Skip to main content
SpringerLink
Log in

Programmable RNA-based systems for sensing and diagnostic applications

  • Trends
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

Abstract

The emerging field of RNA nanotechnology harnesses the versatility of RNA molecules to generate nature-inspired systems with programmable structure and functionality. Such methodology has therefore gained appeal in the fields of biosensing and diagnostics, where specific molecular recognition and advanced input/output processing are demanded. The use of RNA modules and components allows for achieving diversity in structure and function, for processing information with molecular precision, and for programming dynamic operations on the grounds of predictable non-covalent interactions. When RNA nanotechnology meets bioanalytical chemistry, sensing of target molecules can be performed by harnessing programmable interactions of RNA modules, advanced field-ready biosensors can be manufactured by interfacing RNA-based devices with supporting portable platforms, and RNA sensors can be engineered to be genetically encoded allowing for real-time imaging of biomolecules in living cells. In this article, we report recent advances in RNA-based sensing technologies and discuss current trends in RNA nanotechnology-enabled biomedical diagnostics. In particular, we describe programmable sensors that leverage modular designs comprising dynamic aptamer-based units, synthetic RNA nanodevices able to perform target-responsive regulation of gene expression, and paper-based sensors incorporating artificial RNA networks.

ᅟ

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Engelhart AE. RNA imaging: a tale of two G-quadruplexes. Nat Chem Biol. 2017;13(11):1140–1.

    Article  CAS  Google Scholar 

  2. Guo P. The emerging field of RNA nanotechnology. Nat Nanotechnol. 2010;5(12):833–42.

    Article  CAS  Google Scholar 

  3. Grabow WW, Jaeger L. RNA self-assembly and RNA nanotechnology. Acc Chem Res. 2014;47(6):1871–80.

    Article  CAS  Google Scholar 

  4. Jasinski D, Haque F, Binzel DW, Guo P. Advancement of the emerging field of RNA nanotechnology. ACS Nano. 2017;11(2):1142–64.

    Article  CAS  Google Scholar 

  5. Chappell J, Watters KE, Takahashi MK, Lucks JB. A renaissance in RNA synthetic biology: new mechanisms, applications and tools for the future. Curr Opin Chem Biol. 2015;28:47–56.

    Article  CAS  Google Scholar 

  6. Slomovic S, Pardee K, Collins JJ. Synthetic biology devices for in vitro and in vivo diagnostics. Proc Natl Acad Sci U S A. 2015;112(47):14429–35.

    Article  CAS  Google Scholar 

  7. Bailey RC. Grand Challenge Commentary: Informative diagnostics for personalized medicine. Nat Chem Biol. 2010;6(12):857–9.

    Article  CAS  Google Scholar 

  8. Bouhedda F, Autour A, Ryckelynck M. Light-up RNA aptamers and their cognate fluorogens: from their development to their applications. Int J Mol Sci. 2018;19(1):E44.

    Article  Google Scholar 

  9. Neubacher S, Hennig S. RNA structure and cellular applications of fluorescent light-up aptamers. Angew Chem Int Ed. 2018. https://doi.org/10.1002/anie.201806482.

  10. Ouellet J. RNA Fluorescence with light-up aptamers. Front Chem. 2016;4:29.

    Article  Google Scholar 

  11. Szeto K, Latulippe DR, Ozer A, Pagano JM, White BS, Shalloway D, et al. RAPID-SELEX for RNA aptamers. PLoS One. 2013;8(12):e82667.

    Article  Google Scholar 

  12. Gotrik M, Sekhon G, Saurabh S, Nakamoto M, Eisenstein M, Soh HT. Direct selection of fluorescence-enhancing RNA aptamers. J Am Chem Soc. 2018;140(10):3583–91.

    Article  CAS  Google Scholar 

  13. Xu W, Lu Y. Label-free fluorescent aptamer sensor based on regulation of malachite green fluorescence. Anal Chem. 2010;82(2):574–8.

