A bistable genetic switch based on designable DNA-binding domains

The art of designed coiled-coils for the regulation of mammalian cells

Synthetic biology aims to engineer complex biological systems using modular elements, with coiled-coil (CC) dimer-forming modules are emerging as highly useful building blocks in the regulation of protein assemblies and biological processes. Those small modules facilitate highly specific and orthogonal protein-protein interactions, offering versatility for the regulation of diverse biological functions. Additionally, their design rules enable precise control and tunability over these interactions, which are crucial for specific applications. Recent advancements showcase their potential for use in innovative therapeutic interventions and biomedical applications. In this review, we discuss the potential of CCs, exploring their diverse applications in mammalian cells, such as synthetic biological circuit design, transcriptional and allosteric regulation, cellular assemblies, chimeric antigen receptor (CAR) T cell regulation, and genome editing and their role in advancing the understanding and regulation of cellular processes.

Accelerating Diverse Cell-Based Therapies Through Scalable Design

Augmenting cells with novel, genetically encoded functions will support therapies that expand beyond natural capacity for immune surveillance and tissue regeneration. However, engineering cells at scale with transgenic cargoes remains a challenge in realizing the potential of cell-based therapies. In this review, we introduce a range of applications for engineering primary cells and stem cells for cell-based therapies. We highlight tools and advances that have launched mammalian cell engineering from bioproduction to precision editing of therapeutically relevant cells. Additionally, we examine how transgenesis methods and genetic cargo designs can be tailored for performance. Altogether, we offer a vision for accelerating the translation of innovative cell-based therapies by harnessing diverse cell types, integrating the expanding array of synthetic biology tools, and building cellular tools through advanced genome writing techniques.

Integrated compact regulators of protein activity enable control of signaling pathways and genome-editing in vivo

Viral proteases and clinically safe inhibitors were employed to build integrated compact regulators of protein activity (iCROP) for post-translational regulation of functional proteins by tunable proteolytic activity. In the absence of inhibitor, the co-localized/fused protease cleaves a target peptide sequence introduced in an exposed loop of the protein of interest, irreversibly fragmenting the protein structure and destroying its functionality. We selected three proteases and demonstrated the versatility of the iCROP framework by validating it to regulate the functional activity of ten different proteins. iCROP switches can be delivered either as mRNA or DNA, and provide rapid actuation kinetics with large induction ratios, while remaining strongly suppressed in the off state without inhibitor. iCROPs for effectors of the NF-κB and NFAT signaling pathways were assembled and confirmed to enable precise activation/inhibition of downstream events in response to protease inhibitors. In lipopolysaccharide-treated mice, iCROP-sr-IκBα suppressed cytokine release ("cytokine storm") by rescuing the activity of IκBα, which suppresses NF-κB signaling. We also constructed compact inducible CRISPR-(d)Cas9 variants and showed that iCROP-Cas9-mediated knockout of the PCSK9 gene in the liver lowered blood LDL-cholesterol levels in mice. iCROP-based protein switches will facilitate protein-level regulation in basic research and translational applications.

Engineered combinatorial cell device for wound healing and bone regeneration

Growth factors are the key regulators that promote tissue regeneration and healing processes. While the effects of individual growth factors are well documented, a combination of multiple secreted growth factors underlies stem cell-mediated regeneration. To avoid the potential dangers and labor-intensive individual approach of stem cell therapy while maintaining their regeneration-promoting effects based on multiple secreted growth factors, we engineered a "mix-and-match" combinatorial platform based on a library of cell lines producing growth factors. Treatment with a combination of growth factors secreted by engineered mammalian cells was more efficient than with individual growth factors or even stem cell-conditioned medium in a gap closure assay. Furthermore, we implemented in a mouse model a device for allogenic cell therapy for an in situ production of growth factors, where it improved cutaneous wound healing. Augmented bone regeneration was achieved on calvarial bone defects in rats treated with a cell device secreting IGF, FGF, PDGF, TGF-β, and VEGF. In both in vivo models, the systemic concentration of secreted factors was negligible, demonstrating the local effect of the regeneration device. Finally, we introduced a genetic switch that enables temporal control over combinations of trophic factors released at different stages of regeneration mimicking the maturation of natural wound healing to improve therapy and prevent scar formation.

A positive mechanobiological feedback loop controls bistable switching of cardiac fibroblast phenotype

Cardiac fibrosis is associated with activation of cardiac fibroblasts (CFs), a pathological, phenotypic transition that is widely believed to be irreversible in the late stages of disease development. Sensing of a stiffened mechanical environment through regulation of integrin-based adhesion plaques and activation of the Piezo1 mechanosensitive ion channel is known to factor into this transition. Here, using integrated in vitro and in silico models, we discovered a mutually reinforcing, mechanical positive feedback loop between integrin β1 and Piezo1 activation that forms a bistable switch. The bistable switch is initiated by perturbations in matrix elastic modulus that amplify to trigger downstream signaling involving Ca²⁺ and YAP that, recursively, leads fibroblasts to further stiffen their environment. By simultaneously interfering with the newly identified mechanical positive feedback loop and modulating matrix elastic modulus, we reversed markers of phenotypical transition of CF, suggesting new therapeutic targets for fibrotic disease.

