Diversity in the dynamical behaviour of a compartmentalized programmable biochemical oscillator

Homogeneous Time Constants Promote Oscillations in Negative Feedback Loops

Biological oscillators are present in nearly all self-regulating systems, from individual cells to entire organisms. In any oscillator structure, a negative feedback loop is necessary, but not sufficient to guarantee the emergence of periodic behaviors. The likelihood of oscillations can be improved by careful tuning of the system time constants and by increasing the loop gain, yet it is unclear whether there is any general relationship between optimal time constants and loop gain. This issue is particularly relevant in genetic oscillators resulting from a chain of different subsequent biochemical events, each with distinct (and uncertain) kinetics. Using two families of genetic oscillators as model examples, we show that the loop gain required for oscillations is minimum when all elements in the loop have the same time constant. On the contrary, we show that homeostasis is ensured if a single element is considerably slower than the others.

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.

A robust and tunable mitotic oscillator in artificial cells

Single-cell analysis is pivotal to deciphering complex phenomena like heterogeneity, bistability, and asynchronous oscillations, where a population ensemble cannot represent individual behaviors. Bulk cell-free systems, despite having unique advantages of manipulation and characterization of biochemical networks, lack the essential single-cell information to understand a class of out-of-steady-state dynamics including cell cycles. Here, by encapsulating Xenopus egg extracts in water-in-oil microemulsions, we developed artificial cells that are adjustable in sizes and periods, sustain mitotic oscillations for over 30 cycles, and function in forms from the simplest cytoplasmic-only to the more complicated ones involving nuclear dynamics, mimicking real cells. Such innate flexibility and robustness make it key to studying clock properties like tunability and stochasticity. Our results also highlight energy as an important regulator of cell cycles. We demonstrate a simple, powerful, and likely generalizable strategy of integrating strengths of single-cell approaches into conventional in vitro systems to study complex clock functions.

Genetic programs can be compressed and autonomously decompressed in live cells

Fundamental computer science concepts have inspired novel information-processing molecular systems in test tubes 1-13 and genetically encoded circuits in live cells 14-21 . Recent research has shown that digital information storage in DNA, implemented using deep sequencing and conventional software, can approach the maximum Shannon information capacity 22 of two bits per nucleotide 23 . In nature, DNA is used to store genetic programs, but the information content of the encoding rarely approaches this maximum 24 . We hypothesize that the biological function of a genetic program can be preserved while reducing the length of its DNA encoding and increasing the information content per nucleotide. Here we support this hypothesis by describing an experimental procedure for compressing a genetic program and its subsequent autonomous decompression and execution in human cells. As a test-bed we choose an RNAi cell classifier circuit 25 that comprises redundant DNA sequences and is therefore amenable for compression, as are many other complex gene circuits 15,18,26-28 . In one example, we implement a compressed encoding of a ten-gene four-input AND gate circuit using only four genetic constructs. The compression principles applied to gene circuits can enable fitting complex genetic programs into DNA delivery vehicles with limited cargo capacity, and storing compressed and biologically inert programs in vivo for on-demand activation.

Gene Expression on DNA Biochips Patterned with Strand-Displacement Lithography

Lithographic patterning of DNA molecules enables spatial organization of cell-free genetic circuits under well-controlled experimental conditions. Here, we present a biocompatible, DNA-based resist termed "Bephore", which is based on commercially available components and can be patterned by both photo- and electron-beam lithography. The patterning mechanism is based on cleavage of a chemically modified DNA hairpin by ultraviolet light or electrons, and a subsequent strand-displacement reaction. All steps are performed in aqueous solution and do not require chemical development of the resist, which makes the lithographic process robust and biocompatible. Bephore is well suited for multistep lithographic processes, enabling the immobilization of different types of DNA molecules with micrometer precision. As an application, we demonstrate compartmentalized, on-chip gene expression from three sequentially immobilized DNA templates, leading to three spatially resolved protein-expression gradients.

Gene-Mediated Chemical Communication in Synthetic Protocell Communities

A gene-directed chemical communication pathway between synthetic protocell signaling transmitters (lipid vesicles) and receivers (proteinosomes) was designed, built and tested using a bottom-up modular approach comprising small molecule transcriptional control, cell-free gene expression, porin-directed efflux, substrate signaling, and enzyme cascade-mediated processing.

