Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery

Current genome mining methods predict many putative non-ribosomal peptides (NRPs) from their corresponding biosynthetic gene clusters, but it remains unclear which of those exist in nature and how to identify their post-assembly modifications. Here, the authors develop NRPminer, a modification-toler...

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Autores principales:	Bahar Behsaz, Edna Bode, Alexey Gurevich, Yan-Ni Shi, Florian Grundmann, Deepa Acharya, Andrés Mauricio Caraballo-Rodríguez, Amina Bouslimani, Morgan Panitchpakdi, Annabell Linck, Changhui Guan, Julia Oh, Pieter C. Dorrestein, Helge B. Bode, Pavel A. Pevzner, Hosein Mohimani
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/56701c0cd5c2408cb5012222fe11866d
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spelling	oai:doaj.org-article:56701c0cd5c2408cb5012222fe11866d2021-12-02T14:47:29ZIntegrating genomics and metabolomics for scalable non-ribosomal peptide discovery10.1038/s41467-021-23502-42041-1723https://doaj.org/article/56701c0cd5c2408cb5012222fe11866d2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23502-4https://doaj.org/toc/2041-1723Current genome mining methods predict many putative non-ribosomal peptides (NRPs) from their corresponding biosynthetic gene clusters, but it remains unclear which of those exist in nature and how to identify their post-assembly modifications. Here, the authors develop NRPminer, a modification-tolerant tool for the discovery of NRPs from large genomic and mass spectrometry datasets, and use it to find 180 NRPs from different environments.Bahar BehsazEdna BodeAlexey GurevichYan-Ni ShiFlorian GrundmannDeepa AcharyaAndrés Mauricio Caraballo-RodríguezAmina BouslimaniMorgan PanitchpakdiAnnabell LinckChanghui GuanJulia OhPieter C. DorresteinHelge B. BodePavel A. PevznerHosein MohimaniNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-17 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Bahar Behsaz Edna Bode Alexey Gurevich Yan-Ni Shi Florian Grundmann Deepa Acharya Andrés Mauricio Caraballo-Rodríguez Amina Bouslimani Morgan Panitchpakdi Annabell Linck Changhui Guan Julia Oh Pieter C. Dorrestein Helge B. Bode Pavel A. Pevzner Hosein Mohimani Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery
description	Current genome mining methods predict many putative non-ribosomal peptides (NRPs) from their corresponding biosynthetic gene clusters, but it remains unclear which of those exist in nature and how to identify their post-assembly modifications. Here, the authors develop NRPminer, a modification-tolerant tool for the discovery of NRPs from large genomic and mass spectrometry datasets, and use it to find 180 NRPs from different environments.
format	article
author	Bahar Behsaz Edna Bode Alexey Gurevich Yan-Ni Shi Florian Grundmann Deepa Acharya Andrés Mauricio Caraballo-Rodríguez Amina Bouslimani Morgan Panitchpakdi Annabell Linck Changhui Guan Julia Oh Pieter C. Dorrestein Helge B. Bode Pavel A. Pevzner Hosein Mohimani
author_facet	Bahar Behsaz Edna Bode Alexey Gurevich Yan-Ni Shi Florian Grundmann Deepa Acharya Andrés Mauricio Caraballo-Rodríguez Amina Bouslimani Morgan Panitchpakdi Annabell Linck Changhui Guan Julia Oh Pieter C. Dorrestein Helge B. Bode Pavel A. Pevzner Hosein Mohimani
author_sort	Bahar Behsaz
title	Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery
title_short	Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery
title_full	Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery
title_fullStr	Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery
title_full_unstemmed	Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery
title_sort	integrating genomics and metabolomics for scalable non-ribosomal peptide discovery
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/56701c0cd5c2408cb5012222fe11866d
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Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery

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