Model-Based Investigation of the Relationship between Regulation Level and Pulse Property of I1-FFL Gene Circuits

Mathematical models are powerful tools in guiding the construction of synthetic biological circuits, given their capability of accurately capturing and predicting circuit dynamics. Recent innovations in RNA technology have enabled the development of a variety of new tools for regulating gene expression at both the transcription and translation levels. However, the effects of different regulation levels on the circuit dynamics remain largely unexplored. In this study, we focus on the type 1 incoherent feed-forward loop (I1-FFL) gene circuit with four different variations (TX, TL, HY-1, HY-2), to investigate how regulation at the transcription and translation levels affect the circuit dynamics. We develop a mechanistic model for each of the four circuits and deploy sensitivity analysis to investigate the circuits' dynamics in terms of pulse generation. Based on the analysis, we observe that the repression regulation mechanism dominates the characteristics of the pulse as compared to the activation regulation mechanism and find that the I1-FFL with transcription repression has a higher chance of generating a pulse meeting the desired criteria. The experimental results in Escherichia coli also confirm our findings from the computational analysis. We expect our findings to facilitate future experimental construction of gene circuits with insights on the selection of appropriate transcription and translation regulation tools.

PERSIST platform provides programmable RNA regulation using CRISPR endoRNases

Regulated transgene expression is an integral component of gene therapies, cell therapies and biomanufacturing. However, transcription factor-based regulation, upon which most applications are based, suffers from complications such as epigenetic silencing that limit expression longevity and reliability. Constitutive transgene transcription paired with post-transcriptional gene regulation could combat silencing, but few such RNA- or protein-level platforms exist. Here we develop an RNA-regulation platform we call "PERSIST" which consists of nine CRISPR-specific endoRNases as RNA-level activators and repressors as well as modular OFF- and ON-switch regulatory motifs. We show that PERSIST-regulated transgenes exhibit strong OFF and ON responses, resist silencing for at least two months, and can be readily layered to construct cascades, logic functions, switches and other sophisticated circuit topologies. The orthogonal, modular and composable nature of this platform as well as the ease in constructing robust and predictable gene circuits promises myriad applications in gene and cell therapies.

A robust method for designing multistable systems by embedding bistable subsystems

Although multistability is an important dynamic property of a wide range of complex systems, it is still a challenge to develop mathematical models for realising high order multistability using realistic regulatory mechanisms. To address this issue, we propose a robust method to develop multistable mathematical models by embedding bistable models together. Using the GATA1-GATA2-PU.1 module in hematopoiesis as the test system, we first develop a tristable model based on two bistable models without any high cooperative coefficients, and then modify the tristable model based on experimentally determined mechanisms. The modified model successfully realises four stable steady states and accurately reflects a recent experimental observation showing four transcriptional states. In addition, we develop a stochastic model, and stochastic simulations successfully realise the experimental observations in single cells. These results suggest that the proposed method is a general approach to develop mathematical models for realising multistability and heterogeneity in complex systems.

Regulation of protein secretion through chemical regulation of endoplasmic reticulum retention signal cleavage

Secreted proteins, such as hormones or cytokines, are key mediators in multicellular organisms. Response of protein secretion based on transcriptional control is rather slow, as it requires transcription, translation and transport from the endoplasmic reticulum (ER) to the plasma membrane via the conventional protein secretion (CPS) pathway. An alternative regulation to provide faster response would be valuable. Here we present two genetically encoded orthogonal regulatory secretion systems, which rely on the retention of pre-synthesized proteins on the ER membrane (membER, released by a cytosolic protease) or inside the ER lumen (lumER, released by an ER-luminal protease), respectively, and their release by the chemical signal-regulated proteolytic removal of an ER-retention signal, without triggering ER stress due to protein aggregates. Design of orthogonal chemically-regulated split proteases enables the combination of signals into logic functions. Its application was demonstrated on a chemically regulated therapeutic protein secretion and regulated membrane translocation of a chimeric antigen receptor (CAR) targeting cancer antigen. Regulation of the ER escape represents a platform for the design of fast-responsive and tightly-controlled modular and scalable protein secretion system for mammalian cells.

Secreted proteins, such as hormones or cytokines, are key mediators in multicellular organisms. Here the authors present two genetically encoded orthogonal regulatory secretion systems that enables inducible protein release and construction of logic gates.

Synthetic multistability in mammalian cells

In multicellular organisms, gene regulatory circuits generate thousands of molecularly distinct, mitotically heritable states through the property of multistability. Designing synthetic multistable circuits would provide insight into natural cell fate control circuit architectures and would allow engineering of multicellular programs that require interactions among distinct cell types. We created MultiFate, a naturally inspired, synthetic circuit that supports long-term, controllable, and expandable multistability in mammalian cells. MultiFate uses engineered zinc finger transcription factors that transcriptionally self-activate as homodimers and mutually inhibit one another through heterodimerization. Using a model-based design, we engineered MultiFate circuits that generate as many as seven states, each stable for at least 18 days. MultiFate permits controlled state switching and modulation of state stability through external inputs and can be expanded with additional transcription factors. These results provide a foundation for engineering multicellular behaviors in mammalian cells.

