Modeling the microbial contribution to human energy balance using the Digestion, Absorption, and Microbial Metabolism (DAMM) model

Abstract

Colonic microorganisms have been linked to human health and disease, specifically metabolic disease states such as obesity, but causal relationships remain to be established. Previous work demonstrated that interactions between the host’s diet and intestinal microbiome were associated with human energy balance by affecting the human’s energy absorption, quantified by metabolizable energy. We developed the Digestion, Absorption and Microbial Metabolism (DAMM) model, which explicitly accounts for the energy contributions of the colonic microbial community in five steps. 1) The DAMM model breaks down the diet composition into the gross energy of the individual macronutrients. 2) It calculates direct absorption in the upper gastrointestinal tract. 3) It uses microbial stoichiometry to estimate the consumption of the remaining unabsorbed nutrients by microbes in the large intestine. 4) It quantitatively predicts microbial production of short-chain fatty acids (SCFA) and methane in the colon. 5) The DAMM model estimates absorption from the colonic tract to the host, including SCFAs. When used to predict the results from a clinical study that compared two distinctly different diets, the DAMM model captured the directionality and magnitude of change in measured metabolizable chemical oxygen demand (which can be converted to metabolizable energy), estimated substrate availability within the colon, and predicted rate of production of microbially derived short-chain fatty acids. It improved on the accuracy of metabolizable chemical oxygen demand predictions compared to the Atwater factors, increasing the fit from R2 = 88% (Atwater) to R2 = 96% (DAMM). The model reduced systematic bias on one of the diets and decreased the mean difference between measurement and predictions from −22.3 gCOD d-1 to −2.5 gCOD d-1. The DAMM model now can be linked to existing human models that predict changes in body energy stores to extend our understanding of how microbial metabolic processes affect macronutrient absorption and metabolizable energy.