Multiple Yap1p-binding Sites Mediate Induction of the Yeast Major Facilitator FLR1 Gene in Response to Drugs, Oxidants, and Alkylating Agents
Bibliographic record
Abstract
The bZip transcription factor Yap1p plays an important role in oxidative stress response and multidrug resistance in Saccharomyces cerevisiae. We have previously demonstrated that the FLR1 gene, encoding a multidrug transporter of the major facilitator superfamily, is a transcriptional target of Yap1p. The FLR1 promoter contains three potential Yap1p response elements (YREs) at positions -148 (YRE1), -167 (YRE2), and -364 (YRE3). To address the function of these YREs, the three sites have been individually mutated and tested in transactivation assays. Our results show that (i) each of the three YREs is functional and important for the optimal transactivation of FLR1 by Yap1p and that (ii) the three YREs are not functionally equivalent, mutation of YRE3 being the most deleterious, followed by YRE2 and YRE1. Simultaneous mutation of the three YREs abolished transactivation of the promoter by Yap1p, demonstrating that the three sites are essential for the regulation of FLR1 by Yap1p. Gel retardation assays confirmed that Yap1p differentially binds to the three YREs (YRE3 > YRE2 > YRE1). We show that the transcription of FLR1 is induced upon cell treatment with the oxidizing agents diamide, diethylmaleate, hydrogen peroxide, and tert-butyl hydroperoxide, the antimitotic drug benomyl, and the alkylating agent methylmethane sulfonate and that this induction is mediated by Yap1p through the three YREs. Finally, we show that FLR1 overexpression confers resistance to diamide, diethylmaleate, and menadione but hypersensitivity to H(2)O(2), demonstrating that the Flr1p transporter participates in Yap1p-mediated oxidative stress response in S. cerevisiae.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".