Top-Down Targeted Proteomics Reveals Decrease in Myosin Regulatory Light-Chain Phosphorylation That Contributes to Sarcopenic Muscle Dysfunction
Bibliographic record
Abstract
Sarcopenia, the loss of skeletal muscle mass and function with advancing age, is a significant cause of disability and loss of independence in the elderly and thus, represents a formidable challenge for the aging population. Nevertheless, the molecular mechanism(s) underlying sarcopenia-associated muscle dysfunction remain poorly understood. In this study, we employed an integrated approach combining top-down targeted proteomics with mechanical measurements to dissect the molecular mechanism(s) in age-related muscle dysfunction. Top-down targeted proteomic analysis uncovered a progressive age-related decline in the phosphorylation of myosin regulatory light chain (RLC), a critical protein involved in the modulation of muscle contractility, in the skeletal muscle of aging rats. Top-down tandem mass spectrometry analysis identified a previously unreported bis-phosphorylated proteoform of fast skeletal RLC and localized the sites of decreasing phosphorylation to Ser14/15. Of these sites, Ser14 phosphorylation represents a previously unidentified site of phosphorylation in RLC from fast-twitch skeletal muscle. Subsequent mechanical analysis of single fast-twitch fibers isolated from the muscles of rats of different ages revealed that the observed decline in RLC phosphorylation can account for age-related decreases in the contractile properties of sarcopenic fast-twitch muscles. These results strongly support a role for decreasing RLC phosphorylation in sarcopenia-associated muscle dysfunction and suggest that therapeutic modulation of RLC phosphorylation may represent a new avenue for the treatment of sarcopenia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".