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Classification and identification of bacteria by mass spectrometry and computational analysis

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Item Type:Article
Title:Classification and identification of bacteria by mass spectrometry and computational analysis
Creators Name:Sauer, S. and Freiwald, A. and Maier, T. and Kube, M. and Reinhardt, R. and Kostrzewa, M. and Geider, K.
Abstract:Background: In general, the definite determination of bacterial species is a tedious process and requires extensive manual labour. Novel technologies for bacterial detection and analysis can therefore help microbiologists in minimising their efforts in developing a number of microbiological applications. Methodology: We present a robust, standardized procedure for automated bacterial analysis that is based on the detection of patterns of protein masses by MALDI mass spectrometry. We particularly applied the approach for classifying and identifying strains in species of the genus Erwinia. Many species of this genus are associated with disastrous plant diseases such as fire blight. Using our experimental procedure, we created a general bacterial mass spectra database that currently contains 2800 entries of bacteria of different genera. This database will be steadily expanded. To support users with a feasible analytical method, we developed and tested comprehensive software tools that are demonstrated herein. Furthermore, to gain additional analytical accuracy and reliability in the analysis we used genotyping of single nucleotide polymorphisms by mass spectrometry to unambiguously determine closely related strains that are difficult to distinguish by only relying on protein mass pattern detection. Conclusions: With the method for bacterial analysis, we could identify fire blight pathogens from a variety of biological sources. The method can be used for a number of additional bacterial genera. Moreover, the mass spectrometry approach presented allows the integration of data from different biological levels such as the genome and the proteome.
Keywords:Algorithms, Bacteria, Bacterial Gene Expression Regulation, Biological Models, Computational Biology, DNA Sequence Analysis, Erwinia, Genotype, Mass Spectrometry, Matrix-Assisted Laser Desorption-Ionization Mass Spectrometry, Microbiology, Phylogeny, Protein Databases, Proteomics, Software
Source:PLOS ONE
ISSN:1932-6203
Publisher:Public Library of Science (U.S.A.)
Volume:3
Number:7
Page Range:e2843
Date:30 July 2008
Official Publication:https://doi.org/10.1371/journal.pone.0002843
PubMed:View item in PubMed

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