Adaptation of Resistance Training is impaired in muscle-specific PGC-1α overexpressing mice

doi:10.21203/rs.3.rs-4437138/v1

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Adaptation of Resistance Training is impaired in muscle-specific PGC-1α overexpressing mice

https://doi.org/10.21203/rs.3.rs-4437138/v1

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Resistance training (RT) is important for skeletal muscle health. However, compared with RT implemented alone, concurrent training can attenuate RT adaptations. We verify the effects of RT on muscle-enriched or hypertrophy-related miRNAs, mammalian target of rapamycin complex 1 (mTORC1) anabolic signaling proteins, and oxidative metabolism-related proteins in mice with different endurance muscle Phenotype. In the present study, we found that muscle-specific overexpression of PGC-1alpha attenuated RT adaptations and resulted in different expression of miR-222-3p and miR-206-3p after RT. The expression level of miR-206-3p and miR-222-3p in Wt+ mice (wild-type trained mice) was significantly higher than that in Tg+ mice (MCK-PGC-1α transgenic trained mice). This suggested that discordant miR-222-3p and miR-206-3p expression levels after RT may play a role in the mechanism contributing to the interference effects. With regard to protein expression,there was no difference in mTORC1 between the genotypes. Furthermore, the levels of parameters for oxidative metabolism were significantly higher in Tg mice than in Wt mice. Our study indicated miR-222-3p and miR-206-3pas novel molecules that could provide a new research direction into the mechanisms underlying the concurrent training effect.

Resistance training

Muscle-specific PGC-1alpha-overexpressing mice

miRNAs

Concurrent training

Resistance training (RT) is known to be an effective strategy to maintain or increase skeletal muscle strength and hypertrophy[1]. RT has been shown to molecularly alter the level of substrate metabolism, such as increasing the synthesis of myofibrillar proteins[2] and myofiber nuclei[3]. The insulin-like growth factor 1 (IGF-1)-phosphoinositide 3-kinase (PI3K)-Akt signaling pathway[4] and the mammalian target of rapamycin complex 1 (mTORC1) signaling complex[4] play key roles in regulating muscle myofiber hypertrophy. Endurance training can increase the activity of the peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) signaling pathway, which regulates myocellular mitochondrial function[5].

Moreover, although the benefits of endurance and RT are numerous, concurrent training, in which resistance and endurance exercises are performed simultaneously, may attenuate the adaptation of RT when compared with either training method alone, which is called the concurrent training effect[6-10]. This phenomenon was first described in 1980 by Robert C. Hickson[11]. Regarding molecular mechanisms, previous studies have focused on the potential antagonism between the AMPK (an upstream activator of PGC-1α) and mTORC1 signaling cascades to elucidate the interference effect of concurrent training[6-10]. In rodent models, after resistance exercise, animals treated with AICAR, the AMPK activator, display a clear reduction in mTORC1 activation as previously described[12]. However, human studies have shown that AMPK activation by endurance training has minimal effects on mTORC1 activation. The most likely explanation is that only the α2 isoform of AMPK is activated by exercise, whereas AICAR activates both the α1 and α2 isoforms[13]. Additionally, load-induced muscle growth is inhibited by AMPK isoform α1 in vivo[14]. In conclusion, this evidence suggests that AMPK activation induced by endurance training inhibits mTORC1 activation, which may be a part of the concurrent training effect. To better understand the molecular mechanisms by which strength adaptations are impaired by concurrent training, we need to evaluate novel potential molecular phenomena that occur after different modes of training.

Previous studies have shown that exercise training or mode can change the level of microRNAs (miRNAs)[15,16], which play a critical role in these physiological adaptations. Thus, miRNAs have been suggested to modulate the above key regulators, which in turn may mediate exercise-induced molecular mechanisms [17].

Thus, given that transgenic mice overexpressing PGC-1α under the control of the muscle creatinine kinase promoter (MCK-PGC-1α) have a constitutively developed endurance muscle phenotype[18], we selected MCK-PGC-1α transgenic (MCK-PGC-1α) mice to perform 8 weeks of RT. Furthermore, we verified the seven muscle-enriched miRNAs (miR-1a-3p, miR-133a-3p, miR-133b-3p, miR-208a-3p, miR-206-3p, miR-486a-5p and miR-499-5p)[19] and three hypertrophy-related miRNAs (miR-155-5p[20], miR-17-3p, miR-222-3p as previously described [17,21]) implicated in crucial exercise adaptations.

