CODY enables quantitatively spatiotemporal predictions on in vivo gut microbial variability induced by diet intervention

Microbial variations in the human gut are harbored in temporal and spatial heterogeneity, and quantitative prediction of spatiotemporal dynamic changes in the gut microbiota is imperative for development of tailored microbiome-directed therapeutics treatments, e.g. precision nutrition. Given the high-degree complexity of microbial variations, subject to the dynamic interactions among host, microbial, and environmental factors, identifying how microbiota colonize in the gut represents an important challenge. Here we present COmputing the DYnamics of microbiota (CODY), a multiscale framework that integrates species-level modeling of microbial dynamics and ecosystem-level interactions into a mathematical model that characterizes spatial-specific in vivo microbial residence in the colon as impacted by host physiology. The framework quantifies spatiotemporal resolution of microbial variations on species-level abundance profiles across site-specific colon regions and in feces, independent of a priori knowledge. We demonstrated the effectiveness of CODY using cross-sectional data from two longitudinal metagenomics studies-the microbiota development during early infancy and during short-term diet intervention of obese adults. For each cohort, CODY correctly predicts the microbial variations in response to diet intervention, as validated by available metagenomics and metabolomics data. Model simulations provide insight into the biogeographical heterogeneity among lumen, mucus, and feces, which provides insight into how host physical forces and spatial structure are shaping microbial structure and functionality.

Automated summary

Microbial variations in the human gut are complex and understanding how microbiota colonize in the gut is a key challenge. The CODY framework integrates species-level modeling of microbial dynamics and ecosystem-level interactions to predict spatiotemporal dynamic changes in the gut microbiota, demonstrating effectiveness in predicting microbial variations in response to diet interventions. Model simulations provide insight into the biogeographical heterogeneity among lumen, mucus, and feces, shaping microbial structure and functionality.