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Gibbons Lab Overview


“We are moving islands, inoculated at birth with a unique set of microbes that are integral to the functioning of our bodies. When the ecology of these microbial communities breaks down, so does our health.”

–Sean Gibbons, PhD, Washington Research Foundation Distinguished Investigator & Assistant Professor
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Research Overview

The Gibbons Lab employs empirical and computational approaches to study how and why complex adaptive systems reorder themselves in response to environmental change. In particular, the mammalian gut microbiome is a superb system for exploring how rapid eco-evolutionary dynamics can reshape ecosystem function (i.e. human health). We tackle basic science questions at the boundary between ecology and evolution and leverage insights gained from this research to develop ecologically aware therapeutics to treat complex diseases.

Research Focus

Predicting how microbial communities respond to disturbance: We are part of a working group that is assembling a large body of published perturbation studies across many different microbial ecosystems (e.g. soil, marine, freshwater, mammalian gut, etc.) to conduct a meta-analysis of how stressors affect microbial systems. We will tackle statistical and bioinformatic challenges inherent to microboime meta-analyses: e.g. working with non-euclidean data and dealing with batch effects across studies. We aim to identify the ecological determinants of community resistance and resilience to environmental disturbance. Our meta-analysis will be a hypothesis-generating platform. These hypotheses will be fed into an engineered microbial bioreactor system for further testing and theory development. We hope to answer basic and applied questions, like “is there a tradeoff between efficiency and robustness in microbial communities?” and “can we engineer microbial systems with enhanced resilience to environmental fluctuations?”

Personalized eco-evolutionary dynamics in the human gut microbiome: Recent work has shown rapid adaptation of a commensal gut bacterium to individual hosts, which suggests that we each harbor a customized microbial community that is adapted to our unique genotype/development/behavior. This adaptation may explain why our microbiomes are often so stable over time (i.e. resistant to invasion by non-indigenous taxa). We aim to track the eco-evolutionary development of these personalized microbiomes over the entire lifespan of a host organism. In particular, we have established a collaboration with the Yerkes National Primate Research Center at Emory University (Dr. Adam Ericsen), which will allow us to longitudinally sample a large cohort of rhesus macaques from birth into adulthood. In addition to sampling in a non-human primate model, we will work with the Providence network of hospitals in Seattle to recruit a large cohort of newborn humans to follow over time, tracking how individual bacterial strains colonize and evolve to their human host.

The gut microbiome and personalized medicine: The one-pathogen-one-disease paradigm – the focus of infectious disease research for more than a century – has been complicated by the discovery of the human microbiome. The gut microbiome is intimately tied to the development of our immune system, our physiology, and even our psychology. A breakdown in the ecological structure of our gut has been associated with inflammatory disorders, metabolic syndromes, and cancer. Ecological restoration of the gut through fecal microbiota transplantation from a healthy donor (FMT) has proven to be an effective treatment for Clostridium difficile infections – responsible for about 30,000 deaths in the U.S. each year. FMTs are the first major example of an effective application of community ecology to treat a common disease. While the promise of ecological therapeutics is great for a range of conditions, we are far from being able to rationally engineer the ecology of the gut. We will work with Arivale to leverage their large 100K Wellness Project dataset, which includes longitudinal microbiome data and clinical data from thousands of patients, to better understand the connections between the microbiome and health. By observing how thousands of microbial communities respond to varying dietary and behavioral patterns, we will begin to build up a repertoire of interventions for predictably altering gut communities to improve human health. In addition, we will use machine learning tools to identify predictive biomarkers for a range of diseases that may arise in our patient cohort. The microbiome will play a crucial role in the development of a personalized approach to medicine.