FoxP1 Represses MEF2A in Striated Muscle
Bibliographic record
Abstract
Myocyte enhancer factor 2 (MEF2) proteins are involved in multiple developmental, physiological, and pathological processes in vertebrates. Protein-protein interactions underlie the plethora of biological processes impacted by MEF2A, necessitating a detailed characterization of the MEF2A interactome. A nanobody based affinity-purification/mass spectrometry strategy was employed to achieve this goal. Specifically, the MEF2A protein complexes were captured from myogenic lysates using a GFP-tagged MEF2A protein immobilized with a GBP-nanobody followed by LC-MS/MS proteomic analysis to identify MEF2A interactors. After bioinformatic analysis, we further characterized the interaction of MEF2A with a transcriptional repressor, FOXP1. FOXP1 coprecipitated with MEF2A in proliferating myogenic cells which diminished upon differentiation (myotube formation). Ectopic expression of FOXP1 inhibited MEF2A driven myogenic reporter genes (derived from the creatine kinase muscle and myogenin genes) and delayed induction of endogenous myogenin during differentiation. Conversely, FOXP1 depletion enhanced MEF2A transactivation properties and myogenin expression. The FoxP1:MEF2A interaction is also preserved in cardiomyocytes and FoxP1 depletion enhanced cardiomyocyte hypertrophy. FOXP1 prevented MEF2A phosphorylation and activation by the p38MAPK pathway. Overall, these data implicate FOXP1 in restricting MEF2A function in order to avoid premature differentiation in myogenic progenitors and also to possibly prevent re-activation of embryonic gene expression in cardiomyocyte hypertrophy.
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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 | 0.001 |
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".