Automated design of programmable enzyme-driven DNA circuits

Programming Dissipation Systems by DNA Timer for Temporally Regulating Enzyme Catalysis and Nanostructure Assembly

Live cells precisely control their temporal pattern in energy dissipative processes such as catalysis and assembly. Here, we demonstrate a DNA-based artificial dissipative nonequilibrium system where the transient state is controlled by the processive digestion of λ-exonuclease (λ Exo). This enzyme reaction serves as an orthogonal and independent molecular timer allowing for the programmable regulation of the transient-state lifetime. This dissipation system is concatenated to enzyme catalysis and nanostructure assembly networks. Dynamic activation of enzyme catalysis and dynamic disassembly of DNA nanotubes (DNT) are realized, and the state lifetimes of these systems are accurately encoded by the DNA timer. This work demonstrates nontrivial dissipation systems with built-in molecular timers, which can be a useful tool for developing artificial reaction networks and nanostructures with enhanced complexities and intelligence.

Programmed mechano-chemical coupling in reaction-diffusion active matter

Embryo morphogenesis involves a complex combination of self-organization mechanisms that generate a great diversity of patterns. However, classical in vitro patterning experiments explore only one self-organization mechanism at a time, thus missing coupling effects. Here, we conjugate two major out-of-equilibrium patterning mechanisms—reaction-diffusion and active matter—by integrating dissipative DNA/enzyme reaction networks within an active gel composed of cytoskeletal motors and filaments. We show that the strength of the flow generated by the active gel controls the mechano-chemical coupling between the two subsystems. This property was used to engineer a synthetic material where contractions trigger chemical reaction networks both in time and space, thus mimicking key aspects of the polarization mechanism observed in C. elegans oocytes. We anticipate that reaction-diffusion active matter will promote the investigation of mechano-chemical transduction and the design of new materials with life-like properties.

Flap Endonuclease 1-Assisted DNA Walkers for Sensitively and Specifically Sensing ctDNAs

DNA walkers have shown superior performance in biosensing due to their programmability to design molecular walking behaviors with specific responses to different biological targets. However, it is still challenging to make DNA walkers capable of distinguishing DNA targets with single-base differences, so that DNA walkers that can be used for circulating tumor DNA sensing are rarely reported. Herein, a flap endonuclease 1 (FEN 1)-assisted DNA walker has been proposed to achieve mutant biosensing. The target DNA is captured on a gold nanoparticle (AuNP) as a walking strand to walk by hybridizing to the track strands on the surface of the AuNP. FEN 1 is employed to report the walking events by cleaving the track strands that must form a three-base overlapping structure recognized by FEN 1 after hybridizing with the captured target DNA. Owing to the high specificity of FEN 1 for structure recognition, the one-base mutant DNA target can be discriminated from wild-type DNA. By constructing a sensitivity-enhanced DNA walker system, as low as 1 fM DNA targets and 0.1% mutation abundance can be sensed, and the theoretical detection limits for detecting the DNA target and mutation abundance achieve 0.22 fM and 0.01%, respectively. The results of epidermal growth factor receptor (EGFR) L858R mutation detection on cell-free DNA samples from 15 patients with nonsmall cell lung cancer were completely consistent with that of next-generation sequencing, indicating that our DNA walker has potential for liquid biopsy.

DNA-Templated Timer Probes for Multiplexed Sensing

Simultaneous analysis based on encoded fluorophores suffers from potential crosstalk between fluorophores and the limited number of colors that can be practically resolved. Inspired by nontrivial temporal patterns in living organisms, we developed a DNA-templated probe by utilizing DNA polymerase (DNAP) for multiplexed detection of nucleic acids. These probes use differential delay times of signaling by a DNAP-mediated extension to distinguish different targets, which serve as the primers. Taking advantage of the high processivity and the controllable kinetics of DNAP, we find that multiplexed detection can be achieved in homogeneous solution using a single fluorophore. As a proof of concept, we developed assays for genomic DNA from four different bacteria. In addition, we designed and implemented probes to undergo a single oscillation in signal as an alternative way for multiplexing. We anticipate this approach will find broad applications not only in sensing but also in synthetic DNA nanosystems.

