Hysteresis in a synthetic mammalian gene network

Mammalian designer cells: Engineering principles and biomedical applications

Biotechnology is a widely interdisciplinary field focusing on the use of living cells or organisms to solve established problems in medicine, food production and agriculture. Synthetic biology, the science of engineering complex biological systems that do not exist in nature, continues to provide the biotechnology industry with tools, technologies and intellectual property leading to improved cellular performance. One key aspect of synthetic biology is the engineering of deliberately reprogrammed designer cells whose behavior can be controlled over time and space. This review discusses the most commonly used techniques to engineer mammalian designer cells; while control elements acting on the transcriptional and translational levels of target gene expression determine the kinetic and dynamic profiles, coupling them to a variety of extracellular stimuli permits their remote control with user-defined trigger signals. Designer mammalian cells with novel or improved biological functions not only directly improve the production efficiency during biopharmaceutical manufacturing but also open the door for cell-based treatment strategies in molecular and translational medicine. In the future, the rational combination of multiple sets of designer cells could permit the construction and regulation of higher-order systems with increased complexity, thereby enabling the molecular reprogramming of tissues, organisms or even populations with highest precision.

Optimal census by quorum sensing

Quorum sensing is the regulation of gene expression in response to changes in cell density. To measure their cell density, bacterial populations produce and detect diffusible molecules called autoinducers. Individual bacteria internally represent the external concentration of autoinducers via the level of monitor proteins. In turn, these monitor proteins typically regulate both their own production and the production of autoinducers, thereby establishing internal and external feedbacks. Here, we ask whether feedbacks can increase the information available to cells about their local density. We quantify available information as the mutual information between the abundance of a monitor protein and the local cell density for biologically relevant models of quorum sensing. Using variational methods, we demonstrate that feedbacks can increase information transmission, allowing bacteria to resolve up to two additional ranges of cell density when compared with bistable quorum-sensing systems. Our analysis is relevant to multi-agent systems that track an external driver implicitly via an endogenously generated signal.

Bacteria regulate gene expression in response to changes in cell density in a process called quorum sensing. To synchronize their gene-expression programs, these bacteria need to glean as much information as possible about their cell density. Our study is the first to physically model the flow of information in a quorum-sensing microbial community, wherein the internal regulator of the individuals response tracks the external cell density via an endogenously generated shared signal. Combining information theory and Lagrangian formalism, we find that quorum-sensing systems can improve their information capabilities by tuning circuit feedbacks. Our analysis suggests that achieving information benefit via feedback requires dedicated systems to control gene expression noise, such as sRNA-based regulation.

Bistability: requirements on cell-volume, protein diffusion, and thermodynamics

Bistability is considered wide-spread among bacteria and eukaryotic cells, useful e.g. for enzyme induction, bet hedging, and epigenetic switching. However, this phenomenon has mostly been described with deterministic dynamic or well-mixed stochastic models. Here, we map known biological bistable systems onto the well-characterized biochemical Schlögl model, using analytical calculations and stochastic spatiotemporal simulations. In addition to network architecture and strong thermodynamic driving away from equilibrium, we show that bistability requires fine-tuning towards small cell volumes (or compartments) and fast protein diffusion (well mixing). Bistability is thus fragile and hence may be restricted to small bacteria and eukaryotic nuclei, with switching triggered by volume changes during the cell cycle. For large volumes, single cells generally loose their ability for bistable switching and instead undergo a first-order phase transition.

Systematic transfer of prokaryotic sensors and circuits to mammalian cells

Prokaryotic regulatory proteins respond to diverse signals and represent a rich resource for building synthetic sensors and circuits. The TetR family contains >10(5) members that use a simple mechanism to respond to stimuli and bind distinct DNA operators. We present a platform that enables the transfer of these regulators to mammalian cells, which is demonstrated using human embryonic kidney (HEK293) and Chinese hamster ovary (CHO) cells. The repressors are modified to include nuclear localization signals (NLS) and responsive promoters are built by incorporating multiple operators. Activators are also constructed by modifying the protein to include a VP16 domain. Together, this approach yields 15 new regulators that demonstrate 19- to 551-fold induction and retain both the low levels of crosstalk in DNA binding specificity observed between the parent regulators in Escherichia coli, as well as their dynamic range of activity. By taking advantage of the DAPG small molecule sensing mediated by the PhlF repressor, we introduce a new inducible system with 50-fold induction and a threshold of 0.9 μM DAPG, which is comparable to the classic Dox-induced TetR system. A set of NOT gates is constructed from the new repressors and their response function quantified. Finally, the Dox- and DAPG- inducible systems and two new activators are used to build a synthetic enhancer (fuzzy AND gate), requiring the coordination of 5 transcription factors organized into two layers. This work introduces a generic approach for the development of mammalian genetic sensors and circuits to populate a toolbox that can be applied to diverse applications from biomanufacturing to living therapeutics.

