Branched‐chain Amino Acid Catabolism is Required for Muscle Cell Differentiation
Bibliographic record
Abstract
The importance of branched‐chain amino acids (BCAAs) in promoting skeletal muscle anabolism has been well studied. BCAAs isoleucine, leucine, and valine have been shown to have a profound effect on activating anabolic signaling pathways in skeletal muscle. This occurs in part by the upregulation in activity of the mammalian target of rapamycin complex‐1 (mTORC1), resulting in increased protein synthesis. However, the regulation of branched‐chain amino acids during the development of muscle remains yet to be elucidated. Here, we studied BCAA metabolism during a 5‐day differentiation of L6 myoblasts. Although no change in intracellular BCAA concentrations was observed during differentiation, L6 cells cultured in the absence of leucine were severely impaired in their ability to differentiate as expression of myosin heavy chain (MHC) was completed abrogated at day 5. Two enzymes which are critical for BCAA metabolism are the branched‐chain amino transferase‐2 enzyme (BCAT2) and the branched chain α‐keto acid dehydrogenase complex (BCKD). BCAT2 catabolizes BCAAs to their corresponding alpha‐keto acids, which are then irreversibly decarboxylated by the BCKD complex. The abundance of BCAT2 did not change during differentiation, whereas levels of the E1α subunit of BCKD was increased 7x on day 5 compared to day 1 (p<0.05). Finally, when either BCAT2 or BCKDE1α was knocked down in the presence of leucine, myoblast differentiation was abrogated (BCKDE1α RNAi: MHC decreased 4.5x from day 3 to day 5 (p<0.05); BCAT2 RNAi: MHC levels completely abolished). Our findings suggest that BCAA catabolism may be a critical process in facilitating muscle differentiation.
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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 | 0.000 | 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".