Chapter - DRO - Deakin University

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Chapter - DRO - Deakin University
IDENTIFICATION AND CHARACTERISATION OF
NOVEL GENES INVOLVED IN SKELETAL MUSCLE
HYPERTROPHY
Kate A. Carey
B. Appl. Sci. (Hons)
A thesis presented in fulfilment of the Degree of Doctor of Philosophy
Supervisor: Dr. David Cameron-Smith
December 2004
School of Exercise and Nutrition Sciences
Faculty of Health and Behavioural Sciences
Deakin University, Melbourne
i
DEAKIN UNIVERSITY
CANDIDATE DECLARATION
I certify that the thesis entitled:
Identification and characterisation of novel genes involved in skeletal muscle
hypertrophy
submitted for the degree of:
Doctor of Philosophy
is the result of my own research, except where otherwise acknowledged, and that this
thesis in whole or in part has not been submitted for an award, including a higher
degree, to any other university or institution.
Full Name:
Kate Alison Carey
Signed ..................................................................................……………….
Date......................................................................................……………….
i
TABLE OF CONTENTS
Page
TABLE OF CONTENTS
i
DECLARATION
viii
ABSTRACT
ix
ACKNOWLEDGEMENTS
xi
PUBLICATIONS
xii
LIST OF TABLES
xiv
LIST OF FIGURES
xv
ABBREVIATIONS
xix
CHAPTER ONE – REVIEW OF THE LITERATURE
I. INTRODUCTION
1
II. CELLULAR & MOLECULAR REGULATION OF SKELETAL MUSCLE
HYPERTROPHY
2
A.
Signalling Pathways Mediating Myofibre Adaptation
2
1. Mechanotransduction & the Integrin Signalling Pathway
4
1.1 Signal Integration
B.
2. PI(3)k/Akt Signalling Pathway
5
3. MAPK Signalling Pathway
5
4. Intracellular Calcium Signalling
6
Contribution Of Satellite Cells To Muscle Adaptation
7
1. Overload Induced Activation of Satellite Cells
8
2. Proliferation & Differentiation Of Satellite Cells
11
2.1 Cell Cycle Regulation
11
2.2. Myogenic Regulatory Factors
11
3. Satellite Cell Fusion
12
4. Satellite Cell Self-Renewal
13
III. TRANSCRIPTIONAL REGULATION OF MUSCLE HYPERTROPHY
A.
4
14
Muscle Derived Growth Factors
14
1. IGF-1/MGF
14
ii
B.
2. Myostatin
15
3. HGF & FGFs
15
Expression Of Structural/Contractile/Enzymatic Genes
16
C. Myogenic Regulatory Factors
IV. PERSPECTIVES
V.
16
17
A.
cDNA Microarray Technology in Studies of Skeletal Muscle
17
B.
Primary Human Skeletal Muscle Cell Culture
18
AIMS
20
VI. HYPOTHESES
21
CHAPTER TWO – DEVELOPMENT AND VALIDATON OF THE
HUMAN SKELETAL MUSCLE SPECIFIC MICROARRAY
I. INTRODUCTION
22
II. METHODS
25
A.
Microarray Fabrication
25
B.
RNA Extraction
25
C. Indirect labelling of cDNA
26
D. Image Acquisition and Normalisation
27
III. RESULTS & DISCUSION
A.
28
Microarray Validation
28
1. Quality of cDNA clones and Microarray Printing
28
2. Homotypic Response
30
3. Repeatability and Reliability
33
3.1 Within-array Reproducibility
33
3.2. Between-Array Reproducibility
33
CHAPTER THREE – IDENTIFICATION OF NOVEL GENES IN
DIFFERENTIATING RHABDOMYOSARCOMA CELLS
I. INTRODUCTION
36
II. METHODS
38
A.
Cell Culture
38
B.
Study Design
38
C. Microarray fabrication
38
D. RNA Extraction
38
E.
39
Indirect Labelling Of cDNA And Hybridisation
iii
F.
Image Acquisition And Data Analysis
39
G. Clone Identification
39
H. Real-Time PCR Analysis
40
1. RNA Extraction
40
2. Reverse Transcription
40
3. Primer Design
40
4. Real-time PCR Reaction
40
5. PCR Efficiency
41
I.
Western Blot Analysis
41
J.
Immunocytochemistry
41
K.
Statistical Analysis
42
III. RESULTS
44
IV. DISCUSSION
53
CHAPTER FOUR – MYOGENIC AND ATROGENIC GENE
EXPRESSION IN HUMAN SKELETAL MUSCLE FOLLOWING
ACUTE RESISTANCE EXERCISE
I. INTRODUCTION
57
II. METHODS
59
A.
Subjects
59
B.
Familiarisation
59
C. Experimental Design
59
D. Muscle Biopsy Procedure
60
E.
Real-Time PCR Analysis
60
1. RNA Extraction
60
2. Reverse Transcription
60
3. Primer Design
60
4. Real-time PCR Reaction
60
5. PCR Efficiency
51
6. PCR Analysis and Endogenous Control Selection
61
Statistical Analysis
62
F.
III. RESULTS
64
A.
Cell Cycle Regulators
65
B.
Myogenic Regulatory Factors
66
C. Myostatin
67
D. Protein Degradation Pathway
68
iv
IV. DISCUSSION
69
A.
Cell Cycle Regulators
69
B.
Myogenic Regulatory Factors
70
C. Possible Roles of p21, MyoD and Myogenin
70
D. Myostatin
71
E.
72
Protein Degradation Pathway
CHAPTER FIVE – IDENTIFICATION OF NOVEL GENES
RESPONSIVE TO ACUTE RESISTANCE EXERCISE
I. INTRODUCTION
74
II. METHODS
76
A.
Subjects
76
B.
Familiarisation
76
C. Experimental Design
76
D. Muscle Biopsy Procedure
76
E.
Microarray Production
76
F.
RNA Extraction
77
G. Indirect Labelling of cDNA
77
H. Image Acquisition and Data Analysis
77
I.
Clone Identification
78
J.
Real-Time PCR Analysis
78
1. RNA Extraction
78
2. Reverse Transcription
78
3. Primer Design
78
4. Real-time PCR Reaction
79
5. PCR Efficiency
79
Statistical Analysis
79
K.
III. RESULTS
A.
81
Microarray Results
81
1. Known Skeletal Muscle Genes
83
2. Unknown cDNA Clones
84
IV. DISCUSSION
88
v
CHAPTER SIX – EXPRESSION OF NOVEL GENES DURING
THE DIFFERENTIATION OF HUMAN PRIMARY SKELETAL
MUSCLE CELLS IN CULTURE
I. INTRODUCTION
93
II. METHODS
96
A.
Materials
96
B.
Subjects
96
C. Human Primary Skeletal Muscle Cell Cultures
96
D. Experimental Conditions
97
E.
Immunocytochemistry
97
F.
Creatine Kinase Activity
98
G. Western Blot Analysis
98
H. Real-Time PCR Analysis
98
I.
1. RNA Extraction
98
2. cDNA Synthesis
98
3. Primer Design
99
4. Real-time PCR Reaction
99
5. PCR Efficiency
99
Statistical Analysis
99
III. RESULTS
101
A.
Characterisation of the Human Primary Skeletal Muscle Cell Cultures
101
B.
Assessment of Proliferation and Differentiation
103
C. Myogenic Regulatory Factor Expression
107
D. Expression of Novel Resistance Exercise Responsive Genes
109
IV. DISCUSSION
111
A.
R3IGF-1 Mediated Differentiation
111
B.
Cell Cycle Regulator and MRF Expression
112
C. Expression of Novel Myogenic Genes
113
CHAPTER SEVEN – EXPRESSION OF THE NOVEL GENES
FOLLOWING AN ACUTE BOUT OF RESISTANCE EXERCISE
I. INTRODUCTION
116
II. METHODS
118
A.
Subjects
118
B.
VO2Peak
118
vi
C. Experimental Design
118
D. Muscle Biopsy Procedure
119
E.
Real-Time PCR Analysis
119
1. RNA Extraction
119
2. Reverse Transcription
119
3. Primer Design
119
4. Real-time PCR Reaction
119
5. PCR Efficiency
119
6. PCR Analysis and Endogenous Control Selection
119
Statistical Analysis
121
F.
III. RESULTS
123
IV. DISCUSSION
127
CHAPTER EIGHT – GENERAL DISCCSION & FUTURE
DIRECTIONS
I. INTRODUCTION
129
II. SUMMARY OF MAJOR FINDINGS
130
A.
ASB5
132
B.
TXNIP
132
C. MLP
133
D. Hypothetical Protein FLJ38973
133
III. FUTURE DIRECTIONS
A.
Functional Analysis of Novel Gene Targets Using Gene Knockdown
and Over-Expression Techniques
134
1. Background
134
2. Aims
134
3. Key Methods
135
3.1 RNA Interference
135
3.1 Over-expression Studies
135
4. Significance
B.
134
136
Examination of cellular localisation and tissue distribution of selected
novel genes
136
1. Background
136
2. Aims
136
3. Key Methods
137
3.1 Fluorescence Microscopy
137
3.1 Western Blot Analysis
137
vii
4. Significance
137
C. Effects of resistance exercise training on the expression of selected
novel resistance exercise responsive genes
138
1. Background
138
2. Aims
138
3. Key Methods
138
4. Significance
138
D. Identification of novel genes demonstrating decreased expression
following acute resistance exercise
139
1. Background
139
2. Aims
139
3. Key Methods
139
3.1 Microarray data analysis
139
3.2 Sequencing
140
3.3 Bioinformatics analysis
140
3.4 Real-Time PCR analysis
140
4. Significance
E.
140
Examination of alternate pathways potentially involved in skeletal
muscle hypertrophy
140
1. Background
140
2. Suggested Targets for Further Investigation
140
IV. CONCLUSIONS
142
REFERENCES
143
APPENDIX A - Ankyrin Repeat and SOCs Box-containing 5
167
APPENDIX B - Thioredoxin Interacting Protein
170
APPENDIX C - Muscle LIM Protein
173
APPENDIX D - Hypothetical Protein FLJ38973
175
viii
DECLARATION
This thesis reports original previously unpublished studies conducted in the School of
Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia. All of the
work conducted in completion of the studies discussed in this thesis is solely the work
of the author with the following exceptions. The clone sequencing discussed in
chapter 3 and chapter 5 were performed by Reuben Klein at the Metabolic Research
Unit, Deakin University. The skeletal muscle biopsies were performed by Dr. Andrew
Garnham.
Kate A. Carey
December 2004
School of Exercise and Nutrition Sciences
Deakin University
Burwood, Australia
ix
ABSTRACT
There is mounting evidence in support of the view that skeletal muscle hypertrophy
results from the complex and coordinated interaction of numerous signalling
pathways. Well characterised components integral to skeletal muscle adaptation
include the transcriptional activity of the members of the myogenic regulatory factors,
numerous secreted peptide growth factors, and the regenerative potential of satellite
cells. Whilst studies investigating isolated components or pathways have enhanced
our current understanding of skeletal muscle hypertrophy, our knowledge of how all of
these components react in concert to a common stimulus remains limited. The broad
aim of this thesis was to identify and characterise novel genes involved in skeletal
muscle hypertrophy. We have created a customised human skeletal muscle specific
microarray which contains ~11,000 cDNA clones derived from a normalised human
skeletal muscle cDNA library as well as 270 genes with known functional roles in
human skeletal muscle. The first aspect of this thesis describes the production of the
microarray and evaluates the robustness and reproducibility of this analytical
technique.
Study one aimed to use this microarray in the identification of genes that are
differentially expressed during the forced differentiation of human rhabdomyosarcoma
cells, an in vitro model of skeletal muscle development. Firstly using this unique model
of aberrant myogenic differentiation we aimed to identify genes with previously
unidentified roles in myogenesis. Secondly, the data from this study permitted the
examination of the performance of the microarray in detecting differential gene
expression in a biological system. We identified several new genes with potential roles
in the myogenic arrest of rhabdomyosarcoma and further characterised the expression
of muscle specific genes in rhabdomyosarcoma differentiation.
In study two, the molecular responses of cell cycle regulators, muscle regulatory
factors, and atrophy related genes were mapped in response to a single bout of
resistance exercise in human skeletal muscle. We demonstrated an increased
expression of MyoD, myogenin and p21, whilst the expression of myostatin was
decreased. The results of this study contribute to the existing body of knowledge on
the molecular regulation skeletal muscle to a hypertrophic stimulus.
x
In study three, the muscle samples collected in study two were analysed using the
human skeletal muscle specific microarray for the identification of novel genes with
potential roles in the hypertrophic process. The analysis uncovered four interesting
genes (TXNIP, MLP, ASB5, FLJ 38973) that have not previously been examined in
human skeletal muscle in response to resistance exercise. The functions of these
genes and their potential roles in skeletal muscle are discussed.
In study four, the four genes identified in study three were examined in human primary
skeletal muscle cell cultures during myogenic differentiation. Human primary skeletal
muscle cells were derived from the vastus lateralis muscle of 8 healthy volunteers (6
males and 2 females). Cell cultures were differentiated using serum withdrawal and
serum withdrawal combined with IGF-1 supplementation. Markers of the cell
proliferation, cell cycle arrest and myogenic differentiation were examined to assess
the effectiveness of the differentiation stimulus. Additionally, the expressions of
TXNIP, MLP, ASB5 and FLJ 38973 measured in an attempt to characterise further
their roles in skeletal muscle. The expression of TXNIP changed markedly in response
to both differentiation stimuli, whilst the expression of the remaining genes were not
altered. Therefore it was suggested that expression of these genes might be
responsive to the mechanical strain or contraction induced by the resistance exercise.
In order to examine whether these novel genes responded specifically to resistance
type exercise, their expression was examined following a single bout of endurance
exercise. The expression of TXNIP, MLP, and FLJ 38973 remained unchanged whilst
ASB5 increased 30 min following the cessation of the exercise.
xi
ACKNOWLEDGMENTS
First and foremost, my sincerest gratitude is due to my supervisor, Dr. David
Cameron-Smith, for firstly providing the opportunity to pursue this research, but more
importantly for his enthusiastic encouragement, support and invaluable advice. I would
also like to thank Professor Greg Collier, Dr. David Segal and the team from the
Metabolic Research Unit at Deakin University for the resources and tireless assistance
necessary for the development of the microarray and analysis undertaken. Special
thanks go to Janelle Mollica, Reuben Klein, Andrew Sanagorski, Mary Malakellis for
their outstanding technical assistance.
Thank you to Dr. Andrew Garnham for his excellent medical assistance during trials
and to all those people who gave their time to take part in these studies – this work
would not have been possible without your willing participation.
Thanks to everyone in the Exercise Muscle and Metabolism Unit who has assisted in
various aspects of my research and has contributed to a thoroughly enjoyable work
environment.
I also wish to record to sincere appreciation to my family for their unwavering love and
continuing support. Above all, I tender my heartfelt love and thanks to my husband
Peter for his love and care. I deeply appreciate his encouragement and support and
he has been, and remains, a profound source of inspiration in my life.
Melbourne, December 2004
Kate Carey
xii
PUBLICATIONS
Results reported in this thesis have been submitted for publication as follows:
Manuscripts in review or preparation:
Carey, KA, Segal, D, Klein, R, Sanigorski, A, Walder, K, Collier, GR, Cameron-Smith,
D. Identification of novel myogenic differentiation related genes in rhabdomyosarcoma
cells using cDNA microarrays.
Carey, KA, Segal, D, Hargreaves, M, Snow, R. Walder, K, Collier, GR, CameronSmith. Myogenic and atrogenic gene expression in human skeletal muscle following
acute resistance.
Carey, KA, Segal, D, Klein, R, Sanigorski, A, Walder, K, Collier, GR, Cameron-Smith,
D. Identification of novel skeletal muscle genes following an acute bout of resistance
exercise using cDNA microarrays.
Publications from collaborative studies conducted during PhD candidature:
Mahoney, DJ, Carey, KA, Fu, MH, Snow, R, Cameron-Smith, D, Parise, G, and
Tarnopolsky, MA. Real-time RT-PCR analysis of housekeeping genes in human
skeletal muscle following acute exercise. Physiol Genom 18: 226-231, 2004.
Spriet LL, Tunstall RJ, Watt MJ, Mehan KA, Hargreaves M, Cameron-Smith D.
Pyruvate dehydrogenase activation and kinase expression inhuman skeletal muscle
during fasting. J App Physiol 96(6): 2082-2087, 2004.
Campbell SE, Mehan KA, Tunstall RJ, Febbraio MA, Cameron-Smith D. 17betaestradiol upregulates the expression of peroxisome proliferator-activated receptor
alpha and lipid oxidative genes in skeletal muscle. J Mol Endo 31(1): 37-45, 2003.
Murphy RM, Tunstall RJ, Mehan KA, Cameron-Smith D, McKenna MJ, Spriet LL,
Hargreaves M, Snow RJ. Human skeletal muscle creatine transporter mRNA and
xiii
protein expression in healthy, young males and females. Mol Cell Biochem 244(1-2):
151-157, 2003.
Tunstall RJ, Mehan KA, Wadley GD, Collier GR, Bonen A, Hargreaves M, CameronSmith D. Exercise training increases lipid metabolism gene expression in human
skeletal muscle. Am J Physiol Endocrinol Metab 283(1): E66-E72, 2002
Tunstall RJ, Mehan KA, Hargreaves M, Spriet LL, Cameron-Smith D. Fasting
activates the gene expression of UCP3 independent of genes necessary for lipid
transport and oxidation in skeletal muscle. Biochem Biophys Res Comm 294(2): 301308, 2002
xiv
LIST OF TABLES
Table
Page
3.1
Real-Time PCR Primer Details
43
3.2
List of genes identified following clone sequencing
48
4.1
Real-Time PCR Primer Details
63
5.1
Real-Time PCR Primer Details
80
5.2
List of genes with increased mRNA abundance in response to an
acute bout of resistance exercise. The mRNA expression for each
gene derived from the microarray analysis is presented as fold
change from the resting (pre) value.
83
5.3
List of genes with decreased mRNA abundance in response to an
acute bout of resistance exercise. The mRNA expression for each
gene derived from the microarray analysis is presented as fold
change from the resting (pre) value.
84
5.4
List of genes identified using microarray analysis with increased
mRNA abundance in response to an acute bout of resistance
exercise. The mRNA expression for each gene derived from the
microarray analysis is presented as fold change from the resting
(pre) value.
85
6.1
Real-Time PCR Primer Details
100
7.1
Real-Time PCR Primer Details
122
xv
LIST OF FIGURES
Figure
Page
1.1
Overview of the main events during resistance exercise leading to skeletal
muscle hypertrophy. (1) Muscular overload is detected by the muscle
through numerous perturbations in the cellular environment. Via receptor
binding and other cellular signals, a network of signal transduction
pathways (2) results in the activation of transcription factors. Active nuclear
transcription factors alter the expression of numerous genes (3) which
ultimately result in increased synthesis and assembly of myofibrillar
proteins (4). Simultaneously, growth factors, cytokines released from
injured cells, and other unknown mechanisms mediate the activation of
satellite cells (5). The activated satellite cells subsequently proliferate,
differentiate and then fuse to existing myofibres to promote muscle repair
and enlargement via increased production of myofibrillar proteins (6).
3
1.2
Overview of overload induced myotrauma and satellite cell activation. (A)
Myofibre damage occurs. (B) inflammatory response releases cytokines
and muscle derived growth factors which in turn activate satellite cells to
(C) proliferate, differentiate and fuse to existing myofibres, resulting in (D)
myofibre hypertrophy.
10
2.1
Overview of microarray production and analysis. Initially selected cDNA
clones are PCR amplified, purified and then spotted onto glass sides by
microarray printing robots. RNA from samples of interest and a reference
are extracted, reverse transcribed and are labelled with Cy3 (usually red)
and Cy5 (usually green) fluorescent dyes. The two samples are then
combined and competitively hybridised to the prepared microarray slides.
Laser excitation of the incorporated fluorescent dyes yields an emission
with a characteristic spectrum, which is measured using a scanning
confocal laser microscope. Thus from the fluorescence intensities and
colours from each spot, the relative expression of that particular RNA
species in the experimental sample can be estimated.
23
2.2
Representative agarose gel of amplified clones. PCR amplified cDNA
clones were run on a 1% agarose gel to verify amplification and the
presence of a single product.
29
2.3
A representative section of a SYBRGold stained microarray slide.
Representative microarrays from each manufactured batch were stained for
DNA using SYBRGold. The resulting image demonstrated a high degree of
DNA retention on the surface of the array, good spot morphology and a
uniform printing pattern.
29
2.4
A false colour image of the muscle:muscle hybridisation (A) and an
enlarged view of a single 20 × 20 grid (B). The array consists of PCRamplified random cDNA clones spotted onto a glass slide. Equal quantities
of skeletal muscle RNA was labelled with Cy3 and Cy5 fluorophores and
competitively hybridised to the array. Yellow dots represent genes that
show no difference in expression between the two sample RNAs.
31
2.5
Homotypic Hybridisations. (A) Scatter plot of the calibrated Cy5 versus Cy3
fluorescence response from a skeletal muscle/skeletal muscle
hybridisation. Virtually all gene elements lie close to the diagonal line
corresponding to the theoretical differential expression ratio of 1. (B) Data
points from the homotypic hybridisations were used to construct a
histogram, which shows the distribution of gene elements around the
expected log ratio of 0.0.
32
xvi
2.6
Hierarchical clustering dendrogram of six identical hybridisations, two
conducted on one day (repeat 1a and 1b), two conducted one week later
(repeat 2a and 2b) and two conducted 4 weeks later. The closest
correlations are indicated by low branches on the dendrogram. The overall
high correlation (top branch on the dendrogram) across the six arrays
indicated very good reproducibility of the microarray.
34
3.1
Western blot analysis of MHC protein expression over 10 days of
differentiation with TPA containing medium. A representative blot from one
replicate experiment is shown above the histogram. The order of samples
on the blot corresponds with the order of bars in the histogram below. The
cell extracts were electrophoresed through a 12% SDS-polyacrylamide gel,
transferred to nitrocellulose membranes and probed with the myosin
antibody (MY-35). The density of the bands was analysed using Kodak 1D
3.5 image analysis software and the average of three independent replicate
experiments is presented.
44
3.2
Immunofluorescence analysis of RMS cells over the 10 days of TPA
induced differentiation. Cells were reacted to the MHC antibody MY-35
(green). Nuclei were counterstained using the DNA binding dye
Bisbenzimide Hoechst 33285 (blue). (A), Control; (B), Day 1; (C), Day 3;
(D), Day 6; (E), Day 8; (F), Day10. Bar represents 100µM.
45
3.3
Hierarchical clustering analysis of expression profiles. Hierarchical
clustering was used to group genes based on their expression profiles.
Each gene element is represented on the vertical axis, and the time points
are shown on the horizontal axis. The expression ratios for each gene at
each time point are colour coded: red indicates increased expression while
green indicated reduced expression relative to the reference expression
level. Two distinct clusters are evident, an up regulated pattern of
expression (highlighted in blue) and a down regulated pattern of
expression. The averages of three independent replicate experiments are
presented.
47
3.4
Microarray expression profiles of selected differentially expressed genes.
Each bar represents the mean ± SEM of three independent, replicate
experiments.
49
3.5
Real-time PCR validation of the genes identified from the microarray
analysis. Data is presented as arbitrary units normalized to the control
value. Bars show the mean ± SEM of six replicate experiments.
51
3.6
Expression of the myogenic basic helix-loop-helix transcription factors.
A. mRNA expression of the MRFs over 10 days of differentiation. Data is
presented as arbitrary units normalized to the control value. Bars show the
mean ± SEM of six replicate experiments.
B. Western blot analysis of myogenin protein expression over 10 days of
differentiation. A representative blot from one replicate experiment is shown
above the histogram. The order of samples on the blot corresponds with
the order of bars in the histogram below. The cell extracts were
electrophoresed through a 12% SDS-polyacrylamide gel, transferred to
nitrocellulose membranes and probed with the myogenin antibody (F5D).
The average of three independent replicate experiments is presented.
52
4.1
Examination of the mRNA expression of the endogenous control β-actin
following an acute bout of resistance exercise. Statistical analysis revealed
no change in the expression of this gene at any time point following the
exercise intervention. Therefore, this was considered an appropriate
endogenous control for this study.
62
4.2
Average concentric (white bars) and eccentric (black bars) torque across
the three exercise sets. The data represented is the average of 12
contractions from 10 subjects, ± SEM.
64
xvii
4.3
The effects of a single bout of heavy resistance exercise on the expression
of cell cycle regulatory factors. Real-time PCR analysis was performed on,
Cyclin D1, PCNA, p21, and p27. Values are means ± SEM.
65
4.4
The effects of a single bout of heavy resistance exercise on the expression
of the Muscle Regulatory Factors. Real-time PCR analysis was performed
on, Myf5, MyoD, myogenin, and Myf6. Values are means ± SEM.
66
4.5
The effects of a single bout of heavy resistance exercise on the expression
of myostatin mRNA. Values are means ± SEM.
67
4.6
The effects of a single bout of heavy resistance exercise on the expression
of atrogin-1 and MuRF-1 mRNA. Values are means ± SEM.
68
5.1
3 × 2 self organising map representation of the patterns of gene expression
observed following a single bout of endurance exercise. Subjects
completed an acute bout of resistance exercise consisting of 3 sets of 12
repetitions of maximal leg extension. Biopsies were taken before exercise
(pre), at 30 min, 4 h, and 24 h post exercise. Self organising map was used
to group genes based on their expression profiles. Each gene element is
represented vertically, and the time points are shown horizontally. The
expression ratios for each gene at each time point are colour coded: red,
increased expression compared to reference RNA; green reduced
expression compared to reference RNA.
82
5.2
Real-time PCR results for selected genes. Subjects completed an acute
bout of resistance exercise consisting of 3 sets of 12 repetitions of maximal
leg extension. Biopsies were taken before exercise (pre), at 30 min, 4 h,
and 24 h post exercise. Bars represent mean ± SEM, average of 10
subjects.
87
6.1
Differentiation of primary human skeletal muscle cell lines. The
differentiation potential of our cell lines was examined using
immunocytochemical staining of MHC protein in proliferating cells (A) and
following 7 days of serum withdrawal mediated differentiation (B). Cells
were reacted to the MHC antibody MY-35 (green). Nuclei were
counterstained using the DNA binding dye Bisbenzimide Hoechst 33285
(blue).
102
6.2
mRNA expression analysis of markers of proliferation (PCNA), cell cycle
arrest (p21, Myostatin) and differentiation (MHC IIx, MHC I, CKM) during
serum withdrawal (DM; solid bars) or serum withdrawal combined with
30ng/ml R3IGF-1 (DM+IGF-1;white bars). Each bar represents the mean ±
SEM of eight independent, replicate experiments.
104
6.3
CK activity increases with time in differentiating conditions. Human primary
skeletal myoblasts were differentiated with serum withdrawal (DM) or
serum withdrawal combined with 30ng/ml R3IGF-1 (DM+IGF-1). CK assay
was performed on cell lysates and is expressed as mU/mg of total protein
normalised to the 0h time-point. The average of eight independent primary
cell cultures is presented, ± SEM.
105
6.4
Western blot analysis of MHC protein expression over time in differentiating
conditions. The cell extracts were electrophoresed through a 6% SDSpolyacrylamide gel, transferred to nitrocellulose membranes and reacted to
the myosin antibody (MY-35). (A) MHC expression analysed using
densitometry. The average of four independent primary cell culture
experiments is presented (B) Representative blots from DM and DM+IGF-1
treated cells.
106
6.5
mRNA expression analysis of the myogenic regulatory factors (MyoD,
Myf5, myogenin, Myf6) during serum withdrawal (DM; solid bars) or serum
withdrawal combined with 30ng/ml R3IGF-1 (DM+IGF-1;white bars). Each
108
xviii
bar represents the mean ± SEM of eight independent, replicate
experiments.
6.6
mRNA expression analysis of the FLJ38973, ASB5, MLP, and TXNIP
during serum withdrawal (DM; solid bars) or serum withdrawal combined
with 30ng/ml R3IGF-1 (DM+IGF-1;white bars). Each bar represents the
mean ± SEM of eight independent, replicate experiments.
110
7.1
Examination of the mRNA expression of the endogenous control β-actin (A)
and cyclophilin (B) following an acute bout of resistance exercise.
Statistical analysis revealed no change in the expression of this gene at
any time point following the exercise intervention. Therefore, this was
considered an appropriate endogenous control for this study.
120
7.2
The effects of a single of bout of endurance exercise on the expression of
resistance exercise sensitive genes. Real-time PCR analysis was
performed on, TXNIP, MLP, ASB5 and FLJ38973. Values are means ±
SEM of 8 subjects.
124
7.3
The effects of a single of bout of endurance exercise on the expression of
the Muscle Regulatory Factors. Real-time PCR analysis was performed on,
Myf5, MyoD, myogenin, and Myf6. Values are means ± SEM of 8 subjects.
125
7.4
The effects of a single bout of endurance exercise on the expression of
PDK4. Values are means ± SEM of 8 subjects.
126
xix
ABBREVIATIONS
ANOVA
analysis of variance
ASB5
ankyrin repeat and SOCs box-containing 5
ATP5I
ATP synthase, H+ transporting mitochondrial F0 complex, subunit E
bFGF
basic fibroblast growth factor
BSA
bovine serum albumin
°C
degrees Celsius
CCT7
chaperonin containing t polypeptide 1 eta
Cdk
cyclin dependent kinase
cDNA
complementary deoxyribonucleic acid
CK
creatine kinase
CKM
creatine kinase muscle
COX6B
cytochrome c oxidase subunit VIb
COX7c
cytochrome c oxidase subunits VIIc
Ct
critical threshold
CV
coefficient of variation
DLAT
dihydroliopoamide S-acetyltransferase
DM
differentiation medium
DMSO
dimethyl sulfoxide
DNA
deoxyribonucleic acid
DTT
dithiothreitol
E
efficiency
EDTA
ethylenediamine tetraacetic acid
ERK
extracellular signal-related kinase
EST
express sequence tags
FAC
focal adhesion complex
FAK
focal adhesion kinase
FBS
foetal bovine serum
GOT2
glutamate oxaloacetate transaminase 2
GSK-3β
glycogen synthase kinase-3β
h
hour
HCL
hydrogen chloride
HDAC
histone deacetylase complex
HEPES
N-2-hydroxyethylpiperazine-N’-2-ethanesulfonic acid
xx
HNRPH1
heterogeneous nuclear ribonucleoproteins H1
HSP27
heat shock protein 27 kDa
HSP40
heat shock protein 40 kDa
IGF-1
insulin like growth factor 1
IgG
immunoglobulin G
IL-6
interlukin-6
KCL
potassium chloride
kDa
kilodalton
kg
kilograms
LIF
leukaemia inhibitory factor
M
mole
MAPK
mitogen-activated kinase
MEM
minimum essential medium
MgCl2
magnesium chloride
MGF
mechano growth factor
MHC
myosin heavy chain
min
minute
ml
millilitre
MLP
muscle LIM protein
MRF
myogenic regulatory factor
mRNA
messenger ribonucleic acid
MuRF-1
muscle ring finger protein 1
MVC
maximal voluntary contraction
MYL1
myosin light chain 1
MYL2
myosin light chain 2
NFΚB1
nuclear factor kappa-B, subunit 1
Nm
newton meters
PBS
phosphate buffered saline
PCNA
proliferating cell nuclear antigen
PCR
polymerase chain reaction
PDK4
pyruvate dehydrogenase kinase isoenzyme 4
PGC-1
peroxisome proliferators-activated receptor-gamma, coactivator 1
PI3k
phosphatidlinositol-3 kinase
PTMA
prothymosin alpha
R3IGF-1
IGF-1 analogue LongTMR3IGF-1
Rb
retinoblastoma
RMS
rhabdomyosarcoma
RNA
ribonucleic acid
xxi
RNAi
RNA interference
rpm
revolutions per minute
RT
reverse transcription
SDS
sodium dodecyl sulfate
SDS-PAGE
sodium dodecyl sulphate-polyacrylamide gel electrophoresis
sec
second
SEM
standard error of the mean
siRNA
small inhibitory RNA
SNAP 29
synaptosomal-associated protein 29 kDa
STAT3
signal transducer and activator of transcription 3
TBST
tris buffered saline plus tween
TGF-β
transforming growth factor-β
Tim10
translocase of inner mitochondrial membrane
TPA
12-O-tetradecanoylphorbol-13-acetate
TTS2.2
transport secretion protein 2.2
TXNIP
thioredoxin interacting protein
UQCRC2
ubiquinol-cytochrome c reductase core protein II
VEGF
vascular endothelial growth factor
VO2
oxygen consumption
VO2 peak
peak oxygen consumption
1
CHAPTER ONE
REVIEW OF THE LITERATURE
I. INTRODUCTION
Skeletal muscle comprises 50-60% of total body mass and is one of the major tissues
involved in regulating metabolism, locomotion and strength. Skeletal muscle mass and
contractile characteristics are readily modified by increased loading (e.g. resistance
exercise). Similarly, conditions of disuse (e.g. bed rest, microgravity), starvation,
aging, and some disease states (e.g. cancer cachexia, AIDS) results in protein
breakdown and considerable skeletal muscle atrophy. Significant loss of muscle mass
results in numerous deleterious consequences including muscle weakness and frailty,
increased risk of falls and associated morbidity, reduction in or prevention of
ambulation, and in severe cases, mortality. Recent developments in molecular biology
have begun to provide some insights into the subtle interactions and complex events
which control these adaptations. Understanding the fundamental mechanisms
underlying hypertrophy has the potential to provide new therapies to treat muscle
disease. Importantly, the molecules and signalling pathways that induce hypertrophy
might be manipulated or mimicked to directly arrest the atrophic process, or indeed
augment the growth of skeletal muscle in these populations. In this review, current
understandings of the cellular and molecular mechanisms of skeletal muscle
hypertrophy are presented.
2
II. CELLULAR & MOLECULAR REGULATION OF
SKELETAL MUSCLE HYPERTROPHY
Skeletal muscle hypertrophy results from a set of complex and highly orchestrated
signalling events which result in increased protein synthesis and the addition of new
contractile filaments to pre-existing fibres, ultimately enabling greater force production.
It has become evident that there are two primary processes mediating hypertrophy.
The first is increased protein synthesis within the myofibre leading to appropriate
cellular adaptations. The second involves the proliferation, differentiation and fusion of
satellite cells, providing additional myonuclei for the enlarging fibre. Equally as
important are the many critical mechanisms by which the cell senses increased
loading and transduces this information into intracellular adaptations (Figure 1.1).
A. Signalling Pathways Mediating Myofibre Adaptation
Strenuous, growth-inducing muscle activity is associated with changes in one or more
variables including myofibre integrity or damage, calcium concentrations, energy
demand, growth factors and cytokines, intramuscular temperature and oxygen
concentrations, as well as mechanical stretch and contraction of the muscle itself
(Rennie et al. 2004). Alterations of an appropriate magnitude in these variables have
the capacity to activate numerous parallel signalling pathways. The involvement of
these signalling pathways in the sensation and transduction of cellular environmental
stimuli is widely recognised as critical in the activation of specific gene expression and
cellular reprogramming (Martineau and Gardiner 2001; Nader and Esser 2001).
Several signalling pathways involving cytoplasmic protein kinases and nuclear
encoded transcription factors have been identified as possible master regulators of
skeletal muscle adaptation. These pathways encompass both the sensing of
mechanical and environmental perturbations as well as the transduction of these
signals into intracellular responses.
3
1
GROWTH FACTORS
CONTRACTION
& STRETCH
MUSCLE DAMAGE
&
IMMUNE RESPONSE
- Cytokines
Integrin Signalling
2
Ca2+
Hypoxia
Transcription Factors
4
3
Transcriptional Induction
Production and assembly of
myofibrillar proteins
6
Satellite cell differentiation
and fusion to the myofibre
Satellite Cell
5
Figure 1.1. Overview of the main events during resistance exercise leading to
skeletal muscle hypertrophy. (1) Muscular overload is detected by the muscle
through numerous perturbations in the cellular environment. Via receptor binding
and other cellular signals, a network of signal transduction pathways (2) results in
the activation of transcription factors. Active nuclear transcription factors alter the
expression of numerous genes (3) which ultimately result in increased synthesis
and assembly of myofibrillar proteins (4). Simultaneously, growth factors,
cytokines released from injured cells, and other unknown mechanisms mediate
the activation of satellite cells (5). The activated satellite cells subsequently
proliferate, differentiate and then fuse to existing myofibres to promote muscle
repair and enlargement via increased production of myofibrillar proteins (6).
