Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants [1 & 2] 1119329701, 9781119329701

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Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants Volume I

Edited by

Yvonne Will, PhD, ATS Fellow Pfizer Drug Safety R&D, Groton, CT, USA

James A. Dykens Eyecyte Therapeutics Califormia, USA

This edition first published 2018 © 2018 John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions. The right of Yvonne Will and James A. Dykens to be identified as the editors of this work has been asserted in accordance with law. Registered Office John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA Editorial Office 111 River Street, Hoboken, NJ 07030, USA For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com. Wiley also publishes its books in a variety of electronic formats and by print‐on‐demand. Some content that appears in standard print versions of this book may not be available in other formats. Limit of Liability/Disclaimer of Warranty In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of experimental reagents, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each chemical, piece of equipment, reagent, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Library of Congress Cataloging‐in‐Publication Data Names: Will, Yvonne, editor. | Dykens, James Alan, 1951– editor. Title: Mitochondrial dysfunction caused by drugs and environmental toxicants / edited by Yvonne Will, James A. Dykens. Description: Hoboken, NJ : John Wiley & Sons, 2018. | Includes bibliographical references and index. | Identifiers: LCCN 2017046043 (print) | LCCN 2017048850 (ebook) | ISBN 9781119329732 (pdf ) | ISBN 9781119329749 (epub) | ISBN 9781119329701 (cloth) Subjects: LCSH: Drugs–Toxicology. | Mitochondrial pathology. Classification: LCC RA1238 (ebook) | LCC RA1238 .M58 2018 (print) | DDC 615.9/02–dc23 LC record available at https://lccn.loc.gov/2017046043 Cover Design: Wiley Cover Image: Courtesy of Sylvain Loric Set in 10/12pt Warnock by SPi Global, Pondicherry, India Printed in the United States of America 10

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Contents List of Contributors xvii Foreword xxix

Part 1

Basic Concepts 1

1

Contributions of Plasma Protein Binding and Membrane Transporters to Drug‐Induced Mitochondrial Toxicity 3 Gavin P. McStay

1.1 1.2 1.3 1.4 1.5 1.6 1.7

Drug Accumulation 3 Small Molecule Delivery to Tissues Entry into Cells 7 Transport Out of Cells 8 Entry into Mitochondria 10 Export from Mitochondria 11 Concluding Remarks 11 References 11

2

The Role of Transporters in Drug Accumulation and Mitochondrial Toxicity Kathleen M. Giacomini and Huan‐Chieh Chien

2.1 2.2 2.3 2.4 2.5 2.6 2.6.1 2.6.2 2.7 2.8

Introduction to Chapter 15 The Solute Carrier (SLC) Superfamily 15 Transporters as Determinants of Drug Levels in Tissues and Subcellular Compartments 17 Drug Transporters in the Intestine 18 Drug Transporters in the Liver 18 Drug Transporters in the Kidney 19 Conservation Mechanisms 19 Detoxification Mechanisms 20 Mitochondrial Transporters 20 Conclusions 22 References 22

3

Structure–Activity Modeling of Mitochondrial Dysfunction 25 Steve Enoch, Claire Mellor, and Mark Nelms

3.1 3.1.1 3.1.2 3.2 3.2.1 3.2.2 3.3 3.3.1 3.3.2

Introduction 25 Mitochondrial Structure and Function 26 Mechanisms of Mitochondrial Toxicity 26 Mitochondrial Toxicity Data Sources 26 Zhang Dataset 26 ToxCast Data 27 In Silico Modeling of Mitochondrial Toxicity 27 Statistical Modeling 27 Structural Alert Modeling 27

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Contents

3.4 3.5 3.6 3.7

Mechanistic Chemistry Covered by the Existing Structural Alerts 31 Structural Alert Applicability Domains: Physicochemical Properties 33 Future Direction: Structure–Activity Studies for Other Mechanisms of Mitochondrial Toxicity 33 Concluding Remarks 33 References 34

4

Mitochondria‐Targeted Cytochromes P450 Modulate Adverse Drug Metabolism and Xenobiotic‐Induced Toxicity 35 Haider Raza, F. Peter Guengerich, and Narayan G. Avadhani

4.1 4.2 4.3 4.3.1 4.3.2 4.3.3 4.3.4 4.3.5 4.3.6 4.4 4.5 4.6 4.7

Introduction 35 Multiplicity of Mitochondrial CYPs 36 Targeting and Significance of Multiple Forms of Mitochondrial CYPs 36 Mitochondrial Import of CYP1A1 38 Mitochondrial Import of CYP1B1 39 Mitochondrial Import of CYP2C8 39 Mitochondrial Import of CYP2D6 39 Mitochondrial Import of CYP2B1 and CYP2E1 40 Import Mechanism of GSH‐Conjugating GSTA4‐4 40 Variations in Mitochondrial CYPs and Drug Metabolism 40 Physiological and Toxicological Significance of Mitochondria‐Targeted CYPs 41 Mitochondrial CYPs and Cell Signaling 42 Conclusion 42 Acknowledgment 43 References 43

Part 2

Organ Drug Toxicity: Mitochondrial Etiology 47

5

Mitochondrial Dysfunction in Drug‐Induced Liver Injury 49 Annie Borgne‐Sanchez and Bernard Fromenty

5.1 5.2 5.2.1 5.2.2 5.2.3 5.2.4 5.3 5.3.1 5.3.2 5.3.3 5.4 5.4.1 5.4.2 5.4.3 5.4.4 5.4.5 5.4.6 5.4.7 5.4.8 5.4.9 5.4.10 5.5

Introduction 49 Structure and Physiological Role of Mitochondria 49 Structure and Main Components of Mitochondria 49 Oxidation of Pyruvate and Fatty Acids 50 Production of ATP 50 Production of ROS as Signaling Molecules 51 Main Consequences of Hepatic Mitochondrial Dysfunction 51 Consequences of Mitochondrial β‐Oxidation Inhibition 51 Consequences of MRC Inhibition 52 Consequences of Mitochondrial Membrane Permeabilization 52 Main Hepatotoxic Drugs Inducing Mitochondrial Dysfunction 53 Acetaminophen 53 Amiodarone 56 Fialuridine 57 Linezolid 57 Nucleoside Reverse Transcriptase Inhibitors 58 Tamoxifen 59 Tetracycline 60 Troglitazone 60 Valproic Acid 61 Other Hepatotoxic Drugs 62 Conclusion 62 References 63

Contents

6

Evaluating Mitotoxicity as Either a Single or Multi‐Mechanistic Insult in the Context of Hepatotoxicity 73 Amy L. Ball, Laleh Kamalian, Carol E. Jolly, and Amy E. Chadwick

6.1 6.2 6.2.1 6.2.2 6.2.2.1 6.2.2.2 6.2.2.3 6.2.3 6.2.4 6.3

Introduction 73 Important Considerations When Studying Drug‐Induced Mitochondrial Toxicity in the Liver 74 Xenobiotic Metabolism 74 Biliary System 75 Mechanisms of Bile Acid and Bile Salt‐Mediated Mitochondrial Toxicity 76 Bile Acid Accumulation Following Mitochondrial Perturbation 76 Bile Acid Toxicity Resulting from Dual Inhibition of Mitochondrial Function and Bile Salt Export 76 Lysosome/Mitochondria Interplay 76 Chronic Toxicity 77 Current and Emerging Model Systems and Testing Strategies to Identify Hepatotoxic Mitotoxicants 78 6.3.1 Mitochondrial Models 78 6.3.1.1 Whole Cell Models 79 6.3.1.2 Isolated Mitochondria 79 6.3.1.3 Permeabilized Cells 79 6.3.2 Cell Models 79 6.3.2.1 Primary Human Hepatocytes 79 6.3.2.2 HepG2 Cells 80 6.3.2.3 HepaRG Cells 80 6.3.2.4 Coculture of Multiple Cell Types 81 6.3.2.5 3D Culture 81 6.3.3 The Development and Validation of Testing Strategies 82 6.4 Case Studies 82 6.4.1 Acetaminophen: Multi‐Mechanistic Mitochondrial Hepatotoxicity 82 6.4.2 Flutamide: Multi‐Mechanistic Mitochondrial Hepatotoxicity 85 6.4.3 Fialuridine: A Case of Chronic, Direct Mitochondrial Toxicity 86 6.5 Concluding Remarks 87 References 87 7

Cardiotoxicity of Drugs: Role of Mitochondria 93 Zoltan V. Varga and Pal Pacher

7.1 7.1.1 7.1.2 7.1.2.1 7.1.2.2 7.1.3 7.1.3.1 7.1.3.2 7.2 7.2.1 7.2.1.1 7.2.1.2 7.2.1.3 7.2.1.4 7.2.1.5 7.2.1.6 7.2.1.7 7.2.2 7.2.3 7.2.3.1

Introduction 93 Mitochondrial Energy Homeostasis in Cardiomyocytes 93 Mitochondrial Oxidative Stress in Cardiomyocytes 94 Sources of Mitochondrial Reactive Oxygen Species 95 Mitochondrial Antioxidant Defense 96 Birth and Death of Cardiac Mitochondria 96 Mitochondrial Biogenesis 96 Mitophagy and Mitochondrial Apoptosis 97 Cardiotoxic Drugs That Cause Mitochondrial Dysfunction 97 Cardiotoxicity During Cancer Chemotherapy 97 Doxorubicin‐Induced Cardiotoxicity 97 Cisplatin‐Induced Cardiotoxicity 98 Trastuzumab‐Induced Cardiotoxicity 98 Arsenic Trioxide‐Induced Cardiotoxicity 99 Mitoxantrone‐Induced Cardiotoxicity 99 Imatinib Mesylate‐Induced Cardiotoxicity 100 Cardiotoxicity of Antiangiogenic Drugs 100 Cardiotoxicity of Antiviral Drugs 100 Cardiotoxicity of Addictive Drugs 101 Cardiotoxicity in Chronic Alcohol Use Disorder 101

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7.2.3.2 Cardiotoxicity in Cocaine Abuse 101 7.2.3.3 Cardiotoxicity in Methamphetamine and Ecstasy Abuse 102 7.2.3.4 Cardiotoxicity of Synthetic Cannabinoids 102 7.3 Conclusions 102 References 102 8

Skeletal Muscle Mitochondrial Toxicity 111 Eric K. Herbert, Saul R. Herbert, and Karl E. Herbert

8.1 8.1.1 8.1.2 8.2 8.2.1

Introduction 111 Type 1 and Type 2 Skeletal Muscle Fibers 111 Drug‐Induced Myopathy 112 Statin Myopathy 112 Observations on Skeletal Muscle Fiber Type Selectivity During Statin Myotoxicity in Rodents 113 8.2.2 Evidence for the Direct and Indirect Impact of Statins on Mitochondrial Function 114 8.2.2.1 Statins and the Biosynthesis of CoQ10 114 8.2.2.2 Evidence for Direct Effects of Statins on Mitochondrial Function 116 8.3 AZT and Mitochondrial Myopathy 120 8.4 Do Other Nucleoside Analogue Drugs Cause Myopathy? 123 8.5 Other Drugs Possibly Associated with Myopathy Due to Mitochondrial Toxicity 123 8.6 Concluding Remarks 124 References 124 9

Manifestations of Drug Toxicity on Mitochondria in the Nervous System 133 Jochen H. M. Prehn and Irene Llorente‐Folch

9.1 9.2 9.2.1 9.2.2 9.2.2.1 9.2.2.2 9.2.2.3 9.2.3 9.3 9.3.1 9.3.2 9.3.3 9.4 9.4.1 9.4.2 9.5 9.5.1 9.5.2 9.6

Introduction: Mitochondria in the Nervous System 133 Mitochondrial Mechanisms of Peripheral Neuropathy 135 Reverse Transcriptase Inhibitors 136 Chemotherapy‐Induced Peripheral Neuropathies (CIPN) 136 Microtubule‐Modifying Agents and Mitochondria: Paclitaxel and Vincristine 137 Platinum Compounds and Mitochondria: Oxaliplatin 138 Protease Inhibitor Bortezomib and Mitochondria 138 Statins 139 Mitochondria and Retinal Drug Toxicity 140 Chloramphenicol 141 Ethambutol 142 Methanol 142 Mitochondria and Ototoxicity 143 Cisplatin 144 Mitochondrial Disorders, Hearing Loss, and Ototoxicity 145 Mitochondrial Mechanisms of Central Nervous System injury 146 Mitochondrial Mechanisms of Neuronal Injury 146 Potential Manifestations of Drug‐Induced Mitochondrial Dysfunction in the CNS 149 Conclusion 149 References 150

10

Nephrotoxicity: Increasing Evidence for a Key Role of Mitochondrial Injury and Dysfunction and Therapeutic Implications 169 Ana Belén Sanz, Maria Dolores Sanchez‐Niño, Adrian M. Ramos, and Alberto Ortiz

10.1 10.2 10.3 10.3.1 10.3.2 10.3.3

Scope of the Problem 169 Pecularities of Tubular Cells 169 Nephrotoxicity and Mitochondria 170 Respiratory Chain: Reactive Oxygen Species (ROS) Formation 170 ATP Generation 170 Cellular Iron Homeostasis 171

Contents

10.3.4 10.4 10.4.1 10.4.2 10.4.3 10.5 10.5.1 10.5.2 10.6 10.6.1 10.6.2 10.6.3 10.7 10.7.1 10.7.2 10.7.3 10.7.4 10.7.5 10.8

Calcium Detoxification by Mitochondria: Role of Mitochondrial Permeability Transition Pore (MPT) 171 Evidence of Mitochondrial Injury in Nephrotoxicity 171 Morphological Changes 171 Mitochondrial Dysfunction 172 Mitochondrial Gene Expression 172 Calcineurin Inhibitor Nephrotoxicity 172 Calcineurin Inhibitors: Mitochondrial Dysfunction 172 Apoptosis in CsA Nephrotoxicity 173 HAART and Nephrotoxicity 175 The Transporters 176 HAART and Mitochondrial Dysfunction 177 Nucleotide Antiviral Drugs and Tubular Cell Apoptosis 177 Other Nephrotoxic Drugs and Mitochondria 177 Anticancer Drugs: Cisplatin 177 Antibiotics: Aminoglycosides and Polymyxins 178 Iron Chelators: Deferasirox 178 Environmental Nephrotoxins: Aristolochic Acid 178 Endogenous Nephrotoxins: Glucose, Glucose Degradation Products, and Heme 178 Therapeutic Implications and Future Lines of Research 178 Acknowledgments 179 References 179

11

Mammalian Sperm Mitochondrial Function as Affected by Environmental Toxicants, Substances of Abuse, and Other Chemical Compounds 185 Sandra Amaral, Renata S. Tavares, Sara Escada‐Rebelo, Andreia F. Silva, and João Ramalho‐Santos

11.1 11.2 11.3 11.4 11.5 11.5.1 11.5.2 11.5.3 11.5.4 11.6 11.6.1 11.6.2 11.6.3 11.6.4 11.6.5 11.7 11.8

Introduction 185 Pesticides, Herbicides, and Other Endocrine‐Disrupting Chemicals (EDCs) 187 In Vivo Studies 188 In Vitro Studies 189 Drugs of Abuse 189 Marijuana 189 Cocaine 190 Nicotine 190 Anabolic–Androgenic Steroids 191 Nutritional Elements: Vitamins and Supplements 191 Coenzyme Q10 191 l‐Carnitine 192 Melatonin 192 Vitamins E and C 192 Lycopene and Fatty Acids 193 Natural Plant Products 193 Conclusions and Perspectives 195 Acknowledgments 195 References 196 Part 3

Methods to Detect Mitochondrial Toxicity: In Vitro, Ex Vivo, In Vivo, Using Cells, Animal Tissues, and Alternative Models 205

12

Biological and Computational Techniques to Identify Mitochondrial Toxicants 207 Robert B. Cameron, Craig C. Beeson, and Rick G. Schnellmann

12.1 12.2 12.3 12.4

Identifying Mitochondrial Toxicants 207 Models to Identify Mitochondrial Toxicants 208 Computational Models for the Identification and Development of Mitochondrial Toxicants 210 Concluding Remarks 212 References 212

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13

The Parallel Testing of Isolated Rat Liver and Kidney Mitochondria Reveals a Calcium‐Dependent Sensitivity to Diclofenac and Ibuprofen 217 Sabine Schulz, Sabine Borchard, Tamara Rieder, Carola Eberhagen, Bastian Popper, Josef Lichtmannegger, Sabine Schmitt, and Hans Zischka

13.1 13.2 13.2.1 13.2.2 13.2.3 13.2.4 13.2.5 13.3 13.3.1 13.3.2 13.3.3 13.3.4 13.4

Introduction 217 Methods 218 Parallel Isolation of Mitochondria from Rat Tissues 218 Electron Microscopy 220 Assessment of the Mitochondrial Membrane Potential (MMP) 220 Analyses of the Mitochondrial Permeability Transition (MPT) 220 Miscellaneous 220 Results and Discussion 220 Parallel Isolation of Intact Mitochondria from Various Rat Tissues 220 Ibuprofen and Diclofenac Differently Impair the MMP of Mitochondria from Rat Liver and Kidney 221 Ibuprofen and Diclofenac Toxicity on Isolated Mitochondria Is Markedly Increased by Calcium 223 Cyclosporine A (CysA) Provides Mitochondrial Protection to Ibuprofen/Ca2+‐Induced Damage 223 Conclusions 223 Acknowledgments 226 References 226

14

In Vitro Methodologies to Investigate Drug‐Induced Toxicities 229 Rui F. Simões, Teresa Cunha‐Oliveira, Cláudio F. Costa, Vilma A. Sardão, and Paulo J. Oliveira

14.1 14.2 14.2.1 14.2.2 14.2.3 14.2.4 14.3 14.3.1 14.3.2 14.3.3 14.3.4 14.4

Mitochondria as a Biosensor to Measure Drug‐Induced Toxicities: Is It Relevant? 229 Drug‐Induced Cellular Bioenergetic Changes: What Does It Mean and How Can We Measure It? 230 Pinpointing Mitochondrial Toxicity: Manipulation of Culture Media Fuels 230 Oxygen Consumption 231 ATP, ADP, and AMP Measurements 233 Respiratory Chain and ATP Synthase Enzymatic Activities 234 Evaluation of Mitochondrial Physiology 235 Measuring Reactive Oxygen Species (ROS) Production with Oxidant-sensitive Probes 235 Monitoring Mitochondrial Transmembrane Electric Potential 236 Calcium Flux Measurements 238 Measuring the Activity of the Mitochondrial Permeability Transition Pore (MPTP) 239 Concluding Remarks 241 Acknowledgments 241 References 241

15

Combined Automated Measurement of Respiratory Chain Complexes and Oxidative Stress: A First Step to an Integrated View of Cell Bioenergetics 249 Marc Conti, Thierry Delvienne, and Sylvain Loric

15.1 15.2 15.2.1 15.2.2 15.3 15.3.1 15.3.2 15.4 15.5

Introduction 249 Technology 250 OXPHOS Complex Measurements 252 OS Pathway Measurements 252 Applications of Functional OXPHOS and OS Measurements in Drug Evaluation 253 Combined OXPHOS and OS Measurements in Drug Toxicity Evaluation 253 Glucose as an Underestimated OXPHOS and OS Metabolic Modifier in Cultured Cells 255 Versatility of the Technology 259 Conclusions and Future Perspectives 261 References 261

16

Measurement of Mitochondrial Toxicity by Flow Cytometry 265 Padma Kumar Narayanan and Nianyu Li

16.1 16.2

Introduction 265 Evaluation of Mitochondrial Function by Flow Cytometry 265

Contents

16.2.1 16.2.2 16.3 16.3.1 16.3.2 16.4 16.5 16.6

Mitochondrial Membrane Potential (MMP) Measurement 265 Mitochondrial Reactive Oxygen Species (ROS) Measurement 268 Evaluation of Xenobiotics‐Induced Mitochondrial Toxicity by Flow Cytometry 268 Cell Culture Conditions: Glucose‐ versus Galactose‐Containing Media 268 Loading Fluorescent Probes 269 Benefits and Limitations 269 Emerging New Fluorescent Probes and Technologies for Mitochondrial Function Assessment 269 Summary 271 References 271

17

MitoChip: A Transcriptomics Tool for Elucidation of Mechanisms of Mitochondrial Toxicity 275 Varsha G. Desai, and G. Ronald Jenkins

17.1 17.2 17.2.1 17.2.2 17.2.3 17.3 17.3.1 17.4 17.5

Development of Mitochondria‐Specific Gene Expression Array (MitoChip) 275 Mouse MitoChip: Assessment of Altered Mitochondrial Function in Mouse Models 277 Flutamide‐Induced Liver Toxicity in Sod2+/− Mice 277 Cisplatin‐Induced Acute Kidney Toxicity in KAP2‐PPARα Transgenic Mice 279 Doxorubicin‐Induced Cardiotoxicity in B6C3F1 Mice 283 Rat MitoChip: Assessment of Altered Mitochondrial Function in a Rat Model 286 Doxorubicin‐Induced Cardiotoxicity in SHR/SST‐2 Rat Model 287 Concluding Remarks 289 Future Direction 289 Conflict of Interest Statement 289 Acknowledgments 289 References 290

18

Using 3D Microtissues for Identifying Mitochondrial Liabilities 295 Simon Messner, Olivier Frey, Katrin Rössger, Andy Neilson, and Jens M. Kelm

18.1

Significance of Metabolic Profiling in Drug Development: Current Tools and New Technologies 295 Use of 3D Microtissues to Detect Mitochondrial Liabilities 296 Limitations of Currently Used In Vitro Cell Models 296 General Characteristics of 3D Microtissues 296 3D Microtissue‐Based Assessment of Mitochondrial Activity 297 Difference of Spare Respiratory Capacity in 2D versus 3D Cultures 297 SRC‐Based Detection of Mitochondrial Liabilities in 3D Human Liver Microtissues 299 SRC‐Based Detection of Mitochondrial Liabilities in Human Cardiac Microtissues 301 Conclusion 301 Acknowledgments 302 References 302

18.2 18.2.1 18.2.2 18.2.3 18.2.4 18.3 18.4 18.5

19

Toward Mitochondrial Medicine: Challenges in Rodent Modeling of Human Mitochondrial Dysfunction 305 David A. Dunn, Michael H. Irwin, Walter H. Moos, Kosta Steliou, and Carl A. Pinkert

19.1 19.2 19.3 19.4 19.5 19.6 19.7 19.8

Introduction 305 Allotopic Expression of ATP6 305 Xenomitochondrial Mice 306 Galactose Treatment 306 Rotenone Treatment 307 Hepatotoxicity with Mitochondrial Dysfunction 307 Hyperactivity of the Mitochondrial Stress Response in Mice 308 Summary 309 References 309

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Measurement of Oxygen Metabolism In Vivo 315 M. P. J. van Diemen, R. Ubbink, F. M. Münker, E. G. Mik, and G. J. Groeneveld

20.1 20.2 20.3

Introduction: The Importance of Measuring Mitochondrial Function in Drug Trials 315 Methods: In Vivo Methods to Measure Drug Effects on Mitochondrial Function in a Clinical Setting 316 Measuring Mitochondrial Oxygen Consumption with the Protoporphyrin IX–Triplet State Lifetime Technique 317 Features of a Novel COMET Measurement System: The First Bedside Monitor of  Cellular Oxygen Metabolism 317 Clinical Trial: Effect of Simvastatin on Mitochondrial Function In Vivo in Healthy Volunteers 317 References 319

20.4 20.5

21

Detection of Mitochondrial Toxicity Using Zebrafish 323 Sherine S. L. Chan and Tucker Williamson

21.1 21.2 21.3 21.3.1 21.3.2 21.3.3 21.3.4 21.3.5 21.4 21.4.1 21.4.2 21.4.3 21.4.4 21.5

Introduction 323 Genetics and Manipulation of Zebrafish for Toxicological Studies 324 Zebrafish Physiology 325 Neuromuscular System 325 Cardiovascular System 328 Liver 330 Reproductive System and Gender 332 Regeneration 333 Mitochondrial Biology and Methods 333 Energetics 334 Reactive Oxygen Species 335 Mitochondrial Dynamics and Mitochondrial Membrane Potential 335 Mitochondrial DNA Stability 337 Conclusions and Future Directions 338 Acknowledgments 338 References 338

22

MiRNA as Biomarkers of Mitochondrial Toxicity 347 Terry R. Van Vleet and Prathap Kumar Mahalingaiah

22.1 22.2 22.3 22.4 22.5 22.6 22.7 22.7.1 22.7.2 22.7.3 22.8 22.8.1 22.8.2 22.8.3 22.8.4 22.9 22.9.1 22.9.2 22.9.3 22.10 22.11

Introduction 347 MicroRNAs: General 348 Properties of miRNA: Useful Biomarkers 349 Mitochondria and miRNAs 350 miRNA Transport in the Mitochondria 351 miRNA Secretion 352 miRNAs Associated with Mitochondrial Function 354 Energy Metabolism/Respiration 354 Mitochondrial Dynamics 354 Mitochondria‐Mediated Apoptosis 355 Mitochondrially Rich Tissues and Tissue‐Specific miRNAs 355 Heart 355 Kidney 358 Liver 359 Brain/Nerve 359 Work to Date Using MiRNA as Biomarkers of Mitochondrial Toxicity 359 Kidney 360 Skeletal Muscle 360 Serum 360 Future Work Needed 361 Conclusions 362 References 363

Contents

23

Biomarkers of Mitochondrial Injury After Acetaminophen Overdose: Glutamate Dehydrogenase and Beyond 373 Benjamin L. Woolbright and Hartmut Jaeschke

23.1 23.2 23.3

Introduction 373 Acetaminophen Overdose as a Model for Biomarker Discovery 373 Acetaminophen Overdose: Mechanisms of Toxicity in Mice and Man 374 Drug Metabolism and Protein Adducts 374 Critical Role of Mitochondria in APAP Hepatotoxicity 374 Biomarkers of Mitochondrial Injury 375 Glutamate Dehydrogenase 375 Mitochondrial DNA (mtDNA) 376 Nuclear DNA 377 Acylcarnitines 378 Carbamoyl Phosphate Synthetase 378 Ornithine Carbamyl Transferase (OCT) 378 Conclusions 379 References 379

23.3.1 23.3.2 23.4 23.4.1 23.4.2 23.4.3 23.4.4 23.4.5 23.4.6 23.5

24

Acylcarnitines as Translational Biomarkers of Mitochondrial Dysfunction 383 Richard D. Beger, Sudeepa Bhattacharyya, Pritmohinder S. Gill, and Laura P. James

24.1 24.2 24.3 24.4 24.5 24.6 24.7

Introduction 383 Acylcarnitine Analysis 384 Acylcarnitines in In Vitro and In Vivo Hepatotoxicity Studies 387 Acylcarnitines and Hepatotoxicants 387 Acylcarnitines in Cardiac Toxicity 389 Clinical Hepatotoxicity 389 Conclusions 390 References 390

25

Mitochondrial DNA as a Potential Translational Biomarker of Mitochondrial Dysfunction in Drug‐Induced Toxicity Studies 395 Afshan N. Malik

25.1 25.2 25.3 25.4 25.5 25.6

Introduction 395 The Mitochondrial Genome 396 Is Mitochondrial DNA a Useful Biomarker of Mitochondrial Dysfunction 397 Methodological Issues for Measuring Mitochondrial DNA Content 399 Acquired Mitochondrial DNA Changes in Human Diseases 401 Conclusions and Future Directions 402 Acknowledgments 403 References 403

26

Predicting Off‐Target Effects of Therapeutic Antiviral Ribonucleosides: Inhibition of Mitochondrial RNA Transcription 407 Jamie J. Arnold and Craig E. Cameron

26.1 26.2 26.3 26.4 26.5 26.6 26.6.1 26.6.2 26.7

Introduction 407 Therapeutic Ribonucleoside Inhibitors Target RNA Virus Infections 407 Nucleoside Reverse Transcriptase Inhibitors (NRTIs) Mediate Mitochondrial Toxicity 408 Mitochondrial Dysfunction Is an Unintended Consequence of Clinical Drug Candidates 409 Mitochondrial Transcription as an “Off‐Target” of Antiviral Ribonucleosides 410 Evaluation of Substrate Utilization by POLRMT In Vitro 410 Determination of the Efficiency of Incorporation by POLRMT 412 Determination of the Sensitivity to Inhibition: Mitovir Score 413 Direct Evaluation of Mitochondrial RNA Transcripts in Cells 414

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26.8 26.9

Inhibition of Mitochondrial Function 415 Conclusions 416 References 416

27

Imaging of Mitochondrial Toxicity in the Kidney 419 Andrew M. Hall, Joana R. Martins, and Claus D. Schuh

27.1 27.2 27.3 27.3.1 27.4 27.4.1 27.4.2 27.4.3 27.5 27.5.1 27.6 27.7 27.8

Mitochondria in the Kidney 419 Drug Toxicity in the Kidney 421 Fluorescence Microscopy 421 Multiphoton Microscopy 421 Assessment of Mitochondrial Function with Fluorescence Microscopy 422 Mitochondrial Membrane Potential and pH 422 Mitochondrial Redox State 422 Mitochondrial Reactive Oxygen Species Production 422 Ex Vivo Imaging of Mitochondria in the Kidney 423 Live Imaging of Kidney Slices 423 Intravital Imaging of Mitochondria in the Kidney 423 Recent Technical Developments in Intravital Kidney Imaging 424 Conclusion 426 Acknowledgments 426 Disclosures 426 Conflicts of Interest 426 References 426

28

Imaging Mitochondrial Membrane Potential and Inner Membrane Permeability 429 Anna‐Liisa Nieminen, Venkat K. Ramshesh, and John J. Lemasters

28.1 28.2 28.2.1 28.2.2 28.2.3 28.3 28.3.1 28.3.2 28.3.3 28.3.4 28.4 28.4.1 28.4.2 28.4.3 28.4.4 28.5

Introduction 429 Isolated Mitochondria 429 Nernstian Distribution of Fluorescent Probes 431 Monitoring Membrane Potential in Isolated Mitochondria 431 Pitfalls with Potential‐Indicating Fluorophores 431 Imaging of Membrane Potentials in Single Intact Cells 433 Image Acquisition and Processing 433 Background Subtraction 434 Fluorescence of the Extracellular Space 434 Pixel‐by‐Pixel Calculation of Ψ 434 Mitochondrial Permeability Transition 435 Swelling Assay of the MPT 436 Release of Carboxydichlorofluorescein 437 Visualizing the MPT in Intact Cells 437 Plasma Membrane Permeability 438 Conclusion 438 Acknowledgments 439 References 439

29

Quantifying Skeletal Muscle Mitochondrial Function In Vivo by 31P Magnetic Resonance Spectroscopy 443 Graham J. Kemp

29.1 29.2 29.3 29.4 29.5 29.6

MRS Methods in Skeletal Muscle 443 The Metabolic and Physiological Background to 31P MRS Studies of Muscle 444 Physiological Principles in the Quantitative Analysis of Dynamic 31P MRS Data 444 Approaches to Measuring Mitochondrial Function In Vivo 446 Some Practical and Experimental Considerations in 31P MRS Studies of Muscle 446 31 P MRS Studies in Resting Muscle 447

Contents

29.7 29.8 29.9 29.10 29.11

31

P MRS Magnetization Transfer Methods 448 Muscle Exercise Responses Studied by 31P MRS 448 Mitochondrial Function Studied by 31P MRS in Recovery from Exercise 449 Validating MRS‐Based Measures of Mitochondrial Function 450 Conclusions and Summary 451 Acknowledgments 452 References 452

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List of Contributors Sandra Amaral

Neha Bansal

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra and Institute for Interdisciplinary Research, University of Coimbra Coimbra Portugal

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA

Sofia Annis

Department of Biology College of Science Northeastern University Boston, MA USA Jamie J. Arnold

201 Althouse Lab, Department of Biochemistry and Molecular Biology The Pennsylvania State University University Park, PA USA Narayan G. Avadhani

Department of Biomedical Sciences, School of Veterinary Medicine University of Pennsylvania Philadelphia, PA USA

Daniel José Barbosa

Cell Division Mechanisms Group Instituto de Biologia Molecular e Celular (IBMC), Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto Porto Portugal Maria de Lourdes Bastos

UCIBIO, REQUIMTE (Rede de Química e Tecnologia), Laboratório de Toxicologia, Departamento de Ciências Biológicas, Faculdade de Farmácia Universidade do Porto Porto Portugal Craig C. Beeson

Department of Drug Discovery and Biomedical Sciences, College of Graduate Studies Medical University of South Carolina Charleston, SC USA

Amy L. Ball

Department of Molecular and Cellular Pharmacology, MRC Centre for Drug Safety Science, The Institute of Translational Medicine The University of Liverpool Liverpool UK

Richard D. Beger

Division of Systems Biology, National Center for Toxicological Research Food and Drug Administration Jefferson, AR USA

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List of Contributors

Sudeepa Bhattacharyya

João Paulo Capela

Department of Pediatrics University of Arkansas for Medical Sciences and Section of Clinical Pharmacology and Toxicology Arkansas Children’s Hospital Little Rock, AR USA

UCIBIO, REQUIMTE (Rede de Química e Tecnologia), Laboratório de Toxicologia, Departamento de Ciências Biológicas, Faculdade de Farmácia Universidade do Porto and FP-ENAS (Unidade de Investigação UFP em Energia, Ambiente e Saúde), CEBIMED (Centro de Estudos em Biomedicina), Faculdade de Ciências da Saúde Universidade Fernando Pessoa Porto Portugal

Eduardo Biala

Department of Biology College of Science Northeastern University Boston, MA and Biology Program University of Guam Mangilao, GU USA Sabine Borchard

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg Germany Annie Borgne‐Sanchez

Mitologics S.A.S. Hôpital Robert Debré Paris France

Francesc Cardellach

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Félix Carvalho

UCIBIO, REQUIMTE (Rede de Química e Tecnologia), Laboratório de Toxicologia, Departamento de Ciências Biológicas, Faculdade de Farmácia Universidade do Porto Porto Portugal

Craig E. Cameron

201 Althouse Lab, Department of Biochemistry and Molecular Biology The Pennsylvania State University University Park, PA USA

Carmen Castaneda‐Sceppa

Robert B. Cameron

Marc Catalán-García

Department of Pharmacology and Toxicology, College of Pharmacy University of Arizona Tucson, AZ and Department of Drug Discovery and Biomedical Sciences, College of Graduate Studies Medical University of South Carolina Charleston, SC USA

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain

Bouve College of Health Sciences, Northeastern University Boston, MA USA

List of Contributors

Amy E. Chadwick

Teresa Cunha‐Oliveira

Department of Molecular and Cellular Pharmacology, MRC Centre for Drug Safety Science, The Institute of Translational Medicine The University of Liverpool Liverpool UK

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal

Sherine S. L. Chan

Department of Drug Discovery and Biomedical Sciences Medical University of South Carolina Charleston, SC USA and Neuroene Therapeutics Mt. Pleasant, SC, USA

Jason Czachor

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA Thierry Delvienne

Metabiolab Brussels Belgium Varsha G. Desai

Huan‐Chieh Chien

Department of Bioengineering and Therapeutic Sciences University of California and Apricity Therapeutics Inc. San Francisco, CA USA Ana Raquel Coelho

CNC—Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Biocant Park Cantanhede and III‐Institute for Interdisciplinary Research, University of Coimbra Coimbra Portugal Marc Conti

IMRB U955EQ7, Mondor University Hospitals; Créteil & URDIA, Saints Pères Faculty of Medicine Descartes University Paris France

Personalized Medicine Branch, Division of Systems Biology, National Center for Toxicological Research U.S. Food and Drug Administration Jefferson, AR USA David A. Dunn

Department of Biological Sciences State University of New York at Oswego Oswego, NY USA Alex Dyson

Bloomsbury Institute of Intensive Care Medicine, Division of Medicine University College London and Magnus Oxygen Ltd, University College London London UK Carola Eberhagen

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg Germany

Cláudio F. Costa

Steve Enoch

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal

School of Pharmacy and Biomolecular Sciences Liverpool John Moores University Liverpool UK

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List of Contributors

Sara Escada‐Rebelo

Jeffrey L. Galinkin

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra and Institute for Interdisciplinary Research, University of Coimbra Coimbra Portugal

Department of Anesthesia University of Colorado School of Medicine and CPC Clinical Research Aurora, CO USA

Luciana L. Ferreira

CNC—Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Biocant Park Cantanhede Portugal Zoe Fleischmann

Department of Biology, College of Science Northeastern University Boston, MA, USA Clàudia Fortuny

Malalties infeccioses i resposta inflamatòria sistèmica en pediatria, Unitat d’Infeccions, Servei de Pediatria Institut de Recerca Pediàtrica Hospital Sant Joan de Déu Barcelona; CIBER de Epidemiología y Salud Pública (CIBERESP) Madrid; Departament de Pediatria Universitat de Barcelona Barcelona; and Traslational Research Network in Pediatric Infectious Diseases (RITIP) Madrid Spain Olivier Frey

InSphero AG Schlieren Switzerland

Priya Gandhi

Department of Biology College of Science Northeastern University Boston, MA USA Laura García-Otero

BCNatal—Barcelona Center for Maternal‐Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona Barcelona and CIBERER Madrid Spain Glòria Garrabou

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Sciences‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Mariana Gerschenson

John A. Burns School of Medicine University of Hawaii at Manoa Honolulu, HI USA Kathleen M. Giacomini

Bernard Fromenty

INSERM, INRA, Université Rennes, UBL, Nutrition Metabolisms and Cancer (NuMeCan) Rennes France

Department of Bioengineering and Therapeutic Sciences University of California San Francisco, San Francisco, CA USA

List of Contributors

Whitney S. Gibbs

G. J. Groeneveld

Department of Drug Discovery and Biomedical Sciences Medical University of South Carolina Charleston, SC and Department of Pharmacology and Toxicology, College of Pharmacy University of Arizona Tucson, AZ USA

Centre for Human Drug Research Leiden The Netherlands

Pritmohinder S. Gill

Department of Pediatrics University of Arkansas for Medical Sciences and Section of Clinical Pharmacology and Toxicology Arkansas Children’s Hospital Little Rock, AR USA Young‐Mi Go

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine Emory University Atlanta, GA USA Ingrid González‐Casacuberta

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Josep Maria Grau

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain

F. Peter Guengerich

Department of Biochemistry Vanderbilt University School of Medicine Nashville, TN USA Mariona Guitart‐Mampel

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Sciences‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Andrew M. Hall

Institute of Anatomy, University of Zurich and Department of Nephrology University Hospital Zurich Zurich Switzerland Iain P. Hargreaves

Neurometabolic Unit, National Hospital London and School of Pharmacy and Biomolecular Science, Liverpool John Moores University Liverpool UK Eric K. Herbert

University of Nottingham Nottingham UK Karl E. Herbert

Department of Cardiovascular Sciences University of Leicester Leicester UK

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List of Contributors

Saul R. Herbert

G. Ronald Jenkins

Queen Mary University of London London UK

Personalized Medicine Branch, Division of Systems Biology, National Center for Toxicological Research U.S. Food and Drug Administration Jefferson, AR USA

Ana Sandra Hernández

BCNatal—Barcelona Center for Maternal‐Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona Barcelona and CIBERER Madrid Spain

Carol E. Jolly

Department of Molecular and Cellular Pharmacology, MRC Centre for Drug Safety Science, The Institute of Translational Medicine The University of Liverpool Liverpool UK

William R. Hiatt

CPC Clinical Research and Division of Cardiology, Department of Medicine University of Colorado Anschutz Medical Campus School of Medicine Aurora, CO USA Ashley Hill

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA Michael H. Irwin

Department of Pathobiology, College of Veterinary Medicine Auburn University Auburn, AL USA Hartmut Jaeschke

Department of Pharmacology, Toxicology & Therapeutics University of Kansas Medical Center Kansas City, KS USA Laura P. James

Department of Pediatrics University of Arkansas for Medical Sciences and Section of Clinical Pharmacology and Toxicology Arkansas Children’s Hospital Little Rock, AR USA

Dean P. Jones

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine Emory University and HERCULES Exposome Research Center, Department of Environmental Health Rollins School of Public Health Atlanta, GA USA Diana Luz Juárez-Flores

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Laleh Kamalian

Department of Molecular and Cellular Pharmacology, MRC Centre for Drug Safety Science, The Institute of Translational Medicine The University of Liverpool Liverpool UK Jens M. Kelm

InSphero AG Schlieren Switzerland

List of Contributors

Graham J. Kemp

Josef Lichtmannegger

Department of Musculoskeletal Biology University of Liverpool Liverpool UK

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg Germany

Konstantin Khrapko

Department of Biology College of Science Northeastern University and Bouve College of Health Sciences, Northeastern University Boston, MA USA Jean‐Daniel Lalau

Department of Endocrinology and Nutrition Amiens University Hospital Amiens France Hong Kyu Lee

Department of Internal Medicine College of Medicine, Eulji University Seoul South Korea John J. Lemasters

Center for Cell Death, Injury & Regeneration, Medical University of South Carolina; Department of Drug Discovery & Biomedical Sciences Medical University of South Carolina; Department of Biochemistry & Molecular Biology Medical University of South Carolina Charleston, SC USA and Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences Pushchino Russian Federation Housaiyin Li

Department of Biology College of Science Northeastern University Boston, MA USA

Steven E. Lipshultz

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA Irene Llorente‐Folch

Department of Physiology and Medical Physics Royal College of Surgeons in Ireland 123 St Stephen’s Green Dublin 2 Ireland Sylvain Loric

IMRB U955EQ7, Mondor University Hospitals; Créteil & URDIA, Saints Pères Faculty of Medicine Descartes University Paris France Anthony L. Luz

Nicholas School of the Environment Duke University Durham, NC USA Prathap Kumar Mahalingaiah

Department of Investigative Toxicology and Pathology, Preclinical Safety Division AbbVie North Chicago, IL USA Afshan N. Malik

Diabetes Research Group, School of Life Course Sciences, Faculty of Life Sciences and Medicine King’s College London London UK Joana R. Martins

Institute of Anatomy, University of Zurich Zurich Switzerland Laura L. Maurer

Nianyu Li

Merck Research Laboratory West Point, PA USA

Nicholas School of the Environment Duke University Durham, NC USA

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List of Contributors

Gavin P. McStay

Walter H. Moos

Department of Life Sciences New York Institute of Technology Old Westbury, NY USA

Department of Pharmaceutical Chemistry, School of Pharmacy University of California San Francisco San Francisco, CA USA

Claire Mellor

School of Pharmacy and Biomolecular Sciences Liverpool John Moores University Liverpool UK Simon Messner

InSphero AG Schlieren Switzerland Miriam Mestre

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA Joel N. Meyer

Nicholas School of the Environment Duke University Durham, NC USA

Constanza Morén

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Sciences‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain

F. M. Münker

Photonics Healthcare B.V. Utrecht The Netherlands

Padma Kumar Narayanan

Ionis Pharmaceuticals Carlsbad, CA USA

E. G. Mik

Department of Anesthesiology Erasmus MC Rotterdam The Netherlands Jose César Milisenda

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Tracie L. Miller

Miller School of Medicine University of Miami Miami, FL USA

Viruna Neergheen

Neurometabolic Unit National Hospital London UK

Andy Neilson

Agilent Technologies Santa Clara, CA USA

Mark Nelms

School of Pharmacy and Biomolecular Sciences Liverpool John Moores University Liverpool UK and US‐EPA Raleigh‐Durham, NC USA

List of Contributors

Anna‐Liisa Nieminen

Youngmi Kim Pak

Center for Cell Death, Injury & Regeneration, Medical University of South Carolina; Departments of Drug Discovery & Biomedical Sciences Medical University of South Carolina Charleston, SC USA and Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences Pushchino Russian Federation

Department of Physiology College of Medicine, Kyung Hee University Seoul South Korea

Antoni Noguera‐Julian

Malalties infeccioses i resposta inflamatòria sistèmica en pediatria, Unitat d’Infeccions, Servei de Pediatria Institut de Recerca Pediàtrica Hospital Sant Joan de Déu Barcelona; CIBER de Epidemiología y Salud Pública (CIBERESP) Madrid; Departament de Pediatria Universitat de Barcelona Barcelona; and Traslational Research Network in Pediatric Infectious Diseases (RITIP) Madrid Spain

Kurt D. Pennell

Department of Civil and Environmental Engineering Tufts University Medford, MA USA Daniela Piga

Centro Dino Ferrari, Dipartimento di Fisiopatologia Medico‐Chirurgica e dei Trapianti Università degli Studi and UOC Neurologia, Fondazione IRCCS Ca’ Granda – Ospedale Maggiore Policlinico Milan Italy Carl A. Pinkert

Department of Biological Sciences, College of Arts and Sciences The University of Alabama Tuscaloosa, AL USA Bastian Popper

Department of Anatomy and Cell Biology, Biomedical Center Ludwig‐Maximilians‐University Munich Martinsried Germany

Paulo J. Oliveira

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal

Jalal Pourahmad

Department of Toxicology and Pharmacology, Faculty of Pharmacy Shahid Beheshti University of Medical Sciences Tehran Iran

Alberto Ortiz

Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid Spain

Jochen H. M. Prehn

Pal Pacher

Alessandro Protti

Laboratory of Cardiovascular Physiology and Tissue Injury National Institutes of Health/NIAAA Bethesda, MD USA

Dipartimento di Anestesia, Rianimazione ed Emergenza‐Urgenza, Fondazione IRCCS Ca’ Granda – Ospedale Maggiore Policlinico Milan Italy

Department of Physiology and Medical Physics Royal College of Surgeons in Ireland 123 St Stephen’s Green Dublin 2 Ireland

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List of Contributors

João Ramalho‐Santos

Dario Ronchi

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra and Department of Life Sciences University of Coimbra Coimbra Portugal

Centro Dino Ferrari, Dipartimento di Fisiopatologia Medico‐Chirurgica e dei Trapianti Università degli Studi and UOC Neurologia, Fondazione IRCCS Ca’ Granda – Ospedale Maggiore Policlinico Milan Italy

Adrian M. Ramos

Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid Spain

Katrin Rössger

InSphero AG Schlieren Switzerland

Adeel Safdar Venkat K. Ramshesh

Center for Cell Death, Injury & Regeneration, Medical University of South Carolina; Departments of Drug Discovery & Biomedical Sciences Medical University of South Carolina Charleston, SC and GE Healthcare Quincy, MA USA Haider Raza

Department of Biomedical Sciences, School of Veterinary Medicine University of Pennsylvania Philadelphia, PA USA and On Sabbatical from Department of Biochemistry College of Medicine and Health Sciences, United Arab Emirates University Al Ain UAE Hiedy Razoky

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA

School of Health Sciences, Humber College Toronto, Ontario Canada Ayesha Saleem

School of Health Sciences, Humber College Toronto, Ontario Canada Stephen E. Sallan

Dana‐Farber Cancer Institute, Harvard Medical School and Department of Medicine, Division of Hematology/Oncology Boston Children’s Hospital Boston, MA USA Maria Dolores Sanchez‐Niño

Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid Spain Alessandro Santini

Tamara Rieder

Institute of Toxicology and Environmental Hygiene Technical University Munich Munich Germany

Dipartimento di Anestesia, Rianimazione ed Emergenza‐Urgenza, Fondazione IRCCS Ca’ Granda – Ospedale Maggiore Policlinico Milan, Italy

List of Contributors

Ana Belén Sanz

Rui F. Simões

Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid Spain

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal

Vilma A. Sardão

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal Sabine Schmitt

Institute of Toxicology and Environmental Hygiene Technical University Munich Munich Germany Rick G. Schnellmann

Department of Pharmacology and Toxicology, College of Pharmacy University of Arizona and Southern Arizona VA Health Care System Tucson, AZ USA Natalie E. Scholpa

Department of Pharmacology and Toxicology, College of Pharmacy University of Arizona Tucson, AZ USA Claus D. Schuh

Institute of Anatomy, University of Zurich Zurich Switzerland

Kosta Steliou

Boston University School of Medicine, Cancer Research Center Boston, MA and PhenoMatriX, Inc. Natick, MA USA Renata S. Tavares

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra Coimbra Portugal Jonathan L. Tilly

Department of Biology College of Science, Northeastern University Boston, MA USA R. Ubbink

Department of Anesthesiology Erasmus MC Rotterdam and Photonics Healthcare B.V. Utrecht The Netherlands

Sabine Schulz

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg Germany

Karan Uppal

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine Emory University Atlanta, GA USA

Andreia F. Silva

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra Coimbra Portugal

M. P. J. van Diemen

Centre for Human Drug Research Leiden The Netherlands

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List of Contributors

Terry R. Van Vleet

Tucker Williamson

Department of Investigative Toxicology and Pathology, Preclinical Safety Division AbbVie North Chicago, IL USA

Department of Drug Discovery and Biomedical Sciences Medical University of South Carolina Charleston, SC USA

Zoltan V. Varga

Dori C. Woods

Laboratory of Cardiovascular Physiology and Tissue Injury National Institutes of Health/NIAAA Bethesda, MD USA

Department of Biology College of Science, Northeastern University Boston, MA USA

Eneritz Velasco‐Arnaiz

Benjamin L. Woolbright

Malalties infeccioses i resposta inflamatòria sistèmica en pediatria, Unitat d’Infeccions, Servei de Pediatria Institut de Recerca Pediàtrica Hospital Sant Joan de Déu Barcelona Spain

Department of Pharmacology, Toxicology & Therapeutics University of Kansas Medical Center Kansas City, KS USA

Luke Wainwright

Department of Molecular Neuroscience Institute of Neurology, University College of London London UK Douglas I. Walker

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine Emory University Atlanta, GA; Department of Civil and Environmental Engineering Tufts University Medford, MA and HERCULES Exposome Research Center, Department of Environmental Health Rollins School of Public Health Atlanta, GA USA Cecilia C. Low Wang

Division of Endocrinology, Metabolism and Diabetes, Department of Medicine University of Colorado Anschutz Medical Campus School of Medicine and CPC Clinical Research Aurora, CO USA

Hans Zischka

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg, Germany and Institute of Toxicology and Environmental Hygiene Technical University Munich Munich Germany Marjan Aghvami

Department of Toxicology and Pharmacology Faculty of Pharmacy, Shahid Beheshti University of Medical Sciences Tehran, Iran Mohammad Hadi Zarei,

Department of Toxicology and Pharmacology Faculty of Pharmacy, Shahid Beheshti University of Medical Sciences Tehran, Iran Parvaneh Naserzadeh

Department of Toxicology and Pharmacology Faculty of Pharmacy, Shahid Beheshti University of Medical Sciences Tehran, Iran

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Foreword The field of mitochondrial medicine is enjoying a renais‑ sance driven largely by advances in molecular biology and genetics. The first draft sequence of the human mitochondrial genome in 1981 provided the critical blueprint that enabled the identification of the first point and single large‐scale deletion mutations of mitochon‑ drial DNA (mtDNA) in 1988. To date, more than 270 dis‑ tinct mtDNA point mutations and hundreds of mtDNA deletions have been identified. Subsequent sequencing of the human nuclear genome in the early 2000s helped to catalyze the discovery of approximately 1000 nuclear genes that, together with the mtDNA, encode the mito‑ chondrial proteome. With a complete parts list, it has been possible to delve deep into the molecular basis of Mendelian mitochondrial disorders, with more than 200 nuclear disease genes now identified. There is now widespread consensus that mitochondrial dysfunction contributes to a spectrum of human conditions, ranging from rare syndromes to common degenerative diseases to the aging process itself. Today, there is great excitement that in the coming dec‑ ade, new medicines will become available that alleviate disease by targeting mitochondria. At the same time, there is widespread appreciation that many drugs fail clinical trials because of their mitochondrial liabilities. Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants represents one of the most important textbooks for those hoping to target mitochondria, as well as for those wanting to avoid mitochondrial side effects. It is a deep and thoughtful resource that will appeal to basic scientists, clinicians, and professional drug developers. Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants provides ample reminders of the intimate connections between mitochondria, pharmacology, and toxicology. Some of the most widely used tool compounds for investigating mitochondrial physiology, such as antimycin and oligomycin, are indeed natural products that serve as a chemical warfare in the microbial world. The fact that antimicrobial agents are often toxic to mitochondria is not surprising given the hypothesized proto‐bacterial origin of mitochondria. These overlapping effects of such drugs are perhaps best

illustrated by aminoglycosides and linezolid antibiotics, which not only inhibit bacterial protein synthesis but are also well known to cause neurotoxicity such as hearing loss, peripheral neuropathy, and optic neuropathy through impairment of mitochondrial translation. Pharmacogenetics contributes to these toxicities with the well‐established link between the m.1555A>G variant that predisposes to aminoglycoside‐induced deafness. Toxic side effects of clinically important and investigational new drugs for viruses have historically provided fundamentally new insights into the replication of mtDNA. One of the earliest anti‐HIV agents, zidovudine (azidothymidine (AZT)), is a nucleoside analogue that effectively inhibits viral reverse transcriptase but, in some patients, inhibits the mitochondrial polymerase gamma, leading to depletion of mtDNA particularly in muscle and causing myopathic weakness. These mitochondrial toxicities exposed the reliance and vulnerability of the mitochondrial genome to disruptions of the deoxynucleotide pool substrates for mtDNA replication. These toxicities also serve as a reminder that the mtDNA replication machinery of mitochondria actually resembles that of viruses. Mitochondrial toxicity is such a common side effect in humans; a thorough understanding and surveillance of these off‐target effects are required for the successful development of new medicines. A vivid case in point is fialuridine or 1‐(2‐deoxy‐2‐fluoro‐1‐d‐arabinofuranosyl)‐ 5‐iodouracil (FIAU), a nucleoside analogue that was tested for therapeutic efficacy for hepatitis B infection but tragi‑ cally caused fatal liver failure and death in 5 of 15 patients and forced liver transplantations in two other patients. Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants takes a rather systematic approach to mitochondrial pharmacology and toxicology and for this reason will be of use to even those outside of strict drug discovery. It begins with a scholarly introduction to the nuances of mitochondrial drug transport and detoxification systems, illustrated with specific case studies (Chapters 1–5). It then reviews cardinal features of mitochondrial toxicity at the organ level, highlighting some of the dose‐limiting toxicities of very commonly used

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Foreword

and lifesaving drugs (Chapter 6–12). One of the greatest challenges in our field lies in measuring mitochondrial function. Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants dedicates many chapters (Chapters 13–29) to reviewing modern technologies for measuring mitochondrial function in vitro, ex vivo, and in vivo. Although these technologies represent the current state of the art, they have their limitations, and much research is required to pioneer new, facile biomarkers and technologies that  are sensitive, specific, and minimally invasive. The  text  then progresses to reports from the clinic (Chapters 30–40) as well as from environmental biology (Chapters 41–45) that offer additional vignettes and examples of drug–mitochondria interactions.

The book Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants is very timely. While genetics and genomics have driven much progress in mitochondrial medicine for the past few decades, we anticipate that chemical biology may represent one of the most exciting new frontiers. We applaud Yvonne Will, James Dykens, and all of their contributors for assembling this new two volume book entitled: Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants. This textbook will be an important canon in the future of mitochondrial medicine and more broadly in modern drug discovery. Vamsi Mootha, M.D. (Boston, MA) and Michio Hirano, M.D. (New York, NY)

1

Part 1 Basic Concepts

3

1 Contributions of Plasma Protein Binding and Membrane Transporters to Drug‐Induced Mitochondrial Toxicity Gavin P. McStay Department of Life Sciences, New York Institute of Technology, Old Westbury, NY, USA

CHAPTER MENU 1.1 Drug Accumulation, 3 1.2 Small Molecule Delivery to Tissues, 4 1.3 Entry into Cells, 7 1.4 Transport Out of Cells, 8 1.5 Entry into Mitochondria, 10 1.6 Export from Mitochondria, 11 1.7 Concluding Remarks, 11 References, 11

1.1

Drug Accumulation

Successful pharmaceutical treatment of disease requires molecules with chemical properties that allow for entry into the human circulation and delivery to the intended site for effective binding to the target molecule. When the small molecule arrives at its target, modulation of a dis‑ ease process is achieved that results in alleviation of the disease symptoms. Many years of research are dedicated to optimization of the chemical properties to ensure a small molecule is effective. However, small molecules rarely affect a single target, and unwanted side effects can arise due to inappropriate tissue accumulation or the presence of a target in other tissues. More recently, it has become increasingly apparent that this is particularly the case for side effects due to accumulation and deleterious consequences on mitochondrial processes. Small molecules that are used as treatments for many types of diseases have been observed as having effects on mitochondrial processes—often inhibiting crucial func‑ tions such as electron transport or increasing production of mitochondrial reactive oxygen species (ROS). These off‐target effects are especially important when consid‑ ering tissues with a high demand for mitochondrial func‑ tion, such as the heart and brain, or those having roles in

general metabolism, such as the liver. The optimal properties of a drug often promote the undesired effects associated with mitochondrial toxicity. Small molecules are optimally lipophilic (displaying a high partition coefficient—log P) in nature, which allows for transit through the circulation by binding to plasma proteins and passage through cellular membranes to gain access to intracellular targets. The molecular composition and architecture of mitochondria is also responsible for attracting certain small molecules that results in accu‑ mulation and impact on mitochondrial function. The  mitochondrial membrane environment is unique because of the presence of specific phospholipids, such as the atypical cardiolipin with four acyl chains, as well as highly folded membrane structures particularly in the inner mitochondrial membrane (IMM) where specific geometry exists with certain structures such as the tips of the inner membrane cristae protrusions. These specific features will allow for certain molecules to accumulate due to affinity for cardiolipin and/or fitting into a specific geometry associated with inherent mitochondrial membrane arrangements. Mitochondrial function is also dependent on an electrochemical gradient across the IMM. This gradient is responsible for driving metabolite and ion transport across the IMM to power

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

4

Mitochondrial Dysfunction by Drug and Environmental Toxicants

processes such as ATP synthesis. Anabolic substrates, such as heme synthesis precursors, and other metabo‑ lites are transported across the IMM through specific transporters that are directly or indirectly driven by the mitochondrial membrane potential. However, certain lipophilic molecules are able to traverse the IMM by passive diffusion due to their chemical properties, and this is driven by the charge and pH differences across the IMM. The mitochondrial matrix is an overall negatively charged environment, with a −180 mV potential across the IMM, as well as being slightly alkaline compared with the intermembrane space and cytosol. This attracts positively charged molecules to the matrix and has been exploited by attaching positively charged moieties onto small molecules to target them to mitochondria, such as  triphenylphosphine (TPP), a lipophilic and cationic moiety (Smith et al., 2011). Impacts on mitochondrial function happen either directly or indirectly. Direct impacts involve small molecules binding to specific mitochondrial targets and impacting directly on a particular mitochondrial process, such as inhibition of mitochondrial DNA replication, modification of mitochondrial resident enzymes, and uncoupling of the electron transport chain. Indirect mechanisms involve small molecules modulating processes within the cell (not in the mitochondria) that eventually impact mitochondrial function. For example, potential indirect effects can be inhibition of fatty acid metabolism by carnitine sequestration in the cytoplasm, general oxidizing agents such as ROS and hydrogen peroxide, or inhibition of HMG‐CoA reductase, an important enzyme in the biosynthesis of the mitochondrial electron carrier coenzyme Q. Therefore, a certain subset of drugs with mitochondrial toxicity act by accumulating in mitochondria, while other drugs only need to gain entry to the cytoplasm to exert their effects. Delivery into these different cellular compartments affects the extent of toxicity by controlling the concentration of drug.

1.2 Small Molecule Delivery to Tissues Small molecules that enter into the bloodstream are transported through the circulatory system in one of two ways depending on their chemical properties. Plasma proteins in the circulation will have a certain affinity for small molecules depending on complementary interaction sites. Plasma proteins that interact readily with small molecules are albumins, lipoproteins, and alpha‐1 acid glycoprotein (AGP‐1)/orosomucoid (Pike et  al., 1983). Drugs with more hydrophilic properties will be soluble in the aqueous environment of the blood and be transported around the circulation until delivered to

target tissues and/or metabolized before clearance from the body. Drugs that interact with a plasma protein will bind to these proteins and be transported to tissues, whereas plasma soluble drugs will be freely delivered to target tissues. Interactions between drugs and plasma proteins are mostly determined by the chemical nature of a drug including hydrophobicity and charge at plasma pH, measured by log P and pKa, respectively. Binding to plasma protein provides a reservoir of the drug capable of providing a longer‐lasting reservoir of the drug compared with those more freely soluble in the bloodstream and may eventually accumulate in target tissues to a greater extent than the latter more hydrophilic drugs (Figure 1.1). Human serum albumin is the most abundant protein in human blood (35–50 g/L ~640 μM) and is responsible for carrying lipid‐soluble molecules such as hormones, steroids, and fatty acids in the circulation. Albumin tends to interact with acidic and neutral drugs at three specific sites that overlap with natural ligand binding sites (Sudlow et  al., 1975; Ghuman et  al., 2005). Due to the high concentration of albumin in the blood, this is the primary plasma transporter of acidic and neutral drugs systemically. Molecules transported by albumin are released in regions of low drug concentration. This mechanism enables drugs to be delivered to target tissues and enter into cells either by transport through specific plasma membrane transporters or via diffusion through the plasma membrane (see Section 1.3). Albumin bound drugs capable of inducing mitochondrial toxicity are listed in Table 1.1. Lipoprotein particles are also responsible for carrying hydrophobic drugs in the circulation, especially when albumin has been saturated. Acidic and neutral drugs can be bound by lipoprotein particles while being transported throughout the circulation. Lipoprotein particles are typically responsible for the transport of hydrophobic molecules, such as triglycerides and cholesterol, in the circulation to target tissues. The lipoprotein particle structure is made up of a polar surface composed of phospholipid, cholesterol, and apolipoprotein on the exterior allowing for solubility in the aqueous bloodstream and a hydrophobic core composed of triglycerides and cholesteryl esters sequestered away from the aqueous environment for delivery to target tissues. The hydrophobic core of lipoprotein particles is therefore the appropriate environment for hydrophobic drugs to be sequestered and transported to various tissues. Several varieties of lipoprotein particles exist that vary in the composition of protein and lipid. High‐density lipoprotein (HDL) particles have the highest protein‐to‐lipid ratio, while very low‐density lipoprotein (VLDL) particles contain the lowest ratio. Both intermediate‐density lipoprotein (IDL) and low‐density lipoprotein (LDL) particles have

Contributions of Plasma Protein Binding and Membrane Transporters to Drug‐Induced Mitochondrial Toxicity

Plasma protein

Protein-mediated transport

Diffusion-mediated entry

Mitochondrial function

Plasma protein

Intracellular target

Mitochondria

Target cell

Bloodstream

Figure 1.1 General mechanisms of drug delivery and impacts on mitochondrial functions in target cells. Drugs are carried by plasma proteins in the bloodstream. Drugs then enter into target cells using specific plasma membrane transporters or via passive diffusion. Drugs with targets in the cytoplasm bind to these target molecules, which then impact mitochondrial function. Drugs with target within mitochondria then enter into mitochondria to bind to the target and impact mitochondrial function. Table 1.1 Drugs that bind to serum albumin.

Drug

Plasma protein binding

Therapy

pKa

log P

References

Acetylsalicylic acid

50–80%

Analgesic/anti‐inflammatory

3.49

1.19

Sułkowska et al. (2006)

Amitriptyline

96%

Antidepressant

9.4

4.92

Brinkschulte and Breyer‐Pfaff (1980)

Chlorpromazine

>90%

Antipsychotic

9.3

5.41

Kitamura et al. (2006), Rukhadze et al. (2001), and Silva et al. (2004) all bovine serum albumin

Diazepam

>90%

Antianxiety

3.4

2.82

Brodersen and Honoré (1989)

Analgesic/anti‐inflammatory

4.15

4.51

Yamasaki et al. (2000)

Diclofenac Fluoxetine

94.5%

Antidepressant

9.8 (predicted)

4.05

Flurbiprofen

99%

Analgesic/anti‐inflammatory

4.42 (predicted)

4.16

Aarons et al. (1985) and Takla et al. (1985)

Ibuprofen

Analgesic/anti‐inflammatory

4.91

3.97

Yamasaki et al. (2000) and Galantini et al. (2010)

Indomethacin

Analgesic/anti‐inflammatory

4.5

4.27

Naproxen

Analgesic/anti‐inflammatory

4.15

3.18

Piroxicam

99%

Tetracycline Zidovudine

30–38%

Analgesic/anti‐inflammatory

6.3

3.06

Antibiotic

3.3

−1.30

Antiretroviral

0.05

Banerjee et al. (2006) bovine serum albumin Bratlid and Bergan (1976) Quevedo et al. (2001)

5

6

Mitochondrial Dysfunction by Drug and Environmental Toxicants

ratios between these two extremes. Lipoprotein parti‑ cles are taken up by LDL receptors present on every nucleated cell type, but especially by liver cells that take up the vast majority of LDL particles. LDL‐bound receptors undergo endocytosis, and eventually the LDL particle is trafficked to the lysosome by endosome fusion. In the lysosome the LDL particle is broken down into constituents, releasing free cholesterol, amino acids, and fatty acids for use in the cell. During the process of LDL particle internalization and transit to the lysosome, the drug may be able to exit into the cytoplasm via passive diffusion or facilitated transport through the endosomal or lysosomal membranes to gain access to the cellular target. There are reports of physical contacts between lysosomes and mitochon‑ dria‐derived vesicles (MDVs) where mitochondrial components are directed to lysosomes presumably for degradation. A reverse pathway has not been described, but could potentially exist, which could supply drugs directly from lysosomes to mitochondria. One drug that binds to lipoprotein particles is amitriptyline (log P, 4.92; pKa, 9.4), indicating a preference for hydropho‑ bic and basic molecules (Brinkschulte and Breyer‐ Pfaff, 1980). AGP‐1 is a plasma protein present at about 1–3% of total plasma protein and is responsible for transporting basic and neutral lipophilic molecules in the blood‑ stream. This allows AGP‐1 to associate with basic and neutral lipophilic drugs that would not normally associ‑ ate with albumin or lipoproteins. However, the serum concentration of AGP‐1 is much lower than albumin so that it becomes saturated at lower drug concentrations. AGP‐1 has a beta‐barrel cavity that is both hydrophobic and acidic, allowing for a variety of substrates to bind, and this cavity is sealed with sugar side chains covalently attached to the polypeptide backbone. Mitochondrial toxins that bind to AGP1‐ are listed in Table 1.2. In some cases, drugs are able to associate with more than one plasma protein. The antidepressants amitriptyline and fluoxetine associate with serum albumin and AGP‐1. This would allow for an increased plasma

accumulation of these drugs, thereby increasing exposure (Brinkschulte and Breyer‐Pfaff, 1980). There are some other plasma proteins that are less abundant that are also able to interact with drugs. For  example, transthyretin—the thyroxine and retinol‐ transporting protein—interacts with diclofenac to stabilize the active form of the protein (Almeida et al., 2004; Miller et  al., 2004). Other plasma proteins are likely to associate with drugs, but the vast majority of plasma protein binding is through albumin, LDL particles, and AGP‐1. Alterations in protein levels of either of these three can lead to alterations in drug transport in the circulation. Diseases associated with altered levels of albumin will alter saturation of drug binding sites. Hypoalbuminemia is caused by liver and kidney malfunctions, while hyperalbuminemia can be caused by dehydration. Decreased levels of albumin will result in a higher concentration of free drug that can lead to increased exposure to the drug and potentially increased mitochondrial toxicity. Elevated albumin levels would allow for more drugs to be sequestered from the circulation; however this could lead to increased persistence of the drug in the circulation and result in a delay in toxic effects. AGP‐1 plasma concentrations can be dramatically altered after infection, physiological changes such as pregnancy, and physical traumas such as burns. Also, lipoprotein particle concentrations vary in the population due to disease and diet, and so drug association with these particles will vary depending on the subject. Therefore, it can be seen that determination of the amounts of plasma proteins is an important consideration when administering any drug, especially those that  are associated with toxicity through impacts on mitochondria. A second consideration is when more than one drug is present in the circulation. As many drugs bind to similar regions on the various plasma proteins, the drug with the higher affinity for the plasma protein will displace that with lower affinity. This displacement will cause an effective increase in the plasma concentration of the lower affinity drug and increase the likelihood of toxicity.

Table 1.2 Drugs that bind to alpha‐1 glycoprotein.

Drug

Plasma protein binding

Therapy

pKa

log P

References

Amitriptyline

96%

Antidepressant

9.4

4.92

Brinkschulte and Breyer‐Pfaff (1980) and Ferry et al. (1986)

Amoxapine

90%

Antipsychotic

8.83 (predicted)

3.4

Ferry et al. (1986)

Fluoxetine

94.5%

Antidepressant

9.8 (predicted)

4.05

Propranolol

90%

Anti‐arrhythmia

9.42

3.48

Ferry et al. (1986)

Contributions of Plasma Protein Binding and Membrane Transporters to Drug‐Induced Mitochondrial Toxicity

1.3

Entry into Cells

Passage of small molecules from the circulation to the interior of a cell relies on two pathways. The chemical properties of the small molecules determine whether they will enter through plasma membrane transporters or pass freely without the aid of transporters via diffu‑ sion. Molecules with lipophilic properties are able to pass freely without membrane transporters and gain access to their sites of action. However, some molecules enter cells through plasma membrane transporters due to their physicochemical properties or similarity to membrane transporter substrates. The cellular reper‑ toire of plasma membrane transporters will therefore govern which small molecules will accumulate within a specific cell type or tissue and so yield organ‐specific toxicity. Several plasma membrane transporter families are involved in the entry of drugs into the cells. These trans‑ porters rely on plasma membrane solute gradients or binding and hydrolysis of ATP to power the entry of the molecule. The solute carrier family (SLC) of proteins is the main family of proteins responsible for transporting drugs into the cells. Substrates of these proteins are transported through facilitated transport or secondary active transport through coupled transport of a sub‑ strate going down the concentration gradient. Proteins not part of the SLC family of plasma membrane trans‑ porters are also capable of drug transport. These include members of the monocarboxylate transporter (MCT) family and Ral‐binding proteins. The MCT family of proteins is responsible for the transport of organic ions across the plasma membrane. Ral‐binding proteins associate with and regulate the activated GTP‐bound form of the G protein Ral that is involved in signal transduction pathways regulating gene expression, cell migration, cell proliferation, and membrane trafficking (Mott and Owen, 2014). The SLC family of transporters transports a wide array of substrates ranging from anions to cations and from small inorganic ions to amino acid‐derived hormones and metabolic carriers, such as carnitine. Transport of these substrates can also be dependent on counterions such as sodium and chloride. These transporters also display varying tissue distributions providing a mecha‑ nism for tissue‐specific accumulation of drugs, leading to tissue‐specific toxicity that is seen with drug‐induced mitochondrial toxicity. The specific types of transporters that allow for drug entry into cells include uptake recep‑ tors of neurotransmitters such as serotonin, noradrena‑ line, and dopamine in the synapse, carnitine transporters in fatty acid‐metabolizing tissues, and copper and steroid hormone and steroid conjugate transporters in tissues with these requirements.

The majority of transporters of drugs into cells are members of the SLC22 family. This includes transporters of organic anions and cations. SLC22A6 (organic anion transporter 1 (OAT‐1)) and SLC22A7 (organic anion transporter 2 (OAT‐2)) are the main transporters of endogenous organic anions such as dicarboxylic acids, prostaglandins, and cyclic nucleotides. These transport‑ ers are highly expressed in the basolateral membrane of epithelial kidney proximal tubule cells (Lopez‐Nieto et al., 1997). These transporters function as antiporters with endogenous dicarboxylic acids cotransported. Increased activity of these transporters can deplete cellular dicarboxylic acids, such as α‐ketoglutarate, which are important components of the citric acid cycle. Organic anion transporters (OATs) are responsible for the transport of several nonsteroidal anti‐inflammatory drugs and antiretroviral drugs such as zidovudine (Takeda et  al., 2002). As the kidney is one of the main routes of drug excretion, drugs can accumulate in the kidneys through these transporters, resulting in kidney‐ specific mitochondrial dysfunction. Interestingly, as dicarboxylic acids are removed from kidney epithelial cells upon drug entry through OATs, this may act as a double hit to these cell types as critical substrates for the citric acid cycle are depleted along with the toxic effects of drugs on mitochondria such as ROS generation, mitochondrial membrane depolarization, and mitochondrial DNA replication inhibition. A related organic anion transporter, SLC02B1 (OATP‐2), is also capable of transporting ibuprofen into the cells (Satoh et al., 2005). SCL02B1 is highly expressed in the liver and functions as a transporter for steroids and steroid conjugates. The organic cation transporters SLC22A5 (OCTN‐2) and SLC22A16 are sodium‐dependent carnitine transporters that are widely expressed to deliver carnitine to fatty acid‐metabolizing tissue. Carnitine is a quaternary ammonium molecule with an overall positive charge, and molecules with similar chemical properties can be substrates of these transporters. Doxorubicin is reported to be a substrate of SLC22A16 (Okabe et  al., 2005). SLC22A2 (organic cation transporter 2 (OCT‐2)) is expressed in the basolateral membrane of kidney proximal tubules and transports cations from the blood into the kidney epithelium for excretion. The chemotherapeutic agent cisplatin is transported via OCT‐2 into kidneys where accumulation can lead to nephrotoxicity (Burger et al., 2010). The neurotransmitter reuptake transporters SLC6A2, SLC6A3, and SLC6A4 are specific for noradrenaline, dopamine, and serotonin, respectively. These transporters are all symporters by transporting sodium simultaneously with the neurotransmitter. These neurotransmitters are part of the monoamine family of molecules and all contain modified aromatic rings, so that drugs with

7

8

Mitochondrial Dysfunction by Drug and Environmental Toxicants

related structures will be substrates for these transport‑ ers. Inhibitors of the reuptake transporters are com‑ monly used as antidepressants. These drugs function by preventing the neurotransmitters from binding to the receptor, thereby extending their synaptic dwell times. For example, citalopram is a potent inhibitor of the serotonin reuptake transporter, resulting in increased neuronal accumulation (Bareggi et al., 2007). The high affinity copper transporters SLC31A1 and SLC31A2 (copper transporter 1 and 2, respectively (CTR‐1 and CTR‐2)) are responsible for the uptake of drugs like cis‐platinum, carboplatin, and oxaliplatin (Song et al., 2004). As copper is an essential cofactor for many enzymes, copper transporters are ubiquitously expressed and will render all cell types susceptible to platinum‐based drug accumulation and toxicity. The MCT family of plasma membrane proton‐ and ion‐linked transporters is part of the SLC family and has an important role in the transport of small charged molecules across the plasma membrane. This family of transporters is involved in the distribution of drugs to various tissues and organs such as the brain (Vijay and Morris, 2014). The anticonvulsant valproate (Depakote) is likely a substrate for MCT‐1 (Fischer et al., 2008). This transporter is ubiquitously expressed and has substrate specificity for short‐chain aliphatic monocarboxylic acids, such as pyruvate and acetoacetate, and short‐chain fatty acids (up to 6 carbon atoms), which are structurally related to valproate (Halestrap and Meredith, 2004). Valproate is a putative carnitine and intramitochondrial sequestering agent, and therefore accumulation of the drug will have impact on cells and tissues that have high metabolic dependency on carnitine for oxidation of fatty acids in mitochondria. Due to these properties, valproate results in severe hepatotoxicity as the liver expresses MCT‐1 and is also a site of both carnitine biosynthesis and coenzyme A‐dependent metabolism (Coulter, 1991; Fromenty and Pessayre, 1995). The carnitine‐binding activity of valproate would be relevant in the cytoplasm and so would not need to gain access to mitochondria to  yield toxic side effects. However, the coenzyme A‐dependent effects would require access to the mitochondrial matrix. How valproate enters the mitochondrial matrix is not well described; however, as it has structural similarity to short‐chain fatty acids, it may be able enter simply by diffusion. Lovastatin, a small molecule that inhibits cholesterol synthesis, is a substrate for MCT‐4 in cultured mesangial cells from rats (Nagasawa et  al., 2002). It is associated with kidney failure as well as myopathy. It also displays both direct and indirect effects on mitochondrial physiology by inhibiting and uncoupling OXPHOS and via decreasing coenzyme Q levels. Skeletal muscle expresses MCT‐4 (Pilegaard et  al., 1999), and this would be in

accord with lovastatin accumulation in the muscle by entry via MCT‐4, so affecting coenzyme Q levels (Folkers et al., 1990). It should be noted in this context that the abundance of this transporter is higher in slow twitch muscle fibers, likely resulting in their greater susceptibility to statin‐induced rhabdomyolysis. Statins are also responsible for lowering plasma LDL, which are used to transport coenzyme Q in the circulation. Therefore, the effects of statins on coenzyme Q levels could also be due to systemic changes in general lipid transport in the circulation (Littarru and Langsjoen, 2007). The analgesics ibuprofen, aspirin, and diclofenac are also substrates for MCTs, as they are low molecular weight monocarboxylic acids (Tamai et  al., 1995; Choi et al., 2005). They are transported by MCT‐1, a ubiquitously expressed member of this family. These molecules are associated with a variety of toxicities due to impacts on mitochondrial function including hepatotoxicity. An unusual transporter of certain drugs into cells is RALBP1 (RalA‐binding protein 1). This protein functions mostly during receptor‐mediated endocytosis by acting as an effector molecule for the small GTPase RalA. RALBP1 has been identified as a transporter of lipid peroxidation‐derived glutathione conjugates that mediates transport of the chemotherapeutic agent doxorubicin (Awasthi et al., 2000). There are also suggestions that the ATP‐binding cassette (ABC) transporter, ABCG2, that is conventionally associated with drug efflux can transport doxorubicin into the cells (Kawabata et al., 2003; Singhal et al., 2007). Several drugs are transported by transporters from different families, such as valproate, ibuprofen, and acetylsalicylic acid (Table 1.3). This allows a greater range of tissue exposure of these drugs and therefore increases the likelihood of any toxicity.

1.4 Transport Out of Cells Cells have a variety of mechanisms that remove drugs and endogenous molecules that may accumulate to yield toxicity. These efflux pumps are usually coupled to ATP hydrolysis and are therefore active transporters. The main transporter types that remove drugs from cells are the ABCB‐ and ABCC‐type ABC transporters, plus the ATPase coupled transporters (ATP7 family), as well as some of the SLC family. The largest family of membrane transporters—the ATP ABC transporters—transports the majority of drugs out of cells. These transporters have a cytosolic ATPase domain that is required for efflux out of the cell. This transporter family recognizes a wide variety of substrates to rid cells of toxic levels of molecules (Chen et  al., 2016). ABCB1 is the most common

Table 1.3 Transporters of mitochondrial toxic drugs. Transporter family

Drug name

Anticonvulsants

Valproate

Antidepressants

Amitriptyline

ABCB1

Faassen et al. (2003) and Mahar Doan et al. (2002)

Fluoxetine

ABCB1

Weiss et al. (2003)

Citalopram

ABCB1

Chlorpromazine

ABCB1

Polli et al. (2001) and Boulton et al. (2002)

Haloperidol

ABCB1

Mahar Doan et al. (2002), Boulton et al. (2002), and Nagy et al. (2004)

Risperidone

ABCB1

Faassen et al. (2003) and Boulton et al. (2002)

Barbiturates

Phenobarbital

ABCB1

Schuetz et al. (1996) and Luna‐Tortós et al. (2008)

Antianxiety

Diazepam

ABCB1

Yamazaki et al. (2001) and Adachi et al. (2001)

Antipsychotics

ABC

ATP

MCT

SLC

MCT‐1

SLC22A6 SLC22A7

Other transporter

Drug class

Cholesterol

Statins—lovastatin

ABCC2

MCT‐4

Ibuprofen

ABCB1

MCT‐1

Acetylsalicylic acid

ABCB1

MCT‐1

Acetaminophen

ABCB1

Diclofenac Indomethacin

Ohashi et al. (1999) and Kobayashi et al. (2002)

Bareggi et al. (2007)

SLC6A2 SLC6A3 SLC6A4

Analgesic/ anti‐inflammatory

Nagasawa et al. (2002) Khamdang et al. (2002), Choi et al. (2005) and Satoh et al. (2005)

SLCO2B1 SLC22A6 SLC22A8 SLC22A7

Choi et al. (2005)

SLC22A6

Faassen et al. (2003) and Wang et al. (2001)

MCT‐1 ABCB1

Choi et al. (2005) SLC22A6 SLC22A8

Antibiotics

Minocycline

Antiretroviral

Zidovudine

ABCB1 ABCC4 ABCC5 ABCG2

SLC22A6

Anticancer

Doxorubicin

ABCB1 ABCB8 (mitochondrial) ABCB11 ABCC1 ABCC2 ABCC6 ABCG2

SLC22A16

Cis‐platinum

ABCB1 ABCC6 ABCG2

Tamoxifen

ABCB1 ABCC2 ABCG2

Khamdang et al. (2002) Active transport Sodium dependent

ATP7A ATP7B

References

SLC22A2 SLC31A1 SLC31A2

Brayton et al. (2002)

Anderson et al. (2006), Abla et al. (2008), Jorajuria et al. (2004), Pan et al. (2007), and Takeda et al. (2002) RALBP1

Singhal et al. (2007), Kawabata et al. (2003), and Okabe et al. (2005)

Song et al. (2004), Burger et al. (2010), Howell et al. (2010), and Holzer et al. (2004) Janvilisri et al. (2003)

10

Mitochondrial Dysfunction by Drug and Environmental Toxicants

multidrug resistance protein (MDR‐1) and has a wide array of substrates with almost every class of drug being exported by this protein. There are also transporters related to ABCB1 capable of drug efflux including ABCB11, ABCC1, ABCC4, ABCC5, and ABCC6 that transport molecules such as bile salts, organic anions, and cyclic nucleotides, among others. Some of these transporters have wide tissue expression, while some have cell‐type‐specific expression such as ABCB11 that is expressed only in the liver and little elsewhere (Vasiliou et al., 2009).

1.5

Entry into Mitochondria

Several mitochondrial toxins are weak acids that, when protonated, are lipid soluble. These molecules act as protonophores and result in dissipation of the mitochondrial membrane potential, thereby uncoupling electron transport from ATP synthesis. These uncoupling agents cause an increased rate of respiration, effectively causing both heat dissipation and substantial increase in oxygen radicals that can overwhelm the oxidative stress resistance capacity. If this is the case, ROS are able to damage macromolecules in the mitochondria such as mitochondrial DNA, phospholipids, and proteins. A general stress of this nature results in overall mitochondrial dysfunction as ATP synthesis and the mitochondrial membrane potential are not maintained with an overall outcome of cellular dysfunction and tissue failure. Examples of mitochondrial toxins in this class are several small molecules

–

Protonation

used as analgesics and anti‐inflammatory molecules such as acetylsalicylic acid (aspirin), mefenamic acid, nabumetone, naproxen, diclofenac, and dipyrone in the rat intestine (Somasundaram et  al., 1997) and kidney (Mingatto et al., 1996). Evidence for the direct action of these small molecules as uncoupling agents is widely available when using isolated mitochondria as well as in isolated cells and when administered to rodents (Mingatto et al., 1996; Somasundaram et al., 1997). In the cytoplasm these molecules exist in their ionized anion state; in the intermembrane space the concentration gradient of protons across the IMM creates an environment with a lower pH than that in the matrix. The ionized form becomes protonated due to the high concentration of protons, rendering the small molecule unionized and hence much more lipophilic. In this state the small molecule can pass through the IMM via diffusion. In the matrix the small molecule deprotonates as protons are used by the electron transport system to attempt to restore the membrane potential. The rapid translocation of the protons by the small molecule dissipates the mitochondrial membrane potential and prevents proton translocation through ATP synthase, thereby diminishing ATP generation (Figure 1.2). Positively charged amphipathic molecules are able to enter the mitochondrial matrix once they arrive at the mitochondrial intermembrane space. The positively charged molecule then accumulates in the mitochondrial matrix due to the difference in charge across the membrane (Figure  1.2). This phenomenon is aided by the lipophilic nature of the molecule, allowing it to pass

+

+

Passive diffusion across IMM

Transport driven by ΔΨm

Loss of ΔΨm – + + Deprotonation

Matrix Inner mitochondrial membrane Intermembrane space Outer mitochondrial membrane

Figure 1.2 Entry of drugs into the mitochondria occurs by two mechanisms. Negatively charged amphipathic molecules are protonated in the intermembrane space. The drug now has no charge and is maximally able to pass through the IMM via diffusion. In the matrix the drug becomes deprotonated. This process results in the dissipation of the mitochondrial membrane potential and can result in mitochondrial dysfunction.

Contributions of Plasma Protein Binding and Membrane Transporters to Drug‐Induced Mitochondrial Toxicity

through the IMM without the aid of a protein channel of transporter. Small molecules such as the antiarrhythmic drug amiodarone, the anticancer drug tamoxifen, the antianginal agent perhexiline, and the opioid buprenor‑ phine accumulate in liver mitochondria through this mechanism (Fromenty et al., 1990; Larosche et al., 2007; Begriche et al., 2011). Short‐ to medium‐chain fatty acids up to 12 carbons in length are able to cross the IMM freely to enter into the matrix for β‐oxidation without the aid of protein transporters. Small molecules that resemble these types of fatty acids are able to pass through the IMM because of  the shared properties. Examples of drugs using this mechanism are valproate (see above).

1.6

Export from Mitochondria

The ABC transporter ABCB8 is localized to the IMM (Hogue et al., 1999) and is a putative exporter of iron– sulfur clusters from the mitochondrial matrix. ABCB8 acts as an exporter of doxorubicin from mitochondria and provides protection for the mitochondrial genome from intercalation and inhibition of DNA replication (Elliott and Al‐Hajj, 2009). ABCB8 is ubiquitously expressed, and although its exact function is not known, it has been shown to protect cardiomyocytes against oxidative stress (Ardehali et al., 2005).

1.7

Concluding Remarks

As mitochondria are the primary source of ATP in most tissues and organs, any impact on mitochondrial function caused by a drug can be severely detrimental. Drugs can be transported systemically through the circulation while liganded to a variety of plasma proteins and so delivered to almost every tissue. Plasma protein binding prolongs the persistence of a drug in the circulation, potentially increasing toxicity. Drugs toxic to mitochondria can enter the cells through diffusion through the plasma membrane or via transport facilitated by transporters and channels. Many members of membrane transport protein families, such as SLC, MCT, and ATP, are able to transport drugs toxic to mitochondria both into and out of cells. Once in the cytoplasm, drugs toxic to mitochondria can elicit effects by interacting with cytoplasmic or non‐mitochondrial targets. Some drugs toxic to mitochondria enter into mitochondria to elicit their effects, which can occur via passive or facilitated transport across the two mitochondrial membranes. Cells have mechanisms to remove toxic molecules, and these are able to reduce the intracellular concentration of a drug to minimize toxic effects. Therefore, considerations of the pharmacokinetic properties of drugs at more complex and tissue‐specific levels are increasingly illuminating efficacy as well as toxicity, so offering potential avenues to increase the former while decreasing the latter.

References Aarons, L., Khan, A.Z., Grennan, D.M., and Alam‐Siddiqi, M. 1985. The binding of flurbiprofen to plasma proteins. The Journal of Pharmacy and Pharmacology 37(9), pp. 644–646. Abla, N., Chinn, L.W., Nakamura, T., Liu, L., Huang, C.C., Johns, S.J., Kawamoto, M., Stryke, D., Taylor, T.R., Ferrin, T.E., Giacomini, K.M., and Kroetz, D.L. 2008. The human multidrug resistance protein 4 (MRP4, ABCC4): functional analysis of a highly polymorphic gene. The Journal of Pharmacology and Experimental Therapeutics 325(3), pp. 859–868. Adachi, Y., Suzuki, H., and Sugiyama, Y. 2001. Comparative studies on in vitro methods for evaluating in vivo function of MDR1 P‐glycoprotein. Pharmaceutical Research 18(12), pp. 1660–1668. Almeida, M.R., Macedo, B., Cardoso, I., Alves, I., Valencia, G., Arsequell, G., Planas, A., and Saraiva, M.J. 2004. Selective binding to transthyretin and tetramer stabilization in serum from patients with familial amyloidotic polyneuropathy by an iodinated diflunisal

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Contributions of Plasma Protein Binding and Membrane Transporters to Drug‐Induced Mitochondrial Toxicity

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Mahar Doan, K.M., Humphreys, J.E., Webster, L.O., Wring, S.A., Shampine, L.J., Serabjit‐Singh, C.J., Adkison, K.K., and Polli, J.W. 2002. Passive permeability and P‐ glycoprotein‐mediated efflux differentiate central nervous system (CNS) and non‐CNS marketed drugs. The Journal of Pharmacology and Experimental Therapeutics 303(3), pp. 1029–1037. Miller, S.R., Sekijima, Y., and Kelly, J.W. 2004. Native state stabilization by NSAIDs inhibits transthyretin amyloidogenesis from the most common familial disease variants. Laboratory Investigation 84(5), pp. 545–552. Mingatto, F.E., Santos, A.C., Uyemura, S.A., Jordani, M.C., and Curti, C. 1996. In vitro interaction of nonsteroidal anti‐inflammatory drugs on oxidative phosphorylation of rat kidney mitochondria: respiration and ATP synthesis. Archives of Biochemistry and Biophysics 334(2), pp. 303–308. Mott, H.R. and Owen, D. 2014. Structure and function of RLIP76 (RalBP1): an intersection point between Ras and Rho signalling. Biochemical Society Transactions 42(1), pp. 52–58. Nagasawa, K., Nagai, K., Sumitani, Y., Moriya, Y., Muraki, Y., Takara, K., Ohnishi, N., Yokoyama, T., and Fujimoto, S. 2002. Monocarboxylate transporter mediates uptake of lovastatin acid in rat cultured mesangial cells. Journal of Pharmaceutical Sciences 91(12), pp. 2605–2613. Nagy, H., Goda, K., Fenyvesi, F., Bacsó, Z., Szilasi, M., Kappelmayer, J., Lustyik, G., Cianfriglia, M., and Szabó, G. 2004. Distinct groups of multidrug resistance modulating agents are distinguished by competition of P‐glycoprotein‐ specific antibodies. Biochemical and Biophysical Research Communications 315(4), pp. 942–949. Ohashi, R., Tamai, I., Yabuuchi, H., Nezu, J.I., Oku, A., Sai, Y., Shimane, M., and Tsuji, A. 1999. Na(+)‐dependent carnitine transport by organic cation transporter (OCTN2): its pharmacological and toxicological relevance. The Journal of Pharmacology and Experimental Therapeutics 291(2), pp. 778–784. Okabe, M., Unno, M., Harigae, H., Kaku, M., Okitsu, Y., Sasaki, T., Mizoi, T., Shiiba, K., Takanaga, H., Terasaki, T., Matsuno, S., Sasaki, I., Ito, S., and Abe, T. 2005. Characterization of the organic cation transporter SLC22A16: a doxorubicin importer. Biochemical and Biophysical Research Communications 333(3), pp. 754–762. Pan, G., Giri, N., and Elmquist, W.F. 2007. Abcg2/Bcrp1 mediates the polarized transport of antiretroviral nucleosides abacavir and zidovudine. Drug Metabolism and Disposition: The Biological Fate of Chemicals 35(7), pp. 1165–1173. Pike, E., Kierulf, P., Skuterud, B., Bredesen, J., and Lunde, P. 1983. Drug binding in sera deficient in lipoproteins, albumin or orosomucoid. British Journal of Clinical Pharmacology 16(3), pp. 233–239.

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2 The Role of Transporters in Drug Accumulation and Mitochondrial Toxicity Kathleen M. Giacomini1 and Huan‐Chieh Chien1,2 1 2

Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA Apricity Therapeutics Inc., San Francisco, CA, USA

CHAPTER MENU 2.1 Introduction to Chapter, 15 2.2 The Solute Carrier (SLC) Superfamily, 15 2.3 Transporters as Determinants of Drug Levels in Tissues and Subcellular Compartments, 17 2.4 Drug Transporters in the Intestine, 18 2.5 Drug Transporters in the Liver, 18 2.6 Drug Transporters in the Kidney, 19 2.7 Mitochondrial Transporters, 20 2.8 Conclusions, 22 References, 22

2.1

Introduction to Chapter

In this chapter, an introduction to transporters that play a role in the accumulation of solutes in tissues, cells, and subcellular compartments is presented. The focus of the chapter is on transporters in the solute carrier (SLC) superfamily. Following a brief introduction on the SLC superfamily and an overview of how transporters can mediate toxicity as well as detoxification, the chapter focuses on transporters in the intestine, liver, and kidney. These tissues are sites of toxicity because of their role in absorption and elimination of xenobiotics including chemical carcinogens and many environmental toxins. Transporters in these tissues work with enzymes as the body’s primary detoxification mechanism. For example, toxins absorbed in the intestine through various mecha‑ nisms may enter the liver through hepatic transporters and be subsequently metabolized via various enzymes. Hydrophilic metabolites of many toxic substances may be eliminated in the kidney by secretory transporters that mediate transepithelial flux into the tubule lumen and urine. Following an overview of transporters in these major absorption and elimination organs, a discussion of mitochondrial transporters is presented. These highly

conserved transporters in the SLC25 family move their substrates in and out of mitochondria and play vital roles in mitochondrial toxicity of many substances. Finally, a short conclusion is presented, which highlights areas that need further study.

2.2 The Solute Carrier (SLC) Superfamily Transporters on cell membranes play critical roles in the disposition of endogenous molecules, macro‐ and micro‑ nutrients from dietary sources, and xenobiotics includ‑ ing environmental toxins, chemical carcinogens, and prescription drugs (Giacomini et  al., 2010). Of the two major superfamilies of transporters that have received wide attention in the disposition of xenobiotics, the ATP‐binding cassette superfamily (ABC superfamily) and SLC superfamily (Lin et al., 2015; Nigam, 2014), this chapter will focus on the latter, which includes mitochondrial transporters as well as transporters on the plasma membrane and on membranes of subcellular organelles. Human ABC transporters, which are efflux pumps, driven by ATP hydrolysis are reviewed elsewhere

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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Mitochondrial Dysfunction by Drug and Environmental Toxicants

Active transport

Facilitated transport

Electrochemical gradient

Electrochemical gradient

Solute concentration

Solute concentration

ATP

Primary

ADP Secondary Na+

Na+ X

Antiport

X

Uniport

Symport

Extracellular

Intracellular

Extracellular

Intracellular

Figure 2.1 Active transport and facilitated transport. Active transport is either primary or secondary. In primary active transport, ATP is hydrolyzed to provide the free energy needed for transport against electrochemical gradient. Secondary active transport uses the energy stored in the concentration gradient of a driven ion (i.e., Na+) and then couples the movement of another molecule or ion with that gradient. When the driving ion and driven ions move in opposite directions, the process is termed an antiport mechanism. When the driving and driven ions move in the same direction, the process is termed a symport mechanism. Facilitated transport is a process in which molecules or ions are transported across the plasma membrane with the help of membrane proteins. Transporters in the SLC superfamily are facilitated or secondary active transporters. ADP, adenosine diphosphate; ATP, adenosine triphosphate; X, transporter substrates.

(Rees et al., 2009; Szakács et al., 2006). The SLC superfamily currently consists of 52 families organized by sequence homology and approximately 395 transporters. Transporters in the SLC superfamily are facilitated or secondary active transporters (Figure  2.1). Facilitated transporters move their substrates across cellular membranes in accordance with the electrochemical gradient. In contrast, secondary active transporters may move their substrates across the plasma membrane against the concentration gradient. They rely on ion gradients across cellular membranes, which have been created by primary active proteins that directly use ATP. For example, Na+/K+ ATPase, which uses ATP to actively pump Na+ and K+, creates an Na+ gradient across the plasma membrane, which is harnessed by many Na+‐dependent secondary active transporters to actively move their substrates from extracellular to intracellular spaces (Morth et  al., 2011). For example, the mitochondrial toxin N‐ methyl‐4‐phenylpyridinium (MPP+) is transported across the plasma membrane of dopaminergic neurons by the Na+‐dependent dopamine transporter (DAT) SLC6A3 and accumulates against its concentration gradient in dopaminergic neurons, ultimately causing cell death (Storch et al., 2004).

Membrane transporters in the SLC superfamily are generally multi‐pass membrane proteins. Secondary structures of the transporters, based on hydropathy analyses, have been predicted and in many cases validated (César‐Razquin et  al., 2015; Schlessinger et  al., 2013). However, to understand the mechanisms by which the transporters actually translocate their substrates across plasma membranes, crystal structures are needed, in particular structures of the transporters in multiple conformations. Unfortunately, as with all membrane proteins, crystal structures of SLC transporters have been difficult to obtain. Thus, the molecular mechanisms by which SLC transporters mediate transmembrane flux of their substrates are poorly understood. Currently, a limited number of prokaryotic and eukaryotic transporters have been crystallized to high resolutions to enable some understanding of their molecular mechanisms. Two major protein folds or structural classes have become apparent. One is the major facilitator family (SLC2, SLC22) (Koepsell, 2013; Mueckler and Thorens, 2013), and the other is the neurotransmitter: sodium symporter (LeuT‐like fold) (Perez and Ziegler, 2013). A so‐called rocker‐switch model appears to characterize solute movement by proteins in the major facilitator family

The Role of Transporters in Drug Accumulation and Mitochondrial Toxicity

Figure 2.2 Rocker‐switch model. The rocker‐switch mechanism involves protein rearrangements around a substrate binding site that results in the substrate being alternately exposed to either side of the membrane.

Substrate Conformational change

Extracellular

Lipid bilayer

Intracellular

(Quistgaard et al., 2016) (Figure 2.2). In this model, the transporter alternates its open face between intracellular and extracellular spaces, allowing substrates to bind and be released. Transporters in the SLC2 family (or glucose transporter (GLUT) family) appear to work in this way, and data suggest that transporters in the SLC22 family are distantly related to SLC2 and share the major facilitator fold. With time, more structures will become available and lead to an increased understanding of the atomic structure of transporters and their molecular mechanisms. These structures will provide information for molecular docking, which can help predict the interaction of mitochondrial toxins and various xenobiotics with transporters.

2.3 Transporters as Determinants of Drug Levels in Tissues and Subcellular Compartments The tissue distribution of each transporter in the SLC superfamily is a key determinant of its biological, pharmacological, and toxicological roles. For example, the tissue distribution of the organic cation transporters (OCTs) (OCT1, OCT2, and OCT3) in the SLC22 family,

the organic ion transporter family, determines the physiologic and pharmacologic roles of the three paralogs (Table  2.1). OCTs have strongly overlapping substrate specificities, mediating the transmembrane flux of low molecular weight hydrophilic organic cations such as the highly prescribed antidiabetic drug metformin; the neurotransmitters serotonin and norepinephrine; and the mitochondrial toxin MPP+. Though substrate selectivity overlaps among the three transporters, they have unique roles because of their tissue distribution. In particular, OCT1 (SLC22A1) is highly expressed in the human liver, with much lower levels in other tissues, and as such plays a major role in the delivery of its substrates to the human liver, which may result in biological action, toxicity, or metabolism and biliary elimination in the liver. However, OCT2 (SLC22A2) is highly expressed in the kidney, where it plays a role in the nephrotoxicity of platinum drugs and in the renal secretion of its substrates including thiamine (vitamin B1) and many cationic drugs such as metformin. Finally, OCT3 (SLC22A3) is ubiquitously expressed at lower levels in multiple tissues and as such plays a role in tissue distribution and pharmacologic/biological activity of its substrates in many tissues including the intestine, liver, kidney, salivary glands, placenta, and blood–brain barrier. Though much attention has been paid to plasma membrane

Table 2.1 Selected transporters in the SLC22 family that play roles in the disposition of xenobiotics. Transporter

Gene

Major tissue distribution

Selected substrates

Selected inhibitors

OCT1

SLC22A1

Liver hepatocyte (sinusoidal)

Metformin, N‐methyl‐4‐phenylpyridinium (MPP+), tetraethylammonium (TEA)

Quinine, quinidine, disopyramide, verapamil

OCT2

SLC22A2

Kidney (proximal tubule)

Metformin, MPP+, TEA

Cimetidine, quinidine, quinine, rifampicin, testosterone

OCT3

SLC22A3

Ubiquitous (intestine, liver, kidney)

Metformin, MPP+, TEA, Ketamine

Cimetidine, quinidine, rifampicin, progesterone

OAT1

SLC22A6

Kidney (proximal tubule), placenta

Para‐aminohippurate, adefovir, cidofovir, methotrexate

Probenecid, novobiocin

OAT2

SLC22A7

Liver (sinusoidal)

2‐Deoxyguanosine, tetracycline, bumetanide

Indomethacin, cyclic GMP

OAT3

SLC22A8

Kidney (proximal tubule), placenta

Nonsteroidal anti‐inflammatory drugs (NSAID), furosemide, estrone‐3‐sulfate

Probenecid, novobiocin

17

18

Mitochondrial Dysfunction by Drug and Environmental Toxicants

transporters, transporters on subcellular organelles have also been characterized. For example, the vesicular monoamine transporters (VMATs) in the SLC18 family have been well characterized (Lawal and Krantz, 2013). These transporters, which take up neurotransmitters such as serotonin, norepinephrine, and dopamine, cycle from intracellular vesicles to the plasma membrane where they release neurotransmitters into the synaptic cleft for action at their receptors. In addition to interact‑ ing with endogenous neurotransmitters, the transport‑ ers also take up other compounds such as MPP+. In fact, through transport and storage in intracellular vesicles (and away from mitochondria), VMATs protect cells from the potent mitochondrial toxicity of MPP+.

2.4 Drug Transporters in the Intestine For an orally administered drug to reach a tissue, it must be taken into the bloodstream via intestinal absorption. Several factors such as compound solubility, chemical stability, and ability to permeate the intestinal surface (polarized enterocytes) will affect drug absorption and systemic bioavailability (the fraction of the dose that reaches the systemic circulation as intact drug). In addi‑ tion, uptake transporters in the SLC superfamily local‑ ized on the apical (brush border) or basolateral membrane of enterocytes facilitate the entry of poorly permeable molecules into the systemic circulation. Such transporters including PEPT1 (SLC15A1), OCTN1 (SLC22A4), and CNTs and ENTs (SLC28 and SLC29 superfamilies) play important roles in the absorption of drugs. ABC efflux transporters such as P‐gp (ABCB1), BCRP (ABCG2), and MRP2 (ABCC2) may limit the absorption of many prescribed drugs and other xenobi‑ otics (Giacomini et  al., 2010). Inhibition of these transporters in the intestine can improve oral drug bioavailability (e.g., verapamil or quinidine increases the plasma levels of digoxin by inhibiting P‐gp (Fromm et al., 1999; Verschraagen et al., 1999). In 2012, the US Food Drug Administration (FDA) proposed that drug developers use a decision tree to determine whether an investigational drug is a substrate (or inhibitor) of P‐gp or BCRP and to aid in determining whether an in vivo clinical drug–drug interaction (DDI) study is needed (FDA Guidance, 2012). As part of the proposed decision trees, the use of in vitro assays such as Caco‐2 cells, a colon adenocarcinoma cell line, was recommended as a model to test both intestinal permeability and efflux activity. Polarized cell lines such as Madin–Darby canine kidney cells (MDCK II), porcine kidney cells (LLC‐PK1), or MDR‐1‐overexpressing cells can also be used for in vitro bidirectional transport

assays. In their excellent review, Estudante et al. (2013) cataloged substrates, inhibitors, and inducers for intestinal efflux and uptake transporters important in drug absorption. In addition, Wu and Benet (2005) proposed a Biopharmaceutics Drug Disposition Classification System (BDDCS) that categorized drugs into four classes based on the drug’s solubility and extent of metabolism. The review and classification system may be helpful in predicting oral drug disposition including the potential of DDI in the intestine.

2.5

Drug Transporters in the Liver

After entry into the systemic circulation, drugs or compounds may distribute into the muscles and other organs such as the liver. Since the liver is the major organ responsible for drug metabolism and indeed for the metabolism of most xenobiotics, hepatic drug transporters can significantly modulate drug metabolism. In addition, hepatic blood flow rate, molecular size and polarity of compounds, binding of compounds to serum proteins, and transporter activity in the hepatocyte will affect the distribution of drugs into the hepatocyte. Figure  2.3 summarizes the uptake and efflux transporters on the basolateral/sinusoidal and apical/canalicular membranes. Uptake transporters such as OCT1 and OCT3 (SLC22A1 and A3), NTCP (SLC10A1), and OATP1B1 and OATP1B3 (SLCO1B1 and SLCO1B3) are localized to the sinusoidal (or basolateral) membrane where they mediate drug entry into the hepatocyte. Two hepatic uptake transporters,OATP1B1 (SLCO1B1) and OATP1B3 (SLCO1B3), are responsible for the uptake of many anionic drugs and play a role in DDI (FDA Guidance, 2012). Efflux transporters including BCRP (ABCG2), P‐gp (ABCB1), MRP2 (ABCC2), BSEP (ABCB11), and MATE1 (SLC47A1) located on the apical membrane transport drugs, drug metabolites, and bile salts across the canalicular membrane into the bile. MPR3 and MRP4 are efflux transporters on the basolateral membrane, which bring their substrates back into the systemic circulation (Funk, 2008; Köck and Brouwer, 2012; Russel et  al., 2008). Once drugs or compounds enter the hepatocytes, they may undergo phase I and/or phase II metabolism (Xu et al., 2005; Yoshida et al., 2013). Cytochrome P450 enzymes (CYPs) regulate phase I (oxidative metabolism), and UDP‐glucuronosyltransferase (UGT), sulfotransferase (SULT), and glutathione S‐transferase (GST) regulate phase II (conjugation reaction), respectively. Numerous studies have shown that metabolites of drugs or various xenobiotics may also be pharmacologically active and sometimes more than the original compounds (Fura, 2006; Obach, 2013). Thus, membrane transporters together with enzymes in

The Role of Transporters in Drug Accumulation and Mitochondrial Toxicity

Hepatocyte OCT1

BSEP

RP BC

OATP

gp

OCT3

P-

Circulation blood

Tight junction E1

T MA

OAT2

MR P2

Bile

including Xenopus laevis oocytes, membrane vesicles, various human embryonic kidney (HEK293) cell lines overexpressing transporters, and primary hepatocytes are commonly used to address questions about potential drug–drug and drug‐transporter interactions. Several issues may complicate in vitro transporter studies (i.e.,  lack of selective inhibitor/substrates and drug‐ transporter/drug metabolism interplay), and combining in silico modeling with in vitro studies will greatly accelerate our understanding of transporters in the liver (Barton et al., 2013; Li et al., 2014; Yoshida et al., 2013).

2.6 Drug Transporters in the Kidney

NTCP

OAT7 MRP4

MRP3

MRP6

Figure 2.3 Selected hepatic transporters for drugs and endogenous substances. Human hepatocyte uptake transporters in the basolateral (sinusoidal) membrane include organic cation transporters, OCT1 (SLC22A1) and OCT3 (SLC22A3); organic anion transporters, OAT2 (SLC22A7) and OAT7 (SLC22A9); organic anion‐transporting polypeptides, OATP1B1 (SLCO1B1), OATP1B3 (SLCO1B3), and OATP2B1 (SLCO2B1); and sodium‐taurocholate cotransporting polypeptide (NTCP, SLC10A1). Efflux pumps in the basolateral membrane include multidrug resistance‐associated protein 3 (MRP3, ABCC3), MRP4 (ABCC4), and MRP6 (ABCC6). Apical (canalicular) efflux pumps including P‐gp (ABCB1), bile salt export pump (BSEP, ABCB11), breast cancer resistance protein (BCRP, ABCG2), MRP2 (ABCC2), and multidrug and toxin extrusion protein 1 (MATE1, SLC47A1).

hepatocytes contribute to the disposition of drugs and other xenobiotics and may also be sites of DDI. For example, lovastatin or simvastatin, a HMG‐CoA reduc‑ tase inhibitor, that is metabolized by CYP3A can have more than 10‐fold increase in the blood when coadmin‑ istered with CYP3A inhibitors such as ketoconazole or erythromycin (Williams and Feely, 2002). Pharmacogenetics of major hepatic transporters have been reported (Franke et  al., 2010; Kerb, 2006). For example, non‐synonymous single nucleotide polymorphisms (SNPs) found in SLC22A1 either completely abolish or partially reduce its transport function (Koepsell et  al., 2007). Furthermore, polymorphisms of OATPs affect statins’ pharmacokinetics and efficacy (Kalliokoski and Niemi, 2009). SNPs in several ABC transporters including BSEP (ABCB11) and BCRP (ABCG2) result in lower efflux activities and had been associated with an increase in the systemic exposure of various compounds such as uric acid and statins (Ishikawa et al., 2005; Lang et al., 2007). In vitro models

SLC transporters in the kidney play vital roles in three of the kidney’s major functions: electrolyte balance, detoxification, and conservation of nutrients (Morrissey et al., 2013). In this section, an overview of SLC transporters involved in detoxification and conservation mechanisms will be presented.

2.6.1

Conservation Mechanisms

The kidney plays a critical role in the reabsorption of essential solutes including macronutrients such as glucose and amino acids, as well as micronutrients such as various vitamins and heavy metals. As many macro‐ and micronutrients are filtered in the glomerulus, reabsorptive transporters, many in the proximal tubule, serve to transport these molecules back into the systemic circulation, playing a vital role in the conservation of glucose, amino acids, oligopeptides, heavy metals, and vitamins. For transepithelial flux across the proximal tubule of the kidney from tubule lumen to systemic circulation (reabsorptive direction), distinct transporters are expressed on the apical and basolateral membranes. For example, transporters in the SLC5 family, notably SGLT2 (SLC5A2), reabsorb glucose across the apical membrane into the proximal tubule cell. SLC5 transporters work in concert with transporters in the SLC2 family, notably GLUT2, which are involved in moving glucose from the intracellular space across the basolateral membrane into the extracellular spaces and ultimately into the systemic circulation (Scheepers et al., 2004; Wright, 2013). Similar mechanisms are involved in reabsorptive flux of other compounds such as oligopeptides and amino acids, where transporters on the apical membrane involved in the transmembrane flux from lumen to cell are distinct from basolateral membrane transporters (Silbernagl, 1988). Often a secondary active transporter is involved in the uphill movement from lumen to cell (e.g., SGLT2

19

20

Mitochondrial Dysfunction by Drug and Environmental Toxicants

for glucose), and a facilitative transporter (e.g., GLUT2 for glucose) is present on the basolateral membrane serving in the downhill flux of substrates from cell to extracellular fluid. 2.6.2

Detoxification Mechanisms

The kidney is the key organ involved in the body’s defense mechanisms against chemical toxins. In particular, the kidney serves to eliminate many toxic substances and their metabolites through filtration in the glomerulus and secretory transporters in the proximal tubule. These transporters, which are generally classified as OCT and organic anion transporters (OATs), include transporters in the SLC22 family (OAT) as well as transporters in the SLC47 family (multidrug toxin and extrusion proteins (MATEs)) (Figure 2.4). The two most well‐studied OATs are OATs 1 and 3 (OAT1, SLC22A6 and OAT3, SLC22A8), which are both expressed on the basolateral membrane and mediate the first step in active tubular secretion of their substrates (Morrissey et  al., 2013). Substrates of these transporters include structurally diverse organic anions including many prescription drugs, for example, antibiotic agents such as penicillins and cephalosporins and antiviral agents such as adefovir and tenofovir (for review see (Burckhardt, 2012)). In addition, OATs are known to transport highly nephrotoxic compounds such as the nephrotoxin; ochratoxin A, which is a substrate of OAT3; and the antiviral drug cidofovir, which must be administered with probenecid, an inhibitor of OAT1 and OAT3, to reduce its accumulation and thus toxicity in the kidney (Burckhardt, 2012; Blood

Urine

OCT2

P-gp

OCT3

BCRP

OAT1

MRP2

OAT2 OAT3 OATP4C1

MRP4 MATE1 MATE2K

Tight junction

Figure 2.4 Selected renal transporters for drugs and endogenous substances. Kidney basolateral uptake transporters including OCT2 (SLC22A2) and OCT3 (SLC22A3) and OAT1 (SLC22A6), OAT2 (SLC22A7), OAT3 (SLC22A8), and OATP4C1 (SLCO4C1). Apical (luminal) transporters including P‐gp (ABCB1), BCRP (ABCG2), MRP2 (ABCC2), and MRP4 (ABCC4) and MATE1 (SLC47A1) and MATE2‐K (SLC47A2).

Hagos and Wolff, 2010). For basic compounds and organic cations, the major transporter on the basolateral membrane that mediates renal secretion is OCT2 (SLC22A2), which plays a key role in renal elimination of drugs and structurally diverse molecules. OCT2 has been implicated in both the nephrotoxicity and ototoxicity of cisplatin (Ciarimboli, 2012, 2014). Working in concert with OCT2 are two transporters in the SLC47 family, MATE1 and MATE2 (Motohashi and Inui 2013), on the apical membrane. These transporters mediate the electroneutral exchange of protons with organic cations and serve to move their substrates from tubule cell to lumen. Several studies have shown that there is much less nephrotoxicity of compounds that are substrates of both OCT2 and MATEs, because these dual substrates are easily secreted into the tubule lumen (Ciarimboli, 2012, 2014; Motohashi and Inui, 2013). However, for some compounds, such as cisplatin, which is an excellent substrate of OCT2, but not a substrate of MATEs, accumulation of the compound in the proximal tubule occurs with resulting nephrotoxicity.

2.7

Mitochondrial Transporters

Mitochondria are double membrane‐bound organelles that are essential to the aerobic eukaryotic cells. The number of mitochondria in a cell can vary from 0 (red blood cells) to more than 2000 (liver cells) (Alberts et al., 2002; Voet et  al., 2016). The outer membrane is freely permeable to small molecules such as sucrose, salt, and nucleotides but not to larger molecules like polyglucans, albumin, and cytochrome c (Salazar‐Roa and Malumbres, 2016). Because many metabolic processes occur in the cytosol followed by the mitochondrial matrix, mitochondrial transporters (or mitochondrial carriers) can transport metabolites formed in the cytosol across the inner mitochondrial membrane and, as such, serve to catalyze several important mitochondrial functions such as oxidative phosphorylation, citric acid cycle, fatty acid oxidation, and apoptosis (Chipuk et al., 2006; Wang and Youle, 2009). Mitochondrial transporters must ensure sufficient rate of solute flux to fulfill the needs of various metabolic pathways. Transport of solutes across the inner mitochondrial membrane is facilitated by transporters encoded by genes in the SLC25 family, which are present on chromosomal DNA. To date, 53 members have been reported in this family from SLC25A1 to SLC25A53 (Palmieri, 2013, 2014). They have similar molecular characteristics, that  is, a tripartite structure, six transmembrane alpha‐helices, and threefold repeat signature motifs that are different from any other transporter families (Berardi et al., 2011; Palmieri, 2013, 2014; Pebay‐Peyroula et  al., 2003).

The Role of Transporters in Drug Accumulation and Mitochondrial Toxicity

These  transporters have different tissue distributions and cellular expression; however, they may have overlapping selectivity for substrates (Palmieri, 2013, 2014). For example, SLC25A4, SLC25A5, and SLC25A6 (adenine nucleotide translocase 1‐3 (ANT1‐3)) are expressed at different levels in various organs, but ADP and ATP are the predominant substrates of all three transporters (Table  2.2, modified from reference (Palmieri, 2013)). Furthermore, several mitochondrial transporters are tissue specific (e.g., SLC25A27 in the brain), suggesting that they play important roles in special functions (Anitha et  al., 2012). Transporters of SLC25 family are not restricted to the mitochondria. For example, several SLC25 family members are located in other organelles such as peroxisomes (e.g., SLC25A17 in humans) (Agrimi et al., 2012), chloroplasts (plant, ortholog of SLC25A42) (Zallot et al., 2013), and mitosomes (parasite, ADP/ATP transporter) (Chan et  al., 2005). If classified by substrates, mitochondrial transporters can be divided into carriers for carboxylates, nucleotides, amino acids, keto acid, and other substrates. Uncoupling proteins (UCPs) (i.e., UCP 1–3, SLC25A7‐9; Table  2.2) are transmembrane proteins that decrease proton ions generated from oxidative phosphorylation. This reaction facilitates the movement of protons into the intermembrane space to return to the mitochondrial matrix. UCP1 is activated in the brown adipose tissue and inhibited by purine nucleotide such as ADP. It plays a critical role in thermogenesis (Krauss et al., 2005; Rousset et al., 2004). In this reaction, norepinephrine released by the sympathetic nervous

system triggers a signaling cascade: conversion of ATP to ADP, followed by catalysis of triglycerides into free fatty acids, which, in turn, activate UCP1 and thermogenin to generate heat. Many mitochondrial DNA mutations cause respiratory chain and oxidative phosphorylation defects. Only a few diseases that are caused by mutations in mitochondrial transporters have been found (Clémençon et  al., 2013; Gutiérrez‐Aguilar and Baines, 2013; Palmieri, 2014). These mitochondrial carrier‐related diseases can be divided into two categories: (1) diseases directly linked to oxidative phosphorylation or (2) diseases associated with mitochondrial carrier gene mutation (Palmieri, 2004, 2008). The first group of disorders include AAC1 deficiency (Palmieri et al., 2005), adPEO (van Goethem et  al., 2001; Kaukonen et  al., 2000), and PiC deficiency (Mayr et  al., 2007) and are caused by defects either in ADP/ATP translocase (SLC25A4) or PiC phosphate carrier (SLC25A3). These disorders are characterized by insufficient energy production. CAC deficiency (Huizing et  al., 1997) (defect of SLC25A20), HHH syndrome (Camacho et  al., 1999) (defect of SLC25A15), and Amish microcephaly (Kelley et  al., 2002) (defect of SLC25A19) belong to the second group. These transporters are responsible for transporting carnitine, ornithine, and thiamine pyrophosphate, respectively, as needed for cellular metabolism. Though much is known about several SLC25 family members, several still have not been characterized, and their functions remain to be determined.

Table 2.2 Selected transporters in the SLC25 family that move substrates across the inner mitochondrial membrane. Transporter

Gene

Major tissue distribution

Predominant substrates

CIC (citrate carrier)

SLC25A1

Liver, kidney, pancreas

Citrate, isocitrate, malate

ORC2 (ornithine carrier)

SLC25A2

Liver, testis, spleen

Ornithine, citrulline, lysine, arginine

PHC (phosphate carrier)

SLC25A3

Isoform A: heart, muscle Isoform B: liver, kidney, brain

Phosphate

ANT1 (adenine nucleotide translocase‐1)

SLC25A4

Heart, skeletal muscle, much less in brain, kidney, lung

ADP, ATP

ANT2 (adenine nucleotide translocase‐2)

SLC25A5

Brain, lung, kidney, pancreas

ADP, ATP

ANT3 (adenine nucleotide translocase‐3)

SLC25A6

Brain, lung, kidney, liver, pancreas

ADP, ATP

UCP1 (uncoupling protein 1)

SLC25A7

Brown adipose tissue

H+

UCP2 (uncoupling protein 2)

SLC25A8

Lung, kidney, spleen

H+

UCP3 (uncoupling protein 3)

SLC25A9

Skeletal muscle, lung

H+

DNC (deoxynucleotide carrier)

SLC25A19

Brain, testis, lung, kidney, liver, skeletal muscle, heart

Thiamine pyrophosphate (TPP), thiamine monophosphate (TMP), deoxynucleotides

CAC (carnitine/ acylcarnitine carrier)

SLC25A20

Heart, skeletal muscle, liver

Carnitine, acylcarnitine

21

22

Mitochondrial Dysfunction by Drug and Environmental Toxicants

2.8

Conclusions

Transporters in the SLC superfamily play critical roles in the accumulation of xenobiotics including mitochondrial toxins in cells, tissues, and organs. Working together, transporters in epithelia with distinct mechanisms medi‑ ate transepithelial flux of substrates, which generally pro‑ motes detoxification, for example, moving substrates from the blood to the tubule lumen and urine. Further, with enzymes, transporters play a major role in detoxification mechanisms in the body. That is, enzymes metabolize hydrophobic toxins to more hydrophilic molecules, which then interact with organic ion transporters in the kidney and undergo renal secretion. Mitochondrial transporters in the SLC25 family have a special role in the accumulation

of chemical substances within the mitochondria and have a direct role in mitochondrial toxicities. Currently there are 53 transporters in the SLC25 family, several of which are still orphan transporters with unknown substrates. These transporters are highly conserved across species, and polymorphisms are generally present at low allele frequencies. Mutations, which are generally rare, in mito‑ chondrial transporters lead to many genetic disorders such as optic atrophy spectrum disorder. For mitochon‑ drial toxins to exert their deleterious effects, they must first gain entry into the tissue of toxicity and then the mitochondria. Clearly, transporters in the SLC superfam‑ ily are involved in both the detoxification and toxicity of many mitochondrial toxins by mediating entry and exit from cells and subcellular compartments.

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The Role of Transporters in Drug Accumulation and Mitochondrial Toxicity

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Koepsell, H. (2013). The SLC22 family with transporters of organic cations, anions and zwitterions. Mol. Aspects Med. 34, 413–435. Koepsell, H., Lips, K., and Volk, C. (2007). Polyspecific organic cation transporters: structure, function, physiological roles, and biopharmaceutical implications. Pharm. Res. 24, 1227–1251. Krauss, S., Zhang, C.‐Y., and Lowell, B.B. (2005). The mitochondrial uncoupling‐protein homologues. Nat. Rev. Mol. Cell Biol. 6, 248–261. Lang, C., Meier, Y., Stieger, B., Beuers, U., Lang, T., Kerb, R., Kullak‐Ublick, G.A., Meier, P.J., and Pauli‐Magnus, C. (2007). Mutations and polymorphisms in the bile salt export pump and the multidrug resistance protein 3 associated with drug‐induced liver injury. Pharmacogenet. Genomics 17, 47–60. Lawal, H.O., and Krantz, D.E. (2013). SLC18: vesicular neurotransmitter transporters for monoamines and acetylcholine. Mol. Aspects Med. 34, 360–372. Li, R., Barton, H.A., and Varma, M.V. (2014). Prediction of pharmacokinetics and drug‐drug interactions when hepatic transporters are involved. Clin. Pharmacokinet. 53, 659–678. Lin, L., Yee, S.W., Kim, R.B., and Giacomini, K.M. (2015). SLC transporters as therapeutic targets: emerging opportunities. Nat. Rev. Drug Discov. 14, 543–560. Mayr, J.A., Merkel, O., Kohlwein, S.D., Gebhardt, B.R., Böhles, H., Fötschl, U., Koch, J., Jaksch, M., Lochmüller, H., Horváth, R., et al. (2007). Mitochondrial phosphate‐ carrier deficiency: a novel disorder of oxidative phosphorylation. Am. J. Hum. Genet. 80, 478–484. Morrissey, K.M., Stocker, S.L., Wittwer, M.B., Xu, L., and Giacomini, K.M. (2013). Renal transporters in drug development. Annu. Rev. Pharmacol. Toxicol. 53, 503–529. Morth, J.P., Pedersen, B.P., Buch‐Pedersen, M.J., Andersen, J.P., Vilsen, B., Palmgren, M.G., and Nissen, P. (2011). A structural overview of the plasma membrane Na+,K+‐ ATPase and H+‐ATPase ion pumps. Nat. Rev. Mol. Cell Biol. 12, 60–70. Motohashi, H., and Inui, K. (2013). Organic cation transporter OCTs (SLC22) and MATEs (SLC47) in the human kidney. Am. Assoc. Pharm. Scient. J. 15, 581–588. Mueckler, M., and Thorens, B. (2013). The SLC2 (GLUT) family of membrane transporters. Mol. Aspects Med. 34, 121–138. Nigam, S.K. (2014). What do drug transporters really do? Nat. Rev. Drug Discov. 14, 29–44. Obach, R.S. (2013). Pharmacologically active drug metabolites: impact on drug discovery and pharmacotherapy. Pharmacol. Rev. 65, 578–640. Palmieri, F. (2004). The mitochondrial transporter family (SLC25): physiological and pathological implications. Pflugers Arch. Eur. J. Physiol. 447, 689–709.

