Loss of Opi3 causes a lipid imbalance that influences the virulence traits of Cryptococcus neoformans but not cryptococcosis
Bibliographic record
Abstract
The basidiomycete fungus Cryptococcus neoformans is a useful model for investigating mechanisms of fungal pathogenesis in mammalian hosts. This pathogen is the causative agent of cryptococcal meningitis in immunocompromised patients and is in the critical priority group of the World Health Organization fungal priority pathogens list. In this study, we employed a mutant lacking the OPI3 gene encoding a methylene-fatty-acyl-phospholipid synthase to characterize the role of phosphatidylcholine (PC) and lipid homeostasis in the virulence of C. neoformans. We first confirmed that OPI3 was required for growth in nutrient limiting conditions, a phenotype that could be rescued with exogenous choline and PC. Additionally, we established that loss of Opi3 and the lack of PC lead to an accumulation of neutral lipids in lipid droplets and alterations in major lipid classes. The growth defect of the opi3Δ mutant was also rescued by sorbitol and polyethylene glycol (PEG), a result consistent with protection of ER function from the stress caused by lipid imbalance. We then examined the impact of Opi3 on virulence and found that the dependence of PC synthesis on Opi3 caused reduced capsule size and this was accompanied by an increase in shed capsule polysaccharide and changes in cell wall composition. Further tests of virulence demonstrated that survival in alveolar macrophages and the ability to cause disease in mice were not impacted by loss of Opi3 despite the choline auxotrophy of the mutant in vitro. Overall, this work establishes the contribution of lipid balance to virulence factor elaboration by C. neoformans and suggests that host choline is sufficient to support proliferation during disease.
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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 | 0.001 |
| 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".