Mitochondrial Dysfunction Caused by Drugs and Environmental Toxicants E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 2498

Veröffentlichungsjahr: 2018

Beschreibung

Developed as a one-stop reference source for drug safety and toxicology professionals, this book explains why mitochondrial failure is a crucial step in drug toxicity and how it can be avoided.

•    Covers both basic science and applied technology / methods
•    Allows readers to understand the basis of mitochondrial function, the preclinical assessments used, and what they reveal about drug effects
•    Contains both in vitro and in vivo methods for analysis, including practical screening approaches for drug discovery and development
•    Adds coverage about mitochondrial toxicity underlying organ injury, clinical reports on drug classes, and discussion of environmental toxicants affecting mitochondria

Leseprobe

Table of Contents

Cover

Volume I

Title Page

List of Contributors

Foreword

Part 1: Basic Concepts

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

1.1 Drug Accumulation

1.2 Small Molecule Delivery to Tissues

1.3 Entry into Cells

1.4 Transport Out of Cells

1.5 Entry into Mitochondria

1.6 Export from Mitochondria

1.7 Concluding Remarks

References

2 The Role of Transporters in Drug Accumulation and Mitochondrial Toxicity

2.1 Introduction to Chapter

2.2 The Solute Carrier (SLC) Superfamily

2.3 Transporters as Determinants of Drug Levels in Tissues and Subcellular Compartments

2.4 Drug Transporters in the Intestine

2.5 Drug Transporters in the Liver

2.6 Drug Transporters in the Kidney

2.7 Mitochondrial Transporters

2.8 Conclusions

References

3 Structure–Activity Modeling of Mitochondrial Dysfunction

3.1 Introduction

3.2 Mitochondrial Toxicity Data Sources

3.3

In Silico

Modeling of Mitochondrial Toxicity

3.4 Mechanistic Chemistry Covered by the Existing Structural Alerts

3.5 Structural Alert Applicability Domains: Physicochemical Properties

3.6 Future Direction: Structure–Activity Studies for Other Mechanisms of Mitochondrial Toxicity

3.7 Concluding Remarks

References

4 Mitochondria‐Targeted Cytochromes P450 Modulate Adverse Drug Metabolism and Xenobiotic‐Induced Toxicity

4.1 Introduction

4.2 Multiplicity of Mitochondrial CYPs

4.3 Targeting and Significance of Multiple Forms of Mitochondrial CYPs

4.4 Variations in Mitochondrial CYPs and Drug Metabolism

4.5 Physiological and Toxicological Significance of Mitochondria‐Targeted CYPs

4.6 Mitochondrial CYPs and Cell Signaling

4.7 Conclusion

Acknowledgment

References

Part 2: Organ Drug Toxicity

5 Mitochondrial Dysfunction in Drug‐Induced Liver Injury

5.1 Introduction

5.2 Structure and Physiological Role of Mitochondria

5.3 Main Consequences of Hepatic Mitochondrial Dysfunction

5.4 Main Hepatotoxic Drugs Inducing Mitochondrial Dysfunction

5.5 Conclusion

References

6 Evaluating Mitotoxicity as Either a Single or Multi‐Mechanistic Insult in the Context of Hepatotoxicity

6.1 Introduction

6.2 Important Considerations When Studying Drug‐Induced Mitochondrial Toxicity in the Liver

6.3 Current and Emerging Model Systems and Testing Strategies to Identify Hepatotoxic Mitotoxicants

6.4 Case Studies

6.5 Concluding Remarks

References

7 Cardiotoxicity of Drugs: Role of Mitochondria

7.1 Introduction

7.2 Cardiotoxic Drugs That Cause Mitochondrial Dysfunction

7.3 Conclusions

References

8 Skeletal Muscle Mitochondrial Toxicity

8.1 Introduction

8.2 Statin Myopathy

8.3 AZT and Mitochondrial Myopathy

8.4 Do Other Nucleoside Analogue Drugs Cause Myopathy?

8.5 Other Drugs Possibly Associated with Myopathy Due to Mitochondrial Toxicity

8.6 Concluding Remarks

References

9 Manifestations of Drug Toxicity on Mitochondria in the Nervous System

9.1 Introduction: Mitochondria in the Nervous System

9.2 Mitochondrial Mechanisms of Peripheral Neuropathy

9.3 Mitochondria and Retinal Drug Toxicity

9.4 Mitochondria and Ototoxicity

9.5 Mitochondrial Mechanisms of Central Nervous System injury

9.6 Conclusion

References

10 Nephrotoxicity: Increasing Evidence for a Key Role of Mitochondrial Injury and Dysfunction and Therapeutic Implications

10.1 Scope of the Problem

10.2 Pecularities of Tubular Cells

10.3 Nephrotoxicity and Mitochondria

10.4 Evidence of Mitochondrial Injury in Nephrotoxicity

10.5 Calcineurin Inhibitor Nephrotoxicity

10.6 HAART and Nephrotoxicity

10.7 Other Nephrotoxic Drugs and Mitochondria

10.8 Therapeutic Implications and Future Lines of Research

Acknowledgments

References

11 Mammalian Sperm Mitochondrial Function as Affected by Environmental Toxicants, Substances of Abuse, and Other Chemical Compounds

11.1 Introduction

11.2 Pesticides, Herbicides, and Other Endocrine‐Disrupting Chemicals (EDCs)

11.3 In Vivo Studies

11.4 In Vitro Studies

11.5 Drugs of Abuse

11.6 Nutritional Elements: Vitamins and Supplements

11.7 Natural Plant Products

11.8 Conclusions and Perspectives

Acknowledgments

References

Part 3: Methods to Detect Mitochondrial Toxicity

12 Biological and Computational Techniques to Identify Mitochondrial Toxicants

12.1 Identifying Mitochondrial Toxicants

12.2 Models to Identify Mitochondrial Toxicants

12.3 Computational Models for the Identification and Development of Mitochondrial Toxicants

12.4 Concluding Remarks

References

13 The Parallel Testing of Isolated Rat Liver and Kidney Mitochondria Reveals a Calcium‐Dependent Sensitivity to Diclofenac and Ibuprofen

13.1 Introduction

13.2 Methods

13.3 Results and Discussion

13.4 Conclusions

Acknowledgments

References

14

In Vitro

Methodologies to Investigate Drug‐Induced Toxicities

14.1 Mitochondria as a Biosensor to Measure Drug‐Induced Toxicities: Is It Relevant?

14.2 Drug‐Induced Cellular Bioenergetic Changes: What Does It Mean and How Can We Measure It?

14.3 Evaluation of Mitochondrial Physiology

14.4 Concluding Remarks

Acknowledgments

References

15 Combined Automated Measurement of Respiratory Chain Complexes and Oxidative Stress: A First Step to an Integrated View of Cell Bioenergetics