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3 Structure–Activity Modeling of Mitochondrial Dysfunction Steve Enoch1, Claire Mellor1, and Mark Nelms1,2 1 2

School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK US‐EPA, Raleigh‐Durham, NC, USA

CHAPTER MENU 3.1 3.2 3.3 3.4 3.5 3.6 3.7

3.1

Introduction, 25 Mitochondrial Toxicity Data Sources, 26 In Silico Modeling of Mitochondrial Toxicity, 27 Mechanistic Chemistry Covered by the Existing Structural Alerts, 31 Structural Alert Applicability Domains: Physicochemical Properties, 33 Future Direction: Structure–Activity Studies for Other Mechanisms of Mitochondrial Toxicity, 33 Concluding Remarks, 33 References, 34

Introduction

Computational toxicology plays a key role in helping to reduce drug attrition in the pharmaceutical industry by aiming to identify problematic chemicals early in the drug development phase (Naven and Louise‐May, 2015). In addition, it also plays an important role in a number of chemical industries, including the cosmetic sector, due to  European Union (EU) law aimed at replacing the use  of  animals in chemical risk assessment (European Commission, 2003, 2007). Increasingly, the methods used in computational toxicology have become a key part of the adverse outcome pathway (AOP) approach to toxicology (Ankley et al., 2010; Landesmann et al., 2013; Vinken, 2013). An AOP is a framework that means to establish a mechanistic connection between an upstream molecular initiating event (MIE) and a downstream adverse effect (e.g., organ toxicity) through a series of testable key events. The MIE is the critical event in the progression of an AOP as it provides insight into the initial interaction(s) between the chemical behavior of the xenobiotic and the biological system that initiates the  perturbation of the normal pathway. Elucidation of the mechanistic information relating to specific MIEs enables the identification of

structural (and physicochemical) features of chemicals that are responsible for the interaction with biological macromolecules, thus facilitating the development of structural alerts and/or (quantitative) structure–activity relationship ((Q)SAR) models. Importantly, these computational tools enable a mechanistic link between chemistry and biology to be established. Research has shown that a range of chemicals can induce mitochondrial dysfunction, leading to organ toxicity in the kidney, liver, cardiac, and nervous tissues (Amacher, 2005; Begriche et al., 2011; Chan et al., 2005; Dykens and Will, 2008; Esposti et al., 2012; Krahenbuhl, 2001; Masubuchi et  al., 2000; Montaigne et  al., 2012; Nadanaciva and Will, 2011; Pessayre et  al., 2012; Rolo et al., 2004). These tissues are most susceptible to mitochondrial dysfunction as they contain high concentrations of mitochondria and, in the case of the liver and  kidney, are exposed to higher concentrations of chemicals (or their metabolites). In order to be able to relate these organ effects to chemistry and thus build predictive structure–activity relationship models, it is important to understand the structure and function of the mitochondria and the possible mechanisms by which toxicity can occur.

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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3.1.1

Mitochondrial Structure and Function

Mitochondria consist of two membranes, the outer and inner membrane, enclosing three compartments, the intermembrane space, the cristae, and the mitochondrial matrix (Mannella, 2008). The outer membrane is rela‑ tively smooth and permeable to molecules that are less than 5 kDa in size. In contrast, the inner membrane con‑ taining multiple invaginations (cristae) is impermeable to all molecules except O2, CO2, and H2O and contains each of the protein complexes within the electron trans‑ port chain, ATP synthase (complex V), and various electron carriers. The mitochondria are responsible for a number of tasks vital to a cell’s normal functioning and  survival. These tasks include the production of approximately 95% of the total amount of adenosine triphosphate (ATP) generated by cells during oxidative phosphorylation. Oxidative phosphorylation is a process whereby energy from the transfer of electrons, generated by the oxidation of nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FADH2), along various complexes of the electron transport chain is utilized to pump protons across the inner mitochondrial membrane, generating an electrochemical gradient. The electron transport chain comprises four complexes situated within the inner mitochondrial membrane. Complexes I and II are involved in the oxidation of NADH and FADH2 respectively, providing the input of electrons into the respiratory chain. Complexes I, III, and IV use the energy released from the transfer of electrons along the electron transport chain to pump protons out of the mitochondrial matrix into the intermembrane space. Complex V, the terminal complex involved in oxidative phosphorylation, utilizes the electrochemical gradient produced to transfer protons from the intermembrane space back into the mitochondrial matrix. The energy released from this action is utilized to phosphorylate adenosine diphosphate into ATP.

3.1.2

Mechanisms of Mitochondrial Toxicity

Five general mechanisms of mitochondrial dysfunction have been identified: (i) inhibition of the electron transport chain and ATP synthase (complex V), (ii) uncoupling of oxidative phosphorylation, (iii) opening of the membrane permeability transition pore, (iv) inhibition of fatty acid β‐oxidation, and (v) disruption of mitochondrial DNA (mtDNA) (Chan et al., 2005; Dykens and Will, 2008; Krahenbuhl, 2001; Nadanaciva and Will, 2011; Scatena et al., 2007; Wallace and Starkov, 2000). Briefly stated, chemicals that inhibit the electron transport chain can do so by either direct binding to the complexes of the electron transport chain or ATP synthase or by acting as an alternative electron acceptor. The inhibition

of electron flow along the electron transport chain by both of these mechanisms may induce the formation of reactive oxygen species, resulting in oxidative stress. Uncouplers of oxidative phosphorylation induce mitochondrial toxicity by shuttling protons into the mitochondrial matrix, via the inner mitochondrial membrane, bypassing ATP synthase. This assisted transport of protons back into the matrix dissipates the electrochemical potential, resulting in the loss of ATP production and, ultimately, cell death. Induction of the membrane permeability transition increases the permeability of the inner mitochondrial membrane to low molecular weight solutes (2 years prior to the investigation of mitochondrial function. The arguments around differences in healthy controls versus patients with hypercholesterolemia again apply to inter‐study interpretation of data. Complex III of the mitochondrial electron transport chain has been suggested as a likely target for statin lactones (Schirris et  al. 2015), which are metabolites of  glucuronosyltransferase enzyme activity in vivo (Prueksaritanont et al. 2002). Basal oxygen consumption in C2C12 myoblasts, treated acutely, was observed for lactones of atorvastatin, cerivastatin, and pitavastatin (Schirris et  al. 2015). Specifically, 5/8 statin lactones reversibly inhibited mitochondrial complex III in isolated mitochondria albeit at relatively high concentrations (100 μM). In silico docking analysis supported the possibility that statin lactones might inhibit the Q0 site of complex III of the mitochondrial electron transport chain. Inhibition of respiration by statin lactones was attenuated by simultaneous convergent electron flow, which competed for binding at the Q0 site, providing a possible therapeutic option for mitigation of statin myopathy. In muscle biopsies from patients with statin‐ induced myopathy, complex III activity and mitochondrial ATP synthesis capacity were reduced compared with healthy controls (Schirris et al. 2015). Although age and sex corrected, these groups differed significantly with respect to phenotype, for example, they presumably suffered from an underlying hyperlipidemia, some having hypertension and diabetes, and there were possibly several other confounding factors present including a  difference in obesity profiles between groups.

Skeletal Muscle Mitochondrial Toxicity

Intriguingly, however, primary skin fibroblasts from individuals with complex III deficiency (28–46% of control) were more sensitive to statin lactone‐ (but not statin acid‐) induced cytotoxicity in vitro (Schirris et al. 2015) (note: this study was performed using n = 3 patients and n = 2 controls). Bouitbir et  al. (2012) proposed an intriguing mitochondrial mechanism to explain how statins might result in cardioprotection (via a mechanism termed “mitohormesis”) yet cause adverse events in skeletal muscle. Observations in a small number of humans revealed decreased atrial appendage oxidant levels and increased mRNA expression of the cytoplasmic and mitochondrial isoforms of superoxide dismutase in patients taking statins. This was associated with an increase in mRNA expression of peroxisome proliferator‐activated receptor gamma coactivator (PGC‐1) family members. PGC‐1 members are transcription factors that promote mitochondrial biogenesis (Kang & Li Ji 2012). In contrast, in patients with statin‐associated myopathy, oxidant levels were increased, and superoxide dismutase expression was greatly decreased in deltoid muscle biopsies compared with untreated healthy controls. Expression of PGC‐1 family members in the skeletal muscle biopsies was also substantially attenuated in the statin myopathy group. Maximal mitochondrial respiration was increased in atrial appendages but decreased in deltoid muscle in statin groups. The apparent cytoprotection by statins in heart muscle in humans was further investigated in rats administered with atorvastatin. Atorvastatin was shown to activate mitochondrial biogenesis (possibly via PGC‐1β pathways and mediated by increases in oxidant production by the statin) and increased mtDNA content in rat heart. In response to increased oxidants, mitochondrial SOD (SOD2) was increased, which subsequently resulted in lower oxidant detection in cardiac muscle. In glycolytic skeletal muscle, with poor endogenous antioxidant protection, atorvastatin enhanced oxidants as detected by electron paramagnetic resonance and dihydroethidium staining. This resulted in a state of oxidative stress in the skeletal muscle cells and decreased PGC‐1 expression, glutathione depletion, and SOD2 decreases (via PGC‐1 decreases) (Bouitbir et  al. 2012). Furthermore, the reduced PGC‐1 expression was associated with a decrease in the maximum mitochondrial respiration in skeletal muscle. Taken together, these effects, mediated by enhanced oxidant production by atorvastatin, were proposed to account for myalgia and general myopathy observed for some statin‐treated individuals. Based on these data, one might expect statins to result in in vivo oxidative stress. However, a recent study by Rasmussen et  al. (2016) in healthy male volunteers reported no effect of short‐term treatment with

simvastatin on in vivo oxidative stress measured using a panel of six markers including well‐validated urinary markers of DNA and RNA oxidation. Mitochondrial function was also studied in patients with hypercholesterolemia who had been treated with simvastatin (10–40 mg/day) for an average of 5 years (Larsen et  al. 2013). Mitochondrial respiration was measured using high‐resolution respirometry in permeabilized muscle fibers prepared from vastus lateralis muscle. Maximal oxidative phosphorylation with complex I and II linked substrates was not different between patients and controls; however, complex I linked substrate (glutamate) sensitivity was higher in simvastatin‐ treated patients than controls. Maximal oxidative phosphorylation capacity with maximized ex vivo input of electron donation into complexes I and II was higher in patients treated with simvastatin compared with controls. This is significant given that maximal fluxes in vitro are still much lower than those observed in vivo (Tonkonogi & Sahlin 1997). The authors claimed that CoQ10 content of muscles was reduced in the simvastatin group of patients but that mitochondrial content (assessed by measurement of citrate synthase, VDAC, and cardiolipin) was similar between the two groups. However, as reported previously, the methodology used in this study provided at best an indirect measure of ubiquinone synthesis (Navas 2013), so any conclusions about the role of CoQ10 depletion by simvastatin in myopathy are yet to be justified. In this study (Larsen et  al. 2013), comparison was made between patients taking long‐term simvastatin and healthy controls. The two groups under study were well matched for age, sex, and other parameters but differed in that patients were treated with simvastatin because of hypercholesterolemia and also were at risk of developing other pathologies such as diabetes, hypertension, and metabolic syndrome. Therefore, we do not know whether the changes observed, particularly to oxidative phosphorylation capacity, are due to the disease itself rather than the statin exposure. A more challenging, yet informative, study would involve a crossover design. One of the problems with this type of study would be that treatments with statins would need to be for a shorter period; we do not know if the changes observed in oxidative phosphorylation and CoQ10 would manifest during acute exposure to statins. Interestingly, the authors reported a quite different profile of skeletal muscle (vastus lateralis) fiber content between patients and controls. Patients had a lower content of type 1 fibers (42%) compared with healthy controls (58%), which may affect mitochondrial substrate utilization (Ponsot et al. 2005) and contribute to the observed increase in mitochondrial substrate sensitivity with substrates that donate electrons into complex I of the electron transport chain. For example,

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mitochondria from glycolytic muscles are well disposed via metabolic adaptation to regenerate NAD+ in the cytosolic compartment, thereby enabling proper glycolytic function (Ponsot et  al. 2005). The healthy control group used in this study does not allow us to fully interpret the potential “changes” in fiber content and whether this might be mediated by simvastatin exposure. If simvastatin does reduce the content of type 1 fibers in patients, then this will be very interesting given that in rats a variety of statins result in toxicity primarily to type 2 rather than type 1 fibers. 8.2.2.2.3

Studies in Other Species

While the effects of statins have been investigated mainly in humans and animal in vivo models, other notable models have been used to study the influences of these drugs on muscle mitochondria. A good example is the use of Caenorhabditis elegans, which lacks the pathway leading from mevalonate to cholesterol (see Figure 8.1) and can be used to study mechanisms not associated with sterol synthesis. Exposure of wild‐type worms to statins causes phenotypic effects that are rescued by mevalonate (Morck et al. 2009) and independent of inhibition of CoQ synthesis by statins (Rauthan et al. 2013). Forced activation of the mitochondrial unfolded protein response (UPRmt) results in the resistance of C. elegans to the effects of statins (Rauthan et al. 2013), suggesting that mitochondria are an important target in the toxic pathways from statins, at least in this model. This fits with the hypothesis that statins interfere with a mitochondrial surveillance pathway, that is, the process of sensing of mitochondrial damage in C. elegans and the subsequent activation of a protective response to the insult (Liu et al. 2014). Subsequently, the importance of HMG‐CoA reductase was highlighted in a C. elegans mutant (hmgr‐1(tm4368)) that lacks the reductase gene and therefore this enzymic activity (Ranji et  al. 2014). This mutation recapitulated the actions of statins in wild‐type worms, which included effects on the organization of mitochondria in the muscle. These muscle defects were rescued by the addition of mevalonate to culture media and by UPRmt activation; subsequently this group and others (Liu et al. 2014) demonstrated that the mevalonate pathway is required for UPRmt activation. Moreover, the resistance to statin cytotoxicity could be induced by activation of the UPRmt in cells from other species, namely, S. pombe, and the NIH 3T3 fibroblast cell line (Rauthan et al. 2013). Although full details of the mechanism are not yet described, it seems that the mevalonate pathway provides FP and GGPP, which are essential for prenylation of proteins, including small GTPases, which is required for the proper activity of these proteins via membrane association. Inhibition of HMG‐CoA reductase prevents the activation of UPRmt,

and this possibly occurs through inhibition of the function of a key GTPase that requires prenylation for activity.

8.3 AZT and Mitochondrial Myopathy NRTIs are one of six classes of antiretroviral drugs used to treat patients infected with human immunodeficiency virus (HIV). Seven NRTI drugs are currently approved by the FDA for the treatment of HIV in the United States. For treatment‐naive patients, current recommendations suggest a combination of two NRTIs plus another drug from a different class of antiretroviral agents. In many treatment regimens, NRTIs are prominent components in the highly active retroviral treatment (HAART) or antiretroviral treatment (ART) of HIV infection to delay or prevent disease progression. As discussed in the following text, zidovudine (AZT) has been most commonly associated with NRTI myopathy and still may be included in one of the current NRTI combinations that are part of lifelong treatment in HIV‐positive people. It remains the preferred drug for use in pregnant women and newborns and for prophylaxis following either occupational or nonoccupational exposure to the virus. Overall, since treatment regimens moved away from monotherapy with AZT and following a reduction in doses of AZT administered to patients, a decrease in the myopathic effects attributed to AZT has been observed. NRTI are deoxynucleoside analogues that counteract HIV via their high affinity for and hence inhibition of the viral reverse transcriptase enzyme. The inhibition of the reverse transcriptase DNA polymerase activity, which converts viral RNA into DNA, aims to prevent the HIV virus from replicating. Zidovudine (3‐azido‐3′‐deoxythymidine; known as “AZT” or “ZDV”) was the first NRTI to be marketed in 1987 for HIV treatment. AZT can also be used for prevention of HIV transmission from mother to fetus during pregnancy. There are six other current drugs in this class that are approved for treating HIV by the FDA, but AZT is by far the most commonly associated with myopathy. The evidence for its proposed myotoxic mechanism(s) of action is therefore discussed in some detail later on. Usually, DNA polymerase enzymes utilize thymine, adenine, cytosine, and guanine deoxynucleoside triphosphates (dNTP) to build a DNA polymer. Elongation requires reaction between a 3′ OH group on the deoxyribose moiety of the growing polymer and the 5′‐phosphate residue of the incoming dNTP. The majority of NRTIs—for example, AZT, dideoxyinosine (ddI), dideoxycytidine (ddC) (withdrawn from clinical use in

Skeletal Muscle Mitochondrial Toxicity

the United States), lamivudine (3TC), stavudine (d4T), abacavir, and emtricitabine—are dideoxynucleotide analogues and contain no 3′ hydroxyl group on the ribose sugar, and therefore their incorporation into DNA causes chain termination of the nascent polynucleotide. Importantly, the dideoxynucleotide analogues require conversion into their triphosphate forms (ddNTP) by cellular kinases in order to elicit an effect. As an off‐target toxicity effect, NRTIs inhibit DNA polymerase of mammalian origin with polymerases β and ϒ most sensitive in vitro (see review by Brinkman et  al. (1998)). DNA polymerase β is mostly involved in DNA repair, and there is little evidence that inhibition by NRTI has a significant effect on this process in cells. However, inhibition of polymerase ϒ by NRTI (Lewis & Dalakas 1995), which is the sole DNA polymerase involved in mtDNA synthesis and repair, is significant. The decreased mtDNA synthesis and the associated reduced expression of mtDNA‐encoded gene products are believed to lead to mitochondrial dysfunction and interference with ATP production by oxidative phosphorylation. Mitochondrial respiratory chain complexes I, III, IV, and V consist of protein components encoded by mtDNA, and so the expected pattern of mitochondrial protein deficiency mirrors that arising from inherited defects in mtDNA‐encoded genes. All organ systems are potentially affected, but those with high ATP demand such as skeletal muscle are most susceptible. Clinical manifestation of disease in different organs and the susceptibility of different tissues have been reviewed (Carr 2003). Originally the clinical expression of the disease was believed to be primarily determined by the level of mtDNA depletion in post‐mitotic tissues such as muscle showing evidence of greatest effect due to lack of mtDNA replication. Tissues with low turnover of mtDNA would also accumulate most mtDNA defects. However, this is the classical, and somewhat simplistic, view of NRTI‐mediated mitochondrial dysfunction leading to adverse events. Beyond the inhibition of polymerase ϒ by NRTI, several other theories propose alternate or complementary mechanisms for mitochondrial inhibition, in part to account for some of the unanswered questions and discrepancies related to observations on the effects of NRTI. For example, there is a lack of correlation between the extent of mtDNA depletion and mitochondrial toxicity. AZT is more toxic to mitochondria than 3TC, yet causes less inhibition of DNA polymerase ϒ (Apostolova et  al. 2011). Apostolova et  al. (2011) and Smith et al. (2013) have recently summarized and speculated on these alternate mechanisms for mitochondrial inhibition, many of which may apply in skeletal muscle. More research is needed, but electron transport chain and mitochondrial enzyme inhibition, inhibition of purine/pyrimidine nucleoside transport,

disturbance of deoxyribonucleotide pools (Selvaraj et al. 2014), NRTI phosphorylation, and oxidant generation are all hypothesized to play roles. One major issue is that both HIV itself and NRTI drugs appear to modulate mitochondrial function directly, making it difficult to assign the cause of mitochondrial toxicity in vivo. The majority of side effects of NRTIs are attributed to mitochondrial toxicity and are similar to the spectrum of effects causing mitochondrial diseases (Brinkman et al. 1998). NRTI mitochondrial toxicity results in a range of effects including peripheral neuropathy, lactic acidosis, cardiovascular risk, myopathy, hepatotoxicity, pancreatitis, dyslipidemia, and insulin resistance. Moreover, NRTI drugs have differing pathological effects. AZT can result in myopathy (Dalakas et al. 1990), whereas ddI, ddC, and 3TC often cause neuropathy; d4T may cause both myopathy and neuropathy (Dalakas 2001). Which tissue is affected by a particular NRTI is probably determined by the distribution of phosphorylation activities for the specific drug (Lewis & Dalakas 1995). Effectiveness of AZT therapy is limited by the toxic effects at high doses for prolonged duration, which include myopathy and cardiomyopathy. In a 1‐year follow‐up study of HIV patients taking relatively high doses of AZT (1–1.2 g/day) for more than 270 days, 17% of patients showed signs of myopathy (Peters et al. 1993). Elevated CK levels preceded the clinical signs of muscle problems. Myopathy was not observed in short‐term therapy, and all signs and symptoms resolved on drug withdrawal. Generally, symptoms of AZT myopathy include muscle pain, weakness, and fatigue and often muscle atrophy, and a raised serum CK is observed (Owczarek et  al. 2005). Alongside mtDNA depletion (Dalakas et al. 1990; Arnaudo et al. 1991; Masanes et al. 1998), these findings indicate mitochondrial disease induction by AZT, although the exact mechanism is still not certain. mtDNA depletion is hypothesized to result in reduced ATP synthesis due to problems with the synthesis and construction of mitochondrial electron transport complexes. Glycolytic metabolism may compensate to some extent, but this also leads to increased lactic acid production. Overall a dysfunction of muscle ensues due to lack of ATP synthesis. Histopathologically, ragged red fibers and abnormal mitochondrial morphology are often observed in skeletal muscle biopsies from patients receiving AZT (Owczarek et al. 2005). These fibers are often seen in some inherited mitochondrial diseases and result from an increase in subsarcolemmal proliferation of aberrant mitochondria. AZT is also associated with muscle fibers lacking cytochrome c oxidase due to complex IV deficiency and fat accumulation in cells (Dalakas et al. 1990).

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The exact mechanism(s) of mtDNA depletion via DNA polymerase ϒ inhibition is uncertain. The original hypothesis was that AZT is phosphorylated in tissues by thymidine kinase (TK) to form AZT triphosphate, which subsequently inhibits DNA polymerase ϒ (Arnaudo et al. 1991; Lewis et al. 1992, 1994). Long‐term inhibition would result in mtDNA depletion, which has been observed in skeletal muscle from patients and rats treated with AZT (Arnaudo et al. 1991; Lewis et al. 1992). In heart muscle, cytoplasmic thymidine kinase 1 (TK1) is virtually absent, and nucleosides such as thymidine and AZT are transported to the mitochondrial matrix for phosphorylation by TK2. McKee et  al. (2004) showed that thymidine was rapidly transported into rat heart mitochondria and phosphorylated to TTP in the matrix, presumably by TK2. AZT was metabolized as far as AZT monophosphate (AZT‐MP) only, resulting in sequestration within the matrix. The lack of AZT triphosphate synthesis suggests lack of inhibition of polymerase ϒ. Similarly, AZT triphosphate is not detected in the matrix of liver mitochondria treated with AZT (Lynx et  al. 2006); therefore, the concentration is insufficient to inhibit polymerase ϒ. However, AZT is a potent inhibitor of thymidine phosphorylation in heart mitochondria (McKee et al. 2004) presumably by inhibition of TK2 by AZT‐MP and could therefore disrupt the supply of TTP for mtDNA synthesis. A disruption in thymidine salvage by mutations in the thymidine phosphorylase gene has been observed in mitochondrial neurogastrointestinal encephalopathy (MNGIE) (Nishino et  al. 1999). The resultant phenotype shares many similar features with mitochondrial toxicity by AZT, albeit by different molecular mechanisms. In mice treated with AZT, dietary uridine supplementation overcomes all aspects of AZT‐induced myopathy including mtDNA depletion, likely acting via restoration of the pyrimidine metabolism (Lebrecht et  al. 2008). A related mechanism has been proposed for inhibition of mtDNA synthesis by AZT and ddI (Sun et al. 2014a, b) with downregulation in TK2 expression following ddI administration in U2OS cell (human osteosarcoma cell line). These authors suggest that intramitochondrial degradation of TK2 protein following oxidant damage due to AZT might be responsible, although this was not proven. Previously, it was reported that changes in mitochondrial protein expression mediated by AZT were correlated with decreases in mtDNA levels (Lewis et al. 1992). Exposure of rats to AZT caused decreased mRNA expression levels of mtDNA‐encoded genes in skeletal muscle fibers, yet mRNA expression of two nuclear‐ encoded genes was not affected (Lewis et al. 1992). TK2 is a nuclear gene, and changes to its transcriptional, translational, and mitochondrial import by AZT treatment have not been investigated, to our knowledge.

Although previous circumstantial data point to accelerated intramitochondrial TK2 protein degradation due to AZT being likely (Sun et  al. 2014a, b), these other effects on TK2 biology cannot be ruled out. Alternatively, the deleterious effects of AZT on mitochondrial activity may not be due to the inhibition of DNA polymerase ϒ (reviewed in Scruggs and Dirks Naylor 2008). For example, AZT inhibited respiration in rat skeletal muscle mitochondria, particularly at electron transport chain complexes I and II (Modica‐Napolitano 1993). In cultures of human muscle cells, AZT, ddI, and ddC all decreased proliferation, caused lipid droplet accumulation in cytoplasm, and increased lactic acid production (Benbrik et al. 1997). All three drugs impaired mitochondrial respiratory chain function, but the high potency of ddC, in particular, casts doubt upon the hypothesis that AZT acts via a simple direct mitochondrial toxic effect since a toxic myopathy is seen with this drug but not with ddC or ddI. Prior to changes being observed in mtDNA content, AZT has been shown to be able to affect ATP synthesis and inhibit rat myocyte contraction (Cazzalini et  al. 2001). Studies in cells also demonstrated a reduction in glutathione levels in response to AZT, implicating oxidative stress as a mechanism. In mice, AZT resulted in increases in 8‐oxo‐deoxyguanosine, a marker of oxidative damage, in mtDNA (de la Asuncion et al. 1998). One hypothesis is that disruption of the mitochondrial electron transport system results in increased oxidant production and oxidative stress (Yamaguchi et al. 2002) and that this precipitates subsequent mtDNA deletion. L‐Carnitine as a Target for NRTI: l‐carnitine is impor‑ tant as it facilitates long‐chain fatty acid transport into mitochondria, which is key for muscle ATP synthesis. AZT is also reported to reduce l‐carnitine levels in patient muscle biopsies (Dalakas et al. 1994) and in myoblasts (Georges et al. 2003), resulting in accumulation of cytoplasmic lipid droplets. In human muscle cells, these effects are mitigated by l‐carnitine supplementation (Semino‐Mora et al. 1994), suggesting that it is the AZT‐ induced l‐carnitine depletion rather than mtDNA deple‑ tion, which causes the defect in fatty acid transport into  mitochondria. At least in a mouse myoblast cell line, it appears that AZT acts to reduce the transport of l‐carnitine into cells via direct inhibition of the trans‑ porter for l‐carnitine (Georges et al. 2003). Apoptosis as a Mechanism for AZT Myopathy: Studies on induction of apoptosis by AZT in skeletal muscle are uncommon. Desai et  al. (2008) noted modest dose‐ dependent effects by AZT on expression of genes associated with apoptosis (and mtDNA maintenance or mitochondrial transport) in skeletal muscle of neonatal B6C3F1 mice. Animals were treated with AZT from postnatal day 1 for 8 days to model the postnatal NRTI

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antiretroviral prophylaxis regimen for babies born to HIV‐positive mothers; this treatment is administered in order to prevent mother‐to‐child transmission of the virus. Recently Adebiyi et al. (2016) suggested that AZT caused an increase in markers of skeletal muscle apoptosis in rats, that is, AZT increased Bax/BCl‐2 ratios.

8.4 Do Other Nucleoside Analogue Drugs Cause Myopathy? In a retrospective study of 69 patients with probable or possible HIV‐associated neuromuscular weakness syndrome, an association with NRTI exposure and raised serum lactic acid suggested a mechanism involving mitochondrial toxicity in muscle; however, causation was not proven (HIV Neuromuscular Syndrome Study Group 2004). Moreover, this was a retrospective analysis, and adequate control group(s), for example, an NRTI‐ naïve HIV patient group, was not included. d4T was the main NRTI ART (89% of patients), and serum lactate levels tended to be raised in the d4T group compared with the small number of patients not taking d4T. It was clear that muscle pathology was present in patients receiving NRTI apart from AZT. Therapy with d4T (as part of HAART) has also been implicated in hyperlactatemia, skeletal muscle mtDNA depletion, and decreased whole‐body oxidative capacity when compared with healthy controls (Haugaard et al. 2005). However, muscle mtDNA content was also decreased in antiretroviral‐naïve patients, suggesting HIV effects independent of treatment and that caution must be used when using mtDNA as a potential surrogate measure of myotoxicity (Haugaard et  al. 2005). Similarly, HIV infection is reported to result in lymphocyte mtDNA depletion independent of NRTI administration (Maagaard et al. 2008). Fialuridine was used as an antiviral nucleoside analogue for the treatment of chronic hepatitis B infection. Preclinical studies had indicated no adverse effects. Unfortunately, fialuridine resulted in liver failure and death in 5 out of 15 patients treated experimentally (McKenzie et al. 1995). Myopathy was observed in several patients, and biopsies showed ragged red fibers and pathology similar to, but less severe than, AZT myopathy. Fialuridine was shown to be toxic to human skeletal muscle myotubes in vitro. Effects included accumulation of lipid droplets and with early, major, and irreversible alterations in mitochondrial structure shown by electron microscopy (Semino‐Mora et al. 1997). Effects of fialuridine on mtDNA of human skeletal muscle cells  are pronounced and progressive with duration of exposure (Birkus et al. 2003).

Unfortunately, adverse events following therapy for hepatitis B did not end with the fialuridine tragedy. Long‐term treatment with the nucleoside analogue clevudine has been associated with myopathy and is well reviewed by Fleischer and Lok (2009). Myopathy occurred between 8 and 13 months of treatment in two clinical trials and was reversible following drug cessation (Kim et al. 2009; Seok et al. 2009). Severe myonecrosis, elevated CK levels, and raised serum lactate were variously observed. Mitochondrial changes included decreased mtDNA in skeletal muscle biopsies (Seok et al. 2009). These effects were not predicted by preclinical studies, and clevudine was not incorporated into mtDNA and did not inhibit/was not a DNA polymerase ϒ substrate (Chu et al. 1998). It was subsequently highlighted that clevudine was preferentially phosphorylated by TK2 in mitochondria (Wang & Eriksson 1996; Tehrani et al. 2008), drawing a parallel with the mechanisms proposed for AZT myopathy as discussed previously.

8.5 Other Drugs Possibly Associated with Myopathy Due to Mitochondrial Toxicity Leflunomide is a disease‐modifying antirheumatic drug that acts on dihydroorotate dehydrogenase, a key component of pyrimidine biosynthesis and a mitochondrial enzyme. There are several side effects of leflunomide treatment including at least three reports of patients suffering from myalgia, polymyositis, and rhabdomyolysis (Rivarola de Gutierrez & Abaca 2004; Ochi et al. 2009; Adamski et al. 2011). To our knowledge, no mechanism has been elucidated. Propofol is a general anesthetic and sedative for intensive care. In rare cases, propofol toxicity, which results in severe life‐threatening “propofol infusion syndrome” (PRIS), has been associated with myopathy, elevated serum CK levels, and even rhabdomyolysis (Stelow et al. 2000). Initial reports suggested reduced complex IV activity in the mitochondrial electron transport chain of skeletal muscle from children with PRIS (Cray et  al. 1998; Mehta et al. 1999). Subsequent reports suggested that propofol reduces oxygen utilization and inhibits mitochondrial electron transport chain in guinea pig hearts (Schenkman & Yan 2000). Impaired fatty acid oxidation in a child given propofol has been reported as a mechanism for PRIS (Wolf et al. 2001). The biochemical findings were consistent with both reduced entry of long‐chain acylcarnitine esters into mitochondria and inhibition of mitochondrial electron transport at complex II. A rise in malonylcarnitine was proposed as a mechanism for reduced transport of long‐chain fatty

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acids into the mitochondria via inhibition of carnitine palmitoyltransferase 1. Recent studies in rats suggest that propofol inhibits mitochondrial complex (II + III) activity in skeletal muscle, possibly at the level of CoQ10 (Vanlander et al. 2015). Multitargeted tyrosine kinase inhibitors are useful anticancer drugs but have been associated with cardiac and skeletal muscle side effects in man. For example, sunitinib has been reported to cause raised serum CK and severe rhabdomyolysis, resulting in renal failure in two patients with renal cell cancer (Ruggeri et al. 2010) but without evidence for mitochondrial liability. Myositis was also reported for sorafenib in patients being treated for hepatocellular carcinoma (Diaz‐Sanchez et al. 2011) but without elevated muscle enzymes. Subsequently, severe rhabdomyolysis was observed in a patient receiving sorafenib that occurred within 10 days and resolved on cessation of the drug (Tsuji et al. 2013). There is some evidence that sorafenib is able to directly inhibit mitochondrial function, at complex (II + III) and complex IV, in H9c2 cells, which are an in vitro model of both cardiac and skeletal myocytes (Will et al. 2008). These results are supported by recent observations in isolated mitochondria (Zhang et al. 2017).

8.6

Concluding Remarks

Despite 30 years of statin use and millions of prescriptions, we still do not fully understand the exact mitochondrial mechanism(s) resulting in skeletal muscle pathology in some individuals. Depletion of muscle CoQ10 observed in some studies does not appear to account for myopathy in man, and, seeking a mechanism, we are forced to address direct inhibition of mitochondrial function. Recent studies highlighting targeting complex III of the mitochondrial electron

transport chain by statin lactones (Schirris et al. 2015) are intriguing, but further confirmation is required. Studies in C. elegans have elegantly pointed toward effects on protein prenylation by statins as potential cell signaling mechanisms that require investigation in man. Off‐target effects of relative high doses of AZT imply inhibition of DNA polymerase ϒ in human skeletal muscle to account for observed myopathy, but the lack of AZT triphosphate synthesis in mitochondria argues against this. Instead, it is more likely that AZT‐MP inhibits TTP synthesis via TK inhibition in the mitochondrial matrix. Proposals that AZT leads to TK2 protein degradation are worthy of further investigation as are the observations that AZT directly inhibits other aspects of mitochondrial function. While the drive to find an exact mechanism for AZT‐induced mitochondrial myopathy appears to be no longer an imperative due to reduced usage and lower doses, it is sobering to note the adverse skeletal muscle events with other nucleoside analogues within the last decade. Mitochondrial toxicity remains a major consideration for drug development with evidence of myopathy for sorafenib, propofol, and leflunomide involving a mitochondrial mechanism. Further research is required on the possible mitochondrial effects leading to skeletal muscle pathology by these drugs. Moreover, since it appears that mitochondria are a key target for many adverse events of a wide array of chemical entities, we need to maintain and further develop in vitro assays to sensitively predict, at an early stage, potential mitochondrial liabilities (Will & Dykens 2014). Where possible these should reflect mechanisms of action and better mirror the clinical effects in humans. To this end application of skeletal muscle cells under conditions that sensitize them to mitochondrial toxicity is a  potential area for development (Will et  al. 2008; Dott et al. 2014; Dott et al. 2018).

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Skeletal Muscle Mitochondrial Toxicity

Taylor, B.A. & Thompson, P.D. 2015, “Muscle‐related side‐effects of statins: from mechanisms to evidence‐based solutions”, Current Opinion in Lipidology, vol. 26, no. 3, pp. 221–227. Tehrani, O.S., Douglas, K.A., Lawhorn‐Crews, J.M. & Shields, A.F. 2008, “Tracking cellular stress with labeled FMAU reflects changes in mitochondrial TK2”, European Journal of Nuclear Medicine and Molecular Imaging, vol. 35, no. 8, pp. 1480–1488. Thibault, A., Samid, D., Tompkins, A.C., Figg, W.D., Cooper, M.R., Hohl, R.J., Trepel, J., Liang, B., Patronas, N., Venzon, D.J., Reed, E. & Myers, C.E. 1996, “Phase I study of lovastatin, an inhibitor of the mevalonate pathway, in patients with cancer”, Clinical Cancer Research: An Official Journal of the American Association for Cancer Research, vol. 2, no. 3, pp. 483–491. Thompson, P.D., Panza, G., Zaleski, A. & Taylor, B. 2016, “Statin‐associated side effects”, Journal of the American College of Cardiology, vol. 67, no. 20, pp. 2395–2410. Tomaszewski, M., Stepien, K.M., Tomaszewska, J. & Czuczwar, S.J. 2011, “Statin‐induced myopathies”, Pharmacological Reports: PR, vol. 63, no. 4, pp. 859–866. Tonkonogi, M. & Sahlin, K. 1997, “Rate of oxidative phosphorylation in isolated mitochondria from human skeletal muscle: effect of training status”, Acta Physiologica Scandinavica, vol. 161, no. 3, pp. 345–353. Tsuji, K., Takemura, K., Minami, K., Teramoto, R., Nakashima, K., Yamada, S., Doyama, H., Oiwake, H. & Hasatani, K. 2013, “A case of rhabdomyolysis related to sorafenib treatment for advanced hepatocellular carcinoma”, Clinical Journal of Gastroenterology, vol. 6, no. 3, pp. 255–257. Vanlander, A.V., Okun, J.G., de Jaeger, A., Smet, J., De Latter, E., De Paepe, B., Dacremont, G., Wuyts, B., Vanheel, B., De Paepe, P., Jorens, P.G., Van Regenmortel, N. & Van Coster, R. 2015, “Possible pathogenic mechanism of propofol infusion syndrome involves coenzyme q”, Anesthesiology, vol. 122, no. 2, pp. 343–352. Vaughan, R.A., Garcia‐Smith, R., Bisoffi, M., Conn, C.A. & Trujillo, K.A. 2013, “Ubiquinol rescues simvastatin‐ suppression of mitochondrial content, function and metabolism: implications for statin‐induced rhabdomyolysis”, European Journal of Pharmacology, vol. 711, no. 1‐3, pp. 1–9. Velho, J.A., Okanobo, H., Degasperi, G.R., Matsumoto, M.Y., Alberici, L.C., Cosso, R.G., Oliveira, H.C. & Vercesi, A.E. 2006, “Statins induce calcium‐dependent mitochondrial permeability transition”, Toxicology, vol. 219, no. 1‐3, pp. 124–132. Waclawik, A.J., Lindal, S. & Engel, A.G. 1993, “Experimental lovastatin myopathy”, Journal of

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9 Manifestations of Drug Toxicity on Mitochondria in the Nervous System Jochen H. M. Prehn and Irene Llorente‐Folch Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, 123 St Stephen’s Green, Dublin 2, Ireland

CHAPTER MENU 9.1 9.2 9.3 9.4 9.5 9.6

Introduction: Mitochondria in the Nervous System, 133 Mitochondrial Mechanisms of Peripheral Neuropathy, 135 Mitochondria and Retinal Drug Toxicity, 140 Mitochondria and Ototoxicity, 143 Mitochondrial Mechanisms of Central Nervous System injury, 146 Conclusion, 149 References, 150

9.1 Introduction: Mitochondria in the Nervous System Although mitochondria are critical for the function of most tissues, they are particularly important for the maintenance and integrity of the nervous system. Neurons are responsible for disproportionate oxygen consumption at rest in humans. The brain uses approximately 20% of the total oxygen consumed at rest but represents only 2% of body mass (Mink et al., 1981). In addition, neurons are critically and almost exclusively dependent on mitochondrial oxidative phosphorylation (OXPHOS) as a major source of adenosine triphosphate (ATP) and have a limited capacity to upregulate energy supply through glycolysis when OXPHOS is compromised (Herrero‐Mendez et al., 2009). Moreover, it has been known for many years that cells match the rate of ATP production and utilization with little or no measurable change in metabolic intermediates. The maintenance of cellular metabolites during alterations in workload has been termed metabolic homeostasis and is probably most thoroughly studied in cardiac and skeletal muscle (Balaban, 2002, 2006; Glancy et al., 2013). However, neurons are also subject to changes in workload, and it is known that most of the energy in the brain is consumed by the

process of synaptic transmission (Attwell & Laughlin, 2001; Hall et  al., 2012; Harris et  al., 2012). Increased synaptic transmission is inevitably associated with a disturbance of ionic gradients across the plasma membrane due to increased Na+ and Ca2+ influx, which subsequently require increased ATP consumption as the consequence of increased Na+/K+ ATPase pump activity to restore basal ion homeostasis (Erecinska & Silver, 1994). In high energy‐demanding tissues such as the brain or the skeletal and cardiac muscle, the major sustainable source of energy is ATP generated by OXPHOS. The potential for injury as a consequence of inhibition of mitochondrial function in neurons is illustrated by a number of different examples of disease states that can be modeled using electron transport chain inhibitors, including Parkinson’s disease (PD) and Huntington’s disease (HD) (Beal et  al., 1993; Betarbet et  al., 2000). The  links between impaired mitochondrial function and  central nervous system (CNS) diseases are further emphasized by the prominently neurological phenotype of syndromes associated with mtDNA mutations such as  Leber’s hereditary optic neuropathy (LHON) and mitochondrial encephalomyopathy, lactic acidosis, and  stroke‐like episodes (MELAS) (Wallace, 1992). Another important concept that can be observed after

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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administration of mitochondrial respiratory chain inhibitors such as rotenone is the phenomenon of “selective” vulnerability. For example, administration of rotenone produces a parkinsonism‐like disorder (Betarbet et  al., 2000). While rotenone inhibits complex I in the entire brain, the development of the disease is mainly associated with the loss of dopaminergic neurons (reviewed in Surmeier & Schumacker, 2013). The concept of selective vulnerability remains poorly understood. It is important to note in this context however that mitochondria differ across tissues, cell types, and even subcellular compartments within neurons (Dubinsky, 2009; Kuznetsov et  al., 2009). Indeed, inherent differences in mitochondrial function, or in the susceptibility to mitochondrial dysfunction, are proposed to mediate the differential neuronal vulnerability in several neurodegenerative disorders, including HD  (Brustovetsky et  al., 2003; Dubinsky, 2009; Oliveira & Goncalves, 2009; Pickrell et al., 2011). Mitochondrial dysfunction and impairments in ATP generation also represent a primary cause of epilepsy. Moreover, seizures by themselves create a substantial challenge to energy metabolism (Kovacs et  al., 2002), which triggers mitochondrial damage and secondary dysfunction (reviewed in Zsurka & Kunz, 2015). Although mitochondrial dysfunction is now considered an important factor in patients with epilepsy, until recently it was almost unrecognized (Arnold, 2012; Lee, Kim, Choung, Kim, & Yu, 2008; Zsurka & Kunz, 2010). Another study concluded that energy failure associated with mitochondrial dysfunction contributes to the severity of the epileptic disorders (El Sabbagh et al., 2010). Furthermore, certain antiepileptic therapeutics such as enzyme‐ inducing antiepileptic drugs (AEDs), for example, carbamazepine, phenytoin, and phenobarbital, may have protective effects on mitochondria, and it has been reported (Miles et al., 2012) that those actions are associated with promoting mitochondrial proliferation and enhanced ETC complex IV (COX) activity. It is also important to consider that some harmful consequences of AEDs such as valproic acid or the classical aromatic AEDs have been related to drug‐induced mitochondrial toxicities (see discussion later on). Calcium ions play a crucial role in the modulation of cellular respiration (reviewed in Llorente‐Folch et  al., 2015; Rueda et al., 2014). In brief, Ca2+ is a versatile and ubiquitous intracellular messenger, acting as a mediator of almost all energy‐demanding processes in mammalian cells. The capacity of mitochondria to take up large quantities of Ca2+ in a membrane potential‐dependent manner has been known for decades (Deluca & Engstrom, 1961; Harris, 1977; Nicholls, 1978). Mitochondrial Ca2+ accumulation serves not only as a Ca2+ buffering system in the cell but also as a pathway to modulate energy

metabolism. Ca2+‐dependent regulation of OXPHOS involves two principal mechanisms—(i) Ca2+ entry into mitochondria through the Ca2+ uniporter (mitochondrial calcium uniporter (MCU)) and (ii) Ca2+‐dependent activation of mitochondrial metabolite transporters (Ca2+‐ regulated mitochondrial carriers)—where Ca2+ acts on the external surface of the inner mitochondrial membrane. Thus, even though cytosolic and mitochondrial Ca2+ signals are usually tightly coupled, they can have distinct effects on mitochondrial metabolism, ensuring differential regulation under physiological and pathophysiological conditions. The physiological importance of mitochondrial Ca2+ handling has been highlighted by research on the first human disease associated with dysfunctional mitochondrial Ca2+ uptake, individuals harboring loss‐of‐function MICU1 mutations (Logan et  al., 2014). MICU1 physically interacts with MCU and sets the threshold for mitochondrial Ca2+ uptake (Csordas et al., 2013; de la Fuente et al., 2014; Mallilankaraman et al., 2012). Patients harboring these mutations display a muscular and brain disorder that develops progressively, leading to learning difficulties, muscle weakness, and locomotor dysfunction, among other symptoms (Bhosale et al., 2015; Logan et  al., 2014). Moreover, the first case of Aralar/AGC1 deficiency has been recently described (Wibom et  al., 2009). Aralar/AGC1 is the mitochondrial transporter of aspartate–glutamate present in the brain and a component of the malate–aspartate NADH shuttle (MAS) (del  Arco et  al., 2016; del Arco & Satrustegui, 1998; Satrustegui et al., 2007). It plays a crucial role in extramitochondrial Ca2+‐mediated activation of neuronal respiration in basal state and upon stimulation (Llorente‐Folch et  al., 2016; Llorente‐Folch et  al., 2013; Rueda et  al., 2016). The patient presented with global hypomyelination, hypotonia, delayed psychomotor development, seizures, and hyperreflexia (Wibom et al., 2009). Therefore, any drug that could potentially interfere not only with mitochondrial‐mediated Ca2+ homeostasis but also with Ca2+‐mediated signaling in mitochondria could be a hazard for physiological brain function. Mitochondrial functions also comprise the production of reactive oxygen species (ROS). The highest ROS production capacity in brain mitochondria has been proven for complex I and complex III of the respiratory chain and for the enzymes dihydrolipoamide dehydrogenase and monoamine oxidases (MAOs) (references in Adam‐ Vizi & Chinopoulos, 2006). ROS function as second messengers in signal transduction but are also mediators of oxidative damage and inflammation. Oxidative stress is believed to be a central feature in neurodegeneration, a finding that is supported by clinical evidences reporting lipid and protein peroxidation in postmortem brains of patients diagnosed with neurodegenerative CNS

Manifestations of Drug Toxicity on Mitochondria in the Nervous System

disorders (Lin & Beal, 2006; Musiek et al., 2006; Sultana et  al., 2006). As ROS often originate in mitochondria, mitochondria are particularly vulnerable to oxidative damage. This damage may play a critical role in controlling neuronal excitability and subsequent seizure susceptibility associated with acquired epilepsy (Waldbaum & Patel, 2010). Neurons are particularly vulnerable to mitochondrial dysfunction not only because of their aforementioned energetic dependence on OXPHOS (Bolanos et  al., 2010; Oliveira, 2011) but also because of their polarized  morphology. Mitochondria need to be efficiently distributed to distant neurites, axons, and synapses to provide energy support for local disruptions in ion homeostasis and Ca2+ handling (Bolanos et  al., 2010; Leitao‐Rocha et  al., 2015; Oliveira, 2011; Schwarz, 2013). The unique morphology and post‐mitotic nature of neurons demands effective mitochondrial quality control mechanisms (Amadoro et al., 2014). Mitochondrial transport, fusion and fission, and the removal of defective mitochondria are complex and ATP‐dependent processes that also rely on the integrity of the cytoskeleton (reviewed in Matic et  al., 2015; Ni et  al., 2015; Oliveira et  al., 2016). Trafficking also depends on other signaling molecules including growth factors and neurotoxins that by themselves do not impair ATP synthesis (Chada & Hollenbeck, 2004; Malaiyandi et al., 2005; Reynolds et al., 2004). The relevance of these processes is highlighted by the fact that defects in mitochondrial trafficking and mitophagy have been described in neurodegenerative diseases (reviewed in Matic et al., 2015; Oliveira et al., 2016). It is therefore reasonable to assume that drugs targeting these processes will also disrupt neuronal function. Even if we increase our understanding of the mechanisms of neurotoxic drug, it remains difficult to predict the manifestations of that toxicity in the nervous system. Typically, adverse effects of drugs that are toxic to nervous system mitochondria are reported as alterations in the function of a sensory or motor modality. Some of the best established examples of mitochondrial toxicity are manifested as peripheral neuropathy as discussed in the following subchapter. However, other manifestations include retinal toxicity, ototoxicity, and CNS toxicity. As discussed earlier, it is not always clear why selectivity exists for a particular subset of neurons or whether differential toxicity results from differential exposure, distinct properties of mitochondria within different types of neurons, or increased vulnerability of neurons arising from a specific feature of the interaction between mitochondria and their cellular environment. For this reason, the strategy taken in this chapter will be to review toxicities based on phenotype and target tissues and then to assess the evidence for a mitochondrial toxicity

mechanism. Given the considerable range of CNS‐active compounds for which mitochondrial activity has been documented (Chan et al., 2005; Hargreaves et al., 2016), the potential for nervous system injury induced by drugs and toxic agents is substantial. The chapter will therefore conclude with a discussion of potential CNS injury mechanisms.

9.2 Mitochondrial Mechanisms of Peripheral Neuropathy Peripheral neuropathy is a well‐known condition most commonly caused by diabetes, alcohol abuse, paraneoplastic syndromes, or toxins. In this chapter we will focus on “drug‐induced peripheral neuropathy,” a term defined as damage to nerves of the peripheral nervous system caused by a chemical substance used in the treatment, cure, prevention, or diagnosis of a disease. Drug‐induced peripheral neuropathy is a condition that requires the physician’s knowledge and awareness to be recognized and subsequently treated. It frequently presents to the physician as a sensory polyneuropathy with paresthesia that might be accompanied by pain with a distal, symmetric sock‐ and glove‐shaped neuropathy caused by affection of the myelin sheath of the  peripheral nerve (demyelination) with or without affection of the nerve axon itself (axonal degeneration). Motor symptoms and signs are generally minor. Although there are different clinical symptoms and signs, the drugs discussed later on may induce neurological impairments severe and persistent enough to restrict the patient’s daily activities (Vilholm et  al., 2014). The key distinguishing features of neuropathy associated with drug treatment rather than the disease itself are a more abrupt onset of neuropathy. Drug‐ induced peripheral neuropathy can begin weeks to months after initiation of treatment with a particular drug and reach a peak at, or after, the end of treatment. In most cases, the onset is associated with the initiation of therapy (Moyle & Sadler, 1998), and generally the pain and paresthesia completely resolve after cessation of treatment. However, in some cases, drug‐induced peripheral neuropathy is only partially reversible and can be permanent (Windebank & Grisold, 2008). Risk factors related to the specific treatment are reviewed in Vilholm et al. (2014, table 1). In the peripheral nervous system,  it  was demonstrated that more than 90% of mitochondria are localized in the axons; since axonal mitochondria are fundamental for energy generation in axons, a defect in mitochondrial energy metabolism can cause axonal  transport degeneration and nerve failure (Park et al., 2008).

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9.2.1

Reverse Transcriptase Inhibitors

Nucleoside and non‐nucleoside reverse transcriptase inhibitors (NNRTIs) are effective antiviral agents that are used in the treatment of herpes virus, hepatitis B virus, and, importantly, human immunodeficiency virus (HIV). While significant health advances have been achieved with the use of these drugs, the necessity for lifelong treatment to control HIV infection is limited by NRTI‐ associated toxicities that arise from virus‐versus‐host polymerase selectivity wherein NRTIs also serve as substrates for host polymerases (Brown et al., 2011; Johnson et al., 2001). Many mechanisms have been proposed for the origins of nucleoside analogue toxicity, but the most obvious sites of action are the enzymes responsible for host cell DNA replication and repair: DNA polymerases α, δ, and ε, which are responsible for chromosomal DNA replication; DNA polymerase β, which is involved in DNA repair; and DNA polymerase γ (pol γ), which carries out mitochondrial DNA (mtDNA) synthesis (Frick et  al., 1988; Hall et  al., 1994; Kewn et  al., 1997). Interestingly, the toxicity manifested in many nonproliferating tissues is thought to result more specifically from the effects of inhibition of DNA pol γ by nucleoside analogues (Barile et  al., 1998; Colacino, 1996; Honkoop et al., 1997; Horn et al., 1997; Perry et al., 1994). mtDNA is necessary for many OXPHOS complex I proteins. mtDNA depletion causes a deficiency in complex I and an overutilization of complex II, resulting in elevated superoxide levels (Lewis et al., 2003). Depletion in mtDNA and increased mtDNA mutations may reduce synthesis of mtDNA‐encoded protein subunits required for OXPHOS. The potential for NNRTIs to cause neuropathy was first encountered with vidarabine in the treatment of hepatitis B and has subsequently been associated with  the use of zalcitabine, didanosine, and stavudine (reviewed by Kakuda, 2000; Moyle & Sadler, 1998). These drugs can induce mtDNA depletion, leading to mitochondrial respiratory chain and OXPHOS deficits. NRTIs exert rapid toxicity by directly inhibiting mitochondrial bioenergetics function (Yamaguchi et al., 2002). The resulting reduction in ATP and increased ROS production have the potential for further mtDNA damage (Lewis et  al., 2001, 2006). The involvement of Ca2+ has been also described since the mitochondrial dysfunction induced by zalcitabine alters Ca2+ homeostasis in cultured DRG neurons (Werth et al., 1994) and in a model of zalcitabine‐associated painful peripheral neuropathy (Joseph et  al., 2004). In addition, NRTIs cause direct mitochondrial toxicity through inhibition of the mitochondrial transmembrane potential in neurons but not in Schwann cells (Keswani et  al., 2003). In vivo, however, Anderson and colleagues (1994) showed that zalcitabine

administration to rabbits produced a neuropathy that was associated with dysfunctional mitochondria in Schwann cells but not neurons. This might suggest that disruption of neuronal support cells could be also critical to the neuropathy produced by NNRTIs. Prolonged exposure of the cell to nucleoside analogues can promote mitochondrial ultrastructural abnormalities in peripheral nerves and  subcutaneous tissue (Cherry et  al., 2002; Dalakas et al., 2001; Lewis & Dalakas, 1995). The fact that toxicity of different drugs is cell, tissue, and organ specific (Benbrik et  al., 1997) indicates that the differences in subcellular bioavailability and pharmacokinetic profile involving the activation and deactivation of these drugs may contribute to their specific clinical toxicity. Moreover, the situation in patients can be complicated by the presence of other factors that predispose to the development of neuropathy, including alcohol intake, diabetes, dietary deficiencies, and other pharmacological agents (Moyle & Sadler, 1998). The presence of these other risk factors may effectively amplify the burdens imposed by NNRTIs, although it is not known whether they share a common mechanism of action. 9.2.2 Chemotherapy‐Induced Peripheral Neuropathies (CIPN) Millions of patients are treated with chemotherapeutic agents for the treatment of solid and hematological cancers in the neoadjuvant, adjuvant, or palliative setting. Among these chemotherapeutic drugs, DNA‐alkylating agents (platinum derivatives such as cisplatin and oxaliplatin), antitubulin compounds (taxanes such as paclitaxel and vinca alkaloids such as vincristine), and proteasome inhibitors (bortezomib) are frequently used. All these compounds are different in nature and chemical structures and also in their mechanism and site of action, but they have a common and relevant side effect that is the onset of a peripheral neurotoxicity that is frequently associated with the development of neuropathic pain (recently reviewed by Canta et al., 2015; Cavaletti & Marmiroli, 2015; Grisold et al., 2012; Travis et al., 2014; Windebank & Grisold, 2008). The observation of the similar clinical presentations of peripheral neuropathies associated with chemotherapeutic agents of diverse chemical classes gave rise to the mitotoxicity hypothesis, which posits that the fundamental cause of this form of chronic peripheral neuropathy is a toxic effect on mitochondria in primary afferent somatosensory neurons (Flatters & Bennett, 2006; Xiao & Bennett, 2012; Zheng et al., 2011, 2012), aimed at resolving the striking paradox that similar neurological symptoms are observed despite diverse anticancer mechanisms of action. In fact, the results of mitochondrial toxicity

Manifestations of Drug Toxicity on Mitochondria in the Nervous System

are more evident in regions with high metabolic request, such as primary afferent sensory neurons, where an elevated mitochondrial content is present (Heppelmann et al., 2001). Cells of the peripheral nervous system are vulnerable because of several unique characteristics, namely, (i)  primary sensory and autonomic neurons are contained in ganglia that lie outside the blood–brain barrier and are supplied by capillaries with fenestrated walls that allow free passage of molecules between the circulation and the extracellular fluid in the ganglia; (ii) long peripheral nerve axons are susceptible to any agents that interfere with the energy metabolism or the structural basis of axonal transport; (iii) drugs that act by disrupting microtubules of the mitotic spindle also disrupt microtubule‐based axonal transport; (iv) agents targeting the increased mitochondrial activity of cancer cells may impair axonal transport; and (v) neurons have apoptotic cell death pathways that are particularly sensitive to DNA damage induced by many chemotherapeutic agents. Specific mechanisms of susceptibility will be discussed with individual classes of agents. 9.2.2.1 Microtubule‐Modifying Agents and Mitochondria: Paclitaxel and Vincristine

Tubulin is a valuable target for anticancer chemotherapy as disruption of the mitotic spindle prevents cell replication. However, microtubules are critical for proper nerve function. They serve as tracks along which proteins, RNA, mitochondria, and other organelles that are synthesized in the cell bodies are transported by motor proteins to the nerve terminals, where synaptic vesicles carry out nerve actions requiring high ATP levels. Several agents with different antitubulin effects are neurotoxic on the peripheral nervous system, but newer compounds with less neurotoxic properties are under development (Klute et al., 2014). There are two major subtypes of microtubule‐targeted drugs, the taxanes and epothilones, that bind initially along microtubule surfaces or sites before becoming internalized into microtubules (Grisold et al., 2012; Ng et  al., 2015; Park et  al., 2013). These are referred to as microtubule stabilizers because, by binding along the microtubule lattice, they stabilize microtubule dynamic instability and inhibit microtubule depolymerization. On the other hand, vinca alkaloids and halichondrins bind only to microtubule ends at their  lowest effective concentrations (Bennett et al., 2014; Ferrier et al., 2013; Park et  al., 2013) and are referred to as microtubule destabilizers because, at high concentrations, they block the addition of new tubulin subunits to  microtubule ends, thus leading to microtubule depolymerization. Despite sharing the ability to suppress microtubule dynamic instability, it has been found that  these two

classes of drugs exert different effects on  microtubule‐ supported transport (reviewed in Smith et al., 2016). 9.2.2.1.1

Paclitaxel

Paclitaxel, belonging to the taxane group, is a microtubule‐binding compound that specifically and reversibly interacts with microtubules to enhance microtubule polymerization and decrease microtubule depolymerization, promoting a polymeric structure (Derry et  al., 1995; Dumontet & Jordan, 2010; Jordan & Wilson, 2004; Kumar, 1981). The result is the arrest of cellular mitosis at the metaphase–anaphase transition (G2/M phase), inducing cancer cells death by apoptosis (Jordan et  al., 1996; Jordan & Wilson, 2004). Paclitaxel is active against proliferating cells or cells having a reduced apoptosis threshold such as cancer cells. However neurons are susceptible to paclitaxel treatment: both in vitro and in vivo studies demonstrated that chronic paclitaxel treatment induces axonal degeneration followed by secondary demyelination and nerve fiber loss in the presence of a severe peripheral neuropathy (Sahenk et al., 1994). It has been proposed that the severity and incidence of CIPN depend on the cumulative dose of paclitaxel (Postma et al., 1995). The use of an albumin‐bound paclitaxel formulation (abraxane) seems to be less neurotoxic (Conlin et al., 2010). Although the exact mechanism of action is still unclear, it has been proposed that paclitaxel promotes mitochondrial damage and a chronic sensory axonal energy defect, in agreement with the mitotoxicity hypothesis. Several in  vitro studies have reported paclitaxel‐induced Ca2+ dysregulation, mitochondrial permeability transition pore (mPTP) opening, and alterations in the activity of Ca2+‐dependent mitochondrial enzymes such as dehydrogenases involved in the TCA cycle, probably affecting ATP production (Canta et  al., 2015, reference herein). Moreover, it has been reported that changes in mitochondrial structure relate to a drug‐induced disturbance of Ca2+ homeostasis (Jaggi & Singh, 2012). This finding was also confirmed by in vivo analyses where it has been observed that numerous swollen and vacuolated mitochondria accumulate in the axons of peripheral nerves of treated rats, supporting the concept of functional damage to peripheral nerve mitochondria (Flatters & Bennett, 2006). Ex vivo studies demonstrated cyclosporine A‐sensitive cytochrome c release and apoptotic pathway activation (Andre et al., 2000; Carre et al., 2002) in mitochondria isolated from human neuroblastoma cells treated with paclitaxel. 9.2.2.1.2

Vincristine

Vincristine is the most severely neurotoxic compound among vinca alkaloids, predominantly used for the treatment of hematologic and lymphatic malignancies. They

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are also used as adjunctive treatments in combination with other drugs for rhabdomyosarcomas, neuroblastomas, and breast ovarian, testicular, lung, and colorectal cancer. Patients in treatment develop disturbances in both motor and sensory functions (Postma et al., 1993) with early numbness and tingling in hands and feet as well as ankle jerks (Balayssac et  al., 2011). Moreover, neuropathic and muscle pain is frequently present, as well as the loss of temperature sensation. The severity of symptoms is related to the duration and the therapeutic doses received, and unfortunately sometimes, after discontinuation, the symptoms worsen instead of improving (Verstappen et al., 2005). Apart from alteration in mitochondrial ultrastructure (Flatters & Bennett, 2006), it has been shown that vincristine‐caused peripheral neuropathy is related to a dysregulation of mitochondrial‐mediated Ca2+ buffering (Tari et  al., 1986), modifying spatiotemporal Ca2+ concentration, Ca2+ signaling (Boitier et al., 1999), and Ca2+‐dependent neurotransmitter release (Montero et  al., 2000) as well as OXPHOS in mitochondria. Moreover, inhibitors of the electron transport chain have been reported to attenuate vincristine‐related neuropathic pain in rats (Joseph & Levine, 2006). Disruption of microtubules in long axons of sensory and motor nerves ought to impact on mitochondrial trafficking and neuronal function. The studies reported here document a number of different effects on mitochondria altering their structure and function. However, neither altered morphology nor differences in Ca2+ handling are obvious results of a selective effect on inhibition of mitochondrial trafficking. Whether altered trafficking contributes to the neuropathy associated with microtubule disrupting drugs requires further analysis. 9.2.2.2 Platinum Compounds and Mitochondria: Oxaliplatin

Platinum compounds belong to a family of platinum (Pt)‐based anticancer drugs that includes several generations of compounds generated to reduce toxicity and enhance their anticancer activity at the same time. Three members of the drug family are currently used: cisplatin, carboplatin (mainly in lung, breast, and ovarian cancer), and oxaliplatin (used for the treatment of colon cancer and other gastrointestinal malignancies). These compounds are alkylating agents that bind the DNA double strand by crosslinks, creating Pt‐DNA adducts. If the amount of DNA damage exceeds the ability to affect repair, the cell undergoes apoptotic cell death. Since 1978, when cisplatin was first approved in the United States to treat cancer, CIPN emerged as a major side effect (Avan et al., 2015). Distal, symmetrical sensory impairment and ataxia are the typical clinical features

observed in platinum drug‐treated patients, and they are both intensity and cumulative dose related. A major issue in the use of platinum drugs is represented by CIPN worsening even after treatment withdrawal (the “coasting” effect) (Cavaletti et  al., 2011), reviewed in Canta et al. (2015) and Grisold et al. (2012). Understanding the oxaliplatin effects on mitochondrial function requires further investigation, but the principal known events are excellently summarized in previous reviews (Canta et al., 2015). In brief, it has been demonstrated that oxaliplatin activates the intrinsic apoptotic pathway in colon carcinoma cells (Arango et al., 2004) and requires the proapoptotic BCL‐2 family proteins Bax and Bak during this process (Gourdier et al., 2004). Moreover, it has been shown that oxaliplatin induced a deficit in respiration rate in both complexes I and II of mitochondrial electron transport chain followed by a decrease of ATP production in drug‐treated rats (Zheng et al., 2011). These respiratory deficits could be aggravated using respiratory chain inhibitors (Xiao et  al., 2012). Furthermore, increases in the mitochondrial ROS levels in neurons exposed to high concentrations of oxaliplatin have been reported (Kelley et  al., 2014), and substantial mitochondrial morphological changes (Xiao & Bennett, 2012) could also play an important role in the pathogenesis of oxaliplatin‐induced peripheral neuropathy. 9.2.2.3 Protease Inhibitor Bortezomib and Mitochondria

The ubiquitin–proteasome system is the major intracellular protein degradation pathway in eukaryotic cells, playing an important role in transcriptional regulation of key transcription factor such as nuclear factor‐κB (NF‐κB). The 26S proteasome, an ATP‐dependent protease, is fundamental for the ubiquitin–proteasome pathway (Lenz, 2003). Bortezomib, a boronic acid dipeptide, acts by inhibiting the proteasome–ubiquitin pathway (Adams, 2004) by specifically and reversibly binding to the 26S subunit of the proteasome (Curran & McKeage, 2009), leading to cell cycle inhibition and apoptosis (Shahshahan et  al., 2011). One of the proposed explanations for this mechanism of action is the decreased activation of NF‐κB that leads to cell death (Traenckner et al., 1994) and increased transcription and stabilization of the proapoptotic Bcl‐2 protein PUMA (Concannon et  al., 2007). In addition, bortezomib has been shown to affect polymerization of α‐tubulin and result in microtubule stabilization, similar to those effects seen with taxanes (Meregalli et al., 2015; Poruchynsky et  al., 2008; Staff et  al., 2013), altering axonal transport in rat DRG neurons (LaPointe et  al., 2013; Meregalli et al., 2014; Staff et al., 2013). Bortezomib monotherapy was approved by the US Food and Drug

Manifestations of Drug Toxicity on Mitochondria in the Nervous System

Administration in 2003 and a year later by the European Medicines Agency for the treatment of refractory multiple myeloma and mantle cell patients (Adams & Kauffman, 2004; Altun et al., 2005). In addition to refractory multiple myeloma, the use of bortezomib has rationale for the treatment of non‐hematologic malignancies (Roussel et al., 2010). Painful peripheral neuropathy is a significant dose‐limiting toxicity of bortezomib (Cavaletti & Nobile‐Orazio, 2007; Meregalli et al., 2012) with severe symptoms. Paresthesia, burning sensations, dysesthesias, numbness, sensory loss, reduced proprioception, and vibratory sensation (Argyriou et al., 2008) are some of the most common symptoms referred by patients, which typically occur within the first courses of bortezomib treatment, reaching a plateau typically after several cycles of treatments, and thereafter do not appear to increase (Richardson et al., 2006; Windebank & Grisold, 2008). Concerning the mechanism of bortezomib‐ induced peripheral neuropathy, a multifactorial cause seems likely, and various bortezomib toxicity mechanisms have been presented till now (extensively reviewed in Meregalli et  al., 2015), but the results are not completely conclusive, so further investigations will be essential. Interestingly, it was demonstrated that bortezomib induces a dysregulation of Ca2+ homeostasis that ultimately leads to apoptotic cell death. Bortezomib alters the levels of many apoptosis‐related proteins, and a role for caspase‐dependent, PUMA‐dependent, and PUMA‐ independent pathways in cell death execution has been proposed (Landowski et  al., 2005; Tuffy et  al., 2010). Moreover, it has been published that bortezomib‐treated rats exhibited defects in mitochondrial function, measured as a significant deficit in ATP production rate following stimulation of the electron transport system (Zheng et  al., 2012), being prevented by a prophylactic treatment with acetyl‐l‐carnitine, which also inhibited the neuropathic pain observed in rats (Zheng et al., 2012). Finally, it has been described that bortezomib induces sensory‐dominant axonal depolarization likely due to an impairment of the Na+/K+‐ATPase‐dependent pump and consequently Na+ axonal accumulation (Han et al., 2008; Kiernan & Bostock, 2000). Bortezomib‐induced mitochondrial impairment would compromise mitochondrial ATP production, which would lead to continuous influx of Na+ ions due to an overload of the Na+/K+ ‐ATPase‐ dependent pump, resulting in mitochondrial energy failure (Nasu et al., 2014). 9.2.3

Statins

HMG‐CoA reductase inhibitors (statins) are perceived to have a favorable safety profile (Bernini et  al., 2001; Davidson, 2001; Smith, 2000) and have well‐documented

benefits for the treatment of cardiovascular diseases. The beneficial effects of statins have been objectively shown to reduce risks for both total mortality and total morbidity (indexed by serious adverse events), specifically in clinical trial equivalent middle‐aged men who are at high cardiovascular risk (Criqui & Golomb, 2004; Long‐Term Intervention with Pravastatin in Ischaemic Disease, LIPID Study Group, 1998; Pedersen et al., 2004). Statins inhibit the enzyme HMG‐CoA reductase at a stage early in the mevalonate pathway (Buhaescu & Izzedine, 2007). This pathway generates a range of other products in addition to cholesterol, such as coenzyme Q10 (CoQ10), heme A, and isoprenylated proteins (Buhaescu & Izzedine, 2007), which have pivotal roles in cell biology and human physiology. Additionally, cholesterol itself is also an intermediate in the synthesis of sex steroids, corticosteroids, bile acids, and vitamin D, several of which have been shown to be affected with statin administration (Hyyppa et  al., 2003; Mol et  al., 1989). The biochemical influences of statins include effects on nitric oxide (NO) and inflammatory markers (Cimino et  al., 2007) or on polyunsaturated fatty acids (PUFA) (Harris et al., 2004), among many others. Despite their efficacy and that statins are generally well tolerated, many patients are obliged to discontinue statin  therapies due to adverse events (reviewed in Gluba‐Brzozka et  al., 2016). Approximately 0.5% of patients present with myopathic side effects, the most commonly reported adverse effects associated with statin therapy (reviewed in Golomb & Evans, 2008). The induction of skeletal muscle fiber apoptosis, mitochondrial dysfunction, and terpenoid depletion may mediate statin‐associated myopathy (Dirks & Jones, 2006; Jimenez‐Santos et al., 2014; Johnson et al., 2004). As statin therapy is extended to a larger population and an earlier onset on the primary prevention of high‐ risk individuals is advised, the milder nonspecific secondary effects of statins gain relevance and must be addressed. Second‐generation statins were developed shortly after their initial development in the 1970s. They include simvastatin, atorvastatin, cerivastatin, rosuvastatin, and pitavastatin (Tobert, 2003). Today, all the approved statins had already lost patent protection in 2016. This has prompted the pharmaceutical industries to seek for new chemical entities or statin derivatives capable of offering new ways to inhibit HMG‐R (Pfefferkorn, 2011). Brain tissue shares with muscle tissue a high mitochondrial vulnerability as both are post‐mitotic tissues with high metabolic demand (De Flora et  al., 1996; Kopsidas et al., 2000; Linnane et al., 2002; Ozawa, 1995; Sastre et al., 2003). Separate from the effects on skeletal muscle, there is clearly evidence of neuropathy induced by statins (Backes & Howard, 2003; De Vivo & DiMauro,

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1990; Peltier & Russell, 2006). Furthermore, mitochondrial defects predispose to problems on statins. Additionally, statins predispose to mitochondrial defects in all users and, to a greater degree, in vulnerable individuals (Golomb & Evans, 2008). The pathogenesis of the adverse myopathic side effects associated with statin therapy is yet to be fully elucidated; however interesting links with mitochondrial function have been documented. Lactic acidosis (Keaney et al., 2014) and elevated lactate/pyruvate ratios (Goli et al., 2002) have been reported in patients following statin therapy, indicating mitochondrial respiratory chain impairment. Statins reduce serum CoQ10 levels (De Pinieux et al., 1996; Mortensen et al., 1997; Rundek et  al., 2004). Some studies have also shown deficit in CoQ10 status directly assessing skeletal muscle following statin treatment (Laaksonen et  al., 1996; Lamperti et al., 2005; Larsen et al., 2013; Paiva et al., 2005). Statin‐ induced depletion of CoQ10 may be associated with enhanced production of free radicals and subsequent damage of mtDNA (Deichmann et  al., 2010) and reduced mitochondrial OXPHOS capacity, resulting in  mitochondrial dysfunction (Larsen et  al., 2013) in skeletal muscle. Importantly, changes in tissue mitochondrial and respiratory function clearly occur also in the brain (Barbiroli et  al., 1997; 1999). Interestingly, Duberley et al. (2013) reported that a 24% decrease in neuroblastoma cell CoQ10 status was sufficient to perturb OXPHOS as indicated by the decrease in cellular ATP status commensurate with a loss of mitochondrial membrane potential. Moreover, it has been shown that CoQ10 supplementation is beneficial in PD (Shults et al., 2002). The results of other studies have suggested that statins may induce myopathy through the impairment of calcium signaling (reviewed in Gluba‐Brzozka et  al., 2016). The mevalonate pathway, which statins inhibit, also produces heme A, which has its own central involvement in mitochondrial electron transport (Manoukian et  al., 1990). Lovastatin and simvastatin inhibit mitochondrial respiration in isolated liver mitochondria by a direct effect on electron transport at complex II/III, complex IV, and/or complex V (Nadanaciva et al., 2007). Evidence for a loss in complex IV activity following statin treatment has been reported in patients treated with the statin cerivastatin together with gemfibrozil (Arenas et al., 2003) and simvastatin in conjunction with cyclosporine and itraconazole, respectively (Duncan et al., 2009). Furthermore, a recent study that investigated the pharmacological effect of statins in their acid and lactone forms found that mitochondrial respiratory complex III inhibition was a potential off‐ target mechanism associated with statin‐induced myopathies (Schirris et al., 2015). In vivo effect of statins on platelet energy metabolism can be attributed to drug

effects on complex I of the electron transport system (Vevera et al., 2016). It is important to bear in mind that although statin‐ induced CoQ10 deficiency and mitochondrial respiratory chain impairment may be a contributory factor to the myopathic adverse effects associated with statin therapy, multiple pathophysiological mechanisms are thought to contribute to statin myotoxicity (Apostolopoulou et  al., 2015; Banach et  al., 2015; Taylor & Thompson, 2015; Tomaszewski et al., 2011), and further studies are required to elucidate mitochondrial dysfunctions that contribute to statin‐induced neuropathy.

9.3 Mitochondria and Retinal Drug Toxicity Humans obtain approximately 80% of external information from vision. Since loss of vision markedly decreases quality of life, it is extremely important to assay the risk of drugs and chemicals for visual toxicity. The focus of  this section will be on injury to the retina and optic nerve. Optic neuropathies are an important cause of chronic visual impairment and have in common the degeneration of retinal ganglion cells (RGCs), whose axons form the optic nerve (Pascolini & Mariotti, 2012). Optic nerve dysfunction can present as the only manifestation of disease or can be part of other systemic or neurological disorders; it can result from ischemic insults, damage by shock, toxins, radiation, trauma, or hereditary factors (Miller & Newman, 2004). The optic nerve is susceptible to damage from toxins, including drugs, metals (e.g., lead, mercury, and thallium), organic solvents (ethylene glycol, toluene, styrene, and perchloroethylene), methanol, carbon dioxide, and tobacco. This group of disorders is named toxic optic neuropathy (TON) and is characterized by bilateral visual loss, papillomacular bundle damage, central or cecocentral scotoma, and reduction of color vision. In most of the cases of TON, the primary lesion is not limited to the optic nerve and may possibly originate in the retina or chiasm, among other origins. It is generally accepted that the common pathway, for at least some of the toxins, is mitochondrial injury and imbalance of intracellular and extracellular‐free radical homoeostasis (Wang & Sadun, 2013). The optic nerve is an extension of the CNS and has some unique structural features that potentially make it vulnerable to disease processes. At an ultrastructural level, unmyelinated nerve fibers exit the eye via the lamina cribrosa, becoming myelinated at its posterior border. Studies of human retina and optic nerve specimens using electron microscopy and histoenzymatic stains for

Manifestations of Drug Toxicity on Mitochondria in the Nervous System

the mitochondrial respiratory complexes showed an inverse relationship between the mitochondrial activities and myelination (Andrews et  al.,1999; Bristow et  al., 2002; Minckler et  al., 1976). The distribution of mitochondria in the optic nerve head reflects functional energy requirements to maintain conduction in the unmyelinated axon. It is abundantly clear that RGCs comprising the optic nerve axons are exquisitely sensitive to even minor disturbances in mitochondrial biogenesis or dynamics, with an innate susceptibility to undergo apoptosis under conditions of heightened cellular stress and elevated ROS levels (Yu‐Wai‐Man et al., 2011, references herein). This is more remarkable if we consider that the brain itself has tremendous energy needs. Furthermore, the relative oxygen consumption of the retina is higher than that of the brain, being one of the highest oxygen‐consuming tissues of the body (Yu & Cringle, 2001). The link between drug‐induced mitochondrial dysfunction and retinal damage is anticipated by findings of inherited diseases associated with mitochondrial genes and optic neuropathy. The two classical mitochondrial optic neuropathies are LHON and autosomal dominant optic atrophy (DOA), which share overlapping clinical and pathological features, despite being caused by mtDNA point mutations and a growing list of nuclear genetic defects, respectively. The defining neuropathological feature of LHON and DOA is the early loss of RGCs within the papillomacular bundle, resulting in an expanding field defect, known as a scotoma, within the patient’s central vision (Gorman et al., 2015). Interestingly, a subgroup of patients can develop a syndromic form of LHON and DOA that is characterized by prominent neurological deficits in addition to optic atrophy. The unique susceptibility of RGCs in mitochondrial optic neuropathies still remains a puzzling mystery, and although several hypotheses have been put forward, none has been conclusively demonstrated (Carelli et al., 2004; Yu‐Wai‐Man et  al., 2011). The highly specialized anatomical and physiological properties of RGCs are likely to be relevant, namely, their relatively high metabolic requirements due to sustained spiking activity; the constant exposure to potentially damaging light; the sharp 90° bend as their axons exit the eye at the lamina cribrosa; and the relatively long unmyelinated intraocular portion that necessitates a high density of packed mitochondria for efficient signal conduction (Andrews et al., 1999; Bristow et al., 2002). There is still an ongoing debate whether the determining factor that drives RGC loss in mitochondrial optic neuropathies is a bioenergetics crisis or toxic ROS levels, or possibly both factors (Levin, 2015). Other cellular mechanisms that have gained increasing attention in the context of mitochondrial optic neuropathies are mtDNA

maintenance and mitophagy and the cross‐talk with the endoplasmic reticulum at mitochondria‐associated membrane (MAM) interfaces (Burte et al., 2015; Tatsuta & Langer, 2008). In vitro approaches have been employed, and the effort of several research groups worldwide has led to the generation of faithful animal models for both LHON and DOA (Burte et al., 2015; Lin et al., 2012). These observations from inherited diseases validate the concept that retinal injury can result from impairment of mitochondrial function and provide a framework for understanding the effects of xenobiotics. In this section, the actions of three well‐known retinal toxins will be discussed, along with the evidence for a mitochondrial target for the toxicity. 9.3.1

Chloramphenicol

Chloramphenicol inhibits bacterial protein synthesis by binding to the 50S ribosomal subunit. The toxicity associated with chloramphenicol arises from inhibition of mitochondrial protein synthesis (Gilman et al., 1985) because of the similarity in structure of bacterial and mitochondrial ribosomes (Holt et  al., 1993; Yunis, 1988). Systemic chloramphenicol is now rarely used for treating severe disseminated infections; however, until the late 1970s, it was frequently used in the management of patients with cystic fibrosis, and a serious complication noted in this group of patients was bilateral optic neuropathy (Godel et al., 1980; Venegas‐Francke et  al., 2000; Yunis et  al., 1970). Transmission electron microscopy of bone marrow cells of patients taking chloramphenicol has shown swollen mitochondria with disrupted cristae and an abnormally high level of intramitochondrial iron deposits, confirming the toxic effect of the drug (Smith et  al., 1970). These findings strongly suggest that the pathological changes in chloramphenicol optic neuropathy are due to a similar mitochondrial toxic effect. In experimental models involving the study of neuronal function, additional evidence suggesting an interaction between chloramphenicol and mitochondrial function also emerges. For example, injury to the auditory nerve induced by high noise levels or gentamicin produces an injury that is associated with (and perhaps ameliorated by) increased biogenesis of mitochondria. Treatment of  animals with chloramphenicol exacerbates this form of injury (Hartlage‐Rubsamen & Rubel, 1996; Hyde & Durham, 1994; Hyde & Rubel, 1995). Chloramphenicol also decreases glucose utilization and inhibits NADH oxidation in rat brain (Mottin et  al., 2003; Moulin‐ Sallanon et al., 2005). Considering the special energetic requirements and mitochondrial distribution of RGCs  previously mentioned, the presumption that the

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chloramphenicol‐induced optical neuropathy is due to mitochondrial dysfunction is reasonable. 9.3.2

Ethambutol

Ethambutol is a commonly used first‐line antituberculous drug; however the course of its ocular toxicity remains unpredictable (Chan & Kwok, 2006). Besides its optic nerve toxicity, ethambutol could also be toxic to the neural retina, which can result in field defects, color vision abnormalities, loss of visual acuity, or even permanent visual impairment (Ezer et  al., 2013; Garg et al., 2015; Koul, 2015). It is generally considered that optic  neuropathy is the dose‐limiting toxicity with ethambutol treatment (Barron et al., 1974; Fraunfelder et al., 2006). Peripheral neuropathy is a rare side effect that can occur also at a lower dose and is duration and dose dependent (Lee et al., 2008; Melamud et al., 2003). The mechanism by which ethambutol produces a selective effect on optic nerve function is not clear, but  studies have suggested a specific involvement of mitochondria and various pathophysiological mechanisms have been proposed including disruption of mitochondrial complex IV activity through a copper‐chelating action, zinc‐mediated lysosomal membrane permeabilization, and glutamate excitotoxicity. Ethambutol’s therapeutic action is hypothesized to act as a chelating agent for zinc and copper. Ethambutol is a metal chelator, destroying bacteria by inhibiting arabinosyltransferase, an important enzyme in mycobacterial cell wall synthesis. Due to the similarity between mammalian mtDNA and bacterial ribosomes, ethambutol also disrupts OXPHOS and mitochondrial function by interfering with iron‐containing complex I and copper‐containing complex IV (Kozak et al., 1998). Copper is a required cofactor for cytochrome c oxidase, an essential component in the electron transport chain. Ethambutol may reduce the level of copper, thereby interfering with OXPHOS. Replacing copper leads to improved RGC survivability in in vivo models of ethambutol optic neuropathy (Yoon et al., 2000). It is interesting that copper deficiency due to malabsorption from bariatric surgery also has been associated with visual loss from optic neuropathy (Becker et al., 2012; Pineles et al., 2010). Other studies suggest that zinc also might play a role in ethambutol toxicity (Leopold, 1978; Yoon et al., 2000) and individuals with reduced serum zinc level may be more susceptible to ethambutol ocular toxicity (De Palma et al., 1989; Delacoux et al., 1978). A study using cell cultures demonstrated that the chelating effect of ethambutol may inhibit lysosomal activation, resulting in accumulation of zinc in lysosomes with increased lysosomal membrane permeability and cell death (Chung et  al., 2009), perhaps

indicating a mechanism of facilitated zinc entry into neurons as is observed with agents such as pyrithione (Kandel, et al., 2012). Although the exact mechanism of the ethambutol ocular toxicity is not yet identified (Koul, 2015), it has been suggested (Heng et  al., 1999) that glutamate‐ mediated excitotoxicity may be the mechanism by which ethambutol is specifically toxic to RGCs. Excitotoxicity may mediate this effect through the generation of ROS, resulting in injury and death of the affected cells (Ezer et al., 2013; Wang & Sadun, 2013). It is well documented that NMDA receptor‐induced cell death is associated with excess calcium influx that is followed by mitochondrial dysfunction, free radical formation, and oxidative stress (Ganapathy et al., 2011; Lipton, 2007). In this context, the (partial) NMDA receptor antagonist memantine has been reported to provide protection against ethambutol‐induced retinal injury, involving normalization of oxidative stress and Müller cell stress responses (Abdel‐Hamid et  al., 2016). Memantine is a selective blocker of the excessive NMDA receptor activity without affecting their physiological function (Lipton, 2007; Seki & Lipton, 2008). Thus, the proposed effects of ethambutol on mitochondrial function recognize several different mechanisms that may contribute to neuronal injury. 9.3.3

Methanol

Methanol is a natural chemical that is used in many aspects of daily life, including its use as an industrial solvent, as a fuel source, or as a cheap adulterant of illicit liquors, and hence poses danger to human health. Methanol has been found to induce CNS dysfunction (Murray et al., 1991; Sweeting et al., 2010) and neurodegeneration (Henzi, 1984; Manuchehri et  al., 2015; Zakharov et al., 2015). Interestingly, methanol metabolism and mechanisms responsible for its toxic actions in primates have been extensively investigated in the periphery; however the mechanisms underlying its toxicity to the brain remain inexplicit in primates. Many studies have reported that methanol toxicity to primates is mainly associated with its metabolites, formaldehyde (FA) and formic acid. For example, formic acid has been found to be responsible for the metabolic acidosis witnessed in methanol‐intoxicated humans (Jacobsen & McMartin, 1986; McMartin et al., 1980) and nonhuman primates (Eells et  al., 2003; McMartin et  al., 1977) and the ocular toxicity observed in methanol‐poisoned humans (Jacobsen & McMartin, 1986; Sharpe et  al., 1982) and nonhuman primates (Martin‐Amat et  al., 1978; Martin‐Amat et al., 1977). Only recently that the toxicity of methanol has been linked to its metabolites, FA and/or formic acid, in the brain (Zhai et al., 2016).

Manifestations of Drug Toxicity on Mitochondria in the Nervous System

It is believed that visual symptoms are related to mitochondrial damage and suppression of oxidative metabolism by inhibiting cytochrome oxidase activity (Eells et  al., 2000; Sadun, 1998) so that toxicity is associated with acute metabolic failure (Nicholls, 1976). Formate is not a particularly potent inhibitor of cytochrome oxidase, with Ki values reported between 1 and 30 mM, depending on the oxidation state of the cytochrome (Nicholls, 1976). However, millimolar concentrations of alcohols in plasma are typical following normal consumption. As a result of the methanol intoxication hyperemia, edema and optic nerve atrophy occur (Sadun, 1998). The failure to oxidize formic acid is a critical element in the toxicity of methanol in humans. As most animal species have the ability to detoxify formic acid, they do not normally suffer methanol toxicity. However, it is possible to model methanol toxicity in rodents by inhibiting formic acid oxidation, and formate‐induced mitochondrial dysfunction and retinal photoreceptor toxicity have been documented in this animal model (Eells et al., 2000; Murray et al., 1991; Seme et al., 1999; 2001). Interestingly, photobiomodulation, also known as low‐level laser therapy or far‐red to near‐infrared (FR/ NIR) light therapy, has been used as an innovative and noninvasive therapeutic approach for retinal conditions including methanol‐induced retinal damage. Since the stimulation of cytochrome c oxidase is the suspected primary effect of FR/NIR phototherapy, it is not surprising that treatment with 670 nm light after methanol poisoning was able to ameliorate the retinal damage in a rat model of methanol toxicity (Eells et  al., 2003) (see Geneva, 2016).

9.4

Mitochondria and Ototoxicity

Ototoxicity is the functional impairment and cellular degeneration of the tissues of the inner ear caused by therapeutic agents or chemicals. While some ototoxic agents have a propensity to affect the auditory system (cochleotoxic) and others the vestibular system (vestibulotoxic), there is an overlap between the two. There are a number of compounds currently in clinical use with known ototoxic properties, including aminoglycoside antibiotics, salicylates, antineoplastic platinum‐based chemotherapy agents, antimalarial drugs, heavy metals, and loop diuretics. Despite differences in chemical composition and function between the relevant drug groups, the symptomatic hearing loss is typically a high‐frequency sensorineural hearing loss, progressing from higher to lower frequencies with prolonged treatment using aminoglycosides (Brummett & Fox, 1989), platinum‐based chemotherapy

(Blakley & Myers, 1993), salicylates (Jung et  al., 1993), antimalarial (Taylor & White, 2004), heavy metals (Rybak, 1992), and loop diuretics (Rybak, 1993). There are however exceptions; aspirin, for example, can give a flat audiogram (Jung et al., 1993). Ototoxic hearing loss is typically symmetrical; however unilateral and asymmetrical cases have been reported (Einarsson et  al., 2010). Despite known risks of ototoxicity, certain medications continue to be used but require a close monitoring of plasma levels. In general, although the associations between the use of these drugs and ototoxic adverse effects are well documented, the mechanisms underlying damage to the ear are not well understood. This section will focus on reviewing the ototoxicity of aminoglycoside antibiotics and cisplatin, because both groups of drugs can cause the most severe and irreversible hearing loss. Aminoglycoside antibiotics include streptomycin, isolated from Streptomyces griseus; natural products such as neomycin, kanamycin, gentamicin, and tobramycin; and  semisynthetic products, such as netilmicin and amikacin. These agents are used clinically for treating infectious diseases, such as tuberculosis, and bacterial infections produced by aerobic Gram‐negative bacteria (such as bacterial endocarditis, urinary tract infections, and pneumonia). The incidence of reported hearing loss ranges from a few percent to up to 33%, and vestibular toxicity occurs in about 15% of patients who are administered with aminoglycosides (Chen et  al., 2007). The hearing impairment is a consequence of damage first to the outer hair cells, which appear to be most sensitive, followed by the inner hair cells. Selectivity of injury to the inner ear over other tissues may arise from the accumulation and slow clearance of these drugs from the ear after extended treatment (Bates, 2003). Aminoglycoside antibiotics exert their antibacterial effects at the level of the prokaryotic ribosome, inducing errors in protein synthesis (Benveniste & Davies, 1973; Gale et al., 1981). The basis for the selective bactericidal effects of the aminoglycosides is presumably their preferential binding to the bacterial ribosome (Alberts et al., 1989). Since mitochondrial ribosomes are structurally more similar to their prokaryotic ancestors than either ribosome is to the eukaryotic ribosome, aminoglycosides might be expected to interfere with mitochondrial protein synthesis, which could be in the basis of their ototoxicity. Work in various eukaryotic systems has shown that aminoglycosides are capable of forming complexes with membrane lipids (Au et al., 1987; Forge et al., 1989; Lipsky & Lietman, 1980; Sastrasinh et al., 1982; Schacht, 1978) and free iron (Priuska & Schacht, 1995). Ternary complexes between these molecules are capable of propagating highly reactive ROS and reactive nitrogen species (RNS) from H2O2 (Lesniak et  al., 2003; 2005).

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Moreover, there is ample evidence of swollen mitochondria in hair cells exposed to aminoglycosides (Bagger‐ Sjoback & Wersall, 1978; Dehne et  al., 2002; Fermin & Igarashi, 1983; Lundquist & Wersall, 1966; Mangiardi et al., 2004; Owens et al., 2007). This type of morphology is consistent with mitochondrial Ca2+ overload (Giorgi et al., 2012; Lemasters et al., 2009). Indeed, it has been shown that mitochondrial Ca2+‐driven increases in Δψ are both a necessary and a sufficient component of aminoglycoside‐induced hair cell death (Esterberg et la., 2014). Recently, it has been described that a functional consequence of this event is the oxidation of mitochondria and production of ROS (Esterberg et  al., 2016). Thus, while many pathways from distinct cellular compartments intersect to govern redox homeostasis (Daiber, 2010), it is proposed that mitochondria are perhaps the largest contributor to the oxidative changes observed during aminoglycoside‐induced hair cell death (Esterberg et al., 2016). These findings are in agreement with those of Chen, Zheng, Schacht, and Sha (2013), who demonstrated the important role of the mitochondrial superoxide anion radical scavenger peroxiredoxin 3; when rendered inactive, intracellular ROS levels are elevated and murine cochlear hair cells are sensitized to aminoglycoside toxicity (Chen et al., 2013). An alternative hypothesis suggests that aminoglycosides promote activation of the NMDA receptor via stimulation of the polyamine site, a proposal supported by the observation that concurrent treatment with NMDA receptor antagonists limits aminoglycoside ototoxicity (Basile et  al., 1996). Notably, this mechanism would also involve the excess production of oxidants following toxic NMDA receptor activation and mitochondrial Ca2+ accumulation (Stout et al., 1998). Antioxidant therapies have been proposed for the attenuation of aminoglycoside toxicity (Huth et  al., 2011; Tadros et  al., 2014; Xie et  al., 2011) using compounds such as reduced glutathione, N‐acetylcysteine, ubiquinone, and vitamin E in order to retain an appropriate redox balance (Kowaltowski et  al., 1998; Mari et al., 2009; 2013; Nordberg & Arner, 2001). 9.4.1

Cisplatin

As mentioned earlier, cisplatin is a widely used chemotherapeutic agent for the treatment of various malignancies, including testicular, ovarian, bladder, cervical, head and neck, and non‐small cell lung cancers. The mechanism of antitumor action of cisplatin involves uptake by the cancer cell and aquation within the tumor cell, which makes the drug more reactive for cellular targets. Then, the platinum atom of cisplatin forms covalent bonds with DNA at the N7 positions of purine bases to form intrastrand and interstrand crosslinks. A number of

downstream signaling pathways can then be activated to cause DNA damage. Cisplatin‐induced ototoxicity is associated with cumulative dose and dose intensity (Brydoy et al., 2009; Oldenburg et al., 2007b; Rademaker‐ Lakhai et al., 2006; Rybak, 2007), although considerable interindividual variability exists (Oldenburg et  al., 2007a,b; Ross et  al., 2009; Rybak, 2007). Studies of long‐term cisplatin ototoxicity that include audiometry  (median follow‐up = 4–6 years; range = 1–13 years) (Bokemeyer et al., 1998; Osanto et al., 1992) show altered hearing thresholds in 28–77% of patients. Cisplatin‐ related hearing loss is usually bilateral and, although it initially involves higher frequencies, eventually affects a broader range, particularly those critical for speech perception (Biro et al., 2006). Long‐term tinnitus after cisplatin affects 19–42% of patients (Brydoy et al., 2009). Both elderly and pediatric patients are reportedly more sensitive to  cisplatin ototoxicity. A recent study thoroughly reviews the cochleotoxicity classification systems that have been published to date (Crundwell et al., 2016). Cisplatin ototoxicity can result from the overproduction of ROS in the cochlea (Rybak, 2007), causing irreversible free radical‐related apoptosis of outer hair cells, spiral ganglion cells, and the stria vascularis (Rybak, 2007; van Ruijven et al., 2005). The superoxides generated by the various cochlear tissues can (i) interact with NO and form peroxynitrites, which nitrosylate and inactivate proteins (Lee et  al, 2004a, b); (ii) form free hydroxyl radicals, which on interaction with iron (Fe) react with PUFA in the lipid bilayer of the cell membranes to generate highly toxic aldehyde 4‐hydroxynonenal (4‐HNE), leading to cell death (Lee et al., 2004a, b) (this increase in 4‐HNE has been associated with increased Ca2+ influx into the outer hair cell and apoptosis) (Clerici et al., 1995; Ikeda et al., 1993); (iii) inactivate antioxidant enzymes (Pigeolet et  al., 1990); and (iv) cause translocation of Bax from the cytosol to mitochondria, leading to release of cytochrome c and subsequent activation of caspase‐3 and caspase‐9. Caspase‐activated deoxyribonuclease (CAD) is then activated, causing DNA breakdown (Watanabe et  al., 2003) and cleavage of fodrin in the cuticular plates of injured hair cells (Wang et al., 2004). In the presence of cisplatin, ROS have been suggested to be produced via mitochondria (Kruidering et  al., 1997; Young et  al., 2002). Another study has indicated the involvement of NADPH oxidase since a unique isoform of nicotinamide adenine dinucleotide phosphate oxidase, NOX 3, has been demonstrated in the rat cochlea and is upregulated following ototoxic doses of cisplatin (Mukherjea et al., 2006). Ideal otoprotectant to be used along with cisplatin should be easy to administer and should not interfere

Manifestations of Drug Toxicity on Mitochondria in the Nervous System

with antitumoral effects of cisplatin. Data from animal models suggest that upregulation of antioxidant pathway activity, such as glutathione S‐transferases (GST) that are expressed in the mammalian cochlea (van Ruijven et  al., 2004), may help protect against ototoxicity (el Barbary et al., 1993). Interestingly it has been shown that siRNA against NOX3 blocked this high ROS generation in the organ of Corti hair cell cultures (UB/OC‐1 cells) (Mukherjea et al., 2008). Cisplatin‐induced cell death with increased lipid peroxidation and altered mitochondrial permeability transition (So et al., 2005) was also inhibited by a calcium channel blocker, flunarizine. Flunarizine is an antagonist of T‐type specific calcium channels that has been widely used to treat vertigo, migraine, epilepsy, and tinnitus. The protective mechanism of flunarizine on cisplatin‐ induced cytotoxicity is associated with direct inhibition of lipid peroxidation and mitochondrial permeability transition activation (Elimadi et  al., 1998). Oral flunarizine is a novel approach to decrease the irreversible assault of cisplatin and its metabolites on auditory cells. Flunarizine is well tolerated and has minimal side effects with oral mode of administration, thus making flunarizine a potential otoprotective agent to be coadministered with cisplatin. 9.4.2 Mitochondrial Disorders, Hearing Loss, and Ototoxicity Mitochondrial disorders are usually associated with pathologies affecting the central and peripheral nervous systems (Carelli & Chan, 2014). The mtDNA is particularly prone to damage, with a mutation rate 10 times higher than that of nDNA (Jeppesen et  al., 2011). Moreover, it replicates more often than the nDNA, and the efficiency of repair mechanisms appears to be less efficient than the one for nDNA (Kazak et  al., 2012). Point mutations are, in general, maternally inherited and heteroplasmic, with an estimated incidence of 1 : 5000 (Chinnery et al., 2012). They can affect mtDNA‐encoded proteins, tRNA or rRNA, and eventually ATP production by promoting OXPHOS deficiency and ROS excess, which may foster cell apoptosis (Carelli & Chan, 2014; Chinnery et al., 2012; Copeland, 2014). In fact, the function of the inner ear is particularly sensitive to impairment of mitochondrial function, and this is reflected by the relatively frequent association of maternally inherited mitochondrial dysfunction with hearing impairments. Almost 600 pathogenic point mutations have been identified in the last years (see review Pinto & Moraes, 2014), involving most of the mtDNA molecule (according to MITOMAP, 299 point mutation involving tRNA–

rRNA and control regions and 274 involving OXPHOS proteins). For example, about 80% of MELAS symptoms cases are caused by a very common A3243G mutation in the mitochondrial tRNALeu(UUR) gene, whereas 10% of  cases carry the T3271C mutation in the same tRNALeu(UUR). Another well‐known multi‐systemic disease and hearing loss disease is the one produce by large mtDNA deletion in Kearns–Sayre syndrome (KSS) (Spector & Johanson, 2010). The first identified mutation was the A1555G mutation in the mitochondrial 12S rRNA gene causing the non‐syndromic hypersensitivity to ototoxic effects of aminoglycosides by increased binding of aminoglycosides to mitochondrial ribosomes, leading to the disruption of mitochondrial protein synthesis (Harpur, 1982; Noller, 1991). Another recently identified mutation in the mitochondrial 12S rRNA gene is the T1494C in the conserved stem structure of 12S rRNA (Zhao et  al., 2004). Other nucleotide changes at position 961 in the 12S rRNA gene have been found to be associated with hearing loss. However, further studies are required to confirm whether and how often these changes would predispose carriers to aminoglycoside toxicity (Bacino et al., 1995; del Castillo et al., 2003). Several mutations in the mitochondrial tRNAser(AGY) gene are also known to cause maternally inherited non‐syndromic hearing loss (MIHL) by disturbing the tRNA structure and function (Guan et al., 1998). MtDNA changes can be a consequence of mutations in nDNA‐encoded genes involved in the maintenance of mtDNA integrity and mtDNA copy number. The most common mutations affect POLG, the gene encoding for the catalytic subunit of the mtDNA polymerase gamma, and PEO1, which encodes for the DNA helicase Twinkle (Milenkovic et al., 2013; Spelbrink et al., 2001). Over 200 mutations in POLG associated with mitochondrial diseases have been identified, causing a plethora of heterogeneous disorders involving different tissues time of onset and severity. Sensorineural hearing loss is an important pathological feature in a range of mitochondrial diseases including patients with POLG mutations (Kullar et  al., 2016). Two different groups created the “mutator mouse” by knocking in PolgA gene carrying two different mutations: the D257A mutation (Trifunovic et  al., 2004) or the AC → CT substitution in positions 1054 and 1055 (Kujoth et  al., 2005). These mutations provoked an accumulation of mtDNA point mutations in different tissues (Williams et  al., 2010), causing two  very similar clinical phenotypes, which included hearing loss. As previously described, Twinkle has a helicase activity essential for mtDNA replication and maintenance (McKinney & Oliveira, 2013). The Twinkle A360T

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mutation and aa 353–365 duplication are typical of PEO so that Twinkle mice have been generated knocking in the mutated gene (Tyynismaa et al., 2005), resulting in an accumulation of multiple large mtDNA deletions mostly in brain and muscle. Recently it has been described that a 13‐year‐old patient present a novel biallelic mutation in C10orf2, encoding the Twinkle mtDNA helicase, with features of infantile onset spinocerebellar ataxia (IOSCA), including a severe hearing loss (Pierce et al., 2016). Finally, mutations in proteins involved in regulation of  mitochondrial functions can also promote hearing dysfunction, and one example is OPA1. OPA1 protein (Alexander et  al., 2000; Delettre et  al., 2000) is a mitochondria‐targeted dynamin‐related GTPase that localizes to the inner mitochondrial membrane (Delettre et  al., 2000; Olichon et  al., 2006). It promotes fusion of  the inner mitochondrial membrane (Olichon et  al., 2006), maintains the integrity and structure of mitochondrial cristae (Frezza et  al., 2006), and is also implicated in maintenance of membrane potential and  OXPHOS (Lodi et  al., 2004). Interestingly, hearing dysfunction in OPA1 patients is underlain by auditory neuropathy due to degeneration of auditory nerve fibers. Santarelli et al. (2015) and Kullar’s results (2016) suggest a complex pathophysiology for sensorineural deafness in mitochondrial diseases, ranging from prevalent auditory neuropathy in OPA1 missense mutations to prominent cochlear or mixed cochlear/neural dysfunction in other genetic defects, particularly in mtDNA‐related diseases.

9.5 Mitochondrial Mechanisms of Central Nervous System injury The preceding sections have highlighted well‐established examples of drugs that produce characteristic adverse effects in the nervous system that are most likely the result of impairment of mitochondrial function. Attribution of the adverse effects to mitochondrial impairment is facilitated by the ability to associate specific and, typically, sensory deficits with drug exposure and then ultimately to link pathophysiological sequelae to one or more mitochondrial targets. This association proves to be much harder to establish in the context of potential toxic effects in the CNS that arise from mitochondrial inhibition. Although there are numerous drugs that act on the nervous system that also affect mitochondrial function (reviewed by Chan et al., 2005; Hargreaves et al., 2016), it proves to be much more difficult to establish explicit pathological consequences for the CNS that arise from mitochondrial inhibition. This is because the injury phenotypes would be expected to develop relatively slowly and would be manifested by altered behaviors or perhaps subtle neurological symptoms rather

than alterations in sensory modalities that are easier to detect and isolate. Rather than attempting to create speculative links between drugs and potential CNS toxicity, it is perhaps more useful to review mitochondrial mechanisms underlying neuronal injury based on known mechanisms derived from established neurotoxins. This will provide the context for understanding the potential manifestations of drug‐induced injury mediated by mitochondria and will provide an appreciation of the nature of the challenge of studying this kind of toxicity. 9.5.1 Mitochondrial Mechanisms of Neuronal Injury Mitochondrial dysfunction and neurotoxicity have been extensively studied along the years and also recently reviewed (Ayala‐Pena, 2013; Bates, 2003; Brand & Nicholls, 2011; Chaturvedi & Flint Beal, 2013; Duchen, 2012; Herrero‐Mendez et al., 2009; Llorente‐Folch et al., 2015; Moncada & Bolanos, 2006; Nicholls, Brand, & Gerencser, 2015; Siddiqui et al., 2012). There are several well‐established mechanisms by which mitochondrial mechanisms mediate neuronal injury. Elevated intracellular calcium, increased ROS, and energy depletion commonly represent the major known pathophysiologic mechanisms impacting neurons. There is also emerging evidence linking effects on mitochondrial morphology and trafficking with neuronal viability that will be briefly discussed. Mitochondria also serve as a focal point for the intrinsic pathways of apoptosis where they release cell death‐activating factors. However, it would be unusual for a drug to directly trigger release of proapoptotic factors from mitochondria, and this is considered beyond the scope of the present discussion. Glutamate is the main excitatory neurotransmitter in the brain, and it is involved in synaptic transmission and neuronal plasticity, neuronal development, outgrowth, and survival and in learning and memory. Under physiological conditions, neuronal mitochondria respond to glutamate by activating mitochondrial respiration (Clerc et  al., 2013; Gleichmann et  al., 2009; Jekabsons & Nicholls, 2004; Johnson‐Cadwell et  al., 2007; Llorente‐ Folch et al., 2016; Rueda et al., 2015; Yadava & Nicholls, 2007). This respiratory stimulation responds to the increased workload imposed by the rise in cytosolic Na+ and Ca2+ that flow through NMDA, AMPA, and kainate receptors (KR) and voltage‐gated Ca2+ channels, which rapidly activates Na+ and Ca2+ extrusion mechanisms that consume ATP (Rueda et al., 2015; Yadava & Nicholls, 2007). In such a way, the increased workload is matched by an increase in respiration and ATP production to cope with the increased energy demand (Llorente‐Folch et al., 2016). In physiological glutamate neurotransmission,

Manifestations of Drug Toxicity on Mitochondria in the Nervous System

glutamate release is rapidly terminated, and glutamate removal mechanisms work efficiently to clear glutamate up from the synaptic cleft. The NMDA receptor‐mediated Ca2+ influx is closely coupled to the generation of NO through the neuronal nitric oxide synthase (nNOS) activity, which acts as a secondary messenger involved in  the control of physiological functions (Moncada & Bolanos, 2006). In contrast to the aforementioned scenarios, the persistent presence of glutamate at synaptic and extrasynaptic sites leads to tonic activation of NMDAR, a situation in which mitochondria fail to counteract the stress induced by glutamate, resulting in a form of neuronal death termed excitotoxicity (Duchen, 2012; Mattson, 2003; Olney & Sharpe, 1969). Excitotoxic neuronal death is important in conditions such as epilepsy or stroke and even in neurodegenerative diseases such as Alzheimer’s disease and PD (Brennan et  al., 2009; Dong, Wang, & Qin, 2009; Hardingham & Bading, 2010; Mattson, 2003, 2008; Nicholls, 2008; Parsons & Raymond, 2014). The survival mechanisms of the cells are overridden by others governed by excessive Ca2+ load, ROS production, disruption of transmembrane ionic gradients, and limitation in energy substrates and ATP production. It has long been appreciated that neurons are injured by large elevations in intracellular Ca2+. There is now clear evidence that the entry and persistence of Ca2+ in mitochondria play a major role in glutamate excitotoxicity. Initially, this was inferred from the protective effects of uncouplers and other pharmacological approaches preventing mitochondrial Ca2+ uptake that protected neurons from death caused by glutamate (Stout et  al., 1998). More recently the finding that silencing of MCU protects against glutamate excitotoxicity (Qiu et  al., 2013) has given further support to the role of matrix Ca2+ in glutamate excitotoxicity. There is also evidence that zinc released from intracellular pools can also actively modulate the excitotoxic cascade (Sensi et  al., 2009). On the other side, ROS production at the onset of glutamate exposure is also involved in excitotoxicity. Activation of NMDARs is closely coupled to the generation of NO through nNOS, which is associated with the receptor through the postsynaptic density protein PSD‐95, promoting RNS and downstream ROS production. Glutamate activation of NMDAR leads to a PI3K‐ mediated rise in NADPH oxidase 2 (NOX2) activity, with a consequent increase in ROS production (Baxter et al., 2014; Brennan‐Minnella et al., 2015). Mitochondria are also involved in excitotoxic superoxide production (Duan et  al., 2007), and there is evidence showing that ROS scavengers decrease excitotoxic neuronal death (Brennan‐Minnella et al., 2013; Duan et al., 2007; Keelan

et  al., 1999). Additionally nNOS inhibitors (Pramila et al., 2015) and PSD‐95‐interacting peptides that block its recruitment to NMDAR (Chen et al., 2015) and NOX2 inhibitors (Brennan‐Minnella et al., 2013) all block excitotoxic neuronal death (for recent reviews see Brennan‐ Minnella et al., 2015; Lai et al., 2008). NO production has been suggested to play a role in respiratory inhibition at short times after glutamate stimulation by directly inhibiting cytochrome oxidase through competition of NO with O2 (Laranjinha et al., 2012; Li et al., 2009). In this regard, the relation between ROS/RNS generation and Ca2+ overload in excitotoxicity remains unresolved. In cortical and cerebellar granule neurons (CGNs), a glutamate‐induced transient increase in cytosolic Ca2+ is followed by a delayed irreversible rise in cytosolic Ca2+ named delayed calcium deregulation (DCD) (Tymianski et al., 1993), which precedes neuronal death. DCD occurs at the time of a collapse in the mitochondrial membrane potential (Abramov & Duchen, 2008; Duchen, 2012) and is followed by an acidification of the mitochondrial matrix (Bolshakov et  al., 2008; Li et  al., 2009), suggesting the involvement of the PTP. Mitochondrial oxidative stress, or more precisely an increased level of superoxide, is an effect, rather than a cause, of DCD (Vesce et  al., 2004), and it is presumably due to the leakage of electrons from complex I and III in the respiratory chain. In the context of drug toxicity to neurons, the inhibition of electron transport and subsequent production of ROS may be one of the more pathophysiologically relevant events. Interestingly, concentrations of rotenone sufficient to stimulate ROS production by brain mitochondria are similar to those associated with Parkinson‐like lesions in animal models, suggesting that mitochondrial ROS generation could be associated with the emergence of specific neurological disease phenotypes (Chaturvedi & Flint Beal, 2013). Moreover, mitochondrial Ca2+ overload and dysfunction, due to excessive Ca2+ entry through overactivated glutamate receptors, is a crucial early event in the excitotoxic cascade that follows ischemic or traumatic brain injury (for review see Murphy et al., 1999). From a therapeutic point of view of ischemia/stroke, interfering with the group of receptor‐operated cation channels opened by glutamate might be interesting. However, clinical trials with agents targeting these receptors have been disappointing (Davis et al., 2000; Kalia et al., 2008; Lees et al., 2000). Thus, it is necessary to consider other routes of Ca2+ entry into cells in order to planning new therapies. Combination therapy, using blockers of several routes of Ca2+ influx, may be necessary to obtain neuroprotective effects (Sattler & Tymianski, 2001; Sattler et al., 1996). The third component of the toxic triumvirate is energy depletion. As noted earlier, the brain is highly dependent on OXPHOS to support ion transport to maintain

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normal neuronal activity. At a gross level, ischemic brain injury is the consequence of the interruption of supply of key substrates and mitochondrial ATP production. Nicholls’ and Mattson’s groups (Gleichmann et  al., 2009; Jekabsons & Nicholls, 2004) along with others (Clerc et al., 2013; Rueda et al., 2015) have consistently reported that in cultured brain neurons, the early glutamate/NMDA‐induced increase in mitochondrial respiration is transient and drops rapidly in the continuous presence of glutamate/NMDA. The drop in respiration is highly sensitive to inhibitors of PARP‐1, and in their presence glutamate/NMDA‐induced increase in respiration is more sustained (Rueda et  al., 2015), pointing at PARP‐1 as cause of the drop in respiration. PARP‐1 uses NAD+ as substrate, and the regeneration of NAD+ uses ATP; it was concluded that the cause of PARP‐1 toxic effects was related to the drop in NAD+ and ATP, resulting in energetic failure (Alano et al., 2010; Eliasson et al., 1997; Ying et al., 2001). Interestingly, a recent study demonstrated that exogenous NAD+ can cross the plasma membrane and elevate mitochondrial NAD+ levels in mammalian cells, causing significant enhancement in mitochondrial oxygen consumption and ATP production (Pittelli et al., 2011). Furthermore, recently, two different groups have reported a direct action of PAR polymers in mitochondria‐associated hexokinase 1 (HK1), leading to an impairment of glycolysis and substrate supply to mitochondria with subsequent decrease in NAD+ and ATP after PARP‐1 activation (Andrabi et  al., 2014; Fouquerel et  al., 2014). Limitation in substrate supply caused by PAR polymers may be prevented by the provision of alternative substrates to mitochondria, such as pyruvate (Andrabi et  al., 2014), which explains the partially protective effect of pyruvate on glutamate excitotoxicity (Ruiz et al., 1998). The effects of PARP‐1 activation have been thoroughly discussed recently (Rueda et al., 2016). As discussed earlier, in addition to the limitation in substrate supply to mitochondria caused by PARP‐1 activation, excitotoxicity causes an irreversible dysfunction of mitochondria involving the PTP (Duchen, 2012; Nicholls, 2008). Involvement of the PTP in mitochondrial dysfunction due to glutamate excitotoxicity has considerable experimental support, but still leaves many open questions. Regarding the main topic of this chapter, one of these questions is the mechanism of the irreversible drop in mitochondrial respiration and mitochondrial dysfunction. It seems reasonable to assign it to the opening of the PTP, since that process, by allowing the release of metabolites and cofactors to the cytosol, would compromise respiration. On the other side, the results of Veas‐Perez de Tudela et al. (2015) suggest that it could be due to an irreversible inhibition of mitochondrial complex I by ROS produced as a consequence of

ATP synthase inhibition through phosphorylation by  Bcl‐xL before PTP opening. On the other hand, glutamate‐induced energy depletion is associated with AMP protein kinase (AMPK) activation, a critical regulator of cellular function in response to energy stress within the cells (Hawley et  al., 2003; Woods et al., 2003). AMPK activation may have a dual function in neurons promoting (i) cell survival during transient energy depletions (Culmsee et  al., 2001; Weisova et  al., 2009) or (ii) cell injury after prolonged AMPK activation (Li et  al., 2007; McCullough et  al., 2005), which implies that the duration and the level of AMPK activity within neurons after energetic stress is a pivotal factor in the decision between cell death and cell survival (reviewed in Weisova et al., 2011). It has been shown that transient glutamate excitation in CGNs results in an AMPK‐dependent increase in GLUT3 translocation to the cell surface and uptake of glucose, which alters mitochondrial bioenergetics in a Ca2+‐independent manner and enhances neuronal survival (Weisova et al., 2009). On the contrary, prolonged AMPK activation due to cellular ATP depletion can lead to neuronal apoptosis via the transcriptional activation of a proapoptotic Bcl‐2 family member, Bim (Concannon et  al., 2010). Though regulation of bim expression is highly complex (Biswas et al., 2007), it has been demonstrated that bim activation and cell death induction requires a two‐step FOXO3 activation by both AMPK‐dependent FOXO3 nuclear translocation and direct FOXO3 phosphorylation by AMPK, representing a key step in excitotoxic neuronal death (Davila et al., 2012). Within the past decade, studies have highlighted the impetus of mitochondrial dynamics in maintaining integral cell and animal physiological processes, influencing function and differentiation, and ultimately affecting survival (Chen & Chan, 2005, 2009). More specifically dysregulated mitochondrial fission and fusion dynamics have been shown to increase ROS, decrease ATP production, and alter apoptosis (Liesa et al. 2009) and mitophagy (Rambold et al., 2011; Shen et  al., 2014). These deficits are also associated with numerous neurodegenerative disorders including PD, Alzheimer’s disease, Charcot–Marie–Tooth disease, amyotrophic lateral sclerosis, and HD (Alobuia et  al., 2013; Korobova et al., 2013; Matic et al., 2015; Press & Milbrandt, 2008; Vohra et  al.,  2010; Wang et  al., 2005; Wen et al. 2011). More recent mechanisms to emerge from studies of mitochondrially mediated neuronal injury include alterations in mitochondrial trafficking and morphology. For example, agents that inhibit mitochondrial energy production including glutamate, oligomycin, and NO also acutely impair mitochondrial movement in neurons

Manifestations of Drug Toxicity on Mitochondria in the Nervous System

(Brown, 1999; Rintoul et  al., 2003, 2006; Zanelli et  al., 2006). Mitochondrial trafficking is also impaired by toxic proteins including expanded polyQ huntingtin (Chang & Reynolds, 2006; Trushina et  al., 2004) and by low but toxic concentrations of intracellular zinc (Malaiyandi et al., 2005). Mitochondrial morphology might also be an important regulator of neuronal viability, given that mitochondrial fission appears to be associated with a greater vulnerability to cellular injury (Bossy‐Wetzel et al., 2003; Brocard et  al., 2003; Frank et  al., 2001) and that toxins like glutamate decrease mitochondrial size (Rintoul et al., 2003). However, there are also signals that regulate mitochondrial movement that are clearly not toxic to neurons, including growth factors (Chada & Hollenbeck, 2004), and signals that stop mitochondrial movement in the vicinity of synapses may be important to ensure correct localization of mitochondria at sites of high energy demand (reviewed by Chang & Reynolds, 2006; Schwarz, 2013). Nevertheless, the direct impact of impeding mitochondrial trafficking on neuronal health and mitochondrial physiology warrants further investigations. 9.5.2 Potential Manifestations of Drug‐Induced Mitochondrial Dysfunction in the CNS The previous section detailed some of the neuronal injury mechanisms that are associated with mitochondrial dysfunction. In many cases, these mechanisms have been established experimentally by the acute application of high concentrations of toxins in short‐term experiments in vitro. It can be challenging to extrapolate from these findings to account for potential effects of mitochondrial toxins that are the result of long‐term exposures of low concentrations of toxins in vivo. However, assuming that drug‐mediated neuronal injury will be the consequence of relatively modest and potentially long‐ term exposures, it is possible to identify scenarios that could be indicative of the effects of a mitochondrial toxin in the CNS. Effects on a selectively vulnerable neuronal population: the experiments that expose rats to systemic low doses of rotenone and produce a Parkinson‐like syndrome (Betarbet et  al., 2000) raise the possibility that toxin exposure at relatively low concentrations at a mitochondrial target within a selectively vulnerable neuronal population could promote neuronal loss and trigger a disease like PD. The basis for selective cell vulnerability is rarely understood, although selective vulnerability is implied in most of the established examples of drug toxicity described in this chapter. Understanding the primary target for this form of injury and the dose and time

relationships between drug exposure and injury would allow the prediction of toxicity in this condition. Additivity with other toxic burdens: as already documented, relatively modest inhibition of mitochondrial function will amplify neuronal injury triggered by other mechanisms. Perhaps the most obvious scenario would be the addition of a low‐level drug‐mediated impairment of mitochondrial function with a second form of injury such as a stroke. The consequence in this case would be a worse outcome (“double hit”). This would be a more difficult form of drug effect to study, because the conclusions would also be dependent on the choice of injury mechanism. It would also be difficult to detect following drug exposure in humans due to the limited number of  comparable injury‐producing events in drug‐taking patients. Slowly accumulated injury: a surprising observation is the time that is sometimes required to see expression of injury following mitochondrial impairment. Examples of slowly developing injury that is unequivocally attributable to altered mitochondrial function include the mitochondrial late‐onset degeneration (MILON) mouse that requires several months following interruption of mtDNA replication and gene expression in the forebrain prior to manifestations of injury (Sorensen et al., 2001) and the MitoPark mouse in which dopaminergic neurons die over a year after the elimination of mitochondrial transcription factor A (Ekstrand et al., 2007). Injury that requires long periods (perhaps several years) of low‐level drug exposure prior to development of a phenotype is very difficult to detect in preclinical models and typically requires extrapolation from the consequences of substantially higher drug doses. These mechanisms are clearly not mutually exclusive, and an anticipated paradigm would reasonably reflect both the slow accumulation of injury and selective tissue vulnerability. Individual pharmacogenomic variation could also be important through an impact on drug absorption, metabolism, or excretion that changes either the drug exposure levels or the formation of active metabolites. The consequence of this combination of variables could plausibly be CNS injury that can only be detected with careful retrospective analysis of data from very large databases of reported adverse reactions, such as a recent report of an amyotrophic lateral sclerosis‐like syndrome in patients taking statins (Edwards, Star, & Kiuru, 2007).

9.6

Conclusion

This chapter has documented several relatively well‐ established cases where drug adverse effects are likely to be caused by toxic effects on mitochondrial function.

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The manifestations of these established toxic effects are largely impairments of sensory or motor function and arise from inhibition of mtDNA replication or transcription and translation of the mitochondrial genome. While the mechanisms that link drug action to injury are compelling, it is rare that the basis for the selectivity of the injury is completely understood. In addition, there are numerous cases where drugs have measurable effects on

electron transport and ATP generation. Several inhibitors of this type are known to produce selective neuronal injury. A further understanding of the consequences of modest mitochondrial impairment as well as the mechanisms underlying the injury produced by known neurotoxins should provide important insights that will refine predictive approaches to understanding drug toxicity in the nervous system.

