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Toehold‐mediated strand displacement (TMSD) reaction, one of the DNA nanotechnologies, has great potential as s biological programmable platform in the cellular environment. Various artificial nucleic acids have been developed to improve stability and affinity for biological applications. However, the lack of understanding of the kinetics of TMSD reaction among artificial nucleic acids has limited their applications. We herein systematically characterized the kinetics of TMSD reactions with acyclic xeno nucleic acids (XNAs): serinol nucleic acid (SNA), acyclic D‐threoninol nucleic acid (D‐aTNA), and acyclic L‐threoninol nucleic acid (L‐aTNA). We found that the strand displacement reactions by D‐aTNA and by L‐aTNA were highly dependent on temperature. D‐aTNA and L‐aTNA systems were orthogonal to each other, and chirality of the input can be switched by using SNA as an interface. We also applied TMSD reactions of XNAs to a seesaw gate amplification system which utilizes the orthogonality. This work will contribute to the developments of thermoresponsive and bioorthogonal nucleic acid circuits. [ABSTRACT FROM AUTHOR]

Exponential DNA amplification techniques are fundamental in ultrasensitive molecular diagnostics. These systems offer a wide dynamic range, but the quantification requires real‐time monitoring of the amplification reaction. Linear amplification schemes, despite their limited sensitivity, can achieve quantitative measurement from a single end‐point readout, suitable for low‐cost, point‐of‐care, or massive testing. Reconciling the sensitivity of exponential amplification with the simplicity of end‐point readout would thus break through a major design dilemma and open a route to a new generation of massively scalable quantitative bioassays. Here a hybrid nucleic acid‐based circuit design is introduced to compute a logarithmic function, therefore providing a wide dynamic range based on a single end‐point measurement. CELIA (Coupling Exponential amplification reaction to LInear Amplification) exploits a versatile biochemical circuit architecture to couple a tunable linear amplification stage – optionally embedding an inverter function – downstream of an exponential module in a one‐pot format. Applied to the detection of microRNAs, CELIA provides a limit of detection in the femtomolar range and a dynamic range of six decades. This isothermal approach bypasses thermocyclers without compromising sensitivity, thereby opening the way to applications in various diagnostic assays, and providing a simplified, cost‐efficient, and high throughput solution for quantitative nucleic acid analysis. [ABSTRACT FROM AUTHOR]

DNA as an informational polymer has, for the past 30 years, progressively become an essential molecule to rationally build chemical reaction networks endowed with powerful signal‐processing capabilities. Whether influenced by the silicon world or inspired by natural computation, molecular programming has gained attention for diagnosis applications. Of particular interest for this review, molecular classifiers have shown promising results for disease pattern recognition and sample classification. Because both input integration and computation are performed in a single tube, at the molecular level, this low‐cost approach may come as a complementary tool to molecular profiling strategies, where all biomarkers are quantified independently using high‐tech instrumentation. After introducing the elementary components of molecular classifiers, some of their experimental implementations are discussed either using digital Boolean logic or analog neural network architectures. [ABSTRACT FROM AUTHOR]

Research on so‐called "chemical artificial intelligence" (CAI) is an emerging field with the aim of constructing information‐processing systems with learning capabilities based on chemical methodologies. This can be regarded as an attempt to reconstruct Cybernetics using molecular based systems. Many chemical reaction systems with computational abilities are proposed, but most are fixed functions that deliver molecular output for a given molecular input. On the other hand, chemical AI is a system with learning capability; namely, the output should be variable and gradually change upon repeated molecular inputs. In this paper, a compartmentalization approach for implementing cellular chemical AI using liposomes is discussed. The existing studies in terms of the methods used for assembling systems consisting of many liposomes with different functions, methods for achieving recursiveness and plasticity in chemical reaction systems, and methods for reconfiguring the network topology by liposome deformation are reviewed. Issues that must be addressed in order to realize chemical AI are also identified. [ABSTRACT FROM AUTHOR]

Main observation and conclusion DNA circuits have been designed for implementation of various functions based on DNA strand displacement in cell‐free settings, but their capabilities in biological environments remain limited. In this work, we report framework nucleic acid (FNA)‐based circuits enabling intracellular logic computation for mRNA imaging. FNAs as rigid scaffolds enable to deliver our built DNA circuits into cells without aid of transfection reagents, evading a time‐consuming and tedious process prior to analysis, and the pendant duplex DNA designed at one vertex of FNA as gate is suitable for four‐way strand exchange, minimizing crosstalk with other nucleic acids in the cellular milieu. We demonstrated that such FNA‐based circuits can operate both in vitro and in vivo logic computation, including OR and AND logic gates. Moreover, in situ mRNA imaging was also realized by exploiting native mRNA as scaffolds to bind multiple FNA‐based gates for the enhanced signal‐to‐background ratio. We hope that this FNA‐based circuit can be applied for disease diagnosis, facilitating the development of biomedicine. [ABSTRACT FROM AUTHOR]

Main observation and conclusion DNA circuits have been designed for implementation of various functions based on DNA strand displacement in cell‐free settings, but their capabilities in biological environments remain limited. In this work, we report framework nucleic acid (FNA)‐based circuits enabling intracellular logic computation for mRNA imaging. FNAs as rigid scaffolds enable to deliver our built DNA circuits into cells without aid of transfection reagents, evading a time‐consuming and tedious process prior to analysis, and the pendant duplex DNA designed at one vertex of FNA as gate is suitable for four‐way strand exchange, minimizing crosstalk with other nucleic acids in the cellular milieu. We demonstrated that such FNA‐based circuits can operate both in vitro and in vivo logic computation, including OR and AND logic gates. Moreover, in situ mRNA imaging was also realized by exploiting native mRNA as scaffolds to bind multiple FNA‐based gates for the enhanced signal‐to‐background ratio. We hope that this FNA‐based circuit can be applied for disease diagnosis, facilitating the development of biomedicine. [ABSTRACT FROM AUTHOR]

Precise control of DNA‐circuit functions facilitates the construction of complex DNA networks to perform sophisticated functions. Inspired by optochemical genetics with high precision for controlling and studying neural networks by photoregulation of membrane receptors, we herein report optochemically controlled DNA switching circuits for regulating computation functions. The DNA‐switching circuits involve a CG–C+ triplex‐based DNA switch that undergoes structural transition from triplex to duplex states after exposure to UV irradiation due to proton transfer, showing optochemical control. We demonstrate that the DNA‐switching circuits enable the regulation of computation functions by optochemical control of the state of the DNA switch, including multiple logic computations and probabilistic computation. We hope this work will broaden DNA‐circuit functions and facilitate the construction of complex DNA networks. [ABSTRACT FROM AUTHOR]

Titelbild: Optochemical Control of DNA-Switching Circuits for Logic and Probabilistic Computation (Angew. Keywords: chemical reaction networks; DNA circuits; DNA switches; logic computations; probabilistic computations EN chemical reaction networks DNA circuits DNA switches logic computations probabilistic computations 3353 3353 1 02/10/21 20210215 NES 210215 B Ein molekularer Computer b aus optochemischen DNA-Schaltkreisen wurde entwickelt, der digitale Rechenoperationen einschließlich Boolescher Logik (dargestellt durch 0 und 1) und Wahrscheinlichkeitsrechnungen (dargestellt durch die Würfel), ausführen kann. Chemical reaction networks, DNA circuits, DNA switches, logic computations, probabilistic computations. [Extracted from the article]