The FASEB Journal. 2020;00:1–12. wileyonlinelibrary.com/journal/fsb2
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1R E S E A R C H A R T I C L E
Three months of bed rest induce a residual transcriptomic
signature resilient to resistance exercise countermeasures
Rodrigo Fernandez-Gonzalo
1|
Per A. Tesch
2|
Tommy R. Lundberg
1|
Björn A. Alkner
3,4|
Eric Rullman
1|
Thomas Gustafsson
1This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
© 2020 The Authors. The FASEB Journal published by Wiley Periodicals LLC on behalf of Federation of American Societies for Experimental Biology Eric Rullman and Thomas Gustafsson Joint senior authors.
Abbreviations: BR, bed rest; BRE, bed rest and exercise; DAVID, The Database for Annotation, Visualization and Integrated Discovery; FC, fold change; FDR, false discovery rate; Go-term, gene ontology-term; Kcal, kilocalorie; LIMMA, linear models for microarray data; MEDES, Space Medicine and Physiology clinic, Toulouse, France; NUSE, normalized unscaled standard error; PCA, principal component analysis; RE, resistance exercise; t-SNE, t-distributed stochastic neighbor embedding
1Department of Laboratory Medicine,
Division of Clinical Physiology, Karolinska Institutet, and Unit of Clinical Physiology, Karolinska University Hospital, Stockholm, Sweden
2Department of Physiology &
Pharmacology, Karolinska Institutet, Stockholm, Sweden
3Department of Orthopaedics, Region
Jönköping County, Eksjö, Sweden
4Department of Biomedical and Clinical
Sciences, Linköping University, Linköping, Sweden
Correspondence
Rodrigo Fernandez-Gonzalo, Department of Laboratory Medicine, Division of Clinical Physiology, Karolinska Institute, and Unit of Clinical Physiology, Karolinska University Hospital, ANA Futura, Alfred Nobels Allé 8, 141 52 Huddinge, Stockholm, Sweden.
Email: rodrigo.gonzalo@ki.se Funding information
Swedish National Space Agency; European Space Agency (ESA); Swedish National Center for Research in Sports
Abstract
This study explored the muscle genome-wide response to long-term unloading (84-day bed rest) in 21 men. We hypothesized that a part of the bed rest-induced gene expression signature would be resilient to a concurrent flywheel resistance exercise (RE) countermeasure. Using DNA microarray technology analyzing 35 345 gene-level probe-sets, we identified 335 annotated probe-sets that were downregulated, and 315 that were upregulated after bed rest (P < .01). Besides a predictable differen-tial expression of genes and pathways related to mitochondria (downregulation; false-discovery rates (FDR) <1E-04), ubiquitin system (upregulation; FDR = 3E-02), and skeletal muscle energy metabolism and structure (downregulation; FDR ≤ 3E-03), 84-day bed rest also altered circadian rhythm regulation (upregulation; FDR = 3E-02). While most of the bed rest-induced changes were counteracted by RE, 209 transcripts were resilient to the exercise countermeasure. Genes upregulated after bed rest were particularly resistant to training (P < .001 vs downregulated, non-reversed genes). Specifically, “Translation Factors,” “Proteasome Degradation,” “Cell Cycle,” and “Nucleotide Metabolism” pathways were not normalized by RE. This study provides an unbiased high-throughput transcriptomic signature of one of the longest unloading periods in humans to date. Classical disuse-related changes in structural and meta-bolic genes/pathways were identified, together with a novel upregulation of circadian rhythm transcripts. In the context of previous bed rest campaigns, the latter seemed to be related to the duration of unloading, suggesting the transcriptomic machinery continues to adapt throughout extended disuse periods. Despite that the RE training offset most of the bed rest-induced muscle-phenotypic and transcriptomic alterations,
1
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INTRODUCTION
In response to reduced mechanical stimuli, the skeletal muscle experiences loss of mass and function, increased fa-tigability and insulin resistance, and a shift toward a faster
muscle fiber phenotype.1-6 The loss of muscle mass during
short periods of disuse or unloading, such as during recovery from injury or illness, is characterized by a rapid increase
in protein breakdown,7,8 along with reduced muscle protein
synthesis.9 In contrast, knowledge about the physiological
and molecular basis for muscle loss during prolonged disuse periods warrants further research, since this has mainly been characterized in cross-sectional studies.
