A tunable genetic switch based on RNAi and repressor proteins for regulating gene expression in mammalian cells

Adoption of the Q Transcriptional System for Regulating Gene Expression in Stem Cells

The field of mammalian synthetic biology seeks to engineer enabling technologies to create novel approaches for programming cells to probe, perturb, and regulate gene expression with unprecedented precision. To accomplish this, new genetic parts continue to be identified that can be used to build novel genetic circuits to re-engineer cells to perform specific functions. Here, we establish a new transcription-based genetic circuit that combines genes from the quinic acid sensing metabolism of Neorospora crassa and the bacterial Lac repressor system to create a new orthogonal genetic tool to be used in mammalian cells. This work establishes a novel genetic tool, called LacQ, that functions to regulate gene expression in Chinese hamster ovarian (CHO) cells, human embryonic kidney 293 (HEK293) cells, and in mouse embryonic stem (ES) cells.

Synthetic circuits that process multiple light and chemical signal inputs

Background

Multi-signal processing circuits are essential for rational design of sophisticated synthetic systems with good controllability and modularity, therefore, enable construction of high-level networks. Moreover, light-inducible systems provide fast and reversible means for spatiotemporal control of gene expression.

Results

Here, in HEK 293 cells, we present combinatory genetic circuits responding to light and chemical signals, simultaneously. We first constructed a dual input circuit converting different light intensities into varying of the sensitivity of the promoter to a chemical inducer (doxycycline). Next, we generated a ternary input circuit, which responded to light, doxycycline and cumate. This circuit allowed us to use different combinations of blue light and the two chemical inducers to generate gradual output values over two orders of magnitude.

Conclusions

Overall, in this study, we devise genetic circuits sensing and processing light and chemical inducers. Our work may provide insights into bio-computation and fine-tuning expression of the transgene.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0384-y) contains supplementary material, which is available to authorized users.

Constructing "quantized quorums" to guide emergent phenotypes through quorum quenching capsules

Microbial cells have for many years been engineered to facilitate efficient production of biologics, chemicals, and other compounds. As the "metabolic" burden of synthetic genetic components can impair cell performance, microbial consortia are being developed to piece together specialized subpopulations that collectively produce desired products. Their use, however, has been limited by the inability to control their composition and function. One approach to leverage advantages of the division of labor within consortia is to link microbial subpopulations together through quorum sensing (QS) molecules. Previously, we directed the assembly of "quantized quorums," microbial subpopulations that are parsed through QS activation, by the exogenous addition of QS signal molecules to QS synthase mutants. In this work, we develop a more facile and general platform for creating "quantized quorums." Moreover, the methodology is not restricted to QS-mutant populations. We constructed quorum quenching capsules that partition QS-mediated phenotypes into discrete subpopulations. This compartmentalization guides QS subpopulations in a dose-dependent manner, parsing cell populations into activated or deactivated groups. The capsular "devices" consist of polyelectrolyte alginate-chitosan beads that encapsulate high-efficiency (HE) "controller cells" that, in turn, provide rapid uptake of the QS signal molecule AI-2 from culture fluids. In this methodology, instead of adding AI-2 to parse QS-mutants into subpopulations, we engineered cells to encapsulate them into compartments, and they serve to deplete AI-2 from wild-type populations. These encapsulated bacteria therefore, provide orthogonal control of population composition while allowing only minimal interaction with the product-producing cell population or consortia. We envision that compartmentalized control of QS should have applications in both metabolic engineering and human disease. Biotechnol. Bioeng. 2017;114: 407-415. © 2016 Wiley Periodicals, Inc.

Mammalian synthetic biology for studying the cell

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology.

A computational method for the investigation of multistable systems and its application to genetic switches

Background

Genetic switches exhibit multistability, form the basis of epigenetic memory, and are found in natural decision making systems, such as cell fate determination in developmental pathways. Synthetic genetic switches can be used for recording the presence of different environmental signals, for changing phenotype using synthetic inputs and as building blocks for higher-level sequential logic circuits. Understanding how multistable switches can be constructed and how they function within larger biological systems is therefore key to synthetic biology.

Results

Here we present a new computational tool, called StabilityFinder, that takes advantage of sequential Monte Carlo methods to identify regions of parameter space capable of producing multistable behaviour, while handling uncertainty in biochemical rate constants and initial conditions. The algorithm works by clustering trajectories in phase space, and iteratively minimizing a distance metric. Here we examine a collection of models of genetic switches, ranging from the deterministic Gardner toggle switch to stochastic models containing different positive feedback connections. We uncover the design principles behind making bistable, tristable and quadristable switches, and find that rate of gene expression is a key parameter. We demonstrate the ability of the framework to examine more complex systems and examine the design principles of a three gene switch. Our framework allows us to relax the assumptions that are often used in genetic switch models and we show that more complex abstractions are still capable of multistable behaviour.