Probabilistic switching circuits in DNA

Biological organisms exhibit sophisticated control over the stochastic states of individual cells, but the understanding of underlying molecular mechanisms remains incomplete. It has been argued that unbiased choices are easy to achieve, but choices biased with specific probabilities are much harder. These natural phenomena raise an engineering challenge: Does there exist a simple method to program molecular systems that control arbitrary probabilities for individual molecular events? Here we show a molecular circuit architecture, using just a simple DNA strand displacement building block that functions as an unbiased switch, for creating a circuit output with any desired probability. We constructed several DNA circuits with multiple layers and feedback, demonstrating complex molecular information processing that exploits the inherent stochasticity of molecular interactions.

A natural feature of molecular systems is their inherent stochastic behavior. A fundamental challenge related to the programming of molecular information processing systems is to develop a circuit architecture that controls the stochastic states of individual molecular events. Here we present a systematic implementation of probabilistic switching circuits, using DNA strand displacement reactions. Exploiting the intrinsic stochasticity of molecular interactions, we developed a simple, unbiased DNA switch: An input signal strand binds to the switch and releases an output signal strand with probability one-half. Using this unbiased switch as a molecular building block, we designed DNA circuits that convert an input signal to an output signal with any desired probability. Further, this probability can be switched between 2ⁿ different values by simply varying the presence or absence of n distinct DNA molecules. We demonstrated several DNA circuits that have multiple layers and feedback, including a circuit that converts an input strand to an output strand with eight different probabilities, controlled by the combination of three DNA molecules. These circuits combine the advantages of digital and analog computation: They allow a small number of distinct input molecules to control a diverse signal range of output molecules, while keeping the inputs robust to noise and the outputs at precise values. Moreover, arbitrarily complex circuit behaviors can be implemented with just a single type of molecular building block.

Stability analysis of an artificial biomolecular oscillator with non-cooperative regulatory interactions

Oscillators are essential to fuel autonomous behaviours in molecular systems. Artificial oscillators built with programmable biological molecules such as DNA and RNA are generally easy to build and tune, and can serve as timers for biological computation and regulation. We describe a new artificial nucleic acid biochemical reaction network, and we demonstrate its capacity to exhibit oscillatory solutions. This network can be built in vitro using nucleic acids and three bacteriophage enzymes, and has the potential to be implemented in cells. Numerical simulations suggest that oscillations occur in a realistic range of reaction rates and concentrations.

Programmable autonomous synthesis of single-stranded DNA

DNA performs diverse functional roles in biology, nanotechnology and biotechnology, but current methods for autonomously synthesizing arbitrary single-stranded DNA are limited. Here, we introduce the concept of primer exchange reaction (PER) cascades, which grow nascent single-stranded DNA with user-specified sequences following prescribed reaction pathways. PER synthesis happens in a programmable, autonomous, in situ and environmentally responsive fashion, providing a platform for engineering molecular circuits and devices with a wide range of sensing, monitoring, recording, signal-processing and actuation capabilities. We experimentally demonstrate a nanodevice that transduces the detection of a trigger RNA into the production of a DNAzyme that degrades an independent RNA substrate, a signal amplifier that conditionally synthesizes long fluorescent strands only in the presence of a particular RNA signal, molecular computing circuits that evaluate logic (AND, OR, NOT) combinations of RNA inputs, and a temporal molecular event recorder that records in the PER transcript the order in which distinct RNA inputs are sequentially detected.

Systems and synthetic biology approaches in understanding biological oscillators

Background

Self-sustained oscillations are a ubiquitous and vital phenomenon in living systems. From primitive single-cellular bacteria to the most sophisticated organisms, periodicities have been observed in a broad spectrum of biological processes such as neuron firing, heart beats, cell cycles, circadian rhythms, etc. Defects in these oscillators can cause diseases from insomnia to cancer. Elucidating their fundamental mechanisms is of great significance to diseases, and yet challenging, due to the complexity and diversity of these oscillators.

Results

Approaches in quantitative systems biology and synthetic biology have been most effective by simplifying the systems to contain only the most essential regulators. Here, we will review major progress that has been made in understanding biological oscillators using these approaches. The quantitative systems biology approach allows for identification of the essential components of an oscillator in an endogenous system. The synthetic biology approach makes use of the knowledge to design the simplest, de novo oscillators in both live cells and cell-free systems. These synthetic oscillators are tractable to further detailed analysis and manipulations.

Conclusion

With the recent development of biological and computational tools, both approaches have made significant achievements.