Synthetic analog and digital circuits for cellular computation and memory

Biological computation is a major area of focus in synthetic biology because it has the potential to enable a wide range of applications. Synthetic biologists have applied engineering concepts to biological systems in order to construct progressively more complex gene circuits capable of processing information in living cells. Here, we review the current state of computational genetic circuits and describe artificial gene circuits that perform digital and analog computation. We then discuss recent progress in designing gene networks that exhibit memory, and how memory and computation have been integrated to yield more complex systems that can both process and record information. Finally, we suggest new directions for engineering biological circuits capable of computation.

Building synthetic memory

Cellular memory - conversion of a transient signal into a sustained response - is a common feature of biological systems. Synthetic biologists aim to understand and re-engineer such systems in a reliable and predictable manner. Synthetic memory circuits have been designed and built in vitro and in vivo based on diverse mechanisms, such as oligonucleotide hybridization, recombination, transcription, phosphorylation, and RNA editing. Thus far, building these circuits has helped us explore the basic principles required for stable memory and ask novel biological questions. Here we discuss strategies for building synthetic memory circuits, their use as research tools, and future applications of these devices in medicine and industry.

Synthetic biology in mammalian cells: next generation research tools and therapeutics

Recent progress in DNA manipulation and gene circuit engineering has greatly improved our ability to programme and probe mammalian cell behaviour. These advances have led to a new generation of synthetic biology research tools and potential therapeutic applications. Programmable DNA-binding domains and RNA regulators are leading to unprecedented control of gene expression and elucidation of gene function. Rebuilding complex biological circuits such as T cell receptor signalling in isolation from their natural context has deepened our understanding of network motifs and signalling pathways. Synthetic biology is also leading to innovative therapeutic interventions based on cell-based therapies, protein drugs, vaccines and gene therapies.

Systems biology: a biologist's viewpoint

The debate over reductionism and antireductionism in biology is very old. Even the systems approach in biology is more than five decades old. However, mainstream biology, particularly experimental biology, has broadly sidestepped those debates and ideas. Post-genome data explosion and development of high-throughput techniques led to resurfacing of those ideas and debates as a new incarnation called Systems Biology. Though experimental biologists have co-opted systems biology and hailed it as a paradigm shift, it is practiced in different shades and understood with divergent meanings. Biology has certain questions linked with organization of multiple components and processes. Often such questions involve multilevel systems. Here in this essay we argue that systems theory provides required framework and abstractions to explore those questions. We argue that systems biology should follow the logical and mathematical approach of systems theory and transmogrification of systems biology to mere collection of higher dimensional data must be avoided. Therefore, the questions that we ask and the priority of those questions should also change. Systems biology should focus on system-level properties and investigate complexity without shying away from it.

Synthetic approaches to study transcriptional networks and noise in mammalian systems

Synthetic biology aims to build new functional organisms and to rationally re-design existing ones by applying the engineering principle of modularity. Apart from building new life forms to perform technical applications, the approach of synthetic biology is useful to dissect complex biological phenomena into simple and easy to understand synthetic modules. Synthetic gene networks have been successfully implemented in prokaryotes and lower eukaryotes, with recent approaches moving ahead towards the mammalian environment. However, synthetic circuits in higher eukaryotes present a more challenging scenario, since its reliability is compromised because of the strong stochastic nature of transcription. Here, the authors review recent approaches that take advantage of the noisy response of synthetic regulatory circuits to learn key features of the complex machinery that orchestrates transcription in higher eukaryotes. Understanding the causes and consequences of biological noise will allow us to design more reliable mammalian synthetic circuits with revolutionary medical applications.

Hidden hysteresis - population dynamics can obscure gene network dynamics

Background

Positive feedback is a common motif in gene regulatory networks. It can be used in synthetic networks as an amplifier to increase the level of gene expression, as well as a nonlinear module to create bistable gene networks that display hysteresis in response to a given stimulus. Using a synthetic positive feedback-based tetracycline sensor in E. coli, we show that the population dynamics of a cell culture has a profound effect on the observed hysteretic response of a population of cells with this synthetic gene circuit.

Results

The amount of observable hysteresis in a cell culture harboring the gene circuit depended on the initial concentration of cells within the culture. The magnitude of the hysteresis observed was inversely related to the dilution procedure used to inoculate the subcultures; the higher the dilution of the cell culture, lower was the observed hysteresis of that culture at steady state. Although the behavior of the gene circuit in individual cells did not change significantly in the different subcultures, the proportion of cells exhibiting high levels of steady-state gene expression did change.