Conclusions

Our results suggest many ways in which genetic switches can be enhanced and offer designs for the construction of novel switches. Our analysis also highlights subtle changes in correlation of experimentally tunable parameters that can lead to bifurcations in deterministic and stochastic systems. Overall we demonstrate that StabilityFinder will be a valuable tool in the future design and construction of novel gene networks.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0375-z) contains supplementary material, which is available to authorized users.

Mammalian Synthetic Biology: Time for Big MACs

The enabling technologies of synthetic biology are opening up new opportunities for engineering and enhancement of mammalian cells. This will stimulate diverse applications in many life science sectors such as regenerative medicine, development of biosensing cell lines, therapeutic protein production, and generation of new synthetic genetic regulatory circuits. Harnessing the full potential of these new engineering-based approaches requires the design and assembly of large DNA constructs-potentially up to chromosome scale-and the effective delivery of these large DNA payloads to the host cell. Random integration of large transgenes, encoding therapeutic proteins or genetic circuits into host chromosomes, has several drawbacks such as risks of insertional mutagenesis, lack of control over transgene copy-number and position-specific effects; these can compromise the intended functioning of genetic circuits. The development of a system orthogonal to the endogenous genome is therefore beneficial. Mammalian artificial chromosomes (MACs) are functional, add-on chromosomal elements, which behave as normal chromosomes-being replicating and portioned to daughter cells at each cell division. They are deployed as useful gene expression vectors as they remain independent from the host genome. MACs are maintained as a single-copy and can accommodate multiple gene expression cassettes of, in theory, unlimited DNA size (MACs up to 10 megabases have been constructed). MACs therefore enabled control over ectopic gene expression and represent an excellent platform to rapidly prototype and characterize novel synthetic gene circuits without recourse to engineering the host genome. This review describes the obstacles synthetic biologists face when working with mammalian systems and how the development of improved MACs can overcome these-particularly given the spectacular advances in DNA synthesis and assembly that are fuelling this research area.

Tools and applications in synthetic biology

Advances in synthetic biology have enabled the engineering of cells with genetic circuits in order to program cells with new biological behavior, dynamic gene expression, and logic control. This cellular engineering progression offers an array of living sensors that can discriminate between cell states, produce a regulated dose of therapeutic biomolecules, and function in various delivery platforms. In this review, we highlight and summarize the tools and applications in bacterial and mammalian synthetic biology. The examples detailed in this review provide insight to further understand genetic circuits, how they are used to program cells with novel functions, and current methods to reliably interface this technology in vivo; thus paving the way for the design of promising novel therapeutic applications.

Upgrading biomaterials with synthetic biological modules for advanced medical applications

One key aspect of synthetic biology is the development and characterization of modular biological building blocks that can be assembled to construct integrated cell-based circuits performing computational functions. Likewise, the idea of extracting biological modules from the cellular context has led to the development of in vitro operating systems. This principle has attracted substantial interest to extend the repertoire of functional materials by connecting them with modules derived from synthetic biology. In this respect, synthetic biological switches and sensors, as well as biological targeting or structure modules, have been employed to upgrade functions of polymers and solid inorganic material. The resulting systems hold great promise for a variety of applications in diagnosis, tissue engineering, and drug delivery. This review reflects on the most recent developments and critically discusses challenges concerning in vivo functionality and tolerance that must be addressed to allow the future translation of such synthetic biology-upgraded materials from the bench to the bedside.

Dose-Dependent Regulation of Alternative Splicing by MBNL Proteins Reveals Biomarkers for Myotonic Dystrophy

Alternative splicing is a regulated process that results in expression of specific mRNA and protein isoforms. Alternative splicing factors determine the relative abundance of each isoform. Here we focus on MBNL1, a splicing factor misregulated in the disease myotonic dystrophy. By altering the concentration of MBNL1 in cells across a broad dynamic range, we show that different splicing events require different amounts of MBNL1 for half-maximal response, and respond more or less steeply to MBNL1. Motifs around MBNL1 exon 5 were studied to assess how cis-elements mediate the MBNL1 dose-dependent splicing response. A framework was developed to estimate MBNL concentration using splicing responses alone, validated in the cell-based model, and applied to myotonic dystrophy patient muscle. Using this framework, we evaluated the ability of individual and combinations of splicing events to predict functional MBNL concentration in human biopsies, as well as their performance as biomarkers to assay mild, moderate, and severe cases of DM.

Our studies provide insight into the mechanisms of myotonic dystrophy, the most common adult form of muscular dystrophy. In this disease, a family of RNA binding proteins is sequestered by toxic RNA, which leads to mis-regulation and disease symptoms. We have created a cellular model with one of these family members to study how these RNA binding proteins function in the absence of the toxic RNA. In parallel, we analyzed transcriptomic data from over 50 individuals (44 affected by myotonic dystrophy) with a range of disease severity. The results from the transcriptomic data provide a rational approach to select biomarkers for clinical research and therapeutic trials.

