Sidero-Mining: Systematic Extraction of Siderophore Biosynthetic Information Using Large Language Models
Siderophores are central mediators of microbial iron acquisition, competition, and ecological adaptation, yet their biosynthetic diversity remains difficult to resolve across species because existing sequence-based BGC comparison is strongly constrained by phylogenetic background. Here we combine large-language-model-assisted literature mining, functional-space comparison, and genome-scale analysis to resolve the global organization of siderophore biosynthesis across bacteria. We first built SideroBank, a manually curated cross-species benchmark of siderophore biosynthetic gene clusters (BGCs), and used it to show that many identical products recur across distant taxa whereas the corresponding BGCs often fail to cluster in sequence space. We then developed BGC Block Aligner, which compares BGCs as ordered systems of functionally meaningful blocks and thereby converts comparison from sequence space to functional space. Applied to 97,432 bacterial genomes, this framework produced the Siderophore Atlas, revealing that siderophore synthesis is a remarkably pervasive trait encoded by over 60% of the analyzed genomes, with certain clusters being the most widely disseminated secondary metabolites across the bacterial domain. This global landscape suggests that the adoption of specific biosynthetic strategies is predominantly driven by ecological lifestyle rather than strict phylogenetic relatedness. Furthermore, a stark macro-evolutionary dichotomy was observed between the continuous structural diversification of NRPS pathways and the standardized, HGT-driven dissemination of NIS systems, linking functional-space genomics to the global ecology and evolution of siderophore biosynthesis..