Parallel molecular computation on digital data stored in DNA.

DNA is an incredibly dense storage medium for digital data. However, computing on the stored information is expensive and slow, requiring rounds of sequencing, in silico computation, and DNA synthesis. Prior work on accessing and modifying data using DNA hybridization or enzymatic reactions had limited computation capabilities. Inspired by the computational power of "DNA strand displacement," we augment DNA storage with "in-memory" molecular computation using strand displacement reactions to algorithmically modify data in a parallel manner. We show programs for binary counting and Turing universal cellular automaton Rule 110, the latter of which is, in principle, capable of implementing any computer algorithm. Information is stored in the nicks of DNA, and a secondary sequence-level encoding allows high-throughput sequencing-based readout. We conducted multiple rounds of computation on 4-bit data registers, as well as random access of data (selective access and erasure). We demonstrate that large strand displacement cascades with 244 distinct strand exchanges (sequential and in parallel) can use naturally occurring DNA sequence from M13 bacteriophage without stringent sequence design, which has the potential to improve the scale of computation and decrease cost. Our work merges DNA storage and DNA computing, setting the foundation of entirely molecular algorithms for parallel manipulation of digital information preserved in DNA.

DNA Logical Computing on a Transistor for Cancer Molecular Diagnosis.

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.

Image Encryption Using a Spectrally Efficient Halton Logistics Tent (HaLT) Map and DNA Encoding for Secured Image Communication.

With the advancement of technology worldwide, security is essential for online information and data. This research work proposes a novel image encryption method based on combined chaotic maps, Halton sequence, five-dimension (5D) Hyper-Chaotic System and Deoxyribonucleic Acid (DNA) encoding. Halton sequence is a known low-discrepancy sequence having uniform distribution in space for application in numerical methods. In the proposed work, we derived a new chaotic map (HaLT map) by combining chaotic maps and Halton sequence to scramble images for cryptography applications. First level scrambling was done by using the HaLT map along with a modified quantization unit. In addition, the scrambled image underwent inter- and intra-bit scrambling for enhanced security. Hash values of the original and scrambled image were used for initial conditions to generate a 5D hyper-chaotic map. Since a 5D chaotic map has complex dynamic behavior, it could be used to generate random sequences for image diffusion. Further, DNA level permutation and pixel diffusion was applied. Seven DNA operators, i.e., ADD, SUB, MUL, XOR, XNOR, Right-Shift and Left-Shift, were used for pixel diffusion. The simulation results showed that the proposed image encryption method was fast and provided better encryption compared to 'state of the art' techniques. Furthermore, it resisted various attacks.

Environment-Recognizing DNA-Computation Circuits for the Intracellular Transport of Molecular Payloads for mRNA Imaging.

Programming intelligent DNA nanocarriers for the targeted transport of molecular payloads in living cells has attracted extensive attention. In vivo activation of these nanocarriers usually relies on external light irradiation. An interest is emerging in the automatic recognition of intracellular surroundings by nanocarriers and their in situ activation under the control of programmed DNA-computation circuits. Herein, we report the integration of DNA circuits with framework nucleic acid (FNA) nanocarriers that consist of a truncated square pyramid (TSP) cage and a built-in duplex cargo containing an antisense strand of the target mRNA. An i-motif and ATP aptamer embedded in the TSP are employed as logic-controlling units to respond to H+ and ATP inside cellular compartments, triggering the release of the sensing element for fluorescent mRNA imaging. Logic-controlled FNA devices could be used to target drug delivery, enabling precise disease treatment.

Self-Assembling Molecular Logic Gates Based on DNA Crossover Tiles.

DNA-based computational hardware has attracted ever-growing attention due to its potential to be useful in the analysis of complex mixtures of biological markers. Here we report the design of self-assembling logic gates that recognize DNA inputs and assemble into crossover tiles when the output signal is high; the crossover structures disassemble to form separate DNA stands when the output is low. The output signal can be conveniently detected by fluorescence using a molecular beacon probe as a reporter. AND, NOT, and OR logic gates were designed. We demonstrate that the gates can connect to each other to produce other logic functions.

Nucleic acid based logical systems.

