Search

Due to the complexity of regulatory networks of disease-related biomarkers, developing simple, sensitive, and accurate methods has remained challenging for precise diagnosis. Herein, an "AND" logic gates DNA molecular machine (LGDM) was constructed, which was powered by the catalytic hairpin assembly (CHA). It was coupled with dual-emission CdTe quantum dots (QDs)-based cation exchange reaction (CER) for label-free, sensitive, and ratiometric fluorescence detection of APE1 and miRNA biomarkers. Benefiting from synergistic signal amplification strategies and a ratiometric fluorometric output mode, this LGDM enables accurate logic computing with robust and significant output signals from weak inputs. It offers improved sensitivity and selectivity even in cell extracts. Using dual-emission spectra CdTe QDs, with a ratiometric signal output mode, ensured good stability and effectively prevented false-positive signals from intrinsic biological interferences compared to the approach relying on a single signal output mode, which enabled the LGDM to achieve rapid, efficient, and accurate natural drug screening against APE1 inhibitors in vitro and cells. The developed method provides impetus to streamline research related to miRNA and APE1, offering significant promise for widespread application in drug development and clinical analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

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

Any modern information system is expected to feature a set of primordial features and functions: a substrate stably carrying data; the ability to repeatedly write, read, erase, reload and compute on specific data from that substrate; and the overall ability to execute such functions in a seamless and programmable manner. For nascent molecular information technologies, proof-of-principle realization of this set of primordial capabilities would advance the vision for their continued development. Here we present a DNA-based store and compute engine that captures these primordial capabilities. This system comprises multiple image files encoded into DNA and adsorbed onto ~50-μm-diameter, highly porous, hierarchically branched, colloidal substrate particles comprised of naturally abundant cellulose acetate. Their surface areas are over 200 cm 2  mg -1 with binding capacities of over 10 12  DNA oligos mg -1 , 10 TB mg -1 or 10 4  TB cm - 3 . This 'dendricolloid' stably holds DNA files better than bare DNA with an extrapolated ability to be repeatedly lyophilized and rehydrated over 170 times compared with 60 times, respectively. Accelerated ageing studies project half-lives of ~6,000 and 2 million years at 4 °C and -18 °C, respectively. The data can also be erased and replaced, and non-destructive file access is achieved through transcribing from distinct synthetic promoters. The resultant RNA molecules can be directly read via nanopore sequencing and can also be enzymatically computed to solve simplified 3 × 3 chess and sudoku problems. Our study establishes a feasible route for utilizing the high information density and parallel computational advantages of nucleic acids., Competing Interests: Competing interests The authors declare the following competing interests: A.J.K. and J.M.T. are cofounders of DNAli Data Technologies that has potential interest in translating and commercializing DNA-based information systems. A.J.K., K.V., J.M.T. and K.N.L. are inventors of patent WO 2020/096679 which has been licensed to DNAli Data Technologies and from which some of this work is derived. W.T. has two patents (8,748,091 and 8,394,584), licensed to Oxford Nanopore Technologies (ONT), which were used for direct RNA sequencing in this work. W.T. has received travel funds to speak at symposia organized by ONT. The other authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Nanozymes are a class of nanomaterials with biocatalytic function and enzyme-like activity, whose advantages include high stability, low cost, and mass production. They can catalyze the substrates of natural enzymes based on specific nanostructures and serve as substitutes for natural enzymes. Their applied research involves a wide range of fields such as biomedicine, environmental governance, agriculture, and food. Molecular logic gates are a new cross-disciplinary discipline, which can simulate the function of silicon circuits on a molecular scale, perform single or multiple input logic operations, and generate logic outputs. A molecular logic gate is a binary operation that converts an input signal into an output signal according to the rules of Boolean logic, generating two signals, a high level, and a low level. The high and low levels represent the "true" and "false" values of the logic gates, and their outputs correspond to "l" and "0" of the molecular logic gates, respectively. The combination of nanozymes and logic gates is a novel and attractive research direction, and the cross-application of the two brings new opportunities and ideas for various fields, such as the construction of efficient biocomputers, intelligent drug delivery systems, and the precise diagnosis of diseases. This review describes the application of logic gates based on nanozymes, which is expected to provide a certain theoretical foundation for researchers' subsequent studies., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

