Metallothionein involvement in mitochondrial function and disease:
a metabolomics investigation
J. Zander Lindeque, M.Sc.
12662275
Thesis submitted for the degree Philosophiae Doctor in Biochemistry at the Potchefstroom Campus of the North-West University
Promotor: Prof. F.H. van der Westhuizen
Centre for Human Metabonomics, North-West University (Potchefstroom Campus), South Africa.
Co-promotor: Dr. R. Louw
Centre for Human Metabonomics, North-West University (Potchefstroom Campus), South Africa.
September 2011
ABSTRACT
One of the many recorded adaptive responses in respiratory chain complex I deficient cells is the over-expression of the small metal binding proteins, metallothioneins (MTs). The antioxidant properties of MTs putatively protect the deficient cells against oxidative damage, thus limiting further damage and impairment of enzymes involved in energy production. Moreover, the role of metallothioneins in supplying metal cofactors to enzymes and transcription factors in order to promote energy metabolism was previously proposed, which could accompany their role as antioxidants. This view is supported by the observations that MT knockout mice tend to become moderately obese, implying a lower energy metabolic rate. Hence, the involvement of metallothioneins in mitochondrial function and disease cannot be ignored. However, this association is still very vague due to the diversity of their functions and the complexity of the mitochondrion. The use of systems biology technology and more specifically metabolomics technology was thus employed to clarify this association by investigating the metabolic differences between wild type and MT knockout mice in unchallenged conditions as well as when mitochondrial function (energy metabolism) was challenged with exercise and/or a high-fat diet.
The metabolic differences between these mice were also studied when complex I of the respiratory chain was inhibited with rotenone. The metabolome content of different tissues and bio-fluids were examined in an untargeted fashion using three standardized analytical platforms and the data mined using modern metabolomics and related statistical methods. Clear metabolic differences were found between the wild type and MT knockout mice during unchallenged conditions. These metabolic differences were persisted and were often amplified when mitochondrial metabolism was specifically challenged through exercise, high-fat intake or complex I inhibition. The data pointed to an overall reduced metabolic rate in the MT knockout mice and possible insulin resistance after the interventions which imply (and confirm) the involvement of MTs in promoting energy metabolism in the wild type mice.
Keywords: Metallothioneins, mitochondria, metabolomics, metallothionein-knockout, chemometrics
“When a thing was new, people said ‘it is not true’. Later when the truth became obvious, people said ‘it is not important’. And when its importance could not be denied, people said ‘anyway, it is
not new’.” – William James (1842 – 1920)
“Whether we model the reality or only a shadow of it, we form a better understanding of the intricate biochemical processes and their scattering in living systems.” (Weckwerth, 2003)
ACKNOWLEDGEMENTS
I would like to express my sincere gratitude to the following people and institutions for their contribution to this study:
My promoter, Prof. Francois van der Westhuizen, and co-promoter, Dr. Roan Louw, for their guidance, support and overall input in this study. They are extraordinary supervisors, scientists, teachers and people.
Prof. Juan Hidalgo at the Autonomous University of Barcelona for providing the metallothionein knockout mice, experimental samples and for his input in this study.
Mr. Peet Jansen van Rensberg, for teaching and assisting me with the analytical instruments and for his input and advice.
Dr. Gerhard Koekemoer (at the Statistical Consultation Services, NWU) for his expert advice and assistance with the statistics.
Mr. Cor Bester, Mrs. Antoinette Fick and Mr. Petri Bronkhorst at the NWU Animal Reseach Centre for their expert assistance with the mice.
Co-students in the Mito-Lab, Marianne, Ané, Karien and Walter, for the part they played in the rotenone study.
BioPAD, National Research Foundation (NRF) and NWU-Centre for Human Metabonomics for financial support.
Mr. Lesley Wyldbore for language and grammar editing.
My family and wife (Jo-anne) for their unconditional support, love and encouragement and also for my wife’s assistance with the processing of my metabolic data.
And finally, I am deeply grateful for the talents and opportunity the Lord gave me through the grace of our Lord Jesus Christ. All honors go to the Lord.
