to a10mm cell culture-treated dish. 5. Incubate at 37 °C in a humidified atmosphere at 5% CO2. 6. When cells reach 90% confluency, aspirate medium and gently rinse cells with 8 mL of RT PBS. 7. Aspirate PBS, add 5 mL of 0.05% trypsin to cells and return to the incubator. 8. Once cells detach from dish surface (after ~5 min), add 10 mL of B16-Flt3L medium pre-warmed to 37 °C, pipette vigorously using a 10 mL serological pipette and transfer to 15 mL conical tube. 9. Aspirate and resuspend in 10 mL of B16-Flt3L medium pre-warmed to 37 °C. 10. Transfer cell suspension to a cell culture-treated T75 cm2 flask and add an additional 20 mL of medium. 11. When the culture medium color turns from red to yellow, harvest supernatant in a 50 mL conical tube. 12. Centrifuge at 3000 g for 10 min. 13. Carefully remove supernatant to avoid contamination with cells and transfer to disposable vacuum filter unit (see Note 3).
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3.3 Isolation of Hematopoietic Progenitors from BM
1. Isolated femurs and tibias should be placed in sterile 1.5 mL Eppendorf tube or 15 mL conical tubes containing ice-cold PBS on ice (see Note 4). 2. Place BM flushing solution (PBS, 2% FCS) on ice. 3. Use tweezers to hold bone while carefully removing the tips of femurs and tibias with the blade. 4. Fill 10 mL syringe with ice-cold BM flushing solution, attach 27-gauge needle and flush the bone into a 50 mL conical (see Note 5). 5. Centrifuge cells at 450 g for 5 min. 6. Resuspend cell pellet in 2 mL of RBC lysis buffer and incubate at RT for ~5 min. 7. Add 8 mL of ice-cold BM flushing solution to the cells. 8. Filter into a 15 mL conical tube through a 70 μm filter. 9. Centrifuge cells at 450 g for 5 min. 10. Resuspend cell pellet in a desired volume of pre-warmed to 37 °C DC medium and count cells (see Note 6).
3.4 Differentiation of Notch DCs from BM Hematopoietic Progenitors
1. Plate 2 × 106 of primary murine BM cell per well in 2 mL of DC medium in 24-well plates (day 0). 2. Incubate BM monocultures at 37 °C in a humidified atmosphere at 5% CO2. 3. Approximately 48 h after starting the BM DC differentiation (day 2), plate 1 × 105 OP9-DL1 cells per well (24-well plates) in 1 mL of OP9-DL1 medium and incubate them at 37 °C in a humidified atmosphere at 5% CO2 (see Note 7). 4. On day 3 of differentiation, transfer half of the volume of cells from each well of BM monocultures directly to a single well containing a monolayer of MMC-treated OP9-DL1 cells in 24-well plates. Aspirate the OP9-DL1 medium prior to adding the BM cells (see Note 8). 5. Incubate BM/OP9-DL1 cocultures at 37 °C in a humidified atmosphere at 5% CO2 for an additional 4 days. For control Flt3L BM culture wells, allow monoculture wells to differentiate until day 7. 6. Analyze cells by flow cytometry on day 7.
3.5 Phenotypic Characterization of Culture-Derived DCs
Flt3L BM cultures produce a mixture of pDCs and cDCs, which can be identified by expression patterns of surface markers (see Table 2). 1. Prepare staining cocktail of selected surface markers by diluting fluorochrome-conjugated antibodies in FACS buffer. Mix and store at 4 °C or on ice in the dark.
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Table 2 Expression of selected markers distinguishing DC types generated from BM progenitors in FL and Notch cultures Surface marker
Notch cDC1
FL cDC1
Notch cDC2
FL cDC2
DEC205
+
-
-
-
B220
-
-
-
-
CD11c
+/High
+
High
+
CD8a
+
-
-
-
CD11b
-
+
+
+
CD24
+
+
-
-
CD103
+
Low
-
-
MHC class II
+
+
+/High
+
CD172a (Sirpa)
-
-/Low
+
+
Clec9a
+
-/Low
-
-
Xcr1
+
+
-
-/Low
2. Harvest cells into 15 mL or 50 mL conical tubes and place on ice (see Note 9). 3. Centrifuge cells at 450 g for 5 min. 4. Resuspend pellet and wash cells twice in ice-cold FACS buffer. 5. Filter cells through a 70 μm followed by a 40 μm filter into new tubes. Count cells. 6. Transfer desired number of cells into tubes compatible for the flow cytometer to be used (see Note 10). 7. Centrifuge cells at 450 g for 5 min. 8. Resuspend pellet in the antibody cocktail. 9. Prepare single color staining samples for compensation from a cell pool of both Flt3L and OP9-DL1 BM cultures. Reserve a portion of the pooled cells in a separate tube to use as an unstained control (see Note 11). 10. Incubate at 4 °C or on ice in the dark for 20 min. 11. Add 500 μL of FACS buffer to the cells and centrifuge cells at 450 g for 5 min. 12. Resuspend pellet in ice-cold FACS buffer and perform FACS analysis (see Fig. 1 and Notes 12 and 13).
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Fig. 1 Phenotypic characterization of cDC subsets identified in BM cultures. FACS plots of cell populations gated previously on B220neg MHC-II+ CD11c+, live single cells. FL cultures (a) produce CD11b+ cDC2 cells, and a CD24+ CD11b+ CD8αneg cDC1-like population. In addition to CD11b+ cDC2, Notch cultures (b) generate authentic CD11bneg cDC1 defined by CD8α, DEC205, XCR1, and CLEC9A expression
4
Notes 1. More BM cells can be obtained from male mice. No obvious difference between sexes was observed within the parameters analyzed for our experiments. Male and female mice were obtained from Jackson Laboratories and used between 8 and 16 weeks of age. Mice were group-housed in individually ventilated cages and maintained under specific pathogen-free conditions. All animal studies were performed according to the investigator’s protocol approved by the Institutional Animal Care and Use Committees of Columbia University or New York University School of Medicine. 2. Cells can be further expanded to generate desired quantity of OP9-DL1 cells. Stocks of mitomycin C-treated OP9 cells can be cryopreserved for subsequent experiments. 3. Cells can be further expanded to produce larger volumes of supernatants, which can be stored at -80 °C for subsequent experiments.
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4. BM cells can also be isolated from the hip and humerus to increase the number of cells for DC differentiation. 5. Bones should appear white and translucent once the marrow has been completely flushed out. 6. Repeat the RBC lysis if the cell pellet appears red or pink in color (incomplete RBC lysis), by reducing the RBC lysis buffer volume and/or incubation time. 7. For each well of BM monoculture, plate 2 wells of OP9-DL1 cells. 8. Some of the cells will attach to the bottom of the wells. Use a 1 mL pipette tip to gently scrape and detach them. Pipette the cells vigorously then transfer to OP9-DL1 monolayer wells. Confirm removal of all cells on a light microscope. The volume of each monoculture well may be slightly less than 2 mL on day 3 due to evaporation. Adjust cell suspension volume to ensure an equal number of cells are transferred to coculture wells (i.e., 800–900 μL instead of 1 mL). 9. Cells from both monoculture and OP9-DL1 coculture will attach to the bottom of the wells. Use a 1 mL pipette tip to gently scrape and detach them. Pipette the cells vigorously before harvesting into conical tubes. 10. 2 × 106 cells were stained in 200 μL of antibody cocktail. 11. Commercially available compensation beads may be used instead of cells for single color controls. 12. OP9-DL1 cells express GFP and can be discriminated from DCs by gating on cells that are GFP negative. However, OP9-DL1 cells can also be gated out by FSC/SSC due to the difference in cell sizes of lymphocytes and OP9-DL1 stromal cells. 13. Flow cytometers used: LSR II (BD) flow cytometer using FACSDiva software (BD Biosciences) or Attune NxT (Invitrogen) using Attune NxT software and further analyzed with FlowJo software (Tree Star).
Acknowledgements ˜ iga-Pflu¨cker and SunWe gratefully acknowledge Juan Carlos Zu´n nybrook Research Institute for OP9-DL1 cells. This work was supported by the NIH grants AI072571, AG049074 and AI115382 (B.R) and AI124661 (M.E.K.).
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References 1. Pulendran B (2015) The varieties of immunological experience: of pathogens, stress, and dendritic cells. Annu Rev Immunol 33:563– 606 2. Steinman RM (2012) Decisions about dendritic cells: past, present, and future. Annu Rev Immunol 30:1–22 3. Merad M, Sathe P, Helft J, Miller J, Mortha A (2013) The dendritic cell lineage: ontogeny and function of dendritic cells and their subsets in the steady state and the inflamed setting. Annu Rev Immunol 31:563–604 4. Mildner A, Jung S (2014) Development and function of dendritic cell subsets. Immunity 40(5):642–656 5. Schraml BU, Reis e Sousa C (2015) Defining dendritic cells. Curr Opin Immunol 32:13–20 6. Lau CM, Tiniakou I, Perez OA, Kirkling ME, Yap GS, Hock H, Reizis B (2018) Transcription factor Etv6 regulates functional differentiation of cross-presenting classical dendritic cells. J Exp Med 215(9):2265–2278 7. Haniffa M, Bigley V, Collin M (2015) Human mononuclear phagocyte system reunited. Semin Cell Dev Biol 41:59–69 8. Guilliams M, Ginhoux F, Jakubzick C, Naik SH, Onai N, Schraml BU, Segura E, Tussiwand R, Yona S (2014) Dendritic cells, monocytes and macrophages: a unified nomenclature based on ontogeny. Nat Rev Immunol 14(8):571–578 9. Maier B, Leader AM, Chen ST, Tung N, Chang C, LeBerichel J, Chudnovskiy A et al (2020) A conserved dendritic-cell regulatory program limits antitumour immunity. Nature 580(7802):257–262 10. Sanchez-Paulete AR, Cueto FJ, Martı´nezLo´pez M, Labiano S, Morales-Kastresana A, Rodrı´guez-Ruiz ME, Jure-Kunkel M et al (2016) Cancer immunotherapy with immunomodulatory anti-CD137 and anti-PD-1 monoclonal antibodies requires BATF3-dependent dendritic cells. Cancer Discov 6(1):71–79 11. Schulz O, Reis e Sousa C (2002) Crosspresentation of cell-associated antigens by CD8alpha+ dendritic cells is attributable to their ability to internalize dead cells. Immunology 107(2):183–189 ˜ o CG, 12. Theisen DJ, Davidson JT 4th, Brisen Gargaro M, Lauron EJ, Wang Q, Desai P et al (2018) WDFY4 is required for crosspresentation in response to viral and tumor antigens. Science 362(6415):694–699 13. Bottcher JP, Bonavita E, Chakravarty P, Blees H, Cabeza-Cabrerizo M, Sammicheli S,
Rogers NC et al (2018) NK cells stimulate recruitment of cDC1 into the tumor microenvironment promoting cancer immune control. Cell 172(5):1022–1037. e14 14. Naik SH, Proietto AI, Wilson NS, Dakic A, Schnorrer P, Fuchsberger M, Lahoud MH et al (2005) Cutting edge: generation of splenic CD8+ and CD8- dendritic cell equivalents in Fms-like tyrosine kinase 3 ligand bone marrow cultures. J Immunol 174(11): 6592–6597 15. Helft J, Bo¨ttcher J, Chakravarty P, Zelenay S, Huotari S, Schraml BU, Goubau D, Reis e Sousa C (2015) GM-CSF mouse bone marrow cultures comprise a heterogeneous population of CD11c(+)MHCII(+) macrophages and dendritic cells. Immunity 42(6): 1197–1211 16. Guilliams M, Malissen B (2015) A death notice for in-vitro-generated GM-CSF dendritic cells? Immunity 42(6):988–990 17. Caton ML, Smith-Raska MR, Reizis B (2007) Notch-RBP-J signaling controls the homeostasis of CD8- dendritic cells in the spleen. J Exp Med 204(7):1653–1664 18. Lewis KL, Caton ML, Bogunovic M, Greter M, Grajkowska LT, Ng D, Klinakis A et al (2011) Notch2 receptor signaling controls functional differentiation of dendritic cells in the spleen and intestine. Immunity 35(5): 780–791 ˜ o CG, Lee JS, Ng D, Man19. Satpathy AT, Brisen ieri NA, Wumesh KC, Wu X, Thomas SR et al (2013) Notch2-dependent classical dendritic cells orchestrate intestinal immunity to attaching-and-effacing bacterial pathogens. Nat Immunol 14(9):937–948 20. Radtke F, MacDonald HR, Tacchini-Cottier F (2013) Regulation of innate and adaptive immunity by Notch. Nat Rev Immunol 13(6): 427–437 21. Vanderkerken M, Maes B, Vandersarren L, Toussaint W, Deswarte K, Vanheerswynghels M, Pouliot P et al (2020) TAO-kinase 3 governs the terminal differentiation of NOTCH2-dependent splenic conventional dendritic cells. Proc Natl Acad Sci U S A 117(49):31331–31342 22. Fasnacht N, Huang H-Y, Koch U, Favre S, Auderset F, Chai Q, Onder L, Kallert S et al (2014) Specific fibroblastic niches in secondary lymphoid organs orchestrate distinct Notchregulated immune responses. J Exp Med 211(11):2265–2279
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Chapter 9 In Vitro Generation of Human Dendritic Cell Subsets from CD34+ Cord Blood Progenitors Pierre Bourdely, Roberto Savoldelli, Mathias Vetillard, Giorgio Anselmi, Julie Helft, and Pierre Guermonprez Abstract Dendritic cells (DCs) are professional antigen-presenting cells controlling the activation of T cells and thus regulating adaptive immune response against pathogens or tumors. Modeling human DC differentiation and function is crucial for our understanding of immune response and the development of new therapies. Considering DC rarity in human blood, in vitro systems allowing their faithful generation are needed. This chapter will describe a DC differentiation method based on the co-culture of CD34+ cord blood progenitors together with mesenchymal stromal cells (eMSCs) engineered to deliver growth factors and chemokines. Key words Cord blood, Hematopoietic stem cells, CD34, Mesenchymal stromal cells, Dendritic cells, Conventional dendritic cells, Plasmacytoid dendritic cell, In vitro differentiation
1
Introduction Dendritic cells (DCs) are key component of the human immune system regulating innate and adaptive immune responses. DCs are short-lived and arise from bone marrow progenitors [1]. Functionally, DCs are endowed with the unique capacity to control the activation of naı¨ve T lymphocytes, thereby driving their differentiation into effector and memory cells or ensuring their functional inactivation for the purpose of maintaining tolerance. At steady state, human blood-circulating DCs are mononuclear HLADR+CD88- cells that could be classified as follows: – IRF8high, CD141+ Clec9A+ DCs also known as type 1 DCs (cDC1). cDC1s are efficient in priming CD8+ T cells through
Pierre Bourdely and Roberto Savoldelli contributed equally with all other contributors. Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_9, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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the cross-presentation of exogenous antigens on class I major histocompatibility complex (MHC-I) [2]. – IRF4high CD1c+ cDC. CD1c+ cells have been shown to encompass BTLA+CD5+/- cDC2s and CD163+CD14+/- type3-DCs (DC3) [3, 4]. Recent studies have characterized a division of labor between cDC2 and DC3, cDC2 being highly efficient in CD4+ T cells priming and DC3 in resident memory CD8+ T cells priming. – CD123+CD45RA+ cells encompassing AXL+ CD1c+ “AS” DCs and AXL-Siglec6- bona fide plasmacytoid DCs (pDCs). pDCs have multiple features of B cells and secrete high levels of type I interferons (IFNs) upon sensing of nucleic acids. “AS” DCs have been proposed to be precursors for both IRF8high cDC1s and BTLA+CD5+ cDC2s or a distinct lineage on its own [5, 6]. – Inflammatory settings are associated with complex changes in DC populations including the appearance of inflammatory CD1c+ CD14+ cells possibly derived from CD14+ monocytes [7, 8] or from a dedicated precursor. Still, it is possible that those cells derive from a terminal maturation of differentiated DCs exposed to a highly inflammatory environment. Recapitulating the development of these various DC subsets in vitro is needed to better characterize their ontogeny. For instance, in vitro methods generating DCs from hematopoietic stem (HSC) and progenitor (HSPC) cells allow the following: (i) the identification of developmental intermediates between HSCs and DCs [3] and (ii) identification of key signals controlling the fate decisions, expansion, and survival [3, 9]. Also, experimental systems faithfully recapitulating the ontogeny of DCs is a prerequisite for the study of their functions. DCs are rare cells in the bloodstream, and this complicates the delineation of their function using in vitro assays of T cell activation for instance. Several cellular sources have been proposed to generate human DCs: CD14+ monocytes, CD34+ HSPCs obtained from cord blood, bone marrow, or purified form blood upon in vivo mobilization by G-CSF. Sallusto et al. have shown that CD14+circulating monocytes culture with GM-CSF and TNF-α or IL-4 generate monocyte-derived DCs and do not recapitulate the ontogeny of multiple DC populations found at homeostasis [10, 11]. Several growth factors and cytokines have been shown to promote DC differentiation: Flt3-ligand (FLT3L) [9, 12–21], stem cell factor (SCF/KITL) [9, 12, 16, 17, 19, 22, 23], TPO (thrombopoietin) [9, 12, 20, 24], GM-CSF [11, 12, 14, 16–19, 22], IL-7 [12, 15, 21, 25], and IL-4 [7, 11, 16, 19, 22, 26]. Several approaches have been developed combining hematogenic stromal cell lines (S17 [25], OP9 [12, 14, 15, 17, 21], MS5 [3, 9, 14, 18, 27, 28]) together with various cytokines and hematopoietic growth
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factors provided as soluble recombinant proteins. Overall, the culture of CD34+ progenitor on mesenchymal stromal cells, together with soluble factors, promotes the terminal differentiation and survival and increases the final DC yields [3, 9, 12, 18, 27]. The originality of the method explained here lies in the implementation of co-culture of CD34+ HSPCs with mesenchymal stromal cells (MSCs) derived from the bone marrow niche, engineered to express membrane bound forms of hematopoietic growth factors and chemokines (eMSCs). Mechanistic experiments demonstrate that MSC-based delivery of membrane-bound FLT3L hematopoietic factor is more efficient than complementation of culture medium with recombinant protein suggesting that DC differentiation proceeds via cell-to-cell contact [9]. Screening experiments have unraveled that SCF and CXCL12 synergize with FLT3L to trigger the differentiation of DCs subsets. Stable MS5 have been produced expressing FLT3L, SCF, and CXCL12 [9]. This system is economic and versatile. It can be adapted to test the impact of defined factors to the differentiation of specific DC subsets. Importantly, this culture method recapitulates the full spectrum of DC subsets (type 1, type 2, AS and pDCs). DCs generated using this method have been characterized and aligned to their circulating counterparts by the following: (i) High-dimensional phenotyping, including CYTOF [9]. (ii) Transcriptional profiling [9, 22]. (iii) Functional assay of T cell activation (priming and polarization) and cytokine secretion [3, 9, 12].
2
Materials 1. Human umbilical cord blood unit. 2. MS5 cell line. 3. 15 and 50 mL Falcon tubes. 4. 70 μm cell strainers. 5. Ficoll-Paque (density 1077 g/mL). 6. DPBS (Dulbecco Phosphate Buffer Saline) no calcium, no magnesium. 7. T75 adherent flask culture treated. 8. CD34 microbead kit ultrapure, human (Miltenyi). 9. MS column (Miltenyi). 10. AccuCheck counting beads (Invitrogen). 11. DAPI (final concentration 0.1 μg/mL). 12. U-bottom 96-well plates tissue culture treated.
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13. Recombinant human GM-CSF. 14. Phosphate Buffered Saline (PBS). 15. Trypsin-EDTA (0.25%), phenol red. 16. ACK Red blood cell lysis buffer. 17. Freezing container such as Mr. Frosty (Thermo Scientific). 18. Human FcR blocking reagents. 19. Iscove’s Modified Dulbecco’s Medium (IMDM), GlutaMAX supplemented with 25 mM HEPES. 20. Fetal Calf Serum (FCS). The FCS should be heat-inactivated 30 min at 56 °C, filtered on a 0.22 μm pore strainer and tested before the experiment to ensure proper in vitro DC differentiation. 21. Complete IMDM (cIMDM): IMDM supplemented with 10% heat-inactivated FCS, 50 μM beta-mercapthoethanol and 100 IU/mL penicillin/streptomycin. 22. HEK 293T cell line. 23. Tissue culture-treated 10 cm dishes. 24. Complete DMEM (cDMEM): DMEM supplemented with 10% heat-inactivated FCS, 50 μM beta-mercapthoethanol and 100 IU/mL penicillin/streptomycin. 25. 2.5 M CaCl2 (store at -20 °C). 26. 2× BBS solution: 50 mM BES (N,N-bis[2-hydroxyethyl]-2aminoethanesulfonic acid), 280 mM NaCl, 1,5 mM Na2HPO4 (13.36 gr NaCl, 10.65 gr BES, 0.21 gr Na2HPO4, adjust the pH at 6.95 with NaOH 1 M, add H2O up to 1 L). The 2× BBS should be filtered on 0.22 μm pore strainer, store at -20 °C. 27. Polybrene. 28. Retrovirus vectors for mammalian expression (here, pMX vectors). 29. Ectotropic packaging plasmid: pCL-Eco suitable for mouse and rat cell transduction. 30. 0.45 μm syringe filters. 31. 1.5 mL Eppendorf tubes. 32. 6-well plate culture treated. 33. FACS buffer: PBS, 3% FCS, 2 mM EDTA. 34. Incubator at 37 °C and 5% CO2. 35. Collection buffer: DPBS, 5 mM EDTA. 36. Antibodies: see Table 1 for markers and corresponding clones. 37. Flow cytometer analyzer with the required number of PMTs. 38. FCS file analysis software (e.g., FlowJo).
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Table 1 Expression of the several surface markers used for the identification of in vitro differentiated DC Surface markers
CD45 CD88 CD123 AXL
Clones
HI30 S5/1 6H6
High
DC IRF8 subsets cDC1 IRF4High cDC2 IRF4High DC3 Macrophages pDC AS-DC
Clec9A CD141 CD1c BTLA4 CD163 CD14 GHI/ 108724 8F9 M80 L161 MIH26 61 M5E2
+
-
-
-
+
+
-
-
-
-
+
-
-
-
-
-
+
-
-
-
+
-
-
-
-
-
+
-
+
+/-
+ + +
+ -
+ +
+
-
-
+
-
+ -
+ -
The clones validated for each marker are listed below them. All the antibodies were purchased from Biolegend, except anti-AXL purchased from R&D
3
Methods
3.1 MS5 and eMS5 Culture
All the steps must be performed under sterile condition. 1. Thaw a vial of 1 mL frozen MS5 in a water bath. 2. Dilute in a 15 mL falcon tube containing 9 mL of cIMDM. 3. Centrifuge at 300 g for 5 min at 4 °C. 4. Resuspend cells in cIMDM and plate 105 cells in a T75 flasks in a total volume of 12 mL. 5. Place in the incubator at 37 °C, 5% CO2. 6. Cells need to be passaged before they reach 80% confluency (see Note 1). 7. Remove culture media and wash cells with room temperature (RT) PBS. 8. Remove PBS and add 2 mL of 0.25% trypsin 0.5 mM EDTA. Place in incubator for 5 min. 9. Gently tap the flask, and make sure that all cells are detached. 10. Add cIMDM to 10 mL and spin 5 min at 300 g at RT and discard supernatant. 11. Count cells and seed at 105 cells in a T75 flasks.
3.2 Generation of the Engineered (e) MS5 for the Growth Factor Production by Retroviral Transduction
All the steps must be performed under sterile condition. 1. Day 1: Seed the HEK 293T in culture treated dishes at 3·106 cells/plate in 10 mL cDMEM (see Note 2). 2. Day 2: Warm up cDMEM media and reagents at RT (CaCl2, 2× BBS, pMX vectors).
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3. Replace the HEK 293T medium with 10 mL of pre-warmed cDMEM. 4. Prepare the solutions A and B for calcium-phosphate transfection. 5. Solution A (for each vector): In a 1.5 mL Eppendorf tube, mix 10 μg of expression vector (pMX-CXCL12-puromycin or pMX-FLT3L-mCherry or pMX-SCF-GFP), 10 μg of packaging plasmid (pCL-Eco), 30 μL of 2.5 M CaCl2 solution and sterile distilled water up to 300 μL. 6. Solution B (1 tube/vector): 300 μL of 2× HBS in a 15 mL tube. 7. Add 300 μL of solution A to solution B drop by drop while continuously agitating the 15 mL tube by vertexing. 8. Incubate for 20 min at room temperature. (A precipitate should be visible in the 15 mL tube ensuring the quality of the transfection mix.) 9. Add 600 μL of the transfection mix on the HEK 293T seeded at day 1. 10. Incubate the plate overnight (~16 h) at 37 °C, 5% CO2 (see Note 3-4). 11. Day 3: Remove medium containing the transfection precipitate and add 10 mL of pre-warmed cIMDM. 12. Incubate 48 h at 37 °C, 5% CO2. 13. Day 4: Prepare a MS5 cell suspension, as described above in Subheading 3.1. 14. Seed the MS5 at 5·105 cells/well in a 6-well plate culture treated in cIMDM. 15. Day 5: Carefully collect the supernatant from the plate containing the transduced HEK 293T cells. 16. Centrifuge at 300 g for 5 min at 4 °C to remove the detached HEK 293T and the cell debris. 17. Filter the supernatant through a 0.45 μm syringe filter. 18. Add 20 μL/mL of 1 M HEPES to the retrovirus containing supernatant. 19. Remove the medium form the MS5. 20. Add 2 mL of retroviral supernatant in each well. 21. Add 6 μg/mL of polybrene in each well. 22. Centrifugate the plate at 300 g for 2 h at 37 °C. 23. Incubate overnight 37 °C, 5% CO2. 24. Day 7: Remove the MS5 culture medium and add pre-warmed cIMDM.
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25. Incubate at 37 °C, 5% CO2. 26. Day 9: If the vector is coding for a fluorescent reporter (e.g., GFP, mCherry), the transduction efficiency can be evaluated by fluorescent microscopy or flow cytometry. The positive MS5 can be subsequently FACS sorted. 27. Day 9: For the vector containing antibiotic resistance gene, the selection can be started. 3.3 CD34+ Cell Isolation from Cord Blood
All the steps must be performed under sterile condition and use 37 °C pre-warmed sterile DPBS and centrifuges. 1. Pour the umbilical cord blood unit in a T75 flask. 2. Dilute the cord blood with pre-warmed PBS 1:1. 3. Pour 15 mL of Ficoll Paque in 50 mL falcon tube. 4. Slowly pour 30 mL of the diluted cord blood on top. 5. Repeat steps 5 and 6 to pour all the diluted cord blood. 6. Spin at 550 g for 20 min at 37 °C (acceleration and brake should be turned off). 7. Collect leukocyte white ring in a 50 mL falcon tube (maximum one 50 mL tube for two leukocyte rings). 8. Top up with pre-warmed DPBS. 9. Spin 5 min at 300 g at 37 °C (acceleration and brake can from now on be turned back on). 10. Discard the supernatant and pool all the collection tube pellets in 50 mL pre-warmed DPBS. 11. Spin 5 min at 300 g at 37 °C. 12. Discard the supernatant and resuspend the pellet in 2 mL of ACK lysis buffer, incubate for 5 min at RT. 13. Dilute the ACK lysis buffer in 18 mL pre-warmed DPBS. 14. Spin 5 min at 300 g at 37 °C. 15. Resuspend the pellet in 10 mL pre-warmed DPBS. 16. Count the cells using a hemocytometer or a cell numeration slide. 17. Proceed to the CD34+ cell isolation following kit manufacturer instruction as follows. 18. Resuspend up to 108 total CD45+ cells in 300 μL of FACS buffer and add 100 μL of FcR block, vortex gently, and incubate for 10 min on ice, agitate gently every 5 min. 19. Add 100 uL of CD34 MicroBeads UltraPure for up to 108 total cells, incubate on ice for 30 min, agitate gently every 5 min.
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20. Wash cells by adding 10 mL of FACS buffer, spin at 300 g for 5 min at 4 °C, discard the supernatant. 21. Resuspend in 1 mL of FACS buffer and keep on ice. 22. Place a MS column on the magnet and wash it twice with 3 mL of FACS buffer allowing to pass through by gravity. 23. Apply the cell suspension onto the column by passing it through a 70 μm cell strainer. 24. Wait for all the cell suspension to go through the MS column. 25. Wash the column with 3 mL of FACS buffer three times. Do not leave the column dry. 26. Remove the column from the magnet and place it on top of a 15 mL Falcon tube, add 3 mL of FACS buffer and let it pass through collecting the cells. 27. Add an extra 3 mL of FACS buffer and flush the remaining cells from the column by firmly pushing the plunger into the column. 28. Spin the selected cells at 300 g for 5 min at 4 °C, discard the supernatant, and resuspend the cells in 520 μL of FACS buffer. 29. Proceed to the count of the CD34+-enriched cells: Prepare a solution of 100 μL of FACS buffer, 5 μL of vigorously vortexed AccuCheck beads (approximately 5000 beads, see Note 5), antihuman CD34 antibody at the right dilution, 0.1 μg/mL DAPI and add 20 μL of cell suspension. Incubate for 20 min at 4 °C and acquire on a flow cytometer. 30. Draw a gate on the beads and on the live (DAPI-) CD34+ cells. 31. Set up the stopping gate on 500 events on the bead gate (1/10 of the total beads in the tune). 32. To calculate the accurate amount of CD34+ cells do as follow: Number of cells in live CD34+ gate X 10 → number of CD34+ cells in the FACS tube X 25 = number of live CD34+ cells in 500 μL cell suspension (see Note 6). 33. CD34+ cells should be used directly for DC differentiation but can be frozen gradually in freezing container (-80 °C for 24 h then liquid nitrogen or -150 °C freezer in normal box) in 90% FCS 10% DMSO. 3.4 In Vitro eMSC and CD34+ Cell Coculture
All the steps must be performed under sterile condition and use 37 °C pre-warmed cIMDM. 1. At day 1, detach the eMSC as described above and plate 104 cells per well of a 96-well plate round bottom in a total volume of 100 μL of cIMDM let them attach for 24 h. 2. If the CD34+ cells have been frozen (see Notes 7 and 8) (if you are using fresh CD34+ cells go to step 7).
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3. Thaw a vial of 1 mL frozen CD34+ cells in a water bath. 4. Dilute in a 15 mL Falcon tube containing 9 mL of pre-warmed cIMDM. 5. Centrifuge at 300 g for 5 min at 4 °C. 6. Count the CD34+ cells at the flow cytometer as previously described. 7. Add 104 CD34+ cells in 100 μL cIMDM (see Note 9). Fill the surrounding wells with PBS to avoid media evaporation. 8. Optional: Add 100 ng/mL recombinant GM-CSF on the culture (see Note 10). 9. Then everyday gently remove 50 μL of media from each well and slowly add 50 μL of fresh, pre-warmed cIMDM or cIMDM containing 100 ng/mL recombinant GM-CSF. 10. At day 15, resuspend cells by gently pipetting up and down in their media. Collect the cells and place in a clean 15 mL Falcon tube on ice. 11. Add to each well 200 μL of collection buffer to detach the remaining cells, incubate at 4 °C for 10 min. Collect the cells and add them to the tube. 12. Top up to 10 mL the cells with FACS buffer and spin at 300 g for 5 min. 13. Resuspend the cells in antibody mix (see Table 1 for antibodies and validated clones) and transfer in 96-well round bottom plate. 14. Incubate for 30 min at 4 °C. 15. Wash the cells with 200 μL of FACS buffer. 16. Centrifuge at 300 g for 5 min 4 °C, discard the supernatant. 17. Repeat steps 6 and 7. 18. Resuspend the cells in FACS buffer and proceed to analysis at the flow cytometer (see Note 11). 19. See Fig. 1 for representative gating strategy of in vitro differentiated DC on eMSC only (MS5), eMSC expressing FLT3L, SCF and CXCL12 (MS5_FS12) alone or with recombinant GM-CSF (MS5_FS12 + recGM-CSF).
4
Notes 1. The eMSC cultures should not grow to confluency since this can affect their viability. 2. The HEK 293T should be kept at a low passage number, ideally less than ten passages.
