Peter J. Hudson - US grants

Understanding the role that infectious diseases play in natural communities is a key question in community ecology. Host-pathogen interactions, perhaps more so than other types of interactions (e.g. predator-prey & competition), are largely determined by the physiological condition of the host. To gain a predictive understanding of the impact that infection may have on host population dynamics requires a detailed understanding of host physiology and immunology. Freshwater wetlands are primary habitat for snails serving as intermediate hosts for a variety of helminthic parasites including digenetic trematodes. Trematodes are responsible for hundreds of thousands of cases of human disease each year (e.g., schistosomiasis) and have been linked with developmental abnormalities in amphibians. Amphibian deformities, in particular those related to limb development, have now been reported throughout North America. The widespread nature and apparent increase in the prevalence of deformities has lead to substantial interest from scientists and the general public. While preliminary laboratory experiments suggest that infection by trematodes can cause some deformities, researchers have pointed out that there is a need for more fieldwork to evaluate the association in nature. In addition, some research has suggested that land use changes in wetlands, such as increased eutrophication and altered hydrology, may precipitate outbreaks of deformities by increasing abundance of intermediate hosts (snails). We propose to examine the role of the host's hormonal response to land use changes (environmental stress) in terms of how it can regulate disease susceptibility. The proposed project will complement an ongoing study examining how land use changes affect snail (intermediate host) abundance and therefore influence amphibian infection rates. This proposal will add significantly to our knowledge of how free-living animals respond physiologically to anthropogenic land use changes, and the data generated on host susceptibility will add significantly to the development of a predictive model for disease outbreak in this host/parasite system.

Despite parasites being found in nearly every community, the relationship between community and disease ecology remains poorly understood. Our goal is to determine the mechanisms by which species interactions and common environmental stressors influence disease properties and community dynamics. Our focal hosts are amphibians, a group of global conservation concern that has been impacted by the recent emergence of infectious diseases. The focal parasites are the trematodes (flatworms) Ribeiroia ondatrae and Echinostoma trivolvis. They are transmitted from snails to amphibians and induce mortality associated with limb deformities and kidney damage, respectively. Our hypothesis is that trematode transmission, associated mortality, and amphibian fitness will depend upon community composition and abiotic stressors. We will conduct surveys to identify relationships among amphibian trematode infections and biotic and abiotic characteristics of wetlands and their surrounding landscape. We will use mesocosm communities to examine how the independent and combined effects of competition and predation (biotic stressors) and pesticides and conditions associated with climate change (abiotic stressors) influence amphibian fitness and disease properties. Additionally, we will elucidate the relationships among amphibian immune responses and biotic and abiotic stressors and infection risk by conducting immunological assays on amphibians from each of our experiments. Finally, we will formulate predictive mathematical models for the spread of trematodes in human-altered environments. This project represents a pioneering effort in the integration of community ecology, immunology, and epidemiology that will improve our ability to forecast future vector-borne disease outbreaks by shedding light on general principles governing host-parasite interactions.

Frog and salamander species are declining worldwide, some apparently due to the emergence of new or more severe diseases. While the precise causes of these epidemics are unclear, they are likely to be influenced by human-induced environmental changes affecting both exposure and susceptibility of amphibians to pathogens. Temperature-dependent immunity may be particularly important to disease dynamics in amphibians, leading to increased susceptibility to infection in springtime or under changing climatic conditions. This project uses the Red-spotted newt, a common temperate salamander, as a model species for studying: (1) seasonality in infection and immunity in amphibians, (2) factors leading to outbreaks of an Ichthyophonus-like fungus implicated in recent amphibian die-offs, and (3) ecological processes structuring the newt parasite community. Capture-mark-recapture methods coupled with lab and field experiments will be used to test hypotheses which explain patterns observed in spatial and seasonal surveys of newt populations and their parasites. This research will provide insights into the effects of seasonal temperature fluctuations on amphibian immune defenses, the transmission dynamics of an important fungal pathogen, and the community ecology of amphibian parasites. Studying multiple immune parameters and parasite species in newts will lead to a broader impact on our understanding of how human-induced environmental changes affect disease dynamics in amphibian populations, by providing insight into general principles of amphibian disease ecology. This project will support the dissertation research of a doctoral candidate.

