Genomic reconstruction of an azole-resistant Candida parapsilosis outbreak and the creation of a multilocus sequence typing scheme


Background. Fluconazole-resistant Candida parapsilosis has emerged as a significant healthcare-associated pathogen with a propensity to spread patient-to-patient and cause nosocomial outbreaks, similar to Candida auris. This study investigates a prolonged outbreak of fluconazole-resistant C. parapsilosis across multiple years and healthcare centers in Germany.
Methods. We employed whole-genome sequencing of isolates from the outbreak, other regions within Germany, and compared them with isolates from a global distribution to understand the molecular epidemiology of this outbreak. Additionally, we used the genomic dataset of 258 samples to identify loci with high discriminatory power to establish the first multi-locus sequence typing (MLST) strategy for C. parapsilosis.
Findings. A clonal, azole-resistant strain of C. parapsilosis was observed causing invasive infections over multiple years and in multiple hospitals within the outbreak city. Including this outbreak clone, we identified three distinct ERG11 Y132F azole-resistant lineages in Germany, marking the first description of this azole-resistance in the country and its endemic status. Using the novel MLST strategy, isolates were categorized into 31 sequence types, proving the utility of the typing scheme for genetic epidemiology and outbreak investigations as a rapid alternative to whole genome sequencing. Interpretation. Temporal and genomic reconstruction of the outbreak indicated that transfer of patients between healthcare facilities was likely responsible for the persistent reimportation of the drug-resistant clone and subsequent person-to-person transmission. This research underscores the importance of monitoring of C. parapsilosis epidemiology, not only in Germany but globally. The emergence of azole-resistant lineages necessitates continuous surveillance and rigorous infection control measures. By combining large-scale genomic epidemiology and introducing a novel typing method, our study offers valuable insights into the management of emerging healthcare-associated pathogens, with direct implications for public health and clinical practice.