In addition, we also evaluated the key molecules of mTOR anabolic signaling, such as mTORC1 upstream (protein kinase B, Akt) and downstream (ribosomal S6 kinase 1, p70S6k, ribosomal protein, S6, eIF4E binding protein 1, 4E-BP1), and PGC-1α catabolic signaling factors, such as adenosine monophosphate-activated protein kinase (AMPK), adenosine triphosphate (ATPase), cytochrome C (cyto-c) and recombinant glucose transporter 4 (GLUT4).

We hypothesized that long-term RT differentially affects these selected molecular metrics in wild-type and MCK-PGC-1α mice, which may provide a better understanding of the molecular mechanisms involved in RT or concurrent training adaptations.

2.1 Experimental animals

Mature male MCK-PGC-1α transgenic (Tg) mice from the C57BL/6J background at the age of 8 weeks and wild-type (Wt) C57BL/6J mice of the same age were included. Dr. 1 (Institution) kindly donated the transgenic MCK-PGC-1α mice (The Jackson Laboratory; Stock no. 008231). Tg mice were produced as previously described. Wt mice were obtained from Beijing Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). Sixteen cages containing 4 mice each were housed in a temperature-controlled room (22 ± 2 °C) with a 12 h light/dark cycle (light: 9 AM to 9 PM, dark: 9 PM to 9 AM) and unlimited water and food. The experimental procedures were approved by the Nanjing University Animal Care and Use Committee. Mice were divided into the following groups: Wt treated with RT (Wt+; n=16), Wt without RT (Wt-; n=16), Tg treated with RT (Tg+; n=16), and Tg without RT (Tg-; n=16). All groups were trained in a well-lit room from 1 PM to 5 PM.

2.2 Genotyping

Mice born from heterozygous MCK-PGC-1α mouse parents were genotyped to confirm their positive Tg status. DNA was then extracted using the cell/tissue genomic DNA extraction kit (centrifugal column type) purchased from Bomaide Biotechnology Co., Ltd. (Beijing, China) and used according to the manufacturer's recommended protocol. The primers used for genomic DNA PCR to identify PGC-1α-tg mice were as follows: C57BL/6-Tg (Ckm-Ppargc1a) 31Brsp/J, 5′ AGC CGT GAC CAC TGA CAA CGA G 3′ (forward) 5′ GCT GCA TGG TTC TGA GTG CTA AG 3′ (reverse).

2.3 Training protocol and performance evaluation

2.3.1 Description of the apparatus used for mouse resistance training

A ladder was made as previously described for the mice to perform the RT protocol. The ladder was 70 cm high and 10 cm wide with a 1.5 cm grid and an angle of 80 degrees to the horizontal desktop. A resting room (10 × 10 × 10 cm) for the mice to rest was on the top of the ladder. The loading apparatus used was a black rubber balloon, which was fastened to the entire length of the mouse tail with waterproof tape.

2.3.2 Maximum voluntary carrying capacity (MVCC) test and resistance training protocol

RT was executed according to the protocol described by Minuzzi with several adjustments[22]. First, an empty weight-bearing device was immobilized on the tail while the mice were acclimated to the ladder. The resting room was placed on the top of the ladder, where the mice were allowed to repose between climbs. To acclimate to the exercise regimen, the mice were kept in the resting room for 120 s before each attempt to climb. The mice were urged to climb by touching their tails until they reached the resting room 3 consecutive times. This protocol was carried out for 5 consecutive days. Then, we determined the MVCC of each mouse. After this adaptation period, the mice rested for 2 days before the start of the test. During the test, the attempt was considered successful if the mice departed from the bottom of the ladder and reached the resting room. The test initiated with a climb carrying 25% of the animal’s body weight, and an incremental load of 3 grams was added to the loading apparatus upon successful completion. This course was successively repeated until a load was reached with which the mouse could no longer accomplish the entire process. After each successful attempt, the mouse settled in the resting room for 5 min until the next attempt started. The highest load the mouse could successfully carry was considered to be the MVCC of the mouse. The training sessions consisted of 20 climbs series at a load of 70% of the animal’s MVCC, with a rest interval of 60-90 s between climbs. Weekly RT with 3 days of training and 4 days off (once every other day) was performed for an 8-week period. Starting at the beginning of training, MVCC was tested once a week (on Mondays) to revise the load for each of the mice. The mice in the Wt- and Tg- groups remained in cages during the experimental period. These mice were trained to climb ladders only in weeks 1, 5 and 9. At these 3 time nodes, these mice needed to complete the corresponding adaptive training as described above and then performed the MVCC test. All of the animals were able to complete the task.

