Evaluation of three MALDI-TOF MS systems for the identification of common microorganisms
10.3760/cma.j.issn.1009-8158.2019.08.018
- VernacularTitle:三种基质辅助激光解吸电离飞行时间质谱系统对常见微生物鉴定结果的比较
- Author:
Linna ZHAO
1
;
Wei ZHANG
;
Na LIU
;
Shenghui CUI
Author Information
1. 中国食品药品检定研究院
- Keywords:
Spectrometry;
mass;
matrix-Assisted laser desorption-ionization;
Bacteria;
Yeasts
- From:
Chinese Journal of Laboratory Medicine
2019;42(8):679-687
- CountryChina
- Language:Chinese
-
Abstract:
Objective To compare the efficiency of domestic MALDI-TOF MS systems Autof MS, Korea Asta MicroIDsys and Bruker Biotyper for common microorganisms identification. Methods This is a methodological comparison study. A total of 169 strains were isolated either from food in our laboratory since 2011 to 2018 or clinical samples in Chinese PLA General Hospital since 2016 to 2018. A total of 39 genus, 95 species were identified through Vitek2 Compact combined with 16S rDNA or ITS sequencing. Among them, a total of 93 Gram-negative bacteria strains, 65 Gram-positive bacteria strains, and 11 yeast strains were identified by three MALDI-TOF MS systems parallelly, while using extended direct smear method for sample preparation. The SPSS 18.0 software was used for data Statistical analysis. Results By Mass spectrometry identification, when 169 strains were at the species level confidence score and acceptable score level, 91.12％ (154/169) was correctly identified to species level by Autof MS system, 86.39％ (146/169) by ASTA MS system, and 81.66％ (138 / 169) by Bruker Biotyper MS system. The difference of identification accuracy to species level between Autof MS and Bruker Biotyper MS was statistically significant. Besides, the accuracy of genus identi fi cation was 98.82％ (167 / 169) by Autof MS mass spectrometry system and 97.04％ (164 / 169) by both ASTA MicroIDsys and Bruker Biotyper mass spectrometry system. The differences of identification accuracy to genus level among the three MS systems were not significant. Conclusions All of the three MS systems have good identification capability for common microorganisms. Autof MS systems performed slightly better than Bruker Biotyper MS systems in species level identification.