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10 Nephrotoxicity: Increasing Evidence for a Key Role of Mitochondrial Injury and Dysfunction and Therapeutic Implications Ana Belén Sanz, Maria Dolores Sanchez‐Niño, Adrian M. Ramos, and Alberto Ortiz Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain

CHAPTER MENU 10.1 Scope of the Problem, 169 10.2 Pecularities of Tubular Cells, 169 10.3 Nephrotoxicity and Mitochondria, 170 10.4 Evidence of Mitochondrial Injury in Nephrotoxicity, 171 10.5 Calcineurin Inhibitor Nephrotoxicity, 172 10.6 HAART and Nephrotoxicity, 175 10.7 Other Nephrotoxic Drugs and Mitochondria, 177 10.8 Therapeutic Implications and Future Lines of Research, 178 References, 179

10.1

Scope of the Problem

Drug‐ and toxin‐induced nephropathies are common, numerous, and frequently underdiagnosed. Drugs may cause hemodynamic actions, leading to renal ischemia, or may be directly toxic to renal cells, leading to lethal or sublethal injury, mainly of tubular and endothelial cells. Several nephrotoxic drugs have been reported to damage mitochondria. A common manifestation of nephrotoxicity is acute kidney injury (AKI). It is estimated that a quarter of all episodes of AKI result from drug‐induced nephrotoxicity (Fillastre and Godin, 1998). AKI may fully recover upon withdrawal of the drug. However, it may evolve into chronic kidney disease requiring renal replacement therapy, either as a result of continuing exposure to the drug or as a result of a severe acute insult that interferes with recovery mechanisms. Drug‐induced tubular cell death (Ortiz et  al., 2003) may cause AKI of the acute tubular necrosis type. However, the term acute tubular necrosis precedes the coinage of the term apoptosis, and it does not indicate a role for a specific form of cell death (Ortiz et al., 2003). Tubular cell death can proceed through apoptosis, necrosis, or diverse forms of regulated necrosis. However, in humans it is often difficult to determine the

predominant mode of cell death, because histological sections can only recognize the absence of tubular cells. The relative contribution of the different cell death mechanisms to the initial tubular cell loss depends on the cause and severity of the insult. Additional mechanisms of drug‐induced renal injury  include idiosyncratic immune‐mediated renal injury, leading to acute tubulointerstitial nephritis, and intratubular precipitation of the drug or its metabolites, leading to crystalluria, nephrolithiasis, and obstructive renal disease. Nephrotoxic drugs may directly cause mitochondrial injury or inflammation, which the latter can further damage mitochondria (Ruiz‐Andres et al., 2015; Tang and Dong, 2016).

10.2

Pecularities of Tubular Cells

Daily function of the kidneys implies the glomerular production of 150–200 L of a plasma ultrafiltrate essentially free of proteins. Tubular cells modify the composition of ultrafiltrate by reabsorbing the bulk of it and by secreting certain molecules, such as organic anions and numerous drugs. Proximal tubular cells are the key contributors to transport processes and are rich in mitochondria, which

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

170

Mitochondrial Dysfunction by Drug and Environmental Toxicants Tubular lumen: urinary space MRP4

MRP2

Microvilli

Mitochondria OAT1

Drug fluxes

Figure 10.1 Schematic representation of the proximal tubular cell. Note the increased cell surface both at the luminal (apical, created by microvilli) and basolateral (membrane invaginations) aspects in order to increase the transport capacity. Different transporter molecules that facilitate antiviral drug fluxes and nephrotoxicity are indicated. A great number of mitochondria provide the energy required for such an intense transmembrane transport. MRP, multidrug‐resistant protein; OAT, organic acid transporter. Courtesy of Alejandro Ortiz.

provide the energy source for transport, and in cell membrane transporter molecules (Figure 10.1). The key ATP‐consuming transporter is the Na+/K+ ATPase in the basolateral membrane that creates an ionic gradient that is then used to drive transport of very diverse molecules in the luminal membrane. Cell membrane transporters contributing to active drug secretion into urine result in  higher intracellular concentrations of potentially cytotoxic drugs in proximal tubular cells than in other organs, as it is the case for certain antiviral drugs. The combination of a high number of mitochondria, high cellular energy requirements, and high intracellular concentrations of potentially nephrotoxic drugs and compounds facilitates proximal tubular cell‐specific toxicity.

10.3 Nephrotoxicity and Mitochondria Renal mitochondria are involved in substrate oxidation, ATP generation, cellular iron homeostasis, and cellular calcium detoxification. In addition, specific parts of the nephron have specific mitochondrial functions. As an example, 1α hydroxylase in proximal tubule mitochondria activates 25 dihydroxycholecalciferol to calcitriol, the active metabolite of vitamin D. These mitochondria

also release the ammonia required by distal segments to secrete protons into the urine. This cornerstone position of mitochondria in the intermediate renal metabolism explains their contribution to nephrotoxicity induction, mediation, or protection. Mitochondrial biogenesis and dynamics require the cooperation of nuclear and mitochondrial genes. Mitochondrial fission and fusion are tightly regulated by dynamin‐related protein (Drp1) and mitochondrial fission‐1 (Fis‐1) for fission and mitofusin 1 and 2 (Mfn1 and Mfn2) and optic atrophy 1 (OPA1) for fusion. 10.3.1 Respiratory Chain: Reactive Oxygen Species (ROS) Formation Small amounts of electrons leak from the respiratory chain at the NADH ubiquinone reductase and the ubiquinone cytochrome c reductase levels are trapped by  oxygen and form soluble oxygen radicals (www. cyberlipid.org/perox/oxid0003.htm, access January 20, 2007). The radical superoxide produced will be reduced to form H2O2. The physiological production of H2O2 is quite important, leading to a cellular concentration of 10−9 to 10−7 M. The activity of the respiratory chain is the rate‐limiting factor for the generation of free radicals. It is usually regulated by mitochondrial ADP availability, which in turn depends on cellular ATP consumption: increased ATP consumption increases ROS production. Under certain circumstances, ADP availability does not regulate mitochondrial oxidation. This circumstance, known as mitochondrial uncoupling, can be observed in the presence of certain nephrotoxins such as nitrophenols or in the presence of very high intracellular calcium levels. When mitochondrial uncoupling takes place, oxidation increases, but ATP production will decrease. The oxidative chain is also regulated by local production of nitric oxide (NO). The mitochondrial isoform of nNOS (mtNOS) (Kanai et  al., 2004) has specific posttranslational modifications. Under physiological conditions and with low NO concentrations (100

~24.9

−

+

Bosentan

N

7.43

>250

257.1

−

−

Perhexiline maleate

Y

2.16

10.07

~7.6

+

+

Ximelagatran

N

0.45

>250

>250

−

−

Antidiabetic drugs

Metformin HCl

N

7.74

>1000

774.2

−

−

Troglitazone

Y

6.39

41.49

19.7

+

+

CNS drugs

Buspirone

N

0.01

>500

>500

−

−

Entacapone

N

3.28

249.7

334.0

−

−

Nefazodone

Y

4.26

~31.8

18.6

+

+

Tolcapone

Y

47.58

57.01

45.3

+

+

Analgetic drugs

Acetaminophen

Y

165.38

6948

3801

+

+

Anti‐inflammatory drugs

Diclofenac

Y

13.13

>250

177.0

−

+

Antiviral drugs

Fialuridine

Y

>100

>100

−

−

that the IC50 value for SRC was smaller than the IC50 value from the viability assay. This indicates that the mitotoxic drug amiodarone causes mitochondrial injury before cellular viability is affected. The non‐mitotoxic drug ximelagatran was used as a negative control compound. A panel of 13 drugs of different compound classes was tested using this method to assess their mitochondrial liabilities. Positive controls were chosen based on clinical data and known association with mitochondrial toxicity; as negative controls, drugs not previously associated with mitochondrial toxicity were used. For this study, 3D InSight™ Human Liver Microtissues were exposed to serially diluted compounds for 48 h, and the IC50SRC (Seahorse XFe96) and IC50ATP (cell viability, CellTiter‐Glo) were determined. Results are summarized in Table 18.1. These data indicate that the 3D human liver microtissues correctly detected the tested mitochondrial toxicants, apart from fialuridine, a drug that is known to affect metabolism only after longer exposures (Bell et al., 2016). Additionally, the classification method allowed categorization of drugs into different risk categories. A drug was only classified as positive (for DILI or mitochondrial liability) if the obtained IC50 value was lower than 30 times the treatment concentrations in human plasma (Cmax).

1

This allows considering only clinically relevant concentrations of the tested drugs. For example, entacapone, a drug without clinical risk for DILI, resulted in a decrease of cellular viability (IC50ATP: 249.7 μM), but this corresponds to 76‐fold the Cmax concentration in human plasma (3.28 μM) and is therefore not counted as DILI positive. With this dataset, the sensitivity for detecting mitochondrial liability was 78% (7 out of 9 positive drugs correctly predicted) with a specificity of 100% (4 out of 4 negative drugs correctly predicted). Although employing a limited set of positive and negative control compounds, this dataset already indicates the suitability of the testing strategy to discriminate non‐mitotoxic compounds from potential hazardous compounds with mitochondrial liabilities. One of the wrongly classified drugs was fialuridine after a 2‐day exposure. Therefore, the incubation time was prolonged to assess the subchronic effect. With increasing exposure time (7 and 14 days), there is a clear increase in the toxicological response that is more pronounced after 14 days (IC50ATP: 8.5 μM; IC50SRC: 22.16 μM) as compared with 7 days (IC50ATP: 98.6 μM; IC50SRC: 74.5 μM) (Figure  18.4). Both cellular viability and SRC decreased simultaneously over time, indicating that the SRC is not preferentially targeted by fialuridine.

Using 3D Microtissues for Identifying Mitochondrial Liabilities

(a)

(b) IC50Day 2 = n. a.

IC50Day 2 = n. a.

150

200

IC50Day 7 = 98.6 μmol/L IC50Day 14 = 8.46 μmol/L SRC (% control)

Cell viability (% control)

200

100

50

0 0.01

0.1

1

10

100

IC50Day 7 = 117.4 μmol/L IC50Day 14 = 57.9 μmol/L

150

100

50

0 0.01

1000

0.1

Fialuridine (μmol/L)

1

10

100

1000

Fialuridine (μmol/L) Day 2

Day 7

Day 14

Figure 18.4 Long‐term toxicity assessment (2, 7, 14 days) of 3D InSight™ Human Liver Microtissues using total ATP content (a) and SRC (b). Error bars indicate standard deviations of at least three replicates.

18.4 SRC‐Based Detection of Mitochondrial Liabilities in Human Cardiac Microtissues Most of the drugs used in cardiology impact mitochondrial activity. However, the degree of impairment depends on the type of drug. Toxicological responses induced by cardiac drugs include (i) impairment of respiratory chain functions resulting in reduced ATP production, (ii) increased production of reactive oxygen species with increased oxidation of proteins or lipids, (iii) reduction of the mitochondrial membrane potential, and (iv) apoptosis. Cardiac drugs that have exhibited mitochondrial toxicity include amiodarone, phenytoin, lidocaine, quinidine, isoproterenol, clopidogrel, acetylsalicylic acid, and molsidomine (Finsterer and Zarrouk‐ Mahjoub, 2015). Anthracyclines, such as doxorubicin and epirubicin, are potent cytotoxic drugs, but their clinical use is often limited by their cardiotoxic side effects. Other cytotoxic drugs that have reported cardiotoxicity include 5‐fluorouracil, cisplatin, the taxoids paclitaxel and docetaxel, and newer drugs such as the monoclonal antibody trastuzumab (Cwikiel et al., 1995; Lieutaud et  al., 1996; Gennari et  al., 1999; Schimmel et al., 2004). Here, amiodarone and docetaxel were tested whether mitochondrial liabilities could be observed using 3D InSight™ Human Cardiac Microtissues. A similar analytical setup was applied as with the human liver microtissues. In accordance with previous results, amiodarone

treatment led to a lower IC50SRC (94.1 μM) than IC50ATP (139 μM) (Figure 18.5), indicating mitochondrial impairment as primary toxicological pathway. Even more pronounced was the shift with docetaxel. Whereas there was no response observed in total ATP content after 2‐ day exposure time, there is a clear dose response observed looking at the SRC. Docetaxel has been associated with increased ROS production and hence mitochondrial impairment (Gorrini et al., 2013).

18.5

Conclusion

Mitochondrial impairment can currently be assessed with biochemical (isolated mitochondria) and cell‐based assays (Glu‐Gal and OCR measurements). The use of microtissues to evaluate the impact of drugs on mitochondrial function represents a next level of an in vitro tissue model. Especially for the liver, a metabolically relevant environment allows to test not only short‐term effects but also effects of mitochondrial active metabolites and long‐term effects. The 3D mitotoxicity assay described herein combines 3D microtissues with the Seahorse XFe96 analyzer providing a novel platform for assessment of mitochondrial impairment. The high SRC of microtissues allows it to be used as an early marker for mitochondrial stress. As described in this chapter, the SRC has shown to be a sensitive and robust endpoint for mitochondrial impairment across three different tissue types. Moreover, setting the IC50SRC in relation to the IC50ATP, compound‐mediated mitochondrial liabilities

301

Mitochondrial Dysfunction by Drug and Environmental Toxicants

ATP CellTiter Glo assay

Spare respiratory capacity

(a)

(b) IC50 = 94.1 μmol/L

200 IC50 = 139.2 μmol/L

150

SRC (% control)

Cell viability (% control)

200

100

50 0

150 100

50 0

100 10 Amiodarone (μmol/L)

1000

10 100 Amiodarone (μmol/L)

1000

1 10 Docetaxel (μmol/L)

100

(d)

(c) 150

150

SRC (% control)

Cell viability (% control)

302

100

50

0

100

50

0 0.1

1

10

100

Docetaxel (μmol/L)

0.1

Figure 18.5 Toxicity assessment of 3D InSight™ Human Cardiac Microtissues using total ATP content (a, c) and SRC (b, d) for amiodarone (a, b) and docetaxel (c, d). Microtissues have been exposed for 2 days to the compounds. Error bars indicate standard deviations of at least three replicates.

can be discriminated from other toxicological pathways. Overall, the integration of 3D microtissues within the Seahorse technology generates a highly versatile platform for investigating mitochondrial response upon exposure of compounds and compound combinations.

Acknowledgments This work was supported by the European H2020 EU‐ ToxRisk (681002) and State Secretariat for Education, Research, and Innovation (SERI).

References Anson, B.D. et al. (2011) Opportunities for use of human iPS cells in predictive toxicology. Clin. Pharmacol. Ther., 89, 754–758. Beauchamp, P. et al. (2015) Development and characterization of a scaffold‐free 3D spheroid model of induced pluripotent stem cell‐derived human cardiomyocytes. Tissue Eng Part C Methods, 21(8), 852–861. Bell, C.C. et al. (2016) Characterization of primary human hepatocyte spheroids as a model system for

drug‐induced liver injury, liver function and disease. Sci. Rep., 6, 1–13. Berger, B. et al. (2016) Comparison of liver cell models using the basel phenotyping cocktail. Front. Pharmacol., 7, 1–12. Chan, K. et al. (2005) Drug‐induced mitochondrial toxicity. Expert Opin. Drug Metab. Toxicol., 1, 655–669. Cwikiel, M. et al. (1995) Changes of blood viscosity in patients treated with 5‐fluorouracil: a link to cardiotoxicity? Acta Oncol. (Madr), 34, 83–85.

Using 3D Microtissues for Identifying Mitochondrial Liabilities

Dykens, J.A. and Will, Y. (2007) The significance of mitochondrial toxicity testing in drug development. Drug Discov. Today, 12, 777–785. Eakins, J. et al. (2016) A combined in vitro approach to improve the prediction of mitochondrial toxicants. Toxicol. In Vitro, 34, 161–170. Finsterer, J. and Zarrouk‐Mahjoub, S. (2015) Mitochondrial toxicity of cardiac drugs and its relevance to mitochondrial disorders. Expert Opin. Drug Metab. Toxicol., 11, 15–24. Gennari, A. et al. (1999) Cardiotoxicity of epirubicin/ paclitaxel‐containing regimens: role of cardiac risk factors. J. Clin. Oncol., 17, 3596–3602. Gorrini, C. et al. (2013) Modulation of oxidative stress as an anticancer strategy. Nat. Rev. Drug Discov., 12, 931–947. Hill, B.G. et al. (2009) Importance of the bioenergetic reserve capacity in response to cardiomyocyte stress induced by 4‐hydroxynonenal. Biochem. J., 424, 99–107. Hynes, J. et al. (2012) High‐throughput analysis of mitochondrial oxygen consumption. Methods Mol. Biol., 810, 59–72. Hynes, J. et al. (2013) A high‐throughput dual parameter assay for assessing drug‐induced mitochondrial dysfunction provides additional predictivity over two established mitochondrial toxicity assays. Toxicol. In Vitro, 27, 560–569. Kelm, J.M. and Fussenegger, M. (2004) Microscale tissue engineering using gravity‐enforced cell assembly. Trends Biotechnol., 22, 195–202. Kelm, J.M. et al. (2003) Method for generation of homogeneous multicellular tumor spheroids applicable to a wide variety of cell types. Biotechnol. Bioeng., 83, 173–180. Kijanska, M. and Kelm, J. (2016) In Vitro 3D Spheroids and Microtissues: ATP‐based Cell Viability and Toxicity Assays. In: Sittampalam, G.S. et al. (Eds.) Assay Guidance Manual. Eli Lilly & Company and the National Center for Advancing Translational Sciences: Bethesda. Lancaster, M.A. et al. (2013) Cerebral organoids model human brain development and microcephaly. Nature 501(7467), 373–379.

Lieutaud, T. et al. (1996) 5‐Fluorouracil cardiotoxicity: a unique mechanism for ischaemic cardiopathy and cardiac failure? Eur. J. Cancer, 32A, 368–369. Marroquin, L.D. et al. (2007) Circumventing the Crabtree effect: replacing media glucose with galactose increases susceptibility of HepG2 cells to mitochondrial toxicants. Toxicol. Sci., 97, 539–547. McBeath, R. et al. (2004) Cell shape, cytoskeletal tension, and RhoA regulate stem cell lineage commitment. Dev. Cell, 6, 483–495. Messner, S. et al. (2012) Multi‐cell type human liver microtissues for hepatotoxicity testing. Arch. Toxicol., 87, 209–213. Nobes, C.D. et al. (1990) Non‐ohmic proton conductance of the mitochondrial inner membrane in hepatocytes. J. Biol. Chem., 265, 12903–12909. Pfleger, J. et al. (2015) Mitochondrial complex II is a source of the reserve respiratory capacity that is regulated by metabolic sensors and promotes cell survival. Cell Death Dis., 6, 1–14. Schimmel, K.J.M. et al. (2004) Cardiotoxicity of cytotoxic drugs. Cancer Treat. Rev., 30, 181–191. Vander Heiden, M.G. et al. (2009) Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science, 324, 1029–1033. Will, Y. and Dykens, J. (2014) Mitochondrial toxicity assessment in industry: a decade of technology development and insight. Expert Opin. Drug Metab. Toxicol., 10, 1061–1067. van der Windt, G.J.W. et al. (2012) Mitochondrial respiratory capacity is a critical regulator of CD8+ T cell memory development. Immunity, 36, 68–78. Wu, M. et al. (2007) Multiparameter metabolic analysis reveals a close link between attenuated mitochondrial bioenergetic function and enhanced glycolysis dependency in human tumor cells. Am. J. Physiol. Cell Physiol., 292, C125–C136. Zuellig, R.A. et al. (2017) Improved physiological properties of gravity‐enforced reassembled rat and human pancreatic. J. Tissue Eng. Regen. Med. 11(1), 109–120.

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19 Toward Mitochondrial Medicine: Challenges in Rodent Modeling of Human Mitochondrial Dysfunction David A. Dunn1, Michael H. Irwin2, Walter H. Moos3, Kosta Steliou4,5, and Carl A. Pinkert6 1

Department of Biological Sciences, State University of New York at Oswego, Oswego, NY, USA Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA 3 Department of Pharmaceutical Chemistry, School of Pharmacy, University of California San Francisco, San Francisco, CA, USA 4 Boston University School of Medicine, Cancer Research Center, Boston, MA, USA 5 PhenoMatriX, Inc., Natick, MA, USA 6 Department of Biological Sciences, College of Arts and Sciences, The University of Alabama, Tuscaloosa, AL, USA 2

CHAPTER MENU 19.1 19.2 19.3 19.4 19.5 19.6 19.7 19.8

19.1

Introduction, 305 Allotopic Expression of ATP6, 305 Xenomitochondrial Mice, 306 Galactose Treatment, 306 Rotenone Treatment, 307 Hepatotoxicity with Mitochondrial Dysfunction, 307 Hyperactivity of the Mitochondrial Stress Response in Mice, 308 Summary, 309 References, 309

Introduction

Efficient mitochondrial function is essential to numerous cellular processes, and mitochondrial dysfunction is understood to be involved in pathologic mechanisms of a growing list of clinical disorders (Irwin et  al., 2016; Moos and Dykens, 2015; Moos et al., 2016, 2017; Murphy et  al., 2016; Parameshwaran et  al., 2015; Steliou et  al., 2015; Wallace, 2013). Lasting moderate mitochondrial dysfunction is a characteristic of numerous human disorders and can be readily produced in cell culture by various means (Matenia and Mandelkow, 2014; Park et  al., 2016; Pickrell and Youle, 2015; Suliman and Piantadosi, 2016; Sun et al., 2016). Gaining insights into the mechanisms by which cellular events are translated into pathophysiological phenomena relies on laboratory animal modeling. Here, we highlight some mouse efforts at modeling mitochondrial dysfunction and the neurodegenerative and hepatotoxic hallmarks of human disease with mitochondrial involvement through multiple genetic and toxicological strategies.

19.2

Allotopic Expression of ATP6

All resident mitochondrial proteins, save the 13 encoded in the mitochondrial genome (mtDNA), are transcribed in the nucleus, translated in the cytoplasm, and transported to the various compartments of mitochondria. Numerous mtDNA mutations are known to result in human disease (Cannon et al., 2004; Dunn et al., 2012; Wallace, 2005, 2013). Nevertheless, one of the few strategies for recapitulating specific pathogenic human mtDNA mutations in cultured cells and the only way to create animal models to date has relied on a strategy of allotopic expression: recoding mtDNA‐encoded genes, adding a mitochondrial transport signal, and expressing the transgene from the nucleus (Dunn and Pinkert, 2012, 2014, 2015; Gearing and Nagley, 1986; Guy et al., 2009; Manfredi et al., 2002; Zullo et al., 2005). Subsequently, a line of transgenic mice was developed that allotopically expressed ATP6, a subunit of ATP synthase (Dunn and Pinkert, 2012, 2014, 2015). Like human patients with an mtDNA T8993G point mutation

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

306

Mitochondrial Dysfunction by Drug and Environmental Toxicants

(Holt et al., 1990), the transgenic protein expressed from the nuclear‐coded ATP6 transgene contained a substituted arginine in place of a conserved leucine at residue 156. Severity of T8993G phenotypes ranges widely in human patients, partially in association with heteroplasmic load (Carelli et al., 2002; Mäkelä‐Bengs et al., 1995; Uziel et al., 1997; White et al., 1999). Transgenic ATP6 mice expressed the mutated transgenic protein, which was transported into mitochondria, but the endogenous wild‐type mtDNA‐encoded ATP6 protein was also expressed. ATP6 is a very hydrophobic protein and has been postulated to cross mitochondrial membranes only with difficulty, but even a low level of normal protein would be expected to moderate deficits to some degree (Boominathan et  al., 2016; Perales‐Clemente et  al., 2011). Therefore, transgenic ATP6 mice were hypothesized to display a phenotype resembling a mild form of human disease associated with T8993G mutation characterized by neuromuscular deficits (Mäkelä‐Bengs et al., 1995). Rates of ATP production and oxygen consumption in heart, brain, and skeletal muscle tissues were not different between transgenic mice harboring mutant ATP6 and non‐transgenic controls. Manganese superoxide dismutase (MnSOD, SOD2) protein levels and serum lactate concentrations also showed no difference. A battery of neuromuscular and motor tests was administered to experimental mice. Transgenic mutant mice exhibited lower measures of neuromuscular strength. Assessments of motor coordination yielded mixed results in which transgenic mutant mice displayed superior performance in some measures, but inferior in others.

19.3

Xenomitochondrial Mice

Respiratory complexes are very large multi‐subunit enzymes made up of proteins encoded in both nuclear and mitochondrial genomes. The need for precise protein–protein interactions between subunits leads to coevolutionary pressures in both genomic compartments whenever residues involved in these interactions are changed via mutation. Therefore, as two species diverge through time, their mitochondrial and nuclear genomes would be expected to become increasingly less compatible with those of the other species. This hypothesis was tested in vitro as multiple lines of  xenomitochondrial cellular hybrids (cybrids) were produced containing nuclear DNA sequences from Mus musculus and mitochondrial genomes from a range of murid species (McKenzie et  al., 2003; Pinkert and Trounce, 2002; Pinkert et al., 2014). Lactate production, as well as respiratory deficits, correlated with increasing evolutionary distance. Attempts at recapitulating these results in vivo followed (McKenzie et  al., 2004; Pinkert

and Trounce, 2007; Trounce et al., 2004). Fusion of enucleated fibroblasts from related species (Mus spretus, Mus terricolor, Mus caroli, and Mus pahari) with Rho‐0 embryonic stem (ES) cells from M. musculus domesticus allowed creation of cybrid ES cells that were then injected into mouse blastocysts and transferred to pseudopregnant female mice for gestation. These efforts, following an exceptionally large number of blastocyst injections using several cybrid ES cell clones, led to production of over 60 founder chimeras, with five fertile germline females identified (McKenzie et al., 2004; Trounce et al., 2004, unpublished data). One of these lines of mice, which harbored mitochondria derived from M. terricolor, was expanded and characterized (Cannon et  al., 2011; McKenzie et  al., 2004). Respiratory oxygen consumption values were within the same range as those obtained from control mice. Behavioral and neuromuscular tests mostly displayed no differences between groups. One exception to this was rotarod analysis of neuromuscular coordination and endurance. Young xenomitochondrial mice (3–5 months of age) performed better than control mice, though this distinction was not seen in aged mice (9–14 months). Microarray analysis of gene expression in whole brain tissue samples of 3‐week‐old mice uncovered seven genes in the immediate early response gene family that were downregulated by at least twofold in comparison with control mice (Cannon et al., 2011).

19.4

Galactose Treatment

Galactose is a hexose sugar that is widely utilized in the production of glycolipids and glycoproteins and can be epimerized to glucose to be used as an energy source. However, it can be toxic as is seen in human patients with congenital mutations in genes encoding enzymes involved in galactose metabolism and in administration in high doses to rats (Lai et al., 2009). Cognitive decline, oxidative stress, and production of advanced glycation end products resulted from galactose treatment in rats (Chen et al., 2006; Lei et al., 2008; Zhang et al., 2005). Accordingly, an effort was envisioned to create a mouse model of human aging characterized by mitochondrial dysfunction with associated cognitive and motor deficits (Parameshwaran et al., 2010). Eight‐week‐ old mice received daily injections of d‐galactose intraperitoneally over a period of 6 weeks at a dose of 100 mg/kg body weight. Galactose‐treated and vehicle control mice were administered three experimental antioxidant compounds (l‐carnitine, alpha‐lipoic acid, and PMX‐500FI) or no additional treatment. Locomotor coordination, anxiety, spatial memory, and serum lactate levels were measured. In this study, galactose‐treated mice were not different from control animals in any of

Toward Mitochondrial Medicine: Challenges in Rodent Modeling of Human Mitochondrial Dysfunction

the measures of cognitive ability and motor function. Mice receiving galactose also did not display increased serum lactate concentrations. One potential factor in the lack of galactose‐mediated toxicity/mitochondrial dysfunction lies in an important genetic difference between mice and humans. Aplysia ras homology member I (ARHI, also known as GTP‐binding protein Di‐Ras3 (DIRAS3)), a tumor suppressor gene that has been evolutionarily lost in mice, is hypothesized to play a central role in galactose toxicity in human patients with inborn errors in galactose metabolism (Lai  et  al., 2008). In human cells lacking galactose‐1‐phosphate uridyltransferase (GALT), ARHI is upregulated when cultured in the presence of galactose. Overexpression of human ARHI in transgenic mice recapitulates many of the clinical signs of genetic galactose metabolism errors (Xu et al., 2000), and homozygous GALT knockout mice are fertile and symptom‐free (Ning et al., 2000). The lack of any discernable phenotype described previously in mice injected with galactose makes sense in light of their genetic lack of ARHI, a putative mediator of galactose toxicity.

19.5

Rotenone Treatment

Rotenone, a natural isoflavonoid produced by plants (Lee et al., 2014), is commonly used as an insecticide and piscicide (Oberg, 1964). Its molecular mechanism of toxicity is as a specific inhibitor of NADH dehydrogenase (Chance et al., 1963; Giordano et al., 2012; Grivennikova et al., 1997; Lee et al., 2014; Palmer et al., 1968). Long‐ term occupational exposure to rotenone in pesticide applicators is associated with increased incidence of Parkinson’s disease (Tanner et al., 2011). Rotenone treatment in laboratory animals is commonly used to model various aspects of Parkinson’s disease (Arif and Khan, 2010; Friedrich, 1999; Lapointe et al., 2004; Panov et al., 2005; Parameshwaran et al., 2012, 2015). With this in mind, rotenone administration was used to produce neurodegeneration in mice as a vehicle for testing the possible ameliorative effects of a synthetic carnitine–lipoic ester in mice (Parameshwaran et  al., 2012, 2015). In the first trial (Parameshwaran et al., 2012), 2‐month‐old mice were given daily doses of 30 mg/kg body weight by oral gavage for 28 days. Behaviorally, mice were assessed for locomotor coordination and neuromuscular strength/endurance. Molecular analyses included reactive oxygen species (ROS) measurements (dichlorofluorescein diacetate (DCFDA) fluorescence) in  lysates containing forebrain, midbrain, and cerebellum  tissues as well as measurement of phosphorylated and total stress‐activated protein kinase/c‐Jun amino‐ terminal kinase (SAPK/JNK), mitogen‐activated protein kinase 9 (MAPK9) as an assessment of generalized cellular stress (Nishina et al., 2004).

Rotarod analyses (locomotor coordination) displayed no differences between control and rotenone‐treated groups. Grip strength/endurance measurements showed marked decreases in mice that had been treated with rotenone. DCFDA fluorescence was elevated, indicating increases in ROS production in forebrain and midbrain, but not in cerebellum tissues of rotenone‐treated mice. Similarly, cellular stress (elevated pSAPK/JNK protein levels) was increased in the forebrain and midbrain, but not in the cerebellum. Here, rotenone‐induced mitochondrial dysfunction was detected via behavioral and cellular analyses. Subsequently, additional experiments were performed in which 3‐month‐old mice were treated daily for 7 days with a 400 mg/kg body weight oral dose of rotenone (Parameshwaran et al., 2015). Phenotypic measurements included electrophysiological recordings of long‐term potentiation (LTP), potentiation during theta burst stimulation (TBS), and measurements of presynaptic neurotransmitter release following TBS. Rotenone‐induced cell death in the hippocampus was assessed by measuring the mitochondrial fraction of proapoptotic effector protein Bcl‐2‐like protein 4 (BAX) as well as the phosphorylated fraction of proapoptotic protein Bcl‐2‐ associated death promoter (BAD). Phosphorylation state of extracellular signal‐related kinases 1/2 (ERK1/2) was also measured. LTP recordings were reduced in hippocampal slices of mice treated with rotenone; no difference between groups was seen in potentiation during TBS, and rotenone treatment resulted in a lower level of presynaptic neurotransmitter release compared with controls. Proapoptotic signaling was enhanced by rotenone. Mitochondrial translocation of BAX from cytoplasmic stores was increased in rotenone‐treated mice, while  phosphorylation of the proapoptotic BH3‐only protein BAD declined. Taken together, data from these two B‐cell lymphoma 2 (Bcl‐2) family proteins illustrate apoptotic neurodegeneration in hippocampi of rotenone‐treated mice. The percentage of phosphorylated ERK, which becomes activated by signals that promote cell survival and proliferation (Mebratu and Tesfaigzi, 2009; Roskoski, 2012), was decreased in the hippocampus tissue of rotenone‐treated mice.

19.6 Hepatotoxicity with Mitochondrial Dysfunction Troglitazone, an antidiabetic PPARγ agonist, was found to display idiosyncratic drug‐induced liver injury (idiosyncratic DILI or IDILI) in human patients, leading to the drug’s market withdrawal (Chojkier, 2005). Mitochondrial dysfunction was identified in conjunction

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with troglitazone hepatotoxicity. Isolated rat liver mitochondria exhibited impaired oxidative phosphorylation in the presence of troglitazone (Nadanaciva et  al., 2007). In cultured human hepatoma cells, troglitazone induced numerous features of mitochondrial dysfunction including increased production of ROS and decreases in mtDNA content and mitochondrial membrane potential (Dan et al., 2015). Yet despite clear mitochondrial involvement in troglitazone‐induced toxicity in vitro, liver damage is not found in troglitazone treatment of healthy mice (Ong et al., 2007). Indeed, a lesson learned from the failure of troglitazone is the lack of correlation between mitochondrial toxicity phenotypes in preclinical animal models and human patients. This growing realization that mitochondrial toxicology profiles in mice do not follow human clinical experience in a number of experimental compounds is a motivating factor in using transgenic mouse models designed to inhibit some aspect of mitochondrial function. SOD2‐deficient mice constitute one such line of transgenic rodents used to model hepatic toxicity. Mice homozygous for a targeted inactivation of SOD2 die within the first three postnatal weeks with severe cardiac myopathy and neurological degeneration (Lebovitz et  al., 1996). Heterozygous mice display no abnormal phenotype (Lee et al., 2008; Ong et al., 2007). However, when heterozygous SOD2+/− mice are treated with troglitazone (Fujimoto et  al., 2009; Lee et  al., 2008; Ong et  al., 2007), flutamide (Kashimshetty et  al., 2009), acetaminophen (Fujimoto et al., 2009), or trovafloxacin (Hsiao et al., 2010), hepatic injury occurs to varying degrees (Zhang et al., 2011). Juvenile visceral steatosis (JVS) mice harbor a mutation in the organic cation/carnitine transporter 2 (OCTN2), leading to systemic carnitine deficiency. Homozygous mice display fatty changes in numerous organ systems and with carnitine supplementation can live up to a year (Kaido et  al., 1997). Heterozygous mice display lower than normal levels of carnitine uptake but few pathological signs (Lahjouji et al., 2002). When heterozygous jvs+/− mice were treated with valproic acid (Knapp et al., 2008) or with dronedarone (Felser et al., 2014), minor hepatocellular steatosis and activation of capase‐3 in a subset of hepatocytes was observed in both models.

19.7 Hyperactivity of the Mitochondrial Stress Response in Mice In general, the aforementioned results indicate that producing enduring mitochondrial impairment in animal models is more difficult than originally envisioned from initial observations in cell culture. From our work in allotopically expressing ATP6, the lack of pathologic phenotype might be partially due to inefficiency in mitochon-

drial transport of the cytosolic protein. Another potential factor could be the presence of endogenous mtATP6. On the other hand, if hydrophobic nuclear‐expressed ATP6 is coating the surface of mitochondria, they might be expected to interfere with normal mitochondrial protein transport and thus cause some measure of mitochondrial dysfunction. Nevertheless, these transgenic mice did not express biochemical or neuromuscular phenotypes consistent with defects in mitochondrial function. Xenomitochondrial experimentation produced results in mice that conflicted with those observed in cell culture. While transmitochondrial cybrid cell lines produced high levels of lactate and displayed diminished respiratory capacity, xenomitochondrial mice did not. In those models in which toxic agents were administered, similar phenomena materialized. Galactose treatment yielded no discernable pathology. As noted previously, lack of the ARHI gene in mice but its presence in humans might be involved in the different levels of toxicity seen in hypergalactosemia (Lai et al., 2009; Xu et al., 2000). Unlike the three models discussed previously, rotenone administration did produce reliable neurodegenerative effects. The phenotypes produced in these studies were useful for their primary intended purpose of testing the potential protective effects of experimental compounds. However, the acute mitochondrial dysfunction produced in these efforts does not mimic the long‐lasting chronic mitochondrial defects seen in human aging and other neurodegenerative disorders. Arriving at the rotenone dosage required to produce the desired phenotypes necessitated substantial titration. Generally, the window between high mortality and lack of dysfunction was narrow (unpublished data) with dosages given close to the reported oral LD50 in mice of 350 mg/kg (Ellenhorn and Barceloux, 1988). The compounds studied in models of DILI cited here induced little to no phenotype in normal mice but produced pathological effects of varying strength in mice with mutations affecting mitochondrial function. Similarly, two genetic mouse models with homozygous mutations in genes involved in mitochondrial homeostasis (ROS detoxification and carnitine transport) displayed severe pathologies, but heterozygotes were healthy and only exhibited a pronounced pathological phenotype in the presence of a secondary chemical insult. Taken in the aggregate, these results suggest that in the face of slight to moderate stress, protective compensatory mechanisms minimize damage and prevent disease states previously hypothesized to result from mitochondrial dysfunction. Cellular mitochondrial turnover is largely modulated by biogenesis (Scott et al., 2014; Zhang et al., 2016), mitochondrial dynamics (Golpich et  al., 2017; Samant et al., 2014; Zhang et al., 2016), mitophagy (a natural subform of autophagy (Boya et al., 2016; Towers and Thorburn, 2016) that cells evolved to remove their damaged mitochondria (Matenia and Mandelkow, 2014;

Toward Mitochondrial Medicine: Challenges in Rodent Modeling of Human Mitochondrial Dysfunction Moderate stress in mice Allotopic expression Xenomitochondrial transfer Galactose Low-dose rotenone

Active stress response: no dysfunction

Moderate stress in humans Increased age Galactose Low-dose rotenone

Blunted stress response: dysfunction

Apoptosis

Severe stress High-dose rotenone

Figure 19.1 Mitochondrial stress response in mice and humans. Based on modeling efforts and a host of identified stressors, responsiveness in mice is more active. This in turn skews data interpretation regarding human mitochondrial dysfunction. Comparative studies characterizing regulatory mechanisms leading to human mitochondrial dysfunction and disease may lend support to our understanding of various pathways but are limited in their overall utility in developing solutions to human disease progression.

Pickrell and Youle, 2015; Wallace, 2013)), and a variety of stress responses (Golpich et al., 2017; Murphy et al., 2016; Zhang et al., 2016). Once the dysfunctional mitochondria are removed from the cell, the remaining healthy mitochondria undergo fission (divide) to replenish the numbers lost (Golpich et al., 2017; Pickrell and Youle, 2015; Samant et al., 2014; Scott et al, 2014; Zhang et al., 2016). Cellular nutrient levels and redox stress also contribute to the overall function of mitochondrial quality control and integrity (Diot et al., 2016; Gleyzer and Scarpulla, 2016; Jovaisaite et al., 2014; Murphy et al., 2016; Toyama et al., 2016; Zhang et al., 2016). Numerous signaling pathways interact to coordinate homeostasis. Varied evidence in our mouse models and those created by others (Fan et al., 2008; Irwin et  al., 2013; Safdar et  al., 2016; Trifunovic et  al., 2004) are indicative of aspects of mitochondrial quality control signaling pathway activation. The varied phenomena highlighted in this chapter describe a highly active mitochondrial quality control state in mice. In these varied models of mitochondrial dysfunction, mild or moderate pathological phenotypes are rare, but severe/lethal neurotoxic or hepatotoxic events occur as the degree of the insult increases. Thus as stress crosses a threshold and mitophagy reaches its limit, large‐scale apoptosis ensues. This outcome is rem-

iniscent of the phenotypic threshold effect seen in diseases caused by mtDNA mutations (Rossignol et al., 2003), likely with the same underlying mechanisms.

19.8

Summary

Reproducing in animal models the types of mitochondrial dysfunction seen in human disease has proven to be a complex problem that lies at the junction of multiple homeostatic and signaling pathways. The way forward is in determining why the mitochondrial stress response seems more active in rodents than in humans (Figure 19.1), thereby making modeling of human mitochondrial dysfunction so difficult. Research efforts into identifying comparative species differences in the regulation of these pathways are required. Once these differences are discovered and optimal combinations of genetic and/or pharmacologic targets identified, creating “humanized” mice (or other species) using gene editing protocols (Cannon et al., 2015; Dunn and Pinkert, 2014; Pinkert et  al., 2014; Seruggia and Montoliu, 2014; Singh et al., 2015) together with targeted delivery of appropriate chemical agents will allow creation of the animal models so desperately needed to more closely recapitulate pathways of human disease.

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Toward Mitochondrial Medicine: Challenges in Rodent Modeling of Human Mitochondrial Dysfunction

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20 Measurement of Oxygen Metabolism In Vivo* M. P. J. van Diemen1, R. Ubbink2,3, F. M. Münker3, E. G. Mik2, and G. J. Groeneveld1 1

Centre for Human Drug Research, Leiden, The Netherlands Department of Anesthesiology, Erasmus MC, Rotterdam, The Netherlands 3 Photonics Healthcare B.V., Utrecht, The Netherlands 2

CHAPTER MENU 20.1 20.2 20.3 20.4 20.5

Introduction: The Importance of Measuring Mitochondrial Function in Drug Trials, 315 Methods: In Vivo Methods to Measure Drug Effects on Mitochondrial Function in a Clinical Setting, 316 Measuring Mitochondrial Oxygen Consumption with the Protoporphyrin IX–Triplet State Lifetime Technique, 317 Features of a Novel COMET Measurement System: The First Bedside Monitor of Cellular Oxygen Metabolism, 317 Clinical Trial: Effect of Simvastatin on Mitochondrial Function In Vivo in Healthy Volunteers, 317 References, 319

20.1 Introduction: The Importance of Measuring Mitochondrial Function in Drug Trials Ever since the discovery of the causal involvement of defective mitochondria in Leber’s hereditary optic neuropathy, the roles of mitochondria in cellular physiology have been expanded from merely being an energy producer to a potential driver of apoptosis (Wallace et  al. 1988). Indeed, evidence is increasing that mitochondrial dysfunction plays important roles in many age‐related disorders, in some measure because mitochondrial capacity declines with age. Many different drug classes have toxic effects on mitochondria. Some of these medications are widely utilized so that it is of special interest to elucidate their mechanism of toxicity in various tissues, including muscle (Hargreaves et al. 2016). One of such drug class is  the statins, with simvastatin being most commonly * Drug‐Induced Mitochondrial Toxicity—Continuing Insight Yields Progress toward the Clinic, Will et al., in press.

prescribed (Diebold et al. 1994; Dai et al. 2010; Bouitbir et  al. 2011). Statins induce mitochondrial dysfunction by  at least three mechanisms. First, statins inhibit the mevalonate pathway, thereby repressing the biosynthesis of cholesterol and thus lowering plasma levels. However, the biosynthesis of coenzyme Q10 (Q10), an essential electron carrier in the electron transport system, is also repressed, which can correspondingly repress ATP production. A decrease in plasma and muscle Q10 levels after statin administration has been shown (Bleske et al. 2001; Lamperti et al. 2005; Paiva et al. 2005; Deichmann et  al. 2010), although discussion persists as to whether such decreases erode oxidative phosphorylation (OXPHOS) (Smith et al. 1991). Second, simvastatin significantly inhibits respiratory complexes I, II, III, IV, and V using immunocaptured complexes (Nadanaciva et al. 2007; Schirris et al. 2015). Finally, among the statins evaluated, simvastatin most potently uncoupled respiration from phosphorylation, dissipating membrane potential and so forestalling OXPHOS. Another class of medications that cause mitochondrial toxicity is the biguanides: phenformin, buformin, and metformin. The first two were withdrawn from the

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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market because of fatal lactic acidosis, while metformin remains on the market and is associated with lactic acidosis as a persistent adverse event (Dykens et al. 2008). All three molecules inhibit complex I of the electron transport chain with IC50s in accord with their systemic toxicity (El‐Mir et al. 2000; Ota et al. 2009; Andrzejewski et al. 2014). Interestingly, metformin has been reported to exert its antidiabetic effect through this inhibition, which represses diminution of hepatic gluconeogenesis and enhancement of glucose utilization in peripheral tissue as glycolysis accelerates to compensate for reduced OXPHOS (Owen et al. 2000). It is apparent that mitochondrial assessments are needed for development of novel drugs designed to enhance and/or maintain mitochondrial function. Given the growing number of drugs with deleterious effects on mitochondrial function, such assessments should be done early in the drug development program, while there is still chemical diversity of the lead screen hits. In addition to avoiding xenobiotic toxicity, the involvement of mitochondrial dysfunction in a wide range of diseases underscores the need for clinical mitochondrial assessments for diagnosis, progression, and prognosis. A number of in vivo techniques can assess mitochondria in their physiological environment, and we have been focusing on the development of noninvasive alternatives to more invasive procedures, such as a muscle biopsy.

20.2 Methods: In Vivo Methods to Measure Drug Effects on Mitochondrial Function in a Clinical Setting The ideal method of measuring mitochondrial function would be inexpensive and noninvasive, yet able to show multiple parameters of mitochondrial function, such as both oxygen consumption and phosphorous metabolism. In vivo assessments reflect mitochondrial function in situ, which, because of the complexity of the interaction of mitochondria and intra‐ and extracellular signals, is arguably most accurate. Several methods are currently available for both research and clinical settings. The gold standard of in vivo mitochondrial assessments relies on monitoring the stable isotope of 31‐phosphorus using magnetic resonance spectroscopy (31P‐MRS) and has been used in the research lab and clinic. 31P‐MRS is not a new technique, and its ability to measure phosphorus metabolism has been used clinically since the early 1980s to study mitochondrial diseases and myopathies (Gadian et  al. 1981; Edwards et al. 1982; Radda et al. 1984). One of the parameters, best reflecting mitochondrial function, is the

phosphocreatine (PCr) recovery time (τ‐PCr) (Bendahan et al. 2006; Lanza et al. 2011). When ATP is consumed, for instance, by muscle tissue during exercise, PCr serves as a “battery,” maintaining a constant level of ATP via PCr kinase. By focusing on the nuclear spins of phosphorus and hydrogen, the three phosphates of ATP and PCr are readily resolved. A typical experimental design entails some sort of stress such as restricting blood flow with a blood pressure cuff, or physical exertion, to deplete PCr and ATP and then monitor the rate of PCr recovery (τ‐PCr), which has been well validated as directly reflecting mitochondrial status, a contention also corroborated by in vitro respirometry (Bendahan et al. 2006; Layec et al. 2009; Lanza et al. 2011). Although use of surface coils renders this technique noninvasive, dynamic 31P‐MRS measurements are expensive and require specialized instrumentation and expertise, so it is not yet used for routine measurements in the clinic. Mitochondrial function can be determined using several less burdensome and cheaper alternatives. For example, systemic mitochondrial dysfunction can be assessed ex vivo by monitoring the mitochondrial membrane potential (MMP) in peripheral blood mononuclear cells (PBMCs). The MMP has long served as a direct reflection of the integrity of the mitochondrial membrane (Perelman et al. 2012) and a direct index of mitochondrial health. It can be disrupted by blockade of the mitochondrial respiratory chain or interference with mitochondria‐related death pathways (Chen 1988; Isenberg and Klaunig 2000; Kim and Blanco 2007; You and Park 2010; Choi and Lee 2011). Uncoupling the proton gradient from ATP production, via opening the mitochondrial permeability “transition pore” allows the protons to flow down the energy gradient bypassing ATP synthase (Moreno‐ Sanchez et al. 1999; Ding et al. 2005). Fluorescent dyes are typically used to examine the MMP. For example, JC‐1 (Perelman et al. 2012) is attracted by the negative charge in the inner membrane space. JC‐1 fluoresces green at low concentrations, but at high concentrations aggregates form that fluoresce red, thereby providing an index of MMP (Perelman et al. 2012). Measuring MMP as an ex vivo assessment can be performed in various types of intact cells or isolated mitochondria and is therefore a usable technique for various diseases and study designs. Perhaps most interestingly is measuring the MMP in PBMCs to assess systemic mitochondrial function. Several studies indeed show a decrease in MMP in circulating PBMCs of patients with neurodegenerative diseases, such as Alzheimer’s and Huntington’s disease (Panov et al. 2002; Lunnon et al. 2012). Oxygen consumption rate can be determined in skeletal muscle tissue, using near‐infrared spectroscopy (NIRS), and in skin, using a new technique called protoporphyrin IX–triplet state lifetime technique (PpIX‐TSLT).

Measurement of Oxygen Metabolism In Vivo

This novel technique makes use of the oxygen‐dependent delayed fluorescence of protoporphyrin IX, a precursor protein in the heme synthesis, which occurs in the mitochondria.

20.3 Measuring Mitochondrial Oxygen Consumption with the Protoporphyrin IX–Triplet State Lifetime Technique A novel technique is now available that enables real‐ time mitochondrial oxygen tension in mmHg in vivo. Mitochondrial oxygen tension (mitoPO2) is measured by means of PpIX‐TSLT, and it is used to assess mitochondrial function in human skin cells in vivo (Harms et  al. 2016). This is possible because of an oxygen‐ dependent time of afterglow (triplet state lifetime) of protoporphyrin IX (PpIX), the final precursor of heme in the biosynthetic pathway located in the mitochondria (Poulson 1976). The human skin has been used to perform the measurements, because of easy access and noninvasive nature, but the technique is not limited to measurements in the skin. All PpIX‐synthesizing cells are potential measurement locations, for example, the kidney and liver (Mik et al. 2008; Harms et al. 2012). Overproduction of PpIX can be induced in active mitochondria by exogenously providing aminolevulinic acid (ALA), the precursor to PpIX. This bypasses the negative feedback controls in the heme biosynthetic pathway, so that PpIX builds up inside the mitochondria overwhelming the slower reactions, converting PpIX to heme (Malik et al. 1995; Fukuda et al. 2005). This is necessary because, under normal (non‐sensitized) conditions, PpIX is present in human skin at very low concentrations and is not detected with the PpIX‐TSLT. As a small molecule, ALA penetrates the stratum corneum, and topical administration of ALA not only increases PpIX to detectable levels but also ensures mitochondrial origin of the triplet state fluorescence signal (Kennedy and Pottier 1992; Mik et al. 2008; Mik et al. 2009). After topical administration of ALA on healthy skin, typically for 4 h or more, PpIX is synthesized. In healthy skin this limits the measurement location and signal origin of the skin sensor to the epidermis with a thickness of about 0.1 mm (Sandby‐Moller et al. 2003). The recommended measurement location is the skin of the sternum. This provides a central measurement location less influenced by temperature changes, movement, and peripheral vasoconstriction (Campbell 2008). The optical properties of PpIX make possible its use as  a mitochondrial oxygen probe. After excitation with a  short pulsed laser, both immediate and triplet state

delayed fluorescence can be detected. The delayed fluorescence lifetime is inversely proportional to the amount of oxygen according to the Stern–Volmer equation (Mik et al. 2002; Mik 2013). Local pressure is applied by gently pressing down the probe, which stops local blood flow, thereby allowing determination of cellular oxygen utilization. In this way, the oxygen disappearance rate (ODR) is determined, as is the recovery rate upon reperfusion (Harms et al. 2013). This may become an easily accessible technique to determine mitochondrial function in real time at the bed side. It has been evaluated in this capacity using healthy volunteers and to detect changes in mitochondrial function in rats and volunteers (Harms et al. 2011, 2012, 2013, 2015, 2016).

20.4 Features of a Novel COMET Measurement System: The First Bedside Monitor of Cellular Oxygen Metabolism After introduction of the PpIX‐TSLT as a new method to  measure mitochondrial oxygen tension in vivo, the development of a clinical monitor was started. The prototype used in the volunteer trial has since been further developed by Photonics Healthcare B.V. (Utrecht, The Netherlands). This resulted in the COMET measurement system, an acronym for Cellular Oxygen METabolism. The COMET is a compact medical device approved for clinical use in Europe in 2016. It consists of a monitor and a skin sensor and uses a pulsed laser to illuminate the measurement site. The delayed fluorescent signal from PpIX accumulated in active mitochondria is projected on a gated red‐sensitive photomultiplier tube. Lifetimes of the raw data are calculated on an embedded control board. The thumb‐sized skin sensor holds optical fibers for excitation and detection. Sensor temperature, used as an approximation of skin temperature, is measured with an electrical resistive sensor.

20.5 Clinical Trial: Effect of Simvastatin on Mitochondrial Function In Vivo in Healthy Volunteers The in vivo techniques discussed previously measure mitochondrial function in different ways and so are complementary. Combining several techniques in a single study could therefore give a more complete and corroborating understanding of how and to what extent a drug might undermine mitochondrial function. To test this notion, we performed a clinical study at the Centre for

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Figure 20.1 Different methods to measure mitochondrial function in vivo or ex vivo. (a) phosphorous MRS, (b) protoporphyrin IX–triplet state lifetime technique, (c) near‐infrared spectroscopy, and (d) mitochondrial membrane potential. *p < 0.05.

Human Drug Research (CHDR, Leiden, The Netherlands), in which mitochondrial dysfunction was induced by administering a typical dose of simvastatin (40 mg once daily) for 4 weeks to healthy subjects. Mitochondrial function was assessed both in vivo and ex vivo using 31P‐ MRS, NIRS, PpIX‐TSLT, and MMP in PBMCs. After 4 weeks of simvastatin treatment, 31P‐MRS revealed that τ‐PCr was significantly prolonged by 15.2% compared with baseline; this is pathognomonic for mitochondrial impairment (from 31.36 to 36.12 s, 95% CI, 2.0–30.0; p < 0.05) (Figure 20.1a). Over the same period, measurements by PpIX‐TSLT revealed that oxygen consumption within mitochondria (mitoVO2) increased 13% (95% CI, −0.014 to 2.716; p = 0.052) (Figure 20.1b). For all subjects, the mVO2 showed a trend toward increasing (95% CI,

−0.25 to 3.418; p = 0.089) (Figure 20.1c), although the differences were not significant. Importantly, the percentage of dysfunctional PBMCs significantly increased from 5.20% at baseline to 14.43% after 4 weeks of simvastatin administration (95% CI, 2.416–16.056; p = 0.016) (see Figure 20.1d). The different techniques showed relative similar change, with the exception of the MMP in PBMCs, which showed a more drastic increase of dysfunction (see Figure 20.2). Taken together, the data indicate that simvastatin induces detectable mitochondrial dysfunction in as little as 4 weeks. This is in accord with the 31P‐MRS results of Wu et al. (2011) who reported that PCr exercise recovery kinetic times doubled (from 28.1 to 55.4 s) after a 4‐week regimen of statin therapy. They used a custom‐built calf

Measurement of Oxygen Metabolism In Vivo Change from baseline 150 PCr recovery time mitoVO2 mVO2

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flexion pedal ergometer that could fit into the magnet and obtained spectra before, during, and after exercise (Wu et al. 2011). Both using NIRS and PpIX‐TSLT techniques, increased in vivo oxygen consumption was revealed, although, in the case of muscle oxygen consumption using NIRS, this effect was only apparent as a trend. However, the mitochondrial oxygen consumption, measured by PpIX‐TSLT, shows to be close to significantly increased. Furthermore, the change in oxygen consumption follows the prolongation in τ‐PCr, measured by 31P‐MRS.

The effects of simvastatin on mitochondrial function and mitochondrial respiration can be distinguished between acute and chronic effects. The acute effect of simvastatin seems to be explained by a decrease of mitochondrial function only. Andreux et  al. (2014) showed that simvastatin decreased the basal oxygen consumption rate in Caenorhabditis elegans after 30 h of administration. The chronic effect of simvastatin, however, might point to an uncoupling effect on mitochondria, causing a decrease in mitochondrial function together with an increase of mitochondrial oxygen consumption. This idea is strengthened by the finding that the MMP in PBMCs decreased after 4 weeks of simvastatin administration. It should be noted in this context that, in an acute exposure model using isolated rat liver mitochondria, most of the statins, including simvastatin, both inhibit respiration and uncouple OXPHOS. Using isolated organelles reveals what could happen in the cell, tissue, or patient, but the latter are the result of interactions between a host of variables, such as drug metabolism, uptake carriers that increase dose concentrations in a subset of cells, and MMP that can increase mitochondrial exposure. In this way, it is difficult to predict the phenotype of mitochondrial dysfunction. For example, simvastatin not only inhibits complexes I, II‐III, IV, and V, which would eventually repress oxygen consumption and deplete MMP, but it also uncouples OXPHOS, which would increase oxygen consumption to the extent that ETS is inhibited. The data here imply that both inhibition (more dysfunctional PBMS with lower MMPs and slower PCr recharge) and uncoupling (increases in oxygen consumption) are occurring. The approach of combining corroborating assays with different readouts, plus the development of the first bedside monitor of cellular oxygen utilization, provides a more robust assessment and clinically relevant of drug‐induced mitochondrial dysfunction.

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Bleske, B. E., R. A. Willis, M. Anthony, N. Casselberry, M. Datwani, V. E. Uhley, S. G. Secontine and M. J. Shea (2001). “The effect of pravastatin and atorvastatin on coenzyme Q10.” Am Heart J 142(2): E2. Bouitbir, J., A. L. Charles, L. Rasseneur, S. Dufour, F. Piquard, B. Geny and J. Zoll (2011). “Atorvastatin treatment reduces exercise capacities in rats: involvement of mitochondrial impairments and oxidative stress.” J Appl Physiol (1985) 111(5): 1477–1483. Campbell, I. (2008) “Body temperature and its regulation.” Anaesth Intensive Care Med 9(6): 259–263. Chen, L. B. (1988). “Mitochondrial membrane potential in living cells.” Annu Rev Cell Biol 4: 155–181.

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Choi, E. M. and Y. S. Lee (2011). “Mitochondrial defects and cytotoxicity by antimycin A on cultured osteoblastic MC3T3‐E1 cells.” Food Chem Toxicol 49(9): 2459–2463. Dai, Y. L., T. H. Luk, C. W. Siu, K. H. Yiu, H. T. Chan, S. W. Lee, S. W. Li, S. Tam, B. Fong, C. P. Lau and H. F. Tse (2010). “Mitochondrial dysfunction induced by statin contributes to endothelial dysfunction in patients with coronary artery disease.” Cardiovasc Toxicol 10(2): 130–138. Deichmann, R., C. Lavie and S. Andrews (2010). “Coenzyme q10 and statin‐induced mitochondrial dysfunction.” Ochsner J 10(1): 16–21. Diebold, B. A., N. V. Bhagavan and R. J. Guillory (1994). “Influences of lovastatin administration on the respiratory burst of leukocytes and the phosphorylation potential of mitochondria in guinea pigs.” Biochim Biophys Acta 1200(2): 100–108. Ding, H., C. Han, J. Zhu, C. S. Chen and S. M. D’Ambrosio (2005). “Celecoxib derivatives induce apoptosis via the disruption of mitochondrial membrane potential and activation of caspase 9.” Int J Cancer 113(5): 803–810. Dykens, J. A., J. Jamieson, L. Marroquin, S. Nadanaciva, P. A. Billis and Y. Will (2008). “Biguanide‐induced mitochondrial dysfunction yields increased lactate production and cytotoxicity of aerobically‐poised HepG2 cells and human hepatocytes in vitro.” Toxicol Appl Pharmacol 233(2): 203–210. Edwards, R. H., M. J. Dawson, D. R. Wilkie, R. E. Gordon and D. Shaw (1982). “Clinical use of nuclear magnetic resonance in the investigation of myopathy.” Lancet 1(8274): 725–731. El‐Mir, M. Y., V. Nogueira, E. Fontaine, N. Averet, M. Rigoulet and X. Leverve (2000). “Dimethylbiguanide inhibits cell respiration via an indirect effect targeted on the respiratory chain complex I.” J Biol Chem 275(1): 223–228. Fukuda, H., A. Casas and A. Batlle (2005). “Aminolevulinic acid: from its unique biological function to its star role in photodynamic therapy.” Int J Biochem Cell Biol 37(2): 272–276. Gadian, D., G. Radda, B. Ross, J. Hockaday, P. Bore, D. Taylor and P. Styles (1981). “Examination of a myopathy by phosphorus nuclear magnetic resonance.” Lancet 2(8250): 774–775. Hargreaves, I. P., M. Al Shahrani, L. Wainwright and S. J. Heales (2016). “Drug‐induced mitochondrial toxicity.” Drug Saf 39(7): 661–674. Harms, F., R. J. Stolker and E. Mik (2016). “Cutaneous respirometry as novel technique to monitor mitochondrial function: a feasibility study in healthy volunteers.” PLoS One 11(7): e0163399. Harms, F. A., S. I. Bodmer, N. J. Raat and E. G. Mik (2015). “Non‐invasive monitoring of mitochondrial oxygenation and respiration in critical illness using a novel technique.” Crit Care 19: 343.

Harms, F. A., S. I. Bodmer, N. J. Raat, R. J. Stolker and E. G. Mik (2012). “Validation of the protoporphyrin IX‐ triplet state lifetime technique for mitochondrial oxygen measurements in the skin.” Opt Lett 37(13): 2625–2627. Harms, F. A., W. M. de Boon, G. M. Balestra, S. I. Bodmer, T. Johannes, R. J. Stolker and E. G. Mik (2011). “Oxygen‐ dependent delayed fluorescence measured in skin after topical application of 5‐aminolevulinic acid.” J Biophotonics 4(10): 731–739. Harms, F. A., W. J. Voorbeijtel, S. I. Bodmer, N. J. Raat and E. G. Mik (2013). “Cutaneous respirometry by dynamic measurement of mitochondrial oxygen tension for monitoring mitochondrial function in vivo.” Mitochondrion 13(5): 507–514. Isenberg, J. S. and J. E. Klaunig (2000). “Role of the mitochondrial membrane permeability transition (MPT) in rotenone‐induced apoptosis in liver cells.” Toxicol Sci 53(2): 340–351. Kennedy, J. C. and R. H. Pottier (1992). “Endogenous protoporphyrin IX, a clinically useful photosensitizer for photodynamic therapy.” J Photochem Photobiol B 14(4): 275–292. Kim, H. A. and F. J. Blanco (2007). “Cell death and apoptosis in osteoarthritic cartilage.” Curr Drug Targets 8(2): 333–345. Lamperti, C., A. B. Naini, V. Lucchini, A. Prelle, N. Bresolin, M. Moggio, M. Sciacco, P. Kaufmann and S. DiMauro (2005). “Muscle coenzyme Q10 level in statin‐related myopathy.” Arch Neurol 62(11): 1709–1712. Lanza, I. R., S. Bhagra, K. S. Nair and J. D. Port (2011). “Measurement of human skeletal muscle oxidative capacity by 31P‐MR spectroscopy: a cross‐validation with in vitro measurements.” J Magn Reson Imaging 34(5): 1143–1150. Layec, G., A. Bringard, Y. Le Fur, C. Vilmen, J. P. Micallef, S. Perrey, P. J. Cozzone and D. Bendahan (2009). “Reproducibility assessment of metabolic variables characterizing muscle energetics in vivo: a 31P‐MRS study.” Magn Reson Med 62(4): 840–854. Lunnon, K., Z. Ibrahim, P. Proitsi, A. Lourdusamy, S. Newhouse, M. Sattlecker, S. Furney, M. Saleem, H. Soininen, I. Kloszewska, P. Mecocci, M. Tsolaki, B. Vellas, G. Coppola, D. Geschwind, A. Simmons, S. Lovestone, R. Dobson, A. Hodges and C. AddNeuroMed (2012). “Mitochondrial dysfunction and immune activation are detectable in early Alzheimer’s disease blood.” J Alzheimers Dis 30(3): 685–710. Malik, Z., G. Kostenich, L. Roitman, B. Ehrenberg and A. Orenstein (1995). “Topical application of 5‐ aminolevulinic acid, DMSO and EDTA: protoporphyrin IX accumulation in skin and tumours of mice.” J Photochem Photobiol B 28(3): 213–218. Mik, E. G. (2013). “Special article: measuring mitochondrial oxygen tension: from basic principles to application in humans.” Anesth Analg 117(4): 834–846.

Measurement of Oxygen Metabolism In Vivo

Mik, E. G., C. Donkersloot, N. J. Raat and C. Ince (2002). “Excitation pulse deconvolution in luminescence lifetime analysis for oxygen measurements in vivo.” Photochem Photobiol 76(1): 12–21. Mik, E. G., C. Ince, O. Eerbeek, A. Heinen, J. Stap, B. Hooibrink, C. A. Schumacher, G. M. Balestra, T. Johannes, J. F. Beek, A. F. Nieuwenhuis, P. van Horssen, J. A. Spaan and C. J. Zuurbier (2009). “Mitochondrial oxygen tension within the heart.” J Mol Cell Cardiol 46(6): 943–951. Mik, E. G., T. Johannes, C. J. Zuurbier, A. Heinen, J. H. Houben‐Weerts, G. M. Balestra, J. Stap, J. F. Beek and C. Ince (2008). “In vivo mitochondrial oxygen tension measured by a delayed fluorescence lifetime technique.” Biophys J 95(8): 3977–3990. Moreno‐Sanchez, R., C. Bravo, C. Vasquez, G. Ayala, L. H. Silveira and M. Martinez‐Lavin (1999). “Inhibition and uncoupling of oxidative phosphorylation by nonsteroidal anti‐inflammatory drugs: study in mitochondria, submitochondrial particles, cells, and whole heart.” Biochem Pharmacol 57(7): 743–752. Nadanaciva, S., J. A. Dykens, A. Bernal, R. A. Capaldi, and Y. Will (2007) Mitochondrial impairment by PPAR agonists and statins identified via immunocaptured OXPHOS complex activities and respiration. Toxicol Appl Pharmacol 223: 277–287. Ota, S., K. Horigome, T. Ishii, M. Nakai, K. Hayashi, T. Kawamura, A. Kishino, M. Taiji and T. Kimura (2009). “Metformin suppresses glucose‐6‐phosphatase expression by a complex I inhibition and AMPK activation‐independent mechanism.” Biochem Biophys Res Commun 388(2): 311–316. Owen, M. R., E. Doran and A. P. Halestrap (2000). “Evidence that metformin exerts its anti‐diabetic effects through inhibition of complex 1 of the mitochondrial respiratory chain.” Biochem J 348(Pt 3): 607–614. Paiva, H., K. M. Thelen, R. Van Coster, J. Smet, B. De Paepe, K. M. Mattila, J. Laakso, T. Lehtimaki, K. von Bergmann, D. Lutjohann and R. Laaksonen (2005). “High‐dose statins and skeletal muscle metabolism in humans: a randomized, controlled trial.” Clin Pharmacol Ther 78(1): 60–68. Panov, A. V., C. A. Gutekunst, B. R. Leavitt, M. R. Hayden, J. R. Burke, W. J. Strittmatter and J. T. Greenamyre (2002).

“Early mitochondrial calcium defects in Huntington’s disease are a direct effect of polyglutamines.” Nat Neurosci 5(8): 731–736. Perelman, A., C. Wachtel, M. Cohen, S. Haupt, H. Shapiro and A. Tzur (2012). “JC‐1: alternative excitation wavelengths facilitate mitochondrial membrane potential cytometry.” Cell Death Dis 3: e430. Poulson, R. (1976). “The enzymic conversion of protoporphyrinogen IX to protoporphyrin IX in mammalian mitochondria.” J Biol Chem 251(12): 3730–3733. Radda, G. K., P. J. Bore and B. Rajagopalan (1984). “Clinical aspects on 31P NMR spectroscopy.” Br Med Bull 40(2): 155–159. Sandby‐Moller, J., T. Poulsen and H. C. Wulf (2003). “Epidermal thickness at different body sites: relationship to age, gender, pigmentation, blood content, skin type and smoking habits.” Acta Derm Venereol 83(6): 410–413. Schirris, T. J., G. H. Renkema, T. Ritschel, N. C. Voermans, A. Bilos, B. G. van Engelen, U. Brandt, W. J. Koopman, J. D. Beyrath, R. J. Rodenburg, P. H. Willems, J. A. Smeitink and F. G. Russel (2015). “Statin‐induced myopathy is associated with mitochondrial complex III inhibition.” Cell Metab 22(3): 399–407. Smith, P. F., R. S. Eydelloth, S. J. Grossman, R. J. Stubbs, M. S. Schwartz, J. I. Germershausen, K. P. Vyas, P. H. Kari and J. S. MacDonald (1991). “HMG‐CoA reductase inhibitor‐ induced myopathy in the rat: cyclosporine A interaction and mechanism studies.” J Pharmacol Exp Ther 257(3): 1225–1235. Wallace, D. C., G. Singh, M. T. Lott, J. A. Hodge, T. G. Schurr, A. M. Lezza, L. J. Elsas, 2nd and E. K. Nikoskelainen (1988). “Mitochondrial DNA mutation associated with Leber’s hereditary optic neuropathy.” Science 242(4884): 1427–1430. Wu, J. S., C. Buettner, H. Smithline, L. H. Ngo and R. L. Greenman (2011). “Evaluation of skeletal muscle during calf exercise by 31‐phosphorus magnetic resonance spectroscopy in patients on statin medications.” Muscle Nerve 43(1): 76–81. You, B. R. and W. H. Park (2010). “The effects of antimycin A on endothelial cells in cell death, reactive oxygen species and GSH levels.” Toxicol In Vitro 24(4): 1111–1118.

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21 Detection of Mitochondrial Toxicity Using Zebrafish Sherine S. L. Chan1,2 and Tucker Williamson1 1 2

Department of Drug Discovery and Biomedical Sciences, Medical University of South Carolina, Charleston, SC, USA Neuroene Therapeutics, Mt. Pleasant, SC, USA

CHAPTER MENU 21.1 21.2 21.3 21.4 21.5

21.1

Introduction, 323 Genetics and Manipulation of Zebrafish for Toxicological Studies, 324 Zebrafish Physiology, 325 Mitochondrial Biology and Methods, 333 Conclusions and Future Directions, 338 References, 338

Introduction

Zebrafish (Danio rerio) are ideal for toxicology and drug discovery studies, as they are small, fecund, and rapidly developing animals. This vertebrate model organism nicely fills the gap between traditional toxicological studies using cell culture and those that use in vivo rodent models. The zebrafish provide an inexpensive means to rapidly test the effects of drugs or chemicals on multiple animals like cells in a dish while gaining critical in vivo data, which could in later studies be used to evaluate whether to proceed with in vivo testing in the more expensive rodent system. Good concordance between complementary cell, mammalian, and zebrafish models has been reported; for example, for nonsteroidal anti‐inflammatory drugs (NSAIDs), good concordance across the NSAID chemical classes was found for multiple toxicity endpoints in isolated mitochondria, rat hepatocytes, and zebrafish (Nadanaciva et  al. 2013). Zebrafish are used to determine adverse outcome pathways for chemical risk assessment (Volz et  al. 2011; Villeneuve et al. 2014) and have been used for analyzing the effects of the ToxCast chemicals (list of chemicals of most interest to the US EPA, which include industrial and consumer products) on developmental toxicity

(Judson et  al. 2010; Padilla et  al. 2012; Truong et  al. 2014). The effects of these chemicals on mitochondrial function are another recent important endpoint (Attene‐Ramos et al. 2013). Researchers such as Dr Robert Tanguay and colleagues have also paved the way for high‐throughput chemical screening, by developing new methods for measuring multiple in vivo endpoints in zebrafish, simultaneously (Truong et  al. 2014). Others, such as Dr Leonard Zon, have used zebrafish for in vivo drug discovery and development. Dr Zon now has two novel therapeutics originally tested with zebrafish in clinical trials of patients with leukemia and melanoma (Zon and Peterson 2005; Bowman and Zon 2010; Santoriello and Zon 2012; Ablain and Zon 2013). Zebrafish not only allows for high‐throughput in vivo screening of chemical agents but also for in‐depth analyses of their mechanisms of action (Rihel et al. 2010). Transgenerational studies can also be performed, as zebrafish remain small up to adulthood and are relatively inexpensive to maintain over their lifespan (Baker et al. 2014a). They are easy to breed, and breeding pairs are able to produce hundreds of offspring up to once per week. Embryos are transparent, allowing researchers to monitor the development of  organs with ease. Zebrafish are readily genetically

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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manipulated through new gene editing mechanisms, and imaging studies are aided by comprehensive transgenic methods. Many zebrafish lines are available within the zebrafish community and in resource centers such as the  Zebrafish International Resource Center (ZFIN) in Oregon (Westerfield 2000), the European Zebrafish Resource Center (Geisler et al. 2016), and the National BioResource Project Zebrafish in Japan (Okamoto and Ishioka 2010). The resulting embryos rapidly develop to free‐swimming larvae in just 5 days and can be used like  cells in culture in multi‐well plates. Zebrafish possess the requisite and genotypic and morphological traits to model human diseases. Although zebrafish are lower‐ order vertebrates, both zebrafish and rodents have approximately 82–84% of same genes known to be associated with human disease (Schriml et  al. 2003; Howe et al. 2013). For mitochondrial toxicology, zebrafish are a particularly tractable model, as zebrafish, like humans and rodents, have the same‐sized mitochondrial genome (mtDNA), mtDNA gene order and genes required for oxidative phosphorylation (OXPHOS), and mtDNA replication machinery and homologues of many mitochondrial genes (Broughton et  al. 2001; Artuso et  al. 2012). They can develop the same disease phenotypes that afflict humans with mitochondrial dysfunction, such as cardiovascular and neurological disorders (Steele et  al. 2014). Many cellular‐based mitochondrial assays have been translated to zebrafish, because they are small enough to be amenable to similar high‐throughput methodologies to assay mitochondrial health, such as respiration measurements (Stackley et  al. 2011; Jayasundara et al. 2015; Rahn et al. 2015). In this chapter, we outline the advantages of the zebrafish for mitochondrial toxicology studies and the tools, models, and methods that have been developed to study mitochondrial toxicology in zebrafish, as well as what has been learned from these studies.

21.2 Genetics and Manipulation of Zebrafish for Toxicological Studies The use of zebrafish as a model for genetic studies stems from the work by Dr George Streisinger in the late 1960s to early 1970s (Grunwald and Eisen 2002). His pioneering work that allowed for the production of clonal lines of homozygous zebrafish that was later continued by several of his students spawned systematic large‐scale screens for embryonic lethal mutations using forward genetic methods (Grunwald and Eisen 2002). These studies paved the way for early understanding of the genetic landscape of zebrafish. In 2001, the Wellcome Trust Sanger Institute began the zebrafish genome sequencing project, which

generated several genome assemblies of the Tuebingen strain, one of the widely used wild‐type (WT) zebrafish strains (Howe et  al. 2013). In 2017, the ZFIN took responsibility for updating and maintenance of these assemblies (http://www.sanger.ac.uk/science/data/ zebrafish‐genome‐project). As a result, by comparing the zebrafish and human reference genomes, approximately 70% of human genes have at least one clear zebrafish orthologue, and of the 3176 genes bearing morbidity descriptions listed in the Online Mendelian Inheritance in Man database, 2601 (82%) of human morbid genes have a zebrafish orthologue (Howe et  al. 2013). Additionally, Gunnarsson et al. determined that zebrafish possessed orthologues for 86% of the 1318 human drug targets surveyed (Gunnarsson et al. 2008). Altogether, this high degree of similarity reinforces the importance of zebrafish in understanding how our genes work, to model human disease, and ultimately, to improve human health. One consideration when using zebrafish in genetic‐based studies is that their genome was duplicated with a subsequent reduction at several loci (Howe et al. 2013). While duplication can add some complexity to analysis, it also provides an opportunity since redundancy can evolve into subfunctionalization or neofunctionalization, leading to tissue‐specific control for some genes. For example, Venkatachalam et al. (2012) examined induction of fatty acid‐binding protein genes by clofibrate (a lipid‐lowering agent that can also cause mitochondrial toxicity (Qu et  al. 2001)) and found a differential induction in several major tissues by different duplications of the genes. It appeared that there were tissue‐specific mechanisms in place that can limit induction of these genes by clofibrate. Discoveries such as this one can be leveraged for experiments in zebrafish to inform of tissue‐specific disease states in humans. Next‐generation sequencing has further refined these initial genomic discoveries, enabling novel discoveries in understanding development and physiology that can be applied to human disease research (Qian et al. 2014). Armed with this knowledge and advanced molecular techniques, researchers are able to produce specific mutations in genes with subsequent screening for phenotypes (reverse genetics), yielding extensive models for human diseases. Investigations of the effects of nuclear‐ encoded mitochondrial genes have been performed using many of these techniques (Steele et  al. 2014). Initially, TILLING was used to generate loss‐of‐function mutations (Moens et al. 2008), though further technological advancements enabled researchers to use zinc‐ finger nucleases (ZFNs) and morpholinos to knockout and knockdown genes, respectively. ZFNs can be used to make targeted genetic mutations and germline

Detection of Mitochondrial Toxicity Using Zebrafish

transmissions at a rate faster than TILLING but are limited by expense and off‐target effects (Foley et al. 2009). Morpholinos can be used at a small scale and are a relatively inexpensive way to block specific molecular elements. They also require very little up‐front predictive information but are limited by dilution over time (usefulness is ~4–5 days’ post‐fertilization (dpf )) and may require several controls and validation experiments due to potential off‐target effects (Eisen and Smith 2008; Bill et al. 2009). Newer gene editing methods have been developed that can and are being used in zebrafish. Gene editing methods utilizing transcription activator‐ like effector nucleases (TALENs) allow for targeted genetic mutation with germline transmission that is faster than TILLING, has few off‐target effects, is cheaper than ZFNs, can in combination with oligonucleotides and homologous recombination be used for  knock‐in mutations, and can be easily customized (Hwang et al. 2013). Their major limitation is that design and generation of TALENs as in‐house generation can be laborious (Zu et al. 2013). The newest genetic method to find use in zebrafish uses engineered clustered regularly interspaced short palindromic repeats (CRISPR)/ Cas9 technology, which adapts a process from bacteria to efficiently mutate specific sites and loci in zebrafish (Hwang et al. 2013). This method is somewhat easier for generating edited mutants than TALEN technology and is less expensive. Off‐target effects can occur with this model but can be minimized (Hwang et al. 2013; Shah et al. 2015). CRISPR/Cas9 has been optimized for rapid genetic screening of new genes involved in biological processes in zebrafish; in a proof‐of‐concept study, two new electrical synapse genes were found using a combination of genetic and phenotypic screening (Shah et al. 2015). One advantage of using zebrafish is that embryos are amenable to quick transplantation experiments, as the location of the cells within the blastula and gastrula stage embryos have been fate‐mapped (Kimmel et  al. 1990, 1995). Transplantation of cells that are, for example, heart‐fated between different embryos can allow one to determine the tissue‐specific effects of a gene of interest, in a background of interest (Stainier et al. 1993). Transgenesis is another common genetic method for zebrafish studies, where a DNA construct is introduced into the genome of the organism (Felker and Mosimann 2016). Stable transmission of the transgene occurs when this DNA is integrated into germ cells, such that subsequent generations also inherit this transgene. For example, transgenesis using Tol2 and Cre/Lox methods and fluorescent reporter transgenes can be used to generate zebrafish lines, enabling mechanistic studies to determine the role of the gene of interest at different developmental time points and the role within a particular organelle, cell, and the organism as a whole.

21.3

Zebrafish Physiology

Zebrafish require an aquatic environment, and thus do not need lungs, but instead require a swim bladder and gills. As such, comparative studies for lung tissue are not advised; however, determining mitochondrial toxicity due to airborne compounds is reproducible in fish as these toxicants (e.g., cigarette smoke) can be bubbled into the water and will cause the same toxic effect in similar tissue types (Hammer et al. 2011; Ellis et al. 2014; Folkesson et  al. 2016). Furthermore, because of its aquatic environs (which may have as low as 1/30th of the oxygen found in air), zebrafish is able to tolerate much greater levels of hypoxia than mammals (Rees et al. 2001; Puente et al. 2014). This particular trait has been used to great advantage for mechanistic studies regarding organ development in hypoxic environments, such as the fetal heart (Puente et al. 2014). Many tissues in the body are sensitive to oxygen levels and energy deficits and thus mitochondrial dysfunction. The brain, for example, consumes many times more oxygen than would be expected for the proportion of the body that it represents (Wallace 2013). We will thus expand on the organ systems that are most susceptible to mitochondrial dysfunction. We will also consider the mitochondrial factors associated with tissue regeneration, an unusual trait of the zebrafish. 21.3.1

Neuromuscular System

Neurotoxicity, in particular, is where the zebrafish model shines. As zebrafish embryos are transparent over the first few days of development, and because of the ease of transgenesis and microinjecting various constructs into the 1–4‐cell stage embryo, fluorescent proteins targeted to different cell types, such as those of the nervous system, can be used to visualize the effects of toxicants on development in real time in vivo (see Section  21.4 and Figure 21.1). The zebrafish brain has similar regions to the mammalian brain, and for all vertebrates, axons projecting from the habenula relay thalamic and telencephalic inputs to the ventral brain (Butler and Hodos 1996). When the animals become larvae, they start to move, hunt, and feed. From this stage onward, researchers can now monitor the locomotor activity and behavior of these fish, which is important for monitoring neurotoxicity (Irons et  al. 2010). Many pollutants commonly found in air are also water soluble as well as those found in aquatic environments. In zebrafish, embryonic DDT exposure enhanced later life susceptibility to seizures due to an exposure to domoic acid, a toxic compound produced by diatoms that impairs mitochondrial function (Tiedeken and Ramsdell 2009; Hiolski et  al. 2014). Many antibiotics also affect mitochondria, due to the evolution of the mitochondrion from bacteria.

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(a)

(b)

(c)

(d) 200

25 20

150 Branch #

Primary axon length (μm)

326

100 * 50

0

15

*

10 5 0

Figure 21.1 Motor neuron abnormalities are observed in Peo1 (mtDNA helicase) knockdown (KD) embryos. (a) Diagram of zebrafish embryo with red box indicating the approximate position of (b and c). Projections of 150 µm two‐photon stacks of control (b) and Peo1 knockdown (c) embryos at 53 hpf. Peo1 KD embryos have altered caudal primary (CaP) motor neuron axonal branch patterns that fail to extend. Growth of CaP motor axon arbors is significantly inhibited in Peo1 KD embryos: total axon branch lengths were decreased as were the length of the primary axon, average sidebranch lengths, and branch numbers. * Indicates significant difference (p < 0.05) from control levels. (See insert for color representation of the figure.)

Detection of Mitochondrial Toxicity Using Zebrafish

Aminoglycoside antibiotics (such as neomycin and gentamicin) are particularly toxic for people with underlying mitochondrial dysfunction (such as mutations in rRNA genes in mtDNA). Aminoglycosides preferentially kill inner ear sensory hair cells in mammals and in the hair cells of the lateral line organs of larval and adult zebrafish (Huth et  al. 2011; Esterberg et  al. 2016). In zebrafish studies, the mitochondrial response to aminoglycoside exposure was found to be quick—within 15 min mitochondrial swelling was detected, leading to hair cell damage and death (Owens et  al. 2007). Because cells close to the surface of the fish were of interest, mitochondrial dyes (such as 2‐(4‐(dimethylamino)styryl)‐N‐ ethylpyridinium iodide (DASPEI)) along with cell vital dyes (such as the vital DNA dye YO‐PRO‐1) could be used to visualize mitochondrial structure, which were followed up with ultrastructural methods such as transmission electron microscopy. The natural movement of zebrafish (swimming) also provides an excellent means of tracking neuromuscular toxicity. Toxicants that target mitochondria (both in the nerves and muscles that they are connected to) may disrupt bioenergetics that impact the ability of the zebrafish to move (Padilla et al. 2011; Faria et al. 2015; Dubinska‐ Magiera et al. 2016). A startle response to touch develops around 1 dpf (Ribera and Nusslein‐Volhard 1998) and can be used to identify neuromuscular defects such as those associated with Charcot–Marie–Tooth type 2A neuropathy. Loss of MFN2 function, a mitochondrial protein involved with fusion of the outer mitochondrial membrane, results in several morphological defects with an impairment to motility. Vetori et al. used zebrafish to model the disease and used the startle response as a measure of severity of disease (Vettori et  al. 2011). Interestingly, organophosphates, which include many insecticides, herbicides, and chemical warfare agents, have been linked to disrupting mitochondrial dynamics and impairment of motor proteins (Terry 2012). Simple tracking of movement using high speed cameras and software (e.g., Noldus Information Technology and ViewPoint Behavior Technology develop equipment and software for these types of zebrafish locomotor and behavioral studies) allows for the measurement of differential movement by zebrafish under different conditions. Researchers can use multi‐well plates to track the movement over time under different conditions (varying light conditions, different chemicals, etc.) as early as 3 dpf (Padilla et  al. 2011). In a study by Wang et  al., zebrafish were exposed to bisphenol A (BPA), a known endocrine‐disrupting chemical that also targets mitochondria (Agarwal et al. 2016), altering their movement (both response and speed) in a concentration‐dependent manner (Wang et al. 2013). The use of larger tanks for larval, juvenile, and adult fish can also be used to track

diving behavior. The laboratories of Drs Edward Levin and Elwood Linney routinely use assays to measure diving ability, which reflect predatory avoidance behaviors (Levin et al. 2011; Roy et al. 2012), and three‐chambered learning assays (Levin 2011) in their research that involves the influence of chemical exposures to development of the nervous system and subsequent behaviors. Researchers can also challenge the zebrafish to exercising and recovery using swim tunnels. These tunnels allow for the monitoring of not only swimming behavior but  also physiological measurements, such as oxygen consumption. Several studies (e.g., Masse et  al. 2013; Massarsky et  al. 2015) have combined the use of these swim tunnels with chemical exposure to assess their effect on zebrafish. The type of movement (quick burst vs. continuous) would also help to define the type of muscle fibers being targeted. The quick burst movement is associated with “fast twitch” (white muscle), while continuous swimming movement is associated with “slow twitch” (red muscle). Different physiological properties of embryonic red and white muscles (Buss and Drapeau 2000) could be differentially affected by exposure to toxicants that target mitochondria, thus affecting their escape response or their continuous swimming. The correct organization of myotomes can also be easily visualized using a light microscope and two polarized light filters for birefringence. Shahid et  al. used birefringence in conjunction with a transgenic green fluorescent protein (GFP) reporter to assess muscle fiber arrangement in response to known muscle toxicants that inhibit acetylcholinesterase (Shahid et  al. 2016). They found that there was reduced muscle integrity with increased hspb11 expression with a dose‐dependent chemical exposure. For ocular toxicity, photomotor response can be measured (Kokel and Peterson 2011), as well as optokinetic response, where animals from the 3 dpf stage up to adults can be immobilized in agar when they are young and small and with physical restraints when they are older (Mueller and Neuhauss 2010; Zou et  al. 2010). A  high‐throughput, behavior‐based approach to discover neuroactive small molecule discovery has been developed using the zebrafish model (Kokel et al. 2010). In this case, researchers used these methods to rapidly identify neuroactive small molecules that could be used as drugs. Conversely, these assays can also be used to determine the neurotoxic effects of chemicals (Olivares et al. 2016). Neuronal activity can be noninvasively measured in an intact living zebrafish through the use of transgenic calcium sensors (Lin and Schnitzer 2016). The use of cell‐type specific promotors allows for the identification and tracking of activity of individual neurons or a population of neurons that act within a tissue. The calcium

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sensors used in zebrafish generally monitor flux of calcium ions that occur in response to depolarizing signals from upstream neurons into voltage‐gated calcium channels and release from intracellular stores. Most often the GCaMP family of proteins is used, which are genetically encoded calcium indicators created from a circularly permuted GFP bound to calmodulin. When Ca2+ binds, a structural shift occurs, resulting in bright fluorescence, which can be imaged and recorded using confocal as well as conventional microscopy (Muto et al. 2011). These techniques can then be used to understand the mechanisms of action of toxicants and to monitor their adverse effects on neuronal activity, such as reported by Esterberg et al. (2014). Healthy mitochondria are important for tissues that have large energy requirements for their function, such as the nervous system. In general, disruption of mitochondrial homeostasis results in impaired OXPHOS. The two major products of OXPHOS—energy in the form of adenosine triphosphate (ATP) and reactive oxygen species (ROS)—are altered, resulting in decreased cellular energy and increased oxidative stress, respectively. Oxidative stress resulting from high cellular ROS is strongly linked to many forms of neurodegeneration, including Parkinson’s disease (Coyle and Puttfarcken 1993; Beal 1995; Schulz et al. 2000; Emerit et al. 2004; Lin and Beal 2006) and epilepsy (Patel 2002), as well as specific mitochondrial diseases (Hayashi and Cortopassi 2015). Alterations in ROS levels are easily visualized in real time in zebrafish by the use of a CM‐H2DCFDA (see Section  21.4.2). Many toxicants exacerbate ROS production (Mugoni et al. 2014); however exposure of zebrafish of some toxicants, such as 2,4‐dinitrophenol (DNP), can decrease OXPHOS and ROS production (Bestman et al. 2015). DNP is a mitochondrial OXPHOS uncoupler that was originally used as a diet agent and is making a resurgence as an illicit drug that can be purchased online. Furthermore, DNP is 89 on the Agency of Toxic Substances and Disease Registry (ATSDR) priority list of hazardous substances. As ROS are important cell signaling molecules needed for development, it was not surprising to observe developmental toxicity, such as the development of the motor neurons (Bestman et al. 2015). Mounting evidence points to mitochondrial dysfunction as a major underlying cause of many neurodegenerative diseases that can be caused by genetic defects in nuclear‐ and mitochondrial‐encoded proteins required for mitochondrial function, as well as exposures to chemicals that target mitochondria (Schapira 2008; Schapira 2011; Exner et al. 2012; Federico et al. 2012; Yan et  al. 2013; Burte et  al. 2015). This suggests that exposures to mitochondria‐targeted drugs and toxicants are important for modifying disease. For example, most of

the gene loci for Parkinson’s disease encode mitochondrial proteins (e.g., PINK1, Parkin, POLG, LRRK2, DJ1) (Kitada et  al. 1998; Lücking et  al. 2000; Shimura et  al. 2001; Valente et al. 2004; Morais et al. 2009; Schapira and Tolosa  2010), and many mitochondrial toxicants (such as  rotenone, paraquat, and 1‐methyl‐4‐phenyl‐1,2,3, 6‐tetrahydropyridine (MPTP)) are associated with Parkinson’s (Cookson 2005; Jackson‐Lewis and Przedborski 2007; Tanner et al. 2011). Dr Marc Ekker’s group has developed some excellent tools for identifying neurotoxicity in zebrafish models of Parkinson’s disease, such as the MPTP mitochondrial toxicant model (Xi et al. 2011). MPTP is a prodrug of MPP+, which is a man‐made neurotoxin that is transported to the dopaminergic (DA) neurons of the substantia nigra and inhibits complex I of the electron transport chain, causing Parkinson’s disease (Goldman 2014). Bretaud et al. also exposed larval and adult zebrafish to MPTP, as well as rotenone and paraquat, two more inhibitors of complex I that can invoke Parkinson’s disease to reveal developmental, behavioral, and DA sensitivity in larvae and decreased locomotor activity in adults (Bretaud et al. 2004). Dr Ekker’s group also developed stable zebrafish lines containing fluorescent proteins targeted to mitochondria of distinct neuronal subtypes like the DA neurons (see Section  21.4) and that have been used to identify mitochondrial toxicity (Noble et  al. 2012). Genetic models of Parkinson’s disease such as the DJ‐1 knockdown zebrafish were also utilized by Bretaud et al. to understand the effects of toxins on a Parkinson’s background and the effects of DJ‐1 in DA toxicity (Bretaud et al. 2007). Stable genetic models of Parkinson’s disease in zebrafish include the knockout and dominant   negative Polg (mtDNA polymerase) mutant models developed by our group through TALEN gene editing (Rahn et al. 2015). Polg is a locus for Parkinson’s disease and shows rapid mtDNA depletion from 7 dpf. MtDNA is a new verified marker of human Parkinson’s disease (Gui et  al. 2015; Pyle et  al. 2016). Altogether, these studies advocate zebrafish as a valuable model for dissecting the molecular mechanisms underlying the gene–environment interactions of Parkinson’s disease. 21.3.2

Cardiovascular System

Since the heart is a highly energetic organ, mitochondria can constitute as much as 40% of the total volume of cardiomyocytes (Knaapen et  al. 1997). Thus, the biomass and activity of mitochondria play an important role in proper heart development and repair of cardiovascular tissues, and exposure to mitochondrial drugs and toxicants can result in failure of mitochondria. The cardiovascular system in zebrafish features a two‐chambered heart consisting of single atrium and a single ventricle

Detection of Mitochondrial Toxicity Using Zebrafish

(Stainier et al. 1993). The atrium is fed by the sinus venosus and the bulbus arteriosus is the outflow tract fed from the ventricle that leads to the rest of the body. While zebrafish have a two‐chambered heart, the genes and processes that drive the development of the tissues that constitute the heart are well conserved with those that form the human four‐chambered heart (Stainier et al. 1993). The zebrafish heart can then act as a simplified model of cardiovascular processes that bear an effect on the human population. Additionally, the transparent nature of zebrafish embryos and the early completion of heart development within 72 hours’ post‐fertilization (hpf ) enables measurements of developmental cardiovascular endpoints (Bakkers 2011). Zebrafish are also known for their ability to regenerate several tissues, including the heart, which has many implications for cardiovascular disease research and cell regeneration studies (Poss 2010). The health of mitochondria plays an  important role in their ability to regenerate; thus toxicants that disrupt mitochondria will likely impact regeneration (Chung et  al. 2007; Hom et  al. 2011). Therefore, benefits of using zebrafish to study the impact of toxicants on mitochondria of the heart can be divided into two time periods with differing assays: early heart development and adult heart regeneration. The use of the zebrafish for human cardiovascular research has been well discussed and reviewed by Drs Bakkers (Bakkers 2011) and Stainier (Stainier et al. 1993; Stainier 2001; Liu and Stainier 2012). In brief, the genetic tools available in the conserved zebrafish model present an opportunity for controlled manipulation and understanding of cardiovascular processes in a highly visible and robust model. These genetic techniques (discussed earlier in this and other chapters) have allowed for the direct control of genes that drive the major processes that are involved in the development of the heart and have produced distinct and highly reproducible phenotypes (Miura and Yelon 2011). For example, disruption of gata5, a gene that produces the transcription factor of the same name that is required for the correct development of the heart, will lead to cardia bifida and the reduction of ventricular tissues (Reiter et  al. 1999). Thus, toxicants that disrupt mitochondria and directly interfere with important cardiac genes will produce a distinct, detectable phenotype that can be measured. An example of direct impact on mitochondrial function comes from Pinho et al. (2013). In their study, respiratory complex inhibitors were screened for their effects on heart development through visual screening of heart characteristics (e.g., edema, bleeding, looping) and their subsequent rescue using multiple quinones. Specifically, the quinones rescue through antioxidant mechanisms as well as electron transfer mechanisms to feed complex III for the production of ATP. This allows delay of heart

defects from exposure to complex I and II inhibitors. The authors reveal that these quinones do not appear to protect against complex III inhibition, as a large increase of ROS was observed. Instead, a link between the addition of these quinones and an increase in NAD(P)H– quinone reductase (NQO1) activity may better explain the cardioprotection observed. Pinho et al. also suggest that a reduced reliance on complex I/II in young zebrafish may explain the lack of disease phenotypes associated with exposures to inhibitors of those complexes and should be considered when interpreting data (Pinho et al. 2013). The ability to use molecular techniques to directly tag mitochondria in particular tissues using specific promotors, such as cmcl2 (Zhang and Gong 2013), for example, can enable real‐time tracking of toxicant effects on the mitochondria in the heart (Figure  21.2). Use of dynamic proteins such as kaede (Bergamin et al. 2016) to visualize changes at different time periods (based on light exposure) can be used in the heart to track mitochondrial dynamics in response to exposures to the suspected toxicants. Quality and quantity of mitochondrial networks can be resolved through microscopy in  the cardiovascular tissues using these techniques. Additionally, early heart tubes and early hearts can be removed using microdissection and mechanical separation from the developing fish for more direct measurements of the impacts of toxicants on the mitochondria and the heart (Lombardo et al. 2015). Granted the material needed to run protein level analysis is difficult to generate at this time scale due to the small size, however large clutch sizes make this possible. The large number of embryos coupled with the transparent nature of their development makes for excellent high‐throughput screening of toxicological effects of mitochondria in the development of the heart (Padilla et  al. 2012; Truong et al. 2014). Researchers can also take advantage of transgenic lines that tag fli1, an ETS transcription factor that is involved with developing vasculature, in zebrafish. Zebrafish have a very distinct patterning for angiogenesis during development with the dorsal longitudinal anastomotic vessel branching ventrally and the aorta branching dorsally until these branches meet to form intersegmental vessels (Childs et al. 2002). In a study conducted by Delov et al. (2014), the intersegmental blood vessel was measured using the fli1 EGF when the fish were exposed to increasing doses of chemicals. One of the chemicals in this study was triclosan (5‐chloro‐2′(2,4‐dichlorophenoxy)phenol), a common antibacterial that disrupts fatty acid biosynthesis in bacteria and is a mitochondrial toxicant causing the uncoupling of respiration (Weatherly et  al. 2016). Triclosan exposure to zebrafish embryos caused vascular defects (Delov et  al. 2014). Like Delov et  al., we also

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(a)

(b)

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Figure 21.2 Mitochondrial GFP targeted to cardiac tissue in zebrafish. The plasmid construct used contains the cmlc2 promoter, a mitochondrial leader sequence, and green fluorescent protein (GFP) sequence, flanked by Tol2 sites. Plasmid and Tol2 mRNA are injected into embryos at the 2‐cell stage. (a) Bright‐field image of a 72 hpf zebrafish at 100× magnification. (b) Fluorescent mitochondria in the heart of the individual from A. Viewed using FITC filter on an inverted Zeiss microscope (excitation, 450–490 nm; emission, 515–545 nm). (c) 72 hpf WT zebrafish injected with the plasmid construct mentioned earlier. Zebrafish were fixed in 4% paraformaldehyde for 5 h at room temperature and washed three times for 10 min in PBS before mounting in agarose. This confocal image was taken on the Olympus FV1200 MPE intravital microscope at 30× magnification and 1.5 µm slice interval. Presented as a heat map of mitochondrial density in a 3D projection. (See insert for color representation of the figure.)

observed vascular defects in zebrafish when exposed with the mitochondrial uncoupler DNP (Figure  21.3). Other common deformities found in studies of chemicals and their effects on zebrafish vascular development include deflection that leads to no connections or looping back, reduction in vessel number, and reduction in size of these branching vessels (Chimote et  al. 2014; Delov et al. 2014; Tal et al. 2016).

21.3.3

Liver

One of the primary targets for mitochondrial toxicants and toxicants in general is the liver. As a primary location for bioactivation and eventual detoxification, it is exposed to a litany of compounds on a regular basis. The  importance of the liver for toxicant screens is reflected in several chapters of this volume. Its ability to

Detection of Mitochondrial Toxicity Using Zebrafish

(a)

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(f) 49 min time lapse

Control

(d)

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(g) 49 min time lapse

DNP

24 hpf

48 hpf

Figure 21.3 DNP exposure disrupts blood vessel development. In vivo 2‐photon stacks acquired through the trunks of 24 and 48 hpf fli1: eGFP zebrafish reveal the developing blood and lymph vessels. (a) Diagram of zebrafish embryo with red box indicating the approximate position of (b–e). At 24 hpf, both control (b) and DNP‐treated (d) zebrafish have dorsally growing intersomitic vessels (isv), but those of DNP‐treated fish end in fewer filopodial projections (arrows, (b, d)), indicating that DNP inhibits angiogenesis. At 48 hpf, the dorsal longitudinal anastomotic vessel (dlav) of control fish has a fully formed lumen able to pass blood cells; it remains constricted in the DNP‐treated fish (e) (arrowheads). Boxed regions in (c) and (e) are magnified and the time lapse frames reveal the filopodial projections (yellow arrowheads) on the growing tip of the developing branch of the parachordal chain in controls (f ), which is absent in the DNP‐treated animal (g). (See insert for color representation of the figure.)

deal with these toxins requires an extensive amount of energy and complex ROS signaling, which are linked to large numbers of mitochondria present (Sato 2007). The liver of the zebrafish is organized slightly differently from a mammalian liver, but all the cell types of the liver, except for Kupffer cells, have been found in zebrafish performing many of the same functions as mammalian liver as early as 3 dpf (Goessling and Sadler 2015). While Kupffer cells, the specialized macrophages in the mammalian liver, are not present in zebrafish, they

do have macrophages that form aggregates present in the liver (Holden et al. 2012). Equally important, researchers have developed transgenic zebrafish lines where each of these different cell types of the liver express specific fluorescent proteins that can be visualized in live embryos and larvae. Thus, the development of these cells can be easily assessed (Goessling and Sadler 2015), and with additional assays, such as bilirubin and alanine aminotransferase (ALT) activity assays, liver function can also be determined (Li et al. 2016). Gross observation of

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changes in color (darkening), texture (degradation), size, and yolk retention (yolk utilization is through the liver) can all be used as endpoints for liver toxicity in zebrafish (Hill et al. 2012). Zebrafish show strong potential as a model to in the study of drug‐induced liver injury (DILI), especially when used in conjunction with other complementary models. Nadanaciva et  al. (2013) assessed two in vitro models alongside an in vivo zebrafish model for the effects of different chemical classes of NSAIDs on the liver. The authors reported good concordance between the different models in assessing liver toxicity, noting that the use of zebrafish allowed for larger drug screens for differential phenotypes across organ systems through the addition of extra assays or endpoints. They also noted one limitation with the use of zebrafish for the study of NSAID‐related hepatic toxicity: certain phenotypes that are associated with liver toxicity can be masked by death of the organism at low concentrations. In the review by Vliegenthart et  al. (2014), the authors point out that while the amount of drug being added to water that the zebrafish inhabit is known, the exact amount of the compound that is taken up by the fish is variable. However, it is possible to directly inject compounds into the yolk sac or use mass spectrometry to measure levels of compound from blood or tissue samples. Disruption of lipid metabolism can lead to adverse effects in liver, and mitochondria play a large role in the transport of lipids. For example, BNIP3 (encoded by nip3a in zebrafish (Feng et al. 2011)) has been shown to play an important role in the regulation of mitochondrial dynamics, mitophagy, and lipid metabolism (Glick et al. 2012). This protein is located on the outer membrane of the mitochondria. Disruption of BNip3 altered lipid synthesis and mitochondrial mass. Despite an increase in mitochondrial mass, several mitochondrial parameters were impacted as shown by loss of membrane potential, abnormal mitochondrial structure, reduced oxygen consumption, and an increase in ROS. Interestingly, BNIP3 has been shown to be influenced by toxicants such as acute cyanide exposure (Zhang et al. 2011) or the heavy metal cadmium (Wang et al. 2014). While “liver toxicity” was not the primary focus of those papers, disruption of BNIP3 is expected to increase lipid accumulation in the liver. This disruption of lipid transport can be visualized using simple lipophilic dyes, such as oil red O, to image lipid droplets. An accumulation of these droplets would indicate dysfunction in the utilization of fatty acids (Kim  et  al. 2015). Different functional groups from the core of 4,4‐difluoro‐4‐bora‐3a,4a‐diaza‐s‐indacene (boron‐dipyrromethene (BODIPY)) fluorescent dyes can be used to measure function of the liver due to differential uptake and breakdown of lipids (Otis and Farber 2016). This method for observing lipid utilization and

trafficking within the liver is highly effective when viewed with confocal microscopy. Human mitochondrial diseases are complex and poorly understood, often resulting in misdiagnosis or a very‐late‐stage proper diagnosis. One of the mitochondrial disorders that results in liver disease is known as Alpers syndrome. This syndrome belongs to a group of mtDNA depletion disorders that are associated with mutations in POLG, the mtDNA polymerase (Nguyen et  al. 2006). While this childhood‐onset syndrome manifests with neurological developmental delay and seizures, it is often the hepatic failure that results in death (Narkewicz et al. 1991). As valproic acid is commonly prescribed for the treatment of epileptic seizures, this may include patients with as yet undiagnosed Alpers syndrome. Unfortunately for patients with POLG mutations and Alpers syndrome, valproic acid can cause fatal hepatotoxicity and should not be prescribed. Valproic acid has many cellular targets, including the inhibition of mitochondrial β‐oxidation (Caldeira da Silva et al. 2008). However, fatty acid oxidation was not found to be the cause of toxicity; instead liver regeneration was affected by valproic acid exposure in this human population (Stewart et al. 2010). 21.3.4

Reproductive System and Gender

Zebrafish are rather fecund: under ideal conditions females starting from 3 to 4 months of age can produce 200–300 oocytes per week (Chhetri et  al. 2014). The male fertilizes the oocytes released by females, and these fertilized eggs, embryos, are small in size, approximately 1 mm in diameter. This small size enables embryos and early larvae to be used in high‐throughput screens (Vogt et  al. 2009). Sperm and oocytes can be squeezed from adults for in vitro fertilization experiments. Furthermore, zebrafish sperm, but not oocytes, can be frozen down and stored in liquid nitrogen for the preservation of important lines (Draper et  al. 2004; Draper and Moens 2009). All zebrafish start to develop undifferentiated juvenile ovaries early in life until 30 days’ post‐hatching. Up to this point zebrafish are considered hermaphrodites. Past this period the juvenile ovary can mature into a proper ovary for females or transform into a testis for males (Liew and Orban 2014). As an addendum to this, gender was found to be flexible later in life, as females could transform into males by exposure to an aromatase inhibitor (Takatsu et  al. 2013). In this study, ovaries of the female zebrafish retracted to give way to testes‐like organs, which produced sperm that could be used to successfully fertilize eggs in vitro. BPA is an example of a well‐established endocrine‐disrupting compound affecting both male and female reproductive health. Zebrafish

Detection of Mitochondrial Toxicity Using Zebrafish

testes show degradation at low concentrations (100 µg/L) of BPA (Lora et al. 2016). These authors demonstrate the ease at which morphological changes can be assessed for toxicological studies. At even lower levels of BPA exposure (0.228 µg/L), zebrafish show a gender bias toward females at both the F1 and F2 generations with decreased sperm density and quality (Chen et al. 2015). Specifically, mitochondrial membrane potential in the sperm is decreased (Singh et  al. 2015). These environmentally relevant low concentrations also affect oocyte growth and maturation. Changes to chromatin structure through histone modifications and apoptotic signals in mature follicles when female zebrafish are exposed to 5 µg/L BPA constitute a detrimental effect on female reproduction (Santangeli et al. 2016). There is good homology of the known sex differentiation genes and pathways between mammals and zebrafish (Marshall Graves and Peichel 2010). However, in addition to the differences stated earlier, gender specification is not as well understood in zebrafish as it is in mammals. Primarily, sex determination in zebrafish appears to be genetic through allelic combinations of several loci (Tong et  al. 2010; Liew and Orban 2014). However, gender can be influenced by environmental factors, such as food consumption: zebrafish that grow faster are more likely to be female (Lawrence et al. 2008). Interestingly, dioxin (2,3,7,8‐tetrachlorodibenzo‐p‐ dioxin (TCDD)) is an aryl hydrocarbon receptor (AHR) agonist and an endocrine disruptor that can impact drug metabolism; exposure of zebrafish to dioxin can also lead to a greater female–male ratio, not just in the current generation but also in at least two later generations that had not been exposed (Baker et  al. 2014b). Zebrafish are also an excellent model for determining the effects of chemicals found in wastewater, such as contraceptives. Hua et  al. found that one such contraceptive agent, levonorgestrel, could significantly alter sex differentiation in zebrafish, with 100% males produced at environmentally relevant concentrations (Hua et  al. 2015). Oxygen levels (upon which mitochondrial OXPHOS is also dependent) can also sway gender ratios, as hypoxia was shown to increase the rate of male offspring in zebrafish (Shang et al. 2006). Pluripotency also appears to be associated with oxygen and bioenergetic status. In mice, undifferentiated embryonic stem cells have high glycolytic metabolism and low oxygen consumption, which are needed to maintain their proliferative capacity (Kondoh et  al. 2007; Facucho‐Oliveira and St John 2009). We also observed in zebrafish that glycolysis is higher in early embryogenesis (Stackley et al. 2011). Thus chemicals that affect oxygen and energetic status not only are likely to interfere with the ability of the embryo to develop and differentiate properly but may also affect the final gender ratios in each clutch.

21.3.5

Regeneration

One of the most interesting abilities of the zebrafish is its ability to regenerate many of its tissues, including the heart, nervous tissue, liver, and fins (Gemberling et  al. 2013). The regenerative abilities of the zebrafish have become an important area of interest especially for the  studies in tissue repair and cardiovascular disease. In particular, Dr Ken Poss’ research group has combined transgenic lines that allow of the visualization of specific cell types in heart with a cardiac resection technique that allows for the tracking of heart regeneration (Poss 2010; Kang et  al. 2016). Mitochondria produce much of the energy needed to complete repair processes, but they also play an important role in cell signaling required to initiate repair processes (Marin‐Garcia 2016). Our studies also show that zebrafish deficient in Polg (the only replicative DNA polymerase in vertebrate mitochondria essential for mtDNA replication and repair) mutant have severely decreased mtDNA copy number and surprisingly, an impaired ability to regenerate damage to their caudal fins (Rahn et al. 2015) (Figure 21.4). This suggests that chemicals that disrupt the ability of mitochondria to regulate mtDNA copy number (e.g., the antiviral nucleoside analogues used to treat HIV (Chan et  al. 2007)) could, in turn, limit the ability of zebrafish to regenerate. Furthermore, as shown in the liver section, patients with POLG mutations and Alpers syndrome are susceptible to valproic acid hepatotoxicity, which is associated with defects in liver regeneration. As our Polg mutant zebrafish shows defects in regeneration, this model could be used to test toxicity of current and new epilepsy drugs on Alpers syndrome (Rahn et al. 2014).

21.4 Mitochondrial Biology and Methods Zebrafish are an excellent model system for mitochondrial biology and diseases (Steele et  al. 2014). Because zebrafish embryos and early‐stage larvae are small and can fit easily into up to 384‐well plates (Zon and Peterson 2005), many mitochondrial assays can be translated from cell culture. These studies have the added advantage (over cell culture) of monitoring the mitochondrial marker of interest across the whole body. For example, how specific mitochondria‐targeted drugs (such as OXPHOS complex inhibitors) affect development and cardiovascular function has been carefully studied in the zebrafish (Pinho et al. 2013). In vivo studies such as these take into account the fact that within the organism there is communication and interaction between the different organ systems that is essential for understanding toxicity, particularly for mitochondrial toxicity where the

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WT

Polg double mutant

Figure 21.4 Zebrafish lacking functional mtDNA polymerase have regenerative defects. Compared with WT at 3 weeks and heterozygous mutants (not shown), zebrafish homozygous for the Polg polymerase mutation show defects in tail regeneration after amputation at 1 week old.

high‐energy‐requiring organs are generally more susceptible than organs that are less dependent on mitochondria (Wallace et al. 2010). 21.4.1

Energetics

As the mitochondrion’s most important function (arguably) is to produce energy for the cell through OXPHOS, a major marker for mitochondrial health is respiration. The traditional method for measuring respiration is via the Clark electrode (Schnellmann 1994; Mendelsohn (a)

et al. 2008). However, newer methods, such as those that use the Seahorse extracellular flux analyzer, enable measurements of respiration (oxygen consumption) in multi‐well plates (24‐ and 96‐well). We and others have developed new methods for utilizing this instrument to measure respiration in intact living zebrafish and larvae up to 10 dpf (Figure 21.5) (Stackley et al. 2011; Rahn et al. 2013), as well as in organs carefully dissected from larval and adult zebrafish (Jayasundara et al. 2015; Rahn et al. 2015). Additional use of inhibitors of the electron transport chain and the ATP synthase allows one to monitor

(b)

Figure 21.5 Zebrafish embryos and larvae up to 10 dpf can be assayed in the Seahorse Bioscience XF24 extracellular flux analyzer. (a) Cross section of a well within an XF24 plate. The embryo (bottom of well) is covered by an islet capture screen (crosses). The probe (gray) descends to form a microchamber with the plate and capture screen, and the consumption of oxygen by the embryo is measured through fluorophores on the probe head (the sensor) that monitor oxygen levels. Two of the four drug injection ports are shown next to the probe. (b) View from the top of a 10 dpf zebrafish embryo in an islet plate well prior to assay. The mesh shown is from the islet capture screen.

Detection of Mitochondrial Toxicity Using Zebrafish

how oxygen is being consumed within the mitochondria and from non‐mitochondrial sources. Furthermore, addition of a mitochondrial uncoupler such as carbonyl cyanide 4‐(trifluoromethoxy)phenylhydrazone (FCCP) will provide a measurement of the maximal respiratory capacity of the mitochondria within the zebrafish. When the basal oxygen consumption rate is subtracted from the maximal FCCP‐uncoupled oxygen consumption rate, this provides a measure of the mitochondrial spare respiratory capacity, which is an excellent marker of mitochondrial health and the ability of the mitochondria and the cell to respond to stressors. Another marker that is measured on this instrument is extracellular acidification, which in cells is a good marker for glycolysis (as lactic acid, the endpoint of glycolysis, is the major acid released from cells). In older animals, extracellular acidification may be a reasonable marker of glycolysis; however in embryos and larvae, we have found that media acidification in this case is reflective of carbonic acid production in the media due to hydration of CO2 generated from aerobic respiration rather than lactic acid extrusion (Stackley et al. 2011), which can be measured using a modification of the traditional lactate assay used for cells (Brandt et  al. 1980; Stackley et  al. 2011). Total ATP levels can also be measured in whole zebrafish as in cells (Rahn et al. 2015). The ability to measure respiration in a high‐throughput fashion has enabled researchers to determine how chemicals affect respiration in cells, and now zebrafish, to inhibit mitochondrial function (Stackley et  al. 2011; Gibert et  al. 2013; Rahn et al. 2013, 2015; Jayasundara et al. 2015; Massarsky et al. 2015; Felix et al. 2016; Jain et al. 2016). Conversely, this technique has also allowed researchers to identify chemical compounds that improve mitochondrial function (Beeson et al. 2010; Gohil et al. 2010; Rahn et al. 2014). 21.4.2

Reactive Oxygen Species

Disruption of mitochondrial homeostasis can result in impaired OXPHOS, leading to not only altered production ATP but also ROS, which is a major by‐product of OXPHOS. These ROS are superoxide radicals that can cause damage to nucleic acids, proteins, and lipids and can be further converted to hydroxyl radical, which is extremely reactive, as well as to less reactive but longer‐ lasting hydrogen peroxide (via superoxide dismutase). Thus measurements of ROS are important for understanding the impact of toxicants on mitochondrial and overall organismal health. Unfortunately, the zebrafish embryo is not amenable to many of the mitochondrial stains that have been developed for cells, such as MitoSOX, which is used to monitor mitochondrial superoxide production (Josey et al. 2013). This is because the zebrafish does not take up many of these dyes,

although superficial cells, such as the neuromasts, can easily take up some of these dyes (Esterberg et al. 2014). When we knock down Peo1, the mtDNA helicase needed for mtDNA replication, we observed an increase in ROS formation (Figure 21.6), which is in concordance with data in mice that showed that defective mtDNA replication can lead to oxidative stress (Lewis et al. 2007). Furthermore, exposures to a mitochondrial toxicant can give rise to increased ROS due to, for example, damage to the OXPHOS complexes such as complex I (Mugoni et  al. 2014). However, shutdown of OXPHOS due to exposures to mitochondrial uncouplers such as DNP can shut down ROS production, as shown in Bestman et al. (2015), where we used CM‐H2DCFDA, a fluorescein derivative that is non‐fluorescent until cleaved by intracellular esterases and then oxidized, to assess oxidation levels in living zebrafish embryos (Anichtchik et al. 2008; Walker et al. 2012). ROS are important second messengers required for developmental processes (Dennery 2007; Dumollard et  al. 2009; Crespo et  al. 2010; Gough  and Cotter 2011; Hom et  al. 2011). Thus, not surprisingly, we also observed a downstream impact on the developing DNP‐exposed embryo. Oxidative DNA lesions such as 8OHdG can also be measured in zebrafish (Puente et al. 2014), but lack specificity in the origin of these lesions. More specific ROS methods are now being used for zebrafish, such as HyPer, which is a genetically encoded fluorescent sensor that is able to detect intracellular hydrogen peroxide (Belousov et al. 2006; Ermakova et  al. 2014; Esterberg et  al. 2016). Newer methods that will allow for multiple ROS measurements are also being developed that will greatly aid in vivo mitochondrial toxicity testing. For example, Dr Christopher Chang’s group is developing new imaging probes that report on ROS as well as reactive sulfur and carbonyl species in living cells and animals (Lippert et al. 2011). These chemical tools will allow researchers to reveal in vivo the precise adverse actions of mitochondrial toxicants in terms of ROS. 21.4.3 Mitochondrial Dynamics and Mitochondrial Membrane Potential One of the major drawbacks of cell culture studies is that they describe the effect in only that cell type, but the interactions of those cells within a tissue and further in the whole organism is lost. The zebrafish model bridges this gap, yet retains some of the inherent advantages of cells in culture due to its small size. The methods used for these types of studies are centered around various microscopy techniques and the ability to identify mitochondria and different cell types using targeted fluorescent proteins. Advancing technology in microscopy has made it easier to track mitochondria in specific cell types in vivo. The microscopy techniques in specific

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Figure 21.6 Increased reactive oxygen species observed in Peo1 knockdown embryos at 3 days’ post‐fertilization. Representative 2‐photon image projections of H2DCFDA fluorescence from mismatch control (a (brightfield) and b (fluorescence)) and Peo1 knockdown (c (brightfield) and d (fluorescence)) embryos. Peo1 knockdown hearts appears to have more H2DCFDA fluorescent product than controls. The bright spots in both panels are epidermal cells (melanocytes) and are excluded from analyses. (See insert for color representation of the figure.)

organs are reviewed in this volume by Drs Andrew Hall and John Lemasters (see Chapters 34 and 35) and can be applied to zebrafish as a whole. For example, the use of spinning disk confocal microscopy can be used to capture exceedingly rapid dynamic events, such as transport within a nerve cell, which laser scanning confocal microscopy is unable to capture in real time (Godinho 2011). These events are easily visualized and can be measured for disruption by toxic agent exposures. The number of established transgenic fluorescent lines is

extensive, and availability of published lines coupled with relative ease of generating new lines makes the zebrafish model an attractive alternative in the study of toxic exposures to mitochondria. Dr Marc Ekker’s research group, for example, has coupled eGFP targeted to DA neuron clusters with mCherry targeted to mitochondria to examine the effect of methylmercury on neuronal development (Noble et al. 2015). Their findings suggest that the function rather than number of DA neurons is affected due to changes in mitochondrial

Detection of Mitochondrial Toxicity Using Zebrafish

dynamics (Noble et al. 2015). They have also been able to use these labeling techniques to examine neurotoxicity in different neuronal tissues such as the olfactory bulb, subpallium, pretectum, diencephalic clusters 2 and 3, caudal hypothalamus, and preoptic area using the DA neurotoxin MPTP, which differentially reduced mCherry labeling in these tissues. In our own studies, we have used fluorescent labeling to examine toxicity of DNP to different neuronal tissues in zebrafish (Bestman et  al. 2015) and to target mitochondria to examine mitochondrial network stability in skeletal muscle with disruption of the mitochondrial dynamics protein Opa1 (Rahn et al. 2013). Other examples from the literature use a transgenic fluorescent reporter zebrafish line that could be photoactivated to observe mitochondrial dynamics (Bergamin et al. 2016; Dukes et al. 2016). Photoactivated mitochondria change from green to red, while newly formed mitochondria maintain a green color. A fission event would result in smaller green or red mitochondria. A fusion event between an activated mitochondrion and one that was not resulted in a yellow label. Through these color differences, the authors were able to report on mitochondrial dynamics in DA neuron transport. The use of dyes to label mitochondria and aspects of the zebrafish is also a viable route for studies. One recent example uses the novel cyanine dye ZMJ214 to visualize membrane potential of mitochondria in neuromasts in zebrafish (Sasagawa et  al. 2016). Using oligomycin and FCCP, known membrane potential disrupters as controls, they measured an increase (hyperpolarization) and a decrease (depolarization) in fluorescence, respectively, and concluded that the dye reflects membrane potential status of the mitochondria. They then tested for the mitochondrial toxicity of troglitazone, a thiazolidinedione developed to treat diabetes but was removed from the market due to hepatic toxicity, and tolcapone, a catechol‐O‐methyltransferase (COMT) inhibitor that was developed for Parkinson’s disease but was also retracted due to off‐target toxicity. In both cases, a decrease in mitochondrial membrane potential was observed. As mentioned earlier, DASPEI stains the mitochondria of live cells and is frequently used to stain the neuromasts, such as in studies to determine the cell death and regeneration response of neuromasts to exposures to aminoglycosides such as neomycin (Harris et al. 2003). While the aqueous environment allows for easy exposure to various dyes for uptake and visualization, efficacy can be limited with some dyes due to poor permeabilization into living tissue. Longer exposures or the use of fixed tissues can be used to increase permeabilization. The darkening of zebrafish from the growth of melanocytes as they mature from embryos to larva to adults increases the innate fluorescence and obscures transparency. Exposure to a low concentration of 1‐phenyl‐2‐thiourea

(PTU) starting at 24 hpf impedes the darkening of the embryo as it grows for a limited time. Logistically, this method is most viable for the first week of life. Continuing to look at fluorescence in adult fish can be achieved through the generation of a stable line cross with the transparent casper zebrafish line and now the transparent crystal zebrafish line, which are superior to the casper line in terms of optical transparency (Antinucci and Hindges 2016). 21.4.4

Mitochondrial DNA Stability

Immature oocytes contain the starting mitochondria that will be passed onto the next generation. During maturation, oocytes undergo massive mtDNA replication. Mutations in mtDNA can be caused by genotoxicants (Meyer et al. 2013), as well as via replication errors (Zheng et al. 2006). Heteroplasmy is the presence within a cell or individual of mtDNA, which have different sequences, whereas for homoplasmy every mitochondrial genome has the same sequence. The level of mtDNA heteroplasmy within a cell or tissue and the particular mutation(s) contained within mtDNA are important considerations for disease. Even 10% heteroplasmy can be pathogenic in certain cases (Suomalainen and Isohanni 2010; Wallace 2013), and 30–35% depletion of mtDNA can be lethal (Naviaux 2000). Wallace’s group showed in an elegant study that in mice harboring deleterious mtDNA mutations, the ovary selectively eliminates the most deleterious mtDNA mutations, which should minimize their impact on population fitness. However, milder mtDNA mutations are not eliminated in the female germline and are introduced into the general population (Fan et al. 2008; Wallace 2010). In zebrafish, many of the methods used to measure mtDNA stability in cells have been translated to zebrafish embryos, larvae, and organs. MtDNA copy number can be measured using real‐time PCR amplification of a short mtDNA fragment and a short nuclear DNA fragment and determining the ratio of mtDNA/nDNA (Rahn et  al. 2013; Rahn et  al. 2015). When zebrafish were exposed to DNP, we observed an increase in mtDNA copy number that was likely due to induction of mitochondrial biogenesis (Bestman et  al. 2015). MtDNA deletions can also be identified by another PCR‐based method. An extra‐long PCR amplifies mtDNA using primers that span a large portion of mtDNA, and all fragments are run on a gel to determine the percentage of smaller (deleted) fragments compared with the full‐ length product within a sample (Rahn et al. 2015). Real‐ time PCR methods have been developed for measuring mtDNA deletions in single cells and could also be used for zebrafish (He et  al. 2002). We also developed an in  vivo mtDNA polymerase activity assay utilizing

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ethidium bromide (EtBr) to deplete mtDNA (Rahn et al. 2015). We used this assay to show that zebrafish with two copies of a mutated mtDNA polymerase (Polg) could not recover mtDNA content after mtDNA depletion by EtBr, revealing that the mutated mtDNA polymerase did not have sufficient DNA polymerase activity. DNA polymerase‐blocking lesions can also be quantified using a PCR‐ based assay developed originally by the Van Houten group and translated to the zebrafish by the Meyer group (Santos et  al. 2006; Hunter et  al. 2010). This assay is described in detail in Dr Meyer’s section within this book (Chapter 48).

