Effective design principles for leakless strand displacement systems

Autonomous walking dynamics of a nanorobot on a nanopore track driven by salt concentration gradients

The walking of a nanorobot with DNA legs requires a preset track to serve as footholds for the DNA legs and a track-matched driving mechanism to propel the nanorobot. Recently, a newly suggested track formed by multiple nanopores has garnered attraction due to its chemical stability. The nanorobot can be powered by biased leg-nanopore interactions along the walking direction. Here, we propose utilizing a salt concentration gradient along the nanopore track to induce an interaction bias based on different local ion screening effects on the nanopore charges. The nanorobot walking behaviors under different salt concentration gradients are studied through a combination of computational simulations and theoretical analyses. We find that the walking properties (such as velocity and directionality) highly depend on the local interactions experienced by the lagging leg. Under strong leg-nanopore attraction, the lagging leg needs a drag force provided by the leading leg to leave from the nanopore, while under weak attraction, the lagging leg can leave the nanopore without the assistance of the leading leg. Therefore, different walking modes can be observed under various ion conditions, leading to the complicated walking dynamics of the nanorobot driven by the salt concentration gradients.

Abstraction-based segmental simulation of reaction networks using adaptive memoization

BACKGROUND

 Stochastic models are commonly employed in the system and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. Many important models feature complex dynamics, involving a state-space explosion, stiffness, and multimodality, that complicate the quantitative analysis needed to understand their stochastic behavior. Direct numerical analysis of such models is typically not feasible and generating many simulation runs that adequately approximate the model's dynamics may take a prohibitively long time.

RESULTS

 We propose a new memoization technique that leverages a population-based abstraction and combines previously generated parts of simulations, called segments, to generate new simulations more efficiently while preserving the original system's dynamics and its diversity. Our algorithm adapts online to identify the most important abstract states and thus utilizes the available memory efficiently.

CONCLUSION

 We demonstrate that in combination with a novel fully automatic and adaptive hybrid simulation scheme, we can speed up the generation of trajectories significantly and correctly predict the transient behavior of complex stochastic systems.

Implementation of Digital Computing by Colloidal Crystal Engineering with DNA

Toehold-mediated strand displacement (TMSD) provides a versatile toolbox for developing DNA digital computing systems. Although different logic circuits with diverse functions have achieved good performance in terms of complexity and scalability, most previous DNA logic circuits perform information processing only at the molecular level, and nonspecific signal leakages are often difficult to avoid. Here, we demonstrate the feasibility of constructing leakless digital computing systems in three-dimensionally ordered colloidal supercrystals. These systems possess a unique signal leakage resistance by integrating different TMSD-based logic gates with the catalytic assembly of DNA-functionalized gold colloids. A complete set of basic Boolean logic gates and different cascaded logic circuits is constructed on the basis of the catalytic assembly strategy enabled by a facilely designed catassembler, where the output signals are recognized by determining whether specific colloidal supercrystals are formed or not. In addition, a half adder is built through a combination of XOR and AND logic gates with two distinct crystal types as readouts. Finally, a leakless two-digit DNA keypad lock for information security protection is demonstrated. The combination of TMSD-based logic circuits with the universal nanoparticle catalytic assembly offers the possibility to develop highly complicated and leakage-free digital computing systems and promotes macroscopic colloidal superlattice materials with programmable logic functions.

Y-switch: a spring-loaded synthetic gene switch for robust DNA/RNA signal amplification and detection

Nucleic acid tests (NATs) are essential for biomedical diagnostics. Traditional NATs, often complex and expensive, have prompted the exploration of toehold-mediated strand displacement (TMSD) circuits as an economical alternative. However, the wide application of TMSD-based reactions is limited by 'leakage'-the spurious activation of the reaction leading to high background signals and false positives. Here, we introduce the Y-Switch, a new TMSD cascade design that recognizes a custom nucleic acid input and generates an amplified output. The Y-Switch is based on a pair of thermodynamically spring-loaded DNA modules. The binding of a predefined nucleic acid target triggers an intermolecular reaction that activates a T7 promoter, leading to the perpetual transcription of a fluorescent aptamer that can be detected by a smartphone camera. The system is designed to permit the selective depletion of leakage byproducts to achieve high sensitivity and zero-background signal in the absence of the correct trigger. Using Zika virus (ZIKV)- and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-derived nucleic acid sequences, we show that the assay generates a reliable target-specific readout. Y-Switches detect native RNA under isothermal conditions without reverse transcription or pre-amplification, with a detection threshold as low as ∼200 attomole. The modularity of the assay allows easy re-programming for the detection of other targets by exchanging a single sequence domain. This work provides a low-complexity and high-fidelity synthetic biology tool for point-of-care diagnostics and for the construction of more complex biomolecular computations.

An efficient DNAzyme-locked leakless enzyme-free amplification system for alpha-foetoprotein detection in liver cancer and breast cancer

Alpha-foetoprotein (AFP) is taken as a diagnostic tumor marker for the screening and diagnosis of cancer. Nucleic acid-based isothermal amplification strategies are emerging as a potential technology in early screening and clinical diagnosis of AFP. The leakages between hairpins dramatically increase the background and reduce the sensitivity. Thus, it is necessary to develop some strategies to reduce the leakage for isothermal amplification strategies. A DNAzyme-locked leakless enzyme-free amplification system was developed for AFP detection in liver cancer and breast cancer. AFP could open the apt-hairpin and initiate the catalytic hairpin assembly (CHA) reaction to produce a Y-shaped duplex. Two tails of a Y-shaped duplex cleaved the two kinds of leakless hairpins. Then, the third tail of the Y-shaped duplex catalyzed the second CHA between the cleaved leakless hairpins to recover the fluorescent intensity. The limit of detection reached 5 fg/mL by the two levels of signal amplifications. Importantly, the leakless hairpin design effectively reduced leakage between hairpins and weakened the background. In addition, it also showed a great promising potential for AFP detection in early screening and clinical diagnosis.

Construction of a Spatial-Confined Self-Stacking Catalytic Circuit for Rapid and Sensitive Imaging of Piwi-Interacting RNA in Living Cells

Piwi-interacting RNAs (piRNAs) are small noncoding RNAs that repress transposable elements to maintain genome integrity. The canonical catalytic hairpin assembly (CHA) circuit relies on random collisions of free-diffused reactant probes, which substantially slow down reaction efficiency and kinetics. Herein, we demonstrate the construction of a spatial-confined self-stacking catalytic circuit for rapid and sensitive imaging of piRNA in living cells based on intramolecular and intermolecular hybridization-accelerated CHA. We rationally design a 3WJ probe that not only accelerates the reaction kinetics by increasing the local concentration of reactant probes but also eliminates background signal leakage caused by cross-entanglement of preassembled probes. This strategy achieves high sensitivity and good specificity with shortened assay time. It can quantify intracellular piRNA expression at a single-cell level, discriminate piRNA expression in tissues of breast cancer patients and healthy persons, and in situ image piRNA in living cells, offering a new approach for early diagnosis and postoperative monitoring.

