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

Nature Chemical Biology volume 7, pages 794–802 (2011)Cite this article

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Abstract

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 (MSn) 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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Figure 1
Figure 2: General workflow of natural product peptidogenomics.
Figure 3: Peptidogenomic connection of a RNP chemotype with its biosynthetic genes in the characterization of the class III lantipeptide AmfS from S. griseus IFO 13350.
Figure 4: Peptidogenomic connection of a NRP chemotype with its biosynthetic genes in the characterization of the lipopeptide stendomycin complex from S. hygroscopicus ATCC 53653.

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Acknowledgements

We thank N. Castellana and V. Bafna for providing the algorithm to enable the six-frame translations of supercontigs. We also thank M. Meehan for FTMS training. Financial support was provided by the US National Institutes of Health (GM085770 to B.S.M. and GM086283 to P.C.D.) and the Beckman Foundation.

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Authors and Affiliations

  1. Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California at San Diego, La Jolla, California, USA

    Roland D Kersten, Sang-Jip Nam, William Fenical, Bradley S Moore & Pieter C Dorrestein

  2. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California at San Diego, La Jolla, California, USA

    Yu-Liang Yang, Yuquan Xu, William Fenical, Bradley S Moore & Pieter C Dorrestein

  3. Department of Bioengineering and Therapeutic Sciences and California Institute of Quantitative Biosciences, University of California, San Francisco, California, USA

    Peter Cimermancic & Michael A Fischbach

  4. Department of Pharmacology and Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, California, USA

    Pieter C Dorrestein

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Contributions

R.D.K. designed and carried out experiments, analyzed data and wrote the paper. Y.-L.Y., Y.X. and S.-J.N. carried out experiments and analyzed data. P.C. and M.A.F. carried out the bioinformatic analysis and analyzed data. W.F. analyzed data. B.S.M. and P.C.D. designed experiments, analyzed data and wrote the paper.

Corresponding authors

Correspondence to Bradley S Moore or Pieter C Dorrestein.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Methods, Supplementary Results, Supplementary Tables 1–13 and Supplementary Figures 1–17 (PDF 7941 kb)

Supplementary Table 6

Mass shifts of RNP monomers and modifications and their corresponding precursor amino acids in precursor peptides (XLS 38 kb)

Supplementary Table 7

Mass shifts of NRP monomers (NORINE monomer list excluding lipids) and corresponding NRPS monomers and genome mining accessibility by NRPSpredictor2 (AntiSMASH, * - biosynthetic monomers can be putative due to lack of biosynthetic knowledge) (XLS 75 kb)

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Kersten, R., Yang, YL., Xu, Y. et al. A mass spectrometry–guided genome mining approach for natural product peptidogenomics. Nat Chem Biol 7, 794–802 (2011). https://doi.org/10.1038/nchembio.684

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