(620d) A Mathematical Model to Study the Effects of Gut Microbes on the Human Host’s Energy Balance | AIChE

(620d) A Mathematical Model to Study the Effects of Gut Microbes on the Human Host’s Energy Balance

Authors 

Davis, T. L. - Presenter, Arizona State University
Krajmalnik-Brown, R., Arizona State University
Rittmann, B., Arizona State University
Marcus, A. K., Arizona State University
The human gut microbiome influences many facets of human health, including weight changes and metabolic disorders such as obesity. While effects of diet on the human gut microbiome are recognized, quantitative relationships among diet, the gut microbiome, and the host metabolism have not been established mechanistically. Many traditional human bioenergetics models link dietary energy intake to the host’s energy expenditures, but the microbial metabolism is often neglected.

Here, we developed a mathematical model describing energy flow within the human body in three parts: 1. the upper gastrointestinal (GI) tract tracks energy absorbed via physiological processes; 2. the colon that hosts microbes and absorbs microbe-derived short-chain fatty acids (SCFAs); 3. the host’s energy reservoirs that store carbohydrates, proteins, fats, and SCFAs absorbed by the GI tract and oxidize them to satisfy the body’s energy-expenditure demands. We evaluated our model and previous models without microbial metabolism by examining the clinical data from Reinhardt et al. (2015) for obese participants on a calorically restrictive diet.

Our model showed increased accuracy when predicting body weight changes while dieting compared with metabolic models that did not include the gut microbiome reactions. Depending on the diet, the SCFAs from microbial production changed the amount of available energy from the ingested food by up to 11%. Diets with higher fiber and protein increased the fraction of available energy from food that the gut microbiome contributed. When in negative energy balance, participants had increased SCFA uptake from microbial processes resulting in an increase in total energy expenditure. Our mathematical modeling framework provides a way to describe how microorganisms mediates the effects of diet on the host’s weight changes and energy expenditures. This could be used for the development of individual-specific probiotics/prebiotics, potentially helping with certain health issues associated with unhealthy gut microbiomes.