Inhibition of kinetic random-distribution in DNA Seesaw gates and biosensors for complete leakage prevention

DNA nanomaterials have a wide application prospect in biomedical field, among which DNA computers and biosensors based on Seesaw-based DNA circuit is considered to have the most development potential. However, the serious leakage of Seesaw-based DNA circuit prevented its further development and application. Moreover, the existing methods to suppress leakage can't achieve the ideal effect. Interestingly, we found a new source of leakage in Seesaw-based DNA circuit, which we think is the main reason why the previous methods to suppress leakage are not satisfactory. Therefore, based on this discovery, we use DNA triplex to design a new method to suppress the leakage of Seesaw-based DNA circuit. Its ingenious design makes it possible to perfectly suppress the leakage of all sources in Seesaw-based DNA circuit and ensure the normal output of the circuit. Based on this technology, we have constructed basic Seesaw module, AND gate, OR gate, secondary complex circuits and DNA detector. Experimental results show that we can increase the working range of the secondary Seesaw-based DNA circuit by five folds and keep its normal output signal above 90%, and we can improve the LOD of the Seesaw-based DNA detector to 1/11 of the traditional one(1.8pM). More importantly, we successfully developed a detector with adjustable detection range, which can theoretically achieve accurate detection in any concentration range. We believe the established triplex blocking strategy will greatly facilitate the most powerful Seesaw based DNA computers and biosensors, and further promote its application in biological systems.

Heteromultivalent DNA Enhances the Assembly Yield of Hybrid Nanoparticles and Facilitates Dynamic Disassembly for Bioanalysis Using ICP-MS

To obtain enhanced physical and biological properties, various nanoparticles are typically assembled into hybrid nanoparticles through the binding of multiple homologous DNA strands to their complementary counterparts, commonly referred to as homomultivalent assembly. However, the poor binding affinity and limited controllability of homomultivalent disassembly restrict the assembly yield and dynamic functionality of the hybrid nanoparticles. To achieve a higher binding affinity and flexible assembly choice, we utilized the paired heteromultivalency DNA to construct hybrid nanoparticles and demonstrate their excellent assembly characteristics and dynamic applications. Specifically, through heteromultivalency, DNA-functionalized magnetic beads (MBs) and gold nanoparticles (AuNPs) were efficiently assembled. By utilizing ICP-MS, the assembly efficiency of AuNPs on MBs was directly monitored, enabling quantitative analysis and optimization of heteromultivalent binding events. As a result, the enhanced assembly yield is primarily attributed to the fact that heteromultivalency allows for the maximization of effective DNA probes on the surface of nanoparticles, eliminating steric hindrance interference. Subsequently, with external oligonucleotides as triggers, it was revealed that the disassembly mechanism of hybrid nanoparticles was initiated, which was based on an increased local concentration rather than toehold-mediated displacement of paired heteromultivalency DNA probes. Capitalizing on these features, an output platform was then established based on ICP-MS signals that several Boolean operations and analytical applications can be achieved by simply modifying the design sequences. The findings provide new insights into DNA biointerface interaction, with potential applications to complex logic operations and the construction of large DNA nanostructures.

DNA as a universal chemical substrate for computing and data storage

DNA computing and DNA data storage are emerging fields that are unlocking new possibilities in information technology and diagnostics. These approaches use DNA molecules as a computing substrate or a storage medium, offering nanoscale compactness and operation in unconventional media (including aqueous solutions, water-in-oil microemulsions and self-assembled membranized compartments) for applications beyond traditional silicon-based computing systems. To build a functional DNA computer that can process and store molecular information necessitates the continued development of strategies for computing and data storage, as well as bridging the gap between these fields. In this Review, we explore how DNA can be leveraged in the context of DNA computing with a focus on neural networks and compartmentalized DNA circuits. We also discuss emerging approaches to the storage of data in DNA and associated topics such as the writing, reading, retrieval and post-synthesis editing of DNA-encoded data. Finally, we provide insights into how DNA computing can be integrated with DNA data storage and explore the use of DNA for near-memory computing for future information technology and health analysis applications.

Dynamic DNA Assembly by Programmable Hybridization Chain Reaction Mimicking Tubulin

Dynamic biological structures involve the continual turnover of molecules within supramolecular assemblies such as tubulin. Inspired by dynamic biology self-organizing systems, we build an artificial dynamic structure based on DNA nanotechnology through a nonequilibrium chemical system. Herein, a metastable domain (MD), essentially a stem-loop structure, was introduced into DNA hairpins within hybridization chain reaction (HCR), thereby imparting dynamic activity to the DNA polymers. Hairpins with MD thermodynamically assemble to a high-energy polymer in the presence of trigger strands. The polymer can relax back to the stable unassembled state once the invader is added and finally relax to the activated hairpin by an anti-invader. Reversible assembly/disassembly of the HCR is achieved through invader/anti-invader cycles. We accomplished kinetic modulation, reversible conformational switching, cascading regulation, and enzyme activity control through the MD-HCR. We believe that the design of the MD-HCR could inspire the development of autonomous biological functions within artificial systems.

Zipper-Confined DNA Nanoframe for High-Efficient and High-Contrast Imaging of Heterogeneous Tumor Cell

Current study in the heterogeneity and physiological behavior of tumor cells is limited by the fluorescence in situ hybridization technology in terms of probe assembly efficiency, background suppression capability, and target compatibility. In a typically well-designed assay, hybridization probes are constructed in a confined nanostructure to achieve a rapid assembly for efficient signal response, while the excessively high local concentration between different probes inevitably leads to nonspecific background leakage. Inspired by the fabric zipper, we propose a novel confinement reaction pattern in a zipper-confined DNA nanoframe (ZCDN), where two kinds of hairpin probes are independently anchored respective tracks. The metastable states of the dual tracks can well avoid signal leakage caused by the nonspecific probe configuration change. Biomarker-mediated proximity ligation reduces the local distance of dual tracks, kinetically triggering an efficient allosteric chain reaction between the hairpin probes. This method circumvents nonspecific background leakage while maintaining a high efficiency in responding to targets. ZCDN is employed to track different cancer biomarkers located in both the cytoplasm and cytomembrane, of which the expression level and oligomerization behavior can provide crucial information regarding intratumoral heterogeneity. ZCDN exhibits high target response efficiency and strong background suppression capabilities and is compatible with various types of biological targets, thus providing a desirable tool for advanced molecular diagnostics.

