Poster Presentations

Tailing ponds are concentrated pools of toxic and corrosive compounds that are produced from oil and mining extraction. The Calgary iGEM team aims to alleviate this potential economic and environmental threat by developing a detection and bioremediation system for the toxins present in tailing ponds. Our system is composed of FRED, the Functional, Robust, Electrochemical Detector, and OSCAR, the Optimized System for Carboxylic Acid Remediation. FRED is capable of detecting multiple compounds present within a sample using an electrochemical output. We created open-source hardware and software to work with FRED to produce a complete biosensor system. OSCAR is able to break down toxic compounds converting them into potentially useable hydrocarbons. In addition, impurities (sulphur, nitrogen) are removed through known degradative microbial pathways from tailing pond waters. We combined OSCAR with a bioreactor system that was engineered and modeled to provide optimal growth conditions and physical containment from the environment. Further layers of containment considerations were developed through kill-switch mechanisms and auxotrophy to prevent accidental release of both FRED and OSCAR into the environment where they could disturb natural organisms. Overall, this system aims to detect and convert toxins into recoverable hydrocarbons in an economical, safe and self-contained process.

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Direct conversion of CO2 to fuel or drug using the ability of carbon fixation of photoautotrophic organisms, such as cyanobacteria, has received increasing attention to solve the energy or environmental problem. We aim to construct a synthetic cyanobacterial host designated as “The CyanofactoryTM”, in which we can control biofuel production, aggregation, and cell lysis by various light signals. Among the many biological tools for cell optimization, RNA has great potential because it can be conveniently designed based on its sequence and predicted structure. In this study, we designed two coupled riboregulators (crRNA and taRNA) to regulate gene expression in cyanobacteria. Located in the 5 untranslated region of a target gene, the crRNA forms a stem-loop structure that includes the ribosome-binding site (RBS), thus preventing the binding of the ribosome to the RBS, resulting in repression of translation of the target gene. The taRNA, which includes a complementary sequence to a region of the crRNA, disrupts the crRNA stem-loop structure, resulting in activation of translation of the target gene. The strict control of gene expression that can be achieved with riboregulators allows us to better control cell activity with various external signals. We designed riboregulators that has RBS designated RBS* showed higher expression level in Synechocystis sp. PCC6803. Fist of all, we evaluated the function of designed riboregulators using GFP as reporter protein in E. coli. By adjusting intramolecular or intermolecular hybridization energy of crRNA or between crRNA and taRNA, respectively, we have succeeded in construction of crRNA, which has RBS* and taRNA. Designed riboregulators also worked well in Synechocystis sp. PCC6803. Since riboregulators can adjust proper gene expression level, they would be useful tools for biofuel production in cyanobacteria.

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Recent synthetic biology projects at BBN Technologies have produced a number of new methods for computational design and analysis of transcriptional logic circuits. To facilitate use of these methods by our collaborators, and to disseminate them more widely through the synthetic biology community, we have implemented several of these methods as web-tools. These web-tools are free, publicly accessible (https://synbiotools.bbn.com), and allow practitioners to take advantage of complex analytics and data management technologies without needing to grapple with a software infrastructure that combines Octave, python, C++, GraphViz, XML, and MySQL. The web-tools keep users’ data private, provide access to the latest code updates, and include documentation. At present, three tools are available online: * The Color Model analysis tool uses flow cytometry control data to produce a non-linear color model that maps fluorescence values to standard units, following the methods described in [1]. * The Characterization Experiments tool provides detailed quantitative analysis of flow cytometry data for experiments such as input-output transfer curves and time series, following the methods described in [1]. * The Biocompiler tool transforms high-level program descriptions into GRNs following the methods described in [2]. Each tool produces both machine-readable and graphical results. Several laboratories are already using these tools, and we hope the web-tools help disseminate our results and seed many more productive collaborations. Our future work includes: simplifying data entry using experiment templates, improving the user interface per user feedback, supporting sharing of data within a group, and adding more tools. [1]: A Method for Fast, High-Precision Characterization of Synthetic Biology Devices, Jacob Beal, Ron Weiss, Fusun Yaman, Noah Davidsohn, and Aaron Adler, MIT CSAIL Tech Report 2012-008, April, 2012. [2]: Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks, Jacob Beal, Ting Lu, Ron Weiss, PLoS ONE 6(8): e22490.

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The purine metabolism pathway is highly conserved from yeast to humans. This pathway includes both the de-novo biosynthesis of AMP and GMP as well as the salvage pathway that regenerates AMP and GMP from nucleic acid turnover. In humans there are more than 20 disorders associated with the purine pathway, and they include a variety of symptoms, including: Gout, autism, blindness, loss of immunity, kidney failure and different neurological abnormalities. Some of these diseases and their hallmarks were extensively studied, however some of the symptoms associated with other disorders are much less well understood. The high conservation of the purine biosynthesis pathway between yeast and humans allows the study of the pathway and the mutational effects to be done in yeast. Using a synthetic approach, we are swapping the entire purine biosynthesis pathway of the yeast with the cognate human genes. We are cloning each human codon optimized gene under its yeast ortholog promoter and terminator. Each gene will be examined for its ability to complement the corresponding deletion of the yeast gene. In addition to swapping each gene at a time, all 26 genes participating in this pathway will be added to yeast cells on a single plasmid. This will allow for future investigation of the entire pathway, and its associated genes, in a variety of yeast based high-throughput methods as well as screening for new drugs for the pathway associated diseases.

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We have analyzed the evolution of the cells aggregation in the frame of polycyclic age-structured model using both the analytical technique and numerical simulation approaches. In the first case we have reduced the temporal-age initial boundary problem for the transport equation to the Volterra integral equation and have resolved it used infinite convergent series. In the second one we have built explicit two layers numerical differential scheme with second order of approximation by time and first order approximation by age with explicit recurrent formulas for boundary condition. We considered the set of income equation coefficients as a set of parametrized algebraic functions with compact sets of parameter definition. The parameters estimation problem was resolved for the both approaches for the observed within 3 seasons time series data of overground dried mass of hop plant. As the relative errors of deviation of simulated curves from the points of observed data were less than 7%, we have concluded that polycyclic age-structured models of cell aggregation are enough efficient to describe the temporal evolution of plant cells mass.

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Neurons play a crucial role in the regulation of cardiovascular and cardiorespiratory systems yet functional roles of different neuronal phenotypes remain unclear. In order to elucidate mechanisms underlying many neurological and cardiovascular disorders, a better understanding of the functional and the physiological role of specific neurons is crucial. Here we describe an entirely novel synthetic biology approach for selectively investigating the identification, function and regulation of different types of neurons by expressing genes encoding fluorescent proteins, ribosome inactivating proteins and light-activated ion channels under the control of synthetically engineered neuron-specific promoters. By engineering synthetic promoters This combined approach has broad applicability and offers a novel strategy to better understand the underlying mechanisms of any cells in any system. A key advantage of the approach that we are outlining here is that we combine targeted cell death and optogenetic stimulation / inhibition approaches using a neuron-specific promoter system that targets cells on the basis of particular genes that they express. This will lead to the development of a toolkit that will enable phenotype-specific knockout of cell groups in vivo; this is a long sought after goal in neuroscience research.

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The expression of a synthetic gene circuit can have a detrimental effect on its chassis cell and these effects can feedback to the performance of the circuit. We investigate how a synthetic circuit uses cellular resources (eg. DNAP, RNAP, ribosomes, tRNA etc) to replicate and express. This is done by considering this shared ‘resource pool’ as an interface between the host cell and the synthetic circuit. We have developed a system for monitoring the availability of the resources used for protein expression within a cell (burden monitor). In order to test how different control points in heterologous gene expression affect the chassis cell, we have constructed a library of plasmid-based synthetic gene circuits with varying copy number, promoter strength, RBS strength and codon usage. By testing this library with our burden monitor we are able to uncover some unexpected behaviours and gain a greater understanding of how to optimise synthetic gene circuits to have minimal affect on their chassis cells.

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We present here the Act Ontology and pathway inference tool, the Act Synthesizer. The Act Ontology formalizes and stores biochemical function knowledge in an extensible and uniform manner. We populate the Act ontology by aggregating enzymatic data across various sources and deriving biochemical rules from them. We use the ontology as the underlying framework for the Act Synthesizer tool that, when provided a natural or unnatural chemical target, generates a plausible enzymatic pathway to the target. We have used the tool’s predictions to design and test E. coli strains to establish the reliability of our tool. The Act Synthesizer allows users to comprehensively survey the space of observed enzymatic reactions in several ways; a user can ask whether a chemical can be made from known reactions, they can identify all alternate pathways to a desired target chemical, and they can compute the list of chemicals that can plausibly be made in cells. We have the ability to predict, at least as a conservative over-approximation, what can be done in the space of microbial chemical factories. This enables our community to anticipate potentially dangerous constructs prior to release of tools with public access, and proactively intervene to avoid unintentional production of dangerous organisms.

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We are working to construct a synthetic gene network intended to allow a population of engineered yeast cells to actively regulate the extracellular concentration of a small molecule. To accomplish this, the cells will be equipped with both the ability to sense the extracellular concentration level of the molecule, as well as the ability to synthesize and secrete the molecule itself. An intercellular control circuit coupling sensing to biochemical synthesis will effectively couple the cell population’s overall secretion rate to the extracellular small molecule concentration. Basing the control circuit design around the strategies of integral control will permit for the secretion rate to change precisely in response to static perturbations to the extracellular concentration. Furthermore, built-in modularity within the design–specifically the ability for the control circuit to interface with different sensing and synthesis units–is intended to allow for future customization toward different molecules of interest.

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Synthetic biology articulates a surprising diversity of actors : life-scientists, computer-scientists, engineers, social-scientists, venture capitalist, but also biohackers and FBI agents. An early and major concern raised by the emerging field was the risk of bioterrorism. My research is looking at the making of the relationship among academic scientists, entrepreneurs, professional scientific association, public administration, do-it-yourself biologists and FBI agents, associated with a common interest to deal with biosecurity risk. I propose to explore how members of synthetic biology community went to engage with the FBI Weapon of Mass Destruction Bioterrorism Prevention Program. This study, based on ethnographic observations and interviews, will show how the fight against terrorist threat got connected to the opportunity for synthetic/DIY biologists to structure their field and project. I will first examine how the government engaged in countering bioterrorism in post 9/11 USA, and how it framed its relation to life-science and amateurs communities. Then, I will trace the specific risks which fall under the concern of US security institutions and scientists, the targeting of synthetic biology as a “field of concern” and the concrete making of a “risk-oriented” relationships among scientists, gene synthesis companies, DIYbio members and FBI agents. The aim of this poster is to provide to members of the synthetic biology community an insightful and critical description of the various interests at stake in biosecurity.

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We have previously engineered a synthetic genetic circuit that enables plants to serve as customizable biological input-output systems. This circuit uses computationally-designed receptors that bind a ligand of interest (input), initiate a signal through a synthetic signal transduction module, producing a readout (output). In our current design, production of a visible readout requires continuous exposure of plants to the ligand. Ideally, this system should be capable of reporting short, transient exposures to a ligand, essentially “remembering” the exposure event. This memory function can be introduced with the addition of a toggle switch circuit, consisting of two mutually repressible promoters that control expression of their respective transcriptional repressors. By controlling the levels of these repressors, this circuit can exist in one of two stable states. This feature not only adds memory to any synthetic circuit, but it also allows input-output systems to be reset. Therefore, we engineered and implemented a plant-functional genetic toggle switch that can be toggled between two stable output states (ON vs. OFF); toggling is controlled by two estrogen inducers. We started by developing novel transcriptional repressor-promoter pairs that function in plants. We then quantitatively characterized the behavior of these pairs by transient expression in isolated plant cells (protoplasts), and used the data obtained in vivo to build a computational model of the plant genetic toggle switch. Based on this model, we generated transgenic plants containing a genetic toggle switch circuit that uses two of these repressor-promoter pairs in a mutually repressing architecture. The switch behavior of this circuit was followed by monitoring in vivo production of a luciferase reporter gene (output) in response to the inducers. By modifying the output of this toggle switch, we are using this circuit to control plant traits with bioenergy applications. Funding: ARPA-E, US-DOE

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Engineered fluorescent dyes are increasingly being developed for use as live cell sensors, extending their utility beyond traditional imaging reagents. The improved photophysical and fluorescence properties of oxazine and xanthene dyes make them ideal components for these powerful tools, which are capable of providing dynamic information on signaling networks, molecular/chemical processes, and protein-protein interactions. As such, fluorescent sensors can be harnessed for screening of many cellular activities of interest. In aim to develop novel methodologies that exploit chemical reagents for directed cellular evolution, we report a novel and scalable synthetic approach to the widely used oxazine and xanthene fluorophores through a common diaryl-ether intermediate. Taking advantage of recent advances in transition-metal catalysis, we prepared electronically activated diaryl-ethers to serve as tethered di-nucleophiles. These diaryl-ethers react with a range of electrophiles to undergo cyclization to oxazine and xanthene fluorophores. Using yet another transition metal catalyzed reaction, a late-stage modification of the synthetic route allows for the preparation of fluorogenic (pro-fluorescent) dyes bearing a series of sensitive caging groups. When encountering the appropriate stimulus, the pro-fluorescent compounds are capable of providing inducible readouts in response to specific cellular processes. We believe these cell permeable dyes will enable new methodology for selectively probing desired functions. By teaming synthetic chemistry with synthetic biology, this work expands the toolkit available for engineering living systems.

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Synthetic Biology aims to design new in vivo biological systems or to redesign existing ones for new or improved functionality and performance. The development of proof-of-concept experimental applications has revealed that, when constructed in the laboratory, most designs do not work as predicted and need to be fine-tuned on a case-by-case basis. Here we use firm engineering principles to establish a redesign framework that reliably generates synthetic bio-systems that behave in a predictable fashion. The framework is based on a systems-engineering, bio-inspired design cycle. We illustrate the application of this cycle on the toggle switch, for which we investigate its quantifiably robust and predictable implementation. We first produce a detailed mathematical model for the system that captures its most important biochemical properties. Combining prior knowledge reported in the literature with experimental data, we show how the model and its parameters can be systematically refined. Based on the models obtained and their robust control analysis, and taking into account model uncertainties and stochastic effects, we propose modifications to biological parts that can be “easily” implemented experimentally (called “dials”), so as to achieve a (re-) design objective which has been specified a priori. We show how the modified systems can be constructed using a “plug-and-play” plasmid that allows direct insertion or modification of any biological part in the system. We then show how experimental data from the implemented prototype systems can be used to refine the models and improve the design through successive iterations.

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Biorefining involves “refining” multiple useful products from biomass. Biorefining of plant fibres produces by-products, such as phenylpropanoids. These phenylpropanoid by-products can be used as feedstock to produce more useful, high-value compounds such as curcuminoids. Curcuminoids are diarylhepatanoids that gives turmeric its distinctive yellow colour. Research has shown these molecules to have anti-tumour, anti-cancer, anti-oxidant and anti-inflammatory effects as well as providing neuroprotection. Therefore, the ability to sustainably produce these compounds in high yields is very lucrative. This project aims to produce curcuminoids and related novel compounds using Saccharomyces cerevisiae. This initially involves taking the two enzymes, diketide CoA synthase (DCS) and curcumin synthase 1 (CURS1), which produce curcuminoids in turmeric (Curcuma longa) and expressing them in yeast. The engineered yeast will then be fed using various phenylpropanoids and the yield of different curcuminoids will be monitored. The focus will then be to optimise this metabolic pathway and investigate ways of elaborating the chemical structure of curcuminoids by adding new enzymes to the system such as glucosyltransferases.

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Two key components of astrobiology are the questions: “Where do we come from?” and “Are we alone?”. To this end, the exploration of extreme conditions in which life can survive provides insight into the environmental parameters surrounding the origin of life and the potential for life elsewhere. Synthetic biology offers a unique approach to this study, as resistance-conferring pathways in extremophiles can be reconstituted into model organisms such as Escherichia coli to enable further study. A “genetic toolkit” providing resistance to basicity, acidity, desiccation, cold, heat and radiation were isolated from various organisms. These genes were characterized by expression in K12 E. coli and all displayed significant resistance to their respective extreme conditions. This suite of naturally-derived parts were formatted through BioBrick standardization and presented as a component of the synthetic astrobiology project by the 2012 Stanford-Brown iGEM team (http://2012.igem.org/Team:Stanford-Brown). The potential for these parts is large in scope: in addition to offering aid in the study of life’s beginnings, they also serve as a standard means to adjust survivability conditions in cell cultures and progress towards the development of extraterrestrially compatible engineered microbes that can support space exploration and colonization

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The stochastic nature of biochemical reactions together with their intrinsic nonlinearity complicates the analysis – and therefore the design – of synthetic biological circuitry. Thus, the transition from a conceptual deterministic analysis of gene expression to a stochastic approach is needed to overcome the present limitations in synthetic biology. As a minimal result this approach will limit the risks of unpredictability, but in a larger and most ambitious perspective it will offer instruments not limited to the control of noise, but aimed to the functional adjustment of the operational properties of synthetic biological systems. In this work the fluorescent output of a test circuit [Ceroni et al. (2012) ACS Synth. Biol. 1:163-171] is modeled using either ordinary differential equations or discrete reactions in the presence of an additional module, intended as a shuttle of intrinsic intracellular noise into the reporter molecular device. The test circuit combines a transcriptional (LacI-based) and a translational (through mRNA hybridization) control of gene expression, allowing to independently modulate and analyze the respective noise contributions to the output of the synthetic device. Noise modulation is achieved tuning the transcriptional rates of the mRNA molecules involved in the translational control. Numerical simulations, performed using the Gillespie’s algorithm, predict that increasing the noise at the translational level improves the sensitivity of the transcriptional control mechanism. These numerical results will be compared with experimental measurements performed in bacterial cells. As the control of intrinsic noise allows to exploit the unavoidable stochasticity of biological processes in the design of synthetic devices, the presented gene circuit is proposed as a tool for e.g. identifying the parameters that optimize the function performed by a synthetic circuit or analyzing the effects of noise on gene expression in nature.

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The appearance of parasite is one of the largest hurdles for primitive self-replicators in prebiotic evolution because once a parasite appears, it amplifies relying on host’s components until inhibiting the replication of the host. It casts a question: how has the primitive self-replication been established under threats of parasites? To understand this question, we are attempted to construct the artificial host-parasite interacting self-replication system in vitro from non-living molecules. We used an artificial self-replication system of RNA derived from RNA phage Q beta, in which RNA replicase is translated from the artificial genome RNA and replicates the RNA. This self-replication system, however, has problems in the efficiency and recursiveness caused by amplification of parasite RNA, a shortened RNA which lost replicase gene. The parasite is replicated rapidly because of its shorter length, resulting in competitive inhibition of the genome replication. We performed long-term self-replication reaction of this artificial host-parasite system in a cell-like compartment (water in oil emulsion), and found that the populations of the host and the parasite oscillate. The oscillation of the host was followed by the oscillation of the parasite like predator-prey system, but driven by the different mechanism, compartmentalization of the parasite into a minor fractions of the emulsion. Our result demonstrated that a primitive self-replication system sustains even in the presence of parasites in compartment structure at appropriate dilution rate. Moreover, the sequencing analysis on the host genomic RNA revealed that frequent changes of the genetic sequence occurred during the oscillation. It might suggest that this parasite-driven oscillation dynamics facilitates the evolution of the host RNA.

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A long-standing goal of synthetic biology is to rapidly engineer new regulatory circuits from simpler regulatory elements whose properties have previously been characterized individually.  A critical impediment, however, has been the lack of accuracy in predictions of circuit behavior made by computational models. The typical constructive approach of synthetic biology has led to models that explicitly encode all the biochemical reactions believed to be significant.  Such models, however, generally rely on difficult to estimate parameters; moreover, while the impact of cellular context on regulatory motifs and signaling pathways is becoming increasingly clear, this impact is not sufficiently well understood to incorporate effectively in reaction models.  Here we introduce a new method, Empirical Quantitative Incremental Prediction (EQuIP), which addresses these problems and provides accurate predictions of biological circuit behavior.  In EQuIP, the basic unit of a circuit is a “device” encapsulating a set of regulatory interactions.  For each device, a composable model of its incremental input/output expression phenotype is derived solely from empirical observation of expression dynamics and device steady-state behavior in the cellular context.  This approach both abstracts away biochemical details and captures significant interactions with cellular context without requiring either explicit or well-understood models of those interactions.  We validate EQuIP by characterizing three transcriptional repression devices with transient transfection in mammalian HEK293FT cells, then precisely predict the behavior of six cascades, each comprising two of these repressors.  For a range of induction levels, these cascades exhibit up to 18-fold +/- difference in fluorescence and over 1000-fold cell-cell variation in fluorescence, yet EQuIP’s computational predictions have a mean error of only 1.6-fold compared to experimental data.  Such accurate predictions will allow synthetic biologists to determine combinations of devices likely to produce a desired behavior, thereby allowing reliable forward engineering of complex biological circuits from libraries of standardized devices.

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The extraordinary fidelity, sensory and regulatory capacity of natural intracellular machinery is generally confined to their endogenous environment. Nevertheless, synthetic bio-molecular components have been engineered to interface with the cellular transcription, splicing and translation machinery in vivo by embedding functional features such as promoters, introns and ribosome binding sites, respectively, into their design. Tapping and directing the power of intracellular molecular processing towards synthetic bio-molecular inputs is potentially a powerful approach, albeit limited by our ability to streamline the interface of synthetic components with the intracellular machinery in vivo. Here we show how a library of synthetic DNA devices, each bearing an input DNA sequence and a logical selection module, can be designed to direct its own probing and processing by interfacing with the bacterial DNA mismatch repair (MMR) system in vivo and selecting for the most abundant variant, regardless of its function. The device provides proof of concept for programmable, function-independent DNA selection in vivo and provides a unique example of a logical-functional interface of an engineered synthetic component with a complex endogenous cellular system. Further research into the design, construction and operation of synthetic devices in vivo may lead to other functional devices that interface with other complex cellular processes for both research and applied purposes.

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The Paris Bettencourt iGEM Team and the CRI Synthetic Biology Club will present a work of interactive biodesign. Our team of undergraduate and master’s students includes biologists, engineers and designers. How might biofabrication become a part of our daily lives? Cellulose is an everyday material and an industrial commodity. We have developed a system to modify, color and shape cellulose as it is produced by live cultures of Acetobacter xylinum. By connecting a living organism to a familiar product, we will invite attendees to consider possible applications of synthetic biology in a model system. What are the strengths, weaknesses, and quirks of biological production? What is biology good at? Biology is noisy, visceral, and evolving. Often biology does not easily adapt to traditional industrial standards of uniformity and precision. Yet life has unique properties, adaptiveness and variability, that may inspire a new perspective on engineering and design. We will invite SB 6.0 participants to explore biocellulose as a biofabrication case study, and to create their own SB 6.0 souvenirs.

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The early detection of specific compounds is essential in successfully combating environmental pollutants and potential biological threats, as well as monitoring human health and ecosystem functions. Microbes offer the potential to act as biosensors but often lack specificity and sensitivity. Synthetic biology is currently offering the potential to create modular designed biosensors of increased specificity and sensitivity capable of operating across a range of microbes and environmental conditions. Whilst previous biosensor experiments in aerobic microbes has been successful (i.e. arsenic and mercury detectors), the potential for biosensors utilizing anaerobic and soil associated microorganisms has not yet been fully explored. Anaerobic bacteria have previously been shown to be naturally efficient in bioremediation and biodegradation efforts. Thus focusing synthetic biology techniques on anaerobic bacteria has the potential to expand the range of whole cell biosensors available. Initial experiments have utilized standard Biobricks™ to determine the potential of current technology and assembly techniques. These initial experiments allow the selection of “user-friendly” designed parts and their potential to be determined for novel biosensor development in a range of microorganisms. While initial biosensor design will be conducted in E. coli, these sensor systems will be moved into other chassis including anaerobic microorganisms (including species from Shewanella and Geobacter genera) and rhizosphere-associated microbes (Pseudomonas species). Once standard sensory systems have been developed across a range of microorganisms, novel sensory components will be designed for the detection of specific heavy metals, microorganisms and other molecules of interest. Detection of a target will be lined to specific outputs, such as biodegradation, which will be a capability integrated into the sensory pathway. This project aims to develop flexible biosensor modules for use across anaerobic and soil associated microorganisms and further develop synthetic biology capacities in Australia.

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Synthetic biology is a developing scientific field with potentially huge impact on the world, possibly positive (e.g. greener fuels and cheaper medication), or negative (e.g. unforeseen and undesired consequences for the environment or controversy in society). Many scholars argue that to realize societal embedding of synthetic biology an interactive multi-stakeholder dialogue including the public at large is needed (1,2). However, since synthetic biology is currently little discussed among the public (3,4), such a dialogue must be facilitated actively. For this, the Interactive Learning and Action (ILA) approach can be deployed. Examples are patient participation in the agenda setting of burns research (5) and the involvement of small-scale farmers in biotechnology innovation processes in developing countries (6). The ILA approach aims to open up science and technology development processes by involving relevant stakeholders in early phases of development. It is structured along five phases: (1) initiation and preparation; (2) in-depth study of needs and visions; (3) integration; (4) priority setting and planning and (5) project formulation and implementation. In phase 2 we have conducted eight focus groups with Dutch citizens to (1) identify their perceptions of synthetic biology and (2) test early-stage public engagement. Results show that while participants were unfamiliar with the topic they were very interested in it. Participants tended to link the cases to negative examples from the past and expressed fear, and mistrust towards government, companies and the industry. The structure and content of discussions differed per proposed synthetic biology application. Overall, these results can help to further design communication tools and shape a healthy science-society dialogue. To put these results in an international perspective we are currently linking up these results to results from similar initiatives such as the Synthetic Biology Dialogue in the United Kingdom (7) and the Synthetic Biology Project in the US (8).

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Light-induced nuclear transport Employing phytochromes for nuclear trafficking of transcription factors Abstract In plants, phytochromes are key in light perception and play an important regulative role for red/far-red-light controlled responses. The nuclear translocation of the excited photoreceptor is nowadays considered as an essential step in signal processing. In this work, we employ mammalian cells to demonstrate the red-light-induced nuclear transport of a genetically engineered phytochrome B (phyB). Upon red-light exposure, the photoreceptor gains tight interaction capabilities to its dedicated NLS-harboring Phytochrome Interaction Factor 3 (PIF3) leading to the formation of a nuclear import complex thus driving the nuclear traffic. A red-light responsive reporter-gene expression system was developed based on this principle by the fusion of the phytochrome moiety (i) directly to a transcriptional activation domain (VP16) and (ii) indirectly in a biotin-dependent coupling to the DNA-binding domain TetR. The expression system shows a tunable spectral response with the highest activity at 660 nm. Illumination with light of a longer wavelength leads to a step-wise decrease in reporter expression and to a complete shutoff at 740nm. Additionally, fusions to fluorescent proteins were generated for the visualization of the nuclear transport by confocal imaging. Further development employing a nuclear export signal (NES) led to a red-light/far-red-light switchable nuclear shuttling of the phytochrome allowing a spatiotemporal control of the allocation and exclusion of phyB fusion-proteins to the nucleus. The principle at hand may reveal further information for basic research on plant phytochrome-singalling, as the formation of so called ‘nuclear speckles’ was observed – structures, which function is hitherto unknown and under heavy investigation mainly in Arabidopsis. On the other hand, the employment of the orthogonal Phytochrome B-based signalling module in mammalian cells allows for a highly valuable de-novo design of robust and sustainable biomolecular circuits and synthetic pathways at a spatiotemporal resolution.

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Transcription Activator-Like Effectors (TALEs) are DNA binding proteins that can be reprogrammed to bind almost any sequence with a high affinity and specificity. We have modified this technology to create transcription factors that orthogonally bind to targeted promoters, whether natural or modified, to regulate gene expression in yeast. To increase the practicality and potential of these TAL Orthogonal Repressors (TALORs), we have developed a method to generate large numbers of unique TALORs and their cognate regulated promoters. Coupled with a novel strategy to rapidly integrate large numbers of transcriptional units into specified chromosomal loci, this technology promises to dramatically increase the number of orthogonal transcription factors available to synthetic biologists and, therefore, the complexity limit of synthetic regulatory networks.

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Synthetic biology promises to enable the production of important commodity chemicals, drugs, and fuels from cheap and renewable feedstock. While the biosynthesis of a large number of natural products has already been achieved in genetically engineered microorganisms, the potential of in vitro synthetic biology has barely been touched due to limited availability, stability, and cost of purified enzymes. However, as biocatalyst prices continue to fall on grounds of significant progress in industrial enzymology, the attractiveness of synthetic pathway biotransformation is increasing rapidly. As a reference platform for in vitro synthetic biology, we have developed a prototype flow-microreactor for enzymatic biosynthesis to enable the small-scale evaluation of novel synthetic pathways, compartmentalization and immobilization strategies, and reaction conditions. Hereby, we report the design, implementation, and computer-aided optimization of a synthetic three-step model pathway within our microfluidic platform. A packed-bed format was shown to be optimal for enzyme compartmentalization after experimental evaluation of several approaches. Within this microreactor, the immobilized pathway’s specific substrate conversion efficiency could be significantly improved by an optimized parameter set obtained via computational modelling. While in vivo systems will always be attractive due to the intrinsic regeneration of biocatalyst and cofactors, our microreactor design provides a platform to explore new synthetic biology solutions for industrial biosynthesis in vitro.

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Genome engineering applications are currently limited by the specificity and designability of available nuclease platforms. Zinc finger nulceases (ZFNs) and transcription activator-like effector nucleases (TALENs), dimeric proteins formed by fusing the FokI cleavage domain with an auxiliary DNA binding domain, have a greater potential for off-target cleavage due to their distinct DNA binding and cleavage domains and by inappropriate coupling of the nuclease halves. Homing endonucleases (HEs) are monomeric, single domain proteins, making them more reliable reagents for creating single or multiplex DNA cleavage events. Their major limitation, however, is the engineerability of their DNA-binding interface; current design and selection methods often yield HEs with reduced affinity and cleavage activity. We have developed a novel designer rare-cleaving endonuclease platform for genome engineering by fusing DNA-binding transcription activator-like effectors with homing endonucleases. These MegaTALs rescue the activity of low affinity homing endonucleases and improve that of high affinity HEs, boosting repair activity well beyond that of their high affinity HE counterparts. Due to their extended sequence recognition, MegaTALs exhibit higher cleavage activity at their desired target and MegaTALs formed with low affinity HEs demonstrate high target specificity. Furthermore, we found that six TAL effector repeat units were sufficient for achieving maximal activity with a low affinity HE, opening up the possibility for sequence divergence and lentiviral delivery of the MegaTAL gene. We propose that MegaTALs are a novel approach to generating active genome engineering nucleases with high activity and extreme target site specificity.

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Teaching synthetic biology is challenging. Principal reasons for the lack of established synthetic biology curricula are 1) interdisciplinarity and thus difficulty in application of knowledge from an unfamiliar field as well as in arranging inter–departmental expertise and 2) requirement to select and characterise necessary biological, electronic and digital resources for successful creation of synthetic biology devices. We aim to lower the barrier to entry for teaching synthetic biology by developing and providing experimental kits, BioBuilder–style, that incorporate biological, electronic and digital parts and protocols to allow introduction of the principles and approaches of synthetic biology through student–driven, investigative, open–ended, practical inquiry. In my presentation I will describe the experimental kits we have developed so far and share our experiences from their deployment during two–week long summer course in practical synthetic biology for undergraduates at the University of Reading.

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Synthetic biologists engineer biological devices by assembling standardized building blocks into an organism that is used as “chassis”. Since the number of components that can be assembled into a single chassis is limited, we aimed at the creation of a stable microorganism co-culture with defined, tunable proportions of two different strains. Such a co-culture could be used as a multicellular chassis for synthetic biology. FINDINGS: This poster presents work done largely by the Buenos Aires team participating in the 2012 International Genetically Engineered Machines (iGEM) competition. We designed a tunable co-culture of two auxotrophic budding yeast strains that feed the amino acids tryptophan and histidine to each other. Mathematical modeling let us identify both the dependence of strain populations on amino acid secretion rates, and the amino acid secretion rates required for auto-regulated co-culture growth. We implemented our design in four novel amino acid crossfeeding devices, which use sequence tags for peptide secretion and cell penetration of a peptide payload. Experimental validation showed that the design of tryptophan secretion was successful and that the crossfeeding devices enhance co-culture growth. CONCLUSIONS: Our amino acid crossfeeding devices show promise as a tunable standard tool for synthetic biology and for the quantitative study of mutualistic interactions between microorganisms.

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In developing embryos, the appearance of highly organized structures such as vessels, branches, cell sheets etc. relies on the succession/repetition of a small number of basic morphogenetic events. These processes, occurring in a specific and controlled sequence, are: adhesion, cell locomotion, apoptosis, cell fusion, epithelial-to mesenchymal or mesenchymal-to-epithelial transition, cell sorting, etc. Together with cell differentiation and proliferation, those fundamental mechanisms allow populations of cells to organize themselves into defined geometries and structures as embryos develop into complex organisms. With synthetic biology, we can program mammalian cells to perform such mechanisms by designing genetic circuits, combining various morphogenetic effectors under the control of distinct logic modules. To this purpose, we constructed a modular library of morphogenetic driver genes inducing adhesion, locomotion, fusion, apoptosis and growth arrest. We are first testing these parts individually in different mammalian cell lines to check their ability to induce the desired morphological changes. The active effectors are then tested under the control of various logic gates in selected cell lines. This way, we aim at combining sequences of morphogenetic effectors in a series of proof-of-concept trials for “synthetic morphology”, where cells are genetically programmed to organize themselves into designed 2-D or 3-D structures from artificial external stimuli. Reproducing basic morphogenetic processes in vitro will allow us to test existing theories of developmental biology away from the complex environment of the embryo. Importantly, the resulting cell arrangements are not restricted to natural ones and un-natural, designed structures can be obtained and may, in the future, be used in surgery and regenerative medicine, making synthetic morphology a powerful tool for tissue engineering.

