An integrative chemical and genomic similarity approach linking fungal secondary metabolites and biosynthetic gene clusters

Abstract

Fungi are well known to biosynthesize structurally complex secondary metabolites (SMs) with diverse bioactivities. These fungal SMs are frequently produced by biosynthetic gene clusters (BGCs). Linking SMs to their BGCs is key to understanding their chemical and biological functions. Reasoning that structural similarity of SMs arises from similarities in the genes involved in their biosynthesis, we developed an integrative approach that leverages known SM-BGC pairs to infer links between detected SMs and genome-predicted BGC regions in fungi. As proof of concept, we structurally characterized 60 metabolites from metabolomic data of 16 strains of the filamentous fungus Aspergillus fischeri. Our approach assigned 22 to known SM-BGC pairs and proposed specific links to BGCs and genetic pathways for the remaining 38 metabolites. These results suggest that coupling chemical structure similarity and genomic sequence similarity is a straightforward and high-throughput approach for linking fungal SMs to their BGCs.