DNA-Aptamer-Based qPCR Using Light-Up Dyes for the Detection of Nucleic Acids

Quantitative polymerase chain reaction (qPCR) is widely used in detection of nucleic acids, but existing methods either lack sequence-specific detection or are costly because they use chemically modified DNA probes. In this work, we apply a DNA aptamer and light-up dye-based chemistry for qPCR for nucleic acid quantification. In contrast to the conventional qPCR, in our method, we observe an exponential decrease in fluorescence upon DNA amplification. The qPCR method we developed produced consistent Ct vs log10 (DNA amount) standard curves, which have a linearfit with R2 value > 0.99. This qPCR technique was validated by quantifying gene targets from Streptococcus zooepidemicus (SzhasB) and Mycobacterium tuberculosis (MtrpoB). We show that our strategy is able to successfully detect DNA at as low as 800 copies/μL. To the best of our knowledge, this is the first study demonstrating the application of light-up dyes and DNA aptamers in qPCR.

Programmable Biomolecule-Mediated Processors

Programmable biomolecule-mediated computing is a new computing paradigm as compared to contemporary electronic computing. It employs nucleic acids and analogous biomolecular structures as information-storing and -processing substrates to tackle computational problems. It is of great significance to investigate the various issues of programmable biomolecule-mediated processors that are capable of automatically processing, storing, and displaying information. This Perspective provides several conceptual designs of programmable biomolecule-mediated processors and provides some insights into potential future research directions for programmable biomolecule-mediated processors.

Twinkle-Catalyzed Toehold-Mediated DNA Strand Displacement Reaction

Strand exchange between homologous nucleic acid sequences is the basis for cellular DNA repair, recombination, and genome editing technologies. Specialized enzymes catalyze cellular strand exchange; however, the reaction occurs spontaneously when a single-stranded DNA toehold can dock the invader strand on the target DNA to initiate strand exchange through branch migration. Due to its precise response, the spontaneous toehold-mediated strand displacement (TMSD) reaction is widely employed in DNA nanotechnology. However, enzyme-free TMSD suffers from slow rates, resulting in slow response times. Here, we show that human mitochondrial DNA helicase Twinkle can accelerate TMSD up to 6000-fold. Mechanistic studies indicate that Twinkle accelerates TMSD by catalyzing the docking step, which typically limits spontaneous reactions. The catalysis occurs without ATP, and Twinkle-catalyzed TMSD rates remain sensitive to base-pair mismatches. The simple catalysis, tunability, and speed improvement of the catalyzed TMSD can be leveraged in nanotechnology, requiring sensitive detection and faster response times.

Neural network execution using nicked DNA and microfluidics

DNA has been discussed as a potential medium for data storage. Potentially it could be denser, could consume less energy, and could be more durable than conventional storage media such as hard drives, solid-state storage, and optical media. However, performing computations on the data stored in DNA is a largely unexplored challenge. This paper proposes an integrated circuit (IC) based on microfluidics that can perform complex operations such as artificial neural network (ANN) computation on data stored in DNA. We envision such a system to be suitable for highly dense, throughput-demanding bio-compatible applications such as an intelligent Organ-on-Chip or other biomedical applications that may not be latency-critical. It computes entirely in the molecular domain without converting data to electrical form, making it a form of in-memory computing on DNA. The computation is achieved by topologically modifying DNA strands through the use of enzymes called nickases. A novel scheme is proposed for representing data stochastically through the concentration of the DNA molecules that are nicked at specific sites. The paper provides details of the biochemical design, as well as the design, layout, and operation of the microfluidics device. Benchmarks are reported on the performance of neural network computation.

Supervised Learning in a Multilayer, Nonlinear Chemical Neural Network

The development of programmable or trainable molecular circuits is an important goal in the field of molecular programming. Multilayer, nonlinear, artificial neural networks are a powerful framework for implementing such functionality in a molecular system, as they are provably universal function approximators. Here, we present a design for multilayer chemical neural networks with a nonlinear hyperbolic tangent transfer function. We use a weight perturbation algorithm to train the neural network which uses a simple construction to directly approximate the loss derivatives required for training. We demonstrate the training of this system to learn all 16 two-input binary functions from a common starting point. This work thus introduces new capabilities in the field of adaptive and trainable chemical reaction network (CRN) design. It also opens the door to potential future experimental implementations, including DNA strand displacement reactions.

Parallel molecular computation on digital data stored in DNA

DNA is an incredibly dense storage medium for digital data. However, computing on the stored information is expensive and slow, requiring rounds of sequencing, in silico computation, and DNA synthesis. Prior work on accessing and modifying data using DNA hybridization or enzymatic reactions had limited computation capabilities. Inspired by the computational power of "DNA strand displacement," we augment DNA storage with "in-memory" molecular computation using strand displacement reactions to algorithmically modify data in a parallel manner. We show programs for binary counting and Turing universal cellular automaton Rule 110, the latter of which is, in principle, capable of implementing any computer algorithm. Information is stored in the nicks of DNA, and a secondary sequence-level encoding allows high-throughput sequencing-based readout. We conducted multiple rounds of computation on 4-bit data registers, as well as random access of data (selective access and erasure). We demonstrate that large strand displacement cascades with 244 distinct strand exchanges (sequential and in parallel) can use naturally occurring DNA sequence from M13 bacteriophage without stringent sequence design, which has the potential to improve the scale of computation and decrease cost. Our work merges DNA storage and DNA computing, setting the foundation of entirely molecular algorithms for parallel manipulation of digital information preserved in DNA.

Leveraging Steric Moieties for Kinetic Control of DNA Strand Displacement Reactions

DNA strand displacement networks are a critical part of dynamic DNA nanotechnology and are proven primitives for implementing chemical reaction networks. Precise kinetic control of these networks is important for their use in a range of applications. Among the better understood and widely leveraged kinetic properties of these networks are toehold sequence, length, composition, and location. While steric hindrance has been recognized as an important factor in such systems, a clear understanding of its impact and role is lacking. Here, a systematic investigation of steric hindrance within a DNA toehold-mediated strand displacement network was performed through tracking kinetic reactions of reporter complexes with incremental concatenation of steric moieties near the toehold. Two subsets of steric moieties were tested with systematic variation of structures and reaction conditions to isolate sterics from electrostatics. Thermodynamic and coarse-grained computational modeling was performed to gain further insight into the impacts of steric hindrance. Steric factors yielded up to 3 orders of magnitude decrease in the reaction rate constant. This pronounced effect demonstrates that steric moieties can be a powerful tool for kinetic control in strand displacement networks while also being more broadly informative of DNA structural assembly in both DNA-based therapeutic and diagnostic applications that possess elements of steric hindrance through DNA functionalization with an assortment of chemistries.

