Integrated genomics and metabolomics survey of steroids from myxobacteria

Steroids from myxobacteria remain largely underexplored compared to other natural product classes, leaving a significant gap in our understanding of their biosynthetic diversity, evolutionary trajectories, and pharmacological potential. To address this, we conducted a systematic genomic survey of myxobacterial genomes to delineate the distribution and phylogenetic context of sterol biosynthetic genes, which we found to be organized in a dispersed manner across the chromosome rather than clustered into canonical biosynthetic gene clusters. While the sterol biosynthetic machinery is broadly distributed across Myxococcota, its occurrence is strikingly uneven among lineages, with Nannocystaceae exhibiting the highest biosynthetic potential. Sequence similarity network mining of the oxidosqualene cyclases (OSCs) essential for sterol biosynthesis revealed extensive sequence divergence and unexplored space for discovering novel catalytic functions. Motivated by these bioinformatics predictions, we further demonstrated that integrated chromatographic pre-fractionation with NMR-based metabolic profiling streamlines the targeted isolation of steroids. This approach yielded 12 (seco-)steroids from 2 in-house myxobacterial strains, including 4 previously undescribed structures featuring diverse oxidative decorations, skeletal rearrangements, and ring degradation. Bioactivity assays uncovered that a co-produced metabolite alkylglycoside synergistically potentiates the antimicrobial activity of select secosteroids. Collectively, this study establishes an integrated genomics-metabolomics pipeline that not only expands the structural repertoire of myxobacterial steroids but also provides a blueprint for future discovery of cryptic sterol metabolites and their hidden biological functions.IMPORTANCEThis study presents a systematic phylogenomic survey of sterol biosynthetic genes across the phylum Myxococcota, revealing a dispersed genomic architecture that diverges from canonical bacterial secondary metabolite gene clusters. Beyond this conceptual advance, we demonstrate, for the first time, that NMR-based metabolomics coupled with chromatographic pre-fractionation can accelerate steroid discovery from myxobacteria, leading to the discovery of previously undescribed (seco-)steroids that expand the known chemical space. This integrated pipeline not only enables efficient discovery of cryptic sterol metabolites but also establishes a foundation for understanding the ecological roles of steroids in myxobacteria.