Genetic analysis of Hsp90 function in <i>Cryptococcus neoformans</i> highlights key roles in stress tolerance and virulence
Bibliographic record
Abstract
The opportunistic human fungal pathogen Cryptococcus neoformans has tremendous impact on global health, causing 181,000 deaths annually. Current treatment options are limited, and the frequent development of drug resistance exacerbates the challenge of managing invasive cryptococcal infections. In diverse fungal pathogens, the essential molecular chaperone Hsp90 governs fungal survival, drug resistance, and virulence. Therefore, targeting this chaperone has emerged as a promising approach to combat fungal infections. However, the role of Hsp90 in supporting C. neoformans pathogenesis remains largely elusive due to a lack of genetic characterization. To help dissect the functions of Hsp90 in C. neoformans, we generated a conditional expression strain in which HSP90 is under control of the copper-repressible promoter CTR4-2. Addition of copper to culture medium depleted Hsp90 transcript and protein levels in this strain, resulting in compromised fungal growth at host temperature; increased sensitivity to stressors, including the azole class of antifungals; altered C. neoformans morphology; and impaired melanin production. Finally, leveraging the fact that copper concentrations vary widely in different mouse tissues, we demonstrated attenuated virulence for the CTR4-2p-HSP90 mutant specifically in an inhalation model of Cryptococcus infection. During invasion and establishment of infection in this mouse model, the pathogen is exposed to the relatively high copper concentrations found in the lung as compared to blood. Overall, this work generates a tractable genetic system to study the role of Hsp90 in supporting the pathogenicity of C. neoformans and provides proof-of-principle that targeting Hsp90 holds great promise as a strategy to control cryptococcal infection.
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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 | 0.001 |
| 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".