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Cyanobacteria are photosynthetic prokaryotes of great biotechnological potential as they can use sunlight as energy source and CO2 from air as carbon source. Engineering these solar-powered bacteria to produce biofuels could supply us with the renewable fuels of the future. However, to facilitate this development, robust and versatile biological parts and tools for engineering cyanobacteria are needed. Among these tools, the control of gene expression is crucial as it is the first step in expressing any functional element inside a living cell. Thus, we develop transcriptional control systems for use in cyanobacteria. The first is a LacI-regulated system based on a modified version of the strong artificial trc promoter that contains a single lac operator. We add another lacO and vary its position to investigate how this affects DNA-looping and transcriptional regulation in both Escherichia coli and the cyanobacterium Synechocystis sp. PCC 6803. This information is important in identifying differences between the native transcriptional machineries of E. coli and Synechocystis, facilitating the design of an optimal LacI-regulated promoter. A second system relies on light for regulation of gene expression. Light is an excellent regulator of gene expression as it is transient and non-invasive, easy to integrate in different systems, and has been demonstrated for in vivo gene regulation using fully genetically encoded light sensors. Furthermore, as sunshine is the energy source of cyanobacteria, being able to synchronize genetic circuits with day/night cycles through a light-regulated orthogonal gene expression system could provide advantages in solar-powered biotechnology. To achieve this we develop light-regulated transcriptional systems that control promoters directly through the binding of light-sensitive dimers of transcription factors.

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It is widely assumed that the strength of ribosome binding sites (RBSs) is one of the most relevant issues in the experimental implementation of synthetic devices, often involving a trade-off between basal signal due to leakiness and output range amplitude. Although models of regulable promoters exist, there is still a lack of knowledge on how should systems be engineered in order to display given, predefined characteristics. In this work we present a simple mathematical approach that allows us to understand the design principles of an inducible promoter. As a proof of concept, our theoretical results are contrasted with empirical data by constructing a library of genetic devices, expressing a Red Fluorescence Protein (RFP) gene reporter by the control of a Lux promoter of Vibrio fischeri in E. coli. In this device, the expression of the homoserine-lactone receptor is constitutively produced but modulated by using different RBSs differing in their strength. Using Biobrick cloning assembly and the part registry repository, we characterize the effects of changing RBSs in both gene reporter and homoserine-lactone receptor. The analysis of transfer functions of the library shows that the use of a higher RBS strength at the gene codifying the Lux receptor produced an increase of the input affinity without a marked enhance of the basal output. However, the increase of the RBS at the reporter gene contributed to enhance the output but, with a penalty on increasing the basal level. Using our case study as a reference, we propose a set of guidelines to better design synthetic circuits and achieve more desirable system’s behaviour.

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As the number and complexity of genetic devices increase over time, they will also have to function in increasingly complex cellular systems, and control and interact with many more molecules and processes simultaneously. This cannot be achieved reliably if the number, type and properties of these interactions, as well as their impact on both synthetic and host systems, are not fully understood. Here we perform a detailed analysis of the interaction between constitutive expression from a test circuit and cell growth properties in a subset of genetic variants of the bacterium Escherichia coli. Differences in generic cellular parameters such as ribosome availability and growth rate are the main determinants (89%) of strain-specific differences of circuit performance in laboratory-adapted strains but are responsible for only 35% of expression variation across 88 mutants of E. coli BW25113. In the latter strains we identify specific cell functions, such as nitrogen metabolism, that cause a significant increase in fitness and circuit output. In contrast, deletion of genes involved in chemotaxis and quorum signaling, such as cheY or qseB as well as several other components of Signal Transduction Pathways, led to reduced cell growth and reporter expression. Finally, we expose aspects of carbon metabolism that act in strain- and sequence-specific manner. The study points to a broader program to discover and classify the mechanisms that govern the host-circuit interface and perhaps, ultimately, to design against them to increase the predictability of synthetic biological design. To this purpose we are expanding our analysis to include all the ~3800 single-gene knockout strains available for E. coli.

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Escherichia coli ribosome synthesis and assembly (biogenesis) is a tightly regulated and ordered process with complex folding and assembly steps. Understanding the complexities of this process is key for ribosome engineering efforts. One aspect of understanding is the order in which the ribosomal (r)RNA is transcribed. To study this, a plasmid based ribosomal operon is mutated such that the native 5’ and 3’ ends of the 23S rRNA are covalently linked, and a circular permutant (CP) is created by opening up new 5’ and 3’ ends at an internal helix. CPs are then evaluated on the ability to support cell growth in E. coli without genomic copies of rRNA. The current data set in this space is severely limited; CPs at only two of the over 100 23S helices are known to be viable. Towards testing the remaining circular permutations, we utilize a parallel and efficient construction method to synthesize CPs of 23S rRNA at all helices on a plasmid based operon. Then CP23S constructs are evaluated on their ability to support cell growth in a strain lacking all 7 genomic copies of ribosomal operons. We identified several new mutations that support cell growth with limited reduction in growth rate. Several mutants cannot support cell growth alone, but cells are viable in their presence. Finally, several mutations are toxic when expressed in E. coli. This work provides a more thorough understanding of ribosome biogenesis in vivo, and informs ongoing ribosomal engineering efforts.

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Inverters (NOT-gates) are elementary Boolean logic circuits, where the output is absent when the input is present. Inverters mimic the inverse relationships between molecules in natural systems that are responsible for maintaining steady state, and as such form an essential tool in the synthetic biologist’s toolkit. Here we are using two separate synthetic genetic inverter circuits to build functionally complete, modular NAND-gates in a single cell by coupling them to a common output. This project explores Device-level modularity and composition, where only whole Devices are tuned, versus Part-level modularity, where most individual Parts or smaller groups of Parts are first tuned and then assembled into larger devices. The component Parts are all from publicly available repositories. We have a library of 10 distinct inverters, each with five different strengths of repression. Each inverter produces a diffusible, intercellular signalling molecule as its intermediate output, which in turn induces the final output. Both NOR and NAND-gates are functionally complete and can be used to construct all other types of combinational logic. Modular synthetic genetic NOR-gates have been previously constructed by the addition of a second input module to an existing inverter, but the additional input module/promoter introduced unexpected changes in the circuit output, requiring significant post-construction tuning. Because inverter-based NAND-gates contain only a single promoter per circuit, we expect to see fewer variations in inverter output expression requiring additional tuning. In keeping with our goals of maintaining device-level modularity, we have chosen to make NAND-gates from our inverters. We aim to show that NAND-gates, like NOR-gates, can also be constructed easily and modularly, and with less manual correction. Modular device-level composition is especially advantageous in a microfluidics framework where individual devices can be arranged to communicate with each other to make complex, scalable logic circuits.

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Cloning, and assembling DNA in general, is one of the main bottlenecks slowing down the progress of synthetic biology: it’s a slow and expensive process, and requires a lot of “ad hoc” adjustments. The lack of a standard also complicates exchange and comparison of constructs between different labs, as the same functional parts can be assembled in radically different ways. We propose a DNA assembly standard compatible with both the “small parts to genes” and the “genes to pathways” level. In order to achieve high throughput and improve reliability, this method is designed to be compatible with automated liquid-handling platforms and uses extremely robust reactions such as restriction digestions and ligations. It is also compatible with a wide range of part sizes and features (such as high GC% or presence of secondary structures) and can be used for the combinatorial assembly of libraries of parts. One of the main defining features of our approach is the use of “linker” DNA sequences to join parts together: they are the ones which participate in the assembly reactions and are computationally designed to achieve maximum efficiency and specificity.

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Bacterial cells have been used for decades for the production of industrially and therapeutically useful molecules. Synthetic biology takes this a step further, where complex genetic devices confer new functions to cells and do this via the production of many different proteins and metabolites. The running of such heterologous systems is known to cause a burden to bacterial host cells who have to share their resources between their own growth and maintenance and the production of molecules they usually don`t synthesise. The cellular response to this burden is complex cell-wide form of stress and can lead to variations in global transcript and protein production that can affect the desired robust behaviour of synthetic devices. Recently, researchers have started to characterize the stress response of bacterial cells to heterologous gene expression. However, an in-depth characterization of how bacteria cope with diverse synthetic genetic circuits is still lacking. Here, we present the characterization of E. coli cells as they respond to the burden caused by a panel of different synthetic biology devices chosen from literature. By examining the causes of burden and the outcomes for the host cells in these cases, we can understand how better to design future synthetic systems for long-term use and plan strategies for self-optimised expression.

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Regulatory noncoding RNAs, such as small regulatory RNAs (sRNAs), are fast-acting and less-energy-consuming regulator widely used in many organisms to precisely control gene expression together with transcriptional control, and therefore they could be a vulnerable regulator for gene expression control. Here we present an approach for constructing synthetic small regulatory RNAs for controlling gene expression. We developed synthetic small regulatory RNAs repressing the translation of DsRed2 mRNA at various levels and also constructed three different sRNAs for the mRNAs of LuxR, AraC, and KanR without cross-reactivity. The results suggest that gene expression can be fine-tuned by designed artificial small RNAs. Synthetic sRNAs can be implemented for metabolic engineering. The ability to fine-tune target genes with designed sRNAs provides substantial advantages over gene-knockout strategies and other large-scale target identification strategies owing to its easy implementation, ability to modulate chromosomal gene expression without modifying those genes and because it does not require construction of strain libraries. Using synthetic sRNAs for the combinatorial knockdown of four candidate genes in 14 different strains, we isolated an engineered E. coli strain (tyrR- and csrA-repressed S17-1) capable of producing 2 g per liter of tyrosine. Using a library of 130 synthetic sRNAs, we also identified chromosomal gene targets that enabled substantial increases in cadaverine production. Repression of murE led to a 55% increase in cadaverine production compared to the reported engineered strain (XQ56 harboring the plasmid p15CadA). [This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (NRF-2012-C1AAA001-2012M1A2A2026556); the Intelligent Synthetic Biology Center through the Global Frontier Project (2011-0031963) of the Ministry of Education, Science and Technology (MEST) through the National Research Foundation of Korea; and the World Class University program (R32-2008-000-10142-0) of MEST.]

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Synthetic biology offers significant promise for advances in health and medicine, food and energy production, and environmental sustainability. Realizing this potential requires continued commitment to driving bio-innovation, ensuring biosafety and biosecurity, and building a robust bioeconomy. We propose the formation of an International Synthetic Biology Society to support the responsible development and deployment of synthetic biology in the public interest. While many disparate organizations are working in synthetic biology, there is currently no primary organization supporting the needs of diverse synthetic biologists seeking to steer and propel the broader trajectory of the field. A synthetic biology society could provide accurate and timely information about the state of the field to practitioners, policymakers, and the public. It would serve as a community forum to foster discussion, debate, and collaboration among diverse stakeholders and engage the public in learning about, and informing, members’ research. We aim to increase awareness and understanding of technical advancements to illustrate how synthetic biology affects, interacts with, and enriches our lives.

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While synthetic biology demonstrations have traditionally been performed in well-mixed liquid cultures, novel applications may require spatial control using cells that communicate with one another. Cellular communication in bacterial species can be currently done with diffusible molecules, but such systems suffer from limited spatial resolution. We aim to bring touch-based communication, which mammalian cells characteristically use for precise developmental control, to bacterial cells. The contact-dependent inhibition (CDI) system was recently discovered that allows Escherichia coli cells to block growth of touching E. coli cells. Utilizing the scaffolding behavior of the CDI system, we engineer a cascade that ultimately results in control of gene expression instead of growth inhibition. We demonstrate the ability to control gene expression in neighboring E. coli cells with simple patterns. Our technology allows the development of spatial programming with micron-level resolution and the study of single-cell signaling rules used in tissue development.

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Synthetic biological circuits and engineered pathways can now incorporate many modules, such as logic gates and scaffolds for spatial organization. However, temporal control and time-sensing modules are still relatively under-developed. The circadian clock in the cyanobacterium, Synechococcus elongatus PCC 7942, maintains a robust day-night cycle by controlling the expression of over 50% of its genes. Consisting of just three core proteins, KaiA, KaiB, and KaiC, the circadian clock oscillates over 24 hours without a transcriptional-translational circuit. Instead, a posttranslational readout, selective phosphorylation of KaiC during the night, conveys information from the core oscillator to downstream components. We engineered the kai circadian clock heterologously in Escherichia coli. After synchronization of cultures, KaiC phosphorylation state was shown to oscillate via western blot, demonstrating functionality of the core oscillator in vivo. In order to construct a downstream transcriptional output at the single cell level, mCherry was put under the control of candidate circadian regulated promoters. Three proteins known to operate downstream of the Kai clock, SasA, RpaA and RpaB were also expressed. An orthogonal strategy utilizing a bacterial two-hybrid system, taking advantage of the known circadian-dependent binding of SasA and KaiC, is also being tested. Synchronization of the clock was achieved by either changing the ATP/ADP ratio through a minimal media starvation shock or by pulse overexpression of KaiA which promotes KaiC phosphorylation. Current progress is being made on connecting the clock with a light inducible promoter, allowing for easy synchronization. An engineered circadian clock not only allows us to better understand the physiology of the native clock in cyanobacteria, but also can be incorporated in complex, time dependent synthetic biology circuits that may have medical and industrial applications.

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Production of target chemical compounds in large quantity is achieved through a number of metabolic engineering strategies. For high production of target chemicals, it is generally required to supply enough precursor pool by redirection of metabolic fluxes. When the goal is overproduction of target chemical which has toxicity, fine-tuning of metabolic flux is needed because highly accumulated intermediate and its efficient conversion to the toxic target may induce cell death or severe growth retardation, leading to decreased target production. For toxic chemical production, concentration of intermediates should be well-balanced to produce toxic chemical as high as host cell can tolerate. Here, to produce phenol, a toxic chemical in Escherichia coli, we developed a mathematical model through tyrosine biosynthetic pathway as a model. The model-based control of tyrosine production fosters to find the maximal phenol production in Escherichia coli. The suitable control of intermediate concentration in assistance with a math model gives an insight to the metabolic engineering for toxic chemical compounds production. [“This work was supported by Intelligent Synthetic Biology Center (2011-0031963) of Korea through the Global Frontier Research Program of the Ministry of Education, Science and Technology (MEST).”]

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Our work focuses on the application of rational gene design for vaccine construction. We have built upon our synthetically-modified and attenuated Streptococcus pneumonia (SP] strain and have begun explore how synthetic gene design can allow this strain to serve as a universal SP vaccine. The need for an improved SP vaccine is to overcome the emerging clinical phenomenon know as serotype replacement (STR). STR is associated with pulmonary and invasive infections by SP. SP has a total of 92 serotypes; however, only 13 or 23 of these serotypes are covered in the current pediatric or adult vaccines, respectively. STR is the growing emergence of SP serotypes not covered by currently utilized anti-SP vaccines, becoming the major cause of pneumonia and other complications from a SP infection. Our work has used rational gene design to over-express what we refer to as ‘common protective proteins’ to construct a universal pneumococcal vaccine, capable of protecting against all 92 serotypes of SP. Given the threat posed by STR, there is a direct need for the development of a vaccine that confers immunity to all serotypes

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Mathematical models often inform the experimental design of synthetic gene networks. However, poor characterization of network parameters reduces the predictive power of models and yields imprecise or undesirable cell behaviors. In certain cases, poor characterization is the result of indirect measurement techniques. For example, DNA components, such as promoters and terminators affect RNA expression; yet, their biological function is quantified by measuring protein expression. This is not ideal since fast RNA dynamics are obscured and protein and mRNA expression do not necessarily correlate due to post-transcriptional processes. Methods that easily detect intracellular RNA levels with high temporal resolution should increase researchers’ ability to accurately describe the function of many poor characterized synthetic gene network components. Here, we describe an RNA-based fluorescence reporter to accurately and precisely measure RNA concentration and RNA synthesis rates in E. coli. The reporter consists of an aptamer that interacts with a cell membrane-diffusible organic dye to produce measureable levels of fluorescence within living cells. A model describing the molecular interactions was developed and kinetic parameters for processes relevant to transcription were determined. Fluorescence was correlated with intracellular aptamer concentration and the RNA-based reporter was shown to produce a specific, sensitive, and accurate signal. The technique was applied to observe changes in RNA expression in growing cells, and to quantify promoter activity and terminator efficiency in a high-throughput manner. Furthermore, the effects of cellular context on DNA component function were investigated. Preliminary results suggest that accounting for state-specific parameters, including cell growth rate and copy number, yield a more robust description of promoter activity. The methods presented in this work can be used to improve the predictive power of computational models, to meaningfully share characterization data of synthetic gene network components between research groups, and to create large repositories of standardized DNA components.

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The atmospheric CO2 concentration has changed during the last 100 years more than in the past 25 million years. A natural antagonistic mechanism to the increasing CO2 concentration is the Calvin cycle of green plants in photosynthetic activity. Engineering this activity could be a way to contrast the increasing of CO2 concentration. We investigate two important metabolic networks: the Rhodobacter spheroides bacterium, and the Chlamydomonas reinhardtii alga. The first models all the most interesting features of photosynthesis, as well as the metabolic capabilities of this kind of organisms. During its photosynthetic growth, R. Sphaeroides uses CO2 as the sole carbon source. The autotrophic metabolism of R. Sphaeroides makes it a potential organism for sequestering atmospheric and industrial CO2. Conversely, the second allows the investigation of photosynthesis in algae. Increasing the ability of these organisms to consume CO2 can be very interesting. Therefore, we adopt a multi-objective optimization approach to maximize CO2 uptake rate and biomass formation in the genome-scale metabolic networks of R. Sphaeroides and C. Reinhardtii. We act both on a genetic level (finding optimal genetic manipulations) and on an input fluxes level (finding the optimal nutrients) in order to improve the CO2 consumption and biomass formation. For the genetic manipulations research, we consider the photoautotrophic conditions for both organisms, i.e. in a poor environment where the only carbon source is CO2. The results are Pareto optimal solutions. Pareto optimality analysis reveals extremely useful to compare different organisms and different strategies. We find that by using genetic strategies, we can obtain high level of CO2 consumption. For instance, R. Spheroides is able to absorb an amount of CO2 until 57.452 mmolh-1gDW-1 (+28.51%) with a biomass rate equal to 0.986 h-1, while C. Reinhardtii obtains a maximum of 6.733 (+6.73%) with a biomass formation equal to 0.138.

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We propose to develop a programmable, multiplexed biosensing platform using genetically engineered bacteria for in vitro biomarkers detection. Such bacteria would be capable of multiplexed detection, logic processing, and data storage in a relevant clinical context while being simple and inexpensive to use. We first validate our in vivo computation strategy via an in silico, whole-cell stochastic model. Analysis and refinement of the model allows us to predict functional properties and limits of our system and to analyze its robustness at the population level. We then demonstrate the operability and robustness of the system in vitro in clinical samples using standard inducible promoters in an Escherichia coli chassis. Finally, we incorporate synthetic parts and devices recently developed to produce a first prototype capable of multiplexed biomarkers detection, signal processing based on Boolean logic and visual readout, all in a clinically relevant context. Our modular platform could be reprogrammed for the detection of different pathologies but also for applications in other fields of engineering like environmental detection and remediation.

Alexis Courbet*2, Jerome Bonnet*1, Patrick Amar3, Drew Endy1, and Franck Molina2.

* co-first authors
1 Department of Bioengineering, Room 269B, Y2E2 Building, 473 Via Ortega, Stanford University, Stanford, CA 94305
2 SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, 1682 rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4
3 Laboratoire de Recherche en Informatique, CNRS, UMR 8623, Université Paris-Sud 11, 91405 Orsay Cedex, France

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Vibrio cholerae is a waterborne pathogen that causes the acute diarrhoeal disease cholera which is prevalent in the developing world with 100-120,000 deaths per year. Current detection methods are lab based, with a timescale of hours to days, using fluorescent labelled antibodies or PCR to detect V. cholerae outer membrane proteins and DNA respectively. We are applying the principles of synthetic biology to produce a fast, simple, sensitive, mobile surveillance system that can be used in the field. The basis of the biosensor design is to detect chemicals involved in ‘quorum sensing’, the process by which bacteria communicate using secreted chemical signalling molecules to assess their population density. Under high cell density conditions V. cholerae produce the signalling molecule CAI-1 which is detected by the CqsS receptor protein causing downstream signalling proteins luxO and luxU to stimulate expression of Qrr genes and cause behavioural changes in the cell. The biosensor consists of a reporter component, and a sensor component of the CqsS-LuxU-LuxO gene cassette whose proteins will detect CAI-1 in a water sample and drive expression of reporter genes under the control of the Qrr promoter. The DNA components of the biosensor have been inserted into the pWH1274 expression plasmid and transformed into Acinetobacter baylyi ADP1 which is a useful robust host in terms of viability, maintenance and storage. Preliminary results show that the DNA components have been successfully incorporated into the plasmid and transformed into A.baylyi using reporter genes GFP and lux operon. We aim to present results of the specificity, sensitivity and operability of the biosensor in detecting V.cholerae in drinking water. Future work is to extend the application of this design of biosensors by looking at quorum sensing systems in other drinking water pathogens.

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The advancements in the field of metabolic engineering and synthetic biology have allowed the rapid de novo construction of multi-enzyme heterologous pathways. However, in order to obtain an optimal flux through a pathway, the various regulatory elements (e.g. promoters, ribosome binding sites) need to be optimized. For example, the massive over-expression of a gene may result in metabolic burden, due to the withdrawal of NADH, ATP, and amino acids from the central metabolism required for the synthesis of the corresponding protein and the concurrent depletion of intermediates required for biomass synthesis or may lead to the accumulation of toxic intermediates due to an unbalanced pathway. The current lack of in-depth knowledge on the various regulatory control levels renders combinatorial approaches popular for pathway optimization. In this context, methods to rapidly and efficiently create variability are crucial. To generate this variability, the promoter and the ribosome binding sites are typically randomized to modulate gene expression and to create gene expression libraries. In this research Gibson assembly was used to introduce promoter and RBS variability into a construct. The biggest advantages are the speed of assembly and the standardized procedure which allow for high-throughput assembly lines. Several libraries were tested: promoter and RBS libraries, but also combinations of both. Furthermore, this developed system was applied for the introduction of multiple libraries at once. Multiple genes could be differentially expressed using a promoter, RBS or promoter-RBS combination library. The research was successfully used for the fast and scarless introduction of various promoter and RBS libraries. This methodology was validated using several fluorescent proteins, and can thus be applied for the combinatorial building of new and synthetic pathways.

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We have collected regulatory sequence and gene expression data for Arabidopsis thaliana into a linked data system hosted by LinkData.org, then created a CAD environment for using this data to design synthetically regulated plant promoters. This environment is written in JavaScript and hosted by the companion site App.LinkData.org. There are several advantages of this system. (1) Non-experts can use the CAD environment and linked data to design functional DNA sequences with a fast learning cycle. (2) JavaScript programmers can readily fork and extend functions of the CAD environment with modular ‘GenoApps,’ which perform queries on the data and editing operations on the DNA sequences. Each module searches for different gene properties such as gene expression level in a particular plant tissue or tissues, or phase and amplitude of circadian oscillations. (3) Users can easily upload additional promoter data for use in the CAD environment. Biologists familiar with particular regulatory sequences can easily add them to the design inside the CAD environment. Researchers can upload additional databases of gene expression and regulatory motif data to generate alternate hypothesis designs. (4) Researchers can perform novel analyses on the linked data, and add derivative data for use by the GenoApps. Mashups of cis-regulatory sequence databases (e.g. PPDB, ATTED-II) and gene expression databases (e.g. AtGenExpress, DIURNAL) allow the user to perform advanced queries and modify gene promoter sequences to create synthetic plant promoters for tissue and time specific expression of an introduced gene. Several example promoter designs are being characterized experimentally by Firefly Luciferase expression in Arabidopsis. We will also discuss results from the promoter designs submitted to GenoCon2, the second international rational genomic design contest: http://genocon.org/

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Molecular mechanisms generating genetic variation provide the basis for evolution and long-term survival of a population in a changing environment. In stable, laboratory conditions, the variation-generating mechanisms are dispensable, as there is limited need for the cell to adapt to adverse conditions. In fact, newly emerging, evolved features might be undesirable when working on highly refined, precise molecular and synthetic biological tasks. By constructing low-mutation-rate variants, we reduced the evolutionary capacity of MDS42, a reduced genome E. coli strain engineered to lack most genes irrelevant for laboratory/industrial applications. Elimination of diversity-generating, error-prone DNA polymerase enzymes involved in induced mutagenesis achieved a significant stabilization of the genome. The resulting strain, while retaining normal growth, showed a significant decrease in overall mutation rate, most notably under various stress conditions. Moreover, the error-prone polymerase-free host allowed relatively stable maintenance of a toxic methyltransferase-expressing clone. In contrast, the parental strain produced mutant clones, unable to produce functional methyltransferase, which quickly overgrew the culture to a high ratio (50% of clones in a 24-h induction period lacked functional methyltransferase activity). The surprisingly large stability-difference observed between the strains was due to the combined effects of high stress-induced mutagenesis in the parental strain, growth inhibition by expression of the toxic protein, and selection/outgrowth of mutants no longer producing an active, toxic enzyme. By eliminating stress-inducible error-prone DNA-polymerases, the genome of the mobile genetic element-free E. coli strain MDS42 was further stabilized. The resulting strain represents an improved host in various synthetic and molecular biological applications, allowing more stable production of growth-inhibiting biomolecules.

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Despite ongoing technological and scientific advancements in the field of synthetic biology, one major bottleneck in the development of applications is the design process. The task of identifying the necessary components that need to be stitched together remains a laborious and time consuming activity. Here I outline the implementation of an accelerated design and engineering methodology for synthetic biology. This methodology is known as Integrated Concurrent Engineering (ICE) in the aerospace industry and has been shown to cut NASA’s preliminary design time from nine months to three weeks. Applying Integrated Concurrent Engineering to synthetic biology (SBICE) could significantly speed up the design, build and test cycles. I will discuss the first trial session where SBICE was implemented and show that by applying engineering methodologies to biology we could enhance the way we design genetic circuits, genomes and organisms.

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Synthetic biology has progressed rapidly over the last decade and is now positioned to impact important problems in energy and health. Accelerating high impact medical applications will require utilizing methods that interface directly with medical infrastructure, genetic circuits that function outside of the controlled lab setting, and safe and clinically-accepted microbial hosts. The ability of certain bacteria to undergo tumor-specific exponential growth can be exploited to create sensitive and specific cancer detectors that overcome challenges of traditional cancer diagnostics. Previously, such bacteria have been genetically engineered to participate in luminescence-, PET-, and MRI-based imaging modalities for tumor detection. Although these diagnostics each have specific utility, they have required intravenous or intratumoral delivery and expensive equipment, limiting their application to select cases. Our cancer diagnostic platform utilizes oral delivery of the currently-prescribed probiotic E. coli Nissle 1917 (EcN) to detect cancer metastases within 24 hours, demonstrating tumor-specific colonization via translocation from the GI-tract for the first time by EcN. Once colonized, our platform uses tumor-specific exponential growth coupled with bacterially produced indicator substrates or enzymes to produce a sensitive and cost-effective system for detection of tumors. We envision this platform to ultimately function in at-home paper tests, field diagnostics, and integrated with existing medical infrastructure for urinalysis.

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The ability to dynamically monitor or visualize local immune states in vivo would transform our ability to understand processes such as the establishment and development of dysfunctional immune states at tumor sites and the response of these multicellular networks to potential therapeutic interventions. To date, however, we are limited to systemic measures (such as profiles of serum cytokines or circulating immune cells) or terminal assays (requiring tissue biopsy or, more commonly, sacrifice of the experimental animal). We have established a novel mammalian synthetic biology technology enabling us to engineer cells into living “biosensors” responsive to environmental stimuli that are exclusively extracellular, such as the cytokines that characterize specific immunological states. These cell-based biosensors detect a relevant analyte of interest and then produce an optical signal that can be imaged in whole, living animals (e.g., luminescence, near-infrared fluorescence). This approach is fundamentally distinct from a reporter gene approach, in which one can only detect whether a given gene is expressed in the engineered cell, not whether the engineered cell is exposed to the analyte. The platform and its components are orthogonal from native signaling components and can be adapted to detect many different extracellular signals allowing the potential for multiparametric evaluation of the extracellular microenvironment. As an initial proof of principle, we will engineer tumor cells to function as biosensors, such that following adoptive transfer of engineered tumor cells to a syngeneic mouse host, the tumor will monitor and report upon its own immunological milieu. We will initially be applying this technology to help understand how the immune response shifts from anti-tumor (immunostimulatory) to pro-tumor (immunosuppressive) during the course of tumor progression. This foundational technology could eventually be extended to generate cell-based therapies by tying biosensing to the expression of therapeutically-relevant gene products.

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Precise control of gene expression is critical for living cells and for many applications in synthetic biology. We have developed a combined genetic, hardware, and control strategy for programming gene expression dynamics in the bacterium E. coli that relies on modulation of an oscillating input pattern, rather than modulation of input intensity as is conventional. This strategy depends on the signal transduction process functioning as a low-pass filter, in which the oscillating input signal is ‘passed’ at low frequencies, resulting in an oscillating output, and attenuated at high frequencies, resulting in a constant output. Above a cut-off frequency, the pathway output can be scaled continuously between the ‘off’ and ‘on’ states through pulse width modulating the input signal. This strategy allows fine-tuning of expression rates, levels and temporal dynamics, as well as the control of bacterial physiology by direct control of expression of a key metabolic enzyme.

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Amyris successfully engineered Saccharomyces cerevisiae for the industrial scale production of artemisinic acid, a precursor to the potent isoprenoid antimalarial drug artemisinin, and (E)–farnesene, a valuable platform molecule from which an energy dense diesel fuel and a variety of chemicals can be derived. To accelerate the identification of yeast strains with improved performance, Amyris developed an Automated Strain Engineering (ASE) platform, based on a modular synthetic biology system which utilizes a series of well-characterized DNA linkers, computer-aided strain design and automated systems for DNA amplification, DNA assembly and transformation. Since its initiation in 2008, more than 12.000 individual DNA fragments have been assembled into over 25.000 unique plasmids. In this presentation, the lessons from 5 years high-throughput DNA assembly will be discussed, including an experimental comparison of different DNA assembly methods and ongoing developments to improve Amyris’ synthetic biology platform.

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The ability to rapidly test and develop new components and subsystems for use in synthetic biology would broaden the repetoire from which new capabilities can be generated. Multiple techniques such as rapid DNA assembly, in vitro transcription-translation systems, and computational protein design may be combined to move from a notional function to proof-of-concept faster than would otherwise be possible. We show preliminary results from a new engineering process that combines computational protein design with a fast in-vitro “breadboarding” system for rapid, low-cost prototyping of a new biological transcription factor-based sensor. The multidrug response regulator qacR from S. aureus, which has been previously characterized, was chosen as a target for re-engineering. Computational protein design targeting the qacR transcription factor’s small molecule binding site was performed, resulting in a set of mutants designed to switch the specificity of qacR to a new small molecule ligand. These mutants are characterized using an in vitro transcription-translation (TX-TL) system. In this process, the TX-TL system provides multiple advantages over the characterization of these transcription factors in vivo. The protein is being engineered to detect a particularly toxic small molecule found in lignocellulosic feedstock. TX-TL allows us to screen for transcription factor sensitivities above concentrations that can be realized inside cells (either due to toxicity or transport), making it possible to characterize potential hits for activities otherwise inaccessible via in vivo screening. Furthermore, control of expression levels of different system components can be achieved by varying the DNA concentrations in the in vitro system, avoiding time-consuming fine tuning of plasmid copy number and promoter strength in early system design phases. As a whole, our new engineering process provides quantitative information about the circuit within hours of setup over a variety of different conditions, enabling cost-effective and rapid protoyping of experimental designs.

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Engineered microorganisms promise to enable the renewable and environmentally friendly production of fuels, bulk chemicals, and therapeutics. To achieve commercial viability for these processes, the most difficult challenge is not necessarily how to build a pathway to produce a desired molecule; rather, it is to optimize that pathway for both yield (i.e. product generated per input consumed) and productivity (i.e. rate of product synthesis). Widely applicable strategies for pathway optimization must be developed in order to get products to market cheaper and faster. A chief consideration for developing such strategies is limiting crosstalk between high-flux engineered metabolic pathways and the cellular processes of the production host. Evolution has solved the problem of crosstalk for many cellular processes by segregating functions into membrane-bound organelles. The goal of this project is to repurpose one of these organelles — specifically the peroxisome of Saccharomyces cerevisiae — to compartmentalize heterologous metabolic pathways. As a proof-of-principle, we are working to demonstrate encapsulation of a short enzymatic pathway within the peroxisome and show that compartmentalization reduces the accumulation of off-pathway side products. Additionally, we are investigating methods to improve the cargo capacity of the peroxisome by both removing endogenous proteins and modulating the expression level of biogenesis genes. Ultimately, this work will contribute to the development of a synthetic organelle as a tool to limit metabolic crosstalk and improve the predictability and efficiency of engineered microorganisms.

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Enzymes vary widely in size, and there is no clear and direct correlation between size and function. Modern enzymes are likely to carry superfluous residues that are evolutionary artefacts, present as a function of that particular enzyme’s history. Deleting unnecessary residues from enzymes could provide insight into the minimal requirements for function, and provide smaller, more tractable systems for mechanistic studies. Furthermore, smaller proteins would potentially be of interest as efficient modules for synthetic systems. Finally, removing non-critical segments of an enzyme would allow exploration of regions of sequence space that are not readily accessible by the standard methods of random mutagenesis. We describe here a convenient method for carrying out random deletions that we have developed, and its application to the model enzyme -lactamase. The method makes use of an initial transposition step followed by exonuclease digestion to produce deletions of variable length and location. By screening libraries carrying deletions of between 3 and about 40 base pairs for in vivo function, we isolated 24 different functional variants that contained deletions varying from 1-5 codons. The deletions are distributed throughout the enzyme structure and are located largely, but not exclusively, in loops. There is no obvious correlation between the length or location of tolerated deletions and the effect on enzymatic activity.

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The SynBio Broker Business Model was developed to participate in the 2012 iGEM Entrepreneurship Competition, wining the “Best Business Model Analysis”. The business broker offers a consultancy service for the creators of biological systems and for companies that are interested in acquiring the technologies that synthetic biology provides. When a deal is closed, the broker takes care of all the transactions needed to deliver the biological system to its destination. The business gets monetary incomes for the consultant service and also for a percentage of the closed sales. Following is a more detailed explanation of the aspects covered by the service of the broker. First we get in touch with a company to hear its needs; then we make a complete study of the case to find a biological system that solves the problem. After that, we contact the creators of the biological system to buy the rights of using it. Later, we take the bought sequence of the biological system to a sequencer company to make it a physical product. Finally we deliver the product to its destination. We follow up every client after the transaction to make sure everything went as expected. This model was created inspired in the amazing projects presented in the iGEM Championship every year, lots worthy of becoming a reality. We are aware that companies have needs and problems, and most of them don’t know all the resources available in the world. This broker helps both parts by getting them in touch, giving the appropriate consultancy and making possible the delivery of a biological system ready to use.

