One Health which recognizes the fundamental dependence of human health on the health of agricultural, industrial, and natural ecosystems. Microbes form hidden linkages that connect these ecosystems and shape their health and disease. Predictive models for the movement of genes, genomes, and microbes among these interconnected microbial ecosystems are desperately needed to develop strategies to address urgent and critical threats to human health including
- Antimicrobial Resistance
- Emergence of Infectious Disease
- Transmission Dynamics in a Changing World
- Maintenance of healthy microbial communities
Our aim is to develop a broad and predictive framework for infection biology that will directly address these challenges.
The study of healthy and diseased microbial ecosystems has been traditionally siloed by methodologies, funding resources, and culture. We aim to connect academic, agricultural, and industrial spheres with coordinated application of novel methods and integration of the resulting big data in a single predictive systems-framework based on ecological and evolutionary principles. Toward this end, the Infection Genomics for One Health (IGOH) theme supports cross-disciplinary collaborations among researchers in ecology, evolution, microbiology, virology, biomedical sciences, agricultural and food sciences, entomology, engineering, and anthropology. They also lead the Labor, Health, Equity, Action Project (LHEAP).
Together we will harness high-throughput, genome-based methods to quantify the spatial and temporal dynamics of both free-living and host-associated microbes important to One Health. We extend principles of ecology and evolution across a series of nested hierarchies, analyzing the dynamics and interactions at the gene, genome, organismal, population, community, and landscape levels through network and community models. At each level, we consider both within- and between-host microbial dynamics.
Our primary objectives are to:
- Identify reservoirs, transmission routes, demographics, and dynamics of genes, genomes, and microbial organisms in changing natural, human, and agricultural ecosystems.
- Determine how social-behavioral networks of host organisms influence microbial transmission and microbiome resistance to invasion by pathogens.
- Identify the adaptive significance of microbial associations in a changing landscape and forecast microbial responses to global change that modulate symbiotic interactions.
IGOH is home to GEMS (Genomics and Eco-evolution of Multi-Scale Symbioses), an NSF Biology Integration Institute that focuses on the classical species interaction between clover and honey bee pollinators as a model to understand the impact and dynamics of the myriad of microbes nested within them. The project takes an integrative approach to understand how molecular interactions impact the ecosystem. Researchers in GEMS are collaborative, diverse, interactive scientists and educators who take an inter-disciplinary approach to answer critical questions about how nested genomes interact and affect the world.
GEMS uses a shared leadership model with co-mentorship between trainer and trainee and multisite educational activities, integrating training programs to prepare the next generation of scientists to solve complex problems of both scientific and societal concern. Undergraduate, graduate, and post-doctoral trainees work in diverse interdisciplinary teams, doing authentic work with outreach professionals and the public and representing under-represented groups in laboratory and field science.