Toward the First Data Acquisition Standard in Synthetic Biology

This paper describes the development of a new data acquisition standard for synthetic biology. This comprises the creation of a methodology that is designed to capture all the data, metadata, and protocol information associated with biopart characterization experiments. The new standard, called DICOM-SB, is based on the highly successful Digital Imaging and Communications in Medicine (DICOM) standard in medicine. A data model is described which has been specifically developed for synthetic biology. The model is a modular, extensible data model for the experimental process, which can optimize data storage for large amounts of data. DICOM-SB also includes services orientated toward the automatic exchange of data and information between modalities and repositories. DICOM-SB has been developed in the context of systematic design in synthetic biology, which is based on the engineering principles of modularity, standardization, and characterization. The systematic design approach utilizes the design, build, test, and learn design cycle paradigm. DICOM-SB has been designed to be compatible with and complementary to other standards in synthetic biology, including SBOL. In this regard, the software provides effective interoperability. The new standard has been tested by experiments and data exchange between Nanyang Technological University in Singapore and Imperial College London.

Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells

One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators.

Engineering Gene Circuits for Mammalian Cell-Based Applications

Synthetic gene switches are basic building blocks for the construction of complex gene circuits that transform mammalian cells into useful cell-based machines for next-generation biotechnological and biomedical applications. Ligand-responsive gene switches are cellular sensors that are able to process specific signals to generate gene product responses. Their involvement in complex gene circuits results in sophisticated circuit topologies that are reminiscent of electronics and that are capable of providing engineered cells with the ability to memorize events, oscillate protein production, and perform complex information-processing tasks. Microencapsulated mammalian cells that are engineered with closed-loop gene networks can be implanted into mice to sense disease-related input signals and to process this information to produce a custom, fine-tuned therapeutic response that rebalances animal metabolism. Progress in gene circuit design, in combination with recent breakthroughs in genome engineering, may result in tailored engineered mammalian cells with great potential for future cell-based therapies.

Stability of genetic regulatory networks based on switched systems and mixed time-delays

In this paper, the switched genetic regulatory networks (GRNs) are modeled from a real biological system, based on switched systems, noise and mixed time-delays. Global asymptotical stability for the proposed switched GRNs are studied by the Lyapunov method and the matrix inequality techniques. Some new sufficient conditions are obtained to ensure the global asymptotical stability of the proposed switched GRNs. Furthermore, the proposed LMI results are computationally efficient as it can be solved numerically with standard commercial software. Finally, an example is provided to illustrate the usefulness of the results.

Hypothetical biomolecular probe based on a genetic switch with tunable symmetry and stability

Background

Genetic switches are ubiquitous in nature, frequently associated with the control of cellular functions and developmental programs. In the realm of synthetic biology, it is of great interest to engineer genetic circuits that can change their mode of operation from monostable to bistable, or even to multistable, based on the experimental fine-tuning of readily accessible parameters. In order to successfully design robust, bistable synthetic circuits to be used as biomolecular probes, or understand modes of operation of such naturally occurring circuits, we must identify parameters that are key in determining their characteristics.

Results

Here, we analyze the bistability properties of a general, asymmetric genetic toggle switch based on a chemical-reaction kinetic description. By making appropriate approximations, we are able to reduce the system to two coupled differential equations. Their deterministic stability analysis and stochastic numerical simulations are in excellent agreement. Drawing upon this general framework, we develop a model of an experimentally realized asymmetric bistable genetic switch based on the LacI and TetR repressors. By varying the concentrations of two synthetic inducers, doxycycline and isopropyl β-D-1-thiogalactopyranoside, we predict that it will be possible to repeatedly fine-tune the mode of operation of this genetic switch from monostable to bistable, as well as the switching rates over many orders of magnitude, in an experimental setting. Furthermore, we find that the shape and size of the bistability region is closely connected with plasmid copy number.

Conclusions

Based on our numerical calculations of the LacI-TetR asymmetric bistable switch phase diagram, we propose a generic work-flow for developing and applying biomolecular probes: Their initial state of operation should be specified by controlling inducer concentrations, and dilution due to cellular division would turn the probes into memory devices in which information could be preserved over multiple generations. Additionally, insights from our analysis of the LacI-TetR system suggest that this particular system is readily available to be employed in this kind of probe.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0279-y) contains supplementary material, which is available to authorized users.

Mammalian synthetic biology: emerging medical applications

In this review, we discuss new emerging medical applications of the rapidly evolving field of mammalian synthetic biology. We start with simple mammalian synthetic biological components and move towards more complex and therapy-oriented gene circuits. A comprehensive list of ON-OFF switches, categorized into transcriptional, post-transcriptional, translational and post-translational, is presented in the first sections. Subsequently, Boolean logic gates, synthetic mammalian oscillators and toggle switches will be described. Several synthetic gene networks are further reviewed in the medical applications section, including cancer therapy gene circuits, immuno-regulatory networks, among others. The final sections focus on the applicability of synthetic gene networks to drug discovery, drug delivery, receptor-activating gene circuits and mammalian biomanufacturing processes.