To achieve a blinded assessment, each animal was evaluated by four different investigators as follows: a first investigator performed randomization. This investigator was the only person aware of the treatment groups allocation. A second investigator was responsible for the behavioural test procedure, whereas a third investigator performed the resistance training protocol. Finally, a fourth investigator (also unaware of treatment) conducted the molecular biology experiments.

2.3.3 Grip Strength Test

We measured mouse limb grasping power by using a grip tester (YLS-13Al; Yiyan Technology & Development, Shandong, China). In brief, mice were placed with their four paws on a grip power board and gently jerked backward until they released their grip. A maximum grip strength measurement was automatically recorded. Data were averaged after triplicate experiments.

2.3.4 Incremental load test (ILT)

Before being subjected to the ILT, mice underwent a five-day adaptation to the treadmill (ZH-PT, Zhenghua, Anhui, China). During this adaptation period, animals ran at 10 m/min for 10 min each day. The test started at 6 m/min, and the speed increased 3 m/min every 3 minutes until exhaustion. We used electrical stimulation to motivate the animals during exercise. When the mice were considered to be exhausted, the exhaustion velocity (EV = V + (n/b) × a, where V is the velocity of the last completed phase, n is the duration maintained in the incomplete phase, b is the duration of the phase, and a is the test enhancement) was computed following the approaches used by Kuipers et al[23]. The EV was used to assess endurance performance.

2.3.5 Low intensity exhaustion test (LIET)

To assess endurance exercise capacity roundly, mice were performed the LIET 72 hours after the ILT. On the day of the experiment, mice were run for 1 h at 10 m/min followed by an increase in speed of 2 m/min each additional 15 min until failure. Mice were defined as exhausted if they remained on the shock grid for five continuous seconds. Exhausted time and distance were used to assess endurance performance.

2.3.6 Training schedule

The details of the Animal experiment schedule are shown in Fig. 1.

2.4 Body weight, body composition and muscle wet weight measurement

Mouse body weight was recorded weekly. Mouse body composition was determined by using dual-energy X-ray absorptiometry (Hologic Horizon Wi, USA). The mice were euthanized by decapitation 72 h after the last behavioral test to rule out the temporary effects of exercise training. The quadriceps femoris (QF), tibialis anterior (TA), extensor digitorum longus (EDL), gastrocnemius (GAS), plantaris (PL) and soleus (SOL) were collected and the excess connective tissue was carefully trimmed off, and the weights of these tissues were determined.

2.5 Western blot analysis

Western blot analysis was conducted according to previous descriptions. Briefly, proteins were extracted from the plantaris using RIPA buffer supplemented with protease inhibitors. The protein samples (40 µg/lane) were separated by 4-20% SDS‒PAGE gels and then blotted onto PVDF membranes. After blocking for 15 min using blocking solution, the membranes were incubated overnight at 4 ℃ by using primary antibodies and then washed 4 times for 10 min in 1 X TBS, 0.1% Tween 20. After incubation with secondary antibodies (1 h at ordinary temperature), washing was repeated. Finally, we visualized the immunoblot results by using an ECL chemiluminescence detection system. The primary antibodies were as follows: Akt (1:1000; Cell Signaling Technology, USA), p-Akt (1:1000; Cell Signaling Technology, USA), mTOR (1:1000; Cell Signaling Technology, USA), p-mTOR (1:1000; Cell Signaling Technology, USA), p70S6K (1:1000; Cell Signaling Technology, USA), p-p70S6K (1:1000; Cell Signaling Technology, USA), S6 (1:1000; Cell Signaling Technology, USA), p-S6 (1:2000; Cell Signaling Technology, USA), 4EBP1 (1:1000; Cell Signaling Technology, USA), p-4EBP1 (1:1000; Cell Signaling Technology, USA), AMPK (1:1000; Cell Signaling Technology, USA), p-AMPK (1:1000; Cell Signaling Technology, USA), ATPase (1:1000; Santa Cruz, USA), PGC-1α (1:1000; Abcam, UK), ATPase (1:1000, Santa Cruz, USA), Cytochrome C (1:1000; BD Biosciences, USA), and Glut 4 (1:1000; Cell Signaling Technology, USA).

