Skip to main content

Interrogation of In Vivo Protein–Protein Interactions Using Transgenic Mouse Models and Stable Isotope Labeling

  • Protocol
  • First Online:
  • 2863 Accesses

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1176))

Abstract

Methods in mass spectrometry have evolved in recent years, facilitating proteomic analyses that were previously beyond the limits of the technology. Transgenic mouse models, coupled with mass spectrometry proteomics, have served as valuable platform for elucidating the in vivo function of individual genes and proteins. Here we discuss the methods we have recently employed to characterize protein–protein interactions and posttranslational modifications in tagged knock-in mouse models. These methods can be broadly applied to other systems for various applications in both basic and translational science.

This is a preview of subscription content, log in via an institution.

Buying options

Protocol
USD   49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   119.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

References

  1. Dunham WH, Mullin M, Gingras AC (2012) Affinity-purification coupled to mass spectrometry: basic principles and strategies. Proteomics 12(10):1576–1590

    Article  CAS  PubMed  Google Scholar 

  2. Schnutgen F et al (2011) Resources for proteomics in mouse embryonic stem cells. Nat Methods 8(2):103–104

    Article  PubMed  Google Scholar 

  3. Cui X et al (2011) Targeted integration in rat and mouse embryos with zinc-finger nucleases. Nat Biotechnol 29(1):64–67

    Article  CAS  PubMed  Google Scholar 

  4. Hockemeyer D et al (2011) Genetic engineering of human pluripotent cells using TALE nucleases. Nat Biotechnol 29(8):731–734

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Jinek M et al (2013) RNA-programmed genome editing in human cells. eLife 2:e00471

    Article  PubMed Central  PubMed  Google Scholar 

  6. Mali P et al (2013) RNA-guided human genome engineering via Cas9. Science 339(6121):823–826

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  7. Wang H et al (2013) One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell 153(4):910–918

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  8. Bantscheff M, Lemeer S, Savitski MM, Kuster B (2012) Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present. Anal Bioanal Chem 404(4):939–965

    Article  CAS  PubMed  Google Scholar 

  9. Wu CC, MacCoss MJ, Howell KE, Matthews DE, Yates JR III (2004) Metabolic labeling of mammalian organisms with stable isotopes for quantitative proteomic analysis. Anal Chem 76(17):4951–4959

    Article  CAS  PubMed  Google Scholar 

  10. Kruger M et al (2008) SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function. Cell 134(2):353–364

    Article  PubMed  Google Scholar 

  11. Rauniyar N, McClatchy DB, Yates JR III (2013) Stable isotope labeling of mammals (SILAM) for in vivo quantitative proteomic analysis. Methods 61(3):260–268

    Article  CAS  PubMed  Google Scholar 

  12. Krijgsveld J et al (2003) Metabolic labeling of C. elegans and D. melanogaster for quantitative proteomics. Nat Biotechnol 21(8):927–931

    Article  CAS  PubMed  Google Scholar 

  13. Savas JN, Toyama BH, Xu T, Yates JR III, Hetzer MW (2012) Extremely long-lived nuclear pore proteins in the rat brain. Science 335(6071):942

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  14. Huttlin EL et al (2009) Discovery and validation of colonic tumor-associated proteins via metabolic labeling and stable isotopic dilution. Proc Natl Acad Sci U S A 106(40):17235–17240

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  15. Bateman RJ et al (2006) Human amyloid-beta synthesis and clearance rates as measured in cerebrospinal fluid in vivo. Nat Med 12(7):856–861

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  16. Mawuenyega KG et al (2010) Decreased clearance of CNS beta-amyloid in Alzheimer’s disease. Science 330(6012):1774

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Ong SE 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):376–386

    Article  CAS  PubMed  Google Scholar 

  18. Wang X, Huang L (2008) Identifying dynamic interactors of protein complexes by quantitative mass spectrometry. Mol Cell Proteomics 7(1):46–57

    Article  PubMed  Google Scholar 

  19. Rao A, Richards TL, Simmons D, Zahniser NR, Sorkin A (2012) Epitope-tagged dopamine transporter knock-in mice reveal rapid endocytic trafficking and filopodia targeting of the transporter in dopaminergic axons. FASEB J 26(5):1921–1933

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  20. Dey A et al (2012) Loss of the tumor suppressor BAP1 causes myeloid transformation. Science 337(6101):1541–1546

    Article  CAS  PubMed  Google Scholar 

  21. Zanivan S, Krueger M, Mann M (2012) In vivo quantitative proteomics: the SILAC mouse. Methods Mol Biol 757:435–450

    Article  PubMed  Google Scholar 

  22. Phu L et al (2011) Improved quantitative mass spectrometry methods for characterizing complex ubiquitin signals. Mol Cell Proteomics 10(5):M110 003756

    Article  PubMed Central  PubMed  Google Scholar 

  23. Sheng Z et al (2012) Ser1292 autophosphorylation is an indicator of LRRK2 kinase activity and contributes to the cellular effects of PD mutations. Sci Transl Med 4(164):164ra161

    Article  PubMed  Google Scholar 

  24. Haas W et al (2006) Optimization and use of peptide mass measurement accuracy in shotgun proteomics. Mol Cell Proteomics 5(7):1326–1337

    Article  CAS  PubMed  Google Scholar 

  25. Perkins DN, Pappin DJ, Creasy DM, Cottrell JS (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20(18):3551–3567

    Article  CAS  PubMed  Google Scholar 

  26. Bakalarski CE et al (2008) The impact of peptide abundance and dynamic range on stable-isotope-based quantitative proteomic analyses. J Proteome Res 7(11):4756–4765

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  27. Huttlin EL, Hegeman AD, Harms AC, Sussman MR (2007) Comparison of full versus partial metabolic labeling for quantitative proteomics analysis in Arabidopsis thaliana. Mol Cell Proteomics 6(5):860–881

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the following collaborators for applications of the in vivo proteomics technology and for helpful discussions and assistance at various stages of the project: Lilian Phu, Daisy Bustos, Corey Bakalarski, Haitao Zhu, Kim Newton, and Vishva Dixit.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anwesha Dey .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this protocol

Cite this protocol

Dey, A., Wu, J., Kirkpatrick, D.S. (2014). Interrogation of In Vivo Protein–Protein Interactions Using Transgenic Mouse Models and Stable Isotope Labeling. In: Wajapeyee, N. (eds) Cancer Genomics and Proteomics. Methods in Molecular Biology, vol 1176. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0992-6_15

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-0992-6_15

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0991-9

  • Online ISBN: 978-1-4939-0992-6

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics