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Targeted inhibition of oncogenic miR-21 maturation with designed RNA-binding proteins

Abstract

The RNA recognition motif (RRM) is the largest family of eukaryotic RNA-binding proteins. Engineered RRMs with well-defined specificity would provide valuable tools and an exacting test of the current understanding of specificity. We have redesigned the specificity of an RRM using rational methods and demonstrated retargeting of its activity in cells. We engineered the conserved RRM of human Rbfox proteins to specifically bind to the terminal loop of a microRNA precursor (pre-miR-21) with high affinity and inhibit its processing by Drosha and Dicer. We further engineered Giardia Dicer by replacing its PAZ domain with the designed RRM. The reprogrammed enzyme degrades pre-miR-21 specifically in vitro and suppresses mature miR-21 levels in cells, which results in increased expression of the tumor suppressor PDCD4 and significantly decreased viability for cancer cells. The results demonstrate the feasibility of rationally engineering the sequence-specificity of RRMs and of using this ubiquitous platform for diverse biological applications.

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Figure 1: Engineering the RNA-binding specificity of Rbfox-RRM by rational design.
Figure 2: Secondary structures of free pre-miR-21 and its complex with Fox-RRM*.
Figure 3: Engineered Fox-RRM* inhibits pri- and pre-miR-21 processing.
Figure 4: Engineering G Dicer to target pre-miR-21.
Figure 5: Engineered RRM*-Dicer reduces cellular mature miR-21 levels, increases expression of PDCD4 and reduces cancer cell viability.

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Protein Data Bank

References

  1. Wang, Y., Wang, Z. & Tanaka Hall, T.M. Engineered proteins with Pumilio/fem-3 mRNA binding factor scaffold to manipulate RNA metabolism. FEBS J. 280, 3755–3767 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  2. Mackay, J.P., Font, J. & Segal, D.J. The prospects for designer single-stranded RNA-binding proteins. Nat. Struct. Mol. Biol. 18, 256–261 (2011).

    CAS  Article  PubMed  Google Scholar 

  3. Chen, Y. & Varani, G. Engineering RNA-binding proteins for biology. FEBS J. 280, 3734–3754 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. Cheong, C.G. & Hall, T.M. Engineering RNA sequence specificity of Pumilio repeats. Proc. Natl. Acad. Sci. USA 103, 13635–13639 (2006).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. Filipovska, A., Razif, M.F.M., Nygård, K.K.A. & Rackham, O. A universal code for RNA recognition by PUF proteins. Nat. Chem. Biol. 7, 425–427 (2011).

    CAS  Article  PubMed  Google Scholar 

  6. Agrawal, A.A., McLaughlin, K.J., Jenkins, J.L. & Kielkopf, C.L. Structure-guided U2AF65 variant improves recognition and splicing of a defective pre-mRNA. Proc. Natl. Acad. Sci. USA 111, 17420–17425 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  7. Blakeley, B.D. & McNaughton, B.R. Synthetic RNA recognition motifs that selectively recognize HIV-1 trans-activation response element hairpin RNA. ACS Chem. Biol. 9, 1320–1329 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. Kuroyanagi, H. Fox-1 family of RNA-binding proteins. Cell. Mol. Life Sci. 66, 3895–3907 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  9. Auweter, S.D. et al. Molecular basis of RNA recognition by the human alternative splicing factor Fox-1. EMBO J. 25, 163–173 (2006).

    CAS  Article  PubMed  Google Scholar 

  10. Zhang, X. & Zeng, Y. The terminal loop region controls microRNA processing by Drosha and Dicer. Nucleic Acids Res. 38, 7689–7697 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. Gu, S. et al. The loop position of shRNAs and pre-miRNAs is critical for the accuracy of dicer processing in vivo. Cell 151, 900–911 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. Choudhury, N.R. & Michlewski, G. Terminal loop-mediated control of microRNA biogenesis. Biochem. Soc. Trans. 40, 789–793 (2012).

