Skeletal muscle is a highly adaptable and dynamic tissue, which demonstrates marked responses to periods of disuse (e.g., illness or bed rest) and exercise training. One of the well-known adaptations to exercise training is the expansion of skeletal muscle microvascular networks (1–3) and improved endothelial function (4,5), which may be accompanied by greater maximal O2 delivery and utilization by skeletal muscle metabolic processes. Skeletal muscle microvascular networks actively regulate blood flow by sensing various stimuli (e.g., alterations in sheer stress, mechanical force, ion concentration), and adaptations as a result of exercise training enhance their ability to deliver required substrates (O2 and fuel sources), as well as remove metabolic by-products (CO2, H+, lactic acid). Although the underlying processes are not necessarily directly linked, improvements in exercise performance and metabolic health, demonstrated as a result of exercise training, occur in tandem with microvascular expansion and improved vascular function (1,6). Angiogenesis in skeletal muscle ensues as a result of traditional endurance exercise training; however, we (7) and others (1,8,9) have also demonstrated increases in capillary networks as a result of resistance exercise training.
The foremost adaptation to resistance exercise training is an increase in the cross-sectional area (CSA) at the limb, whole muscle, and fiber levels (7,10,11). The expansion of microvascular networks is important to maintain perfusion capacity of the hypertrophied skeletal muscle, such that an increase in CSA is accompanied by an increase in capillary-to-fiber ratio (C/Fi), effectively maintaining diffusion capacity across that fiber’s membrane. Expanded microvascular networks may also facilitate hypertrophy by ensuring the effective delivery of substrates required for muscle expansion (e.g., amino acids) (12). As such, it could be speculated that increases in skeletal muscle vascularization may be required to facilitate a hypertrophic response to stimuli such as resistance exercise training. On the other hand, metabolic stressors (e.g., ATP turnover, or reduced PO2, etc.) are potent stimuli for microvascular expansion. For example, increases in muscle fiber CSA resulting in lower PO2 could elicit an up-regulation of pathways involving hypoxia-inducible factor 1α (HIF1α) and vascular endothelial growth factor (VEGF) to promote angiogenesis (13). Consequently, it could also be speculated that microvascular expansion occurs in response to muscle growth, representing a compensatory adaptation to maintain perfusion capacity.
Expansion of the skeletal muscle capillary network is inconsistently reported after prolonged resistance exercise training in young healthy individuals (8–10,14). Moreover, the time course of these adaptations has never been investigated in humans. Therefore, the purpose of this study was to determine the temporal responses of angiogenesis in skeletal muscle in healthy young men before and after 2, 4, 8, and 12 wk of resistance exercise training. We hypothesized that prolonged resistance exercise training would augment the microvascular network to maintain, but not increase O2 delivery and/or perfusion capacity as demonstrated by the capillary-to-fiber perimeter exchange index (CFPE index). In addition, we have previously shown that protein supplementation augments the increase in skeletal muscle CSA after 12 wk of resistance exercise training (15). Therefore, as a secondary aim, we assessed whether dietary protein supplementation affects the temporal nature of microvascular adaptations over a 12-wk training period. We hypothesized that because of the superior hypertrophic response in the protein group, a greater angiogenic response would ensue, again resulting in maintenance of fiber perfusion capacity.
Thirty-six healthy young men (22 ± 1 yr) participated in a 12-wk resistance exercise training program, with (n = 18) or without (n = 18) additional protein supplementation. Medical history was evaluated and a fasting blood sample was taken; participants were excluded when glycated hemoglobin content exceeded 6.5% or fasting plasma glucose was >7 mmol·L−1. All subjects were recreationally active, performing sports on a noncompetitive basis between 2 and 5 h·wk−1. None had a history of participation in structured resistance exercise training to improve performance over the past 2 yr. All subjects were informed of the nature and possible risks of the experimental procedures before their written informed consents were obtained. This study was approved by the Medical Ethics Committee of the Maastricht University Medical Center and complied with the guidelines set by the Declaration of Helsinki as revised in 2013. This trial was registered at ClinicalTrials.gov as NCT02222415. This study was part of a larger project investigating the effects of dietary protein supplementation during long-term resistance exercise training for which data on muscle mass, strength, and muscle fiber size were previously published (15). Inclusion in the present study was based on the availability of ample muscle tissue to perform the analyses described hereinafter.