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CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) and CRISPR-associated (Cas) systems in bacteria and archaea employ RNA-guided DNA endonuclease activity to provide adaptive immunity against invading foreign nucleic acids. Here we report the use of Type II bacterial CRISPR/Cas system in Saccharomyces cerevisiae for genome engineering. The CRISPR components, Cas9 gene and a designer genome targeting CRISPR guide RNA (gRNA), show robust and specific RNA guided endonuclease activity at targeted endogenous loci in yeast. Using a constitutive Cas9 expression and a transient gRNA cassette we show that targeted double-strand breaks can increase homologous recombination rates of single and double-stranded oligonucleotide donors by 5-fold and 130-fold, respectively. Our approach provides foundations for a simple and powerful genome engineering tool for site-specific mutagenesis and allelic replacement in yeast.

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The increased usage of oral contraceptives is becoming dangerous for our water safety. In order to see how severe the danger is, an adequate sensor for steroids hormones is necessary since as of now, no in situ sensors are available. Therefore we had decided to explore the possibilities to construct a steroid biosensor, based on the use of engineered bacterial cells. To develop the input module of the sensor we are making use of both the HpaA and the RepA proteins, found in Escherichia coli and Comamonas testosteroni respectively. HpaA detects and binds to phenylacetic acid, a plant hormone, while RepA binds to human steroid sex hormones. Both act as transcription factors after binding their respective ligands. At first a proof-of-principle biosensor has been developed using the HpaA receptor. When connected to a lacZ output module, HpaA has been found to elicit a linear dose-responsive result when induced by (hydroxy)phenylacetic acid, a prerequisite for an adequate sensor. The HpaA input module has also been connected to an electrical readout output module, producing a compact, working biosensor. Data gathered by this construct will be used to create a general in silico model of a hormone biosensor. The human steroid biosensor makes use of the RepA receptor to detect testosterone and various estrogens. Experiments have shown that when induced by these steroids RepA produces a dose dependent response. Further constructions using RepA are yet to be developed. One such planned construct is a coupling of the repA gene with an electrical readout module based on the production of pyocyanin to produce a compact in situ sensor. The aim of this project is to construct two working biosensors, one proof-of-principle plant hormone biosensor and one human steroid hormone biosensor.

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Cells have an inherent sense-and-respond capability that makes novel synthetic cells a promising area for the design of sensor systems. The design of such systems consists of a number of subsystems, including potentially novel sensing mechanisms – for example proteins adapted to recognize a novel ligand, signal transduction mechanisms, and reporter constructs. Additionally, for sensors expected to be released into the environment, a “kill-switch” mechanism may have to be designed to prevent proliferation of the synthetic species. We are utilizing Clotho (http://www.clothocad.org), an open source platform for the design of synthetic biological systems, to build tools in support of this work. Clotho provides a rich data model designed specifically for synthetic biology, as well as an extensible infrastructure for the design of applications and tools to support research in the field. In addition to storing the data produced by our analyses, we are building Clotho modules for the visualization and analysis of parts and data. We have designed a module for viewing protein structures created and scored using our protein design pipeline (PDP) and importing the results as parts into Clotho. Additionally, we are designing tools for running jobs locally and remotely using Clotho’s actor computation model, as well as the Akka (http://akka.io) framework. Our work has largely focused on structure-based methods for design. This includes the design of novel ligand-binding proteins and riboswitches. This poster describes the methods we have used, as well as the tools we are building within Clotho with the goal of producing and end-to-end workflow for the design of cell-based sensor systems.

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Synthetic biology is going to explode a new biotechnological revolution creating a completely new level of biological engineering. Along with the scientific development of synbio, new ethical, legal and social issues (ELSI) are arising. Since synbiologists are aware of the relevance of this, there is a great interest in discussing how to face the challenges ahead. Despite the remarkable inter-institutional effort to address these issues, just a few scientists have considered and analyzed the importance of the ELSI debate in developing countries. Scientific (and non-scientific) community in growing economies has quite different concerns about the potential risks and applications of synbio. Specially in Mexico, there are a big concern about food sovereignty and GMO´s biosafety. The problem is that Mexican legislators and decision makers have tried to imitate public policies proposed in developed countries instead of design original frameworks, consistent to their economic reality. Mexico is experiencing a scientific awakening, there is an unprecedented interest in technological development, if Mexico (and other developing countries) wants to be competitive and take part of the global advance of synbio it is very important to open a debate towards the implementation of public policies that allow the effective growth of biotechnology in the country. Mexican scientists, stakeholders and decision makers must consider the opinion of the global leaders and learn from experiences in order to create an appropriate strategy. This work aims to determine the key aspects to take into account to establish public policies for synbio development in Mexico.

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Proteins are attractive candidates for synthetic component, but the relatively limited range of structural diversity available in nature (compared to the possible range of structures) may lead to restrictions in designing new functions and interactions. From a topological point of view, the space of possible structures is vastly larger than the space which has apparently been used by nature, with predictions of the number of possible folds based on known structures converging on a number of about 2-3,000. By contrast, the number of possible folds — even given a restricted number of secondary structural elements — is larger by several orders of magnitude, providing many possibilities for combinations of functional sites and interaction surfaces. The periodic table of protein structures offers, uniquely in present descriptions of fold space, a means to describe many of these possible structures on the topological level. We propose a pipeline for taking these abstract structural descriptions all the way to full-atom models with amino acid sequences, starting with rough alpha-carbon only models and progressing through several stages of high-resolution refinement, sequence design and filtering according to known principles of protein structure, coarse-grained and high-resolution knowledge-based potentials and secondary/tertiary structure prediction methods. The resulting sequences are tested using a medium-throughput expression pipeline and analyzed using 2D NMR HSQC spectra, following which soluble folded proteins can be taken forward for full structural characterization.

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A technology enabling the transmission of independent, synthetic, high information content signals between cells in a multicellular network remains a grand challenge in mammalian synthetic biology. This capability could enable the construction of networks involving division of labor, spatial organization, and coordinated functions eventually leading to applications including regenerative medicine and tissue engineering, as well as new tools for fundamental research. Protein-based signaling mediators are well-suited to this role, and molecules such as cytokines and chemokines serve exactly this function in natural regulation of multicellular organisms. However, to date we lack synthetic biology ligand-receptor platforms suitable to sending and receiving protein-based signals. To meet this need, we have developed a novel orthogonal signaling platform of modular synthetic cytokines (which we have termed, “synthetikines”) and corresponding modular synthetic receptors that can detect and discriminate between these signaling molecules. We show how modular receptor design enables both the use of orthogonal signal transduction mechanisms and optimization of desirable receptor performance characteristics. Our synthetikine networks recapitulate both paracrine signaling (i.e., via secretion of soluble ligands) and juxtacrine signaling (i.e., by cell surface-bound ligands), each of which play key roles in processes such as homeostasis and development. Here, we characterize a foundational platform based on mammalian cells, although the core technology could also be adapted to enable interkingdom signaling (e.g., for interrogating or manipulating interactions between host and bacteria in the gut). This novel capability in the mammalian synthetic biology toolkit should prove useful for both investigating and implementing design principles for engineering synthetic multicellular networks.

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One of the goals of mammalian synthetic biology is to design new functional organs for therapeutic applications. To survive and function effectively within a multicellular organism, their component cells must act in a coordinated fashion within the organ itself but also interact with the whole organism. It may therefore become critical to engineer short and long range intercellular communication mechanisms for de-novo organogenesis based on genetic reprogramming of cells.
To address this challenge, we developed two different in-vitro synthetic intercellular communication systems in mammalian cells, designed to prevent cross talk with the endogenous cell signaling pathways.
To allow short-range communication, we created a paracrine signaling mechanism by coupling sender cells producing an inert and diffusible plant metabolite via an engineered metabolic pathway; and receiver cells sensitive to the concentration levels of this metabolite. Several promoters/transcription factors were constructed allowing the implementation of various responses.
To allow long-range communication, we hijacked the Rous Sarcoma Virus genome to create virus-like particles, free of viral DNA but specifically carrying an effector protein of interest (recombinase, transcription factor, etc…). We demonstrated the modularity and scalability of this cell-to-cell protein transduction system by integrating multiple signals to perform intercellular logic computation.
We believe these systems will be useful for a very broad range of applications and will fasten the development of therapeutic applications of mammalian synthetic biology.

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Fluorescent proteins are a valuable tool for research, with uses ranging from reporters in transgenic systems to biosensors. The tangle of intellectual property restrictions, as well as protein characteristics like brightness, oligomeric state and sensitivity to environmental conditions limits the breadth of tasks to which fluorescent proteins can be applied. We have created a large set of new colored and fluorescent proteins by backtranslating a set of sequences from Genbank, using GeneDesigner software to simultaneously minimize sequence differences and match an E coli codon bias. Oligonucleotides designed to synthesize each gene were combined to create chimeric genes. The resultant chimeras were selected under various illuminations. Analysis of sequence and spectral data allowed us to infer correlations between them. Correlations were then tested by creating specific individual sequences and determining whether their spectral properties were as predicted. Three amino acid positions were found to be individually responsible for cyan, green or yellow fluorescence emission. We also identified variants with non-overlapping spectra as candidates for applications using more than one fluorescent protein, for example microscopy and FRET (Fluorescence Resonance Energy transfer) applications. DNA2.0 will make its Protein Paintbox™ available without intellectual property restrictions, for the Synthetic Biology research community to improve upon and to incorporate into innovative products.

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An exciting avenue of synthetic biology is expanding the scope of life’s chemistry. Unnatural amino acids in proteins can drastically alter their functionality, enabling chemical reactions that would otherwise be impossible using the canonical genetic code. To achieve site directed incorporation of unnatural amino acids, aminoacyl tRNA synthetases are engineered that have a broadened substrate specificity and tRNAs are modified to read through amber (UAG) codons. Engineering these components can be challenging and improved methodologies are desirable. We developed a novel platform for the directed evolution of biomolecules called Compartmentalized Partnered Replication (CPR), which was used to evolve a tRNA synthetase pair. CPR is an emulsion-based selection system that couples the in vivo functioning of a gene to its in vitro amplification. Libraries of the Saccharomyces Cerevisiae Tryptophanyl tRNAs and cognate synthetases were generated and transformed into cells harboring a plasmid containing a Taq DNA polymerase gene with one or more amber codons in the open reading frame. The suppression of the amber codons in the Taq gene is essential for expressing full length Taq polymerase. The E. coli cells are emulsified along with buffers, dNTPs, and primers specific to the synthetase or tRNA genes. Upon thermal cycling, active synthetases are amplified due to their ability to make functional Taq polymerase. iterations of this process enrich for the most active variants in the population. By altering the binding pocket of the synthetase an unnatural amino acid, 5-HydroxyTryptophan can induce suppression of an amber codon. The cognate tRNA was also modified such that suppression of amber codons was increased by 6-fold over the starting construct. Since CPR is a generalizable platform for the evolution of biomolecules, future efforts will be directed towards expanding the repertoire of engineered biomolecules.

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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. In the presented work 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.

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The genetic tuning of circuits and pathways to hit their “sweet spot” remains a key bottleneck of the design-build-test cycle of Synthetic Biology, and will continue to stymie efforts to engineer more complicated genetic systems. New approaches are needed that systematically identify the optimal DNA sequence to carry out a targeted activity, while performing the fewest number of characterization experiments. We present a new model-designed, experimental approach that efficiently maps the relationship between a genetic system’s DNA sequence, protein expression levels, and system activity (QSEA Map), combining our next-generation RBS Calculator v1.2 with an optimal search algorithm. Using QSEA Maps, synthetic biologists can design synthetic sequences to rationally navigate the multi-dimensional protein expression level space and to target regions with a desired behavior. We first demonstrate our approach on a collection of NOT gates, enabling the rapid connection of multiple genetic circuits to create multi-layer logical programs. We then employ QSEA Mapping to optimize a three enzyme biosynthesis pathway, using fewer than 100 characterization experiments to chart its pathway activity space, across a 1000-fold range, and to design synthetic pathways with maximized activities. QSEA Maps encapsulate many possible behaviors of a genetic module, and predicts the sequences that control its function, revolutionizing our ability to rationally connect circuits and pathways together, and promising to dramatically reduce our cloning efforts.

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Protein nanocages (PNs) are spherically shaped polymeric structures with large internal cavities. In nature, PNs enable nano-scale compartmentalization. Cellular organisms use these nano-scale compartments to sequester toxic species, enhance reaction kinetics, traffic molecules and re-fold proteins. Virally encoded PNs (termed capsids) confer both host specificity and protection during the extracellular phase of their life cycle. The diversity of PNs and their occurrence in all domains of life reflect both the importance of nanoscale compartmentalization and the flexibility of the ‘hollow sphere’ architecture. From a biotechnological perspective, PNs represent an attractive engineering substrate. They are genetically programmable, biocompatible, biodegradable and physically uniform. To rationalize design, we have collated a library of naturally occurring PNs and developed an accompanying suite of in-silico characterisation tools. We hope that this resource will support Synthetic Biologists in their selection and use of PNs for the construction of nano-scale devices. In addition, we demonstrate how PNs can be re-engineered such that their inner cavities can be loaded with different nanoparticles. We are presently investigating how the external surfaces of these hybrid PNs can be functionalized to produce a targeted therapeutic against cholangiocarcinoma.

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Dynamic response characteristics are a cornerstone of system design and control yet related tools are lacking. Time-lapse microscopy of individual cells expressing synthetic reporter proteins represents one of the only tools capable of making dynamic measurements. Disadvantages of time-lapse microscopy are limited throughput and photobleaching. Herein we explore changes in dielectrophoretic forces caused by changes in expression of membrane proteins in S. cerevisiae. Dielectrophoresis is proven in medium throughput experiments and is not subject to protein damage permitting longer exposure times and more sensitive measurements. Hence, the described changes potentially enable dynamic measurements of gene expression and subsequently the development of tools that better meet the engineering needs. Theoretical and FEM models were simulated and the results were investigated in detail. Linear dependence of the first crossover frequency in the dielectrophoretic response on membrane protein concentration was revealed. Several microfluidic experiments were designed to confirm the theoretical expectations.

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An important branch of Control Theory, namely System Identification, aims to derive from measurement data a dynamical model of a physical system able to predict its behavior to future inputs. In biology, System Identification could be used either to design feedback control strategies to steer the biological system towards a desired goal, or even to understand the biological mechanisms underlying a biological process. However, current experimental techniques in biology allow measurements of only a few time points during a time-course, thus limiting the application of System Identification paradigms. Here, we propose an experimental approach, to make biological application of System Identification and Control Theory possible. We designed and implemented an experimental platform based on a microfluidic device, a time – lapse microscopy apparatus and, a set of automated syringes all controlled by a computer. Then we used this platform to realize in-vivo experiments on yeast cells; microfluidics allows to isolate the biological material and to precisely change cell environmental conditions (i.e. by using automated syringes to modulate the nutrients provided to yeasts). This platform allowed us to implement and compare different linear system identification methods to a simple network in S. cerevisiae, and to control gene expression within a complex network integrated in yeast cells. The ability to precisely dosage a protein in living cells could be exploited for several biological purposes. We are applying this approach to study the onset of protein aggregates involved in neurodegeneration: an engineered yeast expressing wild-type (wt) and mutated (mt) forms of the human protein alpha-synuclein under the control of the GAL1 promoter will be used to precisely control the level of wt and mt alpha-synuclein and to quantify aggregate formation propensity and protein aggregation dynamics.

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Recent advancements in DNA synthesis and assembly have continued to drive forward synthetic biology research. However, DNA assembly techniques such as isothermal DNA assembly and transformation-associated recombination (TAR) cloning, are expensive in terms of time or money. Here we propose to investigate the capabilities of lysates from wild-type Escherichia coli, Saccharomyces cerevisiae and Deinococcus radiodurans to mediate DNA assembly. The process is as simple as culturing and harvesting lysate from your assembly microbe, adding linear DNA fragments, incubating for an hour and directly transforming circularized products. This assembly methodology harnesses the same innate DNA-repair mechanisms exploited in TAR cloning, yet obviates the need for transformation and subsequent isolation of S. cerevisiae-compatible final products. With respect to Gibson’s Isothermal assembly, this process is significantly less expensive per reaction, improving assembly throughput with limited resources. We expect this lysate-based DNA assembly approach to further enable the implementation of genetically encoded systems of increasing size and complexity for both applications and basic biological research.

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Toxicity of organic solvents to microbial hosts is a major consideration in the economical production of biofuels such as ethanol and especially butanol, with low product concentrations leading to high recovery costs. Understanding the mechanisms involved in solvent tolerance is crucial for rationally engineering robust microbes. We have developed a bioluminescence assay to determine the effects of different genes on survival in four model inhibitors-ethanol, n-butanol, acetone and furfural. Adopting a synthetic biology approach, a library of potential solvent tolerance BioBricks (genes) was generated and tested as proof-of-concept. Using this method, we have generated a set of tolerance modules suited for these inhibitory compounds, which can then be combined with genetic modules encoding substrate breakdown and product formation pathways. Ultimately, we hope to generate improved biofuel-producing systems which can generate higher product concentrations, greatly improving process economics. A similar approach can be used to model interactions between different genes which give rise to other complex phenotypes.

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Synthetic biology tools allow for the design of novel therapeutic bacteria as an alternative treatment to antibiotics in controlling outbreaks of pathogenic microbes. One approach is to develop engineered bacteria (EB) as a method to target phage release to attack and eradicate pathogens. Phages make an attractive option for treatments due to their relatively narrow range of viable hosts and potential for self-perpetuation. Detection of the target microbes can be used to regulate lysis of EB cells and release of phages by engineering the bacterial cell-cell system; quorum-sensing. The development of these EB into therapeutic probiotics will demand inclusion of a component capable of auto-regulating population size to avoid out-competing native flora in host organisms. This component will also coordinate phage release in order to successfully overcome the target pathogen population. Placing the expression of a lethal gene under control of quorum-sensing creates an EB population that can maintain a tunable population density. Mathematical models that characterize the design of such a circuit that can balance population loss due to lysis and growth-regulation are outlined here. The models also elucidate the dynamics of EB populations in the presence of pathogens and the effect of tuning circuit parameters on population stability. Model outcomes are compared to preliminary in vitro results demonstrating the behaviour of our EB. Exploring the dynamics of this complex synthetic circuit will provide essential insight into the challenges present when designing therapeutic microbes.

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Fatty acids are highly reduced, energy rich compounds that are potential precursors to biofuels and other commodities. E.coli produce an abundance of fatty acids as a major component of their lipid membranes and much work has been done to increase E.coli production of these long chain fatty acids. In this work, we engineer E.coli to selectively produce medium chain fatty acids, which are potentially more valuable biofuel precursors than long chain fatty acids. To this end, we use traditional metabolic engineering techniques including gene knockouts and over-expression, but also replace an endogenous fatty acid synthesis enzyme with one designed to produce eight carbon fatty acids. Finally, we make use of a previously engineered ClpXP inducible degradation system to degrade a second, essential, fatty acid synthesis enzyme that pulls carbon flux away from medium chain fatty acid production. Using these techniques, we show that we can produce medium chain fatty acids at greater than 12% theoretical yield in E.coli. We are currently using this same inducible degradation system to degrade other essential metabolic enzymes in E.coli and thereby dynamically redirect metabolic flux. We predict that these techniques can be used to increase the biological production of a variety of commercially desirable compounds.

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The ability to design new biological parts, devices and systems, or redesign existing biological systems for useful purposes using engineering approaches is at the heart of synthetic biology. Although there have recently been a number of success stories, the ultimate goal of creating a selection of parts that can be picked off the shelf and assembled into functional devices is still tantalisingly out of reach. Living systems exhibit greater integration of parts than those in synthetic models, potentially causing unpredictability in device behaviour. We developed a tool to help predict relative promoter activity based on the underlying nucleotide sequence of promoters. We investigated the effects of device construction on the relative promoter activity. We found that standard promoters (which may have short nucleutide sequences) display device-dependent relative promoter activity, while the strength of insulated promoters strength is usually device-independent. Our simulations indicate that the RBS can affect the transcription initiation rate and well as the translational initiation rate in standard promoters. Our computational results are inline with experimental data for an example GFP device with various promoters. A part can effect the promoter preceding it in a device, because its upstream nucleotide sequence can extended into the ITR of the promoter, possibly effecting the elements that affect transcription initiation and promoter escape. Insulated promoters are protected from this device dependent behaviour because their underlying nucleotide sequence is designed to span the entire region that contains the majority of transcription factor-binding sites in natural bacterial promoters, and most of the elements that affect transcription initiation and promoter escape (positions -105 to +55). Our work indicates that an analysis of the nucleutide sequences of promoters allows us to predict more realistically the strength of the various promoters and therefore the dynamics of the designed systems.

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Cyclic expression of genes (i.e. oscillation) is involved in basic processes such as the cell cycle and the circadian clock. Ultradian oscillations, i.e. with periods much shorter than 24 hours, have been observed also in the major signalling pathways, but their relevance is still unclear. Little is known about how cells orchestrate their individual clocks in order to obtain a collective behaviour: this happens when a population of oscillators starts “beating in time”, or synchronise. Here we investigate the role of synchronisation of oscillations of the Notch-effector Hes1 using a model system mouse myoblasts (C2C12), where Hes1 oscillations are prominent. When investigating properties such as cyclic gene expression, the bias of dealing with a population of cells must be taken into account; experimental measurements reflect the average behaviour of the cell population, which can be very different from what happens in the single cell. To this aim, we took advantage of an innovative microfluidic platform (Kolnik et al., 2012) and of engineered Hes1 reporters, to study the properties of the Hes1 oscillator by applying periodic stimuli in time-lapse fluorescence microscopy over several days. Understanding pulses of different signalling molecules affect synchronisation of cell-autonomous oscillators will ultimately allow to gain insight on the role of oscillations in the coordination of a collective response at the population level. [This work was funded by the European Community's Seventh Framework Programme [FP7/2007-2013] under grant agreement n° 259743 (MODHEP) and by the Telethon Foundation Grant TGM11SB1 to DdB]

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Replication of all living cells relies on the multi-rounds flow of the central dogma, and reconstituting this flow is an important step in both understanding and in creating self-reproducible system. Especially, expression of DNA replication proteins is a key step to circulate the processes of the central dogma. Here we achieved the entire sequential transcription-translation-replication process by autonomous expression of chromosomal DNA replication machineries from a reconstituted transcription-translation system (PURE system). We found that low temperature is essential to express functional DNA polymerase III holoenzyme in a single tube using the PURE system. Our results showed that adding 9 DNAs to the PURE system is enough to reconstitute DNA polymerase III holoenzyme, and raised the first direct evidence of that chaperones are not needed to form the complex DNA polymerase III from polypeptides. These are surprising because the classical methods to reconstitute DNA polymerase III holoenzyme need several steps, and co-overexpression of the 9 genes in living cells causes aggregation. Addition of the 13 genes, including initiator, DNA helicase, helicase loader, RNA primase and DNA polymerase III holoenzyme, to the reconstituted protein expression system gave rise to a DNA replication system by a coupling manner. An artificial genetic circuit demonstrated that the DNA produced as a result of the replication is able to provide genetic information for proteins, indicating reconstitution of an in vitro central dogma cycle.

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Engineered biological systems that execute precisely regulated responses are useful in a variety of applications. For instance, gene- or cell-based therapies for killing pathogenic cells can be engineered instead of development of novel drugs. However, there have been only a few proof of such concept so far. Here, we show approaches for specific input-triggered programmed killing of engineered or non-engineered yeast cells by rewiring the osmoregulatory high-osmolarity glycerol (HOG) MAPK pathway. Combinatorial integration of rich genetic parts such as a heterologous kinase, constitutively active components and chemical-inducible promoters allows controlling yeast growth via improper activation of the HOG pathway in a Boolean logic manner. Rewiring two upstream osmosensing branches of the HOG pathway as different logic functions (AND, NOR, or N-IMPLIES) enables also complex XNOR and XOR logic killing. Moreover, we propose a genetic-based predator-prey system, in which engineered cells kill specific target cells in a target cell-dependent manner. As a proof of concept, we demonstrate that engineered yeast cells (predator) carrying sleeping MAPK-disorder genes kill virtual pathogenic yeast cells (prey) in an AND logic manner. Thus, rewiring MAPK signalling with existing genetic parts provides new synthetic biological strategies useful for future medical applications.

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The Synthetic Biology Open Language (SBOL) is a community-driven standard to exchange information pertinent to DNA designs among software tools, research groups, and commercial service providers. Compared to existing flat annotation formats, such as GenBank or FASTA, SBOL provides expressive and extensible data exchange capabilities, to share rich information about synthetic biological designs. The SBOL community, consisting of academic and industry members, defined a core data model that enables the exchange of DNA sequences and their components. The core data model provides extension capabilities to annotate the DNA components with additional information. In working groups, SBOL developers act jointly to provide minimal but expressive extensions to annotate DNA components with regulatory interactions, host context information, performance characteristics, or simulation results. The structured, hierarchical nature of the core data model and its extensions makes it possible to share all the required information to fully re-engineer synthetic biological designs. To integrate the SBOL standard into a software tool, we have developed software libraries and specification documents. To reassure a growing SBOL community and to receive input from the Synthetic Biology academic and industrial community, we demonstrate SBOL’s current data exchange capabilities on two case studies. The first case study exemplifies the exchange of DNA components between three sites using four different software tools. The second case study illustrates the data exchange between a graphical design tool and a textual design language. Both case studies demonstrate SBOL’s applicability and utilization in the exchange of DNA components while designing novel synthetic biological systems using biological CAD tools. The SBOL community aims to reach a wider range of software to make SBOL more accessible to non-developers. Furthermore, we continue to enrich SBOL’s data exchange capabilities, making it ultimately possible to fully re-engineer synthetic biological designs using biological CAD tools.

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Since the Asilomar Conference of 1975, scientists have acknowledged the need for genetic safeguards that enable biocontainment. Sterile technique can limit the spread of genetically modified microorganisms (GMMs), and genetic strategies that prevent lateral transfer of recombinant episomes have been reported, but the problem of genetically containing engineered cells has not been solved. An inducible gene switch permitting regulation of cell viability would diminish the chance of GMM escape and could permit use of engineered microorganisms outside controlled laboratory environments. By bringing essential genes under the control of engineered RNA-based post-transcriptional regulators, we have built a collection of E coli strains capable of growth only in the presence of synthetic small molecule inducers. When grown with these inducers, our biocontained strains show little or no fitness defect compared to wildtype cells. The frequency of escape from biocontainment among these strains is already 10-8. We hypothesize that co-incorporation of several riboregulated essential genes will increase the Hamming distance between contained and escaped genomes causing the escape frequency to be reduced further still. To prevent mutation from occurring in the first place, we are also constructing a strain background genetically optimized for biocontainment. The E coli chromosome encodes nonessential transcription factors, polymerases, mobile genetic elements, and signaling cascades that increase the rate of mutation during stress. A modifiable mutation rate helps bacteria mount a response to selective pressures while preserving genomic integrity at other times. We are deleting these elements and characterizing the basal mutation rate of mutants to find a genetic background whose capacity for stress-induced mutagenesis is ablated. By combining multiple riboregulated essential genes in a genetically stabilized background we hope to build a biocontained strain that would permit introduction of GMMs into animal hosts as living therapeutics or into polluted environments for bioremediation.

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One of the major design challenges of Synthetic Biology has been in designing novel genetic devices. Although many such devices have been currently built and tested in-vivo, a major issue faced is in translating a desired behavior to a combination of available genetic Devices quickly, accurately and automatically. Tools that can accomplish this will free designers to focus on the assembly and test of larger systems. In particular, these tools should propose multiple potential implementations with different DNA parts, technologies, and performance driven by user defined “motif libraries”. We present a software workflow called “Cello” to encapsulate Devices as independent modules and combine them to produce biological systems satisfying a more complex behavior. First, we describe “Cello-Motif”; a method for specifying Device composition, its intended function and rules for device to Device combination. Next, we present an algorithm to automatically generate candidate biological circuits satisfying a given specification using a library of Cello-Motifs. The specification can be either full or partial specified Boolean logic. The algorithm utilizes user-defined constraints: Upper-bound on the length of the circuit and the number of Parts of a particular type to be used – to produce an optimal set of candidate circuits. The components of the resultant candidate circuits are assigned Parts from a database, and the dynamic behavior of the circuit can be simulated if biophysical models of the underlying Parts are available. We provide transcriptional, translational and recombinase based “Cello-Motif” examples and the resultant candidate circuits generated for a given specification. This demonstrates that the approach is sufficiently powerful to describe functionality and composition of Devices, while independent of the underlying biological mechanism realizing the function. We also demonstrate methods to use simulated results to computationally predict the “best-match” circuit from the candidate set by asserting which result statistically best-fits the proposed specification.

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The study of in vivo cellular events is not always feasible due to the high complexity of living organisms. Even though a full understanding of a system is the final goal, sometimes one must focus in the minimal set of components that carry on a specific cellular event in vitro. One particular process that has been studied by many years is cell division. In E. coli, the set of proteins involved in the process have been identified, but the detailed performance of each component in the whole event is not yet understood. Most of the proteins somehow interact with the cell membrane, thus, when reconstructing the minimal set of players for cell division, model cell membranes are an important element to take into account. In recent years, different model lipid bilayers have been described with particular properties, complexities and methods of preparation. Supported lipid bilayers (SBLs) are lipid bilayer structures on a solid support; they are stable and durable models suitable for high resolution imaging characterization. SBLs flexibility allows the use of different lipids composition to emulate the native components present in a specific cell membrane. In our case of interest, E.coli membrane is primarily composed by phosphatidylglycerol, phosphatidylethanolamine, cardiolipin, however, it also presents a high percent of membrane proteins. The main goal of this work is to develop different SLBs for the study of the bacterial cell division machinery. In the first place SLBs with different lipid composition were tested, trying to obtain minimal sets of mixtures that are able to support the performance of the whole cell-division machinery. In second place, SBLs that resembles the high protein content of E. coli membrane are sought, either by using E. coli lipid extracts doped either with ZipA proteoliposomes or, inner membrane vesicles (IMVs).

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A major goal of synthetic biology is to be able to modularly engineer robust synthetic genetic regulatory circuits from a library of individually characterized parts such as promoters, RBS, genes and degradation tags. However, very often synthetic parts that are borrowed from one biological system for use in other biological system do not behave as expected when used out of their native biological context. As a result, assembled synthetic circuits rarely show the intended behavior in the first implementation as chosen parts may have the correct function but lack the required quantitative properties. This is often followed by a length process of fine-tuning of imperfect parts or testing alternate parts to resolve the observed issues in the first implementation. We have developed a modeling toolbox for computationally assembling synthetic genetic networks such that the resulting system works robustly in experiments across a wide range of Promoter strengths, RBS strengths, and mRNA/protein degradation rates. The proposed approach is currently being applied in our group to design synthetic bistable memory circuits based on the genetic components borrowed from native lambda phages. We demonstrate the practical application of our modeling approach through a case study where we simulated various combinations of Promoters, RBS and mRNA/protein degradation tags using our modeling toolbox to provide explanations for why genetic components from native lambda phage system do not show bistability when used out of context in designing synthetic bistable circuit in E. Coli. The simulation results also suggested a correct range of synthetic Promoters strengths, RBSs and mRNA/protein degradation tags that can replace their native counterparts from lambda phage such that the bistable memory circuit behaves robustly across a range of environmental conditions.

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miRNAs are small non-coding RNAs able to modulate target-gene expression. It has been postulated that miRNAs may confer robustness to biological processes, but no clear evidence has been reported yet. Using a synthetic biology approach, we demonstrated that microRNAs provide phenotypic robustness to transcriptional regulatory networks by buffering fluctuations in protein levels. We constructed a network motif in mammalian cells, which is commonly found in endogenous regulatory networks, consisting of an inducible transcription factor that self-regulates its own transcription, and the transcription of a miRNA inhibiting the transcription factor itself. We confirmed, using mathematical modeling and experimental approaches, that this motif behaves as a “toggle-switch” in which two alternative protein expression levels define its ON and OFF states. The microRNA confers robustness to the toggle-switch, allowing the cell to maintain and transmit its state indefinitely. When absent,a dramatic increase in protein noise level occurs, causing the cell to randomly switch between the two states.

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The lac repressor (LacI) is one of the most widely used systems for the overexpression of heterologous proteins in Escherichia coli. The protein works as a homodimer that recognizes and binds to a specific sequence on the DNA (operator DNA). Two copies of the operator DNA favour the formation of a dimer of dimers that causes the DNA to loop, inhibits binding of the RNA polymerase and results in protein production being switched off. In nature, binding of allolactose induces rearrangements in the protein structures that result in DNA release and de-repression of transcription. Instead, the non-hydrolysable mimic isopropyl -D-1-thiogalactopyranoside (IPTG) is used for protein over-expression as it efficiently triggers DNA release but remains at high concentration inside the cell. With the aim of altering its responsiveness to IPTG, we mutagenized the inducer-binding pocket of LacI. One mutant showed efficient protein production in the presence of IPTG, but at the same time significantly reduced basal expression levels in the absence of the inducer. GFP expression was used to characterise this mutant and expression kinetics revealed an up to 100-fold decrease in basal expression levels at both 37 °C and 25 °C. As GFP production levels still reach those of wild type LacI, the mutant effectively has a wider dynamic range. Thermal shift assays and isothermal calorimetry showed that, compared to wt, the mutant has lower affinity for IPTG and higher for the operator. When used for the expression of a toxic protein, faster E. coli growth rates are observed with mutant LacI as compared to wt. A single mutation in the LacI inducer-binding site generated a variant with a wider dynamic range and reduced leakiness that is suitable for heterologous protein production. The characterisation of its biological and biophysical behaviour reveals key factors for the function of the lac repressor.

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Inclusion bodies formation of recombinant proteins is one of the major obstacles for their industrial applications. Several approaches such as the use of solubility-enhancing tags, the overexpression of folding modulators, and the modification of physicochemical conditions, have been explored to minimize the formation of inclusion bodies. To further minimize the formation of inclusion bodies while increasing the solubility of recombinant proteins, we designed a novel RNA scaffold system in which a molecular chaperone DnaJ was fused with an RNA binding domain that specifically binds a unique RNA sequence in an engineered RNA hairpin loop structure on the 3’-UTR of the recombinant protein-encoding mRNA. Arranging molecular chaperones in proximity with the translational machinery of recombinant proteins can promote the rapid interaction between molecular chaperones and newly synthesized recombinant proteins to prevent the formation of inclusion bodies. As expected, our RNA scaffold system successfully increased the solubility of selected aggregation-prone proteins overproduced in Escherichia coli (UDP-6-glucose-dehydrogenase, anti p21-Ras ScFv, and anti p21-Ras ScFv fused with a cell penetrating peptide). Our RNA scaffold system would provide a valuable tool for the production of recombinant proteins in soluble and active forms in E. coli as well as for the improvement of the yields of metabolically engineered pathways.