Molecular information technology with DNA

Qian and Winfree constructed complex biochemical circuits with computation capability from scratch, demonstrating the programmability of biomolecules. One day, programming molecular information processing may be just like how electronic machines are programmed today, with exciting applications in nanoscale science and biotechnology.

A Theoretical Framework for Implementable Nucleic Acids Feedback Systems

Chemical reaction networks can be utilised as basic components for nucleic acid feedback control systems' design for Synthetic Biology application. DNA hybridisation and programmed strand-displacement reactions are effective primitives for implementation. However, the experimental validation and scale-up of nucleic acid control systems are still considerably falling behind their theoretical designs. To aid with the progress heading into experimental implementations, we provide here chemical reaction networks that represent two fundamental classes of linear controllers: integral and static negative state feedback. We reduced the complexity of the networks by finding designs with fewer reactions and chemical species, to take account of the limits of current experimental capabilities and mitigate issues pertaining to crosstalk and leakage, along with toehold sequence design. The supplied control circuits are quintessential candidates for the first experimental validations of nucleic acid controllers, since they have a number of parameters, species, and reactions small enough for viable experimentation with current technical capabilities, but still represent challenging feedback control systems. They are also well suited to further theoretical analysis to verify results on the stability, performance, and robustness of this important new class of control systems.

Molecular Computation for Molecular Classification

DNA as an informational polymer has, for the past 30 years, progressively become an essential molecule to rationally build chemical reaction networks endowed with powerful signal-processing capabilities. Whether influenced by the silicon world or inspired by natural computation, molecular programming has gained attention for diagnosis applications. Of particular interest for this review, molecular classifiers have shown promising results for disease pattern recognition and sample classification. Because both input integration and computation are performed in a single tube, at the molecular level, this low-cost approach may come as a complementary tool to molecular profiling strategies, where all biomarkers are quantified independently using high-tech instrumentation. After introducing the elementary components of molecular classifiers, some of their experimental implementations are discussed either using digital Boolean logic or analog neural network architectures.

Toehold-Mediated Strand Displacement in Random Sequence Pools

Toehold-mediated strand displacement (TMSD) has been used extensively for molecular sensing and computing in DNA-based molecular circuits. As these circuits grow in complexity, sequence similarity between components can lead to cross-talk, causing leak, altered kinetics, or even circuit failure. For small non-biological circuits, such unwanted interactions can be designed against. In environments containing a huge number of sequences, taking all possible interactions into account becomes infeasible. Therefore, a general understanding of the impact of sequence backgrounds on TMSD reactions is of great interest. Here, we investigate the impact of random DNA sequences on TMSD circuits. We begin by studying individual interfering strands and use the obtained data to build machine learning models that estimate kinetics. We then investigate the influence of pools of random strands and find that the kinetics are determined by only a small subpopulation of strongly interacting strands. Consequently, their behavior can be mimicked by a small collection of such strands. The equilibration of the circuit with the background sequences strongly influences this behavior, leading to up to 1 order of magnitude difference in reaction speed. Finally, we compare two established and one novel technique that speed up TMSD reactions in random sequence pools: a three-letter alphabet, protection of toeholds by intramolecular secondary structure, or by an additional blocking strand. While all of these techniques were useful, only the latter can be used without sequence constraints. We expect that our insights will be useful for the construction of TMSD circuits that are robust to molecular noise.

Programming Non-Nucleic Acid Molecules into Computational Nucleic Acid Systems

Nucleic acid (NA) computation has been widely developed in the past years to solve kinds of logic and mathematic issues in both information technologies and biomedical analysis. However, the difficulty to integrate non-NA molecules limits its power as a universal platform for molecular computation. Here, we report a versatile prototype of hybridized computation integrated with both nucleic acids and non-NA molecules. Employing the conformationally controlled ligand converters, we demonstrate that non-NA molecules, including both small molecules and proteins, can be computed as nucleic acid strands to construct the circuitry with increased complexity and scalability, and can be even programmed to solve arithmetical calculations within the computational nucleic acid system. This study opens a new door for molecular computation in which all-NA circuits can be expanded with integration of various ligands, and meanwhile, ligands can be precisely programmed by the nuclei acid computation.

Measuring the Affinities of RNA and DNA Aptamers with DNA Origami-Based Chiral Plasmonic Probes

Reliable characterization of binding affinities is crucial for selected aptamers. However, the limited repertoire of universal approaches to obtain the dissociation constant (K_D) values often hinders the further development of aptamer-based applications. Herein, we present a competitive hybridization-based strategy to characterize aptamers using DNA origami-based chiral plasmonic assemblies as optical reporters. We incorporated aptamers and partial complementary strands blocking different regions of the aptamers into the reporters and measured the kinetic behaviors of the target binding to gain insights on aptamers' functional domains. We introduced a reference analyte and developed a thermodynamic model to obtain a relative dissociation constant of an aptamer-target pair. With this approach, we characterized RNA and DNA aptamers binding to small molecules with low and high affinities.

Pathogen Identification: Ultrasensitive Nucleic Acid Detection via a Dynamic DNA Nanosystem-Integrated Ratiometric Electrochemical Sensing Strategy

Sensitively determining trace nucleic acid is of great significance for pathogen identification. Herein, a dynamic DNA nanosystem-integrated ratiometric electrochemical biosensor was proposed to determine human immunodeficiency virus-associated DNA fragment (HIV-DNA) with high sensitivity and selectivity. The dynamic DNA nanosystem was composed of a target recycling unit and a multipedal DNA walker unit. Both of them could be driven by a toehold-mediated strand displacement reaction, enabling an enzyme-free and isothermal amplification strategy for nucleic acid determination. The target recycling unit could selectively recognize HIV-DNA and activate the multipedal DNA walker unit to roll on the electrode surface, which would lead to bidirectional signal variation for ratiometric readout with cascade signal amplification. Benefiting from the synergistic effect of the dynamic DNA nanosystem and the ratiometric output mode, the ultrasensitive detection of HIV-DNA was achieved in a wide linear range of 6 orders of magnitude with a limit of detection of 36.71 aM. The actual usability of the proposed sensor was also verified in complex biological samples with acceptable performance. This dynamic DNA nanosystem-integrated ratiometric sensing strategy might be promising in the development of reliable point-of-care diagnostic devices for highly sensitive and selective pathogen identification.

