Biocomputing Based on DNA Strand Displacement Reactions

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.

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.

Fluorescence-Based Multimodal DNA Logic Gates

The use of DNA structures in creating multimodal logic gates bears high potential for building molecular devices and computation systems. However, due to the complex designs or complicated working principles, the implementation of DNA logic gates within molecular devices and circuits is still quite limited. Here, we designed simple four-way DNA logic gates that can serve as multimodal platforms for simple to complex operations. Using the proximity quenching of the fluorophore-quencher pair in combination with the toehold-mediated strand displacement (TMSD) strategy, we have successfully demonstrated that the fluorescence output, which is a result of gate opening, solely relies on the oligonucleotide(s) input. We further demonstrated that this strategy can be used to create multimodal (tunable displacement initiation sites on the four-way platform) logic gates including YES, AND, OR, and the combinations thereof. The four-way DNA logic gates developed here bear high promise for building biological computers and next-generation smart molecular circuits with biosensing capabilities.

Concept and Development of Algebraic Topological Framework Nucleic Acids

Nucleic acids are considered as promising materials for developing exquisite nanostructures from one to three dimensions. The advances of DNA nanotechnology facilitate ingenious design of DNA nanostructures with diverse shapes and sizes. Especially, the algebraic topological framework nucleic acids (ATFNAs) are functional DNA nanostructures that engineer guest molecules (e. g., nucleic acids, proteins, small molecules, and nanoparticles) stoichiometrically and spatially. The intrinsic precise properties and tailorable functionalities of ATFNAs hold great promise for biological applications, such as cell recognition and immunotherapy. This Perspective highlights the concept and development of precisely assembled ATFNAs, and outlines the new frontiers and opportunities for exploiting the structural advantages of ATFNAs for biological applications.

Engineering Modular DNA Reaction Networks for Signal Processing

Diversified molecular information-processing methods have significant implications for nanoscale manipulation and control, monitoring and disease diagnosis of organisms, and direct intervention in biological activities. However, as an effective approach for implementing multifunctional molecular information processing, DNA reaction networks (DRNs) with numerous functionally specialized molecular structures have challenged them on scale design, leading to increased network complexity, further causing problems such as signal leakage, attenuation, and cross-talk in network reactions. Our study developed a strategy for performing various signal-processing tasks through engineering modular DRNs. This strategy is based on a universal core unit with signal selection capability, and a time-adjustable signal self-resetting module is achieved by combing the core unit and self-resetting unit, which improves the time controllability of modular DRNs. In addition, multi-input and -output signal cross-catalytic and continuously adjustable signal delay modules were realized by combining core and threshold units, providing a flexible, precise method for modular DRNs to process the signal. The strategy simplifies the design of DRNs, helps generate design ideas for large-scale integrated DRNs with multiple functions, and provides prospects in biocomputing, gene regulation, and biosensing.

Amplification- and Enzyme-Free Magnetic Diagnostics Circuit for Whole-Genome Detection of SARS-CoV-2 RNA

Polymerase chain reaction (PCR) requires thermal cycling and enzymatic reactions for sequence amplification, hampering their applications in point-of-care (POC) settings. Magnetic bioassays based on magnetic particle spectroscopy (MPS) and magnetic nanoparticles (MNPs) are isothermal, wash-free, and can be quantitative. Realizing them amplification- and enzyme-free on a benchtop device, they will become irreplaceable for POC applications. Here we demonstrate a first-in-class magnetic signal amplification circuit (MAC) that enables detection of whole genome of SARS-CoV-2 by combining the specificity of toehold-mediated DNA strand displacement with the magnetic response of MNPs to declustering processes. Using MAC, we detect the N gene of SARS-CoV-2 samples at a concentration of 104 RNA copies/μl as determined by droplet digital PCR. Further, we demonstrate that MAC can reliably distinguish between SARS-CoV-2 and other human coronaviruses. Being a wash-, amplification- and enzyme-free biosensing concept and working at isothermal conditions (25 °C) on a low-cost benchtop MPS device, our MAC biosensing concept offers several indispensable features for translating nucleic acid detection to POC applications.

