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The regulation of cellular dynamics and responses to stimuli by genetic regulatory networks suggests how in vitro chemical reaction networks might analogously direct the dynamics of synthetic materials or chemistries. A key step in developing genetic regulatory network analogues capable of this type of sophisticated regulation is the integration of multiple coordinated functions within a single network. Here, we demonstrate how such functional integration can be achieved using in vitro transcriptional genelet circuits that emulate essential features of cellular genetic regulatory networks. By successively incorporating functional genelet modules into a bistable circuit, we construct an integrated regulatory network that dynamically changes its state in response to upstream stimuli and coordinates the timing of downstream signal expression. We use quantitative models to guide module integration and develop strategies to mitigate undesired interactions between network components that arise as the size of the network increases. This approach could enable the construction of in vitro networks capable of multifaceted chemical and material regulation. The regulation of cellular response to stimuli by genetic regulatory networks (GRNs) suggests how in vitro chemical reaction networks might be used to direct the dynamics of synthetic materials or chemical reactions. Now, multiple functional in vitro transcriptional circuit modules have been integrated to form composite regulatory networks capable of complex features analogous to those found in cellular GRNs.

During embryo development, patterns of protein concentration appear in response to morphogen gradients. These patterns provide spatial and chemical information that directs the fate of the underlying cells. Here, we emulate this process within non-living matter and demonstrate the autonomous structuration of a synthetic material. First, we use DNA-based reaction networks to synthesize a French flag, an archetypal pattern composed of three chemically distinct zones with sharp borders whose synthetic analogue has remained elusive. A bistable network within a shallow concentration gradient creates an immobile, sharp and long-lasting concentration front through a reaction–diffusion mechanism. The combination of two bistable circuits generates a French flag pattern whose ‘phenotype’ can be reprogrammed by network mutation. Second, these concentration patterns control the macroscopic organization of DNA-decorated particles, inducing a French flag pattern of colloidal aggregation. This experimental framework could be used to test reaction–diffusion models and fabricate soft materials following an autonomous developmental programme. A DNA-based reaction network has now been developed that creates a French flag pattern with immobile and sharp borders from a shallow initial concentration gradient. The output pattern can be used to control the macroscopic organization of DNA-decorated particles thereby inducing a French flag pattern of colloidal aggregation.

When multicellular systems need to communicate over long distances, and signalling molecules are too slow to diffuse, travelling fronts of these molecules emerge—a phenomenon now reconstituted in a coupled array of artificial cells. Living systems employ front propagation and spatiotemporal patterns encoded in biochemical reactions for communication, self-organization and computation 1 , 2 , 3 , 4 . Emulating such dynamics in minimal systems is important for understanding physical principles in living cells 5 , 6 , 7 , 8 and in vitro 9 , 10 , 11 , 12 , 13 , 14 . Here, we report a one-dimensional array of DNA compartments in a silicon chip as a coupled system of artificial cells, offering the means to implement reaction–diffusion dynamics by integrated genetic circuits and chip geometry. Using a bistable circuit we programmed a front of protein synthesis propagating in the array as a cascade of signal amplification and short-range diffusion. The front velocity is maximal at a saddle-node bifurcation from a bistable regime with travelling fronts to a monostable regime that is spatially homogeneous. Near the bifurcation the system exhibits large variability between compartments, providing a possible mechanism for population diversity. This demonstrates that on-chip integrated gene circuits are dynamical systems driving spatiotemporal patterns, cellular variability and symmetry breaking.

During development, cells gain positional information through the interpretation of dynamic morphogen gradients. A proposed mechanism for interpreting opposing morphogen gradients is mutual inhibition of downstream transcription factors, but isolating the role of this specific motif within a natural network remains a challenge. Here, we engineer a synthetic morphogen-induced mutual inhibition circuit in E. coli populations and show that mutual inhibition alone is sufficient to produce stable domains of gene expression in response to dynamic morphogen gradients, provided the spatial average of the morphogens falls within the region of bistability at the single cell level. When we add sender devices, the resulting patterning circuit produces theoretically predicted self-organised gene expression domains in response to a single gradient. We develop computational models of our synthetic circuits parameterised to timecourse fluorescence data, providing both a theoretical and experimental framework for engineering morphogen-induced spatial patterning in cell populations. Morphogen gradients can be dynamic and transient yet give rise to stable cellular patterns. Here the authors show that a synthetic morphogen-induced mutual inhibition circuit produces stable boundaries when the spatial average of morphogens falls within the region of bistability.

