Myofibrillar protein accumulation but reduced protein synthesis in PDCD4-depleted myotubes
Bibliographic record
Abstract
Abstract Skeletal muscle is critical to whole-body functionality and homeostasis. The mammalian/mechanistic target of rapamycin complex 1 (mTORC1) is a nutrient/growth-factor sensitive positive regulator of skeletal muscle mass. Amongst other substrates, mTORC1 phosphorylates the ribosomal protein S6 kinase (S6K1). Activated S6K1 acts through multiple effectors, including programmed cell death 4 (PDCD4), to activate mRNA translation and protein synthesis. Much of what is known about PDCD4 is in non-muscle cells. We previously demonstrated that the effect of PDCD4 differs between myoblasts and myotubes. Here, we showed that PDCD4 depletion in L6 and C2C12 myotubes enhanced myotube diameter (+36%) and accumulation of myofibrillar proteins (+163 – 237%). These effects occurred along with increased phosphorylation of AKT ser473 (+85%) and of the mTORC1 substrate S6K1 thr389 (+152%), but protein synthesis was suppressed. There was increased phosphorylation of FoxO3a ser253 (+250%) and a corresponding reduction in the expression of the muscle protein ubiquitin ligase MuRF1 (–44%), but there was no significant effect on measures of proteolysis or autophagy. In starved myotubes treated with the proteasome inhibitor MG132, accumulation of ubiquitinated proteins was attenuated in PDCD4-depleted cells. PDCD4 depletion did not augment measures of myotube contraction but was associated with reduced ATP and intracellular amino acid levels. Finally, AKT inhibition partially attenuated the effect of PDCD4 depletion on myofibrillar protein abundance. In summary, myofibrillar protein accumulation in PDCD 4-depleted myotubes did not lead to improved myotube function, likely due to reduced energy level. Our data point to a pivotal role for PDCD4 in regulating myotube size and metabolism.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".