COS 80-3
Multi-scale relationships of parasite co-infection of populations and individual wild mice

Wednesday, August 12, 2015: 2:10 PM
319, Baltimore Convention Center
Evelyn Rynkiewicz, Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
Andy Fenton, School of Biological Sciences, University of Liverpool, Liverpool, United Kingdom
Amy B. Pedersen, Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
Background/Question/Methods

Although most individuals are co-infected, we have little knowledge of how and why their parasite communities are structured. Using tools from community ecology to study patterns of disease has elucidated interactions among host resources, the immune response, and between co-infecting parasites. These processes can lead to non-random assembly of parasite communities, where those of low species richness are subsets of high richness communities, known as nestedness. Parasite-parasite and parasite-host interactions, as well as targeted parasite treatments with drugs or other therapies, occur at the individual scale yet parasite prevalence and measurements of disease epidemiology occur at the population scale. We hypothesized that patterns of parasite associations at the host population level would provide a framework for making testable predictions of how individuals become co-infected. We tested this hypothesis using cross-sectional and longitudinal data collected from wild mice and their parasite communities.

Results/Conclusions

We tested the nestedness of within-host communities of 7 taxonomically diverse parasite species infecting wild wood mice (Apodemus sylvaticus) in Northern England sampled from 2009-2011. We found significant nestedness in these within-host communities, meaning communities were not random assemblages of all possible parasite taxa. There was also significant nestedness of parasites infecting the within-host habitats of gut and blood. These results were used to make predictions about order of infection, tested using an independent, long-term, longitudinal dataset of wood mice sampled every two weeks during 2012. Multi-state Markov models showed that the order of infection of the three most common parasites was similar but not identical to the nestedness predictions. Parasite-specific traits, such as transmission mode, life history, and infection site may contribute to these deviations. Due to the parasites used in the analysis infecting either the blood or the gut, interactions may depend on infection location and be direct (i.e. competition for space) or indirect through resource competition or mediated by the host immune response. Our findings illustrate how parasite community patterns at a population level can be driven by individual exposure to parasites and that within-host interactions may be important for among within-host habitat co-infection dynamics.