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Transcriptomic and epigenetic responses to short-term nutrient-exercise stress in humans

  • St. Vincent's Institute of Medical Research

Abstract and Figures

High fat feeding impairs skeletal muscle metabolic flexibility and induces insulin resistance, whereas exercise training exerts positive effects on substrate handling and improves insulin sensitivity. To identify the genomic mechanisms by which exercise ameliorates some of the deleterious effects of high fat feeding, we investigated the transcriptional and epigenetic response of human skeletal muscle to 9 days of a high-fat diet (HFD) alone (Sed-HFD) or in combination with resistance exercise (Ex-HFD), using genome-wide profiling of gene expression and DNA methylation. HFD markedly induced expression of immune and inflammatory genes, which was not attenuated by Ex. Conversely, Ex markedly remodelled expression of genes associated with muscle growth and structure. We detected marked DNA methylation changes following HFD alone and in combination with Ex. Among the genes that showed a significant association between DNA methylation and gene expression changes were PYGM, which was epigenetically regulated in both groups, and ANGPTL4, which was regulated only following Ex. In conclusion, while short-term Ex did not prevent a HFD-induced inflammatory response, it provoked a genomic response that may protect skeletal muscle from atrophy. These epigenetic adaptations provide mechanistic insight into the gene-specific regulation of inflammatory and metabolic processes in human skeletal muscle.
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SCIENtIFIC RePoRTS | 7:15134 | DOI:10.1038/s41598-017-15420-7
Transcriptomic and epigenetic
responses to short-term nutrient-
exercise stress in humans
R. C. Laker1, C. Garde1, D. M. Camera2, W. J. Smiles2, J. R. Zierath1,3, J. A. Hawley2,4 &
R. Barrès
High fat feeding impairs skeletal muscle metabolic exibility and induces insulin resistance, whereas
exercise training exerts positive eects on substrate handling and improves insulin sensitivity. To
identify the genomic mechanisms by which exercise ameliorates some of the deleterious eects of
high fat feeding, we investigated the transcriptional and epigenetic response of human skeletal muscle
to 9 days of a high-fat diet (HFD) alone (Sed-HFD) or in combination with resistance exercise (Ex-
HFD), using genome-wide proling of gene expression and DNA methylation. HFD markedly induced
expression of immune and inammatory genes, which was not attenuated by Ex. Conversely, Ex
markedly remodelled expression of genes associated with muscle growth and structure. We detected
marked DNA methylation changes following HFD alone and in combination with Ex. Among the genes
that showed a signicant association between DNA methylation and gene expression changes were
PYGM, which was epigenetically regulated in both groups, and ANGPTL4, which was regulated only
following Ex. In conclusion, while short-term Ex did not prevent a HFD-induced inammatory response,
it provoked a genomic response that may protect skeletal muscle from atrophy. These epigenetic
adaptations provide mechanistic insight into the gene-specic regulation of inammatory and
metabolic processes in human skeletal muscle.
Skeletal muscle function is critical for voluntary movement, heat production and energy homeostasis1. e role
of skeletal muscle in metabolism and the control of blood glucose is particularly important, since this organ
is responsible for up to 80% of whole body insulin-stimulated glucose uptake2. Skeletal muscle is also highly
adaptive and displays a robust molecular and morphological response to diet and habitual physical activity3,4.
High fat diets are detrimental for the function of metabolic tissues, including skeletal muscle. Indeed, increases
in circulating lipids that accompany a fat-rich diet results in lipid accumulation within metabolic tissues, dis-
ruption to normal mitochondrial function, impaired insulin signalling and loss of muscle mass57. However,
high-fat, low-carbohydrate diets have become popular regimes to achieve weight loss, mainly due to the satiating
properties of these fatty acids. Resistance exercise promotes muscle hypertrophy and strength through the acti-
vation of signalling pathways that ultimately increase muscle protein synthesis8. Additionally, citrate synthase,
hexokinase9 and muscle-specic lipid oxidation capacity10 is increased following resistance exercise in human
skeletal muscle. Whether resistance exercise confers protection to skeletal muscle under conditions of a high-fat,
low-carbohydrate diet has not been investigated. Early transcriptomic responses following the transition from
a normal ‘healthy’ diet to a high fat diet (HFD) may provide important information as to the initial adaptive
responses that result in loss of muscle mass and metabolic dysfunction. We therefore determined whether resist-
ance exercise, in conjunction with high-fat feeding in humans, prevents maladaptive transcriptomic responses
typically observed aer such diets.
Altered DNA methylation has previously been linked to metabolic dysfunction in skeletal muscle of people
with type 2 diabetes11 and in response to acute, intense exercise12. erefore, to further probe the regulatory
mechanisms responsible for skeletal muscle gene expression in response to diet/nutrient stimuli, we investigated
1Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
2Mary MacKillop Institute for Health Research, Centre for Exercise and Nutrition, Australian Catholic University,
Melbourne, Australia. 3Integrative Physiology, Department of Molecular Medicine and Surgery and Department of
Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden. 4Research Institute for Sport and Exercise
Sciences, Liverpool John Moores University, Liverpool, United Kingdom. Correspondence and requests for materials
should be addressed to R.B. (email:
Received: 13 July 2017
Accepted: 27 October 2017
Published: xx xx xxxx
Correction: Author Correction
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SCIENtIFIC RePoRTS | 7:15134 | DOI:10.1038/s41598-017-15420-7
the epigenetic modication of DNA methylation. We hypothesized that altered DNA methylation may be an epi-
genetic mechanism responsible for exercise and/or high-fat diet-induced adaptations in skeletal muscle. Indeed,
changes in CpG methylation within promoters or enhancers can alter DNA structure and thereby block the access
of transcriptional machinery to DNA, resulting in altered or suppressed gene expression.
We performed transcriptomic and genome-wide DNA methylation proling in human skeletal muscle before
and aer nine days of HFD with or without three bouts of resistance exercise training in middle-aged, sedentary
males. We report that diet- and exercise-induced changes in DNA methylation were associated with very specic
gene regulation in the post-intervention resting state. Our ndings also demonstrate the robust impact of resist-
ance exercise on transcriptional remodelling in skeletal muscle, which may compensate for the deleterious eects
of high-fat diets. is study provides insight into the possible initiating mechanisms of HFD-induced inamma-
tion, metabolic dysfunction and loss of tissue mass in skeletal muscle.
Research Design and Methods
Study participants and experimental design. Thirteen healthy middle-aged sedentary men were
recruited for this study. Body weight and BMI were in the normal range (Table1). Participants were provided with
oral and written information about the purpose, nature and potential risks involved with the study, and written
informed consent was obtained prior to participation. All experimental protocols and methodologies related to
the study were approved by the Australian Catholic University Human Research Ethics Committee (#2015-103 H,
clinical trial registration date 12/10/2015) and conformed with the policy statement regarding the use of human
subjects in the latest revision of the Declaration of Helsinki. e trial was registered with the Australian New
Zealand Clinical Trials Registry (ACTRN 369316). A timeline of the experimental protocol that encompassed a
parallel groups design is shown (Fig.1). Ten days prior to the start of an intervention, all participants underwent
DEXA scan (GE Lunar Prodigy Pro, GE Healthcare) to determine body composition, and preliminary exercise
testing consisting of peak aerobic power (VO2peak) and one repetition maximum leg extension and leg press
strength testing. At the commencement of the experimental period, all participants were provided with a stand-
ardized pre-packed control diet (breakfast, lunch, dinner and snacks) for three days. is diet was customized to
the subject to provide 45 kcal/kg fat-free mass (FFM) per day with 6.1 g carbohydrate/kg FFM (55% totalcaloric
intake), 1.7 g protein/kg FFM (15%) and 1.5 g fat/kg FFM (30%). Following an overnight fast, biopsies were col-
lected under local anaesthesia (2-3 mL 1% Xylocaine) from the vastus lateralis muscle using a 5-mm Bergstrom
needle, modied with suction, and denoted as the “Pre” time point. Participants then commenced a high-fat
low-carbohydrate (HFD) diet consisting of 0.8 g carbohydrate kg/FFM (8% total caloric intake), 1.7 g protein/kg
FFM (15%) and 3.9 g fat/kg FFM (77%)13 for the remaining experimental period, which was a further 9 days. is
diet has been promoted by othersto induce nutritional ketosis and to be benecial for athletic performance and
weight loss13,14. is diet contains the required minerals to maintain physiological function, protein for lean body
mass and sucient carbohydrates for brain function13. We found this diet had no impact on muscle protein turn-
over in the study participants and published the results elsewhere15. Meal plans were created using Foodworks
7.0 ® Xyris Soware (Melbourne, Australia). Compliance was monitored and participants maintained a food
checklist. Participants were divided into two groups that were pair matched for fat-free mass and strength: partic-
ipants who remained sedentary (Sed-HFD) and those that performed three bouts of resistance exercise training
(Ex-HFD), starting 1 day aer commencing HFD, which corresponds to days 4, 7 and 10 of the experimental
timeline (Fig.1). Exercise consisted of 4 × 8–10 repetitions of leg press at 80% 1-RM, 4 × 8–10 repetitions of leg
extensions at 80% 1-RM, and 4 sets of dumbbell squats. ere was a 3 min recovery period between each set.