Engineering Synthetic Gene Circuits in Living Cells with CRISPR Technology

One of the goals of synthetic biology is to build regulatory circuits that control cell behavior, for both basic research purposes and biomedical applications. The ability to build transcriptional regulatory devices depends on the availability of programmable, sequence-specific, and effective synthetic transcription factors (TFs). The prokaryotic clustered regularly interspaced short palindromic repeat (CRISPR) system, recently harnessed for transcriptional regulation in various heterologous host cells, offers unprecedented ease in designing synthetic TFs. We review how CRISPR can be used to build synthetic gene circuits and discuss recent advances in CRISPR-mediated gene regulation that offer the potential to build increasingly complex, programmable, and efficient gene circuits in the future.

Layer-by-layer inorganic/polymeric nanoparticles for kinetically controlled multigene delivery

Nonviral gene delivery methods represent a potential safe and effective approach for treating myriad diseases. For many gene therapy applications, delivering multiple exogenous genes and controlling the time profile that these genes are expressed would be advantageous. Polymeric nonviral gene carriers are versatile and can be readily tailored for particular therapeutic applications, have the ability to carry multiple large genes within each particle, and can be more easily manufactured than viruses used for gene delivery. A layer-by-layer (LbL) theranostic-enabling nanoparticle was developed to incorporate two plasmid types which have differing expression time profiles. Temporally controlling the expression of exogenous DNA enables superior control over the microenvironment and could lead to better control over differentiation pathways and cell fate. © 2015 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 707-713, 2016.

Synthetic Biology--Toward Therapeutic Solutions

Higher multicellular organisms have evolved sophisticated intracellular and intercellular biological networks that enable cell growth and survival to fulfill an organism's needs. Although such networks allow the assembly of complex tissues and even provide healing and protective capabilities, malfunctioning cells can have severe consequences for an organism's survival. In humans, such events can result in severe disorders and diseases, including metabolic and immunological disorders, as well as cancer. Dominating the therapeutic frontier for these potentially lethal disorders, cell and gene therapies aim to relieve or eliminate patient suffering by restoring the function of damaged, diseased, and aging cells and tissues via the introduction of healthy cells or alternative genes. However, despite recent success, these efforts have yet to achieve sufficient therapeutic effects, and further work is needed to ensure the safe and precise control of transgene expression and cellular processes. In this review, we describe the biological tools and devices that are at the forefront of synthetic biology and discuss their potential to advance the specificity, efficiency, and safety of the current generation of cell and gene therapies, including how they can be used to confer curative effects that far surpass those of conventional therapeutics. We also highlight the current therapeutic delivery tools and the current limitations that hamper their use in human applications.

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.

Synthetic feedback control using an RNAi-based gene-regulatory device

Background

Homeostasis within mammalian cells is achieved through complex molecular networks that can respond to changes within the cell or the environment and regulate the expression of the appropriate genes in response. The development of biological components that can respond to changes in the cellular environment and interface with endogenous molecules would enable more sophisticated genetic circuits and greatly advance our cellular engineering capabilities.

Results

Here we describe a platform that combines a ligand-responsive ribozyme switch and synthetic miRNA regulators to create an OFF genetic control device based on RNA interference (RNAi). We developed a mathematical model to highlight important design parameters in programming the quantitative performance of RNAi-based OFF control devices. By modifying the ribozyme switch integrated into the system, we demonstrated RNAi-based OFF control devices that respond to small molecule and protein ligands, including the oncogenic protein E2F1. We utilized the OFF control device platform to build a negative feedback control system that acts as a proportional controller and maintains target intracellular protein levels in response to increases in transcription rate.

Conclusions

Our work describes a novel genetic device that increases the level of silencing from a miRNA in the presence of a ligand of interest, effectively creating an RNAi-based OFF control device. The OFF switch platform has the flexibility to be used to respond to both small molecule and protein ligands. Finally, the RNAi-based OFF switch can be used to implement a negative feedback control system, which maintains target protein levels around a set point level. The described RNAi-based OFF control device presents a powerful tool that will enable researchers to engineer homeostasis in mammalian cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s13036-015-0002-3) contains supplementary material, which is available to authorized users.

