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Anal Chem. 2002 Jul 1;74(13):3174-82.

Mass spectrometric methods for generation of protein mass database used for bacterial identification.

Author information

1
Department of Chemistry, University of Alberta, Edmonton, Canada.

Abstract

The availability of a suitable database is critical in a proteomic approach for bacterial identification by mass spectrometry (MS). The major limitation of the present public proteome database is the lack of extensive low-mass bacterial protein entries with masses experimentally verified for most bacteria. Here, we present a method based on mass spectrometry to create protein mass tables specifically tailored for bacterial identification. Several issues related to the detection of bacterial proteins for the purpose of database creation are addressed. Three species of bacteria, namely, Escherichia coli, Bacillus megaterium, and Citrobacter freundii, which can be found in the ambient environment, were chosen for this study. Direct matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS analysis of each bacterial extract reveals 20-29 protein components in the mass range from 2000 to 20,000 Da. HPLC fractionation of bacterial extracts followed by off-line MALDI-TOF analysis of individual fractions detects 156-423 components. Analysis of the extracts by HPLC/electrospray ionization MS shows the number of detectable proteins in the range of 46-59. Although a number of components were common to the three detection schemes employed, some unique components were found using each of these techniques. In addition, for E. coli where a large proteome database exists in the public domain, a number of masses detected by the mass spectrometric methods do not match with the proteome database. Compared to the public proteome database, the mass tables generated in this work are demonstrated to be more useful for bacterial identification in an application where the bacteria of interest have limited protein entries in the public database. The implication of this work for future development of a comprehensive mass database is discussed.

PMID:
12141680
DOI:
10.1021/ac015725f
[Indexed for MEDLINE]

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