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System-wide identification of RNA-binding proteins by interactome capture

Abstract

Owing to their preeminent biological functions, the repertoire of expressed RNA-binding proteins (RBPs) and their activity states are highly informative about cellular systems. We have developed a novel and unbiased technique, called interactome capture, for identifying the active RBPs of cultured cells. By making use of in vivo UV cross-linking of RBPs to polyadenylated RNAs, covalently bound proteins are captured with oligo(dT) magnetic beads. After stringent washes, the mRNA interactome is determined by quantitative mass spectrometry (MS). The protocol takes 3 working days for analysis of single proteins by western blotting, and about 2 weeks for the determination of complete cellular mRNA interactomes by MS. The most important advantage of interactome capture over other in vitro and in silico approaches is that only RBPs bound to RNA in a physiological environment are identified. When applied to HeLa cells, interactome capture revealed hundreds of novel RBPs. Interactome capture can also be broadly used to compare different biological states, including metabolic stress, cell cycle, differentiation, development or the response to drugs.

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Figure 1: Schematic representation of the interactome capture pipeline.
Figure 2: Interactome capture as a selective protocol for capturing RBPs in HeLa and Huh-7 cells.
Figure 3: Interactome capture applied to determine in vivo RNA-binding activities of candidate proteins of interest.
Figure 4: Monitoring protein content in input, wash and eluate samples of a cellular interactome capture experiment.

References

  1. Ascano, M., Hafner, M., Cekan, P., Gerstberger, S. & Tuschl, T. Identification of RNA-protein interaction networks using PAR-CLIP. Wiley Interdiscip Rev. RNA 3, 159–177 (2012).

    CAS  Article  Google Scholar 

  2. Konig, J., Zarnack, K., Luscombe, N.M. & Ule, J. Protein-RNA interactions: new genomic technologies and perspectives. Nat. Rev. Genet. 13, 77–83 (2011).

    Article  Google Scholar 

  3. Baltz, A.G. et al. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Mol. Cell 46, 674–690 (2012).

    CAS  Article  Google Scholar 

  4. Castello, A. et al. Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell 149, 1393–1406 (2012).

    CAS  Article  Google Scholar 

  5. Scherrer, T., Mittal, N., Janga, S.C. & Gerber, A.P. A screen for RNA-binding proteins in yeast indicates dual functions for many enzymes. PLoS ONE 5, e15499 (2010).

    CAS  Article  Google Scholar 

  6. Tsvetanova, N.G., Klass, D.M., Salzman, J. & Brown, P.O. Proteome-wide search reveals unexpected RNA-binding proteins in Saccharomyces cerevisiae. PLoS ONE 5, e12671 (2010).

    Article  Google Scholar 

  7. Butter, F., Scheibe, M., Morl, M. & Mann, M. Unbiased RNA-protein interaction screen by quantitative proteomics. Proc. Natl Acad. Sci. USA 106, 10626–10631 (2009).

    CAS  Article  Google Scholar 

  8. Anantharaman, V., Koonin, E.V. & Aravind, L. Comparative genomics and evolution of proteins involved in RNA metabolism. Nucleic Acids Res. 30, 1427–1464 (2002).

    CAS  Article  Google Scholar 

  9. Brimacombe, R., Stiege, W., Kyriatsoulis, A. & Maly, P. Intra-RNA and RNA-protein cross-linking techniques in Escherichia coli ribosomes. Methods Enzymol. 164, 287–309 (1988).

    CAS  Article  Google Scholar 

  10. Hockensmith, J.W., Kubasek, W.L., Vorachek, W.R. & von Hippel, P.H. Laser cross-linking of nucleic acids to proteins. Methodology and first applications to the phage T4 DNA replication system. J. Biol. Chem. 261, 3512–3518 (1986).

    CAS  PubMed  Google Scholar 

  11. Hafner, M. et al. Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell 141, 129–141 (2010).

    CAS  Article  Google Scholar 

  12. Pashev, I.G., Dimitrov, S.I. & Angelov, D. Cross-linking proteins to nucleic acids by ultraviolet laser irradiation. Trends Biochem. Sci. 16, 323–326 (1991).

    CAS  Article  Google Scholar 

  13. Suchanek, M., Radzikowska, A. & Thiele, C. Photo-leucine and photo-methionine allow identification of protein-protein interactions in living cells. Nat. Methods 2, 261–267 (2005).

    CAS  Article  Google Scholar 

  14. Creamer, T.J. et al. Transcriptome-wide binding sites for components of the Saccharomyces cerevisiae non-poly(A) termination pathway: Nrd1, Nab3, and Sen1. PLoS Genet. 7, e1002329 (2011).