A high-efficiency recombineering system with PCR-based ssDNA in Bacillus subtilis mediated by the native phage recombinase GP35

Bacillus subtilis and its closely related species are important strains for industry, agriculture, and medicine. However, it is difficult to perform genetic manipulations using the endogenous recombination machinery. In many bacteria, phage recombineering systems have been employed to improve recombineering frequencies. To date, an efficient phage recombineering system for B. subtilis has not been reported. Here, we, for the first time, identified that GP35 from the native phage SPP1 exhibited a high recombination activity in B. subtilis. On this basis, we developed a high-efficiency GP35-meditated recombineering system. Taking single-stranded DNA (ssDNA) as a recombineering substrate, ten recombinases from diverse sources were investigated in B. subtilis W168. GP35 showed the highest recombineering frequency (1.71 ± 0.15 × 10(-1)). Besides targeting the purine nucleoside phosphorylase gene (deoD), we also demonstrated the utility of GP35 and Beta from Escherichia coli lambda phage by deleting the alpha-amylase gene (amyE) and uracil phosphoribosyltransferase gene (upp). In all three genetic loci, GP35 exhibited a higher frequency than Beta. Moreover, a phylogenetic tree comparing the kinship of different recombinase hosts with B. subtilis was constructed, and the relationship between the recombineering frequency and the kinship of the host was further analyzed. The results suggested that closer kinship to B. subtilis resulted in higher frequency in B. subtilis. In conclusion, the recombinase from native phage or prophage can significantly promote the genetic recombineering frequency in its host, providing an effective genetic tool for constructing genetically engineered strains and investigating bacterial physiology.

Inducible suppression of global translation by overuse of rare codons

Recently, artificial gene networks have been developed in synthetic biology to control gene expression and make organisms as controllable as robots. Here, I present an artificial posttranslational gene-silencing system based on the codon usage bias and low tRNA content corresponding to minor codons. I engineered the green fluorescent protein (GFP) gene to inhibit translation indirectly with the lowest-usage codons to monopolize various minor tRNAs (lgfp). The expression of lgfp interfered nonspecifically with the growth of Escherichia coli, Saccharomyces cerevisiae, human HeLa cervical cancer cells, MCF7 breast cancer cells, and HEK293 kidney cells, as well as phage and adenovirus expansion. Furthermore, insertion of lgfp downstream of a phage response promoter conferred phage resistance on E. coli. Such engineered gene silencers could act as components of biological networks capable of functioning with suitable promoters in E. coli, S. cerevisiae, and human cells to control gene expression. The results presented here show general suppressor artificial genes for live cells and viruses. This robust system provides a gene expression or cell growth control device for artificially synthesized gene networks.

Applications of synthetic gene networks

Synthetic gene networks have evolved from simple proof-of-concept circuits to complex therapy-oriented networks over the past 15 years. This advancement has greatly facilitated the expansion of the emerging field of synthetic biology. In this review, we highlight the main applications ofsynthetic gene networks in understanding biological design principles, developing biosensors for diagnosis, producing industrial and biomedical compounds, and treating human diseases. Finally, we outline current challenges and future prospects of synthetic gene networks for advancing practical applications.

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.

CRISPR-based self-cleaving mechanism for controllable gene delivery in human cells

Controllable gene delivery via vector-based systems remains a formidable challenge in mammalian synthetic biology and a desirable asset in gene therapy applications. Here, we introduce a methodology to control the copies and residence time of a gene product delivered in host human cells but also selectively disrupt fragments of the delivery vehicle. A crucial element of the proposed system is the CRISPR protein Cas9. Upon delivery, Cas9 guided by a custom RNA sequence cleaves the delivery vector at strategically placed targets thereby inactivating a co-expressed gene of interest. Importantly, using experiments in human embryonic kidney cells, we show that specific parameters of the system can be adjusted to fine-tune the delivery properties. We envision future applications in complex synthetic biology architectures, gene therapy and trace-free delivery.

A library of mammalian effector modules for synthetic morphology

BACKGROUND

In mammalian development, the formation of most tissues is achieved by a relatively small repertoire of basic morphogenetic events (e.g. cell adhesion, locomotion, apoptosis, etc.), permutated in various sequences to form different tissues. Together with cell differentiation, these mechanisms allow populations of cells to organize themselves into defined geometries and structures, as simple embryos develop into complex organisms. The control of tissue morphogenesis by populations of engineered cells is a potentially very powerful but neglected aspect of synthetic biology.

RESULTS

We have assembled a modular library of synthetic morphogenetic driver genes to control (separately) mammalian cell adhesion, locomotion, fusion, proliferation and elective cell death. Here we describe this library and demonstrate its use in the T-REx-293 human cell line to induce each of these desired morphological behaviours on command.

CONCLUSIONS

Building on from the simple test systems described here, we want to extend engineered control of morphogenetic cell behaviour to more complex 3D structures that can inform embryologists and may, in the future, be used in surgery and regenerative medicine, making synthetic morphology a powerful tool for developmental biology and tissue engineering.

Programming the group behaviors of bacterial communities with synthetic cellular communication

Synthetic biology is a newly emerged research discipline that focuses on the engineering of novel cellular behaviors and functionalities through the creation of artificial gene circuits. One important class of synthetic circuits currently under active development concerns the programming of bacterial cellular communication and collective population-scale behaviors. Because of the ubiquity of cell-cell interactions within bacterial communities, having an ability of engineering these circuits is vital to programming robust cellular behaviors. Here, we highlight recent advances in communication-based synthetic gene circuits by first discussing natural communication systems and then surveying various functional engineered circuits, including those for population density control, temporal synchronization, spatial organization, and ecosystem formation. We conclude by summarizing recent advances, outlining existing challenges, and discussing potential applications and future opportunities.

