The molecular and genetic evolution of foot-and-mouth disease virus

Logan, Grace (2017) The molecular and genetic evolution of foot-and-mouth disease virus. PhD thesis, University of Glasgow.

Full text available as:
[thumbnail of 2017LoganPhD.pdf] PDF
Download (43MB)
Printed Thesis Information: https://eleanor.lib.gla.ac.uk/record=b3255184

Abstract

Foot-and-mouth disease virus (FMDV) (Family: Picornaviridae, Genus: Aphthovirus) is a significant global pathogen with extensive economic impact. FMDV has a low fidelity RNA-dependent RNA polymerase and lacks proof reading capability. This coupled with its relatively short generation time and large population sizes means it exists in a swarm of genetically closely related variants. The reservoir of diversity contained within this mutant spectrum allows the virus to adapt rapidly to new environments. Much of the previous work looking at virus evolution has focused on the consensus level genetic sequence. The advent of next generation sequencing (NGS) technologies enables evolutionary studies of the entire viral swarm. This PhD project uses NGS technologies to interrogate the swarm structure by investigating factors affecting the viral swarm and the dynamics of variants within it. Furthermore, this work shows how analysis of the swarm can reveal fundamental information about virus biology.

A PCR-free NGS methodology was developed to create deep sequencing data sets of all genomes present within an FMDV viral swarm. The elimination of the PCR step results in less errors being introduced in the sequencing process thereby improving the resolution and reliability of the identification of low level variants. This optimised method was then used to define and compare the FMDV swarms of several wildtype isolates. This revealed differences in swarm structure from isolate to isolate and produced evidence of within swarm selection. Not all proteins known to be under selection at the consensus level were also under selection within the swarm. The diversity of viruses within the swarm was found to be dependent upon the host from which a virus was sampled, with African buffalo potentially able to maintain multiple infections. Subconsensus variants in these mixed samples had mutations at positions previously associated with immune escape. Investigation of the evolution of swarm structure when adapting to new cell type in vitro indicated that two distinct population structures can exist relative to the existence of adaptive pressure. These two population structures have different distributions of variable nucleotides but comparative total levels of variation (as measured by Shannon's entropy). Deep sequencing of the virus swarm enabled the discovery of conserved novel stem loop structures, which were hypothesized to be required for packaging of the virus genome. Mutating these sites produced a virus with decreased packaging efficiency.

This thesis includes novel analysis techniques for considering the viral swarm. It demonstrates how investigating the diversity in the swarm can help us to understand virus molecular biology, its evolution and the limits upon this. Understanding viral evolution at this scale has the capacity to improve our fundamental understanding of the biology and evolution of FMDV which can in turn inform vaccine design and disease control strategies

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: FMDV, virus evolution, genetic evolution, NGS, viral packaging, Picornaviridae.
Subjects: Q Science > QR Microbiology > QR355 Virology
Colleges/Schools: College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
Supervisor's Name: Haydon, Professor D.T., Tuthill, Dr. T.J., Cottam, Dr. E.M. and King, Dr. D.P.
Date of Award: 2017
Depositing User: Dr G Logan
Unique ID: glathesis:2017-7877
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 07 Feb 2017 11:50
Last Modified: 10 Mar 2017 10:20
URI: https://theses.gla.ac.uk/id/eprint/7877

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year