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Title: The population structure of bacterial pathogens
Author: Watkins, Eleanor Rose
ISNI:       0000 0004 6063 2982
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2015
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Populations of many bacterial pathogens are structured into discrete strains despite frequent genetic exchange. Although insights from several studies suggest that different selection pressures operate in different areas of the genome, few theoretical and conceptual frameworks of bacterial population structure examine the effects of distinct competitive processes acting on different loci in the genome, and fewer still have considered the metabolic genes despite their increasingly-recognised importance in virulence. Buckee et al. (2008) investigated the combined effects of ecological competition operating at metabolic genes and immunological competition at antigenic genes on strain diversity using a stochastic model. A key prediction was that prevalent strains should show stable, non-overlapping associations between alleles of antigenic and metabolic genes. In this work, the roles of ecological and immunological competition in structuring bacterial pathogen populations is explored further using a multidisciplinary approach of mathematical modelling and whole genome analysis, focusing in particular on the well-characterised pathogens Neisseria meningitidis and Streptococcus pneumoniae as detailed case studies. We find support for the hypothesis that ecological and immunological competition play roles in structuring pathogen populations - even if present at relatively low levels - including support at the whole genome level. After extending the mathematical framework to encompass virulence-associated genes, we explore the effects of strain-targeted vaccination. We find that metabolic and virulence-associated genes from vaccine-strains are observed following vaccination in association with non-vaccine strains. The final chapter demonstrates how multilocus mathematical models coupled with whole genome analysis can be used together to gain additional insight into the evolution and population structure of bacterial pathogens.
Supervisor: Gupta, Sunetra ; Maiden, Martin Sponsor: Jackson Scholarship ; Merton College
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available