2.6 RNA isolation and quantification of miRNAs

Frozen plantaris muscle tissue was homogenized using TRIzol Reagent (Code No. 15596018, Ambion, USA) for total RNA isolation according to the corresponding protocol. Real-time quantitative polymerase chain reaction (RT‒qPCR) was used to measure the expression of miRNAs in plantaris muscle tissue with all samples processed in the same batch. Nanodrop ND 1000 (Thermo Scientific, Wilmington, USA) was used to measure the RNA concentration and quality (OD260/280 ratio). The corresponding cDNA products were obtained by RT‒qPCR using a miRNA reverse transcription kit (Vazyme, Nanjing, China). An RT‒qPCR kit (Vazyme, Nanjing, China) and Roche LightCycler®96 (Roche, Basel, Switzerland) were used for the qPCR test. Groups were distributed randomly across plates, and longitudinal samples from the same individual were run on the same plate to reduce potential batch effects. The real-time PCR conditions consisted of a preincubation step at 95 °C for 5 min, 40 cycles at 95 °C for 10 s, 60 °C for 30 s, 95 °C for 15 s, 60 °C for 60 s and 95 °C for 15 s. The relative snRNAU6 expression of miRNAs in the plantaris muscle tissue was used for normalization, and the Ct values were calculated using the 2−ΔΔCt method, with each sample analyzed three times.

The nucleotide sequences of the RT‒qPCR primers used in this experiment are shown in Table 1.

2.7 Statistical analysis

Data presented in the paper are presented as the mean ± standard error of the mean (SEM), and statistical analysis was performed using GraphPad Prism 8. The normality of data was checked by the Shapiro-Wilk test. Homogeneity of variance was checked using Bartlett’s test. For comparison between two groups, two-tailed paired or unpaired t-test, Welch’s correction t-test, or Mann-Whitney test was performed. For comparisons of three or more groups, one-way ANOVA or two-way ANOVA was performed. Tukey’s multiple comparisons test was used for post-hoc comparisons after the ANOVA tests.

3.1 Aerobic exercise performance of Wt mice and Tg mice before training

As shown in Fig. 2, we examined the Aerobic exercise performance of Wt mice and Tg mice before training. Total distance (P < 0.01; Fig. 2a) and total time (P < 0.001; Fig. 2b) during LIET of the Tg mice were significantly higher than those of the Wt mice before training. In addition, the EV values of the Tg mice was significantly higher than that of the Wt mice before training (P < 0.05; Fig. 2c).

3.2 Body weight

Fig. 3a shows the body weight (g) of the four groups during each week of the experimental period. The body weight of the Tg+ group was significantly lower than that of the Wt- group from the third week until the final ninth week ( all P < 0.05). The same tendency was shown in the Wt+ group, where the body weight of the Wt+ group was significantly lower than that of the Wt- group at weeks 3-6 and week 8 (P < 0.05, P < 0.01). At week 2, mice in the Tg- group weighed significantly more than mice in the Wt- group (P < 0.01). As indicated in Fig. 3b, compared with 9 weeks prior, the body weight increased by 24.33%, 18.58%, 19.78% and 8.86% in the Wt-, Wt+, Tg- and Tg+ groups, respectively. Moreover, the percent change in body weight of Tg+ mice was significantly lower than that in the other three groups (P < 0.0001).

