Computing in mammalian cells with nucleic acid strand exchange

Intelligent guide RNA: dual toehold switches for modulating luciferase in the presence of trigger RNA

The CRISPR system finds extensive application in molecular biology, but its continuous activity can yield adverse effects. Leveraging programmable CRISPR/Cas9 function via nano-device mediation effectively mitigates these drawbacks. The integration of RNA-sensing platforms into CRISPR thus empowers it as a potent tool for processing internal cell data and modulating gene activity. Here, an intelligent guide RNA-a cis-repressed gRNA synthetic circuit enabling efficient recognition of specific trigger RNAs-is developed. This platform carries two toehold switches and includes an inhibited CrRNA sequence. In this system, the presence of cognate trigger RNA promotes precise binding to the first toehold site, initiating a cascade that releases CrRNA to target a reporter gene (luciferase) in this study. Decoupling the CrRNA segment from the trigger RNA enhances the potential of this genetic logic circuit to respond to specific cellular circumstances, offering promise as a synthetic biology platform.

DNA Nanotechnology for Application in Targeted Protein Degradation

DNA is a kind of flexible and versatile biomaterial for constructing nanostructures and nanodevices. Due to high biocompatibility and programmability and easy modification and fabrication, DNA nanotechnology has emerged as a powerful tool for application in intracellular targeted protein degradation. In this review, we summarize the recent advances in the design and mechanism of targeted protein degradation technologies such as protein hydrolysis targeted chimeras, lysosomal targeted chimeras, and autophagy based protein degradation. Subsequently, we introduce the DNA nanotechnologies of DNA cascade circuits, DNA nanostructures, and dynamic machines. Moreover, we present the latest developments in DNA nanotechnologies in targeted protein degradation. Finally, the vision and challenges are discussed.

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.

Modified Unit-Mediated Strand Displacement Reactions for Direct Detection of Single Nucleotide Variants in Active Double-Stranded DNA

Accurate identification of single nucleotide variants (SNVs) in key driver genes holds a significant value for disease diagnosis and treatment. Fluorescent probes exhibit tremendous potential in specific, high-resolution, and rapid detection of SNVs. However, additional steps are required in most post-PCR assays to convert double-stranded DNA (dsDNA) products into single-stranded DNA (ssDNA), enabling them to possess hybridization activity to trigger subsequent reactions. This process not only prolongs the complexity of the experiment but also introduces the risk of losing target information. In this study, we proposed two strategies for enriching active double-stranded DNA, involving PCR based on obstructive groups and cleavable units. Building upon this, we explored the impact of modified units on the strand displacement reaction (SDR) and assessed their discriminatory efficacy for mutations. The results showed that detection of low variant allele frequencies (VAF) as low as 0.1% can be achieved. The proposed strategy allowed orthogonal identification of 45 clinical colorectal cancer tissue samples with 100% specificity, and the results were generally consistent with sequencing results. Compared to existing methods for enriching active targets, our approach offers a more diverse set of enrichment strategies, characterized by the advantage of being simple and fast and preserving original information to the maximum extent. The objective of this study is to offer an effective solution for the swift and facile acquisition of active double-stranded DNA. We anticipate that our work will facilitate the practical applications of SDR based on dsDNA.

DNA Logic Gates Integrated on DNA Substrates in Molecular Computing

Due to nucleic acid's programmability, it is possible to realize DNA structures with computing functions, and thus a new generation of molecular computers is evolving to solve biological and medical problems. Pioneered by Milan Stojanovic, Boolean DNA logic gates created the foundation for the development of DNA computers. Similar to electronic computers, the field is evolving towards integrating DNA logic gates and circuits by positioning them on substrates to increase circuit density and minimize gate distance and undesired crosstalk. In this minireview, we summarize recent developments in the integration of DNA logic gates into circuits localized on DNA substrates. This approach of all-DNA integrated circuits (DNA ICs) offers the advantages of biocompatibility, increased circuit response, increased circuit density, reduced unit concentration, facilitated circuit isolation, and facilitated cell uptake. DNA ICs can face similar challenges as their equivalent circuits operating in bulk solution (bulk circuits), and new physical challenges inherent in spatial localization. We discuss possible avenues to overcome these obstacles.

Harnessing Catalytic RNA Circuits for Construction of Artificial Signaling Pathways in Mammalian Cells

Engineering of genetic networks with artificial signaling pathways (ASPs) can reprogram cellular responses and phenotypes under different circumstances for a variety of diagnostic and therapeutic purposes. However, construction of ASPs between originally independent endogenous genes in mammalian cells is highly challenging. Here we report an amplifiable RNA circuit that can theoretically build regulatory connections between any endogenous genes in mammalian cells. We harness the system of catalytic hairpin assembly with combination of controllable CRISPR-Cas9 function to transduce the signals from distinct messenger RNA expression of trigger genes into manipulation of target genes. Through introduction of these RNA-based genetic circuits, mammalian cells are endowed with autonomous capabilities to sense the changes of RNA expression either induced by ligand stimuli or from various cell types and control the cellular responses and fates via apoptosis-related ASPs. Our design provides a generalized platform for construction of ASPs inside the genetic networks of mammalian cells based on differentiated RNA expression.

