Genomic analyses reveal high diversity and rapid evolution of <i>Pichia kudriavzevii</i> within a neonatal intensive care unit in Delhi, India
Bibliographic record
Abstract
ABSTRACT Pichia kudriavzevii causes life-threatening infections in immunocompromised hosts, including hospitalized neonates. This pathogen is intrinsically resistant to fluconazole, while uncommon P. kudriavzevii strains resistant to multiple antifungal drugs, including voriconazole, amphotericin B, and echinocandins, have also been reported from healthcare environments. Thus, understanding how P. kudriavzevii spread, persist, and adapt to healthcare settings could help us develop better infection management strategies. In this study, whole genome sequencing identifies multiple outbreaks of bloodstream infections in a single neonatal intensive care unit (NICU) over 5 years caused by genetically diverse strains of P. kudriavzevii . Interestingly, two genetically distinct clusters of P. kudriavzevii strains showed frequent loss of heterozygosity (LOH) events between two temporal samples. The first outbreak cluster (2015–2016) showed LOH at chromosomes 1, 4, and 5, and the other outbreak cluster (2020) exhibited LOH at chromosome 2. The circulation of two separate strain clusters of P. kudriavzevii suggests nosocomial transmission in the NICU in different time periods. Furthermore, we compared the transcriptomic profiles of three isolates of clusters I and II that exhibited distinct fluconazole and itraconazole MICs. While no significant difference in gene expression was found at the azole-target gene ERG11 or the ATP-binding cassette (ABC) transporter genes, such differences were found in genes involved in cell division and filamentation, such as SIR2 (sirtuin deacetylase) and RFA1 (replication factor A). Interestingly, increased filamentation was observed in clade I isolate exhibiting high fluconazole MICs. Together, our study indicates significant diversity, persistence, and rapid evolution of P. kudriavzevii within a single NICU.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".