Control of DNA Strand Displacement Kinetics Using Toehold Exchange

Aptamer-controlled stimuli-responsive drug release

Aptamers have been widely researched and applied in nanomedicine due to their programmable, activatable, and switchable properties. However, there are few reviews on aptamer-controlled stimuli-responsive drug delivery. This article highlights the mechanisms and advantages of aptamers in the construction of stimuli-responsive drug delivery systems. We summarize the assembly/reconfiguration mechanisms of aptamers in controlled release systems. The assembly and drug release strategies of drug delivery systems are illustrated. Specifically, we focus on the binding mechanisms to the target and the factors that induce/inhibit the binding to the stimuli, such as strand, pH, light, and temperature. The applications of aptamer-based stimuli-responsive drug release are elaborated. The challenges are discussed, and the future directions are proposed.

Thermodynamics and Kinetics-Directed Regulation of Nucleic Acid-Based Molecular Recognition

Nucleic acid-based molecular recognition plays crucial roles in various fields like biosensing and disease diagnostics. To achieve optimal detection and analysis, it is essential to regulate the response performance of nucleic acid probes or switches to match specific application requirements by regulating thermodynamics and kinetics properties. However, the impacts of thermodynamics and kinetics theories on recognition performance are sometimes obscure and the relative conclusions are not intuitive. To promote the thorough understanding and rational utilization of thermodynamics and kinetics theories, this review focuses on the landmarks and recent advances of nucleic acid thermodynamics and kinetics and summarizes the nucleic acid thermodynamics and kinetics-based strategies for regulation of nucleic acid-based molecular recognition. This work hopes such a review can provide reference and guidance for the development and optimization of nucleic acid probes and switches in the future, as well as for advancements in other nucleic acid-related fields.

Strong sequence-dependence in RNA/DNA hybrid strand displacement kinetics

Strand displacement reactions underlie dynamic nucleic acid nanotechnology. The kinetic and thermodynamic features of DNA-based displacement reactions are well understood and well predicted by current computational models. By contrast, understanding of RNA/DNA hybrid strand displacement kinetics is limited, restricting the design of increasingly complex RNA/DNA hybrid reaction networks with more tightly regulated dynamics. Given the importance of RNA as a diagnostic biomarker, and its critical role in intracellular processes, this shortfall is particularly limiting for the development of strand displacement-based therapeutics and diagnostics. Herein, we characterise 22 RNA/DNA hybrid strand displacement systems, alongside 11 DNA/DNA systems, varying a range of common design parameters including toehold length and branch migration domain length. We observe  that differences in stability between RNA-DNA hybrids and DNA-DNA duplexes have large effects on strand displacement rates, with rates for equivalent sequences differing by up to 3 orders of magnitude. Crucially, however, this effect is strongly sequence-dependent, with RNA invaders strongly favoured in a system with RNA strands of high purine content, and disfavoured in a system when the RNA strands have low purine content. These results lay the groundwork for more general design principles, allowing for creation of de novo reaction networks with novel complexity while maintaining predictable reaction kinetics.

Rewireable Building Blocks for Enzyme-Powered DNA Computing Networks

Neural networks enable the processing of large, complex data sets with applications in disease diagnosis, cell profiling, and drug discovery. Beyond electronic computers, neural networks have been implemented using programmable biomolecules such as DNA; this confers unique advantages, such as greater portability, electricity-free operation, and direct analysis of patterns of biomolecules in solution. Analogous to bottlenecks in electronic computers, the computing power of DNA-based neural networks is limited by the ability to add more computing units, i.e., neurons. This limitation exists because current architectures require many nucleic acids to model a single neuron. Each additional neuron compounds existing problems such as long assembly times, high background signal, and cross-talk between components. Here, we test three strategies to solve this limitation and improve the scalability of DNA-based neural networks: (i) enzymatic synthesis for high-purity neurons, (ii) spatial patterning of neuron clusters based on their network position, and (iii) encoding neuron connectivity on a universal single-stranded DNA backbone. We show that neurons implemented via these strategies activate quickly, with a high signal-to-background ratio and process-weighted inputs. We rewired our modular neurons to demonstrate basic neural network motifs such as cascading, fan-in, and fan-out circuits. Finally, we designed a prototype two-layer microfluidic device to automate the operation of our circuits. We envision that our proposed design will help scale DNA-based neural networks due to its modularity, simplicity of synthesis, and compatibility with various neural network architectures. This will enable portable computing power for applications in portable diagnostics, compact data storage, and autonomous decision making for lab-on-a-chips.

Scalable DNA recognition circuits based on DNA strand displacement

DNA is a kind of nano-molecule considered to be computable on the molecular level, and the precise Watson-Crick principle of base pairing has made it possible for DNA to be a novel computer material. The DNA strand displacement technology has greatly facilitated the development of DNA computing in both logical and intelligent computation. In this paper, we proposed and implemented a molecular recognition circuit based on DNA strand displacement, which can achieve recognition and summation functions. This circuit has a simple molecular composition and is easily scalable. A cross-inhibition module was integrated based upon the molecular recognition circuit to construct a molecular comparator. Considering the advantages of modularity and the experimental feasibility of a scalable recognition circuit, it could be used as a pattern signal recognition and classification module in smart molecular circuits or biosensors.

Bacteriophage λ exonuclease and a 5'-phosphorylated DNA guide allow PAM-independent targeting of double-stranded nucleic acids

Sequence-specific recognition of double-stranded nucleic acids is essential for molecular diagnostics and in situ imaging. Clustered regularly interspaced short palindromic repeats and Cas systems rely on protospacer-adjacent motif (PAM)-dependent double-stranded DNA (dsDNA) recognition, limiting the range of targetable sequences and leading to undesired off-target effects. Using single-molecule fluorescence resonance energy transfer analysis, we discover the enzymatic activity of bacteriophage λ exonuclease (λExo). We show binding of 5'-phosphorylated single-stranded DNA (pDNA) to complementary regions on dsDNA and DNA-RNA duplexes, without the need for a PAM-like motif. Upon binding, the λExo-pDNA system catalytically digests the pDNA into nucleotides in the presence of Mg2+. This process is sensitive to mismatches within a wide range of the pDNA-binding region, resulting in exceptional sequence specificity and reduced off-target effects in various applications. The absence of a requirement for a specific motif such as a PAM sequence greatly broadens the range of targets. We demonstrate that the λExo-pDNA system is a versatile tool for molecular diagnostics, DNA computing and gene imaging applications.