15.1 Introduction

15.2 Technology

15.3 Applications of Functional OXPHOS and OS Measurements in Drug Evaluation

15.4 Versatility of the Technology

15.5 Conclusions and Future Perspectives

References

16 Measurement of Mitochondrial Toxicity by Flow Cytometry

16.1 Introduction

16.2 Evaluation of Mitochondrial Function by Flow Cytometry

16.3 Evaluation of Xenobiotics‐Induced Mitochondrial Toxicity by Flow Cytometry

16.4 Benefits and Limitations

16.5 Emerging New Fluorescent Probes and Technologies for Mitochondrial Function Assessment

16.6 Summary

References

17 MitoChip

17.1 Development of Mitochondria‐Specific Gene Expression Array (MitoChip)

17.2 Mouse MitoChip: Assessment of Altered Mitochondrial Function in Mouse Models

17.3 Rat MitoChip: Assessment of Altered Mitochondrial Function in a Rat Model

17.4 Concluding Remarks

17.5 Future Direction

Conflict of Interest Statement

Acknowledgments

References

18 Using 3D Microtissues for Identifying Mitochondrial Liabilities

18.1 Significance of Metabolic Profiling in Drug Development: Current Tools and New Technologies

18.2 Use of 3D Microtissues to Detect Mitochondrial Liabilities

18.3 SRC‐Based Detection of Mitochondrial Liabilities in 3D Human Liver Microtissues

18.4 SRC‐Based Detection of Mitochondrial Liabilities in Human Cardiac Microtissues

18.5 Conclusion

Acknowledgments

References

19 Toward Mitochondrial Medicine

19.1 Introduction

19.2 Allotopic Expression of ATP6

19.3 Xenomitochondrial Mice

19.4 Galactose Treatment

19.5 Rotenone Treatment

19.6 Hepatotoxicity with Mitochondrial Dysfunction

19.7 Hyperactivity of the Mitochondrial Stress Response in Mice

19.8 Summary

References

20 Measurement of Oxygen Metabolism

In Vivo

20.1 Introduction: The Importance of Measuring Mitochondrial Function in Drug Trials

20.2 Methods:

In Vivo

Methods to Measure Drug Effects on Mitochondrial Function in a Clinical Setting

20.3 Measuring Mitochondrial Oxygen Consumption with the Protoporphyrin IX–Triplet State Lifetime Technique

20.4 Features of a Novel COMET Measurement System: The First Bedside Monitor of Cellular Oxygen Metabolism

20.5 Clinical Trial: Effect of Simvastatin on Mitochondrial Function

In Vivo

in Healthy Volunteers

References

21 Detection of Mitochondrial Toxicity Using Zebrafish

21.1 Introduction

21.2 Genetics and Manipulation of Zebrafish for Toxicological Studies

21.3 Zebrafish Physiology

21.4 Mitochondrial Biology and Methods

21.5 Conclusions and Future Directions

Acknowledgments

References

22 MiRNA as Biomarkers of Mitochondrial Toxicity

22.1 Introduction

22.2 MicroRNAs: General

22.3 Properties of miRNA: Useful Biomarkers

22.4 Mitochondria and miRNAs

22.5 miRNA Transport in the Mitochondria

22.6 miRNA Secretion

22.7 miRNAs Associated with Mitochondrial Function

22.8 Mitochondrially Rich Tissues and Tissue‐Specific miRNAs

22.9 Work to Date Using MiRNA as Biomarkers of Mitochondrial Toxicity

22.10 Future Work Needed

22.11 Conclusions

References

23 Biomarkers of Mitochondrial Injury After Acetaminophen Overdose

23.1 Introduction

23.2 Acetaminophen Overdose as a Model for Biomarker Discovery

23.3 Acetaminophen Overdose: Mechanisms of Toxicity in Mice and Man

23.4 Biomarkers of Mitochondrial Injury

23.5 Conclusions

References

24 Acylcarnitines as Translational Biomarkers of Mitochondrial Dysfunction

24.1 Introduction

24.2 Acylcarnitine Analysis

24.3 Acylcarnitines in

In Vitro

and

In Vivo

Hepatotoxicity Studies

24.4 Acylcarnitines and Hepatotoxicants

24.5 Acylcarnitines in Cardiac Toxicity

24.6 Clinical Hepatotoxicity

24.7 Conclusions

References

25 Mitochondrial DNA as a Potential Translational Biomarker of Mitochondrial Dysfunction in Drug‐Induced Toxicity Studies

25.1 Introduction

25.2 The Mitochondrial Genome

25.3 Is Mitochondrial DNA a Useful Biomarker of Mitochondrial Dysfunction

25.4 Methodological Issues for Measuring Mitochondrial DNA Content

25.5 Acquired Mitochondrial DNA Changes in Human Diseases

25.6 Conclusions and Future Directions

Acknowledgments

References

26 Predicting Off‐Target Effects of Therapeutic Antiviral Ribonucleosides

26.1 Introduction

26.2 Therapeutic Ribonucleoside Inhibitors Target RNA Virus Infections

26.3 Nucleoside Reverse Transcriptase Inhibitors (NRTIs) Mediate Mitochondrial Toxicity

26.4 Mitochondrial Dysfunction Is an Unintended Consequence of Clinical Drug Candidates

26.5 Mitochondrial Transcription as an “Off‐Target” of Antiviral Ribonucleosides

26.6 Evaluation of Substrate Utilization by POLRMT

In Vitro

26.7 Direct Evaluation of Mitochondrial RNA Transcripts in Cells

26.8 Inhibition of Mitochondrial Function

26.9 Conclusions

References

27 Imaging of Mitochondrial Toxicity in the Kidney

27.1 Mitochondria in the Kidney

27.2 Drug Toxicity in the Kidney

27.3 Fluorescence Microscopy

27.4 Assessment of Mitochondrial Function with Fluorescence Microscopy

27.5

Ex Vivo

Imaging of Mitochondria in the Kidney

27.6 Intravital Imaging of Mitochondria in the Kidney

27.7 Recent Technical Developments in Intravital Kidney Imaging

27.8 Conclusion

Acknowledgments

Disclosures

Conflicts of Interest

References

28 Imaging Mitochondrial Membrane Potential and Inner Membrane Permeability

28.1 Introduction

28.2 Isolated Mitochondria

28.3 Imaging of Membrane Potentials in Single Intact Cells

28.4 Mitochondrial Permeability Transition

28.5 Conclusion

Acknowledgments

References

29 Quantifying Skeletal Muscle Mitochondrial Function In Vivo by

31

P Magnetic Resonance Spectroscopy

29.1 MRS Methods in Skeletal Muscle

29.2 The Metabolic and Physiological Background toP MRS Studies of Muscle

29.3 Physiological Principles in the Quantitative Analysis of DynamicP MRS Data

29.4 Approaches to Measuring Mitochondrial Function

In Vivo

29.5 Some Practical and Experimental Considerations in P MRS Studies of Muscle

29.6 P MRS Studies in Resting Muscle

29.7 P MRS Magnetization Transfer Methods

29.8 Muscle Exercise Responses Studied by P MRS

29.9 Mitochondrial Function Studied by P MRS in Recovery from Exercise

29.10 Validating MRS‐Based Measures of Mitochondrial Function

29.11 Conclusions and Summary

Acknowledgments

References

Volume II

Title Page

List of Contributors

Foreword

Part 4: Reports from the Clinic

30 Statin and Fibrate‐Induced Dichotomy of Mitochondrial Function

30.1 Introduction

30.2 Statins

30.3 Effect of Statin Treatment on Endogenous CoQ

10

Status

30.4 Effect of Statin Treatment on Cerebral CoQ

10

Status

30.5 Effect of Statin Treatment on Oxidative Phosphorylation

30.6 Fibrates

30.7 The Effect of Fibrate Treatment on Mitochondrial Respiratory Chain Function

30.8 Fibrates in the Treatment of Oxidative Phosphorylation Defects

30.9 Conclusion

References

31 Friend or Foe

31.1 Beneficial Effects of ROS and Mitotoxin Exposure

31.2 Window of Opportunity for ROS and Mitotoxins: Low Concentration and Short Time

31.3 Endurance Exercise, a Greatly Beneficial, Transient ROS‐Generating Activity, Causes Translocation of p53 to Mitochondria

31.4 Mild Exposure to Mitochondrial Toxins

In Vitro

Recapitulates a Beneficial Endpoint of Endurance Exercise (Translocation of p53 to Mitochondria)

31.5 Progeroid mtDNA Mutator Mouse: A Test Ground for the Similarity between the Effects of Mitotoxin Exposure and Exercise