Virtual Parts Repository 2: Model-Driven Design of Genetic Regulatory Circuits

Engineering genetic regulatory circuits is key to the creation of biological applications that are responsive to environmental changes. Computational models can assist in understanding especially large and complex circuits for which manual analysis is infeasible, permitting a model-driven design process. However, there are still few tools that offer the ability to simulate the system under design. One of the reasons for this is the lack of accessible model repositories or libraries that cater to the modular composition of models of synthetic systems. Here, we present the second version of the Virtual Parts Repository, a framework to facilitate the model-driven design of genetic regulatory circuits, which provides reusable, modular, and composable models. The new framework is service-oriented, easier to use in computational workflows, and provides several new features and access methods. New features include supporting hierarchical designs via a graph-based repository or compatible remote repositories, enriching existing designs, and using designs provided in Synthetic Biology Open Language documents to derive system-scale and hierarchical Systems Biology Markup Language models. We also present a reaction-based modeling abstraction inspired by rule-based modeling techniques to facilitate scalable and modular modeling of complex and large designs. This modeling abstraction enhances the modeling capability of the framework, for example, to incorporate design patterns such as roadblocking, distributed deployment of genetic circuits using plasmids, and cellular resource dependency. The framework and the modeling abstraction presented in this paper allow computational design tools to take advantage of computational simulations and ultimately help facilitate more predictable applications.

Photoredox-catalyzed hydroxymethylation of β-ketoesters: application to the synthesis of [3.3.3] propellane lactones

Photoredox-catalysed hydroxymethylation of β-ketoesters substituted by an allyl subunit on the α-position afforded directly the corresponding bicyclic lactones possessing both a hydroxy group and an unsaturation. A subsequent regioselective iodoetherification led to the formation of original [3.3.3] propellane structures. Substitution of the iodine atom by various nucleophiles afforded highly functionnalized structures including triazolomethyl derivatives.

Rational design of complex phenotype via network models

We demonstrate a modeling and computational framework that allows for rapid screening of thousands of potential network designs for particular dynamic behavior. To illustrate this capability we consider the problem of hysteresis, a prerequisite for construction of robust bistable switches and hence a cornerstone for construction of more complex synthetic circuits. We evaluate and rank most three node networks according to their ability to robustly exhibit hysteresis where robustness is measured with respect to parameters over multiple dynamic phenotypes. Focusing on the highest ranked networks, we demonstrate how additional robustness and design constraints can be applied. We compare our results to more traditional methods based on specific parameterization of ordinary differential equation models and demonstrate a strong qualitative match at a small fraction of the computational cost.

A major challenge in the domains of systems and synthetic biology is an inability to efficiently predict function(s) of complex networks. This work demonstrates a modeling and computational framework that allows for a mathematically justifiable rigorous screening of thousands of potential network designs for a wide variety of dynamical behavior. We screen all 3-node genetic networks and rank them based on their ability to act as an inducible bistable switch. Our results are summarized in a searchable database that can be used to construct robust switches. The ability to quickly screen thousands of designs significantly reduces the set of viable designs and allows synthetic biologists to focus their experimental and more traditional modeling tools to this much smaller set.

An engineered protein-phosphorylation toggle network with implications for endogenous network discovery

Synthetic biological networks comprising fast, reversible reactions could enable engineering of new cellular behaviors that are not possible with slower regulation. Here, we created a bistable toggle switch in Saccharomyces cerevisiae using a cross-repression topology comprising 11 protein-protein phosphorylation elements. The toggle is ultrasensitive, can be induced to switch states in seconds, and exhibits long-term bistability. Motivated by our toggle's architecture and size, we developed a computational framework to search endogenous protein pathways for other large and similar bistable networks. Our framework helped us to identify and experimentally verify five formerly unreported endogenous networks that exhibit bistability. Building synthetic protein-protein networks will enable bioengineers to design fast sensing and processing systems, allow sophisticated regulation of cellular processes, and aid discovery of endogenous networks with particular functions.

Designing an irreversible metabolic switch for scalable induction of microbial chemical production

Bacteria can be harnessed to synthesise high-value chemicals. A promising strategy for increasing productivity uses inducible control systems to switch metabolism from growth to chemical synthesis once a large population of cell factories are generated. However, use of expensive chemical inducers limits scalability of this approach for biotechnological applications. Switching using cheap nutrients is an appealing alternative, but their tightly regulated uptake and consumption again limits scalability. Here, using mathematical models of fatty acid uptake in E. coli as an exemplary case study, we unravel how the cell's native regulation and program of induction can be engineered to minimise inducer usage. We show that integrating positive feedback loops into the circuitry creates an irreversible metabolic switch, which, requiring only temporary induction, drastically reduces inducer usage. Our proposed switch should be widely applicable, irrespective of the product of interest, and brings closer the realization of scalable and sustainable microbial chemical production.

