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.

Figure 1. Main holdings associated with herds in the dataset and badger locations by year.

Herd locations indicate centroids of main holdings, and do not include isolated land parcels or rented land.

Figure 2. Maximum likelihood network of M. bovis genomes with tips arranged according to sampling date.

Position of other nodes is simply shown for convenience and does not reflect known branch times. Black circles represent single nucleotide polymorphisms separating sequences, dashed lines indicates branches without mutational events. The size of the circle proportional to the number of isolates sharing the same sequence.

Figure 3. Genetic versus spatial and network distances.

On both axes, all values are scaled to the maximum value for herd-to-herd interactions. On the x-axes, the minimum number of SNPs differentiating isolates from the two herds (X-Y). In panel (A) above, spatial distance versus genetic distance between herds (black squares). On the y-axis, the cartesian distance between the main holdings of two herds (X-Y) showing a high level of correlation with genetic distance (R² = 0.720). For reference, the equivalent data for the badger isolates (not fitted) are shown as unfilled circles and diamonds for badger-badger and badger-herd relationships, respectively. Panel (B) below, network separation versus genetic distance between herds. On the y-axis, the network separation defined as (1−p_ij), where p_ij is the probability that herds i and j and linked via cattle movements through the network, considering all possible pathways through any herd from which the same genotype of M. bovis has been isolated, and p_animal is the per animal probability of contact that best explains the genetic distance data. The best fit value (p_animal = 1.35×10⁻³) shows a poor correlation with genetic distance (R² = 0.094).

Figure 4. Life histories of all cattle with from which Mycobacterium bovis samples of VNTR type 10 were obtained.

Showing all individuals residing within the five study herds at some time from 1994 to 2010. Cattle residence times indicated by the length of the horizontal bars (each bar representing a single animal). In black, all cattle from which sequences are derived (herd indicated by surrounding type). Test dates on which one herd received a whole herd test are indicated by vertical dashed lines. Herd colours correspond to colours in Figure 1 (1 – pink, 2 – purple, 3 – blue, 4 – orange, 5 – red).

Figure 5. Probabilities of pairwise transmission pathways amongst infected cattle with sequenced isolates.

The weighted, directed network shows the probability that a transmission path exists between cattle with sequenced isolates that does not pass through other sequenced isolates. Infection events poorly explained by transmission amongst reactor cattle are therefore more likely to be caused by a ‘reservoir’, which potentially encompasses infected badgers, between-herd interactions, latent infections, or environmental contamination. Sequences belonging to the same herd are surrounded by dashed outlines.