This project will improve the ability to predict how disease causing parasites affect their host (animal) populations and whether disease transmission is altered when different species of parasite occur within the same individual host, a process known as co-infection. Parasites, by definition, use energy from the hosts they infect in order to reproduce and spread to new hosts. While previous research has made great strides in understanding how traits of single parasite species affect disease transmission, predicting interactions among co-infecting parasites remains a research frontier. When two parasite species occupy the same host, the outcome of infection may not be the same as when each parasite occurs separately, due to interactions between the parasites. This project will evaluate the consequences of co-infection for host health, the spread of disease, and host population biology, using a model organism that impacts food safety in stored grains. Additionally, this project will provide scientific training and mentoring to high school, undergraduate, and graduate students; identify factors that affect the agricultural control of pests and pollinators; and implement an outreach project to recruit women from under-represented minorities to fields in STEM.
The researchers will use mathematical models and laboratory experiments to evaluate the effects of parasite co-infection on a flour beetle (Tribolium castaneum) model host system. The first objective is to determine the mechanisms through which co-infecting parasites interact in order to evaluate the impact of co-infection on parasite growth rates and host infection outcomes. The researchers will manipulate host nutrient acquisition, alter parasite infection routes, and quantify the impact of co-infection on host immune response using next-generation mRNA sequencing. This objective will elucidate the importance of top-down (immune-mediated) versus bottom-up (resource-mediated) ecological interactions for structuring parasite communities within the host. The second objective is to quantify the impact of infection order and the strength of within-host interactions on the transmission of each co-infecting parasite to new flour beetle hosts, connecting within-host to epidemiological processes. The final objective is to develop mathematical models of Tribolium population biology that predict how co-infecting parasites influence host population dynamics and parasite persistence, based on the experimental data. This project will provide novel and generalizable insight into the wider ecological context of co-infection and the impact of dynamical feedback across scales.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