Although the interrelated kinetics of gene expression and cell growth are unpredictable at first sight, we were able to resolve the surprising dilution-dependent hysteresis as a result of two interrelated phenomena - the stochastic switching between the ON and OFF phenotypes that led to the cumulative failure of the gene circuit over time, and the nonlinear, logistic growth of the cell in the batch culture.

Conclusions

These findings reinforce the fact that population dynamics cannot be ignored in analyzing the dynamics of gene networks. Indeed population dynamics may play a significant role in the manifestation of bistability and hysteresis, and is an important consideration when designing synthetic gene circuits intended for long-term application.

Network nonlinearities in drug treatment

Despite major achievements in the understanding of human disease, there is a general perception that the drug development industry has failed to meet the expectations that recent advances in biotechnology should drive. One of the potential sources of failure of many next generation drugs is that their targets are embedded in highly nonlinear signaling pathways and gene networks with multiple negative and positive feedback loops of regulation. There is increasing evidence that this complex network shapes the response to external perturbations in the form of drug treatment, originating bistability, hypersensitivity, robustness, complex dose-response curves or schedule dependent activity. This review focuses on the effect of nonlinearities on signaling and gene networks involved in human disease, using tools from Nonlinear Dynamics to discuss the implications and to overcome the effects of the nonlinearities on regulatory networks.

Multi-chromatic control of mammalian gene expression and signaling

The emergence and future of mammalian synthetic biology depends on technologies for orchestrating and custom tailoring complementary gene expression and signaling processes in a predictable manner. Here, we demonstrate for the first time multi-chromatic expression control in mammalian cells by differentially inducing up to three genes in a single cell culture in response to light of different wavelengths. To this end, we developed an ultraviolet B (UVB)-inducible expression system by designing a UVB-responsive split transcription factor based on the Arabidopsis thaliana UVB receptor UVR8 and the WD40 domain of COP1. The system allowed high (up to 800-fold) UVB-induced gene expression in human, monkey, hamster and mouse cells. Based on a quantitative model, we determined critical system parameters. By combining this UVB-responsive system with blue and red light-inducible gene control technology, we demonstrate multi-chromatic multi-gene control by differentially expressing three genes in a single cell culture in mammalian cells, and we apply this system for the multi-chromatic control of angiogenic signaling processes. This portfolio of optogenetic tools enables the design and implementation of synthetic biological networks showing unmatched spatiotemporal precision for future research and biomedical applications.

The interplay of intrinsic and extrinsic bounded noises in biomolecular networks

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a biomolecular network. The influence of intrinsic and extrinsic noises on biomolecular networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i) the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii) a model of enzymatic futile cycle and (iii) a genetic toggle switch. In (ii) and (iii) we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possible functional role of bounded noises.

Sequestration-based bistability enables tuning of the switching boundaries and design of a latch

Engineering of the sigma/anti-sigma system in Escherichia coli shows that sequestration combined with positive feedback can be used to build a bistable memory device. The minimal requirement of this design makes it potentially scalable and generalizable.

A sigma factor and its cognate anti-sigma factor are used to build a bistable switch without relying on cooperativity.

The switching boundaries are tunable and allow rapid design of a set-reset latch.

This design is analytically tractable and should be scalable to more sigma/anti-sigma pairs.

Natural biological systems have evolved a diverse array of switches to realize their strategies for environmental response and development. Emerging applications of synthetic biology have begun to exploit such switches to achieve increasingly sophisticated designed behaviors. However, not all switch architectures allow facile design of the switching and memory properties. Furthermore, not all designs are built from components for which large families of variants exist, a requirement for building many orthogonal switch variants. Therefore, there is a critical need from genetic engineers for scalable strategies that yield custom bistable switches. Here, we use a sigma factor and its cognate anti-sigma factor to experimentally verify that ultrasensitivity from sequestration combined with positive feedback is sufficient to build a bistable switch. We show that sequestration allows us to predictably tune the switching boundaries, and we can easily tune our switch to function as a set–reset latch that can be toggled between two states by a pulse of inducer input.

