A computational framework to explore large-scale biosynthetic diversity
2019
Navarro-Muñoz, Jorge C. | Selem-Mojica, Nelly | Mullowney, Michael W. | Kautsar, Satria A. | Tryon, James H. | Parkinson, Elizabeth I. | De Los Santos, Emmanuel L.C. | Yeong, Marley | Cruz-Morales, Pablo | Abubucker, Sahar | Roeters, Arne | Lokhorst, Wouter | Fernandez-Guerra, Antonio | Cappelini, Luciana Teresa Dias | Goering, Anthony W. | Thomson, Regan J. | Metcalf, William W. | Kelleher, Neil L. | Barona-Gomez, Francisco | Medema, Marnix H.
Genome mining has become a key technology to exploit natural product diversity. Although initially performed on a single-genome basis, the process is now being scaled up to mine entire genera, strain collections and microbiomes. However, no bioinformatic framework is currently available for effectively analyzing datasets of this size and complexity. In the present study, a streamlined computational workflow is provided, consisting of two new software tools: the ‘biosynthetic gene similarity clustering and prospecting engine’ (BiG-SCAPE), which facilitates fast and interactive sequence similarity network analysis of biosynthetic gene clusters and gene cluster families; and the ‘core analysis of syntenic orthologues to prioritize natural product gene clusters’ (CORASON), which elucidates phylogenetic relationships within and across these families. BiG-SCAPE is validated by correlating its output to metabolomic data across 363 actinobacterial strains and the discovery potential of CORASON is demonstrated by comprehensively mapping biosynthetic diversity across a range of detoxin/rimosamide-related gene cluster families, culminating in the characterization of seven detoxin analogues.
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