Identification of a Candida albicans Ferrichrome Transporter and Its Characterization by Expression inSaccharomyces cerevisiae
Bibliographic record
Abstract
Saccharomyces cerevisiae can accumulate iron through the uptake of siderophore-iron. Siderophore-iron uptake can occur through the reduction of the complex and the subsequent uptake of iron by the high affinity iron transporter Fet3p/Ftr1p. Alternatively, specific siderophore transporters can take up the siderophore-iron complex. The pathogenic fungus Candida albicans can also take up siderophore-iron. Here we identify a C. albicans siderophore transporter, CaArn1p, and characterize its activity. CaARN1 is transcriptionally regulated in response to iron. Through expression studies in S. cerevisiae strains lacking endogenous siderophore transporters, we demonstrate that CaArn1p specifically mediates the uptake of ferrichrome-iron. Iron-ferrichrome and gallium-ferrichrome, but not desferri-ferrichrome, could competitively inhibit the uptake of iron from ferrichrome. Uptake of siderophore-iron resulting from expression of CaARN1 under the control of the MET25-promoter in S. cerevisiae was independent of the iron status of the cells and of Aft1p, the iron-sensing transcription factor. These studies demonstrate that the expression of CaArn1p is both necessary and sufficient for the nonreductive uptake of ferrichrome-iron and suggests that the transporter may be the only required component of the siderophore uptake system that is regulated by iron and Aft1p.
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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".