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Proteolytic cleavage is a strategy utilized by both prokaryotic and eukaryotic cells in order to rapidly initiate a wide range of cellular processes. These include protein activation or inactivation by removal of inhibitory or catalytic domains, mediation of protein degradation by revealing stabilizing or destabilizing residues, and initiation of protein translocation by removal of peptide signal sequences or exposure of latent ones. By regulating such a diverse array of cellular processes, proteolytic cleavage presents itself as an excellent candidate for synthetic control. Here, we demonstrate in Dictyostelium discoideum a novel light-inducible protease system which has been constructed by fusing split halves of the NIa tobacco etch virus protease (TEVP) to the light dimerizing proteins phytochrome B (phyB) and PIF6. By coupling the proteolytic output of split-TEVP to the light input dependent activity of phyB and PIF6 we show that target proteins of interest can be modified to enter the N-end rule pathway for rapid protein degradation in a light-controllable manner. Finally, we are working to take full advantage of the precise spatiotemporal nature of light to control the numerous other forms of post-translational regulation which can be mediated by proteolytic cleavage. We envision this system being a general tool for making post-translational cellular processes easier to engineer and study by making it possible to control and perturb these processes on the same millisecond and sub-micron length scale that cells do.

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Synthetic biology is rapidly expanding thanks to the rational design and construction of artificial gene regulatory networks. It allows for the analysis of isolated networks in simple model organisms including the budding yeast Saccharomyces cerevisiae while eliminating variables such as unknown endogenous interactions of the network components. However these gene networks require the assembly of DNA fragments encoding for functional biological parts in a defined order and can prove time costly. To address this time-constraint we have created a series of Gateway vectors that facilitates the construction of an artificial gene from a promoter and open reading frame cassette by one-step recombination reaction in vitro. Depending on the vector backbone used the resulting expression vector can then be introduced as a plasmid into S. cerevisiae or integrated into the genome. This approach allows rapid assembly of the synthetic gene and testing of its function in yeast. As flexible regulatory components of a synthetic genetic network, we also created new versions of the tetracycline-regulated transactivators tTA and rtTA by fusing them to the auxin-inducible degron (AID). Using our gene assembly approach, we made yeast expression vectors of these engineered transactivators, AIDtTA and AIDrtTA, and tested their functions in yeast. We showed that these factors can be regulated by doxycycline and degraded rapidly after addition of auxin to the medium allowing for a finer degree of temporal control. Taken together, the method for combinatorial gene assembly described here is versatile and would be a valuable tool for yeast synthetic biology.

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New promoter sequences which drive the transcription of genes can be derived by mutagenesis of natural promoters or designed de novo by rational, semi-rational and evolutionary approaches. While synthetic promoters for protein expression in prokaryotic organisms can be well designed and constructed by consensus sequence strategies and oligo nucleotide synthesis, eukaryotic promoters are less well understood and most concepts employ natural core promoters where regulatory sequences are fused to improve the strength and regulatory properties of such promoters in eukaryotes. Starting with mutagenesis of the strong and tightly regulated natural AOX1 promoter of Pichia pastoris we have recently developed a library of promoters for protein expression in this methylotrophic yeast which differ in strength and regulation. Based on natural core promoters of P. pastoris and S. cerevisiae new short promoter sequences with related regulatory profiles but diversified sequences were developed. Recently we have also developed synthetic bidirectional promoters for novel coexpression strategies.

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Bistable systems are ubiquitous in nature. Prototypical examples are the S. cerevisiae GAL network and the E. coli lac operon. The bistable and hysteretic behavior of such systems has been analyzed in depth in theoretical and experimental work, but important open questions remain and conflicting results have been reported. For instance, it is unclear how different feedback loops impact on the bistable behavior and a detailed description of how noise influences the switching of cells between different stable states is lacking. Quantitative experimental analyses performed so far have tried to answer these questions for systems in their natural context. However, in this situation the system behavior might be influenced by interactions with unknown cellular factors. To overcome these limitations we implemented a synthetic bistable system resembling the E. coli lac operon in S. cerevisiae based exclusively on orthogonal parts. To determine the state of the system in individual cells we implemented fluorescent protein based reporter systems. Quantitative analysis of the system’s behavior by flow cytometry and fluorescence microscopy demonstrated the system’s bistable and hysteretic properties. We developed a dynamic mathematical model that can reproduce the experimental findings. It predicted how to modify the system to expand the bistable range and to influence switching rates. We demonstrate how the combination of quantitative analysis and mathematical description helps to design bistable synthetic systems in yeast. The system presented here is more complex than positive feedback circuits that were previously established in yeast. Such increased complexity will expand the scope of synthetic systems to understand natural systems.

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Mammalian cell cultures are used for production of biopharmaceuticals, e.g. monoclonal antibodies. Only mammalian hybridoma cells contain the pathways for antibody production, but due to their multicellular origin the cells have complex nutrient requirements. Cell growth and antibody production is limited by supply of essential nutrients such as glutamine and accumulation of toxic waste products such as lactate. Many attempts have been made at tackling these challenges, e.g. by optimising growth media to keep metabolite concentrations at optimal levels. These approaches have been hampered by our ability to monitor relevant cell culture parameters such as metabolite concentration dynamics in real time. The aim of this study is to develop a solution to this problem using a Synthetic Biology approach. Whole-cell bacterial biosensors for important culture parameters, such as glutamine and lactate were designed, built and characterised. The biosensors were designed by applying the principles of standardisation and modularisation to natural metabolite-sensing systems. Characterisation of the biosensors in isolation is followed by validation using cell culture samples and co-culture with hybridoma cells allowing on-line monitoring. Our biosensors are also more generally applicable in any experimental context that requires sensing of metabolites. The results of this study also highlight the many challenges of applying synthetic biology constructs to complex industrial contexts. Finally, these whole-cell bacterial biosensors have great potential. By linking the detection step to a transcriptional output, the bacterial cells could directly respond to the information by changing culture conditions. This could lead to a low-cost artificial symbiosis system.

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Biosensors offer a built-in energy supply and inherent sensing machinery that when exploited correctly may surpass traditional sensors. However, biosensor systems are still limited when compared to traditional sensors in signal production and in their inability to integrate information from multiple sensors. Signal integration in biosensors has the potential to reduce false positive responses and increase specificity, for example if two different sensors that detect the same ligand produce an output only when both are activated. Similarly, signal integration will enable sensing of combinations of ligands that indicate nefarious activities when detected together. Amplifying signal output will increase the detection range of the biosensor, and increase sensitivity since activation of a few cells will induce reporter protein expression over the entire sensor. To address these issues we are making use of recent advances in synthetic biology to create biological ‘circuits’, by utilizing plasmids to act as logic gates in E. coli and connecting them by quorum sensing molecule ‘wires’. RNA-based translational control switches, or riboswitches, leverage conformational changes in the structure of RNA molecules when bound to a specific ligand to regulate the accessibility of a ribosome-binding site of a transcribed gene. Using the Registry of Standard Biological Parts and previously identified riboswitches, we have designed plasmids that confer AND gate logic when transformed into E. coli. The output of the AND gate is the production of a quorum signaling molecule. This molecule serves as the input to a signal amplification circuit that initiates the overproduction of a fluorescent protein. In this presentation we describe the production of these circuits, and quantify the changes in fluorescent output and sensitivity that they confer.

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Synthetic biology makes extensive use of protein machinery to enable, regulate and extend cellular capabilities. Due to the difficulties in creating functional proteins de novo most systems to date have relied on natural diversity, combining genetic parts from multiple organisms into a common chassis. By expressing these genes and connecting them together in novel ways, larger systems can be built. While this approach has enabled the development of sensor systems able to signal the presence of chemicals and detect spatial boundaries, it relies on the ability of genes taken from one organism to be functionally expressed in another. Often this is not the case with extensive `tuning’ required to create a fully working part or device. Problems stem from differences in the native and required expression levels causing production of inactive aggregated forms or misfolded proteins, divergent codon usages across organisms affecting translational dynamics, and in some cases the protein being toxic to the host. To better understand the influence of these factors, we designed a set of expression constructs for multiple proteins known to be either easy or difficult to express in E. coli. Experiments will be performed to measure both the quantity (concentration) and quality (enzymatic activity) of these proteins produced in different ways. By varying the promoter strength (mRNA copy number), RBS strength (translational initiation rate), and codon usage (ribosomal movement speed), we will be able to examine how both the mode of expression and coding sequence play a role in the forms of protein product produced. This will provide insight into the inherent tradeoffs between protein quantity and quality. Result will become available first half 2013. As the ambitions of synthetic biology grow, studies like this will be essential for gaining sufficient foundational knowledge to ensure synthetic parts work as intended in differing contexts.

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Proteins are versatile natural nanomachines; yet, artificial polypeptide folds are challenging to create de novo. Here, we present a strategy to design self-assembling polypeptide nanostructures, based on modularization using orthogonal coiled-coil dimer-forming segments. We designed the tetrahedron that self-assembles from a single polypeptide chain comprising 12 concatenated coiled-coil-forming segments separated by flexible peptide hinges. Path of the polypeptide chain through the 4 vertices of a tetrahedron is defined by the precise sequential order of coiled-coil-forming segments that traverse each of its 6 rigid edges twice forming coiled-coil dimer with their corresponding pair segment. Split fluorescent protein, attached to the termini of the recombinant polypeptide, is reconstituted only by the formation of tetrahedral topology, while polypeptides with a deleted or scrambled segment order fail to self-assemble correctly. This technological platform provides the basis for a design of nanostructures that form new topological polypeptide folds for diverse potential biotechnological applications.

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Cells must process information from environment using molecular interaction networks that orchestrate adequate responses often by regulating changes in gene expression. Stochastic fluctuations in different steps on the path from gene to protein generate cell-to-cell variability in the levels of expression. A current challenge in systems and synthetic biology is to understand how different molecular processes contribute to the variability observed in the phenotype and to what extent this variability is under cellular control. At the level of promoter dynamics, stochastic effects have been characterized, showing that the levels of variability in expression might be encoded in the organization of the regulatory elements in the promoter, i.e., promoter architecture. However, signaling networks and transcription factor activation dynamics, which have been shown to account for an important source of additional variation, have not been considered in these studies. In this work we seek to address the question of whether different promoter architectures can process the variation generated from the signaling network and consequently producing different population-scale phenotypes. We will focus on the family of Two-Component Systems signaling pathways as they have been extensively characterized both experimentally and theoretically. By creating and characterizing a library of semi-randomly mutated promoters regulated by the CusRS TCS in Escherichia Coli we aim to identify those motifs in the promoter architecture that significantly affect variability in expression. The library will allow us to explore the potential of a single TCS in generating different population scale responses. We will then combine these results with mathematical modeling in order to engineer promoter architectures for fine tuning population-scale expression. Our final goal is to achieve precise control on the dynamics of the proportion of cells that turn on gene expression and understand how population scale organization arises from molecular dynamics.

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In 1952, Alan Turing proposed a model for the emergence of self-organizing patterns from a near-homogeneous field of cells. His work presented a possible mechanism by which the diffusion and reaction of chemical substances would, through positive and negative feedback, amplify random differences within the field of cells resulting in stable patterns across the field. There has been much contentious debate about the biological relevance of Turing’s theoretical model but now, sixty years after the publication of Turing’s seminal paper, synthetic biology gives us the tools and the conceptual framework to build genetic circuits from known parts to specifically test Turing’s ideas divorced from the complexity and historical contingency of naturally evolved systems. I am currently developing the parts and devices required for creating a Turing-patterning circuit in E. coli. A key requirement for such a circuit is the presence of two diffusing substances that Turing called morphogens. The obvious choice for morphogens are acyl homoserine lactones (AHLs). I have developed a two-channel receiver for 3-oxo-C6-homoserine lactone (C6) and 3-oxo-C12-homoserine lactone (C12) that minimizes crosstalk between the channels and can be used as a platform for patterning circuits. In order for patterning to occur, morphogens must diffuse at different rates. Initial diffusion experiments suggest that diffusion coefficients of C6 and C12 are not sufficiently different. I am therefore attempting to use polymers that selectively bind single AHLs to influence diffusion rates to create the necessary difference. Modelling provides an estimate of parameters (including ratio of diffusion coefficients) required for the system but even with careful characterization it is difficult to land a full circuit into the appropriate spot in parameter space to achieve patterning, I am therefore using a parallel construction and screening approach to arrive at a functional circuit.

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Secretion into culture media is a desirable route for biomanufacturing proteins employing a prokaryotic host, as they will be free from cytoplasmic contaminants. In gram negative bacteria, fusion of target proteins to a classical signal peptide will simply direct undesirable periplasmic export, possibly resulting in proteolysis, complicated downstream processing or unpredictable secretion that can complicate scale up. The bacterial flagellum is not only a highly efficient nanomotor, but also an efficient secretion machine for flagella structural proteins, extruding them through the flagellar lumen before assembly at the distal growing tip. It contains several thousand monomers of flagellin (FliC), making FliC one of the most abundant extracellular proteins in E. coli. Flagellar biogenesis is extensively characterised and indicates that the flagella represents a structure that is amenable to engineering into an efficient protein secretion device. We have constructed strains with a truncated flagellar structure that we have transformed into a streamlined secretion conduit and demonstrated secretion of eukaryotic and prokaryotic proteins, by targeting with an mRNA and protein signal to the Flagellar Type III secretion apparatus. We are currently working on a number of exemplar proteins that also require manipulation of the E. coli metabolic network to increase production of proline rich eukaryotic proteins.

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One of the major hurdles of synthetic biology is in the process of standardizing the assembly of DNA Parts into Devices. The first attempt at addressing this hurdle was in the form of BioBricks, a binary assembly technique with a standardized library of DNA Parts including, but not limited to, promoters, ribosomal binding sites, coding sequences, and terminators. The next phase of DNA assembly included multi-way techniques such as Golden Gate, Gibson, and Gateway. These techniques greatly increased the speed when making Devices, but they lack modularity in terms of interchangeability of Parts and, thus far, there are no standardized libraries of Parts available for these methods. Modular cloning (or MoClo) was introduced in 2011 as a modular, multi-way assembly technique that’s based on the Type IIS restriction enzyme strategy used in Golden Gate assembly. Here, we present a MoClo library of standardized DNA Parts that includes various promoters, ribosomal binding sites, coding sequences, fusion proteins, and transcriptional terminators. The majority of these parts has been converted from BioBricks and will be made available for use through the Registry of Standard Biological Parts. We also discuss our improvements to the reaction time and efficiency of the original MoClo protocol and highlight various logic gate Devices generated using our new library of Parts. In addition to the biological experiments, we demonstrate how the wet lab knowledge of MoClo is captured in the synthetic biology software tools that have been developed in our dry lab. These include the Clotho Apps Eugene Scripter and Raven, as well as a new MoClo format for use in Clotho. Finally, we will discuss the advantages of a collaborative research environment between computational and biological researchers and how this collaboration is leading to an automation pipeline for the design, assembly, and characterization of DNA Devices.

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The integration of orthogonality is a crucial research strategy in the rational design of biological systems for novel applications [1]. In order to produce such highly predictable orthogonal systems, we propose to employ cell-free systems of highly engineered composition generated from living cells, which are complex enough to reproduce the major synthetic capabilities of living cells – such as the synthesis of natural and artificial saccharides – but are simplified enough to come close to truly engineerable systems [2]. We propose a two-step-strategy: In a first step, the protein synthesis of a growing bacterial cell will be channeled solely to a limited set of system components with the help of the RNA-interferase MazF [3]. In a second step, the cells will be homogenized and the resulting cell-free extract, already enriched in the required protein components, will be subjected to selective hydrolysis of predefined proteins, which otherwise would connect the designed system to the remaining protein background, which would make the performance of the complex system unpredictable. As a proof-of-concept, we propose to implement a preparative 12-step synthesis from cheap glucose and N-acetyl-glucosamine to a valuable antiviral-precursor, N-acetyl-neuraminic acid. 1) Endy (2005) Nature 438, 449-453 2) Bujara, Schumperli, Pellaux, Heinemann, and Panke (2011) Nat. Chem. Biol. 7, 271-277 3) Suzuki, Zhang, Liu, Woychik, and Inouye (2005) Mol. Cell 18, 253-261

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Systems for the in vivo incorporation of unnatural amino acids (UAAs) via amber stop codon suppression have made it possible to expand the genetic codes of many organisms with novel chemical functionalities. However, the long-term effects of access to an artificial genetic code on the global evolution of an organism’s coding sequences remain largely unexplored. Whole-organism experiments of this kind could lead to a better understanding of natural processes of codon reassignment and to more efficient synthetic systems for genome-wide UAA incorporation. We are exploring the consequences of expanded genetic codes through experimental evolution projects involving whole organisms. After serial transfer of T7 bacteriophage on amber-suppressor RF-zero Escherichia coli hosts, we observed mutations leading to UAA incorporation in essential proteins, substitutions that restore stop codons in amber-terminated genes, and addiction such that T7 growth requires an amber-suppressor host. These results pave the way for future experiments that couple the evolution of more efficient UAA incorporation to the survival of addicted organisms and for systematically examining whether genetic codes with certain chemical functionalities lead to greater overall evolvability.

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In response to the construction of complex electrical circuits and control systems, the engineering community has developed a range of analytical tools to robustly characterize and model integrated systems that would otherwise be unpredictable. Broadly labeled system identification, it provides a framework for the parameterization of such systems and the construction of a “black box” input-output relationship, called a transfer function. Transfer function models are used to determine the operating limits of newly-engineered components and reliably predict the behavior of those components when interfaced with others. Such analysis has previously been applied to cellular systems using step and oscillatory inputs, most recently using microfluidic apparatus to modulate chemical inputs. While valuable, these methods are impractical for interfacing with cells on fast (< 1 minute) timescales and are not amenable to spatial patterning, in contrast to our previously published light-sensing two component systems, which can be modulated quickly and patterned easily. In order to parameterize a transfer function input-output model of signal transduction via these light sensors, we have performed frequency analysis on two different sensors by subjecting cells to sinusoidally oscillating light inputs spanning a wide range of amplitudes and frequencies, and monitoring gene expression output precisely and with high temporal resolution. Our model has yielded a better understanding of the sensors’ filtering characteristics, noise, and signal transduction limits, suggesting methods of improving sensor performance via engineering. Improved sensors would be ideally suited for applications requiring high-fidelity spatio-temporal patterning of gene expression, for example in the study of developmental processes by patterning precise morphogen gradients with light. This characterization will also enable the light sensors to be used to assess the frequency response of other genes or gene networks, leveraging all the advantages of light induction to address the challenge of analyzing more complex genetic regulatory systems, synthetic or otherwise.

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In vitro E. coli cell-free expression systems are emerging as a powerful new platform for engineering synthetic circuits. Cell-free expression systems are unencumbered by complications inherent to living cells, such as the potential toxicity of expressed products, the cells’ drive to survive, adapt and evolve, and the extraordinary complexity of molecular crosstalk. A recently developed TX-TL cell-free expression system preserves the native E. coli transcription-translation machinery, allowing rapid debugging of novel constructs and a detailed exploration of how individual circuit elements affect circuit performance. However, extract-based systems are currently limited in their ability to probe circuit dynamics, as cell division is non-existent and protein degradation is minimal. Control of degradation further expands the complexity of circuits (e.g. oscillators) that can be tested in vitro. We improve on the TX-TL cell-free expression system by implementing a biochemical emulation of cellular division using an ATP-powered protease and specific proteolysis tags. This system allows us to finely control degradation rates in TX-TL. To demonstrate protein degradation technology, we construct a novel type 1 incoherent feed-forward loop (I1-FFL). I1-FFLs are common motifs in living cells, used to both generate a pulse-like signal and to accelerate system response time. Our I1-FFL utilizes sigma factors, a repressor and a novel combinatorial promoter to generate a pulse of fluorescent reporter protein. We conclude with current efforts to translate in vitro I1-FFLs constructed in TX-TL to in vivo.

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In nature, microbes are constantly communicating. This allows for cooperative feats such as Vibrio fischeri’s coordinated illumination of sea-faring eukaryotic hosts, and the formation of bacterial communities in biofilms. Many such inter-species microbial conversations are mediated by metabolic cross-feeding though the evolution of these relationships is poorly understood and the engineering of them in controlled systems is infrequent. In order to investigate these interactions, this work proposes a synthetic metabolic syntrophy between cyanobacteria, Synechococcus elongatus, and heterotrophs commonly used in metabolic engineering applications. This syntrophy is established through sucrose export by engineered indole-auxotroph cyanobacteria coupled with indole export by a partner heterotroph, either Saccharomyces cerevisiae or Escherichia coli. Such a consortia would harness the power of photosynthesis and remove the need for feedstocks derived from potential food sources separating food and commodity markets. This system shows commercial promise while also allowing for insight into biological questions about growth dynamics, basic science, game theory and evolution.

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Photosynthesis is the primary source of energy and organic carbon for almost all life on Earth, and the ultimate source of feedstocks for many existing and possible future industries. Two processes are involved: the capture and storage of light energy, which occurs rapidly; and the use of that energy to fix CO2 from the atmosphere, which is a much slower process. The mismatch between light capture and carbon fixation means that photosynthesis is inefficient under typical high-light, carbon-limited conditions. This problem is compounded in populations of microbial photoautotrophs, where most cells receive either more light than they can use, or too little light to fix carbon (they are shaded by other cells). We have engineered a microbial consortium to perform photosynthesis in cooperative manner, exporting excess energy in the light and importing energy to fix carbon in the dark. Crucially, there is no net transfer of carbon between cells, so the transfer mechanism is not constrained by the supply of fixed carbon. This ‘distributed photosynthesis’ strategy could increase the carbon-fixing capacity of a photosynthetic population, and is unlikely to have been explored by natural selection, unlike conventional efforts to improve carbon-concentrating mechanisms or the key rate-limiting enzyme RuBisCO.

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Cellular-electrical connections have the potential to combine the distinct capabilities of electronic technologies and living systems. Our research seeks to optimize bi-directional flow of electrons between cells and an electrode, to enable new possibilities in bioenergy, biosensing and bioremediation. We have pioneered a novel genetic approach, in which the electron transfer (ET) pathway from Shewanella oneidensis1 is transplanted into a heterologous organism, providing a molecularly defined route for intracellular electron to move to extracellular electron acceptors.2 The efficacy of this pathway to carry out inward electron transfer has been demonstrated in S. oneidensis, where the reduction of Fumarate to Succinate was carried out using a cathode as the sole electron donor.3 Current work in our group focuses on utilizing the recombinant ET pathway to carry out bio-electrosynthesis in E. coli. In S. oneidensis, the components of the ET pathway are able to directly transfer electrons to the Fumarate reductase, and the electrons are not transferred into the cytoplasm where they would be needed for other electro-synthetic reactions. In E. coli however, the components of the recombinant ET pathway are separated from the Fumarate reductase by the inner membrane; the successful reduction of Fumarate requires electron transfer through the menaquinone pool to a reduction center located in the cytoplasm. Successful inward electron transfer will demonstrate the synthesis of a biological bi-directional cellular-electrode electrical adapter, providing a route for reducing equivalents to move between the extracellular space, and cytoplasm. Future work will focus on studying the effect of intercellular electron transfer on driving the flux of fermentative pathways, potentially leading to an increased capacity of E. coli to synthesize certain economically important products in higher yield and purity.

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Cellular communication has relied on chemical messengers to exchange information. As such, these messengers regardless of their scope are constrained to a chemical system. For instance, the cellular membrane acts as a barrier through which only specific molecules can transverse. In this project, the goal is to render the chemical barrier deprecated in the cellular communication process by using a non-chemical messenger: light. It will transport information between bacterial cells that have been engineered to sense and emit light. Both light emitters and receptors are expressed in Escherichia coli. As light is a messenger effectively decoupled from the chemical layer, novel options arise to expand the already known possibilities of communication among bacteria; being the transfer of information between biological and in silicon systems, such as computers, an attractive bridge to exploit the control of biological processes directed by electronic systems. We believe that this new level will soon change reasoning and design in synthetic biology while interfacing living systems with themselves and informational systems. The modules of reception are photo-receptors that suffer a light dependent conformational change, thus switching from an inactive to an active conformation, which induces or represses a gene expression. A blue light photo sensor (LOVTAP) was assembled by Strickland et al., and submitted to the registry in 2009 by Lausanne team. In this work, we describe in detail the experimental progress obtained characterizing LOVTAP module, including the design and construction steps followed, as well a theoretical stochastic rule-based model that tests different scenarios to analyze its transcriptional behavior. Finally, we used a model to study protein folding and dynamics to explore the effects of punctual aminoacid changes.

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Bacterial flagella are extensively characterised extracellular appendages used for locomotion. Being long proteinaceous fibres, they present great potential as vehicles to display bioactive peptides. We have targeted the field of poorly healing wounds as an application of flagellar display technology. Such wounds are characterised by poor vasculature, a dearth of adhesive molecules – such as collagen IV, VII and laminin – and a surfeit of collagen I and degradative enzymes. The E. coli flagellar filament is comprised of a protein called flagellin (FliC) consisting of four domains denoted D0, D1, D2 and D3. Domains D0 and D1 are formed from two peptides each, one located at the N-terminus and the other at C-terminus of the FliC peptide, and form the core of the polymerised flagellin filament. The D2 and D3 domains face the exterior of the molecule, and can be removed without affecting polymerisation. We have produced a set of modular peptide presentation plasmids that enable replacement of varying lengths of the D2 and D3 domains with candidate bioglue molecules. These include collagen and laminin binding proteins from bacterial and human origin. All fusion proteins effectively polymerise and can be produced and purified from E. coli. In 2D models, these “bioglues” effectively bind collagen I and laminin and furthermore promote attachment of keratinocytes to surfaces. Several E. coli strains have been engineered for their ability to allow optimal production of a flagellin fusion protein under the control of an artificial promoter. Optimum production parameters for an apparatus that requires growth under aerobic, low-shear conditions are also defined.

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The forward engineering of biological systems from the ground up has long been a goal of Synthetic Biology. While the number of these parts has been rapidly increasing, the quality associated with these parts has not kept pace. Large numbers of parts characterised using high quality, standardised methods are required to fulfil this objective and allow the rapid advancement of developments within the field. To enable the rapid characterisation of BioParts a standard workflow designed to characterise promoters on an automated platform has been developed. The automated assay is separated into stages of subculturing, growth and measurement to improve data quality and ensure the accuracy of characterisation results. To characterise the BioParts, dynamic output data is collected from bacterial populations by a microplate reader and more sensitive single cell data is collected using automated flow cytometry and presented in relative (RPU) or absolute (GFP molecules per cell) unit formats. The workflow has been used to characterise both constitutive and inducible promoters; a subset of constitutive promoters has been tested under varying conditions to observe how these extra-cellular contexts would alter part functionality within the host and a few inducible promoters have been fully characterised to demonstrate the high detail output of the system. The developed workflow allows the rapid production of highly accurate part characterisation data which will be of particular use to system designers attempting to predict the outcome of their designs. While primarily designed for promoters, the workflow should be scalable to any expression based BioParts and enable the probing of how context factors alter the functional behaviour of those parts.

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Chitosan is one of the most versatile functional biopolymers, and it is commercially derived from the renewable resource chitin, one of the most abundant biopolymers on earth. It already has been shown that the degree of polymerization (DP) and the degree of acetylation (DA) are parameters influencing the physico-chemical properties and biological activities, but there is still a lack of detailed understanding of structure/function relationships of partially acetylated chitosans at the molecular level. We have hypothesized that for the biological activities also the pattern of acetylation (PA) plays a crucial role, especially in a target tissue after possessing by a sequence-specific chitosan hydrolase. As commercially available chitosans are produced chemically from fully acetylated chitin, they invariably carry random PA, while enzymes have the potential to create non-random patterns. The role of PA has not yet been studied, mostly due to a lack of analytical methods and to the non-availability of chitosans with non-random PA. We here describe how chitin and chitosan modifying enzymes, such as chitin deacetylases and chitosan hydrolases, can be used for analysis and synthesis of chitosans with non-random PA. These enzymes are often arranged in a modular fashion, like glycoside hydrolase or carbohydrate esterase modules as the catalytic domain either without or in combination with one or more different carbohydrate-binding modules. We want to investigate how these modules influence the enzymes’ properties and mode of action towards possible substrates. Moreover, a combination of various modules, generating chimeric enzymes could alter, e.g. the substrate specificity, processivity, and the resulting product. By using bio-engineered enzymes with novel qualities, the production of designer chitosans with known structures and defined functions becomes feasible, as a prerequisite for the development of reliable chitosan-based products, e.g. for plant disease protection or scar-free wound healing.

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One of the major applications of synthetic biology is the engineering of biological systems into useful organismic platforms. A fundamental requirement is the ability to manipulate genomes and functional genetics for applications such as designer in vivo circuits, gene-based therapeutics, or transgenic disease models. Programmable sequence-specific endonucleases that facilitate precise editing or regulation of the genome are now enabling systematic interrogation of cellular function from molecules to behavior. The CRISPR (clustered regularly interspaced short palindromic repeats) system is a form of microbial adaptive immunity used to defend against invading phages or plasmids. We and others recently engineered the RNA-guided Cas9 nuclease from the type II CRISPR locus of Streptococcus pyogenes for genome editing in mammalian cells. The ability to program the cleavage specificity of Cas9 using a guide RNA provides a significant design and accessibility advantage over existing genome engineering technologies such as TALENs and zinc finger nucleases, which require involved molecular cloning or protein engineering. Although this unique RNA-programmable nuclease system has enormous potential for advancing genome engineering, the cleavage activity and target recognition fidelity of CRISPR/Cas have yet to be well characterized. We systematically generated a set of chimeric guide RNA truncations and identified an optimal architecture for maximal cleavage activity, achieving up to 50% target modification of 2 different loci. We then used next-generation sequencing to study the ability of single mutations and multiple combinations of mismatches within 15 different Cas9 guide RNAs to mediate target locus modification within the endogenous human EMX1 gene. Based on our analysis of permissive guide RNA mutations that exhibit on-target activity, we propose a set of guide RNA design rules and design a computational algorithm for predicting Cas9 off-target sites throughout the genome.

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The integration of microfluidics and synthetic biology has the potential to produce rapid prototyping platforms for characterization of genetic devices, testing of drug candidates, and development of biosensors. Microfluidics and synthetic biology may be combined to increase the complexity of genetic circuits. Due to the size and complexity of some genetic circuits, a Compuer Aided Design (CAD) framework will be needed to map the circuits to a microfluidic chip. We describe here the CAD framework Fluigi for optimizing the layout of genetic circuits on a microfluidic chip, generating the control sequence of the valves on the microfluidic chip, and simulating the behavior of the chip and the circuits it contains. Fluigi will provide the following features: logic minimization, technology mapping, place and route, valve control plan generation, and chip-level simulation. The user will input a series of boolean logic expressions, where each expression has some number of inputs and generates one output from those inputs, which will be then be converted to a minimal form to eliminate redundant logic. The minimal expressions will be converted to a tree of logic gates, where each gate is an available genetic circuit defined by the user, and will then be mapped to the chambers on the microfluidic chip within a given set of constraints. The sequence of valve controls will be generated from this mapping. Finally, Fluigi will run the sequence of valve controls and simulate the behavior of the chip. Fluigi and the functions it provides represent an important step towards the integration of synthetic biology and microfluidic platforms.

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The functional promoter library regulated by the TetR repressor was demonstrated with the reporter EYFP (enhanced yellow fluorescent protein) gene, for the first time, in the unicellular cyanobacterium Synechocystis sp. strain ATCC27184 (i.e. glucose-tolerant Synechocystis sp. strain PCC 6803). Some promoters in the library show appreciably wide dynamic range of transcription regulation; about 200-fold gene induction in 24 or 48 hours depending on the growth condition. The key strategy of promoter engineering is to alter the transcription initiation by systematic changes of few nucleotides in the region between the -10 element and the transcription start site. This region coincides with the “discriminator” region in the case of rRNA or tRNA promoter of Escherichia coli, which has been shown its effective role in affecting transcription initiation [1]. Thanks to the versatile properties of well-developed TetR repressor regulation system [2], the present promoter library can contribute to implement novel functionalities in the chassis [3] derived from this photosynthetic microorganism via layering new genetic circuits [4] in the framework of synthetic biology. REFERENCES 1. Haugen SP, Berkmen MB, Ross W, Gaal T, Ward C, Gourse RL: rRNA promoter regulation by nonoptimal binding of sigma region 1.2: an additional recognition element for RNA polymerase. Cell 2006, 125:1069-1082. 2. Bertram R, Hillen W: The application of Tet repressor in prokaryotic gene regulation and expression. Microb Biotechnol 2008, 1:2-16. 3. Pinto F, van Elburg KA, Pacheco CC, Lopo M, Noirel J, Montagud A, Urchueguia JF, Wright PC, Tamagnini P: Construction of a chassis for hydrogen production: physiological and molecular characterization of a Synechocystis sp. PCC 6803 mutant lacking a functional bidirectional hydrogenase. Microbiology 2012, 158:448-464. 4. Moon TS, Lou C, Tamsir A, Stanton BC, Voigt CA: Genetic programs constructed from layered logic gates in single cells. Nature 2012.

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Direct amide formation between carboxylic acid and amine under physiological condition helps to build multiple-function protein assembly with native activities. However, the formation of peptide bond (amide) through condensation of carboxylic acid and amine requires high temperature and pressure. At physiological condition the condensation may occur in the absence of toxic catalyst; however, extremely low yield is expected. We plan to fish out few successful products out of large excess of reactants using single-molecule sensing and catching platform. A protein transistor made of single antibody binding two gold nanoparticles was fabricated. The electrical conductance across antibody monitors the structure dynamics and also the physical states of antibody in real-time. Pepsin treatment cleaved off the Fc domain of antibody leaving two Fab’ fragments connected to each other. The binding of pepsin and the cleavage of Fc domain was visualized by the increase and decrease of electrical conductance. When Fc fragment was delivered using microfluidic channel to Fab’s, an increase of conductance was observed and stably maintained. It was assumed that the Fab’ fragments were capable of catching and ligating Fc fragment at physiological condition. The reconstructed antibody exhibited similar electric characteristics compared to intact antobody. Negative differential resistance (NDR) was observed with intact antibody. NDR disappeared when Fc domain was cleaved. However, when Fc domain was ligated back to Fab’s, NDR appeared, indicating the structural integrity was recovered. Several enzymes were successfully ligated to the Fab’s, including DNA polymerase I, phi 29 DNA polymerase, glucose oxidase, horse relish peroxidase, beta-galactosidase, and T4 DNA polymerase. In particular, these conjugated enzymes showed comparable native activity. Although the yield of carboxylic acid/amine condensation is extremely low at physiological condition, we were able to fish out spontaneous formation of peptide bond using the ultra-sensitive single-molecule detecting system.