TABLE OF CONTENTS
LIST OF ABBREVIATIONS AND SYMBOLS I
LIST OF FIGURES V
LIST OF EQUATIONS XI
LIST OF TABLES XII
CHAPTER ONE: INTRODUCTION 1
CHPATER TWO: REVIEW: THE INVOLVEMENT OF METALLOTHIONEINS IN MITOCHONDRIAL
FUNCTION AND DISEASE 4
2.1. Introduction 4
2.2. Mitochondrial function and disease 5
2.2.1. Biological importance and function 5
2.2.2. Mitochondrial disorders and oxidative stress 6
2.3. Metallothioneins 8
2.3.1. General properties of metallothioneins 8
2.3.2. Biological importance and function of metallothioneins 9
2.3.2.1. Metal homeostasis 10
2.3.2.2. Heavy metal detoxification 11
2.3.2.3. Free radical scavenging 12
2.3.2.4. Free radical scavenging mechanisms 12
2.3.2.5. MT research models and current trends 13
2.3.3. Metallothionein localization 14
2.4. Functional associations between metallothioneins and the mitochondrion 16
2.4.1. Metallothioneins, ROS and oxidative stress 18
2.4.2. Apoptosis 20
2.4.3. The metallothionein-glutathione cycle 22
2.4.4. Energy metabolism 24
2.4.4.1. Metal homeostasis and enzyme activity 25
2.4.4.2. Enzyme inhibition and re-activation 27
2.4.4.3. Mitochondrial permeability transition pore 28
2.4.4.4. Nucleotide complex formation 29
2.4.4.5. Cytochrome c and Coenzyme Q 30
2.4.5. Nuclear- and mitochondrial DNA transcription regulation 31
2.5. Conclusions and future prospects 33
CHAPTER THREE: STUDY DESIGN 34
3.1. Problem statement 34
3.2. Study aim 36
3.3. Experimental approaches and design 37
3.3.1. Part1: Establishing metabolomics analyses, data processing and statistical methods for
high-throughput and precision work 37
3.3.1.1. Experimental samples 37
3.3.1.2. Selected metabolomics approach 38
3.3.1.3. Analytical platforms of choice 39
3.3.2. Part 2: A metabolomics investigation on the involvement of MTs in mitochondrial function:
Metabolic differences in WT, MT1+2KO and MT3KO mice when challenged with exercise
and high fat intake (Chapter 4) 40
3.3.3. Part 3: A metabolomics investigation on the involvement of MTs in mitochondrial function and disease: Metabolic differences in WT and MT1+2KO mice during complex I dysfunction
(Chapter 5) 42
CHAPTER FOUR: A METABOLOMICS INVESTIGATION ON THE INVOLVEMENT OF MTs IN MITOCHONDRIAL FUNCTION: METABOLIC DIFFERNCES IN WT, MT1+2KO AND MT3KO MICE WHEN CHALLENGED WITH EXERCISE
AND HIGH FAT INTAKE 44
4.1. Introduction 44
4.2. Materials and methodology 45
4.2.1. Materials 45
4.2.2. Experimental groups and samples 46
4.2.3. Sample preparation 47
4.2.3.1. Deproteinization of plasma samples for metabolic footprinting 47 4.2.3.2. Metabolome extraction from tissue samples for metabolic fingerprinting 48
4.2.3.3. Oximation and silylation 49
4.2.3.4. Methylation 49
4.2.3.5. Sample blocking 50
4.2.4. Instrumentation and analysis 50
4.2.4.1. Positive scan LC-MS 50
4.2.4.2. GC-MS analysis of trimethylsilyl esters 51
4.2.4.3. GC-MS analysis of FAMEs 51
4.2.5. Data extraction 51
4.2.5.1. LC-MS data 51
4.2.5.2. GC-MS data 52
4.2.6. Data pre-processing and normalization 53
4.2.6.1. LC-MS data 53
4.2.6.2. GC-MS data 53 4.2.6.3. Batch correction of plasma and gastrocnemius data 54 4.2.7. Data pre-treatment, statistical analysis and bio-informatics 54
4.2.7.1. Univariate analysis 54
4.2.7.2. Multivariate analysis 55
4.3. Results and Discussion 57
4.3.1. Evaluating the effect of exercise on the metabolome and exometabolome 57
4.3.1.1. Plasma exometabolome 57 4.3.1.2. Gastrocnemius metabolome 62 4.3.1.3. Liver metabolome 67 4.3.1.4. Brain metabolome 78 4.3.1.5. Biological interpretation of the effect of exercise on the metabolism 85 4.3.2. Evaluating the effect of high fat intake on the metabolome and exometabolome 87 4.3.2.1. Plasma exometabolome 87 4.3.2.2. Gastrocnemius metabolome 90 4.3.2.3. Liver metabolome 93 4.3.2.4. Brain metabolome 98
4.3.2.5. Biological interpretation of the effect of the HFD on the metabolism 101
4.3.3. Evaluating the combined effect of exercise and high fat intake on the metabolome and exometabolome 105
4.3.3.1. Plasma exometabolome 105
4.3.3.2. Gastrocnemius metabolome 108
4.3.3.3. Liver metabolome 112
4.3.3.4. Brain metabolome 117
4.3.3.5. Biological interpretation of the effect of high-fat diet and exercise on the metabolism 120
4.3.4. Metabolic differences between WT, MT1+2KO and MT3KO mice during unchallenged conditions 121
4.3.4.1. Plasma exometabolome 121
4.3.4.2. Gastrocnemius metabolome 123
4.3.4.3. Liver metabolome 126
4.3.4.4. Brain metabolome 133
4.3.4.5. Biological interpretation of the metabolic differences between the WT, MT1+2KO and MT3KO mice 137
4.3.5. Metabolic differences between WT, MT1+2KO and MT3KO mice after challenged with exercise 142
4.3.5.1. Plasma exometabolome 142
4.3.5.2. Gastrocnemius metabolome 144
4.3.5.3. Liver metabolome 148
4.3.5.4. Brain metabolome 156
4.3.5.5. Biological interpretation of the metabolic differences between the WT, MT1+2KO and MT3KO mice when challenged with exercise 161
4.3.6. Metabolic differences between WT, MT1+2KO and MT3KO mice after challenged with a high fat intake 163
4.3.6.1. Plasma exometabolome 163
4.3.6.2. Gastrocnemius metabolome 167
4.3.6.3. Liver metabolome 169
4.3.6.4. Brain metabolome 177