Digital switching in a biosensor circuit via programmable timing of gene availability

Transient delivery of gene circuits is required in many potential applications of synthetic biology, yet pre-steady-state processes that dominate this delivery route pose significant challenges for robust circuit deployment. Here we show that site-specific recombinases can rectify undesired effects by programmable timing of gene availability in multi-gene circuits. We exemplify the concept with a proportional sensor for endogenous microRNA and show dramatic reduction in its ground state leakage thanks to desynchronization of circuit’s repressor components and their repression target. The new sensors display dynamic range of up to 1000-fold compared to 20-fold in the standard configuration. We applied the approach to classify cell types based on miRNA expression profile and measured > 200-fold output differential between positively- and negatively-identified cells. We also showed major improvement of specificity with cytotoxic output. Our study opens new venues in gene circuit design via judicious temporal control of circuits’ genetic makeup.

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.

A quantitative framework for the forward design of synthetic miRNA circuits

Synthetic genetic circuits incorporating regulatory components based on RNA interference (RNAi) have been used in a variety of systems. A comprehensive understanding of the parameters that determine the relationship between microRNA (miRNA) and target expression levels is lacking. We describe a quantitative framework supporting the forward engineering of gene circuits that incorporate RNAi-based regulatory components in mammalian cells. We developed a model that captures the quantitative relationship between miRNA and target gene expression levels as a function of parameters, including mRNA half-life and miRNA target-site number. We extended the model to synthetic circuits that incorporate protein-responsive miRNA switches and designed an optimized miRNA-based protein concentration detector circuit that noninvasively measures small changes in the nuclear concentration of β-catenin owing to induction of the Wnt signaling pathway. Our results highlight the importance of methods for guiding the quantitative design of genetic circuits to achieve robust, reliable and predictable behaviors in mammalian cells.

Linear population allocation by bistable switches in response to transient stimulation

Many cellular decision processes, including proliferation, differentiation, and phenotypic switching, are controlled by bistable signaling networks. In response to transient or intermediate input signals, these networks allocate a population fraction to each of two distinct states (e.g. OFF and ON). While extensive studies have been carried out to analyze various bistable networks, they are primarily focused on responses of bistable networks to sustained input signals. In this work, we investigate the response characteristics of bistable networks to transient signals, using both theoretical analysis and numerical simulation. We find that bistable systems exhibit a common property: for input signals with short durations, the fraction of switching cells increases linearly with the signal duration, allowing the population to integrate transient signals to tune its response. We propose that this allocation algorithm can be an optimal response strategy for certain cellular decisions in which excessive switching results in lower population fitness.

Negative autoregulation matches production and demand in synthetic transcriptional networks

We propose a negative feedback architecture that regulates activity of artificial genes, or "genelets", to meet their output downstream demand, achieving robustness with respect to uncertain open-loop output production rates. In particular, we consider the case where the outputs of two genelets interact to form a single assembled product. We show with analysis and experiments that negative autoregulation matches the production and demand of the outputs: the magnitude of the regulatory signal is proportional to the "error" between the circuit output concentration and its actual demand. This two-device system is experimentally implemented using in vitro transcriptional networks, where reactions are systematically designed by optimizing nucleic acid sequences with publicly available software packages. We build a predictive ordinary differential equation (ODE) model that captures the dynamics of the system and can be used to numerically assess the scalability of this architecture to larger sets of interconnected genes. Finally, with numerical simulations we contrast our negative autoregulation scheme with a cross-activation architecture, which is less scalable and results in slower response times.

Enhanced killing of antibiotic-resistant bacteria enabled by massively parallel combinatorial genetics

New therapeutic strategies are needed to treat infections caused by drug-resistant bacteria, which constitute a major growing threat to human health. Here, we use a high-throughput technology to identify combinatorial genetic perturbations that can enhance the killing of drug-resistant bacteria with antibiotic treatment. This strategy, Combinatorial Genetics En Masse (CombiGEM), enables the rapid generation of high-order barcoded combinations of genetic elements for high-throughput multiplexed characterization based on next-generation sequencing. We created ∼ 34,000 pairwise combinations of Escherichia coli transcription factor (TF) overexpression constructs. Using Illumina sequencing, we identified diverse perturbations in antibiotic-resistance phenotypes against carbapenem-resistant Enterobacteriaceae. Specifically, we found multiple TF combinations that potentiated antibiotic killing by up to 10(6)-fold and delivered these combinations via phagemids to increase the killing of highly drug-resistant E. coli harboring New Delhi metallo-beta-lactamase-1. Moreover, we constructed libraries of three-wise combinations of transcription factors with >4 million unique members and demonstrated that these could be tracked via next-generation sequencing. We envision that CombiGEM could be extended to other model organisms, disease models, and phenotypes, where it could accelerate massively parallel combinatorial genetics studies for a broad range of biomedical and biotechnology applications, including the treatment of antibiotic-resistant infections.

