Multilocus sequence typing indicates diverse origins of invasive Candida tropicalis isolates in China

Background According to data from the China Hospital Invasive Fungal Surveillance Net (CHIF-NET) 2010, Candida tropicalis (C. tropicalis) is the third most common pathogen causing invasive candidiasis. Moreover, the majority of fluconazole-resistant C. tropicalis isolates were from a single hospital. Therefore, a molecular epidemiological survey is necessary to investigate the genetic relatedness of C. tropicalis isolates in China. Methods In this study, 48 C. tropicalis isolates causing invasive fungal infections from four tertiary hospitals in China were studied. All the isolates were identified by sequencing the internal transcribed spacer region. Antifungal susceptibility to triazoles, amphotericin B, and caspofungin was determined by the Clinical and Laboratory Standards Institute standard broth microdilution method. Multilocus sequence typing (MLST) was performed, and phylogenetic analysis was further performed by the eBURST and maximum parsimony (MP) methods to characterize the genetic relatedness of isolates. Results MLST discriminated 40 diploid sequence types (DSTs) among 48 isolates, including 36 novel DSTs, and the XYR1 gene showed the highest discriminatory power. The DSTs obtained from this study were compared with those of previously reported C. tropicalis isolates, and there was poor type alignment with regional strains. Nine groups and 11 singletons were identified by eBURST, whereas two groups and 10 subgroups were clustered by MP analysis. Generally, there were no obvious correlations between clonal clusters generated and the specimen source or hospital origin. Seven fluconazole-resistant isolates were confirmed and assigned to three distinguishable branches. Conclusions The results suggested diverse origins of invasive C. tropicalis isolates in China. Although most invasive C. tropicalis strains in the mainland of China were clustered with previously characterized Asian isolates, major C. tropicalis clusters identified in this study were genetically distinct from those of other geographic regions.