4.3.6.5. Biological interpretation of the metabolic differences between the WT, MT1+2KO and MT3KO mice when challenged with a high fat intake 182
4.3.7. Metabolic difference between WT, MT1+2KO and MT3KO mice after challenged with a high fat intake and exercise 186
4.3.7.1. Plasma exometabolome 186
4.3.7.2. Gastrocnemius metabolome 188
4.3.7.3. Liver metabolome 192
4.3.7.4. Brain metabolome 198
4.3.7.5. Biological interpretation of the metabolic differences between the WT, MT1+2KO and MT3KO mice when challenged with a high fat intake and exercise 202
4.4. Chapter summary 205
CHAPTER FIVE: THE INVOLVEMENT OF MTs IN MITOCHONDRIAL FUNCTION AND DISEASE: METABOLIC DIFFERENCES IN WT AND MT1+2KO MICE DURING COMPLEX I DYSFUNCTION 207
5.1. Introduction 207
5.2. Materials and Methodology 208
5.2.1. Materials 208
5.2.2. Test animals 208
5.2.3. Genotyping 209
5.2.4. Experimental procedures 209
5.2.5. Sample collection 210
5.2.6. Sample preparation 211
5.2.6.1. Deproteinization of serum samples for metabolic footprinting 211
5.2.6.2. Preparation of urine samples for metabolic footprinting 212
5.2.6.3. Oximation and silylation 212
5.2.6.4. Methylation 212
5.2.6.5. Sample blocking 213
5.2.7. Instrumentation and analysis 213
5.2.7.1. Positive scan LC-MS 213
5.2.7.2. GC-MS of trimethylsilyl esters 213
5.2.7.3. GC-MS of FAMEs 213
5.2.8. Data extraction 213
5.2.8.1. LC-MS data 213
5.2.8.2. GC-MS data 213
5.2.9. Data pre-processing and normalisation 214
5.2.9.1. LC-MS data 214
5.2.9.2. GC-MS data 214
5.2.10. Data pretreatment, statistical analysis and bio-informatics 214
5.2.10.1. Univariate analysis 214
5.2.10.2. Multivariate analysis 214
5.3. Results and discussion 215
5.3.1. Genotyping 215
5.3.2. Evaluating the effect of rotenone treatment in the exometabolome 216
5.3.2.1. Snapshot of serum exometabolome 217
5.3.2.2. Urine exometabolome: 14 hour overview of metabolic state 221
5.3.2.3. Biological interpretation of the effect of the rotenone treatment and complex I inhibition on the metabolism 226
5.3.3. Metabolic differences between WT and MT1+2KO mice during unchallenged conditions 227
5.3.3.1. Snapshot of serum exometabolome 227
5.3.3.2. Urine exometabolome: 14 hour overview of metabolic state 230
5.3.3.3. Biological interpretation of metabolic differences between the WT and MT1+2KO mice during unchallenged conditions 233
5.3.4. Metabolic differences between WT and MT1+2KO mice during complex I dysfunction 235
5.3.4.1. Snapshot of serum exometabolome 235
5.3.4.2. Urine exometabolome: 14 hour overview of metabolic state 239
5.3.4.3. Biological interpretation of metabolic differences between the WT and MT1+2KO mice during complex I dysfunction 242
5.4. Chapter summary 246
CHAPTER SIX: CONCLUSIONS AND FUTURE PROSPECTS 248
6.1. Study aims and objectives: motivation and accomplishments 248
6.1.1. The establishment and standardisation of a high-throughput and precise metabolomics data generation, data processing and statistics workflow 250 6.1.2. Metabolic differences between WT, MT1+2KO and MT3KO mice during
unchallenged conditions and when mitochondrial metabolism was
specifically challenged with exercise and/or high-fat intake 251
6.1.3. Metabolic differences between WT and MT1+2KO mice during unchallenged conditions and when complex I is dysfunctional 253
6.2. New concepts and Hypotheses 254
6.2.1. Hypothetical roles of MTs in mitochondria function and disease 255
6.3. Critical assessment of this study 259
6.4. Final conclusion and future prospects 261
REFERENCES 263
ANNEXURE A: METABOLOMICS: TECHNOLOGY, APPROACHES AND DATA MINING 293
A.1. Metabolomics approaches and technology 293
A.1.1. Introduction 293
A.1.1.1. Terminology 294
A.1.2. Metabolomics approaches 296
A.1.3. Analytical platforms (technologies) 298
A.1.3.1. GC-MS: overview, advantages and limitations 300
A.1.3.2. LC-MS: overview, advantages and limitations 302
A.1.4. Metabolomics (fingerprinting) methodology 304
A.1.4.1. Sample collection and storage 304
A.1.4.2. Sample preparation 305
A.1.4.2.1. Metabolite extraction from tissue samples and cells 305
A.1.4.2.2. Deproteinization of blood plasma and serum 307
A.1.4.2.3. Preparation of urine 308
A.1.4.3. Technical variance and the use of internal standards in MS-based metabolomics 309
A.1.4.4. Derivatization strategies for GC-MS analysis 312
A.1.4.4.1. Oximation and silylation 312
A.1.4.4.2. Methylation 315
A.2. Metabolomics data processing and statistical analysis 316
A.2.1. Introduction 316
A.2.2. Raw data cleanup and extraction 318
A.2.2.1. First order data cleaning 318
A.2.2.2. Data extraction 318
A.2.2.2.1. LC-MS data extraction 320
A.2.2.2.2. GC-MS data extraction 323
A.2.3. Data pre-processing 324
A.2.4. Data normalisation and pre-treatment 327
A.2.4.1. Data normalisation 327
A.2.4.1.1. Normalisation to sample weight 327
A.2.4.1.2. Normalisation to internal standard(s) 328
A.2.4.1.3. Normalisation to total signal 328
A.2.4.2. Data pre-treatment 329
A.2.4.2.1. Centering 330
A.2.4.2.2. Auto-scaling 330
A.2.4.2.3. Pareto scaling 330
A.2.4.2.4. VAST scaling 331
A.2.4.2.5. Log transformation 331
A.2.4.2.6. Power and fourth root transformation 332