A dual-signal aptasensor based on cascade amplification for ultrasensitive detection of aflatoxin B1

Aflatoxin B1 (AFB1) is considered as a serious carcinogenic mycotoxin that was widely detected in grains and foods, and its sensitive analysis is of key importance to avoid the health threats for consumers. In this study, a dual-signal aptasensor based on cascade of entropy-driven strand displacement reaction (ESDR) and linear rolling circle amplification (LRCA) was fabricated for ultrasensitive determination of AFB1. At the sensing system, the complementary strand would be released after the aptamer combined with AFB1, which will bring about the functional domains exposed, triggering the subsequent ESDR. Meanwhile, the two strands that were outputted by ESDR would incur the downstream LRCA reaction to produce a pair of long strands to assist in the generation of fluorescence and absorbance signals. Under the optimized conditions, the proposed aptasensor could achieve excellent sensitivity (limit of detection, 0.427 pg/mL) with satisfactory accuracy (recoveries, 92.8-107.9 %; RSD, 2.4-5.0 %), mainly ascribed to the cascade amplification. Importantly, owing to the flexibility design of nucleic acid primer, this analytical method can be applied in monitoring various hazardous substances according to the specific requirements. Our strategy provides some novel insights at signal amplification for rapid detection of AFB1 and other targets.

Synthetic biological neural networks: From current implementations to future perspectives

Artificial neural networks, inspired by the biological networks of the human brain, have become game-changing computing models in modern computer science. Inspired by their wide scope of applications, synthetic biology strives to create their biological counterparts, which we denote synthetic biological neural networks (SYNBIONNs). Their use in the fields of medicine, biosensors, biotechnology, and many more shows great potential and presents exciting possibilities. So far, many different synthetic biological networks have been successfully constructed, however, SYNBIONN implementations have been sparse. The latter are mostly based on neural networks pretrained in silico and being heavily dependent on extensive human input. In this paper, we review current implementations and models of SYNBIONNs. We briefly present the biological platforms that show potential for designing and constructing perceptrons and/or multilayer SYNBIONNs. We explore their future possibilities along with the challenges that must be overcome to successfully implement a scalable in vivo biological neural network capable of online learning.

Data Storage Using DNA

The exponential growth of global data has outpaced the storage capacities of current technologies, necessitating innovative storage strategies. DNA, as a natural medium for preserving genetic information, has emerged as a highly promising candidate for next-generation storage medium. Storing data in DNA offers several advantages, including ultrahigh physical density and exceptional durability. Facilitated by significant advancements in various technologies, such as DNA synthesis, DNA sequencing, and DNA nanotechnology, remarkable progress has been made in the field of DNA data storage over the past decade. However, several challenges still need to be addressed to realize practical applications of DNA data storage. In this review, the processes and strategies of in vitro DNA data storage are first introduced, highlighting recent advancements. Next, a brief overview of in vivo DNA data storage is provided, with a focus on the various writing strategies developed to date. At last, the challenges encountered in each step of DNA data storage are summarized and promising techniques are discussed that hold great promise in overcoming these obstacles.

Construction of DNA-based molecular circuits using normally open and normally closed switches driven by lambda exonuclease

Building synthetic molecular circuits is an important way to realize ion detection, information processing, and molecular computing. However, it is still challenging to implement the NOT logic controlled by a single molecule input in synthetic molecular circuits wherein the presence or absence of the molecule represents the ON or OFF state of the input. Here, based on lambda exonuclease (λ exo), for the first time, we propose the normally open (NO) and normally closed (NC) switching strategy with a unified signal transmission mechanism to build molecular circuits. Specifically, the opposite logic can be output with or without a single signal, and the state of the switch can be adjusted by the addition order and time interval of the upstream signal and switch signal, which endows the switch with time-responsive characteristics. In addition, a time-delay relay with the function of delayed disconnection is developed to realize quantitative control of outputs, which has the potential to meet the automation control need of the system. Finally, digital square and square root circuits are constructed by cascading the NO and NC switches, which demonstrates the versatility of switches. Our design can be extended to time logic and complex digital computing circuits for use in information processing and nanomachines.

Self-powered logically operated fluorescent detection of hepatitis B virus (HBV)

In this study, a novel sensing strategy based on double sensing/actuating pathway is demonstrated, being capable to trigger the DNA-based AND gate for the sensitive and selective detection of hepatitis B virus DNA (HBV-DNA). Such an approach encompasses an enzymatic machinery logically operated using the variation of physiologically relevant biomarkers for liver dysfunctions. Alanine aminotransferase (ALT) and lactate dehydrogenase (LDH) are used as inputs of an AND gate generating an output signal, namely lactate. In particular, lactate is oxidized back to pyruvate at the anodic electrode by lactate oxidase connected in mediated electron transfer through ferrocene moieties (creating an amplifying recycling mechanism). The anodic electrode is further connected with a Myrothecium verrucaria bilirubin oxidase (MvBOx) based biocathode modified with SiO₂ nanoparticles (SiO₂NPs) functionalized with phenyl boronic acid and trigonelline, triggering the release of quenching DNA (qDNA) upon local pH change at the electrode surface (notably, modified SiONPs gets negatively recharged upon local pH gradient releasing negatively charged DNA). Next, the released qDNA labeled with BHQ2 and detecting DNA (dDNA, labeled with FAM) are detecting HBV-DNA. The proposed biosensor can discriminate between the absence and presence of HBV-DNA setting the threshold at 0.05 fM in model buffer solutions and 1 fM in human serum. This enzymatic/DNA logic network can be of particular interest for future biomedical applications (e.g., early detection of liver cancer disease etc.). In the future development this technology could be easily integrated with a smartphone camera, allowing more user-friendly applications.