4
1. Mechanotransduction & the Integrin Signalling Pathway
Mechanotransduction is the mechanism by which mechanical stress initiates
intracellular signalling. Striated muscle cells are particularly responsive to mechanical
stress as evidenced by the fact that cellular size is in large part dictated by physical
forces. A fundamental unanswered question concerns how skeletal muscle cells
sense mechanical loading and transduce this information into cellular level
adaptations.
One potential candidate for influencing load-induced changes in skeletal muscle
protein synthesis through the regulation of gene transcription is the integrin-mediated
signalling pathway. Initially, integrins were considered solely as membrane-associated
proteins necessary for maintaining adhesive interactions with the extracellular matrix,
cell growth and cell motility (Carson and Wei 2000). More recently however, it is
believed that integrins constitute a critical component of the signalling pathways by
which the cell integrates physical or mechanical signals from the surrounding
environment (Carson and Wei 2000). Activation of cellular signalling through
extracellular matrix-integrin interactions initially occurs by the formation of focal
adhesion complexes (FACs). Within the FACs, signalling proteins are brought into
close proximity - thereby facilitating signal transduction.
Importantly, the formation of FACs appears sensitive to mechanical forces. The focal
adhesion protein focal adhesion kinase (FAK) is activated by the mechanical stretch of
muscle and both FAK and paxillin (a down-stream target of FAK) protein
concentrations are increased in hypertrophied skeletal muscle (Flück et al. 1999;
Gordon et al. 2001). Equally, the expression of a down stream effector molecule of
integrins, RhoA, is increased following functional overload and during the recovery
from disuse atrophy (McClung et al. 2003; McClung et al. 2004). Indeed, RhoA can
regulate the expression of the muscle specific transcription factors, MyoD and
myogenin and is critical for skeletal muscle differentiation (Carnac et al. 1998; Takano
et al. 1998; Wei et al. 1998).
1.1. Signal Integration
Whilst integrins may be important for transducing mechanical stimuli into cellular level
signalling, there is some suggestion that integrins may also be excellent candidates
for integrating many of the signalling cascades activated during hypertrophy (Carson
and Wei 2000). Muscle overload and contraction alter innumerable variables which, in
turn activate many signalling pathways simultaneously. It appears to be that the
combinatorial activation of these signal transduction pathways as well as the relative
5
magnitude of the signals ultimately result in the specific adaptations of the cell.
Integrins may provide a mechanism by which all of these signalling pathways work
together to give a unified response resulting in appropriate cellular adaptations.
Signalling pathways that have been shown to be connected to integrin signalling
include phosphatidylinositol-3 kinase (P13k), mitogen-activated protein kinase
(MAPK), and calcium signalling pathways (Clarke and Brugge 1995; Goel and Dey
2002; Zhang et al. 2003; Kim et al. 2004; Velling et al. 2004).
2. PI(3)k/Akt Signalling Pathway
Numerous studies have identified critical roles for the PI3k/Akt pathway in modulating
the intracellular response to resistance exercise. Most notably, the growth factor
insulin-like growth factor I (IGF-1), a powerful stimulator of muscle hypertrophy
(Vandenburgh et al. 1991; Coleman et al. 1995), has recently been shown to act via
the PI3k/Akt signalling pathway (Bodine et al. 2001b; Rommel et al. 2001). IGF-1
binding to the IGF-1 receptor stimulates a cascade of events which ultimately result in
the activation of P13k and further downstream, Akt. Akt in turn phosphorylates an ever
increasing set of substrates amongst which are proteins that induce protein synthesis,
block apoptosis, activate cell proliferation, and mediate gene transcription, steps
essential for the development of skeletal muscle hypertrophy (Glass 2003; Matsui et
al. 2003). Targeted activation of PI3k has been shown to induce skeletal muscle
hypertrophy (Murgia et al. 2000). Indeed, pharmacological inhibition of PI3k is
sufficient to block IGF-1 stimulated hypertrophy (Rommel et al. 1999). Equally, the
over-expression of a constitutively active form of Akt plays critical roles in both the
promotion of muscle hypertrophy and the inhibition of muscle atrophy in vivo (Bodine
et al. 2001b). Furthermore, specific inhibition of mTOR, a downstream target of Akt,
with rapamycin leads to a 95% inhibition of hypertrophy. Conversely, another
downstream target of Akt, glycogen synthase kinase-3β (GSK-3β) appears to be a
negative regulator of skeletal muscle hypertrophy. GSK-3β phosporylation and
inactivation by Akt has been observed during hypertrophy in animals (Bodine et al.
2001b) and in culture (Rommel et al. 2001; Vyas et al. 2002). Collectively, these
studies identify a crucial role for the P13k-Akt signalling pathway in regulating the
development of skeletal muscle hypertrophy.
3. MAPK Signalling Pathway
The involvement of the MAPK cascades in mechanically induced signalling from the
cytosol to the nucleus is receiving increasing attention. This function is compatible with
the well known role of the MAPKs as points of convergence for various signalling
cascades regulating gene expression (Martineau and Gardiner 2001). The MAPK
superfamily can be separated into distinct parallel pathways including the extracellular
6
signal-related kinase (ERK) 1/2, the stress activated protein kinase cascades
(SAPK1/JNK and SAPK2/p38) and ERK5. Cellular stresses can elicit signal
transduction of the MAPK signalling pathways through protein phosphorylation on
serine, threonine, and tyrosine residues. Many factors associated with exercise,
including growth factors and their cell surface receptors, cytokines, hypoxia, changes
in intracellular calcium and mechanical stresses have been shown to stimulate MAPK
signal cascades (Widegren et al. 2001). Thus MAPK signal cascades are a likely
candidate system that may convert the mechanical and biochemical stimuli associated
with muscle contraction into appropriate intracellular responses (Widegren et al.
2001). Importantly, recent evidence suggests that exercise and muscle contraction
can induce phosphorylation and activation of components of the ERK, JNK and p38
MAPK cascades in both human and rat skeletal muscle (Aronson et al. 1997a;
Aronson et al. 1997b; Aronson et al. 1998; Boppart et al. 1999; Boppart et al. 2000;
Osman et al. 2000; Ryder et al. 2000; Wretman et al. 2000; Carlson et al. 2001;
Martineau and Gardiner 2001; Thompson et al. 2003). Furthermore, several of these
studies (Aronson et al. 1997a; Aronson et al. 1998) demonstrated a rapid and
concurrent induction of c-jun and c-fos mRNA levels, early response genes which
have been implicated in the activation of genetic events leading to the differential
regulation of muscle specific genes (Williams and Neufer 1996). Thus muscular
contraction activates MAPK signalling cascades that ultimately lead to the activation of
different transcription factors responsible for initiating muscle specific gene and protein
expression.
4. Intracellular Calcium Signalling
Changes in intracellular calcium regulate many important cellular processes, including
motility, neurotransmitter release, proliferation and gene expression (Bading et al.
1997). Calcium has been shown to regulate gene expression via multiple signalling
pathways by activating calcium sensitive kinases such as calmodulin kinases, and
mitogen-activated protein kinases. Although the essential role of intracellular calcium
concentrations in the regulation of skeletal muscle contraction has been established,
its role in the regulation of muscle growth is less well understood.
Changes in intracellular calcium have been implicated in regulating diverse processes
in skeletal muscle, including differentiation, hypertrophy and fibre type determination.
The calcium/calmodulin-dependant protein phosphatase, calcineurin plays an
important role in mediating downstream calcium-dependant signalling. Calcineurin is a
serine/threonine phosphatase that is activated in response to sustained increases in
intracellular calcium (Dolmetsch et al. 1997). In skeletal muscle, calcineurin activation
has been shown to be necessary for hypertrophic growth in response to insulin-like
7
growth factor-1 (Musarò et al. 1999), or during compensatory overload (Dunn et al.
1999). Considerable controversy exists however as to the relative importance of
calcineurin in this process. Whereas some groups have reported that cyclosporin A,
an inhibitor of calcineurin, blocks hypertrophy (Dunn et al. 1999), others have seen no
effect (Bodine et al. 2001b; Musarò et al. 2001; Rommel et al. 2001; DupontVersteegden et al. 2002). Calcineurin dependant pathways have also been implicated
in myoblast differentiation (Delling et al. 2000; Friday et al. 2000) through the
activation of MyoD and MEF2 (Friday et al. 2003) as well as skeletal muscle
regeneration (Sakuma et al. 2003). More recently, the hypothesised roles of
calcineurin have been extended to include the regulation of skeletal muscle fibre type
switching (Mitchell et al. 2002; Parsons et al. 2004). Indeed, calcineurin has been
shown to selectively activate the expression of the slow MHC isoform (Delling et al.
2000).
B. Contribution of Satellite Cells to Muscle Adaptation
Each myonucleus controls the production of mRNA and proteins over a finite volume
of cytoplasm, known as the myonuclear domain. mRNA encoding proteins do not
freely mix along the fibre length but remain concentrated around their myonuclei of
origin (Hall and Ralston 1989; Pavlath et al. 1989). Therefore, any increase in the size
of a muscle fibre, in response to increased mechanical load for example, would
necessitate the incorporation of additional myonuclei (Yan 2000). Yet, mature
myofibres within adult skeletal muscle are terminally differentiated and therefore
incapable of mitotic division to produce additional myonuclei in times of increased
protein synthesis and muscle growth. Satellite cells, myogenic precursor cells located
between the basal lamina and sarcolemma of multinucleated myofibres, provide the
additional pool of myonuclei necessary for muscle growth (Hawke and Garry 2001). In
normal mature fibres, satellite cells are quiescent. Rates of RNA and protein synthesis
are low but the cell retains the ability to divide. Upon activation, they re-enter the cell
cycle, proliferate, and differentiate to form myofibres by fusing with themselves or
existing fibres (Hawke and Garry 2001).
There is very strong evidence to suggest that skeletal muscle remodelling and
regeneration is dependent, to a large extent upon the activity of satellite cells
(Rosenblatt and Parry 1992; Rosenblatt and Parry 1993). Such that, upon mild γradiation induced inhibition of satellite cell proliferation, overload induced hypertrophy
was obliterated (Rosenblatt and Parry 1992; Rosenblatt and Parry 1993). The exact
contribution of satellite cells to the hypertrophic response remains unclear however, as
8
the induction of hypertrophy has been observed despite the elimination of satellite cell
activity (Lowe and Alway 1999). Similarly, studies have reported an enlargement of
myofibre size before an increase in satellite derived myonuclear number had occurred
(Allen et al. 1995a; Roy et al. 1999). Collectively, these observations indicate that
although the activity of satellite cells are an integral component of skeletal muscle
hypertrophy, existing myonuclei must also act in concert with satellite cells to regulate
the adaptation of the entire myofibre.
Mechanical loading, has been shown to induce augmented activation and proliferation
of satellite cells in the muscle of humans (Kadi and Thornell 2000; Crameri et al. 2004;
Kadi et al. 2004b) and adult rats (Darr and Schultz 1987; Rosenblatt et al. 1994; Smith
et al. 2001). Increased myonuclei numbers have been reported in high-level
resistance trained subjects as the result of years of intensive training (Kadi et al. 1999)
and more recently in response to 10 weeks of strength training in women (Kadi and
Thornell 2000). Since the importance of satellite cells to the remodelling and
regenerative potential of skeletal muscle was described, much research has focused
on understanding the molecular and cellular mechanisms regulating their functions in
muscle.
1. Overload Induced Activation of Satellite Cells
In mature muscle, satellite cells are normally quiescent and require appropriate
signals to become activated, proliferate and differentiate as required. As mentioned
previously, resistance exercise has the capacity to generate numerous, parallel
signalling pathways within skeletal muscle that ultimately result in cellular level
adaptations. A variety of extracellular signalling pathways have been found to govern
satellite cell activities, most prominently, cytokines from inflammatory cells and growth
factors released from muscle and surrounding tissues (Vierck et al. 2000). Initially,
strenuous or unaccustomed resistance exercise may result in muscle damage ranging
from micro-tears to large tears in the sarcolemma and basal lamina as well as within
the contractile proteins of the myofibre (Vierck et al. 2000). Whether muscle damage
is causally linked to the hypertrophic process remains unclear. However, eccentric
muscular contractions induce more muscle damage than concentric exercise and the
hypertrophic response is blunted when the eccentric phase is omitted from resistance
training (Hather et al. 1991).
One proposed theory suggests that resistance exercise resulting in myotrauma may
initiate the release of signalling factors that stimulate and attract immune cells to the
injury site. Cytokines from the activated immune cells, along with muscle-derived
9
growth factors, initiate a sequence of events that ultimately results in satellite cell
proliferation and differentiation (Vierck et al. 2000), see Figure 1.2.
Integral to the proliferative response are the growth factors insulin-like growth factor
(IGF-1), hepatocyte growth factor, basic fibroblast growth factor (bFGF) , transforming
growth factor β (TGF-β) and growth hormone as well as interlukin-6 (IL-6), and
leukaemia inhibitory factor (LIF) (Vierck et al. 2000). Such factors differ in their effects
on myogenesis: IL-6 and LIF only stimulate myoblast proliferation (Austin and Burgess
1991), whereas bFGF stimulates myoblast proliferation but also inhibits muscle
differentiation (Gospodarowicz et al. 1976) and TGF-β inhibits proliferation. IGF-1 is
unique amongst growth factors in that it is capable of stimulating both proliferation and
differentiation of satellite cells (Allen and Boxhorn 1987).
Although there is no general consensus on the exact contribution of cytokines and
muscle derived growth factors in overload induced hypertrophy, it is generally
accepted that some, if not all of these factors contribute to the regulation of satellite
cell activity within muscle.
10
Overload Induced Muscle Damage
Myofibre damage
A
Satellite cell
Basal Lamina
Macrophage
Immune
Response
Growth Factors
IGF-I
IGF-II
MGF
FGF
HGF
TGF-β
Satellite cell proliferation
LIF
IL-6
B
Neutrophil
&
Differentiation & Fusion of
Satellite Cells
C
Myofibre hypertrophy
D
Figure 1.2. Overview of overload induced myotrauma and satellite cell activation.
(A) Myofibre damage occurs. (B) inflammatory response releases cytokines and
muscle derived growth factors which in turn activate satellite cells to (C)
proliferate, differentiate and fuse to existing myofibres, resulting in (D) myofibre
hypertrophy.
11
2. Proliferation & Differentiation of Satellite Cells
The effective capacity for regeneration and remodelling of muscle via satellite cell
activity is remarkable considering that satellite cells constitute an estimated 2.5-6% of
myofibre nuclei (Zammit et al. 2002). Once activated, satellite cells re-enter the cell
cycle and proliferate until signalled to withdraw from the cell cycle and differentiate or
return to a state of quiescence. Much research has focused on delineating the
molecular mechanisms necessary for entire process of myogenesis including the
regulation of the satellite cell cycle, myoblast determination, differentiation and
subsequent fusion and maturation.
2.1. Cell Cycle Regulation
The decision of an activated satellite cell to progress through a new division appears
primarily regulated late in the first gap phase (G1), before the initiation of DNA
synthesis (S phase). Critical to this process is the activity of positive cell cycle
regulators, the G1 cyclins (D1, D2, D3, A and E) and the regulatory subunits for the G1
cyclin-dependant kinases (Cdks) (Cdk4, Cdk6 and Cdk2) which together, promote
progression into successive phases of the cell cycle (Sherr 1994). Conversely,
permanent cell cycle withdrawal, necessary for the terminal differentiation and
maturation of satellite cells, requires that the major positive cell cycle regulators are
inhibited. The major negative regulators comprise the Cdk-inhibitors (p21cip, p27kip,
p57kip), the product of the retinoblastoma susceptibility gene (Rb protein) and the two
related Rb family proteins p107 and p130 (Guo et al. 1995; Halevy et al. 1995; Parker
et al. 1995; Novitch et al. 1996).
Central to cell cycle regulation is the activity of the Rb protein. Active Cdk4/6-cyclin D1
phosphorylates Rb during early G1; this leads to the up-regulation of cyclin E, its
assembly with Cdk2, activation of the Cdk2-cyclin E complex and subsequent
hyperphosphorylation of Rb. Hyperphosphorylated Rb releases, and subsequently
activates the transcription factor E2F-1, allowing expression of genes necessary for
G1/S progression, and mitosis (Ishida et al. 2001). Conversely, dephosphorylation of
Rb protein by Cdk-inhibitors results in Rb binding and inactivating E2F-1, contributing
to permanent cell cycle withdrawal (Sherr and Roberts 1999; Mal et al. 2000).
2.2. Myogenic Regulatory Factors
Whilst the activity of the Cdks and Cdk-inhibitors are important in the proliferative
response in many cell types, the specification of the skeletal muscle phenotype is
dependent on the activity of the basic-loop-helix family of muscle regulatory factors
(MRFs). The MRFs comprise four members: MyoD, Myf5, myogenin and Myf6 (MRF4,
12
Herculin) that bind to specific consensus sites that are functionally important in the
transcription of muscle-specific genes. Despite potentially overlapping roles of the
MRFs, current understanding suggests specification of muscle cell fate is reliant on
the activation of the core network of myogenic regulatory factors, rather than on the
independent action of a single myogenic factor. In all known skeletal muscle lineages,
MRF expression follows essentially the same pattern. MyoD and Myf5 are expressed
in actively proliferating cells prior to differentiation, followed, at the beginning of
differentiation by increased myogenin expression (Montarras et al. 1991; Lassar et al.
1994). Lastly, Myf6 is transiently expressed during myofibre maturation (Montarras et
al. 1991).
It is well known that the MRFs are functionally important in regulating the expression
of muscle specific genes (Piette et al. 1990; Lin et al. 1991; Wentworth et al. 1991;
Muscat et al. 1992; Lassar et al. 1994; Li and Capetanaki 1994). More recently
however, it has been suggested that the MRFs (in particular MyoD) interact with cell
cycle regulators to promote cell cycle arrest and thus differentiation of myogenic cells.
MyoD is capable of inducing the expression of p21, p27, p57, and Rb (Martelli et al.
1994; Guo et al. 1995; Halevy et al. 1995; Parker et al. 1995; Reynaud et al. 2000). As
mentioned previously, the induction of these Cdk-inhibitors activate Rb protein and
contribute to permanent cell cycle arrest.
Numerous studies have indicated that cells must exit the cell cycle to terminally
differentiate. Central to the differentiation of skeletal myoblasts is myogenin, the
absence of which results in the failure of myoblasts to attain the differentiated
phenotype (Hasty et al. 1993). Myogenin, in conjunction with MyoD and the myocyte
enhancer family protein, MEF-2C subsequently regulate the late phase of myogenesis
by inducing the expression of myofibrillar and muscle specific proteins (Gu et al. 1993;
Olson and Klein 1994).
3. Satellite Cell Fusion
The last critical step in terminal differentiation of satellite cells is the fusion of the
differentiated myoblasts, either to themselves to form syncytial muscle fibres or to
existing myofibres to promote repair and/or hypertrophy. Cell-surface molecules such
as cadherins, ADAMs, EMC receptors, and the Ig superfamily molecules N-CAM and
VCAM, have all been implicated in the regulation of myoblast fusion (Mege et al. 1992;
Charlton et al. 2000; Cooper 2001; Fischer-Lougheed et al. 2001; Kang et al. 2003).
Additionally, β1 integrins have been implicated in myoblast fusion and sarcomere
incorporation (Li et al. 1999). Furthermore, the inactivation of Rho/ROCK signalling
13
and subsequent nuclear translocation of the transcription factor FKHR is required for
myoblast fusion (Bois and Grosveld 2003; Nishiyama et al. 2004).
4. Satellite Cell Self-Renewal
Central to the continued regenerative and adaptive potential of muscle is the selfrenewal of satellite cells without which recurrent demands for increased myonuclei
would rapidly deplete the satellite cell pool. Several scenarios have been proposed to
explain how the satellite cell pool is replenished. Firstly, it has been suggested that
two populations of satellite cells exist; one rapidly dividing population responsible for
the provision of myonuclei and a slowly dividing pool of ‘reserve cells’, thought
responsible for the replenishment of the quiescent satellite cell population (Rantanen
et al. 1995; Yoshida et al. 1998; Zammit et al. 2004). Alternatively, satellite cells might
represent an intrinsically homogenous pool of cells, capable of rapid proliferation and
yet able, as required, to withdraw from the differentiation program and return to
quiescence. Furthermore, renewal of the satellite cell pool may not rely exclusively on
the satellite cell compartment. Indeed, several recent studies have shown that other
cells, isolated both from muscle (side population cells) and a diverse range of tissues
(bone marrow in particular) are capable of adopting a myogenic phenotype, albeit at a
reduced frequency (Ferrari et al. 1999; Asakura et al. 2002; LaBarge and Blau 2002;
Camargo et al. 2003; Corbel et al. 2003). The relative importance of these cell types to
normal muscle repair and remodelling is unknown.
14
III. TRANSCRIPTIONAL REGULATION OF MUSCLE
HYPERTROPHY
Skeletal muscle adaptation involves the modification of cellular (myofibrils,
mitochondria etc.) and extracellular compartments (capillaries, connective tissue etc.)
such that the muscle is appropriately modified to suit its functional demands.
Alterations in the molecular components of muscle tissue during adaptation are largely
dependant on modulations in the protein make-up of the myofibres. The change in
protein content and protein constituents can potentially be controlled at many steps,
from RNA synthesis (transcription) to the synthesis of new proteins (translation) and
post translational modifications. Translational regulation has been identified as a
critical modulator of increased protein synthesis during skeletal muscle hypertrophy,
however it is beyond the scope of this review and the reader is directed to several
excellent reviews in the area (Jefferson and Kimball 2001; Nader et al. 2002; Bolster
et al. 2003). Equally, it has long been recognised that increased transcription is
essential for skeletal muscle hypertrophy (Goldberg and Goodman 1969; Sobel and
Kkaufman 1970), although the genes and regulatory mechanisms responsible are only
just beginning to be elucidated.
A. Muscle Derived Growth Factors
Changes in the availability of muscle derived growth factors appears to be a central
regulatory process in muscle hypertrophy. These factors are produced locally within
the muscle and act both in an autocrine and paracrine fashion. Muscle contraction or
damage activates signal transduction pathways, ultimately stimulating the production
of these growth factors most likely via increased transcription. In vitro, numerous
growth factors have been implicated in muscle proliferation and differentiation
including members of the FGF and TGF-β families, IGF-1, and HGF. However,
physiological functions in vivo have only been described for relatively few of these
factors, most notably IGF-1 and myostatin.
1. IGF-1/MGF
The role of IGF-1 in regulating growth and development in many tissues is widely
acknowledged. More recently, the autocrine/paracrine regulation of IGF-1 within
muscle tissue has become apparent with numerous studies identifying increased
production and release of this factor following exercise or overload (Adams et al.
15
1999; Bamman et al. 2001; Psilander et al. 2003). Moreover, an alternate splice
variant of IGF-1, called mechano-growth factor (MGF) or IGF-IEc, has been identified
as being expressed exclusively in muscle in response to contraction or stretch (Yang
et al. 1996; McKoy et al. 1999; Owino et al. 2001; Bickel et al. 2003; Hameed et al.
2003). Whilst the mechanisms by which IGF-1 and MGF promote muscle hypertrophy
are not entirely clear, it is evident that they act by signalling to both satellite cells
(promoting both proliferation and differentiation) and the mature myofibre (activating
signalling pathways and ultimately increasing protein synthesis).
1. Myostatin
Myostatin (growth/differentiation factor 8), a member of the TGB-β family (McPherron
et al. 1997) is a powerful endogenous negative regulator of muscle hypertrophy
(Sharma et al. 2001). Myostatin is synthesised and secreted as an inactive complex of
the N-terminus propeptide and active C-terminus. The latent form of myostatin
circulates bound to and inhibited by follistatin. Mature myostatin exerts its effects via
interaction with the activin/TGF-β ActIIb receptor and subsequent activation of the
Smad family to control gene transcription (Rebbapragada et al. 2003; Rios et al.
2004). Further studies have confirmed that myostatin signals satellite cell quiescence
by up-regulating p21 thus reducing the differentiation potential of satellite cells, and
subsequent capacity for hypertrophy (Carlson et al. 1999; Joulia et al. 2003). Mice,
cattle and humans with inactive or absent myostatin proteins exhibit a gross
hypermuscular phenotype (Grobet et al. 1997; Kambadur et al. 1997; McPherron and
Lee 1997; Schuelke et al. 2004). Furthermore, reductions in circulating myostatin
(Walker et al. 2004), and myostatin gene expression (Roth et al. 2003) have been
observed following resistance exercise training in humans. Collectively, these studies
suggest a model in which myostatin expression is responsive to muscle loading and
plays a key role in regulating muscles adaptation to this increased load.
1. HGF & FGFs
Both HGF and FGF family members have been described as potent regulators of
satellite cell activity (Allen et al. 1995b; Bischoff 1997; Sheehan and Allen 1999;
Yablonka-Reuveni et al. 1999), however the importance of their expression in vivo
during muscle overload is not well understood. To date only one study has
investigated the expression of these growth factors following increased muscle
loading. FGF family members, and HGF mRNAs were increased following
compensatory overload of rat plantaris muscle, suggesting prominent roles in the early
proliferative response of satellite cells during muscle adaptation (Sheehan and Allen
1999).
16
B. Expression of structural/contractile/enzymatic genes
Resistance or strength exercise, characterised by ‘low repetition, high load’ muscular
contractions, induces specific and distinct structural and functional modifications in
muscle fibres. Increases in structural and contractile proteins (e.g. desmin, troponin I)
as well as muscle specific enzymes (e.g. muscle creatine kinase) are necessary for
muscle to hypertrophy and remain functional. Numerous studies have observed
increased structural, contractile and enzymatic gene expression following acute and
chronic resistance exercise in humans as well as overload models of hypertrophy in
animals. Both acute (1 session) and chronic (12 weeks) heavy resistance exercise
results in an increased expression of myosin heavy chain isoforms, type I, type IIa
and type IIx (Willoughby and Rosene 2001; Willoughby and Nelson 2002). In rats,
compensatory overload has been associated with increased expressions of β-tubulin,
cardiac troponin T and atrial myosin light chain 1 (Carson et al. 2002). Similarly,
increased desmin and creatine kinase expression has been observed during quail
muscle hypertrophy (Lowe et al. 1998).
C. Myogenic Regulatory Factors
The altered contractile characteristics and increased myofibre size is a generally
excepted adaptation of skeletal muscle to increased loading. Importantly, research is
beginning to elucidate the molecular mechanisms required for these cellular
adaptations. The MRFs are likely candidates as regulators of this process considering
the importance of their expression during myogenesis, and because of their regulation
of the transcription of muscle specific genes including α-actin (Muscat et al. 1992),
desmin (Li and Capetanaki 1994), nicotinic Ach receptor (Piette et al. 1990), muscle
creatine kinase (Lassar et al. 1994), troponin I (Lin et al. 1991) and myosin light chain
(Wentworth et al. 1991). Load mediated increases in the expression of the MRFs have
been observed in animals models of hypertrophy (Carson and Booth 1998; Lowe et al.
1998; Lowe and Alway 1999; Adams et al. 2002; Carson et al. 2002; Haddad and
Adams 2002). Similarly, alterations in MRF expression patterns have been
demonstrated in response to resistance exercise training (Willoughby and Rosene
2003) as well as acute resistance exercise bouts (Willoughby and Nelson 2002; Bickel
et al. 2003; Psilander et al. 2003; Bamman et al. 2004; Bickel et al. 2004). Importantly,
the exact roles the MRFs play in mature muscle adaptation are yet to be established.
Whilst their temporal patterns of expression and driving roles in myogenesis have
been well described in vitro, it is yet to be determined whether these expression
patterns and functions are mimicked in vivo. Equally, the relative contributions of the
17
MRFs to adaptation within the mature myofibre compared with their roles in satellite
cell activity are yet to be fully characterised.
IV. PERSPECTIVES
Much progress has been made in recent years into understanding the molecular
mechanisms by which skeletal muscle adapts to changes in physiological stimuli.
Substantial information about the interrelationships between signalling pathways and
the impact on transcriptional and translational processes has been accrued. Similarly,
the importance of satellite cells and their mechanisms of action during skeletal muscle
hypertrophy and remodelling are being established. Nevertheless, there are
considerable gaps in our understanding. We still have no clear idea of the
commonality of, or indeed distinct nature of the pathways governing satellite cell
activity versus pathways necessary for mature myofibre adaptation. The common
thread in all of these processes is that they rely on transcriptional reprogramming.
Importantly, only a handful of genes have been isolated to date that have been shown
to be uniquely responsive to resistance exercise and increased loading. The recent
advancement in molecular biological techniques, particularly the use of highthroughput transcriptional profiling should enable the identification of previously
unknown molecules. Similarly, the use of more sophisticated in vitro tools such as
human primary skeletal muscle cell cultures provide a more physiologically revellent
model to examine novel gene expression and function.
A. cDNA Microarray Technology in Studies of Skeletal Muscle
The complete identification of coding sequences in the human genome and advances
in molecular biology have preceded the development of methods such as cDNA
microarrays which allow the investigation of the transcriptional activity of thousands of
genes or indeed the entire transcriptome simultaneously. cDNA microarrays can be
used to compare the gene expression in two different cell types or tissue samples for
example cancerous versus normal tissue. They can also be used to examine changes
in transcriptional activity over time and following any number of potential interventions.
The use of microarray technology on human skeletal muscle samples following
different exercise paradigms provides a new and exciting avenue for investigation.
Microarrays have been used to characterise gene expression patterns in skeletal
muscle in a variety of contexts including atrophy (Gomes et al. 2001; Jagoe et al.
2002; Lecker et al. 2004), treatment with thyroid hormone (Clement et al. 2002),
18
during a
hyperinsulinemic clamp (Rome et al. 2003), in disease states such as
diabetes (Yang et al. 2002; Hansen et al. 2004) and muscular dystrophy (Chen et al.
2000; Bakay et al. 2002; Noguchi et al. 2003), as well as the comparison of fast
versus slow muscle tissue (Campbell et al. 2001).
The complex nature of the molecular processes regulating skeletal muscle
development, adaptation and regeneration make it an ideal candidate for the
development of a tissue specific microarray. Microarray analysis has also been used
to examine the transcriptional response of skeletal muscle to various exercise
interventions. Barash (Barash et al. 2003) observed the up-regulation of 36 known
genes in eccentric exercised mouse muscle compared to contralateral and
isometrically exercised controls. Similarly, Carson (Carson et al. 2002) used
microarray analysis to identify 112 mRNAs differentially expressed in overload versus
control rat muscle. To date, only three studies have employed microarray technology
to examine global gene expression in skeletal muscle following exercise interventions.
Roth (Roth et al. 2002) studied the role of age, sex and strength training on human
muscle gene expression with 69 genes identified as differentially regulated by strength
training, 200 genes differentially expressed between the sexes and 50 genes
differentially expressed in relation to age. Zambon (Zambon et al. 2003) used
microarrays to determine the effects of resistance exercise on gene regulation in
biopsy samples of human quadriceps muscle obtained 6 and 18 hours after an acute
bout of isotonic exercise with one leg. Diurnal gene regulation was also profiled at the
same time points in the non-exercised leg. The results suggested that resistance
exercise may directly modulate circadian rhythms in human skeletal muscle. Finally,
Chen and colleagues (Chen et al. 2003) examined the effect of eccentric exercise on
gene expression in human skeletal muscle Volunteers performed 300 concentric
contractions with one leg and 300 eccentric contractions with the opposite leg.
Pronounced increases in inflammatory and vascular remodelling gene responses were
observed following eccentric exercise.
B. Primary Human Skeletal Muscle Cell Culture
Both primary skeletal muscle cell cultures and established muscle cell lines have
become important tools as model systems for skeletal muscle development. The
dividing myoblasts provided by these systems provide great flexibility in studies of
myogenesis as cultures are readily manipulated allowing the examination of distinct
aspects of muscle development. Although many studies have been carried out on the
19
growth and differentiation of muscle cells, the vast majority use immortalised rat and
mouse muscle cell lines. Considerable differences exist however, in the expression
profiles (James et al. 1993; McCusker and Clemmons 1998; Crown et al. 2000), and
physiological responses of these cell culture systems (Florini et al. 1991; Foulstone et
al. 2003). Human primary skeletal muscle cell cultures are a more physiologically
relevant in vitro model of adult skeletal muscle because the cells retain the
characteristics of the donor. For example, cells cultured from type 2 diabetic patients
retain their characteristic insulin resistant skeletal muscle phenotype (reduced insulinstimulated glucose uptake and glycogen synthesis) (Henry et al. 1995; Henry et al.
1996). Human primary skeletal muscle cultures have been used previously to examine
the mechanisms of type 2 diabetes (Henry et al. 1995; Henry et al. 1996; Hansen et
al. 2004), myoblast differentiation (Chazaud et al. 1998; Konig et al. 2004), the effect
of IGF-1 treatment
(Crown et al. 2000; Foulstone et al. 2003), mechanisms of
muscular dystrophy (Merickel et al. 1981), and susceptibility to malignant
hyperthermia (Girard et al. 2002).
Despite the complexity of the mechanisms governing skeletal muscle hypertrophy,
advances in powerful molecular biological tools should begin to provide considerable
insights into the regulation of this process, ultimately paving the way for the
development of interventions and treatments for the myriad of diseases affecting
skeletal muscle.
20
V. AIMS
The broad aims of the thesis are to examine the molecular regulation of skeletal
muscle hypertrophy with a focus on the identification of novel genes involved in this
process. This series of studies is critical to further elucidate the transcriptional events
that contribute to the development of skeletal muscle hypertrophy.
The specific aims of this thesis are:
•
To develop and test a human skeletal muscle specific cDNA microarray for
global transcriptional profiling and the identification of novel gene transcripts.
•
To further enhance current understanding of the process of myogenesis by
examining the expression profile of rhabdomyosarcoma cells undergoing forced
differentiation using the human skeletal muscle specific microarray.
•
To further test the sensitivity and reliability of the microarray in identifying
changes in gene expression in a biological system. Thus ensuring reliable and
reproducible results would be attainable from the microarray in subsequent
studies using less readily available human skeletal muscle samples.
•
To investigate the expression of myogenic and atrogenic genes in human
skeletal muscle following an acute bout of resistance exercise.
•
To use the human skeletal muscle specific microarray to study the time-course
of transcriptional changes and identify novel genes expressed following an
acute bout of resistance exercise.
•
To use human primary skeletal muscle cell cultures o identify whether the
expression of the novel genes were (1) activated at any time during
proliferation, cell cycle arrest or differentiation or (2) activated by the additional
mitogenic and myogenic stimulation provided by exogenous IGF-1 peptide
supplementation.
•
To examine whether the novel genes are a unique response to resistance
exercise or if they were responsive to skeletal muscle contraction or exercise in
general.
21
VI. HYPOTHESES
It is hypothesised that:
•
cDNA microarray analysis of the transcriptional profile of differentiating
rhabdomyosarcoma cells will result in the identification of novel differentially
expressed genes.
•
An acute bout of resistance exercise will increase the expression of the MRFs
and cell cycle regulators whilst reducing the expression of genes involved in
skeletal muscle atrophy.
•
The transcriptional analysis of human skeletal muscle following an acute bout of
resistance exercise using a human skeletal muscle specific cDNA microarray
will identify novel differentially expressed genes.
•
The expression of ASB5, TXNIP, MLP, FLJ38973 and the MRFs will be altered
during the differentiation of human skeletal muscle primary cell cultures.
•
The expression of ASB5, TXNIP, MLP, FLJ38973 and the MRFs will not be
altered following an acute bout of resistance exercise.
22
CHAPTER TWO
DEVELOPMENT AND VALIDATION OF A HUMAN
SKELETAL MUSCLE SPECIFIC MICROARRAY
I. INTRODUCTION
New methods for the simultaneous assessment of the levels of expression of
hundreds or thousands of mRNA levels in individual tissue samples are an attractive
means by which biological processes can be studied. The analysis of gene transcript
abundance is an important step in the determination of the functional roles of genes,
how these genes and gene products interact as well as the comparison of gene
expression patterns under different experimental conditions. Although mRNA is not
the ultimate product of a gene, transcription is the first regulatory step in gene
expression, and information about the mRNA levels is important for the understanding
of gene regulatory networks.
The ability to monitor global gene expression at the transcript level has become
possible due to the advent of cDNA microarray technologies. The power of microarray
lies in its ability to simultaneously estimate the comparative level of gene expression
of a large number of genes (up to 20,000 per array) in a single sample. Microarrays
have been developed that allow a high throughput and provide identity and expression
of both selected known genes and cDNAs representing uncharacterised genes
between numerous biological samples.
