The endosomal sorting complex required for transport machinery influences haem uptake and capsule elaboration in <scp><i>C</i></scp><i>ryptococcus neoformans</i>
Bibliographic record
Abstract
Iron availability is a key determinant of virulence in the pathogenic fungus Cryptococcus neoformans. Previous work revealed that the ESCRT (endosomal sorting complex required for transport) protein Vps23 functions in iron acquisition, capsule formation and virulence. Here, we further characterized the ESCRT machinery to demonstrate that defects in the ESCRT-II and III complexes caused reduced capsule attachment, impaired growth on haem and resistance to non-iron metalloprotoporphyrins. The ESCRT mutants shared several phenotypes with a mutant lacking the pH-response regulator Rim101, and in other fungi, the ESCRT machinery is known to activate Rim101 via proteolytic cleavage. We therefore expressed a truncated and activated version of Rim101 in the ESCRT mutants and found that this allele restored capsule formation but not growth on haem, thus suggesting a Rim101-independent contribution to haem uptake. We also demonstrated that the ESCRT machinery acts downstream of the cAMP/protein kinase A pathway to influence capsule elaboration. Defects in the ESCRT components also attenuated virulence in macrophage survival assays and a mouse model of cryptococcosis to a greater extent than reported for loss of Rim101. Overall, these results indicate that the ESCRT complexes function in capsule elaboration, haem uptake and virulence via Rim101-dependent and independent mechanisms.
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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".