Coiled-coil heterodimers with increased stability for cellular regulation and sensing SARS-CoV-2 spike protein-mediated cell fusion

Coiled-coil (CC) dimer-forming peptides are attractive designable modules for mediating protein association. Highly stable CCs are desired for biological activity regulation and assay. Here, we report the design and versatile applications of orthogonal CC dimer-forming peptides with a dissociation constant in the low nanomolar range. In vitro stability and specificity was confirmed in mammalian cells by enzyme reconstitution, transcriptional activation using a combination of DNA-binding and a transcriptional activation domain, and cellular-enzyme-activity regulation based on externally-added peptides. In addition to cellular regulation, coiled-coil-mediated reporter reconstitution was used for the detection of cell fusion mediated by the interaction between the spike protein of pandemic SARS-CoV2 and the ACE2 receptor. This assay can be used to investigate the mechanism of viral spike protein-mediated fusion or screening for viral inhibitors under biosafety level 1 conditions.

Information processing using an integrated DNA reaction network

Living organisms use interconnected chemical reaction networks (CRNs) to exchange information with the surrounding environment and respond to diverse external stimuli. Inspired by nature, numerous artificial CRNs with a complex information processing function have been recently introduced, with DNA as one of the most attractive engineering materials. Although much progress has been made in DNA-based CRNs in terms of controllable reaction dynamics and molecular computation, the effective integration of signal translation with information processing in a single CRN remains to be difficult. In this work, we introduced a stimuli-responsive DNA reaction network capable of integrated information translation and processing in a stepwise manner. This network is designed to integrate sensing, translation, and decision-making operations by independent modules, in which various logic units capable of performing different functions were realized, including information identification (YES and OR gates), integration (AND and AND-AND gates), integration-filtration (AND-AND-NOT gate), comparison (Comparator), and map-to-map analysis (Feynman gate). Benefitting from the modular and programmable design, continuous and parallel processing operations are also possible. With the innovative functions, we show that the DNA network is a highly useful addition to the current DNA-based CRNs by offering a bottom-up strategy to design devices capable of cascaded information processing with high efficiency.

Signaling in Systems Chemistry: Programing Gold Nanoparticles Formation and Assembly Using a Dynamic Bistable Network

Living cells exploit bistable and oscillatory behaviors as memory mechanisms, facilitating the integration of transient stimuli into sustained molecular responses that control downstream functions. Synthetic bistable networks have also been studied as memory entities, but have rarely been utilized to control orthogonal functions in coupled dynamic systems. We herein present a new cascade pathway, for which we have exploited a well-characterized switchable peptide-based replicating network, operating far from equilibrium, that yields two alternative steady-state outputs, which in turn serve as the input signals for consecutive processes that regulate various features of Au nanoparticle shape and assembly. This study further sheds light on how bridging together the fields of systems chemistry and nanotechnology may open up new opportunities for the dynamically controlled design of functional materials.

A guide to the design of synthetic gene networks in mammalian cells

Synthetic biology aims to harness natural and synthetic biological parts and engineering them in new combinations and systems, producing novel therapies, diagnostics, bioproduction systems, and providing information on the mechanism of function of biological systems. Engineering cell function requires the rewiring or de novo construction of cell information processing networks. Using natural and synthetic signal processing elements, researchers have demonstrated a wide array of signal sensing, processing and propagation modules, using transcription, translation, or post-translational modification to program new function. The toolbox for synthetic network design is ever-advancing and has still ample room to grow. Here, we review the diversity of synthetic gene networks, types of building modules, techniques of regulation, and their applications.

Biosystems Design to Accelerate C3-to-CAM Progression

Global demand for food and bioenergy production has increased rapidly, while the area of arable land has been declining for decades due to damage caused by erosion, pollution, sea level rise, urban development, soil salinization, and water scarcity driven by global climate change. In order to overcome this conflict, there is an urgent need to adapt conventional agriculture to water-limited and hotter conditions with plant crop systems that display higher water-use efficiency (WUE). Crassulacean acid metabolism (CAM) species have substantially higher WUE than species performing C3 or C4 photosynthesis. CAM plants are derived from C3 photosynthesis ancestors. However, it is extremely unlikely that the C3 or C4 crop plants would evolve rapidly into CAM photosynthesis without human intervention. Currently, there is growing interest in improving WUE through transferring CAM into C3 crops. However, engineering a major metabolic plant pathway, like CAM, is challenging and requires a comprehensive deep understanding of the enzymatic reactions and regulatory networks in both C3 and CAM photosynthesis, as well as overcoming physiometabolic limitations such as diurnal stomatal regulation. Recent advances in CAM evolutionary genomics research, genome editing, and synthetic biology have increased the likelihood of successful acceleration of C3-to-CAM progression. Here, we first summarize the systems biology-level understanding of the molecular processes in the CAM pathway. Then, we review the principles of CAM engineering in an evolutionary context. Lastly, we discuss the technical approaches to accelerate the C3-to-CAM transition in plants using synthetic biology toolboxes.

Quantitative and Predictive Genetic Parts for Plant Synthetic Biology

Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs.

Engineering and Rewiring of a Calcium-Dependent Signaling Pathway

An important feature of synthetic biological circuits is their response to physicochemical signals, which enables the external control of cellular processes. Calcium-dependent regulation is an attractive approach for achieving such control, as diverse stimuli induce calcium influx by activating membrane channel receptors. Most calcium-dependent gene circuits use the endogenous nuclear factor of activated T-cells (NFAT) signaling pathway. Here, we employed engineered NFAT transcription factors to induce the potent and robust activation of exogenous gene expression in HEK293T cells. Furthermore, we designed a calcium-dependent transcription factor that does not interfere with NFAT-regulated promoters and potently activates transcription in several mammalian cell types. Additionally, we demonstrate that coupling the circuit to a calcium-selective ion channel resulted in capsaicin- and temperature-controlled gene expression. This engineered calcium-dependent signaling pathway enables tightly controlled regulation of gene expression through different stimuli in mammalian cells and is versatile, adaptable, and useful for a wide range of therapeutic and diagnostic applications.

