AUTHOR=Yi Qiaolian , Xiao Meng , Fan Xin , Zhang Ge , Yang Yang , Zhang Jing-Jia , Duan Si-Meng , Cheng Jing-Wei , Li Ying , Zhou Meng-Lan , Yu Shu-Ying , Huang Jing-Jing , Chen Xin-Fei , Hou Xin , Kong Fanrong , Kudinha Timothy , Xu Ying-Chun 

TITLE=Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=11

YEAR=2021

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2021.628828

DOI=10.3389/fcimb.2021.628828

ISSN=2235-2988

ABSTRACT=<p>Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been accepted as a rapid, accurate, and less labor-intensive method in the identification of microorganisms in clinical laboratories. However, there is limited data on systematic evaluation of its effectiveness in the identification of phylogenetically closely-related yeast species. In this study, we evaluated two commercially available MALDI-TOF systems, Autof MS 1000 and Vitek MS, for the identification of yeasts within closely-related species complexes. A total of 1,228 yeast isolates, representing 14 different species of five species complexes, including 479 of <italic>Candida parapsilosis</italic> complex, 323 of <italic>Candida albicans</italic> complex, 95 of <italic>Candida glabrata</italic> complex, 16 of <italic>Candida haemulonii</italic> complex (including two <italic>Candida auris</italic>), and 315 of <italic>Cryptococcus neoformans</italic> complex, collected under the National China Hospital Invasive Fungal Surveillance Net (CHIF-NET) program, were studied. Autof MS 1000 and Vitek MS systems correctly identified 99.2% and 89.2% of the isolates, with major error rate of 0.4% versus 1.6%, and minor error rate of 0.1% versus 3.5%, respectively. The proportion of isolates accurately identified by Autof MS 1000 and Vitek MS per each yeast complex, respectively, was as follows; <italic>C. albicans</italic> complex, 99.4% vs 96.3%; <italic>C. parapsilosis</italic> complex, 99.0% vs 79.1%; <italic>C glabrata</italic> complex, 98.9% vs 94.7%; <italic>C. haemulonii</italic> complex, 100% vs 93.8%; and <italic>C. neoformans</italic>, 99.4% vs 95.2%. Overall, Autof MS 1000 exhibited good capacity in yeast identification while Vitek MS had lower identification accuracy, especially in the identification of less common species within phylogenetically closely-related species complexes.</p>