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As the engineerable properties of biomolecules and the synthetic networks created from them are elucidated, the augmentation of natural functionalities will become increasingly important to create ever complex and increasingly abiotic enzymes and pathways. One such instantiation is to introduce synthetic building blocks (nucleotides, amino acids) into biomolecules to augment or completely redefine their function and interactions with other biomolecules. The programmable nature of nucleic acids, with their defined interactions between complementary nucleobases has made them an attractive medium for the creation of biologically-inspired materials such as DNA hydrogels, DNA origami nanostructures, etc…. Unlike nucleic acids, protein-protein interactions are not based on a straightforward and thus readily engineerable interaction rule set. Instead interacting proteins have evolved idiosyncratically to interact with one another based on the ‘drunken-walk’ of natural selection. The ability to control the interaction and localization of protein-protein interactions in a predictable manner, especially proteins introduced from exogenous sources, could help to improve flux through synthetic metabolic pathways, enable the formation of novel protein chimeras as well as enable the directed evolution of interacting protein pairs. However, to date progress in this vein has been tepid. Herein we present our progress towards the genetic incorporation of nucleobase functionalized amino acids into proteins. These novel, synthetic amino acids contain the standard L-amino acid backbone with sidechains that include the nucleobase functionalities from nucleic acids. When placed in the proper structural context within a protein sequence, these amino acids should allow for programmable interactions between proteins similar to the strands of a DNA molecule. To facilitate the genetic incorporation of nucleobase amino acids, we have developed novel orthogonal aminoacyl tRNA synthetase/tRNA pairs as scaffolds for the directed evolution of amino acid specificity. Additionally, we report on the augmentation of these orthogonal pairs for incorporation of nucleobase and other unnatural amino acids.

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Cell-to-cell communication has incorporated multicellularity into the existing genetic circuitry, broadening its spectrum of application. It has been successfully applied to both microbial and mammalian systems and achieved complex cellular behaviors such as multicellular computing, synthetic ecosystems, biosensors, and pattern formations. Cell-to-cell communication among engineered cells has so far been based on the quorum sensing inspired system where communication is mediated by signaling molecules secreted by sender cells into the environment and subsequently received by receiver cells. However, the intrinsic properties of this system such as limited types of signaling molecules or confinement of communication in a population level may hinder further utilization for a number of applications. Here we have demonstrated a unique one-to-one communication between individual mammalian cells connected via tunneling nanotubes (TNT)-like structures. A sender cell constructs a membranous tube and connects itself with a receiver cell. Through this conduit, cellular components such as ions, macromolecules, nucleotides, proteins, vesicles, or even organelles, are transported and are capable of acting as signals. As a first step, we have built genetic circuits that modularly control the construction of TNT-like structures and relay signals among cells in vitro. Additionally, carried by Herpes simplex viral capsids, the large genetic circuits themselves are transported from sender cells to receiver cells. This new way of communication will be a critical addition to the existing tool box for creating gene networks that encode artificial developmental programs in mammalian cells and that coordinate the action of cell-level morphogenetic processes in space and time. Moreover, this system can be implemented to develop cancer therapeutic agents with enhanced dissemination rates within the tumor microenvironment.

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Terpenoids make up the largest class of natural organic compounds and include medically and commercially important members such as artemisinin and isoprene, respectively. As such, the terpenoid pathway has been the subject of much investigation for improving efficiency and increasing yields. Refactoring is a recently applied technique with potential for further enhancing metabolic engineering approaches through optimization of the gene cluster and its regulation. This refactoring approach is being applied to the terpenoid pathway and its precursor MEP pathway to optimize beta-carotene production in E. coli. The refactored operon is regulated by novel transcriptional machinery composed of a modified T7 RNAP and zinc finger array (ZFA) transcription factors. Development of this system will allow for the induction of transcription at any location definable by zinc finger arrays, essentially creating a promoter at this location. In addition, the possibility of regulating protein-protein interactions between the modified T7 and the ZFAs, can allow for a highly flexible system for inducing and tuning transcription. Preliminary experimental results will be presented.

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Generation and detection of pulses by genetic circuits is important for the control of natural biological systems. While synthetic biological systems have incorporated pulse-generating circuits, pulse-detecting circuits have not yet been built. Here, we use components of the lambda phage repressor system to build a pulse-detecting genetic circuit in E. coli. Lambda cI protein dimers bind cooperatively to activate transcription from the PRM promoter. Mutations in cI that abolish DNA binding will be dominant-negative (cIDN); mutant protein heterodimerizes with wild-type protein diminishing its ability to bind DNA. We constructed a circuit that consists of a gene that expresses both cIDN – tagged with a degradation tag – and cI in response to tetracycline. A reporter construct that expresses a reporter such as lacZ, YFP, or luciferase under control of the PRM promoter generates a detectable output. Initially, in the absence of inducer, the reporter will not be expressed. In the continued presence of inducer the reporter will not be expressed due to the presence of cIDN. However, once inducer is removed, cIDN is rapidly degraded, cI forms active homodimers, and activates transcription of the reporter. Thus, this circuit responds to a pulse of inducer rather than sustained induction. The pulse-detecting genetic circuit presented here represents a novel architecture that can produce a non-monotonic input for downstream genes. This will allow the construction of more complex genetic circuits with more complicated dynamics.

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Assembling larger biological systems from primitive Parts is a key design paradigm in synthetic biology. While DNA synthesis technology continues to improve, piecewise assembly will remain crucial for rapid combinatorial assembly of biological Devices. This approach can develop and expand only as quickly as DNA assembly systems allow. Most efficient assembly systems currently either require one-off planning and oligo synthesis or depend upon slower assembly methods but allow more modularity. Utilizing a variation of modular cloning (MoClo, Weber et al., 2011) and a growing library of interchangeable DNA Parts, we have a developed a multiplex modular cloning (MMC) methodology which rapidly increases the efficiency of characterization efforts and construction of related Devices. Standard MoClo assembly allows for the rapid assembly of up to six DNA Parts in a single digestion-ligation reaction by utilizing restriction type IIS enzymes. By adjusting the reaction conditions, Multiplex Modular Cloning provides the ability to construct multiple Devices by adding a library of any one Part type rather than single Parts with only a modest decrease in ligation efficiency. Additionally, MMC can be designed as a high throughput assembly and screening system where in a variety of design candidates are assembled and functionally screened for activity by transforming into cells along with a reporter cassette such that only cells in which the variable construct functions correctly produces antibiotic resistance or a visible reporter. Further efforts are underway to integrate this assembly and screening methodology with a combination of liquid handling robotics and flow cytometry. This variation of assembly methodology and integration with computational design and analysis tools will rapidly increase the rate at which related devices can be synthesized and characterized.

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Metabolic engineering of microorganisms has been traditionally relied on rational approach based on detailed knowledge of the producing host and the target pathway. However, combinatorial approach also has been proving its ability in metabolic engineering by utilizing nature’s genuine mechanism, diversification and selection. Current limitations of rational and combinatorial approach are fine and predictive expression of pathway enzymes and screening of superior and optimized variant out of vast library, respectively. Here, we present an integrated synthetic biology approach which settled the problems of rational and combinatorial approach to produce L-tryptophan from Escherichia coli. First, we removed known bottlenecks on L-tryptophan synthesis pathway by using a predictive model of protein expression level, UTR Designer, which can precisely predict expression level of enzyme based on folding energy of specific features in mRNA secondary structure. UTR sequences of bottleneck enzymes were re-designed to maximize the metabolic flux through the pathway. Then we optimized the producing strain by utilizing a riboswitch-based screening tool, riboselector, which modulates expression level of selective marker gene in response to the target molecule. Riboselector for L-tryptophan was able to enrich superior variants out of vast library which were constructed from rationally engineered strain. We claim here that remarkable producing strains could be obtained through integrated synthetic biology approach by resolving pre-existing problems of metabolic engineering.

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Our capacity to read and write DNA has outpaced our ability to design useful and predictable DNA sequences. Synthesizing genomes could enable powerful new approaches to biological discovery, however, due to the overwhelming complexity of biological systems, most designs have largely recapitulated natural sequences. To advance synthetic genome design methods we focused on the 5.4 kb X174 bacteriophage genome because it is: (1) small enough to enable rapid prototyping of new designs, and (2) complex, displaying an intricate architecture encoding 11 overlapped genes spanning all reading frames. Two approaches were used to reduce the complexity of the X174 genome while addressing important biological questions. Gene overlaps are common in nearly every genome and their functional significance is controversial. We investigated the origin of gene overlaps by designing a fully decompressed synthetic genome ‘X174.1f’, that contained no overlapping genetic elements. We describe our genome design, construction, and successful redeployment. Phenotypic comparisons between wild type and X174.1f showed there were minimal observable differences between the two viruses, and no essential information in the gene overlaps. Additionally, the results suggest that gene decompression is a viable approach to reducing genome complexity. Secondly, we developed a method of genome simplification called ‘negative genomics’ that seeks to address a fundamental question of genome annotation: at what point can we confidently say we have found all the genes? To establish all potential open reading frames (ORFs), other than the 11 known genes, we searched the X174 genome using computational gene-finding tools. Finding 85 candidate cryptic ORFs we designed a new genome, called ‘X_clean’, with 88% of these cryptic ORFs erased via synonymous changes. Testing the prototype X_clean genome revealed that it is capable of forming plaques but is phenotypically different from wild type, suggesting previously undiscovered functions associated with the disrupted ORFs.

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Esterases catalyse a wide variety of reactions of major industrial interest including the preparation of enantiopure fine chemicals and pharmaceuticals, biopolymer generation and biodiesel production [1][2]. They are also important components of washing detergent formulations constituting a major industrial market for enzymes. Therefore esterase parts which can be used in biotechnology and synthetic biology applications are needed. Molecular scaffolds have previously been used to improve the product titer of multienzyme pathways through co-localisation of sequential enzymes with control of enzyme stoichiometry and spatial organization [3]. By arranging enzymes involved in cleaning catalysis in such a manner, we hope to initially increase the overall efficiency of this reaction as well as stabilizing the enzymes. [1] Bornscheuer UT. FEMS Microbiol Rev. 2002. [2] Panda T, Gowrishankar BS. Appl Microbiol Biotechnol. 2005. [3] Lee H, Deloache WC, Dueber, JE. Metab Eng. 2012

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Due to the extraordinary strength of its non-covalent bond to biotin (KD < 10-13 M) streptavidin can be used as a handy and flexible tool in synthetic biology including the use as a protein scaffold for the creation of artificial metalloenzymes that are able to perform bio-orthogonal reactions including transfer hydrogenation, allylic alkylation or enantioselective sulfoxidation. In this approach an organometallic catalyst is coupled to a biotin moiety to enable the supramolecular anchoring of the catalytic unit into the protein scaffold of the biotin binding pocket of streptavidin in order to combine the features of homogenous catalysis with the beneficial characteristics of enzymes[1]. The resulting complex can exhibit superior catalytic features compared to the free low-molecular catalyst itself. These features potentially include enhanced stereoselectivity, access to aqueous media and ambient conditions, catalytic rate acceleration, higher turnover numbers, catalyst recovery and protection from degradation and so forth. Additionally to chemical tailoring of the biotinylated catalysts an optimization of the protein scaffold can be achieved by the means of protein engineering. This has been shown for several reactions and led to a significant improvement of the catalytic performance[2]. Currently we are working on the development of a fluorescence based assay for artificial metalloenzymes that will allow for the efficient screening of beneficial mutants in a high-throughput manner. We hope that this will lead to the development of a broad range of artificial metalloenzymes and generate a bio-orthogonal tool box that could be employed in chemical biology as well as synthetic biology. [1] Ward TR. Acc Chem Res. 2011. 44(1):47-57. [2] Dürrenberger et al. Angew Chem Int Ed Engl. 2011. 50(13):3026-9.

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Horizontal gene transfer (HGT) is known to play a fundamental role in the evolution of microorganisms. HGT likely plays a large role in shaping microbial communities, including those that make up the human microbiome, which has great influence on health and disease. While a great deal of research has been done on the transfer of genes, little research has been done on the transfer of regulatory elements and how they function after acquisition. Here we develop a system for high-throughput measurement of promoter activities after laboratory transformation. A large library (>50,000) of chip-synthesized promoters with barcodes were cloned into species-specific vectors upstream of GFP. The library consists of regulatory sequences from known horizontally transferred genes as well as a comprehensive set selected to cover various COGs, antibiotic resistance genes, virulence factors, and phylogenetic groups. The forced horizontal transfer of the promoter library through transformation into diverse microbial species allows for multiplexed measurement of transcription levels under various growth conditions by RNA-seq. Cells can also be sequenced after FACS to measure translation levels. This approach will allow us to determine how phylogeny, ecology, and other factors affect fate of horizontally transferred regulatory elements. It may also shed light on microbial acquisition of antibiotic resistance and pathogenicity. Additionally, the results also provide us with a large set of promoters characterized in multiple species that should prove useful for synthetic biologists aiming to engineer diverse species and synthetic ecosystems.

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Jean Cocteau said “Art is science made clear”. To test the hypothesis that artworks can help clarify and contextualize advances in Synbio, we explored the viewer’s understanding of it before and after the work was presented. Specific case studies include ‘Stranger Visions’ by Heather Dewey-Hagborg for adults and bacterial painting for children. ‘Stranger Visions’ utilized current technologies to analyze DNA extracted from samples such as hairs, cigarette butts, and discarded chewing gum found in public places. Trait analysis allowed the artist to construct a portrait sculpture of an individual she had never met. Although 100% accuracy is not achievable at the present time, the work points towards the day when it will become more feasible, and challenges the viewer to ask themselves what that will mean to their sense of self, personal boundaries, privacy, etc. Individuals experiencing ‘Stranger Visions’ through exhibition or through two separate documentaries produced about the work will be surveyed to assess their understanding of the power and scope of the technology and their attitude towards it before and after the work was viewed.

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Genome engineering is a fast-expanding branch of synthetic biology, at the cutting-edge of current research. The synthetic yeast project (Sc2.0) is one of the most significant and pioneering examples of genome engineering, with a global consortium aiming to completely synthesise a human-designed version of the Saccharomyces cerevisiae yeast genome by 2017. Within the Sc2.0 consortium, Imperial College London is constructing the synthetic chromosome XI (0.67 Mbp). We have collaborated with Johns Hopkins University on the design and assembly strategy for SynChrXI and present our progress on the first 100 kbp. As well as building a synthetic chromosome, we are also investigating it’s suitability as a host for diverse genetic pathways and circuits and plan the construction of an artificial sub-telomere region to aid in the evolution of new phenotypes.

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Signaling processes are at the heart of cellular responses to environmental cues. Thanks to a precisely controlled exchange of signals between nucleic acids, proteins, organelles and cells, many mechanisms of living cells are perfectly regulated, like the metabolic machinery, cell growth, differentiation, death and the survival in a dynamic environment. Thus, deregulations of signaling pathways result in emergence of diseases like cancer, immunological disorders or metabolic diseases. Most of cell-signaling events are composed into three parts: first there is (i) the reception of an external signal, then (ii) the recruitment of proteins at the plasma membrane in order to allow transduction of the signal and finally (iii) the nuclear translocation of transcription factors. In this work, we designed synthetics modules based on optogenetics to understand cell-signaling processes. Light is an ideal tool to gain spatiotemporal control of biological processes. We used genetically engineered phytochromes, which are plant photoreceptors that naturally convert the information contained in light into biological signal. This family of chromoproteins is particularly attractive for biological applications because these proteins sense and respond to changes in the red-light (660 nm) and far-red-light (740 nm) that are well tolerated by biological systems and that have good tissue penetrance. Phytochrome B (phyB) from Arabidopsis thaliana is one of the best characterized members of this family and is known to interact with its Phytochrome Interacting Factor 3 (PIF3). Based on these two proteins, we designed different systems that control signaling events into mammalian cells with red/far-red-light activation. These cell-signaling events can be controlled in each step of the process at high spatial and temporal resolution.

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The possibility to trap small signaling molecules in cages and to subsequently uncage them in a controlled manner at the site of interest allows for the spatiotemporal manipulation of signaling processes. Caging has successfully been applied to a vast array of small signaling molecules, leading to a revolutionized understanding of the biological processes controlled by these molecules. As many cellular processes rely on proteins rather than on small signaling molecules, the ability to cage proteins in a similar manner is highly desirable. Techniques potentially applicable to the caging of proteins have been reported; however, these are complicated and must be tailored for each specific protein of interest. A method enabling the caging of arbitrary proteins is thus much needed. Here, we demonstrate a general procedure utilizing a pharmacological-based cage to trap one or several proteins of choice equipped with an immunoglobulin (IgG) Fc-tag. In addition, to further address the high demand of time-resolved control of protein-governed processes, a “protein switch” enabling the protein activity to be switched on and off by the addition of small molecules was developed. The potential of the caging technique and the protein switch to manipulate growth factor-controlled signaling pathways was demonstrated by stimulating time-resolved migration of mesenchymal progenitor cell and human umbilical vein endothelial cells, respectively. The concepts presented here are believed to be valuable for fundamental and applied research ranging from elucidating signaling pathways to the targeted differentiation of cells in tissue engineering.

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In the 21st Century molecular hydrogen (H2) has become an essential industrial commodity. It is widely heralded as an exciting alternative to petroleum-based transportation fuels and also plays indispensable roles in many other important industrial processes, including hydrogenation of fats and oils, methanol production, and ammonia production – an essential component of agricultural fertilizers. Biohydrogen (Bio-H2) is molecular hydrogen produced by microorganisms and is an exciting prospect as a fully renewable, commercially-viable second-generation biofuel. Bio-H2 can be produced at ambient temperatures by metal-dependent hydrogenase enzymes, with potentially no CO or H2S contamination, and is a carbon neutral/positive process. Escherichia coli naturally produces Bio-H2 during mixed-acid fermentation via its own endogenous nickel-dependent hydrogenase enzymes. The main aim of this project is to enhance Bio-H2 production by E. coli and to achieve this synthetic hydrogenases have been designed, constructed and expressed. The structure and activity of the synthetic hydrogenase has been characterised in vitro using a number of techniques including autoradiography, spectroscopy, SEC-MALLS, protein-film voltammetry and H2 production assays. Metabolic engineering of various E. coli strains and directed protein evolution has been carried out to integrate this synthetic hydrogenase activity into cell metabolism and the resulting strains were characterised using metabolomics and standard microbiological approaches. Finally, a number of alternative synthetic biology approaches to increase H2 production E. coli are currently being investigated, including the construction and expression of unusal enzyme chimeras.

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Variation of synonymous codons within a gene can strongly affect protein expression levels. Therefore, understanding which codons are optimal for a particular gene is of great importance for synthetic biology, for interpreting patterns of evolutionary conservation and for understanding gene regulation. Previous methods of codon optimization have focused on mimicking global patterns such as the average frequencies of codon usage across the genome, but with limited success. At present, we still lack a detailed understanding of which codons are optimal at varying positions within a gene. Here we present a new method for systematically making single-codon variants of an essential gene in E. coli, and measuring the resulting change in growth rates. Mutant libraries were constructed using Multiplex Automated Genome Engineering (MAGE) transformations. Mutants were pooled together in a competition assay, and the change in frequency of all mutants over time was measured using next-generation sequencing. We systematically measured growth rates of more than 4500 single-codon variants across the entire length of a gene that is essential for initiating translation, infA (IF1). We found that many single-codon synonymous changes have a significant negative effect on growth rate. I will present our analysis of this dataset, describing patterns of global and position-specific codon bias at the level of an individual gene.

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Social representations of “life” in discourses about synthetic biology and genetic engineering

The debate about definitions of life and its value is very diverse. There are philosophical, biological and even literary definitions of life. Biological concepts of life include a number of necessary traits of organisms that make them living entities. Modern techno-sciences like genetic engineering, stem-cell research and synthetic biology bring new challenges for the expert discourse on life. What is the status of the new life created in synthetic biology laboratories? Are there different levels of life? Shall we standardize/modularize/patent life? However, these are issues in philosophical and biological discourses. What about the public? How are the definition and the value of life treated in everyday discourse and everyday knowledge? The present study investigates into social representations of “life” in discourses about synthetic biology. Focus groups and qualitative interviews were held to shed a light on the role of the term “Life” in laypeople’s understanding and in the context of synthetic biology.

Results show that laypeople understand life in terms of “motion” and intrinsic change, as concepts from naïve biology, combined with the abovementioned lists of traits from later socialisation at school or university. Furthermore vitalist, and within the frame of the “natural”, essentialist views of life can be encountered.

As regards the context of synthetic biology, one can identify an anthropocentric shift within the discussions. Although the stimulus material and the interviewer predominantly spoke about microorganisms the participants of the study often projected the frames of discussion on human beings. Being aware of this thematic gap will help to clarify misunderstandings in the dialogue between scientists in synthetic biology and the public.

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At earlier stages in the evolution of the universal genetic code, fewer than 20 amino acids were considered to be used. Although this notion is supported by a wide range of data, the actual existence and function of the genetic codes with a limited set of canonical amino acids have not been addressed experimentally, in contrast to the successful development of the expanded codes. Recently, we constructed artificial genetic codes involving a reduced alphabet [1]. In one of the codes, a tRNA(Ala) variant with the Trp anticodon reassigns alanine to an unassigned UGG codon in the Escherichia coli S30 cell-free translation system lacking tryptophan. We confirmed that the efficiency and accuracy of protein synthesis by this Trp-lacking code were comparable to those by the universal genetic code, by an amino acid composition analysis, GFP fluorescence measurements and the crystal structure determination. We also showed that another code, in which UGU/UGC codons are assigned to Ser, synthesizes an active enzyme. This method will provide not only new insights into primordial genetic codes, but also an essential protein engineering tool for the assessment of the early stages of protein evolution and for the improvement of pharmaceuticals. In this presentation, we will show the generality of our method for the simplification, by constructing other types of further simplified codes including a 16-amino-acid code.

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Due to the inherently noisy environment of the cell, it is often advantageous for synthetic biology applications to use engineered genetic circuits that follow pathways with predictable logic, and whose outputs are quasi-digital “high” or “low” values. By using modular components, these devices can be combined with increasing complexity to broaden the number of functions and tasks accessible within biological systems. We describe here the design, construction, and characterization of a simple genetic half adder – one of the building blocks of arithmetic logic circuits – comprising two plasmids transformed into E. coli. Isopropyl -D-1-thiogalactopyranoside (IPTG) and doxycycline (DOX), act as input signals eliciting specific responses from the cell. Each of the input molecules is independently sensed by the first plasmid expressing enhanced green fluorescence protein as an output signal; the first plasmid behaves as an OR gate. The simultaneous presence of both input molecules is sensed by the second plasmid, responding in two ways: 1) td-Tomato is expressed as an output signal; the second plasmid behaves as an AND gate, 2) the cI lambda repressor is expressed, inhibiting the expression of the output signal for both inputs of the OR gate; the second plasmid also converts the OR gate into an XOR gate. The combination of these Boolean logic gates thus results in a half adder with robust, quasi-digital responses. Since half adders can be combined to form full adders and other more complex arithmetic circuits, the realization of this modular genetic element will hopefully expand the potential for increased control over more complex, engineered genetic networks.

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Saccharomyces cerevisiae is one of the most widely used cell factory in industrial biotechnology and it is used for the production of fuels, chemicals, food ingredients, food and beverages, and pharmaceuticals. Such bioprocesses frequently require multiple rounds of metabolic engineering to obtain the production strain with the proper phenotype and product yield. However, the sequential number of metabolic engineering is time-consuming. Furthermore, the number of available selectable markers is also limiting the number of genetic modifications. To overcome these limitations, we have developed a new set of shuttle vectors for convenience of use for high-throughput cloning and selectable marker recycling. The new USER-based cloning vectors consist of a unique USER site and a CRE-loxP-mediated marker recycling system. The USER site allows insertion of genes of interest along with a bidirectional promoter of choice into the vector backbone with time- and cost-effective. The selectable marker cassette is flanked by loxP recognition sites for the CreA recombinase to allow reutilization of the same selectable marker. Furthermore, our USER vector set provides a choice of different selectable markers both auxotrophic and dominant markers for convenience of use. Our vector set also contains both integrating and multicopy vectors for stability of protein expression and high expression level. We will make the new vector system available to the yeast community and provide a comprehensive protocol for cloning in these vectors using USER cloning strategy.

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In biological organisms, efficient processing of the temporal sequence of inputs represents an important task for development and survival. Over the last decade, engineering approaches in synthetic biology community demonstrated several logic gates and complex circuits in biological organisms. Recently, a recombinase-based cascade of memory units was successfully utilized for synthetic circuits that respond to a sequence of inducer inputs, indicating its potential for general implementation of temporal logic in cells.
Synthetic biology approaches in cell-free expression system offers an attractive alternative to cellular engineering for rapid prototyping and engineering of controller for production of natural and unnatural, even cytotoxic products. Here, we focus on the construction and characterization of an event detector in a cell-free expression system. The design of an event detector utilizes a previously characterized synthetic transcriptional memory module that responds to two distinct DNA inputs, ‘A’ and ‘B’, resulting in two stable steady-states depending on which input becomes available first. Utilizing modular and programmable switch motifs, it is straightforward to implement an event detector that distinguishes the temporal sequence of inputs.
The functionality of event detector is first demonstrated in a cell-free transcription system. When the event detector is configured to recognize ‘input A then input B’ case, the output signal, an RNA aptamer for fluorescent dye, is produced only upon the introduction of input ‘A’ followed by the input ‘B’, whereas no output signal is detected upon the introduction of any single input or the two inputs in reverse order. To further develop the general applicability of such circuits, we also tested the event detector in a cell-free transcription/translation system (PURExpressTM), where the transcription switch modules support efficient translational control of target proteins by generating programmable antisense signals. Together, the modular transcriptional circuit architecture in cell-free expression system offers a powerful platform for temporal logic control.

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We developed a highly scalable ‘shotgun’ DNA synthesis technology by utilizing microchip oligonucleotides, shotgun assembly and next-generation sequencing technology. A pool of microchip oligonucleotides targeting a penicillin biosynthetic gene cluster were assembled into numerous random fragments, and tagged with 20 bp degenerate barcode primer pairs. An optimal set of error-free fragments were identified by high-throughput DNA sequencing, selectively amplified using the barcode sequences, and successfully assembled into the target gene cluster.

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The development of synthetic biology enables genetically modified microbes to produce useful biochemicals especially for the cost-effective and sustainable green chemistry. Currently one of the essential tasks of the cell factory research is to optimize the bioprocess of the target chemicals for maximizing the production efficiency. To this end, we have applied the G-network which is a type of queuing networks that have had a broad range of applications ranging from the evaluation of production efficiency in a factory to the performance analysis of computer systems and network routing. Although molecule based modeling is limited by the nature the queuing system (e.g. merging and spiriting of a molecule), we show that a latent molecule containing the expression information of related chemical species successfully describes the chemical reaction processes by modeling the flows of the latent molecule. As an example, a genetic circuit consisting of two AND gates, one Input and one GFP output is modeled along with the single cell based GFP fluorescence level from a high-throughput flow cytometry technique. Thanks to the analytical steady-state solution of the G-networks, we can evaluate the circuit performance and its dynamics without time demanding computational simulations. Although the G-network approach still has limitations for describing a non-steady-state system such as oscillatory expressions, it will be beneficial for optimizing the complex cell factory involving tens of hundreds of molecules by detecting bottle necks in a target chemical production pathway.

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Medium-chain fatty acids (MCFA) and their corresponding -hydroxylated- and dicarboxylic acid derivatives represent important building blocks for the synthesis of a wide variety of industrial relevant products such as biopolymers, lubricants, and plasticizer. The production of MCFA using renewable resources and the de novo fatty acid biosynthesis cycle of the bacterium Escherichia coli offer a sustainable and economical promising alternative to the chemical synthesis of these molecules. In order to achieve this goal, we firstly cloned and expressed the MCFA specific thioesterase FatB2 from the seed of Cuphea hookeriana and the -ketoacyl-ACP-synthase mtKAS from the mitochondria of Arabidopsis thaliana in a -oxidation deficient (fadD) E. coli strain. Interestingly, after optimization of protein solubility, culture conditions, inductor concentrations, and the extraction and analysis methods, octanoic acid levels were only marginally increased in a strain co-expressing both enzymes. In contrast, a strain expressing FatB2 alone showed a 420-fold increase in detectable octanoic acid levels compared to the wildtype, indicating that the maintenance of two plasmids expressing mtKAS and FatB2 most likely increases the metabolic burden of the cell to a level that is detrimental for octanoic acid production. However, the octanoic acid overproducing strain now serves as a platform for our current engineering approaches including i) the production of -hydroxylated octanoic acid by the co-expression of a self-sufficient monooxygenase fusion protein, which has been recently constructed in our lab and demonstrated to exhibit the desired substrate specificity and ii) optimising carbon flux into the fatty acid biosynthesis by the overexpression of the host’s acetyl-CoA carboxylase (accABCD). In addition, we are currently trying to establish a yeast surface display approach, which would allow the screening of a random mutant library of FatB2 for the identification of variants with altered substrate specificity.

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Background: Molecular obesity, i.e. the tendency to generate more potent compounds by increasing their MW and lipophilicity, is one of the main reasons for problems in absorption, distribution, metabolism, excretion, toxicity (ADMET) and costly failures in drug development. Therefore, medicinal chemists nowadays increasingly use a range of physico-chemical parameters to select the most suitable chemical structures for lead optimisation. Based on their co-evolution with target proteins, natural products exhibit many favourable physicochemical, structural and shape properties, but often also suffer from the problem of molecular obesity. In this study, properties of compounds obtained by Synthetic Biology are compared to chemical screening collections on one side and natural products on the other. Experimental approach: Saccharomyces cerevisiae (baker’s yeast) was transformed with artificial chromosomes, containing genes of a number of metabolic pathways absent in yeast, as well as cDNA libraries from natural products producing sources. In addition, the yeast was engineered to express a functional assay which interacts with the chemicals produced from the YAC-encoded enzymes and confers the producing yeast a survival advantage. Chemicals produced by surviving yeasts were isolated and their structures and biological properties determined. Results: 75% of the molecules found were new, i.e. previously not described elsewhere. 20% of the compounds showed novel and very diverse scaffold structures. In terms of size, the described synthetic biology approach resulted in mainly fragment- to scaffold-sized molecules which retained excellent biological activity. Their structural and physico-chemical properties are in line with established rules of drug-likeness and exhibit very favourable shape complexity. Compounds obtained by Synthetic Biology therefore fit perfectly into the pharmaceutical industry drug discovery value chain and represent valuable, alternative and complementary sources for further lead optimisation.

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Chitosan, the linear heteropolysaccharide of glucosamine (GlcN) and N-acetylglucosamine (GlcNAc) residues, is the only naturally occuring polycationic polymer. As such, it has a number of highly attractive physico-chemical properties and, through interaction with the mostly anionic components of living cells, interesting biological activities, e.g., antimicrobial, plant strengthening, and immuno-modulatory activities. Chitosans are defined by their degree of polymerisation (DP), degree of acetylation (DA) and their pattern of acetylation (PA). We found a strong influence of DA and a less pronounced influence of DP on all biological activities. But even when using chitosans with well-defined DP and DA, the results of some bioassays tend to be variable, leading to the hypothesis that the PA has a crucial influence on their bioactivities. However, PA is not only difficult to determine, but also difficult to generate. In the ChitoBioEngineering project, we now combine different chitin synthases which produce chitin oligomers with a defined DP, with very specific chitin deacetylases which not only define the DA but also the PA of the chitosan oligomers generated. Combinations of these enzymes already give us a broad range of fully defined chitosan oligomers in vitro, but also enable us to establish biotechnological processes with different combinations of chitin synthase and chitin deacetylase modules in vivo to directly produce the desired, well-defined (DP, DA, PA) chitosan oligomers. Furthermore, we have not only established a chitosan oligomer sequencing procedure with highly specific exo-acting enzymes, but also managed to develop a fully synthetic biosensor for the detection of chitosan oligomers in vitro and in vivo. This biosensor is based on the idea of fluorescence indicator proteins, which generate a Frster resonance energy transfer signal in dependence on the concentration of the analyte. Thus, the biobricks are now available to build and evaluate cell factories to produce monoclonal oligochitosans.

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The ability to engineer synthetic transcriptional circuits holds enormous potential for applications from basic science and biotechnology to medical engineering. Spatiotemporal and quantitative bimodal control is necessary for the precise construction of artificial transcriptional circuits in vivo. Here, we describe the development of Light-Inducible Transcriptional Effectors (LITEs), a novel optogenetic tool capable of bimodally modulating gene expression from the endogenous mammalian genome. LITEs are a two-component system integrating the programmable TALE DNA-binding domain with the light-sensitive cryptochrome 2 protein and its interacting partner CIB1 from Arabidopsis thaliana. They can be engineered to mediate positive and negative regulation of endogenous mammalian gene expression in a reversible manner, with changes in mRNA levels occurring within minutes following optical illumination. We have applied this system in mammalian cell lines, primary neurons, and within the brain of awake, behaving mice in vivo. The LITE system offers bidirectional gene regulation and quantitative control of gene expression through adjustment of light intensity. In addition, it enables programming of biological processes with a high degree of spatiotemporal precision. Finally, LITEs are amenable to multiplexing with other optogenetic technologies through wavelength discrimination. Taken together, LITEs hold great promise for the construction of complex transcriptional circuits in vivo.

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Engineering synthetic consortia of microorganisms is a new frontier for synthetic biology. Assembling synthetic communities will enable parallelized engineering and opens up the door to applications such as a synthetic human microbiome. Understanding design principles of microbial interactions will help engineer community-based microbial factories where different production steps are distributed between different members of the community. To understand how communities develop, evolve and interact, a quantitative approach is needed to study how small numbers of microbes develop into full consortia. This necessitates a method for isolating controlled numbers of microbial cells in individual vessels, and tracking how these synthetic consortia develop over time. In addition, it must be sufficiently high throughput to enable large numbers of these trials to be analyzed. Here we present preliminary efforts in developing a droplet-based microfluidic system to encapsulate and study microbial populations. By precisely controlling cell numbers, genetic background, composition of the micro-environment and the population, we aim to measure microbial community assembly quantitatively and on a physiologically relevant scale.

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A key challenge in synthetic biology is the characterisation of genetic parts. The need of obtaining kinetic data (time-series) in order to achieve this is undoubtedly important. A dynamic model which is able to interpret such data is an asset to characterisation. The cornerstone to the design of higher order genetic parts is a simplistic transcriptional-translational genetic part, which exhibits a switching characteristic that is nonlinear in dynamics. We take a systems level approach using only input/output data to model and analyse this behaviour (rather than a network based approach which takes into account the intermediate reactions taking place). By taking inspiration from the Nonlinear AutoRegressive Moving Average model (NARMAX), a concise and compact model which exhibits accurate representation of real data is derived. Genetic parts exhibit noise and variability which results in stochasticity and heterogeneity respectively, causing shortcomings in typical model performance. We address this and propose an identification framework using the NARMAX model and Approximate Bayesian Computation–Sequential Monte Carlo (ABC-SMC) technique. ABC-SMC provides the posterior distribution of the model parameters thereby capturing the observed variation in genetic parts. A quorum-sensing genetic part from the “registry of parts” is used as a case study to demonstrate the derivation of a parsimonious model whose parameters are estimated as a posterior distribution. The identified model is computationally convenient to analyse for design purposes, which is an advantage of the modelling approach.

