Exercise Induces Different Molecular Responses in Trained and Untrained Human Muscle : Medicine & Science in Sports & Exercise

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Exercise Induces Different Molecular Responses in Trained and Untrained Human Muscle


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Medicine & Science in Sports & Exercise 52(8):p 1679-1690, August 2020. | DOI: 10.1249/MSS.0000000000002310


Maintaining or increasing muscle mass and strength is associated with a reduced risk of mobility disability, cardiovascular disease, type 2 diabetes, and cancer (1). In this, strength training has a key role in muscular development and is a critical component of healthy aging. As skeletal muscle generally becomes more resistant to growth stimulus with age, which is accompanied by a gradual loss of muscle mass and strength (2), it is prompted that strength training should be initiated in early adulthood and subsequently maintained. This notion is exemplified by master athletes being found to have muscular fitness comparable with that of young adults (3). Importantly, it is also argued that if individuals have had a history of strength training before a period of less or no training, muscle mass regrows more rapidly, or to a greater extent, upon new training stimulus (4–6). Data indicate, in other words, that previously trained muscle is more sensitive to new stimuli or possesses a “memory.”

The process of muscle hypertrophy is driven by acute stimulation of transcriptional and translational processes in the muscle fiber after each resistance exercise bout. More specifically this relates to a mechanistic target of rapamycin complex 1 (mTORC1)-dependent stimulation of protein synthesis (7), as well as induced expression of genes related to muscle structure, myogenesis, protein turnover, extracellular matrix, and angiogenesis (8). During hypertrophy, the outcome efficiency and capacity of mRNA translation and gene transcription are also influenced by satellite cell-induced myonuclear addition (9), ribosomal biogenesis (10), and epigenetic modifications (4). With regard to the existence of a “muscle memory,” much attention has been directed to strength training-induced increases in myonuclear content, nuclei which are preserved during atrophy and may enable rapid hypertrophy upon reloading (11–13). However, current scientific evidence of such a memory is limited to animal models and has yet to be shown in humans (14).

Numerous studies have shown that continuous training has a clear effect on the degree of acute exercise-induced cell signaling responses, gene expression, and rate of protein synthesis after both strength and endurance type of exercise (5,15–22). Although most of these studies have demonstrated an overall attenuation in the acute molecular response, a few studies have shown that some molecular processes can be sensitized. The mechanisms underlying these altered acute responses after a period of training, and the question of whether these alterations are preserved after a period of detraining remains to be determined. However, epigenetic modifications may play a role. Seaborne et al. (4) recently showed that strength training-induced epigenetic modifications are sustained after 7 wk of detraining and could partially explain the augmented hypertrophic response upon reloading. By contrast, Lindholm et al. (23) found no endurance training-induced transcriptome differences between previously trained and untrained legs after a 40-wk detraining period.

Although the studies of Lindholm et al. (23) and Seaborne et al. (4) have provided important data regarding training-induced muscle memory in resting human skeletal muscle, no researchers have explored the potential of a muscle memory concerning acute exercise-induced gene expression and cell signaling response. Accordingly, in this study, young and completely untrained women and men underwent a 10-wk unilateral leg strength training program followed by a 20-wk detraining period. This period was followed by an acute strength training session involving both the previously trained and untrained (control) legs. Skeletal muscle biopsy samples were collected at rest and 1 h after exercise to determine both basal and exercise-induced gene expression, protein content, and phosphorylation status of proteins known to respond acutely to strength training stimuli. We hypothesized that the previously trained and untrained legs would show differences, indicating long-lasting qualitative changes in the molecular machinery regulating muscle adaptations to resistance exercise.



Nineteen healthy, inactive subjects (10 women and 9 men) who had never been engaged in any regular sport or physical activity volunteered to participate in this study. Their mean ± SD age was 25 ± 1 yr, mean weight was 71 ± 4 kg, and mean height was 175 ± 8 cm. The subjects were carefully informed about the experimental design and possible risks related to the project and signed a written consent form before entering the project. The study was approved by the Regional Ethics Committee of Stockholm, Sweden (DNR 2015/211-31/4) and was performed in accordance with the Declaration of Helsinki.

Experimental protocol

Figure 1 is a schematic illustration of the experimental design. Subjects underwent a 10-wk unilateral strength training period, followed by 20 wk of detraining, during which no training was allowed. Only the memory leg was trained during the unilateral training period. The exercises included were leg presses and leg extensions, and training usually took place three times per week. Both moderate (70% to 75% of one-repetition maximum [1RM]) and heavy loading (80% to 85% of 1RM) were performed in an undulating, periodized manner. During weeks 4 and 8, low-load, blood flow–restricted exercise was performed as well. The purpose of this strength training design was to maximize hypertrophy, satellite cell activation, and fusion with the aim of stimulating possible lasting effects in the trained leg. To ensure optimal protein intake and to stimulate muscle growth, subjects consumed 25 g of whey protein concentrate (One Whey; Fitnessguru Sweden AB, Stockholm, Sweden) immediately after each training session. A more detailed description of the training protocol was published by Psilander et al. (14).

Schematic illustration of the experimental protocol. Only one leg (the memory leg) was trained during the unilateral training period, whereas both legs were trained during the acute exercise session after the detraining period. A 1RM test was performed individually for each leg after the detraining period to ensure same relative load in the acute exercise session. Skeletal muscle biopsy samples from the vastus lateralis were taken before and 1 h after completion of the acute exercise session. Each exercise session consisted of three sets of leg presses, followed by three sets of leg extension at 75% of 1RM. In the acute exercise session, the legs were exercised one at a time, alternating between sets.

