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Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria

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 mos...

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Detalles Bibliográficos
Autores principales: Belknap, Kaitlyn C., Park, Cooper J., Barth, Brian M., Andam, Cheryl P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005152/
https://www.ncbi.nlm.nih.gov/pubmed/32029878
http://dx.doi.org/10.1038/s41598-020-58904-9
Descripción
Sumario: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.