Design of a Biohybrid Materials Circuit with Binary Decoder Functionality

Synthetic biology applies concepts from electrical engineering and information processing to endow cells with computational functionality. Transferring the underlying molecular components into materials and wiring them according to topologies inspired by electronic circuit boards has yielded materials systems that perform selected computational operations. However, the limited functionality of available building blocks is restricting the implementation of advanced information-processing circuits into materials. Here, a set of protease-based biohybrid modules the bioactivity of which can either be induced or inhibited is engineered. Guided by a quantitative mathematical model and following a design-build-test-learn (DBTL) cycle, the modules are wired according to circuit topologies inspired by electronic signal decoders, a fundamental motif in information processing. A 2-input/4-output binary decoder for the detection of two small molecules in a material framework that can perform regulated outputs in form of distinct protease activities is designed. The here demonstrated smart material system is strongly modular and can be used for biomolecular information processing for example in advanced biosensing or drug delivery applications.

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.

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.

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 Logic Gates for Small Molecule Activation Circuits in Cells

DNA-based devices such as DNA logic gates self-assemble into supramolecular structures, as dictated by the sequences of the constituent oligonucleotides and their predictable Watson-Crick base pairing interactions. The programmable nature of DNA-based devices permits the design and implementation of DNA circuits that interact in a dynamic and sequential manner capable of spatially arranging disparate DNA species. Here, we report the application of an activatable fluorescence reporter based on a proximity-driven inverse electron demand Diels-Alder (IEDDA) reaction and its robust integration with DNA strand displacement circuits. In response to specific DNA input patterns, sequential strand displacement reactions are initiated and culminate in the hybridization of two modified DNA strands carrying probes capable of undergoing an IEDDA reaction between a vinyl-ether-caged fluorophore and its reactive partner tetrazine, leading to the activation of fluorescence. This approach provides a major advantage for DNA computing in mammalian cells since circuit degradation does not induce fluorescence, in contrast to traditional fluorophore-quencher designs. We demonstrate the robustness and sensitivity of the reporter by testing its ability to serve as a readout for DNA logic circuits of varying complexity inside cells.

A spatially-controlled DNA triangular prism nanomachine for AND-gated intracellular imaging of ATP in acidic microenvironment

A DNA triangular prism nanomachine (TPN)-based logic device for intracellular AND-gated imaging of adenosine triphosphate (ATP) has been constructed. By using i-motif sequences and ATP-binding aptamers as logic control units, the TPN logic device is qualified to respond to the acidic environment and ATP in cancer cell lysosomes. Once internalized into the lysosome, the specific acidic microenvironment in lysosome causes the i-motif sequence to fold into a tetramer, resulting in compression of DNA tri-prism. Subsequently, the split ATP aptamer located at the tip of the collapsed triangular prism binds stably to ATP, which results in the fluorescent dyes (Cy3 and Cy5) modified at the ends of the split aptamer being in close proximity to each other, allowing Förster Resonance Energy Transfer (FRET) to occur. The FRET signals are excited at a wavelength of 543 nm and can be collected within the emission range of 646-730 nm. This enables the precise imaging of ATP within a cell. We also dynamically operate AND logic gates in living cells by modulating intracellular pH and ATP levels with the help of external drugs. Owing to the AND logic unit on TPN it can simultaneously recognize two targets and give corresponding intelligent logic judgment via imaging signal output. The accuracy of molecular diagnosis of cancer can be improved thus eliminating the false positive signal of single target-based detection. Hence, this space-controlled TPN-based logical sensing platform greatly avoids sensitivity to extracellular targets during the cell entry process, providing a useful tool for high-precision imaging of the cancer cell's endogenous target ATP.

A DNA Logic Circuit Equipped with a Biological Amplifier Loaded into Biomimetic ZIF-8 Nanoparticles Enables Accurate Identification of Specific Cancers In Vivo

DNA logic circuits (DLC) enable the accurate identification of specific cell types, such as cancer cells, but they face the challenges of weak output signals and a lack of competent platforms that can efficiently deliver DLC components to the target site in the living body. To address these issues, we rationally introduced a cascaded biological amplifier module based on the Primer Exchange Reaction inspired by electronic circuit amplifier devices. As a paradigm, three abnormally expressed Hela cell microRNAs (-30a, -17, and -21) were chosen as "AND" gate inputs. DLC response to these inputs was boosted by the amplifier markedly enhancing the output signal. More importantly, the encapsulation of DLC and amplifier components into ZIF-8 nanoparticles resulted in their efficient delivery to the target site, successfully distinguishing the Hela tumor subtype from other tumors in vivo. Thus, we envision that this strategy has great potential for clinical cancer diagnosis.