Throughout the 12-wk intervention period, subjects were randomly assigned in a double-blind manner to consume a 300-mL bottle containing either a placebo drink (PLA; n = 18) or protein drink (PRO; n = 18) daily immediately before sleep. On average, subjects consumed 98% ± 1% of the beverages, with no differences between groups. The PRO beverage contained 13.75 g of casein hydrolysate (Peptopro), 13.75 g of casein, 15 g of carbohydrate, and 0.1 g of fat (DSM, Delft, the Netherlands), providing 746 kJ of energy. The PLA was a noncaloric placebo beverage, as explained and discussed in the original article (15).
Supervised resistance exercise training was performed three times per week for a 12-wk period as previously reported (15). Briefly, the training sessions consisted of a 5-min warm-up on a cycle ergometer, four sets of leg press and leg extension (Technogym, Rotterdam, the Netherlands) with alternating two sets of chest press and horizontal row or vertical pull-down and shoulder press. Sessions ended with a 5-min cool down on the cycle ergometer. During the first week of the training period, the workload was increased gradually from 70% (10–15 repetitions) of 1-repetition maximum (1RM) to 80% of 1RM (8–10 repetitions). Thereafter, training was performed at 80% 1RM. Workload intensity was adjusted on the basis of the outcome of the successive 1RM tests (performed at weeks 4 and 8). In addition, workload was increased when >8 repetitions could be performed in three of four sets. Training sessions were, on average, well attended (PLA, 91% ± 1%; PRO, 90% ± 1%) with no differences between groups.
Seven days before the onset of the training (time 0) and after 2, 4, 8, and 12 wk of training, needle muscle biopsy specimens were sampled from each participant after an overnight fast. After local anesthesia (1% lidocaine), percutaneous needle biopsies (50–80 mg) were collected from the vastus lateralis, ~15 cm above the patella and 1–2 cm away from any previous biopsy sites (16). To prevent acute effects of the last training session, sessions 3 d before the biopsy sample were not performed at 2, 4, and 8 wk. Biopsy samples were embedded in Tissue-Tek (Sakura Finetek, Zoeterwoude, the Netherlands), frozen in liquid nitrogen–cooled isopentane (Sigma-Aldrich, Dorset, United Kingdom), and stored at −80°C for further histochemical analysis. A separate sample was snap frozen in liquid nitrogen for Western blotting and polymerase chain reaction (PCR) analyses.
Fiber type–specific capillary content
Cryosections 5 μm thick were cut at −20°C, with all samples from a given participant mounted on the same glass slide. Immunohistochemical staining was performed to determine fiber type–specific skeletal muscle capillarization. Slides were taken from the −80°C freezer and thawed for 30 min at room temperature. After fixation for 5 min with acetone (VWR), samples were air dried for 15 min. Slides were incubated for 45 min with CD31 (dilution 1/50; M0823; Dako, Glostrup, Denmark), then washed (3 × 5 min 0.05% Tween–phosphate-buffered saline (PBS)). After that, 45-min incubation with goat antimouse biotin (1/200, BA-2000; Vector Laboratories, Burlingame, CA) was started, and a wash was performed. Slides were then incubated with Avidin Texas Red (A2006, dilution 1/400; Vector Laboratories) and antibodies against MHC-I (A4.840, dilution 1/25; DSHB), and laminin (polyclonal rabbit anti-laminin, dilution 1/50; Sigma) for 45 min and washed. Finally, GAMIgM AlexaFluor488 and GARIgG AlexaFluor350 (Molecular Probes) were applied for 30 min. After the final washing, slides were mounted with Mowiol (Calbiochem). The staining procedure resulted in images with laminin in blue, MHC-I in green, and CD31 in red. Images were automatically captured at 10× magnification using an Olympus BX51 fluorescence microscope with customized spinning disk unit (DSU; Olympus) with an ultrahigh-sensitivity monochrome electron multiplier CCD camera (1000 × 1000 pixels, C9100-02; Hamamatsu Photonics).
