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Time Course of Skeletal Muscle miRNA Expression after Resistance, High-Intensity Interval, and Concurrent Exercise

TELLES, GUILHERME DEFANTE1; LIBARDI, CLEITON AUGUSTO2; CONCEIÇÃO, MIGUEL SOARES1; VECHIN, FELIPE CASSARO1; LIXANDRÃO, MANOEL EMÍLIO1; DE ANDRADE, ANDRÉ LUÍS LUGNANI3; GUEDES, DANIEL NOVAIS4; UGRINOWITSCH, CARLOS1; CAMERA, DONNY MICHAEL5

Author Information
Medicine & Science in Sports & Exercise: August 2021 - Volume 53 - Issue 8 - p 1708-1718
doi: 10.1249/MSS.0000000000002632
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Abstract

Resistance exercise (RE) performed to muscle failure is an efficient protocol to optimize muscle mass gains (1), whereas high-intensity interval exercise (HIIE) can maximize increases in V˙O2max (2). Combining RE and HIIE into an unique training program, termed concurrent exercise (CE) training, is highly recommended to improve both variables concomitantly (3,4). Regardless of the exercise modality, muscle contraction has been shown to modulate cell transcription and translation activity through several mechanisms at genomic and postgenomic levels, which form the basis of exercise adaptation responses (5–7).

MicroRNAs (miRNAs) are a class of small (~22 nucleotides) noncoding ribonucleic acids (RNA) that play a crucial role in cell cycle and developmental processes, at the posttranscriptional level, by decreasing protein abundance either through mRNA degradation or gene translation repression (8). miRNAs have recently risen in prominence as regulators of skeletal muscle plasticity (9) and have been implicated in the control of exercise-induced muscle adaptations (10–17) by modulating key cellular processes involved in skeletal muscle growth (e.g., myogenesis) and energy metabolism (9,18–25). In this regard, exercise-induced contraction can alter the expression of a variety of miRNAs in human skeletal muscle including miR-1, miR-23a, miR-133a, miR-133b, miR-181a, miR-206, miR-378a, and miR-486 (10–17,26). However, the specificity in miRNA expression with different contractile stimuli is not well understood.

Although previous work has investigated skeletal muscle miRNA responses after resistance, aerobic, and concurrent exercise protocols, to date, no study directly compared miRNA expression between them in a unique experimental design while minimizing between-subject variability, limiting the ability to make inferences regarding exercise-specific miRNA responses. In addition, few studies have investigated acute skeletal muscle miRNA responses after an HIIE bout. As aerobic exercise protocols mainly activates molecular pathways related to energy metabolism (5) and considering that HIIE imposes high acute intracellular stress and changes in metabolic signaling (27), it is plausible that HIIE can induce a robust aerobic/metabolic-oriented miRNA response, distinct from RE. Moreover, considering putative molecular interactions when combining RE and HIIE (17), it stands to reason that CE could alter the expression pattern of specific skeletal muscle miRNAs when compared with isolated RE and HIIE exercise protocols. For instance, one could speculate that an HIIE-based CE protocol may alter muscle miRNAs that putatively target/are targeted by the myogenic regulatory factors (MRFs) when compared with RE performed in isolation, as the magnitude of expression of these genes might be changed after an HIEE-based CE protocol (28–30). There is also a paucity of data regarding the acute time course of the changes in skeletal muscle miRNA expression with divergent exercise modes. Indeed, most studies in the literature have only investigated miRNA expression at a single or two closely separated time points after exercise. This lack of temporal resolution has prevented more precise associations between exercise-induced changes in miRNA expression and cell signaling responses involved in muscle adaptation processes. Therefore, the primary aim of the present study was to compare the acute expression of select skeletal muscle miRNAs after a bout of RE, HIIE, or CE. A secondary aim was to provide a more accurate and detailed time course of skeletal muscle miRNA expression with the three types of exercise stimuli. As RE and HIIE are thought to mainly activate distinct cellular signaling pathways, we hypothesized RE and HIIE would induce distinct responses in the miRNA expression pattern. Also, we hypothesized that CE would induce a divergent expression pattern of miRNAs with implicated roles in myogenesis compared with RE only.

METHODS

Participants

Nine subjects (age, 23.9 ± 2.8 yr; body mass (BM), 70.1 ± 14.9 kg; height, 177.2 ± 3.0 cm; V˙O2peak, 41.4 ± 5.2 mL·kg−1·min−1) volunteered to participate. Inclusion criteria were as follows: not participating in any systematized physical training protocol for at least 6 months before the commencement of the study and not having conditions that could impair the performance of high-intensity efforts (i.e., free from any cardiopulmonary or musculoskeletal disorder). Given the variety of experimental protocols in the literature measuring miRNA expression from exercised skeletal muscle as well as the extended time course (8 h after exercise) we incorporated for the first time in the current work, it was not possible to precisely estimate the magnitude of expression of each miRNA a priori to accurately perform a power analysis.

Participants signed an informed consent form after being presented to the risks and benefits associated with the experimental protocol and stated that they were not taking nutritional supplements and anabolic steroids. The present research protocol was approved by the ethics committee of human research of the University of Sao Paulo and conducted in accordance with all the policy statements regarding human participants according to the latest revision of the Declaration of Helsinki.

Experimental Design

The study comprised a randomized counterbalanced, crossover experimental design, in which each subject performed three experimental conditions: RE, HIIE, and CE.