Micro-compartmentalized strand displacement reactions with a random pool background

Toehold-mediated strand displacement (TMSD) is a widely used process in dynamic DNA nanotechnology, which has been applied for the actuation of molecular devices, in biosensor applications, and for DNA-based molecular computation. Similar processes also occur in a biological context, when RNA strands invade secondary structures or duplexes of other RNA or DNA molecules. Complex reaction environments-inside cells or synthetic cells-potentially contain a large number of competing nucleic acid molecules that transiently bind to the components of the strand displacement reaction of interest and thus slow down its kinetics. Here, we investigate the kinetics of TMSD reactions compartmentalized into water-in-oil emulsion droplets-in both the presence and absence of a random sequence background-using a droplet microfluidic 'stopped flow' set-up. The set-up enables one to determine the kinetics within thousands of droplets and easily vary experimental parameters such as the stoichiometry of the TMSD components. While the average kinetics in the droplets coincides precisely with the bulk behaviour, we observe considerable variability among the droplets. This variability is partially explained by the encapsulation procedure itself, but appears to be more pronounced in reactions involving a random pool background.

Supervised Learning in a Multilayer, Nonlinear Chemical Neural Network

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

A Cationic Copolymer Enhances Responsiveness and Robustness of DNA Circuits

Toehold-mediated DNA circuits are extensively employed to construct diverse DNA nanodevices and signal amplifiers. However, operations of these circuits are slow and highly susceptive to molecular noise such as the interference from bystander DNA strands. Herein, this work investigates the effects of a series of cationic copolymers on DNA catalytic hairpin assembly, a representative toehold-mediated DNA circuit. One copolymer, poly(L -lysine)-graft-dextran, significantly enhances the reaction rate by 30-fold due to its electrostatic interaction with DNA. Moreover, the copolymer considerably alleviates the circuit's dependency on the length and GC content of toehold, thereby enhancing the robustness of circuit operation against molecular noise. The general effectiveness of poly(L -lysine)-graft-dextran is demonstrated through kinetic characterization of a DNA AND logic circuit. Therefore, use of a cationic copolymer is a versatile and efficient approach to enhance the operation rate and robustness of toehold-mediated DNA circuits, paving the way for more flexible design and broader application.

Nano Self-Assembly for Apoptosis Induction and Early Therapeutic Efficacy Monitoring

Real-time monitoring of early antitumor efficacy is one of the key issues in realizing high-efficiency and more precise tumor treatment. As a highly specific event in the early stage of apoptosis, the release of cytochrome c may act as a key biomarker for monitoring cell apoptosis. However, achieving real-time monitoring of the cytochrome c release in vivo remains a challenge. Herein, we report a novel integrated nanosystem named DFeK nanoparticle (DFeK NP) to achieve a favorable collaboration of inducing tumor cell apoptosis and monitoring early therapeutic efficacy, which combined the cytochrome c-activated DNA nanoprobe cApt-App with pro-apoptotic peptide [KLAKLAK]2 and ferrous ions. [KLAKLAK]2 can target the mitochondria to disrupt the mitochondrial membrane together with reactive oxygen species produced by ferrous ions via the Fenton reaction to promote mitochondrial damage. Then, cytochrome c is released from damaged mitochondria to trigger apoptosis, further activating the cApt-App probe from the fluorescence "off" state to the "on" state. The cytochrome c-specific "off-to-on" transition was successfully applied in fluorescence imaging of cytochrome c in vivo and thus achieved real-time early therapeutic efficacy monitoring. Collectively, this work presents a valuable integrated tool for tumor inhibition and therapeutic efficacy evaluation to realize more precise and more effective tumor treatment.

Temporal logic circuits implementation using a dual cross-inhibition mechanism based on DNA strand displacement

Molecular circuits crafted from DNA molecules harness the inherent programmability and biocompatibility of DNA to intelligently steer molecular machines in the execution of microscopic tasks. In comparison to combinational circuits, DNA-based temporal circuits boast supplementary capabilities, allowing them to proficiently handle the omnipresent temporal information within biochemical systems and life sciences. However, the lack of temporal mechanisms and components proficient in comprehending and processing temporal information presents challenges in advancing DNA circuits that excel in complex tasks requiring temporal control and time perception. In this study, we engineered temporal logic circuits through the design and implementation of a dual cross-inhibition mechanism, which enables the acceptance and processing of temporal information, serving as a fundamental building block for constructing temporal circuits. By incorporating the dual cross-inhibition mechanism, the temporal logic gates are endowed with cascading capabilities, significantly enhancing the inhibitory effect compared to a cross-inhibitor. Furthermore, we have introduced the annihilation mechanism into the circuit to further augment the inhibition effect. As a result, the circuit demonstrates sensitive time response characteristics, leading to a fundamental improvement in circuit performance. This architecture provides a means to efficiently process temporal signals in DNA strand displacement circuits. We anticipate that our findings will contribute to the design of complex temporal logic circuits and the advancement of molecular programming.