Image acquisition was done by Micromanager 1.4 software, and images were analyzed with ImageJ. The images were recorded and analyzed by an investigator blinded to subject coding. In all sections, a minimum of 30 fibers was counted per fiber type, with longitudinal fibers excluded from analysis. Muscle fiber CSA was automatically determined for each fiber separately using ImageJ software (2009 National Institute of Health, Bethesda, MD). The number of capillaries was manually counted and expressed as capillary count (CC; number of capillaries in contact with each fiber), sharing factor (SF; number of fibers sharing each capillary), C/Fi (where the C/Fi = number of CC divided by the mean SF for each fiber), capillary density (CD; numbers of capillaries per square millimeter), and CFPE (number of capillaries per 1000-μm perimeter) as previously reported (17). For all fiber characteristics, average values were calculated for Type I and II fibers separately, for each subject and time point, with the exception of CD. Representative images of histochemical analyses are shown in Figure 1.
Muscle was homogenized, protein concentration was detected using the Bradford assay (18), and samples, along with a control sample, were prepared at 1 μg·μL−1. Whole-muscle homogenates were separated on a criterion gel% TRIS gels by electrophoresis using SDS-PAGE and transferred to Trans-blot turbo 0.2-μm nitrocellulose membranes (Bio-Rad). Membranes were incubated overnight at 4°C with the following commercially available antibodies prepared in 50% Odyssey blocking buffer (Li-Cor Biosciences Part No. 927-40000): endothelial nitric oxide synthase (eNOS, 1/1000, ab5589; Abcam), VEGF (Abcam 1/1000, ab46154), VEGF receptor 2 (VEGFR2, 1/1000, ab39256; Abcam), HIF1α (1/1000, ab463; Abcam), and α-tubulin (1/5000, ab40742; Abcam). After incubation, membranes were washed 2 × 15 min in 0.05% PBS–Tween 20 and 1 × 15 min with PBS. Membranes were then incubated for 1 h at room temperature with the appropriate secondary antibodies. After final washing, protein detection was performed using the Odyssey Infrared Imaging System (LI-COR Biotechnology, Lincoln, NE) and densitometry was quantified (Image Studio Lite Version 5.2). To limit variability, samples were detected from the same Western blot by cutting gels and transferring onto a single membrane where possible, with a standard control sample loaded on each gel and equal loading of protein verified using Ponceau staining. α-Tubulin was also detected on each membrane to verify consistent/equal loading (α-tubulin was analyzed separately and demonstrated no differences; therefore, analysis was done on absolute values of each protein). Detection of all membranes for a given target was done at the same time.
Quantitative reverse transcription PCR
Total RNA was isolated from 10–20 mg of frozen muscle tissue using TRIzol Reagent (Life Technologies, Invitrogen), and quantification was performed spectrophotometrically at 260 nm (NanoDrop ND-1000 Spectrophotometer; Thermo Fisher Scientific, Waltham, MA). RNA purity was determined as the ratio of readings at 260/280 nm. The first-strand cDNA was synthesized from 1 μg of RNA sample using the iScript cDNA synthesis kit (Bio-Rad). Taqman PCR was performed using the 7300 Real Time PCR system (Applied Biosystems, Foster City, CA), with 2 μL of cDNA (diluted five times) and Taqman Gene Expression Mastermix (Applied Biosystems) at a total volume of 25 μL. Gene Expression Assays (Applied Biosystems) for 18S, VEGF, VEGFR2, Hif1α, and eNOS are listed in Table, Supplemental Digital Content, Gene expression assays, http://links.lww.com/MSS/B61. Each sample was run in duplicate and the housekeeping gene 18S was used as an internal control. Thermal cycling conditions used included the following: 2 min at 50°C, 10 min at 95°C, followed by 40 cycles at 95°C for 15 s and 60°C for 1 min. The threshold cycle (Ct) values of the target gene were normalized to Ct values of the internal control 18S, and final results were calculated as relative expression against the standard curve. Statistical analysis for all mRNA data was performed on the delta Ct values. The muscle biopsy attained before the training began (0 wk) was given a value of 1, and fold changes at 2, 4, 8, and 12 wk were calculated for figure presentation.
Data are expressed as mean ± SEM. Student t-test was used to verify that groups were comparable at baseline. Repeated-measures ANOVA, with time (0, 2, 4, 8, and 12 wk) and dietary supplementation (PLA vs PRO) as factors was used to assess the effect of resistance training on skeletal muscle characteristics. In case of a significant interaction, separate analyses were performed: one-way repeated-measures ANOVA to assess time effects (e.g., the effects of 12 wk of training) within groups and unpaired t-tests to compare PLA versus PRO at specific time points. Significant time effects were further analyzed using paired t-tests. To provide the best possible insight into any relevant temporal changes and avoid any unwanted reduction in the power to detect such changes, no corrections for multiple testing were applied (19). Fiber types were analyzed separately, as Type II fibers demonstrate a more robust change in CSA in response to resistance exercise training when compared with Type I fibers (15). Statistical significance was set at P < 0.05. All data were analyzed and graphed using GraphPad Prism for Mac version 5.0 (San Diego, CA). In principle, all analyses were performed on n = 18 per group. In each figure legend, the number of samples included in the analysis is clearly indicated.