Hitherto attempts to provide mechanistic information on the molecular programs governing unloading-induced mus-cle deconditioning have included the exploration of tran-scriptome changes in muscle after short-term bed rest or unilateral lower limb suspension/cast immobilization,
rang-ing from 24 hours to 21 days,10-17 or longer periods of bed
rest (60 days).18,19 A common disuse signature, regardless of
the differences in methods and/or study duration, is a marked downregulation of gene networks related to both energy me-tabolism and structural components, together with an
upreg-ulation of the ubiquitin-proteasome pathway.10-12,14,15,17-19
In addition, we recently identified the MEF2 family of tran-scription factors, in particular MEF2C, as potential master regulators of skeletal muscle alterations to short-term
un-loading (21-day bed rest),15 while microRNAs seemed to
play a negligible role.16 In contrast, the molecular basis of
long-term disuse atrophy have remained scantly research. Thus, although unloading models, in particular bed rest, in-duce robust muscle atrophy solely due to lack of mechani-cal stimuli, it is plausible that the transcriptomic information gathered from long-term bed rest could further our under-standing of more complex and multifactorial muscle wasting
conditions.20 Indeed, additional mechanistic information on
the driving forces behind disuse-induced muscle loss would allow for better characterization of nutritional/pharmacolog-ical and/or exercise countermeasures to prevent, or at least attenuate, muscle loss during long-term lack of mechanical stimuli such as during extended disease episodes.
One of the most efficient strategies to preserve muscle in-tegrity during unloaded conditions is high-intensity resistance exercise (RE). The use of an iso-inertial flywheel exercise
paradigm was able to preserve mm. quadriceps mass, and halved the atrophy in m. triceps surae after 90 days of bed rest
in men.1 We also showed that this protocol was effective in
counteracting some, but not all, of the metabolic alterations
in muscle triggered by 84-day bed rest.21 However, whether
those positive adaptations induced by RE were due to a re-versal effect on the specific molecular pathways controlling muscle integrity during unloading, or to an activation of dif-ferent pathways, or a combination, remains to be elucidated. It follows that the potential existence of groups of genes that are not reversed by the countermeasure employed might be of particular interest, since these could provide mechanistic insight into disuse-related changes that are resilient to current interventions employed to combat muscle loss.
The main purpose of the current study was to analyze the genome-wide muscle transcriptome response to long-term bed rest with or without RE. We hypothesized that pathways related to metabolism, cell structure, and protein synthesis would be downregulated, while molecular routes direct-ing protein breakdown would be upregulated by 84 days of bed rest. In addition, while we hypothesized that RE would restore the majority of the transcriptional signature of bed rest, we specifically sought to explore the potential existence of genes that would be resilient to the countermeasure em-ployed. Finally, we used an exon usage analysis to determine splice events induced by long-term bed rest.
2
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MATERIALS AND METHODS
2.1
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General design
Twenty-one healthy men (age range 26-41 years) were ran-domly assigned to performed 90-day bed rest with (bed rest and exercise, BRE; n = 9) or without (BR; n = 12) concur-rent iso-inertial RE every third day targeting the quadriceps muscle group (ie, supine squat; four sets of seven maximal concentric-eccentric repetitions) and the calf muscles (ie, calf press; 4 sets of 14 concentric-eccentric repetitions) employing flywheel technology. Muscle biopsies from m. vastus lateralis were obtained from all subjects before and after 84 days of bed rest. The muscle specimens were used to conduct a DNA microarray analysis. We and others have previously reported on functional, structural, and metabolic we contend that the human skeletal muscle also displays a residual transcriptomic signature of unloading that is resistant to an established exercise countermeasure.
K E Y W O R D S
muscle adaptations during the same bed rest project,1,3,6,21-23
as well as tendon24 and bone properties,25,26 and vascular
alterations.27
2.2
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Subjects
Specialized personnel from the Institute for Space Medicine and Physiology clinic (MEDES) interviewed potential can-didates. Finally, 21 healthy men were recruited, and after a thorough medical examination, nine men (33 ± 5 years, 176 ± 5 cm, and 71 ± 6 kg) were randomly assigned to 90-day bed rest with concurrent flywheel resistance exercise (BRE), and 12 men (32 ± 4 years, 173 ± 3 cm, and 72 ± 5 kg) to 90-day bed rest only (BR). One of the subjects in BRE had a previous unreported knee injury that made him failed to com-plete some training sessions and post-bed rest physical tests. Three subjects from BR received pamidronate supplementa-tion. The purposes, premises, and risks associated with the experiments were clearly described before subjects signed a written consent form to participate. The study was designed and performed according to the Declaration of Helsinki. All the experiments included in the study were approved by the local Ethics Committee.