Swelling characteristics of DNA polymerization gels

The development of biomolecular stimuli-responsive hydrogels is important for biomimetic structures, soft robots, tissue engineering, and drug delivery. DNA polymerization gels are a new class of soft materials composed of polymer gel backbones with DNA duplex crosslinks that can be swollen by sequential strand displacement using hairpin-shaped DNA strands. The extensive swelling can be tuned using physical parameters such as salt concentration and biomolecule design. Previously, DNA polymerization gels have been used to create shape-changing gel automata with a large design space and high programmability. Here we systematically investigate how the swelling response of DNA polymerization gels can be tuned by adjusting the design and concentration of DNA crosslinks in the hydrogels or DNA hairpin triggers, and the ionic strength of the solution in which swelling takes place. We also explore the effect hydrogel size and shape have on the swelling response. Tuning these variables can alter the swelling rate and extent across a broad range and provide a quantitative connection between biochemical reactions and macroscopic material behaviour.

Establishing artificial gene connections through RNA displacement-assembly-controlled CRISPR/Cas9 function

Construction of synthetic circuits that can reprogram genetic networks and signal pathways is a long-term goal for manipulation of biosystems. However, it is still highly challenging to build artificial genetic communications among endogenous RNA species due to their sequence independence and structural diversities. Here we report an RNA-based synthetic circuit that can establish regulatory linkages between expression of endogenous genes in both Escherichiacoli and mammalian cells. This design employs a displacement-assembly approach to modulate the activity of guide RNA for function control of CRISPR/Cas9. Our experiments demonstrate the great effectiveness of this RNA circuit for building artificial connections between expression of originally unrelated genes. Both exogenous and naturally occurring RNAs, including small/microRNAs and long mRNAs, are capable of controlling expression of another endogenous gene through this approach. Moreover, an artificial signal pathway inside mammalian cells is also successfully established to control cell apoptosis through our designed synthetic circuit. This study provides a general strategy for constructing synthetic RNA circuits, which can introduce artificial connections into the genetic networks of mammalian cells and alter the cellular phenotypes.

Design and Simulation of a Multilayer Chemical Neural Network That Learns via Backpropagation

The design and implementation of adaptive chemical reaction networks, capable of adjusting their behavior over time in response to experience, is a key goal for the fields of molecular computing and DNA nanotechnology. Mainstream machine learning research offers powerful tools for implementing learning behavior that could one day be realized in a wet chemistry system. Here we develop an abstract chemical reaction network model that implements the backpropagation learning algorithm for a feedforward neural network whose nodes employ the nonlinear "leaky rectified linear unit" transfer function. Our network directly implements the mathematics behind this well-studied learning algorithm, and we demonstrate its capabilities by training the system to learn a linearly inseparable decision surface, specifically, the XOR logic function. We show that this simulation quantitatively follows the definition of the underlying algorithm. To implement this system, we also report ProBioSim, a simulator that enables arbitrary training protocols for simulated chemical reaction networks to be straightforwardly defined using constructs from the host programming language. This work thus provides new insight into the capabilities of learning chemical reaction networks and also develops new computational tools to simulate their behavior, which could be applied in the design and implementations of adaptive artificial life.

Closed Cyclic DNA Machine for Sensitive Logic Operation and APE1 Detection

DNA self-assembly has been developed as a kind of robust signal amplification strategy, but most of reported assembly pathways are programmed to amplify signal in one direction. Herein, based on mutual-activated cascade cycle of hybridization chain reaction (HCR) and catalytic hairpin assembly (CHA), a closed cycle circuit (CCC) based DNA machine is developed for sensitive logic operation and molecular recognition. Benefiting from the synergistically accelerated signal amplification, the closed cyclic DNA machine enabled the logic computing with strong and significant output signals even at weak input signals. The typical logic operations such as OR, YES, AND, INHIBIT, NOR, and NAND gate, are conveniently and clearly executed with this DNA machine through rational design of the input and computing elements. Moreover, by integrating the target recognition module with the CCC module, the proposed DNA machine is further employed in the homogeneous detection of apurinic/apyrimidinic endonuclease 1 (APE1). The precise recognition and exponential signal amplification facilitated the highly selective and sensitive detection of APE1 with limit of detection (LOD) of 7.8 × 10^-5 U mL^-1 . Besides, the normal cells and tumor cells are distinguished unambiguously by this method according to the detected concentration difference of cellular APE1, which indicates the robustness and practicability of this method.