Proposal Number: DEB-0520468
Proposal Title: Parasite Induced Susceptibility and Transmission in a
Seasonal Environment: Micro and Macro Interactions and the Dynamics of the Parasite Community of Mice


Parasites, by definition, cause their host harm and so the community of parasites within an individual host can be expected to interact with one another indirectly through the host's immune system. Whether presence of one parasite is beneficial or detrimental to another is a crucial, but as yet overlooked, factor in disease control and dynamics. This project will investigate how a community of parasites is shaped at the individual level and the consequences this has for disease dynamics at the population level using a mixture of experiments and mathematical modeling.

Not all individuals are equal; they differ in their ability to fight and spread infections. Importantly this can give rise to certain individuals being accountable for the majority of disease transmission; super-spreaders. These super-spreaders may have predictable characteristics that allow for thier identification and so target disease control most effectively. However, the mechanisms that create super-spreaders thus far have been elusive.

We explore the idea that a super-spreader may be a function of the parasites it harbors and the interactions that occur between them. As such we will tease apart the inherent differences between individuals that lead to changes in susceptibility and exposure to parasites whilst also determining how infection mediated through an individual's immune system will shape the parasite community. These interactions will be investigated in a seasonal environment since the availability of parasitic infective stages and therefore the community structure may be a function of the highly variable development and survival rates of different parasites at different temperatures.

Insights gained from this project on the mechanisms that determine parasite community dynamics should help researchers indentify important factors in disease emergence, determine why some parasites may be more prevalent than others, and identify the characteristics that create super-spreaders. The project will use a mouse-human pathogen system to infer disease dynamics at the human-pathogen level. The program will support training of post-doc, graduate and undergraduate students.

This project will provide travel funds for graduate students and post-doctoral scholars to attend the Fourth Annual Conference on the Ecology and Evolution of Infectious Diseases to be held at Penn State University on 18-20 May, and to attend a workshop preceeding the conference. The purpose of the workshop is to provide hands-on training in modeling disease systems, especially as they pertain to Pathogen genetic variation is modulated by host immunity, transmission bottlenecks and epidemic dynamics: these processes interact to shape the range of pathogen phylogenies observed at scales from within-host to population.The field of ecology and evolution of infectious disease is rapidly expanding. However, there is an acute shortage of people trained in disease modeling or biologists who are sufficiently quantitative to work with mathematicians. The workshop will address this shortage. The training of graduate students and post-docs is especially important as they represent the new wave of researchers in this area. The conference is the third focusing on these topics and is becoming the primary annual meeting for this topic. The understanding of the ecology of infectious disease has important implications for human health and the economics of agriculture.

Levels of parasite infection are influenced by variations in host susceptibility and exposure which in turn are determined by environmental conditions. A major challenge for disease workers is to predict how climate change will influence infection risk. This proposal aims to identify both the role of long-term climate change and seasonal variation in relation to changes in the abundance of parasite species in a community of parasites that inhabit a free living host population. The study is based on a unique long term dataset where rabbits have been sampled every month for 29 years. Details are collected on rabbits demography, parasite community structure and environmental data to test the hypothesis that climate warming has increased level of parasitism in species not regulated by immunity but not in species regulated by immunity. Insights will be integrated into seasonal models of increased complexity to provide a working explanation of how climate affects parasite and host ecology, predict future changes and identify means of making control effective.

This detailed interdisciplinary scientific program has some very important broader impacts for our understanding of disease emergence and persistence. Not only will it provide one of the most comprehensive and insightful descriptions of how climate change can affect parasite community in different ways but will represent an ideal condition for training students in a broad range of lab/field techniques and data analyses and teach them how to operate within a dynamic and productive research team and have an international working experience.

