Tools for Studying Metabolism in the Human Gastrointestinal Microbiome
Moutinho, Thomas, Biomedical Engineering - School of Engineering and Applied Science, University of Virginia
Papin, Jason, MD-BIOM Biomedical Eng, University of Virginia
The human gastrointestinal (GI) microbiome is a complex ecosystem consisting of trillions of microorganisms. The microbial life present in the gut contributes significantly to human physiological processes, health, and well-being. Conversely, disturbances in the GI microbiome have been correlated with a broad array of diseases, having a particularly strong connection to the brain, immune system, cardiovascular system, and GI tract. With a high exposure to external factors, the GI microbiome can be rapidly influenced by drugs, diet, and life-style. There is a need for an improved understanding of GI microbial communities for applications in medical diagnostics and treatments. In this dissertation I worked to advance three distinct tools for the study of GI microbiomes. In aim 1, I identify biomarkers for Parenteral Nutrition Associated Cholestasis in neonatal intensive care unit (NICU) infants using 16S sequencing data and fecal metabolomics. This aim is the first step in work to develop a point-of-care diagnostic tool to expand precision medicine in the NICU. Leveraging systems biology to understand clinical microbiome data and developing a mechanistic understanding of pathophysiology requires advanced research tools. In aim 2, I design and develop a computational tool to aid in the procedural generation of organism-specific metabolic network reconstructions that explicitly accounts for uncertainty in the datasets utilized for the building process. An essential aspect of this tool relies on an alteration to the structure of these models for enhanced representation of the biological evidence for the resulting network. In aim 3, I developed an in vitro culture device for the pairwise co-culture of microbes to study contact-independent microbial interactions. The co-culture plate allows bacterial growth curves to be generated for two microbial cultures that are physically separated by a semipermeable membrane while interacting via diffusion. Contact-independent interactions are important for understanding the mechanisms that influence how microorganisms interact in communities. This dissertation covers the design and development of three different tools for the study and leveraging of the human GI microbiome to improve the treatment of associated diseases.
PHD (Doctor of Philosophy)
Metabolism, Genome-scale metabolic network reconstructions, Parenteral nutrition associated cholestasis, Microbial interactions, Gastrointestinal microbiome
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