A novel bio-sensor based on DNA strand displacement

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.

Spiking image processing unit based on neural analog of Boolean logic operations

McCulloch and Pitts hypothesized in 1943 that the brain is entirely composed of logic gates, akin to current computers' IP cores, which led to several neural analogs of Boolean logic. The current study proposes a spiking image processing unit (SIPU) based on spiking frequency gates and coordinate logic operations, as a dynamical model of synapses and spiking neurons. SIPU can imitate DSP functions like edge recognition, picture magnification, noise reduction, etc. but can be extended to cater for more advanced computing tasks. The proposed spiking Boolean logic platform can be used to develop advanced applications without relying on learning or specialized datasets. It could aid in gaining a deeper understanding of complex brain functions and spur new forms of neural analogs.

DNA Strand Displacement with Base Pair Stabilizers: Purine-2,6-Diamine and 8-Aza-7-Bromo-7-Deazapurine-2,6-Diamine Oligonucleotides Invade Canonical DNA and New Fluorescent Pyrene Click Sensors Monitor the Reaction

Purine-2,6-diamine and 8-aza-7-deaza-7-bromopurine-2,6-diamine 2'-deoxyribonucleosides (1 and 2) were implemented in isothermal DNA strand displacement reactions. Nucleoside 1 is a weak stabilizer of dA-dT base pairs, nucleoside 2 evokes strong stabilization. Strand displacement reactions used single-stranded invaders with single and multiple incorporations of stabilizers. Displacement is driven by negative enthalpy changes between target and displaced duplex. Toeholds are not required. Two new environmental sensitive fluorescent pyrene sensors were developed to monitor the progress of displacement reactions. Pyrene was connected to the nucleobase in the invader or to a dendritic linker in the output strand. Both new sensors were constructed by click chemistry; phosphoramidites and oligonucleotides were prepared. Sensors show monomer or excimer emission. Fluorescence intensity changes when the displacement reaction progresses. Our work demonstrates that strand displacement with base pair stabilizers is applicable to DNA, RNA and to related biopolymers with applications in chemical biology, nanotechnology and medicinal diagnostics.

Anomeric DNA Strand Displacement with α-D Oligonucleotides as Invaders and Ethidium Bromide as Fluorescence Sensor for Duplexes with α/β-, β/β- and α/α-D Configuration

DNA strand displacement is a technique to exchange one strand of a double stranded DNA by another strand (invader). It is an isothermal, enzyme free method driven by single stranded overhangs (toeholds) and is employed in DNA amplification, mismatch detection and nanotechnology. We discovered that anomeric (α/β) DNA can be used for heterochiral strand displacement. Homochiral DNA in β-D configuration was transformed to heterochiral DNA in α-D/β-D configuration and further to homochiral DNA with both strands in α-D configuration. Single stranded α-D DNA acts as invader. Herein, new anomeric displacement systems with and without toeholds were designed. Due to their resistance against enzymatic degradation, the systems are applicable to living cells. The light-up intercalator ethidium bromide is used as fluorescence sensor to follow the progress of displacement. Anomeric DNA displacement shows benefits over canonical DNA in view of toehold free displacement and simple detection by ethidium bromide.

DNA Transformations for Diagnosis and Therapy

Due to its unique physical and chemical characteristics, DNA, which is known only as genetic information, has been identified and utilized as a new material at an astonishing rate. The role of DNA has increased dramatically with the advent of various DNA derivatives such as DNA-RNA, DNA-metal hybrids, and PNA, which can be organized into 2D or 3D structures by exploiting their complementary recognition. Due to its intrinsic biocompatibility, self-assembly, tunable immunogenicity, structural programmability, long stability, and electron-rich nature, DNA has generated major interest in electronic and catalytic applications. Based on its advantages, DNA and its derivatives are utilized in several fields where the traditional methodologies are ineffective. Here, the present challenges and opportunities of DNA transformations are demonstrated, especially in biomedical applications that include diagnosis and therapy. Natural DNAs previously utilized and transformed into patterns are not found in nature due to lack of multiplexing, resulting in low sensitivity and high error frequency in multi-targeted therapeutics. More recently, new platforms have advanced the diagnostic ability and therapeutic efficacy of DNA in biomedicine. There is confidence that DNA will play a strong role in next-generation clinical technology and can be used in multifaceted applications.

Repositioning Drugs to the Mitochondrial Fusion Protein 2 by Three-Tunnel Deep Neural Network for Alzheimer's Disease

Alzheimer's disease (AD) is a common neurodegenerative dementia in the elderly. Although there is no effective drug to treat AD, proteins associated with AD have been discovered in related studies. One of the proteins is mitochondrial fusion protein 2 (Mfn2), and its regulation presumably be related to AD. However, there is no specific drug for Mfn2 regulation. In this study, a three-tunnel deep neural network (3-Tunnel DNN) model is constructed and trained on the extended Davis dataset. In the prediction of drug-target binding affinity values, the accuracy of the model is up to 88.82% and the loss value is 0.172. By ranking the binding affinity values of 1,063 approved drugs and small molecular compounds in the DrugBank database, the top 15 drug molecules are recommended by the 3-Tunnel DNN model. After removing molecular weight <200 and topical drugs, a total of 11 drug molecules are selected for literature mining. The results show that six drugs have effect on AD, which are reported in references. Meanwhile, molecular docking experiments are implemented on the 11 drugs. The results show that all of the 11 drug molecules could dock with Mfn2 successfully, and 5 of them have great binding effect.

