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Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery.

  • Author(s): Behsaz, Bahar;
  • Bode, Edna;
  • Gurevich, Alexey;
  • Shi, Yan-Ni;
  • Grundmann, Florian;
  • Acharya, Deepa;
  • Caraballo-Rodríguez, Andrés Mauricio;
  • Bouslimani, Amina;
  • Panitchpakdi, Morgan;
  • Linck, Annabell;
  • Guan, Changhui;
  • Oh, Julia;
  • Dorrestein, Pieter C;
  • Bode, Helge B;
  • Pevzner, Pavel A;
  • Mohimani, Hosein
  • et al.
Abstract

Non-Ribosomal Peptides (NRPs) represent a biomedically important class of natural products that include a multitude of antibiotics and other clinically used drugs. NRPs are not directly encoded in the genome but are instead produced by metabolic pathways encoded by biosynthetic gene clusters (BGCs). Since the existing genome mining tools predict many putative NRPs synthesized by a given BGC, it remains unclear which of these putative NRPs are correct and how to identify post-assembly modifications of amino acids in these NRPs in a blind mode, without knowing which modifications exist in the sample. To address this challenge, here we report NRPminer, a modification-tolerant tool for NRP discovery from large (meta)genomic and mass spectrometry datasets. We show that NRPminer is able to identify many NRPs from different environments, including four previously unreported NRP families from soil-associated microbes and NRPs from human microbiota. Furthermore, in this work we demonstrate the anti-parasitic activities and the structure of two of these NRP families using direct bioactivity screening and nuclear magnetic resonance spectrometry, illustrating the power of NRPminer for discovering bioactive NRPs.

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