New insights into how muscles change during resistance training

The more we exercise our resistance, the fitter we become and so do our muscles. They adapt to the load and are able to perform better over a longer period of time. A research team from the University of Basel has now discovered new insights into these muscular adaptations through experiments carried out in mice.

Resistance training is beneficial. Regular training not only improves physical fitness and well-being, but also triggers profound muscle remodeling. This is reflected in the typical effects of training: muscles fatigue less quickly, provide more energy and use oxygen more efficiently.

“The adaptation of muscles to physical activity is a well-known phenomenon”, says Prof. Christoph Handschin, who has long researched muscle biology at the Biozentrum at the University of Basel. “We wanted to understand what exactly happens in the muscle during physical training.” He and his team have now published new insights in Nature’s Metabolism.

Training status is reflected in genes

In the current study, Handschin’s team compared muscles from untrained mice with those from trained mice and investigated how gene expression changes in response to exercise. “Since resistance training induces substantial muscle remodeling, we assumed that adaptations would be reflected in gene expression,” says first author Regula Furrer.

“However, in contrast to our expectations, the expression of relatively few, about 250 genes, was altered in muscles trained at rest compared to untrained muscles at rest. Surprisingly, about 1,800 to 2,500 genes were upregulated after an acute bout of exercise. How many and which genes respond largely depends on training status.”

Muscles respond differently to physical stress

In untrained muscles, for example, resistance training activates inflammatory genes, triggered by small injuries that cause what we know as muscle pain.

“We could not observe this in trained mice; instead, the genes that protect the muscle are more active. Thus, trained muscles respond completely differently to the stress of exercise,” explains Furrer. “They are more efficient and resilient – ​​in short, they can handle physical load better.”

Epigenetic pattern shapes muscle fitness

The question is: how is it possible that muscles respond so differently to resistance exercise depending on their training status? Scientists have found an answer in epigenetics.

Genes are activated or deactivated by so-called epigenetic modifications, chemical marks in the genome. “It was surprising that the epigenetic pattern between untrained and trained muscles is totally different and that many of these modifications occur in key genes that control the expression of several other genes”, emphasizes Furrer. Consequently, exercise activates a completely different program in trained muscles compared to untrained ones.

This epigenetic information determines how the muscle responds to training. “Chronic resistance training changes the epigenetic pattern of the muscle, both in the short and long term. It appears that trained muscles are prepared for prolonged training due to their epigenetic pattern. They respond much faster and work more efficiently”, he summarizes Handschin. “With each training session, muscular resistance increases.”

A low number of differentially expressed genes (DEGs) defines a trained WT muscle. The, All functional annotation clusters of proteins upregulated (orange) and downregulated (blue) in trained muscles with an enrichment score >2. ROS, reactive oxygen species. BExamples of proteins involved in the stress response in untrained (light gray) and unperturbed (dark gray) sedentary muscles (box plots show the median and 25th to 75th percentiles and whiskers indicate minimum and maximum values). wNumber of genes differentially expressed in unperturbed trained muscles (cutoff: FDR<0.05; log_two(FC)0.6). dAll functional annotation clusters of upregulated (orange) and downregulated (blue) genes in trained muscles with an enrichment score >2. It is, Motifs of ISMARA transcription factors that are among those with the highest and lowest activity. AU, arbitrary units. fNumber of genes after an acute bout of exercise exhaustion that are up-regulated (orange) and down-regulated (blue). gVenn diagram of all genes that are changed in unperturbed trained muscle (orange is upregulated and blue is downregulated) and those that are upregulated after an acute bout of maximal exercise (light color, dashed line). H, Heatmap of all differentially expressed genes in unperturbed trained muscles to visualize overlap with acutely regulated genes using hierarchical Euclidean distance clustering for rows. Data are from five biological replicates and represent means.in (unless otherwise noted). Proteomic data statistics were performed using Bayes-moderated empirical data t-statistics implemented in the R/Bioconductor limma package and for RNA-seq data with the CLC Genomics Workbench software. Exactly P proteomic data values ​​and z-ISMARA data scores are displayed in Source data. The asterisk indicates difference to control (Ctrl; pre-exercise condition) if not indicated otherwise: in B, ^*P<0.05, in It is, ^*z-score > 1.96 (Extended Data Fig. 1 and Supplementary Tables 14). Credit: Nature’s Metabolism (2023). DOI: 10.1038/s42255-023-00891-y

From mouse to human

Researchers have revealed how muscles adapt to regular resistance training over time in rats. The next step is to find out whether these results can also be transferred to humans. In competitive sports, biomarkers that reflect training progress can be used to improve training efficiency.

Most importantly, “understanding how healthy muscle works allows us to understand what goes wrong in disease,” says Handschin. This is crucial to unlocking innovative avenues for treating age-related muscle loss or disease.