Breast Tumor Diagnosis Based on Molecular Learning Vector Quantization Neural Networks

DNA nanotechnology plays a crucial role in precise cancer medicine. Currently, molecular logic circuits are applied to detect tumor-specific biomarkers and control the release of therapeutic drugs. However, these systems lack self-learning capabilities for intelligent diagnostics in biological samples, and their data processing capabilities are limited. Here, a molecular learning vector quantization neural network (LVQNN) model based on DNA strand displacement (DSD) technology for breast tumor diagnosis is developed. Compared to previous work, the molecular LVQNN boasts powerful computing abilities, handling high-dimensional data for intelligent cancer diagnosis. To verify the feasibility and versatility of the network, two distinct typical datasets are selected: one from a single source with cell morphology data from 569 cases, and a more extensive one spanning different populations and ages, with miRNA gene expression data from 1881 cases. By using the molecular LVQNN, diagnostic experiments are conducted on 50 and 120 public individuals from these two datasets, respectively, achieving accuracy rates of 94% and 97.5%. This study demonstrates that the LVQNN model exhibits significant advantages in breast cancer diagnosis and enhances diagnostic accuracy while introducing new approaches for intelligent cancer diagnosis, anticipated to bring significant breakthroughs and application prospects to precise cancer medicine.

Learning from Classic: DNA-Based Conditional Equilibrium Constant To Regulate Affinity "On-the-Fly" for Bioassays

Artificial programming of affinity is beneficial to optimize responsiveness in biomolecules for various applications. In one classical theory, one comprehensive parameter, conditional equilibrium constant (K'EDTA), can accurately and quantitatively define the affinity of ethylene diamine tetraacetic acid (EDTA) for metal ions. Learning from the classic, we have proposed a novel DNA-based conditional equilibrium constant (K'DNA) to regulate DNA probes' affinity and response "on-the-fly", long after the probe design and synthesis. Artificial regulation of affinity over several magnitudes has been simply realized via short oligonucleotides with different lengths, concentrations, and combinations. The thermodynamic response can be quantitatively simulated by one DNA-based conditional equilibrium constant (K'DNA), acting as an analogue to the classical EDTA system. The proof of concept of affinity programming also allows improved discrimination of single-nucleotide variants as well as assaying ribonuclease and doxycycline in a homogeneous solution. Therefore, the theory of DNA-based conditional equilibrium constant (K'DNA) will enable to engineer versatile DNA switches with programmable affinity in assays and bionanotechnology.

Understanding the relationship between sequences and kinetics of DNA strand displacements

Precisely modulating the kinetics of toehold-mediated DNA strand displacements (TMSD) is essential for its application in DNA nanotechnology. The sequence in the toehold region significantly influences the kinetics of TMSD. However, due to the large sample space resulting from various arrangements of base sequences and the resulted complex secondary structures, such a correlation is not intuitive. Herein, machine learning was employed to reveal the relationship between the kinetics of TMSD and the toehold sequence as well as the correlated secondary structure of invader strands. Key factors that influence the rate constant of TMSD were identified, such as the number of free hydrogen bonding sites in the invader, the number of free bases in the toehold, and the number of hydrogen bonds in intermediates. Moreover, a predictive model was constructed, which successfully achieved semi-quantitative prediction of rate constants of TMSD even with subtle distinctions in toehold sequence.

Programming gel automata shapes using DNA instructions

The ability to transform matter between numerous physical states or shapes without wires or external devices is a major challenge for robotics and materials design. Organisms can transform their shapes using biomolecules carrying specific information and localize at sites where transitions occur. Here, we introduce gel automata, which likewise can transform between a large number of prescribed shapes in response to a combinatorial library of biomolecular instructions. Gel automata are centimeter-scale materials consisting of multiple micro-segments. A library of DNA activator sequences can each reversibly grow or shrink different micro-segments by polymerizing or depolymerizing within them. We develop DNA activator designs that maximize the extent of growth and shrinking, and a photolithography process for precisely fabricating gel automata with elaborate segmentation patterns. Guided by simulations of shape change and neural networks that evaluate gel automata designs, we create gel automata that reversibly transform between multiple, wholly distinct shapes: four different letters and every even or every odd numeral. The sequential and repeated metamorphosis of gel automata demonstrates how soft materials and robots can be digitally programmed and reprogrammed with information-bearing chemical signals.

Programming Fast DNA Amplifier Circuits with Versatile Toehold Exchange Pathway

DNA amplifier circuits establish powerful tools to dynamically control molecular assembly for computation, sensing, and biological applications. However, the slow reaction speed remains a major barrier to their practical utility. Here, diverse fast DNA amplifier circuits termed toehold exchange polymerization (TEP) and toehold exchange catalysis (TEC) using toehold exchange-mediated assembly as a fundamental mechanism are built. Both TEP and TEC with a duplex and a hairpin can respond within minutes to diverse nucleic acid inputs with high fidelity. In addition, the circuits can amplify live-cell signals for fluorescence imaging target RNA dynamics and discriminating different cell lines. Compared with existing DNA circuits that involve time scales of hours for transducing small signals, TEP and TEC exhibit much faster dynamics, simpler design, and comparable sensitivity. These features make TEP and TEC promising platforms to develop programmable nucleic acid tools and devices and to create fast sensing and processing systems, amenable to wide practical applications.

Nucleic acid-responsive smart systems for controlled cargo delivery

Stimulus-responsive delivery systems allow controlled, highly regulated, and efficient delivery of various cargos while minimizing side effects. Owing to the unique properties of nucleic acids, including the ability to adopt complex structures by base pairing, their easy synthesis, high specificity, shape memory, and configurability, they have been employed in autonomous molecular motors, logic circuits, reconfigurable nanoplatforms, and catalytic amplifiers. Moreover, the development of nucleic acid (NA)-responsive intelligent delivery vehicles is a rapidly growing field. These vehicles have attracted much attention in recent years due to their programmable, controllable, and reversible properties. In this work, we review several types of NA-responsive controlled delivery vehicles based on locks and keys, including DNA/RNA-responsive, aptamer-responsive, and CRISPR-responsive, and summarize their advantages and limitations.

SemiSynBio: A new era for neuromorphic computing

Neuromorphic computing has the potential to achieve the requirements of the next-generation artificial intelligence (AI) systems, due to its advantages of adaptive learning and parallel computing. Meanwhile, biocomputing has seen ongoing development with the rise of synthetic biology, becoming the driving force for new generation semiconductor synthetic biology (SemiSynBio) technologies. DNA-based biomolecules could potentially perform the functions of Boolean operators as logic gates and be used to construct artificial neural networks (ANNs), providing the possibility of executing neuromorphic computing at the molecular level. Herein, we briefly outline the principles of neuromorphic computing, describe the advances in DNA computing with a focus on synthetic neuromorphic computing, and summarize the major challenges and prospects for synthetic neuromorphic computing. We believe that constructing such synthetic neuromorphic circuits will be an important step toward realizing neuromorphic computing, which would be of widespread use in biocomputing, DNA storage, information security, and national defense.

