Network modeling of dietary effect on host and microbial metabolism

The National Institute of Diabetes and Digestive and Kidney Diseases awarded $100,228 to The Regents of The University of Colorado, doing business as University of Colorado-Denver, on December 21, 2026, under the Diabetes, Digestive, and Kidney Diseases Extramural Research program (CFDA 93.847) to develop a network-based computational framework analyzing diet-microbe-host metabolic interactions.

The funded work develops a systems-level model integrating genomic, microbiome, metabolomic, and dietary data to link dietary compounds with microbial and host enzymatic functions. The framework leverages existing databases including the Kyoto Encyclopedia of Genes and Genomes (KEGG) and FooDB to identify co-metabolic pathways at the compound-enzyme level. Research uses experimental datasets from individuals with diverse dietary patterns and disease states, including a cohort of people living with HIV in Zimbabwe and a large inflammatory bowel disease dataset. Deliverables include a scalable, queryable framework applicable to related biological experiments, designed to enhance detection of diet-microbe-host interactions across diverse health contexts.

Performance occurs in Colorado, with a period of performance from December 21, 2026, through May 20, 2028. University of Colorado-Denver is a public research institution headquartered in Aurora, Colorado, functioning primarily as a federal research grant recipient under NIH and NSF.

Abstract

The human GUT microbiome plays a critical role in host health, influencing complex diseases such as obesity, type 2 diabetes, alzheimer's, and parkinson's disease. A key mediator of this relationship is microbial metabolism of compounds present in the diet. Understanding the interplay among diet, microbes, and the host is crucial to advancing knowledge of human health and disease. Dietary compounds can be metabolized by GUT microbes and the host, producing metabolites that impact health outcomes. For example, microbial-host CO- metabolism of choline from red meat into trimethylamine-n-oxide (tmao) increases heart disease risk, while other microbe-host CO-metabolic pathways, such as those involving polyphenols or essential amino acids, have protective effects. Despite this, current computational tools lack a unified approach to directly link dietary compounds, microbial enzymatic functions, and host metabolism. This proposal seeks to address this GAP by developing a networks-based framework (nodes and edges) to integrate genomic, microbiome, metabolomic, and dietary data. Using experimental datasets from individuals with diverse dietary patterns and disease states, including a cohort of people living with HIV (plwh) in zimbabwe and a large inflammatory bowel disease (IBD) dataset, this work will systematically connect diet-originating compounds with microbial and host enzymes. This approach will enhance the ability to detect diet-microbe-host interactions, facilitating the exploration of CO- metabolism in diverse health contexts. Leveraging databases such as the kyoto encyclopedia of genes and genomes (kegg) and foodb, the overarching objective of this study is to develop a computational framework to analyze diet-microbe-host interactions at the compound-enzyme level. The findings will provide a scalable, queryable framework applicable to any related biological experiment, offering new tools for studying the impacts of diet on health through GUT microbiome activity. Ultimately, this work will advance understanding of diet- microbe-host interactions and their contributions to disease mechanisms, guiding future research and therapeutic development.