DNA looping in prokaryotes: experimental and theoretical approaches

Transcriptional regulation is at the heart of biological functions such as adaptation to a changing environment or to new carbon sources. One of the mechanisms which has been found to modulate transcription, either positively (activation) or negatively (repression), involves the formation of DNA loops. A DNA loop occurs when a protein or a complex of proteins simultaneously binds to two different sites on DNA with looping out of the intervening DNA. This simple mechanism is central to the regulation of several operons in the genome of the bacterium Escherichia coli, like the lac operon, one of the paradigms of genetic regulation. The aim of this review is to gather and discuss concepts and ideas from experimental biology and theoretical physics concerning DNA looping in genetic regulation. We first describe experimental techniques designed to show the formation of a DNA loop. We then present the benefits that can or could be derived from a mechanism involving DNA looping. Some of these are already experimentally proven, but others are theoretical predictions and merit experimental investigation. Then, we try to identify other genetic systems that could be regulated by a DNA looping mechanism in the genome of Escherichia coli. We found many operons that, according to our set of criteria, have a good chance to be regulated with a DNA loop. Finally, we discuss the proposition recently made by both biologists and physicists that this mechanism could also act at the genomic scale and play a crucial role in the spatial organization of genomes.

Frontiers of optofluidics in synthetic biology

The development of optofluidic-based technology has ushered in a new era of lab-on-a-chip functionality, including miniaturization of biomedical devices, enhanced sensitivity for molecular detection, and multiplexing of optical measurements. While having great potential, optofluidic devices have only begun to be exploited in many biotechnological applications. Here, we highlight the potential of integrating optofluidic devices with synthetic biological systems, which is a field focusing on creating novel cellular systems by engineering synthetic gene and protein networks. First, we review the development of synthetic biology at different length scales, ranging from single-molecule, single-cell, to cellular population. We emphasize light-sensitive synthetic biological systems that would be relevant for the integration with optofluidic devices. Next, we propose several areas for potential applications of optofluidics in synthetic biology. The integration of optofluidics and synthetic biology would have a broad impact on point-of-care diagnostics and biotechnology.

A synthetic biology approach to understanding cellular information processing

The survival of cells and organisms requires proper responses to environmental signals. These responses are governed by cellular networks, which serve to process diverse environmental cues. Biological networks often contain recurring network topologies called "motifs". It has been recognized that the study of such motifs allows one to predict the response of a biological network and thus cellular behavior. However, studying a single motif in complete isolation of all other network motifs in a natural setting is difficult. Synthetic biology has emerged as a powerful approach to understanding the dynamic properties of network motifs. In addition to testing existing theoretical predictions, construction and analysis of synthetic gene circuits has led to the discovery of novel motif dynamics, such as how the combination of simple motifs can lead to autonomous dynamics or how noise in transcription and translation can affect the dynamics of a motif. Here, we review developments in synthetic biology as they pertain to increasing our understanding of cellular information processing. We highlight several types of dynamic behaviors that diverse motifs can generate, including the control of input/output responses, the generation of autonomous spatial and temporal dynamics, as well as the influence of noise in motif dynamics and cellular behavior.

Teasing apart translational and transcriptional components of stochastic variations in eukaryotic gene expression

The intrinsic stochasticity of gene expression leads to cell-to-cell variations, noise, in protein abundance. Several processes, including transcription, translation, and degradation of mRNA and proteins, can contribute to these variations. Recent single cell analyses of gene expression in yeast have uncovered a general trend where expression noise scales with protein abundance. This trend is consistent with a stochastic model of gene expression where mRNA copy number follows the random birth and death process. However, some deviations from this basic trend have also been observed, prompting questions about the contribution of gene-specific features to such deviations. For example, recent studies have pointed to the TATA box as a sequence feature that can influence expression noise by facilitating expression bursts. Transcription-originated noise can be potentially further amplified in translation. Therefore, we asked the question of to what extent sequence features known or postulated to accompany translation efficiency can also be associated with increase in noise strength and, on average, how such increase compares to the amplification associated with the TATA box. Untangling different components of expression noise is highly nontrivial, as they may be gene or gene-module specific. In particular, focusing on codon usage as one of the sequence features associated with efficient translation, we found that ribosomal genes display a different relationship between expression noise and codon usage as compared to other genes. Within nonribosomal genes we found that sequence high codon usage is correlated with increased noise relative to the average noise of proteins with the same abundance. Interestingly, by projecting the data on a theoretical model of gene expression, we found that the amplification of noise strength associated with codon usage is comparable to that of the TATA box, suggesting that the effect of translation on noise in eukaryotic gene expression might be more prominent than previously appreciated.