Microarrays are constructed by “spotting” PCR-amplified cDNA clones at high density
onto optically flat glass microscope slides in an orderly array (Hegde et al. 2000). RNA
extracted from experimental samples can be fluorescently labelled and competitively
hybridised to the microarray against a reference RNA sample, which is labelled with a
different fluorophore (Figure 2.1).
23
cDNA
Clones
PCR
amplification and
purification
Robotic printing
onto glass slides
Sample
RNA
Reference
RNA
PCR
Amplification
Label RNA
with dyes
RNAs are combined
and competitively
hybridised to the
prepared arrays
Image Analysis
Laser 1
Scanning
Laser 2
Figure 2.1. Overview of microarray production and analysis. Initially cDNA clones are PCR amplified,
purified and then spotted onto glass sides by microarray printing robots. RNA from samples of
interest and a reference are extracted, reverse transcribed, and labelled with Cy3 (usually red) and
Cy5 (usually green) fluorescent dyes. The two samples are then combined and competitively
hybridised to the prepared microarray slides. Laser excitation of the incorporated fluorescent dyes
yields an emission with a characteristic spectrum, which is measured using a scanning confocal laser
microscope. Thus from the fluorescence intensities and colours from each spot, the relative
expression of that particular RNA species in the experimental sample can be estimated. Laser
excitation of the incorporated targets yields an emission with a characteristic spectrum which is
measured using a scanning confocal laser microscope. Thus from the fluorescence intensities and
colours for each spot, the relative expression level of that particular RNA species in the experimental
sample can be estimated.
24
The complex nature of the molecular processes regulating skeletal muscle
development, adaptation and regeneration make it an ideal candidate for the
development of a tissue specific microarray. To this end we have created a
customised microarray containing up to 11,000 uncharacterised cDNAs derived from a
human skeletal muscle cDNA library as well as 270 genes with known functional roles
in skeletal muscle. The genes chosen represent key regulatory steps in signal
transduction pathways, various biochemical pathways including glycolysis and fatty
acid oxidation, as well as a number of transcription factors, cytoskeletal and proteolytic
proteins. The cDNA library used to construct the microarray was a human skeletal
muscle 5’-STRETCH PLUS cDNA library. The mRNA source for this library was
pooled from the quadriceps, iliopsoas and pectoralis major muscles from 8 male and
female Caucasians, aged 29-60, who died following trauma. Furthermore, the cDNA
library underwent extensive normalisation, a complex process where the cDNA copies
of a primary library are equalized, so that each original mRNA transcript is
represented in the normalized library to the same extent as all the rest of the clones.
Subsequently, by increasing the frequency of occurrence of rare cDNAs whilst
simultaneously decreasing the percentage of abundant genes, normalisation can
expedite the discovery of novel transcripts.
The extraction of reliable information from the massive amounts of data generated by
microarrays however, is dependant on optimal study design, array fabrication, data
acquisition, data quality and data analysis. There are many process variables that will
impact on the quality of the data generated by microarray platforms. Thus the
parameters required for the effective manufacture of cDNA microarrays with highly
reproducible performance characteristics, the quality and quantity of sample mRNA’s
used to create the dye-labelled cDNA probes and the effects of these optimised
procedures on the overall performance, accuracy, and precision are needed to be
extensively tested to guarantee the reliability of generated expression data.
Therefore, the aims of this study were firstly to describe the fabrication of the
microarray and secondly, evaluate the robustness and reproducibility of this analytical
technique.
25
II. METHODS
A. Microarray Fabrication
cDNA clones corresponding to the 270 known skeletal muscle genes were purchased
from Incyte Genomics (Palo Alto, CA). The clones were grown overnight and inserts
were PCR amplified using vector specific primers. Products were visualized by
agarose gel electrophoresis, then excised and sequence verified using a BigDye
Terminator Cycle Sequencing Ready Reaction Kit (Applied Biosystems, Foster City,
CA). For the gene discovery aspect of the microarray, the Human Skeletal Muscle 5'STRETCH PLUS cDNA Library was purchased from Clontech (Palo Alto, CA). The
clones were grown overnight and picked by the Australian Genome Research Facility
(Melbourne, Victoria, Australia) using a BioPick automated colony picker (BioRobotics
Woburn, MA). The inserts were PCR amplified and the products visualized by agarose
gel electrophoresis to confirm amplification of a single PCR product. Amplified cDNAs
were then purified using an ArrayIT PCR Purification Kit (Telechem, Sunnyvale, CA)
and resuspended in Spotting Solution Plus (Telechem) in preparation for arraying onto
SuperAmine Microarray Substrates (TeleChem) using a ChipWriter Pro microarrayer
(Virtek, Toronto, Canada). DNA adhesion to the glass was achieved by firstly baking
the printed arrays for 1h at 80°C, followed by rehydration at 37°C and irradiation in a
Stratalinker® UV Crosslinker (Stratagene, La Jolla, CA) at an energy output of 60mJ.
To minimise any potential non-specific probe interactions with the glass the
microarrays were washed for 2 min in 0.2% SDS (Invitrogen), followed by three rinses
in H2O for 2 minutes each with the last wash conducted at 95°C. They were washed
again for 2 min in 0.2% SDS, and rinsed a further two times in H2O for 2 min each.
Finally, the arrayed slides were dried by brief centrifugation and stored in opaque
plastic slide boxes at room temperature.
B. RNA Extraction
The RNA used for the homotypic hybridisations was a commercially available human
skeletal muscle RNA (Ambion, Austin, TX)
RNA for the repeatability and reliability analysis was derived from differentiating
rhabdomyosarcoma cells and formed part of a larger study (see chapter 3). Total RNA
was extracted using the RNA-bee (Tel-Test, Friendswood, TX) reagent and purified
26
using RNeasy Columns (Qiagen, Mannhiem, Germany) as per the manufactures
instructions (Qiagen 2001). Briefly, an appropriate volume of Trizol Reagent (Life
Technologies, Invitrogen, Carlsbad, CA) was used to ensure complete cellular
disruption and release of genetic material. Chloroform was added to the solution,
thoroughly mixed, incubated on ice for 5 mins followed by centrifugation at 4°C for 15
min. The upper aqueous layer was removed and mixed with an equal volume of 70%
ethanol before being added to the RNeasy spin column. After washing the column, the
RNA was eluted as described in the manufacture’s protocol. RNA quality and
concentration was determined using the Agilent 2100 Bioanalyzer (Agilent
Technologies, Inc., Palo Alto, CA).
C. Indirect labelling of cDNA
Fluorescently labelled cDNA was prepared from total RNA using an indirect labelling
method. cDNA synthesis was performed in a 20µl reaction containing 5µg oligo-dT
primer, 400U SuperscriptII (Invitrogen), 1X first strand buffer, 0.01M DTT, 0.5mM of
each dATP, dCTP and dGTP, 0.150mM dTTP (Amersham, Buckinghamshire, UK) and
0.2mM aminoallyl-dUTP (Sigma, St Louis, MO). Synthesis was conducted in a
GeneAmp PCR System 9700 (Applied Biosystems) at 42°C for 2 h. The reaction was
stopped by addition of 5µl of 0.5M EDTA and RNA was hydrolysed by addition of 20µl
of 1M NaOH at 70°C for 20 minutes. The reaction was neutralised with 25µl of 1M
HEPES and the cDNA was purified using Qiaquick PCR purification kits (Qiagen)
according to manufacturer’s instructions and eluted in nuclease-free water. The cDNA
was concentrated using Microcon30 spin columns (Millipore, Bedford, MA). Following
the addition of 0.09M sodium bicarbonate, the cDNA was coupled to Cy3 or Cy5
monofunctional N-hydroxysuccinimyl ester reactive dyes (Amersham). The coupling
reaction was conducted in the dark for 1 h.
The fluorescently labelled cDNA was purified using Qiaquick PCR purification kits
(Qiagen), combined and added to 10µg Human Cot1 DNA (Invitrogen). The cDNAs
were again concentrated to the required volume with Microcon30 spin columns
(Millpore). The cDNA were hybridised in a 40µl volume, containing the labelled cDNA,
5X SSC, 0.3% SDS, 4µg yeast tRNA, 8µg polydA, 2.5X Denhart’s solution. The cDNA
was denatured at 98°C for 2 minutes and maintained at 60°C until required. 38µl of
the hybridisation solution was applied to cover slips and then mounted onto the array
slide. Hybridisation was conducted in humid hybridisation chambers in a hybridisation
oven at 65°C for 16-20 hours.
27
D. Image Acquisition and Normalisation
Fluorescent images of the microarrays were acquired using the GenePix 4000B laser
scanner (Axon Instruments, Inc., Union City, CA) and the images processed using
Genepix Pro 3 software (Axon Instruments). Data files were entered into Acuity 4.0
software (Axon Instruments) where a global normalisation strategy was applied to
normalise signal intensities across all arrays. Normalisation of signal intensities across
all arrays is necessary in order to eliminate the effects of array-to-array variations in
target preparation, hybridisation and scanning.
28
III. RESULTS & DISCUSSION
A. Microarray Validation
1. Quality of cDNA clones and Microarray Printing
The manufacture of high quality, reproducible arrays with 10,000 or more unique PCR
products is an expensive and time consuming process. It requires considerable
attention to the details and necessary procedures in each step to ensure the quality
and reproducibility of the end product. Yue (Yue et al. 2001) state in their evaluation of
the performance of cDNA arrays that low concentrations of DNA in the input printing
solutions results in reduced amounts of arrayed DNA and this, in turn, reduces the
dynamic signal range and produces an apparent underestimation of differential
expression. Prior to being spotted onto optically flat microscope slides, the cDNA
clones for both the known and discovery aspects of the microarray were PCR
amplified, purified and visualised on agarose gels to verify amplification and presence
of a single PCR product (Figure 2.2). Plates containing greater than 15% PCR failure
or multiple products were not included in the array printing. Additionally, PCR products
corresponding to the known genes were sequence verified as previous findings have
identified incorrect sequences as a significant source of error (Knight 2001).
Representative microarrays from each manufactured batch were stained for DNA
using SYBRGold (Molecular Probes) and scanned on a GenePix 4000A scanner
(Axon Instruments) at 535 nm. The resulting image (Figure 2.3) demonstrated a high
degree of DNA retention on the surface of the array, good spot morphology and a
uniform printing pattern. The median diameter of the features on the array was 100
µm, with a preset spacing between the centres of adjacent features of 200 µm.
29
1kb Ladder
No insert
Figure 2.2. Representative agarose gel of amplified clones. PCR amplified cDNA
clones were run on a 1% agarose gel to verify amplification and the presence of a
single product.
Figure 2.3. A representative section of a SYBRGold stained microarray slide.
Representative microarrays from each manufactured batch were stained for DNA
using SYBRGold. The resulting image demonstrated a high degree of DNA
retention on the surface of the array, good spot morphology and a uniform
printing pattern.
30
2. Homotypic Response
An estimate of the accuracy and precision of microarray expression data was first
made by performing a homotypic hybridisation. A competitive hybridisation of
fluorescently labelled Cy3 and Cy5 cDNA, both prepared from the same mRNA,
should theoretically give a ratio of 1 (i.e. Cy3 fluorescence divided by Cy5
fluorescence). Replicate hybridisations provide valuable information on the overall
precision of the data by examining any deviations from the theoretical value (Yue et al.
2001).
Twenty µg of human skeletal muscle RNA was coupled to both Cy3 and Cy5
fluorophores and competitively hybridised to the skeletal muscle microarray. Figure
2.4 shows a false colour image of the hybridised microarray (A) with one 20 × 20 grid
enlarged (B). Typically, an array composed of disparate RNA samples, each labelled
with a different fluorophore, will exhibit varying degrees of expression typically
represented as red and green spots on an array. Elements showing no difference in
expression between the two samples are represented by yellow spots. As expected, a
homotypic hybridisation such as the one shown in Figure 2.4 is composed almost
exclusively of yellow spots.
A scatter plot of the Cy3 versus Cy5 fluorescent response and a histogram of intensity
ratios from the skeletal muscle/skeletal muscle hybridisation is shown in Figure 2.5.
Virtually all gene elements lie close to the diagonal line corresponding to the
theoretical differential expression ratio of 1 (Log ratio of 0, r2 = 0.99) The average
calculated relative fluorescence ratios for all elements was 1.057 with the 99.5%
confidence interval falling between 0.054 (lower bound) and 1.061 (upper bound). The
average coefficient of variation for ‘differential expression’ of any element in this
homotypic experiment is 11% over the entire signal range. These results demonstrate
equal incorporation of Cy3 and Cy5 to the RNA and equal hybridisation to the
microarray.
31
A
Figure 2.4. A false colour image of
the muscle:muscle hybridisation (A)
and an enlarged view of a single 20
× 20 grid (B). The array consists of
PCR-amplified random cDNA clones
spotted onto a glass slide. Equal
quantities of skeletal muscle RNA
was labelled with Cy3 and Cy5
fluorophores
and
competitively
hybridised to the array. Yellow dots
represent
genes
that
show
no
difference in expression between
the two sample RNAs.
B
32
A
Homotypic Hybridization
r 2=0.99
Cy5 Signal Value
100000
10000
1000
100
100000
10000
1000
100
Cy3 Signal Value
B
1600
Frequency
1200
800
400
.69
.49
.28
.07
-.13
-.34
-.55
-.75
0
Log Ratio
Figure 2.5. Homotypic Hybridisations. (A) Scatter plot of the calibrated Cy5
versus Cy3 fluorescence response from a skeletal muscle/skeletal muscle
hybridisation. Virtually all gene elements lie close to the diagonal line
corresponding to the theoretical differential expression ratio of 1. (B) Data points
from the homotypic hybridisations were used to construct a histogram, which
shows the distribution of gene elements around the expected log ratio of 0.0.
33
3. Repeatability and Reliability
3.1 Within-array reproducibility
To examine the spot to spot reproducibility and reliability within arrays, a total of 155
genes printed in duplicate on each array were examined across 18 microarrays. The
printing of replicate spots on the arrays allowed us to examine whether identical spots
on the array produced comparable results. From the 18 arrays in this data set we
calculated a coefficient of variation (CV) for each of the 155 duplicated genes. The
average CV was observed to be 15% across the entire signal range, although there
was slightly greater variation at low signal levels. Consequently, replicate genes
showing large variation in expression were excluded from subsequent analysis.
3.2 Between-array reproducibility
To examine the influence on hybridisations conducted on different days, six identical
hybridisations were performed: two performed on one day (repeat 1a and 1b), two
performed one week later (repeat 2a and 2b) and two performed 4 weeks later (repeat
3a and 3b). Skeletal muscle RNA was coupled to Cy3 dye and RNA extracted from
differentiated rhabdomyosarcoma cells was coupled to Cy5 dye. Disparate samples
were chosen for this analysis to examine the reproducibility and reliability of the data
over a range of expression values. Following normalisation and log transformation,
clustering methods were utilised to examine the similarity between the replicate
hybridisations. Algorithms utilized in clustering result in genes or groups whose
members resemble each other, and thus provide a convenient way to illustrate the
data. In this context, hierarchical clustering was performed to examine how similar or
different the overall arrays were across the six replicate hybridizations. Hierarchical
clustering partitions the data into a tree, so that substances that are not grouped
together on one branch of the tree are grouped together at a higher branch.
Substances occur only once in the tree. The distance between clusters was
determined by the distance between 'average neighbours'. Figure 2.6 shows the
hierarchical clustering dendrogram of the six replicate hybridisations. Pearson’s
Correlation Coefficient was used to examine the similarities between clusters. The
replicate hybridisations conducted on the same days showed a very high degree of
similarity (r2 = 0.97, 0.91 and 0.99 for replicates 1, 2, and 3 respectively) indicating a
very high degree of reproducibility. Greater variance was observed between arrays
conducted on different days, however the highly positive correlation (r2 =0.84)
indicated very good overall precision and reproducibility for the microarray.
34
Figure 2.6. Hierarchical clustering dendrogram of six identical hybridisations, two
conducted on one day (repeat 1a and 1b), two conducted one week later (repeat
2a and 2b) and two conducted 4 weeks later. The closest correlations are
indicated by low branches on the dendrogram. The overall high correlation (top
branch on the dendrogram) across the six arrays indicated very good
reproducibility of the microarray.
35
cDNA microarrays are a very attractive and powerful means of examining global gene
expression. The extraction of reliable information from the massive amounts of data
generated by microarrays however, is dependant on optimal study design, array
fabrication, data acquisition, data quality and data analysis. An important first step in
developing cDNA microarrays is the validation of the experimental and analytical
techniques. It is critical to establish whether repeated hybridisations with identical RNA
deliver comparable results before any attempt is made to quantitate biological
variability. We have developed a skeletal muscle specific cDNA microarray from a
normalised human skeletal muscle cDNA library which will allow expression analysis
and identification of novel genes in a range of different experimental systems. The
results presented demonstrate the robustness of the microarray in producing accurate
and reliable data.
36
CHAPTER THREE
IDENTIFICATION OF NOVEL GENES IN
DIFFERENTIATING RHABDOMYOSARCOMA
CELLS
I. INTRODUCTION
Skeletal muscle differentiation is characterised by terminal withdrawal from the cell
cycle, muscle-specific gene activation and subsequent fusion of myoblasts into
multinucleated myotubes. It has been well documented that myogenic differentiation is
under the control of a family of regulatory genes which belong to the basic helix-loophelix family of transcription factors, also referred to as the myogenic regulatory factors
(MRFs). The MRFs encode a family of transcription factors comprising four members,
MyoD, Myf5, myogenin and Myf6 (MRF4, herculin) that bind to specific consensus
sites that are functionally important in the transcription of muscle-specific genes
(Megeney and Rudnicki 1995; Yun and Wold 1996). These factors are characterised
by the ability, upon transfection, to convert nonmyogenic cells to the muscle
phenotype. Although these transcription factors play a major role in the myogenic
differentiation process, it is becoming evident that although their activity is necessary,
multiple signalling pathways are required to act in concert for the execution of the
differentiation program of muscle cells (Puri and Sartorelli 2000; Wei and Paterson
2001).
Rhabdomyosarcoma (RMS) are highly aggressive, malignant soft tissue sarcomas
that primarily affect children and young adults. These tumours resemble primitive
skeletal muscle-forming cells in appearance, suggesting that RMS may arise as a
consequence of regulatory disruption of the growth and differentiation of skeletal
muscle progenitor cells. Normal myogenesis is characterised by the expression of the
MRFs (MyoD and Myf5 and then myogenin and Myf6), followed by the differentiation
of myoblasts and formation of multinucleated myotubes. RMS cells however, are
blocked on their way to terminal muscle differentiation. Paradoxically, this abortive
myogenic differentiation occurs despite the expression of the MRFs, MyoD and
myogenin, (Aguanno et al. 1990; Bouche et al. 1993). Most RMS cell lines of human
and animal origin retain the ability to differentiate despite limited differentiation in vivo.
37
Treatment of RMS cells with phorbol esters such as 12-O-tetradecanoylphorbol-13acetate (TPA) has been widely shown to induce growth arrest and myogenic
differentiation, without affecting the expression of the myogenic transcription factors
(Garvin et al. 1986; Mayer et al. 1988; Aguanno et al. 1990; Lollini et al. 1991; Bouche
et al. 1993; Bouche et al. 1995; Bouche et al. 2000). Suggesting that the differentiation
arrest is due to mechanisms that interfere with the MRFs; downstream of their
expression (Bouche et al. 1995). However, the precise molecular mechanisms
responsible for the disruption of the myogenic characteristics of RMS is not well
understood.
The genetic regulation of RMS tumours is of great interest as the differentiation
potential strongly influences metastic ability and therefore prognosis of these tumours
(Lollini et al. 1991). Furthermore, the aberrant myogenic differentiation program in
RMS tumours provides a unique model for the identification of genes with previously
unidentified roles in myogenesis. An extensive body of work has demonstrated the
temporal and spatial roles of specific genes during myogenesis, however, limited
knowledge exists about how broad the transcriptional control of this process may be or
even which specific processes are the critical regulators of differentiation,
determination and fusion of muscle cells. Given the complexity of myogenesis, clearly
there are a host of genes, some known and some novel, involved in this process.
Thus, identifying known molecules with unknown functions or novel molecules that
play critical roles in the cascade of molecular events will help provide an essential
foundation for our understanding of myogenesis.
Because of the wide spectrum of genes likely to be involved in myogenesis, cDNA
microarray technology is well suited for the examination of genes expressed at key
time points during proliferation and differentiation. Microarray technology is a very
valuable tool, not only for the simultaneous examination of thousands of genes but
also in its ability to examine the expression of novel genes. The aims of this study
were two-fold. In chapter 2, the development of a skeletal muscle specific cDNA was
discussed. The first aim of this study was to further enhance current understanding of
the process of myogenesis by examining the expression profile of rhabdomyosarcoma
cells undergoing forced differentiation using the human skeletal muscle specific
microarray. The second aim was to further test the sensitivity and reliability of the
microarray in identifying changes in gene expression in a biological system. Thus
ensuring reliable and reproducible results would be attainable from the microarray in
subsequent studies using less readily available human skeletal muscle samples.
38
II. METHODS
A. Cell culture
The rhabdomyosarcoma cell line RD-A was a kind gift from Dr. Bruce Thorley at the
Victorian Infectious Diseases Reference Laboratory (North Melbourne, Australia). The
cells were maintained in high glucose Dulbecco’s Modified Eagle Medium (Gibco,
Invitrogen Corporation, Carlsbad, CA) containing 10% foetal bovine serum (Gibco) in
a humidified atmosphere of 5% CO2 in air at 37°C.
B. Study Design
RD-A cells were seeded at a density of 3000 cells/cm2 in complete medium on the day
prior to experimentation. After 24 h the medium was replaced with fresh medium
containing 2% horse serum (Gibco) to reduce proliferative factors. At the same time
100nM of TPA (Sigma, St Louis, MO) in DMSO (Sigma) was added to the medium to
induce differentiation. Cells were cultured for up to 10 days, with RNA and protein
extracted for analysis at day 1, day 3, day 6, day 8 and day 10. The control condition
for this experiment consisted of actively proliferating cells collected immediately before
the addition of the differentiation medium. At least 3 independent replicate
experiments were conducted.
C. Microarray Fabrication
The human skeletal muscle specific microarray was constructed as previously
described.
D. RNA extraction
Total RNA was extracted using the RNA-bee (Tel-Test, Friendswood, TX) reagent and
purified using RNeasy columns (Qiagen, Mannhiem, Germany) as per the
manufacturer’s instructions (Qiagen 2001). Briefly, an appropriate volume of Trizol
Reagent was used to ensure complete cellular disruption and release of genetic
material. Chloroform was added to the solution, thoroughly mixed, incubated on ice for
5 min followed by centrifugation at 4°C for 15 min. The upper aqueous layer was
39
removed and mixed with an equal volume of 70% ethanol before being added to the
RNeasy spin column. After washing the column, the RNA was eluted as described in
the manufacture’s protocol. RNA quality and concentration was determined using the
RNA Nano 6000 kit (Agilent Technologies, Inc., Palo Alto, CA).on the Agilent 2100
Bioanalyzer (Agilent Technologies).
E. Indirect labelling of cDNA and hybridisation
Fluorescently labelled cDNA was prepared from 40µg of total RNA using an indirect
labelling method. The reference RNA for this study was pooled from both
undifferentiated and differentiated rhabdomyosarcoma cells. Indirect labelling of the
RNA and subsequent hybridisation was prepared as previously described. In all
hybridisations, the reference RNA was labelled with Cy5 dye, whilst the experimental
samples were labelled with Cy3 dye.
F. Image Acquisition and Data Analysis
Fluorescent images of the microarrays were acquired using the GenePix 4000B laser
scanner (Axon Instruments, Inc., Union City, CA) and the images processed using
GenePix Pro4 software (Axon Instruments). Data files were entered into Acuity 4.0
software (Axon Instruments) for subsequent data analysis. The microarrays were
normalized using a linear, ratio-based normalization strategy. The normalization factor
was calculated from the average ratio of all features with expression ratios between
0.1 and 10. Flagged spots and spots with less than 55% of feature pixels with
intensities more than two standard deviations above the background pixel intensity
were not retained for further analysis. Furthermore, genes had to be present in at least
70% of arrays to be considered in the analysis. The elements and time-points were
averaged across replicate experiments and then organized by hierarchical clustering
with the Pearson correlation metric and average linkage clustering (Eisen et al. 1998).
Paired t-tests were used to identify ten elements with the greatest evidence of
differential expression during the differentiation process.
G. Clone Identification
Selected cDNA clones were grown overnight and plasmid isolation was conducted
using the QIAprep Spin Miniprep Kit (Qiagen) according to the manufacturer’s
instructions. Inserts were PCR amplified using vector specific primers. Products were
40
visualized by agarose gel electrophoresis then excised and the sequence was
determined using a BigDye Terminator Cycle Sequencing Ready Reaction Kit (Applied
Biosystems).
The
basic
local
http://www.ncbi.nlm.nih.gov/BLAST/)
alignment
search
tool
(BLAST,
was used to compare the cDNA clone
sequences with previously characterized genes (Altschul et al. 1990)
H. Real-time PCR Analysis
1. RNA Extraction
Total RNA was extracted as previously described (Chapter 3, section II, part D). The
RNA used for the real-time PCR analysis was derived from the same original stock
used in the microarray analysis.
2. Reverse Transcription
Prior to reverse transcription, the diluted RNA was heated to 65° C for 10 mins, then
quenched on ice for 5 mins. 1 µg of RNA was reverse transcribed to synthesise first
strand cDNA using the AMV reverse transcriptase kit (A3500; Promega, Madison, WI).
The RNA was added to a master mix containing a final concentration of 5 mM MgCl2,
10 mM Tris-HCl (pH 8.8), 50 mM KCl, 1% Triton X-100, 1 mM of each dNTP, 20 U
Recombinant Rnasin Ribonuclease Inhibitor (40 U/µl) and 1 µg oligo (dT)15 Primer
per 1 µg RNA. Following the addition of 15 U AMV Reverse Transcriptase (20 U/µl)
(Promega, Madison, WI), the mixture was incubated at 42° C for 60 mins, before the
reaction was terminated by incubation at 99° C for 5 mins followed by 5 mins at 4° C
using the PCR Express Thermal Cycler (Hybaid, Middlesex, UK). The cDNA was
stored at -20° C for subsequent analysis. A reverse transcription (RT) negative was
obtained by not adding any RNA to an aliquot of the RT mix.
3. Primer Design
To perform PCR, specific primers were designed for all genes using Primer Express
software (Applied Biosystems, Foster City, CA) on sequences obtained from GenBank
(see Table 3.1 for details). Where possible, primers were designed spanning intronexon boundaries to prevent amplification of the target region from any contaminating
DNA. Sequence information, including the positions of intron-exon boundaries was
obtained from the Ensemble Genome Project (www.ensembl.org) (Hubbard et al.
2002). Primer specificity was confirmed using BLAST (www.ncbi.nlm.nih.gov/BLAST/).
Primers were purchased from GeneWorks (Adelaide, SA, Australia).
41
4. Real-time PCR Reaction
For the PCR step, reaction volumes of 20µl contained SYBR Green 1 Buffer (Applied
Biosystems, Foster City, CA), forward and reverse primers (see Table 3.1) and cDNA
template (diluted 1:40). All samples were run in duplicate. Real-time PCR was run for
1 cycle (50ºC 2 min, 95ºC 10 min) followed by 40 cycles (95ºC 15 s, 60ºC 60 s) and
fluorescence was measured after each of the repetitive cycles. A melting point
dissociation curve generated by the instrument was used to confirm that only a single
product was amplified. The expression of the gene of interest in a given sample was
calculated by subtracting the CT of the target gene for a given sample, from the CT of
the control sample. The relative expression of the gene of interest compared with
control was then calculated using the expression 2-∆CT.
5. PCR Efficiency
For each gene, the PCR efficiency of the primer pairs was determined using a dilution
series of cDNA input into the PCR reaction. Linear regression was used to analyse the
response of CT vs. the logarithm of the cDNA concentration. Using the slopes of the
lines, we calculated the efficiency (E) of the target amplification with the equation E =
(10-1/slope)-1 (Lekanne Deprez et al. 2002). PCR efficiencies indicated a linear
detection of the cDNA for all genes (Table 3.1).
I. Western Blot Analysis
Rhabdomyosarcoma cells were cultured as described above. Control cells and cells
collected at day 1, day 3, day 6, day 8 and day 10 were resuspended in lysis buffer
(50mM Tris, pH7.6, 250mM NaCl, 5mM EDTA, 0.1% IGEPAL, Complete Protease
Inhibitor Cocktail (Sigma) and passed through a syringe. The cell extracts were
centrifuged to pellet cell debris, supernatants removed and analysed for total protein
(BCA protein assay kit, Pierce, Rockford, IL) (Langley et al. 2002). Equal amounts of
denatured total proteins from each sample were separated by electrophoresis on
either a 10% (myogenin) or 6% (total myosin heavy chain (MHC)) SDS-polyacrylamide
gel and transferred to nitrocellulose membrane by electroblotting. Membranes were
blocked for 2 h with 5% skim milk in Tris-buffered saline (50 mM Tris-HCl, 750 mM
NaCl, 0.25% Tween), and were incubated overnight at 4°C with a polyclonal anti-MHC
(MY-32, Zymed, San Francisco, CA) or anti-myogenin antibody (F5D, Developmental
Studies Hybridoma Bank, University of Iowa). Membranes were washed (4 x 5 min),
followed by a 60 min incubation with anti-rabbit IgG (MHC) or anti-mouse IgG
(myogenin) conjugated to horse-radish peroxidase (1 in 10,000 dilution) (Santa Cruz
Biotechnology, Santa Cruz, CA), then washed again. Immunoreactive bands were
42
detected using enhanced chemiluminescence (Western Lightning Chemiluminescent
Reagent, Perkin-Elmer, Boston, MA). An internal control was used in each gel to
normalize for variation in signal observed across the membranes. The density of the
bands was analysed using Kodak 1D 3.5 image analysis software (Kodak Digital
Science, Rochester, NY).
J. Immunocytochemistry
Myosin heavy chain expression was evaluated on cells grown on cover slips under the
conditions described above. At different time points, the cells were fixed in cold 100%
methanol at -20°C for 10min. Non-specific binding sites were blocked with 1% BSA in
PBS followed by incubation in the primary antibody reactive to skeletal myosin heavy
chain (MY-32, Zymed, San Francisco, CA). Subsequently, the cells were incubated
with the fluorescent secondary antibody, anti-mouse AlexaFluor 488 (Molecular
Probes, Oregon, USA). Nuclei were stained by incubating the cells in the DNA binding
dye Bisbenzimide Hoechst 33285 (Sigma). Immunostained cells were visualised with
an Olympus IX70 fluorescent microscope (Olympus, Australia) and digital images
collected (Spot RT slider camera: Image-Pro® Plus Software).
K. Statistical Analysis
Statistical analysis was performed using GraphPad Prism 4.1 (GraphPad Software,
San Diego, CA). Unless stated, means were compared using a one-way ANOVA (for
normally distributed data) and any significant differences analysed using a Dunnet’s
Multiple Comparison and using a Kruskal-Wallis test (for non-Gaussian distributions)
and any significant differences analysed using a Dunn’s post test. Data is presented
as mean ± standard error of the mean (SEM) unless otherwise stated. P<0.05 was
considered statistically significant.
43
Table 3.1. Real-Time PCR Primer Details.
Gene
GenBank
Accession
Number
Forward Primer (5’-3’)
Conc,
µM
Reverse Primer (5’-3’)
Conc,
µM
Exon
Span
Amplicon
Size, bp
PCR
Efficiency
CCT7
NM_006429
AGAGATTGCTGTGACCGTGAAG
2
CGGTCATGGCACACTTTTCC
2
4&5
74
0.8
CKM
NM_001824
GGCATCTGGCACAATGACAA
2
GATGACCCGGAGGTGATCCT
2
4&5
69
0.8
MYF5
NM_005593
TTCTACGACGGCTCCTGCATA
2
CCACTCGCGGCACAAACT
2
---
67
1.2
MYF6
NM_002469
CACCCTGCGCGAAAG
2
CACAGTTCGCCGCTTCAGT
2
---
70
1.1
MYL1
NM_079420
TGCTGAACTCCGCCATGTT
2
CCATCAGGGCTTCCACTTCTT
2
4&5
71
0.9
MYOD
NM_002478
CCGCCTGAGCAAAGTAAATGA
4
GCAACCGCTGGTTTGGATT
4
---
74
1.0
myogenin
NM_002479
GGTGCCCAGCGAATGC
2
TGATGCTGTCCACGATGGA
2
2&3
155
0.9
PTMA
NM_002823
CTCAGACGCAGCCGTAGACA
2
CTGCCTCTTCCACAACTTCCTT
2
1&2
80
0.9
Tim10
NM_012456
TCCTCTCAGGGCCCAACAG
2
GTTGATCATATCGGCCATCATCTC
2
---
64
0.9
Primer sequences were designed using Primer Express Version 2 software (Applied Biosystems) using sequences accessed through GenBank and checked for specificity using
Nucleotide-Nucleotide Blast search (http://www.ncbi.nlm.gov/BLAST/). Exon information was obtained from the Ensembl Genome Database (http://www.ensembl.org/). The
concentrations of forward and reverse primers are indicated along with the intron-exon divide the primers were designed around (if possible) and amplicon size in base pairs. PTMA,
Prothymosin alpha; CCT7, chaperonin containing t polypeptide 1 eta; CKM, creatine kinase, muscle; MYL1, myosin, light polypeptide 1; Tim10, translocase of inner mitochondrial
membrane 10 homolog;.
44
III. RESULTS
A human skeletal muscle specific microarray was used to examine the gene
expression of rhabdomyosarcoma cells undergoing a forced differentiation. TPA was
used to induce growth arrest and myogenic differentiation of a derivative of the
embryonal rhabdomyosarcoma cell line RD, RD-A. As expected, differentiation of the
cells was accompanied by a significantly increased expression (p<0.01) of myosin
heavy chain protein (Figure 3.1) and an increased appearance of some multinuclear,
myotube-like structures (Figure 3.2).
This
**
120
100
arbitraray units
MHC Protein Expression
140
**
**
80
*
60
40
20
0
Control
Day 1
Day 3
Day 6
Day 8
Day 10
Figure 3.1. Western blot analysis of MHC protein expression over 10 days of
differentiation with TPA containing medium. A representative blot from one
replicate experiment is shown above the histogram. The order of samples on the
blot corresponds with the order of bars in the histogram below. The cell extracts
were electrophoresed through a 6% SDS-polyacrylamide gel, transferred to
nitrocellulose membranes and probed with the myosin antibody (MY-35). The
arbitrary density of the bands was analysed using Kodak 1D 3.5 image analysis
software and the average of three independent replicate experiments is
presented.
* Significantly different from control (p<0.05)
** Significantly different from control (p<0.01)
45
A
B
C
D
E
F
Figure 3.2. Immunofluorescence analysis of RMS cells over the 10 days of TPA
induced differentiation. Cells were reacted to the MHC antibody MY-35 (green).
Nuclei were counterstained using the DNA binding dye Bisbenzimide Hoechst
33285 (blue). (A), Control; (B), Day 1; (C), Day 3; (D), Day 6; (E), Day 8; (F),
Day10. Bar represents 100µM.
46
The microarray used for the experiments was fabricated from a human skeletal
muscle cDNA library and contained approximately 11,000 elements. Due to the
marked differences in gene expression between normal human skeletal muscle and
rhabdomyosarcoma tissue, hybridization of rhabdomyosarcoma RNA to the
microarray resulted in only 4042 elements showing adequate expression levels
following normalization. Using hierarchical clustering and paired t-tests, genes were
grouped according to common patterns of expression over the time-course of
differentiation (Figure 3.3). Analysis was focused on the identification of genes with
evidence for either increased or decreased expression during the differentiation
process. 105 elements demonstrated consistent up-regulation of expression
throughout the differentiation in all three of the replicate experiments. Conversely, 190
elements showed a reproducible reduction in expression.
47
Figure 3.3. Hierarchical clustering analysis of expression profiles. Hierarchical
clustering was used to group genes based on their expression profiles. Each
gene element is represented on the vertical axis, and the time points are shown
on the horizontal axis. The expression ratios for each gene at each time point are
colour coded: red indicates increased expression while green indicated reduced
expression relative to the reference expression level. Two distinct clusters are
evident, an up regulated pattern of expression (highlighted in blue) and a down
regulated pattern of expression. The averages of three independent replicate
experiments are presented.
48
Ten elements showing the greatest evidence of altered expression during
differentiation were selected for sequencing and further analysis (Table 3.3). These
ten elements were found to consist of seven genes that were differentially expressed
during the differentiation of RMS cells. Muscle creatine kinase (CKM) and several
cytoskeletal proteins including myosin light chain 1 (MLY1) and myosin light chain 2
(MLY2) were markedly up-regulated during differentiation (Figure 3.4). In contrast
prothymosin alpha (PTMA), chaperonin containing t-complex polypeptide 1, eta
subunit (CCT7) and translocase of inner mitochondrial membrane 10 (Tim10) showed
reduced expression during differentiation.
