Document Type

Article

Publication Date

2023

Journal Title

Molecular Metabolism

Volume Number

79

DOI

https://doi.org/10.1016/j.molmet.2023.101857

Version

Publisher PDF: the final published version of the article, with professional formatting and typesetting

Disciplines

Engineering

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 a 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 the 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.

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