Siderophore synthetase-receptor gene coevolution reveals habitat and pathogen-specific bacterial iron interaction networks

Bacterial social interactions play crucial roles in various ecological, medical, and biotechnological contexts. However, predicting these interactions from genome sequences is notoriously difficult. Here, we developed bioinformatic tools to predict whether secreted iron-scavenging siderophores stimulate or inhibit the growth of community members. Siderophores are chemically diverse and can be stimulatory or inhibitory depending on whether bacteria possess or lack corresponding uptake receptors. We focused on 1928 representative Pseudomonas genomes and developed an experimentally validated co-evolution algorithm to match encoded siderophore synthetases to corresponding receptor groups. We derived community-level iron interaction networks to show that siderophore-mediated interactions differ across habitats and lifestyles. Specifically, dense networks of siderophore sharing and competition were observed among environmental and non-pathogenic species, while small, fragmented networks occurred among human-associated and pathogenic species. Altogether, our sequence-to-ecology approach empowers the analyses of social interactions among thousands of bacterial strains and offers opportunities for targeted intervention to microbial communities.

Methods
All genome data were collected from the open dataset (e.g., Pseudomonas Genome Database), the siderophore synthetase and receptor genes were obtained through genomic data mining. Please check the corresponding article for details.