The detraining period was followed by a bilateral exercise session (three sets of leg presses and three sets of leg extension) performed at approximately 75% of 1RM until volitional failure. The legs were exercised one at a time, alternating between sets. A bilateral 1RM test was performed in the leg press and leg extension before the exercise session, and the relative load (75%) was calculated from this test. Details of the 1RM test protocol are available in an article by Psilander et al. (14). Biopsy samples were obtained from both legs before and approximately 1 h after exercise. The subjects reported to the laboratory between 8:30 am and 3:30 pm in a nonfasted state. Only water was allowed during the 1-h postexercise period.

Muscle biopsies

The muscle biopsies were collected under local anesthesia (2% Carbocain; AstraZeneca, Södertälje, Sweden) from the midpart of m. vastus lateralis, proximally separated by at least 3 cm. An incision was made in the skin and the fascia before the biopsies were obtained using a Weil–Blakesley conchotome. The typical yield was 50 to 100 mg of muscle tissue. The tissue obtained was rapidly frozen in liquid nitrogen and stored at −80°C. The frozen samples were thereafter freeze-dried; powdered; dissected free of blood, fat, and connective tissue; and stored at −80°C for later determination of DNA/mRNA content and immunoblotting.

RNA extraction and cDNA synthesis

Total RNA was extracted from approximately 3 mg of freeze-dried skeletal muscle tissue with the TRIzol® (Invitrogen) method. Briefly, the skeletal muscle sample was homogenized in TRIzol with a bead beater and subsequently mixed with chloroform. After centrifugation, the aqueous phase was mixed with an equal volume of isopropanol to cause RNA precipitation. After centrifugation, the RNA pellet was washed in 75% ethanol, air-dried, and resuspended in ultrapure RNA water. To completely dissolve the RNA, the pellet was incubated at 55°C for 10 min, and concentration was subsequently measured on a NanoDrop Spectrophotometer. One microgram of RNA was used for cDNA conversion with the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA) in a total volume of 20 μL, in accordance with the manufacturer’s specifications.

Gene expression

Quantitative real-time polymerase chain reaction (PCR) was performed for gene expression analysis of ABRA, ANGPT2, ANGPTL2, AXIN1, FBXO32, MSTN, MYF6, MYOD1, MYOG, PPARGC1A-exon 1a, PPARGC1A-exon 1b, PPARGC1A total (PGC1α), SETD3, SPRYD7, TGFB1, TRAF1, TRIM63, and UBR5. β2-Microglobulin was used as a housekeeping control, and expression levels were calculated with the 2-ΔΔCT method (24). All samples were run in duplicates on a C1000 Touch thermal cycler (Bio-Rad Laboratories, Richmond, CA) using the SsoAdvanced Universal SYBR Green Supermix (model 1725272; Bio-Rad Laboratories). PCR primers and assays were synthesized by Eurofins Genomics (Luxembourg), Sigma-Aldrich (St. Louis, MO), and Qiagen (Hilden, Germany). Primer sequences and assay information are listed in Supplemental Table 1 (see Appendix, Supplemental Digital Content, Primer sequences and melt curves, https://links.lww.com/MSS/B939).

Methylation analysis

The Gentra Puregene DNA purification kit (Qiagen, no. 158667) with Proteinase K (Qiagen, no. 158918) and RNAse A solution (Qiagen, no. 158922) was used to extract genomic DNA from the freeze-dried skeletal muscle by bead homogenization. The EpiTect Fast DNA Bisulfite kit (Qiagen, no. 59824) was used to perform bisulfite transformation with 500 μg of genomic DNA as starting material. The PyroMark PCR kit (Qiagen, no. 978703) with 10 ng of bisulfite-transformed DNA was used to amplify the transformed DNA. PCR primers were synthesized by Eurofins Genomics (see Supplemental Table 2, Appendix, Supplemental Digital Content, Primer sequences and melt curves, https://links.lww.com/MSS/B939). Assays were designed in the genomic environment of the PGC1α-ex1a with the selected region based on the H3K4me3 mark annotation of the UCSC genome browser (GRCh37/hg19 assembly). Pyrosequencing was performed with the PyroMark Q96 ID device (Qiagen), PyroMark Gold Q96 pyrosequencing reagents (Qiagen, no. 972804), and sequencing primers synthesized by Eurofins Genomics (see Supplemental Table 2, Appendix, Supplemental Digital Content, Primer sequences and melt curves, https://links.lww.com/MSS/B939). For bias control, bisulfite-transformed control DNA from the EpiTect PCR Control DNA Set (Qiagen no. 59695) was used. CpG pyrosequencing was analyzed with PyroMark Q96 software (Qiagen).

Protein extraction and Western blot

Lyophilized muscle samples (approximately 3 mg) free from blood and connective tissue were homogenized by a Bullet Blender (Next Advance, Troy, NY) in ice-cold buffer (100 μL⋅mg−1 dry weight) containing 2 mM of HEPES buffer (pH 7.4), 1 mM of EDTA, 5 mM of EGTA, 10 mM of MgCl2, 50 mM of β-glycerophosphate, 1% Triton X-100, 1 mM of Na3VO4, 2 mM of dithiothreitol, 1% phosphatase inhibitor cocktail (Sigma P-2850), and 1% (v/v) Halt Protease Inhibitor Cocktail (Thermo Scientific, Rockford, IL). After homogenization, the samples were rotated for 30 min at 4°C and subsequently cleared from myofibrillar and connective tissue debris by centrifugation at 10,000g for 10 min at 4°C, and the resulting supernatant was collected.

Protein concentration of the supernatants was determined in aliquots diluted 1:10 in distilled water with the Pierce™ 660 nm protein assay (Thermo Fisher Scientific). Samples were diluted in 4× Laemmli sample buffer (Bio-Rad Laboratories) and homogenizing buffer to obtain a final protein concentration of 1.25 μg⋅μL−1. All samples were then heated at 95°C for 5 min to denature the proteins and subsequently kept at −20°C until further separation in SDS–PAGE.