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The yeast Saccharomyces cerevisiae possesses characteristics that make it an attractive cell factory for production of biotechnology products. It is a robust industrial organism and is able to grow under a variety of industrial conditions including low pH, high temperature, and less stringent nutritional requirements compared to bacteria. In addition, S. cerevisiae is genetically tractable and well-characterized. Much information is available on S. cerevisiae, including a complete genome sequence, as well as characterization of its metabolic pathways and various ‘omics’ data. However, despite these resources, introduction of entire pathways into yeast is still relatively slow when compared to E. coli and it can take a significantly longer time to obtain industrially-usable strains. The goal of this project is, therefore, to develop a synthetic biology platform to facilitate the rapid introduction of entire pathways into yeast. This includes a library of parts, including constitutive and inducible promoters of various strengths, terminators and markers. A series of improved episomal plasmids for rapid pathway screening has also been developed. In addition, this platform includes a variety of integration vectors for single and multi-copy integration. These vectors contain different auxotrophic and dominant markers that allow a single-step introduction of entire pathways into both laboratory and industrial strains. In addition, novel marker recycling systems that facilitate excision of all the markers without additional transformation steps are presented.

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Essential genes represent the core of biological functions required for viability. Molecular understanding of essentiality as well as design of synthetic cellular systems includes the engineering of essential proteins. On the other hand they potentially make excellent selection systems as it is difficult to obtain false positives. An impediment to this effort is the lack of simple growth-based selection systems suitable for directed evolution approaches. As the genes are essential, producing knock-out strains is not possible and alternative strategies such as bleach out strains are tedious because they lead to situations where wild-type and variant genes co-exist and recombination confuses experimental outcomes. We established a simple strategy for genetic replacement of essential genes by a (library of) variant(s) during transformation1. A central element of the method is that the complementation vector carrying a copy of the wild-type form of the essential gene contains an I-SceI nuclease recognition site and can thus be rapidly and conditionally eliminated in the presence of an I-SceI nuclease-expressing helper plasmid. We applied the system to the engineering of the essential enzymes adenylate kinase (Adk), the essential chaperonin GroEL, and the glycerol-3-phosphate dehydrogenase GpsA in Escherichia coli to confirm its generality. We are currently expanding the system to explore the construction of selection strains for the design of novel orthogonal pyrrolysine aminoacyl-tRNA synthetase/tRNA (PylRS) pairs. By providing essential proteins with alternative, non-canonical amino acids, very powerful selection systems can be constructed and the selection system can be fortified against hitherto overlooked potential pitfalls of the screening process. This process will be coupled to efforts of developing pathways for the in vivo synthesis of the non-canonical amino acids to obtain an informationally expanded strain that is again autonomous in terms of amino acid synthesis.

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Anthropogenic compounds introduced into the biosphere by humans since the industrial revolution are often recalcitrant and persist in the environment. 1,2,3-trichloropropane (TCP) is such an anthropogenic compound which is produced in chemical industries as a solvent and also as a by-product during manufacture of epichlorohydrin. Due to improper disposal, this chemical spreads in the environment and retains over decades in ground water, causing a serious health threat. There is no single microorganism in nature capable of degrading TCP completely to the harmless compound. To address this problem, we assembled a synthetic biochemical pathway using a haloalkane dehalogenase (DhaA) and two associated enzymes, haloalcohol dehalogenase (HheC) and epoxide hydrolase (EchA), for complete conversion of TCP to glycerol (GLY)1. We used a wild type and two engineered variants of DhaA, one with improved activity2 and another with increased selectivity3. The synthetic pathway was introduced into Escherichia coli. Toxicity level of TCP and its intermediate to the E. coli was determined. Then the TCP degradation pathway was rationally engineered by tuning the parameters of individual enzyme. The optimal enzyme ratios for maximum GLY production and minimum toxicity of metabolites were predicted by a mathematical modelling. A number of E. coli strains were constructed based on these predictions and characterized for their potential to survive, degrade and utilize TCP as a source of carbon and energy for their growth. We achieved a good agreement between predicted and experimental data in the designed constructs in terms of enzyme ratios and their degradation profile. The results demonstrate the rational engineering of TCP biodegradation pathway in vivo by using protein and metabolic pathway engineering.
References 1. Bosma et al., Appl. Env. Microbiol. 68: 3582-3587, 2002 2. Pavlova et al., Nat. Chem. Biol. 5: 727-733, 2009
3. van Leeuwen et al., ChemBioChem. 13: 137-148, 2012

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The goal of this study is to develop a new biosensor platform technology for point-of-care testing, specifically designed for the detection of medically relevant protein biomarkers. The shift of focus from centralised laboratories to point-care testing has the potential to greatly improve patient care as well as to slash costs to healthcare providers and insurers. The study will address the question of whether recent technological advancements in the field of synthetic biology can be utilised for the development of a reliable and affordable biosensor for the detection of a model biomarker protein that can compete with established market products. Two different approaches will be investigated. The first will make use of an in-vitro assay based on ribo-switch technology in which a protein biomarker binding to an aptamer domain results in reporter molecule expression. The second approach will involve a whole-cell biosensor with surface displayed llama antibody fragments. The presence of the biomarker molecules will bring cells with different antigen specificity in close proximity, resulting in a quantifiable signal for the user to read. The development of a system that can detect and accurately quantify protein concentrations and can integrate with existing biosensor modules will result in extending the use of synthetic biology biosensors to new application areas and analysis of even more complex sample mixtures.

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One of the aims of synthetic biology is to reach a level of systematicity and automaticity usually found in engineering. Achieving this goal requires abstracting away the details of the actual implementation and working at a higher level. When designing their organism, the user will usually make use of “active” parts like promoters and protein-coding sequences, and ignore more “house-keeping” parts like RBS and terminators. We present atgc, a biocompiler that automatically builds viable sequences of DNA given a small set of necessary parts. With no user intervention, atgc (for Assistant To Genome Compilation): a) completes the devices by adding RBS, spacers and effective terminators, b) finds a viable arrangement of the parts and c) finds the parts’ sequences in a built-in database, populated by parts from biofab and REbase. atgc thus automatically produces a biologically-plausible sequence reflecting the original aim of the user. atgc has been designed together with experimentalists and was inspired by their workflow. It comes with a simple language which allows users to add constraints on the resulting sequence. For example, it is possible a) to add in-house parts not found in the database, b) to impose the relative positions of parts, e.g. to import constructs found in the literature and c) to add multiple cloning sites, with the restriction enzymes being automatically selected. Rather than helping the user design their custom DNA sequence, atgc offers a way to automate the whole process and thus gets closer to the overall aim of synthetic biology.

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A grand challenge in biology is to use our current knowledge to create innovative functionalities based on known properties of organic molecules in living cells. Based on our recent success in validating the first fully automated design methodology of synthetic RNA interaction circuits working in a cellular environment, designing several positive riboregulators with diverse structure and interaction models, we decided to extend our methodology to the design of small molecule-sensing RNAs, synthetic riboswitches. Sensing is a fundamental feature that is critical for survival and adaptation and RNA aptamers have the ability to attach specifically to almost any kind of small molecules. In order to design synthetic riboswitches for a given molecule, we take advantage of existing RNA aptamer libraries. When a RNA aptamer binds to a given ligand, its structure is altered, but RNA aptamers remain non-functional molecules as long as they can’t propagate information about their state to another molecule. In order to trigger the propagation of an allosteric change, we created a computational algorithm, based on a physicochemical model, that evolve a RNA backbone in the form of a 5’UTR around the RNA aptamer to connect it to another functional RNA domain (RBS, anti-terminator, ribozyme…). We tested our methodology in E. coli by designing several positive riboswitches from the known RNA aptamer for theophylline. The designed sequences exhibit non-significant similarity to any known non-coding RNA sequence. Our RNA devices work independently and in combination with transcription regulation to create complex logic circuits. Our results demonstrate that a computational methodology based on first principles can be used to engineer functional regulatory RNA sensors in living cells from non-functional RNA aptamers.

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The remarkable degree of evolutionary conservation of most essential genes means that homologous genes often share the same functions, even between very distantly related organisms. Beyond retaining the same functions within their respective organisms, many essential genes can also be exchanged between organisms; that is, they both retain the core functionality of the common ancestor gene and can perform that function in the context of multiple extant organisms. This property has been exploited to clone human genes by complementing yeast mutants, in spite of yeast and humans diverging more than 1 billion years ago. While isolated examples are known, it is unknown if these are the exception to the rule, or if this is a general property of even the most distant homologs. Thus, we ask to what extent human genes functionally replace their yeast counterparts by systematically testing all essential yeast genes with single (1:1) human orthologs. We find many essential yeast genes can be replaced by their human equivalents with little to no detectable growth defects. Additionally, we aim to uncover rules governing the ability to complement by testing features of both human and yeast genes for their ability to predict replaceability. These data suggest that the core functions of many essential yeast genes are well retained and not subject to excessive neutral drift in those functions present in the last common ancestor of yeast and humans, even after greater than 1 billion years of divergent evolution.

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Introduction of complex regulatory circuits into mammalian cells requires the availability of several designable orthogonal switches. While prokaryotic regulators appear to be an efficient tool for construction of genetic devices in mammalian cells, their number is limited and their properties differ, which does not allow direct scalability required for the construction of complex logical functions. Modular DNA-binding protein domains such as zinc finger proteins or TAL effectors can be designed to bind almost any DNA sequence, providing high orthogonality. An orthogonal switch based on such designable elements would allow simultaneous introduction of several multistable switches into mammalian cells for an advanced level of regulation in different applications. Epigenetic toggle switches have been constructed based on bacterial transcription factors. Here we present a bistable toggle switch based on designable and freely scalable elements. The functional core of our device is composed of TAL effector-based transcriptional regulators. Simple wiring of mutual repressors as used in previous genetic toggle switches did not result in a functional switch due to the lack of cooperativity as demonstrated also by modeling. Functional switch was prepared by the addition of two positive feedback loops in a switch combining a pair of mutual repressors and a pair of activators that compete for the same operator sequence. This switch is robust and many different orthogonal switches can function in the complex system of mammalian cells. Switches can be used as the basic building blocks of memory cells, analogous to electronic components. A set of orthogonal bistable switches could be used to build biological memory of significantly higher complexity than previous attempts.

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There is a lack of hands-on demonstrations of Darwinian evolution in action in both high school and undergraduate level biology courses. This is likely due to the large time frames needed to observe the changes caused by the forces of evolution. In vitro directed evolution (IVDE) closely mimics natural evolution but produces observable phenotypic changes in a matter of hours as opposed to years. An IVDE demo kit would serve to both directly demonstrate the forces of Darwinian evolution and introduce students to an essential method of modern synthetic biology. In order to produce an IVDE demo kit, continuous IVDE of a T500 ribozyme ligase based pool has been paired with a fluorescence-based strand displacement reporter system in order to visualize the evolution of improved catalytic function. Ribozyme pools are taken through rounds of isothermal-based amplification dependent on the self-ligation of a T7 promoter. Dilution between rounds of evolution will select for ribozymes with faster ligation kinetics. As the pool evolves the strand displacement system allows for the monitoring of the pool’s ligation rate. The strand displacement reporter system allows for visual detection of ligated ribozyme. When ligated with the T7 promoter, the 5’ end of the ribozyme possesses enough complementarity with a fluorophore-labeled DNA oligo to displace, through toehold mediated strand displacement, an quencher-labeled DNA oligo, in turn, generating a visible signal upon UV light excitation. As the ligation rate of the pool increases due to the selection for faster ligating species, the student will observe more rapid development of fluorescent signal in later rounds of evolution. The pairing of the continuous isothermal system with the fluorescence-based strand displacement detection scheme allows any user, provided with minimal materials to model the continuous directed evolution of a biomolecule.

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One of the key challenges in construction of synthetic biological networks is to understand the mechanisms that enable the system to process and respond to multiple environmental inputs. Such mechanisms for regulation of gene expression are implemented by appropriate designs of promoter architectures and the upstream regulatory networks. Processing multiple inputs can potentially generate great diversity in the temporal dynamics of the resulting behaviours, contributing to versatility of the system response in constantly changing environmental settings. We take a combined experimental and theoretical approach to investigate the design of both promoter architecture and upstream regulatory network for Response-to-Dehydration 29A (RD29A), a plant stress gene that is inducible by a variety of abiotic stresses: NaCl and ABA. The gene’s inducibility by multiple types of stresses is conferred by its promoter, with presence of non-overlapping binding sites for multiple types of TFs that are regulated by different stress signalling pathways. Our experiments showed clearly distinct temporal expression profiles of RD29A under single NaCl and single ABA stress conditions, and synergistic profile of RD29A expression when exposed simultaneously to the two stresses. We proposed a mathematical model of the upstream regulatory pathways and revealed the underlying mechanisms for these experimentally observed RD29A expression dynamics. The overall expression dynamics of a gene is driven by tight temporal coordination between ‘slow’ transcriptional and ‘fast’ enzymatic signalling pathways while the synergistic temporal expression profile primarily arises from crosstalks in upstream regulatory steps. This observation provides a novel insight as to how the expression dynamics, and thus the response of the gene towards multiple environmental inputs, can be appropriately controlled through rational design of its promoter and upstream regulatory networks. The design principles obtained in this study is expected to be applied to the systems with more than two inputs.

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Since synthetic biology has been emerged, biological research which just studied about how to enhance cell’s productivity has shifted its paradigm toward re-programming of organism considering physiology and systems of the cell. With this trend, circuit systems such as logic gates, genetic toggle switches and oscillators has been embodied in cellular system to control metabolic pathways or regulatory networks. However, many of these systems work in irreversible manner. To construct a programmable reversible synthetic pathway system, we designed a promoter positioned between attB and attP sequences, the specific binding sites of Mycobacterium phage Bxb1 integrase/excisionase, which can be inverted by gene recombination mechanism. This invertible promoter flanked by synthetic pathways can initiate their transcription selectively according to the level of cellular signal. In this research, bio-indigo pathway which is operated by bacterial flavin-containing monooxygenase(bFMO) was a target synthetic pathway and quorum-sensing system was adopted as an indicator of level of metabolites. We demonstrated that bio-indigo pathway can be ON and OFF according to the amount of quorum-sensing molecules, respectively. This programmable synthetic pathway system provides an efficient platform tool needed to advance fine-tuned controllable metabolic processes for industrial applications. [This work was supported by the Intelligent Synthetic Biology Center of Global Frontier Project funded by the Ministry of Education, Science and Technology (2011-0031957).]

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Despite numerous approaches for the developments of L-threonine producing strains, the strain development is still hampered by intrinsic inefficiency of metabolic reactions caused by simple diffusion and random collisions of enzymes and metabolites. A scaffold system, which can promote the proximity of metabolic enzymes and increase the local concentration of intermediates, was reported to be one of the most promising solutions. Here, we report an improvement in L-threonine production in E. coli using a DNA scaffold system, in which a zinc finger protein serves as an adapter for the site-specific binding of each enzyme involved in L-threonine production to a precisely ordered location on a DNA double helix to increase the proximity of enzymes and the local concentration of metabolites to maximize the production. The optimized DNA scaffold system for L-threonine production significantly increased the efficiency of the threonine biosynthetic pathway in E. coli, substantially reducing the production time for L-threonine (by over 50%). In addition, this DNA scaffold system enhanced the growth rate of the host strain by reducing the intracellular concentration of toxic intermediates such as a homoserine. Our DNA scaffold system can be used as a platform technology for the construction and optimization of artificial metabolic pathways as well as for the production of many useful biomaterials.

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Synthetic biology strives to enable reprogramming and repurposing of biological elements ranging from molecules to ecosystems. In engineering organisms, we manipulate gene expression to alter or redirect cell metabolism, and due to the interconnected nature of the cell, it is often multiple genes that we must target to produce a desired effect. To that end, we have developed a system of combinatorial assembly of well-characterized parts, followed by a rapid and inexpensive genotyping assay that enables us to construct and analyze large libraries of heterologous pathways in Saccharomyces cerevisiae. By having genotypic information to associate with phenotypic differences, we use regression modeling to explore and understand the expression landscapes of these pathways. This strategy accelerates the process of building and testing multi-gene systems, to allow for the investigation of more pathways and the inclusion of–and control over–more genes than has previously been possible.

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Industrial-scale fed-batch fermentation of Escherichia coli results in numerous imposed stresses to the culture as a result of non-ideal mixing, high cell densities, and maintenance of environmental homeostasis. These stresses include elevated temperature, acetate accumulation, pH fluctuations, high osmolarity, oxidative stress, and product toxicity. A number of diverse non-pathogenic strains have been utilized as platform strains for metabolic engineering, however relatively little is known about differences in their stress tolerance. We first characterized the growth phenotypes of six wild-type E. coli strains under several imposed stresses. Remarkable differences were observed between strains for most stresses, with different strains exhibiting superior growth under different conditions, and genetically very similar strains exhibiting distinct phenotypes. Utilizing a comparative genomics analysis of these strains, we are employing both semi-rational and random strain engineering approaches that target primarily regulatory and membrane-associated genes. It is anticipated that this strategy will assist both in unraveling genetic determinants of strain-dependent phenotypes and in aiding the development of a universally stress-tolerant host strain of E. coli for bioproduction.

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Creating synthetic devices that are robust to changing cellular contexts will be key to the success of synthetic biology. When faced with a set of competing designs for a given genetic circuit one is likely to choose the simplest possible model that can achieve the desired behaviour. However simple systems are often the least robust and it is well known that additional feedback interactions can increase robustness to extrinsic noise sources. Here we utilise a design methodology that takes advantage of Bayesian statistics. This allows us to use model selection to compare designs based on their robustness and handle uncertainty in biochemical rate constants. We examine small gene networks, implementing various common behaviours, which take an input signal and trigger a response – ultimately leading to the production of a protein as an output signal. For each network device, we consider multiple models, each one capable of generating the desired behaviour but containing different feedback connections. We consider both deterministic and stochastic processes for the dynamics and use Bayesian model selection to directly compare the competing designs for their ability to perform in the face of extrinsic noise. The method also provides distributions of the kinetic parameters required to give the desired input and output characteristics thus providing information on the strengths of the required feedbacks. Our results provide insight into strategies for constructing more robust synthetic devices.

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The de novo design of Transcriptional Activator-Like Effectors (TALEs) targeting a given sequence is simple and enables the generation of a set of transcription factors that are orthogonal to each other and to a host genome. Thus, TALEs represent potentially attractive components of synthetic gene regulatory circuits. Towards this goal, we here tested whether TALEs can be used for Boolean logic computation in mammalian cells. In order to minimize interference with transcriptional regulation in the host cell, we computationally designed a TALE recognizing a 20 base pair sequence that is orthogonal to all promoter regions in the human and mouse genomes. We then identified an amino acid position within this TALE that is optimal for split intein-mediated protein splicing. Employing this TALE protein splicing strategy we generated two- and three-input AND logic circuits, which show 200 – 600 fold induction of transcriptional activity in transient transfection assays. Using a novel approach for modular assembly of large DNA constructs we integrated and tested variants of these logic circuits at a defined genomic site in mouse embryonic stem cells. Together, these results demonstrate the potential of split TALEs as a novel tool for building transcriptional networks in mammalian cells.

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The biggest hurdle to synthesizing the E. coli ribosome in vitro is reconstituting several post-transcriptional modifications of the peptidyl transferase center (PTC) of 23S ribosomal RNA (1). The modification reaction whose knock out produces the most significant growth defect is methylation of the ribose 2’O of U2552 by RlmE (2). Two other modification reactions of the PTC are performed by the recently-discovered enzymes RlmJ (3) and RlmM (4) which methylate the base of A2030 and the ribose 2’O of C2498, respectively. These two nucleotides are adjacent in the ribosome due to a tertiary interaction between A2030 and C2498. All three enzymes use S-adenosyl-methionine as the methyl donor. In this study, all three enzymes were overexpressed in His-tagged form and their reactions assayed and optimized using reverse transcription and tritium-incorporation assays. RlmE required the full 50S ribosomal subunit as a substrate, as previously demonstrated (2). In contrast, RlmJ and RlmM were both found to specifically methylate 23S rRNA in unmodified form, facilitating substrate recognition studies. Domain V alone was sufficient for recognition by RlmM (5), while RlmJ only required a 26-nucleotide stem loop. This work should aid future ribosome reconstitution from transcripts for directed evolution of ribosomes and synthesis of a minimal cell. References 1. Forster, A C, Church, G M (2006) Mol Syst Biol, 2(45), 1. 2. Caldas T, Binet E, Bouloc P, Costa A, Desgres J, Richarme G (2000) J Biol Chem. 275(22), 16414. 3. Golovina A Y, Dzama M M, Osterman I A, Sergiev P V, Serebryakova M V, Bogdanov A A, Dontsova O A (2012) RNA, 18, 1725. 4. Purta E, O’Connor M, Bujnicki J M, Douthwaite S (2009) Molecular Microbiology 72(5), 1147. 5. Punekar A S, Shepherd T R, Liljeruhm J, Forster A C, Selmer M (2012), Nucleic Acids Res, 40, 10507.

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Advances in metabolic engineering and synthetic biology could fulfill a global demand for the production of commercially valuable chemicals such as petroleum-derived chemicals, fuels, and pharmaceuticals. To achieve the successful design of the biological systems, however, one of the important issues to be solved is balancing the intracellular redox state that plays a governing factor for the continuation of both catabolism and anabolism. The concept of the rebalancing redox state is also important to make cells efficiently utilize various feedstocks, because typically different catalytic amounts of reducing equivalent are required depending on the carbon flux of the different substrates. Here, we show that how the changes of intracellular redox state affect the pathway performance of n-butanol production from glucose and galactose in Escherichia coli as a model system. We built the synthetic n-butanol production pathway by implementing synthetic constitutive promoters and designing synthetic 5’-untranslated regions (5’-UTR) based on our predictive model (UTR Designer), which we term “UTR engineering”, for each gene. The redox rebalancing was achieved by anaerobically activating pyruvate dehydrogenase (PDH) complex and additionally tuning expression level of NAD+-dependent formate dehydrogenase (fdh1 from Saccharomyces cerevisiae) through UTR engineering. As a result, we found that the optimal expression levels of fdh1 were dramatically different to efficiently produce n-butanol from glucose or galactose. This work provides intriguing insight that genetic contexts dependent-engineering is promising for strain improvement, even with the same genetic contents, by rebalancing of the intracellular redox state depending on the target products and substrates.

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One of the fundamental hurdles in genetic engineering is to gauge the effects of transgenes to the native system. High-throughput transcriptome profiling, such as microarrays and RNA-seq, can only profile the effects of transgenes after the cloning process is completed. However, it will be handy to estimate the effects of transgene prior to cloning. Many studies had demonstrated that co-expressed genes are biologically significant and many tools had been developed to deduce pathways from co-expression data. As first instance, we present a correlation-based model for predicting the native transcriptome using expression values from 59 genes as markers. This can be the basis for a model to estimate the effects of transgenes on the native system. The model was developed using a set of 605 microarrays across 40 different experiments. A linear regression model is calculated for each pair of genes to predict the expression of adjacent genes. Our analysis using pairs of probes detecting the same transcript suggests 19.2% intra-array variation. We developed a single-pass transcriptome predictor to predict expression values of the entire transcriptome using linear regression models. Evaluation on predictability was performed using microarrays that were not used for network development. Our results shows that gene-pairs intervened by 3 co-expressed genes (4 jumps in total) can be reliably predicted within 3 standard deviations using at least 30 different paths between the marker genes and the target genes to be predicted. Using a random set of 30 microarrays, our results demonstrated that the average error of predicted expression values to be within 3 standard deviations (29 out of 30 transcriptomes predicted; 96.7%) or within 40% (23 out of 30 transcriptomes predicted; 76.7%), inclusive of the intra-array variation. These results are promising and represent a first-draft of transcriptome prediction using a relatively small set of marker genes.

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The development of biology-friendly standard cross-platform programming tools is a crucial step towards automation of research laboratories. The current lack of such tools is a major obstacle for modernization of the Life Science. We have developed high-level biology-friendly programming language PR-PR (Programming Robot) that is used for management of liquid-handling robotic and microfluidic automated platforms. This language allows researchers efficient implementation of protocols for automated DNA synthesis and other complex Synthetic Biology processes, permitting plethora of new high-throughput complex experiments. PR-PR has established the same set of basic commands for any automation platform. Most of the advanced features of the language are also available for all the compatible platforms, while the underlying optimization and translation processes are unique for each platform. We have created PR-PR as an open source project to boost the adoption of the language as a standard and to encourage the scientific community to add translators for various automated platforms. Performing laboratory operations on small scales and increasing experiments throughput by using miniaturized microfluidic Lab-on-a-Chip (LOC) devices is the next step forward in the laboratory automation. We are working on development of a new integrated multipurpose microfluidics platform, operated by PR-PR. We can perform a broad spectrum of Synthetic Biology applications on our microfluidics platform using the same PR-PR scripts that can be run on the robotic platforms.

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In the past, all engineering disciplines have developed their own unique set of standardized components and toolsets to facilitate and accelerate the construction and development of novel items. We envision Synthetic Biology to be situated at the dawn of being a constructive technology, rather than a descriptive science. What’s lagging behind are the capabilities to (a) select suitable sequence elements from a well-defined database and (b) to assemble these in a defined but flexible way. As a key provider of gene synthesis and related services we observe an augmented demand for standard building blocks for higher-order construction, with a strong focus on individualized vector design. The presented Parts & Devices concept addresses these needs by setting up a database of well-described sequence parts ranging from promoters & terminators, to reporters & gateway sites. By providing an intuitive CAD software, users are enabled to combine these parts on a symbolic meta-level without any restrictions regarding the sequence junctions of the parts. Once the in silico design is final, customers can either order the fully assembled synthetic construct as a whole or obtain the separate parts, together with a kit for their seamless assembly. This complete package will further advance the transition of biotechnology into a true engineering discipline of Synthetic Biology.

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The field of synthetic biology has recently emerged as a result of achieving a critical mass in our knowledge of biology. While many biological molecules and systems are still too complex to be rationally designed de novo, the continued efforts in isolation and characterization of individual biological components offer the possibility of integrating them into biologically inspired devices that exhibit novel functionalities. Rather than deconstructing existing biological systems, our vision is to assemble biological parts into systems. As a first step in this direction, we seek to emulate biological systems that would have immediate benefit and also serve as a test-bed for such design strategy. To this end, we have identified platelets as a tractable first target. Platelets are anucleate cells that are pre-programmed to execute a fixed pattern of behaviors that lead to the activation of the clotting cascade. Our synthetic biology approach requires more than reconstitution of the parts that make up a platelet. Rather, we propose designing an artificial platelet that is based on mimicking the functionality of a natural platelet, through a novel combination of biological components. Our approach includes incorporating mechanosensitive channels, phosphatidylserine scramblase, and phosphatylserine synthase into lipid vesicles that would activate the clotting cascade when bound to injured vasculature. A plan for building artificial platelets by breaking this challenging problem into manageable modules will be described and our progress in testing the design strategies will be reported.

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Precise timing is important for many people in our daily life, and it’s also extremely important for nearly every biological process at the molecular level. In accordance with the day/night switch on earth, biological behaviors are generally guided by a 24h rhythm. In human and eukaryotes, this rhythm was believed to be governed by transcription-translation-feedback loops (TTFL). However, it was shown in the last two years that non-TTFL biological clocks also exist in human and other eukaryotic cells, although the detailed molecular mechanisms are pending to be elucidated. Therefore, we are using a non-TTFL clock, the KaiA/KaiB/KaiC clock from blue-green algae, as a model to study the basic mechanism. As the only known protein-protein interaction based biological clock, the KaiA/KaiB/KaiC oscillator can be fully reconstituted in vitro. Combining computational and experimental methods, we’re interested to know what parameters are deterministic for this protein-based molecular clock, and how to design an orthogonal clock from this one, how to modulate this clock with artificial inputs, and how to output signals from this clock. We have identified some critical residues at protein-protein interfaces, and designed a light-modulatable protein, as well as a starting network model. We will interrogate the clock with our designs, incorporate our experimental data in the network model, and hopefully predict new behaviors and parameters from optimized models.

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Vanillin (4-hydroxy-3-methoxybenzaldehyde) is the key compound that contributes to the vanilla aroma which can be found in food and cosmetic products. Due to its heavy consumption, natural vanillin produced from the seed pods of Vanilla plantifola contributes to less than 1% of the total global supply, with the majority coming from chemical synthesis using petroleum based materials. Various attempts to biologically produce vanillin from renewable materials such as ferulic acid, eugenol and isoeugenol have been reported. However, the biological production of vanillin often requires inducers such as L-arabinose and IPTG. Artificial induction in many cases is less favorable due to high economic cost of inducers, inducer toxicity, incompatibilities with industrial scale-up and detrimental growth conditions. Hence, in this study, we have attempted to engineer E. coli that is capable of auto-inducing and self-regulating its protein expressions based on the presence of the substrate, ferulic acid and its cell population density. We aimed to demonstrate that by having controlled and self-regulated expression, E. coli could have improvements on its viability and growth rate, thereby enabling a larger population for bioconversion. By having a large bio-catalytic population in the shortest time, it could possibly lead to a more efficient production of vanillin from agro-industrial wastes that contain ferulic acid. To construct the ferulic acid sensing device, we implemented the sensing mechanism of Pseudomonas spp. in E. coli. Besides the ferulic acid sensing device, we also introduced a second regulatory device that is based indirectly on cell density. By combining the ferulic acid sensing device and the indirect cell density device for regulating vanillin genes, we demonstrated a highly efficient production of vanillin in our engineered E. coli.

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Future space exploration missions to the Moon, Mars and other solar system destinations will be severely constrained by weight limitations associated with habitats and other built structures needed to support surface operations. Synthetic biology provides a variety of approaches for the creation of materials that combine readily available lunar or planetary soil with biopolymers to create “biocomposite” materials that can be used for manufacturing and construction purposes. In situ production of these regolith biomposites, using space hardy organisms, will provide the maximum up-mass savings, and will support the fabrication of building components and finished structures for a sustained human presence at these sites. Initial development of these novel materials, involving both NASA Ames and Stanford University, has shown that a variety of bio-polymeric materials are suitable as the matrix for regolith biocomposites. Unlike conventional fiber/resin composites, in which the matrix component predominates, the regolith biocomposites that we have developed have a high proportion of dispersed phase (regolith) material, and a relatively low proportion of matrix, which optimizes the overall economy of producing such materials in space. Initial characterization of regolith biocomposites indicates that the material is very strong in compression (approaching that of concrete), with favorable elastic modulus that can be controlled by the composition of the material. The results of both mechanical testing and ultra-structural analysis will be presented. We believe this new composite material may be one of the most important synthetic biology applications for future space exploration.

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Synthetic genetic programs are built from circuits that integrate sensors and implement temporal control of gene expression1–4. Transcriptional circuits are layered by using promoters to carry the signal between circuits. In other words, the output promoter of one circuit serves as the input promoter to the next. Thus, connecting circuits requires the physical connection of a promoter to the next circuit. We show that the sequence at the junction between the input promoter and circuit can affect the input-output response (transfer function) of the circuit5–9. A library of putative sequences that might reduce (or buffer) such context effects, which we refer to as “insulator parts,” is screened in E. coli. We find that ribozymes that cleave the 5’ untranslated region (5’-UTR) of the mRNA are effective insulators. They generate quantitatively identical transfer functions, irrespective of the identity of the input promoter. When these insulators are used to join synthetic gene circuits, the behavior of layered circuits can be predicted using a mathematical model. The inclusion of insulators will be critical in reliably permuting circuits to build different programs.

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The idea of programming cells to perform specific tasks has become an active research topic with applications in biomedical research and industrial biotechnology. This is promoted by synthetic biology through the development of a variety of artificial biological parts. However, computational simulation of a programmable cell is currently not possible due to the lack of integrated modeling of the synthetic parts within the cellular chassis. The goal of this work is the development of a computational modeling framework for a programmable E. coli cell. It begins with an extensive search of biological parts that have been built and experimentally validated. These will be modeled in silico to create a small library of plug-and-play model components. They will then be integrated into recent large-scale regulatory and metabolic model reconstructions of E. coli. The development of methods for integrated simulation of the synthetic parts within the cellular metabolism is one of the novel aspects of this work. The advantages of this framework are two-fold. First, it can save time and money in the laboratory by predicting ahead which combinations of the parts and the host metabolism will not work as expected. On the other hand, it will facilitate the computational design of new potential applications by combining and fine-tuning different parts. This framework will be tested in a practical case study for optimal biochemical production in E. coli from a feedstock containing multiple carbon sources.

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Electrical current is ubiquitous in human civilization, where it serves as a versatile energy source and medium of information transmission. Electricity would also make an inexpensive input for biotechnology applications, where it could be used to drive microbial metabolism to produce commodities like fuels. This will require a robust interface between solid-state electronics and the aqueous chemistry of living cells. In most bacteria, the machinery for interconverting chemical and electrical energy – the electron transport chain – is separated from the environment by a nonconductive outer membrane. The best-studied conduit across this space at present is the metal reducing (Mtr) cytochromes of the gammaproteobacterium Shewanella. These bacteria use their periplasmic and outer membrane cytochromes to respire anaerobically onto solid iron and manganese, and recent studies indicate that they can also carry current in reverse, delivering electrons from an electrode to the inner membrane, where they could potentially be used to power synthetic pathways. We are studying the electrophysiology and gene expression dynamics of current delivered through the Mtr cytochromes, both in their native context in Shewanella, and in Escherichia coli cells engineered to express these genes. The lessons learned in these studies will be applied to the improvement of the electrode:bacterium interface, which may reduce costs and increase control over commodity production from microbes.