Tunable and Modular miRNA Classifier through Indirect Associative Toehold Strand Displacement

The programmability of nucleic acids allows detection devices with complex behaviors to be designed de novo. While highly specific, these high-order circuits are usually sequence constrained, making their adaptability toward biological targets challenging. Here, we devise a new strategy called indirect associative strand displacement to decouple sequence constraints between miRNA inputs and de novo strand displacement circuits. By splitting circuit inputs into their toehold and branch migration regions and controlling their association through a docking strand, we demonstrate how any miRNA sequence can be interfaced with synthetic DNA circuits, including catalytic hairpin assembly and a four-input classifier.

Massively Parallel DNA Computing Based on Domino DNA Strand Displacement Logic Gates

DNA computing has gained considerable attention due to the characteristics of high-density information storage and high parallel computing for solving computational problems. Building addressable logic gates with biomolecules is the basis for establishing biological computers. In the current calculation model, the multiinput AND operation often needs to be realized through a multilevel cascade between logic gates. Through experiments, it was found that the multilevel cascade causes signal leakage and affects the stability of the system. Using DNA strand displacement technology, we constructed a domino-like multiinput AND gate computing system instead of a cascade of operations, realizing multiinput AND computing on one logic gate and abandoning the traditional multilevel cascade of operations. Fluorescence experiments demonstrated that our methods significantly reduce system construction costs and improve the stability and robustness of the system. Finally, we proved stability and robustness of the domino AND gate by simulating the tic-tac-toe process with a massively parallel computing strategy.

Protecting Heterochiral DNA Nanostructures against Exonuclease-Mediated Degradation

Heterochiral DNA nanotechnology employs nucleic acids of both chiralities to construct nanoscale devices for applications in the intracellular environment. Interacting directly with cellular nucleic acids can be done most easily using D-DNA of the naturally occurring right-handed chirality; however, D-DNA is more vulnerable to degradation than enantiometric left-handed L-DNA. Here we report a novel combination of D-DNA and L-DNA nucleotides in triblock heterochiral copolymers, where the L-DNA domains act as protective caps on D-DNA domains. We demonstrate that the D-DNA components of strand displacement-based molecular circuits constructed using this technique resist exonuclease-mediated degradation during extended incubations in serum-supplemented media more readily than similar devices without the L-DNA caps. We show that this protection can be applied to both double-stranded and single-stranded circuit components. Our work enhances the state of the art for robust heterochiral circuit design and could lead to practical applications such as in vivo biomedical diagnostics.

Advancements in Testing Strategies for COVID-19

The SARS-CoV-2 coronavirus, also known as the disease-causing agent for COVID-19, is a virulent pathogen that may infect people and certain animals. The global spread of COVID-19 and its emerging variation necessitates the development of rapid, reliable, simple, and low-cost diagnostic tools. Many methodologies and devices have been developed for the highly sensitive, selective, cost-effective, and rapid diagnosis of COVID-19. This review organizes the diagnosis platforms into four groups: imaging, molecular-based detection, serological testing, and biosensors. Each platform's principle, advancement, utilization, and challenges for monitoring SARS-CoV-2 are discussed in detail. In addition, an overview of the impact of variants on detection, commercially available kits, and readout signal analysis has been presented. This review will expand our understanding of developing advanced diagnostic approaches to evolve into susceptible, precise, and reproducible technologies to combat any future outbreak.

Automated Leak Analysis of Nucleic Acid Circuits

Nucleic acids are a powerful engineering material that can be used to implement a broad range of computational circuits at the nanoscale, with potential applications in high-precision biosensing, diagnostics, and therapeutics. However, nucleic acid circuits are prone to leaks, which result from unintended displacement interactions between nucleic acid strands. Such leaks can grow combinatorially with circuit size, are challenging to mitigate, and can significantly compromise circuit behavior. While several techniques have been proposed to partially mitigate leaks, computational methods for designing new leak mitigation strategies and comparing their effectiveness on circuit behavior are limited. Here we present a general method for the automated leak analysis of nucleic acid circuits, referred to as DSD Leaks. Our method extends the logic programming functionality of the Visual DSD language, developed for the design and analysis of nucleic acid circuits, with predicates for leak generation, a leak reaction enumeration algorithm, and predicates to exclude low probability leak reactions. We use our method to identify the critical leak reactions affecting the performance of control circuits, and to analyze leak mitigation strategies by automatically generating leak reactions. Finally, we design new control circuits with substantially reduced leakage including a sophisticated proportional-integral controller circuit, which can in turn serve as building blocks for future circuits. By integrating our method within an open-source nucleic acid circuit design tool, we enable the leak analysis of a broad range of circuits, as an important step toward facilitating robust and scalable nucleic acid circuit design.

A DNA molecular printer capable of programmable positioning and patterning in two dimensions

Nanoscale manipulation and patterning usually require costly and sensitive top-down techniques such as those used in scanning probe microscopies or in semiconductor lithography. DNA nanotechnology enables exploration of bottom-up fabrication and has previously been used to design self-assembling components capable of linear and rotary motion. In this work, we combine three independently controllable DNA origami linear actuators to create a nanoscale robotic printer. The two-axis positioning mechanism comprises a moveable gantry, running on parallel rails, threading a mobile sleeve. We show that the device is capable of reversibly positioning a write head over a canvas through the addition of signaling oligonucleotides. We demonstrate "write" functionality by using the head to catalyze a local DNA strand-exchange reaction, selectively modifying pixels on a canvas. This work demonstrates the power of DNA nanotechnology for creating nanoscale robotic components and could find application in surface manufacturing, biophysical studies, and templated chemistry.

Cotranscriptionally encoded RNA strand displacement circuits

Engineered molecular circuits that process information in biological systems could address emerging human health and biomanufacturing needs. However, such circuits can be difficult to rationally design and scale. DNA-based strand displacement reactions have demonstrated the largest and most computationally powerful molecular circuits to date but are limited in biological systems due to the difficulty in genetically encoding components. Here, we develop scalable cotranscriptionally encoded RNA strand displacement (ctRSD) circuits that are rationally programmed via base pairing interactions. ctRSD circuits address the limitations of DNA-based strand displacement circuits by isothermally producing circuit components via transcription. We demonstrate circuit programmability in vitro by implementing logic and amplification elements, as well as multilayer cascades. Furthermore, we show that circuit kinetics are accurately predicted by a simple model of coupled transcription and strand displacement, enabling model-driven design. We envision ctRSD circuits will enable the rational design of powerful molecular circuits that operate in biological systems, including living cells.