The stochastic nature of gene expression leads to cell-to-cell differences in protein level referred to as noise. Expression noise can be disadvantageous, by affecting the precision of biological functions, but it may also be advantageous by enabling heterogeneous stress-response programs to environmental changes. Therefore various genes and gene groups might display various levels of expression noise. Importantly, gene expression is a multi-step process and the stochasticity of its individual steps, including transcription and translation, contributes to the resulting variability. Recent single cell analyses of gene expression in yeast have confirmed the theoretically predicted general trend where expression noise scales with protein abundance. However, some deviations from this basic trend have also been observed, prompting questions about the contribution of gene-specific features to such deviations. Accounting for noise heterogeneity in different gene groups, we revealed a clear relationship between noise and translation-related genomic features, specifically codon usage and 5′ UTR secondary structure. Our results suggest that the effect of translation on these deviations might be more prominent than previously appreciated, and provide important clues towards understanding expression stochasticity in yeast.

Successes and failures in modular genetic engineering

Synthetic biology relies on engineering concepts such as abstraction, standardization, and decoupling to develop systems that address environmental, clinical, and industrial needs. Recent advances in applying modular design to system development have enabled creation of increasingly complex systems. However, several challenges to module and system development remain, including syntactic errors, semantic errors, parameter mismatches, contextual sensitivity, noise and evolution, and load and stress. To combat these challenges, researchers should develop a framework for describing and reasoning about biological information, design systems with modularity in mind, and investigate how to predictively describe the diverse sources and consequences of metabolic load and stress.

Modeling of hysteresis in gene regulatory networks

Hysteresis, observed in many gene regulatory networks, has a pivotal impact on biological systems, which enhances the robustness of cell functions. In this paper, a general model is proposed to describe the hysteretic gene regulatory network by combining the hysteresis component and the transient dynamics. The Bouc-Wen hysteresis model is modified to describe the hysteresis component in the mammalian gene regulatory networks. Rigorous mathematical analysis on the dynamical properties of the model is presented to ensure the bounded-input-bounded-output (BIBO) stability and demonstrates that the original Bouc-Wen model can only generate a clockwise hysteresis loop while the modified model can describe both clockwise and counter clockwise hysteresis loops. Simulation studies have shown that the hysteresis loops from our model are consistent with the experimental observations in three mammalian gene regulatory networks and two E.coli gene regulatory networks, which demonstrate the ability and accuracy of the mathematical model to emulate natural gene expression behavior with hysteresis. A comparison study has also been conducted to show that this model fits the experiment data significantly better than previous ones in the literature. The successful modeling of the hysteresis in all the five hysteretic gene regulatory networks suggests that the new model has the potential to be a unified framework for modeling hysteresis in gene regulatory networks and provide better understanding of the general mechanism that drives the hysteretic function.

Rewiring and dosing of systems modules as a design approach for synthetic mammalian signaling networks

Modularly structured signaling networks coordinate the fate and function of complex biological systems. Each component in the network performs a discrete computational operation, but when connected to each other intricate functionality emerges. Here we study such an architecture by connecting auxin signaling modules and inducible protein biotinylation systems with transcriptional control systems to construct synthetic mammalian high-detect, low-detect and band-detect networks that translate overlapping gradients of inducer molecules into distinct gene expression patterns. Guided by a mathematical model we apply fundamental computational operations like conjunction or addition to rewire individual building blocks to qualitatively and quantitatively program the way the overall network interprets graded input signals. The design principles described in this study might serve as a conceptual blueprint for the development of next-generation mammalian synthetic gene networks in fundamental and translational research.

Tunable oscillations and chaotic dynamics in systems with localized synthesis

Biological systems contain biochemical control networks that reside within a remarkable spatial structure. We present a theoretical study of a biological system in which two chemically coupled species, an activating species and an inhibiting species forming a negative feedback, are synthesized at unique sites and interact with each other through diffusion. The dynamical behaviors in these systems depend on the spatial locations of these synthetic sites. In a negative feedback system with two sites, we find two dynamical modes: fixed point and stable oscillations whose frequency can be tuned by varying the distance between the sites. When there are multiple synthetic sites, we find more diverse dynamics, including chaos, quasiperiodicity, and bistability. Based on this theoretical analysis, it should be possible to create in the laboratory synthetic circuits displaying these dynamics. This study illustrates the concept of "spatial switching," in which bifurcations in the dynamics occur as a function of the geometry of the system.

Feedback control of protein expression in mammalian cells by tunable synthetic translational inhibition

Feedback regulation plays a crucial role in dynamic gene expression in nature, but synthetic translational feedback systems have yet to be demonstrated. Here we use an RNA/protein interaction-based synthetic translational switch to create a feedback system that tightly controls the expression of proteins of interest in mammalian cells. Feedback is mediated by modified ribosomal L7Ae proteins, which bind a set of RNA motifs with a range of affinities. We designed these motifs into L7Ae-encoding mRNA. Newly translated L7Ae binds its own mRNA, inhibiting further translation. This inhibition tightly feedback-regulates the concentration of L7Ae and any fusion partner of interest. A mathematical model predicts system behavior as a function of RNA/protein affinity. We further demonstrate that the L7Ae protein can simultaneously and tunably regulate the expression of multiple proteins of interest by binding RNA control motifs built into each mRNA, allowing control over the coordinated expression of protein networks.