    CAS  Article  Google Scholar 

  15. Jamonnak, N. et al. Yeast Nrd1, Nab3, and Sen1 transcriptome-wide binding maps suggest multiple roles in post-transcriptional RNA processing. RNA 17, 2011–2025 (2011).

    CAS  Article  Google Scholar 

  16. Jungkamp, A.C. et al. In vivo and transcriptome-wide identification of RNA binding protein target sites. Mol. Cell 44, 828–840 (2011).

    CAS  Article  Google Scholar 

  17. Hafner, M. et al. PAR-CliP—a method to identify transcriptome-wide the binding sites of RNA binding proteins. J. Vis. Exp. 41, e2034 published online; doi:10.3791/2034 (2010).

    Google Scholar 

  18. Xu, T., Wong, C.C., Kashina, A. & Yates, J.R. Identification of N-terminally arginylated proteins and peptides by mass spectrometry. Nat. Protoc. 4, 325–332 (2009).

    CAS  Article  Google Scholar 

  19. Boersema, P.J., Aye, T.T., van Veen, T.A., Heck, A.J. & Mohammed, S. Triplex protein quantification based on stable isotope labeling by peptide dimethylation applied to cell and tissue lysates. Proteomics 8, 4624–4632 (2008).

    CAS  Article  Google Scholar 

  20. Choe, L. et al. 8-plex quantitation of changes in cerebrospinal fluid protein expression in subjects undergoing intravenous immunoglobulin treatment for Alzheimer′s disease. Proteomics 7, 3651–3660 (2007).

    CAS  Article  Google Scholar 

  21. Ross, P.L. et al. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell Proteomics 3, 1154–1169 (2004).

    CAS  Article  Google Scholar 

  22. Ong, S.E. & Mann, M. A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC). Nat. Protoc. 1, 2650–2660 (2006).

    CAS  Article  Google Scholar 

  23. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).

    CAS  Article  Google Scholar 

  24. Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).

    CAS  Article  Google Scholar 

  25. Wisniewski, J.R., Zougman, A., Nagaraj, N. & Mann, M. Universal sample preparation method for proteome analysis. Nat. Methods 6, 359–362 (2009).

    CAS  Article  Google Scholar 

  26. Villen, J. & Gygi, S.P. The SCX/IMAC enrichment approach for global phosphorylation analysis by mass spectrometry. Nat. Protoc. 3, 1630–1638 (2008).

    Article  Google Scholar 

  27. Krijgsveld, J., Gauci, S., Dormeyer, W. & Heck, A.J. In-gel isoelectric focusing of peptides as a tool for improved protein identification. J. Proteome Res. 5, 1721–1730 (2006).

    CAS  Article  Google Scholar 

  28. Cox, J. et al. A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat. Protoc. 4, 698–705 (2009).

    CAS  Article  Google Scholar 

  29. Smyth, G.K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3 published online; doi:10.2202/1544-6115 (2004).

  30. Gentleman, R., Carey, V., Dudoit, S., Irizarry, R. & Huber, W. Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Springer,, 2005).

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Acknowledgements

We thank M. Landthaler (Max Delbrück Center for Molecular Medicine) for generously sharing his expertise on PAR-CL. We are grateful to R. Pepperkok (EMBL) for plasmids and M. Gromeier (Duke University Medical Center) for the HeLa Flip-in TRex cell line. We thank M. Muckenthaler (University of Heidelberg) for Huh-7 cells. We acknowledge A. Perez and the EMBL Flow Cytometry Core Facility for FACS experiments, and EMBL Gene and Proteomics Core Facilities for support throughout this work. We also thank Chromotek for expert technical advice and support. A.C. is the beneficiary of a Marie Curie postdoctoral fellowship (FP7). M.W.H. acknowledges support by the European Research Council (ERC) Advanced Grant ERC-2011-ADG_20110310 and the Virtual Liver Network of the German Ministry for Science and Education.

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A.C., J.K., L.M.S. and M.W.H. contributed to the conception and design of the project. A.C., R.H., C.S., B.F. and K.E. carried out the experimental work. A.C. and M.W.H. wrote the manuscript.

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Correspondence to Matthias W Hentze.

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The authors declare no competing financial interests.

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Castello, A., Horos, R., Strein, C. et al. System-wide identification of RNA-binding proteins by interactome capture. Nat Protoc 8, 491–500 (2013). https://doi.org/10.1038/nprot.2013.020

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