A carbon nanotube reporter of microRNA hybridization events in vivo

Abstract

MicroRNAs and other small oligonucleotides in biofluids are promising disease biomarkers, yet conventional assays require complex processing steps that are unsuitable for point-of-care testing or for implantable or wearable sensors. Single-walled carbon nanotubes are an ideal material for implantable sensors, owing to their emission in the near-infrared spectral region, photostability and exquisite sensitivity. Here, we report an engineered carbon-nanotube-based sensor capable of real-time optical quantification of hybridization events of microRNA and other oligonucleotides. The mechanism of the sensor arises from competitive effects between displacement of both oligonucleotide charge groups and water from the nanotube surface, which result in a solvatochromism-like response. The sensor, which allows for detection via single-molecule sensor elements and for multiplexing by using multiple nanotube chiralities, can monitor toehold-based strand-displacement events, which reverse the sensor response and regenerate the sensor complex. We also show that the sensor functions in whole urine and serum, and can non-invasively measure DNA and microRNA after implantation in live mice.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Carbon nanotube sensor for the detection of miRNA hybridization events.
Figure 2: Characterization of miRNA detection limit, kinetics and functionality.
Figure 3: Single-nanotube response to miRNA hybridization.
Figure 4: Sensor multiplexing.
Figure 5: Monitoring toehold-mediated strand displacement.
Figure 6: Detection of miRNA in biofluids and non-invasively in live mice.

References

  1. 1

    Tokuhisa, M. et al. Exosomal miRNAs from peritoneum lavage fluid as potential prognostic biomarkers of peritoneal metastasis in gastric cancer. PLoS ONE 10, e0130472 (2015).

    Article  Google Scholar 

  2. 2

    Parrella, P., Zangen, R., Sidransky, D. & Nicol, T. Molecular analysis of peritoneal fluid in ovarian cancer patients. Mod. Pathol. 16, 636–640 (2003).

    Article  Google Scholar 

  3. 3

    Mitchell, P. S. et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc. Natl Acad. Sci. USA 105, 10513–10518 (2008).

    CAS  Article  Google Scholar 

  4. 4

    Dawson, S. J. et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N. Engl. J. Med. 368, 1199–1209 (2013).

    CAS  Article  Google Scholar 

  5. 5

    Tomlins, S. A. et al. Urine TMPRSS2:ERG fusion transcript stratifies prostate cancer risk in men with elevated serum PSA. Sci. Transl. Med. 3, 94ra72 (2011).

    CAS  Article  Google Scholar 

  6. 6

    Thierry, A. R. et al. Clinical validation of the detection of KRAS and BRAF mutations from circulating tumor DNA. Nat. Med. 20, 430–435 (2014).

    CAS  Article  Google Scholar 

  7. 7

    Deras, I. L. et al. PCA3: a molecular urine assay for predicting prostate biopsy outcome. J. Urol. 179, 1587–1592 (2008).

    Article  Google Scholar 

  8. 8

    Weber, J. A. et al. The microRNA spectrum in 12 body fluids. Clin. Chem. 56, 1733–1741 (2010).

    CAS  Article  Google Scholar 

  9. 9

    Lawrie, C. H. et al. Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. Br. J. Haematol. 141, 672–675 (2008).

    Article  Google Scholar 

  10. 10

    Yamada, Y. et al. MiR-96 and miR-183 detection in urine serve as potential tumor markers of urothelial carcinoma: correlation with stage and grade, and comparison with urinary cytology. Cancer Sci. 102, 522–529 (2011).

    CAS  Article  Google Scholar 

  11. 11

    Hanke, M. et al. A robust methodology to study urine microRNA as tumor marker: microRNA-126 and microRNA-182 are related to urinary bladder cancer. Urol. Oncol. 28, 655–661 (2010).

    CAS  Article  Google Scholar 

  12. 12

    Snowdon, J., Boag, S., Feilotter, H., Izard, J. & Siemens, R. A pilot study of urinary microRNA as a biomarker for urothelial cancer. Can. Urol. Assoc. J. 7, 28–32 (2013).