21.5 Conclusions and Future Directions In conclusion, there are many advantages to using zebrafish to study mitochondrial toxicology of drugs and other chemicals. Not only do they fill an important gap between cellular and rodent models, but they have great utility for high‐throughput methodologies, an important consideration for chemical screens. New drugs have been developed stemming from zebrafish

screens, and new methods for genetic manipulation have contributed to the rise in use of zebrafish for disease models and for understanding gene–environment interactions. There is a greater awareness of the ability of many chemicals to affect mitochondrial function, and this can be a major mechanism for toxicity issues found for many drugs. Many mitochondrial assays have been developed for zebrafish that translate methodologies that have long been the domain of cell culture. Long‐ term studies for age‐related diseases and epigenetic and transgenerational investigations are now being performed. Finally, zebrafish are an important model for tissue regeneration. As new studies reveal underlying and key roles of mitochondria in proper regeneration, it will be important to understand how exposures to chemicals that target mitochondria also affect tissue regeneration.

Acknowledgments We would like to thank Drs Jennifer Bestman and Jennifer Rahn for helping to generate some of the images shown in this chapter.

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Weatherly, L. M., J. Shim, H. N. Hashmi, R. H. Kennedy, S. T. Hess and J. A. Gosse (2016). “Antimicrobial agent triclosan is a proton ionophore uncoupler of mitochondria in living rat and human mast cells and in primary human keratinocytes.” J Appl Toxicol 36(6): 777–789. Westerfield, M. (2000). The Zebrafish Book. A Guide for the Laboratory Use of Zebrafish (Danio rerio). Eugene, University of Oregon Press. Xi, Y., M. Yu, R. Godoy, G. Hatch, L. Poitras and M. Ekker (2011). “Transgenic zebrafish expressing green fluorescent protein in dopaminergic neurons of the ventral diencephalon.” Dev Dyn 240(11): 2539–2547. Yan, M. H., X. Wang and X. Zhu (2013). “Mitochondrial defects and oxidative stress in Alzheimer disease and Parkinson disease.” Free Radic Biol Med 62: 90–101. Zhang, X. and Z. Gong (2013). “Fluorescent transgenic zebrafish Tg(nkx2.2a:mEGFP) provides a highly sensitive monitoring tool for neurotoxins.” PLoS One 8(2): e55474. Zhang, P. C., A. Llach, X. Y. Sheng, L. Hove‐Madsen and G. F. Tibbits (2011). “Calcium handling in zebrafish ventricular myocytes.” Am J Physiol Regul Integr Comp Physiol 300(1): R56–R66. Zheng, W., K. Khrapko, H. A. Coller, W. G. Thilly and W. C. Copeland (2006). “Origins of human mitochondrial point mutations as DNA polymerase gamma‐mediated errors.” Mutat Res 599(1–2): 11–20. Zon, L. I. and R. T. Peterson (2005). “In vivo drug discovery in the zebrafish.” Nat Rev Drug Discov 4(1): 35–44. Zou, S. Q., W. Yin, M. J. Zhang, C. R. Hu, Y. B. Huang and B. Hu (2010). “Using the optokinetic response to study visual function of zebrafish.” J Vis Exp (36): 1742. Zu, Y., X. Tong, Z. Wang, D. Liu, R. Pan, Z. Li, Y. Hu, Z. Luo, P. Huang, Q. Wu, Z. Zhu, B. Zhang and S. Lin (2013). “TALEN‐mediated precise genome modification by homologous recombination in zebrafish.” Nat Methods 10(4): 329–331.

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22 MiRNA as Biomarkers of Mitochondrial Toxicity Terry R. Van Vleet and Prathap Kumar Mahalingaiah Department of Investigative Toxicology and Pathology, Preclinical Safety Division, AbbVie, North Chicago, IL, USA

CHAPTER MENU 22.1 22.2 22.3 22.4 22.5 22.6 22.7 22.8 22.9 22.10 22.11

22.1

Introduction, 347 MicroRNAs: General, 348 Properties of miRNA: Useful Biomarkers, 349 Mitochondria and miRNAs, 350 miRNA Transport in the Mitochondria, 351 miRNA Secretion, 352 miRNAs Associated with Mitochondrial Function, 354 Mitochondrially Rich Tissues and Tissue‐Specific miRNAs, 355 Work to Date Using MiRNA as Biomarkers of Mitochondrial Toxicity, 359 Future Work Needed, 361 Conclusions, 362 References, 363

Introduction

The mitochondria are a major target of many drugs and xenobiotics. Loss of mitochondrial function and, more importantly, the number of mitochondria can have disastrous effects on cells (Dykens and Will, 2007). Because of the vital role of mitochondria in energy production, loss of mitochondria is extremely detrimental to target cells and tissues with the greatest energy demands. Mitochondrially rich/dependent tissues are often the most sensitive target of mitochondrial toxicants. Whereas mitochondrial toxicity can be assessed in tissues by functional assays or copy number assessments, reliable systemic biomarkers of mitochondrial toxicants are still needed to assess mitochondrial toxicity in vivo. This is particularly true in the clinical setting where humans are exposed to drugs, chemicals, or other xenobiotics that may be toxic to mitochondria. Detection of mitochondrial toxicity has been particularly difficult because the effects are often delayed until after depletion of mitochondria and/or mitochondrial function as most

cells can tolerate this condition until their minimal capacity or energy demand is reached (Picard et  al., 2013). In addition, there are a number of diverse mechanisms that may be involved in mitochondrial toxicities including perturbations in lipid metabolism, oxidative phosphorylation, membrane integrity, proton gradient, and oxidative stress (Pereira et al., 2009a, b). The aims of this chapter are to review the current work testing microRNA (miRNA) biomarkers of mitochondrial toxicity, to provide background information demonstrating the potential usefulness of mitochondrial miRNA (mitomiR) as biomarkers, to provide information guiding readers in assessing miRNA changes associated with mitochondrial toxicity in susceptible tissues, and to discuss current gaps in knowledge that need to be filled to use miRNA to their potential as biomarkers of mitochondrial toxicity. Presently, the science of mitomiR and their use as biomarkers of mitochondrial toxicity is in its infancy. Despite the description of many miRNAs that are associated with both toxicity and mitochondrial function, few efforts have focused on mitomiR changes

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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associated with mitochondrial toxicity and known mitochondrial toxicants. miRNAs have been isolated within mitochondria that are of both nuclear and mitochondrial in origin, and miRNA‐targeting mitochondrial genes from both mitochondrial and nuclear genomes have been identified, demonstrating the importance and complexity of miRNA in the regulation of mitochondrial genes. Many tissue‐specific or tissue‐enriched miRNAs have also been found with links to mitochondrial function. This suggests the potential for miRNA markers of mitochondrial function that are tissue specific, ideally helping to monitor mitochondrial toxicity, in specific tissues of interest, or eluding to the target tissues where mitochondrial toxicity is occurring. There is still much to discover about miRNAs and their role in regulating mitochondrial function and compensatory actions due to mitochondrial toxicants. miRNAs have many chemical and physical properties that make them particularly appealing for use as biomarkers. These topics will be discussed in detail among others.

22.2

MicroRNAs: General

miRNAs are single‐stranded, short noncoding RNAs that post‐transcriptionally regulate the expression of target genes and that were first discovered in Caenorhabditis elegans by Lee et al. (1993). Biogenesis of the majority of miRNAs involves a standard canonical pathway that has been discussed in detail by several excellent reviews (Macfarlane and Murphy, 2010; Borralho et al., 2014; Ha and Kim, 2014; Makarova et al., 2016). In brief, miRNA biogenesis begins with transcription by RNA polymerase II to generate transcripts of varying lengths (generally 100 to 1000 nucleotides), forming hairpin‐like structures with flanking ssRNA regions containing 5′ cap and 3′ poly A (adenosine) tails called primary miRNAs (pri‐ miRNAs) (Cai et al., 2004; Han et al., 2006). Pri‐miRNAs (within the nucleus) are further processed by the microprocessor complex containing Drosha, RNAse III endonuclease and its cofactor, and DiGeorge syndrome critical region gene 8 (DGCR8) to produce (cleaved at the stem) 60–70 bp hairpin‐containing precursor miRNA (pre‐miRNA) (Gregory et al., 2004; Borralho et al., 2015). Exportin‐5 binds to the two nucleotide length 3′ overhang in pre‐miRNA and exports them from the nucleus to the cytoplasm in a Ran guanosine triphosphate (Ran‐ GTP)‐dependent manner (Yi et al., 2003; Bohnsack et al., 2004). In the cytoplasm, an RNAse III enzyme (Dicer), facilitated by RNA‐binding proteins such as transactivation response RNA‐binding protein (TRBP) or protein kinase R‐activating protein (PACT), processes pre‐ miRNA further to produce double‐stranded (hairpin‐ less) duplexes of miRNA (~18–25 nucleotides) that are

bound to AGO proteins (AGO1–4) with the help of chaperones (HSP70‐90) to form the pre‐RNA‐induced silencing complex (pre‐RISC) (Lee et  al., 2006; Graves and Zeng, 2012; Srinivasan and Das, 2015; Makarova et  al., 2016). In the pre‐RISC complex, one strand of miRNA duplex (guide strand) is loaded with an AGO protein as mature miRNA and the other strand (passenger strand) is removed and degraded in the cytoplasm (Borralho et al., 2014) to form the mature RISC. In addition, alternative noncanonical pathways are also associated with the biogenesis of some miRNAs, which includes processing of de‐branched introns to associate with the miRNA processing complex without cleavage by RNA III endonuclease DROSHA (mirtrons) or without other components of miRNA biogenesis (simtrons) (Meister, 2013; Borralho et al., 2014). Mature miRNA, within the RISC complex, binds to a target mRNA sequence with partial complementarity (in most cases) base pairing to 3′UTR regions and induces post-transcriptional gene silencing by inhibiting translation or facilitating mRNA degradation via deadenylation and decapping (Lee et al., 2004; Carthew and Sontheimer, 2009; Fabian and Sonenberg, 2012; Li et  al., 2012a; Bandiera et  al., 2013; Bienertova‐Vasku et  al., 2013). AGO2 is an effector protein in the RISC complex, and GW182 is its key partner that mediates recruitment of deadenylating/decapping enzymes targeting mRNA to generate unprotected mRNA. The resulting unprotected mRNA gets cleaved by exonucleases or has inhibited translation due to binding of the cap‐binding protein eIF4E or interfering with ribosomal mRNA scanning (Czech and Hannon, 2011). Recent studies also suggest that miRNA interference happens through the binding of miRNA to 5′ UTR or open reading frames (ORFs) of their target mRNA sequence (Moretti et  al., 2010). miRNA‐mediated increases in gene translation have also been reported in certain instances (Vasudevan et  al., 2007; Zhang et al., 2014). Each miRNA may regulate multiple target genes (Duarte et al., 2014), and their roles are often associated with several key cellular processes including proliferation and/or apoptosis and differentiation (Tetreault and De Guire, 2013). miRNAs have often been estimated to regulate the expression of dozens of genes and in some cases may be as many as hundreds of genes (Qiao et al., 2013). Hence dysregulation or abnormal expression of miRNAs may contribute to cellular or organ dysfunction associated with toxicity or disease conditions (Nunez‐Iglesias et al., 2010; Melman et al., 2014; Vliegenthart et al., 2015). In addition, miRNAs may play a compensatory role in affected cells to correct for lost or diminished function due to toxicity or disease conditions (Jacovetti et al., 2012; Plaisance et al., 2014). Understanding miRNA changes is likely a key to understanding the pathogenesis of many

MiRNA as Biomarkers of Mitochondrial Toxicity

Table 22.1 miRNA databases. 1

MicroRNA.org

For experimentally observed expression patterns as well as predicted microRNA targets and target down regulation scores

2

miRDB.org

For miRNA target prediction and functional annotations

4

miRGen 2.0

For microRNA genomic information and regulation

5

miRNAMap

Collection of experimentally verified microRNAs and miRNA target genes in multiple species

6

TargetScan

For prediction of miRNA biological targets by searching for the conserved 8mer, 7mer, and 6mer sites matching the seed region of miRNAs

7

miRWalk2.0

Comprehensive atlas of predicted and experimentally verified miRNA‐target interactions

disease conditions such as cardiovascular diseases, obesity, diabetes, mental disorders, and cancers, in addition to mechanisms of various toxicities (Ali et al., 2011). The mitochondrial genome is also a well‐established target for miRNA in multiple tissues and species. Both computational modeling (Barrey et al., 2011) and experimental studies (Das et al., 2012) have demonstrated the presence of miRNA target sequences in the mitochondrial genome. Several publically available databases have also been established to identify the known functions of miRNA. They serve as an excellent resource for identifying the potential function of miRNA biomarkers, including those related to mitochondrial functions. Table  22.1 contains several online miRNA database resources.

22.3 Properties of miRNA: Useful Biomarkers Traditional biomarkers of toxicity, such as those for cardiac and skeletal muscles, have limitations due to either lack of tissue specificity or short half‐life (Calvano et  al., 2016). Hence miRNAs with their long half‐life, high stability, and higher tissue specificity may be ideal for use as potential sensitive biomarkers of these tissue toxicities. miRNAs are currently being used more frequently as translational biomarkers of tissue injury in cases where they are conserved between species (Pasquinelli et al., 2000). In general, miRNAs are more stable and persist more readily in the systemic circulation than other amplifiable biomarkers such as mRNA (Seyhan, 2015). Evolutionarily, this may be partially due to their important regulatory

role in gene expression. Several studies have shown the presence of miRNA in a number of body fluid matrices including blood, urine, saliva, milk, tears, and bile (Turchinovich and Cho, 2014). Indeed, miRNAs are routinely found constitutively in the circulation in exosomes. Tissues under the effects of drugs and xenobiotics undergo changes in gene expression and regulation that may be compensatory for deleterious effects in order to re‐establish equilibrium (Jacovetti et  al., 2012). These perturbations can be measured as changes in proteins, metabolites, or gene expression, which may all serve as biomarkers of toxic effects from drugs. miRNAs are also modulated in response to toxic insults, as key regulators of gene expression, and are often released in the systemic circulation or other body fluids (Nassirpour et al., 2015; Vliegenthart et  al., 2015; Sharapova et  al., 2016). Additionally miRNAs are released as a consequence of cell/tissue lysis due to necrosis. In these two ways, they can serve as systemic biomarkers of tissue dysfunction, damage, and loss. Due to the unique sequence of each 18–25mer, miRNA can be easily and conclusively identified via RT‐PCR, miRNA microarrays, or next‐generation sequencing (RNA‐Seq). The ability to identify and differentiate between individual miRNA affords strong specificity to their detection. As more miRNA functions are elucidated, the identification of specific mechanisms of toxicity/dysfunction associated with these will be more easily accomplished as well. This may also allow for the identification of specific tissues of injury in some cases. Alterations in miRNAs involved in mitochondrial function specifically are expected with drugs and xenobiotics that affect mitochondrial function or cause direct toxicity and loss of mitochondria. Changes in miRNA due to drug treatments and changes related to drug‐mediated toxicities are well described (Cao et al., 2015; Harrill et al., 2016). Detection of miRNA is amenable to highly sensitive methodologies that involve the amplification of miRNA transcripts (Brustoloni et al., 2007; Muniesa et al., 2014). Because of this, the detection of very small amounts of miRNAs is possible. The sensitivity of miRNA changes may be, in some cases, sensitive enough to precede the detection of lesions by histology methods (Baumgart et  al., 2016). This property makes miRNA particularly appealing as candidate biomarkers of mitochondrial toxicity. Typical PCR‐based methods (as for miRNA detection) are highly quantitative (Brustoloni et al., 2007; Muniesa et al., 2014), giving researchers the opportunity to make accurate measurements of miRNA levels in tissues and body fluids. When these assessments are for safety biomarker use, accuracy is critical for confidence in the observed changes. Some methods such as RT‐PCR or RNA‐Seq can accurately estimate the precise copy number of transcripts of interest under some conditions.

349

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22.4

Mitochondria and miRNAs

In the classical pathway of miRNA gene regulation, miRNA activity is located mainly in the cytosolic compartment within RNA‐rich granules called processing bodies (P bodies) and chromatoid bodies (in male germ cells), which are the major sites of localization for miRNAs with RISC complex components (Hutvagner and Zamore, 2002; Kotaja et  al., 2006). However, increased understanding of the role of miRNAs has suggested the involvement of several different organelles/intracellular components in miRNA localization including the nucleus (Jeffries et al., 2011; Chen et al., 2012a), exosomes (Mittelbrunn et  al., 2011), endosomal membranes (Gibbings et  al., 2009), and mitochondria (Dasgupta et al., 2015). An association between P bodies and mitochondrial membranes has been described and suggests a potential role of mitochondria in miRNA processing/ activity as well (Huang et al., 2011). Interestingly, disruption of the RISC complex with release of AGO2 protein from P bodies is associated with increased mitochondrial membrane permeability and strongly supports an association of mitochondria with P bodies and miRNA activity (Huang et  al., 2011). The presence of P body markers such as YB‐1 in mitochondria further supports the idea that mitochondria are involved in miRNA signaling/processing (de Souza‐Pinto et al., 2009). Mitochondrial miRNAs (which are transcribed from either the nuclear or mitochondrial genomes) are

referred as mitomiRs. They have been identified within the mitochondria in multiple studies (Kren et al., 2009; Bian et al., 2010; Huang et al., 2011), and nuclear‐encoded mitomiRs have been shown to be processed within the mitochondria to mediate post-transcriptional regulation of mitochondrial‐encoded proteins as well. Interestingly, different cell types appear to harbor different sets of mitomiRs. Multiple miRNAs have been identified in purified mitochondrial fractions isolated from various tissues and cell types including the liver, skeletal muscle, heart, HEK 293 cells, and HeLa cells as listed in Table 22.2. Tissue‐specific miRNA sequencing analyses are useful in understanding the differential expression of miRNAs in different tissue/cell types. For example, systematic analysis of small RNAs, including miRNA associated with mitochondria by subcellular fractionation and deep sequencing analyses, demonstrated differential expression of the majority of miRNAs in HEK293 and HeLa cells (Sripada et al., 2012). In the same study, a total of 28 miRNAs were aligned to positions of 16S rRNA and tRNA and subunits of complex I in mitochondrial genome. The results of other targeted approaches using tissue‐specific microarray analyses also suggest the presence of cell‐ and tissue‐specific mitomiRs. For example, miR‐181c has been identified as a cardiac‐specific mitomiR in rats (Das et al., 2012) in this way. In addition, a unique set of mitomiRs were identified in human skeletal muscle (Barrey et  al., 2011) and HeLa cells (Bandiera et al., 2011).

Table 22.2 Mitochondria‐associated miRNAs in cells/tissues. Tissue/cell type

MiRNA

Reference

Myotubes, human

miR‐720, miR‐133b, miR‐1974, miR‐24, miR‐133a, miR‐125a‐5p, miR‐1979, miR‐103, miR‐125b, miR‐103, miR‐221, miR‐23a, let‐7b, miR‐423‐3p, miR‐106a, miR‐23b, miR‐92a, miR‐193b, miR‐365, miR‐93

Bandiera et al. (2011)

Liver, rats

miR‐130a, miR‐130b, miR‐140*, miR‐320, miR‐494, miR‐671, miR‐202, miR‐705, miR‐709, miR‐721, miR‐761, miR‐763, miR‐198, miR‐765

Kren et al. (2009)

Liver, mouse

miR‐122, miR‐805, miR‐690, miR‐689, miR‐494, miR‐705, miR‐721, miR‐720, miR‐188‐5p, miR‐101, let‐7f, miR‐711, miR‐432, miR‐181b, miR‐361‐5p, miR‐680, miR‐181d, miR‐29c, miR‐29a, miR‐762

Bian et al. (2010)

HeLa cells

miR‐1973 miR‐1275 miR‐494 miR‐513a‐5p miR‐1246 miR‐328‐5p miR‐1908, miR‐1972 miR‐1977 miR‐638 miR‐1974 miR‐1978 miR‐1201

Bandiera et al. (2011)

HEK293 cells

hsa‐miR‐10a, hsa‐miR‐128, hsa‐miR‐1307, hsa‐miR‐140‐3p, hsa‐miR‐185, hsamiR‐196a, hsa‐miR‐25, hsa‐miR‐320a, hsa‐miR‐330‐3p, hsamiR‐340, hsa‐ miR‐423‐5p, hsa‐miR‐629, hsa‐miR‐744

Sripada et al. (2012)

HeLa cells

let‐7i, hsa‐miR‐181b, hsa‐miR‐21, hsa‐miR‐23a, hsa‐miR‐29a, hsamiR‐30a, hsa‐miR‐31, hsa‐miR‐452

Sripada et al. (2012)

Heart, mouse

21a‐5p, 125b‐5p, 128‐3p, 151‐3p, 203‐3p, 212‐3p, 22‐3p, 23a‐3p, 27a‐3p, 27b‐3p, 320‐3p, 1932, 1199‐5p, 5108, 375‐3p, 3963, 341‐3p, 342‐3p, 148a‐3p, 200c‐3p, let7a‐5p, 300‐3p, let‐7d‐5p, 181b‐5p, 5112, 203‐3p, 423‐3p, 378‐5p, 2137, 5131, 26a‐5p, 5119

Jagannathan et al. (2015)

Cardiomyocytes, rat

MiR‐181c

Das et al. (2012)

MiRNA as Biomarkers of Mitochondrial Toxicity

The first evidence of an association of mitochondria with miRNA and RNA interference component proteins came from a study showing the specific association of mitochondrial tRNA(Met) with effector proteins of RNA interference such as AGO2 (Maniataki and Mourelatos, 2005). The identification of pre‐miRNAs in mitochondria further suggests that mitochondria are involved in the processing of pre‐miRNA sequences locally within the mitochondria to produce mature miRNA and regulate transcripts within the mitochondria (Barrey et  al., 2011). In addition to miRNA and pre‐miRNA, the detection of effector proteins of miRNA machinery such as Argonaute and Dicer confirms the presence of active miRNA processing and post-transcriptional gene silencing machinery inside mitochondria (Bandiera et  al., 2011; Wang et al., 2015b). Zhang et al. (2014) provided direct evidence for the presence of AGO2 within the mitochondria using highly purified mitochondria and as well as mitoplasts (selectively removed outer mitochondrial membrane) by digitonin treatment. However GW182, a key partner of the AGO2 protein, appears to be absent in mitochondria (Zhang et al., 2014), suggesting that the RNA silencing machinery in mitochondria may be somewhat different from the cytoplasmic machinery. The association of miRNA with mitochondria suggests several potential roles of mitochondria in regulating miRNA functions. Some miRNAs are highly enriched in the mitochondria compared with the cytoplasm, suggesting distinctive miRNAs are associated with the modulation of mitochondrial function (Bian et  al., 2010). It has also been hypothesized that mitochondria may serve as storehouses for miRNA to supply them to the cytosol or as a vehicle to deliver miRNAs to other intracellular organelles such as the endoplasmic reticulum and P bodies on demand (Wang et al., 2015b). Mitochondria may also serve as a platform for the interaction of the RNAi components. The association of nuclear‐encoded miRNAs and effector proteins of RNAi (AGO2) with the outer membrane of mitochondria is reported in multiple studies and suggests that mitochondria may serve as an anchor for miRNA signaling (Bandiera et  al., 2011; Sripada et  al., 2012). The mitochondrial uncoupler, carbonyl cyanide p‐chlorophenylhydrazone (CCCP), induced mitochondrial morphology changes and significantly reduced RISC assembly and miRNA‐mediated gene silencing, suggesting that mitochondrial toxicity/ dysfunction may contribute for RNAi defects as well (Huang et al., 2011). Substantial evidence also suggests that the mitochondrial genome is a source of mitomiRs (Sripada et  al., 2012; Shinde et  al., 2015). Some mitomiRs that originate from mtDNA (mitochondrial genome) appear to directly regulate mitochondrial transcripts (Bandiera

et  al., 2013). In humans and mice, the production of small noncoding RNA sequences has been identified specifically from tRNA loci from within the mitochondrial genome (Mercer et  al., 2011; Smalheiser et  al., 2011). Pre‐miRNA (pre‐miR‐ let7b and pre‐miR‐302a) and miRNA (miR‐1974, miR‐1977, and miR‐1978) sequences have also been shown to align within the human mitochondrial genome (Bandiera et  al., 2011; Barrey et  al., 2011). Bioinformatic analyses of the human mitochondrial genome in skeletal muscle predicted six novel miRNA sequences (hsa‐miR‐mit‐1 to 6) (Shinde and Bhadra, 2015). Experimental studies further confirmed the localization of these six miRNAs within a highly purified human skeletal muscle mitochondrial fraction. The influence of miRNAs on mitochondrial function is attributed mainly to three different routes of activity (Bandiera et  al., 2013): (i) nuclear‐encoded miRNAs may act in cytosol to cause posttranslational silencing of target mRNAs, which code proteins of mitochondrial function, (ii) nuclear miRNAs get translocated into mitochondria to regulate translation of genes within the mitochondria, and (iii) miRNAs encoded by mitochondrial genome act locally to regulate the translation of mitochondrial proteins inside mitochondria. In addition to translational repression, a primary effect of miRNAs (including presumably mitomiRs) is positive effects on translation in mitochondria (Lee and  Vasudevan, 2013). For example, nuclear‐encoded miR‐1, which gets induced during muscle differentiation, is shown to enter mitochondria and enhance translation of specific mitochondrially encoded transcripts of the ND1‐containing complex I and COX1‐ containing complex IV (Zhang et  al., 2014). In the cytoplasm, however, miR‐1 represses the expression of nuclear‐encoded targets HDAC4 and elongation factor for RNA polymerase II 2 (ELL2), suggesting a different mechanism of regulation in the cytosol versus mitochondria (Chen et  al., 2006; Zhang et  al., 2014). Even though a clear mechanistic understanding of miRNA‐ enhanced translation in the mitochondria is not known, the lack of cap or typical long poly(A) tail in mitochondrial transcripts, and rearranged miRNA machinery without GW182 (a key partner of AGO2 protein in the mitochondria), has been proposed as a potential mechanism (Zhang et al., 2014).

22.5 miRNA Transport in the Mitochondria The majority of mitomiRs are encoded in the nuclear genome and translocated into mitochondria. The first direct evidence that some miRNAs encoded in the

351

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Mitochondrial Dysfunction by Drug and Environmental Toxicants

nuclear genome are translocated into the mitochondria came from a study showing miRNAs in mtDNA‐less cell  mitochondria (Dasgupta et  al., 2015). 206 ρ° cells are  143B‐derived human osteosarcoma cells treated with ethidium bromide that contains no mitochondrial genome, and hence there is no transcription of mitochondrial RNAs in these cells. Next‐generation sequencing analyses of the miRNA profile showed enrichment of multiple miRNAs including miR‐181c‐5p and miR‐ 146a‐5p in 206 ρ° cells. Several other researchers have also confirmed the import of nuclear genome encoded miRNAs into the mitochondria (Bandiera et  al., 2011; Mercer et  al., 2011). In fact, some miRNA appear to localize preferentially in specific regions within the mitochondria as well. For example, miR‐146a, miR‐103, and miR‐16 are reported to be preferentially localized within the intermembrane space of human mitochondria (Mercer et  al., 2011). The biological significance of miRNA localization within the mitochondria is not currently well understood. Das et  al. (2012) reported the first evidence of mitochondrial transcripts serving as a target for nuclear‐ encoded miRNAs, demonstrating post-transcriptional regulation of mt‐CO1 by miR‐181c (Das et  al., 2012). Import of miR‐181c into the mitochondria, and posttranscriptional repression of its target gene COX1, was confirmed in mitochondria isolated from rat heart (Das et al., 2014). Exactly how these miRNAs get transported into the mitochondria is still under ongoing debate. Several hypotheses regarding mechanism have been proposed including the import of noncoding RNA via a protein import system. Passive transfer of miRNAs into mitochondria has been generally ruled out considering their size and charged nature (Geiger and Dalgaard, 2017). Translocation of nuclear‐encoded miRNAs from the nucleus into the mitochondria appears to involve an ATP‐dependent import mechanism(s), which may also vary in species‐specific manner (Tarassov et  al., 2007; Ballatore et  al., 2013). The AGO2 protein may act as a carrier protein trafficking miRNA into mitochondria (Bandiera et al., 2011), or import may involve mitochondrial membrane channels, translocase of the outer membrane (TOM), or translocase of the inner membrane (TIM) complex(es) (Bandiera et al., 2011; Srinivasan and Das, 2015). In addition, AGO2‐independent pathways possibly involving exoribonuclease polyribonucleotide nucleotidyl transferase (PNPT1/ PNPASE) of the mitochondrial intermembrane space (Wang et al., 2010), porins, and/or voltage‐dependent anion‐selective channel protein (VDAC) (Bandiera et  al., 2013) have also been reported. It has also been hypothesized that there is a close association of mitochondria with RISC complex components such as P bodies and the endoplasmic reticulum, which may facilitate translocation of miRNA and

AGO2 protein into mitochondria (Huang et  al., 2011; Makarova et al., 2016). The results of an interesting study have shown localization of miRNA, AGO2/3 protein, and target mRNA in the outer mitochondrial membrane (Sripada et al., 2012). This finding suggests a possible role of the mitochondrial outer membrane as a platform for assembly of the RISC complex and site of regulation of intracellular protein levels (Sripada et  al., 2012) but may also be related in some way to miRNA internalization. Figure  22.1 outlines the biosynthesis, transport, and processing of miRNAs.

22.6

miRNA Secretion

Several active mechanisms have been proposed for the release/secretion of miRNAs from cells into the circulation, and miRNAs also appear to be released (leaked) passively from cells with damaged membrane integrity during the process of cell apoptosis or necrosis (Chen et al., 2012b). The active secretion of miRNAs has been reportedly associated with various extracellular vesicles (mainly exosomes and microvesicles), apoptotic bodies (Zernecke et  al., 2009), or in association with RNA‐ binding proteins (microvesicle‐free) such as high‐density lipoproteins (HDL) (Vickers et al., 2011) and AGO proteins (Turchinovich et al., 2011). Among these secretion routes, the exosome pathway is the most studied and is generally considered to be the main pathway. The biological significance of secreted miRNAs is an interesting and growing focus of research. Extracellular miRNAs appear to be transferred between cells mainly through exosomes released from parental cells and are also functional in association with RNA interference machinery in recipient cells (Valadi et al., 2007; Chiba et al., 2012; Montecalvo et  al., 2012). Hence, exosomes (with miRNAs) are getting increased attention as a mode of intercellular signaling/communication (Zhang et al., 2015). miRNA profiling studies have revealed sequence‐ specific sorting mechanisms in parental cells to guide selected miRNAs into exosomes. For example, the preferential entry of miR‐150, miR‐142‐3p, and miR‐451 into exosomes has been shown in multiple cell lines (Guduric‐ Fuchs et al., 2012). The let‐7 miRNA precursor is abundant in exosomes derived from the gastric cancer cell line AZ‐P7a compared with exosomes derived from lung and colorectal cancer cell lines (Ohshima et  al., 2010). In  addition, significantly higher levels of miR‐21 were reported in exosomes from serum samples of glioblastoma patients compared with healthy individuals (Skog et al., 2008). Interestingly, miR‐21 is a mitomiR involved in mitochondrial redox regulation (Chau et  al., 2012). Recently, a role for the hnRNPA2B1 protein, which

MiRNA as Biomarkers of Mitochondrial Toxicity

Exosomes RNA polymerase II Pri-miRNA miRNA gene

AAA

Cap Multivesicular bodies

Drosha

Cropping

AGO

miRNA–Ago complex

DGCR8

Nucleus

miRNA secretion

Pre-miRNA

miRNA HDL miRNA–HDL complex

Exportin5/RAN-GTP

miRNA duplex

Dicer

Cytosol

TRBP/PACT

Pre-miRNA

Pre-RISC HSC70

AGO1–4

HSP90 Apoptotic bodies

Passenger strand degradation

? AGO1–4

GW182

AGO1–4

GW182

? Dicer Pre-miRNA

miRNA

Mitochondrial genome encoded

Processing and maturation ?

Mature RISC

miRISC

?

? AGO2

Target mRNA

Translational repression

mRNA degradation

Act locally Inhibit translation of mitochondrial mRNA

Figure 22.1 Biosynthesis of miRNAs: In the canonical pathway, miRNA biogenesis begins in the nucleus with transcription by RNA polymerase II into larger primary transcripts with hairpin‐like structure called pri‐miRNAs, which are further cleaved by a microprocessor complex (type III RNase, Drosha, and its cofactor DGCR8) into pre‐miRNA. Exportin‐5 binds to the 2 nucleotide length 3′ overhang in pre‐ miRNAs and exports them from nucleus into the cytoplasm in a Ran guanosine triphosphate (Ran‐GTP)‐dependent manner for further processing. Once in the cytoplasm, pre‐miRNAs get further cleaved by Dicer and processed into double‐stranded miRNAs. These miRNA duplexes are bound to AGO proteins (AGO1–4) with the help of chaperones (HSP70‐90) to form a multi‐protein complex called the pre‐ RNA‐induced silencing complex (pre‐RISC). In the pre‐RISC complex, one strand of the miRNA duplex (guide strand) is loaded onto AGO proteins as mature miRNA and other strand (passenger strand) gets removed. Mature miRNA (guide strand) within RNA‐induced silencing complex (RISC) binds to target mRNA sequences and induces post-transcriptional gene silencing by inhibiting translation or facilitating mRNA degradation via deadenylation and decapping. Either pre‐miRNA or miRNA (with AGO‐2 protein or separately) is transported into the mitochondria (mechanisms not clearly understood). Once inside the mitochondria, nuclear‐encoded pre‐miRNA get further processed into mature miRNA (with the addition of an acetyl group), which acts locally inside mitochondria to regulate mRNA expression or for transport into cytosol to act on nuclear‐encoded target mRNA. In addition to nuclear‐encoded miRNA, miRNAs may also derive from mitochondrial genome and be processed similarly to act locally within the mitochondria or to get transported to cytosol. How mitochondrial‐encoded miRNAs are transported into cytosol is still largely unknown. miRNAs also get secreted into circulation (extracellular fluids). Several pathways for miRNA secretion have been proposed. MiRNAs mainly get secreted in association with extracellular vesicles including exosomes or with apoptotic bodies in cells undergoing death. In addition, miRNA secretion also happens in association with RNA‐binding proteins such as high‐density lipoproteins (HDL) or AGO2 proteins. MiRNAs likely also get released (leaked) passively from cells with damaged membrane integrity during the process of cell apoptosis or necrosis.

specifically recognizes the GGAG sequence in miRNA, has also been associated with the transport of miRNAs into exosomes (Villarroya‐Beltri et al., 2013). Conditions of stress, due to either disease or toxicity, affect the expression of miRNA as well as the localization of miRNA in mitochondria (Bian et  al., 2010). However, how miRNAs may be released from the mitochondria into cytosol for excretion into circulation is not yet known. Changes in exosomal miRNA profiles with toxicity or disease, aligned with the ability to identify the  origin of exosomes from specific tissues or cells using  specific membrane proteins, will allow miRNA to  be used more effectively as potential noninvasive

biomarkers for organ dysfunction (Gross et  al., 2012; Zhang et al., 2015). Even though the biological significance of circulating miRNAs is not completely defined, the recent discovery of sequence‐specific sorting of miRNAs into extracellular vesicles such as exosomes (Villarroya‐Beltri et  al., 2013) clearly suggests a role of these circulating miRNAs in tissue fluids and lymph for intercellular communication. Several in vitro studies have reported the transfer of miRNA containing exosomes from donor cells and posttranscriptional regulation of genes in recipient cells (Collino et al., 2010; Penfornis et al., 2016). There is also evidence suggesting that the RNA‐binding protein,

353

354

Mitochondrial Dysfunction by Drug and Environmental Toxicants

AGO2, is involved in miRNA transport as a functional complex (independent of vesicles) in the circulation (Arroyo et  al., 2011). Nucleophosmin, another RNA‐ binding protein, has also been shown to carry miRNA into serum to mediate intercellular communication (Wang et al., 2010). miRNAs associated with exosomes or RNA‐binding proteins can enter recipient cells and regulate the genes of recipient cells just as endogenous miRNAs do. For example, miR‐146A secreted from donor cells (COS‐7 cells, a monkey kidney fibroblast‐like cell line) is shown to be taken up by prostate cancer (PC‐3M‐luc) cells to post‐transcriptionally suppress ROCK1 expression, a target gene for miR‐146a (Kosaka et al., 2010). The mechanism of uptake of secreted miRNAs into recipient cells is also incompletely understood. Immature miRNAs also appear to be secreted into circulation. In cultured mesenchymal stem cells, for example, miRNA‐mediated intercellular communication has been associated with the secretion of pre‐miRNA‐enriched microparticles and uptake by recipient cells (H9C2 cardiomyocytes) to form mature‐miRNA/RISC complexes within the target cells (Chen et  al., 2010). The significance of these in vitro findings has not yet been established in vivo, but the implications for intercellular communication via miRNA and pre‐miRNA are exciting. Identification of extracellular circulating miRNAs in plasma (Lawrie et al., 2008), as well as in other mammalian body fluids (Weber et al., 2010), has spawned a great interest in the potential use of miRNAs as noninvasive biomarkers of diseases or toxicity.

22.7 miRNAs Associated with Mitochondrial Function A dynamic relationship has been reported between critical mitochondrial functions and the activity of multiple miRNAs (Bian et al., 2010; Bandiera et al., 2011; Barrey et  al., 2011; Mercer et  al., 2011; Sripada et  al., 2012; Shinde and Bhadra, 2015). Several miRNAs have been identified in mitochondria, and their dysregulation/ alteration has been closely correlated with mitochondrial dysfunction. Indeed, miRNAs have been associated with a wide variety of dysfunctions in mitochondria including mitochondrial metabolism, apoptosis, fusion, fission, and mitophagy. 22.7.1

Energy Metabolism/Respiration

Mitochondrial energy metabolism, which involves oxidative phosphorylation and ATP production, is critical for providing the cell with the energy to perform biological processes. Impaired mitochondrial energy metabolism is associated with multiple neurodegenerative and

metabolic diseases (Sivitz and Yorek, 2010; Hroudova et al., 2014). The involvement of miRNAs in the regulation of mitochondrial oxidative phosphorylation (respiratory chain) genes is of special significance. Because tissue‐specific differences exist in the composition of the oxidative phosphorylation system (Benard et  al., 2006; Johnson et  al., 2007), it is possible that the differential expression of mitomiRs accounts, at least partly, for tissue‐specific differences in respiratory chain activity. In obese mice fed with a high fat diet, mitochondrial dysfunction eventually results in skeletal muscle disorders. Mechanistically, decreased mitochondrial function and biogenesis in obese mice are associated with low levels of miR‐149, high levels of the miR‐149 target gene PARP‐2, and decreased activation of the SIRT‐1/PGC‐1α pathway (Mohamed et  al., 2014). MiR‐15b, miR‐16, miR‐195, and miR‐424 are reported to target ADP‐ ribosylation factor‐like 2 (ARL2), and the increased expression of these miRNAs is associated with decreased mitochondrial ATP production in rats (Nishi et al., 2010; Tomasetti et al., 2014). In addition, increased expression of both miR‐15b and miR‐195 is associated with ATP reductions and mitochondrial degeneration in rat cardiomyocytes (Duarte et  al., 2014). Similarly, many other miRNAs are associated with effects on mitochondrial ATP production through effects on the electron transport system in various species and tissue/cell types. For example, miR‐181c (with its target mt‐COX1 gene) in rat cardiomyocytes (Das et al., 2012), miR‐338 (with its target COX IV gene), has been associated with altered mitochondrial function in rat neurons (Aschrafi et al., 2012) and miR‐210 (with its target COX 10 and succinate dehydrogenase subunit D (SDHD) genes; components of complexes IV and II, respectively) with altered mitochondrial function in human fibroblasts (Colleoni et al., 2013). 22.7.2

Mitochondrial Dynamics

Mitochondrial turnover and dynamics, which mainly involve fusion, fission, and mitophagy, are critical for maintaining cellular homeostasis and differentiation (Duarte et  al., 2014). Mitochondrially rich cells such as cardiomyocytes are especially sensitive to changes in mitochondrial dynamics. Interestingly, changes in the expression of several miRNAs are associated with mitochondrial dynamics. For example, increased expression of miR‐761 downregulates its target gene, mitochondrial fission factor (MFF), and suppresses the mitochondrial fission process (Long et al., 2013). MiR‐30 is associated with apoptosis through modulation of the mitochondrial fission process and targeting of the p53 gene (Li et al., 2010). MiR‐484 targets the mitochondrial fission protein 1 (Fis1), and decreased levels of miR‐484 are associated with increased Fis1 and mitochondrial fission and the

MiRNA as Biomarkers of Mitochondrial Toxicity

development of insulin resistance in diabetes mellitus (Yoon et al., 2011). MiR‐140 promotes mitochondrial fission by targeting the mitochondrial fusion protein (Mitofusin 1) and contributing to apoptosis in cardiomyocytes (Li et  al., 2014b). In Parkinson’s disease, decreased expression of miR‐34b/c is reported as an early event contributing to mitochondrial dysfunction and increased mitochondrial fission by targeting the DJ1 and Parkin proteins (Minones‐Moyano et al., 2011). Mitophagy is the removal of damaged mitochondria and is an essential intracellular quality control process for regulating mitochondrial abundance based on cellular metabolic or developmental stage demand (Kundu et  al., 2008). MiR‐101 (targeting STMN1, RAB5A, and ATG4D) (Frankel et al., 2011), miR‐204 (targeting LC3‐II protein) (Xiao et al., 2011), Mir‐30a (targeting Beclin 1‐ protein) (Wang et  al., 2014), and miR‐137 (targeting FUNDC1 and NIX) (Li et  al., 2014c) are all associated with inhibition of the mitophagy process. 22.7.3

Mitochondria‐Mediated Apoptosis

Mitochondria play an important role in initiating the intrinsic apoptotic pathway. In response to apoptotic stimuli, proapoptotic molecules like Bax and Bad get translocated into mitochondria to increase mitochondrial membrane permeability and thereby promote the release of mitochondrial proteins (and possibly miRNAs) into the cytoplasm (Li et al., 2012b). Antiapoptotic proteins such as Bcl‐2 and Bcl‐xL get associated with proapoptotic Bax and Bad and prevent cell apoptosis (Cleland et  al., 2011). miRNAs such as miR‐15a and miR‐16‐1 promote apoptosis through regulating Bcl‐2 and disrupting mitochondrial membrane potential (membrane permeability transition (MPT)) (Gao et al., 2010). Similarly, induction of the intrinsic apoptotic pathway through mitochondrial dysfunction is associated with miR‐143 and miR‐1 in human colorectal cancer DLD‐1 cells (Nakagawa et  al., 2007) and cardiomyocytes (Yu et  al., 2008), respectively. The following table (Table 22.3) contains miRNA associated with various mitochondrial functions, their corresponding target genes, and the models where they have been identified.

22.8 Mitochondrially Rich Tissues and Tissue‐Specific miRNAs Mitochondrial number generally varies from cell to cell and also between organisms. Tissues with high energy requirements such as the skeletal muscle, heart, kidney, and brain are richest in mitochondria (Bandiera et al., 2013).

A number of tissue‐specific or ‐enriched miRNAs have been elucidated (Table  22.4). Several have been used successfully as biomarkers of toxicity of their host tissues. In addition, many of these have an association with mitochondrial function and could represent biomarkers of mitochondrial toxicity in specific organs with further study. Other tissue‐specific miRNAs may be linked to mitochondrial regulation in the future. Our goal in this section is to outline many miRNAs that could qualify as future mitochondrial toxicity biomarkers. Assessing the expression of these miRNAs, within their respective tissues, in preclinical studies is likely to be the most sensitive approach to assessing toxicities, including mitochondrial toxicities. However, these may also offer the greatest potential for systemic biomarkers of mitochondrial toxicity in specific tissues. Some emphasis should be paid to the target tissues of defined mitochondrial toxicants as these can vary somewhat between toxicants. Tissue‐specific or ‐enriched miRNA changes have great potential for use as novel safety biomarkers of acute or chronic injury in cell‐free body fluids such as the plasma, serum, and urine as sensitive and tissue‐specific biomarkers of multiple pathophysiological states (Salamin et al., 2016). 22.8.1

Heart

The heart (cardiac muscle) requires significantly higher energy than many other tissues and mainly depends on mitochondrial metabolism to generate this higher energy requirement (Lemieux and Hoppel, 2009). Hence cardiac tissue is highly enriched with mitochondria, and mitochondrial dysfunction is associated with multiple cardiovascular pathologies (Hatch, 2004). Gaining a better understanding of miRNA changes associated with dysfunction or toxicity of cardiac muscle is of great interest. MiR‐208/miR208a, miR‐1, miR‐133a, and miR‐133b have been reported to be heart‐specific miRNA with possible utility as biomarkers (Nishimura et al., 2015). In rats, a comparison of serum levels of miRNA changes with conventional cardiac toxicity markers revealed that miR‐208 levels increased in a cardiac lesion‐specific manner and were detectable for a longer duration than conventional cardiac biomarkers such as cardiac troponin (cTn) and FABP3 (Calvano et al., 2016). In contrast to miR‐208, which is reportedly cardiac muscle specific, MiR‐133a/b is reported to be a sensitive biomarker for toxicity to both skeletal muscle and cardiac muscle (Calvano et al., 2016). Hence, the use of both these miRNAs in combination has been recommended for evaluation of toxicity to skeletal muscle and cardiac muscle. In a rat model of streptozotocin‐induced diabetic cardiomyopathy, significant increases in miR‐30d expression were reported. Increased miR‐30d targets foxo3a

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Table 22.3 List of miRNAs associated with mitochondrial functions. miRNA

Function

Target

Model

Reference

miR‐133a‐1 and miR‐133a‐2

Mitochondrial metabolism

Dynamin 2

Mice

Liu et al. (2011)

miR‐491‐5p

Intrinsic mitochondria‐mediated apoptosis pathways

TP53 and Bcl‐XL

Human pancreatic adenocarcinoma cell lines

Guo et al. (2012)

miR‐7

Regulates function of the mitochondrial permeability transition pore (MPTP)

VDAC1 (voltage‐dependent anion channel 1)

Human neuroblastoma cells, C57BL/6J mice

Chaudhuri et al. (2016)

miR‐15b

Mitochondrial apoptotic pathway

Bcl‐2

Sprague Dawley (SD) rats, neonatal rat cardiomyocytes

Liu et al. (2014b)

miR‐15b

Mitochondrial ATP production

ADP ribosylation factor‐like 2 (Arl2)

Neonatal rat ventricular myocytes (NRVMs), Sprague Dawley rats

Nishi et al. (2010)

miR‐21

Mitochondrial redox regulation, biogenesis

Mpv17‐like

Mouse models of chronic kidney disease

Chau et al. (2012) and Gomez et al. (2016)

miR‐22

Mitochondrial oxidative injury

Sirtuin‐1 (Sirt1) and peroxisome proliferator‐ activated receptor‐γ coactivator‐1α (PGC1α)

Sprague Dawley rats, H9c2 myocardial cell line

Du et al. (2016)

miR‐27b

Mitochondrial biogenesis

miRNA‐27b directly targets to Foxj3

Mouse C2C12 myoblasts (CRL‐1772)

Shen et al. (2016)

miR‐106b

Mitochondrial morphology, fusion

Mitofusin‐2

Mouse C2C12 myoblasts

Zhang et al. (2013)

miR‐122

Mitochondrial biogenesis/respiration

PPARGC1A, SDHA, and SDHB

Male C57BL/6 mice, human HCC patient samples

Burchard et al. (2010)

miR‐125b

Mitochondrial apoptotic pathway

Multiple genes, including Bak1, Mcl1, and p53

Human cervical cancer HeLa cells, human prostate cancer PC3 cells

Zeng et al. (2012)

miR‐532‐3p

Mitochondrial fission

Apoptosis repressor with caspase recruitment domain (ARC)

Mice

Wang et al. (2015b)

Cardiomyocytes

miR‐125b‐2

Mitochondrial apoptosis pathway

Undefined

Human glioblastoma tissues, primary glioblastoma cell cultures

Shi et al. (2012)

miR‐145

Mitochondrial apoptotic pathway in heart challenged with oxidative stress

Bnip3

Mouse model of ischemia/reperfusion (I/R) injury, primary neonatal rat ventricular myocytes

Li et al. (2012b)

miR‐149

Mitochondrial biogenesis

PARP‐2

Male C57BL/6J mice C2C12 cells

Mohamed et al. (2014)

miR‐181c

Mitochondrial morphology

Bcl2

Mouse myocardial cells

Wang et al. (2015a)

miR‐210

Mitochondrial metabolism and ROS production

HIF‐1 alpha

Human embryonic kidney (HEK293) cells, mouse embryonic fibroblasts

Mutharasan et al. (2011)

miR‐210

Mitochondrial free radical response (metabolism) to hypoxia

Iron–sulfur cluster protein (ISCU), that is, HOXA1, HOXA9, and FGFRL1

MCF7 and HCT116 cells

Favaro et al. (2010)

mir‐214

Controlling Ca2+ overload and cell death (activation of mitochondrial apoptosis)

Sodium/calcium exchanger 1 (Ncx1)

Mice

Aurora et al. (2012)

miR‐494

Mitochondrial biogenesis

Mitochondrial transcription factor A and Forkhead box j3

C2C12 myoblasts, C57BL/6J mice

Yamamoto et al. (2012)

miR‐761

Mitochondrial biogenesis

PGC‐1a and the p38 MAPK signaling pathways

Mice, C2C12 myoblasts

Xu et al. (2015)

miR‐378 and 378*

Mitochondrial metabolism and systemic energy homeostasis

MED13 and CRAT

Mice

Carrer et al. (2012)

miR‐25

Mitochondrial Ca2+ signaling

Mitochondrial calcium uniporter

HeLa, Hek293, HCT116, and RKO cells

Marchi et al. (2013)

miR‐17*

Mitochondrial antioxidant enzymes

Manganese superoxide dismutase (MnSOD), glutathione peroxidase‐2 (GPX2), thioredoxin reductase‐2 (TrxR2)

Human prostate cancer cells

Xu et al. (2010)

miR‐24

Mitochondrial apoptosis pathway

Bax

Primary cardiomyocytes from neonatal mouse hearts

Wang and Qian (2014)

miR‐27

Mitochondrial fission (mitochondrial morphology changes)

Mitochondrial fission factor (MFF)

Human CHANG liver cells

Tak et al. (2014)

miR‐30

Mitochondrial fission, apoptosis

p53, dynamin‐related protein‐1 pathway

Rat cardiac fibroblasts

Li et al. (2010)

miR‐33

Mitochondrial respiration, energy metabolism

PGC‐1α, PDK4, and SLC25A25

Human macrophages

Karunakaran et al. (2015)

miR‐34a

Mitochondrial function

Cytochrome c

Cerebrovascular endothelial cells

Bukeirat et al. (2016)

miR‐141

Mitochondrial energy production

Mitochondrial phosphate carrier (Slc25a3) in the type 1 diabetic heart

Mice

Baseler et al. (2012)

miR‐141‐3p

Mitochondrial energy production

PTEN

HFD mice

Ji et al. (2015)

miR‐151a‐5p

Mitochondrial electron transport chain

Cytb

Humans

Zhou et al. (2015)

miR‐181

Mitochondrial function, apoptosis

Bcl‐2, Mcl‐1, and Bim

Mouse primary astrocyte cultures

Ouyang et al. (2012)

miR‐181c

Mitochondrial bioenergetics

COX1

Rats

Das et al. (2014)

miR‐210

Mitochondrial respiration

Mitochondrial associated ISCU

Human placenta

Muralimanoharan et al. (2012)

miR‐221/222

Mitochondrial apoptosis pathway

PUMA

Human glioblastoma cells

Chen et al. (2012b)

miR‐326

Mitochondrial apoptosis pathway

Antiapoptotic Bcl‐xL

Human platelets

Yu et al. (2015)

miR‐335 and miR‐34a

Mitochondrial antioxidative pathway

SOD2 and Txnrd2

Rats

Bai et al. (2011)

miR‐361

Mitochondrial biogenesis and morphology

Prohibitin (PHB)

Mice, cardiomyocytes

Wang et al. (2015c)

miR‐484

Mitochondrial fission and apoptosis

Fis1

Cardiomyocytes (mouse) and adrenocortical cancer cells

Wang et al. (2012a)

miR‐497 and miR‐302b

Mitochondrial apoptosis pathway

Bcl2 Protein and cyclin D2

SH‐SY5Y cells

Yadav et al. (2011)

miR‐499

Mitochondrial dynamics (fission)

Calcineurin and dynamin‐related protein‐1

Mice

Wang et al. (2011)

miR‐761

Mitochondrial fission

Mitochondrial fission factor

Neonatal rat cardiomyocytes

Long et al. (2013)

miRNA‐30c

Mitochondrial oxidative phosphorylation (OXPHOS)

Mitochondrial‐encoded OXPHOS genes Cytb, COI, COII, and COIII

Mouse cardiomyocytes

Wijnen et al. (2014)

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Mitochondrial Dysfunction by Drug and Environmental Toxicants

Table 22.4 Tissue‐specific (enriched) miRNAs. Tissue

miRNAs

References

Liver

miR‐122, MiR‐122a, miR‐192, miR‐101b, miR‐148a, miR‐15a, miR‐193, ‐miR‐194, miR‐21, miR‐720, miR‐483, miR‐92a

Baskerville and Bartel (2005), Liang et al. (2007), Wang et al. (2009), Jopling (2012), and Guo et al. (2014)

Brain

miR‐9,miRNA‐128, miR‐125 a‐b, miR‐23, miR‐132, miR‐137, miR‐139, miR‐9, miR‐124 a‐b, miR‐134, miR‐135, miR‐153, miR‐219, miR‐330, miR‐199a, miR‐199b, miR‐214, miR‐153, miR‐137, miR‐143, miR‐99b, miR‐125a, miR‐125b, miR‐31, miR‐124, miR‐129, miR‐138, miR‐218, miR‐708, miR‐128a, miR‐128b, miR‐186, miR‐95, miR‐149, miR‐323, miR‐330, miR‐33a, miR‐346, miR‐93, miR‐212, miR 128a/b

Baskerville and Bartel (2005), Landgraf et al. (2007), Liang et al. (2007), Choudhury et al. (2013), and Adlakha and Saini (2014)

Skeletal muscle

miR‐206, miR‐133b, MiR‐1, MiR‐133a, miR‐134, miR‐193a, miR‐128a, miR‐133b, miR‐95, miR‐208a

Beuvink et al. (2007), Liang et al. (2007), McCarthy (2008), Chen et al. (2009), Nielsen et al. (2010), and Guo et al. (2014)

Cardiac muscle/ heart

miR‐208, miR‐302a, miR‐302b, miR‐302d, miR‐302c, miR‐367, miR‐499, miR‐1, miR‐126, miR‐208, miR‐302d, miR‐367, miR‐133a, miR‐133b, miR‐133, miR‐181c, miR‐1192, and miR‐883, miR‐30

Liang et al. (2007), Chen et al. (2009), Li et al. (2010), Malizia and Wang (2011), Das et al. (2012), and Guo et al. (2014)

Kidney

miR‐204, miR‐215, miR‐216, miR‐200a, miR‐196a, miR‐196b, miR‐10a, miR‐10b, miR‐146a, miR‐30c, miR‐204, miR449c‐5p and miR‐449b‐5p

Sun et al. (2004), Akkina and Becker (2011), Guo et al. (2014), Schena et al. (2014), and Ludwig et al. (2016)

expression and its downstream protein, apoptosis repressor with caspase recruitment domain (ARC), to promote pyroptosis (pro‐inflammatory programmed cell death) (Li et al., 2014d). Isoproterenol‐induced cardiotoxicity is associated with mitochondrial dysfunction in cardiomyocytes (Mukherjee et al., 2015). In rats treated with isoproterenol, consistent elevations of plasma miR‐208 levels were observed as early as 24 h post‐dose, which is much earlier than significant increases in cTn concentrations, suggesting great promise as an early biomarker of cardiotoxicity. In addition, increased miR‐208 was also observed, following repeated exposure of rats to isoproterenol, with chronic lesions also observed in rat hearts (fibrosis) (Nishimura et  al., 2015). In a similar study, miR‐208 was validated as a sensitive biomarker of isoproterenol‐induced cardiac injury in superoxide dismutase‐2 (Sod2(+/−) and C57BL/6J wild‐type mice (Liu et al., 2014a). Doxorubicin‐induced cardiotoxicity has also been associated with mitochondrial toxicity (Ichikawa et  al., 2014). Doxorubicin‐induced cardiotoxicity (apoptosis of cardiomyocytes) is associated with upregulation of cardiac‐specific miR‐208, which targets GATA4. Therapeutic silencing of miR‐208a restored GATA4 levels and also attenuated doxorubicin cardiotoxicity in Balb/C mice (Tony et al., 2015). Increased levels of miRNA‐532‐3p are also reported in doxorubicin‐induced cardiotoxicity. MiRNA‐532‐3p targets apoptosis repressor with caspase recruitment domain (ARC) and regulates mitochondrial fission (Wang et  al., 2015a). In addition, differential expression of several miRNAs with biological relevance

to cardiomyocyte function including miR‐34a, miR‐34b, miR‐187, miR‐199a, miR‐199b, miR‐146a, miR‐15b, miR‐130a, miR‐214, and miR‐424 is reported in doxorubicin‐treated human cardiomyocytes (Holmgren et  al., 2016). In a similar study, differential deregulation of multiple miRNAs including miR‐187‐3p, miR‐182‐5p, miR‐486‐3p, miR‐486‐5p, miR‐34a‐3p, miR‐4423‐3p, miR‐34c‐3p, miR‐34c‐5p, and miR‐1303 was observed in human iPSC‐derived cardiomyocytes during doxorubicin toxicity earlier than increases in other cytotoxicity markers such as lactate dehydrogenase (LDH) (Chaudhari et  al., 2016). These results suggested great potential for the use of these miRNAs as sensitive early biomarkers of cardiotoxicity and in some cases the associated mitochondrial toxicity. 22.8.2

Kidney

The kidneys are a common target organ for xenobitic‐ induced toxicities. miRNA changes associated with kidney injury are of great interest because urine can be easily analyzed for noninvasive biomarkers such as miRNAs. Kidney‐specific miRNA changes are associated with renal dysfunction as well as toxicity. In rats, aristolochic acid I (AAI)‐induced acute kidney injury (AKI) is associated with increases in plasma miR‐21‐3p preceding the increase in conventional kidney injury markers such as blood urea nitrogen (BUN) and creatinine (Pu et  al., 2017). Hence, miR‐21‐3p has been suggested as a potential early biomarker for AKI in rats. Similarly, in a cisplatin‐induced AKI rat model, significant increases in miR‐146b were observed at a much earlier time point

MiRNA as Biomarkers of Mitochondrial Toxicity

than changes in creatinine and BUN levels. These results have been further confirmed under in vitro conditions with increased miR‐146b following cisplatin treatment of kidney tubular epithelial cells (Zhu et al., 2016). In addition, enhanced cisplatin toxicity was observed in miR‐155 deficient mice (Pellegrini et al., 2014). In AKI, patient miRNA profiling in urine samples revealed significant increases in miR‐21, miR‐200c, and miR‐423 levels and significant decreases in miR‐4640 levels compared with non‐AKI patients, suggesting potential application of these miRNAs as diagnostic as well as prognostic markers of AKI (Ramachandran et al., 2013). Increased miR‐218 is associated with high glucose‐related podocyte injury in a mouse diabetic nephropathy model. MiR‐218 targets heme oxygenase to promote glucose‐induced apoptosis of mouse podocytes (Yang et  al., 2016). MiR‐21 upregulation was reported in multiple chronic fibrotic renal disease and experimental rat and mouse models of diabetic nephropathy with a positive correlation between the severity of fibrosis and rate of decreased renal function (McClelland et  al., 2015). MiR‐21 targets PTEN and SMAD7 and promotes accumulation of extracellular matrix and renal fibrosis in diabetic nephropathy (McClelland et al., 2015). MiR‐21 is considered a central regulator of metabolic activity in the kidneys. Increased expression of miR‐21 is reported in both acute and chronic kidney diseases in animal models as well as in human kidney tissue samples (Zarjou et  al., 2011; Kole et  al., 2012). Upregulation of miR‐21 suppresses multiple genes involved in mitochondrial biogenesis and promotes fibrosis and organ dysfunction in the kidneys (Gomez et  al., 2016). MiR‐155 and miR‐ 146a levels are increased in diabetic nephropathy animal models as well as in diabetic nephropathy patients and correlated with inflammation‐mediated injury to  glomerular endothelial cells (Huang et  al., 2014). High glucose‐related increases in TNF‐α, TGF‐β1, and NF‐κB, expression consequent to increased miR‐155 and miR‐146a levels, in human renal glomerular endothelial cells further support the in vivo findings (Huang et al., 2014). 22.8.3

Liver

MiR‐122 has been reported to be highly tissue specific and is the most abundant miRNA in liver. MiR‐122 plays a key role in the regulation of lipid and glucose metabolism and is considered to be a novel biomarker for metabolic diseases (Willeit et al., 2016). This miRNA has also been associated with mitochondrial function through its role in lipid metabolism (Jin et  al., 2014) and has been considered to have ideal properties for use as a systemic biomarker of liver toxicity including good stability, tissue

specificity (Parkinson et al. 2013), and ease of detection in multiple species (Sharapova et  al., 2016). Systemic release of miR‐122 has been successfully used as a biomarker of general liver toxicity without regard to mitochondrial involvement (Laterza et  al., 2009; Sharapova et al., 2016); however, alterations in tissue miR‐122 may prove useful for detection of mitochondrial effects in the liver preclinically. MiR199a‐5p has an important role in mitochondrial activity and mitochondrial β‐oxidation and lipid metabolism in liver. Increased expression of miR199a‐5p has been observed in liver samples from nonalcoholic fatty liver disease (NAFLD) patients, as well as in obese db/db mice fed a high fat diet (Li et  al., 2014a). Increased miR199a‐5p was associated with decreases in caveolin (CAV1) and PPARα, suggesting that miR199a‐5p impairs FA β‐oxidation in hepatocyte mitochondria that is mediated by CAV1 and the PPARα. 22.8.4

Brain/Nerve

Increased levels of brain‐specific miR‐338 have been associated with mitochondrial dysfunction, reduced mitochondrial metabolic activity, and decreased ATP production in neuronal tissue (Wienholds et  al., 2005; Aschrafi et al., 2008). MiR‐338 targets the cytochrome c oxidase IV (COXIV) gene, which codes for a critical protein within the electron transport chain. Dysregulation of mitochondrial biogenesis (fission) is often associated with brain disorders, which implicate other miRNAs associated with mitochondrial fission as potential biomarkers of effects in brain as well (Yang et  al., 2006; Edwards et al., 2010).

22.9 Work to Date Using MiRNA as Biomarkers of Mitochondrial Toxicity Several studies mentioned previously have identified candidate tissue‐specific miRNA biomarkers of organ toxicity that are, in some cases, associated with the regulation of mitochondrial function; however, only one study has been conducted to date using known mitochondrial toxicants specifically to identify miRNA biomarkers associated with mitochondrial toxicity and dysfunction (Baumgart et al., 2016). In this work, Sprague Dawley rats were dosed daily with the prototypical mitochondrial toxicants rotenone (respiratory complex I inhibitor) and 3‐nitropropionic acid (3NP) (respiratory complex II inhibitor) for 1 week (Baumgart et al., 2016). Changes in miRNAs associated with mitochondrial function were assessed in the kidney, skeletal muscle,

359

360

Mitochondrial Dysfunction by Drug and Environmental Toxicants

and serum. Interestingly, changes in the levels of identified miRNA preceded the formation of any histological lesions and generally correlated with decreases in mitochondrial copy number. miRNA changes in the tissues of animal models, related to mitochondrial toxicity, may offer the greatest opportunity to detect very early biomarkers of mitochondrial dysfunction. In addition, as knowledge of mitomiR functions grows, the pattern of changes in mitochondrial miRNA may be interpretable for the specific mechanism(s) of dysfunction, just as patterns of gene (mRNA) expression change are often used to decipher mechanisms of toxicity in target tissues of xenobiotics. With the natural evolution of technology from microarray to RNA‐Seq evaluations, this lays a foundation for the collection and management of miRNA‐rich datasets and for interpretations in the context of histology and gene expression changes. 22.9.1

Kidney

MiR‐338‐5p is associated with mitochondrial dysfunction such as increased ROS production with loss of membrane potential and decreased ATP synthesis. In the Baumgart et al. (2016) study, dose‐dependent induction of miR‐338‐5P was observed in the kidneys of rats treated with the mitochondrial toxicants rotenone and 3NP (Baumgart et al., 2016). The magnitude of increased miR‐338‐5p was higher in the kidneys of rotenone than 3NP‐treated rats, and this change was also detectable in serum samples from those animals suggesting miR‐ 338‐5‐p as potential systemic biomarker of mitochondrial toxicity in kidneys (Baumgart et al., 2016). Two other mitomiRs were altered in the kidneys of treated animals in this study. MiR‐202‐3p is associated with apoptotic cell death and inhibition of Bcl‐2 (Zhao et al., 2013) and was shown to be significantly decreased in the kidneys of rats treated with rotenone as well (Baumgart et al., 2016). In addition, miR‐546 appears to be another potential marker of mitochondrial toxicity in the kidney as it was dose‐dependently downregulated in the kidneys of rats treated with rotenone (Baumgart et al., 2016). MiR546 has been linked to changes in membrane potential and levels of ROS in mitochondria (Wu et al., 1999; Fan et al., 2004). 22.9.2

Skeletal Muscle

MiR‐122 has been repeatedly reported to be a liver‐specific miRNA, as discussed previously in this chapter, with a role in controlling mitochondrial function (Lewis and Jopling, 2010; Filipowicz and Grosshans, 2011; Qiao et al., 2011). MiR‐122 expression has also been strongly linked to mitochondrial damage (Burchard et al., 2010).

In the Baumgart et al. (2016) study, both rotenone and 3NP treatments of Sprague Dawley rats resulted in profound upregulation (up to 390‐fold) of miR‐122 in the skeletal muscle of treated rats (Baumgart et  al., 2016). Induction of miR‐122 was dose dependent for both mitochondrial toxicants, supporting the relationship of this induction with mitochondrial toxicity. In addition, miR‐122 induction was greatest with 3NP treatments, in which mitochondrial copy number was also decreased to the greatest extent. Interestingly, despite the massive increases in miR‐122 in skeletal muscle tissue, no significant changes were detected in serum, suggesting that this miRNA may not be readily released into the systemic circulation during miR‐122 induction in skeletal muscle, as has been established in cases of liver toxicity where this miRNA is constitutively expressed. This may also be not only due to the early stage of toxicity, which preceded the observation of histologic changes, but also correlated with decreases in mitochondrial copy number. In extrahepatic tissues, miR‐122 induction within tissues would make a potentially outstanding biomarker of mitochondrial toxicity because of its lack of constitutive expression. It is plausible that it would be released as lesions form and may represent a valid biomarker for mitochondrial toxicity with the confounding complication of potential interference due to hepatotoxicity unrelated to mitochondrial toxicity. Evaluating tissue miRNA levels would obviously be best suited to a preclinical setting because of the invasiveness of sample collection. MiR‐546 levels were also significantly increased in the skeletal muscle of both rotenone‐ and 3NP‐treated rats (Baumgart et  al., 2016). Because this study reported miR‐546 alterations in both the kidney and skeletal muscle, this may represent a mitochondrial toxicity biomarker that can be used across tissues. 22.9.3

Serum

The only serum miRNAs associated with mitochondrial function, in the Baumgart study, that were significantly altered by the treatment of rats with rotenone and 3NP were miR‐34c and miR‐338‐5p (Baumgart et al., 2016). Interestingly, 3NP treatment significantly reduced and rotenone significantly increased serum levels of both miRNAs. This may be reflective of compensatory induction versus significant toxicity and loss of mitochondria. There were differences in the levels of mitochondrial toxicity between the two toxicants that are supportive of this conclusion. In addition, rotenone is a reversible inhibitor of mitochondrial respiration (Complex I), whereas 3NP is an irreversible respiratory inhibitor of Complex II. Fold changes in this study were substantial with decreases in 3NP‐treated animals reaching −7.7‐ fold and increases in rotenone treated rats reaching

MiRNA as Biomarkers of Mitochondrial Toxicity

+21.1‐fold. In concordance, 3NP‐treated rats had greater and more consistent decreases in mitochondria numbers (copy number) in both the kidney and skeletal muscle. Compensatory changes in the case of rotenone treatment, with reversal related to mitochondrial losses with 3NP treatment, are the most likely explanation of the differences in direction of effects reported. These have been the first evidence of serum miRNA biomarkers of mitochondrial toxicity reported. Both MiR‐34c and MiR‐338‐5p have been linked to ROS production and loss of mitochondrial membrane potential (Aschrafi et al., 2008, 2012). These molecular responses are consistent with mitochondrial toxicants inhibiting oxidative phosphorylation such as rotenone and 3NP. Clinically, serum biomarkers have the greatest potential for monitoring and identifying drugs that act as mitochondrial toxicants for reasons of invasiveness and ease of collection. If mitochondrial toxicants can be identified before significant depletion occurs, dosing can be stopped prior to lesion formation and irreversible tissue damage occurs in patients or healthy volunteers. MiRNA represent a plausible opportunity to find biomarkers of this serious toxicity.

22.10

Future Work Needed

The identification and characterization of miRNA biomarkers associated mitochondrial toxicity is still in its infancy as discussed throughout this chapter. To this point a single study has been reported attempting to identify some original candidate miRNA associated specifically with mitochondrial toxicity as described earlier (Baumgart et  al., 2016). This work focused on miRNA changes in only two mitochondrially rich tissues (kidney and skeletal muscle) and serum. Additional work is needed to examine miRNA changes in other tissues, particularly mitochondrially rich tissues, such as the heart, liver, and brain, as well as other matrices such as urine, bile, lymph, saliva, and so on. Other tissues may also be appropriate for study of mitomiR biomarkers based on exposure levels, sensitivity, metabolite formation, or other factors. Additional work is also needed to better understand the different miRNA biomarkers associated with various mechanisms of mitochondrial toxicity. With the identification of many tissue‐specific or tissue‐enhanced miRNAs, and many of those with ties to mitochondrial function, it may also be possible to identify miRNA biomarkers associated with mitochondrial toxicity from specific tissues in time. Based on the effects of known mitomiRs that have already been identified, miRNAs are involved in regulating the expression of mitochondrial proteins involved in a diverse array of functions. Likely,

others are yet to be elucidated, and continued efforts in this regard are clearly needed. The identification of additional roles for miRNA is needed and will continue to shed light on the roles of miRNA on mitochondrial function. This information will likely lead to the discovery of additional potential miRNA biomarkers of mitochondrial toxicities. A role for the mitochondria in miRNA storage has been proposed, but additional work is needed to confirm this and  define the role this might fulfill. With reports of miRNAs being deposited within the intermembrane space, it is possible that these miRNA play a role of some sort during apoptotic signaling as they would be released into the cytosol along with cytochrome c during MPT or  pore formation via bax family members (Li et  al., 2008). During MPT, the inner membrane swells to capacity after opening of the permeability transition pore and fluid influx. Because the outer membrane is smaller than the convoluted inner membrane, it lyses and releases the  contents of the intermembrane space including cytochrome c, which binds the apoptosome and activates caspases 3, 7, and 9 causing apoptosis (Jiang and Wang, 2000). One of the significant gaps in our current knowledge is  how exactly miRNAs are transported into the mitochondria. Transport appears to be ATP related. Energy‐ dependent transporters of nucleosides have been identified and characterized in the mitochondria, and their role in the uptake of nucleosides and nucleoside analogues is well known (Govindarajan et  al., 2009). Likely candidates for transport of miRNA into mitochondria include those already described for the transport of nuclear mRNA (Entelis et al., 2001). Others have been suggested previously in this chapter and include porins/VDAC (Bandiera et  al., 2013), AGO2 (Bandiera et al., 2011), TIM and TOM complexes (Bandiera et al., 2011), and PNPT1/PNPASE (Wang et al., 2010). Ideally the mitomiR biomarker would be exported from the mitochondria and into the systemic circulation during injury, whether as a result of toxicity or as a compensatory reaction to functional deficit. Extracellular release would obviously be an earlier event than release due to cell death and lysis. Detecting effects on function, prior to the irreversible stage of cell death, provides opportunity to stop dosing (in the case of environmental exposures) or remove from exposure to protect affected tissues and allow for recovery. Data analyses of mitochondrial RNA should take into account the proper normalizations for any gene expression analyses. These normalizations include corrections of RNA loading via a housekeeping gene and normalization to a control group or unexposed population. To avoid bias due to amplification efficiency, amplicons of a  similar size to miRNA should be used and similar

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amplification efficiencies confirmed between target and housekeeping gene/miRNA. A reasonable approach is to use the U6 snRNA, a commonly used reference transcript, as a housekeeping gene (Hu et  al., 2012). Other housekeeping miRNAs may be identified in the future that are suitable for normalization. When a miRNA standard is available for generation of a standard curve, absolute quantitation is an option. If this approach is taken, care must be exercised to use excellent PCR hygiene practices to avoid carryover contamination of test samples (Aslanzadeh, 2004). If a control (predose) or untreated reference is available, relative quantitative analyses is an excellent option. By including the second normalization to a control, a relative quantity or fold‐ change value can be calculated relatively simply as follows (Baumgart et al., 2016): Ct (Ct target mitomiR treated tissue Ct U 6 snRNA treated tissue ) (Ct target mitomiR control tissue Ct U 6 snRNA control tissue ) Relative quantity 2 Ct Considering species‐to‐species variation in miRNA expression and response to toxicants, including mitochondrial toxicants, the evidence seems to point to conservation of function for many miRNAs. It is important to consider that this is not universally the case and additional work is needed in this area. Bioinformatic predictions, in conjunction with microarray analysis and sequence‐directed cloning, have identified several human miRNAs that are not conserved beyond primates (Bentwich et  al., 2005). The extent to which tissue‐ specific miRNA abundance is conserved across species is another important question to understand when considering the translatability of miRNA biomarkers. Even though a conserved tissue‐specific abundance pattern between human and rodents is shown for multiple miRNAs such as miR‐133B, miR‐124, and miR‐9 (Ludwig et  al., 2016), understanding differences for other miRNAs and in other species commonly used for toxicity evaluation is going to be critical for the further expansion of miRNA use as biomarkers, including biomarkers of mitochondrial toxicity. Higher mutation rates and accelerated evolution of the mitochondrial DNA in animal species may contribute to considerable differences in the mitochondrial DNA sequences between closely related species (Yang et al., 2014). Hence mitomiRs, specifically mitochondrial DNA encoded miRNA, may also vary between the species. Sex‐related variations in miRNA expression and/or tissue abundance patterns are another factor, which may influence interpretation of miRNA data in toxicity.

Investigation of intrinsic variability of circulating miRNA in healthy human males and females revealed differential expression with 63–95% higher levels of miRNAs such as hsa‐miR‐548‐3p, hsa‐miR‐1323, and hsa‐miR‐940 in females compared with those in males (Duttagupta et al., 2011). Similarly, slightly higher serum levels of miR‐130b and miR‐18b have been reported in males compared with those in females (Wang et al., 2012b). Hence, a difference in the miRNA profiles between individuals due to sex is another important factor to consider. Sex‐related differences in cellular metabolism are also well documented. Substantial gender‐specific differences in mitochondrial function such as mitochondrial fusion/fission (Arnold et al., 2008), mitochondrial membrane potential and respiration (Weis et al., 2012; Demarest et al., 2016), and mitochondrial gene expression (Vijay et  al., 2015) suggest that mitomiR profiles may also be influenced by gender. However, there is currently a gap in understanding the differential expression profile of mitochondrial function associated miRNAs in males and females and their response to toxicants.

22.11

Conclusions

Despite the early state of the science of using mitomiRs as biomarkers of mitochondrial dysfunction and toxicities, the key role of miRNA in mitochondrial function offers promise. The need for biomarkers of mitochondrial toxicants is clearly high, particularly for assessing mechanisms of toxicity for pharmaceuticals. Such markers would be invaluable as screens for compounds that could potentially impair mitochondrial function or result in direct mitochondrial toxicity. Because of the  delayed nature of mitochondrial toxicant effects in  humans consuming drugs with this adverse profile, these toxicities often go undetected until prolonged exposures have been reached (Julie et al., 2008). In some cases, delayed mitochondrial toxicities manifest clinically sometime after treatments have been discontinued (Julie et al., 2008). The information presented here has given researchers an up‐to‐date summary of work in the area of miRNA use for assessing mitochondrial toxicants. More importantly, there has been considerable information collected to point researchers toward other potential miRNA biomarkers of mitochondrial toxicity that be explored. The gaps in knowledge needed to advance this science have also been presented to guide those interested in contributing to the realization of establishing biomarkers of mitochondrial toxicities. It is our hope that this information will be of use in  guiding efforts in the important area of biomarker

MiRNA as Biomarkers of Mitochondrial Toxicity

discovery. The applications of success may not be limited to screening patients in clinical trials or on medications. Translation of biomarkers to human industrial or envi-

ronmental exposures of chemicals or translations to other species in an environmental setting may eventually be possible as well.

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23 Biomarkers of Mitochondrial Injury After Acetaminophen Overdose: Glutamate Dehydrogenase and Beyond Benjamin L. Woolbright and Hartmut Jaeschke Department of Pharmacology, Toxicology & Therapeutics, University of Kansas Medical Center, Kansas City, KS, USA

CHAPTER MENU 23.1 Introduction, 373 23.2 Acetaminophen Overdose as a Model for Biomarker Discovery, 373 23.3 Acetaminophen Overdose: Mechanisms of Toxicity in Mice and Man, 374 23.4 Biomarkers of Mitochondrial Injury, 375 23.5 Conclusions, 379 References, 379

23.1

Introduction

In the drug discovery process, drug‐induced liver injury is one of the most common reasons for failure in preclinical development and in clinical trials. In addition, idiosyncratic hepatotoxicity leads to black box warnings or even withdrawal of approved drugs from the market. Whereas currently used biomarkers for liver injury (alanine (ALT) and aspartate aminotransferases (AST)) and dysfunction (bilirubin) are sufficiently sensitive to detect dose‐dependent hepatotoxins, there are no biomarkers available that could alert to a potential idiosyncratic toxicity. Clinically, acetaminophen (APAP) overdose remains the most common source of both drug‐induced liver injury and acute liver failure (ALF) (Lee, 2013). Patients that develop ALF have a very poor outcome, with mortality up to 50% (Lee, 2013). Early identification of which patients will proceed to ALF is critical, as these patients can be treated more aggressively or listed for transplantation earlier. As such, biomarkers of patient outcome are of considerable clinical value for determining early during the patient’s hospitalization which patients will proceed to ALF and will die or need a liver transplant and which patients will recover spontaneously. The best biomarkers are those that are also informative of the mechanisms at play in the pathophysiology or valuable clinically due to prognostic capacity. Biomarkers

present in the serum or urine of patients are of the most interest and the greatest use. Many of these serum and urine biomarkers have a single point of origin in tissue and thus accurately reflect what is happening in these tissues, in a mechanistic fashion, without the need for biopsy. A number of these “mechanistic biomarkers” have recently been a source of focus in the literature, and considerable research has gone into fully investigating these compounds (Antoine et al., 2012; McGill et al., 2012; Luo et al., 2014; McGill and Jaeschke, 2014; Beger et al., 2015). Release of many of these mechanistic biomarkers can be traced back to damage of the mitochondria, and thus considerable progress has recently been made in the field of biomarkers of mitochondrial damage. The purpose of this chapter will be to define these markers and discuss their clinical viability and basic science relevance with regard to the murine APAP hepatotoxicity model and human patients with APAP overdose.

23.2 Acetaminophen Overdose as a Model for Biomarker Discovery A number of mitochondrial biomarkers have been established for liver disease. Many of these were originally defined in the murine APAP overdose model (reviewed in McGill and Jaeschke, 2014). This model is convenient

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume I, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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for biomarker discovery for a number of reasons: (i) it is technically simple and highly repeatable, (ii) the mechanisms associated with the model are largely well delineated, and (iii) it is a clinically relevant murine model with high fidelity to the human condition (McGill et al., 2012; Jaeschke et  al., 2014, Jaeschke, 2015). We will briefly discuss the APAP overdose model as it relates to mitochondrial dysfunction and subsequent cell death. This is not a complete overview of the understood mechanisms of APAP (for a more complete, updated overview: Ramachandran and Jaeschke, 2017; Woolbright and Jaeschke, 2017), but rather a version focused on the pathology associated with the mitochondria.

23.3 Acetaminophen Overdose: Mechanisms of Toxicity in Mice and Man 23.3.1 Drug Metabolism and Protein Adducts APAP is an over‐the‐counter analgesic and antipyretic. Normally, greater than 85% of an APAP dose is conjugated to either UDP‐glucuronide or sulfate and excreted via phase II metabolism (McGill and Jaeschke, 2013). Therapeutic doses are safe; however, an overdose of APAP partially overwhelms phase II metabolism and results in substantial oxidation of APAP to the reactive metabolite N‐acetyl‐p‐benzoquinone imine (NAPQI) (Dahlin et al., 1984), which is a reactive electrophile that covalently adducts cellular proteins causing oxidative stress in the cell (Dahlin et al., 1984) and is largely detoxified through a spontaneous reaction with the endogenous antioxidant glutathione (GSH) (Mitchell et  al., 1973). This results in the depletion of cellular GSH levels in the liver. GSH depletion is currently used as a hallmark for measuring APAP metabolic activation experimentally (McGill and Jaeschke, 2013). The interaction between NAPQI and GSH is also the basis for the current gold‐standard therapeutic, N‐acetylcysteine (NAC), which is a precursor for GSH synthesis. The newly formed GSH can scavenge NAPQI (Corcoran and Wong, 1986) and later detoxify reactive oxygen and peroxynitrite (Knight et  al., 2002). During this metabolism and GSH depletion, NAPQI begins to adduct sulfhydryl groups on proteins forming acetaminophen–cysteine (APAP–CYS) adducts (Pumford et  al., 1989), which have  been proposed as a diagnostic indicator of APAP overdose in patients (Roberts et al., 2017). Levels above 1 μM of APAP–CYS in serum are associated with liver toxicity, although recent data indicate APAP–CYS adducts may be released even at therapeutic doses when patients do not have any liver toxicity (Heard et al., 2011;

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Rossiter HB. Exercise: kinetic considerations for gas exchange. Compr Physiol 1: 203–244, 2011. Saks V, Guzun R, Timohhina N, Tepp K, Varikmaa M, Monge C, Beraud N, Kaambre T, Kuznetsov A, Kadaja L, Eimre M, and Seppet E. Structure‐function relationships in feedback regulation of energy fluxes in vivo in health and disease: mitochondrial interactosome. Biochim Biophys Acta 1797: 678–697, 2010. Sala E, Roca J, Marrades RM, Alonso J, Gonzalez De Suso JM, Moreno A, Barbera JA, Nadal J, de Jover L, Rodriguez‐Roisin R, and Wagner PD. Effects of endurance training on skeletal muscle bioenergetics in chronic obstructive pulmonary disease. Am J Resp Crit Care Med 159: 1726–1734, 1999. Schmid AI, Schrauwen‐Hinderling VB, Andreas M, Wolzt M, Moser E, and Roden M. Comparison of measuring energy metabolism by different 31P‐magnetic resonance spectroscopy techniques in resting, ischemic, and exercising muscle. Magn Reson Med 67: 898–905, 2012. Schmitz JP, Jeneson JA, van Oorschot JW, Prompers JJ, Nicolay K, Hilbers PA, and van Riel NA. Prediction of muscle energy states at low metabolic rates requires feedback control of mitochondrial respiratory chain activity by inorganic phosphate. PLoS One 7: e34118, 2012. Sleigh A, Savage DB, Williams GB, Porter D, Carpenter TA, Brindle KM, and Kemp GJ. 31P magnetization transfer measurements of Pi‐‐>ATP flux in exercising human muscle. J Appl Physiol 120: 649–656, 2016. Stratton JR, Dunn JF, Adamopoulos S, Kemp GJ, Coats AJ, and Rajagopalan B. Training partially reverses skeletal muscle metabolic abnormalities during exercise in heart failure. J Appl Physiol 76: 1575–1582, 1994. Taivassalo T, Shoubridge EA, Chen J, Kennaway NG, DiMauro S, Arnold DL, and Haller RG. Aerobic conditioning in patients with mitochondrial myopathies: physiological, biochemical, and genetic effects. Ann Neurol 50: 133–141, 2001. Takahashi H, Inaki M, Fujimoto K, Katsuta S, Anno I, Niitsu M, and Itai Y. Control of the rate of phosphocreatine resynthesis after exercise in trained and untrained human quadriceps muscles. Eur J Appl Physiol 71: 396–404, 1995. Taylor DJ, Kemp GJ, and Radda GK. Bioenergetics of skeletal muscle in mitochondrial myopathy. J Neurol Sci 127: 198–206, 1994. Taylor DJ, Kemp GJ, Thompson CH, and Radda GK. Ageing: effects on oxidative function of skeletal muscle in vivo. Mol Cell Biochem 174: 321–324, 1997. Thompson CH, Kemp GJ, Sanderson AL, and Radda GK. Skeletal muscle mitochondrial function studied by kinetic analysis of postexercise phosphocreatine resynthesis. J Appl Physiol 78: 2131–2139, 1995.

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Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants Volume II

Edited by

Yvonne Will, PhD, ATS Fellow Pfizer Drug Safety R&D, Groton, CT, USA

James A. Dykens Eyecyte Therapeutics Califormia, USA

This edition first published 2018 © 2018 John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions. The right of Yvonne Will and James A. Dykens to be identified as the editors of this work has been asserted in accordance with law. Registered Office John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA Editorial Office 111 River Street, Hoboken, NJ 07030, USA For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com. Wiley also publishes its books in a variety of electronic formats and by print‐on‐demand. Some content that appears in standard print versions of this book may not be available in other formats. Limit of Liability/Disclaimer of Warranty In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of experimental reagents, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each chemical, piece of equipment, reagent, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Library of Congress Cataloging‐in‐Publication Data Names: Will, Yvonne, editor. | Dykens, James Alan, 1951– editor. Title: Mitochondrial dysfunction caused by drugs and environmental toxicants / edited by Yvonne Will, James A. Dykens. Description: Hoboken, NJ : John Wiley & Sons, 2018. | Includes bibliographical references and index. | Identifiers: LCCN 2017046043 (print) | LCCN 2017048850 (ebook) | ISBN 9781119329732 (pdf ) | ISBN 9781119329749 (epub) | ISBN 9781119329701 (cloth) Subjects: LCSH: Drugs–Toxicology. | Mitochondrial pathology. Classification: LCC RA1238 (ebook) | LCC RA1238 .M58 2018 (print) | DDC 615.9/02–dc23 LC record available at https://lccn.loc.gov/2017046043 Cover Design: Wiley Cover Image: Courtesy of Sylvain Loric Set in 10/12pt Warnock by SPi Global, Pondicherry, India Printed in the United States of America 10

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Contents List of Contributors xiii Foreword xxv

Part 4

Reports from the Clinic

457

30

Statin and Fibrate‐Induced Dichotomy of Mitochondrial Function 459 Viruna Neergheen, Alex Dyson, Luke Wainwright, and Iain P. Hargreaves

30.1 30.2 30.3 30.4 30.5 30.5.1 30.5.2 30.5.3 30.5.4 30.5.5 30.5.6 30.6 30.7 30.8 30.9

Introduction 459 Statins 460 Effect of Statin Treatment on Endogenous CoQ10 Status 460 Effect of Statin Treatment on Cerebral CoQ10 Status 462 Effect of Statin Treatment on Oxidative Phosphorylation 463 Impairment of Isoprenylation 463 Uncoupling Oxidative Phosphorylation 464 Direct Interaction with the Enzyme Complexes of the Oxidative Phosphorylation System 464 Oxidative Stress 465 Statin Lactones 465 Mitochondrial Biogenesis 466 Fibrates 467 The Effect of Fibrate Treatment on Mitochondrial Respiratory Chain Function 467 Fibrates in the Treatment of Oxidative Phosphorylation Defects 468 Conclusion 469 References 469

31

Friend or Foe: Can Mitochondrial Toxins Lead to Similar Benefits as Exercise? 475 Sofia Annis, Adeel Safdar, Eduardo Biala, Ayesha Saleem, Housaiyin Li, Priya Gandhi, Zoe Fleischmann, Carmen Castaneda‐Sceppa, Jonathan L. Tilly, Dori C. Woods, and Konstantin Khrapko

31.1 31.2 31.3

Beneficial Effects of ROS and Mitotoxin Exposure 475 Window of Opportunity for ROS and Mitotoxins: Low Concentration and Short Time 476 Endurance Exercise, a Greatly Beneficial, Transient ROS‐Generating Activity, Causes Translocation of p53 to Mitochondria 477 Mild Exposure to Mitochondrial Toxins In Vitro Recapitulates a Beneficial Endpoint of Endurance Exercise (Translocation of p53 to Mitochondria) 477 Progeroid mtDNA Mutator Mouse: A Test Ground for the Similarity between the Effects of Mitotoxin Exposure and Exercise 478 Mutational Analysis Hints Existence of the “Good” and the “Bad” mtDNA and Evokes Alternative Hypotheses 478 Mitotoxins May Ameliorate Accumulation of mtDNA Damage by Alteration of Mitochondrial Dynamics and Activation of Mitophagy Resulting in Removal of the “Bad” Mitochondria 479 Mitotoxins May Ameliorate Accumulation of mtDNA Damage by Activating Mitochondria‐Derived Vesicle Trafficking and/or by Formation of Mitochondrial Spheroids 480

31.4 31.5 31.6 31.6.1 31.6.2

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31.7 31.8

Ab Absurdo: Lack of Exercise May Result in Increased Damage 480 Conclusions, Disclaimers, and Perspectives 480 Acknowledgments 481 References 481

32

Involvement of Mitochondrial Dysfunction on the Toxic Effects Caused by Drugs of Abuse and Addiction 487 Daniel José Barbosa, João Paulo Capela, Maria de Lourdes Bastos, and Félix Carvalho

32.1 32.2 32.3 32.4 32.5 32.6 32.7 32.8

Introduction 487 The Tricarboxylic Acid Cycle as a Target Pathway 488 Effects on the Mitochondrial Electron Transport Chain 490 Drugs of Abuse Might Target Mitochondrial Biogenesis 493 Mitochondrial Quality Control and Drugs of Abuse 495 Mitochondrial Fusion/Fission Equilibrium Is Affected by Drugs of Abuse 496 Mitochondrial Distribution under the Influence of Drugs of Abuse 498 Concluding Remarks 501 References 501

33

Drug‐Induced Mitochondrial Toxicity during Pregnancy 509 Diana Luz Juárez-Flores, Ana Sandra Hernández, Laura Garcia, Mariona Guitart‐Mampel, Marc Catalán‐Garcia, Ingrid González‐Casacuberta, Jose César Milisenda, Josep Maria Grau, Francesc Cardellach, Constanza Morén, and Glòria Garrabou

33.1 33.2 33.2.1

Mitochondria in Human Fertility 510 Mitochondrial Toxicity in Human Pregnancy 510 Risk Categories of Mitochondrial Toxic Drugs According to their Capacity to Cause Birth Defects during Pregnancy 510 Clinical Spectrum of Mitochondrial Toxicity during Pregnancy 512 Classes of Mitochondrial Toxic Drugs Administered during Pregnancy 512 Antibiotics 512 Antidepressants 513 Antipsychotics 514 Nonsteroidal Anti‐inflammatory Drugs (NSAIDs) 514 Antiepileptics 514 Local Anesthetics 514 Antivirals 514 Antifungals 515 Antiarrhythmics 515 Therapeutic Approach of Drug‐Induced Mitochondriopathies 515 Conclusions 516 Funding 516 References 517

33.2.2 33.2.3 33.2.3.1 33.2.3.2 33.2.3.3 33.2.3.4 33.2.3.5 33.2.3.6 33.2.3.7 33.2.3.8 33.2.3.9 33.3 33.4

34

Mitochondrial Toxicity in Children and Adolescents Exposed to Antiretroviral Therapy 521 Antoni Noguera‐Julian, Eneritz Velasco‐Arnaiz, and Clàudia Fortuny

34.1 34.2 34.3

Introduction 521 Mitochondrial Toxicity in Children and Adolescents Infected with HIV 522 Mitochondrial Toxicity in HIV‐Uninfected Infants That Were Perinatally Exposed to Antiretrovirals 524 References 525

35

Drug‐Induced Mitochondrial Cardiomyopathy and Cardiovascular Risks in Children 529 Neha Bansal, Mariana Gerschenson, Tracie L. Miller, Stephen E. Sallan, Jason Czachor, Hiedy Razoky, Ashley Hill, Miriam Mestre, and Steven E. Lipshultz

35.1 35.2

Introduction 529 HIV Therapy 529

Contents

35.3 35.4

Cancer Therapy 533 Conclusion 538 Funding 539 References 539

36

Role of Mitochondrial Dysfunction in Linezolid‐Induced Lactic Acidosis 547 Alessandro Santini, Dario Ronchi, Daniela Piga, and Alessandro Protti

36.1 36.2 36.3 36.4 36.5 36.6 36.7 36.8 36.9 36.10

Mechanisms Responsible for Lactic Acidosis in Critically Ill Subjects 548 Mechanisms Responsible for Tissue Hypoxia in Critically Ill Subjects 548 Relationship between Lactic Acidosis and Oxygen‐Derived Variables 548 Incidence and Risk Factors of Linezolid‐Induced Lactic Acidosis 549 Relationship between Linezolid‐Induced Lactic Acidosis and Oxygen‐Derived Variables 552 Mitochondrial Ribosomes and Translation 552 How Linezolid Exerts its Therapeutic—and Toxic—effects 553 Mitochondrial DNA Polymorphisms and Susceptibility to Linezolid 553 Mitochondrial Toxicity of Linezolid 555 Conclusion 555 References 556

37

Metformin and Lactic Acidosis Jean‐Daniel Lalau

37.1 37.2 37.3 37.4

Introduction 559 Metformin‐Induced Lactic Acidosis 559 Further Complications of the Debate 560 In Clinical Practice 560 References 560

38

Lessons Learned from a Phase I Clinical Trial of Mitochondrial Complex I Inhibition 563 Cecilia C. Low Wang, Jeffrey L. Galinkin, and William R. Hiatt

559

References 567 39

Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies 569 Whitney S. Gibbs, Natalie E. Scholpa, Craig C. Beeson, and Rick G. Schnellmann

39.1 39.2 39.3 39.4 39.4.1 39.4.2 39.4.3 39.4.4 39.4.5 39.5 39.5.1 39.6 39.7 39.7.1 39.7.2 39.8 39.8.1 39.8.2 39.8.3 39.9

Introduction 569 Regulation of MB 570 Mitochondrial Dysfunction in Disease 570 Acute Diseases 571 Ischemia/Reperfusion 571 Myocardial Infarction (MI) 572 Acute Kidney Injury (AKI) 572 Spinal Cord Injury 572 Stroke 573 Chronic Diseases 573 Neurodegenerative Diseases 573 Pharmacological Activation of MB 574 Kinase Modulators 575 AMPK 575 ERK1/2 576 G Protein‐Coupled Receptor Modulators 576 5‐HT Receptors 576 β‐Adrenergic Receptors 578 Cannabinoid‐1 Receptor 579 Cyclic Nucleotide Modulators 579

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39.9.1 39.9.2 39.10 39.10.1 39.10.2 39.11 39.12

NO/cGMP Pathway 579 cAMP/PKA/CREB Pathway 580 Transcription Factor Modulators 580 PPAR Agonists 580 ER Agonists 581 Sirtuins 581 Conclusions 582 References 583

40

Mitochondrial Toxicity Induced by Chemotherapeutic Drugs 593 Luciana L. Ferreira, Ana Raquel Coelho, Paulo J. Oliveira, and Teresa Cunha‐Oliveira

40.1 40.2 40.3 40.3.1 40.3.2 40.3.3 40.3.4 40.3.5 40.3.6 40.3.6.1 40.3.6.2 40.3.6.3 40.3.7 40.4 40.5

Introduction 593 Mitochondria and Cancer Chemotherapy 593 Conventional Chemotherapeutic Agents and Mitochondria 594 Alkylating Agents 594 Antitumor Antibiotics 597 Antimetabolites 598 Taxanes 600 Topoisomerase Inhibitors 601 Targeted Therapy 601 Proteasome Inhibitors 601 Monoclonal Antibodies 601 Tyrosine Kinase Inhibitors 602 Estrogen Receptor Modulators 602 Mitoprotectants as Adjuvants in Chemotherapy 603 Conclusion 604 Acknowledgments 605 References 605

Part 5

Environmental Toxicants and Mitochondria 613

41

The Mitochondrial Exposome 615 Douglas I. Walker, Kurt D. Pennell, and Dean P. Jones

41.1 41.1.1 41.1.2 41.1.3 41.1.4 41.2 41.2.1 41.2.2 41.2.3 41.2.4 41.3 41.4 41.4.1 41.4.2 41.5 41.5.1 41.5.2 41.5.2.1 41.5.2.2 41.5.2.3

Introduction 615 The Human Exposome 615 The Mitochondrial Exposome 616 Mitochondrial DNA Adductome 616 Mitochondrial Genome and Proteome 617 Environmental Pollutants and Mitochondrial Toxicity 617 Polycyclic Aromatic Hydrocarbons 618 Organohalogens 618 Contemporary Pesticides 619 High‐Throughput Screening for Mitochondrial Toxicants 619 Bioaccumulation of Environmental Pollutants 620 Mitochondria High‐Resolution Metabolomics 622 High‐Resolution Metabolomics 622 Metabolic Phenotyping of Intact Mitochondria 623 Case Study: Profiling the Human Mitochondrial Exposome 625 Adrenal Glands 625 Methods 626 Adrenal Gland Selection Criteria and Procurement 626 Adrenal Gland Tissue Preparation 626 Mitochondria Isolation and Sample Preparation 627

Contents

41.5.2.4 41.5.2.5 41.5.3 41.5.3.1 41.5.3.2 41.5.3.3 41.5.3.4 41.5.3.5 41.6

High‐Resolution Metabolomics 627 Data Processing and Feature Annotation 627 Results 627 Tissue Procurement 627 Mitochondria Isolation 628 High‐Resolution Metabolomics Results 628 Characterizing the Mitochondrial Exposome 628 Case Study Conclusions 630 Conclusions 632 Acknowledgments 632 References 632

42

Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents: Integrated Omics for Visualization 639 Young‐Mi Go, Karan Uppal, and Dean P. Jones

42.1 42.2 42.3 42.4 42.5 42.6

Introduction 639 High‐Resolution Metabolomics 641 High‐Resolution Metabolomics of Liver Mitochondria 642 Integration of Mitochondrial Redox Proteomics and Metabolomics: RMWAS 643 Integration of HRM with Transcriptomics: TMWAS 645 Three‐Way Integration of Redox Proteomics, Metabolomics, and Transcriptomics to Create RMT Association Study for Mitochondrial Signaling in Manganese (Mn) Toxicity 645 Integrated Omics Applications in Mitochondrial Metabolic Disorder: Fatty Liver, Diabetes, Obesity, and Neurodegenerative Diseases 648 Summary and Perspective 649 Acknowledgments 650 References 650

42.7 42.8

43

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans 655 Laura L. Maurer, Anthony L. Luz, and Joel N. Meyer

43.1 43.1.1 43.1.2 43.1.3 43.1.4 43.1.5 43.2 43.2.1 43.2.2 43.2.3 43.2.4 43.2.5 43.2.6 43.2.7 43.3 43.3.1 43.3.2 43.3.3 43.3.4 43.3.4.1 43.3.4.2 43.3.4.3 43.3.5 43.4

What We Know about Pollutant Influences on Mitochondria 655 Introduction 655 Environmental Mitotoxicants 657 How Should We Prioritize Environmental Chemicals and Stressors for Mitotoxicity Testing? 658 Mechanistic Organization of Mitotoxic Effects 658 Testing Environmental Chemicals and Stressors for Mitotoxicity: Approaches and Considerations 659 Advantages of the Caenorhabditis elegans Model 660 Introduction 660 C. elegans Biology 661 Mitochondrial Biology in C. elegans 661 Mutagenesis and Mutant Availability 662 RNA Interference 662 DNA Transformation 663 C. Elegans: A Model of Expanding Utility in Toxicology 663 Limitations of C. elegans for Studying Mitochondrial Toxicity 663 Introduction 663 Genetic and Phylogenetic Differences 663 Biochemical Differences 664 Physiological Limitations 665 Brain Mitochondria 665 Cardiac Mitochondria 666 Lung Mitochondria 666 Concluding Remarks on Limitations of C. elegans as a Model Organism 666 Methods for Assessing Mitochondrial Toxicity in C. Elegans 667

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43.4.1 43.4.2 43.4.3 43.4.4 43.4.5 43.4.6 43.4.7 43.4.8 43.4.9 43.4.10 43.4.11 43.5 43.5.1 43.5.2 43.5.3 43.5.4

Introduction 667 General Toxicity Assays 667 Mitochondrial Respiration 668 Steady‐State ATP Levels 668 Transcriptomics, Proteomics, and Metabolomics 668 Enzyme Activity 669 Mitochondrial Morphology 669 Mitochondrial Membrane Potential 669 Stress Response 669 Mitochondrial DNA Damage and Genome Copy Number 670 Limitations 670 Environmental Mitotoxicants and C. Elegans: Unique Discoveries and Emerging Roles 670 Introduction 670 Contributions of C. elegans in Discovering Key Mitochondrial Roles in Neurotoxicity 671 General Stress Response Mechanisms Important for Mitigating Mitochondrial Toxicity and Promoting Healthspan: Discoveries in C. elegans 672 Emerging Roles for C. elegans in Investigating Environmental Mitotoxicants 672 References 673

44

Persistent Organic Pollutants, Mitochondrial Dysfunction, and Metabolic Syndrome 691 Hong Kyu Lee and Youngmi Kim Pak

44.1 44.2 44.3 44.4 44.5 44.6 44.7 44.7.1 44.7.2 44.7.3 44.7.4 44.8 44.9 44.9.1 44.9.2 44.10 44.10.1 44.10.2 44.10.3 44.11

Introduction 691 Health Hazard of Environmental Chemicals: A Short History 691 Low‐Level Exposure to Multiple Chemicals 692 POPs and Obesity Paradox 692 Body Burden of Chemicals 693 Diabetes Mellitus, Insulin Resistance, and Metabolic Syndrome 693 Association of POPs with Diabetes and Metabolic Syndrome 695 Ecological Studies 695 Epidemiologic Studies on the Association between POPs and T2DM 695 Animal Experiments: Low‐Dose Exposure to Chemicals and Development of Diabetes 696 Cause–Effect Relationship between Exposure to POPs and the Onset of T2DM or MetS 696 Toxic and Biological Effects of Some POPs via AhR 696 Insulin Resistance and Mitochondrial Dysfunction 698 Mitochondrial Damages Induced by Environmental Chemicals 699 Scaling Law and Mitochondria 700 Measurement of POPs 702 Instrumental Analysis for POPs 702 Cell‐Based Assays for POPs 702 Association between CALA‐Determined Serum POP Levels and Mitochondria Inhibitor Activity 702 Summary 703 References 703

45

Cigarette Smoke and Mitochondrial Damage 709 Jalal Pourahmad, Marjan Aghvami, Mohammad Hadi Zarei, and Parvaneh Naserzadeh

45.1 45.2 45.3 45.4 45.4.1 45.4.1.1 45.4.2 45.4.3 45.4.3.1

Introduction 709 Cigarette Smoke Components and Mitochondrial Toxicity 709 Health Problems Caused by Cigarette Smoking 711 Cigarette Smoke and Mitochondrial Damage in Different Disease 712 Cardiovascular Disease 712 Endothelial Superoxide Anion 714 Brain Related Diseases 714 Respiratory System‐Related Diseases 715 Cigarette Smoke‐Induced Mitochondrial Damage in Airway Smooth Muscle 715

Contents

45.4.3.2 45.4.3.3 45.4.3.4 45.4.3.5 45.4.4 45.4.5 45.4.6 45.5

Effects of Cigarette Smoke Extract on Alveolar Epithelial Cells 716 Cigarette Smoke Effect on Mitochondrial Respiratory Chain 716 Cigarette Smoke Effects on Mitochondrial in Alveolar Epithelial Cells 717 Aryl Hydrocarbon Receptor and Cigarette Smoke‐Induced Mitochondrial Dysfunction 717 Cigarette Smoke Damage on Mitochondria in the Retinal Cells 717 Cigarette Smoke Induce Mitochondrial Damage in Blood Cells 717 Mitochondrial Damage by Cigarette Smoke Results in Cancer 718 Summary 719 References 719 Index 727

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List of Contributors Sandra Amaral

Neha Bansal

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra and Institute for Interdisciplinary Research, University of Coimbra Coimbra Portugal

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA

Sofia Annis

Department of Biology College of Science Northeastern University Boston, MA USA Jamie J. Arnold

201 Althouse Lab, Department of Biochemistry and Molecular Biology The Pennsylvania State University University Park, PA USA Narayan G. Avadhani

Department of Biomedical Sciences, School of Veterinary Medicine University of Pennsylvania Philadelphia, PA USA

Daniel José Barbosa

Cell Division Mechanisms Group Instituto de Biologia Molecular e Celular (IBMC), Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto Porto Portugal Maria de Lourdes Bastos

UCIBIO, REQUIMTE (Rede de Química e Tecnologia), Laboratório de Toxicologia, Departamento de Ciências Biológicas, Faculdade de Farmácia Universidade do Porto Porto Portugal Craig C. Beeson

Department of Drug Discovery and Biomedical Sciences, College of Graduate Studies Medical University of South Carolina Charleston, SC USA

Amy L. Ball

Department of Molecular and Cellular Pharmacology, MRC Centre for Drug Safety Science, The Institute of Translational Medicine The University of Liverpool Liverpool UK

Richard D. Beger

Division of Systems Biology, National Center for Toxicological Research Food and Drug Administration Jefferson, AR USA

xiv

List of Contributors

Sudeepa Bhattacharyya

João Paulo Capela

Department of Pediatrics University of Arkansas for Medical Sciences and Section of Clinical Pharmacology and Toxicology Arkansas Children’s Hospital Little Rock, AR USA

UCIBIO, REQUIMTE (Rede de Química e Tecnologia), Laboratório de Toxicologia, Departamento de Ciências Biológicas, Faculdade de Farmácia Universidade do Porto and FP-ENAS (Unidade de Investigação UFP em Energia, Ambiente e Saúde), CEBIMED (Centro de Estudos em Biomedicina), Faculdade de Ciências da Saúde Universidade Fernando Pessoa Porto Portugal

Eduardo Biala

Department of Biology College of Science Northeastern University Boston, MA and Biology Program University of Guam Mangilao, GU USA Sabine Borchard

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg Germany Annie Borgne‐Sanchez

Mitologics S.A.S. Hôpital Robert Debré Paris France

Francesc Cardellach

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Félix Carvalho

UCIBIO, REQUIMTE (Rede de Química e Tecnologia), Laboratório de Toxicologia, Departamento de Ciências Biológicas, Faculdade de Farmácia Universidade do Porto Porto Portugal

Craig E. Cameron

201 Althouse Lab, Department of Biochemistry and Molecular Biology The Pennsylvania State University University Park, PA USA

Carmen Castaneda‐Sceppa

Robert B. Cameron

Marc Catalán-García

Department of Pharmacology and Toxicology, College of Pharmacy University of Arizona Tucson, AZ and Department of Drug Discovery and Biomedical Sciences, College of Graduate Studies Medical University of South Carolina Charleston, SC USA

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain

Bouve College of Health Sciences, Northeastern University Boston, MA USA

List of Contributors

Amy E. Chadwick

Teresa Cunha‐Oliveira

Department of Molecular and Cellular Pharmacology, MRC Centre for Drug Safety Science, The Institute of Translational Medicine The University of Liverpool Liverpool UK

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal

Sherine S. L. Chan

Department of Drug Discovery and Biomedical Sciences Medical University of South Carolina Charleston, SC USA and Neuroene Therapeutics Mt. Pleasant, SC, USA

Jason Czachor

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA Thierry Delvienne

Metabiolab Brussels Belgium Varsha G. Desai

Huan‐Chieh Chien

Department of Bioengineering and Therapeutic Sciences University of California and Apricity Therapeutics Inc. San Francisco, CA USA Ana Raquel Coelho

CNC—Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Biocant Park Cantanhede and III‐Institute for Interdisciplinary Research, University of Coimbra Coimbra Portugal Marc Conti

IMRB U955EQ7, Mondor University Hospitals; Créteil & URDIA, Saints Pères Faculty of Medicine Descartes University Paris France

Personalized Medicine Branch, Division of Systems Biology, National Center for Toxicological Research U.S. Food and Drug Administration Jefferson, AR USA David A. Dunn

Department of Biological Sciences State University of New York at Oswego Oswego, NY USA Alex Dyson

Bloomsbury Institute of Intensive Care Medicine, Division of Medicine University College London and Magnus Oxygen Ltd, University College London London UK Carola Eberhagen

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg Germany

Cláudio F. Costa

Steve Enoch

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal

School of Pharmacy and Biomolecular Sciences Liverpool John Moores University Liverpool UK

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List of Contributors

Sara Escada‐Rebelo

Jeffrey L. Galinkin

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra and Institute for Interdisciplinary Research, University of Coimbra Coimbra Portugal

Department of Anesthesia University of Colorado School of Medicine and CPC Clinical Research Aurora, CO USA

Luciana L. Ferreira

CNC—Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Biocant Park Cantanhede Portugal Zoe Fleischmann

Department of Biology, College of Science Northeastern University Boston, MA, USA Clàudia Fortuny

Malalties infeccioses i resposta inflamatòria sistèmica en pediatria, Unitat d’Infeccions, Servei de Pediatria Institut de Recerca Pediàtrica Hospital Sant Joan de Déu Barcelona; CIBER de Epidemiología y Salud Pública (CIBERESP) Madrid; Departament de Pediatria Universitat de Barcelona Barcelona; and Traslational Research Network in Pediatric Infectious Diseases (RITIP) Madrid Spain Olivier Frey

InSphero AG Schlieren Switzerland

Priya Gandhi

Department of Biology College of Science Northeastern University Boston, MA USA Laura García-Otero

BCNatal—Barcelona Center for Maternal‐Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona Barcelona and CIBERER Madrid Spain Glòria Garrabou

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Sciences‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Mariana Gerschenson

John A. Burns School of Medicine University of Hawaii at Manoa Honolulu, HI USA Kathleen M. Giacomini

Bernard Fromenty

INSERM, INRA, Université Rennes, UBL, Nutrition Metabolisms and Cancer (NuMeCan) Rennes France

Department of Bioengineering and Therapeutic Sciences University of California San Francisco, San Francisco, CA USA

List of Contributors

Whitney S. Gibbs

G. J. Groeneveld

Department of Drug Discovery and Biomedical Sciences Medical University of South Carolina Charleston, SC and Department of Pharmacology and Toxicology, College of Pharmacy University of Arizona Tucson, AZ USA

Centre for Human Drug Research Leiden The Netherlands

Pritmohinder S. Gill

Department of Pediatrics University of Arkansas for Medical Sciences and Section of Clinical Pharmacology and Toxicology Arkansas Children’s Hospital Little Rock, AR USA Young‐Mi Go

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine Emory University Atlanta, GA USA Ingrid González‐Casacuberta

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Josep Maria Grau

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain

F. Peter Guengerich

Department of Biochemistry Vanderbilt University School of Medicine Nashville, TN USA Mariona Guitart‐Mampel

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Sciences‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Andrew M. Hall

Institute of Anatomy, University of Zurich and Department of Nephrology University Hospital Zurich Zurich Switzerland Iain P. Hargreaves

Neurometabolic Unit, National Hospital London and School of Pharmacy and Biomolecular Science, Liverpool John Moores University Liverpool UK Eric K. Herbert

University of Nottingham Nottingham UK Karl E. Herbert

Department of Cardiovascular Sciences University of Leicester Leicester UK

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List of Contributors

Saul R. Herbert

G. Ronald Jenkins

Queen Mary University of London London UK

Personalized Medicine Branch, Division of Systems Biology, National Center for Toxicological Research U.S. Food and Drug Administration Jefferson, AR USA

Ana Sandra Hernández

BCNatal—Barcelona Center for Maternal‐Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona Barcelona and CIBERER Madrid Spain

Carol E. Jolly

Department of Molecular and Cellular Pharmacology, MRC Centre for Drug Safety Science, The Institute of Translational Medicine The University of Liverpool Liverpool UK

William R. Hiatt

CPC Clinical Research and Division of Cardiology, Department of Medicine University of Colorado Anschutz Medical Campus School of Medicine Aurora, CO USA Ashley Hill

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA Michael H. Irwin

Department of Pathobiology, College of Veterinary Medicine Auburn University Auburn, AL USA Hartmut Jaeschke

Department of Pharmacology, Toxicology & Therapeutics University of Kansas Medical Center Kansas City, KS USA Laura P. James

Department of Pediatrics University of Arkansas for Medical Sciences and Section of Clinical Pharmacology and Toxicology Arkansas Children’s Hospital Little Rock, AR USA

Dean P. Jones

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine Emory University and HERCULES Exposome Research Center, Department of Environmental Health Rollins School of Public Health Atlanta, GA USA Diana Luz Juárez-Flores

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Laleh Kamalian

Department of Molecular and Cellular Pharmacology, MRC Centre for Drug Safety Science, The Institute of Translational Medicine The University of Liverpool Liverpool UK Jens M. Kelm

InSphero AG Schlieren Switzerland

List of Contributors

Graham J. Kemp

Josef Lichtmannegger

Department of Musculoskeletal Biology University of Liverpool Liverpool UK

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg Germany

Konstantin Khrapko

Department of Biology College of Science Northeastern University and Bouve College of Health Sciences, Northeastern University Boston, MA USA Jean‐Daniel Lalau

Department of Endocrinology and Nutrition Amiens University Hospital Amiens France Hong Kyu Lee

Department of Internal Medicine College of Medicine, Eulji University Seoul South Korea John J. Lemasters

Center for Cell Death, Injury & Regeneration, Medical University of South Carolina; Department of Drug Discovery & Biomedical Sciences Medical University of South Carolina; Department of Biochemistry & Molecular Biology Medical University of South Carolina Charleston, SC USA and Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences Pushchino Russian Federation Housaiyin Li

Department of Biology College of Science Northeastern University Boston, MA USA

Steven E. Lipshultz

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA Irene Llorente‐Folch

Department of Physiology and Medical Physics Royal College of Surgeons in Ireland 123 St Stephen’s Green Dublin 2 Ireland Sylvain Loric

IMRB U955EQ7, Mondor University Hospitals; Créteil & URDIA, Saints Pères Faculty of Medicine Descartes University Paris France Anthony L. Luz

Nicholas School of the Environment Duke University Durham, NC USA Prathap Kumar Mahalingaiah

Department of Investigative Toxicology and Pathology, Preclinical Safety Division AbbVie North Chicago, IL USA Afshan N. Malik

Diabetes Research Group, School of Life Course Sciences, Faculty of Life Sciences and Medicine King’s College London London UK Joana R. Martins

Institute of Anatomy, University of Zurich Zurich Switzerland Laura L. Maurer

Nianyu Li

Merck Research Laboratory West Point, PA USA

Nicholas School of the Environment Duke University Durham, NC USA

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List of Contributors

Gavin P. McStay

Walter H. Moos

Department of Life Sciences New York Institute of Technology Old Westbury, NY USA

Department of Pharmaceutical Chemistry, School of Pharmacy University of California San Francisco San Francisco, CA USA

Claire Mellor

School of Pharmacy and Biomolecular Sciences Liverpool John Moores University Liverpool UK Simon Messner

InSphero AG Schlieren Switzerland Miriam Mestre

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA Joel N. Meyer

Nicholas School of the Environment Duke University Durham, NC USA

Constanza Morén

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Sciences‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain

F. M. Münker

Photonics Healthcare B.V. Utrecht The Netherlands

Padma Kumar Narayanan

Ionis Pharmaceuticals Carlsbad, CA USA

E. G. Mik

Department of Anesthesiology Erasmus MC Rotterdam The Netherlands Jose César Milisenda

Muscle Research and Mitochondrial Function Laboratory, Cellex‐IDIBAPS, Faculty of Medicine and Health Science‐University of Barcelona, Internal Medicine Department‐Hospital Clínic of Barcelona (HCB) Barcelona and CIBERER Madrid Spain Tracie L. Miller

Miller School of Medicine University of Miami Miami, FL USA

Viruna Neergheen

Neurometabolic Unit National Hospital London UK

Andy Neilson

Agilent Technologies Santa Clara, CA USA

Mark Nelms

School of Pharmacy and Biomolecular Sciences Liverpool John Moores University Liverpool UK and US‐EPA Raleigh‐Durham, NC USA

List of Contributors

Anna‐Liisa Nieminen

Youngmi Kim Pak

Center for Cell Death, Injury & Regeneration, Medical University of South Carolina; Departments of Drug Discovery & Biomedical Sciences Medical University of South Carolina Charleston, SC USA and Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences Pushchino Russian Federation

Department of Physiology College of Medicine, Kyung Hee University Seoul South Korea

Antoni Noguera‐Julian

Malalties infeccioses i resposta inflamatòria sistèmica en pediatria, Unitat d’Infeccions, Servei de Pediatria Institut de Recerca Pediàtrica Hospital Sant Joan de Déu Barcelona; CIBER de Epidemiología y Salud Pública (CIBERESP) Madrid; Departament de Pediatria Universitat de Barcelona Barcelona; and Traslational Research Network in Pediatric Infectious Diseases (RITIP) Madrid Spain

Kurt D. Pennell

Department of Civil and Environmental Engineering Tufts University Medford, MA USA Daniela Piga

Centro Dino Ferrari, Dipartimento di Fisiopatologia Medico‐Chirurgica e dei Trapianti Università degli Studi and UOC Neurologia, Fondazione IRCCS Ca’ Granda – Ospedale Maggiore Policlinico Milan Italy Carl A. Pinkert

Department of Biological Sciences, College of Arts and Sciences The University of Alabama Tuscaloosa, AL USA Bastian Popper

Department of Anatomy and Cell Biology, Biomedical Center Ludwig‐Maximilians‐University Munich Martinsried Germany

Paulo J. Oliveira

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal

Jalal Pourahmad

Department of Toxicology and Pharmacology, Faculty of Pharmacy Shahid Beheshti University of Medical Sciences Tehran Iran

Alberto Ortiz

Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid Spain

Jochen H. M. Prehn

Pal Pacher

Alessandro Protti

Laboratory of Cardiovascular Physiology and Tissue Injury National Institutes of Health/NIAAA Bethesda, MD USA

Dipartimento di Anestesia, Rianimazione ed Emergenza‐Urgenza, Fondazione IRCCS Ca’ Granda – Ospedale Maggiore Policlinico Milan Italy

Department of Physiology and Medical Physics Royal College of Surgeons in Ireland 123 St Stephen’s Green Dublin 2 Ireland

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List of Contributors

João Ramalho‐Santos

Dario Ronchi

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra and Department of Life Sciences University of Coimbra Coimbra Portugal

Centro Dino Ferrari, Dipartimento di Fisiopatologia Medico‐Chirurgica e dei Trapianti Università degli Studi and UOC Neurologia, Fondazione IRCCS Ca’ Granda – Ospedale Maggiore Policlinico Milan Italy

Adrian M. Ramos

Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid Spain

Katrin Rössger

InSphero AG Schlieren Switzerland

Adeel Safdar Venkat K. Ramshesh

Center for Cell Death, Injury & Regeneration, Medical University of South Carolina; Departments of Drug Discovery & Biomedical Sciences Medical University of South Carolina Charleston, SC and GE Healthcare Quincy, MA USA Haider Raza

Department of Biomedical Sciences, School of Veterinary Medicine University of Pennsylvania Philadelphia, PA USA and On Sabbatical from Department of Biochemistry College of Medicine and Health Sciences, United Arab Emirates University Al Ain UAE Hiedy Razoky

Wayne State University School of Medicine Children’s Hospital of Michigan Detroit, MI USA

School of Health Sciences, Humber College Toronto, Ontario Canada Ayesha Saleem

School of Health Sciences, Humber College Toronto, Ontario Canada Stephen E. Sallan

Dana‐Farber Cancer Institute, Harvard Medical School and Department of Medicine, Division of Hematology/Oncology Boston Children’s Hospital Boston, MA USA Maria Dolores Sanchez‐Niño

Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid Spain Alessandro Santini

Tamara Rieder

Institute of Toxicology and Environmental Hygiene Technical University Munich Munich Germany

Dipartimento di Anestesia, Rianimazione ed Emergenza‐Urgenza, Fondazione IRCCS Ca’ Granda – Ospedale Maggiore Policlinico Milan, Italy

List of Contributors

Ana Belén Sanz

Rui F. Simões

Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz Universidad Autónoma de Madrid Madrid Spain

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal

Vilma A. Sardão

CNC—Center for Neuroscience and Cell Biology, University of Coimbra Cantanhede Portugal Sabine Schmitt

Institute of Toxicology and Environmental Hygiene Technical University Munich Munich Germany Rick G. Schnellmann

Department of Pharmacology and Toxicology, College of Pharmacy University of Arizona and Southern Arizona VA Health Care System Tucson, AZ USA Natalie E. Scholpa

Department of Pharmacology and Toxicology, College of Pharmacy University of Arizona Tucson, AZ USA Claus D. Schuh

Institute of Anatomy, University of Zurich Zurich Switzerland

Kosta Steliou

Boston University School of Medicine, Cancer Research Center Boston, MA and PhenoMatriX, Inc. Natick, MA USA Renata S. Tavares

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra Coimbra Portugal Jonathan L. Tilly

Department of Biology College of Science, Northeastern University Boston, MA USA R. Ubbink

Department of Anesthesiology Erasmus MC Rotterdam and Photonics Healthcare B.V. Utrecht The Netherlands

Sabine Schulz

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg Germany

Karan Uppal

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine Emory University Atlanta, GA USA

Andreia F. Silva

Biology of Reproduction and Stem Cell Group, CNC—Center for Neuroscience and Cell Biology University of Coimbra Coimbra Portugal

M. P. J. van Diemen

Centre for Human Drug Research Leiden The Netherlands

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List of Contributors

Terry R. Van Vleet

Tucker Williamson

Department of Investigative Toxicology and Pathology, Preclinical Safety Division AbbVie North Chicago, IL USA

Department of Drug Discovery and Biomedical Sciences Medical University of South Carolina Charleston, SC USA

Zoltan V. Varga

Dori C. Woods

Laboratory of Cardiovascular Physiology and Tissue Injury National Institutes of Health/NIAAA Bethesda, MD USA

Department of Biology College of Science, Northeastern University Boston, MA USA

Eneritz Velasco‐Arnaiz

Benjamin L. Woolbright

Malalties infeccioses i resposta inflamatòria sistèmica en pediatria, Unitat d’Infeccions, Servei de Pediatria Institut de Recerca Pediàtrica Hospital Sant Joan de Déu Barcelona Spain

Department of Pharmacology, Toxicology & Therapeutics University of Kansas Medical Center Kansas City, KS USA

Luke Wainwright

Department of Molecular Neuroscience Institute of Neurology, University College of London London UK Douglas I. Walker

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine Emory University Atlanta, GA; Department of Civil and Environmental Engineering Tufts University Medford, MA and HERCULES Exposome Research Center, Department of Environmental Health Rollins School of Public Health Atlanta, GA USA Cecilia C. Low Wang

Division of Endocrinology, Metabolism and Diabetes, Department of Medicine University of Colorado Anschutz Medical Campus School of Medicine and CPC Clinical Research Aurora, CO USA

Hans Zischka

Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich German Research Center for Environmental Health Neuherberg, Germany and Institute of Toxicology and Environmental Hygiene Technical University Munich Munich Germany Marjan Aghvami

Department of Toxicology and Pharmacology Faculty of Pharmacy, Shahid Beheshti University of Medical Sciences Tehran, Iran Mohammad Hadi Zarei,

Department of Toxicology and Pharmacology Faculty of Pharmacy, Shahid Beheshti University of Medical Sciences Tehran, Iran Parvaneh Naserzadeh

Department of Toxicology and Pharmacology Faculty of Pharmacy, Shahid Beheshti University of Medical Sciences Tehran, Iran

xxv

Foreword The field of mitochondrial medicine is enjoying a renaissance driven largely by advances in molecular biology and genetics. The first draft sequence of the human mitochondrial genome in 1981 provided the critical blueprint that enabled the identification of the first point and single large‐scale deletion mutations of mitochondrial DNA (mtDNA) in 1988. To date, more than 270 distinct mtDNA point mutations and hundreds of mtDNA deletions have been identified. Subsequent sequencing of the human nuclear genome in the early 2000s helped to catalyze the discovery of approximately 1000 nuclear genes that, together with the mtDNA, encode the mitochondrial proteome. With a complete parts list, it has been possible to delve deep into the molecular basis of Mendelian mitochondrial disorders, with more than 200 nuclear disease genes now identified. There is now widespread consensus that mitochondrial dysfunction contributes to a spectrum of human conditions, ranging from rare syndromes to common degenerative diseases to the aging process itself. Today, there is great excitement that in the coming decade, new medicines will become available that alleviate disease by targeting mitochondria. At the same time, there is widespread appreciation that many drugs fail clinical trials because of their mitochondrial liabilities. Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants represents one of the most important textbooks for those hoping to target mitochondria, as well as for those wanting to avoid mitochondrial side  effects. It is a deep and thoughtful resource that will appeal to basic scientists, clinicians, and professional drug developers. Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants provides ample reminders of the intimate connections between mitochondria, pharmacology, and toxicology. Some of the most widely used tool compounds for investigating mitochondrial physiology, such as antimycin and oligomycin, are indeed natural products that serve as a chemical warfare in the microbial world. The fact that antimicrobial agents are often toxic to mitochondria is not surprising given the hypothesized proto‐bacterial origin of mitochondria. These overlapping effects of such drugs are perhaps best

illustrated by aminoglycosides and linezolid antibiotics, which not only inhibit bacterial protein synthesis but are also well known to cause neurotoxicity such as hearing loss, peripheral neuropathy, and optic neuropathy through impairment of mitochondrial translation. Pharmacogenetics contributes to these toxicities with the well‐established link between the m.1555A>G variant that predisposes to aminoglycoside‐induced deafness. Toxic side effects of clinically important and investigational new drugs for viruses have historically provided fundamentally new insights into the replication of mtDNA. One of the earliest anti‐HIV agents, zidovudine (azidothymidine (AZT)), is a nucleoside analogue that effectively inhibits viral reverse transcriptase but, in some patients, inhibits the mitochondrial polymerase gamma, leading to depletion of mtDNA particularly in muscle and causing myopathic weakness. These mitochondrial toxicities exposed the reliance and vulnerability of the mitochondrial genome to disruptions of the deoxynucleotide pool substrates for mtDNA replication. These toxicities also serve as a reminder that the mtDNA replication machinery of mitochondria actually resembles that of viruses. Mitochondrial toxicity is such a common side effect in humans; a thorough understanding and surveillance of these off‐target effects are required for the successful development of new medicines. A vivid case in point is fialuridine or 1‐(2‐deoxy‐2‐fluoro‐1‐d‐arabinofuranosyl)‐ 5‐iodouracil (FIAU), a nucleoside analogue that was tested for therapeutic efficacy for hepatitis B infection but tragi‑ cally caused fatal liver failure and death in 5 of 15 patients and forced liver transplantations in two other patients. Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants takes a rather systematic approach to mitochondrial pharmacology and toxicology and for this reason will be of use to even those outside of strict drug discovery. It begins with a scholarly introduction to the nuances of mitochondrial drug transport and detoxification systems, illustrated with specific case studies (Chapters 1–5). It then reviews cardinal features of mitochondrial toxicity at the organ level, highlighting some of the dose‐limiting toxicities of very commonly used

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Foreword

and lifesaving drugs (Chapter 6–12). One of the greatest challenges in our field lies in measuring mitochondrial function. Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants dedicates many chapters (Chapters 13–29) to reviewing modern technologies for measuring mitochondrial function in vitro, ex vivo, and in vivo. Although these technologies represent the current state of the art, they have their limitations, and much research is required to pioneer new, facile biomarkers and technologies that  are sensitive, specific, and minimally invasive. The  text  then progresses to reports from the clinic (Chapters 30–40) as well as from environmental biology (Chapters 41–45) that offer additional vignettes and examples of drug–mitochondria interactions.

