mTORC2 affects the maintenance of the muscle stem cell pool
Bibliographic record
Abstract
BACKGROUND: The mammalian target of rapamycin complex 2 (mTORC2), containing the essential protein rictor, regulates cellular metabolism and cytoskeletal organization by phosphorylating protein kinases, such as PKB/Akt, PKC, and SGK. Inactivation of mTORC2 signaling in adult skeletal muscle affects its metabolism, but not muscle morphology and function. However, the role of mTORC2 in adult muscle stem cells (MuSCs) has not been investigated. METHOD: Using histological, biochemical, and molecular biological methods, we characterized the muscle phenotype of mice depleted for rictor in the Myf5-lineage (RImyfKO) and of mice depleted for rictor in skeletal muscle fibers (RImKO). The proliferative and myogenic potential of MuSCs was analyzed upon cardiotoxin-induced injury in vivo and in isolated myofibers in vitro. RESULTS: Skeletal muscle of young and 14-month-old RImyfKO mice appeared normal in composition and function. MuSCs from young RImyfKO mice exhibited a similar capacity to proliferate, differentiate, and fuse as controls. In contrast, the number of MuSCs was lower in young RImyfKO mice than in controls after two consecutive rounds of cardiotoxin-induced muscle regeneration. Similarly, the number of MuSCs in RImyfKO mice decreased with age, which correlated with a decline in the regenerative capacity of mutant muscle. Interestingly, reduction in the number of MuSCs was also observed in 14-month-old RImKO muscle. CONCLUSIONS: Our study shows that mTORC2 signaling is dispensable for myofiber formation, but contributes to the homeostasis of MuSCs. Loss of mTORC2 does not affect their myogenic function, but impairs the replenishment of MuSCs after repeated injuries and their maintenance during aging. These results point to an important role of mTORC2 signaling in MuSC for muscle homeostasis.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".