2.3
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Head-down tilt bed rest
Subjects from both BR and BRE were subjected to 6º head-down tilt position at all times (ie, rest, exercise training, toi-let procedures, shower, transportation, etc). The participants were only allowed to rest on their elbows during meals, and to move in the horizontal plane. Video surveillance and pres-sure-sensitive mattresses were used to assess compliance. On a daily basis, physiotherapists performed massages and ankle circumduction movements in all participants. Diet and time of the day for each meal were controlled during the bed rest period. The caloric intake was based on subjects' body weight,
and it corresponded to 34.8 kcal kg−1 day−1 (50%-55%
carbo-hydrates, 30%-35% lipids, and 12%-15% proteins).28
2.4
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Flywheel RE
The RE performed by BRE consisted of 6° head-down tilt su-pine squat and calf press exercises using iso-inertial flywheel
technology (Yo-Yo Technology Inc, Stockholm, Sweden1)
every third day (2-3 days per week; ~3 minutes of actual muscle activation per week). The exercise training began on day 5 of bed rest. Four sets of 7 or 14 maximal, coupled con-centric-eccentric repetitions were performed in each session for the supine squat and calf press, respectively. Two min-utes of rest were allowed between sets. During all repetitions
force, power, work, joint angle, and angular velocity were
recorded.1
2.5
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Skeletal muscle biopsies
Before (PRE) and after (POST) 84-day bed rest, yet prior to re-ambulation, muscle biopsies were obtained from m. vas-tus lateralis of the dominant leg from all subjects. Despite the bed rest period lasting 90 days, biopsies were obtained at day 84 to avoid any interference with the demanding testing schedule following the intervention. All pre- and post-bed rest biopsies were taken in the morning within a 2-3-hour window. Briefly, after local anesthesia had been applied, tissue samples were collected using 5- or 6-mm Bergström needles. Samples were cleansed from fat, connective tissue, and excess blood, before being frozen in liquid nitrogen and stored at −80°C.
2.6
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RNA extraction and
microarray analysis
Using a bead beater device (BioSpec Products, Inc, Bartlesville, OK) and TRIzol (Invitrogen Life Technologies, Carlsbad, CA), total RNA was extracted from ~20-mg frozen muscle samples. Then, the RNA was purified using PureYield RNA Midiprep System (Promega Corporation, Madison, WI) and RNA quality was checked using an Agilent 2100 bioanalyzer (Agilent Technologies, Amsterdam, NL). HTA 2.0 gene-chips were processed according to the manufac-turer's protocol. Fragmented (5 μg) cDNA was hybridized to each array and scanned using a Gene Chip Scanner 30007G. Probesets were scaled, normalized and summarized on Ensbl-gene- and exon-level, respectively using the
Aroma-pipeline29 and chip definition files from Brainarray V19.30
Quality control was performed using normalized unscaled standard error (NUSE) and principal components analysis (PCA). The complete data set is publicly available at Gene Expression Omnibus with accession ID (GSE148152).
Unsupervised cluster-analysis was carried out using
t-distributed stochastic neighbor embedding (t-SNE)31,32
utilizing Rt-SNE.33 Gene-level differential expression was
assessed using Limma, analyzing PRE vs POST block wise per subject as well as differences between BR and BRE over time: ENSG~(BR_POST – BR_PRE) − (BRE_POST – BRE_PRE). False discovery rates (FDR) were calculated based on Bayesian moderated t-statistics where an FDR of 1% was considered significant.
Gene-ontology analysis and pathway enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) (biological function and cel-lular compartment) for overrepresentation among differentially
expressed genes, with all genes tested for differential expression as background. Pathway analysis was performed using gene-set enrichment analysis where pathway annotation of genes was
retrieved from wiki-pathways (current as of December 2018).34
For both over-representation and gene-set enrichment, an FDR of 5% was considered significant.
The continuous relationship between BR and BRE was in-vestigated using FC-FC plot using the logFC of BR (x-axis) and logFC of BRE (y-axis) for each gene, thus creating a polar coordinate system illustrating similarities/dissimilarities of gene-expression between the two conditions. The resulting cle is divided into eight sectors each covering 45° of the cir-cle. Each sector will contain genes with a similar regulation in both conditions, significant effect after BR but not BRE, or vice versa. Pathway-level comparison of BR vs BRE differential expression was calculated using two-sided Wilcoxon tests on empirical cumulative distributions where an FDR of 5% was considered significantly different between BR and BRE.
Transcript isoform expression was analyzed by re-anno-tation of the probe-data from the microarray to the transcript level Ensbl-transcript probeset version 19 from Brainarray. Differential expression after bed rest was analyzed in the same manner as gene-level data. To identify isoforms within the same gene with different response to bed rest, the transcript-isoforms for each differentially expressed gene were analyzed for dif-ferences in response to the bed rest intervention by compar-ing the pairwise transcripts uscompar-ing Wilcoxon-test. Alternative exon usage was analyzed using the diffSplice function within Limma, where t-statistics (P < .05) is used to compare each exon to the average of all other exons for the same gene.