Single-molecule force spectroscopy of toehold-mediated strand displacement

Toehold-mediated strand displacement (TMSD) is extensively utilized in dynamic DNA nanotechnology and for a wide range of DNA or RNA-based reaction circuits. Investigation of TMSD kinetics typically relies on bulk fluorescence measurements providing effective, bulk-averaged reaction rates. Information on individual molecules or even base pairs is scarce. In this work, we explore the dynamics of strand displacement processes at the single-molecule level using single-molecule force spectroscopy with a microfluidics-enhanced optical trap supported by state-of-the-art coarse-grained simulations. By applying force, we can trigger and observe TMSD in real-time with microsecond and nanometer resolution. We find TMSD proceeds very rapidly under load with single step times of 1 µs. Tuning invasion efficiency by introducing mismatches allows studying thousands of forward/backward invasion events on a single molecule and analyze the kinetics of the invasion process. Extrapolation to zero force reveals single step times for DNA invading DNA four times faster than for RNA invading RNA. We also study the kinetics of DNA invading RNA, a process that in the absence of force would rarely occur. Our results reveal the importance of sequence effects for the TMSD process and have relevance for a wide range of applications in nucleic acid nanotechnology and synthetic biology.

Temporally controlled multistep division of DNA droplets for dynamic artificial cells

Synthetic droplets mimicking bio-soft matter droplets formed via liquid-liquid phase separation (LLPS) in living cells have recently been employed in nanobiotechnology for artificial cells, molecular robotics, molecular computing, etc. Temporally controlling the dynamics of synthetic droplets is essential for developing such bio-inspired systems because living systems maintain their functions based on the temporally controlled dynamics of biomolecular reactions and assemblies. This paper reports the temporal control of DNA-based LLPS droplets (DNA droplets). We demonstrate the timing-controlled division of DNA droplets via time-delayed division triggers regulated by chemical reactions. Controlling the release order of multiple division triggers results in order control of the multistep droplet division, i.e., pathway-controlled division in a reaction landscape. Finally, we apply the timing-controlled division into a molecular computing element to compare microRNA concentrations. We believe that temporal control of DNA droplets will promote the design of dynamic artificial cells/molecular robots and sophisticated biomedical applications.

Enhancing DNA-based nanodevices activation through cationic peptide acceleration of strand displacement

Dynamic DNA-based nanodevices offer versatile molecular-level operations, but the majority of them suffer from sluggish kinetics, impeding the advancement of device complexity. In this work, we present the self-assembly of a cationic peptide with DNA to expedite toehold-mediated DNA strand displacement (TMSD) reactions, a fundamental mechanism enabling the dynamic control and actuation of DNA nanostructures. The target DNA is modified with a fluorophore and a quencher, so that the TMSD process can be monitored by recording the time-dependent fluorescence changes. The boosting effect of the peptides is found to be dependent on the peptide/DNA N/P ratio, the toehold/invader binding affinity, and the ionic strength with stronger effects observed at lower ionic strengths, suggesting that electrostatic interactions play a key role. Furthermore, we demonstrate that the cationic peptide enhances the responsiveness and robustness of DNA machinery tweezers or logic circuits (AND and OR) involving multiple strand displacement reactions in parallel and cascade, highlighting its broad utility across DNA-based systems of varying complexity. This work offers a versatile approach to enhance the efficiency of toehold-mediated DNA nanodevices, facilitating flexible design and broader applications.

Kinetics of Strand Displacement Reaction with Acyclic Artificial Nucleic Acids

Toehold-mediated strand displacement (TMSD) reaction, one of the DNA nanotechnologies, has great potential as s biological programmable platform in the cellular environment. Various artificial nucleic acids have been developed to improve stability and affinity for biological applications. However, the lack of understanding of the kinetics of TMSD reaction among artificial nucleic acids has limited their applications. We herein systematically characterized the kinetics of TMSD reactions with acyclic xeno nucleic acids (XNAs): serinol nucleic acid (SNA), acyclic D-threoninol nucleic acid (D-aTNA), and acyclic L-threoninol nucleic acid (L-aTNA). We found that the strand displacement reactions by D-aTNA and by L-aTNA were highly dependent on temperature. D-aTNA and L-aTNA systems were orthogonal to each other, and chirality of the input can be switched by using SNA as an interface. We also applied TMSD reactions of XNAs to a seesaw gate amplification system which utilizes the orthogonality. This work will contribute to the developments of thermoresponsive and bioorthogonal nucleic acid circuits.

Spatially Localized Entropy-Driven Evolution of Nucleic Acid-Based Constitutional Dynamic Networks for Intracellular Imaging and Spatiotemporal Programmable Gene Therapy

The primer-guided entropy-driven high-throughput evolution of the DNA-based constitutional dynamic network, CDN, is introduced. The entropy gain associated with the process provides a catalytic principle for the amplified emergence of the CDN. The concept is applied to develop a programmable, spatially localized DNA circuit for effective in vitro and in vivo theranostic, gene-regulated treatment of cancer cells. The localized circuit consists of a DNA tetrahedron core modified at its corners with four tethers that include encoded base sequences exhibiting the capacity to emerge and assemble into a [2 × 2] CDN. Two of the tethers are caged by a pair of siRNA subunits, blocking the circuit into a mute, dynamically inactive configuration. In the presence of miRNA-21 as primer, the siRNA subunits are displaced, resulting in amplified release of the siRNAs silencing the HIF-1α mRNA and fast dynamic reconfiguration of the tethers into a CDN. The resulting CDN is, however, engineered to be dynamically reconfigured by miRNA-155 into an equilibrated mixture enriched with a DNAzyme component, catalyzing the cleavage of EGR-1 mRNA. The DNA tetrahedron nanostructure stimulates enhanced permeation into cancer cells. The miRNA-triggered entropy-driven reconfiguration of the spatially localized circuit leads to the programmable, cooperative bis-gene-silencing of HIF-1α and EGR-1 mRNAs, resulting in the effective and selective apoptosis of breast cancer cells and effective inhibition of tumors in tumor bearing mice.

Strategies to Reduce Promoter-Independent Transcription of DNA Nanostructures and Strand Displacement Complexes

Bacteriophage RNA polymerases, in particular T7 RNA polymerase (RNAP), are well-characterized and popular enzymes for many RNA applications in biotechnology both in vitro and in cellular settings. These monomeric polymerases are relatively inexpensive and have high transcription rates and processivity to quickly produce large quantities of RNA. T7 RNAP also has high promoter-specificity on double-stranded DNA (dsDNA) such that it only initiates transcription downstream of its 17-base promoter site on dsDNA templates. However, there are many promoter-independent T7 RNAP transcription reactions involving transcription initiation in regions of single-stranded DNA (ssDNA) that have been reported and characterized. These promoter-independent transcription reactions are important to consider when using T7 RNAP transcriptional systems for DNA nanotechnology and DNA computing applications, in which ssDNA domains often stabilize, organize, and functionalize DNA nanostructures and facilitate strand displacement reactions. Here we review the existing literature on promoter-independent transcription by bacteriophage RNA polymerases with a specific focus on T7 RNAP, and provide examples of how promoter-independent reactions can disrupt the functionality of DNA strand displacement circuit components and alter the stability and functionality of DNA-based materials. We then highlight design strategies for DNA nanotechnology applications that can mitigate the effects of promoter-independent T7 RNAP transcription. The design strategies we present should have an immediate impact by increasing the rate of success of using T7 RNAP for applications in DNA nanotechnology and DNA computing.

