Individual animals are typically home to a staggeringly complex community of smaller organisms. This observation has led researchers to consider individuals as ecosystems in their own right.
The gut is an important example of how such within-individual ecosystems might affect host physiology and health and consequently ecological and evolutionary dynamics of wild animals. In vertebrates the gut is home to trillions of ‘friendly’ bacteria (the ‘microbiota’) which have an essential role in extracting nutrition from the food they eat. Conversely, the gut is also home to diverse communities of parasites which compete with their host for resources and can cause serious illness. However, our current understanding of the drivers of the relationship among members of the gut ecosystem and their consequences for host fitness in natural populations is very limited.
This project will apply next-generation sequencing methods to faecal samples collected from Soay sheep which are part of the larger long-term study on St Kilda. This will allow us to monitor variation in gut bacteria, protozoan and nematode communities and diet over seasons, years and individuals. We will address fundamental outstanding questions about which factors drive gut community dynamics within individuals and the outcomes of these dynamics for health and fitness under natural conditions. Our project will also involve the development and application of a novel statistical approach to integrate data on gut community ecology with our understanding of host ecology and genetics. These new ecological and epidemiological models will transform our understanding of how the gut ecosystem impacts on host population and disease dynamics in nature.
The project has four over-arching aims – illustrated in the diagram below:
AIM 1: To determine how host factors (e.g. genotype, age, sex, immune phenotype) and environmental factors (e.g. climate, shared habitat, diet) interact to predict variation in the structure of gut communities.
AIM 2: To test the drivers of sub-community (bacteria, coccidia, nematode) interactions in the host gut.
AIM 3: To test how interactions among the gut bacteria and parasite sub-communities, diet and host immune phenotype combine to shape host fitness.
AIM 4: To build predictive models of host demography and parasite epidemiology that incorporate the new understanding of gut community dynamics arising from aims 1-3.