Phylogenomic analysis of natural products biosynthetic gene clusters allows discovery of arseno-organic metabolites in model streptomycetes

Abstract

Data deposition: Annotation of the Biosynthetic Gene Cluster for Arseno-organic metabolites in Streptomyces lividans has been deposited at MiBIG under the accession BGC0001283. AbstractNatural products from microbes have provided humans with beneficial antibiotics for millennia. However, a decline in the pace of antibiotic discovery exerts pressure on human health as antibiotic resistance spreads, a challenge that may better faced by unveiling chemical diversity produced by microbes. Current microbial genome mining approaches have revitalized research into antibiotics, but the empirical nature of these methods limits the chemical space that is explored.Here, we address the problem of finding novel pathways by incorporating evolutionary principles into genome mining. We recapitulated the evolutionary history of twenty-three enzyme families previously uninvestigated in the context of natural product biosynthesis in Actinobacteria, the most proficient producers of natural products. Our genome evolutionary analyses where based on the assumption that expanded-repurposed enzyme families-from central metabolism, occur frequently and thus have the potential to catalyze new conversions in the context of natural products biosynthesis. Our analyses led to the discovery of biosynthetic gene clusters coding for hidden chemical diversity, as validated by comparing our predictions with those from state-of-the-art genome mining tools; as well as experimentally demonstrating the existence of a biosynthetic pathway for arseno-organic metabolites in Streptomyces coelicolor and Streptomyces lividans, Using a gene knockout and metabolite profile combined strategy.As our approach does not rely solely on sequence similarity searches of previously identified biosynthetic enzymes, these results establish the basis for the development of an evolutionary-driven genome mining tool termed EvoMining that complements current platforms. We anticipate that by doing so real 'chemical dark matter' will be unveiled.

Computational approaches to natural product discovery

“…The EvoMining approach 26 exploits this conjecture by detecting the presence of ‘additional’ copies of primary metabolic enzymes in genomes (e.g., from amino acid metabolism), and then using phylogenetic analysis to identify outliers that have undergone significant sequence (and presumably also functional) divergence. These enzymes are subsequently visualized in their genomic context in order to identify new types of biosynthetic gene clusters.…”

Convergent evolution of Streptomyces protease inhibitors involving a tRNA-mediated condensation-minus NRPS

“…We anticipate that the discovery of this tRUE, which functionally interacts with a C-minus NRPS, will pave the way for exploiting this unprecedented biosynthetic logic to uncover novel natural products, and will assist in the development of auxiliary synthetic biology tools to inhibit proteolysis (Cruz-Morales et al 2015a& 2015b. Similar implications are envisaged for leupeptin once its BGC is fully characterized.…”

BiG-SLiCE: A Highly Scalable Tool Maps the Diversity of 1.2 Million Biosynthetic Gene Clusters

“…Clade "a1" shares its 9,402 fungal BGCs with 10,972 bacterial (67.56% came from Pseudomonas) and 13 archaeal ones. This clade includes two simple NRP-encoding fungal BGCs from MIBiG dataset, encoding the biosynthesis of the proteasome inhibitor fellutamide B [82] (BGC0001399) and aspergillic acid [83] (BGC0001516) from Aspergillus (and on the bacterial side: four MIBiG BGCs including another simple proteasome inhibitor livipeptin [84,85] encoded by BGC0001168 from Streptomyces lividans). Clade "a2" We can also see a narrow but distinct clade "b" highly represented by RiPP BGCs from the "gut" Next, by looking at how the pink (innermost) bar is spread all across the phylogram, we can infer that despite holding no more than 2,000 entries presently, the BGCs in the MIBiG database are actually diverse enough to cover much of the general diversity of BGCs.…”