Intelligent Cell Profiling and Precision Release: Multimolecular Marker-Activated Transmembrane DNA Computing Nanosystem.

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 (MTDAND-AND) demonstrates exceptional specificity, allowing targeted release of drug-DNA specifically in MCF-7 cells. Furthermore, the transformed OR-AND logic-gated system (MTDOR-AND) exhibits broader adaptability, facilitating the release of drug-DNA in three positive cancer cell lines (MCF-7, HeLa, and HepG2). Importantly, MTDAND-AND and MTDOR-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.

Stability Analysis for Large-Scale Multi-Agent Molecular Communication Systems.

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.

Exploring the Potential of DNA Computing for Complex Big Data Problems: A Case Study on the Traveling Car Renter Problem.

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(n2m) 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.

On the Target Detection Performance of a Molecular Communication Network With Multiple Mobile Nanomachines.

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.

Tri-state logic computation by activating DNA origami chains.

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.

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.

DNA Molecular Computation Using the CRISPR-Mediated Reaction and Surface Growth of Gold Nanoparticles.

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.

A spatially localized DNA linear classifier for cancer diagnosis.

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.

A novel activation function based on DNA enzyme-free hybridization reaction and its implementation on nonlinear molecular learning systems.

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.

Arbitrary Digital DNA Computing: A Programmable Molecular Perceptron Driven by Lambda Exonuclease for Lighting up Concatenated Circuits.

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.

An enzymatically activated AND-gate DNA logic circuit for tumor cells recognition via multi-microRNAs detection.

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.

Performance Analysis and ISI Mitigation With Imperfect Transmitter in Molecular Communication.

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.

Design of DNA Storage Coding Scheme With LDPC Codes and Interleaving.

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.

pH-dependent complex formation with TAR RNA and DNA: application towards logic gates.

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.

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

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

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.

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.

Sea Anemone-like Nanomachine Based on DNA Strand Displacement Composed of Three Boolean Logic Gates: Diversified Input for Intracellular Multitarget Detection.

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.

Towards the development of a DNA automaton: modular RNA-cleaving deoxyribozyme logic gates regulated by miRNAs.

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.

An approach for state differentiation in nucleic acid circuits: Application to diagnostic DNA computing.

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.