A Logic Programming Language for Computational Nucleic Acid Devices

Computational nucleic acid devices show great potential for enabling a broad range of biotechnology applications, including smart probes for molecular biology research, in vitro assembly of complex compounds, high-precision in vitro disease diagnosis and, ultimately, computational theranostics inside living cells. This diversity of applications is supported by a range of implementation strategies, including nucleic acid strand displacement, localization to substrates, and the use of enzymes with polymerase, nickase, and exonuclease functionality. However, existing computational design tools are unable to account for these strategies in a unified manner. This paper presents a logic programming language that allows a broad range of computational nucleic acid systems to be designed and analyzed. The language extends standard logic programming with a novel equational theory to express nucleic acid molecular motifs. It automatically identifies matching motifs present in the full system, in order to apply a specified transformation expressed as a logical rule. The language supports the definition of logic predicates, which provide constraints that need to be satisfied in order for a given rule to be applied. The language is sufficiently expressive to encode the semantics of nucleic strand displacement systems with complex topologies, together with computation performed by a broad range of enzymes, and is readily extensible to new implementation strategies. Our approach lays the foundation for a unifying framework for the design of computational nucleic acid devices.

Computer-aided biochemical programming of synthetic microreactors as diagnostic devices

Biological systems have evolved efficient sensing and decision-making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non-living biomolecular devices could offer promising avenues toward various real-world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell-like microreactors embedding biochemical logic circuits, or protosensors, to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof-of-concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses.

Design and Analysis of Compact DNA Strand Displacement Circuits for Analog Computation Using Autocatalytic Amplifiers

A main goal in DNA computing is to build DNA circuits to compute designated functions using a minimal number of DNA strands. Here, we propose a novel architecture to build compact DNA strand displacement circuits to compute a broad scope of functions in an analog fashion. A circuit by this architecture is composed of three autocatalytic amplifiers, and the amplifiers interact to perform computation. We show DNA circuits to compute functions sqrt(x), ln(x) and exp(x) for x in tunable ranges with simulation results. A key innovation in our architecture, inspired by Napier's use of logarithm transforms to compute square roots on a slide rule, is to make use of autocatalytic amplifiers to do logarithmic and exponential transforms in concentration and time. In particular, we convert from the input that is encoded by the initial concentration of the input DNA strand, to time, and then back again to the output encoded by the concentration of the output DNA strand at equilibrium. This combined use of strand-concentration and time encoding of computational values may have impact on other forms of molecular computation.

Nicking enzyme-controlled toehold regulation for DNA logic circuits

DNA strand displacement is widely used in DNA-related nanoengineering for its remarkable specificity and predictability. We report a nicking enzyme-assisted mechanism to regulate strand displacement, where DNA toeholds are dynamically controlled. To demonstrate the strategy, a protein/DNA-based Boolean operation system is constructed and based on it a two-channel multiplexer controlled by three different nicking enzymes is realized. The proposed regulatory mechanism can be used for switch logic statement and bridges protein and DNA logic circuits.

Boosting functionality of synthetic DNA circuits with tailored deactivation

Molecular programming takes advantage of synthetic nucleic acid biochemistry to assemble networks of reactions, in vitro, with the double goal of better understanding cellular regulation and providing information-processing capabilities to man-made chemical systems. The function of molecular circuits is deeply related to their topological structure, but dynamical features (rate laws) also play a critical role. Here we introduce a mechanism to tune the nonlinearities associated with individual nodes of a synthetic network. This mechanism is based on programming deactivation laws using dedicated saturable pathways. We demonstrate this approach through the conversion of a single-node homoeostatic network into a bistable and reversible switch. Furthermore, we prove its generality by adding new functions to the library of reported man-made molecular devices: a system with three addressable bits of memory, and the first DNA-encoded excitable circuit. Specific saturable deactivation pathways thus greatly enrich the functional capability of a given circuit topology.

Nonlinearity in synthetic molecular circuits is usually achieved by manipulation of network topology or of production kinetics. Here, the authors achieve bistability and other nonlinear behaviours by manipulating the individual degradation rate laws of circuit components using saturable pathways.

High-resolution mapping of bifurcations in nonlinear biochemical circuits

Analog molecular circuits can exploit the nonlinear nature of biochemical reaction networks to compute low-precision outputs with fewer resources than digital circuits. This analog computation is similar to that employed by gene-regulation networks. Although digital systems have a tractable link between structure and function, the nonlinear and continuous nature of analog circuits yields an intricate functional landscape, which makes their design counter-intuitive, their characterization laborious and their analysis delicate. Here, using droplet-based microfluidics, we map with high resolution and dimensionality the bifurcation diagrams of two synthetic, out-of-equilibrium and nonlinear programs: a bistable DNA switch and a predator-prey DNA oscillator. The diagrams delineate where function is optimal, dynamics bifurcates and models fail. Inverse problem solving on these large-scale data sets indicates interference from enzymatic coupling. Additionally, data mining exposes the presence of rare, stochastically bursting oscillators near deterministic bifurcations.

Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach

Living cells are able to produce a wide variety of biological responses when subjected to biochemical stimuli.