31.6 Mutational Analysis Hints Existence of the “Good” and the “Bad” mtDNA and Evokes Alternative Hypotheses

31.7

Ab Absurdo

: Lack of Exercise May Result in Increased Damage

31.8 Conclusions, Disclaimers, and Perspectives

Acknowledgments

References

32 Involvement of Mitochondrial Dysfunction on the Toxic Effects Caused by Drugs of Abuse and Addiction

32.1 Introduction

32.2 The Tricarboxylic Acid Cycle as a Target Pathway

32.3 Effects on the Mitochondrial Electron Transport Chain

32.4 Drugs of Abuse Might Target Mitochondrial Biogenesis

32.5 Mitochondrial Quality Control and Drugs of Abuse

32.6 Mitochondrial Fusion/Fission Equilibrium Is Affected by Drugs of Abuse

32.7 Mitochondrial Distribution under the Influence of Drugs of Abuse

32.8 Concluding Remarks

References

33 Drug‐Induced Mitochondrial Toxicity during Pregnancy

33.1 Mitochondria in Human Fertility

33.2 Mitochondrial Toxicity in Human Pregnancy

33.3 Therapeutic Approach of Drug‐Induced Mitochondriopathies

33.4 Conclusions

Funding

References

34 Mitochondrial Toxicity in Children and Adolescents Exposed toAntiretroviral Therapy

34.1 Introduction

34.2 Mitochondrial Toxicity in Children and Adolescents Infected with HIV

34.3 Mitochondrial Toxicity in HIV‐Uninfected Infants That Were Perinatally Exposed to Antiretrovirals

References

35 Drug‐Induced Mitochondrial Cardiomyopathy and Cardiovascular Risks in Children

35.1 Introduction

35.2 HIV Therapy

35.3 Cancer Therapy

35.4 Conclusion

Funding

References

36 Role of Mitochondrial Dysfunction in Linezolid‐Induced Lactic Acidosis

36.1 Mechanisms Responsible for Lactic Acidosis in Critically Ill Subjects

36.2 Mechanisms Responsible for Tissue Hypoxia in Critically Ill Subjects

36.3 Relationship between Lactic Acidosis and Oxygen‐Derived Variables

36.4 Incidence and Risk Factors of Linezolid‐Induced Lactic Acidosis

36.5 Relationship between Linezolid‐Induced Lactic Acidosis and Oxygen‐Derived Variables

36.6 Mitochondrial Ribosomes and Translation

36.7 How Linezolid Exerts its Therapeutic—and Toxic—effects

36.8 Mitochondrial DNA Polymorphisms and Susceptibility to Linezolid

36.9 Mitochondrial Toxicity of Linezolid

36.10 Conclusion

References

37 Metformin and Lactic Acidosis

37.1 Introduction

37.2 Metformin‐Induced Lactic Acidosis

37.3 Further Complications of the Debate

37.4 In Clinical Practice

References

38 Lessons Learned from a Phase I Clinical Trial of Mitochondrial Complex I Inhibition

References

39 Pharmacological Activation of Mitochondrial Biogenesis for the Treatment of Various Pathologies

39.1 Introduction

39.2 Regulation of MB

39.3 Mitochondrial Dysfunction in Disease

39.4 Acute Diseases

39.5 Chronic Diseases

39.6 Pharmacological Activation of MB

39.7 Kinase Modulators

39.8 G Protein‐Coupled Receptor Modulators

39.9 Cyclic Nucleotide Modulators

39.10 Transcription Factor Modulators

39.11 Sirtuins

39.12 Conclusions

References

40 Mitochondrial Toxicity Induced by Chemotherapeutic Drugs

40.1 Introduction

40.2 Mitochondria and Cancer Chemotherapy

40.3 Conventional Chemotherapeutic Agents and Mitochondria

40.4 Mitoprotectants as Adjuvants in Chemotherapy

40.5 Conclusion

Acknowledgments

References

Part 5: Environmental Toxicants and Mitochondria

41 The Mitochondrial Exposome

41.1 Introduction

41.2 Environmental Pollutants and Mitochondrial Toxicity

41.3 Bioaccumulation of Environmental Pollutants

41.4 Mitochondria High‐Resolution Metabolomics

41.5 Case Study: Profiling the Human Mitochondrial Exposome

41.6 Conclusions

Acknowledgments

References

42 Central Mitochondrial Signaling Mechanisms in Response to Environmental Agents

42.1 Introduction

42.2 High‐Resolution Metabolomics

42.3 High‐Resolution Metabolomics of Liver Mitochondria

42.4 Integration of Mitochondrial Redox Proteomics and Metabolomics: RMWAS

42.5 Integration of HRM with Transcriptomics: TMWAS

42.6 Three‐Way Integration of Redox Proteomics, Metabolomics, and Transcriptomics to Create RMT Association Study for Mitochondrial Signaling in Manganese (Mn) Toxicity

42.7 Integrated Omics Applications in Mitochondrial Metabolic Disorder: Fatty Liver, Diabetes, Obesity, and Neurodegenerative Diseases

42.8 Summary and Perspective

Acknowledgments

References

43 Detection of Mitochondrial Toxicity of Environmental Pollutants Using

Caenorhabditis elegans

43.1 What We Know about Pollutant Influences on Mitochondria

43.2 Advantages of the

Caenorhabditis elegans

Model

43.3 Limitations of

C. elegans

for Studying Mitochondrial Toxicity

43.4 Methods for Assessing Mitochondrial Toxicity in

C. Elegans

43.5 Environmental Mitotoxicants and

C. Elegans

: Unique Discoveries and Emerging Roles

References

44 Persistent Organic Pollutants, Mitochondrial Dysfunction, and Metabolic Syndrome

44.1 Introduction

44.2 Health Hazard of Environmental Chemicals: A Short History

44.3 Low‐Level Exposure to Multiple Chemicals

44.4 POPs and Obesity Paradox

44.5 Body Burden of Chemicals

44.6 Diabetes Mellitus, Insulin Resistance, and Metabolic Syndrome

44.7 Association of POPs with Diabetes and Metabolic Syndrome

44.8 Toxic and Biological Effects of Some POPs via AhR

44.9 Insulin Resistance and Mitochondrial Dysfunction

44.10 Measurement of POPs

44.11 Summary

References

45 Cigarette Smoke and Mitochondrial Damage

45.1 Introduction

45.2 Cigarette Smoke Components and Mitochondrial Toxicity

45.3 Health Problems Caused by Cigarette Smoking

45.4 Cigarette Smoke and Mitochondrial Damage in Different Disease

45.5 Summary

References

Index

End User License Agreement

List of Tables

Chapter 01

Table 1.1 Drugs that bind to serum albumin.

Table 1.2 Drugs that bind to alpha‐1 glycoprotein.

Table 1.3 Transporters of mitochondrial toxic drugs.

Chapter 02

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

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

Chapter 03

Table 3.1 Published structural alerts for mitochondrial toxicity.

Chapter 04

Table 4.1 Altered substrate metabolism by mitochondria‐targeted CYPs.

Chapter 05

Table 5.1 Mechanisms of mitochondrial dysfunction induced by different hepatotoxic drugs.

Chapter 06

Table 6.1 A summary of the development of preclinical testing strategies to identify compounds with mitochondrial liabilities and to predict compounds capable of inducing DILI.

Chapter 07

Table 7.1 Putative mechanism of mitochondrial toxicity.

Chapter 10

Table 10.1 HAART drugs and nephrotoxicity.

Chapter 11

Table 11.1 Effects of different types of compounds on the mitochondrial function of mammalian sperm.

Chapter 15

Table 15.1 Advantages and key benefits of functional metabolism evaluation.

Table 15.2 Rotenone effect on either OXPHOS or OS pathways.

Table 15.3 Versatility of functional metabolism evaluation.

Chapter 16

Table 16.1 Fluorescent probes for detecting mitochondrial membrane potential (MMP) change or mitochondrial reactive oxygen species (ROS) production by flow cytometry.

Chapter 17

Table 17.1 Genes significantly altered by flutamide in the liver of male

Sod2

+/−

mice.

Table 17.2 Genes altered by cisplatin alone or in presence of testosterone in kidney of female KAP2‐PPARα transgenic mice.

Table 17.3 Doxorubicin effect on selected gene ontology terms.

Chapter 18

Table 18.1 Assessment of mitochondrial liabilities with 13 reference drugs comparing the effect on cellular viability (IC

50

ATP (μM)) and spare respiratory capacity (IC

50

SRC (μM)).

Chapter 22

Table 22.1 miRNA databases.

Table 22.2 Mitochondria‐associated miRNAs in cells/tissues.

Table 22.3 List of miRNAs associated with mitochondrial functions.

Table 22.4 Tissue‐specific (enriched) miRNAs.

Chapter 24

Table 24.1 MS methods for measuring acylcarnitines in biological samples.

Chapter 25

Table 25.1 Key differences between the human mitochondrial and nuclear genomes.

Chapter 28

Table 28.1 Isolation of rat liver mitochondria (Schneider 1948; Lemasters and Hackenbrock 1980).

Chapter 33

Table 33.1 The Food and Drug Administration (FDA) (USA) and Therapeutic Goods Administration (TGA) (AU) classification for mitochondrial toxic drugs potentially used during pregnancy depending on their association to birth defects.

