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.

Public Health Relevance

Accurate and thorough compositional and functional characterization of the microbiome contributing to colitis is limited by the use of 16S rRNA sequencing or using fecal samples as a proxy for mucosa-associated populations in modern microbiome studies. ?Selective? long-read metagenome sequencing will enable detailed taxonomic and functional classification of mucosally-associated microbiota by depleting host DNA, including sub-species level characterization of adherent-invasive bacteria and function of mucosa-associated microbiota. I will apply this approach to characterize differences between luminal and mucosal samples from the distal ileum and cecum of conventionalized WT and Il10-/- mice, germ-free Il10-/- mice co-colonized with specific strains of adherent-invasive and non-adherent-invasive E. coli, and colon biopsies from IBD and non-IBD patients.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Scientist Development Award - Research & Training (K01)
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Kidney, Urologic and Hematologic Diseases D Subcommittee (DDK)
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Saslowsky, David E
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University of North Carolina Chapel Hill
Schools of Medicine
Chapel Hill
United States
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