The Heterogeneity, Distribution, and Environmental Associations of Borrelia burgdorferi Sensu Lato, the Agent of Lyme Borreliosis, in Scotland

Marianne C. James, Lucy Gilbert, Alan S. Bowman, Ken J. Forbes

Lyme borreliosis is an emerging infectious human disease caused by the Borrelia burgdorferi sensu lato complex of bacteria with reported cases increasing in many areas of Europe and North America. To understand the drivers of disease risk and the distribution of symptoms, which may improve mitigation and diagnostics, here we characterize the genetics, distribution, and environmental associations of B. burgdorferi s.l. genospecies across Scotland. In Scotland, reported Lyme borreliosis cases have increased almost 10-fold since 2000 but the distribution of B. burgdorferi s.l. is so far unstudied. Using a large survey of over 2200 Ixodes ricinus tick samples collected from birds, mammals, and vegetation across 25 sites we identified four genospecies: Borrelia afzelii (48%), Borrelia garinii (36%), Borrelia valaisiana (8%), and B. burgdorferi sensu stricto (7%), and one mixed genospecies infection. Surprisingly, 90% of the sequence types were novel and, importantly, up to 14% of samples were mixed intra-genospecies co-infections, suggesting tick co-feeding, feeding on multiple hosts, or multiple infections in hosts. B. garinii (hosted by birds) was considerably more genetically diverse than B. afzelii (hosted by small mammals), as predicted since there are more species of birds than small mammals and birds can import strains from mainland Europe. Higher proportions of samples contained B. garinii and B. valaisiana in the west, while B. afzelii and B. garinii were significantly more associated with mixed/deciduous than with coniferous woodlands. This may relate to the abundance of transmission hosts in different regions and habitats. These data on the genetic heterogeneity within and between Borrelia genospecies are a first step to understand pathogen spread and could help explain the distribution of patient symptoms, which may aid local diagnosis. Understanding the environmental associations of the pathogens is critical for rational policy making for disease risk mitigation and land management.