Chapter 35

Table 35.1 Nucleoside reverse transcriptase inhibitor toxicities in HIV‐infected patients and their relation to mitochondrial pathways.

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.

Table 35.3 Different types of anthracycline cardiotoxicity.

Table 35.4 Risk factors for anthracycline‐induced cardiotoxicity.

Chapter 36

Table 36.1 Cases of linezolid‐induced lactic acidosis in adults, retrieved in PubMed in September 2016.

Chapter 38

Table 38.1 Number and severity of adverse events.

Table 38.2 Pharmacokinetic (PK) parameters for R118.

Chapter 39

Table 39.1 Partial list of diseases characterized by mitochondrial dysfunction and evidence of MB as therapeutic interventions for each.

Table 39.2 A selective list of pharmacological inducers of mitochondrial biogenesis.

Chapter 41

Table 41.1 Thirty‐eight compounds selected for confirmation analysis and further mechanistic studies, grouped based on oxygen consumption rate following IC

50

exposure.

Table 41.2 Environmental chemicals detected in mitochondria isolated from mouse liver.

Table 41.3 Adrenal tissues available for mitochondrial isolation.

Table 41.4 Matches to environmental chemicals detected in mitochondria isolated from human adrenal tissue.

Chapter 43

Table 43.1 Some important mechanisms of mitochondrial toxicity and representative environmental pollutants.

Table 43.2 Cellular and tissue‐specific exposure route differences in physiological systems targeted by environmental mitotoxicants in mammals and

Caenorhabditis elegans

.

Table 43.3 Methods to detect mitochondrial toxicity in

C. elegans

.

Chapter 44

Table 44.1 The nature of common EDCs or POPs and their known health hazards.

Table 44.2 ATP III criteria for diagnosing the metabolic syndrome.

Table 44.3 Environmental chemicals associated with T2DM and obesity.

Table 44.4 Metabolic disruptors, disrupted metabolisms mitochondrial dysfunction.

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.

Chapter 45

Table 45.1 Effect of cigarette smoke on cardiovascular disease.

List of Illustrations

Chapter 01

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.

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.

Chapter 02

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.

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.

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).

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).

Chapter 03

Figure 3.1 Schematic of how a chemical capable of facile reduction can act as an alternate electron acceptor leading to disruption of the electron transport chain.

Figure 3.2 Reduction of 2‐nitroaniline leading to the production of the alternate electron acceptor 1,2‐phenylenediamine.

Figure 3.3 Schematic showing the ability of weak acids to transport protons across the inner mitochondrial membrane (IMM) from the intermembrane space (IMS) to the mitochondrial matrix (MM).

Figure 3.4 Resonance stabilized weak acid behavior for chemicals containing a thiazolidinedione structural alert.

Chapter 04

Figure 4.1 Schematic representation of bimodal targeting of CYPs. A: SRP‐dependent microsomal translocation of CYPs. B: Mitochondrial translocation after N‐terminal truncation (e.g., CYP1A1, CYP1B1). C: Mitochondrial translocation after PKA/PKC phosphorylation and activation of chimeric signals.

Figure 4.2 Specific targeting signal for mitochondrial import of CYPs and GSTA4‐4. (a) CYP signals. (b) GST signal.

Chapter 05

Figure 5.1 Consequences of severe inhibition of mitochondrial fatty acid oxidation and respiratory chain. A severe inhibition of mitochondrial fatty acid oxidation (mtFAO) can induce different deleterious effects for the hepatocytes. (i) Accumulation of free fatty acids and triglycerides, thus explaining the occurrence of steatosis. Free fatty acids are also metabolized into acylcarnitine derivatives and dicarboxylic acids, which can be detected in plasma and urine. Free fatty acids and dicarboxylic acids can be toxic for mitochondria, thus reinforcing mitochondrial dysfunction. (ii) Reduction of ATP synthesis, which can induce energy shortage and hepatic cytolysis. (iii) Decreased ketogenesis with lower generation of ketone bodies (mainly acetoacetate and β‐hydroxybutyrate). (iv) Inhibition of gluconeogenesis with decreased hepatic glucose production. Low plasma levels of ketone bodies and glucose can be responsible for a profound energy deficiency in extrahepatic tissues. A severe impairment of the mitochondrial respiratory chain (MRC) activity can also have different harmful consequences: (i) reduction of ATP synthesis, thus inducing energy shortage and hepatic cytolysis; (ii) a secondary inhibition of the tricarboxylic acid cycle (TCA), thus leading to an accumulation of lactate and subsequent lactic acidosis; (iii) a secondary inhibition of mtFAO with the previously mentioned consequences; and (iv) increased generation of mitochondrial ROS, which could favor the progression of steatosis to steatohepatitis.

Figure 5.2 Mechanisms of amiodarone‐induced impairment of oxidative phosphorylation and mitochondrial fatty acid oxidation. Amiodarone (Am) is an amphiphilic compound that harbors a protonable nitrogen within its diethyl‐aminoethoxy moiety. In the intermembrane space of mitochondria, which is an acidic milieu, Am undergoes a protonation to generate Am

+

. This cationic derivative thus freely enters the mitochondrion thanks to the mitochondrial transmembrane potential Δ

ψ

. The entry of the protonated molecule Am

+

has two major consequences regarding oxidative phosphorylation (OXPHOS), mitochondrial fatty acid oxidation (mtFAO), and the mitochondrial respiratory chain (MRC): (i) a transient uncoupling of OXPHOS since protons are not entering the matrix by the use of the ATP synthase and (ii) a progressive accumulation of Am

+

in the mitochondrial matrix, which induces the subsequent inhibition of different enzymes involved in MRC and mtFAO. Hence, amiodarone‐induced inhibition of mtFAO could be due to direct impairment of FAO enzymes (e.g., CPT1 and LCAD) and to MRC inhibition, in particular at the level of complexes I and II.

Figure 5.3 Mechanisms of inhibition of mitochondrial DNA replication by the thymidine analogues stavudine and fialuridine. The antiviral stavudine (d4T) and fialuridine (FIAU) are able to impair mitochondrial DNA (mtDNA) replication by two different mechanisms. The antiretroviral nucleoside reverse transcriptase inhibitor (NRTI) d4T is a thymidine analogue in which the hydroxyl group (OH) in the 3′ position on the sugar ring is replaced by a hydrogen atom. D4T (S) can be incorporated into the growing chain of mtDNA by the DNA polymerase γ (Polγ). However, if d4T is not removed by the proofreading activity of this DNA polymerase, mtDNA replication is blocked. Indeed, no other nucleotides can be incorporated after d4T because the DNA chain now lacks a 3′OH end. Note that other NRTIs such as zidovudine (AZT) and didanosine (ddI) are also able to inhibit mtDNA replication via a similar mechanism. The anti‐HBV FIAU is also a thymidine analogue, but it was never marketed because of severe hepatotoxicity. Unlike d4T, FIAU (F) can be incorporated into mtDNA without immediately stopping mtDNA replication since this drug carries a 3′OH group on the sugar moiety. However, when several adjacent molecules of FIAU are successively incorporated into a growing chain of mtDNA, DNA Polγ is strongly inhibited. D4T‐ and FIAU‐induced blockage of mtDNA replication can lead to severe mtDNA depletion and impairment of mitochondrial respiratory chain (MRC) activity, which subsequently inhibits mitochondrial fatty acid oxidation (mtFAO) and tricarboxylic acid (TCA) cycle. Impairment of mtFAO and TCA cycle can secondarily induce severe hepatic steatosis and lactic acidosis, respectively.

