Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Autonomous molecular cascades for evaluation of cell surfaces

Nature Nanotechnology volume 8, pages 580–586 (2013)Cite this article

Subjects

Abstract

Molecular automata are mixtures of molecules that undergo precisely defined structural changes in response to sequential interactions with inputs1,2,3,4. Previously studied nucleic acid-based automata include game-playing molecular devices (MAYA automata3,5) and finite-state automata for the analysis of nucleic acids6, with the latter inspiring circuits for the analysis of RNA species inside cells7,8. Here, we describe automata based on strand-displacement9,10 cascades directed by antibodies that can analyse cells by using their surface markers as inputs. The final output of a molecular automaton that successfully completes its analysis is the presence of a unique molecular tag on the cell surface of a specific subpopulation of lymphocytes within human blood cells.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Design considerations for automata operating on cell surfaces.
Figure 2: Demonstration of automata assessing the presence of two cell-surface markers.
Figure 3: Demonstration of automata assessing the absence of a cell-surface marker.
Figure 4: Demonstration of automata assessing the presence of three markers (CD45, CD3 and CD8) on the surface of the cell.
Figure 5: Demonstrations of the potential for practical applications.

Similar content being viewed by others

References

  1. Rothemund, P. in 1st DIMACS Workshop on DNA Based Computers (eds Lipton, R. J. & Baum, E. B.) 75–120 DIMACS Series 27 (American Mathematical Society, 1996).

    Google Scholar 

  2. Benenson, Y. et al. Programmable and autonomous computing machine made of biomolecules. Nature 414, 430–434 (2001).

    Article  CAS  Google Scholar 

  3. Stojanovic, M. N. & Stefanovic, D. A deoxyribozyme-based molecular automaton. Nature Biotechnol. 21, 1069–1074 (2003).

    Article  CAS  Google Scholar 

  4. Wang, Z.-G., Elbaz, J., Remacle, F., Levine, R. D. & Willner, I. All DNA finite-state automata with finite memory. Proc. Natl Acad. Sci. USA 107, 21996–22001 (2010).

    Article  CAS  Google Scholar 

  5. Pei, R., Matamoros, E., Liu, M., Stefanovic, D. & Stojanovic, M. N. Training a molecular automaton to play a game. Nature Nanotech. 5, 773–777 (2010).

    Article  CAS  Google Scholar 

  6. Benenson, Y., Gil, B., Ben-Dor, U., Adar, R. & Shapiro, E. An autonomous molecular computer for logical control of gene expression. Nature 429, 423–429 (2004).

    Article  CAS  Google Scholar 

  7. Rinaudo, K. et al. A universal RNAi based logic evaluator that operates in mammalian cells. Nature Biotechnol. 25, 795–801 (2007).

    Article  CAS  Google Scholar 

  8. Xie, Z., Wroblewska, L., Prochazka, L., Weiss, R. & Benenson, Y. Multi-input RNAi-based logic circuit for identification of specific cancer cells. Science 333, 1307–1311 (2011).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  10. Qian, L., Winfree, E. & Bruck, J. Neural network computation with DNA strand displacement cascades. Nature 475, 368–372 (2011).

    Article  CAS  Google Scholar 

  11. Weiner, L. M., Surana, R. & Wang, S. Monocolonal antibodies: versatile platforms for cancer immunotherapy. Nature Rev. Immunol. 10, 317–327 (2010).

    Article  CAS  Google Scholar 

  12. Grützkau, A. & Radbruch, A. Small but mighty: how the MACS-technology based on nanosized superparamagnetic particles has helped to analyze the immune system within the last 20 years. Cytometry A 77, 643–647 (2010).

    Article  Google Scholar 

  13. Ichise, M. & Harris, P. E. Imaging of β-cell mass and function. J. Nucl. Med. 51, 1001–1004 (2010).

    Article  CAS  Google Scholar 

  14. De Silva, A. P. & Uchiayam, S. Molecular logic and computing. Nature Nanotech. 2, 399–410 (2007).

    Article  CAS  Google Scholar 

  15. Katz, E. & Privman, V. Enzyme-based logic systems for information processing. Chem. Soc. Rev. 39, 1835–1857 (2010).

    Article  CAS  Google Scholar 

  16. Bendall, S. C. et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687–696 (2011).

    Article  CAS  Google Scholar 

  17. Liu, H., Chumsae, C., Gaza-Bulseco, G., Hurkmans, K. & Radziejewski, C. H. Ranking the susceptibility of disulfide bonds in human IgG1 antibodies by reduction, differential alkylation, and LC-MS analysis. Anal. Chem. 82, 5219–5226 (2010).