Design Approaches to Expand the Toolkit for Building Cotranscriptionally Encoded RNA Strand Displacement Circuits

Cotranscriptionally encoded RNA strand displacement (ctRSD) circuits are an emerging tool for programmable molecular computation, with potential applications spanning in vitro diagnostics to continuous computation inside living cells. In ctRSD circuits, RNA strand displacement components are continuously produced together via transcription. These RNA components can be rationally programmed through base pairing interactions to execute logic and signaling cascades. However, the small number of ctRSD components characterized to date limits circuit size and capabilities. Here, we characterize over 200 ctRSD gate sequences, exploring different input, output, and toehold sequences and changes to other design parameters, including domain lengths, ribozyme sequences, and the order in which gate strands are transcribed. This characterization provides a library of sequence domains for engineering ctRSD components, i.e., a toolkit, enabling circuits with up to 4-fold more inputs than previously possible. We also identify specific failure modes and systematically develop design approaches that reduce the likelihood of failure across different gate sequences. Lastly, we show the ctRSD gate design is robust to changes in transcriptional encoding, opening a broad design space for applications in more complex environments. Together, these results deliver an expanded toolkit and design approaches for building ctRSD circuits that will dramatically extend capabilities and potential applications.

A Theoretical Framework for Implementable Nucleic Acids Feedback Systems

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

Endogenous Enzyme-Operated Spherical Nucleic Acids for Cell-Selective Protein Capture and Localization Regulation

Precise regulation of protein activity and localization in cancer cells is crucial to dissect the function of the protein-involved cellular network in tumorigenesis, but there is a lack of suitable methodology. Here we report the design of enzyme-operated spherical nucleic acids (E-SNAs) for manipulation of the nucleocytoplasmic translocation of proteins with cancer-cell selectivity. The E-SNAs are constructed by programmable engineering of aptamer-based modules bearing enzyme-responsive units in predesigned sites and further combination with SNA nanotechnology. We demonstrate that E-SNAs are able to regulate cytoplasmic-to-nuclear shuttling of RelA protein efficiently and specifically in tumor cells, while they remain inactive in normal cells due to insufficient enzyme expression. We further confirmed the generality of this strategy by investigating the enzyme-modulated inhibition/activation of thrombin activity by varying the aptamer-based design.

Genetic switches based on nucleic acid strand displacement

Toehold-mediated strand displacement (TMSD) is an isothermal switching process that enables the sequence-programmable and reversible conversion of DNA or RNA strands between single- and double-stranded conformations or other secondary structures. TMSD processes have already found widespread application in DNA nanotechnology, where they are used to drive DNA-based molecular devices or for the realization of synthetic biochemical computing circuits. Recently, researchers have started to employ TMSD also for the control of RNA-based gene regulatory processes in vivo, in particular in the context of synthetic riboregulators and conditional guide RNAs for CRISPR/Cas. Here, we provide a review over recent developments in this emerging field and discuss the opportunities and challenges for such systems in in vivo applications.

Toehold-Mediated Strand Displacement in Random Sequence Pools

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

Nucleic acid-based artificial nanocarriers for gene therapy

Nucleic acid nanotechnology is a powerful tool in the fields of biosensing and nanomedicine owing to their high editability and easy synthesis and modification. Artificial nucleic acid nanostructures have become an emerging research hotspot as gene carriers with low cytotoxicity and immunogenicity for therapeutic approaches. In this review, recent progress in the design and functional mechanisms of nucleic acid-based artificial nano-vectors especially for exogenous siRNA and antisense oligonucleotide delivery is summarized. Different types of DNA nanocarriers, including DNA junctions, tetrahedrons, origami, hydrogels and scaffolds, are introduced. The enhanced targeting strategies to improve the delivery efficacy are demonstrated. Furthermore, RNA based gene nanocarrier systems by self-assembly of short strands, rolling circle transcription, chemical crosslinking and using RNA motifs and DNA-RNA hybrids are demonstrated. Finally, the outlook and potential challenges are highlighted. The nucleic acid-based artificial nanocarriers offer a promising and precise tool for gene delivery and therapy.

DNA Nanotechnology-Empowered Live Cell Measurements

The systematic analysis and precise manipulation of a variety of biomolecules should lead to unprecedented findings in fundamental biology. However, conventional technology cannot meet the current requirements. Despite this, there has been progress as DNA nanotechnology has evolved to generate DNA nanostructures and circuits over the past four decades. Many potential applications of DNA nanotechnology for live cell measurements have begun to emerge owing to the biocompatibility, nanometer addressability, and stimulus responsiveness of DNA. In this review, the DNA nanotechnology-empowered live cell measurements which are currently available are summarized. The stability of the DNA nanostructures, in a cellular microenvironment, which is crucial for accomplishing precise live cell measurements, is first summarized. Thereafter, measurements in the extracellular and intracellular microenvironment, in live cells, are introduced. Finally, the challenges that are innate to, and the further developments that are possible in this nascent field are discussed.