A localized DNA finite-state machine with temporal resolution

The identity and timing of environmental stimulus play a pivotal role in living organisms in programming their signaling networks and developing specific phenotypes. The ability to unveil history-dependent signals will advance our understanding of temporally regulated biological processes. Here, we have developed a two-input, five-state DNA finite-state machine (FSM) to sense and record the temporally ordered inputs. The spatial organization of the processing units on DNA origami enables facile modulation of the energy landscape of DNA strand displacement reactions, allowing precise control of the reactions along predefined paths for different input orders. The use of spatial constraints brings about a simple, modular design for the FSM with a minimum set of orthogonal components and confers minimized leaky reactions and fast kinetics. The FSM demonstrates the capability of sensing the temporal orders of two microRNAs, highlighting its potential for temporally resolved biosensing and smart therapeutics.

Novel RNase H Inhibitors Blocking RNA-directed Strand Displacement DNA Synthesis by HIV-1 Reverse Transcriptase

In retroviruses, strand displacement DNA-dependent DNA polymerization catalyzed by the viral reverse transcriptase (RT) is required to synthesize double-stranded proviral DNA. In addition, strand displacement during RNA-dependent DNA synthesis is critical to generate high-quality cDNA for use in molecular biology and biotechnology. In this work, we show that the loss of RNase H activity due to inactivating mutations in HIV-1 RT (e.g. D443N or E478Q) has no significant effect on strand displacement while copying DNA templates, but has a large impact on DNA polymerization in reactions carried out with RNA templates. Similar effects were observed with β-thujaplicinol and other RNase H active site inhibitors, including compounds with dual activity (i.e., characterized also as inhibitors of HIV-1 integrase and/or the RT DNA polymerase). Among them, dual inhibitors of HIV-1 RT DNA polymerase/RNase H activities, containing a 7-hydroxy-6-nitro-2H-chromen-2-one pharmacophore were found to be very potent and effective strand displacement inhibitors in RNA-dependent DNA polymerization reactions. These findings might be helpful in the development of transcriptomics technologies to obtain more uniform read coverages when copying long RNAs and for the construction of more representative libraries avoiding biases towards 5' and 3' ends, while providing valuable information for the development of novel antiretroviral agents.

Programming cell-free biosensors with DNA strand displacement circuits

Cell-free biosensors are powerful platforms for monitoring human and environmental health. Here, we expand their capabilities by interfacing them with toehold-mediated strand displacement circuits, a dynamic DNA nanotechnology that enables molecular computation through programmable interactions between nucleic acid strands. We develop design rules for interfacing a small molecule sensing platform called ROSALIND with toehold-mediated strand displacement to construct hybrid RNA–DNA circuits that allow fine-tuning of reaction kinetics. We use these design rules to build 12 different circuits that implement a range of logic functions (NOT, OR, AND, IMPLY, NOR, NIMPLY, NAND). Finally, we demonstrate a circuit that acts like an analog-to-digital converter to create a series of binary outputs that encode the concentration range of the molecule being detected. We believe this work establishes a pathway to create ‘smart’ diagnostics that use molecular computations to enhance the speed and utility of biosensors.

Equipping ROSALIND, a cell-free biosensing platform, with information processing circuits based on toehold-mediated DNA strand displacement enhances sensor performance and enables logic gate computation.

Programmable allosteric DNA regulations for molecular networks and nanomachines

Structure-based molecular regulations have been widely adopted to modulate protein networks in cells and recently developed to control allosteric DNA operations in vitro. However, current examples of programmable allosteric signal transmission through integrated DNA networks are stringently constrained by specific design requirements. Developing a new, more general, and programmable scheme for establishing allosteric DNA networks remains challenging. Here, we developed a general strategy for programmable allosteric DNA regulations that can be finely tuned by varying the dimensions, positions, and number of conformational signals. By programming the allosteric signals, we realized fan-out/fan-in DNA gates and multiple-layer DNA cascading networks, as well as expanding the approach to long-range allosteric signal transmission through tunable DNA origami nanomachines ~100 nm in size. This strategy will enable programmable and complex allosteric DNA networks and nanodevices for nanoengineering, chemical, and biomedical applications displaying sense-compute-actuate molecular functionalities.

Multiplex SNP Genotyping Using SWITCH: Sequence-Specific Nanoparticle with Interpretative Toehold-Mediated Sequence Decoding in Hydrogel

Single nucleotide polymorphisms (SNPs) that can alter phenotypes of individuals play a pivotal role in disease development and, more importantly, responses to therapy. However, SNP genotyping has been challenging due to the similarity of SNP alleles and their low concentration in biological samples. Sequence-specific nanoparticle with interpretative toehold-mediated sequence decoding in hydrogel (SWITCH) for multiplex SNP genotyping is presented. The encoding with gold nanoparticle probes transduces each SNP target to ≈1000 invaders with prominently different sequences between wild and mutant types, featuring polymerase chain reaction (PCR)-free amplification. Subsequently, the toehold-mediated DNA replacement in hydrogel microparticles decodes the invaders via SNP-specific fluorescence signals. The 4-plex detection of the warfarin-associated SNP targets spiked in commercially validated human serum (S1-100ML, Merck) is successfully demonstrated with excellent specificity. This work is the first technology development presenting PCR-free, multiplex SNP genotyping with a single reporting fluorophore, to the best of knowledge.

Toehold-mediated strand displacement to measure released product from self-cleaving ribozymes

This paper presents a probe comprising a fluorophore and a quencher, enabling measurement of released product from self-cleaving hammerhead ribozyme, without labeled RNA molecules, regular sampling or use of polyacrylamide gels. The probe is made of two DNA strands; one strand is labeled with a fluorophore at its 5'-end, while the other strand is labeled with a quencher at its 3'-end. These two DNA strands are perfectly complementary, but with a 3'-overhang of the fluorophore strand. These unpaired nucleotides act as a toehold, which is utilized by a detached cleaved fragment (coming from a self-cleaving hammerhead ribozyme) as the starting point for a strand displacement reaction. This reaction causes the separation of the fluorophore strand from the quencher strand, culminating in fluorescence, detectable in a plate reader. Notably, the emitted fluorescence is proportional to the amount of detached cleaved-off RNAs, displacing the DNA quencher strand. This method can replace or complement radio-hazardous unstable ³²P as a method of measurement of the product release from ribozyme cleavage reactions; it also eliminates the need for polyacrylamide gels, for the same purpose. Critically, this method allows to distinguish between the total amount of cleaved ribozymes and the amount of detached fragments, resulting from that cleavage reaction.

