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The mammalian-membrane two-hybrid assay (MaMTH) for probing membrane-protein interactions in human cells

Nature Methods volume 11, pages 585–592 (2014)Cite this article

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Abstract

Cell signaling, one of key processes in both normal cellular function and disease, is coordinated by numerous interactions between membrane proteins that change in response to stimuli. We present a split ubiquitin–based method for detection of integral membrane protein-protein interactions (PPIs) in human cells, termed mammalian-membrane two-hybrid assay (MaMTH). We show that this technology detects stimulus (hormone or agonist)-dependent and phosphorylation-dependent PPIs. MaMTH can detect changes in PPIs conferred by mutations such as those in oncogenic ErbB receptor variants or by treatment with drugs such as the tyrosine kinase inhibitor erlotinib. Using MaMTH as a screening assay, we identified CRKII as an interactor of oncogenic EGFR(L858R) and showed that CRKII promotes persistent activation of aberrant signaling in non–small cell lung cancer cells. MaMTH is a powerful tool for investigating the dynamic interactomes of human integral membrane proteins.

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Figure 1: The MaMTH system.
Figure 2: Use of MaMTH to monitor agonist-dependent interactions of a GPCR.
Figure 3: MaMTH allows detection of PPIs in ErbB family members.
Figure 4: Monitoring phosphorylation-dependent interactions of oncogenic ErbB receptors.
Figure 5: Confirmation of MaMTH interactors and involvement of CRKII in bypassing erlotinib-mediated toxicity in NSCLC cells.

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References

  1. Stevens, T.J. & Arkin, I.T. Do more complex organisms have a greater proportion of membrane proteins in their genomes? Proteins 39, 417–420 (2000).

    Article  CAS  Google Scholar 

  2. Jones, R.B., Gordus, A., Krall, J.A. & MacBeath, G. A quantitative protein interaction network for the ErbB receptors using protein microarrays. Nature 439, 168–174 (2006).

    Article  CAS  Google Scholar 

  3. Schulze, W.X., Deng, L. & Mann, M. Phosphotyrosine interactome of the ErbB-receptor kinase family. Mol. Syst. Biol. 1, 2005.0008 (2005).

    Article  Google Scholar 

  4. Lievens, S., Lemmens, I. & Tavernier, J. Mammalian two-hybrids come of age. Trends Biochem. Sci. 34, 579–588 (2009).

    Article  CAS  Google Scholar 

  5. Michnick, S.W., Ear, P.H., Manderson, E.N., Remy, I. & Stefan, E. Universal strategies in research and drug discovery based on protein-fragment complementation assays. Nat. Rev. Drug Discov. 6, 569–582 (2007).

    Article  CAS  Google Scholar 

  6. Rojo-Niersbach, E., Morley, D., Heck, S. & Lehming, N. A new method for the selection of protein interactions in mammalian cells. Biochem. J. 348, 585–590 (2000).

    Article  CAS  Google Scholar 

  7. Kerppola, T.K. Visualization of molecular interactions by fluorescence complementation. Nat. Rev. Mol. Cell Biol. 7, 449–456 (2006).

    Article  CAS  Google Scholar 

  8. Stefan, E. et al. Quantification of dynamic protein complexes using Renilla luciferase fragment complementation applied to protein kinase A activities in vivo. Proc. Natl. Acad. Sci. USA 104, 16916–16921 (2007).

    Article  CAS  Google Scholar 

  9. Wehrman, T.S. et al. A system for quantifying dynamic protein interactions defines a role for Herceptin in modulating ErbB2 interactions. Proc. Natl. Acad. Sci. USA 103, 19063–19068 (2006).

    Article  CAS  Google Scholar 

  10. Wehr, M.C. et al. Monitoring regulated protein-protein interactions using split TEV. Nat. Methods 3, 985–993 (2006).

    Article  CAS  Google Scholar 

  11. Ciruela, F. Fluorescence-based methods in the study of protein-protein interactions in living cells. Curr. Opin. Biotechnol. 19, 338–343 (2008).