Synchrony and pattern formation of coupled genetic oscillators on a chip of artificial cells

Understanding how biochemical networks lead to large-scale nonequilibrium self-organization and pattern formation in life is a major challenge, with important implications for the design of programmable synthetic systems. Here, we assembled cell-free genetic oscillators in a spatially distributed system of on-chip DNA compartments as artificial cells, and measured reaction-diffusion dynamics at the single-cell level up to the multicell scale. Using a cell-free gene network we programmed molecular interactions that control the frequency of oscillations, population variability, and dynamical stability. We observed frequency entrainment, synchronized oscillatory reactions and pattern formation in space, as manifestation of collective behavior. The transition to synchrony occurs as the local coupling between compartments strengthens. Spatiotemporal oscillations are induced either by a concentration gradient of a diffusible signal, or by spontaneous symmetry breaking close to a transition from oscillatory to nonoscillatory dynamics. This work offers design principles for programmable biochemical reactions with potential applications to autonomous sensing, distributed computing, and biomedical diagnostics.

Droplet microfluidics for synthetic biology

Synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to most researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.

Massively parallel and multiparameter titration of biochemical assays with droplet microfluidics

Biochemical systems in which multiple components take part in a given reaction are of increasing interest. Because the interactions between these different components are complex and difficult to predict from basic reaction kinetics, it is important to test for the effect of variations in the concentration for each reagent in a combinatorial manner. For example, in PCR, an increase in the concentration of primers initially increases template amplification, but large amounts of primers result in primer-dimer by-products that inhibit the amplification of the template. Manual titration of biochemical mixtures rapidly becomes costly and laborious, forcing scientists to settle for suboptimal concentrations. Here we present a droplet-based microfluidics platform for mapping of the concentration space of up to three reaction components followed by detection with a fluorescent readout. The concentration of each reaction component is read through its internal standard (barcode), which is fluorescent but chemically orthogonal. We describe in detail the workflow, which comprises the following: (i) production of the microfluidics chips, (ii) preparation of the biochemical mixes, (iii) their mixing and compartmentalization into water-in-oil emulsion droplets via microfluidics, (iv) incubation and imaging of the fluorescent barcode and reporter signals by fluorescence microscopy and (v) image processing and data analysis. We also provide recommendations for choosing the appropriate fluorescent markers, programming the pressure profiles and analyzing the generated data. Overall, this platform allows a researcher with a few weeks of training to acquire ∼10,000 data points (in a 1D, 2D or 3D concentration space) over the course of a day from as little as 100-1,000 μl of reaction mix.

Phagocytosis-inspired behaviour in synthetic protocell communities of compartmentalized colloidal objects

The spontaneous assembly of micro-compartmentalized colloidal objects capable of controlled interactions offers a step towards rudimentary forms of collective behaviour in communities of artificial cell-like entities (synthetic protocells). Here we report a primitive form of artificial phagocytosis in a binary community of synthetic protocells in which multiple silica colloidosomes are selectively ingested by self-propelled magnetic Pickering emulsion (MPE) droplets comprising particle-free fatty acid-stabilized apertures. Engulfment of the colloidosomes enables selective delivery and release of water-soluble payloads, and can be coupled to enzyme activity within the MPE droplets. Our results highlight opportunities for the development of new materials based on consortia of colloidal objects, and provide a novel microscale engineering approach to inducing higher-order behaviour in mixed populations of synthetic protocells.

Synthetic quorum sensing in model microcapsule colonies

Biological quorum sensing refers to the ability of cells to gauge their population density and collectively initiate a new behavior once a critical density is reached. Designing synthetic materials systems that exhibit quorum sensing-like behavior could enable the fabrication of devices with both self-recognition and self-regulating functionality. Herein, we develop models for a colony of synthetic microcapsules that communicate by producing and releasing signaling molecules. Production of the chemicals is regulated by a biomimetic negative feedback loop, the "repressilator" network. Through theory and simulation, we show that the chemical behavior of such capsules is sensitive to both the density and number of capsules in the colony. For example, decreasing the spacing between a fixed number of capsules can trigger a transition in chemical activity from the steady, repressed state to large-amplitude oscillations in chemical production. Alternatively, for a fixed density, an increase in the number of capsules in the colony can also promote a transition into the oscillatory state. This configuration-dependent behavior of the capsule colony exemplifies quorum-sensing behavior. Using our theoretical model, we predict the transitions from the steady state to oscillatory behavior as a function of the colony size and capsule density.