Synthetic biology: advancing biological frontiers by building synthetic systems

Advances in synthetic biology are contributing to diverse research areas, from basic biology to biomanufacturing and disease therapy. We discuss the theoretical foundation, applications, and potential of this emerging field.

Therapeutic synthetic gene networks

The field of synthetic biology is rapidly expanding and has over the past years evolved from the development of simple gene networks to complex treatment-oriented circuits. The reprogramming of cell fate with open-loop or closed-loop synthetic control circuits along with biologically implemented logical functions have fostered applications spanning over a wide range of disciplines, including artificial insemination, personalized medicine and the treatment of cancer and metabolic disorders. In this review we describe several applications of interactive gene networks, a synthetic biology-based approach for future gene therapy, as well as the utilization of synthetic gene circuits as blueprints for the design of stimuli-responsive biohybrid materials. The recent progress in synthetic biology, including the rewiring of biosensing devices with the body's endogenous network as well as novel therapeutic approaches originating from interdisciplinary work, generates numerous opportunities for future biomedical applications.

Genetic aspects of cell line development from a synthetic biology perspective

Animal cells can be regarded as factories for the production of relevant proteins. The advances described in this chapter towards the development of cell lines with higher productivity capacities, certain metabolic and proliferation properties, reduced apoptosis and other features must be regarded in an integrative perspective. The systematic application of systems biology approaches in combination with a synthetic arsenal for targeted modification of endogenous networks are proposed to lead towards the achievement of a predictable and technologically advanced cell system with high biotechnological impact.

Design and construction of synthetic gene networks in mammalian cells

Advances in the development of molecular tools for the inducible control of transcription, translation, and protein degradation are the basis for the rapidly emerging design and construction of synthetic gene networks in mammalian cells.In this chapter, we describe such tools and how they can be integrated into a synthetic gene network with desired functionality. The network design and construction process is illustrated in the form of a detailed protocol for the implementation of a logic NOR gate based on an inducible promoter combined with an inducible protein degradation system.

Xbp1-based engineering of secretory capacity enhances the productivity of Chinese hamster ovary cells

A variety of successful transcription and translation engineering strategies implemented during the past decade have driven the specific productivity of mammalian cells to an apparent limit. Restricted post-translation competence has since been considered the major bottleneck preventing mammalian cells from fully exploiting their physiologic production capacity in a biopharmaceutical manufacturing scenario. Through ectopic expression of the human transcription factor Xbp1 (X-box-binding-protein 1), evolved to manage plasma cell differentiation and coordinate the unfolded protein response, we have specifically expanded the endoplasmic reticulum and the Golgi of transgenic Chinese hamster ovary (CHO-K1)-derived cell lines with a resulting increase in overall production capacity. Xbp-1-based engineering of secretory bottlenecks was compatible with a variety of different promoter–product gene configurations suggesting that Xbp-1 induces generic production increases in CHO-K1 cell derivatives. Secretion engineering, illustrated here by Xbp1-based reprogramming of the post-translational processing machinery, provides a first insight into mastering a major system bottleneck which impacts biopharmaceutical manufacturing of secreted protein therapeutics.

The food additive vanillic acid controls transgene expression in mammalian cells and mice

Trigger-inducible transcription-control devices that reversibly fine-tune transgene expression in response to molecular cues have significantly advanced the rational reprogramming of mammalian cells. When designed for use in future gene- and cell-based therapies the trigger molecules have to be carefully chosen in order to provide maximum specificity, minimal side-effects and optimal pharmacokinetics in a mammalian organism. Capitalizing on control components that enable Caulobacter crescentus to metabolize vanillic acid originating from lignin degradation that occurs in its oligotrophic freshwater habitat, we have designed synthetic devices that specifically adjust transgene expression in mammalian cells when exposed to vanillic acid. Even in mice transgene expression was robust, precise and tunable in response to vanillic acid. As a licensed food additive that is regularly consumed by humans via flavoured convenience food and specific fresh vegetable and fruits, vanillic acid can be considered as a safe trigger molecule that could be used for diet-controlled transgene expression in future gene- and cell-based therapies.