Figure 5.4 Mechanisms of valproic acid (VPA)‐induced inhibition of mitochondrial fatty acid β‐oxidation. VPA is an analogue of medium‐chain fatty acid that freely enters the mitochondrion and generates a coenzyme A ester (VPA‐CoA) within the mitochondrial matrix. VPA is also metabolized by cytochromes P450 (CYPs) into ∆

4

‐VPA, a VPA metabolite that presents a double bond between carbons 4 and 5. Like VPA, ∆

4

‐VPA is able to freely enter the mitochondrion and to generate a coenzyme A ester (∆

4

‐VPA‐CoA) and other metabolites. Both VPA‐CoA and ∆

4

‐VPA‐CoA can inhibit the mitochondrial fatty acid oxidation (mtFAO) by two different mechanisms: (i) a sequestration of CoA, which is a cofactor mandatory for fatty acid activation and subsequent mtFAO, and (ii) a direct inhibition of different mtFAO enzymes such as SCAD, MCAD, and CPT1. Note that ∆

4

‐VPA‐CoA and other CYP‐generated VPA metabolites (e.g., ∆

2,4

‐VPA‐CoA) could be particularly deleterious for the mtFAO pathway. This may explain why CYP inducers such as phenobarbital and phenytoin significantly increase the risk of VPA‐induced severe hepatotoxicity.

Chapter 06

Figure 6.1 Graphical representation of the important mechanisms to consider when assessing the importance of mitochondrial dysfunction in the onset of DILI. Representative drugs associated with each mechanism, discussed in the detailed case studies, are included in brackets.

Figure 6.2 Comparison of

in vitro

models for the investigation of mitotoxicity in DILI. (a) Comparison of multiple cell models from which mitotoxicity can be assessed: from isolated mitochondria to 3D cell models such as spheroids. (b) Comparison of three commonly used liver cell types for mitotoxicity‐DILI investigation: HepG2 and HepaRG cell lines as well as fresh human hepatocytes (FHH).

Figure 6.3 The multiple mechanisms involved in APAP mitochondrial and subsequent hepatocyte toxicity. Formation of protein adducts within mitochondria and initial oxidative stress (1), which results in lysosomal free iron–mitochondria interplay (2) and activation of JNK pathway (3). The excessive ROS formation due to mechanisms 2 and 3 will initiate onset of MPT and cell necrosis. The initial ROS formation within the mitochondria also triggers the formation of reactive nitrogen species, mainly nitrotyrosine (4), resulting in mitochondrial DNA damage and accumulation of Ca

2+

within the cell (5), both of which contribute to further oxidative stress, nuclear DNA damage, and cell necrosis.

Chapter 08

Figure 8.1 Proposed mechanisms of myopathy by statins. Statins inhibit HMG‐CoA reductase and therefore the biosynthesis of cholesterol and other important biomolecules from acetyl‐CoA. The sterol pathway is absent in

C

.

elegans

. In addition to cholesterol, statins inhibit the synthesis of other important molecules such as CoQ10, dolichol, and farnesyl pyrophosphate (farnesyl‐PP). The latter along with geranylgeranyl pyrophosphate mediates protein prenylation, which is important in the membrane association of some key biochemical signaling molecules, such as small GTPases. Statins are also reported to inhibit the mitochondrial electron transport chain, promote mitochondrial oxidant formation, and stimulate mitochondrial pore transition (MPT) pore opening, leading to apoptosis. Furthermore, inhibition of lactate efflux from cells by statins may occur at the level of MCT4 inhibition and lead to apoptosis via a rise in intracellular pH.

Chapter 10

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.

Figure 10.2 Anti‐calcineurin nephrotoxicity: the example of cyclosporine A (CsA).

Figure 10.3 Intracellular pathways for CsA‐induced renal tubular cell apoptosis.

Chapter 11

Figure 11.1 Structure of the human spermatozoon. The human sperm cell is composed of a sperm head, mostly occupied by the haploid condensed nucleus, which is partially overlaid by a secretory vesicle (the acrosome) in the anterior portion. The full length of the tail includes the midpiece, where mitochondria are clustered.

Chapter 12

Figure 12.1 Probing mitochondria with small molecules. (a) A representative oxygen consumption rate (OCR) following the addition of the ATP synthase inhibitor oligomycin, the uncoupler FCCP, and the electron transport chain inhibitors rotenone and antimycin A. Using these compounds allows for the identification of oxygen consumption required for ATP production (1), maximal oxygen consumption and electron transport chain activity (2), proton leak (3), and non‐mitochondrial oxygen consumption (4). (b) Inhibitors (rotenone, antimycin A, and oligomycin) and activators (succinate, ascorbate) of electron transport chain complexes and uncouplers of the mitochondrial proton gradient (FCCP) can be used to selectively monitor electron flow. These compounds can be used to determine the mechanism of mitochondrial toxicants.

Figure 12.2 Developing toxicophore models from known toxicants. (a) Highly similar compounds with a shared chemical scaffold (i) are rigidly aligned (ii) to develop a toxicophore model (iii). This strategy is particularly useful for identifying functional groups to exclude from consideration during the optimization of lead compounds. (b) Compounds with moderate structural similarity but a dissimilar chemical scaffold (iv) are flexibly aligned (v) to generate a toxicophore model (vi). This strategy is particularly useful for the identification of potential toxicants during initial screening of large chemical libraries.

Chapter 13

Figure 13.1 Flow chart for the simultaneous isolation of mitochondria from rat liver and kidney for further structural and functional analysis.

Figure 13.2 Isolated mitochondria from rat liver and kidney respond differently to calcium challenge. (a) Electron micrographs of mitochondria isolated in parallel from rat liver and kidney tissues show comparable high purities and intact inner and outer membranes. A 100 μM Ca

2+

challenge results in mitoplast formation in mitochondria isolated from both tissues, that is, enlarged inner membrane vesicles with highly electron‐transmissive matrices and disrupted or depleted outer membranes. Scale bars equal 1 µm. (b, c) In rat liver and kidney mitochondria, the presence of 20 μM Ca

2+

leads to a late loss of OD

540 nm

, whereas 100 μM Ca

2+

rapidly induce mitochondrial permeability transition (MPT) as assessed by a massive OD

540 nm

decrease in comparison with control conditions. The preincubation of rat liver mitochondria with 5 μM cyclosporine A (CysA) completely prevents Ca

2+

‐induced MPT. In contrast, CysA only slows down Ca

2+

‐induced MPT in kidney mitochondria. (d, e) In liver and kidney mitochondria, 100 μM Ca

2+

results in an immediate mitochondrial membrane potential (MMP) depletion, which can be fully prevented by 5 μM CysA in liver, but only delayed in kidney mitochondria. White arrows indicate the Ca

2+

addition, and black arrows indicate the addition of the protonophore FCCP as internal positive control. Shown are exemplary curves (

N

 = 3).

Figure 13.3 Ibuprofen and diclofenac do not induce the mitochondrial permeability transition, but high concentrations may impair the mitochondrial membrane potential. (a, b) Ibuprofen does not induce MPT in liver and kidney mitochondria. (c, d) In contrast to liver mitochondria, kidney mitochondria reveal a higher sensitivity to ibuprofen as shown by partial MMP losses. (e, f) MPT is not induced in rat liver mitochondria by diclofenac. However, a slight loss of OD

540 nm

is detectable in kidney mitochondria, indicating a higher susceptibility compared with liver mitochondria. (g, h) Diclofenac impairs the mitochondrial membrane potential in liver and especially in kidney mitochondria in a dose‐dependent manner. White arrows indicate the NSAID addition, and black arrows indicate the addition of the protonophore FCCP as internal positive control. Shown are exemplary curves (

N

 = 3).

Figure 13.4 Ibuprofen and diclofenac cause the induction of the MPT and the loss of MMP in calcium‐pretreated liver and kidney mitochondria. (a–d) In the presence of 20 μM Ca

2+

, ibuprofen causes an immediate dose‐dependent MPT induction and MMP loss in rat liver and kidney mitochondria. (e–h) In the presence of 20 μM Ca

2+

, diclofenac immediately induces MPT and MMP loss in liver and kidney mitochondria, whereas kidney mitochondria are slightly less sensitive. White arrows indicate the NSAID/Ca

2+

addition, and black arrows indicate the addition of the protonophore FCCP as internal positive control. Shown are exemplary curves (

N

 = 3).

Figure 13.5 Cyclosporine A can protect against the calcium‐dependent toxicity of ibuprofen in rat liver mitochondria. (a–d) CysA is protective against ibuprofen/Ca

2+

MPT induction and MMP loss in rat liver mitochondria but to a markedly lesser extent in kidney mitochondria. (e–h) The diclofenac/Ca

2+

induced MPT and MMP loss is largely prevented by CysA in liver but not in kidney mitochondria. CysA was present at the beginning of the measurement. White arrows indicate the NSAID/Ca

2+

addition, and black arrows indicate the addition of the protonophore FCCP as internal positive control. Shown are exemplary curves (

N

 = 3).