    Article  CAS  Google Scholar 

  18. Holmes, D. Buy buy bispecific antibodies. Nature Rev. Drug Discov. 10, 798–800 (2011).

    Article  CAS  Google Scholar 

  19. Söderberg, O. et al. Direct observation of individual endogenous protein complexes in situ by proximity ligation. Nature Methods 3, 995–1000 (2006).

    Article  Google Scholar 

  20. Douglas, S. M., Bachelet, I. & Church, G. M. A logic-gated nanorobot for targeted transport of molecular payloads. Science 335, 831–834 (2012).

    Article  CAS  Google Scholar 

  21. Gu, H., Chao, J., Xiao, S.-J. & Seeman, N. C. A proximity-based programmable DNA nanoscale assembly line. Nature 465, 202–205 (2010).

    Article  CAS  Google Scholar 

  22. Lund, K. et al. Molecular robots guided by prescriptive landscapes. Nature 13, 206–210 (2010).

    Article  Google Scholar 

  23. Butler, Z. & Rizzi, A. in Distributed and Cellular Robots (Springer Handbook of Robotics, eds Siciliano, B. & Khatib, O.) Ch. 39, 911–920 (Springer, 2008).

    Book  Google Scholar 

Download references

Acknowledgements

The research presented in this manuscript, as well as past attempts that eventually led to the current design, was supported by the National Institutes of Health (R21CA128452, RC2CA147925, R21EB014477 and RGM104960, to S.R. and M.N.S.), the National Science Foundation (CCF-0218262, CCF-0621600, ECCS-1026591 and CBET-1033288), the National Aeronautics and Space Administration (NAS2-02039), and a fellowship from the Lymphoma and Leukemia Foundation (CPD Award) to M.N.S. The authors thank J. Loeb, E. Meffre and D. Stefanovic for their advice and comments on the manuscript.

Author information

Author notes

  1. Maria Rudchenko and Steven Taylor: These authors contributed equally to this work

Authors and Affiliations

  1. Research Division, Hospital for Special Surgery, 535E 70th Street, New York, 10021, New York, USA

    Maria Rudchenko, Steven Taylor, Alesia Dechkovskaia & Sergei Rudchenko

  2. Department of Medicine, Columbia University, 630W 168th Street, New York, 10032, New York, USA

    Payal Pallavi, Safana Khan, Vincent P. Butler Jr, Sergei Rudchenko & Milan N. Stojanovic

  3. Departments of Biomedical Engineering and Systems Biology, Columbia University, 630W 168th Street, New York, 10032, New York, USA

    Milan N. Stojanovic

Authors
  1. Maria Rudchenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Steven Taylor
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Payal Pallavi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alesia Dechkovskaia
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Safana Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Vincent P. Butler Jr
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sergei Rudchenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Milan N. Stojanovic
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.R. and S.T. are considered equal first authors. M.R. was the principal experimenter on cells, and S.T. carried out conjugations and optimized cascades in the solution phase. P.P. performed exploratory experiments. A.D. and S.K. carried out model experiments on beads. S.R. was in charge of flow cytometry experiments, and S.T. and M.N.S. were in charge of non-cell-based experiments. M.N.S. and V.B. designed and suggested early proposals for the implementation of molecular computing on cell surfaces and settled on lymphocytes as targets. M.R., S.T., S.R. and M.N.S. analysed the data. S.R. and M.N.S. were the primary designers of the experiments and are most responsible for the structure of the presentation in this paper. M.N.S. wrote the initial draft of the manuscript.

Corresponding authors

Correspondence to Sergei Rudchenko or Milan N. Stojanovic.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary information

Supplementary information (PDF 3083 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rudchenko, M., Taylor, S., Pallavi, P. et al. Autonomous molecular cascades for evaluation of cell surfaces. Nature Nanotech 8, 580–586 (2013). https://doi.org/10.1038/nnano.2013.142

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nnano.2013.142

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research