Rational design of allosterically regulated toehold mediated strand displacement circuits for sensitive and on-site detection of small molecule metabolites

Development of small molecule biosensors enables rapid and de-centralized small molecule detection that meets the demands of routine health monitoring and rapid diagnosis. Among them, allosteric transcription factor (aTF)-based biosensors have shown potential in modular design of small molecule detection platforms due to their ligand-regulated DNA binding activity. Here, we expand the capabilities of a biosensor that leverages the aTF-based regulation of toehold-mediated strand displacement (TMSD) circuits for uric acid (UA) detection in non-invasive salivary samples by utilizing the UA-responsive aTF HucR. The impact of the low ligand affinity of the native HucR was addressed by engineering a two-pass TMSD circuit with in silico rational design. This combined strategy achieved enrichment of the output signal and overcame the negative impact of the matrix effect on the sensitivity and overall response of the biosensor when using real samples, which enabled semi-quantitative detection in the normal salivary UA levels. As well, enhancements provided by the two-pass design halved the turnaround time to less than 15 minutes. To sum up, the two-cycle DNA circuit design enabled aTF-based simple, rapid and one-step non-invasive salivary UA detection, showing its potential in metabolite detection for health monitoring.

Nucleic acid-based molecular computation heads towards cellular applications

Nucleic acids, with the advantages of programmability and biocompatibility, have been widely used to design different kinds of novel biocomputing devices. Recently, nucleic acid-based molecular computing has shown promise in making the leap from the test tube to the cell. Such molecular computing can perform logic analysis within the confines of the cellular milieu with programmable modulation of biological functions at the molecular level. In this review, we summarize the development of nucleic acid-based biocomputing devices that are rationally designed and chemically synthesized, highlighting the ability of nucleic acid-based molecular computing to achieve cellular applications in sensing, imaging, biomedicine, and bioengineering. Then we discuss the future challenges and opportunities for cellular and in vivo applications. We expect this review to inspire innovative work on constructing nucleic acid-based biocomputing to achieve the goal of precisely rewiring, even reconstructing cellular signal networks in a prescribed way.

A non-enzymatic, isothermal strand displacement and amplification assay for rapid detection of SARS-CoV-2 RNA

The current nucleic acid signal amplification methods for SARS-CoV-2 RNA detection heavily rely on the functions of biological enzymes which imposes stringent transportation and storage conditions, high cost and global supply shortages. Here, a non-enzymatic whole genome detection method based on a simple isothermal signal amplification approach is developed for rapid detection of SARS-CoV-2 RNA and potentially any types of nucleic acids regardless of their size. The assay, termed non-enzymatic isothermal strand displacement and amplification (NISDA), is able to quantify 10 RNA copies.µL⁻¹. In 164 clinical oropharyngeal RNA samples, NISDA assay is 100 % specific, and it is 96.77% and 100% sensitive when setting up in the laboratory and hospital, respectively. The NISDA assay does not require RNA reverse-transcription step and is fast (<30 min), affordable, highly robust at room temperature (>1 month), isothermal (42 °C) and user-friendly, making it an excellent assay for broad-based testing.

The reliance on enzymes in SARS-CoV-2 RNA detection imposes limits on transport and storage conditions. Here the authors use non-enzymatic isothermal amplification to detect RNA with no need for reverse transcription.

A last-in first-out stack data structure implemented in DNA

DNA-based memory systems are being reported with increasing frequency. However, dynamic DNA data structures able to store and recall information in an ordered way, and able to be interfaced with external nucleic acid computing circuits, have so far received little attention. Here we present an in vitro implementation of a stack data structure using DNA polymers. The stack is able to record combinations of two different DNA signals, release the signals into solution in reverse order, and then re-record. We explore the accuracy limits of the stack data structure through a stochastic rule-based model of the underlying polymerisation chemistry. We derive how the performance of the stack increases with the efficiency of washing steps between successive reaction stages, and report how stack performance depends on the history of stack operations under inefficient washing. Finally, we discuss refinements to improve molecular synchronisation and future open problems in implementing an autonomous chemical data structure.

DNA is becoming increasingly used as a medium to store non-genetic information. Here the authors present a dynamic stack data structure implemented as a DNA polymer chemistry able to record and retrieve signals in a last-in first-out order.

Integration of chemically modified nucleotides with DNA strand displacement reactions for applications in living systems

Watson-Crick base pairing rules provide a powerful approach for engineering DNA-based nanodevices with programmable and predictable behaviors. In particular, DNA strand displacement reactions have enabled the development of an impressive repertoire of molecular devices with complex functionalities. By relying on DNA to function, dynamic strand displacement devices represent powerful tools for the interrogation and manipulation of biological systems. Yet, implementation in living systems has been a slow process due to several persistent challenges, including nuclease degradation. To circumvent these issues, researchers are increasingly turning to chemically modified nucleotides as a means to increase device performance and reliability within harsh biological environments. In this review, we summarize recent progress toward the integration of chemically modified nucleotides with DNA strand displacement reactions, highlighting key successes in the development of robust systems and devices that operate in living cells and in vivo. We discuss the advantages and disadvantages of commonly employed modifications as they pertain to DNA strand displacement, as well as considerations that must be taken into account when applying modified oligonucleotide to living cells. Finally, we explore how chemically modified nucleotides fit into the broader goal of bringing dynamic DNA nanotechnology into the cell, and the challenges that remain. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Diagnostic Tools > Biosensing.

Minimizing Leakage in Stacked Strand Exchange Amplification Circuits

Signal amplification is ubiquitous in biology and engineering. Protein enzymes, such as DNA polymerases, can routinely achieve >10⁶-fold signal increase, making them powerful tools for signal enhancement. Considerable signal amplification can also be achieved using nonenzymatic, cascaded nucleic acid strand exchange reactions. However, the practical application of such kinetically trapped circuits has so far proven difficult due to uncatalyzed leakage of the cascade. We now demonstrate that strategically positioned mismatches between circuit components can reduce unprogrammed hybridization reactions and therefore greatly diminish leakage. In consequence, we were able to synthesize a three-layer catalytic hairpin assembly cascade that could operate in a single tube and that yielded 3.7 × 10⁴-fold signal amplification in only 4 h, a greatly improved performance relative to previous cascades. This advance should facilitate the implementation of nonenzymatic signal amplification in molecular diagnostics, as well as inform the design of a wide variety of increasingly intricate nucleic acid computation circuits.