The book Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants is very timely. While genetics and genomics have driven much progress in mitochondrial medicine for the past few decades, we anticipate that chemical biology may represent one of the most exciting new frontiers. We applaud Yvonne Will, James Dykens, and all of their contributors for assembling this new two volume book entitled: Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants. This textbook will be an important canon in the future of mitochondrial medicine and more broadly in modern drug discovery. Vamsi Mootha, M.D. (Boston, MA) and Michio Hirano, M.D. (New York, NY)

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Part 4

Reports from the Clinic

459

30 Statin and Fibrate‐Induced Dichotomy of Mitochondrial Function Viruna Neergheen1, Alex Dyson2,3, Luke Wainwright4, and Iain P. Hargreaves1,5 1

Neurometabolic Unit, National Hospital, London, UK Bloomsbury Institute of Intensive Care Medicine, Division of Medicine, University College London, London, UK 3 Magnus Oxygen Ltd, University College London, London, UK 4 Department of Molecular Neuroscience, Institute of Neurology, University College of London, London, UK 5 School of Pharmacy and Biomolecular Science, Liverpool John Moores University, Liverpool, UK 2

CHAPTER MENU 30.1 30.2 30.3 30.4 30.5 30.6 30.7 30.8 30.9

30.1

Introduction, 459 Statins, 460 Effect of Statin Treatment on Endogenous CoQ10 Status, 460 Effect of Statin Treatment on Cerebral CoQ10 Status, 462 Effect of Statin Treatment on Oxidative Phosphorylation, 463 Fibrates, 467 The Effect of Fibrate Treatment on Mitochondrial Respiratory Chain Function, 467 Fibrates in the Treatment of Oxidative Phosphorylation Defects, 468 Conclusion, 469 References, 469

Introduction

The mitochondrial respiratory chain (MRC) (Figure 30.1) is located in the inner mitochondrial membrane and plays a central role in cellular energy generation (Wallace, 1999). The MRC consists of four enzyme complexes: complex I (NADH: ubiquinone reductase; EC 1.6.5.3), complex II (succinate: ubiquinone reductase; EC 1.3.5.1), complex III (ubiquinol: cytochrome c reductase; EC 1.10.2.2), and complex IV (cytochrome c oxidase; EC 1.9.3.1) (Hatefi, 1985). The MRC together with complex V (ATP synthase; EC 3.6.3.14) undertakes the process of oxidative phosphorylation and is consequently known as the oxidative phosphorylation system (Hatefi, 1985, Wallace, 1999). In this process, electron transport between complex I and IV is coupled to proton pumping at complexes I, III, and IV, which creates a proton motive gradient between the inner and outer mitochondrial membranes. Complex V then utilizes this proton gradient to synthesize ATP from ADP and inorganic phosphate (Pi) (Rahman and Hanna, 2009). As protons

are transferred through the Fo sector of complex V, this causes a conformational change in the F1 sector of the enzyme, which provides energy for ATP synthesis by means of “rotary catalysis” (Jonckheere et  al., 2012). In  addition to the enzyme complexes, the electron carriers, coenzyme Q10 (CoQ10) and cytochrome c, are also essential for oxidative phosphorylation with a deficiency in CoQ10 biosynthesis, representing a potentially treatable form of MRC disorder (Hargreaves, 2014). As far as the authors are aware, there have been no reported cases of cytochrome c deficiency that suggests that a deficit in the level of this cytochrome may not be compatible with life. Recent studies have indicated that although the enzymes in the oxidative phosphorylation system can exist as discrete entities, they may also be  present in the inner mitochondrial membrane in the form of super enzyme complexes. These “supercomplexes” are composed of aggregates of complexes I, III, and IV, complexes I and III, and complexes III and IV (Lapuente‐Brun et  al., 2013). Mitochondrial DNA (mtDNA) encodes for 13 of the approximately 90 protein

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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Mitochondrial Dysfunction by Drug and Environmental Toxicants

Figure 30.1 Diagram of the mitochondrial respiratory chain (MRC) and complex V illustrating proton (H+) movement during oxidative phosphorylation, where Cyt c, cytochrome c; Q, coenzyme Q10.

Intermembrane space 4H+

4H+

2H+ Cyt c

Inner mitochondrial membrane

Q

I

III

IV

V

II 1/2O2 + 2H+ H2O

NADH + H+ NAD+ FADH2

FAD+

Mitochondrial matrix

subunits that constitute the MRC and complex V, the remainder being encoded for by nuclear DNA (nDNA) (Saraste, 1999). In contrast to the other enzyme complexes, complex II is entirely nDNA encoded (Saraste, 1999). mtDNA in contrast to nDNA is not protected by histones or DNA‐binding proteins and therefore is vulnerable to free radical‐induced oxidative damage (Wei, 1998). Furthermore, impairment of oxidative phosphorylation system enzyme activities may also result from oxidative damage to their protein subunits as well as the inner mitochondrial membrane phospholipids (Zang et al., 1990). This therefore indicates that in addition to genetic causes that have an incidence of 1 in 5000 live births (Rahman and Hanna, 2009), defects in oxidative phosphorylation may also be caused by secondary factors that result in oxidative stress generation such as disease pathophysiology or “off‐target” drug‐induced mitochondrial toxicity. In addition to oxidative stress generation, pharmacotherapy may also cause mitochondrial impairment by the direction inhibition of the enzyme complexes, uncoupling of oxidative phosphorylation, and/or impairment of mtDNA replication (Hargreaves et al., 2016). Although a number of pharmacotherapies have been associated with mitochondrial toxicity, there are some classes of drugs that have been associated with both an impairment and an improvement in mitochondrial function. This chapter will illustrate this phenomenon by focusing on two pharmacotherapies, statins and fibrates, which are used in the treatment of dyslipidemia, highlighting the putative mechanisms responsible for their contrasting effects on mitochondrial function.

30.2

Statins

Statins competitively inhibit the enzyme, HMG‐CoA reductase, the rate‐limiting enzyme of the mevalonate pathway and subsequently cholesterol synthesis

ADP + Pi H+ ATP

(Figure 30.2), and were introduced in 1987 to treat hypercholesterolemia (Hargreaves et  al., 2005). A number of clinical trials with statins have suggested an acceptable safety profile; however, statin‐associated muscle symptoms (SAMS) have been increasingly reported with this pharmacotherapy, resulting in skeletal muscle dysfunction in up to 25% of statin users who exercise (Sinzinger et  al., 2002, Stroes et  al., 2015). These myopathic side effects include myalgia, myositis, muscle weakness, and in rare cases rhabdomyolysis, but in many patients SAMS may be more subtle and may occur with or without serum creatine kinase (CK) elevation (Sathasivam, 2012). In view of their pleiotropic nature, the myopathic side effects of statin therapy may arise from a number of causes; however this chapter will outline the evidence for mitochondrial dysfunction as a contributing factor to these adverse side effects of the drug.

30.3 Effect of Statin Treatment on Endogenous CoQ10 Status Although the pathogenesis of statin‐induced muscle dysfunction has yet to be fully elucidated, studies have associated statin treatment with a decrease in mitochondrial function together with an attenuation of energy production (Stroes et  al., 2015). Lactic acidosis and elevated plasma lactate:pyruvate ratios have also been reported in patients following statin therapy, indicating a perturbation in oxidative phosphorylation (De Pinieux et al., 1996; Goli et al., 2002). In view of the commonality of the CoQ10 and cholesterol biosynthetic pathways (Figure 30.2) together with the essential electron carrier role of CoQ10 in the MRC, a number of studies have assessed whether a statin‐induced deficit in endogenous CoQ10 status may be a contributing factor to the mitochondrial dysfunction observed in patients. The majority of these studies have assessed the effect of statin therapy on circulatory CoQ10 status by measuring the

Statin and Fibrate‐Induced Dichotomy of Mitochondrial Function Acetyl-CoA

HMG-CoA Statins

HMG-CoA reductase Mevalonate

Signal transduction, protein localization Isoprenylated proteins

Isopentenyl adenosine

IPP Famesyl-protein transferase all-transGGPP synthase

GGPP

FPP

cis-Prenyl transferase

Polyprenyl-PP

Polyprenyl-PP

Squalene synthase

trans-Prenyl transferase Tyrosine (or phenylalanine)

t-RNA Protein synthesis

Dolichol

Squalene

Dolichyl-P Glycosylation of proteins

4-OH-Benzoic acid Polyprenyl-4-hydroxybenzoic acid transferase

2,3-Squalene epoxide Oxidosqualene cyclase

Polyprenyl-4-OHbenzoic acid

Lanosterol

Cholesterol Precursor for bile acids and steroid hormones

Coenzyme Q OH O O OH

n

Figure 30.2 Mevalonate pathway, where PP, pyrophosphate.

levels of this isoprenoid in both serum and plasma (Banach et al., 2015). The majority of these studies have found evidence of a decrease in circulatory levels of CoQ10 following statin treatment ranging from an approximate 27–50% reduction (Hargreaves et al., 2005). In the circulation, the majority of CoQ10 is carried by the lipoproteins, predominantly the low‐density lipoprotein (LDL) fraction (Hargreaves, 2003). In view of this, it has been suggested that plasma and serum CoQ10 status

should be normalized to either total serum lipid or cholesterol levels (Hughes et  al., 2002). Since statins target the liver causing a decrease in LDL synthesis, the diminution in plasma/serum CoQ10 status following statin therapy may simply reflect the decrease in the circulatory level of LDL induced by this pharmacotherapy (Hargreaves et  al., 2005). Indeed, in the majority of studies, the decrease in plasma/serum CoQ10 status is  nullified once the fall in circulatory total lipid or

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cholesterol is taken into account (Hargreaves et  al., 2005). In contrast, the decrease in circulatory CoQ10 status in some studies appears to be more pronounced than the diminution in lipid/cholesterol levels, indicating a possible statin‐induced inhibition of CoQ10 biosynthesis (Ghirlanda et al., 1993; Watts et al., 1993; Human et al., 1997). In these studies, however, the possibility of a preexisting CoQ10 deficiency or increased oxidative stress may have had an effect on circulatory levels of CoQ10 (Hargreaves et al., 2005). Since plasma/serum may not be the most appropriate surrogate to gauge tissue levels of CoQ10 following statin treatment, a few studies have assessed the effect of this pharmacotherapy on muscle CoQ10 status. This would seem appropriate as the major side effects associated with statin therapy are of muscle origin (Sinzinger et al., 2002; Stroes et  al., 2015). Surprisingly, however, few studies have assessed the effect of statin therapy on muscle CoQ10, and of these the results have been contradictory with few studies showing evidence of a decrease in CoQ10 status following this pharmacotherapy. Since the incidence of statin‐associated adverse effects appears to be dose dependent and exacerbated by drugs that affect their metabolism/detoxification (Duncan et  al., 2009), it is not surprising that evidence of decrease in muscle CoQ10 status has been reported under these conditions. In the study by Päivä et al. (2005), evidence of  an approximately 34% decrease in skeletal muscle CoQ10 status was reported following 8 weeks of treatment of 16 hypercholesterolemia patients taking a high dose (80 mg/day) of simvastatin. Interestingly, no associated myopathic side effects were reported although one patient was found to have a threefold increase in plasma hepatic transaminase levels. The authors suggested that the deficit in muscle CoQ10 status may reflect the concomitant decrease in mitochondrial enrichment or volume as indicated by the decrease in the activity of the  mitochondrial marker enzyme, citrate synthase (Päivä et al., 2005). Evidence of muscle CoQ10 deficiency (77 pmol/mg; reference interval: 140–580 pmol/mg) has been reported in a patient who experienced rhabdomyolysis and renal failure following the increase in the dosage of simvastatin from 20 to 40 mg a day (Duncan et  al., 2009). Importantly, the patient was also being treated with cyclosporine that has been reported to inhibit the hepatic cytochrome P450 enzymes involved in the metabolism and detoxification of simvastatin, which has been associated with an increased bioavailability of the statin (Arnadottir et al., 1993). Interestingly, in a recent study in rats, evidence was reported of myopathy and associated muscle mitochondrial dysfunction (indicated by decreased ATP level, elevated lactate:pyruvate ratio, and abnormal mitochondrial morphology) following a high‐dose atorvastatin

treatment (100 mg/kg; El‐Ganainy et  al., 2016). Coadministration of CoQ10 was found to ameliorate both the statin‐induced myotoxicity and mitochondrial dysfunction in the rats (El‐Ganainy et  al., 2016). Unfortunately, muscle CoQ10 status was not assessed in  this study, and therefore it is uncertain whether the adverse myopathic side effects of atorvastatin treatment were attributable to a decreased muscle CoQ10 status (El‐Ganainy et al., 2016). In view of the invasiveness of a muscle biopsy, investigators have used other cell types to evaluate the effect of statin therapy on endogenous CoQ10 status. In the study by Bargossi et al. (1994), platelets were used to evaluate the effect of simvastatin (20 mg/day) treatment on endogenous CoQ10 levels in hypercholesterolemia patients and reported a 12.5% decrease from basal levels following 90 days of treatment. More recently, blood mononuclear cells (MNCs) were employed to assess the effect of the statin and rosuvastatin therapy on the CoQ10 status of children with familial hypercholesterolemia (Avis et al., 2011). In this study a 32% decrease in MNC CoQ10 status was reported following 29 weeks of statin treatment. The decrease in MNC CoQ10 status was found to be insufficient to perturb cellular ATP synthesis, although we cannot dismiss the possibility that an upregulation in glycolysis may have maintained the cellular energy status (Avis et  al., 2011). The possibility arises that the threshold to which CoQ10 must fall below  before oxidative phosphorylation becomes compromised may vary between cell types that may influence their susceptibility to statin‐induced mitochondrial dysfunction. Furthermore, an underlying defect in CoQ10 biosynthesis or the inheritance of a particular polymorphism in gene encoding for a CoQ10 biosynthetic pathway enzyme, which has been reported in the case of the COQ2 gene (which encodes for the enzyme, 4‐hydroxybenzoate polyprenyltransferase), may increase the susceptibility of an individual to statin‐ induced myotoxicity (Oh et al., 2007).

30.4 Effect of Statin Treatment on Cerebral CoQ10 Status Statin therapy has also been associated with cognitive impairment with reports of memory loss, insomnia, depression, and cerebellar ataxia being reported (Langsjoen and Langsjoen, 2015; Teive et  al., 2016). Although it is uncertain whether all statins can cross the blood–brain barrier (BBB), animal studies have indicated that the lipophilic statins, lovastatin, and simvastatin are able to cross the BBB and enter the brain (Shepardson et  al., 2011). At present it is uncertain whether the neurological side effects associated with statin therapy

Statin and Fibrate‐Induced Dichotomy of Mitochondrial Function

are linked to a diminution in cerebral CoQ10 status. However, the reports of statin‐induced cerebral ataxia (Negvesky et al., 2000; Berner, 2010; Teive et al., 2016), which is the most common clinical presentation of primary CoQ10 deficiency (Emmanuele et  al., 2012), have indicated the possibility that statins may be inducing this neurological dysfunction as the result of diminution in cerebral CoQ10 status. Unfortunately, no assessment of endogenous CoQ10 status was made in any of the studies that reported an association between statin therapy and cerebral ataxia (Negvesky et al., 2000; Berner, 2010; Teive et al., 2016). In order to assess the effect of statin therapy on cerebral CoQ10 status, the authors exposed three adult rats to simvastatin (20 mg/kg) for 3 days and then assessed the total cerebral ubiquinone status (CoQ10 + coenzyme Q9; CoQ9; predominant ubiquinone species in rat; Hargreaves, 2003) in comparison with three “vehicle”‐treated controls. Following 3 days of statin treatment, there was a 14% decrease in total cerebral ubiquinone status in comparison with control levels (Figure 30.3), which was found to be insufficient to perturb the activities of the cerebral MRC enzymes (results not shown). Because there was only a marginal decrease in cerebral total ubiquinone status following simvastatin therapy, a longer‐term study may be required, which takes into account the half‐life of ubiquinone in tissues (>50 h) before the potential inhibitory effect of statin therapy upon cerebral ubiquinone biosynthesis can be confirmed or refuted (Thelin et la., 1992). A recent in  vitro study that assessed the effect of statin therapy on a human BBB cell model reported the ability of this pharmacotherapy to induce the increased expression of LDL receptors on the BBB cell surface (Pinzón‐Daza et al., 2012). Since LDLs are the major carriers of CoQ10 Total ubiquinone 500 450 400 350 300 CTR

SIM

CTR = Control SIM = Simvastatin • 14% decrease in rat cerebral total ubiquinone (CoQ10 + CoQ9) status following 3 days of treatment with Simvastatin (SIM; 10 mg/kg/day) • No effect on MRC enzyme activity

Figure 30.3 Effect of simvastatin on rat cerebral ubiquinone status.

in the circulation (Hargreaves, 2003), this indicates that statins may also have the potential to increase cerebral CoQ10 status.

30.5 Effect of Statin Treatment on Oxidative Phosphorylation Impairment of oxidative phosphorylation has been associated with adverse side effects of statin treatment (Golomb and Evans, 2008), with the lipophilicity of the statin being an important determinant of this mitochondrial toxicity (Kaufman et  al., 2006). Lipophilic statins (cerivastatin, simvastatin, and fluvastatin) may be able to penetrate biological membranes more easily than hydrophilic ones (rosuvastatin and pravastatin) as the result of passive diffusion (Hargreaves et al., 2005; Schirris et al., 2015). However, statins can also be transported into cells through the monocarboxylate transporter, MCT4, whose variability in expression may also influence tissue levels (Dobouchaud et  al., 2000). MCT4 is predominantly expressed in the glycolytic fast‐twitch fibers of skeletal muscle, which appear to be more sensitive to statin‐ induced necrosis than their oxidative counterparts (Wilson et  al., 1998; Westwood et  al., 2005). Although evidence of mitochondrial toxicity has been reported at therapeutic levels of the drug, 0.1–1 μM (Sirvent et  al., 2005b), higher concentrations of statins as the result of tissue accumulation and drug–drug interactions may be required to elicit these adverse side effects (Kaufman et  al., 2006; Luh and Karnath, 2003). Nonetheless, an underlying defect in oxidative phosphorylation may also render the patient more susceptible to the mitochondrial toxicity and the adverse side effects of statins at lower doses (Hargreaves et  al., 2016). This is illustrated by patients with the subclinical presentation of the mitochondria DNA syndrome, mitochondrial encephalopathy, lactic acidosis, and stroke‐like episodes (MELAS), who presented with evidence of severe myotoxicity following statin therapy (Chariot et  al., 1993; Thomas et  al., 2007; Tay et  al., 2008). A number of inhibitory mechanisms have been suggested to account for the ability of statins to impair oxidative phosphorylation, which will be outlined in the following section. In addition, the putative role of statins in mitochondrial biogenesis will also be discussed. 30.5.1

Impairment of Isoprenylation

The possibility arises that the loss of MRC enzyme activity may simply result from an impairment in the isoprenylation of the enzyme. Isoprenylation is involved in the posttranslational modification of proteins and

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requires the attachment of either a farnesyl or geranylgeranyl group, which is a product of the mevalonate pathway, to a protein to facilitate its attachment to cell membranes and/or to enhance protein–protein interactions (Zhang and Casey, 1996). In the study by Arenas et  al. (2003), evidence of decreased muscle MRC complex IV activity (35% of control level) in association with muscle weakness, myalgia, and elevated plasma creatinine kinase (CK) activity (50,000 U/L: normal: 5 mmol/L) together with elevated anion gap metabolic acidosis or elevated alanine levels will confirm the diagnosis. In such cases, the concomitant determination of amylase, lipase, serum albumin, and hepatic transaminases is recommended. However, in the absence of symptoms, the routine measurement of serum lactate is not recommended, because of its low specificity (Brinkman, 2001; Panel CDC Child, 2016). In any case, because of ongoing glycolytic erythrocyte metabolism, the proper collection and processing of venous blood for lactate determination is critical to avoid false elevated levels. Prolonged tourniquet application is discouraged, and, ideally, venous blood needs to be collected in a prechilled fluoride–oxalate‐ containing tube, put on ice, and processed within 15–30 min of collection (Andersen et al., 2013). Symptomatic hyperlactatemia with lactic acidosis has been reported with all available NRTIs (Church et  al., 2001; Rey et al., 2003; Rosso et al., 2003; Shah, 2005), but

Mitochondrial Toxicity in Children and Adolescents Exposed to Antiretroviral Therapy

stavudine and didanosine carry the highest risk, especially when the two drugs are used together; in fact, the use of stavudine is discouraged in the most recent treatment guidelines, while the use of didanosine is either no longer considered a first‐line option or discouraged (WHO, 2010; Bamford et  al., 2015; Panel CDC Child, 2016). Other risk factors for lactic acidosis that have been described in the adult patient are female gender, advanced HIV infection, CD4 cell counts below 350/ mm3, African–American race, hepatitis C virus coinfection, pregnancy, elevated body mass index, and coadministration of other drugs with either stavudine or didanosine, such as metformin, tetracycline, tenofovir, and ribavirin (Panel CDC Child, 2016). Lactic acidosis is probably the only metabolic adverse event in which immediate discontinuation of all ARV agents is mandatory. Early diagnosis and implementation of supportive therapy (intravenous fluids including bicarbonate infusions, oxygen, respiratory support, etc.) is critical, because lactic acidosis is associated with high mortality rates in the adult patient (33–58%). Together with supportive therapy, supplementation with high‐ dose vitamins (thiamine and riboflavin), carnitine, vitamin C, or coenzyme Q10 has been recommended. A nucleoside‐sparing regimen or a HAART combination including mitochondrion‐friendly nucleosides, including abacavir, tenofovir, and lamivudine/emtricitabine, is recommended for resuming treatment in patients previously affected with an episode of symptomatic hyperlactatemia; close clinical follow‐up and monthly monitoring of lactate during the first months of a new HAART regimen is highly recommended in these cases. In the research setting, the pathogenesis of HIV‐ and HAART‐associated mitochondrial dysfunction in HIV‐ infected patients has been much less studied in children and adolescents compared with adults. In pediatric patients, most of the available studies have focused on the analysis of mitochondrial metabolism in peripheral blood mononuclear cells (PBMCs), which retains the tissue of choice because of the ease of sampling, despite other limitations (Maagaard et  al., 2006). Our group has demonstrated a mild depletion of mtDNA in a cohort of asymptomatic HIV‐infected children on HAART when compared with healthy controls (Morén et  al., 2011b). Similar levels of mitochondrial RNA, complex IV protein subunit content, and enzymatic activity (measured in PBMCs) were observed between these groups, and these findings were not altered by mitochondrial abundance. Previous studies in smaller case series of HIV‐infected pediatric patients had reported no differences in mtDNA levels (Cossarizza et  al., 2002; Rosso et  al., 2008), while others had identified only didanosine as a mtDNA suppressor (Saitoh et  al., 2007). A recent study has reported rates of mtDNA depletion from a large cohort of

HIV‐infected HAART‐treated Chinese children and adolescents (Liu et al., 2013) that were consistent with our results. In a subsequent analysis, we demonstrated lower levels of mtDNA and a reduction of mitochondrial function among HIV‐infected children and adolescents affected with body fat distribution abnormalities as compared with patients who were asymptomatic. These findings were independent of the use of HAART or control of viral replication (Morén et  al., 2012). A mitochondrial basis for the development of body fat abnormalities has been reported in adults (Garrabou et  al., 2011). In this context, it should be noted that the potential protective role of antioxidant supplementation in the development of lipoatrophy is under investigation (Milazzo et al., 2010). In the first study (Morén et al., 2011b), the mitochondrial genome depletion was not reflected in differences in transcription, structural, or functional activities. However, in a detailed analysis of the mitochondrial respiratory chain (MRC) that included a control group of healthy controls, we observed a significant reduction of the general CI‐III‐IV activity (but not in isolated MRC complexes) in HAART‐treated children and a reduction by 50% in global oxygen consumption in naïve patients (measured in PMBCs) (Morén et al., 2013). In the latter study, a trend toward an increase in apoptosis was also observed. These findings not only confirmed the deleterious role of HIV itself on mitochondrial function that has been extensively described in adults (Miró et  al., 2004; Cummins and Badley, 2010) but also suggested a generalized mitochondrial impairment in the HIV‐infected child due to both HIV and HAART, rather than a specific profound and localized damage to any of the complexes of the MRC. More recently, a three-fold increase in mtDNA mutations, as measured by sequencing, was reported in a small series of HIV‐infected HAART‐treated children in China (Ouyang et al., 2016). Although these patients did not show signs or symptoms consistent with mitochondrial dysfunction, some of the mutations that were identified (i.e., G15043A and A15662G) have been associated with mitochondrial diseases. In the early 2000s, different strategies regarding HAART were considered when an adult patient developed mitochondrial‐associated clinically relevant toxicity, including (i) NRTI dose reduction, (ii) interruption of therapy, (iii) use of an NRTI‐sparing regimen, and (iv) switching to a mitochondrion‐friendly NRTI. Given the current availability of new ARV drugs that are more potent and less toxic, and after the results of the SMART trial (Strategies for Management of Antiretroviral Therapy; El‐Sadr et  al., 2006), the two first strategies have become obsolete in both pediatric and adult patients. Nonetheless, we reported a partial restoration of mtDNA levels and a decrease in plasma lactatemia after planned interruption of HAART in a small case

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study of HIV‐infected children (Noguera et  al., 2010). We also demonstrated a significant reduction in cytochrome c oxidase activity among untreated HIV‐ infected children and in those receiving HAART including “first”‐generation NRTIs (ZDV, didanosine, and stavudine), but not in patients receiving lamivudine/ emtricitabine, abacavir, or tenofovir (Morén et al., 2012). Overall, these findings are consistent with the large body of evidence available on the pathogenesis of HIV‐ related mitochondrial toxicity in the HIV‐infected adult patient (Côté et  al., 2002; Miró et  al., 2003, 2004), but their clinical implications in children remain unclear, especially in the long term. Further longitudinal studies in large cohorts of MTCT HIV‐infected children and adolescents are needed to better illuminate mitochondrial toxicity pathways and their clinical significance in the pediatric population.

34.3 Mitochondrial Toxicity in HIV‐Uninfected Infants That Were Perinatally Exposed to Antiretrovirals As is the case with HIV‐infected children and adolescents, the benefit obtained from the use of ARV to prevent HIV MTCT far outweighs the ARV‐associated fetal and infant toxicity that has been thus far described. In the last 10 years, the use of the more toxic NRTIs has been progressively abandoned in the treatment of HIV infection, and this includes pregnant HIV‐infected women. The use of didanosine and/or stavudine is discouraged in pregnancy, while ZDV remains the leading alternative option (Panel CDC Pregnancy, 2016). Newer NRTIs show a much lower propensity to cause mitochondrial toxicity (Curran and Ribera, 2011). However, the long‐term risk of this exposure in these otherwise healthy children remains a concern, and long‐term investigations are required, especially as antenatal ARV drugs and regimens continue to evolve. Hematological and mitochondrial adverse events have been the most commonly reported among HEU infants to date (Panel CDC Pregnancy, 2016). Hematological toxicity was early described in HEU infants exposed to ZDV during the third trimester of pregnancy, delivery, and neonatal period (Connor et al., 1994). This mainly consists of macrocytic anemia, usually non‐symptomatic and self‐limited by the age of 3 months. Exposure to maternal or neonatal combined ARV therapy increases the severity of anemia, seldom requiring discontinuation of prophylaxis or therapeutic interventions (Dryden‐Peterson et  al., 2011). Small decreases in other cell lines (platelet, lymphocyte, CD4 and CD8 cell, and neutrophil counts) have also been

described; unlike hemoglobin levels, these decreases may persist through age 18–24 months, or even longer in the case of neutrophil and lymphocyte counts (Bunders et al., 2005). These findings have shown very little clinical relevance to date, and the timing and need of hematologic monitoring in non‐symptomatic HEU infants are uncertain; most experts recommend retesting hemoglobin levels and neutrophil counts when diagnostic HIV tests samples are obtained (Panel CDC Pregnancy, 2016). Genetic and biochemical findings consistent with mitochondrial injury have been described in HEU children, ultimately leading to infrequent clinical syndromes that are similar to those of inherited mitochondrial diseases (Blanche et  al., 1999; Barret et  al., 2003; Brogly et al., 2007). The French cohort was the first to raise the alert about the risk of clinically significant mitochondrial toxicity in a group of eight ARV‐exposed HIV‐uninfected children with severe biological and neurological abnormalities consistent with mitochondrial dysfunction, such as delays in cognitive development, motor abnormalities, seizures, abnormal cerebral magnetic resonance imaging, and hyperlactatemia, either with a typical histologic pattern or with a deficit in the enzymologic study of the respiratory chain complexes. Two of these patients died (Blanche et al., 1999). The 18‐month incidence of mitochondrial disease in this cohort was 0.26%, as compared with 0.01% in the French general population (Barret et al., 2003), and they also reported a higher risk of febrile seizures below the age of 18 months (Landreau‐Mascaro et  al., 2002). Using the same diagnostic criteria, the Pediatric AIDS Clinical Trials Group protocols 219/219C retrospectively identified 20 cases (out of 1037, 1.6%) of possible mitochondrial disease among HIV/ARV‐exposed healthy children in the United States (Brogly et  al., 2007). Of note, the median age at clinical onset in the two largest case studies of mitochondrial disease in HEU children was 7 months (Blanche et al., 1999) and 16 months (Brogly et al., 2007). It is thus possible that early mitochondrial toxicity may persist until later in life and should always be kept in mind by physicians caring for HEU children, with special attention paid to the long‐term follow‐up of this population into adulthood. In fact, the development of significant organ system abnormalities of unknown etiology in HEU children should prompt the evaluation for potential mitochondrial dysfunction (Panel CDC Pregnancy, 2016), particularly if the nervous system or the heart is affected (Williams et  al., 2010; Nozyce et  al., 2014; Sibiude et al., 2015). Hyperlactatemia rates ranging from 13 to 68% have been reported in HEU cohorts, with infants generally symptom‐free and showing a trend toward normalization during the first year of life (Alimenti et  al., 2003; Noguera et al., 2004; Ekouevi et al., 2006). A recent study

Mitochondrial Toxicity in Children and Adolescents Exposed to Antiretroviral Therapy

in the United States reported a significantly lower rate (3.4%) of hyperlactatemia, but included both infants and children up to 12 years of age (Crain et al., 2011). In our experience, elevated lactate levels were associated with gestational exposure to didanosine, but not to other ARV drugs or regimens, neither during pregnancy nor later. Three female infants (out of 127, 2.4%) developed neurologic symptoms consistent with mitochondrial dysfunction together with hyperlactatemia (Noguera et  al., 2004). In any case, routine measurement of serum lactate is not recommended in HEU infants because of its low predictive value for relevant toxicity and should only be considered if a patient develops severe clinical symptoms of unknown etiology, particularly neurologic symptoms (Panel CDC Pregnancy, 2016). As mentioned previously, in neonates and infants, venous blood samples for lactate determination need to be appropriately obtained and processed to avoid false‐positive results. If lactate levels are elevated in a symptomatic infant, ARV should be discontinued if the patient remains on prophylaxis, and supportive therapy should be initiated. The mitochondrial toxic effect derived from HIV itself has been well demonstrated in ARV‐naïve HIV‐infected patients, but cannot be directly invoked in the HEU child. Therefore, in this population, other explanations for mitochondrial dysfunction are needed, including not only NRTI‐related toxicity but also possible NRTI‐ unrelated mechanisms, especially mitochondrial toxicity affecting maternal tissues associated with fetal development, such as placenta and cord blood (Shiramizu et al., 2003; Divi et al., 2007; Gingelmaier et al., 2009; Hernàndez et al., 2012). It is likely that this phenomenon is the final result of different converging causes and pathogenic pathways. With regard to mtDNA content in PBMCs of HEU infants, some studies have shown mtDNA depletion (Poirier et al., 2003; Aldrovandi et al., 2009), while others have reported increased mtDNA levels when compared with ARV‐unexposed controls (Côté et  al., 2008; McComsey et al., 2008; Ross et al., 2012). Methodological differences regarding how mtDNA results were reported, methods for PBMC isolation, platelet contamination, timing of blood sampling, and type and duration of ARV exposure may explain these contradictory findings. We

recently longitudinally assessed mtDNA content in a large cohort of HEU infants and found stable amounts during the first year of life (Noguera‐Julian et al., 2015). These results are consistent with those reported by Aldrovandi and colleagues in a cohort of 411 healthy HIV‐unexposed pediatric patients aged 0–18 years, in whom PBMC mtDNA levels did not show age‐related differences (Aldrovandi et  al., 2009). We also observed lower complex IV enzymatic activity in HEU infants at all time points when compared with healthy controls, and that this activity showed a linear trend toward normalization with age. These data nicely reflect a reversible mitochondrial dysfunction that tends to gradually normalize over the first year of life. Moreover, these data are consistent with the previously reported normalization of plasma lactate levels in these patients (Noguera et  al., 2004), although we found no correlation between lactate levels and complex IV activities (Noguera‐Julian et  al., 2015). Previous studies had failed to demonstrate significant differences in MRC function, assessed by means of the complex II/IV ratio of cytochrome c oxidase in frozen neonatal PBMCs obtained within the first 48 h of life between HEU and unexposed neonates (McComsey et al., 2008; Ross et al., 2012). Interestingly, we observed an inverse correlation between complex IV enzymatic activity and mtDNA up to the age of 6 months (Noguera‐ Julian et al., 2015), suggesting that an increase in mtDNA content initially counteracts mitochondrial toxicity in the HEU infant (Brogly et al., 2011). No differences have been reported between HEU children and healthy controls in mtDNA deletions or mitochondrial haplotypes (Brogly et al., 2011), mitochondrial RNA content (Côté et  al., 2008), or telomere length (Poirier et al., 2003; Imam et al., 2012). Conversely, AC/ TG mtDNA mutations were more common both in HIV‐ infected mothers and their uninfected infants, raising concerns about long‐term consequences as these mutations have been associated with aging and age‐associated diseases (Jitratkosol et al., 2012). In an American study including over one million newborns, the rate of abnormal newborn metabolic screens in HEU infants was almost double that for the general population (2.2% vs. 1.2%), and most of these disorders were related to mitochondrial metabolism (Kirmse et al., 2013).

References Alam N, Cortina‐Borja M, Goetghebuer T, Marczynska M, Vigano A, Thorne C; European Paediatric HIV and Lipodystrophy Study Group in EuroCoord. Body fat abnormality in HIV‐infected children and adolescents living in Europe: prevalence and risk factors. J Acquir Immune Defic Syndr 2012;59:314–324.

Aldrovandi GM, Chu C, Shearer WT, et al. Antiretroviral exposure and lymphocyte mtDNA content among uninfected infants of HIV‐1‐infected women. Pediatrics 2009;124:e1189–e1197. Alimenti A, Burdge DR, Ogilvie GS, Money DM, Forbes JC. Lactic acidemia in human immunodeficiency

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Cossarizza A, Pinti M, Moretti L, et al. Mitochondrial functionality and mitochondrial DNA content in lymphocytes of vertically infected human immunodeficiency virus‐positive children with highly active antiretroviral therapy‐related lipodystrophy. J Infect Dis 2002;185:299–305. Côté H, Brumme ZL, Craib KJP, et al. Changes in mitochondrial DNA as a marker of nucleoside toxicity in HIV‐infected patients. N Engl J Med 2002;346:811–820. Côté HC, Raboud J, Bitnun A, et al. Perinatal exposure to antiretroviral therapy is associated with increased blood mitochondrial DNA levels and decreased mitochondrial gene expression in infants. J Infect Dis 2008;198:851–859. Crain MJ, Williams PL, Griner R, et al. Point‐of‐care capillary blood lactate measurements in human immunodeficiency virus‐uninfected children with in utero exposure to human immunodeficiency virus and antiretroviral medications. Pediatr Infect Dis J 2011;30:1069–1074. Cummins NW, Badley AD. Mechanisms of HIV‐ associated lymphocyte apoptosis: 2010. Cell Death Dis 2010;1:e99. Curran A, Ribera E. From old to new nucleoside reverse transcriptase inhibitors: changes in body fat composition, metabolic parameters and mitochondrial toxicity after the switch from thymidine analogs to tenofovir or abacavir. Expert Opin Drug Saf 2011;10:389–406. Desai N, Mathur M, Weedon J. Lactate levels in children with HIV/AIDS on highly active antiretroviral therapy. AIDS 2003;17:1565–1568. Divi RL, Leonard SL, Kuo MM, et al. Transplacentally exposed human and monkey newborn infants show similar evidence of nucleoside reverse transcriptase inhibitor‐induced mitochondrial toxicity. Environ Mol Mutagen 2007;48:201–209. Dowell P, Flexner C, Kwiterovich PO, Lane MD. Suppression of preadipocyte differentiation and promotion of adipocyte death by HIV protease inhibitors. J Biol Chem 2000;275:41325–41332. Dryden‐Peterson S, Shapiro RL, Hughes MD, et al. Increased risk of severe infant anemia after exposure to maternal HAART, Botswana. J Acquir Immune Defic Syndr 2011;56:428–436. Ekouevi DK, Touré R, Becquet R, et al. Serum lactate levels in infants exposed peripartum to antiretroviral agents to prevent mother‐to‐child transmission of HIV: Agence Nationale de Recherches Sur le SIDA et les Hépatites Virales 1209 study, Abidjan, Ivory Coast. Pediatrics 2006;118:e1071–e1077. El‐Sadr WM, Lundgren J, Neaton JD, et al. CD4+ count‐ guided interruption of antiretroviral treatment. N Engl J Med 2006;355:2283–2296.

Mitochondrial Toxicity in Children and Adolescents Exposed to Antiretroviral Therapy

Espiau M, Yeste D, Noguera‐Julian A, et al. Metabolic syndrome in children and adolescents living with HIV. Pediatr Infect Dis J 2016;35:e171–e176. Fortuny C, Deyà‐Martínez Á, Chiappini E, et al. Metabolic and renal adverse effects of antiretroviral therapy in HIV‐infected children and adolescents. Pediatr Infect Dis J 2015;34:S36–S43. Foster C, Lyall H. HIV and mitochondrial toxicity in children. J Antimicrob Chemother 2008;61:8–12. Foster C, Bamford A, Turkova A, et al. Paediatric European Network for Treatment of AIDS Treatment Guideline 2016 update: antiretroviral therapy recommended for all children living with HIV. HIV Med 2017;18(2):133–134. Garrabou G, López S, Morén C, et al. Mitochondrial damage in adipose tissue of untreated HIV‐infected patients. AIDS 2011;25:165–170. Gingelmaier A, Grubert TA, Kost BP, et al. Mitochondrial toxicity in HIV type‐1‐exposed pregnancies in the era of highly active antiretroviral therapy. Antivir Ther 2009;14:331–338. Hazra R, Hance LF, Monteiro JP, et al. Insulin resistance and glucose and lipid concentrations in a cohort of perinatally HIV‐infected Latin American children. Pediatr Infect Dis J 2013;32:757–759. Hernàndez S, Morén C, López M, et al. Perinatal outcomes, mitochondrial toxicity and apoptosis in HIV‐treated pregnant women and in‐utero‐exposed newborn. AIDS 2012;26:419–428. Imam T, Jitratkosol MH, Soudeyns H, et al. Leukocyte telomere length in HIV‐infected pregnant women treated with antiretroviral drugs during pregnancy and their uninfected infants. J Acquir Immune Defic Syndr 2012;60:495–502. Jitratkosol MH, Sattha B, Maan EJ, et al. Blood mitochondrial DNA mutations in HIV‐infected women and their infants exposed to HAART during pregnancy. AIDS 2012;26:675–683. Kirmse B, Hobbs CV, Peter I, et al. Abnormal newborn screens and acylcarnitines in HIV‐exposed and ARV‐ exposed infants. Pediatr Infect Dis J 2013;32:146–150. Koczor CA, Lewis W. Nucleoside reverse transcriptase inhibitor toxicity and mitochondrial DNA. Expert Opin Drug Metab Toxicol 2010;6:1493–1504. Landreau‐Mascaro A, Barret B, Mayaux MJ, Tardieu M, Blanche S. Risk of early febrile seizure with perinatal exposure to nucleoside analogues. Lancet 2002;359:583–584. Langat A, Benki‐Nugent S, Wamalwa D, et al. Lipid changes in Kenyan HIV‐1‐infected infants initiating highly active antiretroviral therapy by 1 year of age. Pediatr Infect Dis J 2013;32:e298–e304. Lim SE, Copeland WC. Differential incorporation and removal of antiviral deoxynucleotides by human DNA polymerase gamma. J Biol Chem 2001;276:23616–23623.

Liu K, Sun Y, Liu D, et al. Mitochondrial toxicity studied with the PBMC of children from the Chinese national pediatric highly active antiretroviral therapy cohort. PLoS One 2013;8:e57223. Maagaard A, Holberg‐Petersen M, Kollberg G, Oldfors A, Sandvik L, Bruun JN. Mitochondrial (mt)DNA changes in tissue may not be reflected by depletion of mtDNA in peripheral blood mononuclear cells in HIV‐infected patients. Antivir Ther 2006;11:601–608. McComsey GA, Kang M, Ross AC, et al. Increased mtDNA levels without change in mitochondrial enzymes in peripheral blood mononuclear cells of infants born to HIV‐infected mothers on antiretroviral therapy. HIV Clin Trials 2008;9:126–136. Milazzo L, Menzaghi B, Caramma I, et al. Effect of antioxidants on mitochondrial function in HIV‐1‐ related lipoatrophy: a pilot study. AIDS Res Hum Retroviruses 2010;26:1207–1214. Miró O, López S, Pedrol E, et al. Mitochondrial DNA depletion and respiratory chain enzyme deficiencies are present in peripheral blood mononuclear cells of HIV‐ infected patients with HAART‐related lipodystrophy. Antivir Ther 2003;8:333–338. Miró O, López S, Martínez E, et al. Mitochondrial effects of HIV infection on the peripheral blood mononuclear cells of HIV‐infected patients who were never treated with antiretrovirals. Clin Infect Dis 2004;39:710–716. Morén C, Noguera‐Julian A, Rovira N, et al. Mitochondrial impact of human immunodeficiency virus and antiretrovirals on infected pediatric patients with or without lipodystrophy. Pediatr Infect Dis J 2011a;30:992–995. Morén C, Noguera‐Julian A, Rovira N, et al. Mitochondrial assessment in asymptomatic HIV‐infected paediatric patients on HAART. Antivir Ther 2011b;16:719–724. Morén C, Noguera‐Julian A, Garrabou G, et al. Mitochondrial evolution in HIV‐infected children receiving first‐ or second‐generation nucleoside analogues. J Acquir Immune Defic Syndr 2012;60:111–116. Morén C, Garrabou G, Noguera‐Julian A, et al. Study of oxidative, enzymatic mitochondrial respiratory chain function and apoptosis in perinatally HIV‐infected pediatric patients. Drug Chem Toxicol 2013;36:496–500. Noguera A, Fortuny C, Sanchez E, et al. Hyperlactatemia in human immunodeficiency virus‐infected children receiving antiretroviral treatment. Pediatr Infect Dis J 2003;22:778–782. Noguera A, Fortuny C, Muñoz‐Almagro C, et al. Hyperlactatemia in human immunodeficiency virus‐ uninfected infants who are exposed to antiretrovirals. Pediatrics 2004;114:e598–e603. Noguera A, Morén C, Rovira N, et al. Evolution of mitochondrial DNA content after planned interruption

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of HAART in HIV‐infected pediatric patients. AIDS Res Hum Retroviruses 2010;26:1015–1018. Noguera‐Julian A, Morén C, Rovira N, et al. Decreased mitochondrial function among healthy infants exposed to antiretrovirals during gestation, delivery and the neonatal period. Pediatr Infect Dis J 2015;34:1349–1354. Nozyce ML, Huo Y, Williams PL, et al. Safety of in utero and neonatal antiretroviral exposure: cognitive and academic outcomes in HIV‐exposed, uninfected children 5‐13 years of age. Pediatr Infect Dis J 2014;33:1128–1133. Ouyang Y, Qiao L, Liu K, et al. Mitochondrial DNA mutations in blood samples from HIV‐1‐infected children undergoing long‐term antiretroviral therapy. Mutat Res Genet Toxicol Environ Mutagen 2016;805:1–6. Panel on Antiretroviral Therapy and Medical Management of HIV‐Infected Children. Guidelines for the Use of Antiretroviral Agents in Pediatric HIV Infection (2016). Available at http://aidsinfo.nih.gov/contentfiles/ lvguidelines/pediatricguidelines.pdf. Accessed on November 1, 2016. Panel on Treatment of HIV‐Infected Pregnant Women and Prevention of Perinatal Transmission. Recommendations for Use of Antiretroviral Drugs in Pregnant HIV‐1‐ Infected Women for Maternal Health and Interventions to Reduce Perinatal HIV Transmission in the United States (2016). Available at http://aidsinfo.nih.gov/ contentfiles/lvguidelines/PerinatalGL.pdf. Accessed on November 1, 2016. Piloya T, Bakeera‐Kitaka S, Kekitiinwa A, Kamya MR. Lipodystrophy among HIV‐infected children and adolescents on highly active antiretroviral therapy in Uganda: a cross sectional study. J Int AIDS Soc 2012;15:17427. Poirier MC, Divi RL, Al‐Harthi L, et al. Long‐term mitochondrial toxicity in HIV‐uninfected infants born to HIV‐infected mothers. J Acquir Immune Defic Syndr 2003;33:175–183. Rey C, Prieto S, Medina A, Pérez C, Concha A, Menéndez S. Fatal lactic acidosis during antiretroviral therapy. Pediatr Crit Care Med 2003;4:485–487. Ross AC, Leong T, Avery A, et al. Effects of in utero antiretroviral exposure on mitochondrial DNA levels, mitochondrial function and oxidative stress. HIV Med 2012;13:98–106. Rosso R, Di Biagio A, Ferrazin A, Bassetti M, Ciravegna BW, Bassetti D. Fatal lactic acidosis and mimicking Guillain‐Barré syndrome in an adolescent with human immunodeficiency virus infection. Pediatr Infect Dis J 2003;22:668–670. Rosso R, Nasi M, Di Biagio A, et al. Effects of the change from Stavudine to tenofovir in human

immunodeficiency virus‐infected children treated with highly active antiretroviral therapy: studies on mitochondrial toxicity and thymic function. Pediatr Infect Dis J 2008;27:17–21. Saitoh A, Fenton T, Alvero C, Fletcher CV, Spector SA. Impact of nucleoside reverse transcriptase inhibitors on mitochondria in human immunodeficiency virus type 1‐infected children receiving highly active antiretroviral therapy. Antimicrob Agents Chemother 2007;51:4236–4242. Saitoh A, Haas RH, Naviaux RK, Salva NG, Wong JK, Spector SA. Impact of nucleoside reverse transcriptase inhibitors on mitochondrial DNA and RNA in human skeletal muscle cells. Antimicrob Agents Chemother 2008;52:2825–2830. Shah I. Lactic acidosis in HIV infected children due to antiretroviral therapy. Indian Pediatr 2005;42:1051–1052. Sharma TS, Jacobson DL, Anderson L, et al. Short communication: The relationship between mitochondrial dysfunction and insulin resistance in HIV‐infected children receiving antiretroviral therapy. AIDS Res Hum Retroviruses 2013;29:1211–1217. Shiramizu B, Shikuma KM, Kamemoto L, et al. Placenta and cord blood mitochondrial DNA toxicity in HIV‐ infected women receiving nucleoside reverse transcriptase inhibitors during pregnancy. J Acquir Immune Defic Syndr 2003;32:370–374. Sibiude J, Le Chenadec J, Bonnet D, et al. In utero exposure to zidovudine and heart anomalies in the ANRS French perinatal cohort and the nested PRIMEVA randomized trial. Clin Infect Dis 2015;61:270–280. Sollai S, Noguera‐Julian A, Galli L, et al. Strategies for the prevention of mother to child transmission in Western countries: an update. Pediatr Infect Dis J 2015;34(5 Suppl 1):S14–S30. Takemoto JK, Miller TL, Wang J, et al. Insulin resistance in HIV‐infected youth is associated with decreased mitochondrial respiration. AIDS 2017;31:15–23. van Ramshorst MS, Struthers HE, McIntyre JA, Peters RP. Blood lactate in HIV‐infected children on antiretroviral therapy in rural South Africa. Pediatr Infect Dis J 2014;33:393–395. Williams PL, Marino M, Malee K, Brogly S, Hughes MD, Mofenson LM; PACTG 219C Team. Neurodevelopment and in utero antiretroviral exposure of HIV‐exposed uninfected infants. Pediatrics 2010;125:e250–e260. World Health Organization. Antiretroviral Therapy of HIV Infection in Infants and Children: Towards Universal Access: Recommendations for a Public Health Approach ‐ 2010 Revision (2010). Available at: http:// www.who.int/hiv/pub/paediatric/infants2010/en/. Accessed on November 1, 2016.

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35 Drug‐Induced Mitochondrial Cardiomyopathy and Cardiovascular Risks in Children Neha Bansal1, Mariana Gerschenson2, Tracie L. Miller3, Stephen E. Sallan4,5, Jason Czachor1, Hiedy Razoky1, Ashley Hill1, Miriam Mestre1, and Steven E. Lipshultz1 1

Wayne State University School of Medicine, Children’s Hospital of Michigan, Detroit, MI, USA John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA 3 Miller School of Medicine, University of Miami, Miami, FL, USA 4 Dana Farber Cancer Institute, Department of Pediatric Oncology, Harvard Medical School, Boston, MA, USA 5 Department of Medicine, Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA, USA 2

CHAPTER MENU 35.1 35.2 35.3 35.4

Introduction, 529 HIV Therapy, 529 Cancer Therapy, 533 Conclusion, 538 Funding, 539 References, 539

35.1

Introduction

Mitochondria are the power plants of the cells and supply most of the energy needed by the cell. The principal function of mitochondria is to make energy in the form of ATP. Often, this function is thought to be the only one of this organelle. However, mitochondria are much more than simple cellular batteries. They are important in regulating cell survival, proliferation (McBride et al., 2006), and death (Kroemer et  al., 2007), as well as calcium homeostasis (Hajnoczky et  al., 2006). Organs, such as cardiac and skeletal muscles and the brain, are metabolically more active and depend more on mitochondrial‐ produced energy than do other cells (Szewczyk and Wojtczak, 2002). As a result, drug‐induced mitochondrial failure increases damage to these critical organs. Mitochondrial impairment is an inadvertent side effect of many medications that causes various organ toxicities, especially to the heart, given its high‐energy demand. Thus, preventing and treating this impairment and understanding its implications for drug development are important. This chapter describes the mechanisms and

the short‐ and long‐term consequences of HIV medications and cancer chemotherapies that are associated with mitochondrial dysfunction and its cardiac consequences in children.

35.2

HIV Therapy

Adults and children with human immunodeficiency virus (HIV) are now living longer because of advances in antiretroviral therapy (ART). However, HIV is still a chronic illness. The long‐term complications of the infection and its treatment are increasingly apparent in both adults and children. Children differ from adults in that most have been exposed to HIV their entire lives (even in utero) and are likely to be exposed to ART for most of the rest of their lives. Furthermore, these exposures occur during vulnerable stages of development: in utero, infancy, and hormonal changes of puberty. Not only has ART helped control disease progression and has extended life for HIV‐infected patients, but it also has emerging and progressive longer‐term complications,

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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Mitochondrial Dysfunction by Drug and Environmental Toxicants

Table 35.1 Nucleoside reverse transcriptase inhibitor toxicities in HIV‐infected patients and their relation to mitochondrial pathways. Mitochondrial pathway

Mitochondrial structure

mtDNA depletion

Decreased mitochondrial proteins

Altered mitochondrial function

Clinical features

NRTI(s)

Skeletal myopathy

Zidovudine

Abnormal, ragged red fibers

Yes

Yes

Yes

Cardiomyopathy

Zidovudine, stavudine

Abnormal

ND

ND

ND

Neuropathy

Zalcitabine, stavudine, didanosine

Abnormal

Yes

ND

ND

Macrocytosis

Zidovudine, stavudine

ND

ND

ND

ND

Pancreatitis

Didanosine

ND

ND

ND

ND

Hepatic steatosis

Zidovudine, stavudine, didanosine

ND

Yes

ND

ND

Lactic acidosis

Zidovudine, stavudine, didanosine

NA

NA

NA

ND

Stavudine, zidovudine

Abnormal

Yes

ND

Lipodystrophy a

Acute kidney injury (AKI)

a

Tenofovir

Yes

a

Yes

a

ND

Yes a

NDa

Gerschenson and Brinkman (2004). Reproduced with permission of Elsevier. NA, not applicable; ND, not determined; NRTI, nucleoside reverse transcriptase inhibitor. a Not in the original table.

such as mitochondrial abnormalities (Dagan et al., 2002; Gerschenson and Brinkman, 2004; Shikuma et al., 2005; Barlow‐Mosha et al., 2013). Metabolic consequences have been reported in up to 60% of HIV‐infected children (Jaquet et al., 2000; Arpadi et al., 2001; Miller et al., 2009) and include dyslipidemia, insulin resistance (IR), and body composition changes (lipoatrophy and lipohypertrophy) (Carr et al., 1998; McComsey and Leonard, 2004; Bitnun et  al., 2005; Sanchez Torres et  al., 2005; Dzwonek et  al., 2006; Kim et al., 2007; Miller et al., 2008). Mitochondrial dysfunction secondary to ART is drug and organ specific (Table 35.1). This specificity was first described in 1988, in HIV patients treated with high doses of the nucleoside reverse transcriptase inhibitor (NRTI), zidovudine (Gertner et al., 1989). These patients experienced mitochondrial‐related skeletal muscle myopathies that were identified by histological and electron microscopy examination of biopsy tissue. Histologically, ragged red fibers were observed, which is the accumulation of mitochondria with paracrystalline inclusions in the subsarcolemmal space (Dalakas et  al., 1990). Concentrations of mtDNA, RNA, and proteins in the muscles of these patients were decreased but were reversed in 50% of patients after the drug was withdrawn (Dagan et al., 2002). These findings led to the hypothesis that NRTIs inhibit mtDNA replication, causing these myopathies. HIV‐infected adults receiving ART are more likely to have altered mtRNA and mtDNA than

HIV‐infected but ART‐naïve individuals (McComsey et al., 2008), indicating that mitochondrial abnormalities cannot be explained by HIV infection alone. Several studies have now reported that mitochondrial function is affected by HIV and ART and perhaps by cytokines through a diverse array of mechanisms, including direct increases in reactive oxygen species (ROS) (Hulgan et al., 2003; McComsey and Morrow, 2003), uncoupling of mitochondria (Pace et  al., 2003; McComsey et  al., 2006), decreases in ATP concentrations in adipocytes and pre‐ adipocytes (Gerschenson et  al., 2006), and apoptosis (Gerschenson and Brinkman, 2004). The combination of ART and HIV in targeting mitochondria is a multi‐hit process (Figure 35.1). The peripheral blood mononuclear cells (PBMCs) of untreated HIV‐infected patients have lower mtDNA content than that of healthy controls (Miro et  al., 2004). Zidovudine inhibits the mitochondrial adenylate, kinase, and adenosine nucleotide translocator in isolated rat liver mitochondria (Gerschenson and Brinkman, 2004), as well as thymidine phosphorylation in rat heart and liver mitochondria (McKee et  al., 2004; Lynx et al., 2006; Susan‐Resiga et al., 2007). HIV polypeptides, such as gp120, can increase oxidative stress (Louboutin et  al., 2010), and Tat induces apoptosis (Kruman et  al., 1998). Thus, decreased mtDNA concentrations do not appear to be a prerequisite for mitochondrial dysfunction. As a result, evaluating mitochondrial function is critical when considering ART‐associated mitochondrial toxicity.

Drug‐Induced Mitochondrial Cardiomyopathy and Cardiovascular Risks in Children HIV

ART

DNA polymerase-γ Uncoupling Transport Oxidative stress

Cytokines

Apoptosis Phosphorylation Proteolytic processing Glycosylation

Figure 35.1 Multi‐hit hypothesis of mitochondrial dysfunction from HIV, ART, and cytokines. Mitochondria are targeted at multiple functional levels by ART drugs, HIV, and cytokines, all of which alter mitochondrial DNA replication, energy metabolism, and apoptosis. Gerschenson and Brinkman (2004). Reproduced with permission of Elsevier.

NRTIs inhibit mtDNA polymerase‐γ and deplete mtRNA, which in turn impair oxidative phosphorylation (OXPHOS), alter ATP concentrations, and cause cell apoptosis and peripheral subcutaneous lipoatrophy, with or without visceral fat accumulation (Gerschenson and Brinkman, 2004). Protease inhibitors inhibit Glut4 (Hruz et al., 2008), transcription factors (e.g., PPAR‐γ, SREBP‐1 [ritonavir]) (Mallon et al., 2005), and fatty acid synthase (saquinavir and ritonavir) (Bastard et  al., 2002; Mallon et  al., 2005); decrease adipocyte differentiation (Caron et al., 2003); and cause cellular apoptosis (Domingo et al., 1999) and IR (Dube et al., 2005). These inhibitors, such as efavirenz, can suppress lipogenic pathways of adipocytes in vitro (Rodriguez de la Concepcion et al., 2005). The most common oxidation products of mtDNA include 8‐oxo‐deoxyguanosine, and high concentrations of the base modifications have been detected in monkeys treated with NRTIs (Bialkowska et al., 2000) and in HIV patients on a stavudine‐based regimen (Gerschenson et  al., 2009). In some studies, up to a third of HIV‐ infected children reportedly have chronic symptom‐free hyperlactatemia (normal values up to 2.1 mmol/L) (Desai et  al., 2003; Noguera et  al., 2003). Mitochondrial dysfunction, hyperlactatemia, and several symptomatic cases have also been described in HIV‐uninfected ART‐ exposed healthy infants (Blanche et  al., 1999; Noguera et al., 2004; Brogly et al., 2007). Clinical features of mitochondrial dysfunction in HIV include lipodystrophy, hepatic steatosis, lactic acidosis, skeletal myopathy, cardiomyopathy, and peripheral neuropathy (Gerschenson and Brinkman, 2004). Zidovudine was the first NRTI used in 1985 to treat HIV infection, and sustained treatment with high doses caused serious myopathies in many patients (Yarchoan et  al., 1986;

Scruggs and Dirks Naylor, 2008). Currently, in combination with other ART drugs, the daily dose of zidovudine has been decreased, which substantially decreased the incidence of myopathy. Although in vitro, other NRTIs are more toxic than zidovudine, and skeletal myopathy has been described predominantly with zidovudine (Loutfy et al., 2003). In contrast, only a few HIV patients have experienced dilated cardiomyopathy during NRTI treatment, and only two had mitochondrial abnormalities (Tanuma et al., 2003). High‐dose zidovudine has been associated with mitochondrial cardiomyopathy in rats (Lewis et al., 1991) and worsened cardiac dysfunction in adult transgenic mice with AIDS (Lewis et al., 2000). This cardiomyopathy altered the steady‐state abundance of mtDNA, mitochondrial RNA, and mitochondrially encoded polypeptides in affected tissues and was associated with molecular evidence of cardiac remodeling (Lewis et al., 1992). However, in contrast to the animal studies, in a prospective study, zidovudine was not associated with acute or chronic abnormalities in left ventricular structure or function in HIV‐infected infants perinatally exposed to the drug (Lipshultz et al., 1992, 2000). In 24 children with symptomatic HIV infection, echocardiograms were acquired immediately before zidovudine therapy was started and at a mean of 1.32 years after therapy began. Progressive left ventricular dilatation caused progressive elevation of ventricular afterload, which depressed ventricular performance, but intrinsic ventricular contractility remained normal (Lipshultz et  al., 1992). The study also followed 382 infants without HIV infection (36 with postpartum zidovudine exposure) and 58 HIV‐infected infants (12 with postpartum zidovudine exposure) with serial echocardiograms (Lipshultz et al., 2000). Zidovudine exposure was not associated with marked echocardiographic abnormalities in mean left ventricular fractional shortening, end‐diastolic dimension, contractility, or mass in either non‐HIV‐infected or HIV‐infected infants. Thus, current ART regimens appear to have reduced the incidence of myopathies. Initial concerns about pediatric HIV‐associated cardiovascular disease (CVD) came from studies in fetal monkeys, in which transplacental exposure to NRTIs resulted in mitochondrial abnormalities, including decreased mtDNA copies per cell and OXPHOS (Gerschenson et  al., 2000, 2004). Additional studies in 1‐year‐old monkeys after NRTI treatment found mitochondrial damage and increased concentrations of mtDNA in the heart (Divi et  al., 2005). HIV‐infected adults have a higher risk of early CVD than that of the  general population because of the HIV infection itself and ARV treatment (Bavinger et  al., 2013; Post et al., 2014).

531

Mitochondrial Dysfunction by Drug and Environmental Toxicants

The global risk of premature CVD in children and adolescents with vertically acquired HIV infection appears to be increasing. Concentrations of cardiac markers, such as carotid intima‐media thickness, were higher in ART‐treated, HIV‐infected children than in age‐, gender‐, race‐, and body mass index (BMI)‐matched uninfected controls, suggesting an elevated cardiovascular risk (McComsey et al., 2007). The US obesity epidemic among youth is also affecting the HIV‐infected children, with prevalence rates up to 12% (Jacobson et al., 2011). Together with obesity and other HIV‐unrelated factors, abnormal body fat distribution, lipid abnormalities, and altered glucose metabolism increase the risk of future CVD in these children (Morrison et  al., 2007). Finally, uncontrolled HIV‐related inflammatory and immunologic factors also contribute to cardiovascular risk (Kuller et al., 2008). Recently, in a large cohort of perinatally HIV‐infected adolescents in the United States, Pathobiological Determinants of Atherosclerosis in Youth (PDAY) risk scores for coronary arteries and abdominal aorta were 1 unit or higher (McMahan et  al., 2005) in 48 and 24%, respectively, indicating an increased CVD risk. The highest scores were predicted by HIV disease severity and boosted protease inhibitor use (Patel et al., 2014). In a prospective cohort study, concentrations of biomarkers of vascular dysfunction were higher in HIV‐infected children than in HIV‐exposed but uninfected children, as were CVD risk factors, including unfavorable lipid concentrations and active HIV replication. Among perinatally HIV‐infected youth with and without IR matched on demographics, pubertal develop-

(a)

ment, current ARV exposures, and HIV disease severity, measures of multiple components of mitochondrial respiration were lower in those with IR than in those without (Takemoto et  al., 2017), which suggests that IR increases the risk of CVD. In PBMCs, mitochondrial respiration was lower in those youth with IR compared with those without. The positive correlation between non‐ mitochondrial respiration and fasting glucose concentrations suggests damage to the electron transport chain. These findings point to a disruption in the use of nutrients to produce energy in the insulin‐resistant group. This disruption suggests dysfunctional mitochondria or a breakdown in the hepatic‐β‐cell feedback loop, both of which can account for the differences in values of glucose, insulin, and mitochondrial respiration. This correlation also suggests that IR may be associated with an alternative and less‐efficient means of energy production (Figure 35.2). Concentrations of mitochondrial respiration markers were lower in HIV‐infected youth with IR than in those without; thus, the disordered mitochondrial respiration may be a potential mechanism for IR in this population. There is no proven, effective therapy for NRTI‐associated mitochondrial toxicity, other than withdrawing the implicated agent. Even then, symptoms may not resolve completely. Similarly, there are no established methods for preventing therapy‐related mitochondrial toxicity. Toxicities depend on the combination of individual drugs and ART and should be monitored at each clinic visit (Welch et al., 2009). Some small studies have found benefits from antioxidants, such as antioxidant supplementation (with vitamin E, beta‐carotene, N‐acetylcysteine,

(b) 1800

9000

1600

8000

p = 0.0091 rho = –0.32

1400 1200 1000 800 600 400 200 0

Non-mitochondrial respiration

Basal respiration (pmol)

532

p = 0.020 rho = 0.29

7000 6000 5000 4000 3000 2000 1000 0

0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15

HOMA-IR

60

70

80

90

100

110

Fasting glucose

Figure 35.2 Metabolic correlations associated with mitochondrial respiratory characteristics. Data are from 66 children perinatally infected with HIV. (a) Relationship between basal respiration and homeostatic model assessment with insulin resistance (HOMA‐IR) with and without insulin resistance. Basal respiration was inversely related to insulin‐resistant status as determined by HOMA‐IR (p = 0.009, Spearman’s rho = −0.32). (b) Non‐mitochondrial respiration was positively correlated with fasting glucose (p = 0.02, Spearman’s rho = 0.29). Takemoto et al. (2017). Reproduced with permission of Wolters Kluwer Health.

Drug‐Induced Mitochondrial Cardiomyopathy and Cardiovascular Risks in Children

Table 35.2 Recommended lifestyle habits and monitoring of metabolic and renal adverse effects in the routine follow‐up of HIV‐infected children and adolescents. Recommended lifestyle habits Calorically appropriate low‐fat diet, especially in patients with a high BMI or dyslipidemias Sufficient calcium and vitamin D intake Regular aerobic exercise; weight‐bearing exercise after puberty Smoking avoidance or cessation Avoidance of other toxic substances, illicit or not Monitoring proposal for routine follow‐up of HIV‐infected children and adolescents Calculate BMI from body weight and height measurements at each visit; measure blood pressure every 3–6 months Assess metabolic toxicities at each visit, including abnormal patterns of body fat distribution In the absence of symptoms, measuring lactate concentrations is not recommended Laboratory monitoring for dyslipidemias and glucose homeostasis before and 4–12 weeks after HAART initiation or switch and at least every 6–12 months thereafter in the absence of ongoing toxicity concerns Periodically measure vitamin D concentrations, especially in the presence of several risk factors for low bone mineral density If available, acquire dual‐energy X‐ray absorptiometry scans every 1–2 years, especially among children with abnormal findings or in the presence of several risk factors for low bone mineral density Calculate estimated glomerular filtration rate from proteinuria and glycosuria measurements at least every 6–12 months and every 3–6 months if tenofovir is used Fortuny et al. (2015). Reproduced with permission of Wolters Kluwer Health.

selenium, Ginkgo biloba extracts, and nutritional supplements), but optimal prevention and monitoring strategies have not been determined (Lopez et  al., 2003; Cherry et  al., 2005). In the absence of proven pharmacological and other medical treatments, lifestyle modifications (e.g., healthy diet and exercise; avoiding smoking and other toxic substances) are probably the most important therapeutic approach to preventing and treating complications in HIV‐infected children (Welch et  al., 2009) (Table 35.2).

35.3

Cancer Therapy

One of the major successes of pediatric oncology is that children with childhood cancers are now living substantially longer and healthier lives because of advances in chemotherapeutic agents. Improved 5‐year survival rates, from less than 58% in the 1970s to 83% today

(Ward et al., 2014), have increased the number of long‐ term survivors of childhood cancer in the United States to an estimated 420,000 (Armstrong and Ross, 2014). Most of this success is attributed to the widely used and highly effective anthracycline, doxorubicin. Anthracycline chemotherapeutics, such as doxorubicin and daunorubicin, are cytotoxic agents used to treat a spectrum of childhood malignancies, including acute lymphoblastic leukemia (ALL), acute myelogenous leukemia, Hodgkin disease, and non‐Hodgkin lymphoma. However, over the years, multiple long‐term follow‐up studies have discovered that doxorubicin treatment is associated with late cardiac effects years later (Lipshultz et  al., 1991; Lipshultz and Adams, 2010; Lipshultz et al., 2013a). In fact, cardiotoxicity is the most serious shortcoming of anthracycline‐based treatment of cancer (Barry et al., 2007). Chemotherapeutic medications are designed to interfere with rapidly dividing neoplastic cells. However, in the process, they can adversely affect normal cell division, especially in tissues with rapid turnover. The cardiovascular system’s regenerative capacity is limited, so potential adverse effects from these chemotherapeutic agents may be unpredictable. Cardiotoxic effects have been documented for several classes of cancer drugs, including anthracyclines (e.g., doxorubicin and epirubicin), alkylating agents (e.g., busulfan and cyclophosphamide), antimetabolites (including 5‐fluorouracil and cytarabine), antimicrotubule agents (e.g., vinca alkaloids), targeted agents (e.g., lapatinib and trastuzumab), and radiation (Simbre et al., 2005; Fulbright, 2011). Of these, anthracycline‐related cardiotoxicity is particularly well studied. The mechanisms of anthracycline‐induced cardiotoxicity remain uncertain. Once anthracycline enters the cell, it forms complexes with iron and reduces the quinone moiety to subquinone. This reduction leads to a cascade production of ROS, which causes some of the deleterious effects on the cell and its components and that ultimately kills cells. Oxidative stress also induces nitric oxide synthase and produces nitric oxide and peroxynitrite, which inactivate myofibrillar creatine kinase and other important cardiac enzymes (Mihm and Bauer, 2002; Fogli et al., 2004). This damage, and the fact that cardiomyocytes divide too slowly to replace damaged cells, leads to organ damage. Several other mechanisms for anthracycline‐related cardiotoxicity have been postulated, including the induction of apoptosis, the production of vasoactive amines, the formation of toxic metabolites, the upregulation of nitric oxide synthetase, and the inhibition of transcription and translation (Ito et  al., 1990; Peng et  al., 2005; Chen et al., 2007). Anthracyclines uncouple the electron transport chain, which creates highly ROS and impairs phosphorylation and ATP synthesis (Simunek et  al.,

533

534

Mitochondrial Dysfunction by Drug and Environmental Toxicants

2009). Anthracyclines also disturb mitochondrial calcium homeostasis, destabilize the mitochondrial membrane, decrease ATP production, and ultimately kill the cell. Cardiomyocytes exposed to anthracyclines show other changes, which may or may not depend on the oxidative pathway. These changes include depleted cardiac stem cells (De Angelis et al., 2010), impaired DNA synthesis (Kalyanaraman et  al., 2002), impaired cell signaling that triggers cell death (Jurcut et  al., 2008), altered gene expression (Rusconi et al., 2004), inhibited calcium release from the sarcoplasmic reticulum (Lowis et  al., 2006), impaired formation of the protein titin in sarcomeres (Lebrecht et al., 2005), and impaired mitochondrial creatine kinase activity and function (Ryberg et al., 2008). These subcellular processes often continue for weeks after anthracycline exposure, which may provide insight into the mechanism of chronic cardiomyopathy (Tokarska‐Schlattner et al., 2006). Given the high‐energy demands of the heart, 45% of myocardial volume is comprised of mitochondria, making them more abundant in cardiac tissue than in other tissues (Marin‐Garcia et al., 2001; Gottlieb and Gustafsson, 2011). Cardiac cells are thus more susceptible to free radical damage because of their highly oxidative metabolism, relatively poor antioxidant defenses, and high concentration of cardiolipin, a phospholipid concentrated in the inner mitochondrial membrane and critical to cell respiration. Cardiolipin accumulates anthracycline in the cardiomyocytes at concentrations 100‐fold higher than those in plasma. Anthracyclines are thought to inhibit the respiratory chain by binding to cardiolipin or by interacting with mtDNA (Lebrecht and Walker, 2007). Doxorubicin damages mtDNA by several mechanisms. Anthracyclines can cause acute mitochondrial toxicity. Early mitochondrial lesions have been found in cardiomyocytes, and the mitochondrial ultrastructure is altered rapidly after doxorubicin infusion (Ferrans, 1978). The rapid kinetics of mitochondrial impairment after acute doxorubicin exposure are likely to result from either the direct ROS‐mediated respiratory complex inactivation or the ability of the Fe3+–doxorubicin complex to bind to cardiolipin (Goormaghtigh et al., 1990; Keizer et al., 1990). Mutations in mtDNA have been identified at low concentrations of doxorubicin after short‐term treatment (Adachi et al., 1993; Serrano et al., 1999). Acute doxorubicin exposure also reduces mtDNA copy numbers in rat  hearts (Hixon et  al., 1981). Doxorubicin may be metabolically transformed into a quinone methide and, through this intermediate, binds covalently to mtDNA (Abdella and Fisher, 1985). The mitochondria are injured slightly during acute doxorubicin treatment. The lesions then accumulate with time and ultimately impinge on the bioenergetic

capacity of the organelles, even when the initial doxorubicin insult is no longer present. This mechanism hinges on the fact that the respiratory chain dysfunction associated with the mtDNA damage can subsequently liberate ROS at the respiratory chain. In turn, ROS may either attack the respiratory chain itself or damage the mitochondrial genome (Corral‐Debrinski et al., 1991; Richter, 1992). MtDNA depletion, mtDNA mutations, and respiratory chain dysfunction that begun during anthracycline chemotherapy may lead to formation of ROS and a cycle of secondary mtDNA and respiratory chain insults that accumulate long after treatment. Such events would explain, in part, the molecular mechanism of “dose memory” and delayed‐onset cardiomyopathy (Lebrecht et al., 2003; Lebrecht et al., 2005). In fact, mitochondrial dysfunction resulting in bioenergetics crisis is an apparent hallmark of doxorubicin‐related cardiotoxicity (Tokarska‐Schlattner et al., 2006). Lastly, doxorubicin inhibits topoisomerase II, an ATP‐ dependent nuclear enzyme that catalyzes the knotting– unknotting and catenation–decatenation reactions during normal replication of double‐stranded DNA (Tsai‐Pflugfelder et al., 1988). Doxorubicin binds to the topoisomerase II–DNA complex and inhibits the broken DNA strands from religating. This process can also induce single‐ or double‐stranded DNA breaks (Tewey et  al., 1984) and a quantitative defect of mtDNA copy number (mtDNA depletion) (Lawrence et  al., 1993). Both qualitative (mutations) and quantitative (depletion) mtDNA lesions may interact synergistically and severely compromise the synthesis of mtDNA‐encoded respiratory chain subunits. Recently, information about doxorubicin‐induced topoisomerase‐II β (Top2β) alterations has partially clarified the mechanism of doxorubicin‐induced toxicity (Zhang et al., 2012; Khiati et al., 2014). The Top2β‐doxorubicin‐DNA ternary cleavage complex induces DNA double‐strand breaks, killing cells (Lyu et  al., 2007). Furthermore, deletion of theTop2β gene in cardiomyocytes of mice protects the cells from doxorubicin‐ induced DNA double‐strand breaks and transcriptome changes that are responsible for defective mitochondrial biogenesis and ROS formation (Zhang et  al., 2012). In patient’s peripheral blood leukocyte, Top2β concentrations were higher in anthracycline‐sensitive patients. This was associated with decreased LV ejection fraction [LVEF] ≥ 10% from baseline and LVEF < 50%, (despite receiving a cumulative doxorubicin dose ≤250 mg/m2) than in anthracycline‐resistant patients (who received a cumulative doxorubicin dose ≥450 mg/m2 with LVEF ≥ 50%), which suggests the potential use of Top2β as a surrogate marker for susceptibility to anthracycline‐induced cardiotoxicity (Vejpongsa and Yeh, 2014). Additionally,

Drug‐Induced Mitochondrial Cardiomyopathy and Cardiovascular Risks in Children

nuclear‐encoded mitochondrial topoisomerase I single‐ nucleotide polymorphisms is associated with doxorubicin cardiotoxicity and could also be examined as a biomarker (Khiati et al., 2014; Nitiss and Nitiss 2014). Doxorubicin‐associated cardiotoxicity is likely at least partially caused by semiquinone free radicals generated by doxorubicin–iron complexes in the myocardium. Furthermore, one animal study found a dose‐dependent increase of doxorubicin in mitochondria, indicating that  doxorubicin accumulates in the mitochondria and increases mitochondrial iron concentrations (Ichikawa et al., 2014). Reaction of these free radicals with oxygen (ROS) leads to lipid peroxidation and ultimately DNA damage (Vile and Winterbourn, 1990; Wallace, 2003). In addition, dexrazoxane, a cardioprotectant, chelates iron, thereby reducing iron from forming doxorubicin–iron complexes and, as a result, reducing free radical DNA damage (Lipshultz et al., 2004). Preclinical studies have associated doxorubicin exposure with irreversible cardiac mitochondrial dysfunction (Zhou et al., 2001; Lipshultz et al., 2016). Clinical histological studies have observed doxorubicin‐related structural abnormalities, and one recent study of childhood ALL survivors found that gene polymorphisms of mitochondrial expression that influences translational control may affect mtDNA replication and possibly indicate susceptibility to doxorubicin (Kwok et al., 2011). In late doxorubicin cardiotoxicity in mice, increased peripheral blood lymphocytes contained mitochondrial mutations that were related to respiratory chain defects and late‐onset cardiomyopathy (Lebrecht et al., 2003). These studies indicate that doxorubicin has deleterious effects on mitochondrial structure and that DNA could affect mtDNA copy numbers and OXPHOS.

Further, preclinical studies on anthracycline exposure in mitochondria have reported disrupted OXPHOS, particularly in the OXPHOS enzyme activities of NADH dehydrogenase (complex I) and cytochrome c oxidase (complex IV) activity (Chandran et al., 2009; Lebrecht et  al., 2010), as well as changes in the mtDNA in the form of mutations, deletions, and reduced copy numbers per cell in heart tissue (Lebrecht and Walker, 2007; Lebrecht et al., 2007). If the mitochondria of doxorubicin‐exposed cancer survivors are indeed impaired, through either DNA intercalation or oxidative stress, their mtDNA may undergo clonal expansion to compensate for mutations or deletions that could lead to normal OXPHOS and ATP production in the myocardium (Lee and Wei, 2005). Studies in rats treated with dexrazoxane and doxorubicin show that concomitant dexrazoxane treatment prevented doxorubicin‐ induced cardiac mitochondrial dysfunction by maintaining OXPHOS activities and mtDNA integrity (Lee and Wei, 2005; Lebrecht et al., 2007). Anthracycline‐related cardiotoxicity can present within a week or decades after the initial treatment (Goorin et al., 1990). Early toxicity is not a prerequisite for toxicity presenting decades later (Trachtenberg et al., 2011). In fact, whether any time limit exists is uncertain. Cardiotoxicity is often classified by when the signs and symptoms appear. Acute‐onset cardiotoxicity occurs within a week of treatment; early‐onset chronic progressive cardiotoxicity occurs between 1 week and 1 year; and late‐onset cardiotoxicity occurs 1 year after treatment (Table 35.3). Several risk factors contribute to cardiac toxicity in survivors of childhood cancers (Table  35.4). A higher cumulative anthracycline dose is associated with an

Table 35.3 Different types of anthracycline cardiotoxicity.

Characteristic

Acute cardiotoxicity

Early‐onset, progressive cardiotoxicity

Late‐onset, progressive cardiotoxicity

Onset

Within the first week of anthracycline treatment

11,000 deaths in 2011 (US Department of Health and Human Services, 2013). In accord with these findings, in many European countries, >25% of S. aureus are resistant to methicillin (European Centre for Disease Prevention and Control, 2015).

Enterococcus is a commensal of humans that can cause difficult‐to‐eradicate nosocomial infections. Multidrug‐ resistant Enterococcus faecalis and E. faecium are becoming more common in both the United States and Europe. Up to 30% of healthcare‐associated infections due to Enterococcus in the United States involve vancomycin‐ resistant strains, with an estimated annual mortality of 1300 patients (US Department of Health and Human Services, 2013). The prevalence of vancomycin resistance among E. faecium in Europe is similarly increasing (European Centre for Disease Prevention and Control, 2015). The reported trends and prevalence in potentially life‐ threatening infections caused by multidrug‐resistant Gram‐positive bacteria pose a serious challenge to healthcare providers and explain the increasing use of linezolid (Monnet and Giesecke, 2014). Linezolid is a safe drug and is used orally or intravenously. It is oxidized by the liver and is eliminated via non‐renal (70%) and renal (30%) routes (Diekema and Jones, 2001). The most common side effects are diarrhea

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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Mitochondrial Dysfunction by Drug and Environmental Toxicants

(4%), nausea (3%), and headache (2%). Other less common side effects are thrombocytopenia and myelosuppression, peripheral and optic neuropathy, and serotonin syndrome (especially in case of concomitant use of serotonergic agents) (Rubinstein et al., 2003). Although some of these side effects might be attributed to mitochondrial dysfunction, current knowledge on this issue remains scarce. Lactic acidosis can develop during linezolid use. When no other risk factors can be identified, it possibly reflects mitochondrial dysfunction induced by linezolid. The primary aim of this chapter is to examine the role of mitochondrial impairment in the etiology of linezolid‐ induced lactic acidosis, with a special emphasis on critically ill subjects who are at higher risk of death.

36.1 Mechanisms Responsible for Lactic Acidosis in Critically Ill Subjects Lactic acid is a product of glycolysis and is normally produced (mainly by the skeletal muscle) and consumed (mainly by the liver) at a rate of ≈1 mmol/h/kg of body weight in humans. As a result of the balance between production and consumption, lactate concentration in blood is normally stable and 28 days) treatment. Even so, peak lactate level was not associated with duration of linezolid use (p = 0.88 for Pearson’s correlation). Linezolid dose, when reported, was always the same (600 mg twice a day). One other risk factor could be renal failure, since linezolid is partly eliminated by the kidneys. Only 8, out of 57, subjects with linezolid‐induced lactic acidosis had acute or chronic renal failure when they started assuming linezolid. Their lactate level (16 ± 9 vs. 13 ± 8 mmol/L, p = 0.30 at Student’s t‐test) and mortality (13% vs. 21%, p = 0.60 at chi‐squared test) were not higher than those of subjects with initially normal renal function. Therefore, kidney injury seems to have a minor (if any) role in the development of the syndrome. The importance of polymorphisms in mitochondrial DNA (mtDNA) was investigated in 6 studies and is discussed in the following text.

549

Table 36.1 Cases of linezolid‐induced lactic acidosis in adults, retrieved in PubMed in September 2016.

Reference

Age

Sex

Reason for using linezolid

Days of therapy

Lactate (mmol/L)

Arterial pH

Clinical presentation

Outcome

Apodaca and Rakita (2003)

52

F

Invasive nocardiosis

77

10

NA

Nausea, vomiting, myelosuppression

Alive

Bernard et al. (2003)

81

M

MRSA osteomyelitis

21

18

6.90

Confusion, hypertension, tachycardia

Dead

Palenzuela et al. (2005)

49

F

Mycobacterium abscessus

58

13

NA

Nausea, diarrhea

Alive

74

F

VRE infection

47

18

NA

Nausea, vomiting, confusion

Dead

Soriano et al. (2005)

25

M

Knee prosthesis infection

90

7

NA

Mild asthenia

Alive

75

M

Nocardia cerebral abscess

80

3

NA

Severe asthenia

Alive

55

M

MRSA knee prosthesis infection

45

5

NA

Mild asthenia

Alive

De Vriese et al. (2006)

63

F

MRSA prosthetic joint infection

120

25

NA

Optical neuropathy, myopathy, acute kidney injury

Alive

Garrabou et al. (2007)

65

M

Methicillin‐resistant S. epidermidis knee prosthesis infection

35

5

NA

None

Alive

74

F

MRSA hip prosthesis infection

44

3

NA

Mild asthenia

Alive

83

M

Methicillin‐resistant S. epidermidis knee prosthesis infection

30

5

NA

Gastrointestinal discomfort

Alive

Carson et al. (2007)

35

F

Mycobacterium avium complex infection in AIDS

35

23

7.16

Diarrhea, abdominal pain, pancreatitis, shock

Alive

Wiener et al. (2007)

80

F

VRE bacteremia

19

19

7.03

Dyspnea, chest pain, thrombocytopenia, anemia

Alive

Scotton et al. (2013)

81

F

Mycobacterium tuberculosis complex paravertebral abscess

12

19

7.24

Nausea, vomiting, anemia

Alive

Kopterides et al. (2005)

70

M

MRSA bacteremia

7

13

None

Alive

Boutoille et al. (2009)

48

M

MDR Mycobacterium tuberculosis

105

12

7.32

Dyspnea, abdominal pain

Dead

Velez and Janech (2010)

36

M

VRE bacteremia

42

13

7.31

Abdominal pain, nausea, altered mental status

Alive

De Bus et al. (2010)

55

F

Prosthetic hip infection

50

13

7.27

Weakness, hitching, abdominal pain, nausea, vomiting, hepatic failure

Alive

Carbajo et al. (2011)

79

M

Prosthetic knee infection

49

3

7.25

Asthenia, anorexia, nausea, vomiting, pancytopenia

Alive

Contou et al. (2011)

81

M

Enterococcus faecium bacteremia

0

16

7.03

Confusion, tachypnea, tachycardia

Alive

Cope et al. (2011)

20

M

MRSA pneumonia in a subject with mitochondrial disease

2

7

NA

Tachypnea, tachycardia, vomiting

Alive

Miyawaki et al. (2013)

75

M

MRSA pyogenic spondylitis

72

25

7.09

Dyspnea, hypothermia, coma

Alive

Lee et al. (2013)

56

F

Urosepsis

1

4

7.37

Septic shock, respiratory failure, refractory lactic acidosis

Alive

Del Pozo et al. (2014)

72

F

Nocardiosis

63

3

7.25

Hypoglycemic coma, diarrhea, vomiting

Alive

43

M

Pulmonary tuberculosis

56

7

7.29

Nausea, asthenia, diarrhea, pancytopenia, acute kidney injury

Alive

Sawyer et al. (2014)

63

M

Chest‐wall abscess, pulmonary nocardiosis

85

23

6.96

Dyspnea, abdominal pain, altered mental status

Alive

Djibré et al. (2014)

70

M

Sternal manubrium infection

15

23

6.89

Vomiting, drowsiness, dyspnea, hypothermia, sepsis

Dead

Hsu et al. (2015)

38

F

Urinary VRE infection

12

24

6.92

Dyspnea, altered mental status, thrombocytopenia, anemia

Alive

Im et al. (2005)

64

M

Soft tissue infection in a subject with diabetes

42

20

6.91

Nausea, shock, acute kidney injury

Dead

77

M

MRSA knee prosthesis infection

28

16

7.10

Tachypnea, tachycardia

Dead

52

F

Urinary VRE infection

7

NA

7.19

Tachypnea, tachycardia, shock

Alive

76

M

Diabetic foot osteomyelitis

5

5

NA

None (routine lactate testing)

Alive

69

F

MRSA spine implant infection

35

5

NA

None (routine lactate testing)

Alive

Holmaas et al. (2014)

70

M

Toe infection

23

29

7.01

Somnolence, dyspnea, anemia

Alive

Johnson et al. (2015)

34

M

VRE endocarditis

12

24

7.07

Somnolence, hypoglycemia, pancreatitis

Alive

Abou Hassan et al. (2016)

74

M

Prosthetic knee infection

35

21

6.90

Shock, myelosuppression

Alive

Protti et al. (2016)

64

M

Respiratory failure in a lung transplant recipient

5

10

7.30

Shock, acute renal failure

Dead

MDR, multidrug resistant; MRSA, methicillin‐resistant Staphylococcus aureus; NA, non‐available; VRE, vancomycin‐resistant Enterococcus.

Mitochondrial Dysfunction by Drug and Environmental Toxicants

36.5 Relationship between Linezolid‐Induced Lactic Acidosis and Oxygen‐Derived Variables We have recently reported the case of a 64‐year‐old man who was admitted to intensive care with acute respiratory failure, 5 months after single lung transplant for pulmonary fibrosis. Computed tomography showed ground glass opacities at the right lung (graft). Initial treatment included linezolid (1200 mg/day IV, continuous infusion), meropenem, amphotericin B, and noninvasive ventilation. By day 3, all microbiological examinations were negative. Suspecting acute graft rejection, methylprednisolone (1 g/day) was started, while antimicrobials were continued. On day 4, respiratory failure worsened. Mechanical ventilation and low‐flow venovenous extracorporeal carbon dioxide removal were initiated. Vasodilatory shock and acute renal failure were treated with increasing dose of catecholamines and continuous venovenous hemodialysis. On day 5, linezolid was discontinued because of refractory severe lactic acidosis possibly related to its use. On day 7, the man died of multiple organ failure. Postmortem examination revealed bilateral pulmonary edema and no bowel ischemia (Protti et al., 2016). Oxygen‐derived variables and blood lactate levels recorded day by day are shown in Figure 36.1. Severe lac-

tic acidosis progressively developed despite normal, or even above normal, venous oxygen saturation. Oxygen delivery slightly decreased over time, from 644 to 504 mL/min/m2, while oxygen consumption substantially declined, from 172 to 52 mL/min/m2. As a result, the oxygen extraction ratio dropped from 0.27 to 0.10, a direct reflection of impaired mitochondrial oxidative phosphorylation. These data strongly resemble those reported in cases of inadvertent metformin accumulation or cyanide intoxication, where some components of the mitochondrial respiratory chain (complexes I and IV, respectively) are largely inhibited (Peddy et al., 2006; Protti et al., 2010, 2012). Linezolid‐induced (type‐B) lactic acidosis thus reflects an inability of mitochondria to use otherwise available oxygen. Of note, linezolid should be considered the most probable cause of lactic acidosis only after excluding other, more common, explanations. This can be very difficult as subjects receiving linezolid usually suffer from some degrees of hypoxemia, anemia, or low cardiac output (possible complications of the infection being treated). Progressive worsening of lactic acidosis in the face of the correction of these abnormalities supports an alternative diagnosis. Even so, no specific symptom, sign, or diagnostic test available at the bedside can definitely prove that lactic acidosis is factually due to linezolid toxicity.

1.0

20

36.6 Mitochondrial Ribosomes and Translation

0.8

16

0.6

12

0.4

8

0.2

4

Most of the mitochondrial proteins, including subunits of respiratory chain complex II and citrate synthase, are encoded by nuclear DNA (nDNA). They are synthetized in cytoplasm and then imported in mitochondria. However, some subunits of respiratory chain complexes I, III, and IV are encoded by mtDNA and synthesized by mitochondrial ribosomes (Beattie et  al., 1966; Sandell et al., 1967). Intra‐mitochondrial translation of messenger RNAs (mRNAs) into proteins relies on transfer RNAs (tRNAs) and ribosomal RNAs (rRNAs) that are encoded by mtDNA. All the other components required, including initiation factors, elongation factors, termination factors, and proteins forming the mitochondrial ribosomes, are encoded in the nucleus. The critical steps of intra‐mitochondrial translation are grossly the same as those of translation in the cytoplasm (Mai et al., 2017). However, organelles devoted to translation (ribosomes) inside mitochondria clearly differ from their cytosolic, and bacterial, counterparts (De Silva et al., 2015). Mammalian mitochondrial ribosomes are made up of a small (28S) subunit and a large (39S)

Arterial lactate (mmol/l)

Mixed or central venous O2 saturation

552

0

0.0 1

2

3

4

5

6

7

Time from admission to intensive care (days)

Figure 36.1 Oxygen‐derived variables during linezolid‐induced lactic acidosis. Changes over time of central (from day 1 to 3; normal value is around 0.70) or mixed (from day 4; normal value is around 0.65) venous oxygen (O2) saturation in a man who developed linezolid‐induced lactic acidosis during his stay in intensive care. Linezolid (1200 mg/day) was continuously infused from days 1 to 5.

Role of Mitochondrial Dysfunction in Linezolid‐Induced Lactic Acidosis

subunit that together form the 55S complex. Each subunit contains a single rRNA: 12S for the small subunit and 16S for the large subunit. Compared with cytosolic (80S) and bacterial (70S) ribosomes, mammalian mitochondrial ribosomes contain much more mitochondrial ribosomal proteins and less rRNA (Chrzanowska‐Lightowlers et al., 2011). As a result, their structure is quite porous and their average density is relatively low.

36.7 How Linezolid Exerts its Therapeutic—and Toxic—effects Linezolid inhibits bacterial growth by interfering with bacterial protein synthesis, as do many other antibiotics. However, its molecular target, that is only partially understood, is probably unique and suggests why linezolid is often active against multidrug‐resistant bacteria. Bacterial ribosomes are made of up two subunits that together form the 70S complex. The small (30S) subunit contains 16S rRNA associated with 21 mitochondrial ribosomal proteins. It is part of the translation process, along with the mRNA, the tRNA carrying N‐formylmethionine (fMet‐tRNA) that initially enters the P‐site, the guanosine triphosphate (GTP) that fuels the reaction, and the initiation factors IF1, IF2, and IF3. The large (50S) subunit contains 5S rRNA, 23S rRNA, and 36 proteins. It assembles with the initiation complex and, together with the elongation factor Ef‐Tu and GFP, facilitates the entry of the second aminoacyl‐tRNA to the A‐ site of the ribosome. The energy released by the hydrolysis of GTP activates the peptidyl transferase center (PTC): the amino acid at the P‐site is transferred to the A‐site where it is bound to the nascent polypeptide. The uncharged tRNA exits the P‐site, the newly formed peptide in the A‐site moves to the P‐site and a new aminoacyl‐tRNA enters the A‐site. Elongation continues until the ribosome reaches a stop codon on the mRNA (termination) (Laursen et al., 2005). In vitro experiments suggest that oxazolidinones inhibit bacterial protein synthesis by interfering with the early stages of translation. They possibly impede the assembly of the initiation complex or the binding of the first fMet‐tRNA to the P‐site (Swaney et al., 1998). More probably, they prevent the entry or the proper placement of the aminoacyl‐tRNA in the active site of the PTC by binding to the A‐site on the 23S rRNA of the large subunit of bacterial ribosomes (Leach et  al., 2007). Several observations support this conclusion: (i) puromycin, which binds specifically to the A‐site, prevents oxalidinones from inhibiting peptidyl transfer when it is present at high concentration (Bobkova et  al., 2003); (ii) similarly to chloramphenicol, linezolid is thought to affect the accuracy of translation that depends on the

ribosomal A‐site (Thompson et al., 2002); and (iii) most of the mutations associated with bacterial resistance to oxazolidinones (such as the G2576U) are located next to the PTC on the 23S rRNA (Meka and Gold, 2004). Insights into the mechanisms responsible for the therapeutic effects of oxazolidinones are important to understand the potential mitochondrial toxicity of these antibiotics. Mitochondria are quite similar to bacteria, because of their endosymbiotic origin. Therefore, mitochondrial ribosomes can be unintended off‐targets of drugs acting on the bacterial ribosomes. Experiments performed with photoreactive substrates in living cells have shown that oxalidinones can interact with mammalian mitochondrial (but not cytoplasmic) ribosomes, at positions A2451 and U2506 of the 16S rRNA of the large subunit, the same positions to which they cross‐link in S. aureus ribosomes (Leach et  al., 2007). This nonselective binding can interfere with mammalian mitochondrial protein synthesis and function. It can thus trigger (type‐B) lactic acidosis, a clear sign of mitochondrial intoxication (Figure 36.2).

36.8 Mitochondrial DNA Polymorphisms and Susceptibility to Linezolid mtDNA sequence polymorphisms can influence the individual response to specific drugs. For example, some mutations of the mitochondrial 12S rRNA cause hypersensitivity to aminoglycosides that can manifest as hearing loss (Jing et al., 2015). As discussed earlier, the therapeutic activity of linezolid depends on the interaction with the bacterial 23S rRNA, while some toxic effects depend on the interaction with the human mitochondrial 16S rRNA. Some genetic polymorphisms of the bacterial 23S rRNA confer resistance to linezolid (Kloss et  al., 1999; Prystowsky et al., 2001; Meka and Gold, 2004), whereas some genetic polymorphisms of human mitochondrial 16S rRNA (such as A2706G and G3010A) increase the risk of linezolid toxicity (Carson et al., 2007; Velez and Janech, 2010; Protti et al., 2016). However, there is a huge discrepancy between the very high frequency of these genetic polymorphisms of human mitochondrial ribosomes and the very rare occurrence of linezolid‐induced lactic acidosis. In our database of subjects (mostly Italian) with fully sequenced mtDNA, A2706G and G3010A substitutions were as frequent as 61 and 15%, respectively. These percentages are even higher in pan‐ethnic cohorts, up to 80% in the general population according the human mtDNA mutation database (http://www.mtdb.igp.uu.se). Therefore, these mitochondrial rRNA polymorphisms act only as weak risk factors. Otherwise, linezolid‐induced lactic acidosis would be a much more common event.

553

Mitochondrial Dysfunction by Drug and Environmental Toxicants

Therapeutic effects

Circular DNA

Toxic effects

Bacteria

Human cells Critically ill subject Mitochondria

Ribosomes AA-tRNA

LSU (50S) P

A

AA 5

mt-LSU (39S)

A

P

AA 5

tRN

A

Nascent polypeptide tRN

554

A

Peptidyl transferase center mRNA SSU (30S) Bacterial ribosome

Linezolid

mt-mRNA

mt-SSU (28S) Mitochondrial ribosome

Electron transport chain Inhibition of bacterial protein synthesis

Inhibition of bacterial growth (resolution of infection)

Inhibition of mitochondrial protein synthesis

Inability to use O2 (lactate overproduction)

Figure 36.2 Therapeutic and toxic effects of linezolid. Bacterial ribosomes are made up of two subunits: a large 50S subunit (LSU) and a small 30S subunit (SSU). The large subunit contains the P‐site where the peptidyl tRNA is formed, the A‐site where the aminoacyl‐tRNA (AA‐tRNA) enters, and the peptidyl transferase center (PTC) where the amino acid at the P‐site is transferred to the A‐site and bond to the nascent polypeptide. Linezolid exerts its therapeutic effect by binding to the A‐site and thus preventing the entry or the proper placement of the AA‐tRNA in the active site of the PTC. As a result, bacterial protein synthesis and growth are inhibited. Mitochondrial ribosomes are structurally similar to their bacterial counterparts. They control the synthesis of some components of the respiratory chain complexes I, III, and IV. In rare cases, linezolid interacts with mitochondrial ribosomes, interferes with mitochondrial protein synthesis, impairs oxygen consumption, and thus accelerates anaerobic glycolysis. Lactate overproduction leads to (type‐B) lactic acidosis.

Another source of variability of linezolid toxicity is possibly represented by ancient and highly frequent single‐nucleotide polymorphisms (SNPs) that define groups of phylogenetically related mtDNA genotypes (mtDNA haplogroups) (Wallace et al., 1999). These mitochondrial sequences are responsible for subtle functional changes

that may affect disease occurrence or drug susceptibility. Subjects belonging to mtDNA haplogroup J1, for instance, may be particularly susceptible to linezolid toxicity (Pacheu‐Grau et al., 2013). Notably, the SNPs that define this haplogroup are very close to the ribosomal PTC sequences. The haplogroup J1 is present in 9% of

Role of Mitochondrial Dysfunction in Linezolid‐Induced Lactic Acidosis

non‐Hispanic white people in the United States (Mitchell et  al., 2014) and in 8–9% of the European population. Therefore 8–9% of the population of these two countries may be at higher risk for developing lactic acidosis during treatment with linezolid (Abou Hassan et al., 2016). In conclusion, it is difficult to define a causal relationship between certain mtDNA polymorphisms and linezolid‐induced lactic acidosis because of the moderate prevalence of these polymorphisms in the general population and the infrequent availability of mtDNA sequence of subjects who have possibly developed the syndrome. Even so, testing the mitochondrial sensitivity to the most frequently used ribosomal antibiotics (constructing a sort of “mitochondrial antibiogram”) might be of benefit (Pacheu‐Grau et al., 2013).

36.9 Mitochondrial Toxicity of Linezolid Since 2003, lactic acidosis during prolonged use of linezolid has been thought to reflect mitochondrial toxicity (Apodaca and Rakita, 2003). Few years later, it was demonstrated that oxazolidinones are able (i) to decrease the rate of mitochondrial incorporation of radiolabelled methionine (i.e., mitochondrial protein synthesis) in several animal tissues and (ii) to inhibit proliferation of human cells in a time‐ and dose‐dependent manner. Treated human cells exhibited low levels of COX1 (a subunit of complex IV encoded by mtDNA) at Western blot analysis. Washing and reseeding these cells in the absence of oxazolidinones resulted in resumption of growth. Remarkably, these toxic effects were not noted in cells without mtDNA (rho‐0) (Nagiec et  al., 2005; McKee et al., 2006). As for human studies, De Vriese and colleagues described mitochondrial structure, mitochondrial respiratory chain enzymes activity and mtDNA content of muscle, liver and kidney tissue samples taken from a subject who have developed optic neuropathy, encephalopathy, myopathy, lactic acidosis, and renal failure after using linezolid for 4 months. At histology, the liver and kidney looked normal and the skeletal muscle only had atrophy and a low number of subsarcolemmal mitochondria. At electron microscopy, few mitochondria had minor alterations of cristae architecture. Even so, biochemical assays revealed severe inhibition of respiratory chain complex I (kidney, muscle) and complex IV (liver, kidney, and muscle) that are mainly encoded by mtDNA. No alteration was noted in the activity of complex II, the only respiratory chain complex entirely encoded by nDNA. The activity of citrate synthase, which grossly reflects mitochondrial content, did not differ between case and controls. SDS‐PAGE analysis of respiratory

chain subunits in the liver and muscle confirmed the selective depletion of respiratory chain complexes encoded by the mtDNA. Sequence analysis did not reveal any quantitative or qualitative defect in mtDNA. These findings were replicated in rats treated with linezolid for 2 (5 mg/kg/day) or 4 (250 mg/kg/day) weeks. Animals treated for short time and with low dose had minor variations in the activity of complex IV in the muscle and liver. Those treated for long time and with high dose suffered from severe reduction in the quantity and activity of mtDNA‐encoded respiratory chain complexes. Citrate synthase activity and mtDNA content were well preserved (De Vriese et al., 2006). Garrabou and colleagues noted a reduction in complex IV activity and COX‐II protein level (a mtDNA‐encoded subunit of complex IV) in peripheral blood mononuclear cells taken from five subjects with linezolid‐induced lactic acidosis. All these abnormalities, including lactic acidosis, resolved after linezolid was discontinued (Garrabou et al., 2007). In the case we have reported, the large decrease in systemic oxygen consumption and extraction (see earlier) was coupled with clear signs of defective mitochondrial protein translation in skeletal muscle biopsies taken at autopsy. In fact, skeletal muscle respiratory chain complexes I, III, and IV were largely inhibited (by 40–50% compared with controls), but complex II was not, with selective decrease in the level of mtDNA‐encoded subunits. Lack of expected compensatory responses, such as induction of stress‐response mitochondrial chaperones and acceleration of mitochondrial turnover, possibly contributed to these changes (Protti et al., 2016). Similar biochemical defects were also found in the muscle of an elderly Lebanese subject with linezolid toxicity. Bilateral globus pallidus lesions, which are common during other human primary mitochondrial encephalo‐ myopathies, were also noted (Abou Hassan et al., 2016). The bulk of these data clearly demonstrates that the use of linezolid, especially if prolonged, can impair the activity of several components of the respiratory chain. This toxic effect is the consequence of abnormal mitochondrial translation.

36.10

Conclusion

Linezolid‐induced lactic acidosis is rare—but potentially lethal—and reflects the untoward interaction between the drug and mitochondrial ribosomes that are structurally and functionally similar to bacterial ribosomes. The inhibition of mitochondrial protein synthesis depletes the electron transfer system of key components triggering acceleration of glycolysis with corresponding increased lactate production that yields (type‐B) lactic acidosis.

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Lactic acidosis should be attributed to linezolid only after excluding other, more common, causes (such as tissue hypoxia). Normal‐to‐high oxygen delivery, high venous oxygen saturation, and lack of response to interventions to increase systemic oxygen delivery all suggest a primary defect in oxygen utilization at the level of the mitochondria.

The current standard‐of‐care treatment of linezolid‐ induced lactic acidosis is based on drug withdrawal and life support. During therapy with linezolid, especially if exposure is prolonged, blood lactate levels should be regularly monitored to promptly recognize this serious adverse effect on mitochondrial function.

References Abou Hassan OK, Karnib M, El‐Khoury R, Nemer G, Ahdab‐Barmada M, BouKhalil P. Linezolid toxicity and mitochondrial susceptibility: a novel neurological complication in a Lebanese patient. Front Pharmacol. 2016;7:325. Apodaca AA, Rakita RM. Linezolid‐induced lactic acidosis. N Engl J Med. 2003;348:86–87. Arieff AI, Graf H. Pathophysiology of type A hypoxic lactic acidosis in dogs. Am J Physiol. 1987;253:E271–E276. Barcroft J. On anoxaemia. Lancet. 1920;2:485–489. Beattie DS, Basford RE, Koritz SB. Studies on the biosynthesis of mitochondrial protein components. Biochemistry. 1966;5:926–930. Bernard L, Stern R, Lew D. Serotonin syndrome after concomitant treatment with linezolid and citalopram. Clin Infect Dis. 2003;36:1197. Bihari D, Smithies M, Gimson A, Tinker J. The effects of vasodilation with prostacyclin on oxygen delivery and uptake in critically ill patients. N Engl J Med. 1987;317:397–403. Bobkova EV, Yan YP, Jordan DB, Kurilla MG, Pompliano DL. Catalytic properties of mutant 23S ribosomes resistant to oxazolidinones. J Biol Chem. 2003;278:9802–9807. Boutoille D, Grossi O, Depatureaux A, Tattevin P. Fatal lactic acidosis after prolonged linezolid exposure for treatment of multidrug‐resistant tuberculosis. Eur J Intern Med. 2009;20:e134–e135. Carbajo T, Fenollosa M, Pons R, Calvo C. Lactic acidosis and linezolid‐induced pancytopaenia. Nefrologia. 2011;31:107–108. Carson J, Cerda J, Chae JH, Hirano M, Maggiore P. Severe lactic acidosis associated with linezolid use in a patient with the mitochondrial DNA A2706G polymorphism. Pharmacotherapy. 2007;27:771–774. Chrzanowska‐Lightowlers ZM, Pajak A, Lightowlers RN. Termination of protein synthesis in mammalian mitochondria. J Biol Chem. 2011;286:34479–34485. Contou D, Fichet J, Grimaldi D, Cariou A. Early life‐ threatening lactic acidosis following a single infusion of linezolid. Int J Antimicrob Agents. 2011;38:84–85. Cope TE, McFarland R, Schaefer A. Rapid‐onset, linezolid‐ induced lactic acidosis in MELAS. Mitochondrion. 2011;11:992–993.

De Bus L, Depuydt P, Libbrecht L, Vandekerckhove L, Nollet J, Benoit D, Vogelaers D, Van Vlierberghe H. Severe drug‐induced liver injury associated with prolonged use of linezolid. J Med Toxicol. 2010;6:322–326. De Silva D, Tu YT, Amunts A, Fontanesi F, Barrientos A. Mitochondrial ribosome assembly in health and disease. Cell Cycle. 2015;14:2226–2250. De Vriese AS, Coster RV, Smet J, Seneca S, Lovering A, Van Haute LL, Vanopdenbosch LJ, Martin JJ, Groote CC, Vandecasteele S, Boelaert JR. Linezolid‐induced inhibition of mitochondrial protein synthesis. Clin Infect Dis. 2006;42:1111–1117. Del Pozo JL, Fernandez‐Ros N, Saez E, Herrero JI, Yuste JR, Banales JM. Linezolid‐Induced lactic acidosis in two liver transplant patients with the mitochondrial DNA A2706G polymorphism. Antimicrob Agents Chemother. 2014;58:4227–4229. Diekema DJ, Jones RN. Oxazolidinone antibiotics. Lancet. 2001;358:1975–1982. Djibré M, Pham T, Denis M, Pras Landre V, Fartoukh M. Fatal lactic acidosis associated with linezolid therapy. Infection. 2014;43:125–126. European Centre for Disease Prevention and Control. Antimicrobial resistance surveillance in Europe—2014. ECDC, Stockholm, 2015. Fink M. Cytopathic hypoxia in sepsis. Acta Anaesthesiol Scand Suppl. 1997;110:87–95. Garrabou G, Soriano A, López S, Guallar JP, Giralt M, Villarroya F, Martínez JA, Casademont J, Cardellach F, Mensa J, Miró O. Reversible inhibition of mitochondrial protein synthesis during linezolid‐related hyperlactatemia. Antimicrob Agents Chemother. 2007;51:962–967. Holmaas G, Lærum JH, Schjøtt J. A man in his seventies with a long‐term infection and severe acid‐base imbalance. Tidsskr Nor Laegeforen. 2014;134:315–319. Hsu SN, Shih MF, Yang CW, Wu CC, Chen CC. Severe linezolid‐induced lactic acidosis in a cirrhosis patient. Nephrology (Carlton). 2015;20:47–48. Im JH, Baek JH, Kwon HY, Lee JS. Incidence and risk factors of linezolid‐induced lactic acidosis. Int J Infect Dis. 2015;31:47–52.

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Jing W, Zongjie H, Denggang F, Na H, Bin Z, Aifen Z, Xijiang H, Cong Y, Yunping D, Ring HZ, Ring BZ. Mitochondrial mutations associated with aminoglycoside ototoxicity and hearing loss susceptibility identified by meta‐analysis. J Med Genet. 2015;52:95–103. Johnson PC, Vaduganathan M, Phillips KM, O’Donnell WJ. A triad of linezolid toxicity: hypoglycemia, lactic acidosis, and acute pancreatitis. Proceedings (Bayl Univ Med Cent). 2015;28:466–468. Kasnitz P, Druger GL, Yorra F, Simmons DH. Mixed venous oxygen tension and hyperlactatemia. Survival in severe cardiopulmonary disease. JAMA. 1976;236:570–574. Kloss P, Xiong L, Shinabarger DL, Mankin AS. Resistance mutations in 23 S rRNA identify the site of action of the protein synthesis inhibitor linezolid in the ribosomal peptidyl transferase center. J Mol Biol. 1999;294:93–101. Kopterides P, Papadomichelakis E, Armaganidis A. Linezolid use associated with lactic acidosis. Scand J Infect Dis. 2005;37:153–154. Kreisberg RA. Pathogenesis and management of lactic acidosis. Annu Rev Med. 1984;35:181–193. Laursen BS, Sørensen HP, Mortensen KK, Sperling‐ Petersen HU. Initiation of protein synthesis in bacteria. Microbiol Mol Biol Rev. 2005;69:101–123. Leach KL, Swaney SM, Colca JR, McDonald WG, Blinn JR, Thomasco LM, Gadwood RC, Shinabarger D, Xiong L, Mankin AS. The site of action of oxazolidinone antibiotics in living bacteria and in human mitochondria. Mol Cell. 2007;26:393–402. Lee YR, Powell N, Bonatti H, Sawyer RG, Barroso L, Pruett TL, Sifri CD, Volles D. Early development of lactic acidosis with short term linezolid treatment in a renal recipient. J Chemother. 2013;20:766–767. Lieberthal W, Menza SA, Levine JS. Graded ATP depletion can cause necrosis or apoptosis of cultured mouse proximal tubular cells. Am J Physiol. 1998;274:F315–F327. Mai N, Chrzanowska‐Lightowlers ZM, Lightowlers RN. The process of mammalian mitochondrial protein synthesis. Cell Tissue Res. 2017;367:5–20. McKee EE, Ferguson M, Bentley AT, Marks TA. Inhibition of mammalian mitochondrial protein synthesis by oxazolidinones. Antimicrob Agents Chemother. 2006;50:2042–2049. Meka VG, Gold HS. Antimicrobial resistance to linezolid. Clin Infect Dis. 2004;39:1010–1015. Mitchell SL, Goodloe R, Brown‐Gentry K, Pendergrass SA, Murdock DG, Crawford DC. Characterization of mitochondrial haplogroups in a large population‐based sample from the United States. Hum Genet. 2014;133:861–868.

Miyawaki A, Ueda T, Nakao A, Adachi M, Ohya M, Yamada I, Takesue Y, Kotani J. Linezolid‐induced lactic acidosis followed by severe hypophosphatemia after discontinuation of linezolid. Surg Infect (Larchmt). 2013;14:229–230. Mizock BA. Lactic acidosis. Dis Mon. 1989;35:233–300. Monnet DL, Giesecke J. Public health need versus sales of antibacterial agents active against multidrug‐resistant bacteria: a historical perspective. J Antimicrob Chemother. 2014;69:1151–1153. Nagiec EE, Wu L, Swaney SM, Chosay JG, Ross DE, Brieland JK, Leach KL. Oxazolidinones inhibit cellular proliferation via inhibition of mitochondrial protein synthesis. Antimicrob Agents Chemother. 2005;49:3896–3902. Nelson DL, Cox MM. Lehninger Principles of Biochemistry. Freeman WH, New York, 2012. Pacheu‐Grau D, Gómez‐Durán A, Iglesias E, López‐ Gallardo E, Montoya J, Ruiz‐Pesini E. Mitochondrial antibiograms in personalized medicine. Hum Mol Genet. 2013;22:1132–1139. Palenzuela L, Hahn NM, Nelson RP Jr, Arno JN, Schobert C, Bethel R, Ostrowski LA, Sharma MR, Datta PP, Agrawal RK, Schwartz JE, Hirano M. Does linezolid cause lactic acidosis by inhibiting mitochondrial protein synthesis? Clin Infect Dis. 2005;40:113–116. Peddy SB, Rigby MR, Shaffner DH. Acute cyanide poisoning. Pediatr Crit Care Med. 2006;7:79–82. Protti A, Russo R, Tagliabue P, Vecchio S, Singer M, Rudiger A, Foti G, Rossi A, Mistraletti G, Gattinoni L. Oxygen consumption is depressed in patients with lactic acidosis due to biguanide intoxication. Crit Care. 2010;14:R22. Protti A, Fortunato F, Monti M, Vecchio S, Gatti S, Comi GP, De Giuseppe R, Gattinoni L. Metformin overdose, but not lactic acidosis per se, inhibits oxygen consumption in pigs. Crit Care. 2012;16:R75. Protti A, Ronchi D, Bassi G, Fortunato F, Bordoni A, Rizzuti T, Fumagalli R. Changes in whole‐body oxygen consumption and skeletal muscle mitochondria during linezolid‐induced lactic acidosis. Crit Care Med. 2016;44:e579–e582. Prystowsky J, Siddiqui F, Chosay J, Shinabarger DL, Millichap J, Peterson LR, Noskin GA. Resistance to linezolid: characterization of mutations in rRNA and comparison of their occurrences in vancomycin‐ resistant enterococci. Antimicrob Agents Chemother. 2001;45:2154–2156. Rivers E, Nguyen B, Havstad S, Ressler J, Muzzin A, Knoblich B, Peterson E, Tomlanovich M; Early Goal‐Directed Therapy Collaborative Group. Early goal‐directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med. 2001;345:1368–1377.

