The Transcription Factor MEF2 Is a Novel Regulator of Gsta Gene Class in Mouse MA-10 Leydig Cells
Bibliographic record
Abstract
Testosterone is essential for spermatogenesis and the development of male sexual characteristics. However, steroidogenesis produces a significant amount of reactive oxygen species (ROS), which can disrupt testosterone production. The myocyte enhancer factor 2 (MEF2) is an important regulator of organogenesis and cell differentiation in various tissues. In the testis, MEF2 is present in Sertoli and Leydig cells throughout fetal and adult life. MEF2-deficient MA-10 Leydig cells exhibit a significant decrease in steroidogenesis concomitant with a reduction in glutathione S-transferase (GST) activity and in the expression of the 4 Gsta members (GST) that encode ROS inactivating enzymes. Here, we report a novel role for MEF2 in ROS detoxification by directly regulating Gsta expression in Leydig cells. Endogenous Gsta1-4 mRNA levels were decreased in MEF2-deficient MA-10 Leydig cells. Conversely, overexpression of MEF2 increased endogenous Gsta1 levels. MEF2 recruitment to the proximal Gsta1 promoter and direct binding on the -506-bp MEF2 element were confirmed by chromatin immunoprecipitation and DNA precipitation assays. In MA-10 Leydig cells, MEF2 activates the Gsta1 promoter and cooperates with Ca(2+)/calmodulin-dependent kinases I to further enhance Gsta1 promoter activity. These effects were lost when the -506-bp MEF2 element was mutated or when a MEF2-Engrailed dominant negative protein was used. Similar results were obtained on the Gsta2, Gsta3, and Gsta4 promoters, suggesting a global role for MEF2 factors in the regulation of all 4 Gsta genes. Altogether, our results identify a novel role for MEF2 in the expression of genes involved in ROS detoxification, a process essential for adequate testosterone production in Leydig 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) | 0.002 | 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".