Stress Responses: Methods and Protocols [1 ed.] 1493925210, 9781493925216

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Methods in Molecular Biology 1292

Christine M. Oslowski Editor

Stress Responses Methods and Protocols

METHODS

IN

MOLECULAR BIOLOGY

Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK

For further volumes: http://www.springer.com/series/7651

Stress Responses Methods and Protocols

Edited by

Christine M. Oslowski Wentworth Institute of Technology, Boston, MA, USA

Editor Christine M. Oslowski Wentworth Institute of Technology Boston, MA, USA

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-4939-2521-6 ISBN 978-1-4939-2522-3 (eBook) DOI 10.1007/978-1-4939-2522-3 Library of Congress Control Number: 2015934151 Springer New York Heidelberg Dordrecht London © Springer Science+Business Media New York 2015 This work is subject to copyright. All rights are reserved 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, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Humana Press is a brand of Springer Springer Science+Business Media LLC New York is part of Springer Science+Business Media (www.springer.com)

Preface Cells are bombarded by stresses on a regular basis. Luckily, cells are armed with several mechanisms to mitigate cell stress and promote cell survival. However, under severe stress conditions, cells undergo dysfunction and ultimately death. This volume of Methods in Molecular Biology includes an array of protocols to detect and study the different cellular stresses, measure their pathological consequences within the cell, and investigate the role of cellular stresses in select diseases. Understanding the mechanisms of the multiple cellular pathways and outcomes triggered by such stresses will lead to the development of novel therapeutics to prevent or treat disease. At the conclusion of this volume, reviews on the crosstalk between different pathways, stress responses during ageing, and targeting stress are included. Boston, MA, USA

Christine M. Oslowski

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Contents Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

v ix

PART I ASSAYS FOR DETECTING AND CHARACTERIZING A VARIETY OF CELLULAR PROCESSES UNDER CELL STRESS 1 Methods for Studying ER Stress and UPR Markers in Human Cells . . . . . . . . Donna Kennedy, Afshin Samali, and Richard Jäger 2 Assays for Induction of the Unfolded Protein Response and Selective Activation of the Three Major Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ananya Gupta, Danielle E. Read, and Sanjeev Gupta 3 Assays to Characterize Molecular Chaperone Function In Vitro. . . . . . . . . . . . Martin Haslbeck and Johannes Buchner 4 Analysis of the Heat Shock Factor Complex in Mammalian HSP70 Promoter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mitsuaki Fujimoto, Ryosuke Takii, Naoki Hayashida, and Akira Nakai 5 Immunofluorescence-Based Methods to Monitor DNA End Resection . . . . . . Bipasha Mukherjee, Nozomi Tomimatsu, and Sandeep Burma 6 Visualizing the Spatiotemporal Dynamics of DNA Damage in Budding Yeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chihiro Horigome, Vincent Dion, Andrew Seeber, Lutz R. Gehlen, and Susan M. Gasser 7 Detecting Reactive Oxygen Species by Immunohistochemistry . . . . . . . . . . . . Geou-Yarh Liou and Peter Storz 8 Investigating Inflammasome Activation Under Conditions of Cellular Stress and Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Clare C. Cunningham, Emma M. Corr, Donal J. Cox, and Aisling Dunne 9 Methods for Studying microRNA Functions During Stress . . . . . . . . . . . . . . . Yoshinari Ando and Anthony K.L. Leung 10 Measuring Autophagy in Stressed Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marina N. Sharifi, Erin E. Mowers, Lauren E. Drake, and Kay F. Macleod 11 Detection of Apoptosis Using Fluorescent Probes . . . . . . . . . . . . . . . . . . . . . . Grishma Khanal, Himali Somaweera, Meicong Dong, Todd Germain, Megan Ansari, and Dimitri Pappas

PART II

3

19 39

53 67

77

97

105 115 129

151

STUDYING CELL STRESS IN THE CONTEXT OF DISEASE

12 Measuring Death of Pancreatic Beta Cells in Response to Stress and Cytotoxic T Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jibran A. Wali, Prerak Trivedi, Thomas W. Kay, and Helen E. Thomas

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Contents

13 Adaptation of the Secretory Pathway in Cancer Through IRE1 Signaling . . . . Stéphanie Lhomond, Nestor Pallares, Kim Barroso, Kathleen Schmit, Nicolas Dejeans, Hélèna Fazli, Saïd Taouji, John B. Patterson, and Eric Chevet 14 Studying Nitrosative Stress in Parkinson’s Disease . . . . . . . . . . . . . . . . . . . . . . Kenny K.K. Chung

PART III

177

195

PERSPECTIVES

15 Cross Talk Between ER Stress, Oxidative Stress, and Inflammation in Health and Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aditya Dandekar, Roberto Mendez, and Kezhong Zhang 16 Stress Responses During Ageing: Molecular Pathways Regulating Protein Homeostasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emmanouil Kyriakakis, Andrea Princz, and Nektarios Tavernarakis 17 Targeting Stress Responses for Regenerative Medicine. . . . . . . . . . . . . . . . . . . Irina Milisav, Samo Ribarič, and Dušan Šuput Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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215 235 245

Contributors YOSHINARI ANDO • Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA MEGAN ANSARI • Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA KIM BARROSO • Inserm, U1053, Bordeaux, France; Université de Bordeaux, Bordeaux, France; ER440, Oncogenesis, Stress & Signaling, Université Rennes 1, Centre de Lutte Contre le Cancer Eugène Marquis, Rennes, France JOHANNES BUCHNER • Munich Center for Integrated Protein Science (CIPSM) and Department Chemie, Technische Universität München, Garching, Germany SANDEEP BURMA • Division of Molecular Radiation Biology, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA ERIC CHEVET • Inserm, U1053, Bordeaux, France; Université de Bordeaux, Bordeaux, France; ER440, Oncogenesis, Stress & Signaling, Université Rennes 1, Centre de Lutte Contre le Cancer Eugène Marquis, Rennes, France KENNY K.K. CHUNG • Division of Life Science, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Hong Kong, China EMMA M. CORR • Molecular Immunology Group, School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, College Green, Dublin 2, Ireland DONAL J. COX • Molecular Immunology Group, School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, College Green, Dublin 2, Ireland CLARE C. CUNNINGHAM • Molecular Immunology Group, School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, College Green, Dublin 2, Ireland ADITYA DANDEKAR • Department of Immunology and Microbiology, Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA NICOLAS DEJEANS • Inserm, U1053, Bordeaux, France; Université de Bordeaux, Bordeaux, France VINCENT DION • Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland; Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland MEICONG DONG • Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA LAUREN E. DRAKE • The Ben May Department for Cancer Research, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA; The Committee on Molecular Pathogenesis and Molecular Medicine, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA AISLING DUNNE • Molecular Immunology Group, School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, College Green, Dublin 2, Ireland HÉLÈNA FAZLI • Inserm, U1053, Bordeaux, France; Université de Bordeaux, Bordeaux, France MITSUAKI FUJIMOTO • Departments of Biochemistry and Molecular Biology, Yamaguchi University School of Medicine, Minami-Kogushi Ube, Japan

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Contributors

SUSAN M. GASSER • Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland LUTZ R. GEHLEN • Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland TODD GERMAIN • Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA ANANYA GUPTA • Discipline of Pathology, School of Medicine, Clinical Science Institute, National University of Ireland, Galway, Ireland SANJEEV GUPTA • Discipline of Pathology, School of Medicine, Clinical Science Institute, National University of Ireland, Galway, Ireland MARTIN HASLBECK • Munich Center for Integrated Protein Science (CIPSM) and Department Chemie, Technische Universität München, Garching, Germany NAOKI HAYASHIDA • Departments of Biochemistry and Molecular Biology, Yamaguchi University School of Medicine, Minami-Kogushi Ube, Japan CHIHIRO HORIGOME • Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland RICHARD JÄGER • Department of Natural Sciences, Bonn-Rhein-Sieg University of Applied Sciences, Rheinbach, Germany THOMAS W. KAY • St. Vincent’s Institute of Medical Research, Fitzroy, Australia; Department of Medicine, St. Vincent’s Hospital,The University of Melbourne, Fitzroy, Australia DONNA KENNEDY • Apoptosis Research Centre (ARC), National University of Ireland, Galway, Dangan, Ireland GRISHMA KHANAL • Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA EMMANOUIL KYRIAKAKIS • Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Plastira, Crete, Greece ANTHONY K.L. LEUNG • Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA STÉPHANIE LHOMOND • Inserm, U1053, Bordeaux, France; Université de Bordeaux, Bordeaux, France GEOU-YARH LIOU • Department of Cancer Biology, Mayo Clinic, Jacksonville, FL, USA KAY F. MACLEOD • The Ben May Department for Cancer Research, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA; The Committee on Cancer Biology, The Gordon Center for Integrative Sciences, The University of Chicago,, Chicago, IL, USA; The Committee on Molecular Pathogenesis and Molecular Medicine, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA ROBERTO MENDEZ • Center for Molecular Medicine and Genetics, Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA IRINA MILISAV • Faculty of Medicine, Institute of Pathophysiology, University of Ljubljana, Ljubljana, Slovenia ERIN E. MOWERS • The Ben May Department for Cancer Research, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA; Medical Scientist Training Program, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA BIPASHA MUKHERJEE • Division of Molecular Radiation Biology, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA AKIRA NAKAI • Departments of Biochemistry and Molecular Biology, Yamaguchi University School of Medicine, Minami-Kogushi Ube, Japan NESTOR PALLARES • Inserm, U1053, Bordeaux, France; Université de Bordeaux, Bordeaux, France

Contributors

xi

DIMITRI PAPPAS • Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA JOHN B. PATTERSON • MannKind Corporation, Valencia, CA, USA ANDREA PRINCZ • Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Plastira, Crete, Greece DANIELLE E. READ • Discipline of Pathology, School of Medicine, National University of Ireland, Galway, Ireland SAMO RIBARIČ • Faculty of Medicine, Institute of Pathophysiology, University of Ljubljana, Ljubljana, Slovenia AFSHIN SAMALI • Apoptosis Research Centre (ARC), National University of Ireland, Galway, Dangan, Ireland KATHLEEN SCHMIT • Inserm, U1053, Bordeaux, France; Université de Bordeaux, Bordeaux, France ANDREW SEEBER • Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland; Faculty of Natural Sciences, University of Basel, Basel, Switzerland MARINA N. SHARIFI • The Ben May Department for Cancer Research, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA; The Committee on Cancer Biology, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA; The Medical Scientist Training Program, The Gordon Center for Integrative Sciences, The University of Chicago, Chicago, IL, USA HIMALI SOMAWEERA • Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, USA PETER STORZ • Department of Cancer Biology, Mayo Clinic, Jacksonville, FL, USA DUŠAN ŠUPUT • Faculty of Medicine, Institute of Pathophysiology, University of Ljubljana, Ljubljana, Slovenia RYOSUKE TAKII • Departments of Biochemistry and Molecular Biology, Yamaguchi University School of Medicine, Minami-Kogushi Ube, Japan SAÏD TAOUJI • Inserm, U1053, Bordeaux, France; Université de Bordeaux, Bordeaux, France NEKTARIOS TAVERNARAKIS • Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Crete, Greece; Department of Basic Sciences, Faculty of Medicine, University of Crete, Crete, Greece HELEN E. THOMAS • St. Vincent’s Institute of Medical Research, Fitzroy, Australia; Department of Medicine, St. Vincent’s Hospital, The University of Melbourne, Fitzroy, Australia NOZOMI TOMIMATSU • Division of Molecular Radiation Biology, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA PRERAK TRIVEDI • St. Vincent’s Institute of Medical Research, Fitzroy, Australia; Department of Medicine, St. Vincent’s Hospital, The University of Melbourne, Fitzroy, Australia JIBRAN A. WALI • St. Vincent’s Institute of Medical Research, Fitzroy, Australia; Department of Medicine, St. Vincent’s Hospital, The University of Melbourne, Fitzroy, Australia KEZHONG ZHANG • Center for Molecular Medicine and Genetics, Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA; Department of Immunology and Microbiology, Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA; Tumor Microenvironment Program, Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA

Part I Assays for Detecting and Characterizing a Variety of Cellular Processes Under Cell Stress

Chapter 1 Methods for Studying ER Stress and UPR Markers in Human Cells Donna Kennedy, Afshin Samali, and Richard Jäger Abstract Many experimentally induced or disease-related cellular dysfunctions stress the endoplasmic reticulum, commonly resulting in an accumulation of unfolded proteins in the ER lumen which is sensed by three ER-resident transmembrane proteins, PERK, ATF6, and IRE1. Their activation by such ER stress affects the unfolded protein response, which consists of a shutoff of protein translation and at the same time the switching-on of specific transcription factors that control genes which function to reduce the burden of unfolded proteins to the ER. Here, we describe two sets of methods for monitoring the occurrence of ER stress and UPR signaling in human cells by analyzing markers of activation of all three ER stress sensor proteins. The first set of methods is based on the qualitative and quantitative analysis of UPR-induced transcripts by qPCR. The second set of methods consists of Western blot-based analysis of UPR-induced proteins or protein modifications. Their combined analysis allows assessment of activation of all three ER stress-activated signaling pathways that in combination are characteristic for the UPR. Key words PERK, ATF6, IRE1, ATF4, XBP1, Real-time PCR, qPCR, Western blot

1

Introduction Proper functioning of the endoplasmic reticulum (ER) is vital for cellular physiology since this large cell organelle serves for the correct folding and posttranslational modification of secreted and transmembrane proteins and also of many proteins located in cell organelles. Furthermore, the ER is involved in membrane biogenesis and Ca2+ homeostasis. In recent years it has become apparent that many functional impairments of the ER manifest in an accumulation of unfolded or misfolded proteins. These evoke a stereotypic stress response that is termed the unfolded protein response (UPR) [1]. The UPR aims to restore proper ER functioning by reducing protein load and increasing the ER’s capacity to fold proteins and remove misfolded ones. However, the UPR can switch on apoptotic programs when ER stress is too severe to be resolved [2]. It is now well established that ER stress and the UPR are involved in many human diseases [1].

Christine M. Oslowski (ed.), Stress Responses: Methods and Protocols, Methods in Molecular Biology, vol. 1292, DOI 10.1007/978-1-4939-2522-3_1, © Springer Science+Business Media New York 2015

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Donna Kennedy et al.

ER stress is sensed by three ER-resident transmembrane proteins that subsequently affect the UPR. These ER stress-sensing and transducing proteins are PERK, ATF6, and IRE1 [1]. PERK is a serine-threonine kinase that autophosphorylates upon activation and then mediates phosphorylation of eukaryotic initiation factor 2 alpha (eIF2α) which leads to a block of general translation, thus lowering the protein load of the ER [2]. However, in the presence of phospho-eIF2α (p-eIF2α), otherwise nontranslated open reading frames on specific mRNAs become preferentially translated. One such mRNA encodes a transcription factor, ATF4, that regulates stress-induced genes [3]. Among those is another transcription factor, CHOP, whose mRNA is likewise preferentially translated in the presence of p-eIF2α [4, 5]. Under conditions of ER stress, the 90 kDa ATF6 becomes transported to the Golgi apparatus where it becomes cleaved, thus liberating the 50 kDa cytoplasmic N-terminal part which is an active transcription factor that translocates to the nucleus and controls several ER stress-induced genes [6]. ER stress leads to multimerization of IRE1 and subsequent activation of its RNase domain that is located at the cytoplasmic side. This specifically mediates the splicing of 26 nucleotides from the central part of the mRNA of XBP1 [7]. The resulting frameshift generates a novel C-terminus conferring transactivation function. The generated XBP1s protein is a potent transcription factor that controls several ER stress-induced genes. Thus, activation of each of these three ER stress sensors leads to expression of a specific transcription factor. The concerted activity of these transcription factors then switches on genetic programs aimed at restoring ER homeostasis. In this article we describe validated and reliable methods to monitor ER stress and UPR activation in human cells or tissues by analyzing components of the UPR. These methods are purely analytical and do not require prior chemical or genetic manipulations of cells or tissues. Complementary methods which involve the genetic manipulation of cells or tissues (to introduce reporter gene constructs) have recently been described elsewhere [8]. We describe two sets of methods. The first set comprises RNAbased methods. These consist of the isolation and reverse transcription of RNA into cDNA, which is subsequently analyzed either by conventional PCR (semiquantitative analysis of XBP1 splicing) or by quantitative PCR (qPCR analysis of XBP1 splicing and of UPR marker gene expression). The second set comprises the Western blot-based analysis of UPR marker proteins. Together, these methods are suited to monitor activation of all three arms of the UPR. For instance, ATF4 protein expression and detection of p-eIF2α are indicative of PERK activation. Transcription of CHOP is dependent on both ATF4 and ATF6, and translation of the CHOP mRNA requires eIF2α phosphorylation. Thus CHOP can serve as

Analysis of UPR in Human Cells

5

a marker of the PERK and of the ATF6 arm of the UPR. Expression levels of GRP78, p58IPK, and ERP72 indicate ATF6 activation more specifically [9]. In addition, ATF6 activation can be monitored on the protein level by detection of the active cleavage product. XBP1 splicing can be directly assessed on the mRNA level, and transcription of EDEM is indicative of XBP1 splicing, whereas HERP expression is driven by both ATF6 and XBP1s [9]. So by analyzing this set of ER stress markers, activation of all three arms of the UPR can be monitored both on the protein and the RNA level. As a word of caution, we would like to note that none of the assays for a single UPR marker on its own is indicative of ER stress. For instance, other eIF2α kinases apart from PERK (e.g., PKR, GCN1, and HRI) can mediate eIF2α phosphorylation and subsequent ATF4 and CHOP expression [10]. In macrophages, splicing of XBP1 can occur independently of ER stress as a consequence of Tolllike receptor-mediated IRE1 activation [11]. Rather, the UPR consists of the concerted activation of all three ER stress sensors and their elicited combinatorial response. Therefore, it is important to assay for several UPR target genes both at the mRNA and protein levels.

2

Materials Unless otherwise indicated use ultrapure, deionized water throughout and use molecular biology grade reagents.

2.1 RNA Isolation Using TRIzol Reagent (See Note 1)

1. PBS. 2. TRIzol reagent (Invitrogen). 3. Nuclease-free ultrapure water (Sigma). 4. Chloroform. 5. Isopropanol. 6. 85 % ethanol (prepared in nuclease-free water).

2.2 RNA Isolation Using Qiagen RNeasy Kit 2.3 Reverse Transcription

1. Qiagen RNeasy kit. 2. Nuclease-free ultrapure water (Sigma). 3. 70 % ethanol (prepared in nuclease-free water). 1. SuperScript II first-strand synthesis system (Invitrogen). 2. 2 U/µL RNase-free DNase and 10× DNase I buffer. 3. 25 mM EDTA.

2.4 Conventional PCR

We prefer using a commercial PCR mix (Promega GoTaq) that contains all necessary ingredients at optimal concentrations. Additional components required are:

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Donna Kennedy et al.

Table 1 List of qPCR assays for UPR marker genes expression

Gene

NCBI reference sequence

Assay name (Applied Biosystems)

EDEM

NM_014674.2

Hs00206467_m1

Grp78

NM_005347.2

Hs00607129_gH

ERP72

NM_004911.3

Hs00191754_m1

CHOP

NM_004083.4

Hs00358796_g1

ATF4

NM_182810.1

Hs00909569_g1

HERP

NM_001010989.1

Hs01124269_m1

P58ipk

NM_006260.2

Hs00939345_m1

1. Nuclease-free ultrapure water (Sigma). 2. Primers (10 μM concentration, diluted in nuclease-free water).

2.5

qPCR

XBP1-Fwd

5′-TTACGAGAGAAAACTCATGGCC-3′

XBP-1-Rev

5′-GGGTCCAAGTTGTCCAGAATGC-3′

GAPDH-Fwd

5′-ACCACAGTCCATGCCATC-3′

GAPDH-Rev

5′-TCCACCCTGTTGCTG-3′

1. We use an Applied Biosystems 7500 Fast Real-Time PCR system in conjunction with StepOne software for data analysis. 2. Fast Optical MicroAmp 96-well plates (Applied Biosystems). 3. 2× Brilliant III Ultra-Fast QPCR Master Mix (Agilent). 4. 20× gene expression assays (Applied Biosystems single-tube assays, see Table 1) or custom-made assays (ordered as 20× assays) for analysis of XBP1 splicing (see Note 2). XBP1s qPCR assay: qXBP1-Fwd

5′-GGAGTTAAGACAGCGCTTGG-3′ (complementary to nucleotides 401–420*)

qXBP1s-Rev

5′-GCACCTGCTGCGGACTC-3′ (complementary to nucleotides 495–512*)

TaqMan probe

5′-GAAGCCAAGGGGAATGAAGT-3′ (complementary to nucleotides 453–472*)

*nucleotide numbers refer to XBP1s mRNA, GenBank: AB076384.1

Analysis of UPR in Human Cells

7

XBP1u qPCR assay: qXBP1u-Rev

5′-CTGCAGAGGTGCACGTAGTC-3′ (complementary to nucleotides 511–530**)

qXBP1-Fwd

5′-GGAGTTAAGACAGCGCTTGG-3′

TaqMan probe

5′-GAAGCCAAGGGGAATGAAGT-3′

**nucleotide numbers refer to XBP1u mRNA, GenBank: AB076383.1 2.6

Protein Isolation

1. PBS. 2. RIPA buffer: 50 mM Tris–HCl, pH 8.8, 150 mM NaCl, 0.5 % Na deoxycholate, 0.1 % SDS, 1 % Nonidet P-40. 3. Protease inhibitors: stock concentrations 100 mM PMSF (dissolve in isopropanol), 1 mg/mL pepstatin, 10 mM leupeptin, 2.5 mg/mL aprotinin, 250 mM ALLN. (All stocks stored at −20 °C, except aprotinin that is stable at 4 °C). 4. Phosphatase inhibitors (500 mM NaF, 250 mM Na3VO4) (see Note 3). 5. 5× Laemmli’s buffer: 1.5 mL of 1 M Tris–HCL (pH 6.8), 0.5 g of SDS, 1 mL of glycerol, 1.25 mL of mercaptoethanol, 0.25 mL of 100 mM PMSF, 1 mL of 0.5 % bromophenol blue, fill with H2O to a total volume of 5 mL.

2.7 Gel Electrophoresis

For gel electrophoresis and electroblotting, we use a Bio-Rad Mini-PROTEAN® Tetra Cell with Mini Trans-Blot® Module and a −20 °C pre-chilled cooling block. We use glass plates with 1 mm spacers and 1 mm thick combs. 1. 10 % SDS solution (see Note 4). 2. 1 M Tris pH 6.8: Dissolve Tris-base in H2O and adjust pH using HCl. 3. 1 M Tris pH 8.8: Dissolve Tris-base in H2O and adjust pH using HCl. 4. 30 % acrylamide solution (see Note 5). 5. 10 % APS: Dissolve 1 g of ammonium peroxodisulfate in 10 mL of H2O. Aliquot and store at −20 °C. 6. Tetramethylethylenediamine (TEMED) (see Note 6). 7. 10× running buffer is prepared in the following way: 31 g of Tris-base, 188 g of glycine, 10 g of SDS, fill to 1 L with H2O. 8. Pre-stained molecular weight standard mixture covering the size range of interest.

2.8

Western Blot

1. 10× CAPS buffer: Dissolve 22.13 g of CAPS (3-[cyclohexylamino]-1-propanesulfonic acid) in 900 mL of H2O. Adjust the pH of CAPS to pH 11 using NaOH and fill with H2O to a final volume of 1 L.

Donna Kennedy et al.

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Table 2 Antibodies used to detect human UPR markers in Western blot analysis

Antibody

Source, product number

Secondary MW (kDa) Dilution antibody of antigen

Actin

Sigma, A2066

1:5,000 Anti-rabbit 42

CHOP

Santa Cruz, sc793

1:1,000 Anti-rabbit 30

eIF2α

Cell Signaling Technology, #9722

1:1,000 Anti-rabbit 38

Phospho-eIF2α

Cell Signaling Technology, #9721

1:1,000 Anti-rabbit 38

GRP78

Stressgen, SPA826

1:5,000 Anti-rabbit 78

XBP1s

BioLegend, 619501

1:1,000 Anti-rabbit 55

ATF6

Cosmo Bio, Bam73-500-ex (see Note 39) 1:1,000 Anti-mouse 90 and 55 (see Note 39)

2. Transfer buffer: 100 mL of 10× CAPS, 200 mL of methanol, 700 mL of H2O (see Note 7). 3. Nonfat dry milk (see Note 8). 4. PBS/Tween: Prepare PBS containing 0.1 % (v/v) Tween 20 by adding 1 mL of Tween to 1 L of PBS in an Erlenmeyer. Mix thoroughly by swirling (see Note 9). 5. Nitrocellulose membranes. 6. Whatman 3MM filter paper. 7. Enhanced chemiluminescence (ECL) reagents. 8. Film cassette, X-ray films, darkroom, and developer solutions (or suitable gel documentation system with a cooled CCD camera). 9. Primary antibodies (see Table 2). 10. Horseradish peroxidase-conjugated goat anti-rabbit or goat anti-mouse antibodies.

3

Methods

3.1 Analysis of UPR-Induced Transcripts by PCR 3.1.1 RNA Isolation from Cells Using TRIzol (See Note 10)

We prefer the TRIzol protocol if RNA is to be used for semiquantitative RT-PCR analysis. Isolation of RNA is performed following the manufacturer’s protocol (see Notes 11–13).

Analysis of UPR in Human Cells 3.1.2 RNA Isolation Using Qiagen RNeasy Kit

9

For subsequent qPCR we prefer isolating highly pure RNA using the silica adsorption-based Qiagen RNeasy kit. 1. Cells (grown in six-well plates) are scraped, collected, and centrifuged at 500 × g for 5 min. Each cell pellet is resuspended in 350 μL RLT buffer by vortexing. 2. Follow the manufacturer’s instructions. 3. RNA is eluted with 50 μL of nuclease-free water and stored at −80 °C until use.

3.1.3 Reverse Transcription

The RNA is reverse-transcribed into cDNA using SuperScript II first-strand RT-PCR system and oligo(dT). 1. To synthesize cDNA, 2 μg of RNA is first subjected to DNase treatment. To this end, add 1 μL of DNase I and 1 μL of 10× DNase I buffer and water for a final volume of 10 μL to RNA; mix and incubate for 15 min at room temperature. 2. Inactivate DNase by adding 1 μL of 25 mM EDTA and incubate at 65 °C for 8 min (see Note 14). 3. To each reaction add 1 μL of 1 μg/μL oligo(dT) primers. Mix well and incubate at 65 °C for 2 min, followed by 42 °C for 2 min (see Note 15). 4. During the incubations of steps 2–4, prepare the first-strand master mix. Per sample mix the following components: Molecular grade H2O

2.6 μL

First-strand buffer

4.0 μL

DTT

2.0 μL

dNTPs (10 mM)

1.0 μL

SuperScript II enzyme

0.4 μL

5. Add 10 μL of first-strand master mix to each sample. 6. Incubate at 42 °C for 50 min followed by 75 °C for 10 min (see Note 16). 7. Samples can be stored at −20 °C. 3.1.4 Semiquantitative Analysis of XBP1 Splicing Using Conventional PCR

Using a pair of primers which flank the sequence that is removed by IRE1’s RNase activity, it is possible to monitor both total and spliced XBP1 by conventional PCR on 2 % agarose gels (see Fig. 1). The unspliced XBP1u will yield a 282 bp product, the spliced XBP1s a 256 bp product. 1. Prepare a master mix containing 3 μL of primer XBP1-Fwd, 3 μL of primer XBP1-Rev (each 10 μM), 4.5 μL of water, and 12.5 μL of Promega GoTaq for each sample. 2. Add 2 μL of cDNA to the master mix per sample in a PCR tube. Total volume is 25 μL. Mix by gently pipetting up and down.

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Fig. 1 (a) Schematic representation of XBP1 splicing. The position of the primers XBP1-Fwd and XBP-1-Rev is indicated. PCR with this primer pair yields a 282 bp product from XBP1u cDNA and a 256 bp product from XBP1s cDNA. Red rectangle: The stretch of 26 nucleotides spliced out by IRE1. (b) Example of a semiquantitative PCR revealing XBP1u- and XBP1s-derived DNA fragments as depicted in A. RPMI8226 cells were treated with 0.1 μM thapsigargin (Tg) for the hours indicated. (c) Schematic depiction of qPCR assays for analyzing XBP1 splicing. Both assays use the same forward primer, qXBP1-Fwd. This is combined with primer qXBP1uRev (spanning the 26 nucleotides removed by IRE1) to amplify XBP1u or with primer qXBP1s-Rev (spanning the junction of the rejoined mRNA after the splicing) to amplify XBP1s. The position of the dual-labeled probe detecting the amplification products is indicated

3. Place tube in a thermocycler and apply the following program: 94 °C for 3 min, 94 °C for 30 s, 58 °C for 30 s, 72 °C for 30 s, 72 °C for 7 min, followed by 4 °C until analysis. Repeat steps 2–4 for 35 cycles (see Note 17). 4. To control for cDNA concentration, GAPDH levels are assessed using the same protocol, however with GAPDH-Fwd and GAPDH-Rev primers. Cycle conditions are as follows: PCR cycle conditions—94 °C for 3 min, 94 °C for 30 s, 55 °C for 30 s, 72 °C for 30 s, 72 °C for 7 min, 4 °C until analysis. Repeat steps 2–4 for 25 cycles. 3.1.5 Quantitative Analysis of XBP1 Splicing

XBP1 splicing can be quantitatively evaluated using TaqMan qPCR (see Subheading 3.1.6) with two separate TaqMan assays for XBP1s and XBP1u. These PCR reactions take advantage of a forward primer, qXBP1-Fwd, that is common in both PCRs and reverse primers specifically amplifying XBP1s or XBP1u (qXBP1s-Rev and qXBP1u-Rev, respectively). The TaqMan probe is the same in both assays. The relative location of primers and probe is depicted in Fig. 1b. We recommend quantitating XBP1s and XBPu separately

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using the ΔΔCt method with GAPDH as endogenous control, as described in Subheading 3.1.6 (see Note 18). 3.1.6 TaqMan qPCR Analysis of UPR Marker Genes

1. Dilute cDNA to yield a final concentration of concentration of 40 ng per 10 μL reaction. 2. Prepare a master mix as follows (see Note 19). (per well, cDNAs are measured in triplicate, so three wells per sample are required). 2× Brilliant III Ultra-Fast QPCR Master Mix (Agilent)

5 μL

20× gene expression assays (Applied Biosystems)

0.5 μL

Diluted Reference Dye

0.15 μL

Water

1.85 μL

3. Pipette 7.5 μL of master mix onto the bottom of each well of a Fast Optical MicroAmp 96-well plate (Applied Biosystems) in triplicate (three wells per cDNA sample). 4. Add 2.5 μL of diluted cDNA to the respective wells to make up a total volume of 10 μL. Pipette into the drop of master mix and mix by gently pipetting up and down twice, avoiding air bubbles. Seal the plate to avoid evaporation (see Note 20). 5. The PCR is run for 40 cycles on an Applied Biosystems fast 7500 system using the following cycling conditions: Hold at 95 °C for 3 min and then 40 cycles at 95 °C for 12 s and 60 °C for 30 s. 6. Data can be analyzed using the Applied Biosystems StepOne software. To calculate changes in gene expression levels, the comparative Ct (ΔΔCt) method is used and results are usually expressed relative to untreated sample (serving as the “calibrator”). Since GAPDH expression does not change significantly during ER stress, GAPDH is used as “endogenous control” for most experiments, serving to normalize for differences in cDNA input by calculating relative expression levels of each sample (see Note 21). 3.2 Western Blot Analysis of UPR Marker Proteins 3.2.1 Protein Extracts

Western blot analysis can be used for detection of proteins upregulated by UPR signaling, for detection of eIF2α phosphorylation, and for analysis of ATF6 cleavage (see Fig. 2). 1. Dislodge cells in medium using a cell scraper and collect in an appropriately sized centrifuge tube (see Note 11). 2. Centrifuge at 500 × g for 5 min. Remove supernatant and resuspend the cell pellet in 1 mL of PBS by gentle agitation (e.g., flicking the tube). Centrifuge again. 3. Remove supernatant completely (see Note 22).

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Fig. 2 Western blot analysis of ATF6 cleavage in ER-stressed HCT1116 cells treated with 500 μg/mL brefeldin A for the hours indicated. Upper panel: Detection of both the uncleaved 90 kDa form of ATF6, pATF6(C), and the cleaved 55 kDa form, pATF6(N), using the same primary monoclonal antibody (see Table 2). Lower panel: The blot was reprobed for beta-actin to control for equal loading. Adapted from Fig. 4 in Cawley et al. 2013 [12]

4. Lyse samples in RIPA buffer containing a freshly added (see Note 23) cocktail of protease inhibitors (1 μM PMSF, 1 μg/ mL pepstatin, 10 μM leupeptin, 2.5 μg/mL aprotinin, and 250 μM ALLN) and phosphatase inhibitors (10 mM NaF, 1 mM Na3VO4) (see Note 24). 5. Vortex samples, firmly shake the content to the bottom of the tube, and leave on ice for 20 min to lyse thoroughly (see Notes 25 and 26). 6. Denature 10 μg of proteins by adding appropriate volume of 5× Laemmli’s buffer and incubating for 5 min at 96 °C. 3.2.2 Gel Electrophoresis

We typically use 8–12 % polyacrylamide (PAA) gels for analysis of UPR markers, depending on the molecular weight of the proteins to be resolved. 1. Prepare an SDS polyacrylamide gel by mixing the following components (amounts listed suffice for one mini gel) in this order (see Notes 27 and 28): 8 % PAA gel (for 25–200 kDa proteins): 2.3 mL of H2O, 1.3 mL of 30 % acrylamide mix, 1.3 mL of 1.5 M Tris–HCl pH 8.8, 50 μL of 10 % SDS, 50 μL of 10 % APS, 3 μL of TEMED.

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10 % PAA gel (for 15–100 kDa proteins): 2.0 mL of H2O, 1.7 mL of 30 % acrylamide mix, 1.3 mL of 1.5 M Tris–HCl pH 8.8, 50 μL of 10 % SDS, 50 μL of 10 % APS, 3 μL of TEMED. 12 % PAA gel (for 10–70 kDa proteins): 1.7 mL of H2O, 2.0 mL of 30 % acrylamide mix, 1.3 mL of 1.5 M Tris–HCl pH 8.8, 50 μL of 10 % SDS, 50 μL of 10 % APS, 3 μL of TEMED. 2. Pour the gel mixture between two protean mini glass plates (a short plate and a spacer plate) assembled using a casting frame and inserted into the casting stands (see Note 29). Cover with 500 μL of isopropanol to prevent air contact (which would prevent polymerization). 3. Leave the gel at room temperature for approx. 30 min to polymerize (see Note 30). 4. Remove isopropanol and rinse three times with 2 mL of water. After pouring out the water, carefully soak residual water using a small stripe of filter paper. 5. Prepare stacking gel by mixing reagents in this order: 1.36 mL of H2O, 340 μL of 30 % acrylamide mix, 260 μL of 1 M Tris– HCl pH 6.8, 20 μL of 10 % SDS, 20 μL of APS, 2 μL of TEMED (see Note 31). 6. Pour stacking gel on top of the resolving gel and insert a tenwell comb, avoiding air bubbles. 3.2.3 Gel Run

1. Prepare 10 μg of protein per sample by adding appropriate volume of 5× Laemmli’s buffer and incubating for 5 min at 96 °C. 2. Prepare 1× running buffer from 10× stock. 3. Place gel in electrophoresis device and fill the buffer reservoirs with 1× running buffer such that the comb is submerged. 4. Carefully pull out the comb. 5. Load samples and pre-stained molecular weight standard (see Notes 32 and 33). 6. Run gels at 60 volts until proteins enter the resolving gel (can be seen using the pre-stained marker). 7. Run gels for the remainder of the time at 90 volts (see Note 34).

3.2.4 Transfer of Proteins

1. Cut nitrocellulose membrane and two sheets of Whatman filter paper to a size of 6 × 9 cm. 2. Disassemble glass plates. The gel will stick to one of them. Remove stacking gel using a scalpel and gently lift the gel containing the proteins from the glass plate.

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3. Soak membrane, protein gel, filter paper, and two foam pads in transfer buffer (see Note 7). 4. Assemble items in a gel holder cassette in the following order: foam pad, filter paper, nitrocellulose membrane, gel, filter paper, foam pad. To remove air bubbles (which impede transfer), roll a 15 mL plastic centrifuge tube over the transfer sandwich. 5. Insert the sandwich into the blot module such that the gel is orientated at the cathode, the nitrocellulose membrane at the anode. 6. Insert blot module into cell tank filled with transfer buffer. Insert −20 °C pre-chilled cooling block and transfer proteins at 110 volts for 90 min at 4 °C. 3.2.5 Detection of Proteins

1. After transfer, disassemble the blot, remove the gel, and mark the bands of the pre-stained protein marker and the positions of the wells with a black ink pen (see Notes 35 and 36). 2. Wash the membrane for 3 min in a tray in 10 mL of PBS/ Tween at room temperature. 3. Replace the PBS/Tween by blocking buffer (5 % nonfat milk made up in PBS/Tween) and slowly shake for 1 h at room temperature. 4. Replace blocking buffer by primary antibodies diluted in blocking buffer as detailed in Table 2. Incubations are carried out at 4 °C overnight. Incubations can be carried out in a tray sealed with plastic wrap (requiring approximately 10 mL of antibody solution) or in small plastic bags (allows a reduction in the volume of antibody solution to 3–5 mL). 5. Following incubation with primary antibody, membranes are washed three times for 5 min in PBS/Tween, using 20 mL for each wash (see Note 37). 6. After washing incubate membranes with appropriate secondary antibody conjugated to horseradish peroxidase (diluted in blocking buffer) for 2 h at room temperature. 7. Wash three times for 5 min in PBS/Tween, using 20 mL for each wash. 8. Wash once in 10 mL of PBS. 9. Cover the protein-containing side of the membrane with enhanced chemiluminescence (ECL) substrate (1 mL total per 6 × 9 cm membrane). 10. Incubate for 5 min and then expose film and develop (or document using CCD camera-based device) (see Note 38).

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Notes 1. TRIzol reagent contains phenol and guanidinium thiocyanate; therefore, handle the stock solution in a fume hood and wear gloves and protective goggles. 2. The choice of fluorophore and quencher depends on the qPCR device used. We prefer using 5′-FAM as the fluorophore and 3′-BHQ as quencher. 3. To dissolve Na3VO4, the pH needs to be adjusted to ten using NaOH. Store in aliquots at −20 °C. 4. Wear a breathing mask when handling SDS powder. 5. Since acrylamide is neurotoxic, we prefer using commercial solutions of 30 % acrylamide (37.5:1 acrylamide/bisacrylamide); handle with gloves. 6. Handle solution in fume hood. 7. Since the mixture becomes warm, it is recommended to prepare the transfer buffer at least 30 min before setting up the blot and pre-chill it on ice or at 4 °C. 8. Most brands of nonfat powdered milk supplied in regular supermarkets fulfill the purpose. 9. Tween is highly viscous and will adhere to the inside of pipettes, thus accurate pipetting is not possible. We therefore use a 1 mL syringe (without needle) to dispense Tween accurately. Excess drops of Tween are wiped away from the syringe with a clean tissue. If stored in a clean environment, the syringe can be reused. 10. To study the UPR or in order to generate positive control samples, it may be useful to induce ER stress in cultured cells. For this purpose cells should be seeded at an appropriate density in a six-well plate 24 h prior to treatments. Classical ER stress-inducing chemical compounds include thapsigargin (TG), tunicamycin (TM), and brefeldin A (BFA). Treatment concentrations need to be determined empirically for each cell type. Dosages typically range from 0.25 to 2 μM of TG, 0.5–2 μM of TM or BFA, respectively. Cells should be 80 % confluent for analysis. 11. Different from the TRIzol protocol, we prefer collecting the adherent cells in 2 mL of growth medium using a cell scraper (do not change medium prior to cell collection, since stressed cells may be less adherent and thus might be washed away). The suspension is transferred to a centrifuge tube and centrifuged at 500 × g for 5 min to pellet the cells. 12. To lyse cells grown in a six-well plate, 500 μL of TRIzol reagent per well is sufficient. Consequently we use 100 μL of

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chloroform for the phase separation step and 750 μL of isopropanol for the precipitation of the RNA. At the end, the RNA pellet is dissolved in 25 μL of nuclease-free water and stored at −80 °C. 13. RNA is quantified using UV spectrophotometry at 260 nm and 280 nm. Pure RNA has an OD260/OD280 ratio of 2.1; however, anything above 1.8 is generally acceptable for cDNA preparation. 14. DNase I is used to remove contaminating genomic DNA. This step may appear unnecessary when using the RNeasy kits, in particular if the primers used in the subsequent PCR assays anneal to different exons. However, several GAPDH pseudogenes exist, which make usage of GAPDH as endogenous control problematic if genomic DNA is still present. To rule out these uncertainties, we routinely carry out DNase I treatment. 15. Incubations in step 2 to 4 are best performed on a thermocycler whose cycle steps have been programmed accordingly. The heated lid prevents evaporation during the 65 °C steps. For addition of oligo(dT), the 65 °C step is paused after 8 min and resumed thereafter for further 2 min. 16. This is best done using a thermocycler to prevent evaporation. 17. To confirm the splicing, one can digest the PCR products with restriction enzyme Pst I (which cuts only in the unspliced cDNA). 18. Usually the increase in spliced XBP1s suffices to monitor IRE1 activation. If the relative increase in XBP1 splicing is of interest, variations in the total amount of XBP1 cDNA (XBP1u plus XBP1s) must be taken into account by dividing the fold increase of XBP1s by the fold increase in total amount of XBP1 cDNA. 19. Prepare a master mix per number of samples plus an additional 10 % to account for loss during pipetting. 20. To increase precision we use siliconized pipette tips for pipetting small volumes. 21. Expression of the controls should not vary by more than one Ct value between samples. 22. At this time cell pellets can be frozen at −80 °C or you can proceed with lysis. 23. PMSF is not stable in aqueous solution and thus needs to be added freshly from the stock. 24. For the analysis of phospho-eIF2α, the preservation of phosphorylation is required; therefore, we include phosphatase inhibitors.

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25. We quantitate proteins using the bicinchoninic acid (BCA) method, as the Bradford method gives high background when lysates contain detergents. 26. Lysates can immediately be stored at −20 °C or be denatured in Laemmli’s buffer and then stored at −20 °C. Before freezing the lysates, we take 2 μL for quantitation using the BCA method. 27. Avoid extensive vortexing of the mixture since oxygen from the air will slow down the polymerization. 28. APS and TEMED cause the gel to polymerize; therefore, do not add them until you are ready to cast the gel. 29. Following assembly of the glass plates, test for leaks by filling the space with deionized water. 30. You can check the polymerization status by gently lifting the gel on one side. 31. Gels can be prepared in advance and stored at 4 °C but generally should be used with in 24 h. 32. We use thin elongated gel loading tips to facilitate loading. 33. To prevent uneven gel runs, fill empty wells with similar volumes of 1× Laemmli’s buffer. 34. The Laemmli’s buffer in the samples contains bromophenol blue allowing to monitor the migration. Gels can be run until the blue dye is starting to run off gel into the running buffer. 35. By labeling the membrane, e.g., samples and date, on the protein-containing side, one can later easily identify the side onto which the detection reagents should be applied. 36. After transfer is completed, the membrane can be stained with Ponceau S (0.1 % in 5 % acetic acid) to ensure that loading and transfer were uniform. The membrane can then be photographed or wrapped in Saran and documented using a flatbed scanner. The stain has to be removed by washing three times for 3 min in 20 mL of PBS/Tween before proceeding. 37. Primary antibodies can be used multiple times if stored at −20 °C. 38. The same membrane can be used for several primary antibodies by cutting into stripes encompassing the desired size range (assessed by the pre-stained molecular weight standards). Alternatively, antibodies can be removed (“stripped”) from the blot by incubating the membrane for 5 min in 0.2 M NaOH. Before incubating with another primary antibody, remove NaOH by extensively washing with PBS (five times for 5 min, 20 mL of PBS each wash). The potential to completely remove a given primary antibody first needs to be confirmed by reprobing a blot with secondary antibody followed

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by ECL detection. Residual antibodies on the membrane are less problematic if the subsequent primary antibody is from a different species. 39. This antibody recognizes the amino-terminal part of ATF6 and is thus suited for monitoring ATF6 cleavage. Detection of ATF6 cleavage requires at least 30 μg of protein, an 8 % gel, and long exposure for detection. We are using the sensitive Amersham ECL Plus detection reagent for ATF6 blots and expose for 20 min. Also a freshly blotted membrane (no prior antibody incubation or stripping) should be used. An example blot is shown in Fig. 2.

Acknowledgments We would like to thank all the members of our groups, in particular Patricia Cleary for the help with the preparation of figures and Lisa Vincenz who generated Fig. 1b. Figure 2 is an adaptation of a portion of Fig. 4 in Cawley et al., PloS One 2013, 8: e73870. Our work is funded by grants from BELSPO, Belgium, and the Breast Cancer Campaign (2010NovPR13). References 1. Walter P, Ron D (2011) The unfolded protein response: from stress pathway to homeostatic regulation. Science 334:1081–1086 2. Jager R, Bertrand MJ, Gorman AM et al (2012) The unfolded protein response at the crossroads of cellular life and death during endoplasmic reticulum stress. Biol Cell 104:259–270 3. Harding HP, Novoa I, Zhang Y et al (2000) Regulated translation initiation controls stressinduced gene expression in mammalian cells. Mol Cell 6:1099–1108 4. Ma Y, Brewer JW, Diehl JA et al (2002) Two distinct stress signaling pathways converge upon the CHOP promoter during the mammalian unfolded protein response. J Mol Biol 318:1351–1365 5. Palam LR, Baird TD, Wek RC (2011) Phosphorylation of eIF2 facilitates ribosomal bypass of an inhibitory upstream ORF to enhance CHOP translation. J Biol Chem 286:10939–10949 6. Yoshida H, Okada T, Haze K et al (2000) ATF6 activated by proteolysis binds in the presence of NF-Y (CBF) directly to the cisacting element responsible for the mammalian unfolded protein response. Mol Cell Biol 20: 6755–6767

7. Yoshida H, Matsui T, Yamamoto A et al (2001) XBP1 mRNA is induced by ATF6 and spliced by IRE1 in response to ER stress to produce a highly active transcription factor. Cell 107: 881–891 8. Cawley K, Deegan S, Samali A et al (2011) Assays for detecting the unfolded protein response. Methods Enzymol 490:31–51 9. Yamamoto K, Yoshida H, Kokame K et al (2004) Differential contributions of ATF6 and XBP1 to the activation of endoplasmic reticulum stress-responsive cis-acting elements ERSE, UPRE and ERSE-II. J Biochem 136:343–350 10. Donnelly N, Gorman AM, Gupta S et al (2013) The eIF2alpha kinases: their structures and functions. Cell Mol Life Sci 70: 3493–3511 11. Martinon F, Chen X, Lee AH et al (2010) TLR activation of the transcription factor XBP1 regulates innate immune responses in macrophages. Nat Immunol 11:411–418 12. Cawley K, Logue SE, Gorman AM et al (2013) Disruption of microRNA biogenesis confers resistance to ER stress-induced cell death upstream of the mitochondrion. PLoS One 8(8):e73870

Chapter 2 Assays for Induction of the Unfolded Protein Response and Selective Activation of the Three Major Pathways Ananya Gupta, Danielle E. Read, and Sanjeev Gupta Abstract The endoplasmic reticulum (ER) is responsible for the proper folding and processing of secreted and transmembrane proteins within the cell. Stimuli that disrupt ER function cause an accumulation of misfolded proteins within the ER lumen, a condition termed ER stress. The unfolded protein response (UPR) is activated in response to ER stress in an attempt to restore ER homeostasis. UPR is initiated by three transmembrane sensors that activate three signaling pathways which lead to the activation of transcription factors and production of chaperones. The coordinated action of these three pathways attempt to restore homeostasis. However, if the ER homeostasis cannot be restored, it initiates apoptosis. Deregulated or compromised functions of these pathways can therefore lead to the pathogenesis of disease. In order to understand the molecular mechanisms involved, it is important to study each pathway independently. Here, we describe a number of approaches to selectively target each arm of UPR and investigate the functional significance of the UPR pathway involved. Key words UPR, Chaperones, ER Stress, XBP1 splicing, PERK, ATF6, IRE1

1

Introduction The endoplasmic reticulum (ER) is responsible for the synthesis and folding of secretory and membrane-bound proteins, which occurs via the ribosomes located on the cytosolic surface of the rough ER. To facilitate protein folding, the ER contains a high proportion of molecular chaperone proteins, for example, GRP78 (BiP), which bind to hydrophobic regions of unfolded proteins and promote conformational changes using ATP hydrolysis activity [1]. A number of stimuli, including calcium imbalance, viral infection, oxidative stress, nutrient deprivation, and altered glycosylation, can interfere with ER homeostasis and cause an accumulation of unfolded/misfolded proteins within the ER which is termed ER stress [2]. The response to the accumulated unfolded proteins is mediated via three transmembrane sensors, PERK (pancreatic ER kinase (PKR)-like ER kinase), ATF6 (activating transcription

Christine M. Oslowski (ed.), Stress Responses: Methods and Protocols, Methods in Molecular Biology, vol. 1292, DOI 10.1007/978-1-4939-2522-3_2, © Springer Science+Business Media New York 2015

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factor 6), and IRE1 (inositol-requiring enzyme 1), which possess a domain in the ER lumen that senses ER stress caused by the accumulation of misfolded proteins and a cytosolic domain, which activates downstream signaling effectors. Collectively, these three signaling pathways are termed the unfolded protein response (UPR) (Fig. 1). The initial functions of the UPR are prosurvival:

Fig. 1 Schematic representation of the unfolded protein response. Upon aggregation of unfolded proteins, BiP (GRP78) dissociates from the endoplasmic reticulum (ER) stress sensors, activating transcription factor 6 (ATF6), pancreatic ER kinase (PKR)-like ER kinase (PERK), and inositol-requiring enzyme 1 (IRE1), allowing their activation. Activated PERK blocks general protein synthesis by phosphorylating eukaryotic initiation factor 2α (eIF2α). Phosphorylation of eIF2α enables translation of the transcription factor ATF4, through an alternative eIF2α-independent translation pathway. ATF4 translocates to the nucleus and induces the transcription of genes involved in the restoration of ER homeostasis. Active ATF6 regulates the expression of ER chaperones and the transcription factors CHOP (C/EBP homologous protein) and X-box binding protein 1 (XBP1). To become active XBP1 undergoes mRNA splicing, which is performed by IRE1. Spliced XBP1 protein (sXBP1) translocates to the nucleus and controls the transcription of chaperones and genes involved in ER-associated protein degradation (ERAD). The combined action of the three arms of the UPR attempts to restore ER function by reducing accumulation of client proteins, enhancing the folding capacity by upregulating chaperones, and promoting degradation of protein aggregates. In addition, ERAD (ER-associated protein degradation) further assists restoration of ER function by targeting misfolded proteins to the proteasome

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halt general protein translation, increase chaperone production to facilitate removal of unfolded proteins, and enhance degradation of misfolded proteins within the ER through ER-associated degradation (ERAD) [3]. In the event that ER stress is prolonged and severe, the UPR signaling progresses to signal apoptosis. Upon accumulation of unfolded proteins, GRP78 dissociates from the ER stress sensor PERK to preferentially bind the misfolded proteins. This allows PERK homodimerization and autophosphorylation of its cytosolic kinase domain, generating active PERK. Eukaryotic initiation factor 2α (eIF2α) is phosphorylated by PERK on serine 51, which inhibits cap-dependent protein translation by preventing the pentameric guanine exchange factor eIF2B from recycling eIF2 to its active GTP-bound form [4, 5]. Reduced level of active eIF2 decreases global translation rate and the quantity of client proteins being loaded into the ER. However, cap-independent translation enables synthesis of key UPR regulatory proteins, including ATF4. ATF4 enters the nucleus and induces transcription of chaperone proteins, GADD34 (growth arrest and DNA damage-inducible protein 34), proteins involved in amino acid transport, glutathione biosynthesis, and resistance to oxidative stress, and also the proapoptotic protein CHOP (C/EBP homologous protein) [6, 7]. PERK activation is reversible: Hsp40 co-chaperone P58IPK is upregulated by ATF6 and binds to the kinase domain to inhibit PERK activity [8, 9]. In addition, the protein phosphatase 1 (PP1) complex dephosphorylates eIF2α to attenuate the translational block and is promoted by ATF4-induced GADD34 in a negative feedback loop [10, 11]. Activated ATF6, another ER stress transmembrane sensor, translocates to the Golgi apparatus where it undergoes sequential cleavage by SP-1 and SP-2 proteases resulting in its active form. Active ATF6 translocates to the nucleus where it activates transcription of target genes, including XBP1 (X-box binding protein 1) which is then available for splicing upon IRE1 activation. Further targets of ATF6 include GRP78, GRP94, PDI (protein disulfide isomerase), and P58IPK, which function to promote survival [12]. IRE1 contains an ER luminal domain that senses ER stress and a cytosolic domain with serine-threonine protein kinase and endoribonuclease activity. Activation is driven by dissociation of GRP78 or direct binding to unfolded proteins [13]. Oligomerized, active IRE1 triggers unconventional splicing of the XBP1 mRNA, to excise a small 26 nucleotide intron which results in a frame shift and allows translation of spliced XBP1 into a functional transcription factor. Spliced XBP1 induces the expression of a number of genes (including chaperones and P58IPK) involved in most aspects of the UPR, whereas unspliced XBP1 acts as a dominant negative for spliced XBP1 and represses gene expression [13]. The UPR signaling plays key roles in many physiological processes. The UPR normally protects cells and reestablishes cellular

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homeostasis, but prolonged UPR activation can lead to the development of various pathologies. The precise genetic and mechanistic association of the UPR with human disease has not been fully investigated yet, and considerable ongoing basic research is focused on uncovering how the UPR contributes to human disease. Malfunction of the ER and failure in localization of proteins to their correct cellular destinations are widely believed to cause a number of diseases in humans including metabolic, neurodegenerative, and oncologic disorders [14, 15]. It has been shown in various pathological conditions that different arms of the UPR get affected differentially. Increased IRE1 signaling has been implicated in obesity, inflammatory bowel disease (IBD) [16], and type II diabetes [17]. ATF6 function has been found to be compromised in cystic fibrosis and fatty liver disease [18]. Deregulated UPR signaling has been shown to be involved in the pathogenesis of neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD) [19, 20]. CHOP has been shown to mediate cell death of dopaminergic neurons in PD [21]. XBP1 is implicated in the accumulation of mutant HTT protein in HD [22]. Elevated levels of phosphorylated PERK have been detected in the hippocampus of AD patients and are believed to be the cause for dysregulated ER calcium homeostasis and ER stress signaling which contributes to AD pathology [23]. UPR has been shown to be activated in the tumor microenvironment in many types of cancers [24]. Inhibition of IRE1 and/or PERK signaling leads to reduced angiogenesis and slower tumor growth. Multiple myeloma cells display increased ER stress and elevated levels of XBP1 [25]. UPR plays a critical role in regulating cell survival and death in response to ER stress. It is therefore very important as a mechanistic link between ER stress and disease pathogenesis [24, 26, 27]. However, the concomitant activation of multiple UPR signaling pathways by ER stress in mammalian cells has hindered precise assessments of the contribution of each specific UPR signaling pathway to disease pathogenesis. Identifying specific UPR regulatory molecules or signaling pathways involved in disease pathogenesis is critical to developing targeted therapies that prevent the development or progression of disease [28, 29]. It is therefore important to evaluate the independent and collective roles of the different UPR pathways in a given condition. To achieve this, each arm or signaling pathway and their corresponding transcription factors have to be activated selectively and studied independent of the others. Therefore, we need to identify methods to monitor and quantify activation of individual UPR signaling pathways in mammalian cells and tissues. Various strategies to artificially and selectively activate or block individual UPR signaling pathways using chemical-genetic approaches can be used for this purpose. Since the three arms of the UPR can be activated differentially depending

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on the inducer and cell line being studied, multiple target gene downstream of each pathway needs to be assessed to clearly elucidate which arm or regulator or pathway is involved. Since there is significant functional overlap and cross talk between the three pathways of UPR signaling, to achieve this experimentally can be challenging. The current article describes the tools needed and discusses a set of techniques which can help in achieving this goal. This guide to UPR analysis techniques assumes a basic understanding of the core techniques discussed and focuses instead on the specific details pertaining to UPR research.

2

Materials Cell Lines

Mammalian cell lines can be obtained from the American Type Culture Collection (ATCC) or European Collection of Cell Cultures (ECACC). Cell lines described in this article MCF7, MDA MB231, T47D, HEK293, 293 T, and H9C2 were obtained from ATCC (see Note 1).

2.2 Chemical Inducers of UPR (See Note 2)

1. Tunicamycin, thapsigargin, and brefeldin A (Tocris Bioscience, Bristol, United Kingdom).

2.1

2. 2-Deoxy-D-glucose and dithiothreitol (Sigma-Aldrich). 3. Bortezomib (Santa Cruz Biotech).