Kinetic Proofreading Can Enhance Specificity in a Nonenzymatic DNA Strand Displacement Network

Kinetic proofreading is used throughout natural systems to enhance the specificity of molecular recognition. At its most basic level, kinetic proofreading uses a supply of chemical fuel to drive a recognition interaction out of equilibrium, allowing a single free-energy difference between correct and incorrect targets to be exploited two or more times. Despite its importance in biology, there has been little effort to incorporate kinetic proofreading into synthetic systems in which molecular recognition is important, such as nucleic acid nanotechnology. In this article, we introduce a DNA strand displacement-based kinetic proofreading motif, showing that the consumption of a DNA-based fuel can be used to enhance molecular recognition during a templated dimerization reaction. We then show that kinetic proofreading can enhance the specificity with which a probe discriminates single nucleotide mutations, both in terms of the initial rate with which the probe reacts and the long-time behavior.

A Dual-Recognition Fluorescence Enzyme-Linked Immunosorbent Assay for Specific Detection of Intact Lipid Nanoparticles via a Localized Scaffolding Autocatalytic DNA Circuit Amplifier

Lipid nanoparticles (LNPs) are emerging as one of the most promising drug delivery systems. The long-circulating effect of intact LNPs (i-LNPs) is the key to efficacy and toxicity in vivo. However, the significant challenge is specific and sensitive detection of i-LNPs. Herein, a dual-recognition fluorescence enzyme-linked immunosorbent assay (DR-FELISA) was developed to directly isolate and detect i-LNPs by combining dual-recognition separation with a one-step signal amplification strategy. The microplates captured and enriched i-LNPs through antibody-antigen reaction. Dual-chol probes were spontaneously introduced into the lipid bilayer of captured i-LNPs, converting the detection of i-LNPs into the detection of double-cholesterol probes. Finally, the end of the dual-chol probes initiated the localized scaffolding autocatalytic DNA circuits (SADC) system for further signal amplification. The SADC system provides a sensitive and efficient amplifier through localized network structures and self-assembled triggers. Simultaneous recognition of i-LNPs surface PEG-lipid and lipid bilayer structures significantly eliminates interference from biological samples. i-LNPs were detected with high selectivity, ranging from 0.2 to 1.25 mg/mL with a limit of detection of 0.1 mg/mL. Moreover, this method allows the isolation and quantitative analysis of different formulations of i-LNPs in serum samples with a satisfactory recovery rate ranging from 94.8 to 116.3%. Thus, the DR-FELISA method provides an advanced platform for the exclusive and sensitive detection of i-LNPs, providing new insights for the study of the quality and intracorporal process of complex formulations.

Controllable detection threshold achieved through the toehold switch system in a mercury ion whole-cell biosensor

Due to the toxicity of mercury and its harmful effects on human health, it is essential to establish a low-cost, highly sensitive and highly specific monitoring method with a wide detection range, ideally with a simple visual readout. In this study, a whole-cell biosensor with adjustable detection limits was developed for the detection of mercury ions in water samples, allowing controllable threshold detection with an expanded detection range. Gene circuits were constructed by combining the toehold switch system with lactose operon, mercury-ion-specific operon, and inducible red fluorescent protein gene. Using MATLAB for design and selection, a total of eleven dual-input single-output sensing logic circuits were obtained based on the basic logic of gene circuit construction. Then, biosensor DTS-3 was selected based on its fluorescence response at different isopropyl β-D-Thiogalactoside (IPTG) concentrations, exhibiting the controllable detection threshold. At 5-20 μM IPTG, DTS-3 can achieve variable threshold detection in the range of 0.005-0.0075, 0.06-0.08, 1-2, and 4-6 μM mercury ion concentrations, respectively. Specificity experiments demonstrated that DTS-3 exhibits good specificity, not showing fluorescence response changes compared with other metal ions. Furthermore spiked sample experiments demonstrated its good resistance to interference, allowing it to distinguish mercury ion concentrations as low as 7.5 nM by the naked eye and 5 nM using a microplate reader. This study confirms the feasibility and performance of biosensor with controllable detection threshold, providing a new detection method and new ideas for expanding the detection range of biosensors while ensuring rapid and convenient measurements without compromising sensitivity.

Rapid, Multiplexed, and Enzyme-Free Nucleic Acid Detection Using Programmable Aptamer-Based RNA Switches

Rapid, simple, and low-cost diagnostic technologies are crucial tools for combatting infectious disease. We describe a class of aptamer-based RNA switches or aptaswitches that recognize target nucleic acid molecules and initiate folding of a reporter aptamer. Aptaswitches can detect virtually any sequence and provide an intense fluorescent readout without intervening enzymes, generating signals in as little as 5 minutes and enabling detection by eye with minimal equipment. Aptaswitches can be used to regulate folding of seven fluorogenic aptamers, providing a general means of controlling aptamers and an array of multiplexable reporter colors. Coupling isothermal amplification reactions with aptaswitches, we reach sensitivities down to 1 RNA copy/μL in one-pot reactions. Application of multiplexed all-in-one reactions against RNA from clinical saliva samples yields an overall accuracy of 96.67% for detection of SARS-CoV-2 in 30 minutes. Aptaswitches are thus versatile tools for nucleic acid detection that are readily integrated into rapid diagnostic assays.

Erasable and Field Programmable DNA Circuits Based on Configurable Logic Blocks

DNA is commonly employed as a substrate for the building of artificial logic networks due to its excellent biocompatibility and programmability. Till now, DNA logic circuits are rapidly evolving to accomplish advanced operations. Nonetheless, nowadays, most DNA circuits remain to be disposable and lack of field programmability and thereby limits their practicability. Herein, inspired by the Configurable Logic Block (CLB), the CLB-based erasable field-programmable DNA circuit that uses clip strands as its operation-controlling signals is presented. It enables users to realize diverse functions with limited hardware. CLB-based basic logic gates (OR and AND) are first constructed and demonstrated their erasability and field programmability. Furthermore, by adding the appropriate operation-controlling strands, multiple rounds of programming are achieved among five different logic operations on a two-layer circuit. Subsequently, a circuit is successfully built to implement two fundamental binary calculators: half-adder and half-subtractor, proving that the design can imitate silicon-based binary circuits. Finally, a comprehensive CLB-based circuit is built that enables multiple rounds of switch among seven different logic operations including half-adding and half-subtracting. Overall, the CLB-based erasable field-programmable circuit immensely enhances their practicability. It is believed that design can be widely used in DNA logic networks due to its efficiency and convenience.

