RTRACS: a modularized RNA-dependent RNA transcription system with high programmability

DNA droplets for intelligent and dynamical artificial cells: from the viewpoint of computation and non-equilibrium systems

Living systems are molecular assemblies whose dynamics are maintained by non-equilibrium chemical reactions. To date, artificial cells have been studied from such physical and chemical viewpoints. This review briefly gives a perspective on using DNA droplets in constructing artificial cells. A DNA droplet is a coacervate composed of DNA nanostructures, a novel category of synthetic DNA self-assembled systems. The DNA droplets have programmability in physical properties based on DNA base sequence design. The aspect of DNA as an information molecule allows physical and chemical control of nanostructure formation, molecular assembly and molecular reactions through the design of DNA base pairing. As a result, the construction of artificial cells equipped with non-equilibrium behaviours such as dynamical motions, phase separations, molecular sensing and computation using chemical energy is becoming possible. This review mainly focuses on such dynamical DNA droplets for artificial cell research in terms of computation and non-equilibrium chemical reactions.

Molecular Computation for Molecular Classification

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.

Cell-Free Production Systems in Droplet Microfluidics

The use of cell-free production systems in droplet microfluidic devices has gained significant interest during the last decade. Encapsulating DNA replication, RNA transcription, and protein expression systems in water-in-oil drops allows for the interrogation of unique molecules and high-throughput screening of libraries of industrial and biomedical interest. Furthermore, the use of such systems in closed compartments enables the evaluation of various properties of novel synthetic or minimal cells. In this chapter, we review the latest advances in the usage of the cell-free macromolecule production toolbox in droplets, with a special emphasis on new on-chip technologies for the amplification, transcription, expression, screening, and directed evolution of biomolecules.

Cell-Free Synthetic Biology Platform for Engineering Synthetic Biological Circuits and Systems

Synthetic biology brings engineering disciplines to create novel biological systems for biomedical and technological applications. The substantial growth of the synthetic biology field in the past decade is poised to transform biotechnology and medicine. To streamline design processes and facilitate debugging of complex synthetic circuits, cell-free synthetic biology approaches has reached broad research communities both in academia and industry. By recapitulating gene expression systems in vitro, cell-free expression systems offer flexibility to explore beyond the confines of living cells and allow networking of synthetic and natural systems. Here, we review the capabilities of the current cell-free platforms, focusing on nucleic acid-based molecular programs and circuit construction. We survey the recent developments including cell-free transcription-translation platforms, DNA nanostructures and circuits, and novel classes of riboregulators. The links to mathematical models and the prospects of cell-free synthetic biology platforms will also be discussed.

Signalling and differentiation in emulsion-based multi-compartmentalized in vitro gene circuits

Multicellularity enables the growth of complex life forms as it allows for specialization of cell types, differentiation, and large scale spatial organization. In a similar way, modular construction of synthetic multicellular systems will lead to dynamic biomimetic materials that can respond to their environment in complex ways. In order to achieve this goal, artificial cellular communication and developmental programs still have to be established. Here, we create geometrically controlled spatial arrangements of emulsion-based artificial cellular compartments containing synthetic in vitro gene circuitry, separated by lipid bilayer membranes. We quantitatively determine the membrane pore-dependent response of the circuits to artificial morphogen gradients, which are established via diffusion from dedicated organizer cells. Utilizing different types of feed-forward and feedback in vitro gene circuits, we then implement artificial signaling and differentiation processes, demonstrating the potential for the realization of complex spatiotemporal dynamics in artificial multicellular systems.

Nanopore Logic Operation with DNA to RNA Transcription in a Droplet System

This paper describes an AND logic operation with amplification and transcription from DNA to RNA, using T7 RNA polymerase. All four operations, (0 0) to (1 1), with an enzyme reaction can be performed simultaneously, using four-droplet devices that are directly connected to a patch-clamp amplifier. The output RNA molecule is detected using a biological nanopore with single-molecule translocation. Channel current recordings can be obtained using the enzyme solution. The integration of DNA logic gates into electrochemical devices is necessary to obtain output information in a human-recognizable form. Our method will be useful for rapid and confined DNA computing applications, including the development of programmable diagnostic devices.

Serial DNA relay in DNA logic gates by electrical fusion and mechanical splitting of droplets

DNA logic circuits utilizing DNA hybridization and/or enzymatic reactions have drawn increasing attention for their potential applications in the diagnosis and treatment of cellular diseases. The compartmentalization of such a system into a microdroplet considerably helps to precisely regulate local interactions and reactions between molecules. In this study, we introduced a relay approach for enabling the transfer of DNA from one droplet to another to implement multi-step sequential logic operations. We proposed electrical fusion and mechanical splitting of droplets to facilitate the DNA flow at the inputs, logic operation, output, and serial connection between two logic gates. We developed Negative-OR operations integrated by a serial connection of the OR gate and NOT gate incorporated in a series of droplets. The four types of input defined by the presence/absence of DNA in the input droplet pair were correctly reflected in the readout at the Negative-OR gate. The proposed approach potentially allows for serial and parallel logic operations that could be used for complex diagnostic applications.