In the first 3 wk of the study, participants were familiarized with the exercise protocols used in the experimental conditions (three familiarization bouts) and with the cardiorespiratory test. The familiarization period attempted to minimize the nonspecific exercise-induced skeletal muscle responses after an unaccustomed exercise bout (31). After this period, volunteers performed the cardiorespiratory test (subsequently described), as it was required to determine HIIE intensity. Then three experimental sessions (RE, HIIE, and CE) were performed (subsequently described) with a 1-wk washout period between each condition to minimize for any carryover effect. The order of the exercise sessions was randomized and balanced (i.e., William’s square) to minimize possible order effects on the study results.

On the evenings before each experimental session, participants consumed standardized meals (subsequently described). The next morning, participants arrived in the laboratory and rested in a supine position for approximately 15 min. A resting skeletal muscle biopsy (Pre) was then taken (subsequently described) from each subject. Participants then performed their assigned exercise bout with further muscle biopsies obtained immediately (0 h), 4 h, and 8 h after each exercise trial. The leg to which muscle biopsies were taken was randomly chosen for each subject at the first muscle biopsy (Pre session 1), and all subsequent muscle biopsies were taken from the same leg during the study. Figure 1 presents a schematic representation of the experimental design.

F1
FIGURE 1:
Schematic representation of the experimental design. S1, first exercise session; S2, second exercise session; S3, third exercise session.

Diet/Exercise Control

During the experimental period, participants were instructed to avoid strenuous physical activity outside the experimental protocol. Participants recorded their food intake during the week before the first experimental session and were instructed to maintain their dietary habits throughout the next 2 wk of the study. On the day before each experimental session, participants were provided with a standard meal as the last meal of the day. The meal consisted of 3 g of carbohydrate per kilogram of BM, 0.5 g of protein per kilogram of BM, and 0.3 g of fat per kilogram of BM (32). On the day of experimental sessions, participants were also provided with another standard meal consisted of 60 g of CHO, 10 g of proteins, and 23.8 g of fat 3 h before each muscle biopsy to avoid possible fasting effects on miRNA expression.

Cardiorespiratory Test

Participants performed a maximum graded exercise test on a treadmill. Gas-exchange data were collected continuously using an automated breath-by-breath metabolic system (Quark CPET; Cosmed®, Rome, Italy). The protocol consisted of a 2-min warm-up at 6 km·h−1, followed by increments of 1 km·h−1 every 1 min up to exhaustion. To ensure that volunteer’s maximum effort was achieved, each volunteer had to meet the two following criteria at the end of the test: 1) RER greater than 1.1 and 2) heart rate greater than 90% of the maximum predicted for age (33). The highest 30-s V˙O2 mean value was expressed as the peak oxygen uptake (V˙O2peak), as a V˙O2 plateau was not observed during the test. The running speed that elicited V˙O2peak was adopted as a reference value for HIIE intensity prescription.

Exercise Protocols

Resistance exercise

After a light warm-up set with 5–10 repetitions at 50% of estimated exercise load, RE consisted of four sets of 8–12 repetition maximum (two sets in the leg press 45° and two sets in the leg extension machines) until concentric muscle failure (i.e., inability to complete another concentric muscle action through the full range of motion). A 1-min rest was allowed between sets and exercises. The exercise load required to perform 8–12 repetition maximum on each exercise was obtained during the familiarization period. For each set, the weight was adjusted to allow participant to perform the required number of repetitions.

High-intensity interval exercise

After a 4-min warm-up at 50% of running speed that elicited V˙O2peak, HIIE was composed of a high-intensity interval training protocol on a treadmill. Participants performed 12 × 1-min sprints at the running speed that elicited V˙O2peak (previously measured in the cardiorespiratory test). A 1-min active recovery period at 50% of running speed that elicited V˙O2peak was allowed between sprints.

Concurrent exercise

For the bout of CE, participants performed the exact same RE protocol followed by a 5-min rest interval before then undertaking the HIIE protocol.

Muscle Biopsies

Muscle biopsies were obtained from the vastus lateralis muscle under local anesthesia (2–3 mL of 1% xylocaine) using a 5-mm Bergstrom needle modified with suction. Approximately 100 mg of muscle tissue was collected during all biopsies, dissected from free from blood and connective tissue, and snap frozen in liquid nitrogen before being stored at −80°C until subsequent analyses.

Quantitative Reverse Transcription Polymerase Chain Reaction

miRNA extraction

Approximately 30 mg of frozen skeletal muscle was homogenized in Buffer RLT Plus by Qiagen following the manufacturer’s instructions. miRNA was subsequently extracted from the lysate using the AllPrep® DNA/RNA/miRNA Universal Kit on a QIAcube automate system by Qiagen (Germantown, MD) as per the manufacturer’s protocol instructions. RNA was eluted in 60 μL RNase-free water and then stored at −80°C. RNA was quantified by a NanoDrop spectrophotometer (Thermofisher Scientific, Carlsbad, CA) and the 260:280-nm absorbance ratio was used to assess RNA purity.

