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A mass spectrometry-guided genome mining approach for natural product peptidogenomics

Peptide natural products show broad biological properties and are commonly produced by orthogonal ribosomal and nonribosomal pathways in prokaryotes and eukaryotes. To harvest this large and diverse resource of bioactive molecules, we introduce here natural product peptidogenomics (NPP), a new MS-gu... Full description

Journal Title: Nature chemical biology 2011-10-09, Vol.7 (11), p.794-802
Main Author: Kersten, Roland D
Other Authors: Yang, Yu-Liang , Xu, Yuquan , Cimermancic, Peter , Nam, Sang-Jip , Fenical, William , Fischbach, Michael A , Moore, Bradley S , Dorrestein, Pieter C
Format: Electronic Article Electronic Article
Language: English
Subjects:
Quelle: Alma/SFX Local Collection
Publisher: United States: Nature Publishing Group
ID: ISSN: 1552-4450
Link: https://www.ncbi.nlm.nih.gov/pubmed/21983601
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recordid: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3258187
title: A mass spectrometry-guided genome mining approach for natural product peptidogenomics
format: Article
creator:
  • Kersten, Roland D
  • Yang, Yu-Liang
  • Xu, Yuquan
  • Cimermancic, Peter
  • Nam, Sang-Jip
  • Fenical, William
  • Fischbach, Michael A
  • Moore, Bradley S
  • Dorrestein, Pieter C
subjects:
  • Amino Acid Sequence
  • Article
  • Bacterial Proteins - chemistry
  • Bacterial Proteins - genetics
  • Bacterial Proteins - metabolism
  • Biological Products - chemistry
  • Biological Products - metabolism
  • formyl peptides
  • Gene clusters
  • Gene Expression Regulation, Bacterial - physiology
  • Genomes
  • Genomics
  • Genomics - methods
  • Genotype
  • lipopeptides
  • Mass Spectrometry - methods
  • Mining
  • Models
  • Molecular Structure
  • natural products
  • Peptides
  • Peptides - chemistry
  • Peptides - genetics
  • Peptides - metabolism
  • Prokaryotes
  • Streptomyces - genetics
  • Streptomyces - metabolism
  • Streptomycetes
ispartof: Nature chemical biology, 2011-10-09, Vol.7 (11), p.794-802
description: Peptide natural products show broad biological properties and are commonly produced by orthogonal ribosomal and nonribosomal pathways in prokaryotes and eukaryotes. To harvest this large and diverse resource of bioactive molecules, we introduce here natural product peptidogenomics (NPP), a new MS-guided genome-mining method that connects the chemotypes of peptide natural products to their biosynthetic gene clusters by iteratively matching de novo tandem MS (MS(n)) structures to genomics-based structures following biosynthetic logic. In this study, we show that NPP enabled the rapid characterization of over ten chemically diverse ribosomal and nonribosomal peptide natural products of previously unidentified composition from Streptomycete bacteria as a proof of concept to begin automating the genome-mining process. We show the identification of lantipeptides, lasso peptides, linardins, formylated peptides and lipopeptides, many of which are from well-characterized model Streptomycetes, highlighting the power of NPP in the discovery of new peptide natural products from even intensely studied organisms.
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 1552-4450
fulltext: fulltext
issn:
  • 1552-4450
  • 1552-4469
url: Link


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descriptionPeptide natural products show broad biological properties and are commonly produced by orthogonal ribosomal and nonribosomal pathways in prokaryotes and eukaryotes. To harvest this large and diverse resource of bioactive molecules, we introduce here natural product peptidogenomics (NPP), a new MS-guided genome-mining method that connects the chemotypes of peptide natural products to their biosynthetic gene clusters by iteratively matching de novo tandem MS (MS(n)) structures to genomics-based structures following biosynthetic logic. In this study, we show that NPP enabled the rapid characterization of over ten chemically diverse ribosomal and nonribosomal peptide natural products of previously unidentified composition from Streptomycete bacteria as a proof of concept to begin automating the genome-mining process. We show the identification of lantipeptides, lasso peptides, linardins, formylated peptides and lipopeptides, many of which are from well-characterized model Streptomycetes, highlighting the power of NPP in the discovery of new peptide natural products from even intensely studied organisms.
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subjectAmino Acid Sequence ; Article ; Bacterial Proteins - chemistry ; Bacterial Proteins - genetics ; Bacterial Proteins - metabolism ; Biological Products - chemistry ; Biological Products - metabolism ; formyl peptides ; Gene clusters ; Gene Expression Regulation, Bacterial - physiology ; Genomes ; Genomics ; Genomics - methods ; Genotype ; lipopeptides ; Mass Spectrometry - methods ; Mining ; Models ; Molecular Structure ; natural products ; Peptides ; Peptides - chemistry ; Peptides - genetics ; Peptides - metabolism ; Prokaryotes ; Streptomyces - genetics ; Streptomyces - metabolism ; Streptomycetes
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abstractPeptide natural products show broad biological properties and are commonly produced by orthogonal ribosomal and nonribosomal pathways in prokaryotes and eukaryotes. To harvest this large and diverse resource of bioactive molecules, we introduce here natural product peptidogenomics (NPP), a new MS-guided genome-mining method that connects the chemotypes of peptide natural products to their biosynthetic gene clusters by iteratively matching de novo tandem MS (MS(n)) structures to genomics-based structures following biosynthetic logic. In this study, we show that NPP enabled the rapid characterization of over ten chemically diverse ribosomal and nonribosomal peptide natural products of previously unidentified composition from Streptomycete bacteria as a proof of concept to begin automating the genome-mining process. We show the identification of lantipeptides, lasso peptides, linardins, formylated peptides and lipopeptides, many of which are from well-characterized model Streptomycetes, highlighting the power of NPP in the discovery of new peptide natural products from even intensely studied organisms.
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pmid21983601
doi10.1038/nchembio.684
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