Paul W. K. Rothemund

Folding DNA to create nanoscale shapes and patterns

‘Bottom-up fabrication’, which exploits the intrinsic properties of atoms and molecules to direct their self-organization, is widely used to make relatively simple nanostructures. A key goal for this approach is to create nanostructures of high complexity, matching that routinely achieved by ‘top-down’ methods. The self-assembly of DNA molecules provides an attractive route towards this goal. Here I describe a simple method for folding long, single-stranded DNA molecules into arbitrary two-dimensional shapes. The design for a desired shape is made by raster-filling the shape with a 7-kilobase single-stranded scaffold and by choosing over 200 short oligonucleotide ‘staple strands’ to hold the scaffold in place. Once synthesized and mixed, the staple and scaffold strands self-assemble in a single step. The resulting DNA structures are roughly 100 nm in diameter and approximate desired shapes such as squares, disks and five-pointed stars with a spatial resolution of 6 nm. Because each oligonucleotide can serve as a 6-nm pixel, the structures can be programmed to bear complex patterns such as words and images on their surfaces. Finally, individual DNA structures can be programmed to form larger assemblies, including extended periodic lattices and a hexamer of triangles (which constitutes a 30-megadalton molecular complex).

The program-size complexity of self-assembled squares (extended abstract)

Molecular self-assembly gives rise to a great diversity of complex forms, from crystals and DNA helices to microtubules and holoenzymes. We study a formal model of pseudocrystalline self-assembly, called the Tile Assembly Model, in which a tile may be added to the growing object when the total interaction strength with its neighbors exceeds a parameter Τ. This model has been shown to be Turing-universal. Thus, self-assembled objects can be studied from the point of view of computational complexity. Here, we define the program size complexity of an NxN square to be the minimum number of distinct tiles required to self-assemble the square and no other objects. We study this complexity under the Tile Assembly Model and find a dramatic decrease in complexity, from N^2 tiles to O(log N) tiles, as Τ is increased from 1 (where bonding is noncooperative) to 2 (allowing cooperative bonding). Further, we find that the size of the largest square uniquely produced by a set of n tiles grows faster than any computable function.

An autonomous polymerization motor powered by DNA hybridization

We present a synthetic molecular motor capable of autonomous nanoscale transport in solution. Inspired by bacterial pathogens such as Rickettsia rickettsii, which locomote by inducing the polymerization of the protein actin at their surfaces to form ‘comet tails’1, the motor operates by polymerizing a double-helical DNA tail2. DNA strands are propelled processively at the living end of the growing polymers, demonstrating autonomous locomotion powered by the free energy of DNA hybridization.

An information-bearing seed for nucleating algorithmic self-assembly

Self-assembly creates natural mineral, chemical, and biological structures of great complexity. Often, the same starting materials have the potential to form an infinite variety of distinct structures; information in a seed molecule can determine which form is grown as well as where and when. These phenomena can be exploited to program the growth of complex supramolecular structures, as demonstrated by the algorithmic self-assembly of DNA tiles. However, the lack of effective seeds has limited the reliability and yield of algorithmic crystals. Here, we present a programmable DNA origami seed that can display up to 32 distinct binding sites and demonstrate the use of seeds to nucleate three types of algorithmic crystals. In the simplest case, the starting materials are a set of tiles that can form crystalline ribbons of any width; the seed directs assembly of a chosen width with >90% yield. Increased structural diversity is obtained by using tiles that copy a binary string from layer to layer; the seed specifies the initial string and triggers growth under near-optimal conditions where the bit copying error rate is <0.2%. Increased structural complexity is achieved by using tiles that generate a binary counting pattern; the seed specifies the initial value for the counter. Self-assembly proceeds in a one-pot annealing reaction involving up to 300 DNA strands containing >17 kb of sequence information. In sum, this work demonstrates how DNA origami seeds enable the easy, high-yield, low-error-rate growth of algorithmic crystals as a route toward programmable bottom-up fabrication.

A Sticker-Based Model for DNA Computation

We introduce a new model of molecular computation that we call the sticker model. Like many previous proposals it makes use of DNA strands as the physical substrate in which information is represented and of separation by hybridization as a central mechanism. However, unlike previous models, the stickers model has a random access memory that requires no strand extension and uses no enzymes; also (at least in theory), its materials are reusable. The paper describes computation under the stickers model and discusses possible means for physically implementing each operation. Finally, we go on to propose a specific machine architecture for implementing the stickers model as a microprocessor-controlled parallel robotic workstation. In the course of this development a number of previous general concerns about molecular computation (Smith, 1996; Hartmanis, 1995; Linial et al., 1995) are addressed. First, it is clear that general-purpose algorithms can be implemented by DNA-based computers, potentially solving a wide class of search problems. Second, we find that there are challenging problems, for which only modest volumes of DNA should suffice. Third, we demonstrate that the formation and breaking of covalent bonds is not intrinsic to DNA-based computation. Fourth, we show that a single essential biotechnology, sequence-specific separation, suffices for constructing a general-purpose molecular computer. Concerns about errors in this separation operation and means to reduce them are addressed elsewhere (Karp et al., 1995; Roweis and Winfree, 1999). Despite these encouraging theoretical advances, we emphasize that substantial engineering challenges remain at almost all stages and that the ultimate success or failure of DNA computing will certainly depend on whether these challenges can be met in laboratory investigations.

