Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery

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
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Science
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Acceso en línea:https://doaj.org/article/56701c0cd5c2408cb5012222fe11866d
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Sumario: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.

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