Approaches for identifying and measuring heteroresistance in azole-susceptible <i>Candida</i> isolates
Bibliographic record
Abstract
ABSTRACT Heteroresistance to antifungal agents poses a significant challenge in the treatment of fungal infections. Currently, the absence of established methods for detecting and measuring heteroresistance impedes progress in understanding this phenomenon in fungal pathogens. In response to this gap, we present a comprehensive set of new and optimized methods designed to detect and quantify azole heteroresistance in Candida albicans . Here, we define two primary assays for measuring heteroresistance: population analysis profiling, based on growth on solid medium, and single-cell assays, based on growth in liquid culture. We observe good correlations between the measurements obtained with liquid and solid assays, validating their utility for studying azole heteroresistance. We also highlight that disk diffusion assays could serve as an additional tool for the rapid detection of heteroresistance. These methods collectively provide a versatile toolkit for researchers seeking to assess heteroresistance in C. albicans . They also serve as a critical step forward in the characterization of antifungal heteroresistance, providing a framework for investigating this phenomenon in diverse fungal species and in the context of other antifungal agents. Ultimately, these advancements will enhance our ability to effectively measure antifungal drug responses and combat fungal infections. IMPORTANCE Heteroresistance involves varying antimicrobial susceptibility within a clonal population. This phenomenon allows the survival of rare resistant subpopulations during drug treatment, significantly complicating the effective management of infections. However, the absence of established detection methods hampers progress in understanding this phenomenon in human fungal pathogens. We propose a comprehensive toolkit to address this gap in the yeast Candida albicans , encompassing population analysis profiling, single-cell assays, and disk diffusion assays. By providing robust and correlated measurements through both solid and liquid assays, this work will provide a framework for broader applications across clinically relevant Candida species. These methods will enhance our ability to understand this phenomenon and the failure of antifungal therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".