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  • Title: Comparative evaluation of the Bruker Biotyper and Vitek MS matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) systems for non-albicans Candida and uncommon yeast isolates.
    Author: Teke L, Barış A, Bayraktar B.
    Journal: J Microbiol Methods; 2021 Jun; 185():106232. PubMed ID: 33961963.
    Abstract:
    INTRODUCTION: Rapid and accurate diagnosis is critically important in invasive and disseminated fungal infections for appropriate antifungal treatment. HYPOTHESIS: MALDI-TOF MS systems are effective for fast and accurate identification of Candida species. AIM: We aimed to compare two MALDI-TOF MS systems for the rapid identification of non-albicans Candida and rare clinical yeast species. METHODOLOGY: This study included 157 isolates representing 23 yeast species. All isolates were identified using Bruker MALDI Biotyper and VITEK MS systems. If both MALDI-TOF MS systems yielded the same results for a certain isolate, the identification is regarded as correct. We performed internal transcribed spacer (ITS) DNA sequencing on five fungal isolates with discordant species names or that were unidentified by the two MALDI-TOF MS systems. RESULTS: The yeast identification sensitivity of MALDI Biotyper was 98.7%, whereas that of VITEK MS was 96.8%. Both MALDI-TOF MS systems correctly identified all strains belonging to four prevalent species, namely, Candida parapsilosis, Candida tropicalis, Candida glabrata, and Candida krusei. For the 19 rare clinical yeast species, identification rates were 96.7% for MALDI Biotyper and 91.7% for VITEK MS. The ITS sequence analysis of five isolates yielded two Meyerozyma caribbica, two Cyberlindnera fabianii, and one Candida dubliniensis. CONCLUSIONS: This study showed the high performance of both MALDI-TOF MS systems, identifying over 90% of yeast isolates in a short time. The disadvantages of these systems are that some species are not present in the databases and it cannot distinguish closely related species. The sensitivity of MALDI-TOF MS systems constantly improves with the expansion of databases in parallel with taxonomic developments for the identification of rare clinical yeast species.
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