Muscle biopsies were collected under fasted conditions on day 11 and denoted as the “Post” time point. Blood
samples were collected on the morning of day 3, 5, 8 and 11 in EDTA tubes, centrifuged at 1,000 × g at 4 °C
Figure 1. Study design. Subjects underwent body composition and exercise testing at the commencement of
the experimental period. Aer 3 days of dietary control, subjects consumed a high-fat low-carbohydrate diet
(HFD) for 9 days. Subjects either remained sedentary (Sed-HFD) or performed resistance exercise (Ex-HFD)
on days 4, 7 and 10 of the experimental period. Blood samples were collected on days 3, 5, 8 and 11 and skeletal
muscle biopsies were obtained before and aer the diet/exercise intervention.
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for 15 min and stored at 80 °C. Total RNA and DNA were simultaneously isolated from the biopsy using the
Allprep® DNA/RNA/miRNA Universal Kit (Qiagen) according to the manufacturer’s instructions.
Plasma Analysis. Plasma tumour necrosis factor α (TNF-α) and interleukin-6 (IL-6) were measured
on 96-well plates utilizing commercially available and customised Milliplex Human magnetic bead panels
(Millipore, Massachusetts, USA) following the kit-specic protocols provided by Millipore. Analytes were quan-
tied in duplicate using the Magpix system utilising xPONENT 4.2 soware. Concentrations of these analytes
were determined on the basis of the t of a standard curve for mean uorescence intensity versus pg/ml. Two
quality controls with designated ranges were run with each assay to ensure validity of data generated. Plasma
FFA concentrations were determined by an enzymatic colorimetric method (Wako Diagnostics, Tokyo, Japan).
RNA sequencing. RNA was checked for quality using the Agilent RNA 600 nano kit and Bioanalyser instru-
ment (Agilent Technologies). 1 µg of RNA per sample was subject to the Illumina TruSeq Stranded Total RNA
with Ribo-Zero Gold protocol (Illumina) and performed as described16. Briey, ribosomal RNA was removed
from the sample using 35 µl rRNA removal beads (Illumina) on a magnetic plate followed by clean-up of the
ribosomal-depleted RNA with 193 µl Agencourt RNAClean XP beads (Beckman Coulter), 70% ethanol wash and
elution into 10 µl Elution buer (Illumina). e RNA sample was fragmented for 4 min at 94 °C in Elute, Prime,
Fragment High Mix (Illumina) and then subject to rst strand cDNA synthesis with 1 µl Superscript III reverse
transcriptase (Life Technologies) per sample and thermocycler programmed to 25 °C for 10 min, 50 °C for 15 min
and 70 °C for 15 min. Second strand cDNA was synthesized by addition of Second Strand Marking Master Mix
and samples subject to 16 °C for 60 min. Samples were subject to another bead clean up prior to A-tailing and liga-
tion of adapters as per kit instructions (Illumina). Following an third bead clean-up samples were enrich for DNA
fragments by amplication using the Illumina PCR Primer Cocktail and PCR Master Mix using a pre-dened
cycle number based on each individual sample and subject to 98 °C for 30 mins then X cycles of 98 °C for 10 secs,
60 °C for 30 secs and 72 °C for 30 secs and nally 72 °C for 5 min. Samples were cleaned and validated for DNA
concentration using the Qubit dsDNA HS assay kit (Invitrogen) and for base pair size and purity using the Aglient
High Sensitivity DNA chip and Bioanalyser instrument. Libraries were subjected to 100-bp single-end sequencing
onthe HiSeq 2500 (Illumina) at the Danish National High-roughput DNA Sequencing Centre. Approximately
8.5 million reads/sample were assigned to genes with 23,373 genes surviving the expression threshold.
DNA methylation analysis. Reduced Representation Bisulfite Sequencing (RRBS) was performed
as described17. Briey, 200 ng of DNA per sample was incubated overnight at 37 °C with MpsI enzyme (NEB
#R0106L) to fragment DNA at CCGG positions to enrich for CpG regions. Samples then underwent gap lling
and A-tailing with 1 µl dNTP mix (10 mM dATP, 1 mM dCTP, 1 mM dGTP) and 1 µl Klenow fragment 3′−5 exo
(NEB) with 30 °C for 20 min and 37 °C for 20 min. Samples underwent bead clean-up using 90 µl AMPure beads
(Beckman Coulter) on a magnetic plate, 2 × 70% ethanol wash and elution into 20 µl elution buer. Illumina
Truseq adapters (diluted 1:20) were ligated with T4 ligase (NEB) and overnight incubation at 16 °C. e enzyme
was deactived by incubation at 65 °C for 20 mins. Samples were pooled (12 samples per pool), volume adjusted
with 20% polyethylene glycol and 2.5 M NaCl prior to bead clean-up in the DynaMag magnet. Bisulte con-
version was performed using the EZ DNA methylation Kit (Zymo Research) according to the manufacturer’s
instructions with 20 hr incubation with CT conversion reagent at 50 °C. DNA was then PCR amplied using Pfu
Turbo hotstart DNA polymerase, dNTP mix (100 mM, 25 mM each) and Illumina primer cocktail. Samples were
subject to 2 min at 95 °C followed by 14 cycles of 95 °C for 30 sec, 65 °C for 30 sec and 72 °C for 45 sec and nally
72 °C for 5 min. Samples underwent nal bead clean-up and library validation for DNA concentration using the
Qubit dsDNA HS assay kit (Invitrogen) and base pair size and purity using the Aglient High Sensitivity DNA
chip and Bioanalyser instrument. Libraries were subjected to 100-bp single-end sequencing onthe HiSeq 2500
(Illumina) at the Danish National High-roughput DNA Sequencing Centre.
Accession Numbers. Sequencing data are archived for public access at the Gene Expression Omnibus
( under accession number GSE99965.
Bioinformatic analysis. RNA-seq reads were subjected to trimming of adapters and low quality anking
ends using Trim Galore v0.3.7 and Cutadapt v1.4.2. Pre-processed reads were mapped to hg38 using Rsubread18
and gene coverages were computed with featureCounts19 and the Gencode annotation. e gene list was ltered to
those with a read coverage larger than 0.1 rpkm in at least 5 samples. Dierential expression was computed using
Ex-HFD (n = 7) Sed-HFD(n = 6)
Age (y) 37.3 ± 5.6 38.8 ± 5.3
Body Mass (kg) 89.4 ± 12.8 84.5 ± 7.4
BMI (kg m2) 26.9 ± 3.0 27.2 ± 2.5
Lean Mass (kg) 60.1 ± 6.0 55.7 ± 5.9
VO2peak (ml/kg/min) 38.4 ± 4.2 34.5 ± 6.0
Leg Extension 1-RM (kg) 79.6 ± 15.4 71.8 ± 18.7
Leg Press 1-RM (kg) 219.7 ± 17.9 216.0 ± 49.2
Table 1. Baseline characteristics of the participants. Values are given as mean ± SD.