CRISPR/Cas9-based coronal nanostructures for targeted mitochondria single molecule imaging

The biological state at the subcellular level is highly relevant to many diseases, and the monitoring of organelles such as mitochondria is crucial based on this. However, most DNA and protein based nanoprobes used for the detection of mitochondrial RNAs (mitomiRs) lack spatial selectivity, which leads to inefficiencies in probe delivery and signal turn-on. Herein, we constructed a novel DNA nanoprobe named protein delivery nano-corona (PDNC) to improve the delivery efficiency of Cas protein, for spatially selective imaging of mitomiRs in living cells switched on by a CRISPR/Cas system. Combined with a single-molecule counting method, this strategy enables highly sensitive detection of low-abundance mitomiR. Therefore, the strategy in this work opens up new opportunities for cell identification, early clinical diagnosis, and research in biological behaviour at the subcellular level.

Standardized excitable elements for scalable engineering of far-from-equilibrium chemical networks

Engineered far-from-equilibrium synthetic chemical networks that pulse or switch states in response to environmental signals could precisely regulate the kinetics of chemical synthesis or self-assembly. Currently, such networks must be extensively tuned to compensate for the different activities of and unintended reactions between a network's various chemical components. Modular elements with standardized performance could be used to rapidly construct networks with designed functions. Here we develop standardized excitable chemical regulatory elements, termed genelets, and use them to construct complex in vitro transcriptional networks. We develop a protocol for identifying >15 interchangeable genelet elements with uniform performance and minimal crosstalk. These elements can be combined to engineer feedforward and feedback modules whose dynamics match those predicted by a simple kinetic model. Modules can then be rationally integrated and organized into networks that produce tunable temporal pulses and act as multistate switchable memories. Standardized genelet elements, and the workflow to identify more, should make engineering complex far-from-equilibrium chemical dynamics routine.

Protecting Heterochiral DNA Nanostructures against Exonuclease-Mediated Degradation

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

Programming Molecular Systems To Emulate a Learning Spiking Neuron

Hebbian theory seeks to explain how the neurons in the brain adapt to stimuli to enable learning. An interesting feature of Hebbian learning is that it is an unsupervised method and, as such, does not require feedback, making it suitable in contexts where systems have to learn autonomously. This paper explores how molecular systems can be designed to show such protointelligent behaviors and proposes the first chemical reaction network (CRN) that can exhibit autonomous Hebbian learning across arbitrarily many input channels. The system emulates a spiking neuron, and we demonstrate that it can learn statistical biases of incoming inputs. The basic CRN is a minimal, thermodynamically plausible set of microreversible chemical equations that can be analyzed with respect to their energy requirements. However, to explore how such chemical systems might be engineered de novo, we also propose an extended version based on enzyme-driven compartmentalized reactions. Finally, we show how a purely DNA system, built upon the paradigm of DNA strand displacement, can realize neuronal dynamics. Our analysis provides a compelling blueprint for exploring autonomous learning in biological settings, bringing us closer to realizing real synthetic biological intelligence.

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.

Cellular Computational Logic Using Toehold Switches

The development of computational logic that carries programmable and predictable features is one of the key requirements for next-generation synthetic biological devices. Despite considerable progress, the construction of synthetic biological arithmetic logic units presents numerous challenges. In this paper, utilizing the unique advantages of RNA molecules in building complex logic circuits in the cellular environment, we demonstrate the RNA-only bitwise logical operation of XOR gates and basic arithmetic operations, including a half adder, a half subtractor, and a Feynman gate, in Escherichia coli. Specifically, de-novo-designed riboregulators, known as toehold switches, were concatenated to enhance the functionality of an OR gate, and a previously utilized antisense RNA strategy was further optimized to construct orthogonal NIMPLY gates. These optimized synthetic logic gates were able to be seamlessly integrated to achieve final arithmetic operations on small molecule inputs in cells. Toehold-switch-based ribocomputing devices may provide a fundamental basis for synthetic RNA-based arithmetic logic units or higher-order systems in cells.