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Adaptation by natural selection is constrained by the available supply of beneficial mutations. Tension exists between finding the best mutation accessible locally, and finding the best mutation existing globally. If a “design” is a suite of mutations making up a successful genotype, how far away are the designs realized in evolution from the best possible design? Populations may not evolve toward the same optimum if alternate strategies exist for continued survival. Furthermore, successful strategies may depend on the strategies played by other members of the population. This type of dynamic is called frequency-dependent selection. For instance, bacteria that specialize on a resource produced by another type of bacteria can co-exist indefinitely, if both types have an advantage over the other when rare. Researchers in our laboratory have evolved 12 lines of Escherichia coli in glucose-limited media for 25 years. This experiment spans over 57,000 generations of bacterial evolution. I present a result in which a nadR mutation that arose in a glucose specialist was engineered into the genome of a competing frequency-dependent strain. As nadR has mutated in many of the 12 lines, I ask whether this globally beneficial mutation can fail in the context of an alternate evolutionary strategy. Second, I present results in which we swapped three parallel mutations in the master regulator spoT among the lineages in which they evolved. Is there a globally superior spoT allele? If so, how far were the realized evolutionary designs from the best possible design? If not, how much do these beneficial mutations depend on the rest of the evolved genetic network? Answering these questions have implications both for designing novel genetic networks, as well as for understanding the variety of ways in which synthetic genetic networks may evolve either toward, or away from a given objective.

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We developed a computational tool for the automatic design of digital synthetic gene circuits (Marchisio and Stelling, PLoS Comp.Biol. 7, e1001083, 2011). We chose digital circuits because they can be used as biosensors that, for instance, produce a fluorescent protein as a response to the presence of chemicals. In the latest version of our tool, the user has to specify the input (chemicals) number and type, fill in the truth table, and indicate if the chemicals bind transcription factors or riboswitches. The truth table is converted into Boolean formulas via the Karnaugh Map method and formulas are translated into circuits organized in two or three layers of gates. Boolean gates exploit transcriptional and translational control at promoter and RBS (ribosome binding site) level, respectively. Digital circuits computed by our tool require three kinds of basic Boolean gates: YES, NOT, and AND. All the schemes corresponding to a given input are ranked according to a complexity score that quantifies the effort required for a practical implementation. A solution chosen by the user is encoded into MDL (Model Description Language) files and is visualized with ProMoT. Circuits can be finally exported to a format suitable for simulations such as SBML or Matlab. As a prof of concept, we implemented in yeast several configurations of basic Boolean gates such as YES, NOT, and AND. They were realized by integrating bacterial repression systems into the yeast genome. Each gate was characterized by the signal separation i.e. the distance between 1 and 0 outputs at steady state. Small digital circuits that sense two or three inputs and arise from the combination of our library of basic gates are currently under construction.

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Bacterial microcompartments (BMCs) are proteinaceous metabolic compartments that are found in a wide variety of bacterial species and enable the efficient breakdown and utilisation of various environmental carbon and nitrogen sources. These compartments have a modular organisation, with an external shell constructed from a family of structurally related proteins. The shell proteins recruit and encapsulate the enzymes required for their function, while creating a semi-permeable barrier between the BMC lumen and the cytosol. The diversity and modularity of BMCs presents a platform with great potential for exploitation in synthetic biology. BMCs could be used as containers for heterologous biosynthetic pathways; as containers for the production of toxic proteins; or as scaffolds for the production of metallic nanoparticles. A major barrier to the use of BMCs in synthetic biology is the lack of understanding of the principles underlying their formation and substrate transport across the shell. A combination of 3D-proteomics and biophysical characterisation is being used to map the interactions that specify BMC formation and enzyme recruitment. The specificity and substrate selectivity of the BMC shell proteins and the encapsulated enzymes is being studied using biochemical and biophysical methods. Using microcompartments with different protein composition and function, taken from various source organisms, conserved and substrate specific features will be determined. The ultimate outcome of this research will be a model of BMC organisation and function that can be used as the basis for the rational design of synthetic BMCs.

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Synthetic morphology is the application of synthetic biology approaches to build anatomical systems. Well-characterised genetic circuits have previously been designed and implemented in both pro- and eukaryotic cells. Such synthetic circuits, in combination with carefully-chosen ‘morphogenetic effectors’, can be designed to integrate external signals and output phenotype – providing a powerful tool-kit for engineering cellular behaviour and morphogenesis. Epithelial tubulogenesis is crucial to higher eumetazoa in defining epithelial organs such as the kidney. Despite its key role in development, the mechanisms underlying tubule outgrowth are still poorly understood. The physicist Richard Feynmann is quoted as having said: “What I cannot create, I do not understand”; synthetic morphology opens the door to understanding systems by a ‘constructionist’ rather than ‘reductionist’ approach – learning by building. Modularity and reusability of genetic ‘parts’ (dubbed ‘BioBricks’ in some circles) is one of the fundamental principles of synthetic biology. We are assembling a library of morphogenetic effectors for use in mammalian cells, and are in the process of testing potential effectors (‘parts’) with the aim of placing them under the control of synthetic circuits to drive tubule formation in Madin-Darby Canine Kidney (MDCK) strain II cells. This constructive approach will allow us to determine the roles and necessity of the signalling pathways and downstream effectors that have already been identified as important in tubule outgrowth more precisely; an approach which will complement and add to the existing body of work. For more information, please see the synthetic morphology platform paper: Davies, J. A. (2008). Synthetic morphology: prospects for engineered, self-constructing anatomies. Journal of Anatomy, 212(6), 707-19. We gratefully acknowledge the support of the Biotechnology and Biological Sciences Research Council (BBSRC) and the Anatomical Society.

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While Systems Biology aims at acquiring a global knowledge of the physiology of the cell, Synthetic Biology pursues inter alia the reprogramming of organisms to execute new-to-nature functions. Deep engineering tasks need to optimize two factors to maximize reprogramming efficiency. First, it is fundamental to possess a suitable genetic tool repertoire and second is to select an appropriate chassis that is easy to manipulate genetically and offers good biotechnological properties. On this background we have developed a number of molecular assets consisting of a collection of constructs assembled in a modular fashion to effortlessly exchange the different functional parts at users’ convenience denominated Standard European Vector Architecture (SEVA). To this end, we have produced dedicated vectors to both eliminate undesired chromosomal regions or –on the contrary, stably implant genetic networks. In order to facilitate the use of these tools, users can interrogate a vector repository to find an optimal configuration through the website http://seva.cnb.csic.es. A large number of intrinsic traits make the soil bacterium Pseudomonas putida an optimal choice as a chassis of reference for different environmental and biotechnological purposes. It is a non-pathogenic, ubiquitous bacterium with a broad metabolic versatility with a considerable tolerance to organic solvents and xenobiotic chemicals. This makes P. putida an appealing organism to develop platform strains for Synthetic Biology. To this end, we have used different SEVA tools for editing the genome of P. putida KT2440 in order to create a distinct type of chassis (x-S) that is enhanced for surface display of proteins. This consists of a cell deleted of its social determinants and designed for presenting active proteins to the external medium that are still attached to the bacterial body. The applications of such strain for creating artificial communities and for acting as a live scaffold for an exo-reactor will be presented.

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Geobacillus thermoglucosidasius is a thermophilic bacterium that can convert monomeric and some oligomeric and polymeric components of lignocellulosic feedstocks into ethanol biofuels at high temperatures. Its application for industrial use is currently hampered by the lack of tools for rational and rapid genetic engineering. To enable design-led synthetic biology and metabolic engineering in this useful thermophile chassis we have developed a modular plasmid tool kit suitable for overlap assembly methods (Gibson) and standard restriction digest cloning. Within this kit is a genetic knockin/knockout system that utilizes green fluorescent protein as a visible marker. We are now able to use it to up-regulate precursor formation and to introduce non-native genes in order to produce the drop-in biofuel, isobutanol.

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For the direct editing of bacterial genome with single-base resolution, two-step recombination methods are widely used. Here, the target site is replaced with PCR-generated DNA cassette first, and the cassette is then replaced with exogenous genes. The DNA cassettes code for positive/negative markers in order to select both for the intermediate/final states. Here, we report the systematic effort to re-design the system to improve the robustness, throughput, and speed of this method to realize the seamless and automation-liable platform for genome engineering. In search for the robust negative genetic selection that can be operated by liquid handling, we found the nuclease kinase activity for non-natural nucleotide dP, originally developed for the directed evolution of genetic switches/circuits (Tashiro et al., Nuc. Acids Res., 39, e12 (2010)), provides robust and efficient selection for the recombinant cell only with liquid handling. Creating/testing the chimeric selectors, duplication of selector genes, tuning of the expression level of individual selector genes enabled us to eliminate the emergence of false-positive clones during the process. Having established the repeatable workflow where all the steps can be rapidly and seamlessly operated by liquid handling, we demonstrate the multi-step and in-parallel operation of genome modifications to generates a diverse set of isoprenoid-overproducing Escherichia coli strains.

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We aim to produce hydrocarbons using methods theoretically more efficient than natural photosynthesis. In an analogous process, our E. coli cells will fix CO2 and gain their reducing equivalents from a green electrical source. The most common CO2 fixation pathway, the Calvin cycle, depends on the slow enzyme Rubisco (kcat ~ 3/sec). Land plants and cyanobacteria make up for this activity by overexpressing it; in some environments it can make up to 30% of the protein by mass (Ellis 1979). The process is oxygen-sensitive; Rubisco is usually sequestered into organelles. Chloroflexus aurantiacus lives commensally in hot springs, and fixes carbon with a unique bicyclic pathway that is insensitive to oxygen and potentially faster (Zarzycki et al 2009). We have divided engineering the bicycle into four key pathways: 1) Carbon fixation via fatty acid synthesis; 2) Carbon fixation by propionyl-CoA; 3) Glyoxylate production; and 4) Glyoxylate/propionate assimilation. Through metabolic engineering techniques we have expressed 13 heterologous enzymes separately in E. coli. We demonstrate function of each of the pathways by the use of a novel propionate biosensor (pathway 1), complementation of relevant knockouts for growth on propionate (2, 4) or diaminopimelic acid (3). We are currently integrating all the pathways into a single engineered E. coli strain for autotrophic growth. Future work includes production of a biofuel from these cells, formation of an integrated bioreactor system in which the cells are provided with reducing equivalents from an electrical source, and integrating with a plant carbon fixation system.

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Synthetic biology, an emerging field of research combining molecular biology and engineering to design and characterize novel biological networks, is constantly in need of new biological “parts” for its increasingly complex devices. To suit the quantitative nature of the field, it is imperative that these parts be robust and well characterized. One class of parts consists of elements involved in transcriptional control, and here we present two examples: an optically-controllable protein and a novel engineered promoter that can be separately activated and repressed. (1) Synthetic biology to date has worked with a limited set of chemically inducible and repressible promoters to design its networks. Placing gene expression under optical control is thus an attractive prospect: it provides a simple method of altering the internal behaviour of cells without the need for time-varying extracellular inducers; and it offers a new set of control mechanisms to be used in complex synthetic network designs. The Woolley group has engineered a fused protein system that displays light-dependant DNA-binding activity in vitro. By incorporating the target DNA sequence into a modified promoter, we have designed and characterized a promoter system that can be regulated using blue light in E.Coli.(2) Yeast is an attractive model organism for the design and testing of biological “parts” for synthetic biology, and parts with multiple functions are helpful in tuning complex networks. In particular, there is a need for “dual-mode” promoters, able to be activated by one input and repressed by another, allowing specific types of feedback (integral controller) to be achieved. We have designed and characterized a synthetic promoter, which contains androgen receptor binding elements upstream and lac operator site downstream of minimal promoter cytochrome C. The promoter regulation was measured by expressing green fluorescent protein in yeast.

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Microbial metabolism can be tailored to meet human specifications, but the degree to which these living systems can be repurposed is still unknown. This work contributes well-characterized genetic tools useful for modulating gene expression (extended promoters) and isolating expression of designed DNA from the endogenous cellular network (orthogonal gene expression systems). Furthermore, the utility of these tools is demonstrated in Escherichia coli through the overproduction of (S)limonene, a cyclic monoterpene with a number of desirable physical properties. In general, this work contributes to the development of artificial biological control strategies aimed at enabling the predictable implementation of novel biological functions (e.g., engineered metabolism).

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As innovations in synthetic biology pave the way for the shift of engineered organisms from the laboratory to the field, the need for understanding the ecological implications of such releases becomes increasingly important. However, the area still contains data gaps and scientific uncertainties. These uncertainties have constrained assessments looking to understand what, and how, to adequately assess risks, and scientists looking to reduce possible hazards. Recently, a series of workshops were convened to attempt to identify and delineate these uncertainties. Stakeholders from across academia, industry, government, and non-governmental organizations gathered to identify hazards associated with synthetic organisms and their interaction with the environment, and develop research agendas to address these concerns. These workshops successfully constituted an exercise of anticipatory and inclusive governance as they translated technological uncertainties about potential risks to health and ecosystems in a way that can be discussed early and treated by scientists and policy makers in an inclusive setting. Here, we 1) present the primary findings from these workshops, and 2) assess the success of the methodology from which they were built.

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The detection of trace amounts of toxic metalloids such as arsenic, down to less than 10 parts per billion (ppb), can be readily achieved using genetically modified microorganisms. Using strains of E. coli, genetic pathways based on the arsenic binding ArsR repressor have been modified to enable the microorganism to function as a whole cell biosensor, capable of expressing reporter genes in response to environmental toxins. However, some key drawbacks to using such modified organisms in field conditions lie in maintaining strain viability during storage and transport, along with long incubation times (many hours). Furthermore, the necessity of widespread global adaptation of such GMOs to adequately assess contaminated sources of drinking water poses large geopolitical hurdles in many regions.
Our approach has been to design fusion proteins capable of altered binding to immobilized “bait” DNA molecules in vitro in the presence of specific toxins, such as arsenic. Detection that is based directly on protein-DNA interactions would also allow for more rapid signaling of toxins since the system is independent of gene expression. Fusion proteins have been designed that comprise of an enzyme coupled to the arsenic binding repressor ArsR. In the absence of arsenic, ArsR binds tightly to operator sites of the native Ars operon. The presence or absence of an enzyme-DNA complex can then be readily detected using a variety of substrates, based on the particular enzyme chosen, such as glutathione-S transferase. The output of the reaction can be visualized either qualitatively, as a color change, or measured more quantitatively. Using a DNA binding assay based approach to biosensors lends itself readily to further expansion to a wide variety of other DNA binding proteins whose affinity is affected by small molecule binding, such as the MerR repressor and mercury.

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Computational automated methods for biochemical pathways constructions are becoming more popular each year. The availability of data of genomes and biochemical reactions allows usage of computers to build probabilistic metabolic routes from an initial compound to a product compound that can be implemented into a living organism. Various computational methods and tools were developed in last decades for metabolic network construction, analysis and optimization. In this work we present the software tool that can be used to predict possible minimal reactions list and its corresponded genes to build novel pathways. It can be used to reach necessary functionality of genetic modification and implement it into selected microorganism chassis like e.coli or yeast. This tool is developed in Matlab environment. To construct a pathway from the input compound to the product, the probabilistic pathway construction algorithm is used. The algorithm is based on data obtained from KEGG database. The algorithm constructs the biochemical network in levels, starting from input substrate it adds reactions into chassis organism model (biochemical model of microorganism in SBML format) and checks, is the source metabolite connected with the product or not. Pathways with smaller number of reactions get an advantage. For these reactions next analysis steps can be performed. The tool uses productivity of Cobra toolbox for biochemical model manipulation (adding and removing reactions and metabolites) and constructed pathways analysis – FBA, FVA, EMA etc.

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Biosynthetic pathways can be engineered into bacteria allowing the production of chemicals with commercial and therapeutic applications. Challenges, when engineering biosynthetic pathways, include balancing levels of proteins and pathway intermediates, competition with existing pathways, finding suitable enzymes, maintaining host viability and increasing yield. We are developing a novel technology, Serine Integrase Recombinational Assembly (SIRA), using site-specific recombination, to assemble and optimize the expression of biosynthetic pathways rapidly. With SIRA technology, genes and regulatory sequences, in the form of DNA “cassettes”, integrate into a landing pad on the plasmid or genome where the new pathway is being built. The assembly process can easily construct pathways in predefined or random gene orders, include multiple gene variants at all positions, and facilitate varied gene expression levels by incorporating degenerate ribosome binding sites. Using the carotenoid and violacein biosynthetic pathways as model systems, we have shown assembly and optimization of two fully functional pathways in just two days. Once assembled, SIRA allows targeted addition, deletion, and replacement of genes and DNA elements within a pathway.

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Synthetic Escherichia coli bioreporters for arsenic detection typically rely on the natural feedback loop that controls ars operon transcription. This loop originates because arsR, the gene that codes for the arsenic-sensitive repressor, belongs to the same operon that it controls. Feedback loops are known to show a wide range linear response to the detriment of the overall amplification of the incoming signal. While being a favorable feature in controlling arsenic detoxification for the cell, a feedback loop is not necessarily the most optimal for obtaining highest sensitivity and response in a designed cellular reporter for arsenic detection.
Here we systematically explore the effects of uncoupling the circuit input (arsenic sensing) from the output (repressor production), and develop a mechanistic model to describe relative ArsR and GFP levels in feedback and uncoupled circuitry. The topology of the arsenic sensing circuitry was changed by placing the expression of arsR under the control of a series of constitutive promoters, which differed in promoter strength, and which could be further modulated by TetR-repression, while the expression of the reporter gene was maintained under the ArsR-controlled Pars-promoter. We find that stronger constitutive ArsR production decreases arsenite-dependent EGFP output from Pars and vice-versa. This leads to a tunable series of arsenite-dependent EGFP outputs in a variety of systematically characterized circuitries. The higher expression levels and sensitivities of the response curves observed in some of the uncoupled circuits will be useful for improving field-test assays using arsenic bioreporters.

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The controlled transcription of genes and functional RNAs is important for the current generation of synthetic biology. In general, T7 RNA polymerase (T7 RNAP) has proven to be a workhorse enzyme for in vivo gene expression, and is also of great utility for in vitro RNA production in molecular biology and molecular diagnostics. We have endeavored to engineer T7 RNAP functionality using a novel platform for directed evolution termed Compartmentalized Partnered Replication (CPR). CPR is an emulsion-based selection system that couples the in vivo function of a gene to its in vitro amplification. In our initial efforts, a library of T7 RNAP variants was transformed into E. coli containing a Taq DNA polymerase (Taq DNAP) gene under the control of a T7 RNA polymerase promoter. After the induction of expression, cells containing the most active T7 RNAP genes also contained high levels of Taq DNAP protein. Cells were then compartmentalized in a water-in-oil emulsion containing buffer, dNTPs, and primers specific to the T7 RNAP gene. Emulsification was performed such that (on average) each cell was isolated in its own compartment. Upon thermal cycling, the most active T7 RNAP genes, which are compartmentalized with the most Taq DNAP protein, are preferentially amplified. Successfully amplified T7 RNAP genes were recovered and used to seed subsequent rounds of selection. Iterative rounds of selection and amplification were found to yield highly active T7 RNAP variants. When the promoter driving the Taq DNAP was altered, new promoter-specific variants of T7 RNAP were selected, including a variety of new orthogonal variants with high activity and specificity. Ongoing work includes expanding the nucleotide specificity of T7 RNAP as well as applying the CPR methodology to the evolution of other proteins and nucleic acids, in particular tRNA synthetase:tRNA pairs.

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One of the primary challenges in synthetic transcriptional network engineering is the difficulty in choosing the correct system components to achieve the desired system behavior. Every modifiable aspect of the system, from promoters and ORFs to protein degrons and transcriptional terminators has the potential to impact the performance of the final network. The requirement to select system components with variable quantitative characteristics creates a multi-dimensional space of possible choices, of which only a sub-set of possible network configurations are likely to produce the desired outcome. In synthetic networks of limited size, it is possible to search through component combinations to find a working configuration, but as a system grows in size, this search process becomes prohibitively expensive. As a result, synthetic networks have averaged less than 6 promoters per system. As a proof of principle, we have developed a modular promoter assembly and characterization process that allows the rational assembly and characterization of synthetic promoter libraries containing non-native transcription factor binding sites. Using this technique, we have assembled a library of promoters with binding sites for two non-yeast transcription factors. The assembled promoters were integrated into the yeast genome and regulatory factors with binding sites in each promoter were titrated into the cell via drug inducible promoters. Synthetic promoter output across a range of input transcription factor concentrations was then measured by the Quantigene platform. Preliminary results indicate that the titration system accurately captures the full dynamic range of the interaction between the titrated factor and the target promoter. The application of this transcription factor titration system will enable the accurate parameterization of transcription factors whose activity cannot be directly controlled by small molecules, expanding the space of well characterized components for future synthetic network engineering.

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While protein-protein interactions are ubiquitous in natural biological systems, the use of protein-protein interactions in synthetic biology has been minimal. Several successful strategies have slowly emerged including modular domain recombination and signal pathway diversion for the creation of small unidirectional pathways that ultimately transduce signals to transcription. However, there have not been any complete circuits built that are based solely on protein-protein interactions. Here we describe the design, construction, and testing of circuits in Saccharomyces cerevisiae based solely on protein-protein interactions. We introduce a new design rule, functional protein scaffolding, in combination with existing practices to form a framework for generalized protein-protein circuit engineering. We apply this framework to create a protein-phosphorylation bistable toggle element by rewiring the existing high osmolarity MAPK cascade with exogenous mammalian, plant, and bacterial components. Our results demonstrate that top-down decomposition in conjunction with bottom-up assembly guided by design rules can be applied to protein-protein interaction based circuits. We anticipate our methodology to be a starting point for more sophisticated protein-protein circuits including the use of toggle switch motifs in tandem with logic operations and sensors to create programmable biosensor elements.

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Chromosome engineering is an emerging focus in the fields of systems biology, genetics, synthetic biology, and the functional analysis of genomes. Here we describe the ‘telomerator’, a new technology/synthetic biology “device” designed to inducibly linearize circular DNA molecules in vivo in Saccharomyces cerevisiae. From a basic science perspective, this tool offers a new way to study the effect of gene placement on chromosomes (i.e. telomere proximity), the essentiality of 3’ non-coding regions of genes, and the plasticity of gene order and chromosome structure on cell fitness. Commercially, this tool provides a flexible new strategy to aid in the construction and expression of large, non-native pathways in S. cerevisiae on supernumerary chromosomes. We demonstrate the function of the telomerator by circularly permuting synIXR, a synthetic yeast chromosome arm previously shown to power growth of a yeast cell as a circular DNA molecule. The resulting 53 permuted strains exhibit differential growth patterns, indicating telomerator-driven linearization is a new way to generate phenotypic diversity. In principle this technology can be extended to other eukaryotic organisms.

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Our ability to (re)design biological systems with complex response dynamics requires a better understanding of natural feedback control systems and the evolutionary processes that led to them. Here, we use tools from Control Engineering to investigate a number of possible design strategies for achieving perfect adaptation to perturbations. While integral feedback is well known to achieve robust adaptation, its biological implementation in a synthetic circuit is likely to be highly challenging. Simpler proportional control schemes might be easier to implement, but their ability to provide robust adaptation is limited. Inspired by studies on the molecular basis of osmoregulation, we explore the ability of an ultrasensitive proportional controller to achieve adaptive dynamics, and we discuss different biochemical architectures that can achieve such control. Ultrasensitivity can be biochemically implemented in a straightforward manner through various different mechanisms, including phosphorylation cycles and cooperative binding. Indeed, in the case of osmoregulation, the Hog1/MAPK pathway, which regulates glycerol production to achieve perfect adaptation, is well documented to be capable of high ultrasensitivity, since it employs a phosphorylation cascade. We first analyse the dynamics of a model with two proportional control loops, and show that it does not achieve robust adaptation, since the adaptation requires a careful tuning of the parameters. Addition of an integral control loop with a finite integration window (as would be implemented in any synthetic circuit) does not result in robust perfect adaptation. However, replacing the simple proportional controllers with ultrasensitive controllers results in a fast and robust adaptation to perturbations that does not require high feedback gains and does not produce large overshoots. Our analysis provides much needed insight into how synthetic biological control schemes could be designed using tools and ideas from feedback control theory.

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Higher alcohols ( C5) are promising for gasoline replacement as they have low hygroscopicity, high energy density and are compatible with transportation infrastructure. Linear and branched higher alcohols can be produced by engineered microorganisms expressing non-fermentative pathways [1,2]. Here, alcohols are biosynthesized in two steps: first, by decarboxylation of 2-ketoacids and second, reduction of the resulting aldehyde to alcohol. However, alcohols are toxic for microorganisms and improvement of cell tolerance do not increase production titers [3]. Therefore, other approaches, as feedback regulation systems and fine-tuning of pathway components are necessary for further optimization of alcohol production. To build such genetic constructs, regulatory elements orthogonally responsive to higher alcohols are mandatory. Previously, the alkB promoter (PalkB) was reported to be inducible by hexanol and heptanols but not butanol or propanol [4]. Thus, we investigated the suitability of PalkB as orthogonal responsive element using pentanol as proof of concept. We found that PalkB is not induced by metabolites like pyruvate, 2-ketoacids, aldehydes and amino acids, but a 40X fold induction was recorded for pentanol. Subsequently, we proceed with PalkB engineering in order to obtained variants with customized transfer functions. We constructed a synthetic combinatorial library of 78’125 promoter variants by variation of main promoter motifs. The library was cloned into a medium-copy plasmid and controlling GFP expression to allow readout. Then, a single-cell fluorescence sorting strategy was employed to specifically enrich and isolate hundreds of inducible variants. Finally, transfer functions were analyzed by flow cytometry and micro-fermentation. The resulting engineered promoters were able to span a wide range of strengths, inducibility ratios and more important, half maximal effective concentrations (EC50). [1] Atsumi et al. Nature. 2008. 451:86-9. [2] Zhang et al. PNAS. 2008. 105(52):20653-8. [3] Atsumi et al. Mol. Syst. Biol. 2010. 6:449. [4] Grund et al. J. Bacteriol. 1975. 123:546-56.

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Synthetic biologists engineer microorganisms using standardized DNA parts to achieve a desired behavior. Since the number of components that can be assembled into a single cell is limited, we sought to create a stable microorganism co-culture with defined, tunable proportions of two different cell types. Such a co-culture could be used as a “multicellular chassis” for synthetic biology. This poster presents work done largely by the Buenos Aires team participating in the 2012 International Genetically Engineered Machines (iGEM) competition. We designed a tunable co-culture of two auxotrophic budding yeast strains that feed the amino acids tryptophan (Trp) and histidine (His) to each other. Mathematical modeling identified the amino acid secretion rates as critical parameters to achieve growth and auto-regulation at fixed strain proportions. To implement the crossfeeding system we design and created four novel genetic devices, which code for secretable peptides rich in either Trp or His, with a cell penetrating sequence. Experimental validation showed that the devices could increase the Trp secretion rate and enable co-culture growth. Our amino acid crossfeeding devices show promise as a tunable standard tool for synthetic biology and for the quantitative study of mutualistic interactions between microorganisms.

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Targeting gene expression cassettes to specific cells is a prerequisite for gene therapy, regenerative medicine and, in our case, for gene dependent prodrug activation therapy (GDEPT). Viruses provide an evolutionary optimized source for gene ferries, yet they need to be tamed and tailored. Since a recombinant Adeno Associated Virus (rAAV) recently became the first gene therapy treatment recommended for approval, we foresee a broader application of such viruses for Synthetic Biology. We established a set of BioBricks enabling the modular assembly of recombinant Adeno-Associated viruses based on serotype 2. We demonstrated that fusion of binding molecules (DARPin, Affibody) to the viral capsid enabled selective targeting to tumor cells expressing surface markers (e.g. EGF-R). As genes of interest we delivered enzymes (CD, TK) activating prodrugs (5FC, ganciclovir). The natural tropism of the viral particle was reduced by capsid mutations. Introducing specific restriction sites flanking two capsid loop coding sequences permitted additional loop insertions, which we used for further modifications or the coding of purification tags. In various cell assays we analyzed and demonstrated the selective binding and killing of tumor cells. Precise gene delivery tools provide the opportunity to apply Synthetic Biology to living organisms and are particular valuable for healthcare.

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DNA oligonucleotides serve as highly customizable building blocks for the assembly of biobricks, large synthetic DNA fragments or whole genomes. However oligonucleotide synthesis technologies, whether producing one sequence at a time or large pools of multiple sequences, are prone to errors. Therefore current assembly methods require cumbersome sequence verification steps to correct for frequent synthesis errors. Here we present the advantage of using error-free oligonucleotides as starting blocks for de novo assembly of large DNA fragments. We have developed a method to produce collections of individually separated, error-free long oligonucleotides from massively parallel synthesis on chips. We demonstrated by deep sequencing that post purification, nearly 100% of the molecules recovered for each individual sequences are perfect. We also show that these error-free building blocks can be efficiently assembled into larger fragments and mitochondrial genomes. And with a size of up to several hundred bases, they can be considered as custom synthetic biological parts ready for integration into complex molecular circuitry. The availability of these inexpensive error-free building blocks will undoubtedly accelerate the pace of research to advance the field of synthetic biology.

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Biological systems exhibit exquisite spatial organization. Here, we propose to create synthetic structures based on DNA/RNA nanostructures to achieve greater levels of organization in vitro and in vivo. Such structures could potentially be utilized to scaffold metabolic enzymes, store molecular cargo, or even process information. Towards the first goal, we are expanding the range of temperatures and conditions under which single stranded tile (SST) DNA nanostructures can form isothermally. We are now capable of assembling SST structures across a wide range of temperatures and conditions, including biological conditions. In addition, we can modify structures to shift their assembly to specified temperatures. We aim to use DNA nanostructures to rapidly prototype RNA structures for eventual production in vivo.

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In vitro transcription and translation reactions can be programmed with DNA templates to produce networks of genetic regulators. In the classical batch format, however, network complexity and reaction time are limited because synthesis rates constantly decrease while precursors are consumed and products accumulate. To be able to produce genetically encoded oscillations during an in vitro transcription and translation reaction, we had to keep synthesis rates at a high level for extended periods of time and to remove reaction products. To achieve these goals we performed reactions in a continuous mode. Fresh reagents were added in short, regular time intervals into nanoliter-scale reactors on a microfluidic chip, where they displaced part of the old reaction volume. Simultaneously, mRNA and protein concentrations could be followed over time by fluorescence measurements. In our device mRNA and protein synthesis proceeded for over 24 hours at steady state. The system was highly predictable and controllable. We showed that it is possible to express a wide range of genetic regulators in our device including a RNA polymerase, transcription factors, RNA based regulators and a protease. In a continuous reaction mode, these genetic regulators can be combined into dynamic regulatory networks. This we demonstrated by constructing a transcription and translation based in vitro oscillator. Our device allowed us to tightly control synthesis and dilution rates to produce oscillations, which only occurred in a small range of the possible parameter space. Dynamic and more complex in vitro networks can be constructed using continuous reaction conditions. This approach will be useful for testing DNA constructs before they are introduced into cells. Furthermore, it raises the question whether there are any limits in the complexity of systems that can be implemented in vitro, and may ultimately allow the assembly of the cytoplasmic functions of an artificial cell.

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We use gene transformation techniques to produce useful materials for bioengineering. In using plants to produce useful materials, plant growth inhibition might reduce product yield, as a consequence of gene transformation. This transgenic growth inhibition might be avoided by limiting gene expression to a specific tissue type or phase of plant growth. For this reason we use appropriate control of gene expression to overcome product yield reduction. In this study we constructed web application and databases to design the synthetic promoter to control gene expression of any organism in a tissue or time specific manner (PromoterCAD). We collected genomic and transcriptomic data using the Semantic Web system LinkData/LinkDataApp, and developed applications to design synthetic promoters by novel arrangement of cis-regulatory elements. We made 4 types of expression-motif sequence data by combining 2 types of expression data (AtGenExpress, Diurnal) and 2 types of regulatory sequence motif (ATTED-II, PPDB). These include information on 21,000 genes from Arabidopsis and 1,410,000 microarray data measurements in 20 growth conditions and 79 tissue organs and developmental stages. The application provides a graphical user interface (GUI), so users can design promoters easily. Users select tissue and developmental stages and circadian expression conditions. Next, the application will provide appropriate motif sequences if users select tools picking maximum and minimum for expression data as well as phase and amplitude of circadian rhythms. Users will then achieve a designed sequence by replacing the original sequence with the motif sequences. Thus we could design the synthetic promoters, which increase production yields. Furthermore, Users can expand the scope of PromoterCAD with additional data including other plant and animal resources (e.g. tomato, mouse). We will present adding PLACE (Plant Cis-acting Regulatory DNA Elements) database, including multiple sizes of sequence motifs in SB6.0. PromoterCAD URL: http://promotercad.org LinkData URL: http://linkdata.org

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Transcription activator-like (TAL) effector proteins are naturally occurring transcriptional activators secreted by Xanthomonas spp. into their plant hosts. They are injected into plant host cells and travel to the nucleus where they bind to and activate specific promoter sequences, leading to changes that are permissive for bacterial infection. The deciphering of the TAL effector ‘code’ (repeat variable di-residues) recently led to the engineering of designer TAL effector proteins that could act as a vehicle to locate various functionalities to essentially any open region of the chromosomes of plants, bacteria, yeast, flies and mammalian cells. These tools will have applications from efficient genomic editing and gene knock-out to modulation of specific promoter activities in various species of cells. Here we present an industrial production platform for the synthesis of tailored DNA binding molecules that will allow researchers to choose the functionality they want and deliver it where they want. Designer TAL effector constructs coding for a TAL nuclease or activator are designed to bind a specific 18 or 24 base DNA sequence of choice. Gene activation and gene knock-out examples in mammalian cells illustrate the vast capability of this new genomic tool set.

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Oligonucleotide mediated allelic replacement is an efficient tool for bacterial genome manipulation (MAGE: Wang et al. Nature 460:894). Mutants with endogenous mismatch repair (MMR) system deficiency have been shown to be a beneficial background for oligonucleotide mediated allelic replacement, due to the increase of mismatch incorporation efficiency and unbiased mutation spectra. However, inactivation of the host’s mismatch repair system results in a dramatically elevated general mutation rate and therefore accumulation of unwanted background mutations across the genome. We present a novel strategy for mismatch repair evasion using temperature sensitive DNA repair mutants and a method for temporal inactivation of the mismatch repair protein complex in Escherichia coli. This method enables the transient suppression of DNA repair during mismatch carrying oligonucleotide integration, but allows normal mismatch correction during cell growth and electrocompetent cell preparation stages. This advanced technique further increases the precision of oligonucleotide mediated allelic replacement and enables more predictable cell programming.

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For the quantitative investigation of intracellular signaling and metabolic networks besides precise observa- tional techniques there is a need for perturbative tools featuring high spatiotemporal resolution and minimum invasiveness. Using genetically encoded photoreceptors, optogenetics offers these features. Based on the blue- light-sensitive YF1 histidine kinase (Mglich et al. JMB (2009) 385, 1433-1444) we implemented light-regulated gene expression in Escherichia coli. We have built two systems, pDusk and pDawn, facilitating suppression or activation of gene expression upon blue-light illumination in a dose-dependent manner, with high dynamic range and up to 460-fold induction, respectively. Furthermore pDusk and pDawn are realized on single plasmids and use a flavin-based photoreceptor, therefore offering good portability and independence of external chromophore supply. Both systems constitute valuable tools suitable for basic research as well as for recombinant protein production. Moreover they allow light control of single nodes of signaling networks to elucidate their function within the cellular context.

