Activating transcription factor 4 regulates mitochondrial content, morphology, and function in differentiating skeletal muscle myotubes
Bibliographic record
Abstract
Mitochondrial function is widely recognized as a major determinant of health, emphasizing the importance of understanding the mechanisms promoting mitochondrial quality in various tissues. Recently, the mitochondrial unfolded protein response (UPRmt) has come into focus as a modulator of mitochondrial homeostasis, particularly in stress conditions. In muscle, the necessity for activating transcription factor 4 (ATF4) and its role in regulating mitochondrial quality control (MQC) have yet to be determined. We overexpressed (OE) and knocked down ATF4 in C2C12 myoblasts, differentiated them to myotubes for 5 days, and subjected them to acute (ACA) or chronic (CCA) contractile activity. ATF4 mediated myotube formation through the regulated expression of myogenic factors, mainly Myc and myoblast determination protein 1 (MyoD), and suppressed mitochondrial biogenesis basally through peroxisome proliferator-activated receptor gamma coactivator 1alpha (PGC-1α). However, our data also show that ATF4 expression levels are directly related to mitochondrial fusion and dynamics, UPRmt activation, as well as lysosomal biogenesis and autophagy. Thus, ATF4 promoted enhanced mitochondrial networking, protein handling, and the capacity for clearance of dysfunctional organelles under stress conditions, despite lower levels of mitophagy flux with OE. Indeed, we found that ATF4 promoted the formation of a smaller pool of high-functioning mitochondria that are more responsive to contractile activity and have higher oxygen consumption rates and lower reactive oxygen species levels. These data provide evidence that ATF4 is both necessary and sufficient for mitochondrial quality control and adaptation during both differentiation and contractile activity, thus advancing the current understanding of ATF4 beyond its canonical functions to include the regulation of mitochondrial morphology, lysosomal biogenesis, and mitophagy in muscle cells.
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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 | 0.000 |
| 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".