2.3 Chemical and Genetic Modulators of UPR Signaling

1. GSK2656157 (PERK inhibitor, EMD Millipore). 2. CCT020312 (PERK activator, Calbiochem). 3. 4μ8C (IRE1 inhibitor, Tocris Bioscience). 4. STF083010 (IRE1 inhibitor, Tocris Bioscience). 5. MKC-3946 (IRE1 inhibitor, MannKind Corp.). 6. pCMVshort-EGFP-ATF6 (Addgene plasmid #32955). 7. pCAX-F-XBP1-venus and pCAX-F-XBP1ΔDBD-venus [30]. 8. p5xATF6-pGL3 reporter [31]. 9. p4xXBP-pGL3 reporter [32]. 10. pCGN-ATF6 m1 (Addgene plasmid # 27174). 11. pCMMP-DN-PERK-IRES-GFP [22]. 12. pCDNA3.1-IRE1 ΔC (gift from Kazunori Imaizumi). 13. pcDNA1-CHOP (Addgene plasmid #21913). 14. pRK-ATF4-FLAG (Addgene plasmid #26114). 15. pCDNA3.1-NRF2-FLAG (Addgene plasmid #36971). 16. pBMN-ATF6-IRES-GFP (gift from Joseph Brewer). 17. pBMN-XBP1s-IRES-GFP (gift from Joseph Brewer).

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Transfection

1. JetPEI (Polyplus Transfection #101-01 N). 2. Lipofectamine 2000 (Invitrogen). 3. TurboFect (Thermo Scientific).

3

Methods

3.1 Cell Lines as Model Systems

Recent studies have shown that endoplasmic reticulum (ER) stress is triggered during many physiologic conditions such as hypoxia and nutrient deprivation, as well as in pathologic conditions, such as in neurological disorders like AD and ALS and in cancer [33]. ER stress occurs when the ER-mitochondria calcium cycle (ERMCC) is disturbed and misfolded proteins accumulate in the ER. To cope with ER stress, the cell engages the unfolded protein response (UPR) [13]. The UPR has recently emerged as a marker for tumor microenvironment-induced stress, which can be triggered within cancer cells by hypoxia or nutrient deprivation [34, 35]. Activation of the UPR has been reported in a variety of human cancers [36]. Cell lines derived from tumors are the most frequently utilized models in cancer research [37]. In order to study the molecular mechanisms involved in the induction of UPR in breast cancer, we used a panel of breast cancer cell lines (MCF7, MDA231, and T47D).

3.2 Chemical Inducers of UPR

To study UPR in a cell line, cells should be seeded on six-well plates and treated with different chemical inducers of ER stress. The induction of UPR can then be assessed by studying the relative mRNA levels for ER chaperones and UPR-coupled transcription factors. Three chemicals are generally used to experimentally induce ER stress in cell lines: tunicamycin, thapsigargin, and brefeldin A (BFA). Although these chemicals target different components of the ER, their common effect is to interfere with ER functions and thereby lead to accumulation of misfolded proteins in the ER. The dosage needed for optimal induction of UPR is dependent on the cell type (see Note 1). For example, in breast cancer cells MCF7, MDA MB231, and T47D, we used the following doses, tunicamycin 1–2 μg/mL and thapsigargin 1–2 μM, and observed a good induction of UPR target genes. The duration of treatment also depends on the cell type and the downstream effect to be studied. In breast cancer cell lines such as MCF7 and T47D, we observed maximum response at 24 h following treatment. While in MDA MB231, there was significant UPR induced as early as 6 h. At 24 h these cells started to show signs of cell death. So the end point or time course selected to study UPR has to be determined experimentally in each cell line and has to be such that there is a good induction of UPR target genes and UPR regulators without significant induction of apoptosis or cell death (see Notes 2 and 3). A more physiologic method of UPR induction is to use 2-deoxyglucose, which blocks glycolysis, in the culture medium [38].

Selective Activation of UPR Pathways 3.2.1 Chemical Inducers of UPR

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Brefeldin A is a lactone antibiotic produced by fungal organisms such as Eupenicillium brefeldianum. Brefeldin A inhibits protein transport from the endoplasmic reticulum (ER) to the Golgi apparatus indirectly by preventing formation of COPIImediated transport vesicles [39]. In mammalian cells, the main target of brefeldin A appears to be a guanine nucleotide exchange factor called Sar1 which mediates formation of transport vesicles by recruiting COPII coat proteins to cargo-bound receptor proteins found in the membrane of the rough ER [40]. Inhibition of Sar1 activity prevents the transport of secretory proteins out of the ER. The accumulation of protein within the ER leads to the collapse of the Golgi stacks, triggers activation of UPR, and ultimately causes apoptosis [39]. Thapsigargin leads to ER Ca+2 depletion due to inhibition of the sarco/endoplasmic reticulum Ca2+-ATPase (SERCA) [41]. It is extracted from a plant, Thapsia garganica. Thapsigargin raises cytosolic (intracellular) calcium concentration by blocking the ability of the cell to pump calcium into the sarcoplasmic and endoplasmic reticulum, which causes these stores to become depleted. Ca2+ is required for the proper folding of the proteins in the ER [41]. Tunicamycin is a mixture of homologous nucleoside antibiotics that inhibits the UDP-HexNAc: polyprenol-P HexNAc1-P family of enzymes [42]. In eukaryotes, this includes the enzyme GlcNAc phosphotransferase (GPT), which catalyzes the transfer of N-acetylglucosamine-1-phosphate from UDPN-acetylglucosamine to dolichol phosphate in the first step of glycoprotein synthesis. Tunicamycin blocks the synthesis of all N-linked glycoproteins (N-glycans) and causes cell cycle arrest in G1 phase [42]. 2-Deoxy-D-glucose is a glucose molecule which has the 2-hydroxyl group replaced by hydrogen, so that it cannot undergo further glycolysis [43]. As such, it acts to competitively inhibit the production of glucose-6-PO4 from glucose at the phosphoglucoisomerase level and thus blocks glycolysis [43]. Dithiothreitol reduces the disulfide bridges of proteins. The denatured proteins accumulated inside the ER [44]. Bortezomib (Velcade) is a proteasome inhibitor. It inhibits proteasomal degradation of the unfolded proteins leading to their accumulation in the ER and induces ER stress leading to apoptosis in mammalian cells [45]. 1. Maintain cells in a 25–75 cm2 flask (Sarstedt) as required in the appropriate growth medium (such as DMEM or RPMI) with required supplements and antibiotics. When cells reach a confluency of approximately 80 %, trypsinize cells using 1× trypsin/EDTA.

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2. For UPR experiments, cells can be seeded to the appropriate density in six-well plates or 25 cm2 flasks depending on the number of cells required for the assay. 3. The next day, treatments can be carried out with appropriate doses of known UPR inducers such as tunicamycin, thapsigargin, or brefeldin A. A dose and time response for the chosen compound should be done prior to commencement of experiments, as this will vary from cell type to cell type. Cells should be observed under a microscope 12–24 h posttreatment to note the extent of cell death. 3.3 Detecting the Activity of XBP1 and ATF6 Using Reporter Assays

3.3.1 Protocol for Reporter Assays for ATF6 and XBP1

The induction of UPR target genes is mediated by cis-acting ERSE (ER stress response element), ERSE-II (ER stress response element II), and UPRE (unfolded protein response element) present in the promoter of UPR target genes [46–48]. The consensus sequence of ERSE is CCAAT-N9-CCACG, which is required for the induction of most ER chaperones (e.g., GRP78, GRP94, and calreticulin). UPRE has the consensus sequence TGACGTGG/A which was originally identified as a DNA sequence bound by bacterially expressed ATF6. The presence of one or more of these sequences in the promoter region of a gene allows UPR transcription factors to bind to them and regulate transcription. There are several reporter systems that can be used to detect ATF6 and XBP1 activation and transcriptional activity. These reporters contain one or more ER stress response elements. In the p5xATF6-pGL3 reporter, the luciferase gene is under the control of the c-fos minimal promoter and five tandem copies of the ATF6 consensus binding site. This sequence was identified by in vitro gel mobility shift assays with recombinant ATF6 [31]. ATF6 will bind to this reporter and drive the transcription of the luciferase gene downstream. Therefore, the amount of luciferase activity can be used as an indirect measure of ATF6 transcriptional activity. Similarly, in p4xXBP-pGL3 reporter, the luciferase gene is under the control of four tandem copies of the XBP1 consensus binding site 5′- CGCG(TGGATGACGTGTACA)4-3′ [32]. This reporter can be used to study the transcriptional activity of XBP1. In addition, there are several other ERSE reporters that have promoter regions of GRP78, GRP94, calreticulin, and XBP1 [46] and an ERSE-II reporter that has the HERP promoter upstream of the luciferase reporter gene [48]. These reporters should be used in combination with the corresponding mutant promoter where the functional cis-elements have been mutated. 1. Seed cells at 70–80 % confluency in a 24-well plate or a sixwell plate. 2. 24 h after seeding, transfect the reporter construct into the cells using the appropriate transfection reagent and optimal

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DNA-lipid ratio, which should be optimized for your model system in advance. Along with the luciferase reporter, a plasmid construct with the gene encoding Renilla luciferase or β-galactosidase should also be transfected to serve as an internal control for transfection efficiency. 3. After 24 h post-transfection, remove the media containing the DNA-lipid from the cells, and the appropriate treatment for inducing ER stress (e.g., using tunicamycin or thapsigargin) can be carried out. Alternatively, the treatment required to study the process under investigation can be done here. Again, the dose and duration of treatment should be determined for different model systems before commencing experiments, but generally, treatments range between 6 and 48 h (see Note 3). 4. Lyse cells in passive lysis buffer and measure the bioluminescence of luciferase. We generally use Promega’s Dual-Glo Luciferase Assay kit. By normalizing to the control plasmid, the fold induction of the reporter’s activity can be determined. Indirectly, this is also a measure of the transcriptional activity of the UPR regulator (e.g., ATF6 or XBP1). 3.4 Detecting IRE1 Activation Using XBP1-GFP Fusion Constructs

In order to study activation of the IRE1, a fluorescent reporter construct has been generated by fusing the full-length XBP1 sequence to the green fluorescent protein, Venus [30], which can be used to monitor IRE1 activation and subsequent XBP1 splicing. The design of the XBP1-venus reporter is shown in Fig. 2d. In this construct, the gene encoding Venus is cloned downstream of the 26-nt ER stress-specific intron of human XBP1 [30]. During the UPR, XBP1 is spliced at this intron by IRE1 to give rise to the active form (Fig. 2a). This splicing can be detected by conventional RT-PCR and qRT-PCR analysis [49] (Fig. 2b, c). Under normal conditions, the mRNA of the fusion gene is not spliced, and its translation terminates at the stop codon near the joint between the XBP1 and Venus gene. However, during UPR when IRE1 is activated, the 26-nt intron is spliced out, leading to a frame shift of the chimeric XBP1-venus mRNA, similar to that of the endogenous XBP1 mRNA. Translation of the spliced mRNA produces an XBP1-venus fusion protein, and cells harboring the active IRE1 can be detected by monitoring the fluorescence activity of Venus. As Venus expression can only occur from the spliced form of the XBP1-GFP mRNA, its presence signals the activation of IRE1 (Fig. 2e). When UPR is induced by tunicamycin treatment in the transfected cells having the XBP1-GFP reporter, fluorescence is detected in the nucleus of these cells, whereas negligible fluorescence is detected in any compartment under normal conditions when IRE1 is not active. Moreover, Venus expression during tunicamycin treatment has been shown in splicing assays to correlate with the extent of splicing of the UPR intron from XBP1/GFP

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Fig. 2 Detecting IRE1 activity using XBP1 splicing and XBP1-venus reporter constructs. (a) Cartoon of XBP1 splicing during ER stress. (b) Detecting XBP1 spliced and unspliced mRNA by conventional RT-PCR. Total RNA was isolated from MCF7 cells either untreated or treated with thapsigargin TG (1 μM) or tunicamycin TM (1 μg/mL) for 24 h, and RT-PCR analysis of total RNA was performed to simultaneously detect both spliced and unspliced XBP1 mRNA (shown by red arrows). (Unspliced XBP1 is XBP1U, Spliced XBP1 is XBP1S.) (c) XBP1 splicing upon exposure to thapsigargin (1 μM) or tunicamycin (1 μg/mL) for 6 h in MDA MB231 cells. Levels of spliced and unspliced XBP1 mRNA were detected using specific probes by qRT-PCR analysis. Expression levels were normalized to RPLP0. (d) Schematic presentation of ERAI plasmid obtained by fusing XBP1 and venus, a variant of the green fluorescent protein (adapted from Iwawaki et al. 2004). (e) 24 h after transfection with F-XBP1-venus and F-XBP1DDBD-venus, 293Τ cells were left untreated or treated with (1 μg/mL) tunicamycin for 24 h and then analyzed by fluorescence microscopy (M marker, TG thapsigargin, TM tunicamycin, XBP1U unspliced XBP1, XBP1S spliced XBP1, CTRL untreated control, and RPLP0 ribosomal protein). Adapted from Samali et al. 2010 [49]

mRNA [30, 50]. One important point to note is that overexpression of F-XBP1-venus construct interferes with the induction of UPR target genes in a dominant-negative manner [30]. In F-XBP1ΔDBD-venus construct, DNA-binding domain (DBD) of XBP1 is deleted. F-XBP1ΔDBD-venus construct is recommended for use, as overexpression of F-XBP1ΔDBD-venus does not affect the induction of UPR target genes and can be used to detect the activation of IRE1 similar to F-XBP1-venus construct (see Note 4).

Selective Activation of UPR Pathways 3.4.1 Protocol for Detecting IRE1 Activation by Fluorescent Microscopy

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1. Seed 293 T cells at 75,000 cells/well in a 24-well plate. 2. 24 h after seeding, transiently transfect cells with F-XBP1venus or F-XBP1ΔDBD-venus using the transfection reagent jetPEI (Polyplus Transfection #101-01 N) at a ratio of 1 μg DNA/2 μL jetPEI per well/24-well plate. 3. Dilute the DNA and jetPEI in 50 μL of NaCl independently and then pool and incubate for 20 min before adding to cells. Perform transfection in antibiotic-free medium. 4. Remove the transfection media after 6–8 h and replace with culture media containing antibiotic. 5. Allow the cells to recover for 24 h post-transfection before ER stress-inducing compounds are added. 6. Treat cells with 1 μg/mL of tunicamycin for 24 h. 7. Remove media 24 h posttreatment, and stain cells with the nuclear dye DAPI and visualize using fluorescent microscopy. Figure 2e shows accumulation of XBP1-venus in the nucleus and the accumulation of XBP1ΔDBD-venus in the cytosol upon tunicamycin treatment (see Note 4).

3.5 Detecting ATF6 Translocation Using Fluorescence Microscopy

After processing by S1P and S2P proteases in the Golgi bodies, the cytoplasm fragment of ATF6 is released from the membrane and translocates into the nucleus, where it activates transcription of its target genes [51, 52]. A GFP-ATF6 fusion protein, which relocates from the ER to the nucleus via the Golgi apparatus in response to ER stress, can be used to monitor the activation of ATF6 by fluorescent microscopy (Fig. 3) (see Note 5). 1. See 293 T cells at 75,000 cells/well in a 24-well plate. 2. 24 h after seeding, transiently transfect cells with pCMVshortGFP-ATF6 (WT) plasmid using the transfection reagent jetPEI (Polyplus Transfection #101-01 N) at a ratio of 1 μg DNA/2 μL jetPEI per well/24-well plate. 3. Dilute the DNA and jetPEI in 50 μL of NaCl independently and then pool and incubate for 20 min before being added to the cells. 4. 24 h after transfection, remove the media containing the DNA-lipid complexes and replace with culture media. 5. Allow the cells to recover for 24 h post-transfection before ER stress-inducing compounds are added. Any other treatment required can be done 24 h after transfection. Treat cells with 1 μg/mL of tunicamycin for 24 h for UPR. 6. Remove media 24 h posttreatment, and stain the cells with the nuclear dye DAPI and visualize using fluorescent microscopy. 7. As shown in Fig. 3, the wild-type GFP-ATF6 was translocated to the nucleus via the Golgi apparatus after tunicamycin treatment.

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Fig. 3 ER stress-induced processing and nuclear translocation of GFP-ATF6. 24 h after transfection with pCMVshort-EGFP-ATF6 (WT), 293T cells were left untreated or treated with 1 μg/mL tunicamycin for the indicated periods. Cells were fixed in 4 % paraformaldehyde, stained with DAPI, and then analyzed by fluorescence microscopy

These results demonstrate that ATF6 is being activated and cleaved under the given conditions and active ATF6 is translocated to the nucleus. 3.6 Chemical Modulators of PERK Activity

Chemical inhibitors can be used to selectively block the activity of PERK. In recent years a small molecule inhibitor has been identified, GSK2656157, which can act as a potent and specific inhibitor of PERK activity [53]. It is an ATP-competitive inhibitor of PERK enzyme activity with an IC(50) of 0.9 nM [53]. It is highly selective for PERK with IC (50) values >100 nM against a panel of 300 kinases. GSK2656157 inhibits PERK activity in cells with an IC(50) in the range of 10–30 nM, which has been shown by inhibition of stress-induced PERK autophosphorylation, eIF2α substrate phosphorylation, and corresponding decreases in ATF4 and CHOP in multiple cell lines [53]. The level of phospho-PERK and phospho-eIF2α can be analyzed by Western blotting as an

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Fig. 4 Selective inhibition and monitoring of the three arms of UPR signaling. (a) Effect of selective IRE1 inhibitors 4μ8C and STF083010 and GSK-PERK inhibitor (GSK-PI) on XBP1 splicing. MCF7 cells were treated with thapsigargin (TG) at 1 μg/mL for 24 to 36 h in the presence or absence of indicated doses of the different inhibitors. RNA isolated was analyzed by RT-PCR. XBP1 splicing was detected by using primers which specifically recognizes the unspliced or the spliced forms of the XBP1 mRNA. The relative concentrations of the two bands indicate the proportion of XBP1 present as spliced form. (b) Effect of selective IRE1 inhibitors 4μ8C and STF083010 and GSK-PERK inhibitor (GSK-PI) on expression of UPR target genes CHOP and GRP78. The RNA sample from (a) was further analyzed using QPCR to evaluate the effect of the inhibitors on the expression of UPR target genes CHOP and GRP78. GSK-PI inhibits PERK activity and compromises the induction of CHOP transcription factor. (M marker, TG thapsigargin, TM tunicamycin, XBP1U unspliced XBP1, XBP1S spliced XBP1, and CTRL untreated control)

indicator for PERK activity. Further, the changes in expression of PERK target genes ATF4 and CHOP can be studied by qRT-PCR. Our group has found this inhibitor to work well within breast cancer cell lines (Fig. 4b). Alternatively, PERK activity can be selectively enhanced using the dihydropyrazole derivative activator CCT020312 (Calbiochem) [54]. CCT020312 increases the phosphorylation of eIF2α in HT29 and MCF7 cells [54]. Increased PERK activity can be similarly assessed by phospho-PERK Western blot or qRT-PCR analysis of target gene downstream of PERK signaling.

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IRE1 Inhibitors

3.7.1 Protocol for Treatment and Evaluation of Inhibitors

The activity of IRE1 can be inhibited by a number of different small molecule inhibitors identified recently, of which 4μ8C (Tocris Bioscience) is one such inhibitor [55]. 4μ8C is a cell-permeable coumarin o-hydroxyaldehyde that inhibits IRE1-RNase activity in a time- and dose-dependent manner (IC (50) = 550 and 45 nM, respectively, with 0 and 16 min drug preincubation needed in RNA cleavage assay). 4μ8C covalently targets IRE1 Lys907 via Schiff base formation, effectively preventing ER stress-induced sitespecific mRNA splicing as well as RIDD (regulated IRE1dependent degradation) mRNA degradation (IC(50) = 6.9 and 4.1 μM, respectively, against XBP1 splicing and Scara3 degradation) in MEF cultures following tunicamycin treatment [55]. Another potent inhibitor of IRE1 activity is STF083010 (Tocris Bioscience), a cell-permeable salicylidene compound that has been shown to directly target IRE1 and disrupt the IRE1-XBP1 UPR arm in RPMI8226 multiple myeloma cells [56]. STF083010 selectively inhibits the ER stress-induced endonuclease activity of IRE1 and blocks XBP1 mRNA splicing in multiple myeloma cells at 60 μM and XBP1 activity in transgenic XBP1-luc mice (bortezomib 1 μg/kg and 60 mg/kg of STF083010) [56]. A further small molecule IRE1 inhibitor, MKC-3946 (MannKind Corp.), is also available. However, our group has not tested this compound. MKC-3946 did not inhibit the phosphorylation of IRE1 but did block XBP1 splicing in multiple myeloma cells [25]. Inhibition of IRE1 activity can be confirmed by analyzing its effect on XBP1 splicing using semiquantitative RT-PCR (Fig. 4a). The figure shows the effect of these inhibitors as a function of dose and time on the activity of IRE1 in response to ER stress induced by tunicamycin and thapsigargin. 1. Cells are maintained in a 25–75 cm2 flask (Sarstedt) as required in the appropriate growth medium (such as DMEM or RPMI) with required supplements and antibiotics. When cells reach a confluency of approximately 80 %, they are trypsinized using 1× trypsin/EDTA (Sigma). 2. For UPR inhibitor experiments, cells can be seeded to the appropriate density in six-well plates or 25 cm2 flasks depending on the number of cells required for the assay. 3. The next day, treatments can be carried out with appropriate doses of IRE1 inhibitors 6 h prior to the treatment under study or 6 h prior to adding known UPR inducers such as tunicamycin, thapsigargin, or brefeldin A. We used 10–100 μM doses for 4μ8C and 100–200 μM of STF083010 in MCF7 and MDA MB231 cells (see Note 6).

Selective Activation of UPR Pathways

3.8 Manipulation of Genetic Expression of UPR Regulators 3.8.1 Dominant Negative of PERK, IRE1, and ATF6

3.8.2 shRNA-Mediated Knockdown of UPR Regulators

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The role of endogenous ATF6 can be studied using a dominantnegative form of ATF6. This is generated by creating point mutations in the basic region of ATF6 in the context of ATF6-(1–373) [31]. These mutations disrupt the DNA-binding activity of the cytoplasmic domain, and it acts as a dominant negative by dimerizing with endogenous ATF6 [31]. This dominant-negative ATF6, ATF6-(1–373)m1, completely inhibited tunicamycin induction of a promoter reporter which contained three ERSE elements, obtained from the rat GRP78 promoter [31]. So the dominantnegative ATF6 blocks the function of endogenous ATF6 and can therefore be used to study the role of endogenous ATF6. Similar dominant-negative constructs are also available for PERK and IRE1, which can block the function of the endogenous protein and can be used to evaluate their role in the process being studied [57]. Here is a detailed example of such an application. Treatment of neuronal cells with ER stress insults, tunicamycin and thapsigargin, increases mtHTT aggregation via IRE1 activation [22]. This function of IRE1 was established in SH-SY5Y cells using wild-type, dominant-negative, and mutant constructs for IRE1, PERK, and ATF6. Human IRE1 cDNA was subcloned into pcDNA3-HA (Invitrogen) (pIRE1-HA). To construct deletion mutants of IRE1, IRE1 ΔC (1–1386) cytosolic domain mutant and IRE1 ΔR (1–2595) endoribonuclease domain mutant were amplified by PCR and subcloned into pcDNA3-HA (pIRE1 ΔC-HA and pIRE1 ΔR-HA, respectively) (Fig. 5a). These constructs can act as dominant negative and inhibit the function of endogenous IRE1 as shown by conventional RT-PCR analysis of XBP1 splicing (Fig. 5b). Ectopic expression of dominant-negative IRE1 (IRE1-DN) lacking its cytosolic region (IRE1 ΔC) abolished ER stress-induced mtHTT aggregation [22]. On the contrary, overexpression of dominant-negative PERK (PERK-DN) mutant or ATF6 [ATF6 (1–373) m1, ATF6 DN] mutant failed to inhibit mtHTT aggregation [22]. Dominant-negative PERK (pPERK-DN) was constructed by subcloning the PCR product of PERK (1–1608) lacking the kinase domain into pcDNA3-HA. The expression of all these constructs was confirmed in cells using Western blotting. Their downstream effects were analyzed by studying the expression of downstream target genes (GRP78, HERP, and CHOP) by qRT-PCR (Fig. 5c). Ectopic expression of ATF6-m1 reduced the UPR-mediated induction of GRP78, while PERK-DN affected the expression of HERP, GRP78, and CHOP (Fig. 5c). Overexpression of IRE1-DN affected XBP1 splicing (Fig. 5c). Cells can be genetically modified to express a shRNA targeting a specific UPR regulator such as PERK, IRE1, or ATF6. Such a knockdown cell line would also help to analyze the role played by each arm of the UPR signaling pathway. The effect of the knockdown could be assessed by the decrease in protein levels or

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Fig. 5 Dominant-negative constructs and selective blocking of UPR signaling. (a) Schematic representation of various mutant constructs of IRE1. (b) Modulation of XBP1 splicing by mutant IRE1. Total RNA was isolated from HEK 293 cells that were transfected with IRE1 mutants, either untreated or treated with thapsigargin (0.5 μM) 6 h, and RT-PCR analysis of total RNA was performed to simultaneously detect both spliced and unspliced XBP1 mRNA and GADPH. (c) Induction of UPR target genes in cells expressing dominant-negative constructs of various UPR regulators and their effects on the expression of UPR target genes upon exposure to tunicamycin. Dominant-negative constructs were expressed in 293T cells as indicated. Cells were treated with 1 μg/mL tunicamycin 24 h after transfection. Total RNA was isolated 24 h after treatment, and the expression levels of the indicated genes were determined by real-time qRT-PCR, normalizing against RPLP0 expression (Adopted from Samali et al. 2010) [49]

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reduction in induction of the target protein in response to UPR. Also a reduction in the mRNA levels (assessed by qRT-PCR analysis) of bonafide target genes can be used to further confirm the functional knockdown. Such knockdown cell lines can be then used to study the role of the target protein in the process being studied. 3.8.3 Overexpression of UPR Regulators

If one specific pathway of UPR signaling or transcription factor is implicated as the major player in a phenomenon, the role of that individual protein can be further studied by overexpressing the protein in a cell line model using mammalian expression vectors or lentiviral transduction. The increased levels of protein can be confirmed by Western blotting. Its functional significance can be evaluated using qRT-PCR analysis to study the mRNA levels of its target genes. These overexpressing cell lines can then be used to evaluate the role of the protein in the process being studied.

3.8.4 Protocol for Transfection of UPR Regulators, DominantNegative Constructs, and shRNA Constructs

1. Cells are seeded at 70–80 % confluency in a six-well plate in serum and antibiotic-free media. 2. 24 h after seeding, the plasmid containing the gene of interest or the dominant-negative construct is transfected into the cells using the appropriate transfection reagent and optimal DNAlipid ratio, which should be optimized for your model system in advance. 3. Harvest cells 24–48 h after transfection. RNA and protein samples are prepared from the cells, and the overexpression or knockdown is confirmed by the RT-PCR or Western blotting for the gene of interest. If the protein is expressed with a tag such as the HA tag or FLAG tag, an antibody detecting the tag can also be used in Western blot analysis. 4. Functional knockdown can be analyzed by treating the cells with tunicamycin or thapsigargin and studying the downstream signaling events. 5. All effects should be compared or normalized with respect to the cells transfected with the control plasmid.

4

Notes 1. Cell lines can be differentially sensitive to different chemical inducers of UPR; therefore, for each cell line, the inducer to be used has to be selected experimentally. Ideally more than one inducer should be used. 2. Each inducer and its dose and time course in a particular cell line has to be optimized.

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3. The end point of experiment has to be optimized such that there is a good induction of UPR response genes such as GRP78 and HERP without inducing too much cell death. 4. It is important to note that the overexpression of XBP1-venus disrupts the induction of its UPR target genes in a dominantnegative manner, whereas XBP1ΔDBD-venus accumulates in the cytosol and does not interfere with endogenous XBP1 regulation of its target genes [30]. 5. One limitation of this approach, however, is that overexpression can sometimes alter the subcellular localization and kinetics of protein trafficking. This problem has been addressed to some extent by expressing GFP-ATF6 from a shortened CMV promoter which has a deletion of 430 base pairs from the 5′-side. The short promoter possesses considerably lower activity than does the full promoter, and GFP-ATF6 expressed using the short CMV promoter is localized exclusively to the ER and translocates to the nucleus similarly to that of endogenous ATF6 [52]. 6. A dose and time response for the chosen compound should be done prior to commencement of experiments, as this will vary with cell type. Cells should be observed under a microscope 12–24 h posttreatment to note the extent of cell death. RNA and protein samples can be isolated at 24 h posttreatment for further analysis.

Acknowledgments This publication has emanated from research conducted with the financial support of Health Research Board (grant numbers HRA_ HSR/2010/24) to S.G. References 1. Hendershot L et al (1996) Inhibition of immunoglobulin folding and secretion by dominant negative BiP ATPase mutants. Proc Natl Acad Sci U S A 93(11):5269–5274 2. Boyce M, Yuan J (2006) Cellular response to endoplasmic reticulum stress: a matter of life or death. Cell Death Differ 13(3):363–373 3. Rutkowski DT, Kaufman RJ (2004) A trip to the ER: coping with stress. Trends Cell Biol 14(1):20–28 4. Marciniak SJ et al (2006) Activation-dependent substrate recruitment by the eukaryotic translation initiation factor 2 kinase PERK. J Cell Biol 172(2):201–209

5. Harding HP, Zhang Y, Ron D (1999) Protein translation and folding are coupled by an endoplasmic-reticulum-resident kinase. Nature 397(6716):271–274 6. Harding HP et al (2003) An integrated stress response regulates amino acid metabolism and resistance to oxidative stress. Mol Cell 11(3):619–633 7. Ma Y et al (2002) Two distinct stress signaling pathways converge upon the CHOP promoter during the mammalian unfolded protein response. J Mol Biol 318(5):1351–1365 8. van Huizen R et al (2003) P58IPK, a novel endoplasmic reticulum stress-inducible protein

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and potential negative regulator of eIF2alpha signaling. J Biol Chem 278(18):15558–15564 Yan W et al (2002) Control of PERK eIF2alpha kinase activity by the endoplasmic reticulum stress-induced molecular chaperone P58IPK. Proc Natl Acad Sci U S A 99(25): 15920–15925 Brush MH, Weiser DC, Shenolikar S (2003) Growth arrest and DNA damage-inducible protein GADD34 targets protein phosphatase 1 alpha to the endoplasmic reticulum and promotes dephosphorylation of the alpha subunit of eukaryotic translation initiation factor 2. Mol Cell Biol 23(4):1292–1303 Ma Y, Hendershot LM (2003) Delineation of a negative feedback regulatory loop that controls protein translation during endoplasmic reticulum stress. J Biol Chem 278(37):34864–34873 Gardner BM et al (2013) Endoplasmic reticulum stress sensing in the unfolded protein response. Cold Spring Harb Perspect Biol 5(3):a013169 Ron D, Walter P (2007) Signal integration in the endoplasmic reticulum unfolded protein response. Nat Rev Mol Cell Biol 8(7): 519–529 Forman MS, Lee VM, Trojanowski JQ (2003) ‘Unfolding’ pathways in neurodegenerative disease. Trends Neurosci 26(8):407–410 Zhao L, Ackerman SL (2006) Endoplasmic reticulum stress in health and disease. Curr Opin Cell Biol 18(4):444–452 Kaser A, Blumberg RS (2009) Endoplasmic reticulum stress in the intestinal epithelium and inflammatory bowel disease. Semin Immunol 21(3):156–163 Laybutt DR et al (2007) Endoplasmic reticulum stress contributes to beta cell apoptosis in type 2 diabetes. Diabetologia 50(4):752–763 Yamamoto K et al (2010) Induction of liver steatosis and lipid droplet formation in ATF6alpha-knockout mice burdened with pharmacological endoplasmic reticulum stress. Mol Biol Cell 21(17):2975–2986 Doyle KM et al (2011) Unfolded proteins and endoplasmic reticulum stress in neurodegenerative disorders. J Cell Mol Med 15(10): 2025–2039 Stefani IC et al (2012) The role of ER stressinduced apoptosis in neurodegeneration. Curr Alzheimer Res 9(3):373–387 Silva RM et al (2005) CHOP/GADD153 is a mediator of apoptotic death in substantia nigra dopamine neurons in an in vivo neurotoxin model of parkinsonism. J Neurochem 95(4): 974–986 Lee H et al (2012) IRE1 plays an essential role in ER stress-mediated aggregation of mutant

23.

24. 25.

26.

27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

38.

37

huntingtin via the inhibition of autophagy flux. Hum Mol Genet 21(1):101–114 Hoozemans JJ et al (2005) The unfolded protein response is activated in Alzheimer’s disease. Acta Neuropathol 110(2):165–172 Lee AS, Hendershot LM (2006) ER stress and cancer. Cancer Biol Ther 5(7):721–722 Mimura N et al (2012) Blockade of XBP1 splicing by inhibition of IRE1alpha is a promising therapeutic option in multiple myeloma. Blood 119(24):5772–5781 Salminen A et al (2009) ER stress in Alzheimer’s disease: a novel neuronal trigger for inflammation and Alzheimer’s pathology. J Neuroinflammation 6:41 Minamino T, Kitakaze M (2010) ER stress in cardiovascular disease. J Mol Cell Cardiol 48(6):1105–1110 Hosoi T, Ozawa K (2010) Endoplasmic reticulum stress in disease: mechanisms and therapeutic opportunities. Clin Sci (Lond) 118(1): 19–29 Boelens J et al (2007) Review. The endoplasmic reticulum: a target for new anticancer drugs. In Vivo 21(2):215–226 Iwawaki T, Akai R (2006) Analysis of the XBP1 splicing mechanism using endoplasmic reticulum stress-indicators. Biochem Biophys Res Commun 350(3):709–715 Wang Y et al (2000) Activation of ATF6 and an ATF6 DNA binding site by the endoplasmic reticulum stress response. J Biol Chem 275(35):27013–27020 Lee AH, Iwakoshi NN, Glimcher LH (2003) XBP-1 regulates a subset of endoplasmic reticulum resident chaperone genes in the unfolded protein response. Mol Cell Biol 23(21): 7448–7459 Wang S, Kaufman RJ (2012) The impact of the unfolded protein response on human disease. J Cell Biol 197(7):857–867 Feldman DE, Chauhan V, Koong AC (2005) The unfolded protein response: a novel component of the hypoxic stress response in tumors. Mol Cancer Res 3(11):597–605 Koumenis C (2006) ER stress, hypoxia tolerance and tumor progression. Curr Mol Med 6(1):55–69 Hetz C, Glimcher LH (2009) Fine-tuning of the unfolded protein response: assembling the IRE1alpha interactome. Mol Cell 35(5): 551–561 Baccelli I, Trumpp A (2012) The evolving concept of cancer and metastasis stem cells. J Cell Biol 198(3):281–293 Xi H et al (2011) 2-Deoxy-D-glucose activates autophagy via endoplasmic reticulum stress

38

39.

40.

41.

42.

43.

44.

45.

46.

47.

Ananya Gupta et al. rather than ATP depletion. Cancer Chemother Pharmacol 67(4):899–910 Moon JL et al (2012) Regulation of brefeldin A-induced ER stress and apoptosis by mitochondrial NADP(+)-dependent isocitrate dehydrogenase. Biochem Biophys Res Commun 417(2):760–764 Torii S et al (1995) Cytotoxicity of brefeldin A correlates with its inhibitory effect on membrane binding of COP coat proteins. J Biol Chem 270(19):11574–11580 Yoshida I et al (2006) Depletion of intracellular Ca2+ store itself may be a major factor in thapsigargin-induced ER stress and apoptosis in PC12 cells. Neurochem Int 48(8): 696–702 Ling YH et al (2009) Activation of ER stress and inhibition of EGFR N-glycosylation by tunicamycin enhances susceptibility of human non-small cell lung cancer cells to erlotinib. Cancer Chemother Pharmacol 64(3):539–548 Yu SM, Kim SJ (2010) Endoplasmic reticulum stress (ER-stress) by 2-deoxy-D-glucose (2DG) reduces cyclooxygenase-2 (COX-2) expression and N-glycosylation and induces a loss of COX-2 activity via a Src kinasedependent pathway in rabbit articular chondrocytes. Exp Mol Med 42(11):777–786 Clement MV, Sivarajah S, Pervaiz S (2005) Production of intracellular superoxide mediates dithiothreitol-dependent inhibition of apoptotic cell death. Antioxid Redox Signal 7(3–4):456–464 Strauss SJ et al (2007) The proteasome inhibitor bortezomib acts independently of p53 and induces cell death via apoptosis and mitotic catastrophe in B-cell lymphoma cell lines. Cancer Res 67(6):2783–2790 Roy B, Lee AS (1999) The mammalian endoplasmic reticulum stress response element consists of an evolutionarily conserved tripartite structure and interacts with a novel stress-inducible complex. Nucleic Acids Res 27(6):1437–1443 Yoshida H et al (1998) Identification of the cisacting endoplasmic reticulum stress response element responsible for transcriptional induction of mammalian glucose-regulated proteins.

48.

49.

50.

51.

52.

53.

54.

55.

56.

57.

Involvement of basic leucine zipper transcription factors. J Biol Chem 273(50):33741–33749 Kokame K, Kato H, Miyata T (2001) Identification of ERSE-II, a new cis-acting element responsible for the ATF6-dependent mammalian unfolded protein response. J Biol Chem 276(12):9199–9205 Samali A et al (2010) Methods for monitoring endoplasmic reticulum stress and the unfolded protein response. Int J Cell Biol 2010:830307 Brunsing R et al (2008) B- and T-cell development both involve activity of the unfolded protein response pathway. J Biol Chem 283(26):17954–17961 Chen X, Shen J, Prywes R (2002) The luminal domain of ATF6 senses endoplasmic reticulum (ER) stress and causes translocation of ATF6 from the ER to the Golgi. J Biol Chem 277(15):13045–13052 Nadanaka S et al (2004) Activation of mammalian unfolded protein response is compatible with the quality control system operating in the endoplasmic reticulum. Mol Biol Cell 15(6):2537–2548 Atkins C et al (2013) Characterization of a novel PERK kinase inhibitor with antitumor and antiangiogenic activity. Cancer Res 73(6):1993–2002 Stockwell SR et al (2012) Mechanism-based screen for G1/S checkpoint activators identifies a selective activator of EIF2AK3/PERK signalling. PLoS One 7(1):e28568 Cross BC et al (2012) The molecular basis for selective inhibition of unconventional mRNA splicing by an IRE1-binding small molecule. Proc Natl Acad Sci U S A 109(15): E869–E878 Papandreou I et al (2011) Identification of an Ire1alpha endonuclease specific inhibitor with cytotoxic activity against human multiple myeloma. Blood 117(4):1311–1314 Page KM et al (2004) Dominant-negative calcium channel suppression by truncated constructs involves a kinase implicated in the unfolded protein response. J Neurosci 24(23):5400–5409

Chapter 3 Assays to Characterize Molecular Chaperone Function In Vitro Martin Haslbeck and Johannes Buchner Abstract Here, we describe a set of assays, using mitochondrial citrate synthase as a model substrate, which are suitable to test for chaperone function of proteins in vitro. Additionally, these assays distinguish between the ability of suppressing the aggregation of diverse substrate proteins by stable interaction (holdase function) and the ability to assist the refolding of substrate proteins (foldase function). Key words Chaperone assay, Protein folding, Protein aggregation, Protein refolding, Citrate synthase, Aggregation suppression, Chaperone function

1

Introduction Molecular chaperones are the most conserved class of stress proteins [1]. They are essential for proteome homeostasis when cells have to endure stressful situations, and some of them are even necessary to ensure the de novo folding of substrate proteins and maintenance of structure at physiological conditions [2]. Specifically, molecular chaperones are able to recognize and bind nonnative proteins, prevent the unspecific aggregation of proteins, and assist in the acquisition of their native structures [1–3]. Commonly, they are subdivided in five major and broadly conserved families: Hsp100s, Hsp90s, Hsp70s, Hsp60s, and small heat shock proteins (sHsps) [1, 2, 4]. In contrast to traditional enzymes, chaperones generally work at stoichiometric ratios to decrease the concentration of nonnative proteins and thus the aggregation potential of folding proteins, as protein aggregation is a higher-order reaction [5]. Molecular chaperones interact promiscuously with a broad range of unfolded proteins [1–4, 6] (Fig. 1). What discriminates a native protein from its nonnative, partially or globally unfolded counterpart is mainly the increased exposure of hydrophobic amino

Christine M. Oslowski (ed.), Stress Responses: Methods and Protocols, Methods in Molecular Biology, vol. 1292, DOI 10.1007/978-1-4939-2522-3_3, © Springer Science+Business Media New York 2015

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Fig. 1 Molecular chaperone mechanism. Citrate synthase folds via increasingly structured intermediates (I1, I2) from the unfolded state (U) to the folded state (N). Under heat shock conditions, this process is reversed. Molecular chaperones bind proteins in nonnative conformations, e.g., I1, I2, and U. Folding of the substrate is triggered by binding and release cycles, which keep the substrate protein on track of the folding pathway. Commonly, molecular chaperones exhibit conformations with different affinities for the substrate. With the exception of the sHsp family of molecular chaperones, the shift from a high-affinity binding state to the low-affinity release state is triggered by ATP binding and hydrolysis

acids, a feature which is recognized by molecular chaperones. Binding may occur to hydrophobic patches, specific peptide sequences, or structural elements of the nonnative protein (Fig. 1). Generally, molecular chaperones do not contribute structural information for folding but prevent unwanted intermolecular interactions. They do this by controlled binding and release of nonnative proteins, which is usually accomplished by a change in affinity of the chaperone for its substrate. In most chaperone families, with the exception of sHsps, this change between at least two affinity states is controlled by the binding and hydrolysis of ATP. Nevertheless, molecular chaperones differ in their mechanism of action and substrate specificity. sHsps seem optimized for efficient binding of nonnative proteins, thus presenting an efficient first line of defense against protein aggregation. These “holdases” are often only expressed upon stress and thus are not needed for de

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novo protein folding, while the “foldases,” like Hsp60, Hsp70, and Hsp90, are commonly constitutively expressed and are also necessary under physiological conditions [2–4]. Progress in understanding the mechanism of chaperone function has been achieved mainly by a reductionist biochemical approach using purified chaperones and “model substrate proteins.” This term implies that the substrate proteins do not necessarily represent natural, in vivo substrates. In many cases, the underlying rationale was that proteins, which are recalcitrant folders in vitro, may also have problems folding in the cell and are therefore good representatives of the unknown natural targets. A number of different substrate proteins have been used to study the function of chaperones including the most common model substrates RuBisCO [7], rhodanese [8], malate dehydrogenase [9], luciferase [10], and citrate synthase [11]. Those substrates differ in their quaternary structure, their rate of folding, and their tendency to undergo irreversible side reactions during folding and unfolding. Among these substrates, citrate synthase is especially well suited to study chaperone functions because unfolding and folding pathways of chemically denatured citrate synthase have been studied in detail [11–14]. Additionally, the influences of the five major families of molecular chaperones on the folding and aggregation of CS have been investigated [15–18]. Especially, when sHsps and their cooperation with the other families of molecular chaperones are studied, citrate synthase is a well-established model substrate, which allows characterizing the corresponding networks [10, 17]. Typical assays analyze that chaperones are able to stabilize a range of model substrates against thermally induced aggregation and to suppress aggregation during refolding. Foldases additionally enhance the efficiency of refolding of model substrates. In contrast, proteins with “chaperone-like” function usually only stabilize specific interacting partner proteins and/or suppress the thermally induced aggregation of model substrates.

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Materials All chemicals used should be of at least pro-analysis grade. 1. Citrate synthase [CS; E.C., 4.1.3.7; MW, 48.969 kDa; dimeric; mitochondrial; from pig heart; E280 nm, 1.78 for a 1 mg/mL solution in a 1 cm quartz cuvette; sp. activity, ~150 U/mg at 25 °C, pH 8.0 for the substrate dithionitrobenzoic acid (DTNB)] (see Note 1) should be purified as described elsewhere [19] or can be purchased in sufficient quality for aggregation and inactivation assays. Prior to use, CS ammonium sulfate suspensions have to be dialysed against TE buffer (see Subheading 2, item 3). For refolding assays, the purchased CS

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should be further purified by size exclusion chromatography (e.g., on Superdex 75 material, GE Healthcare, Munich, Germany) pre-equilibrated in TE buffer. CS stock solutions [at a concentration of 15 μM or 150 μM (monomer)] are prepared in TE buffer by concentrating CS via ultrafiltration using Amicon Ultra microconcentrators with 30 kDa cutoff (Merck Millipore, Darmstadt, Germany). After concentration, precipitated protein must be removed by sedimentation at 40,000 × g for 30 min at 4 °C. Aliquots of 100 μL are shockfrozen in liquid nitrogen and stored at −20 °C (or −80 °C) where they are stable for at least 12 months. Thawed aliquots are stored on ice but should not be refrozen. 2. Molecular chaperones are dialyzed against the respective assay buffers (commonly 40 mM HEPES/KOH, pH 7.5) and should be prepared at concentrations of at least 1 mg/ mL. After dialysis, precipitated content of the molecular chaperone solutions should be removed by sedimentation at 40,000 × g for 30 min at 4 °C. Most dialyzed chaperone solutions can be stored on ice for several days. However, in many cases, long-term storage (and freeze-thawing) of the molecular chaperones in the recommended assay buffers is not possible, and precipitates must be removed at least daily. 3. TE buffer: 50 mM Tris/HCl, 2 mM EDTA, pH = 8.0, sterile filter, and degas (see Note 2). 4. OAA solution: dissolve 10 mM oxaloacetic acid (OAA) in 50 mM Tris base without pH adjustment (see Note 3). 5. DTNB solution: dissolve 10 mM dithionitrobenzoic acid (DTNB) in TE buffer (see Note 4). 6. Acetyl-CoA solution: dissolve 5 mM acetyl coenzyme A (Acetyl-CoA) in TE buffer (see Note 5). Do not freeze and thaw the substrate solutions (2–4), store on ice, and prepare solutions 2 and 3 freshly every day (see Note 6).

3

Methods

3.1 Citrate Synthase Activity Assay

CS catalyzes the reaction of oxaloacetic acid (OAA) and acetyl coenzyme A (Acetyl-CoA) to citrate and CoA [20]. The enzyme activity is determined by a colorimetric test using DTNB, which reacts with the free thiol groups of the reaction product CoA. This reaction can be easily followed in a UV/Vis spectrophotometer at 412 nm. 1. For the activity assay, prepare the reaction mixture consisting of 930 μL of TE buffer, 10 μL of OAA solution, 10 μL of DTNB solution, and 30 μL of Acetyl-CoA solution.

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2. Mix solutions in 1 mL plastic cuvettes and pre-equilibrate at 25 °C (see Notes 7 and 8). 3. Start the reaction by adding 20 μL of a 0.15 μM CS (monomer) solution to one of the pre-equilibrated cuvettes. 4. The change in absorbance at 412 nm is followed for 1 min in a UV/Vis spectrophotometer thermostated at 25 °C. Data points are taken continuously every 2 s. The activity is represented by the slope at the beginning of the enzymatic reaction (see Note 9). The specific activity can be calculated as follows: specific activity (U/mg) = ΔE/min × V/(εdνc), where V is the test volume (mL), ε is the molar extinction coefficient of DTNB (13,600 M−1 cm−1), d is the path length of the cell (cm), ν is the sample volume (mL), and c is the enzyme concentration (mg/mL). 3.2 Thermal Inactivation of CS

1. The inactivation reaction is typically monitored for 60 min incubation at the respective temperature (Fig. 2), determining the specific activity at different time points (e.g., at 0 (=100 % activity), 2, 7, 15, 25, 35, 45, and 60 min).

Fig. 2 Investigating the substrate release from sHsps. The influence of the ATPdependent Hsp70 and Hsp100 chaperone systems on the release of CS from CS-sHsp complexes was investigated using the respective S. cerevisiae proteins. CS (0.15 μM) was incubated in the presence of 0.15 μM Hsp26 (sHsp) at 43 °C for 60 min (filled circle, e.g., inactivation kinetics). Reactivation of CS was started by shifting the reaction to 25 °C and addition of 1 mM OAA as well as 0.3 μM Hsp104 (open circle, Hsp100 system) or a combination of 0.3 μM Hsp104 and 0.3 μM Ssa1/Ydj1 (open square, e.g., Hsp100 and Hsp70/40 system), 5 mM ATP and 5 mM MgCl2. Error bars indicate the variation in three independent experiments

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2. In a test tube on ice, CS (15 μM) is diluted 100-fold into 200 μL of 40 mM HEPES/KOH, pH 7.5 (see Note 10), in the presence or absence of chaperones or a control protein (see Note 11). 3. The activity at the specific time points is determined by pipetting 20 μL of the inactivation reaction into a cuvette containing the reaction mixture. After gently mixing by inverting the cuvette, the enzymatic activity is monitored as described in step 4 of Subheading 3.1. The respective enzymatic activity is set to 100 % for normalization. 4. Inactivation is started by placing the test tube containing the inactivation reaction (see steps 1–2 in Subheading 3.2) in a 43 °C water bath. 5. During the time course of inactivation, 20 μL aliquots are withdrawn at the respective time points, and activity is determined as described in step 3, Subheading 3.2 (see Note 12). 3.3 Reactivation of CS

Either thermally (proceed with step 1 of Subheading 3.3) or chemically (proceed with step 5 of Subheading 3.3), inactivated CS can be used for reactivation: 1. For the preparation of thermally inactivated CS, proceed as described in Subheading 3.2. 2. Commonly, reactivation is started after 45 or 60 min when complete inactivation is observed (Fig. 2; see Note 13). 3. Reactivation after thermal inactivation is initiated by shifting the test tube containing the inactivation reaction to a 25 °C water bath and subsequent addition of 1 mM OAA (see Note 14) and varying concentrations and combinations of chaperones (Fig. 2). 4. Follow the kinetics of reactivation for up to 4 h by determining the activity as described in step 4 of Subheading 3.1.4 at different time points (e.g., at 0, 5, 10, 15, 20, 30, 45, 60, 120, 180, and 240 min.) 5. For reactivation of chemically inactivated CS, first unfold 150 μM CS by 1:10 dilution into 4 M guanidinium chloride (GdmCl) in TE buffer and incubate for 2 h at 16 °C (see Note 15). Prior to the reactivation measurements, control the activity of the denatured CS, which should be 0, as described in step 3 of Subheading 3.1. 6. Dilute the unfolded CS 1:10 in TE buffer including 1 mM OAA, pre-equilibrated at 25 °C with or without additional chaperones. 7. Follow the kinetics of reactivation for up to 4 h by determining the activity as described in step 4 in Subheading 3.1 (e.g., at the following time points: 0, 5, 10, 15, 20, 30, 45, 60, 120, 180, and 240 min).

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Fig. 3 Suppression of the thermally induced aggregation of CS by a sHsp. A typical chaperone assay using CS as substrate is shown. The influence of increasing amounts of Hsp26 (sHsp from S. cerevisiae ) on the thermal aggregation of CS was monitored. (a) CS (final concentration, 0.6 μM) was diluted into a thermostated solution of 0.3 μM (inverted open triangle ), 0.6 μM (filled triangle ), and 1.2 μM (filled square ) Hsp26. Closed circles (filled circle ) represent the spontaneous aggregation of CS at 43 °C. The kinetics of aggregation was determined by measuring the absorbance of the samples at 360 nm. (b) The degree of aggregation reached at the plateau of the reaction (after 45 min) for different ratios of Hsp26:CS is shown. The resulting sigmoidal graphs allow determining the ratio needed for half maximum suppression of aggregation. The error bars indicate the mean of three independent experiments

3.4 Thermally Induced Aggregation of CS

The assay is suitable to analyze whether a protein is able to stabilize other proteins against thermal unfolding (Fig. 3). 1. The increase in light scattering is monitored to visualize the thermal aggregation of CS (see Note 16). 2. Pre-equilibrate 40 mM HEPES/KOH pH 7.5 with and without additional chaperones at 43 °C (see Note 17). 3. Monitor the initial light scattering signal at 360 nm, which should be constant. Take data points at least every min (see Notes 18 and 19). The signal prior to CS addition is set to 0 (= no aggregation). 4. Using a UV/Vis spectrophotometer (Fig. 3a), after 5 min (see Note 20), dilute CS to an end concentration of 0.6 μM (4:100 using the 15 μM stocks) into the pre-equilibrated cuvettes of the running kinetics (see Note 21). The kinetics should be monitored for 45–60 min (until a plateau is reached). 5. The plateau of CS aggregation in the absence of additional chaperones is set to 1 (= complete aggregation) for normalizing the data sets. 6. To visualize influences of chaperones on the thermal aggregation of CS, a range from sub-stoichiometric ratios to an excess of chaperone vs. CS (typically 0.125–16:1) is recommended (Fig. 3; see Notes 12 and 22).

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7. To compare the efficiency of different chaperones, the ratio chaperone to CS needed for half maximal suppression of aggregation can be used (Fig. 3b; see Note 23). 3.5 Chemically Induced Aggregation of CS

1. 150 μM CS is unfolded by 1:10 dilution into 4 M GdmCl and 40 mM HEPES/KOH (pH 7.5) and incubated for 2 h at 16 °C prior to use. 2. Pre-equilibrate 40 mM HEPES/KOH pH 7.5 with and without additional chaperones at 25 °C in 200 μL quartz cuvettes. 3. Start measurements by following the absorption (light scattering; see Note 16) signal at 360 nm in a UV/Vis spectrophotometer, taking data points every 5 s (Fig. 4). 4. The baseline signal is set to 0 (= no aggregation) for normalization. 5. Aggregation of the unfolded CS is induced by diluting it 1:100 to a final concentration of 0.15 μM into the preequilibrated cuvette (see Note 24). 6. Aggregation is monitored for up to 15 min, until a plateau is reached (see Note 25). The plateau of CS aggregation in the absence of additional chaperones is set to 1 (= complete aggregation) for normalizing the data sets.

Fig. 4 Temperature dependence of the suppression of the chemically induced aggregation of CS by a sHsp. A typical assay of chemically induced aggregation of 0.15 μM CS measured in a UV/Vis spectrophotometer is shown (open square). CS aggregation was suppressed by the presence of 0.6 μM Hsp26 which was incubated for 20 min at 25 °C (open triangle), 37 °C (open diamond), or 43 °C (open circle) prior to its use in the assay

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7. To visualize influences of chaperones on the chemical aggregation of CS, a range from sub-stoichiometric ratios to an excess of chaperone/CS (typically 0.125–16:1) is suitable (see Notes 22 and 26). The chaperones are added to the pre-equilibrated buffer in quartz cuvettes directly before the addition of CS.

4

Notes 1. Mitochondrial CS is one of the few substrates which can be used for a variety of assays, allowing a complete functional description of a chaperone using only one substrate. Furthermore, the three-dimensional structure of CS is known, and the folding pathway of CS is thoroughly described [11, 12, 16], allowing profound conclusions and especially the separation of effects on early and late unfolding intermediates. CS is a nuclear-encoded α-helical protein which is imported into mitochondria posttranslationally where it catalyzes the first step of the citric acid cycle, the condensation of oxaloacetic acid (OAA) and acetyl-CoA to citrate and coenzyme A. In E. coli, CS was identified as an in vivo substrate of GroE [21], and it can be used as a general substrate for molecular chaperones because it rapidly denatures and aggregates at temperatures >37 °C [20, 22]. When bound to CS, the substrate OAA stabilizes CS by locking it in an active conformation, shifting the midpoint of thermal transition from 43 °C to 66.5 °C [22]. The characterization of the folding/unfolding pathway of CS [11, 12] revealed the presence of at least two unfolding intermediates, which are in equilibrium with the native state (Fig. 1). Depending on the individual molecular chaperone and its specific properties of substrate recognition, influences on the inactivation kinetics, reactivation kinetics, yield of reactivated species, and aggregation kinetics of thermally unfolding or chemically refolding CS can be used for characterization. Individual molecular chaperones may differ in their propensity to recognize different types of intermediates. “Chaperonelike” proteins, however, commonly only stabilize the native enzyme and inhibit unfolding but do not recognize completely unfolded intermediates of CS. 2. The pH value of Tris buffers is temperature dependent. Adjust the pH at the respective temperature used in the assay. Use 32 % HCl for adjusting the pH. 3. OAA is acidic. It does not dissolve completely in TE buffer. 4. DTNB is poorly soluble and gives an emulsion. Extended stirring at 4 °C is needed to dissolve DTNB, prior to use. 5. Acetyl-CoA is a fluffy powder. Weigh in carefully.

