Glutathione metabolism impacts fungal virulence by modulating the redox environment
Bibliographic record
Abstract
Pathogens must overcome the hostile conditions of their hosts to survive, proliferate and cause disease. The fungal pathogen Cryptococcus neoformans is particularly adept at mitigating challenges in the host environment and has developed an arsenal of defense mechanisms to evade oxidative and nitrosative agents released by phagocytic cells during infection. Among these mechanisms, melanin production is crucially linked to both fungal virulence and defense against harmful free radicals that facilitate host innate immunity and clearance of invading pathogens. Here, we employed comparative global metabolomics to demonstrate that metabolism of the antioxidant glutathione (GSH) is inextricably linked to redox-active processes that facilitate melanin production, and that genetic perturbations in GSH biosynthesis affect fungal growth and virulence in a murine model of cryptococcosis. Furthermore, we show that disruption of GSH biosynthesis leads to overaccumulation of reducing and acidic compounds in the extracellular environment of mutant cells. These changes not only impacted melanin formation but also influenced titan cell and urease production as well as survival in macrophages. Overall, these findings highlight the importance of redox homeostasis and metabolic compensation in pathogen adaptation to the host environment and suggest new avenues for antifungal drug development.
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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 | 0.000 | 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) | 0.001 | 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".