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Robin ED. Special report: dysoxia. Abnormal tissue oxygen utilization. Arch Intern Med. 1977;137:905–910. Ronco JJ, Fenwick JC, Tweeddale MG, Wiggs BR, Phang PT, Cooper DJ, Cunningham KF, Russell JA, Walley KR. Identification of the critical oxygen delivery for anaerobic metabolism in critically ill septic and nonseptic humans. JAMA. 1993;270:1724–1730. Rubinstein E, Isturiz R, Standiford HC, Smith LG, Oliphant TH, Cammarata S, Hafkin B, Le V, Remington J. Worldwide assessment of linezolid’s clinical safety and tolerability: comparator‐controlled phase III studies. Antimicrob Agents Chemother. 2003;47:1824–1831. Sandell S, Löw H, von der Decken A. A critical study of amino acid incorporation into protein by isolated liver mitochondria from adult rats. Biochem J. 1967;104:575–585. Sawyer AJ, Haley HL, Baty SR, McGuffey GE, Eiland EH, III. Linezolid‐induced lactic acidosis corrected with sustained low‐efficiency dialysis: a case report. Am J Kidney Dis. 2014;64:457–459. Schumacker PT, Cain SM. The concept of a critical oxygen delivery. Int Care Med. 1987;13:223–229. Scotton P, Fuser R, Torresan S, Carniato A, Giobbia M, Rossi C, Inojosa WO, Vaglia A. Early linezolid‐ associated lactic acidosis in a patient treated for tuberculous spondylodiscitis. Infection. 2013;36:387–388.

Snyder JV, Pinsky MR. Oxygen Transport in the Critically Ill. Year Book Medical Publisher, Inc., Chicago, 1987. Soriano A, Miró O, Mensa J. Mitochondrial toxicity associated with linezolid. N Engl J Med. 2005;353:2305–2306. Swaney SM, Aoki H, Ganoza MC, Shinabarger DL. The oxazolidinone linezolid inhibits initiation of protein synthesis in bacteria. Antimicrob Agents Chemother. 1998;42:3251–3255. Thompson J, O’Connor M, Mills JA, Dahlberg AE. The protein synthesis inhibitors, oxazolidinones and chloramphenicol, cause extensive translational inaccuracy in vivo. J Mol Biol. 2002;322:273–279. US Department of Health and Human Services. Antibiotic resistance threats in the United States. CDC, Atlanta, 2013. Velez JC, Janech MG. A case of lactic acidosis induced by linezolid. Nat Rev Nephrol. 2010;6:236–242. Wallace DC, Brown MD, Lott MT. Mitochondrial DNA variation in human evolution and disease. Gene. 1999;238:211–230. Wiener M, Guo Y, Patel G, Fries BC. Lactic acidosis after treatment with linezolid. Infection. 2007;35:278–281. World Health Organization. Antimicrobial resistance global report on surveillance: 2014 summary. WHO, Geneva, 2014.

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37 Metformin and Lactic Acidosis Jean‐Daniel Lalau Department of Endocrinology and Nutrition, Amiens University Hospital, Amiens, France

CHAPTER MENU 37.1 37.2 37.3 37.4

37.1

Introduction, 559 Metformin‐Induced Lactic Acidosis, 559 Further Complications of the Debate, 560 In Clinical Practice, 560 References, 560

Introduction

While metformin is acknowledged as having a primary role in the treatment of type 2 diabetes mellitus, many cases of lactic acidosis have been reported in metformin‐ treated diabetic patients. In fact, these case reports featured all the possible permutations of metformin treatment with diseases capable of triggering lactic acidosis—especially in the context of shock syndromes (Lalau et al., 2017). Metformin’s variable contribution to lactic acidosis is reflected by use of the ambiguous term “metformin‐associated lactic acidosis” (MALA). It is therefore essential to distinguish between “generic” MALA on one hand and a condition due exclusively to metformin (i.e., metformin‐induced lactic acidosis (MILA)) on the other. In clinical practice, typical settings for MILA include metformin intoxication (due to overdosing) and acute metformin accumulation (due solely to acute kidney failure).

37.2 Metformin‐Induced Lactic Acidosis It is well known that metformin affects lactate metabolism (Bailey et al., 1992). In the intestine, metformin increases lactate production by accelerating glycolysis and by shifting glucose metabolism from aerobic pathways to

anaerobic pathways (Arieff et  al., 1980; Radziuk et  al., 1997). Postprandial lactate production by the small intestine (Bailey et  al., 1992) and poor lactate uptake by hepatocytes (Radziuk et  al., 1997) increase the plasma lactate level. If the recommended dose is adhered to, metformin’s effects on glycemia control and glucose oxidation do not significantly modify the blood lactate concentration because lactate is converted to glucose in the liver (via the Cori cycle) (Stumvoll et  al., 1995). In contrast, abnormally high levels of metformin accentuate the inhibition of hepatic gluconeogenesis and increase the level of anaerobic metabolism by the hepatocytes; this impairs lactate elimination and prompts a further decline in lactate uptake (Chu et al., 2003; von Mach et al., 2004). It was recently reported that metformin suppresses gluconeogenesis in rodents by inhibiting the hepatic redox shuttle enzyme mitochondrial glycerophosphate dehydrogenase. Thus, metformin indirectly decreases the substrate fluxes of lactate and glycerol to gluconeogenesis and the flux of electrons to the mitochondrial respiratory chain (Madiraju et al., 2014). In fact, metformin interferes with cell respiration only when mM concentrations (normally found solely in the  intestine) are reached (He and Wondisford, 2015). The intestine is physiologically primed to promote glycolysis and the formation of lactate from glucose (Adeva‐Andany et  al., 2014). As long as the liver is working normally, hyperlactatemia is highly unlikely to result from intestinal lactate production. Conversely,

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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blood lactate levels may rise rapidly if the liver’s uptake or metabolism of lactate is impaired because this organ is by far the main site for lactate recycling.

37.3 Further Complications of the Debate The causal role of metformin as the triggering agent in lactic acidosis is difficult to assess because (i) metformin accumulation (even when major) does not necessarily lead to hyperlactatemia (Lalau and Race, 2000), and (ii) hyperlactatemia (even when major) does not necessarily lead to acidosis. Indeed, although the term “lactic acidosis” is used very frequently, a cause–effect relationship between lactate production and acidotic status has never been clearly established—at least in muscle tissue (Marcinek et al., 2010). Hence MILA is not necessarily a “pure” phenomenon; it may merely reveal underlying defects in lactate metabolism and/or the acid–base balance.

37.4

In Clinical Practice

In situations with a risk of metformin accumulation, the following information is essential for sensibly assessing the relationship between metformin and lactic acidosis and, ultimately, for establishing a prognosis: (i) the metformin dose level, (ii) the time since administration of the last dose, (iii) the time interval between the last dose of metformin and collection

of the blood sample used to assay metformin, and (iv) the presence of any concomitant medications (in a context of metformin intoxication). Once these factors are taken into account, it becomes clear that true MILA is very rare. In a review on metformin intoxication, Dell’Aglio et  al. (2009) cited our reports (Lalau et  al., 1998) but omitted the available information on multidrug intoxication in 11 of the 13 cases. In fact, this type of information is critical when determining the prognosis of an individual patient, since  the course of lactic acidosis may be influenced by  concurrent intoxication with drugs that alter ventilation. Lastly, it should be remembered that lactate is not toxic per se. In fact, lactate production is the hallmark of impaired cellular energy production, and lactate can even substitute for glucose as a metabolic substrate under critical conditions (anaerobic conditions, in particular) via the tricarboxylic acid cycle entry (when it can be used as a gluconeogenic substrate, oxidized, or transaminated into alanine). Similarly, it is difficult to still consider metformin as a toxic drug. Although massive metformin accumulation may alter mitochondrial respiration, hyperlactatemia is highly unlikely to result from intestinal lactate production as long as the liver is able to eliminate the excess lactate. Furthermore, a study of a cohort of septic patients with lactic acidosis showed that the mortality rate was much lower in those who were treated with metformin—even though a high lactate concentration is classically associated with a poor prognosis in this setting (Doenyas‐Barak et  al., 2016). This finding shows that metformin’s beneficial effects are impressive—even in the most critical situations.

References Adeva‐Andany M, López‐Ojén M, Funcasta‐Calderón R, Ameneiros‐Rodríguez E, Donapetry‐García C, Vila‐Altesor M, Rodríguez‐Seijas J. Comprehensive review on lactate metabolism in human health. Mitochondrion 2014; 17:76–100. Arieff AI, Park R, Leach WJ, Lazarowitz VC. Pathophysiology of experimental lactic acidosis in dogs. Am J Physiol 1980; 239:F135–F142. Bailey CJ, Wilcock C, Day C. Effect of metformin on glucose metabolism in the splanchnic bed. Br J Pharmacol 1992; 105:1009–1013. Chu CK, Chang YT, Lee BJ, Hu SY, Hu WH, Yang DY. Metformin‐associated lactic acidosis and acute renal failure in a type 2 diabetic patient. J Chin Med Assoc 2003; 66:505–508.

Dell’Aglio DM, Perino LJ, Kazzi Z, Abramson J, Schwartz MD, Morgan BW. Acute metformin overdose: examining serum pH, lactate level, and metformin concentrations in survivors versus nonsurvivors: a systematic review of the literature. Ann Emerg Med 2009; 54:818–823. Doenyas‐Barak K, Beberashvili I, Marcus R, Efrati S. Lactic acidosis and severe septic shock in metformin users: a cohort study? Critical Care 2016; 20:10. He L, Wondisford FE. Metformin action: concentrations matter. Cell Metab 2015; 21:159–162. Lalau JD, Race JM. Metformin and lactic acidosis in diabetic humans. Diabetes Obes Metab 2000; 2:131–137. Lalau JD, Mourlhon C, Bergeret A, Lacroix C. Consequences of metformin intoxication. Diabetes Care 1998; 21:2036–2037.

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Lalau JD, Kajbaf F, Protti A, Christensen MM, De Broe M, Wiernsperger N. Metformin‐associated lactic acidosis (MALA): moving towards a new paradigm. Diabetes Obes Metab 2017; 19(11):1502–1512. von Mach MA, Sauer O, Sacha Weilemann L. Experiences of a poison center with metformin‐associated lactic acidosis. Exp Clin Endocrinol Diabetes 2004; 112:187–190. Madiraju AK, Erion DM, Rahimi Y, Zhang XM, Braddock DT, Albright RA, Prigaro BJ, Wood JL, Bhanot S, MacDonald MJ, Jurczak MJ, Camporez JP, Lee HY, Cline GW, Samuel VT, Kibbey RG, Shulman GI. Metformin suppresses gluconeogenesis by inhibiting

mitochondrial glycerophosphate dehydrogenase. Nature 2014; 510:542–546. Marcinek DJ, Kushmerick MJ, Conley KE. Lactic acidosis in vivo: testing the link between lactate generation and H+ accumulation in ischemic mouse muscle. J Appl Physiol 2010; 108:1479–1486. Radziuk J, Zhang Z, Wiernsperger N, Pye S. Effects of metformin on lactate uptake and gluconeogenesis in the perfused rat liver. Diabetes 1997; 46:1406–1413. Stumvoll M, Nurjhan N, Perriello G, Dailey G, Gerich JE. Metabolic effects of metformin in non‐insulin‐ dependent diabetes mellitus. N Engl J Med 1995; 333:550–554.

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38 Lessons Learned from a Phase I Clinical Trial of Mitochondrial Complex I Inhibition Cecilia C. Low Wang1,2, Jeffrey L. Galinkin2,3, and William R. Hiatt2,4 1

Division of Endocrinology, Metabolism and Diabetes, Department of Medicine, University of Colorado Anschutz Medical Campus School of Medicine, Aurora, CO, USA CPC Clinical Research, Aurora, CO, USA 3 Department of Anesthesia, University of Colorado School of Medicine, Aurora, CO, USA 4 Division of Cardiology, Department of Medicine, University of Colorado Anschutz Medical Campus School of Medicine, Aurora, CO, USA 2

CHAPTER MENU References, 567

In 2014, a first‐in‐human clinical trial of a drug intended to treat symptomatic peripheral artery disease (PAD) via activation of 5′ AMP‐activated protein kinase (AMPK) was performed. By the time this phase I trial was prematurely halted, two healthy volunteers required endotracheal intubation and mechanical ventilation for severe metabolic acidosis. This section will describe experience from this clinical trial that may inform future development of this class of drugs. Further details may be found in Low Wang et al. (2015). PAD affects approximately 8.5 million people in the United States including 12–20% of individuals older than age 60 (CDC 2016 fact sheet). It is usually caused by atherosclerotic narrowing of arteries supplying the lower extremities. However, revascularization of large arteries supplying the lower limbs alone is not always sufficient to normalize function and eliminate claudication, the calf muscle cramping, and pain with walking that occurs in PAD that may severely limit function (Muller et  al. 2013; SVS 2015). Skeletal muscle and mitochondrial dysfunction, as well as endothelial cell dysfunction with impairment of endothelial nitric oxide synthase (eNOS), are additional factors that contribute to the functional limitations observed in PAD (Kiani et  al. 2013; Pipinos et al. 2008). Activation of AMPK with R118, an indirect AMPK activator, was demonstrated to increase eNOS production and improve exercise capacity in a mouse model of PAD (Baltgalvis et  al. 2014). R118 is a small molecule that was being investigated by a pharmaceutical company called Rigel Pharmaceuticals, Inc. for

potential use in PAD. R118 does not activate AMPK directly, but rather inhibits mitochondrial respiration by inhibiting mitochondrial complex I with blunting of NADH oxidation (Baltgalvis et al. 2014). Mitohormesis, the intermittent production of reactive oxygen species in mitochondria leading to adaptation to subsequent stress (Ristow and Zarse 2010; Tapia 2006), has been proposed as a potential mechanism for the beneficial effect of partial inhibition of mitochondrial respiration (Baltgalvis et  al. 2014). Investigators have demonstrated increased mitochondrial number and efficiency in response to weak RNA interference of a component of mitochondrial complex I (Owusu‐Ansah et al. 2013) and improved mitochondrial function in response to exercise (Ascensao et  al. 2005) and caloric restriction (Anson et  al. 2003). Both rodent and primate data supported the safety of R118 (Baltgalvis et al. 2014, Rigel investigator’s brochure 2013): at the 20 mg/kg/day dose in Sprague‐Dawley rats, minimal reversible gastrointestinal adverse effects were seen; the 30 mg/kg/day dose used to achieve similar serum exposure in cynomolgus monkeys resulted in emesis and glucosuria, but no remarkable elevations in lactic acid concentrations. The phase I trial of R118 was designed to investigate the safety and tolerability of R118 and to characterize the pharmacokinetic and pharmacodynamic profile of R118 in healthy human volunteers. The design was single center, randomized, placebo controlled, and double blinded with the exception of the initial dosing group, in which the first 2 subjects were randomized 1 : 1 to receive

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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Table 38.1 Number and severity of adverse events. Treatment group 1

2

3

4

Total

Placebo (n = 4)

30 mg aq susp, fasted (n = 5)

75 mg aq susp, fasted (n = 5)

75 mg aq susp, fed (n = 5)

74 mg cap (2–37 mg/cap), fasted (n = 5)

R118 (n = 20)

Number (%) of subjects with at least 1 AE

1 (25%)

5 (100%)

5 (100%)

5 (100%)

5 (100%)

20 (100%)

Number of AEs

1

9

16

21

31

77

1

5

10

9

6

30

Number of AEs by severity Grade 1 (mild) Grade 2 (moderate)

0

4

6

12

21

43

Grade 3 (severe)

0

0

0

0

4

4

Number of SAEs

0

0

0

0

6

6

Number of AEs leading to hospitalization

0

0

0

0

7

7

Number of AEs leading to intubation

0

0

0

0

3

3

R118 versus placebo and the remaining four subjects all received R118. Subsequent dosing employed a randomization ratio of 5 : 1 for R118 versus placebo. Frequent monitoring of lactic acid and beta‐hydroxybutyrate concentrations was performed within 24 h of dosing, and individual stopping rules for elevated lactic acid were incorporated into the trial protocol. The dose of R118 was carefully chosen based upon pharmacology studies performed in rodents and a safety factor of 20‐fold below the no observed adverse effect levels (NOAEL) of 30 mg/kg/day in a cynomolgus monkey study that showed no evidence of lactic acidosis during 28 days of dosing. The original dosing protocol was amended after the trial began because of gastrointestinal adverse effects experienced by the human subjects. Dosing group 1 involved a 30 mg dose of R118 in an aqueous suspension in a fasted subject as compared with one subject receiving placebo and was followed by 30 mg dosed in four additional subjects. This dose was tolerated except for mild to moderate nausea (all subjects), vomiting (two of the five subjects), and cold sweats (one of the five subjects) in the subjects randomized to receive R118 (Table 38.1). There were two subjects in this first dosing group who had mild lactic acid elevations lasting longer than 16 h post‐dosing. The three subsequent dosing groups were randomized 5 : 1 as noted earlier. Group 2 received a single dose of 75 mg administered in an aqueous suspension, in the fasted state. This was not tolerated as well by the subjects, with all subjects experiencing at least one adverse event (AE) that was graded moderate in 37.5% of subjects and mild in 62.5%: four

subjects experienced nausea, four subjects experienced vomiting, two subjects experienced dizziness, and one subject experienced diarrhea (Low Wang et  al. 2015). Three subjects exhibited mild elevations in lactic acid concentrations, which lasted for longer than 16 h in a single subject. Group 3 involved a single dose of 75 mg in fed subjects, but unfortunately the number and severity of AEs increased further. These were predominantly gastrointestinal in nature (nausea and vomiting, with diarrhea in one subject) along with headache in a single subject and presyncope in a single subject. Two of the five subjects receiving R118 exhibited more marked elevations in lactic acid. Group 4 turned out to be the final dosing group and involved a single dose of 74 mg (2–37 mg capsules) dosed to subjects in the fasted state using an encapsulated spray‐dried dispersion of R118 in an effort to improve tolerability. This form of dosing resulted in approximately threefold higher R118 exposure than the aqueous suspension, but there was large interindividual variation, as was observed with the aqueous suspension (Low Wang et al., 2015). Group 4 exhibited a higher degree of lactic acid elevation, with two of five subjects developing lactic acidosis severe enough to require intubation. The R118 serum levels peaked earlier than lactic acid levels (Figure 38.1). Lactic acid levels in each subject in group 4 are shown in Figure 38.2. The first of the two subjects requiring intubation did not have any significant medical history, did not smoke or use illicit drugs, and used alcohol only occasionally. He was a 51‐year‐old African–American man who had not taken any concomitant medications within 15 days of

Lessons Learned from a Phase I Clinical Trial of Mitochondrial Complex I Inhibition 150

8

6 100 4

75 50

2

R118 LA

25

0

0 0

4

2

6 Time (h)

8

10

12

14 12 10 Lactate (mmol/L)

Figure 38.2 Serum lactate concentrations within 8 h of dosing in group 4 including the subject receiving placebo (inverted triangles). Each line represents lactate concentrations for a single subject over time. Lactate concentrations for subject 1 are denoted by the larger circles, while those for subject 2 are denoted by squares. Lactate concentrations were markedly elevated in 2 of the subjects (denoted by diamonds and triangles, respectively), but this did not correlate with the clinical presentation, and these subjects did not require intubation.

Lactic acid (mmol/L)

125 R118 (ng/mL)

Figure 38.1 Mean R118 and lactic acid concentrations in healthy volunteers in group 4 after a single dose of R118. R118 levels are denoted with squares, while lactic acid levels are denoted with circles. Low Wang et al. (2015). Reproduced with permission of John Wiley & Sons.

8 6 4 2 0 0

dosing. He began vomiting 1 h after receiving the 74 mg dose of R118. He was given 1 L of intravenous (IV) normal saline and promethazine 25 mg IV, but he became progressively agitated, with acute mental status changes and reported hypotension, so he was transported to the local emergency room (ER). Upon presentation, he was found to be hypothermic to 90.9°F. Within minutes of arrival and receiving diphenhydramine 50 mg IV, he developed severe hypotension with a blood pressure of 60/0 mmHg and unresponsiveness. He was intubated to preserve his airway and given benztropine 1 mg IV. At that point, he was also found to have acute kidney injury with a serum creatinine of 1.64 mg/dL and severe metabolic acidosis with arterial blood gas showing pH 6.63 at 5 h post‐dosing. He was given three doses of sodium bicarbonate 50 mEq IV, and serum lactate 6.5 h post‐dosing was greater than 20 mmol/L (reference range 0.9–1.70). He was transferred to the intensive care unit (ICU) and started on vasopressors including norepinephrine and  vasopressin. After undergoing hemodialysis for

1

2

3 5 4 Number of hours post-dosing

6

7

8

metabolic acidosis and receiving ICU supportive care, subject 1’s lactate normalized 28 h post‐dose, and he was discharged in good condition on day 7 post‐dosing. Subject 2 was a 54‐year‐old Hispanic man who had a medical history significant for hypercholesterolemia, long‐standing tinnitus, lower back pain, and treated depression. He used tramadol as needed for his back pain but had not taken any concomitant medications within 15 days of taking the blinded 74 mg dose of R118. He did not smoke or use illicit drugs and had only 1 alcohol‐containing drink per week. Approximately 5 h after the R118 dose, he experienced multiple episodes of vomiting. He was given 1 L of IV fluid but began to report abdominal pain and was noted to be tachypneic, so he was transported to a local ER. His lactic acid level was  noted to be 16.6 (units and reference range not available). He was intubated and transferred to the ICU. He  underwent hemodialysis for his metabolic acidosis (pH 7.138, serum bicarbonate 7.5 mEq/L). He was extubated 2 days after dosing and was off vasopressors and

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following commands, but then became more agitated with increasing lactate (to 6 mEq/L), so he was reintubated and hemodialysis was restarted. By 3 days post‐ dosing, his serum lactate had normalized, and he was extubated 5 days after dosing but remained unresponsive until 7 days after initial dosing of R118. By day 8, he was awake and responding to commands, and he was finally discharged on day 11. The other three subjects who had received 74 mg of R118 capsules in phase A4 developed nausea and vomiting and were hospitalized for observation but did not require intubation and were discharged in good health the day following dosing of R118. In retrospect, the lactate levels in group 3 suggested a possible narrow therapeutic window for R118. What was unexpected from preclinical studies was the marked difference in pharmacokinetics of the uncoated encapsulated form of R118 administered in group 4. The final dosing phase of R118 resulted in severe toxicity that was likely multifactorial, with a longer half‐life, markedly increased maximum concentration (Cmax), and area under the curve (AUC) than what had been observed in preclinical studies with presumed increased tissue accumulation of R118 (Figure  38.3), and possible stronger inhibition of complex I (Table  38.2). In mitohormesis, the “right” amount of stress from reactive oxygen species appears to induce an adaptive response that increases resilience to stress and protects against subsequent harm from a similar stress (Ristow and Zarse, 2010, Tapia 2006). However, with this narrow therapeutic window, creating just the right degree of stress by inhibiting mitochondrial complex I may be difficult, as demonstrated in this first‐in‐human clinical trial of R118. An additional

consideration is that the severe adverse metabolic consequences with R118 were seen in the resting condition. The intended use of the drug was to improve exercise performance in PAD, yet exercise per se can increase muscle and systemic lactate concentrations, which would be expected to further exacerbate the adverse effects of mitochondrial complex I inhibition. In addition, there was the difficulty of translating animal studies to humans. Although a primate study showed similar serum R118 concentrations after dosing with R118 in aqueous suspension versus capsules, these two

14 12

Lactic acid Cmax (mmol/L)

566

10 8 6 4 2 0 0

100

200

300

R118 Cmax (ng/mL)

Figure 38.3 Correlation between peak Cmax of R118 and peak lactate concentrations in each dosing group. Groups 1, 2, and 3 are represented by open circles. Group 4 is represented by filled circles. Low Wang et al. (2015). Reproduced with permission of John Wiley & Sons.

Table 38.2 Pharmacokinetic (PK) parameters for R118. Group

PK parameters

1

2

3

4

30 mg suspension, fasted (N = 5)

75 mg suspension, fasted (N = 5)

75 mg suspension, fed (N = 5)

74 mg capsules, fasted (N = 5)

Mean

Tmax (h)

1.10

SD

0.548

Mean

1.60

SD

1.39

Mean

0.80

SD

0.274

Mean

2.7

SD

2.22

Cmax (ng/mL)

26.4

19.5

55.9

42.0

74.8

30.2

171

97.4

AUC lasta (ng·h/mL)

166

145

519

295

341

205

1570

1220

AUC0‐∞ (ng·h/mL)

232

206

657

352

440

197

1810

1370

T½ (h)

30.1

14.7

47.2

18

84.4

37

39.3

11.5

a

Low Wang et al. (2015). Reproduced with permission of John Wiley & Sons; Group names changed from A1 to A4 in original manuscript to 1–4 in current chapter for consistency. Note that the mechanism of clearance and volume of distribution is not known for R118. SD, standard deviation. a  AUC estimates for group 4 may be overestimated due to the fact that some subjects had missing time points while being treated at the hospital.

Lessons Learned from a Phase I Clinical Trial of Mitochondrial Complex I Inhibition

forms of dosing resulted in markedly different exposures in humans. Complex I contains 14 subunits, of which seven are derived from mitochondrial DNA. Although the complex I subunits are highly conserved among mammals, mitochondrial DNA from old world monkeys (including the cynomolgus monkeys studied for this compound) are distinct enough from human mitochondrial DNA to lack the ability to restore oxidative phosphorylation when combined with human rho0 cells  (Kenyon and Moraes 1997). The differences in mitochondrial genome‐derived complex I subunits may

account for the inability to predict drug toxicity for this compound using these preclinical and primate models. It is quite possible that inhibition of complex I may still  be an important target for drug development. Unfortunately, as was observed in this clinical trial, the interindividual pharmacokinetics of R118 varied dramatically (Figure 38.2), and serum R118 levels did not necessarily predict degree of lactic acidosis (Low Wang et  al. 2015). The experience from this phase I clinical trial was a dramatic demonstration of how essential it is to utilize the right preclinical model to translate safety data to humans.

References Anson RM, Guo Z, de Cabo R, Iyun T, Rios M, Hagepanos A, Ingram DK, Lane MA, Mattson MP. Intermittent fasting dissociates beneficial effects of dietary restriction on glucose metabolism and neuronal resistance to injury from calorie intake. Proc Natl Acad Sci U S A. 2003;100(10):6216–6220. Ascensao AA, Magalhães JF, Soares JM, Ferreira RM, Neuparth MJ, Appell HJ, Duarte JA. Cardiac mitochondrial respiratory function and oxidative stress: the role of exercise. Int J Sports Med 2005;26(4):258–267. Baltgalvis KA, White K, Li W, Claypool MD, Lang W, Alcantara R, Singh BK, Friera AM, McLaughlin J, Hansen D, McCaughey K, Nguyen H, Smith IJ, Godinez G, Shaw SJ, Goff D, Singh R, Markovtsov V, Sun TQ, Jenkins Y, Uy G, Li Y, Pan A, Gururaja T, Lau D, Park G, Hitoshi Y, Payan DG, Kinsella TM. Exercise performance and peripheral vascular insufficiency improve with AMPK activation in high‐fat diet‐fed mice. Am J Physiol Heart Circ Physiol 2014;306(8):H1128–H1145. Centers for Disease Control and Prevention. Peripheral Arterial Disease (PAD) Fact Sheet. Content source: National Center for Chronic Disease Prevention and Health Promotion, Division for Heart Disease and Stroke Prevention, 2016. http://www.cdc.gov/dhdsp/ data_statistics/fact_sheets/docs/fs_pad.pdf (Accessed November 20, 2016). Kenyon L, Moraes CT. Expanding the functional human mitochondrial DNA database by the establishment of primary xenomitochondrial cybrids. Proc Natl Acad Sci 1997;94:9131–9135. Kiani S, Aasen JG, Holbrook M, Khemka A, Sharmeen F, LeLeiko RM, Tabit CE, Farber A, Eberhardt RT, Gokce N, Vita JA, Hamburg NM. Peripheral artery disease is associated with severe impairment of vascular function. Vasc Med 2013;18(2):72–78.

Low Wang CC, Galinkin JL, Hiatt WR. Toxicity of a novel therapeutic agent targeting mitochondrial complex I. Clin Pharmacol Ther 2015;98(5):551–559. Muller MD, Reed AB, Leuenberger UA, Sinoway LI. Physiology in medicine: peripheral artery disease. J Appl Physiol 2013;115:1219–1226. Owusu‐Ansah E, Song W, Perrimon N. Muscle mitohormesis promotes longevity via systemic repression of insulin signaling. Cell 2013;155(3):699–712. Pipinos II, Swanson SA, Zhu Z, Nella AA, Weiss DJ, Gutti TL, McComb RD, Baxter BT, Lynch TG, Casale GP. Chronically ischemic mouse skeletal muscle exhibits myopathy in association with mitochondrial dysfunction and oxidative damage. Am J Physiol Regul Integr Comp Physiol 2008;295(1):R290–R296. Rigel Pharmaceuticals, Inc. Investigator’s Brochure R942118, version 1.0, December 13, 2013. Ristow M, Zarse K. How increased oxidative stress promotes longevity and metabolic health: the concept of mitochondrial hormesis (mitohormesis). Exper Gerontol 2010;45:410–418. Society for Vascular Surgery Lower Extremity Guidelines Writing Group, Conte MS, Pomposelli FB, Clair DG, Geraghty PJ, McKinsey JF, Mills JL, Moneta GL, Murad MH, Powell RJ, Reed AB, Schanzer A, Sidawy AN; Society for Vascular Surgery. Society for Vascular Surgery practice guidelines for atherosclerotic occlusive disease of the lower extremities: management of asymptomatic disease and claudication. J Vasc Surg 2015;61(3 Suppl):2S–41S. Tapia PC. Sublethal mitochondrial stress with an attendant stoichiometric augmentation of reactive oxygen species may precipitate many of the beneficial alterations in cellular physiology produced by caloric restriction, intermittent fasting, exercise and dietary phytonutrients: “Mitohormesis” for health and vitality. Med Hypotheses 2006;66(4):832–843.

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39 Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies Whitney S. Gibbs1,2, Natalie E. Scholpa2, Craig C. Beeson3, and Rick G. Schnellmann2,4 1

Department of Drug Discovery and Biomedical Sciences, Medical University of South Carolina, Charleston, SC, USA Department of Pharmacology and Toxicology, College of Pharmacy, University of Arizona, Tucson, AZ, USA 3 Department of Drug Discovery and Biomedical Sciences, College of Graduate Studies, Medical University of South Carolina, Charleston, SC, USA 4 Southern Arizona VA Health Care System, Tucson, AZ, USA 2

CHAPTER MENU 39.1 39.2 39.3 39.4 39.5 39.6 39.7 39.8 39.9 39.10 39.11 39.12

39.1

Introduction, 569 Regulation of MB, 570 Mitochondrial Dysfunction in Disease, 570 Acute Diseases, 571 Chronic Diseases, 573 Pharmacological Activation of MB, 574 Kinase Modulators, 575 G Protein‐Coupled Receptor Modulators, 576 Cyclic Nucleotide Modulators, 579 Transcription Factor Modulators, 580 Sirtuins, 581 Conclusions, 582 References, 583

Introduction

Mitochondria orchestrate a wide range of metabolic pathways and are central to many critical cellular functions, including adenosine triphosphate (ATP) production, apoptosis, ion homeostasis, antioxidant defenses, and reactive oxygen species (ROS) production. As such, mitochondria are integral to the preservation of cell and tissue function necessary for human health. In the presence of toxicants or cellular stresses, mitochondria can be damaged, leading to increased ROS production, suppressed oxidative phosphorylation (OXPHOS) proteins, and diminished ATP production (Funk and Schnellmann 2012; McGill et al. 2012; Gibbs et al. 2016; Pisano et al. 2016). Thus, it is not surprising that mitochondrial dysfunction is important in a variety of acute and chronic disease processes across multiple organ systems.

Cells are capable of survival in a remarkable range of environments and disease states due, in part, to the plastic nature of mitochondria. Mitochondria are highly dynamic organelles able to adapt their size, shape, and organization in response to both internal and external stimuli. Dynamic quality control of mitochondrial mechanisms, including fission and fusion, mitophagy, and biogenesis, grants mitochondria the necessary plasticity and protection under cellular stress to meet metabolic needs for cell repair and regeneration (Friedman and Nunnari 2014). Because disruption of mitochondrial quality control mechanisms has been implicated in various diseases, strategies aimed at maintaining and restoring these cellular processes have received increasing attention. Specifically, pharmacological induction of mitochondrial biogenesis (MB), the generation of new, functional mitochondria, has proven to be a promising therapeutic target for a wide range of

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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acute and chronic diseases characterized by mitochondrial dysfunction (Whitaker et al. 2016).

39.2

Regulation of MB

MB is a multifactorial process involving the integration of strictly regulated transcriptional events, lipid membrane and protein synthesis/assembly, and replication of mitochondrial DNA (mtDNA) (Ventura‐Clapier et  al. 2008). Mitochondria are unique among extranuclear organelles in that they contain their own circular genome consisting of a small number of genes necessary for the architecture and function of mitochondria. Due to this limited coding capacity, MB requires coordination of both the mitochondrial and nuclear genomes (Scarpulla 2008). There are a number of nuclear transcription factors that increase expression of genes involved in OXPHOS, mitochondrial import and export systems, antioxidant defense, and mitochondrial gene transcription; however, these nuclear transcription factors are also involved in other cellular events independent of MB. In turn, the nuclear‐encoded peroxisome proliferator‐ activated receptor γ coactivator 1 (PGC‐1) family of transcription coactivators, comprised of PGC‐1α, PGC‐1β, and PGC‐related coactivator (PRC), have emerged as selective regulators of MB and respiratory function (Scarpulla 2008). The PGC‐1 coactivators serve as docking platforms that recruit additional protein complexes responsible for the transcription of nuclear genes involved in MB. PGC‐1α is the most studied and founding member of  this family and is a positive regulator of MB and respiration, adaptive thermogenesis, and gluconeogenesis (Scarpulla 2008). Importantly, the expression of PGC‐1α is highly inducible by physiological cues signaling for increased energy needs, such as exercise, cold exposure, caloric restriction, oxidative stress, and cell division (Handschin and Spiegelman 2006). Due to the highly inducible nature of PGC‐1α, its activation has become an attractive therapeutic strategy for inducing MB. PGC‐1α is also regulated through a host of posttranslational modifications, including methylation, acetylation, small ubiquitin‐like modifier (SUMO)ylation, and phosphorylation. These modifications allow fine‐tuning of PGC‐1α activity in a context‐dependent manner. Deacetylation by silent mating type information regulation 2 homologue (sirtuin, SIRT) 1 and methylation by protein arginine methyltransferase 1 (PRMT1) increases PGC‐1α activity, whereas acetylation by general control nonderepressible 5 (GCN5) and SUMOylation by SUMO1 negatively impacts its function (Rodgers et  al.

2005; Teyssier et al. 2005; Lerin et al. 2006; Rytinki and Palvimo 2009). Phosphorylation of PGC‐1α can increase or decrease its activity depending on the phosphorylating kinase. For example, p38 mitogen‐activated protein kinase (MAPK) phosphorylation increases PGC‐1α activity, while AKT phosphorylation inhibits its activity (Puigserver et  al. 2001; Li et  al. 2007). Finally, PGC‐1α and other transcription factors associated with MB can be activated by nitric oxide (NO)/cyclic guanosine monophosphate (cGMP) and Ca2+‐dependent signaling (Wu et al. 2002; Handschin et al. 2003; Nisoli et al. 2004). In summary, multiple cellular mechanisms allow for the tight control of MB and mitochondrial homeostasis necessary to meet energy demands under physiological and pathological conditions. The activating effects of PGC‐1α on MB are exerted through its coactivation of nuclear respiratory factors (NRFs), transcription factors that increase the transcriptional activity of numerous mitochondrial genes (Wu et al. 1999). The induction of NRFs by PGC‐1α increases the expression of not only mitochondrial transcriptional factor a (TFAM), but also other mitochondrial subunits of electron transport chain (ETC) complexes, such as ATP synthase, cytochrome c, and cytochrome oxidase IV. Following transcription and translation of the TFAM gene, the protein translocates to the mitochondrial matrix where it stimulates mtDNA replication and mitochondrial gene expression (Ventura‐Clapier et al. 2008). In addition to NRFs, PGC‐1α also interacts with and coactivates other transcription factors, including peroxisome proliferator‐activated receptors (PPARs), thyroid hormone, glucocorticoids, estrogen, and estrogen‐ related α and γ receptors for the increased expression of OXPHOS genes, mitochondrial transporters, antioxidant proteins, and other mitochondrial transcription factors (Ventura‐Clapier et al. 2008).

39.3 Mitochondrial Dysfunction in Disease Given the importance of mitochondria in a plethora of integral cellular processes, deregulation of mitochondrial homeostasis can have debilitating consequences, including loss of ATP‐dependent cellular functions, increased ROS production, and oxidative damage. Therefore, mitochondrial dysfunction has been implicated in the pathophysiology of many disease states. In the following passages, and summarized in Table 39.1, we will discuss the contribution of mitochondrial dysfunction in several acute and chronic pathologies, as well as the enhancement of MB as a potential therapeutic strategy for each.

Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies

Table 39.1 Partial list of diseases characterized by mitochondrial dysfunction and evidence of MB as therapeutic interventions for each. Disease

Mitochondrial dysfunction

Tested MB treatments

References

Ischemia: ↓OXPHOS proteins, ↓ATP synthesis, ↓ATP‐dependent cellular processes, ↓ion homeostasis

↑Exercise: ↓oxidative stress

Jiang et al. (2014)

Reperfusion: ↑ROS, ↑oxidative stress, ↑Ca2+, mPTP opening, ↑cell death

↑TFAM: ↑survival

Ikeuchi et al. (2005)

PDE inhibitors, formoterol, LY344864: ↑mitochondrial and renal function

Whitaker et al. (2013), Jesinkey et al. (2014a), and Garrett et al. (2014)

Acute diseases Ischemia/reperfusion ●

●

Myocardial infarction

Acute kidney injury

●

Spinal cord injury

↑PGC‐1α: ↓cell death, ↑function

Hu et al. (2016)

●

Stroke

↑PGC‐1α: ↓oxidative stress, ↓cell death Resveratrol: ↑neuron survival

St‐Pierre et al. (2006); Dasgupta and Milbrandt (2007), and West et al. (2007)

Bezafibrate: ↑PGC‐1α, ↑behavior AICAR: ↑function, ↓cell death

Dumont et al. (2012), Kim et al. (2007), Cheng et al. (2016), and Vingtdeux et al. (2010)

Chronic diseases Neurodegenerative ●

●

●

●

Alzheimer’s disease

↓MB, ↑mitochondrial size and structural damage, ↓content, ↑fragmentation, ↑mtDNA mutations

Resveratrol, TZDs,

Parkinson’s disease

↑mtDNA mutations (complex I), ↑oxidative damage, ↓PGC‐1α, ↓OXPHOS, ↓homeostasis

Resveratrol: ↑function, ↓cell death

Blanchet et al. (2008) and Long et al. (2009)

Huntington’s disease

↓MB, ↓PGC‐1α, ↓complex I‐III activity, ↑mtDNA deletions, ↓mitochondrial genes

Resveratrol: ↑function, ↓cell death

Ho et al. (2010)

Amyotrophic lateral sclerosis

↑Deformed mitochondria, ↓ETC activity, ↓ATP, ↑ROS, ↑oxidative stress, ↑Ca2+ dysregulation

Resveratrol: ↑function, ↓cell death

Kim et al. (2007)

Arrows indicated increase (↑) and decrease (↓). AICAR, 5‐aminoimidazole‐4‐carboxamide ribonucleotide; ATP, adenosine triphosphate; Ca2+, calcium ion; ETC, electron transport chain; MB, mitochondrial biogenesis; mPTP, mitochondrial permeability transition pore; mtDNA, mitochondrial DNA; OXPHOS, oxidative phosphorylation; PDE, phosphodiesterase; PGC‐1α, peroxisome proliferator‐activated receptor‐γ coactivator 1‐α; ROS, reactive oxygen species; TFAM, mitochondrial transcription factor A; TZDs, thiazolidinediones.

39.4

Acute Diseases

39.4.1

Ischemia/Reperfusion

Loss of mitochondrial function, and the subsequent energy deficit, is a major contributor to the tissue damage that occurs following ischemia (Stallons et al. 2013; Whitaker et  al. 2016). The mechanisms underlying the resulting tissue damage are consistent, regardless of the site of injury or the method of ischemia induction. Deficient oxygen delivery halts OXPHOS, resulting in loss of mitochondrial membrane potential and eventually decreased ATP synthesis. This dysfunction is critical, as the organ systems that are most susceptible to ischemic injury have high energy requirements. Neurons,

for example, are greatly dependent upon efficient ion transport across the plasma membrane to maintain electrical homeostasis, conduct action potentials, and accommodate the release/uptake of neurotransmitters (Adibhatla and Hatcher 2010). Additionally, the kidney and heart are reliant upon ATP for the regulation of blood filtration and muscle contraction/relaxation, respectively (Hausenloy and Yellon 2013; Stallons et al. 2013; Whitaker et al. 2016). While reperfusion following ischemia allows for reoxygenation and the reintroduction of nutrients to damaged tissue, the reinstatement of blood flow is also characterized by oxidative damage and inflammation (Moskowitz et al. 2010). Cells bordering the central site,

571

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while hypoxic, are not solely dependent upon the vessel blocked during the ischemic event and as such are able to survive due to partial perfusion from surrounding vasculature. Upon reperfusion, however, the inrush of oxygen into these hypoxic peripheral cells leads to the generation of ROS, a large portion of which are formed from the ETC of dysfunctional mitochondria (Hausenloy and Yellon 2013; Sanderson et al. 2013). This increased ROS production not only overwhelms endogenous antioxidant defenses, but also leads to Ca2+ overload and opening of the mitochondrial permeability transition pore (mPTP). mPTP opening releases Ca2+ into the intermembrane space and allows the influx of ions and water into the mitochondrial matrix, simultaneously resulting in loss of the electrochemical gradient required to produce ATP and causing the matrix to swell, expanding the inner membrane until the outer membrane ruptures (Hirsch et al. 1998; McEwen et al. 2011). Rupturing releases accumulated Ca2+, as well as ROS and proapoptotic proteins into the cytosol, initiating lipid/protein oxidation and apoptotic cell death (Sesso et  al. 2004; Kalogeris et  al. 2014). Therefore, therapeutics aimed at  restoring mitochondrial homeostasis could aid in rescuing organ function following ischemic/reperfusion (I/R) injury. 39.4.2

Myocardial Infarction (MI)

Unfortunately, strategies targeting specific aspects of mitochondrial dysfunction following I/R have proven largely inconsistent or unsuccessful (Andreadou et  al. 2009; Kalogeris et al. 2014). For example, while beneficial as pretreatments, antioxidant‐based treatments have shown limited, if any, therapeutic advantage when administered during or after reperfusion (Kalogeris et al. 2014). When administered at the time of reperfusion, the  mPTP inhibitor cyclosporine A (CsA) enhanced mitochondrial function and decreased infarct size in the post‐I/R heart in vivo (Jurado et al. 1998; Lim et al. 2007; Skyschally et  al. 2010); however, data from human studies investigating CsA for the treatment of myocardial infarction (MI), which occurs following decreased blood flow to cardiac muscle, have been mixed (Piot et al. 2008; Ottani et al. 2016). Regardless of any positive results, CsA is toxic, making it less than ideal as a therapeutic (Caramelo et  al. 2004; Schenk et  al. 2010; Rabchevsky et al. 2011; Szalowska et al. 2015). Evidence suggests, however, that enhanced MB may be an advantageous method for the treatment of MI. Increased MB following exercise was found to lessen oxidative stress in  rats following MI (Jiang et  al. 2014). Additionally, overexpression of TFAM has been correlated with increased survival following permanent ligation of the coronary artery in mice (Ikeuchi et al. 2005). While the

aforementioned studies are preliminary and few in number, they indicate the potential therapeutic efficacy of augmenting MB for the treatment of MI. 39.4.3

Acute Kidney Injury (AKI)

There is constant movement of ions and small molecules within the kidney epithelium and, as such, renal epithelial cells are heavily dependent on mitochondrial function and the production of ATP to facilitate active transport. Rapid and persistent mitochondrial damage, and the subsequently increased ROS and loss of ATP and antioxidant defenses, largely contributes to the cell death that occurs with acute kidney injury (AKI) (Jassem et al. 2002; Jassem and Heaton 2004; Feldkamp et  al. 2005; Bellomo et al. 2012; Funk and Schnellmann 2012; Stallons et al. 2013). The mortality rate of AKI can range from 10 to 80% depending on the specific patient population assessed, strongly demonstrating the need for new, more efficacious therapeutic interventions (Thadhani et  al. 1996; Stallons et  al. 2013). Recently, PGC‐1α and MB have gained popularity as potential treatment strategies following AKI. PGC‐1α expression has been found to correlate with renal function, with levels decreasing after AKI and partially restoring during recovery (Tran et al. 2011; Funk and Schnellmann 2012). In addition to these findings, our laboratory previously demonstrated that pharmacological activation of MB beginning 24 h following I/R–AKI, when injury is maximum, accelerates mitochondrial and renal function recovery in mice. Interestingly, comparable results were observed when MB was induced using phosphodiesterase (PDE) inhibitors (Whitaker et al. 2013), the 5‐HT1F receptor agonist LY344864 (Garrett et  al. 2014), or the Food and Drug Administration (FDA)‐approved β2‐adrenergic receptor agonist formoterol (Jesinkey et al. 2014a). These data not only strongly suggest the potential of MB as a treatment for AKI, but also indicate that the precise mechanism of MB induction is not critical to its therapeutic effect. 39.4.4

Spinal Cord Injury

Spinal cord injury (SCI) is a debilitating condition with no meaningful therapy. The initial injury causes disruption of vasculature within the spinal cord, resulting in vasoconstriction (Tator and Fehlings 1991; Baptiste and Fehlings 2006; Graumann et al. 2011), and within minutes to hours following this primary injury, the subsequent local decrease in oxygen delivery contributes to a self‐propagating secondary cascade. Ischemia is a key mechanism of secondary injury post‐SCI, with the degree of functional loss being proportional to the degree of ischemia (Tator and Fehlings 1991). Additional consequences of secondary injury include neuronal cell

Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies

death (Beattie et al. 2002; Anwar et al. 2016), progressive axon demyelination (Totoiu and Keirstead 2005), inflammation (Qiao et  al. 2010; Qiao et  al. 2015), and  mitochondrial dysfunction. Loss of mitochondrial homeostasis results in decreased ATP production and inactivation of ATP‐dependent ion pumps required for regulation of ion concentrations and reuptake of the excitatory neurotransmitter glutamate. This dysfunction ultimately leads to excitotoxicity, Ca2+ overload, and the eventual initiation of cell death cascades, all of which are hallmarks of SCI and further exacerbate injury (Choi and Rothman 1990; Rowland et  al. 2008; Oyinbo 2011). Studies suggest that restoration of mitochondrial function shortly after SCI may be an efficacious therapeutic strategy. Unfortunately, despite in vivo data using treatments aimed at specific components of mitochondrial function, such as enhancing antioxidant defenses (Pandya et al. 2014; Patel et al. 2014) or inhibiting opening of the mPTP (Ibarra et  al. 1996a, b; Rabchevsky et  al. 2001; Ibarra et al. 2003; McMahon et al. 2009), there remains no approved pharmacological intervention. Enhanced MB, however, is a largely unexplored strategy for targeting multiple aspects of mitochondrial function for the treatment of SCI. Hu et al. (2015, 2016) recently reported that not only is PGC‐1α expression decreased in the spinal cord after contusive SCI in rats, but also spinal lentiviral overexpression of PGC‐1α immediately after injury attenuates neuronal cell death and promotes functional recovery, suggestive of the potential benefit of pharmacologically increasing PGC‐1α and MB following injury. 39.4.5

Stroke

Excessive ROS generation has long been implicated in neuronal cell death in various neurological and neurodegenerative pathologies, including cerebral ischemia (Chen et al. 2011; Sanderson et al. 2013). Similar to the consequences observed with SCI secondary injury, the lack of oxygen and nutrients being supplied to the brain disrupts neuronal homeostasis, ultimately leading to cell death. Multiple studies have indicated protective effects of PGC‐1α and endogenous MB following cerebral ischemia. Neuronal PGC‐1α is necessary for the generation of several proteins with antioxidant activity, including glutathione peroxidase, uncoupling protein 2 (UCP2), and superoxide dismutase 2 (SOD2) (St‐Pierre et  al. 2006). Furthermore, overexpression of PGC‐1α has been suggested to protect neurons from oxidative stress and subsequent cell death, while knockdown of the protein has the opposite effect (St‐Pierre et al. 2006; Chen et al. 2010). Interestingly, ischemic brain injury has been shown to induce PGC‐1α and MB, presumably as an endogenous repair mechanism (Gutsaeva et al. 2008; Yin et  al. 2008). These findings largely implicate PGC‐1α,

and MB, as a potential neural protectant against ischemia‐induced neuronal loss. Therefore, exogenously augmenting MB may facilitate these protective properties. For example, the polyphenol resveratrol, a main component of wine, has been observed to induce MB in neurons and, in a separate study, to protect against neonatal cerebral ischemia (Dasgupta and Milbrandt 2007; West et al. 2007).

39.5

Chronic Diseases

39.5.1

Neurodegenerative Diseases

Mitochondrial dysfunction and oxidative stress are hallmarks of many neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD), the two most common neurodegenerative disorders (Yan et al. 2013). Postmortem analysis of the brain tissue of AD patients revealed mitochondrial structural damage, increased mitochondrial size, and decreased mitochondrial number (Hirai et al. 2001), indicating the disrupted nature of mitochondrial homeostasis in the diseased brain. Further supporting this phenomenon is alterations in mitochondrial fusion and fission proteins in the AD brain, suggestive of increased mitochondrial fragmentation (Yan et al. 2013). Detrimental mutations in mtDNA are present in various brain regions of both AD and PD patients (Khan et al. 2000; Coskun et al. 2012). Importantly, variants in mtDNA‐ or nuclear‐encoded mitochondrial complex I genes, leading to altered OXPHOS, have been connected to increased predisposition to PD (Coskun et al. 2012). The dopaminergic neurons of the substantia nigra are particularly susceptible to mtDNA mutations and oxidative damage due to high amounts of prooxidant iron and low amounts of the antioxidant glutathione (Bender et  al. 2006). Additionally, several genetic defects converging on mitochondrial pathways have been discovered in both sporadic and familial PD, strongly implicating loss of mitochondrial homeostasis in the disease. For example, in autosomal recessive juvenile parkinsonism, mutations in parkin and PTEN‐induced putative kinase 1 (PINK1), components of mitophagy, result in failed clearance of damaged mitochondria, leading to persistent elevation of ROS in the substantia nigra and eventual neuron loss (Yan et al. 2013). Huntington’s disease (HD) is a lethal autosomal dominant disorder caused by a mutation of the huntingtin (Htt) gene and characterized by striatal degeneration and behavioral and cognitive defects. Patients with HD have metabolic deficits in the brain and muscle, as well as reduced complex I, II, and III activity in the striatum (Antonini et  al. 1996; Tabrizi et  al. 1999; Feigin et  al. 2001). mtDNA mutations are also involved in the

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pathology of HD, with increased mtDNA deletions being observed in the brains of HD patients compared with controls (Banoei et  al. 2007). Importantly, the mutated form of Htt directly impairs mitochondrial function through interaction with PGC‐1α, leading to decreased expression of mitochondrial genes, including TFAM, altering mitochondrial function, and homeostasis (Cui et  al. 2006; McGill and Beal 2006; Weydt et  al. 2006; Chaturvedi and Beal 2013). Furthermore, postmortem analysis revealed decreased PGC‐1α and downstream target gene expression, as well as reduced mitochondrial content and MB in HD brain and muscle tissue (Chaturvedi et al. 2009; Kim et al. 2010). Mitochondrial dysfunction is related to many of the proposed mechanisms of neurodegeneration that occurs with amyotrophic lateral sclerosis (ALS), a motor neuron disorder that generally results in death due to respiratory failure within 5 years of onset (Cozzolino and Carrì 2012). Deformed, often swollen and vacuolated, mitochondria have been observed in the muscles and motor neurons of ALS patients and are thought to contribute to the formation of ALS‐specific Bunina bodies (Hart et al. 1977; Sasaki et  al. 2007; Cozzolino and Carrì 2012). Analysis of central nervous system (CNS) tissue from ALS patients has consistently uncovered alterations in ETC activity, although the precise dysfunction has varied between cohorts (Bowling et al. 1993; Fujita et al. 1996; Wiedemann et  al. 2002). In skeletal muscle, however, consistent deficiencies in complexes I and IV have been observed (Vielhaber et  al. 2000; Crugnola et  al. 2010). This loss of mitochondrial function is accompanied by increased ROS production and oxidative stress, as well as Ca2+ dysregulation and excitotoxicity. Importantly, the motor neurons affected by ALS have a low Ca2+ buffering capacity and are therefore highly vulnerable to excitotoxicity (Van Den Bosch et al. 2000), strongly indicating the need for improved mitochondrial function in these neurons. Interestingly, mitochondrial dysfunction has also been found in tissues unassociated with ALS, including in the liver and lymph nodes, of ALS patients (Nakano et al. 1987). Current therapeutic treatments for these neuropathologies are palliative, as there exists no method of stopping or slowing progression of the diseases. There is  substantial evidence suggesting that augmenting MB is a potential therapeutic strategy for neurodegenerative disorders. For example, not only is PGC‐1α decreased in animal models of PD, but loss of PGC‐1α also increases susceptibility to the disease (St‐Pierre et al. 2006). Similarly, dysregulation of PGC‐1α has been shown to exacerbate lead‐induced neurotoxicity, while modestly increasing PGC‐1α expression proved neuroprotective against the environmental toxicant associated with increased risk of developing PD.

Additionally, substantia nigral cells exposed to lead increased PGC‐1α transcription, likely as an endogenous protection mechanism (Dabrowska et al. 2015). Impaired MB has also been implicated in the mitochondrial dysfunction that accompanies AD, and overexpression of PGC‐1α was found to ameliorate this dysfunction (Sheng et  al. 2012). Furthermore, bezafibrate, a PPAR agonist that activates PGC‐1α, was found to enhance behavior in a transgenic mouse model of AD (Dumont et  al. 2012). Treatment with various thiazolidinediones (TZDs), selective PPARγ agonists shown to enhance MB, has resulted in improved cognitive function in patients with early mild to moderate AD (Watson et al. 2005; Risner et al. 2006; Heneka et al. 2015; Cheng et  al. 2016). Interestingly, treatment with resveratrol, which activates PGC‐1α via SIRT1 expression and increased AMP‐activated protein kinase (AMPK), has resulted in functional improvement and decreased neuronal degeneration in animal models of PD, AD, HD, and ALS (Kim et  al. 2007; Blanchet et  al. 2008; Long et  al. 2009; Ho et al. 2010; Whitaker et al. 2016). Rotenone is a widely used pesticide and is considered the principal environmental risk factor for the development of nonfamilial PD; chronic exposure to low doses of rotenone results in complex I dysfunction and oxidative stress, two major contributors to the pathology of PD. Recently, resveratrol was observed to enhance mitochondrial homeostasis following rotenone exposure both in vivo and in vitro, correlating with increased TFAM and PGC‐1α expression, indicating improved MB (Peng et  al.  2016). Furthermore, a phase III clinical trial (NCT00678431) is underway investigating combinatorial treatment with resveratrol, glucose, and malate as a potential treatment option for mild to moderate AD (Wang and Chen 2016). Direct activation of AMPK using the adenosine analogue AMPK activator 5‐aminoimidazole‐4‐carboxamide ribonucleotide (AICAR) was also found to be neuroprotective using a mouse model of AD (Vingtdeux et  al. 2010). These studies, among others, indicate that pharmacological amplification of PGC‐1α and subsequent enhancement of MB may be an effective strategy for the treatment of various acute and chronic degenerative disorders.

39.6 Pharmacological Activation of MB Several compounds that modulate MB have been identified via target‐based and phenotypic screens, including kinases, as well as compounds that bind to and modulate specific G protein‐coupled receptors (GPCRs), nuclear

Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies

Pharmacological Agonists

5-HTRs βARs

U0126 Trametinib

MEK1/2 eNOS cAMP

AMP

ERK1/2

PI3K

Resveratrol Natural products sGC

NO donors Rolipram Cilostazol

AKT

NO

PDE

TFAM

SIR

PGC-1α Cinaciguat BAY 41-2272

T1

cGMP

Ac PGC-1α

PDE

Ac

Sildenafil

mtDNA

AMPK GMP

PGC-1α

PGC-1α GCs

Nucleus

Mitochondrial proteins

AICAR Metformin

CREB

ERRs

PPARs

TZDs Bezafibrate

NRFs

TFAM

OXPHOS mRNAs

OXPHOS proteins

Cytoplasm

Figure 39.1 Pharmacological activation of MB. MB is a highly regulated cellular process that, while controlled by the central transcriptional coactivator PGC‐1α, involves an array of diverse pathways. Various pharmacological agents can augment MB by targeting different aspects of these pathways, including agonism of G protein‐coupled receptors, increased AMPK and cGMP, enhanced SIRT1‐mediated PGC‐1α deacetylation, and activation of coactivators that interact with PGC‐1 α, culminating in increased expression of mitochondrial genes and MB. 5‐HTRs, 5‐hydroxytryptamine receptors; βARs, β adrenergic receptors; Ac, acetyl group; AICAR, 5‐aminoimidazole‐4‐carboxamide ribonucleotide; AKT, protein kinase B; AMP, adenosine monophosphate; AMPK, adenosine monophosphate‐activated kinase; cAMP, cyclic adenosine monophosphate; cGMP, cyclic guanosine monophosphate; CREB, cAMP response element binding; eNOS, endothelial nitric oxide synthase; ERK1/2, extracellular signal‐regulated kinase 1/2; ERRs, estrogen‐related receptors; GCs, glucocorticoids; GMP, guanosine monophosphate; MEK1/2, mitogen‐activated protein kinase kinases 1/2; mtDNA, mitochondrial DNA; NO, nitric oxide; NRFs, nuclear respiratory factors; OXPHOS, oxidative phosphorylation; PDE, phosphodiesterase; PGC‐1α, peroxisome proliferator‐activated receptor‐γ coactivator 1‐α; PI3K, phosphoinositide 3‐kinase; PPARs, peroxisome proliferator‐activated receptors; sGC, soluble guanylate cyclase; SIRT1, sirtuin 1; TFAM, mitochondrial transcription factor A.

receptors, and other transcription factors. Hallmark compounds identified using this approach include modulators for PPARs, estrogen receptors (ERs), sirtuins (SIRTs), AMPK, and the cyclic nucleotides cyclic adenosine monophosphate (cAMP) and cGMP. Animal models, and some human studies, have provided evidence supporting the efficacy of compounds that target MB for ameliorating mitochondrial dysfunction. In the following sections, we will discuss several mitochondrial biogenic drugs with therapeutic potential for the treatment of acute and chronic diseases, as well as their molecular targets. The affected pathways are outlined in Figure 39.1.

39.7

Kinase Modulators

39.7.1

AMPK

AMPK is an ubiquitously expressed heterotrimeric kinase that acts as a highly conserved energy sensor and participates in the regulation of energy‐generating and consumption pathways. It turns on catabolic pathways to generate ATP while simultaneously switching off anabolic pathways that consume ATP. It also triggers increases in glucose uptake, OXPHOS, autophagy, and MB. It has been reported to directly phosphorylate PGC‐1α at two sites, activating its transcription

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(Jager et al. 2007). An alternative mechanism by which AMPK may activate PGC‐1α function is via deacetylation catalyzed by the nicotinamide adenine dinucleotide (NAD)‐dependent deacetylase SIRT1(Rodgers et al. 2005). Evidence of AMPK‐induced PGC‐1α upregulation originated from a study that fed rats β‐guanidinopropionic acid (β‐GPA), a creatine analogue that results in ATP depletion. Muscle phosphocreatine, ATP, and ATP/AMP ratios were all markedly decreased in the β‐GPA rats, leading to the activation of AMPK. Under these conditions, NRF‐1 binding activity, cytochrome c content, and muscle mitochondrial density were all increased (Bergeron et  al. 2001). These data suggest that AMPK plays an important role in promoting mitochondrial adaptation to energy stress and MB. Pharmacological activation of AMPK has been observed with multiple compounds, including AICAR and metformin (Rambert et  al. 1961; Zhang et  al. 2006). AICAR is an adenosine analogue AMPK activator, which has shown positive effects following cardiac and renal I/R injury through enhanced glucose uptake and SIRT1 expression, respectively (Russell et al. 1999; Lempiainen et al. 2012). AICAR has also been successful in chronic disease models, such as type 2 diabetes, by preventing insulin resistance in multiple tissues, as well as in AD through decreases in amyloid‐β protein levels (Boon et al. 2008; Bikman et al. 2010; Vingtdeux et  al. 2010). Table 39.2 summarizes AICAR‐mediated MB in multiple tissues. 39.7.2

ERK1/2

MAPKs are serine–threonine kinases that mediate intracellular signaling associated with a variety of cellular activities, including cell proliferation, differentiation, survival, death, and transformation. Extracellular signal‐regulated kinase (ERK1/2), a member of the MAPK family, has been implicated as a negative regulator of MB (Collier et  al. 2016). Table 39.2 summarizes trametinib‐mediated MB following renal I/R injury in mice. ERK1/2 reduces PGC‐1α and its downstream targets in a number of disease models. In animal models of PD, TFAM phosphorylation as a result of ERK1/2 activation decreased the transcription of mtDNA (Wang et  al. 2014b). In AD, ERK1/2 activation impaired mitochondrial function, as evidenced by altered mitochondrial fission and fusion processes and reduced mitochondrial membrane potential (Gan et  al. 2014). ERK1/2 activation is also a downstream event of ROS generation. Using renal proximal tubules cells (RPTC), our laboratory showed that following administration of the oxidant tert‐butyl hydroperoxide (TBHP), ERK1/2 phosphorylation correlated with reduced complex I activity and ATP production (Nowak et  al. 2006). Furthermore, I/R–AKI‐induced ERK1/2 activation

preceded the initial decrease in renal  PGC‐1α mRNA and loss of renal function (Collier et al. 2016). ERK1/2 is thought to be the only substrate for mitogen‐activated protein kinase kinase (MEK1/2) phosphorylation; therefore, pharmacological inhibition of ERK1/2 can be accomplished using MEK1/2 inhibitors. Treatment with the inhibitor U0126 was found to rescue hippocampal PGC‐1α, TFAM, and NRF‐1 protein levels following amyloid‐β injections in rats (Ashabi et  al. 2012). Additionally, our laboratory has reported that inhibition of ERK1/2 using trametinib not only attenuates the early decrease in PGC‐1α but also prevents decreased renal function following I/R– AKI (Collier et al. 2016). These studies provide evidence that targeting negative regulators of MB is an effective strategy to induce MB and restore organ function following injury.

39.8 G Protein‐Coupled Receptor Modulators GPCRs are the largest and most diverse group of membrane receptors. These cell surface receptors are affected by both endogenous ligands and pharmacological agents. GPCRs are involved in an array of functions within the human body, and it is estimated that between one‐third and one‐half of all marketed drugs are GPCR ligands (Flower 1999; Robas et al. 2003). They consist of a single polypeptide that is folded into a globular shape and embedded within the cellular plasma membrane. As the name implies, GPCRs interact with G proteins, in that external signaling molecules bind to a GPCR, inducing a conformational change and triggering the interaction between the GPCR and a nearby G protein. G protein activation can affect the production of hundreds to thousands of downstream effectors, including those that modulate MB. Downstream effectors of GPCRs that can regulate mitochondrial function include cGMP, Ca2+, phosphoinositide 3‐kinase (PI3K), and endothelial nitric oxide synthase (eNOS) (Dudzinski and Michel 2007; Tuteja 2009). While GPCRs are well‐characterized regulators of a variety of cell processes, studies exploring GPCR ligands as inducers of MB are limited. 39.8.1

5‐HT Receptors

5‐Hydroxytryptamine (5-HT, serotonin) receptors have been classified into seven groups based on structure and signal transduction mechanisms. 5‐HT receptors are predominantly GPCRs and are known to be involved in various CNS and peripheral functions, such as anxiety, sleep, blood vessel constriction, and gastrointestinal

Table 39.2 A selective list of pharmacological inducers of mitochondrial biogenesis. Class

Drugs

MB effects

References

AMPK activators

AICAR

↑MB, ↑ATP production, ↑oxygen consumption in multiple tissues

Bikman et al. (2010), Boon et al. (2008), Lempiainen et al. (2012), Russell et al. (1999), and Vingtdeux et al. (2010)

MEK inhibitors

Trametinib

↑PGC‐1α, ↑TFAM in RPTC, ↑recovery of renal function and MB following mouse I/R

Collier et al. (2016) and Nowak et al. (2006)

↑PGC‐1α, ↑OXPHOS proteins, ↑mtDNA, ↑oxygen consumption, ↑recovery of renal function and MB following mouse I/R

Garrett et al. (2014)

SB242084

↑PGC‐1α, ↑OXPHOS genes, ↑oxygen consumption in RPTC

Harmon et al. (2016)

β‐adrenergic agonists

Formoterol

↑PGC‐1α, ↑OXPHOS proteins, ↑mtDNA, ↑oxygen consumption in RPTC, ↑recovery of renal function and MB following mouse I/R

Jesinkey et al. (2014a) and Wills et al. (2012)

CB1 antagonists

Rimonabant ↑OXPHOS genes, ↑oxygen consumption, ↑eNOS activation in mouse white adipocytes

Tedesco et al. (2008)

PDE inhibitors

Sildenafil

↑PGC‐1α, ↑OXPHOS genes, ↑mtDNA, ↑oxygen consumption in RPTC, ↑recovery of renal function and MB following mouse folic acid‐induced AKI

Whitaker et al. (2013)

Vardenafil

↑PGC‐1α, ↑mtDNA in human adipose tissue

De Toni et al. (2011)

Rolipram

↑PGC‐1α, ↑TFAM, ↑PGC‐1α activity, ↑mtDNA, Park et al. (2012) ↑AMPK in skeletal muscle

Cilostazol

↑PGC‐1α, ↑TFAM, ↑mtDNA, ↑ATP, ↑CREB in cultured endothelial

Zuo et al. (2013)

↑PGC‐1α, ↑TFAM, ↑OXPHOS genes, ↑oxygen consumption in mammalian cultured models

Nisoli et al. (2004)

5HT agonists LY344864 DOI

NO mimetics DETA‐NO

Rasbach et al. (2010)

GC stimulators

Bay 41‐2272 ↑PGC‐1α, ↑OXPHOS genes, ↑oxygen Cinaciguat consumption in cultured models, protective in I/R and LPS models Riociguat

Nisoli et al. (2004) and Salloum et al. (2012)

PPARγ agonists

TZDs

↑PGC‐1α, ↑TFAM, ↑OXPHOS genes in adipose tissue and skeletal muscle in diabetes

Bogacka et al. (2005), Mensink et al. (2007), and Rong et al. (2007)

PPARα agonists

Fibrates

↑PGC‐1α, ↑AMPK activation in multiple tissues

Ansquer et al. (2009), Grabacka et al. (2013), and Sarma (2012)

PPARδ agonists

GW501516

↑PGC‐1α, ↑FAO in muscle and liver

Barroso et al. (2011) and Kleiner et al. (2009)

ER agonists

Estradiol

↑PGC‐1α, ↑TFAM, ↑OXPHOS proteins, ↑oxygen consumption in multiple tissues

Capllonch‐Amer et al. (2014), Irwin et al. (2008), Mattingly et al. (2008), and Sbert‐Roig et al. (2016)

Sirtuin activators

Resveratrol

↑PGC‐1α, ↑SIRT1, ↑mitochondrial function in multiple tissues

Csiszar et al. (2009), Feige et al. (2008), Funk and Schnellmann (2013), Libri et al. (2012), Menzies et al. (2013), Milne et al. (2007, Tong et al. (2013), and Wang et al. (2014a)

SRT1720 SRT1460 SRT2104 SRT2379

Natural products

Isoflavones

↑PGC‐1α, ↑OXPHOS proteins, ↑oxygen Rasbach and Schnellmann (2008) consumption, ↑ATP, ↑SIRT1 activation in RPTC

Flavonoids

↑PGC‐1α, ↑TFAM, ↑OXPHOS proteins, ↑SIRT1 in multiple tissues

Li et al. (2016), Ramirez‐Sanchez et al. (2016), and Rayamajhi et al. (2013)

Arrows indicated increase (↑) and decrease (↓). 5‐HT, hydroxytryptamine; AICAR, 5‐aminoimdazole‐4‐carboxamide ribonucleotide; AKI, acute kidney injury; AMPK, AMP‐activated protein kinase; ATP, adenosine triphosphate; CB1, cannabinoid receptor 1; CREB, cAMP response element‐binding protein; DETO‐NO, diethylenetriamine/NO adduct; DOI, 2,5‐dimethoxy‐4‐iodamphetamine; eNOS, endothelial nitric oxide synthase; ER, estrogen receptor; ERK, extracellular signal‐regulated kinase; FAO, fatty acid oxidaton; GC, guanylate cyclase; I/R, ischemia/ reperfusion; LPS, lipopolysaccharide; MB, mitochondrial biogenesis; mtDNA, mitochondrial DNA; NO, nitric oxide; OXPHOS, oxidative phosphorylation; PDE, phosphodiesterase; PGC‐1α, peroxisome proliferator‐activated receptor‐γ coactivator‐1α; PPAR, peroxisome proliferator‐activated receptor; RPTC, renal proximal tubule cells; SIRT1, sirtuin 1; TFAM, mitochondrial transcription factor A; TZDs, thiazolidinediones.

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Mitochondrial Dysfunction by Drug and Environmental Toxicants

motility (Vanhoutte and Luscher 1986; Leonard 1996; Nichols and Nichols 2008). 5‐HT receptors have also been identified as targets for alterations in mitochondrial function, including apoptosis and mitochondrial membrane integrity (Nebigil and Maroteaux 2003). Our  laboratory recently made the novel observation that  several 5‐HT receptor ligands can induce MB. The nonselective 5‐HT receptor agonist α‐methyl‐5‐HT increased mitochondrial respiration, a marker of MB, in RPTC (Garrett et  al. 2014). We have also identified specific ligands of 5‐HT2 and 5‐HT1 receptors as potent inducers of MB. 2,5‐Dimethoxy‐4‐iodoamphetamine (DOI), a 5‐HT2 receptor agonist, promoted renal MB in  vitro, as evidenced by increased mitochondrial respiration genes and proteins, as well as rescued mitochondrial respiration following oxidant injury (Rasbach et  al. 2010). Interestingly, the selective 5‐HT2C agonist CP809101 and the 5‐HT2C antagonist 6‐Chloro‐2,3‐ dihydro‐5‐methyl‐N‐[6‐[(2‐methyl‐3‐pyridinyl)oxy]‐3‐ pyridinyl]‐1H‐indole‐1‐carboxyamide dihydrochloride (SB242084) induced MB in vitro and in naïve mice. However, studies utilizing siRNA and knockout mice revealed that these ligands employ their mitochondrial biogenic effects through the 5‐HT2A receptor. Similarly, the 5‐HT2A agonist NBOH‐2C‐CN also elevated renal mitochondrial respiration, confirming that the 5‐HT2A receptor is a target for the induction of MB (Harmon et  al. 2016). Table 39.2 summarizes 5‐HT‐induced MB pathways. The 5‐HT1F receptor agonists LY344864 and lasmiditan were also found to be potent inducers of mitochondrial respiration and ETC genes in vitro and in renal, cardiac, and hepatic tissue in mice (Garrett et al. 2014). LY344864 treatment accelerated the recovery of renal function following I/R–AKI, correlating with restoration of mtDNA copy number (Garrett et al. 2014). Additionally, daily treatment with LY344864 reduced behavior impairments and increased mitochondrial gene expression and mtDNA content, indicative of enhanced MB, in a mouse model of PD (Scholpa et al. 2017). Recent data revealed that stimulation of the 5‐HT1F receptor induces MB through the activation of the stimulatory AKT/eNOS/ cGMP pathway (Gibbs et al. 2017). Collectively, these data provide compelling evidence that exploitation of 5‐ HT receptors has a significant therapeutic role in the recovery of mitochondrial and organ function. 39.8.2

β‐Adrenergic Receptors

Catecholamine‐binding adrenergic receptors can be divided into two main groups, α and β, with dynamic roles in an array of functions β, with each group being further divided into classes. The β1‐adrenergic recep-

tor is predominately expressed in cardiac tissue and pharmacologically targeted for heart rate stimulation and  contractility. The β3 receptor is localized mainly in adipose tissue and the bladder and, as such, is a target to treat overactive bladder. The ubiquitously expressed β2 receptor is targeted by drugs used to treat asthma and chronic obstructive pulmonary disease (COPD). Adrenergic receptors have become an attractive target for MB due to their role in cold‐ induced MB. Studies revealed that in a cold environment, release of the catecholamine norepinephrine leads to the activation of β‐adrenergic receptors, stimulation of adenylate cyclase, and an increase in intracellular cAMP, resulting in the phosphorylation of cAMP response element‐binding protein (CREB), a transcriptional activator of PGC‐1α (Ye et al. 2013a). Thus, adrenergic receptor ligands can act as pharmacological modulators of MB. The nonselective β‐adrenergic receptor agonist isoproterenol increases PGC‐1α expression in brown adipose tissue in naïve mice (Muller et  al. 2013). Interestingly, in models of cardiac dysfunction, the β 1‐selective antagonist metoprolol, with a reported pKi of 7–7.6, enhances PGC‐1α activation and improves cardiac metabolism and function (Sharma et al. 2009; Alexander et al. 2015). The β2‐adrenergic receptor has also been demonstrated as a target for MB. Formoterol, a  long‐acting β2‐adrenergic receptor agonist, stimulates mitochondrial respiration, PGC‐1α mRNA, and PGC‐1α‐dependent gene expression in RPTC and in naïve mouse kidney (Wills et  al. 2012). Formoterol administration following I/R–AKI accelerated renal recovery, correlating with improved mitochondrial respiration (Jesinkey et al. 2014a). In addition to these renal effects, formoterol also induced MB in cardiac tissue and skeletal muscle (Wills et  al. 2012; Jesinkey et  al. 2014b). Table 39.2 summarizes formoterol‐ mediated MB following renal I/R injury in mice. The identification of formoterol as an inducer of MB led to the screening of other β2‐adrenergic receptor ligands. Interestingly, other such ligands, including clenbuterol and isoetharine, did not induce MB in RPTC (Peterson et  al. 2013). Clenbuterol, however, was shown to activate receptor‐interacting protein 140 (RIP140), a negative regulator of MB, leading to the suppression of PGC‐1α in muscle (Hoshino et  al. 2012). Recent data from our laboratory revealed that both formoterol and clenbuterol increase cAMP; however, formoterol‐induced MB occurs through Gβγ‐dependent activation of the AKT/eNOS/cGMP pathway, which does not occur with clenbuterol, likely contributing to the differences in MB induction observed between the two agonists (Cameron et al. 2017). These data suggest

Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies

that functional selectivity based on spatial and chemical characteristics can be explored for the future development of pharmacological agents with structural similarities to β2 agonists that induce MB.

mitochondrial dysfunction; therefore, modulators of cyclic nucleotides represent a class of potential therapeutics for the induction of MB in various diseases (Whitaker et al. 2016).

39.8.3

39.9.1

Cannabinoid‐1 Receptor

Cannabinoid type 1 (CB1) receptors are the most abundant GPCR expressed in the brain. CB1 receptors are also highly expressed in peripheral organs, especially white adipose tissue (WAT), where it functions to modulate energy metabolism. The endocannabinoid system is overactive in peripheral tissues as evidenced by markedly increased levels of the endocannabinoid arachidonoyl glycerol (2‐AG), which has been correlated with body fat, visceral mass, and plasma insulin concentrations, in visceral fat of obese and diabetic subjects (Bluher et  al. 2006). Previous studies suggest that CB1 receptor overstimulation causes a downregulation in MB in high metabolic tissues, partially explaining increased fat deposits and metabolic dysfunction in an obese setting (Tedesco et  al. 2010). CB1 receptor‐ deficient mice are lean, resistant to high‐fat diet, and have increased MB in WAT (Tedesco et  al. 2008). Studies using the selective CB1 receptor agonist rimonabant persistently reduced body weight and liver steatosis and improved WAT metabolism and glucose uptake in skeletal muscle in obese mice. Additionally, rimonabant increased MB in cultured white adipocytes through an eNOS‐dependent increase in AMPK activity, as evidenced by elevated mRNA expression of PGC‐1α, TFAM, and NRF‐1 (Tedesco et al. 2008). Table 39.2 summarized rimonabant‐mediated MB in mouse white adipocytes. These studies indicate that antagonism of the CB1 receptor stimulates fat metabolism through the activation of MB. Thus, pharmacological and genetic blockade of the CB1 receptor is a potential pharmacological strategy for the treatment of impaired energy metabolism.

39.9

Cyclic Nucleotide Modulators

The cyclic nucleotides cGMP and cAMP are ubiquitous second messengers that play a crucial role in MB. Following extracellular signaling, NO activates soluble guanylate cyclase (sGC), which produces cGMP, while  stimulation of Gαs activates adenylate cyclase activity, producing cAMP. These cyclic nucleotides either directly activate downstream kinases or are hydrolyzed by PDEs. cGMP and cAMP formations are disrupted in numerous pathological states with

NO/cGMP Pathway

cGMP is a starting point for multiple signal transduction cascades. The biological importance of NO/cGMP signaling was first recognized for promoting vascular smooth muscle relaxation and platelet disaggregation (Karaki et al. 1988; Radomski et  al. 1990). The effects of NO/cGMP signaling on differentiation of vascular smooth muscle in response to growth factors, vasoactive peptides, physical damage, and other stimuli have also been clearly demonstrated (Garg and Hassid 1989; Protter et al. 1996; Garcha and Hughes 2006). Results from these and other studies drove the search for therapies targeting the NO/cGMP pathway. Activation of the NO/cGMP signaling pathway through the use of NO donors such as diethylamine‐ NONOate (DEA‐NONOate), cGMP mimetics, sGC stimulators such as cinaciguat and BAY 41‐2272, and cGMP‐selective PDE inhibitors such as sildenafil and vardenafil has been shown to increase PGC‐1α‐dependent MB and mitochondrial function in vivo (Nisoli et al. 2004; De Toni et al. 2011; Salloum et al. 2012; Whitaker et al. 2013). Cinaciguat has also been shown to protect against cardiac I/R injury through protein kinase G (PKG)‐ dependent induction of hydrogen sulfide (H2S), a known inducer of MB (Salloum et al. 2012). Bay 41‐2272 induces PGC‐1α and other mitochondrial genes, increasing brown fat differentiation in mice (Nisoli et al. 2004). Sildenafil, a PDE5 inhibitor, causes accumulation of cGMP, leading to elevated mitochondrial respiration, ATP production, and ETC gene expression in RPTC and in the renal cortex of naïve mice (Whitaker et  al. 2013). Sildenafil promotes recovery via MB and reduced renal tubular injury following AKI induced by folic acid, supporting the use of PDE inhibitors in models of toxicant‐induced mitochondrial toxicity (Whitaker et al. 2013). See Table 39.2 for a summary of MB pathways mediated by NO donors, GC stimulators, and PDE inhibitors. It is important to note that stimulation of MB through the 5‐HT1F receptor using LY344864 and through the β2‐ adrenergic receptor using formoterol increases eNOS phosphorylation and cGMP production in vitro (unpublished data). Activation of eNOS leads to the generation of NO from the endothelium, causing the activation of sGC and the subsequent production of cGMP. Interestingly, β‐oxidation in eNOS knockout mice was reduced compared with wild‐type mice. This was accompanied by reductions in energy expenditure and mRNA levels of PGC‐1α, TFAM, and NRF‐1, indicating that

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mitochondrial content is effected by the loss of eNOS‐ generated NO and implicating MB  as  an important downstream effect of NO (Le Gouill et al. 2007). In summary, NO/cGMP serves as a central regulator of MB in multiple signaling pathways, supporting the importance of this pathway as a target for MB.

of the ETC (Lee  et  al. 2005). In summary, numerous studies reveal the protective effects of CREB‐induced MB through cGMP and PKA activation. See Table 39.2 for a summary of MB pathways mediated by rolipram and cilostazol.

39.9.2

39.10 Transcription Factor Modulators

cAMP/PKA/CREB Pathway

cAMP and its cellular effector protein kinase A (PKA) are responsible for the phosphorylation and activation of CREB. As discussed, CREB is a transcription factor that binds to CRE and recruits other coactivators to regulate transcriptional activity. The PGC‐1α promoter contains a CRE‐binding site, and activation of CREB leads to increased transcriptional expression of PGC‐1α and downstream gene expression. CREB‐induced activation of PGC‐1α in response to thermogenesis, gluconeogenesis, and exercise has been well-studied in several different tissues. In contrast, CREB activity has been shown to be reduced in cognitive and neurodegenerative disorders, such as AD and HD (DeMarch et al. 2007; Sheng et al. 2012). Due to the tight regulation of cAMP via PDE inhibitors, these compounds are often used to activate the cAMP/ PKA/CREB pathway and have proven to be effective in  preclinical models of neurodegenerative diseases. Rolipram and cilostazol are cAMP‐selective PDE inhibitors that have been found to induce PGC‐1α and mitochondrial activity in multiple in vitro models, indicating their potential for preclinical disease models (Park et al. 2012; Zuo et al. 2013). Rolipram has also been shown to improve synaptic conduction in an AD model, associated with CREB phosphorylation (Gong et al. 2004). Cilostazol was found to reduce neuroinflammation, infarct size, and apoptosis following ischemic brain injury (Choi et  al. 2002). In addition to the effects in the CNS, cilostazol also reduced oxidant‐induced mitochondrial dysfunction and MI size, also associated with CREB phosphorylation (Ye et al. 2013b; Chattipakorn et al. 2014). Finally, recent studies propose the transportation of nuclear CREB to the mitochondria via chaperone proteins (Lee et al. 2005). Once inside the mitochondria, it is thought that CREB interacts with CRE sites in mtDNA, thereby regulating the expression of ETC proteins (De Rasmo et  al. 2009). Mitochondrial CREB phosphorylation was shown to regulate the expression of mtDNA‐encoded proteins, including NADH dehydrogenase subunit 1 (ND1) and ND6, mediated by PKA‐ induced CREB phosphorylation (Ryu et  al. 2005; De Rasmo et al. 2009). Furthermore, disruption in mitochondrial CREB activity alters the expression of various mitochondrial genes, ultimately leading to impairment

As mentioned earlier, the MB program involves the integration of multiple transcriptional regulatory pathways controlling the expression of both nuclear and mitochondrial genes. While the transcriptional control of MB requires complex cooperation, nuclear‐encoded transcription factor coactivators serve as major targets for the selective induction of MB. Members of the nuclear receptor superfamily, including PPARs and ERs, have been shown to regulate mitochondrial metabolism and function. Modulation of these pathways has demonstrated positive effects on MB, mitochondrial function, and disease outcomes in several animal and cellular models. 39.10.1

PPAR Agonists

PPAR isoforms (α, β/δ, and γ) have distinct tissue distributions and functions involved in lipid and fatty acid metabolism. PPARγ, a well‐characterized pharmacological target for the induction of MB, is highly expressed in white and brown adipose tissue and in endothelial cells. The primary function of PPARγ is adipocyte proliferation and differentiation, with agonism increasing peripheral insulin sensitivity, potentially through MB and oxidative metabolism. TZDs such as pioglitazone and rosiglitazone are PPARγ agonists used for the treatment of type 2 diabetes. While the effects of TZDs are pleiotropic, the capacity of TZDs to sensitize multiple tissues to the effects of insulin has been correlated with increased expression of mitochondrial proteins, suggesting that the induction of MB may be central to the clinical efficacy of these drugs (Bolten et al. 2007). Specifically, pioglitazone induced MB and reduces ROS production in subcutaneous adipose tissue (Bogacka et  al. 2005), while rosiglitazone induced MB in human skeletal muscle of obese type 2 diabetic patients (Mensink et  al. 2007; Rong et  al. 2007). PPARγ‐induced MB also improved outcomes in renal and cardiac ischemic injury, neurodegenerative diseases, and multiple sclerosis models (Ito et al. 2003; Quintanilla et al. 2008; Bernardo et al. 2009; Wu et al. 2011; Zolezzi et al. 2013).

Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies

While the positive pharmacological effects of PPARγ are the best characterized of the PPARs, data has also emerged describing PPARα‐ and PPARδ‐induced augmentation of MB. PPARα stimulation using fibrates increased PGC‐1α expression in models of cardiac disease, cancer, and metabolic disorders (Ansquer et al. 2009; Sarma 2012; Grabacka et  al. 2013). Similarly, PPARδ activation using GW501516 increased fatty oxidation and PGC‐1α expression in hepatic and muscle tissue (Kleiner et al. 2009; Barroso et al. 2011). Despite the promising data on PPARα and PPARδ agonists as inducers of MB, additional investigation is needed to determine the full therapeutic application and efficacy of  these compounds. Table 39.2 summarizes MB pathways mediated by PPAR agonists.

39.10.2

ER Agonists

ERs, including ERα and ERβ, are nuclear receptors important for hormone binding and transcription. A recent topic of interest is understanding how estrogen affects mitochondrial function and how this relates to sex‐dependent differences in lifespan (Klinge 2008). Estradiol, a biologically active estrogen, was found to increase mtDNA copy number in vitro following 24, 48, and 72 h of exposure (Mattingly et  al. 2008). In animal models, estradiol has also been shown to increase respiratory capacity and antioxidant defenses while reducing ROS production in the heart, brain, and skeletal muscle (Irwin et al. 2008; Capllonch‐Amer et al. 2014; Sbert‐Roig et  al. 2016). More recently, estradiol was observed to induce TFAM expression, leading to increased mtDNA transcription, via a NRF‐1‐dependent mechanism (Scarpulla 2006). Table 39.2 summarizes estradiol‐mediated MB pathways in multiple tissues. It is important to note that ERs are also located within the mitochondria, where they are predicted to bind to the D‐loop of mouse and human mtDNA (Chen et al. 2008). Whether or not ERs directly or indirectly mediate mtDNA transcription is unknown; nonetheless, the presence of ERs in both the nucleus and mitochondria makes ERs a viable target for the modulation of mitochondrial respiratory function and MB.

39.11

Sirtuins

The SIRTs are a family of proteins that act predominately as NAD‐dependent deacetylases. In mammals, seven SIRT family members exist, including mitochondrial, cytosolic, and nuclear‐localized SIRTs. Of this family, SIRT1 has received the most interest because of its

positive regulation of PGC‐1α (Canto and Auwerx 2009; Canto et al. 2009). As mentioned earlier, PGC‐1α is activated through promoter deacetylation, which primarily occurs via its interaction with SIRT1. SIRT1 also controls the acetylation of Forkhead box O (FOXO) transcription factors, which are important regulators of lipid and glucose metabolism (Brunet et  al. 2004; Canto and Auwerx 2009). The acetylation status of FOXO directs it to certain targets, such as the PGC‐1α promoter (Canto and Auwerx 2009; Fernandez‐Marcos and Auwerx 2011). Studies revealing SIRT1‐induced activation of PGC‐1α led to interest in nutraceutical and pharmacological activators of SIRT1. Resveratrol has been shown to increase SIRT1 activity in AMPK‐dependent and independent mechanisms (Lagouge et al. 2006). It has also been shown to activate PPARα and PPARγ, which are both inducers of MB (Calleri et al. 2014; Takizawa et al. 2015). It also induces MB in a SIRT1‐dependent manner in multiple cell types (Csiszar et  al. 2009; Menzies et  al. 2013; Wang et  al. 2014a). Activation of SIRTs using resveratrol has been shown to be beneficial in animal models of metabolic diseases, improving lipid profiles and antioxidant defenses in diabetic and obese patients (Csiszar et  al. 2009; Brasnyo et  al. 2011; Timmers et  al. 2011; Bhatt et  al. 2012). As previously mentioned, resveratrol has also been found to be neuroprotective against the aforementioned neurodegenerative disorders. In addition to resveratrol, other natural products can increase SIRT1‐ mediated MB and metabolic functions, such as the isoflavones daidzein and genistein found in soybeans; the flavonoids quercetin, epicatechin, and green tea polyphenols found in fruits and cocoa, respectively; and a variety of other foods (Rasbach and Schnellmann 2008; Rayamajhi et  al. 2013; Li et  al. 2016; Ramirez‐Sanchez et al. 2016). Interestingly, quercetin has been shown to increase mtDNA copy number and mitochondrial content in various brain regions of rats exposed to aluminum, a widely distributed element linked to several neurological diseases including AD, PD, and ALS, and known to induce oxidative stress and reduced MB (Sharma et al. 2013; Sharma et al. 2015). Furthermore, quercetin treatment also resulted in increased PGC‐1α expression in these rats, indicating enhanced MB (Sharma et  al. 2015). PGC‐1α activation using green tea  polyphenols rescued reductions in OXPHOS proteins and mtDNA content in a rat model of CsA‐ induced nephrotoxicity, consequently attenuating kidney injury and improving renal function. These data implicate natural products as a promising therapeutic strategy for toxicant‐induced mitochondrial suppression to promote tissue repair and regeneration (Rehman et al. 2014).

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Identification of natural SIRT1 activators encouraged the search for pharmacological inducers of SIRT1. As a result, a number of SIRT1 activators were developed, including SRT1720, SRT1460, and SRT2104. In models of type 2 diabetes, these compounds improve insulin, glucose, and fatty acid metabolism while also improving mitochondrial oxidative capacity (Milne et  al. 2007; Feige et  al. 2008; Libri et  al. 2012). SRT1720 demonstrated protective effects across a variety of disease states in mice, including renal ischemic injury and MI, through activation of SIRT1/PGC‐1α (Funk and Schnellmann 2013; Tong et  al. 2013). Furthermore, SRT1720 prevented the development of age‐related metabolic diseases in mice by increasing insulin sensitivity and fatty acid oxidation and reducing inflammation and oxidative stress, therefore increasing lifespan (Mitchell et al. 2014). These data suggest that the use of SIRT1 activators may enhance disease outcomes by improving mitochondrial function. See Table 39.2 for a summary of MB pathways mediated by sirtuin activators and natural products.

39.12

Conclusions

Given the critical role of mitochondrial dysfunction in the development of multiple acute and chronic diseases, new therapeutic strategies to target MB to augment mitochondrial content and oxidative metabolism are actively under investigation. Preclinical and human studies indicate that induction of MB via various pathways promotes functional recovery in a variety of disease states, including metabolic disorders, I/R injuries, neurodegenerative, and cardiovascular pathologies. Unfortunately, however, relatively few drugs have been identified for the induction of MB, and such drugs are often functionally promiscuous. Therefore, a significant amount of work is still required to improve the safety and efficacy of MB-based therapeutics for the treatment of acute and chronic diseases. Research on repurposing existing FDA‐approved drugs is becoming a popular strategy in drug development, in part because of the known safety profiles of these agents. Interestingly, several classes of  FDA‐approved drugs are inducers of MB, such as rosiglitazone, formoterol, and sildenafil, suggestive of the safety of MB. It is also important to consider the MB‐independent mechanisms of many of these drugs. For example, TZDs, estrogens, and SIRT1 activators can also stimulate off‐target transcriptional programs that have been demonstrated to cause detrimental effects, such as hyperproliferation. Therefore, selective induction of MB has the potential to avert these toxic side effects.

In addition to the acute and chronic diseases mentioned herein, augmented MB also has the potential to aid in drug‐induced mitochondrial toxicity. Several studies have investigated the effects of pharmacologically enhanced MB on mitochondrial toxicity in various organ systems, including the aforementioned rotenone‐ and lead‐induced neurotoxicity and aluminum‐induced oxidative stress. Interestingly, melatonin administration was found to reduce carbon tetrachloride‐induced hepatocellular damage (Doherty 2000) and oxidative stress in rats while increasing mtDNA content, the expression of various MB proteins, including PGC‐1α and TFAM and mitophagy‐ related proteins. Additionally, melatonin treatment increased AMPK phosphorylation in these animals, an upstream activator of PGC‐1α (Kang et  al. 2016). The environmental pollutant cadmium also induces hepatotoxicity via oxidative stress and mitochondrial dysfunction, including decreased SIRT1 activity, decreased deacetylation, and subsequent activation of PGC‐1α. Pretreatment with melatonin, however, was found to protect from these cadmium‐induced effects in  vitro, presumably via SIRT1‐dependent PGC‐1α activation and increased MB (Guo et  al. 2014). Although a great deal of work remains to be done, these recent studies indicate the potential for augmented MB and enhanced PGC‐1α as therapeutic interventions for a variety of pathologies converging on mitochondrial dysfunction and loss of mitochondrial homeostasis, including drug‐ induced mitochondrial toxicity. Pharmacological induction of MB also has the capacity to activate MB in off‐target organs, which may have harmful effects in the form of increased systemic oxidative stress and inflammation. Timing and duration of pharmacological intervention is also of importance when discussing the potential effectiveness of MB inducers. For example, MB prior to insult may be protective against mitochondrial dysfunction, but also presents the opportunity to propagate organ dysfunction due to increased mitochondrial content and ROS production. Furthermore, oxidative stress‐induced pathways, such as mtDNA damage, that occur immediately after insult (i.e., I/R injury) may impair the function of the newly generated mitochondria. Additionally, prolonged treatment with agents targeting receptors may result in receptor desensitization and/or activation of antagonistic pathways, both of which could hinder MB signaling. By optimizing dosing strategies, we will gain insight on maximizing the efficacy of MB induction. Well‐executed preclinical animal models investigating natural products and pharmacological inducers of MB will undoubtedly provide researchers and clinicians with valuable tools for  developing MB‐based strategies for therapeutic intervention of both acute and chronic diseases.

Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies

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Wu, Z., P. Puigserver, U. Andersson, C. Zhang, G. Adelmant, V. Mootha, A. Troy, S. Cinti, B. Lowell, R. C. Scarpulla and B. M. Spiegelman (1999). “Mechanisms controlling mitochondrial biogenesis and respiration through the thermogenic coactivator PGC‐1.” Cell 98(1): 115–124. Yan, M. H., X. Wang and X. Zhu (2013). “Mitochondrial defects and oxidative stress in Alzheimer disease and Parkinson disease.” Free Radic Biol Med 62: 90–101. Ye, L., J. Wu, P. Cohen, L. Kazak, M. J. Khandekar, M. P. Jedrychowski, X. Zeng, S. P. Gygi and B. M. Spiegelman (2013a). “Fat cells directly sense temperature to activate thermogenesis.” Proc Natl Acad Sci U S A 110(30): 12480–12485. Ye, Y., J. Qian, A. C. Castillo, S. Ling, H. Ye, J. R. Perez‐ Polo, M. Bajaj and Y. Birnbaum (2013b). “Phosphodiesterase‐3 inhibition augments the myocardial infarct size‐limiting effects of exenatide in mice with type 2 diabetes.” Am J Physiol Heart Circ Physiol 304(1): H131–H141. Yin, W., A. P. Signore, M. Iwai, G. Cao, Y. Gao and J. Chen (2008). “Rapidly increased neuronal mitochondrial biogenesis after hypoxic‐ischemic brain injury.” Stroke 39(11): 3057–3063. Zhang, L., M. Frederich, H. He and J. A. Balschi (2006). “Relationship between 5‐aminoimidazole‐4‐ carboxamide‐ribotide and AMP‐activated protein kinase activity in the perfused mouse heart.” Am J Physiol Heart Circ Physiol 290(3): H1235–H1243. Zolezzi, J. M., C. Silva‐Alvarez, D. Ordenes, J. A. Godoy, F. J. Carvajal, M. J. Santos and N. C. Inestrosa (2013). “Peroxisome proliferator‐activated receptor (PPAR) gamma and PPARalpha agonists modulate mitochondrial fusion‐fission dynamics: relevance to reactive oxygen species (ROS)‐related neurodegenerative disorders?” PLoS One 8(5): e64019. Zuo, L., Q. Li, B. Sun, Z. Xu and Z. Ge (2013). “Cilostazol promotes mitochondrial biogenesis in human umbilical vein endothelial cells through activating the expression of PGC‐1alpha.” Biochem Biophys Res Commun 433(1): 52–57.

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40 Mitochondrial Toxicity Induced by Chemotherapeutic Drugs Luciana L. Ferreira1,* , Ana Raquel Coelho1,2,* , Paulo J. Oliveira1, and Teresa Cunha‐Oliveira1 1 2

CNC—Center for Neuroscience and Cell Biology, University of Coimbra, UC Biotech, Biocant Park, Cantanhede, Portugal III‐Institute for Interdisciplinary Research, University of Coimbra, Coimbra, Portugal

CHAPTER MENU 40.1 40.2 40.3 40.4 40.5

40.1

Introduction, 593 Mitochondria and Cancer Chemotherapy, 593 Conventional Chemotherapeutic Agents and Mitochondria, 594 Mitoprotectants as Adjuvants in Chemotherapy, 603 Conclusion, 604 References, 605

Introduction

Cancer chemotherapy involves the use of drugs to treat cancer, usually as part of a multimodality therapy in combination with surgery and/or radiotherapy, with the final goal of achieving and maintaining cancer remission. This is often a long‐term process, requiring the use of one or more chemical agents given in repeated doses, and the characteristics of the treatment are highly dependent on the tumor type (Airley 2009). Remission implicates the complete eradication of the disease for at least 1 month, and the treatment is aimed at preventing recurrence both at the primary tumor site and at distant sites (metastasis) (Airley 2009). Ideally, chemotherapeutic agents should specifically kill cancer cells, with minimal collateral damage to normal cells. Thus, many forms of chemotherapy are focused on preventing cell division and inducing cell death by apoptosis, since cancer cells are more likely to be replicating during treatment than normal cells. However, cytotoxicity of chemotherapeutic drugs also affects normal cells, and anticancer treatments are

*These authors equally contributed.

associated with significant dose‐limiting side effects (Payne and Miles 2008). In  addition, cancer cells may develop resistance to chemotherapy, which is associated with the upregulation of antiapoptotic mechanisms, which leads to decreased susceptibility to cytotoxic drugs (Hassan et al. 2014). Although current chemotherapeutic agents are fairly successful in the treatment of cancer, patients often develop adverse effects that could force therapeutic alterations (Chu and Sartorelli 2015). Adverse effects can persist after cessation of chemotherapy for weeks, months, or even years, reducing long‐term quality of life of these patients (Vichaya et al. 2015).

40.2 Mitochondria and Cancer Chemotherapy Mitochondria play a central role in tumorigenesis (Tan et al. 2014; Tokarz and Blasiak 2014) and the use of drugs that target mitochondria provides an attractive anticancer approach (Fulda et al. 2010; Weinberg and Chandel 2015; Wen et al. 2013). Cancer cells often present higher levels of mitochondrial DNA (mtDNA) mutations and/or decreased mtDNA copy number, overproduction of

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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mitochondrial reactive oxygen species (ROS), increased mitochondrial transmembrane electric potential (ΔΨm), and aberrant apoptotic machinery (Chatterjee et al. 2011; van Gisbergen et al. 2015). When defective mitochondrial respiration in cancer cells is restored by mtDNA acquisition, tumor‐forming ability is regained (Berridge et  al. 2015; Tan et al. 2015). These mitochondrial characteristics of cancer cells may provide selective therapeutic targets to promote tumor cell death and decrease drug resistance. Drugs that act directly on mitochondria, causing bioenergetic changes have been called mitocans (Guzman‐Villanueva and Weissig 2016). These drugs can be naturally occurring, or chemically directed to cancer cell mitochondria through the conjugation of lipophilic cations or peptides with therapeutic compounds that target the antioxidant defenses and pro‐apoptotic proteins (Chen et al. 2010; Guzman‐Villanueva and Weissig 2016; Ralph et  al. 2006), and can be combined with conventional chemotherapeutic agents (Ralph et  al. 2006). Targeting the cancer cell powerhouses can take advantage of the higher ΔΨm in tumor cells and aims to limit the supply of cellular building blocks and mitochondrial substrates, inhibit oxidative phosphorylation (OXPHOS), increase mitochondrial oxidative stress, or target the mitochondrial transition pore (mPTP) and the aberrant apoptotic machinery (Deus et  al. 2014, 2015; Sandoval‐ Acuna et al. 2016). However, these drugs may not be so helpful against cancer stem cells, which were shown to be less reliant on mitochondria and are more difficult to kill with mitochondria‐directed therapies (Song et  al. 2017; Vega‐Naredo et al. 2014). Nevertheless, mitochondria of tumor‐initiating cells possess special characteristics, which may be used to create drugs that specifically target them (Yan et al. 2015, 2016). Mitochondria are also involved in some of the adverse effects of classic chemotherapeutic agents, which often disturb mitochondrial function in nontarget cells (Figure  40.1) (Wang et  al. 2010). Drug‐induced mitochondrial dysfunction can be caused by the parent drug itself or by reactive metabolites produced by cytochrome P450 in the liver (Chen et al. 2016; Pereira et al. 2012a; Shirakawa et al. 2015), and every year a number of drug candidates do not reach the market due to toxicity issues, which are later shown to be associated with mitochondria (Nadanaciva et al. 2007). Mitochondrial disruption induced by chemotherapeutic agents affects predominantly high metabolic demand tissues/organs, such as the skeletal (Gilliam et al. 2016; Sorensen et al. 2016) and cardiac muscles (Carvalho et  al. 2014; Monsuez et  al. 2010; Sampaio et  al. 2016), the liver (Ramadori and Cameron 2010), and the brain (Waseem et al. 2016; Xiao and Bennett 2012; Zheng et al. 2012). The circular structure of mtDNA allows an easier intercalation of chemotherapeutic agents that can lead to mitochondrial

dysfunction, since mtDNA has a higher rate of mutation and a more limited repair system compared with nuclear DNA (Figure 40.1a) (Scheede‐Bergdahl and Jagoe 2013; Sorensen et al. 2016; Tuppen et al. 2010). On the other hand, some agents show a strong affinity to cardiolipin, one of the most abundant phospholipids in the inner mitochondrial membrane (IMM) and essential for electron transport chain (ETC) enzymatic activities, increasing the propensity to mitochondria‐induced toxicity (Carvalho et al. 2014). Mitochondrial injury by chemotherapeutic agents can be caused by direct or indirect effects in this organelle, resulting in alterations of metabolic pathways and damage to mitochondrial components (Vichaya et  al. 2015). The mechanisms of mitochondrial disruption include uncoupling of ETC followed by decreased ATP production (Figure  40.1e), inhibition of OXPHOS complexes (Figure 40.1b), oxidative stress, opening of mPTP, depletion of mtDNA, inhibition of tricarboxylic acid cycle (TCA) or β‐oxidation (Figure 40.1g), and inhibition of membrane transporters (Begriche et al. 2011; Gogvadze et al. 2009). Increase in mitochondrial ROS was described as a main cause of chemotherapy‐induced mitochondrial dysfunction (Rovini et al. 2011). Some chemotherapeutic drugs can directly induce oxidative stress via interaction of their chemical structure with oxygen, while others can decrease antioxidant defenses (Figure 40.1c, d) (Gilliam and St Clair 2011). Inside mitochondria, mtDNA and the iron–sulfur centers of aconitase and of complexes I, II, and III of the ETC are the most susceptible structures to oxidative damage (Guo et al. 2013). Chemotherapy‐ associated mitochondrial dysfunction may also involve mitochondrial p53 accumulation and formation of drug‐mtDNA adducts, as a result of inflammatory and non-inflammatory‐based mechanisms, which leads to apoptosis (Figure  40.1h) (Vichaya et  al. 2015). In the next sections, we highlight the mitochondrial effects of some of the most well‐known classes of anticancer drugs.

40.3 Conventional Chemotherapeutic Agents and Mitochondria 40.3.1

Alkylating Agents

Alkylating agents (AAs) are among the most widely used anticancer drugs and were the first effective nonhormonal drugs used in chemotherapy. Although they were used as chemical weapons during the World War I, their chemotherapeutic effects were only discovered in the 1940s (Tahmasbpour et  al. 2015). Classes of AA comprise nitrogen mustards (e.g., mechlorethamine and cyclophosphamide), nitrosoureas, triazines, ethylenimides,

Mitochondrial Toxicity Induced by Chemotherapeutic Drugs

(a) mtDNA lesions causing disturbance in protein synthesis and defective respiratory chain elements I

III IV V

mtDNA

H+

H+

H+ cyt c

Q II

I

III

H+ + H+ H H+ H+ H+

+

IV

•O2–

Antiox ida enzym nt es

(d) Unbalanced ROS/antioxidant defenses (e) Depression in ATP production (f) Altered activity of redoxsensitive enzymes

∆ψm V

O2

(b) Disruption of mitochondrial oxidative phosphorylation (c) Overproduction of ROS

–

H+ ADP ATP + Pi

ROS

Pyruvate Acetyl-CoA (g) Decline of fatty acid β-oxidation and Krebs cycle efficiency Krebs cycle

Fatty acid β-oxidation

Acetyl-CoA

p Bcl2/Bax p53

Cytochrome c release Bax cluster

(h) Increased p53-mediated apoptosis (i) Bax upregulation

Apoptosis

Figure 40.1 Main mechanisms by which anticancer drugs affect mitochondrial related functions. Some of the consequences of chemotherapeutic treatments include a decrease in mtDNA content and quality, increased oxidative stress, which leads to the oxidation of mitochondrial membranes and other structures such as proteins from electron transport chain, resulting in electron leak and even more mtROS production, decreased ATP content, collapse of ΔΨ, decreased mitochondrial biogenesis, inhibition of essential metabolic cycles, cytochrome c release from intermembrane space, caspase activation, and apoptosis. ΔΨm, mitochondrial transmembrane electric potential; cyt c, cytochrome c; mtDNA, mitochondrial DNA; Q, coenzyme Q.

and platinum‐based compounds (e.g., oxaliplatin and cisplatin, Figure  40.2). These classes can further be grouped into two types: drugs that react directly with biological molecules and drugs that require a metabolic activation to form an intermediate, which in turn reacts with the biological molecules (Damia and D’Incalci 1998;

Sorensen et al. 2016). Cytotoxic AAs are widely used in chemotherapy of solid tumors, such as breast, ovarian, and lung cancer and leukemia and lymphoma malignancies (Taha et al. 2015). AAs mainly target DNA by attaching an alkyl group to the nucleic acid, reacting mainly with the N7 of guanine, although they can also alkylate

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Alkylating agents

Antitumor antibiotics O

OH

O

NH3

CI

OH

Pt

OH

NH3

CI

OH

OCH3 O

O

O

Cisplatin OH

Doxorubicin

Antimetabolites

O

NH2

H 2N

O

O

H2N

O

H N

N

CH3

H3C H3C O

O

N

N

N

O OH

N H

N

N

Taxanes

OH

O

NH2

NH

CH3 CH3

N

N

OH O

O

CH3

OH O

SH

O

Paclitaxel

6-mercaptopurine

Topoisomerase inhibitors

Proteasome inhibitors O

HO

H O H

HO

O H O

O

H N

N N H

O

B OH

O

N

OH

O O

OH

O

O H

O

Bortezomib

Etoposide

Estrogen receptor modulators

Tyrosine kinase inhibitors

CH3 CF3

O

CI

H H

O

Methotrexate

OH

O

O

N H

O N CH3

CH3

N N H

N H

Sorafenib

Tamoxifen

Figure 40.2 Molecular structures of elements from the different classes of anticancer drugs focused on this chapter.

other DNA positions, including O6 and N1 of guanine; N7, N3, and N1 of adenine; N3 of cytosine; and O4 of thymine (Damia and D’Incalci 1998). Thus, AAs can induce double‐strand breaks that block DNA replication

and transcription and trigger DNA repair mechanisms. If repair is not efficient, apoptosis or other cell death pathways can be activated (Mourtada et al. 2013). AAs also form adducts with RNA, lipids, and proteins, as well

Mitochondrial Toxicity Induced by Chemotherapeutic Drugs

as increase ROS, and all these interactions lead to inhibition of nucleic acid and protein syntheses and disruption of energy metabolism, ultimately triggering cell death (Tahmasbpour et  al. 2015; Zanotto‐Filho et  al. 2016). However, the cytotoxic effects of AAs are mostly due to the reactions with DNA, and since most of the major AAs are bifunctional, having two reactive groups, they can react with both strands of the DNA molecule by simultaneously alkylating two groups, leading to DNA crosslinkings (Kufe et al. 2003). The antitumor properties of AAs affect mainly the proliferative cancer cells, as these cells are more susceptible to DNA damage, although they may also present cytotoxic effects in normal cells that proliferate quickly, including in bone marrow, gastrointestinal tract, and testicles. Thus, despite the promising efficiency of these compounds, the side effects limit their clinical usage (Kufe et al. 2003; Waissbluth et al. 2017). Mitochondria seem to be a key player in the deleterious consequences of these compounds in somatic cells (Druzhyna et  al. 2008). Dysregulation of mitochondrial energy homeostasis through mutations in mtDNA or in nuclear‐ encoded mitochondrial proteins lead to negative side effects (Gilliam et al. 2016). It is also extensively described that AAs increase oxidative stress and reduce antioxidant defenses in different types of cells (Gilliam et  al. 2016; Kufe et  al. 2003; Taha et  al. 2015; Tahmasbpour et al. 2015; Zanotto‐Filho et al. 2016). The most prevalent forms of toxicity induced by AAs are nephrotoxicity, neurotoxicity, and ototoxicity, but the most severe toxic consequence during treatment with AAs occurs in the renal system and is usually the dose‐limiting side effect (Rybak et  al. 2009; Taha et  al. 2015). AAs and their 4‐ hydroxy metabolites are excreted by the urinary tract where they may interact with local cells, react with DNA, and increase ROS (Taha et  al. 2015). Oxidative stress heavily affects bladder cell mitochondria, leading to degeneration of this organelle due to swelling, membrane rupture, and destruction of cristae, resulting in permeabilization of the bladder epithelium membrane and consequent inflammation, which ultimately ends in necrosis (Taha et al. 2015). In skeletal muscle, the adverse effects of AA chemotherapy include muscle atrophy and dysfunction, insulin resistance, weakness, and fatigue, which strongly reduce the quality of life and increase the mortality of the patients (Sorensen et  al. 2016). It has been shown in the C2C12 myotube cell line that oxaliplatin‐induced reversible inhibition of key respiratory enzymes and interacted with complex IV, dysregulating electron flow through ETC (Sorensen et al. 2016). This dysfunction of electron transference increased the production of superoxide anion and peroxynitrite, leading to augmented toxicity (Tahmasbpour et  al. 2015). The chronic side effects of the AA treatment are also related

to mitochondrial dysfunction and increased mitochondrial ROS production, due to nDNA and mtDNA mutations (Sorensen et al. 2016). Once increased ROS levels are the main cause of toxicity, a conjugation of antioxidants and chemotherapy seems to be a good strategy to overcome the side effects (Bhattacharya et al. 2001; Taha et al. 2015). 40.3.2

Antitumor Antibiotics

Antitumor antibiotics are another class of agents used in chemotherapy. These chemotherapeutic drugs affect the enzymes involved in DNA replication and transcription and can interfere with all phases of cell cycle (Sorensen et al. 2016). Among this class of drugs, anthracyclines are the most used in chemotherapy. Anthracyclines were first identified in the 1950s in the soil bacterium Streptomyces peucetius. This antibiotic family is composed of four main anthracyclines: doxorubicin (DOX, also known as adriamycin), daunorubicin, epirubicin, and idarubicin, with DOX being the most effective in cancer therapy (Simůnek et al. 2009; Volkova and Russell 2011). Concerning the chemical structure, these agents have a rigid planar tetracyclic ring with quinone moieties and an amino sugar attached to the tetracyclic ring (Figure 40.2). These molecules are highly effective anti­ neoplastic agents and are extensively used to treat numerous types of adult and pediatric cancers (Menna et al. 2007; Smith et al. 2010; Volkova and Russell 2011), although their antineoplastic mechanism still raises con­ troversy. Initially, the mechanism responsible for anti­ cancer effects was attributed to intercalation of the planar ring into the DNA helix, which unwinds nucleic acids and causes a stereochemical disorder, blocking transcription and replication, and preventing the rapid growth of cancer cells (Branco et al. 2012). Anthracyclines also bind to mtDNA and to proteins involved in DNA replication and transcription, and these bonds lead to inhibition of DNA, RNA, and protein syntheses, leading to cell death (Sardão et  al. 2009a; Yang et  al. 2014). Nowadays, topoisomerase II is recognized as a main cel­ lular target of these class of drugs, which acts by stabiliz­ ing the enzymatic reaction when the cut DNA strands are covalently linked to the enzyme, blocking subsequent DNA resealing, and inducing cell death (Pommier et al. 2010). Increased production of ROS in the presence of anthracyclines was also described as another antineo­ plastic mechanism (Kratz et al. 2006; Nitiss 2009). The success of the treatment with anthracyclines is hampered by the dose‐related side effects, such as hematopoietic suppression, vomiting, extravasation, impaired muscle function, and gastrointestinal disorders (Gouspillou et  al. 2015; Kratz et  al. 2006; Pereira et  al. 2011). Although several organs are affected, the heart

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seems to be the main target, with several forms of cardiotoxicity described, including acute (pericarditis and arrhythmias), early (left ventricular systolic dysfunction), or late onset (chronic cardiomyopathy and congestive heart failure) (Pereira et  al. 2012a; Sardão et  al. 2009a; Zhang et al. 2009). In a subchronic DOX toxicity model, Pereira et  al. (2012b) demonstrated that cardiac mitochondria were more affected than their liver or kidney counterparts, suffering more alterations including decreased mitochondrial oxygen consumption and ΔΨm, which was also demonstrated by Serrano et  al. (1999), using low doses of DOX injected weekly. DOX‐induced cardiotoxicity has a strong mitochondrial component and oxidative stress on cardiac cells has been implicated as a major player (Sardão et al. 2009b; Zhang et al. 2011) (Figure 40.3). DOX structure contains a quinone moiety that interacts with cellular dehydrogenases, mainly NADH dehydrogenase (complex I) of the ETC, being reduced to an unstable semiquinone that can then react with oxygen and generate ROS (Vejpongsa and Yeh 2014; Volkova and Russell 2011). Since mtDNA is more susceptible to oxidative stress than nDNA, it has been reported to be damaged by DOX‐induced ROS, or directly by DOX, leading to ETC failure and further increasing ROS production (Palmeira et al. 1997; Sardão et al. 2009a). In addition, DOX administration increases endothelial nitric oxide synthase (NOS) and inducible NOS activities, resulting in unbalanced production of NO and consequent harmful effects, while DOX can also be metabolized by NOS, leading to further production of superoxide anion (Garner et  al. 1999; Vasquez‐Vivar et  al. 1997). This increase in NO levels, in cardiomyocytes, could result due to a dysregulation of iron homeostasis by DOX (Aldieri et  al. 2002). The formation of DOX–iron complexes also favors hydroxyl radical generation through the Fenton reaction, acting by recycling ferric anion. However, it is thought that there is not enough free iron to complex with DOX and cause cardiomyopathy by itself (Octavia et al. 2012). The resulting oxidative stress damages different mitochondrial structures, through protein and lipid peroxidation, oxidation of mtDNA, and induction of mPTP (Sardão et al. 2009a). Moreover, DOX can undergo a two‐electron reduction, being converted into doxorubicinol, which is more potent in dysregulating calcium and iron homeostasis (Menna et al. 2008; Minotti et al. 1998). Calcium plays an essential role in muscle contraction and in the regulation of important mitochondrial enzymes, such as pyruvate dehydrogenase and ATP synthase (Zhao et  al. 2014). Interplay between oxidative stress and alterations in calcium homeostasis after DOX treatment may also play a role, since increased ROS levels stimulate calcium release from the sarcoplasmic reticulum (SR), which is located closely to mitochondria, leading to an accumula-

tion of calcium in mitochondria, with a further increase in mitochondrial ROS (Lebrecht et  al. 2010; Octavia et  al. 2012). The combination of calcium dysregulation and oxidative stress may trigger the opening of the mPTP, increasing the permeability of the IMM and disrupting the energy‐generating processes (Carvalho et  al. 2014; Octavia et al. 2012; Solem et al. 1996; Zhang et al. 2009; Zhou et al. 2001). In this context, the cardiac bioenergetics may be disturbed in different ways, through the oxidation of mtDNA and proteins, formation of complexes between DOX and cardiolipin, or direct interaction of DOX with ETC complexes (Lagoa et al. 2014; Zhao et al. 2014). In fact, a significant increase in extracellular acidification and lactate production, a by‐product of glycolysis, and the decrease in OXPHOS suggest a shift to glycolysis after DOX treatment (Carvalho et  al. 2010). Altogether, these processes caused by DOX treatment create a bioenergetic crisis in cardiomyocytes that could trigger cell death signaling, leading to autophagy, apoptosis, or necrosis (Octavia et al. 2012). Pro‐apoptotic factors such as Bax (Figure 40.1h) and Bak can be directed to mitochondria after DOX treatment, leading to disruption of mitochondrial membrane permeability, allowing the release of several apoptotic initiators, including AIF and cytochrome c (Pereira et  al. 2011; Volkova and Russell 2011), which lead to the activation of caspases‐9 (Sardão et al. 2009a) and ‐3 (Octavia et al. 2012). DOX‐ induced cardiomyocyte apoptosis has been shown to be associated with increased expression and activation of the p53 tumor suppressor protein, leading to transcriptional activation of pro‐apoptotic Bcl‐2 proteins (Sardão et al. 2009a). DOX treatment also induces p53 translocation to mitochondrial membranes, leading to mitochondrial dysfunction and cell apoptosis (Sardão et al. 2009a). Using a chemical inhibitor of p53, pifithrin‐α, a blockage of apoptosis via the inhibition of p53 downstream activity was observed (Sardão et al. 2009a), affecting Bax and MDM2 expression, which were increased by DOX treatment (Liu et  al. 2004). However, p53‐independent cell death may also occur through DOX‐induced oxidative stress, also involving cytochrome c release and caspase‐3 activation (Tsang et al. 2003). 40.3.3

Antimetabolites

Antimetabolites are a class of chemotherapeutic drugs that, because of their similarity to endogenous molecules, block nucleic acid synthesis by limiting deoxyribonucleoside triphosphate availability, target enzymes involved in de novo biosynthesis of purines and pyrimidines, and/or get misincorporated into nucleic acids (Grem and Keith 2005). These drugs interfere with DNA and RNA syntheses and are cell cycle specific, being active during G1 and S phases (Payne and Miles 2008).

Mitochondrial Toxicity Induced by Chemotherapeutic Drugs

O

O

OH

OH

NAD(P)+

CH2OH O2

OCH3 1e–

O

O

OH O

H3C

•OH H2O2

1e–

HO NH2 O–

NAD(P)H + H+

OH

O –

OH • OCH3 O

•O2

CH2OH

O

OH O

H3C

HO NH2

H+

H+

H+

H+ H+

ATP

H AD

N

Succinate

DOX ADP O2

Krebs cycle Fatty acid β-oxidation

ROS

Acetyl-CoA TOP2

H+

DOX

H+ ADP ATP

DOX ROS H+ H+ H+

ROS mPTP Bax cluster Cytochrome c

AIF

Apoptosis

Figure 40.3 Overview of molecular reactions and mitochondrial alterations associated with development of doxorubicin cardiotoxicity. DOX accepts electrons from NAD(P)H‐dependent flavoproteins generating a semiquinone form. Molecular oxygen can accept the electron from this semiquinone, forming superoxide anions. Subsequent mechanisms based on free iron and antioxidant enzymes may induce the generation of other ROS (H2O2 and •OH). AIF, apoptosis inducing factor; DOX•, doxorubicin semiquinone radical; mPTP, mitochondrial permeability transition pore; ROS, reactive oxygen species; TOP2, topoisomerase II.

