DNA rendering of polyhedral meshes at the nanoscale

Abstract

It was suggested1 more than thirty years ago that Watson–Crick base pairing might be used for the rational design of nanometre-scale structures from nucleic acids. Since then, and especially since the introduction of the origami technique2, DNA nanotechnology has enabled increasingly more complex structures3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18. But although general approaches for creating DNA origami polygonal meshes and design software are available14,16,17,19,20,21, there are still important constraints arising from DNA geometry and sense/antisense pairing, necessitating some manual adjustment during the design process. Here we present a general method of folding arbitrary polygonal digital meshes in DNA that readily produces structures that would be very difficult to realize using previous approaches. The design process is highly automated, using a routeing algorithm based on graph theory and a relaxation simulation that traces scaffold strands through the target structures. Moreover, unlike conventional origami designs built from close-packed helices, our structures have a more open conformation with one helix per edge and are therefore stable under the ionic conditions usually used in biological assays.

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Figure 1: Design paradigm and automated workflow for scaffold-routeing sequence design of origami 3D meshes.
Figure 2: 3D meshes rendered in DNA.
Figure 3: Cryo-electron microscopy reveals the hollow characteristics and details of polyhedral meshes.
Figure 4: Mesh origami folds in and is fully stable in physiological buffers.

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Acknowledgements

This work was funded through grants from the Swedish Research Council (grants 2010-5060 and 2013-5883 to B.H.), the Swedish Foundation for Strategic Research (grant FFL12-0219 to B.H.) and the Knut and Alice Wallenberg foundation (Academy Fellow grant KAW2014.0241 to B.H.). E.B. was also funded by a Wallenberg Scholars grant to O. Inganäs. The work of A.M. was supported by the Helsinki Doctoral Education Network on Information and Communications Technology. We acknowledge the computational resources provided by the Aalto Science-IT project and the use of the Facility for EM Tomography at the Karolinska Institutet. A.M., E.C. and P.O. thank G. García Pérez for help in implementing early variants of the scaffold routing software. We thank P. Kumar Areddy (Karolinska Institutet) and A.-L. Bank Kodal and K. Gothelf (Aarhus University) for help with early experimental testing.

Author information

B.H. conceived and designed the study. P.O., E.C. and A.M. performed the theoretical work. E.B. performed the experimental work. A.M. performed most of the algorithm implementation. J.G. collaborated on the algorithm implementation and implemented the relaxation method and the vHelix plug-in. S.M. performed the cryo-electron tomography and tomography with help from E.B. All authors contributed to the writing of the manuscript.

Correspondence to Björn Högberg.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Comparison with previous strategy for polygonal DNA origami.

a, Previous strategies for folding polygonal DNA origami have relied on folding the circular single-stranded DNA into a tree-like shape, where each branch is composed of an even number of helices (two in this illustration), these branches are then connected using helper joins as in b, where staple strands (in blue) bridge the gap between the distant parts of the scaffold, to yield the final polyhedral structure: the tetrahedron to the right in this example. c, The target shape and its flattened Schlegel representation. d, Previous methods have introduced helper joins in N − 1 of the edges, where N is the number of faces in the structure. Notably, the structures presented in this work would require on the order of 100 helper joins. A large number of helper joins is commonly believed to increase aggregation problems owing to the sticky ends produced as intermediates during folding. e, The strategy presented in this work. The goal is to route the entire scaffold through all the edges of the mesh, without crossing and with preferably only one traverse per edge. *It turns out that one helix per edge is not possible for all meshes (as described in the main text, Fig. 1 and in Supplementary Note 1). Odd-degree vertices require some edges to be traversed twice by the scaffold routeing.

Extended Data Figure 2 An overview of vHelix.

To be able to work with non-canonical origami designs, we implemented software that would allow free-form manipulation of helices directly in 3D space. The software was implemented as a plug-in for Autodesk Maya (several versions) and is available at http://www.vhelix.net. The associated source code can be found at https://github.com/gardell/vHelix. a, The interface in vHelix when viewing the design of the ball structure. b The ‘Helix’ menu provides most of the functionality, such as the ability to create new helices, disconnect and connect bases. c, Close-up of a connected vertex. Selecting a base shows its associated connectivity by highlighting all connected bases and displaying the associated sequence if a sequence has been applied. d, Using the “apply sequence” command to one of the strands (the scaffold), the plug-in calculates the sequence of all paired bases (on the staple strands) and subsequently the command “export strands” generates a spreadsheet file containing the staple-strand sequences. The physical dimensions of the DNA model follows what is usually used in DNA nanotechnology design processes (that is, a 2-nm helical radius, a 0.334-nm rise, a 34.286° pitch and a 155° minor groove). e, Overlaying the model with crystallography data from the literature39 shows that the model fits natural DNA well.

Extended Data Figure 3 Design pipeline overview.

a, We started the designs in Autodesk Maya, importing or modelling our own 3D polygon mesh object. b, The triangulation step is not mandatory because the scaffold routeing and further processing is not limited to triangulated meshes, but it is used for all structures reported here to achieve extra rigidity by triangulation. Steps ce are implemented as a series of scripts that process the mesh exported from the 3D design software. c, All odd-degree vertices are joined by helper edges using a minimum weight perfect matching algorithm (see Supplementary Note 1). d, The re-conditioned mesh is fed to a script implementing the A-trails routeing algorithm (see Supplementary Note 1). e, After scaffold routeing, the physical relaxation model reads the routed path. Up until now, the mesh has been treated as an abstract graph; in the relaxation step, however, an input is required to set the physical size of the desired DNA rendering, that is, the user sets a scaling value to fit the mesh to the scaffold available for the folding. The relaxation simulation and length-modification scheme (described in more detail in Supplementary Note 2) will rotate and shorten/lengthen some edges to find an overall best fit to the desired 3D shape while accounting for strain between nucleotides in the vertices. The output of the relaxation/length modification optimization is a file readable by vHelix, a plug-in for Autodesk Maya. f, As the file is imported into vHelix, the user has the option of automatically positioning staple-strand break-points by stating parameters for maximum staple length and the minimum length of edges with breakpoints. Alternatively, the staple-strand breakpoints can be edited manually in vHelix after importing. g, The DNA sequences of all staple strands given a scaffold input is calculated and exported to a spreadsheet by vHelix. h, The mixing of staple strands and scaffold is done by hand but a pipetting robot could conceivably also make this last step highly automated.

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Supplementary Information

This file contains Supplementary Notes 1–2, Supplementary Figures 1–26 and Supplementary Tables 1–8. (PDF 18428 kb)

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Benson, E., Mohammed, A., Gardell, J. et al. DNA rendering of polyhedral meshes at the nanoscale. Nature 523, 441–444 (2015). https://doi.org/10.1038/nature14586

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