Multistable and dynamic CRISPRi-based synthetic circuits

Gene expression control based on CRISPRi (clustered regularly interspaced short palindromic repeats interference) has emerged as a powerful tool for creating synthetic gene circuits, both in prokaryotes and in eukaryotes; yet, its lack of cooperativity has been pointed out as a potential obstacle for dynamic or multistable synthetic circuit construction. Here we use CRISPRi to build a synthetic oscillator (“CRISPRlator”), bistable network (toggle switch) and stripe pattern-forming incoherent feed-forward loop (IFFL). Our circuit designs, conceived to feature high predictability and orthogonality, as well as low metabolic burden and context-dependency, allow us to achieve robust circuit behaviors in Escherichia coli populations. Mathematical modeling suggests that unspecific binding in CRISPRi is essential to establish multistability. Our work demonstrates the wide applicability of CRISPRi in synthetic circuits and paves the way for future efforts towards engineering more complex synthetic networks, boosted by the advantages of CRISPR technology.

Synthetic circuits based on CRISPRi have not achieved multistable and dynamic behaviors. Here the authors build an oscillator, a toggle switch and an incoherent feed-forward loop using CRISPRi, and provide a mathematical model suggesting that unspecific binding in CRISPRi enables multistability.

Controlling spatiotemporal pattern formation in a concentration gradient with a synthetic toggle switch

The formation of spatiotemporal patterns of gene expression is frequently guided by gradients of diffusible signaling molecules. The toggle switch subnetwork, composed of two cross-repressing transcription factors, is a common component of gene regulatory networks in charge of patterning, converting the continuous information provided by the gradient into discrete abutting stripes of gene expression. We present a synthetic biology framework to understand and characterize the spatiotemporal patterning properties of the toggle switch. To this end, we built a synthetic toggle switch controllable by diffusible molecules in Escherichia coli. We analyzed the patterning capabilities of the circuit by combining quantitative measurements with a mathematical reconstruction of the underlying dynamical system. The toggle switch can produce robust patterns with sharp boundaries, governed by bistability and hysteresis. We further demonstrate how the hysteresis, position, timing, and precision of the boundary can be controlled, highlighting the dynamical flexibility of the circuit.

Design of Protein Logic Gate System Operating on Lipid Membranes

Lipid membranes are becoming increasingly popular in synthetic biology due to their biophysical properties and crucial role in communication between different compartments. Several alluring protein-membrane sensors have already been developed, whereas protein logic gates designs on membrane-embedded proteins are very limited. Here we demonstrate the construction of a two-level protein-membrane logic gate with an OR-AND logic. The system consists of an engineered pH-dependent pore-forming protein listeriolysin O and its DARPin-based inhibitor, conjugated to a lipid vesicle membrane. The gate responds to low pH and removal of the inhibitor from the membrane either by switching to a reducing environment, protease cleavage, or any other signal depending on the conjugation chemistry used for inhibitor attachment to the membrane. This unique protein logic gate vesicle system advances generic sensing and actuator platforms used in synthetic biology and could be utilized in drug delivery.

A chemically fueled non-enzymatic bistable network

One of the grand challenges in contemporary systems chemistry research is to mimic life-like functions using simple synthetic molecular networks. This is particularly true for systems that are out of chemical equilibrium and show complex dynamic behaviour, such as multi-stability, oscillations and chaos. We report here on thiodepsipeptide-based non-enzymatic networks propelled by reversible replication processes out of equilibrium, displaying bistability. Accordingly, we present quantitative analyses of the bistable behaviour, featuring a phase transition from the simple equilibration processes taking place in reversible dynamic chemistry into the bistable region. This behaviour is observed only when the system is continuously fueled by a reducing agent that keeps it far from equilibrium, and only when operating within a specifically defined parameter space. We propose that the development of biomimetic bistable systems will pave the way towards the study of more elaborate functions, such as information transfer and signalling.

Computational analysis of viable parameter regions in models of synthetic biological systems

Background

Gene regulatory networks with different topological and/or dynamical properties might exhibit similar behavior. System that is less perceptive for the perturbations of its internal and external factors should be preferred. Methods for sensitivity and robustness assessment have already been developed and can be roughly divided into local and global approaches. Local methods focus only on the local area around nominal parameter values. This can be problematic when parameters exhibits the desired behavior over a large range of parameter perturbations or when parameter values are unknown. Global methods, on the other hand, investigate the whole space of parameter values and mostly rely on different sampling techniques. This can be computationally inefficient. To address these shortcomings ’glocal’ approaches were developed that apply global and local approaches in an effective and rigorous manner.