For protein separation, 18.75 μg of protein from each sample was loaded on 26-well Criterion TGX gradient gels (4% to 20% acrylamide; Bio-Rad Laboratories), and electrophoresis was performed on ice at 300 V for 30 min. Next, gels were equilibrated in transfer buffer (25 mM Tris base, 192 mM glycine, and 10% methanol) for 30 min at 4°C, after which proteins were transferred to polyvinylidene fluoride membranes (Bio-Rad Laboratories) at a constant current of 300 mA for 3 h at 4°C. To confirm equal loading and transfer, the membranes were stained with MemCode™ Reversible Protein Stain Kit (Thermo Fisher Scientific). For each target proteins, all samples from each subject were loaded on the same gel, and gels for all subjects were run simultaneously.

Blocking of membranes was performed for 1 h at room temperature in Tris-buffered saline (TBS; 20 mM of Tris base and 137 mM of NaCl; pH 7.6) containing 5% nonfat dry milk and followed by overnight incubation with commercially available primary antibodies diluted in TBS supplemented with 0.1% Tween-20 containing 2.5% nonfat dry milk (TBS-TM). Membranes were washed free from primary antibody with TBS-TM and then incubated for 1 h at room temperature with secondary HRP-conjugated antibodies. Next, the membranes were washed with TBS-TM (twice for 1 min, three times for 10 min), followed by four washes for 5 min with TBS only. Finally, to visualize the target proteins, SuperSignal™ West Femto Chemiluminescent Substrate (Thermo Fisher Scientific) was applied to the membranes, and a ChemiDoc™ XRS molecular imaging system was used for detection. The detected bands were quantified using the contour tool in the Quantity One® version 4.6.3 software (Bio-Rad Laboratories).

Before blocking, membranes from each gel were cut in strips for each target protein and assembled. Accordingly, all samples were exposed to the same blotting conditions. After visualization, the membranes were stripped of the phosphospecific antibodies by Restore Western Blot Stripping Buffer (Thermo Fisher Scientific) for 30 min at 37°C, after which the membranes were washed and reprobed with primary antibodies for each respective total protein, as described previously. All phosphoproteins were normalized to their corresponding total protein. For MuRF-1, SPRYD7, GAPDH, COX IV, and rpS6 values were normalized against the total protein stain obtained with the MemCode™ kit.

For immunoblotting, primary antibodies against mTOR (Ser2448, no. 2971; total, no. 2983), S6K1 (Thr389, no. 9234; total, no. 2708), 4E-BP1 (Ser65, no. 9456; total, no. 9644), eEF2 (Thr56, no. 2331; total, no. 2332), AMPK (Thr172, no. 4188; total, no. 2532), S6 (Ser235/236, no. 2211; total, no. 2217), COX IV (no. 4850), and GAPDH (no. 5174) were purchased from Cell Signaling Technology (Beverly, MA). Primary antibody against 4E-BP1Thr46 (no. sc-271947), MuRF-1 (no. sc-32920), and SPRYD7 (no. sc-514533) antibody was purchased from Santa Cruz Biotechnology (Heidelberg, Germany).

All primary antibodies were diluted 1:1000 except for phospho-eEF2, COX IV, GAPDH, and S6 total, which were diluted 1:2000, and 4E-BP1Thr46, which was diluted 1:200. Secondary antirabbit (no. 7074; 1:10,000) and secondary antimouse (no. 7076; 1:10,000) were purchased from Cell Signaling Technology.

Statistical analysis

Data are presented as mean ± SEM. Statistics for gene expression, as well as for protein content and phosphorylation, were calculated by repeated-measures ANOVA together with Fisher’s LSD post hoc test and Bonferroni’s multiple comparison test on group level (control, N = 19; memory, N = 19), as well as on males (n = 9) and females (n = 10) separated using Statistica 13.3 (TIBCO Software, Inc.). Statistics for methylation analysis was calculated by two-way ANOVA with Prism 7.05 (GraphPad, San Diego, CA). Statistical significance was determined at P < 0.05.


1RM test and loading during the exercise session

The memory leg was significantly stronger than the control leg after 20 wk of detraining in both the leg press (126 ± 10 vs 98 ± 9 kg, respectively; P < 0.05) and the leg extension (45 ± 3 vs 41 ± 3 kg, respectively; P < 0.05) exercise. There were however no differences between legs in mean muscle fiber cross-sectional area (CSA) at this stage that contributed to the difference in strength, memory leg 4385 μm2 (range 2478–6187), and control leg 4237 μm2 (range 2997–6235), see Psilander et al. (14) for details. The absolute load used during the exercise session was therefore higher for the memory leg than for the control leg (94 ± 8 vs 74 ± 7 kg, respectively, for the leg press and 34 ± 2 vs 31 ± 2 kg, respectively, for the leg extension; P < 0.05). The average number of repetitions performed during the exercise session was similar for the memory leg (10.5 ± 0.3 repetitions) and control leg (10.7 ± 0.2 repetitions) in the leg press exercise. However, a small difference between the legs was observed for the leg extension exercise (9.6 ± 0.4 repetitions for the memory leg and 9.0 ± 0.4 repetitions for the control leg; P < 0.05).

Gene expression

Total expression of PGC1α mRNA was 18% lower in the memory leg at baseline and decreased significantly after exercise only in the control leg (P < 0.05 for time and leg interaction; Fig. 2A). These effects on total PGC1α at group level were primarily mediated by the male subjects, whereas the female subjects had similar levels at baseline and exhibited no change after exercise (Fig. 2B). PGC1α-ex1a mRNA was affected by exercise only in the memory leg and increased by approximately 60% at group level (P < 0.05 for time and leg interaction; Fig. 2C). In sex-specific gene expression analysis, PGC1α-ex1a expression was increased only in the male subjects (Fig. 2D).