Chemical and Biological Dynamics Using Droplet-Based Microfluidics

Recent years have witnessed an increased use of droplet-based microfluidic techniques in a wide variety of chemical and biological assays. Nevertheless, obtaining dynamic data from these platforms has remained challenging, as this often requires reading the same droplets (possibly thousands of them) multiple times over a wide range of intervals (from milliseconds to hours). In this review, we introduce the elemental techniques for the formation and manipulation of microfluidic droplets, together with the most recent developments in these areas. We then discuss a wide range of analytical methods that have been successfully adapted for analyte detection in droplets. Finally, we highlight a diversity of studies where droplet-based microfluidic strategies have enabled the characterization of dynamic systems that would otherwise have remained unexplorable.

Artificial cell mimics as simplified models for the study of cell biology

Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.

Synthetic Biology-The Synthesis of Biology

Synthetic biology concerns the engineering of man-made living biomachines from standardized components that can perform predefined functions in a (self-)controlled manner. Different research strategies and interdisciplinary efforts are pursued to implement engineering principles to biology. The "top-down" strategy exploits nature's incredible diversity of existing, natural parts to construct synthetic compositions of genetic, metabolic, or signaling networks with predictable and controllable properties. This mainly application-driven approach results in living factories that produce drugs, biofuels, biomaterials, and fine chemicals, and results in living pills that are based on engineered cells with the capacity to autonomously detect and treat disease states in vivo. In contrast, the "bottom-up" strategy seeks to be independent of existing living systems by designing biological systems from scratch and synthesizing artificial biological entities not found in nature. This more knowledge-driven approach investigates the reconstruction of minimal biological systems that are capable of performing basic biological phenomena, such as self-organization, self-replication, and self-sustainability. Moreover, the syntheses of artificial biological units, such as synthetic nucleotides or amino acids, and their implementation into polymers inside living cells currently set the boundaries between natural and artificial biological systems. In particular, the in vitro design, synthesis, and transfer of complete genomes into host cells point to the future of synthetic biology: the creation of designer cells with tailored desirable properties for biomedicine and biotechnology.

Cell Guidance on Nanostructured Metal Based Surfaces

Metal surface nanostructuring to guide cell behavior is an attractive strategy to improve parts of medical implants, lab-on-a-chip, soft robotics, self-assembled microdevices, and bionic devices. Here, we discus important parameters, relevant trends, and specific examples of metal surface nanostructuring to guide cell behavior on metal-based hybrid surfaces. Surface nanostructuring allows precise control of cell morphology, adhesion, internal organization, and function. Pre-organized metal nanostructuring and dynamic stimuli-responsive surfaces are used to study various cell behaviors. For cells dynamics control, the oscillating stimuli-responsive layer-by-layer (LbL) polyelectrolyte assemblies are discussed to control drug delivery, coating thickness, and stiffness. LbL films can be switched "on demand" to change their thickness, stiffness, and permeability in the dynamic real-time processes. Potential applications of metal-based hybrids in biotechnology and selected examples are discussed.

Engineering chemical reaction modules via programming the assembly of DNA hairpins

The architect of enzyme-free chemical reaction modules, working as building blocks in implementing complex computing tasks, was achieved by modulating the assembly of DNA hairpins, including non-catalytic and catalytic systems. The performance of heterogeneous outputted sequences, which were programmed on different hairpins for triggering the downstream reaction, was asymmetric in the non-catalytic system, whereas symmetric in the catalytic system. Furthermore, complicated DNA-only chemical modules possessing controllable species of inputs or outputs were constructed based on our strategy. The kinetic studies revealed that the performance of the chemical modules was toehold length correlated; on the basis of which, a DNA concentration monitor was constructed.

Biologically inspired design of feedback control systems implemented using DNA strand displacement reactions

The use of abstract chemical reaction networks (CRNs) as a modelling and design framework for the implementation of computing and control circuits using enzyme-free, entropy driven DNA strand displacement (DSD) reactions is starting to garner widespread attention in the area of synthetic biology. Previous work in this area has demonstrated the theoretical plausibility of using this approach to design biomolecular feedback control systems based on classical proportional-integral (PI) controllers, which may be constructed from CRNs implementing gain, summation and integrator operators. Here, we propose an alternative design approach that utilises the abstract chemical reactions involved in cellular signalling cycles to implement a biomolecular controller - termed a signalling-cycle (SC) controller. We compare the performance of the PI and SC controllers in closed-loop with a nonlinear second-order chemical process. Our results show that the SC controller outperforms the PI controller in terms of both performance and robustness, and also requires fewer abstract chemical reactions to implement, highlighting its potential usefulness in the construction of biomolecular control circuits.