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edgeR with the glmQLFit/glmQLFTest modeling framework and the following models y~Timepoint + Subject
were used for each of the HFD-Ex and HFD-Sed groups20. Genes with a false discovery rate (FDR) below 0.1 were
considered dierentially expressed.
RRBS reads were processed with the ‘rrbs’ setting of Trim Galore v0.3.7 and Cutadapt v1.4.2. Processed reads
were mapped to hg38 followed by derivation of CpG methylation using Bismark21. Dierentially methylated
regions (FDR < 0.1) were identied using BiSeq22 from the subset of CpG sites that are covered by at least half of
the samples using the following models y~Timepoint + Subject for each of the HFD-Ex and HFD-Sed groups.
Our condence in bisulte conversion eciency was assessed based on the level of non-CpG methylation, which
at CHG sites averaged1.41% and at CHH sites averaged 1.39%, which is in the expected range (Fig.S1). We also
identied CpG sites known to be highly or lowly methylated in adult human skeletal muscle as well as 50 other
tissue and cell types using RRBS data available from the Epigenome Roadmap. We found that the methylation
levels of these sites within our analysis were consistent with the expected levels (Fig.S2). Finally, we assessed the
distribution of methylation of identied CpG sites for each sample, which was bimodal with peaks in the 0–15%
and 85–100% range (Fig.S3).
Statistics. Enrichment studies were conducted using hypergeometric tests and corrected for multiple testing
using the Benjamini-Hochberg procedure. An FDR of <0.1 was used as signicance level. Two-way ANOVA fol-
lowed by Student Newman Kuels post-hoc tests were performed to determine dierences between Ex-HFD and
Sed-HFD groups, and time (Pre-and Post). Data are presented as mean ± SEM with P values < 0.05 indicating
statistical signicance.
Results and Discussion
Short-term resistance exercise causes major changes in the skeletal muscle transcriptome
compared with HFD alone. To identify regulatory mechanisms involved in the early adaptive response to
high-fat feeding and the interaction with resistance exercise, we proled the skeletal muscle transcriptome before
and aer 9 days of HFD, with or without 3 bouts of resistance exercise. Within the RNA-seq analysis, 23,373
genes were annotated. Principal component analysis showed a clear separation of the treatment groups between
the Pre and Post time points, with no clear separation between individuals that performed resistance exercise
and individuals that remained sedentary aer the intervention (Fig.2A). To conrm the accuracy of our RNA-
seq results we compared the expression prole of genes previously analysed by qRT-PCR in a subset of samples
from the same experiment, which were previously reported15. We found that both the dierentially expressed
and unchanged genes were consistent between the two analyses (Fig.S4). Nine days of HFD in sedentary men
(Sed-HFD) resulted in dierential expression of 412 genes in skeletal muscle (Pre vs. Post), with 264 up-regulated
and 148 down-regulated (Fig.2B and D; TableS1). Conversely, when resistance exercise was performed in com-
bination with HFD (Ex-HFD), a greater transcriptomic response was evident, with 2,617 genes changed (Pre vs.
Post) of which 1,561 were up-regulated and 1,056 were down-regulated (Fig.2C and E; TableS1). e dierent
magnitude of change in gene expression suggests that resistance exercise initiates robust transcriptional activity
in skeletal muscle, which far outweighs the impact of HFD alone.
Of the 1,561 up-regulated genes following Ex-HFD, only 240 genes were also up-regulated in the Sed-HFD
group. is implies that the remaining 1,321 genes were up-regulated as a direct response to resistance exer-
cise (Fig.3A). Similarly, of the 1,056 genes down-regulated in the Ex-HFD group, only 103 genes were also
down-regulated in the Sed-HFD group, suggesting that resistance exercise was primarily responsible for the
down-regulation of the remaining 953 genes. We performed an enrichment analysis of gene ontology (GO)
terms to identify whether the genes regulated in the Ex-HFD group were associated with specic cellular
compartments, biological processes and molecular functions (TableS2). However, due to the large number
of dierentially expressed genes, we retrieved a long list of GO terms. erefore, we used the Revigo tool to
summarize the GO terms based on semantic similarity23. We found many GO terms related to skeletal muscle
structure, myogenic activity and metabolism (Fig.3C and D; TableS2). Consistent with the biology of skeletal
muscle, we found that the cellular compartment GOs were related to neuromuscular junction, sarcomere and
mitochondrion (Fig.3C and D;TableS2), while biological process GOs included skeletal muscle satellite cell
migration, cell junction assembly and muscle cell dierentiation, among other metabolic and transcriptional
processes (Fig.3C and D; TableS2). Finally, molecular function gene ontologies were related to signal trans-
ducer activity, myogenic regulatory factor binding and structural constituent of muscle (Fig.3C and D; TableS2).
Of note, the top two GOs of the down-regulated genes were rhythmic process and circadian rhythm (Fig.3D;
TableS2). Since the muscle biopsies were taken at the same time of the day (~8am), pre- and post-intervention,
this suggests that resistance exercise may transcriptionally regulate the innate circadian oscillations of skeletal
muscle. is may be important considering the close link between circadian and metabolic gene regulation24,25
and could have widespread implications for the timing of exercise to optimize metabolic health outcomes.
Taken collectively, our analyses suggest that resistance exercise may protect skeletal muscle against the negative
impact of HFD. However, we acknowledge that functional outcomes are dicult to determine based on the
short-term exercise intervention in the current study. Of note, metabolic analyses from this cohort revealed
the Ex-HFD group showed a tendency for improved glucose tolerance15. e functional impact of resistance
exercise, when performed in conjunction with HFD, may become more apparent aer a prolonged exercise
training regimen.
Short-term HFD induces immune and inammatory genes regardless of physical activity. We
identied 343 genes that were dierentially regulated following both interventions (Sed-HFD and Ex-HFD;
Fig.4A), with 240 genes up-regulated and 103 genes down-regulated (Fig.3A and B). Only one gene, ChaC
Glutathione Specic Gamma-Glutamylcyclotransferase 1 (CHAC1), showed divergent transcriptional regulation
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between Sed-HFD and Ex-HFD groups (Fig.4A). CHAC1 plays a role in glutathione degradation, notch sig-
nalling and activation of autophagy and apoptosis2628. To our knowledge, the only report on CHAC1 in skel-
etal muscle suggests that CHAC1 is induced in response to re-feeding and participates in the unfolded protein
response29, which is consistent with our observation that CHAC1 is regulated by the nutritional state in humans.
Next, we performed gene ontology analysis of the 344 genes dierentially regulated by both Sed-HFD and
Ex-HFD. We identied at least 20 individual GO terms associated with immune and inammatory processes
(Fig.4B and C). Of potential interest, many of the up-regulated GO terms were associated with the extracel-
lular space, which suggests that immune and inammatory signalling is occurring outsidethe skeletal muscle,
likely through a combination of secreted and membrane-expressed proteins, as well as recruitment of mac-
rophages. Whether macrophage recruitment or muscle damage per se is driving the immune and inammatory
Figure 2. Short-term resistance exercise initiates robust transcriptional regulation compared with HFD alone.
(A) Principal component analysis (PCA) of RNA-seq for the major two principal components (PC). e 95%
condence ellipses are shown for each group. Heatmaps (B and C) and volcano plots (D and E) represent
dierentially expressed genes in skeletal muscle before (Pre) and aer (Post) 9 days of HFD (Sed-HFD; B and
D) or HFD with 3 bouts of resistance exercise training (Ex-HFD; C and E). FDR < 0.1.
