Using Strand Displacing Polymerase To Program Chemical Reaction Networks

Rewireable Building Blocks for Enzyme-Powered DNA Computing Networks

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.

Programmable Primer Switching for Regulating Enzymatic DNA Circuits

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.

Self-Assembly of Designed Peptides with DNA to Accelerate the DNA Strand Displacement Process for Dynamic Regulation of DNAzymes

Toehold-mediated DNA strand displacement (TMSD) is a powerful tool for controlling DNA-based molecular reactions and devices. However, the slow kinetics of TMSD reactions often limit their efficiency and practical applications. Inspired by the chemical structures of natural DNA-operating enzymes (e.g., helicase), we designed lysine-rich peptides to self-assemble with DNA-based systems. Our approach allows for accelerating the TMSD reactions, even during multiple displacement events, enhancing their overall efficiency and utility. We found that the acceleration is dependent on the peptide's sequence, length, and concentration as well as the length of the DNA toehold domain. Molecular dynamics simulations revealed that the peptides promote toehold binding between the double-stranded target and the single-stranded invader, thereby facilitating strand displacement. Furthermore, we integrated our approach into a horseradish peroxidase-mimicking DNAzyme, enabling the dynamic modulation of enzymatic functions on and off. We anticipate that the established acceleration of strand displacement reactions and the modulation of enzymatic activities offer enhanced functionality and control in the design of programmable DNA-based nanodevices.

Implementation of an Ultrasensitive Biomolecular Controller for Enzymatic Reaction Processes With Delay Using DNA Strand Displacement

In this article, a set of abstract chemical reactions has been employed to construct a novel nonlinear biomolecular controller, i.e, the Brink controller (BC) with direct positive autoregulation (DPAR) (namely BC-DPAR controller). In comparison to dual rail representation-based controllers such as the quasi sliding mode (QSM) controller, the BC-DPAR controller directly reduces the number of CRNs required for realizing an ultrasensitive input-output response because it does not involve the subtraction module, reducing the complexity of DNA implementations. Then, the action mechanism and steady-state condition constraints of two nonlinear controllers, BC-DPAR controller and QSM controller, are investigated further. Considering the mapping relationship between CRNs and DNA implementation, a CRNs-based enzymatic reaction process with delay is constructed, and a DNA strand displacement (DSD) scheme representing time delay is proposed. The BC-DPAR controller, when compared to the QSM controller, can reduce the number of abstract chemical reactions and DSD reactions required by 33.3% and 31.8%, respectively. Finally, an enzymatic reaction scheme with BC-DPAR controller is designed using DSD reactions. According to the findings, the enzymatic reaction process's output substance can approach the target level at a quasi-steady state in both delay-free and non-zero delay conditions, but the target level can only be achieved during a finite-time period, mainly due to the fuel stand depletion.

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

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

3D DNA Walker-Assisted CRISPR/Cas12a Trans-Cleavage for Ultrasensitive Electrochemiluminescence Detection of miRNA-141

In this study, a CRISPR/Cas12a (LbCpf1)-mediated electrochemiluminescence (ECL) paper-based platform on the basis of a three-dimensional (3D) DNA walker was proposed for the ultrasensitive detection of miRNA-141. Initially, 3D-rGO with a tremendous loading space was modified on the paper working electrode (PWE) to construct an excellent conductive substrate and facilitate the growth of AuPd nanoparticles (NPs). Afterward, the AuPd NPs were introduced as the coreaction emitter medium of the 3D-rGO/PWE to provide convenience for the transformation between S₂O₈^2- and SO₄^2-, amplifying the ECL emission of g-C₃N₄ nanosheets (NSs). Meanwhile, with the help of Nt.BsmAI nicking endonuclease, a 3D DNA walker signal amplifier was designed to convert and magnify the target miRNA-141 into a particular trigger sequence, which could act as activator DNA to motivate the trans-acting deoxyribonuclease activity of CRISPR/Cas12a to further achieve efficient annihilation of the ECL signal. Furthermore, the proposed multimechanism-driven biosensor exhibited excellent sensitivity and specificity, with a relatively low detection limit at 0.331 fM (S/N = 3) in the concentration range between 1 fM and 10 nM. Consequently, the designed strategy not only extended the application scope of CRISPR/Cas12a but also devoted a new approach for the clinical diagnosis of modern medicine.