Table 3.3. List of genes identified following clone sequencing.
Up-Regulated Genes
Clone ID
Gene
Down-Regulated Genes
Clone ID
Gene
M15n5
Creatine kinase, muscle
M17c4
Prothymosin, alpha
M11a3
Creatine kinase, muscle
M34l16
Translocase of inner
mitochondrial membrane 10
M12l14
Creatine kinase, muscle
M07d22
Chaperonin containing tcomplex polypeptide 1, eta
subunit
M52e6
M52f20
M02i7
M06e16
Myosin, light polypeptide
2, regulatory, cardiac,
slow
Myosin, light polypeptide
1, alkali; skeletal, fast
Myosin, light polypeptide
3, alkali; ventricular,
skeletal, slow
Creatine kinase, muscle
2
2
1
1
1
0
0
0
-1
-1
-3
**
**
-4
**
**
3
**
**
MYL2
**
2
**
**
3
**
-1
-2
-2
-2
-3
-3
-3
-4
-4
**
**
**
**
-4
**
**
1
Day 10
-1
Day 8
-1
Day 6
0
Day 3
0
Day 1
0
**
**
MYL3
2
1
2
**
-4
1
3 CKM
**
-3
**
1
Figure 3.4. Microarray expression profiles of
* Significantly different from control (p<0.05)
-4
Day 10
independent, replicate experiments.
-3
Day 8
-2
Day 3
bar represents the mean ± SEM of three
Day 1
selected differentially expressed genes. Each
Control
0
-1
Day 6
(cy3/cy5)
Log2 Ratio of medians
**
2
(cy3/cy5)
**
-4
3 MYL1
Log2 Ratio of medians
-3
**
-2
Day 1
**
-2
**
-1
*
Control
-2
*
Day 10
2
Tim10
Day 8
3
Day 6
3 PTMA
Day 3
3 CCT7
Control
(cy3/cy5)
Log2 Ratio of medians
49
** Significantly different from control (p<0.01)
50
To confirm the results of the microarray experiments, the changes in mRNA levels of 5
genes were quantified using real-time RT-PCR (Figure 3.5). The changes measured
by real-time PCR were very similar to that of the microarray with the exception of one
gene, CCT7, whose expression was not changed over the time course of
differentiation as measured by real-time PCR. CKM and MYL1 demonstrated a
significant ~12-fold (p<0.01) and ~16-fold (p<0.01) increase in gene expression
respectively following 3 days of differentiation which continued to increase after 6 days
(although not significantly) and then slowly decreased. Tim10 mRNA tended to
decrease during differentiation, but this did not reach statistical significance (p=0.09).
PTMA expression was significantly reduced (p<0.01) following 3 days (2.5-fold), 6
days (2.5 fold), 8 days (4.7 fold) and 10 days (5.4 fold) of TPA induced differentiation
of rhabdomyosarcoma cells.
Since the muscle regulatory factors are considered critical in the process of normal
myogenic differentiation, we examined their expression over the time course of RMS
differentiation. MyoD and Myf5 are expressed early on in the differentiation cascade,
showing a significant reduction in expression at days 8 and 10 (MyoD, p=0.01) and
days 6, 8 and 10 (Myf5, p<0.01) as shown in Figure 3.6. Myf6 (p=0.03) and myogenin
(p=0.04) mRNA expression both increased in response to differentiation, however due
to quite marked variability, the ~40-fold increase in Myf6 expression was only
significant at day 6. Myogenin mRNA showed a marked (~6-fold) increase in
expression which remained elevated above control at day 10. Again due to variability
in expression, significant differences (p= 0.05) were only evident at day 8 (3 fold
increase). Myogenin protein expression was not detectable in proliferating cells and
increased maximally (p<0.01) at day 3 (Figure 3.6B).
51
Tim10
PTMA
1.00
**
0.50
**
**
0.25
0.00
Control Day 1
Day 3
Day 6
**
Arbitrary Units
0.75
Normalised to Control
Arbitrary Units
Normalised to Control
1.00
0.75
0.50
0.25
0.00
Day 8 Day 10
Control Day 1
**
Arbitrary Units
10
5
Day 3
Day 6
Normalised to Control
Normalised to Control
Arbitrary Units
15
Control Day 1
Day 8 Day 10
**
17.5
20
0
Day 6
CKM
MYL1
25
Day 3
Day 8 Day 10
15.0
12.5
10.0
7.5
5.0
2.5
0.0
Control Day 1
Day 3
Day 6
Day 8 Day 10
CCT7
Arbitrary Units
Normalised to Control
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
Control Day 1
Day 3
Day 6
Day 8 Day 10
Figure 3.5. Real-time PCR validation of the genes identified from the microarray
analysis. Data is presented as arbitrary units normalized to the control value. Bars
show the mean ± SEM of six replicate experiments.
* Significantly different from control (p<0.05)
** Significantly different from control (p<0.01)
52
A
Myf5
MyoD
1.00
1.0
0.8
0.6
**
0.4
*
0.2
0.0
Control Day 1
Day 3
Day 6
Arbitrary Units
1.2
Normalised to Control
Arbitrary Units
Normalised to Control
1.4
0.75
**
0.50
0.25
0.00
Day 8 Day 10
**
**
Control Day 1
Day 3
Day 6
Normalised to Control
Arbitrary Units
Normalised to Control
Arbitrary Units
80
*
Control Day 1
Day 6
**
60
40
20
0
Day 8 Day 10
*
Control Day 1
Day 3
Day 6
Day 8 Day 10
Myogenin Protein Expression
arbitrary units
B
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
**
Control
Day 1
Day 3
Needd
Day 6
**
Day 8 Day 10
Myf6
Myogenin
9
8
7
6
5
4
3
2
1
0
Day 3
Day 8
Day 10
Figure 3.6. Expression of the myogenic basic helix-loop-helix transcription factors.
(A) mRNA expression of the MRFs over 10 days of differentiation. Data is presented as arbitrary
units normalized to the control value. Bars show the mean ± SEM of six replicate experiments.
(B) Western blot analysis of myogenin protein expression over 10 days of differentiation. A
representative blot from one replicate experiment is shown above the histogram. The order of
samples on the blot corresponds with the order of bars in the histogram below. The cell extracts
were electrophoresed through a 12% SDS-polyacrylamide gel, transferred to nitrocellulose
membranes and probed with the myogenin antibody (F5D). The average of three independent
replicate experiments is presented.
* Significantly different from control (p<0.05)
** Significantly different from control (p<0.01)
53
IV. DISCUSSION
Differentiation of skeletal muscle involves the withdrawal of myoblasts from the cell
cycle and the subsequent expression of muscle-specific genes. We used an in vitro
model of myogenesis and microarray technology to identify novel genes involved in
time course of RMS proliferation arrest and progression towards terminal
differentiation. RMS differentiation was induced by the addition of a phorbol ester and
assessed by the appearance of myosin heavy chain, a widely used marker of
differentiation. As expected, differentiation of the cells was accompanied by an
increased expression of myosin heavy chain protein. Interestingly, the maximal rate of
differentiation appeared evident following 6 days of treatment with TPA and
subsequently declined. Aguanno (Aguanno et al. 1990) reported the presence of
elongated
and
multinucleated
myofibre-like
structures
in
TPA-treated
rhabdomyosarcoma cultures in addition to mononucleated and extremely elongated
spindle cells, polygonal or star-shaped cells and small round cells. The small round
cells were shown to rapidly proliferate and eventually reach confluence when the
medium was replaced, even in the continued presence of TPA. The length of
treatment in the present study necessitated the replacement of culture medium to
maintain cell viability and is likely to have contributed to the increased percentage of
mono-nucleated, undifferentiated cells observed and subsequent reduction in myosin
heavy chain expression at 8 and 10 days post differentiation. Similarly, multinucleated
cells may have detached during the extended culture times and possibly contributed to
the reduction in myosin postive cells post 8 days of differentiation.
Using microarray analysis of gene expression, we identified a cluster of genes which
demonstrated marked up-regulation throughout the forced differentiation of the RMS
cells. In addition, a number of genes were dramatically reduced in their expression
following differentiation. The majority of genes that showed increased expression were
markers of terminal skeletal muscle differentiation such as myosin light chain, desmin
and creatine kinase. Among the genes showing decreased expression were markers
of cell proliferation, consistent with proliferation arrest, which is necessary for
progression along the myogenic pathway. Of particular interest are two genes whose
expression has not, to our knowledge, been investigated in RMS, including
prothymosin alpha (PTMA), and translocase of inner mitochondrial membrane 10
(Tim10).
PTMA is an acidic, nuclear protein which is highly conserved and ubiquitously
expressed in a wide variety of tissues. Despite the number of effects described for this
protein, none are accepted as its physiological role and thus its function remains
54
elusive. Of its many reported functions, the relationship between PTMA and cellular
proliferation and survival appears to be the mostly widely acknowledged. Expression
of PTMA is generally correlated with cellular proliferation and its over-expression has
been shown to stimulate cell division due to shortening of the G1 phase of the cell
cycle (Wu et al. 1997b) as well as inhibit cell differentiation (Rodriguez et al. 1999). It
was reported that terminal differentiation signals in HL-60 cells lead to a pronounced
decrease in PTMA expression (Dosil et al. 1993), and a subsequent study confirmed
that this decrease was related to the signal for the cessation of proliferation, rather
than for the start of differentiation (Smith et al. 1993). Whilst PTMA appears to play a
critical role in the process of proliferation and differentiation in a wide range of cells,
the mechanism of action remains unclear.
Due to its proliferative activity, PTMA has also been extensively studied in tumoral
processes. PTMA expression is evident at higher concentrations in malignant tumours
than normal or surrounding tissues (Tsitsiloni et al. 1993) and has been established as
a marker for breast cancer (Dominguez et al. 1993; Tsitsilonis et al. 1998; Magdalena
et al. 2000), hepatocarcinoma (Wu et al. 1997a) and lung cancer (Sasaki et al. 2001).
Thus the possibility remains that PTMA might also be an effective marker of RMS, and
as in the case of breast cancer, has the potential to be of prognostic value in
determining metastatic capacity and also the risk of death (Tsitsilonis et al. 1998).
Mitochondria import the vast majority of their proteins from the cytosol. To cope with
the variety of these precursors, they have dedicated translocation machineries that
facilitate importation through the outer (TOM translocase) and inner (TIM translocase)
membrane. The carrier import pathway also depends on the function of a soluble 70
kDa complex made of Tim9 and Tim10 (the TIM10 complex). The passage of proteins
across the intermembrane space is specifically mediated by the TIM10 complex which
facilitates the transfer of carriers from the outer membrane to the outer surface of the
inner membrane. This complex appears to be important as both the Tim9 and Tim10
genes are essential in yeast (Koehler et al. 1998; Leuenberger et al. 1999; Tokatlidis
and Schatz 1999). In the present study, the Tim10 mRNA expression was markedly
reduced during differentiation of rhabdomyosarcoma cells. However, its role in this
context is unclear. No studies have previously identified differential expression of the
Tim10 gene in either the cell cycle or associated with tumoral processes. However, it
remains a possibility that proliferation arrest may be associated with a reduced
mitochondrial proliferation and therefore a reduced need for associated mitochondrial
proteins. Regardless of the functions of this protein, the change in its expression is
more likely to be a consequence of the differentiation stimulus, rather than as a critical
regulator of the process.
55
In addition to the hypothesis generating approach of microarray, we also used a more
informed approach to examine the expression of the myogenic regulatory factors
(MRFs) during the time course of rhabdomyosarcoma differentiation. Previous studies
that have examined the MRF expression in rhabdomyosarcoma differentiation, have
done so only at single time points (Bouche et al. 1993; Wasserman et al. 1996; Astolfi
et al. 2001; Sirri et al. 2003) and did not observe any detectable level of Myf5
expression (Bouche et al. 1993; Wasserman et al. 1996), contradicting the results
presented here. It is possible however, due to its very limited expression, that the
methodologies used in the previous studies were not sensitive enough to detect the
lowly expressed transcript.
Although the expression of the MRFs in rhabdomyosarcoma has been reported
previously, no studies to date have examined the expression of all four of the basic
helix-loop-helix factors over the time course of rhabdomyosarcoma differentiation. The
expression of each of the MRFs observed reflects that previously described in normal
myogenic differentiation (Megeney and Rudnicki 1995). MyoD and Myf5 were more
highly expressed in proliferating cells and very early in the differentiated state,
supporting their roles in the determination and/or maintenance of myogenic identity
(Braun et al. 1992; Rudnicki et al. 1992), however their continued expression during
myogenic differentiation may be required (Bergstrom and Tapscott 2001). Whereas,
myogenin and Myf6 expression increased during differentiation, again consistent with
their known roles in myogenic differentiation (Hasty et al. 1993; Sumariwalla and Klein
2001) and fusion (Dedieu et al. 2002).
The data presented here confirm and extend previous research by not only identifying
the expression of the MRFs in RMS, but also mapping the temporal pattern of their
expression throughout differentiation. These results again support the theory that the
suppression of differentiation in rhabdomyosarcoma cells is due to mechanisms that
interfere with the activity of the MRFs, rather than with their expression (Bouche et al.
1995).
As a secondary aim, this study sought to test the sensitivity and reliability of the
microarray in detecting changes in gene expression in a biological system. The gene
changes observed over the differentiation time-course were appropriate and occurred
in a chronologically appropriate manner. Furthermore, quantitative real-time PCR
confirmed the results of the microarray thus ensuring confidence in the microarray as
a robust, reliable and sensitive measure of global changes in gene expression.
56
The microarray data presented here identify new information related to the genetic
regulation of myogenesis in differentiating human rhabdomyosarcoma cells. Our
current understanding of the differentiation block evident in rhabdomyosarcomas
however remains limited. We also examined the temporal pattern of MRF expression
over the time-course rhabdomyosarcoma differentiation identifying a remarkably
similar pattern of expression to that exhibited in normal myogenesis.
57
CHAPTER FOUR
MYOGENIC AND ATROGENIC GENE EXPRESSION
IN HUMAN SKELETAL MUSCLE FOLLOWING
ACUTE RESISTANCE EXERCISE
I. INTRODUCTION
Skeletal muscle size is determined by the complex interplay between hypertrophic and
atrophic stimuli ensuing remarkable adaptability to environmental challenges. Central
to this adaptive process is the activation of satellite cells which are responsible for
postnatal muscle growth. Increased loading, stretch, and muscular damage is
accompanied by a myriad of growth signals that trigger normally mitotically quiescent
satellite cells to re-enter the cell cycle and replicate (Rosenblatt et al. 1994; Kadi and
Thornell 2000; Hill et al. 2003; Wozniak et al. 2003). The decision for the cell to divide
occurs when a cell passes a restriction point late in the G1 phase of the cell cycle,
after which it commits to the autonomous progression to divide. Critical to this G1 to S
transition is the activity of a family of cyclin/cyclin-dependant kinases (Cdks) (eg.
Cdk4, cyclin D1, cyclin E). Proliferation is also regulated by a number of Cdk-inhibitors
(eg. p21cip, p27kip, p57kip), that inhibit the activity of the Cdks and thus promote cell
cycle arrest and progression towards terminal differentiation.
Whilst the activity of the Cdks and Cdk-inhibitors are important in the proliferative
response in many cell types, the specification of the skeletal muscle phenotype is
dependant on the activity of the basic-loop-helix family of MRFs. The MRFs comprise
four members: MyoD, Myf5, myogenin and Myf6 (MRF4, Herculin) that bind to specific
consensus sites that are functionally important in the transcription of muscle-specific
genes. The critical role the MRFs play in muscle development (Braun et al. 1992;
Rudnicki et al. 1992; Rudnicki et al. 1993; Ramakers et al. 2003) and their temporal
expression during myogenic proliferation and differentiation has been extensively
described (Montarras et al. 1991; Smith et al. 1994; Barjot et al. 1995). More recently,
the role of the MRFs has been expanded to included the control of regenerating adult
muscle (Cooper et al. 1999; Sakuma et al. 1999; Mendler et al. 2000; Launay et al.
2001) as well as the adaptive response of skeletal muscle to hypertrophic stimuli
(Lowe et al. 1998; Adams et al. 1999; Alway et al. 2001; Carson et al. 2002; Bickel et
58
al. 2003; Psilander et al. 2003; Willoughby and Rosene 2003; Bamman et al. 2004;
Bickel et al. 2004).
Since satellite cell regulation and specification of the muscle phenotype constitute
critical components of skeletal muscle hypertrophy, several recent studies have begun
to investigate the expression patterns of MRFs and cell cycle regulators in response to
both acute resistance exercise (Haddad and Adams 2002; Willoughby and Nelson
2002; Psilander et al. 2003; Bickel et al. 2004) and following resistance exercise
training (Bamman et al. 2004) in human skeletal muscle. To our knowledge however,
no study has systematically investigated the temporal expression of all members of
the MRF family in conjunction with both stimulators and inhibitors of the satellite cell
cycle in human skeletal muscle. Furthermore, it has yet to be established whether
acute loading of muscle through resistance exercise is sufficient to activate the entire
process of satellite cell activation and differentiation. Indeed, understanding of the
coordinated regulation of the multiple signalling pathways and molecular responses
currently recognized in hypertrophying skeletal muscle is limited. In the present study,
the expression of markers of the cell cycle and MRFs following a single bout of
resistance exercise was investigated.
It has been established that many signalling pathways operate concurrently in skeletal
muscle to elicit muscle adaptation. Although much interest has focused on the
regulation of the anabolic response of skeletal muscle, the inhibition of the protein
degradation pathways must also constitute an important part of the hypertrophy
pathway. A secondary aim of the present study was to investigate the expression of
recently identified down stream members of the protein degradation pathway following
resistance exercise. It was hypothesised that a single bout of resistance exercise
would increase the expression of members of the MRF and cell cycle regulator
families whilst the expression of genes involved in skeletal muscle atrophy would be
reduced.
59
II. METHODS
A. Subjects
Ten healthy male subjects volunteered to participate in this study. Informed written
consent was obtained from each subject before participation in the study, after the
nature, purpose and risks of the study were explained. Age, height and weight were
on average 27.1 ± 2 years, 179.3 ± 1.6 cm, and 78.4 ± 2.7 kg (mean ± SEM).
Concentric and eccentric maximal voluntary contraction of the quadriceps was 229.6 ±
10 NM and 273.4 ± 9.5 NM, respectively. Exclusion criteria included resistance training
within the past six months or previous history of a diagnosed condition or illness that
would endanger the subjects during strenuous resistance exercise. All experimental
procedures involved in this study were formally approved by the Deakin University
Ethics Committee.
B. Familiarisation
Each subject completed a familiarization session on a Cybex NORM dynamometer
(Cybex International Inc. UK) to become familiar with the execution of the exercise.
Isokinetic maximal voluntary contraction (MVC) strength was assessed during knee
extension during the familiarization session. MVC was determined at 60°.sec-1 over
five maximal leg extensions and the peak torque (Nm) for both concentric and
eccentric contractions was recorded. Subjects were instructed to contract as hard as
possible and were verbally encouraged throughout the test. Familiarization and
strength testing was completed at least 7 days before the trial to prevent residual
effects of the familiarization routine.
C. Experimental Design
Subjects arrived at the laboratory in the fasted state for a resting muscle biopsy. For
the 24 h preceding, and the days of the trial, subjects were provided with and
consumed a standard diet of 20% fat, 14% protein, 66% carbohydrate and abstained
from alcohol, caffeine, tobacco and additional exercise. Macronutrient intake was
assessed using FoodWorks 3.0 (Xyris Software, Australia). Following the resting
biopsy, subjects completed an acute bout of concentric and eccentric isokinetic leg
60
extension exercise. All exercise was completed on the non-dominant limb using the
Cybex NORM dynamometer at a constant speed of 60°.sec-1. Subjects completed 3
sets of 12 repetitions of maximal singled-legged knee extension exercise with 2
minutes rest between each set. The system provided visual graphical feedback for
both subject and investigator. Subjects were instructed to contract as hard as possible
and were verbally encouraged throughout each set. Further muscle samples from the
recovering leg were obtained 30 min, 4h, and 24 h post exercise.
D. Muscle Biopsy Procedure
The vastus lateralis muscle of the non-dominant leg was sampled by percutaneous
needle biopsy technique (Bergström 1962) modified to include suction (Evans et al.
1982). Excised muscle tissue from each biopsy was immediately frozen and stored in
liquid nitrogen for subsequent analysis. Sampling muscle by needle biopsy will
inevitably damage tissue and stimulate muscle regeneration in the immediate area. To
minimise the impact of muscle damage from previous biopsies site on the response of
muscle to the exercise serial muscle biopsies were collected from separate incisions
made at least 2cm from previous biopsy sites. Repeat biopsies have been shown
previously to have a negliable effect on the MRF gene expression in human skeletal
muscle (Psilander et al. 2003). Additionally, fibre type variability across the vastus
lateralis muscle may impact on variations in gene expression observed. Care was
taken to ensure that muscle biopsies were collected from a similar anatomical position
for all subjects. Considerable inter-human variability evident in skeletal muscle gene
expression precluded a comparison of intra-muscular variation with an untreated
control population of subjects.
E. Real-Time PCR Analysis
1. RNA Extraction
RNA was extracted from skeletal muscle samples (5-10mg) using the FastRNA™ KitGreen (BIO 101, Vista CA) protocol and reagents (Dana et al. 1995). RNA quality and
concentration were determined by UV spectrometry. (Heλios, Unicam, Cambridge,
U.K). RNA concentration was determined using the equation OD260 / 0.0625 µg/µl
(Sambrook et al. 1989). RNA purity was determined by the equation OD260/OD280,
with values required to be >1.7 to be accepted as non-contaminated. An aliquot of the
RNA was stored at -80° C for subsequent reverse transcription.
61
2. cDNA Synthesis
cDNA synthesis was performed as described previously (Chapter 3, section II, part
H.2)
3. Primer Design
Primer design was performed as previously described (Chapter 3, section II, part H.3)
4. Real-time PCR Reaction
Real-time PCR was performed using the GeneAmp® 5700 Sequence Detection
System (Applied Biosystems, Foster City, CA). For the PCR step, reaction volumes of
20µl contained SYBR Green 1 Buffer (Applied Biosystems), forward and reverse
primers (see Table 4.1) and cDNA template (diluted 1:40). All samples were run in
duplicate. Real-time PCR was run for 1 cycle (50ºC 2 min, 95ºC 10 min) followed by
40 cycles (95ºC 15 s, 60ºC 60 s) and fluorescence was measured after each of the
repetitive cycles. A melting point dissociation curve generated by the instrument was
used to confirm that only a single product was amplified.
5. PCR Efficiency
RNA extracted from a single human muscle sample was used to examine the dynamic
range of responses for a series of dilutions of cDNA generated from the RT step.
Linear regression was used to analyse the response of CT vs. the logarithm of the
cDNA concentration. Using the slopes of the lines, we calculated the efficiency (E) of
target amplification with the equation E = (10-1/slope)– 1 (Table 4.1).
6. PCR Analysis and Endogenous Control Selection
Data was analysed using the comparative critical threshold (Ct) method where the
amount of target normalised to the amount of the endogenous control is given by 2-∆Ct.
β-actin has previously been identified as an appropriate endogenous control for
resistance exercise studies (Mahoney et al. 2004) and as such was selected for the
endogenous control for this study. The appropriateness of this gene as an
endogenous control was confirmed by examining the 2-∆Ct normalised to control values
(Figure 4.1).
62
β-actin
Arbitrary units normalised to
control
1.75
1.50
1.25
1.00
0.75
0.50
0.25
0.00
Pre
30min
4h
24h
Figure 4.1. Examination of the mRNA expression of the endogenous control βactin following an acute bout of resistance exercise. Statistical analysis revealed
no change in the expression of this gene at any time point following the exercise
intervention (p<0.05). Therefore, this was considered an appropriate endogenous
control for this study.
G. Statistical Analysis
Statistical analysis was performed using GraphPad Prism 4.1 (GraphPad Software,
San Diego, CA). Means were compared using a one-way ANOVA and any significant
differences analysed using a Dunnet’s multiple comparison test. Data is presented as
mean ± standard error of the mean (SEM). A probability level of <0.05 was adopted
throughout to determine statistical significance unless otherwise stated.
63
Table 4.1. Real-Time PCR Primer Details.
Gene
GenBank
Accession
Number
Forward Primer (5’ Æ 3’)
Conc,
µM
Reverse Primer (5’ Æ 3’)
Conc,
µM
IntronExon
Divide
Amplicon
Length
PCR
Efficiency
Atrogin-1
NM_058229
CATCCTTATGTACACTGGTCCAAAGA
6
TCCGATACACCCACATGTTAATG
6
---
74
0.8
β-Actin
NM_001101
AAGCCACCCCACTTCTCTCTAA
2
AATGCTATCACCTCCCCTGTGT
2
---
141
1.1
Cyclin D1
NM_053056
GCATGTTCGTGGCCTCTAAGA
2
CGGTGTAGATGCACAGCTTCTC
2
---
69
1.2
MuRF-1
NM_032588
GGCGTGGCTCTCATTCCTT
6
TCTCCAAGTTCTCCATGGGATT
6
---
81
0.7
Myf5
NM_005593
TTCTACGACGGCTCCTGCATA
4
CCACTCGCGGCACAAACT
4
---
67
1.2
Myf6
NM_002469
CACCCTGCGCGAAAG
2
CACAGTTCGCCGCTTCAGT
2
---
70
1.1
MyoD
NM_002478
CCGCCTGAGCAAAGTAAATGA
4
GCAACCGCTGGTTTGGAT
4
---
74
1.0
myogenin
NM_002479
GGTGCCCAGCGAATGC
2
TGATGCTGTCCACGATGGA
2
exon 2 & 3
155
0.9
Myostatin
NM_005259
CCAGGAGAAGATGGGCTGAA
2
CAAGACCAAAATCCCTTCTGGAT
2
exon 2 & 3
82
0.8
p21
NM_000389
GGCAGACCAGCATGACAGATTT
6
GGCGGATTAGGGCTTCCTCT
6
---
73
0.9
p27
NM_004064
CGGTGGACCACGAAGAGTTAA
2
GGCTCGCCTCTTCCATGTC
2
---
66
0.9
PCNA
NM_002592
CTAAAATGCGCCGGCAAT
2
GCTTCAAATACTAGCGCCAAGGT
2
exon 2 & 3
155
1.0
Primer sequences were designed using Primer Express Version 2 software (Applied Biosystems) using sequences accessed through GenBank and checked for specificity using
Nucleotide-Nucleotide Blast search (http://www.ncbi.nlm.gov/BLAST/). Exon information was obtained from the Ensembl Genome Database (http://www.ensembl.org/). The
concentrations of forward and reverse primers are indicated along with the intron-exon divide the primers were designed around (if possible) and amplicon size in base pairs.
MuRf-1, muscle ring finger protein 1; PCNA, proliferating cell nuclear antigen.
64
III. RESULTS
10 male subjects performed 3 sets of 12 maximal concentric and eccentric isokinetic
exercises with 2 minutes rest between each set. Peak torque was 229.6 ± 10.1 Nm
and 273.4 ± 9.5 Nm for the concentric and eccentric contractions respectively. To
ensure that the subjects were contracting maximally over the three sets, both
concentric and eccentric torque was recorded for each of the 12 contractions in all
three sets. Figure 4.2 shows that there was no significant difference in either
concentric or eccentric average torque over the three exercise sets. This indicates that
the two minute rest between each set provided sufficient recovery to allow subjects to
contract at or near maximal force throughout the exercise session.
Average Torque (NM)
250
Concentric
Eccentric
200
150
100
50
0
Set 1
Set 2
Set 3
Figure 4.2. Average concentric (white bars) and eccentric (black bars) torque
across the three exercise sets. The data represented is the average of 12
contractions from 10 subjects, ± SEM.
65
A. Cell Cycle Regulators
The markers of cell proliferation, cyclin D1 and PCNA demonstrated no statistically
significant change in their expression patterns however, the expression of both genes
appeared to decrease somewhat, 30 min post exercise (Figure 4.3). p21, a Cdk
inhibitor which blocks progression through the cell cycle, increased dramatically (8.5fold) at 4 hours and remained elevated (7.5-fold) at 24 hours post exercise (p<0.01).
The expression of p27, however, another member of the Cdk inhibitor family, was not
altered at any point following exercise.
Cyclin D1
PCNA
0.06
mRNA expression relative to
β-actin
mRNA expression relative to
β-actin
0.00075
0.00050
0.00025
0.00000
pre
30min
4h
0.05
0.04
0.03
0.02
0.01
0.00
24h
pre
p21
**
0.00125
0.00100
0.00075
0.00050
0.00025
pre
30min
24h
4h
4h
24h
0.00065
mRNA expression relative to
β-actin
mRNA expression relative to
β-actin
0.00150
0.00000
4h
p27
**
0.00175
30min
24h
0.00052
0.00039
0.00026
0.00013
0.00000
pre
30min
Figure 4.3. The effects of a single of bout of heavy resistance exercise on the
expression of cell cycle regulatory factors. Real-time PCR analysis was
performed on Cyclin D1, PCNA, p21, and p27. Values are means ± SEM.
**Significantly different from control (p<0.01)
66
B. Myogenic Regulatory Factors
The single bout of resistance exercise induced a small but significant increase (1.8fold; p=0.01) in MyoD mRNA expression at 4 h although no change in the expression
of Myf5 was observed (Figure 4.4). Myogenin mRNA expression increased 2-fold at 4
hours following exercise (p<0.01) with no change in the expression of Myf6.
Myf5
MyoD
0.0020
*
0.05
mRNA expression relative to
β-actin
mRNA expression relative to
β-actin
0.06
0.04
0.03
0.02
0.01
0.00
pre
30min
4h
24h
0.0015
0.0010
0.0005
0.0000
pre
30min
**
mRNA expression relative to
β-actin
mRNA expression relative to
β-actin
0.15
0.10
0.05
pre
30min
4h
24h
0.6
0.20
0.00
24h
Myf6
Myogenin
0.25
4h
4h
24h
0.5
0.4
0.3
0.2
0.1
0.0
pre
30min
Figure 4.4. The effects of a single of bout of heavy resistance exercise on the
expression of the Muscle Regulatory Factors. Real-time PCR analysis was
performed on Myf5, MyoD, myogenin, and Myf6. Values are means ± SEM.
*Significantly different from control (p<0.05)
**Significantly different from control (p<0.01)
67
C. Myostatin
In addition to examining the cell cycle regulators and MRFs, the expression of a
powerful negative regulator of muscle growth, Myostatin, was investigated (Figure
4.5). As expected, Myostatin showed a marked reduction in expression during the
recovery from exercise with approximately a 2-fold reduction at 4 and 24 hours post
exercise (p<0.01).
Myostatin
mRNA expression relative to
β-actin
0.025
0.020
0.015
**
0.010
**
0.005
0.000
pre
30min
4h
24h
Figure 4.5. The effects of a single bout of heavy resistance exercise on the
expression of myostatin mRNA. Values are means ± SEM.
**Significantly different from control (p<0.01)
68
D. Protein Degradation Pathway
Two ubiquitin ligases, atrogin-1 and muscle ring finger protein 1 (MuRF-1), whose
expression is increases significantly during multiple models of muscle atrophy were
also examined as potential negative regulators of muscle hypertrophy (Figure 4.6).
Interestingly, MuRF-1 expression appeared to increase (2.4-fold) although not
significantly (p=0.07) at 4 hours post exercise. Conversely, atrogin-1 expression
appeared to decrease slightly at 4 hours post exercise, although again not
significantly.
mRNA expression relative to
β-actin
Atrogin-1
0.55
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
pre
30min
4h
24h
4h
24h
MURF-1
mRNA expression relative to
β-actin
0.005
0.004
0.003
0.002
0.001
0.000
pre
30min
Figure 4.6. The effects of a single bout of heavy resistance exercise on the
expression of atrogin-1 and MuRF-1 mRNA. Values are means ± SEM. No
statistical significance was observed (p>0.05).
69
IV. DISCUSSION
Whilst the central role that satellite cells play in skeletal muscle repair and adaptive
hypertrophy has been well established, our understanding of the mechanisms
necessary for, and regulating the satellite cell response is limited. In the present study,
the aim was to investigate the expression of both activators and repressors of the cell
cycle as well as the expression of critical drivers of the muscle phenotype, the MRFs,
following a single bout of resistance exercise.
A. Cell cycle regulators
Crucial to the hypertrophic response is the progression of muscle precursor cells, or
satellite cells through the cell cycle. Whilst it has been clearly established that satellite
cells are activated in response to extensive damage to muscle cells (Vierck et al.
2000) and following heavy resistance exercise training (Kadi and Thornell 2000), it
remains unclear whether a single bout of resistance exercise is capable of stimulating
the entire process of satellite cell activation and differentiation. Therefore the
expression of two markers of cellular proliferation, PCNA (involved in DNA replication)
and cyclin D1 was investigated. Somewhat surprisingly, neither PCNA nor cyclin D1
expression increased following the resistance exercise bout. Whilst the expression of
PCNA, to our knowledge, has not previously been investigated following resistance
exercise, two previous studies (Haddad and Adams 2002; Bickel et al. 2004) found
similar results for cyclin D following a single bout of resistance exercise. Interestingly,
these studies demonstrated that two bouts of exercise seemed sufficient to elicit a
significant increase in the expression of this gene. Collectively, these results seem to
suggest that a single bout of resistance exercise is not sufficient to generate a
measurable increase in the gene expressions of markers of satellite cell proliferation.
Considering the lack of observed changes in markers of proliferation, it was surprising
to observe a marked increase the Cdk inhibitor and mediator of cell cycle arrest, p21.
Although a closely related Cdk-inhibitor family member, p27, showed no changes in
expression following resistance exercise. In view of the very early induction of p21
following the hypertrophic stimulus (4 hours), it seems unlikely that any activated and
proliferating satellite cells (or indeed any other proliferating non-muscle cells) would
have time to reach differentiation.
70
B. Myogenic Regulatory Factors
The results of the present study demonstrated an up-regulation of MyoD and
myogenin expression 4 hours following an acute bout of resistance exercise whilst no
change in the expression of Myf5 and Myf6 was observed. These results support the
results reported previously in human skeletal muscle following a single bout of
resistance exercise (Willoughby and Nelson 2002; Bickel et al. 2003; Psilander et al.
2003). However, the present study is the only study to date to examine the expression
of all four members of the MRF family following a single bout of heavy resistance
exercise.
In addition to the up-regulation of muscle specific genes, the MRFs (in particular
MyoD) interact with cell cycle regulators to promote cell cycle arrest and differentiation
of myogenic cells. Previous studies have indicated that MyoD is capable of inducing
the expression of p21 (Guo et al. 1995; Halevy et al. 1995; Parker et al. 1995) as well
as the other Cdk inhibitors , p27 and p57 (Reynaud et al. 2000) during myogenesis.
Although numerous studies have identified an up-regulation of p21 following
resistance exercise (Carson et al. 2002; Bickel et al. 2003; Welle et al. 2004), its
interaction with the MRFs in regulating this adaptive response has not been
investigated. The results of the present study, with MyoD and p21 both up-regulated 4
h post exercise might suggest cooperation between the Ckd inhibitors and MyoD in
the differentiation signaling pathways in adult skeletal muscle. Similarly, myogenin
mRNA expression, considered one of the earliest markers of differentiation and itself
up-regulated by MyoD, was increased markedly at 4 h post exercise. As mentioned
previously however, it seems highly unlikely that the observed increase in markers of
satellite cell differentiation would be a result of satellite cell activation, proliferation, cell
cycle arrest and differentiation within 4 hours of the exercise stimulus
C. Possible Roles of p21, MyoD and Myogenin
The most likely source of the increased expression of p21, myogenin and MyoD at 4 h
post exercise is the mature myofibres. Previously, the expression of p21, MyoD and
myogenin has been localized in mature myonuclei early after the initiation of an
overload stimulus (Ishido et al. 2004b). However the function of these proteins in
myonuclei of adult myofibres has not been elucidated. It has been clearly established
that myogenin and MyoD regulate the expression of muscle specific genes such as
CKM and MYL. Therefore, it is quiet likely that the increased expression of these
mRNAs in the immediate recovery period following heavy resistance exercise is
71
contributing to the early repair and/or adaptive response of the myofibre such as
increased expression of the contractile filaments and fibre-type transitions. In contrast,
following the exercise stimulus satellite cells would become activated and then from
approximately 24 h undergo DNA synthesis and cell division (proliferation). MyoD and
Myogenin expression would subsequently increase from up to 3 days later regulating
the differentiation, fusion and hypertrophic events (McGeachie and Grounds 1987).
