Molecular Metabolism (Jan 2024)
Molecular profiling of high-level athlete skeletal muscle after acute endurance or resistance exercise – A systems biology approach
Abstract
Objective: Long-term high-level exercise training leads to improvements in physical performance and multi-tissue adaptation following changes in molecular pathways. While skeletal muscle baseline differences between exercise-trained and untrained individuals have been previously investigated, it remains unclear how training history influences human multi-omics responses to acute exercise. Methods: We recruited and extensively characterized 24 individuals categorized as endurance athletes with >15 years of training history, strength athletes or control subjects. Timeseries skeletal muscle biopsies were taken from M. vastus lateralis at three time-points after endurance or resistance exercise was performed and multi-omics molecular analysis performed. Results: Our analyses revealed distinct activation differences of molecular processes such as fatty- and amino acid metabolism and transcription factors such as HIF1A and the MYF-family. We show that endurance athletes have an increased abundance of carnitine-derivates while strength athletes increase specific phospholipid metabolites compared to control subjects. Additionally, for the first time, we show the metabolite sorbitol to be substantially increased with acute exercise. On transcriptional level, we show that acute resistance exercise stimulates more gene expression than acute endurance exercise. This follows a specific pattern, with endurance athletes uniquely down-regulating pathways related to mitochondria, translation and ribosomes. Finally, both forms of exercise training specialize in diverging transcriptional directions, differentiating themselves from the transcriptome of the untrained control group. Conclusions: We identify a “transcriptional specialization effect” by transcriptional narrowing and intensification, and molecular specialization effects on metabolomic level Additionally, we performed multi-omics network and cluster analysis, providing a novel resource of skeletal muscle transcriptomic and metabolomic profiling in highly trained and untrained individuals.
