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Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters

Streptomyces are Gram-positive bacteria of significant industrial importance due to their ability to produce a wide range of antibiotics and bioactive secondary metabolites. Recent advances in genome mining have revealed that Streptomyces genomes possess a large number of unexplored silent secondary...

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Autores principales: Lee, Namil, Kim, Woori, Hwang, Soonkyu, Lee, Yongjae, Cho, Suhyung, Palsson, Bernhard, Cho, Byung-Kwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018776/
https://www.ncbi.nlm.nih.gov/pubmed/32054853
http://dx.doi.org/10.1038/s41597-020-0395-9
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author Lee, Namil
Kim, Woori
Hwang, Soonkyu
Lee, Yongjae
Cho, Suhyung
Palsson, Bernhard
Cho, Byung-Kwan
author_facet Lee, Namil
Kim, Woori
Hwang, Soonkyu
Lee, Yongjae
Cho, Suhyung
Palsson, Bernhard
Cho, Byung-Kwan
author_sort Lee, Namil
collection PubMed
description Streptomyces are Gram-positive bacteria of significant industrial importance due to their ability to produce a wide range of antibiotics and bioactive secondary metabolites. Recent advances in genome mining have revealed that Streptomyces genomes possess a large number of unexplored silent secondary metabolite biosynthetic gene clusters (smBGCs). This indicates that Streptomyces genomes continue to be an invaluable source for new drug discovery. Here, we present high-quality genome sequences of 22 Streptomyces species and eight different Streptomyces venezuelae strains assembled by a hybrid strategy exploiting both long-read and short-read genome sequencing methods. The assembled genomes have more than 97.4% gene space completeness and total lengths ranging from 6.7 to 10.1 Mbp. Their annotation identified 7,000 protein coding genes, 20 rRNAs, and 68 tRNAs on average. In silico prediction of smBGCs identified a total of 922 clusters, including many clusters whose products are unknown. We anticipate that the availability of these genomes will accelerate discovery of novel secondary metabolites from Streptomyces and elucidate complex smBGC regulation.
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spelling pubmed-70187762020-03-03 Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters Lee, Namil Kim, Woori Hwang, Soonkyu Lee, Yongjae Cho, Suhyung Palsson, Bernhard Cho, Byung-Kwan Sci Data Data Descriptor Streptomyces are Gram-positive bacteria of significant industrial importance due to their ability to produce a wide range of antibiotics and bioactive secondary metabolites. Recent advances in genome mining have revealed that Streptomyces genomes possess a large number of unexplored silent secondary metabolite biosynthetic gene clusters (smBGCs). This indicates that Streptomyces genomes continue to be an invaluable source for new drug discovery. Here, we present high-quality genome sequences of 22 Streptomyces species and eight different Streptomyces venezuelae strains assembled by a hybrid strategy exploiting both long-read and short-read genome sequencing methods. The assembled genomes have more than 97.4% gene space completeness and total lengths ranging from 6.7 to 10.1 Mbp. Their annotation identified 7,000 protein coding genes, 20 rRNAs, and 68 tRNAs on average. In silico prediction of smBGCs identified a total of 922 clusters, including many clusters whose products are unknown. We anticipate that the availability of these genomes will accelerate discovery of novel secondary metabolites from Streptomyces and elucidate complex smBGC regulation. Nature Publishing Group UK 2020-02-13 /pmc/articles/PMC7018776/ /pubmed/32054853 http://dx.doi.org/10.1038/s41597-020-0395-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Lee, Namil
Kim, Woori
Hwang, Soonkyu
Lee, Yongjae
Cho, Suhyung
Palsson, Bernhard
Cho, Byung-Kwan
Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters
title Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters
title_full Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters
title_fullStr Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters
title_full_unstemmed Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters
title_short Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters
title_sort thirty complete streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018776/
https://www.ncbi.nlm.nih.gov/pubmed/32054853
http://dx.doi.org/10.1038/s41597-020-0395-9
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