Mitochondrial defects result in decreased susceptibility to echinocandins via the transcriptional regulator Pdr1 in <i>Candida glabrata</i>
Bibliographic record
Abstract
ABSTRACT In the human fungal pathogen Candida glabrata , the transcription factor Pdr1 controls the expression of genes encoding drug efflux pumps such as Cdr1. Pdr1 also controls its own expression by binding to pleiotropic drug responsive elements (PDREs) located in its promoter. Increased resistance to the antifungal drugs azoles (e.g. fluconazole) is often due to gain-of-function mutations in PDR1 that render the factor hyperactive. Mitochondrial defects also result in increased resistance to azoles via Pdr1. Resistance to another class of antifungals, the echinocandins (e.g. micafungin), is generally due to mutations in the FKS1 and FKS2 genes that encode the catalytic subunit of 1,3-beta-D-glucan synthase, the echinocandin target. We have observed that mitochondrial defects also result in increased resistance to echinocandins and we have shown that this process is mediated by Pdr1. Mitochondrial defects result in increased levels of PDR1 mRNA. Overexpression of PDR1 by replacing its native promoter by the strong ADH1 promoter resulted in increased resistance to micafungin. However, mutations in PDR1 that decrease susceptibility to azoles generally have modest effects on echinocandin resistance. We randomly mutagenized the PDR1 gene and screened for mutants with altered resistance to micafungin. Single amino acid changes downstream of the DNA binding domain result in preferential resistance to micafungin as compared to fluconazole. We also show that auto-regulation of PDR1 expression is necessary for resistance to micafungin. One PDR1 mutant showed over 15-fold increased promoter activity in a PDRE-dependent manner. In summary, we have identified a novel role for the transcriptional regulator Pdr1.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".