Fig. 1 Flow cytometry analysis of in vitro DC generated on MS5 feeders. Representative gating strategy for the identification of in vitro differentiated DC after 15 days of CD34+ progenitor culture on eMSC expressing FLT3L, SCF, CXCL12 with or without GM-CSF
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3. From this step, the plate is containing retrovirus particles. We recommend to always wear specific lab coat dedicated to virus production, googles, double gloves with the first pair taped to the lab coat to ensure maximal protection. 4. All the plastic in contact with viral particle should be decontaminated overnight in bleach. 5. The exact number of beads can change between two batches of AccuCheck beads. The exact bead number can be checked on the Invitrogen website. 6. A human cord blood unit can contain between 5·105 and 3·106 CD34+ cells. 7. We recommend to not freeze CD34+ cells and use them fresh for further DC differentiation as freezing/thawing cycle can induce progenitor cell death. If frozen CD34+ cells are used, they should be in all the replicate experiments. 8. In case of freezing, 30–50% of the frozen CD34+ cells are found dead. In fact, it is crucial to count again the live CD34+ cells after thawing. 9. Do not pool several CD34+ cell for the differentiation to avoid MHC class I mismatch. NK cells could remain in the enriched CD34+ cells and kill the other cell donor. 10. Recombinant GM-CSF can be used to increase the yield of CD14+ DC3 in the culture. 11. An antihuman CD45 antibody should be added to the antibody panel to discriminate properly the CD34+-derived cells (CD45+) from the eMSCs (CD45-) on day 15. References 1. Guermonprez P, Gerber-Ferder Y, Vaivode K, Bourdely P, Helft J (2019) Origin and development of classical dendritic cells. Int Rev Cell Mol Biol. Elsevier 349:1–54 2. Bachem A et al (2010) Superior antigen crosspresentation and XCR1 expression define human CD11c+CD141+ cells as homologues of mouse CD8+ dendritic cells. J Exp Med 207:1273–1281 3. Bourdely P et al (2020) Transcriptional and functional analysis of CD1c+ human dendritic cells identifies a CD163+ subset priming CD8+CD103+ T cells. Immunity 53:335– 352.e8 4. Nakamizo S et al (2021) Single-cell analysis of human skin identifies CD14+ type 3 dendritic cells co-producing IL1B and IL23A in psoriasis. J Exp Med 218:e20202345
5. See P et al (2017) Mapping the human DC lineage through the integration of highdimensional techniques. Science 356: eaag3009 6. Villani A-C et al (2017) Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science 356:eaah4573 7. Goudot C et al (2017) Aryl hydrocarbon receptor controls monocyte differentiation into dendritic cells versus macrophages. Immunity 47:582–596.e6 8. Segura E et al (2013) Human inflammatory dendritic cells induce Th17 cell differentiation. Immunity 38:336–348 9. Anselmi G et al (2020) Engineered niches support the development of human dendritic cells in humanized mice. Nat Commun 11:2054
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10. Banchereau J, Steinman RM (1998) Dendritic cells and the control of immunity. Nature 392: 245–252 11. Sallusto F, Lanzavecchia A (1994) Efficient presentation of soluble antigen by cultured human dendritic cells is maintained by granulocyte/macrophage colony-stimulating factor plus interleukin 4 and downregulated by tumor necrosis factor alpha. J Exp Med 179: 1109–1118 12. Balan S et al (2018) Large-scale human dendritic cell differentiation revealing notchdependent lineage bifurcation and heterogeneity. Cell Rep 24:1902–1915.e6 13. Blom B, Ho S, Antonenko S, Liu Y-J (2000) Generation of interferon α–producing predendritic cell (Pre-Dc)2 from human Cd34+ hematopoietic stem cells. J Exp Med 192: 1785–1796 14. Breton G et al (2015) Circulating precursors of human CD1c+ and CD141+ dendritic cells. J Exp Med 212:401–413 15. Dontje W et al (2006) Delta-like1-induced Notch1 signaling regulates the human plasmacytoid dendritic cell versus T-cell lineage decision through control of GATA-3 and Spi-B. Blood 107:2446–2452 16. Helft J et al (2017) Dendritic cell lineage potential in human early hematopoietic progenitors. Cell Rep 20:529–537 17. Kirkling ME et al (2018) Notch signaling facilitates in vitro generation of cross-presenting classical dendritic cells. Cell Rep 23:3658– 3672.e6 18. Lee J et al (2015) Restricted dendritic cell and monocyte progenitors in human cord blood and bone marrow. J Exp Med 212:385–399 19. Poulin LF et al (2010) Characterization of human DNGR-1+ BDCA3+ leukocytes as putative equivalents of mouse CD8α+ dendritic cells. J Exp Med 207:1261–1271 20. Proietto AI, Mittag D, Roberts AW, Sprigg N, Wu L (2012) The equivalents of human blood and spleen dendritic cell subtypes can be generated in vitro from human CD34+ stem cells
in the presence of fms-like tyrosine kinase 3 ligand and thrombopoietin. Cell Mol Immunol 9:446–454 21. Schotte R, Nagasawa M, Weijer K, Spits H, Blom B (2004) The ETS transcription factor Spi-B is required for human plasmacytoid dendritic cell development. J Exp Med 200:1503– 1509 22. Balan S et al (2014) Human XCR1+ dendritic cells derived in vitro from CD34+ progenitors closely resemble blood dendritic cells, including their adjuvant responsiveness, contrary to monocyte-derived dendritic cells. J Immunol 193:1622–1635 23. Thordardottir S et al (2014) The aryl hydrocarbon receptor antagonist StemRegenin 1 promotes human plasmacytoid and myeloid dendritic cell development from CD34+ hematopoietic progenitor cells. Stem Cells Dev 23: 955–967 24. Chen W et al (2004) Thrombopoietin cooperates with FLT3-ligand in the generation of plasmacytoid dendritic cell precursors from human hematopoietic progenitors. Blood 103:2547–2553 25. Spits H, Couwenberg F, Bakker AQ, Weijer K, Uittenbogaart CH (2000) Id2 and Id3 inhibit development of Cd34+ stem cells into predendritic cell (Pre-Dc)2 but not into Pre-Dc1: evidence for a lymphoid origin of Pre-Dc2. J Exp Med 192:1775–1784 26. Sander J et al (2017) Cellular differentiation of human monocytes is regulated by timedependent interleukin-4 signaling and the transcriptional regulator NCOR2. Immunity 47:1051–1066.e12 27. Breton G et al (2016) Human dendritic cells (DCs) are derived from distinct circulating precursors that are precommitted to become CD1c+ or CD141+ DCs. J Exp Med 213: 2861–2870 28. Itoh K et al (1989) Reproducible establishment of hemopoietic supportive stromal cell lines from murine bone marrow. Exp Hematol 17: 145–153
Chapter 10 In Vitro Generation of Human Cross-Presenting Type 1 Conventional Dendritic Cells (cDC1s) and Plasmacytoid Dendritic Cells (pDCs) Xinlong Luo, Sreekumar Balan, Catharina Arnold-Schrauf, and Marc Dalod Abstract Dendritic cells (DCs) represent one of the most important immune cell subsets in preventing the host from pathogen invasion by promoting both innate and adaptive immunity. Most research on human dendritic cells has focused on the easy-to-obtain dendritic cells derived in vitro from monocytes (MoDCs). However, many questions remain unanswered regarding the role of different dendritic cell types. The investigation of their roles in human immunity is hampered by their rarity and fragility, which especially holds true for type 1 conventional dendritic cells (cDC1s) and for plasmacytoid dendritic cells (pDCs). In vitro differentiation from hematopoietic progenitors emerged as a common way to produce different DC types, but the efficiency and reproducibility of these protocols needed to be improved and the extent to which the DCs generated in vitro resembled their in vivo counterparts required a more rigorous and global assessment. Here, we describe a cost-effective and robust in vitro differentiation system for the production of cDC1s and pDCs equivalent to their blood counterparts, from cord blood CD34+ hematopoietic stem cells (HSCs) cultured on a stromal feeder layer with a combination of cytokines and growth factors. Key words CD34+ hematopoietic stem cells, Hematopoiesis, Type 1 conventional dendritic cells, Plasmacytoid dendritic cells, Notch, Stromal cells
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Introduction Human dendritic cells (DCs) reside in both lymphoid and nonlymphoid tissues and act as host sentinels to sense incoming pathogens. DCs serve as the bridge connecting innate and adaptive immunity [1]. Human blood DCs are composed of three identified cell types. (1) Type 1 conventional DCs (cDC1s) are also named CD141+ cDCs due to their selective expression of CD141 [2]. cDC1s play an important role in the cross-presentation of exogenous antigens to activate CD8+ T cell response [3], in particular for cell-associated antigens [4–6]. (2) Type 2 conventional
Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_10, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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DCs (cDC2s) can be identified with a combination of markers including HLA-DR, CD11c, CD5, BTLA, and CLEC10A [7, 8]. cDC2s excel in presenting antigens to CD4+ T cells for the initiation of humoral immune response [3]. (3) Plasmacytoid DCs (pDCs) are the main source of type I and III interferons (IFNs) upon their stimulation by viral-type stimuli [9]. IFNs produced by pDCs exert antiviral functions in the host by inducing the expression of a plethora of IFN-stimulated genes (ISGs) encoding viral restriction factors [10]. Whether and how efficiently pDCs can present antigens to CD8+ or CD4+ T cells for the induction of adaptive immune responses is debated [11]. In human PBMC, DCs represent around 1% of the total number of cells [2, 12]. Among the three DC types described above, the frequency in PBMCs of cDC2s is similar to that of pDCs and much higher than that of cDC1s that are thus the most difficult DC type to study directly ex vivo. In vitro differentiation of DCs from peripheral blood CD14+ monocyte (MoDCs) [13] has been the most commonly used method to study DC biology and their clinical potential [14, 15]. However, it has been known for over 10 years that MoDCs strongly differ from blood DC types in their gene expression pattern and hence likely in their functional specialization [15, 16]. The extremely low number of DCs in blood and other tissues is one of the biggest obstacles to directly study these cells ex vivo. In addition, for a long time, no simple and robust protocol had been described to generate pDCs, cDC1s, and/or cDC2s in vitro from hematopoietic progenitors [15]. Although pDC lines have been derived from natural neoplasms [17–19], they should only be used as surrogates for primary pDCs with great caution, taking into consideration that they have acquired numerous mutations that have considerably modified their functions including an abnormal lack of dependency on IRF7 for IFN production [20–23]. In this chapter, we describe a protocol for the efficient in vitro production of cDC1s and pDCs from CD34+ cord blood (CB) hematopoietic stem cells (HSCs), by using OP9 and OP9DL1 feeder layer cells and specific cytokine cocktails [24]. Our protocol has three advantages. (a) It includes a first step of amplification of CD34+ HSCs. This step allows a cost-effective usage of the CD34+ cells as compared to their direct use for differentiation. It also provides flexibility by allowing to freeze and thaw the expanded CD34+ HSCs, for future use and to perform series of complementary experiments with the same batch of HSCs during an extended time window. (b) It enables large-scale and simultaneously production of cDC1s and pDCs. (c) The DC types produced in vitro with this protocol were demonstrated to be equivalent to their counterparts isolated from peripheral blood, by comparing their gene expression profiles at single cell level by RNA sequencing [24]. Moreover, we showed that they share the
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same response pattern to Toll-like receptor (TLR) ligand stimulations [24]. Finally, this protocol is amenable to the use of lentiviral vectors for overexpression or knockdown of candidate genes in CD34+ hematopoietic progenitors to decipher the molecular regulation of the differentiation and functions of human DC types [25].
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Materials The overall design of the protocol is described in Fig. 1.
2.1 Cell Lines and Feeder Layer Preparation
1. OP9, OP9-DL1. 2. 100 mm TC-treated cell culture dish. 3. 24-well clear flat bottom TC-treated multiwell cell culture plate. 4. Feeder layer medium: α-MEM Glutamax, 20% fetal calf serum (FCS) (see Note 1), 10 mM HEPES, 1 mM sodium pyruvate, 100 units/mL penicillin, 100 μg/mL streptomycin, 2 mM LGlutamin, 50 μM β-mercaptoethanol, and nonessential amino acids (NEAA, 100 μM each). 5. Trypsin EDTA.
2.2 Expansion of CD34+ CB Cells
1. Recombinant human cytokines: FMS-like tyrosine kinase 3 ligand (FLT3-L), stem cell factor (SCF), interleukin (IL)-7, and thrombopoietin (TPO). 2. Amplification medium: α-MEM Glutamax, 10% FCS, 25 ng/ mL FLT3-L, 2.5 ng/mL SCF, 5 ng/mL IL-7, and 5 ng/mL TPO, to be prepared extemporaneously. 3. 96-well clear round bottom TC-treated cell culture microplate.
2.3 Cryopreservation and Revival of Expanded CD34+ CB Cells
1. Deoxyribonuclease I from bovine pancreas. 2. Cryotubes (e.g., Nunc® CryoTubes®). 3. Isopropanol.
Fig. 1 Schematic description of the protocol. The whole process described in this protocol is divided into two phases. (1) An expansion phase, which allows the amplification of CD34+ cord blood cells and takes 1 week. (2) A differentiation phase, which requires OP9/OP9-DL1 feeder layer cells and takes 2–3 weeks
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4. Freezing container (e.g., Mr. Frosty, Nalgene). 5. Freezing medium #1 (FM1): Iscove Modified Dulbecco medium (IMDM), 30% FCS. 6. Freezing medium #2 (FM2): IMDM, 30% FCS, 20% DMSO, to be prepared extemporaneously. 7. 15 mL or 50 mL polypropylene tissue culture Falcon tube. 8. Water bath adjustable to 37 C. 2.4 Differentiation of DCs from Expanded CD34+ CB Cells
1. Recombinant human cytokines: FLT3-L, TPO, and IL-7. 2. Differentiation medium: α-MEM Glutamax, 10% FCS, 10 mM HEPES, 1 mM sodium pyruvate, 100 units/mL penicillin, 100 μg/mL streptomycin, 2 mM L-Glutamin, 50 μM β-mercaptoethanol, and NEAA (100 μM each). 3. Differentiation medium +1 cytokines: Differentiation medium, 15 ng/mL FLT3-L, 5 ng/mL IL-7 and 2.5 ng/mL TPO, to be prepared extemporaneously. 4. Differentiation medium +2 cytokines: Differentiation medium, 30 ng/mL FLT3-L, 10 ng/mL IL-7, and 5 ng/mL TPO, to be prepared extemporaneously. 5. 24-well clear flat bottom TC-treated multi-well cell culture plate. 6. 15 mL or 50 mL polypropylene tissue culture Falcon tube.
2.5 Staining for Flow Cytometry Analysis
1. Fluorochrome-coupled monoclonal antibodies depending on the intended cell population or biological process to be studied. Critical antibodies to identify DC types in the culture include CD206, CD14, BDCA2 (CLEC4C), CD123 (IL3R), BDCA3 (CD141), and CLEC9A (Table 1). 2. 96-well clear round bottom TC-treated cell culture. 3. 70 μm cell strainer. 4. FACS buffer: PBS, 1 mM EDTA, 10 mM HEPES. 5. Staining buffer (SB): FACS buffer, 2% FCS. 6. Human TruStain FcX™ (Fc Receptor Blocking Solution, Biolegend). 7. Blocking buffer (BB): SB complemented 1:20, vol:vol, with Human TruStain FcX™ (e.g., 50 μL TruStain FcX™ for 1 mL SB). 8. Zombie NIR™ Fixable Viability Kit (1:1000, vol:vol, e.g., 1 μL/mL SB). 9. OneComp eBeads (eBioscience) for compensation control. 10. Fluorescence-activated cell sorter for analysis of cells.
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Table 1 Antibodies used for staining in vitro derived cDC1s, cDC2s, and pDCs Antigen
Conjugates
Clone
Dilution
Brand
Reference
CD14
BV786
M5E2
1:100
BD Biosciences
563698
CD206
PE-Cy7
19.2
1:100
Life Technology
25-2069-42
CD123
PerCP-Cy5.5
6H6
1:100
Life Technology
45-1239-42
BDCA2
BV510
201A
1:50
Biolegend
354231
CD141
BV711
1A4
1:100
BD Biosciences
563155
CLEC9A
PE
8F9
1:100
Biolegend
353804
HLA-DR
AF700
LN3
1:50
eBioscience
56-9956-42
a
CD11c
BV650
B-ly6
1:50
BD Biosciences
563403
BTLA
PE-CF594
J168-540
1:100
BD Biosciences
564801
CLEC10A
APC
H037G3
1:100
Biolegend
354705
Zombie NIR™ fixable viability kit
APC-Cy7
Not applicable
1:1000
Biolegend
423105
a
Alternately, the CD11c clone Bu15 can be used, which could yield a higher signal-to-noise ratio on cDC1s that express lower levels of CD11c than cDC2s or MoDCs
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Methods
3.1 Maintenance of Cell Lines and Preparation of the Feeder Layers
1. OP9 and OP9-DL1 cell lines are maintained with feeder layer medium and passaged at 1:5 every 48–72 h, when they are 80–90% confluent (see Note 2). 2. Pre-warm the trypsin EDTA and PBS to 37 C in a water bath set to 37 C. 3. Remove the spent medium gently with pipettes, wash the cells once with 10 mL PBS, add 0.5 mL warm trypsin (0.05%), gently shake the petri dish to ensure that the whole plate is covered by trypsin. Gently remove the eventual excess of trypsin. Put the petri dish back into the incubator. 4. After 4 min, gently tap the flask to dissociate the cells. 5. Collect the cells by adding 10 mL of feeder layer medium. 6. Add 2 mL of cell suspension to a new petri dish and fill up the volume to 10 mL of feeder layer medium. Gently move the flask while in a horizontal position to ensure even distribution of the cells.
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3.2 Expansion of CD34+ CB Cells
1. Wash the CD34+ cells and re-suspend them in amplification medium at a cell density of 2.5 104 cells/mL. 2. Plate 200 μL/well of the cell suspension, in U-bottom 96-well tissue culture-treated plates. 3. Harvest the cells on the day 7: transfer the cells into 15 mL or 50 mL tubes and centrifuge at 450 g and 4 C for 5 min (see Note 3). 4. Re-suspend the cells in α-MEM Glutamax +10% FCS and determine the number of viable cells using trypan blue. 5. Expanded cells can be either directly used for setting up the differentiation culture or cryopreserved for future use.
3.3 Cryopreservation of Expanded CD34+ CB Cells
1. The day before, prepare the freezing container by replenishing it with fresh isopropanol according to the manufacturer’s instructions. Pre-cool it overnight at around 4 C. 2. Prepare FM1 and FM2 and incubate them on ice for a time long enough to allow them to cool to 4 C (for 10 min, depending on the volume). 3. Label the appropriate number of cryotubes with sample name, cell number, date, etc. 4. Cool the cryotubes on ice for >10 min. 5. Harvest the cell culture and determine the number of viable cells. 6. Re-suspend the cells in FM1, in half of the final volume of cell suspension to be frozen. 7. Keep the cell suspension on ice for a time long enough to allow it to cool to 4 C. 8. Add an identical volume of FM2 to the cell suspension, drop by drop, to achieve a 1:1 mixture of cell suspension and FM2, with continuous gentle agitation of the cell suspension tube. The tubes must be on ice during the entire procedure. 9. Transfer 1 mL of the cell suspension to each cryotube, on ice. 10. Transfer the vials to the pre-cooled freezing container. 11. Cool the freezing container at
80 C overnight.
12. The day after, transfer the vials to liquid nitrogen for long-term storage. 3.4 Revival of Frozen Expanded CD34+ CB Cells
1. Set the water bath at 37 C. 2. Transfer the vials to the water bath and thaw the cells rapidly, until only a small piece of ice is left in the tube to ensure that the temperature of the cell suspension remains below +4 C. 3. Transfer the cells to a 15 mL polypropylene tissue culture tube.
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4. Dilute the cell suspension fivefold in cold IMDM, 5% FCS, 20 U/mL DNase I. 5. Gently mix the cell suspension, on ice. 6. Centrifuge the cell at 450 g for 5 min at 4 C at low break. 7. Resuspend the cells in cold medium #2. 3.5 Preparation of the Feeder Layer for CD34+ Cell Coculture
1. Harvest the OP9 and OP9-DL1 cell lines 48 h after seeding (80% confluent) as described above.
3.6 Seeding of Expanded CD34+ Cells on Feeder Layer Cells for Differentiation
1. Remove as much medium as possible from each well, without disturbing the feeder layer that has been prepared 1 day before, keeping just enough medium to cover the feeder layer without leaving it to dry out.
2. Dispense 12,500 cells/well, of a mixture containing 75% of OP9 cells and 25% of OP9-DL1 cells, in 24-well plate and make the final volume to 500 μL with feeder layer medium, keep the plates in the incubator for 24 h (see Note 4).
2. Count the expanded CD34+ HSCs and adjust their concentration to 10,000 cells/mL, in differentiation medium +1 cytokines (15 ng/mL FLT3L; 5 ng/mL IL-7 and 2.5 ng/mL TPO). Seed 1 mL of the cell suspension onto the feeder layer cells (see Note 5). 3. On day 7, gently remove 500 μL of medium without disturbing the feeder layer and cells. 4. Carefully add 500 μL of differentiation medium +2 cytokines. This step is very critical and should be done carefully and gently; otherwise, the feeder layer can be detached, which will affect the DC differentiation. 5. Cells can be harvested on day 14, or maintained for another 7 days (21 days) upon repeating of the procedure described in step 4 (see Note 6). 6. Harvest the cells including the feeder layer by mixing with a pipette and collect the cells from all the wells into 15 mL or 50 mL tubes. 7. Gently mix the cell suspension with a 5 mL pipette, to make a single cell suspension and to detach the DCs from the feeder layer cells. 8. Transfer the cell suspension through a 70 μM strainer into a new 15 mL or 50 mL tube to remove cell clumps. 9. Centrifuge the tubes at 450 g for 5 min at 4 C and suspend in fresh α-MEM Glutamax +10% FCS and determine the viable cell count using trypan blue.
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3.7 Phenotypic Identification of the DC Populations at the End of the Culture
The cultures include three different cell populations based on the expression of CD206 and CD14: CD206+ cells, CD206 CD14+ cells, and CD206 CD14 cells (see Note 7, Fig. 2). The CD206 CD14 fraction contains a CD123high fraction, positive for BDCA2, which represents pDCs (see Note 8). The CD123neg cells encompass BDCA3high cells whose CLEC9A-positive fraction represents the XCR1+ cDC1s (see Note 8). The CD206 CD14 CD123 CLEC9A cell fraction can be further analyzed to identify cDC2s as cells positive for HLA-DR, CD11c, BTLA, and CLEC10A (see Note 9, Fig. 3). The yields of DC types can vary from donor to donor (see Notes 10 and 11). The protocol
Fig. 2 Gating strategy for cDC1s and pDCs in the culture. Within the gate of singlet cells, live cells are gated as negative for the live/dead dye. Then, CD14+ monocytes and CD206+ macrophages are excluded. In this CD206 CD14 gate, pDCs are identified as CD123+BDCA2+ cells. In the non-pDC gate (CD123 BDCA2 ), cDC1s are identified as CD141+CLEC9A+
Fig. 3 Gating strategy for cDC1s, cDC2s, and pDCs in the culture. Following the gating strategy for cDC1s and pDCs shown in Fig. 2, cDC2 can be identified from the non-cDC1 gate (CD206 CD14 CD123 BDCA2 CLEC9A cells) by first selecting the CD11c+HLA-DR+ cells, and then within those, the CLEC10A+ BTLAint cells
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can be adapted for users aiming primarily at studying either pDCs or cDC1s (see Note 12). A similar method has been reported in a paper published in parallel to ours [26].
4
Notes 1. It is recommended to test different FCS batches in order to select a batch yielding optimal DC differentiation. 2. The culture system uses the adherent cell lines OP9 and OP9DL1 as the feeder layer for the differentiation of CB CD34+ cells. To ensure optimal supporting ability, OP9 and OP9-DL1 cells should not be passaged for more than ten generations; we suggest using the cells between second and sixth generation after their thawing. OP9-DL1 cells readily form clusters when highly confluent, which may lead to inaccuracy in cell number counting. To avoid this, passage the cells when their confluence reaches 90%. 3. CD34+ cells can be differentiated into distinct DC types with or without the 7 days expansion step. The expansion step allows large-scale proliferation of the cells and increase the total number of pDCs and cDC1s generated from one unit number of CD34+ cells. This procedure is also helpful for the cryopreservation of the amplified precursors as well as to ease lentiviral transduction of the progenitors to achieve gene overexpression or knockdown. 4. CD34+ cell or 7 days expanded CD34+ cells can be used for the coculture. These cells are seeded on the feeder layer prepared 1 day in advance with OP9 and OP9-DL1 cells and are incubated with the cytokine cocktail for 2–3 weeks. The feeder layer must be uniformly distributed in the 24-well plates and should cover at least 80–90% of the surface area before the seeding. 5. To avoid repeated freeze-and-thaw process of all cytokines, it is preferred to prepare cytokine stocks at 10 ng/mL and freeze aliquots in sterile PCR tubes. 6. We suggest harvesting the cells between 2 and 3 weeks after seeding onto the feeder layer for differentiation. 7. The Antibody Panel used is detailed in Table 1. 8. We have noticed that all of the CD123hi cells are BDCA2 positive; thus, it is possible to use CD123 only to identify pDCs in the culture. This allows releasing the BV510 channel for other antibodies that could be used in further experiments. For cDC1s staining, it is better to include both CD141 and CLEC9A because not all CD141+ cells are CLEC9A positive.
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Table 2 CD34+ HSC expansion and differentiation from four donors Expansion (7 days) Batch No.
Input cell #.
Output cell #.
19IHP231
200,000
940,000
20IHP040
200,000
20IHP043 20IHP046
Differentiation (~21 days) Fold increase
% of cDC1s
% of pDCs
4.7
11.2
3.16
1,800,000
9.0
13.8
1.67
200,000
540,000
2.7
20.5
7.33
200,000
2,200,000
11.0
22.6
4.62
9. The CLEC9A fraction can be analyzed further to identify cDC2s (Fig. 3) by gating the HLA-DR+CD11c+ subset and then the BTLAint and CLEC10Ahi subset. These cells are homogenously positive for BDCA1 and CD33. This is consistent with the recently published studies that refined phenotypic identification of human bona fide cDC2s [7, 8]. 10. The expansion of CD34+ HSCs and the percentages of cDC1s and pDCs produced in the cultures vary among different donor (Table 2). It is recommended to first test a small batch of CD34+ HSCs from different donors to perform a quick expansion and differentiation test. Only then, order a large number of CD34+ HSCs from those donors that gave the highest frequency of the desired DC types. In addition, adding granulocyte-macrophage colony-stimulating factor (GM-CSF, 0.25–0.5 ng/mL) during the differentiation step can contribute to overcome the donor-to-donor variation by increasing the proliferation of DC precursors and their differentiation into cDC1s especially. 11. There is also a large expansion of cell numbers during the differentiation phase. Under a microscope, you can easily observe that the cell confluence above the feeder layer cells can reach up to 90% around 2.5 weeks after differentiation initiation. It is possible to sort around 1 106 cDC1s and 0.3~0.5 106 pDCs from one 24-well plate, although this can strongly vary between different donors. 12. If users are primarily interested in pDCs, then they should switch to a simpler protocol yielding higher numbers of pDCs, by using only OP9 cells as feeders, with the same cytokine combination and methods. Reciprocally, if users are primarily interested in cDC1s, they should use only OP9-DL1 cells as feeders, and add GM-CSF (0.25–0.5 ng/mL) to the cytokine cocktail during the differentiation step. A recent protocol has been published, which enables the generation of human cDC1s, cDC2s, and pDCs from CD34+ HSCs in the absence of feeder layer but using type I IFN [27].
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Acknowledgments This work was performed in the frame of the I2HD collaborative project between CIML, AVIESAN, and SANOFI. It received additional funding from Inserm, CNRS, Agence Nationale de Recherches sur le SIDA et les he´patites virales (ANRS to M.D.), Institut National du Cancer (INCa grant #2011-155), FRM (Equipe labellise´e to M.D.), and the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007–2013 Grant Agreement no. 281225, to M.D.). S.B. was supported through the Agence Nationale de la Recherche (EMICIF, ANR-08-MIEN-008-02 to M.D.) and the I2HD project. X.L. was supported through SIDACTION and ANRS post-doctoral fellowships. References 1. Mildner A, Jung S (2014) Development and function of dendritic cell subsets. Immunity 40(5):642–656. https://doi.org/10.1016/j. immuni.2014.04.016 2. Dzionek A, Fuchs A, Schmidt P, Cremer S, Zysk M, Miltenyi S, Buck DW, Schmitz J (2000) BDCA-2, BDCA-3, and BDCA-4: three markers for distinct subsets of dendritic cells in human peripheral blood. J Immunol 165(11):6037–6046. https://doi.org/10. 4049/jimmunol.165.11.6037 3. Vu Manh TP, Bertho N, Hosmalin A, Schwartz-Cornil I, Dalod M (2015) Investigating evolutionary conservation of dendritic cell subset identity and functions. Front Immunol 6:260. https://doi.org/10.3389/fimmu. 2015.00260 4. Jongbloed SL, Kassianos AJ, McDonald KJ, Clark GJ, Ju X, Angel CE, Chen CJ, Dunbar PR, Wadley RB, Jeet V, Vulink AJ, Hart DN, Radford KJ (2010) Human CD141+ (BDCA3)+ dendritic cells (DCs) represent a unique myeloid DC subset that cross-presents necrotic cell antigens. J Exp Med 207(6):1247–1260. https://doi.org/10.1084/jem.20092140 5. Bachem A, Guttler S, Hartung E, Ebstein F, Schaefer M, Tannert A, Salama A, Movassaghi K, Opitz C, Mages HW, Henn V, Kloetzel PM, Gurka S, Kroczek RA (2010) Superior antigen cross-presentation and XCR1 expression define human CD11c +CD141+ cells as homologues of mouse CD8+ dendritic cells. J Exp Med 207(6): 1273–1281. https://doi.org/10.1084/jem. 20100348 6. Crozat K, Guiton R, Contreras V, Feuillet V, Dutertre CA, Ventre E, Vu Manh TP,
Baranek T, Storset AK, Marvel J, Boudinot P, Hosmalin A, Schwartz-Cornil I, Dalod M (2010) The XC chemokine receptor 1 is a conserved selective marker of mammalian cells homologous to mouse CD8alpha+ dendritic cells. J Exp Med 207(6):1283–1292. https:// doi.org/10.1084/jem.20100223 7. Heger L, Balk S, Luhr JJ, Heidkamp GF, Lehmann CHK, Hatscher L, Purbojo A, Hartmann A, Garcia-Martin F, Nishimura SI, Cesnjevar R, Nimmerjahn F, Dudziak D (2018) CLEC10A is a specific marker for human CD1c(+) dendritic cells and enhances their toll-like receptor 7/8-induced cytokine secretion. Front Immunol 9:744. https://doi. org/10.3389/fimmu.2018.00744 8. Heger L, Hofer TP, Bigley V, de Vries IJM, Dalod M, Dudziak D, Ziegler-Heitbrock L (2020) Subsets of CD1c(+) DCs: dendritic cell versus monocyte lineage. Front Immunol 11:559166. https://doi.org/10.3389/ fimmu.2020.559166 9. Tomasello E, Pollet E, Vu Manh TP, Uze G, Dalod M (2014) Harnessing mechanistic knowledge on beneficial versus deleterious IFN-I effects to design innovative immunotherapies targeting cytokine activity to specific cell types. Front Immunol 5:526. https:// doi.org/10.3389/fimmu.2014.00526 10. Schoggins JW (2019) Interferon-stimulated genes: what do they all do? Annu Rev Virol 6(1):567–584. https://doi.org/10.1146/ annurev-virology-092818-015756 11. Cabeza-Cabrerizo M, Cardoso A, Minutti CM, Pereira da Costa M, Reis ESC (2021) Dendritic cells revisited. Annu Rev Immunol 39:131.
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https://doi.org/10.1146/annurev-immunol061020-053707 12. Chen XQ, Liu XF, Liu WH, Guo W, Yu Q, Wang CY (2013) Comparative analysis of dendritic cell numbers and subsets between smoking and control subjects in the peripheral blood. Int J Clin Exp Pathol 6(2):290–296 13. Sallusto F, Lanzavecchia A (1994) Efficient presentation of soluble antigen by cultured human dendritic cells is maintained by granulocyte/macrophage colony-stimulating factor plus interleukin 4 and downregulated by tumor necrosis factor alpha. J Exp Med 179(4):1109–1118. https://doi.org/10. 1084/jem.179.4.1109 14. Tacken PJ, de Vries IJ, Torensma R, Figdor CG (2007) Dendritic-cell immunotherapy: from ex vivo loading to in vivo targeting. Nat Rev Immunol 7(10):790–802. https://doi.org/ 10.1038/nri2173 15. Crozat K, Guiton R, Guilliams M, Henri S, Baranek T, Schwartz-Cornil I, Malissen B, Dalod M (2010) Comparative genomics as a tool to reveal functional equivalences between human and mouse dendritic cell subsets. Immunol Rev 234(1):177–198. https://doi. org/10.1111/j.0105-2896.2009.00868.x 16. Robbins SH, Walzer T, Dembele D, Thibault C, Defays A, Bessou G, Xu H, Vivier E, Sellars M, Pierre P, Sharp FR, Chan S, Kastner P, Dalod M (2008) Novel insights into the relationships between dendritic cell subsets in human and mouse revealed by genome-wide expression profiling. Genome Biol 9(1):R17. https://doi.org/10.1186/gb2008-9-1-r17 17. Chaperot L, Bendriss N, Manches O, Gressin R, Maynadie M, Trimoreau F, Orfeuvre H, Corront B, Feuillard J, Sotto JJ, Bensa JC, Briere F, Plumas J, Jacob MC (2001) Identification of a leukemic counterpart of the plasmacytoid dendritic cells. Blood 97(10): 3210–3217. https://doi.org/10.1182/ blood.v97.10.3210 18. Chaperot L, Perrot I, Jacob MC, Blanchard D, Salaun V, Deneys V, Lebecque S, Briere F, Bensa JC, Plumas J (2004) Leukemic plasmacytoid dendritic cells share phenotypic and functional features with their normal counterparts. Eur J Immunol 34(2):418–426. https:// doi.org/10.1002/eji.200324531 19. Maeda T, Murata K, Fukushima T, Sugahara K, Tsuruda K, Anami M, Onimaru Y, Tsukasaki K, Tomonaga M, Moriuchi R, Hasegawa H, Yamada Y, Kamihira S (2005) A novel plasmacytoid dendritic cell line, CAL-1, established from a patient with blastic natural killer cell
lymphoma. Int J Hematol 81(2):148–154. https://doi.org/10.1532/ijh97.04116 20. Steinhagen F, McFarland AP, Rodriguez LG, Tewary P, Jarret A, Savan R, Klinman DM (2013) IRF-5 and NF-kappaB p50 co-regulate IFN-beta and IL-6 expression in TLR9-stimulated human plasmacytoid dendritic cells. Eur J Immunol 43(7):1896–1906. https://doi.org/10.1002/eji.201242792 21. Steinhagen F, Rodriguez LG, Tross D, Tewary P, Bode C, Klinman DM (2016) IRF5 and IRF8 modulate the CAL-1 human plasmacytoid dendritic cell line response following TLR9 ligation. Eur J Immunol 46(3): 647–655. https://doi.org/10.1002/eji. 201545911 22. Pelka K, Latz E (2013) IRF5, IRF8, and IRF7 in human pDCs – the good, the bad, and the insignificant? Eur J Immunol 43(7): 1693–1697. https://doi.org/10.1002/eji. 201343739 23. Ciancanelli MJ, Huang SX, Luthra P, Garner H, Itan Y, Volpi S, Lafaille FG, Trouillet C, Schmolke M, Albrecht RA, Israelsson E, Lim HK, Casadio M, Hermesh T, Lorenzo L, Leung LW, Pedergnana V, Boisson B, Okada S, Picard C, Ringuier B, Troussier F, Chaussabel D, Abel L, Pellier I, Notarangelo LD, Garcia-Sastre A, Basler CF, Geissmann F, Zhang SY, Snoeck HW, Casanova JL (2015) Infectious disease. Life-threatening influenza and impaired interferon amplification in human IRF7 deficiency. Science 348(6233):448–453. https://doi. org/10.1126/science.aaa1578 24. Balan S, Arnold-Schrauf C, Abbas A, Couespel N, Savoret J, Imperatore F, Villani AC, Vu Manh TP, Bhardwaj N, Dalod M (2018) Large-scale human dendritic cell differentiation revealing notch-dependent lineage bifurcation and heterogeneity. Cell Rep 24(7): 1902–1915. e1906. https://doi.org/10. 1016/j.celrep.2018.07.033 25. Silvin A, Yu CI, Lahaye X, Imperatore F, Brault JB, Cardinaud S, Becker C, Kwan WH, Conrad C, Maurin M, Goudot C, MarquesLadeira S, Wang Y, Pascual V, Anguiano E, Albrecht RA, Iannacone M, Garcia-Sastre A, Goud B, Dalod M, Moris A, Merad M, Palucka AK, Manel N (2017) Constitutive resistance to viral infection in human CD141(+) dendritic cells. Sci Immunol 2(13). https://doi.org/10. 1126/sciimmunol.aai8071 26. Kirkling ME, Cytlak U, Lau CM, Lewis KL, Resteu A, Khodadadi-Jamayran A, Siebel CW, Salmon H, Merad M, Tsirigos A, Collin M, Bigley V, Reizis B (2018) Notch signaling
In Vitro Generation of Human pDCs and cDC1s From HSCs facilitates in vitro generation of crosspresenting classical dendritic cells. Cell Rep 23(12):3658–3672 e3656. https://doi.org/ 10.1016/j.celrep.2018.05.068 27. van Eck van der Sluijs J, van Ens D, Thordardottir S, Vodegel D, Hermens I, van der Waart AB, Falkenburg JHF, Kester MGD, de Rink I, Heemskerk MHM, Borst J, Schaap
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Chapter 11 Culture System Allowing the Simultaneous Differentiation of Human Monocytes into Dendritic Cells and Macrophages Using M-CSF, IL-4, and TNF-α Javiera Villar, Alice Coillard, Corne´ van Roessel, and Elodie Segura Abstract Monocytes circulate in the blood and infiltrate tissues where they differentiate into either macrophages or dendritic cells, in particular during inflammation. In vivo, monocytes are exposed to various signals that modulate their commitment toward macrophage or dendritic cell fate. Classical culture systems for human monocyte differentiation yield either macrophages or dendritic cells, but not both populations in the same culture. In addition, monocyte-derived dendritic cells obtained with such methods do not closely mimic dendritic cells that are present in clinical samples. Here, we describe a protocol to simultaneously differentiate human monocytes into macrophages and dendritic cells that resemble their in vivo counterparts from inflammatory fluids. Key words Monocytes, Human, Differentiation, Macrophage, Dendritic cells
1
Introduction Human dendritic cells (DCs) can be classified into four main groups based on their ontogeny: classical DC (cDC1 and cDC2), plasmacytoid DC (pDC), DC3, and monocyte-derived DC (mo-DC) [1]. Monocytes circulate in the blood and have been shown to differentiate after entering tissues into either macrophages or dendritic cells. In human, mo-DC have been described in clinical samples at steady state in the intestine and lung, as well as in several inflamed tissues in the context of acute inflammation or chronic disease [2]. Due to limitations inherent to working with human samples, mo-DC are commonly studied in vitro. Pioneer work has shown that human monocytes can differentiate into DC when cultured with granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin (IL)-4 [3]. These cells display phenotypic markers of human DC such as CD1a and CD1c and typical
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DC functions such as stimulation of naı¨ve T cells. However, recent studies have revealed a number of differences with naturally occurring mo-DC that can be isolated from clinical samples. In particular, we have identified human mo-DC in peritoneal tumor ascites [4, 5] and found using transcriptomic profiling and functional assays that they do not closely resemble the mo-DC that can be obtained in vitro with GM-CSF and IL-4 [6]. In addition, this culture system only yields mo-DC, with some heterogeneity [7], but not bona fide macrophages. By contrast, monocyte-derived macrophages (mo-Mac) can be obtained by culturing human monocytes with macrophage colony-stimulating factor (M-CSF). In vivo, monocytes are exposed to several signals (such as cytokines) that will modulate their commitment into either mo-Mac or mo-DC. A limitation of these culture systems is that it does not allow the analysis of alternative fates of monocytes (mo-DC vs. mo-Mac). Here, we describe a protocol to simultaneously differentiate monocytes into mo-Mac and mo-DC in the same culture, using a cocktail of cytokines consisting of M-CSF, IL-4 and tumor necrosis factor (TNF)-α. In addition, the mo-DC obtained in this culture system share phenotypic, transcriptional, and functional properties with the mo-DC found in peritoneal ascites from cancer patients and synovial fluid from rheumatoid arthritis patients [6].
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Materials
2.1 Blood Monocyte Isolation
1. Human peripheral blood from healthy donors.
2.1.1
3. PBS 1×.
PBMC Purification
2. Lymphoprep (stem cell). 4. Blood separation filter tubes (see Note 1).
2.1.2
Monocyte Isolation
1. Human CD14+ Isolation Kit (Miltenyi). 2. Staining buffer: PBS, 0.5% human serum, and 2 mM EDTA. 3. LS columns (Miltenyi Biotec). 4. Pre-separation filters (Miltenyi Biotec). 5. MACS separator magnet (Miltenyi Biotec).
2.2 Monocyte Culture
1. Cell counter. 2. Differentiation medium: RPMI-Glutamax, 10% fetal bovine serum (FBS), 100 IU/mL penicillin/streptomycin, 100 ng/ mL human M-CSF, 5 ng/mL human IL-4 and 5 ng/mL, human TNF-α. 3. 24-well-plate treated for cell culture.
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Table 1 Antibodies for monocyte-derived cell phenotyping Name
Fluorochrome
Clone
Company
Suggested dilution
Anti-CD1a
APC
HI149
Biolegend
1/300
Anti-CD16
FITC
3G8
Biolegend
1/200
Human TruStain FcX™
–
–
Biolegend
1/50
2.3 Quantification of Differentiated Cells by Flow Cytometry
1. Staining buffer: PBS, 0.5% human serum, and 2 mM EDTA. 2. Human Fc receptor blocking reagent (TruStain, BioLegend). 3. Polypropylene 96-well V bottom plates. 4. Antibodies for phenotypic staining (see Table 1). 5. DAPI (Di Aminido Phenyl lndol): stock solution at 1 mg/mL. 6. Flow cytometer.
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Methods
3.1 Blood Monocyte Isolation 3.1.1
PBMC Purification
Peripheral blood mononuclear cells (PBMC) are prepared by centrifugation on a Ficoll gradient and then blood CD14+ monocytes are isolated by positive selection using magnetic beads. 1. Add 16 mL of Ficoll to 50 mL blood separation tubes. You will need one tube for every 30 mL of blood (see Note 1). 2. Centrifuge 1 min at 1000 g at room temperature (RT). 3. Place gently 30 mL of blood into each blood separation tube. Complete with PBS if necessary. 4. Centrifuge 15 min at 800 g at RT, without brake. 5. Remove the leukocyte rings with a 5 mL pipette and pool them in one 50 mL Falcon tube. 6. Fill up the 50 mL tube with PBS. 7. Centrifuge 7 min at 500 g at 4 °C. 8. Discard the supernatant carefully. Resuspend the cells in 50 mL of PBS. 9. Repeat steps 6 and 7 twice, for a total of three washes. 10. Count the cells.
