Lisa K. Belden, Ph.D. - US grants

As the incidence of infectious diseases in both wildlife and human populations continues to rise, studies addressing the ecology of disease are becoming more important. Too often, though, our understanding of pathogens and parasites in natural systems develops from studies abstracted from the complex ecological communities in which disease dynamics actually play out. Recent evidence suggests that the presence/absence and relative abundance of different species in the biological community can substantially influence the outcome of host-parasite interactions. However, changing the composition of the community can result in either an increase or decrease in disease risk, and the mechanisms responsible for these outcomes have been experimentally investigated in very few systems. This research will experimentally investigate the role of community composition in modulating disease outcomes in a complex host-parasite system composed of snails, amphibians, and a trematode parasite. A series of experiments will address how infection of parasite hosts is influenced by changes in the composition and relative abundance of multiple hosts, multiple parasite infectious stages and non-host competitors.

This proposal will establish a collaborative research program between the laboratories of the PIs at Virginia Tech and Radford University (a predominately undergraduate institution 25 km from Virginia Tech) that will provide broader educational experiences for the students at both institutions. The partnership between Virginia Tech and Radford University includes collaborative research projects, joint laboratory meetings, and support of graduate students at Virginia Tech and undergraduate student research at both universities. In addition, a teaching module on host-parasite interactions based on the research results will be developed for Ecology and Parasitology courses at Radford University and will be disseminated to the broader teaching community.

In adult humans, symbiotic microbes outnumber human cells ten to one. The composition of these microbial communities can influence whether individuals are lean or obese and the likelihood that pathogens are able to successfully establish themselves in the body. Amphibians also possess a diverse symbiotic microbiota, and these bacterial symbionts may limit infection by pathogens, such as the fungus Batrachochytrium dendrobatidis (Bd) that has decimated many natural amphibian populations. This research will examine links between three critical diversity components of the symbiotic microbial communities that reside on amphibian skin: taxonomic diversity (number and relative abundance of species), genetic diversity (which genes are turned on), and functional diversity (disease resistance). Using focused field surveys and manipulative experiments, three objectives will be addressed: (1) establish the range of taxonomic, genetic, and functional diversity within the microbial community on five species of host amphibians in Panama, (2) examine how the presence of a pathogen (Bd) impacts diversity components, and (3) examine the relationship between microbial diversity and resistance to disease. As all animals host symbiotic microbes, these results will have broad applicability to other systems, including humans. In addition, new statistical methods for these complex datasets will be developed, which will rapidly expand the ability to integrate these diversity components in a wide array of systems.

Undergraduate students will be trained in research. In addition, in Panama, a partnership with the Panama Amphibian Rescue and Conservation Project (PARC) will be established. A PARC intern will be supported to work with school groups to stress the importance of conservation, beneficial microbes and biodiversity. The partnership with PARC will extend to working with them on novel probiotic solutions, based on antifungal skin bacteria, that will allow successful reintroductions of threatened frogs, thereby helping to restore biodiversity to the Neotropics.

Most new infectious diseases in humans are zoonotic, which means the pathogens that cause these diseases originate in wild and domestic animals and then spread to humans. Many pathogens that infect livestock and wildlife species are also found in other species. Mathematical models that describe pathogen transmission within single wildlife host species (e.g., rabies transmission within bat populations) and between different host species (e.g., rabies transmission between bats and skunks) are critical tools for understanding and predicting disease outbreaks in humans, livestock, and wildlife. In addition to being used to understand the spread of pathogens among hosts, these same models can be used to understand the spread of beneficial symbionts (small organisms such as bacteria that live in much larger hosts) that help rather than harm the host. However, the fundamental assumptions that underlie these mathematical models are rarely tested, because observing animal contact rates and spread of disease in nature is difficult. This research will use a system of hosts and their symbionts to test assumptions on which the existing models are built, and will quantify how well those models can predict disease transmission in wildlife populations. The results of this research will ultimately lead to mathematical models that are better at predicting symbiont transmission.

Wildlife population densities often vary across space and time. Classic epidemiological models use one of two mechanistic transmission functions to describe the relationship between host density and pathogen transmission rates. The first assumes that animal contact rates and thus transmission rates increase linearly with host density (density-dependent transmission), and the second assumes that animal contact rates and transmission rates are not affected by host density (frequency-dependent transmission). However, nonlinear relationships that fall somewhere between those extremes may be more appropriate in many host-symbiont systems. Using an experimentally tractable multi-host system - symbiotic annelid worms living on freshwater snails - this research will: (1) empirically quantify the relationship between host density and both intra- and inter-specific host contact rates, and (2) use the resulting model to make and test predictions regarding symbiont transmission dynamics in single and multi-host host communities at broad spatial and temporal scales in natural systems. Critical evaluation of fundamental model assumptions and the resulting model predictions will lead to better predictive models of symbiont transmission.

Ecological communities are composed of many interacting species and provide valuable ecosystem services ranging from clean water to pollination. To maintain these ecosystem services, it is important to understand the processes that determine where, when and which species occur together. Dispersal, or the movement of organisms across the landscape, is an important process in determining what species exist at a specific site; however, the importance of dispersal is likely to vary for different types of organisms and for different habitats. To date, most research examining the role of dispersal has focused on habitats with distinct boundaries, such as forest fragments or ponds. The primary goal of this research is to explore the role of dispersal in structuring communities of wildlife parasites live in streams. A second goal of the research is to develop methods to use new DNA sequencing technologies to quantify the abundance of parasites in water samples, making it possible to rapidly survey parasite communities and identify areas of high and low infection. Streams and rivers can be important channels for the movement of pathogens, and this research will increase our understanding of infectious disease dynamics in freshwater ecosystems while also contributing new methods for assessing the distribution and abundance of freshwater parasites.

Trematodes, also known as flukes or parasitic flatworms, are obligate endoparasites of mollusks and all classes of vertebrates. They have complex life cycles requiring multiple hosts, and because the hosts disperse at different spatial scales (e.g., fish vs. birds), they represent a valuable system for examining the role of dispersal in local community structure. This research will employ field surveys and molecular analyses to characterize trematode abundance and diversity within and across multiple stream networks in the southeastern U.S. Proceeding from mainstem to headwaters, investigators will quantify trematode infection in first-intermediate hosts (snails) from 15 sites within each stream network. As the obligate first-intermediate hosts of multiple trematode species, snails integrate information on the entire community of hosts involved in trematode life cycles. Investigators hypothesize that: i) there will be an increasing downstream gradient of overall trematode prevalence and diversity due to the continuous movement of free-living parasite stages and infected hosts downstream; and ii) that trematodes with mammalian or avian hosts will have a less pronounced downstream gradient of prevalence and diversity than those with fish hosts, due to greater host mobility across the landscape. By focusing on a diverse community of parasites that all use the same snail species as a first-intermediate host but that vary in vertebrate host use and thus dispersal potential, this research will provide new insights into the importance of dispersal in structuring local communities.

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.