The application of whole genome sequencing approaches to elucidate the genetic structure, phylogeny and infection dynamics of Mycobacterium avium subspecies paratuberculosis in Ireland

Mycobacterium avium subspecies paratuberculosis (MAP) is the causative agent of Johne’s
disease (JD) in ruminants, a chronic enteric disease that is a burden on the cattle industry.
Having a clear picture of the genetic diversity of a pathogen provides an understanding of its
biology and epidemiology, both of which are crucial for improving and refining control of
the disease. The main aim of this thesis was therefore to apply whole genome sequencing
(WGS) methodology as a means of studying MAP genetic diversity and infection dynamics
across the island of Ireland.
To initiate the WGS analyses, several techniques for method optimisation were first
pursued, including DNA extraction, library preparation and computational analysis of
sequence data. I then used these optimised methods to explore whether there was an
obvious genetic basis for the suspected attenuation of a clinical Irish MAP isolate, CIT003,
that had been used in an experimental infection study of cattle that failed to progress to
infection. These analyses found mutations in several genes that may have led to attenuation
of the CIT003 strain used, including prpB, which encodes methylcitrate lyase (MCL), a key
enzyme in the methylcitrate metabolic cycle responsible for metabolising fatty acids. These
in silico leads these were then followed up by in vitro culture experiments, revealing the
potential impact of these mutations on growth in vivo.
The next stage was to apply WGS to a collection of 197 MAP isolates from the years 2013-
2019, spanning 27 Irish counties. When compared with previously used MIRU-VNTR
methods, WGS demonstrated considerably better resolution, revealing that Irish isolates fell
into eight distinct clades separated by as much as ~200 SNPs. Isolate data also revealed
cases of mixed infection within herds, as well as identical isolates being present in different
areas of the country, suggesting MAP infection is spread across the island via cattle trade
networks. An attempt to expand upon the temporal depth in the Irish MAP dataset by
sequencing isolates from 2004 and 2005 was attempted, but this effort was met with
contamination issues present in the samples.
By integrating published datasets from across Europe, Australia, Canada, and the US it was
found that most European isolates clustered together with Irish isolates, while most
Canadian, US and Australian isolates formed their own clades. A simple preliminary
coalescent model in BEAST indicated that most Irish and European isolates share a common
ancestry somewhere within the last 50-100 years. The BEAST model also estimated a
substitution rate of 0.25-0.27 SNPs/genome/year for MAP, which is consistent with
previously published rates.
The final approach was to use WGS at a finer scale on specific problem herds identified
during the work, seeking to establish the levels of genetic diversity within these herds, and
resolve potential transmission chains. Isolates within the problem herd ‘Cork 10’ were found
to be highly similar, with the combination of WGS and computational approaches able to
resolve a transmission chain linking the similar isolates together. However, herd ‘Tyrone
CaA’ showed high intra-herd variation, confounding the resolution transmission chains. The
opportunistic nature of sampling carried out in these herds limited the temporal depth
captured, and in both cases affected the ability to resolve transmission chains.
Overall, the data presented in this thesis highlights the utility and resolution offered by WGS
and sheds new light on the MAP global genetic diversity, as well as infection transmission
and persistent infection in herds in Ireland.