A.2.4.2.7. Data pre-treatment combinations in the literature 332
A.2.5. Statistical analysis of the data using chemometrics and univariate methods 333
A.2.5.1. Univariate statistics 334
A.2.5.2. Chemometrics techniques 334
A.2.5.2.1. Principal component analysis (PCA) 335
A.2.5.2.2. Independent component analysis (ICA) 336
A.2.5.2.3. Partial least squares (projection to latent structures) – discriminant analysis (PLS-DA) 337
A.3. Annexure summary 337
ANNEXURE B: METABOLOMICS: METHODOLOGY CONSIDERATIONS, DEVELOPMENT AND STANDARDISATION 338
B.1. Introduction 338
B.2. Standardising the extraction and LC-MS analysis of polar metabolite 338
B.2.1. LC-MS analysis of polar metabolites 338
B.2.2. Selection of internal and external standards 339
B.2.2.1. Materials and method 339
B.2.2.2. Results and discussion 340
B.2.3. Metabolite extraction from tissue sample for metabolic fingerprinting 343
B.2.3.1. Materials and methods 344
B.2.3.2. Results and discussion 345
B.2.4. Deproteinization of plasma/serum samples for metabolic footprinting 348
B.2.4.1. Materials and method 349
B.2.4.2. Results and discussion 349
B.2.5. Preparation of urine samples for metabolic footprinting 351
B.2.5.1. Materials and method 351
B.2.5.2. Results and discussion 351 B.3. Standardising the extraction, trimethylsilylation and GC-MS analysis of primary
metabolites 352
B.3.1. GC-MS analysis of trimethylsilyl esters 352
B.3.2. Selection of internal and external standards 352
B.3.2.1. Materials and methods 353
B.3.2.2. Results and discussions 354
B.3.3. Metabolite extraction from tissue samples for metabolic fingerprinting 355
B.3.3.1. Materials and methods 355
B.3.3.2. Results and discussion 356
B.3.4. Deproteinization of plasma/serum samples for metabolic footprinting 357
B.3.5. Preparation of urine samples for metabolic footprinting 357
B.3.5.1. Materials and method 358
B.3.5.2. Results and discussion 359
B.3.6. Silylation and oximation of metabolites to give trimethylsilyl esters 360
B.3.6.1. Materials and methods 361
B.3.6.2. Results and discussions 363
B.4. Standardising the extraction, methylation and GC-MS analysis of lipids and fatty acids 365
B.4.1. GC-MS analysis of FAMEs 365
B.4.2. Selection of internal and external standards 365
B.4.2.1. Materials and methods 366
B.4.2.2. Results and discussions 366
B.4.3. Metabolite extraction from tissue samples for metabolic fingerprinting 367
B.4.3.1. Materials and methods 367
B.4.3.2. Results and discussion 368
B.4.4. Deproteinization of plasma/serum samples for metabolic footprinting 368
B.4.5. Preparation of urine samples for metabolic footprinting 368
B.4.6. Methylation of lipids to give fatty acid methyl esters 369
B.4.6.1. Materials and methods 369
B.4.6.2. Results and discussions 370
B.5. Annexure summary 372
ANNEXURE C: METABOLOMICS DATA PROCESSING AND STATISTICAL ANALYSIS: APPROACH AND METHOD SELECTION FOR A HIGH-THROUGHPUT WORKFLOW 373
C.1. Introduction 373
C.2. Raw data cleanup and extraction 373
C.2.1. First order data cleaning 373
C.2.2. Data extraction 374
C.2.2.1. LC-MS data extraction 374
C.2.2.1.1. MassHunter-MPP untargeted data extraction procedure 375
C.2.2.1.2. MassHunter-MPP targeted data extraction procedure 376
C.2.2.2. GC-MS data extraction 376
C.2.2.2.1. Materials and methods 377
C.2.2.2.2. Results and discussion 378
C.2.2.2.3. AMDIS - MET-IDEA data extraction procedure 382
C.3. Data pre-processing 383
C.3.1. LC-MS data pre-processing 383
C.3.1.1. Materials and methods 385
C.3.1.2. Results and discussion 385
C.3.2. GC-MS data pre-processing 386
C.3.2.1. Materials and methods 387
C.3.2.2. Results and discussion 388
C.4. Data normalisation and pre-treatment 389
C.4.1. Data normalisation 389
C.4.1.1. Normalisation to sample weight 389
C.4.1.2. Normalisation to internal standard(s) 390
C.4.1.3. Normalisation to total signal 390
C.4.1.4. Batch normalisation and signal correction 391
C.4.1.5. Data pre-treatment 392
C.5. Statistical analysis 393
C.5.1. Univariate statistics 393
C.5.2. Multivariate statistics 394
C.5.2.1. Principal component analysis (PCA) 394
C.5.2.2. Partial least square discriminant analysis 395
C.6. Annexure summary 395
ANNEXURE D: RE-EVALUATING THE INFLUENCE OF MOISTURE IN DERIVATIZATION: DOES RESIDUAL WATER IN DRIED URINE AND TISSUE SAMPLES MATTER? 396
D.1. Introduction 396
D.2. Materials and methods 396
D.3. Results and discussion 397
ANNEXURE E: BODY WEIGHT GAIN OF WT, MT1+2KO AND MT3KO MICE ON NORMAL AND HIG-FAT DIET 400
ANNEXURE F: THE COLLABORATIVE INVESTIGATION OF THE ROLE OF MTs IN MITOCHONDRIAL FUNCTION AND DISEASE: THE
ROTENONE STUDY 403
F.1. Description of the collaborative study 403
F.2. Supplementary data showing complex I inhibition 403
ANNEXURE G: SUPPLEMENTARY MATERIAL: CD 407
ANNEXURE H: PUBLICATIONS AND CONFERENCE PROCEEDINGS 408
ANNEXURE I: CO-AUTHOR CONSENT 409
I
LIST OF ABBREVIATIONS AND SYMBOLS
SYMBOLS
α alpha
β beta
m milli (10-3) µ micro (10-6) n nano (10-9)
°C degrees Celsius
% percentage
> greater than
< less than
< v.c below visual cut-off
~ approximately
# number
x g g-force (9.80665 m/s2)
ABBREVIATIONS ACN acetonitrile
ADP adenosine diphosphate
Ag silver
ATP adenosine triphosphate
bp base pairs
BSA bovine serum albumin
BSTFA O-bis(trimethylsilyl)trifluoroacetamide
CCMN Cross-Contribution robust Multiple internal standard Normalization
Cd cadmium
CI complex I (NADH:ubiquinone oxidoreductase) CII complex II (succinate:ubiquinone oxidoreductase) CIII complex III (coenzyme Q - cytochrome c reductase)
II CIV complex IV (cytochrome c oxidase) CoQ coenzyme Q (ubiquinone)
Cu copper
CV coefficient of variance cyt c cytochrome c
Da Dalton
DMPA N,N-dimethyl-L-phenylalanine DNA deoxyribonucleic acid
EC environmental control
EDTA ethylene diamine tetra-acetate ESI electrospray ionisation
ETC electron transport chain EtOH ethanol
FAD flavin adenine dinucleotide FbF find by formula
FbI find by ion
g gram
GC gas chromatography
GPx glutathione peroxidase GSH reduced glutathione
GSSG oxidized glutathione (dimer)
h hour
HCl hydrochloric acid HFD high-fat diet
HFD-E high-fat diet & exercise
Hz Hertz
IMs important metabolites
III kDa kilo Dalton
KOH potassium hydroxide
l liter
LC liquid chromatography
M molar
MeOH methanol
MFE molecular feature extraction
min minutes
ml milliliter
mM milli-molar
MPP Mass Profiler Professional
MS mass spectrometry
MSTFA N-Methyl-N-trifluoroacetamide MSTUS mass spectrometry total useful signal MT metallothionein
MT-1 metallothionein isoform 1 MT-2 metallothionein isoform 2 MT-3 metallothionein isoform 3 MT-4 metallothionein isoform 4
MTKO metallothionein knockout (unspecified, referring to both MT1+2KO and MT3KO) MT1+2KO metallothioneins isoforms 1 and 2 knockout
MT3KO metallothioneins isoform 3 knockout mtDNA mitochondrial DNA
MTs metallothioneins
m/z mass to charge
NAD(H) nicotinamide adenine dinucleotide (reduced)
nM nano-molar
nm nanometer
OH˙ hydroxyl radical
OXPHOS oxidative phosphorylation
IV PBS phosphate buffered saline
PC principal component
PCA principal component analysis PCR polymerase chain reaction
PLS Partial least squares (projection to latent structures) PLS-DA partial least squares discriminant analysis
PLSR partial least squares regression ppm parts per million
QC quality control
Q-TOF quadrupole time of flight
RNS reactive nitrogen species ROS reactive oxygen species
RP reverse phase
RT retention time; rotenone treatment
SD standard deviation SOD superoxide dismutase
TIC total ion chromatogram TOF time of flight
VAST variable stability VC vehicle control
WT wild type
Zn zinc
V
LIST OF FIGURES
Figure # Title Page #
2.1 Cellular localization of EGFP-MT-1B fusion protein in HeLa cells visualised by confocal microscopy
16
2.2 Summarized schematic presentation of the putative interactions of MTs with the mitochondrion
17
2.3 The metallothioneins-glutathione redox and metal exchange cycle 23
3.1 Illustration of the common workflow of a metabolomics experiment 38 3.2 Schematic presentation of the experimental and metabolomics strategy designed to
investigate the involvement of MTs in normal mitochondrial function and metabolism
41
3.3 Schematic presentation of the experimental and metabolomics strategy to comprehensively investigate the role of MTs in mitochondrial disease (complex I deficiency)
42
4.1 Experimental procedures for investigating the role of MTs in challenged mitochondrial function
46
4.2 Sample preparation and analytical procedures for liver (A), plasma (B), brain (C) and gastrocnemius (D) samples
48
4.3 The two-dimensional comparison of experimental groups 56
4.4 The effect of the exercise, high-fat diet and high-fat diet with exercise on the plasma exometabolome as detected with untargeted LC-MS analyses
58
4.5 The effect of exercise, high-fat diet and high-fat diet with exercise on the gastrocnemius metabolome as detected with LC-MS analyses
63
4.6 The effect of exercise, high-fat diet and high-fat diet with exercise on the gastrocnemius metabolome as detected with silylation-GC-MS analyses
64
4.7 Preliminary PCA results of the liver samples showing clear differences between male and female mice
67
4.8 The effect of exercise, high-fat diet and high-fat diet with exercise on the liver metabolome of female mice as detected with LC-MS analyses
68
4.9 The effect of exercise, high-fat diet and high-fat diet with exercise on the liver metabolome of male mice as detected with LC-MS analyses
69
4.10 The effect of exercise, high-fat diet and high-fat diet with exercise on the liver metabolome of female mice as detected with silylation-GC-MS analyses
70
4.11 The effect of exercise, high-fat diet and high-fat diet with exercise on the liver 71
VI
metabolome of male mice as detected with silylation-GC-MS analyses
4.12 The effect of exercise, high-fat diet and high-fat diet with exercise on the liver metabolome of female mice as detected with methylation-GC-MS analyses
72
4.13 The effect of exercise, high-fat diet and high-fat diet with exercise on the liver metabolome of male mice as detected with methylation-GC-MS analyses
73
4.14 The effect of exercise, high-fat diet and high-fat diet with exercise on the brain metabolome as detected with LC-MS analyses
79
4.15 The effect of exercise, high-fat diet and high-fat diet with exercise on the brain metabolome as detected with silylation-GC-MS analyses
80