DNA Strand Displacement Driven by Host-Guest Interactions

Base-pair-driven toehold-mediated strand displacement (BP-TMSD) is a fundamental concept employed for constructing DNA machines and networks with a gamut of applications─from theranostics to computational devices. To broaden the toolbox of dynamic DNA chemistry, herein, we introduce a synthetic surrogate termed host-guest-driven toehold-mediated strand displacement (HG-TMSD) that utilizes bioorthogonal, cucurbit[7]uril (CB[7]) interactions with guest-linked input sequences. Since control of the strand-displacement process is salient, we demonstrate how HG-TMSD can be finely modulated via changes to the structure of the input sequence (including synthetic guest head-group and/or linker length). Further, for a given input sequence, competing small-molecule guests can serve as effective regulators (with fine and coarse control) of HG-TMSD. To show integration into functional devices, we have incorporated HG-TMSD into machines that control enzyme activity and layered reactions that detect specific microRNA.

Ratiometric fluorescence sensing with logical operation: Theory, design and applications

The construction of ratiometric fluorescence sensing logic systems has gradually become a hot topic in fluorescence analysis, due to the multi-target analysis potential of logic operations and the high specificity and selectivity of ratiometric fluorescence sensing. In this paper, the basic principles of various logic functions implemented in ratiometric fluorescence detection are discussed in the context of sensing mechanisms, and the strategies for constructing logic systems in different ratiometric fluorescence sensing application areas are summarized. Although there are limitations such as cumbersome operations and complicated experiments, ratiometric fluorescence sensing logic circuits that combine the visualization of logic operations and the accuracy of ratiometric fluorescence are still worthy of in-depth study. This review may be useful for researchers interested in the construction of logic operations based on ratiometric fluorescence sensing applications.

Exponential Function Computation Based on DNA Strand Displacement Circuits

Due to its high programmability and storage, DNA circuits have been widely used in biological computing. In this paper, the addition, subtraction, multiplication, division, n-order and 1/n-order gates are built through DNA strand displacement reactions. The chemical reaction networks of the exponential function are established by using the six DNA analog computation gates. The integrated DNA strand displacement circuits are built through the chemical reaction networks. The exponential function polynomials can be computed through the integrated DNA strand displacement circuits. Finally, through visual DSD software verification, this design can realise the computation of exponential function polynomials, which provides a reference for solving exponential function equations and neural network computations in the future.

DNA Input Classification by a Riboregulator-Based Cell-Free Perceptron

The ability to recognize molecular patterns is essential for the continued survival of biological organisms, allowing them to sense and respond to their immediate environment. The design of synthetic gene-based classifiers has been explored previously; however, prior strategies have focused primarily on DNA strand-displacement reactions. Here, we present a synthetic in vitro transcription and translation (TXTL)-based perceptron consisting of a weighted sum operation (WSO) coupled to a downstream thresholding function. We demonstrate the application of toehold switch riboregulators to construct a TXTL-based WSO circuit that converts DNA inputs into a GFP output, the concentration of which correlates to the input pattern and the corresponding weights. We exploit the modular nature of the WSO circuit by changing the output protein to the Escherichia coli σ28-factor, facilitating the coupling of the WSO output to a downstream reporter network. The subsequent introduction of a σ28 inhibitor enabled thresholding of the WSO output such that the expression of the downstream reporter protein occurs only when the produced σ28 exceeds this threshold. In this manner, we demonstrate a genetically implemented perceptron capable of binary classification, i.e., the expression of a single output protein only when the desired minimum number of inputs is exceeded.

