Genome mining methods to discover bioactive natural products

Abstract

Covering: 2016 to 2021With genetic information available for hundreds of thousands of organisms in publicly accessible databases, scientists have an unprecedented opportunity to meticulously survey the diversity and inner workings of life. The natural product research community has harnessed this breadth of sequence information to mine microbes, plants, and animals for biosynthetic enzymes capable of producing bioactive compounds. Several orthogonal genome mining strategies have been developed in recent years to target specific chemical features or biological properties of bioactive molecules using biosynthetic, resistance, or transporter proteins. These "biosynthetic hooks" allow researchers to query for biosynthetic gene clusters with a high probability of encoding previously undiscovered, bioactive compounds. This review highlights recent case studies that feature orthogonal approaches that exploit genomic information to specifically discover bioactive natural products and their gene clusters.

Fig. 1. Overall scheme for genome mining new natural products with different target chemical features including (A) reactive chemical features, (B) ligand binding features, and (C) compound family defining features. In each case, the diagnostic biosynthetic genes are used to bioinformatically identify candidate gene clusters that putatively encode the production of a target natural product. Subsequent production, isolation, characterization, and bioactivity assay tests validate the bioinformatic prediction.

Fig. 2. NRM solution structure of polytheonamide B (PDB: 2RQO) reveals N-methyl Asns are found on one face of the β-helix. This repeating N–X₅–N motif was targeted for genome mining efforts.

Fig. 3. By mining for the presence of duplicate housekeeping genes, it is possible to discover natural products and their biological target simultaneously.

Fig. 4. Bioinformatically identified natural products can be produced either synthetically or biosynthetically to generate new molecules that mimic the authentic compound.

Fig. 5. Sub-clustering of genes is responsible for the installation of bioactive chemical features and class-defining chemical features. Gene clusters not shown to scale. (A) Sub-clustering of the DUF and cysteine lyase domains (red) is responsible for the installation of reactive 1,3-dioxo-1,2-dithiolane moiety and is seen in leinamycin (lnm) BGC, guangnanmycin (gnm) BGC, and weishanmycin (wsm) BGC (Section 2.1.4). (B) Sub-clustering of two genes grbD and grbE (blue) that are responsible for the installation of the diazeniumdiolate moiety is evident in the gramibactin BGC (grb) as well as the BGCs responsible for production of megapolibactin from a symbiotic bacterial strain and gladiobactin/plantaribactin from a pathogenic bacterial strain (Section 2.2.1). C. Genes required for installation of the cinnamoyl-moiety (green) are found sub-clustered in the BGCs for WS9326 (cal), skyllamycin (sky), and kitacinnamycin (kcn) (Section 3.3).

Katherine D. Bauman

Keelie S. Butler

Bradley S. Moore

Jonathan R. Chekan