Identification of MEF2A, MEF2C, and MEF2D interactomes in basal and Fsk‐stimulated mouse MA‐10 Leydig cells
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Bibliographic record
Abstract
BACKGROUND: Myocyte enhancer factor 2 transcription factors regulate essential transcriptional programs in various cell types. The activity of myocyte enhancer factor 2 factors is modulated through interactions with cofactors, chromatin remodelers, and other regulatory proteins, which are dependent on cell context and physiological state. In steroidogenic Leydig cells, MEF2A, MEF2C, and MEF2D are key regulators of genes involved in steroid hormone synthesis, reproductive function, and oxidative stress defense. However, the specific network of myocyte enhancer factor 2-interacting proteins in Leydig cells remains unknown. OBJECTIVE: To identify the interactome of each MEF2 factor present in Leydig cells. MATERIALS AND METHODS: TurboID proximity-mediated biotinylation combined with mass spectrometry and bioinformatic analyses were used to identify the protein‒protein interaction networks of MEF2A, MEF2C, and MEF2D in MA-10 Leydig cells under basal and stimulated conditions. RESULTS: We identified 109 potential myocyte enhancer factor 2-interacting proteins, including some previously known myocyte enhancer factor 2 partners. The interactome for each myocyte enhancer factor 2 factor is dynamic and exhibits unique and shared interaction networks between basal and stimulated conditions. Further analysis through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment categorized these interactions, revealing involvement in pathways related to cellular metabolism, transcriptional regulation, and steroidogenesis. DISCUSSION AND CONCLUSION: These findings suggest that myocyte enhancer factor 2 factors can participate in diverse transcriptional activities, capable of gene activation or repression, depending on different protein‒protein interactions. In addition, the differential interactome for each myocyte enhancer factor 2 factor suggests unique regulatory roles for each factor in modulating Leydig cell function. Overall, this study provides new mechanistic insights into myocyte enhancer factor 2 action in Leydig cells by identifying interacting partners that likely influence their functions.
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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 it