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Mapping Protein–Protein Interactions by Quantitative Proteomics

  • Joern Dengjel
  • Irina Kratchmarova
  • Blagoy Blagoev
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 658)

Abstract

Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein–protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used to characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions.

Key words

Protein complex protein interaction signaling mass spectrometry proteomics SILAC 

Notes

Acknowledgments

We thank all CEBI group members for helpful discussions and support. The research leading to these results has received funding from the European Commission’s 7th Framework Programme (grant agreement HEALTH-F4-2008-201648/PROSPECTS), the Danish Natural Science Research Council, the Danish Medical Research Council, and the Lundbeck Foundation. JD was supported by the European Molecular Biology Organization and by the Excellence Initiative of the German Federal and State Governments.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Joern Dengjel
    • 1
    • 2
  • Irina Kratchmarova
    • 1
  • Blagoy Blagoev
    • 1
  1. 1.Center for Experimental BioInformatics, Department of Biochemistry and Molecular BiologyUniversity of Southern DenmarkOdenseDenmark
  2. 2.Freiburg Institute for Advanced Studies and Zentrum für BiosystemanalyseUniversity of FreiburgFreiburgGermany

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