    Article  CAS  Google Scholar 

  14. Bang GS, Cho S, Lee N, Lee B-R, Kim J-H, Kim B-G. Rational design of modular allosteric aptamer sensor for label-free protein detection. Biosens Bioelectron. 2013;39(1):44–50.

    Article  Google Scholar 

  15. Paige JS, Wu KY, Jaffrey SR. RNA mimics of green fluorescent protein. Science. 2011;333(6042):642–6.

    Article  CAS  Google Scholar 

  16. Filonov GS, Moon JD, Svensen N, Jaffrey SR. Broccoli: rapid selection of an RNA mimic of green fluorescent protein by fluorescence-based selection and directed evolution. J Am Chem Soc. 2014;136(46):16299–308.

    Article  CAS  Google Scholar 

  17. Dolgosheina EV, Jeng SCY, Panchapakesan SSS, Cojocaru R, Chen PSK, Wilson PD, et al. RNA Mango aptamer-fluorophore: a bright, high-affinity complex for RNA labeling and tracking. ACS Chem Biol. 2014;9(10):2412–20.

    Article  CAS  Google Scholar 

  18. You M, Litke JL, Jaffrey SR. Imaging metabolite dynamics in living cells using a Spinach-based riboswitch. Proc Natl Acad Sci. 2015;112(21):E2756.

    Article  CAS  Google Scholar 

  19. Ying Z-M, Wu Z, Tu B, Tan W, Jiang J-H. Genetically encoded fluorescent RNA sensor for ratiometric imaging of microRNA in living tumor cells. J Am Chem Soc. 2017;139(29):9779–82.

    Article  CAS  Google Scholar 

  20. Jepsen MDE, Sparvath SM, Nielsen TB, Langvad AH, Grossi G, Gothelf KV, et al. Development of a genetically encodable FRET system using fluorescent RNA aptamers. Nat Commun. 2018;9(1):18.

    Article  Google Scholar 

  21. Warner KD, Chen MC, Song W, Strack RL, Thorn A, Jaffrey SR, et al. Structural basis for activity of highly efficient RNA mimics of green fluorescent protein. Nat Struct Mol Biol. 2014;21(8):658–63.

    Article  CAS  Google Scholar 

  22. Paige JS, Nguyen-Duc T, Song W, Jaffrey SR. Fluorescence imaging of cellular metabolites with RNA. Science. 2012;335(6073):1194.

    Article  CAS  Google Scholar 

  23. Park MH, Igarashi K. Polyamines and their metabolites as diagnostic markers of human diseases. Biomol Ther. 2013;21(1):1–9.

    Article  CAS  Google Scholar 

  24. Fernie AR, Trethewey RN, Krotzky AJ, Willmitzer L. Metabolite profiling: from diagnostics to systems biology. Nat Rev Mol Cell Biol. 2004;5(9):763–9.

    Article  CAS  Google Scholar 

  25. Aw SS, Tang MX, Teo YN, Cohen SM. A conformation-induced fluorescence method for microRNA detection. Nucleic Acids Res. 2016;44(10):e92.

    Article  Google Scholar 

  26. Huang K, Doyle F, Wurz ZE, Tenenbaum SA, Hammond RK, Caplan JL, et al. FASTmiR: an RNA-based sensor for in vitro quantification and live-cell localization of small RNAs. Nucleic Acids Res. 2017;45(14):e130.

    Article  CAS  Google Scholar 

  27. Krichevsky AM, Gabriely G. miR-21: a small multi-faceted RNA. J Cell Mol Med. 2008;13(1):39–53.

    Article  Google Scholar 

  28. Autour A, Jeng SCY, Cawte DA, Abdolahzadeh A, Galli A, Panchapakesan SSS, et al. Fluorogenic RNA Mango aptamers for imaging small non-coding RNAs in mammalian cells. Nat Commun. 2018;9(1):656.

    Article  Google Scholar 

  29. Wang Z, Luo Y, Xie X, Hu X, Song H, Zhao Y, et al. In situ spatial complementation of aptamer-mediated recognition enables live-cell imaging of native RNA transcripts in real time. Angew Chem Int Ed. 2018;57(4):972–6.