3.1.2
Monocyte Isolation
1. Calculate how many PBMC to use according to the desired number of monocytes (see Note 2). 2. Collect the required number of PBMC and centrifuge at 450 g 5 min at 4 °C.
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3. Discard the supernatant and resuspend the pellet in 1 mL of staining buffer per 400 × 106 PBMC. 4. Add 100 uL of CD14-coupled magnetic beads per mL of buffer. 5. Mix gently by pipetting up and down. 6. Incubate 15 min in the fridge (4–8 °C). 7. During the incubation, place LS columns on the magnet (one column per donor, for a maximum of 1 × 109 PBMC) and pre-separation filters on the top of the columns. 8. Add 3 mL of staining buffer to each column. Discard the flow through. 9. At the end of the incubation in the fridge, wash the cell suspension by adding 5 mL of staining buffer. 10. Centrifuge at 450 g 5 min at 4 °C. Discard the supernatant. 11. Resuspend the cells in 1 mL of staining buffer and transfer to the column through the pre-separation filter. 12. Wash the column three times, using 3 mL of staining buffer each time (see Note 3). 13. Discard the pre-separation filter. 14. Place a 15 mL tube per donor on a tube holder. 15. Remove carefully the column from the magnet, and place into the 15 mL tube. 16. Add 4 mL of staining buffer in each column. 17. Elute the cells by flushing them out with the plunger. 18. Count the cells. 3.2 Monocyte Culture
Monocytes are cultured for 5 days in differentiation medium containing human M-CSF, IL-4, and TNF-α (see Fig. 1). Monocytes will differentiate into mo-Mac (CD16+ cells) and mo-DC (CD1a+ cells) in ratios that vary between donors (see Fig. 2). If desired, higher proportions of mo-DC can be obtained by increasing the concentration of TNF-α (see Fig. 3 and Note 4). This protocol describes monocyte culture in 24-well plates, but larger or smaller wells can be used, as well as flasks. However, density should be carefully considered before calculating the required number of cells (see Note 5). 1. Prepare the required volume of differentiation medium. 2. Resuspend monocytes at 2 × 106 cells/mL in differentiation medium. 3. Plate 500 uL of monocytes in each well of a 24-well plate (see Notes 5 and 6). 4. Incubate at 37 °C 5% CO2 for 5 days (see Note 7).
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Fig. 1 Cell morphology at the end of the culture. Blood CD14+ monocytes were cultured with M-CSF + IL4 + TNF-α for 5 days in 24-well plates. Bright field pictures of one representative culture. (b) Magnification of zones indicated in (a) by dotted line. Mo-Mac are elongated and adherent cells, indicated by green arrows. By contrast, mo-DCs are round and semi-adherent cells that form small clusters, indicated by red arrows
Fig. 2 The final proportion of mo-Mac and mo-DC varies between donors. Blood CD14+ monocytes were cultured with M-CSF + IL-4 + TNF-α for 5 days in 24-well plates. (a) Flow cytometry plots showing the final outcome of monocyte differentiation of two individual donors performed on the same day in the same conditions. (b) Quantification of mo-Mac and mo-DC percentages in 30 individual donors from at least seven independent experiments. Each color represents an individual donor. The line represents the median
3.3 Quantification of Differentiated Cells by Flow Cytometry
We routinely check the terminal differentiation of mo-DC and mo-Mac by staining for CD1a and CD16 as we have found this is the most robust readout (see Fig. 2a). Other phenotypic markers can also be used such as CD1b and CD226 for mo-DC, and CD163 for mo-Mac.
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Fig. 3 TNF-α enhances mo-DC differentiation. Blood CD14+ monocytes were cultured for 5 days with (a) M-CSF 100 ng/mL, (b) M-CSF 100 ng/mL + IL-4 5 ng/mL, (c) M-CSF 100 ng/mL + IL-4 5 ng/mL + TNF-α 5 ng/ mL or (d) M-CSF 100 ng/mL + IL-4 5 ng/mL + TNF-α 20 ng/mL. M-CSF allows the differentiation of mo-Mac only, while adding IL-4 and TNF-α triggers the differentiation of mo-DC. Increasing TNF-α concentration enhances mo-DC differentiation
1. Collect the supernatant from each well, containing the floating cells, in individual tubes (see Note 8). 2. Add 500 uL of staining buffer to each well and incubate 15 min on ice (see Note 9). 3. Flush the well by pipetting extensively. You can check the efficiency of flushing by examination under a microscope. 4. Collect the cell suspension and pool with the supernatant from the same well. 5. Centrifuge the tubes (5 min, 450 g, 4 °C). 6. Discard the supernatant and resuspend in 500 uL to count the cells. 7. Transfer a minimum of 1 × 105 cells per condition in the well of a 96-well plate. 8. Centrifuge the plate at 450 g 5 min, 4 °C to pellet the cells. Discard the supernatant. 9. Prepare the staining antibody cocktail in staining buffer, with 30 uL per well (see Table 1). 10. Resuspend the cells in 30 uL of antibody cocktail and incubate for 20 min at 4 °C in the dark to minimize exposure to light. 11. Wash the cells by adding 200 uL of staining buffer per well and centrifuge (5 min, 450 g, 4 °C). 12. Discard carefully the supernatant. 13. Resuspend the cells in staining buffer containing DAPI as viability dye (200 ng/mL final concentration) (see Note 10). 14. Acquire cells in a flow cytometer. Mo-DC are CD1a+CD16while mo-Mac are CD1a-CD16+ (see Fig. 2 for the gating strategy).
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Notes 1. Blood needs to be added on top of the Ficoll solution very gently. To facilitate this step, we use special blood separation filter tubes. These can be SepMate™-50 (Stemcell) or Bloodsep-filter (Dacos). 2. Monocytes usually make up around 5–15% of PBMC. This can vary between donors. 3. CD14+ monocytes will be retained on the magnet, while other PBMC will be eluted in the flow through. You can use the flow through to isolate other cell populations; otherwise, you can discard the flow through. 4. TNF-α enhances mo-DC differentiation in a dose-response manner. If only mo-DC are desired, the concentration of TNF-α can be increased to inhibit mo-Mac differentiation. 5. We have noticed that cell density is critical in obtaining a balanced mo-Mac/mo-DC ratio (see Fig. 4). High cell densities will increase mo-Mac differentiation. Each user should carefully calculate the expected density according to the culture plate or flask to be used. 6. To test the impact of a given compound on monocyte differentiation, the tested molecule can be added at the beginning of the culture, or at later time points. 7. In this culture system, the medium is not refreshed. The culture can be kept until day 6. After day 6, viability will decrease. 8. The cells can be recovered in Eppendorf tubes, Falcon tubes or 96-deep-well plates depending on the volume.
Fig. 4 Cell density is a critical parameter of the culture system. Blood CD14+ monocytes were cultured for 5 days with M-CSF + IL-4 + TNF-α for 5 days in 24-well plates at the indicated cell densities. We recommend plating cells at a density around 0.4 × 106 cells/cm2 for balanced proportions of mo-Mac and mo-DC
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9. To detach adherent cells from the wells, we recommend avoiding enzymatic treatments, such as trypsin. Instead, we incubate the cells in staining buffer (containing EDTA) on ice. This will allow detaching them by flushing, without damaging them. 10. Other viability dyes can be used. References 1. Villar J, Segura E (2020) Decoding the heterogeneity of human dendritic cell subsets. Trends Immunol 41:1062–1071 2. Coillard A, Segura E (2019) In vivo differentiation of human monocytes. Front Immunol 10: 1–7. https://doi.org/10.3389/fimmu.2019. 01907 3. Sallusto F, Lanzavecchi A (1994) Efficient presentation of soluble antigen by cultured human dendritic cells is maintained by granulocyte/ macrophage colony-stimulating factor plus iuterleukin 4 and downregulated by tumor necrosis factor α. J Exp Med 179:1109–1118. https://doi.org/10.1084/jem.179.4.1109 4. Tang-Huau TL, Gueguen P, Goudot C et al (2018) Human in vivo-generated monocytederived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway.
Nat Commun 9:1–2. https://doi.org/10. 1038/s41467-018-04985-0 5. Segura E, Touzot M, Bohineust A et al (2013) Human inflammatory dendritic cells induce Th17 cell differentiation. Immunity 38:336– 348. https://doi.org/10.1016/j.immuni. 2012.10.018 6. Goudot C, Coillard A, Villani AC et al (2017) Aryl hydrocarbon receptor controls monocyte differentiation into dendritic cells versus macrophages. Immunity 47:582–596.e6. https://doi. org/10.1016/j.immuni.2017.08.016 7. Sander J, Schmidt SV, Cirovic B et al (2017) Cellular differentiation of human monocytes is regulated by time-dependent interleukin-4 signaling and the transcriptional regulator NCOR2. Immunity 47:1051–1066.e12. https://doi.org/10.1016/j.immuni.2017. 11.024
Chapter 12 Clonal Analysis of Human Dendritic Cell Progenitors Using a Stromal Cell Culture Kang Liu, Jaeyop Lee, and Thomas Luh Abstract Dendritic cells (DCs) are a heterogenous population of professional antigen-presenting cells that play an “educator” role in immunity. Multiple DC subsets collaboratively initiate and orchestrate innate and adaptive immune responses. Recent advances in our ability to investigate cellular transcription, signaling, and function at the single-cell level have opened opportunities to examine heterogeneous populations at unprecedented resolutions. Culturing of mouse DC subsets from single bone marrow hematopoietic progenitor cells, that is, clonal analysis, has enabled identification of multiple progenitors with distinct potentials and furthered understanding of mouse DC development. However, studies of human DC development have been hampered by the lack of a corresponding system to generate multiple human DC subsets. Here, we describe a protocol to functionally profile the differentiation potentials of single human hematopoietic stem and progenitor cells (HSPCs) to multiple DC subsets, myeloid and lymphoid cells that will facilitate investigation of human DC lineage specification and reveal its molecular bases. Key words Dendritic cell, Human, Culture, Single cell, CD34+, Cord blood, Progenitor, Differentiation, Stromal cells, Flow cytometry
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Introduction Dendritic cells are a heterogenous population of professional antigen-presenting cells that play an “educator” role in orchestrating immune response [1]. In humans, there are multiple subsets of DCs: CD141+ classic DC (cDC1), CD1c+ classic DC (cDC2), CD163+ classic DC3 (cDC3), and plasmacytoid DCs (pDCs) [2– 5]; collaboratively, they initiate and orchestrate innate and adaptive immune responses. DCs are short-lived and must be constantly replenished from their bone marrow progenitors through hematopoiesis [6, 7]. The origin and development of these DC subsets and their relationship with myeloid and lymphoid lineages have been long debated topics. These debates have stimulated the development of new research approaches in the field of hematopoiesis.
Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_12, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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Hematopoiesis had traditionally been described in terms of a tree-like hierarchical bifurcation model, with stepwise developmental transitions between progenitors. This assumes progenitor populations at each stage are homogeneous in phenotype and function. According to this model, the first bifurcation generates common myeloid progenitors (CMPs) and common lymphoid progenitors (CLPs) thought to be mutually exclusive, that is, CMPs produce myeloid phagocytes executing innate immunity and CLPs produce B and T lymphocytes executing adaptive immunity. DCs were first considered to be of myeloid origin, but this theory was confounded by the apparent ability of lymphoid progenitors to also produce DCs indistinguishable from those descended from myeloid progenitors, functionally and transcriptionally [8, 9]. The development of techniques for measurements of cell transcription, signaling, and function at the single-cell level, alongside preexisting technologies such as flow cytometry, has allowed new lenses to examine these complex, heterogeneous HSPC populations. While transcriptional profiling of single cells provides a snapshot of the molecular status of heterogeneous HSPCs, functional profiling is essential proof of each cell’s differentiation potential enabled by the transcriptional features and molecular circuit. Hematopoiesis is driven by cytokines. McKenna et al. provided genetic evidence that FMS-like tyrosine kinase 3 ligand (Flt3L) cytokine is indispensable for differentiation of mouse dendritic cells in vivo [10]. Corroborating this, expression of FLT3, the receptor of Flt3L, marks the DC potential of HSPC in the mouse bone marrow [11]. Naik et al. established a Flt3L-based culture system to differentiate mouse bone marrow progenitors to generate cDC and pDC subsets that functionally and transcriptionally resemble their counterparts in vivo [12, 13]. Using this culture at single cell level, several groups revisited heterogeneous mouse HSPCs and identified a common dendritic cell precursor (CDP) that committed to cDCs and pDCs [14, 15], a common monocyte precursor (cMOP) that committed to monocytes [16], as well as pre-cDC1 and pre-cDC2 precursors committed to respective cDC subsets [17]. In contrast to mouse DCs, Flt3L is insufficient to nurture multiple human DC subsets from HSPCs in vitro. Development of in vitro culture to generate multiple human DC subsets is a result of years of cumulative efforts from multiple groups. The granulocyte-macrophage colony-stimulating factor (GM-CSF)/ interleukin (IL)-4 culture produces large numbers of monocytederived DC (mo-DCs) widely used in clinical research, although these mo-DCs differ from cDCs transcriptionally and developmentally [18–20]; a two-step cytokine cocktail culture produces large amounts of cDCs from CD34+ HSPCs [21, 22], and stromal cell cultures have been developed to produce pDCs [23, 24]. In 2015, our group established and optimized a culture system combining
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stromal cell and cytokines to generate multiple DC subsets in vitro and demonstrated that these DC subsets functionally and transcriptionally resemble their in vivo counterparts [25–28]. In this protocol, we describe our method to culture single cells of human CD34+ HSPCs in a stromal cell culture with cytokines and enumerate the clonal outcome of six different lineages (i.e., granulocyte, monocyte, lymphocyte, CD141+ dendritic cell (conventional type 1 DC (cDC1)), CD1c+ dendritic cell (conventional type 2 DC (cDC2)), and plasmacytoid dendritic cells (pDCs)) from each progenitor. Other groups and we have shown that this protocol is feasible to examine cells from prospectively isolated populations based on their differentiation potential and commitment to DC subsets, myeloid or lymphoid lineages, and has enabled identification of multiple human DC progenitors, granulocytemonocyte-dendritic progenitor (GMDP), monocyte-dendritic cell progenitor (MDP), CDP, cMOP, and pre-cDCs, with distinct potentials to cDC, pDC, and monocytes [26, 28–32]. Collectively, these studies suggest an “early-imprinting” model for DC lineage development [5, 31, 33]. Specifically, specification to the DC lineage occurs in parallel with specification to the myeloid and lymphoid lineages in hematopoietic stem cells (HSCs). It starts as a lineage bias defined by specific transcriptional programs correlated with the combinatorial dosages of the transcription factors IRF8 and PU.1, which is transmitted to most progeny cells and in a dosedependent manner and cooperates with additional key transcription factors including BATF3 and C/EBPα to guide differentiation toward DC1 and monocyte lineages, respectively [33, 34]. Importantly, IRF8 upregulation in the HSPCs and dosage maintenance is critically dependent on the hematopoietic cytokine FLT3L [33].
2
Materials 1. A source of human CD34+ hematopoietic cells (i.e., cord blood) (see Note 1). 2. 15 cm tissue culture-treated plates. 3. 15 mL Falcon® tubes. 4. 96-well V-bottom plates. 5. Flat-bottom 96-well plates. 6. 50 mL Falcon® tubes. 7. Serological pipettes. 8. Opaque Eppendorf tubes. 9. Eppendorf tubes. 10. Pasteur pipette. 11. 100 μm cell strainer.
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12. 0.20 μm filter. 13. MS5 mouse stromal cell line [27, 28]. 14. OP9 mouse stromal cell line [27, 33]. 15. Trypsin. 16. Trypan blue. 17. Ficoll-Paque Plus. 18. Antihuman CD34 MACS microbeads (Miltenyi Biotec). 19. Recombinant human Flt3L. 20. Recombinant human stem cell factor (SCF). 21. Recombinant human GM-CSF. 22. Antibodies (details of clone name, fluorochrome, manufacturer, and dilution are listed in Tables 1 and 3). 23. FcR blocking buffer (Miltenyi Biotec). 24. Absolute Counting Beads. 25. Complete MEMα medium: MEMα, 10% fetal bovine serum (FBS), 100 IU/mL penicillin/streptomycin.
Table 1 Antibody preparation for purification of progenitors from human cord blood Volume per 1 106 cell (mL)
Fluorochrome
Antigen
Company
Clone
Dilution factor
Alexa Fluor (AF) 700
CD45
Biolegend
HI30
200
0.05
Qdot-655
CD14
Invitrogen
Tuk4
800
0.01
Brilliant Violet (BV) 650
CD19
Biolegend
HIB19
200
0.05
BV650
CD3
Biolegend
OKT
200
0.05
BV650
CD56
Biolegend
HCD56
200
0.05
BV650
CD16
Biolegend
3G8
200
0.05
APC-Cy7
CD34
Biolegend
581
200
0.05
PE
CD10
Biolegend
HI10a
100
0.1
FITC
CD45RA
Biolegend
HI100
80
0.13
BV421
CD38
Biolegend
HIT2
80
0.13
BV510
CD123
Biolegend
6H6
80
0.13
Additional PBS Final volume
9.21 10.00
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26. Mitomycin C stock (1 mg/mL): dissolve 2 mg Mitomycin C powder in 2 mL dH2O, vortex and filter the solution with a 0.20 μm filter and stock at 20 C (see Note 2). 27. FACS buffer: PBS, 2 mM EDTA, 0.5% BSA. 28. Anti-CD34 microbeads/FcR blocking mix: 15% FcR blocking buffer, 25% anti-CD34 MACS beads, 60% FACS buffer. Prepare 2 μL of the mix per one million total nucleated cells. 29. Cell culture incubator. 30. Inverted phase contrast microscope. 31. Flow cytometer that is equipped with lasers and emission filters suitable for the analysis of cells stained with the dyes listed in the antibody panel (see Note 3).
3
Methods
3.1 Culture of Stromal Cells (Day 4 to Day 0) 3.1.1 Passaging Stromal Cells
1. Grow MS5 and OP9 cells in complete MEMα medium. For 15 cm plates, seed 1.5 106 cells in 20 mL medium. 2. For normal passage, microscopically verify that the cells are 80–90% confluent. 3. Remove medium from the culture plate by aspiration and wash cells with 10 mL sterile PBS pre-warmed to 37 C to remove medium and FBS. 4. Remove the PBS and then add 3 mL trypsin pre-warmed to 37 C. 5. Incubate for 2–3 min at 37 C, and microscopically verify that cells have started to detach. 6. Add 10 mL complete MEMα medium pre-warmed to 37 C to stop trypsin activity. 7. Resuspend cells by pipetting up and down, and then transfer cells to 15 mL collecting tubes. 8. Centrifuge at 450 g for 5 min at 4 C. 9. Remove supernatant, and then resuspend the cells in 1 mL complete MEMα medium (cell concentrate). 10. In a new 15 cm plate, add 20 mL complete MEMα medium. Transfer 100 μL cell concentrate to the new plate. This new plate will become confluent after 3–4 days. 11. Incubate at 37 C, 5% CO2 for 3–4 days, or until cells are 80–90% confluent (see Note 4). 12. Passage the cells again, to a maximum of 13 passages (see Note 5).
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3.1.2 Treating Stromal Cells with Mitomycin C
1. Verify that MS5/OP9 cells are 80–90% confluent. 2. Label collecting tubes (“MS5 + mitC,” “OP9 + mitC”). 3. Add Mitomycin C stock (1 mg/mL, 100) directly into the medium pre-warmed to 37 C to achieve a final concentration of 10 μg/mL. For example, aspirate medium and add back exactly 10 mL, and add 100 μL Mitomycin C stock. 4. Mix by swirling gently for 3–5 s. 5. Incubate at 37 C for 3 h.
3.1.3 Plating Mitomycin C-Treated Stromal Cells
1. Remove medium, and then add 10 mL PBS pre-warmed to 37 C. Gently swirl the plate for 3–5 s. 2. Remove the PBS, and then add 3 mL trypsin pre-warmed to 37 C. 3. Incubate for 2–3 min at 37 C, and use a microscope to verify that cells have started to detach. 4. Add 10 mL complete MEMα medium pre-warmed to 37 C to stop trypsin. 5. Resuspend cells by pipetting up and down, and then transfer cells to labeled harvesting tubes. 6. Centrifuge at 450 g for 5 min at 4 C. 7. Remove medium, and then resuspend in 1 mL complete MEMα medium. 8. Count cells, and calculate the number and volume of cells needed for the final plating. Each well in a flat-bottom 96-well plate should contain 6250 OP9 cells and 37,500 MS5 cells in 50 μL complete MEMα medium (see Note 6). 9. Incubate cells at 37 C overnight. 10. Verify that cells are attached to plate by shaking gently while viewing under a light microscope (see Note 7). 11. Within 1–3 days, sort and plate progenitors on these cells.
3.2 Purification of CD34+ HSPC from Human Cord Blood (Day 0) 3.2.1 Isolation of Cord Blood Mononuclear Cells Using Ficoll-Paque (See Note 8)
1. Add 25 mL PBS into multiple 50 mL tubes. 2. Sterilize the outside of the cord blood sample container with 70% ethanol. 3. In 15 mL portions, evenly distribute the cord blood sample into the prepared 50 mL Falcon tubes containing PBS. 4. Rinse the blood sample container with some additional room temperature PBS, and use the rinse to “top off” the last Falcon tube (such that each tube has a fluid volume of 40 mL). On average, use seven Falcon tubes per bag of cord blood (see Note 9). 5. Tightly seal each of the tubes, and gently invert them three to five times to resuspend any sedimented cells.
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6. Underlay the cell suspension with 10.5 mL of Ficoll-Paque with a 10 mL serological pipette (see Note 10). 7. Centrifuge at 450 g for 25 min at room temperature. Use lower acceleration (level 3 of 9) and no brakes for deceleration (see Note 11). 8. During the centrifugation prepare one 15 mL buffy collection tube for each 50 mL tube from the previous steps. Add 2 mL PBS in each tube. 9. After centrifugation, there should be four layers: – The topmost layer PBS/serum mix.
(yellow/clear,
~35
mL)
is
a
– The second layer from top (cloudy, ~1 mL) is a leukocytecontaining buffy coat. – The third layer from top (clear, ~10 mL) contains FicollPaque. – The bottommost layer (red, ~5 mL) contains red blood cells (RBCs). – Additionally, at the buffy coat layer, a smeared pellet of cells (cloudy, ~1–5 mm) should be deposited along the test tube wall. 10. Remove the PBS/serum layer until only 10 mL of this layer remains, using caution to avoid turbulence by aspirating from the top of the layer (see Note 12). 11. With a 10 mL serological pipette, transfer the buffy coat layer to a buffy collection tube, and use caution to minimize fluid transfer (see Note 13). Leave ~5 mL of PBS/serum for the next step. 12. Resuspend the smeared pellet of cells in the Ficoll-Paque by gently rocking the tube, using caution to avoid mixing the fluid layers (see Note 14). 13. Transfer as much Ficoll-Paque layer as possible to the buffy collection tube, while completely avoiding the RBC layer. Avoiding the PBS/serum layer is ideal, but not critical. 14. Centrifuge at 450 g for 10 min at 4 C. 15. Remove supernatant, and resuspend cells in 1 mL FACS buffer. 16. Collect cell suspensions from all collection tubes into a single 50 mL Falcon tube. 17. Wash the cells by adding FACS buffer until the total fluid volume is 50 mL. 18. Count the cells (see Note 15). 19. Centrifuge at 450 g for 5 min at 4 C. 20. Remove supernatant, deriving a mononuclear cell pellet.
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3.2.2 Enrichment of CD34+ Cells
1. In a 15 mL conical tube, dilute the cells in 2 μL anti-CD34 microbeads/FcR blocking mix per 1 106 nucleated cells. 2. Incubate at 4 C for 30–40 min. 3. Add FACS buffer up to the 15 mL line. 4. Centrifuge at 450 g for 5 min at 4 C. 5. Remove supernatant. 6. Resuspend cells in FACS buffer at the concentration of 100 106/mL. 7. Prepare an elution tube: 15 mL Falcon tube +2 mL FACS buffer. 8. Perform positive selection for CD34+ cells with a LS MACS column. 9. Place a 100 μm cell strainer on top of the column. 10. Equilibrate the column by filtering 5 mL FACS buffer through the strainer; discard the flow-through. 11. Gently vortex the cells to ensure suspension. 12. Filter the cells through the LS MACS column; retain the flowthrough. 13. Optional: wash the column once by passing 4 mL FACS buffer through it; discard this wash. Then, re-load the flow-through from the previous step on the column to increase cell yield. 14. Wash the column by passing 4 mL FACS buffer through it; discard the wash. 15. Repeat the wash a second time, and discard the wash again. 16. Remove the MACS column from its magnetic holder, and place it on top of the elution tube. 17. Add 4 mL of FACS buffer to the column, and allow gravity elution to occur. 18. Add 4 mL of FACS buffer, taking caution to prevent the column from drying out, and use a plunger to push the FACS buffer through. 19. Count the cells (see Note 16). 20. Centrifuge at 450 g for 5 min at 4 C. 21. Remove supernatant. 22. Proceed to culture (next step) (see Note 17).
3.3 Culture of Purified Cells in Single-Cell Environment (Day 0–7) 3.3.1 Single-Cell Sorting and Plating
1. Stain CD34+ HSPCs with antibody mix. Use 10 μL antibody mix for 1 106 cells according to the following dilution (Table 1). Incubate cells on ice for 40 min, and using flow cytometry, sort cells according to following gating (Table 2, Fig. 1).
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Table 2 Characterization of progenitor populations in human cord blood Progenitor
Markers
Hematopoietic stem cell (HSC)
CD34+CD38 CD45RA CD90+
Multipotent progenitor (MPP)
CD34+CD38 CD45RA CD90
Lymphoid-primed multipotent progenitor (LMPP)
CD34+CD38 CD45RA+CD10
Multilymphoid progenitor (MLP)
CD34+CD38 CD45RA+CD10+
B and NK cell progenitor (BNKP)
CD34+CD38+CD45RA+CD123int/ CD115 CD10+
Common myeloid progenitor (CMP)
CD34+CD38+CD45RA CD10 CD123int
Granulocyte/monocyte/DC progenitor (GMDP)
CD34+CD38+CD45RA+CD10 CD123int
Monocyte/DC progenitor (MDP)
CD34+CD38+CD45RA+CD123intCD115+
Common DC progenitor (CDP)
CD34+CD38+CD45RA+CD123hiCD115
Megaerythrokaryocyte progenitor (MEP)
CD34+CD38+CD45RA CD10 CD123
Fig. 1 Visual gating strategy of progenitor populations in human cord blood. Flow cytometry plots show separation of CD34+ cord blood cells into ten populations, HSC, MPP, LMPP, MLP, BNKP, CMP, MEP, GMDP, MDP, and CDP. Lin 1 includes CD3/14/16/19/56 and Lin 2 includes CD66b/11c/303
2. Sort single cells into each well of stromal-cell-containing 96-well plates with 50 μL complete MEMα medium per well. 3.3.2 Cell Culture Over Time
1. Prepare a 2 mixture of cytokines in complete medium: 200 ng/mL Flt3L (final 1 concentration 100 ng/mL), 40 ng/mL SCF (final 1 concentration 20 ng/mL), 20 ng/ mL GM-CSF (final 1 concentration 10 ng/mL) (see Note 18).
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Table 3 Antibody preparation for analysis of progeny from human cord blood
Fluorochrome Antigen Company Live Dead
Clone
Life Technology
Volume per Dilution sample (24-well factor plate) (μL)
Volume per sample (96-well plate) (μL)
1000
0.01
0.01
Alexa Fluor (AF) 700
CD45
Biolegend
HI30
200
0.05
0.02
Qdot-655
CD14
Invitrogen
Tuk4
800
0.01
0.01
PE
Clec9a
Biolegend
8F9
500
0.02
0.01
PerCP-Cy5.5
CD66b Biolegend
G10F5
100
0.10
0.04
PE-Cy7
CD1c
Biolegend
L161
100
0.10
0.04
FITC
CD303 Biolegend
201A
100
0.10
0.04
APC-Cy7
CD56
Biolegend
HCD56
100
0.10
0.04
APC-Cy7
CD19
Biolegend
HIB19
80
0.13
0.05
BV510
CD123 Biolegend
6H6
80
0.13
0.05
APC
CD141 Miltenyi
AD514H12
80
0.13
0.05
9.13
3.65
Additional PBS Final volume
10.00
4
2. Add the 2 mixture of cytokines to seeded stromal cell wells. (Add 50 μL for 96-well plate.) 3. On day 7, for each well, prepare 50 μL medium containing cytokines at 3 concentration. Gently add 50 μL fresh media with 3 cytokines into the well by pipetting onto the wall (see Note 19). 4. On day 14, prepare 50 μL medium containing cytokine at 3 concentration as in previous step. Gently remove 50 μL of the old medium from each well, and then add 50 μL fresh media into the well by pipetting onto the wall. 3.4 Harvest and Analyze CD34+ Cells’ Output (Day 7–21) 3.4.1 Read Cells via Flow Cytometry
1. Prepare antibody mixture in FACS buffer using the following dilution (Table 3). 2. Add PBS such that each well is filled, using a multichannel pipet (250 μL on a 96-well plate). 3. Pipet up and down 10–20 times to resuspend cells, and transfer 150 μL to 96-well V-bottom plates for staining.
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4. Centrifuge at 450 g for 5 min at 4 C. 5. Discard the supernatant by microtip aspiration, using caution to keep the fluid level above the slanted portion of the well. 6. Transfer the remaining 100 μL of cells to the 96-well V-bottom plates. 7. Centrifuge at 450 g for 4 min at 4 C. 8. Discard the supernatant, as before. 9. Add 4 μL of antibodies to the side wall of the well. 10. Gently vortex the plate to resuspend the cells, using caution to avoid any fluid spillage. To do so, reduce the vortex speed to minimum, grasp the plate firmly, and firmly place it on the vortex mixer. Slowly increase the vortex speed, and gently reduce pressure on the vortex mixer so that the vortex mixer can shake. Then, decrease the vortex speed and remove the plate. As needed, this process may be repeated in each of the plate’s four quadrants. It is advised to practice this technique with a test plate and tap water to ensure no sample loss (see Note 20). 11. Gently vortex the plate to mix cells with the antibody, as before. 12. Centrifuge with a quick spin (50 g, 5 s) to bring down the cells and staining mix to the bottom of the well. 13. Incubate in the dark for 40 min at 4 C. 14. Add 200 μL PBS to wash. 15. Centrifuge at 450 g for 5 min at 4 supernatant.
C. Discard the
16. Resuspend in 50 μL FACS buffer. 17. Vortex the counting beads stock solution for 30 s, and make a 1:10 dilution of counting beads in FACS buffer. 18. Add 10 μL of dilute counting beads to each well (~1000 beads per well). 19. Acquire cells on a flow cytometer (BD-LSRII or LSR Fortessa) (see Note 3), and gate cells according to the following gating (Table 4, Fig. 2, and [33]). 20. Proceed to data analysis.
4
Notes 1. Although this culture protocol only reports differentiation potential of granulocyte, monocyte, lymphocyte, CD141+ dendritic cell (cDC1), CD1c+ dendritic cell (cDC2), and plasmacytoid dendritic cells (pDCs) of hematopoietic lineage from
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Table 4 Characterization of progeny populations in human cord blood Progeny
Markers
Granulocyte (G)
CD45+CD66b+
CD1c DC (C)
CD45+CD66b CLEC9a+CD141+
CD141 DC (A)
CD45+CD66b CLEC9a CD1c+
Monocyte (M)
CD45+CD66b CLEC9a CD1c CD14+
pDC (P)
CD45+CD66b CLEC9a CD1c CD14 CD123+CD303+
Lymphocyte (L)
CD45+CD66b CLEC9a CD1c-CD14 CD123 CD19/56+
Fig. 2 Visual gating strategy for analysis of progeny populations in human cord blood. Flow cytometry plots show phenotype of six cell types differentiated from CD34+ cells cultured in MP + FSG, granulocytes, monocytes, cDC1, cDC2, pDC, and B/NK (lymphoid) cell
cord blood, the method can be applied to culture CD34+ HSPCs from human bone marrow. However, the proliferative capacity of adult bone marrow HSPCs is lower than those from cord blood. 2. Mitomycin C should be used up to 3-months post solubilization, after this period of time its activity decreases. 3. We currently use BD flow cytometers LSRII or LSRFortessaTM for flow cytometric analysis. If instruments with the suitable set up are not available, antibody panel can be changed according to cytometer configuration. 4. For both MS5 and OP9 cells when 15 cm plate reach 80–90% confluency you can expect 15–20 106 cells. 5. Stromal cell should not exceed 13 passages after which cells start undergo senescence. 6. If you wish to prepare for one full 96-well plate, resuspend 0.625 106 OP9 cells and 3.75 106 MS5 cells in 5 mL complete MEMα medium, mix well, and then distribute 50 μL into each well. 7. Stromal cells should be firmly attached to the plate and not drifting around with the fluid movement. 8. The step involving HSPC isolation should be handled at room temperature to preserve cell quality and viability.
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9. Cord blood samples usually contain about 50 mL of blood material. 10. This step should be carried out with great caution. We advise to follow these steps: load 10.5 mL Ficoll-Paque into the pipette. Without releasing any fluid, gently bring the pipette to the bottom of the tube. For the first 2 mL, very slowly release Ficoll-Paque into the bottom of the tube. The goal is to have a pure layer of Ficoll-Paque at the bottom of the tube. For the next 8 mL, the Ficoll-Paque release can be slightly sped up, but use caution to avoid turbulence that may disrupt the FicollPaque-blood boundary. For the last 0.5 mL, slow down the Ficoll-Paque release, and observe the meniscus in the pipette. Use caution to prevent introducing air bubbles into FicollPaque. 11. For this centrifugation step, we advise to orient the opaque sections of the test tube face toward the central motor of the centrifuge, so that cell deposits will collect on a transparent section of the test tube, away from the motor, and so can be easily visualized. 12. If the buffy coat line is at the 30 mL line, stop aspiration when the remaining fluid reaches 40 mL mark. 13. To minimize fluid transfer, hold the pipette tip directly above the buffy coat, and slowly aspirate, then eject fluid to the buffy collection tube. 14. The rocking motion allows the liquid-liquid interface between the Ficoll-Paque and the PBS/serum mix to rub the pellet off the wall. 15. Commonly each bag of cord blood yields ~300–1000 106 cells. 16. After positive selection an individual cord blood yields about 5–20 106 CD34+ cells. 17. Upon positive selection, CD34+ cells can be stored overnight on ice at 4 C, or frozen in 10% DMSO +90% FBS media; however, proceeding with fresh cells without an intermediate freezing step is recommended for optimal clonal output and cell viability. 18. GM-CSF stimulates and inhibits proliferation of various cell subtypes. 19. Here, a higher concentration of cytokines is prepared because the final media volume will be increased, while the volume of media-cytokine mixture remains the same. Media is not removed from the wells to avoid disturbing cell attachment. 20. Alternatively, cells could be resuspended by gently pipetting up and down 10–20 times.
