Protein engineering of <i>Saccharomyces cerevisiae</i> transporter Pdr5p identifies key residues that impact <i>Fusarium</i> mycotoxin export and resistance to inhibition
Bibliographic record
Abstract
Cereal infection by the broad host range fungal pathogen Fusarium graminearum is a significant global agricultural and food safety issue due to the deposition of mycotoxins within infected grains. Methods to study the intracellular effects of mycotoxins often use the baker's yeast model system (Saccharomyces cerevisiae); however, this organism has an efficient drug export network known as the pleiotropic drug resistance (PDR) network, which consists of a family of multidrug exporters. This study describes the first study that has evaluated the potential involvement of all known or putative ATP-binding cassette (ABC) transporters from the PDR network in exporting the F. graminearum trichothecene mycotoxins deoxynivalenol (DON) and 15-acetyl-deoxynivalenol (15A-DON) from living yeast cells. We found that Pdr5p appears to be the only transporter from the PDR network capable of exporting these mycotoxins. We engineered mutants of Pdr5p at two sites previously identified as important in determining substrate specificity and inhibitor susceptibility. These results indicate that it is possible to alter inhibitor insensitivity while maintaining the ability of Pdr5p to export the mycotoxins DON and 15A-DON, which may enable the development of resistance strategies to generate more Fusarium-tolerant crop plants.
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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".