DNA computing is regarded as one of the most promising candidates for the next generation of molecular computers, utilizing DNA to execute Boolean logic operations. In recent decades, DNA computing has garnered widespread attention due to its powerful programmable and parallel computing capabilities, demonstrating significant potential in intelligent biological analysis. This review summarizes the latest advancements in DNA logic systems and their biomedical applications. Firstly, it introduces recent DNA logic systems based on various materials such as functional DNA sequences, nanomaterials, and three-dimensional DNA nanostructures. The material innovations driving DNA computing have been summarized, highlighting novel molecular reactions and analytical performance metrics like efficiency, sensitivity, and selectivity. Subsequently, it outlines the biomedical applications of DNA computing-based multi-biomarker analysis in cellular imaging, clinical diagnosis, and disease treatment. Additionally, it discusses the existing challenges and future research directions for the development of DNA computing.

Given the high degree of variability and complexity of cancer, precise monitoring and logical analysis of different nucleic acid markers are crucial for improving diagnostic precision and patient survival rates. However, existing molecular diagnostic methods normally suffer from high cost, cumbersome procedures, dependence on specialized equipment and the requirement of in-depth expertise in data analysis, failing to analyze multiple cancer-associated nucleic acid markers and provide immediate results in a point-of-care manner. Herein, we demonstrate a transistor-based DNA molecular computing (TDMC) platform that enables simultaneous detection and logical analysis of multiple microRNA (miRNA) markers on a single transistor. TDMC can perform not only basic logical operations such as "AND" and "OR", but also complex cascading computing, opening up new dimensions for multi-index logical analysis. Owing to the high efficiency, sensing and computations of multi-analytes can be operated on a transistor at a concentration as low as 2×10 -16 M, reaching the lowest concentration for DNA molecular computing. Thus, TDMC achieves an accuracy of 98.4 % in the diagnosis of hepatocellular carcinoma from 62 serum samples. As a convenient and accurate platform, TDMC holds promise for applications in "one-stop" personalized medicine., (© 2024 Wiley-VCH GmbH.)

Tumor-associated antigens (TAAs) are not exclusively expressed in cancer cells, inevitably causing the "on target, off tumor" effect of molecular recognition tools. To achieve precise recognition of cancer cells, by using protein tyrosine kinase 7 (PTK7) as a model TAA, a DNA molecular logic circuit Aisgc8 was rationally developed by arranging H + -binding i-motif, ATP-binding aptamer, and PTK7-targeting aptamer Sgc8c in a DNA sequence. Aisgc8 output the conformation of Sgc8c to recognize PTK7 on cells in a simulated tumor microenvironment characterized by weak acidity and abundant ATP, but not in a simulated physiological environment. Through in vitro and in vivo results, Aisgc8 demonstrated its ability to precisely recognize cancer cells and, as a result, displayed excellent performance in tumor imaging. Thus, our studies produced a simple and efficient strategy to construct DNA logic circuits, opening new possibilities to develop convenient and intelligent precision diagnostics by using DNA logic circuits.

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.

DNA circuits are important fundamental tools for performing temporal logic operations with complex structures, but they lack sequence orthogonality. Here, we developed a simple and orthogonal hairpin exonuclease assistance signal (H-EAST) architecture to construct DNA domino circuits with time-delay characteristics and temporal logic operations, which has potential applications in biomolecular computing.

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., (© 2024. The Author(s).)

Current molecular logic gates are predominantly focused on the qualitative assessment of target presence, which has certain limitations in scenarios requiring quantitative assessment, such as chemical contaminant monitoring. To bridge this gap, we have developed a novel DNA logic gate featuring a tunable threshold, specifically tailored to the limits of contaminants. At the core of this logic gate is a DNA-gold nanoparticle (AuNP) hybrid film that incorporates aptamer sequences to selectively bind to acetamiprid (ACE) and atrazine (ATR). Upon interaction with these contaminants, the film degrades, releasing AuNPs that, in the presence of Hg 2+ , catalyze the oxidation of TMB, resulting in a visible blue coloration on test paper. This aptamer-enabled process effectively establishes an OR logic gate, with ACE and ATR as inputs and the appearance of blue color as the output. A key innovation of our system is its tunable input threshold. By adjusting the concentration of Hg 2+ , we can fine-tune the color mutation points to match the input threshold to predefined limits, such as Maximum Residue Limits (MRLs). This alignment allows semiquantitative assessment of contaminant levels, providing intuitive visual feedback of contaminant exceedance. Validation experiments with spiked samples confirm its accuracy and reliability by closely matching HPLC results. Therefore, our colorimetric DNA logic gate is emerging as a promising tool for easy and semiquantitative monitoring of chemical contaminants across diverse applications.

