Role of TFEB and TFE3 in mediating lysosomal and mitochondrial adaptations to contractile activity in skeletal muscle myotubes
Bibliographic record
Abstract
Exercise is potent stimulus for mitochondrial adaptations, serving to activate mitochondrial biogenesis as well as mitochondrial turnover. Through the process of mitophagy, dysfunctional mitochondria are selectively targeted and recycled via the lysosomes, which is activated following a single bout of exercise. The microphthalamia (MiT) family of transcription factors, including TFEB and TFE3, are widely recognized as the master regulators of lysosomal biogenesis, as they homo- and hetero-dimerize to transcriptionally regulate lysosomal and macroautophagy-related genes. It is currently unknown to what extent TFEB and TFE3 regulate mitophagy, and whether these transcription factors mediate mitochondrial adaptations to contractile activity (CA). Here we show that following an acute bout of contractile activity in cultured C2C12 murine skeletal muscle myotubes, LC3-II mitophagy flux is induced and the absence of TFEB or TFE3 impairs this acute mitophagic response. However, the loss of either transcription factor alone does not mitigate the improvements in oxygen consumption seen following chronic contractile activity (CCA). Chronic contractile activity also elicited functional improvements in lysosomes including a reduction in size and increased proteolytic activity, evidenced by increased digestion and unquenching of DQ-BSA fluorophore, thereby illustrating a level of redundancy between the two transcription factors in mediating chronic contractile activity-induced adaptations. However, in the absence of both TFEB and TFE3, lysosomal adaptations were not observed following chronic contractile activity and subsequent mitochondrial adaptations were attenuated. These findings underscore the importance of the lysosomes, and of TFEB and TFE3, in mediating mitochondrial adaptations to chronic contractile activity.
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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".