cDNA synthesis

cDNA synthesis was performed on a BioRad thermal cycler using the TaqMan™ Advanced miRNA cDNA Synthesis Kit (catalog no. A28007; Applied Biosystems, Victoria, Australia) following the manufacturer’s protocol. The maximum quantity (10 ng) of RNA suggested in the protocol was used for cDNA synthesis. After reverse transcription, a preamplification step (pre-miR amplification) was performed with the TaqMan™ Advanced miRNA cDNA Synthesis Kit, using universal forward and reverse primers to increase cDNA abundance. After reverse transcription, a miR-Amp Reaction Mix was prepared in a 1.5-mL microcentrifuge tube, containing (per one reaction): 25 μL of 2× miR-Amp Master Mix, 2.5 μL miR-Amp Primer Mix, and 17.5 μL RNase-free water, in a 45 μL final reaction volume. Thereafter, 5 μL of the reverse transcription reaction product was added to the 45 μL miR-Amp Reaction Mix and then incubated in a thermal cycler using the following settings: enzyme activation, 1 cycle, 5 min at 95°C; denaturation and annealing/extension, 14 cycles, 3 and 60 s at 95°C and 60°C, respectively; and stop reaction, 1 cycle, 10 min at 99°C. After pre-miR amplification, the stock preamplification-generated product was diluted (1:10) as per the manufacturers’ protocol and used for quantitative real-time polymerase chain reaction (qPCR).

Quantitative real-time PCR

miRNA abundance was quantified (in duplicate) on a CFX96 Touch™ real-time PCR Detection System (Bio-Rad, Hercules, CA) using the Applied Biosystems™ TaqMan™ Fast Advanced Master Mix (catalog no. 4444963; Applied Biosystems, Victoria, Australia) and TaqMan Advanced miRNA Assays (catalog no. A25576; Table 1) in a 20 μL reaction, following all manufacture’s protocol instructions. Data were excluded from the analyses if an SD >1 cycle between duplicates was obtained. For normalization, we firstly attempted to use the geometric mean (34) of three miRNAs (miR-361, miR-191, and miR-186) suggested as “stable miRNAs to be used as endogenous controls” by the Taqman Advanced miRNA Assay Protocol and previously used for normalization in exercise training studies using human skeletal muscle samples (13,35). However, expression of these three targets and their geometric mean were not stably expressed throughout time points of analysis in our experimental protocol (Table 2). Thus, we assessed and discussed miRNA expression as 2−ΔCt where each participants response was represented as the fold change relative to their individual Pre Ct values (ΔCt = (Ct target)time x − (Ct target)Pre) as previously adopted in the literature (35). We also presented the data normalized to the geometric mean of the three initially chosen reference miRNAs as 2−ΔΔCt (∆∆Ct = (Ct target − Ct geomean)time x − (Ct target − Ct geomean)Pre; Table 2) with the aim to present the distinct results pattern that would be obtained from data normalization using this method.

TABLE 1 - miRNAs analyzed and assay ID number.
miRNA Assay ID
hsa-miR-1-3p 477820_mir
hsa-miR-23a-3p 478532_mir
hsa-miR-133a-3p 478511_mir
hsa-miR-133b 480871_mir
hsa-miR-181a-3p 479405_mir
hsa-miR-186-5p 477940_mir
hsa-miR-191-5p 477952_mir
hsa-miR-206 477968_mir
hsa-miR-361-5p 478056_mir
hsa-miR-378a-5p 478076_mir
hsa-miR-486 478128_mir

TABLE 2 - Mean Ct values, SD between duplicates, and coefficient of variation (CV%) for skeletal muscle miRNA expression Pre, immediately (0 h), 4 h, and 8 h after exercise recovery following RE, HIIE, or CE.
miRNA Pre 0 h 4 h 8 h Mean Duplicates SD Mean CV%
RE HIIE CE RE HIIE CE RE HIIE CE RE HIIE CE
miR-186-5p 26.32 ± 1.18 26.11 ± 1.26 26.05 ± 0.93 26.62 ± 1.71 26.13 ± 1.3 26.01 ± 1.04 25.88 ± 1.48 26.43 ± 1.8 25.83 ± 1.2 25.58 ± 1.18 25.53 ± 1.19 25.61 ± 1.46 0.09 4.96
miR-191-5p 25.98 ± 1.16 25.67 ± 1.06 25.69 ± 0.8 25.49 ± 0.89 25.69 ± 1.16 25.45 ± 0.96 25.01 ± 1.4 25.24 ± 1.29 24.8 ± 1.15 24.3 ± 1.22 24.27 ± 1.21 24.64 ± 1.62 0.11 4.96
miR-361-5p 26.51 ± 0.81 26.3 ± 0.72 26.17 ± 0.42 26.49 ± 0.7 26.52 ± 0.95 26.18 ± 0.54 26.26 ± 1.1 26.43 ± 1.26 26.05 ± 0.82 25.91 ± 0.92 25.78 ± 1.12 26.06 ± 1.15 0.09 3.39
miR-1-3p 16.32 ± 0.99 16.18 ± 1.01 16.08 ± 0.82 16.44 ± 1.05 16.21 ± 1.24 16.02 ± 1.03 16.17 ± 1.42 16.65 ± 1.4 15.89 ± 0.96 15.72 ± 0.92 15.58 ± 1.28 15.81 ± 1.58 0.11 7.05
miR-23a-3p 19.77 ± 0.86 19.52 ± 0.72 19.82 ± 0.79 19.61 ± 0.82 19.79 ± 1.24 19.85 ± 0.42 19.55 ± 0.99 19.66 ± 0.64 19.43 ± 1.17 19.25 ± 0.98 19.24 ± 1.05 19.12 ± 1.06 0.42 4.64
miR-133a-3p 16.55 ± 1.09 16.3 ± 1.04 16.22 ± 1.11 16.51 ± 1.48 16.38 ± 1.33 16.5 ± 0.92 16.42 ± 1.38 16.84 ± 1.63 16.21 ± 1.12 16.21 ± 0.95 15.93 ± 1.06 16.11 ± 1.5 0.25 7.22
miR-133b 21.95 ± 0.83 21.5 ± 1 21.45 ± 0.95 21.7 ± 0.92 21.78 ± 0.85 21.72 ± 0.64 21.77 ± 0.72 22.31 ± 1.03 21.58 ± 1.13 21.64 ± 0.71 21.31 ± 0.51 21.34 ± 0.89 0.17 3.97
miR-181a-3p 29.33 ± 0.82 29 ± 0.93 28.95 ± 0.46 29.47 ± 1.17 29.26 ± 1.18 29.17 ± 0.55 28.88 ± 1.14 29.56 ± 1.82 28.7 ± 0.91 28.2 ± 0.56 28.23 ± 0.79 28.46 ± 0.96 0.11 3.57
miR-206 20.87 ± 1.41 21.03 ± 1.45 21.41 ± 1.53 21.11 ± 1.62 21.41 ± 1.49 20.95 ± 1.29 20.85 ± 1.78 21.33 ± 1.52 20.74 ± 1.49 20.08 ± 1.41 20.55 ± 1.37 21.27 ± 1.13 0.34 6.80
miR-378a-5p 24.73 ± 0.9 24.39 ± 0.73 24.31 ± 0.62 24.65 ± 1.21 24.44 ± 0.92 24.39 ± 0.51 24.34 ± 0.95 24.89 ± 1.45 24.28 ± 1.16 24.46 ± 0.78 24.11 ± 0.81 24.14 ± 1.12 0.09 3.80
miR-486 23.82 ± 1.02 23.48 ± 1.07 23.63 ± 0.8 23.33 ± 0.71 23.59 ± 0.81 23.56 ± 0.74 23.42 ± 1.12 23.64 ± 1.13 23.19 ± 0.98 22.95 ± 1.01 22.9 ± 0.78 22.97 ± 1.22 0.09 4.11
Ct values are expressed as mean ± SD. SD values between duplicates are presented as the mean of all SD between duplicates of qPCR analysis. Coefficient of variation = (SD of all Ct values/Mean of all Ct values × 100).