Effect of the resistance exercise session on PGC1α-total (A, B), PGC1α-ex1a (C, D), SPRYD7 (E, F), and ANGPTL2 (G, H) mRNA content in the vastus lateralis muscle before (Pre) and 1 h after (Post) exercise. Control, leg without a history of strength training; Memory, leg that had previously undergone strength training for 10 wk. N = 19. Values are reported as mean ± SEM. aDifference between preexercise and postexercise values was significant, P < 0.05. bDifference between memory leg and control leg was significant, P < 0.05, at the indicated time point. Letters above lines indicate a main effect in the ANOVA, and letters above single bars indicate an interaction between leg and time.

SPRYD7 mRNA was unaffected by exercise in the memory leg but decreased by approximately 35% in the control leg and was expressed at lower levels in the memory leg at baseline (P < 0.05 for time and leg interaction; Fig. 2E). The expression of ANGPTL2 mRNA increased after exercise in both legs (P < 0.05 for time; Fig. 2G), but sex-specific analysis demonstrated this increase only in the female subjects (P < 0.05 for time; Fig. 2H). Moreover, the male subjects exhibited a 13% to 32% higher expression of ANGPTL2 mRNA in the memory leg, independent of time (P < 0.05 for leg; Fig. 2H).

MYOG mRNA was 15%–65% higher in the memory leg independent of time, with the expression also being reduced after exercise in both legs (P < 0.05 for time and leg; Fig. 3A). The expression of MYOD1 mRNA was not different between legs and was not altered by exercise on group basis (Fig. 3C). However, a decrease in MYOD1 mRNA content was noted among the male subjects after exercise in the control leg only; the expression in the control leg was also significantly different from that in the memory leg at that time point (P < 0.05 for time and leg interaction; Fig. 3D).

Effect of the resistance exercise session on MYOG (A, B), MYOD1 (C, D), FBOX32 (E, F), and SETD3 (G, H) mRNA content in the vastus lateralis muscle before (Pre) and 1 h after (Post) exercise. Control, leg without a history of strength training; Memory, leg that had previously undergone strength training for 10 wk. N = 19. Values are reported as mean ± SEM. aDifference between preexercise and postexercise values was significant, P < 0.05. bDifference between memory leg and control leg was significant P < 0.05, at the indicated time point. Letters above lines indicate a main effect in the ANOVA, and letters above single bars indicate an interaction between leg and time.

At group level, the mRNA content of FBXO32 was unaffected by exercise and expressed to a similar degree in both legs (Fig. 3E). However, in male subjects only, FBXO32 mRNA expression was 30% lower in the memory leg at baseline and decreased by 37% in the control leg after exercise (P < 0.05 for time and leg interaction; Fig. 3F), with no differences noted in the female subjects. The expression pattern of SETD3 mRNA was similar to that of FBXO32 mRNA, with no differences noted a group level but a similar interaction between time and leg for the male subjects (Fig. 3G and H). The mRNA content of ABRA, AXIN1, MYF6, PGC1α-ex1b, TGFB1, and TRIM63 increased acutely after exercise and, to a similar extent, in both legs (P < 0.05 for time; Table 1), whereas that of UBR5, TRAF1, and MSTN showed no changes in all biopsy samples.

Genes with similar mRNA expression in both legs (no detectable memory effect).

Methylation of key promotor regions of the PGC1α-ex1a isoform

As stated previously, there was a significant difference in the expression level of the PGC1α-ex1a isoform between the memory leg (60%) and the control leg (no increase). A bisulfite methylation assay was performed to investigate whether this could be explained by differences in the methylation level of key promotor regions of the PGC1α-ex1a isoform. Seven CpG sites located in association with exon 1a were included in the analysis; methylation levels ranged from 2.2% to 18.6%. Statistical testing across time points for each site showed no significant difference between methylation of target site in control and memory legs.

Protein phosphorylation and content

The phosphorylation of 4E-BP1Thr46 was reduced by 13% in the control leg after exercise; the phosphorylation was 18% higher in the memory leg at that time point (P < 0.05 for time and leg interaction; Fig. 4A). These effects at group level were present in the male subjects, whereas the female subjects exhibited a 15% increase in phosphorylation in the memory leg only (P < 0.05 for time and leg interaction; Fig. 4B). The phosphorylation of 4E-BP1Ser65 exhibited a similar pattern to that of 4E-BP1Thr46 without an exercise-induced increase in the memory leg for the women (data not shown). The phosphorylation of mTORSer22448, S6K1Thr389, and S6Ser235/236 increased by approximately 30%, 6-fold, 15-fold, and 15-fold, respectively, after exercise in both the control and memory legs (P < 0.05 for time; Table 2), with no differences in response between the two legs.

Effect of the resistance exercise session on phosphorylation of 4E-BP1Thr46 (A, B), eEF2Thr56 (C, D), and AMPKThr172 (E, F) as well as SPRYD7 (G, H) protein content in the vastus lateralis muscle before and 1 h after exercise. Control, leg without a history of strength training; Memory, leg that had previously undergone strength training for 10 wk. N = 19. Values are reported as mean ± SEM. aDifference between preexercise and postexercise values was significant, P < 0.05. bDifference between memory leg and control leg was significant, P < 0.05, at the indicated time point. Letters above lines indicate a main effect in the analysis of variance; letters over single bars indicate an interaction between leg and time. I, A panel of representative blots from both male and female subjects for the protein data (phosphorylated, total, and loading control) presented.
Proteins with similar content and phosphorylation in both legs (no detectable memory effect).

