Transcriptomic signatures of human single skeletal muscle fibers in response to high-intensity interval exercise.

Abstract

The heterogeneous fiber type composition of skeletal muscle makes it challenging to decipher the molecular signaling events driving the health- and performance benefits of exercise. We developed an optimized workflow for transcriptional profiling of individual human muscle fibers before, immediately after, and after 3 h of recovery from high-intensity interval cycling exercise. From a transcriptional point-of-view, we observe that there is no dichotomy in fiber activation, which could refer to a fiber being recruited or nonrecruited. Rather, the activation pattern displays a continuum with a more uniform response within fast versus slow fibers during the recovery from exercise. The transcriptome-wide response immediately after exercise is characterized by some distinct signatures for slow versus fast fibers, although the most exercise-responsive genes are common between the two fiber types. The temporal transcriptional waves further converge the gene signatures of both fiber types toward a more similar profile during the recovery from exercise. Furthermore, a large heterogeneity among all resting and exercised fibers was observed, with the principal drivers being independent of a slow/fast typology. This profound heterogeneity extends to distinct exercise responses of fibers beyond a classification based on myosin heavy chains. Collectively, our single-fiber methodological approach points to a substantial between-fiber diversity in muscle fiber responses to high-intensity interval exercise.NEW & NOTEWORTHY By development of a single-fiber transcriptomics technology, we assessed the transcriptional events in individual human skeletal muscle fibers upon high-intensity exercise. We demonstrate a large variability in transcriptional activation of fibers, with shared and distinct gene signatures for slow and fast fibers. The heterogeneous fiber-specific exercise response extends beyond this traditional slow/fast categorization. These findings expand on our understanding of exercise responses and uncover a profound between-fiber diversity in muscle fiber activation and transcriptional perturbations.