Fiber CSA and capillary networks
First, we aimed to characterize the effect of 2, 4, 8, and 12 wk of resistance exercise training with and without protein supplementation on skeletal muscle morphology (representative slides are presented in Fig. 1). As previously reported (15), muscle fiber CSA increased as a result of prolonged resistance exercise training. Twelve weeks of exercise training elicited a 15% ± 4% increase in CSA (P = 0.015) in Type I fibers, which was evident from 4 wk of training onward, with no further expansion observed as a result of PRO supplementation (Fig. 2A; time–group interaction, P = 0.28). Primarily, hypertrophy was demonstrated in Type II fibers (28% ± 5%; main effect of 12 wk of training, P < 0.0001), which was evident after 2 wk of training, and PRO tended to enhance this effect over PLA (Fig. 2D; time–group interaction, P = 0.078).
Next, we assessed the CC per fiber type. The CC per Type I fiber was significantly increased as a result of resistance exercise training (Table 1; main effect of 12 wk of training, P = 0.016) with no differences between PRO and PLA. Although numerically, CC per Type II fiber also seemed to increase, these changes did not reach statistical significance (Table 1; main effect of 12 wk of training, P = 0.17). Again, this finding was not dependent on PRO supplementation. Similarly, the calculated SF demonstrated significant changes in Type I fibers only, showing a small decline as a result of resistance training with no effect of PRO (Table 1; main effect of 12 wk of training, P = 0.024). Resistance training did not alter the CD in either PLA or PRO (Table 1; main effect of 12 wk of training, P = 0.405).
To further delineate the effect of resistance exercise training and PRO on the capillary networks, we examined the C/Fi in both Type I and II fibers. Interestingly, in both PLA and PRO, C/Fi significantly increased in Type I fibers as a result of resistance training (Fig. 2B, ~6%–12% increase; main effect of 12 wk of training, P = 0.001). Although the temporal response seemed different between groups, particularly at the 4-wk time point, no significant interaction was present (Fig. 2B; time–group interaction, P = 0.085). Notably, the increase in Type I fiber C/Fi was already evident after 2 wk of training (~6%). A significant increase in C/Fi as a result of resistance training was also demonstrated in the Type II fibers (Fig. 2E, ~9%–15% increase; main effect of 12 wk of training, P = 0.015), with no differences between PRO and PLA.
The CFPE index allows for quantitation of the capillary supply relative to the region of greatest resistance to oxygen flux, the capillary-to-fiber interface (20). Therefore, although the CFPE does not take into account tortuosity or branching of the capillaries, it may provide an indication on the overall effect of changes in the capillary network on the capillary supply, or “diffusion capacity” of muscle fibers (20). Despite the robust increase in muscle fiber size, no reduction was observed in the CFPE index as a result of 12 wk of exercise training. In fact, the increased C/Fi in conjunction with the slightly increased fiber CSA resulted in an increase in CFPE index in the Type I fibers that was borderline significant (Fig. 2C; main effect of 12 wk of training, P = 0.054), with no differences between PRO and PLA. Importantly, despite the significantly greater increase in CSA (Fig. 2D), the CFPE index was maintained in Type II fibers throughout the 12 wk of resistance exercise training in both the PLA and PRO groups (Fig. 2F).
Skeletal muscle mRNA expression and protein content
To determine the temporal changes on factors involved in the molecular signaling cascade associated with angiogenesis during the 12 wk of training, we assessed mRNA expression of VEGF, VEGFR2, HIF1α, and eNOS in both the PLA and PRO groups. VEGF mRNA expression was reduced in response to training relative to baseline (Fig. 3A; main effect of 12 wk of training, P = 0.008). Resistance exercise training resulted in an increase in the relative expression of VEGFR2 mRNA (Fig. 3B; P = 0.016). A significant increase in both HIF1α (Fig. 3C; main effect of 12 wk of training, P = 0.016) and eNOS (Fig. 3D; main effect of 12 wk of training, P = 0.010) mRNA expression was also observed in response to 12 wk of exercise training in both PLA and PRO. Post hoc tests showed that both VEGF and VEGFR2 mRNA expressions were different from baseline at all time points, whereas HIF1α and eNOS mRNA expressions were only different from baseline at week 12 (Fig. 3).
