Function-Based Selection of Synthetic Communities Enables Mechanistic Microbiome Studies
Understanding the complex interactions between microbes and their environment requires robust model systems such as synthetic communities (SynComs). We developed a functionally directed approach to generate SynComs by selecting strains that encode key functions identified in metagenomes. This approach enables the rapid construction of SynComs tailored to any ecosystem. To optimize community design, we implemented genome-scale metabolic models, providing in silico evidence for cooperative strain coexistence prior to experimental validation. Using this strategy, we designed multiple host-specific SynComs, including those for the rumen, mouse, and human microbiomes. By weighting functions differentially enriched in diseased versus healthy individuals, we constructed SynComs that capture complex host-microbe interactions. Notably, we designed an inflammatory bowel disease SynCom of 10 members that successfully induced colitis in gnotobiotic IL10-/- mice, demonstrating the potential of this method to model disease-associated microbiomes. Our study establishes a targeted framework for designing SynComs to advance mechanistic insights into host-microbe interactions. HighlightsO_LIAutomated functional selection of SynComs based on metagenomic data C_LIO_LIEcosystem-specific SynComs capture the functional landscape of microbiota C_LIO_LIColitis-inducing SynCom developed as a model for inflammatory bowel diseases C_LI