Highlights d Endurance training shifts the transcriptome significantly compared with controls d Sex differences in the muscle transcriptome are diminished with endurance training d Strength training appears to not have a large effect on the resting transcriptome d A comparative analysis reveals genes that could attenuate metabolic diseases

Human skeletal muscle characteristics such as fiber type composition, fiber size and myonuclear content are widely studied in clinical and sports related contexts. Being aware of the methodological and biological variability of the characteristics is a critical aspect in study design and outcome interpretation, but comprehensive data on the variability of morphological features in human skeletal muscle is currently limited. Accordingly, in the present study, m. vastus lateralis biopsies (10 per subject) from young and healthy individuals, collected in a systematic manner, were analyzed for various characteristics using immunohistochemistry (n=7) and SDS-PAGE (n=25). None of the analyzed parameters; fiber type % (FT%), type I and II CSA (fCSA), percentage fiber type area (fCSA%), myosin heavy chain composition (MyHC%), type IIX content, myonuclear content or myonuclear domain varied in a systematic manner longitudinally along the muscle or between the two legs. The average within subject coefficient of variation for FT%, fCSA, fCSA%, and MyHC% ranged between 13-18%, but was only 5% for fiber specific myonuclear content, which reduced the variability for myonuclear domain size to 11-12%. Pure type IIX fibers and type IIX MyHC were randomly distributed and present in <24% of the analyzed samples, with the average content being 0.1 and 1.1%, respectively. In conclusion, leg or longitudinal orientation does not seem to be an important aspect to consider when investigating human vastus lateralis characteristics. However, single muscle biopsies should preferably not be used when studying fiber type and fiber size related aspects given the notable sample to sample variability.

Mitochondrial derived peptides (MDPs) humanin (HN) and mitochondrial open reading frame of the 12S rRNA-c (MOTS-c) are involved in cell survival, suppression of apoptosis and metabolism. Circulating levels of MDPs are altered in chronic diseases such as diabetes type 2 and chronic kidney disease. Whether acute resistance (RE) or endurance (EE) exercise modulates circulating levels of HN and MOTS-c in humans is unknown. Following familiarization, subjects were randomized to EE (n=10, 45 min cycling at 70% of estimated VO2max), RE (n=10, 4 sets x 7RM, leg press and knee extension), or control (CON, n=10). Skeletal muscle biopsies and blood samples were collected before and at 30 minutes and 3 hours following exercise. Plasma concentration of HN and MOTS-c, skeletal muscle MOTS-c as well as gene expression of exercise related genes were analyzed. Acute EE and RE promoted changes in skeletal muscle gene expression typically seen in response to each exercise modality (c-Myc, 45S pre-rRNA, PGC-1α-total and PGC-1α-ex1b). At rest, circulating levels of HN were positively correlated to MOTS-c levels and age. Plasma levels of MDPs were not correlated to fitness outcomes (VO2max, leg strength or muscle mitochondrial (mt) DNA copy number). Circulating levels of HN were significantly elevated by acute EE but not RE. MOTS-C levels showed a trend to increase after EE. These results indicate that plasma MDP levels are not related to fitness status but that acute EE increases circulating levels of MDPs, in particular HN.

While manual quantification is still considered the gold standard for skeletal muscle histological analysis, it is time-consuming and prone to investigator bias. We assembled an automated image analysis pipeline, FiNuTyper (Fiber and Nucleus Typer), from recently developed deep learning-based image segmentation methods, optimized for unbiased evaluation of fresh and postmortem human skeletal muscle. We validated and utilized SERCA1 and SERCA2 as type-specific myonucleus and myofiber markers. Parameters including myonuclei per fiber, myonuclear domain, central myonuclei per fiber, and grouped myofiber ratio were determined in a fiber type-specific manner, revealing a large degree of gender- and muscle-related heterogeneity. Our platform was also tested on pathological muscle tissue (ALS) and adapted for the detection of other resident cell types (leukocytes, satellite cells, capillary endothelium). In summary, we present an automated image analysis tool for the simultaneous quantification of myofiber and myonuclear types, to characterize the composition of healthy and diseased human skeletal muscle.