Emerging infectious diseases present a broad challenge to humans, other animals and plants, in both human-dominated and natural communities. Anticipating effects of emerging diseases will require synthesis of ecological, epidemiological, genetic, and evolutionary data, and solutions must address issues such as pandemics, species jumps, drug resistance, and roles of immunity and vaccination. The leading edge of infectious disease research will move with development of mathematical models and the enormous capacity of genome projects to gather data. This demands a step change in training the next generation of scientists, by integrating quantitative analysis from ecology and evolution with more traditional analyses in epidemiology and biomedicine. This project will fund workshops to train the next generation of infectious disease researchers in quantitative analyses, to form interdisciplinary teams to synthesize the growing mountain of data, and to link research in ecology, evolution, genomics, epidemiology, microbiology/parasitology, and immunology. The project will use a flexible curriculum integrating state-of-the-art modeling approaches with analysis of data sets provided by workshop participants.

Broader impacts include bringing together students and instructors with diverse backgrounds, and training students from underrepresented groups by targeted recruiting. Collaborative projects arising from the training will lead to advances in public health and epidemiology, including understanding of pathogen emergence in the face of changing human populations, drug therapies, vaccination strategies, and global change.

Proposal #: CNS 08-21527
PI(s): Raghavan, Padma
Chen, Long-Quing; Hudson, Peter J.; Kandemir, Mahmut T.; Smith, Brian K.
Institution: Pennsylvania State University
University Park, PA 16802-700
Title: MRI/Acq.: Acq.of A Scalable Instrument for Discovery through Computing
MRI Acquisition of a Scalable Instrument for Discovery through Computing

This award from the Major Research Instrumentation Program (MRI)
provides funds for the acquisition of a terascale advanced computing
instrument at the Pennsylvania State University. The instrument
will enable researchers from seven disciplines (biological, materials
and social sciences, computer and information science, engineering,
education, and geosciences), to perform virtual experiments toward
discovery and design through computing. Research projects concern:
predictive network modeling of infectious disease dynamics, designing
new piezoelectric materials, designing next-generation chip
multiprocessors, modeling human interactions to promote learning
in virtual communities, and the development of a critical zone
environmental observatory. Despite their diversity, these projects
share computational scalability challenges to be addressed for
enabling scientific advances that often depend on solving large
problems representing a sufficient level of detail and complexity.
The instrument will form the core of a multidisciplinary collaborative
environment to enable transformative approaches to address the
challenges of scaling at multiple levels. It will support a set of
integrated research, education, training, and outreach activities
to: (i) enable collaborative scaling across projects through the
transfer of scaling approaches from one domain into another, while
addressing algorithmic, system, or instrument scaling challenges
within individual projects, (ii) promote technology-transfer through
industrial partnerships, and (iii) grow and enhance the diversity
of the limited computational science talent pool.

This grant will support a three-day workshop to take a broad overview of the field of infectious disease ecology and assess where the field will be headed in the next 5 to 10 years. The field of infectious disease ecology is relatively young. Although there is identifiable research that extends back at least several decades, it is only in the past 10 to 15 years that there has been a surge in interest with new journals being established and a large increase in research. Now is an appropriate time for such an overview assessment. Issues to be explored include: methodological developments over the past 10 years, limitations in accomplishments over that time, what new tools and disciplines are needed, and how these might allow greater insights into disease dynamics and control in a changing world.

Improving our knowledge of infectious disease ecology has important implications for public health, agro-economics, and the management of wildlife and natural systems. The workshop will assess previous successes in these issues and identify novel approaches and interdisciplinary insights that could build on our understanding of disease dynamics and be improved means of predicting, preventing and intervening with disease outbreaks.

Solar panel development in the Western Mojave has resulted in a large number of threatened Desert Tortoises being moved from one location to another. Studies have shown that this species has become threatened through habitat loss and pneumonia infections and the translocation of tortoises will exacerbate disease risk. This project will examine the effects of social network structure on disease transmission dynamics using desert tortoises as a model system. The project will use a non-fatal mycoplasm infection and controlled introductions to follow disease spread in a system where the movements and interactions of all individuals can be tracked. The investigators will examine when translocation disrupts contact patterns and increases likelihood of an outbreak. Specifically they will undertake detailed experiments at both small and large scales and link these with probabilistic network models.