The DNA-based logic circuit, constructed to mimic biochemical reaction networks, is highly significant in detecting biomarkers at the molecular level. The differences in the expression levels of microRNAs (miRNAs) within different types of cells provide hope for distinguishing cell subtypes. However, reliance on a single miRNA often leads to unreliable results. Herein, we constructed an enzyme-triggered cascade logic circuit based on the AND gate, which is capable of generating corresponding fluorescence signals in the presence of target miRNAs. The introduction of apurinic/apyrimidinic (AP) sites effectively reduces the likelihood of false signal generation. Amplification of the fluorescence signal relies on the catalytic hairpin assembly and the repetitive reuse of the multicomponent nucleic acid enzyme (MNAzyme). We demonstrated that the logic circuit can not only distinguish cancer cells from normal cells but also identify different types of cancer cells. The programmability of the logic circuits and the simplicity of the assay system allow us to modify the functional sequences to recognize different types of biomarkers, thus providing a reference for the identification of various cell subtypes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

A network of nanomachines (NMs) can be used to build a target detection system for a variety of promising applications. They have the potential to detect toxic chemicals, infectious bacteria, and biomarkers of dangerous diseases such as cancer within the human body. Many diseases and health disorders can be detected early and efficiently treated in the future by utilizing these systems. To fully grasp the potential of these systems, mathematical analysis is required. This paper describes an analytical framework for modeling and analyzing the performance of target detection systems composed of multiple mobile nanomachines of varying sizes with passive/absorbing boundaries. We consider both direct contact detection, in which NMs must physically contact the target to detect it, and indirect sensing, in which NMs must detect the marker molecules emitted by the target. The detection performance of such systems is calculated for degradable and non-degradable targets, as well as mobile and stationary targets. The derived expressions provide various insights, such as the effect of NM density and target degradation on detection probability.

In this paper, we propose a new coding scheme for DNA storage using low-density parity-check (LDPC) codes and interleaving techniques. While conventional coding schemes generally employ error correcting codes in both inter and intra-oligo directions, we show that inter-oligo LDPC codes, optimized by differential evolution, are sufficient in ensuring the reliability of DNA storage due to the powerful soft decoding of LDPC codes. In addition, we apply interleaving techniques for handling non-uniform error characteristics of DNA storage to enhance the decoding performance. Consequently, the proposed coding scheme reduces the required number of oligo reads for perfect recovery by 26.25% ~ 38.5% compared to existing state-of-the-art coding schemes. Moreover, we develop an analytical DNA channel model in terms of non-uniform binary symmetric channels. This mathematical model allows us to demonstrate the superiority of the proposed coding scheme while isolating the experimental variation, as well as confirm the independent effects of LDPC codes and interleaving techniques.

Molecular communication (MC) is recently featured as a novel communication tool to connect individual biological nanorobots. It is expected that a large number of nanorobots can form large multi-agent MC systems through MC to accomplish complex and large-scale tasks that cannot be achieved by a single nanorobot. However, most previous models for MC systems assume a unidirectional diffusion communication channel and cannot capture the feedback between each nanorobot, which is important for multi-agent MC systems. In this paper, we introduce a system theoretic model for large-scale multi-agent MC systems using transfer functions, and then propose a method to analyze the stability for multi-agent MC systems. The proposed method decomposes the multi-agent MC system into multiple single-input and single-output (SISO) systems, which facilitates the application of simple analysis technique for SISO systems to the large-scale multi-agent MC system. Finally, we demonstrate the proposed method by analyzing the stability of a specific large-scale multi-agent MC system and clarify a parameter region to synchronize the states of nanorobots, which is important to make cooperative behaviors at a population level.