Cotranscriptionally encoded RNA strand displacement circuits

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

Multi-arm RNA junctions encoding molecular logic unconstrained by input sequence for versatile cell-free diagnostics

Applications of RNA-based molecular logic have been hampered by sequence constraints imposed on the input and output of the circuits. Here we show that the sequence constraints can be substantially reduced by appropriately encoded multi-arm junctions of single-stranded RNA structures. To conditionally activate RNA translation, we integrated multi-arm junctions, self-assembled upstream of a regulated gene and designed to unfold sequentially in response to different RNA inputs, with motifs of loop-initiated RNA activators that function independently of the sequence of the input RNAs and that reduce interference with the output gene. We used the integrated RNA system and sequence-independent input RNAs to execute two-input and three-input OR and AND logic in Escherichia coli, and designed paper-based cell-free colourimetric assays that accurately identified two human immunodeficiency virus (HIV) subtypes (by executing OR logic) in amplified synthetic HIV RNA as well as severe acute respiratory syndrome coronavirus-2 (via two-input AND logic) in amplified RNA from saliva samples. The sequence-independent molecular logic enabled by the integration of multi-arm junction RNAs with motifs for loop-initiated RNA activators may be broadly applicable in biotechnology.

A high-integrated DNA biocomputing platform for MicroRNA sensing in living cells

DNA logic computing has captured increasing interest due to its ability to assemble programmable DNA computing elements for disease diagnosis, gene regulation, and targeted therapy. In this work, we developed an aptamer-equipped high-integrated DNA biocomputing platform (HIDBP-A) with a dual-recognition function that enabled cancer cell targeting. Dual microRNAs were the input signals and can perform AND logic operations. Compared to the free DNA biocomputing platform (FDBP), the integration of all computing elements into the same DNA tetrahedron greatly improved logic computing speed and efficiency owing to the confinement effect reflected by the high local concentration of computing elements. As a proof of concept, the utilization of microRNA as the input signal was beneficial for improving the scalability and flexibility of the sequence design of the logic nano-platform. Given that the different microRNAs were over-expressed in cancer cells, this new HIDBP-A has great promise in accurate diagnosis and logic-controlled disease treatment.

Programmable siRNA pro-drugs that activate RNAi activity in response to specific cellular RNA biomarkers

Since Paul Ehrlich's introduction of the "magic bullet" concept in 1908, drug developers have been seeking new ways to target drug activity to diseased cells while limiting effects on normal tissues. In recent years, it has been proposed that coupling riboswitches capable of detecting RNA biomarkers to small interfering RNAs (siRNAs) to create siRNA pro-drugs could selectively activate RNA interference (RNAi) activity in specific cells. However, this concept has not been achieved previously. We report here that we have accomplished this goal, validating a simple and programmable new design that functions reliably in mammalian cells. We show that these conditionally activated siRNAs (Cond-siRNAs) can switch RNAi activity against different targets between clearly distinguished OFF and ON states in response to different cellular RNA biomarkers. Notably, in a rat cardiomyocyte cell line (H9C2), one version of our construct demonstrated biologically meaningful inhibition of a heart-disease-related target gene protein phosphatase 3 catalytic subunit alpha (PPP3CA) in response to increased expression of the pathological marker atrial natriuretic peptide (NPPA) messenger RNA (mRNA). Our results demonstrate the ability of synthetic riboswitches to regulate gene expression in mammalian cells, opening a new path for development of programmable siRNA pro-drugs.

Sensitive Logic Nanodevices with Strong Response for Weak Inputs

Sensitive sensing is critical when developing new calculation systems with weak input signals (ISs). In this work, a "weak-inputs-strong-outputs" strategy was proposed to guide the construction of sensitive logic nanodevices by coupling an input-induced reversible DNA computing platform with a hybridization chain reaction-based signal amplifier. By rational design of the sequence of computing elements (CEs) so as to avoid cross-talking between ISs and signal amplifier, the newly formed logic nanodevices have good sensitivity to the weak ISs even at low concentrations of CEs, and are able to perform YES, OR, NAND, NOR, INHIBIT, INHIBIT-OR and number classifier operation, showing that the DNA calculation proceeds in dilute solution medium that greatly improves the calculation proficiency of logic nanodevices without the confinement of the lithography process in nanotechnology.

Delivery of therapeutic oligonucleotides in nanoscale

Therapeutic oligonucleotides (TOs) represent one of the most promising drug candidates in the targeted cancer treatment due to their high specificity and capability of modulating cellular pathways that are not readily druggable. However, efficiently delivering of TOs to cancer cellular targets is still the biggest challenge in promoting their clinical translations. Emerging as a significant drug delivery vector, nanoparticles (NPs) can not only protect TOs from nuclease degradation and enhance their tumor accumulation, but also can improve the cell uptake efficiency of TOs as well as the following endosomal escape to increase the therapeutic index. Furthermore, targeted and on-demand drug release of TOs can also be approached to minimize the risk of toxicity towards normal tissues using stimuli-responsive NPs. In the past decades, remarkable progresses have been made on the TOs delivery based on various NPs with specific purposes. In this review, we will first give a brief introduction on the basis of TOs as well as the action mechanisms of several typical TOs, and then describe the obstacles that prevent the clinical translation of TOs, followed by a comprehensive overview of the recent progresses on TOs delivery based on several various types of nanocarriers containing lipid-based nanoparticles, polymeric nanoparticles, gold nanoparticles, porous nanoparticles, DNA/RNA nanoassembly, extracellular vesicles, and imaging-guided drug delivery nanoparticles.

