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Dereplication of peptidic natural products through database search of mass spectra

Nature Chemical Biology volume 13, pages 30–37 (2017)Cite this article

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Abstract

Peptidic natural products (PNPs) are widely used compounds that include many antibiotics and a variety of other bioactive peptides. Although recent breakthroughs in PNP discovery raised the challenge of developing new algorithms for their analysis, identification of PNPs via database search of tandem mass spectra remains an open problem. To address this problem, natural product researchers use dereplication strategies that identify known PNPs and lead to the discovery of new ones, even in cases when the reference spectra are not present in existing spectral libraries. DEREPLICATOR is a new dereplication algorithm that enables high-throughput PNP identification and that is compatible with large-scale mass-spectrometry-based screening platforms for natural product discovery. After searching nearly one hundred million tandem mass spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure, DEREPLICATOR identified an order of magnitude more PNPs (and their new variants) than any previous dereplication efforts.

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Figure 1: DEREPLICATOR pipeline.
Figure 2: Number of PSMs and peptides identified by DEREPLICATOR.
Figure 3: Number of peptides identified by DEREPLICATOR in SpectraHigh data set.
Figure 4: Spectral networks illustrating the results of the SILAC experiment.
Figure 5: Generating theoretical spectra and computing P values of PSMs formed by PNPs with various architectures.

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Acknowledgements

We thank M. Wang and N. Bandeira for insightful suggestions on using molecular networking and spectral library search, and M. Medema for guidelines on running antiSMASH. The work of H.M., P.D. and P.A.P. was supported by the US National Institutes of Health (grant 2-P41-GM103484). P.D. is supported by GM097509. A.G., A.M. and P.A.P. were supported by Russian Science Foundation (grant 14-50-00069).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California, USA

    Hosein Mohimani & Pavel A Pevzner

  2. Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia

    Alexey Gurevich, Alla Mikheenko & Pavel A Pevzner

  3. Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA

    Neha Garg, Louis-Felix Nothias & Pieter C Dorrestein

  4. Laboratory of Aquatic Natural Products Chemistry, School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan

    Akihiro Ninomiya & Kentaro Takada

  5. Department of Pharmacology, University of California, San Diego, La Jolla, California, USA

    Pieter C Dorrestein

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Contributions

H.M. and A.G. implemented DEREPLICATOR algorithm. H.M., A.G. and A.M. designed the webserver. N.G. and L.-F.N. collected and analyzed mass spectrometry data and conducted SILAC experiments. A.N. and K.T. purified standard surugamide. P.C.D. and P.A.P. designed and directed the work. H.M. and P.A.P. wrote the manuscript.

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Correspondence to Pavel A Pevzner.

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Competing interests

P.A.P. has an equity interest in Digital Proteomics, LLC, a company that may potentially benefit from the research results. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies.

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Supplementary Results, Supplementary Tables 1–7, Supplementary Figures 1–12 and Supplementary Note. (PDF 4114 kb)

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Mohimani, H., Gurevich, A., Mikheenko, A. et al. Dereplication of peptidic natural products through database search of mass spectra. Nat Chem Biol 13, 30–37 (2017). https://doi.org/10.1038/nchembio.2219

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