Considerations for Identifying Endogenous Protein Complexes from Tissue via Immunoaffinity Purification and Quantitative Mass Spectrometry

  • Joel D. Federspiel
  • Ileana M. CristeaEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1977)


Protein complexes perform key roles in nearly all aspects of biology. Identification of the composition of these complexes offers insights into how different cellular processes are carried out. The use of affinity purification coupled to mass spectrometry has become a method of choice for identifying protein-protein interactions, but has been most frequently applied to cell model systems using tagged and overexpressed bait proteins. Although valuable, this approach can create several potential artifacts due to the presence of a tag on a protein and the higher abundance of the protein of interest (bait). The isolation of endogenous proteins using antibodies raised against the proteins of interest instead of an epitope tag offers a means to examine protein interactions in any cellular or animal model system and without the caveats of overexpressed, tagged proteins. Although conceptually simple, the limited use of this approach has been primarily driven by challenges associated with finding adequate antibodies and experimental conditions for effective isolations. In this chapter, we present a protocol for the optimization of lysis conditions, antibody evaluation, affinity purification, and ultimately identification of protein complexes from endogenous immunoaffinity purifications using quantitative mass spectrometry. We also highlight the increased use of targeted mass spectrometry analyses, such as parallel reaction monitoring (PRM) for orthogonal validation of protein isolation and interactions initially identified via data-dependent mass spectrometry analyses.

Key words

Immunoaffinity purification Protein-protein interactions Mass spectrometry Tissue Quantitative MS PRM Parallel reaction monitoring IP-MS 



We are grateful for funding from the CHDI foundation and from the NIH (GM114141 and HL126509). We thank Todd M. Greco and Elizabeth A. Rowland for helpful comments in the preparation of this manuscript.