4.16 The mitochondrion - the hub of metabolism and energy production 86 4.17 Proposed metabolic implications of a long term high-fat diet 103 4.18 Glutathione is synthesized and catabolised in the γ-glutamyl cycle 104 4.19 Differences in the plasma exometabolome composition of WT, MT1+2KO and
MT3KO mice as detected with untargeted LC-MS analyses
122
4.20 Differences in the gastrocnemius metabolome composition of WT, MT1+2KO and MT3KO mice as detected with untargeted LC-MS analyses
124
4.21 Differences in the gastrocnemius metabolome composition of WT, MT1+2KO and MT3KO mice as detected with silylation GC-MS analyses
124
4.22 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO male mice as detected with untargeted LC-MS analyses
128
4.23 Differences in the liver metabolome composition of WT, MT1+KO and MT3KO female mice as detected with untargeted LC-MS analyses
128
4.24 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO male mice as detected with silylation-GC-MS analyses
129
4.25 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO female mice as detected with silylation-GC-MS analyses
129
4.26 Differences in the liver lipidome composition of WT, MT1+2KO and MT3KO male mice as detected with methylation-GC-MS
130
4.27 Differences in the liver lipidome composition of WT, MT1+2KO and MT3KO female mice as detected with methylation-GC-MS
130
4.28 Differences in the brain metabolome composition of WT, MT1+2KO and MT3KO mice as detected with untargeted LC-MS analyses
135
4.29 Differences in the brain metabolome composition of WT, MT1+2KO and MT3KO mice as detected with silylation-GC-MS analyses
135
4.30 Cyclic-AMP stimulates glycogenolysis and lipolysis 138
4.31 Biosynthesis of different lipid species from phosphatidate (1-acyl-sn-glycerol-3- 140
VII
phosphate)
4.32 An overview of biosynthesis linked to the central metabolism 141 4.33 Differences in the plasma exometabolome composition of WT, MT1+2KO and
MT3KO mice after exercise as detected with untargeted LC-MS analyses
143
4.34 Differences in the gastrocnemius metabolome composition of the WT, MT1+2KO and MT3KO mice after exercise as detected with untargeted LC-MS analyses
146
4.35 Differences in the gastrocnemius metabolome composition of the WT, MT1+2KO and MT3KO mice after exercise as detected with silylation-GC-MS analyses
146
4.36 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO male mice after exercise as detected with untargeted LC-MS analyses
150
4.37 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO female mice after exercise as detected with untargeted LC-MS analyses
150
4.38 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO male mice after exercise as detected with silylation-GC-MS analyses
151
4.39 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO female mice after exercise as detected with silylation-GC-MS analyses
151
4.40 Differences in the liver lipidome composition of WT, MT1+2KO and MT3KO male mice after exercise as detected with methylation-GC-MS analyses
152
4.41 Differences in the liver lipidome composition of WT, MT1+2KO and MT3KO female mice after exercise as detected with methylation-GC-MS analyses
152
4.42 Differences in the brain metabolome composition after exercise as detected with untargeted LC-MS analyses
157
4.43 Differences in the brain metabolome composition after exercise as detected with silylation-GC-MS analyses
157
4.44 Differences in the plasma exometabolome composition of WT, MT1+2KO and MT3KO mice as detected with untargeted LC-MS analyses
163
4.45 Differences in the gastrocnemius metabolome composition of WT, MT1+2KO and MT3KO mice as detected with untargeted LC-MS analyses
168
4.46 Differences in the gastrocnemius metabolome composition of WT, MT1+2KO and MT3KO mice as detected with silylation GC-MS analyses
168
4.47 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO male mice as detected with untargeted LC-MS analyses
171
4.48 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO female mice as detected with untargeted LC-MS analyses
171
4.49 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO male mice as detected with silylation GC-MS analyses
172
4.50 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO 172
VIII
female mice as detected with silylation GC-MS analyses
4.51 Differences in the liver lipidome composition of WT, MT1+2KO and MT3KO male mice as detected with methylation GC-MS analyses
173
4.52 Differences in the liver lipidome composition of WT, MT1+2KO and MT3KO female mice as detected with methylation GC-MS analyses
173
4.53 Differences in the brain metabolome composition of WT, MT1+2KO and MT3KO mice as detected with untargeted LC-MS analyses
178
4.54 Differences in the brain metabolome composition of WT, MT1+2KO and MT3KO mice as detected with silylation GC-MS analyses
178
4.55 Interplay of organs and metabolic pathways 184
4.56 Differences in the plasma exometabolome composition of WT, MT1+2KO and MT3KO mice as detected with untargeted LC-MS analyses
186
4.57 Differences in the gastrocnemius metabolome composition of WT, MT1+2KO and MT3KO mice as detected with untargeted LC-MS analyses
190
