Proteasome inhibition as a therapeutic target for the fungal pathogen <i>Cryptococcus neoformans</i>
Bibliographic record
Abstract
ABSTRACT The current therapeutic challenges for treating fungal diseases demand new approaches and new drugs. A promising strategy involves combination therapy with agents of distinct mechanisms of action to increase fungicidal activity and limit the impact of mutations leading to resistance. In this study, we evaluated the antifungal potential of bortezomib by examining the inhibition of proteasome activity, cell proliferation, and capsule production by Cryptococcus neoformans , the causative agent of fungal meningoencephalitis. Chemical genetic screens with collections of deletion mutants identified potential druggable targets for combination therapy with bortezomib. In vitro assays of combinations of bortezomib with flucytosine, chlorpromazine, bafilomycin A1, copper sulfate, or hydroxyurea revealed antifungal effects against C. neoformans . Furthermore, combination treatment with bortezomib and flucytosine in a murine inhalation model of cryptococcosis resulted in the improvement of neurological functions and reduced fungal replication and dissemination, leading to a delay in disease progression. This study therefore highlights the utility of chemical genetic screens to identify new therapeutic approaches as well as the antifungal potential of proteasome inhibition. IMPORTANCE Fungal diseases of humans are difficult to treat, and there is a clear need for additional antifungal drugs, better diagnostics, effective vaccines, and new approaches to deal with emerging drug resistance. Fungi are challenging to control because they share many common biochemical functions with their mammalian hosts and it is therefore difficult to identify fungal-specific targets for drug development. One approach is to employ existing antifungal drugs in combination with agents that target common cellular processes at levels that are (ideally) not toxic for the host. We pursued this approach in this study by examining the potential of the clinically approved proteasome inhibitor bortezomib to influence the proliferation and virulence of Cryptococcus neoformans . We found that the combination of bortezomib with the anti-cryptococcal drug flucytosine improved the survival of infected mice, thus demonstrating the potential of this strategy for 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 | 0.001 |
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".