手机体育投注平台

Advertisement

Ribozymes pp 113-143 | Cite as

Inverse RNA Folding Workflow to Design and Test Ribozymes that Include Pseudoknots

  • Mohammad Kayedkhordeh
  • Ryota Yamagami
  • Philip C. BevilacquaEmail author
  • David H. MathewsEmail author
Protocol
  • 59 Downloads
Part of the Methods in Molecular Biology book series (MIMB, volume 2167)

Abstract

Ribozymes are RNAs that catalyze reactions. They occur in nature, and can also be evolved in vitro to catalyze novel reactions. This chapter provides detailed protocols for using inverse folding software to design a ribozyme sequence that will fold to a known ribozyme secondary structure and for testing the catalytic activity of the sequence experimentally. This protocol is able to design sequences that include pseudoknots, which is important as all naturally occurring full-length ribozymes have pseudoknots. The starting point is the known pseudoknot-containing secondary structure of the ribozyme and knowledge of any nucleotides whose identity is required for function. The output of the protocol is a set of sequences that have been tested for function. Using this protocol, we were previously successful at designing highly active double-pseudoknotted HDV ribozymes.

Key words

RNA design RNA inverse folding Ribozyme RNA pseudoknots 

Notes

Acknowledgements

手机体育投注平台This study was supported by National Institutes of HealthGrants R35GM127064 to P.C.B. and R01GM076485 to D.H.M. R.Y. was supported by a JSPS Overseas Research Fellowship.