    Article  CAS  Google Scholar 

  30. Bertucci A, Porchetta A, Ricci F. Antibody-templated assembly of an RNA mimic of green fluorescent protein. Anal Chem. 2018;90(2):1049–53.

    Article  CAS  Google Scholar 

  31. Karunanayake Mudiyanselage APKK, Yu Q, Leon-Duque MA, Zhao B, Wu R, You M. Genetically encoded catalytic hairpin assembly for sensitive RNA imaging in live cells. J Am Chem Soc. 2018;140(28):8739–45.

    Article  CAS  Google Scholar 

  32. Michnick SW, Ear PH, Manderson EN, Remy I, Stefan E. Universal strategies in research and drug discovery based on protein-fragment complementation assays. Nat Rev Drug Discov. 2007;6(7):569–82.

    Article  CAS  Google Scholar 

  33. Zhang H, Li F, Dever B, Wang C, Li X-F, Le XC. Assembling DNA through affinity binding to achieve ultrasensitive protein detection. Angew Chem Int Ed. 2013;52(41):10698–705.

    Article  CAS  Google Scholar 

  34. Kolpashchikov DM. Binary malachite green aptamer for fluorescent detection of nucleic acids. J Am Chem Soc. 2005;127(36):12442–3.

    Article  CAS  Google Scholar 

  35. Kikuchi N, Kolpashchikov DM. Split Spinach aptamer for highly selective recognition of DNA and RNA at ambient temperatures. Chembiochem. 2016;17(17):1589–92.

    Article  CAS  Google Scholar 

  36. Kikuchi N, Kolpashchikov DM. A universal split spinach aptamer (USSA) for nucleic acid analysis and DNA computation. Chem Commun. 2017;53(36):4977–80.

    Article  CAS  Google Scholar 

  37. Rogers TA, Andrews GE, Jaeger L, Grabow WW. Fluorescent monitoring of RNA assembly and processing using the split-Spinach aptamer. ACS Synth Biol. 2015;4(2):162–6.

    Article  CAS  Google Scholar 

  38. Alam KK, Tawiah KD, Lichte MF, Porciani D, Burke DH. A fluorescent split aptamer for visualizing RNA-RNA assembly in vivo. ACS Synth Biol. 2017;6(9):1710–21.

    Article  CAS  Google Scholar 

  39. Xie M, Fussenegger M. Designing cell function: assembly of synthetic gene circuits for cell biology applications. Nat Rev Mol Cell Biol. 2018;19(8):507–25.

    Article  CAS  Google Scholar 

  40. Masubuchi T, Endo M, Iizuka R, Iguchi A, Yoon DH, Sekiguchi T, et al. Construction of integrated gene logic-chip. Nat Nanotechnol. 2018;13(10):933–40.

    Article  CAS  Google Scholar 

  41. Nielsen AAK, Der BS, Shin J, Vaidyanathan P, Paralanov V, Strychalski EA, et al. Genetic circuit design automation. Science. 2016;352(6281):7341.

    Article  Google Scholar 

  42. McKeague M, Wong RS, Smolke CD. Opportunities in the design and application of RNA for gene expression control. Nucleic Acids Res. 2016;44(7):2987–99.

    Article  CAS  Google Scholar 

  43. Etzel M, Mörl M. Synthetic riboswitches: from plug and pray toward plug and play. Biochemistry. 2017;56(9):1181–98.

    Article  CAS  Google Scholar 

  44. Chen YY, Jensen MC, Smolke CD. Genetic control of mammalian T-cell proliferation with synthetic RNA regulatory systems. Proc Natl Acad Sci U S A. 2010;107(19):8531–6.

    Article  CAS  Google Scholar 

  45. Isaacs FJ, Dwyer DJ, Ding C, Pervouchine DD, Cantor CR, Collins JJ. Engineered riboregulators enable post-transcriptional control of gene expression. Nat Biotechnol. 2004;22(7):841–7.

    Article  CAS  Google Scholar 

  46. Bayer TS, Smolke CD. Programmable ligand-controlled riboregulators of eukaryotic gene expression. Nat Biotechnol. 2005;23(3):337–43.

