Author(s): WEI, J., SANER, N.J., TAYLOR, D.F., KUANG, J.J., LI, H.Z., GARNHAM, A., BISHOP, D.J., Institution: INSTITUTE FOR HEALTH & SPORT , Country: AUSTRALIA, Abstract-ID: 1411

INTRODUCTION:
Exercise-induced adaptations are initiated by homeostatic perturbations (e.g., changes in metabolites) that activate intracellular signalling and transcriptional responses. The magnitude and type of adaptations are determined by the exercise prescription, with exercise intensity being a central factor. Although studies have demonstrated that certain metabolites and genes are sensitive to exercise intensity, the effects of exercise intensity on both the global metabolome and transcriptome in human skeletal muscle have never been reported. Furthermore, the mechanisms underlying the blunted transcriptional response to exercise after training continue to be debated. To address these knowledge gaps, we combined the latest ‘omics’ techniques with an innovative study design that required participants to exercise above and below their maximal lactate steady state (MLSS) before and after training designed to increase their MLSS.
METHODS:
17 healthy and active males (30.9 ± 6.8 y; 36.9 ± 4.4 mL/min/kg; 78.4 ± 12.8 kg) first performed exercise below (Before Moderate; BM) and above (Before High; BH) their MLSS. Participants then underwent 8 weeks of high-intensity interval training (HIIT) before performing exercises below (After Moderate; AM) and above (After High; AH) their new MLSS. Muscle samples were collected pre-, immediately post-, and +4 hours post each exercise session. Metabolomics was performed on muscle samples collected pre- and immediately post-exercise, and RNA sequencing was performed on muscle samples collected pre- and +4 h post-exercise.
RESULTS:
Following BM, BH, AM, and AH, we identified 62, 71, 41, and 76 differentially expressed metabolites (DEMs) and 6165, 6247, 6271, and 3760 differentially expressed genes (DEGs), respectively. While there was considerable overlap, there were also distinct metabolic and transcriptomic signatures to moderate- and high-intensity exercise. An additional novel finding was that post-training, fewer DEMs but a similar number of DEGs were observed following moderate-intensity exercise (below the MLSS). In contrast, after 8 weeks of HIIT, there were a similar number of DEMs but almost half as many DEGs following high-intensity exercise (above the MLSS).
CONCLUSION:
In conclusion, exercise-induced metabolic and transcriptional responses in human skeletal muscle were modulated by exercise intensity and training status. For the first time, we have shown that HIIT reduces metabolic perturbations but not the transcriptional response to moderate-intensity exercise (below the MLSS). However, the same HIIT dramatically reduced the transcriptional response, but not metabolic perturbations, to high-intensity exercise (above the MLSS). Our novel experimental design has allowed us to uncover a disassociation between metabolic perturbations and transcriptional signatures in response to different exercise intensities.