English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Classification and identification of bacteria by mass spectrometry and computational analysis

Sauer, S., Freiwald, A., Maier, T., Kube, M., Reinhardt, R., Kostrzewa, M., et al. (2008). Classification and identification of bacteria by mass spectrometry and computational analysis. PLoS One, (7), e2843-e2843. doi:10.1371/journal.pone.0002843.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7F71-5 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7F72-3
Genre: Journal Article

Files

show Files
hide Files
:
journal.pone.0002843.pdf (Any fulltext), 422KB
Name:
journal.pone.0002843.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
eDoc_access: PUBLIC
License:
-

Locators

show

Creators

show
hide
 Creators:
Sauer, Sascha1, Author              
Freiwald, Anja1, Author              
Maier, Thomas, Author
Kube, Michael2, Author              
Reinhardt, Richard2, Author              
Kostrzewa, Markus, Author
Geider, Klaus, Author
Affiliations:
1Nutrigenomics and Gene Regulation (Sascha Sauer), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479662              
2High Throughput Technologies, Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433552              

Content

show
hide
Free keywords: -
 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.

Details

show
hide
Language(s): eng - English
 Dates: 2008-07-30
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: PLoS One
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: (7) Sequence Number: - Start / End Page: e2843 - e2843 Identifier: ISSN: 1932-6203