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.

Highlights

  • The application of whole genome sequencing (WGS) technology to infectious bacterial diseases has resulted in unprecedented advances in our ability to resolve epidemic data at the global scale [1,2], provided new insights into within-host replication processes [3], and been used to corroborate the importance of exhaustively identified transmission chains and social drivers of transmission [4,5]

  • Whole genome sequencing (WGS) offers the potential for unprecedented insight into infectious diseases spread at the individual-to-individual level

  • WGS data must be corroborated with epidemiological data in welldescribed systems, in order to enhance our confidence in their broader use

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Summary

Introduction

The application of whole genome sequencing (WGS) technology to infectious bacterial diseases has resulted in unprecedented advances in our ability to resolve epidemic data at the global scale [1,2], provided new insights into within-host replication processes [3], and been used to corroborate the importance of exhaustively identified transmission chains and social drivers of transmission [4,5]. Combining mathematical models and pathogen sequence data has been an area of increased attention in the epidemiology of fast-evolving RNA viruses [6,7,8,9], but is as yet largely unexplored for bacteria, for TB and other slow growing mycobacteria, where transmission intervals and routes tend to be more uncertain and evolutionary rates are slower, warranting more extensive sequence information. While this presents a unique set of challenges, WGS offers promising research solutions to this problem

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