Chapter 14

Figure 14.1 Mitochondria as bio‐sensors for drug‐induced toxicity. The different approaches described in this chapter that can measure mitochondrial alterations involving reactive oxygen species, mitochondrial membrane potential, calcium flux, adenine nucleotide concentrations and opening of the mitochondrial permeability transition pore. ADP, adenosine diphosphate; AMP, adenosine monophosphate; ATP, adenosine triphosphate; Ca

2+

, calcium; CAT1H, 1‐hydroxy‐2,2,6,6‐tetramethylpiperidin‐4‐yl‐trimethylammonium; CMH, 1‐hydroxy‐3‐methoxycarbonyl‐2,2,5,5‐tetramethylpyrrolidine; Co

2+

, cobalt; DCFH

2

, 2′,7′‐dichlorodihydrofluorescein; DCPIP, 2,6‐dichlorophenolindophenol; DHE, dihydroethidium; DHR, dihydrorhodamine; DiOC

6

, 3,3′‐dihexyloxacarbocyanine iodide; GEGI, genetically encoded calcium indicators; GFP, green fluorescent protein; HPLC, high‐performance liquid chromatography; JC‐1, 5,5′,6,6′‐tetrachloro‐1,1′,3,3′‐tetraethylbenzimidazolylcarbocyanine iodide; MPTP, mitochondrial permeability transition pore; PPH, 1‐hydroxy‐4‐phosphono‐oxy‐2,2,6,6‐tetramethylpiperidine; Rhod123, rhodamine 123; Rhod‐2 AM, rhodamine 2 acetoxymethyl; TMRE, tetramethylrhodamine ethyl ester; TMRM, tetramethylrhodamine methyl ester; YFP, yellow fluorescent protein.

Chapter 15

Figure 15.1 Low CVs’ importance to detect tiny metabolic variations. Low CVs, as compared with high ones, allow detecting significant small variations. The figure here summarized the increase along the time of, for example, two enzymatic activities. With a low CV technique, we have to wait only for the second observation time T2 to consider without any doubt that the two observed enzymatic activities are significantly different (the two box plots do not show any overlap). In the case of the high CV technique, at T2, the important overlap between the observed results impairs any conclusion regarding the two results. They still must be considered as identical. It holds the same at T3 and even at T4 as there are still overlapping values between the two series.

Figure 15.2 Spider representation of LNCaP versus PNT2 OXPHOS and OS metabolism (culture of both cells at glucose 1 g/L; PNT2 cells metabolism is used as reference and represents 100%).

Figure 15.3 OXPHOS complex results in PNT2 and LNCAP cells. (a) OXPHOS complexes and CS results for both cells under normal conditions (glucose 1 g/L). (b) OXPHOS complex results after normalization with CS value. (c) Spider representation of OXPHOS/CS values for PNT2 and LNCaP cells cultured at 1 g/L. PNT2 values are given as reference (100%) and LNCaP values in % are calculated from the reference. (d) Spider representation of OXPHOS/CS values for PNT2 and LNCaP cells cultured at 5 g/L. PNT2 values are given as reference (100%) and LNCaP values in % are calculated from the reference.

For Figure 15.3a and b, results values are given as mean ± SD of five different culture flasks for each cell line.

Figure 15.4 OXPHOS and OS metabolisms of PNT2 cells cultured at 1 and 5 g/L glucose. (a) OXPHOS metabolism. (a) OS metabolism.

For Figure 15.4a and b, results values are given as mean ± SD of five different culture flasks for PNT2 cell line.

Figure 15.5 OXPHOS and OS metabolisms of LNCaP cells cultured at 1 and 5 g/L glucose. (a) OXPHOS metabolism. (a) OS metabolism.

For Figure 15.5a and b, results values are given as mean ± SD of five different culture flasks for LNCaP cell line.

Figure 15.6 Spider representation of compared OXPHOS and OS metabolisms at 1 and 5 g/L glucose in culture. (a) PNT2 cells. (b) LNCaP cells. For both cell lines, 1 g/L glucose results are given as reference (100%) and 5 g/L values are calculated from the reference.

Figure 15.7 Automated functional metabolic measurement can be performed with the same accuracy from early drug discovery experiments to late phase clinical studies.

Chapter 16

Figure 16.1 (a) Kinetics of JC‐1 loading in HL‐60 cells. Cells were pelleted by centrifugation at 250 × 

g

for 2 min. Cells were then resuspended in 100 μL PBS containing 5 μM JC‐1. Cells were incubated with JC‐1 for 3, 5, 10, 15, and 20 min at 37°C. After incubation, cells were pelleted at 300 × 

g

, supernatant removed and resuspended in 100 μL PBS. (b) In a separate experiment, sample data of MMP completely depleted by treating HL‐60 cells with 300 μM antimycin for 6 h is shown. JC‐1 fluorescence was measured on a BD‐LSR™ flow cytometer.

Chapter 17

Figure 17.1 Representation of cisplatin effect on transcript levels of mitochondria‐related genes in kidney of female KAP2‐PPARα transgenic mice and attenuation by pretreatment of mice with testosterone. Volcano plot presented as relative fold changes in the transcript level of 542 mitochondria‐related genes against a false discovery rate for each gene influenced by cisplatin in the absence or presence of testosterone treatments. Pretreatment with testosterone modulated the expression level of mitochondria‐related genes that were downregulated by cisplatin in kidneys of female KAP2‐PPARα transgenic mice. Black solid circles indicate effect of cisplatin in absence of testosterone in KAP2‐PPARα transgenic mice and gray solid circles indicate effect of cisplatin in presence of testosterone in KAP2‐PPARα transgenic mice.

Figure 17.2 Illustration of role of mitochondria in various cardiac events leading to doxorubicin‐induced cardiotoxicity in B6C3F

1

mice. Downregulation of cardiac genes associated with oxidative phosphorylation, fatty acid metabolism, and the Krebs cycle during early stages of doxorubicin treatment can impair cardiac energy metabolism. This can induce expression of apoptotic genes that may promote cardiomyocyte loss, leading to early hypertrophy‐related changes in the heart. These doxorubicin‐mediated early transcriptional changes together can alter cardiac function. Persistent doxorubicin treatment can severely alter transcript levels that ultimately can manifest into myocardial injury, resulting in elevated cardiac troponin T levels in plasma followed by overt cardiac pathology. Up arrow indicates increased activity of the gene/pathway/biological process, and down arrow indicates decreased activity of the gene/pathway/molecular function.

Figure 17.3 Effect of doxorubicin on various mitochondria‐related gene ontologies in SHR/SST‐2 rat heart. Male and female SHR/SST‐2 heart tissues were analyzed for doxorubicin effect on mitochondria‐related gene ontologies (pathways/molecular function). A greater drug effect in male SHR/SST‐2 heart was indicated by a significant doxorubicin effect on 24 gene ontologies (black solid bars), whereas drug effect was observed only in one gene ontology (black open bar) in female SHR/SST‐2 heart. Each bar represents the −log10

p

‐value of each statistically significant gene ontology. The total number of genes in each gene ontology is presented in parentheses to the right of each bar, and the number of statistically significant genes within that gene ontology is to the left of the parentheticals. Significance was determined at an alpha of 0.05. Black solid bar represents male and black open bar represents female.

Chapter 18

Figure 18.1 (a) Schematic representation of handling steps. 3D microtissues are formed in hanging drops and transferred in to GravityTRAP plates for compound treatment. For analysis, 3D microtissues are transferred to Seahorse assay plates. (b) OCR trace over time is recorded using the Seahorse MST assay for primary human hepatocytes cultured either in 2D or as 3D microtissues. (c) Comparison of basal respiration, maximal respiration, and spare respiratory capacity (SRC) between 2D and 3D.

Figure 18.2 Spare respiratory capacity (SRC (pmol/min)) of 3D human liver microtissues derived from two single donor batches and one multi‐donor batch (10‐donor).