A fundamental part of this project is to identify a relationship between population structure, contact patterns and disease spread that can be used more generally to predict the likelihood of disease outbreaks. One outcome will be a management tool that can be used to assess risk of disease outbreaks in relation to tortoise translocation. More generally the researchers seek to examine the relationships between contact patterns and disease risk in other types of populations, including human and livestock. In this respect this study will be of great importance in understanding how emerging infections invade naïve populations.

The immune system plays a critical role in maintaining overall health and keeping parasites at bay. While investment in immune function may improve survival, it may also come at a cost to reproduction, either because of limited resources or an over-reactive immune system attacking the body. Here, the authors aim to explore the evidence for relationships between immune investment, disease severity, survival, and reproduction in a wild population of gray wolves. Gray wolves were reintroduced into Yellowstone National Park in 1995, and within this population, researchers have studied the natural process of parasite infections. This work has shown that individual wolves vary in their response to infection with canine distemper virus and sarcoptic mange, despite the high survival-costs associated with an inability to control infection. None of this variation is explained by host characteristics such as age, sex, and social status. This project will test the hypothesis that a tradeoff between immune function and reproduction explains the maintenance of immune variation among individuals. Several indices of immune investment (natural antibodies, specific antibodies, and total antibodies) will be measured as predictors of disease severity and survival through known disease outbreaks. This information will be matched to reproductive fitness in order to test whether increased immune responsiveness comes at a cost to reproduction. This work will further test the specific prediction that costs to reproduction occur in the form of decreased litter sizes, and that these costs may be offset during disease outbreaks in the form of increased litter survival.

Results from this research will improve our understanding of the mechanisms by which variation in immune function is maintained in wildlife populations, which has important applications in conservation biology and wildlife management. The project will build on a rich, long-term public dataset on a wild carnivore being reintroduced to national parks, and will further our understanding of the drivers of an iconic conservation species. Results from this study will be published on a citizen science website, and disseminated via public lectures through the National Park Service and to school groups. This study will also expand the research training and skill sets of a doctoral student.

Emerging infectious diseases (EIDs) threaten global health and security, but when and where they will occur remains unfortunately hard to predict. In part, this may be because pathogens are usually studied in isolation. An alternative approach is to consider emerging pathogens as members of an ecological community of interacting microbes. The community ecology of viruses co-occurring in hosts -- the virome -- has yet to be explored as an ecological community even though viruses are known to be important emerging disease agents. The research supported by this award will address this deficiency by focusing on the viromes living inside two widespread species that live in close association with humans: the white footed mouse (Peromyscus leucopus) and the blacklegged tick (Ixodes scapularis). Blacklegged ticks feed abundantly on white-footed mice, and the two species freely exchange microbes during the lengthy blood meals. By exploring how the viromes of these two species are assembled and how they interact and flow between mice and ticks, the proposed research will reveal how viromes shape transmission of existing and potential pathogens. The research will be carried out in the northeast corridor of the United States, an area known to be an excellent location for studying virus emergence and the role played by white-footed mice and blacklegged ticks in the transmission of zoonotic pathogens (those transmitted from vertebrate animals to humans). White-footed mice and blacklegged ticks serve as reservoir host and vector, respectively, of many emerging diseases of humans, including Lyme disease. Pilot studies have revealed that these same two species also harbor a community of previously undescribed viruses that may emerge as zoonotic diseases in the future.

The researchers take an explicitly ecological approach to understanding viromes of reservoir and vector hosts. The researchers will: (1) characterize the viromes of both mouse and tick; (2) determine patterns of virome assembly throughout the lifetimes of both mouse and tick; (3) determine how virus communities affect the transmission of several important vector borne zoonotic pathogens; (4) identify whether viromes affect differences between individual mice and ticks in their abilities to transmit known and new pathogens; and (5) determine whether viromes and transmission probabilities change along with changing abundance of mice and between suburban/urban and more rural habitats. Data generated by each of these specific aims will be modeled using statistical (machine learning) algorithms, which accommodate diverse data types and apply a model-free analytical approach. By using complex and high-dimensional empirical data describing hosts, vectors, viromes, and their shared natural environments, these algorithms can achieve superior pattern detection (such as virome composition) and improved ability to make useful predictions (such as what combinations of traits of vector viromes and mammal hosts best predict virus transmission).