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Part IV Enrichment of Dendritic Cells
Chapter 13 Enrichment of Large Numbers of Splenic Mouse Dendritic Cells After Injection of Flt3L-Producing Tumor Cells Pauline Santa, Anaı¨s Roubertie, Se´verine Loizon, Anne Garreau, Amandine Ferriere, Dorothe´e Duluc, and Vanja Sisirak Abstract Dendritic cells (DCs) are antigen-presenting cells (APCs) that shape innate and adaptive immunity. There are multiple subsets of DCs distinguished according to their phenotype and functional specialization. DCs are present in lymphoid organs and across multiple tissues. However, their frequency and numbers at these sites are very low making their functional study difficult. Multiple protocols have been developed to generate DCs in vitro from bone marrow progenitors, but they do not fully recapitulate DC complexity found in vivo. Therefore, directly amplifying endogenous DCs in vivo appears as an option to overcome this specific caveat. In this chapter, we describe a protocol to amplify murine DCs in vivo by the injection of a B16 melanoma cell line expressing the trophic factor FMS-like tyrosine kinase 3 ligand (Flt3L). We have also compared two methods of magnetic sorting of amplified DCs, both giving high yields of total murine DCs, but different representation of the main DC subsets found in vivo. Key words Conventional dendritic cells, Plasmacytoid dendritic cells, Flt3L, DC enrichment
1
Introduction Dendritic cells (DCs) are sentinels disseminated throughout the body playing a key role in initiating and controlling immune responses. In mouse spleen, three phenotypically and functionally distinct subsets can be found at steady state including plasmacytoid dendritic cells (pDCs) and two subsets of conventional dendritic cells (cDCs) [1–5]. The pDCs are defined by their low expression of CD11c and MHC-II and their high expression of mPDCA1 (Bst2), B220, and Siglec-H [6–8]. All subsets of cDCs express high levels of CD11c and MHC-II and are further separated into CD8α+, Xcr1+ cDC1 and CD8α-, CD11b+, SIRPα+ (CD172a) cDC2 [9, 10]. In addition to their differential phenotype, these three splenic DC subsets display distinct functional properties. PDCs are specialized in the production type I interferons (IFNs) notably
Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_13, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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in response to endosomal Toll-like receptor (TLR) 7/9 stimulation by viral nucleic acids and thus play and important role in antiviral immune responses [11]. The cDC1 subset mainly control responses directed against intracellular pathogens [12, 13] as well as tumor antigens (Ag) [14] and is specialized in the crosspresentation of exogenous Ag in major histocompatibility complex (MHC)-I to CD8 T cells [14–16]. The cDC2 subset mediates immune responses directed against extracellular pathogens including fungi and bacteria and preferentially activate CD4 T cells through Ag presentation in MHC-II molecules [17–19]. The understanding of DC functions is facilitated by their manipulation in vitro. However, at steady state, DCs represent only 1–2% of the total splenocytes, and they are even scarcer in tissues making them rare cells. In addition, the distribution of different subsets of DCs is not equal, with cDC1 being particularly underrepresented. Therefore, isolating DCs in numbers required for their functional characterization in vitro is difficult. Multiple protocols have been established to generate DC in vitro from bone marrow (BM) progenitors. The culture of BM cells with granulocyte-macrophage colony-stimulating factor (GM-CSF) +/- interleukin (IL)-4 leads to the differentiation of cDC2 resembling inflammatory DCs [20] and contains contaminant macrophages [21]. In addition, such BM cultures do not induce the generation of cDC1 nor pDCs. Conversely, culture of BM cells in the presence of Fms-like tyrosine kinase receptor 3 ligand (Flt3L) allows the differentiation of both pDCs and cDCs resembling splenic DCs found endogenously at steady state [22–24]. Nevertheless, the cDC1 subset obtained from BM cultures in Flt3L exhibits an immature phenotype and does not express canonical cDC1 markers such as CD8α. Recently, addition of feeder cells (OP9) expressing the ligand of Notch receptors (delta like ligand 1) to BM cultures in Flt3L allowed the generation of fully mature cDC1 and cDC2 but severely impaired pDCs generation [25]. Therefore, in vitro generation of DCs from BM cells gives rise to functional DCs, but such methods do not individually generate the full spectrum of DC subsets found in vivo. Flt3L function in DC development has been long established. Indeed, Flt3L deficiency leads to the loss of DCs [26], while supplementation of mice with recombinant Flt3L causes a massive expansion of endogenous DCs [27, 28]. Given the role of DCs in priming antitumor immune responses, tumor cell lines such as the B16 melanoma expressing Flt3L ligand have been established [29]. Their injection in mice greatly amplified DCs in vivo and boosted antitumor immune responses [29, 30]. This amplification occurs in lymphoid organs and tissues and affects all DC subsets including pDCs and cDCs. These observations provided a strong rationale to use these tumor cell lines to amplify DCs in vivo to facilitate their isolation and functional studies in vitro. The use of
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Fig. 1 Schematic overview of the experimental design. 5·105 B16-Flt3L cells are injected subcutaneously in each flank of wild-type mice. Once the total tumor volume reaches 1500 mm3, splenocytes are isolated (Step 1). Next, TCRβ+, CD19+, and F4/80+ cells are depleted by magnetic selection (Step 2), and the negative fraction is used to isolate total DC by positive selection following two protocols. In protocol A, the CD11c+ cells are magnetically sorted (Step 3A), while in the protocol B, both CD11c+ and mPDCA1+ cells are magnetically sorted (Step 3B)
Flt3L expressing tumor cells allows its continuous production in sustained systemic levels in contrast to injections of the recombinant protein and is more cost-effective. Here, we describe a protocol based on the implantation of B16 melanoma cell line expressing Flt3L to amplify splenic DCs (see Fig. 1). After ~15 days of implantation of B16-Flt3L cells, mice show a splenomegaly that is mostly due to an accumulation of DCs that correspond to 25% of splenocytes (see Fig. 2). From these splenocytes, we describe two methods based on magnetic sorting to purify large numbers of total DCs, which differ in the final yields in individual DCs subsets (see Fig. 1).
2
Materials
2.1 Injection of B16Flt3L Tumor Cells In Vivo
1. C57Bl/6J mice (8–20 weeks old). 2. B16-Flt3L melanoma cell line-secreting murine Flt3L. 3. T75 culture flasks. 4. Complete RPMI medium: RPMI-1640, 10% fetal bovine serum (FBS, decomplemented at 55 °C for 1 h and filtered through 0.22 μm filter), 1% HEPES, 1 mM sodium pyruvate, 2 mM L-glutamine, 1 mM nonessential amino-acid, 100 U/ mL penicillin, 100 μg/mL streptomycin. 5. Phosphate Buffered Saline (PBS) 1×, pH 7.4. 6. Trypsin-EDTA 0.05%, phenol red. 7. 15 mL Falcon tubes. 8. Malassez counting chamber.
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Fig. 2 Injection of B16-Flt3L cells expands all splenic DC subsets. Splenocytes were isolated from control mice (n = 3) or mice injected with B16-Flt3L cells (n = 5). (a) Singlets live CD45+ cells were gated. Next, pDCs were identified as B220+ Siglec H+, cDCs as B220- MHC-IIhigh, CD11c+, and cDCs were further separated in cDC1 (CD8α+ CD11b-) and cDC2 (CD8α- CD11b+). (b–d) Combined data showing the frequencies of (b) all DC subsets among CD45+ cells, (c) cDC1 and cDC2 subsets among total cDCs (CD11c+, MHC-II High) and (c) the absolute numbers of each DCs subset cells in control and B16-Flt3L injected mice. Data are presented as mean +/- SD
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9. 1 mL syringe. 10. 26G needle. 11. Measuring caliper. 1. Complete RPMI medium.
2.2 Preparation of Single-Cell Suspensions of Splenocytes
2. Dissecting pliers and scissors. 3. PBS 1×, pH 7.4. 4. 70 μm cell strainers. 5. 10 mL Syringe plungers. 6. 15 and 50 mL Falcon tubes. 7. MACS buffer: PBS 1×, 1% FBS, 2 mM EDTA. 8. Red blood cell (RBC) lysis buffer: 0.15 M NH4Cl, 10 mM KHCO3, 0.5 M EDTA that was adjusted to pH 7.2 and filtered at 0.22 μm. 9. Fc receptor (FcR) block: anti-CD16/CD32 Antibody (Ab). 10. Antibodies cocktail to verify DC amplification (see Table 1). 11. V-bottom 96-well plates. 12. 1.4 mL U-bottom micronic tubes. 13. Flow cytometers equipped with lasers and emission filters suitable for the analysis of cells stained with the dyes listed in the antibody panel (see Table 1). 14. FlowJo software for flow cytometry data analysis.
2.3 Depletion of T cells, B cells, and Macrophages
1. FcR block: anti-CD16/CD32 Ab. 2. Mouse biotin antibodies cocktail (see Table 2). 3. MACS buffer.
Table 1 Antibodies used to analyze DC frequencies at each step of the protocol Target
Fluorochrome
Zombi
Aqua
CD45
PerCPCy5.5
CD11c
Clone
Source
Concentration
Biologend
1/200
30-F11
BD Pharmingen
0.25 μg/mL
PE
N418
Biolegend
0.4 μg/mL
MHCII
PB
AF6-120.1
Biolegend
1.25 μg/mL
B220
PE CF5945
RA3-6B2
BD Pharmingen
0.5 μg/mL
CD11b
APC-Cy7
M1/70
Molecular probes
0.25 μg/mL
CD8α
BV785
53-6.7
Biolegend
0.5 μg/mL
Siglec H
APC
551
Biolegend
1 μg/mL
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Table 2 Antibodies cocktail for the negative selection Target
Clone
Provider
Concentration (μg/mL)
TCRβ
H57-597
Biolegend
2.5
CD19
6D5
Biolegend
2.5
F4/80
BM8
Biolegend
2.5
4. Streptavidin beads (Miltenyi Biotec). 5. MACS LD column (Miltenyi Biotec). 6. Magnet and magnet holders (Miltenyi Biotec). 7. 15 and 50 mL Falcon tubes. 8. Malassez counting chamber. 9. Antibodies cocktail to verify DC enrichment (see Table 1). 10. V-bottom 96 well plates. 11. 1.4 mL U-bottom micronic tubes. 12. Flow cytometers equipped with lasers and emission filters suitable for the analysis of cells stained with the dyes listed in the antibody panel (see Table 1). 13. FlowJo software for flow cytometry data analysis. 2.4 Positive Selection of DCs
1. Anti-CD11c biotin antibody. 2. Streptavidin beads (Miltenyi Biotec). 3. Pan DC Microbeads kit (Miltenyi Biotec). 4. MACS buffer. 5. MACS LS column (Miltenyi Biotec). 6. Magnet and magnet holders (Miltenyi Biotec). 7. Complete RPMI medium. 8. 15 mL Falcon tubes. 9. Malassez counting chamber. 10. Antibodies cocktail to verify DC enrichment (see Table 1). 11. V bottom 96-well plates. 12. 1.4 mL U-bottom micronic tubes. 13. Flow cytometers equipped with lasers and emission filters suitable for the analysis of cells stained with the dyes listed in the antibody panel (see Table 1). 14. FlowJo software for flow cytometry data analysis.
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Methods
3.1 Implantation of B16-Flt3L Tumors in Mice
1. Culture B16-Flt3L cells in complete RPMI medium in T75 culture flask. 2. When cells reach 70–80% confluence, remove the medium, wash with 10 mL PBS 1×. 3. Add 5 mL of Trypsin for 1 min at 37 °C to detach the cells. 4. Add 5 mL of complete RPMI and transfer the cells to falcon 15 mL tube. 5. Centrifuge at 300 g for 5 min at room temperature. 6. Resuspend the cell pellet in 10 mL of PBS 1×. 7. Count the cells using a Malassez counting chamber (see Note 1). 8. Centrifuge at the cells at 300 g for 5 min at room temperature. 9. Resuspend cells at concentration of 2·106 cells/mL in PBS 1×. 10. Inject subcutaneously 250 μL (5·105) of cells in each flank of the mice with a 1 mL syringe with a 26G needle (see Note 2). 11. Start measuring the tumor volume 7 days after the injection with a caliper and euthanize the mice (using methods approved by your institutional animal care and use committee) when the total tumor volume reaches 1500 mm3 (see Note 3).
3.2 Preparation of Single-Cell Suspensions of Splenocytes
1. Harvest the spleen from the mouse into 2 mL of cold complete RPMI medium (see Note 4). 2. Section the spleen with scissors in two to three large pieces. 3. Grind spleen pieces with syringe plunger and filter through a 70 μm cell strainer into 50 mL Falcon tube. 4. Wash the cell strainer with 10 mL of PBS 1×. 5. Centrifuge cells at 300 g for 5 min at room temperature. 6. Resuspend the cell pellet with 1 mL of RBC lysis buffer and incubate for 5 min at room temperature (see Note 5). 7. After the RBC lysis add to cells 10 mL of PBS 1×. 8. Centrifuge cells at 300 g for 5 min at room temperature. 9. Resuspend the cell pellet in 3 mL of MACS buffer and count the cells using a Malassez counting chamber (see Table 3). 10. Collect 5·105 cells to verify the DC amplification in vivo by flow cytometry and keep the rest of the cells for the next step. 11. To verify DCs amplification, resuspend 5·105 splenocytes in 100 μL of MACS buffer and place them in a V-bottom 96-well plate (see Note 6).
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Table 3 Cell count at the different steps of the protocols Step 1 cell number (106)
Step 2 cell number (106)
Step 3 cell number (106)
B16-FLT3L
Protocol
_
Protocol A Protocol B
59 52 48
5 4 3
1 0.52 0.64
+
Protocol A
205 218 167 200 135
134 113 78 112 61
16 16 38 37 39
Protocol B
Each line represents one mouse
12. Incubate the cells with 2.5 μg/mL of FcR Block for 15 min at 4 °C. 13. Wash cells by adding to the wells 100 μL of MACS buffer and spin the plate at 300 g for 5 min at 4 °C. 14. Remove the supernatants by flipping the plate. 15. Stain the cells using in 100 μL of MACS buffer containing the Ab cocktail described in Table 1 for 15 min at 4 °C in the dark. 16. Wash cells by adding to each well 100 μL of MACS buffer and spin the plate at 300 g for 5 min at 4 °C. 17. Remove the supernatants by flipping the plate cautiously. 18. Resuspend cells in 200 μL of MACS buffer and transfer them in U-bottom micronic tubes. 19. Acquire sample on a flow cytometer equipped with lasers and emission filters suitable for the analysis of cells stained with the dyes listed in the antibody panel and analyze the data using FlowJo software (see Fig. 2 and see Note 7). 3.3 Depletion of T cells, B cells, and Macrophages
1. Adjust the remaining cell concentration of splenocytes at 108 cells/mL in MACS buffer in a 50 mL Falcon tube. 2. Incubate cells with biotinylated anti-TCRβ, anti-CD19, and anti-F4/80 Abs (see Table 2) for 20 min at 4 °C. 3. Wash cells by adding 20 mL MACS buffer and centrifuge for 5 min at 300 g at 4 °C. 4. Resuspend the pellet in 950 μL of MACS buffer per 108 cells. 5. Add 50 μL of anti-Streptavidin beads per 108 cells. 6. Incubate 20 min at room temperature. 7. Wash cells by adding 20 mL of MACS buffer and centrifuge for 5 min at 300 g at 4 °C.
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8. Resuspend the cell pellet with 1 mL of MACS buffer. 9. Place the LD column on the magnet and a 15 mL Falcon collecting tube under the column. 10. Rinse the column with 2 mL of MACS buffer. 11. Add the cell suspension onto the column (see Note 8). 12. Collect the flow through containing unlabeled cells. 13. Wash twice the column by adding 1 mL of MACS buffer and collect the flow through (combined with the cells collected in step 12). 14. Count the collected cells using a Malassez counting chamber (see Table 3). 15. Collect 5·105 cells to verify the enrichment of DCs by flow cytometry and proceed to the next step with the remaining cells. 16. To verify DCs enrichment after depletion of T cells, B cells, and macrophages, stain the 5·105 cells with the 100 μL of Ab cocktail described in Table 1 for 15 min at 4 °C in the dark in a 96-well V-bottom plate. 17. Wash the cells by adding to the wells 100 μL of MACS buffer and spin the plate at 300 g for 5 min at 4 °C. 18. Remove the supernatants by flipping the plate cautiously. 19. Resuspend cells in 200 μL of MACS buffer and transfer them in U-bottom micronic tubes. 20. Acquire samples on a flow cytometer equipped with lasers and emission filters suitable for the analysis of cells stained with the dyes listed in the antibody panel and analyze the data using FlowJo software (see Fig. 3 and see Note 9). 3.4 Positive Selection of DC Cells
1. Adjust the cell concentration of the enriched cells at 108 cells/ mL in MACS buffer in a 15 mL Falcon tube.
3.4.1 Protocol A (Positive Selection of CD11c+ Cells)
2. Incubate cells with 2.5 μg/mL of biotinylated anti-CD11c antibody for 20 min at 4 °C. 3. Wash cells by adding 10 mL of MACS buffer and centrifuge for 5 min at 300 g at 4 °C. 4. Resuspend the cell pellet in 950 μL of MACS buffer per 108cells. 5. Add 50 μL of anti-Streptavidin beads per 108 cells. 6. Incubate 20 min at room temperature. 7. Wash cells by adding 10 mL of MACS buffer and centrifuge for 5 min at 300 g. 8. Resuspend the cell pellet in 3 mL of MACS buffer. 9. Proceed to magnetic positive isolation.
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Fig. 3 Analysis of splenic DC subsets after two purification protocols. DCs were isolated from splenocytes isolated from B16-Flt3 injected mice. (a) Frequencies of pDC, total cDC, or cDC1 and cDC2 were determined at each step of the procedure by flow cytometry. Live CD45+ cells were gated, and doublets were excluded. pDCs were identified as B220+ SiglecH+, and cDCs were gated on B220- cells and identified as MHC-IIhigh, CD11c+, cDC1 as CD8α + CD11b-, and cDC2 as CD8α- CD11b+ by flow cytometry. (b) Frequencies of pDCs, total cDCs, the remaining contaminants as well as of (c) of cDC1 and cDC2 among CD45+ cells obtained at the final step of each protocol are presented. Data are presented as mean +/- SD 3.4.2 Protocol B (Positive Selection of CD11c+ mPDCA1+ Cells)
1. Resuspend the cells in 400 μL of MACS buffer per 108 cells. 2. Incubate cells with 100 μL of Pan DC microbeads per 108 cells for 15 min at 4 °C. 3. Wash cells by adding 1–2 mL of MACS buffer per 107 cells and centrifuge for 5 min at 300 g at 4 °C. 4. Resuspend the cell pellet in 500 μL of buffer per 108 cells. 5. Proceed to magnetic positive isolation.
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1. Place the LS column on the magnet and a collecting 15 mL Falcon tube under the column. 2. Rinse the column by adding 2 mL of MACS buffer. 3. Add the cell suspension onto the column. 4. Wash twice the column by adding 3 mL of MACS buffer and collect the flow through. 5. Remove the column from the magnet and place it on a 15 mL Flacon collecting tube. 6. Add 5 mL of MACS buffer onto the column and flush out the labeled cells using the plunger to collect DCs. 7. Count the collected cells using a Malassez counting chamber (see Table 3). 8. Collect 5·105 cells to verify the purity of DCs by flow cytometry and proceed to functional assays with the remaining cells (see Note 10).
3.4.4 Verification of Cell Purity by Flow Cytometry
1. Place the 5·105 collected cells for flow cytometry into V bottom 96-well plate. 2. Centrifuge the plate at 300 g for 5 min at 4 °C. 3. Resuspend the cell pellets in 100 μL of antibodies cocktail prepared in MACS buffer (see Table 1). 4. Incubate 15 min at 4 °C and protect from light. 5. Wash cells by adding 100 μL MACS buffer and centrifuge the plate at 300 g for 5 min at 4 °C. 6. Remove the supernatants by flipping the plate cautiously. 7. Resuspend cells in 200 μL of MACS buffer and transfer them into U-bottom micronic tubes. 8. Run samples on a flow cytometer equipped with lasers and emission filters suitable for the analysis of cells stained with the dyes listed in the antibody panel and analyze the data using FlowJo software (see Fig. 3 and see Notes 11 and 12).
4
Notes 1. In one T75 flask that is 70–80% confluent one can recover 5–10·106 of B16-FLT3L cells. 2. Injection B16-FLT3L on both flanks increases the amount of systemic Flt3L and thus increases the yield of DCs. 3. To measure the tumor volume, apply the following formula: Volume in mm3 = ½ (Length (mm) × Width (mm)2).
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Commonly the total tumor (including both tumors) volume reach 1500 mm3 to 15–20 days after injection. 4. The injection of B16-Flt3L cells induces a splenomegaly in mice. The cellularity of the spleen goes from 53 ± 5 in million cells in control mice to 185 ± 26 million cells in mice implanted with B16-Flt3L. 5. Make sure to respect the timing of the RBC lysis, since increasing the time of RBC lysis can affect the final cell viability. When working with multiple spleens, you can adapt the volume of RBC lysis buffer to the number of spleens as follows: 1 mL RBC lysis buffer/spleen. 6. Transferring cells into 96-well plates allows their washing and staining in smaller volumes and thus using less Ab for the staining. V-bottom 96-well plates allow a better visualization of cell pellets and minimizes cell loss during washing procedures. 7. The expansion induced by B16-Flt3L implantation in mice results in a 5.5-fold increase of pDCs frequency (from 0.7 ± 0.5% to 3.9 ± 0.8% of total splenocytes) and a 12.8fold increase in total cDCs frequency (from 1.6 ± 0.1% to 20.5 ± 1.9% of splenocytes). The relative frequencies of cDC1 and cDC2 among total cDCs is perturbed by the in vivo amplification procedures and increases particularly cDC1 representation (from 23.9 ± 4% to 37.5 ± 3% of total splenocytes). Upon amplification DCs constitute ~25% of total splenocytes. 8. It is recommended to not exceed 2·108 cells on the column since it can lead to inefficient depletion and higher contamination by unwanted cells. 9. After the depletion of T cells, B cells, and macrophages, DCs represent about 45% of total cells. This step allows a pre-enrichment of DCs that increases the final purity of DCs after positive selection. 10. Both purification protocols lead to a mixture of DC subsets, which can be further purified by cell sorting, if individual cells need to be functionally assayed. 11. CD11c positive selection (protocol A) leads to a cDCs purity of 87.5 ± 0.7%. However, the yield of pDCs obtained by this approach is low with pDCs representing 4.3 ± 0.9% of the selected cells. This could be explained by the low levels of CD11c expression on pDCs. Using a Pan-DC kit (protocol B), pDC represent 9.7 ± 4.3% and cDCs represent 71.5 ± 4.8% of isolated cells. Thus, this second protocol allows a better enrichment of pDCs.
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12. Contaminants are present in DC preparations obtained using both protocols (7 ± 0.04% with protocol A and 17.1 ± 3.5% with protocol B). 25.5 ± 8.8% of these contaminants are NK cells. Therefore, adding an anti-NK1.1 biotinylated Ab at the step 2 described in Subheading 3.3 would lead to a better enrichment of DC populations.
Acknowledgments The authors would like to thank Vincent Pitard and Atika Zouine from the flow cytometry core at the University of Bordeaux, and Benoit Rousseau and Julien Izotte from the animal facility core of the University of Bordeaux for their assistance in the establishment of these experimental procedures. Figures were created with Biorender.com. The work in our laboratory is supported by research grant from the IdEx junior chair program from the University of Bordeaux, the Agence Nationale de la Recherche (ANR JCJC DOMINOS), the Institut National du Cancer (INCa-PLBIO22124) and the SIRIC Brio. References 1. Anderson DA, 3rd, Murphy KM, Briseno CG. Development, diversity, and function of dendritic cells in mouse and human. Cold Spring Harb Perspect Biol. 2018;10 (11) a028613 2. Cella M, Jarrossay D, Facchetti F, Alebardi O, Nakajima H, Lanzavecchia A et al (1999) Plasmacytoid monocytes migrate to inflamed lymph nodes and produce large amounts of type I interferon. Nat Med 5(8):919–923 3. Guilliams M, Ginhoux F, Jakubzick C, Naik SH, Onai N, Schraml BU et al (2014) Dendritic cells, monocytes and macrophages: a unified nomenclature based on ontogeny. Nat Rev Immunol 14(8):571–578 4. Vremec D, Pooley J, Hochrein H, Wu L, Shortman K (2000) CD4 and CD8 expression by dendritic cell subtypes in mouse thymus and spleen. J Immunol 164(6):2978–2986 5. Vremec D, Zorbas M, Scollay R, Saunders DJ, Ardavin CF, Wu L et al (1992) The surface phenotype of dendritic cells purified from mouse thymus and spleen: investigation of the CD8 expression by a subpopulation of dendritic cells. J Exp Med 176(1):47–58 6. Blasius AL, Giurisato E, Cella M, Schreiber RD, Shaw AS, Colonna M (2006) Bone marrow stromal cell antigen 2 is a specific marker of type I IFN-producing cells in the naive mouse, but a promiscuous cell surface antigen
following IFN stimulation. J Immunol 177(5):3260–3265 7. Zhang J, Raper A, Sugita N, Hingorani R, Salio M, Palmowski MJ et al (2006) Characterization of Siglec-H as a novel endocytic receptor expressed on murine plasmacytoid dendritic cell precursors. Blood 107(9): 3600–3608 8. Nakano H, Yanagita M, Gunn MD (2001) CD11c(+)B220(+)Gr-1(+) cells in mouse lymph nodes and spleen display characteristics of plasmacytoid dendritic cells. J Exp Med 194(8):1171–1178 9. Merad M, Sathe P, Helft J, Miller J, Mortha A (2013) The dendritic cell lineage: ontogeny and function of dendritic cells and their subsets in the steady state and the inflamed setting. Annu Rev Immunol 31:563–604 10. Shortman K, Heath WR (2010) The CD8+ dendritic cell subset. Immunol Rev 234(1): 18–31 11. Reizis B (2019) Plasmacytoid dendritic cells: development, regulation, and function. Immunity 50(1):37–50 12. Mashayekhi M, Sandau MM, Dunay IR, Frickel EM, Khan A, Goldszmid RS et al (2011) CD8alpha(+) dendritic cells are the critical source of interleukin-12 that controls acute
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infection by Toxoplasma gondii tachyzoites. Immunity 35(2):249–259 13. Reis e Sousa C, Hieny S, Scharton-Kersten T, Jankovic D, Charest H, Germain RN et al (1997) In vivo microbial stimulation induces rapid CD40 ligand-independent production of interleukin 12 by dendritic cells and their redistribution to T cell areas. J Exp Med 186(11):1819–1829 14. Hildner K, Edelson BT, Purtha WE, Diamond M, Matsushita H, Kohyama M et al (2008) Batf3 deficiency reveals a critical role for CD8alpha+ dendritic cells in cytotoxic T cell immunity. Science 322(5904):1097–1100 15. den Haan JM, Lehar SM, Bevan MJ (2000) CD8(+) but not CD8(-) dendritic cells crossprime cytotoxic T cells in vivo. J Exp Med 192(12):1685–1696 16. Pooley JL, Heath WR, Shortman K (2001) Cutting edge: intravenous soluble antigen is presented to CD4 T cells by CD8- dendritic cells, but cross-presented to CD8 T cells by CD8+ dendritic cells. J Immunol 166(9): 5327–5330 17. Persson EK, Uronen-Hansson H, Semmrich M, Rivollier A, Hagerbrand K, Marsal J et al (2013) IRF4 transcription-factordependent CD103(+)CD11b(+) dendritic cells drive mucosal T helper 17 cell differentiation. Immunity 38(5):958–969 18. Plantinga M, Guilliams M, Vanheerswynghels M, Deswarte K, BrancoMadeira F, Toussaint W et al (2013) Conventional and monocyte-derived CD11b(+) dendritic cells initiate and maintain T helper 2 cellmediated immunity to house dust mite allergen. Immunity 38(2):322–335 19. Schlitzer A, McGovern N, Teo P, Zelante T, Atarashi K, Low D et al (2013) IRF4 transcription factor-dependent CD11b+ dendritic cells in human and mouse control mucosal IL-17 cytokine responses. Immunity 38(5):970–983 20. Naik SH, Metcalf D, van Nieuwenhuijze A, Wicks I, Wu L, O’Keeffe M et al (2006) Intrasplenic steady-state dendritic cell precursors that are distinct from monocytes. Nat Immunol 7(6):663–671 21. Helft J, Bottcher J, Chakravarty P, Zelenay S, Huotari J, Schraml BU et al (2015) GM-CSF mouse bone marrow cultures comprise a heterogeneous population of CD11c(+)MHCII (+) macrophages and dendritic cells. Immunity 42(6):1197–1211
22. Naik SH, O’Keeffe M, Proietto A, Shortman HH, Wu L (2010) CD8+, CD8-, and plasmacytoid dendritic cell generation in vitro using flt3 ligand. Methods Mol Biol 595:167–176 23. Naik SH, Proietto AI, Wilson NS, Dakic A, Schnorrer P, Fuchsberger M et al (2005) Cutting edge: generation of splenic CD8+ and CD8- dendritic cell equivalents in Fms-like tyrosine kinase 3 ligand bone marrow cultures. J Immunol 174(11):6592–6597 24. Naik SH, Sathe P, Park HY, Metcalf D, Proietto AI, Dakic A et al (2007) Development of plasmacytoid and conventional dendritic cell subtypes from single precursor cells derived in vitro and in vivo. Nat Immunol 8(11): 1217–1226 25. Kirkling ME, Cytlak U, Lau CM, Lewis KL, Resteu A, Khodadadi-Jamayran A et al (2018) Notch signaling facilitates in vitro generation of cross-presenting classical dendritic cells. Cell Rep 23(12):3658–72 e6 26. McKenna HJ, Stocking KL, Miller RE, Brasel K, De Smedt T, Maraskovsky E et al (2000) Mice lacking flt3 ligand have deficient hematopoiesis affecting hematopoietic progenitor cells, dendritic cells, and natural killer cells. Blood 95(11):3489–3497 27. Karsunky H, Merad M, Cozzio A, Weissman IL, Manz MG (2003) Flt3 ligand regulates dendritic cell development from Flt3+ lymphoid and myeloid-committed progenitors to Flt3+ dendritic cells in vivo. J Exp Med 198(2): 305–313 28. Maraskovsky E, Brasel K, Teepe M, Roux ER, Lyman SD, Shortman K et al (1996) Dramatic increase in the numbers of functionally mature dendritic cells in Flt3 ligand-treated mice: multiple dendritic cell subpopulations identified. J Exp Med 184(5):1953–1962 29. Mach N, Gillessen S, Wilson SB, Sheehan C, Mihm M, Dranoff G (2000) Differences in dendritic cells stimulated in vivo by tumors engineered to secrete granulocyte-macrophage colony-stimulating factor or Flt3-ligand. Cancer Res 60(12):3239–3246 30. Salmon H, Idoyaga J, Rahman A, Leboeuf M, Remark R, Jordan S et al (2016) Expansion and activation of CD103(+) dendritic cell progenitors at the tumor site enhances tumor responses to therapeutic PD-L1 and BRAF inhibition. Immunity 44(4):924–938
Chapter 14 Isolation and Identification of Dendritic Cell Subsets from Human and Mouse Tumors Yamila Rocca, Aure´lien Voissie`re, Jenny Valladeau-Guilemond, and Nathalie Bendriss-Vermare Abstract Dendritic cells (DCs) are professional antigen-presenting cells (APCs) that have the ability to orchestrate adaptive and innate immune responses by antigen phagocytosis and T cell activation across different inflammatory settings such as tumor development. As specific DC identity and how these cells interact with their neighbors is still not fully understood, it remains a challenge to unravel DC heterogeneity, particularly in human cancers. In this chapter, we describe a protocol to isolate and characterize tumorinfiltrating DCs. Key words Dendritic cells, DC subsets, DC isolation, DC identification, Human, Mouse, Tumors
1
Introduction Dendritic cells (DCs) are professional antigen-presenting cells (APCs) that, despite of usually representing a small fraction of the tumor microenvironment, play a central role in the initiation and the control of antitumor immune responses [1]. It has been demonstrated that DCs actively participate in the elimination of immunogenic tumors [2] and that their infiltration can predict response to anti-PD-1 immunotherapy [3]. In the past few years, the knowledge on DC diversity was highly increased identifying several subsets in blood and tissues that usually share phenotypic and functional overlapping features. The DC network is comprised of a heterogeneous population of cells, including conventional DCs (cDC1 and cDC2), plasmacytoid DCs (pDC), and monocyte-like inflammatory DC s(MoDC) [4]. In addition, Langerhans cells represent another DC type of peripheral tissues presenting different
Yamila Rocca and Aure´lien Voissie`re contributed equally with all other contributors. Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_14, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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specificities according to their localization. In human, cDC1 cells are identified as CD141+XCR1+CLEC9A+ and are specialized in antigen cross-presentation to CD8 T cells and type III interferons (IFNs) production. cDC2 cells are defined as CD11c+CD11b+C D1c+SIRPα+ and are capable of activating both CD4+ and CD8+ T cells. pDC cells are CD11c-BDCA2+CD123+ and are specialized in type I and III IFN production in response to viral infections. MoDCs are determined by their resemblance with macrophages as they may express one or more of the markers CD88, CD14, and C D163 and are able to recruit and activate different immune subsets. Langerhans cells are identified as CD11c+CD207+Epcam+ and have the ability to respond to intracellular pathogens and viruses and activate CD8+ T cells [5, 6]. In mice, several CD11c+ DC types can also be identified including CD103+CD8α+XCR1+ cDC1 and CD11b+SIRPα+EpCAMcDC2, CD11b+SIRPα+EpCAM+ Langerhans cells, CD11b-Ly6c+SiglecH+ pDCs, and CD64+CD11b+Ly6C+ MoDCs [7]. The current protocols were designed for the isolation and/or identification of DC types from both human and murine tumor tissues consisting in sequential steps of tissue enzymatic digestion, DC enrichment, and FACS cell sorting/analysis.
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Materials
2.1 Human Tumor Processing
1. Sterile disposable scalpel.
2.1.1 Mechanical and Enzymatic Tumor Digestion
3. Disposable 0.22 μm filter.
2. Sterile polystyrene pliers. 4. Petri dishes for tissue culture 60 mm. 5. Magnetic stirrers. 6. Magnetic agitator. 7. Polypropylene sterile jar. 8. 50 mL polypropylene tubes. 9. RPMI 1640 GlutaMAX medium. 10. Penicillin-streptomycin. 11. Fetal bovine serum (FBS). 12. DNase type I. 13. Collagenase type IV (see Note 1). 14. MACS SmartStrainer 70 μm. 15. MACS SmartStrainer 30 μm. 16. Digestion medium: RPMI 20% FBS, 1% penicillinstreptomycin, 200 units/mL of Collagenase IV, 25 μg/mL of DNase I. 17. Incubator at 37 °C, 5% CO2.
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1. EasySep Magnet (Stem cell). 2. EasySep Human PanDC Pre-Enrichment Kit (Stem Cell). 3. PBS 10X. 4. Sterile water. 5. EDTA. 6. 5 mL polystyrene round-bottom tubes. 7. 15 mL polypropylene tubes. 8. Enrichment medium: PBS1X, 2% FBS, 1 mM of EDTA.
2.1.3
Cell Sorting
1. FcR Blocking Reagent, human (Miltenyi). 2. Fc blocking solution: PBS1X and blocking reagent at 1:5 concentration. 3. Staining buffer: PBS1X, 2% FBS, 1 mM of EDTA, and BD Brilliant Stain Buffer (see Note 2). 4. Monoclonal antibodies (see Table 1). 5. Strainer 70 μm. 6. DAPI: stock solution at 10 μg/mL. 7. 5 mL polypropylene tubes. 8. Eppendorf 1.5 mL microtubes. 9. FACSAria Cell sorter.
Table 1 Antibodies used for cell sorting of human tumor DCs Name
Fluorochrome
Clone
Company
Suggested dilution
Mouse anti-CD123
BV605
7G3
BD
1:50
Mouse anti-HLA-DR
BV510
L243
Biolegend
1:100
Mouse anti-CD11c
PerCP Cy5.5
BU15
Biolegend
1:50
Mouse anti-CD45
FITC
J33
Beckman Coulter
1:50
Mouse anti-CD1c
PE-Cy7
L161
Biolegend
1:100
Mouse anti-CD3
PE-CF594
UCHT1
BD
1:100
Mouse anti-CD14
PE-CF594
MΦP9
BD
1:100
Mouse anti-CD15
PE-CF594
MC480
BD
1:100
Mouse anti-CD19
PE-CF594
HIB19
BD
1:100
Mouse anti-CD56
PE-CF594
NCAM16.2
BD
1:100
Mouse anti-CLEC9A
PE
8F9
Miltenyi
1:50
Mouse anti-CD207
APC-Vio770
MB22-9F5
Miltenyi
1:50
Mouse anti-BDCA3
APC
AD5-14H12
Miltenyi
1:50
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1. Surgical scissors and forceps.
2.2 Mouse Tumor Processing
2. Scalpels. 3. 10 cm Petri dishes. 4. 5 mL Syringes. 5. Magnetic stirrers. 6. Magnetic agitator. 7. 15–50 mL polypropylene tubes. 8. 1.20 μm filter 9. 70 and 30 μm cell strainers. 10. 96-well plates 11. Incubator 37 °C, 5% CO2. 12. Monoclonal antibodies (see Table 2). 13. Flow cytometer and FlowJo Software. 14. FACSAria Cell sorter. 15. Medium: RPMI 1640, 10% FBS, 100 IU penicillin, 10 μg/mL streptomycin.
Table 2 Antibodies used for mouse DC subset identification and sorting Antigen
Fluorochrome
Clone
Supplier
Catalog
Dilution
CD16/32
–
–
Biolegend
101302
1:100
MHC-II (I-A/I-E)
BV711
M5/114.15.2
Biolegend
107631
1:200
CD11b
BV650
M1/70
BD Pharmigen
563402
1:100
Zombie Aqua
AF430
–
Biolegend
148216
1:400
XCR1
BV421
ZET
Biolegend
148216
1:200
EpCAM
PercP-Cy 5.5
G8.8
Biolegend
118220
1:200
CD172a (Sirpα)
A488
P84
Biolegend
144024
1:50
CD11c
PE-Cy7
N418
Biolegend
117318
1:50
CD49b
PE-Dazzle 594
DX5
Biolegend
108924
1:50
CD3e
PE-Dazzle 594
145-2C11
Biolegend
100348
1:200
CD19
PE-Dazzle 594
6D5
Biolegend
115554
1:200
CD64
PE
X54–5/7.1
Biolegend
139304
1:50
Ly6C
APC-Cy7
AL-21
BD Pharmigen
560596
1:50
CD45
AF700
30-F11
Biolegend
103128
1:400
SiglecH
APC
551
Biolegend
129612
1:50
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16. Digestion cocktail: Medium, 1 mg/mL Collagenase I, 0.02 mg/mL DNAse I. 17. 1X PBS. 18. FACS buffer: 1X PBS, 2% FBS, 2 mM EDTA. 19. Red cell lysis solution: BD Pharmlyse. 20. Fixation solution: 2% formaldehyde.
3
Methods
3.1 Human Tumor Processing
3.1.1 Mechanical and Enzymatic Tissue Digestion
The use of human samples must be approved by an institutional ethics committee. Carry out all procedures at room temperature (RT), unless otherwise specified. Washing steps are performed by centrifugation at 350 × g for 10 min at 4 °C. 1. Immediately on arrival in the laboratory, transfer the tumor to a precisely pre-weighed vial. 2. To allow for the accurate determination of cell number per gram of tissue biopsy, weigh the tumor. 3. Place the tumor on the petri dish. Add RPMI medium (1 mL for 500 mg of tissue). 4. Use a scalpel to chop the tissue into small pieces of 1 or 2 mm3. 5. Aspirate the medium into a 15 mL tube and centrifuge it for 10 min at 350 × g at RT. Collect the supernatant and filter it with the 0.22 μm filter. This supernatant can be frozen at -80 °C for future experiments (see Note 3). Resuspend the cell pellet and add it to the petri dish. 6. Add the digestion medium (10 mL/g tissue) and transfer it together with tumor fragments into the digestion jar. 7. Put the magnetic stirrers. 8. Incubate for 30 min under constant agitation in an incubator at 37 °C (see Note 4). 9. Add 10 mL of RPMI 20% FBS at RT (see Note 5). 10. Pass the single-cell suspension through a 70 μm cell strainer into a 50 mL Falcon tube. Wash the filter three times with 10 mL of RPMI 20% FBS (see Note 6). 11. Centrifuge for 10 min at 350 × g at RT, discard the supernatant, and resuspend the pellet in 20 mL of RPMI 20% FBS. 12. Pass the single-cell suspension through a 30 μm cell strainer into a 50 mL Falcon tube. Wash the filter three times with 10 mL of RPMI 20% FBS. 13. Centrifuge for 10 min at 350 × g at RT, resuspend the cells in 5–10 mL of RPMI 20% FBS and determine cell number with Trypan Blue and Turk solution (see Note 7).