3
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RESULTS
Changes in muscle size and function from the 90-day bed rest project have been described previously. In brief, the un-loading intervention induced an 18% decreased of quadriceps muscle volume, which was counteracted by the RE protocol
employed.1 Similarly, decrements in muscle function of knee
extensor muscles after the bed rest period were partially
off-set by the flywheel RE training program,1 as well as some
of the metabolic alterations induced by long-term bed rest.21
3.1
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Bed rest
Following 84 days of bed rest, 35 345 gene-level probe sets were analyzed for differential expression, of these 17 207 were un-annotated. Gene-level differential expression iden-tified 335 annotated probe sets that were downregulated, and 315 that were upregulated after BR at an FDR of 0.01 (Figure 1A, Table S1). Fifteen biological functions and eight cellular compartments were enriched at an FDR of <1%
among the downregulated genes, and eight biological func-tions and seven cellular compartments among the upregu-lated genes (Figure 1A, Table S2).
Of the downregulated ontologies, the most notable were related to mitochondrial compartment and function. In fact, 53 of the 335 downregulated genes were associated with mi-tochondrial function (Figure 1A, Table S1). Mitochondrion was overwhelmingly dominating in cellular compartment, that is, 109 of the 335 genes were annotated as localized within the mitochondrion rendering a >20-fold enrich-ment for mitochondrial related genes. Consistent with the substantial loss of muscle mass, ontologies related to mus-cle structural components were highly enriched among the downregulated genes (Figure 1A, Table S2). While most of the myosin-related genes were downregulated, for example, MYH7 and MYL2, the fast-twitch myosin MYH1 and peri-natal MYH8 (P = .0107) were both upregulated (Table S1). Of the upregulated ontologies, the most highly enriched were related to genes involved in mRNA-processing and regulation of transcription, followed by members of the ubiquitin system (Figure 1A, Table S2). The expression of several genes pre-viously reported to be involved in the regulation of circadian rhythm was also greater after bed rest (9.7-fold enrichment) (Figure 1A, Table S2), including the well-known Bmal1 tran-scription factor regulators RORA and NR1D2. While RORA acts as an activator of Bmal1 transcription, NR1D2, a mem-ber of the nuclear hormone receptor subgroup Rev-erb,
inhib-its Bmal1 expression.35,36
A substantial number (ie, 85) of transcription factors and co-factors were differentially expressed after the bed rest period. There were significantly (P < .001) more tran-scription factors among the upregulated (n = 64) than the downregulated genes (n = 21) (Figure 1B, Table S3). A majority of these transcription factors changed in a pattern coherent with the observed gene expression profile, re-flecting their documented regulatory functions. Several of these factors have previously been linked to metabolic al-teration and atrophy processes in skeletal muscle following unloading, such as the downregulation of PGC1-alpha and PPARA, and the upregulation of Foxo3 and NF-kappa-beta. Yet, several transcription factors not previously associated with lack of mechanical stimuli were also identified. For example, TEF-1 (TEAD1), a transcription factor implicated
in the fast-to-slow fiber-type transition,37 and PROX1,
which is specifically expressed in slow muscle fibers,38
were downregulated in BR. This was in accordance with the upregulation of genes related to fast-twitch myosin (see above). Other downregulated transcription factors with a known impact on molecular regulation of skeletal muscle were the glucose-sensing MLXIPL, the circadian rhythm factor NPAS2, and ESRRA, an important component of the regeneration-to-injury process. Upregulated transcription factors following BR, with a role in muscle remodeling and
molecular regulation, were EPC1, KLF10, RBPJ, NFE2L2 (alt. Nfr2), and SP3 (skeletal muscle growth regulation); MDM2 and TRIM32 (E3 ubiquitin-protein system); and RBFOX2 (exon splicing) (Figure 1B, Table S3).
Using the diffSplice method in linear models for microar-ray data (LIMMA), transcript isoform and alternative exon usage was analyzed. We discovered 553 genes that had ≥1 exon with alternative exon usage at an FDR < 1%. Of these, 219 could be attributed to genes that had ≥2 transcript iso-forms differentially expressed at an FDR < 1%, and 83 genes had transcripts with isoforms where the response to bed rest was significantly different among the transcripts (Table S4, Figure S1). These transcripts belonged to genes primarily associated with muscle structural components and contrac-tile machinery; in fact, “muscle filament sliding” (FDR 5%)
was the only Gene ontology-term (GO-term) significantly enriched among the genes with differentially expressed tran-script isoforms.