    Article  CAS  Google Scholar 

  12. Johnsson, N. & Varshavsky, A. Split ubiquitin as a sensor of protein interactions in vivo. Proc. Natl. Acad. Sci. USA 91, 10340–10344 (1994).

    Article  CAS  Google Scholar 

  13. Stagljar, I., Korostensky, C., Johnsson, N. & te Heesen, S. A genetic system based on split-ubiquitin for the analysis of interactions between membrane proteins in vivo. Proc. Natl. Acad. Sci. USA 95, 5187–5192 (1998).

    Article  CAS  Google Scholar 

  14. Paumi, C.M. et al. Mapping protein-protein interactions for the yeast ABC transporter Ycf1p by integrated split-ubiquitin membrane yeast two-hybrid analysis. Mol. Cell 26, 15–25 (2007).

    Article  CAS  Google Scholar 

  15. Snider, J. et al. Mapping the functional yeast ABC transporter interactome. Nat. Chem. Biol. 9, 565–572 (2013).

    Article  CAS  Google Scholar 

  16. Emami, K.H. & Carey, M. A synergistic increase in potency of a multimerized VP16 transcriptional activation domain. EMBO J. 11, 5005–5012 (1992).

    Article  CAS  Google Scholar 

  17. Sadowski, I., Ma, J., Triezenberg, S. & Ptashne, M. GAL4–VP16 is an unusually potent transcriptional activator. Nature 335, 563–564 (1988).

    Article  CAS  Google Scholar 

  18. Schmitz, M.L. & Baeuerle, P.A. The p65 subunit is responsible for the strong transcription activating potential of NF-kappa B. EMBO J. 10, 3805–3817 (1991).

    Article  CAS  Google Scholar 

  19. Remy, I. & Michnick, S.W. Application of protein-fragment complementation assays in cell biology. Biotechniques 42, 137–141 (2007).

    Article  CAS  Google Scholar 

  20. Johnsson, N. & Varshavsky, A. Ubiquitin-assisted dissection of protein transport across membranes. EMBO J. 13, 2686–2698 (1994).

    Article  CAS  Google Scholar 

  21. Rhee, Y., Gurel, F., Gafni, Y., Dingwall, C. & Citovsky, V. A genetic system for detection of protein nuclear import and export. Nat. Biotechnol. 18, 433–437 (2000).

    Article  CAS  Google Scholar 

  22. Deribe, Y.L. et al. Regulation of epidermal growth factor receptor trafficking by lysine deacetylase HDAC6. Sci. Signal. 2, ra84 (2009).

    PubMed  Google Scholar 

  23. Moore, C.A., Milano, S.K. & Benovic, J.L. Regulation of receptor trafficking by GRKs and arrestins. Annu. Rev. Physiol. 69, 451–482 (2007).

    Article  CAS  Google Scholar 

  24. DeWire, S.M., Ahn, S., Lefkowitz, R.J. & Shenoy, S.K. Beta-arrestins and cell signaling. Annu. Rev. Physiol. 69, 483–510 (2007).

    Article  CAS  Google Scholar 

  25. Yarden, Y. & Sliwkowski, M.X. Untangling the ErbB signalling network. Nat. Rev. Mol. Cell Biol. 2, 127–137 (2001).

    CAS  PubMed  Google Scholar 

  26. Prickett, T.D. et al. Analysis of the tyrosine kinome in melanoma reveals recurrent mutations in ERBB4. Nat. Genet. 41, 1127–1132 (2009).

    Article  CAS  Google Scholar 

  27. da Cunha Santos, G., Shepherd, F.A. & Tsao, M.S. EGFR mutations and lung cancer. Annu. Rev. Pathol. 6, 49–69 (2011).

    Article  Google Scholar 

  28. Pines, G., Kostler, W.J. & Yarden, Y. Oncogenic mutant forms of EGFR: lessons in signal transduction and targets for cancer therapy. FEBS Lett. 584, 2699–2706 (2010).

    Article  CAS  Google Scholar 

  29. Carey, K.D. et al. Kinetic analysis of epidermal growth factor receptor somatic mutant proteins shows increased sensitivity to the epidermal growth factor receptor tyrosine kinase inhibitor, erlotinib. Cancer Res. 66, 8163–8171 (2006).

