Role of clathrin-mediated endocytosis in the use of heme and hemoglobin by the fungal pathogen <i>Cryptococcus neoformans</i>
Bibliographic record
Abstract
Summary Heme is a major source of iron for pathogens of humans, and its use is critical in determining the outcome of infection and disease. Cryptococcus neoformans is an encapsulated fungal pathogen that causes life-threatening infections in immunocompromised individuals. C. neoformans effectively uses heme as an iron source but the underlying mechanisms are poorly defined. Non-iron metalloporphyrins (MPPs) are toxic analogues of heme and are thought to enter microbial cells via endogenous heme acquisition systems. We therefore carried out a mutant screen for susceptibility against manganese metalloporphyrin (Mn MPP) to identify new components for heme uptake in C. neoformans . We identified several genes involved in signaling, DNA repair, sugar metabolism and trafficking that play important roles in susceptibility to Mn MPP and in the use of heme as an iron source. We focused on investigating the role of clathrin-mediated endocytosis (CME) and found that several components of CME including Chc1, Las17, Rvs161 and Rvs167 are required for growth on heme and hemoglobin, and for endocytosis and intracellular trafficking of these molecules. We show that the hemoglobin uptake process in C. neoformans involves clathrin heavy chain, Chc1, which appears to co-localize with hemoglobin containing-vesicles and to potentially assist in proper delivery of hemoglobin to the vacuole. Additionally, C. neoformans strains lacking Chc1, Las17, Rvs161, or Rvs167 were defective in the elaboration of several key virulence factors and a las17 mutant was avirulent in a mouse model of cryptococcosis. Overall, this study unveils crucial functions of CME in the use of heme iron by C. neoformans and reveals a role for CME in fungal pathogenesis.
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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".