<i>Saccharomyces cerevisiae</i> Genome-Wide Mutant Screen for Sensitivity to 2,4-Diacetylphloroglucinol, an Antibiotic Produced by <i>Pseudomonas fluorescens</i>
Bibliographic record
Abstract
2,4-Diacetylphloroglucinol (2,4-DAPG), an antibiotic produced by Pseudomonas fluorescens, has broad-spectrum antibiotic activity, inhibiting organisms ranging from viruses, bacteria, and fungi to higher plants and mammalian cells. The biosynthesis and regulation of 2,4-DAPG in P. fluorescens are well described, but the mode of action against target organisms is poorly understood. As a first step to elucidate the mechanism, we screened a deletion library of Saccharomyces cerevisiae in broth and agar medium supplemented with 2,4-DAPG. We identified 231 mutants that showed increased sensitivity to 2,4-DAPG under both conditions, including 22 multidrug resistance-related mutants. Three major physiological functions correlated with an increase in sensitivity to 2,4-DAPG: membrane function, reactive oxygen regulation, and cell homeostasis. Physiological studies with wild-type yeast validated the results of the mutant screens. The chemical-genetic fitness profile of 2,4-DAPG resembled those of menthol, sodium azide, and hydrogen peroxide determined in previous high-throughput screening studies. Collectively, these findings indicate that 2,4-DAPG acts on multiple basic cellular processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".