Use of bacterial whole-genome sequencing to investigate local persistence and spread in bovine tuberculosis

• Main Authors: Hannah Trewby, David Wright, Eleanor L. Breadon, Samantha J. Lycett, Tom R. Mallon, Carl McCormick, Paul Johnson, Richard J. Orton, Adrian R. Allen, Julie Galbraith, Pawel Herzyk, Robin A. Skuce, Roman Biek, Rowland R. Kao
• Format: Article
• Language: English
• Published: Elsevier 2016-03-01
• Series: Epidemics
• Subjects: Bacterial evolution; Livestock disease; Molecular epidemiology; Mycobacterium bovis; Phylogeography
• Online Access: http://www.sciencedirect.com/science/article/pii/S1755436515000833

Mycobacterium bovis is the causal agent of bovine tuberculosis, one of the most important diseases currently facing the UK cattle industry. Here, we use high-density whole genome sequencing (WGS) in a defined sub-population of M. bovis in 145 cattle across 66 herd breakdowns to gain insights into local spread and persistence. We show that despite low divergence among isolates, WGS can in principle expose contributions of under-sampled host populations to M. bovis transmission. However, we demonstrate that in our data such a signal is due to molecular type switching, which had been previously undocumented for M. bovis. Isolates from farms with a known history of direct cattle movement between them did not show a statistical signal of higher genetic similarity. Despite an overall signal of genetic isolation by distance, genetic distances also showed no apparent relationship with spatial distance among affected farms over distances <5 km. Using simulations, we find that even over the brief evolutionary timescale covered by our data, Bayesian phylogeographic approaches are feasible. Applying such approaches showed that M. bovis dispersal in this system is heterogeneous but slow overall, averaging 2 km/year. These results confirm that widespread application of WGS to M. bovis will bring novel and important insights into the dynamics of M. bovis spread and persistence, but that the current questions most pertinent to control will be best addressed using approaches that more directly integrate WGS with additional epidemiological data.