Emerging biomedical applications of synthetic biology

Synthetic biology aims to create functional devices, systems and organisms with novel and useful functions on the basis of catalogued and standardized biological building blocks. Although they were initially constructed to elucidate the dynamics of simple processes, designed devices now contribute to the understanding of disease mechanisms, provide novel diagnostic tools, enable economic production of therapeutics and allow the design of novel strategies for the treatment of cancer, immune diseases and metabolic disorders, such as diabetes and gout, as well as a range of infectious diseases. In this Review, we cover the impact and potential of synthetic biology for biomedical applications.

The bacterial nanorecorder: engineering E. coli to function as a chemical recording device

Synthetic biology is an emerging branch of molecular biology that uses synthetic genetic constructs to create man-made cells or organisms that are capable of performing novel and/or useful applications. Using a synthetic chemically sensitive genetic toggle switch to activate appropriate fluorescent protein indicators (GFP, RFP) and a cell division inhibitor (minC), we have created a novel E. coli strain that can be used as a highly specific, yet simple and inexpensive chemical recording device. This biological "nanorecorder" can be used to determine both the type and the time at which a brief chemical exposure event has occurred. In particular, we show that the short-term exposure (15-30 min) of cells harboring this synthetic genetic circuit to small molecule signals (anhydrotetracycline or IPTG) triggered long-term and uniform cell elongation, with cell length being directly proportional to the time elapsed following a brief chemical exposure. This work demonstrates that facile modification of an existing genetic toggle switch can be exploited to generate a robust, biologically-based "nanorecorder" that could potentially be adapted to detect, respond and record a wide range of chemical stimuli that may vary over time and space.

Identification of novel targets for breast cancer by exploring gene switches on a genome scale

BACKGROUND

An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches.

RESULTS

We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER) and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2) is uncovered. We further suggest a likely transcription factor that regulates TACSTD2.

CONCLUSIONS

Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.

De novo design and construction of an inducible gene expression system in mammalian cells

Inducible expression systems represent the founding technology for the emergence of synthetic biology in mammalian cells. The core molecules in these systems are bacterial regulator proteins that bind to or dissociate from a cognate DNA operator sequence in response to an exogenous stimulus like a small-molecule inducer. In this chapter, we describe a generic protocol of how bacterial regulator proteins can be applied to the design, construction, and optimization of an inducible expression system in mammalian cells. By choosing regulator proteins with an appropriate small-molecule inducer, this protocol provides a straightforward approach for establishing biosensors, cell-to-cell communication systems, or tools to control gene expression in vivo.

Bistable responses in bacterial genetic networks: designs and dynamical consequences

A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles networks with bistable responses.

Inflammation, HIF-1, and the epigenetics that follows

We summarize recent findings linking inflammatory hypoxia to chromatin modifications, in particular to repressive histone signatures. We focus on the role of Hypoxia-Induced Factor-1 in promoting the activity of specific histone demethylases thus deeply modifying chromatin configuration. The consequences of these changes are depicted in terms of gene expression and cellular phenotypes. We finally integrate available data to introduce novel speculations on the relationship between inflammation, histones, and DNA function and integrity.

Hysteresis modeling for calcium-mediated ciliary beat frequency in airway epithelial cells

A hysteresis model is proposed to describe calcium-mediated Ciliary beat frequency (CBF) in airway epithelial cells. In this dynamic model, the kinetics of coupling between calcium and CBF is posited as a two-step configuration. First, Ca²+ directly binds to or indirectly acts on the axonemal proteins to modulate the activity of axonemal proteins. This step can be modeled by a Hill function in biochemistry. In the second step, the activity of axonemal proteins interacts with the sliding velocity of axonemal microtubules, the equivalent to regulating the CBF. The well-known Bouc-Wen model for hysteresis in mechanical engineering, which can only generate the stable clockwise hysteresis loops, is modified to describe the counter clockwise hysteresis loops commonly observed in the biological experiments. Based upon this new hysteresis model, the dynamic behavior of calcium-regulated CBF in epithelial airway cells is investigated through simulation studies. The numerical results demonstrate that the CBF dynamics in airway epithelial cells predicted by the hysteresis model is more consistent with the experimental observations than that predicted by previous static model in the literature.

Spatial cycles in G-protein crowd control

The nature of living systems and their apparent resilience to the second law of thermodynamics has been the subject of extensive investigation and imaginative speculation. The segregation and compartmentalization of proteins is one manifestation of this departure from equilibrium conditions; the effect of which is now beginning to be elucidated. This should not come as a surprise, as even a cursory inspection of cellular processes reveals the large amount of energetic cost borne to maintain cell-scale patterns, separations and gradients of molecules. The G-proteins, kinases, calcium-responsive proteins have all been shown to contain reaction cycles that are inherently coupled to their signalling activities. G-proteins represent an important and diverse toolset used by cells to generate cellular asymmetries. Many small G-proteins in particular, are dynamically acylated to modify their membrane affinities, or localized in an activity-dependent manner, thus manipulating the mobility modes of these proteins beyond pure diffusion and leading to finely tuned steady state partitioning into cellular membranes. The rates of exchange of small G-proteins over various compartments, as well as their steady state distributions enrich and diversify the landscape of possibilities that GTPase-dependent signalling networks can display over cellular dimensions. The chemical manipulation of spatial cycles represents a new approach for the modulation of cellular signalling with potential therapeutic benefits.

