Whole Genome Sequencing Reveals Local Transmission Patterns of Mycobacterium bovis in Sympatric Cattle and Badger Populations

Abstract

Whole genome sequencing (WGS) technology holds great promise as a tool for the forensic epidemiology of bacterial pathogens. It is likely to be particularly useful for studying the transmission dynamics of an observed epidemic involving a largely unsampled ‘reservoir’ host, as for bovine tuberculosis (bTB) in British and Irish cattle and badgers. BTB is caused by Mycobacterium bovis, a member of the M. tuberculosis complex that also includes the aetiological agent for human TB. In this study, we identified a spatio-temporally linked group of 26 cattle and 4 badgers infected with the same Variable Number Tandem Repeat (VNTR) type of M. bovis. Single-nucleotide polymorphisms (SNPs) between sequences identified differences that were consistent with bacterial lineages being persistent on or near farms for several years, despite multiple clear whole herd tests in the interim. Comparing WGS data to mathematical models showed good correlations between genetic divergence and spatial distance, but poor correspondence to the network of cattle movements or within-herd contacts. Badger isolates showed between zero and four SNP differences from the nearest cattle isolate, providing evidence for recent transmissions between the two hosts. This is the first direct genetic evidence of M. bovis persistence on farms over multiple outbreaks with a continued, ongoing interaction with local badgers. However, despite unprecedented resolution, directionality of transmission cannot be inferred at this stage. Despite the often notoriously long timescales between time of infection and time of sampling for TB, our results suggest that WGS data alone can provide insights into TB epidemiology even where detailed contact data are not available, and that more extensive sampling and analysis will allow for quantification of the extent and direction of transmission between cattle and badgers.

Author Summary

Whole genome sequencing (WGS) offers the potential for unprecedented insight into infectious diseases spread at the individual-to-individual level. However, this potential can be compromised when a poorly sampled ‘reservoir’ population contributes to transmission, as strong biases in the obtained data are inevitable. Therefore WGS data must be corroborated with epidemiological data in well-described systems, in order to enhance our confidence in their broader use. The epidemic of bovine tuberculosis (bTB) in British and Irish cattle has both economic and animal health importance; it also involves a management host (the cattle) whose demographic history is exceptionally well-documented, and with a reservoir host (the badgers) whose role in bTB spread has defied decades of study and observation. Here, we show that the observed spatial patterns provide a good match to M. bovis WGS data, but cattle movement networks and within-herd transmission patterns generated by mathematical models do not. Thus WGS offers considerable promise for revealing basic principles about bTB maintenance in British cattle and the role of badgers, as well as suggesting that similar approaches combining mathematical models and WGS data could be useful for the study of human TB and other infectious diseases where sampling biases are known to exist.