ERK5 Cooperates With MEF2C to Regulate <i>Nr4a1</i> Transcription in MA-10 and MLTC-1 Leydig Cells
Bibliographic record
Abstract
Leydig cells produce hormones required for the development and maintenance of sex characteristics and fertility in males. MEF2 transcription factors are important regulators of Leydig cell gene expression and steroidogenesis. ERK5 is an atypical member of the MAP kinase family that modulates transcription factor activity, either by direct phosphorylation or by acting as a transcriptional coactivator. While MEF2 and ERK5 are known to cooperate transcriptionally, the presence and role of ERK5 in Leydig cells remained unknown. Our goal was to determine whether ERK5 is present in Leydig cells and whether it cooperates with MEF2 to regulate gene expression. We found that ERK5 is present in Leydig cells in testicular tissue and immortalized cell lines. ERK5 knockdown in human chorionic gonadotrophin-treated MA-10 Leydig cells reduced steroidogenesis and decreased Star and Nr4a1 expression. Luciferase assays using a synthetic reporter plasmid containing 3 MEF2 elements revealed that ERK5 enhances MEF2-dependent promoter activation. Although ERK5 did not cooperate with MEF2 on the Star promoter in Leydig cell lines, we found that ERK5 and MEF2C do cooperate on the Nr4a1 promoter, which contains 2 adjacent MEF2 elements. Mutation of each MEF2 element in a short version of the Nr4a1 promoter significantly decreased the ERK5/MEF2C cooperation, indicating that both MEF2 elements need to be intact. The ERK5/MEF2C cooperation did not require phosphorylation of MEF2C on Ser387. Taken together, our data identify ERK5 as a new regulator of MEF2 activity in Leydig cells and provide potential new insights into mechanisms that regulate Leydig cell gene expression and function.
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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".