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          Institute: MPI für molekulare Genetik     Collection: Independent Junior Research Groups (Otto-Warburg-Laboratory)     Display Documents

ID: 406326.0, MPI für molekulare Genetik / Independent Junior Research Groups (Otto-Warburg-Laboratory)
Classification and identification of bacteria by mass spectrometry and computational analysis
Authors:Sauer, Sascha; Freiwald, Anja; Maier, Thomas; Kube, Michael; Reinhardt, Richard; Kostrzewa, Markus; Geider, Klaus
Research Context:This work was supported by the German Ministry of Education and Research, the European Union and the Max-Planck Society
Date of Publication (YYYY-MM-DD):2008-07-30
Title of Journal:PLoS One
Issue / Number:7
Start Page:e2843
End Page:e2843
Full name of Issue-Editor(s):Ching-Hong Yang, University of Wisconsin-Milwaukee, United States of America
Copyright:© 2008 Sauer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Review Status:not specified
Audience:Experts Only
Abstract / Description: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.
Comment of the Author/Creator:Competing interests: The authors T.M. and M.Ko. declare competing financial interests. T.M. and M.Ko. are employed by the mass spectrometry company Bruker Daltonik.

E-mail: sauer@molgen.mpg.de
External Publication Status:published
Document Type:Article
Version Comment:Automatic journal name synchronization
Communicated by:OWL-Group
Affiliations:MPI für molekulare Genetik
External Affiliations:1.Bruker Daltonik, Leipzig, Germany;
2.Julius Kuehn Institute for Plant Protection in Fruit Crops and Viticulture, Dossenheim, Germany.
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