The phosphorylation of eEF2Thr56 was 16% to 19% lower in the control leg, regardless of time point (P < 0.05 for leg; Fig. 4C), and after exercise, phosphorylation was reduced by approximately 40% in both legs (P < 0.05 for time; Fig. 4C). These effects were apparent in both male and female subjects (Fig. 4D). In conformity with eEF2Thr56, the phosphorylation of AMPKThr172 was 10% to 17% lower in the control leg at both time points (P < 0.05 for leg; Fig. 4E) but increased to a similar extent in both legs as a result of the exercise (P < 0.05 for time). The sex-specific analysis revealed a difference between legs only in the women (P < 0.05 for leg; Fig. 4E), with insufficient power to detect an increase over time.

Total protein levels of SPRYD7 were similar in both legs and not altered by exercise at group level (Fig. 4G), but the male subjects exhibited 23% to 57% higher SPRYD7 protein levels in the memory leg (P < 0.05 for leg; Fig. 4G). Total protein levels of MuRF-1 were increased after exercise, detected as a main effect of time in the statistical analysis, with a 10% increase in the control leg and a 3% increase in the memory leg (P < 0.05 for time; Table 2). Protein levels of GAPDH and COX IV (Table 2), as well as total protein content of the proteins probed for phosphorylation status, were not altered by exercise and did not differ between legs at baseline before exercise.


In this study, using a model in which previously strength-trained and untrained muscles were subjected to an acute bout of resistance exercise, we obtained novel data showing that basal and exercise-induced specific gene expression and cell signaling are modified by previous training history. More specifically, we showed that the previously trained memory leg had lower preexercise levels of total PGC1α mRNA and that exercise-induced increases in PGC1α-ex1a transcripts occurred only in that leg. Moreover, the postexercise phosphorylation of 4E-BP1Thr46 and 4E-BP1Ser65 was higher in the memory leg, as was the overall phosphorylation of AMPKThr172 and eEF2Thr56. We also found that previous training history modified both basal and exercise-induced mRNA expression of the novel gene SPRYD7. Finally, we show that differences in mRNA expression between the memory and the control legs were apparent for ANGPTL2, MYOG, MYOD1, FBXO32, and SETD3. Overall, our data suggest that the regulation of transcriptional and translational processes in skeletal muscle in relation to exercise can be both reduced and augmented by previous training history. The alteration, which was both suppressive and stimulatory, conforms to findings in previous research that a continuous training period induces a diverse adaptive response in related molecular processes (5,15–20), which emphasizes the necessity of gene- and protein-specific evaluations with regard to training status/history.

The participants in this study had no previous experience in sports or physical activity ensuring that the untrained leg served as a true training naïve and intraindividual control. The 20-wk detraining period ensured proper reversal of previous training-induced hypertrophy, and the unilateral training model enabled control of engagement in any spontaneous physical activities during detraining. The unilateral training model also enabled control of confounding factors such as genetics, environmental stress, and diet as well as acute exercise-induced systemic factors such as hormones, myokines, and lactate levels. Observed differences between the control and memory legs are thus probably attributable to previous training per se. Moreover, it is worth noticing that satellite cell and myonuclear content in these subjects did not change during the initial training period or during detraining (14). There were also no differences in muscle fiber CSA between the legs at this point, and we could not find any correlations between gene expression or protein content/phosphorylation and muscle fiber CSA. Therefore, observed differences could not be ascribed to altered nuclei number but were more likely to result from sustained epigenetic modifications, acetylase/deacetylase activity, phosphorylase/dephosphorylase activity, or other preserved structural adaptations.

Continuous strength training has been shown to alter both resting and exercise-induced rates of protein synthesis. Although previous findings are somewhat disparate, taken together, they suggest that the basal synthesis rate is increased, but exercise-induced synthesis magnitude is reduced with improved training status (15,21,22). Whether and how rapidly detraining alters this response is unknown, but it is evident that physical inactivity or muscle disuse rapidly reduces muscle protein synthesis rates (25,26). With regard to mTORC1-signaling, Wilkinson et al. (15) found no changes in basal or exercise-induced mTORC1-signaling after 10 wk of strength training. By contrast, Ogasawara et al. (5) demonstrated that mTORC1-signaling is attenuated during chronic strength training but sensitized after subsequent detraining in rat skeletal muscle. As in previous data (27–29), mTORC1-signaling was clearly induced by the acute resistance exercise bout in this study, but, interestingly, the postexercise phosphorylation of 4E-BP1Thr46 and 4E-BP1Ser65 was higher in the memory leg. The fact that no differences between the control and memory legs was noted for mTORSer2448, S6K1Thr389, and S6Ser235/236 suggests that upstream stimulatory mechanisms did not differ between the legs and that differences in 4E-BP1Thr46 and 4E-BP1Ser65phosphorylation between the legs could be attributed to a process such as modified phosphatase activity (30).

Moreover, we found higher preexercise and postexercise phosphorylation status of eEF2Thr56 and AMPKThr172 in the memory leg, which could indicate a general reduction in translational capacity (31,32). This is, however, unlikely or has only minor physiological relevance, inasmuch as muscle mass and fiber size did not differ between the legs after the detraining period or after the subsequent 5 wk of reloading in these subjects (14). One obvious potential explanation for the observed differences in the phosphorylation of AMPK, eEF2, and also 4E-BP1 for that matter is altered specific total protein content. However, no differences in total protein content between legs were noted for any of the analyzed signaling proteins. It is therefore possible, although speculative, that differences in eEF2Thr56 and AMPKThr172 between the legs are attributable to sustained training-induced alterations in upstream kinase activity or phosphatase action.

Of note was that higher levels of AMPKThr172 in the memory leg were observed only in the female subjects. Women have lower resting levels of AMPKThr172 than do men (33), which is ascribed to the higher type II fiber content in men, inasmuch as resting AMPKThr172 has been shown to be higher in type II fibers than that in type I fibers and has also been shown to increase to a similar extent in both fiber types after a short intensified training period (34). In this study, although the female subjects had a lower proportion of type II fibers than did the male subjects (data not shown), there were no differences in fiber-type composition between legs. This argues that the higher AMPKThr172 phosphorylation in the memory leg is attributable not to fiber-type differences per se but rather to a training-induced elevation that is preserved in a sex-specific manner.