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.

Nonlinear compliance of NompC gating spring and its implication in mechanotransduction

Cytoskeleton-tethered mechanosensitive channels (MSCs) utilize compliant proteins or protein domains called gating springs to convert mechanical stimuli into electric signals, enabling sound and touch sensation and proprioception. The mechanical properties of these gating springs, however, remain elusive. Here, we explored the mechanical properties of the homotetrameric NompC complex containing long ankyrin-repeat domains (ARDs). We developed a toehold-mediated strand displacement approach to tether single membrane proteins, allowing us to exert force on them and precisely measure their absolute extension using optical tweezers. Our findings revealed that each ARD has a low stiffness of ~0.7 pN/nm and begins to unfold stepwise at ~7 pN, leading to nonlinear compliance. Our calculations indicate that this nonlinear compliance may help regulate NompC's sensitivity, dynamic range, and kinetics to detect mechanical stimuli. Overall, our research highlights the importance of a compliant and unfolding-refolding gating spring in facilitating a graded response of MSC ion transduction across a wide spectrum of mechanical stimuli.

Live-Cell Imaging of MicroRNA Expression via Photoinduced Electron Transfer Controlled by Catalytic Hairpin Assembly

MicroRNAs (miRNAs) serve as emerging biomarkers for a range of diseases, and their quantitative analysis draws increasing attention. Yet, current invasive methods limit continuous tracking within living cells. To overcome this, a nonenzymatic DNA-based nanoprobe is developed for dynamic, noninvasive miRNA tracking via live-cell imaging. This probe features a unique hairpin DNA structure with five guanines that act as internal quenchers, suppressing fluorescence from an attached fluorophore via photoinduced electron transfer. Target miRNA initiates toehold-mediated strand displacement, restoring, and amplifying the fluorescence signal. Additionally, by introducing a single mismatch to the hairpin DNA, the nanoprobe's sensitivity is significantly enhanced, lowering the detection limit to about 60 pM without compromising specificity. To optimize intracellular delivery for prolonged monitoring, the nanoprobe is encapsulated within multilamellar lipid nanovesicles, fluorescently labeled for dual-wavelength ratiometric analysis. The proposed nanoprobe demonstrates a significant advance in live-cell miRNA detection, promising enhanced in situ analysis for a better understanding of miRNAs' pathophysiological function.

Autonomous assembly and disassembly of gliding molecular robots regulated by a DNA-based molecular controller

In recent years, there has been a growing interest in engineering dynamic and autonomous systems with robotic functionalities using biomolecules. Specifically, the ability of molecular motors to convert chemical energy to mechanical forces and the programmability of DNA are regarded as promising components for these systems. However, current systems rely on the manual addition of external stimuli, limiting the potential for autonomous molecular systems. Here, we show that DNA-based cascade reactions can act as a molecular controller that drives the autonomous assembly and disassembly of DNA-functionalized microtubules propelled by kinesins. The DNA controller is designed to produce two different DNA strands that program the interaction between the microtubules. The gliding microtubules integrated with the controller autonomously assemble to bundle-like structures and disassemble into discrete filaments without external stimuli, which is observable by fluorescence microscopy. We believe this approach to be a starting point toward more autonomous behavior of motor protein-based multicomponent systems with robotic functionalities.

ANNaMo: Coarse-grained modeling for folding and assembly of RNA and DNA systems

The folding of RNA and DNA strands plays crucial roles in biological systems and bionanotechnology. However, studying these processes with high-resolution numerical models is beyond current computational capabilities due to the timescales and system sizes involved. In this article, we present a new coarse-grained model for investigating the folding dynamics of nucleic acids. Our model represents three nucleotides with a patchy particle and is parameterized using well-established nearest-neighbor models. Thanks to the reduction of degrees of freedom and to a bond-swapping mechanism, our model allows for simulations at timescales and length scales that are currently inaccessible to more detailed models. To validate the performance of our model, we conducted extensive simulations of various systems: We examined the thermodynamics of DNA hairpins, capturing their stability and structural transitions, the folding of an MMTV pseudoknot, which is a complex RNA structure involved in viral replication, and also explored the folding of an RNA tile containing a k-type pseudoknot. Finally, we evaluated the performance of the new model in reproducing the melting temperatures of oligomers and the dependence on the toehold length of the displacement rate in toehold-mediated displacement processes, a key reaction used in molecular computing. All in all, the successful reproduction of experimental data and favorable comparisons with existing coarse-grained models validate the effectiveness of the new model.

Double base mismatches mediated catalytic hairpin assembly for enzyme-free single-base mutation detection: integrating signal recognition and amplification in one

Single nucleotide polymorphism (SNP) biosensors are emerging rapidly for their promising applications in human disease prevention diagnosis, treatment, and prognosis. However, it remains a bottleneck in equipping simple and stable biosensors with the traits of high sensitivity, non-enzyme, and low cost. Double base mismatches mediated chain displacement reactions have attracted fascinating advantages of tailorable thermodynamics stability, non-enzyme, and excellent assembly compliance to involvement in SNP identification. As the base mismatch position and amount in DNA sequence can be artificially adjusted, it provides plenty of selectivity and specificity for exploring perfect biosensors. Herein, a biosensor with double base mismatches mediated catalytic hairpin assembly (CHA) is designed via one base mismatch in the toehold domain and the other base mismatch in the stem sequence of hairpin 1 (H1) by triggering CHA reaction to achieve selective amplification of the mutation target (MT) and fluorescence resonance energy transfer (FRET) effect that is composed of Cy3 and Cy5 terminally attached H1 and hairpin 2 (H2). Depending on the rationally designed base mismatch position and toehold length, the fabricated biosensors show superior SNP detection performance, exhibiting a good linearity with high sensitivity of 6.6 fM detection limit and a broad detection abundance of 1%. The proposed biosensor can be used to detect the KRAS mutation gene in real samples and obtain good recoveries between 106 and 116.99%. Remarkably, these extendible designs of base mismatches can be used for more types of SNP detection, providing flexible adjustment based on base mismatch position and toehold length variations, especially for their thermodynamic model for DNA-strand displacement reactions.

Building a stable and robust anti-interference DNA dissipation system by eliminating the accumulation of systemic specified errors

BACKGROUND

The emergence of DNA nanotechnology has enabled the systematic design of diverse bionic dissipative behaviors under the precise control of nucleic acid nanodevices. Nevertheless, when compared to the dissipation observed in robust living systems, it is highly desirable to enhance the anti-interference for artificial DNA dissipation to withstand perturbations and facilitate repairs within the complex biological environments.