3.3 Body composition and muscle wet weight

To evaluate the effects of our training program on body composition and hypertrophied muscle, we measured lean body mass without bone, body fat percentage and muscle wet weight of the mice. After eight weeks of training, lean body mass without bone of the Wt-, Wt+, Tg- and Tg+ groups were not significantly different (Fig. 4a) In addition, the body fat percentage of the mice in the Wt- group was significantly lower than that in the Wt+ group (P < 0.01). Compared with the Wt- group mice, the Tg- group and Tg + group mice exhibited a decrease in body fat percentage, but there was no significant difference (P > 0.05) (Fig. 4b). Moreover, Fig. 4c presents the changes in the wet weight (mg) of PL, SOL, GAS, QF, TA and EDL in the four groups after eight weeks of training. Overall, the muscle wet weight of the Wt+ group was significantly higher than that of the Wt- group. The muscle wet weight of the Tg+ group was less than that of the Tg- group. The PL wet weight of the Wt+ group (P < 0.05) and Tg- group (P < 0.001) was significantly increased compared to the PL wet weight of the Wt- group. For the muscle wet weight of the TA,Tg- group was significantly higher than those of the Wt- group (P < 0.0001) and Wt+ group (P < 0.001).

3.4 Maximal voluntary carrying capacity (MVCC)

Fig. 5a shows the results of MVCC recorded in the Wt+ and Tg+ groups during the nine-week training regimen. MVCC improved in both the Wt+ and Tg+ groups during the first few weeks, and the MVCC levels of the two groups were nearly the same in the third week. From then on, the MVCC level of the Tg+ group showed an upward trend, which was higher than that of the Wt+ group. According to the MVCC test results in the ninth week, there was no significant difference in MVCC between the two groups (P > 0.05).

In addition, we used the MVCC test results of the first week, the fifth week and the ninth week of the eight-week exercise scheme to represent the start stage, the intermediate stage and the end of the exercise cycle, respectively. As shown in Fig. 5b, there was no significant difference in the three MVCC test results between the Wt- group and Tg- group (P > 0.05). The MVCC measurement results of Wt+ mice at week 5 and week 9 were significantly higher than those at week 1 (P < 0.0001). The MVCC measurement results in the fifth and ninth weeks of the Tg + group were significantly improved compared with those in the first week (P < 0.0001).

3.5 Incremental load test (ILT)

As shown in Fig. 5c, the EV values of the Tg+ and Tg- groups were slightly higher than those of the Wt+ and Wt- groups in the first week, while the EV values of the Wt-, Wt+, Tg- and Tg+ groups were not significantly different. However, in the test conducted in the ninth week, the EV value recorded for the Wt+ group was significantly higher than the EV value recorded for the Wt- group (P < 0.05) and Tg+ group (P < 0.001). Moreover, the EV value of the Tg+ group was significantly lower than that of the Tg- group (P < 0.05).

3.6 Grip strength

The results of the grip test performed on the four groups of mice at weeks 1, 5 and 9 are presented in Fig. 5d. The maximum grip strength value recorded in week 9 of the Wt- group was significantly lower than the value recorded in week 1 (P < 0.05). The maximum grip strength recorded in week 5 for the Wt+ group was the same as that in week 9, which was significantly higher than the maximum grip strength recorded in week 1. Compared with the maximum grip strength at week 1, the maximum grip strength at week 5 was significantly lower in the Tg- group (P < 0.01). No difference reached statistical significance in the Tg+ group.

3.7 Expression of mTOR signaling proteins

To investigate the effects of long-term concurrent training on skeletal muscle, Western blotting was utilized to detect the expression of Akt/mTOR pathway signaling proteins. After eight weeks of concurrent training, no significant difference in the expression levels of Akt, mTOR, S6 and 4EBP1 (Fig. 6a-d, 6g-j) was observed. In addition, p70S6K phosphorylation levels in the Tg- group and Tg+ group were almost the same, and were significantly increased compared with those in the Wt- group (P < 0.001) and Wt+ group (P < 0.01; Fig. 6e). As shown in Fig. 6f, the protein expression level of p70S6K in the Tg- group was significantly lower than that in the Wt- group (P < 0.05).

3.8 Expression of oxidative metabolism-related proteins

No significant differences were observed in the expression levels of proteins related to oxidative metabolism (AMPK, ATP synthase) among the four groups (Fig. 7a-c). The protein expression levels of PGC-1α, a major master regulator of metabolism, were significantly increased in the Tg- group (P < 0.01) and Tg+ group (P < 0.05) compared with the Wt- group (Fig. 7d). Fig. 7e indicatesthat the expression level of the cytochrome C protein in the plantaris muscle of the Tg- group was significantly higher than that in the plantaris muscle of the Wt- group (P < 0.001) and Wt+ group (P < 0.01), and that in Tg+ group was significantly higher than that in Wt- group (P < 0.01) and Wt+ group (P < 0.01). Glut4, one of the determinants of skeletal muscle glucose uptake during exercise, was significantly upregulated in the Tg+ group compared with the Wt- group (P < 0.05) and Wt+ group (P < 0.05; Fig. 7f).