Results

Herein, we present a computational approach for ’glocal’ analysis of viable parameter regions in biological models. The methodology is based on the exploration of high-dimensional viable parameter spaces with global and local sampling, clustering and dimensionality reduction techniques. The proposed methodology allows us to efficiently investigate the viable parameter space regions, evaluate the regions which exhibit the largest robustness, and to gather new insights regarding the size and connectivity of the viable parameter regions. We evaluate the proposed methodology on three different synthetic gene regulatory network models, i.e. the repressilator model, the model of the AC-DC circuit and the model of the edge-triggered master-slave D flip-flop.

Conclusions

The proposed methodology provides a rigorous assessment of the shape and size of viable parameter regions based on (1) the mathematical description of the biological system of interest, (2) constraints that define feasible parameter regions and (3) cost function that defines the desired or observed behavior of the system. These insights can be used to assess the robustness of biological systems, even in the case when parameter values are unknown and more importantly, even when there are multiple poorly connected viable parameter regions in the solution space. Moreover, the methodology can be efficiently applied to the analysis of biological systems that exhibit multiple modes of the targeted behavior.

Towards control of cellular decision-making networks in the epithelial-to-mesenchymal transition

We present the epithelial-to-mesenchymal transition (EMT) from two perspectives: experimental/technological and theoretical. We review the state of the current understanding of the regulatory networks that underlie EMT in three physiological contexts: embryonic development, wound healing, and metastasis. We describe the existing experimental systems and manipulations used to better understand the molecular participants and factors that influence EMT and metastasis. We review the mathematical models of the regulatory networks involved in EMT, with a particular emphasis on the network motifs (such as coupled feedback loops) that can generate intermediate hybrid states between the epithelial and mesenchymal states. Ultimately, the understanding gained about these networks should be translated into methods to control phenotypic outcomes, especially in the context of cancer therapeutic strategies. We present emerging theories of how to drive the dynamics of a network toward a desired dynamical attractor (e.g. an epithelial cell state) and emerging synthetic biology technologies to monitor and control the state of cells.

Polarized displacement by transcription activator-like effectors for regulatory circuits

The interplay between DNA-binding proteins plays an important role in transcriptional regulation and could increase the precision and complexity of designed regulatory circuits. Here we show that a transcription activator-like effector (TALE) can displace another TALE protein from DNA in a highly polarized manner, displacing only the 3'- but not 5'-bound overlapping or adjacent TALE. We propose that the polarized displacement by TALEs is based on its multipartite nature of binding to DNA. The polarized TALE displacement provides strategies for the specific regulation of gene expression, for construction of all two-input Boolean genetic logic circuits based on the robust propagation of the displacement across multiple neighboring sites, for displacement of zinc finger-based transcription factors and for suppression of Cas9-gRNA-mediated genome cleavage, enriching the synthetic biology toolbox and contributing to the understanding of the underlying principles of the facilitated displacement.

Cellular checkpoint control using programmable sequential logic

Biological processes that require orderly progression, such as growth and differentiation, proceed via regulatory checkpoints where the cell waits for signals before continuing to the next state. Implementing such control would allow genetic engineers to divide complex tasks into stages. We present genetic circuits that encode sequential logic to instruct Escherichia coli to proceed through a linear or cyclical sequence of states. These are built with 11 set-reset latches, designed with repressor-based NOR gates, which can connect to each other and sensors. The performance of circuits with up to three latches and four sensors, including a gated D latch, closely match predictions made by using nonlinear dynamics. Checkpoint control is demonstrated by switching cells between multiple circuit states in response to external signals over days.

The hallmarks of living systems: towards creating artificial cells

Despite the astonishing diversity and complexity of living systems, they all share five common hallmarks: compartmentalization, growth and division, information processing, energy transduction and adaptability. In this review, we give not only examples of how cells satisfy these requirements for life and the ways in which it is possible to emulate these characteristics in engineered platforms, but also the gaps that remain to be bridged. The bottom-up synthesis of life-like systems continues to be driven forward by the advent of new technologies, by the discovery of biological phenomena through their transplantation to experimentally simpler constructs and by providing insights into one of the oldest questions posed by mankind, the origin of life on Earth.

Engineering synthetic regulatory circuits in plants

Plant synthetic biology is a rapidly emerging field that aims to engineer genetic circuits to function in plants with the same reliability and precision as electronic circuits. These circuits can be used to program predictable plant behavior, producing novel traits to improve crop plant productivity, enable biosensors, and serve as platforms to synthesize chemicals and complex biomolecules. Herein we introduce the importance of developing orthogonal plant parts and the need for quantitative part characterization for mathematical modeling of complex circuits. In particular, transfer functions are important when designing electronic-like genetic controls such as toggle switches, positive/negative feedback loops, and Boolean logic gates. We then discuss potential constraints and challenges in synthetic regulatory circuit design and integration when using plants. Finally, we highlight current and potential plant synthetic regulatory circuit applications.

Synthetic Toolkit for Complex Genetic Circuit Engineering in Saccharomyces cerevisiae

Sustainable production of chemicals, materials, and pharmaceuticals is increasingly performed by genetically engineered cell factories. Engineering of complex metabolic routes or cell behavior control systems requires robust and predictable gene expression tools. In this challenging task, orthogonality is a fundamental prerequisite for such tools. In this study, we developed and characterized in depth a comprehensive gene expression toolkit that allows accurate control of gene expression in Saccharomyces cerevisiae without marked interference with native cellular regulation. The toolkit comprises a set of transcription factors, designed to function as synthetic activators or repressors, and transcription-factor-dependent promoters, which together provide a broad expression range surpassing, at high end, the strongest native promoters. Modularity of the developed tools is demonstrated by establishing a novel bistable genetic circuit with robust performance to control a heterologous metabolic pathway and enabling on-demand switching between two alternative metabolic branches.

