Autonomously designed free-form 2D DNA origami

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Autonomously designed free-form 2D DNA origami by Hyungmin Jun, Fei Zhang, Tyson Shepherd, Sakul Ratanalert, Xiaodong Qi, Hao Yan, and Mark Bathe Science Volume 5(1):eaav0655 January 2, 2019 Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

Fig. 1 Automated design of 2D wireframe scaffolded DNA origami objects. Automated design of 2D wireframe scaffolded DNA origami objects. (A) Arbitrary target geometries can be specified in two ways: free-form boundary design (top), defining only the border of the target object, with the internal mesh geometry designed automatically, or free-form boundary and internal design (bottom), specifying the complete internal and external boundary geometry using piecewise continuous lines. (B) 2D line-based geometric representations are used as input to the algorithm that performs automatic scaffold and staple routings, converting each edge into two parallel duplexes joined by antiparallel crossovers. The single-stranded scaffold is routed throughout the entire origami object, with staple strands ranging in length from 20 to 60 nucleotides (nt; mean length, 40 nt). The circular maps illustrate the connectivities of staples hybridized to the circular scaffold in the final, self-assembled object, where each terminal point of the connecting staple line is located at the middle of its corresponding double-stranded DNA (dsDNA) domain in the folded line. caDNAno input files are also generated by the algorithm for manual editing of staple sequences or the scaffold routing path. (C) Staple sequences generated by the algorithm are used with the input scaffold to synthesize the programmed 2D wireframe object using standard one-pot thermal annealing. Hyungmin Jun et al. Sci Adv 2019;5:eaav0655 Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

Fig. 2 Automatic scaffold routing and staple sequence design. Automatic scaffold routing and staple sequence design. (A) Step 1: Double-line segments representing two parallel B-form DNA duplexes are generated along the edges of the target wireframe geometry. Step 2: Endpoints are joined such that each duplex becomes part of a loop (blue) containing all possible scaffold double crossovers (red) between closed loops. Step 3: The dual graph of the loop-crossover structure is introduced by converting each loop into a node and each double crossover into an edge. Step 4: The spanning tree of the dual graph is computed and inverted to route the ssDNA scaffold throughout the entire origami object automatically (position of the scaffold nick is indicated by a solid red circle), which enables the assignment of complementary staple strands. Step 5: Last, a 3D atomic-level structural model is generated, assuming canonical B-form DNA duplexes. (B) Design using continuous edge length for asymmetric and irregular shapes. The target geometry can be modeled in two ways: Using a discrete edge length consisting of multiples of 10.5 bp rounded to the nearest nucleotide or a continuous edge length with no constraint on length. Continuous edge lengths enable the design of objects with arbitrary edge lengths, which require duplex extensions to fill gaps in vertices. Both edge types were experimentally tested by folding and visualizing with AFM (figs. S6 to S8). The highest folding yields occurred with continuous edge length particles with unpaired nucleotides at the vertices. Excess scaffold is apparent in the AFM images at the position of the scaffold nick indicated in the scaffold routing diagram in (A). Scale bars, 150 nm. Hyungmin Jun et al. Sci Adv 2019;5:eaav0655 Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

Fig. 3 Designing variable vertex numbers, edge lengths, and mesh patterns. Designing variable vertex numbers, edge lengths, and mesh patterns. (A to C) Variable vertex numbers consisting of four-, five-, or six-arm junctions (A), variable edge lengths of 42, 63, and 84 bp (B), and variable mesh patterns, including quadrilateral, constant direction triangular, and mixed-direction triangular meshes (C), can be used. A mechanical model of the curved arm geometry predicts flexibility using the (left) constant direction triangular mesh pattern, with increased in-plane mechanical stiffness introduced by the (right) mixed-direction triangular mesh pattern, demonstrating the importance of internal mesh geometry on overall in-plane flexibility (fig. S37). Scale bars, 20 nm (atomic structures) and 50 and 150 nm (zoom-in and zoom-out AFM images, respectively). Hyungmin Jun et al. Sci Adv 2019;5:eaav0655 Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

Fig. 4 Fully automatic sequence design of 15 diverse scaffolded origami wireframe objects. Fully automatic sequence design of 15 diverse scaffolded origami wireframe objects. Target 2D wireframe objects and DNA-based atomic models of nanostructures are shown with (blue) triangular, (red) quadrilateral, and (yellow) N-polygonal meshes, where N is the number of sides of the discrete mesh element. Representative AFM images for a square lattice and honeycomb lattice with triangular cavities, a rhombic tiling and a quarter circle with quadrilateral cavities, and a Cairo pentagonal tiling and lotus with N-polygon cavities are shown. Scale bars, 20 nm (atomic structures) and 50 nm (AFM images). Hyungmin Jun et al. Sci Adv 2019;5:eaav0655 Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).