Researchers increasingly visualize a significant role for artificial biochemical logical systems in biological engineering, much like digital logic circuits in electrical engineering. Those logical systems could be utilized as a type of servomechanism to control nanodevices in vitro, monitor chemical reactions in situ, or regulate gene expression in vivo. Nucleic acids (NA), as carriers of genetic information with well-regulated and predictable structures, are promising materials for the design and engineering of biochemical circuits. A number of logical devices based on nucleic acids (NA) have been designed to handle various processes for technological or biotechnological purposes. This article focuses on the most recent and important developments in NA-based logical devices and their evolution from in vitro, through cellular, even towards in vivo biological applications.

Unlocking Genetic Profiles with a Programmable DNA-Powered Decoding Circuit.

Human genetic architecture provides remarkable insights into disease risk prediction and personalized medication. Advances in genomics have boosted the fine-mapping of disease-associated genetic variants across human genome. In healthcare practice, interpreting intricate genetic profiles into actionable medical decisions can improve health outcomes but remains challenging. Here an intelligent genetic decoder is engineered with programmable DNA computation to automate clinical analyses and interpretations. The DNA-based decoder recognizes multiplex genetic information by one-pot ligase-dependent reactions and interprets implicit genetic profiles into explicit decision reports. It is shown that the DNA decoder implements intended computation on genetic profiles and outputs a corresponding answer within hours. Effectiveness in 30 human genomic samples is validated and it is shown that it achieves desirable performance on the interpretation of CYP2C19 genetic profiles into drug responses, with accuracy equivalent to that of Sanger sequencing. Circuit modules of the DNA decoder can also be readily reprogrammed to interpret another pharmacogenetics genes, provide drug dosing recommendations, and implement reliable molecular calculation of polygenic risk score (PRS) and PRS-informed cancer risk assessment. The DNA-powered intelligent decoder provides a general solution to the translation of complex genetic profiles into actionable healthcare decisions and will facilitate personalized healthcare in primary care.

Microfluidic Enrichment of Intact SARS-CoV-2 Viral Particles by Stoichiometric Balanced DNA Computation.

Health diagnostic tools for community safety and environmental monitoring require selective and quantitatively accurate active viral load assessment. Herein, we report a microfluidic enrichment strategy to separate intact SARS-CoV-2 particles by AND logic gate with inputs of cholesterol oligonucleotides for the envelope and aptamers for the spike viral proteins. Considering the unequal quantity of endogenous spikes and lipid membranes on SARS-CoV-2, a dual-domain binding strategy, with two aptamers targeting different spike domains, was applied to balance the spike-envelope stoichiometric ratio. By balancing the stoichiometric with DNA computation and promoting microscale mass transfer of the herringbone chip, the developed strategy enabled high sensitivity detection of pseudotyped SARS-CoV-2 with a limit of detection as low as 37 active virions/µL while distinguishing it from inactive counterparts, other nontarget viruses, and free spike protein. Moreover, the captured viral particles can be released through DNase I treatment with up to 90% efficiency, which is fully compatible with virus culture and sequencing. Overall, the developed strategy not only identified SARS-CoV-2-infected patients (n = 14) with 100% identification from healthy donors (n = 8) but also provided a fresh perspective on the regulation of stoichiometric ratio to achieve a more biologically relevant DNA computation.

DNA Computing: NOT Logic Gates See the Light.

DNA-based Boolean logic gates (for example, AND, OR, and NOT) can be assembled into complex computational circuits that generate an output signal in response to specific patterns of oligonucleotide inputs. However, the fundamental nature of NOT gates, which convert the absence of an input into an output, makes their implementation within DNA-based circuits difficult. Premature execution of a NOT gate before completion of its upstream computation introduces an irreversible error into the circuit. By utilizing photocaging groups, we developed a novel DNA gate design that prevents gate function until irradiation at a certain time point. Optical activation provides temporal control over circuit performance by preventing premature computation and is orthogonal to all other components of DNA computation devices. Using this approach, we designed NAND and NOR logic gates that respond to synthetic microRNA sequences. We further demonstrate the utility of the NOT gate within multilayer circuits in response to a specific pattern of four microRNAs.

Enzyme-Regulated DNA-Based Logic Device.