    Article  CAS  Google Scholar 

  47. Mutalik VK, Qi L, Guimaraes JC, Lucks JB, Arkin AP. Rationally designed families of orthogonal RNA regulators of translation. Nat Chem Biol. 2012;8(5):447–54.

    Article  CAS  Google Scholar 

  48. Liu CC, Qi L, Lucks JB, Segall-Shapiro TH, Wang D, Mutalik VK, et al. An adaptor from translational to transcriptional control enables predictable assembly of complex regulation. Nat Methods. 2012;9(11):1088–94.

    Article  CAS  Google Scholar 

  49. Isaacs FJ. Synthetic biology: automated design of RNA devices. Nat Chem Biol. 2012;8(5):413–5.

    Article  CAS  Google Scholar 

  50. Green AA, Silver PA, Collins JJ, Yin P. Toehold switches: de-novo-designed regulators of gene expression. Cell. 2014;159(4):925–39.

    Article  CAS  Google Scholar 

  51. Karig DK. Cell-free synthetic biology for environmental sensing and remediation. Curr Opin Biotechnol. 2017;45:69–75.

    Article  CAS  Google Scholar 

  52. Parolo C, Merkoçi A. Paper-based nanobiosensors for diagnostics. Chem Soc Rev. 2013;42:450–7.

    Article  CAS  Google Scholar 

  53. Yamada K, Shibata H, Suzuki K, Citterio D. Toward practical application of paper-based microfluidics for medical diagnostics: state-of-the-art and challenges. Lab Chip. 2017;17:1206–49.

    Article  CAS  Google Scholar 

  54. Pardee K, Green AA, Ferrante T, Cameron DE, Daleykeyser A, Yin P, et al. Paper-based synthetic gene networks. Cell. 2014;159(4):940–54.

    Article  CAS  Google Scholar 

  55. Takahashi MK, Tan X, Dy AJ, Braff D, Akana RT, Furuta Y, et al. A low-cost paper-based synthetic biology platform for analyzing gut microbiota and host biomarkers. Nat Commun. 2018;9:3347.

    Article  Google Scholar 

  56. Pardee K, Green AA, Takahashi MK, Braff D, Lambert G, Lee JW, et al. Rapid, low-cost detection of Zika virus using programmable biomolecular components. Cell. 2016;165(5):1255–66.

    Article  CAS  Google Scholar 

Download references

Funding

A.P. received support from the University of Rome Tor Vergata under the grant “MIRA” no E81I18000200005. This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement no 704120 (“MIRNANO”). A.B. is a global Marie Skłodowska-Curie fellow. M.R. and S.R. are supported from a Fondazione Umberto Veronesi “postdoctoral fellowship 2019”. 

Author information

Authors and Affiliations

  1. Department of Chemical Sciences and Technologies, University of Rome Tor Vergata, 00133, Rome, Italy

    Marianna Rossetti, Erica Del Grosso, Simona Ranallo, Davide Mariottini, Alessandro Bertucci & Alessandro Porchetta

  2. Department of Chemistry and Biochemistry, University of California Santa Barbara, Santa Barbara, CA, 93106, USA

    Andrea Idili

  3. Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, 92093, USA

    Alessandro Bertucci

Authors
  1. Marianna Rossetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Erica Del Grosso
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Simona Ranallo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Davide Mariottini
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Andrea Idili
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alessandro Bertucci
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Alessandro Porchetta
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Alessandro Bertucci or Alessandro Porchetta.

Ethics declarations

No experiments involving human participants and/or animals have been conducted for this publication.

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Published in the topical collection Young Investigators in (Bio-)Analytical Chemistry with guest editors Erin Baker, Kerstin Leopold, Francesco Ricci, and Wei Wang.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rossetti, M., Del Grosso, E., Ranallo, S. et al. Programmable RNA-based systems for sensing and diagnostic applications. Anal Bioanal Chem 411, 4293–4302 (2019). https://doi.org/10.1007/s00216-019-01622-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-019-01622-7

Keywords

Search

Navigation