4.58 Differences in the gastrocnemius metabolome composition of WT, MT1+2KO and MT3KO mice as detected with silylation GC-MS analyses
190
4.59 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO male mice as detected with untargeted LC-MS analyses
193
4.60 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO female mice as detected with untargeted LC-MS analyses
193
4.61 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO male mice as detected with silylation GC-MS analyses
194
4.62 Differences in the liver metabolome composition of WT, MT1+2KO and MT3KO female mice as detected with silylation GC-MS analyses
194
4.63 Differences in the liver lipidome composition of WT, MT1+2KO and MT3KO male mice as detected with methylation GC-MS analyses
195
4.64 Differences in the liver lipidome composition of WT, MT1+2KO and MT3KO female mice as detected with methylation GC-MS analyses
195
4.65 Differences in the brain metabolome composition of WT, MT1+2KO and MT3KO mice as detected with untargeted LC-MS analyses
199
4.66 Differences in the brain metabolome composition of WT, MT1+2KO and MT3KO mice as detected with silylation GC-MS analyses
199
5.1 Experimental procedures for investigating the role of MTs in mitochondrial function during complex I inhibition
210
5.2 Sample preparation and analytical procedures 211
5.3 The two-dimensional comparison of experimental groups 215
IX
5.4 Example of PCR and gel electrophoresis genotyping 216
5.5 The effect of rotenone treatment on the serum exometabolome as detected with LC- MS and silylation-GC-MS
219
5.6 The effect of rotenone treatment on the urinary exometabolome as detected with LC-MS and silylation-GC-MS
223
5.7 Differences in the serum exometabolome composition of WT and MT1+2KO mice as detected with untargeted LC-MS analyses
228
5.8 Differences in the serum exometabolome composition of WT and MT1+2KO mice as detected with silylation GC-MS analyses
228
5.9 Differences in the urine exometabolome composition of WT and MT1+2KO mice as detected with untargeted LC-MS analyses
231
5.10 Differences in the urine exometabolome composition of WT and MT1+2KO mice as detected with silylation GC-MS analyses
231
5.11 Differences in the serum exometabolome composition of WT and MT1+2KO mice as detected with untargeted LC-MS analyses
236
5.12 Differences in the serum exometabolome composition of WT and MT1+2KO mice as detected with silylation GC-MS analyses
236
5.13 Differences in the urinary exometabolome composition of WT and MT1+2KO mice as detected with untargeted LC-MS analyses
240
5.14 Differences in the urinary exometabolome composition of WT and MT1+2KO mice as detected with silylation GC-MS analyses
240
5.15 Metabolic pathways involved in perturbation and the involvement of insulin 243 516 Proposed events leading to moderate insulin resistance and counteractions of MTs 245
6.1 Schematic presentation illustrating the hypothetical roles of MTs in mitochondrial and insulin function
257
A.1 The ‘omics’ cascade 294
A.2 Approaches to study metabolic responses in biological systems 297
A.3 The oximation and silylation reaction 313
A.4 The base-catalyzed methylation reaction 316
A.5 The process of data mining to acquire relevant biological information from complex metabolomics data
317
A.6 The three main steps involved in data extraction 319
A.7 Multivariate vs. univariate statistics in grouping and validation 333
A.8 PCA scores plot (A) and loadings plot (B). 336
X
B.1 Overlaid LC-MS chromatograms of all the tested standards (A) and representative mice samples (B).
341
B.2 Data and score plots indicating the repeatable metabolite extraction of liver (soft) and muscle (hard) tissue samples
345
B.3 Data and score plots indicating the metabolite extraction at different temperatures and different organic solvents.
347
B.4 Data and score plots of plasma samples deproteinized with acetonitrile and ultrafiltration.
350
B.5 Comparative (mirror) data plot of acetonitrile treated and untreated urine samples. 352 B.6 Chromatograms of all the tested standards and mice tissue/bio-fluid samples. 354 B.7 Experimental strategy to study the difference in monophasic and biphasic
metabolite extraction for silylation and GC-MS analyses.
356
B.8 Experimental strategy to investigate different urine preparation methods for silylation - GC-MS.
358
B.9 Representative chromatograms of mice urine prepared with acetonitrile (A) and organic acid extraction (B).
359
B.10 Experimental procedure to validate selected oximation and silylation conditions. 362 B.11 Validation results of the selected oximation and silylation conditions. 364 B.12 Overlaid GC-MS chromatograms of all the tested standards (A) and representative
mice samples (B).
367
B.13 Overlaid chromatogram of the FAME (A) and PUFA (B) mix alone and after silylation with BSTFA.
371
C.1 Comparison of the variability of the extracted data of five replicate samples with numerous software options.
379
C.2 Data and score plots of LC-MS data before and after pre-processing. 386 C.3 Data and score plots of GC-MS data before and after pre-processing. 388 C.4 An S-type bar plot of the average Euclidean distances determined from the loadings
matrix.