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3.1.2 Dendritic Cell Enrichment (See Note 8)
1. Prepare the cell suspension at 5 × 107 cells/mL in the polystyrene round-bottom tubes (see Notes 9 and 10). 2. Block Fc receptors by incubating with Fc block (30 μL/mL of sample). 3. Add the Component A of the Pan-DC enrichment kit (50 μL/mL of sample). 4. Add the Component B of the Pan-DC enrichment kit (50 μL/mL of sample). 5. Incubate for 30 min under agitation at RT (see Note 11). 6. Add pre-vortexed magnetic particles (100 μL/mL of sample). 7. Incubate for 10 min under agitation at RT. 8. Add enrichment medium up to 2.5 mL/tube. 9. Place the tube into the EasySep magnet and incubate for 5 min at RT. 10. Carefully invert the magnet together with the tube discharging the enriched cell suspension in a new 15 mL Falcon polypropylene tube (see Note 12).
3.1.3 Cell Staining and Dendritic Cell Sorting
1. Resuspend the DC-enriched fraction in Fc blocking solution (10 × 106 cells/100 μL) (see Note 13). 2. Incubate for 10 min at 4 °C. 3. Centrifuge and resuspend the cells in staining buffer containing antibodies (see Table 1) at 5 × 106 cells/100 μL. 4. Incubate 30 min at 4 °C (see Note 14). 5. Wash the cells by doubling the staining volume with cold staining buffer. Spin the tube at 400 × g, 6 min at 4 °C. Remove the supernatant and resuspend the cells in staining buffer containing DAPI (1 μg/mL) at 10 × 106 cells/mL. 6. Pass the single-cell suspension through a 70 μm cell strainer into a 50 mL Falcon tube. Transfer the single-cell suspension to polypropylene tubes (see Note 15). 7. Prepare 4 Eppendorf microtubes containing 1 mL of RPMI 20% FBS medium to collect the sorted DCs. 8. Perform the cell sorting of different DC subsets according to phenotype description (see Fig. 1 and Note 16).
3.2 Mouse Tumor Processing 3.2.1 Mouse Mammary Tumor Processing
1. Euthanize mice according to appropriate ethical guidelines and immediately remove the tumor from mouse and place it in petri dish containing 1 mL of RPMI for 500 mg of tissue (see Note 17). 2. Using scalpel, cut tumor into 1–2 mm3 fragments.
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Fig. 1 Gating strategy for FACS sorting of DC subsets from human tumors. Identification of four DC subsets among viable CD45+ HLA-DR+ Lineage- (CD3/CD14/CD15/CD19/CD56) cells: cDC1 (CD11c+ BDCA1BDCA3hi), cDC2 (CD11c+ BDCA1+ BDCA3-/low CD207-), pDC (CD11c- CD123+), and Langerhans cells (CD11c+ BDCA1+ BDCA3-/low CD207hi).
3. Aspirate the medium into a 2 mL tube and centrifuge it for 10 min at 350 × g at RT. Collect the supernatant and filter it with the 0.45 μm filter. This supernatant can be frozen at -80 °C for future experiments (see Note 3). Resuspend the cell pellet and add it to the petri dish. 4. Add 5 mL of digestion cocktail (see Notes 18 and 19) and transfer it together with tumor fragments into the digestion jar. 5. Put the magnetic stirrers. 6. Transfer to an incubator at 37 °C for 30–40 min under stirring (see Note 20). 7. Add 10 mL of medium to stop the enzymatic reaction. 8. Pass the single-cell suspension through superposed 70 and 30 μm cell strainers. 9. Crush undigested fragments using 5 mL syringe plunger. 10. Rinse filters with 10 mL of medium. 11. Centrifuge at 400 × g for 5 min. 12. Resuspend in 10 mL of 1X Pharmlyse for 5 min to lyse red blood cells. 13. Add 30 mL of 1X PBS to stop the reaction. 14. Wash the cell twice in 1X PBS. 15. Resuspend cells in complete medium. 16. Count live cells using blue trypan (see Note 7). 17. Centrifuge at 400 × g for 5 min and resuspend the pellet at 4 × 106 cells in 100 μL of FACS buffer. 3.2.2 Cell Preparation for FACS Analysis of Murine DCs
Washing steps were performed by centrifugation at 400 × g for 3 min at 4 °C. 1. Centrifuge the cells at 400 × g for 3 min. 2. Resuspend the cell pellet in Zombie Aqua/Fc Block solution (in 1X PBS) and incubate for 20 min at 4 °C in the dark.
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3. Centrifuge the cells and resuspend cell pellet with surface antibody mix (see Table 2 and Notes 21 and 22) and incubate 30 min at 4 °C in the dark. 4. Wash the cells twice in FACS buffer. (a) Option: Fix cells with 2% formaldehyde for 20 min at 4 °C in the dark (see Note 23). 5. Acquire the samples on a flow cytometer or sort DC subsets using FACSAria Cell sorter according to phenotype description (see Fig. 2 and Table 3).
Fig. 2 Gating strategy commonly used to identify DC subsets in a murine spontaneous mammary tumor. (a) By successive gating on live cells (Zombie Aqua negative), CD45+ and LIN-CD64- cells, DC can be identified. Subsequently gating on CD11c+, I-A/I-E+ cells, conventional DCs can be identified, which are further split in XCR1+Sirpα- cDC1 (Red) and heterogeneous XCR1-SIRPα+ DCs. Finally, among CD11b+ cells, EpCAM is used to discriminate cDC2 (EpCAM-, Yellow) from LC (EpCAM+, Green). pDCs are identified by successive gating on I-A/I-E+/- CD11b- cells, Ly6C+ SiglecH+ cells (Blue). (b) Monocyte-derived DCs (Mo-DC, Orange) are identified by successive gating on live cells (Zombie Aqua negative), CD45+ LIN-cells, CD11c+I-A/I-E+ cells, CD64+ CD11b+ cells and discriminated from macrophages (Purple) by selecting Ly6C+ cells. LIN: CD3, CD19, CD49b
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Table 3 Expression patterns of surface antigens on murine DC subsets
cDC1
cDC2
pDC
Langerhans cells
Mo-DC
Macrophages
CD45
+
+
+
+
+
+
CD64
-
-
-
-
+
+
MHC Class II
+
+
Lo/-
+
+
+
CD11c
+
+
Lo/+
+
+
+
CD11b
-
+
-
+
+
+
XCR1
+
-
-
-
-
-
Sirpα/ CD172
-
+
+
+
+
+
Siglec H
-
-
+
-
-
-
Ly6C
-
-
+
-
+
-
EpCAM
-
-
-
+
-
-
4
Notes 1. In human settings, Collagenase IV is used instead of Collagenase I because of its lower antigen stripping. 2. EDTA minimizes adherence of cells to plastics by chelating Ca2+. 3. Several cytokines and chemokines can be quantified in supernatants of dissociated tumors by ELISA or similar methods. 4. Tumor digestion is performed in constant agitation to ameliorate efficiency. 5. The addition of complete medium, particularly of FBS stops the enzymatic digestion of tumor tissue. 6. Change the strainer if there are clogs. 7. Typical cell yield from a human biopsy ranges from 20 to 300 × 106 total cells. For murine mammary tumor, the average cell yield is 80 × 106 total live cells for an average tumor weight of 400 mg. 8. If there is a high representation of DC in tumor infiltrate, pre-enrichment step could be skipped. 9. Using polystyrene rather than polypropylene tubes favors the attachment of bead-coated cells to the tube wall.
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10. Determine how many polystyrene tubes are needed for optimum enrichment. For optimum efficacy of enrichment, a maximum starting concentration of 5 × 107 cells/mL is used. 11. Pre-DC Enrichment incubations are performed under constant agitation to avoid cellular aggregates. 12. For optimum blood DC enrichment, it is recommended to perform two steps of magnetic separation. Nevertheless, it is not recommended when working with tumor samples due to cell loss in the additional steps. 13. Addition of anti-CD16/CD32 minimizes background fluorescence by inhibiting non-specific binding of antibodies to FcG—receptors present on immune cells. 14. To avoid DC activation induced by manipulation, it is better to perform staining at 4 °C. 15. Using polypropylene tubes decreases the attachment of DCs to tube wall during staining or sorting. 16. Typical DC yield from a human tumor range from 1% to 50% of total CD45+ live cells with an average of 16% of DCs. In murine mammary tumors, all DC subsets represent 0.5–5% of tumor immune infiltrate (CD45+) with an average yield of 106 cDC1, 587 cDC2, 182 pDC, and 344 LC per mg of tumor tissue. One tumor should provide sufficient cells for multiparameter FACS analysis of DC subsets although not all subsets are always present. If subset purification is required, two to three tumors should be pooled but reagents should be adapted appropriately. Each volume mentioned in the present protocol is for only one tumor. 17. This protocol was optimized for the identification and isolation of murine DC subsets in mammary tumors, but it can be used for the identification of DC subsets in other mouse tumor models and tissues (spleen, lymph nodes, bone marrow. . .). 18. Enzymatic digestion of murine mammary tumors is more efficient using Collagenase I. 19. Adding FBS in digestion mix is essential to protect DC antigens allowing a more efficient identification of DC subsets. 20. Digestion time of tumor can be increased until the tissue will be fully digested (or up to 45 min). 21. Antigen expression for the identification of NK cells differs depending of mouse strains. Indeed, NK1.1 antigen is expressed in C57Bl/6 and FVB strains but not in Balb/c and 129Sv strains. CD49b antigen is expressed on NK cells in a majority of mouse strains.
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22. For murine analyses, we typically acquire 6 × 106 of total live cells to be able to visualize sufficient numbers of all DC subsets. 23. Fixed cells with formaldehyde 2% are stable 7 days and may not be acquired right after the staining.
Acknowledgments The authors would like to thank current and past members of the Christophe Caux laboratory who have made key contributions to the development and optimization of these procedures. Y.R. and A.V. were supported by grants from INCa (PLBIO17-187) and LABEX DEVweCAN (ANR-10-LABX-0061) of the University of Lyon, within the program “Investissements d’Avenir” organized by the French National Research Agency (ANR). References 1. Steinman RM (2012) Decisions about dendritic cells: past, present, and future. Annu Rev Immunol 30:1–22 2. Hildner K, Edelson B, Purtha W et al (2008) Batf3 deficiency reveals a critical role for CD8alpha+ dendritic cells incytotoxic T cell immunity. Science 322:1097–1100 3. Barry K, Hsu J, Broz M et al (2018) A natural killer-dendritic cell axis defines checkpoint therapy-responsive tumor microenvironments. Nat Med 24:1178–1191 4. Gerhard M, Bill R, Messemaker M et al (2020) Tumor-infiltrating dendritic cell states are
conserved across solid human cancers. J Exp Med 218:e20200264 5. Collin M, Bigley V (2018) Human dendritic cell subsets: an update. Immunology 154:3–20 6. Hubert M, Gobbini E, Couillault C et al (2020) IFN-III is selectively produced by cDC1 and predicts good clinical outcome in breast cancer. Sci Immunol 46:eaav3942 7. Anderson DA III, Dutertre CA, Ginhoux F, Murphy K (2020) Genetic models of human and mouse dendritic cell development and function. Nat Rev Immunol 21:101–115
Part V Functional Characterization of Dendritic Cells
Chapter 15 Optimized Nonviral Gene Disruption in Primary Murine and Human Myeloid Cells Emily C. Freund, Simone M. Haag, Benjamin Haley, and Aditya Murthy Abstract Genetically engineered myeloid cells such as monocytes, macrophages, and dendritic cells have broad applications in basic and translational research. Their central roles in innate and adaptive immunity make them attractive as putative therapeutic cell products. However, efficient gene editing of primary myeloid cells presents unique challenges owing to their sensitivity to foreign nucleic acids and poor editing efficiencies using current methodologies (Hornung et al., Science 314:994–997, 2006; Coch et al., PLoS One 8:e71057, 2013; Bartok and Hartmann, Immunity 53:54–77, 2020; Hartmann, Adv Immunol 133: 121–169, 2017; Bobadilla et al., Gene Ther 20:514–520, 2013; Schlee and Hartmann, Nat Rev Immunol 16:566–580, 2016; Leyva et al., BMC Biotechnol 11:13, 2011). This chapter describes nonviral CRISPRmediated gene knockout in primary human and murine monocytes as well as monocyte-derived or bone marrow-derived macrophages and dendritic cells. Electroporation-mediated delivery of recombinant Cas9 complexed with synthetic guide RNAs can be applied for population-level disruption of single or multiple gene targets. Key words Myeloid cells, Monocytes, Macrophages, Dendritic cells, Bone marrow, Human, Murine, Mouse, CRISPR, Cas9, RNP, Electroporation, Gene editing, Genetic engineering, Knockout, Innate immunity, Cell biology, Immunology
1
Introduction Genetic reprogramming of the immunomodulatory functions of monocytes, macrophages, and dendritic cells (DCs) has broad implications for treatment of infectious and chronic inflammatory diseases as well as oncology. For example, macrophages engineered to express a chimeric antigen receptor delivered by an adenovirus have recently been proposed as a therapeutic modality in cancer immunotherapy [1]. CRISPR-Cas9 technology involves targeting the Cas9 endonuclease to genomic regions of interest via guide RNAs (gRNAs) to induce site-specific double-stranded DNA
Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_15, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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breaks. Improper repair of these breaks leads to genomic alterations such as insertion-deletions (indels) and, consequently, gene disruption. This approach has significantly accelerated genetic engineering in cell biology. However, compared to the abundance of methodologies for genetic modification of lymphocytes such as T and natural killer (NK) cells, myeloid cell gene editing is poorly investigated [2–15]. Such difficulty for editing myeloid cells is likely due to their heightened responses to both viral infection and transfection with foreign genetic material [16–22]. As a result, current tools are limited to transformed cell lines (e.g., THP-1, U937, and RAW cells) and transgenic Cas9 knock-in mice, while practices for engineering primary human and murine myeloid cells are lacking [22–27]. In this chapter, we provide detailed protocols for nonviral gene disruption in primary non-granulocytic myeloid cells of human and murine origin. We focus on the delivery of Cas9-synthetic guide RNA ribonucleoprotein (RNP) complexes using defined electroporation conditions. This approach consistently generates high levels of gene knockout (>90%) in all tested cell types, and it permits multiple gene knockouts to be created within a single cell population. The ability to edit total bone marrow cells also allows for investigation of myeloid cell differentiation. We first detail guide RNA selection (protocol 2.3), isolation of human monocytes from peripheral blood (protocol 3.1), and isolation of murine monocytes from bone marrow and culture of murine bone marrow-derived macrophages (protocol 3.2). We then cover the generation of Cas9-RNPs (protocol 3.3) and subsequent electroporation of both human and murine cells (protocol 3.4). We describe protocols for post-editing differentiation of human and murine monocytes/ bone marrow into macrophages or dendritic cells (protocol 3.5, 3.6) as well as analysis of gene editing efficiency (protocol 3.7) (Figs. 1 and 2).
2
Materials Please prepare the materials as detailed in the following section. All solutions should be prepared with RNAse/DNAse free water, and reagents can be stored at room temperature unless indicated otherwise. Thaw frozen reagents on ice (unless indicated otherwise).
2.1 Human Monocyte Preps and Myeloid Cell Culturing
1. SepMate-50 tubes. 2. Phosphate-buffered saline (PBS). 3. Ammonium-chloride-potassium (ACK) lysing buffer. 4. 70 μm filter.
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Fig. 1 Schematic representation of Cas9-RNP workflow. (a) sgRNA(s) and recombinant Cas9 protein are combined to produce Cas9-RNPs. (b) Human monocytes, mouse bone-marrow or bone-marrow-derived macrophages are isolated. (c) Cas9-RNPs are delivered to cells by electroporation. (d, e) Cells are then cultured and knockout efficiency is assayed by flow cytometry
5. EasySep Human Monocyte Isolation Kit (Stem Cell Technologies cat# 19359). 6. Easy50 magnet (Stem Cell Technologies cat# 18002). 7. Tissue culture (TC)-treated 6-well plates. 8. Non-adherent 6-well plates. 9. Monocyte-derived dendritic cell (moDC) media: RPMI supplemented with 10% fetal bovine serum (FBS), 2 mM l-alanyl-lglutamine (GlutaMAX), 50 μM β-mercaptoethanol, 100 U/ mL penicillin, 100 μg/mL streptomycin, and cytokines GM-CSF 800 U/mL and IL-4 500 U/mL. 10. Monocyte-derived macrophage (moMac) media: DMEM high glucose supplemented with 10% FBS, 2 mM l-alanyl-l-glutamine (GlutaMAX), 100 U/mL penicillin, 100 μg/mL streptomycin, and cytokines M-CSF 100 ng/mL. 11. Tissue culture incubator.
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a 250K
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Fig. 2 Disruption of single and multiple genes in human monocyte-derived macrophages. (a) Representative flow cytometry plots show a gating strategy for using Cas9-RNPs loaded with non-targeting control (NTC) gRNA to determine B2M negative cells in each cell population. Monocyte-derived macrophages were further
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2.2 Mouse BMDM and BMDC Preps and Culturing
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1. PBS. 2. ACK lysing buffer. 3. 70 μm filter. 4. TC-treated 6-well plates. 5. Non-adherent 6-well plates. 6. Sterile forceps. 7. Scissors. 8. G18 needle. 9. Non-TC-treated petri dish. 10. Rubber policeman. 11. Bone marrow-derived dendritic cell (BMDC) media: RPMI supplemented with 10% FBS, 2 mM l-alanyl-l-glutamine (GlutaMAX), 50 μM β-mercaptoethanol, 100 U/mL penicillin, 100 μg/mL streptomycin, and 100 ng/mL Flt3 ligand. 12. Bone marrow-derived macrophage (BMDM) media: DMEM high glucose supplemented with 10% FBS, 2 mM l-alanyl-lglutamine (GlutaMAX), 100 U/mL penicillin, 100 μg/mL streptomycin, and cytokines rmM-CSF 50 ng/mL. 13. Tissue culture incubator.
2.3 Cas9-RNA Complex Formation
1. Nuclease-Free Duplex buffer (IDT cat# 11-05-01-12). 2. PCR strips or 96-well PCR plate. 3. Synthetic guide RNAs: Both the duplexed crRNA/tracrRNA guide RNA format (IDT) as well as single-guide RNAs (sgRNAs) are compatible with this protocol. In our experience, sgRNAs offer simplified preparation and improved activity relative to the crRNA/tracrRNA duplex format. At the time of this publication, chemically synthesized sgRNAs can be attained from several vendors including IDT, Synthego, and Thermo Fisher (see Note 1). A description of guide RNA target site selection schemes has been reviewed extensively elsewhere [28]. Various sgRNA suppliers provide pre-designed reagents for mouse or human genetic perturbation (see Note 2). sgRNA sequences designed to target example genes from protocol 3.5:
ä Fig. 2 (continued) defined by expression of CD64. The bottom right flow cytometry plot shows the gating strategy for determining CD64 positive cells in unstained control cells. (b) Knockout efficiency was determined by gating for negatively stained cells using the NTC. (c) B2M knockout efficiency in monocyte-derived DCs (pink, left bar graph) and macrophage (right, blue bars) cells electroporated with distinct B2M targeting sequences or NTC complexed with IDT V3 Cas9 (dark bars) or Thermo Fisher TruCut V2 Cas9 (light bars). Data is representative of two independent experiments. (d) Bar graphs depicting the % knockout of B2M, CD14, and CD81 monocyte-derived macrophages as measured by flow cytometry. Data are mean +/- S.D. (n = 3) and representative of three independent donors. ((c) and (d) Reproduced from Freund et al. [36], with permission from Journal of Experimental Medicine)
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(a) Non-targeting control (NTC) gRNA (CGTTAATCGCG TATAATACG). (b) Human CD14 gRNA (GTAGATACAACTGACCCTGT). (c) Human CD81 gRNA (GTTGGCTTCCTGGGCTGCTA). (d) Human B2M gRNA2—IDT, HS.Cas9.B2M.1.AA (CGT GAGTAAACCTGAATCTT). 4. Recombinant Cas9 protein used to make Cas9-RNPs: We have successfully applied Cas9 protein from different vendors, including IDT Alt-R Cas9 V3 and Thermo Fisher TrueCut Cas9 V2. Cas9 used in this study: (a) Alt-R Cas9 V3 (IDT cat# 1081058). (b) TrueCut Cas9 V2 (Thermo Fisher cat# A36496). 2.4 Monocyte Nucleofection
1. P3 Primary Cell Nucleofector X Kit S (Lonza cat# V4XP3032). 2. 4D Nucleofector Core Unit (Lonza cat# AAF-1002B). 3. 4D Nucleofector X Unit (Lonza cat# AAF-1002X). 4. PBS. 5. Cell counter (Vi-cell XR cell viability analyzer).
2.5 Flow Cytometric Analysis of Target Gene Disruption
1. FACS Buffer: 1X PBS, 0.5% BSA, 0.05% NaN3 (sodium azide), 2.5 mM EDTA. 2. 2% PFA solution: Dilute 4% paraformaldehyde solution 1:1 in PBS. 3. PBS. 4. Detachin (Genlantis cat# T100100). 5. 96-well U-bottom plate. 6. LIVE/DEAD Fixable Near-IR Dead Cell Stain Kit (Thermo Fisher cat# L0119). 7. Antibodies against target gene and appropriate cell-surface markers (see protocol 3.8).
3
Methods This protocol makes use of recombinant Cas9 protein and synthetic guide RNA scaffolds based on the sequences derived from Streptococcus pyogenes [29–32]. Alternative Cas systems, such as Cas9 derived from Staphylococcus aureus or Cpf1/Cas12a, will require separate optimization and target site selection methods. Figure 1 provides a general schematic of the steps involved in Cas9-RNP preparation, cell isolation, and KO generation and cell culture.
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3.1 Isolation of Human Monocytes
3.1.1 Isolation of Human Peripheral Blood Mononuclear Cells (PBMCs)
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The following protocol describes isolation of monocytes from a fresh buffy coat using SepMate tubes and the Human Monocyte Isolation Kit from Stem Cell technologies. It is also possible to isolate monocytes from a leukopak for larger scale experiments. 1. Prepare SepMate-50 tubes by pipetting 15 mL of Lymphoprep into the tubes through the hole in the separator. Prepare three tubes per 50 mL buffy coat. 2. Dilute the buffy coat with equal volume of room temperature (RT) PBS. 3. Aliquot diluted blood to SepMate tubes, pipetting slowly to avoid the blood flowing below the separator. Add ~30 mL per tube (max 35 mL). 4. Spin Sepmate tubes 800 × g for 15 min at RT. 5. After centrifugation, collect the upper layer (containing PBMCs) of each tube by quickly pouring it into a 50 mL conical tube with a secure cap (invert tube for less than 2 s). 6. Dilute the cells to 50 mL with RT PBS. Pellet cells by centrifugation at 400 × g for 5 min. Discard the supernatant. 7. Lyse red blood cells by adding 10 mL of ACK lysing buffer and incubating for 10 min at RT. Combine the three cell pellets from each 50 mL tube into a single aliquot of 10 mL of lysis buffer by sequentially adding and resuspending each pellet and then moving to the next tube. 8. Once the pellets are merged and lysis is complete, wash cells by bringing the total solution to 50 mL with RT PBS and follow with centrifugation at 400 × g for 5 min. 9. Remove liquid without disturbing the cell pellet, resuspend pellet in 50 mL RT PBS buffer, and filter the cells twice through a 70 μm filter to remove any clumps. 10. Count cells using your preferred method. Generally, the yield will be 1–3e9 PBMCs per donor; however, this will vary by donor.
3.1.2 Isolation of Human Monocytes
1. Dilute purified PBMCs with RT PBS buffer to 5e7 cells/mL in a final volume of ≤40 mL of cell suspension. Aliquot PBMC suspension into 50 mL tubes and, as needed, use multiple kits to isolate >40 mL of volume or >2e9 PBMCs. 2. Add 50 μL of isolation cocktail and 50 μL of platelet removal cocktail per mL of cell suspension (i.e., all 2 mL provided by one kit for 40 mL or 2e9 cells) and incubate for 5 min at RT. 3. Nearing the end of the 5 min incubation, vortex magnetic particles for 30 s then add 50 μL/mL of starting volume and incubate for an additional 5 min at RT.
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4. For samples ≤10 mL top up to 25 mL, and for samples >10 mL top up to 50 mL with PBS. 5. Place the 50 mL tube into the Easy50 magnet without a lid and let sit at RT for 10 min to allow the magnetic particles to be captured along the edge of the conical. Ensure that the tube is fully inserted into the magnet. 6. Use appropriate pipette (5–25 mL) to transfer the supernatant from the magnet into a new 15 or 50 mL conical tube. 7. Count cells using a preferred method. Obtaining a yield of 10–15% monocytes or 100–150e6 monocytes from a buffy coat of ~2e9 PBMCs is expected but will vary by donor. 8. Primary monocytes are now ready for electroporation or storage. Cells can be stored in liquid nitrogen for later use. We find that freshly isolated monocytes consistently show higher knockout frequency and cell viability (see Note 3). 9. ~50,000–200,00 cells can be plated in a 96-well plate in PBS and stored at 4 °C. These cells can be stained later that same day with the flow cytometry panel listed in Table 1 and analyzed by flow cytometry to verify the purity of the isolated monocytes. Generally, >90% purity is obtained, but the acceptable range will depend on the downstream assays being performed with the cells post knockout. 10. If proceeding to electroporation of freshly isolated monocytes, create single cell suspensions of 1e6 cells/mL in moDC or moMac media with appropriate cytokines (see Subheading 2.1) in non-adherent 6-well plates. Plate 3 mL per well or ~18e6 cells per 6-well plate. 11. Incubate cells overnight at 37 °C in a standard tissue culture incubator.
Table 1 Flow cytometry panel for assessing monocyte purity Target
Antibody
Fluorophore
Cell type
CD56
Biolegend 318303
FITC
NK cells
CD3
Biolegend 300405
FITC
T cells
CD19
Biolegend 302205
FITC
B cells
CD66b
Biolegend 305105
PE
Granulocyte
CD14
Biolegend 50-167-294
APC
Monocyte
Live/Dead
Thermo Fisher L34975
Near-IR
Dead cells
HLA-DR
Biolegend 307615
PE-Cy7
Monocyte
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3.2 Murine Bone Marrow Isolation and BMDM Culture 3.2.1 Isolate Bone Marrow from Tibias and Femurs of Mice [33]
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1. Euthanize mouse using institutionally approved protocols. 2. Isolate femur and tibia with sterile forceps and scissors and remove residual muscle or tissue attached to the bones. If necessary, store isolated bones in PBS on ice until further processing. 3. Push a 18G needle through the bottom of a 0.5 mL microcentrifuge tube to generate a small hole and place the 0.5 mL microcentrifuge tube in a larger 1.5 mL microcentrifuge tube. 4. To isolate the bone marrow from the harvested bones, place femur and tibia (maximum one femur and two tibia) in the 0.5 mL microcentrifuge tube nested in the 1.5 mL conical tube and close the lid. Centrifuge the tubes at 10,000 × g for 30 s. 5. Confirm complete transfer of marrow into the bottom tube after centrifugation. If residual bone marrow is maintained in the bones, cut off epiphysis and repeat the centrifugation step. 6. Resuspend the isolated bone marrow in 2 mL ACK lysing buffer and incubate at RT for 2 min. 7. Place a 0.70 μm sterile filter on a 50 mL conical tube, wet the filter with PBS and filter the bone marrow suspension into the tube. Wash the filter with 30 mL PBS and centrifuge the bone marrow at 350 × g for 4 min. Resuspend cells in PBS and count cells using preferred methods. 8. If knockout using total bone marrow as the cell source is desired, repeat the PBS wash for a total of two washes. Then follow the instructions on Cas9-RNP complex formation provided in Subheading 3.4.
3.2.2
BMDM Culture
1. If CRISPR-Cas9 editing of day 5 BMDMs is desired, plate bone marrow in BMDM culture medium at a density of 0.5 × 10e6 cells/mL in 150 mm non-TC-treated petri dishes in a volume of 20 mL/dish. After 2 days, add 20 mL fresh BMDM culture medium without removal of any medium. On day 4, remove all medium and add 20 mL fresh BMDM culture medium. On day 5, fully remove BMDM culture medium and carefully add 5 mL PBS. Scrape cells in PBS from dishes using a rubber policeman and transfer them into a 50 mL conical tube. Wash the petri dish once with 30 mL PBS and harvest cells via centrifugation. Resuspend cells in 10 mL PBS, count and aliquot appropriate number of cells for transfection, typically 1e6 per cuvette (see Note 4).
3.3 Cas9-RNP Complex Formation
The optimized protocol describes RNP complex formation and gene disruption using synthetic sgRNAs. However, the crRNA/ tracrRNA duplexes can also be used for KO (see Note 5). Perform the following at RT unless otherwise indicated. The volumes listed are for use with the Lonza Amaxa 4D.
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1. Reconstitute lyophilized sgRNAs in nuclease-free duplex buffer to a final concentration of 100 μM. 2. Mix 2 μL sgRNA (100 pmol) with 2 μL of 5 mg/mL Cas9 (60 pmol) per transfection. When using crRNA/tracrRNA duplexes, the ratio should be increased to 3 μL of guide with 2 μL of 5 mg/mL Cas9 (see Note 6). 3. Mix Cas9-RNPs by pipetting up and down or gently flicking the tube and spinning down; avoid bubbles. 4. Incubate complexes at RT for at least 20 min. During this time, cells can be harvested for electroporation, see Subheading 3.4. 5. For producing complexes with more than 1 sgRNA, with the goal of either multiple sgRNAs targeting a single gene or targeting multiple genes with a mix of gene-specific guides, combine sgRNAs then incubate with appropriate amounts of Cas9. This can be done for up to three guides or 12 μL total volume of RNP in solution. 6. Aliquot 4–12 μL of RNP (scaling by 4 μL for each unique sgRNA) into each well of a PCR strip or 96-well plate. It may be possible to reduce the amount of Cas9-RNP when using highly efficacious sgRNA sequences (see Note 7). 3.4 Monocyte Nucleofection
3.4.1 Preparing Cells and Reagents for Electroporation
This protocol describes the electroporation of human and mouse monocytes after overnight culture as described in Subheadings 3.1 and 3.2. It is best performed earlier in the day to minimize cell handling time prior to Cas9-RNP treatment, ensuring peak cell viability throughout the process. It details the protocol for electroporation of cells using the Lonza 4D Amaxa. 1. Pre-warm appropriate amount of moDC, moMac, BMDM, BMDC media at 37 °C for at least 30 min. Best practice is to aliquot media into each plate that cells will be cultured in postelectroporation and warm plates in TC incubator during treatment with Cas9-RNPs. Non-adherent plates should be used with moDCs, while moMacs, BMDM, and BMDCs should be plated on adherent tissue culture-treated plates. 2. Calculate the amount of buffer P3 from Lonza P3 Primary Cell Nucleofector X Kit S needed for all electroporations, and prepare a mastermix of the P3 buffer and included supplement following the ratio listed in the below table. Scale up to have excess volume (e.g., for five electroporations, produce a 6X mastermix) (Table 2). Let P3 Mastermix (MM) warm to RT while preparing cells for electroporation. 3. Harvest suspension human monocytes from the 6-well plates in the following by pooling media from each well of each plate in a 15 or 50 mL conical tube and immediately adding 1–2 mL of PBS per well to avoid wells drying out during cell harvest.
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Table 2 Buffer P3 Mastermix Reagent
1X (μL)
6X (μL)
Buffer P3
16.4
98.4
Supplement
3.6
21.6
Total
20
120
4. Collect the remaining cells by using the PBS to gently wash the wells. Pipette up and down ~3 times and then add PBS to previously collected media. 5. Harvest adherent BMDMs from non-TC-treated plates by removing culture media and adding 5 mL PBS to each plate. Carefully detach cells using a cell scraper. Collect cells in a 50 mL conical tube and wash plate with 5–10 mL of PBS. 6. Pellet cells by centrifugation for 5 min at 400 × g. 7. Wash cells with >5 mL of PBS (see Note 8). 8. Resuspend cells in 10 mL of PBS and count cells using preferred method. 9. Aliquot appropriate number of cells for transfection, typically 1e6 cells per transfection but can go as low as 5e5 or as high as 5e6 without significant reduction in knockout efficiency. Pellet cells by centrifugation for 5 min at 400 × g and remove all residual PBS using a small volume pipette (20–200 μL) if necessary. 3.4.2 Electroporation of Cas9-RNP Complexes Produced in Subheading 3.3
1. Turn on the 4D-Nucleofector system and choose the CM-137 program and code for electroporation. 2. Resuspend cell pellets from Subheading 3.4.1, step 9 in appropriate volume of Buffer P3 MM made in from Subheading 3.4.1, step 2. Once cells are in Buffer P3 MM, move efficiently through steps 3–6 to reduce the amount of time cells are exposed to the buffer as it is toxic over time. 3. Aliquot 20 μL of cells in P3 buffer MM into each well containing the Cas9-RNP complexes from protocol 3.3. Pipette up and down slowly to mix so as to avoid bubbles. 4. Transfer the full volume of the Cas9-RNP-cell mix immediately from PCR strip or plate into the 16-well cuvette supplied in the Lonza kit; a multi-channel pipette is suggested for this transfer. Pipette Cas9-RNP cell solution into the bottom of the cassette. Place cover on cassette and tap cassette one to two times gently to settle bubbles.
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5. Place the cuvette strip into the 4D-Nucleofector and press OK to electroporate the cells. 6. Once the program is complete, immediately remove the cassette and pipette 150 μL of media from the prewarmed plate into each filled well of the cuvette. Pipette up and down gently and then transfer the entire volume back to the final plate. 7. Incubate plate in 37 °C incubator for 5–7 days following the culturing protocol listed in Subheading 3.5. 3.5 Human Myeloid Cell Culturing Post Nucleofection 3.5.1 Human MonocyteDerived Dendritic Cell Culturing
1. Change media every 3 days by removing half of the volume in each well (e.g., 100 μL for 96-well or 1.5 mL for a 6-well). Save the harvested media from each well and centrifuge for 5 min at 400 × g to pellet cells in suspension. Remove supernatant and then resuspend cell pellet in moDC media with 2X cytokines. Pipette cell suspension with refreshed media back into the original well (see Note 9). 2. Culture cells for 5–7 days before harvesting for knockout efficiency analysis (see Note 10).
3.5.2 Human MonocyteDerived Macrophage Culturing
1. Change media every 3 days by adding half the volume of media supplemented with 1X cytokines into each well.
3.6 Mouse BMDC and BMDM Culturing Post Nucleofection
1. Culture electroporated bone marrow in prewarmed BMDC media.
3.6.1
BMDC Culturing
2. Culture cells for 5 days before harvesting for analysis of knockout efficiency (see Note 10).
2. Change media every 3 days by removing half of the volume in each well and supplementing with freshly prepared media containing 2X cytokines. 3. Culture cells for 9 days before harvesting for analysis of knockout efficiency.
3.6.2
BMDM Culturing
3.7 Flow Cytometry Analysis of Knockout Frequency
1. Culture the electroporated cells for 5 days with complete medium changes at day 2 and 4 after electroporation. This protocol is for assaying the knockout frequency of multiple cell surface markers with validated detection antibodies (see Note 11). Knockout of Beta-2-microglobulin (B2M), CD14, and CD81 in human moMacs is highlighted as an example (see Note 12). 1. Harvest cells from each plate for flow cytometry staining. For moDCs: Harvest suspension cells in media. Collect the remaining cells by using PBS to gently wash the wells by pipetting up and down ~3 times and then collecting PBS. For moMacs: Harvest moMacs in a similar manner to moDCs, except after PBS wash add appropriate volume of Detachin
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to cover well generously (e.g., 500 μL for a 6-well). Incubate plates for 5 min at 37 °C to allow any attached cells to be released. Collect Detachin and pool it with previously collected media and PBS. 2. Spin collected cells for 5 min at 400 × g. 3. Resuspend pelleted cells in 200 μL of ice-cold PBS and transfer to a 96-well plate. Place on ice. 4. Pipette an aliquot of cells into a well for an unstained control. Take a second aliquot of cells and place in a 1.5 mL centrifuge tube to create a heat-killed cell viability control. Heat the 1.5 mL tubes at 95 °C for 5 min to kill the cells. Transfer heat-killed cells to a well in the 96-well plate. 5. Spin 96-well plate for 5 min at 500 × g. 6. During 5 min spin, prepare a working solution of LIVE/ DEAD Fixable Dead Cell dye by diluting 1:50 in PBS. 7. Add 50 μL of the diluted viability dye to each well (including heat-killed but excluding unstained control). Incubate plate for 10 min at RT protected from light. 8. Add 150 μL of PBS to each well then pellet cells by spinning for 5 min at 500 × g. 9. During spin, prepare a working solution of fluorophoreconjugated antibodies in FACS buffer at the antibody manufacturer recommended dilution. See below for an example flow cytometry panel analyzing moMACs for purity and B2M, CD14 and CD81 for knockout frequency (Table 3). 10. Resuspend pelleted cells in 100 μL of antibody working solution (excluding heat-killed and unstained cell controls) and incubate for at least 30 min in the dark at 4 °C.