RESULTS

In this study, we introduce strategically designed "trash cans" to facilitate kinetic control over interferences, transforming the stochastic binding of individual components within a homogeneous solution into a competitive binding process. This approach effectively eliminates incorrect binding and the accumulation of systemic interferences while ensuring a consistent pattern of energy fluctuation from response to silence. Remarkably, even in the presence of numerous interferences differing by only one base, we successfully achieve complete system reset through multiple cycles, effectively restoring the energy level to a minimum.

SIGNIFICANCE

The system was able to operate stably without any adverse effect under conditions of irregular interference, high-abundance interference, and even multiplex interferences including DNA and RNA crosstalk. This work not only provides an effective paradigm for constructing robust DNA dissipation systems but also greatly broadens the potential of DNA dissipation for applications in high-precision molecular recognition and complex biological reaction networks.

Sequence-Guided Localization of DNA Hybridization Enables Highly Selective and Robust Genotyping

Genetic variations are always related to human diseases or susceptibility to therapies. Nucleic acid probes that precisely distinguish closely related sequences become an indispensable requisite both in research and clinical applications. Here, a Sequence-guided DNA LOCalization for leaKless DNA detection (SeqLOCK) is introduced as a technique for DNA hybridization, where the intended targets carrying distinct "guiding sequences" act selectively on the probes. In silicon modeling, experimental results reveal considerable agreement (R2 = 0.9228) that SeqLOCK is capable of preserving high discrimination capacity at an extraordinarily wide range of target concentrations. Furthermore, SeqLOCK reveals high robustness to various solution conditions and can be directly adapted to nucleic acid amplification techniques (e.g., polymerase chain reaction) without the need for laborious pre-treatments. Benefiting from the low hybridization leakage of SeqLOCK, three distinct variations with a clinically relevant mutation frequency under the background of genomic DNA can be discriminated simultaneously. This work establishes a reliable nucleic acid hybridization strategy that offers great potential for constructing robust and programmable systems for molecular sensing and computing.

Predicting DNA toehold-mediated strand displacement rate constants using a DNA-BERT transformer deep learning model

Dynamic DNA nanotechnology is driving exciting developments in molecular computing, cargo delivery, sensing and detection. Combining this innovative area of research with the progress made in machine learning will aid in the design of sophisticated DNA machinery. Herein, we present a novel framework based on a transformer architecture and a deep learning model which can predict the rate constant of toehold-mediated strand displacement, the underlying process in dynamic DNA nanotechnology. Initially, a dataset of 4450 DNA sequences and corresponding rate constants were generated in-silico using KinDA. Subsequently, a 1D convolution neural network was trained using specific local features and DNA-BERT sequence embedding to produce predicted rate constants. As a result, the newly trained deep learning model predicted toehold-mediated strand displacement rate constants with a root mean square error of 0.76, during testing. These findings demonstrate that DNA-BERT can improve prediction accuracy, negating the need for extensive computational simulations or experimentation. Finally, the impact of various local features during model training is discussed, and a detailed comparison between the One-hot encoder and DNA-BERT sequences representation methods is presented.

A DNA circuit that records molecular events

Characterizing the relative onset time, strength, and duration of molecular signals is critical for understanding the operation of signal transduction and genetic regulatory networks. However, detecting multiple such molecules as they are produced and then quickly consumed is challenging. A MER can encode information about transient molecular events as stable DNA sequences and are amenable to downstream sequencing or other analysis. Here, we report the development of a de novo molecular event recorder that processes information using a strand displacement reaction network and encodes the information using the primer exchange reaction, which can be decoded and quantified by DNA sequencing. The event recorder was able to classify the order at which different molecular signals appeared in time with 88% accuracy, the concentrations with 100% accuracy, and the duration with 75% accuracy. This simultaneous and highly programmable multiparameter recording could enable the large-scale deciphering of molecular events such as within dynamic reaction environments, living cells, or tissues.

Latent Toehold-Mediated DNA Circuits Based on a Bulge-Loop Structure for Leakage Reduction and Its Application to Signal-Amplifying DNA Logic Gates

DNA circuits based on successive toehold-mediated DNA displacement reactions, particularly entropy-driven DNA circuit (EDC) systems, have attracted considerable attention as powerful enzyme-free tools for dynamic DNA nanotechnology. However, background leakage (noise signal) often occurs when the circuit is executed nonspecifically, even in the absence of the appropriate catalyst DNA (input). This study designed and developed a new latent toehold-mediated DNA circuit (LDC) system that relies on a bulge-loop structure as a latent toehold toward leakage reduction. Furthermore, the number (size) of nucleotides (nt) in the bulge-loop is found to play a significant role in the performance (i.e., leakage, signal, and kinetics) of LDC systems. In fact, the signal rate for the LDC systems increased as the number of nt in the bulge-loop increased from 4 to 8, whereas the leakage rate of the LDC systems with bulge-loops of 7 nt or less was low, but the leakage rate of the LDC system with a bulge-loop of 8 nt increased significantly. Note that the LDC system with the optimal bulge-loop (7 nt) was capable of not only reducing the leakage but also accelerating the circuit speed without any signal loss, unlike methods of reducing the leakage by reducing the signal reported previously for the conventional EDC systems. These facts indicate that the 7 nt bulge-loop acts as a "latent" toehold for the DNA circuit system. By using the amplification function of output signals with an accelerated circuit and reduced leakage, our LDC system with a 7 nt bulge-loop could be applied directly and successfully to signal-amplifying DNA logic gates such as OR and AND gates, and thus, sufficient output signals could be obtained even with a small amount of input. These findings reveal that our LDC systems with a bulge-loop structure can replace the conventional EDC system and have enormous potential in the field of DNA nanotechnology.

A New Architecture for DNA-Templated Synthesis in Which Abasic Sites Protect Reactants from Degradation

The synthesis of artificial sequence-defined polymers that match and extend the functionality of proteins is an important goal in materials science. One way of achieving this is to program a sequence of chemical reactions between precursor building blocks by means of attached oligonucleotide adapters. However, hydrolysis of the reactive building blocks has so far limited the length and yield of product that can be obtained using DNA-templated reactions. Here, we report an architecture for DNA-templated synthesis in which reactants are tethered at internal abasic sites on opposite strands of a DNA duplex. We show that an abasic site within a DNA duplex can protect a nearby thioester from degradation, significantly increasing the yield of a DNA-templated reaction. This protective effect has the potential to overcome the challenges associated with programmable, sequence-controlled synthesis of long non-natural polymers by extending the lifetime of the reactive building blocks.

Short-stranded DNA segment-modulated LAMP/H+ as signal transducer to guide CHA-cooperated amplifiable electrochemical biosensing

BACKGROUND

Modulating loop-mediated isothermal amplification (mLAMP) by short-stranded DNA segment trigger (T) to generate byproducts H+ ions (mLAMP/H+) as signal transducer is intriguing for developing catalytic hairpin assembly (CHA)-cooperated amplifiable electrochemical biosensors. This would be a big challenge for traditional LAMP that is basically suitable for amplifying long-stranded oligonucleotides up to 200-300 nt. To address this inherent limitation of traditional LAMP, many researchers have put in efforts to explore improvements in this that would allow LAMP to be used for a wider range of target species amplification.