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6. Be aware that only small volumes of the solutions are needed. Weigh in the mg amounts needed on an analytical balance. 7. Prepare in advance one cuvette for each time point of the inactivation kinetics. Cuvettes should be pre-equilibrated using a temperature-controlled water bath. 8. To ensure the reproducibility of the measurements, throughout all experiments, special care should be taken to pipette correct solution volumes, especially when handling small volumes. Droplets and solution films on the outside of the pipette tip must be avoided; use light-duty tissue wipers (low lint, low extractables, antistatic) to clean the outside of the pipette tip before transferring the volumes to the cuvettes or reaction devices. 9. Because the slope at the beginning of the reaction is used for comparison, it is essential that pipetting steps and sample processing are always performed at the same speed. Some training of the assay handling might be needed. Typically, triplicates of measurements performed by well-trained researchers should not deviate by more than 5–10 %. 10. CS is stabilized by Tris and high salt concentrations. If possible dialyze chaperones into HEPES/KOH, pH 7.5, at low salt concentrations (below 50 mM). 11. To visualize influences of chaperones on the inactivation of CS, a range from stoichiometric ratios (chaperone/CS) to an excess of 32:1 (chaperone/CS) is suitable. Always perform buffer controls by adding the identical volume of dialysis buffer without chaperone to the CS inactivation reaction. This ensures that stabilizing effects of buffer components are not misinterpreted. 12. High-quality, lipid-free bovine serum albumin (BSA) is recommended as a non-chaperone control protein. BSA should not show influences on the inactivation kinetics of CS up to ratios of 80:1 (BSA:CS). 13. Upon complete inactivation, all CS molecules are monomerized or aggregated. It is possible to investigate the influence of chaperones on early unfolding intermediates (e.g., inactive but still dimeric CS or monomeric but not completely unfolded or aggregated molecules) by initiating the reactivation when 50 % inactivation is reached. 14. The addition of OAA, e.g., ligand, stabilizes the refolded CS dimers, enhancing refolding efficiency. The addition of 1 mM OAA without temperature shift can be used to investigate refolding at 43 °C. Refolding by a temperature shift to 25 °C alone is possible to some extent, but in this case longer refolding kinetics have to be monitored.

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15. 15 μM CS solution in 4 M GdmCl can be aliquoted, shockfrozen in liquid nitrogen, and stored at -20 °C. Freeze-thaw cycles must be avoided. 16. Best results are achieved when light scattering is monitored in a fluorescence spectrophotometer setting the excitation and emission wavelength to 360 or 400 nm and using thermostated, stirred quartz cuvettes. The emission and excitation slits should be set to 2–5 nm. Alternatively, it is also possible to monitor good aggregation kinetics in a UV/Vis spectrophotometer (Fig. 3) at an absorbance of 360 or 400 nm, in thermostated quartz cuvettes. At 360 nm, where smaller aggregates are already detected, usually more change in signal is observed than at 400 nm. However, the signal stability (signal to noise ratio) is usually better at 400 nm. 17. The assay volume depends on the cuvettes used; we recommend stirred 1.5 mL quarts cuvettes for use in a fluorescence spectrophotometer and 200 μL quartz cuvettes (black with windows) for use in a UV/Vis spectrophotometer. 18. Using a UV/Vis spectrophotometer, taking data points every 15 s is recommended. 19. During aggregation not only the number of aggregates but also the size of the aggregates increases, resulting in graphs where the signal might decrease again at the end of the kinetics. 20. A stable signal should be obtained. 21. When using a UV/Vis spectrophotometer, final CS concentrations of 0.6–2 μM are recommended. The change in absorbance signal at 360 nm for 0.6 μM CS is typically ~0.1–0.2 and ~0.4– 0.6 for 2 μM CS, depending on the type of the UV/Vis spectrophotometer. For smaller changes in signal, usually more experimental repeats are needed. Using a fluorescence spectrophotometer, an end concentration of 0.15 μM CS is sufficient. 22. Identical volumes of chaperone dialysis buffer should be used as a control to exclude stabilizing effects of buffer components. 23. The effect of a chaperone should be concentration dependent and thus titratable, leading to usually sigmoidal titration curves. Because aggregation processes are complex reactions, the comparison of curve slopes or lag phases is not recommended. Identical buffer conditions are mandatory for the direct comparison of different chaperones. The obtained values will vary when other substrate proteins are used, and the values vary depending on the assay used (e.g., to suppress the chemically induced aggregation of CS, usually more chaperone is needed than for suppressing thermal aggregation). 24. After dilution, denatured CS starts to refold, which is unproductive under these buffer conditions and results in aggregation. Because the aggregation process starts at the level of

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unfolded nascent chains, the efficiency of molecular chaperones may vary depending on the underlying molecular mechanism of interaction. Similar to the thermally induced aggregation of CS, higher concentrations (typically 0.15–2 μM) of CS can be used, depending on the changes in signal achieved in the spectrophotometer. 25. In contrast to the thermally induced aggregation, the chemically induced aggregation is much faster. Commonly spontaneous CS aggregation reaches saturation 5–10 min after dilution into the pre-equilibrated cuvette (Fig. 4). 26. The enzymatic assay itself is always performed at 25 °C. However, this assay is especially suitable to determine the temperature-dependent activation of chaperones. Especially, ATP-independent sHsps seem to regulate the switching between the high- and low-affinity substrate binding states by temperature (e.g., Hsp26, a sHsp from S. cerevisiae, is activated by heat stress temperatures (Fig. 4)). Hsp26 was incubated 20 min at different temperatures prior to the measurement of the aggregation suppression at a ratio of 4:1 (Hsp26:CS).

Acknowledgments We thank Isabel Schulien for excellent experimental assistance. This research was supported by the Deutsche Forschungsgemeinschaft (SFB 1035, A06). References 1. Richter K, Haslbeck M, Buchner J (2010) The heat shock response: life on the verge of death. Mol Cell 40:253–266 2. Vabulas RM, Raychaudhuri S, Hayer-Hartl M, Hartl FU (2010) Protein folding in the cytoplasm and the heat shock response. Cold Spring Harb Perspect Biol 2:a004390 3. Walter S, Buchner J (2002) Molecular chaperones-cellular machines for protein folding. Angew Chem Int Ed Engl 41: 1098–1113 4. Bukau B, Weissman J, Horwich A (2006) Molecular chaperones and protein quality control. Cell 125:443–451 5. Kiefhaber T, Rudolph R, Kohler HH, Buchner J (1991) Protein aggregation in vitro and in vivo: a quantitative model of the kinetic competition between folding and aggregation. Biotechnology (N Y) 9:825–829 6. Viitanen PV, Gatenby AA, Lorimer GH (1992) Purified chaperonin 60 (groEL) interacts with

7.

8.

9.

10.

the nonnative states of a multitude of Escherichia coli proteins. Protein Sci 1:363–369 Goloubinoff P, Gatenby AA, Lorimer GH (1989) GroE heat-shock proteins promote assembly of foreign prokaryotic ribulose bisphosphate carboxylase oligomers in Escherichia coli. Nature 337:44–47 Mendoza JA, Lorimer GH, Horowitz PM (1992) Chaperonin cpn60 from Escherichia coli protects the mitochondrial enzyme rhodanese against heat inactivation and supports folding at elevated temperatures. J Biol Chem 267:17631–17634 Lee GJ, Roseman AM, Saibil HR, Vierling E (1997) A small heat shock protein stably binds heat-denatured model substrates and can maintain a substrate in a folding-competent state. EMBO J 16:659–671 Bepperling A, Alte F, Kriehuber T, Braun N, Weinkauf S, Groll M, Haslbeck M, Buchner J (2012) Alternative bacterial two-component

Analysis of Chaperone Function In Vitro

11.

12.

13.

14.

15.

16.

small heat shock protein systems. Proc Natl Acad Sci U S A 109:20407–20412 Grallert H, Rutkat K, Buchner J (1998) GroEL traps dimeric and monomeric unfolding intermediates of citrate synthase. J Biol Chem 273:33305–33310 Grallert H, Buchner J (1999) Analysis of GroE-assisted folding under nonpermissive conditions. J Biol Chem 274:20171–20177 Jaenicke R (1993) What does protein refolding in vitro tell us about protein folding in the cell? Philos Trans R Soc Lond B Biol Sci 339:287–294 Buchner J, Grallert H, Jakob U (1998) Analysis of chaperone function using citrate synthase as nonnative substrate protein. Methods Enzymol 290:323–338 Buchner J, Schmidt M, Fuchs M, Jaenicke R, Rudolph R, Schmid FX, Kiefhaber T (1991) GroE facilitates refolding of citrate synthase by suppressing aggregation. Biochemistry 30: 1586–1591 Jakob U, Lilie H, Meyer I, Buchner J (1995) Transient interaction of Hsp90 with early unfolding intermediates of citrate synthase. Implications for heat shock in vivo. J Biol Chem 270:7288–7294

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17. Haslbeck M, Miess A, Stromer T, Walter S, Buchner J (2005) Disassembling protein aggregates in the yeast cytosol: The cooperation of Hsp26 with Ssa1 and Hsp104. J Biol Chem 280:23861–23868 18. Ehrnsperger M, Graber S, Gaestel M, Buchner J (1997) Binding of non-native protein to Hsp25 during heat shock creates a reservoir of folding intermediates for reactivation. EMBO J 16:221–229 19. Haslbeck M, Schuster I, Grallert H (2003) GroE-dependent expression and purification of pig heart mitochondrial citrate synthase in Escherichia coli. J Chromatogr B Analyt Technol Biomed Life Sci 786:127–136 20. Srere PA (1966) Citrate-condensing enzymeoxaloacetate binary complex. Studies on its physical and chemical properties. J Biol Chem 241:2157–2165 21. Horwich AL, Low KB, Fenton WA, Hirshfield IN, Furtak K (1993) Folding in vivo of bacterial cytoplasmic proteins: role of GroEL. Cell 74:909–917 22. Zhi W, Srere PA, Evans CT (1991) Conformational stability of pig citrate synthase and some active-site mutants. Biochemistry 30:9281–9286

Chapter 4 Analysis of the Heat Shock Factor Complex in Mammalian HSP70 Promoter Mitsuaki Fujimoto, Ryosuke Takii, Naoki Hayashida, and Akira Nakai Abstract The heat shock response is characterized by the induction of heat shock proteins (HSPs) and is one of prominent mechanisms that regulate proteostasis capacity in the cell. In mammals, heat shock factor 1 (HSF1) regulates the expression of HSPs transcriptionally in both unstressed and stressed cells. Recent reports show that the HSF1-RPA complex constitutively gains access to nucleosomal DNA in part by recruiting a histone chaperone and a chromatin-remodeling component. Here, we describe the strategies to substitute endogenous HSF1 with ectopically expressed HSF1 or its mutant and to detect the occupancy of HSF1 transcription complex including RPA in vivo on two heat shock response elements located close together in the human or mouse HSP70 promoters by chromatin immunoprecipitation assay with high sensitivity and specificity. Key words Heat shock, Transcription, Nucleosome, Adenovirus, Knockdown, Chromatin immunoprecipitation

1

Introduction All living organisms respond to elevated temperatures by producing a limited set of evolutionally conserved heat shock proteins (HSPs) or chaperones, which facilitate protein folding, and numerous non-HSP proteins with diverse functions, including protein degradation and metabolisms [1–3]. This response, called the heat shock response, is a universal adaptive response to proteotoxic stress including heat shock and oxidative stress [4] and is one of prominent mechanisms of controlling proteostasis capacity [5]. The heat shock response is regulated at the level of transcription by evolutionally conserved heat shock factor (HSF) that binds to heat shock response elements (HSEs) in eukaryotes [6]. Transcriptional regulation of this response has been extensively studied as a model system of inducible gene expression [7, 8]. Metazoan HSF1 remains as an inactive monomer in unstressed cells and is converted to an active trimer that binds to the HSE

Christine M. Oslowski (ed.), Stress Responses: Methods and Protocols, Methods in Molecular Biology, vol. 1292, DOI 10.1007/978-1-4939-2522-3_4, © Springer Science+Business Media New York 2015

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during heat shock [9–11]. However, HSF1 by itself cannot gain access to nucleosomal DNA [12, 13]. In Drosophila, GAGA factor restricts nucleosome occupancy in the HSP70 promoter, allowing for the establishment of paused RNA polymerase II in unstressed condition and quick access of HSF upon heat shock [7]. HSF binding induces the rapid loss of nucleosomes within the body of HSP70 [14], which is followed by the activation and spread of poly(ADP-ribose) polymerase, recruitment of elongation factors such as P-TEFb and Spt6, and histone-modifying enzymes including Trithorax and CREB-binding protein (CBP) [15–17]. HSF also binds constitutively to limited developmental loci in vivo [18]. In fact, analysis of the genome-wide distribution of HSF by the ChIP-seq assay revealed only 20 HSF-binding sites in unstressed Drosophila cells and as much as 464 sites in heat-shocked cells [19]. In mammals, little is known about mechanisms of HSF1mediated opening of the chromatin structure and formation of the transcription complex. HSF1 was at least shown to promote its transcription by recruiting a chromatin-remodeling complex containing BRG1 during heat shock [20, 21]. Although amount of trimeric HSF1 in unstressed cells is far less than that in heatshocked cells, a weak, but distinct HSE-binding activity was also detected in extracts of unstressed human cervical carcinoma HeLa cells [22]. Actually, HSF1 deficiency resulted in impaired neurogenesis and altered behavior [23–26], ciliary dyskinesia [27], and reduced immune response [28, 29] in mice. The ChIP-chip and ChIP-seq analyses showed that HSF1 binds to many genomic loci even in unstressed cells [30–32]. We first showed that HSF1 binds to IL-6 gene as well as HSP70 gene in vivo in unstressed primary MEF cells and opens the chromatin structure [33, 34]. HSF1 also regulates the expression of various proteostasis capacity pathways in unstressed MEF and HeLa cells [3], indicating a significant physiological role of its constitutive DNA binding [35]. HSF1 forms a complex with replication protein A (RPA) [36], which binds to and stabilizes single-strand DNA (ssDNA) regions during DNA replication and repair [37]. This HSF1-RPA complex gains access to nucleosomal DNA in part by recruiting a histone chaperone FACT and BRG1 [36], suggesting that HSF1 is a “pioneer” transcription factor, which is first able to access its target element in nucleosomal DNA when other factors cannot [38, 39]. In mouse HSP70 (HSP70.3, also known as HSPA1A) promoter, proximal HSE (pHSE) (-91 to -120) and distal HSE (dHSE) (-172 to -216) are located close together (Fig. 1). Chromatin immunoprecipitation (ChIP) assay shows that HSF1 constitutively binds to pHSE at a low level, but not to dHSE, and its binding dramatically increases in both pHSE and dHSE during heat shock (Fig. 2) [36]. Constitutive HSF1 binding to pHSE is

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Fig. 1 Proximal and distal HSEs in mouse HSP70.3 (also known as HSPA1A) promoter. (a) Schematic representation of mHSP70.3 locus. Amplified DNA regions by real-time PCR are shown as gray boxes. dHSE (-172 to -216), pHSE (-91 to -120), and intergenic region. (b) Nucleic acid sequences of mHSP70.3 promoter. The pHSE and dHSE are boxed. Consensus nGAAn units are underlined and conserved nucleotides shown as red. Arrows indicate primers used for real-time PCR (see Table 1)

Fig. 2 Occupancy of HSF1 and RPA1 on the pHSE and dHSE in mouse HSP70.3 promoter during heat shock. MEF cells maintained at 37 °C (control) were treated with heat shock for 10 min (10 min HS). ChIP analyses were performed using HSF1 (a) or RPA1 (b) antibody

eliminated by HSF1 knockdown and is restored by overexpression of wild-type HSF1, but not by any interaction mutant (hHSF1G87S or hHSF1G87A) (Fig. 3a, c). Furthermore, RPA1 occupies the pHSE only when it interacts with HSF1 (Fig. 3b). The pHSE (-86 to -115) and dHSE (-179 to -223) are also located close together in human HSP70 (HSP70-1, also known as HSPA1A) promoter (Fig. 4). HSF1 and RPA1 constitutively occupy the pHSE in HeLa and melanoma HMV-1 cells, but they did not when wild-type HSF1 is substituted with its interaction mutant (Fig. 5) [36].

Fig. 3 Occupancy of hHSF1 mutants and RPA1 on the pHSE and dHSE in mouse HSP70.3 promoter. Wild-type hHSF1, each hHSF1 mutant, or GFP was expressed in wild-type (HSF1+/+, gray bars) or HSF1-null (HSF1−/−, white bars) MEF cells. ChIP analyses were performed using HSF1 (a) or RPA1 (b) antibody. (c) Western blotting was performed using each specific antibody

Fig. 4 Proximal and distal HSEs in human HSP70-1 (also known as HSPA1A) promoter. (a) Schematic representation of hHSP70-1 locus. Amplified DNA regions by real-time PCR are shown as gray boxes. dHSE (-179 to -223), pHSE (-86 to -115), and intergenic region. (b) Nucleic acid sequences of hHSP70-1 promoter. The pHSE and dHSE are boxed. Consensus nGAAn units are underlined and conserved nucleotides shown as red. Arrows indicate primers used for real-time PCR (see Table 1)

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Fig. 5 Occupancy of hHSF1 mutants on the pHSE in human HSP70-1 promoter. Human HeLa (a) or HMV (b) cells were infected with Ad-SCR (gray bars) or Ad-sh-hHSF1-KD1 (white bars) and then with adenovirus expressing wild-type hHSF1, each hHSF1 mutant, or GFP. ChIP analyses were performed using HSF1 antibody (upper). Western blotting was performed using each specific antibody (lower)

The aim of this chapter is to describe strategies to detecting the occupancy of HSF1 transcription complex including RPA1 in vivo on the pHSE and dHSE located close together in HSP70 promoter in immortalized MEF or HeLa cells by ChIP assay with high sensitivity and specificity. We also provide protocols for substituting endogenous HSF1 with ectopically expressed HSF1 or its mutant, which cannot interact with RPA1.

2 2.1

Materials Cell Culture

1. Culture medium: Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10 % fetal bovine serum (FBS). 2. 10× PBS stock buffer: Dissolve 80 g of NaCl, 2 g of KCl, 14.4 g of Na2HPO4, and 2.4 g of KH2PO4 in 800 mL distilled

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H2O (dH2O). Adjust pH to 7.4 and volume to 1 L with additional dH2O. Sterilize it by autoclaving. 3. 1× PBS: Dilute 50 mL of 10× PBS stock buffer in 450 mL of sterilized dH2O. 2.2

Adenovirus

1. Adenovirus stock solution: 10 % glycerol in 1× PBS. 2. Adenovirus titer: Determine titer by 50 % tissue culture infectious dose (TCID50) assay.

2.3

ChIP

1. Formaldehyde solution (~37 %). 2. ChIP Assay Kit (catalog number: 17-295) (Millipore, Billerica, MA, USA). ●

SDS lysis buffer: Containing protease inhibitors (1 mM phenylmethylsulfonyl fluoride, 1 μg/mL aprotinin, and 1 μg/mL pepstatin A).

●

Salmon sperm DNA/protein A agarose (50 % slurry).

●

ChIP dilution buffer.

●

Immune complex wash buffer: low salt, high salt, and LiCl.

●

1× TE.

●

Elution buffer: 1 % SDS, 0.1 M NaHCO3.

3. Power SYBR Green PCR Master Mix (2×) (catalog number 4368577) (Applied Biosystems/ Life Technologies, Carlsbad, CA, USA).

3

Methods

3.1 Heat Shock Treatment

1. Prepare 2 × 106 immortalized wild-type MEF cells (stock #10) in 10 mL culture medium on each 10 cm dish, and incubate them for 16–24 h at 37 °C in 5 % CO2. 2. For the treatment of cells with heat shock, the cell culture dish is sealed with Parafilm and is submerged into water bath at 42 °C for indicated periods (see Note 1). 3. Move to Subheading 3.4.

3.2 Overexpression of HSF1 Mutants

1. Prepare 2 × 105 immortalized wild-type (HSF1+/+; stock #10) and HSF1-null (HSF1−/−; stock #4) MEF cells (see Note 2) in 10 mL culture medium on each 10 cm dish, and incubate them for 16–24 h at 37 °C in 5 % CO2. 2. Wash the cells twice with 1× PBS, and add 2 mL of serum-free DMEM. To overexpress HSF1 mutants as well as wild-type HSF1, add Ad-hHSF1 (human HSF1), Ad-hHSF1-G87S, or Ad-hHSF1-G87A at a final virus titer of 1 × 107 pfu/mL into each dish (see Note 3), and incubate the cells for 2 h at 37 °C in

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Table 1 Primer sequences used for ChIP assay CHIP-qPCR

Forward primer

Reverse primer

mHSP70.3 (dHSE) (−235 to −172)

5′-ACCCTCCCCCTCAGG AATC-3′

5′-GTCCAGAACTCTCCAGAGGTTT-3′

mHSP70.3 (pHSE) (−151 to −54)

5′-GATTACTCAAGGGAG GCGGG-3′

5′-TCCGCTGGGCCAATCA-3′

mIntergenic (+3138 to +3218)

5′-GTGGCGCATGCCTT TGAT-3′

5′-CTTTGTAGAACAGGCTGACCTTGA-3′

hHSP70-1 (dHSE) (−221 to−146)

5′-CCCTGTCCCCTCCA GTGAAT-3′

5′-ACCAATCAGAGGCCAGAGT-3′

hHSP70-1 (pHSE) (−124 to −48)

5′-GACGGGAGGCGAA AACCCT-3′

5′-CTTTTCCCTTCTGAGCCAATCA-3′

hIntergenic (+2784 to +2840)

5′-CCCAGGAAGCAGTG GTAGCA-3′

5′-GCCCAGGCTAGAGTGCAATG-3′

5 % CO2. As a control, add Ad-GFP at the same titer (see Note 4). Wash the cells twice with PBS, and add 10 mL of culture medium. Incubate the cells for 46 h at 37 °C in 5 % CO2. 3. Move to Subheading 3.4. 3.3 HSF1 Substitution

1. Prepare 1 × 105 human cervical carcinoma HeLa and melanoma HMV cells in 10 mL culture medium on each 10 cm dish, and incubate them for 16–24 h at 37 °C in 5 % CO2. 2. Wash the cells twice with 1× PBS, and add 2 mL of serum-free DMEM. For HSF1 knockdown, add Ad-sh-hHSF1-KD1 at a final virus titer of 1 × 107 pfu/mL (see Note 5), and incubate the cells for 2 h at 37 °C in 5 % CO2. As a control, add Ad-shSCR at the same titer (see Note 6). Wash the cells twice with 1× PBS, and add 10 mL of culture medium. Incubate the cells for 22 h at 37 °C in 5 % CO2. 3. Wash the cells twice with 1× PBS, and add 2 mL of serum-free DMEM. To overexpress HSF1 mutants as well as wild-type HSF1, add Ad-hHSF1, Ad-hHSF1-G87S, or Ad-hHSF1G87A at a final virus titer of 1 × 106 pfu/mL into Ad-shhHSF1-KD1-infected cells (see Note 3), and incubate the cells for 2 h at 37 °C in 5 % CO2. As a control, add Ad-GFP at the same titer into Ad-sh-hHSF1-KD1-infected cells as well as Ad-sh-SCR-infected cells. Wash the cells twice with PBS, and add 10 mL of culture medium. Incubate the cells for 46 h at 37 °C in 5 % CO2. 4. Move to Subheading 3.4.

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3.4 Chromatin Immunoprecipitation

1. To cross-link DNA to associated proteins in vivo, add formaldehyde solution (~37 %) directly to culture medium in the cell culture dishes to a final concentration of 1 % and mix well (see Note 7). Incubate at 37 °C for 10 min. 2. Remove the culture medium completely. Wash the cells twice with ice-cold 1× PBS containing protease inhibitors (1 mM phenylmethylsulfonyl fluoride, 1 μg/mL aprotinin, and 1 μg/ mL pepstatin A), and add 500 μL of the same solution. Collect the cells into 1.5 mL microcentrifuge tube by using a rubber scraper. Centrifuge the tube at 2,000 × g-force for 4 min at 4 °C, and remove supernatant. 3. Suspend the cell pellet in 200 μL of SDS lysis buffer, and incubate on ice for 10 min. 4. Sonicate the cell lysate on ice to shear DNA into fragments, whose average sizes are 100–300 base pairs (see Note 8). 5. Centrifuge the sonicated cell lysate at 13,000 × g-force at 4 °C for 10 min. Transfer the supernatant (200 μL) into a new 2 mL microcentrifuge tube, and add 1.8 mL of ChIP dilution buffer. 6. To reduce nonspecific background, mix the diluted cell supernatant with 80 μL of salmon sperm DNA/protein A agarose (50 % slurry) and rotate at 4 °C for 30 min (see Note 9). 7. Centrifuge the mixture at 1,000 × g-force at 4 °C for 1 min, and transfer the supernatant to a new 2 mL microcentrifuge tube. 8. For preparing input DNA, transfer 1 % (20 μL) of the supernatant to a new 1.5 mL microcentrifuge tube. To reverse protein-DNA cross-links, add 1 μL of 5 M NaCl and heat at 65 °C for 4 h. 9. For ChIP, add 3 μL anti-HSF1 antibody (α-mHSF1j) (see Note 10), 10 μL anti-RPA1 antibody (sc-28304, Santa Cruz Biotechnology), or IgG to the remaining supernatant (2 mL), and rotate the microcentrifuge tube at 4 °C overnight. 10. Add 60 μL of salmon sperm DNA/protein A agarose (50 % slurry) to the tube, and rotate it at 4 °C for 1 h. Centrifuge the tube at 1,000 × g-force at 4 °C for 1 min, and remove the supernatant. 11. Mix the precipitated agarose beads with 1 mL of wash buffers listed below and rotate at 4 °C for 3 min. Centrifuge the tube at 1,000 × g-force at 4 °C for 1 min, and remove the supernatant. Low salt immune complex wash buffer, one wash. High salt immune complex wash buffer, one wash. LiCl immune complex wash buffer, one wash. 1× TE, two washes. 12. Add 250 μL of elution buffer (1 % SDS, 0.1 M NaHCO3) to the precipitated agarose beads, and mix well by vortexing it shortly. Incubate it at room temperature for 15 min.

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13. Centrifuge the tube at 1,000 × g-force at room temperature for 1 min, and transfer the supernatant to a new 1.5 mL microcentrifuge tube. Again, add 250 μL of the elution buffer to the precipitated agarose beads, mix, and incubate for 15 min. Centrifuge at 1,000 × g-force at room temperature for 1 min, and transfer the supernatant to the same 1.5 mL microcentrifuge tube (total 500 μL of the eluate). 14. To reverse protein-DNA cross-links, add 20 μL of 5 M NaCl to the eluate and heat at 65 °C for 4 h. 15. Add 10 μL of 0.5 M EDTA, 20 μL of 1 M Tris-HCl (pH 6.5), and 2 μL of 10 mg/mL proteinase K to the eluate, and incubate at 45 °C for 1 h. 16. Extract DNA from the eluate, as well as input DNA solution (step 8), by phenol/chloroform extraction. Add 20 μg glycogen as a carrier, and recover DNA by ethanol precipitation. Wash the pellet with 70 % ethanol and air dry. 17. Resuspend the pellet in 30 μL of H2O (ChIP sample). 3.5

Quantitative PCR

1. Mix the ChIP sample, forward and reverse primers, and a Power SYBR Green PCR Master Mix (2×) as below. Primer sets for proximal and distal HSE as well as an intergenic region are shown in Table 1. ChIP sample

1 μL

Power SYBR Green PCR Master Mix (2×)

10 μL

Forward primer (10 pmol/μL)

0.4 μL

Reverse primer (10 pmol/uL)

0.4 μL

Distilled water

8.2 μL

Total 20 μL

2. Perform real-time PCR as described below. 95 °C

10 min

95 °C 15 s 60 °C

1 min

95 °C

15 s

40 cycles

60 °C 1 min 95 °C

15 sec

+3 °C/cycle, repeat until it reaches to 95 °C

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3. Percentage input is determined by comparing the cycle threshold value (CT value) of each sample with a standard curve, which is generated from a 5-point serial dilution of genomic input (see Notes 11).

4

Notes 1. ChIP assay showed that the DNA-binding activity of HSF1 in vivo in our immortalized MEF cells (see Notes 2) reaches to a peak at 30 min after heat shock at 42 °C. Profiles of HSF1 binding during heat shock differ even in MEF cells derived from mice with different genetic backgrounds. 2. Primary cultures of fibroblasts from wild-type (HSF1+/+) or HSF1-null (HSF1−/−) mouse embryos (ICR background) [40] were infected with retrovirus expressing SV40 large T antigen (loxP-HyTK-large T) [41] and were subcultured 20 times (Passage 20). Pools of wild-type cell culture (HSF1+/+; stock #10) and HSF1-null cell culture (HSF1−/−; stock #4) were stored in liquid nitrogen. 3. It is important to determine optimal titers for each viral expression vector. Similar amounts of ectopically expressed wild-type and mutated HSF1 as well as endogenous HSF1 should be detected by Western blotting (see Fig. 3c). Viral infection should not affect cell growth and morphology until 72 h. 4. To exclude the possibility that observed phenotypes could be due to effects of adenoviral infection or forced overexpression of some protein, an adenovirus expressing GFP (Ad-GFP) should be infected into cells as a control. 5. Construction of the adenovirus vector for shRNA is shown previously [42]. Knockdown efficiency should be determined by Western blotting using extracts of cells at 72 h after the infection with adenovirus expressing each shRNA. 6. We use adenovirus expressing a scrambled shRNA (Ad-shSCR) as a control. The nucleotide sequences are 5′-GAA TGT ACT GCG CGT GGA GAC-3′. 7. Add 270 μL of formaldehyde solution (~37 %) directly into 10 mL culture medium in a 10 cm culture dish. 8. It is necessary to determine an optimal condition for shearing genome DNA by sonication. We use the Sonifier 450 (Branson Ultrasonics Corporation, USA) and set output control 3 and duty cycle 30 %. The cells suspended in 200 μL of SDS lysis buffer (see step 3 in Subheading 3.4) were sonicated different times (20 s/each time and incubate on ice in the intervals), added with 8 μL of 5 M NaCl, and heated at 65 °C for 4 h to reverse protein-DNA cross-links (see Subheading 3.4, step 14).

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Fig. 6 Optimizing the conditions for shearing genome DNA by sonication. The cells suspended in 200 μL of SDS lysis buffer (see step 3 in Subheading 3.4) were sonicated, and sizes of DNA fragments were estimated by agarose gel electrophoresis and ethidium bromide staining. Numbers indicate sonication times. M, molecular weight marker (see Note 8)

The DNA was extracted by phenol/chloroform, collected by ethanol precipitation, and subjected to agarose gel electrophoresis (Fig. 6). Sonication conditions, which generated DNA fragments with average sizes of 100–300 base pairs, should be selected. We here sonicated genomic DNA 12 times. 9. This ChIP protocol, in which immunoprecipitated DNA fragments are contaminated with salmon sperm DNA, is not suitable for ChIP-seq analysis. 10. To immunoprecipitate specifically one of human and mouse HSF family members [11], we use a rabbit antiserum raised against the C-terminus, which consists of relatively unique sequences, of mouse HSF1 (α-mHSF1j) [36, 43], mouse HSF2 (α-mHSF2-4) [44], or mouse HSF4 (α-mHSF4t) [43, 45]. The antibody α-mHSF1j can be purchased from Merck Millipore (catalog number ABE1044). 11. This protocol can be applied to detect components of HSF1 transcription including histone-modifying enzymes and chromatin-remodeling complexes or active or inactive chromatin marks in the HSP70 promoter.

Acknowledgment This work was supported in part by MEXT/JSPS KAKENHI Grant Number 3307, 24390081, 25430090, 25440010, the Takeda Science Foundation Special Project Research, the Uehara Memorial Foundation, and the Yamaguchi University Research Project on STRESS.

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References 1. Lindquist S (1986) The heat-shock response. Annu Rev Biochem 55:1151–1191 2. Richter K, Haslbeck M, Buchner J (2010) The heat shock response: life on the verge of death. Mol Cell 40:253–266 3. Hayashida N, Fujimoto M, Tan K, Prakasam R, Shinkawa T, Li L, Ichikawa H, Takii R, Nakai A (2010) Heat shock factor 1 ameliorates proteotoxicity in cooperation with the transcription factor NFAT. EMBO J 29: 3459–3469 4. Morimoto RI (2008) Proteotoxic stress and inducible chaperone networks in neurodegenerative disease and aging. Genes Dev 22:1427–1438 5. Balch WE, Morimoto RI, Dillin A, Kelly JW (2008) Adapting proteostasis for disease intervention. Science 319:916–919 6. Wu C (1995) Heat shock transcription factors: structure and regulation. Annu Rev Cell Dev Biol 11:441–469 7. Fuda NJ, Ardehali MB, Lis JT (2009) Defining mechanisms that regulate RNA polymerase II transcription in vivo. Nature 461:186–192 8. Weake VM, Workman JL (2010) Inducible gene expression: diverse regulatory mechanisms. Nat Rev Genet 11:426–437 9. Morimoto RI (1998) Regulation of the heat shock transcriptional response: cross talk between a family of heat shock factors, molecular chaperones, and negative regulators. Genes Dev 12:3788–3796 10. Akerfelt M, Morimoto RI, Sistonen L (2010) Heat shock factors: integrators of cell stress, development and lifespan. Nat Rev Mol Cell Biol 11:545–555 11. Fujimoto M, Nakai A (2010) The heat shock factor family and adaptation to proteotoxic stress. FEBS J 277:4112–4125 12. Becker PB, Rabindran SK, Wu C (1991) Heat shock-regulated transcription in vitro from a reconstituted chromatin template. Proc Natl Acad Sci U S A 88:4109–4113 13. Taylor IC, Workman JL, Schuetz TJ, Kingston RE (1991) Facilitated binding of GAL4 and heat shock factor to nucleosomal templates: differential function of DNA-binding domains. Genes Dev 5:1285–1298 14. Petesch SJ, Lis JT (2008) Rapid, transcriptionindependent loss of nucleosomes over a large chromatin domain at Hsp70 loci. Cell 134:74–84 15. Smith ST, Petruk S, Sedkov Y, Cho E, Tillib S, Canaani E, Mazo A (2004) Modulation of

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

heat shock gene expression by the TAC1 chromatin-modifying complex. Nat Cell Biol 6:162–167 Zobeck KL, Buckley MS, Zipfel WR, Lis JT (2010) Recruitment timing and dynamics of transcription factors at the Hsp70 loci in living cells. Mol Cell 40:965–975 Petesch SJ, Lis JT (2012) Activator-induced spread of poly(ADP-ribose) polymerase promotes nucleosome loss at Hsp70. Mol Cell 45:64–74 Westwood JT, Clos J, Wu C (1991) Stressinduced oligomerization and chromosomal relocalization of heat-shock factor. Nature 353:822–827 Guertin MJ, Lis JT (2010) Chromatin landscape dictates HSF binding to target DNA elements. PLoS Genet 6:e1001114 Sullivan EK, Weirich CS, Guyon JR, Sif S, Kingston RE (2001) Transcriptional activation domains of human heat shock factor 1 recruit human SWI/SNF. Mol Cell Biol 21:5826–5837 Fan HY, He X, Kingston RE, Narlikar GJ (2003) Distinct strategies to make nucleosomal DNA accessible. Mol Cell 11:1311–1322 Mosser DD, Theodorakis NG, Morimoto RI (1998) Coordinate changes in heat shock element-binding activity and HSP70 gene transcription rates in human cells. Mol Cell Biol 8:4736–4744 Santos SD, Saraiva MJ (2004) Enlarged ventricles, astrogliosis and neurodegeneration in heat shock factor 1 null mouse brain. Neuroscience 126:657–663 Takaki E, Fujimoto M, Sugahara K, Nakahari T, Yonemura S, Tanaka Y, Hayashida N, Inouye S, Takemoto T, Yamashita H, Nakai A (2006) Maintenance of olfactory neurogenesis requires HSF1, a major heat shock transcription factor in mice. J Biol Chem 281: 4931–4937 Homma S, Jin X, Wang G, Tu N, Min J, Yanasak N, Mivechil NF (2007) Demyelination, astrogliosis, and accumulation of ubiquitinated proteins, hallmarks of CNS disease in hsf1deficient mice. J Neurosci 27:7974–7986 Uchida S, Hara K, Kobayashi A, Fujimoto M, Otsuki K, Yamagata H, Hobara T, Abe N, Higuchi F, Shibata T, Hasegawa S, Kida S, Nakai A, Watanabe Y (2011) Impaired hippocampal spinogenesis and neurogenesis and altered affective behavior in mice lacking heat shock factor 1. Proc Natl Acad Sci U S A 108:1681–1686

HSF1 Complex in the HSP70 Promoter 27. Takaki E, Fujimoto M, Nakahari T, Yonemura S, Miyata Y, Hayashida N, Yamamoto K, Vallee RB, Mikuriya T, Sugahara K, Yamashita H, Inouye S, Nakai A (2007) Heat shock transcription factor 1 is required for maintenance of ciliary beating in mice. J Biol Chem 282:37285–37292 28. Inouye S, Izu H, Takaki E, Suzuki H, Shirai M, Yokota Y, Ichikawa H, Fujimoto M, Nakai A (2004) Impaired IgG production in mice deficient for heat shock transcription factor 1. J Biol Chem 279:38701–38709 29. Zheng H, Li Z (2004) Cutting edge: crosspresentation of cell-associated antigens to MHC class I molecule is regulated by a major transcription factor for heat shock proteins. J Immunol 173:5929–5933 30. Trinklein ND, Murray JI, Hartman SJ, Botstein D, Myers RM (2004) The role of heat shock transcription factor 1 in the genome-wide regulation of the mammalian heat shock response. Mol Biol Cell 15:1254–1261 31. Santagata S, Mendillo ML, Tang YC, Subramanian A, Perley CC, Roche SP, Wong B, Narayan R, Kwon H, Koeva M, Amon A, Golub TR, Porco JA Jr, Whitesell L, Lindquist S (2013) Tight coordination of protein translation and HSF1 activation supports the anabolic malignant state. Science 341:1238303 32. Vihervaara A, Sergelius C, Vasara J, Blom MA, Elsing AN, Roos-Mattjus P, Sistonen L (2013) Transcriptional response to stress in the dynamic chromatin environment of cycling and mitotic cells. Proc Natl Acad Sci U S A 110:E3388–E3397 33. Inouye S, Fujimoto M, Nakamura T, Takaki E, Hayashida N, Hai T, Nakai A (2007) Heat shock transcription factor 1 opens chromatin structure of interleukin-6 promoter to facilitate binding of an activator or a repressor. J Biol Chem 282:33210–33217 34. Takii R, Inouye S, Fujimoto M, Nakamura T, Shinkawa T, Prakasam R, Tan K, Hayashida N, Ichikawa H, Hai T, Nakai A (2010) Heat shock transcription factor 1 inhibits expression of IL-6 through activating transcription factor 3. J Immunol 184:1041–1048 35. Hayashida N, Fujimoto M, Nakai A (2011) Transcription factor cooperativity with heat shock factor 1. Transcription 2:91–94 36. Fujimoto M, Takaki E, Takii R, Tan K, Prakasam R, Hayashida N, Iemura S, Natsume

37.

38.

39.

40.

41.

42.

43.

44.

45.

65

T, Nakai A (2012) RPA assists HSF1 access to nucleosomal DNA by recruiting histone chaperone FACT. Mol Cell 48:182–194 Wold MS (1997) Replication protein A: a heterotrimeric, single-stranded DNA-binding protein required for eukaryotic DNA metabolism. Annu Rev Biochem 66:61–92 Zaret KS, Carroll JS (2011) Pioneer transcription factors: establishing competence for gene expression. Genes Dev 25:2227–2241 Magnani L, Eeckhoute J, Lupien M (2011) Pioneer factors: directing transcriptional regulators within the chromatin environment. Trends Genet 27:465–474 Inouye S, Katsuki K, Izu H, Fujimoto M, Sugahara K, Yamada S, Shinkai Y, Oka Y, Katoh Y, Nakai A (2003) Activation of heat shock genes is not necessary for protection by heat shock transcription factor 1 against cell death due to a single exposure to high temperatures. Mol Cell Biol 23:5882–5895 Li LP, Schlag PM, Blankenstein T (1997) Transient expression of SV 40 large T antigen by Cre/LoxP-mediated site-specific deletion in primary human tumor cells. Hum Gene Ther 8:1695–1700 Fujimoto M, Hayashida N, Katoh T, Oshima K, Shinkawa T, Prakasam R, Tan K, Inouye S, Takii R, Nakai A (2010) A novel mouse HSF3 has the potential to activate non-classical heat shock genes during heat shock. Mol Biol Cell 21:106–116 Fujimoto M, Oshima I, Shinkawa T, Wang B, Inouye S, Hayashida N, Takii R, Nakai A (2008) Analysis of HSF4 binding regions reveals its necessity for gene regulation during development and heat shock response in mouse lenses. J Biol Chem 283:29961–29970 Shinkawa T, Tan K, Fujimoto M, Hayashida N, Yamamoto K, Takaki E, Takii R, Prakasam R, Inouye S, Mezger V, Nakai A (2011) Heat shock factor 2 is required for maintaining proteostasis against febrile range thermal stress and polyglutamine aggregation. Mol Biol Cell 22:3571–3583 Tanabe M, Sasai N, Nagata K, Liu X-D, Liu P-CC, Thiele DJ, Nakai A (1999) The mammalian HSF4 gene generates both an activator and a repressor of heat shock genes by alternative splicing. J Biol Chem 274: 27845–27856

Chapter 5 Immunofluorescence-Based Methods to Monitor DNA End Resection Bipasha Mukherjee, Nozomi Tomimatsu, and Sandeep Burma Abstract Double-strand breaks (DSBs) are the most deleterious among all types of DNA damage that can occur in the cell. These breaks arise from both endogenous (e.g., DNA replication stress) and exogenous insults (e.g., ionizing radiation). DSBs are principally repaired by one of two major pathways: nonhomologous end joining (NHEJ) or homologous recombination (HR). NHEJ is an error-prone process that can occur in all phases of the cell cycle, while HR is limited to the S and G2 phases of the cell cycle when a sister chromatid is available as a template for error-free repair. The first step in HR is “DNA end resection,” a process during which the broken DNA end is converted into a long stretch of 3′-ended single-stranded DNA (ssDNA). In recent years, DNA end resection has been identified as a pivotal step that controls “repair pathway choice,” i.e., the appropriate choice between NHEJ and HR for DSB repair. Therefore, methods to quantitatively or semiquantitatively assess DNA end resection have gained importance in laboratories working on DNA repair. In this chapter, we describe two simple immunofluorescence-based techniques to monitor DNA end resection in mammalian cells. The first technique involves immuno-detection of replication protein A (RPA), an ssDNA-binding protein that binds to resected DNA. The second technique involves labeling of genomic DNA with 5-bromo-2′-deoxyuridine (BrdU) that can be detected by anti-BrdU antibody only after the DNA becomes single stranded due to resection. These methods are not complicated, do not involve sophisticated instrumentation or reporter constructs, and can be applied to most mammalian cell lines and, therefore, should be of broad utility as simple ways of monitoring DNA end resection in vivo. Key words DNA damage, DNA double-strand break (DSB), DNA repair, Homologous recombination, DNA end resection, Single-stranded DNA (ssDNA), RPA, BrdU

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Introduction Genomic insults like ionizing radiation (IR) or chemotherapeutic drugs cause double-strand breaks (DSBs) in our DNA. DSBs also arise from DNA replication stress due to the stalling and collapse of replication forks. Such breaks can trigger genomic instability and cause cell death or cancer if they are not repaired promptly and correctly. Two major pathways have evolved to deal with these breaks in mammalian cells—nonhomologous end joining (NHEJ)

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and homologous recombination (HR) [1]. NHEJ can occur throughout the cell cycle and rapidly rejoins the broken DNA ends following limited end processing and can thus be error-prone [2]. HR is restricted to post-replicative phases of the cell cycle and typically uses an undamaged sister chromatid as a template to restore genomic integrity and is thus potentially error-free [3]. A fine balance between the usage of NHEJ and HR is necessary for optimally maintaining genomic integrity. It would be important to minimize HR usage in G1 as recombination in the absence of a sister chromatid could lead to loss of heterozygosity (LOH) or chromosomal rearrangements due to recombination with the homologous chromosome or with homologous sequences elsewhere in the genome. However, use of HR in S and G2 phases would promote error-free repair, and, indeed, HR would be the only means to repair one-ended replication fork-associated breaks. Hence, mechanisms of “repair pathway choice” or the appropriate choice between NHEJ and HR are important for cell survival upon DNA damage, and these mechanisms control a critical step in HR termed “DNA end resection” [4–7]. DNA end resection is an early step in HR during which the broken DNA end is converted into a long stretch of 3′-ended single-stranded DNA (ssDNA). The ssDNA tail that is generated is rapidly coated by RPA (replication protein A), a heterotrimeric protein which prevents the formation of secondary structures and protects against degradation of the ssDNA [8]. Next, RPA is replaced with Rad51 to generate a recombinogenic nucleoprotein filament that searches for homologous sequences in the sister chromatid or elsewhere in the genome. As the generation of ssDNA promotes HR and thwarts NHEJ (by preventing the binding of NHEJ proteins), it is easy to understand why DNA end resection is a critical step at which repair pathway choice is exercised. DNA end resection occurs in a “two-step” manner [6, 7]. The first step, “initiation of resection,” involves the removal of ~50–100 bases of DNA from the 5′ end by the MRX/MRN complex (Mre11Rad50-Xrs2 in yeast and Mre11-Rad50-Nbs1 in mammals) in conjunction with Sae2/CtIP [9–13]. The second step, “long-range resection,” is carried out by two alternate pathways involving either the 5′ to 3′ exonuclease Exo1 alone or the helicase Sgs1/Blm in concert with Exo1 or the nuclease Dna2 [14–16]. Long-range resection proceeds at the rate of 4 kb per hour in yeast, and the ssDNA tails generated can be several kilobases in length [6]. DNA end resection is regulated, at one level, by the mutually antagonistic relationship between Rif1-53BP1-PTIP and Brca1-CtIP wherein resection is blocked in G1 by 53BP1 which block is lifted by the action of Brca1 in S and G2 [17]. At another level, DNA end resection is regulated by CDKs that drive cells through S and G2 phases such that phosphorylation of resection nucleases CtIP, Exo1, and Dna2 by these CDKs promotes resection and restricts it

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Fig. 1 Representative images of mock-irradiated or gamma-irradiated U2OS cells immunostained with antiRPA antibody (red ) or with anti-BrdU antibody (red ). Nuclei are stained with DAPI (blue )

to the post-replicative phases of the cell cycle [18–21]. DNA end resection also inactivates ATM kinase while activating ATR kinase at the same time, thereby actuating a transition in the mode of cell cycle checkpoint signaling [22, 16]. Given its pivotal role in repair pathway choice and cell cycle checkpoint signaling mechanisms, DNA end resection is currently an area of avid interest among researchers in the field of DNA repair, and several assays are in use to quantitatively or semiquantitatively monitor DNA end resection. Here, we describe two simple immunofluorescence-based techniques to monitor DNA end resection in mammalian cells. One technique is indirect and visualizes the binding of RPA to resected DNA in the nucleus by immunofluorescence staining with anti-RPA antibody. The second method is more direct and involves labeling of genomic DNA with 5-bromo-2′-deoxyuridine (BrdU) that can be detected by antiBrdU antibody only after the DNA becomes single stranded due to resection. The resected DNA can be visualized by fluorescence microscopy as punctate RPA or BrdU/ssDNA “foci” (Fig. 1) whose numbers can serve as a metric to quantify resection in cells responding to DNA damage or replication stress. These two protocols are a synthesis of methods published by other groups [23–27] that were further modified by us and described in previous publications from our group [28, 16, 29, 21].

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Materials

2.1 Tissue Culture Slides

1. Falcon™ Culture Slides (4 chambers) (Fisher Scientific, Catalog no: 08-774-209). 2. Fisherfinest™ Premium Cover Glasses (50 × 20 mm) (Fisher Scientific, Catalog no: 12-548-5E).

2.2 Buffers and Solutions

1. Phosphate buffered saline (PBS), pH 7.4. 2. Extraction buffer 1: 10 mM PIPES, pH 7.0; 100 mM NaCl; 300 mM Sucrose; 3 mM MgCl2; 1 mM EGTA; 0.5 % Triton X-100. Store at 4 °C and use within 2–3 weeks. 3. Extraction buffer 2: 10 mM Tris–HCl, pH 7.5; 10 mM NaCl; 3 mM MgCl2, 1 % Tween 40, 0.5 % sodium deoxycholate. Store at 4 °C and use within 2–3 weeks. 4. 4 % paraformaldehyde solution (PFA): Dissolve 4 g of paraformaldehyde in 50 mL of water and 1 mL of 1 M NaOH (heat at 65 °C in a water bath until powder is completely dissolved). Cool to room temperature. Add 10 mL of 10× PBS. Adjust the pH to 7.4 using HCl. Make up the volume to 100 mL with water. Filter through 0.2 μm filter. Store at −20 °C in aliquots covered in aluminum foil and use within a month. 5. 0.5 % Triton X-100 in PBS, store at 4 °C and use within 2–3 weeks. 6. 5 % BSA (fraction V) in PBS, store at 4 °C and use within 2–3 weeks. 7. 1 % BSA (fraction V) in PBS, store at 4 °C and use within 2–3 weeks. 8. 10 mg/mL BrdU in distilled water. Aliquot and store at −80 °C and use within a year (Sigma, Catalog no: B5002). 9. Vectashield with DAPI (Vector Labs, Catalog no: H-1200).

2.3

Antibodies

1. Anti-RPA (Ab-3) mouse mAb (Calbiochem, Catalog no: NA19l). 2. Anti-BrdU mouse mAb (BD Biosciences, Catalog no: 347580). 3. Alexa Fluor® 568 donkey anti-mouse IgG (Life Technologies, Catalog no: A10037).

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Methods

3.1 Cell Culture and Treatments

Both immunofluorescence protocols were standardized for U2OS cells and may need to be modified for other cell lines (see Note 1). DSBs can be induced by irradiating cells using a gamma- or x-ray irradiator. We use a Shepherd Mark 1–68 Cesium-137 irradiator.

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Alternatively, radiomimetic drugs (such as bleomycin or neocarzinostatin) or topoisomerase inhibitors (such as camptothecin or etoposide) may be added to the culture medium. Radiation doses or drug concentrations would have to be individually standardized depending upon the experiment and the level of background DNA damage in the cell line being used. 3.2 RPA Immunostaining Protocol

1. Seed cells in a tissue culture-treated 4-chamber slide (60,000 cells in 500 μL of cell culture medium per chamber) and allow them to attach and grow for about 16 h (see Note 2). 2. Irradiate cells with a total dose of 6 Gy and incubate cells at 37 °C in a CO2 incubator for 3 h (see Note 3). 3. Wash cells with PBS. Aspirate off cell culture medium using low suction pressure, gently add 500 μL of PBS down the walls of the chamber, rock slide gently a couple of times, and aspirate off PBS. Take care to not let slide dry between steps and minimize time between steps. Keep slide on ice as much as possible and all solutions cold (until step 11). 4. Incubate cells in 500 μL of extraction buffer 1 for 10 min on ice (see Notes 4 and 5). 5. Wash cells with PBS. 6. Incubate cells in 500 μL of extraction buffer 2 for 10 min on ice. 7. Wash cells with PBS. 8. Fix cells in 500 μL of 4 % PFA for 20 min on ice (see Note 6). 9. Wash cells with PBS. 10. Permeabilize cells by incubating in 500 μL of 0.5 % Triton X-100 for 10 min on ice. 11. Wash cells with PBS. 12. Block slide by incubating in 500 μL of 5 % BSA in PBS on ice for 20 min. 13. Incubate with primary antibody (anti-RPA at 1:500 dilution in 1 % BSA) for 16 h at 4 °C in a humid chamber (a small plastic box with a tight lid and wet Kimwipes at the bottom works fine). At least 200 μL of antibody solution should be used to prevent chamber from drying out. 14. Wash cells in PBS three times at room temperature; each time leave the PBS on for at least 10 min (see Note 7). 15. Incubate with secondary antibody (Alexa Fluor® 568 antimouse at 1:1,000 dilution in 1 % BSA) in a dark box for 1 h at room temperature. 16. Wash cells in PBS three times at room temperature; each time leave the PBS on for at least 10 min keeping cells in a dark box.

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17. Remove chambers and gently aspirate off excess PBS taking care to not scratch the cells. Air-dry the slide for a couple of minutes in a dark box (do not overdry). Add a small drop of Vectashield containing DAPI to each chamber, cover with glass coverslip, tap gently to remove bubbles, and seal the coverslip with quick drying transparent nail polish. Store slides at −20 °C in a dark box. 3.3 BrdU Immunostaining Protocol

1. Seed cells in a tissue culture-treated 4-chamber slide such that they will be about 50–60 % confluent the next day (typically 40,000 cells in 500 μL of cell culture medium per chamber) and allow them to attach and grow for about 24 h (see Note 2). 2. Add BrdU to cells at a final concentration of 10 μg/mL and incubate for 16 h (approximately one cell cycle). 3. Irradiate cells with a total dose of 10 Gy and incubate cells at 37 °C in a CO2 incubator for 1 h (see Note 3). 4. Wash cells with PBS: Aspirate off cell culture medium using low suction pressure, gently add 500 μL of PBS down the walls of the chamber, rock slide gently a couple of times, and aspirate off PBS. Take care to not let slide dry between steps and minimize time between steps. Keep slide on ice as much as possible and all solutions cold (until step 12). 5. Incubate cells in 500 μL of extraction buffer 1 for 10 min on ice (see Notes 4 and 5). 6. Wash cells with PBS. 7. Incubate cells in 500 μL of extraction buffer 2 for 10 min on ice. 8. Wash cells with PBS. 9. Fix cells in 500 μL of 4 % PFA for 20 min on ice (see Note 6). 10. Wash cells with PBS. 11. Permeabilize cells by incubating in 500 μL of 0.5 % Triton X-100 for 10 min on ice. 12. Wash cells with PBS. 13. Block slide by incubating in 500 μL of 5 % BSA in PBS on ice for 20 min. 14. Incubate with primary antibody (anti-BrdU at 1:100 dilution in 1 % BSA) for 16 h at 4 °C in a humid chamber (a small plastic box with a tight lid and wet Kimwipes at the bottom works fine). At least 200 μL of antibody solution should be used to prevent chamber from drying out. 15. Wash cells in PBS three times at room temperature; each time leave the PBS on for at least 10 min (see Note 7). 16. Incubate with secondary antibody (Alexa Fluor® 568 antimouse at 1:1,000 dilution in 1 % BSA) in a dark box for 1 h at room temperature.

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17. Wash cells in PBS three times at room temperature; each time leave the PBS on for at least 10 min keeping cells in a dark box. 18. Remove chambers and gently aspirate off excess PBS without touching areas with cells. Air-dry the slide for a couple of minutes in a dark box (do not overdry). Add a small drop of Vectashield containing DAPI to each chamber, cover with glass coverslip, tap gently to remove bubbles, and seal the coverslip with quick drying transparent nail polish. Store slides at −20 °C in a dark box. 3.4 Quantification of Foci

4

Images of nuclei can be obtained using a fluorescence microscope at magnifications ranging from 40× to 100×. If a confocal microscope is used to capture z-sections, the sections should be merged so that all foci are visible on a single plane. The average numbers of foci per nucleus are determined after manually counting 50–100 nuclei using the ImageJ Cell Counter software (see Notes 8 and 9).

Notes 1. The protocol can be used for most human and murine cell lines. However, “flatter” cells (e.g., U2OS) provide better images. 2. As a less expensive alternative to chamber slides, cells can be grown on coverslips in a 12-well plate and processed in the well. 3. The incubation time after DNA damage induction may have to be varied depending upon the experiment and the cell line being used to obtain maximum number of foci. We recommend using a range of doses of the DNA damaging agent and varying incubation times while standardizing the protocol. 4. The extraction steps with buffers 1 and 2 are important for obtaining clear RPA or BrdU foci. The extraction time in each of the buffers is critical and may have to be standardized for other cell lines. We recommend doing a pilot experiment with different incubation times in the extraction buffers if using a cell line other than U2OS. 5. Some cell lines may become more prone to detachment after the extraction steps. Handle slides carefully after extraction and check under microscope between steps to ensure that cells are not detaching. 6. In our experience, PFA quality appears to be the most important factor affecting overall image quality. PFA should be made carefully and the pH balanced accurately. We prefer to not use PFA that is more than a month old. Freshly made PFA works best in our hands. 7. Longer washes after incubation with primary or secondary antibodies may help reduce nonspecific signals.

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8. Since extensive resection occurs only in cells in S and G2 phases of the cell cycle, all cells will not show the presence of RPA or BrdU/ssDNA foci. 9. While both methods allow quantification of the number of breaks undergoing extensive resection at any given time, these methods do not allow us to measure the extent of resection at a given break. A different protocol can be used to directly assess the length of resection at a restriction enzyme-generated DSB at a sequence-specific site [30]. In addition, one can indirectly measure the extent of resection at micro-laser-induced DSBs in living cells in real time by quantifying the accumulation of GFP-tagged RPA [16].

