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Lopez-Peralta, E.

Publications and source records attributed to Lopez-Peralta, E..

2 recordsLinked to original sources

Nationwide Spread of Fluconazole-Resistant Candida parapsilosis Clones: Insights from the Antifungal Resistance Surveillance Program

Background: Outbreaks of fluconazole-resistant Candida parapsilosis have recently emerged worldwide. In Spain, this phenomenon has been reported since 2020, mainly involving isolates from different clones harbouring the Y132F mutation at Erg11. Methods: We analysed the expansion of fluconazole resistant C. parapsilosis strains within the national antifungal resistance surveillance program. Genetic clustering and relationships were assessed using microsatellite typing and whole genome sequencing. Findings: We identified the expansion of three distinct clones carrying the Y132F mutation. Additionally, there was an increase in strains harbouring the G458S mutation, most of which belonged to a clonal complex, although other less prevalent clones were also detected. G458S isolates showed higher resistance to azoles than Y132F strains, particularly to voriconazole and isavuconazole. This increased resistance was associated with mutations in the Tac1 transcriptional regulator and duplication of a chromosomal region containing Tac1 and Erg11. One G458S isolate without mutation at Tac1 exhibited lower MIC values. Furthermore, two isolates carried the K143R mutation, and a distinct group of resistant strains without detectable ERG11 mutations was also identified. Resistant cases were detected across 31 hospitals in 12 autonomous regions. Interpretation: Our findings indicate a concerning nationwide expansion of antifungal-resistant C. parapsilosis in Spain, involving multiple resistance mechanisms and clonal lineages, with implications for antifungal treatment and infection control strategies.

microbiology↗

Dissection of genotype-phenotype relationships in Candida parapsilosis uncovers drivers of clinically-relevant traits

Hospital outbreaks caused by the fungal pathogen Candida parapsilosis are of growing concern due to their increased drug resistance and high mortality rates. However, the genetic bases of clinically-relevant traits in this species remain poorly explored. Here, we mapped genotype-phenotype relationships across 189 isolates from a multi-hospital Candida parapsilosis outbreak, for which we measured 61 diverse clinical phenotypes and generated complete genome sequences. As variation in previously-known genes explained little of the observed phenotypic diversity, we leveraged convergence genome-wide association studies and interpretable machine-learning models that predict phenotypes from genetic variants. These approaches identified candidate drivers of virulence and antifungal resistance, confirming expected mechanisms while uncovering novel ones. Predictive models were accurate for key traits, including azole resistance and clinical features of infected patients. Our results shed light on the genetic bases of clinically-relevant traits in a major fungal pathogen, and pave the way towards sequence-based diagnostics for improved patient outcomes.

microbiology↗