The traveling car renter problem (TCRP) is a variant of the Traveling Salesman Problem (TSP) wherein the salesman utilizes rented cars for travel. The primary objective of this problem is to identify a solution that minimizes the cumulative operating costs. Given its classification as a non-deterministic polynomial (NP) problem, traditional computers are not proficient in effectively resolving it. Conversely, DNA computing exhibits unparalleled advantages when confronted with NP-hard problems. This paper presents a DNA algorithm, based on the Adleman-Lipton model, as a proposed approach to address TCRP. The solution for TCRP can be acquired by following a series of fundamental steps, including coding, interaction, and extraction. The time computing complexity of the proposed DNA algorithm is O(n 2 m) for TCRP with n cities and m types of cars. By conducting simulation experiments, the solutions for certain instances of TCRP are computed and compared to those obtained by alternative algorithms. The proposed algorithm further illustrates the potential of DNA computing, as a form of parallel computing, to address more intricate large-scale problems.

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., (© 2024 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

In molecular communication (MC), molecules are released from the transmitter to convey information. This paper considers a realistic molecule shift keying (MoSK) scenario with two species of molecule in two reservoirs, where the molecules are harvested from the environment and placed into different reservoirs, which are purified by exchanging molecules between the reservoirs. This process consumes energy, and for a reasonable energy cost, the reservoirs cannot be pure; thus, our MoSK transmitter is imperfect, releasing mixtures of both molecules for every symbol, resulting in inter-symbol interference (ISI). To mitigate ISI, the properties of the receiver are analyzed and a detection method based on the ratio of different molecules is proposed. Theoretical and simulation results are provided, showing that with the increase of energy cost, the system achieves better performance. The good performance of the proposed detection scheme is also demonstrated.

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The invention of DNA nanotechnology has enabled molecular computation as a promising substitute for traditional semiconductors which are limited to two-dimensional architectures and by heating problems resulting from densification. Current studies of logic gates achieved using DNA molecules are predominately focused on two-state operations (AND, OR, etc .); however, realizing tri-state logic (high impedance Z) in DNA computation is understudied. Here we actively fold DNA origami chain-like hinged rods to induce conformational changes that return tri-state logic signals. We use rigid six helix-bundle (6HB) DNA origami to self-assemble a linear trimer chain as a circuit platform with functional single-stranded (ss) DNA near each semi-flexible hinge. The presence or absence of ssDNA enable and input strands allows hybridization to take place at the hinges, activating one fold (0) or two folds (1) from the straight linear geometry (defined as High-Z) of the trimer chain. We design two different tri-state logic gate platforms, buffer and inverter, with corresponding enable/input ssDNA to unambiguously return tri-state signals, characterized by Atomic Force Microscopy (AFM) and/or agarose gel electrophoresis (GEL). Our work on tri-state logic significantly enhances DNA computation beyond the current two-state Boolean logic with both research and industrial applications, including cellular treatments and living matter utilizing the biocompatibility of DNA molecules.

DNA has emerged as a promising tool to build logic gates for biocomputing. However, prevailing methodologies predominantly rely on hybridization reactions or structural alterations to construct DNA logic gates, which are limited in simplicity and diversity. Herein, we developed simple and smart DNA-based logic gates for biocomputing through the DNA-mediated growth of gold nanomaterials without precise structure design and probe modification. Capitalizing on their excellent plasmonic properties, the surface growth of gold nanomaterials enables distinct wavelength shifts and unique shapes, which are modulated by the composition, length, and concentration of the DNA sequences. Combined with a CRISPR-mediated reaction, we constructed DNA circuits to achieve complicated biocomputing to modulate the surface growth of gold nanomaterials. By implementing logic functions controlled by input-mediated growth of gold nanomaterials, we established YES/NOT, AND/NAND, OR/NOR, XOR, and INHIBIT gates and further constructed cascade logic circuits, parity checker for natural numbers, and gray code encoder, which are promising for DNA biocomputing.

In the last few decades, DNA-based self-assembly tiles has become a hot field in research due to its special applications and advantages. The regularity and strong design methods comprise other DNA-based digital circuit design methods. In addition to the obvious advantages of this method, there are challenges in performing computations based on self-assembly tiles, which have hindered the development and construction of large computing circuits with this method. The first challenge is the creation of crystals from DNA molecules in the output, which has led to the impossibility of cascading. The second challenge of this method is the uncontrollability of the reactions of the tiles, which increases the percentage of computing errors. In this article, these two challenges have been solved by changing the structure of leading tiles so that without the activator strand, tiles remain inactive and cannot be connected to other tiles. Also, when the tiles are activated, single-strand DNA will be released after connecting to other tiles, which will be used as the output of the circuit. This output gives the possibility of cascading to self-assembly designed circuits. The method introduced in this article can be a beginning for the re-development of DNA-based circuit design with the self-assembly tile method.

