Extensive functional redundancy in the regulation of <scp><i>C</i></scp><i>andida albicans</i> drug resistance and morphogenesis by lysine deacetylases <scp>H</scp>os2, <scp>H</scp>da1, <scp>R</scp>pd3 and <scp>R</scp>pd31
Bibliographic record
Abstract
Current treatment efforts for fungal infections are hampered by the limited availability of antifungal drugs and by the emergence of drug resistance. A powerful strategy to enhance the efficacy of antifungal drugs is to inhibit the molecular chaperone Hsp90. Hsp90 governs drug resistance, morphogenesis and virulence in a leading fungal pathogen of humans, Candida albicans. Our previous work with Saccharomyces cerevisiae established acetylation as a novel mechanism of posttranslational control of Hsp90 function in fungi. We implicated lysine deacetylases (KDACs) as key regulators of resistance to the most widely deployed class of antifungals, the azoles, in both S. cerevisiae and C. albicans. Here, we demonstrate high levels of functional redundancy among the KDACs that are important for regulating Hsp90 function. We identify Hos2, Hda1, Rpd3 and Rpd31 as the KDACs mediating azole resistance and morphogenesis in C. albicans. Furthermore, we identify lysine 30 and 271 as critical acetylation sites on C. albicans Hsp90, and substitutions at these residues compromise Hsp90 function. Finally, we show that pharmacological inhibition of KDACs phenocopies pharmacological inhibition of Hsp90 and abrogates Hsp90-dependent azole resistance in numerous Candida species. This work illuminates new facets to the impact of KDACs on fungal drug resistance and morphogenesis, provides important insights into the divergence of the C. albicans Hsp90 regulatory network and reveals new targets for development of antifungal drugs.
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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".