Table 3 Flow cytometry panel for determining KO frequency of B2M in moMacs Target
Antibody
Fluorophore
Function
CD64
BD Biosciences 561189
APC
moMac marker
CD163
Biolegend 333617
FITC
moMac marker
CD14
Invitrogen 46-0141-82
PerCP-eFluor 710
Target identification
CD81
Biolegend 349503
FITC
Target identification
β2-microglobulin
Biolegend 316305
PE
Target identification
Live/Dead Fixable Stain
Thermo Fisher L10119
Near IR
Live cells
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11. Wash cells twice with FACS buffer. For the first wash add 100 μL to wells and pellet cells for 5 min at 500 × g. Discard supernatant. Add an additional 180 μL of FACS buffer to wells and spin 5 min at 500 × g. 12. Fix cells by adding 50 μL of 2% PFA in PBS and incubating for 10 min at RT protected from light. 13. Wash cells twice with FACS buffer as before in step 11. 14. Resuspend cells after final wash in 180 μL of ice cold FACS buffer for analysis by flow cytometry. 15. Analyze knockout efficiency in the samples by flow cytometry using heat-killed cells and unstained cells as controls for livedead and positive antibody staining (Fig. 2a, b). 16. Example of B2M KO sgRNA efficiency in moDCs and moMacs (Fig. 2c). 17. Example of single, double, and triple gene KO efficiencies in moMacs (Fig. 2d).
4
Notes 1. In vitro transcribed sgRNAs should be avoided due to their potential for activating innate immune receptors [34, 35]. 2. Our protocol is intended specifically for disruption of up to three genes at a time by concurrent delivery of 1–2 sgRNAs per target locus. We recommend optimizing knockout using co-delivery of 2 sgRNAs per gene at first, followed by evaluation and further optimization (as-needed) of the process using individual sgRNAs for each gene. Details for preparation of the Cas9-RNP complexes for single or multiple sgRNA delivery can be found in Subheading 3.4. 3. Isolated monocytes may be frozen in freezing media such as Crystor CS10 (Stem Cell Technologies cat# 07930) and stored long-term in liquid nitrogen. Storage of frozen monocytes at 80 °C for longer than a week will result in significant loss in viability and knockout efficiency. Additionally, thawed monocytes are only 30–50% viable and their use generally results in lower knockout efficiencies compared to freshly isolated monocytes. 4. Typically, between 50 and 60e6 bone marrow cells are isolated from one mouse. After 5 days in BMDM culture, we typically obtain 60–80e6 cells. 5. Recombinant Cas12a and associated sgRNAs can also be used in this protocol. It is important to note that advances are being made in RNP technology, and this protocol is flexible and can be used with varying guide chemistries, recombinant Cas
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proteins, and DNA damage-modifying small molecules (i.e., electroporation enhancers). 6. Protocol alterations for duplexed crRNA/tracrRNAguide RNA preparation are listed below: (a) Place annealed guides on ice until use and/or aliquot. Aliquots can be frozen at -20 °C and thawed once. (i) Reconstitute lyophilized Alt-R crRNA and Alt-R tracrRNA in Nuclease-Free Duplex Buffer at 100 μM. Vortex tubes well, let sit for 10 min, and then vortex again. Place guides and tracrRNA on ice. (ii) Mix appropriate volume (depending on number of transfections) of reconstituted crRNA and tracrRNA at 1:1 ratio in a PCR strip on ice, mix well (50 μL max volume/well for standard PCR machines). (iii) When using the 2-part crRNA + tracrRNA gRNA format, the addition of an electroporation enhancer (IDT cat# 1075915) at 4 μM can help increase knockout efficiency [36]. 7. For efficient guides it may be possible to use less Cas9-RNP complex. A titration should be performed for each Cas9-RNP to determine the minimal amount of complex needed to achieve top knockout efficiency [36]. 8. Residual FBS can cause the electroporation to fail, and therefore, it is essential to wash the cell pellet in a large volume of PBS to dilute or remove any remaining FBS. 9. If creating knockouts in alternative cell types, it is important to optimize cell culture conditions as gene editing efficiency and subsequent population expansion can be reduced by the electroporation of stressed or unhealthy cells. 10. It is recommended to check for activation of the cells ~24 h post-electroporation and at day 5–7 of cell culturing, when knockout efficiency is assessed. This can be done using flow cytometry to detect the levels of the cellular activation markers CD80 and CD86. In addition, quantification of type I interferon released into culture media can be performed through Luminex or ELISA using commercially available kits. 11. Beyond assessing the activation status of the cells, it is important to perform the appropriate experiments to be certain that electroporation and/or gene depletion does not negatively affect the biology being assayed in the knockout cells such that you cannot accurately quantify or assay the phenotype of interest. 12. If the gene intended for knockout is not expressed on the cell surface, alternative methods can be used to detect editing (e.g.,
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intracellular staining followed by flow cytometry or western blot analysis). Additionally, if the target does not have validated antibodies, then qPCR, ddPCR, or direct sequencing of the genomic locus can be used to assay knockout efficiency.
Acknowledgments We thank J.Y. Lock, J. Oh, T. Maculins, L. Delamarre and C.J. Bohlen for their contributions to the initial study developing this protocol [36]. Conflict of Interests ECF, SMM, and BH are employees of Roche/Genentech, a for-profit institution. AM is an employee of Gilead Sciences, a for-profit institution. ECF, BH and AM reported a patent for efficient gene modification in myeloid cells using nonviral delivery of CRISPR-Cas9 (pending).
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Chapter 16 Characterization of Dendritic Cell Metabolism by Flow Cytometry Eline C. Brombacher, Thiago A. Patente, Marjolein Quik, and Bart Everts Abstract In response to different stimuli, dendritic cells (DCs) undergo metabolic reprogramming to support their function. Here we describe how fluorescent dyes and antibody-based approaches can be used to assess various metabolic parameters of DCs including glycolysis, lipid metabolism, mitochondrial activity, and the activity of important sensors and regulators of cellular metabolism, mTOR and AMPK. These assays can be performed using standard flow cytometry and will allow for the determination of metabolic properties of DC populations at single-cell level and to characterize metabolic heterogeneity within them. Key words Dendritic cells, Metabolism, Flow cytometry, Mitochondria, Glucose, Lipids, ROS
1
Introduction Dendritic cells (DCs) play a key role in the orchestration of pro-inflammatory as well as regulatory T cell responses. Classically, DCs undergo an activation program upon sensing of pathogen- or host-derived signals that endow them with the capacity to prime and polarize T cell responses. In recent years, it has become clear that DC activation is accompanied with and supported by reprogramming of their cellular metabolism and that their ability to drive different T cell responses is underpinned by distinct metabolic pathways [1, 2]. Hence, metabolic characterization of DCs provides valuable information about their biology and function in the context of different immune responses. Metabolomics and flux analysis are commonly used methods to assess metabolic properties of immune cells. These techniques generally require high cell numbers as input, which makes their use for metabolic profiling of scarce cell populations, such as DCs, problematic. Moreover, in such approaches, information about metabolic heterogeneity
Eline C. Brombacher and Thiago A. Patente contributed equally. Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_16, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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within cell populations is lost. This protocol describes how metabolic properties, specifically those related to nutrient uptake, mitochondrial function, and activity of key regulators and sensors of cellular metabolism, mTOR and AMPK, can be assessed at singlecell level in primary and in vitro-cultured DCs using commercially available antibodies, fluorescent dyes, and standard flow cytometry. One of the central regulators of cellular metabolism is AMP-activated protein kinase (AMPK), which is activated in nutrient-poor conditions [1]. AMPK controls the activity of various metabolic pathways to inhibit anabolism and to promote catabolism. Another crucial metabolic kinase is mammalian target of rapamycin (mTOR), which opposes the functions of AMPK, as it is active in nutrient-rich conditions and drives metabolic processes associated with biosynthesis [1]. A commonly used method to study the activity of kinases involves assessing the phosphorylation status of downstream targets. Here, we provide a flow cytometry protocol for the staining of phosphorylated proteins acetyl-CoA carboxylase (ACC) and S6, as markers for AMPK and mTOR activity, respectively. Two major nutrient sources for cells are glucose and fatty acids. A shift towards glucose metabolism is commonly observed upon immunogenic DC activation [3], while rewiring of lipid metabolism is associated with tolerogenic DC function [4]. The fluorescently labelled glucose analog 2-(N-(7-nitrobenz-2-oxa-1,3diazol4-yl)amino)-2-deoxyglucose (2-NBDG) can be used to measure glucose uptake in live cells, while BODIPY™ lipid probes allow for the characterization of fatty acid uptake and intracellular lipid accumulation [5, 6]. We describe a flow-cytometry-based protocol that is applicable for, but not restricted to, staining with 2-NBDG, BODIPY 4,4-difluoro-5,7-dimethyl-4-bora-3a,4adiaza-s-indacene-3-hexadecanoic acid (BODIPY™ FL C16), and 4,4-difluoro-1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-sindacene (BODIPY™ 493/505) to characterize glucose uptake, fatty acid uptake, and lipid accumulation, respectively, in live DCs. Mitochondria serve as central metabolic hubs in cells, including DCs, through citric acid cycle activity, oxidative phosphorylation for ATP production, and reactive oxygen species (ROS) production [2]. Several fluorescent dyes allow for easy analysis of various mitochondrial parameters. Mitochondrial mass, a measure of overall mitochondrial content in a cell, can be determined through the use of various MitoTracker dyes, which are commercially available in different fluorescence spectra [7]. Mitochondrial membrane potential (Δψ m), the driving force of mitochondrial ATP production and as such an important measure of cellular metabolism, can be stained with tetramethylrhodamine methyl (TMRM) [8, 9]. Mitochondrial ROS (mtROS), which are by-products of oxidative phosphorylation, and total cellular ROS production can be analyzed through the dye MitoSOX™ Red, which fluoresces proportional to mtROS production and CM-H2DCFDA, respectively [9–11].
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The procedural steps for aforementioned stainings are described below to provide a framework for the metabolic characterization of in vitro-cultured and primary human and murine DCs by standard flow cytometry as well as options to combine multiple dyes using advanced spectral flow cytometry.
2 2.1
Materials Cellular Systems
2.2 Flow Cytometry Reagents and Equipment
This protocol provides detailed information for measurements in primary murine splenic DCs, human blood-derived DCs, and in vitro-cultured DC populations, including murine bone-marrowderived DCs (BMDCs) and human monocyte-derived DCs (moDCs), but may also be applicable to other cell types. 1. Phosphate-buffered saline (PBS). 2. FACS buffer: 1% bovine serum albumin (BSA) in PBS. 3. Lineage-defining antibodies (Tables 3, 4, 5, and 6). 4. αCD16/αCD32 (Fc block). 5. Viability dye (see Note 1). 6. 96-well V-bottom plate. 7. FACS tubes. 8. Flow cytometer equipped with lasers and emission filters suitable for the analysis of cells stained with the antibodies and dyes listed in the antibody panel (Tables 3, 4, 5, 6, and 7).
2.3 Intracellular Staining for Metabolic Phosphorylated Proteins
1. 16% formaldehyde, methanol free, UltraPure. 2. Formaldehyde, stabilized with methanol. 3. 100% methanol, stored at -20 °C. 4. 10× eBioscience™ Permeabilization Buffer (perm buffer). 5. Conjugated antibody or primary and secondary antibodies (Table 2). 6. Complete RPMI: RPMI 1640 medium with GlutaMAX, 10% fetal calf serum (FCS), 100 IU/mL penicillin, 100 μg/mL streptomycin, and 50 μM 2-mercaptoethanol. 7. 24-well cell culture plate. 8. 96-well flat-bottom plate. 9. 1 mL syringe. 10. 5 mL FACS tubes.
2.4
Metabolic Dyes
1. Metabolic dyes (Table 7).
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Methods Throughout the protocol, centrifugation is set at 300 × g for 4 min at 4 °C, unless stated otherwise.
3.1 Intracellular Staining of Phosphorylated Metabolic Proteins
This protocol describes in detail the staining procedure of phosphorylated ACC and S6, as a direct reflection of AMPK and mTOR activity, respectively. This protocol can be applied to other intracellular and/or phosphorylated proteins as well (see Note 2). In brief, the general procedure for intracellular staining of phosphorylated metabolic proteins consists of the following steps: 1. Fixation of cells: • Phosphorylation is generally an unstable posttranslational modification, and therefore, it is recommended to fix cells prior to any processing (see Note 3). Live and dead cells can be distinguished by strict gating in the FSC-A vs SSC-A plot (Fig. 1a).
Fig. 1 pACC and pS6 staining in murine tissue-derived DCs. (a) Strict gating of the FSC-A is required to remove dead cells in a sample without viability staining. (b) pACC and pS6 data is shown from MHC-II+CD11c+ splenic DCs. The signal of (c) pACC and (d) pS6 is lost in CD11cΔAMPKα1 and CD11cΔraptor mice, respectively
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• The fixation protocol is divided into three parts: (1) procedure for direct fixation of DCs in tissues prior to their isolation, (2) fixation procedure of tissue- and bloodderived DCs after their isolation from tissues, and (3) fixation procedure for in vitro-cultured DCs. 2. Permeabilization of cells 3. Staining with primary antibody (see Note 4) 4. Staining with secondary antibody 5. Cell acquisition on flow cytometer Fixation
1. Add 500 μL of 2% formaldehyde/PBS to a 24-well plate, 1 well per tissue.
Fixation Prior to Tissue Processing
2. Transfer tissue of interest to 2% formaldehyde/PBS (see Note 5).
3.1.1
3. Immediately smash the tissue with the back of a 1 mL syringe. 4. Fix the cells for 30 min at room temperature (RT). 5. Add 500 μL of RPMI (no additives) to the wells to lower the concentration of the fixative. Continue with the next step if all tissues have been in fixative for at least 30 min. 6. Centrifuge the 24-well plate. 7. Transfer as much supernatant as possible, without transferring pieces of tissue, to a sterile 5 mL FACS tube. 8. Add 1 mL of RPMI (no additives) to the wells of the 24-well plate and spin down the plate. 9. Repeat steps 7 and 8. 10. After the second centrifugation of the plate, remove supernatant from the well as in step 7 and spin down the 5 ml FACS tubes. In the meantime, add 350 μL of RPMI (no additives) to the wells 11. After centrifugation, remove the supernatant from the tubes by decantation. 12. Resuspend the pellet (may not be visible) in the remaining ±150 μL of medium and transfer this solution back to the 24-well plate containing 350 μL of medium. 13. The wells containing the tissues should be now in a total of 500 μL of medium. 14. Process the tissues using your standard protocol to generate single-cell suspensions (see Note 6). 15. After generation of single-cell suspensions, store cells in 200 μL FACS buffer at 4 °C for a maximum of 1 week. Continue with Subheading 3.1.2.
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Fixation of Single-Cell Suspensions After Tissue or Blood Processing
1. Process tissues or blood according to your standard protocol to obtain single-cell suspensions or PBMCs, respectively. 2. Plate the desired number of isolated cells (Table 2) in a 96-well V-bottom plate. 3. Fill the wells to 200 μL with PBS. 4. Centrifuge the plate and remove supernatant by flicking. 5. Repeat steps 3 and 4. 6. Stain cells with a viability stain of your choice (see Note 7). 7. Repeat steps 3 and 4. 8. Add 200 μL of complete medium. 9. Incubate the cells for 1–2 h at 37 °C (see Note 8). 10. Take the plate out of the incubator and immediately add 65 μL of 16% UltraPure methanol free formaldehyde, to reach a final concentration of 4% (see Notes 9 and 10). 11. Fix cells for 15 min at RT (see Note 11). 12. Repeat steps 3 and 4 twice, but use FACS buffer instead of PBS. 16. Store cells in 200 μL FACS buffer at 4 °C for a maximum of 1 week. Continue with Subheading 3.1.2.
Fixation of In Vitro-Cultured DCs
1. Plate the desired number of cells (Table 2) in complete RPMI in a 96-well flat-bottom plate. Include wells for the controls: a staining with the secondary antibody only and an unstained sample. 2. Fill the wells to 200 μL with complete RPMI and stimulate cells with your compound of interest. 3. Take the plate out of the incubator and immediately add 65 μL of 16% UltraPure methanol free formaldehyde, to reach a final concentration of 4% and resuspend. 4. Fix cells for 15 min at RT. 5. Put the plate on ice and carefully loosen the adherent cells by scraping with 200 μL pipet tips. 6. Transfer cells to a V-bottom plate. 7. Centrifuge the plate. 8. Discard supernatant by flicking the plate. 9. Add 200 μL FACS buffer. 10. Repeat steps 7–9 twice. 11. Store plate at 4 °C for a maximum of 1 week. Continue with Subheading 3.1.2.
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Table 1 Antibodies used for staining of intracellular (phosphorylated) proteins Target
Source
Identifier
Control
Reference for control
Phospho-acetyl-CoA Carboxylase (Ser79)
Cell Signaling
11818
Metformin
[19]
Phospho-S6 (Ser240) – PE
BD Biosciences
560430
LPS
[20]
Goat anti-rabbit AF647
Thermo Fisher
A-21244
–
–
3.1.2
Staining Procedure
1. Centrifuge the plate and remove supernatant by flicking. 2. Add 200 μL of 1× eBioscience permeabilization buffer to each well. 3. Centrifuge the plate and remove supernatant by flicking. 4. Repeat steps 2 and 3. 5. Resuspend cells in 100 μL of 100% methanol for further permeabilization (see Note 12). 6. Incubate for 20 min at -20 °C. 7. Repeat steps 2 and 3 twice. 8. Resuspend cells in 20 μL of 1× eBioscience permeabilization buffer containing the primary antibody and Fc block (αCD16/ αCD32) (see Table 1). 9. Incubate for 30 min at 4 °C. 10. Repeat steps 2 and 3. 11. Resuspend cells in 30 μL of 1× eBioscience permeabilization buffer containing the secondary antibody and the desired antibody cocktail mix (see Note 13 and Tables 3, 4, 5, and 6). 12. Incubate for 30 min at 4 °C. 13. Fill wells up to 200 μL with FACS buffer. 14. Centrifuge the plate and remove supernatant by flicking. 15. Resuspend cells in the appropriate volume of FACS buffer to be acquired in a flow cytometer. A representative example of pACC and pS6 staining is shown in Fig. 1.
3.2 Glucose and Lipid Metabolism
Various fluorescent dyes are available to evaluate nutrient uptake and accumulation using flow cytometry. Here, we provide a protocol for assessing glucose uptake (2-NBDG), cellular neutral lipid droplet content (BODIPY™ 493/505), and uptake of long-chain fatty acids (BODIPY™ FL C16).
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Table 2 Recommended number of cells to ensure a proper staining for identification of phosphorylated proteins and metabolic dyes in DCs Source of cells
Cell concentration
Pure DC population (from in vitro DC cultures)
1 × 10 /mL
Mixed population (from tissues/PBMCs)
10 × 10 /mL
3.2.1
Staining Procedure
6
6
Minimum number of cells 50,000 1,000,000
1. Plate the desired number of live cells (Table 2) in complete RPMI in a 96-well V-bottom plate. Include wells for the controls treated with 2-DG (in case of 2-NBDG, see Note 14) or incubated in PBS containing 10% FCS (in case of BODIPY™ FL C16 and BODIPY™ 493/505, see Note 15). 2. Fill wells with PBS to up to 200 μL. 3. Spin down and remove supernatant. 4. Repeat steps 2 and 3. 5. Stain cells with the viability dye of your choice and Fc block (αCD16/αCD32) in PBS. 6. Incubate cells for 15 min at RT. 7. Repeat steps 2 and 3. 8. Incubate cells with either 50 μM of 2-NBDG, 5 μM of BODIPY™ 493/505 dye, or 10 μM BODIPY™ FL C16 (diluted in PBS) and incubate cells for 15 min at 37 °C in a CO2 incubator (see Notes 16–19). 9. Add FACS buffer to wells to reach 200 μL. 10. Centrifuge the plate and remove supernatant. 11. Resuspend cells in 30 μL of FACS buffer containing the antibody cocktail mix (see Tables 3, 4, 5, and 6). 12. Incubate for 30 min at 4 °C. 13. Repeat steps 9 and 10. 14. Resuspend cells in the appropriate volume of FACS buffer to be acquired in a flow cytometer. See Table 7 for information on excitation and emission wavelengths for each dye. A representative example of 2-NBDG and BODIPY™ FL C16 staining in DCs is shown in Fig. 2.
3.3 Mitochondrial Metabolism
MitoTracker and TMRM are dyes commonly used to measure mitochondrial mass and mitochondrial membrane potential, respectively (see Note 20). Due to the positive charge of these probes, they can enter live, polarized mitochondria, but not depolarized mitochondria. While TMRM is a dye available only with a specific emission wavelength, different MitoTrackers are
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Table 3 Lineage-defining antibodies required for identification of primary murine DC subsets Marker
Target population
Clone
CD3
T cells
17A2
B220
B cells/pDCs
RA3-6B2
Ly6C
Monocytes/pDCs
HK1.4
CD64
Macrophages
X54-5/7.1
CD11c
Monocytes/DCs
N418
MHC-II
Monocytes/DCs
M5/114.15.2
XCR1
cDC1
ZET
CD11b
cDC2
M1/70
CD172a
cDC2/pDCs
P84
Siglec-H
pDCs
551
CD16/32
FC receptors
93
Table 4 Lineage-defining antibodies required for identification of primary human DC subsets Marker
Target population
Clone
CD3
T cells
UCHT1
CD19
B cells
HIB19
CD56
NK cells
NCAM16.2
CD11c
Monocytes/DCs
Bu15
HLA-DR
Monocytes/DCs
L243
CD16
Monocytes
3G8
CD14
Monocytes
MΦP9
CD1c
cDC2
L161
CD141
cDC1
AD5-14H12
CD123
pDC
9F5
CD16/32
FC receptors
Polyclonal
commercially available with fluorescence in different wavelengths (i.e., MitoTracker Green FM and MitoTracker Deep Red FM). The following protocol is optimized for MitoTracker Green FM, but can also be applied to the other available MitoTracker dyes (see Note 21).
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Table 5 Lineage-defining antibodies for identification of human in vitro-cultured DC populations Marker
Clone
CD11c
h: Bu15
HLA-DR
h: L243/
CD14
MΦP9
CD1a
HI149
Table 6 Lineage-defining antibodies for identification of mouse in vitro-cultured DC populations Marker
Clone
Differentiation protocol
CD11c
N418
GM-CSF/FLT3L
MHC II
M5/114.15.2
GM-CSF/FTL3L
CD11b
M1/70
GM-CSF/FLT3L
CD115
AFS98
GMCSF
CD135
A2F10
GMCSF
CD24
M1/69
FLT3L
CD172a
P84
FTL3L
Siglec-H
551
FTL3L
Table 7 Metabolic dyes Dye
Source
Identifier
Concentration
Excitation
Emission
MitoTracker™ Deep Red FM
Thermo Fisher
M22426
10 nM
540
595
MitoTracker™ Green FM
Thermo Fisher
M7514
20 nM
490
516
TMRM
Thermo Fisher
T668
20 nM
548
574
2-NBDG
Thermo Fisher
N13195
50 μM
465
540
BODIPY™ FL C16
Thermo Fisher
D3821
200 nM
488
508
BODIPY™ 493/503
Thermo Fisher
D3922
5 μM
493
503
HCS LipidTOX™ Deep Red
Thermo Fisher
H34477
1:200
644
665
MitoSOX™ Red
Thermo Fisher
M36008
5 μM
510
580
H2DCFDA (H2-DCF, DCF)
Thermo Fisher
D399
1 μM
492–495
517–527
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Fig. 2 2-NBDG and BODIPY™ FL C16 staining in murine tissue-derived MHCII+CD11c+ DCs. (a) 2-DG functions as a negative control for 2-NBDG staining. (b) 10% FCS can be used as a negative control for BODIPY™ FL C16 staining 3.3.1
Staining Procedure
1. Plate the desired number of cells (Table 2) in complete RPMI in a 96-well V-bottom plate. Include one well for FCCPtreated cells as control (see Note 22). 2. Fill wells up to 200 μL with complete RPMI. 3. Centrifuge the plate and remove supernatant. 4. Repeat steps 2 and 3. 5. Stain cells with the viability dye of your choice and Fc block (αCD16/αCD32) in PBS. 6. Incubate cells for 15 min at RT. 7. Repeat steps 2 and 3. 8. Incubate cells with 10 nM of TMRM and 20 nM of MitroTracker Green FM for 15 min at 37 °C in complete RPMI. 9. Repeat steps 2 and 3. 10. Incubate control well with 50 μM of FCCP for 15 min at 37 °C in complete RPMI. 11. Centrifuge the plate and remove supernatant. 12. Fill wells up to 200 μL with FACS buffer. 13. Centrifuge the plate and remove supernatant. 14. Resuspend cells in 30 μL of FACS buffer containing the antibody cocktail mix (see Tables 3, 4, 5, and 6).
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Fig. 3 MitoTracker Green FM and TMRM staining. (a, b) MitoTracker Green FM and TMRM staining in murine tissue-derived DCs gives a heterogenous staining. Signal can be quantified using MFI or the frequency of positive cells. (c, d) Staining of moDCs, a homogenous population, with the same dyes, gives a single population. In these cells, signal can be quantified using MFI
15. Incubate for 30 min at 4 °C. 16. Repeat steps 11 and 12. 17. Resuspend cells in the appropriate volume of FACS buffer to be acquired in a flow cytometer. See Table 7 for information on excitation and emission wavelengths for each dye. A representative example of MitoTracker Green FM and TMRM staining in DCs is shown in Fig. 3. 3.4
3.4.1
ROS Staining
Staining Procedure
A variety of commercial kits and dyes are available to detect intracellular production of ROS via flow cytometry. Here we describe a staining procedure for CM-H2DCFDA and MitoSOX™ Red for DCs, which detect total intracellular ROS and mitochondriaderived superoxide, respectively (see Note 23). 1. Plate the desired number of cells (Table 2) in complete RPMI in 96-well V-bottom plate. If desired, plate two additional wells for positive (H2O2) and negative (N-acetyl cysteine [NAC]) control. 2. Fill wells up to 200 μL with complete RPMI. 3. Spin down and remove supernatant. 4. Repeat steps 2 and 3. 5. Incubate controls well with 0.03% H2O2 or 1 μM of NAC for 1 h at 37 °C in complete RPMI (see Note 24). 6. Repeat steps 2 and 3.
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Fig. 4 MitoSOX and H2DCFDA staining in in vitro-cultured human moDCs. Vitamin D (VitD) was used as positive control [18]. (a) MtROS and (b) total ROS production are increased in VitD-treated DCs. (c) MtROS and total ROS can be stained together and distinguished from each other. In these cells, signal can be quantified using MFI
7. Stain cells with the viability dye of your choice and Fc block (αCD16/αCD32) in PBS. 8. Incubate cells for 15 min at RT. 9. Repeat steps 2 and 3. 10. Incubate cells with 5 μM of MitoSOX™ Red or 1 μM of CM-H2DCFDA for 15 min at 37 °C in complete RPMI. 11. Fill wells up to 200 μL with FACS buffer. 12. Centrifuge the plate and remove supernatant. 13. Resuspend cells in 30 μL of FACS buffer containing the antibody cocktail mix (see Tables 3, 4, 5, and 6). 14. Incubate the cells for 30 min at 4 °C. 15. Repeat steps 11 and 12. 16. Resuspend the cells in the appropriate volume of FACS buffer to be acquired in a flow cytometer. See Table 7 for information on excitation and emission wavelengths for each dye. A representative example of MitoSOX™ Red and CM-H2DCFDA staining in DCs is shown in Fig. 4. 3.5 Metabolic Panel Tested on Cytek Spectral Flow Cytometer
Metabolic dyes can be measured with standard flow cytometers, but spectral overlap between a number of these dyes makes it difficult to design a panel in which multiple dyes are combined. However, with the five-laser Cytek Aurora, a spectral flow cytometer, one can combine up to four dyes in one panel, namely, 2-NBDG, BODIPY™ FL C16, TMRM, and MitoTracker Green FM. Therefore, spectral flow cytometry allows for metabolic profiling using multiple metabolic dyes in parallel when the number of cells is limited, for example, in the case of murine tissue-derived DCs (Fig. 5).
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Fig. 5 Mitochondrial dye staining using spectral flow cytometry. (a) Gating strategy to identify DC subsets in murine splenocytes. (b) cDC1s and cDC2s show differences in uptake of 2-NBDG and BODIPY™ FL C16
4
Notes 1. Cells can be stained with the viability dye of your choice. We successfully tested LIVE/DEAD™ Fixable Aqua (1:400 dilution when performing experiments on a BD FACSCanto II, BD FACS LSR, or BD FACS Fortessa X20 flow cytometer and 1:1000 dilution when performing experiments on a Cytek Aurora Spectral flow cytometer) and LIVE/DEAD™ Fixable Blue and Zombie NIR™ Fixable (both 1:1000 on a Cytek Aurora spectral flow cytometer). 2. Not all unconjugated antibodies are suitable for flow cytometry. Make sure to have a proper positive and negative control to test if the staining is reliable.
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3. To maintain the in situ phosphorylation status of the protein of interest, it is recommended to fix tissues directly after harvesting. In our hands, this protocol works well for murine spleen, lymph nodes, and tumors, but not for lamina propria of the murine small intestine. Furthermore, if a tissue is also used for experiments that require live cells, it is recommended to fix only part of the tissue. 4. If the antibody of interest is already conjugated to a fluorochrome (e.g., pS6-PE (Table 1)), this step can be skipped and the antibody can be included in the antibody cocktail together with lineage-defining antibodies. 5. This protocol is optimized for murine lymphoid tissues such as spleen and lymph nodes. In case of tissues other than spleen or lymph nodes, one can use the standard protocol implemented in your laboratory, replacing the solution normally used to collect the tissue of interest with 2% formaldehyde/PBS. Wash the fixative away with medium or PBS before digesting the tissue. 6. Fixing the samples prior to tissue processing might result in less efficient digestion of the tissues and, as a consequence, reduced number of cells. Digestion of spleen and lymph nodes using DNase I and collagenase D is still effective when performed on fixed samples. 7. When processing tissue samples before fixing the cells, we recommend to stain the cells with a viability dye before resting the cells in the incubator. Not only the mechanic procedure to obtain the cells can lead to cell death, but the heterogeneity of cells makes it difficult to distinguish live and dead cells by size and complexity. On the other hand, in vitro-cultured DCs comprise a more homogenous population when analyzing the samples by size and complexity and the removal of dead cells based on these parameters can be performed easier. Additionally, the viability of in vitro-cultured DCs is normally high. However, if working with additional treatments that affect viability DCs, we recommend to include a viability dye staining. 8. The processing procedure to obtain a single-cell suspension from tissues can interfere with the in situ phosphorylation status of the protein of interest. Therefore, we recommend to leave cells following their isolation for 1–2 h in an CO2 incubator. This resting of the cells will help restore phosphorylation status more comparable to their original in situ profile. 9. In our experience, adding 22 μL of the standard 37% formaldehyde, which contains methanol as a stabilizer, is also an option. However, this option provides a higher background signal and our advice is to use 16% ultra-pure formaldehyde.
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10. 4% ultra-pure formaldehyde can damage epitopes in tissues. Test your panel to see whether binding of your antibodies of interest are affected and perform a titration from 1% to 4% of ultra-pure formaldehyde if needed to improve staining signal. In our experience XCR1 binding is highly affected by fixation. Staining cells with XCR1 after the fixation might lead to the appearance of false CD172a+XCR1+ DC population. To prevent this, stain cells with XCR1 before fixation, for example, together with the viability dye. 11. Fixation can also be performed at 37 °C without affecting the phosphorylation signal. However, in our experience, the recovery of cells is higher when fixation was performed at RT. 12. The 100% methanol should be stored at -20 °C and taken out of the freezer right before addition to the cells. Be aware that methanol can damage some epitopes, thereby interfering with cell staining. We observed that CD11c is sensitive to methanol permeabilization, leading to signal loss and making it challenging to identify DCs in tissues. To prevent that, we recommend to stain CD11c prior to methanol permeabilization, for example, together with the viability dye. Carefully select your CD11c fluorochrome because some of them are methanolsensitive and cannot be used prior to methanol permeabilization. In our experience, CD11c-BV421 signal is still retained after methanol permeabilization. 13. For staining of in vitro-cultured human moDCs, compounds like vitamin D, retinoic acid, or dexamethasone can markedly decrease CD1a expression. In that case, we recommend to stain for only CD11c and HLA-DR. In case of bone marrow-derived DCs differentiated in the presence of GM-CSF, be aware that this is a mixed population of DCs and macrophage-like cells [12] and additional markers might be required depending on your research question. 14. Even though 2-NBDG has been commonly used as a readout for glucose uptake, its use for this purpose was recently questioned [13]. Interpret your results carefully and make sure to always include appropriate controls. The following molecules can be used as controls for 2-NBDG staining: (1) 2-DG acts as a substrate for hexokinase to block its activity and directly competes with 2-NBDG; (2) 4,6-O-ethylidene-α-D-glucose (4,6-O) is a glucose analogue that binds to the external site of glucose transporters (GLUTs) but is not transported into cells; and (3) cytochalasin B (CytB) diffuses through the cell membrane and binds to the internal site of GLUTs, also preventing entry of glucose into cells [14].
