Characterizing Protein Arginine Methyltransferase Expression, Localization, and Function During Myogenesis
Bibliographic record
Abstract
Protein arginine methyltransferases (PRMTs) play a critical role in the development of skeletal muscle. Despite the importance of PRMTs, the expression, localization, and function of these enzymes, specifically PRMT1, PRMT4, and PRMT5, during muscle development remains poorly understood. Therefore, the purpose of our study was to investigate quantitative, temporal, spatial, and functional metrics of PRMT biology in skeletal muscle cells during myogenesis. C 2 C 12 skeletal muscle differentiation was employed as an in vitro model of skeletal muscle development. Cells were assessed during the myoblast stage, and during days 1, 3, 5, and 7 of differentiation. RT‐qPCR was used to examine transcript levels, while Western blotting was used to assess protein expression, localization, and function throughout the experimental timecourse. In situ immunofluorescence techniques were employed to investigate cell morphology and maturity. The progression of myogenesis throughout the experimental timecourse was confirmed via significant increases in embryonic myosin heavy chain and myogenin expression, two molecular markers of muscle development. PRMT1 transcript levels progressively increased throughout differentiation and were 50–120% higher (p < 0.05) at day 5 and 7 compared to all preceding timepoints. Similarly, PRMT1 protein expression gradually increased during myogenesis and was 1.5‐fold higher (p < 0.05) at day 5 of differentiation, as compared to the myoblast stage. Interestingly, PRMT1 protein expression followed a similar pattern of expression as myogenin, suggesting a co‐regulation between these molecules during myogenic differentiation. PRMT4 transcript and protein levels were significantly lower (~20–50%) at day 5 and 7 of differentiation compared to the myoblast stage. In contrast, PRMT5 transcript and protein expression progressively increased during the timecourse and was significantly higher by day 5 of differentiation compared to the myoblast stage. Collectively, these data demonstrate PRMT‐specific patterns of expression during myogenesis. Monomethylarginine content, a marker of global PRMT activity, was similar across the timecourse. This suggests that, despite enzyme‐specific differentiation‐induced alterations in PRMT expression, PRMTs are active methyl donors throughout myogenesis. Cell fractionation analyses revealed a 3‐fold greater (p < 0.05) PRMT protein content within the cytosol, as compared to the myonuclei at all timepoints of differentiation. Furthermore, PRMT1 and PRMT5 protein levels gradually increased in the cytosol during myogenesis and were significantly higher compared to the myoblast stage by day 7 of differentiation. In contrast, PRMT4 protein expression progressively increased in the myonuclei throughout the timecourse, consistent with its reported transcriptional coactivator functions. To specifically examine the role of PRMT1 during myogenic differentiation, cells were treated with TC‐E 5003 (TCE), a selective inhibitor of PRMT1. In comparison to vehicle‐treated cells, TCE‐treated cells exhibited a deficiency in muscle differentiation, as indicated by significant reductions in myoblast fusion, and decreased myotube surface area. Altogether, our data reveal that PRMT expression, localization, and function are dynamic during myogenesis. This study expands our understanding of PRMT biology during skeletal muscle remodelling. Support or Funding Information Natural Sciences and Engineering Research Council of Canada and Canada Research Chairs
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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 | 0.001 | 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 | 0.001 |
| 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".