HapX Positively and Negatively Regulates the Transcriptional Response to Iron Deprivation in Cryptococcus neoformans
Bibliographic record
Abstract
The fungal pathogen Cryptococcus neoformans is a major cause of illness in immunocompromised individuals such as AIDS patients. The ability of the fungus to acquire nutrients during proliferation in host tissue and the ability to elaborate a polysaccharide capsule are critical determinants of disease outcome. We previously showed that the GATA factor, Cir1, is a major regulator both of the iron uptake functions needed for growth in host tissue and the key virulence factors such as capsule, melanin and growth at 37°C. We are interested in further defining the mechanisms of iron acquisition from inorganic and host-derived iron sources with the goal of understanding the nutritional adaptation of C. neoformans to the host environment. In this study, we investigated the roles of the HAP3 and HAPX genes in iron utilization and virulence. As in other fungi, the C. neoformans Hap proteins negatively influence the expression of genes encoding respiratory and TCA cycle functions under low-iron conditions. However, we also found that HapX plays both positive and negative roles in the regulation of gene expression, including a positive regulatory role in siderophore transporter expression. In addition, HapX also positively regulated the expression of the CIR1 transcript. This situation is in contrast to the negative regulation by HapX of genes encoding GATA iron regulatory factors in Aspergillus nidulans and Schizosaccharomyces pombe. Although both hapX and hap3 mutants were defective in heme utilization in culture, only HapX made a contribution to virulence, and loss of HapX in a strain lacking the high-affinity iron uptake system did not cause further attenuation of disease. Therefore, HapX appears to have a minimal role during infection of mammalian hosts and instead may be an important regulator of environmental iron uptake functions. Overall, these results indicated that C. neoformans employs multiple strategies for iron acquisition during infection.
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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".