Lulu Qian

Scaling Up Digital Circuit Computation with DNA Strand Displacement Cascades

Scalability and noise control are demonstrated in a molecular computer built from DNA. To construct sophisticated biochemical circuits from scratch, one needs to understand how simple the building blocks can be and how robustly such circuits can scale up. Using a simple DNA reaction mechanism based on a reversible strand displacement process, we experimentally demonstrated several digital logic circuits, culminating in a four-bit square-root circuit that comprises 130 DNA strands. These multilayer circuits include thresholding and catalysis within every logical operation to perform digital signal restoration, which enables fast and reliable function in large circuits with roughly constant switching time and linear signal propagation delays. The design naturally incorporates other crucial elements for large-scale circuitry, such as general debugging tools, parallel circuit preparation, and an abstraction hierarchy supported by an automated circuit compiler.

Neural network computation with DNA strand displacement cascades

The impressive capabilities of the mammalian brain—ranging from perception, pattern recognition and memory formation to decision making and motor activity control—have inspired their re-creation in a wide range of artificial intelligence systems for applications such as face recognition, anomaly detection, medical diagnosis and robotic vehicle control. Yet before neuron-based brains evolved, complex biomolecular circuits provided individual cells with the ‘intelligent’ behaviour required for survival. However, the study of how molecules can ‘think’ has not produced an equal variety of computational models and applications of artificial chemical systems. Although biomolecular systems have been hypothesized to carry out neural-network-like computations in vivo and the synthesis of artificial chemical analogues has been proposed theoretically, experimental work has so far fallen short of fully implementing even a single neuron. Here, building on the richness of DNA computing and strand displacement circuitry, we show how molecular systems can exhibit autonomous brain-like behaviours. Using a simple DNA gate architecture that allows experimental scale-up of multilayer digital circuits, we systematically transform arbitrary linear threshold circuits (an artificial neural network model) into DNA strand displacement cascades that function as small neural networks. Our approach even allows us to implement a Hopfield associative memory with four fully connected artificial neurons that, after training in silico, remembers four single-stranded DNA patterns and recalls the most similar one when presented with an incomplete pattern. Our results suggest that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment.

Efficient turing-universal computation with DNA polymers

Bennetts proposed chemical Turing machine is one of the most important thought experiments in the study of the thermodynamics of computation. Yet the sophistication of molecular engineering required to physically construct Bennetts hypothetical polymer substrate and enzymes has deterred experimental implementations. Here we propose a chemical implementation of stack machines -- a Turing-universal model of computation similar to Turing machines -- using DNA strand displacement cascades as the underlying chemical primitive. More specifically, the mechanism described herein is the addition and removal of monomers from the end of a DNA polymer, controlled by strand displacement logic. We capture the motivating feature of Bennetts scheme: that physical reversibility corresponds to logically reversible computation, and arbitrarily little energy per computation step is required. Further, as a method of embedding logic control into chemical and biological systems, polymer-based chemical computation is significantly more efficient than geometry-free chemical reaction networks.

A Simple DNA Gate Motif for Synthesizing Large-Scale Circuits

The prospects of programming molecular systems to perform complex autonomous tasks has motivated research into the design of synthetic biochemical circuits. Of particular interest to us are cell-free nucleic acid systems that exploit non-covalent hybridization and strand displacement reactions to create cascades that implement digital and analog circuits. To date, circuits involving at most tens of gates have been demonstrated experimentally. Here, we propose a DNA catalytic gate architecture that appears suitable for practical synthesis of large-scale circuits involving possibly thousands of gates.

Asymmetric DNA Origami for Spatially Addressable and Index-Free Solution-Phase DNA Chips

A solution-phase DNA chip is produced using DNA origami-based asymmetric self-assembled tiles incorporating single-stranded DNA linear probes. This DNA origami chip is fully spatially addressable, without having to use position index oligonucleotides. The DNA hybridization is readily detected via atomic force microscopy.

