Extensive Diversity and Prevalent Fluconazole Resistance among Environmental Yeasts from Tropical China
Bibliographic record
Abstract
Yeasts play important roles in both the environment and in human welfare. While some environmental yeasts positively contribute to nutrient cycling and food production, a significant number of yeast species are opportunistic human pathogens, including several that are tolerant/resistant to commonly used antifungal drugs. At present, most of our understanding of environmental yeasts has come from a few terrestrial environments in selected geographic regions. Relatively little is known about yeast diversity in tropical environments and their potential impacts on human health. Here, we characterize culturable yeasts in 968 environmental samples from eight regions in tropical China. Among the 516 soil, 273 freshwater, and 179 seawater samples, 71.5%, 85.7%, and 43.6% contained yeasts, respectively. A total of 984 yeast isolates were analyzed for their DNA barcode sequences and their susceptibilities to fluconazole. DNA sequence comparisons revealed that the 984 yeast isolates likely belonged to 144 species, including 106 known species and 38 putative novel species. About 38% of the 984 isolates belonged to known human pathogens and the most common species was Candida tropicalis, accounting for 21% (207/984) of all isolates. Further analyses based on multi-locus sequence typing revealed that some of these environmental C. tropicalis shared identical genotypes with clinical isolates previously reported from tropical China and elsewhere. Importantly, 374 of the 984 (38%) yeast isolates showed intermediate susceptibility or resistance to fluconazole. Our results suggest that these environmental yeasts could have significant negative impacts on human health.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".