An engineered mammalian band-pass network

Gene expression circuitries, which enable cells to detect precise levels within a morphogen concentration gradient, have a pivotal impact on biological processes such as embryonic pattern formation, paracrine and autocrine signalling, and cellular migration. We present the rational synthesis of a synthetic genetic circuit exhibiting band-pass detection characteristics. The components, involving multiply linked mammalian trans-activator and -repressor control systems, were selected and fine-tuned to enable the detection of ‘low-threshold’ morphogen (tetracycline) concentrations, in which target gene expression was triggered, and a ‘high-threshold’ concentration, in which expression was muted. In silico predictions and supporting experimental findings indicated that the key criterion for functional band-pass detection was the matching of componentry that enabled sufficient separation of the low and high threshold points. Using the circuitry together with a fluorescence-encoded target gene, mammalian cells were genetically engineered to be capable of forming a band-like pattern of differentiation in response to a tetracycline chemical gradient. Synthetic gene networks designed to emulate naturally occurring gene behaviours provide not only insight into biological processes, but may also foster progress in future tissue engineering, gene therapy and biosensing applications.

Modeling bistable cell-fate choices in the Drosophila eye: qualitative and quantitative perspectives

A major goal of developmental biology is to understand the molecular mechanisms whereby genetic signaling networks establish and maintain distinct cell types within multicellular organisms. Here, we review cell-fate decisions in the developing eye of Drosophila melanogaster and the experimental results that have revealed the topology of the underlying signaling circuitries. We then propose that switch-like network motifs based on positive feedback play a central role in cell-fate choice, and discuss how mathematical modeling can be used to understand and predict the bistable or multistable behavior of such networks.

Synthetic biology: applications come of age

Early synthetic biology designs, namely the genetic toggle switch and repressilator, showed that regulatory components can be characterized and assembled to bring about complex, electronics-inspired behaviours in living systems (for example, memory storage and timekeeping).

Through the characterization and assembly of genetic parts and biological building blocks, many more devices have been constructed, including switches, memory elements, oscillators, pulse generators, digital logic gates, filters and communication modules.

Advances in the field are now allowing expansion beyond small gene networks to the realm of larger biological programs, which hold promise for a wide range of applications, including biosensing, therapeutics and the production of biofuels, pharmaceuticals and biomaterials.

Synthetic biosensing circuits consist of sensitive elements that bind analytes and transducer modules that mobilize cellular responses. Balancing these two modules involves engineering modularity and specificity into the various circuits.

Biosensor sensitive elements include environment-responsive promoters (transcriptional), RNA aptamers (translational) and protein receptors (post-translational).

Biosensor transducer modules include engineered gene networks (transcriptional), non-coding regulatory RNAs (translational) and protein signal-transduction circuits (post-translational).

The contributions of synthetic biology to therapeutics include: engineered networks and organisms for disease-mechanism elucidation, drug-target identification, drug-discovery platforms, therapeutic treatment, therapeutic delivery, and drug production and access.

In the microbial production of biofuels and pharmaceuticals, synthetic biology has supplemented traditional genetic and metabolic engineering efforts by aiding the construction of optimized biosynthetic pathways.

Optimizing metabolic flux through biosynthetic pathways is traditionally accomplished by driving the expression of pathway enzymes with strong, inducible promoters. New synthetic approaches include the rapid diversification of various pathway components, the rational and model-guided assembly of pathway components, and hybrid solutions.

Advances in the synthetic biology field are allowing an expansion beyond small gene networks towards larger biological programs that hold promise for a wide range of applications, including biosensing, therapeutics and the production of biofuels, pharmaceuticals and biomaterials.

Synthetic biology is bringing together engineers and biologists to design and build novel biomolecular components, networks and pathways, and to use these constructs to rewire and reprogram organisms. These re-engineered organisms will change our lives over the coming years, leading to cheaper drugs, 'green' means to fuel our cars and targeted therapies for attacking 'superbugs' and diseases, such as cancer. The de novo engineering of genetic circuits, biological modules and synthetic pathways is beginning to address these crucial problems and is being used in related practical applications.