    Article  CAS  Google Scholar 

  30. Shortt, J. & Johnstone, R.W. Oncogenes in cell survival and cell death. Cold Spring Harb. Perspect. Biol. 4, a009829 (2012).

    Article  Google Scholar 

  31. Ahn, R. et al. The ShcA PTB domain functions as a biological sensor of phosphotyrosine signaling during breast cancer progression. Cancer Res. 73, 4521–4532 (2013).

    Article  CAS  Google Scholar 

  32. Bisson, N. et al. Selected reaction monitoring mass spectrometry reveals the dynamics of signaling through the GRB2 adaptor. Nat. Biotechnol. 29, 653–658 (2011).

    Article  CAS  Google Scholar 

  33. Barrios-Rodiles, M. et al. High-throughput mapping of a dynamic signaling network in mammalian cells. Science 307, 1621–1625 (2005).

    Article  CAS  Google Scholar 

  34. Taipale, M. et al. Quantitative analysis of HSP90-client interactions reveals principles of substrate recognition. Cell 150, 987–1001 (2012).

    Article  CAS  Google Scholar 

  35. Blakely, K., Ketela, T. & Moffat, J. Pooled lentiviral shRNA screening for functional genomics in mammalian cells. Methods Mol. Biol. 781, 161–182 (2011).

    Article  CAS  Google Scholar 

  36. Sriram, G. & Birge, R.B. Emerging roles for crk in human cancer. Genes Cancer 1, 1132–1139 (2010).

    Article  CAS  Google Scholar 

  37. Cheung, H.W. et al. Amplification of CRKL induces transformation and epidermal growth factor receptor inhibitor resistance in human non-small cell lung cancers. Cancer Discov. 1, 608–625 (2011).

    Article  CAS  Google Scholar 

  38. Kosaka, T., Yamaki, E., Mogi, A. & Kuwano, H. Mechanisms of resistance to EGFR TKIs and development of a new generation of drugs in non-small-cell lung cancer. J. Biomed. Biotechnol. 2011, 165214 (2011).

    Article  Google Scholar 

  39. Li, J. et al. Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms. Mol. Syst. Biol. 9, 705 (2013).

    Article  CAS  Google Scholar 

  40. Yang, X. et al. A public genome-scale lentiviral expression library of human ORFs. Nat. Methods 8, 659–661 (2011).

    Article  CAS  Google Scholar 

  41. Lemercier, C. et al. mHDA1/HDAC5 histone deacetylase interacts with and represses MEF2A transcriptional activity. J. Biol. Chem. 275, 15594–15599 (2000).

    Article  CAS  Google Scholar 

  42. Kurat, C.F. et al. Restriction of histone gene transcription to S phase by phosphorylation of a chromatin boundary protein. Genes Dev. 25, 2489–2501 (2011).

    Article  CAS  Google Scholar 

  43. Brown, K.R. & Jurisica, I. Unequal evolutionary conservation of human protein interactions in interologous networks. Genome Biol. 8, R95 (2007).

    Article  Google Scholar 

  44. Zhu, C.Q. et al. Understanding prognostic gene expression signatures in lung cancer. Clin. Lung Cancer 10, 331–340 (2009).

    Article  CAS  Google Scholar 

  45. Marcotte, R. et al. Essential gene profiles in breast, pancreatic, and ovarian cancer cells. Cancer Discov 2, 172–189 (2012).

    Article  CAS  Google Scholar 

  46. Pinheiro, J.C. & Bates, D.M. Mixed-effects models in S and S-PLUS (Springer, 2000).

  47. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).

    Google Scholar 

  48. Chung, Y., Rabe-Hesketh, S., Dorie, V., Gelman, A. & Liu, J. A nondegenerate penalized likelihood estimator for variance parameters in multilevel models. Psychometrika 78, 685–709 (2013).

