Abstract

Background: Candida is the main causative agent of severe mucosal and invasive candidiasis. Different species of Candida have shown varying levels of resistance to antifungal treatments. It is estimated that each 12-hour delay in antifungal treatment is associated with a significant increase in patient mortality and treatment costs. The culture method is regarded as the gold standard for identifying Candida species, but its time-consuming process is a clear disadvantage. Objectives: This study established a method using membrane technology combined with dual-target melting analysis for rapid cultivation and identification of common Candida species. This method is expected to preserve the advantages of the conventional culture method and improve upon its weaknesses while also evaluating the practical application of the method. Methods: A microfiltration membrane-based culture followed by a color indicator method was established to rapidly cultivate Candida cultures. The 5.8S ribosomal DNA region and internal transcribed spacer 2 (ITS2) region were used as target gene regions, for which two sets of primers were employed. Melting analysis following dual-target real-time polymerase chain reaction (PCR) was conducted to distinguish among Candida albicans, C. tropicalis, C. glabrata, and C. krusei. To evaluate its practical application, the method was tested with 72 clinical isolates, and the results were compared with those obtained using the chromogenic culture method and DNA sequencing. Results: Distinctive melting temperatures in the two gene targets were detected among the four common Candida species. The entire process, from cultivation to identification, was completed within 12 hours, about 50% less time than the gold-standard method. The minimum detection limit of Candida species was 10 femtograms. The results of the identification of the clinical isolates were consistent with those of DNA sequencing. Conclusions: The short-term membrane-based cultivation combined with dual-target melting analysis can be used to rapidly, easily, and accurately identify common Candida species, thus reducing the time needed to initiate targeted treatment for patients with severe candidiasis.

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