MyoD and p21 have also been considered as effectors of anti-apoptosis (Wang and
Walsh 1996; Zhang et al. 1999; Ishido et al. 2004a). A number of studies have
demonstrated that apoptosis can be induced in skeletal muscle during denervation,
unloading and disease, suggesting that apoptosis may contribute to the loss of
myonuclei and myofibre atrophy under these conditions (Allen et al. 1997; Allen et al.
1999; Yoshimura and Harii 1999; Schmalbruch and Lewis 2000). Similarly,
hypertrophic stimuli such as stretch may elicit apoptotic cell death (Cheng et al. 1995).
p21
contributes
to
protection
against
apoptosis
by
dephosphorylating
the
retinoblastoma protein (Rb). Dephosphorylated Rb inhibits the activation of members
of the E2F family of transcription factors, which are involved in the induction of
apoptosis (Wang et al. 1997; Wang 1997). Furthermore, mice lacking the p21 gene fail
to form myotubes and demonstrate increased apoptotic rates in myoblasts (Walsh
1997; Zhang et al. 1999). Similarly, Rb deficient myotubes demonstrate increased
rates of apoptosis (Zacksenhaus et al. 1996). Ishido (Ishido et al. 2004a) recently
proposed that MyoD might contribute to protection against apoptosis by up-regulating
the expression of p21 during denervation. A theory is proposed whereby MyoD upregulates the expression of p21 in myofibres early in the recovery from heavy
resistance exercise to help protect against apoptotic cell death.
D. Myostatin
In addition to examining the expression of cell cycle regulatory factors and MRFs, we
sought to examine the expression of a powerful negative regulator of skeletal muscle,
myostatin. Myostatin (growth and differentiation factor 8) has demonstrated a
remarkable capacity to regulate skeletal muscle growth such that animals exhibiting
null mutations in the myostatin gene result in a dramatic hypermuscular phenotype
(Grobet et al. 1997; Kambadur et al. 1997; McPherron et al. 1997; McPherron and Lee
1997). Myostatin gene expression is suppressed in human muscle following 9 weeks
of heavy resistance strength training, indicating that it is responsive to changes in the
loading state of the muscle.
72
The results of the present study demonstrated that acute resistance exercise is indeed
capable of a rapid and marked down-regulation of the myostatin gene. Myostatin
appears to inhibit muscle hypertrophy via two independent pathways. Firstly, it inhibits
the progression of myoblasts through the cell cycle via the up-regulation of p21
(Thomas et al. 2000; McCroskery et al. 2003). Secondly, myostatin can also inhibit
differentiation through the up-regulation of Smad3; Smad3 subsequently binds and
represses the transcriptional activity of MyoD. As a result, the expression of several
regulatory factors is reduced (myogenin, p21, Myf5, Rb), which results in improper cell
cycle arrest and inhibition of myoblast differentiation (Allen and Boxhorn 1989;
Langley et al. 2002; Rìos et al. 2002). Resistance exercise appears to regulate the
transcriptional activity of myogenin such that its atrogenic effect is mitigated during
recovery.
E. Protein Degradation Pathway
Several recent studies have indicated that muscle growth is not only reliant on
anabolic processes but also on the suppression of protein breakdown (Sacheck et al.
2004; Stitt et al. 2004). During atrophy, there is an increase in the amount of
components of the ubiquitin-protein conjugates and increased transcription of
components of the ubiquitin degradation pathway (Bodine et al. 2001a; Haddad et al.
2003a; Haddad et al. 2003b). Two of the most sensitive markers of muscle atrophy
are the mRNA expression of two muscle specific ubiquitin-ligases, atrogin-1 and
muscle ring finger protein 1 (MuRF-1) (Sacheck et al. 2004). Rapid suppression of
atrogin-1 and MuRF-1 mRNA has recently been demonstrated following a
hypertrophic stimulus in vitro suggesting that inhibition of the protein degradation
pathway is an important component of muscle growth (Sacheck et al. 2004).
The significance of the inhibition of the protein degradation pathways in human
skeletal muscle hypertrophy has not, to our knowledge, been investigated.
Surprisingly, atrogin-1 expression demonstrated only a small non-significant reduction
in expression, whilst MuRF-1 mRNA levels appeared to increase, although again not
significantly. The lack of reduction in the expression of these genes observed in this
study contrasts with previous in vitro work (Sacheck et al. 2004). The hypertrophic
stimulus (IGF-1 stimulation of myogenic cells) employed by Sacheck et al. is likely to
promote a greater hypertrophic response to that induced by a single bout of resistance
exercise. Therefore a pronounced reduction in the expression of these genes might be
observed following a more powerful, prolonged hypertrophic stimulus in vivo (e.g.
resistance exercise training).
73
The activation and proliferation of satellite cells has been identified as a critical
component of adaptive skeletal muscle hypertrophy. Despite recent advances in our
understanding of the importance of satellite cells, many questions remain
unanswered. The early induction of p21, MyoD and myogenin following resistance
exercise likely preclude the involvement of satellite cells in the very early adaptive
response to resistance exercise. Therefore, it is possible that the increased
expression of these mRNAs in the immediate recovery period following heavy
resistance exercise is contributing to the early repair and/or adaptive response of the
myofibre.
74
CHAPTER FIVE
IDENTIFICATION OF NOVEL GENES RESPONSIVE
TO ACUTE RESISTANCE EXERCISE
I. INTRODUCTION
There is mounting evidence in support of the view that skeletal muscle hypertrophy
results from the complex and coordinated interaction of numerous signalling
pathways. Well characterised components integral to skeletal muscle adaptation
include the IGF-1 mediated activation of the PI3K-Akt pathway, transcriptional activity
of the members of the myogenic regulatory factors, numerous secreted peptide growth
factors, and the regenerative potential of satellite cells. Whilst studies investigating
isolated components or pathways have enhanced our current understanding of
skeletal muscle hypertrophy, our knowledge of how all of these components react in
concert to a common stimulus remains limited. Moreover, as it is estimated that
approximately 40% of the 30,000 - 40,000 definitive genes in the human genome have
undefined functions, it is likely that numerous genes integral in skeletal muscle
hypertrophy are yet to be characterised (Blumenthal 2001). Receiving increasing
focus has been the identification of novel genes that may play roles in the regulatory
network through which muscle cells coordinate growth, adaptation and repair.
Gene expression profiling technology permits the parallel assessment of expression
levels of thousands of genes and may lead to a better understanding of the signalling
pathways activated in skeletal muscle in response to a hypertrophic stimulus. A
number of recent studies have all employed microarray technology to examine global
gene expression in skeletal muscle following exercise. Carson (Carson et al. 2002)
examined gene expression following synergist ablation-induced functional overload in
rats whilst Chen (Chen et al. 2002) and Barash (Barash et al. 2003) examined the
transcriptional response of muscle to eccentric contractions in rats and mice
respectively. Jozsi (Jozsi et al. 2000) used filter arrays to examine both the influence
of age and exercise on skeletal muscle expression profiles, Zambon (Zambon et al.
2003) examined the effects of circadian rhythms and exercise on skeletal muscle gene
expression and finally Chen (Chen et al. 2003) investigated the molecular response of
human skeletal muscle to eccentric contractions. Whilst each study has provided
75
valuable progress towards the overall understanding of skeletal muscle adaptation to
exercise, many questions remain unanswered.
The primary purpose of the present study was to use microarray technology to study
the transcriptional changes during the 24 hours following an acute bout of resistance
exercise. Importantly, a time-course approach was chosen for this analysis in order to
capture a more thorough picture of the molecular changes occurring at different times
throughout the recovery period. Specifically the time-points selected provide a glimpse
into the early responding and transient genes as well as genes with more prolonged or
delayed responses to resistance exercise.
76
II. METHODS
A. Subjects
Ten healthy male subjects volunteered to participate in this study. Informed written
consent was obtained from each subject before participation in the study, after the
nature, purpose and risks of the study were explained. Age, height and weight were
on average 27.1 ± 2 years, 179.3 ± 1.6 cm, and 78.4 ± 2.7 kg (means ± SE).
Concentric and eccentric maximal voluntary contraction of the quadriceps was 229.6 ±
10 Nm and 273.4 ± 9.5 Nm respectively. Exclusion criteria included resistance training
within the past six months or previous history of a diagnosed condition or illness that
would endanger the subjects during strenuous resistance exercise. All experimental
procedures involved in this study were formally approved by the Deakin University
Ethics Committee.
B. Familiarisation
Familiarisation was conduced as described previously (Chapter 4, section II, part B).
C. Experimental Design
The experiment was conducted as described previously (Chapter 4, section II, part C).
D. Muscle Biopsy Procedure
The muscle biopsy was performed as previously described (Chapter 4, section II, part
D).
E. Microarray Production
The skeletal muscle specific microarray was prepared as described previously
(Chapter 2, section II, part A).
77
F. RNA Extraction
Total RNA was extracted from skeletal muscle biopsy samples by a two-step
procedure using Trizol Reagent followed by purification using RNeasy columns
(Qiagen, Mannhiem, Germany) according to the manufactures instructions (Qiagen
2001). Briefly, frozen muscle was homogenised using a rotor-stator homogenizer in an
appropriate volume of Trizol. Chloroform was added to the solution, thoroughly mixed,
incubated on ice for 5 mins followed by centrifugation at 4°C for 15 min. The upper
aqueous layer was removed and mixed with an equal volume of 70% ethanol before
being added to the RNeasy spin column. After washing the column, the RNA was
eluted as described in the manufacture’s protocol. RNA quality and concentration was
determined using the Agilent 2100 Bioanalyzer (Agilent Technologies, Inc., Palo Alto,
CA)
G. Indirect labelling of cDNA
Fluorescently labelled cDNA was prepared from equal quantities of total RNA using an
indirect labelling method as described previously (Chapter 2, section II, part C). The
reference RNA used for this study was a commercially available human skeletal
muscle RNA (Ambion, Austin, TX).
H. Image Acquisition and Data Analysis
Fluorescent images of the microarrays were acquired using the GenePix 4000B laser
scanner (Axon Instruments, Inc., Union City, CA) and the images processed using
Genepix Pro3 software (Axon Instuments). Data files were entered into Acuity 4.0
software (Axon Instruments) where a global normalisation strategy was applied to
normalise between arrays. Flagged spots and spots with less than 55% of feature
pixels with intensities more than two standard deviations above the background pixel
intensity were not retained for further analysis. Furthermore, genes had to be present
in at least 70% of arrays to be considered in the analysis. Initially, self organising map
clustering analysis was performed to provide an overall picture of the pattern of gene
expression. Clustering is mainly applied to microarray data in order to reduce the
dimensions of the data and to provide visualisations of the complex microarray
experiment, but are also particularly useful if current knowledge of the transcriptional
patterns of the biological system is limited (Hautaniemi et al. 2003). Importantly, once
the data is grouped, the investigator needs to visually identify and interpret the results
of the clustering.
78
Following clustering analysis, the expression of genes contained within individual
clusters
was
examined
more
closely.
Statistical
analysis
revealed
genes
demonstrating consistent and marked changes in each of the 10 subjects, over the
time-course of recovery from exercise. Using the statistical analysis tools provided
within the microarray analysis package Acuity 4.0, we calculated paired t-tests to
explore the changes in each time-point compared to control. However in order to
minimise the false discovery rate and lack of power for appropriate statistical analysis,
we chose to confirm all discussed novel gene changes with quantitative real-time PCR
and more stringent statistical analysis.
I. Clone Identification
Selected cDNA clones were grown overnight and plasmid isolation was conduction
using the QIAprep Spin Miniprep Kit (Qiagen) according to the manufacturer’s
instructions. Inserts were PCR amplified using 5’-amino modified vector specific
primers. Products were visualized by agarose gel electrophoresis then excised and
the sequence was determined using a BigDye Terminator Cycle Sequencing Ready
Reaction Kit (Applied Biosystems). The resultant sequence was entered into BLAST
(www.ncbi.nlm.nih.gov/BLAST/) to ascertain its homology to known gene sequences.
J. Real-time PCR Analysis
1. RNA Extraction
RNA was extracted from skeletal muscle samples (5-10mg) as described previously
(Chapter 4, section II, part E.1).
2. cDNA Synthesis
Reverse transcription was conduced as described previously (Chapter 3, section II,
part H.2).
3. Primer Design
To perform PCR, specific primers were designed for all genes using Primer Express
software (Applied Biosystems, Foster City, CA) as described previously (Chapter 3,
section II, part H.3) See Table 5.1 for details.
79
4. Real-time PCR Reaction
The real-time PCR reaction was conduced as previously described (Chapter 3, section
II, part H.4).
5. PCR Efficiency
PCR efficiency was conducted as previously described (Chapter 3, section II, part
H.5). See table 5.1 for details.
6. PCR Analysis and Endogenous Control Selection
PCR analysis and analysis of the endogenous control was conducted as previously
described (Chapter 4, section II, part H.6).
K. Statistical Analysis
Statistical analysis was performed using GraphPad Prism 4.1 (GraphPad Software,
San Diego, CA). Means were compared using a one-way ANOVA and any significant
differences analysed using a Dunnet’s multiple comparison test. Data is presented as
mean ± standard error of the mean (SEM). A probability level of <0.05 was adopted
throughout to determine statistical significance unless otherwise stated.
80
Table 5.1. Real-Time PCR Primer Details.
Gene
GenBank
Accession
Number
Forward Primer (5’ Æ 3’)
Conc,
µM
Reverse Primer (5’ Æ 3’)
Conc,
µM
Exon
Divide
Amplicon
Length
PCR
Efficiency
ASB5
AY057053
AAATGCAGTAACCTTAGACCATGTCA
2
ACATGCCACGTGATCTCCAA
2
---
67
0.8
β-Actin
NM_001101
AAGCCACCCCACTTCTCTCTAA
2
AATGCTATCACCTCCCCTGTGT
2
---
141
1.1
FLJ38973
NM_153689
GAATGGTTGCAAGGGAGAAA
4
GCGTCATTTAGTGATGGTGGATAA
4
---
87
1.1
MLP
NM_003476
TCAGTCTATGCTGCTGAGAAGGTT
2
GATGGCACAGCGGAAACAG
2
exon 4 & 5
72
0.8
Myf5
NM_005593
TTCTACGACGGCTCCTGCATA
4
CCACTCGCGGCACAAACT
4
---
67
1.2
Myf6
NM_002469
CACCCTGCGCGAAAG
2
CACAGTTCGCCGCTTCAGT
2
---
70
1.1
MyoD
NM_002478
CCGCCTGAGCAAAGTAAATGA
4
GCAACCGCTGGTTTGGAT
4
---
74
1.0
myogenin
NM_002479
GGTGCCCAGCGAATGC
2
TGATGCTGTCCACGATGGA
2
exon 2 & 3
155
0.9
Myostatin
NM_005259
CCAGGAGAAGATGGGCTGAA
2
CAAGACCAAAATCCCTTCTGGAT
2
exon 2 & 3
82
0.8
TTS2.2
XM_290535
CAGACGGCGAGAATGTCATTATAT
4
TGCAGACATTGGCCTGGA
4
exon 2 & 3
69
0.7
TXNIP
NM_006472
AGATCAGGTCTAAGCAGAACA
4
TCAGATCTACCCAACTCATCTCAGA
4
---
73
1.0
Primer sequences were designed using Primer Express Version 2 software (Applied Biosystems) using sequences accessed through GenBank and checked for specificity
using Nucleotide-Nucleotide Blast search (http://www.ncbi.nlm.gov/BLAST/). Exon information was obtained from the Ensembl Genome Database (http://www.ensembl.org/).
The concentrations of forward and reverse primers are indicated along with the intron-exon divide the primers were designed around (if possible) and amplicon size in base
pairs. ASB5, ankyrin repeat and SOCs box-containing 5; MLP, muscle LIM protein; TXNIP, thioredoxin interacting protein; TTS2.2, transport secretion protein 2.2
81
III. RESULTS
A. Microarray results
Gene expression profiling analysis was performed using a customised human skeletal
muscle cDNA microarray during the recovery from an acute bout of resistance
exercise. Since the majority of the spots on the microarray were derived from a human
skeletal muscle cDNA library, specifically designed for the analysis of gene expression
in human skeletal muscle, it was not surprising to see that 7,229 elements out of the
11,000 showed adequate expression levels, indicating a high degree of hybridisation
to the array. Initially, self organising map clustering analysis was performed to provide
an overall picture of the pattern of gene expression changes during the recovery from
resistance exercise. Clustering in microarray experiments utilise algorithms that
typically result in groups of genes whose member’s exhibit similar expression profiles.
Thus clustering methods offer convenient ways to illustrate data. Figure 5.1 shows a 3
× 2 self organising map whereby genes were grouped together based on similar
patterns of expression. Cluster A contains genes showing a reduction in expression
following resistance exercise, whilst clusters B and C contain genes with increased
expression levels following exercise. Subsequently, the expression patterns in each of
these clusters was examined more closely in order to isolate elements that
demonstrated the most statistically significant and dramatic changes in expression
and importantly, consistent patterns of expression across all subjects.
82
Pre
30min
4h
24h
Pre
30min
4h
24h
Pre
A
B
C
D
E
F
30min
4h
24h
Figure 5.1. 3 × 2 self organising map representation of the patterns of gene expression observed following a single bout of endurance exercise.
Subjects completed an acute bout of resistance exercise consisting of 3 sets of 12 repetitions of maximal leg extension. Biopsies were taken before
exercise (pre), at 30 min, 4 h, and 24 h post exercise. Self organising map was used to group genes based on their expression profiles. Each gene
element is represented vertically, and the time points are shown horizontally. The expression ratios for each gene at each time point are colour coded:
red, increased expression compared to reference RNA; green reduced expression compared to reference RNA.
The average results of ten subjects are presented.
83
1. Known skeletal muscle genes
In addition to the unknown gene elements derived from the skeletal muscle cDNA
library, 270 genes with known functional roles in skeletal muscle were selected for
printing on to the microarray. Following hybridisation however, it appeared that only a
fraction of the selected genes demonstrated adequate expression levels. The
remainder of the known genes provided little or no expression data and were therefore
unsuitable for further analysis. The reasons for the poor hybridisation levels in this
subset of genes are unclear. The results of the remaining genes which demonstrated
adequate expression must therefore be interpreted with a degree of caution. We
identified 11 genes that demonstrated an increase in their mRNA expression following
the acute bout of resistance exercise (Table 5.2). Whilst a further eight genes were
identified as showing a reduction in expression following exercise (Table 5.3).
Table 5.2. List of genes with increased mRNA abundance in response to an acute
bout of resistance exercise. The mRNA expression for each gene derived from the
microarray analysis is presented as fold change from the resting (pre) value.
FOLD CHANGE
GENE NAME
30 MINS
4 HOURS
24 HOURS
1.22
1.20
1.10
Intracellular signalling
CDC-like kinase 2
Metabolism
COX7c
1.24
1.38
1.12
DLAT
1.50
-1.11
1.15
GLUT4
-1.10
1.10
1.21
PDK4
3.21
1.54
1.10
Serpine1
2.03
1.81
2.29
SNAP 29
-1.25
1.02
1.32
1.16
1.00
1.14
1.00
1.34
1.08
HSP27
1.43
1.51
1.56
NFκB1
-1.14
1.27
1.32
Regulatory proteins
Structural / contractile proteins
Dystrophin
Transcription
PGC-1
Abbreviations: COX7c, cytochrome c oxidase, subunits VIIc; DLAT, dihydrolipoamide Sacetyltransferase;
PDK4, pyruvate dehydrogenase kinase, isoenzyme 4; SNAP 29,
synaptosomal-associated protein, 29 kDa; PGC-1, peroxisome proliferators-activated
receptor-gamma, coactivator 1; HSP27, heat shock 27-kDa protein; NFκB1, nuclear factor
kappa-B, subunit 1
84
Table 5.3. List of genes with decreased mRNA abundance in response to an acute
bout of resistance exercise. The mRNA expression for each gene derived from the
microarray analysis is presented as fold change from the resting (pre) value.
30 MINS
FOLD CHANGE
4 HOURS
24 HOURS
PIK3R1
-1.43
-1.25
1.01
STAT3
-1.52
-1.01
1.05
ATP5I
-1.54
-1.04
-1.09
Enolase 3
-1.10
-1.16
-1.28
GOT2
-1.14
-1.22
-1.25
UQCRC2
-1.49
-1.32
1.07
Decorin
-1.01
-1.19
-1.61
α-actinin 1
-1.05
-1.19
-1.43
GENE NAME
Intracellular signalling
Metabolism
Structural / contractile proteins
Abbreviations: PIK3R1, phosphatidylinositol 3-kinase, regulatory 1; STAT3, signal
transducer and activator of transcription 3; ATP5I, ATP synthase, H
+
transporting,
mitochondrial F0 complex, subunit E; GOT2, glutamate oxaloacetate transaminase,
mitochondrial; UQCRC2, ubiquinol-cytochrome c reductase core protein II.
2. Unknown cDNA clones
Due to the nature of the array construction, all cDNAs spotted from the cDNA library
are unknown until sequencing analysis is performed. As it is impractical to sequence
all differentially expressed genes, a subset of these genes were selected for
sequencing. Only genes showing consistent expression across the majority of the ten
subjects, and showing the greatest statistically significant fold change from the control
biopsy were selected for sequencing. In order to obtain a good cross section of both
early and late responding genes, elements were selected that showed differential
expression at each, but not necessarily all time-points. In total, 19 elements were
sequenced, with 15 individual genes identified as shown in Table 5.4.
85
Table 5.4. List of genes identified using microarray analysis with increased mRNA
abundance in response to an acute bout of resistance exercise. The mRNA
expression for each gene derived from the microarray analysis is presented as fold
change from the resting (pre) value.
FOLD CHANGE
GENE ID
M02e13
M07d10
M11h23
M13d6
M13e13
M17j10
M17j8
M20a22
M20p18
M20k22
M21h1
M23a7
M23m3
M23n22
M12i11
M24n10
M28p16
M29p15
M31n6
M32i7
M34j8
M46d2
M52i5
GENE NAME
Crystallin, alpha B
Leiomodin 2 (cardiac)
HNRPH1
Synaptopodin 2
TXNIP
MLP
MLP
ASB5
Filamin C, gamma
NADH dehydrogenase 1 β
TXNIP
LRP16 protein
Troponin I
RNA binding motif protein 8A
MLP
FLJ38973
HSP27
α-tropomyosin
COX6B
PDK4
TTS2.2
ASB5
HSP40
30 MINS
4 HOURS
24 HOURS
1.32
1.24
1.10
1.26
1.72
-1.10
1.15
-1.33
1.09
1.05
1.68
1.34
2.25
1.03
1.13
1.62
1.39
-1.02
1.00
1.80
-1.06
1.16
1.11
1.12
1.79
1.09
-1.25
-1.69
1.75
1.41
2.95
1.58
1.31
-2.38
1.25
-1.79
1.70
1.47
2.18
1.71
1.25
1.30
1.37
1.21
2.41
1.91
-1.10
1.76
1.30
1.02
-1.16
2.39
1.81
1.80
2.16
1.51
-1.43
1.21
-1.11
1.94
1.74
1.69
1.80
0.87
1.18
-1.05
-1.05
1.92
1.83
Abreviations: HNRPH1, Heterogeneous nuclear ribonucleoproteins H1; TXNIP, thioredoxin
interacting protein; MLP, muscle LIM protein; ASB5, ankyrin repeat and SOCS boxcontaining 5; HSP27, heat shock 27-KD protein; COX6B, cytochrome c oxidase subunit VIb;
PDK4, pyruvate dehydrogenase kinase; TTS2.2, transport secretion protein 2.2; HSP40
heat-shock 40-kDa protein 1.
Of the 15 genes identified, 5 were selected for further analysis. The genes selected,
ankyrin repeat and SOCS box-containing 5 (ASB5), thioredoxin interacting protein
(TXNIP), muscle LIM protein (MLP), unknown protein FLJ38973 and transportsecretion protein 2.2 (TTS2.2) all showed marked changes in expression and
represented potentially interesting candidates for roles in the adaptive response to
resistance exercise. Extensive bioinformatical analysis was performed on the selected
genes to identify the gene sequence, transcript structure, amino acid profile in addition
to known or predicted functions of the protein. The databases searched for this
analysis
included,
Ensemble
(http://www.ensembl.org/),
GeneCards
86
(http://bioinfo.weizmann.ac.il/cards/index.shtml) and the Entrez suit of databases
(http://www.ncbi.nlm.nih.gov/Entrez/). Information on each of the selected genes was
readily available from these databases and is presented in Appendices A-D.
Further analysis and confirmation of the microarray data was performed using
quantitative real-time PCR on ASB5, TXNIP, MLP, FLJ38973 and TTS2.2 (Figure 5.2).
The results of the real-time PCR analysis generally supported the microarray results
with one exception, TTS2.2. FJL38973 gene expression increased markedly (~2-fold)
although not significantly at 4 hours post exercise. ASB5 mRNA expression increased
significantly at 4 hours (~3-fold increase, p<0.01) which remained elevated at 24hours
(~2.3-fold). MLP expression markedly increased (~4-fold increase, p<0.01) 24 hours
following the exercise bout. Whilst TXNIP showed a marked (~10-fold increase,
p<0.01) albeit transient increase at 30 minutes followed by a rapid return to resting
levels by 4 hours.
87
FLJ38973
ASB5
0.0025
0.0020
0.0015
0.0010
0.0005
0.0000
**
0.25
mRNA expression relative to
β-actin
mRNA expression relative to
β-actin
0.0030
pre
30min
4h
0.20
0.15
0.10
0.05
0.00
24h
*
pre
30min
4h
24h
4h
24h
TXNIP
MLP
1.0
0.8
0.6
0.4
0.2
0.0
**
0.08
**
pre
30min
4h
24h
4h
24h
mRNA expression relative to
β-actin
mRNA expression relative to
β-actin
1.2
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00
pre
30min
TTS2.2
mRNA expression relative to
β-actin
0.0035
0.0030
0.0025
0.0020
0.0015
0.0010
0.0005
0.0000
pre
30min
Figure 5.2. Real-time PCR results for selected genes. Subjects completed an
acute bout of resistance exercise consisting of 3 sets of 12 repetitions of maximal
leg extension. Biopsies were taken before exercise (pre), at 30 min, 4 h, and 24 h
post exercise. Bars represent mean ± SEM, average of 10 subjects.
* Significantly different from control, p<0.05
** Significantly different from control, p<0.01
88
IV. DISCUSSION
Gene expression profiling analysis was performed using a customised human skeletal
muscle cDNA microarray during the recovery from an acute bout of resistance
exercise. Muscle biopsies were taken from the vastus lateralis muscle before, 30 min,
4 h and 24 h after the exercise bout. An examination of the transcriptional events over
the time-course of 24 hours was employed to monitor both early and transient
responses to the exercise as well as delayed or sustained gene changes. Thus the
chances of identifying novel genes with important roles in the response to resistance
exercise was far greater than by simply examining a single time point post exercise. In
addition to the examination of potentially novel genes, a selection of genes with known
or potentially interesting roles in skeletal muscle was included in the development of
the microarray.
Expression analysis of these known genes revealed 11 up-regulated genes. Of note
was the increase in PDK4, previously recognised for its rapid increase during and after
more prolonged endurance type exercise (Pilegaard et al. 2000; Hildebrandt et al.
2003; Pilegaard and Neufer 2004). As well as the increase in expression of HSP27
and NFκB1, two genes that have previously been implicated in mediating cellular
stress responses (Kumar and Boriek 2003; Thompson et al. 2003). In contrast, nine
genes demonstrated slight decreases in expression following the resistance exercise
bout. Surprisingly, the magnitude of gene changes, were on the whole, somewhat
smaller than expected although consistent with the degree of change in general that
has been observed previously using microarray following acute resistance exercise
(Zambon et al. 2003).
The second aspect to this study involved the examination of the expression patterns of
genes derived from a human skeletal muscle cDNA library. A subset of genes
demonstrating markedly increased expression following the resistance exercise bout
was selected for sequencing and further analysis. Whilst only genes showing
increased expression were sequenced for this analysis, it is anticipated that similar
analysis will be conducted for genes exhibiting down-regulation expression. In total, 19
cDNA clones were sequenced with 15 individual genes identified following sequencing
and bioinformatics analysis. Importantly, two of these genes, PDK4 and HSP27 were
also identified as showing increased expression in the analysis of the known skeletal
muscle genes. In addition to HSP27, the expressions of two further heat shock
proteins (HSP40 and alpha-2-B crystallin) were also shown to increase following
89
resistance exercise. The increased expression of these proteins has been linked to
the facilitation of muscle repair and remodelling following damaging exercise as well
as providing considerable protection against subsequent periods of resistance type
exercise (Neufer et al. 1998; Thompson et al. 2001; McArdle et al. 2002; Thompson et
al. 2003).
From the 15 genes identified, five genes were selected for further analysis based on:
(1) the statistically significant degree of change demonstrated by the microarray
expression analysis, (2) their unique nature, and/or (3) their known or potentially
important role in skeletal muscle. The genes selected were TTS2.2, hypothetical
protein FLJ38973, ASB5, MLP, and TXNIP. Real-time PCR validation confirmed the
expression of all but TTS2.2 which showed no change in expression following
exercise and was subsequently excluded from further analysis. The reasons for the
incongruent results from the two analytical techniques are unclear however it may
reflect inadvertent measurement of the expression of a closely related unidentified
gene or perhaps differential exon usage of the gene itself.
MLP (also referred to as CRP3) was originally discovered in denervated skeletal
muscle and identified as a positive regulator of the myogenic program in myogenic
cells (Arber et al. 1994). MLP belongs to the LIM superfamily of proteins and consists
of two tandem LIM motifs each followed by a glycine-rich region that serve as points of
interaction with other proteins (Arber et al. 1994; Bach 2000). Detected exclusively in
skeletal and cardiac muscle, MLP has been shown to be up-regulated in fast muscle
by enhanced contractile activity (Schneider et al. 1999) as well as during the transition
to slower phenotypes (Willmann et al. 2001) in rats and mice respectively.
Furthermore, MLP transcripts have been shown to be induced during C2C12 myocyte
differentiation (Arber et al. 1994; Shen et al. 2003) as well as being up-regulated
during the recovery from eccentric contraction in the tibialis anterior muscles of mice
(Barash et al. 2003).
To our knowledge this is the first study to measure the up-regulation of MLP in human
skeletal muscle following an acute bout of resistance exercise. Whilst the exact
function of MLP in muscle adaptive response to contractile activity is not discernable
from this study, mice homozygous null for MLP exhibit highly disorganised cytoskeletal
architecture and decreased cell-cell interactions (Arber et al. 1997) suggesting critical
roles in the development of muscle structure and function. Further to this MLP has
been observed to interact with the structural proteins β1-spectrin, telethonin and αactinin suggesting that it may be involved in facilitating the assembly or stabilization of
the myofibril apparatus (Flick and Konieczny 2000) in addition to a potential role in the
90
mechanical stretch sensor machinery (Knoll et al. 2002). The understanding of the
mechanistic actions of MLP is further confounded however by its dual sub-cellular
localization, initially expressed exclusively in the nucleus early in muscle differentiation
and later translocating to the cytoplasm (Arber et al. 1994). Interestingly, nuclear MLP
appears to positively regulate myogenesis through the interaction with the myogenic
transcription factors, MyoD, Myf6 and myogenin (Kong et al. 1997). Collectively these
data seem to suggest multiple complementary roles for MLP in sensing mechanical
stretch, regulating the subsequent transcriptional response and ultimately facilitating
the assembly or stabilization of the contractile apparatus. Thus it appears that in
response to a stimulus like resistance exercise, MLP plays a critical and coordinated
role in the repair and adaptation of skeletal muscle.
Thioredoxin-interacting protein (TXNIP), also known as vitamin-D3 up-regulating
protein-1 or thioredoxin-binding protein-2, is the endogenous inhibitor of thioredoxin, a
major regulator of cellular redox state. Several recent studies, through examination of
the TXNIP-null mouse, have established a causal relationship between the loss of
TXNIP and disregulated carbohydrate and lipid metabolism (Donnelly et al. 2004; Hui
et al. 2004; Van Greevenbroek et al. 2004). Furthermore, TXNIP has been described
as a stress responsive gene that regulates cardiac hypertrophy and cardiomyocyte
viability through interaction with thioredoxin. In contrast to the present study however,
expression
of
TXNIP
was
rapidly
suppressed
by
biomechanical
strain
in
cardiomyocytes (Wang et al. 2002) and by transverse aortic constriction in vivo
(Yoshioka et al. 2004). Importantly, pathological cardiac hypertrophy is characterized
by diminished contractility and ultimately congestive heart failure, whilst skeletal
muscle hypertrophy is characterized by enhanced muscle contractility and strength
gains. Although cardiac and skeletal muscle hypertrophy share elements of common
signalling pathways (Molkentin and Olson 1996), it is likely that there exist numerous
divergent regulatory mechanisms providing a potential explanation for these
paradoxical results.
Whilst the mechanisms regulating TXNIP expression or the significance of its
observed increase in response to exercise cannot be elucidated from this study, its
marked, early induction is of interest. TXNIP is readily inducible by various stress
stimuli including H202, TGF-β and heat shock (Junn et al. 2000). We have
demonstrated here that an acute bout of resistance exercise is sufficient to increase
the expression of several markers of cellular stress (HSP27, HSP40, alpha-2-B
crystallin). As such, it is interesting to speculate that the very rapid and transient
increase in TXNIP might constitute an early signalling response to the stress imposed
91
by the exercise. The exact function of TXNIP in skeletal muscle and its role in the
response to resistance exercise however requires further investigation.
Ankyrin repeat and SOCS box-containing 5 (ASB5) is a member of the asb family,
which is characterized by a non-conserved N-terminus, a various number of ankyrin
repeats as well as a C-terminal SOCS box (Kile et al. 2000). To date only one study
has investigated the expression of ASB5 which observed its up-regulation in growing
collateral arteries following femoral ligation (Boengler et al. 2003). The authors noted
an increased expression of ASB5 in both endothelial and smooth muscle cells which
proliferate rapidly during collateral artery growth. Interestingly, these studies indicated
that ASB5 is expressed predominately in skeletal muscle and to a lesser extent in
cardiac muscle (Kile et al. 2000; Boengler et al. 2003). Moreover, ASB5 proteins have
been localized in some satellite cells whilst mature myocytes themselves do not
appear to express this protein (Boengler et al. 2003). These data, combined with the
marked up-regulation in skeletal muscle presented here, suggest a role for ASB5 in
the recovery and adaptation from resistance exercise. Since ASB5 has been shown to
be up-regulated in actively proliferating cells, we speculate that this protein might
constitute a novel molecule involved in the proliferation of satellite cells in response to
a hypertrophic stimulus. Similarly, since skeletal muscle biopsies contain a mixture of
cells types (e.g. myofibers, satellite cells, fibroblasts, endothelial cells, smooth muscle
cells, and nerve cells), the increase in ASB5 might not reflect changes in muscle cells
at all. Capillary proliferation is an important feature of skeletal muscle hypertrophy
(Hather et al. 1991; McCall et al. 1996; Kadi et al. 1999; Chen et al. 2003; Degens et
al. 2003a; Degens et al. 2003b). Moreover, elevated markers of capillarisation
including vascular endothelia growth factor (VEGF) mRNA and protein expression are
evident following compensatory hypertrophy before increased capillary growth is
evident (Takahashi et al. 2002; Degens et al. 2003b). Since ASB5 expression has
been identified during arteriogenesis, it is plausible that the increased ASB5
expression observed in the present study might be associated with capillary growth
rather than a muscle specific adaptation. Therefore it would be of interest to further
examine importance of ASB5 during the response of skeletal muscle to a hypertrophic
stimulus, both within muscle cells and surrounding supportive structures.
The hypothetical protein FLJ38973, because of its novel character, represented a
potentially interesting gene to investigate further. FLJ38973 was originally identified
during a large-scale screen of ESTs for the purpose of identifying the full-open reading
frame cDNA sequence for each human and mouse gene (Mammalian Gene Collection
Program Team et al. 2002). Whilst no subsequent study has investigated FLJ38973,
bioinformatics analysis using AceView (http://www.aceview.org/) revealed that it is
92
located on chromosome 2 and produces, by alternative splicing, 2 different transcripts
(aDec03, bDec03) together encoding 2 different protein isoforms. PSORT II analysis
(http://psort.nibb.ac.jp), trained on yeast data, predicts that the subcellular location of
this protein is most likely in the nucleus (43%) or in the mitochondria (43%). Less likely
possibilities are in the cytoplasm (13%). We report here, for the first time that the
hypothetical protein FLJ38973, is found in skeletal muscle and that its mRNA levels
increase following a bout of resistance exercise in human skeletal muscle. Much work
however is necessary to fully describe the functional role of this protein.