RESULTS

Here in this work, we are inspired to explore two-step loop-mediated amplification, firstly forming T-activated double-loop dumbbell structure (DLDS) intermediate by a recognition hairpin and a hairpin precursor, and next DLDS-guided mLAMP process with the aid of two primers to yield mLAMP/H+ during successive DNA incorporation via nucleophilic attacking interaction. To manipulate the mLAMP/H+-directed transduction of input T, a pH-responsive triplex strand is designed with the ability of self-folding in Hoogsteen structure at slightly acidic conditions, resulting in the dehybridization of a fuel strand (FS) to participate in CHA between two hairpins on the modified electrode surface, in which FS is repetitively displaced and recycled to fuel the progressive CHA events. In the as-assembled dsDNA complexes, numerous electroactive ferrocene labels are immobilized in the electrode sensing interface, thereby generating significantly amplified electrochemical current signal that can sense the presented and varied T.

SIGNIFICANCE

It is clear that we have creatively constructed a unique electrochemical biosensor for disease detection. Benefited from the rational combination of mLAMP and CHA, our electrochemical strategy is highly sensitive, specific and simplified, and would provide a new paradigm to construct various mLAMP/H+-based biosensors for other short-stranded DNA or microRNAs markers.

Transient states during the annealing of mismatched and bulged oligonucleotides

Oligonucleotide hybridization is crucial in various biological, prebiotic and nanotechnological processes, including gene regulation, non-enzymatic primer extension and DNA nanodevice assembly. Although extensive research has focused on the thermodynamics and kinetics of nucleic acid hybridization, the behavior of complex mixtures and the outcome of competition for target binding remain less well understood. In this study, we investigate the impact of mismatches and bulges in a 12 bp DNA or RNA duplex on its association (kon) and dissociation (koff) kinetics. We find that such defects have relatively small effects on the association kinetics, while the dissociation kinetics vary in a position-dependent manner by up to 6 orders of magnitude. Building upon this observation, we explored a competition scenario involving multiple oligonucleotides, and observed a transient low specificity of probe hybridization to fully versus partially complementary targets in solution. We characterize these long-lived metastable states and their evolution toward equilibrium, and show that sufficiently long-lived mis-paired duplexes can serve as substrates for prebiotically relevant chemical copying reactions. Our results suggest that transient low accuracy states may spontaneously emerge within all complex nucleic acid systems comprising a large enough number of competing strands, with potential repercussions for gene regulation in the realm of modern biology and the prebiotic preservation of genetic information.

Coarse-grained modeling of DNA-RNA hybrids

We introduce oxNA, a new model for the simulation of DNA-RNA hybrids that is based on two previously developed coarse-grained models-oxDNA and oxRNA. The model naturally reproduces the physical properties of hybrid duplexes, including their structure, persistence length, and force-extension characteristics. By parameterizing the DNA-RNA hydrogen bonding interaction, we fit the model's thermodynamic properties to experimental data using both average-sequence and sequence-dependent parameters. To demonstrate the model's applicability, we provide three examples of its use-calculating the free energy profiles of hybrid strand displacement reactions, studying the resolution of a short R-loop, and simulating RNA-scaffolded wireframe origami.

Turn-on RNA Mango Beacons for trans-acting fluorogenic nucleic acid detection

The Mango I and II RNA aptamers have been widely used in vivo and in vitro as genetically encodable fluorogenic markers that undergo large increases in fluorescence upon binding to their ligand, TO1-Biotin. However, while studying nucleic acid sequences, it is often desirable to have trans-acting probes that induce fluorescence upon binding to a target sequence. Here, we rationally design three types of light-up RNA Mango Beacons based on a minimized Mango core that induces fluorescence upon binding to a target RNA strand. Our first design is bimolecular in nature and uses a DNA inhibition strand to prevent folding of the Mango aptamer core until binding to a target RNA. Our second design is unimolecular in nature, and features hybridization arms flanking the core that inhibit G-quadruplex folding until refolding is triggered by binding to a target RNA strand. Our third design builds upon this structure, and incorporates a self-inhibiting domain into one of the flanking arms that deliberately binds to, and precludes folding of, the aptamer core until a target is bound. This design separates G-quadruplex folding inhibition and RNA target hybridization into separate modules, enabling a more universal unimolecular beacon design. All three Mango Beacons feature high contrasts and low costs when compared to conventional molecular beacons, with excellent potential for in vitro and in vivo applications.

Bubble DNA tweezer: A triple-conformation sensor responsive to concentration-ratios

DNA tweezers, with their elegant simplicity and flexibility, have been pivotal in biosensing and DNA computing. However, conventional tweezers are confined to a binary transformation pre/post target signal recognition, limiting them to presence/absence judgments. This study introduces bubble DNA tweezers (BDT), capable of three distinct conformations based on variable target signal ratios. In contrast to traditional compact tweezers, BDT features a looser structure centered around a non-complementary bubble domain located between the tweezer arms' connecting axis and target signal recognition jaws. This bubble triggers toehold-free DNA strand displacement, leading to three conformational changes at different target signal concentrations. BDT detects presence/absence and true concentration with remarkable specificity and sensitivity. This adaptability is not confined to ideal scenarios, proving valuable in complex, noisy environments. Our method facilitates target DNA/miRNA signal quantification within a specific length range, promising applications in clinical research and environmental detection, while inspiring future biological assay innovations.

Plug-and-Play Module for Reversible and Continuous Control of DNA Strand Displacement Kinetics

Regulatory modules for controlling the kinetics of toehold-mediated strand displacement (TMSD) play critical roles in designing dynamic and dissipative DNA chemical reaction networks (CRNs) but are hardwired into sequence designs. Herein, we introduce antitoehold (At), a plug-and-play module for reversible and continuous tuning of TMSD kinetics by temporarily occupying the toehold domain via a metastable duplex and base stacking. We demonstrate that kinetic control can be readily activated or deactivated in real time for any TMSD by simply adding At or anti-At. Continuous tuning of TMSD kinetics can also be achieved by altering the concentration of At. Moreover, the simple addition of At could readily reprogram existing TMSDs into a pulse-generation DNA CRN with continuous tunability. Our At approach also offers a new way for engineering continuously tunable DNA hybridization probes, which may find practical uses for discriminating clinically important mutations. Because of the simplicity, we anticipate that At will find wide applications for engineering DNA CRNs with diverse dynamic and dissipative behaviors, and DNA hybridization probes with tunable affinity and selectivity.

