A computational method for the dynamic simulation of the human gut microbiome

Abstract

The human gut microbiome contributes to human health and disease through the complex microbe-microbe and host-microbe metabolic interactions. However, the complexity of metabolic interactions in the gut environment makes it difficult to interpret the experimental data from gut microbiome studies and to understand the functions of individual microbes in the gut. We developed a dynamic flux-balance-analysis-based simulator to predict the dynamics of microbe-microbe and host-microbe metabolic interactions in the human gut and to understand the mechanistic role of the gut microbes. The activities of individual microbes are simulated by using their genome-scale metabolic models, which utilize a common pool of metabolites in the gut environment. The simulator also allows the host cells to exchange the metabolites by accessing the common pool of metabolites. We demonstrate the utility of the simulator by simulating changes in the densities of microbes and in the concentrations of short-chain fatty acids in response to dietary changes. The model predicts the altered microbial metabolic activities due to macronutrient shifts and the prediction is consistent with the experimental observations. This work was supported by the National Research Foundation (NRF) of Korea via RS-2023-00263411 and RS-2024-00345749.