    Article  Google Scholar 

  13. 13

    Lan, Y. F. et al. MicroRNA-494 reduces ATF3 expression and promotes AKI. J. Am. Soc. Nephrol. 23, 2012–2023 (2012).

    CAS  Article  Google Scholar 

  14. 14

    Chung, Y. W. et al. Detection of microRNA as novel biomarkers of epithelial ovarian cancer from the serum of ovarian cancer patient. Int. J. Gynecol. Cancer 23, 673–679 (2013).

    Article  Google Scholar 

  15. 15

    Pajek, J. et al. Cell-free DNA in the peritoneal effluent of peritoneal dialysis solutions. Ther. Apher. Dial. 14, 20–26 (2010).

    CAS  Article  Google Scholar 

  16. 16

    Johnson, B. N. & Mutharasan, R. Biosensor-based microRNA detection: techniques, design, performance, and challenges. Analyst 139, 1576–1588 (2014).

    CAS  Article  Google Scholar 

  17. 17

    Chen, C. et al. Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res. 33, e179 (2005).

    Article  Google Scholar 

  18. 18

    Baker, M. MicroRNA profiling: separating signal from noise. Nat. Methods 7, 687–692 (2010).

    CAS  Article  Google Scholar 

  19. 19

    Hunt, E. A., Broyles, D., Head, T. & Deo, S. K. MicroRNA detection: current technology and research strategies. Annu. Rev. Anal. Chem. 8, 217–237 (2015).

    CAS  Article  Google Scholar 

  20. 20

    Dong, H. et al. MicroRNA: function, detection, and bioanalysis. Chem. Rev. 113, 6207–6233 (2013).

    CAS  Article  Google Scholar 

  21. 21

    Kruss, S. et al. Carbon nanotubes as optical biomedical sensors. Adv. Drug Deliv. Rev. 65, 1933–1950 (2013).

    CAS  Article  Google Scholar 

  22. 22

    Iverson, N. M. et al. In vivo biosensing via tissue-localizable near-infrared-fluorescent single-walled carbon nanotubes. Nat. Nanotech. 8, 873–880 (2013).

    CAS  Article  Google Scholar 

  23. 23

    Wang, F., Dukovic, G., Brus, L. E. & Heinz, T. F. The optical resonances in carbon nanotubes arise from excitons. Science 308, 838–841 (2005).

    CAS  Article  Google Scholar 

  24. 24

    O’Connell, M. J. et al. Band gap fluorescence from individual single-walled carbon nanotubes. Science 297, 593–596 (2002).

    Article  Google Scholar 

  25. 25

    Cheong, W. F., Prahl, S. A. & Welch, A. J. A review of the optical properties of biological tissues. IEEE J. Sel. Top. Quantum 26, 2166–2185 (1990).

    Article  Google Scholar 

  26. 26

    Heller, D. A. et al. Optical detection of DNA conformational polymorphism on single-walled carbon nanotubes. Science 311, 508–511 (2006).

    CAS  Article  Google Scholar 

  27. 27

    Barone, P. W., Baik, S., Heller, D. A. & Strano, M. S. Near-infrared optical sensors based on single-walled carbon nanotubes. Nat. Mater. 4, 86–92 (2005).

    CAS  Article  Google Scholar 

  28. 28

    Cognet, L. et al. Stepwise quenching of exciton fluorescence in carbon nanotubes by single-molecule reactions. Science 316, 1465–1468 (2007).

    CAS  Article  Google Scholar 

  29. 29

    Roxbury, D. et al. Hyperspectral microscopy of near-infrared fluorescence enables 17-chirality carbon nanotube imaging. Sci. Rep. 5, 14167 (2015).

    CAS  Article  Google Scholar 

  30. 30

    Olive, V. et al. miR-19 is a key oncogenic component of mir-17-92. Genes Dev. 23, 2839–2849 (2009).

    CAS  Article  Google Scholar 

  31. 31

    Zheng, M. et al. Structure-based carbon nanotube sorting by sequence-dependent DNA assembly. Science 302, 1545–1548 (2003).

