The characterisation of foot-and-mouth disease viral populations subjected to host immune pressure

Foot-and-mouth disease virus (FMDV) typically exists within a replication site as a heterogeneous population. This diversity allows FMDV populations to rapidly adapt to new selection pressures, for example an immune response. High-throughput sequencing (HTS) technologies allow for this sequence diversity to be characterised, however challenges still exist to distinguish real biological variation from process-introduced error. To improve variant calling accuracy, artificial DNA and RNA based populations containing sequence variants at known positions and frequencies were created. These were used to systematically investigate the impact of different laboratory and bioinformatics protocols on variant calling and error generation in HTS datasets. Analysis revealed that variants as low as 0.2% could be predicted in all DNA populations and RNA samples with a high amount of template. While decreasing the amount of RNA input required higher frequency percentage thresholds and more technical replicates to maintain accuracy. The optimised pipeline was applied to FMDV infected epithelium samples derived from vaccinated cattle and identified capsid surface bound substitutions associated with immune escape, all of which were unique to individual viral populations. In order to establish more control over the viral and antibody input, an in vitro experiment was performed with FMDV passaged in the presence of sub-neutralising antibody serum derived from vaccinated cattle. HTS analysis identified capsid surface bound immune escape associated substitutions, unique to individual viral populations. This thesis includes a novel systematic approach to accurately characterise low-frequency variants and demonstrates the evolutionary nature of FMDV, with results suggesting at an individual replication site, immune escape evolution is a stochastic process. Characterising immune escape associated substitutions within FMDV populations has the capacity to improve the fundamental understanding of FMDV evolution which in turn can be used to inform vaccine design and FMD control strategies