Finally, we aimed to determine the effect of resistance training on the content of proteins involved in the angiogenic signaling cascade (VEGF, VEGFR2, and HIF1α) and in the rate-limiting step for the production of the vasodilator nitric oxide (eNOS) with and without PRO supplementation. VEGF protein content was not significantly altered as a result of training in PLA or PRO (Fig. 4A, E). To further elucidate the effect on VEGF and its signaling cascade, we next examined the protein content of its main receptor, VEGFR2. No changes were observed in the receptor content in either the PLA or PRO (Fig. 4B, F). HIF1α is highly regulated by cellular PO2 levels and remained overall unchanged in PLA. The PRO group demonstrated significantly higher HIF1α content when compared with PLA (Fig. 4C, G). Although there was no time–treatment group interaction and this effect therefore represented a main effect of treatment group (P = 0.02), HIF1α protein content did not seem different between PRO and PLA at baseline (P = 0.30). We next examined the protein response of eNOS, which is found primarily in the endothelial layer of vascular feed arteries, arterioles, and capillaries. Interestingly, eNOS followed a dissimilar trend in PLA and PRO as a result of resistance exercise training (Fig. 4D, H; time–group interaction, P = 0.049); PRO demonstrated a significant increase in eNOS at 2 (P < 0.01) and 8 wk (P < 0.05) compared with PLA. No significant change in eNOS was demonstrated as a result of training in PLA, although a trend (P = 0.14) was observed at 4 wk.
This study demonstrates expansion in skeletal muscle microvascular networks as a result of 12 wk of resistance exercise training, some of which was evident after only 2 wk of training. Interestingly, microvascular adaptations followed the same temporal pattern as the training-induced muscle fiber hypertrophy. Dietary PRO supplementation did not affect the extent or alter the temporal nature of these microvascular adaptations. Importantly, we provide evidence that skeletal muscle adapts to maintain the CFPE index and CD through the expansion of microvascular networks in response to resistance exercise training. In young men, increases in fiber CSA and capillarization occur in tandem, likely to preserve overall diffusion capacity for O2 and for the transport of substances that rely on receptor or transporter-mediated processes (i.e., insulin and glucose) (6).
Although it is well established that resistance exercise training promotes adaptive hypertrophy in the trained skeletal muscle (21,22), discrepancies remain on its effect on microvasculature, particularly in young healthy individuals (8–10,14). Although angiogenesis may occur to some extent with appropriate intensity and duration of resistance exercise training (8), the timeline of this response remains unknown. Muscle hypertrophy may be facilitated by the expansion of vascular networks, which ensures the effective delivery of substrates required. However, it could also be speculated that angiogenesis occurs in response to muscle growth to maintain diffusion capacity. In addition, it has previously been demonstrated that increases in CD are proportional to increases in mitochondrial volume, again a response likely aimed at maintaining the metabolic capacity of the fiber as both O2 delivery (capillaries) and O2 utilization (mitochondria) are tightly linked under normal, healthy conditions (23).
To determine the temporal responses of angiogenesis in skeletal muscle in healthy young men, we examined muscle biopsies before and after 2, 4, 8, and 12 wk of resistance exercise training. Here, we confirm that training effectively induced muscle fiber hypertrophy, as evident by the 15% ± 4% increase in Type I and the 28% ± 5% increase in Type II muscle fiber CSA. Interestingly, the increase in muscle fiber CSA was already evident after 2 (Type II) and 4 wk (Type I) of exercise training. Without concomitant changes in capillarization, this hypertrophic response would result in a relative decline of diffusion capacity of the tissue. With the interface of capillary and muscle fiber membrane representing the greatest barrier for diffusion (20), the CFPE index likely represents one of the critical determinants for overall muscle fiber diffusion capacity. Importantly, our data show that the CFPE index and CD are effectively maintained throughout the entire training period (Fig. 2, Table 1), because both the muscle fiber size and the C/Fi increased in response to exercise training in both the Type I and II muscle fibers. These findings indicate that merely 2 wk of resistance exercise training is sufficient to not only increase CSA but also to expand vascular networks, with the overall maintenance of diffusion capacity. In accordance, we (7,24) and others (25) have demonstrated effective hypertrophy and angiogenesis in response to resistance exercise training in older men, where CFPE index was not only maintained but also increased in both Type I and II fibers (7), in accordance with previous literature (17). This may be explained by the fact that older individuals demonstrate smaller C/Fi and CFPE when compared with younger men (7,26,27), thereby offering a greater potential for exercise-induced adaptations.