A Robust Molecular Network Motif for Period-Doubling Devices

Life is sustained by a variety of cyclic processes such as cell division, muscle contraction, and neuron firing. The periodic signals powering these processes often direct a variety of other downstream systems, which operate at different time scales and must have the capacity to divide or multiply the period of the master clock. Period modulation is also an important challenge in synthetic molecular systems, where slow and fast components may have to be coordinated simultaneously by a single oscillator whose frequency is often difficult to tune. Circuits that can multiply the period of a clock signal (frequency dividers), such as binary counters and flip-flops, are commonly encountered in electronic systems, but design principles to obtain similar devices in biological systems are still unclear. We take inspiration from the architecture of electronic flip-flops, and we propose to build biomolecular period-doubling networks by combining a bistable switch with negative feedback modules that preprocess the circuit inputs. We identify a network motif and we show it can be "realized" using different biomolecular components; two of the realizations we propose rely on transcriptional gene networks and one on nucleic acid strand displacement systems. We examine the capacity of each realization to perform period-doubling by studying how bistability of the motif is affected by the presence of the input; for this purpose, we employ mathematical tools from algebraic geometry that provide us with valuable insights on the input/output behavior as a function of the realization parameters. We show that transcriptional network realizations operate correctly also in a stochastic regime when processing oscillations from the repressilator, a canonical synthetic in vivo oscillator. Finally, we compare the performance of different realizations in a range of realistic parameters via numerical sensitivity analysis of the period-doubling region, computed with respect to the input period and amplitude. Our mathematical and computational analysis suggests that the motif we propose is generally robust with respect to specific implementation details: functionally equivalent circuits can be built as long as the species-interaction topology is respected. This indicates that experimental construction of the circuit is possible with a variety of components within the rapidly expanding libraries available in synthetic biology.

Designed Transcriptional Regulation in Mammalian Cells Based on TALE- and CRISPR/dCas9

Transcriptional regulation lies at the center of many cellular processes and is the result of cellular response to different external and internal signals. Control of transcription of selected genes enables an unprecedented access to shape the cellular response. While orthogonal transcription factors from bacteria, yeast, plants, or other cells have been used to introduce new cellular logic into mammalian cells, the discovery of designable modular DNA binding domains, such as Transcription Activator-Like Effectors (TALEs) and the CRISPR system, enable targeting of almost any selected DNA sequence. Fusion or conditional association of DNA targeting domain with transcriptional effector domains enables controlled regulation of almost any endogenous or ectopic gene. Moreover, the designed regulators can be linked into genetic circuits to implement complex responses, such as different types of Boolean functions and switches. In this chapter, we describe the protocols for achieving efficient transcriptional regulation with TALE- and CRISPR-based designed transcription factors in mammalian cells.

Design of synthetic epigenetic circuits featuring memory effects and reversible switching based on DNA methylation

Epigenetic systems store information in DNA methylation patterns in a durable but reversible manner, but have not been regularly used in synthetic biology. Here, we designed synthetic epigenetic memory systems using DNA methylation sensitive engineered zinc finger proteins to repress a memory operon comprising the CcrM methyltransferase and a reporter. Triggering by heat, nutrients, ultraviolet irradiation or DNA damaging compounds induces CcrM expression and DNA methylation. In the induced on-state, methylation in the operator of the memory operon prevents zinc finger protein binding leading to positive feedback and permanent activation. Using an mf-Lon protease degradable CcrM variant enables reversible switching. Epigenetic memory systems have numerous potential applications in synthetic biology, including life biosensors, death switches or induction systems for industrial protein production. The large variety of bacterial DNA methyltransferases potentially allows for massive multiplexing of signal storage and logical operations depending on more than one input signal.

Recording systems would allow synthetic organisms to store a ‘memory' of a past event for future reference. Here the authors design an epigenetic memory system in E. coli that methylates DNA in response to exogenous and endogenous signals.

Classical Mechanics Approach Applied to Analysis of Genetic Oscillators

Biological oscillators present a fundamental part of several regulatory mechanisms that control the response of various biological systems. Several analytical approaches for their analysis have been reported recently. They are, however, limited to only specific oscillator topologies and/or to giving only qualitative answers, i.e., is the dynamics of an oscillator given the parameter space oscillatory or not. Here, we present a general analytical approach that can be applied to the analysis of biological oscillators. It relies on the projection of biological systems to classical mechanics systems. The approach is able to provide us with relatively accurate results in the meaning of type of behavior system reflects (i.e., oscillatory or not) and periods of potential oscillations without the necessity to conduct expensive numerical simulations. We demonstrate and verify the proposed approach on three different implementations of amplified negative feedback oscillator.

