# Advanced sequencing as a novel diagnostic tool to discover strain-level variation and function of mucosal-adherent bacteria contributing to IBD > **NIH NIH K01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 · $150,591 ## Abstract Metagenomic analysis of the gut microbiome continues to provide critical insights into the function of microbiota in inflammatory bowel diseases (IBD). In contrast to luminal and fecal samples, the mucosa-associated microbiome is thought to be more directly relevant to host immune response and disease state. However, 16S profiling does not permit low-level taxonomic inference or characterization of functional potential and mucosa-associated microbiota are not amenable to traditional whole- metagenome sequencing due to prohibitively high host DNA. There is a critical need to develop novel sequencing and analysis methods that enable unbiased metagenomic sequencing of tissue-associated microbiota in complex host-microbiome systems. I will use a novel host-depleted metagenome sequencing approach to define the compositional and functional differences between mucosal, luminal, and fecal microbiota, and between healthy and disease states in unprecedented detail. My long-term goal is to establish an independent research program in computational genomics for human disease and personalized medicine focused on the gut microbiome and IBD. The central hypothesis of this proposal is that metagenomic sequencing of mucosa-associated microbiota will identify location-specific, species- and strain-level composition and functional variation associated with intestinal inflammation and human disease pathogenesis. I recently developed a novel sequencing and informatics protocol that interfaces with existing nanopore sequencing technology to enable dynamic selection and identification of species or genes from a metagenomic sample. This approach can be used to dynamically filter out DNA sequences belonging to previously observed microbial species or contaminating host genome. I will apply this method to perform the first effective high-depth shotgun sequencing of mucosa-associated microbiota in the ileum and colon of Il10-/- and wild-type mice. Using these data, I will compare host-depleted deep sequencing to traditional short-read shotgun sequencing and 16S rRNA sequencing for assaying composition and function of adherent communities. I will identify relative differences in taxonomic and genic abundances associated with colitis in a mouse model, including species- and strain-level variants that are not captured by existing approaches. I will also use this approach to determine whether adherent-invasive Escherichia coli (AIEC) selectively colonize the mucosal surface relative to the lumen in germ-free Il10-/- mice, supporting their role as causal pro-inflammatory agent in a mouse model of colitis. Lastly, I will assess variation in the mucosa-associated microbiome in colon biopsy samples from IBD and non-IBD patients to characterize disease behavioral phenotypes, potentially leading to novel diagnostic and therapeutic tools. ## Key facts - **NIH application ID:** 10240527 - **Project number:** 5K01DK119582-03 - **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL - **Principal Investigator:** Jeremy R Wang - **Activity code:** K01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $150,591 - **Award type:** 5 - **Project period:** 2019-09-01 → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10240527 ## Citation > US National Institutes of Health, RePORTER application 10240527, Advanced sequencing as a novel diagnostic tool to discover strain-level variation and function of mucosal-adherent bacteria contributing to IBD (5K01DK119582-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10240527. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*