Programmable disorder in random DNA tilings
Abstract
Scaling up the complexity and diversity of synthetic molecular structures will require strategies that exploit the inherent stochasticity of molecular systems in a controlled fashion. Here we demonstrate a framework for programming random DNA tilings and show how to control the properties of global patterns through simple, local rules. We constructed three general forms of planar network—random loops, mazes and trees—on the surface of self-assembled DNA origami arrays on the micrometre scale with nanometre resolution. Using simple molecular building blocks and robust experimental conditions, we demonstrate control of a wide range of properties of the random networks, including the branching rules, the growth directions, the proximity between adjacent networks and the size distribution. Much as combinatorial approaches for generating random one-dimensional chains of polymers have been used to revolutionize chemical synthesis and the selection of functional nucleic acids, our strategy extends these principles to random two-dimensional networks of molecules and creates new opportunities for fabricating more complex molecular devices that are organized by DNA nanostructures.
Additional Information
© 2016 Macmillan Publishers Limited. Received 7 July 2016; accepted 18 October 2016; published online 28 November 2016. We thank S. Wang for designing the fish and gear tile (Supplementary Fig. 38) and J. Parkin, A. Karan and S. Wang for designing and creating a heart shape that is self-assembled from square DNA origami tiles (Supplementary Fig. 68). We thank E. Winfree, P. Rothemund, D. Soloveichik and A. Condon for critique on the manuscript. G.T. was supported by an NSF grant (1317694). P.P. was supported by a NIH/NRSA training grant (5 T32 GM07616). L.Q. was supported by a Career Award at the Scientific Interface from the Burroughs Wellcome Fund (1010684) and a Faculty Early Career Development Award from the NSF (1351081). Author Contributions: G.T. and P.P. performed the experiments and analysed the data. P.P. performed the simulations and developed the software tools. G.T., P.P. and L.Q. designed the systems and wrote the manuscript. L.Q. initiated and guided the project. These authors contributed equally to this work: Grigory Tikhomirov & Philip Petersen. Code availability. The code for the yield calculations can be accessed online at http://qianlab.caltech.edu/YieldCalculator/. The authors declare no competing financial interests.Attached Files
Supplemental Material - nnano.2016.256-s1.pdf
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Additional details
- Eprint ID
- 71035
- DOI
- 10.1038/nnano.2016.256
- Resolver ID
- CaltechAUTHORS:20161012-163039195
- NSF
- CCF-1317694
- NIH Predoctoral Fellowship
- 5 T32 GM07616
- Burroughs Wellcome Fund
- 1010684
- NSF
- CCF-1351081
- Created
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2016-11-29Created from EPrint's datestamp field
- Updated
-
2021-11-11Created from EPrint's last_modified field