The first established microsatellite markers to distinguish Candida orthopsilosis isolates and detection of a nosocomial outbreak in China

The infection proportion of Candida orthopsilosis, a member of the C. parapsilosis complex, has increased globally in recent years, and nosocomial outbreaks have been reported in several countries. This study aimed to establish microsatellite loci-based typing method that was able to effectively distinguish among C. orthopsilosis isolates. Three reference C. orthopsilosis genome sequences were analyzed to identify repeat loci. DNA sequences containing over eight bi- or more nucleotide repeats were selected. A total of 51 loci were initially identified, and locus-specific primers were designed and tested with 20 epidemiologically unrelated isolates. Four loci with excellent reproducibility, specificity, and resolution for molecular typing purposes were identified, and the combined discriminatory power (DP, based on 20 epidemiologically unrelated isolates) of these four loci was 1.0. Reproducibility was demonstrated by consistently testing three strains each in triplicate, and stability, demonstrated by testing 10 successive passages. Then, we collected 48 C. orthopsilosis non-duplicate clinical isolates from the China Hospital Invasive Fungal Surveillance Net study to compare the DP of the microsatellite-based typing with internal transcribed spacer (ITS) and amplified fragment length polymorphism (AFLP) typing analyses, using ATCC 96139 as a reference strain. These 49 isolates were subdivided into 12 microsatellite types (COMT1–12), six AFLP types, and three ITS types, while all the isolates with the same COMT belonged to consistent AFLP and ITS type, demonstrating the high DP of our microsatellite-type method. According to our results, COMT12 was found to be the predominant type in China, and COMT5 was the second largest and responsible for causing a nosocomial outbreak. This microsatellite-type method is a valuable tool for the differentiation of C. orthopsilosis and could be vital for epidemiological studies to determine strain relatedness and monitor transmission.