The biological clock synchronizes with the environmental light-dark cycle through circadian photoentrainment. While intracellular pathways regulating clock gene expression after light exposure in the suprachiasmatic nucleus are well studied in mammals, the neuronal circuits driving phase shifts remain unclear. Here, using a mouse model, we show that chemogenetic activation of early-night light-responsive neurons induces phase delays at any circadian time, potentially breaking the photoentrainment dead zone. In contrast, activating late-night light-responsive neurons mimics light-induced phase shifts. Using in vivo two-photon microscopy, we found that most neurons in the suprachiasmatic nucleus exhibit stochastic light responses, while a small subset is consistently activated in the early subjective night and another is inhibited in the late subjective night. Our findings suggest a dynamic bi-stable network model for circadian photoentrainment, where phase shifts arise from a functional circuit integrating signals to groups of outcome neurons, rather than a labeled-line principle seen in sensory systems. Neural mechanisms underlying circadian photoentrainment are not fully understood. Using in vivo two-photon imaging with a GRIN lens, this study reveals a dynamic bi-stable circuit in the suprachiasmatic nucleus that regulates light-driven circadian clock shifts, providing insight into mechanisms of circadian photoentrainment.

We demonstrate universal computation in an all-fluidic two-phase microfluidic system. Nonlinearity is introduced into an otherwise linear, reversible, low-Reynolds number flow via bubble-to-bubble hydrodynamic interactions. A bubble traveling in a channel represents a bit, providing us with the capability to simultaneously transport materials and perform logical control operations. We demonstrate bubble logic AND/OR/NOT gates, a toggle flip-flop, a ripple counter, timing restoration, a ring oscillator, and an electro-bubble modulator. These show the nonlinearity, gain, bistability, synchronization, cascadability, feedback, and programmability required for scalable universal computation. With increasing complexity in large-scale microfluidic processors, bubble logic provides an on-chip process control mechanism integrating chemistry and computation.

Information processing using biochemical circuits is essential for survival and reproduction of natural organisms. As stripped‐down analogs of genetic regulatory networks in cells, we engineered artificial transcriptional networks consisting of synthetic DNA switches, regulated by RNA signals acting as transcription repressors, and two enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H. The synthetic switch design is modular with programmable connectivity and allows dynamic control of RNA signals through enzyme‐mediated production and degradation. The switches support sharp and adjustable thresholds using a competitive hybridization mechanism, allowing arbitrary analog or digital circuits to be created in principle. As an example, we constructed an in vitro bistable memory by wiring together two synthetic switches and performed a systematic quantitative characterization. Good agreement between experimental data and a simple mathematical model was obtained for switch input/output functions, phase plane trajectories, and the bifurcation diagram for bistability. Construction of larger synthetic circuits provides a unique opportunity for evaluating model inference, prediction, and design of complex biochemical systems and could be used to control nanoscale devices and artificial cells. Synopsis Information processing using biochemical networks is essential for survival and reproduction of natural organisms (Hartwell et al , 1999 ). Despite many molecular components of biological organisms being identified and characterized, it is still not possible to predict system behavior except in the simplest systems. By constructing increasingly complex analogs of natural circuits, synthetic biology attempts to test sufficiency of mechanistic models and gain insights that observation and analysis alone do not provide (Benner and Sismour, 2005 ). Several synthetic networks constructed by rearranging regulatory components in a cell have been characterized (Gardner et al , 2000 ; Elowitz and Leibler, 2000 ; Becskei et al , 2001 ; Atkinson et al , 2003 ). However, detailed studies of synthetic systems within cells can be difficult because of unknown and uncontrollable parameters. An in vitro reconstruction with known components offers a unique opportunity to investigate how system behavior derives from reaction mechanisms. The first nontrivial system behavior created by an in vitro chemical system was the Belousov‐Zhabotinsky oscillator (Zaikin and Zhabotinsky, 1970 ). Biochemical circuits outside the cell have been constructed within cell‐free transcription‐translation systems (Noireaux et al , 2003 ; Isalan et al , 2005 ), and within a much simpler in vitro system containing only three enzymes (Wlotzka and McCaskill, 1997 ; Ackermann et al , 1998 ). Still, constructing diverse sets of circuits and quantitative modeling are outstanding challenges. In order to investigate a wide range of possible circuits using a small selection of known components, we developed an experimental analog of genetic regulatory circuits that makes use of only T7 RNA polymerase (RNAP) and E. coli ribonuclease H (RNase H) in addition to synthetic DNA templates regulated by RNA transcripts. This system meets our goal of dramatically reducing the chemical complexity by removing the irrelevant genes and regulatory processes of the whole organism, which includes removing protein production and degradation machinery. Moreover, nucleic acid regulatory molecules have the advantage that the structures are well defined and that interactions governed by Watson–Crick base‐paring rules can be easily programmed, allowing for modular designs. Despite the simplicity of our system, we have shown theoretically that arbitrary logic circuits and abstract neural network computations can be implemented (Kim et al , 2004 ). The main conclusions of our experimental and modeling studies are as follows. First, our synthetic switches and feedforward circuits exhibit sigmoidal transfer curves with sharp and adjustable thresholds (Figure 2 ). This shows that proteins are not required for crisp regulation of transcription and validates the system as a model of regulatory networks. The threshold is established by a competitive hybridization mechanism analogous to the ‘inhibitor ultrasensitivity’ mechanism (Ferrell, 1996 ) rather than cooperative binding. Second, synthetic switches are modular and programmable. The mutually inhibitory circuit created by linking two previously characterized switches shows bistability (Figure 5 ), as expected based on the transfer curves of the feedforward circuits (Figure 2 ). Third, we achieved dynamic behavior and steady states by enzyme‐controlled production and degradation. The saturation of RNase H degradation capacity is an important determinant of multistability in our mutually inhibitory circuit (Figure 5B ). Finally, we explain various aspects of the circuit behavior with a simple mathematical model. should be 'This model reproduces the transfer curves for individual switches (Figure 2 ), the bifurcation diagram for the bistable circuit (Figure 5B ), and the phase plane dynamics for the bistable circuit (Figure 5D ) with a single parameter set. The simplicity of the synthetic transcriptional circuit design facilitates probing parameter space and evaluating mathematical models for in vitro biochemical networks. Thus, the in vitro transcriptional circuit can serve as a tool for exploring alternative biochemical circuit designs and studying design principles such as composability, performance, robustness, and efficiency. We developed an experimental analogue of genetic regulatory circuits that makes use of only T7 RNA polymerase and E. coli ribonuclease H in addition to synthetic DNA templates regulated by RNA transcripts. We designed modular and programmable synthetic transcriptional switches that support sharp and adjustable thresholds derived from a competitive hybridization mechanism. A simple mathematical model explains various aspects of circuit behavior such as the bifurcation diagram and the phase plane dynamics for the bistable circuit.

