Journal of Proteomics & Bioinformatics
Open Access

Abstract

Multivariate Statistical Analysis of Diverse Strains of Yersinia pestis by Comparative Proteomics

Todd H Corzett, Angela M Eldridge, Jennifer S Knaack, Christopher H Corzett, Sandra L McCutchen-Maloney and Brett A Chromy

To address the difficulty in characterizing unusual, engineered or emergent pathogens in clinical and environmental samples, novel methods to discover proteins that differentiate pathogenic strains are needed. Differentially expressed proteins that reveal the function of an uncharacterized strain of bacteria can be considered biomarkers; panels of these can lead to improved pathogen classification and characterization. To this end, the protein expression patterns of differentially virulent isolates of the plague pathogen, Yersinia pestis, were studied using two-dimensional difference gel electrophoresis (2-D DIGE). The resulting characterization was used to identify a protein expression panel for the clustering and classification of Y. pestis strains. Two different methods were used to produce different biomarker panels based on either experimental- or pattern-based clustering. Each panel is able to successfully classify unknown samples in a blinded fashion, allowing an unbiased discovery of differentially expressed proteins, as well as the rapid classification of protein expression patterns.