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gene response aer a combined HFD and resistance exercise regimen warrants further investigation. Within the
cellular compartment category, the down-regulated GO terms were highly associated with mitochondria, and
supports the notion that HFD induces impairments in mitochondrial function (Fig.4C). Indeed, many of the
Figure 3. Short-term resistance exercise is associated with large-scale transcriptional remodelling in skeletal
muscle in the presence of HFD. Venn diagrams representing the number of genes that were up-regulated
(A) and down-regulated (B) in Sed-HFD and Ex-HFD group (excludes CHAC1 gene, which was upregulated in
Ex-HFD and downregulated in Sed-HFD). e intersection represents the genes that were regulated following
both interventions. Gene ontology analysis of genes that were up-regulated (C) and down-regulated (D)
exclusively in the Ex-HFD group. FDR < 0.1 is shown by the dotted line.
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biological function GOs terms derived from the down-regulated genes were associated with mitochondrial func-
tion and metabolic processes including cellular respiration, metabolic process, gluconeogenesis, glycolytic process
and canonical glycolysis (Fig.4C).
Figure 4. HFD induces immune and inammatory genes associated with systemic inammation, regardless of
physical activity. (A) Scatter plot of 344 dierentially expressed gene following 9 days of HFD, with or without
resistance exercise (Sed-HFD and Ex-HFD intersection). Gene ontology analysis of the 344 genes that were
either up-regulated (B) or down-regulated (C) in both the Sed-HFD and Ex-HFD groups. FDR < 0.1 is shown
by the dotted line. Plasma proles of free fatty acids (FFA; D), interleukin 6 (IL-6; E) and TNF-α (F) throughout
the intervention period. #p < 0.002 for the eect of time; $p < 0.02 for the eect of exercise.
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In support of the transcriptional profiling data, we found that circulating free fatty acids progressively
increased throughout the high-fat diet intervention in both groups (Fig.4D). Surprisingly, this occurred to a
greater extent in the exercise group compared with the sedentary group (Fig.4D). We also observed a marked
elevation of the inammatory markers IL-6 and TNF-α in both groups (Fig.4E and F). Collectively, these ndings
suggest that HFD, regardless of physical activity, elevates circulating lipids associated with systemic inammation,
and promotes local inammation/immune responses in skeletal muscle. ese observations suggest that concom-
itant resistance exercise does not fully protect skeletal muscle from deleterious HFD-induced gene regulation. We
cannot exclude the possibility that a longer exposure to an exercise stimulus (i.e. weeks, months) may reverse this
Transcriptional response to short-term HFD. We report that 67 genes were uniquely altered in the
Sed-HFD group and unchanged in the Ex-HFD group. is number excludes the CHAC1 gene which was
altered in both groups but in opposite directions (see Fig.4A). is nding suggests that resistance exer-
cise preserved expression of these genes at a basal level. Although we were unable to perform gene ontol-
ogy analysis due to the small number of genes, we found that many of these 67 genes were associated with
mitochondrial function and localization, metabolic enzymes, and immune regulation (Table2). Of particu-
lar interest are the Interleukin 1 Receptor Associated Kinase 2 (IRAK2), Nuclear Protein 1, Transcriptional
Regulator (NUPR1; also known as p8) and Fibroblast Growth Factor 6 (FGF6) (Table2). IRAK2 was increased
by ~2-fold following HFD. IRAK2 is a receptor for IL1 and mediates toll like receptor (TLR) and NF-ĸB
signalling to induce transcription and mRNA stabilization for chemokine production (TNFα, IL6, IL1)30,31.
e early induction of IRAK2 by HFD feeding suggests that IRAK2 participates in the initiation of inamma-
tory signalling in skeletal muscle3234 and may be a key mechanism underlying subsequent insulin resistance.
NUPR1 was also induced following HFD by ~1.7-fold. NUPR1 interacts directly with the critical myogenic
regulatory factor MyoD to regulate MyoD target genes35. In C2C12 myoblasts, over expression of NUPR1
represses MyoD and myogenin gene expression35. Furthermore, NUPR1 is involved in resistance to stress
induced by a change in the microenvironment36,37. us, our observation that NUPR1 is induced following
HFD may represent a stress response to the inux of fatty acids, which ultimately results in the HFD-induced
loss of muscle mass. Finally, FGF6 was decreased ~50% following nine days of HFD in skeletal muscle. FGF6
plays an role in muscle regeneration and dierentiation through stimulation of satellite cell proliferation and
early dierentiation3840. We speculate that the decrease of FGF6 along with increased NUPR1 participates in
the loss of muscle mass with HFD.
In addition to the set of known genes that were dierentially expressed following HFD, there was a set of
eight transcripts with no identied protein product (Table3). ese transcripts exhibited an extremely robust
decrease in expression following HFD (between ~40–98% reduction; Table3). e transcripts are quite long
and could therefore, be long non-coding RNA that could confer a transcriptional response. Alternatively, some
Ensembl ID Gene Description logFC P value FDR
ENSG00000124107 SLPI secretory leukocyte peptidase inhibitor 2,82 7,17E-09 7,28E-06
ENSG00000138193 PLCE1 phospholipase C epsilon 1 0,94 2,22E-05 4,80E-03
ENSG00000014641 MDH1 malate dehydrogenase 1 0,79 3,68E-05 7,17E-03
ENSG00000134070 IRAK2 interleukin 1 receptor associated kinase 2 1,01 5,31E-05 8,94E-03
ENSG00000176046 NUPR1 nuclear protein 1, transcriptional regulator 0,76 8,99E-05 1,29E-02
ENSG00000154518 ATP5G3 ATP synthase, H + transporting, mitochondrial Fo
complex subunit C3 (subunit 9) 0,74 1,07E-04 1,46E-02
ENSG00000112715 VEGFA vascular endothelial growth factor A 0,73 1,47E-04 1,88E-02
ENSG00000087586 AURKA aurora kinase A 1,14 1,56E-04 1,95E-02
ENSG00000110955 ATP5B ATP synthase, H + transporting, mitochondrial F1
complex, beta polypeptide 0,71 2,88E-04 3,13E-02
ENSG00000159423 ALDH4A1 aldehyde dehydrogenase 4 family member A1 0,68 5,48E-04 4,75E-02
ENSG00000263232 ATP5A1P3 ATP synthase, H + transporting, mitochondrial F1
complex, alpha subunit 1 pseudogene 3 0,71 6,70E-04 5,32E-02
ENSG00000132313 MRPL35 mitochondrial ribosomal protein L35 0,70 7,28E-04 5,63E-02
ENSG00000111241 FGF6 broblast growth factor 6 1,05 8,14E-04 6,18E-02
ENSG00000169692 AGPAT2 1-acylglycerol-3-phosphate O-acyltransferase 2 0,73 8,36E-04 6,18E-02
ENSG00000176340 COX8 A cytochrome c oxidase subunit VIIIA (ubiquitous) 0,63 9,09E-04 6,48E-02
ENSG00000166343 MSS51 MSS51 mitochondrial translational activator 0,71 1,02E-03 7,01E-02
ENSG00000184076 UQCR10 ubiquinol-cytochrome c reductase, complex III
subunit X 0,61 1,23E-03 7,98E-02
ENSG00000244482 LILRA6 leukocyte immunoglobulin-like receptor, subfamily
A (with TM domain), member 6 2,51 1,43E-03 8,74E-02
ENSG00000260318 COX6CP1 cytochrome c oxidase subunit VIc pseudogene 1 1,05 1,72E-03 9,85E-02
ENSG00000120992 LYPLA1 lysophospholipase I 0,90 1,72E-03 9,85E-02
Table 2. Selected genes associated with mitochondrial function and localization, metabolic enzymes, and
immune regulation dierentially regulated by HFD and preserved by concomitant resistance exercise.
