Identificación de genes de resistencia antifúngica en Candida auris aislada de muestras clínicas: una aproximación bioinformática

Abstract

Candida auris infections represent a growing threat to public health because they can develop resistance to multiple antifungal agents, reducing treatment options and promoting persistent outbreaks in hospitals. Access to public genomic data in the United States enables a more accurate characterization of circulating variants and the evaluation of their resistance mechanisms. This study examined 207 complete genomes of C. auris isolated from clinical blood samples collected from several U.S. states: 9 from California, 86 from Minnesota, 9 from Tennessee, 20 from Texas, 47 from Utah, 12 from Washington, and 24 from Wisconsin. These genomes were obtained from the NCBI SRA database and processed using next-generation sequencing (NGS). Quality control was performed in Galaxy Australia using AQ 20 and AQ 30 thresholds, followed by genome assembly with SPAdes. Detection of resistance genes was carried out using Pathogenwatch. Approximately 90% of the isolates presented at least one mutation associated with antifungal resistance, with the most frequent being ERG11_K143R, ERG11_Y132F, and ERG11_F126L, all associated with decreased susceptibility to azoles. The frequency and combinations of mutations showed geographic variability, with significant clusters in Utah and Minnesota. The AQ 20 threshold maintained a broader diversity of variants, whereas AQ 30 enabled a more precise identification of clinically relevant mutations, highlighting the importance of standardizing analysis parameters. In conclusion, the combination of NGS and bioinformatics platforms is an effective tool for the genomic surveillance of C. auris, providing crucial information for decision-making in clinical and public health settings. This type of study, in addition to improving the detection and monitoring of multidrug-resistant strains, creates a methodological model that can be applied in areas with scarce genomic data, such as much of Latin America, contributing to strengthening the genomic surveillance of this emerging pathogen.