    CAS  Article  Google Scholar 

  32. 32

    Bachilo, S. M. et al. Structure-assigned optical spectra of single-walled carbon nanotubes. Science 298, 2361–2366 (2002).

    CAS  Article  Google Scholar 

  33. 33

    Campbell, J. F., Tessmer, I., Thorp, H. H. & Erie, D. A. Atomic force microscopy studies of DNA-wrapped carbon nanotube structure and binding to quantum dots. J. Am. Chem. Soc. 130, 10648–10655 (2008).

    CAS  Article  Google Scholar 

  34. 34

    Roxbury, D., Jena, P. V., Shamay, Y., Horoszko, C. P. & Heller, D. A. Cell membrane proteins modulate the carbon nanotube optical bandgap via surface charge accumulation. ACS Nano 10, 499–506 (2016).

    CAS  Article  Google Scholar 

  35. 35

    Yang, R. et al. Carbon nanotube-quenched fluorescent oligonucleotides: probes that fluoresce upon hybridization. J. Am. Chem. Soc. 130, 8351–8358 (2008).

    CAS  Article  Google Scholar 

  36. 36

    Heller, D. A. et al. Peptide secondary structure modulates single-walled carbon nanotube fluorescence as a chaperone sensor for nitroaromatics. Proc. Natl Acad. Sci. USA 108, 8544–8549 (2011).

    CAS  Article  Google Scholar 

  37. 37

    Moore, V. C. et al. Individually suspended single-walled carbon nanotubes in various surfactants. Nano Lett. 3, 1379–1382 (2003).

    CAS  Article  Google Scholar 

  38. 38

    McDonald, J. S., Milosevic, D., Reddi, H. V., Grebe, S. K. & Algeciras-Schimnich, A. Analysis of circulating microRNA: preanalytical and analytical challenges. Clin. Chem. 57, 833–840 (2011).

    CAS  Article  Google Scholar 

  39. 39

    Gregory, P. A. et al. The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1. Nat. Cell Biol. 10, 593–601 (2008).

    CAS  Article  Google Scholar 

  40. 40

    Landry, M. P. et al. Comparative dynamics and sequence dependence of DNA and RNA binding to single walled carbon nanotubes. J. Phys. Chem. C 119, 10048–10058 (2015).

    CAS  Article  Google Scholar 

  41. 41

    Johnson, R. R., Johnson, A. T. & Klein, M. L. The nature of DNA-base-carbon-nanotube interactions. Small 6, 31–34 (2010).

    CAS  Article  Google Scholar 

  42. 42

    Cognet, L., Tsyboulski, D. A. & Weisman, R. B. Subdiffraction far-field imaging of luminescent single-walled carbon nanotubes. Nano Lett. 8, 749–753 (2008).

    CAS  Article  Google Scholar 

  43. 43

    Machinek, R. R., Ouldridge, T. E., Haley, N. E., Bath, J. & Turberfield, A. J. Programmable energy landscapes for kinetic control of DNA strand displacement. Nat. Commun. 5, 5324 (2014).

    CAS  Article  Google Scholar 

  44. 44

    Srinivas, N. et al. On the biophysics and kinetics of toehold-mediated DNA strand displacement. Nucleic Acids Res. 41, 10641–10658 (2013).

    CAS  Article  Google Scholar 

  45. 45

    Johnson-Buck, A. et al. Kinetic fingerprinting to identify and count single nucleic acids. Nat. Biotechnol. 33, 730–732 (2015).

    CAS  Article  Google Scholar 

  46. 46

    Toiyama, Y. et al. Serum miR-21 as a diagnostic and prognostic biomarker in colorectal cancer. J. Natl Cancer Inst. 105, 849–859 (2013).

    CAS  Article  Google Scholar 

  47. 47

    Arroyo, J. D. et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc. Natl Acad. Sci. USA 108, 5003–5008 (2011).

    CAS  Article  Google Scholar 

  48. 48

    Turchinovich, A., Weiz, L., Langheinz, A. & Burwinkel, B. Characterization of extracellular circulating microRNA. Nucleic Acids Res. 39, 7223–7233 (2011).