3.2
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Effect of exercise countermeasure
To evaluate the gene expression profile following prolonged bed rest with and without RE countermeasure, data were ex-plored in an unsupervised data-driven fashion using t-SNE. This analysis revealed distinct clustering into three groups (PRE, BR, and BRE), where the Euclidian distance between the PRE and BRE observations was significantly smaller and with a certain degree of overlap, compared with the distance between BR and BRE (Figure 2A). This was also
FIGURE 1 V-plots of long-term bed rest. A, V-plot showing overall gene expression alterations by 84 days of bed rest (FDR < 0.01), with the significantly upregulated (red) and downregulated (blue) genes, together with representative cellular compartments and biological processes. B, V-plot highlighting differentially expressed genes after 84 days of bed rest belonging to transcription factors
0 2 4 6 −2 −1 0 1 2 0 2 4 6 −1 0 1 (A) (B) Description FC FDR Description FC FDR Description FC FDR Description FC FDR MSTN MYH7B BCKDK SLC41A1 SPATA25 USP6 RRAD PPIF MYL3 NMRK2 ADH1B LMOD1 CIR1 NINJ2 HSPB6MYH7 ANKRD12 DHCR24 FOXO3 ADH1C ARHGAP28 NEDD4L TNNT1 ART3 MYH1 CASQ2 PDE11A PLCE1 TP63 ABCA5 FABP3 MYOZ2 logFC −logFDR MDM2 CIR1 ELP2 DEKEPC2 PPARGC1B FOXO3 HMBOX1 NFYC THAP4 NFKBIA NR1D2 SFPQ SMARCC1 ARHGAP35 TP63 PROX1 NPAS2 PPARA PREB MLXIPL logFC −logFD R Transcription factors mitochondrial inner membrane 8.7 3.E-41
mitochondrion 4.4 2.E-38 mitochondrial matrix 5.9 1.E-14
mitochondrial electron transport 17.4 7.E-10 tricarboxylic acid cycle 16.2 2.E-05 muscle filament sliding 12.4 1.E-04
nucleus 1.8 3.E-15 nucleoplasm 2.0 1.E-09 chromatin 6.0 1.E-02
mRNA processing 5.3 1.E-03 transcription, DNA-templated 1.7 6.E-02 protein ubiquitination 2.9 3.E-02 regulation of circadian rhythm 8.3 3.E-02
Cellular compartment
Biological process
Cellular compartment
FIGURE 2 Effects of high-intensity, low-volume resistance exercise to counteract the transcriptomic alterations induced by 84 days of bed rest. A, tSNE-plot with hierarchical clustering of global gene expression before (PRE) and after 84 days of bed rest with (BRE) and without (BR) resistance exercise countermeasure. B, Representation of the continuous relationship between BR and BRE using FC-FC plot using the logFC of BR (x-axis) and logFC of BRE (y-axis) for each gene. This polar coordinate system illustrates the similarities/dissimilarities of gene-expression between the two conditions. The resulting circle is divided into 8 sectors each covering 45° of the circle. Genes that were not normalized by exercise are shown in purple, those where exercise normalized the expression (related to PRE) are shown in soft green, and those where exercise actually overcompensated the expression of the particular transcript (related to PRE) are displayed in dark green. C, Pie charts showing the power of the exercise countermeasure employed to normalize transcriptome alterations induced by 84 days of bed rest with specific focus on both downregulated and upregulated factors. Note the greater proportion of genes not normalized by exercise among the upregulated genes (45%) when compared with the downregulated ones (20%) (***; P < .001)
BR BR + E Time No Normalized by Exercise: Yes
Yes plus overcompensated Downregulated by Bedrest n = 335 Upregulated by Bedrest n = 315 *** 20% 74% 6% 45% 54% 1% (A) (B) (C)
Not Normalized by Exercise
Overcompensated by Exercise Normalized by Exercise
evident from the differential expression analysis, where 52 of the downregulated and 22 of the upregulated genes had an interaction between BR and BRE over time (P < .05). The propensity of the genes that were reversed by the exercise countermeasure were further analyzed based on co-variance
between BR and BRE.39 This approach allowed us to
visual-ize the effects of the two interventions on the gene-level and to stratify genes based on their propensity to become reversed (or amplified) in the BRE condition. The majority (268 of 335) of the genes downregulated by BR were reversed by exercise, and 20 genes were even over-compensated, that is, negative FC in BR and a positive FC in BRE (Figure 2B,C). Only 20% of the genes (67 of 335) that were downregulated in BR remained downregulated to a similar extent follow-ing BRE, which was in contrast to the 45% (142 out of 315) of genes that were upregulated following both BR and BRE (Figure 2B,C; Table S5). To test whether the group of genes not reversed in the BRE group was due to a lack of exer-cise effects on these genes, or rather induced by both stimuli (unloading and exercise), the genes included in the residual signature were compared with RE training transcriptome
data sets from young men in untrained-basal vs trained-basal
conditions.40,41 The overlap between the BRE residual
signa-ture and the genes differentially expressed by RE (ie, Pre vs Post differences P < .05) had little similarities. Thus, only 6 and 28 genes out of the 209 genes included in the residual
signature were differentially regulated by RE in Raue et al41
and Damas et al,40 respectively. Overall, these results reflect
specific disuse transcriptomic alterations that are independ-ent from RE-increased levels of muscle activation and/or tension.
