Quantifying and Mitigating Antifungal Tolerance in the Pathogenic Yeast Candida auris
Bibliographic record
Abstract
Candida auris is an emerging pathogen that has been detected on five continents and is linked to resistance against the main three classes of antifungal drugs used to treat invasive infections, leading to healthcare-associated outbreaks. Tolerance refers to the ability of a drug-susceptible fungal strain to grow slowly in the presence of an antifungal drug at concentrations above the minimum inhibitory concentration (MIC). This phenomenon can be reversed when the drug pressure is eliminated [1–3]. In this thesis, we examined the presence of tolerant subpopulations against several antifungal drugs, including fluconazole, itraconazole, caspofungin, voriconazole, posaconazole, amphotericin B, and anidulafungin. We obtained five Candida auris isolates from clinical samples collected at the Public Health Lab-Alberta Precision Laboratories. I employed the microdilution assay to determine the MIC and conducted the disk diffusion assay (DDA) to determine the radius of the zone of inhibition (RAD). Images of the DDA were analyzed using diskImageR and imageJ software to quantify the fraction of growth (FOG) within the zone of inhibition (ZOI). Slow growing colonies within the ZOI were considered as tolerant subpopulations. The FOG within the ZOI served as a variable to quantify the degree of tolerance. Additionally, I measured supra-MIC growth (SMG) as another variable to quantify tolerance, which determined the growth in drug concentrations above MIC. After 48 hours of drug treatment, an increase in SMG was observed for certain antifungal drug- C. auris isolate combinations. To explore whether tolerance was a non-genetic or genetic trait, I sub-cultured the colonies growing inside and outside the ZOI. I then repeated the DDA, MIC, and SMG experiments. The isolates from inside and outside the ZOI did not exhibit any changes in the RAD, MIC, or SMG. These findings suggests that a non-genetic mechanism may underlie tolerance in C. auris. The potential synergy between various antifungals and an adjuvant, chloroquine, was then assessed against C. auris, C. parapsilosis, and I. orientalis. I found that the antifungal drug fluconazole when combined with the adjuvant chloroquine, reduced or eliminated tolerance in C. auris. Finally, I performed a numerical simulation to investigate the diffusion concentration profile of antifungal drugs within agar media. My findings revealed a concentration gradient, with higher drug concentrations observed near the center of the ZOI and lower concentrations at the periphery of the ZOI, which explains why the tolerant colonies were often observed at the edge of the ZOI; that is that tolerance is a drug-dependent phenomenon.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".