  1. 1.
    Joshi P, Greco TM, Guise AJ et al (2013) The functional interactome landscape of the human histone deacetylase family. Mol Syst Biol 9:672CrossRefGoogle Scholar
  2. 2.
    Budayeva HG, Cristea IM (2016) Human Sirtuin 2 localization, transient interactions, and impact on the proteome point to its role in intracellular trafficking. Mol Cell Proteomics 15(10):3107–3125CrossRefGoogle Scholar
  3. 3.
    Diner BA, Li T, Greco TM et al (2015) The functional interactome of PYHIN immune regulators reveals IFIX is a sensor of viral DNA. Mol Syst Biol 11(1):787CrossRefGoogle Scholar
  4. 4.
    Kohli P, Bartram MP, Habbig S et al (2014) Label-free quantitative proteomic analysis of the YAP/TAZ interactome. Am J Physiol Cell Physiol 306(9):C805–C818CrossRefGoogle Scholar
  5. 5.
    Huttlin EL, Ting L, Bruckner RJ et al (2015) The BioPlex network: a systematic exploration of the human interactome. Cell 162(2):425–440CrossRefGoogle Scholar
  6. 6.
    Hubner NC, Bird AW, Cox J et al (2010) Quantitative proteomics combined with BAC TransgeneOmics reveals in vivo protein interactions. J Cell Biol 189(4):739–754CrossRefGoogle Scholar
  7. 7.
    Li X, Tran KM, Aziz KE et al (2016) Defining the protein-protein interaction network of the human protein tyrosine phosphatase family. Mol Cell Proteomics 15(9):3030–3044CrossRefGoogle Scholar
  8. 8.
    Scifo E, Szwajda A, Soliymani R et al (2015) Quantitative analysis of PPT1 interactome in human neuroblastoma cells. Data Brief 4:207–216CrossRefGoogle Scholar
  9. 9.
    Yadav L, Tamene F, Goos H et al (2017) Systematic analysis of human protein phosphatase interactions and dynamics. Cell Syst 4(4):430–444 e5CrossRefGoogle Scholar
  10. 10.
    Oda Y, Huang K, Cross FR et al (1999) Accurate quantitation of protein expression and site-specific phosphorylation. Proc Natl Acad Sci U S A 96(12):6591–6596CrossRefGoogle Scholar
  11. 11.
    Ong SE, Blagoev B, Kratchmarova I et al (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1(5):376–386CrossRefGoogle Scholar
  12. 12.
    Tackett AJ, DeGrasse JA, Sekedat MD et al (2005) I-DIRT, a general method for distinguishing between specific and nonspecific protein interactions. J Proteome Res 4(5):1752–1756CrossRefGoogle Scholar
  13. 13.
    Wang X, Huang L (2008) Identifying dynamic interactors of protein complexes by quantitative mass spectrometry. Mol Cell Proteomics 7(1):46–57CrossRefGoogle Scholar
  14. 14.
    Greco TM, Guise AJ, Cristea IM (2016) Determining the composition and stability of protein complexes using an integrated label-free and stable isotope labeling strategy. Methods Mol Biol 1410:39–63CrossRefGoogle Scholar
  15. 15.
    Wang X, Huang L (2014) Defining dynamic protein interactions using SILAC-based quantitative mass spectrometry. Methods Mol Biol 1188:191–205CrossRefGoogle Scholar
  16. 16.
    Federspiel JD, Codreanu SG, Palubinsky AM et al (2016) Assembly dynamics and stoichiometry of the apoptosis signal-regulating kinase (ASK) signalosome in response to electrophile stress. Mol Cell Proteomics 15(6):1947–1961CrossRefGoogle Scholar
  17. 17.
    Toyama BH, Savas JN, Park SK et al (2013) Identification of long-lived proteins reveals exceptional stability of essential cellular structures. Cell 154(5):971–982CrossRefGoogle Scholar
  18. 18.
    Zanivan S, Krueger M, Mann M (2012) In vivo quantitative proteomics: the SILAC mouse. Methods Mol Biol 757:435–450CrossRefGoogle Scholar
  19. 19.
    Kennedy L, Kaltenbrun E, Greco TM et al (2017) Formation of a TBX20-CASZ1 protein complex is protective against dilated cardiomyopathy and critical for cardiac homeostasis. PLoS Genet 13(9):e1007011CrossRefGoogle Scholar
  20. 20.
    Crow MS, Cristea IM (2017) Human antiviral protein IFIX suppresses viral gene expression during herpes simplex virus 1 (HSV-1) infection and is counteracted by virus-induced proteasomal degradation. Mol Cell Proteomics 16(4 suppl 1):S200–s214CrossRefGoogle Scholar
  21. 21.
    Diner BA, Lum KK, Toettcher JE et al (2016) Viral DNA sensors IFI16 and cyclic GMP-AMP synthase possess distinct functions in regulating viral gene expression, immune defenses, and apoptotic responses during Herpesvirus infection. MBio 7(6):e01553-16CrossRefGoogle Scholar
  22. 22.
