In Vitro Evolution of Itraconazole Resistance in <i>Aspergillus fumigatus</i> Involves Multiple Mechanisms of Resistance
Bibliographic record
Abstract
We investigated the evolution of resistance to the antifungal drug itraconazole in replicate populations of Aspergillus fumigatus that were founded from a strain with a genotype of sensitivity to a single drug and then propagated under uniform conditions. For each population, conidia were serially transferred 10 times to agar medium either with or without itraconazole. After 10 transfers in medium supplemented with itraconazole, 10 itraconazole-resistant mutant strains were isolated from two populations. These mutant strains had different growth rates and different levels of itraconazole resistance. Analysis of the ergosterol contents of these mutants showed that they accumulate ergosterol when they are grown in the presence of itraconazole. The replacement of the CYP51A gene of the wild-type strain changed the susceptibility pattern of this strain to one of itraconazole resistance only when CYP51A genes with N22D and M220I mutations were used as selectable marker genes. Real-time quantitative reverse transcription-PCR was used to assess the levels of expression of the Afumdr1, Afumdr2, Afumdr3, Afumdr4, AtrF transporter, CYP51A, and CYP51B genes in these mutant strains. Most mutants showed either constitutive high-level expression or induction upon exposure of Afumdr3, Afumdr4, and AtrF to itraconazole. Our results suggest that overexpression of drug efflux pumps and/or selection of drug target site mutations are at least partially responsible for itraconazole resistance and could be considered mechanisms for the emergence of clinical resistance to this drug.
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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) | 0.000 | 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".