We demonstrate microscopic fluidic control and memory elements through the use of an aqueous viscoelastic polymer solution as a working fluid. By exploiting the fluid's non-Newtonian rheological properties, we were able to demonstrate both a flux stabilizer and a bistable flip-flop memory. These circuit elements are analogous to their solid-state electronic counterparts and could be used as components of control systems for integrated microfluidic devices. Such miniaturized fluidic circuits are insensitive to electromagnetic interference and may also find medical applications for implanted drug-delivery devices.

The d-wave pairing symmetry in high-critical temperature superconductors makes it possible to realize superconducting rings with built-in π phase shifts. Such rings have a twofold degenerate ground state that is characterized by the spontaneous generation of fractional magnetic flux quanta with either up or down polarity. We have incorporated π phase-biased superconducting rings in a logic circuit, a flip-flop, in which the fractional flux polarity is controllably toggled by applying single flux quantum pulses at the input channel. The integration of p rings into conventional rapid single flux quantum logic as natural two-state devices should alleviate the need for bias current lines, improve device symmetry, and enhance the operation margins.

Analysis of synthetic gene regulatory circuits can provide insight into circuit behavior and evolution. An alternative approach is to modify a naturally occurring circuit, by using genetic methods to select functional circuits and evolve their properties. We have applied this approach to the circuitry of phage λ. This phage grows lytically, forms stable lysogens, and can switch from this regulatory state to lytic growth. Genetic selections are available for each behavior. We previously replaced λ Cro in the intact phage with a module including Lac repressor, whose function is tunable with small molecules, and several cis-acting sites. Here, we have in addition replaced λ CI repressor with another tunable module, Tet repressor and several cis-acting sites. Tet repressor lacks several important properties of CI, including positive autoregulation and cooperative DNA binding. Using a combinatorial approach, we isolated phage variants with behavior similar to that of WT λ. These variants grew lytically and formed stable lysogens. Lysogens underwent prophage induction upon addition of a ligand that weakens binding by the Tet repressor. Strikingly, however, addition of a ligand that weakens binding by Lac repressor also induced lysogens. This finding indicates that Lac repressor was present in the lysogens and was necessary for stable lysogeny. Therefore, these isolates had an altered wiring diagram from that of λ. We speculate that this complexity is needed to compensate for the missing features. Our method is generally useful for making customized gene regulatory circuits whose activity is regulated by small molecules or protein cofactors.