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SCIENtIFIC RePoRTS | 7:15134 | DOI:10.1038/s41598-017-15420-7
of these genes appear to be subject to splicing and may be host genes to microRNAs, which are transcribed,
spliced and then degraded. In any case, the function of these transcripts remains unknown and they may
play a critical role in maintaining mass and/or metabolic homeostasis in skeletal muscle. An important future
direction will be to determine if these HFD-regulated genes also participate in HFD-induced inammation,
metabolic dysregulation or loss of muscle mass, and how resistance exercise prevents this HFD-induced genetic
Epigenetic response to HFD and resistance exercise. We used RRBS to prole dierentially meth-
ylated DNA regions (DMRs) with the aim of investigating whether epigenetic mechanisms play a role in the
transcriptomic response to nutrient/exercise. We found that a HFD alone induced a greater degree of hypermeth-
ylation, while concomitant resistance exercise resulted in a preference towards hypomethylation of DNA (Fig.5F
and G). We found 809 DMRs following short-term HFD, while concomitant resistance exercise revealed 474
DMRs, with only 38 DMRs common between the two groups (Fig.5A–C). Gene ontology analysis of all DMRs
revealed only one term, which was regulation of transcription. Furthermore, we identied only 10 genes in the
Sed-HFD group and 54 genes in the Ex-HFD group that showed signicant association with dierential gene
expression (Fig.5A and C). is limited relationship is surprising considering that more DMRs were found in
promoters, compared with other genomic regions (Fig.5D and E), and theoretically would cause altered expres-
sion of the genes associated with these promoters. One could speculate that thespecic location of the DMR
within the promoter region will be an important factor dictating whether gene expression would be altered,
which is dependent on the recruitment of methy-CpG binding proteins specically to the transcription factor
binding sites to block their access. Another explanation is that the DMRs have no apparent impact unless there
is a stimulus to initiate transcriptional activity of the associated gene, following which the functional impact of
DNA methylation or demethylation can be realized. Indeed, in the present study, biopsies were taken 48 hours
aer the nal exercise bout, when skeletal muscle was in a resting/basal state with low levels of transcriptional
activity. erefore, the dierential methylation states identied may have regulatory functions for transcriptional
activation/repression during times of stress or stimulation. For example, DNA demethylation following resistance
exercise training may function to poise a promoter region for rapid transcriptional activation in response to a
subsequent exercise bout, as previously hypothesized41. We propose that the importance of DNA methylation for
exercise adaptation may be observed if the biopsy was sampled during a dynamic period of transcription such as
immediately aer exercise.
e glycogen phosphorylase, muscle associated (PYGM) gene was one of the genes that did show a rela-
tionship between expression and promoter methylation. e promoter of PYGM was hypermethylated in both
groups following HFD, regardless of exercise and the level of methylation was inversely correlated with gene
expression (Fig.5H). PYGM is an enzyme involved in the breakdown of glycogen to glucose-1-phosphate42,43.
e epigenetic regulation of PYGM may be an adaptive response to the high-fat low-carbohydrate diet, since
glycogen stores are expected to progressively decline in skeletal muscle and the requirement for an enzyme that
breaks down glycogen (i.e. PYGM) would be abolished in the absence of the substrate. Indeed, the decline in
muscle glycogen stores has been reported in human muscle following a similar diet for 4 weeks14. Meanwhile,
angiopoiten like 4 (ANGPTL4) was hypomethylated in both groups, with changes in gene expression only
observed following resistance exercise, but to a substantial degree (Fig.5I). ANGPTL4 is a secreted serum hor-
mone that regulates blood glucose, lipid metabolism and insulin sensitivity4446. Hypomethylation of ANGPTL4
may be a compensatory response to HFD, yet a stimulus such as exercise may be required for transcriptional
activation. Interestingly, ANGPTL4 induces lipolysis in adipocytes44. us, increased expression of ANGPTL4 in
the Ex-HFD group may contribute to the higher levels of FFAs as compared with the sedentary group provided
with the same HFD.
In conclusion, we have reported transcriptional proles in skeletal muscle from men fed a high-fat diet with
or without a concomitant resistance exercise intervention. e extent to which resistance exercise can prevent
the deleterious impact of HFD on skeletal muscle function remain unanswered, but the dramatic number of
exercise-responsive genes identied suggest that growth and development pathways are up-regulated, along with
changes in metabolism and transcription. We found signicant changes in DNA methylation, predominantly at
promoter regions. Furthermore, genes associated with the DMRs were generally unrelated between the Sed-HFD
and Ex-HFD groups and their functional signicance has yet to be determined. Overall, our ndings suggest that
resistance exercise may be a promising intervention to maintain skeletal muscle mass and metabolic health under
conditions of a high-fat diet, currently prevalent throughout the world. Future studies are warranted to investigate
Ensembl ID Gene logFC P value FDR
ENSG00000261303 RP11–160C18.2 5,36 6,96E-06 2,06E-03
ENSG00000262420 RP11–490O6.2 1,44 1,19E-04 1,60E-02
ENSG00000224550 RP11–270C12.3 0,72 2,21E-04 2,58E-02
ENSG00000272631 RP11–359E3.4 2,27 3,88E-04 3,81E-02
ENSG00000271347 RP11–701H24.7 1,48 1,07E-03 7,27E-02
ENSG00000277954 RP11–679B19.1 1,18 1,22E-03 7,98E-02
ENSG00000223935 AC008074.3 2,24 1,26E-03 8,00E-02
ENSG00000183154 RP11–863K10.7 2,30 1,74E-03 9,91E-02
Table 3. Un-annotated genes down-regulated by HFD and protected by concomitant resistance exercise.
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SCIENtIFIC RePoRTS | 7:15134 | DOI:10.1038/s41598-017-15420-7
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e Novo Nordisk Foundation Centre for Basic Metabolic Research is an independent research centre at the
University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation.
Author Contributions
R.C.L. performed experiments, analysed the data and wrote the manuscript; C.G. performed bioinformatics
analysis and generated gures; D.M.C. and W.J.S. performed human experiments and plasma analysis; J.R.Z.
provided expert advice and edited the manuscript; J.H. designed the study and edited the manuscript; R.B.
designed the study, analysed the data and wrote the manuscript.
Additional Information
Supplementary information accompanies this paper at
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... Instead, the transcriptional profile was enriched in genes involved in the remodeling of the ECM, maintenance of the actin cytoskeleton, and inflammation (188). Other acutely regulated biological processes included satellite cell migration and myogenic regulatory factor binding, reflecting the important role these processes play in muscle remodeling (142). Taken together, while the acute damage response to RE is considered crucial for the regeneration of damaged skeletal muscle following a structural disruption, the latter remodeling events that occur after damage has subsided are thought to contribute to muscle hypertrophy associated with RT (60). ...
... Environmentally regulated DNA and histone modifications influence gene expression by altering the accessibility of upstream activators and repressors to gene regulatory regions. Laker et al. (142) demonstrated that acute RT is associated with extensive gene hypomethylation-which under most conditions increases transcription of the corresponding gene. Interestingly, out of the 474 genes differentially methylated following 11 days of RT, 54 showed altered expression (142). ...
... Laker et al. (142) demonstrated that acute RT is associated with extensive gene hypomethylation-which under most conditions increases transcription of the corresponding gene. Interestingly, out of the 474 genes differentially methylated following 11 days of RT, 54 showed altered expression (142). The authors hypothesized that the remaining differentially methylated genes that did not show a change in gene expression, within the time frame measured, were instead "primed" to respond to subsequent bouts of exercise. ...
Skeletal muscle is the organ of locomotion, its optimal function is critical for athletic performance, and is also important for health due to its contribution to resting metabolic rate and as a site for glucose uptake and storage. Numerous endogenous and exogenous factors influence muscle mass. Much of what is currently known regarding muscle protein turnover is owed to the development and use of stable isotope tracers. Skeletal muscle mass is determined by the meal- and contraction-induced alterations of muscle protein synthesis and muscle protein breakdown. Increased loading as resistance training is the most potent nonpharmacological strategy by which skeletal muscle mass can be increased. Conversely, aging (sarcopenia) and muscle disuse lead to the development of anabolic resistance and contribute to the loss of skeletal muscle mass. Nascent omics-based technologies have significantly improved our understanding surrounding the regulation of skeletal muscle mass at the gene, transcript, and protein levels. Despite significant advances surrounding the mechanistic intricacies that underpin changes in skeletal muscle mass, these processes are complex, and more work is certainly needed. In this article, we provide an overview of the importance of skeletal muscle, describe the influence that resistance training, aging, and disuse exert on muscle protein turnover and the molecular regulatory processes that contribute to changes in muscle protein abundance. © 2021 American Physiological Society. Compr Physiol 11:2249-2278, 2021.