A cargo-sorting DNA robot

Sorting molecules with DNA robots Single-stranded DNA robots can move over the surface of a DNA origami sheet and sort molecular cargoes. Thubagere et al. developed a simple algorithm for recognizing two types of molecular cargoes and their drop-off destinations on the surface (see the Perspective by Reif). The DNA robot, which has three modular functional domains, repeatedly picks up the two types of molecules and then places them at their target destinations. No additional power is required because the DNA robot does this by random walking across the origami surface. Science, this issue p. eaan6558; see also p. 1095 A single-stranded DNA with modular function domains undergoes a random walk and sorts two molecular cargoes. INTRODUCTION Since the 1980s, the design and synthesis of molecular machines has been identified as a grand challenge for molecular engineering. Robots are an important type of molecular machine that automatically carry out complex nanomechanical tasks. DNA molecules are excellent materials for building molecular robots, because their geometric, thermodynamic, and kinetic properties are well understood and highly programmable. So far, the development of DNA robots has been limited to simple functions. Most DNA robots were designed to perform a single function: walking in a controlled direction. A few demonstrations included a second function combined with walking (for example, picking up nanoparticles or choosing a path at a junction). However, these relatively more complex functions were also more difficult to control, and the complexity of the tasks was limited to what the robot can perform within 3 to 12 steps. In addition, each robot design was tailored for a specific task, complicating efforts to develop new robots that perform new tasks by combining functions and mechanisms. RATIONALE The design and synthesis of molecular robots presents two critical challenges, those of modularity and algorithm simplicity, which have been transformative in other areas of molecular engineering. For example, simple and modular building blocks have been used for scaling up molecular information processing with DNA circuits. As in DNA circuits, simple building blocks for DNA robots could enable more complex nanomechanical tasks, whereas modularity could allow diverse new functions performed by robots using the same set of building blocks. RESULTS We demonstrate a DNA robot that performs a nanomechanical task substantially more sophisticated than previous work. We developed a simple algorithm and three modular building blocks for a DNA robot that performs autonomous cargo sorting. The robot explores a two-dimensional testing ground on the surface of DNA origami, picks up multiple cargos of two types that are initially at unordered locations, and delivers each type to a specified destination until all cargo molecules are sorted into two distinct piles. The robot is designed to perform a random walk without any energy supply. Exploiting this feature, a single robot can repeatedly sort multiple cargos. Localization on DNA origami allows for distinct cargo-sorting tasks to take place simultaneously in one test tube or for multiple robots to collectively perform the same task. On average, our robot performed approximately 300 steps while sorting the cargos. The number of steps is one to two magnitudes larger than the previously demonstrated DNA robots performing additional tasks while walking. Using exactly the same robot design, the system could be generalized to multiple types of cargos with arbitrary initial distributions, and to many instances of distinct tasks in parallel, whereas each task can be assigned a distinct number of robots depending on the difficulty of the task. CONCLUSION Using aptamers, antibodies, or direct conjugation, small chemicals, metal nanoparticles, and proteins could be transported as cargo molecules so that the cargo-sorting DNA robots could have potential applications in autonomous chemical synthesis, in manufacturing responsive molecular devices, and in programmable therapeutics. The building blocks developed in this work could also be used for diverse functions other than cargo sorting. For example, inspired by ant foraging, adding a new building block for leaving pheromone-like signals on a path, DNA robots could be programmed to find the shortest path and efficiently transport cargo molecules. With simple communication between the robots, they could perform even more sophisticated tasks. With more effort in developing modular and collective molecular robots, and with simple and systematic approaches, molecular robots could eventually be easily programmed like macroscopic robots, but working in microscopic environments. Conceptual illustration of two DNA robots. The robots are collectively performing a cargo-sorting task on a DNA origami surface, transporting fluorescent molecules with different colors from initially unordered locations to separated destinations. Considerable artistic license has been taken. ILLUSTRATION: DEMIN LIU (WWW.MOLGRAPHICS.COM) Two critical challenges in the design and synthesis of molecular robots are modularity and algorithm simplicity. We demonstrate three modular building blocks for a DNA robot that performs cargo sorting at the molecular level. A simple algorithm encoding recognition between cargos and their destinations allows for a simple robot design: a single-stranded DNA with one leg and two foot domains for walking, and one arm and one hand domain for picking up and dropping off cargos. The robot explores a two-dimensional testing ground on the surface of DNA origami, picks up multiple cargos of two types that are initially at unordered locations, and delivers them to specified destinations until all molecules are sorted into two distinct piles. The robot is designed to perform a random walk without any energy supply. Exploiting this feature, a single robot can repeatedly sort multiple cargos. Localization on DNA origami allows for distinct cargo-sorting tasks to take place simultaneously in one test tube or for multiple robots to collectively perform the same task.