Statistical Analysis

Visual inspection techniques and the Shapiro–Wilk test were used to verify the presence of extreme observations and the normality of the data. A mixed model was used for each dependent variable, with group and time as fixed factors and subjects as a random factor. In the occurrence of a significant F-ratio, simple contrasts were performed using the Bonferroni correction for P values. The significance level was defined as P < 0.05, and data are presented as mean and SD. Coefficient of variation of Ct values was calculated as SD/mean of all Ct values × 100. In addition, we calculated the mean effect sizes and respective confidence intervals (CI; Hedges correction applied) (36) of the differences between the peak change in miRNA expression of each condition, considering positive and negative CI (i.e., did not cross zero) as significant. Graphs were produced using GraphPad Prism 8.3.0 Software (GraphPad Software Inc., La Jolla, CA). Statistical analysis was performed using SAS version 9.3 for Windows (SAS Institute Inc., Cary, NC). Effect sizes and CI were calculated in Microsoft Excel for Mac 2020.

RESULTS

Mean Ct values, SD between duplicates, and coefficient of variation

Mean Ct values for each miRNA at Pre and immediately (0 h), 4 h, and 8 h after exercise following all exercise conditions (RE, HIIE, and CE) are presented in Table 2. Mean and SD of experimental duplicates were lower than 0.5 for all miRNAs and lower than 0.1 for miR-186-5p, miR-361-5p, miR-378a-5p, and miR-486 (Table 2). Mean coefficients of variation among all Ct values were lower than 5% for all miRNAs (Table 2).

miR-1-3p, miR-133a-3p, miR-133b, miR-378aa-5p, miR-23a-3p, miR-181a-3p, miR-206, and 486 expression

A main effect of time was found for miR-1-3p (P = 0.0077), miR-133a-3p (P = 0.04), and miR-133b (F = 2.89; P < 0.0415) where expression at 8 h was higher only when compared with Pre (Figs. 2A, C, D, respectively). There was also a main effect of time for miR-181a-3p (F = 10.01; P < 0.0001) and miR-486 (F = 8.23; P < 0.0001) in which 8 h was augmented when compared with all previous times (Figs. 2E, H) for all conditions. A main effect of time and of condition for both miR-23a-3p (F = 4.31 [P = 0.0078] and F = 3.41 [P = 0.0424], respectively) and miR-206 (F = 3.44 [P = 0.02] and F = 4.00 [P = 0.02], respectively) were also observed. miR-23a-3p expression was higher at 8 h when compared with Pre and 0 h values (Fig. 2B), and miR-206 expression was augmented at 8 h only compared with Pre (Fig. 2F). Regarding the main effect of condition, both targets showed lower expression after HIIE when compared with RE and CE conditions. miR-23a-3p effect size analysis showed a significant difference between the peak change of HIIE compared with peak change of RE (ES, −1.18; 95% CI, −2.25 to −0.11) and to peak change of CE (ES, −1.31; 95% CI, −2.40 to −0.23). Also, miR-206 effect size analysis showed a significant difference between the peak change of HIIE compared with peak change of RE (ES, −2.00; 95% CI, −3.29 to −0.71). Finally, there were no significant differences at any time point during recovery or between groups for miR-378a-5p expression (F = 2.35; P = 0.07; Fig. 2G).

