A conserved MADS-box phosphorylation motif regulates differentiation and mitochondrial function in skeletal, cardiac, and smooth muscle cells
Bibliographic record
Abstract
Exposure to metabolic disease during fetal development alters cellular differentiation and perturbs metabolic homeostasis, but the underlying molecular regulators of this phenomenon in muscle cells are not completely understood. To address this, we undertook a computational approach to identify cooperating partners of the myocyte enhancer factor-2 (MEF2) family of transcription factors, known regulators of muscle differentiation and metabolic function. We demonstrate that MEF2 and the serum response factor (SRF) collaboratively regulate the expression of numerous muscle-specific genes, including microRNA-133a (miR-133a). Using tandem mass spectrometry techniques, we identify a conserved phosphorylation motif within the MEF2 and SRF Mcm1 Agamous Deficiens SRF (MADS)-box that regulates miR-133a expression and mitochondrial function in response to a lipotoxic signal. Furthermore, reconstitution of MEF2 function by expression of a neutralizing mutation in this identified phosphorylation motif restores miR-133a expression and mitochondrial membrane potential during lipotoxicity. Mechanistically, we demonstrate that miR-133a regulates mitochondrial function through translational inhibition of a mitophagy and cell death modulating protein, called Nix. Finally, we show that rodents exposed to gestational diabetes during fetal development display muscle diacylglycerol accumulation, concurrent with insulin resistance, reduced miR-133a, and elevated Nix expression, as young adult rats. Given the diverse roles of miR-133a and Nix in regulating mitochondrial function, and proliferation in certain cancers, dysregulation of this genetic pathway may have broad implications involving insulin resistance, cardiovascular disease, and cancer biology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".