In conclusion, this experiment used microarray technology to examine the
transcriptional response of human skeletal muscle to a single bout of resistance
exercise. The analysis uncovered four interesting genes that have not previously been
examined in this context. The role of these genes in the biological response of muscle
to hypertrophic stimuli such as resistance exercise remains to be determined.
However, their identification constitutes a valuable contribution to our understanding of
the molecular responses of skeletal muscle following resistance exercise.
93
CHAPTER SIX
EXPRESSION OF NOVEL GENES DURING THE
DIFFERENTIATION OF HUMAN PRIMARY
SKELETAL MUSCLE CELLS IN CULTURE
I. INTRODUCTION
Strenuous, growth-inducing exercise is associated with changes in numerous
variables including growth factors, cytokines, cellular damage, sarcoplasmic calcium
concentrations and energy demand. Alterations in any one or more of these factors is
capable of stimulating signal transduction pathways that ultimately regulate the
transcription of genes differentially expressed during muscle hypertrophy (Rennie et
al. 2004). Insulin-like growth factor (IGF-1) is released during skeletal muscle stretch
and overload, and is a potent regulator of muscular growth and repair (Frost and Lang
2003). The most pronounced examples of the anabolic effect of IGF-1 on muscle
growth comes from studies of transgenic animals whereby localised over-expression
of IGF-1 results in a dramatic increase in skeletal muscle mass (Coleman et al. 1995;
Musarò et al. 2001).
Much of our understanding of the signalling mechanisms mediating IGF-1 induced
hypertrophy, and indeed hypertrophy in general have come from the study of myoblast
proliferation and differentiation in culture. The process of muscle hypertrophy has
been described as a recapitulation of the stages of embryonic muscle development
with the proliferation, differentiation and fusion of muscle specific stem cells (satellite
cells) integral to both (Grounds 1991; Chambers and McDermott 1996; Grounds et al.
2002). IGFs are unique among growth factors in that they are capable of stimulating
both proliferation and differentiation of muscle cells in culture. Initially, IGF-1
stimulates proliferation via inhibition of the growth suppressor retinoblastoma (Rb)
protein, and up-regulation of the mRNA expression of proliferative factors including
proliferating cell nuclear antigen (PCNA) and cyclin-dependant protein 1 (cyclin D1)
whilst simultaneously inhibiting the expression of myogenin (Rosenthal and Chen
1995). Following an unknown differentiation signal however, IGF-1 stimulates the
expression of MyoD which in turn up-regulates the expression of the cyclin-dependent
kinase inhibitor p21, ultimately resulting in cell cycle arrest, expression of myogenin
94
and progression towards terminal differentiation (Lawlor and Rotwein 2000; Xu and
Wu 2000).
Central to the terminal differentiation of myoblasts, which is characterised by cell cycle
arrest, expression of muscle specific proteins, formation and maturation of myofibres,
is the expression of the MRFs. The examination of the developmental sequence of
myogenesis has clearly established the temporal pattern of MRF expression and
action. As such the expression of the MRFs along with other muscle specific genes
provides valuable molecular markers for the entire process of muscle development.
Both primary skeletal muscle cell cultures and established muscle cell lines have
become important tools as model systems for skeletal muscle development. The
dividing myoblasts provided by these systems provide great flexibility in studies of
myogenesis in that they remain as activity proliferating cells until growth factors
provided in the medium are withdrawn. Following the reduction of growth factors
below a critical threshold, myoblasts readily cease proliferating and progress towards
terminal differentiation with the expression of muscle specific genes and proteins and
finally fuse with adjacent myoblasts to become syncytial myotubes. Thus these
cultures are readily manipulated allowing the examination of distinct aspects of muscle
development.
Many studies have been carried out on the growth and differentiation of muscle cells
however the vast majority use immortalised rat and mouse muscle cell lines. Although
these studies have highlighted the critical role of IGF-1 in the control of proliferation
and differentiation, these muscle cell lines differ in which IGF binding proteins they
express (James et al. 1993; McCusker and Clemmons 1998; Crown et al. 2000) and
are not identical in their responses to IGFs (Florini et al. 1991). The great advantage
of primary skeletal muscle cell cultures, readily obtainable from adult human muscle
biopsies, is that they provide a more physiologically relevant in vitro model of the
human skeletal muscle phenotype.
Previous studies in this thesis have identified a number of genes that show increased
expression in skeletal muscle following an acute bout of resistance exercise. Three of
these genes: thioredoxin-interacting protein (TXNIP), ankyrin repeat and SOCS boxcontaining 5 (ASB5), and unknown protein FLJ38973, have not been previously
investigated in skeletal muscle and as such provide unique targets for further
investigation into the molecular regulation of hypertrophy. The fourth gene, muscle
LIM protein (MLP), has previously been implicated in skeletal muscle hypertrophy
however the exact functions of this protein in muscle are not completely understood.
95
In an effort to understand the functional roles of these genes in skeletal muscle a
human primary skeletal muscle cell culture model was employed to examine the
expression of the genes during the proliferation, cell cycle arrest and differentiation.
Since IGF-1 is a potent stimulator of muscle hypertrophy, satellite cells in culture were
stimulated to differentiate with serum withdrawal, and serum withdrawal combined with
exogenous IGF-1 administration.
In this study the aim was to identify whether the expression of these genes were (1)
activated at any time during proliferation, cell cycle arrest or differentiation or (2)
activated by the additional mitogenic and myogenic stimulation provided by
exogenous IGF-1. It was hypothesised that the expression of ASB5, TXNIP, MLP,
FLJ38973 and the MRFs would be altered during the differentiation of human
myoblasts in culture.
96
II. METHODS
A. Materials
All media and supplements were purchased from (Gibco, Invitrogen Corporation,
Carlsbad, CA) unless otherwise stated. Primary skeletal muscle growth medium
consisted of minimum essential medium (MEM)-alpha modification with 50 IU/ml
penicillin, 5 µg/ml streptomycin and 10% FBS. Differentiation medium consisted of
MEM-alpha modification with 50 IU/ml penicillin, 5 µg/ml streptomycin and 2% horse
serum to reduce proliferative growth factors. The IGF-1 analogue LongTMR3IGF-1 was
purchased from GroPep, (Adelaide, SA). LongTMR3IGF-1 is a variant of human IGF-I
that contains an amino terminal extension peptide as well as glutamate-3 replaced by
arginine, exhibits very weak binding to IGF-binding proteins and has been shown to
exhibit greater biological activity than natural IGF-1 (Francis et al. 1992; Tomas et al.
1993).
B. Subjects
Human primary skeletal muscle cells were obtained from the vastus lateralis muscle of
8 healthy volunteers (6 males and 2 females, average age 25.1 ± 1.3 years). Informed
written consent was obtained from each subject before participation in the study, after
the nature, purpose and risks of the study were explained. All experimental
procedures involved in this study were formally approved by the Deakin University
Ethics Committee.
C. Human primary skeletal muscle cell cultures
Skeletal muscle samples were excised using the percutaneous needle biopsy
technique (Bergström 1962) modified to include suction (Evans et al. 1982). Human
primary skeletal muscle cells were cultured according to the technique of Gaster
(Gaster et al. 2001). The excised muscle was immersed and extensively washed in
ice-cold Hams F-10 medium before being minced in 0.5% Trypsin/EDTA. Minced
tissue was then digested in 0.5% Trypsin/EDTA at room temperature with agitation for
20 minutes to release the myoblasts. The supernatant containing the myoblasts was
then collected and the process repeated a further two times to break down any
remaining tissue. FBS was subsequently added to the supernatant to a final
97
concentration of 10%. The supernatant was filtered through a 100µm filter to remove
any connective tissue and then spun for 7 minutes at 1600rpm to collect the cells. The
resulting cell pellet was resuspended in α-MEM medium. The cells were then seeded
on to an uncoated flask and incubated at 37°C for 25 minutes to induce fibroblast
attachment, leaving myoblasts suspended in the medium. The medium was aspirated
and seeded on to an extra-cellular matrix-coated (Sigma, St Louis, MO) flask. The
resulting primary cell cultures were maintained in α-MEM medium containing 10%
FBS in humidified air at 37°C and 5% CO2.
D. Experimental conditions
Primary skeletal myoblasts were plated onto plates coated with ECM containing
laminin and entactin derived from Engelbroh-Holm Swarm murine sarcoma cells. In
each experiment, the cells were initially plated in α-MEM medium containing 10% FBS
until 80% confluency was attained. The plating medium was then removed, the cells
were washed twice with PBS and the standard differentiation medium (DM) (α-MEM
containing 2% horse serum) or IGF-1 treated medium (DM+IGF-1) (α-MEM containing
2% horse serum plus 30ng/ml LongTMR3IGF-1) was added. Medium was changed
every 48h throughout the 72 differentiation time-course. Following 2 washes with PBS,
cells were extracted at 12h, 24h, 48h and 72h following the addition of the
differentiation medium. The control for each condition consisted of actively
proliferating cells grown in the maintenance medium and extracted immediately before
the addition of the differentiation medium (0h).
E. Immunocytochemistry
The differentiation potential of our skeletal muscle cell cultures was initially determined
using immunocytochemical staining of myosin heavy chain MHC. MHC expression
was evaluated on cells grown on cover slips in the proliferative state and following 7
days of differentiation in DM. The cells were fixed in cold 100% methanol at -20°C for
10min. Non-specific binding sites were blocked with 1% BSA in PBS followed by
incubation in the primary antibody reactive to skeletal myosin heavy chain (MY-32,
Zymed, San Francisco, CA). Subsequently, the cells were incubated with the
fluorescent secondary antibody, anti-mouse AlexaFluor 488 (Molecular Probes,
Oregon, USA). Nuclei were stained by incubating the cells in the DNA binding dye
Bisbenzimide Hoechst 33285 (Sigma). Immunostained cells were visualised with an
98
Olympus IX70 fluorescent microscope (Olympus, Australia) and digital images
collected (Spot RT slider camera: Image-Pro® Plus Software).
F. Creatine kinase activity
The creatine kinase (CK) activity, an established marker of myoblast differentiation
(Gaster et al. 2001), was determined in cell culture lysates. Cells were resuspended in
lysis buffer (50mM Tris, pH7.6, 250mM NaCl, 5mM EDTA, 0.1% IGEPAL, Complete
protease inhibitor cocktail) and passed through a syringe. The cell extracts were
centrifuged to pellet cell debris and supernatants and analysed for total protein (BCA
protein assay kit, Pierce, Rockford, IL). CK activity in aliquots of the supernatant was
determined with a commercial assay kit (Randox Laboratories Ltd. Crumlin, UK) and
automated clinical analyser (RX Daytona, Randox).
G. Western blot analysis
100 µg of denatured total proteins (extracted as described above) from each sample
were separated by electrophoresis on a 6% (MHC) SDS-polyacrylamide gel and
transferred to nitrocellulose membrane by electroblotting. Membranes were blocked
for 2 h with 5% skim milk in Tris-buffered saline (50 mM Tris-HCl, 750 mM NaCl,
0.25% Tween), and were incubated overnight at 4oC with a polyclonal anti-MHC (MY32, Zymed, San Francisco, CA). Membranes were washed (4 x 5 min), followed by a
60 min incubation with anti-rabbit IgG conjugated to horse-radish peroxidase (1 in
10,000 dilution) (Santa Cruz Biotechnology, Santa Cruz, CA), then washed again.
Immunoreactive bands were detected using enhanced chemiluminescence (Western
Lightning Chemiluminescent Reagent, Perkin-Elmer, Boston, MA). An internal control
was used in each gel to normalize for variation in signal observed across the
membranes.
H. Real-time PCR analysis
1. RNA Extraction
RNA was extracted as previously described (Chapter 3, section II, part D).
2. cDNA Synthesis
The cDNA synthesis reaction was conducted as previously described (Chapter 3,
section II, part H.2).
99
3. Primer Design
Primers were designed as previously described (Chapter 3, section II, part H.3). See
Table 6.1 for details.
4. Real-time PCR reaction
PCR was performed as previously described (Chapter 3, section II, part H.4).
5. PCR Efficiency
For each gene, the PCR efficiency of the primer pairs was determined as previously
described (Chapter 3, section II, part H.5). See Table 6.1 for details
I. Statistical Analysis
Statistical analyses were performed using GraphPad Prism 4.1. Two-way ANOVAs
with repeated measures were performed to examine differences in both treatment and
time. Significant main effects were explored using Bonforoni post hoc tests. Data is
presented as mean ± standard error of the mean (SEM). A probability level of <0.05
was adopted throughout to determine statistical significance unless otherwise stated.
100
Table 6.1. Real-Time PCR Primer Details.
Gene
ASB5
GenBank
Accession
Number
AY057053
Forward Primer (5’-3’)
Conc,
µM
Reverse Primer (5’-3’)
Conc,
µM
Exon
Divide
Amplico
n Size,
PCR
Efficiency
AAATGCAGTAACCTTAGACCATGTCA
2
ACATGCCACGTGATCTCCAA
2
---
67
0.8
FLJ38973
NM_153689
GAATGGTTGCAAGGGAGAAA
4
GCGTCATTTAGTGATGGTGGATAA
4
---
87
1.1
MHC I
NM_000257
TGAAAGTGGGCAATGAGTACG
2
TCCAGTTGAACATCCTCTCATACA
2
exon 10 & 11
105
0.8
111
0.7
MHC IIx
NM_005963.2
GACTGATCGGGAGAATCAGTCTATC
2
TCCCCAGTAACTGCAATTGTTG
2
exon 3, 4, 5
&6
MLP
NM_003476
TCAGTCTATGCTGCTGAGAAGGTT
2
GATGGCACAGCGGAAACAG
2
exon 4 & 5
72
0.8
Myf5
NM_005593
TTCTACGACGGCTCCTGCATA
4
CCACTCGCGGCACAAACT
4
---
67
1.2
Myf6
NM_002469
CACCCTGCGCGAAAG
2
CACAGTTCGCCGCTTCAGT
2
---
70
1.1
MyoD
NM_002478
CCGCCTGAGCAAAGTAAATGA
4
GCAACCGCTGGTTTGGAT
4
---
74
1.0
myogenin
NM_002479
GGTGCCCAGCGAATGC
2
TGATGCTGTCCACGATGGA
2
exon 2 & 3
155
0.9
Myostatin
NM_005259
CCAGGAGAAGATGGGCTGAA
2
CAAGACCAAAATCCCTTCTGGAT
2
exon 2 & 3
82
0.8
p21
NM_000389
GGCAGACCAGCATGACAGATTT
6
GGCGGATTAGGGCTTCCTCT
6
---
73
0.7
CTAAAATGCGCCGGCAAT
2
GCTTCAAATACTAGCGCCAAGGT
2
exon 2 & 3
155
1.0
AGATCAGGTCTAAGCAGAACA
4
TCAGATCTACCCAACTCATCTCAGA
4
---
73
1.0
PCNA
NM_182649.1
TXNIP
NM_006472
Primer sequences were designed using Primer Express Version 2 software (Applied Biosystems) using sequences accessed through GenBank and checked for specificity
using Nucleotide-Nucleotide Blast search (http://www.ncbi.nlm.gov/BLAST/). Exon information was obtained from the Ensembl Genome Database (http://www.ensembl.org/).
The concentrations of forward and reverse primers are indicated along with the intron-exon divide the primers were designed around (if possible) and amplicon size in base
pairs. ASB5, ankyrin repeat and SOCs box-containing 5; MLP, muscle LIM protein; TXNIP, thioredoxin interacting protein; MHC I, myosin heavy chain I, MHC IIx, myosin
heavy chain IIx; PCNA, proliferating cell nuclear antigen.
101
III. RESULTS
In an effort to improve the understanding of the functional roles of several novel
resistance exercise responsive genes a human primary skeletal muscle cell culture
model was employed to examine the expression of the genes during the proliferation,
cell cycle arrest and differentiation. Human primary skeletal muscle cell cultures were
established from vastus lateralis muscles from 8 healthy young male and female
volunteers. These cell lines were maintained in a proliferating state in medium
containing 10% foetal bovine serum and all experiments were performed between the
2nd and 6th passages. Cells were stimulated to differentiate with serum withdrawal, and
serum withdrawal combined with over-expression of exogenous IGF-1 (R3IGF-1).
Since IGF-1 is a potent stimulator of muscle hypertrophy we sought to identify whether
the expression of our novel genes were (1) activated at any time during proliferation,
cell cycle arrest or differentiation or (2) activated by the additional mitogenic and
myogenic stimulation provided by R3IGF-1.
A. Characterisation of human skeletal muscle cell cultures
Initially, the capacity of the human skeletal muscle cells lines to differentiate was
examined using classical serum withdrawal induced differentiation. Cells actively
proliferating in high serum media and cells exposed to low serum conditions were
grown for up to 6 days on glass cover slips for immunocytochemical analysis of MHC
protein expression. MHC expression is a widely used marker of differentiation in
skeletal muscle cell cultures. No MHC expression was evident in proliferating cells
(Figure 6.1, A), whereas by 7 days, extensive MHC expression was apparent with
multi-nucleation and myotube formation evident (Figure 6.1, B).
102
A
B
Figure 6.1. Differentiation of primary human skeletal muscle cell lines. The
differentiation
potential
of
our
cell
lines
was
examined
using
immunocytochemical staining of MHC protein in proliferating cells (A) and
following 7 days of serum withdrawal mediated differentiation (B). Cells were
reacted to the MHC antibody MY-35 (green). Nuclei were counterstained using
the DNA binding dye Bisbenzimide Hoechst 33285 (blue). Bar represents
100µm.
103
B. Assessment of Proliferation and Differentiation
To examine the relative effectiveness of our treatments on myogenesis, well
established markers of progression through the cell cycle and myoblast differentiation
were examined using real-time PCR (Figure 6.2). The expression of PCNA, necessary
for cell cycle progression, was examined to assess cell proliferation. As expected,
differentiation stimulated a reduction in the expression of PCNA for both the IGF-1
treated and untreated differentiating cells (significant main effect of time, p<0.01). No
statistically significant difference was observed between treatments; however,
DM+IGF-1 treatment appeared to initially increase the expression of PCNA (~1.4-fold)
12 h after the initiation of differentiation. The expression of p21, a prominent regulator
of and molecular marker of cell cycle arrest, demonstrated a significant main effect of
time (p<0.01); however no differences in expression were observed between DM and
DM+IGF-1 treatment groups. Myostatin, a powerful negative regulator of muscle
growth, has been shown to regulate cell cycle arrest through p21 (McCroskery et al.
2003). Differentiation appeared to decrease the expression of myostatin (main effect
of time, p<0.01); although the decrease observed in the IGF-1 treated group failed to
reach statistical significance. No differences between treatment groups were
observed. In addition to the analysis of cell cycle regulators, we sought to examine the
expression of several established markers of myogenic differentiation. As expected,
the expression of myosin heavy chain type IIx (MHC IIx) was markedly increased by
DM (~35-fold) and DM+IGF-1 (~27-fold) however no differences between treatment
groups were observed (main effect of time, p<0.01). Conversely, the expression of the
slow MHC isoform (MHC I) displayed marked differences between DM and DM+IGF-1
treatment groups. DM treatment alone significantly increased MHC I expression (~12fold) whilst DM+IGF-1 treatment resulted in a comparably modest (~3-fold) and
insignificant increase in MHC I expression. Furthermore, significant main effects of
time were observed for CKM mRNA and activity, during DM and DM+IGF-1
treatments; however no differences between treatment groups were observed.
To further confirm effectiveness of differentiation stimuli, we examined both the
expression of a muscle specific protein (MHC) as well as the activity of CMK. CKM
activity increased following 48 h and remained elevated 72 h post differentiation
(Figure 6.3). Finally, MHC protein expression was assessed to confirm the attainment
of the differentiated state (Figure 6.4). Consistent with CKM activity, no difference in
MHC protein expression was observed between treatment groups, although MHC
protein expression increased over the time-course of differentiation (Figure 6.4).
104
DM
DM+IGF-1
PCNA
p21
2.5
1.50
1.25
1.00
0.75
**
0.50
0.25
0.00
0h
12 h
24 h
**
**
**
48 h
*
**
Arbitrary units normalised
to 0 h
Arbitrary units normalised
to 0 h
1.75
2.0
1.5
1.0
0.5
0.0
72 h
0h
12 h
Myostatin
1.25
1.00
*
0.75
0.50
*
0.25
0h
12 h
24 h
48 h
Arbitrary units normalised
to 0 h
Arbitrary units normalised
to 0 h
60
1.50
**
*
***
40
30
20
10
0
72 h
0h
12 h
**
*
12.5
10.0
7.5
5.0
2.5
72 h
48 h
72 h
Hours post differentiation
**
*
8
7
6
5
**
4
2
1
0h
12 h
24 h
48 h
Hours post differentiation
Figure 6.2. mRNA expression analysis of markers of proliferation (PCNA), cell
cycle arrest (p21, Myostatin) and differentiation (MHC IIx, MHC I, CKM) during
serum withdrawal (DM; solid bars) or serum withdrawal combined with 30ng/ml
R3IGF-1 (DM+IGF-1;white bars). Each bar represents the mean ± SEM of eight
independent, replicate experiments.
* Significantly different from control (p<0.05)
**
3
0
24 h
48 h
9
Arbitrary units normalised
to 0 h
Arbitrary units normalised
to 0 h
15.0
12 h
24 h
CKM
17.5
0h
72 h
50
MHC I
0.0
48 h
MHC IIx
1.75
0.00
24 h
72 h
105
Significant Time Main Effect
(p<0.01)
CK activity
(mU/mg normalised to 0h)
3
*
DM
DM+IGF-1
*
2
*
*
1
0
0h
12 h
24 h
48 h
72 h
Hours post differentiation
Figure 6.3. CK activity increases with time in differentiating conditions. Human
primary skeletal myoblasts were differentiated with serum withdrawal (DM) or
serum withdrawal combined with 30ng/ml R3IGF-1 (DM+IGF-1). CK assay was
performed on cell lysates and is expressed as mU/mg of total protein
normalised to the 0h time-point. The average of eight independent primary cell
cultures is presented, ± SEM.
* Significantly different from control.
106
A
35000
DM
Arbitrary Units
30000
DM+IGF-1
25000
20000
15000
10000
5000
0
0h
12 h
24 h
48 h
72 h
Hours post differentiation
B
DM
DM+IGF-1
Figure 6.4. Western blot analysis of MHC protein expression over time in
differentiating conditions. The cell extracts were electrophoresed through a 6%
SDS-polyacrylamide gel, transferred to nitrocellulose membranes and reacted
to the myosin antibody (MY-35). A: MHC expression analysed using
densitometry and expressed as arbitrary density units. The average of four
independent primary cell culture experiments is presented B: Representative
blots from DM and DM+IGF-1 treated cells.
107
C. Myogenic regulatory factor expression
Since the temporal expression of the MRF transcription factors is critical to the
appropriate development of the muscle phenotype, the expression of these factors
was examined during the 72 h differentiation treatments (Figure 6.5). MyoD
expression decreased significantly 72 h following DM and DM+IGF-1 treatments
(p<0.05) however there were no differences in expression between treatments. In
contrast, Myf5 showed no significants main effects of time or treatment; however a
moderate decrease seemed evident at 48 h and 72 h post differentiation. Myogenin,
considered the one of the earliest indicators of differentiation, demonstrated a
dramatic increase at 24 h post differentiation which was sustained out to 72 h. Again,
no differences were observed between groups. Myf6 expression demonstrated a
significant main effect of time (p<0.01), with no significant difference evident between
treatment groups. Myf6 expression was decreased by approximately 3-fold at both 48
h and 72 h in the DM treatment group. The expression of Myf6 was reduced by
approximately 4-fold at 48 h and 72 h in the DM+IGF-1 treatment group.
108
Myf5
1.2
1.75
1.0
1.50
0.8
0.6
*
0.4
*
0.2
0.0
0h
12 h
24 h
48 h
Arbitrary units normalised
to 0 h
Arbitrary units normalised
to 0 h
MyoD
72 h
1.25
1.00
0.75
0.50
0.25
0.00
0h
12 h
30
25
20
**
10
**
5
0
0h
12 h
**
**
24 h
48 h
72 h
Hours post differentiation
Arbitrary units normalised
to 0 h
Arbitrary units normalised
to 0 h
**
35
15
72 h
48 h
72 h
1.4
**
40
48 h
Myf6
Myogenin
45
24 h
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0h
12 h
24 h
Hours post differentiation
Figure 6.5. mRNA expression analysis of the myogenic regulatory factors
(MyoD, Myf5, myogenin, Myf6) during serum withdrawal (DM; solid bars) or
serum withdrawal combined with 30ng/ml R3IGF-1 (DM+IGF-1;white bars).
Each bar represents the mean ± SEM of eight independent, replicate
experiments.
* Significantly different from control (p<0.05)
** Significantly different from control (p<0.01)
109
D. Expression of novel resistance exercise responsive genes
Once the temporal patterns of expression of markers of cell cycle and myogenic
events that characterise the myogenic differentiation were established, we examined
the expression of the novel genes previously identified as being responsive to
resistance exercise (Figure 6.6). The expression of FLJ38973, ASB5 did not change
with either the DM or DM+IGF-1 treatments, whilst MLP expression appeared to
increase slightly, although not significantly different during differentiation. A significant
main effect of time (p<0.05) was observed for TXNIP expression with early induction
evident from 12 h post exercise, sustained out to 72 h. No differences between
treatment groups were observed for any of these genes.
110
FLJ38973
ASB5
2.0
Arbitrary units normalised
to 0 h
Arbitrary units normalised
to 0 h
2.5
2.0
1.5
1.0
0.5
0.0
0h
12 h
24 h
48 h
1.5
1.0
0.5
0.0
72 h
0h
12 h
MLP
Arbitrary units normalised
to 0 h
Arbitrary units normalised
to 0 h
3.0
2.5
2.0
1.5
1.0
0.5
0h
12 h
24 h
48 h
72 h
TXNIP
3.5
0.0
24 h
48 h
72 h
12
11
10
9
8
7
6
5
4
3
2
1
0
**
**
**
**
0h
Hours post differentiation
12 h
**
**
24 h
TXNIP during serum withdrawal (DM; solid bars) or serum withdrawal
combined with 30ng/ml R3IGF-1 (DM+IGF-1;white bars). Each bar represents
** Significantly different from control (p<0.01)
48 h
Hours post differentiation
Figure 6.6. mRNA expression analysis of the FLJ 38973, ASB5, MLP, and
the mean ± SEM of eight independent, replicate experiments.
**
72 h
111
IV. DISCUSSION
Muscle differentiation is a multi-step process involving permanent cell cycle arrest,
expression of muscle specific genes and proteins, and fusion of myoblasts to form
multi-nucleated myotubes. Previous work has clearly delineated the sequential
expression of numerous molecular markers of muscle differentiation. Using human
primary skeletal muscle cell cultures derived from the vastus lateralis muscle of
healthy volunteers, and the established knowledge of the temporal patterns of
myogenesis, the expression patterns of several novel myogenic genes were
investigated.
A. R3IGF-1 mediated differentiation
The differentiation of skeletal myogenic cells in culture is classically induced by serum
deprivation. In an attempt to augment an in vitro hypertrophic response, the standard
differentiation stimulus of serum withdrawal was combined with the added
hypertrophic stimulus of exogenous IGF-1. The IGF-1 analogue we selected,
LongTMR3IGF-1 is a variant of human IGF-I that contains an amino terminal extension
peptide as well as glutamate-3 replaced by arginine. This form of IGF-1, exhibits very
weak binding to IGF-binding proteins and has been shown to exhibit greater biological
activity than natural IGF-1 (Francis et al. 1992; Tomas et al. 1993). Since IGF-1 has
been reported to stimulate both the proliferation and differentiation of muscle cells in
culture, several molecular markers were selected to compare the mitogenic and
myogenic effects of DM+IGF-1 and DM alone on our human primary skeletal muscle
cell cultures. Somewhat surprisingly, no obvious differences in the expressions of any
of the chosen markers were observed between the two differentiation stimuli, with the
possible exception of PCNA and MHC I. PCNA is a widely used marker of proliferating
myoblasts with increased expression in the G1 phase of the cell cycle, peak during S
phase, and decline during G2 (Bravo and Macdonald-Bravo 1987; Mesires and Doumit
2002). The moderate increase observed in PCNA expression at 12 hours post
differentiation in the DM+IGF-1 group might indicate increased proliferative activity in
these cells.
Despite this minor difference, DM+IGF-1 appeared to have very little if any effect on
the differentiation potential of the human skeletal muscle cell cultures above DM
alone. Although unexpected, the lack of an obvious increase in the differentiation
potential of IGF-1 treated myoblasts might be explained by endogenous IGF-1
112
production. After serum withdrawal, spontaneous IGF-1 peptide production is
observed in muscle cells (Tollefsen et al. 1989a; Tollefsen et al. 1989b; Rosenthal et
al. 1991). Therefore, exogenous IGF-1 in the DM+IGF-1 treated cells may have had
no added effect on differentiation than the endogenous IGF-1 produced following
serum deprivation in the DM cells. Alternatively, the concentrations of IGF-1 used in
this study (30ng/ml) may not have been sufficient or indeed too high to augment
differentiation in human primary myoblasts. However, at least one previous study has
demonstrated increased differentiation in primary human myoblasts with 30ng/ml
R3IGF-1
(Foulstone
et
al.
2003).
Comparisons
between
IGF-1
stimulated
differentiation and differentiation (induced by serum withdrawal) in this study were only
examined at 7 days post differentiation. Thus the possibility remains that the type
points selected in the present study were too short to see any marked increase in IGF1 stimulated differentiation.
B. Cell cycle regulator and MRF expression during differentiation
Despite the equivocal effects of the IGF-1 treatment, serum withdrawal alone was
sufficient to promote a marked differentiation response in our human skeletal muscle
cell cultures. The expression patterns of the cell cycle regulators and MRF were
initially examined to establish the temporal pattern of myogenesis exhibited in the
human primary skeletal muscle cultures. It was anticipated that this would allow the
association of observed changes in the expression of novel genes with specific stages
of the differentiation program.
The decision of myoblasts to proliferate or exit the cell cycle and progress towards
skeletal muscle differentiation is determined in late G1 of the cell cycle and is
governed by the activity of G1 cyclins/Cdk complexes (Pardee 1989). The cyclin / Cdk
complexes cyclin D/Cdk4 and cyclin E / Cdk2, cooperate to control the G1 to S
transition through the phosphorylation and inactivation of retinoblastoma protein (Rb).
The commitment of myogenic cells into skeletal muscle differentiation requires prior
irreversible cell cycle arrest and inactivation of cell cycle activators by cell cycle
inhibitors (such as Rb p21, p27 and p57). Central to this process are the MRFs which
are involved not only in the expression of muscle specific genes, but also cooperate
with cell cycle regulators in mediating the transition from the proliferative stage.
Previous studies have indicated the MyoD is capable of inducing the expression of
p21 (Guo et al. 1995; Halevy et al. 1995; Parker et al. 1995) as well as other Cdk
inhibitors , p27, p57 (Reynaud et al. 2000) and Rb (Martelli et al. 1994) during
myogenesis. The time window for cells to exit the cell cycle and into differentiation is in
113
G1, when MyoD expression is maximal and Myf5 expression is lowest (Kitzmann et al.
1998; Kitzmann and Fernandez 2001). In the present study, MyoD expression was
maximal at 0 h and 12 h post differentiation, followed by a small increase in p21
expression. p21 works redundantly with p57 (Zhang et al. 1999) by blocking
progression through the cell cycle by binding to PCNA (to inhibit DNA synthesis) as
well as the G1 phase cyclin/Cdk complexes to prevent their enzymatic activity
(Boulaire et al. 2000). As expected, PCNA expression was markedly reduced by 24 h
post differentiation, despite only minor changes in the expression of p21. Although p57
expression was not measured in this study, it is possible that increased p57
expression might account for the attenuated expression of p21. The expression of
myogenin, considered one of the earliest markers of differentiation, was increase at 12
h with expression peaking at 48 h and 72 h. Myogenin expression preceded the
expression and activity of markers of terminal myoblast differentiation MHC and CKM.
Myf6 expression, consistent with its suggested role at the latest stages of myogenesis,
possibly during myobirillogenesis (Rudnicki and Jaenisch 1995) was down-regulated
throughout the 72 h differentiation time-course.
Collectively, these observations suggested that our model exhibited the molecular
markers of muscle differentiation in a chronologically appropriate manner. Importantly,
the establishment of the temporal pattern of myogenesis in this model would allow the
association of observed changes in the expression of novel genes with specific stages
of the differentiation program. As discussed in chapter 5, the genes examined in this
study were all observed to be up-regulated in the vastus lateralis during the 24 h
recovery from a single bout of resistance exercise. The genes investigated were
muscle LIM protein (MLP), thioredoxin interacting protein (TXNIP), ankyrin repeat and
SOCS box-containing 5 (ASB5), and hypothetical protein FLJ38973.
C. Examination of the Expression Patterns of Novel Myogenic
Genes
MLP was originally discovered in denervated skeletal muscle and has shown an
enriched pattern of expression in striated muscle tissue (Arber et al. 1994). Several
previous studies have identified important roles for MLP in myogenesis and in the
promotion of myogenic differentiation (Arber et al. 1994; Arber et al. 1997; Louis et al.
1997; Shen et al. 2003). More specifically, the actions of MLP have been described
late in differentiation potentially facilitating the assembly or stabilization of the
myofibrillar apparatus by interacting with the structural proteins β1-spectrin, telethonin
and α-actinin (Louis et al. 1997; Stronach et al. 1999; Flick and Konieczny 2000) The
114
results of the present study show MLP slightly increased at 72 h, however, as
described previously, MLP expression is likely to peak later in differentiation (i.e. after
6 days (Shen et al. 2003)), outside the time-frame of this study.
TXNIP, is a ubiquitous protein that binds with high affinity to thioredoxin and has been
implicated the maintenance of cellular redox state and insulin secretion (Hui et al.
2004), development of hepatic steatosis (Donnelly et al. 2004; Van Greevenbroek et
al. 2004), among others (Ikarashi et al. 2002; Yoshioka et al. 2004). In chapter 5,
TXNIP expression was shown to be rapidly and transiently increased in skeletal
muscle following a resistance exercise bout; providing the first evidence of a role for
TXNIP in skeletal muscle. Interestingly, in the present study following the
differentiation signal, TXNIP expression was rapidly increased and remained elevated
throughout the differentiation time-course. The expression of TXNIP was the earliest
induction of any of our markers of the myogenic program, which might suggest a very
early role in the transduction of the differentiation stimulus. Similarly, TXNIP
expression was markedly expressed very early (30 min) following the resistance
exercise bout, supporting a potential role as an immediate responsive gene. Previous
research has identified elevated levels of TNXIP expression in terminally differentiated
epithelial cells of the human gastrointestinal tract (Takahashi et al. 2003) as well as
reduced TXNIP expression in gastrointestinal cancers, characterized increases in their
proliferative potential (Ikarashi et al. 2002). Collectively, these results suggest a
potentially vital role for TXNIP in cellular differentiation. Whilst a role in differentiation
remains speculative at this stage, it would be interesting to investigate the forced
inhibition of TXNIP on the capacity of myobasts to attain the differentiated phenotype.
Conversely, the expression of ASB5 and hypothetical protein FLJ38973 demonstrated
no altered expression patterns during primary myoblast differentiation. Very little is
known about the functions of ASB5, one study has identified increased expression of
this gene in growing collateral arteries following femoral ligation (Boengler et al. 2003).
The authors noted an increased expression of ASB5 in both endothelial and smooth
muscle cells which proliferate rapidly during collateral artery growth. Thus the
possibility remains that ASB5 might exert its function on actively proliferating cells,
despite no reduction in its expression post differentiation. Alternatively, it is intriguing
to speculate that the expression of ASB5 might respond exclusively to the damage,
contraction, or stretch imposed by resistance exercise. In support of this, the
expression of ASB5 has been localized in some satellite cells whilst mature myocytes
themselves do not appear to express this protein (Boengler et al. 2003). Thus the
possibility still remains that ASB5 might constitute a novel molecule involved in
proliferative response of satellite cells in response resistance exercise. Equally,
115
nothing is known of the functions of the unknown protein FLJ38973 and the results of
this study provide little answers as to its role during skeletal myogenesis.