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15. Staining cells in PBS 10% FCS serves as a negative control for the uptake of BODIPY™ FL C16 and BODIPY™ 493/505. The lipids present in FCS are targets for BODIPY™ 493/505, reducing the availability of the dye for binding to cellular lipid structures. Additionally, lipids present in FCS will directly compete with BODIPY™ FL C16 for uptake by cells, thereby reducing BODIPY™ FL C16 uptake. 16. As an alternative to BODIPY™ 493/503, HSC LipidTOX is a commercially available dye that stains neutral lipids. This neutral lipid staining can be performed on fixed and permeabilized as well as unpermeabilized cells, which makes this dye an interesting option if cells need to be fixed. According to the manufacturer’s instruction, HSC LipidTOX should be diluted 200× and stained in PBS. 17. Thermo Fisher provides BODIPY™ lipid probes for multiple purposes, including the staining of membrane lipids, uptake of fatty acids of various lengths, and nonpolar probes for neutral lipid staining with different fluorescence. This protocol may be applicable to other BODIPY™ lipid probes as well, but carefully read the manufacturer’s instructions. 18. BODIPY™ 493/505 and BODIPY™ FL C16 are hydrophobic dyes that do not disperse readily into aqueous solutions. To ensure proper dissolving of the dye, vigorously vortex them before preparing the staining mix. 19. The metabolic dyes can be stained together with the viability dye. In that case, make sure to stain your cells at 37°C instead of RT. The viability dyes can resist higher temperatures while most of the metabolic dyes allow less flexibility in this respect and require a specific temperature for optimal staining. 20. MitoTrackers and TMRM are both lipophilic cationic dyes that stain live, polarized mitochondria. However, differently from TMRM, MitoTrackers bind to intramitochondrial protein thiols and remain bound, even after depolarization. Because of these differences, TMRM and MitoTracker are commonly used to measure mitochondrial membrane potential and mitochondrial mass, respectively. 21. Besides MitoTracker Green FM and MitoTracker Deep Red FM, there are also other MitoTrackers options, including MitoTracker Red FM and MitoTracker Red CMXRos. However, these MitoTrackers, in contrast to MitoTracker Green FM and MitoTracker Deep Red FM, accumulate in mitochondria in a membrane-potential-dependent manner (in a similar way as TMRM). If one is interested in mitochondrial mass, the preferred choice would be MitoTracker Green FM or MitoTracker Deep Red FM. One important difference between
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these two dyes is the fact that MitoTracker Deep Red FM is a dye that is well-retained in the mitochondria after fixation of the cells, while MitoTracker Green FM is not. 22. Even though MitoTracker Green FM and MitoTracker Deep Red FM are considered mitochondrial mass dyes, both of their signals seem to be at least partially affected by mitochondrial membrane potential [15]. MitoTracker Deep Red FM seems to be more affected than MitoTracker Green FM and the combination of both dyes has been used to identify dysfunctional mitochondria [16, 17]. It is important to have an appropriate negative mitochondrial membrane potential control, such as ionophore FCCP, that depolarizes the mitochondrial membrane, to ensure that your MitoTracker staining is not being affected by membrane potential and, also, to properly demonstrate that the TMRM staining is affected by the membrane depolarization. 23. CM-H2DCFDA (and its derivatives) are nonspecific ROS dyes that report general ROS production but cannot be used with fixed cells. If one needs to study ROS production in fixed or permeabilized cells, CellROX™ Green can be used. For more specific ROS detection, one can use dihydroethidium (DHE) (which detects intracellular levels of superoxide) or DAF-FM diacetate (which detects intracellular levels of NO). 24. Incubation time for the positive control well can be reduced by increasing the percentage of H2O2. Be aware that H2O2 can be toxic if cells are exposed to high concentrations for a longer period of time. References 1. Kelly B, O’Neill LA (2015) Metabolic reprogramming in macrophages and dendritic cells in innate immunity. Cell Res 25(7):771–784 2. O’Neill LA, Kishton RJ, Rathmell J (2016) A guide to immunometabolism for immunologists. Nat Rev Immunol 16(9):553–565 3. Everts B, Amiel E, Huang SC, Smith AM, Chang CH, Lam WY et al (2014) TLR-driven early glycolytic reprogramming via the kinases TBK1-IKKvarepsilon supports the anabolic demands of dendritic cell activation. Nat Immunol 15(4):323–332 4. Zhao F, Xiao C, Evans KS, Theivanthiran T, DeVito N, Holtzhausen A et al (2018) Paracrine Wnt5a-beta-catenin signaling triggers a metabolic program that drives dendritic cell tolerization. Immunity 48(1):147–60 e7 5. Zou C, Wang Y, Shen Z (2005) 2-NBDG as a fluorescent indicator for direct glucose uptake
measurement. J Biochem Biophys Methods 64(3):207–215 6. Herber DL, Cao W, Nefedova Y, Novitskiy SV, Nagaraj S, Tyurin VA et al (2010) Lipid accumulation and dendritic cell dysfunction in cancer. Nat Med 16(8):880–886 7. Clutton G, Mollan K, Hudgens M, Goonetilleke N (2018) A reproducible, objective method using MitoTracker® fluorescent dyes to assess mitochondrial mass in T cells by flow cytometry. Cytometry A 95(4):450–456 8. Scaduto RC, Grotyohann LW (1999) Measurement of mitochondrial membrane potential using fluorescent rhodamine derivatives. Biophys J 76:9 9. Little AC, Kovalenko I, Goo LE, Hong HS, Kerk SA, Yates JA et al (2020) High-content fluorescence imaging with the metabolic flux
Dendritic Cell Metabolism With Flow Cytometry assay reveals insights into mitochondrial properties and functions. Commun Biol 3(1):271 10. Kauffman ME, Kauffman MK, Traore K, Zhu H, Trush MA, Jia Z et al (2016) MitoSOX-based flow cytometry for detecting mitochondrial ROS. React Oxyg Species (Apex) 2(5):361–370 11. Kuznetsov AV, Kehrer I, Kozlov AV, Haller M, Redl H, Hermann M et al (2011) Mitochondrial ROS production under cellular stress: comparison of different detection methods. Anal Bioanal Chem 400(8):2383–2390 12. Helft J, Bottcher J, Chakravarty P, Zelenay S, Huotari J, Schraml BU et al (2015) GM-CSF mouse bone marrow cultures comprise a heterogeneous population of CD11c(+)MHCII (+) macrophages and dendritic cells. Immunity 42(6):1197–1211 13. Sinclair LV, Barthelemy C, Cantrell DA (2020) Single cell glucose uptake assays: a cautionary tale. Immunometabolism 2(4):e200029 14. Holman GD (2018) Chemical biology probes of mammalian GLUT structure and function. Biochem J 475(22):3511–3534 15. Xiao B, Deng X, Zhou W, Tan EK (2016) Flow cytometry-based assessment of mitophagy using MitoTracker. Front Cell Neurosci 10:76
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16. Yu J, Nagasu H, Murakami T, Hoang H, Broderick L, Hoffman HM et al (2014) Inflammasome activation leads to Caspase-1dependent mitochondrial damage and block of mitophagy. Proc Natl Acad Sci U S A 111(43):15514–15519 17. Ye J, Jiang Z, Chen X, Liu M, Li J, Liu N (2017) The role of autophagy in pro-inflammatory responses of microglia activation via mitochondrial reactive oxygen species in vitro. J Neurochem 142(2):215–230 18. Ferreira GB, Vanherwegen AS, Eelen G, Gutierrez ACF, Van Lommel L, Marchal K et al (2015) Vitamin D3 induces tolerance in human dendritic cells by activation of intracellular metabolic pathways. Cell Rep 10(5): 711–725 19. Zhou G, Myers R, Li Y, Chen Y, Shen X, Fenyk-Melody J et al (2001) Role of AMP-activated protein kinase in mechanism of metformin action. J Clin Investig 108(8): 1167–1174 20. Amiel E, Everts B, Freitas TC, King IL, Curtis JD, Pearce EL et al (2012) Inhibition of mechanistic target of rapamycin promotes dendritic cell activation and enhances therapeutic autologous vaccination in mice. J Immunol 189(5): 2151–2158
Chapter 17 In Vivo and In Vitro Assay to Address Dendritic Cell Antigen Cross-Presenting Capacity Pengju Ou, Lifen Wen, Hai Ni, and Cliff Y. Yang Abstract Antigen cross-presentation by dendritic cells is an important pathway to prime CD8+ T cells in infections, cancer, and other immune-mediated pathologies. Particularly in cancer, cross-presentation of tumorassociated antigens is crucial for an effective antitumor CTL response. The mostly accepted crosspresentation assay is to use chicken ovalbumin (OVA) as a model antigen and then utilize OVA-specific TCR transgenic CD8+ T (OT-I) cells to measure the cross-presenting capacity. Here we describe in vivo and in vitro assays to measure the function of antigen cross-presentation using cell-associated OVA. Key words Dendritic cells, Cross-presentation, Ovalbumin (OVA), OT-I cells, Cell-associated antigens, T cell cross priming
1
Introduction Antigen cross-presentation is the specific ability of dendritic cells to present exogenous antigen via major histocompatibility complex (MHC) class I molecules. This unique ability is crucial to prime CD8+ T cells in response to intracellular infections, cancer, and other immune-mediated pathologies [1, 2]. Conventional type 1 dendritic cells (cDC1s) are the major cross-presenting DC subset in vivo [3]. cDC1s were previously identified by many markers such as CD8α+/CD103α+/XCR1+/DNGR-1/CLEC9A+ or the essential transcriptional factor Batf3 [4–9]. In addition to cDC1s, DCs derived under inflammatory conditions from hematopoietic progenitors or monocytes (moDCs) are capable of cross-presentation [10, 11]. Although there are many model antigens available, chicken ovalbumin (OVA) remains the most widely used antigen. There are three major way to deliver OVA to dendritic cells: OVA itself, OVA-conjugated beads, and cell-associated OVA. OVA itself, in
Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_17, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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excessive amount, may yield to false-positive results due to the trace amount of fragment peptide and contaminants that may directly activate DCs. OVA-conjugated beads address these caveats while creating its own artificiality with latex beads. Cell-associated OVA is the most accepted antigen delivery method, since it mimics how antigens from dead cells are cross-presented in vivo [12]. To avoid interference from classical MHC class I presentation, antigen-loaded cells are obtained either from a different genetic background such as BALB/c (if the DCs are from C57BL/6 background) or from MHC class I-deficient transgenic mouse strains such as Tap1 / mice. In this chapter, we will present in vivo and in vitro methods to evaluate and quantify DCs cross-presenting capacity using cellassociated OVA [13, 14]. BALB/c splenocytes are loaded with OVA by osmotic shock. This process is achieved by their incubation with hypertonic medium containing OVA and then with hypotonic medium. After lethal irradiation, OVA-loaded cells are given to DCs in vivo or in vitro. Proliferation of cross-primed OT-I CD8 T cells is then measured by a proliferation dye.
2
Materials Prepare all solutions using RPMI 1640 (do not use water) and analytical grade reagents. Diligently follow all waste disposal regulations when disposing waste materials.
2.1 Reagents and Plasticware
1. Hypertonic medium: 0.5 M sucrose, 10% weight/volume of polyethylene glycol 1000, and 10 mM Hepes in RPMI 1640; adjust to pH 7.2. Volume size is dependent on your samples (see Note 1). Store at 4 C. 2. Hypertonic medium with OVA: Add 10 mg/mL OVA to the previously made hypertonic medium (see Note 2). Use OVA products with less than 95% purity (see Note 3). Pre-warm and keep at 37 C. 3. Hypotonic medium: 6 mL of deionized UltraPure water, 9 mL RPMI 1640, to a total volume of 15 mL. Pre-warm and keep at 37 C. 4. CFSE solution: 10 μM of CFSE proliferative dye (see Note 4) in RPMI 1640. Keep at 4 C. 5. RPMI 10 media: 1 mM glutamine, 100 IU/mL penicillin, 100 IU/mL, streptomycin, 10% fetal calf serum (FCS), 90% RPMI 1640. Volume size is dependent on your media bottle. Keep at 4 C. 6. FACS buffer: PBS 1, 1% FBS, 2 mM EDTA.
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7. Phosphate-buffered saline (PBS) 1. 8. Red blood cell (RBC) lysis buffer. 9. 6-well tissue culture plate. 10. 15 and 50 mL conical Falcon tubes. 11. Dissecting pliers and scissors. 12. Insulin syringe with a 28-gauge needle. 13. 70 μm cell strainers. 14. 10 mL syringe plungers. 15. Malassez counting chamber. 16. Fluorescently labelled anti-CD45.1 and anti-CD8α antibodies. 17. Flow cytometers equipped with lasers and emission filters suitable for the analysis of cells stained with the fluorescent antibodies. 18. FlowJo software for flow cytometry data analysis. 2.2 Gamma Irradiation Source
Strictly follow your institutional guidelines for irradiator use, as erroneous operations will result in severe injury. Gamma irradiation is one type of ionizing irradiation that can be used to lethally irradiate cells. The source may be 137cesium, 60cobalt, or highenergy X-rays (see Note 5). Depending on your equipment, 1000–1500 rads (gray) are enough to lethally irradiate single-cell suspensions in a 15 or 50 mL conical tube at room temperature.
2.3
Although transgenic mice can be obtained by different means, we highly recommend that they are derived from Jackson Laboratory or another verified source.
Transgenic Mice
1. BALB/c mice: Mice with this background are very common to obtain; thus, no specific vendor is required (see Note 6). 2. OT-I mice: This TCR transgenic strain is also called C57BL/6Tg (TcraTcrb)1100Mjb/J. We also highly recommend to cross OT-I to a congenic marker, such as B6.SJL-PtprcaPepcb/BoyJ (CD45.1+), to track them in vivo upon adoptive transfer (see Note 7). 3. Batf3 / mice: Batf3-deficient mice is used as an excellent negative control in vivo (see Note 8). We recommend B6.129S(C)-Batf3tm1Kmm/J from Jackson Laboratory.
3
Methods Prepare and store all cells in RPMI 10 media at ice-cold (4 C) temperature (unless indicated otherwise). Important: Procedures for in vitro and in vivo crosspresentation assays are different and should be followed separately.
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Fig. 1 Schematics for in vitro cross-presentation assay. (a) Simplified protocols for preparing cell-associatedOVA: BALB/c splenocytes were incubated in hypertonic medium with OVA and then incubated with hypotonic medium before washing. (b) Simplified protocols for preparing CSFE-labeled OT-I: OT-I cells were purified and incubated with CSFE dilutions before washing. (c) Simplified protocols for final DC-T cell culture: Cellassociated OVA is added to DC first and then CSFE-labeled OT-I cells. About 3 days later, nonadherent cells are harvested for flow cytometry analysis 3.1 In Vitro Assay to Address DC CrossPresenting Capacity 3.1.1 Preparation of Single-Cell Suspensions
DC cross-presentation in vitro assays are described in Fig. 1, and for this assay, all cell populations can be prepared on the same day. 1. DCs: cDC1s were isolated from spleen single-cell suspension through a positive selection of CD11c-magnetic microbead enrichment and subsequently sorted by flow cytometry to a 95–99% purity using the following gating strategy: B220 , CD11c+, MHC IIhigh, XCR1+, CD172a . DC extraction or purification protocols are not covered in this chapter (see Note 9). 2. OT-I cells: Prepare single-cell suspensions from spleens of OT-I mice. We also recommend further purification of CD8+ T cells with antibody-conjugated magnetic beads, though it is not absolutely required (see Note 10). 3. BALB/c splenocytes: Prepare single-cell suspensions from spleen of BALB/c mice (see Note 11). 4. To prepare spleen single-cell suspensions, harvest the spleen from the mouse into 2 mL of cold complete RPMI 10 medium. 5. Section the spleen with scissors in two to three large pieces. 6. Grind spleen pieces with syringe plunger and filter through a 70 μm cell strainer into a 50 mL falcon tube.
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7. Wash the cell strainer with 10 mL of PBS 1. 8. Centrifuge cells at 400 g for 5 min at room temperature. 9. Resuspend the cell pellet with 1 mL of RBC lysis buffer and incubate for 5 min at room temperature. 10. After the RBC lysis, add to cells 10 mL of PBS 1. 11. Centrifuge cells at 400 g for 5 min at 4 C. 12. Count the cells using a Malassez counting chamber. 13. Purify the desired cells, including cDC1 and OT-I CD8 T cells. 3.1.2 Preparation of Labeled OT-I Cells
1. Use 1 107 of CD8+ OT-I T lymphocytes in RPMI 10 (seeNote 12). 2. Spin at 400 g for 4 min at room temperature or 4 C. 3. Remove supernatants, and resuspend in 1 mL of RPMI 10 containing 10 μM CSFE. 4. Incubate for 10 min at 37 C in the dark (see Note 13). 5. Wash cells once with 10 mL of RPMI 1640 and spin again at 400 g for 4 min at room temperature or 4 C (see Note 14). 6. Resuspend in RPMI 10 to a concentration of 5 106 cells/ mL.
3.1.3 Antigen (OVA) Loading of Cells by Osmotic Shock
1. Use at least 4 107 BALB/c splenocytes in RPMI 10 (see Note 15). 2. Spin at 400 g for 4 min at room temperature or 4 C. 3. Remove supernatants and resuspend in 1 mL of pre-warmed hypertonic medium with OVA. 4. Incubate for 10 min at 37 C. 5. Add 13 mL of prewarmed hypotonic medium. 6. Incubate for an additional 2 min at 37 C. 7. Wash the cells twice with 10 mL of cold RPMI 10 by spinning at 400 g for 4 min. 8. Resuspend the cell pellet in RPMI 10 to a concentration of 2.5 107 cells/mL. 9. Gamma-irradiate the cells at 1350 rads (see Note 16).
3.1.4 Cross-Priming of OT-I by DCs
1. Calculate and prepare your samples to have a 1:5 ratio of DC to cell-associated OVA in a final volume of 1–2 mL maximum. Use 1 105 DCs per well in a 6-well tissue culture plate (see Note 17). 2. Gently mix the DCs and OVA-loaded BALB/c splenocytes with a pipette. As a positive control, use 1 ng/mL of OVA peptide 257–264 (SIINFEKL) instead of BALB/c splenocytes. 3. Incubate overnight at a 5% (v/v) CO2 incubator at 37 C.
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Fig. 2 OT-I proliferation analysis for in vitro cross-presentation assay. (a) CFSE staining for CD45.1+CD44+CD8α+ cells for 3 days without any antigens (a), with positive control OVA peptide SIINFEKL (b), and (c) with cell-associated OVA (c)
4. Add next 2 105 CSFE-labeled OT-I cells to each well. 5. Mix gently, and incubate for 60–72 h in a 5% (v/v) CO2 incubator at 37 C (see Note 18). 6. Harvest nonadherent cells in 15 mL Falcon tube and complete with ice-cold PBS 1. 7. Spin the cells at 400 g, 5 min at 4 C, and resuspend in the cell pellet in 100 μL of FACS buffer. 8. Stain nonadherent cells with anti-CD45.1, anti-CD44, and anti-CD8α antibodies at 4 C for 15 min. 9. Wash the cells by completing the staining tube/plate with FACS buffer and then spin at 400 g, 5 min at 4 C. 10. Resuspend cells in 200 μL of FACS buffer and acquire samples on flow cytometer. 11. Analyze OTI proliferation on a flow cytometer through the assessment of CFSE dilution (Fig. 2). 3.2 In Vivo Assay to Address DC CrossPresenting Capacity
Important: Procedures for in vivo cross-presentation assays are different from in vitro assay and described in Fig. 3.
3.2.1 Preparation of OT-I Cells at Day 0
OT-I cells: Prepare single-cell suspensions from spleens of OT-I mice. We also recommend further purification of CD8+ T cells with antibody-conjugated magnetic beads, though it is not absolutely required (see Note 10).
3.2.2 Preparation of Labeled OT-I Cells at Day 0
1. Use 1 107 cells of CD8+ OT-I T lymphocytes in RPMI 10 (see Note 12). 2. Spin at 400 g for 4 min at room temperature or 4 C.
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Fig. 3 Schematics for in vivo cross-presentation assay. Simplified protocol for using cell-associated OVA in vivo: CFSE-labeled OT-I cells were injected intravenously to designated mice at day 0. Cell-associated OVA were then injected intravenously at day 1. After 3 days, immune organs can be harvested to analyze proliferation of the OT-I population
3. Remove supernatants, and resuspend in 1 mL RPMI 10 containing 10 μM CSFE. 4. Incubate for 10 min at 37 C in the dark (see Note 13). 5. Wash cells once with 10 mL of RPMI 1640 and spin again at the same speed (see Note 14). 6. After the last wash, resuspend cell pellet in serum-free RPMI 1640 to a concentration of 10 106 cells/mL. 3.2.3 Injections of Labeled OT-I Cells at Day 0
1. Adoptively transfer 1 106 CFSE-labeled OT-I cells (100 μL of the cell preparation) per mouse intravenously via tail vein injections using an insulin syringe with a 28-gauge needle. 2. Wait for 1 day (see Note 19).
3.2.4 Preparation of Antigen-Loaded Cells at Day 1
1. Prepare single-cell suspensions from spleen of BALB/c mice, as previously described in Subheading 3.2.1. 2. Use at least 4 107 BALB/c splenocytes in RPMI 10 (see Note 15). 3. Spin at 400 g for 4 min at room temperature or 4 C. 4. Remove supernatants, and resuspend in 1 mL of pre-warmed hypertonic medium with OVA. 5. Incubate for 10 min at 37 C. 6. Add 13 mL of prewarmed hypotonic medium. 7. Incubate additional 2 min at 37 C. 8. Wash twice by completing cells with 10 mL of cold RPMI 10 and spinning at 400 g for 4 min at room temperature or 4 C. 9. Resuspend cell pellet in RPMI 10 to a concentration of 2.5 107 cells/mL. 10. Gamma-irradiate at 1350 rads (see Note 16).
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3.2.5 Injection of Antigen-Loaded Cells at Day 1
1. Adoptively transfer 5 106 OVA-loaded BALB/c splenocytes per mouse intravenously via tail vein injections and insulin syringe with a 28-gauge needle. Batf3-deficient mice is highly recommended as a negative control. 2. Wait for 3 days (see Note 19) and harvest the spleen (see Note 20). 3. Prepare single-cell suspension of spleen. 4. Section the spleen with scissors in two to three large pieces. 5. Grind spleen pieces with a syringe plunger and filter through a 70 μm cell strainer into a 50 mL falcon tube. 6. Wash the cell strainer with 10 mL of PBS 1. 7. Centrifuge cells at 400 g for 5 min at room temperature. 8. Resuspend the cell pellet with 1 mL of RBC lysis buffer and incubate for 5 min at room temperature. 9. After the RBC lysis, add to cells 10 mL of PBS 1. 10. Centrifuge cells at 400 g for 5 min at 4 C and resuspend them in 1 mL of FACS buffer. 11. Count the cells using a Malassez counting chamber. 12. Stain at least 5.106 cells with anti-CD45.1, anti-CD44, and anti-CD8α antibodies at 4 C for 15 min. 13. Wash the cells by completing the staining tube/plate with FACS buffer and then spin at 400 g, 5 min at 4 C. 14. Resuspend cells in 200 μL of FACS buffer. 15. Analyze OT-I proliferation on a flow cytometer by evaluating the frequency of adoptively transferred cells expressing CD45.1, CD44, and CD8α (Fig. 4) (see Note 21).
4
Notes 1. It is recommended to make a large (50 mL) stock of hypertonic medium, and store at 4 C for future use. Each sample will only use 1 mL each time. 2. Once OVA is added to the hypertonic medium, use immediately. 3. Highly pure (>95%) versions of OVA contain less immunogenic contaminants and will negatively impact your assay. 4. CFSE should be stored in aliquots to avoid repeated freezing and thawing. Once diluted, it should be kept in the dark and used immediately. 5. These are the same irradiators to generate bone marrow chimeras.
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Fig. 4 OT-I proliferation analysis for in vivo cross-presentation assay. (a) Percentage of OT-I cells (gated on live splenic CD45.1+, CD44+, and CD8α+ cells) in Batf3 / mice 3 days after injection of OT-I cells and cell-associated OVA. (b) Percentage of OT-I cells (gated on live splenic CD45.1+, CD44+, and CD8a+ cells) in C57BL/6 mice 3 days after injection of OT-I cells and cellassociated OVA
6. Please be aware that this strain is only applicable if your DC strain is C57BL/6. Alternatively, B6.129S2-Tap1tm1Arp/J (Tap1 / ) mice can be also used. 7. It is important to differentiate cross-presentation and crosspriming, though they were sometimes used interchangeably. A direct readout for antigen presentation is to measure the presence of specific peptide on MHC class I molecules. In terms of OVA, this antigen/MHC complex could be measured by an antibody 25.D1.16. However, this antibody suffers from low specificity/avidity, as fluorescent signals will not register a huge difference between your negative and positive controls. As a result, a commonly used method is to use cross-primed T cells to measure the extent of cross-presentation. CD8+ T cells from transgenic TCR OT-I mice specifically recognize a SIINFEKL peptide from OVA with its MHC class I molecule H-2Kb. If you cannot acquire OT-I cells, there are two other possibilities: a SIINFEKL-H2-Kb tetramer+ or a CD8+ T cell line that recognizes SIINFEKL and releases IL-2 upon activation. In this chapter we will be using OT-I cells to measure the crosspresentation capacity of DCs. 8. One of the key points in cross-presentation assays is to make sure that CD8+ T cells are exclusively primed by exogenous antigens via cross-presentation, not via the classic MHC class I pathway. In vitro, this could be ensured easily, since antigens are directly added exogenously. In vivo, it would be difficult to interpret if the T cell response is completely driven by
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cross-presentation. To this end, Batf3-deficient mice is highly recommended as a negative control. Batf3-deficient mice lack cDC1s, and a correctly conducted cross-presentation assay will not yield any T cell response in them. 9. It is common to use primary cell culture such as BMDCs. For FACS-sorted cDC1s, you can use a minimum of 1 104 cells. 10. We recommend to purify CD8 T cells using positive selection with anti-CD8a antibodies. 11. A lot of cells will be needed. If you are short on mice, you can also extract lymphocytes from cervical, axillary, brachial, inguinal, and mesenteric lymph nodes. 12. It is recommended to label all OT-I cells that you have. Do not worry about exceeding the listed cell numbers as this CSFE concentration will be excessive anyway. 13. Use aluminum foil to cover up your cells in the conical or tube. 14. CSFE-labeled pellet should look green to naked eyes. 15. You will lose a substantial number of cells after osmotic shock. If you have more cells, feel free to use all the cells you obtained. 16. If possible, you should use more cells per sample, because cellassociated antigen is weakly immunogenic. 17. If you have less cells to begin with, simply recalculate splenocytes and OT-I cells using the ratios indicated. 18. The T cell priming time depends on a lot of factors, and you may to need to harvest earlier or later than 3 days. A time course is highly recommended. 19. Mice need to recover from intravenous tail vein injections. However, you can wait for less than 1 day, if you are confident about your intravenous tail injection skills. You can also wait for up to a month before the next step, since OT-I cells will not die in vivo. 20. You can also extract lymphocytes from cervical, axillary, brachial, or inguinal lymph nodes in order to increase the number of analyzed cells. 21. The cell proliferation of the transferred OT-I cells can also be analyzed by evaluating the dilution of the CFSE dye on gated CD45.1+, CD44+, and CD8α+ cells.
Acknowledgements This work is supported by the National Key R&D Program of China (2018YFA0508300) and the National Natural Science Foundation of China (31570863) to C.Y.Y.
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References 1. Rock KL, Shen L (2005) Cross-presentation: underlying mechanisms and role in immune surveillance. Immunol Rev 207:166–183. https://doi.org/10.1111/j.0105-2896.2005. 00301.x 2. Ackerman AL, Cresswell P (2004) Cellular mechanisms governing cross-presentation of exogenous antigens. Nat Immunol 5(7): 678–684. https://doi.org/10.1038/ni1082 3. Guilliams M, Ginhoux F, Jakubzick C, Naik SH, Onai N, Schraml BU, Segura E, Tussiwand R, Yona S (2014) Dendritic cells, monocytes and macrophages: a unified nomenclature based on ontogeny. Nat Rev Immunol 14(8):571–578. https://doi.org/10.1038/ nri3712 4. den Haan JM, Lehar SM, Bevan MJ (2000) CD8(+) but not CD8( ) dendritic cells crossprime cytotoxic T cells in vivo. J Exp Med 192(12):1685–1696 5. Jung S, Unutmaz D, Wong P, Sano G, De los Santos K, Sparwasser T, Wu S, Vuthoori S, Ko K, Zavala F, Pamer EG, Littman DR, Lang RA (2002) In vivo depletion of CD11c+ dendritic cells abrogates priming of CD8+ T cells by exogenous cell-associated antigens. Immunity 17(2):211–220 6. Hildner K, Edelson BT, Purtha WE, Diamond M, Matsushita H, Kohyama M, Calderon B, Schraml BU, Unanue ER, Diamond MS, Schreiber RD, Murphy TL, Murphy KM (2008) Batf3 deficiency reveals a critical role for CD8alpha+ dendritic cells in cytotoxic T cell immunity. Science 322(5904): 1097–1100. https://doi.org/10.1126/sci ence.1164206 7. Poulin LF, Reyal Y, Uronen-Hansson H, Schraml BU, Sancho D, Murphy KM, Hakansson UK, Moita LF, Agace WW, Bonnet D, Reis e Sousa C (2012) DNGR-1 is a specific and universal marker of mouse and human Batf3dependent dendritic cells in lymphoid and nonlymphoid tissues. Blood 119(25):6052–6062. https://doi.org/10.1182/blood-201201-406967 8. Yamazaki C, Sugiyama M, Ohta T, Hemmi H, Hamada E, Sasaki I, Fukuda Y, Yano T, Nobuoka M, Hirashima T, Iizuka A, Sato K,
Tanaka T, Hoshino K, Kaisho T (2013) Critical roles of a dendritic cell subset expressing a chemokine receptor, XCR1. J Immunol 190(12):6071–6082. https://doi.org/10. 4049/jimmunol.1202798 9. Sancho D, Joffre OP, Keller AM, Rogers NC, Martinez D, Hernanz-Falcon P, Rosewell I, Reis e Sousa C (2009) Identification of a dendritic cell receptor that couples sensing of necrosis to immunity. Nature 458(7240): 8 9 9 – 9 0 3 . h t t p s : // d o i . o r g / 1 0 . 1 0 3 8 / nature07750 10. Helft J, Bottcher J, Chakravarty P, Zelenay S, Huotari J, Schraml BU, Goubau D, Reis e Sousa C (2015) GM-CSF mouse bone marrow cultures comprise a heterogeneous population of CD11c(+)MHCII(+) macrophages and dendritic cells. Immunity 42(6): 1197–1211. https://doi.org/10.1016/j. immuni.2015.05.018 11. Oberkampf M, Guillerey C, Mouries J, Rosenbaum P, Fayolle C, Bobard A, Savina A, Ogier-Denis E, Enninga J, Amigorena S, Leclerc C, Dadaglio G (2018) Mitochondrial reactive oxygen species regulate the induction of CD8(+) T cells by plasmacytoid dendritic cells. Nat Commun 9(1):2241. https://doi. org/10.1038/s41467-018-04686-8 12. Canton J, Blees H, Henry CM, Buck MD, Schulz O, Rogers NC, Childs E, Zelenay S, Rhys H, Domart MC, Collinson L, Alloatti A, Ellison CJ, Amigorena S, Papayannopoulos V, Thomas DC, Randow F, Reis ESC (2021) The receptor DNGR-1 signals for phagosomal rupture to promote cross-presentation of deadcell-associated antigens. Nat Immunol 22(2): 140–153. https://doi.org/10.1038/s41590020-00824-x 13. Ou P, Wen L, Liu X, Huang J, Huang X, Su C, Wang L, Ni H, Reizis B, Yang CY (2019) Thioesterase PPT1 balances viral resistance and efficient T cell crosspriming in dendritic cells. J Exp Med 216(9):2091–2112. https:// doi.org/10.1084/jem.20190041 14. Moore MW, Carbone FR, Bevan MJ (1988) Introduction of soluble protein into the class I pathway of antigen processing and presentation. Cell 54(6):777–785
Chapter 18 Assays to Detect Cross-Dressing by Dendritic Cells In Vivo and In Vitro Alok Das Mohapatra and Pramod K. Srivastava Abstract The presentation of peptides derived from exogenous antigens on major histocompatibility complex (MHC) class I molecules of antigen-presenting cells (APCs), termed cross-presentation, is crucial for the activation of cytotoxic T-lymphocytes during cell-mediated immune response. Typically, the APCs acquire exogenous antigens by (i) endocytosis of soluble antigens present in their external milieu, or (ii) through phagocytosis of dying/dead cancer cells or infected cells, followed by intracellular processing, before presentation by MHC I on the surface, or (iii) uptake of heat shock protein–peptide complexes generated in the antigen donor cells (3). In a fourth new mechanism, preformed peptide–MHC complexes can be directly transferred from the surface of antigen donor cells (i.e., cancer cells or infected cells) to that of APCs, without the need of further processing, in a process referred to as cross-dressing. Recently, the importance of cross-dressing in dendritic cell-mediated antitumor immunity and antiviral immunity has been demonstrated. Here, we describe a protocol to study cross-dressing of dendritic cells with tumor antigens. Key words Dendritic cells, Cross presentation, Cross-dressing, Tumor immunity, SIINFEKL-Kb
1
Introduction Adaptive cell-mediated immune response to cancers and viruses typically involves CD8 T-cell-mediated recognition of antigenic peptides presented in the context of major histocompatibility complex (MHC) class I molecules on antigen-presenting cells (APCs). Conventionally, APCs can present peptides on their surface by either direct presentation or cross-presentation. In direct presentation, professional APCs acquire antigens from different intracellular pathogens by directly getting infected [1]. In cross-presentation, the APCs can acquire exogenous antigens through various mechanisms including micropinocytosis of soluble proteins, receptormediated uptake of heat shock protein–peptide complexes generated inside the cancer or virus-infected cell, and phagocytosis of apoptotic cells [2, 3]. Once internalized, the antigens are processed
Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_18, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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and trimmed by the intracellular machinery including proteasomes, amino terminal-peptidases, cathepsins, or other intracellular proteases to generate precise peptides, which are loaded on preformed MHC class I molecules in specific intracellular compartments (i.e., endoplasmic reticulum, phagosome, endosome, etc.) and exported to the cell surface [2–4]. An alternative way of antigen presentation by uninfected APCs involves the transfer of preformed peptide– MHC complexes from the surface of an infected cell or an abnormal cell such as cancer cell to the APC surface, without the need of further processing and is referred as cross-dressing [5–7]. Although different types of APCs can cross-present model antigens in vitro, dendritic cells (DCs) appear to be the main cross-presenting APCs in vivo [8]. Recently, the importance of cross-dressing in the priming of effective antiviral immunity [6] and tumor immunity [7] by DCs has been demonstrated. Here we describe a protocol to address the cross-dressing of DCs with tumor antigens. Ovalbumin is a model antigen represented by its dominant epitope SIINFEKL presented by the MHC I allele H-2b [9, 10]. The EG7 tumor cells that will be used in this protocol are derived from the C57BL/6 (H-2b) mouse lymphoma cell line EL4, by transfecting them with the plasmid pAc-neo-OVA, which carries a complete copy of chicken ovalbumin (OVA) mRNA and the neomycin (G418) resistance gene. The protocol described here for the in vitro assay of cross-dressing (see Fig. 1) relies on the transfer of SIINFEKL–Kb complexes from the surface of EG7 cells to the bone marrow-derived dendritic cells (BMDCs) of BALB/c mice (H-2d) as monitored by staining with 25-D1.16 antibody that stains SIINFEKL–Kb complexes [11]. Further, the cross-dressing of SIINFEKL–Kb complexes by BALB/c BMDCs was functionally validated by co-culturing the sorted BALB/c BMDCs (pre-cultured with EG7 cells), with CFSE-labeled OT-I cells which are CD8 T-cells with a transgenic T-cell receptor (TCR) specific to SIINFEKL–Kb complexes. The BALB/c BMDCs can induce proliferation of OT-I cells, only when they are cross-dressed with SIINFEKL–Kb complexes (see Fig. 1). Similarly, the protocol described here to address in vivo cross-dressing relies on the transfer of SIINFEKL–Kb complexes from the injected SIINFEKLpulsed EL4 cells to the surface of DCs of H2Kbm1 mice (see Fig. 2). The H-2Kbm1 mice harbor a mutation in Kb that allows the mutant Kbm1 to bind SIINFEKL but prevents the resulting SIINFEKL–Kbm1 complexes from being recognized by the TCR of CD8 T-cells due to an alteration in the region of Kbm1 that interacts with the TCR [12]. Hence, the DCs of H2Kbm1 mice fail to induce proliferation of OT-I cells. However, the same DCs sorted from the draining lymph nodes of H2Kbm1 mice can induce proliferation of OT-I cells, only when they are cross-dressed with SIINFEKL–Kb complexes from the injected SIINFEKL-pulsed EL4 cells.
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Assay for cross-dressing, in vitro SIINFEKL-Kb complex BMDC
EG7 Tumor cells of C57BL/6(H2Kb) origin
Peptide-Kd complex
BMDCs of BALB/c(H2Kd) origin
Co-culture for 12 hours
Sorting and analysis of BMDCs
BMDC
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Cross-dressing- No
Cross-dressing-Yes -Transfer of
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to BALB/c BMDC-Yes
-Transfer of SIINFEKL-Kb to BALB/c BMDC- No
-Induce Proliferation of OT-I CD8+T cells-Yes
-Induce Proliferation of OT-I CD8+T cells- No
-Staining with anti-SIINFEKL-Kb antibody-Yes
-Staining with anti-SIINFEKL-Kb antibody- No
Fig. 1 Schematic representation of assays to address cross-dressing in vitro
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Materials
2.1 In Vitro Assay for Cross-Dressing
1. BALB/c mice. 2. OT-I mice with CD45.1 congenic marker. 3. EL4 and EG7 cell lines. 4. Hanks Balanced Salt Solution (HBSS). 5. Phosphate buffered saline (PBS) 1×. 6. FACS buffer: PBS 1×, 5 mM EDTA, 2% heat-inactivated fetal bovine serum (FBS). 7. Complete RPMI 1640 medium: RPMI 1640 medium, 1% FBS, 1 mM sodium pyruvate, 100 IU/mL penicillin–streptomycin, and 1 mM glutamine. 8. EG7 culture medium: RPMI 1640 medium, 10% FBS, 1 mM sodium pyruvate, 100 IU/mL penicillin–streptomycin, 1 mM glutamine, 1 mM nonessential amino acids, and 50 μM 2-mercaptoethanol.
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Assay for cross-dressing, in vivo - SIINFEKL-Kbm1
Experimental outline
- SIINFEKL-Kb
SIINFEKL pulsed EL4 cells
CFSE labeled OT-I cells
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Co-culture the sorted APCs with CFSE labeled OT-I cells Assess proliferation of OT-I cells
OT-I Proliferation-Yes OT-I Proliferation-No Cross-dressing-Yes
Cross-dressing-No
Fig. 2 Schematic representation of assays to address cross-dressing in vivo
9. Granulocyte-macrophage (GM-CSF).
colony-stimulating
factor
10. SIINFEKL peptide. 11. Mouse Fc receptor block. 12. Antibodies for flow cytometry: anti-mouse CD11c-APC; CD3-PECy7; CD8-Alexa Flour 700; CD45.1-APC; and 25-D1.16-PE. 13. Carboxyfluorescein succinimidyl ester (CFSE)-dye. 14. EasySep™ Mouse CD8+ T-Cell Isolation Kit (Stem Cell). 15. 70 and 100 μm cell strainers. 16. 10-cm2 bacteriological Petri dishes. 17. 15 and 50 mL Falcon® tubes. 18. Mouse dissection tools (scissor, forceps, dissection tray, etc.). 19. Flow cytometer equipped with lasers and emission filters suitable for the analysis of cells stained with the listed antibody panel. 20. FlowJo software for flow cytometry data analysis.
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2.2 In Vivo Assay for Cross-Dressing
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1. H2Kbm1 mice. 2. OT-I mice with CD45.1 congenic marker. 3. Mouse dissection tools (scissor, forceps, dissection tray, etc.). 4. HBSS with Ca2+ and Mg2+. 5. 24-well plates. 6. Collagenase D. 7. DNase I. 8. 26-gauge needles. 9. FACS buffer: PBS 1×, 5 mM EDTA, 2% heat-inactivated FBS. 10. Complete RPMI 1640 medium: RPMI 1640 medium, 1% FBS, 1 mM sodium pyruvate, 100 IU/mL penicillin–streptomycin, and 1 mM glutamine. 11. Carboxyfluorescein succinimidyl ester (CFSE) dye. 12. 50 mL Flacon tubes. 13. 1 mL syringe. 14. 5 mL FACS tube. 15. 100 μm cell strainer. 16. Mouse Fc receptor block. 17. Antibodies for flow cytometry: Anti-mouse CD3-PECy7; CD19-PECy7; CD11c-BV421; MHCII-PercP-Cy5.5; CD8Alexa Flour 700; B220-Brilliant Violet 650; CD11b-FITC; ef-780-live/dead; CD45.1-APC; and CD169-APC. 18. Flow cytometer equipped with lasers and emission filters suitable for the analysis of cells stained with the listed antibody panel. 19. FlowJo software for flow cytometry data analysis.
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Methods
3.1 Assays to Study Cross-Dressing In Vitro (See Fig. 1) 3.1.1 Culture of Bone Marrow-Derived Dendritic Cells (BMDCs)
1. Harvest femurs and tibias of 6–8-week-old BALB/c mice aseptically. 2. After cutting out the ends of these bones, flush out the bone marrow cells with 10–15 mL of HBSS under sterile conditions into sterile 15 mL Falcon tubes, and spin the cell at 400 × g during 5 min at room temperature. 3. Wash the harvested bone marrow cells thoroughly with complete RPMI 1640 medium and culture about 2–3 × 106 cells in complete RPMI 1640 medium supplemented with 20 ng/mL of recombinant murine GM-CSF in 10 cm2 bacteriological Petri dishes.
