Molecular characterization of Candida auris outbreak isolates in Qatar from patients with COVID-19 reveals the emergence of isolates resistant to three classes of antifungal drugs
Bibliographic record
Abstract
OBJECTIVES: During the COVID-19 pandemic in Qatar, many patients who were severely ill were colonized and infected by Candida auris, an invasive multidrug-resistant yeast pathogen that spreads through nosocomial transmission within healthcare facilities. Here, we investigated the molecular epidemiology of these C. auris isolates and the mechanisms associated with antifungal drug resistance. METHODS: Whole genomes of 76 clinical C. auris isolates, including 65 from patients with COVID-19 collected from March 2020 to June 2021, from nine major hospitals were sequenced on Illumina NextSeq. Single nucleotide polymorphisms were used to determine their epidemiological patterns and mechanisms for antifungal resistance. The data were compared with those published prior to the COVID-19 pandemic from 2018 to 2020 in Qatar. RESULTS: Genomic analysis revealed low genetic variability among the isolates from patients with and without COVID-19, confirming a clonal outbreak and ongoing dissemination of C. auris among various healthcare facilities. Based on antifungal susceptibility profiles, more than 70% (22/28) of isolates were resistant to both fluconazole and amphotericin B. Variant analysis revealed the presence of multi-antifungal resistant isolates with prominent amino acid substitutions: Y132F in ERG11 and V704L in CDR1 linked to reduced azole susceptibility and the emergence of echinocandin resistance samples bearing mutations in FKS1 in comparison with pre-COVID-19 pandemic samples. One sample (CAS109) was resistant to three classes of antifungal drugs with a unique premature stop codon in ERG3 and novel mutations in CDR2, which may be associated with elevated amphotericin B and azole resistance. DISCUSSION: Candida auris isolates from patients with COVID-19 and from most patient samples without COVID-19 in Qatar were highly clonal. The data demonstrated the emergence of multidrug-resistant strains that carry novel mutations linked to enhanced resistance to azoles, echinocandins, and amphotericin B. Understanding the epidemiology and drug resistance will inform the infection control strategy and drug therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".