The difference regarding the effect of the exercise countermeasure between the downregulated and upregulated genes persisted when we summarized the data on the level of pathways and biological functions (Figure 3). Thus, for all downregulated pathways after BR, the effect was reduced (ie, more similar to the pre-bed rest condition) in the BRE group, which was not the case for the upregulated pathways (see below). The highest degree of reversibility by exercise was found in those genes associated to “Electron Transport Chain” (Wilcoxon-test 7e-21). This pathway was even slightly elevated compared with the pre-level in the BRE
FIGURE 3 Log-change (related to PRE) of molecular pathways after 84 days of bed rest with (BRE) or without (BR) concurrent resistance exercise training
Electron Transport Chain Oxidative phosphorylation Fatty Acid Beta Oxidation Circadian rythm related genes TCA Cycle TGF−beta Signaling Pathway
PPAR Alpha Pathway TP53 Network Cell Cycle Nucleotide Metabolism Proteasome Degradation Translation Factors −0.4 0.0 0.4 logFC BR BRE 1.4 1.4 1.5 1.3 1.6 0.7 1.4 0.6 1.3 0.7 0.6 0.6 n.s n.s n.s n.s 2.E-02 7.E-03 9.E-05 8.E-05 3.E-05 1.E-06 3.E-18 7.E-21 0.03 0.02 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 WX-P-value FDR FC Pathway
group (FC = 1.05; Figures 3 and 4). Other downregulated pathways with high degree of normalization in BRE were “Fatty acid beta-oxidation,” “TCA cycle,” and “PPAR Alpha pathway” (Figures 3 and 4). Among the upregulated path-ways that were normalized in BRE we found “TGF − beta
Signaling Pathway,”42 “Circadian rhythm related genes,”
and “TP53 Network.” However, despite a general counter-acting effect of RE at the transcriptomic level, a number of bed rest-induced upregulated pathways were not normal-ized by the exercise countermeasure; “Translation Factors,” “Proteasome Degradation,” “Cell Cycle,” and “Nucleotide Metabolism” (Figures 3 and 4).
4
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DISCUSSION
This study provides unique information about the transcrip-tomic changes occurring in skeletal muscle during one of the longest bed rest campaigns ever performed. In comparison to shorter bed rest studies, the results indicate that the transcrip-tomic machinery continues to adapt throughout extended dis-use periods, and that high-intensity, low-volume RE, capable of offsetting unloading-induced muscle atrophy, neutralizes most but not all of the molecular changes induced by 84 days of bed rest. Thus, we reveal a skeletal muscle residual tran-scriptomic signature of unloading that is resilient to RE.
FIGURE 4 Representation of the continuous relationship between BR and BRE using FC-FC plot using the logFC of BR (x-axis) and logFC of BRE (y-axis) for genes related to (a) electron transport and oxidative phosphorylation, (b) proteasome, (c) PPAR-signaling, and (d) translation factors. Purple and green arrows indicate the direction of the transcript expression alterations in a specific sector induced by bed rest and bed rest plus exercise, respectively
BR + E Time SDHC NDUFB6 ATP5MC2 SURF1 NDUFV3 ATP5PB NDUFB8 COX15 ATP5IF1 ATP5F1C COX5A ATP5MC3 COX6B1 ATP5MC1 BR + E Time NEDD4 UBE2D1 PSMD1 UBE2B PSMD11 PSMD5 PSMD10 PSMD3 HLA−E UCHL3 PSMD7 PSMC3 PSMD4 BR + E Time FABP6 CYP27A1 FABP1 RXRG UCP1 CYP8B1 AQP7 CD36 PPARA FABP3 BR + E Time EIF4A2 EIF4H EIF3E EIF4B EIF5B EIF2AK2 EIF2AK3 EIF2S3 EIF2B1 EIF3B EIF5
The current data show that the biological perturbations in skeletal muscle after 84 days of bed rest are at least as
large, if not greater, than what has been described after 2115
or 60 days of bed rest.18,19 For example, pathways related to
mitochondria, energy metabolism, and structural components were downregulated, and those involved in the ubiquitin sys-tem upregulated, which is consistent with findings in
skele-tal muscle after short-10-15,17 and moderately long periods of
unloading.18,19 Similarly, we found a transcriptomic profile
indicating slow-to-fast fiber transition, a common event in
unloading studies.6,43-46 Thus, MYH1 and MYH8, myosin
isoforms much more abundant in fast-twitch fibers,47 were
highly upregulated after bed rest. Among the factors
regulat-ing fiber type composition, PPAR48 and MEF2,49 were
down-regulated with bed rest, which is in line with shorter bed rest
campaigns.15 Our data add Prox1 as a factor involved in the
unloading-induced fiber shifting. Prox1, which was downreg-ulated after 84-day of bed rest, is specifically expressed in
slow muscle fibers.38 This factor is an important component
of the molecular program protecting the slow fiber type and activates the NFAT pathway (a key regulator of slow muscle
fiber phenotype).38
