Leveraging Gut Microbiome-Derived Metabolites for Therapeutic Discovery in Ulcerative Colitis

Introduction: : Ulcerative Colitis (UC) is an inflammatory bowel disease that is characterized by chronic inflammation of the large intestine, causing ulcerations and debilitating symptoms. Studies have found that UC is characterized by dysregulated cellular and microbial communities. These mechanisms have been studied separately through single-cell RNA-sequencing (scRNAseq) and investigation of multi-omics in the gut. However, there has been limited exploration of how microbial and metabolic states directly relate to specific cell-type expression in UC. To close this gap, we developed a multi-omic approach, integrating scRNAseq and paired metabolomic and bulk human transcriptome data to score individual cells based on metabolite signatures from bulk data.

Materials and

Methods: : We accessed publicly available scRNAseq data through the Gene Expression Omnibus (GSE182270, GSE214695, GSE231993, GSE250487, GSE253719, GSE282122) to generate an atlas of UC and control (C) biologic-naive colonic single-cells. Samples from whole tissue were separated into epithelial, stromal, and immune populations and re-clustered for fine-grain annotation. Immune cells were further separated into T, myeloid, B, and plasma populations for further specified annotation. Multi-omics data was taken from the integrative human microbiome project. Bulk metabolite signatures were derived for UC and C populations by performing a Spearman correlation between paired tissue transcript and metabolomics data. From these signatures, C and UC cells were individually scored for each metabolite signature based on the average expression of the top 250 metabolite-associated genes as compared to a control gene set. Finally, a Mann-Whitney U test was run to determine metabolites/microbes that had higher metabolite enrichment scores between the two populations. For differential expression analysis between cell-types, we employed the MAST framework.

Results, Conclusions, and Discussions:: Our clustering revealed detailed populations of cells. From our metabolite enrichment analysis, we investigated enterocytes and goblet cells for dysregulated metabolite signatures due to their role in protecting the epithelium and regulating immune responses respectively. Several metabolite signatures were enriched in C samples relating to balanced membrane lipid profiles and primary bile acid activity. In UC, metabolite signatures relating to nucleotide turnover and fatty-acid substrates were enriched. The enrichment of primary bile acids taurochenodeoxycholate and glycocholate was particularly of interest, as literature has shown that the stool levels of PBAs are increased in UC. Exploring gene expression, we found several pro-inflammatory genes like CXCL8 (p.adj=4.0e-9) and IL1B (p.adj=5.5e-3) to be increased in UC enterocytes. We also found genes that support the mucus layer like MUC2 (p.adj=2.0e-17) and FCGBP (p.adj =5.7e-3) to be decreased in UC goblet cells.

We found that primary bile acid signatures were decreased in enrichment in UC cells when compared to control cells. Microbes in the colon are responsible for metabolizing conjugated primary bile acids (PBA) into secondary bile acids. Enterocytes and Goblet cells receive signals from conjugated PBA derivatives that repress inflammation and maintain epithelial integrity. For example, lithocholate and deoxycholate suppress inflammation in enterocytes. Also, chenodeoxycholic acid, a deconjugated primary bile acid, interacts with goblet cells to produce mucin and antimicrobial peptides. Our results indicate that there may be a decrease in primary bile acid metabolizing bacteria in the UC colon. Supplementing UC patients with high fecal bile acid content with PBA metabolizing bacteria may offer a low cost, novel therapeutic option.

The single-cell atlas we developed pooled information across studies into a single comprehensive resource for UC exploration. The workflow developed effectively integrates single-cell RNA-sequencing data with multi-omics data to derive metabolites associated with cellular signatures in Ulcerative Colitis. This characterizes the dysregulation of the gut-microbiome at a cellular level and opens the door for investigations into utilizing microbiota or metabolite-based therapies for treating Ulcerative Colitis. Further work is needed to determine microbe regulated gene expression signatures and their relationships with cells. Additionally, deriving signatures associated with biologic treatment could inform non-response mechanisms.

Acknowledgements and/or References (Optional)::