Literature DB >> 20486690

Identification of Yersinia pestis and Escherichia coli strains by whole cell and outer membrane protein extracts with mass spectrometry-based proteomics.

Rabih E Jabbour1, Mary Margaret Wade, Samir V Deshpande, Michael F Stanford, Charles H Wick, Alan W Zulich, A Peter Snyder.   

Abstract

Whole cell protein and outer membrane protein (OMP) extracts were compared for their ability to differentiate and delineate the correct database organism to an experimental sample and for the degree of dissimilarity to the nearest neighbor database organism strains. These extracts were isolated from pathogenic and nonpathogenic strains of Yersinia pestis and Escherichia coli using ultracentrifugation and a sarkosyl extraction method followed by protein digestion and analysis using liquid chromatography tandem mass spectrometry (MS). Whole cell protein extracts contain many different types of proteins resident in an organism at a given phase in its growth cycle. OMPs, however, are often associated with virulence in Gram-negative pathogens and could prove to be model biomarkers for strain differentiation among bacteria. The mass spectra of bacterial peptides were searched, using the SEQUEST algorithm, against a constructed proteome database of microorganisms in order to determine the identity and number of unique peptides for each bacterial sample. Data analysis was performed with the in-house BACid software. It calculated the probabilities that a peptide sequence assignment to a product ion mass spectrum was correct and used accepted spectrum-to-sequence matches to generate a sequence-to-bacterium (STB) binary matrix of assignments. Validated peptide sequences, either present or absent in various strains (STB matrices), were visualized as assignment bitmaps and analyzed by the BACid module that used phylogenetic relationships among bacterial species as part of a decision tree process. The bacterial classification and identification algorithm used assignments of organisms to taxonomic groups (phylogenetic classification) based on an organized scheme that begins at the phylum level and follows through the class, order, family, genus, and species to the strain level. For both Gram-negative organisms, the number of unique distinguishing proteins arrived at by the whole cell method was less than that of the OMP method. However, the degree of differentiation measured in linkage distance units on a dendrogram with the OMP extract showed similar or significantly better separation than the whole cell protein extract method between the sample and correct database match compared to the next nearest neighbor. The nonpathogenic Y. pestis A1122 strain used does not have its genome available, and thus, data analysis resulted in an equal similarity index to the nonpathogenic 91001 and pathogenic Antiqua and Nepal 516 strains for both extraction methods. Pathogenic and nonpathogenic strains of E. coli were correctly identified with both protein extraction methods, and the pathogenic Y. pestis CO92 strain was correctly identified with the OMP procedure. Overall, proteomic MS proved useful in the analysis of unique protein assignments for strain differentiation of E. coli and Y. pestis. The power of bacterial protein capture by the whole cell protein and OMP extraction methods was highlighted by the data analysis techniques and revealed differentiation and similarities between the two protein extraction approaches for bacterial delineation capability.

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Year:  2010        PMID: 20486690     DOI: 10.1021/pr100402y

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  7 in total

1.  Assessment of marker proteins identified in whole cell extracts for bacterial speciation using liquid chromatography electrospray ionization tandem mass spectrometry.

Authors:  Jennifer Kooken; Karen Fox; Alvin Fox; David Wunschel
Journal:  Mol Cell Probes       Date:  2013-08-29       Impact factor: 2.365

2.  A peptide identification-free, genome sequence-independent shotgun proteomics workflow for strain-level bacterial differentiation.

Authors:  Wenguang Shao; Min Zhang; Henry Lam; Stanley C K Lau
Journal:  Sci Rep       Date:  2015-09-23       Impact factor: 4.379

3.  Comparative Analysis of Two Helicobacter pylori Strains using Genomics and Mass Spectrometry-Based Proteomics.

Authors:  Roger Karlsson; Kaisa Thorell; Shaghayegh Hosseini; Diarmuid Kenny; Carina Sihlbom; Åsa Sjöling; Anders Karlsson; Intawat Nookaew
Journal:  Front Microbiol       Date:  2016-11-11       Impact factor: 5.640

4.  A gel-free proteomic-based method for the characterization of Bordetella pertussis clinical isolates.

Authors:  Yulanda M Williamson; Hercules Moura; Kaneatra Simmons; Jennifer Whitmon; Nikkol Melnick; Jon Rees; Adrian Woolfitt; David M Schieltz; Maria L Tondella; Edwin Ades; Jacquelyn Sampson; George Carlone; John R Barr
Journal:  J Microbiol Methods       Date:  2012-04-18       Impact factor: 2.363

Review 5.  "Omic" Approaches to Bacteria and Antibiotic Resistance Identification.

Authors:  Daria Janiszewska; Małgorzata Szultka-Młyńska; Paweł Pomastowski; Bogusław Buszewski
Journal:  Int J Mol Sci       Date:  2022-08-24       Impact factor: 6.208

Review 6.  Omics strategies for revealing Yersinia pestis virulence.

Authors:  Ruifu Yang; Zongmin Du; Yanping Han; Lei Zhou; Yajun Song; Dongsheng Zhou; Yujun Cui
Journal:  Front Cell Infect Microbiol       Date:  2012-12-13       Impact factor: 5.293

7.  Investigation of Yersinia pestis Laboratory Adaptation through a Combined Genomics and Proteomics Approach.

Authors:  Owen P Leiser; Eric D Merkley; Brian H Clowers; Brooke L Deatherage Kaiser; Andy Lin; Janine R Hutchison; Angela M Melville; David M Wagner; Paul S Keim; Jeffrey T Foster; Helen W Kreuzer
Journal:  PLoS One       Date:  2015-11-24       Impact factor: 3.240

  7 in total

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