Exploiting the sequence diversity of TALE-like repeats to vary the strength of dTALE-promoter interactions

Designer transcription activator-like effectors (dTALEs) are programmable transcription factors used to regulate user-defined promoters. The TALE DNA-binding domain is a tandem series of amino acid repeats that each bind one DNA base. Each repeat is 33-35 amino acids long. A residue in the center of each repeat is responsible for defining DNA base specificity and is referred to as the base specificying residue (BSR). Other repeat residues are termed non-BSRs and can contribute to TALE DNA affinity in a non-base-specific manner. Previous dTALE engineering efforts have focused on BSRs. Non-BSRs have received less attention, perhaps because there is almost no non-BSR sequence diversity in natural TALEs. However, more sequence diverse, TALE-like proteins are found in diverse bacterial clades. Here, we show that natural non-BSR sequence diversity of TALEs and TALE-likes can be used to modify DNA-binding strength in a new form of dTALE repeat array that we term variable sequence TALEs (VarSeTALEs). We generated VarSeTALE repeat modules through random assembly of repeat sequences from different origins, while holding BSR composition, and thus base preference, constant. We used two different VarSeTALE design approaches combing either whole repeats from different TALE-like sources (inter-repeat VarSeTALEs) or repeat subunits corresponding to secondary structural elements (intra-repeat VarSeTALEs). VarSeTALE proteins were assayed in bacteria, plant protoplasts and leaf tissues. In each case, VarSeTALEs activated or repressed promoters with a range of activities. Our results indicate that natural non-BSR diversity can be used to diversify the binding strengths of dTALE repeat arrays while keeping target sequences constant.

Steady state statistical correlations predict bistability in reaction motifs

We show that steady state cross-moments and cross-cumulants predict bistability in feedback-regulated reaction networks.

Genome-Editing Technologies: Principles and Applications

Targeted nucleases have provided researchers with the ability to manipulate virtually any genomic sequence, enabling the facile creation of isogenic cell lines and animal models for the study of human disease, and promoting exciting new possibilities for human gene therapy. Here we review three foundational technologies-clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9), transcription activator-like effector nucleases (TALENs), and zinc-finger nucleases (ZFNs). We discuss the engineering advances that facilitated their development and highlight several achievements in genome engineering that were made possible by these tools. We also consider artificial transcription factors, illustrating how this technology can complement targeted nucleases for synthetic biology and gene therapy.

Benchmarking of TALE- and CRISPR/dCas9-Based Transcriptional Regulators in Mammalian Cells for the Construction of Synthetic Genetic Circuits

Transcriptional activator-like effector (TALE)- and CRISPR/Cas9-based designable recognition domains represent a technological breakthrough not only for genome editing but also for building designed genetic circuits. Both platforms are able to target rarely occurring DNA segments, even within complex genomes. TALE and dCas9 domains, genetically fused to transcriptional regulatory domains, can be used for the construction of engineered logic circuits. Here we benchmarked the performance of the two platforms, targeting the same DNA sequences, to compare their advantages for the construction of designed circuits in mammalian cells. Optimal targeting strands for repression and activation of dCas9-based designed transcription factors were identified; both platforms exhibited good orthogonality and were used to construct functionally complete NOR gates. Although the CRISPR/dCas9 system is clearly easier to construct, TALE-based activators were significantly stronger, and the TALE-based platform performed better, especially for the construction of layered circuits.

Computational Framework for Modeling Multiple Noncooperative Transcription Factor Binding and Its Application to the Analysis of Nuclear Factor Kappa B Oscillatory Response

Recent studies have shown that regulation of many important genes is achieved with multiple transcription factor (TF) binding sites with low or no cooperativity. Additionally, noncooperative binding sites are gaining more and more importance in the field of synthetic biology. Here, we introduce a computational framework that can be applied to dynamical modeling and analysis of gene regulatory networks with multiple noncooperative TF binding sites. We propose two computational methods to be used within the framework, that is, average promoter state approximation and expression profiles based modeling. We demonstrate the application of the proposed framework on the analysis of nuclear factor kappa B (NF-κB) oscillatory response. We show that different promoter expression hypotheses in a combination with the number of TF binding sites drastically affect the dynamics of the observed system and should not be ignored in the process of quantitative dynamical modeling, as is usually the case in existent state-of-the-art computational analyses.

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.

An analytical approach to bistable biological circuit discrimination using real algebraic geometry

Biomolecular circuits with two distinct and stable steady states have been identified as essential components in a wide range of biological networks, with a variety of mechanisms and topologies giving rise to their important bistable property. Understanding the differences between circuit implementations is an important question, particularly for the synthetic biologist faced with determining which bistable circuit design out of many is best for their specific application. In this work we explore the applicability of Sturm's theorem--a tool from nineteenth-century real algebraic geometry--to comparing 'functionally equivalent' bistable circuits without the need for numerical simulation. We first consider two genetic toggle variants and two different positive feedback circuits, and show how specific topological properties present in each type of circuit can serve to increase the size of the regions of parameter space in which they function as switches. We then demonstrate that a single competitive monomeric activator added to a purely monomeric (and otherwise monostable) mutual repressor circuit is sufficient for bistability. Finally, we compare our approach with the Routh-Hurwitz method and derive consistent, yet more powerful, parametric conditions. The predictive power and ease of use of Sturm's theorem demonstrated in this work suggest that algebraic geometric techniques may be underused in biomolecular circuit analysis.