Programmable disorder in random DNA tilings

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.

Fractal assembly of micrometre-scale DNA origami arrays with arbitrary patterns

Self-assembled DNA nanostructures enable nanometre-precise patterning that can be used to create programmable molecular machines and arrays of functional materials. DNA origami is particularly versatile in this context because each DNA strand in the origami nanostructure occupies a unique position and can serve as a uniquely addressable pixel. However, the scale of such structures has been limited to about 0.05 square micrometres, hindering applications that demand a larger layout and integration with more conventional patterning methods. Hierarchical multistage assembly of simple sets of tiles can in principle overcome this limitation, but so far has not been sufficiently robust to enable successful implementation of larger structures using DNA origami tiles. Here we show that by using simple local assembly rules that are modified and applied recursively throughout a hierarchical, multistage assembly process, a small and constant set of unique DNA strands can be used to create DNA origami arrays of increasing size and with arbitrary patterns. We illustrate this method, which we term ‘fractal assembly’, by producing DNA origami arrays with sizes of up to 0.5 square micrometres and with up to 8,704 pixels, allowing us to render images such as the Mona Lisa and a rooster. We find that self-assembly of the tiles into arrays is unaffected by changes in surface patterns on the tiles, and that the yield of the fractal assembly process corresponds to about 0.95m − 1 for arrays containing m tiles. When used in conjunction with a software tool that we developed that converts an arbitrary pattern into DNA sequences and experimental protocols, our assembly method is readily accessible and will facilitate the construction of sophisticated materials and devices with sizes similar to that of a bacterium using DNA nanostructures.

Parallel and Scalable Computation and Spatial Dynamics with DNA-Based Chemical Reaction Networks on a Surface

We propose a theoretical framework that uses a novel DNA strand displacement mechanism to implement abstract chemical reaction networks (CRNs) on the surface of a DNA nanostructure, and show that surface CRNs can perform efficient algorithmic computation and create complex spatial dynamics. We argue that programming molecular behaviors with surface CRNs is systematic, parallel and scalable.

Compiler-aided systematic construction of large-scale DNA strand displacement circuits using unpurified components

Biochemical circuits made of rationally designed DNA molecules are proofs of concept for embedding control within complex molecular environments. They hold promise for transforming the current technologies in chemistry, biology, medicine and material science by introducing programmable and responsive behaviour to diverse molecular systems. As the transformative power of a technology depends on its accessibility, two main challenges are an automated design process and simple experimental procedures. Here we demonstrate the use of circuit design software, combined with the use of unpurified strands and simplified experimental procedures, for creating a complex DNA strand displacement circuit that consists of 78 distinct species. We develop a systematic procedure for overcoming the challenges involved in using unpurified DNA strands. We also develop a model that takes synthesis errors into consideration and semi-quantitatively reproduces the experimental data. Our methods now enable even novice researchers to successfully design and construct complex DNA strand displacement circuits.