Skeletal muscle differentiation is a highly complex and coordinated process requiring
the prior irreversible cell cycle arrest, before terminal differentiation, the expression of
muscle specific genes and ultimately the formation of multinucleated myotubes. Here,
the expression of novel myogenic genes in the context of the expression of known
regulators and markers of skeletal myogenesis during the forced differentiation of
human primary skeletal muscle cell cultures was investigated. Whilst the exact
functions of these genes in skeletal muscle remains to be determined, these data
provide additional insights into their regulation during myogenesis, and go some way
to potentially identifying their mechanisms of action.
116
CHAPTER SEVEN
EXPRESSION OF THE NOVEL GENES
FOLLOWING AN ACUTE BOUT OF ENDURANCE
EXERCISE
I. INTRODUCTION
Skeletal muscle is an extremely dynamic tissue, which possesses the ability to adapt
to a variety of physiological stimuli resulting in improved muscular capacity,
specifically adapted to its functional demands. The plasticity of muscle is illustrated by
the diverse phenotypic profiles of muscle evident following different exercise training
regimes. For example, endurance training improves the metabolic properties of
muscles, including an increase in number and size of mitochondria, switches in
muscle fibre types from fast to slow isoforms, as well as the activity of enzymes
related to fat and carbohydrate oxidation. Conversely, resistance training results in
greater accumulation of contractile proteins, increased myofibre cross-sectional area,
increased numbers of myonuclei and a shift in fibre type from slow to fast isoforms.
Despite a great understanding of the specific phenotypic adaptations to endurance
and resistance exercise. The knowledge surrounding the regulatory mechanisms
governing the highly specified cellular level changes is limited. Through the use of
molecular biology tools, we are starting to identify specific molecules and signalling
pathways, which together result in the appropriate adaptation of skeletal muscle. For
example, increases in the expression of genes related to fat and carbohydrate
oxidation have been observed following both acute and chronic endurance exercise
(i.e. GLUT4, PDK4) (Pilegaard et al. 2000; Hildebrandt et al. 2003; Pilegaard and
Neufer 2004). Whereas resistance exercise has been shown to promote the
expression of genes associated with muscle regeneration and development (i.e.
MyoD, myogenin) (Willoughby and Nelson 2002; Bickel et al. 2003; Psilander et al.
2003).
In chapter 5, the identification of a number of genes that show increased expression in
skeletal muscle following an acute bout of resistance exercise was described. Three of
these genes: thioredoxin-interacting protein (TXNIP), ankyrin repeat and SOCS boxcontaining 5 (ASB5), and unknown protein FLJ38973, have not previously investigated
117
in skeletal muscle and as such provide unique targets for further investigation into the
molecular regulation of hypertrophy. The fourth gene, muscle LIM protein (MLP), has
previously been implicated in skeletal muscle hypertrophy however its mechanisms of
action remain equivocal.
In chapter 6, the expression of these genes was investigated during the differentiation
of human primary myoblasts. The results of this study showed that ASB5 and
FLJ38973 mRNA was not altered at any time during proliferation arrest or
differentiation. Conversely, the expression of MLP tended to increase and TXNIP
mRNA increased rapidly and markedly following the initiation of differentiation. Whilst,
these results suggested potential roles for TXNIP and MLP in the differentiation of
skeletal muscle satellite cells during hypertrophy, it provided no clues as to the
potential importance of the increased expression of ASB5 and FLJ38973 in skeletal
muscle. Furthermore, we were no closer to determining if the responses of these
genes were a unique response to resistance exercise or if they were responsive to
skeletal muscle contraction or exercise in general. Therefore, in the present study the
expression of resistance exercise responsive genes following a single bout of
endurance exercise was investigated.
Additionally, the expression of the muscle regulatory factors (MRFs) was examined.
Whilst the majority of studies to date have examined the expression of the MRFs in
the context of resistance exercise, there is some suggestion that the MRFs might have
the capacity to mediate muscle metabolic and contractile properties, not only towards
phenotypes suited to resistance exercise, but also towards a more oxidative
phenotype such as that observed following endurance training (Hughes et al. 1993;
Bottinelli et al. 1994; Hughes et al. 1997; Hughes et al. 1999; Kadi et al. 2004a; Siu et
al. 2004). Since these studies had focused on MyoD and myogenin, the expression of
all four MRFs was investigated following an acute bout of endurance exercise. It was
hypothesised that the expression of ASB5, TXNIP, MLP, FLJ38973 and the MRFs
would not be altered following a single bout of endurance exercise.
118
II. METHODS
A. Subjects
Eight healthy, habitually active but non-endurance trained male subjects volunteered
to participate in this study. Age, height and weight were on average 26.1 ± 1.6 years,
183.2 ± 2.5 cm, and 77.1 ± 2.9 kg (mean ± SEM). Peak oxygen uptake (VO2 peak)
determined by an incremental bicycle test was 47.5 ± 2 ml.kg-1.min-1. Exclusion
criteria included endurance training status as evidence by a VO2 peak greater than 55
ml.kg-1.min-1 or previous history of a diagnosed condition or illness that would
endanger the subjects during strenuous endurance exercise. Informed written consent
was obtained from each subject before participation in the study, after the nature,
purpose and risks of the study were explained. All experimental procedures involved
in this study were formally approved by the Deakin University Ethics Committee.
B. VO2 Peak
All subjects completed a VO2 peak test on an electromagnetically braked cycle
ergometer (Lode, Groninegen, The Netherlands) with an incremental protocol and
subjects pedalling at a self selected rate. Respiratory gasses were collected and
analysed using Vista TurboFit software (Vacumetrics Inc. Ventura, CA) connected to
Applied Electrochemistry Technologies oxygen (Model S-34) and carbon dioxide
(Model CD-3A) analysers (Pittsburg, Pennsylvania). The gas analysers were
calibrated prior to each test against commercially prepared (BOC, Australia) alpha
rated gases of known concentrations.
C. Experimental Design
Subjects arrived at the laboratory in the fasted state for a resting muscle biopsy. For
the 24 h preceding, and the days of the trial, subjects were provided with and
consumed a standard diet of 20% fat, 14% protein, 66% carbohydrate and abstained
from alcohol, caffeine, tobacco and additional exercise. Macronutrient intake was
assessed using FoodWorks 3.0). Following the resting biopsy, subjects began cycling
at a power output requiring approximately 70% peak oxygen consumption (average
across all subjects throughout the exercise was 71.2 ± 2.1%). The exercise bout
119
lasted 60 min and subjects were permitted to consume water ad libitum. Further
muscle samples were obtained 30 min after the exercise bout, 4 hours after the
exercise bout and again 24 hours after the exercise bout.
D. Muscle Biopsy Procedure
The vastus lateralis muscle of the non-dominant leg was sampled by percutaneous
needle biopsy technique as described previously (Chapter 4, section II, part D).
E. Real-Time PCR Analysis
1. RNA Extraction
The RNA extraction was performed as described previously (Chapter 4, section II, part
E.1).
2. Reverse Transcription
The cDNA synthesis reaction was performed as described previously (Chapter 3,
section II, part H.2)
3. Primer Design
PCR primers were designed as described previously (Chapter 3, section II, part H.3).
PCR primer sequences are presented in Table 7.1.
4. Real-time PCR reaction
The real-time PCR reaction was performed as previously described (Chapter 3,
section II, part H.4).
5. PCR Efficiency
Linearity of PCR primers was performed as described previously (Chapter 3, section
II, part H.5), see Table 7.1 for details.
6. PCR Analysis and Endogenous Control Selection
Data was analysed using the comparative critical threshold (Ct) method where the
amount of target normalised to the amount of the endogenous control is given by 2-∆Ct.
β-actin has previously been identified as an appropriate endogenous control for
endurance exercise studies (Mahoney et al. 2004) and as such was selected for the
endogenous control for this study. The appropriateness of this gene as an
120
endogenous control was examined by using the 2-∆Ct normalised to control values
(Figure 7.1A). However, this analysis revealed significant changes in the expression of
this gene and as such was deemed to be an inappropriate endogenous control to use
for this study. Subsequently, cyclophilin was investigated as an endogenous control
(Figure 7.1B). No significant change in its expression following endurance exercise
was observed and therefore was selected as the endogenous control for this study.
A
β -actin
Arbitrary units normalised to
control
1.05
B
1.00
0.95
*
0.90
0.85
0.80
0.75
Pre
30min
4h
24h
Cyclophilin
Arbitrary units normalised to
control
2.0
1.5
1.0
0.5
0.0
Pre
30min
4h
24h
Figure 7.1. Examination of the mRNA expression of the endogenous control βactin (A) and cyclophilin (B) following an acute bout of resistance exercise. , The
expression of the endogenous control in a given sample was calculated by
subtracting the CT of each sample from the CT of the corresponding pre or control
value. The relative expression of the gene of interest normalised to control was
calculated using the expression 2
-∆CT
. Statistical analysis revealed no change in
the expression of this gene at any time point following the exercise intervention.
Therefore, this was considered an appropriate endogenous control for this study.
121
F. Statistical Analysis
Statistical analysis was performed using GraphPad Prism 4.1 (GraphPad Software,
San Diego, CA). Means were compared using a one-way ANOVA and any significant
differences analysed using a Dunnet’s multiple comparison test. Data is presented as
mean ± standard error of the mean (SEM). A probability level of <0.05 was adopted
throughout to determine statistical significance unless otherwise stated.
122
Table 7.1. Real-Time PCR Primer Details.
Gene
GenBank
Accession
Number
Forward Primer (5’ Æ 3’)
Conc,
µM
Reverse Primer (5’ Æ 3’)
Conc,
µM
Exon
Divide
Amplicon
Length
PCR
Efficiency
ASB5
AY057053
AAATGCAGTAACCTTAGACCATGTCA
2
ACATGCCACGTGATCTCCAA
2
---
67
0.8
β-Actin
NM_001101
AAGCCACCCCACTTCTCTCTAA
2
AATGCTATCACCTCCCCTGTGT
2
---
141
1.1
Cyclophilin
NM_021130
CATCTGCACTGCCAAGACTGA
4
TTCATGCCTTCTTTCACTTTGC
4
exon 4 & 5
80
0.9
FLJ38973
NM_153689
GAATGGTTGCAAGGGAGAAA
4
GCGTCATTTAGTGATGGTGGATAA
4
---
87
1.1
MLP
NM_003476
TCAGTCTATGCTGCTGAGAAGGTT
2
GATGGCACAGCGGAAACAG
2
exon 4 & 5
72
0.8
Myf5
NM_005593
TTCTACGACGGCTCCTGCATA
4
CCACTCGCGGCACAAACT
4
---
67
1.2
Myf6
NM_002469
CACCCTGCGCGAAAG
2
CACAGTTCGCCGCTTCAGT
2
---
70
1.1
MyoD
NM_002478
CCGCCTGAGCAAAGTAAATGA
4
GCAACCGCTGGTTTGGAT
4
---
74
1.0
myogenin
NM_002479
GGTGCCCAGCGAATGC
2
TGATGCTGTCCACGATGGA
2
exon 2 & 3
155
0.9
PDK4
NM_002612
ATGGATAATTCCCGGAATGCT
2
ACTTGGCATACAGACGAGAAATTG
2
---
93
0.9
TXNIP
NM_006472
AGATCAGGTCTAAGCAGAACA
4
TCAGATCTACCCAACTCATCTCAGA
4
---
73
1.0
Primer sequences were designed using Primer Express Version 2 software (Applied Biosystems) using sequences accessed through GenBank and checked for specificity using
Nucleotide-Nucleotide Blast search (http://www.ncbi.nlm.gov/BLAST/). Exon information was obtained from the Ensembl Genome Database (http://www.ensembl.org/). The
concentrations of forward and reverse primers are indicated along with the intron-exon divide the primers were designed around (if possible) and amplicon size in base pairs.
ASB5, ankyrin repeat and SOCs box-containing 5; MLP, muscle LIM protein; PDK4, pyruvate dehydrogenase kinase 4; thioredoxin interacting protein.
123
III. RESULTS
The expressions of the resistance exercise responsive genes were examined
following a single bout of endurance exercise (Figure 7.2). Interestingly, the
expressions of TXNIP, MLP and FLJ38973 were not altered at any time-point post
exercise. Conversely, the expression of ASB5 was rapidly increased (p<0.05) by
approximately 2-fold, 30 min following the cessation of exercise before returning to
resting levels by 4 h.
Additionally, the expression of the muscle regulatory factors was investigated (Figure
7.3). Myf5 expression appeared to increase by approximately 2-fold at 30 min
however considerable between-subject variability was evident and this increase failed
to reach significance. MyoD and Myf6 expression was not altered at any point
following endurance exercise. Myogenin expression appeared to increase at 24 h,
although again this failed to reach significance.
Finally, the expression of PDK4, previously shown to be up-regulated following
endurance exercise (Pilegaard et al. 2000; Hildebrandt et al. 2003; Pilegaard and
Neufer 2004), was examined to ensure the exercise bout in conducted this study was
sufficient to elicit expected increases in gene expression (Figure 7.4). As expected,
PDK expression significantly increased by approximately 10-fold 4 h following the
endurance exercise bout.
124
TXNIP
MLP
20
35
mRNA expression
relative to cyclophilin
mRNA expression
relative to cyclophilin
30
25
20
15
10
5
0
Pre
30min
4h
15
10
5
0
24h
Pre
ASB5
mRNA expression
relative to cyclophilin
mRNA expression
relative to cyclophilin
2.5
Pre
30min
24h
4h
24h
0.05
5.0
0.0
4h
FLJ38973
*
7.5
30min
4h
24h
0.04
0.03
0.02
0.01
0.00
Pre
30min
Figure 7.2. The effects of a single of bout of endurance exercise on the expression of
resistance exercise sensitive genes. Real-time PCR analysis was performed on
TXNIP, MLP, ASB5 and FLJ38973. Values are means ± SEM of 8 subjects.
*Significantly different from control (p<0.05)
125
MyoD
0.35
0.8
0.30
0.7
mRNA expression
relative to cyclophilin
mRNA expression
relative to cyclophilin
Myf5
0.25
0.20
0.15
0.10
0.05
0.00
0.6
0.5
0.4
0.3
0.2
0.1
Pre
30min
4h
0.0
24h
Pre
30min
Myogenin
mRNA expression
relative to cyclophilin
mRNA expression
relative to cyclophilin
15
10
5
Pre
30min
24h
4h
24h
Myf6
20
0
4h
4h
24h
11
10
9
8
7
6
5
4
3
2
1
0
Pre
30min
Figure 7.3. The effects of a single of bout of endurance exercise on the expression of
the Muscle Regulatory Factors. Real-time PCR analysis was performed on Myf5,
MyoD, myogenin, and Myf6. Values are means ± SEM of 8 subjects. No significantly
different changes in gene expression were observed (p>0.05).
126
PDK4
1.75
**
mRNA expression
relative to cyclophilin
1.50
1.25
1.00
0.75
0.50
0.25
0.00
Pre
30min
4h
24h
Figure 7.4. The effects of a single bout of endurance exercise on the expression of
PDK4. Values are means ± SEM of 8 subjects.
**Significantly different from control, p<0.01
127
IV. DISCUSSION
Following a single bout of resistance exercise, microarray technology was used to
identify genes whose expression changed markedly, and therefore had the potential to
play important roles in the repair and adaptation of skeletal muscle. Since very little is
known about the functions of these genes (TXNIP, ASB5, MLP and FLJ 39873) in
muscle, this study aimed to determine whether these changes were specific to
resistance type exercise, or a common response to muscle contraction.
Previously in chapter 5 it was demonstrated that ASB5 gene expression increased
markedly 4 and 24 h following a single bout of resistance exercise. Interestingly, ASB5
expression also increased in the present study, 30 min following a single bout of
endurance exercise. The expression of ASB5 had been shown to be significantly
increased in endothelial and smooth muscle cells during arteriogenesis. Since
increased capillarisation is an adaptive response to both endurance and resistance
type exercise. It seems that the likely explanation for the increased expression of
ASB5 mRNA following both of these types of exercise is as an adaptive response to
an increased need for capillaries within the muscle. In support of this, increased
VEGF, a very early marker of arteriogenesis, is evident following both endurance and
resistance exercise well before capillarisation itself is likely to have occurred
(Gustafsson et al. 1999; Takahashi et al. 2002; Degens et al. 2003b). Thus, it appears
likely that ASB5 is a novel molecule implicated in the initiation of arteriogenesis,
although its mechanisms of action remain to be determined.
The lack of increased expression of TXNIP, MLP and FLJ38973 following endurance
exercise seem to suggest a reliance on conditions specifically imposed on the muscle
during resistance type exercise for their transcriptional activation. Numerous divergent
signals unique to each type of exercise might be responsible for the different
molecular responses of, and ultimately, phenotypic endpoint of resistance versus
endurance type training. Potential regulators of early gene expression in muscle
include, but are not limited to: exercise induced myotrauma, energy demands,
intracellular calcium, growth factors, and mechanical stretch. Different exercise
paradigms have the obvious potential to alter many different signalling pathways
within muscle ultimately resulting in the unique patterns of gene expression and
muscular adaptation. Thus TXNIP, MLP and FLJ38973 might constitute critical early
molecular adaptations within skeletal muscle with the potential, following training, to
promote muscle hypertrophy.
128
Several studies have suggested that MRFs may be involved in determining structural
and metabolic characteristics of postmitotic skeletal muscles (Hughes et al. 1993;
Bottinelli et al. 1994; Hughes et al. 1997; Adams et al. 1999; Allen et al. 2001).
Specifically, these studies have suggested that myogenin expression is associated
with the slow myosin heavy chain expression and increased oxidative capacity,
whereas MyoD is related to the expression of the fast isoforms and a shift towards
greater glycolytic activity. This is the first study to investigate the gene expression of
all members of the MRF family following a single bout of endurance exercise. Whilst
no significant change was evident in any of the MRFs, Myf5 express tended to
increase however considerable variability was evident between subjects likely
contributing to the lack of statistical power. Conversely, in a previous study (see
chapter 4) utilizing identical time-points post exercise, marked increases in both MyoD
and myogenin were evident following a single bout of resistance exercise. The results
of this study seem to suggest that immediate changes in the gene expressions of the
MRFs are not critical adaptations to endurance exercise.
Previous studies have demonstrated increased nuclear localization of myogenin
following a single bout of exercise (Kadi et al. 2004a) and increased myogenin mRNA
and protein levels following 8 weeks of endurance exercise (Siu et al. 2004). Despite
the lack of increase in myogenin mRNA expression in the present study it is possible
that the cellular localisation of myogenin protein might be adequate in mediating the
short term adaptation of muscle following endurance exercise. Whereas repeated
bouts of exercise might be necessary for increased myogenin gene and protein
expression. Importantly, current understanding of the genes whose trans-activation is
directly regulated by members of the MRF family is limited. Further examinations into
to specific gene targets of each MRF will further clarify the divergent functions of these
critical regulators of muscle development.
Resistance and endurance exercise results in the activation of numerous divergent
signalling pathways that ultimately result in the unique expression of muscle specific
proteins and development of a phenotypic profile highly suited to its functional
demands. In this study, the expressions of resistance exercise sensitive genes was
further characterised by examining their expression following endurance exercise.
Furthermore, we have examined the primary regulators of the muscle phenotype, the
MRFs following endurance exercise. These data provide further evidence of the
unique molecular mechanisms that regulate the exercise-induced adaptations of
skeletal muscle.
129
CHAPTER EIGHT
GENERAL DISCUSSION & FUTURE DIRECTIONS
I. INTRODUCTION
Skeletal muscle confers numerous vital functions including locomotion and postural
behaviour, strength, breathing and metabolism. Unfortunately, diseases of skeletal
muscle such as age related sarcopenia, muscular dystrophies, cancer cachexia,
disuse atrophy and other wasting disorders (e.g. AIDS) can lead to considerable
morbidity, loss of functional capacity and in the worst cases, lethality. Understanding
the mechanisms regulating skeletal muscle mass is therefore of great importance.
Both in the development of therapeutic strategies that may alleviate some of the
pathological conditions associated with diseases of muscle. But also in the
development of preventative measures that might assist in the maintenance of muscle
mass to arrest the currently inevitable muscle atrophy associated with ageing.
The specific aims of this thesis were:
•
To develop and test a human skeletal muscle specific cDNA microarray for
global transcriptional profiling and the identification of novel gene transcripts.
•
To further enhance current understanding of the process of myogenesis by
examining the expression profile of rhabdomyosarcoma cells undergoing forced
differentiation using the human skeletal muscle specific microarray.
•
To further test the sensitivity and reliability of the microarray in identifying
changes in gene expression in a biological system. Thus ensuring reliable and
reproducible would be attainable from the microarray in subsequent studies
using less readily available human skeletal muscle samples.
•
To investigate the expression of myogenic and atrogenic genes in human
skeletal muscle following an acute bout of resistance exercise.
130
•
To use the human skeletal muscle specific microarray to study the time-course
of transcriptional changes and identify novel genes expressed following an
acute bout of resistance exercise.
•
To identify whether the expression of the novel genes identified in chapter 5
were (1) activated at any time during proliferation, cell cycle arrest or
differentiation or (2) activated by the additional mitogenic and myogenic
stimulation provided by exogenous IGF-1 peptide supplementation.
•
To examine whether the novel genes identified in chapter 5 were a unique
response to resistance exercise or if they were responsive to skeletal muscle
contraction or exercise in general.
II. SUMMARY OF MAJOR FINDINGS
The broad aim of this thesis was to further understand the mechanisms of hypertrophy
by identifying novel genes involved in resistance exercise induced increases in
skeletal muscle mass. In chapter 2, the development of a human skeletal muscle
specific microarray was discussed. Approximately 11,000 cDNA clones derived from a
normalised human skeletal muscle cDNA library were arrayed onto the microarray
along with 270 genes with known functional roles in skeletal muscle. It was
demonstrated that the expression profiling data derived from the microarray was
accurate, reliable and would allow expression analysis and identification of novel
genes in a range of different experimental systems. The results presented
demonstrate the robustness of the microarray in producing accurate and reliable data.
In chapter 3, the human muscle specific microarray was used to profile the temporal
expression of genes during the differentiation of a model of skeletal muscle
myogenesis, rhabdomyosarcoma cells. It was demonstrated that, despite aberrant
differentiation in vivo, during forced differentiation, rhabdomyosarcoma cells exhibit a
pattern of gene expression consistent with that observed during normal myogenesis.
Furthermore, two genes (PTMA and Tim10) were identified as being markedly downregulated during rhabdomyosarcoma differentiation. This was the first study to
investigate the expression of these genes in rhabdomyosarcoma.
131
The activation and proliferation of satellite cells has been identified as a critical
component of adaptive skeletal muscle hypertrophy. In chapter 4, the expression of
several cell cycle regulatory factors was examined following a single bout of
resistance exercise. It was identified that, whilst markers of cell proliferation were not
altered within the 24 h following an acute exercise bout, a marker of cell cycle
withdrawal, p21 was markedly and rapidly induced by 4 h post exercise. Similarly, the
expression of two members of the MRF family, MyoD and myogenin were also rapidly
induced by 4 h. The time-course of these changes however, likely preclude the
involvement of satellite cells in these gene responses. It was proposed that MyoD and
p21 act within the myonuclei of mature myofibres to reduce apoptotic cell death. In
addition, the expression of several negative regulators of skeletal muscle hypertrophy,
myostatin and the atrophy related genes, MURF-1 and atrogin-1 was investigated. To
date, this is the first study to examine the expression of these genes following a single
bout of resistance exercise in human subjects.
In chapter 5, the human skeletal muscle microarray was used to identify novel genes
involved in the early recovery from resistance exercise. Four genes (hypothetical
protein FLJ38973, ASB5, MLP, and TXNIP) demonstrating marked increases in
expression following resistance exercise were identified and had not previously been
investigated in this context. To further understand the functions of these genes in
skeletal muscle, a human primary skeletal muscle cell culture model was employed to
examine the expression of the genes during proliferation, cell cycle arrest and
differentiation. No change in expression was observed for MLP, ASB5 and FLJ38973
throughout the time-course of differentiation. Conversely, TXNIP expression was
rapidly increased and remained elevated throughout the 72 h of differentiation. Finally,
the expression of these novel genes was examined following a single bout of
endurance exercise to determine if the responses observed in chapter 5 were a
unique response to resistance exercise or if they were responsive to skeletal muscle
contraction or exercise in general. The expressions of TXNIP, MLP and FLJ38973
were not altered by the endurance exercise protocol, whilst ASB5 expression
increased at 30 min post exercise.
The results of this thesis describe the identification of four genes whose expression
had not previously been examined in skeletal muscle in response to an acute bout of
resistance exercise; consequently increasing the overall body of knowledge regarding
the transcriptional activity following a single bout of resistance exercise. Additionally,
the potential functions of these genes in the early adaptive response to resistance
exercise was further characterised by examining their expressions during myogenic
differentiation as well as during the recovery from a single bout of endurance exercise.
132
Collectively, the results described in this thesis, in part, describe the potential
functional roles of these genes in skeletal muscle.
A. ASB5
ASB5 was originally detected in endothelial and smooth muscle cells proliferating
rapidly during collateral artery growth following femoral ligation (Boengler et al. 2003).
In this thesis, ASB5 was observed to be up-regulated following both resistance and
endurance exercise bouts, however no change in ASB5 expression was demonstrated
during the differentiation of human primary skeletal muscle cells in culture. From these
and previous studies, it seems that the likely functions of the observed increases in
ASB5 mRNA following endurance and resistance exercise is as an adaptive response
to an increased need for capillaries within the muscle. The exact functional role of the
ASB5 protein in these processes however remains unknown.
B. TXNIP
TXNIP, is a ubiquitous protein that binds with high affinity to thioredoxin and has been
implicated the maintenance of cellular redox state and insulin secretion (Hui et al.
2004), development of hepatic steatosis (Donnelly et al. 2004; Van Greevenbroek et
al. 2004), among others (Ikarashi et al. 2002; Yoshioka et al. 2004). In this thesis,
TXNIP expression was shown to be markedly, and transiently up-regulated 30 min
following a single bout of resistance exercise, whilst no change was observed
following endurance exercise. Interestingly, it was also demonstrated that TXNIP
mRNA was markedly induced during differentiation. Several possible functions for
TXNIP in skeletal muscle can be hypothesized from the results presented here. Firstly,
The lack of induction following endurance exercise seems to suggest a reliance on
conditions specifically imposed on the muscle during resistance type exercise for its
transcriptional activation. Secondly, increased TXNIP expression during differentiation
in vitro might suggest a potential role in the differentiation of satellite cells in vivo.
However, the very early (30 min) and transient nature (return to resting levels by 4 h)
of TXNIP expression following resistance exercise would likely preclude a role for
TXNIP in satellite cell differentiation within this time frame. It is possible therefore, that
TXNIP might be acting within the myonuclei to exert its functions on the
adapting/repairing myofibre. Importantly, considerable work is necessary to further
delineate its functions within skeletal muscle.
133
C. MLP
MLP was originally discovered in denervated skeletal muscle and identified as a
positive regulator of the myogenic program in myogenic cells (Arber et al. 1994). In
this thesis, it was demonstrated for the first time that MLP transcriptional expression is
increased by resistance exercise whilst not being altered following endurance
exercise. Numerous functions have been attributed to MLP in skeletal muscle
including facilitating the assembly or stabilization of the myofibril apparatus (Flick and
Konieczny 2000) contributing to the mechanical stretch sensor machinery (Knoll et al.
2002), and regulating myogenesis through the interaction with the myogenic
transcription factors, MyoD, Myf6 and myogenin (Kong et al. 1997). Collectively these
data seem to suggest multiple complementary roles for MLP in sensing mechanical
stretch, regulating the subsequent transcriptional response and ultimately facilitating
the assembly or stabilization of the contractile apparatus. Thus it appears that in
response to a stimulus like resistance exercise, MLP plays a critical and coordinated
role in the repair and adaptation of skeletal muscle.
D. Hypothetical Protein FLJ38973
The hypothetical protein FLJ38973 was originally identified during a large-scale
screen of ESTs for the purpose of identifying the full-open reading frame cDNA
sequence for each human and mouse gene (Mammalian Gene Collection Program
Team et al. 2002). Whilst no subsequent study has investigated FLJ38973,
bioinformatics analysis using revealed that it is located on chromosome 2 and
produces, by alternative splicing, 2 different transcripts (aDec03, bDec03) together
encoding 2 different protein isoforms. In the thesis, FLJ38973 mRNA was
demonstrated to be up-regulated following an acute bout of resistance exercise, whilst
no changes in expression were observed during differentiation or following a single
bout of endurance exercise. This is the first collection of studies to investigate this
gene and provides valuable data on its possible functions in vivo. Considerable work
is necessary to further characterise the tissue distribution, cellular localisation, and
most important, biological functions of the protein(s) encoded by this gene.
134
III. FUTURE DIRECTIONS
This thesis describes the identification and characterisation of four novel genes whose
expression was increased during the early recovery from a single bout of resistance
exercise in human vastus lateralis muscle. Subsequently, the expression patterns of
these genes was investigated during the differentiation of primary human skeletal
muscle cells in culture as well as following a single bout of endurance exercise. Whilst
these studies go some way towards characterising the functions of these genes,
considerable work is necessary to delineate their biological functions in skeletal
muscle. In this section, details of future studies designed to advance current
understanding of functions of these gene products will be discussed.
Throughout this thesis, each study focused not only on the identification of novel
genes, but also on understanding further the importance of the myogenic pathways in
the development of skeletal muscle hypertrophy. Despite the recent advances in the
understanding
of
the
molecular
regulation
of
skeletal
muscle
hypertrophy,
considerable gaps remain. Further research required to advance knowledge in this
area will be discussed.
A. Functional analysis of novel gene targets using gene
knockdown and over-expression techniques
1. Background
In chapter 5, the identification of several novel resistance exercise responsive genes
was discussed. Subsequently, the potential functions of these genes were examined
during myogenic differentiation in culture (chapter 6) and following a single bout of
endurance exercise (chapter 7). Whilst these studies provided considerable
information on the transcriptional regulation of these genes, very little is currently
known about their functions within skeletal muscle. Targeted gene knockdown and
over-expression techniques are effective ways of analysing the functions of genes in
vitro.
2. Aims
(i)
To investigate the functions of selected genes by examining the
phenotypic changes induced by targeted knockdown in myogenic
cells in culture.
135
(ii)
To investigate the functions of selected genes by examining the
phenotypic changes induced by targeted over-expression in myogenic
cells in culture.
3. Key Methods
3.1 RNA Interference
RNAi has been widely adopted as the simplest and most effective method of
suppressing a gene’s product resulting in null or hypomorphic phenotypes.
Subsequently, the biological effects of knocking down a target gene can be examined
and functions of a gene inferred. In mammalian cells, RNAi is typically induced by the
introduction of small inhibitory RNAs (siRNA) (specifically designed to target the gene
of interest whilst minimizing the effects on non-target genes) into the cell culture
system (Sago et al. 2004).
Following siRNA synthesis, delivery of the siRNA into the cell system is usually
accomplished via transfection with a lipid- or amine-based reagent. Delivery into
primary cells, however, can be problematic, if not impossible, using standard
transfection methodologies. In these cases, electroporation using a specialized,
gentle-on-cells buffer and optimized pulsing conditions generally results in very
efficient siRNA delivery without compromising cell viability. Following transfection, the
effectiveness of the siRNA in inducing knockdown of its intended target needs to be
assessed. siRNAs exert their effects at the mRNA level, therefore, quantitative realtime PCR analysis would be required for siRNA validation and transfection
optimization purposes. Subsequently, the effect of the targeted knock-down of the
gene can be assayed using standard functional, morphological and phenotypical
measures. For example, targeted gene knockdown of IL-6 in muscle cells has been
used previously to examine its effect on myogenic differentiation (Baeza-Raja and
Munoz-Canoves 2004).
3.2 Over-expression studies
Over-expression techniques involve the forced expression of a specific gene and
subsequent examination of biological changes induced by the gene product. Standard
techniques are available for cloning of the selected gene into an expression plasmid
and the transient transfection of the target gene into the cell line of interest. Classical
136
transfection technologies that are widely used include the DEAE-dextran method, the
calcium phosphate method, electroporation, and liposome mediated transfection.
Following verification and optimisation of the transfection techniques, standard
functional, morphological and phonotypical measures would be employed to examine
the effect of the forced over-expression of the gene. For example, over-expression
studies have been effectively employed to examine the effect of integrin binding
proteins on muscle differentiation (Li et al. 1999) and the effect of Chemokine-like
factors on myoblast proliferation (Xia et al. 2002).
4. Significance
The genes identified in this thesis are all likely to be involved in the repair or
adaptation of muscle. Therefore measures of proliferation (e.g. PCNA mRNA, DNA
content), differentiation (e.g. creatine kinase activity, MHC protein content) and
myofibre size (hypertrophy) would all be appropriate end-point measures to assess
possible functions of each target gene in vitro. For example, the knock-down of a gene
exhibiting markedly reduced creatine kinase activity and MHC expression would likely
play a critical role in myogenic differentiation. Similarly, dramatic increases in the rate
of proliferation following the over-expression of a particular gene would likely indicate
a role in the cellular proliferation. Therefore these studies would be valuable in further
examining the functions of these genes in skeletal muscle.
B. Examination of cellular localisation and tissue distribution of
selected novel genes
1. Background
Microarray analysis and gene expression analysis in general are valuable measures of
the regulation of biological processes. However, mRNA expression patterns are by
themselves insufficient for the quantitative description of a biologically active product.
Further examination of the functions of the novel resistance exercise sensitive genes
would be advanced by the examination of the cellular localisation and tissue
distribution of the proteins encoded by each gene. Whilst commercially produced
antibodies may be available for some of the proteins of interest, others may need to
be custom produced. The development of a polyclonal antibody to target the protein
encoded by the gene of interest would provide numerous avenues for further
investigation into its functions.
137
2. Aims
(i)
To investigate the cellular localisation of selected novel proteins in
skeletal muscle using confocal microscopy.
(ii)
To investigate the tissue distribution of selected novel genes using
western blot analysis
3. Key Methods
3.1 Fluorescence Microscopy
Specific primary antibodies could be used to examine the cellular localisation (if not
already known) of the novel skeletal muscle sensitive proteins. Furthermore,
immunohistochemical techniques could be used to track the cellular localisation of
these proteins in mounted muscle tissue following, for example, a single bout of
resistance exercise. Similarly, immunocytochemical techniques might be used to
examine the possible changes in cellular localisation during proliferation and
differentiation of satellite cells in culture.
3.2 Western Blot Analysis
The development of specific primary antibodies or the use of commercially available
antibodies specific to the protein of interest would provide an opportunity to compare
the expression of the selected protein across many different tissues. Analysis of the
protein expression in many tissues would be carried out using standard western
analysis techniques.
4. Significance
These analysis strategies would further advance current understanding of the potential
functions and mechanisms of actions of the proteins encoded by these novel genes.
For example tissue distribution analysis might reveal that a particular protein is
expressed exclusively in skeletal muscle or alternatively is enriched in skeletal and
cardiac muscles tissues whilst demonstrating minimal expression in other tissues.
Such a protein would be of particular interest as a potentially critical mediator of the
skeletal muscle phenotype.
138
C. Effects of resistance exercise training on the expression of
selected novel resistance exercise responsive genes
1. Background
The novel resistance exercise sensitive genes discussed in this thesis were identified
following a single bout of resistance exercise. However a single bout of resistance
exercise is unlikely to confer marked phenotypic or functional changes within the
skeletal musculature. Therefore it would be of interest to examine the effects of a
resistance exercise training protocol, of sufficient intensity and duration to induce
marked increases in muscle hypertrophy and strength, on the expression of these
previously identified genes.
2. Aims
(i)
To examine the mRNA expression of novel resistance exercise
sensitive genes following 12 weeks of high intensity resistance
exercise training.
(ii)
To examine the protein expression of novel resistance exercise
sensitive genes following 12 weeks of high intensity resistance
exercise training.
3. Key Methods
Approximately 10 young male subjects would be recruited to undergo a 12 week
heavy resistance exercise training protocol. Vastus lateralis muscle biopsies would be
collected before exercise and following a single bout of resistance exercise. Following
the 12 weeks of training, subsequent biopsies would be collected at rest and again
following a single bout of exercise.
RNA and protein would be extracted from the muscle biopsies and analysed to
measure RNA and protein expression for each of the novel resistance exercise
sensitive genes.
4. Significance
The study would provide further valuable data on both the transcriptional regulation of
these genes as well as the translational regulation of the proteins following a single
bout of resistance exercise. The great advantage of this study design would however,
be to examine the effect of training on the expression of these genes and proteins. If
these genes are indeed important regulatory components of the hypertrophic
response, a marked increase in their expression would be likely following the intensive
139
training regime. Thus valuable data collected from this study would further current
understanding of the molecular regulation of skeletal muscle hypertrophy.
D.