39 Changes in muscle enriched-miRNA and hypertrophy-related miRNA levels in response to ladder-climbing training

As shown in Fig. 8, we examined the expression of muscle enriched-miRNAs and hypertrophy-related miRNAs in plantaris muscle tissue after the ladder-climbing training protocol using RT‒qPCR. Three microRNAs (miR-1a-3p, miR-133a-3p, miR-133b-3p) were significantly downregulated in all Tg mouse groups (Tg- and Tg+): The expression levels of miR-1a-3p, miR-133a-3p and miR-133b-3p were significantly lower in Tg mice (Tg- and Tg+) than in Wt mice (Wt- and Wt+), while the expression levels of these microRNAs were not significantly changed by ladder climbing (Fig. 8a-c). In contrast, the expression level of miR-486a-5p was significantly higher in Tg mice (Tg- and Tg+) than in Wt mice (Wt- and Wt+), while the expression levels of these microRNAs were not significantly changed by ladder climbing (Fig. 8g). In addition, the relative expression of miR-155-3p in the Tg- group was significantly higher than that in the Wt- (P<0.01) and Wt+ (P<0.05) groups, and that in Tg+ group was significantly higher than that in Wt- group (P < 0.05) while the relative expression of miR-17-3p in the Tg+ group was lower than that in the Wt- (P<0.001) and Wt+ (P<0.01) groups (Fig. 8h-i). Furthermore, the expression of miR-206-3p and miR-222-3p in the Wt+ group was significantly higher than that in the Tg+ group (P<0.01, P<0.01) (Fig. 8d and j). Significant differences in the miRNA expression levels of miR-208a-3p and miR-499-5p were not observed in the plantaris muscle tissue among the four experimental groups (Fig. 8e-f).

RT represents unique physiological stimuli for examining the morphological or functional adaptation or molecular regulation of exercise-induced skeletal muscle adaptations[24,25,26]. Overall, the above findings suggest that Tg mice showed abnormal adaptations following 8 weeks of RT. However, our selected mammalian target of rapamycin complex 1 (mTORC1) anabolic signaling pathway proteins and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) catabolic signaling pathway proteins did not show differential expression between genotypes. In addition, our selected muscle-enriched or hypertrophy-related miRNAs did not show significant differential expression between genotypes,; however, the different miR-206-3p and miR-222-3p changes may likely be a potential mechanism underlying interference effects.

The muscle morphological or functional adaptation responses to resistance exercise commonly focus on gains in muscle strength, hypertrophy, endurance and power. Manipulating RT variables (e.g., intensity, volume, exercise selection, etc.) may enhance the muscle-specific stimulus[27]. It is generally thought that body recomposition, in which muscle mass is gained and fat mass is lost simultaneously, mainly occurs following RT[28]. In our study, we observed that the exercised Tg mice showed significantly lower body weight, body weight without bone and muscle wet weight; in contrast, the exercised Wt mice showed significantly higher body weight. Moreover, we observed that body fat percentage decreased only in exercised Wt mice. Our results indicated that morphological changes were likely different between genotypes.

With regard to functional tests, we did not observe different changes in MVCC between genotypes; however, we observed that ILT and grip strength increased in exercised Wt mice, while ILT and grip strength decreased or remained unchanged in exercised Tg mice. Our results also indicated that the functional changes were likely different between genotypes, and the Tg mice showed conflicting neuromuscular adaptations.

In summary, our results demonstrated that RT results in compromised adaptation in Tg mice compared to Wt mice, and there likely existed a potential interference in strength development. Given that MCK-PGC-1α, under the muscle creatinine kinase promoter with higher aerobic capacity, has an endurance-like genetic mode, RT seems to have a negative impact on normal adaptations. Thus, it is likely that the ‘interference phenomenon’ occurred.