Acknowledgments SB is supported by grants from the National Institutes of Health (RO1 CA149461) and the National Aeronautics and Space Administration (NNX13AI13G). References 1. Wyman C, Kanaar R (2006) DNA doublestrand break repair: all’s well that ends well. Annu Rev Genet 40:363–383 2. Lieber MR (2010) The mechanism of doublestrand DNA break repair by the nonhomologous DNA end-joining pathway. Annu Rev Biochem 79:181–211 3. Heyer WD, Ehmsen KT, Liu J (2010) Regulation of homologous recombination in eukaryotes. Annu Rev Genet 44:113–139 4. Chapman JR, Taylor MR, Boulton SJ (2012) Playing the end game: DNA double-strand break repair pathway choice. Mol Cell 47: 497–510 5. Shrivastav M, De Haro LP, Nickoloff JA (2008) Regulation of DNA double-strand break repair pathway choice. Cell Res 18: 134–147 6. Symington LS, Gautier J (2011) Doublestrand break end resection and repair pathway choice. Annu Rev Genet 45:247–271 7. Huertas P (2010) DNA resection in eukaryotes: deciding how to fix the break. Nat Struct Mol Biol 17:11–16 8. Fanning E, Klimovich V, Nager AR (2006) A dynamic model for replication protein A (RPA) function in DNA processing pathways. Nucleic Acids Res 34:4126–4137 9. Gravel S, Chapman JR, Magill C et al (2008) DNA helicases Sgs1 and BLM promote DNA

10.

11.

12.

13.

14.

15.

16.

double-strand break resection. Genes Dev 22:2767–2772 Mimitou EP, Symington LS (2008) Sae2, Exo1 and Sgs1 collaborate in DNA doublestrand break processing. Nature 455:770–774 Zhu Z, Chung WH, Shim EY et al (2008) Sgs1 helicase and two nucleases Dna2 and Exo1 resect DNA double-strand break ends. Cell 134:981–994 Makharashvili N, Tubbs AT, Yang SH et al (2014) Catalytic and noncatalytic roles of the CtIP endonuclease in double-strand break end resection. Mol Cell 54:1022–1033 Nicolette ML, Lee K, Guo Z et al (2010) Mre11-Rad50-Xrs2 and Sae2 promote 5′ strand resection of DNA double-strand breaks. Nat Struct Mol Biol 17:1478–1485 Nimonkar AV, Genschel J, Kinoshita E et al (2011) BLM-DNA2-RPA-MRN and EXO1BLM-RPA-MRN constitute two DNA end resection machineries for human DNA break repair. Genes Dev 25:350–362 Bolderson E, Tomimatsu N, Richard DJ et al (2010) Phosphorylation of Exo1 modulates homologous recombination repair of DNA double-strand breaks. Nucleic Acids Res 38:1821–1831 Tomimatsu N, Mukherjee B, Deland K et al (2012) Exo1 plays a major role in DNA end resection in humans and influences double-

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17.

18.

19.

20.

21.

22.

23.

strand break repair and damage signaling decisions. DNA Repair (Amst) 11:441–448 Daley JM, Sung P (2014) 53BP1, BRCA1, and the choice between recombination and end joining at DNA double-strand breaks. Mol Cell Biol 34:1380–1388 Chen X, Niu H, Chung WH et al (2011) Cell cycle regulation of DNA double-strand break end resection by Cdk1-dependent Dna2 phosphorylation. Nat Struct Mol Biol 18:1015–1019 Ferretti LP, Lafranchi L, Sartori AA (2013) Controlling DNA-end resection: a new task for CDKs. Front Genet 4:99 Huertas P, Cortes-Ledesma F, Sartori AA et al (2008) CDK targets Sae2 to control DNA-end resection and homologous recombination. Nature 455:689–692 Tomimatsu N, Mukherjee B, Catherine HM et al (2014) Phosphorylation of EXO1 by CDKs 1 and 2 regulates DNA end resection and repair pathway choice. Nat Commun 5:3561 Shiotani B, Zou L (2009) Single-stranded DNA orchestrates an ATM-to-ATR switch at DNA breaks. Mol Cell 33:547–558 Mirzoeva OK, Petrini JH (2001) DNA damage-dependent nuclear dynamics of the Mre11 complex. Mol Cell Biol 21:281–288

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24. Kaidi A, Weinert BT, Choudhary C et al (2010) Human SIRT6 promotes DNA end resection through CtIP deacetylation. Science 329:1348–1353 25. Hu Y, Scully R, Sobhian B et al (2011) RAP80directed tuning of BRCA1 homologous recombination function at ionizing radiationinduced nuclear foci. Genes Dev 25:685–700 26. Cuadrado M, Martinez-Pastor B, Murga M et al (2006) ATM regulates ATR chromatin loading in response to DNA double-strand breaks. J Exp Med 203:297–303 27. Raderschall E, Golub EI, Haaf T (1999) Nuclear foci of mammalian recombination proteins are located at single-stranded DNA regions formed after DNA damage. Proc Natl Acad Sci U S A 96:1921–1926 28. Tomimatsu N, Mukherjee B, Burma S (2009) Distinct roles of ATR and DNA-PKcs in triggering DNA damage responses in ATMdeficient cells. EMBO Rep 10:629–635 29. Costelloe T, Louge R, Tomimatsu N et al (2012) The yeast Fun30 and human SMARCAD1 chromatin remodellers promote DNA end resection. Nature 489:581–584 30. Zhou Y, Caron P, Legube G et al (2014) Quantitation of DNA double-strand break resection intermediates in human cells. Nucleic Acids Res 42:e19

Chapter 6 Visualizing the Spatiotemporal Dynamics of DNA Damage in Budding Yeast Chihiro Horigome, Vincent Dion, Andrew Seeber, Lutz R. Gehlen, and Susan M. Gasser Abstract Fluorescence microscopy has enabled the analysis of both the spatial distribution of DNA damage and its dynamics during the DNA damage response (DDR). Three microscopic techniques can be used to study the spatiotemporal dynamics of DNA damage. In the first part we describe how we determine the position of DNA double-strand breaks (DSBs) relative to the nuclear envelope. The second part describes how to quantify the co-localization of DNA DSBs with nuclear pore clusters, or other nuclear subcompartments. The final protocols describe methods for the quantification of locus mobility over time. Key words DNA damage, Double-strand breaks, Chromatin mobility, Nuclear pore clustering, Mean-square displacement analysis, Fluorescence microscopy

1

Introduction

1.1 Determining the Subnuclear Localization of DNA Double-strand Breaks

In budding yeast, DNA double-strand breaks (DSBs) that lack a functional donor for repair by homologous recombination (HR) shift at least transiently to the nuclear periphery, where they appear to bind either the Nup84 nuclear pore subcomplex or an essential inner nuclear membrane SUN-domain protein, Mps3 [1–4]. Recent work confirms that these are functionally non-equivalent sites and that the requirements for the relocation of DSBs to Mps3 are distinct from the requirements for relocation to nuclear pores [5]. To determine the relative position of the damaged chromatin locus to the nuclear envelope in spherical nuclei, a quantitative subnuclear positioning assay, called the zoning assay, can be applied [6] (Fig. 1a, b). This protocol was developed originally for determining where a yeast chromatin locus tends to localize in a yeast nucleus. It takes advantage of arrays of lacO or tetO sequences that bind LacI or TetR proteins fused to a fluorescent protein [7, 8]. The fluorescent signal is therefore concentrated into a single spot

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Fig. 1 Determining the position of a DNA double-strand break relative to the nuclear periphery or to a nuclear pore cluster (a) Shown is the lacO tagged MAT locus on Chr III in a strain bearing deleted homologous donor loci (hmlΔ/hmrΔ). The lacO array allows visualization by GFP-LacI. Pores are visualized by GFP-Nup49 or CFPNup49. The strain must also express a galactose-inducible endonuclease HO, which cleaves at MAT only. (b) Locus position is scored relative to the nuclear diameter in its plane of focus. Distance over diameter ratios are binned into three equal zones, with zone 1 being the outermost and zone 3 being the innermost zone.

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that corresponds to the specific locus at which the bacterial operator sites are integrated. The same method can be used to localize Rad52-tagged DNA repair foci in the yeast nucleus [9, 10]. Required conditions include the marking of the nuclear periphery with a fluorescent protein (for example RFP- or CFP-Nup49) and a spherical nuclear shape. In this protocol, we focus on determining the subnuclear position of a DNA DSB produced by a galactose-induced endonuclease [11]. This method serves as well for assays aimed at determining whether a targeted protein has the ability to shift a chromatin locus towards or away from the nuclear periphery (see Note 1). All of the described Excel sheets and macros are available upon request (see Note 2). 1.2 Co-localization of DNA DSBs with the Nuclear Pore Cluster

Persistent DNA DSBs are recruited to the nuclear periphery in budding yeast. Both the Nup84 pore subcomplex and Mps3, an inner nuclear membrane SUN-domain protein, have been implicated in DSB binding. Mps3 and nuclear pores distribute independently around the nuclear rim in vegetatively growing cells [12] and define distinct survival pathways [5]. The two sites at the nuclear envelope can be distinguished by nuclear pore- and Mps3chromatin immunoprecipitation (ChIP) assays. However, results from ChIP assays should be confirmed with an assay that does not depend on crosslinking, given that formaldehyde crosslinking efficiency varies significantly from protein to protein. A complementary means to score for DSB co-localization with nuclear pore complexes is based on the high-resolution spinning disk confocal microscopy of a GFP-LacI-tagged DSB and CFP-tagged nuclear pores in a genetic background that leads to pore clustering (Fig. 1c). In a nup133ΔN (deletion of aa 44–236 in the endogenous NUP133 gene) background, pores form a large, single cluster at the nuclear periphery. If they are fluorescently tagged, this allows accurate scoring of co-localization with DSBs [13]. The deletion of aa 44–236 in the Nup133 N terminus does not affect macromolecular import or export, and does not confer sensitivity to DNA damaging agents, unlike complete deletion of NUP133 or genes encoding other Nup84 subcomplex components [13, 14].

Fig. 1 (continued) Shown are images of equatorial confocal planes through nuclei which express CFP-Nup49. (c) Scoring of MAT co-localization with the Nup49-CFP pore cluster in nup133ΔN after cut induction. We score three degrees of co-localization of the tagged-chromatin locus with the pore cluster, as indicated. (d) Co-localization of MAT locus and CFP-Nup49 pore cluster signal in wild-type and hoΔ cells (both in a nup133ΔN background). Pink and red shaded regions = touching, partial overlap or complete overlap as described in c. A background of co-localization (grey dotted line) was determined from the strain lacking the gene for the HO endonuclease (hoΔ). The figures are reproduced with authors’ permission from ref. [5]

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We score three degrees of co-localization with the pore cluster (Fig. 1c, d): fully overlapping (if the vast majority of the DSB signal coincides with pore fluorescence), partially overlapping (when a minority of the DSB coincides with the pore) and juxtaposition (or “touching” such that DSB is contiguous with the pore signal). All three degrees of co-localization are consistent with molecular interaction of the break with the pore cluster, given the relative signal sizes of the lacO array and the cluster was pore, and the length of the pore associated inner-basket of protein fibrils [15]. The background or stochastic value for co-localization of a randomly distributed chromatin locus and a pore cluster was analytically calculated to be around 9 % [15], but was empirically determined as 20 % [15, 5]. Particularly for galactose-induced DSBs, the measured background is significantly higher than the computed likelihood of a lacO focus coinciding with the pore cluster, based on the relative sizes of these foci and the size of a haploid yeast nucleus. The cause of this variation is unclear, but can be influenced by the absence of glucose in the growth media. Thus, we recommend determining the co-localization of a given locus with the pore cluster in the absence of a DSB, and using this as the background above which co-localization can be considered biologically relevant. 1.3 Quantification of Locus Mobility Under Conditions of DNA Damage

Interphase chromatin is highly active. A constant battery of DNAbased processes, including chromatin remodelling, leads to changes in nucleosome composition and spacing, which changes the subnuclear position of loci as well. Indeed, chromatin is physically dynamic [16, 17] and its movement is constrained by both the confines of the nuclear envelope and by the properties of the chromatin fiber [18]. This protocol describes how to track a fluorescent spot in live yeast cells and quantify its mobility. It can be done with any fluorescent protein that forms a discernible fluorescent focus. We have used this method extensively for tracking lacO/LacI, tetO/TetR, and foci formed by a wide variety of repair proteins tagged with a fluorescent protein [1, 10, 16, 17, 19–24] (Fig. 2a). In our analysis the center of the nucleus is used as the point of reference for the calculation of the mobility. This allows us to subtract movement that arises from translational movement of the nucleus or the cell or which arises from the mechanics of the imaging apparatus. To achieve this it is ideal to have the nuclear periphery marked with a fluorescent protein, for example GFP-Nup49, although in some cases it may be possible to use the background fluorescence provided by a diffuse signal of the tagged protein to calculate the nuclear center. Other laboratories have calculated the relative distance between two identical spots (loci on homologous chromosomes in a diploid cell), after which they divide the Mean Square Displacement (MSD) by 2 to calculate the movement of the single locus [25, 26]. Both approaches are mathematically valid, yet analyzing the mobility of a single locus in haploid cells allows one to exploit the genetics of yeast most effectively (Fig. 2b, c).

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Fig. 2 Mean square displacement (MSD) analysis. (a) A time-lapse tracking of a single tagged chromosomal locus is shown in color, with the trajectory spanning 7.5 min based on image stacks taken at 1.5 s intervals in a living yeast cell. The frames have been aligned to the nuclear center. The nuclear volume is in green. A similar trajectory is projected after alignment onto a 2D plane (right panel) and accurate x, y coordinates for positions at 1.5 s intervals are determined (green dots and tracks). The actual movement is likely to be much more fine-grained (grey track). The red and blue dotted lines represent different time intervals. (b) Based on the 2D projection data, the mean square displacement graph is generated. The formulae shown are generic, and one uses d=2 for projected data, and d=3 for non-projected data in 3 dimensions of data. MSD analysis is a standard physical analysis of random motion. (c) Shown are actual MSD curves from a lacO-LacI tagged locus on Chr VI from cells in G1 phase (pink) or in S phase (blue). The graphs show the mean and standard variation from the MSD analysis of 26 movies in G1 phase and 14 movies in S phase, each containing 300 stacks of images taken at 1.5 s intervals. The radius of constraint and nuclear volume (%) within which the locus moves decreases in S-phase cells. A previous study shows similar data in which it is shown that the reduced mobility in S phase is lost if cohesin is released by cleavage [10]. See refs. [10, 17, 20] for details of the analyses

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Here we describe the procedure of image acquisition of a moving particle and the processing of the resulting data. The protocol includes the use of the ImageJ plug-in SpotTracker [27] followed by a custom-made Excel macro that we have designed to be versatile and extendable (see Note 2). It provides an easy way of generating MSD plots, which plot the average square distance that a spot moves against increasing time intervals. From these plots one can derive diffusion coefficients and radii of constraint (Rc) (Fig. 2b). From a parallel analysis of the trajectories one determines the number of large steps (empirically defined as >0.5 μm within 10.5 s or 7 frames at 1.5 s intervals). For a detailed discussion of these movement parameters and their limitations, see refs. [6, 17, 18]. This method can also be used to track a DNA repair protein focus such as that formed by Rad52-YFP.

2

Materials

2.1 Determining the Subnuclear Localization of DNA DSBs 2.1.1 Strains

2.1.2 Media

A yeast strain bearing an array of lacO or tetO sites next to an HO endonuclease consensus [28, 29] or a I-SceI [30, 31] cleavage site is needed. The strain(s) must co-express LacI or TetR tagged with a fluorescent protein, at low levels from an integrated, constitutively active promoter. The strain should ideally also contain a fluorescent protein fusion that marks the nuclear periphery (e.g., GFP-Nup49 or CFP-Nup49) (Fig. 1a, b). The endonuclease needs to be tightly repressed when it is not induced, and be rapidly expressed on the correct media [11]. The optimal number of lacO or tetO sites ranges determining the subnuclear localization of DNA damage from 50 to 250. 1. YPAD plate: Bacto peptone (2 %, w/v), yeast extract (1 %, w/v), glucose (2 %, w/v), adenine (0.0025 %, w/v) and agarose (2 %, w/v). 2. SCLGg medium: Add 5 ml of 40 % lactic acid pH 6 (final 2 %) and 3.5 ml of 85 % glycerol (final 3 %) to 80 ml of water. Add 10 M NaOH while stirring until the pH reaches 5.5. Dissolve 0.17 g of Yeast nitrogen base (w/o amino acids and ammonium sulfate), 0.06 g of Synthetic Complete (SC) powder (use dropout mix if selection is necessary), 0.5 g of ammonium sulfate, and 0.05 g of glucose (final 0.05 %). Bring volume up to 100 ml. 3. SCLG: same as SCLGg medium but without glucose and with agarose (1.4 %, w/v).

2.1.3 HO Endonuclease Expression and Fixation

1. 20 % (w/v) galactose: Filter-sterilize the galactose stock solution. Do not autoclave, because galactose isomerizes at high temperatures. 2. 4 % paraformaldehyde (PFA): Dissolve 0.8 g of PFA (final 4 %) in pre-warmed (50–60 °C) 17 ml of 0.1 M Na2HPO4 using a

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magnetic stirrer. Once it is dissolved, add 3 ml of 0.1 M NaH2PO4. Final pH should be around 7.6. Prepare immediately before use under an evacuation hood with appropriate ventilation. Do not store. 3. 1× PBS: 1× phosphate-buffered saline (10 mM Na-PO4, 140 mM NaCl, pH 7.5). 2.1.4 Microscope Hardware

1. Microscope (see Note 3). 2. High-sensitivity, cooled and back-lit CCD camera. 3. A magnification objective lens with high numerical aperture (magnification 100, NA > 1.4).

2.1.5 Immobilizing Yeast Cells for Microscopy

1. Depression slides (Glaswarenfabrik Karl Hecht KG “Assistant” Micro slides, order no.: 2415) and cover slips. 2. Aliquot of 1.4 % agarose dissolved in SCLG without glucose. The aliquots in Eppendorf tubes can be kept for months at room temperature.

2.1.6 Zoning Assay

1. ImageJ (http://rsbweb.nih.gov/ij/) or Fiji (http://fiji.sc/Fiji). 2. PointPicker Plugin pointpicker/).

2.2 Co-localization of DNA DSBs with the Nuclear Pore Cluster 2.2.1 Strains

2.3 Quantification of Locus Mobility Under Conditions of DNA Damage 2.3.1 Strains 2.3.2 Media

(http://bigwww.epfl.ch/thevenaz/

The appropriately modified yeast strain bears a locus at which a DSB can be induced (HO or I-SceI site) near integrated tetO or lacO arrays. Alternatively the break can be visualized by fluorescent Rad52. The strain should also contain a fluorescent protein fusion that marks the core structure of nuclear pores, which is visualized as a single pore cluster in the nuclear envelope due to the nup133ΔN mutation (deletion of aa 44–236) [13]. We recommend the use of different fluorescent proteins with distinct emission wavelengths to determine DSB-nuclear pore co-localization, because the overlap of pores and foci tagged with the same fluorescence will be difficult to discern (often the LacI-GFP tagged DSB is much brighter than the Nup49-GFP signal, but not always). The combination of GFPLacI/lacO at the DSB site with CFP-Nup49 is recommended (Fig. 1c). The other material is the same as in section of “Determining the subnuclear localization of DNA damage”. The yeast strain must carry lacO or tetO arrays at a locus of interest, and must express a fusion protein of LacI or TetR with a fluorescent protein such as GFP, YFP or CFP. In addition, it is necessary to have a nuclear pore component such as Nup49 tagged with a fluorescent protein for visualization of the nuclear periphery and subsequent alignment of the nucleus in sequential frames. Synthetic Complete (SC) medium

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2.3.3 Microscopy

1. 18 mm and 24 mm round coverslips. 2. Vacuum grease. 3. A Ludin chamber and microscope stage (obtained from http://www.lis.ch/thechamber.html) preferentially temperature controlled. 4. A temperature controlled spinning disk microscope with an EMCCD camera. 5. Concanavalin A (Sigma): Stock solution 10 mg/ml. 6. 18 mm coverslips coated with Concanavalin A: Pipet 50–100 μl of 10 mg/ml stock solution onto a glass coverslip. Pipet it back up and reuse on another coverslip. Let coverslips dry for 2 h and store at 4 °C for up to 3 months.

2.3.4 Mobility Assay

3

ImageJ or Fiji with the plugin SpotTracker 2D (obtained from http://bigwww.epfl.ch/sage/soft/spottracker).

Methods

3.1 Determining the Subnuclear Localization of DNA Damage 3.1.1 Cell Culture and HO Endonuclease Induction

Carry out all procedures at room temperature unless otherwise specified. Protocols for the induction of HO endonuclease (or I-SceI endonuclease [30]) and the subsequent zoning assay are described here. 1. Grow yeast cells for 2 days on YPAD plate (or synthetic drop out plate if selection is required) at 30 °C (see Note 4). 2. Inoculate the cells in 7.5 ml of SCLGg medium. Grow at 30 °C shaking overnight. 3. Check the cell density by counting cells in a cytometer. It should be an exponentially growing cell population with no more than 5 × 106 cells/ml (see Note 5). 4. Add galactose (filtered stock solution 20 % w/v) to a final concentration of 2 % (w/v) to induce expression of the endonuclease. Cleavage efficiency usually reaches a maximum by 30 min after the addition of galactose (see ref. [5]).

3.1.2 Sampling for Microscopy

1. Harvest 500 μl of culture by centrifugation (1,300 × g, minimal time, e.g., 5 s) at least 30 min after induction by galactose addition. In parallel, one must harvest same amount of culture to monitor the cutting efficiency (see Note 6). 2. Aspirate 450 μl of the supernatant. Dilute the remaining 50 μl in 100 μl of 4 % PFA solution (freshly prepared or stored in small aliquots at −20 °C). Leave at room temperature for 5 min. 3. Collect the cells by centrifugation as above. Wash three times with 300 μl of 1× PBS, pH 7.4. 4. Resuspend in 200 μl of 1× PBS. Store the sample at 4 °C.

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1. Melt SCLG agarose medium at 95 °C for 2–5 min. Prolonged heating causes autofluorescence. 2. Remove 500 μl of the melted agarose medium and add it to a multi-depression slide. Cover with a glass slide to make a flat agarose surface. Let it cool, then remove the glass slide. 3. Add 5–10 μl of the fixed cells well resuspended to the top of the agarose pad. Cover with coverslip. Avoid placing pressure on the agarose pad (see Note 7). 4. Place the sample slide on the microscope and image using the required fluorescent channels, taking 21 focal sections in Z, each of 0.2 μm (16 sections at 0.3 μm is another alternative). If you are using dual color-fluorescence, you should take dual or multichannel images of commercially available fluorescent beads (0.1–0.2 μm, TetraSpeck Fluorescent Microspheres Size Kit, Catalog Number T14792, Life Technologies), to allow you to correct for dichroic or mechanical shift from different channels. 5. Take bright-field images as well (one image plane may be enough) to be able to define the stage of the cell cycle of the imaged cells (see Note 8). It may be necessary to scan the entire 21 planes to identify small buds. 6. See Note 3 concerning our preferred microscopy system.

3.1.4 Determining Chromatin Localization Relative to the Nuclear Periphery

1. First, print out bright-field images and confirm that you can identify the stage of the cell cycle based on (a) absence of bud, (b) presence and size of bud, and (c) position and shape of nucleus. Small buds are easy to miss and will give an aberrant G1-phase score. 2. Open a stack of fluorescent channels. If you use multiple fluorescence channels, open all and merge them. Correct their alignment by using reference dual or multichannel images of commercially available TetraSpeck fluorescent beads. 3. Decide which cells you want to analyze—selecting preferentially cells that have spherical nuclei. Deformed nuclei are not suitable for the 3-zone analysis and should be scored with an alternative “distance from periphery technique” described for C. elegans muscle nuclei in [32]. Only score nuclei if the fluorescent spot is within the middle 50 % of the Z-stack, because due to the limited resolution in Z the distance from the upper and lower cap of pore signal is inaccurate (see ref. [6] for an explanation of this phenomenon and the error in distribution determination that arises from eliminating these planes). Alternatively, one can deconvolve the images and use all planes for measurement.

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4. Once cells are chosen, assign the appropriate cell-cycle stage to each. This is done according to the following criteria: (a) G1: no bud, round nucleus (b) eS: tiny bud, round nucleus (c) mid-to-late S: bud diameter up to 2/3 of the diameter of the mother, round nucleus (d) G2: at least two of the following three criteria: –

Oval shaped nucleus

–

Nucleus moved to the bud neck

–

Bud diameter at least 2/3 of the diameter of the mother cell

5. In ImageJ, with your 3D fluorescent stack open, click on Plugins → pointpicker. 6. Your menu should have changed. In order from the left, these symbols mean: add a point, move a point, remove a point, point in one plane only, point in all planes, show results, quit, zoom in and out. 7. Click on “point in all planes”. 8. Then click on the magnifying glass and zoom into a single nucleus. 9. Identify the plane in the Z stack in which the spot of interest is the brightest. 10. In this plane you will measure the position of the fluorescent spot relative to the nuclear envelope. First click on “add a point”. 11. For each nucleus, click once on the nuclear periphery, closest to a GFP-LacI/lacO spot, then click on the spot, and finally click on the nuclear periphery directly across from the first point. Every time you click a nucleus, mark its relevant stage of the cell cycle on the printed bright-field image that contains the ID number. 12. Do this for all the cells in the field. Then click on “show results”, which is the tool with a file icon, and “open”. You will have 6 columns labelled: ID, point, x, y, slice, color. Point is the click number. Each set of three refers to a single nucleus. X is the X coordinate (in pixels) in your image. Y is the Y coordinate (in pixels) in your image. The fourth column, slice is the slice number. Color is the color of each spot that you clicked, which is useful for tagging cells so that you can identify specific nuclei or cells in dense fields. 13. Copy and paste your data into the premade Excel sheet. The Excel sheet calculates the size of the nucleus in relative terms (i.e., it does not take into account the pixel size). Then it

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calculates the fraction of the nuclear diameter that constitutes the distance between the periphery (1st click) and the spot (2nd click). If the distance is less than ~0.185 × r (the relative radius from the periphery corresponding to 1/3 of the area) it classifies the spot as zone 1. If it is between ~0.185 × r and ~0.44 × r, it is in zone 2. Above that, it is in zone 3. The cell cycle stage is manually entered as a number (1 = G1, 2 = G2, 3 = eS, 4 = mid-to-late S), but the position will be automatically scored. Thanks to Cavalieri’s principle, the determination of position in a single plane is relevant for the focus’ distribution in three dimensions. 14. Do this with 100–150 cells in G1 or in S phase to allow decent statistical power. From fewer than 100 nuclei, it is difficult to draw meaningful conclusions. If you need the G2 data, you will need to analyze a larger number of cells because G2 is a short phase of the cell cycle in budding yeast and many of these cells have a distorted nucleus that is unsuitable for threezone quantitation. 15. The statistical analysis embedded in the Excel sheet is a Fisher’s exact test, which can evaluate whether a spot is significantly enriched in zone 1 over a random distribution. This is not useful to determine if the entire distribution is random nor if the distributions of two different strains or conditions are significantly different. For this analysis, use a χ2- test with a degree of freedom of 2. Note that numbers of nuclei counted should be the same when comparing two conditions or strains. 3.2 Determining DSB Co-localization with Nuclear Pore Clusters 3.2.1 Culture Conditions, Endonuclease Induction, Sampling, and Microscopy 3.2.2 Co-localization of the DSB to Clustered Nuclear Pores

Follow the procedure described in the section “Determining the subnuclear localization of DNA damage”. However, because this method relies entirely on accurate dual-color imaging, it is important to eliminate phase shift due to the different emission wavelengths of two different fluorescent proteins. To manually align images, one must first prepare images of commercial fluorescein calibration beads at the start of each microscopy session, with all relevant channels and filter settings. 1. Print out bright-field images to provide a record of the cells monitored. 2. Open a 3D stack of images in each fluorescent channel, and merge them (the use of false red and false green channels is recommended, as yellow is easy to score for overlapping signals). Correct the alignments of the different channels using as a reference small fluorescent beads captured under identical conditions. 3. Choose the cells relevant for the experiment (cell cycle stage, presence of Rad52 focus or not, etc.). Monitor the position of

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the damage focus in nuclei that have a clear pore cluster. Note that even though the nup133ΔN mutation causes nuclear pore clustering, there can be more than one cluster. You will not be able to monitor co-localization in cells in which pores fail to cluster. 4. Assign a number and appropriate cell cycle stage to each cell. This is done according to the criteria mentioned in Subheading 3.1.4. 5. Score three degrees of co-localization of the tagged chromatin locus with the pore cluster as described above (Fig. 1c, d). (a) Fully overlapping (vast majority of the DSB signal coincides with the pore) (b) Partially overlapping (minority of DSB signal overlaps with pore) (c) Juxtaposition (“touching”; DSB and pore signals are adjacent but without yellow overlap) The statistical frequency of spontaneous or random occurrence of each phenotype should be calculated based on estimated volumes for the pore cluster and fluorescent focus [15]. 3.3 Monitoring the Dynamics of DNA in Yeast 3.3.1 Single Particle Tracking in Live Yeast Cells

1. Day 1: Inoculate one colony in SC medium, and grow with shaking overnight at 30 °C, to obtain a healthy culture the next morning. Note that all cell growth is at 30 °C unless one is using a temperature sensitive allele. 2. Day 2: Dilute the cells 1/100 or 1/50 in fresh SC and continue culturing in SC for at least 4 h, reaching a maximum culture density of 2–5 × 106 cells per ml. Do not go above this density as the depletion of the glucose levels impacts chromatin movement (see ref. [16]). 3. Pre-warm the microscope temperature box to 25 °C. 4. Assemble the Ludin chamber. Smear vacuum grease on the inner edges of the Ludin chamber base where the coverslip sits. Place a single Concanavalin A coated 18 mm coverslip in the bottom of the Ludin chamber with the coated side facing up. Screw in the middle part of the Ludin chamber. 5. Pipette 2 ml of the yeast culture on top. Allow 2–3 min for the cells to settle and adhere to the coverslip. 6. Pipet out the culture and gently rinse three times with SC medium. The excess of cells that have not adhered to the coverslip will be washed away. Take care to pipet gently to the side of the coverslip so as to not wash away any adhered cells. 7. Add 1.5 ml of SC medium to the Ludin chamber, cover with a 24 mm coverslip and screw in the top part of the chamber. 8. Add oil to the objective and place the Ludin chamber into its stage.

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9. Acquire the images using the 100 × N/A 1.45 oil objective. It is important to ensure that the correct balance of signal intensity to bleaching is worked out before the experiment is started. In addition, as little light should be used as possible to protect cells from laser-induced damage, which is known to change chromatin mobility [23]. Particularly if cells will be imaged over prolonged periods of time, one must check for light-induced DNA damage by monitoring the effects of imaging on cell cycle progression. Moreover, one must ensure that glucose levels are not being depleted. Media containing 4 % carbon source can circumvent the latter problem. Acquisition settings for the movies vary depending on the capabilities of the microscope. Typically, images are acquired every 1.5 s taking a Z-stack of 4 μm spread through 300 nm slices for 5 min. Successful imaging has been done at acquisition intervals as low as 80 ms where the Z-stack was reduced to 1.6 μm with 200 nm slices for 1 min. However, this requires a good EMCCD camera as well a bright spot. Another limitation is that the speed of reading a complete EMCCD chip is approximately 30 ms and thus when acquiring at 80 ms intervals only a small portion of the chip can be selected to allow the images to be sent to the computer before the next image is acquired. This usually means that only a single nucleus can be tracked at any one time. 3.3.2 Image Processing

1. Once the images are acquired they will be too noisy to analyze and must first be deconvolved with a program such as Huygens Professional. For example, deconvolve the images with Huygens Remote Manager (http://huygens-rm.org/home/) using S/N = 5, automatic background subtraction with 15 iterations or quality change of 0.1. Determining the correct parameters for deconvolution is critical for yeast nuclei due to their small size, and goes beyond the scope of this review. 2. Open the deconvolved images either with Imaris or with ImageJ (Fiji distribution). 3. Crop the images so that there is only one cell in the field of view and that the nucleus remains within the field of view for the entire movie. 4. Project the 3D movie in 2D (ImageJ: image → stack →z-project→maximum intensity projection). For a discussion of 3D vs 2D tracking see ref. [17]. 5. Change the bit depth from 32 to 8 (image →type →8-bit). 6. Select the movie containing the spot you want to track and start the spot tracker plugin. 7. On the drop-down menu on the right section, select M.I.P (stands for maximum intensity projection). This will allow the

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spot and the nuclear background to be better distinguished but does not change the tracking properties. 8. Next the nucleus must be aligned. To do this click: Processing → nucleus alignment 9. Adjust the threshold so that only the nucleus is highlighted in red while the background remains black. 10. Click on align. 11. The software will draw a green line around the nucleus in each frame. A good alignment is one in which the nuclear centers form a straight line. This will not be possible for poor quality movies and they should be excluded from the analysis. Repeat the alignment as often as you need to get a perfect alignment. 12. The quality of the alignment is critical. If it is not aligned well, there will be artifacts in your tracking and there is likely to be an overestimation of the movement. 13. Note that not all cells will be of good enough quality to be able to be tracked accurately. Do not use cells where the nuclear shape changes midway through the movie or where alignment is not possible. Try to monitor cells all in the same stage of the cell cycle. This can be determined by bud size. 14. Once you are confident that your alignment is good, click on track. 15. Use the following parameters: (a) Cone aperture (that is the expected size of the spot you would like to track): 5 (b) Normalize factor: 80 (c) Movement constraint (maximum distance that the spot is expected to travel between two frames): 25. Note that a smaller value favors smaller steps between two frames. (d) Center constraint (how far from the periphery is the spot expected to be?): 20. Note that a smaller value favors smallers steps between two frames. (e) Check subpixel resolution (it will fit a Gaussian to the signal and determine the center of the focus with 0.1 pixel accuracy). (f) Confidence decision (the software will calculate a score of how close to perfect it estimates that spot position is correct): 10 16. Click on “track”. 17. The software will draw a line through the path of your spot. Go through each frame using the sliding bar at the bottom and make sure that the program has accurately located the spot.

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18. If it does not, the position of the spot can be redefined (but in this case subpixel resolution is lost) by right clicking over the position you want the path to go through (i.e., the spot position in that frame) and select “add a node”. Click “track” again. 19. This can be done as often as necessary. However, it should be done as little as possible. If the movie requires that it is done more than two to three times, it is probably because the images are not of good enough quality and the movie should be dropped from the analysis. 20. Once done, save the resulting trace: Results → show as table → Summary. (a) The summary will have four columns: –

Spot x and spot y are the coordinates for the position of your spot

–

Center x and center y are the coordinates for the nuclear center in each frame.

(b) To save: “file → save as”. 21. The trace can now be imported into the Excel macro. 3.3.3 Quantification of Locus Mobility of DNA Damage with the MS Excel Macro

1. Preparation: Open msd_analysis.r0037.xls (where 0037 is the version number). 2. Enable Macros (Excel should prompt you when you open the document). 3. Parameters: This section describes the parameters that can be set to influence the behavior of the different import and analysis modules. First adjust the import parameters of the traces in row 2. Note that the units decided upon here should be the same throughout. The macro will not take into account changes in units. It is important to enter the right parameters before the analysis is started. 4. Trajectory Import: Fill in the pixel size for your microscope in microns in cell A2. 5. Fill in the time in seconds between each frame taken in cell D2 (default is 1.5). 6. MSD analysis: Fill in the X-axis (in the time unit you chose above) in cell N5 and Y-axis upper limit (in the square of the length unit chosen above) for the MSD output graph. These parameters only apply to the graphical output. The software will calculate the full MSD regardless of what is introduced here. 7. The diffusion coefficient (D) is calculated from the initial slope on an MSD graph, where the curve is linear (see Note 9). Since the curves will not be necessarily linear for the same number of time intervals depending on experimental settings

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and the time between the frames, the upper and lower limits that the software will use to calculate the diffusion coefficient can be specified in cells R5 and T5. These numbers refer to the number of steps, not to the number of seconds! For example, if 1 and 5 are entered and the time between the frames of 1.5 (in cell D2), it will calculate D for the time intervals between 1.5 and 7.5 s. 8. Large steps: A large step is counted when the distance between two points on the trajectory that are separated by a fixed time window exceeds a given threshold. These give the impression of directional movement on a short time scale, and often large steps in one direction are followed by a return movement, suggesting an elastic character of the chromatin fiber (see Note 10). 9. Threshold distance (in the same unit of length as in cell A2), default 0.5. 10. Number of time steps (n.b. not the time in seconds) between start and end point of a large step, default = 7. 11. Normalization of time window (in the time unit N5 if movie lengths vary, a standard limit for the time can be entered. By default this number is 600 s (10 min). 12. Trajectory Import: Click on “Import SpotTracker Trajectories”. Select the SpotTracker output files to analyze and click OK. Due to limitations imposed by Excel, the names of the files should not be longer than 27 characters. This will NOT rename the files that you saved on your computer, and the full path to each file is saved in cell C1 of the trajectory sheet. It is essential that the output file has 4 columns in the following order: Spot1X, Spot1Y, Spot2X, Spot2Y. The name of the columns is not important, but the order of the columns and their number are crucial. 13. After clicking OK, the software will import the numbers and calculate the changes in positions multiplied by the pixel size to obtain actual distances. Each movie will have a separate worksheet. 14. The software will bring up the worksheet called “admin”, which has all the parameter data. Clicking on the newly created worksheets one will observe the imported data on the left and, in yellow, the distances adjusted to your pixel size along with the time intervals on the right. 15. MSD analysis: On the admin worksheet, click on MSD. This macro calculates the MSD for each imported file and generates the plots. It also creates a worksheet called MSD summary. 16. The MSD summary sheet: Go to the MSD summary sheet. 17. The file names are shown in green on the left, the MSD data in yellow in the middle and the graph on the right. The three

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columns in yellow are, from left to right, time intervals (the X -axis), MSD value (the Y -axis), and standard error of the MSD mean (the error bars). Above the graph, in cell J4, is the diffusion coefficient. It is expressed in the units of the pixel size and the time step (see admin sheet cell B2). If you used micron for the pixel size and second for the time step then the diffusion coefficient will be given in micrometer2/s. Cell K4 contains the standard error of the mean, and cell J5 presents the radius of constraint (see Note 11). The diffusion coefficient for each individual movie can also be found in their MSD sheets in cell J4. 18. Exclusion and inclusion of trajectories: Go to the newly created “MSD graphs” worksheet. 19. A visual inspection of each movie should be done to identify errors. If one or more movies need to be excluded from the analysis, go back to the MSD summary sheet and click “exclude trajectories”. It will bring up the list of MSD sheets. Select the ones to be excluded and click OK. The software will recalculate the average MSD and show the excluded movie in red on the left. It also recalculates the radius of constraint and its error, and the diffusion coefficient. 20. To include a rejected movie, click on “include trajectories”, select the movie to be included and click OK. 21. Large Steps analysis: On the admin sheet, click on “Large Steps”. Then click on the Large step worksheet tab. 22. This calculates the number of large steps for each movie and also displays the normalized version of each based on the parameters you have entered on the admin sheet. 23. Import trajectory worksheets: This button, found on the admin sheet, allows one to import the movies from a different analysis. Instead of reimporting each movie separately, click “Import trajectory worksheet” and select the previous spreadsheet containing the data to be updated. 24. Clear and Clear MSD: The Clear button will delete permanently all sheets except “admin”. Use wisely. 25. The Clear MSD button only deletes MSD sheets, but keeps the imported movies intact. This is useful if one wants to recalculate D or Rc with different parameters.

4

Notes 1. This is done by inserting 4 double LexA binding sites next to the lacO array, in a strain that expresses LexA fused to the protein of interest. A control of expressing LexA alone should be performed, although in our hands LexA does not alter the

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position of either a randomly distributed or a peripherally anchored locus. For details on this method see ref. [33]. 2. Excel sheets and macros: All the described Excel sheets and macros are available upon request (contact [email protected]). 3. Our preferred microscope apparatus is as follows: Images for zoning measurements are captured on a Metamorph-driven Spinning-disk confocal system based on an Olympus IX81 microscope, Yokogawa CSU-X1 scan head, EM-CCD Cascade II (Photometrics) camera and an ASI MS-2000 Z-piezo stage. We use PlanApo × 100, NA 1.45 total internal reflection fluorescence microscope oil objective. 4. Note that strains carrying lacO or tetO arrays should not be stored on plates as the repeats are unstable and copy number is often reduced by recombination. Always check for that the focus is visible in a colony before using it for inoculation. 5. High cell concentrations should be avoided, due to changes induced by the diauxic shift upon glucose depletion (see ref. [16]). It is also inappropriate if cells are taken too early (low concentration) because the residual presence of glucose dampens the expression of HO or I-SceI from the GAL1 promoter. 6. In assays that aim to score the position of a DSB, one must harvest a fraction of the cells used for position measurements, in order to monitor the cutting efficiency by qPCR at each time-point. A standard genomic DNA preparation is used for the qPCR-based analysis of cut efficiency. 7. Make sure that cells are not distorted by the pressure of the coverslip. 8. It is important to take bright-field images as well as fluorescence stacks, and to make sure that images of control and experimental samples are taken close to the same time. Use the same setting for camera and exposure for robust comparative experiments. 9. Diffusion coefficient: The diffusion coefficient calculation takes the initial slope of each movie using Excel’s linear fit algorithm (see Excel help for details) and then derives D. It averages the D from each movie and calculates the standard error of the mean. 10. Large steps: This macro will find for each movie the large steps defined empirically as 0.5 μm steps within 10.5 s, normalized over 10 min. It uses a sliding window of 10.5 s (7 frames of 1.5 s each) until it encounters a large step. Once the software encounters a large step, it will start looking for additional large steps with a window starting from the last time frame containing the large step and 7 frames later. The macro does this to avoid having a single, long “large step” counted several times.

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If the software finds a large step within the last 6 frames (the window size −1) from the end of the movie, it will count it and then stop. 11. Radius of constraint (Rc): Rc is calculated as the maximum MSD value between 0 and the value entered in cell N5 of the admin sheet. The equation is Rc = (max MSD/0.8)½. This formula is unique to the analysis of 3D movies projected and tracked in 2D, whereas the formula in Fig. 2 are generic. See the Supplementary material in ref. [17] for detailed explanations and the formulae needed for the analysis of movement in 3D and Rc calculation.

Acknowledgement We thank J. E. Haber for yeast strains and the Friedrich Miescher Institute Microscopy Facility for technical help. C.H. thanks the Marie Curie International program and JSPS Research Abroad program for fellowships. The Gasser laboratory thanks the Novartis Research Foundation, the Swiss National Science Foundation “Sinergia grant,” NCCR “Frontiers in Genetics,” and the Human Frontier Science Program (RGP0017). References 1. Nagai S, Dubrana K, Tsai-Pflugfelder M et al (2008) Functional targeting of DNA damage to a nuclear pore-associated SUMO-dependent ubiquitin ligase. Science 322:597–602 2. Oza P, Jaspersen SL, Miele A et al (2009) Mechanisms that regulate localization of a DNA double-strand break to the nuclear periphery. Genes Dev 23:912–927 3. Oza P, Peterson CL (2010) Opening the DNA repair toolbox: localization of DNA double strand breaks to the nuclear periphery. Cell Cycle 9:43–49 4. Kalocsay M, Hiller NJ, Jentsch S (2009) Chromosome-wide Rad51 spreading and SUMO-H2A.Z-dependent chromosome fixation in response to a persistent DNA doublestrand break. Mol Cell 33:335–343 5. Horigome C, Oma Y, Konishi T et al (2014) SWR1 and INO80 chromatin remodelers contribute to DNA double-strand break perinuclear anchorage site choice. Mol Cell 55:626–639 6. Meister P, Gehlen LR, Varela E et al (2010) Visualizing yeast chromosomes and nuclear architecture. Methods Enzymol 470:535–567 7. Belmont AS (2001) Visualizing chromosome dynamics with GFP. Trends Cell Biol 11:250–257

8. Straight AF, Belmont AS, Robinett CC, Murray AW (1996) GFP tagging of budding yeast chromosomes reveals that proteinprotein interactions can mediate sister chromatid cohesion. Curr Biol 6:1599–1608 9. Bystricky K, Van Attikum H, Montiel MD et al (2009) Regulation of nuclear positioning and dynamics of the silent mating type loci by the yeast Ku70/Ku80 complex. Mol Cell Biol 29:835–848 10. Dion V, Kalck V, Seeber A et al (2013) Cohesin and the nucleolus constrain the mobility of spontaneous repair foci. EMBO Rep 14: 984–991 11. Sugawara N, Haber JE (2012) Monitoring DNA recombination initiated by HO endonuclease. Methods Mol Biol 920:349–370 12. Horigome C, Okada T, Shimazu K et al (2011) Ribosome biogenesis factors bind a nuclear envelope SUN domain protein to cluster yeast telomeres. EMBO J 30:3799–3811 13. Doye V, Wepf R, Hurt EC (1994) A novel nuclear pore protein Nup133p with distinct roles in poly(A) + RNA transport and nuclear pore distribution. EMBO J 13:6062–6075 14. Loeillet S, Palancade B, Cartron M et al (2005) Genetic network interactions among

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15.

16.

17.

18.

19.

20.

21.

22.

23.

Chihiro Horigome et al. replication, repair and nuclear pore deficiencies in yeast. DNA Repair (Amst) 4:459–468 Schober H, Ferreira H, Kalck V et al (2009) Yeast telomerase and the SUN domain protein Mps3 anchor telomeres and repress subtelomeric recombination. Genes Dev 23: 928–938 Heun P, Laroche T, Shimada K et al (2001) Chromosome dynamics in the yeast interphase nucleus. Science 294:2181–2186 Neumann FR, Dion V, Gehlen LR et al (2012) Targeted INO80 enhances subnuclear chromatin movement and ectopic homologous recombination. Genes Dev 26:369–383 Dion V, Gasser SM (2013) Chromatin movement in the maintenance of genome stability. Cell 152:1355–1364 Hediger F, Dubrana K, Gasser SM (2002) Myosin-like proteins 1 and 2 are not required for silencing or telomere anchoring, but act in the Tel1 pathway of telomere length control. J Struct Biol 140:79–91 Rosa A, Maddocks JH, Neumann FR et al (2006) Measuring limits of telomere movement on nuclear envelope. Biophys J 90: L24–L26 Taddei A, Van Houwe G, Hediger F et al (2006) Nuclear pore association confers optimal expression levels for an inducible yeast gene. Nature 441:774–778 Dion V, Kalck V, Horigome C et al (2012) Increased mobility of double-strand breaks requires Mec1, Rad9 and the homologous recombination machinery. Nat Cell Biol 14:502–509 Seeber A, Dion V, Gasser SM (2013) Checkpoint kinases and the INO80 nucleosome remodeling complex enhance global chromatin mobility in response to DNA damage. Genes Dev 27:1999–2008

24. Gartenberg MR, Neumann FR, Laroche T et al (2004) Sir-mediated repression can occur independently of chromosomal and subnuclear contexts. Cell 119:955–967 25. Marshall WF, Straight A, Marko JF et al (1997) Interphase chromosomes undergo constrained diffusional motion in living cells. Curr Biol 7:930–939 26. Mine-Hattab J, Rothstein R (2012) Increased chromosome mobility facilitates homology search during recombination. Nat Cell Biol 14:510–517 27. Sage D, Neumann FR, Hediger F et al (2005) Automatic tracking of individual fluorescence particles: application to the study of chromosome dynamics. IEEE Trans Image Process 14: 1372–1383 28. Jensen RE, Herskowitz I (1984) Directionality and regulation of cassette substitution in yeast. Cold Spring Harb Symp Quant Biol 49:97–104 29. Sandell LL, Zakian VA (1993) Loss of a yeast telomere: arrest, recovery, and chromosome loss. Cell 75:729–739 30. Plessis A, Perrin A, Haber JE, Dujon B (1992) Site-specific recombination determined by I-SceI, a mitochondrial group I intronencoded endonuclease expressed in the yeast nucleus. Genetics 130:451–460 31. Jacquier A, Dujon B (1985) An intronencoded protein is active in a gene conversion process that spreads an intron into a mitochondrial gene. Cell 41:383–394 32. Meister P, Towbin BD, Pike BL et al (2010) The spatial dynamics of tissue-specific promoters during C. elegans development. Genes Dev 24:766–782 33. Taddei A, Hediger F, Neumann FR et al (2004) Separation of silencing from perinuclear anchoring functions in yeast Ku80, Sir4 and Esc1 proteins. EMBO J 23:1301–1312

Chapter 7 Detecting Reactive Oxygen Species by Immunohistochemistry Geou-Yarh Liou and Peter Storz Abstract In cultured cells, an increase in cellular levels of reactive oxygen species (ROS) can be detected using multiple techniques including colorimetric assays, immunoblotting, and immunofluorescence. These methods can also be applied for ROS measurement in tissue samples, but often require tissue homogenization, and therefore do not distinguish between the different cell types within a tissue. Here, we describe a detailed protocol for determination of altered oxidative stress levels in different cell types in tissues, by detecting ROS-caused alteration of macromolecules using immunohistochemistry (IHC). This method is demonstrated by using 4HNE as a marker for lipid peroxidation in mouse pancreas tissue that contains precancerous lesions high in cellular oxidative stress. Key words Oxidative stress, Reactive oxygen species, Immunohistochemistry, Lipid peroxidation, 4HNE

1

Introduction Aberrant, net accumulation of reactive oxygen species (ROS) in cells and tissues has been implicated in numerous diseases such as diabetes, neurodegenerative disorders, and cancer, but also shortening of lifespan and organismal aging. Reactive oxygen species (ROS) are highly reactive molecules containing oxygen with unpaired electrons. Generation of ROS can be induced by environmental and other extracellular sources or internally in cellular organelles during biological processes. Inside a cell, ROS are generated as byproducts in many organelles including mitochondria, endoplasmic reticulum, and peroxisomes. These highly reactive molecules not only attack DNA to cause DNA damage and adduct formation (i.e., DNA double strand breaks, 8-hydroxy-2deoxyguanosine/8-oxo-dG) but also lead to protein oxidation (i.e., nitro-tyrosine) and lipid peroxidation (i.e., 4 hydroxy-2noneal/4HNE, malondialdehyde). Elimination of excess cellular ROS is mediated by scavenging systems including superoxide

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Table 1 Antigens that can be targeted to evaluate cellular ROS levels in tissue immunohistochemistry Antibody directed against

Readout for ROS

Tissue fixation

Reference

8-Hydroxy-2-deoxyguanosine (8-oxo-dG)

DNA damage

Formalin ethanol

[3, 4]

8-Nitroguanine

DNA damage

Formalin

[5, 6]

Thymidine glycol (TG)

DNA damage

Formalin

[7]

Dinitrophenyl (DNP)

Protein oxidation

Methacarn

[8, 9]

Nitrotyrosine

Protein oxidation

Formalin

[10, 11]

4-Hydroxy-2-noneal (4HNE)

Lipid peroxidation

Formalin

[3, 12]

Malondialdehyde (MDA)

Lipid peroxidation

Formalin

[13, 14]

Acrolein (ACR)

Lipid peroxidation

Paraformaldehyde

[15, 16]

Methyglyoxal (MG)

Lipid peroxidation

Formalin

[17]

Hexanoyl-lysine (HEL)

Lipid peroxidation

Formalin

[18, 19]

Crotonaldhyde (CRA)

Lipid peroxidation

Paraformaldehyde formalin

[20, 21]

7-Ketocholesterol (7-KC) a

Lipid peroxidation

a

N/A

[22, 23]

Frozen tissue section

dismutase, catalase, glutathione peroxidase, and peroxiredoxins [1]. Since long-term imbalance between cellular ROS production and elimination has been implicated in organismal aging and onset and progression of numerous disorders including neurodegenerative diseases and cancer, it is important to be able to evaluate cellular ROS levels in clinical patient tissue samples or in animal models recapitulating disease [1, 2]. In this chapter, we provide an immunohistochemistry protocol to assess cellular oxidative stress levels, using mouse pancreatic precancerous lesions and the lipid peroxidation product 4HNE as an indicator of ROS. With minor modifications (i.e., first antibody, and adjustment of dilution) this protocol can be applied to also detect DNA adducts, protein oxidation, and other lipid peroxidation products (Table 1) by immunohistochemistry in any tissue of interest.

2 2.1

Materials Buffers

1. Sodium citrate buffer pH 6.0: 10 mM sodium citrate, 0.05 % Tween 20, in distilled H2O. Adjust pH to 6.0. 2. Phosphate-buffered saline (PBS): Dissolve 8 g of NaCl, 0.2 g of KCl, 1.44 g of Na2HPO4 and 0.24 g of KH2PO4 in 800 ml

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of distilled H2O; then adjust pH to 7.4; and then adjust volume to 1 L with additional distilled H2O. 3. TBST buffer pH 7.6: 50 mM Tris, 150 mM NaCl, 0.05 % Tween 20, in distilled H2O. Adjust pH to 7.6. 4. Blocking buffer: 5 % goat serum in 1× TBST buffer. 5. 95 % ethanol solution: 95 mL of 100 % ethanol, 5 mL of distilled H2O. 6. 80 % ethanol solution: 80 mL of 100 % ethanol, 20 mL of distilled H2O. 7. 3 % H2O2 solution: 5 mL of 30 % H2O2, 45 mL of distilled H2O. 2.2 Immunohistochemistry

1. Rabbit anti-4HNE sera from Alpha Diagnostic International Inc. (San Antonio, TX, USA); or other antibodies directed against antigens that can serve as readout for increased oxidative stress (Table 1). 2. HRP-conjugated goat-anti-rabbit antibody (or other HRPconjugated secondary antibody directed against the species in which the primary antibody was raised). 3. 3,3′-diaminobenzidine (DAB) peroxidase substrate kit (available from multiple vendors).

2.3

Other Materials

1. Tissue slides with tissue of interest. 2. Pressure cooker or steamer. 3. Staining jar or holder (use polyethylene instead of glass). 4. Pap pen (optional). 5. Sharp-end forcep tweezers. 6. Standard IHC mounting medium (available from multiple vendors). 7. Coverslips.

3

Methods Unless otherwise specified, carry out all procedures at room temperature (20 °C). 1. Incubate tissue slides in xylene for 5 min.

3.1 Deparaffinization of Tissue Slides

2. Repeat step 1 for another two times (see Note 1).

3.2 Rehydration of Tissue Slides

1. Perform three washes with 100 % ethanol (see Note 2), 3 min for each wash. 2. Perform two washes with 95 % ethanol, 3 min for each wash.

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3. Perform two washes with 80 % ethanol, 3 min for each wash. 4. Rinse tissue slides in distilled water for 5 min, twice. 3.3

Antigen Retrieval

1. Heat tissue slides (see Notes 3 and 4) in sodium citrate buffer pH 6.0 at 95–100 °C for 20 min. 2. Remove the heat and let tissue slides cool in sodium citrate buffer on the bench until the temperature reaches room temperature (see Note 5). 3. Wash tissue slides with phosphate buffered saline (PBS) for 5 min, three times (see Note 6).

3.4 Immunohistochemical Staining of Tissue Slides

1. Incubate tissue slides with 3 % hydrogen peroxide for 10 min. 2. Wash tissue slides with PBS for 5 min; repeat this step three times. 3. Place tissue slides in blocking buffer for 1 h at room temperature. 4. Prepare 4HNE antibody solution by adding rabbit anti-4HNE antibody to blocking buffer at a dilution of 1:600 (see Note 7). 5. Remove tissue slides from blocking buffer. 6. Apply 4HNE antibody solution to tissue sample area (see Note 8) and incubate overnight at 4 °C (see Note 9). 7. Remove 4HNE antibody solution from tissue slides. 8. Wash tissue slides with TBST buffer for 5 min; repeat this step three times. 9. Prepare secondary antibody solution by adding HRPconjugated goat-anti-rabbit antibody in blocking buffer at a dilution recommended by the manufacturer. 10. Remove tissue slides from TBST buffer. 11. Apply HRP-conjugated goat-anti-rabbit secondary antibody solution to the tissue slide (see Note 10) and incubate for 30 min at room temperature (20 °C). 12. Remove secondary antibody solution from tissue slides. 13. Wash tissue slides with TBST buffer for 5 min; repeat this step three times. 14. Prepare DAB substrate solution according to the manufacturer’s instructions. 15. Apply DAB substrate solution to tissue slides. Ensure that the substrate solution completely covers the tissue sample area. 16. Watch closely as tissue sample color turns into brown (see Note 11). When the signal intensity reaches the ideal condition (not too light, not too dark; Fig. 1), stop the reaction by immersing slides in distilled water. 17. Wash tissue slides with distilled water for 5 min, twice.

