<i>Candida auris</i> Metabolism and Growth Preferences in Physiologically Relevant Skin-like Conditions
Bibliographic record
Abstract
ABSTRACT Candida auris is an opportunistic, multidrug-resistant yeast with high capacity of skin colonization in healthcare settings, which can lead to subsequent infections with high mortality rates. Given the recent emergence of at least four distinct clades at the global scale, little remains known about how C. auris is so adept at growing on skin and the key genes and pathways it utilizes to metabolize the scarce nutrients available. Here, we identify the roles that conventional and alternative carbon metabolism genes and metabolic pathways have in facilitating C. auris growth through laboratory-based experiments and bioinformatics analyses. In artificial skin-like media, all four clades of C. auris were more capable of growing than C. albicans SC5314, a clinically relevant counterpart. By investigating the differential regulation of C. auris when growing in skin-like media as compared to rich fungal media, we uncovered hundreds of genes in multiple metabolic pathways. To further test the mechanisms of these metabolic pathways, we deleted several non-essential gene candidates including FOX2 (B9J08_002847), CAT2 (B9J08_000010), and ICL1 (B9J08_003374). The mutant strains all exhibited abrogated growth in skin-like media and demonstrated nutrient preferences that differed from the wild type. Thus, we propose a model of how C. auris has the capacity to metabolize nutrients that are naturally available on skin by changing its metabolic profile. Targeting these metabolic pathways to mitigate C. auris growth on skin is a potential avenue to explore in controlling the spread of this emerging human fungal pathogen. IMPORTANCE Candida auris is an emerging fungal pathogen with skin as its primary site of colonization and subsequent transmission. Here, we show the importance of conventional and alternative carbon metabolism for C. auris’ ability to grow in artificial skin-like media. This knowledge provides a better understanding of C. auris metabolism and sheds light on genes and pathways that could be targeted to interfere with persistent skin colonization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".