Rapid identification and typing of Yersinia pestis and other Yersinia species by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry

Author:

Ayyadurai Saravanan,Flaudrops Christophe,Raoult Didier,Drancourt Michel

Abstract

Abstract Background Accurate identification is necessary to discriminate harmless environmental Yersinia species from the food-borne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis and from the group A bioterrorism plague agent Yersinia pestis. In order to circumvent the limitations of current phenotypic and PCR-based identification methods, we aimed to assess the usefulness of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) protein profiling for accurate and rapid identification of Yersinia species. As a first step, we built a database of 39 different Yersinia strains representing 12 different Yersinia species, including 13 Y. pestis isolates representative of the Antiqua, Medievalis and Orientalis biotypes. The organisms were deposited on the MALDI-TOF plate after appropriate ethanol-based inactivation, and a protein profile was obtained within 6 minutes for each of the Yersinia species. Results When compared with a 3,025-profile database, every Yersinia species yielded a unique protein profile and was unambiguously identified. In the second step of analysis, environmental and clinical isolates of Y. pestis (n = 2) and Y. enterocolitica (n = 11) were compared to the database and correctly identified. In particular, Y. pestis was unambiguously identified at the species level, and MALDI-TOF was able to successfully differentiate the three biotypes. Conclusion These data indicate that MALDI-TOF can be used as a rapid and accurate first-line method for the identification of Yersinia isolates.

Publisher

Springer Science and Business Media LLC

Subject

Microbiology (medical),Microbiology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3