Global analysis of genetic circuitry and adaptive mechanisms enabling resistance to the azole antifungal drugs
Bibliographic record
Abstract
Invasive fungal infections caused by the pathogen Candida albicans have transitioned from a rare curiosity to a major cause of human mortality. This is in part due to the emergence of resistance to the limited number of antifungals available to treat fungal infections. Azoles function by targeting the biosynthesis of ergosterol, a key component of the fungal cell membrane. Loss-of-function mutations in the ergosterol biosynthetic gene ERG3 mitigate azole toxicity and enable resistance that depends upon fungal stress responses. Here, we performed a genome-wide synthetic genetic array screen in Saccharomyces cerevisiae to map ERG3 genetic interactors and uncover novel circuitry important for azole resistance. We identified nine genes that enabled erg3-mediated azole resistance in the model yeast and found that only two of these genes had a conserved impact on resistance in C. albicans. Further, we screened a C. albicans homozygous deletion mutant library and identified 13 genes for which deletion enhances azole susceptibility. Two of the genes, RGD1 and PEP8, were also important for azole resistance acquired by diverse mechanisms. We discovered that loss of function of retrograde transport protein Pep8 overwhelms the functional capacity of the stress response regulator calcineurin, thereby abrogating azole resistance. To identify the mechanism through which the GTPase activator protein Rgd1 enables azole resistance, we selected for mutations that restore resistance in strains lacking Rgd1. Whole genome sequencing uncovered parallel adaptive mechanisms involving amplification of both chromosome 7 and a large segment of chromosome 3. Overexpression of a transporter gene on the right portion of chromosome 3, NPR2, was sufficient to enable azole resistance in the absence of Rgd1. Thus, we establish a novel mechanism of adaptation to drug-induced stress, define genetic circuitry underpinning azole resistance, and illustrate divergence in resistance circuitry over evolutionary time.
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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".