Novel Sarcopenia-related Alterations in Sarcomeric Protein Post-translational Modifications (PTMs) in Skeletal Muscles Identified by Top-down Proteomics
Bibliographic record
Abstract
Sarcopenia, the age-related loss of skeletal muscle mass and strength, is a significant cause of morbidity in the elderly and is a major burden on health care systems. Unfortunately, the underlying molecular mechanisms in sarcopenia remain poorly understood. Herein, we utilized top-down proteomics to elucidate sarcopenia-related changes in the fast- and slow-twitch skeletal muscles of aging rats with a focus on the sarcomeric proteome, which includes both myofilament and Z-disc proteins-the proteins that constitute the contractile apparatuses. Top-down quantitative proteomics identified significant changes in the post-translational modifications (PTMs) of critical myofilament proteins in the fast-twitch skeletal muscles of aging rats, in accordance with the vulnerability of fast-twitch muscles to sarcopenia. Surprisingly, age-related alterations in the phosphorylation of Cypher isoforms, proteins that localize to the Z-discs in striated muscles, were also noted in the fast-twitch skeletal muscle of aging rats. This represents the first report of changes in the phosphorylation of Z-disc proteins in skeletal muscle during aging. In addition, increased glutathionylation of slow skeletal troponin I, a novel modification that may help protect against oxidative damage, was observed in slow-twitch skeletal muscles. Furthermore, we have identified and characterized novel muscle type-specific proteoforms of myofilament proteins and Z-disc proteins, including a novel isoform of the Z-disc protein Enigma. The finding that the phosphorylation of Z-disc proteins is altered in response to aging in the fast-twitch skeletal muscles of aging rats opens new avenues for the investigation of the role of Z-discs in age-related muscle dysfunction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".