Genomic-Based Prediction of Exopolysaccharide Composition and Structure: Insights from Rhizobium and Sinorhizobium Species
Bacterial exopolysaccharides (EPS) are key components in biofilm formation, stress protection, and symbiosis in Rhizobiaceae. While EPS structural diversity is extensive, experimental characterization remains limited. In this study, we experimentally determined and compared four distinct EPS structures produced by ten Rhizobium alamii strains. Using genomic data, we bioinformatically identified supra-operonic clusters (SOCs) responsible for these EPS biosynthesis. We introduced a computational framework to predict, score, and compare EPS SOCs across 84 Rhizobium and Sinorhizobium species, linking gene content to structural and functional EPS diversity. A total of 743 EPS SOCs was selected for network analyses, allowing the identification of 36 major groups of orthologous EPS SOCs, successfully recovering all known EPS biosynthetic loci and two novels SOCs potentially encoding uncharacterized EPS (xEPS-I, xEPS-II). Profiles of EPS SOCs correlated with taxonomical groups, with a single EPS SOC conserved through all 84 genomes and distinct additional EPS SOCs depending on the group, but do not strictly explain symbiotic capacity. Genetic comparisons of transporters (Wzx, Wzy) and glycosyltransferase sequences indicated these proteins as key markers of EPS structure. Overall, this computational framework accurately identified and classified EPS SOCs, providing a scalable, genome-based method for predicting EPS biosynthetic potential in Rhizobiaceae and usable in other microbial genera. Author Summary We developed a computational approach to predict how beneficial soil bacteria produce natural exopolysaccharides (EPS) that help them survive and interact with plants. These macromolecules, which form protective coatings and enable partnerships with crops, are currently difficult and expensive to study using traditional laboratory methods. By examining the genetic blueprints of 84 bacterial species from the Rhizobiaceae, we identified the key gene clusters responsible for producing these EPS, including two that were previously unknown. Our findings show that while some genetic patterns are widely shared among many bacteria, others are unique to specific types, shaping their individual abilities and characteristics. This research provides a faster, more cost-effective way to explore the vast diversity of these important macromolecules across different bacterial species. These insights could enable enhanced bacterial treatments that boost crop growth and resilience, particularly against water stress. Additionally, our method offers a valuable template for studying similar processes in other beneficial microorganisms, ultimately advancing our understanding of how they contribute to plant health, soil fertility, and the development of more sustainable farming practices worldwide.