Identification of Bacillus anthracis by Using Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry and Artificial Neural Networks

Author:

Lasch Peter1,Beyer Wolfgang2,Nattermann Herbert3,Stämmler Maren1,Siegbrecht Enrico1,Grunow Roland3,Naumann Dieter1

Affiliation:

1. P25

2. Institute for Environmental and Animal Hygiene and Veterinary Medicine at the University of Hohenheim, Garbenstraße 30, D-70599 Stuttgart, Germany

3. ZBS2, Robert Koch-Institut, Nordufer 20, D-13353 Berlin, Germany

Abstract

ABSTRACT This report demonstrates the applicability of a combination of matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) and chemometrics for rapid and reliable identification of vegetative cells of the causative agent of anthrax, Bacillus anthracis. Bacillus cultures were prepared under standardized conditions and inactivated according to a recently developed MS-compatible inactivation protocol for highly pathogenic microorganisms. MALDI-TOF MS was then employed to collect spectra from the microbial samples and to build up a database of bacterial reference spectra. This database comprised mass peak profiles of 374 strains from Bacillus and related genera, among them 102 strains of B. anthracis and 121 strains of B. cereus . The information contained in the database was investigated by means of visual inspection of gel view representations, univariate t tests for biomarker identification, unsupervised hierarchical clustering, and artificial neural networks (ANNs). Analysis of gel views and independent t tests suggested B. anthracis - and B. cereus group-specific signals. For example, mass spectra of B. anthracis exhibited discriminating biomarkers at 4,606, 5,413, and 6,679 Da. A systematic search in proteomic databases allowed tentative assignment of some of the biomarkers to ribosomal protein or small acid-soluble proteins. Multivariate pattern analysis by unsupervised hierarchical cluster analysis further revealed a subproteome-based taxonomy of the genus Bacillus . Superior classification accuracy was achieved when supervised ANNs were employed. For the identification of B. anthracis , independent validation of optimized ANN models yielded a diagnostic sensitivity of 100% and a specificity of 100%.

Publisher

American Society for Microbiology

Subject

Ecology,Applied Microbiology and Biotechnology,Food Science,Biotechnology

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