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Fingerprinting of Campylobacter jejuni by using resolution-optimized binary gene targets derived from comparative genome hybridization studies
Authors:Price Erin P  Huygens Flavia  Giffard Philip M
Institution:Cooperative Research Centre for Diagnostics, Institute of Health and Biomedical Innovation, Queensland University of Technology, Cnr Blamey St. and Musk Ave., Kelvin Grove, Queensland 4059, Australia.
Abstract:The aim of this investigation was to exploit the vast comparative data generated by comparative genome hybridization (CGH) studies of Campylobacter jejuni in developing a genotyping method. We examined genes in C. jejuni that exhibit binary status (present or absent between strains) within known plasticity regions, in order to identify a minimal subset of gene targets that provide high-resolution genetic fingerprints. Using CGH data from three studies as input, binary gene sets were identified with "Minimum SNPs" software. "Minimum SNPs" selects for the minimum number of targets required to obtain a predefined resolution, based on Simpson's index of diversity (D). After implementation of stringent criteria for gene presence/absence, eight binary genes were found that provided 100% resolution (D=1) of 20 C. jejuni strains. A real-time PCR assay was developed and tested on 181 C. jejuni and Campylobacter coli isolates, a subset of which have previously been characterized by multilocus sequence typing, flaA short variable region sequencing, and pulsed-field gel electrophoresis. In addition to the binary gene real-time PCR assay, we refined the seven-member single nucleotide polymorphism (SNP) real-time PCR assay previously described for C. jejuni and C. coli. By normalizing the SNP assay with the respective C. jejuni and C. coli ubiquitous genes, mapA and ceuE, the polymorphisms at each SNP could be determined without separate reactions for every polymorphism. We have developed and refined a rapid, highly discriminatory genotyping method for C. jejuni and C. coli that uses generic technology and is amenable to high-throughput analyses.
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