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Antimetabolites are classified based on the molecules with which they interfere, such as pyrimidine antagonists (5‐fluorouracil‐ 5‐FU), purine antagonists (6‐mercaptopurine, Figure  40.2), and folic acid antagonists (methotrexate, Figure  40.2) (Payne and Miles 2008). Once these drugs are converted into analogues of cellular nucleotides, they cause DNA damage and consequent apoptosis (Hwang et al. 2015; Olaussen and Postel‐Vinay 2016; Parker 2009; Sorensen et al. 2016). Antimetabolite molecules are commonly used in the treatment of leukemia and breast, ovary, and gastrointestinal tract cancers (Sorensen et al. 2016). 5‐FU, one of the most commonly used antimetabolites, and its prodrug capecitabine cause severe toxic effects in about 15–30% of the patients, including diarrhea, mucositis, and neurotoxicity, which could result from decreased dihydropyrimidine dehydrogenase activity (Lunenburg et  al. 2016). However, the decreased activity or content of this enzyme just partly explains the side effects of 5‐FU, and cardiotoxicity seems to be independent of it (Lischke et al. 2015). One of the metabolites produced by 5‐FU catabolism is fluoroacetate, which inhibits the enzyme aconitase from the TCA cycle, impairing mitochondrial energy metabolism, inducing ATP depletion, and leading to cardiotoxicity (Lischke et al. 2015). This drug is also associated with myocardial ischemia, once it reduces endothelial NO synthase leading to coronary artery vasospasm, and also induces endothelium‐independent vasoconstriction via protein kinase C (Cameron et al. 2016). The use of methotrexate is also limited by off‐target toxicity, including intestinal toxicity, cardiotoxicity, nephrotoxicity, and hepatotoxicity, which are probably caused by increased ROS accumulation and consequently with lipid and protein peroxidation (Gautam et al. 2016). Treatment with azathioprine, which belongs to the purine analogues, being a prodrug for mercaptopurine, leads to hepatotoxicity due to ATP depletion and to a decrease in reduced glutathione, mainly in mitochondria, leading to cell death (Tapner et al. 2004). 40.3.4 Taxanes Taxanes are a class of diterpenes used as chemotherapeutic drugs. One of these drugs is paclitaxel (Figure  40.2), which is used in the treatment of several types of solid tumors such as breast, ovarian, and lung cancer, exerting its antineoplastic effects on microtubules during the cell cycle (Mukhtar et  al. 2014). Paclitaxel binds to β‐ tubulin in microtubules, stabilizing the microtubule lattice and suppressing depolymerization, leading to mitotic arrest during the G2/M phase of the cell cycle (Gornstein and Schwarz 2014). Thus, paclitaxel is highly effective against proliferating cancer cells. Despite the

promising antineoplastic action, paclitaxel properties turn it toxic to healthy tissues as well, most prominently to the peripheral nervous system. Even though neurons are not proliferative cells, they are also affected. The sensory symptoms in the peripheral nervous system initiate in the distal extremities and include sensory loss, temperature hypersensitivity, paresthesia, and neuropathic pain syndrome (Gornstein and Schwarz 2014). Persistent painful chemoneuropathy was reported to last months to years after cessation of paclitaxel treatment (Boyette‐ Davis et  al. 2013). The effects on the microtubules are generally considered responsible for paclitaxel‐induced neurotoxicity, but other off‐targets should not be discarded because microtubule dynamic instability, despite being mostly accepted as responsible for the toxicity in microtubule‐rich axons, has not been definitively demonstrated (Gornstein and Schwarz 2014). In a rat model of paclitaxel‐induced painful peripheral neuropathy, atypical (swollen and vacuolated) mitochondria were observed in C‐fibers and myelinated axons and these morphological alterations were suggested to result from the opening of the mPTP and consequent mitochondrial swelling (Flatters and Bennett 2006). On the other hand, the mPTP is associated with calcium movement (Jaggi and Singh 2012), and the mitochondria play a key role in intracellular calcium homeostasis. Impaired mitochondrial calcium uptake or increased leakage of mitochondrial calcium may be responsible for the increase in calcium‐mediated neuronal excitability (Gleichmann and Mattson 2011). Rapid calcium release from mitochondria was observed after paclitaxel treatment in pancreatic acinar cells (Kidd et al. 2002), and calcium chelating agents significantly improve neuropathic pain in a rat model of paclitaxel‐induced pain (Siau and Bennett 2006). In another study, paclitaxel was shown to induce cytochrome c release from mitochondria isolated from human neuroblastoma cells, which was prevented by cyclosporine A, a drug that binds to cyclophilin D and leads to desensitization of the mPTP (Andre et  al. 2000). As mitochondria are a major source of ROS, pharmacological approaches aimed to decrease ROS levels were investigated as preventive measures for neuropathy (Fidanboylu et al. 2011). The global inhibition of ROS using the nonspecific ROS scavenger phenyl N‐tert‐butylnitrone (PBN) has been shown to improve paclitaxel‐induced hypersensitivity and pain behaviors (Fidanboylu et al. 2011; Kim et al. 2010). Furthermore, since hepatic metabolism plays a pivotal role in the elimination of paclitaxel, its administration in patients with liver impairment should be handled with care (King and Perry 2001). In isolated liver mitochondria, paclitaxel caused the dissipation of ΔΨm and induced ROS formation, in a concentration‐dependent manner, and the release of cytochrome c from the intermembrane space (Varbiro et al. 2001).

Mitochondrial Toxicity Induced by Chemotherapeutic Drugs

40.3.5 Topoisomerase Inhibitors Topoisomerase enzymes play an essential role in the high‐order structuring of DNA, locally unwinding DNA duplex whose fixed ends cause stress by DNA supercoiling (Chen et al. 2013). Topoisomerases are divided into classes I and II, depending on whether one strand is cleaved and the opposing strand passes through it, or the DNA passes through a double‐strand gap generated by the enzyme in the duplex DNA, respectively (Champoux 2001). Etoposide (Figure 40.2) is a class II topoisomerase (TOP2) inhibitor. It increases the levels of TOP2:DNA covalent complexes, introducing high levels of transient protein‐associated breaks in the DNA (Nitiss 2009). Etoposide has been used to treat a wide variety of cancers, including lung, germ‐cell malignancies, leukemias, lymphomas, and neuroblastomas (Belani et  al. 1994). However, toxic side effects are associated with this treatment and include bone marrow suppression, nausea, vomiting, alopecia, and, at higher concentrations, mucositis and liver toxicity (Johnson et al. 1983). In rat liver mitochondria, etoposide was shown to increase mitochondrial sensitivity to calcium‐induced swelling, depolarization of ΔΨm, and calcium release from mitochondria (Custodio et  al. 2001). According to the authors, etoposide increased mitochondrial sensitivity to calcium‐dependent induction of mPTP. In agreement, cyclosporine A was shown to inhibit or revert these effects (Custodio et al. 2001) and avoided the release of cytochrome c from mitochondrial intermembrane space into the cytosol, reducing the loss of cell viability (Karpinich et al. 2002).

40.3.6 Targeted Therapy 40.3.6.1

Proteasome Inhibitors

Bortezomib (BTZ, Figure 40.2) is an antineoplastic drug, firstly described as an inflammation inhibitor, but whose cytotoxic action rapidly changed its main application to cancer therapy (Goldberg 2011). BTZ belongs to the protease inhibitor class of chemotherapeutic agents since its reversible binding to 26S proteasome subunit leads to the inhibition of protein degradation and, consequently, to increased apoptosis (Chen et al. 2011). Approved in 2003 to be used primarily in myeloma treatment, BTZ was also investigated in the treatment of solid tumors, but the low efficiency and lack of improvement in patient responses encouraged the development of novel proteasome inhibitors (Chen et al. 2011). Despite being relatively well tolerated both when used as single agent and in combination with other drugs, its use is limited by peripheral neurotoxicity. Particularly in the case of chemotherapy‐related neurotoxicity, BTZ is associated to severe dose‐limiting peripheral neuropathy, characterized by sensory loss,

paresthesias, dysesthesias, and numbness, as well as reduced tendon reflexes and autonomic innervation in the skin (Argyriou et al. 2008; Carozzi et al. 2015; Cavaletti and Nobile‐Orazio 2007). Mitochondrial damage has been suggested as an important key factor on BTZ‐ induced side effects. In rats, BTZ‐induced painful peripheral neuropathy was associated with long‐lasting dysfunction in axonal mitochondria, which presented deficient complex I‐ and complex II‐mediated respiration, as well as decreased ATP production (Zheng et al. 2012). Mitochondrial dysfunction in cancer cell lines also seems to be determinant for BTZ cytotoxic action, involving not only ROS generation (Du et  al. 2009) but also dysregulation of calcium influx (Landowski et al. 2005). 40.3.6.2

Monoclonal Antibodies

Trastuzumab is a humanized monoclonal antibody directed against the extracellular domain of human epidermal growth factor receptor 2 (HER2) and is mainly used in the treatment of women with HER2‐positive breast cancers (Slamon et  al. 2001). The HER2 gene is overexpressed in 25–30% of breast cancers and the abnormal high levels of the encoded protein increase the aggressiveness of the tumor (Slamon et  al. 1987). Trastuzumab has been used as single agent or in combination with standard chemotherapy regimens, such as anthracyclines, and while this last class is suggested to induce irreversible cardiotoxicity, at least if lately diagnosed, trastuzumab‐induced cardiac changes are usually reversible (Florescu et  al. 2013). A number of mechanisms are proposed to be behind trastuzumab‐induced cancer cell death, such as interference with the HER2 dimerization required in signal transduction, induction of antibody‐dependent immune cell‐mediated cytotoxicity (Arnould et al. 2006), or enhanced activity of the cell cycle inhibitor p27, inducing G1 cell cycle arrest and tumor growth inhibition (Le et  al. 2003). Despite the improvement provided by trastuzumab treatment in the survival rate and cancer recurrence, multiple cardiotoxic events were reported. In a follow‐up study (median 32.6 months) conducted by Guarneri et  al., 28% of patients experienced cardiac adverse events (Guarneri et  al. 2006). The high incidence of cardiac dysfunction was not surprising because of the significant percentage of patients with a previous history of cardiac disease or prior exposure to anthracyclines (Guarneri et al. 2006). Similar results were previously obtained when trastuzumab was used in combination with both anthracyclines and cyclophosphamide (cardiotoxicity in up to 27% of the patients), but the percentage decreased in patients receiving trastuzumab alone (about 7%) (Riccio et  al. 2016; Slamon et  al. 2001). Trastuzumab‐induced cardiotoxicity is not totally understood in terms of molecular mechanisms, and the clinical management

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currently relies on echocardiography to identify risk situations based on the reduction left ventricular ejection fraction (LVEF) (Florescu et  al. 2013). However, some studies started to mechanistically highlight the toxic action of trastuzumab. HER2 belongs to epidermal growth factor (EGF) receptor family and is known to heterodimerize with other HER receptors, including HER4, upon the binding of ligands called neuregulins, which results in a series of auto‐ and trans‐phosphorylations in the receptors, determining the elicited downstream signaling cascade (Wieduwilt and Moasser 2008). HER2‐ related signaling is required for a normal embryonic development and plays an important role in cardiac myocyte functioning. The HER2/HER4 heterodimerization has been postulated to be essential for cardiomyocyte function due to its role on the stimulation of survival signals upon stress and/or pressure overload (Albini et  al. 2011). In mice, HER2 (also known as ErbB2) mutants exhibited multiple parameters of cardiomyopathy, including chamber dilation, wall thinning, and decreased contractility (Negro et al. 2004). HER2/ErbB2 overexpression has also been correlated with increased Bcl‐xL/Bcl‐xS ratio in the heart, which are antiapoptotic and pro‐apoptotic proteins, respectively (Sysa‐Shah et al. 2012). Trastuzumab‐mediated inhibition of HER2/ ErbB2 was associated with alterations of Bcl‐xL/Bcl‐xS balance, increased mitochondrial Bax oligomerization, reduction of the ΔΨm and ATP depletion (Grazette et al. 2004), which may impair cardiomyocyte contractile function. ElZarrad et al. found that in mice heart, trastuzumab exerted an inhibitory effect on the expression of several genes related with cardiac contractibility, adaptation to stress, proliferation, wound healing, and mitochondrial function, with significantly less mitochondria found in the cardiomyocytes of the treated animals, which lacked the close contact organization predominantly observed in cardiomyocytes of the control group (ElZarrad et  al. 2013). 3‐Nitrotyrosine and 4‐hydroxynonenal‐protein adducts were also elevated in hearts of trastuzumab‐treated animals, accompanied by increased caspase 3/7 activity, indicating the presence of oxidative stress and activation of apoptotic pathways, which were hypothesized to be the causes of the ultrastructural damages observed (ElZarrad et al. 2013). 40.3.6.3 Tyrosine Kinase Inhibitors

Sorafenib (Figure 40.2), a tyrosine kinase inhibitor (TKI), is used in the treatment of patients with unresectable hepatocellular carcinoma and advanced renal cell carcinoma and is usually better tolerated than most conventional chemotherapeutic drugs, with promising results observed in radioactive iodine refractory‐differentiated thyroid cancer (Brose et  al. 2014b). Sorafenib mainly inhibits vascular endothelial growth factor (VEGF) receptors‐1,‐2,‐3, Raf kinases, RET (including RET/PTC), and

platelet‐derived growth factor receptor β, thus acting toward the inhibition of angiogenesis and tumor cell proliferation (Wilhelm et al. 2006). Both VEGF and Raf pathways regulate diverse signaling cascades involved in different physiological processes and are critical to the homeostasis of many organs (Chen and Cleck 2009; Leicht et al. 2007). Thus, the blockage of these signaling pathways, apart from being responsible for the efficiency of the treatment, also leads to the toxic phenotype. Treatment interruptions and dose reductions are often recommended to manage the adverse effects associated with the treatment (Brose et al. 2014a). Some of the most common side effects are hand– foot skin reaction, rash, gastrointestinal distress, hypertension, and, although not so common, cardiovascular events, such as myocardial ischemia and congestive heart failure (Brose et  al. 2014a; Li et  al. 2015). VEGF/VEGF receptor signaling is essential in processes such as angiogenesis, vasodilation and maintenance of an antithrombotic state, and antiangiogenic therapies affect VEGF‐related events including hypertension, wound healing, proteinuria, and arterial thromboembolic events (Chen and Cleck 2009). The cardiomyopathy associated with sorafenib treatment was hypothesized to rely on myocardial mitochondrial degeneration since at concentrations above 10 μM, sorafenib depleted ATP in a cardiomyoblast cell line (Will et al. 2008). In the same work but using isolated rat heart mitochondria, sorafenib was the most potent inhibitor of OXPHOS complexes activities at clinically relevant concentrations, among several TKI drugs (Will et  al. 2008). Structural and functional changes induced by sorafenib were also analyzed using in vivo and in vitro cardiac models (French et al. 2010). Functional changes were milder than expected, with sorafenib inducing a slight but significant decrease in ATP levels and showing no effect on ΔΨm, although disrupted mitochondrial cristae were also found in sorafenib‐treated rats (French et al. 2010). However, sunitinib, another TKI, promoted mitochondrial swelling, accumulation of dense deposits, matrix cavitation, and decrease in ΔΨm in the same model in a dose‐dependent manner (French et  al. 2010). The exact mechanism of TKI‐induced cardiotoxicity is unknown but could be related to inhibition of other kinases implicated in the regulation of mitochondrial function (French et al. 2010). 40.3.7

Estrogen Receptor Modulators

Tamoxifen (TAM, Figure 40.2) is an estrogen suppressor used in hormonal therapy in patients with estrogen receptor (ER) positive cancers, including breast cancer (Yang et  al. 2013). ER‐positive cancers are classified as  such because of their responsiveness to estrogen that  induces the proliferation of tumor cells and the progression of the disease (Yang et al. 2013). Estrogen is essential in female physiology, binding to ER‐α and ER‐β in their ligand‐binding domains and inducing ER

Mitochondrial Toxicity Induced by Chemotherapeutic Drugs

association with some DNA sequences called estrogen response elements. This interaction leads to the recruitment of coactivators that catalyze the transcription of estrogen responsive genes important not only in physiological responses but also in the proliferation of breast cancer cells (Nilsson et al. 2001). TAM has the capacity to bind to ERs, disrupting the function of one of their domains, which compromises the normal estrogen‐ mediated gene expression and triggers genomic effects such as cytostasis (Johnston et  al. 1995). In addition, there is evidence that TAM exerts its apoptotic properties through nongenomic mechanisms as well, even in ER negative cells (Jordan 2015). It is important to refer that, despite the success as a chemotherapeutic agent, TAM treatment is associated with an increased incidence of vaginal bleeding, ovarian cysts, endometrial thickening, decreased bone mineral density in premenopausal women, and, as a major concern, liver injury (Baum 2002; Ribeiro et  al. 2014). Furthermore, long‐ term use of TAM may also induce secondary endometrial cancer in women, being considered a class I human carcinogen (Fisher et  al. 1994). TAM works, as many other chemotherapeutic drugs, by inducing mitochondria‐mediated apoptosis (Nazarewicz et  al. 2007). The amine group of TAM can be protonated at physiological pH, followed by its translocation across the inner membrane into the mitochondrial matrix. The matrix alkaline environment favors the dissociation of the protons, leading to loss of ΔΨm and impaired respiration (Cardoso et  al. 2001). Furthermore, TAM promotes oxidative stress and apoptosis through mitochondria‐dependent and nitric oxide (NO)‐dependent pathways, by increasing NOS activity (Nazarewicz et al. 2007). It was previously described that mitochondria possess an NOS isoform that generates NO in response to increased intramitochondrial calcium concentration (Navarro and Boveris 2008; Valdez and Boveris 2007; Valdez et al. 2006). The formed NO not only controls mitochondrial bioenergetics via reversible regulation of cytochrome oxidase (complex IV) activity but also contributes to generate reactive nitrogen species (RNS), including peroxynitrite (Brown and Borutaite 2007). TAM increases calcium levels in mitochondria, stimulates mtNOS activity, and, at therapeutic concentrations, decreases oxygen consumption (Nazarewicz et al. 2007). Through mtNOS stimulation, lipid peroxidation is also increased, which inevitably destabilizes the supramolecular structure and fluidity of membranes, resulting in cytochrome c release from liver mitochondria (Nazarewicz et  al. 2007; Tabassum et  al. 2007). Other studies also showed TAM‐related toxic effects in mitochondria, including increased levels of superoxide radicals and decreased Mn‐SOD activity (Tabassum et al. 2007), collapse of ΔΨm, and ETC inhibition (Tuquet et al. 2000), as reviewed elsewhere (Ribeiro et  al. 2014; Yang et  al. 2013). Furthermore, TAM

decreased mtDNA synthesis in hepatic cells decreasing mtDNA copy number, which sensitized mitochondria to drug‐induced effects due to a decrease in the synthesis of mtDNA‐encoded respiratory chain subunits (Larosche et  al. 2007). Moreover, β‐oxidation was inhibited by TAM, presumably through the inhibition of carnitine palmitoyltransferase I (CPT1), which partly controls β‐ oxidation of long‐chain fatty acids by regulating their entry into mitochondria (Larosche et al. 2007).

40.4 Mitoprotectants as Adjuvants in Chemotherapy It is clear by now that chemotherapy is associated with toxic side effects of varying severity. This not only compromises the efficiency of the treatment, forcing the use of lower doses of drug or decreasing the number of cycles of chemotherapeutic regimen, but also entails a considerable cost in later treatments (Menna et al. 2008). Mitochondria are an important key target in toxic mechanisms, and thus many pharmacological strategies have been studied aiming to prevent those deleterious effects by protecting mitochondria. Excess ROS/RNS production is a result of the action of several chemotherapeutic agents, and oxidative stress has been established as one of the primary causes of mitochondrial dysfunction (Sinha et  al. 2013). Consequently, cellular structures such as membrane lipids, proteins, and nuclear and mtDNA suffer oxidation and are damaged. The excessive oxidative damage that exceeds the cellular repair capacity results in disease and abnormal functioning of the biological systems (Turrens 2003). Membrane lipid peroxidation, for instance, affects membrane fluidity, permeability, and electron transport function in mitochondria (Radi et al. 1994). Highly associated with cancer therapy, fatigue was reported in more than 75% of cancer patients during the course of their disease and treatment (Vogelzang et  al. 1997). Although underestimated, fatigue was also considered as one of the most distressing complaints among cancer patients and is often a reason why many patients discontinue the treatment (Liu et  al. 2005). Among several factors including psychological conditions, sociocultural, and physiological factors, fatigue is also related with deficient energy supply and reduced efficiency of mitochondria (Ciregia et  al. 2016; Gorman et  al. 2015). Lipid replacement therapy (LRT) combined with antioxidants is a strategy that has been used in the treatment of certain clinical disorders, including chronic fatigue (Nicolson and Ellithorpe 2006). The treatment consists in providing high concentrations of undamaged lipids that will later replace the damaged membrane lipids and restore, or at least improve, the function of cellular structures (Nicolson 2005; Nicolson and Conklin 2008). The therapy is usually supplemented

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with antioxidants to protect lipids from oxidation and ensure a safer delivery. A successful dietary supplement based on this principle is NTFactor®, which contains encapsulated components, including phospholipids, glycophospholipids, and other types of lipids, that easily escape from the oxidation in the gut and reach the tissues without undue damage (Nicolson and Conklin 2008). Episodes of chemotherapy‐induced fatigue, nausea, diarrhea, and other effects were reduced in patients with colon, rectal, and pancreatic cancers and an improvement in quality of life was reported, after the oral LRT (Colodny et al. 2000). Considering the link between toxicity and oxidative stress, many antioxidants have been tested in vitro and in vivo. In sensory neurons in culture, alpha‐lipoic acid that is essential in cell energy metabolism, antioxidant regulation, and calcium homeostasis showed to be neuroprotective against cisplatin and paclitaxel‐induced peripheral neuropathy (Melli et al. 2008). Other antioxidants such as vitamin A, vitamin E, N‐acetylcysteine, or resveratrol have also been investigated, with some of them showing promising results, but others yielding some negative or contradictory findings (Arafa et al. 2014; Dresdale et al. 1982; Sterba et al. 2013; Wang et al. 1980). Unclear data may be due to a difficult translation of experimental results into chronic cardiotoxicity treatments (Gianni et al. 2008). BTZ (Section 40.3.6.1) is a promising drug in the treatment of childhood cancers, such as leukemia, but one worrisome side effect in this population is the possible suppression of bone growth (Eriksson et  al. 2012). Humanin, a mtDNA‐encoded peptide with proved protective action in brain disorders (Hashimoto et al. 2001), prevented BTZ‐induced bone growth impairment in mice, while not interfering with its anticancer effects (Eriksson et al. 2014). In an anthracycline‐treated group of children with acute lymphoblastic leukemia or non‐ Hodgkin lymphoma, coenzyme Q10 therapy was tested, and the antioxidant had a protective effect on cardiac function (Iarussi et al. 1994). Carvedilol, a neurohormonal antagonist that blocks adrenoceptors and has vasodilating properties, also showed promising results by preventing the inhibitory effects of DOX on mitochondrial respiration and the decrease in mitochondrial calcium loading capacity (Oliveira et al. 2004; Santos et al. 2002). In patients undergoing anthracycline therapy, carvedilol seemed to be an interesting protector of left ventricle function (Kalay et  al. 2006). However, dexrazoxane (DEX) is, so far, the only approved method for anthracycline cardiotoxicity prevention with many clinical trials supporting its beneficial action (Lipshultz et al. 2010; Marty et al. 2006; Swain and Vici 2004). DEX was initially developed to be a chemotherapeutic agent due to its effects on TOP2 inhibition, but soon the attention moved to its cardioprotective effects against anthracycline‐induced cardiotoxicity (Classen et al. 2003). In a study by Lipshultz et al., children

with acute lymphoblastic leukemia were followed during the treatment with DOX alone or DOX combined with DEX. The control group treated only with DOX showed a higher increase in serum levels of cardiac troponin T after the treatment compared with the group receiving the combined therapy (Lipshultz et al. 2012). Moreover, DEX also reduced the incidence and severity of early and late cardiotoxicity in children with solid tumors receiving DOX (Choi et al. 2010). Cardiac function was measured based on fractional shortening and systolic and diastolic left ventricular diameter, and the DOX plus DEX group presented significant fewer cardiac events (27.7% vs. 52.4%) and less severe congestive heart failure (6.4% vs. 14.3%), compared with the group treated with DOX alone (Choi et al. 2010). In addition, DEX seemed not to affect the response rates to chemotherapy (Elbl et al. 2006; Marty et al. 2006). Although the mechanism of cardioprotection is still not completely understood, the most accepted hypothesis proposes its ability to chelate intracellular iron and to decrease free radical formation (Sterba et al. 2013). At physiological conditions of pH and temperature, DEX undergoes hydrolysis, ultimately leading to the formation of its ring‐opened metal ion‐binding form, ADR925, which has a structure similar to EDTA, and can then either remove iron from the iron‐ANT complexes or bind free iron, preventing oxygen radical formation (Sterba et  al. 2013). However, more recently DEX‐induced TOP2β depletion was also suggested as essential for an effective cardioprotection against anthracycline cardiotoxicity (Jirkovska‐Vavrova et al. 2015).

40.5

Conclusion

As described in the previous sections, chemotherapeutic agents affect different mitochondrial pathways. Some of these interactions are part of their therapeutic effects in cancer cells, but mitochondrial dysfunction resulting from treatment with chemotherapeutic agents also induces resistance to drug‐induced apoptosis in cancer cells and affects the viability of normal cells, limiting their clinical utilization. This chapter demonstrates that mitochondria are a critical mediator of chemotherapy‐induced off‐target toxicity. The multitude of structures and pathways in,  and generating from, mitochondria increases the likelihood that chemotherapy may disturb bioenergetics and/or redox balances in that organelle. Despite what is described in this chapter, and facing the ever‐growing list of mitochondrial findings, it is likely that the future will yield new evidence on how chemotherapy damages mitochondria in normal tissues, and how those organelles can be protected, opening the way for more effective and safer cancer treatments.

Mitochondrial Toxicity Induced by Chemotherapeutic Drugs

Acknowledgments This work was funded by FEDER through the Operational Program for Competitiveness Factors—COMPETE and  national funds by FCT—Foundation for Science and  Technology under research grants, PTDC/ DTP‐FTO/2433/2014, POCI-01-0145-FEDER-016659,

and strategic project POCI-01-0145-FEDER-007440. This is also supported by QREN project 4832 with reference CENTRO‐ 07‐ST24‐FEDER‐002008 financed through FEDER. TC‐O (SFRH/BPD/101169/2014) was supported by a FCT Post‐Doctoral fellowship and ARC (SFRH/BD/103399/2014) and LF (SFRH/BD/52429/2013) were supported by FCT PhD fellowships.

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metabolism after doxorubicin treatment. Free Radic Biol Med 72:55–65. Zheng H, Xiao WH, Bennett GJ (2012) Mitotoxicity and bortezomib‐induced chronic painful peripheral neuropathy. Exp Neurol 238(2):225–234. Zhou S, Heller LJ, Wallace KB (2001) Interference with calcium‐dependent mitochondrial bioenergetics in cardiac myocytes isolated from doxorubicin‐treated rats. Toxicol Appl Pharmacol 175(1):60–67.

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41 The Mitochondrial Exposome Douglas I. Walker1,2,3, Kurt D. Pennell2, and Dean P. Jones1,3 1

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, Emory University, Atlanta, GA, USA Department of Civil and Environmental Engineering, Tufts University, Medford, MA, USA 3 HERCULES Exposome Research Center, Department of Environmental Health, Rollins School of Public Health, Atlanta, GA, USA 2

CHAPTER MENU 41.1 41.2 41.3 41.4 41.5 41.6

41.1

Introduction, 615 Environmental Pollutants and Mitochondrial Toxicity, 617 Bioaccumulation of Environmental Pollutants, 620 Mitochondria High‐Resolution Metabolomics, 622 Case Study: Profiling the Human Mitochondrial Exposome, 625 Conclusions, 632 References, 632

Introduction

41.1.1 The Human Exposome Humans are subjected to a diverse chemical experience that includes chronic as well as episodic exposures that vary spatially and temporally and in magnitude. While some environmental factors are known to contribute to disease, the relationship between many chemical exposures and human health is largely unknown. Identification of environmental stressors and their roles in human health and disease will improve the ability to implement preventative measures and reduce disease risk. Despite completion of genome‐wide association studies (GWAS) for a large number of chronic diseases, only a small number of identified variants describe risk  (Thomas 2010). Interactions between genetic and environment/lifestyle risk factors are now suspected as important contributors to chronic disease burden; however, technologies that provide sequencing of environmental exposures are not available (Rappaport et  al. 2014; Patel 2016; Rappaport 2016). In addition, exposure of different organs and cellular components may cause a range of toxicological responses. Thus, characterizing the contribution of environmental factors

to human health is inherently more complex than profiling the genome. The need to include environmental exposures in understanding human disease led Christopher Wild to introduce the term exposome (Wild 2005), which he defined as “encompassing life‐course environmental exposures (including lifestyle factors), from the prenatal period onwards.” The exposome was proposed as a complement to the genome, where life course of exposures and their interactions with the genome defines disease risk. Unlike the genome, exposures are transient at both short‐ and long‐term time scales. Thus, quantitative assessment of chemical exposure over a lifetime poses substantial challenges. A more practical definition of the exposome was proposed by Miller and Jones (2014): “The cumulative measure of environmental influences and associated biological responses throughout the lifespan, including exposures from the environment, diet, behavior, and endogenous processes.” The exposome, as described in this framework, is not only limited to external chemical exposures but also includes processes internal to the body and socioeconomic influences (Rappaport and Smith 2010; Wild 2012). Importantly, by defining the exposome in terms of

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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cumulative measure of environmental influences and biological response, Miller and Jones (2014) acknowledge that the entirety of an individual’s exposure does not need to be quantified, with exposure effect and maladaptation linking environment to health and disease. The human metabolome is the expression of an individual’s metabolic phenotype. The metabolome includes all endogenous metabolites, chemicals from human– environment interaction, and reactants arising from interaction of these compounds with enzymatic and bacterial processes. By extension, the metabolome provides a means to assess an individual’s exposome. Application of metabolic profiling in human populations indicates that core metabolic processes only contribute to a fraction of the detected chemical species, with a large number of chemicals arising from environment and dietary sources. Current estimates suggest that upwards of one million chemicals are likely to contribute to the human metabolome (Uppal et al. 2016). Plants are likely to contain 105 to 106 small molecules (0.5

Hydrophobicity range

Protein targeting 7%

Figure 41.1 (a) Functional classification of mitochondrial proteins isolated from human heart tissue and identified using mass spectrometry‐based proteomics. (b) Hydrophobicity range of identified mitochondrial proteins, based upon mean Kyte–Doolittle amino acid values. As reference, RNA/DNA/protein synthesis proteins, which tend to be more hydrophilic, and transport proteins, which tend to be more hydrophilic, were included for reference. Adapted from Taylor et al. (2003). Reproduced with permission of Nature Publishing Group.

41.2.1

Polycyclic Aromatic Hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) are widely distributed and persistent environmental pollutants that are recognized as mitochondrial toxicants, either as the pure compound (van Grevenynghe et al. 2004; Babu et  al. 2005) or bound to ultrafine particulate matter (Li  et  al. 2003b). Sources of PAHs include food, water, cooking, indoor air, vehicle exhaust, and other combustion products, with inhalation as the predominant exposure pathway (Menzie et  al. 1992; Walker et  al. 2016b). Toxicity of whole and hydrophobic/hydrophilic fractions of captured diesel exhaust particles was evaluated by Xia et al. (2004). When exposed to the particles and extracted organic material, the largest influence on mitochondrial viability was observed for the polar fraction, which increased reactive oxygen production and membrane potential in a dose‐dependent manner. Similar behavior was observed for the nonpolar fraction, which included aromatics and parent PAH compounds. Membrane and Ca2+‐induced swelling were associated with exposure to both PAH fractions. Xia et  al. (2004) hypothesized that this effect was occurring due to interaction of the PAH metabolites within the matrix itself, with the more polar quinone metabolites competing with ubiquinone and altering electron transfer in the inner membrane complexes. The results of this study have important implications for the mitochondrial exposome; specifically, mechanisms exist for the introduction of PAHs into the mitochondrial matrix, and sequestered environmental pollutants can directly interact with metabolic pathways.

41.2.2

Organohalogens

Environmental exposure to organohalogens, including organochlorine pesticides, polychlorinated biphenyls, brominated flame retardants, dioxins, and perfluorinated compounds, has been associated with negative health outcomes (Hatcher‐Martin et al. 2012; Cohn et al. 2015; Walker et al. 2016a). Due to their recalcitrant properties, lipophilic nature, and tendency to bioaccumulate, organohalogens are widespread and persistent throughout the environment and have been detected at measureable levels in most human populations (Patel et  al. 2016). Acute toxicity includes disruption to a range of metabolic pathways, many of which include secondary effects that alter mitochondrial function. Thus, there is the potential for mitochondrial disruption from low‐dose chronic exposure to organohalogens. Primary toxicity is exerted through the generation of oxidative stress by increased formation of reactive oxygen species (ROS), which is suspected in the pathogenesis of many age‐related diseases (Brieger et al. 2012; Hwang 2013). To determine whether the pesticide methoxychlor caused mitochondrial dysfunction and generated oxidative stress, Gupta et  al. (2006) used mitochondria isolated from mouse ovaries to evaluate how exposure altered function and overall cellular homeostasis. Methoxychlor caused oxidative damage both in vitro and in vivo due to altered mitochondrial respiration and H2O2 production. Decreased expression levels of Sod1, GPX, and CAT were also observed, which can contribute to accumulation of ROS, but these are cytoplasmic rather  than mitochondrial enzymes. In support of the

The Mitochondrial Exposome

mitochondrial effects, Schuh et  al. (2005) found that methoxychlor acts as a complex I inhibitor in studies of brain mitochondria. In vivo exposure to 3‐methylsulfonyl‐dichlorodiphenyldichloroethylene (msDDE) has also been associated with altered adrenal cortical mitochondria. Jonsson et al. (1991) evaluated mitochondrial structure using electron microscopy and irreversible protein binding following perinatal exposure to msDDE. Dose‐dependent effects included reduction in the number of mitochondria, increased vacuolization, and reduction of cristae. Irreversible binding of msDDE was 50‐fold higher within the mitochondrial fraction, which was attributed metabolic activation by 11β‐steroid hydroxylase. The polybrominated diphenyl ether (PBDE) class of flame retardants results in mitochondrial dysfunction through a number of mechanisms, including changing mitochondrial depolarization, altered morphology, calcium homeostasis, triggering apoptosis, and ROS generation (Thorat et  al. 1990; Voorspoels et  al. 2007; Dingemans et  al. 2008). For example, the toxicity of 2,2′,4,5′‐tetrabromodiphenyl ether (PBDE‐49), a common component of commercial brominated flame retardant mixtures, causes mitochondrial dysfunction in neuronal tissue (Napoli et al. 2013). PBDE‐49 disrupted mitochondrial morphology and caused loss of membrane potential and increased oxidative stress; uncoupling of electron transport occurred at lower exposure levels than inhibition of complexes IV and V. These results are consistent with the toxicity data reported for PBDE mixtures (Yu et  al. 2008) and other brominated flame retardants (Birnbaum and Staskal 2004). Perfluoroalkyl acids (PFAAs) have also been identified as mitochondrial toxicants. This class of chemicals includes perfluorooctanoic acid (PFOA) and perfluorosulfonic acid (PFOS), which have gained attention due to widespread persistence in groundwater and developmental risks associated with exposure (Giesy and Kannan 2002; Holzer et al. 2008; Napoli et al. 2013). Both in vitro and in vivo studies show that PFAAs and associated metabolites induce mitochondrial dysfunction. Adverse mitochondrial effects include induction of the mitochondrial permeability transition (MPT), uncoupling of oxidative phosphorylation (Starkov and Wallace 2002), stimulation of hepatic peroxisome proliferation (Berthiaume and Wallace 2002), and stimulation of mtRNA transcription (Walters et al. 2009). PFAAs share structural similarities with endogenous fatty acids and exhibit similar biological activities (Walters et al. 2009). 41.2.3

Contemporary Pesticides

Newer pesticides, including organophosphates, carbamates, triazines, and pyrethroids tend to be less persistent in the

environment (Barr and Needham 2002) than many earlier pesticides, for example, dichlorodiphenyltrichloroethane (DDT). Nevertheless, levels of these compounds have measured in human blood and urine (Patel et al. 2016), with pharmacokinetic modeling and exposure estimates indicating exposure occurs often enough to approach steady‐state blood levels (Wetmore et  al. 2012; Wambaugh et  al. 2013). Examples of these chemicals exhibiting mitochondrial toxicity include rotenone, an important insecticide allowed for production of “organic” foods. Rotenone is a complex I inhibitor that results in ROS production (Li et  al. 2003a). Other insecticides, permethrin and cyhalothrin, also inhibit complex I (Gassner et al. 1997). The herbicide, paraquat, acts as a mitochondrial redox cycler (Martinez and Greenamyre 2012), while atrazine inhibits F1F0‐ATP synthase in sperm (Hase et al. 2008). To increase the efficacy of the newer pesticides, synergists are also included in commercial formulations, including piperonyl butoxide (PBO) and N‐octyl bicycloheptene dicarboximide (MGK 264). These compounds act as inhibitors of detoxification pathways, enabling longer biological half‐lives of the active ingredients in pesticide formulations (Bernard and Philogene 1993). PBO, which is a cytochrome P450 inhibitor, has important implications for mitochondrial pathways utilizing this family of enzymes, including steroid biosynthesis and chemical detoxification. 41.2.4 High‐Throughput Screening for Mitochondrial Toxicants High‐throughput screening (HTS) assays for testing mitochondrial toxicity enable screening and prioritization of a large number of environmental pollutants. Programs focusing on HTS assays, which include the Tox21 and ToxCast programs, use mammalian cell‐ derived enzymatic, receptor signaling, and protein‐based assays representing a range of responses and pathways (Dix et al. 2007). Within the ToxCast program, screening assays are primarily pathway based, with biochemical activity represented by assay response (Sipes et al. 2013). These assays include mitochondrial specific pathways, such as CYP450 and fatty acid signaling pathways; however, none specifically test for exposure‐related mitochondrial dysfunction or for the potential interaction of important therapeutic drugs with common environmental agents. Unlike ToxCast, Tox21 uses a HepG2 hepatocyte cell line to rapidly screen for in vitro perturbations to mitochondria. In the study by Attene‐Ramos et al. (2013), the use of a cell‐based assay allowed the evaluation of 1408 chemical compounds at 14 dosing levels to test for mitochondrial toxicity by exposure‐induced changes to

619

620

Mitochondrial Dysfunction by Drug and Environmental Toxicants

membrane potential. Following initial screening, 91 and 88 compounds at two different time points were classified as active and found to decrease mitochondrial membrane potential at 1 and 5 h, respectively. These results were confirmed by testing 38 active compounds using different metrics of mitochondrial function, including imaging‐based measurement of membrane potential, lactate dehydrogenase (LDH) release, and changes in oxygen consumption rate (OCR). Additional testing identified 37 of the 38 compounds exhibiting activity after 5 h (Table 41.1). LDH results indicated that out of the 38 compounds, four had minimal cytotoxicity at 1 h and six compounds in total (including the initial four) were cytotoxic at 5 h. In addition, 31 compounds resulted in OCR changes at the IC50, which suggests alteration in oxidative phosphorylation and subsequent inhibition of ATP synthesis. Although many advances have improved the ability of HTS to assess toxic effects (Tice et al. 2013), the method does not provide direct evidence of short‐ and long‐term toxicity to human populations. Furthermore, translating in vitro findings to quantitative risk assessment for human populations has proven challenging. Phenotyping of the mitochondrial exposome can be used for hazard identification by surveying populations for the occurrence of exposures, and prevalence can be used to prioritize toxicity. Thus, HTS provides important insights into relevant chemical species in the mitochondrial exposome, but does not directly address risks in human populations. While the previously discussed studies are based on in vitro and acute dosage animal studies, they do provide insight into the potential for interaction between human mitochondria, environmental toxicants, and commonly used therapeutic agents. Thus, there is a critical need to identify exogenous chemicals that bioaccumulate within human mitochondria. Quantitative information on the levels of these chemicals will allow better assessment of whether realistic exposures result in appreciable accumulation of these agents and improve understanding of the mitochondrial exposome.

41.3 Bioaccumulation of Environmental Pollutants The ability of environmental pollutants to cause alterations in mitochondrial function suggests interaction within mitochondria; however, it does not account for accumulation of chemicals arising from low‐dose, chronic exposures. Many environmental pollutants are lipophilic and tend to bioaccumulate in human tissues (Malarvannan et  al. 2013). Hydrophobic regions of cellular components, such as the phospholipid‐based

inner membrane provide ideal microenvironments for sequestration of lipophilic compounds. Accumulated chemicals have the potential to exert toxicological activity through multiple mechanisms, including the parent compound, activated metabolites present in the mitochondria, and/or endoplasmic reticulum (Meyer et  al. 2013). Studies evaluating chemical compartmentalization within mitochondria have been based on in vitro and animal models, with results indicating environmental chemicals can accumulate within mitochondria. As discussed previously, PBDEs have been associated with increased ROS production and apoptotic cell death. In a study by Huang et  al. (2010), the toxicity and accumulation of PBDE congers were evaluated using an in vitro cerebellar granule neuron model cultured from 7‐day‐old mice. Figure  41.2 shows the distribution of PBDE congeners within different cellular components, including cytosolic, mitochondrial, nuclear, and microsomal fractions. Accumulation of the individual congeners within the mitochondria was exceeded only by the microsomal fraction, with congener‐specific accumulation observed. Comparison of the lower (1 μM) and higher (10 μM) dose showed similar percent accumulation at both doses, which has important implications for exposure at environmentally relevant concentrations. Due to the higher pH in the mitochondrial matrix, it is well recognized that cationic, lyophilic compounds partition into mitochondria. However, the potential exists for accumulation of hydrophobic compounds within the mitochondrial matrix, even with the cytoplasm as the preferred environment for neutral compounds. For example, partitioning of hydrophobic chemicals to lipid membranes or cotransport with proteins is possible, and the direct contact of mitochondria with a cytoplasmic region enriched with environmental chemicals can facilitate transfer through diffusion and cotransport. Therapeutic studies have also identified compounds that selectively bind to mitochondria. These  include sulfonylurea‐related chemicals and anthracyclines (Hoye et al. 2008). Although the potential exists for chemical accumulation within mitochondria and represents a central component of the mitochondrial exposome, limited to no information is available on the chemical profile in human mitochondria. While quantification of specific analytes is possible using traditional analytic approaches, methodologies providing greater chemical coverage are needed due to the wide variation in exposures across human populations. The use of HRM, which provides measure of 10,000–20,000 unique chemical species without a priori selection of analytes, has the potential to greatly improve the chemical characterization of human mitochondria. In the next section, we address application of HRM to the study of the mitochondrial metabolome and exposome.

The Mitochondrial Exposome

Table 41.1 Thirty‐eight compounds selected for confirmation analysis and further mechanistic studies, grouped based on oxygen consumption rate following IC50 exposure. Compound name

Classification

1,8‐Dihydroxy‐4,5‐dinitroanthraquinone

Decreased OCR‐irreversible uncoupling

2,2′‐Methylenebis‐(4‐chlorophenol)

Decreased OCR‐irreversible uncoupling

2,2′‐Thiobis(4‐chlorophenol)

Decreased OCR‐irreversible uncoupling

3,4,5‐Trichlorophenol

Decreased OCR‐irreversible uncoupling

3,4‐Dichlorophenyl isocyanate

Decreased OCR‐irreversible uncoupling

4,4‐Thiobis(6‐t‐butyl‐m‐cresol)

Decreased OCR‐irreversible uncoupling

4‐Cumylphenol

Decreased OCR‐irreversible uncoupling

Captan

Decreased OCR‐irreversible uncoupling

Diphenylurea

Decreased OCR‐irreversible uncoupling

Emodin

Decreased OCR‐irreversible uncoupling

Hexachlorophene

Decreased OCR‐irreversible uncoupling

Kaempferol

Decreased OCR‐irreversible uncoupling

Kepone

Decreased OCR‐irreversible uncoupling

Nitazoxanide

Decreased OCR‐irreversible uncoupling

n‐Phenyl‐2‐naphthylamine

Decreased OCR‐irreversible uncoupling

o‐Benzyl‐p‐chlorophenol

Decreased OCR‐irreversible uncoupling

p‐n‐Nonylphenol

Decreased OCR‐irreversible uncoupling

p‐Aminophenol

Decreased OCR‐irreversible uncoupling

Phenmedipham

Decreased OCR‐irreversible uncoupling

Tetra‐N‐octylammonium bromide

Decreased OCR‐irreversible uncoupling

Hexamethyl‐p‐rosaniline chloride

Increased OCR‐decreased FCCP OCR

Malachite green oxalate

Increased OCR‐decreased FCCP OCR

4‐Hydroxyphenyl retinamide

Suppressed FCCP OCR

Curcumin

Suppressed FCCP OCR

Genistein (4′,5,7‐trihydroxyisoflavone)

Suppressed FCCP OCR

Silibinin

Suppressed FCCP OCR

Basic red 9 (p‐rosaniline HCl)

Decreased OCR and FCCP uncoupled OCR

Diethylstilbestrol (DES)

Decreased OCR and FCCP uncoupled OCR

Digitonin

Decreased OCR and FCCP uncoupled OCR

Phenyl mercuric acetate

Decreased OCR and FCCP uncoupled OCR

Zearalenone

Decreased OCR and FCCP uncoupled OCR

1,5‐Naphthalenediamine

Decreased MMP, no change in OCR/FCCP OCR

2‐Aminoanthraquinone

Decreased MMP, no change in OCR/FCCP OCR

Apigenin

Decreased MMP, no change in OCR/FCCP OCR

Formulated fenaminosulf (dexon)

Decreased MMP, no change in OCR/FCCP OCR

o,p′‐DDD (mitotane)

Decreased MMP, no change in OCR/FCCP OCR

Resveratrol

Decreased MMP, no change in OCR/FCCP OCR

Riboflavin

Decreased MMP, no change in OCR/FCCP OCR

Adapted from Attene‐Ramos et al. (2013). Reproduced with permission of American Chemical Society. Carbonilcyanide p‐triflouromethoxyphenylhydrazone (FCCP) was added at the completion of the 1 h monitoring period to evaluate maximal mitochondria uptake and non‐basal oxygen consumption rate (OCR).

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Mitochondrial Dysfunction by Drug and Environmental Toxicants

(a)

(b)

60

80

BDE-47 BDE-99 BDE-100 BDE-153 BDE-209

60 PBDE accumulation (%)

80

PBDE accumulation (%)

622

40

20

BDE-47 BDE-99 BDE-100 BDE-153 BDE-209

40

20

0

0 Cyt

Mito

Micro

Nuc

Cyt

Fraction

Mito

Micro

Nuc

Fraction

Figure 41.2 Percent PBDE accumulation within the cytosol (Cyt), mitochondria (Mito), microsome (Micro), and nuclei (Nuc) fraction of cerebellar granule cells following exposure to (a) 1 μM or (b) 10 μM PBDE solutions for 24 h. Adapted from Huang et al. (2010). Reproduced with permission of Oxford University Press.

41.4 Mitochondria High‐Resolution Metabolomics Limited data exist on the metabolic profile of intact mitochondria, with primary focus on the measure of endogenous metabolites. In‐depth characterization of chemical compartmentalization within mitochondria is required as a critical component of the mitochondrial exposome. HRM, developed as an advanced analytical framework for precision medicine and exposome research (Walker et al. 2016a), provides the capabilities necessary for phenotyping the mitochondrial exposome. By supporting quantification of large numbers of chemicals detected in human samples, HRM yields systematic biological and environmental chemical measurements required for profiling the exposome (Jones 2016). Recent applications of HRM in human populations have shown that current instrumentation provides the sensitivity and selectivity to measure pollutants in human samples at environmentally relevant concentrations (Soltow et  al. 2013; Jamin et  al. 2014; Roca et  al. 2014; Go et  al. 2015; Rager et  al. 2016). The ability to measure environmental toxicant burden in a systematic and quantitative way greatly enhances capabilities for internal exposure assessment, which traditionally relied on

external exposure monitoring, lifestyle factors, modeling, observational data, and targeted biomonitoring data. For  example, in the study by Go et  al. (2015), plasma from a healthy population of 153 individuals was analyzed using HRM profiling. Only 40% of the quantified environmental chemicals have previously reported reference levels, and the others were previously undetected in human populations. Similar results were obtained by Roca et  al. (2014) and Jamin et  al. (2014), where untargeted chemical measurements detected both  common exposure (i.e., organophosphates and carbamate fungicides) and previously uncharacterized environmental chemical metabolites. 41.4.1

High‐Resolution Metabolomics

No single platform will provide comprehensive coverage of all chemical species present within the mitochondria due to the diverse physiochemical properties of metabolites (Rappaport et  al. 2014); however, current instrumentation and workflows provide sufficient chemical coverage for detailed screening. Nuclear magnetic resonance (NMR) spectroscopy and MS have been used for metabolic profiling of biological samples obtained from a thousand or more individuals to identify metabolic changes associated with aging, diet, and environment

The Mitochondrial Exposome

41.4.2 Metabolic Phenotyping of Intact Mitochondria To date, characterization of the mitochondrial metabolome is limited. In a study by Roede et al. (2012), mitochondria isolated from wild type (WT) and thioredoxin‐2 transgenic (TRX‐TG) mice were profiled using HRM, which detected 2127 mitochondria‐specific chemical features. Subsequent matching to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Kanehisa et  al. 2012) identified metabolites/features from a number of relevant pathways, supporting this approach for characterizing mitochondrial specific chemicals (Figure 41.3). Of the detected features, a large proportion was unidentified, suggesting uncharacterized environmental chemicals or metabolic intermediates. The results from this study provide an important framework for the use of HRM to characterize mitochondria isolates. First, these data demonstrate that exposure to environmental agents is universal. The mice selected for  this study were housed in well‐controlled facilities; however, exposure to environmental toxicants still occurred and was detected within mouse organ mitochondria. Second, these data illustrate the need to account for background exposures even when using laboratory‐bred and housed animals. Based on the 2127 detected chemical features, Roede et al. (2012) utilized a metabolome‐wide association study (MWAS) framework to differentiate metabolic differences related to gender and genetic phenotype. Results obtained from these two studies support the use of HRM for chemical

# of mapped metabolites

50 40 30 20 10

ch

id o

n Am ic a ci in d Pu o s m Py rin ug et rim e m ar id et me N i ab t P eu or ne ph m olis ro et ac m y tiv rin abo e m l i s lig et St a m a er St nd bol oi d ero rec ism Pe hor id b ep t. m i nt on osy int os nt . e e he bi ph os osy sis n p Ty ha th e ro t si e p sis ne at m hw et a ab y ol is m

0

Ar a

(Holmes et al. 2008a, b; Menni et al. 2013; Dunn et al. 2015), in addition to being identified as one of the key technologies in exposome research (Wild 2012; Wild et al. 2013; Athersuch and Keun 2015; Go et  al. 2015). Due to variations in methodology, chemical coverage by metabolomic platforms varies widely. Increased use of MS for metabolomics has largely been driven by advances in data analytic tools (Smith et al. 2006; Uppal et al. 2013; Yu et  al. 2013; Libiseller et  al. 2015), dedicated instrumentation (Park et  al. 2012), and high‐resolution, high scanning speed MS (Makarov et  al. 2006; Kanu et  al. 2008; Cribbs et  al. 2014; Frediani et  al. 2014), making measure of 15,000–20,000 unique features possible (Go et al. 2015a, b; Uppal et al. 2015). Current feasibility studies show increased coverage will be available with further development of data extraction tools and complementary ion characterization (Uppal et al. 2016). HRM provides a number of advantages over traditional analytical approaches. High‐resolution mass detection offers improved coverage of low abundance environmental, dietary, microbiome, and drug‐related metabolites. Recent studies have shown that triplicate analysis enhances reliability of detection and improves quantification, especially for low abundance chemicals (Uppal et al. 2013). In addition, a simple extraction procedure (addition of solvent with internal standards followed by removal of protein precipitate) reduces error due to variation in efficiency of recovery or variability in detection of internal standard. Use of profile mode instead of centroid mode preserves ability to discriminate chemicals with very similar mass‐to‐charge ratio (m/z), and use of a data re‐extraction routine with options to optimize parameter settings improves detection and quantitative accuracy (Uppal et  al. 2013; Libiseller et al. 2015). It is now possible to implement HRM for chemical surveillance in human populations, with studies showing external exposure can be linked to internal dose, biological response, and pathophysiological changes (Walker et al. 2016c; de Sousa Rodrigues et al. 2017). To characterize the overall influence of environment and phenotypic character on the mitochondrial exposome, evidence‐based associations must be established. Untargeted profiling allows maximum chemical coverage and reduces bias by not limiting analytical targets to known pollutants, with detected chemical signals that are characterized after categorizing their importance. While initial validation requires confirmation with coelution and ion dissociation studies, development of cumulative detected metabolic feature databases and certified, well‐characterized reference material (i.e., NIST SRM 1950 (Phinney et  al. 2013)) provides direct identification and quantification based on instrumentally acquired information.

Figure 41.3 High‐resolution metabolomic profiling of isolated mouse liver mitochondria detected metabolites from a range of metabolic pathways, including those specific to mitochondrial processes. Reproduced with permission of Roede et al. (2012).

623

624

Mitochondrial Dysfunction by Drug and Environmental Toxicants

characterization of mitochondria and use of HRM in a mitochondrial exposome framework. Further characterization of the mitochondria metabolome described by Go et al. (2014b) provides additional evidence of HRM suitability to measure the mitochondrial exposome and as a tool for monitoring mitochondrial function in vivo. Annotation for the presence of

chemicals arising from environmental sources identified 140 mass‐to‐charge (m/z) features matching relevant chemicals, which included fungicides, herbicides, insecticides, pesticide synergist, plant growth regulators, plasticizers, food preservatives, flame retardant, and antiscald agent (Table 41.2). While not tested, Go et al. (2014b) speculate that the sources of these chemicals

Table 41.2 Environmental chemicals detected in mitochondria isolated from mouse liver.

Environmental chemical

Chemical formula

Classification

Detected m/z [M+H]+

Delta

Mass error (ppm)

Propamocarb hydrochloride

C9H21ClN2O2

Fungicide

225.1370

−0.0005

−2.174

Cyproconazole

C15H18ClN3O

Fungicide

292.1225

−0.0014

−4.752

Triadimefon

C14H16ClN3O2

Fungicide

294.0998

0.0006

1.947

Tridemorph

C19H39NO

Fungicide

298.3084

0.0020

6.758

Benzimidazole

C16H14F3N3O2S

Fungicide

119.0606

−0.0002

−1.595

Piperonyl butoxide

C19H30O5

Pesticide synergist

339.2183

−0.0017

−5.121

Clopyralid

C6H3Cl2NO2

Herbicide

191.9608

0.0006

3.049

Acetochlor

C14H20ClNO2

Herbicide

270.1258

−0.0002

−0.841

Butachlor

C17H26ClNO2

Herbicide

312.1725

0.0000

0.066

Propazine

C9H16ClN5

Herbicide

230.1146

0.0021

9.078

Atrazine GSHa adduct Ib

C18H30N8O6S

Herbicide

487.2083

−0.0001

−0.291

Atrazine GSH adduct IIb

C18H29N8O6SCl

Herbicide

521.1655

0.0037

7.041

Atrazine GSH adduct IIIb

C18H29N8O7SCl

Herbicide

537.1657

−0.0016

−2.930

Cyanazine GSH adductb

C19H29N9O6S

Herbicide

512.2088

−0.0054

−10.477

Simazine

C7H12ClN5

Herbicide

202.0836

0.0018

8.835

Cyanazine

C9H13ClN6

Herbicide

241.0931

0.0032

13.066

Diethyltoluamide (DEET)

C12H17NO

Insect repellant

192.1371

0.0012

6.375

Acetamiprid

C10H11ClN4

Insecticide

223.0737

0.0008

3.464

Bifenazate

C17H20N2O3

Insecticide

301.1533

0.0014

4.697

Cypermethrin

C22H19Cl2NO3

Insecticide

416.0792

0.0023

5.535

Indoxacarb

C22H17ClF3N3O7

Insecticide

528.0787

−0.0007

−1.380

Pirimicarb

C11H18N4O2

Insecticide

239.1527

−0.0024

−9.946

Ethephon

C2H6ClO3P

Plant growth regulator

144.9811

0.0004

3.046

Forchlorfenuron

C12H10ClN3O

Plant growth regulator

248.0574

0.0011

4.469

Daminozide

C6H12N2O3

Plant growth regulator

161.0909

0.0012

7.487

Dimethyl phthalate

C10H10O4

Plasticizer

195.0639

0.0013

6.690

Monobutyl phthalate

C12H14O4

Plasticizer

223.0950

0.0015

6.706

Benzylbutyl phthalate

C19H20O4

Plasticizer

313.1411

0.0023

7.216

Di‐n‐heptyl phthalate

C22H34O4

Plasticizer

363.2507

0.0023

6.467

Diisodecyl phthalate

C28H46O4

Plasticizer

447.3435

0.0034

7.641

Phenoxyethanol

C8H10O2

Preservative

139.0744

0.0010

6.930

3‐Iodo‐2‐propynylbutylcarbamate

C8H12INO2

Preservative

282.0013

−0.0027

−9.702

Triphenyl phosphate

C18H15O4P

Flame retardant

327.0757

0.0024

7.249

Go et al. (2014b). Reproduced with permission of Oxford University Press. Delta = theoretical m/z − detected m/z; mass error = delta/(theoretical m/z) × 106. a  Glutathione. b  LeBlanc and Sleno (2011).

The Mitochondrial Exposome

included water, food, and bedding, which consist of cultivated vegetative products. In addition to detecting the parent compound, detoxification products consistent with mitochondrial defense mechanisms were detected. For example, the active compound for three different triazine herbicides (propazine, simazine, and cyanazine) was detected. Detoxification products of these compounds and other triazines were also detected, including three different atrazine–glutathione adducts and a cyanazine–glutathione adduct. Formation of glutathione adducts is a key mechanism in protecting mitochondria from oxidative stress, and detection of these metabolites using HRM approaches demonstrates that these techniques provide sufficient sensitivity and selectivity for broad chemical characterization. In addition to environmental chemical profiling of mouse liver mitochondria, Go et  al. (2014b) investigated the feasibility of using circulating mitochondrial specific m/z features in plasma to evaluate mitochondrial dysfunction in vivo. Comparison of the mitochondrial metabolome to the plasma metabolome identified 30 metabolites specific to mitochondrial function that were also detected in human plasma from a cohort of 99 subjects. Overall, 1425 m/z features were detected in both the mitochondrial and human plasma metabolome, providing potential biomarkers for in vivo measure of mitochondrial function in humans. A limited number of studies have used HRMS approaches to characterize specific aspects of mitochondrial biology or study toxic effects of exposure in animal models. Bird et al. (2011) isolated and extracted rat liver mitochondria for the hybrid targeted/untargeted analysis of cardiolipins and monolysocardiolipids. These lipids are essential for maintaining mitochondrial structure and are central to proper functioning of complexes I, III, IV, and V (Paradies et al. 2014). The mitochondrial lipids were characterized using different MS procedures, including reverse phase chromatography with data‐ dependent collision‐induced dissociation. This methodology was then applied to evaluate the effect of diet on mitochondrial biochemistry. These data showed a link between the major fat component of diet and a specific monolysocardiolipid, suggesting that diet directly affects the mitochondrial metabolic footprint. To investigate the toxicity of cadmium to liver mitochondria, Go et  al. (2014a) used an integrated redox proteome and mitochondrial metabolome approach to measure antioxidant defense and associated metabolic changes. Comparison of cadmium‐exposed mice to controls revealed almost half of the isotope‐coded affinity tag (ICAT) identified cysteine‐containing peptides were oxidized more than 1.5‐fold following exposure. A  statistically significant decrease in glutathione and glutathione disulfide and an increase in the cysteine redox potential were also observed, showing an increase in oxidative stress with increasing cadmium exposure.

HRM profiling identified changes in key mitochondrial pathways involved with fatty acid metabolism, including several carnitines and palmitoyl‐coenzyme A. Thus, this study directly related acute exposure to cadmium to biological response evidenced by alterations within the mitochondrial metabolome. These results support the robustness and suitability of mitochondrial extraction and analysis to evaluate effects of environmental exposure on mitochondrial function. The accumulating experience with HRM shows this to be an effective analytical platform for profiling the mitochondrial metabolome under experimental conditions in rodent models. Results show sample preparation and profiling methods enable detection of a large range of endogenous and exogenous chemicals. To date, there are no data available on the application of HRM to human mitochondria to determine the presence and distribution of environmental chemicals. In principle, the same approaches used for model studies could be used to study the relationship of endogenous chemical burden to the mitochondrial metabolic phenotype. Thus, a critical next step in developing the mitochondrial exposome will be to apply the approaches described previously to characterize isolates obtained from human tissues. An example of this approach is provided hereafter.

41.5 Case Study: Profiling the Human Mitochondrial Exposome Due in part to the relative difficulty of obtaining tissue samples, the chemical burden of human tissues and subcellular fractions is largely unknown. In most epidemiology studies, body burden of environmental chemicals is estimated by measuring levels in easily obtainable biological fluids, such as urine or blood; however, this does not adequately reflect accumulation of lipophilic compounds in diverse body compartments. Development of HRM, which provides untargeted screening capabilities for a large number of low molecular weight chemicals in biological samples, has greatly improved the ability to characterize the exposome. Applying HRM to study isolated human mitochondria has the potential to provide new insight into the chemical burden arising from exposure to environmental chemicals and to identify potential toxicological targets. In this case study, we use HRM to profile and identify environmental chemicals in mitochondria isolated from human adrenals. These results represent the first characterization of the human mitochondrial exposome. 41.5.1

Adrenal Glands

The human body contains two adrenal glands, one located on the top of each kidney. Each gland is 4–6 cm long, 1 cm thick, and 4–6 g in weight (Lacroix and Clavier 2001).

625

626

Mitochondrial Dysfunction by Drug and Environmental Toxicants

Within each adrenal gland exist two separate compartments providing different biological functions. The inner compartment is the adrenal medulla and comprises 10–20% of the gland. The outer adrenal cortex fully surrounds the adrenal medulla and comprises the remaining 80–90% of the gland. The adrenal cortex is the location for synthesis of hormones derived from cholesterol, which includes aldosterone, cortisol, corticosterone, dehydroepiandrosterone, and androstenedione (Parker and Rainey 2004). While cortisol and corticosterone are important in metabolism and stress response, dehydroepiandrosterone and androstenedione are common precursors for both male and female sex hormones, including testosterone, estradiol, and estrogen. Similar to the testes, steroid biosynthesis is rate limited by the transfer of cholesterol from the outer mitochondrial membrane to the inner membrane (Griffin and Ojeda 2004), which occurs via the steroidogenic acute regulatory (StAR) protein. Once within the inner membrane, steroidogenesis occurs by cholesterol side‐chain cleavage (Lacroix and Clavier 2001). The inner adrenal medulla is primarily responsible for secreting catecholamines, which provide critical functions related to the sympathetic nervous system (Griffin and Ojeda 2004). Hormones produced by the adrenal medulla include epinephrine and norepinephrine, which are synthesized from the hydroxylation of tyrosine through a pathway that includes levodopa and dopamine as precursors. Catecholamine synthesis pathways are almost identical to those within sympathetic nerves, with the medulla a modified sympathetic ganglion with postganglionic cells but no axons (Parker and Rainey 2004). The adrenal glands receive the highest rate of blood flow in the body on a per gram basis (Parker and Rainey 2004). Arterial blood enters through the outer cortex, flows through fenestrated capillaries between the cords of adrenocortical cells, and drains inwardly into venules in the medulla. This suggests that the adrenal gland could be highly exposed to internal levels of environmental chemicals based on a high blood flow/mass ratio. Furthermore, the adrenal gland plays a very important functional role in ensuring endocrine system health and has been reported to be the most highly targeted organ within the endocrine system by toxins (Rosol et al. 2001; Harvey et al. 2007). Thus, detection and identification of environmental chemicals within adrenal tissue mitochondria would improve estimates of exposure and allow more thorough evaluation of alterations to hormone production. Biomarkers of oxidative stress correlating with the presence of environmental chemicals in adrenal tissue will also provide means to improve exposure assessments. Adrenal tissues, especially within the

adrenal cortex, are high in unsaturated fatty acids, which is susceptible to lipid peroxidation (Gutteridge 1995). While there are a number of diseases arising from adrenal dysfunction, chronic exposure to ambient environmental chemicals could have a more subtle influence on adrenal gland function (Takayanagi et  al. 2000). Currently, limited data are available on how environmental exposures affect adrenal glands, even though a number of the enzymatic steps required for adrenal hormone synthesis are inhibited or induced by environmentally relevant chemicals. These include polychlorinated biphenyls, organochlorine pesticides, and plasticizers (Hornsby 1989; Xu et  al. 2006; Harvey et  al. 2007). In addition, exposure‐induced alterations to steroidogenesis show that cytochrome enzyme overexpression results in increased production of androstenedione (Xu et  al. 2006). Long‐term disruption of adrenal mitochondria could impact overall adrenal gland health, and metabolic profiling of the tissue and mitochondria could provide insight into which pathways are most affected. Accordingly, we selected adrenal gland tissue for initial characterization of the mitochondrial exposome: application of the methods described hereafter can be easily extended to different tissues. 41.5.2

Methods

41.5.2.1 Adrenal Gland Selection Criteria and Procurement

Due to the challenges inherent in obtaining fresh organs from recently deceased patients and the lack of relevant information on environmental chemicals in human adrenals, we placed few limitations on donor characteristics. The adrenals were procured from the International Institute for the Advancement of Medicine (IIAM), an organization providing human organs and tissues for medical research, education, and development. Exclusion criteria included high body mass index (>45); evidence of current kidney bacterial infection; extended downtime (>30 min); serology positive for Anti‐H I–II, HBsAg, HBcAb, Anti‐HCV, Syphilis, Anti‐CMV, and EBV; and the presence of health defects that would result in significant alteration in daily life. For our studies, single adrenal glands were obtained from deceased patients, with time of death no more than 36 h prior to tissue collection. The adrenal glands were removed by trained recovery teams and shipped using standard transport methods for transplantable organs, which included storage in preservation solution on ice. 41.5.2.2

Adrenal Gland Tissue Preparation

In this initial study, no attempt was made to separate the  medulla from the cortex so the preparation is

The Mitochondrial Exposome

expected to large represent the adrenal cortex mitochondria (80–90% of the adrenal is cortex). All samples were kept on ice within the original packaging until processing, and the initial dissection and homogenization were completed on ice in a 4°C room. The adrenal was rinsed three times with ice‐cold calcium and magnesium‐free HBSS, and the total weight of the gland was recorded. The adrenal was then sliced along the pressure ridge and sectioned into individual pieces of approximately 1 g. Each piece was washed with mitochondrial isolation buffer containing 2 mg/mL bovine serum albumin (BSA) and placed in a homogenization vessel containing 5 mL  of isolation buffer. The tissue was homogenized using 15–20 strokes of a dounce homogenizer, and two isolates were prepared by pooling two homogenized tissue samples. 41.5.2.3 Mitochondria Isolation and Sample Preparation

Mitochondria were prepared using differential centrifugation (Savage et  al. 1991; Roede et  al. 2012), which provides an extract with approximately 90% purity and includes limited contamination from lysosomes and peroxisomes (Graham 2001). Briefly, the pooled homogenate was first centrifuged in an ice‐cold isolation buffer containing BSA at 4°C for 5 min at 600×g to remove nucleic material and residual cell debris. The resulting supernatant was pipetted to a separate, chilled 15 mL centrifuge tube, and 3 mL of isolation buffer containing BSA were added to resuspend the pellet for rehomogenization. The suspension was then centrifuged at 4°C for 11 min at 11,000×g, the supernatant was discarded, and the mitochondrial pellet was resuspended in 2 mL of isolation buffer containing BSA. The mitochondrial preparation was then used to create two equivalent fractions, one for HRM analysis and the other for characterization of mitochondrial integrity. The supernatant was transferred to two chilled microcentrifuge tubes, and centrifuged at 8000×g for 10 min. Pellet 1, which was collected for HRM analysis, was flash frozen in liquid N2 and stored at −80°. Pellet 2 was used to evaluate mitochondrial viability via a MPT assay. Mitochondria were extracted for HRM profiling using established methods (Roede et al. 2012; Go et al. 2014b). Briefly, an aliquot of isolate providing 400 µg protein was first diluted to 100 μL in deionized water. The suspension was then treated with two volumes acetonitrile containing 13C– and 15N–labeled internal standards, mixed on a vortex mixer, and allowed to stand on ice for 30 min. The  extract was then centrifuged at 16,100×g at 4°C for  10 min. A 200 μL aliquot of the supernatant was transferred to a low volume autosampler vial, maintained in a refrigerated autosampler, and analyzed within 24 h.

41.5.2.4

High‐Resolution Metabolomics

HRM of the mitochondria isolates was performed using liquid chromatography with HRMS (Park et  al. 2012; Soltow et al. 2013). Analyte separation was accomplished by dual C18 chromatography with acetonitrile gradient– formic acid gradient (total run time of 10 min) using an Ultimate 3000 high‐performance LC system equipped with refrigerated autosampler, dual channel pumps, and heated column compartment. A Thermo Scientific Q‐Exactive mass spectrometer was used for mass detection and operated with positive and negative electrospray ionization. Twelve replicates were analyzed for each extract, with 6 corresponding to each polarity mode. Feature detection and peak alignment were completed using apLCMS (Yu et al. 2009) and xMSanalyzer (Uppal et  al. 2013), which provided the final metabolic feature table consisting of accurate mass m/z features based upon m/z, retention time and ion intensity. 41.5.2.5

Data Processing and Feature Annotation

A threshold filtering criteria of 1.5 (ratio of average abundance of feature in mitochondria isolate to average feature abundance in resuspension blank) was applied to identify features enriched in mitochondria. The m/z features were then characterized using ion intensities, retention time, and coefficient of variation (CV). Metabolite annotation was completed using the KEGG database and match accuracy of 10 parts per million (ppm). Environmental chemical classes were evaluated based on use and KEGG BRITE classification. 41.5.3

Results

41.5.3.1 Tissue Procurement

During the collection period, five adrenal glands were collected from five deceased donors. A summary of individual characteristics is given in Table 41.3. The individuals included a range of ages (27–71), geographic locations, and pathologies. All tissues were received within the designated delivery time following removal and were successfully dissected and processed for mitochondria. Table 41.3 Adrenal tissues available for mitochondrial isolation. ID

Source

Sex

Age

Cause of death

AG001

R adrenal

M

29

CVA 2nd ICH possible drug overdose suspected

AG002

R adrenal

F

56

Anoxia 2nd cardiovascular

AG003

R adrenal

M

27

HT 2nd GSW

AG004

R adrenal

F

46

CVA 2nd ICH

AG005

R adrenal

M

47

Anoxia 2nd asphyxiation

627

Mitochondrial Dysfunction by Drug and Environmental Toxicants

41.5.3.2

The observed elution pattern suggested lower molecular weight chemicals eluted early, with greater retention of hydrophobic and larger molecular weight compounds, including lipids and environmental chemicals.

Mitochondria Isolation

The isolation procedure provided sufficient yield for metabolic profiling, with total mitochondrial protein concentrations ranging from 4,700 to 29,000 µg/mL. Isolation of viable mitochondria was achieved for all preparations, which was verified by the time‐dependent drop in absorbance measured at 540 nM when 15 uL of 2 mM CaCl2 due  to MPT and swelling of the intact mitochondria. The  associated cytosolic fraction and reference blank exhibited negligible change under the same conditions. 41.5.3.3

41.5.3.4 Characterizing the Mitochondrial Exposome

Matching feature m/z to the KEGG database provided accurate mass matches of 5823 m/z features, with 1554 and 1818 unique to positive and negation ionization, respectively. Due to the role of adrenal mitochondria in steroid biosynthesis, detected metabolites were mapped to the KEGG steroid biosynthesis pathways, which resulted in 73 matches using both positive and negative mode data (Figure  41.5). The ability to detect metabolites from this pathway in adrenal mitochondria shows that measures of metabolic function can be measured within the mitochondrial isolates, providing markers that can be used to assess exposure‐related alterations to key metabolic pathways. KEGG BRITE categorization, which provides a hierarchical classification scheme for different classes of endogenous and exogenous metabolites, was used to characterize the remaining matches (Figure 41.6). Both anthropogenic and biological metabolites were observed, supporting the use of HRM chemical characterization of the mitochondrial exposome. Limited data exists on body burden for many of these chemicals (Wambaugh et al. 2014; Rager et al. 2016), so use of untargeted HRM greatly improved the ability to detect unexpected and previously unidentified environmental exposures. Annotated features within the pesticides and endocrine‐disrupting BRITE categories were selected for further characterization. Using m/z features detected in positive and/or negative mode, 822 provided tentative

High‐Resolution Metabolomics Results

Using apLCMS and xMSanalyzer for data extraction, 8746 and 9953 unique features were detected in positive and negative modes, respectively. To remove artifacts introduced during sample preparation, m/z features were referenced against blank buffer and filtered based upon fold change, resulting in 5387 (positive) and 6805 (negative) m/z features enriched in mitochondria. The abundance for the different m/z features varied over a nine‐order‐of‐magnitude range, suggesting detection of both high and low abundance chemical species (Figure 41.4a). Median replicate CV for the six replicates analyzed for each sample was also shown to be quantitatively reproducible, with a median CV for all features of 23% (equivalent to standard error of the mean of 8.5% for n = 6) (Figure 41.4b). Because this study was to evaluate whether low‐level environmental chemicals could be detected within human mitochondria, the m/z features with high CV were included during annotation. Feature m/z and abundance was relatively consistent across the series of analyses. There was a significant decrease in number of  features detected with increasing retention time and  a  similar decrease in abundance (Figure  41.4c). (a)

(b)

(c)

1200

11

900

9

Time 600

7

300

Log10(abundance)

400 Frequency

628

300 600 200 300

100 0 3

5 7 9 Log10(abundance)

11

0

0

25

50

75

100

Coefficient of variation

0 5

3

250

750

1250

Feature m/z

Figure 41.4 Characterization of high‐resolution metabolomic profiling results for mitochondrial specific features. Log10(abundance) (a), coefficient of variation (b), and m/z feature retention time (c) show untargeted profiling of mitochondria isolates provides coverage of a wide range of chemical signals. Distributions were similar for negative mode (data not shown).

The Mitochondrial Exposome

Figure 41.5 Annotation of both positive ESI and negative ESI m/z features for steroid biosynthesis metabolism. Coverage of this pathway provides important biological response measures for assessing exposure‐related changes to adrenal pathways.

matches to these categories, with 224 and 346 unique to positive and negative, respectively. While these matches were based upon accurate mass alone and will require confirmation with reference standards, previous studies using coelution with authentic standards and in ion dissociation, we have found matches to known metabolic intermediates to be correct 60–80% of the time (Osborn et al. 2013). Figure 41.7 contains representative matches to different environmental chemicals from negative/positive

ionization polarities, and Table  41.4 provides a more detailed list, which includes chemical classification. Different types of environmental chemicals were detected, including pesticide synergists, chemical products, insecticides, fungicides, and halogenated chemicals. The presence of these chemicals within the mitochondria has important implications for human health. For example, PBO was detected in all the individuals and confirmed by ion dissociation and coelution with authentic

629

Mitochondrial Dysfunction by Drug and Environmental Toxicants

standard. It is a potent CYP450 inhibitor (Willoughby et al. 2007), primarily used in insecticide formulations to increase the efficacy of treatment, widely applied in aerial spraying for mosquito control, and included in pesticide formulations for household use. Limited information is available on the effect of PBO to CYP450scc, the enzyme responsible during steroid biosynthesis for side‐chain cleavage of cholesterol, which, following transport of the cholesterol into the mitochondrial inner membrane, is the next step in biogenesis for most steroidal hormones. Disruption of this metabolic pathway has the potential for adverse effects on health and growth. Bisphenol A (BPA) is used for manufacture of polycarbonate plastics and resins and is recognized as a possible endocrine disruptor. BPA was detected within all adrenal mitochondrial samples, suggesting accumulation within human mitochondria. Further investigation of the

Endocrinedisrupting compounds 0.3% Natural toxins 1%

metabolic alterations from BPA exposure could provide plausible hypotheses on the mechanisms by which BPA effects hormonal production. In positive ionization mode, matches to insecticides and fungicides were also detected. These include the commonly used carbamate insecticides (used in agricultural areas) and fungicides (added to produce to avoid molding during harvest and shipping). Additional environmental chemicals included chemicals used in industrial processes, commercial products, herbicides, and PAHs. 41.5.3.5

Carcinogens 4%

Lipids 11%

Phytochemical compounds 13%

Uncategorized 61%

Compounds with biological roles 5%

Figure 41.6 BRITE classification of annotated m/z features for positive ionization mode. Similar distributions were observed for negative mode (data not shown). Piperonyl butoxide

1.0

20

0.5

0.0

4

-0 05 AG

-0 0 AG

-0 03 AG

-0 02 AG

AG

-0 01

0

40

Bisphenol A M+ACN+Na M+Na–2H

30 20 10 0

AG -0 01 AG -0 02 AG -0 03 AG -0 04 AG -0 05

40

Ion abundance (×106)

M+Na M–H

50

1.5 M–H adduct abundance (×106)

60

Case Study Conclusions

The results presented here show that the cytochrome P450 inhibitor—PBO—is present in human mitochondria. The results also show accurate mass matches (Level 5 identification by Schymanski et  al. (2014)) to large numbers of other environmental chemicals, which will require confirmation by ion dissociation, coelution with standards, or other methods. Although some will be incorrect, available environmental chemical databases are biased toward commonly used chemicals, and our prior experience shows that a large fraction of matches are correct identifications. Thus, the results show that HRM profiling of mitochondria from human adrenal tissue is suitable for characterization of low‐level environmental pollutants that have not previously been studied in human mitochondria. The use of an untargeted methodology in tandem with ultrahigh accuracy MS enables detection of a broad range of chemicals that would be difficult and expensive if limited by a requirement for a priori selection of analytical targets and validation of targeted methods. The results support the suitability of HRM for environmental chemical surveillance and detection of exposure biomarkers in human tissues available for research. Such  an approach could be very useful as a basis to understand environmental effects on adverse drug toxicities involving mitochondria.

Pesticides 5%

M+Na adduct abundance (×106)

630

Figure 41.7 Detected environmental chemicals in adrenal mitochondria isolates with the potential to exert endocrine‐disrupting effects. Piperonyl butoxide was confirmed and using authentic reference standards.

Table 41.4 Matches to environmental chemicals detected in mitochondria isolated from human adrenal tissue. Environmental chemical

Chemical formula

Classification

Detected m/z

Delta

Mass error (ppm)

Chlorfenethol

C14H12Cl2O

Acaricide

289.0160

0.0003

Chloropropylate

C17H16Cl2O3

Acaricide

339.0556

0.0008

2.23

Spiroxamine

C18H35NO2

Fungicide

298.2740

3.12E−05

0.10

0.98

Fuberidazole

C11H8N2O

Fungicide

185.0702

−0.0008

4.27

Cycloate

C11H21NOS

Herbicide

216.1425

−0.0008

−3.87

Chlorsulfuron

C12H12ClN5O4S

Herbicide

358.0347

−0.0025

7.08

Paraquat

C12H14N2

Herbicide

250.1301

−0.0014

7.55

EPTC

C9H19NOS

Herbicide

190.1268

0.0009

4.57

Nicosulfuron

C15H18N6O6S

Herbicide

433.0930

0.0029

7.05

Styrene

C8H8

Industrial precursor/intermediate

105.0704

−0.0005

−4.79

4‐Aminobiphenyl

C12H11N

Industrial precursor/intermediate

170.0964

4‐Octylphenol

C14H22O

Industrial precursor/intermediate

251.1372

Metolcarb

C9H11NO2

Insecticide

166.0862

2.23E‐05

2‐Hydroxyphenyl methylcarbamate

C8H9NO3

Insecticide

168.0655

3.69E−05

Xylylcarb

C10H13NO2

Insecticide

180.1020

−0.0001

−0.46

Aldicarb sulfoxide

C7H14N2O3S

Insecticide

207.0799

−0.0001

−0.51

Propoxur

C11H15NO3

Insecticide

210.1125

−4.78E−05

−0.23

Fenchlorphos

C8H8Cl3O3PS

Insecticide

364.8731

0.0023

7.03

Aminocarb

C11H16N2O2

Insecticide

209.1266

−0.0019

9.25

Propamocarb

C9H20N2O2

Insecticide

189.1598

0.0001

0.29

Chlorpyrifos

C9H11Cl3NO3PS

Insecticide

331.9257

0.0033

9.39

Chlorpyrifos‐methyl

C7H7Cl3NO3PS

Insecticide metabolite

365.8650

−0.0012

3.68

4.03E−05 −0.0010

0.24 5.04 0.13 0.22

Metaldehyde

C8H16O4

Molluscicide

177.1123

−0.0001

−0.66

Maleic hydrazide

C4H4N2O2

Plant growth regulator

113.0355

−0.0010

−8.43

Daminozide

C6H12N2O3

Plant growth regulator

161.0922

0.0001

0.46

Di‐n‐propyl phthalate

C14H18O4

Plasticizer

251.1272

0.0006

2.37

Di‐n‐butyl phthalate

C16H22O4

Plasticizer

279.1589

0.0001

0.53

Dimethyl phthalate

C10H10O4

Plasticizer

195.0644

−0.0008

3.90

Bis(2‐ethylhexyl)phthalate

C24H38O4

Plasticizer

429.2406

0.0005

1.21

Anthanthrene

C22H12

Polycyclic aromatic hydrocarbon

277.1035

−0.0024

−8.54

Delta = theoretical m/z − detected m/z; mass error = delta/(theoretical m/z) × 106.

632

Mitochondrial Dysfunction by Drug and Environmental Toxicants

Accumulation of the mitochondria burden of environmental chemicals is most likely a result from transfer of  circulating levels of the chemicals to the organ and accumulation within the mitochondrial compartment. Understanding the mitochondrial exposome and how it is influenced by systemic exposures will be a critical part of linking mitochondrial dysfunction to environmental factors. For this, studies of environmental chemical distribution in animal models, especially determining half‐life of chemicals within mitochondria, will be important to understand both short‐term and long‐term impacts of this accumulation.

41.6

Conclusions

Extensive data exist on the susceptibility of mitochondria to environmental toxins; however, there is a poor understanding of mitochondrial burden of chemicals in   humans and the associated contribution to chronic disease. To address this knowledge gap, we introduce the concept of the mitochondrial exposome, defined as a measure of environmental stressors and associated biological response on mitochondrial function in humans. HRM profiling, which is based upon HRMS, allows for comprehensive characterization of the mitochondrial exposome through untargeted profiling of environmental chemicals and associated metabolic response. Measurement of the mitochondrial metabolic phenotype

provides biomarkers of biologically relevant dose, reducing the need for apical endpoints, and enables in vivo measurement of biochemical perturbations. This is comparable to high‐throughput in vitro assays for chemical hazard identification because dose–response relationships can be evaluated for individual chemicals and mixtures; and chemical disposition, metabolism, and products can be evaluated for differential effects. Application of HRM to isolated mitochondria from human adrenal glands showing sufficient chemical coverage is available to assess the accumulated body burden of many anthropogenic compounds. While the results shown in this study are exploratory in nature, the techniques demonstrated here have broad applicability to characterize mitochondria from other tissues and species. Thus, continued development and measure in human populations are possible, providing avenues to develop new understanding of the environmental contribution to mitochondrial health.

Acknowledgments This work was funded by the National Institute of Health and supported by the HERCULES Exposome Research Center (award# ES019776), National Exposure Assessment Laboratory (award# ES026560), and Alzheimer’s Disease Research Center (award# AG025688) at Emory University.

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42 Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents: Integrated Omics for Visualization Young‐Mi Go1, Karan Uppal1, and Dean P. Jones1,2 1 2

Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, Emory University, Atlanta, GA, USA HERCULES Exposome Research Center, Department of Environmental Health, Rollins School of Public Health, Atlanta, GA, USA

CHAPTER MENU 42.1 42.2 42.3 42.4 42.5 42.6

Introduction, 639 High‐Resolution Metabolomics, 641 High‐Resolution Metabolomics of Liver Mitochondria, 642 Integration of Mitochondrial Redox Proteomics and Metabolomics: RMWAS, 643 Integration of HRM with Transcriptomics: TMWAS, 645 Three‐Way Integration of Redox Proteomics, Metabolomics, and Transcriptomics to Create RMT Association Study for Mitochondrial Signaling in Manganese (Mn) Toxicity, 645 42.7 Integrated Omics Applications in Mitochondrial Metabolic Disorder: Fatty Liver, Diabetes, Obesity, and Neurodegenerative Diseases, 648 42.8 Summary and Perspective, 649 References, 650

42.1

Introduction

Mitochondria function in aerobic metabolism plays a central role at the interface between an individual, defined as a functional genome, and associated environment, defined by environmental resources and threats (Go and Jones, 2014; Jones and Sies, 2015). With maturation of omics technologies, the central dogma of information storage in DNA, transcribed to RNA and translated into protein, emerges as integrated functional genome with epigenetic control of gene expression (Rydzanicz et al., 2013), posttranscriptional editing of RNA transcripts (Pineda et  al., 2015), posttranslational modifications of the epiproteome (Dai and Rasmussen, 2007; Waldrip et al., 2014), and integrated control of biochemical reactions. This functional genome contains exposure memory systems (Jones, 2015), which enable the functional genome to remember exposures and improve utilization of resources and defend against challenges. Lifelong exposures of an individual, cumulatively termed the “exposome” (Miller and Jones, 2014; Wild, 2005), impact mitochondrial function but have not yet been well described.

Importantly, the exposome includes a broad range of  chemicals derived from food, microbiome, pharmaceuticals, commercial products, and environmental exposures, but relatively few of these chemicals have been studied in the context of mitochondrial function and dysfunction (Go et al., 2014b). Although containing only about 10% of the proteins encoded by the nuclear genome, the mitochondrial metabolome appears to include representative metabolites of up to 90% of the gene‐directed metabolome. Mitochondrial metabolomics research has often focused on the citric acid cycle and energy metabolism, but mitochondria contain metabolic precursors and intermediates for mitochondrial replication (Walberg and Clayton, 1983), transcription (Edwards et  al., 1982), translation (Ostrander et al., 2001; Pfisterer and Buetow, 1981), and posttranslational modifications (Bhattacharjee et al., 2009; Chavez et al., 2011). Many ancillary systems are also present, such as the ATP‐dependent protease La (LON) (Ngo and Davies, 2007) that generates peptides, mitochondrial sirtuins (He et  al., 2012) that generate acetylated and succinylated protein derivatives, and other mechanisms to modify bases in RNA.

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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The spectrum of metabolism in mitochondria is very broad, with enzymes catalyzing steps of purine and pyrimidine biosynthesis (Eriksson and Wang, 2008); carbohydrate (Kaminsky et al., 1982), amino acid (Guda et al., 2007), and fatty acid oxidation (Kunau et al., 1995); anabolic systems for biosynthesis; and elimination of nitrogen through ureagenesis (Christian and Spremulli, 2012; Sumegi and Srere, 1984). Metabolic pathways for energy metabolism include central processes for β‐oxidation of fatty acids, including import of fatty acids as acylcarnitines (Kunau et al., 1995), which are deranged in many disease processes. Branched‐chain amino acids (BCAA) are oxidized through branched‐chain fatty acid intermediates (Crown et  al., 2015), and these are also commonly altered in disease. Other pathways include porphyrin and heme biosynthesis (Richardson et  al., 2010; Sano et al., 1959), terpene and terpenoid products, such as squalene precursors for cholesterol and vitamin D synthesis (Miller and Auchus, 2011; Schroepfer, 1981) and activation of vitamin D and biosynthesis of steroids, including sex hormones, mineralocorticoids and glucocorticoids (Miller, 2013). The terpene/squalene pathway also functions in biosynthesis of coenzyme Q, an essential electron carrier for mitochondrial bioenergetics (Tran and Clarke, 2007). Mitochondria also contain a spectrum of cytochromes P450 (Cyp) (Nebert and

Russell, 2002), glutathione S‐transferases (Sato et  al., 1977; Wiseman and Woods, 1977), and other detoxification enzymes, such as the rhodanese system for H2S and thiocyanate metabolism (Aussignargues et al., 2012). Overall, this extensive array of metabolism illustrates that mitochondria are intrinsic elements in the adaptive interface of the genome and exposome. As such, this implies that mitochondrial metabolomics will reflect adaptive and toxic responses to environment and also reveal perturbations as elements of toxicity and disease. The present article describes (i) new high‐resolution metabolomics (HRM) as a practical approach for metabolic surveillance, (ii) application of HRM to measure mitochondrial metabolism, (iii) use of HRM with redox proteomics in a redox proteome × metabolome‐wide association study (RMWAS) to understand mechanisms of mitochondrial cadmium (Cd) toxicity, (iv) combination of HRM in transcriptome × metabolome‐wide association study (TMWAS) of environmental fungicide and herbicide toxicity, and (v) combination of the redox proteome, metabolome, and transcriptome in redox proteome × metabolome × transcriptome‐wide association study (RMTWAS) of manganese (Mn) toxicity (Figure 42.1). We conclude with a conceptual framework to use these approaches for comorbidities and complex multimorbidities, such as those commonly observed

Environmental and diet stress Cd, fungicide, herbicide, excess Mn

Liver

RMWAS redox proteomics HRM

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Pancreas Mitochondria

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AD, HD, PD CVD

Figure 42.1 The use of integrated omics approaches for complex multimorbidities to understand central mitochondrial signaling mechanisms in response to environmental agents or drugs. Chronic exposures to environmental toxicants (cadmium, fungicide, herbicide, excess manganese) affect mitochondrial signaling and metabolism resulting in systematic dysfunctions of organs and contribute to development of multimorbidities. Application of high‐resolution metabolomics (HRM) to measure mitochondrial metabolism and integrated omics approaches of HRM with redox proteomics (RMWAS), transcriptomics (TMWAS), and RMT (redox proteomics × HRM × transcriptomics) will advance our understanding of drug‐ or environmental agent‐induced multimorbidities such as fatty liver disease associated with obesity and type 2 diabetes and further cardiovascular diseases (CVD) and neurodegenerative diseases (Alzheimer’s disease (AD), Huntington’s disease (HD), Parkinson’s disease (PD)).

Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents: Integrated Omics for Visualization

with drug‐induced liver injury including fatty liver disease associated with obesity and type 2 diabetes, and further extended to neurodegeneration, cardiovascular disease, renal disease, and lung disease (Figure 42.1).

to four orders of magnitude higher abundance in human samples than environmental chemicals (Rappaport and  Smith, 2010). Thus, challenges for metabolomics include ability to measure a broad spectrum of metabolites covering an extensive range of concentrations. HRM addresses these key needs by providing high‐ throughput, reproducible, and quantitative methods with extensive metabolic coverage (Go et  al., 2015b; Walker et al., 2016) (Figure 42.2). HRM takes advantage of ultrahigh mass resolution and mass accuracy of Fourier transform mass spectrometry (FTMS) with three technical replicates to improve reproducibility and sensitivity for metabolic studies. With three technical replicates, deep data extraction with adaptive processing (apLCMS) (Yu et  al., 2009) and xMSanalyzer (Uppal et al., 2013) and a quantification structure using reference standardization (Go et al., 2015b), large numbers of metabolites can be quantified (Figure  42.2). Detailed comparisons of different mass spectrometry approaches are available (Marshall and Hendrickson, 2008); special ion traps with a central electrode (Orbitrap (Makarov, 2000)) are of great utility, allowing measurement of greater than 20,000 metabolites in biological

42.2 High‐Resolution Metabolomics Genome‐wide association studies (GWAS) suggest that only 15–20% of diseases have a strong genetic component (Wild, 2005), with the remaining 80–85% likely having important exposome components (Rappaport and Smith, 2010). Consideration of chemicals of the exposome along with endogenous metabolism indicates that an extensive number of chemicals are present in biologic systems including pharmaceuticals, environmental chemicals, microbiome products, food additives, and non‐nutritional phytochemicals, as well as endogenous chemical species (e.g., carbohydrates, amino acids, peptides, lipids, nucleic acids) and dietary compounds (e.g., vitamins, minerals) (Jones et al., 2012). Quantitative data show that endogenous metabolites are often three

HRM workflow

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Pathway enrichment analysis Interactive networks

Metabolites of interest Pathways networks

20 0 –20 –40 0 –20 20 40 Component 1 (14.6%)

Mummichog, MetabNet

Figure 42.2 HRM workflow. HRM of high‐throughput, reproducible, and quantitative measurement by ultrahigh mass spectrometry with computational tool for data extraction and analysis allows to measure greater than 20,000 metabolites and associated metabolic pathways and networks. See references (Go et al., 2014b; Jones, 2016; Walker et al., 2016) for details.

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samples (Jones, 2016). In principle, one million or more chemicals can be measured (Uppal et al., 2016) including large numbers of low abundance metabolites.

42.3 High‐Resolution Metabolomics of Liver Mitochondria The mitochondrial metabolome within a specific cell type is a subset of an individual’s metabolic phenotype, including endogenous metabolites, chemicals from individual–environment interaction, and products derived from mitochondrial activities. Because of the tissue and cellular heterogeneities, the extent of variation of the mitochondrial metabolome is unknown; one can expect, however, that this is extensive. Extensive research will be needed to gain a substantial understanding of the spectrum of endogenous metabolites as well as content of microbiome metabolites and dietary and environmental chemicals. HRM was used in a pilot study of mouse liver mitochondria to gain an understanding of the spectrum of metabolites present in mitochondria (Roede et al., 2012). Mitochondria were isolated from male and female wild‐ type C57BL/6J mice and from mice overexpressing the mitochondrial protein thioredoxin‐2 (Trx2). Half of the mice were less than 6 months old and half were greater than 12 months old. For the Trx2 transgenic mice, human Trx2 (Chen et  al., 2002) was fused with a V5 epitope for detection of the transgene product (He et al., 2008). For mitochondrial isolation, livers were rapidly excised, homogenized in 22 mM mannitol, 70 mM sucrose, 2 mM Hepes (pH 7.4), and 1 mM EGTA, and mitochondria were isolated by differential centrifugation (Savage et al., 1991). Mitochondria were extracted with acetonitrile and analyzed by HRM with a dual chromatography method using anion‐exchange and reverse‐phase chromatography (Soltow et al., 2013). HRM results showing 6000–8000 metabolic features were detected for each column; many of the features were detected on both columns, and mitochondria were prepared with solutions containing biologic products that could contribute signals. Consequently, data were filtered to remove all features that were less than fourfold higher in mitochondria than in isolation medium and combined to yield a single set of 2127 metabolic features (Roede et al., 2012). High‐resolution matches to Madison Metabolomics Consortium Database and METLIN, followed by mapping to Kyoto Encyclopedia of Genes and Genomes (KEGG), showed matches to 745 out of 1485 metabolites in the human pathways, or approximately 50% of all metabolites. With the recognition that

more than 70% of the metabolic signals were filtered out because the levels were not fourfold greater than found in the sucrose–mannitol isolation solution, the results show that the mitochondrial metabolome broadly mirrors all aspects of metabolism. Matches to metabolites in  136 out of 154 KEGG pathways were present, with the top 10 metabolic pathways including arachidonic acid metabolism, amino sugar and pentose phosphate metabolism, purine and pyrimidine metabolism, porphyrin metabolism, steroid and steroid hormone biosynthesis, tyrosine metabolism, and neuroactive ligand receptor intermediate metabolism (Roede et  al., 2012). Comparisons of mitochondria from males  and females showed that hundreds of metabolic features differ, with  specific examples of amino acids (methionine, glutamate, leucine + isoleucine) higher in males and adenosine, amino‐octadecanoic acid, and sphinganine higher in females. No significant differences were detected for mitochondria from Trx2 transgenic mice, but partial least squares discriminant analysis (PLS‐DA) showed metabolic differences associated with 1‐carbon metabolism, including methylated nucleotides, folate, and choline. No significant metabolic differences were observed between mitochondria from mice less than 6 months compared with mice greater than 12 months (Roede et  al., 2012). Comparison of mitochondrial features and plasma features showed that 1425  were common, and these were used to select a list of 30 plasma markers of mitochondrial metabolism (Go et al., 2014b). This list includes substrates and products of mitochondrial enzymes in MitoCarta (Pagliarini et al., 2008), such as products of BCAA metabolism (3‐methyl‐2‐oxovaleric acid, α‐ketoisocaproate, α‐ketoisovalerate), indicators of mitochondrial NAD‐dependent metabolism (acetoacetate, β‐hydroxybutyrate), heme biosynthesis (δ‐aminolevulinate, protoporphyrinogen), coenzyme A biosynthesis (pantothenate), fatty acid metabolism (carnitine, multiple acylcarnitines), amino acid metabolism and the urea cycle (acetylglutamate, pyrroline‐5‐carboxylate, glutaric semialdehyde, saccharopine, kynurenine, fumarylacetoacetate), and 1‐carbon metabolism (choline, dimethylcholine, sarcosine) (Go et al., 2014b). Thus, the data clearly show that mitochondrial metabolism is extensively interconnected with all aspects of cellular metabolism and that mitochondrial metabolites are present in plasma for use as indicators of mitochondrial function in vivo. An important point, however, is that more than half of the metabolic features in mouse mitochondria had no database matches, indicating that mitochondria contain  many uncharacterized metabolites. The chemical nature of these features can be inferred from multiple database matches to dietary chemicals (leucocyanidin),

Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents: Integrated Omics for Visualization

drugs and drug metabolites (carbachol, lomefloxacin, N‐desmethyltrifluoperazine, quinaprilat), and environmental chemicals (dihydrorotenone, 7‐(acetyloxy)‐3‐(3‐ pyridinyl)‐2H‐1‐benzopyran‐2‐one) (Roede et al., 2012). There is also a possibility that other uncharacterized metabolic pathways are present in mitochondria and that metabolites derived from the intestinal microbiome are present. The results point to an important need to extend mitochondrial biology to a more complete definition of the mitochondrial metabolome.

42.4 Integration of Mitochondrial Redox Proteomics and Metabolomics: RMWAS We built upon this HRM analysis of mitochondria in research to investigate cadmium (Cd) effects on nonalcoholic fatty liver disease (NAFLD) (Go et al., 2015a). Cd contributes to diseases impacting many organ systems, for example, liver, kidney, lung, and others, but the underlying mechanisms are not well understood. Cd is an important environmental metal because it is present in food and accumulates in humans due to a 20‐year biologic half‐life. Previous studies showed that Cd affects activity and transcription of Trx reductase (Chrestensen et  al., 2000; Sakurai et  al., 2005) and that low environmental doses caused protein oxidation and stimulated inflammatory signaling (Go et al., 2013a, b). To determine whether Cd‐dependent oxidation of mitochondrial proteins was associated with metabolic effects, we exposed mice to Cd, isolated liver mitochondria, and measured the redox proteome and metabolome (Go et  al., 2015a). Redox states of liver mitochondrial proteins were measured by redox proteomics–mass spectrometry using isotope‐coded affinity tag (ICAT). Analyses of 2687 cysteine‐containing peptides showed that 1667 peptides from 657 proteins were detected in both control and Cd‐exposed samples. Forty‐six percent of the peptides were oxidized more than 1.5‐fold in mitochondria from Cd‐treated mice compared with controls. Pathway analyses showed 86 pathways affected by Cd, including 24 Cys residues in proteins of BCAA metabolism and 14 Cys in proteins for acylcarnitine, carnitine, and fatty acid β‐oxidation metabolism. Although no enzyme or transport data were available to suggest altered metabolic activities, protein oxidation is frequently associated with loss of activity. Thus, from this analysis, one can predict impact on BCAA and fatty acid metabolism. Consistent with this prediction, HRM analysis showed that Cd treatment altered metabolites in BCAA and fatty

acid metabolism pathways. HRM data included 4745 features, with 250 increased by Cd and 292 decreased by Cd after FDR correction. Pathway enrichment analysis showed significant associations with 29 pathways associated with increased or decreased features in the mitochondria (Go et al., 2014a). The results showed increases in isobutyryl‐CoA, succinyl‐CoA, acetyl‐CoA, and palmitoyl‐CoA, consistent with impaired branched‐chain fatty acid and β‐oxidation pathways. HRM analyses also identified several metabolic features associated with carnitine/acylcarnitine system supporting β‐oxidation, including carnitine, acetylcarnitine, propionylcarnitine, malonylcarnitine, palmitoylcarnitine, and stearylcarnitine. Cd‐dependent inhibition of the acylcarnitine system was confirmed in studies of 2H3‐palmitoylcarnitine uptake in mitochondria from Cd‐treated mice compared with control mice. Together with the redox proteomics data, the results show that Cd induces oxidation of specific Cys in proteins with associated changes in intermediates of mitochondrial fatty acid metabolism. This study provides straightforward methods to investigate drug‐induced mitochondrial oxidative stress and associated effects on metabolism. Additionally, the results suggest that low‐level environmental Cd impairs mitochondrial fatty acid metabolism. Such an effect could potentiate diet‐induced or drug‐induced fatty liver. HRM provides a functional measure of the consequences of oxidation in protein redox state so that a combined approach of redox proteomics and metabolomics (RMWAS) as described in the following text provides an efficient way to investigate central mechanisms of toxicity (Figure 42.3a). Continuous efforts have been made to advance our understanding of drug‐ and environmental agent‐induced toxicity and disease; a similar integrated omics strategy with transcriptomics and metabolomics (TMWAS) (Figure 42.3b) was applied and described after the section of RMWAS. Figure  42.4 illustrates an approach to combine redox proteomics and metabolomics data in developing a RMWAS. Data from Go et  al. (2014a) for redox proteomics and metabolomics effects of Cd in mouse liver mitochondria were used for redox proteomics × metabolome integration using partial least squares regression (PLSR) and network() function implemented in R package mixOmics (Gonzalez et  al., 2012; Le Cao et  al., 2009). The network() function in the mixOmics package was used to generate the association matrix and visualize the associations (Gonzalez et  al., 2012). The resulting visualization at a correlation threshold of 0.3 shows multiple central hubs of redox‐sensitive Cys residues in proteins with a very complex network of metabolic interactions (Figure  42.4a). At a correlation threshold of 0.5, the overall structure is largely preserved

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(a)

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Altered transcriptome

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Altered metabolome

Altered transcriptome

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Figure 42.3 Strategy of integrated omics approaches, RMWAS and TMWAS. Oxidants generated from drug and environmental agents affect redox states of proteome in a relatively short time frame. Oxidized protein redox state affects enzymatic and transport function leading to metabolic alterations (a, RMWAS). Similarly, such exposures could affect transcriptome and alter metabolome or vice versa depending on exposure time and dose (b, TMWAS).

(a)

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Proteins of BCAA metabolism Proteins of fatty acid β-oxidation

Peptidyl Cys Metabolites

Figure 42.4 Visualization of integrated redox proteomics and metabolomics (RMWAS). The data of Cd‐affected mitochondrial redox proteome and metabolome from the previous study by Go et al. (2014a) was used for RMWAS. The results of RMWAS were visualized by correlation threshold (|r| > 0.3 (a), |r| > 0.5 (b), |r| > 0.7 (c)). circle and rectangle represent oxidized protein peptide (peptidyl Cys) and altered metabolite in abundance by Cd, respectively. Adapted from Go et al. (2014a). Reproduced with Permission of Oxford University Press.

and shows two hubs of redox‐sensitive Cys with multiple peripheral associations (Figure  42.4b). At a correlation threshold of 0.7, only one central hub remained, with redox‐sensitive Cys in proteins associated with fatty acid

β‐oxidation, including carnitine acyltransferases and proteins directly involved in β‐oxidation (Figure 42.4c). Associated metabolites included acyl‐CoAs and acylcarnitines (Go et  al., 2014a). The more loosely connected

Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents: Integrated Omics for Visualization

cluster of Cys residues on the right were associated with  proteins involved in metabolism of BCAA and corresponding branched‐chain fatty acids (Figure 42.4c). The metabolites connected to both the central hub and this cluster included branched‐chain fatty acyl‐CoAs. Notably, the correlations were negative, suggesting that the branched‐chain fatty acyl‐CoAs may be negatively impacting the normal function of β‐oxidation.

42.5 Integration of HRM with Transcriptomics: TMWAS A similar integrated omics approach was used with transcriptomics and metabolomics (TMWAS) in a Parkinson’s disease model involving a combination of the herbicide paraquat (PQ) and fungicide maneb (MB) (Roede et  al., 2014). Epidemiologic studies showed an association of PQ and MB exposures with Parkinson’s disease, and experimental studies in neuroblastoma cell lines confirmed toxicity of PQ plus MB. Detailed understanding of mechanisms has been elusive, however, because the two chemicals did not appear to share common mechanisms. A study to investigate mechanisms of combined toxicity of PQ and MB was conducted in a neuroblastoma cell line with PQ and MB concentrations that individually caused 20% cell death and together caused 50% cell death. Cells were treated and samples were collected under conditions where there was minimal cell death. HRM data were filtered to 1,358 metabolites and transcriptome array data was analyzed for 30,869 transcripts. Bioinformatics analyses showed that MB alone had far greater effect on metabolites and transcripts than PQ. The effect of the combination of PQ and MB was far greater than either MB or PQ alone. Pairwise comparisons of arrays were created for transcripts and metabolites so that the correlations could be filtered for statistical criteria and ranked according to strength of correlation. The resulting TMWAS showed that MB alone had a very strong central hub of transcripts correlated with a large cluster of metabolites, while PQ alone had only a weak association structure with no clearly defined hub or significant organization. Importantly, the combination of PQ and MB created a second network substructure in addition to the large central structure associated with MB alone. The additional PQ + MB hub from the TMWAS contained four clearly discerned clusters of genes and associated metabolites. One of these clusters contained genes for two cation transporters and a cation transporter regulatory protein that is recognized as a proapoptotic protein. The cation transporters have previously been associated with enhanced mitochondrial accumulation

of PQ and manganese, thereby providing clear evidence that this transcript‐metabolite cluster represents a hub contributing to the mechanism of toxicity. Specifically, MB altered expression of transport systems that facilitated PQ transport and toxicity (Roede et al., 2014). The other three clusters included stress response genes and transporters linked to cytoprotective mechanisms. One of these was an early response cluster including heme oxygenase, a second was an antioxidant response cluster with increased expression of a transporter that supports GSH biosynthesis and cystine clearance, and a third cluster including PPARα and increased nonessential amino acid transport. Together, the results show that most of the responses to the toxic combination or PQ and MB were adaptive responses rather than toxicologic responses. Only a small subset of the overall response pattern reflected the underlying toxicologic mechanism of the combined neurotoxicity of PQ and MB. The results clearly establish the principle that combined toxicity can occur through network‐level interactions and show that TMWAS provides an effective way to investigate such complex mechanisms (Roede et al., 2014). Although the experiments were selected to measure metabolic and transcriptional changes before substantial effects on protein abundance occurred, one must be aware that in this type of study, the causal relationship is not necessarily clear. In the RMWAS described above a relatively short time of exposure was used so the oxidation of proteins could be inferred to be causal in the changes in the metabolome (Figure  42.3a). Similarly, a relatively short time frame was used for the TMWAS (Roede et al., 2014). For longer exposures in a TMWAS, however, metabolic effects could cause changes in transcription, or changes in transcription could cause changes in protein abundance with secondary effects on metabolism (Figure 42.3b). Hence, caution is required in assigning causal relationships.

42.6 Three‐Way Integration of Redox Proteomics, Metabolomics, and Transcriptomics to Create RMT Association Study for Mitochondrial Signaling in Manganese (Mn) Toxicity The 2‐way integration of metabolomics with redox proteomics or transcriptomics suggests that higher‐scale integrations may provide an even more powerful and sensitive way to map functional networks associated with mitochondrial redox signaling. Mn exposure in a neuroblastoma SH‐SY5Y cell model provides a model to test this development (Fernandes et al., 2016).

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Mn is an abundant mineral that is nutritionally essential in mammals and causes toxicity with excess exposure (Smith et al., 2016). The dose–response curve for effects of Mn exposure on neurodevelopment endpoints at 12 and 36 months of age showed that both high and low Mn exposure can negatively influence child neurodevelopment (Claus Henn et al., 2010). Mn is an essential cofactor for the mitochondrial antioxidant protein superoxide dismutase‐2 (SOD2), in addition to a diverse set of other enzymes required for biosynthesis and metabolism of lipids, carbohydrates, and amino acids (Burton and Guilarte, 2009; Takeda, 2003). The Food and Nutrition Board (FNB) of the Institute of Medicine established adequate intake (AI) levels of Mn at 2.3 and 1.8 mg Mn/ day, respectively, for men and women (Institute of Medicine (US) Panel on Micronutrients, 2001). Occupational toxicity from Mn is well documented (ATSDR, 2012a), and emerging evidence indicates that environmental Mn exposure from recycling waste, agricultural agents, fuel combustion, natural or anthropogenic contaminations of soil and water, and contaminated foods, infant formulas, food and nutritional products can also pose a threat in the general population (ATSDR, 2012a; Golub et al., 2005; Loranger et al., 1994; O’Neal and Zheng, 2015; Roede et  al., 2011). Excess Mn exposures cause cognitive and behavioral deficits in a  Parkinson’s disease‐like neurological syndrome (Bouchard et  al., 2011; Kwakye et  al., 2015; Menezes‐ Filho et al., 2011; Myers et al., 2009). Neurological effects of occupational Mn are well documented by neurobehavioral tests of cognition, mood, and neuromotor activities (Beuter et al., 1999; Bouchard et al., 2005; Lucchini et  al., 1995; Standridge et  al., 2008; Wasserman et  al., 2006). Mn‐induced neurotoxicity involves oxidative damage, mitochondrial dysfunction, and apoptotic cell death (Anantharam et  al., 2002; Galvani et  al., 1995; Gavin et al., 1992; Maddirala et al., 2015; Milatovic et al., 2009; Oubrahim et  al., 2001; Yoon et  al., 2011; Zhang et al., 2004). Extrapolation of risks to the general population is difficult, however, and an interim guidance value for Mn, 0.16 mg/kg/day (ATSDR, 2012a), was set to be consistent with the upper limit of exposure set by the FNB. Importantly, the interim guidance maximum intake level of 11.2 mg/day for a 70 kg man is less than fivefold higher than the AI level. This narrow fivefold range between adequate and toxic intake levels emphasizes needs to understand the most critical functional deficits from Mn insufficiency and most sensitive functional disruptions from excess. Mn concentrations in cells and human brain samples have been well characterized (Bowman and Aschner, 2014), enabling relevant dose–response studies to be performed with cell culture. Importantly, these studies  demonstrate enhanced oxidant production and

apoptosis in HeLa cells treated with 0.5–2 mM MnCl2 for 24 h (Oubrahim et al., 2001), increased oxidant production and decreased ATP in SH‐SY5Y cells treated with 0.8 mM MnCl2 for 24 h (Maddirala et  al., 2015), inhibition of mitochondrial complex I in PC12 cell cultures (Galvani et al., 1995), and inhibition of ATP synthesis in isolated mitochondria in vitro (Gavin et al., 1992). A Mn dose–response study showed that additions of Mn in the range of 1–10 μM to the culture medium for SH‐SY5Y cells resulted in physiological cellular Mn levels (≤16 ± 1 ng/mg protein) (Fernandes et  al., 2016). These concentrations stimulated mitochondrial respiration, while concentrations in the range of 50–100 μM cellular Mn (toxicological; >37 ± 2 ng/mg protein) inhibited mitochondrial respiration and caused cellular thiol oxidation. Over the entire range of Mn concentration, Mn did not increase mitochondrial superoxide amount as measured by aconitase activity or MitoSOX fluorescence intensity. In contrast, Mn‐treated cells had increased H2O2 production over the entire range as measured by MitoPY1. The results show that controlled Mn exposure provides a useful cell manipulation for toxicological studies of mitochondrial H2O2 signaling. This model establishes appropriate conditions to test tools for  study of mitochondrial oxidant signaling that are mediated through redox proteomics, metabolomics, or transcriptomics mechanisms. The principles for development of an integrated redox proteomics, metabolomics, and transcriptomics tool are derived from the concept of a targeted metabolome‐ wide association study (MWAS), originally used in a study of phenylalanine metabolism, with visualization by Manhattan plots (Go et al., 2015c), and further developed into a software tool, MetabNet, with visualization using Cytoscape (Uppal et  al., 2015). An important capability of MetabNet is illustrated in Figure  42.5, which shows that global network structures are visualized at low stringency for correlation and subnetwork structures can be progressively visualized at greater stringency. This approach allows arrays of omics data to be regressed against any quantitative parameter, such as Mn concentration or mitochondrial H2O2 production rate. In principle, one can observe multiparameter interaction structures by combining multiple omics arrays. A prototype tool for visualization of multi‐omics integration is shown in Figure 42.6. By creating an array with pairwise tests for correlation among arrays, one can select top correlations, ranked by r and/or filtered by statistical criteria. With this approach, central hubs are readily visualized to connect metabolome and transcriptome response structures to redox proteome variations or proximal signaling events such as Mn‐induced H2O2 production by mitochondria.

Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents: Integrated Omics for Visualization ∣r∣ > 0.3

∣r∣ > 0.5

∣r∣ > 0.7

Hubs: metabolites of interest Positively or negatively associated metabolites

Figure 42.5 Network visualization capability of targeted MWAS by MetabNet. A capability of MetabNet (Uppal et al., 2015) is illustrated showing progressive visualization of subnetwork structures from the global network structures by increasing stringency of correlation threshold (|r| > 0.3 → |r| > 0.5 → |r| > 0.7).

Metabolite Gene Protein Environmental agent Negative interaction Positive interaction

Figure 42.6 Visualization of multi‐omics integrations. A conceptual representation of network structures resulted from multi‐omics approaches (redox proteomics × metabolomics × transcriptomics).

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42.7 Integrated Omics Applications in Mitochondrial Metabolic Disorder: Fatty Liver, Diabetes, Obesity, and Neurodegenerative Diseases The availability of integrative omics tools allows new ways to study complex, interorgan disease processes, such as drugs, environmental agents, or dietary factors impacting mitochondria in different tissues. Useful applications for humans, however, are likely to require extensive data due to the heterogeneity of populations. For instance, in Figure  42.7 the redox metabolome is combined with clinical phenotype measures and HRM analyses for 500 individuals. The resulting network

structures at high stringency show separate hubs linked to the more reduced counterpart, GSH, and the more oxidized counterpart, cystine. Notably, by using MetabNet to obtain the broader associated metabolic network structure and Mummichog to test for pathway enrichment, one finds that the plasma redox metabolome is tightly linked to mitochondrial pathways of the citric acid cycle, BCAA metabolism, the urea cycle, and other central metabolic pathways. These data show that the principles developed from cell culture and animal models can be directly applied to human research to extend knowledge of complex biologic functions. The results demonstrate an opportunity to advance understanding of human disease by development of principles and tools through carefully controlled studies in experimental models. For instance, the challenge to

Figure 42.7 Application of integrated omics approaches in monitoring human health and disease. Application of multi‐omics approaches in clinical measurement is illustrated. Metabolic features positively or negatively associated with redox factors (cysteine (Cys), cystine (CySS), glutathione (GSH), glutathione disulfide (GSSG), redox potential of glutathione (EhGSSG), mixed disulfide (CySSG), total cysteine (Cys + CySS), total glutathione (GSH + GSSG)) and clinical variables (smoking status, gender, high‐density lipoprotein (HDL)) are analyzed from 500 healthy individuals.

Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents: Integrated Omics for Visualization

understand variable contributions of multiple low‐level environmental exposures to human health is considerable because of the variability of thousands of low‐dose exposures in the presence of many behavioral, dietary, and drug exposures with similar or greater impacts. Low‐dose Cd potentiation of airway hyper‐reactivity provides an effective example. Airway hyper‐reactivity contributes to asthma and other diseases impacting the lungs. Addition of Cd to drinking water at levels that result in lung Cd levels similar to values in nonsmoking, non‐occupationally exposed individuals caused an increase in reactivity measured by methacholine challenge (Chandler et  al., 2016). Gene expression arrays with validation by real‐time PCR showed that neuronal receptors represented by enriched olfactory, glutamatergic, cholinergic, and serotonergic gene sets were major inducible targets of low‐dose Cd. Olfactory receptor gene sets were the most enriched, and these regulate chemosensory function and airway hypersensitivity. HRM showed that metabolites in pathways of glutamatergic (glutamate), serotonergic (tryptophan), cholinergic (choline), and catecholaminergic (tyrosine) receptors were also increased in the lung tissue. The glutamate receptor GRIN2A was found to be increased by Western blotting. Thus, the results clearly show that integrated omics can be very powerful to identify contributions of low‐dose exposures to disease mechanisms. The availability of integrated omics methods as described above raises the possibility that animal models can be used to address drug and environmental contributions to multimorbidities. Barnett et al. (2012) showed that most human diseases do not occur in isolation, but instead, multimorbidity is the most common disease process. By performing controlled low‐level exposures in animal models, detailed analyses can be used to create network structures, which can be used to interpret complex human data. As an example, one can consider potential benefits from integrated omics studies of interorgan toxicities from low‐level Cd exposure. NAFLD, defined by hepatic steatosis without significant alcohol consumption, steatogenic medication, or hereditary disorders, includes a spectrum of disease ranging from a relatively benign deposition of fat (NAFL) to fat deposition with inflammation and fibrosis, termed nonalcoholic steatohepatitis (NASH) (Chalasani et  al., 2012). NAFLD is common among Americans (28.8 million in 1988–1994 NHANES III (Lazo et  al., 2013)) and is generally associated with obesity, diabetes mellitus, and dyslipidemia. Because obesity and diabetes are increasing, there is an expectation for a continuing increase in NAFLD in the coming decades (Michelotti et  al., 2013). NAFLD is associated with higher overall and liver‐related mortality in the general US population, and liver disease is a significant cause

of death among persons with NAFLD (Ong et al., 2008). Of particular concern, the prevalence of suspected NAFLD has more than doubled over the past 20 years in adolescents (Welsh et al., 2013), potentially foreboding a health crisis in coming decades. Low‐level Cd causes fatty liver in mice, and human epidemiological data also show that after multivariate correction for other factors such as smoking, the top quartile of exposures in NHANES III (cutoffs 0.65 and 0.83 µg/g urinary creatinine for men and women, respectively) was associated with increased NAFLD, NASH, and risk of liver disease mortality (Hyder et  al., 2013). Environmental contamination of food is the major source of Cd exposure for nonsmokers; daily intake of Cd for adult males and females is about 0.35 and 0.30 µg/ kg, respectively (ATSDR, 2012b). The European Food Safety Authority recommended a tolerable intake of 2.5 µg/kg/week (Authority, 2011), or 0.35 µg/kg/day, which approximates average Cd intake by US adults. Cd is not effectively excreted and accumulates in humans (10–35 years half‐life) (Goyer, 1997; Peters et al., 2010). The integrated redox proteomics and metabolomics data described above show that Cd impacts liver mitochondrial function and dyslipidemia. Evidence from several studies implicates mitochondrial dysfunction in NAFLD. Cd also contributes to pancreatic islet dysfunction, also likely due to mitochondrial dysfunction (Chang et  al., 2013). The frequent occurrence of NAFLD with obesity and type 2 diabetes suggests common underlying mechanisms. Application of integrated omics methods to plasma and multiple tissues (e.g., liver, pancreas, and adipose tissue) could provide the information whether low‐dose Cd has similar impact. Studies of mitochondria from these tissues in Cd‐treated mice could then be used to define common plasma markers reflecting sensitive redox proteomics, metabolomics, and transcriptomics responses. The results would considerably enhance understanding of potential multimorbidities linked to a common environmental agent. Such an approach could also be useful for drug‐induced mitochondrial toxicities and extended to studies of aging and other at‐risk conditions.

42.8

Summary and Perspective

Mitochondria are the powerhouse of most mammalian cells, and this has often led to a simplistic view that mitochondrial metabolomics can be assessed by measurement of a relatively small number of respiration‐ dependent metabolites. Energy production is only a fraction of the range of metabolism and function supported by mitochondria, and a broader view is needed to effectively address the contribution of mitochondrial

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dysfunctions to disease. Plasma is a readily accessible body fluid, but its use to measure disease processes in specific organs is often limited by its interaction with all organ systems. On the other hand, mitochondria are present in most tissues, and toxic effects on mitochondria may simultaneously occur in many tissues. HRM of liver mitochondria show that thousands of metabolites are present, and conservative comparison of plasma and liver enzymes and metabolite contents provides a short list of candidate plasma markers of mitochondrial function. Studies of low environmental levels of Cd, Mn, and other environmental chemicals show disruption of mitochondrial function. Innovative approaches to combine HRM data with redox proteomics and transcriptomics provide a comprehensive approach to study mitochondrial signaling in response to dietary and environmental stresses. The approach has been found to be useful to measure both toxic and adaptive hub responses, and this has important implications for all aspects of drug and environmental mitochondrial toxicities. Prototype software has been developed to enable combined RMTWAS to detect mitochondrial oxidative

signaling pathways. Such software could be made available as an online tool to facilitate use for sensitive detection of mitochondrial signaling in response to environmental exposures (Uppal et  al., https://kuppal. shinyapps.io/xmwas/). The progress in application of integrated omics approaches to understand toxicologic mechanisms suggests that the approach can be extended to complex interorgan disease processes, such as NAFLD linked to obesity, type 2 diabetes, and neurodegeneration. Such application to controlled mouse models with simultaneous studies of different organ systems could considerably enhance understanding of  the contribution of environmental exposures to multimorbidities.

Acknowledgments The authors acknowledge support by NIH grants  R01ES023485, R21ES025632, P20HL113451, P30ES019776, 1U2CES026560, U24DJ112341, and OD018006.

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Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents: Integrated Omics for Visualization

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43 Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans Laura L. Maurer, Anthony L. Luz, and Joel N. Meyer Nicholas School of the Environment, Duke University, Durham, NC, USA

CHAPTER MENU 43.1 43.2 43.3 43.4 43.5

What We Know about Pollutant Influences on Mitochondria, 655 Advantages of the Caenorhabditis elegans Model, 660 Limitations of C. elegans for Studying Mitochondrial Toxicity, 663 Methods for Assessing Mitochondrial Toxicity in C. Elegans, 667 Environmental Mitotoxicants and C. Elegans: Unique Discoveries and Emerging Roles, 670 References, 673

43.1 What We Know about Pollutant Influences on Mitochondria 43.1.1

Introduction

A growing area of concern, and one that has been informed by pioneering pharmaceutical research, is the possibility that environmental pollutants or other environmental stressors may also cause mitochondrial toxicity (Brunst et al. 2015; Caito and Aschner 2015; Meyer et al. 2013). Although environmental pollutants rarely reach concentrations in people that are comparable with those achieved as part of a drug dosing regimen, there is cause for concern. First, there are clear cases of pollutants that are mitotoxicants, as discussed in Section 43.1.2. Second, there are very large numbers of pollutants—close to 100,000—that are in the jurisdiction of the US Environmental Protection Agency (EPA) (Bell and Edwards 2015; Judson et  al. 2009), and many can be detected in people (Porta 2012, Park et  al. 2014, and chapter 47). Third, chemicals intended for industrial use, or produced accidentally, are not tested for toxicity nearly as rigorously as are drugs. If we were slow to realize the mitochondrial impacts of drugs—which are tested relatively carefully in preclinical and clinical trials, and

whose use and effects are carefully tracked and therefore easier to study epidemiologically—what pollutant‐induced mitochondrial impacts might we be missing? There are a number of theoretical reasons why we might expect mitochondria to be vulnerable to toxicant exposure, as recently reviewed (Caito and Aschner 2015; Meyer et al. 2013; Shaughnessy et al. 2014). These include: 1) The lipid‐rich double membrane, which attracts lipophilic compounds 2) The presence of uptake pathways (channels and transporters) for essential metals such as calcium that may also take up toxic metals (Bridges and Zalups 2005) 3) The ability of compounds that are lipophilic but ionizable in the relatively high pH of the matrix to therefore be bioaccumulated in the matrix (Ross et al. 2005) 4) The normal production of ROS by the electron transport chain, which can be increased greatly under conditions such as inhibition of electron transport that hyper‐reduce the ETC (Drose and Brandt 2012; Murphy 2009) or by the presence of redox cycling agents that can be reduced in the mitochondria (e.g., (Lopert and Patel 2016; Monks et al. 1992; Robb et al. 2015), but note that many of these chemicals can also redox cycle in the cytosol)

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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Pb2+, Mn2+, Cd2+

ETC dysfuntion can result in decreased ATP, increased ROS, and altered membrane potential

Nucleus

Ca2+ transporter

Proximity to ETC and lack of histones may increase vulnerability

Pb2+

Cross-talk with nucleus via calcium signaling, apoptotic, retrograde, and epigenetic pathways

Metal ions can enter via Ca2+ channels and replace metal cofactors, bind to proteins, or redox cycle

Electron transport chain I

III II

IV

V

ROS

Multiplicity of mtDNAs is protective but varies by cell type and developmental stage, creating windows of vulnerability

ATP Nucleoid

Pb2+

H+ H+ Intermembrane space pH ~ 6.9 H+ H+ Outer membrane

Inner membrane

– Mitochondrial cytochrome P450 may activate HO accumulated OH Benzo(a)pyrene Benzo(a)pyrene environmental 7.8 diol–9.10 toxicants epoxide O

Rich phospolipid bilayer attracts lipophilic toxicants

– –

– Pb2+

EtBr+

Matrix pH ~ 8, also negatively charged due to H+ pumping for oxidative phosphorylation, resulting in accumulation of cationic metals and lipophilic amphiphilic compounds

Figure 43.1 Theoretical reasons for mitochondrial sensitivity to exposures to environmental chemicals. Meyer et al. (2013). Reproduced with permission of Oxford University Press. (See insert for color representation of the figure.)