Multiplexed fluorescence readout using time responses of color coded signals for biomolecular detection

Fluorescence readout is an important technique for detecting biomolecules. In this paper, we present a multiplexed fluorescence readout method using time varied fluorescence signals. To generate the fluorescence signals, coded strands and a set of universal molecular beacons are introduced. Each coded strand represents the existence of an assigned target molecule. The coded strands have coded sequences to generate temporary fluorescence signals through binding to the molecular beacons. The signal generating processes are modeled based on the reaction kinetics between the coded strands and molecular beacons. The model is used to decode the detected fluorescence signals using maximum likelihood estimation. Multiplexed fluorescence readout was experimentally demonstrated with three molecular beacons. Numerical analysis showed that the readout accuracy was enhanced by the use of time-varied fluorescence signals.

Hydrazone Switch-Based Negative Feedback Loop

A negative feedback loop that relies on the coordination-coupled deprotonation (CCD) of a hydrazone switch has been developed. Above a particular threshold of zinc(II), CCD releases enough protons to the environment to trigger a cascade of reactions that yield an imine. This imine sequesters the excess of zinc(II) from the hydrazone switch, hence lowering the effective amount of protons, and switching the cascade reactions "OFF", thus establishing the negative feedback loop.

Predatory behaviour in synthetic protocell communities

Recent progress in the chemical construction of colloidal objects comprising integrated biomimetic functions is paving the way towards rudimentary forms of artificial cell-like entities (protocells). Although several new types of protocells are currently available, the design of synthetic protocell communities and investigation of their collective behaviour has received little attention. Here we demonstrate an artificial form of predatory behaviour in a community of protease-containing coacervate microdroplets and protein-polymer microcapsules (proteinosomes) that interact via electrostatic binding. The coacervate microdroplets act as killer protocells for the obliteration of the target proteinosome population by protease-induced lysis of the protein-polymer membrane. As a consequence, the proteinosome payload (dextran, single-stranded DNA, platinum nanoparticles) is trafficked into the attached coacervate microdroplets, which are then released as functionally modified killer protocells capable of rekilling. Our results highlight opportunities for the development of interacting artificial protocell communities, and provide a strategy for inducing collective behaviour in soft matter microcompartmentalized systems and synthetic protocell consortia.

Inference of gene regulation functions from dynamic transcriptome data

To quantify gene regulation, a function is required that relates transcription factor binding to DNA (input) to the rate of mRNA synthesis from a target gene (output). Such a ‘gene regulation function’ (GRF) generally cannot be measured because the experimental titration of inputs and simultaneous readout of outputs is difficult. Here we show that GRFs may instead be inferred from natural changes in cellular gene expression, as exemplified for the cell cycle in the yeast S. cerevisiae. We develop this inference approach based on a time series of mRNA synthesis rates from a synchronized population of cells observed over three cell cycles. We first estimate the functional form of how input transcription factors determine mRNA output and then derive GRFs for target genes in the CLB2 gene cluster that are expressed during G2/M phase. Systematic analysis of additional GRFs suggests a network architecture that rationalizes transcriptional cell cycle oscillations. We find that a transcription factor network alone can produce oscillations in mRNA expression, but that additional input from cyclin oscillations is required to arrive at the native behaviour of the cell cycle oscillator.

DOI:http://dx.doi.org/10.7554/eLife.12188.001

Living cells rely on networks of genes to control their behavior, including how they grow, develop and respond to stress. Genes encode instructions needed to make proteins and other molecules, and much of the control is exerted at the first stage of protein production, known as transcription. During this process, a gene is copied to make molecules known as transcripts that may later be used as templates to make proteins.

Many genes encode proteins that act to regulate transcription. Therefore, an individual gene may receive inputs from other genes, and these inputs affect how much transcript the gene produces, which can be considered as the gene’s output. While these inputs and outputs can often be wired together to form a network, it is less clear exactly how all the different inputs at a gene interact to determine its output. These interactions are known as “gene regulation functions”, and knowing them would be an important step towards understanding gene networks, which would help us to predict how cells will behave in different situations.

Gene regulation functions are difficult to measure directly, so researchers would like to find other ways to assess them indirectly. A recently developed experimental technique called “dynamic transcriptome analysis” seemed promising as it measures both the inputs and outputs of all genes in a cell over time. Hillenbrand et al. used this technique to infer gene regulation functions with one or two inputs in yeast cells.

