Genome-scale metabolic models for a synthetic soil microbial community as a path for understanding community functioning

Abstract

Microbial communities drive essential ecosystem processes, yet community-level behavior often deviates from predictions based on single-species studies. This mismatch reflects the context-dependent nature of nutrient dependencies, metabolic interactions, and resource availability in complex environments. Here, we present a mechanistic, species-resolved framework to dissect metabolism and nutrient exchange in a defined 21-member soil synthetic community spanning five bacterial phyla. For each isolate, we reconstructed and manually curated thermodynamically constrained genome-scale metabolic models, reconciling predictions with growth phenotypes across rich and minimal media. We mapped minimal nutrient requirements, cataloged environment-specific uptake and secretion profiles, and compared metabolic pathways to identify potential competitive and cooperative interactions. Using community-scale metabolomics, we assigned putative producers and consumers for detected metabolites and revealed medium-dependent shifts in niche overlap. This approach exposes metabolic strategies that govern community function and resilience, offering a predictive basis for understanding and manipulating microbiomes. Our findings highlight how species-level metabolic maps can clarify why microbial interventions succeed or fail and guide targeted manipulations in soil ecosystems.