Herein, we report a carbazole (Cz) ligand that displays distinct turn-on fluorescence signals upon interaction with human telomeric G-quadruplex ( h-TELO) and nuclease enzymes. Interestingly, Cz selectively binds and stabilizes the mixed hybrid topology of h-TELO G-quadruplex that withstands digestion by exonucleases and nuclease S1. The distinct fluorescence signatures of Cz-stabilized h-TELO with nucleases are used to design conceptually novel DNA devices for selectively detecting the enzymatic activity of DNase I as well as performing logic operations. An INHIBIT logic gate is constructed using h-TELO and DNase I as the inputs while the inputs of h-TELO and nuclease S1 form a YES logic gate. Furthermore, a two-input two-output reusable logic device with "multireset" function is developed by using h-TELO and DNase I as inputs. On the basis of this platform, combinatorial logic systems (INHIBIT-INHIBIT and NOR-OR) have been successfully installed using different combinations of nucleases as inputs. Moreover, this new strategy of using a synthetic dual emissive probe and enzyme/DNA inputs for constructing reusable logic device may find important applications in biological computing and information processing.

DNA-Based Analog Computing.

The field of DNA computation makes use of DNA reactions to do molecular-scale computation. Most works in DNA computation execute digital computations such as evaluation of Boolean circuits. This chapter surveys novel DNA computation methods that execute analog computations, where the inputs and outputs are real values specified by the concentrations of particular DNA strands.

The Formal Language and Design Principles of Autonomous DNA Walker Circuits.

Simple computation can be performed using the interactions between single-stranded molecules of DNA. These interactions are typically toehold-mediated strand displacement reactions in a well-mixed solution. We demonstrate that a DNA circuit with tethered reactants is a distributed system and show how it can be described as a stochastic Petri net. The system can be verified by mapping the Petri net onto a continuous-time Markov chain, which can also be used to find an optimal design for the circuit. This theoretical machinery can be applied to create software that automatically designs a DNA circuit, linking an abstract propositional formula to a physical DNA computation system that is capable of evaluating it. We conclude by introducing example mechanisms that can implement such circuits experimentally and discuss their individual strengths and weaknesses.

Optically Controlled Signal Amplification for DNA Computation.

The hybridization chain reaction (HCR) and fuel-catalyst cycles have been applied to address the problem of signal amplification in DNA-based computation circuits. While they function efficiently, these signal amplifiers cannot be switched ON or OFF quickly and noninvasively. To overcome these limitations, a light-activated initiator strand for the HCR, which enabled fast optical OFF → ON switching, was developed. Similarly, when a light-activated version of the catalyst strand or the inhibitor strand of a fuel-catalyst cycle was applied, the cycle could be optically switched from OFF → ON or ON → OFF, respectively. To move the capabilities of these devices beyond solution-based operations, the components were embedded in agarose gels. Irradiation with customizable light patterns and at different time points demonstrated both spatial and temporal control. The addition of a translator gate enabled a spatially activated signal to travel along a predefined path, akin to a chemical wire. Overall, the addition of small light-cleavable photocaging groups to DNA signal amplification circuits enabled conditional control as well as fast photocontrol of signal amplification.

A parallel algorithm for solving the n-queens problem based on inspired computational model.

DNA computing provides a promising method to solve the computationally intractable problems. The n-queens problem is a well-known NP-hard problem, which arranges n queens on an n × n board in different rows, columns and diagonals in order to avoid queens attack each other. In this paper, we present a novel parallel DNA algorithm for solving the n-queens problem using DNA molecular operations based on a biologically inspired computational model. For the n-queens problem, we reasonably design flexible length DNA strands representing elements of the allocation matrix, take appropriate biologic manipulations and get the solutions of the n-queens problem in proper length and O(n(2)) time complexity. We extend the application of DNA molecular operations, simultaneity simplify the complexity of the computation and simulate to verify the feasibility of the DNA algorithm.

A new fast algorithm for solving the minimum spanning tree problem based on DNA molecules computation.

The minimum spanning tree (MST) problem is to find minimum edge connected subsets containing all the vertex of a given undirected graph. It is a vitally important NP-complete problem in graph theory and applied mathematics, having numerous real life applications. Moreover in previous studies, DNA molecular operations usually were used to solve NP-complete head-to-tail path search problems, rarely for NP-hard problems with multi-lateral path solutions result, such as the minimum spanning tree problem. In this paper, we present a new fast DNA algorithm for solving the MST problem using DNA molecular operations. For an undirected graph with n vertex and m edges, we reasonably design flexible length DNA strands representing the vertex and edges, take appropriate steps and get the solutions of the MST problem in proper length range and O(3m+n) time complexity. We extend the application of DNA molecular operations and simultaneity simplify the complexity of the computation. Results of computer simulative experiments show that the proposed method updates some of the best known values with very short time and that the proposed method provides a better performance with solution accuracy over existing algorithms.