Protein arginine methyltransferase biology in humans during acute and chronic skeletal muscle plasticity
Bibliographic record
Abstract
Protein arginine methyltransferases (PRMTs) are a family of enzymes that catalyze the methylation of arginine residues on target proteins. While dysregulation of PRMTs has been documented in a number of the most prevalent diseases, our understanding of PRMT biology in human skeletal muscle is limited. This study served to address this knowledge gap by exploring PRMT expression and function in human skeletal muscle in vivo and characterizing PRMT biology in response to acute and chronic stimuli for muscle plasticity. Fourteen untrained, healthy men performed one session of sprint interval exercise (SIE) before completing four bouts of SIE per week for 6 wk as part of a sprint interval training (SIT) program. Throughout this time course, multiple muscle biopsies were collected. We found that at basal, resting conditions PRMT1, PRMT4, PRMT5, and PRMT7 were the most abundantly expressed PRMT mRNAs in human quadriceps muscle. Additionally, the broad subcellular distribution pattern of PRMTs suggests methyltransferase activity throughout human myofibers. A spectrum of PRMT-specific inductions, and decrements, in expression and activity were observed in response to acute and chronic cues for muscle plasticity. In conclusion, our findings demonstrate that PRMTs are present and active in human skeletal muscle in vivo and that there are distinct, enzyme-specific responses and adaptations in PRMT biology to acute and chronic stimuli for muscle plasticity. This work advances our understanding of this critical family of enzymes in humans. NEW & NOTEWORTHY This is the first report of protein arginine methyltransferase (PRMT) biology in human skeletal muscle in vivo. We observed that PRMT1, -4, -5, and -7 were the most abundant PRMT mRNAs in human muscle and that PRMT proteins exhibited a broad subcellular localization that included myonuclear, cytosolic, and sarcolemmal compartments. Acute exercise and chronic training evoked PRMT-specific alterations in expression and activity. This study reveals a hitherto unknown complexity to PRMT biology in human muscle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".