Molecular computing is an emerging paradigm that plays an essential role in data storage, bio-computation, and clinical diagnosis with the future trends of more efficient computing scheme, higher modularity with scaled-up circuity and stronger tolerance of corrupted inputs in a complex environment. Towards these goals, we construct a spatially localized, DNA integrated circuits-based classifier (DNA IC-CLA) that can perform neuromorphic architecture-based computation at a molecular level for medical diagnosis. The DNA-based classifier employs a two-dimensional DNA origami as the framework and localized processing modules as the in-frame computing core to execute arithmetic operations (e.g. multiplication, addition, subtraction) for efficient linear classification of complex patterns of miRNA inputs. We demonstrate that the DNA IC-CLA enables accurate cancer diagnosis in a faster (about 3 h) and more effective manner in synthetic and clinical samples compared to those of the traditional freely diffusible DNA circuits. We believe that this all-in-one DNA-based classifier can exhibit more applications in biocomputing in cells and medical diagnostics., (© 2024. The Author(s).)

DNA circuits, as a type of biochemical system, have the capability to synchronize the perception of molecular information with a chemical reaction response and directly process the molecular characteristic information in biological activities, making them a crucial area in molecular digital computing and smart bioanalytical applications. Instead of cascading logic gates, the traditional research approach achieves multiple logic operations which limits the scalability of DNA circuits and increases the development costs. Based on the interface reaction mechanism of Lambda exonuclease, the molecular perceptron proposed in this study, with the need for only adjusting weight and bias parameters to alter the corresponding logic expressions, enhances the versatility of the molecular circuits. We also establish a mathematical model and an improved heuristic algorithm for solving weights and bias parameters for arbitrary logic operations. The simulation and FRET experiment results of a series of logic operations demonstrate the universality of molecular perceptron. We hope the proposed molecular perceptron can introduce a new design paradigm for molecular circuits, fostering innovation and development in biomedical research related to biosensing, targeted therapy, and nanomachines.

Accurate classification of tumor cells is of importance for cancer diagnosis and further therapy. In this study, we develop multimolecular marker-activated transmembrane DNA computing systems (MTD). Employing the cell membrane as a native gate, the MTD system enables direct signal output following simple spatial events of "transmembrane" and "in-cell target encounter", bypassing the need of multistep signal conversion. The MTD system comprises two intelligent nanorobots capable of independently sensing three molecular markers (MUC1, EpCAM, and miR-21), resulting in comprehensive analysis. Our AND-AND logic-gated system (MTD AND-AND ) demonstrates exceptional specificity, allowing targeted release of drug-DNA specifically in MCF-7 cells. Furthermore, the transformed OR-AND logic-gated system (MTD OR-AND ) exhibits broader adaptability, facilitating the release of drug-DNA in three positive cancer cell lines (MCF-7, HeLa, and HepG2). Importantly, MTD AND-AND and MTD OR-AND , while possessing distinct personalized therapeutic potential, share the ability of outputting three imaging signals without any intermediate conversion steps. This feature ensures precise classification cross diverse cells (MCF-7, HeLa, HepG2, and MCF-10A), even in mixed populations. This study provides a straightforward yet effective solution to augment the versatility and precision of DNA computing systems, advancing their potential applications in biomedical diagnostic and therapeutic research.