394
D.1 Experimental strategy to study the influence of moisture on silylation. 397 D.2 Chromatograms showing the influence of moisture on silylation. 398
E.1 Body weight gain of the WT, MT1+2KO and MT3KO mice that was fed a high-fat diet or a control (chow) diet
400
E.2 Absolute weights of liver, gonadal and inguinal fat depost from the WT, MT1+2KO and MT3KO mice
401
XI
F.1 Schematic presentation of the strategy designed to comprehensively investigate the role of MTs in mitochondrial disease (complex I deficiency)
404
F.2 Box and whiskers plots showing the different OXPHOS enzyme activities in the heart
405
F.3 Box and whiskers plots showing the different OXPHOS enzyme activities in the skeletal muscle
406
F.4 Bar plot presentation of the enzyme quantities as determined using BN-PAGE and western blot analyses of heart mitochondrial fractions
406
LIST OF EQUATIONS
Equation # Title Page #
C.1 Equation for determining effect size between two groups 394
XII
LIST OF TABLES
Table # Title Page #
4.1 Important plasma metabolites that differed markedly between the exercise and control group of each strain
59
4.2 Pathway analysis results from the plasma LC-MS IMs obtained when the exercise group of each mouse strain was compared to their respective control group
60
4.3 Important metabolites that differed markedly between the control and exercise group in the gastrocnemius
65
4.4 Pathway analysis results from the gastrocnemius IMs obtained after the exercise group was compared to the control
65
4.5 Important metabolites that differed markedly between the control and exercise group in the liver
74
4.6 Pathway analysis results from the liver IMs obtained after the exercise group was compared to the control
76
4.7 Important metabolites that differed markedly between the control and exercise group in the brain
81
4.8 Pathway analysis results from the brain IMs obtained after the exercise group was compared to the control
83
4.9 Important plasma metabolites that differed markedly between the control- and HFD group for each genotype, respectively
88
4.10 Pathway analysis results from the plasma LC-MS IMs obtained after the HFD group was compared to the control
89
4.11 Important metabolites that differed markedly between the control and HFD group in the gastrocnemius
91
4.12 Pathway analysis results from the plasma LC-MS IMs obtained after the HFD group was compared to the control
92
4.13 Important metabolites that differed markedly between the control and HFD group in the liver
94
4.14 Pathway analysis results from the liver IMs obtained after the HFD group was compared to the control
96
4.15 Important metabolites that differed markedly between the control and HFD group in the brain
98
4.16 Pathway analysis results from the brain IMs obtained after the HFD group was compared to the control
100
XIII
4.17 Important plasma metabolites that differed markedly between the control and HFD- E group
106
4.18 Pathway analysis results from the plasma IMs obtained after the HFD-E group was compared to the control
107
4.19 Important metabolites in the gastrocnemius that differed markedly between the control and HFD-E group
108
4.20 Pathway analysis results from the gastrocnemius IMs obtained after the HFD-E group was compared to the control
110
4.21 Important hepatic metabolites that differed markedly between the control and HFD- E group
113
4.22 Pathway analysis results from the liver IMs obtained after the HFD-E group was compared to the control
116
4.23 Important metabolites from the brain that differed markedly between the control and HFD-E group
118
4.24 Pathway analysis results from the brain IMs obtained after the HFD-E group was compared to the control
120
4.25 Important plasma metabolites that differed markedly between the strains 123 4.26 Important gastrocnemius metabolites that differed markedly between the strains 125 4.27 Pathway analysis results from the gastrocnemius IMs obtained after the MT
knockouts were compared to the WT
125
4.28 Important hepatic metabolites that differed markedly between the strains 131 4.29 Pathway analysis results of the IMs obtained after the males and females MT
knockout mice were compared to the WT mice
133
4.30 Important brain metabolites that differed markedly between the strains 136 4.31 Pathway analysis results from the IMs obtained after the MT knockout mice were
compared to the WT
136
4.32 Important plasma metabolites that differed markedly between the strains after exercise
144
4.33 Pathway analysis results from the plasma IMs obtained after the MT knockouts were compared to the WT
144
4.34 The important gastrocnemius metabolites that differed markedly between the strains after exercise
147
4.35 Pathway analysis results of the IMs obtained after the MT knockout mice was compared to the WT.
147
4.36 Important liver metabolites that differed markedly between the strains after exercise 153 4.37 Pathway analysis results of the IMs obtained after the male and female MT
knockout mice was compared to the WT
155
XIV
4.38 The important brain metabolites that differed markedly between the strains after exercise.
158
4.39 Pathway analysis results of the IMs obtained after the MT knockout mice were compared to the WT mice
160
4.40 Important plasma metabolites that differed markedly between the strains after a long term HFD
164
4.41 Pathway analysis results from the plasma IMs obtained after the MT knockouts were compared to the WT
165
4.42 Important metabolites in the gastrocnemius that differed markedly between the strains after a long term HFD
169
4.43 Pathway analysis results from the gastrocnemius IMs obtained after the MT knockouts were compared to the WT
169
4.44 Important hepatic metabolites that differed markedly between the strains after a long term HFD
174
4.45 Pathway analysis results from the hepatic IMs obtained after the MT knockouts were compared to the WT
176
4.46 Important brain metabolites that differed markedly between the strains after a long term HFD
179
4.47 Pathway analysis results from the brain IMs obtained after the MT knockouts were compared to the WT
181
4.48 Important plasma metabolites that differed markedly between the strains after a long term HFD and one hour swim
187
4.49 Pathway analysis results from the plasma IMs obtained after the MT knockouts were compared to the WT
187
4.50 Important gastrocnemius metabolites that differed markedly between the strains after a long term HFD and one hour swim
191
4.51 Pathway analysis results from the gastrocnemius IMs obtained after the MT knockouts were compared to the WT
191
4.52 Important hepatic metabolites that differed markedly between the strains after a long term HFD and one hour swim
196
4.53 Pathway analysis results from the liver IMs obtained after the MT knockouts were compared to the WT
197
4.54 Important brain metabolites that differed markedly between the strains after a long term HFD and one hour swim
200
4.55 Pathway analysis results from the brain IMs obtained after the MT knockouts were compared to the WT
201