F2
FIGURE 2:
miR-1-3p (A), miR-23a-3p (B), miR-133a-3p (C), miR-133b (D), miR-181a-3p (E), miR-206 (F), miR-378a-5p (G), and miR—486 (H) skeletal muscle expression Pre, immediately (0 h), 4 h, and 8 h after exercise recovery following RE, HIIE, or CE. Values expressed as 2−ΔCt relative to each individual Pre value and presented in arbitrary units (mean ± SD). aMain effect of time from Pre (P < 0.05). bMain effect of time from 0 h (P < 0.05). cMain effect of time from 4 h (P < 0.05). dMain effect of condition (P < 0.05).

Expression of endogenous controls (miR-186-5p, miR-191-5p, and miR-361-5p) selected a priori

There was a main effect of time for miR-186-5p (F = 6.37; P = 0.0007), miR-191-5p (F = 12.73; P < 0.0001), miR-361-5p (F = 4.90; P = 0.0038) and the geometric mean of all three miRNAs (F = 9.34; P < 0.0001), with 8 h higher than Pre and 0 h. miR-191-5p and the geometric mean of all three miRNAs were also higher at 8 h when compared with 4 h (Fig. 3).

F3
FIGURE 3:
miRNAs previously reported (13,35) and suggested by TaqMan miRNA Advanced Assay Protocol as endogenous controls. miR-186-5p (A), miR-191-5p (B), miR-361-5p (C), and geometric mean (D) of three suggested endogenous controls’ skeletal muscle expression Pre, immediately (0 h), 4 h, and 8 h after exercise recovery following RE, HIIE, or CE. Values expressed as 2−ΔCt relative to each individual Pre value and presented in arbitrary units (mean ± SD). aMain effect of time from Pre (P < 0.05). bMain effect of time from 0 h (P < 0.05). cMain effect of time from 4 h (P < 0.05).

Comparison of nonnormalized and normalized data

Contrasting expression patterns were observed between nonnormalized data with values normalized by the geometric mean of suggested and previously reported endogenous controls (miR-186-5p, miR-191-5p, and miR-361-5p; Table 2). Although nonnormalized data showed a significant increased expression for all conditions at 8 h compared with PRE for miR-1-3p, normalized data showed a main effect of time (F = 4.11; P = 0.0098) where 4-h expression decreased compared with Pre and 0 h. A distinct expression pattern for miR-133b was also observed where nonnormalized data showed a significant increased expression for all conditions at 8 h compared with PRE, whereas normalized data showed a main effect of time (F = 5.11; P = 0.0029) in which expression values at 4 and 8 h were decreased compared with Pre. Also, although there were no significant differences for miR-378a-5p in nonnormalized data, there was a main effect of time for (F = 6.76; P = 0.0005) with a decrease at 4-h expression compared with Pre and at 8 h compared with both Pre and 0 h levels for normalized data. Finally, although nonnormalized data showed significant increases after all conditions for miR-23a, miR-133a-3p, miR-181a-3p, miR-206, and miR-486, there were no significant changes in normalized data (P > 0.05). All contrasting results are presented in Table 3.