Comparing these estimates with experimental data from previous studies showed that these inferred gene regulation functions could successfully predict the output of a gene based on its inputs. Hillenbrand et al. then used these estimates to search and model a well-known genetic network that is thought to be part of the molecular clockwork that controls the timing of events that cause a cell to divide.

Currently, the approach used by Hillenbrand et al. treats gene regulation functions like “black boxes”. This means that, while an output can be predicted if the inputs are known, it cannot reveal all of the detailed mechanisms behind it. Gaining insights into the inner workings of these black boxes will require taking more data into account, such as how abundant the proteins that regulate transcription are, where they are located within cells or whether they are active or not. Therefore, the next challenge is to incorporate these kinds of data to gain a fuller picture of how gene networks operate within cells.

DOI:http://dx.doi.org/10.7554/eLife.12188.002

Analog Computation by DNA Strand Displacement Circuits

DNA circuits have been widely used to develop biological computing devices because of their high programmability and versatility. Here, we propose an architecture for the systematic construction of DNA circuits for analog computation based on DNA strand displacement. The elementary gates in our architecture include addition, subtraction, and multiplication gates. The input and output of these gates are analog, which means that they are directly represented by the concentrations of the input and output DNA strands, respectively, without requiring a threshold for converting to Boolean signals. We provide detailed domain designs and kinetic simulations of the gates to demonstrate their expected performance. On the basis of these gates, we describe how DNA circuits to compute polynomial functions of inputs can be built. Using Taylor Series and Newton Iteration methods, functions beyond the scope of polynomials can also be computed by DNA circuits built upon our architecture.

The nanotechnology of life-inspired systems

For some decades now, nanotechnology has been touted as the 'next big thing' with potential impact comparable to the steam, electricity or Internet revolutions - but has it lived up to these expectations? While advances in top-down nanolithography, now reaching 10-nm resolution, have resulted in devices that are rapidly approaching mass production, attempts to produce nanoscale devices using bottom-up approaches have met with only limited success. We have been inundated with nanoparticles of almost any shape, material and composition, but their societal impact has been far from revolutionary, with growing concerns over their toxicity. Despite nebulous hopes that making hierarchical nanomaterials will lead to new, emergent properties, no breakthrough applications seem imminent. In this Perspective, we argue that the time is ripe to look beyond individual nano-objects and their static assemblies, and instead focus on systems comprising different types of 'nanoparts' interacting and/or communicating with one another to perform desired functions. Such systems are interesting for a variety of reasons: they can act autonomously without external electrical or optical connections, can be dynamic and reconfigurable, and can act as 'nanomachines' by directing the flow of mass, energy or information . In thinking how this systems nanoscience approach could be implemented to design useful - as opposed to toy-model - nanosystems, our choice of applications and our nanoengineering should be inspired by living matter.

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.

Enzymatic reactions in confined environments

Within each biological cell, surface- and volume-confined enzymes control a highly complex network of chemical reactions. These reactions are efficient, timely, and spatially defined. Efforts to transfer such appealing features to in vitro systems have led to several successful examples of chemical reactions catalysed by isolated and immobilized enzymes. In most cases, these enzymes are either bound or adsorbed to an insoluble support, physically trapped in a macromolecular network, or encapsulated within compartments. Advanced applications of enzymatic cascade reactions with immobilized enzymes include enzymatic fuel cells and enzymatic nanoreactors, both for in vitro and possible in vivo applications. In this Review, we discuss some of the general principles of enzymatic reactions confined on surfaces, at interfaces, and inside small volumes. We also highlight the similarities and differences between the in vivo and in vitro cases and attempt to critically evaluate some of the necessary future steps to improve our fundamental understanding of these systems.

Molecular Titration Promotes Oscillations and Bistability in Minimal Network Models with Monomeric Regulators

Molecular titration is emerging as an important biochemical interaction mechanism within synthetic devices built with nucleic acids and the CRISPR/Cas system. We show that molecular titration in the context of feedback circuits is a suitable mechanism to enhance the emergence of oscillations and bistable behaviors. We consider biomolecular modules that can be inhibited or activated by input monomeric regulators; the regulators compete with constitutive titrating species to determine the activity of their target. By tuning the titration rate and the concentration of titrating species, it is possible to modulate the delay and convergence speed of the transient response, and the steepness and dead zone of the stationary response of the modules. These phenomena favor the occurrence of oscillations when modules are interconnected to create a negative feedback loop; bistability is favored in a positive feedback interconnection. Numerical simulations are supported by mathematical analysis showing that the capacity of the closed loop systems to exhibit oscillations or bistability is structural.