Dynamically elongated associative toehold for tuning DNA circuit kinetics and thermodynamics

Associative toehold is a powerful concept enabling efficient combinatorial computation in DNA circuit. A longer association length boosts circuit kinetics and equilibrium signal but results in higher leak rate. We reconcile this trade-off by using a hairpin lock design to dynamically elongate the effective associative toehold length in response to the input target. Design guidelines were established to achieve robust elongation without incurring additional leakages. Three hairpin initiators with different combinations of elongated associative toehold (4 → 6 nt, 5 → 8 nt and 6 → 9 nt) were shortlisted from the design framework for further discussion. The circuit performance improved in terms of reaction kinetics, equilibrium signal generated and limit of detection. Overall, the elongated associative toehold served as a built-in function to stabilize and favour the forward, desired reaction when triggered.

Biocomputing Based on DNA Strand Displacement Reactions

The high sequence specificity and precise base complementary pairing principle of DNA provides a rich orthogonal molecular library for molecular programming, making it one of the most promising materials for developing bio-compatible intelligence. In recent years, DNA has been extensively studied and applied in the field of biological computing. Among them, the toehold-mediated strand displacement reaction (SDR) with properties including enzyme free, flexible design and precise control, have been extensively used to construct biological computing circuits. This review provides a systemic overview of SDR design principles and the applications. Strategies for designing DNA-only, enzymes-assisted, other molecules-involved and external stimuli-controlled SDRs are described. The recently realized computing functions and the application of DNA computing in other fields are introduced. Finally, the advantages and challenges of SDR-based computing are discussed.

Hairpin DNA-Mediated isothermal amplification (HDMIA) techniques for nucleic acid testing

Nucleic acid detection is of great importance in a variety of areas, from life science and clinical diagnosis to environmental monitoring and food safety. Unfortunately, nucleic acid targets are always found in trace amounts and their response signals are difficult to be detected. Amplification mechanisms are then practically needed to either duplicate nucleic acid targets or enhance the detection signals. Polymerase chain reaction (PCR) is one of the most popular and powerful techniques for nucleic acid analysis. But the requirement of costly devices for precise thermo-cycling procedures in PCR has severely hampered the wide applications of PCR. Fortunately, isothermal molecular reactions have emerged as promising alternatives. The past decade has witnessed significant progress in the research of isothermal molecular reactions utilizing hairpin DNA probes (HDPs). Based on the nucleic acid strand interaction mechanisms, the hairpin DNA-mediated isothermal amplification (HDMIA) techniques can be mainly divided into three categories: strand assembly reactions, strand decomposition reactions, and strand creation reactions. In this review, we introduce the basics of HDMIA methods, including the sensing principles, the basic and advanced designs, and their wide applications, especially those benefiting from the utilization of G-quadruplexes and nanomaterials during the past decade. We also discuss the current challenges encountered, highlight the potential solutions, and point out the possible future directions in this prosperous research area.

Rapid Visual Authentication Based on DNA Strand Displacement

Novel ways to track and verify items of a high value or security is an ever-present need. Taggants made from deoxyribonucleic acid (DNA) have several advantageous properties, such as high information density and robust synthesis; however, existing methods require laboratory techniques to verify, limiting applications. Here, we leverage DNA nanotechnology to create DNA taggants that can be validated in the field in seconds to minutes with a simple equipment. The system is driven by toehold-mediated strand-displacement reactions where matching oligonucleotide sequences drive the generation of a fluorescent signal through the potential energy of base pairing. By pooling different "input" oligonucleotide sequences in a taggant and spatially separating "reporter" oligonucleotide sequences on a paper ticket, unique, sequence-driven patterns emerge for different taggant formulations. Algorithmically generated oligonucleotide sequences show no crosstalk and ink-embedded taggants maintain activity for at least 99 days at 60 °C (equivalent to nearly 2 years at room temperature). The resulting fluorescent signals can be analyzed by the eye or a smartphone when paired with a UV flashlight and filtered glasses.

Handhold-Mediated Strand Displacement: A Nucleic Acid Based Mechanism for Generating Far-from-Equilibrium Assemblies through Templated Reactions

The use of templates is a well-established method for the production of sequence-controlled assemblies, particularly long polymers. Templating is canonically envisioned as akin to a self-assembly process, wherein sequence-specific recognition interactions between a template and a pool of monomers favor the assembly of a particular polymer sequence at equilibrium. However, during the biogenesis of sequence-controlled polymers, template recognition interactions are transient; RNA and proteins detach spontaneously from their templates to perform their biological functions and allow template reuse. Breaking template recognition interactions puts the product sequence distribution far from equilibrium, since specific product formation can no longer rely on an equilibrium dominated by selective copy-template bonds. The rewards of engineering artificial polymer systems capable of spontaneously exhibiting nonequilibrium templating are large, but fields like DNA nanotechnology lack the requisite tools; the specificity and drive of conventional DNA reactions rely on product stability at equilibrium, sequestering any recognition interaction in products. The proposed alternative is handhold-mediated strand displacement (HMSD), a DNA-based reaction mechanism suited to producing out-of-equilibrium products. HMSD decouples the drive and specificity of the reaction by introducing a transient recognition interaction, the handhold. We measure the kinetics of 98 different HMSD systems to prove that handholds can accelerate displacement by 4 orders of magnitude without being sequestered in the final product. We then use HMSD to template the selective assembly of any one product DNA duplex from an ensemble of equally stable alternatives, generating a far-from-equilibrium output. HMSD thus brings DNA nanotechnology closer to the complexity of out-of-equilibrium biological systems.

Information processing based on DNA toehold-mediated strand displacement (TMSD) reaction

SemiSynBio is an emerging topic toward the construction of platforms for next-generation information processing. Recent research has indicated its promising prospect toward information processing including algorithm design and pattern manipulation with the DNA TMSD reaction, which is one of the cores of the SemiSynBio technology route. The DNA TMSD reaction is the process in which an invader strand displaces the incumbent strand from the gate strand through initiation at the exposed toehold domain. Also, the DNA TMSD reaction generally involves three processes: toehold association, branch migration and strand disassociation. Herein, we review the recent progress on information processing with the DNA TMSD reaction. We highlight the diverse developments on information processing with the logic circuit, analog circuit, combinational circuit and information relay with the DNA origami structure. Additionally, we explore the current challenges and various trends toward the design and application of the DNA TMSD reaction in future information processing.