Transcription Factor GATA-4 Is Activated by Phosphorylation of Serine 261 via the cAMP/Protein Kinase A Signaling Pathway in Gonadal Cells
Bibliographic record
Abstract
Gonadal gene expression is regulated by pituitary hormones acting through the cAMP/protein kinase A (PKA) signal transduction pathway. The downstream molecular effectors of these signals, however, have yet to be fully understood. We have recently shown that cAMP stimulation of gonadal cells leads to phosphorylation of the transcription factor GATA-4, a key regulator of gonadal gene expression, thus suggesting that this factor might be a novel target for the cAMP/PKA signaling pathway. We now show that the rapid phosphorylation of GATA-4 induced by cAMP in vivo can be blocked by a PKA-specific inhibitor but not by mitogen-activated protein kinase inhibitors, indicating that GATA-4 is predominantly phosphorylated by PKA in response to cAMP in gonadal cells. In addition, using in vitro kinase assays, we show that PKA phosphorylation of GATA-4 occurs predominantly on an evolutionarily conserved serine residue located at position 261. Phosphorylation of GATA-4 Ser261 by PKA enhances its transcriptional activity on different gonadal promoters, an effect that was markedly reduced with a S261A mutant. Moreover, the S261A mutant blunted cAMP-induced promoter activity in gonadal cells. Finally, PKA-dependent phosphorylation of GATA-4 also led to enhanced recruitment of the CREB-binding protein coactivator. This recruitment and transcriptional cooperation were dramatically impaired with the S261A mutant. Thus, our results identify GATA-4 as a novel downstream effector of cAMP/PKA signaling in gonadal cells, where phosphorylation of Ser261 and recruitment of CREB-binding protein likely represent a key mechanism for conveying the cAMP responsiveness of gonadal genes that lack classical cAMP regulatory elements.
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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".