Elucidating the unknown ecology of bacterial pathogens from genomic data

Seecharran, T.K., 2018. Elucidating the unknown ecology of bacterial pathogens from genomic data. PhD, Nottingham Trent University.

Preview

Text Tristan.Seecharran-2018.pdf - Published version Download (10MB) | Preview

Abstract

Our knowledge and understanding of how bacterial pathogens have evolved has been limited by inadequate information on the full ecology of these organisms. Large-scale population genomic analyses have enabled a high-resolution view of variation at the core and accessory genome level, within and between bacterial populations, revealing previously hidden patterns of variation among microorganisms. This sheds light on the evolution and maintenance of ecologically distinct populations of bacteria and has raised the question of whether the same approach can uncover novel information on the ecology of established, clinically important pathogens. Yersinia pseudotuberculosis and Escherichia coli represent 'model' organisms in the study of microbial evolution, but given the high degree of niche overlap in both species, their ecology is largely unknown.

In this study, genomic analyses of Y. pseudotuberculosis strains, obtained from various habitats worldwide, revealed a phylogeographic split within the population, with an Asian ancestry and subsequent dispersal of successful clonal lineages across the rest of the world. These lineages were differentiated by CRISPR arrays and we demonstrated that genetic exchange between lineages is restricted. Despite the coexistence of these lineages for thousands of years, the discrete lineage structure of the population is maintained due to the restriction of inter-lineage genetic exchange. The analyses did not identify a role for ecological barriers in defining the distinct lineage structure of the species, suggesting that Y. pseudotuberculosis is a host generalist able to succeed in multiple habitats.

The relative abundance of multidrug-resistant extraintestinal pathogenic E. coli (ExPEC) among E. coli inhabiting non-human niches is undetermined, owing to many studies selectively isolating resistant bacteria. To compare the population structure of E. coli from non-human environments with the well-defined population structure of human-clinical E. coli, unbiased sampling of E. coli isolates from river water and retail poultry samples was undertaken. Genomic analysis of isolates revealed a low prevalence of clinically-associated sequence types and potential ExPEC strains among non-human E. coli when contrasted with human-clinical E. coli, suggesting two distinct populations. Comparative genomic analyses further supported this, revealing a noticeable difference in accessory genome content between the two populations and low levels of genetic exchange between closely related strains. This suggests ecological barriers, resulting in gradual genetic isolation, may have contributed to the divergence of these niche-associated populations of E. coli. The investigation concluded that the non-human population of E. coli is unlikely to contribute significantly to the weight of hospital- and community-acquired extraintestinal infections in humans.

Item Type:	Thesis
Creators:	Seecharran, T.K.
Date:	June 2018
Rights:	I hereby declare that the work presented in this thesis is the result of original research carried out by the author, unless otherwise stated. No material contained herein has been submitted for any other degree, or at any other institution. This work is an intellectual property of the author. You may copy up to 5% of this work for private study, or personal, non-commercial research. Any re-use of the information contained within this document should be fully referenced, quoting the author, title, university, degree level and pagination. Queries or requests for any other use, or if a more substantial copy is required, should be directed in the owner(s) of the Intellectual Property Rights.
Divisions:	Schools > School of Science and Technology
Record created by:	Linda Sullivan
Date Added:	07 Jan 2019 11:38
Last Modified:	07 Jan 2019 11:38
URI:	https://irep.ntu.ac.uk/id/eprint/35484

Actions (login required)

Edit View

Views

Downloads