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.
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References
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).
Parrella, P., Zangen, R., Sidransky, D. & Nicol, T. Molecular analysis of peritoneal fluid in ovarian cancer patients. Mod. Pathol. 16, 636–640 (2003).
Mitchell, P. S. et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc. Natl Acad. Sci. USA 105, 10513–10518 (2008).
Dawson, S. J. et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N. Engl. J. Med. 368, 1199–1209 (2013).
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).
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).
Deras, I. L. et al. PCA3: a molecular urine assay for predicting prostate biopsy outcome. J. Urol. 179, 1587–1592 (2008).
Weber, J. A. et al. The microRNA spectrum in 12 body fluids. Clin. Chem. 56, 1733–1741 (2010).
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).
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).
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).
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).
Lan, Y. F. et al. MicroRNA-494 reduces ATF3 expression and promotes AKI. J. Am. Soc. Nephrol. 23, 2012–2023 (2012).
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).
Pajek, J. et al. Cell-free DNA in the peritoneal effluent of peritoneal dialysis solutions. Ther. Apher. Dial. 14, 20–26 (2010).
Johnson, B. N. & Mutharasan, R. Biosensor-based microRNA detection: techniques, design, performance, and challenges. Analyst 139, 1576–1588 (2014).
Chen, C. et al. Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res. 33, e179 (2005).
Baker, M. MicroRNA profiling: separating signal from noise. Nat. Methods 7, 687–692 (2010).
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).
Dong, H. et al. MicroRNA: function, detection, and bioanalysis. Chem. Rev. 113, 6207–6233 (2013).
Kruss, S. et al. Carbon nanotubes as optical biomedical sensors. Adv. Drug Deliv. Rev. 65, 1933–1950 (2013).
Iverson, N. M. et al. In vivo biosensing via tissue-localizable near-infrared-fluorescent single-walled carbon nanotubes. Nat. Nanotech. 8, 873–880 (2013).
Wang, F., Dukovic, G., Brus, L. E. & Heinz, T. F. The optical resonances in carbon nanotubes arise from excitons. Science 308, 838–841 (2005).
O’Connell, M. J. et al. Band gap fluorescence from individual single-walled carbon nanotubes. Science 297, 593–596 (2002).
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).
Heller, D. A. et al. Optical detection of DNA conformational polymorphism on single-walled carbon nanotubes. Science 311, 508–511 (2006).
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).
Cognet, L. et al. Stepwise quenching of exciton fluorescence in carbon nanotubes by single-molecule reactions. Science 316, 1465–1468 (2007).
Roxbury, D. et al. Hyperspectral microscopy of near-infrared fluorescence enables 17-chirality carbon nanotube imaging. Sci. Rep. 5, 14167 (2015).
Olive, V. et al. miR-19 is a key oncogenic component of mir-17-92. Genes Dev. 23, 2839–2849 (2009).
Zheng, M. et al. Structure-based carbon nanotube sorting by sequence-dependent DNA assembly. Science 302, 1545–1548 (2003).
Bachilo, S. M. et al. Structure-assigned optical spectra of single-walled carbon nanotubes. Science 298, 2361–2366 (2002).
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).
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).
Yang, R. et al. Carbon nanotube-quenched fluorescent oligonucleotides: probes that fluoresce upon hybridization. J. Am. Chem. Soc. 130, 8351–8358 (2008).
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).
Moore, V. C. et al. Individually suspended single-walled carbon nanotubes in various surfactants. Nano Lett. 3, 1379–1382 (2003).
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).
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).
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).
Johnson, R. R., Johnson, A. T. & Klein, M. L. The nature of DNA-base-carbon-nanotube interactions. Small 6, 31–34 (2010).
Cognet, L., Tsyboulski, D. A. & Weisman, R. B. Subdiffraction far-field imaging of luminescent single-walled carbon nanotubes. Nano Lett. 8, 749–753 (2008).
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).
Srinivas, N. et al. On the biophysics and kinetics of toehold-mediated DNA strand displacement. Nucleic Acids Res. 41, 10641–10658 (2013).
Johnson-Buck, A. et al. Kinetic fingerprinting to identify and count single nucleic acids. Nat. Biotechnol. 33, 730–732 (2015).
Toiyama, Y. et al. Serum miR-21 as a diagnostic and prognostic biomarker in colorectal cancer. J. Natl Cancer Inst. 105, 849–859 (2013).
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).
Turchinovich, A., Weiz, L., Langheinz, A. & Burwinkel, B. Characterization of extracellular circulating microRNA. Nucleic Acids Res. 39, 7223–7233 (2011).
Seelig, G., Soloveichik, D., Zhang, D. Y. & Winfree, E. Enzyme-free nucleic acid logic circuits. Science 314, 1585–1588 (2006).
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).
Wanunu, M. et al. Rapid electronic detection of probe-specific microRNAs using thin nanopore sensors. Nat. Nanotech. 5, 807–814 (2010).
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).
Schirle, N. T. & MacRae, I. J. The crystal structure of human Argonaute2. Science 336, 1037–1040 (2012).
Schirle, N. T., Sheu-Gruttadauria, J. & MacRae, I. J. Structural basis for microRNA targeting. Science 346, 608–613 (2014).
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).
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).
Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).
Sugita, Y. & Okamoto, Y. Replica-exchange molecular dynamics method for protein folding. Chem. Phys. Lett. 314, 141–151 (1999).
Bonomi, M. & Parrinello, M. Enhanced sampling in the well-tempered ensemble. Phys. Rev. Lett. 104, 190601 (2010).
Case, D. A. et al. Amber 2016 (Univ. California, 2016).
Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. Model. 14, 33–38 (1996).
Berendsen, H. J. C., Vanderspoel, D. & Vandrunen, R. Gromacs — a message-passing parallel molecular-dynamics implementation. Comput. Phys. Commun. 91, 43–56 (1995).
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).
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).
Essmann, U. et al. A smooth particle mesh Ewald method. J. Chem. Phys. 103, 8577–8593 (1995).
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).
Zheng, M. et al. DNA-assisted dispersion and separation of carbon nanotubes. Nat. Mater. 2, 338–342 (2003).
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).
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.
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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.
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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)
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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
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DOI: https://doi.org/10.1038/s41551-017-0041
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