References

  1. 1.
    Weber W, Fussenegger M (2011) Emerging biomedical applications of synthetic biology. Nat Rev Genet 13(1):21–35.  
  2. 2.
    Smanski MJ, Zhou H, Claesen J, Shen B, Fischbach MA, Voigt CA (2016) Synthetic biology to access and expand nature’s chemical diversity. Nat Rev Microbiol 14(3):135–149.  
  3. 3.
    Glasscock CJ, Lucks JB, DeLisa MP (2016) Engineered protein machines: emergent tools for synthetic biology. Cell Chem Biol 23(1):45–56.  
  4. 4.
    Baker D (2019) What has de novo protein design taught us about protein folding and biophysics? Protein Sci 28(4):678–683.  
  5. 5.
    Wolfe BR, Porubsky NJ, Zadeh JN, Dirks RM, Pierce NA (2017) Constrained multistate sequence design for nucleic acid reaction pathway engineering. J Am Chem Soc 139(8):3134–3144.  
  6. 6.
    Gu H, Chao J, Xiao SJ, Seeman NC (2009) Dynamic patterning programmed by DNA tiles captured on a DNA origami substrate. Nat Nanotechnol 4(4):245–248.  
  7. 7.
    Douglas SM, Marblestone AH, Teerapittayanon S, Vazquez A, Church GM, Shih WM (2009) Rapid prototyping of 3D DNA-origami shapes with caDNAno. Nucleic Acids Res 37(15):5001–5006.  
  8. 8.
    Chappell J, Watters KE, Takahashi MK, Lucks JB (2015) A renaissance in RNA synthetic biology: new mechanisms, applications and tools for the future. Curr Opin Chem Biol 28:47–56.  
  9. 9.
    Chworos A, Severcan I, Koyfman AY, Weinkam P, Oroudjev E, Hansma HG, Jaeger L (2004) Building programmable jigsaw puzzles with RNA. Science 306(5704):2068–2072.  
  10. 10.
    Jain S, Laederach A, Ramos SBV, Schlick T (2018) A pipeline for computational design of novel RNA-like topologies. Nucleic Acids Res 46(14):7040–7051.  
  11. 11.
    Jaeger L, Leontis NB (2000) Tecto-RNA: one-dimensional self-assembly through tertiary interactions. Angew Chem Int Ed Engl 39(14):2521–2524.  
  12. 12.
    Tuerk C, Gold L (1990) Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science 249(4968):505–510.  
  13. 13.
    Ellington AD, Szostak JW (1990) In vitro selection of RNA molecules that bind specific ligands. Nature 346(6287):818–822.  
  14. 14.
    Gold L (2015) SELEX: how it happened and where it will go. J Mol Evol 81(5–6):140–143.  
  15. 15.
    Hofacker IL (2014) Energy-directed RNA structure prediction. Methods Mol Biol 1097:71–84.  
  16. 16.
    Seetin MG, Mathews DH (2012) RNA structure prediction: an overview of methods. Methods Mol Biol 905:99–122.  
  17. 17.
    Markham NR, Zuker M (2008) UNAFold: software for nucleic acid folding and hybridization. Methods Mol Biol 453:3–31.  
  18. 18.
    Churkin A, Retwitzer MD, Reinharz V, Ponty Y, Waldispuhl J, Barash D (2018) Design of RNAs: comparing programs for inverse RNA folding. Brief Bioinform 19(2):350–358.  
  19. 19.
    Andronescu M, Fejes AP, Hutter F, Hoos HH, Condon A (2004) A new algorithm for RNA secondary structure design. J Mol Biol 336(3):607–624.  
  20. 20.
    Busch A, Backofen R (2006) INFO-RNA—a fast approach to inverse RNA folding. Bioinformatics 22(15):1823–1831.  
  21. 21.
    Zadeh JN, Wolfe BR, Pierce NA (2011) Nucleic acid sequence design via efficient ensemble defect optimization. J Comput Chem 32:439–452.  
  22. 22.
    Hofacker IL, Fontana W, Stadler PF, Bonhoeffer LS, Tacker M, Schuster P (1994) Fast folding and comparison of RNA secondary structures. Monatsh Chem 125:167–168
  23. 23.
    Taneda A (2011) MODENA: a multi-objective RNA inverse folding. Adv Appl Bioinform Chem 4:1–12. http://dx.doi.org/10.2147%2Faabc.s14335
  24. 24.
    Garcia-Martin JA, Clote P, Dotu I (2013) RNAiFOLD: a constraint programming algorithm for RNA inverse folding and molecular design. J Bioinforma Comput Biol 11(2):1350001.  
  25. 25.
    Aguirre-Hernandez R, Hoos HH, Condon A (2007) Computational RNA secondary structure design: empirical complexity and improved methods. BMC Bioinformatics 8:34.  
  26. 26.
    Anderson-Lee J, Fisker E, Kosaraju V, Wu M, Kong J, Lee J, Lee M, Zada M, Treuille A, Das R, Eterna P (2016) Principles for predicting RNA secondary structure design difficulty. J Mol Biol 428(5 Pt A):748–757.  
  27. 27.
    Andronescu M, Condon A, Turner DH, Mathews DH (2014) The determination of RNA folding nearest neighbor parameters. Methods Mol Biol 1097:45–70.  
  28. 28.
    Garcia-Martin JA, Dotu I, Clote P (2015) RNAiFold 2.0: a web server and software to design custom and Rfam-based RNA molecules. Nucleic Acids Res 43(W1):W513–W521.  
  29. 29.
    Garcia-Martin JA, Clote P, Dotu I (2013) RNAiFold: a web server for RNA inverse folding and molecular design. Nucleic Acids Res 41(Web Server issue):W465–W470.  
  30. 30.
    Liu B, Mathews DH, Turner DH (2010) RNA pseudoknots: folding and finding. F1000 Biol Rep 2:8.  
  31. 31.
    Reuter JS, Mathews DH (2010) RNAstructure: software for RNA secondary structure prediction and analysis. BMC Bioinformatics 11:129.  
  32. 32.
    Dotu I, Garcia-Martin JA, Slinger BL, Mechery V, Meyer MM, Clote P (2014) Complete RNA inverse folding: computational design of functional hammerhead ribozymes. Nucleic Acids Res 42(18):11752–11762.  
  33. 33.
    Yamagami R, Kayedkhordeh M, Mathews DH, Bevilacqua PC (2019) Design of highly active double-pseudoknotted ribozymes: a combined computational and experimental study. Nucleic Acids Res 47(1):29–42.  
  34. 34.
    Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673–4680.  
  35. 35.
    Crooks GE, Hon G, Chandonia JM, Brenner SE (2004) WebLogo: a sequence logo generator. Genome Res 14(6):1188–1190.  
  36. 36.
    Webb CH, Riccitelli NJ, Ruminski DJ, Luptak A (2009) Widespread occurrence of self-cleaving ribozymes. Science 326(5955):953.  
  37. 37.
    Kalvari I, Argasinska J, Quinones-Olvera N, Nawrocki EP, Rivas E, Eddy SR, Bateman A, Finn RD, Petrov AI (2018) Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families. Nucleic Acids Res 46(D1):D335–D342.  
  38. 38.
    Bellaousov S, Kayedkhordeh M, Peterson RJ, Mathews DH (2018) Accelerated RNA secondary structure design using pre-selected sequences for helices and loops. RNA 24:1555–1567.  
  39. 39.
    Bellaousov S, Mathews DH (2010) ProbKnot: fast prediction of RNA secondary structure including pseudoknots. RNA 16:1870–1880.  
  40. 40.
    Fay MM, Lyons SM, Ivanov P (2017) RNA G-quadruplexes in biology: principles and molecular mechanisms. J Mol Biol 429(14):2127–2147.  
  41. 41.
    Dhapola P, Chowdhury S (2016) QuadBase2: web server for multiplexed guanine quadruplex mining and visualization. Nucleic Acids Res 44(W1):W277–W283.  
  42. 42.
    Regulski EE, Breaker RR (2008) In-line probing analysis of riboswitches. Methods Mol Biol 419:53–67.  
  43. 43.
    Webb CH, Luptak A (2011) HDV-like self-cleaving ribozymes. RNA Biol 8(5):719–727.  
  44. 44.
    Salehi-Ashtiani K, Luptak A, Litovchick A, Szostak JW (2006) A genomewide search for ribozymes reveals an HDV-like sequence in the human CPEB3 gene. Science 313(5794):1788–1792.  

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2021

Authors and Affiliations

  1. 1.Department of Biochemistry and Biophysics and Center for RNA BiologyUniversity of Rochester Medical CenterRochesterUSA
  2. 2.Department of ChemistryPennsylvania State UniversityUniversity ParkUSA
  3. 3.Center for RNA Molecular BiologyPennsylvania State UniversityUniversity ParkUSA
  4. 4.Department of ChemistryPennsylvania State UniversityUniversity ParkUSA
  5. 5.Department of Biochemistry and Molecular BiologyPennsylvania State UniversityUniversity ParkUSA
  6. 6.Department of Biochemistry and BiophysicsUniversity of Rochester Medical CenterRochesterUSA
  7. 7.Department of Biostatistics and Computational BiologyUniversity of Rochester Medical CenterRochesterUSA

Personalised recommendations