TABLE 3 - Nonnormalized (2−ΔCt) and normalized (2−ΔΔCt) data for skeletal muscle miRNA expression immediately (0 h), 4 h, and 8 h after exercise recovery after RE, HIIE, or CE
miRNA Data Format 0 h 4 h 8 h
RE HIIE CE RE HIIE CE RE HIIE CE
miR-1-3p Nonnormalized (2−ΔCt) 1.18 ± 0.71 1.13 ± 0.65 1.11 ± 0.45 1.50 ± 1.12 0.81 ± 0.58 1.47 ± 1.01 1.78 ± 1.03 a 1.39 ± 0.96 a 1.53 ± 0.97 a
Normalized/geomean (2−ΔΔCt) 0.92 ± 0.28 1.08 ± 0.29 1.00 ± 0.25 0.78 ± 0.21 a, b 0.70 ± 0.09 a,b 0.91 ± 0.34 a,b 0.87 ± 0.47 0.83 ± 0.19 0.88 ± 0.34
miR-23a-3p Nonnormalized (2−ΔCt) 1.16 ± 0.41 0.78 ± 0.67 c 1.07 ± 0.52 1.31 ± 0.65 0.94 ± 0.43 c 1.53 ± 1.00 1.64 ± 0.70 a,b 1.07 ± 0.52 a,b,c 1.85 ± 0.84 a,b
Normalized/geomean (2−ΔΔCt) 1.14 ± 0.89 0.74 ± 0.31 0.94 ± 0.24 0.97 ± 0.66 1.22 ± 0.54 1.05 ± 0.41 0.73 ± 0.20 0.78 ± 0.35 0.93 ± 0.34
miR-133a-3p Nonnormalized (2−ΔCt) 1.37 ± 0.95 1.03 ± 0.49 0.93 ± 0.55 1.47 ± 0.98 0.86 ± 0.65 1.27 ± 1.03 1.55 ± 1.14 a 1.44 ± 0.69 a 1.56 ± 1.38 a
Normalized/geomean (2−ΔΔCt) 1.03 ± 0.29 1.05 ± 0.33 0.80 ± 0.24 0.78 ± 0.29 0.75 ± 0.23 0.83 ± 0.34 0.69 ± 0.29 0.94 ± 0.89 0.83 ± 0.44
miR-133b Nonnormalized (2−ΔCt) 1.32 ± 0.74 0.98 ± 0.63 0.91 ± 0.60 1.34 ± 0.70 0.70 ± 0.47 1.27 ± 1.29 1.51 ± 0.98 1.37 ± 0.84 1.46 ± 1.34
Normalized/geomean (2−ΔΔCt) 1.07 ± 0.47 0.96 ± 0.38 0.78 ± 0.23 0.81 ± 0.26 a 0.64 ± 0.25 a 0.75 ± 0.33 a 0.68 ± 0.28 a 0.75 ± 0.47 a 0.83 ± 0.45 a
miR-181a-3p Nonnormalized (2−ΔCt) 1.24 ± 0.73 0.96 ± 0.51 c 0.97 ± 0.54 1.69 ± 1.09 1.22 ± 1.48 c 1.40 ± 1.01 2.49 ± 1.12 a,b,d 2.27 ± 1.56 a,b,d 1.83 ± 1.25 a,b,d
Normalized/geomean (2−ΔΔCt) 0.96 ± 0.40 0.92 ± 0.27 0.86 ± 0.32 0.96 ± 0.24 0.87 ± 0.49 0.96 ± 0.37 1.15 ± 0.38 1.11 ± 0.39 1.02 ± 0.36
miR-206 Nonnormalized (2−ΔCt) 0.92 ± 0.31 0.77 ± 0.49 1.44 ± 0.59 1.22 ± 0.74 0.82 ± 0.45 1.94 ± 1.56 1.83 ± 0.49 a 1.00 ± 0.42 a,c 1.90 ± 1.44 a
Normalized/geomean (2−ΔΔCt) 0.93 ± 0.44 1.02 ± 0.44 1.33 ± 0.67 0.76 ± 0.30 1.06 ± 1.03 1.94 ± 2.00 0.95 ± 0.48 0.77 ± 0.47 1.52 ± 1.69
miR-378a-5p Nonnormalized (2−ΔCt) 1.32 ± 0.72 1.01 ± 0.34 1.00 ± 0.40 1.46 ± 0.69 0.88 ± 0.68 1.32 ± 1.03 1.48 ± 1.05 1.34 ± 0.78 1.36 ± 0.76
Normalized/geomean (2−ΔΔCt) 0.99 ± 0.20 1.05 ± 0.29 0.89 ± 0.14 0.94 ± 0.34 a 0.74 ± 0.17 a 0.82 ± 0.30 a 0.66 ± 0.31 a,b 0.79 ± 0.39 a,b 0.81 ± 0.27 a,b
miR-486 Nonnormalized (2−ΔCt) 1.49 ± 0.65 1.06 ± 0.52 1.09 ± 0.29 1.53 ± 0.80 1.07 ± 0.73 1.59 ± 1.09 2.11 ± 1.12 a,b,d 1.75 ± 1.10 a,b,d 1.97 ± 1.28 a,b,d
Normalized/geomean (2−ΔΔCt) 1.33 ± 0.75 1.09 ± 0.53 1.04 ± 0.33 0.94 ± 0.28 1.01 ± 0.55 1.10 ± 0.42 0.97 ± 0.41 0.93 ± 0.47 1.16 ± 0.42
Nonnormalized data expressed as 2−ΔCt, where ΔCt = (Ct target)time x − (Ct target)Pre, and normalized data to the geometric mean of the three endogenous controls miRNAs selected a priori expressed as 2−ΔΔCt, where ∆∆Ct = (Ct target − Ct geomean)time x − (Ct target − Ct geomean)Pre. Values presented in arbitrary units (mean ± SD).
aMain effect of time from Pre (P < 0.05).
bMain effect of time from 0 h (P < 0.05).
cMain effect of condition (P < 0.05).
dMain effect of time from 4 h (P < 0.05).

DISCUSSION

Exercise-induced miRNAs play a fundamental role in the transcriptional/translational regulation of target mRNAs that form the mechanistic basis of skeletal muscle plasticity (9). This is the first study to directly compare the expression patterns of select skeletal muscle miRNAs related to exercise-induced adaptations with three distinct exercise modes in an extended temporal short-term time course (8 h after exercise) to explain the specificity in acute expression of such miRNAs. Our results showed similar expression patterns (i.e., upregulation) in miR-1-3p, miR-133a-3p, miR-133b, miR-378aa-5p, miR-181a-3p, and miR-486 between RE, HIIE, and CE conditions despite inherent differences in contractile regimen between exercise modalities. On the other hand, our results also suggest a lower miR-23a-3p and miR-206 expression after HIIE compared with RE and CE. We also demonstrated that the comparable postexercise changes in specific miRNAs between RE, HIIE, and CE protocols were mainly confined to the 8-h postexercise period. Collectively, our findings 1) suggest there is no short-term expression pattern specificity for miR-1-3p, miR-133a-3p, miR-133b, miR-378aa-5p, miR-181a-3p, and miR-486 in human skeletal muscle between RE, HIIE, and CE; 2) indicate that RE has a higher effect on the expression of miR-23a-3p and miR-206 than HIIE; and 3) show a new short-term “peak” of expression at 8 h after divergent exercise modes for the assessed miRNAs.

