Ecological drivers of a vector borne pathogen: distribution and abundance of Borrelia burgdorferi sensu lato and its vector Ixodes ricinus in Scotland

Vector-borne disease emergence in recent decades has been associated with different environmental drivers including changes in habitat, hosts and climate. Lyme borreliosis is among the most important vector-borne diseases in the Northern hemisphere and is an emerging disease in Scotland. Transmitted by Ixodid tick vectors between large numbers of wild vertebrate host species, Lyme borreliosis is caused by bacteria from the Borrelia burgdorferi sensu lato species group. Ecological studies can inform how environmental factors such as host abundance and community composition, habitat and landscape heterogeneity contribute to spatial and temporal variation in risk from B. burgdorferi s.l. In this thesis a range of approaches were used to investigate the effects of vertebrate host communities and individual host species as drivers of B. burgdorferi s.l. dynamics and its tick vector Ixodes ricinus. Host species differ in reservoir competence for B. burgdorferi s.l. and as hosts for ticks. Deer are incompetent transmission hosts for B. burgdorferi s.l. but are significant hosts of all life-stages of I. ricinus. Rodents and birds are important transmission hosts of B. burgdorferi s.l. and common hosts of immature life-stages of I. ricinus. In this thesis, surveys of woodland sites revealed variable effects of deer density on B. burgdorferi prevalence, from no effect (Chapter 2) to a possible ‘dilution’ effect resulting in lower prevalence at higher deer densities (Chapter 3). An invasive species in Scotland, the grey squirrel (Sciurus carolinensis), was found to host diverse genotypes of B. burgdorferi s.l. and may act as a spill-over host for strains maintained by native host species (Chapter 4). Habitat fragmentation may alter the dynamics of B. burgdorferi s.l. via effects on the host community and host movements. In this thesis, there was lack of persistence of the rodent associated genospecies of B. burgdorferi s.l. within a naturally fragmented landscape (Chapter 3). Rodent host biology, particularly population cycles and dispersal ability are likely to affect pathogen persistence and recolonization in fragmented habitats. Heterogeneity in disease dynamics can occur spatially and temporally due to differences in the host community, habitat and climatic factors. Higher numbers of I. ricinus nymphs, and a higher probability of detecting a nymph infected with B. burgdorferi s.l., were found in areas with warmer climates estimated by growing degree days (Chapter 2). The ground vegetation type associated with the highest number of I. ricinus nymphs varied between studies in this thesis (Chapter 2 & 3) and does not appear to be a reliable predictor across large areas. B. burgdorferi s.l. prevalence and genospecies composition was highly variable for the same sites sampled in subsequent years (Chapter 2). This suggests that dynamic variables such as reservoir host densities and deer should be measured as well as more static habitat and climatic factors to understand the drivers of B. burgdorferi s.l. infection in ticks. Heterogeneity in parasite loads amongst hosts is a common finding which has implications for disease ecology and management. Using a 17-year data set for tick infestations in a wild bird community in Scotland, different effects of age and sex on tick burdens were found among four species of passerine bird (Chapter 5). There were also different rates of decline in tick burdens among bird species in response to a long term decrease in questing tick pressure over the study. Species specific patterns may be driven by differences in behaviour and immunity and highlight the importance of comparative approaches. Combining whole genome sequencing (WGS) and population genetics approaches offers a novel approach to identify ecological drivers of pathogen populations. An initial analysis of WGS from B. burgdorferi s.s. isolates sampled 16 years apart suggests that there is a signal of measurable evolution (Chapter 6). This suggests demographic analyses may be applied to understand ecological and evolutionary processes of these bacteria. This work shows how host communities, habitat and climatic factors can affect the local transmission dynamics of B. burgdorferi s.l. and the potential risk of infection to humans. Spatial and temporal heterogeneity in pathogen dynamics poses challenges for the prediction of risk. New tools such as WGS of the pathogen (Chapter 6) and blood meal analysis techniques will add power to future studies on the ecology and evolution of B. burgdorferi s.l.

