Inside Intestinal Disease

Inflammatory bowel diseases (IBD) are relapsing and remitting chronic conditions of the gut that have a major impact on patients’ quality of life. Current therapeutic approaches aim to reduce symptoms – but their effectiveness varies, and patients may develop tolerances to the drugs. As such, it’s really important to have ways of assessing disease activity to better manage patients. Identifying microbial alterations associated with IBD could provide a diagnostic tool that enables us to spot disease earlier and minimize damage. It also contributes to better understanding of the underlying mechanisms associated with disease pathogenesis, allowing the design of improved therapeutic strategies.

The first line of defense against potential microbial invasion in the gut is a viscous layer of mucus that covers the intestinal epithelium. In our study (1), we excised the relevant mouse gut segment, opened it up longitudinally, and washed to remove residual luminal contents before scraping off the mucus for further testing. It’s a difficult procedure to translate into human studies because most patients undergo routines such as colonic lavage before they are biopsied, resulting in samples that may not fully replicate the in situ bacterial communities. However, an in situ method of mucus sampling without colonic lavage that can be performed in the clinic was recently developed (2), so in the future it should be easier to get patient mucus samples. Testing would involve either qPCR or a form of protein analysis, such as ELISA.

Given that differences in microbiota composition start in the mucus before the onset of inflammation, our findings provide a framework for identifying temporal and spatial changes in the most relevant microbial communities that underpin subsequent development of IBD. Now, we are exploring whether the shifts in mucus microbial communities correlate with changed function and altered metabolite profiles. We are also developing methodologies to analyze microbial networks to develop better predictive strategies.