We have previously shown that protein supplementation further enhanced Type II muscle fiber hypertrophy in response to a 12-wk training program in young men (15). Although statistical significance was not reached in the current analyses, the addition of PRO supplementation had an apparent effect on CSA in the present study as well (Fig. 2). Importantly, however, absolutely no effect of PRO supplementation on the overall CFPE relationship was detected. Although it could be speculated that increases in either vascularization or CSA would be detected at different time points with PRO when compared with PLA, our data indicate that the temporal changes in skeletal muscle capillarization did not differ between PLA and PRO. Maintenance of the CFPE would prevent a decrease in the O2 diffusing capacity that would manifest as a result of the additional increase in CSA due to PRO supplementation. According to our data and in agreement with our hypothesis, CFPE is as effectively maintained in both PLA and PRO, implying that PRO supplementation does not preclude the microvascular adaptive response to resistance exercise training in young healthy men. On the other hand, PRO did not enhance the microvascular response; CFPE, CC, and the C/Fi were differentially altered in PRO versus PLA, which was against our hypothesis. In this light, one could argue that PRO supplementation may have limited the need to (further) enhance angiogenesis in the PRO group, because effective delivery of substrates was already accomplished through increased availability of plasma amino acids. Thus, whereas angiogenesis is not limited by hypertrophy, the degree of hypertrophic response is also not limited by the angiogenic response. The overall lack of effect of PRO supplementation on the microvascular response seems to underline the idea that angiogenesis is a tightly regulated process that, though related to changes in fiber size, is likely dependent on multiple other factors, aimed at maintaining the overall metabolic capacity of a muscle fiber. Given the tendency for differences between the PLA and PRO groups only toward the end of the 12-wk training program, it would be of interest to establish the potential effects of protein supplementation during a more prolonged (e.g., 6–12 months) training program.
Although the overall morphological effect of resistance exercise training with and without PRO supplementation did not differ, the molecular signaling cascades demonstrated some discrepancies. Although the protein contents of VEGF and VEGFR2 did not change, in accordance with the previously demonstrated temporal nature of these proteins (28), both HIF1α and eNOS protein contents were significantly different between PLA and PRO (Fig. 4). HIF1α was significantly elevated in PRO versus PLA throughout the intervention, whereas eNOS demonstrated significant interaction. Although the main effect of PRO on HIF1α would suggest that any difference between groups was already present at baseline, between-group comparisons at baseline revealed no differences for HIF1α (or any other variable). HIF1 is a DNA transcription factor composed of two subunits, one of which is primarily regulated by hypoxia (HIF1α) (29), although many other factors also play a role in its regulation (29) (see Szade et al.  for a review on this topic). Genes regulated by HIF1 are involved in the processes of angiogenesis and metabolism (31), and exercise training alters the expression of these genes (32). Although the physiological relevance of elevated HIF1α in response to PRO in this study remains speculative, it potentially signifies a limitation or reduction in the capacity of O2 transport in the PRO group, when CSA is at its highest as a result of the additive effects of training and supplemental PRO (as could be suggested from Fig. 2A, D) where groups tend to differentiate toward the 12-wk time point. As shown in Figure 4C, it seems that the largest differences in HIF1α are observed at 12 wk, although caution should be taken in this approach because the statistical analyses indicated an overall main effect. However, the expression of HIF1α in skeletal muscle is higher in glycolytic (Type II) fibers (33), and, as we have previously shown that 12 wk of resistance exercise training resulted in a higher expression of Type II fibers (15), fiber type–specific expression of HIF1α likely explains the current findings.