With the advent of the post-Moore's Law era, the development of traditional silicon-based computers has reached its limit, and there is an urgent need to develop new computing technologies to meet the needs of science, technology, and daily life. Due to its super-strong parallel computing capability and outstanding data storage capacity, DNA computing has become an important branch and hot research topic of new computer technology. DNA enzyme-free hybridization reaction technology is widely used in DNA computing, showing excellent performance in computing power and information processing. Studies have shown that DNA molecules not only have the computing function of electronic devices, but also exhibit certain human brain-like functions. In the field of artificial intelligence, activation functions play an important role as they enable artificial intelligence systems to fit and predict non-linear and complex variable relationships. Due to the difficulty of implementing activation functions in DNA computing, DNA circuits cannot easily achieve all the functions of artificial intelligence. DNA circuits need to rely on electronic computers to complete the training and learning process. Based on the parallel computing characteristics of DNA computing and the kinetic features of DNA molecule displacement reactions, this paper proposes a new activation function. This activation function can not only be easily implemented by DNA enzyme-free hybridization reaction reactions, but also has good nesting properties in DNA circuits, and can be cascaded with other DNA reactions to form a complete DNA circuit. This paper not only provides the mathematical analysis of the proposed activation function, but also provides a detailed analysis of its kinetic features. The activation function is then nested into a nonlinear neural network for DNA computing. This system is capable of fitting and predicting a certain nonlinear function.

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., (© 2024 Wiley‐VCH GmbH.)

This paper studies the secrecy performance in a 3-D diffusive molecular communication system with the general depleted molecule shift keying (D-MoSK) modulation, where a point transmitter Alice transmits through diffusion multiple types of molecules modulation to a legitimate absorbing receiver Bob, suffering the eavesdropping from an absorbing eavesdropper Eve. We first develop a solid theoretical framework to determine the probabilistic distributions for the number of molecules absorbed by Bob and Eve, respectively. Based on the results, we then derive the average symbol error rate (SER) as well as the mutual information of Alice-Bob and Alice-Eve, and further apply the Shannon theory to determine the secrecy capacity of Alice-Bob transmission. We also develop the closed-form results for the optimal detection threshold at Bob to achieve the secrecy capacity, and thus devise a complete algorithm for secrecy capacity maximization. Finally, we provide numerical results to illustrate the secrecy performance in the concerned system.

Nucleic acid-based logic gates have shown great potential in biotechnology, medicine as well as diagnostics. Herein, we have constructed pH-responsive logic devices by utilizing HIV-1 TAR hairpins in combination with a thiazole peptide that exhibits turn-on fluorescence upon interacting with TAR RNA or DNA. Based on this, INHIBIT-AND and YES-INHIBIT-AND logic gates were constructed in parallel. The pH alteration leads to conformational changes of the hairpin structure, enabling the construction of a multi-reset reusable logic system which could be developed for in vitro sensing of the HIV-1 viral RNA.

Background: Differentiating between different states in nucleic acid circuits is crucial for various biological applications. One approach, there is a requirement for complicated sequential summation, which can be excessive for practical purposes. By selectively labeling biologically significant states, this study tackles the issue and presents a more cost-effective and streamlined solution. The challenge is to efficiently distinguish between different states in a nucleic acid circuit., Results: An innovative method is introduced in this study to distinguish between states in a nucleic acid circuit, emphasizing the biologically relevant ones. The circuit comprises four DNA logic gates and two detection modules, one for determining fetal gender and the other for diagnosing X-linked genetic disorders. The primary module generates a G-quadruplex DNAzyme when activated by specific biomarkers, which leads to a distinct colorimetric signal. The secondary module responds to hemophilia and choroideremia biomarkers, generating one or two DNAzymes. The absence of female fetus indicators results in no DNAzyme or color change. The circuit can differentiate various fetal states by producing one to four active DNAzymes in response to male fetus biomarkers. A single-color solution for state differentiation is provided by this approach, which promises significant advancements in DNA computing and diagnostic applications., Significance: The innovative approach used in this study to distinguish states in nucleic acid circuits holds great significance. By selectively labeling biologically relevant states, circuit design is simplified and complexity is reduced. This advancement enables cost-effective and efficient diagnostic applications and contributes to DNA computing, providing a valuable solution to a fundamental problem., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Efficient and accurate acquisition of cellular biomolecular information is crucial for exploring cell fate, achieving early diagnosis, and the effective treatment of various diseases. However, current DNA biosensors are mostly limited to single-target detection, with few complex logic circuits for comprehensive analysis of three or more targets. Herein, we designed a sea anemone-like DNA nanomachine based on DNA strand displacement composed of three logic gates (YES-AND-YES) and delivered into the cells using gold nano bipyramid carriers. The AND gate activation depends on the trigger chain released by upstream DNA strand displacement reactions, while the output signal relies on the downstream DNAzyme structure. Under the influence of diverse inputs (including enzymes, miRNA, and metal ions), the interconnected logic gates simultaneously perform logical analysis on multiple targets, generating a unique output signal in the YES/NO format. This sensor can successfully distinguish healthy cells from tumor cells and can be further used for the diagnosis of different tumor cells, providing a promising platform for accurate cell-type identification.