Programmable molecular recognition based on the geometry of DNA nanostructures

From ligand-receptor binding to DNA hybridization, molecular recognition plays a central role in biology. Over the past several decades, chemists have successfully reproduced the exquisite specificity of biomolecular interactions. However, engineering multiple specific interactions in synthetic systems remains difficult. DNA retains its position as the best medium with which to create orthogonal, isoenergetic interactions, based on the complementarity of Watson-Crick binding. Here we show that DNA can be used to create diverse bonds using an entirely different principle: the geometric arrangement of blunt-end stacking interactions. We show that both binary codes and shape complementarity can serve as a basis for such stacking bonds, and explore their specificity, thermodynamics and binding rules. Orthogonal stacking bonds were used to connect five distinct DNA origami. This work, which demonstrates how a single attractive interaction can be developed to create diverse bonds, may guide strategies for molecular recognition in systems beyond DNA nanostructures.

On Applying Molecular Computation to the Data Encryption Standard

Recently, Boneh, Dunworth, and Lipton (1996) described the potential use of molecular computation in attacking the United States Data Encryption Standard (DES). Here, we provide a description of such an attack using the sticker model of molecular computation. Our analysis suggests that such an attack might be mounted on a tabletop machine using approximately a gram of DNA and might succeed even in the presence of a large number of errors.

A single-stranded architecture for cotranscriptional folding of RNA nanostructures

The future of RNA origami writ large Researchers have long fabricated intricate nanostructures from carefully linked DNA strands. Now they can use RNA made by gene expression, which avoids the costly strand synthesis and lengthy annealing steps necessary with DNA origami. Geary et al. used molecular modeling to extend the size of folded RNA origami structures (see the Perspective by Leontis and Westhof). The modeling revealed assembly patterns for linking single-stranded RNA into A-form helices. The authors created two-dimensional structures as large as 660 nucleotides on mica surfaces. Science, this issue p. 799; see also p. 732 The size of RNA origami nanostructures has been increased with a distinct assembly pattern. [Also see Perspective by Leontis and Westhof] Artificial DNA and RNA structures have been used as scaffolds for a variety of nanoscale devices. In comparison to DNA structures, RNA structures have been limited in size, but they also have advantages: RNA can fold during transcription and thus can be genetically encoded and expressed in cells. We introduce an architecture for designing artificial RNA structures that fold from a single strand, in which arrays of antiparallel RNA helices are precisely organized by RNA tertiary motifs and a new type of crossover pattern. We constructed RNA tiles that assemble into hexagonal lattices and demonstrated that lattices can be made by annealing and/or cotranscriptional folding. Tiles can be scaled up to 660 nucleotides in length, reaching a size comparable to that of large natural ribozymes.

Self-Assembled Circuit Patterns

Self-assembly is a process in which basic units aggregate under attractive forces to form larger compound structures. Recent theoretical work has shown that pseudo-crystalline self-assembly can be algorithmic, in the sense that complex logic can be programmed into the growth process [26]. This theoretical work builds on the theory of two-dimensional tilings [8], using rigid square tiles called Wang tiles [24] for the basic units of self-assembly, and leads to Turing-universal models such as the Tile Assembly Model [28]. Using the Tile Assembly Model, we show how algorithmic self-assembly can be exploited for fabrication tasks such as constructing the patterns that define certain digital circuits, including demultiplexers, RAM arrays, pseudowavelet transforms, and Hadamard transforms. Since DNA self-assembly appears to be promising for implementing the arbitrary Wang tiles [30,13] needed for programming in the Tile Assembly Model, algorithmic self-assembly methods such as those presented in this paper may eventually become a viable method of arranging molecular electronic components [18], such as carbon nanotubes [10,1], into molecular-scale circuits.

Solution of a Satisfiability Problem on a Gel-Based DNA Computer

We have succeeded in solving an instance of a 6-variable 11-clause 3-SAT problem on a gel-based DNA computer. Separations were performed using probes covalently bound to polyacrylamide gel. During the entire computation, DNA was retained within a single gel and moved via electrophoresis. The methods used appear to be readily automatable and should be suitable for problems of a significantly larger size.