From sequence to ecology: siderophore-receptor coevolution algorithm predicts bacterial interactions in complex communities

Abstract

AbstractUnlocking the secrets of microbial interactions through genomics is pivotal for advancing microbial ecology. In most ecosystems, the scarcity of iron makes iron-mediated interactions a central theme in shaping microbial communities. Bacteria have evolved diverse strategies, including the production of siderophores—diverse secondary metabolites—to scavenge iron from their surroundings. Here, we use bioinformatic tools to predict siderophore iron-interaction networks among 1928Pseudomonasstrains from sequence data. Our approach uses coevolution analysis to group siderophore synthetase clusters and receptors used for uptake into key-lock pairs. Through a mix of computational analyses and experimental validation, we reconstructPseudomonasiron-interaction networks across a spectrum of habitats, from soil to water, plants, and human-related environments and reveal substantial differences in network structure and connectivity across habitats. Altogether, our sequence-to-interaction mapping tool empowers researchers to decode bacterial ecology in complex microbiomes, setting the stage for novel interventions to engineer microbiome functionality.