基于基质辅助激光解析电离飞行时间质谱技术的快速沙门菌血清型分型

王鲁彦; 侯心娇; 孙慧颖; 刁保卫; 李杰; 闫梅英

Abstract

王鲁彦,侯心娇,孙慧颖,刁保卫,李杰,闫梅英.基于基质辅助激光解析电离飞行时间质谱技术的快速沙门菌血清型分型[J].Chinese journal of Epidemiology,2024,45(9):1266-1272

基于基质辅助激光解析电离飞行时间质谱技术的快速沙门菌血清型分型

Rapid serotyping of Salmonella based on matrix assisted laser desorption ionization-time of flight mass spectrometry

Received:March 14, 2024

DOI：10.3760/cma.j.cn112338-20240314-00121

KeyWord: 基质辅助激光解析电离飞行时间质谱血清分型沙门菌

English Key Word: Matrix assisted laser desorption ionization-time of flight mass spectrometry Serotyping Salmonella

FundProject:基于质谱法的沙门菌分型研究（KFYJ-2021-009）；主要沙门菌血清型荧光PCR鉴定技术（KFYJ-2021-027）

Author Name	Affiliation	E-mail
Wang Luyan	Yangxin County Center for Disease Control and Prevention of Shandong Province, Binzhou 251800, China
Hou Xinjiao	National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China School of Public Health, Shandong University, Jinan 250061, China
Sun Huiying	National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Diao Baowei	National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Li Jie	National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Yan Meiying	National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China	yanmeiying@icdc.cn

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Abstract:

目的应用基质辅助激光解析电离飞行时间质谱（MALDI-TOF MS）对常见沙门菌血清型进行鉴定，为临床早期精确治疗提供病原学依据。方法收集不同地区来源的500株菌株，采用血清凝集及基因组测序方法确定5种临床常见的沙门菌（包括伤寒沙门菌、甲型副伤寒沙门菌、鼠伤寒沙门菌、肠炎沙门菌、印第安纳沙门菌）血清型，提取菌株的蛋白复合物，进行图谱采集，构建肽指纹图谱数据库，利用不同模块算法建立沙门菌血清分型方法，然后用155株测试菌株评价该分型方法的准确性。结果建立了5种沙门菌血清型MALDI-TOF MS数据库，在此基础上建立基于匹配算法和基于神经元卷积网络机器学习方法的2种沙门菌血清型分型方法，通过测试菌株分别评价2种分型方法的鉴定效果，发现基于匹配算法的MALDI-TOF MS能够快速识别、鉴定5种临床常见的沙门菌血清型，对沙门菌血清型鉴定的准确率可达100.00%，分型的敏感性及特异性均达100.00%。而且，该分型方法用时短（15~20 min）、重复性好。而基于机器学习的方法不能准确区分不同的血清型，分型的敏感性及特异性分别为82.23%和95.81%。结论本研究建立的基于MALDI-TOF MS技术的沙门菌血清分型方法能够简便、快速、准确地进行临床常见沙门菌血清分型。

English Abstract:

Objective To establish a matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) assay for the identification of common Salmonella serotypes and provide etiology evidence for the early precise treatment of salmonellosis. Methods A total of 500 strains were collected from different regions and sources and five predominant Salmonella serotypes (Salmonella Typhi, Salmonella Paratyphi A, Salmonella Typhimurium, Salmonella Enteritidis, and Salmonella Indiana) of each strain was identified by agglutination test and whole-genome sequencing. The protein complex of the strains was extracted by using optimized pretreatment method to establish the fingerprint database of peptides for each Salmonella serotype. The new serotyping assays were established by using different modules based on the mass spectra database. Additional 155 strains with specified serotypes and variant sources were used to test and evaluate the accuracy of the new typing assays. Results Five MALDI-TOF MS databases were established, and two new serotyping assays were established via peptide fingerprint mapping/matching and machine learning of the neuronal convolutional network respectively based on the databases. The Results showed that the fingerprint matching approach could quickly identify five common Salmonella serotypes in clinical practice compared with the machine learning method, the accuracy of fingerprint matching assay to identify five Salmonella serotypes reached 100.00% and the serotyping can be conducted within a short time (15-20 minutes) and had a good reproducibility, while the machine learning method could not completely identify these serotypes. Moreover the sensitivity and specificity of fingerprint matching assay were all 100.00% respectively, while they were only 82.23% and 95.81% for machine learning method. Conclusion The established Salmonella serotyping assay based on MALDI-TOF MS in this study can easily, rapidly and accurately identify different serotypes of Salmonella.

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