Advertisement

Nonlocalized Searching of HCD Data for Fast and Sensitive Identification of ADP-Ribosylated Peptides

  • Thomas Colby
  • Juan José Bonfiglio
  • Ivan Matic
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1813)

Abstract

ADP-ribosylation is a technically challenging PTM which has just emerged into the field of PTM-specific proteomics. But this fragile modifier requires special treatment on both a data acquisition and data processing level: it is highly labile under higher-energy collisional dissociation (HCD), and the degree of lability can depend on the site it modifies. Its behavior thus violates some assumptions on which proteomics algorithms are based. Here we present nonlocalized ADPr searching: a simple principle for maximizing sensitivity toward ADP-ribosylation when searching conventional HCD data. By scoring the strong fragment ions generally observed in ADPr spectra rather than the weak and often absent localization-dependent ions, nonlocalized searches are more sensitive. They also run significantly faster, due to reduced search space, and require no assumptions about which amino acids can be modified. We illustrate implementation in three search systems: Morpheus, MaxQuant, and MASCOT, and we also present a means of rapidly finding and extracting ADP-ribosylated peptide spectra from large datasets for more focused searching. This approach both improves identification of ADP-ribosylated peptides and avoids mis-localization of the modification sites.

Key words

ADP-ribosylation Serine ADPr HCD fragmentation Localization Lability Nonlocalized 

Notes

Acknowledgments

This work was funded by the Deutsche Forschungsgemeinschaft (Cellular Stress Responses in Aging-Associated Diseases) (grant EXC 229 to I.M.) and the European Union’s Horizon 2020 research and innovation program (Marie Skłodowska-Curie grant agreement 657501 to J.J.B. and I.M.). Very special thanks to Craig Wenger for adding neutral loss searching features to the Morpheus system. Thanks as well to Dr. Ilian Atanassov for useful discussions.

References

  1. 1.
    Villén J, Beausoleil SA, Gygi SP (2009) Evaluation of the utility of neutral-loss-dependent MS3 strategies in large-scale phosphorylation analysis. Proteomics 8(21):4444–4452CrossRefGoogle Scholar
  2. 2.
    Martello R, Leutert M, Jungmichel S, Bilan V, Larsen SC, Young C, Hottiger MO, Nielsen ML (2016) Proteome-wide identification of the endogenous ADP-ribosylome of mammalian cells and tissue. Nat Commun 7:12917. https://doi.org/10.1038/ncomms12917 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Neuhauser N, Michalski A, Cox J, Mann M (2012) Expert system for computer-assisted annotation of MS/MS spectra. Mol Cell Proteomics 11(11):1500–1509CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Myers SA, Daou S, Affar EB, Burlingame AL (2013) Electron transfer dissociation (ETD): the mass spectrometric breakthrough essential for O-GlcNAc protein site assignments – a study of the O-GlcNAcylated protein host cell factor C1. Proteomics 13(6):982–991CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367–1372CrossRefGoogle Scholar
  6. 6.
    Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M (2011) Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res 10:1794–1805CrossRefPubMedGoogle Scholar
  7. 7.
    Wenger CD, Coon JJ (2013) A proteomics search algorithm specifically designed for high-resolution tandem mass spectra. J Proteome Res 12(3):1377–1386CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Leidecker O, Bonfiglio JJ, Colby T, Zhang Q, Atanassov I, Zaja R, Palazzo L, Stockum A, Ahel I, Matic I (2016) Serine is a new target residue for endogenous ADP-ribosylation on histones. Nat Chem Biol 12:998–1000. https://doi.org/10.1038/nchembio.2180 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Thomas Colby
    • 1
  • Juan José Bonfiglio
    • 1
  • Ivan Matic
    • 1
  1. 1.Max Planck Institute for Biology of AgeingCologneGermany

Personalised recommendations