Microbial Community-Scale Metabolic Modeling: Personalized Predictions for Short-Chain Fatty Acid Production from the Human Gut Microbiome

Abstract

Small-molecule production in response to dietary input is a primary mechanism in which the gut microbiome can affect the health of the host. Microbially-derived short chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, individuals exposed to identical diets often show significant variation in the level of produced SCFAs, which remains poorly understood at a systems scale. Addressing this gap, we propose employing microbial community-scale metabolic models (MCMMs) to predict individual-specific SCFA production profiles. To validate this approach, we leverage in vitro and ex vivo fluxomic data across several independent datasets. Furthermore, the clinical relevance of MCMMs is illustrated by associating predicted SCFA profiles with physiological markers of inflammation and cardiometabolic health, and by demonstrating the use of this approach to design and test precision microbiome-targeted interventions. Finally, work towards integration of MCMMs with a metabolic model of the human colonic epithelium allows for a comprehensive exploration of metabolic exchanges influencing health and disease. Ultimately MCMMs offer a promising avenue for the future of precision nutrition, aimed at modulating metabolic production from the gut microbiome to benefit human health.