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Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences

Sequencing of DNA extracted from environmental samples can provide key insights into the biosynthetic potential of uncultured bacteria. However, the high complexity of soil metagenomes, which can contain thousands of bacterial species per gram of soil, imposes significant challenges to explore secon...

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Autores principales: Libis, Vincent, Antonovsky, Niv, Zhang, Mengyin, Shang, Zhuo, Montiel, Daniel, Maniko, Jeffrey, Ternei, Melinda A., Calle, Paula Y., Lemetre, Christophe, Owen, Jeremy G., Brady, Sean F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710260/
https://www.ncbi.nlm.nih.gov/pubmed/31451725
http://dx.doi.org/10.1038/s41467-019-11658-z
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author Libis, Vincent
Antonovsky, Niv
Zhang, Mengyin
Shang, Zhuo
Montiel, Daniel
Maniko, Jeffrey
Ternei, Melinda A.
Calle, Paula Y.
Lemetre, Christophe
Owen, Jeremy G.
Brady, Sean F.
author_facet Libis, Vincent
Antonovsky, Niv
Zhang, Mengyin
Shang, Zhuo
Montiel, Daniel
Maniko, Jeffrey
Ternei, Melinda A.
Calle, Paula Y.
Lemetre, Christophe
Owen, Jeremy G.
Brady, Sean F.
author_sort Libis, Vincent
collection PubMed
description Sequencing of DNA extracted from environmental samples can provide key insights into the biosynthetic potential of uncultured bacteria. However, the high complexity of soil metagenomes, which can contain thousands of bacterial species per gram of soil, imposes significant challenges to explore secondary metabolites potentially produced by rare members of the soil microbiome. Here, we develop a targeted sequencing workflow termed CONKAT-seq (co-occurrence network analysis of targeted sequences) that detects physically clustered biosynthetic domains, a hallmark of bacterial secondary metabolism. Following targeted amplification of conserved biosynthetic domains in a highly partitioned metagenomic library, CONKAT-seq evaluates amplicon co-occurrence patterns across library subpools to identify chromosomally clustered domains. We show that a single soil sample can contain more than a thousand uncharacterized biosynthetic gene clusters, most of which originate from low frequency genomes which are practically inaccessible through untargeted sequencing. CONKAT-seq allows scalable exploration of largely untapped biosynthetic diversity across multiple soils, and can guide the discovery of novel secondary metabolites from rare members of the soil microbiome.
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spelling pubmed-67102602019-08-28 Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences Libis, Vincent Antonovsky, Niv Zhang, Mengyin Shang, Zhuo Montiel, Daniel Maniko, Jeffrey Ternei, Melinda A. Calle, Paula Y. Lemetre, Christophe Owen, Jeremy G. Brady, Sean F. Nat Commun Article Sequencing of DNA extracted from environmental samples can provide key insights into the biosynthetic potential of uncultured bacteria. However, the high complexity of soil metagenomes, which can contain thousands of bacterial species per gram of soil, imposes significant challenges to explore secondary metabolites potentially produced by rare members of the soil microbiome. Here, we develop a targeted sequencing workflow termed CONKAT-seq (co-occurrence network analysis of targeted sequences) that detects physically clustered biosynthetic domains, a hallmark of bacterial secondary metabolism. Following targeted amplification of conserved biosynthetic domains in a highly partitioned metagenomic library, CONKAT-seq evaluates amplicon co-occurrence patterns across library subpools to identify chromosomally clustered domains. We show that a single soil sample can contain more than a thousand uncharacterized biosynthetic gene clusters, most of which originate from low frequency genomes which are practically inaccessible through untargeted sequencing. CONKAT-seq allows scalable exploration of largely untapped biosynthetic diversity across multiple soils, and can guide the discovery of novel secondary metabolites from rare members of the soil microbiome. Nature Publishing Group UK 2019-08-26 /pmc/articles/PMC6710260/ /pubmed/31451725 http://dx.doi.org/10.1038/s41467-019-11658-z Text en © The Author(s) 2019 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/.
spellingShingle Article
Libis, Vincent
Antonovsky, Niv
Zhang, Mengyin
Shang, Zhuo
Montiel, Daniel
Maniko, Jeffrey
Ternei, Melinda A.
Calle, Paula Y.
Lemetre, Christophe
Owen, Jeremy G.
Brady, Sean F.
Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences
title Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences
title_full Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences
title_fullStr Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences
title_full_unstemmed Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences
title_short Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences
title_sort uncovering the biosynthetic potential of rare metagenomic dna using co-occurrence network analysis of targeted sequences
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710260/
https://www.ncbi.nlm.nih.gov/pubmed/31451725
http://dx.doi.org/10.1038/s41467-019-11658-z
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