Brief Communication | Published:

Single-molecule motions enable direct visualization of biomolecular interactions in solution

Nature Methods volume 11, pages 555558 (2014) | Download Citation

Abstract

Biomolecular interactions are generally accompanied by modifications in size and charge of biomolecules at the nanometer scale. Here we describe a single-molecule method to sense these changes in real time based on statistical learning of diffusive and electric field–induced motion parameters of a trapped molecule in solution. We demonstrate the approach by resolving a monomer-trimer mixture along a protein dissociation pathway and visualizing the binding-unbinding kinetics of a single DNA molecule.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    Curr. Opin. Biotechnol. 22, 75–80 (2011).

  2. 2.

    , & Nat. Struct. Mol. Biol. 19, 623–627 (2012).

  3. 3.

    et al. Nano Lett. 10, 4756–4761 (2010).

  4. 4.

    & Nat. Methods 4, 319–321 (2007).

  5. 5.

    & Annu. Rev. Phys. Chem. 63, 595–617 (2012).

  6. 6.

    , & Biopolymers 17, 361–367 (1978).

  7. 7.

    et al. Eur. Phys. Lett. 83, 46001 (2008).

  8. 8.

    & Proc. Natl. Acad. Sci. USA 103, 4362–4365 (2006).

  9. 9.

    & ACS Nano 5, 5792–5799 (2011).

  10. 10.

    & Proc. Natl. Acad. Sci. USA 108, 8937–8942 (2011).

  11. 11.

    & J. Phys. Chem. B 117, 4641–4648 (2012).

  12. 12.

    Appl. Phys. B 71, 773–777 (2000).

  13. 13.

    Extending Expectation Propagation for Graphical Models. PhD Thesis, Massachusetts Institute of Technology (2004).

  14. 14.

    & J. Time Ser. Anal. 3, 253–264 (1982).

  15. 15.

    , & Biochemistry 26, 243–245 (1987).

  16. 16.

    , , , & Arch. Microbiol. 111, 225–238 (1977).

  17. 17.

    & Nucleic Acids Res. 33, W577–W581 (2005).

  18. 18.

    & Nat. Chem. 2, 179–186 (2010).

  19. 19.

    , , & Chem. Soc. Rev. 10.1039/C3CS60207A (10 September 2013).

  20. 20.

    et al. Nat. Methods 10.1038/nmeth.2809 (19 January 2014).

  21. 21.

    & Opt. Express 16, 6941–6956 (2008).

  22. 22.

    , & BioTechniques 34, 505–510 (2003).

  23. 23.

    & Electrophoresis 22, 644–655 (2001).

  24. 24.

    Stat. Sci. 19, 140–155 (2004).

  25. 25.

    & IEEE Trans. Wirel. Comm. 6, 348–355 (2007).

  26. 26.

    , & Ann. Stat. 38, 2916–2957 (2010).

  27. 27.

    Machine Learning: a Probabilistic Perspective (The MIT Press, 2012).

  28. 28.

    , & Nat. Methods 3, 891–893 (2006).

  29. 29.

    , & Biophys. J. 94, 1826–1835 (2008).

Download references

Acknowledgements

We thank Y. Jiang for help with high-performance liquid chromatography purification, and C. Calderon, G. Schlau-Cohen, H.-Y. Yang, S. Bockenhauer and S.J. Sahl for discussion. This work is funded in part by the Division of Chemical Sciences, Geosciences and Biosciences, Office of Basic Energy Sciences of the US Department of Energy through grant DE-FG02-07ER15892.

Author information

Affiliations

  1. Department of Chemistry, Stanford University, Stanford, California, USA.

    • Quan Wang
    •  & W E Moerner
  2. Department of Electrical Engineering, Stanford University, Stanford, California, USA.

    • Quan Wang

Authors

  1. Search for Quan Wang in:

  2. Search for W E Moerner in:

Contributions

Q.W. and W.E.M. conceived the project, discussed the results and wrote the manuscript. Q.W. designed and performed the experiments and data analysis.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to W E Moerner.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–19, Supplementary Tables 1–5 and Supplementary Notes 1–7

Videos

  1. 1.

    Real-time estimation of single-molecule transport coefficients in an anti-Brownian electrokinetic trap.

    Screen recording during an experiment trapping single Alexa647 labeled 10nt-ssDNA molecules without complementary strand. Intensity (I) is photon counts every 10 ms, diffusion coefficient (D) and electrokinetic mobility (μx and μy) are estimated every 5,000 photons using the real-time EM algorithm. Occasional intensity spikes are indicative of transient co-occupancy of two objects in the trap. Time axis units: 10 ms

  2. 2.

    Real-time visualization of single-DNA binding-unbinding dynamics.

    Screen recording during an experiment trapping single 10nt-ssDNA in presence of unlabeled complementary strand (2 μM of 24nt-10comp). Frequent anti-correlated dynamics in diffusion coefficient (D) and electrokinetic mobility (μx and μy) visualize transitions between ssDNA (blue band) and dsDNA (red band). Time axis units: 10 ms

Text files

  1. 1.

    Supplementary Software

    C program implementation of the parameter estimation algorithm.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nmeth.2882

Further reading