Solving 0-1 Integer Programming Problem Based on DNA Strand Displacement Reaction Network

Chemical reaction networks (CRNs) based on DNA strand displacement (DSD) can be used as an effective programming language for solving various mathematical problems. In this paper, we design three chemical reaction modules by using the DNA strand displacement reaction as the basic principle, with a weighted reaction module, sum reaction module, and threshold reaction module. These modules are used as basic elements to form chemical reaction networks that can be used to solve 0-1 integer programming problems. The problem can be solved through the three steps of weighting, sum, and threshold, and then the results of the operations can be expressed through a single-stranded DNA output with fluorescent molecules. Finally, we use biochemical experiments and Visual DSD simulation software to verify and evaluate the chemical reaction networks. The results have shown that the DSD-based chemical reaction networks constructed in this paper have good feasibility and stability.

DNA strand displacement reactions to accomplish a two-degree-of-freedom PID controller and its application in subtraction gate

Synthesis control circuits can be used to effectively control biochemical molecule processes. In the controller design based on chemical reaction networks (CRNs), generally only the tracking set-point is considered. However, the influence of disturbances, which are frequently encountered in biochemical systems, is often neglected, thus weakening the control effect of the system. In this article, tracking set-point input and suppressing disturbance input are considered in the control effect. Firstly, CRNs are adopted to construct a two-degree-of-freedom PID controller by combining a one-degree-of-freedom PID controller with a feedforward controller for the first time. Then, CRN expressions of the two input functions (step function and ramp function) used as input signals are defined. Furthermore, the two-degree-of-freedom PID controller is founded by DNA strand displacement (DSD) reaction networks, because DNA is an ideal engineering material to constitute molecular devices based on CRNs. The overshoot of the two-degree-of-freedom PID control system is significantly reduced compared to the one-degree-of-freedom PID control system. Finally, a leak reaction is treated as an extraneous disturbance input to a subtraction gate. The influence of external disturbance is solved by the two-degree-of-freedom PID controller. It is worth noting that the two-degree-of-freedom subtraction gate control system better restrains the impact of a disturbance input (leak reaction).

Dictated Emergence of Nucleic Acid-Based Constitutional Dynamic Networks by DNA Replication Machineries

The emergence of nucleic acid-based constitutional dynamic networks, CDNs, from a pool of nucleic acids is a key process for the understanding and modality of the evolution of biological networks. We present a versatile method that applies a library of nucleic acids coupled to biocatalytic DNA machineries as functional modules for the emergence of CDNs of diverse composition, complexity, and structural diversity. A set of four DNA template/blocker scaffolds coupled to the polymerase/dNTP replication machinery leads, in the presence of a primer, P₁, to the gated replication of the scaffolds and to the displacement of four components that reconfigure into a [2 × 2] CDN. Using six template/blocker scaffolds and the polymerase/dNTPs, the P₁-guided emergence of a [3 × 3] CDN is demonstrated. In addition, by further engineering the template/blocker scaffolds, the hierarchical control over the composition of the P₁-guided emergence of [3 × 3] CDNs is accomplished. Also, sequence-engineered template/blocker scaffolds, coupled to the polymerase/dNTP machinery, lead, in the presence of two primers P₁ and/or P₂, to the selective emergence of two different [2 × 2] CDNs or to a [3 × 3] CDN. Also, a set of six appropriately engineered template/blocker scaffolds, coupled to the polymerase/dNTP machinery, leads to the emergence of a CDN composed of four equilibrated DNA tetrahedra constituents. Finally, by further sequence engineering of the set of template/blocker scaffolds and their coupling to a nicking/polymerization/dNTP replication machinery, the amplified high-throughput emergence of CDNs is demonstrated.