Global Stress Responses Identify the Functionally Divergent Regulators Required for <i>Candida auris</i> Commensalism and Pathogenicity
Bibliographic record
Abstract
ABSTRACT Given its global distribution and high transmissibility in the environment, Candida auris poses a serious threat to global public health. However, the underlying mechanisms of its adaptive strategies remain poorly understood. Here we delineate the pan‐genome structures of 1,306 representative C. auris isolates collected from 28 countries. In addition to the clade‐related genetic diversity and highly variable pan‐genomes, we identify the key regulatory modules and genes specific to C. auris in response to 32 different host microenvironment‐mimicking stresses. Through comparative analysis with evolutionarily close fungal relatives, we uncover both shared and species‐specific transcriptional responses in C. auris . Intriguingly, our results reveal a distinct pathogenic role for the conserved iron regulon in this species. Unexpectedly, we also identify an evolutionarily divergent functional role for RIM101 in regulating both pathogenicity and commensalism of C. auris . Mechanistically, the high‐affinity glucose transporters were found to enhance the tolerance to alkaline stress through alleviation of RIM101 ‐dependent glucose repression in the host microenvironment. These findings provide mechanistic insights into the evolutionarily divergent adaptive strategies in both commensalism and virulence of the emerging critical priority fungal pathogen, C. auris .
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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".