    Article  Google Scholar 

  49. Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank B. Andrews for providing access to equipment and C. Nislow (University of British Columbia) for providing cDNA clones, J. Moffat (University of Toronto) for providing lentiviral plasmids, M.-S. Tsao (Princess Margaret Cancer Centre) for providing erlotinib and B. Neel (Princess Margaret Cancer Centre) for providing imatinib; S. Angers, K. Blakely, J. Jin, S. Kittanakom, A. Arnoldo, M. Mendoza and Y. Fedyshyn for experimental assistance and advice; and U. Petrovic, M. Ali, M. Lam, Z. Yao, K. Sokolina for advice and/or critical review of the manuscript. This work was supported by grants from the Ontario Genomics Institute (303547), Canadian Institutes of Health Research (Catalyst-NHG94491, PPP-125785), Canadian Foundation for Innovation (IOF-LOF), Natural Sciences and Engineering Research Council of Canada (RGPIN 372393-12), Canadian Cystic Fibrosis Foundation (300348), Canadian Cancer Society (2010-700406), Novartis and University Health Network (GL2-01-018) to I.S.; J.P. was funded by a Fonds zur Förderung der wissenschaftlichen Forschung–Erwin Schrödinger postdoctoral fellowship.

Author information

Author notes

  1. Christoph F Kurat

    Present address: Present address: Cancer Research UK London Research Institute, South Mimms, UK.,

  2. Tony Pawson: Deceased.

Authors and Affiliations

  1. Donnelly Centre, University of Toronto, Toronto, Ontario, Canada

    Julia Petschnigg, Bella Groisman, Christoph F Kurat, Azin Sayad, Mojca Mattiazzi Usaj, Jamie Snider, Alex Nachman, Jason Moffat & Igor Stagljar

  2. Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada

    Max Kotlyar, J Rafael Sierra, Ming-Sound Tsao & Igor Jurisica

  3. Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA

    Mikko Taipale, Irina Krykbaeva & Susan Lindquist

  4. Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada

    Yong Zheng & Tony Pawson

  5. Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada

    Ming-Sound Tsao & Igor Jurisica

  6. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada

    Ming-Sound Tsao

  7. Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada

    Jason Moffat & Igor Stagljar

  8. Howard Hughes Medical Institute, Cambridge, Massachusetts, USA

    Susan Lindquist

  9. Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Susan Lindquist

  10. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada

    Igor Jurisica

  11. Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada

    Igor Stagljar

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Contributions

I.S. conceived the project, provided guidance and assisted in manuscript preparation. J.P. coordinated, managed and was actively involved in all experiments, and wrote the bulk of the manuscript. B.G. was actively involved in the design and performance of the functional and screening part of MaMTH. M.K. and I.J. provided bioinformatics predictions and analysis of EGFR interactors. M.T., I.K. and S.L. were responsible for LUMIER assays. Y.Z. and T.P. generated co-IP and MS data. C.F.K. performed knockdown confirmations and provided technical help for all experiments. A.S., J.R.S., M.-S.T. and J.M. generated and analyzed shRNA knockdown data. J.S. was actively involved in manuscript preparation and provided project guidance. M.M.U. and A.N. were involved in data analysis, bait and prey generation, and fluorescence microscopy. All authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Igor Stagljar.

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Competing interests

A provisional patent application was filed by the University of Toronto on 2 July 2013 to the US Patent and Trademark Office, application 61/833,304. The intellectual property has been assigned to the University of Toronto and its commercialization is being managed by the Innovations and Partnership Office.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–15, Supplementary Tables 1, 4, and 6–10 (PDF 15809 kb)

Supplementary Table 2

Previously identified EGFR interactors plus PubMed-IDs and number of preys identified in various publications. (XLSX 20 kb)

Supplementary Table 3

EGFR screening luciferase data and unrelated bait interaction data. (XLSX 73 kb)

Supplementary Table 5

Previously identified EGFR interactors not detected by MaMTH. (XLSX 10 kb)

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Petschnigg, J., Groisman, B., Kotlyar, M. et al. The mammalian-membrane two-hybrid assay (MaMTH) for probing membrane-protein interactions in human cells. Nat Methods 11, 585–592 (2014). https://doi.org/10.1038/nmeth.2895

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