Applied evolution: An integrated approach to studying life history traits in response to drug selection

The use of chemical control measures to reduce the impact of parasite and pest species has frequently resulted in the development of resistance. Thus, resistance management has become a key concern in human and veterinary medicine, and in agricultural production. Although it is known that factors such as gene flow between susceptible and resistant populations, drug type, application methods, and costs of resistance can affect the rate of resistance evolution, less is known about the impacts of density-dependent eco-evolutionary processes that could be altered by drug-induced mortality. The overall aim of this thesis was to take an experimental evolution approach to assess how life history traits respond to drug selection, using a free-living dioecious worm (Caenorhabditis remanei) as a model. In Chapter 2, I defined the relationship between C. remanei survival and Ivermectin dose over a range of concentrations, in order to control the intensity of selection used in the selection experiment described in Chapter 4. The dose-response data were also used to appraise curve-fitting methods, using Akaike Information Criterion (AIC) model selection to compare a series of nonlinear models. The type of model fitted to the dose response data had a significant effect on the estimates of LD50 and LD99, suggesting that failure to fit an appropriate model could give misleading estimates of resistance status. In addition, simulated data were used to establish that a potential cost of resistance could be predicted by comparing survival at the upper asymptote of dose-response curves for resistant and susceptible populations, even when differences were as low as 4%. This approach to dose-response modeling ensures that the maximum amount of useful information relating to resistance is gathered in one study. In Chapter 3, I asked how simulations could be used to inform important design choices used in selection experiments. Specifically, I focused on the effects of both within- and between-line variation on estimated power, when detecting small, medium and large effect sizes. Using mixed-effect models on simulated data, I demonstrated that commonly used designs with realistic levels of variation could be underpowered for substantial effect sizes. Thus, use of simulation-based power analysis provides an effective way to avoid under or overpowering a study designs incorporating variation due to random effects. In Chapter 4, I 3 investigated how Ivermectin dosage and changes in population density affect the rate of resistance evolution. I exposed replicate lines of C. remanei to two doses of Ivermectin (high and low) to assess relative survival of lines selected in drug-treated environments compared to untreated controls over 10 generations. Additionally, I maintained lines where mortality was imposed randomly to control for differences in density between drug treatments and to distinguish between the evolutionary consequences of drug treatment versus ecological processes affected by changes in density-dependent feedback. Intriguingly, both drug-selected and random-mortality lines showed an increase in survivorship when challenged with Ivermectin; the magnitude of this increase varied with the intensity of selection and life-history stage. The results suggest that interactions between density-dependent processes and life history may mediate evolved changes in susceptibility to control measures, which could result in misleading conclusions about the evolution of heritable resistance following drug treatment. In Chapter 5, I investigated whether the apparent changes in drug susceptibility found in Chapter 4 were related to evolved changes in life-history of C. remanei populations after selection in drug-treated and random-mortality environments. Rapid passage of lines in the drug-free environment had no effect on the measured life-history traits. In the drug-free environment, adult size and fecundity of drug-selected lines increased compared to the controls but drug selection did not affect lifespan. In the treated environment, drug-selected lines showed increased lifespan and fecundity relative to controls. Adult size of randomly culled lines responded in a similar way to drug-selected lines in the drug-free environment, but no change in fecundity or lifespan was observed in either environment. The results suggest that life histories of nematodes can respond to selection as a result of the application of control measures. Failure to take these responses into account when applying control measures could result in adverse outcomes, such as larger and more fecund parasites, as well as over-estimation of the development of genetically controlled resistance. In conclusion, my thesis shows that there may be a complex relationship between drug selection, density-dependent regulatory processes and life history of populations challenged with control measures. This relationship could have implications for how resistance is monitored and managed if life histories of parasitic species show such eco-evolutionary responses to drug application.