The Stability and Transactivation Potential of the Mammalian MafA Transcription Factor Are Regulated by Serine 65 Phosphorylation
Bibliographic record
Abstract
The level of the MafA transcription factor is regulated by a variety of effectors of beta cell function, including glucose, fatty acids, and insulin. Here, we show that phosphorylation at Ser(65) of mammalian MafA influences both protein stability and transactivation potential. Replacement of Ser(65) with Glu to mimic phosphorylation produced a protein that was as unstable as the wild type, whereas Asp or Ala mutation blocked degradation. Analysis of MafA chimeric and deletion constructs suggests that protein phosphorylation at Ser(65) alone represents the initial degradation signal, with ubiquitinylation occurring within the C terminus (amino acids 234-359). Although only wild type MafA and S65E were polyubiquitinylated, both S65D and S65E potently stimulated transactivation compared with S65A. Phosphorylation at Ser(14) also enhanced activation, although it had no impact on protein turnover. The mobility of MafA S65A was profoundly affected upon SDS-PAGE, with the S65E and S65D mutants influenced less due to their ability to serve as substrates for glycogen synthase kinase 3, which acts at neighboring N-terminal residues after Ser(65) phosphorylation. Our observations not only illustrate the sensitivity of the cellular transcriptional and degradation machinery to phosphomimetic mutants at Ser(65), but also demonstrate the singular importance of phosphorylation at this amino acid in regulating MafA activity.
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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 | 0.000 |
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 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".