Understanding the Roles of Nutrient-Niche Dynamics In Clostridioides difficile Colonization in Human Microbiome Colonized Minibioreactors

Authors

Xiaoyun Huang, University of Nebraska - LincolnFollow

First Advisor

Jennifer Auchtung

Date of this Version

Summer 7-2021

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Food Science and Technology, Under the Supervision of Professor Jennifer Auchtung. Lincoln, Nebraska: July 2021

Copyright © 2021 Xiaoyun Huang

Abstract

Clostridioides difficile is a Gram-positive pathogen that is one of the most common causes of health care-associated infections in the U.S. Because of its importance to human health, researchers are trying to understand risk factors for infection and identify new therapies to treat disease. A “healthy” gut microbiome has the ability to protect the host against colonization of C. difficile or other pathogens by providing colonization resistance. One proposed mechanism for colonization resistance is through competition for nutrients with pathogens by the members of the healthy microbiome. We tested whether competition for nutrients was important for colonization resistance in human fecal minibioreactor arrays (MBRAs), an in vitro model of C. difficile colonization resistance that can be used to culture fecal communities from different healthy humans. We found that C. difficile growth was limited when amino acids were depleted and that ability to metabolize proline, an amino acid shown to be important in mouse models of infection, was required for C. difficile to colonize in some fecal communities but not others. As several previous studies point to proline as potentially important niche during human infections, these results provide further support for use of this model to understand factors important for C. difficile colonization that vary across fecal communities and can be used for further development of predictive models of important nutrient niches. Future studies that build upon this work could combine sequence data, metabolomics data, and compound and pathway enrichment analysis to begin developing models that predict important nutrient niches in specific fecal communities as a way to develop personalized clinical therapy.

Advisor: Jennifer Auchtung