All animals contain complex communities of bacteria and other microbes, known collectively as the microbiome. These microbes perform many important functions for their host, including defense against infection by parasites and pathogens. To accomplish these functions the microbes must interact closely with both host and parasite cells. Increasingly, scientific evidence suggests that these interactions occur through the production of chemical messengers that allow communication among the bacteria in the microbiome, the host and the parasite. This research project advances understanding of the microbiome by devising a model honey bee gut system. Such a system has significantly fewer bacterial taxa and performs the same functions as other gut microbiomes, including playing a role in host defense against parasites. In this honey bee system, both network models and experimental manipulations of the gut microbiome are used to further understanding of the microbiome and its role in host defense. The knowledge derived from the project would be important for manipulating the microbiome for host health, including, ultimately, that of humans. A computer science and biology-based outreach module for elementary school students is being developed. Students and teachers are guided through the building of Raspberry Pi clusters, which are then used for student-driven projects based on the research datasets.
Growing evidence points to the critical role that the microbiome plays in host health and defense against parasites via interspecies cellular signaling. This research uses a systems biology framework to advance understanding of interspecific cellular signaling in host-microbiome-parasite interactions. The model system is the honey bee gut microbiome which consists of less than ten bacterial taxa. Three objectives collectively address the role of the microbiome in host defense against parasites, assess functional redundancy in the microbiome in relation to parasite resistance, and experimentally test network predictions. Bees with a common gut parasite provide data to generate interaction networks for bees that are parasite-infected and for bees that are resistant to infection. Within these networks, specific gene modules and bacterial taxa, important for parasite resistance, are identified within the gut microbiome. In this way key interactions among the host, parasite and bacteria are elucidated. Next, an alternative, complimentary approach to building microbiome networks for this system is developed. For this approach whole genome sequences of dominant bee gut bacteria are collected from apiaries that vary in parasite infection prevalence. The importance of strain-level variation in these dominant bacterial taxa are explored in a large set of computationally-derived networks. Shifts in network topology, including changes in the empirically-derived resistance modules, are assessed. Finally, based on the empirical and computational networks, predictions are made about microbiome community structures that are most likely to result in parasite resistance. These predictions are tested by creating bees with synthetic gut microbiomes that are predicted to be parasite-resistant or susceptible. This project will significantly advance knowledge of the mechanisms by which the microbiome impacts host health.
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.
