Scientific Reports · 2020 · 245 citations · 47 references
Life SciencesMicrobiologyMolecular BiologyComparative GenomicsGenomicsPhylogeneticsBiosynthetic Gene ClustersMicrobial Metabolite ProductionMicrobial PhylogeneticsMicrobial PhylogenyMolecular PhylogenyPhylogenetic ClassificationBiosynthetic Gene Cluster AnalysisGenome MiningMicrobial Genome-encoded BiosynthesisNon-ribosomal Peptide BiosynthesisSecondary MetabolitesStrain-level GenomicsStrain-level VariationTerpene Biosynthetic Gene Clusters
Streptomyces bacteria are known for their prolific production of secondary metabolites, many of which have been widely used in human medicine, agriculture and animal health. To guide the effective prioritization of specific biosynthetic gene clusters (BGCs) for drug development and targeting the most prolific producer strains, knowledge about phylogenetic relationships of Streptomyces species, genome-wide diversity and distribution patterns of BGCs is critical. We used genomic and phylogenetic methods to elucidate the diversity of major classes of BGCs in 1,110 publicly available Streptomyces genomes. Genome mining of Streptomyces reveals high diversity of BGCs and variable distribution patterns in the Streptomyces phylogeny, even among very closely related strains. The most common BGCs are non-ribosomal peptide synthetases, type 1 polyketide synthases, terpenes, and lantipeptides. We also found that numerous Streptomyces species harbor BGCs known to encode antitumor compounds. We observed that strains that are considered the same species can vary tremendously in the BGCs they carry, suggesting that strain-level genome sequencing can uncover high levels of BGC diversity and potentially useful derivatives of any one compound. These findings suggest that a strain-level strategy for exploring secondary metabolites for clinical use provides an alternative or complementary approach to discovering novel pharmaceutical compounds from microbes.
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Basic local alignment search tool
Stephen F. Altschul, Warren Gish, Webb Miller et al. · Journal of Molecular Biology · 1990 · 94.5K citations
Prokka: rapid prokaryotic genome annotation
Torsten Seemann · Bioinformatics · 2014 · 19.6K citations