Exchanging and Releasing Information in Synthetic Digital Polymers Using a Strand-Displacement Strategy

Toehold-mediated strand displacement (TMSD) was tested as a tool to edit information in synthetic digital polymers. Uniform DNA-polymer biohybrid macromolecules were first synthesized by automated phosphoramidite chemistry and characterized by HPLC, mass spectrometry, and polyacrylamide gel electrophoresis (PAGE). These precursors were diblock structures containing a synthetic poly(phosphodiester) (PPDE) segment covalently attached to a single-stranded DNA sequence. Three types of biohybrids were prepared herein: a substrate containing an accessible toehold as well as input and output macromolecules. The substrate and the input macromolecules contained noncoded PPDE homopolymers, whereas the output macromolecule contained a digitally encoded segment. After hybridization of the substrate with the output, incubation in the presence of the input led to efficient TMSD and the release of the digital segment. TMSD can therefore be used to erase or rewrite information in self-assembled biohybrid superstructures. Furthermore, it was found in this work that the conjugation of DNA single strands to synthetic segments of chosen lengths greatly facilitates the characterization and PAGE visualization of the TMSD process.

Programming crystallization kinetics of self-assembled DNA crystals with 5-methylcytosine modification

Self-assembled DNA crystals offer a precise chemical platform at the ångström-scale for DNA nanotechnology, holding enormous potential in material separation, catalysis, and DNA data storage. However, accurately controlling the crystallization kinetics of such DNA crystals remains challenging. Herein, we found that atomic-level 5-methylcytosine (5mC) modification can regulate the crystallization kinetics of DNA crystal by tuning the hybridization rates of DNA motifs. We discovered that by manipulating the axial and combination of 5mC modification on the sticky ends of DNA tensegrity triangle motifs, we can obtain a series of DNA crystals with controllable morphological features. Through DNA-PAINT and FRET-labeled DNA strand displacement experiments, we elucidate that atomic-level 5mC modification enhances the affinity constant of DNA hybridization at both the single-molecule and macroscopic scales. This enhancement can be harnessed for kinetic-driven control of the preferential growth direction of DNA crystals. The 5mC modification strategy can overcome the limitations of DNA sequence design imposed by limited nucleobase numbers in various DNA hybridization reactions. This strategy provides a new avenue for the manipulation of DNA crystal structure, valuable for the advancement of DNA and biomacromolecular crystallography.

Membrane localization accelerates association under conditions relevant to cellular signaling

Translocation of cytoplasmic molecules to the plasma membrane is commonplace in cell signaling. Membrane localization has been hypothesized to increase intermolecular association rates; however, it has also been argued that association should be faster in the cytosol because membrane diffusion is slow. Here, we directly compare an identical association reaction, the binding of complementary DNA strands, in solution and on supported membranes. The measured rate constants show that for a 10-µm-radius spherical cell, association is 22- to 33-fold faster at the membrane than in the cytoplasm. The kinetic advantage depends on cell size and is essentially negligible for typical ~1 µm prokaryotic cells. The rate enhancement is attributable to a combination of higher encounter rates in two dimensions and a higher reaction probability per encounter.

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.

Heterochiral modifications enhance robustness and function of DNA in living human cells

Oligonucleotide therapeutics are becoming increasingly important as more are approved by the FDA, both for treatment and vaccination. Similarly, dynamic DNA nanotechnology is a promising technique that can be used to sense exogenous input molecules or endogenous biomarkers and integrate the results of multiple sensing reactions in situ via a programmed cascade of reactions. The combination of these two technologies could be highly impactful in biomedicine by enabling smart oligonucleotide therapeutics that can autonomously sense and respond to a disease state. A particular challenge, however, is the limited lifetime of standard nucleic acid components in living cells and organisms due to degradation by endogenous nucleases. In this work, we address this challenge by incorporating mirror-image, ʟ-DNA nucleotides to produce heterochiral "gapmers". We use dynamic DNA nanotechnology to show that these modifications keep the oligonucleotide intact in living human cells for longer than an unmodified strand. To this end, we used a sequential transfection protocol for delivering multiple nucleic acids into living human cells while providing enhanced confidence that subsequent interactions are actually occurring within the cells. Taken together, this work advances the state of the art of ʟ-nucleic acid protection of oligonucleotides and DNA circuitry for applications in vivo.

DNA Reaction System That Acquires Classical Conditioning

Biochemical reaction networks can exhibit plastic adaptation to alter their functions in response to environmental changes. This capability is derived from the structure and dynamics of the reaction networks and the functionality of the biomolecule. This plastic adaptation in biochemical reaction systems is essentially related to memory and learning capabilities, which have been studied in DNA computing applications for the past decade. However, designing DNA reaction systems with memory and learning capabilities using the dynamic properties of biochemical reactions remains challenging. In this study, we propose a basic DNA reaction system design that acquires classical conditioning, a phenomenon underlying memory and learning, as a typical learning task. Our design is based on a simple mechanism of five DNA strand displacement reactions and two degradative reactions. The proposed DNA circuit can acquire or lose a new function under specific conditions, depending on the input history formed by repetitive stimuli, by exploiting the dynamic properties of biochemical reactions induced by different input timings.

Programmable Primer Switching for Regulating Enzymatic DNA Circuits

Developing DNA strand displacement reactions (SDRs) offers crucial technical support for regulating artificial nucleic acid circuits and networks. More recently, enzymatic SDR-based DNA circuits have gained significant attention because of their modular design, high orthogonality signaling, and extremely fast reaction rates. Typical enzymatic SDRs are regulated by relatively long primers (20-30 nucleotides) that hybridize to form stable double-stranded structures, facilitating enzyme-initiated events. Implementing more flexible primer-based enzymatic SDR regulations remains challenging due to the lack of convenient and simple primer control mechanism, which consequently limits the development of enzymatic DNA circuits. In this study, we propose an approach, termed primer switching regulation, that implements programmable and flexible regulations of enzymatic circuits by introducing switchable wires into the enzymatic circuits. We applied this method to generate diverse enzymatic DNA circuits, including cascading, fan-in/fan-out, dual-rail, feed-forward, and feedback functions. Through this method, complex circuit functions can be implemented by just introducing additional switching wires without reconstructing the basic circuit frameworks. The method is experimentally demonstrated to provide flexible and programmable regulations to control enzymatic DNA circuits and has future applications in DNA computing, biosensing, and DNA storage.

Fast, multicolour optical sectioning over extended fields of view with patterned illumination and machine learning

Structured illumination can reject out-of-focus signal from a sample, enabling high-speed and high-contrast imaging over large areas with widefield detection optics. However, this optical sectioning technique is currently limited by image reconstruction artefacts and poor performance at low signal-to-noise ratios. We combine multicolour interferometric pattern generation with machine learning to achieve high-contrast, real-time reconstruction of image data that is robust to background noise and sample motion. We validate the method in silico and demonstrate imaging of diverse specimens, from fixed and live biological samples to synthetic biosystems, reconstructing data live at 11 Hz across a 44 × 44μm2 field of view, and demonstrate image acquisition speeds exceeding 154 Hz.