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4. Incubate the above petri dishes at 37 °C for 7 days to generate BMDCs. 5. After the incubation, harvest the nonadherent cells from the Petri dishes by gentle flushing with complete RPMI 1640 medium and use the BMDCs in subsequent experiments. 3.1.2 Culture of EL4 and EG7 Cells and Pulsing of EG7 Cells with SIINFEKL
1. Culture the EL4 cells in complete RPMI 1640 medium (negative control). 2. Culture EG7 in EG7 culture media. 3. Harvest the EG7 cells from culture into 15 mL Falcon tubes. 4. Wash EG7 cells once with complete medium by centrifugation at 300 g for 5 min at room temperature (RT). 5. Resuspend EG7 cells in minimum volume of medium for SIINFEKL pulsing. 6. Pulse the cells with 100 μM of SIINFEKL for 1 h, and gently disturb the cells every 20 min to push them into suspension. 7. Add 10 mL of complete RPMI 1640 medium and spin the cells 300 g for 5 min at RT. 8. Resuspend pellet in complete RPMI 1640 medium and repeat step 7. 9. Finally, resuspend cells in complete RPMI 1640 medium at a final concentration of 10 × 106 cells/mL.
3.1.3 Detection of CrossDressing of BALB/c BMDCs with SIINFEKL–Kb Complexes
1. Incubate 5 × 106 BALB/c BMDCs with an equal number of EL4 cells (negative control sample) or SIINFEKL-pulsed EG7 (experimental sample) cells in 1 mL final volume of complete RPMI 1640 medium, in triplicates for 12 h at 37 °C in a 24-well tissue culture plate (see Note 1). 2. Harvest and pool the above co-cultured cells from the three identical wells into 15 mL Falcon tubes. 3. Wash the cells twice by filling the tube with HBSS and spinning 300 g for 5 min at RT. 4. Incubate the cells with Fc receptor block for 10 min at RT. 5. Wash the cells by filling the tube with HBSS and spinning 300 g for 5 min at RT. 6. Stain the cells with APC-conjugated anti-mouse CD11c and PE-conjugated 25-D1.16-PE (anti-SIINFEKL) antibodies to detect the presence of SIINFEKL–Kb complexes on the surface of BALB/c BMDCs (see Fig. 3).
3.1.4 Labeling of OT-I Cells with CFSE
1. Harvest inguinal, axillary, brachial, and mesenteric lymph nodes from the OT-I mice. 2. Place them in individual wells of the 24-well plate containing 1 mL of complete RPMI 1640 medium.
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Fig. 3 BALB/c BMDCs present live tumor cell-associated antigens through cross-dressing. Representative zebra plots displaying the percentage of SIINFEKL–Kb-positive BMDCs after 12-h co-culture of BALB/c BMDCs with SIINFEKL-pulsed EG7 cells (live or irradiated [IR]). EG7 cells were pulsed with SIINFEKL as the endogenous expression of SIINFEKL–Kb was below the threshold of detection by the antibody. Data points in the bar diagram represent mean ± SEM (n = 3), ***P = 0.0004
3. Take four 50 mL tubes with one 70 μm cell strainer over a mouth of each of them. 4. Pre-wet the cell strainers by passing through them 2 mL sterile complete RPMI 1640 medium. 5. Then physically crush the lymph nodes over the strainers using the piston base of 1 mL syringes, with intermittent flushing with complete RPMI 1640 medium. 6. Pool the cell suspension and then follow the protocol for negative magnetic enrichment of OT-I CD8 T-cells, using the stem cell kit. 7. Wash the enriched cells with at least ten volumes of PBS 1× once and finally resuspend cells at a concentration of 5 × 106 cells/mL.
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8. If you have 2 mL of enriched OT-I cells at 5 × 106 cells/ml, take this 2 mL in a 50 mL centrifuge tube. 9. Then take 2 mL of PBS 1× in a separate 15 mL centrifuge tube and add 2 μL of 5 mM CFSE to make the final concentration to 5 μM. 10. Immediately add this 2 mL of 5 μM CFSE solution to 2 mL of OT-I cells and mix gently and thoroughly using a 1 mL pipette. 11. Incubate in a 37 °C incubator for 5 min. 12. After 5 min, add complete RPMI 1640 medium up to 50 mL to stop further labeling. 13. Centrifuge the cells at 300 g for 5 min at RT. 14. Wash the cell pellet twice more with complete RPMI 1640 medium by spinning at 300 g for 5 min at RT. 15. Finally, resuspend the cells in 1 mL of complete RPMI 1640 medium and count the cells for further use. 3.1.5 FACS Sorting of BMDCs After Co-Culture with Tumor Cells
1. Co-culture BMDCs with EG7 cells (without pulsing with SIINFEKL) as described in Subheading 3.1.3 (see Note 2). 2. After harvesting the cells from co-culture, label the BMDCs with APC-conjugated anti-mouse CD11c antibody and gate the singlet CD11c+ BMDCs and sort them in to FACS tubes containing 1 mL of sterile RPMI medium with 10% FBS using a flow cytometer (see Fig. 4a). 3. Check the purity of the sorted BMDC population using a very small aliquot of sorted BMDCs and make sure to get high purity, i.e., close to 99% (see Note 3).
3.1.6 Functional Validation of CrossDressing by Co-Culturing Sorted BMDCs with CFSELabeled OT-I Cells
1. After labeling the OT-I cells with CFSE as described in Subheading 3.1.4, count them, and lower their density with complete RPMI 1640 medium to 1 × 106 cells/mL. 2. Count the sorted BMDCs, and co-culture them in complete RPMI 1640 medium in triplicate with CFSE-labeled OT-I cells such that the BMDC to OT-I ratio is 1:4, i.e., for 25,000 DCs, add 100,000 OT-I cells/well (see Note 4). 3. Incubate for 3.5 days at 37 °C. 4. Harvest the co-cultured cells from three identical wells, pool them, and label the OT-I cells using antibodies to CD3, CD8, and the congenic marker CD45.1. 5. Gate the OT-I cells as previously shown [7] (CD3+, CD8+, and CD45.1+) and analyze the proliferation of OT-I cells in terms of dilution of CFSE (see Fig. 4b and Note 5).
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Fig. 4 BALB/c BMDCs cross-dressed with SIINFEKL–Kb complexes induce proliferation of OT-I cells. (a) Representative pseudo-color plots displaying the proportion of CD11c+ BMDCs and EG7 cells in pre-sorted (first plot from the left) and post-sorted (second plot from the left) samples after 12-h co-culture. The two plots in the right represent the SSC and FSC profile of sorted BMDCs. The numbers in the box represent the percentage of population in corresponding gates in the respective plots. (b) Representative histogram plots displaying proliferation of OT-I cells by BALB/c BMDCs pre-cultured with live/IR EG7 cells for 12 h. Data points in the bar diagram represent mean ± SEM (n = 3), ***P = 0.0013 3.2 Assays to Study Cross-Dressing In Vivo (See Fig. 2) 3.2.1 Injection of SIINFEKL-Pulsed EL4 Tumor Cells into H2Kbm1 Mice
1. Pulse EL4 cells Subheading 3.1.2.
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SIINFEKL
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described
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2. Count the SIINFEKL-pulsed EL4 cells and resuspend them in HBSS for injection. 3. Inject intradermally about 10 × 106 SIINFEKL-pulsed EL4 cells resuspended in 100 μL volume of HBSS to both the left and right flank of 20 H2Kbm1 mice.
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3.2.2 Preparation of Single-Cell Suspension from Draining Lymph Nodes
1. Harvest the inguinal and axillary draining lymph nodes of both sides (four LNs per mouse), after 24–30 h of injection of tumor cells (see Note 6). 2. Place 1 mL of Ca+2 and Mg+2 containing HBSS in the first and third rows of a 24-well plate and 1 mL of a mixture of 500 μg/ mL collagenase D and 500 μg/mL DNase I in RPMI, in the second and fourth rows. 3. First, transfer the harvested lymph nodes to individual wells of the above 24-well plate containing HBSS (2 lymph nodes/ well/1 mL HBSS) for washing. 4. After thorough washing, transfer the lymph nodes to the next wells of the 24-well plate, containing a mixture of collagenase D and DNase I in RPMI (1 mL/well/2 lymph nodes) using forceps. 5. Tease apart the lymph nodes in the individual wells of the 24-well plate in the enzyme mixture, using 26-gauge needles, and incubate the tissue fragments for 45 min at 37 °C with intermittent mixing of the digested tissue, every 10 min. 6. Place 100 μm cell strainers on the mouth of individual 50 mL tubes and pre-wet the strainers by passing about 2 mL of FACS buffer through them, down to the bottom of the 50 mL tube. 7. Pipette out the digested lymph node tissue from two different wells using a 1 mL pipette and pass it through the strainer into one 50 mL tube. 8. Then physically crush the larger tissue chunks on the strainers using the back of the 1 mL syringe pistons, and flush everything down through a nylon mesh using ice-cold FACS buffer and collect the single-cell suspension at the bottom of 50 mL tubes. 9. Adjust the volume of single-cell suspension to 10 mL by passing additional FACS buffer through the strainer. 10. After crushing LN tissues from two wells, equivalent to four LNs, immediately transfer the 50 mL tube with cell suspension on to ice (see Note 7). 11. Centrifuge the 50 mL tubes with the 10 mL single-cell suspension at 300 g for 5 min at 4 °C. 12. Resuspend the cell pellet in each 50 mL tube, in 1 mL of FACS buffer, and transfer this 1 mL to 5 mL FACS tubes for antibody staining.
3.2.3 Staining of the Dendritic Cells in the Single-Cell Suspension
1. Pellet the cells in the 5 mL FACS tube by centrifugation at 300 g for 5 min at 4 °C (see Note 8 and 9). 2. Wash the cells once with 1 mL PBS 1× and pellet the cells by centrifugation at 300 g for 5 min at RT.
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3. Resuspend the cell pellet in 100 μL of PBS containing 1× live/ dead dye (eFluor 780) and incubate for 10 min at RT. 4. Wash the cells with 1 mL of FACS buffer by centrifugation at 300 g for 5 min at RT. 5. Discard the supernatant by returning the tube and resuspend the cell pellet in the residual FACS buffer. 6. Add to each sample 2 μL of Fc receptor block and incubate at RT for 10 min. 7. Next, add 100 μL of antibody cocktail containing the indicated antibodies in the Subheading 2.2 at recommended dilutions or using a suitable antibody concentration after titrating individual antibodies (anti-mouse CD-3-PECy7; CD19-PE-Cy7; CD11c-BV421; MHCII-PercP-Cy5.5; CD8-Alexa Flour 700; B220-Brilliant Violet 650; CD11b-FITC; and CD169APC). 8. Incubate the cells with the above antibody cocktail on ice for 30–45 min. 9. Wash the cells once with the 5 mL FACS buffer by centrifugation at 300 g for 5 min at 4 °C. 10. Resuspend the cell pellet of each tube in 100 μL of complete medium, and finally, pool the cell suspension in 20 tubes to get 2 mL of cell suspension. 11. Filter the cell suspension through the 100 μm strainer to avoid any cell clumps. 12. Sort the cells immediately using a flow cytometer (i.e., FACSAria, BD Biosciences). 3.2.4 Sorting and CoCulture of DCs with CFSELabeled OT-I Cells
1. In the CD3- and CD19- population, identify and gate the desired APC subsets, i.e., CD8α+ CD11b- cDC1, CD8αCD11b+ cDC2, B220+ CD8α+/- pDCs, and CD169+ macrophages as shown previously [7], and then sort them in FACS tubes containing 1 mL of sterile RPMI medium with 10% FBS using a flow cytometer. 2. Check the purity of the sorted APC population using a very small aliquot of sorted cells and make sure to get high purity, i.e., close to 99% (see Note 3). 3. While the APCs are being sorted, label the OT-I cells with CFSE as described in Subheading 3.1.4. 4. Once the sorting is done, centrifuge the individual FACS tubes containing sorted cells at 500 g for 5 min at RT. 5. Decant the supernatant by inverting the tube only once, and then pipette out hanging drops of medium from the mouth of the tube, while the tube is still in an inverted position so that residual medium is minimized.
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6. Based on the count of the sorted APCs, add an appropriate volume of complete medium to obtain the desired concentration of sorted cells in the suspension. 7. Set up a co-culture of sorted APCs with CFSE-labeled OT-I cells in 96-well plates in duplicate or triplicate, if possible, with about 25,000 of APCs and 100,000 OT-I cells (1/4 ratio) in 200 μL of final volume of complete RPMI 1640 medium per well. 8. Incubate the co-culture for 3.5 days at 37 °C. 9. Harvest the co-cultured cells from three identical wells, pool them, and label the OT-I cells using antibodies to CD3, CD8, and the congenic marker CD45.1 (as in Subheading 3.1.6). 10. Gate the OT-I cells as per the gating strategy shown previously [7] (see Note 10) (CD3+, CD8+, and CD45.1+) and analyze the proliferation of OT-I cells in terms of dilution of CFSE (see Fig. 5).
Fig. 5 CD8α + DCs effectively present live tumor cell-associated antigens through cross-dressing. (a, b) Graphs displaying proliferation of OT-I cells induced by different APC subsets, sorted from single-cell suspension of skin-draining LNs of H-2Kbm1 mice immunized with 107 SIINFEKL-pulsed live EL4 cells (a) and 107 SIINFEKL-pulsed irradiated EL4 cells (b), respectively. Splenocytes of C57BL/6 mice and H-2Kbm1 mice were pulsed with SIINFEKL and used as positive control and negative control in the OT-I proliferation assay, respectively. Data points in the graph represent mean ± SEM (n = 3), **P value 95% for pDCs. 7. The analysis of the efficiency of pDC isolation from PBMCs is performed by immunostaining and flow cytometry analysis of PBMCs before and after pDC isolation and isolated pDCs [21, 22]. The pDCs are detected by combining detection of the CD123- and BDCA2-specific markers, using PE-conjugated anti-CD123 and mouse APC-conjugated antiBDCA-2, respectively (MACS, Miltenyi Biotec). 8. Two rounds of passage of the cell suspension through the column increase the purity with a minimal loss of pDCs. 9. Adjust the multiplicity of infection (MOI) if needed to avoid the cytopathic effect of the viral infection and adjust based on the pilot experiment of infection and depending on the virus of interest and cell type used. 10. Simoa technology [20]: reagents are purchased from Quanterix (reference 100860) and loaded onto the Simoa HD-1 Analyzer (Quanterix) according to the manufacturer’s instructions and using three-step assay configurations. Briefly, the beads are pelleted with a magnet to remove supernatant. Following several washes, the detector antibody is added, according to the manufacturer’s instructions. The beads are then pelleted with a magnet, followed by washes, and 100 μL of ß-D-galactosidase (SβG) is added. The beads are washed, resuspend in resorufin ß-D-galactopyranoside (RGP) solution, and loaded onto the array. Images of the arrays are analyzed and AEB (average enzyme per bead) values are calculated by the software in the HD-1 Analyzer [20]. Human plasma samples along with calibration curves are measured using the Simoa HD-1 Analyzer. The calibration curves are fit using a 4PLfit with 1/y2 weighting factor and are used to determine the concentrations of the unknown human plasma samples [20]. This analysis is done automatically using the software provided by Quanterix with the Simoa HD-1 Analyzer.
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11. To determine the level of apoptosis by flow cytometry, surfacestained cells are further stained using annexin V and 7-AAD according to the manufacturer’s instructions (BioLegend). Wash the cells by adding 100 μL of Annexin V Binding Buffer (BioLegend), spin the cells at 800 × g for 1 min at 4 °C, discard the supernatant, and fix the cells with 100 μL of PBS, 4% PFA, solution for 30 min at 4 °C. Repeat the washing step using staining buffer, and analyze samples by flow cytometry. 12. The level of viral spread from infected cells to uninfected cells (i.e., transduced using RFP expressing lentivirus prior to cocultures but not the infected cell population) and thus distinguished as RFP+ post-coculture and is thus determined by flow cytometry as the frequency of infected cell population among the RFP+ cell population and similarly in RFPpopulations. 13. Three-dimensional reconstructions of pDC are performed using the Imaris (Bitplane Inc.) software package. Surfaces are created for each staining channel. Surfaces are adjusted at the level of surface details, threshold, and relevant size (number of voxels). Colors and textures are applied according to the immunofluorescent pictures. 14. The Airyscan technology of Zeiss LSM microscopes (e.g., LSM880, 980) allows to obtain a higher resolution as compared to classic confocal microscopy analysis. The classic confocal microscopy analysis consists of a restricted collection of only few photons of the center of the Airy disc formed by light diffraction from an illuminated point, thus enabling obtention of a focused imaging, while losing a lot of photons. Airyscan technology is an area detector consisting of 32 elements that collects all photons of 1.25 Airy units. This detector thus allows the pinhole to be left open and collect more light from the Airy disk at once. The extracted spatial information enables to calculate a single highly resolved pixel with a high sensitivity [40].
Acknowledgments We are grateful to Dr. Brian Webster for critical reading of the manuscript and to our colleagues for encouragement and help. We acknowledge the contribution of SFR Biosciences (UMS3444/CNRS, US8/Inserm, ENS de Lyon, UCBL) including the PLATIM and AniRA-cytometry facilities, especially J. Brocard and S. Dussurgey for technical assistance of imaging and flow cytometry analyses, respectively. We acknowledge the contribution of the EFS Decine-Lyon. This work was supported by grants from the Agence Nationale de la Recherche (ANR JCJCiSYN and ANR-22-CE15-0034-03), the Fondation pour le
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recherche me´dicale (FRM-ANR; IFN-COVID-19), the Agence Nationale pour la Recherche contre le SIDA et les He´patites Virales (ANRS—N21006CR and N19017CR), the UDL/ANR IA ELAN ERC (G19005CC), FINOVI (AO11—collaborating project), and EU H2020 Consortium ZIKAlliance (E16001CA). The PhD and postdoc fellowships for M.R. and A.B. are both sponsored by ANRS. G.J. is awarded by the PhD fellowship program called “Contrats doctoraux Lyon 1 de´die´s `a l’International” from Universite´ Lyon 1. References 1. Reizis B (2019) Plasmacytoid dendritic cells: development, regulation, and function. Immunity 50:37–50 2. Merad M et al (2013) The dendritic cell lineage: ontogeny and function of dendritic cells and their subsets in the steady state and the inflamed setting. Annu Rev Immunol 31: 563–604 3. Crouse J, Kalinke U, Oxenius A (2015) Regulation of antiviral T cell responses by type I interferons. Nat Rev Immunol 15:231–242 4. Makris S, Paulsen M, Johansson C (2017) Type I interferons as regulators of lung inflammation. Front Immunol 8:259 5. Lazear HM, Schoggins JW, Diamond MS (2019) Shared and distinct functions of type I and type III interferons. Immunity 50:907– 923 6. Kim YM, Shin EC (2021) Type I and III interferon responses in SARS-CoV-2 infection. Exp Mol Med 53:750–760 7. Sommereyns C et al (2008) IFN-lambda (IFN-lambda) is expressed in a tissuedependent fashion and primarily acts on epithelial cells in vivo. PLoS Pathog 4:e1000017 8. Esashi E et al (2012) PACSIN1 regulates the TLR7/9-mediated type I interferon response in plasmacytoid dendritic cells. Eur J Immunol 42:573–579 9. Blasius AL et al (2010) Slc15a4, AP-3, and Hermansky-Pudlak syndrome proteins are required for Toll-like receptor signaling in plasmacytoid dendritic cells. Proc Natl Acad Sci U S A 107:19973–19978 10. Sasai M, Linehan MM, Iwasaki A (2010) Bifurcation of Toll-like receptor 9 signaling by adaptor protein 3. Science 329:1530–1534 11. Kumagai Y et al (2009) Cutting Edge: TLR-Dependent viral recognition along with type I IFN positive feedback signaling masks the requirement of viral replication for IFN-{alpha} production in plasmacytoid dendritic cells. J Immunol 182:3960–3964
12. Assil S, Webster B, Dreux M (2015) Regulation of the host antiviral state by intercellular communications. Viruses 7:4707–4733 13. Swiecki M, Colonna M (2015) The multifaceted biology of plasmacytoid dendritic cells. Nat Rev Immunol 15:471–485 14. Bruel T et al (2014) Plasmacytoid dendritic cell dynamics tune interferon-alfa production in SIV-infected cynomolgus macaques. PLoS Pathog 10:e1003915 15. Pichyangkul S et al (2003) A blunted blood plasmacytoid dendritic cell response to an acute systemic viral infection is associated with increased disease severity. J Immunol 171: 5571–5578 16. Swiecki M et al (2010) Plasmacytoid dendritic cell ablation impacts early interferon responses and antiviral NK and CD8(+) T cell accrual. Immunity 33:955–966 17. Swiecki M et al (2013) Plasmacytoid dendritic cells contribute to systemic but not local antiviral responses to HSV infections. PLoS Pathog 9:e1003728 18. Smit JJ, Rudd BD, Lukacs NW (2006) Plasmacytoid dendritic cells inhibit pulmonary immunopathology and promote clearance of respiratory syncytial virus. J Exp Med 203: 1153–1159 19. Webster B et al (2018) Plasmacytoid dendritic cells control dengue and Chikungunya virus infections via IRF7-regulated interferon responses. Elife 7:e34273 20. Venet M et al (2022) Severe COVID-19 patients have impaired plasmacytoid dendritic cellmediated control of SARS-CoV-2-infected cells. medRxiv:2021.09.01.21262969. https://doi. org/10.1101/2021.09.01.21262969 21. Decembre E et al (2014) Sensing of immature particles produced by dengue virus infected cells induces an antiviral response by plasmacytoid dendritic cells. PLoS Pathog 10:e1004434 22. Dreux M et al (2012) Short-range exosomal transfer of viral RNA from infected cells to
Monitoring of Innate Immunity Induced by Cell-Cell Contact plasmacytoid dendritic cells triggers innate immunity. Cell Host Microbe 12:558–570 23. Wieland SF et al (2014) Human plasmacytoid dendritic cells sense lymphocytic choriomeningitis virus-infected cells in vitro. J Virol 88: 752–757 24. Feng Z et al (2015) Human pDCs preferentially sense enveloped hepatitis A virions. J Clin Invest 125(1):169–176 25. Bruni D et al (2015) Viral entry route determines how human plasmacytoid dendritic cells produce type I interferons. Sci Signal 8:ra25 26. Garcia-Nicolas O et al (2016) Sensing of porcine reproductive and respiratory syndrome virus-infected macrophages by plasmacytoid dendritic cells. Front Microbiol 7:771 27. Assil S et al (2019) Sensing of cell-associated HTLV by plasmacytoid dendritic cells is regulated by dense beta-galactoside glycosylation. PLoS Pathog 15:e1007589 28. Assil S et al (2019) Plasmacytoid dendritic cells and infected cells form an interferogenic synapse required for antiviral responses. Cell Host Microbe 25:730–745 e6 29. Webster B, Assil S, Dreux M (2016) Cell-cell sensing of viral infection by plasmacytoid dendritic cells. J Virol 90:10050–10053 30. Yun TJ et al (2021) Human plasmacytoid dendritic cells mount a distinct antiviral response to virus-infected cells. Sci Immunol 6: eabc7302 31. Costa VV et al (2013) Inflammatory and innate immune responses in dengue infection: protection versus disease induction. Am J Pathol 182(6):1950–1961
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Part VI Omic Approaches to Study Dendritic Cells
Chapter 22 Harnessing Single-Cell RNA Sequencing to Identify Dendritic Cell Types, Characterize Their Biological States, and Infer Their Activation Trajectory Ammar Sabir Cheema, Kaibo Duan, Marc Dalod, and Thien-Phong Vu Manh Abstract Dendritic cells (DCs) orchestrate innate and adaptive immunity, by translating the sensing of distinct danger signals into the induction of different effector lymphocyte responses, to induce the defense mechanisms the best suited to face the threat. Hence, DCs are very plastic, which results from two key characteristics. First, DCs encompass distinct cell types specialized in different functions. Second, each DC type can undergo different activation states, fine-tuning its functions depending on its tissue microenvironment and the pathophysiological context, by adapting the output signals it delivers to the input signals it receives. Hence, to better understand DC biology and harness it in the clinic, we must determine which combinations of DC types and activation states mediate which functions and how. To decipher the nature, functions, and regulation of DC types and their physiological activation states, one of the methods that can be harnessed most successfully is ex vivo single-cell RNA sequencing (scRNAseq). However, for new users of this approach, determining which analytics strategy and computational tools to choose can be quite challenging, considering the rapid evolution and broad burgeoning in the field. In addition, awareness must be raised on the need for specific, robust, and tractable strategies to annotate cells for cell type identity and activation states. It is also important to emphasize the necessity of examining whether similar cell activation trajectories are inferred by using different, complementary methods. In this chapter, we take these issues into account for providing a pipeline for scRNAseq analysis and illustrating it with a tutorial reanalyzing a public dataset of mononuclear phagocytes isolated from the lungs of naı¨ve or tumor-bearing mice. We describe this pipeline step-by-step, including data quality controls, dimensionality reduction, cell clustering, cell cluster annotation, inference of the cell activation trajectories, and investigation of the underpinning molecular regulation. It is accompanied with a more complete tutorial on GitHub. We hope that this method will be helpful for both wet lab and bioinformatics researchers interested in harnessing scRNAseq data for deciphering the biology of DCs or other cell types and that it will contribute to establishing high standards in the field. Key words Dendritic cell types, cDC1, Single-cell RNA sequencing, Computational pipeline, Seurat, Monocle, Velocyto
Vanja Sisirak (ed.), Dendritic Cells: Methods and Protocols, Methods in Molecular Biology, vol. 2618, https://doi.org/10.1007/978-1-0716-2938-3_22, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023
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Introduction Dendritic cells (DCs) are immune cells that can sense a variety of danger signals and respond to it by delivering specific output signals to effector lymphocytes, including innate lymphoid cells and T cells, to orchestrate innate and adaptive immunity towards mounting the responses the best suited to face the threat [1]. Hence, depending on the pathophysiological context, DCs can polarize immune responses towards different and even opposite functions, namely, tolerance or immunosuppression versus immunity, including by inducing CD4 T cell responses efficient against viral infections or cancer (e.g., type 1 helper responses, Th1), bacterial or fungal infections (e.g., Th17), or worm infestation (e.g., Th2). This functional plasticity of DCs results from two key characteristics [1]. First, DCs encompass distinct cell types specialized in the polarization of immune responses towards different functions. For example, type 1 conventional DCs (cDC1s) excel in the activation of naı¨ve CD8 T cells against intracellular pathogens or tumor cells and are thus critical for host defense against viral infections and cancer [2, 3]. Second, each DC type can exert different functions depending on its activation state, which is instructed by input signals derived from the tissue microenvironment and from the pathophysiological context. For example, the mature cDC1s present in the thymus or migrating from nonlymphoid organs to their draining lymph nodes at steady state are tolerogenic, whereas cDC1s that have matured under conditions of stimulation with pathogen-associated molecular patterns are immunogenic [4]. Hence, one of the currently very active lines of research in the DC field is to understand how precisely DCs promote protective immune responses in individuals overcoming infections or cancer, or on the contrary are paralyzed or even hijacked by pathogens or the tumor microenvironment in individuals who harbor enhanced susceptibility to the disease. In other words, researchers aim at understanding which combinations of DC types and activation states are protective or on the contrary deleterious for host defense against infections or cancer, what corresponding output signals DCs deliver to effector lymphocytes, and which input signals instruct these DC responses. To decipher the nature, functions, and regulation of DC types and their physiological activation states, one of the methods that can be harnessed most successfully is the generation and analysis of single-cell RNA sequencing (scRNAseq) data from the cells directly isolated from diseased tissues versus their normal counterpart. Indeed, scRNAseq analyses represent a very powerful and unbiased approach to identify and characterize in depth the DCs that are naturally present in vivo in various tissues under different pathophysiological conditions and to decipher their functional
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heterogeneity [5–8]. This approach is especially useful to help generate hypotheses on the functions of DC types and their activation states, because of the very high resolution of the co-expressed gene modules identified and the statistical power reached when mining them for functional annotation enrichment or for predictions of receptor/ligand-based interactions with other cell types [6–9]. Moreover, this approach is especially well suited to help generate hypotheses on the underpinning molecular regulation, by integrating the gene expression profiles of the different DC activation states to infer their relationships, namely, to define the activation trajectory of the DCs, and to identify the corresponding pathways based on in silico identification of the upstream regulators [6–8]. However, specific strategies are required to annotate the cell clusters for cell type identity and activation states in a manner that is the most unbiased, robust, tractable, and reproducible as possible. In addition, caution must also be exerted in how the cell activation trajectories are inferred and interpreted from scRNAseq data, calling for the use of different and complementary methods based on distinct mathematical formalisms to examine whether they converge towards similar results [7]. In this chapter, we provide a tutorial proposing and illustrating a pipeline for scRNAseq analysis to identify DC types, characterize their biological states, and infer their activation trajectory. We describe in detail the different steps of this pipeline, from the quality controls of the data to the inference of the cell activation trajectories and of the underpinning molecular regulation, including key steps of dimensionality reduction, cell clustering, and annotation of cells for cell type identity and activation states. We use the proposed pipeline to reanalyze a public dataset from mononuclear phagocytes isolated from the lungs of mice engrafted with murine lung adenocarcinoma cells, in which analysis by the authors of the original paper enabled the identification and characterization of a regulatory program limiting the immunogenicity of tumorassociated cDC1s [6]. This dataset was especially suited for our purpose for four reasons: first, the high quality of the data and metadata; second, the inclusion of a series of distinct cell types and activation states, including mature cDC1s and cDC2s that are notoriously difficult to discriminate from one another based only on gene expression analysis, because maturation leads to transcriptional convergence of DC types, including the down-modulation of many of the genes constituting their steady-state transcriptomic fingerprint [4, 7, 10, 11]; third, the inclusion of data on the phenotype of the cells, which enabled independent checking of the accuracy of our assignment of cell type identities and activation states based only on gene expression profiling; and fourth, encompassing two different pathophysiological conditions, making it possible to assess whether and how this impacted activation trajectory inference. We hope that this pipeline and the corresponding
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tutorial will be helpful for both wet lab and bioinformatics researchers interested in harnessing scRNAseq data for deciphering the biology of DCs or other cell types and that it will contribute to establishing high standards in the field.
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Materials In this section, we will set up the environment for performing the analyses, by downloading the files required and by listing the bioinformatics programs or packages that will be used.
2.1 List of Files to Download
In order to run the analyses, several files need to be downloaded: 1. Four input files: the two preprocessed raw counts of scRNAseq data (one file for naı¨ve and one file for tumor-bearing lungs), the two metadata files containing the antibody-derived tag (ADT) information, corresponding to the original publication [6]. 2. Two “ImmGen phase 1” files that are both necessary for the generation of the signature files used for the connectivity map (CMAP) analysis [12], one expression file containing the normalized gene expression data (.gct) and one class file providing the cell type identity for each sample/microarray (.cls). 3. Two signature files used as inputs for the CMAP analysis (one for positive and one for negative signatures), in case one wants to skip the signature generation step. 4. Two .R scripts necessary to run single-cell CMAP analyses, in order to assess the enrichment of transcriptomic signatures on single cells, for cell type identification. 5. Although not mandatory, we provide a Docker image in order to simplify the reproducibility of our analyses.
2.2 Download the Input Files
1. Download the expression and metadata files from mouse CD45+ Lin- MHCII+ CD11c+ cells isolated from normal or tumor-bearing lungs [6], encompassing type 1 conventional dendritic cells (cDC1s), from the Gene Expression Omnibus (GEO) website. The GEO accession number is GSE131957 and description of this dataset can be found here https://www. ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE131957. The download links are as follows: https://ftp.ncbi.nlm.nih.gov/geo/samples/GSM3 832nnn/GSM3832735/suppl/GSM3832735_wt_naive_gex. csv.gz https://ftp.ncbi.nlm.nih.gov/geo/samples/GSM3832nnn/ GSM3832736/suppl/GSM3832736_wt_naive_adt.csv.gz
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https://ftp.ncbi.nlm.nih.gov/geo/samples/GSM3832nnn/ GSM3832737/suppl/GSM3832737_wt_tumor_gex.csv.gz https://ftp.ncbi.nlm.nih.gov/geo/samples/GSM3832nnn/ GSM3832738/suppl/GSM3832738_wt_tumor_adt.csv.gz 2. Uncompress these files (an example is shown for only one of the four files, for Linux and Mac users) (see Notes 1 and 2): ↝gunzip GSM3832735_wt_naive_gex.csv.gz
2.3 Download the Files for the Signature Generation
Download from our Zenodo repository the Microarray Phase 1 expression (.gct) and class (.cls) files (https://doi.org/10. 5281/zenodo.5511970), provided in the correct formats (https:// software.broadinstitute.org/cancer/software/gsea/wiki/index. php/Data_formats). The positive and negative signature files can also be downloaded directly in case one wants to skip the signature generation (https://doi.org/10.5281/zenodo.5511975).
2.4 Download the .R Scripts to Run SingleCell CMAP
Download from our GitHub repository the two .R scripts that will be used to run CMAP on the scRNAseq dataset (https://github. com/SIgN-Bioinformatics/sgCMAP_R_Scripts/tree/main/ sgCMAP_R_Scripts).
2.5 Download the Docker File
The easiest way to reproduce this workflow is to load and run the Docker image that we provide (see below on how to use it). This image was generated in Linux and can be loaded directly by Linux and Mac users, after having installed Docker (https://docs.docker. com/get-docker/). Windows users can theoretically use this image as well (https://www.docker.com/blog/preview-linux-containerson-windows). However, if for any reason, Docker cannot be installed/used, an alternative solution is to download each software/package (described below) independently. Download the Docker image from this link (https://doi.org/ 10.5281/zenodo.5385611), and then load the image (you need administrator privileges): ↝docker load -i /mdalab_cdc1_maturation.tar
Run the Docker container from the Docker image (Linux and Mac users) (see Note 3): ↝docker run --name DC1_maturation -d -p 8181:8787 -v /home/ $USER:/home/$USER/ -e USER=$(whoami) -e USERID=$(id -u) -e GROUPID=$(id -g) -e PASSWORD= -t mdalab_cdc1_maturation
To use this container on a local computer, type in the address bar of your browser: ⤇localhost:8181
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To use this Docker on a remote server, type in the address bar of your browser: ⤇:8181
The browser will display an RStudio screen asking for username and password. Type the session user and the password () provided to run the container. The RStudio environment will open with all required packages in the correct version already installed. 2.6 Programs and Packages Used in This Workflow
This workflow for analyzing scRNAseq data is performed mostly under the R statistical environment, which can be downloaded from http://www.r-project.org. We recommend using RStudio, a set of tools interfacing with R, in order to simplify the usage of R (https://www.rstudio.com/products/rstudio/download/). Below is the list of the main R packages used in our workflow (see Note 4). All these packages do not need to be installed when using our Docker image. 1. Seurat (v 4.0) Seurat enables performing several key steps of scRNAseq data analyses: quality checks, filtering cells and genes, clustering cells, and performing dimensionality reduction and visualization (see Note 5). It can be downloaded from https://satijalab. org/seurat/ [13]. 2. Scater (v 1.18.6) Here, we use the Scater toolkit specifically to calculate the cutoff of mitochondrial gene expression for filtering dying cells, which are known to harbor a higher ratio of mitochondrial to nuclear DNA content (http://bioconductor.org/ packages/scater) [14]. 3. Monocle (v 3.1) Monocle investigates cell trajectories and the dynamics of gene expression over the pseudo-time computed along these trajectories (https://cole-trapnell-lab.github.io/monocle3/) [15]. 4. Velocyto (v 0.6) RNA velocity analysis predicts the future direction in which cells are moving in the transcriptional space by estimating, for each cell, the time derivative of RNA abundance (http:// velocyto.org/) [16]. In other words, Velocyto computes for each cell a vector predicting its future transcriptional state, by integrating the unspliced versus spliced mRNA ratio for many genes, in order to project a vector field reflecting the predicted activation trajectory of the cells.
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5. SeuratWrappers (v 0.3) SeuratWrappers is a collection of methods and extensions provided by the bioinformatics community and curated by the Satija Lab. These methods include functionalities not initially present in Seurat. In this chapter, we will use functions which simplify the RNA velocity analysis (https://github.com/ satijalab/seurat-wrappers). 6. ggplot2 (v 3.3.2) ggplot2 is an R package used for data visualization (https://ggplot2.tidyverse.org/). 7. enrichR (v 3.0) enrichR provides an interface to the Enrichr database. It is used to calculate statistical enrichment of functional annotations based on gene lists and gene annotation databases of i n t e r e s t ( h t t p s : // C R A N . R - p r o j e c t . o r g / p a c k a g e = enrichR) [17]. 8. BubbleGUM (v 1.3.19) In addition to R, we also use BubbleGUM, a java-based computational tool used here to automatically extract signatures based on transcriptomic data. It is available at http:// www.ciml.univ-mrs.fr/applications/BubbleGUM/index. html [18].
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Methods
3.1 Running the Seurat Workflow on All the Cells from the Original Data File
The workflow described in this chapter is also provided as a Markdown file (.md) on GitHub (https://github.com/DalodLab/ MDlab_cDC1_differentiation/blob/main/scRNAseq_pipe line.md). In this file, there are extra command lines that were not included here due to space limitations. These extra command lines include supplementary quality checks and figures that are helpful for the analysis of the dataset. 1. Organize the files Put the four input files into a single separate folder, named input_files. In the Console of RStudio, set the working directory to the folder containing the input files (see Note 6): ➤setwd("/input_files/")
2. Read the input files • Read the two expression files for naive lungs and for tumorbearing lungs: ➤naive_counts