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Fig. 1 Detection of elevated ROS levels in pre-cancerous lesions. Staining of pancreatic tissues from a control mouse and a p48cre; LSL-KrasG12D mouse, in which Kras with a proto-oncogenic mutation (KrasG12D) was expressed under a pancreatic cell-specific transcription factor (p48). Expression of KrasG12D leads to precancerous pancreatic lesions that show high levels of oxidative stress. Tissues were fixed in formalin and then subjected to 4HNE immunohistochemistry (top panel) as described in this chapter. Additional hematoxylin & eosin (H&E) staining was performed to show pancreas morphology (bottom panel). The data shows that our protocol is effective to detect oxidative stress-mediated lipid oxidation in the abnormal pancreatic lesions (brown staining), but not in the control. Scale bar: 40 μm

3.5 Dehydration and Mounting of Tissue Slides

1. Incubate tissue slides with 80 % ethanol for 10 s, twice (see Note 12). 2. Incubate tissue slides with 95 % ethanol for 10 s, twice. 3. Incubate tissue slides with 100 % ethanol for 10 s, twice. 4. Incubate tissue slides with xylene for 10 s, twice. 5. Apply mounting media to the tissue slides and apply coverslips (see Note 13).

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Notes 1. Xylene is flammable and a health hazard. This step should be carried out in a chemical fume hood with outdoor exhaust ventilation. 2. Ethanol is flammable and a hazardous material. This step should be carried out in a chemical fume hood with outdoor exhaust ventilation. 3. A pressure cooker or steamer is ideal for this key step because it can maintain a fairly constant temperature nearing boiling point. 4. Do not use a glass staining jar or holder in this step because they will crack at high temperature. A polyethylene staining jar which can endure high temperature is best suitable for this process. In addition, using a polyethylene staining jar inside the streamer reduces the amount of sodium citrate buffer to be used. 5. Make sure that the surface of the tissue sample area is always moist and kept in buffer or solution. 6. Immediately proceeding to the immunostaining procedure is highly recommended after antigen retrieval. 7. This dilution (1:600) for the 4HNE antibody is optimized for mouse pancreas tissues. For other tissue types, either mouse or human, optimal dilution can vary and needs to be determined. 8. If you want to decrease the amount of 4HNE antibody solution that will be used in the next step, create a water-proof barrier by circling the tissue sample area on the glass slide using a pap pen. 9. To avoid the 4HNE antibody solution from drying out during overnight incubation, the tissues slide can be placed on top of a wet paper towel in a sealable plastic container. This preserves the moisture inside the container. 10. Ensure that the goat-anti-rabbit antibody solution completely covers the tissue sample area. 11. The time period of incubation to develop signals varies and depends on the (DAB) peroxidase substrate kit used (see manufacturer’s instructions). To test the incubation time for optimal signal intensity, it is recommended using tissue samples that have high levels of cellular ROS and control tissue slides (see Fig. 1). At ideal development time, a clear difference of 4HNE signal intensity between positive and negative tissue samples should be observed. 12. Steps 1–4 should be performed in a chemical fume hood with outdoor exhaust ventilation.

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13. To avoid generating air bubbles between tissue sample area and coverslip, drop mounting media directly on top of the tissue area. Then use sharp-end forcep tweezers to hold the coverslip at one end and let the other end of the coverslip stand on the tissue slide. Slowly close the gap between tissue slide and coverslip by putting down the coverslip entirely.

Acknowledgement This work was supported by NIH grants CA140182 and GM086435 to PS. References 1. Liou GY, Storz P (2010) Reactive oxygen species in cancer. Free Radic Res 44:479–496 2. Quintanilla RA, Orellana JA, von Bernhardi R (2012) Understanding risk factors for Alzheimer’s disease: interplay of neuroinflammation, connexin-based communication and oxidative stress. Arch Med Res 43:632–644 3. Young O, Crotty T, O’Connell R et al (2010) Levels of oxidative damage and lipid oxidation in thyroid neoplasia. Head Neck 32: 750–756 4. De Luca G, Russo MT, Degan P et al (2008) A role for oxidized DNA precursors in Huntington’s disease-like striatal neurodegeneration. PLoS Genet 4:e1000266 5. Hiraku Y, Kawanishi S (2009) Immunohistochemical analysis of 8-nitroguanine, a nitrative DNA lesion, in relation to inflammationassociated carcinogenesis. Methods Mol Biol 512:3–13 6. Horiike S, Kawanishi S, Kaito M et al (2005) Accumulation of 8-nitroguanine in the liver of patients with chronic hepatitis C. J Hepatol 43:403–410 7. Ito K, Yano T, Morodomi Y et al (2012) Serum antioxidant capacity and oxidative injury to pulmonary DNA in never-smokers with primary lung cancer. Anticancer Res 32:1063–1067 8. Aksenov MY, Aksenova MV, Butterfield DA et al (2001) Protein oxidation in the brain in Alzheimer’s disease. Neuroscience 103:373–383 9. Smith MA, Sayre LM, Anderson VE et al (1998) Cytochemical demonstration of oxidative damage in Alzheimer disease by immunochemical enhancement of carbonyl reaction with 2,4-dinitrophenylhydrazine. J Histochem Cytochem 46:731–735 10. Win S, Than TA, Han D et al (2011) c-Jun N-terminal kinase (JNK)-dependent acute

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13.

14.

15.

16.

17.

18.

liver injury from acetaminophen or tumor necrosis factor (TNF) requires mitochondrial Sab protein expression in mice. J Biol Chem 286:35071–35078 Vlahos R, Stambas J, Bozinovski S et al (2011) Inhibition of Nox2 oxidase activity ameliorates influenza A virus-induced lung inflammation. PLoS Pathog 7:e1001271 Kweider N, Huppertz B, Wruck CJ et al (2012) A role for Nrf2 in redox signaling if the invasive extravillous trophoblast in severe early onset IUGR associated with preeclampsia. PLoS One 7:e47055 Neria F, Castilla MA, Sanchez RF et al (2009) Inhibition of JAK2 protects renal endothelial and epithelial cells from oxidative stress and cyclosporine A toxicity. Kidney Int 75: 227–234 Kong X, Zhang Y, Wu HB et al (2012) Combination therapy with losartan and pioglitazone additively reduces renal oxidative and nitrative stress induced by chronic high fat, sucrose, and sodium intake. Oxid Med Cell Longev 2012:856085 Gregg SQ, Gutierrez V, Robinson A et al (2012) A mouse model of accelerated liver aging caused by a defect in DNA repair. Hepatology 55:609–621 Okuno Y, Nakamura-Ishizu A, Otsu K et al (2012) Pathological neoangiogenesis depends on oxidative stress regulation by ATM. Nat Med 18:1208–1216 Oya T, Hattori N, Mizuno Y et al (1999) Methylglyoxal modification of protein. Chemical and immunochemical characterization of methylglyoxal-arginine adducts. J Biol Chem 274:18492–18502 Fukuchi Y, Miura Y, Nabeno Y et al (2008) Immunohistochemical detection of oxidative

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stress biomarkers, dityrosine and N(epsilon)(hexanoyl)lysine, and C-reactive protein in rabbit atherosclerotic lesions. J Atheroscler Thromb 15:185–192 19. Tomaru M, Takano H, Inoue K et al (2007) Pulmonary exposure to diesel exhaust particles enhances fatty change of the liver in obese diabetic mice. Int J Mol Med 19:17–22 20. Shibata N, Kawaquchi M, Uchida K et al (2007) Protein-bound crotonaldehyde accumulates in the spinal cord of superoxide dismutase-1 mutation-associated familial amyotrophic lateral sclerosis and its transgenic mouse model. Neuropathology 27:49–61

21. Kawaguchi-Niida M, Shibata N, Morikawa S et al (2006) Crotonaldehyde accumulates in glial cells of Alzheimer’s disease brain. Acta Neuropathol 111:422–429 22. Myoishi M, Hao H, Minamino T et al (2007) Increased endoplasmic reticulum stress in atherosclerotic plaques associated with acute coronary syndrome. Circulation 116:1226–1233 23. Moreira EF, Larrayoz IM, Lee JW et al (2009) 7-Ketocholesterol is present in lipid deposits in the primate retina: potential implications in the induction of VEGF and CNV formation. Invest Ophthalmol Vis Sci 50:523–532

Chapter 8 Investigating Inflammasome Activation Under Conditions of Cellular Stress and Injury Clare C. Cunningham, Emma M. Corr, Donal J. Cox, and Aisling Dunne Abstract Inflammasomes are large multiprotein complexes that assemble in response to cellular stress and infection. NOD-like receptor-related proteins (NLRPs) are essential components of these complexes and are activated by exogenous and endogenous danger signals such as crystalline substances, extracellular ATP, and pore-forming toxins. In general, inflammasome activation is accompanied by perturbations in cellular homeostasis. For example, most inflammasome activators will trigger cation efflux, reactive oxygen species (ROS) generation and caspase-1-dependent cell death, commonly referred to as pyroptosis. In this chapter, we describe protocols to examine inflammasome activation and accompanying events in vitro. Key words Inflammasome, Interleukin-1β, Cell stress, Reactive oxygen species, Pyroptosis

1

Introduction NOD-like receptor-related proteins (NLRPs) are a family of intracellular receptors that are activated in response to endogenous danger-associated molecular patterns (DAMPs) as well as a range of microbial products, collectively referred to as pathogen-associated molecular patterns (PAMPs). Of the currently identified NLRP family members, NLRP3 is undoubtedly the most extensively characterized. On activation, NLRP3 forms a large multiprotein complex termed the inflammasome resulting in caspase-1 activation and the subsequent cleavage of pro-IL-1β and pro-IL-18 into their mature and active forms [1]. In many cases this is also coupled to a form of cell death referred to as pyroptosis, so called as it is characterized by necrotic cell death coupled to inflammatory cytokine release [2]. A number of factors and changes typically associated with cellular stress have been proposed to contribute to inflammasome assembly, for example, oxidative stress and lysosomal rupture by crystalline substances appear sufficient to drive IL-1β processing [3]. Ion flux is also associated with inflammasome activation and all NLRP3 activators identified to date drive an efflux of potassium

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ions (K+) from target cells. Experimentally this can be demonstrated by exposing cells to K+-depleting agents such as nigericin, gramicidin, and ouabain, all of which will stimulate the cleavage of pro-IL-1β to its mature form [2] or via the addition of excess KCl (100–130 mM) to cell culture medium which prevents K+ efflux thereby inhibiting NLRP3 activation and IL-1β maturation [4]. One of the most well known activators of NLRP3 is ATP which is released following cellular injury and necrosis and is hence considered a DAMP [5]. Purinergic (P2) receptors sense this extracellular nucleotide triggering pore-formation and the opening of ion channels to elicit a robust inflammatory response [6]. Finally, reactive oxygen species (ROS) generation is intrinsically coupled to inflammasome activation as demonstrated by the finding that ROS scavengers can attenuate IL-1β processing [7]. While there is still controversy surrounding the origin of these ROS, accumulating evidence suggests that they are mitochondrial derived [8, 9]. Protocols to examine events coupled to cell stress and inflammasome activation are described herein, namely (1) measurement of caspase-1 activity using a cleavable, fluorescent caspase-1 substrate (2) western blotting and ELISA measurement of mature, secreted IL-1β, (3) measurement of ATP release from target cells, (4) measurement of ROS production, and (5) measurement of inflammasome-associated cell death.

2 2.1

Materials Cell Treatments

1. Inflammasome activators: ATP (Sigma-Aldrich) and monosodium urate crystals (Invivogen). 2. LPS (Invivogen).

2.2 Caspase-1 Detection

1. FAM-FLICA Caspase-1 Detection Kit (ImmunoChemistry Technologies).

2.3 Western Blotting and ELISA for IL-1β

1. RIPA buffer: 50 mM HEPES, 100 mM NaCl, 1 mM EDTA, 10 % Glycerol, 1 % NP-40. 2. Strataclean Resin for protein extraction from cell supernatants (Agilent Technologies). 3. Laemmli Buffer for protein sample resuspension (BioRad). 4. Chloroform. 5. Methanol. 6. Two 15 % Resolving gels: 7.5 mL of 30 % protogel, 3.4 mL of water, 3.8 mL of 1.5 M Tris–HCl and 150 μL of 10 % SDS. To initiate the polymerization of the acrylamide, add 150 μL of 10 % APS and 6 μL of TEMED. 7. Stacking gel: 670 μL of 30 % protogel, 2.7 mL of water, 500 μL of 1 M Tris–HCl and 40 μL of 10 % SDS. To initiate the

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polymerisation of the acrylamide, add 40 μL of 10 % APS and 6 μL of TEMED. 8. PVDF or nitrocellulose. 9. 5 % desiccated milk or 5 % BSA for membrane blocking. 10. Goat anti-mouse IL-1β polyclonal antibody (R&D Systems, AB-401-NA). 11. HRP conjugated anti-goat IgG (Sigma-Aldrich, A5420). 12. ELISAs to detect mature murine IL-1β are available, for example, from R&D systems (cat #: DY401). 2.4 ATP Measurement

1. The luminescent ATP detection assay (ATPlite) (Perkin Elmer).

2.5 ROS Measurement

1. DCFDA Cellular ROS Detection Assay Kit (Abcam).

2.6 Cell Death Detection

1. Annexin-binding buffer: 10 mM HEPES, 140 mM NaCl, and 2.5 mM CaCl2, pH 7.4. 2. Annexin V, Alexa Fluor® 488 conjugate (Life Technologies). 3. Propidium Iodide (PI) (Sigma Aldrich). 4. LDH Cytotoxicity Assay Kit can be purchased from (Thermo Fisher Scientific).

3

Methods The methods described below have been verified in murine bone marrow-derived macrophages and dendritic cells. Where IL-1β processing and secretion is to be examined, cells must first be primed with LPS (100 ng/mL, ultrapure from E. coli 0111:B4, Invivogen) for at least 3 h in order to drive the production of proIL-1β. LPS also upregulates the expression of NLRP3 and other inflammasome components. For the purpose of this chapter, ATP or monosodium urate crystals are given as examples of standard inflammasome activators; however, these can be substituted with other known and novel activators and inducers of cell stress.

3.1 Analysis of Active Caspase-1 in Macrophages Using a Cleavable Fluorescent Substrate

Reagents used here are part of the FAM-FLICA Caspase-1 Detection Kit. This assay is based on the irreversible binding of a cell permeable fluorescein labeled inhibitor to the active enzyme, which can be detected by fluorescence microscopy; however, we will describe its application in flow cytometry. 1. Seed cells such as BMDM or BMDC in a 24-well plate (500 μL/well) at a density of 1 × 106 per mL the day before carrying out this assay.

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2. Treat cells with ATP (5 mM) for 30 min at 37 ˚C. Priming these cells with LPS does not seem to increase caspase-1 activity in this assay. 3. Detach cells from the base of the wells using a cell scraper and transfer to FACS tubes. 4. Reconstitute FLICA reagent with 50 μL of DMSO to generate a 150× stock solution (see Note 1). Dilute the required amount of 150× stock solution 1:5 in phosphate buffered saline, pH 7.4 immediately prior to use, this will form a 30× stock solution. 5. Add 16 μL of 30× FLICA reagent to ATP treated and untreated cells and incubate for 1 h at 37 °C under 5 % CO2 (Unlabeled ATP treated and untreated cells should be included as additional controls). 6. Centrifuge at μ + 3σ where μ and σ are the blank mean intensity and standard deviation, respectively. Each cell must also be measured for DNA staining, using the same threshold approach for dead cells. Healthy cells will be Annexin-V-/DNA Stain-, apoptotic cells will be Annexin-V+/DNA Stain-, and dead cells (regardless of death mechanism) will be Annexin-V+/DNA Stain+ (Fig. 3).

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Fig. 4 White light (a) and red fluorescence (b) images of Ramos cells induced by 1.75 μg/mL staurosporine for 3 h and stained by 0.2 μM 2SBPO-Casp. Apoptotic cells are easily distinguished from healthy cells by a strong, background-free fluorescence. Reproduced with permission [12] 3.4

Caspase Activity

1. Use staurosporine or anti-CD95 solution to induce apoptosis in positive control cells (see Note 8). 2. Wash, centrifuge at 4,500 × g-force for 5 min, and resuspend cells in PBS. 3. For detection, add 0.2 μM 2SBPO-Casp or L-bisaspartic acid Rhodamine 110 to a 30 μL cell suspension. 4. A fluorescent image of cells incubated with the probe but not induced to become apoptotic should be acquired at each time frame. 5. Fluorescence should be acquired at each time frame of the experiment. Typically measurements every 30 min yield adequate time-based data (Fig. 4).

3.5 Ultrasensitive Caspase Activity

1. Divide sample cell suspension (105–106 cells/mL) into blank, control, and sample aliquots. 2. Wash cell suspension once by centrifugation (1,400 × g for 4 min) and discard the supernatant. Resuspend the cell pellets with equal amounts of growth medium. 3. Add 1.75 μg/mL staurosporine to sample and control cell suspension [4, 5]. 4. Add 1 μL 20 mM Z-VAD-FMK to the control cell suspension, the final concentration of Z-VAD-FMK is 20 μM. 5. Incubate cell suspensions (blank + control + sample) at 37 °C and 5 % CO2 atmosphere for the desired time (see Note 9). 6. Centrifuge cells, discard supernatant, and resuspended in PBS buffer. Repeat process a total of two times (see Note 10). This is a critical step, as the detection system sensitivity is very high.

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7. Place a 30 μL cell sample drop on a microscope coverslip. For caspase probes, add a droplet to the sample to achieve a final concentration of 10 nM. Position a cell in the laser-beam path with the laser shuttered (see Notes 11 and 12). 8. Open the shutter and focus laser beam on the cell. Acquire fluorescence/fluorescence correlation spectroscopy data (Fig. 5). 9. Repeat process with a new cell, measure 15–30 cells per hour up to a 4-h time scale to obtain representative data. 10. Fluorescence autocorrelation is calculated in photon arrival mode using software developed by Rieger and coworkers [3] using a National Instruments counting board (PCI-6022) and software (Labview v8.0). However, other hardware- or software-based correlators will yield similar data. 11. Autocorrelation curves of fluorescence signal are fit with the 3D diffusion model:

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4

Notes 1. For fluorescence readout, a microscope equipped with a suitable excitation source, excitation and emission filter set, and a camera will be capable of conducting these assays. 2. For Annexin-V imaging or flow cytometry, it is important to choose an Annexin-V protein conjugated to a fluorophore suitable for the microscope or flow cytometry fluorescence filters. Annexin-V assays require simultaneous measurement of DNA exclusion, as Annexin-V will label phosphatidyl serine on both the inside and outside of the cell membrane. 3. For fluorescent probes for caspase activity or mitochondrial release, the choices of excitation and emission wavelength are more limited. 4. Typically cell suspension densities should be 105–106 cells/mL for analysis. Suspended cells can be maintained by changing the cell culture medium twice or thrice per week as needed. To maintain adherent cells, remove the cell culture medium and then wash with 10 mL of PBS buffer, followed by incubation with 5 mL trypsin-EDTA in the incubator to detach cells from the extracellular matrix. Once cells have detached, add 5 mL of cell culture medium to quench the trypsin and use the cell suspension as required. 5. The nature of the cell controls used will depend on the experiment needs and application. However, it is generally advisable to have both positive and negative controls. Negative controls would have no induction agent or cell stress present, but would be stained with the fluorescent probes needed for the assay at hand. Positive controls would be incubated with the same probes as well as an induction agent. In our labs, we typically use staurosporine as the positive control for the intrinsic pathway and a functional anti-CD95 antibody as the positive control for the extrinsic pathway. It is important to note that not all cells respond to induction agents equally. Certain cells, such as PC-3 prostate cancer cells, are particularly resistant to apoptosis induction [17].

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6. The amount of medium needed to resuspend cells depends upon the cell concentration needed and how many cells are in the pellet. 7. Emission maxima for probes used: MitoTracker Red (644 nm), MitoTracker Deep Red (655 nm), and MitoTracker Green (516 nm). 8. Not all anti-CD95 antibodies induce apoptosis. Thus check with manufacturer before using anti-CD95. Staurosporine should be handled with special care to avoid accidental exposure. 9. Apoptosis process is monitored in a 4-h time scale. Measurements are taken as early as 15 min after incubation begins, and measure every following hour. 10. The volume of buffer should be adjusted based on the cell concentrations. 11. The laser power should be set to a minimum to detect fluorescence and avoid photobleaching, typically 100–200 μW at the sample using a 100×, 1.4 NA objective, depend on wavelength, dye, cell, etc. [2]. 12. Out of focus alignment will produce reduced autocorrelation and signal.

Acknowledgements The authors acknowledge support from the National Institutes of Health (RR025782 and GM103550). References 1. LaCasse E, Holcik M, Korneluk R, MacKenzie A (2005) Apoptosis in health, disease, and therapy: overview and methodology. In: Holcik M, LaCasse E, MacKenzie A, Korneluk R (eds) Apoptosis in health and disease. Cambridge University Press, Cambridge, pp 1–48 2. King KL, Cidlowski JA (1998) Cell cycle regulation and apoptosis. Annu Rev Physiol 60: 601–617 3. Nagata S (1997) Apoptosis by death factor. Cell 88:355–365 4. Stellar H (1995) Mechanisms and genes of cellular suicide. Science 267:1445–1449 5. Kutuk O, Basaga H (2010) Apoptotic pathways in mitochondria. In: Preedy V (ed) Apoptosis. Science Publishers, Enfield, NH, pp 1–18 6. Vaux DL, Korsmeyer SJ (1999) Cell death in development. Cell 96:245–254

7. Ferlini C, Scambia G (2007) Assay for apoptosis using the mitochondrial probes, Rhodamine 123 and 10-N-nonyl acridine orange. Nat Protoc 2:3111–3114 8. Khanal G, Chung K, Solis-Wever X, Johnson B, Pappas D (2011) Ischemia/reperfusion injury of primary porcine cardiomyocytes in a low-shear microfluidic culture and analysis device. Analyst 136:3519–3526 9. Iyer D, Ray RD, Pappas D (2013) High temporal resolution fluorescence measurements of a mitochondrial dye for detection of early stage apoptosis. Analyst 138:4892–4897 10. Hug H, Los M, Hirt W (1999) Rhodamine 110-linked amino acids and peptides as substrates to measure caspase activity upon apoptosis induction in intact cells. Biochemistry 38:13906–13911 11. Reif R, Aguas C, Martinez M, Pappas D (2010) Temporal dynamics of receptor-induced

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12.

13.

14.

15.

apoptosis in an affinity microdevice. Anal Bioanal Chem 397:3387–3396 Dong M, Martinez M, Mayer M, Pappas D (2012) Single molecule fluorescence correlation spectroscopy of single apoptotic cells using a red-fluorescent caspase probe. Analyst 137: 2997–3003 Qiao Y, Ma LY (2013) Predicting efficacy of cancer cell killing under hypoxic conditions with single cell DNA damage. Anal Chem 85:6953–6957 Darzynkiewicz Z, Galkowski D, Zhao H (2008) Analysis of apoptosis by cytometry using TUNEL assay. Methods 44:250–254 Olive PL, Banath JP (2006) The comet assay: a method to measure DNA damage in individual cells. Nat Protoc 1:23–29

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16. Pappas D (2010) Getting starting (and getting the cells). In: Pappas D (ed) Practical cell analysis. Wiley, New York 17. Gao Y, Li P, Pappas D (2013) A microfluidic localized, multiple cell culture array using vacuum actuated cell seeding: integrated anticancer drug testing. Biomed Microdevices 15:907–915 18. Pappas D (2010) The cell-culture laboratory (tools of the trade). In: Pappas D (ed) Practical cell analysis. Wiley, New York, pp 35–63 19. Pappas D (2010) Microscopy of cells. In: Pappas D (ed) Practical cell analysis. Wiley, New York, pp 89–122 20. Reif R, Martinez MM, Wang K, Pappas D (2009) Simultaneous cell capture and induction of apoptosis using an anti-CD95 affinity microdevice. Anal Bioanal Chem 395:787–795

Part II Studying Cell Stress in the Context of Disease

Chapter 12 Measuring Death of Pancreatic Beta Cells in Response to Stress and Cytotoxic T Cells Jibran A. Wali, Prerak Trivedi, Thomas W. Kay, and Helen E. Thomas Abstract Apoptosis of pancreatic beta cells is a feature of type 1 and type 2 diabetes, although by different effector mechanisms. In type 1 diabetes, beta cells are the targets of cytotoxic CD8+ T cells that kill by releasing the contents of their cytotoxic granules into the immunological synapse with the target beta cell. In type 2 diabetes, the mechanisms of beta cell apoptosis are less clear, but believed to be due to cellular stresses including endoplasmic reticulum stress and oxidative stress induced by chronic exposure to high concentrations of glucose, lipids, inflammatory cytokines, or islet amyloid polypeptide. Measuring apoptosis in primary islets can be more difficult than in a beta cell line because islets exist as a cluster of cells and it is often difficult to obtain sufficient cells for any particular type of assay. Here, we describe two different methods for measuring islet cell apoptosis. The first method is the measurement of DNA fragmentation, a hallmark of apoptosis, of islets that have been cultured with reagents that induce stress. The second method is the measurement of islet lysis by activated cytotoxic T cells. We describe methods using mouse islets, but these can easily be adapted for human islets. Key words Pancreatic islets, Diabetes, Apoptosis, Cytotoxic T lymphocytes, Flow cytometry, ER stress, Oxidative stress, DNA fragmentation, 51Cr cytotoxicity

1

Introduction Diabetes affects over 380 million people worldwide and has significant impact on individuals and their families as well as health care budgets. The pathogenesis of type 1 and type 2 diabetes is complex, with immune abnormalities in type 1 and insulin resistance in type 2 diabetes. However, pancreatic beta cell deficiencies and loss of functional beta cell mass are a feature of both diseases. Type 1 diabetes is caused by immune-mediated destruction of beta cells in the islets of the pancreas, with consequent insulin deficiency. While CD8+ T cells are believed to be the main cytotoxic

Jibran A. Wali and Prerak Trivedi have contributed equally to this Chapter. Christine M. Oslowski (ed.), Stress Responses: Methods and Protocols, Methods in Molecular Biology, vol. 1292, DOI 10.1007/978-1-4939-2522-3_12, © Springer Science+Business Media New York 2015

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mediators of beta cell destruction, CD4+ T cells and macrophages may also cause beta cell death. T cells use a range of cytolytic molecules to kill target cells, including the pore-forming toxin perforin and the granzyme serine proteases, ligands of the death receptors such as Fas Ligand and TNF, and pro-inflammatory cytokines that are toxic to beta cells. Much work has been done to elucidate the roles of these different factors in beta cell killing [1]. Evidence from human pancreas samples suggests that there is a decrease in beta cell mass due to apoptosis in type 2 diabetic subjects [2–4], and that declining beta cell mass may be responsible for the gradual worsening of type 2 diabetes over time. Several mechanisms for beta cell loss have been proposed. These include chronic exposure to hyperglycemia and hyperlipidemia, pancreatic islet amyloid polypeptide (IAPP), and pro-inflammatory cytokines such as IL-1β. These factors induce endoplasmic reticulum (ER) stress and production of reactive oxygen species (ROS) in beta cells that leads to their demise [5]. Studying loss of beta cells is important for understanding the pathogenesis of diabetes. The preservation of beta cell mass would improve glycemic control and reduce the likelihood of developing complications of diabetes, transforming disease outcomes for people with diabetes. To study how beta cells die, we describe two in vitro assays. The first is the measurement of DNA fragmentation in islet cells that have been cultured with reagents that induce cell stress and death. This assay can be used to determine the susceptibility of islets to individual immune or metabolic factors that have been implicated in diabetes development. Here, we describe the use of reagents that induce islet ER and oxidative stress. The second method is a Chromium-51 release cytotoxicity assay, measuring islet cell lysis caused by cytotoxic T lymphocytes (CTL). This assay, specific to immune-mediated killing, can be used to determine the susceptibility of islets to the whole armory of a cytotoxic T cell, as might occur in vivo. It is plausible that data obtained with cell lines may not truly reflect how a beta cell will respond to a certain stimulus because cell lines are transformed and not at an identical differentiation stage, and also cell lines do not fully reflect the mixed cell context of primary islets as found in vivo. Therefore, the assays we describe are performed using primary rodent or human islets, isolated according to published protocols [6]. Apoptosis is characterized by chromatin condensation, nuclear fragmentation, and overall cell shrinkage [7]. Nuclear fragmentation can be detected by distinguishing the sub-G1 (hypodiploid) DNA content from the normal (diploid) DNA content. We have adapted the method developed for studying apoptosis of thymocytes by Nicoletti et al. [8, 9] for the study of primary islet cells [10, 11]. This is a rapid and simple method that utilizes a hypotonic buffer with propidium iodide to stain nuclear DNA, and visualization on the red channel of the flow cytometer. The advantages of this method over common microscopic techniques are that

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it provides quantitative results that limit operator bias, and because >10,000 events per sample are collected, it has improved statistical power. The 51Cr cytotoxicity assay was first described by Brunner et al. in 1968 [12], and has not significantly changed since then. It is based on the measurement of target cell lysis by release of radioactive chromium (51Cr) from pre-labeled cells in the presence of activated CTL. It was found that 90 % of the label could be released from target cells in 6–9 h of incubation with allogeneic CTL. We adapted this method for studying the lysis of mouse or human islets by beta cell antigen-specific CTL [13, 14]. In our description, we use mouse CTL that are specific for the beta cell protein islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP), derived from T cell receptor transgenic NOD8.3 mice developed in the lab of Santamaria [15]. Splenocytes from these mice are easily activated in vitro with specific peptide (IGRP206–214) for use in this assay [14]. However, the assay can easily be adapted for the use of CTL specific for different beta cell antigens or allogeneic CTL [16], or for human CTL [13].

2

Materials

2.1 Measuring Stress-Induced DNA Fragmentation of Islet Cells

1. Complete CMRL culture medium for islets: CMRL medium-1066 (Invitrogen), 100 U/mL penicillin, 100 U/ mL streptomycin, 2 mM glutamine, 10 % v/v fetal calf serum. 2. Trypsin: 342 U/mL bovine trypsin and 20 mM EDTA dissolved in sterile PBS and filtered to sterilize. 3. DNA fragmentation buffer: 0.1 % w/v Triton X-100, 50 μg/ mL propidium iodide, 0.1 % w/v sodium citrate, deionized water. 4. Thapsigargin (Calbiochem, Darmstadt, Germany): dissolve in 100 % ethanol at stock concentration of 2 mmol/L, which can be stored at −20 °C. Use at a final concentration of 5 μmol/L to induce ER stress. 5. Tunicamycin (Sigma-Aldrich, St Louis, MO): dissolve in DMSO at stock concentration of 10 mg/mL and store at −80 °C. Use at a final concentration of 10 μg/mL to induce ER stress. 6. Hydrogen peroxide (Sigma-Aldrich): dilute to a stock concentration of 1 mmol/L in complete CMRL and dilute to a final concentration of 30 μmol/L in islets to induce generalized oxidative stress. Prepare fresh every time. 7. Rotenone (Sigma-Aldrich): dissolve in DMSO at a stock concentration of 50 μmol/L and store at −80 °C. Use at a final concentration of 100 nmol/L to induce mitochondrial oxidative stress.

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8. D-Ribose (Sigma-Aldrich): Dissolve in complete CMRL at a concentration of 1 mol/L and dilute to 50 mmol/L final concentration into cultures. Prepare fresh each time. L-Ribose (Sigma-Aldrich) should be used at the same concentration as an osmolarity control. D-Ribose is a reducing sugar that induces islet ER and oxidative stress. 9. Tauroursodeoxycholic acid (TUDCA, Sigma-Aldrich): dissolve in complete CMRL at 100 mmol/L and dilute to 0.5 mmol/L final concentration into cultures. Prepare fresh each time. This is a chemical chaperone that attenuates ER stress. 10. 4-phenyl butyric acid (PBA, Sigma-Aldrich): dissolve in 0.5 N NaOH at a concentration of 0.5 mol/L then dilute to 2.5 mmol/L final concentration into cultures. Prepare fresh each time. PBA is a chemical chaperone that attenuates ER stress. 11. N-acetylcysteine (NAC, Sigma-Aldrich): Dissolve in complete CMRL at a concentration of 100 mmol/L then dilute into cultures to final concentration of 1 mmol/L. Prepare fresh each time. NAC is a glutathione precursor that inhibits oxidative stress. 12. Q-VD-OPh (Enzyme Systems Products, Livermore, CA): Dissolve in DMSO at a stock concentration of 10 mmol/L and store at −80 °C. Dilute into cultures at final concentration of 50 μmol/L. This is a pan-caspase inhibitor. 13. Flow cytometer for analysis of DNA fragmentation. We use a FACS Calibur or LSR Fortessa (Becton Dickinson, Franklin Lakes, NJ) for acquisition of data. 14. Flow cytometry analysis software such as FlowJo (Tree Star Inc, Ashland, OR). 2.2 T Cell-Mediated Cytotoxicity of Islets

1. Complete CMRL culture medium for islets (cCMRL): CMRL medium-1066 (Invitrogen), 100 U/mL penicillin, 100 U/ mL streptomycin, 2 mM glutamine, 10 % v/v fetal calf serum. 2. Complete RPMI culture medium for T cells (cRPMI): RPMI medium-1640 (Invitrogen), 100 U/mL penicillin, 100 U/ mL streptomycin, 10 % v/v fetal calf serum. 3. One spleen from a NOD/Lt mouse and one from a NOD8.3 mouse [15]. 4. Pancreatic islets isolated from 4 to 6 week old NOD/Lt mice. 5. Recombinant human IL-2 used at a final concentration of 10 U/mL. 6. Chromium-51 Radionuclide, 5 mCi from PerkinElmer, product number NEZ030005MC.

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7. 2 % Triton X-100 made up in deionised H2O. 8. Tri-buffered Ammonium Chloride (TAC) buffer for lysis of red blood cells: dissolve 0.747 g NH4Cl in 95 mL dH2O then add 1.7 mL 1 M Tris (pH 7.5). Adjust pH to 7.2 with HCl and then top up with dH2O to make 100 mL. 9. Ficoll-paque PLUS from GE Healthcare. Product no: 17-1440-02. 10. IGRP206–214 peptide (VYLKTNVFL): prepare IGRP peptide stock at 5 mM in DMSO, then dilute in cRPMI to the working concentration of 1 μmol/L. 11. Splenocytes from NOD/Lt mouse (to use as antigen presenting cells) and from NOD8.3 transgenic mouse (to use as effector T cells).

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3.1 Inducing Islet Stress and Apoptosis

1. After isolation, wash and hand pick islets clean under the dissecting microscope in a 6 cm petri dish containing 4 mL of complete CMRL medium (see Notes 1 and 2). 2. Leave the islets overnight in the incubator at 37 °C with 5 % CO2 for recovery. 3. Next day, count 100 islets of similar sizes for each sample and culture them in 1 mL of complete CMRL in a 3 cm petri dish (see Notes 2 and 3). 4. To induce ER stress, use 5 μM thapsigargin, 10 μg/ml tunicamycin or 50 mM ribose. Attenuate these with the chemical chaperones 2.5 mM PBA or 0.5 mM TUDCA. To induce oxidative stress, use 30 μM H2O2, 100 nM rotenone or 50 mM ribose and use 1 mM NAC to attenuate this stress. 50 μM of the caspase inhibitor Q-VD-OPh can be used to assess the role of caspase activation in islet cell death (see Notes 4 and 5). 5. Place the petri dishes in the incubator (see Note 6). 6. For DNA fragmentation assay, treat whole islets for 4 days with 5 μM thapsigargin or 10 μg/ml tunicamycin, 2 days with 30 μM H2O2 or 100 nM rotenone or 4 days with 50 mM ribose to induce substantial apoptosis (see Note 7).

3.2 Quantification of DNA Fragmentation

1. At the conclusion of islet culture, islets and culture medium containing floating dead cells are collected from the petri dishes into flow cytometry tubes using a plastic transfer pipette. Petri dishes are washed with PBS to collect any residual islets/ cells in the dish and the PBS is transferred to the same flow cytometry tube. 2. Centrifuge islets at 1,000 × g-force for 2 min.

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3. Carefully remove medium (see Note 8). 4. Add 300 μL of trypsin to islets and leave in 37 °C water bath for 5 min. 5. After 5 min, pipette islets and trypsin up and down 3–5 times to disperse islets into single cells. 6. Add 1 mL of complete CMRL to stop the trypsin activity. 7. Centrifuge cells at 1,200 × g-force for 5 min. 8. Pour off supernatant and add 1 mL of complete CMRL to resuspend islet cells. 9. Leave tubes in the incubator at 37 °C for 30 min to allow islet cells to recover. 10. Centrifuge at 1,200 × g-force for 5 min. 11. Pour off supernatant. 12. Add 300 μL of DNA fragmentation buffer to islet cells. 13. Immediately analyze islet cells on a flow cytometer (488 nm laser for excitation) to differentiate between hypodiploid (fragmented) nuclei and diploid (intact) nuclei (see Note 9 and Fig. 1). Set up the flow cytometer with forward scatter (FSC) and side scatter (SSC) on a linear scale so that most of the cells appear in the bottom left-hand corner of the plot. Because islets are a mixture of cell types, there will be cells with higher FSC and SSC, some even off the scale of the plot. This is normal. Set FL-3 (propidium iodide) on a log scale so that a histogram plot of control, untreated islets looks like Fig. 1. Collect 5,000–10,000 events without gating. 14. For analysis, set a region using the FL-3 histogram from a control sample (Fig. 1), and copy this region into the test samples. All events to the left of the diploid peak are considered fragmented nuclei (see Note 9). 3.3 Generation of Activated NOD8.3 T Cells for Cytotoxicity Assay

1. In separate tubes, prepare a single cell suspension of both NOD/Lt and NOD8.3 splenocytes and lyse red blood cells by incubating for 5 min at 37 °C in 5 mL of TAC lysis buffer. 2. Stop the action of TAC lysis buffer after 5 min by adding 5 mL of cRPMI and centrifuge at 1,200 × g-force for 5 min. Discard the supernatant. 3. Wash cells in PBS and centrifuge at 1,200 × g-force for 5 min. Resuspend the cell pellet in 5 mL of cRPMI. Keep NOD8.3 splenocytes on ice while preparing NOD/Lt splenocytes as antigen presenting cells. 4. Irradiate NOD/Lt splenocytes at 2 Gy. 5. Wash two times with PBS as in step 3 and then resuspend in 5 mL of cRPMI.

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DNA fluorescence (FL3) Fig. 1 Example of flow cytometry plots for DNA fragmentation assay. Figure shows examples of forward and side scatter (top plots), FL3/red fluorescence, and forward scatter (middle plots) and FL3 histograms (bottom plots) for control and stressed islet cells. Note position of gates on histogram plots to quantify % DNA fragmentation

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6. Pulse irradiated splenocytes with peptide by incubating 1 mL splenocytes with 1 μmol/L IGRP peptide for 40–45 min at 37 °C. 7. Wash off excess peptide two times with cRPMI. Count cells using a hemocytometer. 8. Transfer 2 × 106 NOD/Lt cells to each well of 6-well plate in 0.5 mL of cRPMI. 9. Add 2 × 107 NOD8.3 splenocytes (prepared in steps 1–3) to each well of the same 6-well plate in 4.5 mL of cRPMI. 10. The final volume should be 5 mL. Mix well after adding cells. 11. Keep cells in culture at 37 °C with 5 % CO2 in air for 2 days. 12. On day 3, remove dead cells using a ficoll gradient. To do this transfer 5 mL of cultured cells to a 10 mL tube, centrifuge at 1,200 × g-force for 5 min and remove supernatant. Add 2 mL of ficoll and overlay 3 mL of cRPMI carefully to make two layers. Centrifuge at 2,000 × g-force for 20 min without break (see Note 10). 13. Collect live cells from the interface, wash two times with PBS as in step 3 then resuspend cells in 5 mL of cRPMI (see Note 10). 14. Culture cells in 5 mL of cRPMI with 10 U/mL IL-2 for 2 days at 37 °C with 5 % CO2 in air. 15. On day 5 examine the cells microscopically. If there are many dead cells (see Note 11) repeat steps 12 and 13 and culture cells for 2 more days. 16. On day 7 cells are ready to be used in a cytotoxicity assay. Before using the cells, repeat steps 12 and 13 to remove dead cells. 17. Count cells using a hemocytometer, resuspend at 2 × 105 cells/100 μL (for 20:1 E:T ratio in cytotoxicity assay) or 1 × 105 cells/100 μL (for 10:1 ratio) in cRPMI. 3.4 Chromium Release Assay

1. Hand pick mouse islets clean under a dissecting microscope and transfer to a 10 mL tube. Place 100–200 islets per tube (see Note 12). 2. Wash islets with 5 mL of cCMRL and resuspend in 200 μL of cCMRL. 3. To load islet with chromium, add 200 μCi 51Cr to islets and incubate for 2 h at 37 °C in 5 % CO2 in air, flicking the tube every 30 min to mix well. Ensure tube is adequately shielded using lead. 4. Wash three times with 10 mL of cCMRL at 1,200 × g-force for 3 min and carefully remove supernatant into radioactive waste container.

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Fig. 2 Layout of 96-well plate for 51Cr cytotoxicity assay. Samples should include islets alone (spontaneous), islets with Triton X-100 (total) and the test wells at E:T ratios of 10:1 and 20:1. Each well should contain 200 μL total volume. Surround the wells with medium only (shaded gray) to prevent them from drying out

5. After final wash, resuspend islets in 3 mL of cCMRL and transfer them into a 6 cm petri dish. 6. Figure 2 shows how to set up the plate for chromium release assay. Perform each treatment and controls in triplicate. 7. Pick 10 islets of equal size in 100 μL of cCMRL per well into a U-bottom 96-well plate. This is the equivalent of 10,000 islet cells/well (see Note 13). 8. Add 100 μL of cRPMI to 100 μL of islets for all wells labeled as spontaneous (without T cells). 9. Add 100 μL of 2 % Triton-X 100 to 100 μL of islets for all wells labeled as total. 10. Add 2 × 105 activated 8.3 T cells (from Subheading 3.3 above) for 20:1 effector to target ratio or 1 × 105 activated 8.3 T cells for 10:1 effector to target (E:T) ratio in the cytotoxicity assay. 100 μL of T cells should be added (see Note 13). 11. The final volume in each well should be 200 μL. Add 200 μL of cRPMI to the wells surrounding the assay wells to prevent them from drying out. 12. Spin plate at 2,000 × g-force for 5 min to pool all the cells together and incubate overnight at 37 °C in 5 % CO2 in air. 13. The next day, spin the plate at 1,200 × g-force for 3 min and carefully remove 100 μL of the supernatant from each well using a 200 μL pipette.

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14. Collect the supernatants into labeled tubes suitable for the gamma radiation counter, and determine the cpm of 51Cr in each sample. 15. Calculate % specific (see Note 14):

51

Cr release using the following formula

cpm ( sample ) - cpm ( spontaneous ) cpm ( total ) - cpm ( spontaneous )

4

´100 0

Notes 1. The percentage of islet cells undergoing apoptosis varies with the quality of islet isolation and age of the mouse at the time of pancreatic harvest. Therefore, when comparing wild-type with knock-out islets, it is important to use age matched mice and perform islet isolation on the same day for each experiment. 2. It is very important to hand pick islets clean and free of any debris. This takes a bit of practice, so inexperienced researchers should hand pick islets through several passages of fresh medium. 3. To make the final volume 1 mL, count islets into 1 mL medium, then swirl islets to center of the dish, remove as much of the medium as possible with a 1 mL pipette tip using the dissecting microscope to ensure islets remain in the petri dish, then immediately add 1 mL medium to the islets in the dish. This also provides islets with an extra wash to ensure all debris is removed before adding apoptotic stimulus. 4. TUDCA, PBA, and NAC can be toxic if used in higher concentrations. The final concentrations indicated were titrated to yield significant inhibition of ribose-induced apoptosis with minimal background toxicity of the reagents. 5. Control samples should have an equal volume of diluent added to culture dishes. 6. To minimize loss of culture medium by evaporation, put the islet dishes in a plastic container made moist by placing wet sterile tissue paper in the bottom before placing petri dishes inside. Make some holes in the container lid to allow ventilation. Place the container in the incubator. 7. The amount of cell death can be assessed during the incubation period by examination of islets microscopically. Typically, islets that are dying have floating cells in the culture, and the edges of the islets are uneven. Healthy islets have clean edges with very few floating cells.

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8. Whole islets do not stick well to the bottom of flow cytometry tubes. It is best to remove the medium using a 1 mL pipette tip, keeping an eye on the pellet to ensure no islets are lost at this step. After the islets are trypsinized to single cells, they stick to the bottom of the tube after centrifugation and the supernatant can be poured off. 9. If the islets have been over-trypsinized or were not hand picked carefully, there can be a lot of cell debris, which appears off the low end of the FL-3 scale. With practice, this can be avoided. If this occurs, set the region slightly above the baseline for FL-3 so as not to count any of this debris in the analysis. 10. It is important to overlay the cRPMI slowly to form a proper layer, otherwise this could result in loss of live cells. After centrifugation, the cells at the interphase form an opaque layer. Carefully collect 4.5 mL with a transfer pipette, leaving 0.5 mL so as not to disturb the pellet. 11. From day 5 onwards, the cells should be microscopically checked daily. Activated cells normally appear pointed, with a tail. Blasting cells are tennis racket-shaped. Dying or dead cells are very small and lose their shape. If there are many dying cells, a ficoll gradient should be performed. 12. After islet isolation, it is important to hand pick the islets to remove any excess pancreatic tissue. It is also important to use islets that are rounded and not losing their shape, because bad quality islets release their 51Cr resulting in a high background. It is also important to only use medium sized islets, all approximately the same size. Use islets from 4 to 6 week old NOD/Lt or NODscid mice that do not have any immune cell infiltration. Always isolate more islets than are required for the assay so that only the good islets are used. 13. Each islet contains approximately 1,000 cells, therefore 10 islets is about 10,000 cells. Therefore for 10:1 effector:target ratio, 1 × 105 T cells are used, and for 20:1 use 2 × 105 T cells. The higher E:T ratio should produce more 51Cr release. 14. The spontaneous lysis (wells with islets only) should have the lowest amount of 51Cr in the supernatant. Islets with 2 % Triton X-100 should have the highest amount of 51Cr because these islets have been lysed (total lysis). Test wells should have cpm in between spontaneous and total.

Acknowledgements The authors would like to thank Dr Nadine L Dudek for originally optimizing the protocol for 51Cr release assays with islets. This work was supported by a project (APP1032610) and a program

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(APP1037321) grant from the National Health and Medical Research Council of Australia (NHMRC), and a NHMRC/Juvenile Diabetes Research Foundation (JDRF) joint special program grant in type 1 diabetes (APP466658). H.E.T. is supported by a fellowship from the NHMRC (APP1042735) and J.A.W. is supported by a University of Melbourne Viola Edith Reid Bequest Scholarship. St Vincent’s Institute is supported in part by the Victorian Government’s Operational Infrastructure Support Program. References 1. Thomas HE, McKenzie MD, Angstetra E, Campbell PD, Kay TW (2009) Beta cell apoptosis in diabetes. Apoptosis 14:1389–1404 2. Butler AE, Janson J, Bonner-Weir S, Ritzel R, Rizza RA, Butler PC (2003) Beta-cell deficit and increased beta-cell apoptosis in humans with type 2 diabetes. Diabetes 52:102–110 3. Rahier J, Guiot Y, Goebbels RM, Sempoux C, Henquin JC (2008) Pancreatic beta-cell mass in European subjects with type 2 diabetes. Diabetes Obes Metab 10(Suppl 4):32–42 4. Yoon KH, Ko SH, Cho JH, Lee JM, Ahn YB, Song KH, Yoo SJ, Kang MI, Cha BY, Lee KW, Son HY, Kang SK, Kim HS, Lee IK, BonnerWeir S (2003) Selective beta-cell loss and alpha-cell expansion in patients with type 2 diabetes mellitus in Korea. J Clin Endocrinol Metab 88:2300–2308 5. Weir GC, Bonner-Weir S (2013) Islet beta cell mass in diabetes and how it relates to function, birth, and death. Ann N Y Acad Sci 1281: 92–105 6. Szot GL, Koudria P, Bluestone JA (2007) Murine pancreatic islet isolation. J Vis Exp 7:255 7. Hotchkiss RS, Strasser A, McDunn JE, Swanson PE (2009) Cell death. N Engl J Med 361:1570–1583 8. Nicoletti I, Migliorati G, Pagliacci MC, Grignani F, Riccardi C (1991) A rapid and simple method for measuring thymocyte apoptosis by propidium iodide staining and flow cytometry. J Immunol Methods 139:271–279 9. Riccardi C, Nicoletti I (2006) Analysis of apoptosis by propidium iodide staining and flow cytometry. Nat Protoc 1:1458–1461 10. McKenzie MD, Carrington EM, Kaufmann T, Strasser A, Huang DC, Kay TW, Allison J, Thomas HE (2008) Proapoptotic BH3-only

11.

12.

13.

14.

15.

16.

protein Bid is essential for death receptorinduced apoptosis of pancreatic beta-cells. Diabetes 57:1284–1292 McKenzie MD, Jamieson E, Jansen ES, Scott CL, Huang DC, Bouillet P, Allison J, Kay TW, Strasser A, Thomas HE (2010) Glucose induces pancreatic islet cell apoptosis that requires the BH3-only proteins Bim and Puma and multi-BH domain protein Bax. Diabetes 59:644–652 Brunner KT, Mauel J, Cerottini JC, Chapuis B (1968) Quantitative assay of the lytic action of immune lymphoid cells on 51-Cr-labelled allogeneic target cells in vitro; inhibition by isoantibody and by drugs. Immunology 14: 181–196 Campbell PD, Estella E, Dudek NL, Jhala G, Thomas HE, Kay TW, Mannering SI (2008) Cytotoxic T-lymphocyte-mediated killing of human pancreatic islet cells in vitro. Hum Immunol 69:543–551 Dudek NL, Thomas HE, Mariana L, Sutherland RM, Allison J, Estella E, Angstetra E, Trapani JA, Santamaria P, Lew AM, Kay TW (2006) Cytotoxic T-cells from T-cell receptor transgenic NOD8.3 mice destroy beta-cells via the perforin and Fas pathways. Diabetes 55:2412–2418 Verdaguer J, Schmidt D, Amrani A, Anderson B, Averill N, Santamaria P (1997) Spontaneous autoimmune diabetes in monoclonal T cell nonobese diabetic mice. J Exp Med 186: 1663–1676 Sutton VR, Estella E, Li C, Chen M, Thomas HE, Kay TW, Trapani JA (2006) A critical role for granzyme B, in addition to perforin and TNFalpha, in alloreactive CTL-induced mouse pancreatic beta cell death. Transplantation 81:146–154

Chapter 13 Adaptation of the Secretory Pathway in Cancer Through IRE1 Signaling Stéphanie Lhomond, Nestor Pallares, Kim Barroso, Kathleen Schmit, Nicolas Dejeans, Hélèna Fazli, Saïd Taouji, John B. Patterson, and Eric Chevet Abstract The unfolded protein response (UPR) was originally identified as a signaling network coordinating adaptive and apoptotic responses to accumulation of unfolded proteins in the endoplasmic reticulum (ER). More recent work has shown that UPR signaling can be triggered by a multitude of cellular events and that the UPR plays a critical role in the prevention of cell transformation but also in tumor development. This has been particularly well illustrated with studies on one of the three major ER stress sensors, IRE1. This ER resident type I transmembrane protein senses luminal ER stress and transduce signals through its cytosolic RNase activity. IRE1 signaling has been shown to contribute to the progression of solid tumors through pro-angiogenic mechanisms. Herein, we expose the methodologies for investigating IRE1 signaling in tumor cells and in tumors. Moreover, we show that selective pharmacological inhibition of IRE1 RNase activity sensitizes tumor cells to ER stress. Key words Endoplasmic reticulum, Unfolded protein response, IRE1, ERN1, XBP1, IRE1 inhibitors

1

Introduction Twenty-five years ago, the existence of a signaling pathway was identified in mammalian cells to control adaptation to protein folding defect. This occurs through the transcriptional upregulation of key ER chaperones [1] mediated by three classes of ER stress sensors, namely, Inositol-requiring enzyme-1 (IRE1, α and β isoforms), activating transcription factor 6 (ATF6) (α and β isoforms) and protein kinase RNA-like ER kinase (PERK) [2]. PERK activation also involves its dimerization and auto-transphosphorylation [3, 4]. Activated PERK phosphorylates the translation initiator factor eIF2α, inhibiting protein synthesis, and nuclear factor erythroid 2-related factor 2 (NRF2), a transcription factor involved in redox metabolism [5]. This reduces the load of newly synthesized

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proteins entering the ER, thus having an important pro-survival effect [6]. Phosphorylation of eIF2α limits the amount of active ribosomes and allows the translation of mRNAs containing short open reading frames (micro-ORFs) in their 5′-untranslated regions, including Activating Transcription Factor-4 (ATF4). ATF4 controls the expression of genes involved in redox and amino acid metabolism, in addition to ER chaperones and foldases [7, 8]. ATF4 also regulates the expression of important genes involved in apoptosis including the transcription factor C/EBP-homologous protein (CHOP) and growth arrest and DNA damage-inducible-34 (GADD34) (see above). GADD34 participates on a feedback loop to dephosphorylate eIF2α by interacting with protein phosphatase 1C (PP1C), restoring protein synthesis [9]. Finally, ATF6α is a type-II ER located protein that contains a bZIP transcription on its cytosolic domain. Upon ER stress ATF6α translocates to the Golgi apparatus where it is cleaved by S1P and S2P proteases to release a cytosolic fragment (ATF6c) [10, 11]. ATF6c is a transcription factor that regulates the expression of genes of the ERAD pathway among other target genes [12, 13]. Exclusive or combined action of ATF6c and XBP1s may also have a differential effect on gene expression [14]. Activation of IRE1α involves its oligomerization, and autotransphosphorylation, leading to a conformational change that activates the RNase domain. IRE1α RNAse excises a 26-nucleotide intron of the X-Box binding protein-1 (XBP1) encoding mRNA, which is then religated by a yet unknown RNA ligase. This changes the coding reading frame of the mRNA, leading to the expression of an active transcription factor, termed XBP1s, for the spliced form [12, 15, 16]. XBP1s trans-activates a subset of target genes involved in protein folding, endoplasmic reticulum-associated degradation (ERAD), protein translocation to the ER, and protein secretion [17, 18] (Fig. 1). IRE1α also signals through the scaffolding of many adapter proteins and regulators, a dynamic protein platform referred to as the UPRosome [5] (Fig. 1). IRE1α interacts with the adapter protein TRAF2, leading to the downstream activation of the kinase JNK [19]. IRE1α RNase activity also degrades a subset of mRNA through a process known as regulated IRE1-dependent decay of mRNA (RIDD) [20–22] (Fig. 1). The pool of RNAs degraded by RIDD depends on the cell type affected and targets mRNAs encoding for proteins of the secretory pathway. The selectivity of IRE1α to degrade particular RIDD substrates may depend on the presence of a conserved nucleotide sequence accompanied by a defined secondary structure [20–23]. Moreover, IRE1α has also been shown to cleave premature microRNAs thereby impacting on the control of apoptosis [24]. Furthermore, the regulation of IRE1α expression levels by microRNAs was shown to impact on its biological functions [25–27].

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Fig. 1 Schematic representation of IRE1 signaling. Upon accumulation of misfolded proteins in the ER, BiP is titered away from IRE1 leading to IRE1 oligomerization and downstream signaling. Three major signaling pathways are activated downstream of IRE1 including the activation of the JNK cascade, the unconventional splicing of XBP1 mRNA and the regulated IRE1 dependent decay of mRNA (RIDD)

The role of IRE1 in cancer has been well documented [28–30]. In particular, we have shown that in glioblastoma IRE1 activity contributes to tumor growth through the activation of pro-angiogenic and pro-inflammatory pathways [28, 31], thereby indicating that IRE1 could represent a potentially relevant therapeutic target in this disease. Herein, we list the methodologies used in our laboratory to investigate and pharmacologically perturb IRE1 [32] signaling in glioblastoma cells.

2

Materials

2.1 Cell Lines and Mouse Strains

1. Human glioblastoma derived cells U87MG were from ATCC.

2.2

1. Mouse monoclonal antibodies against XBP1s (clones 2G4 and 5E4) were produced in-house and respectively used for immunohistochemistry and immunoblotting.