... Muscle contraction results in large-scale transcriptional remodelling of metabolic, antioxidant and contractile genes which participate in the adaptation to the increased demands placed on the tissue [2]. This transcriptional remodelling is associated with changes in DNA methylation after both acute exercise [3][4][5] and exercise training [5][6][7]. For example, intense exercise in humans (80% maximal aerobic capacity) resulted in an immediate reduction in promoter methylation of PPARGC1A, TFAM, MEF2A and PDK4 and expression levels of these genes were upregulated 3 hours later in an intensity-dependent manner [3]. ...
... However, exercise-mediated demethylation of promoter regions is transient and re-methylation quickly occurs, within 1-3 hours [3], suggesting possible directed methylation. Changes in nutritional status, either through diabetes status [8], fasting [9], weight loss [10] or diet [7,11] have also been shown to alter DNA methylation in skeletal muscle. ...
... Comparably, we found that acute exercise causes a much more robust effect on the transcriptome than on the methylome. This would suggest that much of the transcriptomic response to acute exercise may not be driven by de novo CpG methylation/demethylation. A similarly small overlap between significantly altered promoter methylation and corresponding transcripts after exercise was found in a previous investigation performed by our lab in human skeletal muscle [7]. As acute exercise is associated with demethylation of exercise-responsive genes [3], ablation of enzymes participating in DNA demethylation such as the TET enzymes, instead of the de novo DNA methyltransferases, may have caused more effects on the transcriptome after exercise. ...
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In response to physical exercise and diet, skeletal muscle adapts to energetic demands through large transcriptional changes. This remodelling is associated with changes in skeletal muscle DNA methylation which may participate in the metabolic adaptation to extracellular stimuli. Yet, the mechanisms by which muscle-borne DNA methylation machinery responds to diet and exercise and impacts muscle function are unknown. Here, we investigated the function of de novo DNA methylation in fully differentiated skeletal muscle. We generated muscle-specific DNA methyltransferase 3A (DNMT3A) knockout mice (mD3AKO) and investigated the impact of DNMT3A ablation on skeletal muscle DNA methylation, exercise capacity and energy metabolism. Loss of DNMT3A reduced DNA methylation in skeletal muscle over multiple genomic contexts and altered the transcription of genes known to be influenced by DNA methylation, but did not affect exercise capacity and whole-body energy metabolism compared to wild type mice. Loss of DNMT3A did not alter skeletal muscle mitochondrial function or the transcriptional response to exercise however did influence the expression of genes involved in muscle development. These data suggest that DNMT3A does not have a large role in the function of mature skeletal muscle although a role in muscle development and differentiation is likely.
... 48 ). Moreover, a study found 809 differentially methylated regions in muscle following short term overfeeding 113 . ...
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Pioneering studies performed over the past few decades demonstrate links between epigenetics and type 2 diabetes mellitus (T2DM), the metabolic disorder with the most rapidly increasing prevalence in the world. Importantly, these studies identified epigenetic modifications, including altered DNA methylation, in pancreatic islets, adipose tissue, skeletal muscle and the liver from individuals with T2DM. As non-genetic factors that affect the risk of T2DM, such as obesity, unhealthy diet, physical inactivity, ageing and the intrauterine environment, have been associated with epigenetic modifications in healthy individuals, epigenetics probably also contributes to T2DM development. In addition, genetic factors associated with T2DM and obesity affect the epigenome in human tissues. Notably, causal mediation analyses found DNA methylation to be a potential mediator of genetic associations with metabolic traits and disease. In the past few years, translational studies have identified blood-based epigenetic markers that might be further developed and used for precision medicine to help patients with T2DM receive optimal therapy and to identify patients at risk of complications. This Review focuses on epigenetic mechanisms in the development of T2DM and the regulation of body weight in humans, with a special focus on precision medicine.
... HIIT also activates AMP-activated protein kinase (AMPK) via ULK1 phosphorylation, resulting in the induction of the autophagy system [60]. The initial increase in mitophagy flux was also encountered after HIIT which was confirmed via the expression of p62, LC3-II, and localization of ubiquitin to a mitochondrial fraction [61]. Based on the studies by Chen et al., the PINK1/ Parkin pathway of inducing mitophagy is assumed to play a pivotal part in the mechanisms of mitochondrial remodeling since HIIT induced mitophagy response was blunted in Parkin knockout animals [62]. ...
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Exercise being a potent stimulator of mitochondrial biogenesis, there is a need to investigate the effects of high-intensity interval training (HIIT) among older adults. This review explores and summarizes the impact of HIIT on mitochondria and various cardio-metabolic health outcomes among older adults, healthy and with comorbid conditions. Electronic databases were scrutinized for literature using permutations of keywords related to (i) Elderly population (ii) HIIT (iii) Mitochondria, cell organelles, and (iv) cardio-metabolic health outcomes. Twenty-one studies that met the inclusion criteria are included in this review. HIIT is an innovative therapeutic modality in preserving mitochondrial quality with age and serves to be a viable, safe, and beneficial exercise alternative in both ill and healthy older adults.
... RNA was checked for quality using the Agilent RNA 600 nano kit and Bioanalyser instrument (Agilent Technologies, Santa Clara, CA). Aliquots of RNA (1 g) were analyzed using the Illumina TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina) as previously described (50,51). Ribosomal RNA was removed from the sample using 35 l of rRNA removal beads (Illumina) on a magnetic plate followed by cleanup of the ribosomal-depleted RNA with 193 l of Agencourt RNAClean XP beads (Beckman Coulter), 70% ethanol wash, and elution into 10 l elution buffer (Illumina). ...
Circadian rhythms are generated by an autoregulatory feedback loop of transcriptional activators and repressors. Circadian rhythm disruption contributes to type 2 diabetes (T2D) pathogenesis. We elucidated whether altered circadian rhythmicity of clock genes is associated with metabolic dysfunction in T2D. Transcriptional cycling of core-clock genes BMAL1, CLOCK, and PER3 was altered in skeletal muscle from individuals with T2D, and this was coupled with reduced number and amplitude of cycling genes and disturbed circadian oxygen consumption. Inner mitochondria–associated genes were enriched for rhythmic peaks in normal glucose tolerance, but not T2D, and positively correlated with insulin sensitivity. Chromatin immunoprecipitation sequencing identified CLOCK and BMAL1 binding to inner-mitochondrial genes associated with insulin sensitivity, implicating regulation by the core clock. Inner-mitochondria disruption altered core-clock gene expression and free-radical production, phenomena that were restored by resveratrol treatment. We identify bidirectional communication between mitochondrial function and rhythmic gene expression, processes that are disturbed in diabetes.
... Studies exploring transcriptional changes induced by exercise in skeletal muscle have shown that genes related to muscle growth and antiatrophy are significantly remodeled. Among these, ANGPTL4 (angiopoietin like 4) is regulated by exercise, whose gene expression is associated with DNA methylation 145 . Hu et al. analyzes gene profiles and transcriptional changes induced by exercise in resistant patients and healthy controls with exercise training. ...