Understanding the pathways that promote interference effects during concurrent training has important fundamental and clinical implications[6-10]. It is well known that resistance exercise is a direct regulator of AKT/mTOR signaling promoting muscle hypertrophy[4] and has little effect on the AMPK/PGC-1a pathway[29]. Previous studies have suggested that increased expression levels of genes and proteins or phosphorylation of intramuscular signaling molecules appears to play an important role in skeletal muscle adaptation. However, in our study, we did not observe any difference in the protein expression or phosphorylation level of Akt, mTOR, p70S6K, S6 and 4EBP1 between genotypes. The lack of change in the present study is perhaps attributed to differences in the skeletal muscle examined. Gastrocnemius, flexor hallucis longus and several other muscles were collected and analyzed after training in previous studies[30,31], whereas the plantaris was the only muscle chosen for analysis due to the results of wet muscle weight in our study. The lack of change can also be attributed to differences in the model of RT, specifically the differences in the training intensity. Most previous studies used relatively low intensity ladder climbing exercise[32,33], whereas the present study used ladder climbing exercise with additional MVCC exercises because it is a relative quantification exercise protocol and is physiologically more similar to human RT.

In addition,endurance training plays a key role in regulating oxidative metabolism. PGC-1a has been suggested as a fundamental component of endurance training exercise-induced adaptations, and elevated PGC-1α mRNA levels are observed following endurance-based exercise in humans[34]. We observed that the PGC-1a level significantly increased in Tg mice, and the cytochrome C and Glut4 levels also significantly increased. However, we did not observe any difference in the protein expression or phosphorylation level of AMPK, ATP synthase, PGC-1a, Cytochrome C and Glut4 between genotypes. Our results support a previous study that suggested that RT appeared to have little impact on the AMPK/PGC-1a pathway[34].

It has been suggested that resistance and endurance training are divergent exercise modes, which may trigger distinct but also overlapping training responses [8]. A better understanding of the molecular mechanisms underlying training-related muscle adaptations may have implications for optimally designing training plans. Recently, miRNAs have been suggested as regulators of signaling pathways involved in skeletal muscle interactions during exercise training, such as the IGF1/PI3K/AKT/mTOR axis[17]. A previous study showed that the levels of muscle-enriched miRNAs miR-1 and miR-133a decreased during skeletal muscle hypertrophy[15]. In our study, we did not observe any difference in our selected muscle-enriched miRNAs, such as miR-1a-3p, miR-133a-3p, miR-133b-3p, miR-208a-3p, miR-486a-5p, and miR-499-5p, between genotypes. Only the increased miR-206-3p level was affected in Wt mice and did not change in Tg mice. More importantly, the increase in miR-206 levels has been observed in power athletes with fast-twitch ﬁber predominance[35]. Given the training effect in Wt mice and training-induced phenotypic maladaptation in Tg mice, our data likely suggest that increased miR-206-3p levels may play an important role in resistance exercise-induced hypertrophy and may be linked to the interference effect.

In addition, with regard to the three hypertrophy-related miRNAs, the level was increased in MCK-PGC-1α mice, the miR-155-3p level in sedentary MCK-PGC-1α mice was also significantly increased, and the level of miR-17-3p, a key regulator of physiological cardiac hypertrophy[36], was decreased, which may reﬂect the genotype background. On a systemic level, factors associated with age-related metabolism showed improvement in MCK-PGC-1α mice. However, these were also not affected by exercise. Moreover, the role of miR-222 in exercise-induced cardiomyocyte growth has been previously evaluated[37]. In our study, we also found increased miR-222-3p levels in Wt mice, while the levels did not change in Tg mice. The miR-222-3p response was similar to that of miR-206-3p, likely indicating that miR-222-3p has a similar effect. Still, it is worth noting that the mice in the Wt- and Tg- groups were also trained to climb ladders and performed the MVCC test at weeks 1, 5, and 9. This might affect the mTORC1 anabolic signaling pathway, oxidative metabolism-related signaling pathway, and muscle-enriched or hypertrophy-related miRNAs in mice in the Wt- and Tg- groups. These limitations need to be considered when interpreting the results.