    CAS  Article  PubMed  Google Scholar 

  13. Michlewski, G., Guil, S., Semple, C.A. & Cáceres, J.F. Posttranscriptional regulation of miRNAs harboring conserved terminal loops. Mol. Cell 32, 383–393 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. Nam, Y., Chen, C., Gregory, R.I., Chou, J.J. & Sliz, P. Molecular basis for interaction of let-7 microRNAs with Lin28. Cell 147, 1080–1091 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Trabucchi, M. et al. The RNA-binding protein KSRP promotes the biogenesis of a subset of microRNAs. Nature 459, 1010–1014 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. Castilla-Llorente, V., Nicastro, G. & Ramos, A. Terminal loop-mediated regulation of miRNA biogenesis: selectivity and mechanisms. Biochem. Soc. Trans. 41, 861–865 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  17. Krichevsky, A.M. & Gabriely, G. miR-21: a small multi-faceted RNA. J. Cell. Mol. Med. 13, 39–53 (2009).

    CAS  Article  PubMed  Google Scholar 

  18. Medina, P.P., Nolde, M. & Slack, F.J. OncomiR addiction in an in vivo model of microRNA-21-induced pre-B-cell lymphoma. Nature 467, 86–90 (2010).

    CAS  Article  PubMed  Google Scholar 

  19. Macrae, I.J. et al. Structural basis for double-stranded RNA processing by Dicer. Science 311, 195–198 (2006).

    CAS  Article  PubMed  Google Scholar 

  20. Asangani, I.A. et al. MicroRNA-21 (miR-21) post-transcriptionally downregulates tumor suppressor Pdcd4 and stimulates invasion, intravasation and metastasis in colorectal cancer. Oncogene 27, 2128–2136 (2008).

    CAS  Article  PubMed  Google Scholar 

  21. Davis, B.N., Hilyard, A.C., Lagna, G. & Hata, A. SMAD proteins control DROSHA-mediated microRNA maturation. Nature 454, 56–61 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. Oubridge, C., Ito, N., Evans, P.R., Teo, C.-H. & Nagai, K. Crystal structure at 1.92 Å resolution of the RNA-binding domain of the U1A spliceosomal protein complexed with an RNA hairpin. Nature 372, 432–438 (1994).

    CAS  Article  PubMed  Google Scholar 

  23. Allers, J. & Shamoo, Y. Structure-based analysis of protein-RNA interactions using the program ENTANGLE. J. Mol. Biol. 311, 75–86 (2001).

    CAS  Article  PubMed  Google Scholar 

  24. Chen, Y., Kortemme, T., Robertson, T., Baker, D. & Varani, G. A new hydrogen-bonding potential for the design of protein-RNA interactions predicts specific contacts and discriminates decoys. Nucleic Acids Res. 32, 5147–5162 (2004).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  25. Minuchehr, Z. & Goliaei, B. Propensity of amino acids in loop regions connecting β-strands. Protein Pept. Lett. 12, 379–382 (2005).

    CAS  Article  PubMed  Google Scholar 

  26. Weeks, K.M. & Mauger, D.M. Exploring RNA structural codes with SHAPE chemistry. Acc. Chem. Res. 44, 1280–1291 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. Chen, Y. et al. Rbfox proteins regulate microRNA biogenesis by sequence-specific binding to their precursors and target downstream Dicer. Nucleic Acids Res. 44, 4381–4395 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  28. Krol, J., Loedige, I. & Filipowicz, W. The widespread regulation of microRNA biogenesis, function and decay. Nat. Rev. Genet. 11, 597–610 (2010).

    CAS  Article  PubMed  Google Scholar 

  29. Nguyen, T.A. et al. Functional anatomy of the human microprocessor. Cell 161, 1374–1387 (2015).

    CAS  Article  PubMed  Google Scholar 

  30. Newman, M.A., Thomson, J.M. & Hammond, S.M. Lin-28 interaction with the Let-7 precursor loop mediates regulated microRNA processing. RNA 14, 1539–1549 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  31. MacRae, I.J., Zhou, K. & Doudna, J.A. Structural determinants of RNA recognition and cleavage by Dicer. Nat. Struct. Mol. Biol. 14, 934–940 (2007).

    CAS  Article  PubMed  Google Scholar 

  32. Peroutka, R.J., Elshourbagy, N., Piech, T. & Butt, T.R. Enhanced protein expression in mammalian cells using engineered SUMO fusions: secreted phospholipase A2. Protein Sci. 17, 1586–1595 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. Si, M.-L. miR-21-mediated tumor growth. Oncogene 26, 2799–2803 (2007).