Figure 18.3 Toxicity assessment of 3D microtissues derived from HepaRG cells and primary human hepatocytes (PHH) using total ATP content (a, c) and SRC (b, d) for amiodarone (a, b, positive control) and ximelagatran (c, d, negative control). Microtissues have been exposed for 2 days to the compounds. Error bars indicate standard deviations of at least three replicates.

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.

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.

Chapter 19

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.

Chapter 20

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.

Figure 20.2 Change from baseline of different methods.

Chapter 21

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.

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.

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).

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.

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.

Figure 21.6 Increased reactive oxygen species observed in Peo1 knockdown embryos at 3 days’ post‐fertilization. Representative 2‐photon image projections of H

2

DCFDA 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 H

2

DCFDA fluorescent product than controls. The bright spots in both panels are epidermal cells (melanocytes) and are excluded from analyses.

Chapter 22

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.

Chapter 24

Figure 24.1 Cartoon of the acylcarnitine shuttle and β‐oxidation of fatty acids in mitochondria. CACT, carnitine/acylcarnitine translocase; CPT1, carnitine palmitoyltransferase 1; CPT2, carnitine palmitoyltransferase 2; LCAD, long‐chain acyl‐CoA dehydrogenase deficiency; MCAD, medium‐chain acyl‐CoA dehydrogenase deficiency; SCAD, short‐chain acyl‐CoA dehydrogenase deficiency; VLCAD, very‐long‐chain acyl‐CoA dehydrogenase deficiency.

Figure 24.2 (a) Cartoon showing the steps involved in the collection of samples for the measurement of acylcarnitines during toxicity studies. Samples can be obtained from

in vitro

and nonclinical toxicity studies or in the clinic from patients with suspected drug‐induced injury. (b) Flow chart showing the steps involved for the measurement of acylcarnitines during toxicity studies.

Figure 24.3 Time response of palmitoyl carnitine (solid line with solid squares) versus ALT (dashed line with solid circles) from mice dosed with 200 mg/kg APAP. *

p

 < 0.05 for palmitoyl carnitine and #

p

 < 0.05 for ALT.

Chapter 25

Figure 25.1 Mitochondrial dysfunction as an early event in disease. Environmental/lifestyle triggers such as high fat and/or glucose or drugs can result in oxidative stress and altered signaling, which in turn damages mitochondria in organs (e.g., kidney, heart, liver), cells (blood cells, adipocytes), and blood vessels; the damage may take decades to manifest itself and cause pathology. Identification of biomarkers for the early detection of metabolic and bioenergetic changes associated with these pathologies could allow intervention and prevention of irreversible bioenergetic dysfunction.

Figure 25.2 Schematic of the hypothesis that mitochondrial DNA can increase in response to oxidative stress as an adaptive response. Environmental/lifestyle triggers such as high fat and/or glucose or drugs result in oxidative stress and altered signaling, which leads to an early adaptive response of increased cellular mtDNA but over time causes systematic damage to mitochondria in organs (e.g., kidney, heart, liver) and cells (blood cells).

Figure 25.3 Changes in cellular mtDNA precede metabolic dysfunction in conditions of oxidative stress. Growth of HMCs in high glucose led to a significant increase in cellular mtDNA, which was detectable within 24 h and highly significant after 4 days. (a) However, the mtDNA was damaged as illustrated by reduced amplification of an mtDNA 8.6 kb fragment (b). Cells showed normal bioenergetic profile at day 4. (c) However, after 8 days, maximal respiration and reserve capacity were significantly reduced in hyperglycemic cells but unaffected in normoglycemic cells (d, e). *

p

 < 0.05, **

p

 < 0.01, ***

p

 < 0.001.

Chapter 26

Figure 26.1 Nucleoside inhibitors target the viral RdRp and inhibit viral replication. See text for details.

Figure 26.2

In vitro

substrate utilization by POLRMT and inhibition of RNA synthesis. (a and b) Factor‐independent assay for POLRMT‐catalyzed nucleotide incorporation. (a) DNA/RNA scaffold. This scaffold consisted of a 12‐nt RNA annealed to an 18‐nt DNA, forming an 8 bp duplex region with a 4‐nt 5′‐RNA overhang and a 10‐nt single‐stranded DNA template. The first templating base is underlined. (b) Single‐ and multiple‐nucleotide incorporation catalyzed by POLRMT. POLRMT is incubated with RNA/DNA‐nucleic acid scaffold and either ATP, ATP, and UTP or ATP, UTP, and GTP for various amounts of time. It forms a stable elongation‐competent complex and readily extends the RNA primer to

n

 + 1,

n

 + 2, and

n

 + 3 in the absence of transcription factors TFB2M and TFAM. (c) Antiviral ribonucleoside triphosphates are substrates for POLRMT. Percentage of RNA product relative to correct nucleotide (ATP, CTP, GTP, or UTP) is shown. Error bars represent s.e.m. (d and e) Inhibition of POLRMT‐mediated transcription. (d) 2′‐C‐methyladenosine ribonucleoside analogue. (e) Non‐obligate chain termination of RNA synthesis

in vitro

. Reaction products from POLRMT‐catalyzed nucleotide incorporation in the presence of the next correct nucleotide substrate, UTP. Reactions containing 2′‐C‐methyl‐ATP were unable to be extended to

n

 + 2, demonstrating the ability of this nucleoside analog to be non‐obligate chain terminator for POLRMT once incorporated into nascent RNA.

Figure 26.3 Determination of the efficiency of nucleotide incorporation by POLRMT. (a) Minimal mechanism for single‐nucleotide incorporation. (b) Kinetics of POLRMT‐catalyzed nucleotide incorporation. POLRMT was incubated with DNA/RNA scaffold and then rapidly mixed with various concentrations of ATP. At each ATP concentration quantitated, the RNA product was plotted as a function of time and fit to a single exponential yielding an observed rate constant,

k

obs

, for POLRMT‐catalyzed nucleotide incorporation. (c) Estimation of

k

pol

and

K

d,app

. Values for

k

obs

were plotted as a function of ATP concentration and fit to a hyperbolic model that defines the mechanism in panel A, yielding estimates of the kinetic parameters

k

pol

, the maximal rate constant for nucleotide incorporation, and

K

d,app

, the apparent dissociation constant for the nucleotide substrate.

Figure 26.4 Predicting adverse effects of antiviral ribonucleosides during preclinical development: The mitovir score. Correlation between cytotoxicity (CC50) and mitovir score for MT4 cells. Metavir score: rate constant for incorporation calculated by using the experimentally determined kinetic parameters

k

pol

and

K

d,app

and the intracellular concentration of nucleoside analog triphosphate [TP]; mitovir score = 

k

eff

(s

−1

) = (

k

pol

 * [TP])/(

K

d,app

 + [TP]). Error bars represent s.d. Nonparametric (Spearman) correlations with

r

values shown. In parentheses are one‐tailed

P

‐values calculated from Spearman coefficients to provide a measure of statistical significance of correlation.

Figure 26.5 Inhibition of POLRMT‐catalyzed RNA synthesis in cells. (a) Experimental design. Huh‐7 cells were treated with ethidium bromide (EtBr) for 24 h to deplete mitochondrial transcripts from cells, washed and treated with 2′‐C‐methyladenosine, total RNA isolated, and Northern blots performed. (b) Northern blots of ND1, ND5, and GAPDH after EtBr treatment and recovery in the presence of 2′‐C‐methyladenosine (2′‐C‐Me‐A). Cells treated with a minimum of 50 μM 2′‐C‐methyladenosine showed specific inhibition of mitochondrial transcription and the inability to produce both ND1 and ND5 transcripts.

Chapter 27

Figure 27.1 Solute handling and uptake of drugs in the nephron. (a) The majority of fluid filtered by the glomerulus (G) is reabsorbed along the proximal tubule (PT). Further reabsorption takes place in the distal tubule (DT) and collecting duct (CD). Various solutes (S) are cotransported across the PT apical membrane with Na

+

, while low molecular weight proteins (LMWPs) are taken up by receptor‐mediated endocytosis into endosomes and eventually lysosomes (L). Sodium transport is driven by the basolateral Na

+

/K

+

‐ATPase, which requires ATP generated by mitochondria (M) located in close proximity (N, nucleus). A number of toxic drugs (X) can rapidly accumulate into PT cells via transporters expressed in the basolateral membrane and induce mitochondrial dysfunction and acute kidney injury. (b) Electron micrograph of a mouse PT showing the characteristic morphological features, including a highly developed apical membrane brush border (BB), numerous subapical endosomes (E), and a high density of elongated mitochondria (M) lying in a striated distribution close to the basolateral membrane (BM). .

