The Orphan Nuclear Receptor NUR77 Regulates Hormone-Induced StAR Transcription in Leydig Cells through Cooperation with Ca2+/Calmodulin-Dependent Protein Kinase I
Bibliographic record
Abstract
Cholesterol transport in the mitochondrial membrane, an essential step of steroid biosynthesis, is mediated by a protein complex containing the steroidogenic acute regulatory (StAR) protein. The importance of this transporter is underscored by mutations in the human StAR gene that cause lipoid congenital adrenal hyperplasia, male pseudohermaphroditism, and adrenal insufficiency. StAR transcription in steroidogenic cells is hormonally regulated and involves several transcription factors. The nuclear receptor NUR77 is present in steroidogenic cells, and its expression is induced by hormones known to activate StAR expression. We have now established that StAR transcription in cAMP-stimulated Leydig cells requires de novo protein synthesis and involves NUR77. We found that cAMP-induced NUR77 expression precedes that of StAR both at the mRNA and protein levels in Leydig cells. In these cells, small interfering RNA-mediated NUR77 knockdown reduces cAMP-induced StAR expression. Chromatin immunoprecipitation assays revealed a cAMP-dependent increase in NUR77 recruitment to the proximal StAR promoter, whereas transient transfections in MA-10 Leydig cells confirmed that NUR77 can activate the StAR promoter and that this requires an element located at -95 bp. cAMP-induced StAR and NUR77 expression in Leydig cells was found to require a Ca2+/calmodulin-dependent protein kinase (CaMK)-dependent signaling pathway. Consistent with this, we show that within the testis, CaMKI is specifically expressed in Leydig cells. Finally, we report that CaMKI transcriptionally cooperates with NUR77, but not steroidogenic factor 1, to further enhance StAR promoter activity in Leydig cells. All together, our results implicate NUR77 as a mediator of cAMP action on StAR transcription in steroidogenic Leydig cells and identify a role for CaMKI in this process.
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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".