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DOI 10.3389/fcimb.2023.1153544

Медицинская библиотека · Frontiers in cellular and infection microbiology · 2023

Rapid automated antifungal susceptibility testing system for yeasts based on growth characteristics.

Yu Jinhan, He Chun, Wang Tong, Zhang Ge, Li Jin, Zhang Jingjia, Kang Wei, Xu Yingchun, Zhao Ying

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

Fungal pathogens are a major threat to public health, as they are becoming increasingly common and resistant to treatment, with only four classes of antifungal medicines currently available and few candidates in the clinical development pipeline. Most fungal pathogens lack rapid and sensitive diagnostic techniques, and those that exist are not widely available or affordable. In this study, we introduce a novel automated antifungal susceptibility testing system, Droplet 48, which detects the fluorescence of microdilution wells in real time and fits growth characteristics using fluorescence intensity over time. We concluded that all reportable ranges of Droplet 48 were appropriate for clinical fungal isolates in China. Reproducibility within ±2 two-fold dilutions was 100%. Considering the Sensititre YeastOne Colorimetric Broth method as a comparator method, eight antifungal agents (fluconazole, itraconazole, voriconazole, caspofungin, micafungin, anidulafungin, amphotericin B, and 5-flucytosine) showed an essential agreement of >90%, except for posaconazole (86.62%). Category agreement of four antifungal agents (fluconazole, caspofungin, micafungin, and anidulafungin) was >90%, except for voriconazole (87.93% agreement). Two Candida albicans isolates and anidulafungin showed a major discrepancy (MD) (2.60%), and no other MD or very MD agents were found. Therefore, Droplet 48 can be considered as an optional method that is more automated and can obtain results and interpretations faster than previous methods. However, the optimization of the detection performance of posaconazole and voriconazole and promotion of Droplet 48 in clinical microbiology laboratories still require further research involving more clinical isolates in the future.

Для цитирования: Yu Jinhan, He Chun, Wang Tong, Zhang Ge, Li Jin, Zhang Jingjia, Kang Wei, Xu Yingchun, Zhao Ying. Rapid automated antifungal susceptibility testing system for yeasts based on growth characteristics.. Frontiers in cellular and infection microbiology. 2023. DOI: 10.3389/fcimb.2023.1153544.

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