Gene networks of fully connected triads with complete auto-activation enable multistability and stepwise stochastic transitions

Fully-connected triads (FCTs), such as the Oct4-Sox2-Nanog triad, have been implicated as recurring transcriptional motifs embedded within the regulatory networks that specify and maintain cellular states. To explore the possible connections between FCT topologies and cell fate determinations, we employed computational network screening to search all possible FCT topologies for multistability, a dynamic property that allows the rise of alternate regulatory states from the same transcriptional network. The search yielded a hierarchy of FCTs with various potentials for multistability, including several topologies capable of reaching eight distinct stable states. Our analyses suggested that complete auto-activation is an effective indicator for multistability, and, when gene expression noise was incorporated into the model, the networks were able to transit multiple states spontaneously. Different levels of stochasticity were found to either induce or disrupt random state transitioning with some transitions requiring layovers at one or more intermediate states. Using this framework we simulated a simplified model of induced pluripotency by including constitutive overexpression terms. The corresponding FCT showed random state transitioning from a terminal state to the pluripotent state, with the temporal distribution of this transition matching published experimental data. This work establishes a potential theoretical framework for understanding cell fate determinations by connecting conserved regulatory modules with network dynamics. Our results could also be employed experimentally, using established developmental transcription factors as seeds, to locate cell lineage specification networks by using auto-activation as a cipher.

Antagonistic control of a dual-input mammalian gene switch by food additives

Synthetic biology has significantly advanced the design of mammalian trigger-inducible transgene-control devices that are able to programme complex cellular behaviour. Fruit-based benzoate derivatives licensed as food additives, such as flavours (e.g. vanillate) and preservatives (e.g. benzoate), are a particularly attractive class of trigger compounds for orthogonal mammalian transgene control devices because of their innocuousness, physiological compatibility and simple oral administration. Capitalizing on the genetic componentry of the soil bacterium Comamonas testosteroni, which has evolved to catabolize a variety of aromatic compounds, we have designed different mammalian gene expression systems that could be induced and repressed by the food additives benzoate and vanillate. When implanting designer cells engineered for gene switch-driven expression of the human placental secreted alkaline phosphatase (SEAP) into mice, blood SEAP levels of treated animals directly correlated with a benzoate-enriched drinking programme. Additionally, the benzoate-/vanillate-responsive device was compatible with other transgene control systems and could be assembled into higher-order control networks providing expression dynamics reminiscent of a lap-timing stopwatch. Designer gene switches using licensed food additives as trigger compounds to achieve antagonistic dual-input expression profiles and provide novel control topologies and regulation dynamics may advance future gene- and cell-based therapies.

Integrating biological redesign: where synthetic biology came from and where it needs to go

Synthetic biology seeks to extend approaches from engineering and computation to redesign of biology, with goals such as generating new chemicals, improving human health, and addressing environmental issues. Early on, several guiding principles of synthetic biology were articulated, including design according to specification, separation of design from fabrication, use of standardized biological parts and organisms, and abstraction. We review the utility of these principles over the past decade in light of the field's accomplishments in building complex systems based on microbial transcription and metabolism and describe the progress in mammalian cell engineering.

MicroRNA-based single-gene circuits buffer protein synthesis rates against perturbations

Achieving precise control of mammalian transgene expression has remained a long-standing, and increasingly urgent, challenge in biomedical science. Despite much work, single-cell methods have consistently revealed that mammalian gene expression levels remain susceptible to fluctuations (noise) and external perturbations. Here, we show that precise control of protein synthesis can be realized using a single-gene microRNA (miRNA)-based feed-forward loop (sgFFL). This minimal autoregulatory gene circuit consists of an intronic miRNA that targets its own transcript. In response to a step-like increase in transcription rate, the network generated a transient protein expression pulse before returning to a lower steady state level, thus exhibiting adaptation. Critically, the steady state protein levels were independent of the size of the stimulus, demonstrating that this simple network architecture effectively buffered protein production against changes in transcription. The single-gene network architecture was also effective in buffering against transcriptional noise, leading to reduced cell-to-cell variability in protein synthesis. Noise was up to 5-fold lower for a sgFFL than for an unregulated control gene with equal mean protein levels. The noise buffering capability varied predictably with the strength of the miRNA-target interaction. Together, these results suggest that the sgFFL single-gene motif provides a general and broadly applicable platform for robust gene expression in synthetic and natural gene circuits.

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.

The synthetic biology future

Herein, I track the evolution of synthetic biology from its earliest incarnations more than 50 years ago, through the DIYbio revolution, to the next 50 years.