Cathepsin B launches an apoptotic exit effort upon cell death-associated disruption of lysosomes

The release of cathepsin proteases from disrupted lysosomes results in lethal cellular autodigestion. Lysosomal disruption-related cell death is highly variable, showing both apoptotic and necrotic outcomes. As the substrate spectrum of lysosomal proteases encompasses the apoptosis-regulating proteins of the Bcl-2 family, their degradation could influence the cell death outcome upon lysosomal disruption. We used Förster resonance energy transfer (FRET)-based biosensors to image the real-time degradation of the Bcl-2-family members, Bcl-xl, Bax and Bid, in living cells undergoing lysosomal lysis and identified an early chain of proteolytic events, initiated by the release of cathepsin B, which directs cells toward apoptosis. In this apoptotic exit strategy, cathepsin B’s proteolytic activity results in apoptosis-inducing Bid and removes apoptosis-preventing Bcl-xl. Cathepsin B furthermore appears to degrade a cystein protease that would otherwise have eliminated apoptosis-supporting Bax, indirectly keeping cellular levels of the Bax protein up. The concerted effort of these three early events shifts the balance of cell fate away from necrosis and toward apoptosis.

Sustainability of Transient Kinetic Regimes and Origins of Death

It is generally recognized that a distinguishing feature of life is its peculiar capability to avoid equilibration. The origin of this capability and its evolution along the timeline of abiogenesis is not yet understood. We propose to study an analog of this phenomenon that could emerge in non-biological systems. To this end, we introduce the concept of sustainability of transient kinetic regimes. This concept is illustrated via investigation of cooperative effects in an extended system of compartmentalized chemical oscillators under batch and semi-batch conditions. The computational study of a model system shows robust enhancement of lifetimes of the decaying oscillations which translates into the evolution of the survival function of the transient non-equilibrium regime. This model does not rely on any form of replication. Rather, it explores the role of a structured effective environment as a contributor to the system-bath interactions that define non-equilibrium regimes. We implicate the noise produced by the effective environment of a compartmentalized oscillator as the cause of the lifetime extension.

Macromolecular crowding creates heterogeneous environments of gene expression in picolitre droplets

Understanding the dynamics of complex enzymatic reactions in highly crowded small volumes is crucial for the development of synthetic minimal cells. Compartmentalized biochemical reactions in cell-sized containers exhibit a degree of randomness due to the small number of molecules involved. However, it is unknown how the physical environment contributes to the stochastic nature of multistep enzymatic processes. Here, we present a robust method to quantify gene expression noise in vitro using droplet microfluidics. We study the changes in stochasticity in the cell-free gene expression of two genes compartmentalized within droplets as a function of DNA copy number and macromolecular crowding. We find that decreased diffusion caused by a crowded environment leads to the spontaneous formation of heterogeneous microenvironments of mRNA as local production rates exceed the diffusion rates of macromolecules. This heterogeneity leads to a higher probability of the molecular machinery staying in the same microenvironment, directly increasing the system's stochasticity.

Pulse-density modulation control of chemical oscillation far from equilibrium in a droplet open-reactor system

The design, construction and control of artificial self-organized systems modelled on dynamical behaviours of living systems are important issues in biologically inspired engineering. Such systems are usually based on complex reaction dynamics far from equilibrium; therefore, the control of non-equilibrium conditions is required. Here we report a droplet open-reactor system, based on droplet fusion and fission, that achieves dynamical control over chemical fluxes into/out of the reactor for chemical reactions far from equilibrium. We mathematically reveal that the control mechanism is formulated as pulse-density modulation control of the fusion–fission timing. We produce the droplet open-reactor system using microfluidic technologies and then perform external control and autonomous feedback control over autocatalytic chemical oscillation reactions far from equilibrium. We believe that this system will be valuable for the dynamical control over self-organized phenomena far from equilibrium in chemical and biomedical studies.

Biological systems typically operate at conditions far from chemical equilibrium. Here, the authors model and develop a microfluidic reactor allowing control over time-variable supply and dissipation of chemicals by droplet fusion and fission, allowing non-equilibrium chemical reactions to be regulated.

