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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Champion, Olivia Lucy
Languages: English
Types: Doctoral thesis
Subjects:
Despite being the principal bacterial cause of gastroenteritis world wide, the\ud epidemiology of Campylobacter jejuni is poorly understood. This is largely because\ud the proportion of human disease caused by different sources of infection is unknown.\ud In this study a diverse strain collection was selected comprising of 91C. jejuni isolates\ud from diverse animal and environmental ecological niches as well as clinical isolates\ud from patients representing a range of disease outcomes. Whole genome comparisons\ud were performed by DNA microarray analysis with the dual aim of identifying genetic\ud markers specific to strains from different ecological niches and identifying novel\ud virulence determinants.\ud A new phylogenomic technique for the analysis of DNA microarray data was\ud developed combining Bayesian algorithms to model phylogeny based on whole\ud genome data with parsimony based algorithms to identify the key genes contributing\ud to the clade formations. This method revealed a previously undetected C. jejuni\ud population structure comprising two main clades, a "chicken clade" and a "nonchicken\ud clade". These statistically supported clades differentiated strains from distinct\ud ecological niches with 94% of strains isolated from chickens and 41% of clinical\ud isolates contained within the "chicken clade". C. jejuni isolates from ovine, bovine\ud and sand isolates also formed distinct clades within the "non-chicken clade". Key\ud genes contributing to the distinction of strains from one ecological niche from another\ud were identified. In particular a putative glycosylation islet cj 1321-cj 1326 was found\ud to be present in strains within the "chicken clade" but absent or divergent from strains\ud in the "non-chicken clade', a result validated by peR screening. This locus represents\ud a potential genetic marker of C. jejuni strains of avian origin.\ud The DNA microarray data analysis method described in this study may be used to\ud study other bacterial pathogens facilitating the identification of bacterial phylogenies\ud and genetic markers associated with specific phenotypes.

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