Resistance exercise training resulted in significant increases in VEGFR2, eNOS, and HIF1α mRNA in both groups, whereas VEGF mRNA relative expression was reduced as a result of 12 wk of training. eNOS protein content demonstrated an interaction, with the PRO group demonstrating higher eNOS at 2 and 8 wk when compared with PLA. Elevated eNOS in the PRO group is in line with the fact that the CFPE did not demonstrate a temporal difference between PLA and PRO at 2 and 8 wk, whereas the CSA was already elevated, which seemed primarily driven by an increase in the Type II fibers of the PRO group, implying angiogenesis in this group to maintain CFPE (Fig. 2). Increases in eNOS protein content have been associated with increases in insulin-stimulated nitric oxide production in the endothelium, a marker of metabolic health (34). The literature clearly demonstrates that resistance training is an effective means of maintaining or increasing muscle mass and strength, as well as promoting metabolic health in both young (15,35) and older (diseased) populations (7,12,36). Resistance exercise training also improves endothelial function in healthy (4,37) and older populations (38,39). Maintenance of skeletal muscle mass and microvascular function are essential for healthy aging and prevention of disease. Undeniably, loss of muscle mass (3) is associated with a reduced quality of life and impaired metabolic health (40). Furthermore, muscle fiber capillarization at baseline is strongly related to muscle fiber hypertrophy during prolonged resistance-type exercise training in older men (12). Importantly, though, we have previously demonstrated that with long-term resistance exercise training, both CSA and microvascular networks undergo expansion (7). It is unclear to what extent expansion of microvascular networks within the trained skeletal muscle accounts for improved metabolic health (e.g., insulin sensitivity), because microvascular expansion as a result of resistance exercise training is not a consistent finding (8,10,14). However, in the present study, using a fiber type–specific approach, we clearly show that prolonged resistance exercise training with and without protein supplementation effectively induces angiogenesis, likely supporting and/or facilitating metabolic improvements.
In the present study, we specifically aimed to assess the timeline of microvascular changes that likely support such metabolic adaptations, to determine whether an increase in capillarization may either facilitate or, alternatively, be compensatory to the hypertrophic process. We have previously shown that muscle fiber hypertrophy is not preceded by changes in myonuclear domain size (11), and the current data extend on these findings by showing that increases in muscle fiber CSA as well as C/Fi seem to occur in tandem and are already evident within 2 wk of resistance-type exercise training. In addition, it has previously been demonstrated that increases in CD are proportional to increases in mitochondrial volume (23), further demonstrating that morphological adaptations and the overall metabolic capacity of a fiber, from O2 delivery (capillary) to O2 utilization (mitochondria), are tightly regulated. In fact, all of the exercise-induced adaptations in the current study were so tightly regulated that we were unable to establish any temporal relationship in the sense of a change in one variable preceding a change in another variable, although it is important to note that mitochondrial volume was not assessed in the current study. In support, we did not observe any correlations between the changes in fiber size and capillarization irrespective of the time points analyzed, or between any of the signaling data and the changes in capillary networks (data not shown). The determination of a relationship between the signaling data and the changes in the capillary network may have been hampered by the time points at which biopsies were taken, which were aimed at identifying the angiogenic response of the capillary network to hypertrophy, but may have been suboptimal for the interpretation of the signaling data. As another, more general limitation, it should be noted that with a sample size of 36, it is possible that we were unable to detect subtle changes and/or differences between groups that are biologically relevant. Nonetheless, with five biopsies collected throughout the 12-wk period, we clearly show that muscle fiber CSA and capillary networks are enhanced in response resistance-type exercise training, with many of the adaptations already evident after 2 to 4 wk of training.
Although it remains to be determined what truly regulates the extent of muscle fiber hypertrophy, it is clear that the entire process is very timely, tightly, and efficiently regulated to ensure a well-balanced adaptation in terms of both structure and function, including metabolic health. Well-rounded exercise programs should include both endurance and resistance exercise training for optimal health gains, a belief held by many leading scientific organizations (American College of Sports Medicine, American Diabetes Association Canadian Society for Exercise Physiology) (41–43).
In conclusion, this study presents novel evidence that skeletal muscle capillarization and the molecular pathways involved are elevated by merely 2 wk of a 12-wk resistance exercise training program and occur in tandem with the hypertrophic response in young healthy men. Our findings provide further support for the promotion of resistance exercise training programs to increase muscle mass and improve muscle fiber vascularization, thereby optimizing both muscle mass and metabolic health.
The execution of the resistance training program in older adults was supported in part by DSM Food Specialties (Delft, the Netherlands) and the Dutch Olympic Committee (NOC*NSF, Arnhem, the Netherlands). The authors declare that the results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.
None of the authors declared any personal or financial conflict of interest regarding the material discussed in this article. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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