Effects of metapopulation structure and recombination on bacterial populations
Author(s)
Connor, Thomas Richard
Type
Thesis
Abstract
Bacteria are subject to a wide variety of complementary and competing forces which work to
shape the populations observed in the natural world. In the case of bacterial pathogens,
epidemiological factors play a significant role in the evolution of a pathogenic species, and
the relatively low diversities observed on a global scale in significant pathogens may be due
to the phenomenon of a microepidemic population structure, operating in concert with
homologous recombination and mutation.
In this work I explicitly define the microepidemic population concept in population genetics
terms, and examine its consequences for pathogen population structure and inference of
population characteristics from data. I make use of simulated metapopulations to model
simplified populations composed of neutral microepidemics in order to examine the varying
effects of homologous recombination and mutation in pathogens. The analysis is then
extended to include different kinds of selection, both at an individual level and at a
metapopulation level, to investigate the consequences of these processes, and to contrast with
the results from neutral populations.
With the increasing number of resources containing large, globally sampled strain
collections, I also examine the effects of metapopulation structure on population genetic
methods of analysis which have been applied to bacterial datasets (including Gst, the Neutral
Microepidemic Model, and IA). Using simulated populations I consider these methods in light
of database limitations such as those arising from the longitudinally sampled nature of the
collections, and those introduced by geographic over- and undersampling.
This is followed by an examination of the effectiveness of some of the methods using
sequence data (phylogenetics, BAPS and ClonalFrame) which are commonly employed to
ask questions relating to population structure. The work concludes with the application of
these methods to examine the population genetics of several bacteria of interest.
shape the populations observed in the natural world. In the case of bacterial pathogens,
epidemiological factors play a significant role in the evolution of a pathogenic species, and
the relatively low diversities observed on a global scale in significant pathogens may be due
to the phenomenon of a microepidemic population structure, operating in concert with
homologous recombination and mutation.
In this work I explicitly define the microepidemic population concept in population genetics
terms, and examine its consequences for pathogen population structure and inference of
population characteristics from data. I make use of simulated metapopulations to model
simplified populations composed of neutral microepidemics in order to examine the varying
effects of homologous recombination and mutation in pathogens. The analysis is then
extended to include different kinds of selection, both at an individual level and at a
metapopulation level, to investigate the consequences of these processes, and to contrast with
the results from neutral populations.
With the increasing number of resources containing large, globally sampled strain
collections, I also examine the effects of metapopulation structure on population genetic
methods of analysis which have been applied to bacterial datasets (including Gst, the Neutral
Microepidemic Model, and IA). Using simulated populations I consider these methods in light
of database limitations such as those arising from the longitudinally sampled nature of the
collections, and those introduced by geographic over- and undersampling.
This is followed by an examination of the effectiveness of some of the methods using
sequence data (phylogenetics, BAPS and ClonalFrame) which are commonly employed to
ask questions relating to population structure. The work concludes with the application of
these methods to examine the population genetics of several bacteria of interest.
Date Issued
2011
Date Awarded
2011-02
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Hanage, Bill
Spratt, Brian
Fraser, Christophe
Sponsor
BBSRC
Creator
Connor, Thomas Richard
Publisher Department
Infectious Disease Epidemiology
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)