Biocompatible fluorinated polyglycerols for droplet microfluidics as an alternative to PEG-based copolymer surfactants

In droplet-based microfluidics, non-ionic, high-molecular weight surfactants are required to stabilize droplet interfaces. One of the most common structures that imparts stability as well as biocompatibility to water-in-oil droplets is a triblock copolymer surfactant composed of perfluoropolyether (PFPE) and polyethylene glycol (PEG) blocks. However, the fast growing applications of microdroplets in biology would benefit from a larger choice of specialized surfactants. PEG as a hydrophilic moiety, however, is a very limited tool in surfactant modification as one can only vary the molecular weight and chain-end functionalization. In contrast, linear polyglycerol offers further side-chain functionalization to create custom-tailored, biocompatible droplet interfaces. Herein, we describe the synthesis and characterization of polyglycerol-based triblock surfactants with tailored side-chain composition, and exemplify their application in cell encapsulation and in vitro gene expression studies in droplet-based microfluidics.

Building a Synthetic Transcriptional Oscillator

Reaction circuits mimicking genetic oscillators can be realized with synthetic, switchable DNA genes (so-called genelets), and two enzymes only, an RNA polymerase and a ribonuclease. The oscillatory behavior of the genelets is driven by the periodic production and degradation of RNA effector molecules. Here, we describe the preparation, assembly, and testing of a synthetic, transcriptional two-node negative-feedback oscillator, whose dynamics can be followed in real-time by fluorescence read-out.

Tactic, reactive, and functional droplets outside of equilibrium

Droplets subject to non-equilibrium conditions can exhibit a range of biomimetic and “intelligent” behaviors.

Fuel-Controlled Reassembly of Metal-Organic Architectures

Many examples exist of biological self-assembled structures that restructure in response to external stimuli, then return to their previous state over a defined time scale, but most synthetic investigations so far have focused on systems that switch between states representing energetic minima upon stimulus application. Here we report an approach in which triphenylphosphine is used as a chemical fuel to maintain Cu^I-based self-assembled metallosupramolecular architectures for defined periods of time. This method was used to exert control over the threading and dethreading of the ring of a pseudorotaxane's axle, as well as to direct the uptake and release of a guest from a metal-organic host. Management of the amount of fuel and catalyst added allowed for time-dependent regulation of product concentration.

Partitioning Variability of a Compartmentalized In Vitro Transcriptional Thresholding Circuit

Encapsulation of in vitro biochemical reaction circuits into small, cell-sized compartments can result in considerable variations in the dynamical properties of the circuits. As a model system, we here investigate a simple in vitro transcriptional reaction circuit, which generates an ultrasensitive fluorescence response when the concentration of an RNA transcript reaches a preset threshold. The reaction circuit is compartmentalized into spherical water-in-oil microemulsion droplets, and the reaction progress is monitored by fluorescence microscopy. A quantitative statistical analysis of thousands of individual droplets ranging in size from a few up to 20 μm reveals a strong variability in effective RNA production rates, which by computational modeling is traced back to a larger-than-Poisson variability in RNAP activities in the droplets. The noise level in terms of the noise strength (the Fano factor) is strongly dependent on the ratio between transcription templates and polymerases, and increases for higher template concentrations.

Automated design of programmable enzyme-driven DNA circuits

Molecular programming allows for the bottom-up engineering of biochemical reaction networks in a controlled in vitro setting. These engineered biochemical reaction networks yield important insight in the design principles of biological systems and can potentially enrich molecular diagnostic systems. The DNA polymerase-nickase-exonuclease (PEN) toolbox has recently been used to program oscillatory and bistable biochemical networks using a minimal number of components. Previous work has reported the automatic construction of in silico descriptions of biochemical networks derived from the PEN toolbox, paving the way for generating networks of arbitrary size and complexity in vitro. Here, we report an automated approach that further bridges the gap between an in silico description and in vitro realization. A biochemical network of arbitrary complexity can be globally screened for parameter values that display the desired function and combining this approach with robustness analysis further increases the chance of successful in vitro implementation. Moreover, we present an automated design procedure for generating optimal DNA sequences, exhibiting key characteristics deduced from the in silico analysis. Our in silico method has been tested on a previously reported network, the Oligator, and has also been applied to the design of a reaction network capable of displaying adaptation in one of its components. Finally, we experimentally characterize unproductive sequestration of the exonuclease to phosphorothioate protected ssDNA strands. The strong nonlinearities in the degradation of active components caused by this unintended cross-coupling are shown computationally to have a positive effect on adaptation quality.

Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models

Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.