Role of Ferroxidases in Iron Uptake and Virulence of <i>Cryptococcus neoformans</i>
Bibliographic record
Abstract
Iron acquisition is a critical aspect of the virulence of many pathogenic microbes, and iron limitation is an important defense mechanism for mammalian hosts. We are examining mechanisms of iron regulation and acquisition in the fungal pathogen Cryptococcus neoformans, and here, we characterize the roles of the ferroxidases Cfo1 and Cfo2. Cfo1 is required for the reductive iron uptake system that mediates the utilization of transferrin, an important iron source for C. neoformans during infection. The virulence of a cfo1 mutant was attenuated in a mouse model of cryptococcosis, and the mutant also displayed increased sensitivities to the antifungal drugs fluconazole and amphotericin B. Wild-type levels of drug sensitivity were restored by the addition of exogenous heme, which suggested that reduced levels of intracellular iron may curtail heme levels and interfere with ergosterol biosynthesis. We constructed green fluorescent protein (GFP) fusion proteins and found elevated expression of Cfo1-GFP upon iron limitation, as well as localization of the fusion to the plasma membrane. Trafficking to this location was disrupted by a defect in the catalytic subunit of cyclic AMP-dependent protein kinase. This result is consistent with findings from studies indicating an influence of the kinase on the expression of protein-trafficking functions in C. neoformans.
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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) | 0.000 | 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 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".