Abstract
AbstractUntangling how factors such as environment, host, associations between species and dispersal predict microbial dynamics is a fundamental challenge. In this study, we use a robust sampling design coupled with complementary machine-learning approaches to quantify the relative role of these factors in shaping microbiome variation of the blacklegged tickIxodes scapularis. I. scapularisis the most important vector forBorrelia burgdorferi. (the causative agent for Lyme disease) in the U.S as well as a range of other important zoonotic pathogens. Yet the relative role of the interactions between pathogens and symbionts compared to other ecological forces is unknown. We found that positive associations between microbes where the occurrence of one microbe increases the probability of observing another, including between both pathogens and symbionts, was by far the most important factor shaping the tick microbiome. Microclimate and host factors played an important role for a subset of the tick microbiome includingBorrelia(Borreliella) andRalstonia, but for the majority of microbes, environmental and host variables were poor predictors at a regional scale. This study provides new hypotheses on how pathogens and symbionts might interact within tick species, as well as valuable predictions for how some taxa may respond to changing climate.
Publisher
Cold Spring Harbor Laboratory