# Multi-modal Omics in Resolving Gut Microbiota and Host Interactions for Diet Induced Obesity

> **NIH NIH P20** · UNIVERSITY OF NEBRASKA LINCOLN · 2021 · $143,388

## Abstract

Obesity affects a significant adult population worldwide and is associated with many human diseases such as 
autoimmune diseases, cardiovascular disorders, type 2 diabetes, respiratory diseases, and cancers. However, obesity 
is less studied than other human diseases like cancer or blood disorder. The global prevalence and fast-growing pace 
of obesity reflects critical and complex causal factors in modern society. Some epidemiological studies have shown 
that dietary intake such as fat and sugar is highly associated with obesity. Thus, understanding the mechanisms of 
diet-induced obesity will provide fundamental knowledge to prevent or treat obesity clinically or in daily life. 
Interestingly, the human microbiome contributes vital functions to human health or disease traits. Emerging evidence 
shows that the gut microbiome is intrinsically associated with obesity risk. Microbes can also be used as a 
revolutionary medical treatment, i.e. through fecal microbiota transplantation. Understanding the metabolic role of gut 
microbes in diet-induced obesity may provide alternative strategies to prevent or treat obesity. Previous studies have 
revealed a common core of bacteria comprised of phyla Firmicutes, Bacteroidetes and Actinobacteria, while the rest 
of the population can be diverse. The insights of this complex and unculturable microbe community and the critical 
functionalities are still very preliminary, as is understanding of host-microbe interaction in the gut. Despite a collection 
of culturable microbes identified in the human gut, a systematic and cost-effective way to co-culture the arbitrary 
microbe community with host cells or tissues is lacking. Thus, the solution relies heavily on the computation algorithm 
to fill the gap between host and microbes in understanding diet-induced obesity. In this project, three specific aims are 
proposed to apply scalable computation methods to understand the role of gut microbe community, host intestine 
cells, and host-microbe interactions that contribute to diet-induced obesity. These aims are to: (1) identify a broader 
range of gut microbiota (culturable and unculturable) associated with obesity; (2) characterize heterogeneous host cell 
functions by single-cell transcriptomics; and (3) resolve host-microbe interactions by metabolomic modeling and 
genetic marks. The datasets - including multi-modal meta-omics gut microbial data and intestinal single-cell 
transcriptomics - will be generated in-house on mouse models with high-fat, medium-fat, and control diet plans. 
Successful completion of this project will provide deeper biological insights of the metabolic roles of gut microbes, host 
cells and host-microbe interactions associated with diet induced obesity, and also a powerful set of large-scale 
computational tools and techniques to conduct the host-microbe research in obesity or other related phenotypes.

## Key facts

- **NIH application ID:** 10246880
- **Project number:** 5P20GM104320-08
- **Recipient organization:** UNIVERSITY OF NEBRASKA LINCOLN
- **Principal Investigator:** Qiuming Yao
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $143,388
- **Award type:** 5
- **Project period:** 2014-08-05 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10246880

## Citation

> US National Institutes of Health, RePORTER application 10246880, Multi-modal Omics in Resolving Gut Microbiota and Host Interactions for Diet Induced Obesity (5P20GM104320-08). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10246880. Licensed CC0.

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