Controlling Dynamic DNA Reactions at the Surface of Single-Walled Carbon Nanotube Electrodes to Design Hybridization Platforms with a Specific Amperometric Readout

Carbon nanotube (CNT)-based electrodes are cheap, highly performing, and robust platforms for the fabrication of electrochemical sensors. Engineering programmable DNA nanotechnologies on the CNT surface can support the construction of new electrochemical DNA sensors providing an amperometric output in response to biomolecular recognition. This is a significant challenge, since it requires gaining control of specific hybridization processes and functional DNA systems at the interface, while limiting DNA physisorption on the electrode surface, which contributes to nonspecific signal. In this study, we provide design rules to program dynamic DNA structures at the surface of single-walled carbon nanotubes electrodes, showing that specific DNA interactions can be monitored through measurement of the current signal provided by redox-tagged DNA strands. We propose the use of pyrene as a backfilling agent to reduce nonspecific adsorption of reporter DNA strands and demonstrate the controlled formation of DNA duplexes on the electrode surface, which we then apply in the design and conduction of programmable DNA strand displacement reactions. Expanding on this aspect, we report the development of novel amperometric hybridization platforms based on artificial DNA structures templated by the small molecule melamine. These platforms enable dynamic strand exchange reactions orthogonal to conventional toehold-mediated strand displacement and may support new strategies in electrochemical sensing of biomolecular targets, combining the physicochemical properties of nanostructured carbon-based materials with programmable nucleic acid hybridization.

Digital Nucleic Acid Signal Amplification Platform for Highly Sensitive DNA Mutation Analysis

Digital nucleic acid analysis technology has shown great application potential due to its excellent performance. However, most current digital nucleic acid detection methods are based on PCR or other template amplification strategies. Here, we present an alternative analysis platform based on digital nucleic acid signal amplification in droplets termed dNASA. Using a bead-based controllable extension bridged cascade signal amplification reaction, we achieved an ultralow background, high efficiency, and highly specific nucleic acid signal amplification analysis. As a "proof of concept", we demonstrated the feasibility of the proposed dNASA platform in single-base DNA mutation analysis using artificially synthesized samples. This platform provides innovative ideas for the field of digital nucleic acid analysis.

Solution of Simultaneous Higher Order Equations Based on DNA Strand Displacement Circuit

Currently, DNA strand displacement is often used to build neural networks or solve logical problems. While there are few studies on the use of DNA strand displacement to solve the higher order equations. In this paper, the catalysis, degradation, annihilation and adjusted reaction modules are built through DNA strand displacement. The chemical reaction networks of the corresponding higher order equations and simultaneous equations are established through these modules, and these chemical reaction networks can be used to build analog circuits to solve binary primary simultaneous equations and binary quadratic simultaneous equations. Finally, through Visual DSD software verification, this design can realize the solution of binary primary simultaneous equations and binary quadratic simultaneous equations, which provides a reference for DNA computation in the future.

Engineering the Stability of Nanozyme-Catalyzed Product for Colorimetric Logic Gate Operations

Recently, the design and development of nanozyme-based logic gates have received much attention. In this work, by engineering the stability of the nanozyme-catalyzed product, we demonstrated that the chromogenic system of 3, 3′, 5, 5′-tetramethylbenzidine (TMB) can act as a visual output signal for constructing various Boolean logic operations. Specifically, cerium oxide or ferroferric oxide-based nanozymes can catalyze the oxidation of colorless TMB to a blue color product (oxTMB). The blue-colored solution of oxTMB could become colorless by some reductants, including the reduced transition state of glucose oxidase and xanthine oxidase. As a result, by combining biocatalytic reactions, the color change of oxTMB could be controlled logically. In our logic systems, glucose oxidase, β-galactosidase, and xanthine oxidase acted as inputs, and the state of oxTMB solution was used as an output. The logic operation produced a colored solution as the readout signal, which was easily distinguished with the naked eye. More importantly, the study of such a decolorization process allows the transformation of previously designed AND and OR logic gates into NAND and NOR gates. We propose that this work may push forward the design of novel nanozyme-based biological gates and help us further understand complex physiological pathways in living systems.

Fluorescent Molecular Logic Gates Driven by Temperature and by Protons in Solution and on Solid

Temperature-driven fluorescent NOT logic is demonstrated by exploiting predissociation in a 1,3,5-trisubstituted Δ² -pyrazoline on its own and when grafted onto silica microparticles. Related Δ² -pyrazolines become proton-driven YES and NOT logic gates on the basis of fluorescent photoinduced electron transfer (PET) switches. Additional PASS 1 and YES+PASS 1 logic gates on silica are also demonstrated within the same family. Beside these small-molecule systems, a polymeric molecular thermometer based on a benzofurazan-derivatized N-isopropylacrylamide copolymer is attached to silica to produce temperature-driven fluorescent YES logic.