Effect of tumor suppressor gene cyclin-dependent kinase inhibitor 2A wild-type and A148T mutant on the cell cycle of human ovarian cancer cells

Single-base substitution may affect the function of genes. This study identified a single-base substitution of G for A in codon 148 of cyclin-dependent kinase inhibitor 2A (CDKN2A/p16) by sequencing human ovarian cancer cell line UACC-1598. As a tumor suppressor gene, the expression of CDKN2A/p16 should be strictly controlled. In order to control CDKN2A/p16 gene expression, an inducible pTUNE vector system was selected. Using recombinant DNA technology, a CDKN2A/p16-A148T and CDKN2A/p16-wild-type gene expression system was successfully constructed to investigate whether this single-base substitution affects the function of CDKN2A/p16. For the wild-type and the mutant, expression of CDKN2A/p16-green fluorescent protein fusion protein increased markedly following isopropyl-β-D-thiogalactoside induction, and was accompanied by significant G1 arrest in the transfected human ovarian cancer SKOV3 cell line. The inducible vectors used in this study, CDKN2A/p16-wild-type and CDKN2A/p16-A148T open reading frame, may be useful for further investigation into whether this somatic mutation could alter the function of CDKN2A/p16 as a tumor suppressor gene. In summary, CDKN2A/p16-A148T was identified in ovarian cancer cells, and this single-base substitution did not affect the ability of CDKN2A/p16 to arrest the cell cycle.

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.

Bile acid-controlled transgene expression in mammalian cells and mice

In recent years, using trigger-inducible mammalian gene switches to design sophisticated transcription-control networks has become standard practice in synthetic biology. These switches provide unprecedented precision, complexity and reliability when programming novel mammalian cell functions. Metabolite-responsive repressors of human-pathogenic bacteria are particularly attractive for use in these orthogonal synthetic mammalian gene switches because the trigger compound sensitivity often matches the human physiological range. We have designed both a bile acid-repressible (BEAROFF) as well as a bile-acid-inducible (BEARON) gene switch by capitalizing on components that have evolved to manage bile acid resistance in Campylobacter jejuni, the leading causative agent of human food-borne enteritis. We have shown that both of these switches enable bile acid-adjustable transgene expression in different mammalian cell lines as well as in mice. For the BEAROFF device, the C. jejuni repressor CmeR was fused to the VP16 transactivation domain to create a synthetic transactivator that activates minimal promoters containing tandem operator modules (Ocme) in a bile acid-repressible manner. Fusion of CmeR to a transsilencing domain resulted in an artificial transsilencer that binds and represses a constitutive Ocme-containing promoter until it is released by addition of bile acid (BEARON). A tailored multi-step tuning program for the inducible gene switch, which included the optimization of individual component performance, control of their relative abundances, the choice of the cell line and trigger compound, resulted in a BEARON device with significantly improved bile acid-responsive control characteristics. Synthetic metabolite-triggered gene switches that are able to interface with host metabolism may foster advances in future gene and cell-based therapies.

Development of a Positive-readout Mouse Model of siRNA Pharmacodynamics

Development of RNAi-based therapeutics has the potential to revolutionize treatment options for a range of human diseases. However, as with gene therapy, a major barrier to progress is the lack of methods to achieve and measure efficient delivery for systemic administration. We have developed a positive-readout pharmacodynamic transgenic reporter mouse model allowing noninvasive real-time assessment of siRNA activity. The model combines a luciferase reporter gene under the control of regulatory elements from the lac operon of Escherichia coli. Introduction of siRNA targeting lac repressor results in increased luciferase expression in cells where siRNA is biologically active. Five founder luciferase-expressing and three founder Lac-expressing lines were generated and characterized. Mating of ubiquitously expressing luciferase and lac lines generated progeny in which luciferase expression was significantly reduced compared with the parental line. Administration of isopropyl β-D-1-thiogalactopyranoside either in drinking water or given intraperitoneally increased luciferase expression in eight of the mice examined, which fell rapidly when withdrawn. Intraperitoneal administration of siRNA targeting lac in combination with Lipofectamine 2000 resulted in increased luciferase expression in the liver while control nontargeting siRNA had no effect. We believe a sensitive positive readout pharmacodynamics reporter model will be of use to the research community in RNAi-based vector development.

DNA strand displacement system running logic programs

The paper presents a DNA-based computing model which is enzyme-free and autonomous, not requiring a human intervention during the computation. The model is able to perform iterated resolution steps with logical formulae in conjunctive normal form. The implementation is based on the technique of DNA strand displacement, with each clause encoded in a separate DNA molecule. Propositions are encoded assigning a strand to each proposition p, and its complementary strand to the proposition ¬p; clauses are encoded comprising different propositions in the same strand. The model allows to run logic programs composed of Horn clauses by cascading resolution steps. The potential of the model is demonstrated also by its theoretical capability of solving SAT. The resulting SAT algorithm has a linear time complexity in the number of resolution steps, whereas its spatial complexity is exponential in the number of variables of the formula.