Are there specific molecular adaptations of skeletal muscle to repeated sprint training in hypoxia?

Abstract

Introduction Athletes increasingly engage in repeated sprint training that consists of repeated short all-out effort (< 10 s) interspersed by short recoveries (< 60 s). When performed in hypoxia (repeated sprints in hypoxia, RSH), it may lead to greater training effect than in normoxia (RSN). However, the mechanisms underlying this superior training effect of RSH are unclear. Specifically, the role of muscle metabolic response to RSH is still debated and results are heterogeneous. Clarifying the molecular pathways of skeletal muscle adaptations to RSH may thus provide new insights into the role of hypoxia-induced response to training. Methods Two groups of healthy young men (randomized) performed three training sessions/week for three weeks. Each training session consisted in six series of six sprints (6 s effort/24 s rest) in either normoxia (RSN, n = 7) or normobaric hypoxia (FiO2 = ~13%, RSH, n = 9). Before and after the training period, vastus lateralis muscle biopsies, a repeated sprint ability (RSA) test and a Wingate test were performed. Metabolic muscle adaptations were studied with proteomics and western blotting. Results RSN and RSH similarly improved power output (p < 0.05) during the RSA test (RSN: + 7.2 ± 7.7% vs. RSH: + 7.9 ± 6.6%) and the Wingate test (RSN: + 1.3 ± 3.6% vs. RSH: + 4.4 ± 5.0%). Proteomics revealed a decrease in several processes involved in oxidative phosphorylation, confirmed by Western Blot with a reduction (p < 0.05) in complexes I (- 19 ± 30%) and V (- 15 ± 24%) protein levels in response to both RSN and RSH. RSN and RSH increased (p < 0.05) protein levels of the hypoxia inducible factor 1α (HIF-1α, + 111 ± 50%) and vascular endothelial growth factor A (VEGFa, + 91 ± 60%). Protein levels of the glycolytic enzyme hexokinase II increased (+ 119 ± 183%, p < 0.05) after both training types. Only RSH induced increased glucose transporter 4 (GLUT4, + 31 ± 18%, p < 0.05) protein level, suggesting specific glycolytic adaptations in response to hypoxia, supported by proteomics data. This specific adaptation may be triggered through the signaling of S100A protein family as we observed an increased S100A13 protein level (+ 467 ± 353%, p < 0.05) and Akt phosphorylation (+ 21 ± 21%, time x group interaction, p < 0.05) as well as several other S100A proteins in proteomics only after RSH training. Discussion/Conclusion To conclude, RSH did not exhibit in greater performance improvement compared to RSN. However, it further improved the glycolytic phenotype compared to RSN, possibly through specific S100A13 proteins signaling. Thus, we suggest that the reported superiority of RSH to RSN in the literature may stem from superior glycolytic adaptations triggered through the activation of a specific pathway involving S100A13 protein. The potential role of S100A13 protein in skeletal muscle adaptative responses to exercise is novel and the present results open new research perspectives in this field.