We found quite variable effects with regard to PGC1α transcription; total levels were lower in the memory leg at baseline, and an exercise-induced reduction was noted in the control leg. At the same time, the PGC1α-ex1a isoform was induced after exercise only in the memory leg, and its levels also tended to be lower in that leg at baseline. To explore potential mechanisms for the differences between legs, we performed a targeted epigenetic analysis of methylated CpG sites within the PGC1α proximal promoter region, which is associated with exon 1a, and found no differences in any of the seven analyzed CpG sites (three located in the immediate transcription start site [TSS] and coding sequence region, three located upstream, and one downstream of TSS) that exhibited sufficient methodological quality. However, this does not contradict the idea that the training history-induced differences in PGC1α transcription result from epigenetics modifications, inasmuch as there are a total of 49 CpG sites related to exon 1a (between 1300 bp upstream and 1500 bp downstream of the TSS of exon 1a; selection based on the H3K4me3 annotation mark track from the UCSC Genome Browser GRCh37/hg19 assembly), and the possibility of histone modifications must also be acknowledged.

The finding that exercise increased specific isoforms in the memory leg, without increasing total PGC1α mRNA, was somewhat unexpected because the unspecific primers used in this study have previously been used to detect robust increases after both resistance and endurance exercise (35,36). One apparent explanation for this is that the 1-h postexercise biopsy might have been too early to detect significant increases. Furthermore, exon 1a and especially exon 1b transcripts are only a fraction of total PGC1α transcripts and that increased expression of one specific isoform could be masked by unaltered or reduced expression of other isoforms in the evaluation of total PGC1α.

On the basis of the data of Seaborne et al. (4), we performed a targeted gene expression analysis of TRAF1, AXIN1, SETD3, and UBR5. The first two genes were reported to be hypomethylated with induced expression after loading, an effect that was preserved after detraining. We found no differences in the expression of TRAF1 and AXIN1 between the control and the memory legs at any time point, but we did detect an acute increase after exercise in both legs. It remains a possibility that our initial loading period did not sufficiently alter TRAF1 and AXIN1 expression, but this seems less likely as the first training period induced significant hypertrophy, and an acute increase in expression was confirmed upon reloading. It is thus possible that a detraining period 13 wk longer than what we used might have reversed potential initial changes in AXIN1 and TRAF1 expression. Furthermore, Seaborne et al. reported that UBR5 and SETD3 hypomethylation and gene expression were increased after loading, reversed after detraining, and then elevated in an augmented manner upon reloading, which indicates the existence of an epigenetic memory in these genes. We found no effects on UBR5 expression, and instead of an augmented effect of training on SETD3, its expression in the memory leg was lower before exercise, and an attenuating effect of exercise was observed in the control leg in the male subjects. In C2C12 cells, SETD3, together with MYOD1, has been reported to control the expression of MYOG (37). Of interest was that we observed reduced expression of all these genes after exercise in the control leg, as well as different expression levels between the control and memory legs; this indicates that there are training history-induced differences in myogenic capacity between the legs.

Although no “muscle memory” effects were noted for the E3 ligase UBR5, we found lower basal expression of FBXO32 (the protein MAFbx) in the memory leg in the male subjects, and only the control leg displayed increased expression after exercise. We also found strong indications that TRIM63 (the protein MuRF-1) had lower basal expression in the memory leg (P = 0.07 for leg and time interaction in the ANOVA), and 16 of the 19 subjects exhibited lower TRIM63 expression in the memory leg than that in the control at baseline. Baehr et al. (38) showed that TRIM63 and FBXO32 mRNA expression increases early during functional overload in mice and that the expression then decreases when hypertrophy becomes pronounced. These data do not conform to those of Léger et al. (39), which in human skeletal muscle showed a pronounced increase in both TRIM63 and FBXO32 mRNA after 8 wk of strength training, which subsequently was completely reversed after a detraining period. In our study, we observed more than just a reversed expression after detraining, inasmuch as the memory leg displayed lower TRIM63 and FBXO32 mRNA levels than did the control leg. Together, our data indicate that training-induced adaptations in the ubiquitin–proteasome pathway could be preserved after detraining.

From a training memory perspective, notable effects were detected for the expression of the novel gene SPRYD7. SPRYD7 (chronic lymphocytic leukemia deletion region gene 6 protein [CLLD6]) is a conserved gene enriched in skeletal muscle tissue (40) and was therefore chosen as novel candidate gene that has not been investigated in skeletal muscle in association to exercise before. The function of SPRYD7 is currently unknown, but according to a genomewide association study, it is linked to body mass (41). We found that the mRNA expression of SPRYD7 was lower in the memory leg at baseline and was reduced after exercise only in the control leg. Although protein levels of SPRYD7 did not change acutely after exercise, the lower mRNA levels in the memory leg coincided with higher protein levels in the male subjects (P = 0.09 for leg at group level, P = 0.01 for leg in male subjects only). It is therefore possible that the higher protein levels in the memory leg resulted in reduced mRNA expression in a negative feedback manner. These findings warrant further investigation to determine the potential role of SPRYD7 in muscle adaptations to strength training.