Antibodies

2. RagGamma mice were produced in the Bordeaux 1 University animal house (Dir. R. Pineau).

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2. Rabbit antisera to JNK1 (SantaCruz, CA, USA), anti phosphoJNK (Cell Signaling Technology, Danvers, MA, USA) 3. Rabbit antisera to IRE1 (SantaCruz, CA, USA), rabbit monoclonal antibodies to phospho-IRE1 (S724) (Abcam, Cambridge, MA, USA). 4. Vimentin (dil. 1/400) (Acris Antibodies, Herford, Germany) 5. CD31 (dil. 1/200) (BD Pharmingen, Franklin Lakes, NJ, USA) 6. Secondary antibodies: Alexa 547 (FluoProbes 547H Donkey Anti-Rat IGG FP-SB6110) 1/200, Alexa 488 (FluoProbes 488H Donkey Anti-Mouse IGG FP-5A4110) 1/200 or EnVision FLEX/HRP (Dako F8010/F8012/F8024). 7. Hoechst ((Molecular Probes 34580) 1/1,000). 2.3 PCR Primers and siRNAs

1. RT-PCR: hPer1 Fwd, 5′-GGGTCCTCCAGTGATAGCAA-3′; Rev, 5′-GAGGAGGAGGCACATTTACG-3′ (amplicon length: 386 bp). 2. RT-PCR: hGapdh Fwd, 5′-ACCACCATGGAGAAGGCT GG-3′; Rev, 5′-CTCAGTGTAGCCCAGGATGC-3′ (amplicon length: 528 bp). 3. RT-PCR: hPer2, Fwd, 5′-TACGCTGGCCACCTTGAAG TA-3′; Rev, 5′-CACATCGTGAGGCGCCAGGA-3′ (amplicon length: 386 bp). 4. siRNA: GL2, 5′-CGUACGCGGAAUACUUCGA-3′; Ire1α, 5′-UUACUGGCUUCUGAUAGGA-3′; Xbp1, 5′-CUCAU GGCCUUGUAGUUGA-3′. 5. qPCR: hPER2, Fwd, 5′-TACGCTGGCCACCTTGAAGTA-3′; Rev, 5′-CACATCGTGAGGCGCCAGGA-3′. 6. qPCR: hPER1, Fwd, 5′-TATACCCTGGAGGAGCTGGA-3′; Rev, 5′-AGGAAGGAGACAGCCACTGA-3′. 7. qPCR: 18S, Fwd, 5′-GGATCCATTGGAGGGCAAGT-3′; Rev, 5′-CCGCTCCCAAGATCCAACTA8. qPCR: miR-17, Fwd, 5′-CAAAGUGCUUACAGUGCAGG UAG-3′; Rev, universal primer provided in the miScript SYBR Green PCR Kit (Qiagen, Ref: 218073).

2.4

Chemicals

1. IRE1 inhibitors: irestatin (Axon Medchem, Vienna, VA, USA), toyocamycin (Sigma-Aldrich, St Louis, MO, USA), and MKC8866 (labeled MKC; MannKind Corporation, WO 2011/127070 A2) [33]. 2. Tunicamycin (Calbiochem, Merck KGaA, Darmstadt, Germany). 3. Acrylamide–Bis-acrylamide 30:1 (Bio-Rad, Hercules, CA, USA). 4. SDS (Thermo Fisher Scientific, Waltham, MA, USA).

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2.5 SDS-PAGE and Phos-tag SDSPAGE Gel Components

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1. 1.5 M Tris–HCl solution, pH 8.8 (4× solution for resolving gel): add about 100 mL of distilled water to a 1 L graduated cylinder or a glass beaker. Weigh 181.7 g of Tris and transfer to the cylinder. Add distilled water to a volume of 900 mL. Mix and adjust pH with HCl. Make up to 1 L with distilled water. Filter the solution. Store at 4 °C in the dark. 2. 0.5 M Tris–HCl solution, pH 6.8 (4× solution for stacking gel): add about 100 mL of distilled water to a 1-L graduated cylinder or a glass beaker. Weigh 60.6 g of Tris and transfer to the cylinder. Add distilled water to a volume of 900 mL. Mix and adjust pH with HCl. Make up to 1 L with distilled water. Store at 4 °C. 3. 10 % (w/v) SDS solution: add about 100 mL of distilled water to a 1-L graduated cylinder or a glass beaker. Weigh 100 g of SDS and transfer to the cylinder. Add distilled water to a volume of 1 L. Store at room temperature. 4. 5.0 mM Phos-tag solution containing 3 % (v/v) methanol: add 0.1 mL of methanol to the oily product Phos-tag AAL-107 plastic tube (Wako Cat. No. 304-93525). Dilute the methanol solution with 3.2 mL of distilled water by pipetting. Wrap the tube with aluminum foil. Keep the solution in 2-mL microtubes at 4 °C in the dark. 5. 10 mM MnCl2 solution: add about 50 mL of distilled water to a 500-mL graduated cylinder or a glass beaker. Weigh 0.10 g of MnCl2•4H2O (MW: 198) and transfer to the cylinder. Add distilled water to a volume of 500 mL. Mix and store at room temperature. 6. 10 % (w/v) ammonium persulfate solution: weigh 500 mg of (NH4)2S2O8 (MW: 228) and transfer to a 15 mL conical flask. Add distilled water to a volume of 5 mL. Mix and aliquot in 2-mL microtubes placed at −20 °C for long-term storage. 7. 30 % acrylamide–Bis solution (29.2:0.8 acrylamide–Bis) (BioRad, Hercules, CA, USA). Store at 4 °C. 8. N, N, N, N′-tetramethyl-ethylenediamine (TEMED) (Sigma Chemical Company, St. Louis, MO, USA). Store at 4 °C. 9. Running buffer, pH 8.3 (10× solution): add about 100 mL distilled water to a 1-L graduated glass beaker. Weigh 30.2 g of Tris, 10.0 g of SDS, and 144 g of glycine and transfer to the glass beaker. Add distilled water to a volume of 500 mL. Vortex to pre-dissolve Tris, SDS, and glycine, then add distilled water to a volume of 900 mL. Mix and adjust pH to 8.3. Make up to 1 L with distilled water. Store at room temperature. 10. Sample buffer (3× solution): add about 1 mL of distilled water to a 10-mL graduated cylinder. Weigh 1.5 mg of bromophenol blue and 0.60 g of SDS and transfer to the cylinder. Add 3 mL

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of glycerol and 3.9 mL of solution b (0.5 M Tris–HCl solution, pH 6.8). Add distilled water to a volume of 8.5 mL. Mix and aliquot in 2-mL microtubes placed at −20 °C for long-term storage. Just before use, thaw the sample buffer and add 15 % of 2-mercaptoethanol. 2.6 Immunoblotting Components

1. PVDF membranes (Millipore, Darmstadt, Germany). 2. Western blot transfer buffer: 0.025 M Tris, 0.192 M glycine and 10 % methanol. 3. Phosphate-buffered saline (PBS; 10×): 1.5 M NaCl, 0.1 M Tris–HCl, pH 7.4. 4. PBST: TBS containing 0.1 % Tween 20. 5. Blocking solution: 3 % bovine serum albumin (BSA) in PBS. Store at 4 °C. 6. Diluent solution: 5 % BSA in PBST. Store at 4 °C. 7. Mini PROTEAN® 3 System glass plates (catalog number 1653311) (Bio-Rad); medium binder clips (1¼ in.); plastic container. 8. Wypall X-60 reinforced paper (Kimberly-Clark, Neenah, WI, USA).

2.7 RNA Extraction and RT-PCR 2.7.1 RNA Extraction

1. TRIzol® Reagent (life technologies, Ref: 15596026). 2. Chloroform (Sigma-Aldrich, Ref: C2432), Isopropanol (Carlo Erba, Ref: 415156). 3. Ethanol 75 %.

2.7.2 Reverse Transcription

1. Nuclease-free water. 2. Random Hexamer 100 pmol (Thermo Scientific, Ref: SO142). 3. dNTP Mix, 10 mM each (Thermo Scientific, Ref: R0191). 4. 5× RT Buffer (Thermo Scientific, Ref: EP074). 5. Ribolock™ RNase Inhibitor (Thermo Scientific, Ref: EO0381). 6. Maxima® Reverse Transcriptase (200 U/μL) (Thermo Scientific, Ref: EP0741). 7. miScript II RT Kit (Qiagen, Ref: 218160).

2.7.3 PCR Amplification

1. 10× PCR Buffer minus MgCl2 (Life technologies, Ref: 18067-017). 2. 50 mM MgCl2 (Life technologies, Ref: 18067-017). 3. 200 U/μL Taq DNA Polymerase (Life technologies, Ref: 10342-053). 4. dNTP Mix,10 mM each (Life technologies, Ref: 18427013). 5. miScript SYBR Green PCR Kit (Qiagen, Ref: 218073).

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1. Agarose (UltraPure™ Agarose, Ref: 16500-100). 2. Tris base, acetic acid and EDTA buffer (TAE) (Sigma-Aldrich, Ref: T9650). 3. UltraPure™ 10 mg/mL Ethidium Bromide used at 0.5 μg/ mL (Life technologies, 15585-011). 4. Loading dye 5× (Qiagen, Ref: 1037649).

2.8 Plasmid Transduction

1. Lentiviral particles containing pCDH lentivector (System Biosciences). 2. U87-MG cells. 3. DMEM medium (Life technologies, Ref: 11570586).

2.9 Immunohistochemistry 2.9.1 CD31 and Vimentin Staining

1. CD31 Rat Anti-Mouse (dil. 1/200) (BD Pharmingen, 550274). 2. Vimentin Mouse (dil.1/400) (Acris BM5050P). 3. Hoechst (Invitrogen 34580). 4. Secondary antibody Alexa 488 (Interchim, FP-SA4110). 5. Secondary antibody Alexa 547 (Interchim). 6. PFA (Electron Microscopy Sciences 15710). 7. Albumin from bovine serum (SIGMA A2153). 8. Mounting medium (Interchim, FP-483331 FluoroMount-G).

2.9.2 H and E

1. Harris Haematoxylin (RAL Diagnostics 361070-2500). 2. Eosin (Sigma-Aldrich E4009). 3. Mounting medium (HistoLab 00811).

2.9.3 XBP1s Staining

1. Mouse anti-XBP1s antibodies were made in-house. 2. EnVision FLEX/HRP (Dako DM822). 3. EnVision FLEX SUBTRATE BUFFER (Dako DM823). 4. EnVision FLEX DAB + CHROMOGEN (Dako DM827). 5. Triton (SIGMA T5;830-0). 6. Albumin from bovine serum (SIGMA A2153). 7. Harris Haematoxylin (RAL Diagnostics 361070-2500). 8. Mounting medium (HistoLab 00811).

3 3.1

Methods Immunoblot

1. Resolve samples by SDS-PAGE and transfer onto PVDF membranes (EMD Millipore, Billerica, MA, USA) using liquid transfer for 40 min at 30 V using and the transfer buffer: 25 mM Tris–HCl, 192 mM glycine pH 8.8.

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2. Wash membranes with distilled water and incubate with Ponceau S (0.1 % (x/v) Ponceau S in 1 % (v/v) acetic acid) for 5 min prior to extensive washing with distilled water. Block membranes with PBS, 0.1 % Tween 20 (PBST), and 3 % (w/v) bovine serum albumin for 45 min at room temperature. 3. Dilute primary antibodies with PBST at the appropriate dilution (see Subheading 2.2) and incubate with the membrane overnight at 4 °C. 4. Wash membranes 5× 5–10 min with PBST prior to incubating with HRP-conjugated secondary antibodies (dil. 1/5,000) for 45 min at room temperature. 5. Wash membranes with PBST 5× 5–10 min (Figs. 2 and 3). 6. Incubate membranes with chemoluminescent reagent (KPL, Gaithersburg, MD, USA) as recommended by the manufacturer and expose to X-ray films. Quantify bands with ImageJ software (NIH). 3.2 Phos-tag Analysis

Carry out all procedures at room temperature unless otherwise specified (see Note 1). 1. Prepare the resolving gel by mixing 2.5 mL of resolving buffer, 3.33 mL of acrylamide mixture, 4 μL of Phos-tag solution, 100 μL of MnCl2 solution, and 3.87 mL of distilled water in a 50 mL conical flask. Add 100 μL of SDS, 50 μL of ammonium persulfate, and 10 μL of TEMED, and cast gel within a 7.25 cm × 10 cm × 1.5 mm gel cassette. Allow space for stacking the gel and gently overlay with isobutanol or water. 2. Prepare the stacking gel by mixing 2.5 mL of resolving buffer, 1.5 mL of acrylamide mixture, and 5.84 mL water in a 50 mL conical flask. Add 100 μL of SDS, 50 μL of ammonium persulfate, and 10 μL of TEMED. Insert a 10-well gel comb immediately without introducing air bubbles. 3. Sample preparation and electrophoresis: Plate U87MG cells onto 6-well plates (200,000 cells/well). 24 h post seeding, treat cells with tunicamycin (5 μg/mL) or vehicle (DMSO) for 6 h. Lyse cells in RIPA buffer with protease and phosphatase inhibitors (Roche, Basel, Switzerland). Mix 12 μL cell lysate samples (around 30 μg total proteins) with 6 μL of 2-mercaptoethanol containing sample buffer. Heat at 95 °C for 5 min and centrifuge the heated samples at 3,000 × g for 30 s to bring down the condensate. Load 18 μL of each sample or 5 μL of protein standard in the gel. Electrophoresis should be performed at 10–15 mA until the dye front (from the bromophenol blue dye in the samples) has reached the bottom of the gel. 4. Following electrophoresis, pry the gel plates open with the use of a spatula. The gel remains on one of the glass plates. Remove

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Fig. 2 IRE1 phosphorylation analysis. (a) Schematic representation of Phos-tag–p-IRE1 interaction. (b) Schematic representation of the Phos-tag analysis protocol. (c) IRE1 phosphorylation analysis using Phos-tag. U87 cells were lysed and protein samples were resolved by SDS-PAGE and Phos-tag. Following transfer onto PVDF membranes, IRE1 and p-IRE1 are visualized by immunoblot with anti-IRE1 antibodies. (d) IRE1 phosphorylation analysis by immunoblotting using anti p-IRE1 (S724). U87 cells were lysed and protein samples were immunoprecipitated with anti-IRE1 antibodies. Immunoprecipitates were resolved by SDS-PAGE, transferred onto PVDF and immunoblotted with anti-p-IRE1 or anti-IRE1 antibodies

the stacking gel. Rinse the gel twice with a general transfer buffer containing 10 mM EDTA for a minimum of 10 min with gentle agitation, to eliminate the manganese ions (Mn2+) from the gel. Transfer carefully to a container with western blot transfer buffer without EDTA for 10 min. 5. Cut a PVDF membrane to the size of the gel and immerse in methanol. Rinse twice in distilled water and once with transfer buffer. Samples are transferred onto PVDF membranes using liquid transfer for 3 h at 10 V at 4 °C using the transfer buffer. Wash membranes with distilled water and incubate with Ponceau S (0.1 % (x/v) Ponceau S in 1 % (v/v) acetic acid) for

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5 min prior to extensive washing with distilled water. Block membranes using PBS, 0.1 % Tween 20, and 3 % (w/v) bovine serum albumin for 45 min at room temperature (Fig. 2). 3.3 RT-PCR for XBP1 mRNA Splicing 3.3.1 mRNA Extraction

mRNA extraction should be performed in a RNase-free environment. 1. After stress, remove medium from the wells and wash cells with PBS. 2. Add 1 mL of TRIzol® Reagent for 10 min in each well. Lyse the cells directly in the wells by pipetting the cells up and down several times. 3. Transfer each extract in a clean 1.5 mL tube and add 200 μL of chloroform. 4. Vortex the tubes vigorously for 15 s. Incubate for 2–3 min at room temperature. 5. Centrifuge the samples at 12,000 × g for 15 min at 4 °C. Remove the aqueous phase of the sample by angling the tube at 45° and

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pipetting the solution out. Avoid drawing any of the interphase or organic layer into the pipette when removing the aqueous phase. Place the aqueous phase (about 0.4 mL) into a new tube. 6. Add 0.4 mL of isopropanol to the aqueous phase. Incubate at −80 °C for 1 h or at −20 °C overnight. 7. Centrifuge at 12,000 × g for 10 min at 4 °C. Remove the supernatant from the tube, leaving only the RNA pellet. 8. Wash the pellet, with 1 mL of 75 % ethanol. Vortex the sample briefly, then centrifuge the tube at 7,500 × g for 5 min at 4 °C. Discard the wash. 9. Vacuum-dry or air-dry the RNA pellet for 5–10 min. Do not dry the pellet by vacuum centrifuge. 10. Resuspend the RNA pellet in 20 μL of RNase-free water at 4 °C for 20 min. 11. After homogenization, dose the RNA at 260 nm. Check the 260/230 and 260/280 ratios for protein contaminant. 3.3.2 Reverse Transcription

1. In a clean 200 μL tube, use 1 μg of RNA as template for the reaction, then add the following reaction components (manufacturer protocol, Thermo Scientific): 1 μL Random Hexamer, 1 μL dNTP Mix 10 mM, 4 μL 5× RT Buffer, 0.5 μL Ribolock™ Rnase Inhibitor, 1 μL Maxima® Reverse Transcriptase Complete with RNase-free Water to 20 μL. 2. Start with 10 min at 25 °C followed by 30 min at 50 °C and terminate the reaction by heating at 85 °C for 5 min.

3.3.3 XBP1 Splicing Polymerase Chain Reaction

PCR reaction should be performed in a DNA-free environment. Use of “clean” dedicated automatic pipettors and aerosol resistant barrier tips are recommended. 1. In a clean 200 μL tube, use 1–2 μL from the RT-PCR reaction mix as template for the reaction, then add the following reaction components (manufacturer protocol, life technologies): 0.3 μM Forward primer, 0.3 μM Reverse primer, 5 μL 10× Buffer minus MgCl2, 2 μL MgCl2 (50 mM), 0.5 μL Taq DNA Polymerase, 1 μL dNTP Mix 10 mM, nuclease-free water to 50 μL. 2. PCR program: initial denaturation step start at 95 °C for 10 min, followed by 40 cycles of: 30 s denaturation step at 95 °C, 45 s annealing step at 60 °C and 45 s elongation step at 72 °C. The PCR reaction was finalized by 10 min elongation at 72 °C.

3.3.4 Agarose Gel Electrophoresis

1. Cast a 4 % agarose gel containing 0.5 μg/mL ethidium bromide in TAE buffer. 2. Mix 10 μL of PCR reaction with 2.5 μL of 5× loading dye.

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3. Load the mix onto the gel and set the power supply at 100 V for 2 h. 4. Observe the result under UV light, prolong the migration time if the Xbp1 unspliced and Xbp1 spliced forms are not separated enough (Fig. 3). 3.4 Measuring RIDD Activation 3.4.1 IRE1 mRNA Decay

This protocol was designed to measure the RIDD activation of IRE1 in U87MG human cells and can be used to evaluate IRE1 mRNA decay activity regulators (see Note 3). 1. Incubate 300,000 cells by well in 4 wells of a 6-well plate, 48 h before siRNA transfection. 2. Transfect Cells by using the siRNAi Max Lipofectamine reagent (Invitrogen Corp.). Briefly, for each siRNA, dilute 9 μl of RNAiMAX Reagent in 150 μL of Opti-MEM® Medium (Life technologies) and 30 pmol of siRNA in 150 μL of OptiMEM® Medium. Add the diluted siRNA to diluted Lipofectamine® RNAiMAX and incubate for 5 min at room temperature. Add 250 μl of this solution to the cells and incubate for 2–4 days. 3. RNA extraction, reverse transcription and PCR—Perform these steps as described in Subheading 3.3.1, except for the PCR program. Samples were denatured for 10 min at 95 °C, then cycled for 30 cycles (denaturation: 95 °C, 30 s; annealing: 62 °C, 30 s; elongation: 72 °C, 45 s) and then subjected to a final elongation of 10 min at 72 °C. 4. Resolve PCR products on 2 % agarose gels. 5. Quantify the bands using the ImageJ software (NIH). Normalize by dividing the PERIOD1 and PERIOD2 signal to the signal of the GAPDH. Normalization of each biological replicate can be performed by dividing the values by the mean of all values of the corresponding experiment or by dividing each value by the control (Fig. 3).

3.4.2 IRE1 miRNA Decay

1. Seed 200,000 cells by well in a 6-well plate, 48 h before RNA extraction. If a treatment is required, adjust the time according to the duration of treatment. Briefly, for each sample, dilute drugs in DMEM Medium (Life technologies) for the appropriate concentration and incubate until RNA extraction. 2. RNA extraction is performed as described in Subheading 3.3.1. 3. miRNA are specifically reverse transcribed using the miScript II RT kit (Qiagen). In a clean 200 μL tube, use 500 ng of total RNA as template for the reaction, then add the following reaction components (manufacturer protocol, Qiagen): 4 μL 5× miScript HiSpec Buffer, 2 μL 10× miScript Nucleics Mix, 2 μL miScript Reverse Transcriptase Mix and complete with

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RNase-free water to 20 μL. Incubate for 60 min at 37 °C followed by 5 min at 95 °C to inactivate miScript Reverse Transcriptase Mix. 4. SYBR-based Quantitative PCR: in a clean 200 μL tube, use 1–2 μL from the RT reaction mix as template for the reaction, then add the following reaction components (manufacturer protocol, Qiagen): 12.5 μL 2× QuantiTect SYBR Green PCR Master Mix, 2.5 μL 10× miScript Universal Primer, 2.5 μL 10× miScript Primer assay and complete with nuclease-free water to 25 μL. Samples were denatured for 15 min at 95 °C, then cycled for 40 cycles (denaturation: 94 °C, 15 s; annealing: 55 °C, 30 s; elongation: 70 °C, 30 s). 5. Quantification of miRNA by Delta Ct analysis and normalization of each biological replicate can be performed with RNA U6B. 3.5 Immunohistochemistry for Vimentin/CD31 and XBP1s 3.5.1 Tissue Preparation

The entire process for Vimentin and CD31 staining is performed at room temperature in a moist chamber (see Note 4).

1. Dry the sheets for 15 min. 2. Fix the tissue with PAF 4 %: 10 mL Formaldehyde 16 % (Electron Microscopy Sciences 15710) plus 30 mL of PBS 1×. 3. Wash with 1× PBS for 5 min. Do this process 3 times. 4. Permeabilize with PBS with Triton 0.1 % for 1 h (Triton 100 %—1 mL in 1 L of PBS 1×). 5. Wash with 1× PBS 3 times for 5 min.

3.5.2 Blocking and Antibody Reaction (Immunofluorescence)

1. Mark the area around the tissue with a Dako Pen (Dako 52002). 2. Saturate with PBS BSA 5 % for 1 h (1 L PBS 1× plus 50 mg of albumin from bovine serum (Sigma 96 %)). Wash with PBS for 5 min, 3 times. 3. Primary antibody: PBS BSA 1 % with Anti-Vimentin 1/400 (Mouse IgG1) (Acris BM5050P) for 1 h. 4. Wash with 1× PBS 3 times for 5 min. 5. Secondary antibody: PBS BSA 1 % with Alexa 488 (FluoProbes 488 Donkey Anti-Mouse IGG FP-5A4110), at a 1/200 dilution for 30 min. 6. Wash with 1× PBS for 5 min 3 times. 7. Primary antibody: PBS BSA 1 % with CD31 Purified Rat AntiMouse 1/200 (BD Pharmingen, 550274) for 1 h. 8. Wash with 1× PBS for 5 min 3 times.

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9. Secondary antibody: PBS BSA 1 % with Alexa 547 (FluoProbes 547 Donkey Anti-Rat IGG FP-SB6110) (dilution 1/200) with Hoechst (PBS BSA 1 % + Hoechst (1/1,000)) for 30 min. 10. Wash with 1× PBS 3 times for 5 min. 11. Mount with 100 μL of glue Interchim (FP-483331 FluoroMount-G Four immunofluorescent) and one coverglass (RS France Coverglass 24 × 60 mm 0.13–0.17 mm). 3.5.3 Antibody Reaction (HRP)

1. Primary antibody: PBS BSA 1 % with Monoclonal XBPIs IgG1 Mouse for 2 h. 2. Wash with 1× PBS 3 times for 5 min. 3. Secondary antibody: EnVision FLEX/HRP (Dako K8010/ K8012/K8024) for 30 min. 4. Wash with PBS 1× 5 min. Do this 3 times. 5. Reveal with EnVision FLEX DAB + CHROMOGEN (Dako K8010/K8012/K8024). 6. Wash with distilled water for 5 min. Stain with hemalun for 3 min. 7. Wash with running water for 5 min. 8. Wash with distilled water and three drops of NH3. 9. Dehydrate by increasing battery graduation alcohol and toluene. 10. Mount with 100 μL of mounting medium (PERTEX HistoLab F/00811) and a coverglass (RS France Coverglass 24 × 60 mm 0.13–0.17 mm) (Fig. 4).

4

Notes 1. For Phos-tag analysis gels must be run at rather low voltage (10–15 mA/gel) to allow better resolution and sharp bands (Fig. 2c). For the detection of IRE1 ser724 phosphorylation using the phosphospecific antibodies, it is better to immunoprecipitate IRE1 (following cell lysis with RIPA buffer containing protease and phosphatase inhibitors (Complete and PhosSTOP; Roche, Basel, Switzerland)) overnight at 4 °C. Immunoprecipitates are then resolved by SDS-PAGE and transferred onto PVDF membranes prior to immunoblotting using anti p-IRE1 antibodies (Fig. 2d). 2. For quantifying the increase in XBP1s expression by immunoblot (Fig. 3b), the amount of basal and ER stress-induced XBP1s should be investigated in preliminary experiments and depend on the cell lines/tissues to be analyzed. Several cell lines exhibit strong basal XBP1s such as Hela cells or human hepatoma HuH7 cells.

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Fig. 4 Orthotopic glioblastoma model in the mouse. (a) Schematic representation of the orthotopic graft injection of U87MG cells into immunocompromised mice. (b) Following injection of U87 cells and 2–3 weeks, mouse brains were collected and preserved. Sections were performed and staining with H and E, anti-XBP1s antibodies (revealed using HRP-conjugated secondary antibodies), anti-Vimentin, anti-CD31 (revealed with fluorescently labeled secondary antibodies). T tumoral; NT nontumoral (see Note 5)

3. RIDD activity: Note that if you intend to validate the ability of IRE1 to cleave an mRNA upon stress, it is necessary to block the transcriptional regulation of potential substrates in order to validate their posttranscriptional regulation by IRE1. Furthermore, in this protocol the degradation of PERIOD1 mRNA was used as a marker of IRE1 endoribonuclease basal activation [31] (Fig. 3). Depending of the cell type, and the expression level of PERIOD1, it could be necessary to use another previously identified substrate of IRE1 mRNA decay activity, such as GPC3 [27] or SPARC [34]. The siIRE1 is used as a positive control of IRE1 modulation and PERIOD2 mRNA, a non-target of IRE1, as a negative control. The siGL2 represents a control unspecific siRNA. The siXBP1 is used to confirm that the regulation of the IRE1 mRNA target is not due to transcriptional regulation mediated by XBP1.

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Fig. 5 Impact of IRE1 inhibition on U87 cells sensitivity to tunicamycin-induced ER stress. (a) Impact of toyocamycin, irestatin, and MKC8866 (labeled MKC) on XBP1 mRNA splicing activity. The concentrations used are indicated in the figure. XBP1 mRNA splicing activity was evaluated in control U87 cells and in U87 cells stably overexpressing wild-type IRE1, a situation sufficient for IRE1 activation. (b) Toxicity of toyocamycin, irestatin, and MKC8866 (labeled MKC) as assessed using sulforhodamine-B staining and increasing concentrations of the compounds. (c) Synergistic effects of MKC8866 and tunicamycin on toxicity in U87 cells (see Note 6)

4. For immunohistochemistry experiments, all the solutions are prepared extemporaneously and conserved fresh. Hematoxylin can be used several times but the incubation time must increase with recycled solutions. Finally, the volume of each solution necessary for each slide (Dakopen-delimited area) is of about 300 μL. 5. For xenografts, cells must be resuspended in 100 μL (1.5 mL tubes) or 50 μL (round bottom tubes) in order for the syringe used for injection to homogenize properly the cell suspension and collect 1 μL/brain for injection. Injecting more than 10,000 cells is not necessary. 6. For inhibition of IRE1 activity, treatment with the inhibitors must be performed 48 h ahead of the treatment with tunicamycin at sub-toxic doses. In our experimental conditions and using our experimental model, only MKC was found to have an effect on cell sensitization to tunicamycin-induced death (Fig. 5).

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Acknowledgements This work was funded by grants from INSERM, Institut National du Cancer (INCa), La Ligue Contre le Cancer to EC. S.L. was supported by a PhD scholarship from the French government, and N.D. was supported by a postdoctoral fellowship from the Fondation de France. References 1. Kozutsumi Y, Segal M, Normington K, Gething MJ, Sambrook J (1988) The presence of malfolded proteins in the endoplasmic reticulum signals the induction of glucoseregulated proteins. Nature 332:462–464 2. Walter P, Ron D (2011) The unfolded protein response: from stress pathway to homeostatic regulation. Science 334:1081–1086 3. Kimata Y, Kohno K (2011) Endoplasmic reticulum stress-sensing mechanisms in yeast and mammalian cells. Curr Opin Cell Biol 23:135–142 4. Bertolotti A, Zhang Y, Hendershot LM, Harding HP, Ron D (2000) Dynamic interaction of BiP and ER stress transducers in the unfolded-protein response. Nat Cell Biol 2:326–332 5. Hetz C (2012) The unfolded protein response: controlling cell fate decisions under ER stress and beyond. Nat Rev Mol Cell Biol 13:89–102 6. Harding HP, Novoa I, Zhang Y, Zeng H, Wek R, Schapira M et al (2000) Regulated translation initiation controls stress-induced gene expression in mammalian cells. Mol Cell 6:1099–1108 7. Harding HP, Zhang Y, Zeng H, Novoa I, Lu PD, Calfon M et al (2003) An integrated stress response regulates amino acid metabolism and resistance to oxidative stress. Mol Cell 11:619–633 8. Lerner AG, Upton JP, Praveen PV, Ghosh R, Nakagawa Y, Igbaria A et al (2012) IRE1alpha induces thioredoxin-interacting protein to activate the NLRP3 inflammasome and promote programmed cell death under irremediable ER stress. Cell Metab 16:250–264 9. Novoa I, Zeng H, Harding HP, Ron D (2001) Feedback inhibition of the unfolded protein response by GADD34-mediated dephosphorylation of eIF2alpha. J Cell Biol 153:1011–1022 10. Haze K, Yoshida H, Yanagi H, Yura T, Mori K (1999) Mammalian transcription factor ATF6 is synthesized as a transmembrane protein and

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12.

13.

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15.

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activated by proteolysis in response to endoplasmic reticulum stress. Mol Biol Cell 10:3787–3799 Asada R, Kanemoto S, Kondo S, Saito A, Imaizumi K (2011) The signalling from endoplasmic reticulum-resident bZIP transcription factors involved in diverse cellular physiology. J Biochem 149:507–518 Lee K, Tirasophon W, Shen X, Michalak M, Prywes R, Okada T et al (2002) IRE1mediated unconventional mRNA splicing and S2P-mediated ATF6 cleavage merge to regulate XBP1 in signaling the unfolded protein response. Genes Dev 16:452–466 Yamamoto K, Sato T, Matsui T, Sato M, Okada T, Yoshida H et al (2007) Transcriptional induction of mammalian ER quality control proteins is mediated by single or combined action of ATF6alpha and XBP1. Dev Cell 13:365–376 Shoulders MD, Ryno LM, Genereux JC, Moresco JJ, Tu PG, Wu C et al (2013) Stressindependent activation of XBP1s and/or ATF6 reveals three functionally diverse ER proteostasis environments. Cell Rep 3(4):1279–1292 Calfon M, Zeng H, Urano F, Till JH, Hubbard SR, Harding HP et al (2002) IRE1 couples endoplasmic reticulum load to secretory capacity by processing the XBP-1 mRNA. Nature 415:92–96 Yoshida H, Matsui T, Yamamoto A, Okada T, Mori K (2001) XBP1 mRNA is induced by ATF6 and spliced by IRE1 in response to ER stress to produce a highly active transcription factor. Cell 107:881–891 Acosta-Alvear D, Zhou Y, Blais A, Tsikitis M, Lents NH, Arias C et al (2007) XBP1 controls diverse cell type- and condition-specific transcriptional regulatory networks. Mol Cell 27:53–66 Lee A-H, Iwakoshi NN, Glimcher LH (2003) XBP-1 regulates a subset of endoplasmic reticulum resident chaperone genes in the unfolded protein response. Mol Cell Biol 23:7448–7459

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19. Urano F, Wang X, Bertolotti A, Zhang Y, Chung P, Harding HP et al (2000) Coupling of stress in the ER to activation of JNK protein kinases by transmembrane protein kinase IRE1. Science 287:664–666 20. Han D, Lerner AG, Vande Walle L, Upton J-P, Xu W, Hagen A et al (2009) IRE1alpha kinase activation modes control alternate endoribonuclease outputs to determine divergent cell fates. Cell 138:562–575 21. Hollien J, Lin JH, Li H, Stevens N, Walter P, Weissman JS (2009) Regulated Ire1dependent decay of messenger RNAs in mammalian cells. J Cell Biol 186:323–331 22. Hollien J, Weissman JS (2006) Decay of endoplasmic reticulum-localized mRNAs during the unfolded protein response. Science 313:104–107 23. Oikawa D, Tokuda M, Hosoda A, Iwawaki T (2010) Identification of a consensus element recognized and cleaved by IRE1 alpha. Nucleic Acids Res 38:6265–6273 24. Upton JP, Wang L, Han D, Wang ES, Huskey NE, Lim L et al (2012) IRE1alpha cleaves select microRNAs during ER stress to derepress translation of proapoptotic Caspase-2. Science 338:818–822 25. Dai BH, Geng L, Wang Y, Sui CJ, Xie F, Shen RX et al (2013) microRNA-199a-5p protects hepatocytes from bile acid-induced sustained endoplasmic reticulum stress. Cell Death Dis 4:e604 26. Maurel M, Chevet E (2013) Endoplasmic reticulum stress signaling: the microRNA connection. Am J Physiol Cell Physiol 304:C1117–C1126 27. Maurel M, Dejeans N, Taouji S, Chevet E, Grosset CF (2013) MicroRNA-1291-mediated

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silencing of IRE1alpha enhances Glypican-3 expression. RNA 19:778–788 Auf G, Jabouille A, Guerit S, Pineau R, Delugin M, Bouchecareilh M et al (2010) Inositol-requiring enzyme 1alpha is a key regulator of angiogenesis and invasion in malignant glioma. Proc Natl Acad Sci U S A 107: 15553–15558 Drogat B, Auguste P, Nguyen DT, Bouchecareilh M, Pineau R, Nalbantoglu J et al (2007) IRE1 signaling is essential for ischemia-induced vascular endothelial growth factor-A expression and contributes to angiogenesis and tumor growth in vivo. Cancer Res 67:6700–6707 Moenner M, Pluquet O, Bouchecareilh M, Chevet E (2007) Integrated endoplasmic reticulum stress responses in cancer. Cancer Res 67:10631–10634 Pluquet O, Dejeans N, Bouchecareilh M, Lhomond S, Pineau R, Higa A et al (2013) Posttranscriptional regulation of PER1 underlies the oncogenic function of IREalpha. Cancer Res 73:4732–4743 Hetz C, Chevet E, Harding HP (2013) Targeting the unfolded protein response in disease. Nat Rev Drug Discov 12:703–719 Volkmann K, Lucas JL, Vuga D, Wang X, Brumm D, Stiles C et al (2011) Potent and selective inhibitors of the inositol-requiring enzyme 1 endoribonuclease. J Biol Chem 286:12743–12755 Dejeans N, Pluquet O, Lhomond S, Grise F, Bouchecareilh M, Juin A et al (2012) Autocrine control of glioma cells adhesion and migration through IRE1alpha-mediated cleavage of SPARC mRNA. J Cell Sci 125:4278–4287

Chapter 14 Studying Nitrosative Stress in Parkinson’s Disease Kenny K.K. Chung Abstract Parkinson’s disease (PD) is marked by a selective degeneration of dopaminergic neurons in the brain stem and it is the second most common neurodegenerative disorder. The pathogenic mechanism of PD is not completely known but it is believed that oxidative stress involving the imbalance of nitric oxide (NO) signaling is involved. Recent studies have suggested that NO, through the modification of protein’s cysteine residues can contribute to the pathogenesis of PD. This NO modification, designated as S-nitrosylation, is emerging as an important signaling mechanism that regulates increasing number of cellular processes such as vesicle trafficking, receptor mediated signal transduction, gene transcription, and cell death. In our studies, we found that increased nitrosative stress promotes the S-nitrosylation of neuroprotective proteins and compromises their function which contributes to the development of PD. One of the obstacles in studying S-nitrosylation signaling is how to detect this modification in biological samples. Here, two simple and commonly used methods in detecting S-nitrosylated proteins are introduced for the study of this NO signaling mechanism. Key words Parkinson’s disease, Oxidative stress, Nitric oxide, S-nitrosylation, Nitrosothiols

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Introduction Parkinson’s disease (PD) is a common neurodegenerative disorder caused by the degeneration of dopaminergic neurons in the brain stem in associated with the presence of intraneuronal protein aggregates designated as Lewy bodies (LBs). Because this group of neurons is involved in the control of movement, patients suffering from this disorder will develop a number of characteristic posture and movement impairment. Beside, some patients will also develop psychiatric complication. The cause of the dopaminergic neuronal degeneration in PD is not known but it is believed to involve multiple pathways. For instance, protein aggregation, mitochondrial dysfunction, and increased oxidative stress have been shown to be the major contributors to the pathogenesis of PD. Oxidative stress has long been regarded as a major factor in PD as studies have shown that the presence of activated glial cells in association with the increased expression of inducible nitric oxide synthase (iNOS)

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is commonly observed in PD patients. In animal models of PD, reduction of NO production by deletion of iNOS or inhibition of neuronal nitric oxide synthase (NOS) has shown to protect dopaminergic neurons against neurotoxin [1, 2]. Previous studies have suggested that NO can combine with free radicals such as superoxide to form peroxynitrite which can damage cellular proteins and DNA and cause cell death [3]. In recent studies, a novel mechanism has been shown how NO can contribute to neurodegeneration through the modification of neuroprotective proteins through S-nitrosylation [4, 5]. S-nitrosylation is a reversible attachment of NO to the cysteine residues on proteins and increasing number of pathways have been shown to be modulated by this signaling mechanism [4, 5]. For instance, proteins that are involved in vesicle trafficking, receptor mediated signal transduction, gene transcription, and cell death have been shown to regulate by S-nitrosylation. S-nitrosylated proteins are designated as nitrosothiols and one of the most common nitrosothiols is the S-nitrosoglutathione (GSNO). One of the obstacles in the study of S-nitrosylation signaling is the detection of this modification in proteins. There are several well-established methods that can analyze S-nitrosylation but some of them might involve expensive equipments or numerous positive and negative controls are needed to confirm the presence of nitrosothiols. For instance, photolysis and chemical-released chemiluminescence can accurately measure the amount of nitrosothiols in biological samples but a custom-made or expensive system is needed [6–8]. AntiS-nitrosocysteine antibody is available in some company but as the antibody can easily cross-react with cysteine residues, proper positive and negative controls will be needed [9]. Here, two widely used approaches to detect S-ntirosylation are introduced in which we have successfully employed to study how S-nitrosylation contributes to the pathogenesis of PD [10, 11].

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Materials All chemicals are from Sigma-Aldrich (St. Louis, MO) unless otherwise stated.

2.1 Colorimetric and Fluorometric Detection of Nitrosothiols

1. Chemicals: NaNO2, glutathione (GSH), NaOH, HgCl2, dimethyl sulfoxide (DMSO), N-(1-Naphthyl)ethylenediamine dihydrochloride (NEDD), sulfanilamide (SULF), 2,3-diaminonaphthalene (DAN), BCA protein assay kit (Thermo Scientific). 2. Griess reagent (57 mM SULF & 1.2 mM NEDD in PBS) is prepared fresh by dissolving 0.25 g of SULF and 7.5 mg of NEDD in 25 mL of PBS.

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3. 10 mM HgCl2 stock solution is prepared by dissolving HgCl2 in DMSO. 4. 10 mM DAN stock solution is prepared by dissolving DAN in DMSO. 5. GSNO is prepared fresh by mixing equal volume of 100 mM GSH and 100 mM NaNO2 with HCl in a final concentration of 75 mM for 10 min at room temperature in darkness. The mixture is then neutralized with NaOH and GSNO is precipitated twice by prechilled acetone. GSNO can then be dissolved in Milli-Q H2O and the concentration is determined by the extinction coefficients (900 M−1 cm−1) at 334 nm. Alternatively, GSNO can also be purchased from Calbiochem. 2.2 Biotin Switch Assay to Label Nitrosothiols

1. Chemicals: HEPES, NaNO2, glutathione (GSH), NaOH, HgCl2, dimethyl sulfoxide (DMSO), neocuproine, methanethiosulfonate (MMTS) (Thermo Scientific), biotin-HPDP (Thermo Scientific), ascorbate, dimethylformamide (DMF), spin columns (Bio-Rad), NeutrAvidin agarose (Thermo Scientific), BCA protein assay kit (Thermo Scientific). 2. HENS buffer: 250 mM HEPES–NaOH pH 7.7, 1 mM EDTA, 0.1 mM neocuproine, 1 % sodium doecylsulfate (SDS) prepared with Milli-Q H2O. 3. 4 mM Biotin-HPDP stock solution is prepared by dissolving biotin-HPDP in DMF.

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Methods

3.1 Colorimetric and Fluorometric Detection of Nitrosothiols

3.1.1 Colorimetric Detection of Nitrosothiols

Colorimetric and fluorometric methods are the most commonly used approaches to detect nitrosothiols in biological samples. The assays usually involve the use of metal ions such as Hg2+ or Cu2+ to induce the release of NO from the nitrosothiols. The released reactive NO will then react with chemicals to produce colored or fluorescent compound, which can be measured by spectrophotometer or spectrofluorometer (Fig. 1). 1. Prepare desired concentrations of GSNO standard (e.g., 5–100 μM) and samples in PBS. 2. Aliquot equal volume of samples or standards and mix them with the Griess reagent in the presence of 100 μM HgCl2 and incubate the mixture at room temperature for 30 min (see Note 1). 3. Measure the absorbance of the reaction mixtures at 496 nm using a spectrophotometer. 4. Calculate the concentration of nitrosothiols in the samples using the standard curve established by the GSNO standard (see Note 2).

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Fig. 1 Conversion of DAN to fluorometric NAT by reaction with NO. NO released from nitrosothiols by Hg2+ will react with DAN in the presence of oxygen to form NAT. The amount of NAT formed can be detected by spectrofluorometer with excitation at 375 nm and emission at 450 nm 3.1.2 Fluorometric Detection of Nitrosothiols

1. Prepare desired concentrations of GSNO standard (e.g., 100 nM–100 μM) and samples are first prepared in PBS. 2. Add DAN and HgCl2 from stock solutions to the standards or samples to the final concentration of 300 μM (DAN) and 100 μM (HgCl2) respectively and incubated at room temperature for 1 h in darkness (see Note 1). 3. Measure the amount of 2,3-napththyltrazole (NAT) formed by the reaction between released NO and DAN by a spectrofluorometer with excitation at 375 nm and emission at 450 nm. 4. Calculate the concentration of the nitrosothiols in the samples using the standard curve established by the GSNO standard (see Note 2).

3.2 Biotin Switch Assay to Label Nitrosothiols

3.2.1 In Vitro Detection of S-Nitrosylation

Biotin switch assay was developed a decade ago in which through a number of treatment, label the S-nitrosylated cysteine residue with biotin [12]. The assay involves first blocking free cysteine by MMTS and then releases the NO by ascorbate treatment. The previously S-nitrosylated cysteine residue is then labeled with biotin by biotin-HPDP treatment (Fig. 2). After the labeling with biotin, the previously S-nitrosylated proteins can be detected by Western blot or subject to mass spectrometry analysis. 1. Prepare samples (see Note 3) in HENS buffer and then incubated with 100 μM of GSH or GSNO for 20 min in darkness at room temperature.

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Fig. 2 Schematic diagram showing steps involved in labeling S-nitrosylated cysteine residue by the biotin switch assay. Free cysteine residue is first blocked by MMTS and the S-nitrosylated cysteine is then reduced by ascorbate. The previously S-nitrosylated cysteine is then labeled with biotin. The biotinylated samples can then be purified by the NeutrAvidin agarose and analyzed by Western blot for protein of interest

2. Remove GSH or GSNO in the samples by passing through the spin column. 3. Incubate samples with MMTS (4 mM final concentration) at 50 °C for 25 min. 4. Remove the MMTS by precipitating the samples with ten volume of −20 °C acetone and resuspend the samples in HENS buffer. 5. Label S-nitrosylated cysteine residue by incubating samples with 0.5 mM biotin-HPDP and 10 mM ascorbate for 1 h at room temperature with rotation. 6. Remove biotin-HPDP in the samples by spin column. 7. Add 50 μL of NeutrAvidin agarose to the samples and incubate at room temperature with rotation for 1 h to pull down the biotinylated proteins. 8. Pellet the NeutrAvidin agarose by centrifugation and wash the beads five times with HENS buffer.

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9. Elute the proteins from the NeutrAvidin agarose with reducing SDS-PAGE buffer. 10. Analysis the elute samples with Western blot for protein of interest. 3.2.2 In Vivo Detection of S-Nitrosylation

1. Prepare samples (see Note 3) in HENS buffer with 4 mM MMTS and incubate samples at 50 °C for 25 min. 2. Follow items 4–10 in Subheading 2.2 (see Note 4).

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Notes 1. While in all the assays introduced, Hg2+ is used to release NO from S-nitrosylated proteins, Cu2+ can also be used, but it is less effective than Hg2+. However, in some situations, this might be desired as it can be used to distinguish the strength of NO–cys bond in the nitrosothiols. 2. For the colorimetric and fluorometric detection of nitrosothiols, special consideration will be needed if the samples are colored or have fluoresces as that might interfere with the measurement. In general, the fluorometric method is more sensitive and can detect nitrosothiols at 50 nM level [13] but colorimetric method is simpler and requires only a spectrophotometer. 3. Samples can be purified proteins, cell lysates, or tissue homogenates. For colorimetric and fluorometric detection of nitrosothiols, cell lysates or tissue homogenates can be prepared in PBS with a suitable concentration of a detergent (e.g., 0.1–1 % Triton). The lysates or homogenates are then cleared by centrifugation at 12,000 × g for 20 min and the supernatant is analyzed accordingly. If needed, the protein concentration of the samples can be determined by the BCA protein assay kit (Thermo Scientific). For the biotin switch assay to label nitrosothiols, samples are prepared similarly except HENS buffer is used instead of PBS. 4. For the detection of in vivo S-nitrosylation by biotin switch assay, negative controls can be established by including samples that omit either ascorbate or biotin-HPDP treatment.

Acknowledgements This work was supported by Hong Kong Research Grants Council Theme-based Research Scheme (T13-607/12R), HKUST10/ CRF/12R and DAG12SC03S.

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References 1. Liberatore GT, Jackson-Lewis V, Vukosavic S et al (1999) Inducible nitric oxide synthase stimulates dopaminergic neurodegeneration in the MPTP model of Parkinson disease. Nat Med 5:1403–1409 2. Przedborski S, Jackson-Lewis V, Yokoyama R et al (1996) Role of neuronal nitric oxide in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced dopaminergic neurotoxicity. Proc Natl Acad Sci U S A 93:4565–4571 3. Tsang AH, Chung KK (2009) Oxidative and nitrosative stress in Parkinson’s disease. Biochim Biophys Acta 1792:643–650 4. Chung KK (2010) Modulation of pro-survival proteins by S-nitrosylation: implications for neurodegeneration. Apoptosis 15:1364–1370 5. Chung KK, David KK (2010) Emerging roles of nitric oxide in neurodegeneration. Nitric Oxide 22:290–295 6. Foster MW, Stamler JS (2004) New insights into protein S-nitrosylation. Mitochondria as a model system. J Biol Chem 279: 25891–25897 7. Stamler JS, Jaraki O, Osborne J et al (1992) Nitric oxide circulates in mammalian plasma primarily as an S-nitroso adduct of serum

8.

9.

10.

11.

12.

13.

albumin. Proc Natl Acad Sci U S A 89: 7674–7677 Yang BK, Vivas EX, Reiter CD et al (2003) Methodologies for the sensitive and specific measurement of S-nitrosothiols, iron-nitrosyls, and nitrite in biological samples. Free Radic Res 37:1–10 Gow AJ, Chen Q, Hess DT et al (2002) Basal and stimulated protein S-nitrosylation in multiple cell types and tissues. J Biol Chem 277:9637–9640 Chung KK, Thomas B, Li X et al (2004) S-nitrosylation of parkin regulates ubiquitination and compromises parkin’s protective function. Science 304:1328–1331 Tsang AH, Lee YI, Ko HS et al (2009) S-nitrosylation of XIAP compromises neuronal survival in Parkinson’s disease. Proc Natl Acad Sci U S A 106:4900–4905 Jaffrey SR, Snyder SH (2001) The biotin switch method for the detection of S-nitrosylated proteins. Sci STKE 2001:PL1 Cook JA, Kim SY, Teague D et al (1996) Convenient colorimetric and fluorometric assays for S-nitrosothiols. Anal Biochem 238: 150–158

Part III Perspectives

Chapter 15 Cross Talk Between ER Stress, Oxidative Stress, and Inflammation in Health and Disease Aditya Dandekar, Roberto Mendez, and Kezhong Zhang Abstract In mammals, endoplasmic reticulum (ER) stress, oxidative stress, and inflammatory responses compose the major defense networks that help the cells adapt to and survive stress conditions caused by biochemical, physiological and pathological stimuli. However, chronic ER stress, oxidative stress, or inflammation have been found to be associated with the initiation and progression of a variety of human diseases in the modern world. Under many pathophysiologic conditions, ER stress response, oxidative stress, and inflammatory responses are integrated and amplified in specialized cell types to facilitate the progression of disease. In the past few decades, ER stress response, oxidative stress, and inflammation as well as their interactive relationships have been hot research topics in biomedicine. In this review, we summarize the recent advance in our understanding of the cross talk between ER stress response, oxidative stress, and inflammation in immunity and in inflammatory and metabolic diseases. Key words ER stress, Unfolded protein response, Oxidative stress, Inflammation, Immunity, Inflammatory disease

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Introduction The endoplasmic reticulum (ER) is an organelle responsible for folding of secreted and membrane-bound proteins [1, 2]. In order to properly fold and assemble these proteins, the ER maintains an optimized environment and a high-fidelity control system to ensure only correctly folded proteins are secreted out of the ER. The oxidizing environment provided by the ER facilitates proper functioning of molecular chaperones and enzymes involved in posttranslational modification, folding, and oligomerization [1, 3, 4]. In the ER, unfolded or misfolded proteins are detected and retained until they are properly folded or degraded. An increase in secreted and membrane-embedded protein translation or a decrease in protein folding capacity can result in a buildup of unfolded or misfolded proteins in the ER lumen, a condition known as ER stress. In response to ER stress, the ER has evolved highly specific

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signaling pathways termed Unfolded Protein Response (UPR). The UPR alleviates ER stress by increasing protein folding capacity, decreasing protein translation rate, and degrading unfolded and misfolded proteins. The canonical UPR signaling is initiated by activation of three ER membrane-bound transducers: Inositol Requiring Enzyme 1 (IRE1), Activating Transcription Factor 6 (ATF6), and Double-Stranded RNA-Activated Protein Kinase-like ER kinase (PERK). Through transcriptional and translational reprogramming, the UPR attempts to help stressed cells adapt to and survive from ER stress conditions. However, in the event that protein folding homeostasis cannot be achieved in the ER, the UPR initiates programmed cell death signaling. 1.1 IRE1-Mediated UPR Signaling

IRE1α is the most conserved UPR transducer that possesses both Ser/Thr kinase and endoribonuclease activities. Under ER stress condition, IRE1α is homo-dimerized and auto-phosphorylated to render its RNase activity. Activated IRE1α catalyzes a nonconventional splicing of the mRNA encoding X-box binding protein 1 (XBP1). The activated XBP1 protein, encoded by the spliced XBP1 mRNA, functions as a potent transcription factor that activates expression of a number of ER chaperones and enzymes to promote protein folding, secretion of correctly folded proteins, and degradation of misfolded proteins [5, 6]. In addition to activating XBP1, IRE1α can also induce the degradation of certain mRNAs or microRNAs, a process known as Regulated IRE1-dependent Decay (RIDD) [7–9]. The physiological significance of RIDD was first explored in insect cells, where it was postulated to be a mechanism to reduce ER stress by limiting the entry of cargo proteins to the ER, given the preferential degradation of mRNAs encoding secretory proteins by RIDD [7]. Recently, increasing evidence suggest that IRE1α regulates a variety of cell physiologies, including metabolism, immunity, cell differentiation, and apoptosis, through the RIDD mechanism [9–16].

1.2 PERK-Mediated UPR Signaling

Under ER stress conditions, PERK phosphorylates eukaryotic translation initiation factor 2 alpha (eIF2α), which attenuates protein translation in a general manner [17]. The suppressed protein translation reduces protein folding burden of the ER. However, under chronic or severe ER stress, PERK-mediated phosphorylation of eIF2α leads to translation of selective mRNAs. In mammals, phosphorylated eIF2α can mediate translation of activating trans-activator 4 (ATF4), which induces expression of a proapoptotic factor CHOP/GADD153, leading to ER stress-induced apoptosis. Under ER stress, ATF4 can also induce expression of the growth arrest and DNA damage-inducible protein GADD34 [18, 19]. GADD34 interacts with the catalytic subunit of type 1 protein serine/threonine phosphatase (PP1) to dephosphorylate eIF2α, providing a negative feedback regulation in the PERK/ eIF2α UPR pathway.

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1.3 ATF6-Mediated UPR Signaling

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Under ER stress conditions, the ER membrane-bound ATF6 is translocated to the Golgi apparatus [20]. In the Golgi, the cytosolic domain of the protein is cleaved by the site-1 and site-2 proteases, the same enzymes that process the sterol-responsive binding element proteins (SREBPs) [21]. Activated ATF6 functions as a transcription factor that plays partially redundant roles of XBP1 in facilitating protein folding and secretion as well as degradation of misfolded proteins [22, 23]. In recent years, the scope and consequences of the UPR have been significantly expanded [24]. A variety of pathophysiologic stimuli, environmental stress, and even lifestyles can directly or indirectly induce ER stress and activate the same UPR pathways induced by biochemical or pharmacological drugs. Increasing evidence indicate that physiological or pathological stress stimuli, independent of unfolded or misfolded proteins, can also activate the UPR transducers, leading to physiological UPR signaling to modulate cell function and survival [24, 25].

Integration of ER Stress and Oxidative Stress Responses Cross talk between ER stress and oxidative stress is evidenced in many physiological and pathological conditions [24] (Fig. 1). The formation of disulfide bonds in ER resident proteins is driven by the enzymes protein disulfide isomerase (PDI) and ER oxidase 1α (ERO1) [26–28]. PDI accepts electrons from protein-folding substrates, thereby oxidizing the thiol group in protein cysteine residues resulting in the formation of disulfide bonds. ERO1 mediates the transfer of electrons from PDI to molecular oxygen, leading to the production of reactive oxygen species (ROS). ROS, produced from the ER or other sources, can target the ER calcium channels, leading to ER calcium release. Ca2+ released from the ER is taken up by the mitochondria, which stimulates mitochondrial metabolism and production of ROS. During ER stress, CHOP regulates expression of ERO1α, which can stimulate inositol-1,4,5trisphosphate receptor (IP3R)-mediated Ca2+ release from the ER [29, 30]. The ER and mitochondria are physically and functionally connected through mitochondria-associated ER membranes (MAMs), which are vital for regulating Ca2+ uptake into the mitochondrial matrix [31]. The major Ca2+ channels including IP3R and the voltage-dependent anion channel (VDAC) are enriched in MAMs. It was suggested that the ER stress sensor PERK is associated with MAMs, where it functions to maintain the ER-mitochondria juxtaposition and promote mitochondrial stress upon oxidative stress [32]. A real-world example for the integration of ER stress and oxidative stress is airborne particulate matter (PM)-induced stress response in the liver [33]. Recent research demonstrated that

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Fig. 1 Illustration of integration between ER stress and oxidative stress response. IP3R inositol-1,4,5-trisphosphate receptor, MAM mitochondria-associated ER membrane

inhalation exposure of mice to environmentally relevant PM in fine ranges (PM2.5) induces ER stress and activation of PERK, leading to phosphorylation of eIF2α and induction of CHOP. Activation of PERK-mediated UPR triggered by PM2.5 can be suppressed by inhibition of ROS production from mitochondria and NAPDH. Interestingly, PM2.5 exposure can activate IRE1α and IRE1α-mediated RIDD, but not IRE1α-mediated Xbp1 mRNA splicing in the liver [33].

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UPR Signaling in Immunity Immune cells release cytokines, antimicrobial peptides, and free radicals in response to cellular infection, damage, and stress pathways. The UPR is actively involved in proper functioning of the immune system. The primary UPR transducer IRE1α is activated to confer immunity against bacterial infection by binding a portion of cholera toxin [11]. The inflammatory response, mediated through IRE1α, depends on the RNase activity of IRE1α in degrading endogenous mRNA, but not splicing Xbp1 mRNA.