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Cardiovascular diseases (CVDs) are a major cause of mortality worldwide, which are mainly driven by factors such as aging, sedentary lifestyle, and excess alcohol use. Exercise targets several molecules and protects hearts against many of these physiological and pathological stimuli. Accordingly, it is widely recognized as an effective therapeutic strategy for CVD. To investigate the molecular mechanism of exercise in cardiac protection, we identify and describe several crucial targets identified from exercised hearts. These targets include insulin-like growth factor 1 (IGF1)-phosphatidylinositol 3 phosphate kinase (PI3K)/protein kinase B (AKT), transcription factor CCAAT/enhancer-binding protein β (C/EBPβ), cardiac microRNAs (miRNAs, miR-222 and miR-17-3p etc.), exosomal-miRNAs (miR-342, miR-29, etc.), Sirtuin 1 (SIRT1), and nuclear factor erythroid 2‑related factor/metallothioneins (Nrf2/Mts). Targets identified from exercised hearts can alleviate injury via multiple avenues, including: (1) promoting cardiomyocyte proliferation; (2) facilitating cardiomyocyte growth and physiologic hypertrophy; (3) elevating the anti-apoptotic capacity of cardiomyocytes; (4) improving vascular endothelial function; (5) inhibiting pathological remodeling and fibrosis; (6) promoting extracellular vesicles (EVs) production and exosomal-molecules transfer. Exercise is one treatment (‘stone’), which is cardioprotective via multiple avenues (‘birds’), and is considered ‘killing multiple birds with one stone’ in this review. Further, we discuss the potential application of EV cargos in CVD treatment. We provide an outline of targets identified from the exercised heart and their mechanisms, as well as novel ideas for CVD treatment, which may provide novel direction for preclinical trials in cardiac rehabilitation.
... ; /2021 Illumina TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina) as described (Laker et al., 2017;Nylander et al., 2016). Ribosomal RNA was removed from the sample using ...
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Circadian rhythms are generated by an auto-regulatory feedback loop composed of transcriptional activators and repressors. Disruption of circadian rhythms contributes to Type 2 diabetes (T2D) pathogenesis. We elucidated whether altered circadian rhythmicity of clock genes is associated with metabolic dysfunction in T2D. Transcriptional cycling of core clock genes ARNTL, CLOCK, CRY1 and NR1D1 was altered in skeletal muscle from individuals with T2D and this was coupled with reduced number and amplitude of cycling genes and disturbed circadian oxygen consumption. Mitochondrial associated genes were enriched for differential circadian amplitudes in T2D, and positively correlated with insulin sensitivity. ChIP-sequencing identified CLOCK and BMAL1 binding to circadian mitochondrial genes associated with insulin sensitivity, implicating regulation by the core clock. Mitochondria disruption altered core-clock gene expression and free-radical production, phenomena that were restored by resveratrol treatment. We identify bi-directional communication between mitochondrial function and rhythmic gene expression, processes which are disturbed in diabetes.
... Reduced representation bisulfite sequencing (RRBS) libraries were generated from female offspring skeletal muscle DNA as described earlier (16) and subjected to 75-bp singleend sequencing (NextSeq 2500, Illumina). Reads were trimmed using Trim Galore! v0.4.3 with the -rrbs flag. ...
Parental health influences embryonic development and susceptibility to disease in the offspring. We investigated whether maternal voluntary running during gestation could protect the offspring from the adverse effects of maternal or paternal high-fat diet (HF) in mice. We performed transcriptomic and whole-genome DNA methylation analyses in female offspring skeletal muscle as well as targeted DNA methylation analysis of the peroxisome proliferator-activated receptor γ coactivator-1α (Pgc-1α) promoter in the both male and female adult offspring. Maternal HF resulted in impaired metabolic homeostasis in male offspring at 9 months of age, while both male and female offspring were negatively impacted by paternal HF. Maternal exercise during gestation completely mitigated these metabolic impairments. Female adult offspring from obese male or female parent had skeletal muscle transcriptional profiles enriched in genes regulating inflammation and immune responses, whereas maternal exercise resulted in a transcriptional profile similar to offspring from normal chow fed parents. Maternal HF, but not paternal HF, resulted in hypermethylation of the Pgc-1α promoter at CpG -260, which was abolished by maternal exercise. These findings demonstrate the negative consequences of maternal and paternal HF for the offspring's metabolic outcomes later in life possibly through different epigenetic mechanisms, and maternal exercise during gestation mitigates the negative consequences.
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Obesity is directly connected to lifestyle and has been associated with DNA methylation changes that may cause alterations in the adipogenesis and lipid storage processes contributing to the development of the disease. We demonstrate a complete protocol from selection to epigenetic data analysis of patients with and without obesity. All steps from the protocol were tested and validated in a pilot study. 32 women participated in the study, in which 15 individuals were classified with obesity according to Body Mass Index (BMI) (45.1 ± 5.4 kg/m2); and 17 individuals were classified without obesity according to BMI (22.6 ± 1.8 kg/m2). In the group with obesity, 564 CpG sites related to fat mass were identified by linear regression analysis. The CpG sites were in the promoter regions. The differential analysis found 470 CpGs hypomethylated and 94 hypermethylated sites in individuals with obesity. The most hypomethylated enriched pathwayswere in the RUNX, WNT signaling, and response to hypoxia. The hypermethylated pathways were related to insulin secretion, glucagon signaling, and Ca2+. We conclude that the protocol effectively identified DNA methylation patterns and trait-related DNA methylation. These patterns could be associated with altered gene expression, affecting adipogenesis and lipid storage. Our results confirmed that an obesogenic lifestyle could promote epigenetic changes in human DNA.
The complexity and dynamics of human diseases are driven by the interactions between internal molecular activities and external environmental exposures. Although advances in omics technology have dramatically broadened the understanding of internal molecular and cellular mechanisms, understanding of the external environmental exposures, especially at the personal level, is still rudimentary in comparison. This is largely owing to our limited ability to efficiently collect the personal environmental exposome (PEE) and extract the nucleic acids and chemicals from PEE. Here we describe a protocol that integrates hardware and experimental pipelines to collect and decode biotic and abiotic external exposome at the individual level. The described protocol has several advantages over conventional approaches, such as exposome monitoring at the personal level, decontamination steps to increase sensitivity and simultaneous capture and high-throughput profiling of biotic and abiotic exposures. The protocol takes ~18 h of bench time over 2–3 d to prepare samples for high-throughput profiling and up to a couple of weeks of instrumental time to analyze, depending on the number of samples. Hundreds to thousands of species and organic compounds could be detected in the airborne particulate samples using this protocol. The composition and complexity of the biotic and abiotic substances are heavily influenced by the sampling spatiotemporal factors. Basic skillsets in molecular biology and analytical chemistry are required to carry out this protocol. This protocol could be modified to decode biotic and abiotic substances in other types of low or ultra-low input samples.
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Skeletal muscle is a major contributor to whole-body metabolism as it serves as a depot for both glucose and amino acids, and is a highly metabolically active tissue. Within skeletal muscle exists an intrinsic molecular clock mechanism that regulates the timing of physiological processes. A key function of the clock is to regulate the timing of metabolic processes to anticipate time of day changes in environmental conditions. The purpose of this study was to identify metabolic genes that are expressed in a circadian manner and determine if these genes are regulated downstream of the intrinsic molecular clock by assaying gene expression in an inducible skeletal muscle-specific Bmal1 knockout mouse model (iMS-Bmal1 (-/-) ). We used circadian statistics to analyze a publicly available, high-resolution time-course skeletal muscle expression dataset. Gene ontology analysis was utilized to identify enriched biological processes in the skeletal muscle circadian transcriptome. We generated a tamoxifen-inducible skeletal muscle-specific Bmal1 knockout mouse model and performed a time-course microarray experiment to identify gene expression changes downstream of the molecular clock. Wheel activity monitoring was used to assess circadian behavioral rhythms in iMS-Bmal1 (-/-) and control iMS-Bmal1 (+/+) mice. The skeletal muscle circadian transcriptome was highly enriched for metabolic processes. Acrophase analysis of circadian metabolic genes revealed a temporal separation of genes involved in substrate utilization and storage over a 24-h period. A number of circadian metabolic genes were differentially expressed in the skeletal muscle of the iMS-Bmal1 (-/-) mice. The iMS-Bmal1 (-/-) mice displayed circadian behavioral rhythms indistinguishable from iMS-Bmal1 (+/+) mice. We also observed a gene signature indicative of a fast to slow fiber-type shift and a more oxidative skeletal muscle in the iMS-Bmal1 (-/-) model. These data provide evidence that the intrinsic molecular clock in skeletal muscle temporally regulates genes involved in the utilization and storage of substrates independent of circadian activity. Disruption of this mechanism caused by phase shifts (that is, social jetlag) or night eating may ultimately diminish skeletal muscle's ability to efficiently maintain metabolic homeostasis over a 24-h period.
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Using an unbiased systems genetics approach, we previously predicted a role for CHAC1 in the endoplasmic reticulum (ER) stress pathway, functionally linked to Activating Transcription Factor 4 (ATF4) following treatment with oxidized phospholipids, a model for atherosclerosis. Mouse and yeast CHAC1 homologs have been shown to degrade glutathione in yeast and a cell-free system. In the present report, we further defined the ATF4-CHAC1 interaction by cloning the human CHAC1 promoter upstream of a luciferase reporter system for in vitro assays in HEK293 and U2OS cells. Mutation and deletion analysis defined two major cis DNA elements necessary and sufficient for CHAC1 promoter-driven luciferase transcription in conditions of ER stress or ATF4 co-expression: the -267 ATF/CRE (Activating Transcription Factor/cAMP-response element) site and a novel -248 ATF/CRE Modifier (ACM) element. We also examined the ability of the CHAC1 ATF/CRE and ACM sequences to bind ATF4 and ATF3 using Immunoblot (IM)-EMSA, and confirmed ATF4, ATF3, and CEBPβ binding at the human CHAC1 promoter in the proximity of the ATF/CRE and ACM using ChIP. To further validate the function of CHAC1 in a human cell model, we measured glutathione levels in HEK293 cells with enhanced CHAC1 expression. Overexpression of CHAC1 led to a robust depletion of glutathione, which was alleviated in a CHAC1 catalytic mutant. These results suggest an important role for CHAC1 in oxidative stress and apoptosis with implications for human health and disease. Copyright © 2015, The American Society for Biochemistry and Molecular Biology.
It is generally accepted that muscle adaptation to resistance exercise (REX) training is underpinned by contraction-induced, increased rates of protein synthesis and dietary protein availability. By using dynamic proteome profiling (DPP), we investigated the contribution of both synthesis and breakdown to changes in abundance on a protein-by-protein basis in human skeletal muscle. Age-matched, overweight males consumed 9 d of a high-fat, low-carbohydrate diet during which time they either undertook 3 sessions of REX or performed no exercise. Precursor enrichment and the rate of incorporation of deuterium oxide into newly synthesized muscle proteins were determined by mass spectrometry. Ninety proteins were included in the DPP, with 28 proteins exhibiting significant responses to REX. The most common pattern of response was an increase in turnover, followed by an increase in abundance with no detectable increase in protein synthesis. Here, we provide novel evidence that demonstrates that the contribution of synthesis and breakdown to changes in protein abundance induced by REX differ on a protein-by-protein basis. We also highlight the importance of the degradation of individual muscle proteins after exercise in human skeletal muscle.—Camera, D. M., Burniston, J. G., Pogson, M. A., Smiles, W. J., Hawley, J. A. Dynamic proteome profiling of individual proteins in human skeletal muscle after a high-fat diet and resistance exercise.
Exposure to ionizing radiation increases the risk of chronic metabolic disorders such as insulin resistance and type 2 diabetes later in life. We hypothesized that irradiation reprograms the epigenome of metabolic progenitor cells, which could account for impaired metabolism after cancer treatment. C57Bl/6 mice were treated with a single dose of irradiation and subjected to high-fat diet (HFD). RNA sequencing and reduced representation bisulfite sequencing were used to create transcriptomic and epigenomic profiles of preadipocytes and skeletal muscle satellite cells collected from irradiated mice. Mice subjected to total body irradiation showed alterations in glucose metabolism and, when challenged with HFD, marked hyperinsulinemia. Insulin signaling was chronically disrupted in skeletal muscle and adipose progenitor cells collected from irradiated mice and differentiated in culture. Epigenomic profiling of skeletal muscle and adipose progenitor cells from irradiated animals revealed substantial DNA methylation changes, notably for genes regulating the cell cycle, glucose/lipid metabolism, and expression of epigenetic modifiers. Our results show that total body irradiation alters intracellular signaling and epigenetic pathways regulating cell proliferation and differentiation of skeletal muscle and adipose progenitor cells and provide a possiblemechanism by which irradiation used in cancer treatment increases the risk for metabolic disease later in life.
Epigenetic changes are caused by biochemical regulators of gene expression that can be transferred across generations or through cell division. Epigenetic modifications can arise from a variety of environmental exposures including undernutrition, obesity, physical activity, stress and toxins. Transient epigenetic changes across the entire genome can influence metabolic outcomes and might or might not be heritable. These modifications direct and maintain the cell-type specific gene expression state. Transient epigenetic changes can be driven by DNA methylation and histone modification in response to environmental stressors. A detailed understanding of the epigenetic signatures of insulin resistance and the adaptive response to exercise might identify new therapeutic targets that can be further developed to improve insulin sensitivity and prevent obesity. This Review focuses on the current understanding of mechanisms by which lifestyle factors affect the epigenetic landscape in type 2 diabetes mellitus and obesity. Evidence from the past few years about the potential mechanisms by which diet and exercise affect the epigenome over several generations is discussed.
The loss of skeletal muscle mass is observed in many pathophysiological conditions including, aging and obesity. The loss of muscle mass and function with aging is defined as sarcopenia and characterized by a mismatch between skeletal muscle protein synthesis (MPS) and breakdown. Characteristic metabolic features of both aging and obese muscle are increases in intramyocellular lipid (IMCL) content. IMCL accumulation may play a mechanistic role in the development anabolic resistance and the progression of muscle atrophy in aging and obesity. In the present study, aged and high-fat fed mice were used to determine mechanisms leading to muscle loss. We hypothesized the accumulation of bioactive-lipids in skeletal muscle, such as, ceramide or diacylglycerols, leads to insulin resistance with aging and obesity and the inability to activate protein synthesis contributing to skeletal muscle loss. We report a positive association between bioactive-lipid accumulation and the loss of lean mass and muscle strength. Obesity and aging induced significantly higher storage of ceramide and diacylglycerol compared to young. Furthermore, there was an attenuated insulin response to components of the mTOR anabolic signaling pathway. We also observed differential increases in the expression of inflammatory cytokines and the phosphorylation of IκBα between aging and obesity. These data challenge the accepted role of increased inflammation in obesity-induced insulin-resistance in skeletal muscle. Furthermore, we have now established IκBα with a novel function in aging-associated muscle loss that may be independent of its previously understood role as an NFκB inhibitor.
Obesity is a heritable disorder, with children of obese fathers at higher risk of developing obesity. Environmental factors epigenetically influence somatic tissues, but the contribution of these factors to the establishment of epigenetic patterns in human gametes is unknown. Here, we hypothesized that weight loss remodels the epigenetic signature of spermatozoa in human obesity. Comprehensive profiling of the epigenome of sperm from lean and obese men showed similar histone positioning, but small non-coding RNA expression and DNA methylation patterns were markedly different. In a separate cohort of morbidly obese men, surgery-induced weight loss was associated with a dramatic remodeling of sperm DNA methylation, notably at genetic locations implicated in the central control of appetite. Our data provide evidence that the epigenome of human spermatozoa dynamically changes under environmental pressure and offers insight into how obesity may propagate metabolic dysfunction to the next generation.
Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data.Availability: The package is freely available under the LGPL licence from the Bioconductor web site (
Exercise represents a major challenge to whole-body homeostasis provoking widespread perturbations in numerous cells, tissues, and organs that are caused by or are a response to the increased metabolic activity of contracting skeletal muscles. To meet this challenge, multiple integrated and often redundant responses operate to blunt the homeostatic threats generated by exercise-induced increases in muscle energy and oxygen demand. The application of molecular techniques to exercise biology has provided greater understanding of the multiplicity and complexity of cellular networks involved in exercise responses, and recent discoveries offer perspectives on the mechanisms by which muscle "communicates" with other organs and mediates the beneficial effects of exercise on health and performance.
Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread ( or Rsubread ( software packages.