This study had a few limitations. First, experiments were not performed in conditions of overnight fasting and were performed during different times of day (approximately 8:00 am to 3:00 pm). This was because all 19 subjects underwent the training study during the same weekly period, and we could not logistically fit 19 acute session in a time-standardized manner within a limited time frame. For nutrition, we know that the phosphorylation of both S6K1 and S6 is very sensitive to nutritional (amino acid) stimuli, and the basal phosphorylation of these proteins was in general very low or barely detectable, which indicates that it was influenced little by prior nutrient intake. The unilateral leg design in which subjects are their own control also reduced the potential confounding influence of nutrition, hormone levels, and circadian rhythm. Furthermore, as the memory leg had preserved some of its initial strength gains despite 20 wk of detraining and reversal of hypertrophy (the memory leg was approximately 10% stronger than the control leg), there was a difference is absolute but not relative load during the acute resistance exercise session. Finally, we are limited by the single postexercise biopsy that was collected 1 h into recovery. It is reasonable to assume that we missed some effects on protein phosphorylation and gene expression that may have peaked earlier or later during recovery. One or two additional biopsies, enabling a time course evaluation, would have been of great benefit for the interpretation. Nonetheless, we did find exercise-induced changes for the majority of genes and proteins analyzed.

In summary, we demonstrated that both basal and exercise-induced gene expression and cell signaling that are important for muscle adaptations to strength training can be altered by previous training history and that some of the changes seem to be sex dependent. We found training history–sensitive factors relating to translation initiation/elongation, myogenesis, oxidative metabolism, angiogenesis, and ubiquitin–proteasome pathway. It is difficult to conclude whether the effect of training history represents a general augmentation or reduction, inasmuch as the genes and proteins studied exhibited both a sensitized and repressed response. This notion is supported by previous data showing that molecular processes in trained muscle are both upregulated and downregulated and emphasizes that the effect of training history must be evaluated in a gene- and protein-specific manner. Altogether, our results indicate that some of the molecular hallmarks of strength-trained muscle can be preserved after 20 wk of detraining. The practical relevance of these findings, as well as the molecular mechanisms explaining the sustained alterations, clearly warrants further investigation.

The authors thank Sebastian Edman, M.Sc., for his help in carefully dissecting the skeletal muscle biopsies. This project has been funded by grants to Dr. Psilander from the Swedish National Centre for Research in Sports (no. 2016-0134) and The Swedish School of Sport and Health Sciences. Dr. Moberg is funded through an Early Career Research Fellowship from the Swedish National Centre for Research in Sports (no. D2017-0012).

The authors declare that the results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation, and the results of the present study do not constitute endorsement by the American College of Sports Medicine. The authors declare no conflict of interest.


