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Journal ArticleDOI

The confluence of big data and evolutionary genome mining for the discovery of natural products.

TLDR
This review covers literature between 2003-2021 and highlights examples where Big Data and evolutionary analyses have been combined to provide bioinformatic resources and tools for the discovery of novel natural products and their biosynthetic enzymes.
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This article is published in Natural Product Reports.The article was published on 2021-11-17. It has received 21 citations till now.

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A Systematic Computational Analysis of Biosynthetic Gene Cluster Evolution: Lessons for Engineering Biosynthesis - eScholarship

TL;DR: By performing a systematic computational analysis of BGC evolution, this work derives evidence for three findings that shed light on the ways in which, despite these constraints, nature successfully invents new molecules.
Journal ArticleDOI

Compendium of specialized metabolite biosynthetic diversity encoded in bacterial genomes

TL;DR: The authors analyzed ~170,000 bacterial genomes and ~47,000 metagenome assembled genomes using a modified BiG-SLiCE and the new clust-o-matic algorithm.
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Microbiome composition modulates secondary metabolism in a multispecies bacterial community

TL;DR: Results from this model community show that bacterial BGC expression and chemical output depend on the identity and biosynthetic capacity of coculture partners, suggesting community composition and microbiome interactions may shape the regulation of secondary metabolism in nature.
Journal ArticleDOI

Targeted Large-Scale Genome Mining and Candidate Prioritization for Natural Product Discovery

TL;DR: Genomics-based approaches for prioritizing candidate BGCs extracted from large-scale genomic data are discussed, by highlighting studies that have successfully produced compounds with high chemical novelty, novel biosynthesis pathway, and potent bioactivities.
Journal ArticleDOI

Integrated Metabolomic–Genomic Workflows Accelerate Microbial Natural Product Discovery

TL;DR: This work considers innovative approaches which have led to prioritization of strain targets and have mitigated rediscovery rates, and discusses integration of principles of comparative evolutionary studies and retrobiosynthetic predictions to better understand biosynthetic mechanistic details and link genome sequence to structure.
References
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Journal ArticleDOI

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

TL;DR: 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, are recapitulated to establish the basis for the development of an evolutionary-driven genome mining tool termed EvoMining that complements current platforms.
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Lateral Gene Transfer Dynamics in the Ancient Bacterial Genus Streptomyces.

TL;DR: It is shown that acquisition and retention of genes through LGT are surprisingly rare in the ubiquitous and biomedically important bacterial genus Streptomyces, with merely one gene acquired in StrePTomyces lineages every 100,000 years.
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Bacterial Secondary Metabolite Biosynthetic Potential in Soil Varies with Phylum, Depth, and Vegetation Type.

TL;DR: This work sampled soils and saprolite from three sites in a northern California Critical Zone Observatory with various vegetation and bedrock characteristics and reconstructed 1,334 metagenome-assembled genomes containing diverse biosynthetic gene clusters (BGCs) for secondary metabolite production.
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Comparative genomics reveals phylogenetic distribution patterns of secondary metabolites in Amycolatopsis species.

TL;DR: The analysis demonstrates that horizontal and vertical gene transfer play an important role in the acquisition and maintenance of valuable secondary metabolites and casts light on the interconnections between secondary metabolite gene clusters.
Journal ArticleDOI

Metabolite-Enzyme Coevolution: From Single Enzymes to Metabolic Pathways and Networks.

TL;DR: This review develops the current knowledge of enzyme evolution into a wider hypothesis of pathway and network evolution and offers an integrative metabolite-enzyme coevolution hypothesis that addresses the origins of new metabolites and of new enzymes and the order of their recruitment.
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