A Programming 20-30nm Rectangular DNA Origami for Loading Doxorubicin to Penetrate Ovarian Cancer Cells

In DNA nanotechnology, the aim in folding DNA origami is to find a good piece of rectangular DNA origami with desired sizes, which could be larger or smaller for different application purposes. In recent three years, the technique of folding smaller ones is paid heavily attentions. In this work, we design a programming rectangular DNA origami in size 20*30nm with M13p18, which is smallest and cheapest to the best acknowledge of the authors. Since it is not hard to prepare with 30 staple strands and short annealing time, the cost of folding our designed rectangular DNA origami is less than 100 dollars. Although the large origami give more space, the smaller ones are cheaper and has the potential applications in penetrating cancer cells. It is obtained by cell penetrating experiments that our designed rectangular DNA origami can penetrate ovarian cancer cells efficiently even loading doxorubicin, but the thermodynamic stability needs further improved. Our designed programming 20 30nm triangular DNA origami shows potential applications in precision control of nanoscale particles and anti-tumor drug delivery in vivo.

A Multifunctional Molecular Probe for Detecting Hg2+ and Ag⁺ Based on Ion-Mediated Base Mismatch

In this paper, a multifunctional biosensing platform for sensitively detecting Hg²⁺ and Ag⁺, based on ion-mediated base mismatch, fluorescent labeling, and strand displacement, is introduced. The sensor can also be used as an OR logic gate, the multifunctional design of sensors is realized. Firstly, orthogonal experiments with three factors and three levels were carried out on the designed sensor, and preliminary optimization of conditions was performed for subsequent experiments. Next, the designed sensor was tested the specificity and target selectivity under the optimized conditions, and the application to actual environmental samples further verified the feasibility. Generally, this is a convenient, fast, stable, and low-cost method that provides a variety of ideas and an experimental basis for subsequent research.

A novel method for multifactorial bio-chemical experiments design based on combinational design theory

Experimental design focuses on describing or explaining the multifactorial interactions that are hypothesized to reflect the variation. The design introduces conditions that may directly affect the variation, where particular conditions are purposely selected for observation. Combinatorial design theory deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. In this work, borrowing the concept of "balance" in combinatorial design theory, a novel method for multifactorial bio-chemical experiments design is proposed, where balanced templates in combinational design are used to select the conditions for observation. Balanced experimental data that covers all the influencing factors of experiments can be obtianed for further processing, such as training set for machine learning models. Finally, a software based on the proposed method is developed for designing experiments with covering influencing factors a certain number of times.

Reversible Data Hiding Based on DNA Computing

Biocomputing, especially DNA, computing has got great development. It is widely used in information security. In this paper, a novel algorithm of reversible data hiding based on DNA computing is proposed. Inspired by the algorithm of histogram modification, which is a classical algorithm for reversible data hiding, we combine it with DNA computing to realize this algorithm based on biological technology. Compared with previous results, our experimental results have significantly improved the ER (Embedding Rate). Furthermore, some PSNR (peak signal-to-noise ratios) of test images are also improved. Experimental results show that it is suitable for protecting the copyright of cover image in DNA-based information security.

Construction of DNA nanotubes with controllable diameters and patterns using hierarchical DNA sub-tiles

The design of DNA nanotubes is a promising and hot research branch in structural DNA nanotechnology, which is rapidly developing as a versatile method for achieving subtle nanometer scale materials and molecular diagnostic/curative devices. Multifarious methods have been proposed to achieve varied DNA nanotubes, such as using square tiles and single-stranded tiles, but it is still a challenge to develop a bottom-up assembly way to build DNA nanotubes with different diameters and patterns using certain universal DNA nanostructures. This work addresses the challenge by assembling three types of spatial DNA nanotubes with different diameters and patterns from the so-called "basic bricks", i.e., hierarchical DNA sub-tiles. A high processing rate and throughput synthesis of DNA nanotubes are observed and analyzed by atomic force microscopy. Experimental observations and data analysis suggests the stability and controllability of DNA nanotubes assembled by hierarchical DNA sub-tiles.

On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses

Spiking neural P systems with rules on synapses are a new variant of spiking neural P systems. In the systems, the neuron contains only spikes, while the spiking/forgetting rules are moved on the synapses. It was obtained that such system with 30 neurons (using extended spiking rules) or with 39 neurons (using standard spiking rules) is Turing universal. In this work, this number is improved to 6. Specifically, we construct a Turing universal spiking neural P system with rules on synapses having 6 neurons, which can generate any set of Turing computable natural numbers. As well, it is obtained that spiking neural P system with rules on synapses having less than two neurons are not Turing universal: i) such systems having one neuron can characterize the family of finite sets of natural numbers; ii) the family of sets of numbers generated by the systems having two neurons is included in the family of semi-linear sets of natural numbers.

A Novel Computational Method to Reduce Leaky Reaction in DNA Strand Displacement

DNA strand displacement technique is widely used in DNA programming, DNA biosensors, and gene analysis. In DNA strand displacement, leaky reactions can cause DNA signals decay and detecting DNA signals fails. The mostly used method to avoid leakage is cleaning up after upstream leaky reactions, and it remains a challenge to develop reliable DNA strand displacement technique with low leakage. In this work, we address the challenge by experimentally evaluating the basic factors, including reaction time, ratio of reactants, and ion concentration to the leakage in DNA strand displacement. Specifically, fluorescent probes and a hairpin structure reporting DNA strand are designed to detect the output of DNA strand displacement, and thus can evaluate the leakage of DNA strand displacement reactions with different reaction time, ratios of reactants, and ion concentrations. From the obtained data, mathematical models for evaluating leakage are achieved by curve derivation. As a result, it is obtained that long time incubation, high concentration of fuel strand, and inappropriate amount of ion concentration can weaken leaky reactions. This contributes to a method to set proper reaction conditions to reduce leakage in DNA strand displacement.