Overall, in our study, we observed changes in whole-body functional outcomes, and the intramuscular anabolic signaling implications for muscle hypertrophy following resistance exercise did not show any significant difference. Although our results indicated that most of the selected miRNAs were not differentially expressed between genotypes, miR-206-3p and miR-222-3p showed opposite responses; thus, it is likely that these miRNAs may be related to the concurrent training effect. At present, given that exercise is important for heath, understanding the potential molecular mechanisms induced by RT, endurance training or concurrent training may help to design training programs to maximize exercise adaptations[6-10]. The possible mechanisms of concurrent training effect mainly includes overtraining hypothesis[38], acute effects hypothesis and chronic adaptations hypothesis[39] from the macro level. on the micro level, the main mechanisms are molecular interference hypothesis[40], AMPK-Akt switching hypothesis[41] and molecular adaptations hypothesis[42]. Most of these hypotheses are needed to be further research due to the differences in experimental design, and one of the most important issues in further studies is the control of irrelevant variables. MCK-PGC-1a mice undergoing strength training simulation concurrent training can effectively control variables such as training interval, training time, training intensity, etc., in order to conduct more in-depth mechanism research on the combination.

Few studies have been conducted to search for new signaling molecules that may participate in the occurrence and development of concurrent training effects. In the present study, we attempted to eliminate the error caused by training intensity, training interval and other variables of concurrent training by using the same RT protocol to train these animals with different phenotypes. Nevertheless, some limitations were inevitable in this study.

The first limitation is attributable to the experimental design. Many factors can affect miRNA expression[43]. Overexpression of PGC-1α in skeletal muscle led to changes in the miRNA expression profile, as described in the results section, and the expression levels of some miRNAs were altered in Tg mice. The issue might limit the generalizability of the study results.

In addition, another limitation is the lack of partial in vivo experiments. miRNA knockout animals should be employed to verify our results. This change will be implemented in a follow-up study.

In summary, these data suggest that the magnitude of the increase in maximum strength was attenuated in Tg mice, which may likely reflect an interference effect. It is likely that these two opposing miRNA levels between genotypes may play an important role in the interference between concurrent resistance and endurance exercise. Thus, future studies will be required to identify the potential possible mechanisms associated with these two miRNAs.

Ethics approval and consent to participate

The experimental procedures were approved by the Nanjing University Animal Care and Use Committee.

Consent for publication

Not applicable.

Availability of data and materials

The data that support the findings of this study are not openly available due to another parallel study and are available from the corresponding author upon reasonable request.

CONFLICTS OF INTEREST

The authors declare that they have no conflict of interest.

Funding

The authors acknowledge that this work was supported by the Natural Science Foundation of Jiangsu Province (BK20211228), the Foundation project in the technical field of the basic strengthening plan in China (2021-JCJQ-JJ-1021), the Basic frontier innovation projects for the Army Engineering University of PLA (KYJXJQZL 2201,2109).

Authors' contributions

HP.Z and TC.X performed the resistance training protocol, and was a major contributor in writing the manuscript. YL.S and RY.B were responsible for the behavioural test procedure. MC.D and SJ.X conducted the molecular biology experiments. HZ.Z was responsible for the data analysis and visualization. SW were responsible for the funding acquisition. CY.Z and JZ.M Managed and coordinated the research activity planning and execution. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

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Table 1 Primer sequence of the corresponding gene
Gene	Primer sequences
snRNAU6		F: CAAATTCGTGAAGCGTTCCA
miR-1a-3p		F: GCGCGTGGAATGTAAAGAAGT
miR-133a-3p		F: GCGTTTGGTCCCCTTCAAC
miR-133b-3p		F: GCGTTTGGTCCCCTTCAAC
miR-208a-3p		F: CGCGATAAGACGAGCAAAAA
miR-206-3p		F: GCGCGTGGAATGTAAGGAAGT
miR-499-5p		F: GCGCGTTAAGACTTGCAGTG
miR-486a-5p		F: CGCGTCCTGTACTGAGCTGC
miR-155-5p		F: GCGCGTTAATGCTAATTGTGAT
miR-17-3p		F: GCGACTGCAGTGAGGGCAC
miR-222-3p		F: CGCGAGCTCATCTGGCTACT
		R: AGTGCAGGGTCCGAGGTATT

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Adaptation of Resistance Training is impaired in muscle-specific PGC-1α overexpressing mice

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2 Materials and methods

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