NERC GW4+ DTP PhD Studentship: How community composition impacts host-parasite coevolution

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP). The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus six Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology, the Met Office, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme, please see http://nercgw4plus.ac.uk/.

Supervisory team -
Main Supervisor: Dr Ben Ashby, Department of Mathematical Sciences, University of Bath
Co-Supervisor: Prof. Angus Buckling, Environment and Sustainability Institute, University of Exeter

Project background -

Understanding the fundamental processes and mechanisms that underpin host-parasite coevolution is a major challenge in evolutionary biology, with significant implications for improving disease management strategies and gaining insights into core biological phenomena. Our knowledge of co-evolution is largely based on studies of pairwise interactions, but hosts and parasites do not exist in isolation; they interact with other potentially harmful or co-operative species in complex communities. Yet precisely how the community affects co-evolution is currently unclear.

This project will develop novel theory to understand how the community affects host-parasite co-evolution. Using mathematical modeling, the student will address how the nature of the community (e.g. antagonistic/mutualistic) affects the outcome of co-evolution (e.g.
directional/fluctuating selection, monomorphism/polymorphism). The student will also study how diffuse co-evolution unfolds when communities consist of multiple hosts or parasites, and will have the opportunity to test key aspects of the theory using experimental evolution of microbial communities.

Project aims and methods -

The central aim of the project is to develop general theory that predicts how host-parasite coevolution unfolds in complex communities. The student will examine how community structure and composition affect the qualitative outcome of host-parasite co-evolution, integrating network analysis, community ecology, and evolutionary biology. In particular, they will address whether certain types of communities (e.g. antagonistic or mutualistic) strengthen or weaken the co-evolutionary dynamics of a focal host and parasite. They will also address whether directional or fluctuating selection become more or less common depending on community composition and whether species with broadly similar characteristics (e.g. antagonists) have a qualitatively similar impact on the outcome. The student will then investigate the dynamics of diffuse co-evolution between multiple hosts and parasites (i.e. how do predictions differ when multiple hosts and parasites co-evolve?).

The student will apply a wide range of modeling techniques to address these questions, including approaches from population genetics, quantitative genetics, adaptive dynamics, and evolutionary game theory, along with numerical analysis and individual based modeling. In
addition to the core theoretical work, the student will have the opportunity to visit the Buckling laboratory to test their predictions through experimental evolution of bacteria and phages.

Candidate -

The successful student will have a strong background in mathematics and a keen interest in modeling biological systems. Prior laboratory experience would be ideal but is not required.

Training -

The student will receive training in a range of mathematical modeling and analytic techniques, including population genetics, quantitative genetics, adaptive dynamics, evolutionary game theory, as well as methods for numerical analysis and individual based modeling through computer simulations (Ashby). During the laboratory placement, the student would also receive training in experimental evolution and co-evolution, general and molecular microbiology and genome resequencing. Specifically, the student will conduct co-evolutionary experiments under a variable community context and determine the phenotypic and genomic consequences (Buckling).

Anticipated start date: 1 October 2018

Candidates should apply using the University of Bath’s online application form selecting PhD programme in Mathematics https://www.bath.ac.uk/study/pg/applications.pl#math-sci

For more information about the Department of Mathematical Sciences at Bath, please visit http://www.bath.ac.uk/math-sci/