Despite the similarities with shorter unloading studies, 84 days of bed rest also resulted in unique transcriptomic alterations not noted after shorter campaigns. Thus, in con-trast to the somewhat generalized idea that the majority of molecular alterations occur at the beginning of the unload-ing period, our data suggest that the muscle transcriptomic responses to unloading are ongoing and continue to adapt (and change) throughout extended periods of disuse. An in-triguing observation was that 84 days of bed rest induced al-terations in several genes and transcription factors involved in circadian rhythm regulation. Muscle activity and nutrient intake are known cues for the circadian rhythm regulation in
skeletal muscle.50,51 Given that diet and time of meals were
controlled for in the current study, and the observed differ-ences between bed rest with vs without exercise (see below), our results support the idea of a disuse-sensitive circadian
molecular clock in the skeletal muscle.52-54 These findings
add information from in vivo human muscle to past reports describing atypical expression of core clock
genes/transcrip-tion factors after muscle denervagenes/transcrip-tion in mice.55 The
Bmal1-CLOCK complex is the central modulator of the circadian rhythm system. In the current study, the antagonistic factors RORA and NR1D2 were both upregulated after long-term bed rest, which may be related to a myocellular effort to sta-bilize the regulatory feedback loop controlling Bmal1 expres-sion, and thus, decrease the impact of the lack of mechanical stimuli on circadian rhythms regulation. The implications of the unloading-induced circadian rhythm alterations reported here should not be overlooked, since the cell-autonomous skeletal muscle clocks have been shown to impact important pathways involved in human skeletal muscle remodeling, and
to be essential for proper insulin handling, lipic homeostasis,
and myokine secretion.56
Past studies have shown that increased levels of physical activity can induce differential isoform-specific expression
in skeletal muscle.57-58 Our exon usage analysis is one of
the first reports showing that genes associated with skele-tal muscle structural components and contractile machinery presented isoforms that responded to long-term disuse in an individual fashion. In the vast majority of the cases, however, the isoforms followed an expression pattern that was similar to that of the common gene, ie, if the gene was downregu-lated by bed rest, the different isoforms were downregudownregu-lated as well, albeit the magnitude of change differed among iso-forms. With the current knowledge, it is difficult to conclude if and how these splice changes are related to the observed skeletal muscle phenotype alterations. However, the finding that isoforms responded to long-term unloading in an in-dividual fashion may be relevant in future attempts to find putative targets and biomarkers for predicting the response of a particular countermeasure to muscle deconditioning, as
suggested for other diseases.59
RE-countermeasures are effective in preserving most of the muscle mass and function with prolonged bed rest, but whether this is associated with a complete or partial nor-malization of the transcriptomic signature, or due to an acti-vation of a different gene expression profile, was unknown. Our unsupervised analysis (ie, t-SNE) revealed that the over-all transcriptomic signature of prolonged bed rest was, to a relatively high degree, reversed by flywheel RE. Thus, the 3-min-per-week of contractile activity (4 sets × 7 reps em-ploying flywheel RE) offset the transcriptomic alterations re-lated to aerobic energy metabolism (eg, “Electron Transport Chain,” “Fatty Acid Beta-Oxidation,” “TCA Cycle,” “PPAR-signaling pathway”), which is further supported by the met-abolic adaptations at the enzymatic level reported from
the same bed rest intervention.21 Similarly, other pathways
important for skeletal muscle integrity were normalized by the exercise intervention, including “TP53 Network” and “TGF-beta Signaling Pathway.” While TGF-beta superfam-ily is associated with an inhibition of muscle regeneration
following injury,60 P53 can exacerbate the stress load upon
the muscle in situations of inactivity-induced atrophy.61 Our
data support the connection of these two pathways with a molecular environment favoring blunted muscle protein syn-thesis and an increase in atrophy-related factors in unloaded, non-injured human skeletal muscle. Interestingly, the bed rest-induced upregulation of “Circadian Rhythm Related Genes” was counteracted by the RE countermeasure em-ployed. This result supports the existence of muscle tension/ activation-specific circadian rhythm regulatory mechanisms (discussed above).