5) The presence of cytochrome P450 (CYP450) enzymes that can activate chemicals that are nonreactive in their “parent” form (see Chapter 7) 6) mtDNA vulnerabilities resulting from close association to sites of ROS generation and absence of some key DNA repair pathways (Alexeyev et  al. 2013; Copeland and Longley 2014; Meyer et  al. 2013; Scheibye‐Knudsen et  al. 2015; Van Houten et al. 2016) 7) The presence of large amounts of endogenous molecules that may exacerbate toxic reactions, such as iron (which can participate in Fenton chemistry) and cytochrome c (which can trigger apoptosis), and easily oxidized lipids, such as cardiolipin, which can mediate cytochrome c release and thus apoptosis (Czerniczyniec et al. 2013; Fariss et al. 2005) However, it should be noted that in some cases, these processes may be protective, for example, resulting in appropriate apoptosis, mitophagy, or activation of antioxidant or other ROS‐induced gene regulation

(Kagan et al. 2015) (Figure 43.1; reprinted with permission from (Meyer et al. 2013)). In addition to these theoretical considerations, recent empirical evidence from screening efforts from the US EPA and National Toxicology Program (NTP), as well as a growing body of academic research, suggests that there are indeed many pollutants that affect mitochondria. Mitochondrial toxicity is rapidly emerging as a mode of action of many toxicants (Brunst et al. 2015; Meyer et al. 2013; Moreira et al. 2011; Pereira et al. 2009; Sabri 1998; Shaughnessy et al. 2010) and is one of the most common outcomes of in vitro toxicity screening efforts, including those of the NTP (Attene‐Ramos et al. 2013, 2015; Houck et  al. 2009; Shah et  al. 2015; Wills et  al. 2015). In this chapter, we summarize some of what is known about environmental mitotoxicants and mechanisms of pollutant‐induced mitochondrial dysfunction, outline some of the challenges and factors that complicate the research community’s ability to address this concern, and discuss the use of the nematode model organism Caenorhabditis

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

Table 43.1 Some important mechanisms of mitochondrial toxicity and representative environmental pollutants. Mechanism of mitochondrial toxicity

Representative chemical or mixture

Mitochondrial DNA damage

Benzo[a]pyrene and some additional polycyclic aromatic hydrocarbons, mixtures such as creosote and air pollution, ultraviolet radiation, some aflatoxins, prooxidants such as paraquat

Protein inhibition (electron transport chain complex and other proteins)

Arsenite, lead, mercury, methylmercury, silver, cadmium, rotenone, pyraclostrobin, 3‐nitropropionic acid

Redox cycling

2,4,6‐Trinitrotoluene, pentachlorophenol, copper, iron, manganese, various quinones

Mitochondrial uncoupling

2,4‐Dinitrophenol, pentachlorophenol, chlorfenapyr, arsenate

Note that each “mechanism” listed could in fact be further subdivided: for example, there are multiple kinds of DNA damage, and inhibition of different proteins has very different effects. Similarly, uncoupling can occur via proton transport by compounds like pentachlorophenol across the inner mitochondrial membrane or by ATP synthase‐mediated addition of arsenate to ADP, generating an unstable molecule in which the ADP‐ arsenate bond quickly breaks; in both cases, but by different mechanisms, oxygen consumption is uncoupled from ATP production.

elegans to study mitochondrial toxicity, including a review of the mitochondrial biology of this organism, mitochondrial assays available, strengths and limitations of C. elegans, and select mitochondrial toxicity discoveries.

43.1.2

Environmental Mitotoxicants

There are a number of very well‐known and specific mitochondrial poisons that exist in the environment, such as cyanide, carbon monoxide, and rotenone, which are discussed in general toxicology textbooks and do not need to be listed again. Perhaps the most interesting thing about them is the fact that many are plant, bacterial, or fungal toxins that target mitochondria via  a variety of classes of chemical structure (e.g., rotenoids, antimycin A, cyanogens, oligomycin, monofluoroacetic acid, etc.) and mechanisms of toxicity (in these cases, inhibitors of ETC complexes I, III, IV, and V and the tricarboxylic acid (TCA) cycle, respectively) (Acamovic and Brooker 2005; Harborne 1988). The fact that multiple species throughout evolution have independently developed different toxicants that target mitochondria provides strong evidence for the sensitivity of organisms to mitochondrial toxicity. Most of the toxins listed in the preceding paragraph are highly specific—so much so, in fact, that many are used in assays of mitochondrial function (e.g., Chapter  15)! However, relatively few cause toxicity in humans, except in unusual cases. Of greater human health concern is the very large number of chemicals to which we are exposed on a regular basis (Lioy and Rappaport 2011; Rappaport 2012; Rappaport et al. 2014) (see Chapter  41 of this volume for a discussion of the human “exposome”). Many of these may have some mitochondrial effects, but we anticipate that relatively

few will be truly specific in the sense that they target only mitochondrial function. For example, in Table 43.1, we have listed a number of important mechanisms of mitochondrial toxicity, along with representative environmental contaminants (note this is meant to be an illustrative, not comprehensive, list of chemicals and of mechanisms). Of these, 2,4‐dinitrophenol is a specific mitochondrial uncoupler (Grundlingh et al. 2011), but many clearly have extramitochondrial targets and/or multiple different mitochondrial targets. For instance, metabolites of benzo[a]pyrene and aflatoxin B1 cause a high level of DNA damage in the mitochondrial genome, and such damage cannot be repaired (in contrast to nuclear DNA damage), yet they and compounds that cause similar kinds of DNA damage clearly have very important effects via nuclear DNA damage, including mutations and carcinogenesis (Luch 2005; Smela et al. 2001). This is also true of shortwave ultraviolet (UV) radiation (Kasiviswanathan et  al. 2012; Kozma and Eide 2014; Tulah and Birch‐Machin 2013). Similarly, arsenic targets mitochondria (Prakash et al. 2016) and inhibits not only multiple mitochondrial enzymes (Bergquist et  al. 2009; Hosseini et al. 2013; Naranmandura et al. 2011) but also many non‐mitochondrial enzymes (Kitchin and Wallace 2008). The same is true of other metals that act by binding sulfhydryl and selenyl residues and affecting protein function, such as methylmercury (Antunes dos Santos et al. 2016)—and may in fact be true of all such metals. Arsenic is also an interesting example, as trivalent arsenicals act by protein inhibition, while pentavalent arsenate uncouples ATP production from oxygen consumption by mimicking phosphate during ATP production, resulting in an unstable ADP‐arsenate bond that quickly breaks (Nemeti et al. 2010). Manganese is another example of an element that is mitotoxic via a wide range of mechanisms, including dopamine oxidation resulting in quinone formation, ETC inhibition, metal substitution, and altered

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calcium homeostasis (Farina et  al. 2013). Dioxin exerts the bulk of its toxic effects via binding to the aryl hydrocarbon receptor (AhR), and it is now clear that one of the many outcomes of AhR activation is mitochondrial toxicity (Shen et al. 2005). Thus, mitochondria are likely one (but not the only) target of many other AhR agonists. This list could go on; the point we wish to emphasize is that the mitochondrial impacts of many chemicals can be important, even when the chemicals do not cause effects exclusively in mitochondria. This does, of course, complicate dissection of mechanisms of action. It would make little sense to try to summarize all the pollutants for which there is some evidence of mitochondrial effects. This would be a long list, yet would be out of date very quickly given how quickly research in this area is growing. We also note that in many cases, the evidence for mitochondrial toxicity as a primary effect, as opposed to a secondary effect resulting from toxicity in another cellular compartment, is weak (e.g., a decrease in membrane potential was observed, but it was not clear whether this was the primary effect of the exposure or whether it resulted from toxicity initiated at another cellular site). Finally, thousands of new chemicals are introduced to the environment annually, and in some cases entirely new classes of materials, such as nanomaterials, are developed. Therefore, any strategy we choose should address these as well. We now move to a discussion of strategies for testing potential mitotoxicity of environmental exposures and stressors. 43.1.3 How Should We Prioritize Environmental Chemicals and Stressors for Mitotoxicity Testing? How should we prioritize which of the approximately 100,000 pollutant chemicals to test for mitochondrial effects? One approach is theoretical; for example, we have proposed that silver nanoparticles, designed to target microbes that are phylogenetically related to mitochondria, may therefore also target mitochondria (Maurer and Meyer 2016). Another approach is high‐ throughput screening, which we address in more detail later on. A final approach is to focus on chemicals or chemical mixtures that are used or occur at high levels, or to which very large numbers of people are exposed. For instance, we have investigated mitochondrial impacts of arsenic in part because arsenic exposure is so widespread (described as constituting the “greatest mass poisoning in human history” (Sen and Biswas 2013)) and methylmercury because of high levels of exposures resulting ultimately from burning of fossil fuels and small‐scale gold mining (Futsaeter and Wilson 2013). Among the greatest environmental health impacts are those associated with air pollution (Brauer et  al. 2012;

Gall et al. 2013; Smith et al. 2014). Both cigarette smoke (Ballinger et al. 1996; Fuller et al. 2012) and air pollution (Clemente et  al. 2016; Grevendonk et  al. 2016) cause mitochondrial toxicity, and in fact, in both cases, there is evidence that multiple different components of these very complex mixtures independently affect mitochondria, including particulate matter (PM) (especially ultrafine or “nano”‐PM) (Li et al. 2015; Soberanes et al. 2009; Xia et al. 2004, 2007), polycyclic aromatic hydrocarbons (Backer and Weinstein 1980; Jung et  al. 2009), acrolein (Mohammad et  al. 2012), quinones (Knecht et al. 2013; Palmeira and Wallace 1997; Xia et al. 2004; Zhu et  al. 1995), 2,4‐dinitrophenol (Belloli et  al. 2006; Harrison et al. 2005; Tremp et al. 1993), 2‐ethylpyridine (Mansoor et  al. 2014), nitrosamines (Bodhicharla et  al. 2014; Braunbeck et al. 1992; Stepanov and Hecht 2009), and multiple metals (Cannino et al. 2009). Pesticides are widely used environmental chemicals, and there is evidence that many pesticides target mitochondria, including some organophosphates and organochlorines (Du et  al. 2015; Gupta et  al. 2006; Karami‐Mohajeri and Abdollahi 2013; Lakroun et  al. 2015) as well as well‐ studied examples such as rotenone and paraquat. Chemicals of emerging concern such as flame retardants (Behl et al. 2015; Jarema et  al. 2015; Oliveri et  al. 2015), triclosan (Shim et al. 2016; Weatherly et al. 2016), and newer‐generation pesticides (Regueiro et  al. 2015; Romero et  al. 2010) have also been associated with mitochondrial toxicity, although the evidence is less comprehensive at this time. One difficulty is that the extent of exposure is not always well known; for example, there is exposure data (even defined very broadly, i.e., production volume) for less than 20% of the approximately 100,000 chemicals that fall under EPA’s mandate (Egeghy et  al. 2012)! Another important challenge is understanding potential synergistic effects of mitochondrial toxicants (reviewed by Cedergreen (2014)), especially given the fact that mechanisms of mitochondrial toxicity can be quite disparate (Table 43.2). 43.1.4 Mechanistic Organization of Mitotoxic Effects As we carry out mitotoxicity testing, we propose that just as gene ontologies have been used successfully to organize genes and gene products by biological roles, it will likely be helpful to organize chemicals by how they affect mitochondria. There are multiple ways in which mitochondrial “mechanisms of toxicity” could be organized. In Table 43.1, we used molecular‐level events, but another very logical approach would be to focus on cellular or biological processes (e.g., ATP production, heme synthesis, calcium buffering, apoptosis, etc.). The recent advent of the “adverse outcome pathway” approach in toxicology

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

Table 43.2 Cellular and tissue‐specific exposure route differences in physiological systems targeted by environmental mitotoxicants in mammals and Caenorhabditis elegans. Mammalian

Nervous system (inhalation, ingestion, dermal exposure routes)

C. elegans

Major tissues

Tissue‐specific cellular components

Major tissues

Brain

Neurons

Nerve ring

Spinal cord

Astrocytes

Tissue‐specific cellular components

Neurons Sensory and synaptic glia (glial system reviewed by Oikonomou and Shaham (2011))

Oligodendrocytes Microglia Schwann cells

Circulatory system (inhalation, ingestion, dermal exposure routes)

Heart

Cardiomyocytes

Blood vessels

Epicardial cells

Respiratory system (inhalation exposure route)

Lungs

Type I and II pneumocytes

Bronchi

Nonciliated bronchiolar ciliary cells

Trachea

Pharynx (developmentally similar to vertebrate heart (Haun et al. 1998)) N/A

Pharynx

Larynx Pharynx Mitochondrial toxicity can manifest as a result of multiple exposure routes and target tissues. However, there are important physiological differences between humans and C. elegans in the three “systems” discussed in the text as mitotoxicant targets. This table describes some of the constitutive tissues and specialized cell types present within these exposure routes and target tissues in mammals that are absent in C. elegans.

offers another approach. AOPs offer a way to group chemicals based on common action and organismal outcome (Ankley et al. 2010; Villeneuve et al. 2014), which may be helpful for testing and regulating a very large number of chemicals (Edwards et  al. 2016; Villeneuve 2015). However, work on mitochondrial AOPs is nascent, with only one relatively narrowly defined (“a consequence of inhibition of the respiratory chain leading to oxidative stress”) “mitochondrial dysfunction AOP” listed on the Wiki (https://aopwiki.org/wiki/index.php/Event:177). Understanding these mechanisms is critical to logically organize data, to inform us regarding which assays might be most predictive of in vivo toxicity by facilitating mechanism‐ based extrapolation, and, possibly, to develop biomarkers of mitochondrial toxicity in people. These would be of great use in epidemiological studies, which provide a critical complement to laboratory‐based toxicity studies (Adami et al. 2011). Biomarkers are particularly useful in epidemiological studies of exposure to environmental chemicals as opposed to drugs, because exposure is typically much harder to quantify than it is for drugs that are prescribed and used relatively carefully. Proposed biomarkers include oxidized lipids (Roede and Jones 2010), mtDNA damage (Gonzalez‐Hunt et  al. 2016; Haugen et  al. 2010; Sanders et  al. 2014), mtDNA copy number (Brunst et al. 2015; Gebhard et al. 2014; Gonzalez‐Hunt

et al. 2016; Kim et al. 2014), mtDNA methylation (Brunst et  al. 2015), metabolomics (Chapter  27), and altered energetics (Chacko et al. 2014). Incomplete understanding of the biological regulation and significance of some of these outcomes remains challenging; for example, exposures have been reported to both increase and decrease mtDNA copy number, and the biological impact of methylation in the mtDNA remains unclear. 43.1.5 Testing Environmental Chemicals and Stressors for Mitotoxicity: Approaches and Considerations Finally, what tests should we actually conduct? This text and others (Pon and Schon 2007) offer a wide range of mitochondrial assays. However, there are far too many environmental chemicals to permit careful mechanistic testing of them all. Current high‐throughput screening efforts utilizing cell culture are focused on mitochondrial membrane potential and ATP content (Attene‐ Ramos et  al. 2015), with follow‐up in some cases by examination of oxygen consumption (Attene‐Ramos et al. 2013) and/or medium‐throughput, whole‐organism work using organisms such as C. elegans and Danio rerio (Behl et al. 2015). In some cases primary cell lines have been used (Wills et  al. 2015), which have much

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more normal mitochondrial function than most immortalized lines. Not all have incorporated advances in understanding from the pharmaceutical field, such as the use of galactose in cell culture (Marroquin et al. 2007 and chapter 20). Ideally, assays should permit testing in the context of normal intercellular interactions, which can modulate or even mediate toxic effects. In addition, assays should incorporate important variables that can modify sensitivity (reviewed by (Meyer et  al. (2013)). These include developmental stage, with early and late life postulated as sensitive windows of exposure; cell type and tissue differences, with post‐mitotic and high‐energy use cells potentially at most risk; genetic background with individuals with differences in genes involved in mitochondrial function or mitochondrial homeostasis likely at most risk (mitochondrial toxicity is likely to be significantly exacerbated in ~1 in 4000 persons who suffer from a mitochondrial disease (Chinnery et al. 2004; Dimauro and Davidzon 2005; Howell et al. 2005; Wallace 2005)); and physical condition including exercise, diet, and disease. A further critical distinction is the difference between short‐term high‐level poisoning‐type mitotoxicity and longer‐term low‐level exposures that could be chronic or intermittent or may occur at particularly critical developmental stages. We argue that the latter are more likely to be of importance to chronic and degenerative diseases, which are the major health threat of the future. For example, mitochondrial dysfunction may be important in neurodegenerative diseases (Farina et  al. 2013; Kaminsky et al. 2015; Kubik and Philbert 2015), cancer (Robey et al. 2015; Salem et al. 2013), diabetes and metabolic syndrome (Kim and Lee 2014 and chapter 49), and cardiovascular disease (Finsterer and Ohnsorge 2013). While this is a relatively new area of inquiry, we and others have found that exposures leading to altered mitochondrial function early in development may lead to lifelong effects on mitochondrial function and related outcomes (Ditzel et al. 2016; Leung et al. 2013b; Wood et al. 2015), which may thus form an important subset of the health impacts of developmental exposures that can cause adult diseases (Birnbaum and Miller 2015). There is also evidence for multigenerational effects of mitochondrial exposures, and potentially even transgenerational effects of mitochondria dysfunction that are presumably mediated by epigenetic changes (Saben et al. 2016), which may themselves in some cases be causally related to mitochondrial function (Audano et  al. 2014; D’Aquila et  al. 2015; Shaughnessy et  al. 2014). These changes may be both adaptive (“mitohormetic” is one term used to describe this process: (Naviaux 2014)) and maladaptive, depending on the context, and the potential for adaptation is itself likely affected by genetic background and timing of exposure.

There are multiple model systems available for mitotoxicity testing (many described in this text). In the succeeding text, we describe the strengths offered by C. elegans, a model system that combines relatively fast and affordable screening‐type toxicity tests in a full‐life history, in vivo model with powerful genetic and molecular tools for mechanistic work. We also address limitations of this model organism for mitochondrial toxicity, assays that are available, and some discoveries that have been made using C. elegans. We feel that no model system is sufficient by itself and hope that this chapter will facilitate the research community’s incorporation of C. elegans into a spectrum of mutually complementary model systems.

43.2 Advantages of the Caenorhabditis elegans Model 43.2.1

Introduction

First developed by Sydney Brenner over 50 years ago as a model to study developmental and neurobiology, the nematode C. elegans has since emerged as an in vivo model for toxicologists (reviewed in Leung et al. (2008), Hunt (2016), Tejeda‐Benitez and Olivero‐Verbel (2016)). This species’ small size (adults are ~1 mm in length), short developmental period (first larval stage to gravid adult in ~72 h) and lifespan (2–3 weeks), high reproductive rate (~300 offspring per hermaphrodite), ease of genetic manipulation, and low maintenance costs make C. elegans amenable to high‐throughput toxicity testing. Many of these same advantages also make this species an attractive model for investigating mitochondrial toxicity in vivo. An in vivo model is advantageous because it preserves developmental stage‐ and tissue‐specific differences in mitochondria, as well as intracellular signals typically lost in vitro, which is important as these signals can influence mitochondrial function. Although nematodes lack many of the well‐defined organs found in mammalian models, they do have many well‐defined tissues, including the cuticle, excretory system, gonad, hypodermis, intestine, muscles, neurons, and pharynx. These tissues can signal one another to control diverse biological processes such as mitochondrial metabolism, stress response, and aging (Bishop and Guarente 2007; Durieux et  al. 2011; Libina et  al. 2003; Taylor et  al. 2014), thus demonstrating the importance of investigating mitochondrial function in vivo. In the succeeding text, we further highlight some of the biological and genetic advantages that make C. elegans an excellent in vivo model for investigating mitochondrial toxicity.

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

43.2.2

C. elegans Biology

Over the past 50 years, a great deal has been learned about C. elegans development, cell signaling, reproduction, and many other biological processes (reviewed in Corsi et  al. (2015)). Furthermore, many significant scientific processes, including apoptosis (Hedgecock et al. 1983), miRNA (Lee et al. 1993), and RNA interference (RNAi) (Fire et al. 1998), have been discovered or mechanistically dissected in C. elegans. Notably, the lineage of all 959 somatic cells in adult hermaphrodites has been completely mapped (Kimble and Hirsh 1979; Sulston and Horvitz 1977; Sulston et al. 1983), while C. elegans also boasts the most comprehensively mapped neural network of any organism (Jarrell et al. 2012; White et al. 1986) (cell lineage and neural network visualized at www.wormatlas.org and www.wormweb.org). This broad understanding of nematode development and anatomy enables toxicologists to identify toxicant‐induced developmental abnormalities. Of particular relevance to mitochondrial effects, a detailed understanding of neural networks and visualization of neuronal subtypes via GFP expression has allowed toxicologists to associate neurodegeneration with well‐defined behavioral changes (Firnhaber and Hammarlund 2013). C. elegans was also the first multicellular organism to have its genome sequenced and annotated (Consortium 1998). Although relatively small in size (100 Mb, ~1/30 of the human genome), the C. elegans genome contains 20,444 protein‐coding genes, 60–80% of which have human homologues (Corsi et al. 2015; Henricson et al. 2004; Kaletta and Hengartner 2006), while 40% of human disease genes have C. elegans orthologues (Culetto and Sattelle 2000). This high genetic homology has allowed researchers to investigate disease etiology and provides human relevance for gene–environment interaction studies. Furthermore, transparent nematodes were the first organism engineered to use GFP as a biological marker of gene expression (Chalfie 1994), a tool allowing researchers to characterize tissue‐ specific gene expression patterns throughout larval development and aging (expression patterns available at http:// gfpweb.aecom.yu.edu/index, https://transgeneome.mpi‐ cbg.de/transgeneomics/index.html, while www.wormbase. org contains information on genome annotation, gene expression, and phenotypes associated with thousands of mutations). This robust understanding of C. elegans biology, combined with numerous online resources, provides toxicologists with the fundamental knowledge to investigate chemical‐induced toxicity.

43.2.3

Mitochondrial Biology in C. elegans

As in mammals, mitochondria play many critical roles throughout the nematode lifespan, and mitochondrial function is highly conserved between C. elegans and

humans. The C. elegans mitochondrial genome is 13,769 bp in size (16,595 bp in humans) (Okimoto et al. 1992) and encodes 22 tRNAs, 2 rRNAs, and 12 ETC subunits (ATP8 is unconfirmed but may also be present (Breton et  al. 2010)). Overall, it is estimated that each somatic cell in adults contains an average of 45–70 copies of mtDNA (Tsang and Lemire 2003). This value is considerably less than in human cells, which can contain hundreds to thousands of copies depending upon cell type and energetic demands. However, how mtDNA copy number varies by cell type in C. elegans remains unknown, except that copy number is higher in germ cells and oocytes (Leung et  al. 2013b; Tsang and Lemire 2003). Nuclear‐ encoded subunits of the ETC are also highly conserved in C. elegans (Tsang and Lemire 2003), as is overall ETC structure and function (Murfitt et al. 1976). In addition to a fully functioning ETC, a complete Krebs cycle is also present, and fatty acid oxidation, glycolysis, and gluconeogenesis are also highly conserved (Kühnl et al. 2005; Murfitt et  al. 1976; O’Riordan and Burnell 1989; Wadsworth and Riddle 1989; Zhang et  al. 2013). Mitochondrial homeostasis pathways such as the unfolded protein response (Durieux et al. 2011), mitodynamics (fusion/fission) (Gandre and Van Der Bliek 2007; Luz et  al. 2015a), mitophagy (Palikaras et  al. 2015a), mitochondrial antioxidant defenses (Hunter et al. 1997; Paek et al. 2012), and other pathways (Liu et al. 2014) are also conserved. The high conservation of mitochondrial metabolism between humans and C. elegans and the fact that 80% of human genes associated with inborn errors in metabolism have C. elegans orthologues (Kuwabara and O’Neil 2001) have permitted the use of C. elegans as a model for numerous metabolic diseases, including mitochondrial diseases (Dancy et al. 2016; Maglioni and Ventura 2016), lysosomal storage disorders (De Voer et  al. 2008), lipid metabolism disorders (Zhang et  al. 2013), and neurodegenerative diseases (Alexander et al. 2014; Lu et al. 2014; Peterson et al. 2008). Although many major metabolic pathways are conserved between humans and C. elegans (reviewed in Braeckman et al. (2009)), some key differences in intermediary metabolism exist. For example, C. elegans appear to lack the urea cycle, as no functional urea cycle enzymes have been identified (Falk et  al. 2008). Furthermore, the C. elegans genome contains only a single uncoupling protein homologue, ucp‐4, which does not function as a classical uncoupler, but instead plays a role in succinate transport (Pfeiffer et al. 2011). Finally, the glyoxylate pathway (a variation of the Krebs cycle not found in humans), which allows developing nematodes to convert energy stored as lipids into carbohydrates (Wadsworth and Riddle 1989), is present and has been implicated in playing an adaptive role in ETC complex I dysfunction by shifting electron flow to

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complex II, thus reducing ROS generation through complex I (Morgan et al. 2015). Much is also known about how mitochondrial function changes throughout the lifespan of C. elegans (reviewed in Tsang and Lemire (2003)). Embryos maternally inherit 25,000 copies of mtDNA, and mtDNA copy number remains constant until the fourth larval stage (L4) when a fivefold increase occurs, followed by a further sixfold increase in adulthood. This large increase in mtDNA copy number is associated with germline and oocyte development (Tsang and Lemire 2002). Glycolysis and the glyoxylate pathway have also been shown to be highly active in developing embryos as stored lipids are converted into carbohydrates for energy utilization; however, upon hatching and during the first larval stage (L1), glycolysis and glyoxylate pathway activity begin to decrease and continue to decrease into adulthood, while a concomitant increase in Krebs cycle activity and mitochondrial oxidative phosphorylation occur (Tsang and Lemire 2003; Wadsworth and Riddle 1989). Finally, mitochondrial function and antioxidant capacity have been shown to decline steadily throughout the aging process (Brys et  al. 2007; Tsang and Lemire 2002; Vanfleteren and De Vreese 1996), while the frequency of mtDNA mutations and deletions increases throughout aging (Melov et al. 1994, 1995). These trends (maternal inheritance of mtDNA, high glycolytic activity throughout development, reduced mitochondrial function and antioxidant capacity with aging, increased mtDNA mutations with aging) in mitochondrial function are similar to trends observed in humans and other mammalian models, further demonstrating the conservation of mitochondrial function throughout the nematode lifespan. 43.2.4

Mutagenesis and Mutant Availability

Availability of C. elegans strains carrying mutations or deletions in genes of interest allows researchers to easily investigate gene function, disease etiology, or gene–environment interactions. The C. elegans community, the C. elegans Knockout Consortium (celeganskoconsortium.omrf.org), and the C. elegans National BioResource Project of Japan (shigen.nig.ac.jp/c.elegans/mutants/index.jsp) have collectively isolated over 6,700 deletion alleles (Kwon et al. 2012), while the Million Mutations Project has established 2,000 mutagenized strains carrying 800,000 unique single nucleotide variants, resulting in approximately eight unique mutations for each of the 20,000 genes in the nematode genome (Thompson et  al. 2013) (strains available through the Caenorhabditis Genetics Center (cbs.umn.edu/cgc)). Wide mutagenic coverage of the nematode genome has allowed researchers to isolate and study myriad strains with mutations in genes that play crucial roles in diverse mitochondrial

processes, including oxidative phosphorylation, fission, fusion, mitophagy, iron homeostasis, antioxidant defense, and mtDNA replication and repair (Bratic et al. 2009; Feng et al. 2001; Luz et al. 2015a; Ventura et al. 2005; Yang and Hekimi 2010). Although knockout strains are not yet available for all genes in the C. elegans genome, numerous techniques for genome‐wide or site‐specific mutagenesis are available (reviewed in Kutscher and Shaham (2014)), which allows new mutants strains to be easily generated.

43.2.5

RNA Interference

Gene silencing via RNAi was first discovered in C. elegans nearly two decades ago (Fire et al. 1998). Since then, its application has expanded to numerous species, providing researchers with a tool to rapidly investigate the function of any gene. In C. elegans, RNAi gene knockdown can be accomplished via several techniques (reviewed in Ahringer (2005)), including feeding, injection, and soaking (Tabara et  al. 1998; Timmons and Fire 1998). However, the delivery method and concentration of double‐stranded RNA must be considered, as dilution of RNAi against several mitochondrial ETC genes has been shown to have a nonmonotonic effect on nematode lifespan (Rea et  al. 2007). Currently, two C. elegans RNAi libraries are available for purchase (Kamath et al. 2003; Rual et  al. 2004) and collectively cover 94% of the nematode genome. The overall ease of RNAi administration, and breadth of RNAi libraries, has enabled researchers to perform large genetic screens for genes that control mitochondrial morphology (Ichishita et  al. 2008) and identified numerous mitochondrial genes as playing critical roles in nematode lifespan (Hamilton et al. 2005; Lee et al. 2003). Interestingly, C. elegans neurons are RNAi insensitive, as they lack the transmembrane protein SID‐1, which is required for passive cellular uptake of RNAi (Tavernarakis et al. 2000; Winston et al. 2002). This observation has led researchers to generate RNAi‐insensitive SID‐1 mutants, which have then been rescued using DNA arrays (discussed further in the succeeding text) encoding SID‐1 under the control of tissue‐specific promoters, allowing researchers to investigate the effect of tissue‐specific gene knockdown. Tissue‐specific RNAi‐sensitive strains include pan‐neuronal (Calixto et al. 2010); GABAergic, dopaminergic, glutamatergic, and cholinergic neurons (Firnhaber and Hammarlund 2013); and hypodermis, intestine, and muscle sensitive strains (Qadota et  al. 2007). These strains have been utilized to demonstrate the cell‐non‐autonomous nature of ETC dysfunction‐mediated effects on nematode lifespan and to investigate tissue‐specific mitochondrial gene–environment interactions (Durieux et al. 2011).

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

43.2.6

DNA Transformation

Ease of genetic manipulation is one of C. elegans’ greatest strengths as a model organism, and thousands of transgenic strains overexpressing or ectopically expressing a gene or recombinant DNA have been generated (reviewed in Evans (2006)). Historically, DNA transformation has been accomplished via microinjection of extrachromosomal DNA arrays into the nematode germline (Mello and Fire 1995; Mello et al. 1991); however, mitotic instability and germline silencing can result in loss of, or mosaic expression of, the array (Kelly et  al. 1997). Chromosomal integration can help solve stability issues, and arrays can be randomly integrated using gamma or UV irradiation (Broverman et  al. 1993), or MosSCI technology can be used to insert the construct into a known location within the genome (Frøkjær‐ Jensen et al. 2008, 2012). Alternatively, DNA transformation can be accomplished via gene bombardment using a gene gun, which offers the major advantage of allowing researchers to isolate integrated strains directly (Praitis et  al. 2001); however, gene bombardment is expensive compared with microinjection. The two methods are reviewed in more detail in Evans (2006). More recently the CRISPR–Cas9 system has been used to edit the nematode genome and generate transgenic lines (Chen et al. 2013; Friedland et al. 2013). The aforementioned methods have allowed researchers to generate a multitude of stable transgenic strains that can be used to investigate various mitochondrial parameters, including steady‐state ATP levels (Lagido et al. 2008), mitochondrial morphology (Benedetti et al. 2006), and redox status (Back et  al. 2012b), while GFP expression driven by a promoter of interest allows researchers to monitor the induction of mitochondrial antioxidant and proteostasis genes (Anbalagan et  al. 2012, 2013). These transgenic tools are discussed further in Section 43.4.

43.2.7 C. elegans: A Model of Expanding Utility in Toxicology Due to the numerous advantages discussed in this chapter, use of the C. elegans model has greatly expanded in toxicology (reviewed in Hunt (2016)). Numerous studies have found that LC50 (the concentration of a chemical required to kill 50% of a given sample) ranking in C. elegans correlates well with both mouse and rat toxicity ranking for many metals (Hunt et al. 2012; Williams and Dusenbery 1988), organophosphate pesticides (Cole et  al. 2004), 100s of diverse compounds from the ToxCast™ phase I and II libraries (Boyd et al. 2016), and numerous other water‐soluble chemicals (Ferguson et al. 2010; Li et al. 2013). However, higher concentrations are

typically required in nematodes, which is likely due to the nematode cuticle, a collagenous barrier that can limit the uptake of bulky or ionized compounds (Au et  al. 2009; Partridge et al. 2008; Watanabe et al. 2005), as well as robust protective mechanisms that allow nematodes to survive in a variety of harsh environments. Given nematodes’ small size, low maintenance costs, and ability to be predictive of mouse and rat LC50 ranking, it is surprising that more high‐throughput toxicity screening has not been performed using C. elegans. Feasibility of high‐throughput screening in C. elegans has been elegantly demonstrated by researchers studying aging, in which large libraries (1,280–88,000) have been screened for compounds that can extend lifespan (Lucanic et  al. 2016; Petrascheck et  al. 2007, Ye et  al. 2014; 2009), while other studies have screened (>1,200 compounds) for induction of mitochondrial hsp‐60 (Rauthan and Pilon 2015). More impressively, a 300,000‐ compound library was recently screened for antimicrobial activity in C. elegans infected with Burkholderia thailandensis (Lakshmanan et al. 2014), while a 364,000‐ compound library was screened for SKN‐1 (NRF‐2 homologue) inhibitors (Leung et  al. 2011, 2013a). These studies have utilized lifespan and lethality assays, as well as various transgenic GFP reporter strains, further demonstrating the flexibility of the C. elegans model.

43.3 Limitations of C. elegans for Studying Mitochondrial Toxicity 43.3.1

Introduction

While there are numerous molecular and genetic parallels between C. elegans and higher‐order organisms (Section  43.2), there are also differences that impose some limitations. These tend to be more significant at higher levels of biological organization (e.g., tissue and organ structure). Here, we discuss important differences that should be kept in mind when designing experiments in C. elegans to study disruption of mitochondrial functions by exposure to environmental contaminants. It is not within the scope of this chapter to review all known or possible limitations, but we highlight differences that may limit extrapolations from C. elegans to higher eukaryotes. 43.3.2

Genetic and Phylogenetic Differences

One of the most well‐characterized and important classes of enzymes involved in the metabolism of xenobiotics is the CYP450 family (reviewed by (Coon (2005) and Guengerich (2008)). The C. elegans genome contains genes closely associated with mammalian genes for the

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CYP2, CYP3, and CYP4 enzyme families (Gotoh 1998). However, the genome appears to lack the CYP1 gene family, which metabolizes classes of polycyclic aromatic hydrocarbons (PAHs) and aromatic amines and are under the transcriptional control of the AhR (Nebert et al. 2004). The lack of biologically active CYP1 enzymes has since been confirmed in C. elegans (Goldstone et al. 2007; Leung et al. 2010). This lack of CYP1 enzymes in C. elegans has direct implications for studying mitochondrial toxicity, since CYP1A1 and CYP1A2 localize to the mitochondrion in mouse (Senft et  al. 2002), as does CYP1B1 (Dong et al. 2013). This limits the use of C. elegans for CYP1 enzymes and associated mitochondrial xenobiotic metabolism mechanisms, at least without the addition of transgenes. C. elegans is still potentially useful for other CYP classes within the CYP450 superfamily of enzymes, although not all CYP2, CYP3, and CYP4 enzymes are conserved; for example, CYP2E1 appears to be absent. In addition, some of the regulation of CYP as well as other xenobiotic metabolism genes is different in C. elegans; for example, while an AhR homologue is present, it does not appear to be a receptor for traditional xenobiotic ligands of the mammalian AhR (Powell‐ Coffman et al. 1998). Mitochondrial fusion is an important function in maintaining mitochondrial networks. C. elegans mitochondrial fusion mutants (such as fzo‐1 and eat‐3) provide a useful genetic background with which to study defects in mitochondrial fusion. However, there are fundamental differences in survival when homozygous mutations in mammalian mitofusins (Mfn1/Mfn2) and their homologue (fzo‐1) in C. elegans are present: homozygous mutations in Mfn1/Mfn2 are embryonic lethal in mammals (Chen et al. 2003; Fyfe et al. 2011), but C. elegans survive throughout adulthood (Ichishita et al. 2008). These differences highlight roles of mitochondrial fusion mechanisms that are specifically essential for mammalian survival that are not represented in C. elegans. This is also true in an example of an enzyme important for mtDNA maintenance (Suetomi et  al. 2013). Additionally, mtDNA biogenesis declines significantly during aging in C.  elegans (Rooney et al. 2014), which would present challenges to studying mitochondrial‐ related aging mechanisms. 43.3.3

Biochemical Differences

C. elegans do not have a complete urea cycle (Falk et al. 2008) and excrete most ammonia via apical ammonia trapping and exocytosis (Adlimoghaddam et  al. 2015), making it difficult to accurately study detoxification of hyperammonemic states caused by exposures in humans (e.g., occupational exposure to hydrazine (Zelnick et al. 2003)). The metabolism of certain antibiotics may also

be difficult to study in C. elegans in this regard; both hydrazine and ammonia are metabolites of isoniazid (metabolism and toxicity reviewed by Preziosi (2007)), and hydrazine itself has been shown to inhibit mitochondrial complex II activity in mammalian cells (Lee and Boelsterli 2014). The potential interactions between mitochondrial inhibition by hydrazine and urea cycle reactions housed within mammalian mitochondria are unclear. Thus, metabolism of a compound like hydrazine is an example of a drug metabolite/occupational exposure causing mitochondrial toxicity that may be difficult to study in C. elegans due to their differential detoxification of ammonia. Metabolic acidosis causes ammoniagenesis in isolated mitochondria, and the reaction is governed by phosphate‐dependent glutaminase activity (Tannen and Kunin 1976). C. elegans contain an orthologue (glna‐2) of the human mitochondrial glutaminase (GLS2) responsible for the observed ammoniagenesis (Hobert 2005); however, the specific activity of glna‐2 has yet to be determined. Thus, the detoxification mechanisms of environmental chemicals causing metabolic acidosis (and resultant mitochondrially induced hyperammonemia) may not be precisely modeled in C. elegans. C. elegans lacks orthologues of heme synthesis enzymes (Jaffe 2003) and instead rely on nutritional sources of heme for biochemical processes (Rao et  al. 2005). Because they do utilize heme for essential pathways, they may still provide a sound in vivo model for aspects of heme transport (Rajagopal et al. 2008), but not necessarily for chemical exposures that interfere with de novo heme synthesis, including both cytosolic and mitochondrially bound enzymes (Rao et al. 2005). For example, lead exposure in humans dramatically inhibits porphobilinogen synthase (PBGS) (Chisolm et al. 1985; Hernberg et  al. 1970; Jaffe et  al. 1991), and circulating PBGS activity is used as an early biomarker of acute lead exposure (Jaffe et  al. 1991; Lawrence et  al. 2013). Environmental and occupational exposures to contaminants other than lead including hexachlorobenzene (Schmid 1960), diazinon, dioxin, and arsenic (reviewed in Daniell et al. (1997)) can cause acute chemical‐induced porphyria (a condition in which heme precursors are not converted to heme) in humans. Porphyria has recently been linked to mitochondrial respiratory failure in a rodent model of the condition (Homedan et  al. 2014), demonstrating a link between heme synthesis mechanisms affected by common environmental contaminants and direct mitochondrial outcomes that could not be effectively investigated in C. elegans. Additionally, C. elegans cannot synthesize sterols de novo from acetate (Rothstein 1968), and cholesterol itself does not appear to have an essential function in membrane structure in this organism (Kurzchalia and Ward 2003). In other organisms, including mammals and yeast,

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

sterols are important in providing rigidity to cellular membranes, and the relative sterol content in membranes influences cross‐membrane transport and association with exogenous substances. The ratio of sterol content to other lipid content is low (1 : 30) for both inner and outer mitochondrial membranes (Bottema and Parks 1980), and increasing the cholesterol content in mitochondrial membranes is associated with membrane depolarization via cardiolipin peroxidation (Montero et al. 2010). Mitochondrial dysfunction associated with proteotoxicity is a well‐documented intracellular pathology in neurodegenerative disease (reviewed by Hashimoto et al. (2003)), and sterol synthesis may play a role. In this way, C. elegans serves as a suitable model for investigation of some molecular pathways of neurodegenerative diseases that may result in part from environmental exposures, including Alzheimer’s disease (AD) (reviewed by Alexander et  al. (2014)) and Parkinson’s disease (PD) (reviewed by Harrington et  al. (2010)). However, more subtle mechanisms of disease development and mitochondrial toxicity in mammals may not be as readily accessible in C. elegans. For example, when sterol synthesis is inhibited in yeast, various splice isoforms of alpha‐synuclein are more likely to associate within vesicles rather than on the plasma membrane, increasing its cellular entry and thus its relative downstream toxicity (Valastyan et al. 2014). Additionally, the presence of AD‐associated amyloid‐β1‐40 significantly decreases cholesterol synthesis in vitro (Koudinova et al. 1996). The demonstrated interaction of molecular hallmarks with AD and PD on endogenous sterol synthesis indicates that C. elegans may not be a suitable model for investigating environmental influences on these particular pathways of disease progression. This is especially important in terms of studying environmental exposures associated with neurodegenerative diseases, since only a small percentage of late‐onset AD and PD cases are explained exclusively by genetics (Bertram and Tanzi 2005). As an additional note, C. elegans exhibit high (relative to mammals) tolerance for both hypoxic (Powell‐ Coffman 2010) and hyperoxic (Yanase and Ishii 2008) conditions, which can potentially confound important oxygen‐dependent mitochondrial mechanisms altered by environmental toxicants in this organism. 43.3.4

Physiological Limitations

While the use of C. elegans for examining important mitochondrial contributions to tissue‐level toxicity research has expanded somewhat recently, it has been limited by species‐specific differences in tissue composition and organization, cellular metabolic demands, and pharmacokinetic differences compared with more

complex mammalian species. A full comparison of mitochondrial differences in all cell types and tissues in C. elegans and humans is beyond the scope of this chapter. However, to illustrate ways in which tissue differences can limit applicability of the C. elegans model in some cases, we highlight specific characteristics of mitochondria in the brain, heart, and respiratory systems that may confer differential susceptibility to environmental mitotoxicants. We focus on these tissues because of the particularly important role of mitochondrial function in these systems. Some key differences between mammals and C. elegans in cellular and tissue organization that may affect both routes of chemical uptake and target tissue effects are illustrated in Table 43.1. We note that this is not an exhaustive comparison; for example, differences in gut physiology and microbiome will affect uptake, and additional tissues (e.g., liver, kidney) are important targets of mitochondrial toxicity in humans, as evidenced by the fact that they are affected by mitochondrial diseases and mitotoxic drugs. 43.3.4.1

Brain Mitochondria

There is strong evidence for mitotoxicity as a mechanism of some forms of chemical‐induced neurotoxicity and neurodegeneration (Farina et  al. 2013; Kaminsky et  al. 2015; Kubik and Philbert 2015). The brain is one of the most highly metabolic tissues in the body, accounting for 60% of the body’s utilization of glucose in a resting state and simultaneously maintaining a very low metabolic reserve: if the glucose supply is exhausted, the brain relies on ketone bodies for energy (because unbound fatty acids do not cross the blood–brain barrier and are thus not used for energy substrates) (Berg et al. 2002). Energetic demands requiring proper mitochondrial function (and the subsequent mitochondrial responses to those demands) are not uniform between functionally and anatomically distinct brain regions (Kayser et  al. 2016; Lee Do et al. 2013; Sundar Boyalla et al. 2011), nor between neural cell types (Motori et al. 2013; Sundar Boyalla et al. 2011; Voloboueva et al. 2007), and are temporally dynamic (Wirtz and Schuelke 2011). This is especially important during region‐specific neural development in mammals, for example, as cerebellum‐specific radial glial cells (Bergmann glial cells) provide an essential cellular scaffold utilized by Purkinje cells during migration, synaptogenesis, and neuronal maturation (reviewed by Yamada and Watanabe (2002)). Radial glial fibers extending from Bergmann glial cell bodies contain mitochondria that are metabolically independent from one fiber to the next and are essential in glial fiber‐specific interactions with adjacent neurons (Grosche et al. 1999). Differential regional and cellular responses in brain mitochondrial function exist in mammals in response to  environmental exposures, such as those that cause

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chemical hypoxia (Roemgens et  al. 2011), naturally occurring elements such as manganese (Rao and Norenberg 2004; Sidoryk‐Wegrzynowicz and Aschner 2013), nitrobenzene compounds (Kubik et  al. 2015; Steiner and Philbert 2011), and polychlorinated biphenyls (PCBs) (Kodavanti et  al. 1998). While C. elegans contain fully functional and well‐characterized neuronal populations and subpopulations (GABAergic, dopaminergic, motor neurons, sensory neurons, etc.) and some glia (reviewed by Oikonomou and Shaham (2011)), they are far fewer in number, classification, and subsequent complexity in physiological connectivity compared with higher‐order organisms (Table  43.1). The regional organization and cellular sophistication found in the mammalian brain and corresponding regional and cell‐ specific mitochondrial contributions to neural function that are impacted by environmental exposures are not physiologically parallel to the C. elegans neural system, rendering it an inadequate model for the study of such tissue‐level relationships. However, our understanding of the role of glia in C. elegans may well keep expanding, and their relevance to human neural mitochondrial health may proportionally expand as a result. 43.3.4.2

Cardiac Mitochondria

Mitochondria within the heart are particularly important to discuss, as they represent a mitochondrial population within a highly metabolic tissue in mammals that is not present in C. elegans. There is evidence of cardiotoxicity mediated by mitochondrial effects of a wide range of chemicals (Finsterer and Ohnsorge 2013). Of note, there are developmental parallels between pharyngeal cells in C. elegans and vertebrate heart (Haun et al. 1998); however, mechanistic links between mitochondrial dysfunction in specific cellular subtypes in vertebrate heart and mitochondrial effects in C. elegans pharynx have not yet been directly established. Cardiomyocytes mainly utilize fatty acids rather than glucose as an energy source (Grynberg and Demaison 1996), which may fundamentally change their susceptibility to environmental exposures compared with other highly metabolic cell types that rely mostly on glucose. Cardiomyocytes are unique from other cell types in that the energy requirements are quite high, but mitochondria are largely fragmented (Kuznetsov and Margreiter 2009). This mitochondrial morphology is very tightly controlled in cardiomyocytes (Piquereau et al. 2010), as is mitochondrial movement, largely due to rigid and crowded cytoarchitecture (Vendelin et  al. 2005). The physical hindrances preventing fusion and movement of mitochondria in cardiomyocytes may render the heart uniquely vulnerable to mitochondrial dysfunction as a result of environmental exposures. For example, classic mitotoxicants such as acetaldehyde and ethanol inhibit mitochondrial

respiration in cardiomyocytes (Segel and Mason 1979). Emerging classes of environmental exposures exhibit mitochondrial toxicity within the heart as well: rodents exposed to mountaintop removal mining particulate matter exhibited decreased cardiac mitochondrial function and mitochondrially mediated induction of apoptosis associated with cardiac dysfunction (Nichols et  al. 2015), and titanium dioxide nanoparticle exposure in utero negatively impacts mitochondrial respiration in hearts of the offspring in rodents (Stapleton et  al. 2015). Whether these changes are due to the fragmented network of mitochondria within the heart is yet to be fully investigated. However, because C. elegans do not have cardiomyocytes, the nematode’s utility for investigating hypotheses related to environmental mitotoxicants and any resultant impacts on specialized mitochondria within these cells is unclear. 43.3.4.3

Lung Mitochondria

Lung mitochondria are involved in multiple responses to stress, including hypoxia sensing and immune cell signaling localized to the pulmonary system (Schumacker et al. 2014). A variety of chemical exposures can target mitochondria in lung cells (Brar et  al. 2012; Xia et  al. 2007; Yamada and Fukushima 1993), with well‐studied pollutant exposures including paraquat and particulate matter. Inhalational routes of exposure in humans are not accurately modeled in C. elegans, as they do not have a respiratory system (Table 43.1). The tight regulation of oxygen exchange throughout the lung has major implications for specialized mitochondrial function. In mammalian lungs, mitochondrial density in type II pneumocytes (surfactant‐producing cells), but not other lung cells, shows a linear correlation with total lung oxygen consumption (Massaro et al. 1975). Type II pneumocyte mitochondria are physically altered by environmental exposures, including lead ferricyanide, alcohol, and epoxypropane (Pattle et  al. 1972). Exposure to acrolein causes a concentration‐dependent inhibition of mitochondrial respiration in type II pneumocytes in vitro and a shift from glucose utilization likely to palmitate (essential for surfactant biosynthesis) utilization as an energetic substrate (Agarwal et al. 2013). This compensatory response to mitochondrial metabolism is likely not observed in other cell types due to substrate availability linked to surfactant production, making it physiologically infeasible to investigate in C. elegans. 43.3.5 Concluding Remarks on Limitations of C. elegans as a Model Organism C. elegans is a powerful model organism for many aspects of mitochondrial research (Section 43.2) and provides a convenient in vivo system to measure mitochondrial

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

dynamics. However, the utility of C. elegans for the study of mitochondrial function is limited in some cases, including absence of specific biochemical pathways, cell types, and complex tissue organization. Mitochondrial researchers should consider and balance the benefits and limitations of the C. elegans model accordingly.

43.4 Methods for Assessing Mitochondrial Toxicity in C. Elegans 43.4.1

Introduction

As discussed earlier in this chapter, the nematode’s small size, transparency, short developmental period and lifespan, high reproductive rate, and well‐conserved mitochondrial function make it a valuable in vivo model for assessing both general and mitochondrial‐specific chemical‐induced toxicity (reviewed in Leung et  al. (2008), Tejeda‐Benitez and Olivero‐Verbel (2016), and Hunt (2016)), and myriad toxicity assays that exploit nematode biology have been developed. Many of the genetic, biochemical, and molecular methods routinely used to assess mitochondrial health in cell culture have been adapted for use in C. elegans and are discussed in Table 43.3.

43.4.2

General Toxicity Assays

C. elegans has only been used as a toxicological model for a relatively short time. Initial pioneering work by Williams and colleagues (Williams and Dusenbery 1988) was eventually followed by myriad assays with medium‐ to high‐throughput potential to monitor well‐defined biological processes, including lethality and lifespan (Stroustrup et al. 2013), larval growth (Boyd et al. 2010b), reproduction (Boyd et  al. 2010a; Ferreira et  al. 2014), locomotion (Boyd et  al. 2010b), germline function (Allard et  al. 2013; Parodi et  al. 2015), epigenetics (Lundby et al. 2016), and feeding (Boyd et al. 2007). Many of these assays utilize the COPAS Biosort (Pulak 2006), a large particle flow cytometer capable of dispensing and measuring thousands of nematodes per minute, making it amenable to high‐throughput toxicity testing. Alternatively, lower‐throughput variations of these assays that do not require costly COPAS equipment have been developed (reviewed in Tejeda‐Benitez and Olivero‐Verbel (2016)). Although growth, reproduction, locomotion, and feeding are energetically demanding processes that are dependent upon proper mitochondrial function, these assays do not specifically assess mitochondrial health. Nevertheless, when used in combination with RNAi or strains deficient in various mitochondrial stress response pathways, these assays

Table 43.3 Methods to detect mitochondrial toxicity in C. elegans. Referencesa

Mitochondrial endpoint

Method

Mitochondrial respiration

Clark‐type electrode e

Steady‐state ATP Mitochondrial morphology

Seahorse XF 24

Luz et al. (2015a, b)

Seahorse XFe96

Andreux et al. (2014) and Koopman et al. (2016)

Isolated mitochondria

Grad et al. (2007) and Kayser et al. 2004)

ATP extraction

Brys et al. (2010) and Todt et al. (2016)

In vivo ATP reporter strains (PE255 & PE327)

Lagido et al. (2008, 2015)

Fluorogenic dyes and transgenic strains expressing fluorescent proteins in mitochondria

De Boer et al. (2015), Rolland (2014), and Smith et al. (2015)

Membrane potential

Potentiometric dyes (diS‐C3(3), TMRE, JC‐1)

Gaffney et al. (2014) and Luz et al. (2016)

mtDNA damage and copy number

Real‐time and long amplicon QPCR

Gonzalez‐Hunt et al. (2016), Hunter et al. (2010), and Rooney et al. (2015).

LC/MS

Arczewska et al. (2013) and Hunt et al. (2013)

Carbohydrate staining (periodic acid Schiff ’s reagent)

Hench et al. (2011)

Lipid staining (oil red O)

Soukas et al. (2009)

ETC complexes I, II, and IV

Grad and Lemire (2004), Hench et al. (2011), and Sciacco and Bonilla (1996)

Histochemical analysis

a

Braeckman et al. (2002)

 When available, detailed step‐by‐step protocols are referenced; however, primary research containing detailed method is also referenced when protocols are not available.

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can provide evidence of mitochondrial toxicity or gene– environment interactions. However, mitochondrial toxicity must be confirmed using more direct measures of mitochondrial health (discussed in the succeeding text) as genes may have yet unrecognized biological functions unrelated to mitochondrial fitness, while RNAi and mutagenesis can cause compensatory changes that may alter the toxicant response. Finally, as for all such studies, it is critical to optimize and standardize assay conditions. Conditions that may be of particular importance with respect to mitochondrial function are nematode density in liquid medium or on plates, availability of food, viability of bacterial food (which may affect xenobiotic metabolism, among other parameters), temperature, oxygen availability, and shaking of liquid culture (Hanna et  al. 2016; Hunt 2016; Maurer et al. 2015). 43.4.3

Mitochondrial Respiration

Historically, mitochondrial respiration has been measured polarographically in nematodes using Clark‐type electrodes (Braeckman et al. 2002); however, Clark‐type respirometers are relatively low throughput. The advent of the Seahorse extracellular flux analyzer (available in 24‐ and 96‐well formats) and its subsequent optimization for use with C. elegans (Andreux et  al. 2014; Luz et  al. 2015a) has aided researchers’ ability to rapidly measure mitochondrial respiration in vivo. Although the bioanalyzer is capable of simultaneously measuring basal oxygen consumption rate (OCR) and the extracellular acidification rate (ECAR) (a measure of glycolysis), ECAR does not appear to provide an accurate measure of glycolysis in nematodes (Luz et al. 2015a), likely due to differences in lactate excretion between cells in culture and nematodes. Finally, the ability to inject ETC inhibitors into Seahorse assays allows researchers to measure additional mitochondrial parameters, including ATP‐ linked OCR, maximal OCR, spare respiratory capacity, and proton leak. All of these parameters have been successfully measured in the Seahorse XFe24 (Luz et  al. 2015a, b), while only basal, maximal, and spare respiratory capacity have been measured in the XFe96 (Andreux et  al. 2014; Koopman et  al. 2016). Although Seahorse technology is relatively novel to the C. elegans community, it has already been used to assess the effects of mutations (Luz et al., 2015a; Shen et al., 2016), pharmaceuticals (Andreux et al. 2014), and environmental toxicants (Caito and Aschner 2016; Luz et  al. 2016) on mitochondrial function. In addition to assaying whole nematodes, both Clark‐ type electrodes and the Seahorse bioanalyzer can be used to assay isolated mitochondria. Methods for isolating and purifying mitochondria from C. elegans are available (Brys et al. 2010; Grad et al. 2007; Kayser et al.

2004); of note, it was recently demonstrated that mitochondrial yield can be significantly increased (50–100%) by pretreating nematodes with collagenase 3, an enzyme that weakens the nematode cuticle, prior to homogenization (Daniele et al. 2016). Once isolated, mitochondrial ETC function can be assayed similarly to mitochondria isolated from cells or tissue (Grad et  al. 2007; Kayser et al. 2004). 43.4.4

Steady‐State ATP Levels

ATP levels can be quantified in C. elegans using commercially available kits that measure luminescence produced by ATP‐powered firefly luciferase in a microplate reader (Braeckman et al. 2002; Brys et al. 2010); however, extraction and purification of ATP is an expensive and time‐consuming process. To overcome this, transgenic strains (PE255 and PE327, both available through CGC) stably expressing a firefly luciferase–GFP fusion protein were generated (Lagido et  al. 2008). These transgenic strains bioluminesce when provided with exogenous d‐ luciferin, providing a relative in vivo measure of steady‐ state ATP. This transgenic approach offers a rapid, low‐cost method of monitoring steady‐state ATP levels and has been used by many researchers to investigate mitochondrial toxicity following pharmaceutical (Rooney et  al. 2014) or toxicant (Andreux et  al. 2014; Bishop and Guarente 2007; Culetto and Sattelle 2000; Lagido et al. 2001; Luz et al. 2015b; Sulston and Horvitz 1977; Sulston et al. 1983; Swierczek et al. 2011) exposure and has potential high‐throughput applications for screening for mitochondrial toxicity (Lagido et al. 2015). Alternatively, Promega’s ToxGlo™ assay was recently optimized for use with C. elegans, which offers researchers a non‐transgenic approach for rapid steady‐state ATP determination (Todt et al. 2016). 43.4.5 Transcriptomics, Proteomics, and Metabolomics To delineate molecular mechanisms of toxicity, C. elegans researchers have employed high‐throughput ‐omics approaches. Changes in the nematode transcriptome have been investigated using DNA microarray and RNA‐ sequencing technology following mitochondrial toxicant exposure (Leung et al. 2013b; Sahu et al. 2013; Schmeisser et  al. 2013; Zhao et  al. 2016). Proteomics and metabolomics approaches have been used by C. elegans researchers to investigate the molecular changes that occur due to mutations in mitochondrial electron transport chain genes (Butler et al. 2010, Morgan et al. 2015; 2013); however, methodology for protein and metabolite extraction can easily be adapted for toxicity studies. Alternatively, non‐omics approaches, such as real‐time PCR, are also

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

frequently used to assess toxicant‐induced alterations in various mitochondrial signaling pathways (biogenesis, stress response, etc.). These approaches are facilitated in C. elegans by the outstanding annotation of the C. elegans genome (Consortium 1998), which was the first‐ sequenced metazoan genome and remains one of the best annotated due to extensive, ongoing centralized curation at Worm Base (www.wormbase.org). 43.4.6

Enzyme Activity

The activities of numerous enzymes involved in intermediary metabolism have been measured in C. elegans following well‐established biochemical principals (Ragan et al. 1987; Srere 1969; Trounce et al. 1996). Key metabolic enzymes that have been assayed in nematodes include fructose 1,6‐bisphosphatase and phosphoenolpyruvate carboxykinase (gluconeogenesis) (Castelein et  al. 2008; O’Riordan and Burnell 1989), hexokinase, phosphofructokinase and pyruvate kinase (glycolysis) (Castelein et al. 2008; O’Riordan and Burnell 1989), aconitase, citrate synthase, fumarase, isocitrate dehydrogenase, malate dehydrogenase, pyruvate dehydrogenase and succinate dehydrogenase (Krebs cycle) (Brys et  al. 2010; Castelein et al. 2008; Luz et al. 2016; O’Riordan and Burnell 1989), isocitrate lyase (glyoxylate cycle) (Castelein et al. 2008), and various complexes of the ETC (Kayser et  al. 2001, 2004). Activity of many of these enzymes can easily be assayed in crude nematode lysate or isolated mitochondria using a microplate reader. 43.4.7

Mitochondrial Morphology

As with cells in culture, mitochondrial membrane potential‐sensitive dyes, such as TMRE (Breckenridge et  al. 2008; Rolland et al. 2009) and MitoTracker Red CMXRos (Kimura et al. 2007; Luz et al. 2015a), can be used to visualize mitochondrial morphology in nematodes. However, due to the nematode cuticle, uptake of dyes is slow, and a longer incubation period (hours vs. minutes) is required to stain mitochondria. Alternatively, transgenic strains (SJ4103, available through CGC) expressing mitochondrial‐targeted GFP under the control of the myo3 promoter, which results in GFP expression in body wall muscle cell mitochondria, have been generated (Benedetti et al. 2006). These transgenic lines have been used by numerous researchers to investigate the effects of genetic deficiencies and toxicants on mitochondrial morphology (Houtkooper et al. 2013; Palikaras et al. 2015b; Rooney et al. 2014) and offer the added advantage of tissue specificity, which in some cases is a major limitation of C. elegans (discussed further in the succeeding text). Finally, mitochondrial morphology can also be assessed using transmission electron microscopy (Frank et  al. 2001).

Detailed protocols for assessing mitochondrial morphology in C. elegans have been published (De Boer et al. 2015; Rolland 2014; Smith et al. 2015). 43.4.8

Mitochondrial Membrane Potential

Mitochondrial membrane potential has been measured in C. elegans using the potentiometric dyes MitoTracker Red CMXRos (Gaffney et al. 2014), diS‐C3(3) (Gaskova et  al. 2007; Lemire et  al. 2009), TMRE (Palikaras et  al. 2015b), and JC‐1 (Du et al. 2015; Iser et al. 2005; Ji et al. 2012; Luz et al. 2016), with the mitochondrial uncouplers CCCP or FCCP being used as a positive control. The accumulation of potentiometric dyes in mitochondria is visualized via confocal microscopy and can then be quantified using ImageJ or other image processing software. Many of the advantages and limitations of these potentiometric dyes are discussed in Perry et al. (2011). 43.4.9

Stress Response

Myriad techniques used to assess oxidative stress in cell culture have been adapted for use in C. elegans (reviewed in Braeckman et al. (2016)). The fluorogenic dyes dihydroethidium and Amplex Red can be used to detect superoxide (Huang and Lemire 2009; Morcos et al. 2008) and hydrogen peroxide (Chávez et  al. 2007; Zeitoun‐ Ghandour et  al. 2011) production, respectively, while MitoTracker Red (CM‐H2X ROS) can be used to detect mitochondrial‐specific ROS production (Schmeisser et  al. 2013). However, fluorogenic dyes must be used with caution, as they are highly reactive, and proper positive controls must always be used. Furthermore, ease of genetic manipulation has allowed researchers to generate transgenic strains expressing fluorescent biosensors, such as HyPer and GRX1‐roGFP2, which allow for the in vivo detection of H2O2 production and redox potential (GSSG/GSH) (Back et  al. 2012b). In addition, GFP expression driven by mitochondrial (sod‐3)‐ or cytosolic (sod‐1)‐specific superoxide dismutase promoters can aid in the identification of the intracellular location of ROS production and provide an indirect measure of oxidative stress (Anbalagan et al. 2013; Curran and Ruvkun 2007), while direct oxidative damage of macromolecules, such as lipids and proteins, can be assessed in C. elegans using LC‐MS/MS (Labuschagne et al. 2013) and Western blots (Adachi et  al. 1998; Wang et  al. 2010; Wu et  al. 2011), respectively. In addition to oxidative stress, GFP reporter strains have also been generated for the rapid assessment of proteotoxicity (mitochondrial and non‐mitochondrial heat shock proteins), xenobiotic response (CYP450s and GSTs), metal response, and the general stress response transcription factor (daf‐16), which allows researchers to

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rapidly and affordably screen for induction of stress response pathways following toxicant exposure (Anbalagan et al. 2012, 2013). 43.4.10 Mitochondrial DNA Damage and Genome Copy Number Following toxicant exposure, DNA damage can be detected in C. elegans using the comet assay (Sobkowiak and Lesicki 2009), GC/MS (Arczewska et al. 2013; Hunt et al. 2013), or the long amplicon quantitative PCR (LA‐ QPCR) assay. Certain DNA lesions can also be detected by antibody (Roerink et  al. 2012). Most of these work poorly for mitochondrial DNA damage. One of the main advantages of using the primer‐based LA‐QPCR assay is that it allows both mitochondrial and nuclear DNA damage to be quantified and it allows for the simultaneous measurement of relative or absolute mitochondrial and nuclear genome copy number. Recently, the LA‐QPCR assay was used to demonstrate for the first time that the environmental toxicants cadmium and paraquat preferentially damage mitochondrial DNA in vivo in C. elegans (Gonzalez‐Hunt et al. 2014), demonstrating the importance of measuring DNA damage in both genomes. Further advantages and limitations of the LA‐QPCR assay are discussed in Meyer (2010), while detailed protocols for measuring DNA damage and genome copy number can be found in Rooney et al. (2015); Gonzalez‐ Hunt et al. (2016), and Hunter et al. (2010). 43.4.11

Limitations

Although nematodes offer an in vivo advantage for studying mitochondrial toxicity, their small size and protective cuticle make it difficult to isolate biochemically relevant amounts of purified tissue; thus, mitochondrial function is typically assessed in whole nematodes or in whole nematode homogenates, preventing the investigation of tissue‐specific mitochondrial dysfunction. However, well‐established histochemical methods have been used to identify tissue‐specific changes in morphology and metabolism (Hench et al. 2011; Tsang et al. 2001). For example, hematoxylin and eosin staining can be used to visualize morphological changes, oil red o (Soukas et  al. 2009) and periodic acid Schiff ’s reagent (Hench et al. 2011) can be used to visualize changes in lipid and carbohydrate storage, and other histochemical stains can be used to measure the activity of electron transport chain complexes I, II, and IV in whole worms or in specific tissues (Grad and Lemire 2004; Hench et al. 2011; Sciacco and Bonilla 1996). Although these histochemical methods are time consuming, they do provide researchers with the ability to evaluate tissue‐specific effects, as demonstrated by the identification of the

gonad as a highly sensitive target tissue of doxycycline and chloramphenicol toxicity (Tsang et al. 2001). In addition to histochemical methods, transgenic strains expressing mitochondrially targeted fluorescent proteins or strains with tissue‐specific (neurons, hypodermis, muscle, intestine) RNAi sensitivities provide researchers with alternative ways to investigate tissue‐ specific mitochondrial toxicity. For example, sensitivity to paraquat has been tested following tissue‐specific knockdown of ETC CIV (Durieux et  al. 2011), while mitochondrial‐targeted fluorescent proteins (GFP, YFP, RFP) under the control of tissue‐specific promoters allow tissue‐specific subpopulations of mitochondria to be identifiable via flow cytometry (Daniele et al. 2016). Furthermore, the use of fluorogenic dyes to assess membrane potential or ROS may be used to assess isolated subpopulations of mitochondria for tissue‐specific disruption of mitochondrial function (Daniele et al. 2016).

43.5 Environmental Mitotoxicants and C. Elegans: Unique Discoveries and Emerging Roles 43.5.1

Introduction

There is a relative paucity of data on environmental contaminants that cause mitochondrial toxicity (reviewed by Meyer et al. (2013)), especially in comparison with what is known about drug‐induced mitochondrial toxicity (reviewed by Varga et  al. (2015), Begriche et  al. (2011), Dykens and Will (2007), and Nadanaciva and Will (2011a, b)). Because of the sheer number and volume of chemicals produced annually, there is mounting concern regarding how to address toxicity resulting from exposure. C. elegans provides a medium‐ to high‐throughput in vivo system with which to address these questions, combining the ease of use provided by an in vitro system with the physiological complexity of an intact organism. For these reasons, researchers across multiple sectors have begun to utilize C. elegans as a model system for studying mitochondrial toxicity. This section describes some of the primary contributions that C. elegans studies have made in understanding mitochondrial toxicity caused by environmental exposures, expanding our current comprehension of these mechanisms in higher organisms. However, these contributions are largely in the area of neurotoxicity and neurodegeneration. Furthermore, they are mostly relatively recent, both because the use of C. elegans for toxicology has been relatively limited until the last decade and because studies of environmental mitochondrial toxicity in any organism have only recently begun to take off. Therefore, we also highlight another related contribution from the C. elegans field: the role of mitochondria in

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

mediating lifespan‐related stress responses, which has been extensively studied in C. elegans. 43.5.2 Contributions of C. elegans in Discovering Key Mitochondrial Roles in Neurotoxicity Some of the most important unique mitochondrial toxicity discoveries using C. elegans are specific to neurotoxicity induced by environmental exposures or related to inherent age‐related neurodegenerative processes. C. elegans is an excellent model for studying certain neurotoxicity endpoints, due to a well‐characterized neural system that retains complex features of a mammalian brain (Bargmann 1998; Hobert et al. 2002) while also containing fewer cells and circuits, which permits simplicity of study (for caveats to this, please refer to Section  43.3). Neural cells are among the most metabolically active cells in an organism, making them vulnerable to imbalances in energy homeostasis, the maintenance of which is largely dependent upon proper mitochondrial function. Environmental exposures are postulated to play a role in the onset or progression of neurodegeneration in mammals, including rotenone, aluminum, copper, zinc, lead, manganese, methylmercury, and others (reviewed by Cannon and Greenamyre (2011) and Shao et  al. (2015)). Mitochondrial dysfunction is associated with exposure‐induced neurodegeneration in C. elegans (Caito and Aschner 2016; Gonzalez‐Hunt et  al. 2014; Vanduyn and Nass 2014; Zhou et  al. 2013), as well as mammalian models and humans (reviewed by Aschner et  al. (2009)). Mitochondria exhibit a proclivity toward accumulating pollutants for a variety of reasons (Meyer et al. 2013), which is usually directly related to toxicity. Divalent metals accumulate in mitochondria via the calcium uniporter (Section  43.1), and recent evidence points to a potential mechanism for mitochondrial accumulation of metals in other valence states. The C. elegans homologue of divalent metal transporter 1 (DMT1), SMF3, is a novel aluminum (Al3+) transporter in vivo and has been implicated as an essential component of neurodegeneration associated with Al3+ exposure (Vanduyn et  al. 2013). DMT1 itself has since been found in the outer mitochondrial membrane (co‐localizing with voltage‐dependent anion channel 1, Tom6, and COXII) in mammalian cells and yeast (Wolff et al. 2014a, b), suggesting that DMT1 is involved in metal import to mitochondria in mammals. This discovery of DMT1 mitochondrial localization in mammals lends credence to the possibilities that Al3+ toxicity mediated by the DMT1 homologue in C. elegans is due at least in part to mitochondrial toxicity, and that C. elegans provides a model with which to study these mitochondrial components of exposure‐induced neurotoxicity in vivo.

The C. elegans model brings to the table several particular strengths for these studies, including the ability to monitor neurodegeneration in vivo, the ability to test genetic sensitivity using mutants and RNAi knockdown, and the ability to screen a large number of individuals (and thus chemicals and doses and gene × environment interactions) quickly. This is important for neurodegeneration, as for mitochondrial toxicity, because the environmental contributions to neurodegeneration are as‐yet poorly understood, and a relatively small number of chemicals have received most of the attention. Recent studies have identified novel candidate chemicals for dopaminergic neurodegeneration, including glyphosate (McVey et al. 2016; Negga et al. 2012), selected for testing based in part of volume of use and likelihood of exposure, and aflatoxin B1 (Gonzalez‐Hunt et  al. 2014), selected for testing based on mechanism of action (generation of irreparable mitochondrial DNA damage). Similarly, recent work has demonstrated increased sensitivity of strains lacking mitochondrial homeostasis‐ related genes to pollutant‐induced neurodegeneration, including paraquat and decreased neurite outgrowth in mitophagy‐deficient pink‐1 mutants (Samann et  al. 2009). Work demonstrating that agents that cause neurodegeneration in mammals do the same in C. elegans supports the possibility that novel findings in nematodes such as those described in this paragraph will be extrapolatable to mammals. However, given the decreased complexity of the nematode nervous system (Section  43.3), these findings will need to be tested in higher eukaryotes. Environmental exposures include not only anthropogenic chemicals and their metabolites but also naturally derived compounds and their respective metabolites (i.e., essential metals, bacteria, etc.). A novel metabolite of Streptomyces venezuelae causes dopaminergic neurodegeneration in C. elegans associated with inhibition of complex I of the ETC, induction of the mitochondrial unfolded protein response (mtUPR), and decreased ATP (Ray et  al. 2014). This bacterial metabolite‐induced mitochondrial toxicity was directly tied to dopaminergic neurodegeneration, as pharmacologic rescue of complex I activity (by either riboflavin or d‐beta‐hydroxybu‑ tyrate) abrogated dopaminergic neurodegeneration in C. elegans (Ray et  al. 2014). This group then showed, using C. elegans as a model for neurotoxicity, that this novel bacterial metabolite causes mitochondrial fragmentation by disrupting proteostasis through dysregulation of ubiquitin pathways, which are genetically regulated by loss of pink‐1 (the C. elegans homologue of PINK1) homeostasis mechanisms (Martinez et al. 2015). Further, the metabolite works synergistically with α‐ synuclein, amyloid‐beta, and mutant huntingtin to cause neurodegeneration in vivo (Martinez et al. 2015), likely

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mediated by defects in mitophagy. These findings provide direct evidence of a novel environmental mitotoxicant mediating neurodegeneration in vivo and are especially striking in models of neurodegeneration, since most cases of neurodegenerative disease are idiopathic in nature and likely require some environmental component (reviewed by Cannon and Greenamyre (2011)). 43.5.3 General Stress Response Mechanisms Important for Mitigating Mitochondrial Toxicity and Promoting Healthspan: Discoveries in C. elegans C. elegans has been instrumental in establishing mitochondrial function as a determinant of longevity in vivo (reviewed by Dancy et  al. (2014), Kirstein‐Miles and Morimoto (2010), and Wolff and Dillin (2006)). Many of the mitochondrial mechanisms probed in these longevity studies are important for mitigating mitochondrial toxicity and are conserved between C. elegans and mammals. Examples of these important mechanisms include the mtUPR (Haynes et al. 2007; Houtkooper et al. 2013; Nargund et  al. 2012) and downstream effects of ETC inhibition (Durieux et  al. 2011; Munkacsy et  al. 2016). Many genetic manipulations that result in activation of the mtUPR also confer both stress resistance and extended lifespan (Tian et  al. 2016), although these responses are to some extent nonmonotonic. For example, inhibition of ETC activity by RNAi, which can be titered quantitatively, results at very low levels of inhibition in no effect on lifespan, then lifespan extension at slightly higher levels, and finally shortened lifespan at high levels (Rea et al. 2007). Work in C. elegans has also helped to uncover the paradoxical nature of the role of mitochondrial ROS (mtROS) and total cellular ROS in aging and propagation of oxidative damage (reviewed by Back et al. (2012a)). A certain amount of mtROS is required for many signaling processes (reviewed by Shadel and Horvath (2015)) and appears to be part of an adaptive response to exposures (Wang and Xing 2010) and aging (Schaar et  al. 2015). The specific effects of individual ROS and the threshold concentrations at which ROS move from essential to detrimental are difficult to untangle, but progress has been made in C. elegans models of mitochondrial mechanisms in this regard. Increasing mitochondrial superoxide levels (either by exposure to paraquat or by deletion of mitochondrial superoxide dismutase), at least up to certain levels, increases lifespan in C. elegans, whereas deletion of cytoplasmic superoxide dismutases significantly decreases lifespan (Schaar et al. 2015), suggesting divergent roles of intracellular compartment‐specific levels of superoxide on lifespan. Repression of mitochondrial peroxiredoxin does not alter lifespan, but decreases ATP

levels, brood size, and motility in wild‐type C. elegans, suggesting that a sufficient concentration of mitochondrial hydrogen peroxide is required to maintain these ATP‐dependent mechanisms (Ranjan et al. 2013). New areas of discovery in C. elegans aging, mtROS signaling, and thresholds of mtROS‐mediated damage continue to emerge through the continued use of mutant backgrounds and exposures across the life course. However, from a toxicological perspective, some caution may be warranted in interpreting these results. For example, deletion of mitochondrial SODs also results in increased sensitivity to a variety of stressors. Furthermore, some of the same responses that result in stress resistance in some contexts, and lifespan extension, carry other fitness costs. For example, Rea et al. reported reduced fecundity and developmental rate in the same nematodes in which RNAi‐based knockdown of ETC resulted in lifespan extension (Rea et al. 2007). C. elegans is an excellent model in which to explore the relationship between hormetic and toxic responses to environmental stressors, an emerging area of research interest for the toxicological community (Mattson 2008a, b) that may have important mitochondrial components (Schmeisser et al. 2013). 43.5.4 Emerging Roles for C. elegans in Investigating Environmental Mitotoxicants The utility of C. elegans, along with other simpler eukaryotes such as Drosophila melanogaster and D. rerio, is appreciated in current and upcoming phases of the Tox21 program (Merrick et al. 2015), a large‐scale governmental effort to move toward higher‐throughput alternatives to traditional animal models in toxicology. Aside from integrative systematic approaches to toxicology, C. elegans continues to be employed in academic institutions to investigate specific hypotheses across a wide range of mitotoxicants. These discoveries are novel for a range of reasons, and include unexpected roles for mitochondrial modulation in phosphine exposure (Zuryn et  al. 2008), inhibition of the UPR by mitochondrial enzyme‐specific mitigation of hydrogen sulfide toxicity (Horsman and Miller 2016), and new mitochondria‐specific interactions with proteotoxic products of aging (Cacho‐Valadez et al. 2012). The advent of modeling sublethal mixture toxicity in C. elegans (Gomez‐Eyles et al. 2009; Jager et al. 2014) provides for the opportunity to screen for synergistic effects of known and suspected mitotoxicants. Discoveries in C. elegans bring the advantageous combination of medium‐ to high‐throughput capacity for analysis and the physiological complexity of an in vivo system. These, and the availability of diverse and specific genetic backgrounds, are strengths of the C. elegans model for isolating complex mitochondrial mechanistic components of environmental exposures.

Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

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Detection of Mitochondrial Toxicity of Environmental Pollutants Using Caenorhabditis elegans

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44 Persistent Organic Pollutants, Mitochondrial Dysfunction, and Metabolic Syndrome Hong Kyu Lee1 and Youngmi Kim Pak2 1 2

Department of Internal Medicine, College of Medicine, Eulji University, Seoul, South Korea Department of Physiology, College of Medicine, Kyung Hee University, Seoul, South Korea

CHAPTER MENU 44.1 44.2 44.3 44.4 44.5 44.6 44.7 44.8 44.9 44.10 44.11

44.1

Introduction, 691 Health Hazard of Environmental Chemicals: A Short History, 691 Low‐Level Exposure to Multiple Chemicals, 692 POPs and Obesity Paradox, 692 Body Burden of Chemicals, 693 Diabetes Mellitus, Insulin Resistance, and Metabolic Syndrome, 693 Association of POPs with Diabetes and Metabolic Syndrome, 695 Toxic and Biological Effects of Some POPs via AhR, 696 Insulin Resistance and Mitochondrial Dysfunction, 698 Measurement of POPs, 702 Summary, 703 References, 703

Introduction

Metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM) are worldwide public health problems. Currently, it is believed that high calorie diet and sedentary lifestyle are main causes of obesity and the interaction between genetic and environmental factors is associated in the onset of obesity, which are T2DM and MetS. However, 75–80% of obese people never develop T2DM (Gregg et al., 2007), so there may be other environmental factors. Recent epidemiological studies suggest a possible contribution of environmental chemicals to metabolic diseases such as MetS, T2DM (Lee et  al., 2006a), and insulin resistance (IR), a prediabetic state (Lee et  al., 2007a). More importantly, mitochondrial dysfunction was suggested to be an underlying cause of IR, MetS, and T2DM (Lee et al., 2010; Petersen et al., 2003, 2004). Optimal mitochondrial function is central to cell physiology. A wide range of chemicals has been reported to disturb mitochondrial function and cause mitochondrial toxicities and diseases (Vuda and Kamath, 2016; Wagner et  al., 2008). Additionally, a series of recent

studies demonstrated the connections between various environmental chemicals and metabolic disorders (Neel and Sargis, 2011). In this chapter, we will provide evidence that environmental chemicals may induce mitochondrial dysfunction resulting in IR, T2DM, and MetS.

44.2 Health Hazard of Environmental Chemicals: A Short History Concerns about environmental chemicals began in 1962 after Rachel Carson published the monumental book entitled Silent Spring (Lytle, 2007). In this book, she claimed that the indiscriminate use of chemicals, especially pesticides, adversely affects the environment. For example, dichlorodiphenyltrichloroethane (DDT) was developed to prevent malaria epidemic by controlling mosquitoes, but its use is now prohibited due to causing human toxicity, cancer, and other illnesses. The US Environmental Protection Agency (EPA) and the United Nations Environment Programme (UNEP) were established in 1970 and 1972, respectively, to

Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants, Volume II, First Edition. Edited by Yvonne Will and James A. Dykens. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc.

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pay closer attention to environmental chemicals and human health. UNEP proposed to control “persistent organic pollutants (POPs),” defined as “chemical substances that persist in the environment, bio‐accumulate through the food chain, and pose a risk of adversely affecting human health and the environment.” Some POP chemicals such as pesticides, industrial chemicals, and by‐products have been banned or are strictly controlled from use and production under the Stockholm Convention (http:// chm.pops.int/TheConvention/ThePOPs/tabid/673/ Default.aspx). In 2009, the Endocrine Society published the landmark paper “Endocrine Disrupting Chemicals (EDC): An Endocrine Society Scientific Statement,” known as “EDC‐1” (Diamanti‐Kandarakis et  al., 2009). Then, UNEP and the World Health Organization (WHO) copublished another landmark book, State of the Science of Endocrine Disrupting Chemicals in 2012. In 2015, the Endocrine Society published EDC‐2, The Endocrine Society’s Second Scientific Statement on Endocrine‐Disrupting Chemicals (Gore et  al., 2015). EDC‐2 described the underlying mechanisms by which exposures during development in animals and humans lay the foundation for diseases later in life. Importantly, it provided a simplified operational working definition of EDCs: an exogenous chemical or mixture of chemicals that interferes with endogenous hormonal axes and induces metabolic disruption in vitro and in vivo. Unlike the early studies of EDCs, which focused on identifying chemicals to modulate the signal transduction of sex steroid and thyroid hormones, emerging data strongly suggest that EDCs disturb the signaling pathways critical for energy homeostasis, mitochondrial activities, and insulin signaling.

44.3 Low‐Level Exposure to Multiple Chemicals Humans are exposed to a complex mixture of chemicals from various sources in everyday life. The exposure levels of individual environmental chemicals to the general population are far lower than in the case of environmental disasters such as chemical plant explosion, military personnel exposures, and occupational exposures. However, even low‐level exposure over decades to a complex cocktail of pollutants in air, water, food, consumer products, and buildings can have a significant effect on the health status of citizens (Commition, 2009). In other words, mixtures of dissimilarly acting chemicals may not be safe even if individual constituent chemicals are at levels below no observed adverse effect levels (NOAELs) or lowest observed adverse effect levels (LOAELs) (Kortenkamp et al., 2007). We refer to this

additive enhancement of chemical actions as “mixture effect” or “cocktail effect.” Many of the synthetic organic chemicals are better known for causing weight loss at high levels of exposure, but much lower concentrations of these same chemicals have powerful weight‐gaining actions. For many years, the mechanisms by which some environmental chemicals acted at low doses were not well understood. There are two major concepts in EDC studies: low‐dose and nonmonotonicity. Low‐dose effects are defined by the National Toxicology Program (NTP) as those that occur in the range of human exposures or effects observed at doses below those used for traditional toxicological studies. Nonmonotonic dose response is a nonlinear relationship between dose and effect where the slope of the curve changes sign somewhere within the range of doses examined (Vandenberg et  al., 2012), suggesting that low‐dose effects may be different, and sometimes even opposite, from high‐dose effects. Nonmonotonic responses and low‐dose effects are remarkably common in studies of natural hormones and EDCs. Hormones produced by the endocrine system are functioning at extremely low concentrations, comparable with the levels of EDCs. Natural hormone‐mimicking EDCs at low doses exert similar biological effects to hormones because they share the same receptor. Circulating natural hormones are present in three different forms: free (the active form of the hormone), bioavailable (bound weakly to proteins such as albumin), and inactive (bound with high affinity to proteins such as hormone binding proteins) (Vandenberg et  al., 2012). Protein‐ bound hormones act as a natural buffering system, allowing the hormone to be accessible in the blood, but preventing large doses of physiologically active hormone from circulating. In contrast, the majority of a circulating EDC can be physiologically active because EDC‐specific binding protein is not present. Therefore, even a low concentration of an EDC can disrupt the natural balance of endogenous hormones in the circulation. Therefore, traditional criteria for chemical testing and safety determination need to be changed to protect human health.

44.4

POPs and Obesity Paradox

POPs are lipophilic chemicals that accumulate in adipose tissue and are hard to eliminate from contaminated environments and human bodies. POPs of concern at present are polychlorinated dibenzo‐p‐dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyl congeners (PCBs), organochlorine pesticides (OCPs), and brominated flame retardants (BFR). Simultaneous exposure to various POPs may cause obesity and diabetes as a mixture effect in the general population

Persistent Organic Pollutants, Mitochondrial Dysfunction, and Metabolic Syndrome

(Lee et  al., 2006b, 2011), which posited environmental “obesogen hypothesis.” This hypothesis postulates that certain EDCs or POPs that interfere with the body’s adipose tissue biology, endocrine hormone systems, or central hypothalamic–pituitary–adrenal axis are derailing the weight control homeostasis (Grun and Blumberg, 2009; Heindel et  al., 2015). It is important to note that POPs in fat tissue, not obesity itself, may contribute to the development of IR and T2DM. An “obesity paradox” has been documented that the overweight and obese elderly have better prognosis than those with normal body weight. This may reflect the relative safety of storing the harmful lipophilic POPs in adipose tissue rather than in bloodstream, which damage other critical organs (Hong et al., 2012).

44.5

Body Burden of Chemicals

More than 800 chemicals may contain endocrine‐disrupting activity (Gore et  al., 2015). Table  44.1 summarized the nature and health hazards of individual POPs and/or EDCs. We did not include heavy metals such as arsenic and cadmium in the table although they are known to be toxic to mitochondria (Prakash et al., 2016) and are causally associated with diabetes and cardiovascular diseases (Kuo et al., 2015; Moon et al., 2013). For better understanding the nature and distribution of EDCs, we categorized them into two groups: nonpersistent and persistent chemicals according to half‐life. Each group is then subdivided by usage or source. Nonpersistent chemicals, such as bisphenol A (BPA) and phthalates, released from widely used plastics and epoxy resins, are commonly detected in most populations. The herbicide atrazine and the fungicide vinclozolin are of great importance in agriculture and are easily excreted. Diethylstilbestrol (DES) and ethinyl estradiol (EE) are synthetic estrogen‐like compounds, which are used as drugs and are involved in carcinogenesis. Without accumulation in the body, nonpersistent EDCs still enhance the risk of diseases such as cancer, liver damages, and/or neurological disorders (Gore et al., 2015; Heindel et al., 2015). Owing to the short biological half‐life of nonpersistent EDCs, human epidemiological studies did not clearly show an association of the plasma or urine levels of EDCs with incidence of obesity and diabetes (James‐Todd et  al., 2016; Lind et al., 2012; Sun et al., 2014). But several animal studies demonstrated that exposure to environmentally relevant doses of these compounds increased body weight, suggesting they are obesogens (Angle et  al., 2013; Lim et  al., 2009). Estrogen receptor has been thought to mediate their obesogenic activities, while adipocyte differentiation and adipogenesis might also be involved via

various mechanisms (Biemann et al., 2012; Chamorro‐Garcia et al., 2012; Heindel et al., 2015). In contrast, persistent EDCs such as dioxins, OCPs, and other POPs are accumulated and stored in adipose tissue. The classification by persistency may help understand the “body burden,” which is defined as the total amount of environmental chemicals that are present in the human body at a given point in time. Body burden tests analyze the concentration of environmental chemicals in blood, urine, breast milk, and other fluids and tissues. This biomonitoring test tells us about the extent of our exposure to various substances, but not necessarily what the effects of this “burden” will be. Because of lipophilicity, a large amount of POPs can be stored in fat tissue depot that may sequester those toxic persistent chemicals to protect vital organs. Upon lipolysis of stored fat, the lipophilic chemicals can also be released into blood from the storage. Therefore, weight loss in the obese elderly with high serum concentrations of POPs may carry some risk of damage on vital organs by the released chemicals although weight loss may be beneficial among the obese elderly with low POP concentrations. To prevent the surge of persistent chemicals into blood, we believe that the biomonitoring test for the chemicals should be performed during weight control or health checkup processes. At the same time, sampling of blood or urine should be done at certain fixed times of the day, like early in the morning without stress, for consistent and reliable monitoring. This classification may also be useful to locate EDCs geographically. Some insecticides are used mostly in rural agricultural areas, while many other POPs are associated with industrial activities.

44.6 Diabetes Mellitus, Insulin Resistance, and Metabolic Syndrome Diabetes is defined by high blood glucose level. In normal physiology, high blood glucose should only occur with low level of insulin, the most important glucose‐ lowering hormone. However, subjects with T2DM frequently have high blood glucose levels with rather high serum insulin levels, suggesting a development of IR in the body. Current paradigm understanding of diabetes is that it occurs when insulin production cannot overcome IR induced by high fat diet and inactivity. Therefore, diabetes is characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. MetS is a cluster of the most dangerous cardiovascular risk factors: hyperglycemia, prediabetes (IR), abdominal obesity, hypertension, and dyslipidemia (Huang, 2009). Reaven named the clustered state of risk factors as syndrome X in 1993 (Reaven, 1988, 1993). In 2001, the Adult

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Table 44.1 The nature of common EDCs or POPs and their known health hazards. Class

Chemicals

Nature

Known health hazards

Nonpersistent

Bisphenol A

Used in plastics and resins

Estrogenic, obesogenic, neurological effects, adverse thyroid hormone action, reproductive and developmental effects

Phthalates

Plasticizers

Carcinogen, liver damage, reproductive and developmental effects, asthma, obesogen

Atrazine

Chlorotriazine herbicide

Endocrine, respiratory, and nervous system targets, liver damage, obesogenic; increases aromatase expression; antiandrogenic

Vinclozolin

Dicarboximide fungicide

Antiandrogenic activity, male reproductive and neurological effects, transgenerational reproductive effects, potential carcinogen

Diethylstilbestrol (DES)

Used as drugs; nonsteroidal synthetic estrogen

Transplacental carcinogen, teratogen

Ethinyl estradiol

Used as drugs; synthetic derivative of 17β‐estradiol

Cardiovascular disease, cerebrovascular disease, thromboembolic disease, gallbladder disease, carcinogenic

Methoxychlor

Organochlorine insecticide

Central nervous system depression, damage to liver and kidney, developmental and reproductive effects in animals, transgenerational kidney and ovary disease, obesogen; binds ER

DDT, DDD, and DDE

Organochlorine insecticides and its metabolite

Carcinogen, central nervous system, kidney, liver and peripheral nervous system effects

TCDD or dioxin

Released from industries; most toxic among dioxins or PCDDs

Liver damage, weight loss, atrophy of thymus gland, immunosuppression, reproductive effects, and cancer

PCDFs

Released from industries; organochlorines

Developmental teratogen and carcinogen

PCBs

Released from industries; organochlorines; 209 possible congeners

Carcinogen, chloracne, stomach and liver damage, reproductive and nervous system effects and thyroid injury, stimulation of fat production; impairs glutamate pathways, mimics estrogen, antiestrogenic activity, and so on

PBDEs

Released from industries; pentaBDE, octaBDE, decaBDE

Alters TH synthesis

PFOA and PFOS

Released from industries; perfluorochemical

Liver and mammary gland developmental and immune system toxicant, carcinogen

Aldrin/dieldrin; chlordane and related compounds; endrin; mirex; heptachlor; hexachlorobenzene; toxaphene

Rarely detected

Estrogenic activity; binds ER; sexually dimorphic behavior Stimulates glucocorticoid receptor; decreases testosterone levels; induces testosterone hydroxylases; modulates binding of ligand to TRE; weakly binds AhR

Persistent

DDD, dichloro‐diphenyldichloro‐ethane; DDE, dichloro‐diphenyldichloro‐ethylene; DDT, p,p′‐dichloro‐diphenyltrichloro‐ethane; DES, diethylstilbestrol; PBDEs, polybrominated diphenyl ethers; PCBs, polychlorinated biphenyls; PCDD, polychlorinated dibenzo‐p‐dioxin; PCDFs, polychlorinated dibenzo‐p‐furans; PFOA, perfluorooctanoic acid; PFOS, perfluoro‐octane yl sulfonic acid; TCDD, tetrachloro‐dibenzo‐p‐dioxin.

Treatment Panel III (ATP III) of the National Cholesterol Education Program of the United States made different diagnostic criteria (Table  44.2), which are now widely used (Expert Panel on Detection and Treatment of High Blood Cholesterol in 2001). It should be noted that the ATP III was created to define MetS for clinical purpose.

Although the MetS is frequently considered as a disease entity, it is a diagnostic category, identifying individuals to initiate lifestyle changes with the goal of decreasing risks of cardiovascular disease, the most important cause of death (Mortality and Causes of Death 2015). IR is a pathophysiological state in which body and cells fail to

Persistent Organic Pollutants, Mitochondrial Dysfunction, and Metabolic Syndrome

respond normally to insulin. But IR is found not only in diabetes but also in many other disease states, such as dyslipidemia, hypertension, and neurodegenerative diseases (Reaven, 1988; Shen et al., 1970), suggesting that IR may be a critical contributor in developing these diseases. The primary value of the concept of IR is that it provides a framework for placing a substantial number of apparently unrelated biological events into a pathophysiological construct (Reaven, 2005). This point is crucial in understanding the association between exposure to environmental chemicals and IR or MetS, because high exposure to environmental chemicals frequently occurs together with IR.

44.7 Association of POPs with Diabetes and Metabolic Syndrome 44.7.1

In 2002, Baillie‐Hamilton hypothesized that the toxic chemicals might be obesogenic, based on an observation that there is a parallel increase of chemical toxin production and incidence of obesity (Baillie‐Hamilton, 2002). The parallelism was firmly established with diabetes in 2011 by Neel and Sargis (2011). Figure  44.1 demonstrated that obesity and diabetes epidemic in United States might be closely related to the increasing production and usage of synthetic organic chemicals. These data suggest that the human exposure to the chemical compounds is strongly suspected as a causal factor in developing the diseases (Heindel et al., 2017).

Table 44.2 ATP III criteria for diagnosing the metabolic syndrome. Any three or more of the five criteria are met

Abdominal obesity

Waist circumference (WC)

44.7.2 Epidemiologic Studies on the Association between POPs and T2DM

Men: WC > 40 inches (102 cm) Women: WC > 35 inches (89 cm) Hyperglycemia

Prior to Baillie‐Hamilton’s report, there have been many anecdotal reports linking exposure to POPs and development of diabetes. However, epidemiologic studies began only recently to prove the association between serum levels of POPs and T2DM. Lee et al. (2006b, 2007a, b) analyzed US NHANES 1999–2002 database and provided critical evidence for the involvement of serum concentrations of POPs in obesity or diabetes. They showed that the sum of 6 most frequently detected POPs (2,2′,4,4′,5,5′‐ hexachlorobiphenyl, 1,2,3,4,6,7,8‐heptachlorodibenzo‐p‐ dioxin, 1,2,3,4,6,7,8,9‐octachlorodibenzo‐p‐dioxin, oxychlordane, p,p′‐dichlorodiphenyltrichloroethane, and

Fasting glucose >110–126 mg/dL (6.1–7.0 mmol/L)

Dyslipidemia

Triglycerides (TG) >150 mg/dL (1.7 mmol/L)

Dyslipidemia

High‐density lipoprotein cholesterol (HDL‐C) Men: 130/80 mm Hg

Chemical production

8 (40)

Diabetes (%) 250

Obesity (%)

6 (35)

200 150

4 (30)

100 2 (25) 50 0 1940 1950 1960 1970 1980 1990 2000 2010 Year

0 (20)

Prevalence (%)

MetS criteria

Ecological Studies

695

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trans‐nonachlor) among US citizens was clearly associated with prevalence of diabetes (Lee et al., 2006b, 2014), which made quite a stir to the scientific community. Cross‐sectional and case–control studies have reported strong associations of T2DM and MetS with OCPs, dioxins, PCBs, and/or dichlorodiphenyldichloroethylene (DDE) (Taylor et al., 2013). There is less indication of an association between T2DM and other non‐organochlorine POPs, such as perfluoroalkyl acids and brominated compounds. There are more than 80 epidemiological studies, showing that POPs are related to altered glucose homeostasis, IR, and/or MetS. As this chapter aims to introduce this field, authors recommend other review articles (Gore et  al., 2015; Lee et  al., 2014; Taylor et  al., 2013) for further details, such as EDC‐2 (Gore et  al., 2015) and the NTP workshop review (Taylor et al., 2013; Thayer et al., 2012), which was organized by US NTP in 2011. In summary, epidemiologic studies have provided sufficient overall evidence for proving a positive association between some organochlorine POPs, BPA, phthalates, organotins, and arsenics with T2DM. 44.7.3 Animal Experiments: Low‐Dose Exposure to Chemicals and Development of Diabetes Experimental data are needed to confirm the causality of low‐level exposure to POPs, which will shed new light on the pathogenesis of diabetes. Lim et al. (2009) reported that atrazine, a chlorotriazine herbicide when given at low concentration, caused IR and induced mitochondrial dysfunction in skeletal muscle in rats, when fed with high fat diet for 2 months. Ruzzin et al. (2010) found that feeding contaminated Atlantic salmon oil to rats for 28 days induced IR and fatty liver. In addition, it induced downregulation of two master regulators of lipid homeostasis, insulin‐induced gene‐1 and Lpin1, as well as genes related to mitochondrial function, including peroxisome proliferator‐activated receptor‐γ (PPARγ) coactivator‐1α (PGC‐1α), citrate synthase, succinate dehydrogenase A, and medium‐chain acyl‐CoA dehydrogenase, in the liver of rats. In addition, various EDCs at low doses were studied for their diabetogenic or obesogenic effects (Heindel et al., 2017; Vandenberg et al., 2012). For example, BPA alone or in combination with DES induced either diabetes or obesity in animal studies. DDT, phthalate metabolites, PCBs (−77, −126, −153), perfluorooctanoic acid (PFOA), perfluoro‐octane yl sulfonic acid (PFOS), tributyltin (TBT), and tetrachlorodibenzo‐p‐dioxin (TCDD), alone or in combinations, are also listed as causative agents for obesity and diabetes (Heindel et  al., 2015, Ngwa et al., 2015; 2016). In fact, there are lots of EDCs for which high‐dose toxicology studies have been performed

and the NOAEL has been derived, but no animal studies in the low‐dose range. Also, several hundred additional EDCs where no significant high‐ or low‐dose testing have been performed. Table 44.3 summarizes a limited selection of the environmental chemicals that are related with obesity and T2DM, nuclear receptors involved in function, and the reported effects on mitochondria. 44.7.4 Cause–Effect Relationship between Exposure to POPs and the Onset of T2DM or MetS Despite many reports, there is no direct evidence that the exposure to POPs is the cause of T2DM or MetS in humans. There are several reasons. Traditionally, a cause of a disease is established when the suspected causative agent meets Koch’s three principles: (i) that agent is always present in the persons with a specific disease, (ii) that agent could be isolated in pure form, and (iii) that transfer of that pure agent reproduces disease in susceptible animals. These principles are not applicable here, because environmental pollutants are enormously diverse chemicals with varying toxicities and the diseases they cause are not specific, but complex. POPs are present in the environment as mixtures of chemicals, some with known toxicities, but potentially others with many unknown ones; hence, they cannot qualify as a specific “causative agent.” It is estimated that about 10,000 new chemicals are synthesized and released to our environment every year without evaluation of their toxicity in humans. Also, there is no good method of evaluating biological or toxicological effects of mixtures of POPs, to which people are exposed. T2DM itself, a component disease of MetS, is a “complex disease,” meaning that T2DM may have many “causes.” It is reasonable to hypothesize that clustering of complex diseases in a person may be a result of introducing a mixture of POPs into our body.

44.8 Toxic and Biological Effects of Some POPs via AhR Some POPs are known to induce adverse effects on various biological systems via binding to aryl hydrocarbon receptor (AhR), a cytosolic nuclear receptor present in most vertebrate tissues (Schlezinger et  al., 2010). AhR is a ligand‐activated transcription factor belonging to the basic helix‐loop‐helix (bHLH)/Per‐Arnt‐Sim family (Beischlag et al., 2008). Ligand binding to AhR activates the transcription of multiple genes including cytochrome P450 (CYP) members, CYP1A1/2 and CYP1B1, and ligand‐metabolizing enzymes. Induction of CYP enzymes enhances the metabolism and clearance of AhR ligands

Table 44.3 Environmental chemicals associated with T2DM and obesity.

Human epidemiological studies

Chemical

Examples

Type or source

PCDD, PCDF

POPs/210 dioxins and furans, 17 highly toxic (e.g., TCDD)

In food, air pollution, incomplete combustion of fossil fuels

MetS, obesity, and T2DM

PCBs

POPs/209 possible congeners (e.g., PCB126, PCB169)

Coolants, plasticizers, and flame retardants

HCB

POPs

OCPs

Potential mechanism: nuclear receptor

Animal studies

Mitochondrial dysfunction

AhR, PPARγ, ERs

Affects energy metabolism, accumulation of visceral fat, inflammation

Mitochondrial fragmentation, decreased OCR, ROS generation, decreased membrane potential, ATP level

MetS, obesity, T2DM, childhood obesity

AhR, PPARγ, ERs

Altered thyroid function, Altered metabolism, bioaccumulation in fat cells

ROS generation, decreased membrane potential, ATP level. Inhibition of OXPHOS complexes I, II, and IV

Fungicide, a byproduct of the industrial chemicals (e.g., CCl4)

Overweight. Obesity in offspring

AhR, TH‐ responsive genes

Obesity in infancy and childhood

NA

POPs/DDT, DDE, endrin, heptachlor, mirex, toxaphene

Pesticides, insecticides

MetS, obesity, T2DM, and childhood obesity

AhR, PPARγ, ERs

Glucose intolerance, hyperinsulinemia, dyslipidemia, altered bile acid metabolism (rat), gender differences

Reduced energy expenditure, impaired thermogenesis

BFR

PBB, PBDE

Chemicals applied to furniture and electronics

Associated with MetS, obesity, and T2DM

PXR, ERs, TR

Alters lipolysis and glucose oxidation (rat)

Impaired mitochondrial bioenergetics, membrane potential, OCR, calcium release, mitochondrial swelling, and ATP levels

PFCs

PFOA, PFOS

Components of lubricants, nonstick coatings, and stain‐ resistant compound

Increased cholesterol level, offspring obesity

ERs, AR, PPARs

Weight gain and increased serum insulin and leptin levels (mice), increased adipocyte differentiation

Alteration in energy metabolism genes, ATPase, OXPHOS complexes 1 and IV, ROS generation

Phthalates

DEHP, DBP, DEP, MEHP

Plasticizers, adhesives, and personal care products

Obesity, insulin resistance

PPARs, CAR/ PXR, GR

Reduced plasma insulin and leptin levels (mice), increased rate of adipocyte differentiation

Uncoupler, mitochondria swelling, inhibiting succinate dehydrogenase

BPA

BPA

Plastics and epoxy resins

Diabetes, insulin resistance, childhood obesity, liver abnormalities

ERs, AR, TR, GR

Increased body weight (mice, rat), Induced adipogenesis

Altered morphology, membrane potential, mass, etc. ROS generation

Organotins

TBT, TPT, TPTO

In food. Fungicide in paints and heat stabilizer in polyvinyl chlorides, pesticide, wood preservation

Obesity

PPARγ, RXR

Induced adipogenesis (mice), increased fat cell differentiation, increased lipid accumulation

NA

AhR, aryl hydrocarbon receptor; AR, androgen receptor; BFR, brominated flame retardant; BPA, bisphenol A; CAR, constitutive androstane receptor; DBP, dibutyl phthalate; DDE, dichlorodiphenyldichloroethylene; DDT, dichlorodiphenyltrichloroethane; DEHP, diethylhexyl phthalate; DEP, diethyl phthalate; ER, estrogen receptor; GR, glucocorticoid receptor; HCB, hexachlorobenzene; MEHP, bis(2‐ethylhexyl) phthalate; MetS, metabolic syndrome; OCPs, organochlorine pesticides; OCR, oxygen consumption rate; PBDE, polybrominated diphenyl ether; PCB, polychlorinated biphenyl; PCDD, polychlorinated dibenzo‐p‐dioxins; PCDF, polychlorinated dibenzofurans; PFC, polyfluoroalkyl compound; PFOA, perfluorooctanoate; PFOS, perfluoro‐ octane yl sulfonic acid; PPAR, peroxisome proliferator–activated receptor; PXR, pregnane X receptor; RXR, retinoid X receptor; T2DM, type 2 diabetes; TBT, tributyltin chloride; TCDD, 2,3,7,8‐tetrachlorodibenzo‐p‐dioxin; TPTO, bis(triphenyltin) oxide; TR, thyroid hormone receptor.

698

Mitochondrial Dysfunction by Drug and Environmental Toxicants

in liver. Since 2,3,7,8‐TCDD is the most potent AhR ligand with high affinity, AhR is called the dioxin receptor. AhR is able to bind a wide range of structurally divergent chemicals, suggesting that AhR contains promiscuous ligand binding site (Denison et  al., 2011). Dennison et al. (Denison and Nagy 2003; Denison et al., 2002) reported exogenous AhR ligands covering diverse synthetic environmental chemicals or naturally occurring compounds such as indole‐3‐carbinol (I3C) and flavonoids using AhR‐mediated reporter gene assays. I3C dietary AhR ligand provided from vegetables protects the host by an induction of active immunologic tolerance in the intestine (Li et al., 2011). A tryptophan catabolite, kynurenine, has been identified as an endogenous AhR ligand that is constitutively generated in human brain tumor cells (Opitz et al., 2011). AhR ligands mediate a wide range of biological and toxic effects, including tumor promotion; teratogenicity; immuno‐, hepato‐, cardio‐, and dermal toxicity; wasting; lethality; and alteration of endocrine homeostasis (Denison et al., 2011). The molecular mechanisms underlying AhR ligand action have been studied with multiple molecules interacting with AhR (Denison et al., 2011). In classical mechanism of AhR‐dependent gene activation, the cytosolic AhR forms a complex with HBV X‐associated protein 2 (XAP2), Hsp90, and p23 (Shetty et al., 2003), which are displaced by Arnt after binding to the ligand. The resulting AhR/Arnt dimer binds to a drug response element (DRE) (5′‐TNGCGTG‐3′) on the promoters of target genes such as CYPs, aldehyde dehydrogenase 3 (ALDH3), AhR repressor (AhRR), p27kip1, and so on. AhRR is another bHLH/Per‐Arnt‐Sim transcription factor, which is also induced by AhR/Arnt complex upon binding on the DRE of AhRR promoter. Unlike other target genes, the transactivation domain‐deficient AhRR functions as a naturally occurring dominant negative factor by competing with AhR for heterodimer formation with Arnt (Evans et al., 2008). Therefore, AhRR and AhR constitute a regulatory loop affecting each other’s transcriptions to maintain a homeostasis. In various human malignant tissues, AhRR mRNA is downregulated due to methylation of DRE sites of the promoter, suggesting that AhRR might play a role as a tumor suppressor (Zudaire et  al., 2008). Despite accumulation of evidence showing that many environmental chemicals are AhR ligands and destroy mitochondrial activities, it is not clearly understood whether their toxic effects are linked to mitochondrial damages. TCDD increases mitochondrial ROS production, which was observed in liver mitochondria of CYP1A1 null mice, but not in those of AhR null mice (Senft et al., 2002). The AhR‐dependent oxidative stress in mitochondria mediated the concomitant mitochondrial DNA (mtDNA) cleavage (Shen et  al., 2005). Proteomic analysis of AhR‐interacting proteins showed that ligand‐ absent AhR was interacting with ATP5α, a subunit of

adenosine triphosphate (ATP) synthase in mitochondria and this interaction was lost upon 10 nM TCDD treatment (Tappenden et al., 2011). Recently, it was found that AhR was present in the intermembrane space of mitochondria. TCDD exposure at 10 nM induced a degradation of mitochondrial AhR, reduction of respiratory capacity, and alteration of mitochondrial proteome in an AhR‐dependent manner (Hwang et  al., 2016). The AhR was also suggested as a regulator of the influx of electrons into electron transfer chain to maintain cellular respiratory capacity. A study using C2C12 skeletal myoblast cells demonstrated that nongenomic AhR signaling generated TCDD‐induced mitochondrial toxicities (Biswas et  al., 2008). Therefore, both genomic and nongenomic AhR signaling would affect mitochondrial toxicities by prolonged TCDD exposure as the TCDD‐induced transcription‐independent retrograde signaling from the mitochondria to the nucleus.

44.9 Insulin Resistance and Mitochondrial Dysfunction Impaired mitochondrial function is linked with aging as well as many pathological states including IR, T2DM, MetS, obesity, and cancer (Petersen et  al., 2003; Vuda and Kamath, 2016). Mitochondria are locations for metabolism of glucose, fatty acid, and protein and calcium homeostasis and are the control tower for cell death. When mitochondrial oxygen consumption is decreased due to altered metabolism, there is an increase in reactive oxygen species (ROS) that can impair different types of molecules and cells. Reversely, insulin is able to stimulate mitochondrial function by enhancing mitochondrial dynamics via the Akt‐mTOR‐NFkappaB‐ Opa‐1 signaling pathway (Parra et al., 2014). Several human studies suggest that mild mtDNA variants, haplogroup or single‐nucleotide polymorphism, may be associated with aging or diseases although mechanistic evidence at the molecular level is lacking. Some human mtDNA variations are associated with IR. Several population studies showed that mitochondrial haplogroup N9a confers resistance against T2DM, MetS (Fuku et al., 2007; Hwang et al., 2011; Tanaka et al., 2007), and diabetic complications (Niu et al., 2015). Conplastic animals with the same nuclear genome but with different mtDNAs show profound transcriptomic, proteomic, and metabolomic differences (Latorre‐Pellicer et  al., 2016). These mtDNA variations were linked to risk factors for T2DM, reduced mitochondrial oxidative phosphorylation (OXPHOS) enzyme levels, IR, cardiac hypertrophy, and systolic dysfunction (Houstek et al., 2014; Pravenec et al., 2007). Recent systematic characterization of conplastic mice throughout their lifespan showed that the mtDNA haplotype profoundly influences mitochondrial

Persistent Organic Pollutants, Mitochondrial Dysfunction, and Metabolic Syndrome

proteostasis and ROS generation, insulin signaling, obesity, and aging parameters and mitochondrial dysfunction (Latorre‐Pellicer et al., 2016). In fact, blood mtDNA content was decreased and mitochondrial function in skeletal muscle was reduced in subjects with IR, offsprings of T2DM, or prediabetes (Petersen et al., 2003; Shoar et  al., 2016). When mtDNA was artificially depleted using ethidium bromide, cellular glucose uptake and glucose metabolism were critically impaired (Park et  al., 2001). Therefore, we believe that mitochondrial function needs to be maintained during lifetime to ensure healthy status (Lee et al., 2010). 44.9.1 Mitochondrial Damages Induced by Environmental Chemicals There are many different ways to damage mitochondria. Environmental chemicals in serum may damage mitochondria of insulin‐sensitive organs such as the adipose

(b)

110

130

100 DCF-DA-ROS (% control)

Intracellular ATP (% control)

(a)

tissue, pancreas, liver, and muscles, which fail to function properly. It is not clear how environmental chemicals mediate mitochondrial dysfunction and IR although many environmental chemicals have been identified as AhR ligands. There are only a handful studies on how POPs damage mitochondria. In addition to the results described in Section 44.7.3, TCDD also induced oxidative stress (Shen et al., 2005), mitochondrial pathways of apoptosis (Camacho et al., 2005), damaged mitochondrial OXPHOS and ATP production, and disrupted cristae structure in mitochondria in cardiomyocytes (Neri et al., 2011). We also demonstrated that TCDD and diabetic serum suppressed the basal oxygen consumption rate and ATP turnover rate of mitochondria (Park et  al., 2013). TCDD at pM concentrations induced mitochondrial fragmentation and dysfunction measured by intracellular ATP concentration by luciferase–luciferin reaction and 5‐(and‐6)‐ chloromethyl‐2′,7′‐dichlorodihydrofluorescein diacetate,

90 80 70 60

120 110 100 90

0

10

20

30

40

50

60

0

TCDD (pM)

10

20

30

40

50

60

TCDD (pM)

(c)

TCDD (pM) 8

16

24

Enlarged

DsRed2-mito

0

Figure 44.2 TCDD treatment‐induced mitochondrial damages. C2C12 cells were treated with various concentrations of TCDD for 72 h. Intracellular ATP contents (a) and ROS generation (b) were determined (*p < 0.05, **p < 0.01 vs. DMSO). (c) The DsRed2‐mito‐transfected SK‐Hep1 cells were treated with TCDD as indicated and fixed. The mitochondrial morphology was visualized by confocal microscopy (×400 magnification, Scale bar = 20 µm). White box of each image was enlarged to view the morphology of mitochondria, reticular or fragmented (scale bar = 10 µm).

699

700

Mitochondrial Dysfunction by Drug and Environmental Toxicants

acetyl ester (CM‐H2DCFDA)‐stained cellular ROS generation (Figure  44.2). The list of environmental chemicals that have shown to induce mitochondrial dysfunction is summarized in Table 44.3. It should be noted that the glucose‐induced insulin secretion is mediated by mitochondrial ATP production through glucose metabolism of glycolysis and the TCA cycle. Increase in blood glucose stimulates glucose uptake into pancreatic β‐cells through glucose transporter (GLUT), where it undergoes glycolysis and mitochondrial TCA cycle to produce ATP. The increase of ATP level closes plasma membrane ATP‐ sensitive K+ channels (KATP channel) that are responsible for the resting membrane potential (ΔΨ). The cellular depolarization opens up the voltage‐dependent calcium channel (VDCC) and increases intracellular calcium level, ultimately resulting in insulin secretion (Figure  44.3). Therefore, if ATP production in mitochondrial is decreased, insulin secretion would also decrease. On the other hand, insulin signaling pathway could be disrupted by mitochondrial dysfunction. Insulin binding to insulin receptor initiates the signaling pathway, leading to glucose uptake, glycogen synthesis, lipogenesis, protein synthesis, decrease of gluconeogenesis, and lipolysis (Figure 44.4). Hub molecule of this pathway is Akt. Various mitochondrial stress‐induced damages decreased Akt phosphorylation as well as serine phosphorylation of insulin‐related substrate (IRS). Consequently, environmental chemical‐induced mitochondrial damages can shut down most insulin‐mediated responses. Recently, a whole issue of BBA Molecular Basis of Disease (Vol 1862. Issue 3, 2016) was devoted to

K+

Glucose

Ca2+

44.9.2

ΔΨ K+

Glucose

ATP

TCP

Insulin secretion

Scaling Law and Mitochondria

Cells are the basic unit of life. Each cell has a certain number of mitochondria, the content of which varies according to the energy requirements of tissue or organ. Mitochondria need to produce as much energy as the cell need for proper functioning. Our body is a complex energy‐dissipating network system that evolves to withstand the destructive forces of the environment physically and chemically using energy and resources with extraordinary efficiency. Individual organism needs to repair damaged parts and the repair process requires energy. If mitochondria cannot supply enough energy (ATP) to repair damaged parts completely, a vicious cycle of energy deficiency and tissue damage will follow. From this point of view, mitochondria play a central role in increasing the entropy of our body, ultimately leading to death. Mitochondrial function shows a complex quantitative relationship to body size, as revealed by its scaling relationship to metabolic rate or energy use (West, 2012). Ultimately, we hypothesized that this scaling relationship could explain the associations between IR and mitochondrial dysfunction. This concept can be extended to include the atherosclerotic process, a complication of T2DM and MetS. In this scheme, atherosclerosis is considered an adaptation of the vasculature to reduced energy demand, diminished mitochondrial function, and the consequently reduced nutrient needs of organs or tissues (Lee and Shim, 2013). Incretins

KATP channel

GLUT

BPA, PCBs, dioxins, PFCs, phthalates, metals

studies on connections between mitochondrial dysfunction and MetS. We refer an article by Jha et al. (2016) and some of key evidences listed in Table 44.4.

GPCR AC

VDCC Gs Ca2+ cAMP

Figure 44.3 Role of mitochondria on insulin secretion in pancreatic β‐cells. Environmental chemical‐induced mitochondrial damages decreased ATP production, leading to closure of KATP channel and depolarization of membrane potential. Consequently, insulin vesicles do not undergo exocytosis because there is no calcium ion influx into cytoplasm through voltage‐dependent calcium channel (VDCC). Incretins activating G‐ coupled receptor enhance cAMP for insulin secretion.

Persistent Organic Pollutants, Mitochondrial Dysfunction, and Metabolic Syndrome

BPA, PCBs, dioxins, OCPs, BFRs, PFCs, phthalates, metals

Insulin Insulin receptor IRS

Dysfunctional mitochondria

Pl3K Akt/PKB

Glut Glucose uptake

GSK3

Lipase

mTOR

Lipolysis

FOXO1 GS SREBP

Glycogen synthesis

PEPCK, G6Pase

ACC

Gluconeogenesis

Lipogenesis

Protein synthesis

Figure 44.4 Role of mitochondria on insulin signaling pathway in insulin‐responding cells, such as liver, muscle, fat, and brain cells. Environmental chemical‐induced mitochondrial damages decreased Akt phosphorylation, leading to failure on insulin responses. Insulin‐ stimulated Akt activation stimulates activities of glucose transporter (Glut), glycogen synthase (GS), sterol response element‐binding protein (SREBP), acyl‐CoA carboxylase (ACC), and mTOR. Insulin also represses activities of lipase, phosphoenolpyruvate carboxykinase (PEPCK), and glucose 6‐phosphatase (G6Pase). Table 44.4 Metabolic disruptors, disrupted metabolisms mitochondrial dysfunction. Chemicals

Obesity

T2DM

Lipid disorders

Mitochondrial toxicity

Bisphenol A

***

***

***

***

DEHP

***

***

***

***

DDT/DDE

***

**

*

***

*

***

PBDE PFOA

**

PFOS TBT

***

***

***

*

***

***

***

***

PAHs PCBs

*

TCDD Atrazine HCB

*

Triflumizole

*

***

***

***

**

***

***

*

**

* ** *

Benzo(a)pyrene Tolylfluanid

** *

Cadmium Arsenic

*** **

**

*

*** *

*

**

***

***

***

***

Adapted from Heindel et al. (2016). Reproduced with permission of Elsevier. The number of asterisk is higher when the strength of evidence is high. BPA, bisphenol A; DDE, dichlorodiphenyldichloroethylene; DDT, dichlorodiphenyltrichloroethane; DEHP, diethylhexyl phthalate; HCB, hexachlorobenzene; PAH, polyaromatic hydrocarbon; PBDE, polybrominated diphenyl ether; PCB, polychlorinated biphenyl; PFOA, perfluorooctanoate; PFOS, perfluoro‐octane yl sulfonic acid; TBT, tributyltin chloride; TCDD, 2,3,7,8‐tetrachlorodibenzo‐p‐dioxin.

701

702

Mitochondrial Dysfunction by Drug and Environmental Toxicants

44.10

Measurement of POPs

44.10.1

Instrumental Analysis for POPs

POPs are quantified by high‐resolution gas chromatography/high‐resolution mass spectrometry (HRGC/ HRMS) method. This conventional analytical method determines the concentrations of individual POP congeners by combining organic solvent extraction of samples and quantification of internal dioxin standards (Bourdon et  al., 2010; Kim et  al., 2010). Toxic effect of POPs is expressed as toxicity equivalence (TEQ) value, which is calculated from the concentration of individual POPs (pg/g lipid) multiplied by their toxic equivalency factor (TEF) values (Van den Berg et al., 2006). The TEF value is a relation of the AhR‐inducing potential of a single compound to that of 2,3,7,8‐TCDD, which has a TEF of 1. The fact that this instrumental analysis requires large amount of serum or plasma samples, organic solvent extraction, lipid normalization, specialized facilities, and expertise as well as its high expense has prevented its application in large‐scale clinical or cohort studies. In addition, various POPs in the serum might not be detectable by the HRGC/HRMS because their concentrations are lower than the detection limit (Rajapakse et al., 2002). However, these non‐detectable POPs may be key contributors to the disease. In addition, the EQ method does not account for the antagonistic activity of POPs. Nevertheless, most epidemiological studies have used data generated by GC/MS for specific POPs of interest, even if they may not necessarily be biologically active. 44.10.2

Cell‐Based Assays for POPs

Many POPs bind to the AhR, leading to transcriptional activation of multiple genes through binding to dioxin‐ responsive element (DRE) of their promoters (Denison and Nagy, 2003). The well‐known chemically activated luciferase gene expression (CALUX) assay is the first cell‐based measurement of AhR ligand mixtures (Schlezinger et  al., 2010; Ziccardi et  al., 2000). The CALUX assay has been used primarily to screen for the presence of POPs rather than to show their possible associations with adverse health effects because it also used the solvent extracted serum (Medehouenou et al., 2010). Later, CALUX‐like methods were adapted to use with unmanipulated neat sera without extraction (Schlezinger et al., 2010). The attraction of this approach lies in its potential to assess the cumulative biological effects of a mixture of extractable AhR agonist and antagonist. Independently, we modified the CALUX assay and established cell‐based AhR ligand activity (CALA) assay. The CALA assay allows us to quantify total AhR‐dependent

Table 44.5 Correlations between phenotype variables and serum AhR ligand activity by CALA assay among subjects who came to Eulji Hospital for health checkup. Phenotype variables

r

P value

Body mass index

0.402