    Jager S, Cimermancic P, Gulbahce N et al (2011) Global landscape of HIV-human protein complexes. Nature 481(7381):365–370CrossRefGoogle Scholar
  23. 23.
    Goldfarb D, Hast BE, Wang W et al (2014) Spotlite: web application and augmented algorithms for predicting co-complexed proteins from affinity purification—mass spectrometry data. J Proteome Res 13(12):5944–5955CrossRefGoogle Scholar
  24. 24.
    Choi H, Larsen B, Lin ZY et al (2011) SAINT: probabilistic scoring of affinity purification—mass spectrometry data. Nat Methods 8(1):70–73CrossRefGoogle Scholar
  25. 25.
    Mellacheruvu D, Wright Z, Couzens AL et al (2013) The CRAPome: a contaminant repository for affinity purification-mass spectrometry data. Nat Methods 10(8):730–736CrossRefGoogle Scholar
  26. 26.
    Sowa ME, Bennett EJ, Gygi SP et al (2009) Defining the human deubiquitinating enzyme interaction landscape. Cell 138(2):389–403CrossRefGoogle Scholar
  27. 27.
    Armean IM, Lilley KS, Trotter MW (2013) Popular computational methods to assess multiprotein complexes derived from label-free affinity purification and mass spectrometry (AP-MS) experiments. Mol Cell Proteomics 12(1):1–13CrossRefGoogle Scholar
  28. 28.
    Teo G, Liu G, Zhang J et al (2014) SAINTexpress: improvements and additional features in Significance Analysis of INTeractome software. J Proteome 100:37–43CrossRefGoogle Scholar
  29. 29.
    MacLean B, Tomazela DM, Shulman N et al (2010) Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26(7):966–968CrossRefGoogle Scholar
  30. 30.
    Cristea IM, Williams R, Chait BT et al (2005) Fluorescent proteins as proteomic probes. Mol Cell Proteomics 4(12):1933–1941CrossRefGoogle Scholar
  31. 31.
    Conlon FL, Miteva Y, Kaltenbrun E et al (2012) Immunoisolation of protein complexes from Xenopus. Methods Mol Biol 917:369–390CrossRefGoogle Scholar
  32. 32.
    Wessel D, Flugge UI (1984) A method for the quantitative recovery of protein in dilute solution in the presence of detergents and lipids. Anal Biochem 138(1):141–143CrossRefGoogle Scholar
  33. 33.
    Ishihama Y, Rappsilber J, Mann M (2006) Modular stop and go extraction tips with stacked disks for parallel and multidimensional peptide fractionation in proteomics. J Proteome Res 5(4):988–994CrossRefGoogle Scholar
  34. 34.
    Li T, Chen J, Cristea IM (2013) Human cytomegalovirus tegument protein pUL83 inhibits IFI16-mediated DNA sensing for immune evasion. Cell Host Microbe 14(5):591–599CrossRefGoogle Scholar
  35. 35.
    Alm T, von Feilitzen K, Lundberg E et al (2014) A chromosome-centric analysis of antibodies directed toward the human proteome using Antibodypedia. J Proteome Res 13(3):1669–1676CrossRefGoogle Scholar
  36. 36.
    Persson H, Preger C, Marcon E et al (2017) Antibody validation by immunoprecipitation followed by mass spectrometry analysis. Methods Mol Biol 1575:175–187CrossRefGoogle Scholar
  37. 37.
    Uhlen M, Bandrowski A, Carr S et al (2016) A proposal for validation of antibodies. Nat Methods 13(10):823–827CrossRefGoogle Scholar
  38. 38.
    Mali S, Moree WJ, Mitchell M et al (2016) Observations on different resin strategies for affinity purification mass spectrometry of a tagged protein. Anal Biochem 515:26–32CrossRefGoogle Scholar
  39. 39.
    Shannon P, Markiel A, Ozier O et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504CrossRefGoogle Scholar
  40. 40.
    Cline MS, Smoot M, Cerami E et al (2007) Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2(10):2366–2382CrossRefGoogle Scholar
  41. 41.
    Diner BA, Lum KK, Javitt A et al (2015) Interactions of the antiviral factor interferon gamma-inducible protein 16 (IFI16) mediate immune signaling and herpes simplex virus-1 immunosuppression. Mol Cell Proteomics 14(9):2341–2356CrossRefGoogle Scholar
  42. 42.
    Huttlin EL, Bruckner RJ, Paulo JA et al (2017) Architecture of the human interactome defines protein communities and disease networks. Nature 545(7655):505–509CrossRefGoogle Scholar
  43. 43.
    Couzens AL, Knight JD, Kean MJ et al (2013) Protein interaction network of the mammalian Hippo pathway reveals mechanisms of kinase-phosphatase interactions. Sci Signal 6(302):rs15CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Molecular BiologyPrinceton UniversityPrincetonUSA

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