Sean Kearney (Alm Lab)

Targeted Perturbations Expand Ecosystem Function in the Mammalian Gut Microbiota

Animal guts harbor the densest microbial ecosystems on the planet, and these ecosystems orchestrate the health of their host. Disruptions of this ecosystem following pathogen infection lead to remodeling of this community. The only microbial therapy in such cases, fecal microbiota transplant, remains ill-defined and difficult to regulate. Here, I demonstrate a targeted approach to remodeling ecosystems in healthy individuals. This work offers a route for development of defined microbial therapeutics in a range of clinical indications.

Kevin Shi (Tidor Lab)

Analysis of a Selenium Chemoprevention Clinical Trial using a Multi-level Modeling Approach

Randomized controlled clinical trials are the gold standard for determining the effectiveness of medical and nutritional interventions. Prior information from metabolic, epidemiologic, and clinical studies inform clinical judgment as to the timeliness and design of clinical trials. Combining these distinct levels of information is an uncertain process and the uncertainty in the information available affects clinical trial outcomes probabilities. Large clinical trials sometimes produce undesirable and unanticipated results. We demonstrate a multi-level modeling framework that applies information theory to propagate uncertainty at the molecular metabolic level to assess its impacts on clinical trial outcomes and thereby identify critical information needs and clinical trial design options that may mitigate critical uncertainties. The metabolic entity addressed is selenium as a prostate cancer preventive agent.