Metabolic modeling of host-microbe interactions

Host-microbe interactions play an integral role in the function and survival of eukaryotes, influencing various processes ranging from metabolism to immune regulation. As our understanding of these interactions deepens, there is a growing shift toward integrative approaches that consider both host and microbial genotypic potential. However, capturing the complexity and dynamic nature of these relationships remains a significant challenge. Genome-scale metabolic models (GEMs) offer a powerful framework to investigate host-microbe interactions at a systems level. By simulating metabolic fluxes and cross-feeding relationships, GEMs enable the exploration of metabolic interdependencies and emergent community functions. These models can be applied independently or in conjunction with experimental data, supporting hypothesis generation and systems-level insights into host-microbe dynamics. In this review, we examine recent applications of GEMs to host-microbe studies, with a focus on how they reveal reciprocal metabolic influences. We also discuss the current technical challenges, highlight available tools and methodological strategies, such as model reconstruction, data integration, and simulation and analysis steps, and outline future directions for advancing host-microbe interaction study using GEMs.