    CAS  Article  PubMed  Google Scholar 

  34. Schmittgen, T.D., Jiang, J., Liu, Q. & Yang, L. A high-throughput method to monitor the expression of microRNA precursors. Nucleic Acids Res. 32, e43 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Lunde, B.M., Moore, C. & Varani, G. RNA-binding proteins: modular design for efficient function. Nat. Rev. Mol. Cell Biol. 8, 479–490 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  36. Auweter, S.D., Oberstrass, F.C. & Allain, F.H.-T. Sequence-specific binding of single-stranded RNA: is there a code for recognition? Nucleic Acids Res. 34, 4943–4959 (2006).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  37. Lünse, C.E. et al. An aptamer targeting the apical-loop domain modulates pri-miRNA processing. Angew. Chem. Int. Ed. Engl. 49, 4674–4677 (2010).

    Article  PubMed  Google Scholar 

  38. Diaz, J.P. et al. Association of a peptoid ligand with the apical loop of pri-miR-21 inhibits cleavage by Drosha. RNA 20, 528–539 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  39. Griffiths-Jones, S., Saini, H.K., van Dongen, S. & Enright, A.J. miRBase: tools for microRNA genomics. Nucleic Acids Res. 36, D154–D158 (2008).

    CAS  Article  PubMed  Google Scholar 

  40. Price, S.R., Oubridge, C., Varani, G. & Nagai, K. Preparation of RNA–protein complexes for X-ray crystallography and NMR. in RNA–Protein Interaction: Practical Approach (ed. Smith, C.) 37–74 (Oxford University Press, 1998).

  41. Schneider, C.A., Rasband, W.S. & Eliceiri, K.W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  42. Wilkinson, K.A., Merino, E.J. & Weeks, K.M. Selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE): quantitative RNA structure analysis at single nucleotide resolution. Nat. Protoc. 1, 1610–1616 (2006).

    CAS  Article  PubMed  Google Scholar 

  43. Das, R., Laederach, A., Pearlman, S.M., Herschlag, D. & Altman, R.B. SAFA: semi-automated footprinting analysis software for high-throughput quantification of nucleic acid footprinting experiments. RNA 11, 344–354 (2005).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  44. Parisien, M. & Major, F. The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data. Nature 452, 51–55 (2008).

    CAS  Article  PubMed  Google Scholar 

  45. Tenzer, S. et al. Proteome-wide characterization of the RNA-binding protein RALY-interactome using the in vivo-biotinylation-pulldown-quant (iBioPQ) approach. J. Proteome Res. 12, 2869–2884 (2013).

    CAS  Article  PubMed  Google Scholar 

  46. Zheng, S., Robertson, T.A. & Varani, G. A knowledge-based potential function predicts the specificity and relative binding energy of RNA-binding proteins. FEBS J. 274, 6378–6391 (2007).

    CAS  Article  PubMed  Google Scholar 

  47. Kortemme, T., Morozov, A.V. & Baker, D. An orientation-dependent hydrogen bonding potential improves prediction of specificity and structure for proteins and protein-protein complexes. J. Mol. Biol. 326, 1239–1259 (2003).

    CAS  Article  PubMed  Google Scholar 

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Acknowledgements

The authors are grateful to J. Mandic and other members of G.V.'s laboratory for technical assistance. We thank the Analytical Biopharmacy Core for access to ITC in the School of Pharmacy at the University of Washington. This work was supported by US National Institutes of Health Grant 1R01 GM103834 to G.V., the University of Trento (Progetto Biotecnologie, P.M.) and the Autonomous Province of Trento (Madelena Project, P.M.).

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Authors

Contributions

Y.C. conceived the project and designed the experiments, performed protein design, biochemical and cell-based assays, analyzed the data and wrote the paper; F.Y. performed ITC and NMR analysis of protein–RNA interactions; L.Z. and T.P. performed the cell biological assays; W.Y. cloned and expressed G Dicer proteins; K.G. performed SHAPE analysis; M.W. performed Dicer processing assays. S.Z. performed protein structural modeling; L.Z. and P.M. analyzed the data and wrote the paper; G.V. conceived the project, analyzed the data and wrote the paper.

Corresponding authors

Correspondence to Yu Chen or Gabriele Varani.

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The authors declare no competing financial interests.

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Supplementary Results, Supplementary Table 1 and Supplementary Figures 1–7. (PDF 3347 kb)

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Chen, Y., Yang, F., Zubovic, L. et al. Targeted inhibition of oncogenic miR-21 maturation with designed RNA-binding proteins. Nat Chem Biol 12, 717–723 (2016). https://doi.org/10.1038/nchembio.2128

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