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The IRE1α RNase activity engages retinoic-acid inducible gene 1 (RIG-I) to induce NF-κB and interferon pathways [11]. Additionally, Brucellamelitenis infection is known to modulate the ER around the nucleus. Brucella infection in macrophages triggers the UPR signaling pathway [34]. Simultaneously, it stimulates TLR2, TLR4, and TLR6 [35–37]. IRE1α-mediated UPR plays an important role in dendritic cells (DC) maturation. Loss of XBP1 represses the major histocompatibility complex (MHC) and CD80 expression. XBP1 deficiency in DC also affects the ability of DC to induce T cell proliferation [12, 38]. The IRE1α-XBP1 pathway of UPR signaling is exclusively involved in B cell-mediated antibody secretion [39]. The defect of the IRE1-XBP1 pathway in DC activates RIDD, which leads to cleavage of mRNAs, including those encoding CD18 integrins and components of MHC class I machinery [12, 40]. The UPR has been shown to be involved in T cell differentiation and activation. IRE1α is activated during thymic T cell development and in CD8+ effector and CD4+ helper T cell activation [41–43]. Stress response factors are upregulated in differentiated Th2 cells, and the UPR mediator eIF2α plays an important role in regulating the translation of IL-4 in Th2 cells [44]. IRE1α promotes cytokine IL-4 production by stabilizing IL4 mRNA in CD4+ T cells [43]. Treatment of T cells with the IRE1α-specific inhibitor 4u8c can repress IL4, IL5, and IL13 production, thus confirming the role of IRE1α in the regulation of IL-4 in T cells. All the UPR pathways are activated in T cells stimulated with phytohemagglutinin [45]. CD8+ T cells need a functional IRE1-XBP1 pathway for antiviral immune response.

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UPR in Inflammatory Cytokine Production The IRE1α branch of the UPR is an important regulator of inflammatory cytokines in endothelial cells, macrophages, and lymphocytes under pathophysiological conditions. Oxidized phospholipids induce ER stress and UPR activation in human aortic endothelial cells and in human atherosclerotic lesions [46]. Through gene targeting and pharmacological approaches, the UPR transcriptional activator XBP1 was found to be essential for optimal expression of the genes encoding IL8, IL6, MCP1, and CXC motif ligand 3 (CXCL3) in human aortic endothellial cells in the basal state or after the treatment of oxidized phospholipids [46]. This observation was consistent with the role of XBP1 in driving expression of proangiogenic factors, including IL8, in multiple cell lines under ER stress inducers, such as thapsigargin treatment and hypoxia [47]. ER stress response has been shown to be involved in inflammatory pathologies through regulating production of the

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pro-inflammatory cytokines. ER stress drives macrophages to produce mature IL-1β in response to TLR4 stimulation through a caspase-8- and TRIF-dependent pathway [48]. Treatments of ER stress–inducing reagents tunicamycin (TM) or thapsigargin (TG), followed by TLR stimulation, promote IL-6 and TNF-α production from macrophages. IL-1β, which was not produced in macrophages in response to treatment with any of the individual TLR agonists in the absence of ER stress, was secreted by TM- or TG-pretreated cells stimulated with LPS. In rheumatoid arthritis (RA), the IRE1α/XBP1-mediated UPR branch is activated in macrophages from synovial fluid of human RA patients [25]. IRE1α plays a key role in facilitating production of pro-inflammatory cytokines, including IL6, TNFα, IL1β, and RANTES, from macrophages in the animal model of inflammatory RA. In macrophages and neutrophils, TLR signaling, through MyD88 and TNF receptor-associated factor 6 (TRAF6), interacts with IRE1α, leading to IRE1a activation to promote expression of the genes encoding pro-inflammatory cytokines [25]. TRAF6 plays a key role in TLR-mediated IRE1α activation by catalyzing IRE1α ubiquitination and blocking the recruitment of protein phosphatase 2A (PP2A), a phosphatase that inactivates IRE1α. The TLR-mediated activation of IRE1α and its role in proinflammatory cytokine production are consistent with the role of XBP1 in macrophage-mediated pro-inflammatory response upon bacterial infection [49]. However, reconstitution of the activated form of XBP1 in the myeloid-specific IRE1α conditional knockout mice failed to fully rescue expression of the pro-inflammatory genes that are defective in IRE1α null macrophages, suggesting that IRE1α may regulate the pro-inflammatory response through additional targets [25]. Importantly, myeloid-specific deletion of the IRE1α gene or treatment with the IRE1α-specific inhibitor 4u8c can significantly repress pro-inflammatory response and development of RA in mice [25]. These discoveries implicate that TLR-mediated IRE1α activation is a potential therapeutic target for inflammatory RA.

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UPR in Inflammatory and Metabolic Diseases ER stress response is involved in many inflammatory diseases. Cross talk between TLR4 signaling and ER stress signaling has been shown to be important for inflammation in RA and Necrotizing enterocolitis (NE) models [25, 50]. In the NE model, the TLR4-Myd88 axis pathway induces ER stress in the intestinal epithelium. TLR4 signaling stimulates activation of the PERKCHOP branch of UPR signaling, which subsequently leads to apoptosis in cells.

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As an inflammatory and secretory organ functioning in a microbial environment, the intestinal epithelium is exquisitely sensitive to extracellular and intracellular challenges [51]. Disruption of the UPR component XBP1 represses the ability of intestinal epithelium to resolve ER stress and results in spontaneous intestinal inflammatory disorder similar to human inflammatory bowel disease [51, 52]. Indeed, dysfunction of XBP1 represents a genetic risk factor for both Crohn’s disease and ulcerative colitis [52, 53]. The cells or tissues with inflammatory metabolic features respond to excessive nutrients or energy fluctuations by activating intracellular stress signals, including UPR components, to facilitate the inflammatory response [54]. For example, exposure of human pancreatic cells to the saturated fatty acid palmitate induces ER stress, NF-κB activation, and upregulation of the cytokines, including IL-1β, TNF, IL-6, IL-8, CCL2, and CXCL1 [55]. Elevated levels of circulating pro-inflammatory cytokines, IL6 and IL1β, induce ER stress in islets isolated from normal mice and humans and causes pancreatic islet dysfunction [56]. Exposure to high levels of IL-1β and IL-6 disrupted glucose-stimulated intracellular calcium responses in isolated islets, and this effect was more severe in islets from prediabetic mice [56]. Increased levels of IL-1β and IL-6 stimulate ER calcium release and upregulate the ER stress markers GRP78/BiP, ATF4, and CHOP. Upregulation of inflammation and ER stress response are correlated with impaired glucose-stimulated insulin secretion and increased islet cell death in prediabetic db/db mice. Indeed, exogenous IL6 and IL-1β administration to prediabetic mice led to deficiencies in calcium handling and insulin secretion, suggesting that systemic proinflammatory response may trigger ER stress-associated islet dysfunction in early stages of type-2 diabetes [56].

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Conclusion and Future Directions The fields of ER stress, oxidative stress, and inflammation have been subjects of tremendous research over the past few decades. Increasing evidence is substantiating the roles of the integrated stress signaling pathways in different disease outcomes. However, an in-depth mechanistic understanding of the cross talk between the intracellular stress signaling pathways and inflammatory responses and their participation in disease progression have not yet been reached. Any shift in the balance of inflammatory stress responses may lead to an outcome in terms of disease progression. The ability of the UPR, oxidative stress, or inflammatory responses to intersect with different physiological signals makes it a lucrative target for therapeutic benefit. As with any therapeutic treatment, achieving the specificity with minimal side effects will be a daunting task. Efforts should be concentrated on maintaining the balance of

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inflammatory stress pathways rather than abrogating them. Perhaps in this double-edged sword we might find a cure for many dreadful diseases.

Acknowledgement This work was partially supported by National Institutes of Health (NIH) grants DK090313 and ES017829, and American Heart Association Grants 0635423Z and 09GRNT2280479 (to K.Z.). References 1. Kaufman RJ (1999) Stress signaling from the lumen of the endoplasmic reticulum: coordination of gene transcriptional and translational controls. Genes Dev 13:1211–1233 2. Ron D, Walter P (2007) Signal integration in the endoplasmic reticulum unfolded protein response. Nat Rev Mol Cell Biol 8:519–529 3. Gething MJ, Sambrook J (1992) Protein folding in the cell. Nature 355:33–45 4. Voeltz GK, Rolls MM, Rapoport TA (2002) Structural organization of the endoplasmic reticulum. EMBO Rep 3:944–950 5. Yoshida H, Matsui T, Yamamoto A, Okada T, Mori K (2001) XBP1 mRNA is induced by ATF6 and spliced by IRE1 in response to ER stress to produce a highly active transcription factor. Cell 107:881–891 6. Lee AH, Iwakoshi NN, Glimcher LH (2003) XBP-1 regulates a subset of endoplasmic reticulum resident chaperone genes in the unfolded protein response. Mol Cell Biol 23:7448–7459 7. Hollien J, Weissman JS (2006) Decay of endoplasmic reticulum-localized mRNAs during the unfolded protein response. Science 313:104–107 8. Hollien J, Lin JH, Li H, Stevens N, Walter P, Weissman JS (2009) Regulated Ire1-dependent decay of messenger RNAs in mammalian cells. J Cell Biol 186:323–331 9. Upton JP, Wang L, Han D, Wang ES, Huskey NE, Lim L, Truitt M, McManus MT, Ruggero D, Goga A, Papa FR, Oakes SA (2012) IRE1alpha cleaves select microRNAs during ER stress to derepress translation of proapoptotic Caspase-2. Science 338:818–822 10. Han D, Lerner AG, Vande Walle L, Upton JP, Xu W, Hagen A, Backes BJ, Oakes SA, Papa FR (2009) IRE1alpha kinase activation modes control alternate endoribonuclease outputs to determine divergent cell fates. Cell 138:562–575 11. Cho JA, Lee AH, Platzer B, Cross BC, Gardner BM, De Luca H, Luong P, Harding HP,

12.

13.

14.

15.

16.

17.

18.

Glimcher LH, Walter P, Fiebiger E, Ron D, Kagan JC, Lencer WI (2013) The unfolded protein response element IRE1alpha senses bacterial proteins invading the ER to activate RIG-I and innate immune signaling. Cell Host Microbe 13:558–569 Osorio F, Tavernier SJ, Hoffmann E, Saeys Y, Martens L, Vetters J, Delrue I, De Rycke R, Parthoens E, Pouliot P, Iwawaki T, Janssens S, Lambrecht BN (2014) The unfolded-proteinresponse sensor IRE-1alpha regulates the function of CD8alpha+ dendritic cells. Nat Immunol 15:248–257 Benhamron S, Hadar R, Iwawaky T, So JS, Lee AH, Tirosh B (2014) Regulated IRE1dependent decay participates in curtailing immunoglobulin secretion from plasma cells. Eur J Immunol 44:867–876 Iqbal J, Dai K, Seimon T, Jungreis R, Oyadomari M, Kuriakose G, Ron D, Tabas I, Hussain MM (2008) IRE1beta inhibits chylomicron production by selectively degrading MTP mRNA. Cell Metab 7:445–455 So JS, Hur KY, Tarrio M, Ruda V, FrankKamenetsky M, Fitzgerald K, Koteliansky V, Lichtman AH, Iwawaki T, Glimcher LH, Lee AH (2012) Silencing of lipid metabolism genes through IRE1alpha-mediated mRNA decay lowers plasma lipids in mice. Cell Metab 16:487–499 Coelho DS, Cairrao F, Zeng X, Pires E, Coelho AV, Ron D, Ryoo HD, Domingos PM (2013) Xbp1-independent Ire1 signaling is required for photoreceptor differentiation and rhabdomere morphogenesis in Drosophila. Cell Rep 5:791–801 Harding HP, Zhang Y, Ron D (1999) Protein translation and folding are coupled by an endoplasmic-reticulum-resident kinase. Nature 397:271–274 Novoa I, Zeng H, Harding HP, Ron D (2001) Feedback inhibition of the unfolded protein response by GADD34-mediated

Crosstalk between ER Stress, Oxidative Stress, and Inflammation

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

dephosphorylation of eIF2alpha. J Cell Biol 153:1011–1022 Ma Y, Hendershot LM (2003) Delineation of a negative feedback regulatory loop that controls protein translation during endoplasmic reticulum stress. J Biol Chem 278:34864–34873 Ye J, Rawson RB, Komuro R, Chen X, Dave UP, Prywes R, Brown MS, Goldstein JL (2000) ER stress induces cleavage of membranebound ATF6 by the same proteases that process SREBPs. Mol Cell 6:1355–1364 Brown MS, Ye J, Rawson RB, Goldstein JL (2000) Regulated intramembrane proteolysis: a control mechanism conserved from bacteria to humans. Cell 100:391–398 Okada T, Yoshida H, Akazawa R, Negishi M, Mori K (2002) Distinct roles of activating transcription factor 6 (ATF6) and double-stranded RNA-activated protein kinase-like endoplasmic reticulum kinase (PERK) in transcription during the mammalian unfolded protein response. Biochem J 366:585–594 Yamamoto K, Sato T, Matsui T, Sato M, Okada T, Yoshida H, Harada A, Mori K (2007) Transcriptional induction of mammalian ER quality control proteins is mediated by single or combined action of ATF6alpha and XBP1. Dev Cell 13:365–376 Zhang K, Kaufman RJ (2008) From endoplasmic-reticulum stress to the inflammatory response. Nature 454:455–462 Qiu Q, Zheng Z, Chang L, Zhao YS, Tan C, Dandekar A, Zhang Z, Lin Z, Gui M, Li X, Zhang T, Kong Q, Li H, Chen S, Chen A, Kaufman RJ, Yang WL, Lin HK, Zhang D, Perlman H, Thorp E, Zhang K, Fang D (2013) Toll-like receptor-mediated IRE1alpha activation as a therapeutic target for inflammatory arthritis. EMBO J 32:2477–2490 Tu BP, Weissman JS (2004) Oxidative protein folding in eukaryotes: mechanisms and consequences. J Cell Biol 164:341–346 Tu BP, Weissman JS (2002) The FAD- and O(2)-dependent reaction cycle of Ero1mediated oxidative protein folding in the endoplasmic reticulum. Mol Cell 10:983–994 Cuozzo JW, Kaiser CA (1999) Competition between glutathione and protein thiols for disulphide-bond formation. Nat Cell Biol 1:130–135 Li G, Mongillo M, Chin KT, Harding H, Ron D, Marks AR, Tabas I (2009) Role of ERO1alpha-mediated stimulation of inositol 1,4,5-triphosphate receptor activity in endoplasmic reticulum stress-induced apoptosis. J Cell Biol 186:783–792 Hetz C (2012) The unfolded protein response: controlling cell fate decisions under ER stress

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

213

and beyond. Nat Rev Mol Cell Biol 13: 89–102 Szabadkai G, Bianchi K, Varnai P, De Stefani D, Wieckowski MR, Cavagna D, Nagy AI, Balla T, Rizzuto R (2006) Chaperonemediated coupling of endoplasmic reticulum and mitochondrial Ca2+ channels. J Cell Biol 175:901–911 Verfaillie T, Rubio N, Garg AD, Bultynck G, Rizzuto R, Decuypere JP, Piette J, Linehan C, Gupta S, Samali A, Agostinis P (2012) PERK is required at the ER-mitochondrial contact sites to convey apoptosis after ROS-based ER stress. Cell Death Differ 19:1880–1891 Laing S, Wang G, Briazova T, Zhang C, Wang A, Zheng Z, Gow A, Chen AF, Rajagopalan S, Chen LC, Sun Q, Zhang K (2010) Airborne particulate matter selectively activates endoplasmic reticulum stress response in the lung and liver tissues. Am J Physiol Cell Physiol 299:C736–C749 Smith JA, Khan M, Magnani DD, Harms JS, Durward M, Radhakrishnan GK, Liu YP, Splitter GA (2013) Brucella induces an unfolded protein response via TcpB that supports intracellular replication in macrophages. PLoS Pathog 9:e1003785 Campos MA, Rosinha GM, Almeida IC, Salgueiro XS, Jarvis BW, Splitter GA, Qureshi N, Bruna-Romero O, Gazzinelli RT, Oliveira SC (2004) Role of Toll-like receptor 4 in induction of cell-mediated immunity and resistance to Brucella abortus infection in mice. Infect Immun 72:176–186 de Almeida LA, Macedo GC, Marinho FA, Gomes MT, Corsetti PP, Silva AM, Cassataro J, Giambartolomei GH, Oliveira SC (2013) Tolllike receptor 6 plays an important role in host innate resistance to Brucella abortus infection in mice. Infect Immun 81:1654–1662 Oliveira SC, de Oliveira FS, Macedo GC, de Almeida LA, Carvalho NB (2008) The role of innate immune receptors in the control of Brucella abortus infection: toll-like receptors and beyond. Microbes Infect 10:1005–1009 Zanetti M (2013) Cell-extrinsic effects of the tumor unfolded protein response on myeloid cells and T cells. Ann N Y Acad Sci 1284:6–11 Iwakoshi NN, Lee AH, Vallabhajosyula P, Otipoby KL, Rajewsky K, Glimcher LH (2003) Plasma cell differentiation and the unfolded protein response intersect at the transcription factor XBP-1. Nat Immunol. 4:321–329 van Anken E, Orsi A, Sitia R (2014) A RIDDle solved: why an intact IRE1/XBP1 signaling relay is key for humoral immune responses. Eur J Immunol 44(3):641–645 Brunsing R, Omori SA, Weber F, Bicknell A, Friend L, Rickert R, Niwa M (2008) B- and

214

42.

43.

44.

45.

46.

47.

48.

49.

Aditya Dandekar et al. T-cell development both involve activity of the unfolded protein response pathway. J Biol Chem 283:17954–17961 Kamimura D, Bevan MJ (2008) Endoplasmic reticulum stress regulator XBP-1 contributes to effector CD8+ T cell differentiation during acute infection. J Immunol 181:5433–5441 Kemp KL, Lin Z, Zhao F, Gao B, Song J, Zhang K, Fang D (2013) The serine-threonine kinase inositol-requiring enzyme 1alpha (IRE1alpha) promotes IL-4 production in T helper cells. J Biol Chem 288:33272–33282 Scheu S, Stetson DB, Reinhardt RL, Leber JH, Mohrs M, Locksley RM (2006) Activation of the integrated stress response during T helper cell differentiation. Nat Immunol 7:644–651 Zheng M, Zhang Q, Joe Y, Lee BH, Ryu do G, Kwon KB, Ryter SW, Chung HT (2013) Curcumin induces apoptotic cell death of activated human CD4+ T cells via increasing endoplasmic reticulum stress and mitochondrial dysfunction. Int Immunopharmacol 15: 517–523 Gargalovic PS, Gharavi NM, Clark MJ, Pagnon J, Yang WP, He A, Truong A, Baruch-Oren T, Berliner JA, Kirchgessner TG, Lusis AJ (2006) The unfolded protein response is an important regulator of inflammatory genes in endothelial cells. Arterioscler Thromb Vasc Biol 26: 2490–2496 Pereira ER, Liao N, Neale GA, Hendershot LM (2010) Transcriptional and posttranscriptional regulation of proangiogenic factors by the unfolded protein response. PLoS One 5 Shenderov K, Riteau N, Yip R, Mayer-Barber KD, Oland S, Hieny S, Fitzgerald P, Oberst A, Dillon CP, Green DR, Cerundolo V, Sher A (2014) Cutting edge: Endoplasmic reticulum stress licenses macrophages to produce mature IL-1beta in response to TLR4 stimulation through a caspase-8- and TRIF-dependent pathway. J Immunol 192:2029–2033 Martinon F, Chen X, Lee AH, Glimcher LH (2010) TLR activation of the transcription

50.

51.

52.

53.

54.

55.

56.

factor XBP1 regulates innate immune responses in macrophages. Nat Immunol 11:411–418 Afrazi A, Branca MF, Sodhi CP, Good M, Yamaguchi Y, Egan CE, Lu P, Jia H, Shaffiey S, Lin J, Ma C, Vincent G, Prindle T Jr, Weyandt S, Neal MD, Ozolek JA, Wiersch J, Tschurtschenthaler M, Shiota C, Gittes GK, Billiar TR, Mollen K, Kaser A, Blumberg R, Hackam DJ (2014) Toll-like receptor 4-mediated endoplasmic reticulum stress in intestinal crypts induces necrotizing enterocolitis. J Biol Chem 289:9584–9599 Kaser A, Adolph TE, Blumberg RS (2013) The unfolded protein response and gastrointestinal disease. Semin Immunopathol 35:307–319 Kaser A, Lee AH, Franke A, Glickman JN, Zeissig S, Tilg H, Nieuwenhuis EE, Higgins DE, Schreiber S, Glimcher LH, Blumberg RS (2008) XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease. Cell 134:743–756 Glas J, Seiderer J, Czamara D, Pasciuto G, Diegelmann J, Wetzke M, Olszak T, Wolf C, Muller-Myhsok B, Balschun T, Achkar JP, Kamboh MI, Franke A, Duerr RH, Brand S (2012) PTGER4 expression-modulating polymorphisms in the 5p13.1 region predispose to Crohn’s disease and affect NF-kappaB and XBP1 binding sites. PLoS One 7:e52873 Gregor MF, Hotamisligil GS (2011) Inflammatory mechanisms in obesity. Annu Rev Immunol 29:415–445 Igoillo-Esteve M, Marselli L, Cunha DA, Ladriere L, Ortis F, Grieco FA, Dotta F, Weir GC, Marchetti P, Eizirik DL, Cnop M (2010) Palmitate induces a pro-inflammatory response in human pancreatic islets that mimics CCL2 expression by beta cells in type 2 diabetes. Diabetologia 53:1395–1405 O’Neill CM, Lu C, Corbin KL, Sharma PR, Dula SB, Carter JD, Ramadan JW, Xin W, Lee JK, Nunemaker CS (2013) Circulating levels of IL-1B+IL-6 cause ER stress and dysfunction in islets from prediabetic male mice. Endocrinology 154:3077–3088

Chapter 16 Stress Responses During Ageing: Molecular Pathways Regulating Protein Homeostasis Emmanouil Kyriakakis, Andrea Princz, and Nektarios Tavernarakis Abstract The ageing process is characterized by deterioration of physiological function accompanied by frailty and ageing-associated diseases. The most broadly and well-studied pathways influencing ageing are the insulin/insulin-like growth factor 1 signaling pathway and the dietary restriction pathway. Recent studies in diverse organisms have also delineated emerging pathways, which collectively or independently contribute to ageing. Among them the proteostatic-stress-response networks, inextricably affect normal ageing by maintaining or restoring protein homeostasis to preserve proper cellular and organismal function. In this chapter, we survey the involvement of heat stress and endoplasmic reticulum stress responses in the regulation of longevity, placing emphasis on the cross talk between different response mechanisms and their systemic effects. We further discuss novel insights relevant to the molecular pathways mediating these stress responses that may facilitate the development of innovative interventions targeting age-related pathologies such as diabetes, cancer, cardiovascular and neurodegenerative diseases. Key words Ageing, Heat shock, Immunity, Inflammasome, Proteostasis, Proteotoxic stress, Unfolded protein response

1

Introduction Over the past years accumulating evidence suggest that stress-response and life-span regulation pathways share similar mechanisms [1, 2]. It is already known that accelerated ageing and ageing-associated diseases prevail when the organism loses the ability to adapt during stress caused by intrinsic or extrinsic burdens. Thus, the ability to cope with stress has a direct impact on physiological ageing. Impaired protein homeostasis and proteotoxic stress are considered a hallmark of ageing. Activation of stress-response pathways may ameliorate age-related proteotoxicity and induce life-span extension [3–5]. During ageing, the sophisticated mechanisms implicated in protein quality control, gradually deteriorate, leading to proteotoxicity and age-associated frailty. Such mechanisms include protein degradation-specific pathways, and networks for the proper folding and

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trafficking of nascent polypeptides. Adaptation of cellular proteostasis is mandatory in order to respond to loss of proteostatic control. Thus, identifying the players involved is essential towards developing strategies for efficiently tackling age-related pathologies. The heat shock response (HSR) that regulates the cytoplasmic proteostasis and the unfolded protein response (UPR) that regulates proteostasis during endoplasmic reticulum (ER) stress are two well-characterized pathways that have evolved independently to ensure proper protein folding. Key molecules implicated in proteotoxic stress response pathways are listed in Table 1. Perturbations in mitochondria may also initiate an UPR that activates transcription of nuclear-encoded mitochondrial chaperones for maintaining proper protein homeostasis [6]. The peroxisomal quality control system has also been implicated [7], expanding the list of organelle-specific proteotoxic stress-response pathways. In this review, we focus on key stress response pathways that preserve proteostasis in the cytoplasm and the ER, the systemic effects exerted by these pathways, and their role during ageing.

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The Heat Shock Response When organisms encounter unfavorable environmental or intrinsic conditions, such as heat stress, oxidative stress or overexpression of aggregation-prone proteins, cell defensive mechanisms become activated. Impairment of these mechanisms due to mutations or advanced ageing, may lead to neurodegenerative and protein conformational diseases (e.g., Alzheimer’s disease, Parkinson’s disease, Huntington disease) [8, 9]. The heat shock response (HSR) is activated within seconds after exposure to stress. The master regulators of the HSR are the heat shock transcription factor family of proteins. While there is only one heat shock transcription factor (HSF-1) in invertebrates, the mammalian genome encodes 4 (HSF-1-4) [10, 11]. In mammals HSF-1 regulates the HSR, whereas the other heat shock factors evolved to fulfil distinct functions throughout development, stress, and ageing [12–16]. HSF-1 becomes active upon exposure to elevated temperature and induces the expression of heat shock proteins (HSP) (chaperones). Five different HSP families are defined by their molecular weight: HSP100, HSP90, HSP70, HSP60, and small HSP (sHSP) [1]. The heat shock transcription factor family members share the same domain structure. The DNA binding domain (DBD) is located at the amino-terminus of the protein and comprises a helixturn-helix motif. Under normal conditions, interaction with Hsp90 inhibits activation of HSFs [10, 17]. When cells experience heat stress, Hsp90 is recruited to unfolded and misfolded proteins, leaving HSF-1 monomers in an intermediate, activation-ready state. As part of the activation process, the hydrophobic heptad repeat domain HR-A/B interacts with the HR-C domain, the carboxy-terminal

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Table 1 Key molecules involved in heat shock and ER stress responses Name

Function

Reference

ATF6

ER-membrane-bound ER-stress-sensor. Translocates to the Golgi, where [67, 68] it gets cleaved, forming a transcription factor responsible for the upregulation of ER chaperones

PERK

ER-membrane-bound ER-stress-sensor. Responsible for repressing [65, 66] global protein synthesis via phosphorylation of the α subunit of eIF2α

IRE-1

ER-membrane-bound ER-stress-sensor. Mediates transcriptional regulation during ER stress through XBP-1

[65]

XBP-1

A bZIP, ER-stress-regulated transcription factor. Upon ER stress the xbp-1 gene is alternatively spliced, generating the active transcription factor form

[63, 65]

eIF2α

mRNA translation initiation factor. Becomes phosphorylated during ER [65, 66] stress, attenuating protein synthesis

GRP78

An ER chaperone and central regulator of ER stress. Interacts with and keeps the three ER-stress-sensors inactive during normal conditions. Dissociates upon ER stress, initiating UPR

[62–68]

CHOP

A stress-specific proapoptotic transcription factor. During ER stress it promotes apoptosis

[70, 71]

NLRP3

NLRP3 inflammasome composes a multiprotein complex capable of sensing intrinsic dangers such as ER stress. NLRP3 activation is responsible for cytokine secretion and inflammation

[90–93]

TXNIP

Links ER stress and inflammation via NLRP3 activation. During severe ER stress TXNIP promotes apoptosis

[92, 93]

miR-211, miRNAs involved in ER stress adaptation miR-30c-2-3p

[77–82]

HSF-1

Master regulator of heat shock response gene transcription

[8, 10, 46]

HSP-90

Inhibits the function of HSF-1 under normal conditions

[10, 17]

HSP-70

Attenuates the heat shock response by binding to the active HSF-1

[29]

DAF-16/FoxO

Transcription factor mediating insulin/insulin-like growth factor signaling

[31, 38–40]

SIRT-1

Deacetylase, regulating the heat shock response through acetylation of HSF-1

[27]

HSR-1

Constitutively expressed noncoding RNA, implicated in activating the heat shock response

[47, 48]

PHA-4/FoxA

Regulates the expression of HSP-90 in a cell-non-autonomous manner

[104]

domain of the protein. The active HSF-1 transcription factor is a trimer, formed by interactions between the HR-A/B domains [18] which localize in nuclear stress bodies (NSBs) [19]. In this form, HSF-1 is capable of binding specific DNA sequences, the heat shock elements (HSEs), which are located in the promoter region of heat

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shock genes. The transcription activation domain (AD) at the carboxy end of HSF-1, is no longer repressed by intramolecular interaction with the regulatory domain, and after proper posttranslational modifications, HSF-1 can activate expression of the heat shock genes [10]. Such posttranslational modifications include phosphorylation [20–24], sumoylation [25, 26], or acetylation [27]. While sumoylation and acetylation suppress the function of HSF-1, phosphorylation can exert a negative or positive impact on HSF-1 activity. Phosphorylation of S303, S307 and S308 represses HSF-1 activation, while phosphorylation of S230, S326 and S419 after exposure to stress triggers the formation of HSF-1 trimers. HSF-1 possesses a phosphorylation dependent sumoylation motif (PDSM), where sumoylation of lysine 298 cannot occur without concomitant phosphorylation of serine 303 and 307. Acetylation of HSF-1 at residue K80 is required for the attenuation of the HSR. This event inhibits the DNA binding ability of HSF-1. Therefore, the extent of HSR depends on an acetylation–deacetylation cycle. Importantly, caloric restriction and the heat shock response act synergistically, and this cross talk requires the deacetylase SIRT1 [27, 28]. Association of HSF-1 with the heat shock protein, HSP70, attenuates HSR [29]. This negative feedback loop maintains appropriate levels of heat shock proteins during the HSR. Two regulators of SIRT1, AROS and DBC1 also modulate HSR. AROS positively regulates the deacetlyase activity of SIRT1, while DBC1 suppresses it. These two regulators influence transcription of hsp70 genes through recruitment of HSF-1 to the hsp70 promoter, and altering the acetylation status of HSF-1. This regulation may occur in a SIRT1-independent fashion, perhaps via alternative deacetylases [30]. Studies on the nematode Caenorhabditis elegans have contributed to a better understanding of the HSR, and its age-related decline. Recent studies have shown that proteostasis deterioration is coupled with the end of the reproductive period in C. elegans. Proteostasis collapses rapidly at this stage and declines gradually for the remaining duration of adult life. Overexpression of HSF-1 or DAF-16/FoxO reverses this rapid reduction, providing longer and healthier life span [31]. Maintenance of proteostasis has been linked to the germ line stem cells (GSC) and reproductive status. Sterile animals better preserve proteostasis in different somatic tissues, and this depends on several, nonredundant signaling pathways that involve HSF-1, DAF-16, DAF-12, DAF-9, DAF-36, NHR-80, and PHA-4 [32]. Therefore, without early GSC arrest, C. elegans cannot maintain the proper somatic proteostasis, leading to early death. Inhibition of oocyte production with the chemical 5-fluoro2-deoxyuridine (FUdR) also improves the proteostasis and protects against stress. This effect is in part HSF-1, DAF-16, and DAF-12 independent [33].

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Perturbation of HSF-1 function as well as the amount of chaperones found in the cell leads to changes in life span. Overexpression of HSF-1 or chaperone quantity elevation promotes long life [34–36], by better maintaining global proteostasis, while loss of HSF-1 results in premature ageing [37], and increased protein aggregate formation in cells. HSF-1 has also been implicated in life span extension by low insulin/IGF-1 signaling [38–40]. However, HSR and life span regulation do not always correlate. The C. elegans gtr-1 (a G-protein coupled receptor) gene is required for the expression of HS genes, but it has no influence on life span [41]. Thus, although HSF-1 and proper HSR is essential for normal life span, there are exceptions where the HSR and the regulation of longevity pathways can be uncoupled. Although HSF-1 is the master regulator of HSR, there are specific cases where other mediators are involved. In addition to HSF-1 (mammals) or HSF-3 (avians) activation during HSR, HSF-2 also becomes activated. Moreover, HSF-2 induces the expression of HS genes through increased activation of HSF-1 or HSF-3. Animals carrying HSF-2 mutations are more susceptible to mild heat shock, demonstrating the importance of HSF-2 in the regulation of proteostasis [42]. The primary hippocampal neurons of the neonatal rat embryos do not express HSF-1; therefore, they are incapable of responding to heat stress, while they express HSF-2 [43]. Mitotic cells are also hypersensitive to elevated temperature and proteotoxicity due to reduced binding and transactivating capacity of HSF-1 during the cell cycle. HSF-2 functions as an epigenetic regulator in mitotic cells. HSF-2 was shown to bind hundreds of loci or localize to condensed chromatin in mitotic and meiotic cells, respectively, driving transcription [44]. HSF-1 also plays an essential role in the proliferation of T cells. HSF-1 (−/−) T cells are unable to respond properly to immune system activating signals, and they exhibit cell cycle defects even at normal temperatures. In these cells the amount of cyclin E and cyclin A is reduced, without a large difference in their transcription [45]. Either HSF-1 is required for the transcription of regulatory genes which mediate translation of cyclin E and A proteins or HSF-1 itself is needed for the proper translation of these genes. Thus, investigating the tissue specific effects of HSF-1 and HSR could provide new insights into their regulation. Although these findings provide a better understanding of the mechanisms and the functions of the HSR, several questions still remain. How stress stimuli are sensed, resulting in HSF-1 activation remains to be elucidated. Four models that are not mutually exclusive have been proposed, relevant to the triggering of the heat shock response [46]. The first model involves the HSP90 chaperone, as already described above. The second model suggests that a ribonucleoprotein complex consisting of the translation elongation factor eEF1A and a noncoding, constitutively expressed RNA molecule,

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HSR-1 (heat shock RNA-1) catalyzes the HSF-1 trimer formation. Downregulation of HSR-1 by RNAi makes cells more susceptible to heat stress. Furthermore, ectopic expression of eEF1A and HSR-1 results in HSF-1 trimer formation [47]. In this case RNA molecules serve as sensors most probably via conformational changes [48]. A third model suggests that HSF-1 itself is capable of sensing changes in ambient temperature, transforming into the active form. This could explain the fact that in about 1 min after heat shock the hsp70 promoter is saturated with active HSF-1 trimers. A motif including disulfide bonds between two cysteine residues in the DBD domain and neighboring aromatic amino acids may serve as an intrinsic sensor on HSF-1 [49, 50]. The fourth model involves a nervous system controlled HSR. In C. elegans HSR is under the control of thermosensory neurons which regulate and coordinate the response in the whole organism (discussed below in more detail) [51]. Despite accumulating data, we are just starting to understand the tissue specific and cell-non-autonomous roles of HSR. Importantly, HSF-1 is not only active under stress conditions, but is an essential transcription factor also during development [52–57]. Moreover, HSF-1 is required for the survival of cancer cells [58]. This effect may be p53-dependent [59]. Therefore, HSF-1 may interact with p53 rendering the efficiency of cancer treatments dependent on the genetic background of cells [60, 61]. Thus, in addition to understanding fundamental cellular processes and stress response pathways, delineating the precise regulation of proteostasis through HSR could facilitate the development of new drugs against age-associated diseases.

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Endoplasmic Reticulum Stress and the Unfolded Protein Response The ER is a complex organelle performing various cellular functions. It is essential for the proper folding and post-translational modification of secreted and membrane-bound proteins and it also serves as a calcium storage organelle among other functions. Perturbations of ER homeostasis caused by physiological or pathological conditions result in ER stress, a condition characterized by overload of misfolded proteins. In response to ER stress, cells mount the unfolded protein response (UPR) to restore normal ER function.

3.1 Canonical and Noncanonical ER Stress-Induced Signaling Pathways

UPR is mediated by an elaborate signaling pathway that functions to ameliorate the accumulation of unfolded proteins in the ER. ER proteostasis is achieved either by proteasomal degradation of aberrant polypeptides in a process termed endoplasmic reticulum associated degradation (ERAD), by attenuating de novo protein synthesis or by inducing expression of chaperones, which are vital for proper protein folding [62–64]. The UPR is orchestrated by evolutionary conserved signaling events composing three consecutive phases

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with different effector functions, namely, adaptation, alarm, and apoptosis. These phases are directed by three major ER stress sensors, the PKR-like ER kinase (PERK), the activating transcription factor 6 (ATF6) and the inositol requiring enzyme-1 (IRE-1). Accumulation of misfolded proteins in the ER triggers ER stress. As a consequence, the otherwise ER-stress-sensor-bound GRP78 chaperone dissociates from the three ER transmembrane receptors, launching UPR [64, 65]. During adaptation, the tripartite signaling cascade facilitates reestablishing normal proteostasis. Protein load in the ER is moderated by translation attenuation, effected by the PERK-mediated phosphorylation of eukaryotic initiation factor 2 (eIF2α) [66]. On the other UPR arm, ATF6 is subjected to proteolytic cleavage after translocation to the Golgi apparatus, forming a transcription factor responsible for the upregulation of ER chaperones such as GRP78 and GRP94 [67, 68]. Activation of IRE-1 facilitates XBP-1 activation, which serves as a transcription factor of genes involved in proteostasis [65]. In addition, the IRE-1 branch of the UPR may also induce apoptosis by causing endonucleolytic decay of ER-localized mRNAs during stress [69]. When adaptive mechanisms fail to compensate in the face of protracted or excessive ER stress, apoptosis is induced to protect the organisms by eliminating compromised cells. The proapoptotic transcription factor C/EBP homologous protein (CHOP), which blocks the expression of antiapoptotic protein BCL-2, plays a central role in these apoptotic mechanisms [70, 71]. ER stress and UPR pathways have also been implicated in the pathogenesis of diseases associated with stress responses. In addition to biochemical approaches [71, 72], novel tools for in vivo monitoring of ER stress uncover new aspects of the pathophysiology of ageing-associated diseases [73–76]. Apart from the extensively discussed canonical UPR pathways, accumulating evidence suggests that miRNAs are important determinants of ER stress responses [77, 78]. However, their role is only starting to be dissected. Intriguingly, UPR may induce or suppress miRNAs, some of which exerting pro-adaptive whereas others pro-apoptotic effects. miRNAs have been suggested to function as UPR rheostats, coupling different components of the response and regulating ER stress-induced apoptosis [79–82]. miR-211 has been identified as a prosurvival miRNA which serves as a switch between adaptation and the apoptotic phase of the UPR. Indeed, PERK-induced miRNA expression prolongs the adaptation phase by attenuating the expression of chop, thus delaying ER stress induced apoptosis [79]. A mechanism which converges two of the three UPR components has also been identified. This mechanism involves the PERK-mediated induction of a miRNA (miR-30c2-3p), responsible for XBP-1 expression [80]. Nevertheless, the transition from adaptation towards apoptosis and the contribution of miRNAs to UPR dependent mechanisms are only now starting to be appreciated.

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During ageing UPR components deteriorate, shifting the balance towards a more apoptotic pathway [83, 84]. In aged mouse livers, misfolded proteins accumulate as a consequence of decreased enzymatic activities of the ER chaperones PDI and GRP78 [85]. Additionally, PERK mRNA levels are significantly reduced in the hippocampus of aged rats compared to younger animals, yet GADD34 and CHOP expression levels are induced in the cortical tissue of aged mice and cells, indicating a shift from a protective adaptive response towards an apoptosis-competent response [83, 84, 86]. Hence, aged animal cells are more vulnerable to apoptotic cell death as a consequence of limited ER stress resistance. Intriguingly, mild stress may exert beneficial effects, promoting longevity through adaptation, whereas severe ER stress may accelerate ageing and aggravate age-associated diseases. This phenomenon, termed hormesis, has attracted much attention, and UPR exhibits characteristics of a hormetic response. ER stress intensity may range between prolonged, damaging ER stress and mild, beneficial ER stress. Given that ER stress adaptation capacity declines during ageing, a slight induction of UPR may be an effective strategy to alleviate age-associated maladies and augment life span. This concept is supported by observations in β cells, which survive better and maintain physiological activity when UPR is restored or maintained at low levels, a mechanism that protects mice from type 1 diabetes [87]. 3.2 Cross Talk Between ER Stress and InflammationDependent Networks: From Adaptation to Death

As discussed earlier, UPR pathways sense different grades of proteotoxic stress and elicit different responses accordingly. However, the precise mechanisms leading to apoptotic cell death remain largely elusive. Noncanonical pathways mediated by miRNAs are partially responsible for the transition from the adaptation phase towards a pro-apoptotic phase. Additional noncanonical UPR pathways have been implicated in the regulation of UPR and the conversion of adaptation to terminal UPR. Some of these networks link stress signaling mechanisms to immune responses and inflammation. In C. elegans the apoptotic receptor CED-1 activates a network of PQN/ABU proteins which are involved in the noncanonical UPR pathway and immune response activation, enhancing animal survival [88]. This study provides evidence of how an apoptosis receptor (CED-1), evokes UPR during ER stress, preventing apoptosis. In another paradigm, neuronal expression of an octopamine G protein-coupled catecholamine receptor OCTR-1, limits innate immunity by downregulating PQN/ABU proteins and the p38 MAPK in non-neuronal cells [89]. These findings suggest that the nervous system regulates and links UPR with immune responses during exogenous threats in a systemic manner. Inflammation, one of the first immune system responses to infection, has been linked to uncontrolled ER stress in inflammatory pathologies such as neurodegenerative diseases and type 2 diabetes.

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The NLRP3 inflammasome has been implicated in sensing intrinsic ER stress, causing subsequent release of the highly pro-inflammatory cytokine IL-1β [90]. In astrocytes the link between ER stress and inflammation is attributed to the uncoupling protein 2 (UCP2). Loss of UCP2 induces ER stress and exacerbates NLRP3 inflammasome activation in astrocytes of the mouse midbrain [91]. Although the association of severe ER stress and inflammation has long been identified, the molecular connections between these two responses remain unknown. Thioredoxin-interacting protein (TXNIP) appears to tightly link irredeemable ER stress and NLRP3 inflammasome activation, leading to β cell death [92, 93]. Thus, TXNIP has been suggested to play an important role in switching from an adaptive response to the apoptotic response induced by severe ER stress. In conclusion, significant advances have been made in the past years towards clarifying the relationship between ER stress and inflammation and the transition between the different UPR phases. Further studies hold promise of identifying intervention targets to efficiently battle inflammatory diseases.

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Systemic Effects in the Regulation of Stress Responses and Ageing The ability of an organism to cope with endogenous and exogenous threats has a direct impact on physiology and healthy ageing. Organismal resistance against such hazards is achieved through physiological pathways that influence tissue communication, by coupling both cell-intrinsic and systemic events. To investigate the influence of such systemic effects on ageing and health span, whole animal studies are required. The genetic model organisms, C. elegans and Drosophila, have proven of great value and have contributed to shed ample light on cell-non-autonomous effects that regulate ageing. It is long known that dietary restriction and the insulin/insulinlike growth factor-like signaling pathway regulate organismal life span and mitigate or lessen age-related diseases. Nevertheless, the importance of hormonal and endocrine signals has not been fully appreciated. In C. elegans, increased neuronal activity induced by dietary restriction contributes to life span extension. Alterations of nutritional status induced by caloric restriction activate skn-1 in a pair of neurons (ASI neurons) in the head of the animal. This in turn leads to induced metabolic activity of non-neuronal body tissue and ultimately promotes longevity in an endocrine fashion [94]. Similarly, excision of insulin-like-peptide-producing cells from the Drosophila brain not only increases glucose levels, resembling effects in diabetic patients, but also induces stress resistance and life span extension due to systemic effects [95]. Similar genetic studies revealed that alterations in organismal life span and stress resistance driven by the germ lineage are also

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due to endocrine effects [32, 96, 97]. Indeed, genotoxic stress in germ cells enhances systemic proteotoxic stress resistance. Specific extrinsic and intrinsic insults targeting the DNA of the germ cells may transiently activate innate immune responses, which in return trigger the ubiquitin–proteasome system (UPS) in somatic tissues. Somatic stress resistance and proteostasis are enhanced by immunityrelated peptides secreted upon ERK MAP kinase activation in compromised germ cells [97]. Thus, protein homeostasis responses may be mediated by systemic effects. Similarly, ER and mitochondrial UPR likely exert systemic effects that have direct impact on longevity and age-related maladies. Although the consequences of mitochondrial function in longevity are long known [98, 99], the systemic effects exerted by mitochondria remain largely enigmatic. Neuronal or muscle specific ablation of cco-1 induces mitochondrial UPR in the intestine by a so far unknown mechanism, influencing the survival of the animal [100]. Systemic effects exerted by UPR have also been recently demonstrated, further to UPR initiated by cell non-autonomous signals [101, 102]. OCTR-1 expressing neurons modulate ER protein homeostasis in the gut during adulthood via regulation of the IRE-1/XBP-1 arm of the tripartite UPR signaling cascade [102]. In addition, neurotransmitters released upon ER UPR initiated by ER stress in a cell-autonomous fashion activate ER UPR in distal cells [101]. This activation confers protection against ER stress and ultimately promotes organismal longevity. Collectively, these findings highlight the importance of UPR coordination between distal cells towards maintaining protein homeostasis and prolonging ageing. Analogous mechanisms also coordinate HSR pathways. Two recent studies in C. elegans demonstrate cell-non-autonomous control of the HSR. A genome-wide RNAi screen identified 7 positive and 59 negative novel modifiers of the HSR. These modifiers act at particular steps during the HSR. Interestingly, although negative regulators show tissue specificity, positive regulators are expressed throughout the animal [103]. More precisely, overexpression of hsp-90 in the muscle leads to expression of the protein in tissues that normally do not express hsp-90, such as the intestine. Moreover, elevated expression of hsp-90 in the intestine or neurons reduces the severity of muscle degeneration in unc-54 mutants. These effects are regulated by the PHA-4 FoxA transcription factor [104]. FoxA-mediated expression of HSP90 maintains organismal proteostasis in a neuronal-independent cell-non-autonomous fashion providing, a global response towards preventing impairment of organismal health, and augmenting survival. In C. elegans, the AFD thermosensory neurons coordinate organismal HSR induction. Regulation of HSR is due to neuroendocrine effects, since mutations affecting AFD neurons inhibit HSR in distal tissues [51]. AFD deficient animals are still capable of moderating protein aggregation by HSF-1-derived chaperone

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expression, indicating that genes not involved in ambient temperature sensation are required for the expression of heat shock genes [105]. One candidate for this role is gtr-1, a G-protein coupled receptor not expressed in AFD neurons, but in other neurons necessary for the HSR [41]. Therefore, upregulation of HSF-1regulated genes is also possible in a thermosensory neuronindependent manner. These findings indicate that neuroendocrine signals mediate proteotoxic stress defense at the level of the whole organism. Indeed, recent studies have revealed that hypothalamic mitofusin 2 (MFN2) regulates whole body energy balance, by modulating ER/ mitochondrial homeostasis and function in pro-opiomelanocortin (POMC) neurons [106]. Therefore, the nervous system rapidly responds to a variety of stimuli and releases warning signals to sensitize distal cells and tissues against threatening events.

5

Conclusions Protein homeostasis is a fundamental prerequisite for cell survival. Subcellular compartment-specific stress responses are important determinants of cell proteostasis and crucial for organismal survival, health span, and life span (Fig. 1). Various age-associated diseases are caused by the deregulation of proteostasis [4, 15]. Protein aggregate deposition has been implicated in neurodegenerative disorders. Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease are some of the late-onset pathologies associated with protein malformation and impaired protein aggregate clearance mechanisms [107]. Numerous studies in cell cultures and animal models indicate that the ability of cells to respond efficiently to detrimental environmental effects declines with age [108]. In vitro [109, 110] and in vivo [111–114] findings have revealed that the amount of HSP70 proteins in response to heat shock decrease during ageing. However, HSF-1 protein levels remain constant throughout life span. Instead, the DNA-binding ability of HSF-1 is impaired in aged rat tissues, compared to young controls [115, 116]. Overexpression of DNAJ chaperones suppresses the cytotoxic effects exerted by mutant huntingtin aggregates in cells [117] and flies [118], and improves mental skills of mouse models of Huntington’s disease [119]. By contrast, HSR is blocked by accumulation of polyglutamine-expanded huntingtin protein [120, 121]. Surprisingly, the most affected HSF-1 target genes are involved in cytoskeletal binding, focal adhesion and GTPase activity, rather than in proteostasis [121]. Overexpression of the HSP70 interacting protein (Hip) increases the efficiency of HSP70 binding to its substrates leading to reduced accumulation of the polyglutamine-expanded androgen receptor, improving the

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Fig. 1 Proteotoxic stress response mechanisms. Cell-autonomous and cell-non-autonomous stress response pathways triggered under conditions of cellular stress. On the upper left part, signals from the stressed ER are depicted, promoting cellular adaptation through eIF-2α phosphorylation and regulation of miRNAs. Switching from adaptation to apoptosis is part of the noncanonical pathways, involving inflammasome activation and IL-1β secretion. Additional organelle-specific response pathways important in maintaining proteostasis, including the heat shock response and the mitochondrial and peroxisomal UPR are shown. Collectively, these stress response pathways have been implicated in the regulation of longevity, and in the pathogenesis of ageing-related disorders via endocrine effects exerted mainly by neuron-released peptides

symptoms of spinobulbar muscular atrophy [122]. Another activator of HSP70, ML346, a barbituric acid scaffold acts through HSF-1, FOXO, and Nrf-2 to induce chaperone expression and proper protein folding in conformational diseases [123]. These new regulatory molecules comprise attractive intervention targets against diseases associated with aberrant HSR. Additionally, the cross talk between ER stress and inflammation has been implicated in obesity and metabolic dysfunction [124]. Metabolic diseases such as diabetes and obesity are associated with proteotoxic stress and more specifically with the UPR network [125]. For example, the insulin secreting β-cells are more susceptible to ER stress induced apoptosis when the PERK component of the UPR is compromised, resulting in the manifestation of diabetes [126, 127]. Interestingly, administration of

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tauroursodeoxycholic acid, an ER stress mitigator, confers protection against type 1 diabetes, through UPR regulation and β-cell preservation [87]. In metazoans, compounds that bind and stain amyloid-β deposits and enhance proteostasis also promote longevity [128]. Such small compounds, which specifically regulate UPR pathways, may be effective in interventions against diseases associated with aberrant HSR. Stress responses and inflammation also play crucial roles in the development of tumors. Cancer cells are characterized by alterations in metabolic activity some of which resemble the metabolic response of non-transformed cells [129]. This metabolic activity directly depends on the tissue microenvironment; however, the role of paracrine and endocrine signals is not well understood. Given that proliferating tumor cells require increased protein folding, manipulation of proteostasis and stress-response pathways may provide a promising therapeutic strategy against cancer. Apoptosis could be triggered in cancer cells by inducing severe stress. Alternatively cancer cells could be mitigated by completely abrogating and limiting stress responses, impairing adaptation to stressful conditions. To this end inhibitors or small molecules targeting UPR pathways have been developed to ameliorate protein misfolding diseases or as potential anticancer drugs with some promising results [130–134]. Stem cells exhibit high proteasome activity allowing them to cope with proteotoxic stress and avoid replicative senescence. Recent studies have revealed novel players of proteostasis in human embryonic stem cells (hESCs) that link longevity and stress resistance. PSMD1 has been shown to efficiently promote proteostasis in hESCs [135]. α-Synuclein also appears to play an important role during pluripotent stem cell (iPS) differentiation, involving ER stress response pathways [136]. Furthermore, ER stress plays important role in epithelial stemness, through UPR, in a PERK dependent manner [137]. HIF-2α also contributes to the maintenance of human hematopoietic stem/progenitor cell (HSPCs) and in the survival of human acute myeloid leukemia cells by protecting against ER stress-induced apoptosis [138]. Given that stem cells are required for tissue regeneration, and ageing is associated with decay in regeneration potential, proteostasis may promote longevity by maintaining the normal function of stem cells. The signaling pathways described here collectively restore or maintain normal protein homeostasis levels through reducing demand and limiting protein aggregation, by enhancing proper folding and therefore safeguarding against proteostasis-related diseases. Mild stressors could potentially be used to precondition cells to more effectively respond to metabolic stress and ageing. Therefore, preadaptation against upcoming stress insults could provide an efficient strategy for an organism to better cope against life-threatening hazards. To this end it is crucial to further

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understand the molecular networks involved and identify thresholds below which a stressor exerts beneficial effects, thus minimizing deleterious consequences. In addition, cellular therapies against degenerative and age-associated diseases with a prominent cell non-autonomous component may prove beneficial. However, major advances are still required in order to understand how these organelle-specific pathways may impinge on whole organismal survival in an autocrine, paracrine or endocrine fashion.

Acknowledgements We apologize to those colleagues whose work could not be referenced directly owing to space limitations. E.K. is supported by the General Secretariat for Research and Technology of the Greek Ministry of Education. A.P. is supported by a European Commission Marie Curie Actions Programme, Initial Training fellowship. Work in the authors’ laboratory is also funded by grants from the European Research Council (ERC) and the European Commission Seventh Framework Programme. References 1. Kourtis N, Tavernarakis N (2011) Cellular stress response pathways and ageing: intricate molecular relationships. EMBO J 30: 2520–2531 2. Salminen A, Kaarniranta K (2010) ER stress and hormetic regulation of the aging process. Ageing Res Rev 9:211–217 3. Tower J (2009) Hsps and aging. Trends Endocrinol Metab 20:216–222 4. Balch WE, Morimoto RI, Dillin A, Kelly JW (2008) Adapting proteostasis for disease intervention. Science 319:916–919 5. Lopez-Otin C, Blasco MA, Partridge L, Serrano M, Kroemer G (2013) The hallmarks of aging. Cell 153:1194–1217 6. Haynes CM, Ron D (2010) The mitochondrial UPR—protecting organelle protein homeostasis. J Cell Sci 123:3849–3855 7. Bartoszewska M, Williams C, Kikhney A, Opalinski L, van Roermund CW, de Boer R, Veenhuis M, van der Klei IJ (2012) Peroxisomal proteostasis involves a Lon family protein that functions as protease and chaperone. J Biol Chem 287:27380–27395 8. Morimoto RI (2011) The heat shock response: systems biology of proteotoxic stress in aging and disease. Cold Spring Harb Symp Quant Biol 76:91–99

9. Koga H, Kaushik S, Cuervo AM (2011) Protein homeostasis and aging: The importance of exquisite quality control. Ageing Res Rev 10:205–215 10. Akerfelt M, Morimoto RI, Sistonen L (2010) Heat shock factors: integrators of cell stress, development and lifespan. Nat Rev Mol Cell Biol 11:545–555 11. Wu C (1995) Heat shock transcription factors: structure and regulation. Annu Rev Cell Dev Biol 11:441–469 12. Bu L, Jin Y, Shi Y, Chu R, Ban A, Eiberg H, Andres L, Jiang H, Zheng G, Qian M, Cui B, Xia Y, Liu J, Hu L, Zhao G, Hayden MR, Kong X (2002) Mutant DNA-binding domain of HSF4 is associated with autosomal dominant lamellar and Marner cataract. Nat Genet 31:276–278 13. Fujimoto M, Izu H, Seki K, Fukuda K, Nishida T, Yamada S, Kato K, Yonemura S, Inouye S, Nakai A (2004) HSF4 is required for normal cell growth and differentiation during mouse lens development. EMBO J 23:4297–4306 14. Kallio M, Chang Y, Manuel M, Alastalo TP, Rallu M, Gitton Y, Pirkkala L, Loones MT, Paslaru L, Larney S, Hiard S, Morange M, Sistonen L, Mezger V (2002) Brain abnormal-

Proteotoxic Stress Response Pathways in Ageing

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

ities, defective meiotic chromosome synapsis and female subfertility in HSF2 null mice. EMBO J 21:2591–2601 Morimoto RI (2008) Proteotoxic stress and inducible chaperone networks in neurodegenerative disease and aging. Genes Dev 22:1427–1438 Sistonen L, Sarge KD, Phillips B, Abravaya K, Morimoto RI (1992) Activation of heat shock factor 2 during hemin-induced differentiation of human erythroleukemia cells. Mol Cell Biol 12:4104–4111 Zou J, Guo Y, Guettouche T, Smith DF, Voellmy R (1998) Repression of heat shock transcription factor HSF1 activation by HSP90 (HSP90 complex) that forms a stresssensitive complex with HSF1. Cell 94: 471–480 Sorger PK, Nelson HC (1989) Trimerization of a yeast transcriptional activator via a coiledcoil motif. Cell 59:807–813 Cotto J, Fox S, Morimoto R (1997) HSF1 granules: a novel stress-induced nuclear compartment of human cells. J Cell Sci 110(Pt 23):2925–2934 Guettouche T, Boellmann F, Lane WS, Voellmy R (2005) Analysis of phosphorylation of human heat shock factor 1 in cells experiencing a stress. BMC Biochem 6:4 Holmberg CI, Hietakangas V, Mikhailov A, Rantanen JO, Kallio M, Meinander A, Hellman J, Morrice N, MacKintosh C, Morimoto RI, Eriksson JE, Sistonen L (2001) Phosphorylation of serine 230 promotes inducible transcriptional activity of heat shock factor 1. EMBO J 20:3800–3810 Kline MP, Morimoto RI (1997) Repression of the heat shock factor 1 transcriptional activation domain is modulated by constitutive phosphorylation. Mol Cell Biol 17:2107–2115 Knauf U, Newton EM, Kyriakis J, Kingston RE (1996) Repression of human heat shock factor 1 activity at control temperature by phosphorylation. Genes Dev 10:2782–2793 Sorger PK, Pelham HR (1988) Yeast heat shock factor is an essential DNA-binding protein that exhibits temperature-dependent phosphorylation. Cell 54:855–864 Anckar J, Hietakangas V, Denessiouk K, Thiele DJ, Johnson MS, Sistonen L (2006) Inhibition of DNA binding by differential sumoylation of heat shock factors. Mol Cell Biol 26:955–964 Hietakangas V, Ahlskog JK, Jakobsson AM, Hellesuo M, Sahlberg NM, Holmberg CI,

27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

229

Mikhailov A, Palvimo JJ, Pirkkala L, Sistonen L (2003) Phosphorylation of serine 303 is a prerequisite for the stress-inducible SUMO modification of heat shock factor 1. Mol Cell Biol 23:2953–2968 Westerheide SD, Anckar J, Stevens SM Jr, Sistonen L, Morimoto RI (2009) Stressinducible regulation of heat shock factor 1 by the deacetylase SIRT1. Science 323: 1063–1066 Raynes R, Leckey BD Jr, Nguyen K, Westerheide SD (2012) Heat shock and caloric restriction have a synergistic effect on the heat shock response in a sir2.1-dependent manner in Caenorhabditis elegans. J Biol Chem 287:29045–29053 Shi Y, Mosser DD, Morimoto RI (1998) Molecular chaperones as HSF1-specific transcriptional repressors. Genes Dev 12:654–666 Raynes R, Pombier KM, Nguyen K, Brunquell J, Mendez JE, Westerheide SD (2013) The SIRT1 modulators AROS and DBC1 regulate HSF1 activity and the heat shock response. PLoS One 8:e54364 Ben-Zvi A, Miller EA, Morimoto RI (2009) Collapse of proteostasis represents an early molecular event in Caenorhabditis elegans aging. Proc Natl Acad Sci U S A 106: 14914–14919 Shemesh N, Shai N, Ben-Zvi A (2013) Germline stem cell arrest inhibits the collapse of somatic proteostasis early in Caenorhabditis elegans adulthood. Aging Cell 12:814–822 Angeli S, Klang I, Sivapatham R, Mark K, Zucker D, Bhaumik D, Lithgow GJ, Andersen JK (2013) A DNA synthesis inhibitor is protective against proteotoxic stressors via modulation of fertility pathways in Caenorhabditis elegans. Aging (Albany NY) 5:759–769 Morrow G, Samson M, Michaud S, Tanguay RM (2004) Overexpression of the small mitochondrial Hsp22 extends Drosophila life span and increases resistance to oxidative stress. FASEB J 18:598–599 Walker GA, Lithgow GJ (2003) Lifespan extension in C. elegans by a molecular chaperone dependent upon insulin-like signals. Aging Cell 2:131–139 Swindell WR, Masternak MM, Kopchick JJ, Conover CA, Bartke A, Miller RA (2009) Endocrine regulation of heat shock protein mRNA levels in long-lived dwarf mice. Mech Ageing Dev 130:393–400 Min JN, Whaley RA, Sharpless NE, Lockyer P, Portbury AL, Patterson C (2008) CHIP deficiency decreases longevity, with accelerated

230

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

48.