1. McLeod M, Breen L, Hamilton DL, Philp A. Live strong and prosper: the importance of skeletal muscle strength for healthy ageing. Biogerontology. 2016;17(3):497–510.
2. Burd NA, Gorissen SH, van Loon LJ. Anabolic resistance of muscle protein synthesis with aging. Exerc Sport Sci Rev. 2013;41(3):169–73.
3. McKendry J, Breen L, Shad BJ, Greig CA. Muscle morphology and performance in master athletes: a systematic review and meta-analyses. Ageing Res Rev. 2018;45:62–82.
4. Seaborne RA, Strauss J, Cocks M, et al. Human skeletal muscle possesses an epigenetic memory of hypertrophy. Sci Rep. 2018;8(1):1898.
5. Ogasawara R, Kobayashi K, Tsutaki A, et al. mTOR signaling response to resistance exercise is altered by chronic resistance training and detraining in skeletal muscle. J Appl Physiol (1985). 2013;114(7):934–40.
6. Staron RS, Leonardi MJ, Karapondo DL, et al. Strength and skeletal muscle adaptations in heavy-resistance-trained women after detraining and retraining. J Appl Physiol (1985). 1991;70(2):631–40.
7. Goodman CA, Frey JW, Mabrey DM, et al. The role of skeletal muscle mTOR in the regulation of mechanical load-induced growth. J Physiol. 2011;589(Pt 22):5485–501.
8. Liu D, Sartor MA, Nader GA, et al. Skeletal muscle gene expression in response to resistance exercise: sex specific regulation. BMC Genomics. 2010;11:659.
9. Adams GR. Satellite cell proliferation and skeletal muscle hypertrophy. Appl Physiol Nutr Metab. 2006;31(6):782–90.
10. Stec MJ, Kelly NA, Many GM, Windham ST, Tuggle SC, Bamman MM. Ribosome biogenesis may augment resistance training-induced myofiber hypertrophy and is required for myotube growth in vitro. Am J Physiol Endocrinol Metab. 2016;310(8):E652–e61.
11. Bruusgaard JC, Johansen IB, Egner IM, Rana ZA, Gundersen K. Myonuclei acquired by overload exercise precede hypertrophy and are not lost on detraining. Proc Natl Acad Sci U S A. 2010;107(34):15111–6.
12. Egner IM, Bruusgaard JC, Eftestol E, Gundersen K. A cellular memory mechanism aids overload hypertrophy in muscle long after an episodic exposure to anabolic steroids. J Physiol. 2013;591(24):6221–30.
13. Lee H, Kim K, Kim B, et al. A cellular mechanism of muscle memory facilitates mitochondrial remodelling following resistance training. J Physiol. 2018;596(18):4413–26.
14. Psilander N, Eftestol E, Cumming KT, et al. Effects of training, detraining, and retraining on strength, hypertrophy, and myonuclear number in human skeletal muscle. J Appl Physiol (1985). 2019;126(6):1636–45.
15. Wilkinson SB, Phillips SM, Atherton PJ, et al. Differential effects of resistance and endurance exercise in the fed state on signalling molecule phosphorylation and protein synthesis in human muscle. J Physiol. 2008;586(15):3701–17.
16. Pilegaard H, Saltin B, Neufer PD. Exercise induces transient transcriptional activation of the PGC-1alpha gene in human skeletal muscle. J Physiol. 2003;546(Pt 3):851–8.
17. Perry CG, Lally J, Holloway GP, Heigenhauser GJ, Bonen A, Spriet LL. Repeated transient mRNA bursts precede increases in transcriptional and mitochondrial proteins during training in human skeletal muscle. J Physiol. 2010;588(Pt 23):4795–810.
18. Nader GA, von Walden F, Liu C, et al. Resistance exercise training modulates acute gene expression during human skeletal muscle hypertrophy. J Appl Physiol (1985). 2014;116(6):693–702.
19. Gordon PM, Liu D, Sartor MA, et al. Resistance exercise training influences skeletal muscle immune activation: a microarray analysis. J Appl Physiol (1985). 2012;112(3):443–53.
20. Egan B, ’Connor PL, Zierath JR, O’Gorman DJ. Time course analysis reveals gene-specific transcript and protein kinetics of adaptation to short-term aerobic exercise training in human skeletal muscle. PLoS One. 2013;8(9):e74098.
21. Phillips SM, Parise G, Roy BD, Tipton KD, Wolfe RR, Tamopolsky MA. Resistance-training-induced adaptations in skeletal muscle protein turnover in the fed state. Can J Physiol Pharmacol. 2002;80(11):1045–53.
22. Kim PL, Staron RS, Phillips SM. Fasted-state skeletal muscle protein synthesis after resistance exercise is altered with training. J Physiol. 2005;568(Pt 1):283–90.
23. Lindholm ME, Giacomello S, Werne Solnestam B, et al. The impact of endurance training on human skeletal muscle memory, global isoform expression and novel transcripts. PLoS Genet. 2016;12(9):e1006294.
24. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method. Methods. 2001;25(4):402–8.
25. Ferrando AA, Tipton KD, Bamman MM, Wolfe RR. Resistance exercise maintains skeletal muscle protein synthesis during bed rest. J Appl Physiol (1985). 1997;82(3):807–10.
26. McGlory C, von Allmen MT, Stokes T, et al. Failed recovery of glycemic control and myofibrillar protein synthesis with 2 wk of physical inactivity in overweight, prediabetic older adults. J Gerontol A Biol Sci Med Sci. 2018;73(8):1070–7.
27. Moberg M, Apro W, Ekblom B, van Hall G, Holmberg HC, Blomstrand E. Activation of mTORC1 by leucine is potentiated by branched-chain amino acids and even more so by essential amino acids following resistance exercise. Am J Physiol Cell Physiol. 2016;310(11):C874–84.
28. Apró W, Moberg M, Hamilton DL, et al. Leucine does not affect mechanistic target of rapamycin complex 1 assembly but is required for maximal ribosomal protein s6 kinase 1 activity in human skeletal muscle following resistance exercise. FASEB J. 2015;29(10):4358–73.
29. Dreyer HC, Fujita S, Cadenas JG, Chinkes DL, Volpi E, Rasmussen BB. Resistance exercise increases AMPK activity and reduces 4E-BP1 phosphorylation and protein synthesis in human skeletal muscle. J Physiol. 2006;576(Pt 2):613–24.
30. Gardner TW, Abcouwer SF, Losiewicz MK, Fort PE. Phosphatase control of 4E-BP1 phosphorylation state is central for glycolytic regulation of retinal protein synthesis. Am J Physiol Endocrinol Metab. 2015;309(6):E546–56.
31. Rose AJ, Bisiani B, Vistisen B, Kiens B, Richter EA. Skeletal muscle eEF2 and 4EBP1 phosphorylation during endurance exercise is dependent on intensity and muscle fiber type. Am J Physiol Regul Integr Comp Physiol. 2009;296(2):R326–33.
32. Bolster DR, Crozier SJ, Kimball SR, Jefferson LS. AMP-activated protein kinase suppresses protein synthesis in rat skeletal muscle through down-regulated mammalian target of rapamycin (mTOR) signaling. J Biol Chem. 2002;277(27):23977–80.
33. Guadalupe-Grau A, Rodríguez-García L, Torres-Peralta R, et al. Greater basal skeletal muscle AMPKα phosphorylation in men than in women: associations with anaerobic performance. Eur J Sport Sci. 2016;16(4):455–64.
34. Lee-Young RS, Canny BJ, Myers DE, McConell GK. AMPK activation is fiber type specific in human skeletal muscle: effects of exercise and short-term exercise training. J Appl Physiol (1985). 2009;107(1):283–9.
35. Ydfors M, Fischer H, Mascher H, Blomstrand E, Norrbom J, Gustafsson T. The truncated splice variants, NT-PGC-1α and PGC-1α4, increase with both endurance and resistance exercise in human skeletal muscle. Physiol Rep. 2013;1(6):e00140.
36. Gidlund EK, Ydfors M, Appel S, Rundqvist H, Sundberg CJ, Norrbom J. Rapidly elevated levels of PGC-1α-b protein in human skeletal muscle after exercise: exploring regulatory factors in a randomized controlled trial. J Appl Physiol (1985). 2015;119(4):374–84.
37. Eom GH, Kim KB, Kim JH, et al. Histone methyltransferase SETD3 regulates muscle differentiation. J Biol Chem. 2011;286(40):34733–42.
38. Baehr LM, Tunzi M, Bodine SC. Muscle hypertrophy is associated with increases in proteasome activity that is independent of MuRF1 and MAFbx expression. Front Physiol. 2014;5:69.
39. Leger B, Cartoni R, Praz M, et al. Akt signalling through GSK-3beta, mTOR and Foxo1 is involved in human skeletal muscle hypertrophy and atrophy. J Physiol. 2006;576(Pt 3):923–33.
40. Mabuchi H, Fujii H, Calin G, et al. Cloning and characterization of CLLD6, CLLD7, and CLLD8, novel candidate genes for leukemogenesis at chromosome 13q14, a region commonly deleted in B-cell chronic lymphocytic leukemia. Cancer Res. 2001;61(7):2870–7.
41. Ng MCY, Graff M, Lu Y, et al. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African ancestry anthropometry genetics consortium. PLoS Genet. 2017;13(4):e1006719.


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