A novel strategy for programmable DNA tile self-assembly with a DNAzyme-mediated DNA cross circuit

The proposed strategy promotes the controllability and modularization of trigger elements, realizes programmable molecular self-assembly, and has broad applications for the construction of DNA nanodevices.

Building Endogenous Gene Connections through RNA Self-Assembly Controlled CRISPR/Cas9 Function

Construction of synthetic circuits that can artificially establish endogenous gene connections is essential to introduce new phenotypes for cellular behaviors. Given the diversity of endogenous genes, it lacks a general and easy-to-design toolbox to manipulate the genetic network. Here we present a type of self-assembly-induced RNA circuit that can directly build regulatory connections between endogenous genes. Inspired from the natural assembling process of guide RNA in the CRISPR/Cas9 complex, this design employs an independent trigger RNA strand to induce the formation of a ternary guide RNA assembly for functional control of CRISPR/Cas9. With this general principle, expressional regulations of endogenous genes can be controlled by totally independent endogenous small RNAs and mRNAs in E. coli via activatable CRISPR/Cas9 function. Moreover, the cellular phenotype of E. coli is successfully programmed with introduction of new gene connections. In addition, the functionality of this design is also verified in the mammalian system. This self-assembly-based RNA circuit exhibits a great flexibility and simplicity of design and provides a unique approach to build endogenous gene connections, which paves a broad way toward manipulation of cellular genetic networks.

DNA Matrix Operation Based on the Mechanism of the DNAzyme Binding to Auxiliary Strands to Cleave the Substrate

Numerical computation is a focus of DNA computing, and matrix operations are among the most basic and frequently used operations in numerical computation. As an important computing tool, matrix operations are often used to deal with intensive computing tasks. During calculation, the speed and accuracy of matrix operations directly affect the performance of the entire computing system. Therefore, it is important to find a way to perform matrix calculations that can ensure the speed of calculations and improve the accuracy. This paper proposes a DNA matrix operation method based on the mechanism of the DNAzyme binding to auxiliary strands to cleave the substrate. In this mechanism, the DNAzyme binding substrate requires the connection of two auxiliary strands. Without any of the two auxiliary strands, the DNAzyme does not cleave the substrate. Based on this mechanism, the multiplication operation of two matrices is realized; the two types of auxiliary strands are used as elements of the two matrices, to participate in the operation, and then are combined with the DNAzyme to cut the substrate and output the result of the matrix operation. This research provides a new method of matrix operations and provides ideas for more complex computing systems.

Molecular communication relays for dynamic cross-regulation of self-sorting fibrillar self-assemblies

Structures in living systems cross-regulate via exchange of molecular information to assemble or disassemble on demand and in a coordinated, signal-triggered fashion. DNA strand displacement (DSD) reaction networks allow rational design of signaling and feedback loops, but combining DSD with structural nanotechnology to achieve self-reconfiguring hierarchical system states is still in its infancy. We introduce modular DSD networks with increasing amounts of regulatory functions, such as negative feedback, signal amplification, and signal thresholding, to cross-regulate the transient polymerization/depolymerization of two self-sorting DNA origami nanofibrils and nanotubes. This is achieved by concatenation of the DSD network with molecular information relays embedded on the origami tips. The two origamis exchange information and display programmable transient states observable by TEM and fluorescence spectroscopy. The programmability on the DSD and the origami level is a viable starting point toward more complex lifelike behavior of colloidal multicomponent systems featuring advanced signal processing functions.

Nucleic acid-based molecular computation heads towards cellular applications

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

A Multivariate-Gated DNA Nanodevice for Spatioselective Imaging of Pro-metastatic Targets in Extracellular Microenvironment

Probing pro-metastatic biomarkers is of significant importance to evaluate the risk of tumor metastasis, but spatially selective imaging of such targets in extracellular microenvironment is particularly challenging. By introducing the bilinguality of PNA/peptide hybrid that can speak both peptide substrate and nucleobase-pairing languages to combine with aptamer technology, we designed a smart DNA nanodevice programmed to respond sequentially to dual pro-metastatic targets, MMP2/9 and ATP, in extracellular tumor microenvironment (TME). The DNA nanodevice is established based on the combination of an ATP-responsive aptamer sensor and a MMP2/9-hydrolyzable PNA/peptide copolymer with a cell membrane-anchoring aptamer module. Taking 4T1 xenograft as a highly aggressive tumor model, the robustness of the DNA nanodevice in spatioselective imaging of MMP2/9 and ATP in TME is demonstrated. We envision that this design will enable the simultaneous visualization of multiple pro-metastatic biomarkers, which allows to gain insights into their pathological roles in tumor metastasis.