Advancements in DNA computation have unlocked molecular-scale information processing possibilities, utilizing the intrinsic properties of DNA for complex logical operations with transformative applications in biomedicine. DNA computation shows promise in molecular diagnostics, enabling precise and sensitive detection of genetic mutations and disease biomarkers. Moreover, it holds potential for targeted gene regulation, facilitating personalized therapeutic interventions with enhanced efficacy and reduced side effects. Herein, we have developed six DNAzyme-based logic gates able to process YES, AND, and NOT Boolean logic. The novelty of this work lies in their additional functionalization with a common DNA scaffold for increased cooperativity in input recognition. Moreover, we explored hierarchical input binding to multi-input logic gates, which helped gate optimization. Additionally, we developed a new design of an allosteric hairpin switch used to implement NOT logic. All DNA logic gates achieved the desired true-to-false output signal when detecting a panel of miRNAs, known for their important role in malignancy regulation. This is the first example of DNAzyme-based logic gates having all input-recognizing elements integrated in a single DNA nanostructure, which provides new opportunities for building DNA automatons for diagnosis and therapy of human diseases.

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., (© 2024. Springer Nature Limited.)

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.

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.

Living organisms switch their intrinsic biological states to survive environmental turbulence, in which temperature changes are prevalent in nature. Most artificial temperature-responsive DNA nanosystems work as switch modules that transit between "ON-OFF" states, making it difficult to construct nanosystems with diverse functions. In this study, we present a general strategy to build multimode nanosystems based on a temperature-responsive DNA strand displacement reaction. The temperature-responsive DNA strand displacement was controlled by tuning the sequence of the substrate hairpin strands and the invading strands. The nanosystems were demonstrated as logic gates that performed a set of Boolean logical functions at specific temperatures. In addition, an adaptive logic gate was fabricated that could exhibit different logic functions when placed in different temperatures. Specifically, upon the same input strands, the logic gate worked as an XOR gate at 10 °C, an OR gate at 35 °C, an AND gate at 46 °C, and was reset at 55 °C. The design and fabrication of the multifunctional nanosystems would help construct advanced temperature-responsive systems that may be used for temperature-controlled multi-stage drug delivery and thermally-controlled multi-step assembly of nanostructures.

DNA-based molecular computing has evolved to encompass a diverse range of functions, demonstrating substantial promise for both highly parallel computing and various biomedical applications. Recent advances in DNA computing systems based on surface reactions have demonstrated improved levels of specificity and computational speed compared to their solution-based counterparts that depend on three-dimensional molecular collisions. Herein, computational biomolecular interactions confined by various surfaces such as DNA origamis, nanoparticles, lipid membranes and chips are systematically reviewed, along with their manipulation methodologies. Monitoring techniques and applications for these surface-based computing systems are also described. The advantages and challenges of surface-confined DNA computing are discussed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Molecular Communications (MC) is a bio-inspired communication technique that uses molecules to encode and transfer information. Many efforts have been devoted to developing novel modulation techniques for MC based on various distinguishable characteristics of molecules, such as their concentrations or types. In this paper, we investigate a particular modulation scheme called Ratio Shift Keying (RSK), where the information is encoded in the concentration ratio of two different types of molecules. RSK modulation is hypothesized to enable accurate information transfer in dynamic MC scenarios where the time-varying channel characteristics affect both types of molecules equally. To validate this hypothesis, we first conduct an information-theoretical analysis of RSK modulation and derive the capacity of the end-to-end MC channel where the receiver estimates concentration ratio based on ligand-receptor binding statistics in an optimal or suboptimal manner. We then analyze the error performance of RSK modulation in a practical time-varying MC scenario, that is mobile MC, in which both the transmitter and the receiver undergo diffusion-based propagation. Our numerical and analytical results, obtained for varying levels of similarity between the ligand types used for ratio-encoding, and varying number of receptors, show that RSK can significantly outperform the most commonly considered MC modulation technique, concentration shift keying (CSK), in dynamic MC scenarios.