Specialized skeletal muscle phenotypes are considered the result of specific exercise-induced cumulative and coordinated cellular transcriptional and posttranscriptional activity after each exercise bout, including miRNA expression (6). In the present study, we observed no specificity in miRNA expression profile with miR1-3p, miR-133a-3p, miR-133b, miR-181a-3p, and miR-486 similarly upregulated from Pre with both RE, HIIE, and CE protocols during short-term recovery. As many of these miRNAs are implicated in the regulation of muscle satellite cell activity (muscle stem cell population implicated in the control of muscle repair and hypertrophy) (37,38), the increase in expression of these miRNAs after RE was expected. However, the nonspecificity in expression of miR-1-3p, miR-133a-3p, miR-133b, miR-181a-3p, and miR-486 after HIIE was unexpected, considering this exercise modality is established to principally activate molecular pathways involved in energy metabolism (5) and does not induce the same magnitude of skeletal muscle hypertrophy as RE-based training (39). Furthermore, considering the likely potential for CE to induce an attenuated molecular anabolic response compared with RE alone (40), the nonspecificity in the expression of these targets after CE was also unexpected and suggests there is no molecular interference in the regulation of these miRNAs targets. Such findings may relate to the fact that one unique miRNA can interact with distinct mRNA targets and then participate in multiple biological processes. For example, miR-133a has been implicated in both skeletal muscle satellite cell activity (41) and mitochondrial biogenesis, exercise tolerance, and responses to aerobic exercise training (25). The nonspecificity might also be due to evidence showing that HIIE and CE can also stimulate satellite cell activity in skeletal muscle (42,43). In addition, we used an HIIE protocol rather than conventional, continuous long duration (>30 min) and submaximal-intensity (~70% V˙O2peak) aerobic exercise. In this regard, the higher intensity and repeated contractile stimulus during HIIE closely resemble RE-induced contractile activity (44) and therefore might induce different fiber recruitment when compared with moderate-intensity continuous HIIE protocols (27). On the other hand, only miR-23a-3p and miR-206 presented lower expression after HIIE when compared with RE and CE. These results are aligned with previous work showing either a decrease or no change in miR-23a and miR-206 expression (10,45) after endurance exercise. Given the upregulation in the expression of these two mRNAs has been more pronounced after RE and CE, it is plausible to suggest that miR-23a and miR-206 expression might be more responsive to the RE stimulus.

Although no other work has directly compared the three exercise protocols, our findings are supported by recent single-mode studies reporting increases in miR-133a and miR-206 expression after a bout of RE (13) and in miR-1, miR-133a, miR-133b, and miR-181a expression after an acute HIIE bout (10,45), and we previously reported increased miR-23a, miR-133b, miR-181a, and miR-486 expression 4 h after a single session of CE with protein feeding (25). However, opposite responses have also been shown in the literature with a decrease or no change in miR-1, miR-133a, miR-133b, miR-181a-5p, and miR-206 expression after RE (15,46); miR-133b after endurance exercise (10,45); and miR-23a, miR-133a, miR-133b, miR-181a, and miR-486 in the placebo condition (i.e., without protein ingestion) of our previous study (25) and in work by Fyfe et al. (17). Although such disparity could be a result of differences between experimental designs, conflicting results have been demonstrated even between studies with similar participant (e.g., age and training status) and exercise protocol (e.g., sets and repetitions) characteristics (such as our current work compared with previous RE studies [15,46]). Thus, we suggest that the vast disparity among results may relate to the inherent individual responsiveness (intersubject variability) in such molecular mechanisms. To exemplify this premise, the aforementioned miRNAs also have been shown to enhance IGF-1/Akt/mTOR signaling pathway activation (47–49), which is involved in the exercise-induced modulation of myofibrillar protein synthesis rates and muscle growth (6). We recently demonstrated that between-participant variability in such muscle growth responses can be up to 40-fold greater than intraparticipant variability in trained individuals after an RE training program (50). Collectively, this demonstrates the potential for marked variation and heterogeneity in individual miRNA expression responses from small and separate studies that may, over time, be involved in the heterogeneity observed in muscle growth responses. In addition, the disparity in miRNA responses between studies in the literature highlight the complexity in the multiple miRNA-mRNA networks regulating diverse cellular processes that emphasize the need for more intrasubject designs comparing different exercise protocols with larger sample sizes.

Another new discovery from our work was the advancement in current understanding regarding the acute time course of miRNA responses with divergent exercise modalities. Although accumulating evidence continues to implicate miRNAs in the mechanistic basis of exercise adaptive responses (10–17,45), current knowledge is somewhat limited by a lack of temporal resolution with most studies in the literature only measuring postexercise miRNA expression at a single or two closely aligned time points. Indeed, no definitive time course for exercise-induced skeletal muscle miRNA expression currently exists. Our current work showed that miRNA transcriptional modulation for the significantly altered miRNAs among our targeted set occurred mainly at 8 h after exercise. It is important to highlight that the differences in miRNA expression discussed above between our results and the literature may be also related to the different time course of analysis between studies. Although previous work showed differences mainly at 3 h, 4 h, and/or 6 h after exercise, we showed a later upregulation at 8 h. The basis for this temporal response is unknown and, in some cases, difficult to reconcile. For instance and as conveyed previously, miR-1, miR-133a, miR-133b, miR-181, miR-206, and miR-486 (i.e., miRNAs significantly altered) play key roles in skeletal muscle satellite cell proliferation and differentiation (18–24,51), and therefore, the temporal response of these miRNAs after exercise may be related to their regulation of proteins within this signaling nexus. The satellite cell cycle is mainly controlled by the MRFs (MyoD, MyoG, Myf5, and Myf6/MRF4) (52), which are also expressed in skeletal muscle between 4 and 8 h after both RE and HIIE (53–55). In this regard, it has been demonstrated that MRF activity is intrinsically involved with miRNA expression dynamics (20,21,51). Therefore, it is possible that miRNA expression was confined to 8 h after exercise in our study, as it follows satellite cell transcriptional activity. Nonetheless, as expression changed only after 8 h, it is possible that more pronounced changes in miRNAs may occur at even later time points.

