Process-based modelling of Microbial community dynamics in the human colon

The human colon contains a dynamic microbial community whose composition has important implications for human health. In this work we build a process-based model of the colonic microbial ecosystem and compare with general empirical observations and the results of in-vivo experiments. Our model comprises a complex microbial ecosystem along with absorption of short chain fatty acids (SCFA) and water by the host through the gut wall, variations in incoming dietary substrates (in the form of “meals” whose composition varies in time), bowel movements, feedback on microbial growth from changes in pH resulting from SCFA, production, and multiple compartments to represent the proximal, trans12 verse and distal colon. We verify our model against a number of observed criteria, e.g. total SCFA concentrations, SCFA ratios, mass of bowel movements, pH and water absorption over the transit time; and then run simulations investigating the effect of colonic transit time, and the composition and amount of indigestible carbohydrate in the host diet, which we compare with in-vivo studies. The code is available as an R package (microPopGut) to aid future research.