DNM1L-mediated fission governs mitophagy & mitochondrial biogenesis during myogenic differentiation
Bibliographic record
Abstract
BACKGROUND: Remodeling of the mitochondrial network is implicated in myogenesis. Remodeling processes including mitochondrial fission, mitophagy, and biogenesis are important as they finetune the mitochondrial network to meet the increased energetic demand of myotubes. Evidence suggests that mitochondrial fission governs other mitochondrial remodeling processes; however, this relationship is unclear in the context of myogenesis. METHODS: We used C2C12 myoblasts to study changes in mitochondrial remodeling processes and their role in regulating myogenesis. To investigate this, we employed genetic manipulation with adenoviruses to modify the levels of key molecules involved in mitochondrial remodeling, including DNM1L, BNIP3, and PPARGC1A. RESULTS: We demonstrate that overexpression of fission protein DNM1L accelerated mitophagic flux, but reduced myotube size without affecting mitochondrial biogenesis. Conversely, DNM1L knockdown reduced mitophagic flux, impaired myoblast differentiation, and suppressed mitochondrial biogenesis signaling. Additionally, DNM1L knockdown increased mitochondrial apoptotic signaling through CASP9 and CASP3 activation. Attempts to rescue myogenesis through overexpression of the mitophagy receptor BNIP3 or the biogenesis regulator PPARGC1A were unsuccessful in the absence of proper mitochondrial fission. Furthermore, DNM1L overexpression in BNIP3-deficient cells enhanced mitophagic flux, but did not promote myogenesis. CONCLUSION: These results underscore the complex interdependencies among mitochondrial remodeling processes and highlight the necessity for sequential activation of mitochondrial fission, mitophagy, and biogenesis.
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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) | 0.001 | 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".