Findings from our current work also advance knowledge of the processes for normalizing exercise-induced miRNA expression. A reliable normalization method is paramount to reduce data variability due to any associated issues with tissue sampling, RNA quality, and experimental error, and thus allow for the identification of the actual changes in miRNA expression (34). We firstly chose our miRNA “housekeeping” targets based on previously published work (13,35) and according to the Taqman Advanced miRNA Assay Protocol (i.e., “stable miRNAs to be used as endogenous controls”). In contrast to previous work, we showed that the geometric mean of the expression (2−Δct related to Pre) of miR-186-5p, miR-191-5p, and miR-361-5p increased significantly at 8 h after all exercise protocols when compared with all previous time points. To determine the possible influence of this unstable expression pattern, we compared the analysis between normalized and nonnormalized data. As presented in Table 3, normalizing data by these miRNAs alters the expression pattern of target miRNAs of interest not only at 8 h (i.e.: when the geometric mean expression levels are significantly increased) but also at other time points in which there were no significant increases. Consequently, and as used previously in the literature (35), we assessed expression of miRNAs of interest as 2−ΔCt where each participant’s response was represented as the fold change relative to their individual Pre Ct values to discuss our findings. As we used the same assays for RNA extraction, cDNA synthesis, and PCR reactions, as well as the same normalization strategy (i.e., geometric mean of three targets), it is unlikely that the divergent results compared with the previous studies cited (13,35) were due to protocol differences or experimental errors. Also, it is noteworthy that the mean coefficient of variation (CV%; Table 3) for those targets in our data is low (miR-186-5p, 4.96%; miR-191-5p, 4.96%; and miR-361-5p, 3.39%) and even similar than some of those previously reported by D’Souza et al. (56) (miR-186-5p, 3.91%; miR-361-5p, 4.23%) as stably expressed after RE and protein feeding. The discrepancy in findings therefore likely relates to the expanded time course to 8 h in our work compared with 4 h in previous work (13,35). Thus, our findings both support (34) and confirm the need for further investigation of more robust, valid, and reproducible normalization strategies of miRNA expression in human skeletal muscle after exercise, particularly over extended time courses.

Despite the novel findings reported here, the present study has some limitations. First and foremost, although we acknowledge that the unstable expression of the geometric mean of our housekeeping miRNAs limits the discussion and extrapolation of our data, one of our central aims was to advance current knowledge of the time course of expression of housekeeping miRNA routinely used in the research field. Second, our small sample size (n = 9) may have been a confounding factor affecting the point-estimate variability of our miRNA due to high between-subject variations in the expression of the selected miRNA. Nevertheless, we believe that using a counterbalanced crossover design may have mitigated the effect of the between-subject variability, increasing the internal validity of our study. In addition, we calculated the mean effect size and CI (Hedges correction applied) (36) of the differences in the peak change between conditions for each miRNA. We considered significant CI as those that did not cross zero. We observed lower expression of miR-23a-3p and miR-206 with HIIE compared with RE and CE, which was supported by the reported main effect of condition. Finally, we only recruited untrained, young men. Although we acknowledge that miRNA expression patterns may be different in other populations (such as trained individuals), we believe that choosing this population and including a familiarization period aiming to minimize the nonspecific molecular responses that might be produced by an unaccustomed exercise bout allowed us to minimize potential bias in the acute postexercise responses that could be caused by a previous exercise training period.

In summary, our results provide new information on the specificity of miRNA responses with diverse exercise modalities and reveal that there is no specificity in early acute skeletal muscle miR-1-3p, miR-133a-3p, miR-133b, miR-378aa-5p, miR-181a-3p, and miR-486 expression between RE, HIIE, or CE in untrained individuals and shows that this expression modulation occurs mainly at 8 h after exercise. Our data also indicate that RE has a higher effect on the expression of miR-23a-3p and miR-206 than HIIE. Such insights are important to help build a molecular basis of adaptation responses with each exercise type. Because miRNA expression is just one of the multiple mechanisms involved in the gene expression regulation in the skeletal muscle after exercise at transcriptional and posttranscriptional level (7), future studies that simultaneously measure miRNA expression with other mechanisms, such as DNA methylation and histones modifications, and their relationship with mRNA expression and satellite cells activity will provide greater insight into the transcriptional pathways preferentially activated/deactivated after different exercise modes.

The authors would like to express gratitude for the São Paulo Research Foundation (grants nos. 2017/01297-8 and 2018/16513-0 to G. D. T. and 2018/12150-0 to C. A. L.). C. A. L. also was supported by the National Council for Scientific and Technological Development (grant no. 302801/2018-9). C. U. was supported by the National Council for Scientific and Technological Development (grant no. 406609/2015-2).

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

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Keywords:

MOLECULAR SIGNALING; EPIGENETICS; INTERFERENCE EFFECT; HYPERTROPHY

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