Detecting population trends for tick-borne pathogens from genomic data: new tools for managing Lyme disease in Scotland

Roman Biek, Paul Everest (III), Roger Evans (NHS Highland)

Combining whole genome sequencing of bacterial pathogens with "phylodynamic" inference methods for detecting population size changes through time, has the potential to revolutionise our understanding of zoonotic pathogen dynamics and their responses to changes in their environment. This project proposes to assess the feasibility of such an approach using the tick-borne bacterial pathogen Borrelia sp, the agent of Lyme disease, as a test case. By whole genome sequencing both historic and contemporary field isolates of Borrelia from Scotland, the project will compile baseline information on recombination, spatial structure, and evolutionary rates. More specifically, these data will be used to test whether the genomic data contain evidence for a recent population expansion of Borrelia in Scotland, as suggested by a ten-fold rise in human cases over the past decade. This study will lay the groundwork for a broader research program on Lyme disease epidemiology and genomics, aimed at identifying long-term population trends, their environmental drivers, and the genetic basis of evolutionary responses in Lyme disease pathogens.