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.

Genetic encoding of DNA nanostructures and their self-assembly in living bacteria

The field of DNA nanotechnology has harnessed the programmability of DNA base pairing to direct single-stranded DNAs (ssDNAs) to assemble into desired 3D structures. Here, we show the ability to express ssDNAs in Escherichia coli (32-205 nt), which can form structures in vivo or be purified for in vitro assembly. Each ssDNA is encoded by a gene that is transcribed into non-coding RNA containing a 3'-hairpin (HTBS). HTBS recruits HIV reverse transcriptase, which nucleates DNA synthesis and is aided in elongation by murine leukemia reverse transcriptase. Purified ssDNA that is produced in vivo is used to assemble large 1D wires (300 nm) and 2D sheets (5.8 μm(2)) in vitro. Intracellular assembly is demonstrated using a four-ssDNA crossover nanostructure that recruits split YFP when properly assembled. Genetically encoding DNA nanostructures provides a route for their production as well as applications in living cells.

Logic Gate Operation by DNA Translocation through Biological Nanopores

Logical operations using biological molecules, such as DNA computing or programmable diagnosis using DNA, have recently received attention. Challenges remain with respect to the development of such systems, including label-free output detection and the rapidity of operation. Here, we propose integration of biological nanopores with DNA molecules for development of a logical operating system. We configured outputs “1” and “0” as single-stranded DNA (ssDNA) that is or is not translocated through a nanopore; unlabeled DNA was detected electrically. A negative-AND (NAND) operation was successfully conducted within approximately 10 min, which is rapid compared with previous studies using unlabeled DNA. In addition, this operation was executed in a four-droplet network. DNA molecules and associated information were transferred among droplets via biological nanopores. This system would facilitate linking of molecules and electronic interfaces. Thus, it could be applied to molecular robotics, genetic engineering, and even medical diagnosis and treatment.

Molecular robots with sensors and intelligence

CONSPECTUS: What we can call a molecular robot is a set of molecular devices such as sensors, logic gates, and actuators integrated into a consistent system. The molecular robot is supposed to react autonomously to its environment by receiving molecular signals and making decisions by molecular computation. Building such a system has long been a dream of scientists; however, despite extensive efforts, systems having all three functions (sensing, computation, and actuation) have not been realized yet. This Account introduces an ongoing research project that focuses on the development of molecular robotics funded by MEXT (Ministry of Education, Culture, Sports, Science and Technology, Japan). This 5 year project started in July 2012 and is titled "Development of Molecular Robots Equipped with Sensors and Intelligence". The major issues in the field of molecular robotics all correspond to a feedback (i.e., plan-do-see) cycle of a robotic system. More specifically, these issues are (1) developing molecular sensors capable of handling a wide array of signals, (2) developing amplification methods of signals to drive molecular computing devices, (3) accelerating molecular computing, (4) developing actuators that are controllable by molecular computers, and (5) providing bodies of molecular robots encapsulating the above molecular devices, which implement the conformational changes and locomotion of the robots. In this Account, the latest contributions to the project are reported. There are four research teams in the project that specialize on sensing, intelligence, amoeba-like actuation, and slime-like actuation, respectively. The molecular sensor team is focusing on the development of molecular sensors that can handle a variety of signals. This team is also investigating methods to amplify signals from the molecular sensors. The molecular intelligence team is developing molecular computers and is currently focusing on a new photochemical technology for accelerating DNA-based computations. They also introduce novel computational models behind various kinds of molecular computers necessary for designing such computers. The amoeba robot team aims at constructing amoeba-like robots. The team is trying to incorporate motor proteins, including kinesin and microtubules (MTs), for use as actuators implemented in a liposomal compartment as a robot body. They are also developing a methodology to link DNA-based computation and molecular motor control. The slime robot team focuses on the development of slime-like robots. The team is evaluating various gels, including DNA gel and BZ gel, for use as actuators, as well as the body material to disperse various molecular devices in it. They also try to control the gel actuators by DNA signals coming from molecular computers.

Dynamic DNA-toolbox reaction circuits: a walkthrough

In living organisms, the integration of signals from the environment and the molecular computing leading to a cellular response are orchestrated by Gene Regulatory Networks (GRN). However, the molecular complexity of in vivo genetic regulation makes it next to impossible to describe in a quantitative manner. Reproducing, in vitro, reaction networks that could mimic the architecture and behavior of in vivo networks, yet lend themselves to mathematical modeling, represents a useful strategy to understand, and even predict, the function of GRN. In this paper, we define a set of in vitro, DNA-based molecular transformations that can be linked to each other in such a way that the product of one transformation can activate or inhibit the production of one or several other DNA compounds. Therefore, these reactions can be wired in arbitrary networks. This approach provides an experimental way to reproduce the dynamic features of genetic regulation in a test tube. We introduce the rules to design the necessary DNA species, a guide to implement the chemical reactions and ways to optimize the experimental conditions. We finally show how this framework, or "DNA toolbox", can be used to generate an inversion module, though many other behaviors, including oscillators and bistable switches, can be implemented.