Emmanouil Kyriakakis et al. aging phenotypes accompanied by altered protein quality control. Mol Cell Biol 28: 4018–4025 Hsu AL, Murphy CT, Kenyon C (2003) Regulation of aging and age-related disease by DAF-16 and heat-shock factor. Science 300:1142–1145 Morley JF, Morimoto RI (2004) Regulation of longevity in Caenorhabditis elegans by heat shock factor and molecular chaperones. Mol Biol Cell 15:657–664 Chiang WC, Ching TT, Lee HC, Mousigian C, Hsu AL (2012) HSF-1 regulators DDL1/2 link insulin-like signaling to heat-shock responses and modulation of longevity. Cell 148:322–334 Maman M, Carvalhal Marques F, Volovik Y, Dubnikov T, Bejerano-Sagie M, Cohen E (2013) A neuronal GPCR is critical for the induction of the heat shock response in the nematode C. elegans. J Neurosci 33: 6102–6111 Shinkawa T, Tan K, Fujimoto M, Hayashida N, Yamamoto K, Takaki E, Takii R, Prakasam R, Inouye S, Mezger V, Nakai A (2011) Heat shock factor 2 is required for maintaining proteostasis against febrile-range thermal stress and polyglutamine aggregation. Mol Biol Cell 22:3571–3583 Marcuccilli CJ, Mathur SK, Morimoto RI, Miller RJ (1996) Regulatory differences in the stress response of hippocampal neurons and glial cells after heat shock. J Neurosci 16:478–485 Vihervaara A, Sergelius C, Vasara J, Blom MA, Elsing AN, Roos-Mattjus P, Sistonen L (2013) Transcriptional response to stress in the dynamic chromatin environment of cycling and mitotic cells. Proc Natl Acad Sci U S A 110:E3388–E3397 Gandhapudi SK, Murapa P, Threlkeld ZD, Ward M, Sarge KD, Snow C, Woodward JG (2013) Heat shock transcription factor 1 is activated as a consequence of lymphocyte activation and regulates a major proteostasis network in T cells critical for cell division during stress. J Immunol 191:4068–4079 Anckar J, Sistonen L (2011) Regulation of HSF1 function in the heat stress response: implications in aging and disease. Annu Rev Biochem 80:1089–1115 Shamovsky I, Ivannikov M, Kandel ES, Gershon D, Nudler E (2006) RNA-mediated response to heat shock in mammalian cells. Nature 440:556–560 Kugel JF, Goodrich JA (2006) Beating the heat: a translation factor and an RNA mobilize

49.

50.

51.

52.

53.

54.

55.

56.

57.

58.

59.

60.

the heat shock transcription factor HSF1. Mol Cell 22:153–154 Ahn SG, Thiele DJ (2003) Redox regulation of mammalian heat shock factor 1 is essential for Hsp gene activation and protection from stress. Genes Dev 17:516–528 Lu M, Lee YJ, Park SM, Kang HS, Kang SW, Kim S, Park JS (2009) Aromatic-participant interactions are essential for disulfide-bondbased trimerization in human heat shock transcription factor 1. Biochemistry 48:3795–3797 Prahlad V, Cornelius T, Morimoto RI (2008) Regulation of the cellular heat shock response in Caenorhabditis elegans by thermosensory neurons. Science 320:811–814 Gallo GJ, Prentice H, Kingston RE (1993) Heat shock factor is required for growth at normal temperatures in the fission yeast Schizosaccharomyces pombe. Mol Cell Biol 13:749–761 Jedlicka P, Mortin MA, Wu C (1997) Multiple functions of Drosophila heat shock transcription factor in vivo. EMBO J 16:2452–2462 Christians E, Davis AA, Thomas SD, Benjamin IJ (2000) Maternal effect of Hsf1 on reproductive success. Nature 407:693–694 Inouye S, Izu H, Takaki E, Suzuki H, Shirai M, Yokota Y, Ichikawa H, Fujimoto M, Nakai A (2004) Impaired IgG production in mice deficient for heat shock transcription factor 1. J Biol Chem 279:38701–38709 Takii R, Inouye S, Fujimoto M, Nakamura T, Shinkawa T, Prakasam R, Tan K, Hayashida N, Ichikawa H, Hai T, Nakai A (2010) Heat shock transcription factor 1 inhibits expression of IL-6 through activating transcription factor 3. J Immunol 184: 1041–1048 Barna J, Princz A, Kosztelnik M, Hargitai B, Takacs-Vellai K, Vellai T (2012) Heat shock factor-1 intertwines insulin/IGF-1, TGFbeta and cGMP signaling to control development and aging. BMC Dev Biol 12:32 Dai C, Whitesell L, Rogers AB, Lindquist S (2007) Heat shock factor 1 is a powerful multifaceted modifier of carcinogenesis. Cell 130:1005–1018 Min JN, Huang L, Zimonjic DB, Moskophidis D, Mivechi NF (2007) Selective suppression of lymphomas by functional loss of Hsf1 in a p53-deficient mouse model for spontaneous tumors. Oncogene 26:5086–5097 Kim EH, Lee YJ, Bae S, Lee JS, Kim J, Lee YS (2009) Heat shock factor 1-mediated aneuploidy requires a defective function of p53. Cancer Res 69:9404–9412

Proteotoxic Stress Response Pathways in Ageing 61. Whitesell L, Lindquist S (2009) Inhibiting the transcription factor HSF1 as an anticancer strategy. Expert Opin Ther Targets 13: 469–478 62. Travers KJ, Patil CK, Wodicka L, Lockhart DJ, Weissman JS, Walter P (2000) Functional and genomic analyses reveal an essential coordination between the unfolded protein response and ER-associated degradation. Cell 101:249–258 63. Schroder M (2008) Endoplasmic reticulum stress responses. Cell Mol Life Sci 65:862–894 64. Malhotra JD, Kaufman RJ (2007) Endoplasmic reticulum stress and oxidative stress: a vicious cycle or a double-edged sword? Antioxid Redox Signal 9:2277–2293 65. Ron D, Walter P (2007) Signal integration in the endoplasmic reticulum unfolded protein response. Nat Rev Mol Cell Biol 8: 519–529 66. Harding HP, Zhang Y, Bertolotti A, Zeng H, Ron D (2000) Perk is essential for translational regulation and cell survival during the unfolded protein response. Mol Cell 5:897–904 67. Chen X, Shen J, Prywes R (2002) The luminal domain of ATF6 senses endoplasmic reticulum (ER) stress and causes translocation of ATF6 from the ER to the Golgi. J Biol Chem 277:13045–13052 68. Shen J, Chen X, Hendershot L, Prywes R (2002) ER stress regulation of ATF6 localization by dissociation of BiP/GRP78 binding and unmasking of Golgi localization signals. Dev Cell 3:99–111 69. Han D, Lerner AG, Vande Walle L, Upton JP, Xu W, Hagen A, Backes BJ, Oakes SA, Papa FR (2009) IRE1alpha kinase activation modes control alternate endoribonuclease outputs to determine divergent cell fates. Cell 138:562–575 70. Szegezdi E, Logue SE, Gorman AM, Samali A (2006) Mediators of endoplasmic reticulum stress-induced apoptosis. EMBO Rep 7:880–885 71. Fribley A, Zhang K, Kaufman RJ (2009) Regulation of apoptosis by the unfolded protein response. Methods Mol Biol 559: 191–204 72. Samali A, Fitzgerald U, Deegan S, Gupta S (2010) Methods for monitoring endoplasmic reticulum stress and the unfolded protein response. Int J Cell Biol 2010:830307 73. Iwawaki T, Akai R, Kohno K, Miura M (2004) A transgenic mouse model for monitoring endoplasmic reticulum stress. Nat Med 10:98–102

231

74. Merksamer PI, Trusina A, Papa FR (2008) Real-time redox measurements during endoplasmic reticulum stress reveal interlinked protein folding functions. Cell 135:933–947 75. Thorp E, Iwawaki T, Miura M, Tabas I (2011) A reporter for tracking the UPR in vivo reveals patterns of temporal and cellular stress during atherosclerotic progression. J Lipid Res 52:1033–1038 76. Hiramatsu N, Kasai A, Hayakawa K, Yao J, Kitamura M (2006) Real-time detection and continuous monitoring of ER stress in vitro and in vivo by ES-TRAP: evidence for systemic, transient ER stress during endotoxemia. Nucleic Acids Res 34:e93 77. Chitnis N, Pytel D, Diehl JA (2013) UPRinducible miRNAs contribute to stressful situations. Trends Biochem Sci 38:447–452 78. Bartoszewska S, Kochan K, Madanecki P, Piotrowski A, Ochocka R, Collawn JF, Bartoszewski R (2013) Regulation of the unfolded protein response by microRNAs. Cell Mol Biol Lett 18(4):555–578 79. Chitnis NS, Pytel D, Bobrovnikova-Marjon E, Pant D, Zheng H, Maas NL, Frederick B, Kushner JA, Chodosh LA, Koumenis C, Fuchs SY, Diehl JA (2012) miR-211 is a prosurvival microRNA that regulates chop expression in a PERK-dependent manner. Mol Cell 48:353–364 80. Byrd AE, Aragon IV, Brewer JW (2012) MicroRNA-30c-2* limits expression of proadaptive factor XBP1 in the unfolded protein response. J Cell Biol 196:689–698 81. Upton JP, Wang L, Han D, Wang ES, Huskey NE, Lim L, Truitt M, McManus MT, Ruggero D, Goga A, Papa FR, Oakes SA (2012) IRE1alpha cleaves select microRNAs during ER stress to derepress translation of proapoptotic caspase-2. Science 338:818–822 82. Cawley K, Logue SE, Gorman AM, Zeng Q, Patterson J, Gupta S, Samali A (2013) Disruption of microRNA biogenesis confers resistance to ER stress-induced cell death upstream of the mitochondrion. PLoS One 8:e73870 83. Naidoo N, Ferber M, Master M, Zhu Y, Pack AI (2008) Aging impairs the unfolded protein response to sleep deprivation and leads to proapoptotic signaling. J Neurosci 28: 6539–6548 84. Hussain SG, Ramaiah KV (2007) Reduced eIF2alpha phosphorylation and increased proapoptotic proteins in aging. Biochem Biophys Res Commun 355:365–370 85. Nuss JE, Choksi KB, DeFord JH, Papaconstantinou J (2008) Decreased

232

86.

87.

88.

89.

90.

91.

92.

93.

94.

95.

Emmanouil Kyriakakis et al. enzyme activities of chaperones PDI and BiP in aged mouse livers. Biochem Biophys Res Commun 365:355–361 Paz Gavilan M, Vela J, Castano A, Ramos B, del Rio JC, Vitorica J, Ruano D (2006) Cellular environment facilitates protein accumulation in aged rat hippocampus. Neurobiol Aging 27:973–982 Engin F, Yermalovich A, Ngyuen T, Hummasti S, Fu W, Eizirik DL, Mathis D, Hotamisligil GS (2013) Restoration of the unfolded protein response in pancreatic beta cells protects mice against type 1 diabetes. Sci Transl Med 5: 211ra156 Haskins KA, Russell JF, Gaddis N, Dressman HK, Aballay A (2008) Unfolded protein response genes regulated by CED-1 are required for Caenorhabditis elegans innate immunity. Dev Cell 15:87–97 Sun J, Singh V, Kajino-Sakamoto R, Aballay A (2011) Neuronal GPCR controls innate immunity by regulating noncanonical unfolded protein response genes. Science 332:729–732 Menu P, Mayor A, Zhou R, Tardivel A, Ichijo H, Mori K, Tschopp J (2012) ER stress activates the NLRP3 inflammasome via an UPRindependent pathway. Cell Death Dis 3:e261 Lu M, Sun XL, Qiao C, Liu Y, Ding JH, Hu G (2014) Uncoupling protein 2 deficiency aggravates astrocytic endoplasmic reticulum stress and nod-like receptor protein 3 inflammasome activation. Neurobiol Aging 35:421–430 Lerner AG, Upton JP, Praveen PV, Ghosh R, Nakagawa Y, Igbaria A, Shen S, Nguyen V, Backes BJ, Heiman M, Heintz N, Greengard P, Hui S, Tang Q, Trusina A, Oakes SA, Papa FR (2012) IRE1alpha induces thioredoxininteracting protein to activate the NLRP3 inflammasome and promote programmed cell death under irremediable ER stress. Cell Metab 16:250–264 Oslowski CM, Hara T, O’Sullivan-Murphy B, Kanekura K, Lu S, Hara M, Ishigaki S, Zhu LJ, Hayashi E, Hui ST, Greiner D, Kaufman RJ, Bortell R, Urano F (2012) Thioredoxininteracting protein mediates ER stressinduced beta cell death through initiation of the inflammasome. Cell Metab 16:265–273 Bishop NA, Guarente L (2007) Two neurons mediate diet-restriction-induced longevity in C. elegans. Nature 447:545–549 Broughton SJ, Piper MD, Ikeya T, Bass TM, Jacobson J, Driege Y, Martinez P, Hafen E, Withers DJ, Leevers SJ, Partridge L (2005) Longer lifespan, altered metabolism, and stress resistance in Drosophila from ablation of cells making insulin-like ligands. Proc Natl Acad Sci U S A 102:3105–3110

96. Hsin H, Kenyon C (1999) Signals from the reproductive system regulate the lifespan of C. elegans. Nature 399:362–366 97. Ermolaeva MA, Segref A, Dakhovnik A, Ou HL, Schneider JI, Utermohlen O, Hoppe T, Schumacher B (2013) DNA damage in germ cells induces an innate immune response that triggers systemic stress resistance. Nature 501:416–420 98. Lionaki E, Tavernarakis N (2013) Oxidative stress and mitochondrial protein quality control in aging. J Proteome 92:181–194 99. Raffaello A, Rizzuto R (2011) Mitochondrial longevity pathways. Biochim Biophys Acta 1813:260–268 100. Durieux J, Wolff S, Dillin A (2011) The cellnon-autonomous nature of electron transport chain-mediated longevity. Cell 144:79–91 101. Taylor RC, Dillin A (2013) XBP-1 is a cellnonautonomous regulator of stress resistance and longevity. Cell 153:1435–1447 102. Sun J, Liu Y, Aballay A (2012) Organismal regulation of XBP-1-mediated unfolded protein response during development and immune activation. EMBO Rep 13:855–860 103. Guisbert E, Czyz DM, Richter K, McMullen PD, Morimoto RI (2013) Identification of a tissue-selective heat shock response regulatory network. PLoS Genet 9:e1003466 104. van Oosten-Hawle P, Porter RS, Morimoto RI (2013) Regulation of organismal proteostasis by transcellular chaperone signaling. Cell 153:1366–1378 105. Prahlad V, Morimoto RI (2011) Neuronal circuitry regulates the response of Caenorhabditis elegans to misfolded proteins. Proc Natl Acad Sci U S A 108:14204–14209 106. Schneeberger M, Dietrich MO, Sebastian D, Imbernon M, Castano C, Garcia A, Esteban Y, Gonzalez-Franquesa A, Rodriguez IC, Bortolozzi A, Garcia-Roves PM, Gomis R, Nogueiras R, Horvath TL, Zorzano A, Claret M (2013) Mitofusin 2 in POMC neurons connects ER stress with leptin resistance and energy imbalance. Cell 155:172–187 107. Ben-Gedalya T, Cohen E (2012) Quality control compartments coming of age. Traffic 13:635–642 108. Kregel KC (2002) Heat shock proteins: modifying factors in physiological stress responses and acquired thermotolerance. J Appl Physiol (1985) 92:2177–2186 109. Fargnoli J, Kunisada T, Fornace AJ Jr, Schneider EL, Holbrook NJ (1990) Decreased expression of heat shock protein 70 mRNA and protein after heat treatment in cells of aged rats. Proc Natl Acad Sci U S A 87:846–850

Proteotoxic Stress Response Pathways in Ageing 110. Liu AY, Lin Z, Choi HS, Sorhage F, Li B (1989) Attenuated induction of heat shock gene expression in aging diploid fibroblasts. J Biol Chem 264:12037–12045 111. Blake MJ, Fargnoli J, Gershon D, Holbrook NJ (1991) Concomitant decline in heatinduced hyperthermia and HSP70 mRNA expression in aged rats. Am J Physiol 260:R663–R667 112. Hall DM, Xu L, Drake VJ, Oberley LW, Oberley TD, Moseley PL, Kregel KC (2000) Aging reduces adaptive capacity and stress protein expression in the liver after heat stress. J Appl Physiol (1985) 89:749–759 113. Kregel KC, Moseley PL, Skidmore R, Gutierrez JA, Guerriero V Jr (1995) HSP70 accumulation in tissues of heat-stressed rats is blunted with advancing age. J Appl Physiol (1985) 79:1673–1678 114. Nitta Y, Abe K, Aoki M, Ohno I, Isoyama S (1994) Diminished heat shock protein 70 mRNA induction in aged rat hearts after ischemia. Am J Physiol 267:H1795–H1803 115. Fawcett TW, Sylvester SL, Sarge KD, Morimoto RI, Holbrook NJ (1994) Effects of neurohormonal stress and aging on the activation of mammalian heat shock factor 1. J Biol Chem 269:32272–32278 116. Locke M, Tanguay RM (1996) Diminished heat shock response in the aged myocardium. Cell Stress Chaperones 1:251–260 117. Hageman J, Rujano MA, van Waarde MA, Kakkar V, Dirks RP, Govorukhina N, Oosterveld-Hut HM, Lubsen NH, Kampinga HH (2010) A DNAJB chaperone subfamily with HDAC-dependent activities suppresses toxic protein aggregation. Mol Cell 37: 355–369 118. Kazemi-Esfarjani P, Benzer S (2000) Genetic suppression of polyglutamine toxicity in Drosophila. Science 287:1837–1840 119. Labbadia J, Novoselov SS, Bett JS, Weiss A, Paganetti P, Bates GP, Cheetham ME (2012) Suppression of protein aggregation by chaperone modification of high molecular weight complexes. Brain 135:1180–1196 120. Chafekar SM, Duennwald ML (2012) Impaired heat shock response in cells expressing full-length polyglutamine-expanded huntingtin. PLoS One 7:e37929 121. Riva L, Koeva M, Yildirim F, Pirhaji L, Dinesh D, Mazor T, Duennwald ML, Fraenkel E (2012) Poly-glutamine expanded huntingtin dramatically alters the genome wide binding of HSF1. J Huntingtons Dis 1:33–45 122. Wang AM, Miyata Y, Klinedinst S, Peng HM, Chua JP, Komiyama T, Li X, Morishima Y, Merry DE, Pratt WB, Osawa Y, Collins CA,

123.

124.

125.

126.

127.

128.

129.

130.

131.

132.

133.

233

Gestwicki JE, Lieberman AP (2013) Activation of Hsp70 reduces neurotoxicity by promoting polyglutamine protein degradation. Nat Chem Biol 9:112–118 Calamini B, Silva MC, Madoux F, Hutt DM, Khanna S, Chalfant MA, Allais C, Ouizem S, Saldanha SA, Ferguson J, Mercer BA, Michael C, Tait BD, Garza D, Balch WE, Roush WR, Morimoto RI, Hodder P (2010) ML346: a novel modulator of proteostasis for protein conformational diseases. In: Probe reports from the NIH Molecular Libraries Program. National Center for Biotechnology Information (US), Bethesda, MD Zhang K, Kaufman RJ (2008) From endoplasmic-reticulum stress to the inflammatory response. Nature 454:455–462 Hotamisligil GS (2010) Endoplasmic reticulum stress and the inflammatory basis of metabolic disease. Cell 140:900–917 Harding HP, Zeng H, Zhang Y, Jungries R, Chung P, Plesken H, Sabatini DD, Ron D (2001) Diabetes mellitus and exocrine pancreatic dysfunction in perk-/- mice reveals a role for translational control in secretory cell survival. Mol Cell 7:1153–1163 Back SH, Scheuner D, Han J, Song B, Ribick M, Wang J, Gildersleeve RD, Pennathur S, Kaufman RJ (2009) Translation attenuation through eIF2alpha phosphorylation prevents oxidative stress and maintains the differentiated state in beta cells. Cell Metab 10:13–26 Alavez S, Vantipalli MC, Zucker DJ, Klang IM, Lithgow GJ (2011) Amyloid-binding compounds maintain protein homeostasis during ageing and extend lifespan. Nature 472:226–229 Schulze A, Harris AL (2012) How cancer metabolism is tuned for proliferation and vulnerable to disruption. Nature 491:364–373 Koong AC, Chauhan V, Romero-Ramirez L (2006) Targeting XBP-1 as a novel anti-cancer strategy. Cancer Biol Ther 5:756–759 Ryno LM, Wiseman RL, Kelly JW (2013) Targeting unfolded protein response signaling pathways to ameliorate protein misfolding diseases. Curr Opin Chem Biol 17:346–352 Calamini B, Silva MC, Madoux F, Hutt DM, Khanna S, Chalfant MA, Saldanha SA, Hodder P, Tait BD, Garza D, Balch WE, Morimoto RI (2012) Small-molecule proteostasis regulators for protein conformational diseases. Nat Chem Biol 8:185–196 Pyrko P, Schonthal AH, Hofman FM, Chen TC, Lee AS (2007) The unfolded protein response regulator GRP78/BiP as a novel target for increasing chemosensitivity in malignant gliomas. Cancer Res 67:9809–9816

234

Emmanouil Kyriakakis et al.

134. Buontempo F, Orsini E, Martins LR, Antunes I, Lonetti A, Chiarini F, Tabellini G, Evangelisti C, Melchionda F, Pession A, Bertaina A, Locatelli F, McCubrey JA, Cappellini A, Barata JT, Martelli AM (2013) Cytotoxic activity of the casein kinase 2 inhibitor CX-4945 against T-cell acute lymphoblastic leukemia: targeting the unfolded protein response signaling. Leukemia 28(3):543–553 135. Vilchez D, Boyer L, Morantte I, Lutz M, Merkwirth C, Joyce D, Spencer B, Page L, Masliah E, Berggren WT, Gage FH, Dillin A (2012) Increased proteasome activity in human embryonic stem cells is regulated by PSMD11. Nature 489:304–308 136. Chung CY, Khurana V, Auluck PK, Tardiff DF, Mazzulli JR, Soldner F, Baru V, Lou Y, Freyzon Y, Cho S, Mungenast AE, Muffat J, Mitalipova M, Pluth MD, Jui NT, Schule B, Lippard SJ, Tsai LH, Krainc D, Buchwald SL, Jaenisch R, Lindquist S (2013) Identification

and rescue of alpha-synuclein toxicity in Parkinson patient-derived neurons. Science 342:983–987 137. Heijmans J, Lidth v, de Jeude JF, Koo BK, Rosekrans SL, Wielenga MC, van de Wetering M, Ferrante M, Lee AS, Onderwater JJ, Paton JC, Paton AW, Mommaas AM, Kodach LL, Hardwick JC, Hommes DW, Clevers H, Muncan V, van den Brink GR (2013) ER stress causes rapid loss of intestinal epithelial stemness through activation of the unfolded protein response. Cell Rep 3:1128–1139 138. Rouault-Pierre K, Lopez-Onieva L, Foster K, Anjos-Afonso F, Lamrissi-Garcia I, SerranoSanchez M, Mitter R, Ivanovic Z, de Verneuil H, Gribben J, Taussig D, Rezvani HR, Mazurier F, Bonnet D (2013) HIF-2alpha protects human hematopoietic stem/progenitors and acute myeloid leukemic cells from apoptosis induced by endoplasmic reticulum stress. Cell Stem Cell 13:549–563

Chapter 17 Targeting Stress Responses for Regenerative Medicine Irina Milisav, Samo Ribarič, and Dušan Šuput Abstract Some internal and external stimuli elicit stress responses on the cellular level and at the level of the organism. When the stimulus is brief and its intensity mild to moderate, it triggers adaptation changes that improve the cell’s or organism’s survival. This adaptation is achieved through a variety of cellular mechanisms such as induction of repair mechanisms, improved removal of damaged macromolecules, upregulation of endogenous antioxidant defenses, and prevention of apoptosis triggering by moderate stressors. The key intracellular signaling pathways involved in stress adaptation are the mTORC1 and SIRT1. Manipulating these stress adaptation signaling pathways with a variety of agents, improves the cellular adaptation to stress, prolongs cell survival, and improves the transplantation outcome in animal models and in clinical trials. The challenge for the future is to fine-tune the numerous experimental techniques to suit the needs of transplantation and regenerative medicine. Key words Stress, Regenerative medicine, Transplantation, Stem cells, Stress response

1

Introduction Organisms and their cells are exposed to many internal and external stimuli, some of which may induce stress. Stress responses are homeostatic mechanisms used by organisms and cells to adapt to and to overcome stress stimuli. Cellular stress responses differ depending on the type of stress, severity, and duration of stress encountered [1, 2]. Then the cells either reestablish cellular homeostasis to the former state or adopt an altered state in the new environment [3]. The cellular responses to stress can be undetected, trigger adaptations to stressors, or result in cell death. The cells, tissues, and organisms may benefit from adaptive stress responses, provided they do not last for extensive amounts of time. For example, mild oxidative stress may increase cell proliferation, while moderate oxidative stress may result in stress adaptation that increases the resistance of cells to subsequent insults. The adaptive stress responses include induction of cell repair mechanisms, improved removal of damaged macromolecules by induced autophagy,

Christine M. Oslowski (ed.), Stress Responses: Methods and Protocols, Methods in Molecular Biology, vol. 1292, DOI 10.1007/978-1-4939-2522-3_17, © Springer Science+Business Media New York 2015

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increased oxidative stress protection through upregulation of endogenous antioxidant defenses, improved resilience to apoptosis triggering by moderate stressors, etc. [1]. Adaptation to stress can improve the survival of stress adapted cells in the presence of moderate stressors. The cells and tissues used in regenerative medicine are likely to be exposed to stressors during handling, or in the recipient when transplanted, and this excess stress could have contributed to the pathology that was treated by transplantation.

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Basic Stress Adaptation Mechanisms Adaptation to stress is achieved mainly through induction of repair mechanisms, improved removal of damaged macromolecules, upregulation of endogenous antioxidant defenses, and prevention of apoptosis triggering by moderate stressors [1]. This is accomplished through a tight regulation of processes like transcription, protein folding, repair, and degradation of damaged intracellular components. Two of the key integrators of these processes are the complexes of the kinase TOR (mechanistic target of rapamycin, mTORC1 and mTORC2) (reviewed in ref. 4) and deacetylases sirtuins (SIRT), mainly SIRT 1 (reviewed in ref. 5). mTOR signaling pathways integrate many environmental cues to regulate organismal growth and homeostasis. Of the two TOR complexes, the mTORC1 is better characterized and integrates inputs from growth factors, stressors, energy status, amino acids, and oxygen availability. When active, mTORC1 promotes protein synthesis, lipogenesis, and energy metabolism and inhibits autophagy and lysosome biogenesis (Fig. 1). Numerous kinases modulate the activity of mTORC1, some through modulation of a complex composed of proteins tuberous sclerosis 1 and 2 (TSC1/2), an inhibitor of mTORC1. For example, availability of nutrients and growth factors stimulate the activity of mTORC1, while various stressors, like nutritional stress, hypoxia, and energy deficit inhibit mTORC1. Inflammation, genotoxic stress, and availability of heat shock proteins (HSP) also influence the activity of mTORC1 [5]. Excess nutrition or reduced chaperone availability (e.g., during increased amounts of unfolded or damaged proteins) causes imbalance between the assembly and disassembly of mTORC1. mTORC2 is activated by growth factors and regulates cytoskeletal organization, metabolism, and survival through phosphorylation of downstream kinases, including Akt and PKC-α. mTORC2 cross-talks with mTORC1 through its downstream kinases and by modulating the activity of TSC1/2 complex. The regulation of homeostatic processes reflects their complexity and is regulated also at the transcriptional level, where the main signal integrators are deacetylases sirtuins, which link metabolic status to the regulation of longevity. The activity of

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Fig. 1 Basic mechanisms of adaptation to stress. Stressors induce one or more stress pathways (red rectangles) to trigger kinase signaling/inducing the transcription of key transcription regulators/reducing the availability of heat shock proteins (ellipses) resulting in adaptive stress response [1, 2, 4, 5]. mTORC1, mTORC2 (mechanistic target of rapamycin, complex 1 and 2), SIRT1 (sirtuin 1), TSC1, TSC2 (tuberous sclerosis 1 and 2); kinases: PKC-α, Akt, SGK1, IKBKB, AMPK, JNK; transcription factors: HSF1 (heat shock factor 1), p53 (transformation-related protein 53), FOXO (forkhead family of transcription factors); HSP (heat shock proteins), SESN (sestrins)

SIRT1 is modulated by nutrient availability and is altered during ageing [5]. SIRT1 regulates activities of many transcription factors involved in cellular stress responses, like heat shock factor 1 (HSF1), transformation-related protein 53 (p53), forkhead family of transcription factors (FOXO), and nuclear factor-κB complex (NF-κB) [1, 2, 5]. The interconnection of stress signaling pathways may explain the observation that moderate stress can trigger cellular adaptations, which improve the chances of survival under the subsequent stress conditions caused by the same or different stressor. Such cross-resistance has been observed many times and is triggered by stressors including oxidants, UV radiation, heat shock, some phytochemicals, ischemia, exercise, and dietary energy restriction as well as hypergravity (reviewed in ref. 1). Cellular processes that prevent excessive oxidative stress and inhibit apoptosis caused by mild stressors can also contribute to adaptation to stress. Milisav and coworkers have described that

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adaptation to stress in primary hepatocytes involves the inhibition of apoptosis triggering through the intrinsic/mitochondrial pathway [6, 7]. Upon encountering mild stress, one of the main apoptosis initiators, caspase-9 is shifted from cytoplasm into the nucleus. Then, caspase-9 is activated only after the activation of the main apoptosis execution caspase, caspase-3 in the stress-adapted cells [6]. In contrast to mildly stressed cells, in the unstressed cells, when caspase-9 is located in the cytoplasm, apoptosis can be triggered through the mitochondrial pathway by activation of the caspase-9 first. Therefore, the mitochondrial pathway of triggering apoptosis is inactivated as the consequence of adaptation to stress, while apoptosis can still be triggered by a more intense trigger than it is needed for the same effect in normal cells through a pathway which activates caspase-3 first. Cells can also evade apoptosis by activating the so-called antiapoptotic genes and proteins, which can temporarily block cell death [1, 8–10]. There are many such genes and proteins, including (1) anti-apoptotic proteins, like B cell lymphoma-2 family members (BCL2), inhibitors of apoptosis proteins (IAPs), FLICEinhibitory proteins (FLIPs), and (2) ROS scavengers, like peroxiredoxin, glutaredoxins, glutathione peroxidase, superoxide dismutase, and sphingomyelin synthase 1 (SMS1). Detailed information is included in many reviews on these topics [5, 8–12].

3

Induction of Stress Responses in Clinical Settings Stress adaptations seem to improve the outcome of transplantations [2]. For example, cold ischemia pretreatment correlates with increased regeneration of epithelial cells immediately after the transplantation of kidney allografts [13]. On the other hand, attenuation of stress adaptation with age results in a lesser survival of kidney grafts and decreases the chances of successful kidney transplantation [13]. Many processes associated with ageing affect pathways involved in tissue damage and stress responses; examples include changes in mitochondrial physiology, increased susceptibility to apoptosis, impaired regeneration and repair, and replicative senescence. Ischemia pretreatment, or preconditioning ischemia, is a common method of inducing adaptation to stress in an organism. It is being tested in clinical practice to decrease the ischemia–reperfusion injury, for example after a full-blown heart attack or brain stroke [1, 14]. The beneficial effects were first described in heart [15] and in brain slices; nowadays there are many reports of ischemic preconditioning, of heart, brain, kidney, and liver (ref. 1 and the references therein). When an organ is exposed to a brief period of moderate ischemia, the cells become more resistant to a larger subsequent ischemia [1]. It is even more important in clinical practice

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when the protective ischemia is initiated in a remote organ to protect other organs. For example, limb ischemia, induced by inflation of a blood pressure cuff, can reduce myocardial ischemic injury as well; this procedure is described as a remote ischemic conditioning [16]. Even the ischemic preconditioning applied after the event that resulted in ischemic damage, i.e., ischemic post-conditioning seems to reduce the damage in heart and brain [1, 16–18]. Apart from ischemia, other environmental factors can improve the performance of cardiovascular system upon stress, e.g., caloric restriction, exercise [19, 20]. The protective adaptation to stress can be initiated also by heat stress, adrenergic drugs, and even noise [21]. Increased hydrostatic pressure improves the survival of murine and bovine blastocysts after freezing or in suboptimal culture conditions [22]. Caloric restriction and exercise can induce oxidative and metabolic stresses by activating stress resistance pathways in cells of different organs [19, 23]. Sustained exercise can result in upregulation of antioxidant enzymes, like superoxide dismutase and glutathione peroxidase and increase cellular concentrations of glutathione [23]. The mechanisms of cross-resistance are important to induce beneficial adaptations to stress, which include the upregulation of cellular defenses to oxidative stress. On the other hand, there are many examples that the externally added antioxidants are not beneficial or are even harmful [24]. Many clinical trials with one or more synthetic antioxidants have failed to demonstrate any beneficial effects of these substances; often the synthetic antioxidants increased adverse effects in the group they were supposed to protect (i.e., heavy smokers, employees exposed to some carcinogens). There are some clues from experimental work as to why exogenous antioxidants can be harmful. Epithelial cells that detach from the extracellular matrix normally lose their ability of glucose uptake resulting in ATP deficiency. However, they can survive by antioxidant treatment, which stimulates fatty acid oxidation otherwise inhibited by detachment-induced reactive oxygen species (ROS) [25]. Repeated brief periods of ischemia/reperfusion led to a quicker return of contractile function of pig hearts on reperfusion, while this adaptive response was not seen in the antioxidant treated conscious animals [26].

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Examples of Pretreatment Protocols for Stress Adaptation in Regenerative Medicine Pretreatment of cells can modulate stress response pathways, thus minimizing cellular damage and improving transplantation outcome. The effectiveness of pretreatment protocols has been successfully demonstrated in a variety of cells, tissues, and organs of

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Table 1 Examples of successful pretreatment protocols Cells/tissue/organ (species)

Pretreatment protocol

Reference

Bone marrow mesenchymal stem cells (rat)

10 μM trimetazidine for 6 h

[32]

Cardiac progenitor cells (mouse)

6 h of hypoxia

[31]

Cultured liver tissue (rat)

Optimal shear stress

[28]

Endothelial progenitor cells (human)

1–10 nM of bradykinin for 10 min

[33]

Kidney (mouse)

Overexpression of HSP 90-binding agent geldanamycin

[35]

Kidney (rat)

Heat preconditioning at 42 °C for 20 min

[29]

Liver (rat)

50 μmol/kg of tin-protoporphyrin IX

[30]

Mesenchymal stem cells (rat)

Overexpression of Hsp20

[36]

Retinal cells (cell line ARPE-19)

A single dose of 1, 10, or 50 μM of H2O2

[27]

Skeletal myoblasts (human)

10–200 ng/mL of hSDF-1α for 1–4 h

[34]

different species and with different physical, chemical, or pharmacological agents (see Table 1 and the text below). Preconditioning of retinal pigment epithelium cells ARPE-19 with nonlethal oxidative stress induced by exposure to a single dose of 1, 10, and 50 μM of H2O2 provided a dose-dependent protection against cell death induced by a lethal dose (900–1,000 μM) of H2O2. This finding may be relevant for limiting cell death by oxidative-stress during transplantation of retinal cells transplanted for repairing the age-related macular degeneration [27]. The application of moderate shear stress on cultured liver tissue slices improved cell survival more than no shear or high shear stress; no shear stress or high shear stresses caused the loss of liverspecific function in tissue slices soon after expression [28]. Therefore, during surgery, perioperative liver perfusion management has to provide an optimal shear stress, i.e., to avoid the excessive shear stress on liver tissue upon a massive liver resection [28]. Kidney graft function and survival are significantly reduced after 24 h of storage in cold University of Wisconsin solution at 4 °C. This time limit was extended in an animal model by heat preconditioning (42 °C for 20 min) of rats resulting in the induction of heme oxygenase-1 (HO-1) and improved outcome following kidney isotransplantation after 45 h of cold storage [29]. HO-1 has also been shown to increase cellular resistance against oxidative injury in rat liver cells. Lewis rats were treated with 50 μmol/kg of tin-protoporphyrin IX (SnP) which induced gene expression and

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protein synthesis of HO-1 in Kupffer-like dendritic cells. Pretreatment with SnP improved viability of 30 h old liver grafts through inhibition of inflammatory adhesion molecules [30]. Cardiac progenitor cells are used in stem cell therapy of ischemic myocardium, but their effectiveness is limited by poor retention of transplanted cells. Hypoxia preconditioning of cardiac progenitor cells for 6 h significantly enhanced cell anti-apoptosis and migration in vitro, and their in vivo survival and cardiac function after being transplanted into acute myocardial infarction mice [31]. Preconditioning of rat bone marrow-derived rat mesenchymal stem cells with trimetazidine (TMZ), which is used for treating angina in cardiac patients, increased the rate of cell survival after transplantation. The cells were preconditioned with 10 μM TMZ for 6 h after which they displayed an increased tolerance against H2O2induced loss of cellular viability, membrane damage, and oxygen metabolism accompanied by a significant increase in HIF-1 alpha, survivin, phosphorylated Akt (pAkt), and Bcl-2 protein levels and Bcl-2 gene expression. Also, there was a significant increase in the recovery of myocardial function and upregulation of pAkt and Bcl-2 levels in rat hearts transplanted with these preconditioned cells [32]. Human endothelial progenitor cell preconditioning reduces cell death after transplantation. Bradykinin preconditioning, 1–10 nM for 10 min, activates the B2 receptor-dependent PI3K/ Akt/eNOS pathway, promotes VEGF secretion, promotes human endothelial progenitor cells survival, and inhibits apoptosis, thereby improving cardiac function of mice in vivo [33]. Preconditioning of human skeletal myoblast for 1–4 h with 10–200 ng/mL of human chemokine stromal cell-derived factor-1α (hSDF-1α) or transfection with hSDF-1α, promotes cytoprotective effects against oxidative and anoxic stress. Increased cell survival under anoxic conditions in vitro was mediated by the Akt/Bcl2 signaling pathways and increased oxidative stress tolerance was promoted by an increased release of VEGF [34]. Overexpression of HSP increases the cells’ tolerance to oxidative stress and ischemia. For example, overexpression of HSP 90-binding agent geldanamycin and some of its analogs protected renal cells from oxidative stress and reduced kidney ischemia– reperfusion injury in a mouse model [35]. Rat mesenchymal stem cells that overexpressed Hsp 20 were also more resistant to oxidative stress and had a twofold increased survival rate after transplantation into the infarcted heart [36].

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Conclusions Adaptation to stress can improve the survival of stress adapted cells in the presence of moderate stressors. This adaptation is achieved through induction of repair mechanisms, improved removal of

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damaged macromolecules, upregulation of endogenous antioxidant defenses, and increased protection by apoptosis triggering. Manipulating the stress response mechanisms, with a variety of agents, improves the cellular adaptation to stress, prolongs cell survival, and improves the transplantation outcome in animal models and in clinical trials. The challenge for the future is to fine-tune the experimental techniques to suit the needs of regenerative medicine. References 1. Milisav I, Poljsak B, Suput D (2012) Adaptive response, evidence of cross-resistance and its potential clinical use. Int J Mol Sci 13: 10771–10806 2. Milisav I (2011) Cellular stress responses. In: Wislet-Gendebien S (ed) Advances in regenerative medicine, InTech, Rijeka, Croatia. pp 215–232 3. Kültz D (2003) Evolution of the cellular stress proteome: from monophyletic origin to ubiquitous function. J Exp Biol 206:119–124 4. Laplante M, Sabatini DM (2012) mTOR signaling in growth control and disease. Cell 149:274–293 5. Kourtis N, Tavernakis N (2011) Cellular stress response pathways and ageing: intricate molecular relationships. EMBO J 30:2520–2531 6. Nipic D, Pirc A, Banic B et al (2010) Preapoptotic cell stress response of primary hepatocytes. Hepatology 51:2140–2151 7. Banič B, Nipič D, Suput D et al (2011) DMSO modulates the pathway of apoptosis triggering. Cell Mol Biol Lett 16:328–341 8. Portt L, Norman G, Clapp C et al (2011) Anti-apoptosis and cell survival: a review. Biochim Biophys Acta 1813:238–259 9. Fulda S, Gorman AM, Hori O et al (2010) Cellular stress responses: cell survival and cell death. Int J Cell Biol. doi:10.1155/2010/214074 10. Fulda S (2010) Evasion of apoptosis as a cellular stress response in cancer. Int J Cell Biol 2010:370835 11. Stancevic B, Kolesnick R (2010) Ceramiderich platforms in transmembrane signaling. FEBS Lett 584:1728–1740 12. Nikolova-Karakashian MN, Rozenova KA (2010) Ceramide in stress response. Adv Exp Med Biol 688:86–108 13. Naesens M (2011) Replicative senescence in kidney aging, renal disease, and renal transplantation. Discov Med 11:65–75 14. Murry CE, Richard VJ, Reimer KA et al (1990) Ischemic preconditioning slows energy metabolism and delays ultrastructural damage

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

during a sustained ischemic episode. Circ Res 66:913–931 Murry CE, Jennings RB, Reimer KA (1986) Preconditioning with ischemia: a delay of lethal cell injury in ischemic myocardium. Circulation 74:1124–1136 Gerczuk PZ, Kloner RA (2012) An update on cardioprotection: a review of the latest adjunctive therapies to limit myocardial infarction size in clinical trials. J Am Coll Cardiol 59: 969–978 Ding ZM, Wu B, Zhang WQ et al (2012) Neuroprotective effects of ischemic preconditioning and postconditioning on global brain ischemia in rats through the same effect on inhibition of apoptosis. Int J Mol Sci 13: 6089–6101 Wagner C, Tillack D, Simonis G et al (2010) Ischemic post-conditioning reduces infarct size of the in vivo rat heart: role of PI3-K, mTOR, GSK-3beta, and apoptosis. Mol Cell Biochem 339:135–147 Abete P, Rengo F (2008) Mild stress in the aging heart. Role of ischemic preconditioning. In: Le Bourg E, Rattan S (eds) Mild stress and healthy aging. Springer, Heidelberg, pp 139–155 Radak Z, Chung HY, Koltai E et al (2008) Exercise, oxidative stress and hormesis. Ageing Res Rev 7:34–42 Raeburn CD, Zimmerman MA, Banerjee A et al (2004) Surgical applications of organ preconditioning. Minerva Chir 59:209–218 Pribenszky C, Vajta G (2011) Cells under pressure: how sublethal hydrostatic pressure stress treatment increases gametes’ and embryos’ performance. Reprod Fertil Dev 23:48–55 Powers SK, Ji LL, Leeuwenburgh C (1999) Exercise training-induced alterations in skeletal muscle antioxidant capacity: a brief review. Med Sci Sports Exerc 31:987–997 Poljsak B, Milisav I (2012) The neglected significance of “antioxidative stress”. Oxid Med Cell Longev. doi:10.1155/2012/480895

Targeting Stress Responses 25. Schafer ZT, Grassian AR, Song L et al (2009) Antioxidant and oncogene rescue of metabolic defects caused by loss of matrix attachment. Nature 461:109–113 26. Sun JZ, Tang XL, Park SW et al (1996) Evidence for an essential role of reactive oxygen species in the genesis of late preconditioning against myocardial stunning in conscious pigs. J Clin Invest 97:562–576 27. Sharma RK, Netland PA, Kedrov MA et al (2009) Preconditioning protects the retinal pigment epithelium cells from oxidative stressinduced cell death. Acta Ophthalmol 87: 82–88 28. Torii T, Miyazawa M, Koyama I (2005) Effect of continuous application of shear stress on liver tissue: continuous application of appropriate shear stress has advantage in protection of liver tissue. Transplant Proc 37:4575–4578 29. Wagner M, Cadetg P, Ruf R et al (2003) Heme oxygenase-1 attenuates ischemia/reperfusioninduced apoptosis and improves survival in rat renal allografts. Kidney Int 63:1564–1573 30. Uchida Y, Tamaki T, Tanaka M et al (2003) Induction of specific stress response increases resistance of rat liver allografts to cold ischemia and reperfusion injury. Transpl Int 16:396–404 31. Yan F, Yao Y, Chen L et al (2012) Hypoxic preconditioning improves survival of cardiac

32.

33.

34.

35.

36.

243

progenitor cells: role of stromal cell derived factor-1α-CXCR4 axis. PLoS One 7:e37948 Wisel S, Khan M, Kuppusamy ML et al (2009) Pharmacological preconditioning of mesenchymal stem cells with trimetazidine (1-[2,3,4-trimethoxybenzyl]piperazine) protects hypoxic cells against oxidative stress and enhances recovery of myocardial function in infarcted heart through Bcl-2 expression. J Pharmacol Exp Ther 329:543–550 Sheng Z, Yao Y, Li Y et al (2013) Bradykinin preconditioning improves therapeutic potential of human endothelial progenitor cells in infarcted myocardium. PLoS One 8:e81505 Elmadbouh I, Haider HK, Ashraf M et al (2011) Preconditioning of human skeletal myoblast with stromal cell-derived factor-1α promotes cytoprotective effects against oxidative and anoxic stress. Int J Stem Cells 4:50–60 Harrison EM, Sharpe E, Bellamy CO et al (2008) Heat shock protein 90-binding agents protect renal cells from oxidative stress and reduce kidney ischemia-reperfusion injury. Am J Physiol Renal Physiol 295:F397–F405 Wang X, Zhao T, Huang W et al (2009) Hsp20-engineered mesenchymal stem cells are resistant to oxidative stress via enhanced activation of Akt and increased secretion of growth factors. Stem Cells 27:3021–3031

INDEX A

D

Activating transcription factor 6 (ATF6)..................... 4, 5, 8, 11, 12, 18–23, 26–27, 29, 30, 33, 34, 36, 177, 206, 207, 217, 221 Adenovirus ............................................................. 57, 58, 62 Agarose gel electrophoresis......................... 63, 183, 187–188 Ageing ...................................................... 215–228, 237, 238 Aggregation suppression.....................................................50 Annexin V ................. 107, 110–112, 152, 153, 155, 156, 159 Antibodies .................................. 8, 12, 14, 17, 18, 35, 55–57, 60, 63, 69–73, 98–100, 102, 107, 109, 112, 117, 121, 132, 139–143, 145–148, 154, 156, 159, 160, 179–180, 183–186, 189–191, 196, 209 Apoptosis................................................21, 24, 25, 111, 127, 147, 151–160, 166, 169, 174, 178, 206, 210, 217, 221, 222, 226, 227, 236–238, 241, 242 Argonaute .........................................................................115 ATF5. See Activating transcription factor 6 (ATF6) Autophagosomes ............................................. 129, 130, 135, 138, 139, 141–145, 147 Autophagy ................................................ 129–148, 235, 236

Deoxyribonucleic acid (DNA) damage .................................................21, 68, 69, 71, 73, 77–95, 97, 98, 127, 151, 178, 206 end resection ...........................................................67–74 fragmentation .....................................................166–171 repair................................................................. 69, 79, 82 Diabetes..................22, 97, 165, 166, 176, 211, 222, 226, 227 DNA double-strand break (DSB) ................................77–79 Dual-luciferase reporter assay ........... 116, 118–119, 125, 126

E ELISA ...................................................... 106–107, 109, 111 Endoplasmic reticulum (ER) ............................. 3, 19, 20, 24, 25, 97, 134, 166, 178, 205, 216, 220–223 ERN1 ER stress ............. 3–22, 24–33, 134, 164, 167–169, 177, 178, 186, 190, 192, 205–212, 216, 217, 220–224, 226, 227

F

5-bromo-2´-deoxyuridine (BrdU) .................... 69, 70, 72–74

Flow cytometry.........................................107, 110, 152, 156, 159, 168, 169, 171, 175 Fluorescence microscopy .........28–30, 69, 107, 130, 152, 156 Fluorescent probes ....................................................151–160

C

H

Caspase activity ........................................ 152–154, 156–159 Cell culture ...............................25–26, 57–58, 60, 62, 70–71, 84, 106, 109, 116, 131, 134, 143, 153–155, 159, 225 Cell death .........................................22, 24, 26, 67, 105–107, 110–111, 133, 151, 166, 169, 174, 196, 206, 211, 222, 223, 235, 238, 240, 241 Cell stress ..........................................106, 107, 109, 159, 166 Cellular homeostasis .................................................151, 235 Chaperone assay .................................................................45 Chaperone function ......................................................39–50 Chaperones ......................... 20, 21, 24, 26, 39–42, 44–50, 53, 169, 177, 178, 205, 206, 216, 217, 219, 221, 222, 225 Chromatin immunoprecipitation (ChIP) ......... 54, 60–61, 79 Chromatin mobility ............................................................89 Chromium release assay............................................172–174 Citrate synthase ............................................................40–43 CLIP-seq.................................................. 115–118, 121–124 Cytotoxicity assay .............. 107, 111, 113, 166, 167, 170–173 Cytotoxic T lymphocytes (CTL) ......................................166

Heat shock ........ 39, 40, 53–63, 216–220, 225, 226, 236, 237 Heat shock response (HSEs) ...................... 53, 216–220, 226 Homologous recombination (HR) ...............................68, 77

B

I Immunity.......................................... 206, 208–209, 222, 224 Immunoblot.............................................. 183–184, 186, 190 Immunocytochemistry......................................................132 Immunohistochemistry ............................. 97–103, 132, 145, 179, 183, 189–190, 192 Immunostaining ...................................................71–72, 102 Inflammasome .......................................... 105–113, 217, 226 Inflammation ............. 205–212, 217, 222–223, 226, 227, 236 Inflammatory disease ................................................210, 223 Inositol equiring enzyme 1 (IRE1)........................ 4, 5, 9, 10, 16, 20–24, 27–29, 31–34, 177–192, 206 inhibitors .................................................. 23, 31, 32, 180 Interleukin-1beta (IL-1β)................................ 105–112, 166, 210, 211, 223, 226

Christine M. Oslowski (ed.), Stress Responses: Methods and Protocols, Methods in Molecular Biology, vol. 1292, DOI 10.1007/978-1-4939-2522-3, © Springer Science+Business Media New York 2015

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STRESS RESPONSES: METHODS AND PROTOCOLS 246 Index K

Q

Knockdown ........................................................... 33, 35, 55, 59, 62, 134–138, 143, 148

Quantitative real-time PCR (qRT-PCR) .................... 27, 28, 31, 33–35

L

R

Lipid peroxidation ........................................................97, 98

Reactive oxygen species (ROS).......................... 97–103, 106, 127, 166, 207, 239 Regenerative medicine..............................................235–242 Replication protein A (RPA) ...................... 54, 68–71, 73, 74 RNA extraction .........................116, 119, 182–183, 186–188

M Mean-square displacement analysis ..............................79–81 Metabolic diseases ............................................ 210–211, 226 MicroRNA ............................................... 115–127, 178, 206 Mitochondrial release ....................................... 153, 155, 159

N Nitric oxide (NO) ............................................. 196–198, 200 Nitrosothiols .............................................................196–200 Nuclear pore clustering.......................................................88 Nucleosome ..................................................................54, 80

O Oxidative stress........................... 19, 21, 53, 98, 99, 101, 105, 110, 166–169, 195, 205–212, 216, 235–237, 239–241

P Pancreatic ER kinase (PERK) ............................. 4, 5, 19–23, 30–31, 33, 177, 206–208, 210, 217, 221, 222, 226, 227 Pancreatic islets................................................. 166, 168, 211 Parkinson’s disease (PD) ......................22, 195–200, 216, 225 Plasmids .......................................................... 23, 27–29, 35, 117–119, 121, 125, 131, 135, 136, 144, 183 Protein aggregation ...............................39, 40, 195, 224, 227 Protein folding............................................... 19, 41, 53, 177, 178, 205–207, 216, 220, 226, 227, 236 Protein isolation ...................................................................7 Protein refolding..................................................... 41, 47, 48 Proteostasis .......................................................... 52, 54, 216, 218–221, 224–227 Proteotoxic stress .........................53, 215, 216, 222, 224–227 Pyroptosis ......................................................... 105, 110, 111

S Single stranded DNA (ssDNA) .........................................68 siRNAs ............................................................. 131, 135, 180 S-nitrosylation .................................................. 196, 198–200 Stem cells ......................................................... 227, 240, 241 Stress adaptation.......................................................235–241 Stress response ...............3, 130, 207–211, 215–228, 235–242

T Transfection ............................................... 24, 26–30, 34, 35, 116, 125, 135, 136, 143, 144, 188, 241 Transplantation................................................. 236, 238–241

U Unfolded protein response (UPR) ........................... 3, 19–36, 148, 206, 216, 220–223

W Western blot ................................. 4, 7–8, 11–14, 31, 35, 109, 130, 131, 133, 136, 138–141, 148, 182, 185, 198–200

X XBP1 ........................................ 4–6, 9, 10, 16, 20–23, 26–29, 31–34, 36, 178–180, 186–188, 191, 192, 206–211 splicing ........................ 4–6, 9, 10, 16, 27, 28, 31–34, 187

Y Yeast cells.................................................... 80, 81, 83, 84, 88