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采用优化分析方法的基质辅助激光解吸/电离飞行时间质谱法鉴定阪崎肠杆菌属菌种。

Identification of Cronobacter species by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry with an optimized analysis method.

作者信息

Wang Qi, Zhao Xiao-Juan, Wang Zi-Wei, Liu Li, Wei Yong-Xin, Han Xiao, Zeng Jing, Liao Wan-Jin

机构信息

Beijing Entry-Exit Inspection and Quarantine Bureau, Tianshuiyuan Street 6, Beijing 100026, China.

Beijing Entry-Exit Inspection and Quarantine Bureau, Tianshuiyuan Street 6, Beijing 100026, China.

出版信息

J Microbiol Methods. 2017 Aug;139:172-180. doi: 10.1016/j.mimet.2017.05.016. Epub 2017 May 27.

DOI:10.1016/j.mimet.2017.05.016
PMID:28559162
Abstract

Rapid and precise identification of Cronobacter species is important for foodborne pathogen detection, however, commercial biochemical methods can only identify Cronobacter strains to genus level in most cases. To evaluate the power of mass spectrometry based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF MS) for Cronobacter species identification, 51 Cronobacter strains (eight reference and 43 wild strains) were identified by both MALDI-TOF MS and 16S rRNA gene sequencing. Biotyper RTC provided by Bruker identified all eight reference and 43 wild strains as Cronobacter species, which demonstrated the power of MALDI-TOF MS to identify Cronobacter strains to genus level. However, using the Bruker's database (6903 main spectra products) and Biotyper software, the MALDI-TOF MS analysis could not identify the investigated strains to species level. When MALDI-TOF MS analysis was performed using the combined in-house Cronobacter database and Bruker's database, bin setting, and unweighted pair group method with arithmetic mean (UPGMA) clustering, all the 51 strains were clearly identified into six Cronobacter species and the identification accuracy increased from 60% to 100%. We demonstrated that MALDI-TOF MS was reliable and easy-to-use for Cronobacter species identification and highlighted the importance of establishing a reliable database and improving the current data analysis methods by integrating the bin setting and UPGMA clustering.

摘要

快速、准确地鉴定阪崎肠杆菌属物种对于食源性病原体检测至关重要,然而,在大多数情况下,商业生化方法只能将阪崎肠杆菌菌株鉴定到属水平。为了评估基于基质辅助激光解吸/电离飞行时间质谱(MALDI-TOF MS)鉴定阪崎肠杆菌属物种的能力,采用MALDI-TOF MS和16S rRNA基因测序对51株阪崎肠杆菌菌株(8株参考菌株和43株野生菌株)进行了鉴定。布鲁克公司提供的Biotyper RTC将所有8株参考菌株和43株野生菌株鉴定为阪崎肠杆菌属物种,这证明了MALDI-TOF MS将阪崎肠杆菌菌株鉴定到属水平的能力。然而,使用布鲁克公司的数据库(6903个主要光谱产物)和Biotyper软件,MALDI-TOF MS分析无法将所研究的菌株鉴定到种水平。当使用内部阪崎肠杆菌数据库与布鲁克公司的数据库相结合、进行分箱设置并采用算术平均的非加权配对组方法(UPGMA)聚类进行MALDI-TOF MS分析时,所有51株菌株被清晰地鉴定为6个阪崎肠杆菌属物种,鉴定准确率从60%提高到了100%。我们证明了MALDI-TOF MS在鉴定阪崎肠杆菌属物种方面可靠且易于使用,并强调了建立可靠数据库以及通过整合分箱设置和UPGMA聚类改进当前数据分析方法的重要性。

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