Scaling down DNA circuits with competitive neural networks

DNA has proved to be an exquisite substrate to compute at the molecular scale. However, nonlinear computations (such as amplification, comparison or restoration of signals) remain costly in term of strands and are prone to leak. Kim et al. showed how competition for an enzymatic resource could be exploited in hybrid DNA/enzyme circuits to compute a powerful nonlinear primitive: the winner-take-all (WTA) effect. Here, we first show theoretically how the nonlinearity of the WTA effect allows the robust and compact classification of four patterns with only 16 strands and three enzymes. We then generalize this WTA effect to DNA-only circuits and demonstrate similar classification capabilities with only 23 strands.

In vitro regulatory models for systems biology

The reductionist approach has revolutionized biology in the past 50 years. Yet its limits are being felt as the complexity of cellular interactions is gradually revealed by high-throughput technology. In order to make sense of the deluge of "omic data", a hypothesis-driven view is needed to understand how biomolecular interactions shape cellular networks. We review recent efforts aimed at building in vitro biochemical networks that reproduce the flow of genetic regulation. We highlight how those efforts have culminated in the rational construction of biochemical oscillators and bistable memories in test tubes. We also recapitulate the lessons learned about in vivo biochemical circuits such as the importance of delays and competition, the links between topology and kinetics, as well as the intriguing resemblance between cellular reaction networks and ecosystems.

Ensemble Bayesian analysis of bistability in a synthetic transcriptional switch

An overarching goal of synthetic and systems biology is to engineer and understand complex biochemical systems by rationally designing and analyzing their basic component interactions. Practically, the extent to which such reductionist approaches can be applied is unclear especially as the complexity of the system increases. Toward gradually increasing the complexity of systematically engineered systems, programmable synthetic circuits operating in cell-free in vitro environments offer a valuable testing ground for principles for the design, characterization, and analysis of complex biochemical systems. Here we illustrate this approach using in vitro transcriptional circuits ("genelets") while developing an activatable transcriptional switch motif and configuring it as a bistable autoregulatory circuit, using just four synthetic DNA strands and three essential enzymes, bacteriophage T7 RNA polymerase, Escherichia coli ribonuclease H, and ribonuclease R. Fulfilling the promise of predictable system design, the thermodynamic and kinetic constraints prescribed at the sequence level were enough to experimentally demonstrate intended bistable dynamics for the synthetic autoregulatory switch. A simple mathematical model was constructed based on the mechanistic understanding of elementary reactions, and a Monte Carlo Bayesian inference approach was employed to find parameter sets compatible with a training set of experimental results; this ensemble of parameter sets was then used to predict a test set of additional experiments with reasonable agreement and to provide a rigorous basis for confidence in the mechanistic model. Our work demonstrates that programmable in vitro biochemical circuits can serve as a testing ground for evaluating methods for the design and analysis of more complex biochemical systems such as living cells.

Evolution of an inhibitory RNA aptamer against T7 RNA polymerase

Aptamers are promising gene components that can be used for the construction of synthetic gene circuits. In this study, we isolated an RNA aptamer that specifically inhibits transcription of T7 RNA polymerase (RNAP). The 38-nucleotide aptamer, which was a shortened variant of an initial SELEX isolate, showed moderate inhibitory activity. By stepwise doped-SELEX, we isolated evolved variants with strong inhibitory activity. A 29-nucleotide variant of a doped-SELEX isolate showed 50% inhibitory concentration at 11 nM under typical in vitro transcription conditions. Pull-down experiments revealed that the aptamer inhibited the association of T7 RNAP with T7 promoter DNA.

An aptazyme-based molecular device that converts a small-molecule input into an RNA output

We describe the construction of an aptazyme-based molecular device that converts, through a cascade of reactions, a small-molecule input into output RNA strands. This device is applicable as an interface between a small molecule and a molecular system that accepts only nucleic acid input.

Inhibitory RNA aptamer against SP6 RNA polymerase

Aptamers are attractive tools for modulating function of a desired target. In this study, we isolated an RNA aptamer that specifically inhibits transcription of SP6 RNA polymerase. The dissociation constant and 50% inhibitory concentration of the aptamer were estimated 9.5 nM and 24.8 nM, respectively. Doped-SELEX and mutational analysis revealed that the aptamer adopts the structure including two stems, two loops, and 5' single-stranded region. Based on the results, the aptamer could be engineered to circular permutant and binary construct forms without decreasing the activity. The aptamer would be applicable for the construction of expression regulation systems.