Figure 27.2 Multiphoton imaging of mitochondria in live mouse kidney cortex slices. A variety of aspects of mitochondrial function can be imaged in different nephron sections. (a–c) Mitochondrial membrane potential (measured using TMRM, excited at 850 nm) in proximal tubules (PTs) (a) and in a distal tubule (DT) (b). High resolution imaging of mitochondria in the PT, demonstrating the typical elongated morphology (c). (d–f) Mitochondrial NADH (excited at 720 nm) (d), mitochondrial pH (measured with SNARF, excited at 800 nm) (e), and the antioxidant glutathione (measured using monochlorobimane, excited at 720 nm) (f) in the PT. Scale bars = 10 µm in (a and b) and (d–f) and 5 µm in (c).

Figure 27.3 Multiphoton imaging of mitochondrial toxicity in live mouse kidney cortex. By adding the drug under investigation to the tissue perfusate, toxic effects on mitochondria in different nephron segments can be visualized in real time. In the example shown, the effects of the established nephrotoxin sodium maleate (20 mg/mL) are depicted on NADH (excited at 720 nm) and membrane potential (measured using TMRM, excited at 850 nm), two important readouts of mitochondrial function. Maleate causes an acute decrease in NADH signal in the proximal tubule (PT), which is followed by progressive loss of potential. G, glomerulus. Scale bar = 10 µm.

Figure 27.4 Intravital multiphoton imaging of mitochondria in the mouse kidney. (a and b) Mitochondrial NADH (excited at 720 µm) (a) and membrane potential (measured using TMRM, injected intravenously, and excited at 850 nm) (b) in tubules of the outer kidney cortex. (c) Mitochondrial signals in the proximal tubule (PT) can be co‐imaged with real‐time uptake of filtered solutes across the apical membrane. In the example depicted, fluorescently labeled albumin injected intravenously can be visualized in the capillaries of the glomerulus (G) and in subapical endosomes of the PT. (d) Example image from a mouse injected with TMRM, acquired 48 h postinjection of cisplatin (30 mg/kg bodyweight), showing mitochondrial damage in PTs, but a normal appearance in the DT. Scale bars = 50 µm in (a and b) and 10 µm in (c and d).

Chapter 28

Figure 28.1 Mitochondrial membrane potential monitored by fluorescence quenching of rhodamine 123. Fluorescence was excited at 503 nm, and emission was measured at 527 nm. Additions are 0.167 mg protein/ml rat liver mitochondria (Mito), 300 μM ADP, 1.3 μM carbonyl cyanide

m

‐chlorophenylhydrazone (CCCP, an uncoupler), and 1.6 µg/mL antimycin (complex III respiratory inhibitor) to a basic reaction medium containing 150 mM sucrose, 5 mM MgCl

2

, 5 mM disodium succinate, 3.2 μM rotenone, 200 nM Rh123, and 5 mM KPi and K‐HEPES buffers, pH 7.4.

Figure 28.2 Red and green mitochondrial fluorescence after loading with JC‐1. A cultured mouse hepatocyte was loaded with 100 nM JC‐1 for 30 min in Krebs–Ringer–Hepes (KRH) buffer at 37 °C, and green and red fluorescence was imaged by multitrack confocal microscopy using 488 and 543 nm excitation light, respectively. Red inclusions within green fluorescing mitochondria are JC‐1 J‐aggregates.

Figure 28.3 Distribution of electrical potential in a cardiac myocyte. An adult feline cardiac myocyte was loaded with 200 nM TMRM for 20 min at 37 °C, and TMRM fluorescence was imaged by confocal microscopy using 543 nm excitation and a 565–615 nm emission filter. The distribution of Ψ is displayed in pseudocolor, as described in the text.

Figure 28.4 Airyscan super‐resolution volume rendering of TMRM‐labeled mitochondria in a primary rat hepatocyte. Mitochondrial color represents median TMRM fluorescence intensity from low (blue to green) to high (yellow to red). The nucleus is segmented based on PicoGreen labeling and is colored red.

Figure 28.5 Mitochondrial swelling and release of carboxydichlorofluorescein after induction of the mitochondrial permeability transition. Rat liver mitochondria were loaded with 5 mM carboxyDCF diacetate during isolation. CarboxyDCF‐loaded mitochondria (0.5 mg/mL) were added to incubation buffer containing 100 mM KCl, 20 mM Tris, 20 mM K‐Hepes, 10 mM NaCl, 1 mM KH

2

PO

4

, 5 mM succinate, 20 μM EGTA, 2 μM rotenone, and 1 µg/mL oligomycin. Absorbance change at 620 nm (top) and carboxyDCF fluorescence excited at 485 nm (bottom) were determined using a multi‐well fluorescence plate reader. CaCl

2

(100 μM) was added after 1 min (first arrow). Alamethicin (5 μM, second arrow) was added to permeabilize and induce swelling of all mitochondria. Dotted lines indicate gaps in measurements as additions were made.

Figure 28.6 Increased mitochondrial inner membrane permeability in a rat hepatocyte induced by

tert

‐butylhydroperoxide. A cultured rat hepatocyte was loaded with TMRM (left panel) and calcein (right panel). Note that dark round voids in the green calcein fluorescence coincide with red TMRM labeling of mitochondria. After 9 min exposure to 100 μM

tert

‐butylhydroperoxide, dark mitochondrial voids filled with green calcein fluorescence. Simultaneously, mitochondrial release red TMRM fluorescence. These events signified onset of the MPT.

Figure 28.7 Inner membrane permeabilization after ischemia/reperfusion in rat myocytes visualized by mitochondrial calcein release after cold ester loading/warm incubation. An adult rat cardiac myocyte was cold‐loaded with calcein AM and subjected to 3 h of simulated ischemia at 37 °C at pH 6.2 followed by reperfusion at pH 7.4 for 10 and 20 min. Green calcein fluorescence was retained by mitochondria at the end of ischemia. After reperfusion, mitochondria began to release calcein, signifying inner membrane permeabilization. For experimental details, see Kim et al. (2006).

Chapter 30

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 Q

10

.

Figure 30.2 Mevalonate pathway, where PP, pyrophosphate.

Figure 30.3 Effect of simvastatin on rat cerebral ubiquinone status.

Chapter 31

Figure 31.1 Evidence for the existence of subpopulations of mtDNA molecules with different levels of non‐mutational DNA damage. (a)

Apparent

mutational load in muscle of PolG mtDNA “mutator” mouse is higher on shorter (3 kb) PCR fragments than longer ones (16 kb) (Safdar et al. 2016a). This observation is puzzling because true mutations are not expected to affect amplifiability of DNA by PCR. (b) To explain lower levels of mutations in the longer PCR fragments we recall that

apparent

mutations detected by PCR‐based approaches are known to include, in addition to the true mutations, a significant proportion of artificial mutations, which result from error‐prone bypass of chemically damaged DNA nucleotides (Khrapko and Vijg, 2009). Additionally, the number of mtDNA molecules amplifiable with 16 kb primers is typically approximately 10 times lower than those amplifiable with 3 kb primers which implies that a majority of molecules in the sample contain at least one molecule impassable lesion, such as strand break or bulky adduct (black crosses). If so, the lack of mutations on long PCR fragments implies that molecules with impassable lesions also contain an excess of bypassable error‐prone damage sites, as illustrated in panel (b). In other words, a subpopulation of ‘good’ molecules (16 kb amplifiable) is devoid both of impassable lesions and damaged sites. This implies that damage is distributed non‐randomly, and that the ‘good’ subpopulation is not merely a shoulder of a broad distribution of damage levels, but a group of molecules systematically protected from damage.

Chapter 32

Figure 32.1 Modulation of mitochondrial tricarboxylic acid (TCA) cycle and electron transport chain (ETC) functioning by drugs of abuse and addiction.

TCA cycle