Ethanol stress stimulates sumoylation of transcription factor Cst6 which restricts expression of its target genes
Bibliographic record
Abstract
ABSTRACT Sumoylation is an essential post-translational modification that functions in multiple cellular processes, including transcriptional regulation. Indeed, transcription factors represent one of the largest groups of proteins that are modified by the SUMO peptide. Multiple roles have been identified for sumoylation of transcription factors, including regulation of their activity, interaction with chromatin, and binding site selection. Here, we examine how Cst6, a bZIP-containing sequence-specific transcription factor in Saccharomyces cerevisiae , is regulated by sumoylation. Cst6 is required for survival during ethanol stress and has roles in the utilization of carbon sources other than glucose. We find that Cst6 is sumoylated to appreciable levels in normally growing yeast at Lys residues 139, 461 and 547, and that its sumoylation level increases in ethanol and oxidative stress conditions, but decreases if ethanol is used as the sole carbon source. To understand the role of Cst6 sumoylation during ethanol stress, we generated a yeast strain that expresses a non-sumoylatable mutant form of Cst6. Cellular levels of the mutant protein are moderately reduced compared to the wild-type form, implying that sumoylation promotes Cst6 stability. Although the mutant can bind DNA, chromatin immunoprecipitation (ChIP) analysis shows that its occupancy level is significantly reduced on promoters of some ethanol stress-regulated genes, suggesting that Cst6 recruitment is attenuated or delayed if it can not be sumoylated. Furthermore, impaired Cst6 sumoylation in the mutant strain correlates with elevated expression of some target genes, either constitutively or during induction by ethanol stress. This is most striking for RPS3 , which shows dramatically increased expression in the mutant strain. Together, our results suggest that sumoylation controls multiple properties of Cst6 to limit the expression of its target genes.
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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".