Identification
of
novel
genes
demonstrating
decreased
expression following acute resistance exercise
1. Background
In chapter 5, a human skeletal muscle specific microarray was used to examine the
global transcriptional response of skeletal muscle to a single bout of resistance
exercise. 7,229 elements out of the 11,000 spotted onto the microarray showed
adequate expression levels, with 3112 elements demonstrating increased expression
following resistance exercise whilst 1436 elements decreased in expression.
Considerable time and cost involved in sequencing gene elements prevented the
analysis of all differentially expressed elements so a subset of these genes were
selected for sequencing and further analysis. Only genes demonstrating increased
expression were selected for this analysis. Genes showing reduced expression
however are likely to constitute and equally important biological adaptation following
resistance exercise.
2. Aims
(i)
To examine the collected microarray data to identify novel genes
down-regulated following a single bout of resistance exercise in
human subjects.
3. Key Methods
3.1 Microarray data analysis
Further detailed analysis of the collected microarray data would be required to isolate
elements demonstrating marked and consistently reduced expression following a
single bout of resistance exercise. A subset of these elements will be selected for
further analysis.
3.2 Sequencing
Sequencing analysis would be performed on the selected clones as previously
described.
140
3.3 Bioinformatics analysis
Extensive bioinformatical analysis will be performed on the selected genes to identify
the gene sequence, transcript structure, amino acid profile in addition to known or
predicted functions of the protein.
3.4 Real-Time PCR
Real-Time PCR analysis would be performed to validate the results of the microarray.
4. Significance
Several proteins (most notably myostatin) have recently been identified as powerful
negative regulators of skeletal muscle mass. Further analysis of the microarray data
collected for this thesis has the potential to isolate further novel genes with critical
biological roles in skeletal muscle.
E. Examination of alternate pathways potentially involved in
skeletal muscle hypertrophy
1. Background
Considerable recent research into the molecular mechanisms regulating skeletal
muscle mass has greatly enhanced the current understanding of this complex
process. In this thesis, several novel resistance exercise responsive genes have been
identified that might constitute important components of early adaptive response to
resistance exercise. Furthermore, a number of genes with identified roles in
myogenesis were examined to investigate potential roles in the early adaptive
response to resistance exercise. Despite these recent breakthroughs, a substantial
amount of work is required to further unlock the complex regulatory mechanisms
mediating skeletal muscle hypertrophy. For example, the mechanism(s) by which
skeletal muscle senses skeletal muscle contraction and transduces this information
into downstream cellular level responses remains unknown. Similarly, it is unclear how
satellite cells and mature myofibres act cooperatively to mediate myofibre adaptation
and hypertrophy. It is likely that there are numerous as yet uncharacterised pathways
that might contribute to skeletal muscle hypertrophy however further research is
necessary to investigate these questions further.
2. Suggested targets for further investigation
Recent research has demonstrated that the Notch signalling pathway is a key
determinant of muscle regeneration. Importantly, components of the Notch signalling
141
mechanism are impaired with age, contributing to the reduced regenerative potential
evident in elderly muscle (Conboy et al. 2003). It is unclear whether this pathway plays
an important role in the regeneration of human skeletal muscle nor whether it might
contribute to skeletal muscle adaptation and hypertrophy. Therefore, this pathway
constitutes a potentially interesting target for further investigation.
Much of our understanding of the biology of skeletal muscle has come from the study
of embryonic muscle development. The processes of muscle regeneration and
adaptation has been described as a recapitulation of the stages of embryonic muscle
development and subsequently may share parallel morphological steps (Grounds
1991; Chambers and McDermott 1996). These initial stages of myogenesis are
regulated by positive and negative signals, including Wnt, bone morphogenetic protein
and sonic hedgehog family members. Therefore, these myogenic regulators would
provide interesting candidates as potential mediators skeletal muscle adaptation.
142
IV. CONCLUSIONS
In summary, the findings of this thesis are as follows:
1. The mRNA expression of two genes, PTMA and Tim10 were identified as
being
down-regulated
following
forced
myogenic
differentiation
of
rhabdomyosarcoma cells.
2. The temporal pattern of the MRF expression over the time-course
rhabdomyosarcoma differentiation was identified as exhibiting a remarkably
similar pattern of expression to that exhibited in normal myogenesis.
3. A single bout of resistance exercise was shown to be sufficient to increase the
expression of the MRF member’s myogenin and MyoD but not Myf5 and Myf6.
The cell cycle regulator p21 was demonstrated to increase following
resistance exercise whilst no change was observed for PTMA, cyclin D1 and
p27. Myostatin mRNA expression was shown to be significantly reduced
following acute resistance exercise.
4. Four novel genes (ASB5, TXNIP, MLP, FLJ38973) were identified as being
increased following an acute bout of resistance exercise. These genes have
not previously been implicated in the early molecular response of skeletal
muscle to resistance exercise in humans.
5. The expression of TXNIP was demonstrated to be increased during the
differentiation of human primary skeletal muscle cell culture. ASB5, MLP and
FLJ38973 expression was not altered during differentiation.
6. The expression of ASB5 was increased following a single bout of endurance
exercise. The expression of MLP, TXNIP and FLJ38973 was not altered by
this exercise protocol. Similarly, the expression of the MRFs was not altered
by a single bout of endurance exercise.
143
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167
APPENDIX A
ANKYRIN REPEAT AND SOCS BOX-CONTAINING PROTEIN5
Official Gene Name: Ankyrin repeat and SOCS box-containing protein 5
Official Gene Symbol: ASB5
Alternative symbols: None
Chromosomal Location: 4q34.2
Gene Size: 55.4 kb
Number of Exons: 7
mRNA Length: 8613 bases
Open Reading Frame Length: 987 bases (329 amino acids)
Protein pI/Mw: 6.34 / 36340.85
Transcript Structure:
Int 3
712 bp
2841 bp
160
4145 bp
1090 bp
Ex 7
43571 bp
Ex 6
Int 6
Ex 4
Ex 5
Int 5
Ex 3
Int 4
Ex 2
Int 2
Ex 1
Int 1
Ex 1
Ex 2
Ex 3
Ex 5
Ex 6
Ex 7
196 bp
80 bp
108 bp
135 bp
192 bp
128 bp
Ex 4
151 bp
168
cDNA and amino acid sequence:
ACCAGCTGATATTTTCTTTCCTCAGGACCAGCTGTTCAGGAGCATCCCGGACGAGAGCCA
GGCACATTTGAGACTTGGATCCAACTAAAGACCGCCGCAGATTCTTCTGCAGCAATGTCG
M S
GTGTTAGAAGAAAATCGGCCGTTTGCTCAACAATTATCCAATGTCTACTTTACAATACTT
V L E E N R P F A Q Q L S N V Y F T I L
TCGCTGTTCTGTTTTAAGCTTTTTGTGAAAATCAGCCTTGCCATCCTCAGTCATTTCTAC
S L F C F K L F V K I S L A I L S H F Y
ATAGTGAAAGGCAACCGCAAGGAAGCGGCAAGGATAGCAGCTGAATTTTATGGAGTAACC
I V K G N R K E A A R I A A E F Y G V T
CAAGGACAAGGTTCCTGGGCAGATCGATCACCACTACATGAAGCAGCAAGTCAAGGTCGC
Q G Q G S W A D R S P L H E A A S Q G R
CTTCTTGCTCTGAGAACATTATTATCACAGGGTTATAATGTAAATGCAGTAACCTTAGAC
L L A L R T L L S Q G Y N V N A V T L D
CATGTCACCCCATTGCACGAAGCCTGCCTTGGAGATCACGTGGCATGTGCCAGAACTCTG
H V T P L H E A C L G D H V A C A R T L
CTGGAAGCAGGAGCTAATGTAAATGCAATCACGATAGATGGCGTGACTCCGTTATTCAAC
L E A G A N V N A I T I D G V T P L F N
GCATGCTCCCAAGGCAGTCCAAGCTGTGCAGAGCTGCTTCTGGAGTATGGTGCCAAAGCC
A C S Q G S P S C A E L L L E Y G A K A
CAGCTGGAGTCATGTCTTCCATCCCCAACGCATGAGGCCGCCAGTAAAGGTCACCATGAA
Q L E S C L P S P T H E A A S K G H H E
TGTCTTGACATCCTGATATCCTGGGGCATAGATGTTGACCAAGAAATTCCTCATTTGGGA
C L D I L I S W G I D V D Q E I P H L G
ACTCCTCTCTATGTAGCTTGTATGTCACAGCAATTCCATTGCATCTGGAAGCTTCTTTAT
T P L Y V A C M S Q Q F H C I W K L L Y
GCTGGTGCTGACGTACAGAAAGGCAAATATTGGGATACTCCATTACATGCTGCTGCTCAA
A G A D V Q K G K Y W D T P L H A A A Q
CAATCCAGCACAGAAATTGTAAACTTACTGCTAGAATTTGGAGCAGATATCAATGCCAAA
Q S S T E I V N L L L E F G A D I N A K
AATACAGAGCTTCTGCGACCTATAGATGTAGCTACGTCTAGCAGTATGGTGGAAAGGATA
N T E L L R P I D V A T S S S M V E R I
TTGCTTCAACATGAAGCTACCCCAAGCTCTCTTTACCAACTTTGCCGACTCTGTATCCGA
L L Q H E A T P S S L Y Q L C R L C I R
AGCTACATAGGAAAACCAAGATTGCACCTTATCCCACAACTCCAGCTGCCAACGTTACTG
S Y I G K P R L H L I P Q L Q L P T L L
AAGAATTTCTTACAGTATCGATAAAACAGTAAAGTAATTCTAAATACCTTGAAAATCAAA
K N F L Q Y R *
ATTTCTATTTCTTTTGCTTAAGGAATAGTTCATATAAAAATATGCTAAAGATAGGATAAA
AGTGAGTGTGAGATCACCCAGGGAAGCAGTAAAATATCAATTTTCATTTTAAGTGTATTA
GTACTATTGTTTTATCATTTATGCTGTCTTTGGATTATAGCATATTTATAATATCTATTT
TTTGTTATTTCAATATACCCTCCTGTTTATTCAGGAAAAAATAATAAAGTCACTATCTTA
TGTTTTCTTTTGGATTGGAAAGAAATAAAGCTCCTAGTAAAGTTATTCATATTATATTTA
AAAAGGTCTATGTTCTTCAACTAATGGGTTAACTTTTTAATTTTGGCTATTGTAATTGGC
TAACTTGTTACTGATATTGACATAAAATATGAATATGGCTTAGCAAAGAGCAACTAATAT
GTTTTCTGAAACCAGGATGATGCTCATTCAGGAAATCCACTATGTTGAATGTCCACTGGT
CATTAGAATGAACACTTCATAAAGATAAATTGCCCCCCTCTCCCCCACTTACCCCTGGCA
AAGGACTCACAAGTCACTTCTCTTCTCCATAGTACATGGACTTGTTACAGAAAAGTGATA
GGATGAAAGGTCAATACTGCCCTCTCACCCTGAGATATTTAGAACATTACACACCTTCTA
AGGCTATGTTAAGACTGCCTCCTTCTCAGGAGTAGCCCCTGATGATCTCTTATCAAGGCG
GTTATATGCATATTACTCCAGCCTTCTTCCATTTCAGAAATTGTCAATAGCTAGTGATAC
TTGGACTTAAGAAAATGAACTATATATCTAATTAACAAACAGGCCCTGGATCATATTCCG
GGGATCATCACATCAGTCCAAGGATATAAAAAAATGGAAGATTAAAAACTCAAATTGTGG
AGTTTTTAAAGAGTGGGTGCCACTTAACACATTGGAGACCTTAAAAAATGTATATAGAGA
ACTTAATCGCACTGTTTCTAATTCTTTTTACACAAAACAAGGGCTTAGAGTATACTGTAT
TTGCAAGTAATAGCAAGAGAGTATTGTATAAAAGAAGATATTACTAAGCTAGTCCTCTGC
AAGGGTAAATACTACGTTTATTCTCTTCAGCTTTAACTATACTTGAGTGCAATAAAAAAC
169
TTAATAAAATTTTATGCCTGTTTTGTAATTCAGGGCCTATTATGATTTTAGAAATAAGAT
AATCAACGTACAACTCTTTGTAAAACAAAAGCAACTTTGGGTGAGTTTTATAGATTTATT
AAATTTTGATAAAGTAAATATTTTGACCACTATTTTCAACAACCCAGGGCTTATTTTCTT
CTGACTTCTTGGCTAACTTCCAGACTATGGGAAAATAAATTATGATTGTATGTGACCCCC
AGATCACTAAGCTTGCATTTTGGCAGAAAGAAAAAAAATCAGTTGTGATTTAAAACGTTT
GTTGAGATTTTCAAACATAGAAATAAAGCTGTAGCATATTCACTAAACAATGTTTTATAT
GAGGATAGGGACCTTTAAATATGTGTTTTATAGAATATCTCACACATTTGTAATGGATAA
CGTGCATTAAAATGGAGTTCTTATTATAGAATAACCTGGTTAAACAGATATTAAAGCTGC
TTTTGGGTAAAACAGGTTTCCACCAGTATTTTCCCTGAGCTAGAGGAGAAGTCTTAGATT
TTAAGAGTAATACAACCCATCTATCTTATTAGTCTTGTGCCAATAAGAGAAGTAAATATC
AAACATTAAAATGGTCACTTTACAATTTCAGTATGTCTGTACCTTGTATCTTAGCTTGAG
TATGATTGTCTTATCAAAGTAGTGTTCTAACTTTAATGTATTGTATGTTTGTTATTATAT
TAAAGTGTGATTATTATTCATTGG
The coding sequence of the ASB5 cDNA and its deduced amino acid
translation (in black). Exons are represented in alternating blue and red text,
whilst non-coding regions are highlighted in yellow. The stop codon (TGA) is
shown as an asterisk (*).
170
APPENDIX B
THIOREDOXIN INTERACTING PROTEIN
Official Gene Name: Thioredoxin interacting protein
Official Gene Symbol: TXNIP
Alternative Gene Names: THIF, VDUP1, HHCPA78, EST01027
Chromosomal Location: 1q21.2
Gene Size: 3.9 kb
Number of Exons: 8
mRNA Length: 8820 bases
Open Reading Frame Length: 1173 bases (391 amino acids)
Protein pI/Mw: 7.46 / 43689.39
Int 5
Int 7
106 b p
128 bp
In t 6
1 13 b p
Ex 6
Ex 3
Ex 7
Int 4
12 8 bp
Ex 5
Int 2
11 2 bp
Ex 4
In t 1
Ex 8
Int 3
1 12 b p
5 40 b p
Ex 2
Ex 1
Transcript Structure:
Ex 1
Ex 2
Ex 4
Ex 6
Ex 8
471 b p
73 bp
103 b p
1 57 bp
13 37 bp
Ex 3
Ex 5
Ex 7
14 8bp
25 7 bp
15 2 bp
171
cDNA and amino acid sequence:
GCTTAGTGTAACCAGCGGCGTATATTTTTTAGGCGCCTTTTCGAAAACCTAGTAGTTAAT
ATTCATTTGTTTAAATCTTATTTTATTTTTAAGCTCAAACTGCTTAAGAATACCTTAATT
CCTTAAAGTGAAATAATTTTTTGCAAAGGGGTTTCCTCGATTTGGAGCTTTTTTTTTCTT
CCACCGTCATTTCTAACTCTTAAAACCAACTCAGTTCCATC
ATGGTGATGTTCAAGAAGATCAAGTCTTTTGAGGTGGTCTTTAACGACCCTGAAAAGGTG
M V M F K K I K S F E V V F N D P E K V
TACGGCAGTGGCGAGAAGGTGGCTGGCCGGGTGATAGTGGAGGTGTGTGAAGTTACTCGT
Y G S G E K V A G R V I V E V C E V T R
GTCAAAGCCGTTAGGATCCTGGCTTGCGGAGTGGCTAAAGTGCTTTGGATGCAGGGATCC
V K A V R I L A C G V A K V L W M Q G S
CAGCAGTGCAAACAGACTTCGGAGTACCTGCGCTATGAAGACACGCTTCTTCTGGAAGAC
Q Q C K Q T S E Y L R Y E D T L L L E D
CAGCCAACAGGTGAGAATGAGATGGTGATCATGAGACCTGGAAACAAATATGAGTACAAG
Q P T G E N E M V I M R P G N K Y E Y K
TTCGGCTTTGAGCTTCCTCAGGGGCCTCTGGGAACATCCTTCAAAGGAAAATATGGGTGT
F G F E L P Q G P L G T S F K G K Y G C
GTAGACTACTGGGTGAAGGCTTTTCTTGACCGCCCGAGCCAGCCAACTCAAGAGACAAAG
V D Y W V K A F L D R P S Q P T Q E T K
AAAAACTTTGAAGTAGTGGATCTGGTGGATGTCAATACCCCTGATTTAATGGCACCTGTG
K N F E V V D L V D V N T P D L M A P V
TCTGCTAAAAAAGAAAAGAAAGTTTCCTGCATGTTCATTCCTGATGGGCGGGTGTCTGTC
S A K K E K K V S C M F I P D G R V S V
TCTGCTCGAATTGACAGAAAAGGATTCTGTGAAGGTGATGAGATTTCCATCCATGCTGAC
S A R I D R K G F C E G D E I S I H A D
TTTGAGAATACATGTTCCCGAATTGTGGTCCCCAAAGCTGCCATTGTGGCCCGCCACACT
F E N T C S R I V V P K A A I V A R H T
TACCTTGCCAATGGCCAGACCAAGGTGCTGACTCAGAAGTTGTCATCAGTCAGAGGCAAT
Y L A N G Q T K V L T Q K L S S V R G N
CATATTATCTCAGGGACATGCGCATCATGGCGTGGCAAGAGCCTTCGGGTTCAGAAGATC
H I I S G T C A S W R G K S L R V Q K I
AGGCCTTCTATCCTGGGCTGCAACATCCTTCGAGTTGAATATTCCTTACTGATCTATGTT
R P S I L G C N I L R V E Y S L L I Y V
AGCGTTCCTGGATCCAAGAAGGTCATCCTTGACCTGCCCCTGGTAATTGGCAGCAGATCA
S V P G S K K V I L D L P L V I G S R S
GGTCTAAGCAGCAGAACATCCAGCATGGCCAGCCGAACCAGCTCTGAGATGAGTTGGGTA
G L S S R T S S M A S R T S S E M S W V
GATCTGAACATCCCTGATACCCCAGAAGCTCCTCCCTGCTATATGGATGTCATTCCTGAA
D L N I P D T P E A P P C Y M D V I P E
GATCACCGATTGGAGAGCCCAACCACTCCTCTGCTAGATGACATGGATGGCTCTCAAGAC
D H R L E S P T T P L L D D M D G S Q D
AGCCCTATCTTTATGTATGCCCCTGAGTTCAAGTTCATGCCACCACCGACTTATACTGAG
S P I F M Y A P E F K F M P P P T Y T E
GTGGATCCCTGCATCCTCAACAACAATGTGCAGTGAGCATGTGGAAGAAAAGAAGCAGCT
V D P C I L N N N V Q *
TTACCTACTTGTTTCTTTTTGTCTCTCTTCCTGGACACTCACTTTTTCAGAGACTCAACA
GTCTCTGCAATGGAGTGTGGGTCCACCTTAGCCTCTGACTTCCTAATGTAGGAGGTGGTC
AGCAGGCAATCTCCTGGGCCTTAAAGGATGCGGACTCATCCTCAGCCAGCGCCCATGTTG
TGATACAGGGGTGTTTGTTGGATGGGTTTAAAAATAACTAGAAAAACTCAGGCCCATCCA
TTTTCTCAGATCTCCTTGAAAATTGAGGCCTTTTCGATAGTTTCGGGTCAGGTAAAAATG
GCCTCCTGGCGTAAGCTTTTCAAGGTTTTTTGGAGGCTTTTTGTAAATTGTGATAGGAAC
172
TTTGGACCTTGAACTTATGTATCATGTGGAGAAGAGCCAATTTAACAAACTAGGAAGATG
AAAAGGGAAATTGTGGCCAAAACTTTGGGAAAAGGAGGTTCTTAAAATCAGTGTTTCCCC
TTTGTGCACTTGTAGAAAAAAAAGAAAAACCTTCTAGAGCTGATTTGATGGACAATGGAG
AGAGCTTTCCCTGTGATTATAAAAAAGGAAGCTAGCTGCTCTACGGTCATCTTTGCTTAA
GAGTATACTTTAACCTGGCTTTTAAAGCAGTAGTAACTGCCCCACCAAAGGTCTTAAAAG
CCATTTTTGGAGCCTATTGCACTGTGTTCTCCTACTGCAAATATTTTCATATGGGAGGAT
GGTTTTCTCTTCATGTAAGTCCTTGGAATTGATTCTAAGGTGATGTTCTTAGCACTTTAA
TTCCTGTCAAATTTTTTGTTCTCCCCTTCTGCCATCTTAAATGTAAGCTGAAACTGGTCT
ACTGTGTCTCTAGGGTTAAGCCAAAAGACAAAAAAAATTTTACTACTTTTGAGATTGCCC
CAATGTACAGAATTATATAATTCTAACGCTTAAATCATGTGAAAGGGTTGCTGCTGTCAG
CCTTGCCCACTGTGACTTCAAACCCAAGGAGGAACTCTTGATCAAGATGCCGAACCCTGT
GTTCAGAACCTCCAAATACTGCCATGAGAAACTAGAGGGCAGGTCTTCATAAAAGCCCTT
TGAACCCCCTTCCTGCCCTGTGTTAGGAGATAGGGATATTGGCCCCTCACTGCAGCTGCC
AGCACTTGGTCAGTCACTCTCAGCCATAGCACTTTGTTCACTGTCCTGTGTCAGAGCACT
GAGCTCCACCCTTTTCTGAGAGTTATTACAGCCAGAAAGTGTGGGCTGAAGATGGTTGGT
TTCATGTTTTTGTATTATG
The coding sequence of the TXNIP cDNA and its deduced amino acid
translation (in black). Exons are represented in alternating blue and red text,
whilst non-coding regions are highlighted in yellow. The stop codon (TGA) is
shown as an asterisk (*).
173
APPENDIX C
MUSCLE LIM PROTEIN
Official Gene Name: Cysteine and glycine rich protein 3
Official Gene Symbol: CRP3
Alternate Gene Names: Muscle LIM Protein (MLP), cardiac LIM protein (CLP),
LMO4, CMD1M
Chromosomal Location: 11p15.1
Gene Size: 10.1 kb
Number of Exons: 5
mRNA Length: 5693 bases
Open Reading Frame Length: 582 bases (194 amino acids)
Protein pI/Mw: 8.89 / 20968.89
Int 5
1170 bp
2205 bp
Ex 6
Int 4
1787 bp
Ex 5
Int 3
4032 bp
Ex 4
Int 2
9477 bp
Ex 3
Int 1
Ex 2
Ex 1
Transcript Structure:
Ex 1
Ex 2
Ex 3
Ex 4
Ex 5
Ex 6
101 bp
140 bp
169 bp
133 bp
94 bp
470 bp
174
cDNA and amino acid sequence:
CCCTTCCCCCAGCAGGCCAAGGCTGGTGACAGCCTTCATATATTTAAAGAGGACAAGAGC
CCCTCAGACTCAGTTGAGCTGAACGGAGTCCACACAGGCAGACTTGACCTTGACCAGATA
GTCTTCAAGATGCCAAACTGGGGCGGAGGCGCAAAATGTGGAGCCTGTGAAAAGACCGTC
M P N W G G G A K C G A C E K T V
TACCATGCAGAAGAAATCCAGTGCAATGGAAGGAGTTTCCACAAGACGTGTTTCCACTGC
Y H A E E I Q C N G R S F H K T C F H C
ATGGCCTGCAGGAAGGCTCTTGACAGCACGACAGTCGCGGCTCATGAGTCGGAGATCTAC
M A C R K A L D S T T V A A H E S E I Y
TGCAAGGTGTGCTATGGGCGCAGATATGGCCCCAAAGGGATCGGGTATGGACAAGGCGCT
C K V C Y G R R Y G P K G I G Y G Q G A
GGCTGTCTCAGCACAGACACGGGCGAGCATCTCGGCCTGCAGTTCCAACAGTCCCCAAAG
G C L S T D T G E H L G L Q F Q Q S P K
CCGGCACGCTCAGTTACCACCAGCAACCCTTCCAAATTCACTGCGAAGTTTGGAGAGTCC
P A R S V T T S N P S K F T A K F G E S
GAGAAGTGCCCTCGATGTGGCAAGTCAGTCTATGCTGCTGAGAAGGTTATGGGAGGTGGC
E K C P R C G K S V Y A A E K V M G G G
AAGCCTTGGCACAAGACCTGTTTCCGCTGTGCCATCTGTGGGAAGAGTCTGGAGTCCACA
K P W H K T C F R C A I C G K S L E S T
AATGTCACTGACAAAGATGGGGAACTTTATTGCAAAGTTTGCTATGCCAAAAATTTTGGC
N V T D K D G E L Y C K V C Y A K N F G
CCCACGGGTATTGGGTTTGGAGGCCTTACACAACAAGTGGAAAAGAAAGAATGAAGAGGT
P T G I G F G G L T Q Q V E K K E *
GCGCCGTTTCTCAGATTTTTTGCGAGCCTAAAACACTTGCCAAGTAATCCTGCACAGATC
GATACCTTTCCCCAAATAGCCTCTCCTTTGTAGTCGTACATTATGTGTTTCTCCTCAGAA
GTGATCAGGTCTTTACTGAATGTTAGAAGAGGCCTTTGGAAGAAAATTATGTAAAGTTTA
ATCTATAACAAATGCTTTATTATTTATAATGCTTGGAATGGGAGAGGCAATAAATAAATG
TTTTAGTGCTATCTTGTATGGCTCTAGATCTTTTCTTTGAGATAGAAATTTTCAAAAACA
TAAAGCTAGTTCAAAAAACGAGTTGCAGAGCATATAATAAATTTGGATGTCAACTGAGAA
AGGAGTGAGAAGGAAGAAACAATGCGCAAAGGAAAGCAGTCTTTCAGAATCTGTCAGCCA
AGTGTCTTTCTAGTTACTGCTAATGGAGAAGAAAACAGGGGGTCTGGGAGAAAATAGAGA
ACATGATAGCAAAATCTAAAAGGAAAATCAAAACTAATAAAATTGCTGAAGAGTTGATCC
CTTTGTCCTATCGTGGGGCTTTGTAATGTTACACATCTCGTGAAAACTCAGAAATGACAA
TAAAGCGTGGCATTTGCCTCTGTATTATAAATG
The coding sequence of the MLP cDNA and its deduced amino acid translation
(in black). Exons are represented in alternating blue and red text, whilst noncoding regions are highlighted in yellow. The stop codon (TGA) is shown as an
asterisk (*).
175
APPENDIX D
HYPOTHETICAL PROTEIN FLJ38973
Official Gene Name: Hypothetical Protein FLJ38973
Official gene symbol: FLJ38973
Alternative symbols: None
Gene Product: hypothetical protein FLJ38973
Chromosomal Location: 2q33.1
Gene Size: 17.0 kb
Number of Exons: 2
mRNA length: 8021 bases
Open Reading Frame Length: 807 bases (269 amino acids)
Protein pI/Mw: 8.65 / 30918.17
Transcript Structure:
13290 bp
Ex 2
Ex 1
Int 1
Ex 1
Ex 2
472 bp
3208 bp
176
cDNA and amino acid sequence:
GCCTCAGCGCCGGCTCCCGGCCGGGCCGCGGCCGCCGACCGTTGAGCCGCCGGCTGAGCC
GCCTGCTGAAGTCCCTCCCTCAGGAACCCCTCCGCCACCCTCCACCTCCGAACCGCTCTC
GCGGCGGCGACCC
ATGTGGGGGTTCAGGCTCCTGCGGTCGCCGCCGTTGCTGCTCCTGCTGCCGCAGCTCGGA
M W G F R L L R S P P L L L L L P Q L G
ATCGGAAACGCCTCGTCCTGCTCTCAGGCCAGAACCATGAACCCGGGCGGCAGCGGCGGC
I G N A S S C S Q A R T M N P G G S G G
GCGCGATGCTCCCTCTCGGCCGAGGTGCGCCGCCGTCAGTGCCTGCAGCTTTCCACCGTG
A R C S L S A E V R R R Q C L Q L S T V
CCTGGAGCCGATCCGCAGCGCAGCAACGAATTGCTCCTGTTGGCGGCGGCCGGGGAGGGA
P G A D P Q R S N E L L L L A A A G E G
CTGGAGCGGCAGGACCTCCCCGGGGACCCAGCGAAGGAGGAGCCGCAGCCGCCGCCCCAG
L E R Q D L P G D P A K E E P Q P P P Q
CATCACGTCCTCTATTTCCCTGGGGATGTGCAGAATTACCATGAAATTATGACTCGTCAT
H H V L Y F P G D V Q N Y H E I M T R H
CCTGAGAATTATCAATGGGAAAACTGGAGTCTAGAAAATGTTGCTACCATTTTAGCCCAC
P E N Y Q W E N W S L E N V A T I L A H
CGGTTCCCCAATAGTTATATTTGGGTGATAAAATGTTCCCGAATGCATTTGCACAAATTC
R F P N S Y I W V I K C S R M H L H K F
AGCTGCTATGACAATTTTGTGAAAAGTAACATGTTTGGTGCCCCAGAACACAATACTGAC
S C Y D N F V K S N M F G A P E H N T D
TTTGGAGCTTTTAAGCACCTTTATATGTTATTAGTTAATGCTTTTAATTTAAGTCAGAAT
F G A F K H L Y M L L V N A F N L S Q N
AGTTTATCAAAGAAAAGTTTGAATGTTTGGAATAAGGACTCCATAGCATCTAACTGTAGA
S L S K K S L N V W N K D S I A S N C R
TCCAGTCCTTCTCATACTACGAATGGTTGCCAGGGAGAAAAAGTGAGGACCTGTGAAAAA
S S P S H T T N G C Q G E K V R T C E K
TCTGATGAGTCTGCCATGAGTTTTTATCCACCATCACTAAATGACGCATCTTTTACTTTG
S D E S A M S F Y P P S L N D A S F T L
ATTGGATTCAGTAAAGGTTGTGTTGTTTTGAATCAGTTGCTTTTTGAATTGAAAGAAGCC
I G F S K G C V V L N Q L L F E L K E A
AAGAAAGACAAGAACATAGATGCTTTTATCAAAAGCATAAGAACAATGTATTGGCTGGAT
K K D K N I D A F I K S I R T M Y W L D
GGTGGTCATTCTGGAGGAAGCAATACTTGGGTTACTTATCCAGAAGTCTTGAAAGAATTT
G G H S G G S N T W V T Y P E V L K E F
GCACAAACAGGAATTATCGTTCACACTCATGTAACACCTTACCAAGTACGTGATCCAATG
A Q T G I I V H T H V T P Y Q V R D P M
AGATCTTGGATTGGAAAGGAGCACAAGAAATTTGTTCAGATACTTGGGGATCTTGGTATG
R S W I G K E H K K F V Q I L G D L G M
CAGGTGACTAGCCAAATTCATTTTACAAAGGAAGCTCCTTCCATAGAGAATCACTTCAGG
Q V T S Q I H F T K E A P S I E N H F R
GTTCATGAAGTATTTTGAGATTACAGGTATATTAATGAACTTGTTCAGTGGAAGAACATA
V H E V F *
AGCACTTTTGAGTGTTATAAATTCAGATAATGGGATGTAATTCATAGCTGCATTGTCAGT
TTTGGGGTATGGGGGGAAGCACACATTCCTAAAATGTGAGTGTAATGTGCAATAGTATTT
TTTGCTTGTGAATGTGAGCAGTTATTAATTTGGATTGAGTTAGAATTAGTTAATTTGAAA
TCTAACAAGGTGGTTTGTAATAATGCTGAGGAGATATAAGACCCTTAAAATGAAAGTTAC
AACATTGTTCTTATAAAAGGTAACTAAAATTGTTACTGTTGGAAATAACTGATTTTCTGA
GTAATGTTTTAAACTAATTTGGTGACATTTTAACAGTAATTAGCTATTTTGAGTGGAAAT
ATTTTCATTTCTCTTCAAACAAAAGCAAAGGTACGATGCTGTTTTCTATCATTTTGGAAT
AACTGCACCCTGCCTTTTGTGTTTTTGTAAACTCCTTGACTCATTCTTTCATGTGTCACC
177
AAGTACTTTTCTCATGAGAGTCAACATATATTTGTTTCCAAATGTCCACAAGTGTACAAT
AGTGTAAAGGTGGTTTTTAAAAACATAGCCAGGTGTGGTGGCACGTGCCTTTAGTTCCAG
CTACTCAGGAGGCTAAGGCAGGAGGATTGCTTGAGCCCAGGCTGTGTGGTTCACCATAAT
TGTGTTTGTGACTAGCTACTGCACTCCAACCTGGGCAACATAGTGGGACTTCATCTCTAA
AACAAAACAAAACAAAATTACACTTAAGCACTATTGTTTAATTTTTAATTGTCAGTTTAT
CATTATTTTGGGTAAGACATTCTGGGGTTTCTTGAATCTTGTCCAAAAACCAGTTGTTTT
GGAAAATTGCTTTAAATTGAGCATATTTATGTATATTGGATAAAAATGTACTACAGAGCA
AATTTCAAATTTTTCATTATATCAGTCTTTTTGAAAGGATCAACTTGGATAAAATAAATA
TATAATGCTCTATTTGTTAGAGCTCTATTAAAAAGGAAACAGATTCCATAGATCTAAGTC
AATGTTTCTCCAGAAGCATGATTTTGTCTGCCAAAAGAAAATAGCTCTCTTTGGCCAAAA
TGCAAAATTACATTGCTATAAGAAAAGTTACAAGGGAAAGTTTGAAGACACAAATGATTT
AATTTTGGCTCAAAAACTGAATTTGCTTAACACTGCTACATAATTTGGGTGAAGTTTCCT
TCTGCCCGTTTTTCTTGACCTAGATAAATACACTTTGAGAAATCCAGATCTAATAAATGT
CAACCAACATTGACATTGTAATTGGGTGATTACAATAAAAGGTGAGCAGTTTGTTGTTTA
TTAATAATTAGCTTTTGCAGGTAATGAAATAGCAGGGAAGTAACATGCTGCTTTAGGACT
AAAAAAAAAAAAAAAAAAAAGACACTGAAGCTTAATACCTTAATGACCCAGAAGACCTAG
ATTTATAAAGCCATATAGAATAAAAATGTTAATTTCTTGGTTTCTTCCCAGAATTATATT
TTAATGACTCCATAAATACATTCCAAATATTCAGAGATTCATGAGAAAGGATTCTTAACA
AATGTTTAAAAATAACATTTCTTTTTGGTGTTTTAACACTTAATTTTATAAACTGCAGAA
CAGCATCTCTAAATGGCTTTTTTTTTTTTTTTAAAGACAAAGTAGTATTATGTTGCTTCA
GTTTCTTTAAATACCTCGTTTCTTTTGAGACCAAAAATTCCCATCAAGGAAATAAATCAG
CCTGATTTTAACATTTTACATATTACATTGCCTTTAAGCACTATGATTGGATGGCTTTTT
TTCTATTTGTTTAATAATCCTTGGCTAAATTCACATGTATCTAAAGGAAAATAGCTGAGT
TACTGAATTCTATAAGGGGAAGAAAAAGCATTTATTTTCACATGATTAACTGAAATGGAA
AAGTAAGACATTTAGCAGAATAATTCATTTAAAAATAATTTTAAAAAATCAGACATATTT
AAAAATCTAGGTTGTCTATCCAGTATGTGAATGCTTAATTATAATTGTTACATGTTGAAT
GGGTATTAAGAGTAAGTCACCAGGTACACAAAACTGCCATCATAGCAAAATGAGACAGTG
TTGAAAAGACAAAATATTTTCTGGAATGAAAATATATTCAAGTTGATCCATATTCAGATG
TTTTCTGTTTAATACTTCAGATTGGTCCTTTGTCCACATTTGTTTAAAACTTATTGTAAT
GTTAATTTACACTTTTGGATTGTGCCTTTGTCATGAGTTGAGAAAAGTAGTCCTACAAAT
AATGTGAAAGTTGTTACCACCACAGCATGAATGTATAATTGTATTAAAATTGATCATCCA
C
The coding sequence of the FLJ38973 cDNA and its deduced amino acid
translation (in black). Exons are represented in alternating blue and red text,
whilst non-coding regions are highlighted in yellow. The stop codon (TGA) is
shown as an asterisk (*).