Performing Department
(N/A)
Non Technical Summary
Movement of pathogens between ecosystems is a major driver of pathogen emergence in humans, animals, agricultural crops, and natural ecosystems. Invasive plants span natural, disturbed, and agricultural systems, provide a novel, abundant hostfor novel groups of microbes, and can have an outsized role in pathogen transmission because invasive plants occur in high density and create conducive environments for disease. This research will examine the role of invasive plants in the eco-evolutionary dynamics of transmission across ecosystems boundaries and crop disease emergence, and capture initial epidemic dynamics of an emerging pathogen on a novel host in real time. The sharp contrasts between agricultural and wild hosts in spatial and community structure, phenology, individual heterogeneity, and microbiomes provide an ideal model system for empirical and theoretical investigation of the interplay of these factors on ecological and evolutionary dynamics of infectious diseases at and across ecosystem boundaries. Our results will advance understanding of ecological and evolutionary drivers of pathogen spillover and adaptation to a novel host, inform more general theory in infectious disease ecology, and ultimately improve prediction and management of emerging diseases.
Animal Health Component
0%
Research Effort Categories
Basic
90%
Applied
10%
Developmental
0%
Goals / Objectives
The overarching goal of this project is to elucidate the process of disease emergence via spillover between plant species and ecosystems. We will investigate the unique role of invasive plants, with their large populations at ecosystem boundaries, as a conduit for spillover of microbes between hosts in natural areas and agroecosystems. Specifically, we will examine the rapid emergence of Bipolaris gigantea, a fungal pathogen of grasses, on industrial hemp (Cannabis sativa containing less than 0.3% THC) that we hypothesize was transmitted from leaf spot epidemics on the invasive grass Microstegium vimineum in natural ecosystems in the same region. Our objectives are to: (1) Quantify ecological drivers of pathogen transmission between species and ecosystems; (2) Determine role of pathogen evolution in disease emergence on a novel host; and (3) Develop eco-evolutionary infectious disease models for coupled natural-agricultural systems. We will address these objectives with field surveys, field and greenhouse experiments, pathogen population genomics, reciprocal host infection and co-infection experiments, and mathematical and computational modeling informed by results of the empirical work.
Project Methods
The proposed research will measure real time pathogen transmission and evolution in coupled natural and agroecosystems and develop novel models of disease dynamics.Objective 1. Quantify ecological drivers of pathogen transmission between ecosystems.To assess the role of invasive plants, and their litter, in pathogen transmission from natural areas to agricultural crops, we will use field surveys and field and greenhouse experiments. We will examine major factors likely to mediate disease on hemp, including distance from diseased invasive plants and their litter, hemp genotype and microbiome, nutrient availability, and abiotic conditions. Specifically, we will carry out extensive field surveys (Year 1), then introduce experimental hemp plants (Years 2, 3) to sites identified during the pathogen survey, manipulate invader litter, nutrients, microbiomes, and hemp genetics, and conduct greenhouse experiments on abiotic factors hypothesized to regulate disease.Objective 2. Determine role of pathogen evolution in disease emergence on a novel host.Hemp has been a host of B. gigantea populations for only a few years, providing a unique opportunity to study the evolution of a fungal pathogen on a novel host. Natural selection and/or reduced gene flow between hosts or ecosystems may result in host or ecosystem-specialized populations. We will examine the role of pathogen evolution on disease emergence, and the roles that movement between hosts and mixed reproduction may play in pathogen evolution. We will test the hypothesis that the pathogen is undergoing evolution in adaptation to hemp. To test this hypothesis, we will sample B. gigantea from hemp and grasses in adjacent ecosystems, estimate gene flow between hosts and ecosystems and the frequency of sexual reproduction, and measure components of pathogen fitness among hosts in growth chamber experiments.Objective 3. Develop eco-evolutionary infectious disease models for coupled natural-agricultural systems.Infectious disease dynamics reflect the interplay of pathogen dynamics within individual hosts, growing-season transmission of infectious propagules among hosts, demographic impacts upon hosts, and pathogen persistence among years in dormant stages or reservoir hosts. It also reflects pathogen adaptation to different hosts and local environmental conditions, spatial (e.g., patchiness) and temporal (e.g., phenology) heterogeneities within and among host populations, and interactions with the microbiome. We will develop mathematical and computational models to explore how these processes influence cross-system spillover, and the potential for emergence of pathogen strains specialized to the novel hemp host (or generalized to both). Our multi-level framework will be used to addressthesekey theoretical questionsin infectious disease, transcendingdetails of our empirical system, and allow interrogation of the key processes that affect pathogen spillover events.We will develop models tailored to the specific empirical system (using data from Obj. 1 and 2), and also general theoretical models to illuminate emergence in multi-host systems more broadly. We will then use these ecological models as a springboard to examine evolutionary dynamics of fungal strains adapting to hemp.We will embed pathogen dynamics into a flexible model of individual plant growth, that accommodates multiple levels of investigation, thereby elucidating mechanisms of plant-pathogen transmission between ecosystems.