Organisms that cause disease often possess features that make evolutionary change likely over relatively short periods of time. The rise of multi-drug resistant bacteria and the switching of hosts (e.g., diseases shifting from animals to humans) are particularly notable examples. Despite the importance of evolutionary change, most epidemiological models assume that pathogens do not change. This project combines mathematical and experimental approaches to study the evolutionary dynamics of pathogens in subdivided populations (i.e., metapopulations). Using a model host-pathogen system (bacteria as hosts and viruses infecting bacteria as pathogens'), the pattern of host/pathogen movement between a large set of subpopulations will be experimentally manipulated and evolution of the pathogen monitored. Pairing these experiments with empirically-based mathematical models will allow an assessment of how the structure of the host-pathogen population influences the evolution of the pathogen. In particular, virulence in the pathogen (i.e., how quickly it kills its host) will be the focus of the research, as the evolution of virulence may depend intimately on the manner by which hosts contact one another.
This work has a range of broader impacts. One goal is the use of this system as an educational tool for postdoctoral, graduate and undergraduate students. In addition, the experimental system will be adapted to serve as a teaching tool within upper-level undergraduate courses. Underrepresented minorities and women will be actively recruited for involvement in the proposed research. Finally, the proposed work may highlight how subtle aspects of population structure could favor different evolutionary paths in human pathogens. Such information would carry important implications for public health management.