    CAS  Article  Google Scholar 

  49. 49

    Seelig, G., Soloveichik, D., Zhang, D. Y. & Winfree, E. Enzyme-free nucleic acid logic circuits. Science 314, 1585–1588 (2006).

    CAS  Article  Google Scholar 

  50. 50

    Joshi, G. K. et al. Label-free nanoplasmonic-based short noncoding RNA sensing at attomolar concentrations allows for quantitative and highly specific assay of microRNA-10b in biological fluids and circulating exosomes. ACS Nano 9, 11075–11089 (2015).

    CAS  Article  Google Scholar 

  51. 51

    Wanunu, M. et al. Rapid electronic detection of probe-specific microRNAs using thin nanopore sensors. Nat. Nanotech. 5, 807–814 (2010).

    CAS  Article  Google Scholar 

  52. 52

    Gunnarsson, A., Jonsson, P., Marie, R., Tegenfeldt, J. O. & Hook, F. Single-molecule detection and mismatch discrimination of unlabeled DNA targets. Nano Lett. 8, 183–188 (2008).

    CAS  Article  Google Scholar 

  53. 53

    Schirle, N. T. & MacRae, I. J. The crystal structure of human Argonaute2. Science 336, 1037–1040 (2012).

    CAS  Article  Google Scholar 

  54. 54

    Schirle, N. T., Sheu-Gruttadauria, J. & MacRae, I. J. Structural basis for microRNA targeting. Science 346, 608–613 (2014).

    CAS  Article  Google Scholar 

  55. 55

    Koshkin, A. A. et al. LNA (locked nucleic acids): synthesis of the adenine, cytosine, guanine, 5-methylcytosine, thymine and uracil bicyclonucleoside monomers, oligomerisation, and unprecedented nucleic acid recognition. Tetrahedron 54, 3607–3630 (1998).

    CAS  Article  Google Scholar 

  56. 56

    Nielsen, P. E., Egholm, M., Berg, R. H. & Buchardt, O. Sequence-selective recognition of DNA by strand displacement with a thymine-substituted polyamide. Science 254, 1497–1500 (1991).

    CAS  Article  Google Scholar 

  57. 57

    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  Google Scholar 

  58. 58

    Sugita, Y. & Okamoto, Y. Replica-exchange molecular dynamics method for protein folding. Chem. Phys. Lett. 314, 141–151 (1999).

    CAS  Article  Google Scholar 

  59. 59

    Bonomi, M. & Parrinello, M. Enhanced sampling in the well-tempered ensemble. Phys. Rev. Lett. 104, 190601 (2010).

    Article  Google Scholar 

  60. 60

    Case, D. A. et al. Amber 2016 (Univ. California, 2016).

  61. 61

    Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. Model. 14, 33–38 (1996).

    CAS  Article  Google Scholar 

  62. 62

    Berendsen, H. J. C., Vanderspoel, D. & Vandrunen, R. Gromacs — a message-passing parallel molecular-dynamics implementation. Comput. Phys. Commun. 91, 43–56 (1995).

    CAS  Article  Google Scholar 

  63. 63

    Hess, B., Kutzner, C., van der Spoel, D. & Lindahl, E. GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory Comput. 4, 435–447 (2008).

    CAS  Article  Google Scholar 

  64. 64

    Hart, K. et al. Optimization of the CHARMM additive force field for DNA: improved treatment of the BI/BII conformational equilibrium. J. Chem. Theory Comput. 8, 348–362 (2012).

    CAS  Article  Google Scholar 

  65. 65

    Essmann, U. et al. A smooth particle mesh Ewald method. J. Chem. Phys. 103, 8577–8593 (1995).

    CAS  Article  Google Scholar 

  66. 66

    Michaud-Agrawal, N., Denning, E. J., Woolf, T. B. & Beckstein, O. MDAnalysis: a toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 32, 2319–2327 (2011).

    CAS  Article  Google Scholar 

  67. 67

    Zheng, M. et al. DNA-assisted dispersion and separation of carbon nanotubes. Nat. Mater. 2, 338–342 (2003).