Despite the counteracting effects of RE, there was a group of genes that was resilient to RE (ie, they were upregulated
or downregulated to a similar extent in both conditions). Other studies analyzing different muscle groups and/or women during shorter bed rest periods have also suggested the existence of genes resilient to diverse exercise
counter-measures.18,19 Interestingly, the current analyses showed
that those genes that were upregulated by bed rest in the current study were less likely to be reversed by the exer-cise countermeasure than the downregulated transcripts. In addition, this group of genes had very little overlap with
transcriptomic changes after RE only,40,41 suggesting that
the residual signature was of an “unloading-specific” na-ture and independent of the particular exercise intervention conducted. It could be that the different muscle activity/ tension pattern of the RE protocol used (ie, high-intensity, low-volume), when compared with that required for the maintenance of an ambulatory position (ie, low-intensity, high-volume), could explain the inefficiency of the counter-measure employed to normalize the residual signature genes. In addition, other bed rest-induced changes, such as microenvironment and/or hemodynamics alterations could have contributed to the differential expression of the genes identified in the residual signature. When analyzed at a pathway level, several molecular pathways were upreg-ulated to a similar extent after bed rest with and without RE, constituting the pathway-level residual signature of bed rest; “Translation Factors,” “Proteasome Degradation,” “Cell Cycle,” and “Nucleotide Metabolism.” Altogether, these results suggest that, despite a rather successful rever-sal of the phenotypic alterations induced by long-term bed
rest (ie, muscle mass),1 the particular RE employed could
not fully counteract all of the transcriptomic changes. The clinical and/or functional impact of the residual signature needs to be examined in future studies.
In conclusion, this study provides the most comprehen-sive human skeletal muscle transcriptome profile to unload-ing to date, as well as delivers novel information about the reversal of transcriptomic changes through RE. We report that (a) besides a predictable differential expression of genes and pathways related to mitochondria, ubiquitin system, and skeletal muscle metabolism and structure, 84 days of bed rest altered other less-expected transcripts involved in, for example, circadian rhythms. This suggests that muscle tran-scriptomic modifications are ongoing throughout extended periods of disuse. (b) As little as 3 minutes per week of mus-cle activation through RE is enough to offset the majority of the bed rest-induced transcriptomic alterations. However, (c) there were transcripts that were resilient to this counter-measure, suggesting the presence of a residual signature of skeletal muscle disuse. Collectively, the current study paves the way for further exploration of skeletal muscle alterations to extreme disuse, and the potential, and limitations, of both current and new countermeasures employed to fight muscle deconditioning.
ACKNOWLEDGMENTS
The experimental part of this study (bed rest intervention) was supported by grants from the Swedish National Space Agency (SNSA), the European Space Agency (ESA), and the Swedish National Centee for Research in Sports (CIF) to PAT. The authors would like to thank BEA—the core facility for Bioinformatics and Expression Analysis service facility at Novum, Karolinska Institutet in Huddinge, for their help-ful contribution.
CONFLICT OF INTEREST
Rodrigo Fernandez-Gonzalo, Per A. Tesch, Tommy R. Lundberg, Björn A. Alkner, Eric Rullman, and Thomas Gustafsson declare they have no competing interests.
AUTHOR CONTRIBUTIONS
P. A. Tesch and B. A. Alkner designed and conducted the bed rest with/without exercise countermeasure intervention and collected the muscle biopsies. R. Fernandez-Gonzalo, T. Gustafsson, and E. Rullman designed the gene array ex-periments. E. Rullman performed the statistical analysis. E. Rullman, T. R. Lundberg, T. Gustafsson, and R. Fernandez-Gonzalo interpreted the results. R. Fernandez-Fernandez-Gonzalo, T. R. Lundberg, and T. Gustafsson drafted the manuscript. B. A. Alkner, P. A. Tesch, and E. Rullman read and provided feedback on the drafted manuscript. All authors read and ap-proved the submitted version.
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SUPPORTING INFORMATION
Additional supporting information may be found online in the Supporting Information section.
How to cite this article: Fernandez-Gonzalo R, Tesch PA, Lundberg TR, Alkner BA, Rullman E, Gustafsson T. Three months of bed rest induce a residual
transcriptomic signature resilient to resistance exercise countermeasures. The FASEB Journal. 2020;00:1–12.
