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Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases
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 effecti...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930211/ https://www.ncbi.nlm.nih.gov/pubmed/33680993 http://dx.doi.org/10.3389/fcimb.2021.628828 |
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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 |
author_facet | 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 |
author_sort | Yi, Qiaolian |
collection | PubMed |
description | 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 Candida parapsilosis complex, 323 of Candida albicans complex, 95 of Candida glabrata complex, 16 of Candida haemulonii complex (including two Candida auris), and 315 of Cryptococcus neoformans 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; C. albicans complex, 99.4% vs 96.3%; C. parapsilosis complex, 99.0% vs 79.1%; C glabrata complex, 98.9% vs 94.7%; C. haemulonii complex, 100% vs 93.8%; and C. neoformans, 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. |
format | Online Article Text |
id | pubmed-7930211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79302112021-03-05 Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases 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 Front Cell Infect Microbiol Cellular and Infection Microbiology 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 Candida parapsilosis complex, 323 of Candida albicans complex, 95 of Candida glabrata complex, 16 of Candida haemulonii complex (including two Candida auris), and 315 of Cryptococcus neoformans 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; C. albicans complex, 99.4% vs 96.3%; C. parapsilosis complex, 99.0% vs 79.1%; C glabrata complex, 98.9% vs 94.7%; C. haemulonii complex, 100% vs 93.8%; and C. neoformans, 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. Frontiers Media S.A. 2021-02-18 /pmc/articles/PMC7930211/ /pubmed/33680993 http://dx.doi.org/10.3389/fcimb.2021.628828 Text en Copyright © 2021 Yi, Xiao, Fan, Zhang, Yang, Zhang, Duan, Cheng, Li, Zhou, Yu, Huang, Chen, Hou, Kong, Kudinha and Xu http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cellular and Infection Microbiology 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 Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases |
title | Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases |
title_full | Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases |
title_fullStr | Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases |
title_full_unstemmed | Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases |
title_short | Evaluation of Autof MS 1000 and Vitek MS MALDI-TOF MS System in Identification of Closely-Related Yeasts Causing Invasive Fungal Diseases |
title_sort | evaluation of autof ms 1000 and vitek ms maldi-tof ms system in identification of closely-related yeasts causing invasive fungal diseases |
topic | Cellular and Infection Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930211/ https://www.ncbi.nlm.nih.gov/pubmed/33680993 http://dx.doi.org/10.3389/fcimb.2021.628828 |
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