    CAS  Article  Google Scholar 

  68. 68

    Harvey, J. et al. Dataset for ‘A carbon nanotube reporter of microRNA hybridization events in vivo’. figsharehttp://dx.doi.org/10.6084/m9.figshare.4567945 (2017).

Download references

Acknowledgements

This work was supported by the US National Institutes of Health (NIH) Director’s New Innovator Award (DP2-HD075698), NIH/National Cancer Institute (NCI) Cancer Center Support Grant (P30-CA008748), the Center for Molecular Imaging and Nanotechnology, the Louis V. Gerstner Jr. Young Investigator’s Fund, the Experimental Therapeutics Center, the Alan and Sandra Gerry Metastasis Research Initiative, Cycle for Survival, the Frank A. Howard Scholars Program, the Honorable Tina Brozman Foundation for Ovarian Cancer Research, the Byrne Research Fund, the Anna Fuller Fund, Mr William H. Goodwin and Mrs Alice Goodwin and the Commonwealth Foundation for Cancer Research, and the Imaging and Radiation Sciences Program at Memorial Sloan Kettering Cancer Center. Molecular simulation work was performed at Lehigh University and is supported by the US Department of Energy (DOE) Office of Science, Basic Energy Sciences (BES), and Division of Material Sciences and Engineering, under award DE-SC0013979. Use of the high-performance computing capabilities of the Extreme Science and Engineering Discovery Environment (XSEDE) was supported by the US National Science Foundation under grant number TG-MCB-120014. This research also used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported under contract no. DE-AC02-05CH11231. P.V.J. was supported by the NCI Grant NIH T32 Training Grant 2T32CA062948-21. H.A.B. was supported by a Medical Scientist Training Program grant from the National Institute of General Medical Sciences of the NIH under award number T32GM007739 to the Weill Cornell/Rockefeller/Sloan-Kettering Tri-Institutional MD-PhD Program. R.M.W. was supported by the Ovarian Cancer Research Fund Alliance (Anna Schreiber Mentored Investigator Award 370463). D.R. was supported by an American Cancer Society 2013 Roaring Fork Valley Research Fellowship and grant no. P20GM103430 from the National Institute of General Medical Sciences of the NIH. We thank the Molecular Cytology Core Facility at Memorial Sloan Kettering Cancer Center and N. Paknejad for the atomic force microscopy measurements.

Author information

Affiliations

Authors

Contributions

J.D.H., P.V.J. and D.A.H. conceived the research, designed the experiments and analysed the data. J.D.H. and H.A.B. performed the experiments. Programs to facilitate data analysis were written by P.V.J. and D.R. Molecular dynamics simulations and analysis were designed and conducted by G.H.Z., D.R. and J.M. Assistance with in vivo work was provided by R.M.W. The probe system for in vivo measurements was designed and built by T.V.G. and D.A.H. The manuscript was prepared and written by J.D.H. and D.A.H.; all authors contributed to editing the manuscript. D.A.H. supervised the project.

Corresponding author

Correspondence to Daniel A. Heller.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary text, figures and tables. (PDF 4966 kb)

Supplementary Video 1

Molecular dynamics simulation showing that a single-stranded portion of the GT15mir19 oligomer is bound to the nanotube, and that the hybridized construct remains stable on the nanotube surface. (MPG 59544 kb)

Supplementary Video 2

Molecular dynamics simulation showing that the entire GT15mir19 oligomer is bound to the surface and wraps the nanotube, with the nucleobases orienting closely to the nanotube surface in a parallel orientation. (MPG 38660 kb)

Supplementary Video 3

Molecular dynamics simulations of hybridized miR-19, without the (GT)15 nanotube binding domain, in the presence of the nanotube. (MPG 19152 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Harvey, J., Jena, P., Baker, H. et al. A carbon nanotube reporter of microRNA hybridization events in vivo. Nat Biomed Eng 1, 0041 (2017). https://doi.org/10.1038/s41551-017-0041

Download citation

Further reading

Search

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing