Azole Resistance in Cryptococcus gattii from the Pacific Northwest: Investigation of the Role of <i>ERG11</i>
Bibliographic record
Abstract
Cryptococcus gattii is responsible for an expanding epidemic of serious infections in Western Canada and the Northwestern United States (Pacific Northwest). Some patients with these infections respond poorly to azole antifungals, and high azole MICs have been reported in Pacific Northwest C. gattii. In this study, multiple azoles (but not amphotericin B) had higher MICs for 25 Pacific Northwest C. gattii than for 34 non-Pacific Northwest C. gattii or 20 Cryptococcus neoformans strains. We therefore examined the roles in azole resistance of overexpression of or mutations in the gene (ERG11) encoding the azole target enzyme. ERG11/ACT1 mRNA ratios were higher in C. gattii than in C. neoformans, but these ratios did not differ in Pacific Northwest and non-Pacific Northwest C. gattii strains, nor did they correlate with fluconazole MICs within any group. Three Pacific Northwest C. gattii strains with low azole MICs and 2 with high azole MICs had deduced Erg11p sequences that differed at one or more positions from that of the fully sequenced Pacific Northwest C. gattii strain R265. However, the azole MICs for conditional Saccharomyces cerevisiae erg11 mutants expressing the 5 variant ERG11s were within 2-fold of the azole MICs for S. cerevisiae expressing the ERG11 gene from C. gattii R265, non-Pacific Northwest C. gattii strain WM276, or C. neoformans strains H99 or JEC21. We conclude that neither ERG11 overexpression nor variations in ERG11 coding sequences was responsible for the high azole MICs observed for the Pacific Northwest C. gattii strains we studied.
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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".