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Stages of cell differentiation are often illustrated as a sequence of events and chemical cues that move a cell from one state to another. Differentiated cells send and receive signals to compute functions on their environments and perform complex tasks such as pattern formation. Commonly used models of development in multicelled organisms are consistent with finite state machines as a natural language to specify and program multicelled behaviors. Consider a set of tools such as a library of customizable transcription factors, a collection of small molecules that can diffuse through cell walls, and programmable chemical kinetics. How is a multicellular behavior such as leader election, stripe formation, branching, or microcolony edge detection specified and compiled into a gene regulatory network? Here, we present a design method for implementing arbitrary finite state machines with gene regulatory networks. Adding to this result, we observe that coupling an implementation of finite state machines with growth, division, and cell-cell communication, a heterogeneous microcolony can implement Turing universal computation. When modeled as a Boolean network, gene regulatory networks composed only of constitutively expressed repressing transcription factors are sufficient to implement any finite state machine. We demonstrate this approach in simulation in gro (Jang, Oishi, Egbert, and Klavins, 2012) with leader election and microcolony edge detection examples, and finally with the automatic construction of a gene regulatory network that implements pattern formation as a Turing tape machine in a simulated growing microcolony.

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Homeostasis requires bacteria to adapt to different kinds of selective pressures. They must sense and quickly respond to a great variety of signals, which usually appear to be completely random. These responses are tightly regulated under a variety of situations depending on the initial stimulus. There is a particular kind of, apparently adaptive, regulations in which a gene (or a set of genes) pre-induce other response systems; this is the basis of the so-called predictive behavior in bacteria. This phenomenon arises from the predictability of some events, in which a first signal or stimulus unchains different pathways that prepare the molecular machinery of the microorganisms to face a violent upcoming change in its surroundings. The objective of this project is to design and engineer a synthetic gene circuit that shows predictive behavior. To achieve this, we developed a deterministic mathematical model which depicts and describes the necessary parts for the circuit to work as expected; then, based on the predictions of the model, two different circuits were proposed, built and tested using E. coli as a chassis. The difference amongst both circuits is the lack of a promoter in one of the genes involved. This detail triggered several new questions regarding the differences between the mechanisms of the responses on individual cells and on a population level. In order to answer these, a stochastic model based on the data acquired from the expression of both circuits will bring new details and will help to further understand the phenomena lying beyond predictive and adaptive behavior. This circuit can be used as a new tool in synthetic biology projects, since it shares features with some other well-known pieces such as the bistable switches, but aims to more specific responses in certain operational scenarios.

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The plasticity of the metabolic network makes microorganism-based biosynthesis of natural products a promising platform for rapid, efficient and highly versatile drug and commodity production. Reprogramming cells for these increasingly sophisticated applications requires the construction of customized multi-gene pathways and their introduction into host organisms. Moreover, the ability to create libraries of pathway variants in order to optimize function using directed evolution approaches is essential. Our DNA assembly system, “Reiterative Recombination”, employs endonuclease-induced homologous recombination in a cyclical format that allows for stepwise elongation of the construct of interest. Here, we exploit Reiterative Recombination as a straightforward and general technology for combinatorial mutagenesis of metabolic flux. We demonstrate preliminary results for the construction of terpenoid pathway in S. cerevisiae using Reiterative Recombination. Furthermore, we present progress towards the application of Reiterative Recombination to optimize metabolic flux for terpenoid production. Together these results establish Reiterative Recombination as a simple and powerful library mutagenesis technique and advance our efforts to engineer the cell for fully in vivo directed evolution. More broadly, our network-oriented experimental approach expands the toolkit available for engineering living cells toward the routine production of valuable natural products in yeast.

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A grand challenge in synthetic biology is to push the design of biomolecular circuits from purely genetic constructs towards systems that interface different levels of the cellular machinery, including signalling networks and metabolic pathways. We focus on genetic circuits for feedback regulation of metabolic pathways. The objective of this control circuit is to dampen the effect of flux perturbations caused by changes in cellular demands or by engineered pathways consuming metabolic intermediates. We consider a mathematical model for a control circuit with an operon architecture, whereby the expression of all pathway enzymes is transcriptionally repressed by the metabolic product. We address the existence and stability of the steady state, the dynamic response of the network under perturbations, and their dependence on common tuneable knobs such as the promoter characteristic and ribosome binding site (RBS) strengths. Our analysis reveals trade-offs between the steady state of the enzymes and the intermediates, together with a separation principle between promoter and RBS design. We show that enzymatic saturation imposes limits on the parameter design space, which must be satisfied to prevent metabolite accumulation and guarantee the stability of the network. The use of promoters with a broad dynamic range and a small leaky expression enlarges the design space. Simulation results with realistic parameter values also suggest that the control circuit can effectively upregulate enzyme production to compensate flux perturbations.

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The design and construction of synthetic biological systems demands managing a network of interrelated information (eg, parts data, assembly techniques). and, increasingly, software tools that use this information. These tools often perform steps along a workflow (eg, from design to physical assembly of a device). A proliferation of software tools that each solve one problem without awareness of other tools hinders users. Ways to move data between related formats, aggregate data relevant to a task, or move fluidly between tools in a workflow will be sporadically implemented without guarantee of interoperability. Our solution is Clotho 3.0, a new version of our platform for high-quality, interoperable applications. In version 3.0, data models are newly extensible, allowing developers to extend Clotho’s default model and add entirely new ones. 3.0 manages conversions between data formats to aggregate data from different sources. The new version also improves app management, enabling fluid workflows that span multiple apps and automating updates of installed applications and their dependencies. Alongside Clotho 3.0, we also present the Nona Foundation, a community incubator of open source synthetic biology software. These features enable biologists to incorporate agilely cutting-edge developments in techniques and information into their research. They help collaborators share apps and data without compatibility hassles. They allow bioinformaticists to instantiate their own database within Clotho and operate on it with new or existing apps. They prevent users expending excessive effort on maintaining their installations of software tools. By making it easier to write high-quality applications, Clotho means synthetic biologists will have more efficient, flexible tools available for their work.

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The mission of the multi-university Synthetic Biology Engineering Research Center (SynBERC) is to make biology into an engineering discipline. Alongside the development of technologies enabling the engineering of complex biological systems, the Center’s Practices Thrust aims to help evaluate and guide best practices and policies for synthetic biology, and biotechnology more broadly. To scale, sustain and tailor consideration of best practices, Practices programs aim to enable Center researchers and Partners in industry and government to identify and assume their roles and shared responsibilities for shaping biotechnology in practice.

Here we describe ongoing efforts in our Center to create and evaluate programs for researcher training and engagement in the societal ramifications of synthetic biology. We describe mechanisms employed to solicit researcher self-identification of interests and uncertainties surrounding the broader context of their work and developments in the field. We highlight researchers’ views on opportunities and challenges associated with anticipating and responding to the economic, political, and cultural milieu of synthetic biology. We describe activities designed to improve researcher education and leadership in practice and policy issues coupled to improved capacities to engineer biology – such as safety, security and intellectual property. Lastly, we discuss frameworks for evaluating these programs, including the extent to which they succeed – and fail – in improving biotechnology in practice.

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We present a unified optimisation framework for (a) the reconstruction and (b) the automatic design of biochemical reaction networks (BRNs) and gene regulatory networks (GRNs). Reconstruction, i.e., automatic inference of the dynamic equations of a BRN/GRN directly from its observed data constitutes one the major problems in systems biology. On the other hand, automatic design of a BRN/GRN capable of generating a desired dynamic behaviour specified in terms of a priori given time-series data constitutes one of the core problems in synthetic biology. Our optimisation formulation allows considering both problems in a unified mathematical framework. When dealing with BRNs/GRNs specific aspects need careful consideration. First, nonlinear time-delayed Ordinary Differential Equations (ODEs) that involve polynomial and rational functions are typically used to model BRNs/GRNs. Second, the resulting optimisation problem is generally nonconvex, meaning that several suboptimal solutions co-exist and that finding the optimal solution is algorithmically very expensive (NP-hard). Third, prior knowledge typically needs to be incorporated under the form of equality or inequality constraints such as positivity of the species numbers/concentrations and of certain parameters. Finally, typically, the dynamical behaviour of only a few species of the BRN/GRN can be measured/predefined whereas the remaining species defining the BRN are “hidden”. To deal with all the aspects mentioned above, we show how the original optimisation problem can be relaxed into a family of convex optimisation problems. Unlike sampling-based algorithms, our proposed framework has several advantages. It allows for efficient computation of the solution of large-scale BRNs/GRNs reconstruction/design problems (in polynomial time), provides near optimal solutions to the original optimisation problem, and is much less sensitive to optimisation initial guesses. The framework is illustrated on the reconstruction of a simple synthetic GRN (the repressilator), and on the automatic design of GRNs exhibiting desired time-series behaviours (perfect adaptation).

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Many nonferrous industries such as mining and surface treatment plants produce co-products that are high in heavy metals and therefore toxic to the environment. A less obvious producer of heavy metal co-products is the whisky industry. Current methods of copper removal from such co-products include electrolysis and membrane filtration which are reported to be impractical and costly. Alternatively, when copper is found as a salt, current methods of removal include settlement, filtration and precipitation. Biological copper ion removal from effluents has been shown to be quite effective.

There are two biological methods to remove copper from effluent which involve biosorption and reduction. Biosorption involves bacteria binding to copper via the cysteine-rich transport proteins that are associated with the cell membrane to precipitate it. Some bacteria are also able to reduce higher valency insoluble copper ions into lower valency insoluble forms of the metal. An example of such a bacterium is Thiobacillus ferrooxidans which is able to reduce Cu²⁺ to Cu⁺ using SFORase. The Cu⁺ ions can then be mixed with a compound to produce an insoluble salt which precipitates and can easily be removed.

Although T. ferrooxidans is able to reduce copper to a lower valency state, it is slow growing with a replication time of 5.2 hours which makes it not very ideal for industrial use. Therefore it is possible to transfer these genes to a faster growing organism such as E. coli using synthetic biology techniques. There is also the possibility to improve the copper reduction effectiveness by modifying the genes responsible for this process. This will potentially yield an organism that is both fast growing and able to reduce copper to an insoluble form in order to precipitate it from solution.

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The genomic stability and integrity of host strains are critical for the production of recombinant proteins in biotechnology because genomes of such microorganisms contain numerous insertion sequences (ISs) that cause a variety of genetic rearrangements, resulting in adverse effects such as instability of genomes and recombinant clones. To minimize the harmful effects of ISs on the expression of recombinant proteins in Escherichia coli, we recently developed an IS-free minimized E. coli strain (MS56) in which all ISs and many unnecessary genes were removed from the E. coli MG1655 genome. Here, we compared the expression profiles of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and bone morphogenetic protein-2 (BMP2) in MG1655 and MS56. The hopping of ISs (IS1, IS3 or IS5) into the genes encoding TRAIL and BMP2 occurred at the rate of ~10-8/gene/h in MG1655 whereas no IS hopping was observed in MS56. Even though IS hopping occurred very rarely (-10-8/gene/h), the IS-inserted TRAIL and BMP2clones became dominant in 28 h, significantly reducing recombinant protein production in batch fermentation. Cells harboring IS-inserted clones grew much faster than the IS-free clones. Our findings clearly indicate that IS hopping is detrimental to the industrial production of recombinant proteins and that the development of IS-free host strain (MS56) is highly desirable for the production of recombinant proteins.

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For rapid and accurate quantitation of recombinant proteins during expression and after purification, without a large metabolic burden on host cells, we introduce a new tagging strategy that expresses both target proteins and limitedly tagged target proteins together in a single cell at a constant ratio by utilizing cis-elements of the programmed -1 ribosomal frameshifting (-1RFS) as an embedded device. The -1RFS is an alternative reading mechanism that composed of two relatively small RNA sequences, a slippery sequence and a downstream RNA secondary structure. This unusual translational mechanism effectively controls protein expression in many viruses. In this study, when a target gene is fused to the green fluorescent protein (GFP) gene with a -1RFS signal implanted in between, the unfused target and the target-GFP fusion proteins are expressed at a fixed ratio. The expression ratio between these two protein products is easily adjustable simply by changing ­1RFS signals. Our result demonstrates that this limited-tagging system was useful for the real-time monitoring of protein expression when optimizing expression condition for a new protein, and in monitoring large-scale bioprocesses. Thus, this new tagging method could open to a variety of applications. For example, this strategy allows direct measure of the quantity of a protein on a chip surface and easy application to proteome-wide study of gene products. This work was supported by the National Research Foundation (NRF) grant (grant no. 2012R1A1A2007721).

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Modularity is one of the hallmarks in the engineering world, as it enables the composition of systems with predictable behaviour upon interconnection of a set of quantitatively characterized components. Synthetic Biology aims to construct novel biological functions by following a bottom-up design approach. Although standard measurement approaches were proposed to facilitate the characterization of parts and the sharing of the resulting quantitative information via datasheets, real modularity is still a major issue and a number of factors may impair the predictability of the designed system (e.g. intrinsic biological noise and cell overburdening). In order to exploit the whole potential of Synthetic Biology in the bottom-up construction of biological circuits, its modularity boundaries must be discovered. Here, model systems were used to test the modularity of different biological input devices when interconnected upstream of a fixed output device in a genetic circuit incorporated in Escherichia coli. If modularity persists, when the input modules produce identical signals the output device should produce identical signals, even if the input modules are structurally different. Three input systems were used: 1) a set of constitutive promoters of different strengths, 2) an IPTG-inducible promoter and 3) an HSL-inducible device. These modules provide a transcriptional signal that drives the output device, which is a tetR-based logic inverter. First, input modules were individually characterized via RFP. Then, they were assembled upstream of the inverter and GFP was used to characterize the output of the interconnected systems. The resulting static characteristics were analyzed to experimentally evaluate the modularity of the used components. The logic inverter was re-used to construct a cold-inducible system by interconnecting a pre-characterized heat-inducible device upstream. The transfer functions of the devices well-predicted the experimental output of the constructed circuit. Temperature-dependent behaviour of the used components was tested and dynamic performance was investigated.

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Several synthetic metabolic pathways for butanol synthesis have been reported in Escherichia coli by modification of the native CoA-dependent pathway from selected Clostridium species. These pathways are all dependent on the O2-sensitive AdhE2 enzyme from Clostridium acetobutylicum that catalyzes the sequential reduction of both butyryl-CoA and butyraldehyde. Although the AdhE2 pathways are capable of producing high titers of butanol they are limited to one carbon source only, glucose. The aim of our research was to develop a modular, oxygen-independent, synthetic pathway which would be active in both Escherichia coli and in photosynthetic organisms, like cyanobacteria. Engineering cyanobacteria to fix CO2 as a carbon source for butanol production instead of glucose, would deminish the needs of using a valuable food source for fuel production. To achieve this, we have combined a selection of bacterial acyl-ACP-thioesterases with carboxylic acid reductase in order to construct a novel oxygen-tolerant butanol-pathway. The thioesterase that resulted in the greatest yield of butanol was studied further in comparison with a previously established reference pathway that is CoA-dependent. The yield of butanol from the ACP-dependent pathway module was stimulated by enhanced O2-availability and co-expression with aldehyde reductase. A product titer of 300 mg/L was obtained under optimal batch growth conditions in E. coli, exceeding the performance of the reference CoA-pathway when evaluated under equivalent conditions. Preliminary experiments using cyanobacteria indicate that the transfer of the pathway module has influenced the metabolism of alkanes rather than alcohols. This illustrates the complexity of pathway transfer from one host to another.

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Bacteriophage P4 is a peculiar organism that presents an unusual wide infection-range that includes E.coli, different pathogens among enterobacteriacea, P.putida and S.meliloti. Our curiosity focuses on the elements that allow this phage to infect different species and how to increase or control that ability. For this project we propose to apply Synthetic Biology principles to generate resources that make easier the study of this phage, its control, construction of redesigned versions, and their biotechnological application. Initially, we built a database with all the information available about P4 and its genetic elements. Using this, we selected useful elements to standardize them and assembly engineered versions of P4 (eP4) entirely from biobricks. We pretend to develop a collection of eP4 variants to study the elements involved on giving P4 a wide infection-range, and also to explore strategies to enhance or limit this characteristic. Furthermore have designed an E.coli strain adapted as an in vivo system specialized on eP4 production. We encourage these resources as a platform to study distinct aspect of P4 and its elements with a different perspective, by building them. Similarly this platform will be useful to design, construct and produce standardized versions of P4 that can include different Synthetic Genetic Systems based on biobricks (SGS). Another application of eP4 phages is like a DNA vehicle to easily mobilize SGS from E.coli into a bigger group of bacteria species than the natural infection-range of P4-WT. Since that group includes species of medical and biotechnological relevance, we expect this project to be useful also in the renascent area of phage therapy, by providing a standardized phage with an adjustable increased infection-range and adaptable to carry SGS from just 3-kbs to up to 30-kbs.

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For many in the Western world we have grown accustomed to ordering oligonucleotides and complex custom genes relatively simply and cheaply from gene foundries. But even in the UK, where the nearest foundry lies across the Channel, turnaround times are unnecessarily long and Brits generally pay pound for dollar on their constructs due to high transaction costs and import tariffs. For those in emerging markets, the problem is compounded. Thai biotech organisations currently pay Malaysian foundries 60 cents/base pair for oligonucleotides (>1 week delivery) and pay 3x what we do for PCR reagent kits and enzymes (also taking several weeks). Gene synthesis costs more than a dollar/base pair and the costs and timeframes for sequencing are similarly unacceptable. It seems the dominance of gene foundry models in the West cannot easily be translated onto the rest of the world. In emerging markets, it is thus much harder to make DNA a commodity in the same way that it is becoming one in our own. Nonetheless, we all generally agree that synthetic biology has a vast potential to positively impact international development and provide emerging economies with access to key resources that they currently lack. But where it is needed the most, there are barriers far too high for significant technological momentum to be generated. Indeed, it is not the technological limitations surrounding gene synthesis that matter the most here, but the combined social, economic, and even political bottlenecks that have been built around this technology. I therefore suggest that emerging markets, with their smaller synbio budgets and limited accessibility stand to benefit greatly from a decentralized synthesis model, wherein gene-manufacturing capabilities are widespread. This will be a bold but necessary step in making synthetic biology accessible to the entire world and not just to well-funded groups in the West.

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The past decades pointed out RNA has alot of functions besides being an information carrier (mRNA). Small RNAs (e.g. antisense RNA) form an essential part of different prokaryotic regulatory mechanisms by, for example, blocking the ribosome binding site (RBS). As such sRNA can be used in synthetically constructed biological devices to silence a gene on demand. Tools and know how for model-based design of RNA molecules that efficiently block the RBS of a specific gene are however still underdeveloped. Here we present a method to design silencing modules that can efficiently block the translational process. This approach uses knowledge on antisense RNA to model the physical nature of this biological interaction. The available literature was used to identify potential characteristics of a good silencing sequence. Based on this information a bioinformatics framework was developed to enable a computational characterization of a potential silencing sequence. Herein, several dynamic programming algorithms are used to accurately predict these RNA-RNA interactions. The influence of the different defined features of the candidate sequences, which were semi-rationally generated and send through a preliminary in silico filter, was investigated. The performance of a group of selected candidate sequences are tested in vivo to determine their silencing capacities. As a test case, mRNA containing a red fluorescent protein was constructed using biofab parts. Based on these results the importance of the features is evaluated. Ultimately, this computational approach can be used for the design of tailor made silencing modules with excellent performance.

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Here we report the design of synthetic adhesins for E. coli that allow an effective and controlled adhesion of bacteria to antigenic surfaces and specific cells in vitro and in vivo. The synthetic adhesins have a modular structure composed by an adhesive immunoglobulin domain of defined specificity and an outer membrane anchoring domain obtained from a engineered member of the the Type V secretion system (T5SS). We have generated synthetic adhesins against different antigen targets, expressed them stably and constitutively from the chromosome of E. coli, and demonstrate that bacteria carrying them show specific adhesion to abiotic surfaces coated with the cognate antigen and to mammaliam cells expressing the corresponding antigen on their surface. We have shown the potential of the synthetic adhesins for targeting E. coli to specific cell types (infected and tumor cells) using in vitro and in vivo models.

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Cyanobacteria are promising “low-cost” cell factories since they have minimal nutritional requirements and high metabolic plasticity. The unicellular non-N2-fixing cyanobacterium Synechocystis sp. PCC 6803 is the best studied strain and the vast amount of physiological and molecular data available already allowed the construction of computational genome-scale metabolic models [1]. Moreover, a previous work from our group reported the construction of a Synechocystis chassis prone to receive synthetic devices primarily designed for hydrogen production [2]. Within this work, five neutral sites were identified and characterized to stably integrate ectopic DNA into the chromosome, foreseeing the use of Synechocystis as a photoautotrophic chassis in biotechnological applications. The neutrality of the sites was evaluated by producing and analyzing deletion/insertion mutants, and their functionality was assessed introducing a synthetic device expressing the reporter green fluorescent protein. Moreover, integrative vectors including a multiple cloning site compatible with the BioBrick RFC[10] standard and insulated by transcription terminators were constructed, constituting robust cloning interfaces for synthetic biology purposes. Synechocystis mutants (chassis) ready to receive purpose-built synthetic modules/circuits are also available. References: [1] Montagud A et al. (2010) BMC Syst Biol 4:156. [2] Pinto F et al. (2012) Microbiology 158:448-464.

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The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICE) is an open source registry platform for managing information about biological parts. It is capable of recording information about ‘legacy’ parts, such as plasmids, microbial host strains and Arabidopsis seeds, as well as DNA parts in various assembly standards. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access and interaction with the platform via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. Starting with version 3.3, ICE also includes a distributed software platform to enable the efficient sharing of composable biological elements across labs in the synthetic biology research community, thus expanding the search space of biological constructs. It offers community collaboration capabilities and opportunities which enable scientists to publish and share their data sets. Advanced security mechanisms are also in place to restrict access to particular data sets that researchers are not yet ready to share with the wider community or will prefer to keep private or restricted to a smaller group. The software also enables defining and managing members of these groups. This Web of Registries infrastructure is constructed to be compatible with existing and emerging computer-aided design tools for synthetic biological systems. JBEI-ICE has been adopted as the registry platform in multiple research labs and institutions including Synberc, PlantFab (Cambridge) and JBEI. A public instance is also available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects.

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The interest in designing gene networks able to carry out simple tasks in a predictable way is becoming critical in the field of synthetic biology. Borrowing ideas from control systems theory, a genetic circuit which aims at maintaining a constant concentration of a signalling molecule, 3-oxohexanoyl-homoserine lactone (3OC6-HSL), was designed and implemented in E. coli-MG1655 Z1 liquid cultures. The system exploits the well-known mechanism of quorum sensing, used by the marine bacterium Vibrio fischeri to activate genetic pathways in a density-dependent manner. A bottom-up approach, based on mathematical modelling and characterization of basic parts composing the system, was used. The model includes promoters activation, enzymes production and degradation, enzymes activity and cell growth. In particular, PTetR (BBa_R0040, an anhydrotetracycline sensitive promoter) was chosen as the input of the circuit; it is responsible for the transcription of luxI, which encodes for an enzyme able to produce 3OC6-HSL. The PLux promoter (BBa_R0062) was placed upstream of aiiA, the coding sequence of a lactonase (i.e. an enzyme degrading 3OC6-HSL), so that, in the presence of a sufficiently high concentration of the signalling molecule, the transcription of aiiA occurs. In this way the system is able to self-regulate the concentration of 3OC6-HSL. First promoters activation functions were characterized, using the Red Fluorescent Protein (RFP) and varying the Ribosome Binding Site (RBS) efficiency. Then, driving the transcription rate of the genes encoding for the two enzymes through PTetR, the parameters representing the production and degradation of 3OC6-HSL were identified. In silico simulations were performed and compared to experimental data from batch culture tests: although the mathematical model well-predicts the steady state value of 3OC6-HSL concentration, it shows faster dynamics than the in vivo-implemented genetic circuit.

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Synthetic biology has roots in industrial biotechnology and, apart from toy examples used as proof-of-principle, most of the examples of engineered systems will produce commercialisable products such as biofuels, pharmaceuticals, novel materials, or other high-value added products. Successful scale up of synthetic organisms will be required to realise the economic potential of synthetic biology and tools that would aid in the development, scale up or manufacturing processes would have a great impact on the field. The ability to tailor organisms for the synthesis of useful products also allows the ability to input genetic circuits that can be used to report the internal state of the cell. Genetically encoded biosensors are potentially a very powerful strategy for bioprocess development where sample sizes can be very limited and non-invasive monitoring techniques can vastly improve high throughput screening strategies. We are interested in using biosensors based on Frster Resonance Energy Transfer (FRET) as ultra-scaled down assays for bioprocess development, medium formulation, and cell line engineering. Our recent work aims to identify good biochemical targets for online monitoring as well as develop FRET sensors for these metabolites. We believe that FRET sensors for basic metabolites can be used to predict more complex phenotypes, particularly when coupled with in silico metabolic modelling.

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Accurate characterisation of genetic control elements is essential for the predictable engineering of synthetic biology systems. Real-time evaluation of biological parts like promoters, riboswitches and ribosome binding sites enables design of customised gene expression and the balancing metabolic pathways. The current standard for in vivo characterisation of control elements is through the use of fluorescent reporter proteins such as GFP. However, gene expression is a multi-step process, specifically with RNA production as a key intermediate. The ability of the Spinach RNA aptamer to mimic the characteristics of the GFP protein; bypasses several disadvantages and limitations of older RNA measurement methods and provides information about the translational efficiency and transcriptional strength of several control elements when the aptamer is used in the context of an ORF.

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Synthetic biology is enabling new applications for cellular engineering, and with this comes a growing need to focus on biosafety for responsible containment of engineered organisms. We are taking a novel approach to address this concern by engineering an E. coli strain that is dependent on an inexpensive, synthetic small molecule for cell survival to create a ‘synthetic auxotroph’. Previous research has shown that indole-dependent allosteric control can be engineered into enzymes by mutating a buried tryptophan residue to glycine and rescuing protein function with indole. We utilized this strategy to identify sensitive sites in the protein core of homodimeric essential gene products to serve as a starting point for further engineering into a ligand-binding pocket. Candidates that displayed a disruption of dimerization upon tryptophan to glycine mutation and rescue in the presence of indole were subjected to saturation mutagenesis of neighboring residues to generate a ligand binding pocket library. Negative and positive selection systems based on the lambda repressor two-hybrid system were constructed and coupled with deep sequencing to identify library members which dimerize only in the presence of a synthetic small molecule of interest. With an essential protein that is dependent on a small molecule for proper protein folding and function, we can engineer a bacterial strain that is dependent on rescue with a synthetic chemical for survival.

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Equal partitioning of bacteria at division is vital to many cellular functions and critical to engineering reliable biological behaviours. E. coli implement a simple self-regulatory mechanism to ensure precise division. The principle behind this mechanism is yet to be explained in literature. Herein, we explore the fundamental principles of the primary protein system (Min system) responsible for the underlying spatial-temporal dynamics. In contrast to existing complex stochastic simulations, we propose a nonlinear deterministic model that is simple yet capable of reproducing the observed behaviours. Random parameter space sampling and cluster analysis is subsequently used to identify parameter combinations that reproduce the observed behaviours robustly. A series of time-lapse microscopy experiments is designed to verify the model using two different E. coli strains expressing GFP-MinD fusions. Computational algorithms are developed to estimate intracellular protein oscillations and the precision of protein partitioning at division. Future work aims to apply the simple model trained on the experimental data to tune the precision of protein partitioning and to use the mechanism to regulate partitioning errors of other proteins fused to the Min proteins.

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Synthetic biology of multicellular organisms is extremely challenging due to their high genetic complexity and the difficulty of manipulation of the tissues. The liverwort Marchantia polymorpha (Marchantia) is a simple plant with a haploid genome and low genetic redundancy. The early embryonic stages of this organism are accessible for live imaging and there is no need to perforate a seed coat to visualise them. Marchantia offers the added benefit that the cells on the surface and their progeny can be easily observed and tracked without the need for clonal markers during early embryogenesis. The procedure for genetic transformation [1] of this plant is much faster than that of Arabidopsis thaliana (Arabidopsis), as it only takes 7 days to obtain transgenic plants and an additional 5-10 days to screen transient mutants with fluorescent reporters and antibiotic selection. This period of time is much shorter than the minimum 2 months required to obtain transgenic Arabidopsis plants. This organism is also very easy to manipulate and ideal for labs that wish to start to do synthetic biology in plants without prior experience. Therefore, it has the advantages of being a multicellular chassis that has an analogous simplicity to that of microbes. This project provides a detailed cellular characterisation of the organism through the application of high throughput imaging (laser scanning confocal microscopy) with fluorescent proteins to mark subcellular structures; combined with segmentation techniques for detailed analysis of cell geometry [2]. We are also transferring existing genetic markers from Arabidopsis into Marchantia for the purpose of future mapping and characterisation of cellular domains for engineering. [1] Ishizaki K, Chiyoda S, Yamato K, Kohchi T, Plant and Cell Physiology, 49:1084-1091 (2008) [2] Federici F, Dupuy L, Laplaze L, Heisler M and Haseloff J, Nature Methods, 9:483-485 (2012)

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The widespread use of caffeine (1,3,7–trimethylxanthine) and other methylxanthines in beverages and pharmaceuticals has led to significant environmental pollution. We have developed a portable caffeine degradation operon by refactoring the alkylxanthine degradation (Alx) gene cluster from Pseudomonas putida CBB5 to function in Escherichia coli. In the process, we discovered that adding a glutathione S-transferase from Janthinobacterium sp. Marseille was necessary to achieve N7-demethylation activity. E. coli cells with the synthetic operon degrade caffeine to the guanine precursor, xanthine. Cells deficient in de novo guanine biosynthesis that contain the refactored operon are “addicted” to caffeine: their growth density is limited by the availability of caffeine or other xanthines. We show that the addicted strain can be used as a biosensor to measure the caffeine content of common beverages. The synthetic N- demethylation operon could be useful for reclaiming nutrient-rich byproducts of coffee bean processing and for the cost-effective bioproduction of methylxanthine drugs.

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The Synthetic Biology Open Language Visual (SBOL Visual) project is an effort toward developing a community-driven open standard for visual representation of genetic designs. Standardized visual notation for communicating designs has proven to be useful in many engineering disciplines. A de facto visual notation does exist in synthetic biology; however, it is incomplete, is often extended ad hoc, and exists as a poorly defined, voluntary, communal convention rather than an explicit standard. Because synthetic biology endeavors often require a multidisciplinary team, a common visual system of communication with well-defined semantics is vital. It is also important that the emerging ecosystem of biological design tools converge upon a common visual language to maximize adoption and minimize ambiguity in results. Given the central role and rich history of visual representation in the life sciences, a well-defined visual notation will also prompt the construction of the formal infrastructure needed to support effective ontologies, meaningful models, and tools tailored to community needs. SBOL Visual comprises a set of symbols used to visually depict functional information encoded by nucleic acid sequences. SBOL Visual is presently being used by synthetic biologists to depict genetic designs in peer-reviewed publications and presentations. Software developers in academia and industry are using SBOL Visual in their computer-aided design tools for synthetic biology. In addition to specifying a symbol set, we initialize a framework for supporting the synthetic biology community’s involvement in growing and maturing SBOL Visual. While the symbols specified in the current version of SBOL Visual are drawn from the de facto visual notation of the synthetic biology community, SBOL Visual must ultimately be community driven if it is to meet the needs of synthetic biologists. Through active input from the synthetic biology community, SBOL Visual will mature into a foundational tool for the communication of genetic design.

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In a relatively short time, synthetic biology has transitioned from construction of circuits that control isolated cellular functions to designing modules for population synchronization to be used in bio-technological applications. Nevertheless, there are very few initiatives working on circuits that can function at the level of microbial communities involving inter-species and inter-kingdom communication. The present work leads to the design of synthetic oscillating circuits in order to control the production of the 3oxo-C12 homoserine lactone, which is part of the Pseudomona aeruginosa quorum sensing system and is an important modulator of virulence factors in Burkholderia cepacia and of dimorphism in Candida albicans, to mention some examples. We have constructed circuits with standardized “Biobrick” parts that allow the spatial-temporal production and degradation of the mentioned signaling molecule. Additionally, our design seeks to create a system that does not depend on the exogenous flux of inductors, in order to be self-sustainable in vitro, and that it might be tunable through the assembly of other oscillating circuits such as “the repressilator”. Our design aims to be a module that allows the control of C. albicans filamentous growth without the virulence factor induction in bacteria.

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Science gamification uses games in order to promote education, science communication and awareness raising. Its goal is to encourage people to engage and learn about particular technological and scientific developments in an educational and entertaining context. Scientific games can either have the potential for real research findings (e.g. Foldit), simulating real-life outcomes, and serve as means of science communication. They can create a funny learning environment, provide freedom to choose the level of complexity depending on the player’s background, help to adopt new technologies as soon as they appear and create positive competition among the users, which may facilitate solving a specific problem. However, some challenges should be addressed as well: each game must be tailored to a certain audience; they should not be oversimplified or overcomplicated; present an adequate learning curve and avoid misinterpretation by the users. We report (and live demonstrate) the design of a new educational synbio mobile game called „Synmod“ about the modular construction of new-to-nature Lantibiotics (a class of peptide antibiotics that contain the thioether amino acid lanthionine) by means of synthetic biology.

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Standardized and well-characterized genetic building blocks allow the convenient and reproducible assembly of novel genetic modules and devices. During the iGEM competition 2012, the team LMU-Munich initiated the development of the BacillusBioBrick Box (B4) – containing vectors, promoters, reporter genes and epitope tags for the Gram-positive model bacterium Bacillus subtilis – which has now been fully evaluated. We developed five BioBrick-compatible vectors by deleting unnecessary parts and removing forbidden restriction sites to allow cloning in BioBrick (RFC10) standard. Three empty backbone vectors with compatible resistance markers and integration sites were generated, allowing the stable chromosomal integration and combination of up to three different devices in one strain. In addition, two integrative reporter vectors, based on the lacZ or luxABCDE cassettes, were BioBrick-adjusted, to enable -galactosidase and luciferase reporter assays, respectively. Six constitutive and two inducible promoters were thoroughly characterized by quantitative, time-resolved measurements. Together, these promoters cover a range of four orders of magnitudes in promoter strength, thereby allowing a fine-tuned adjustment of cellular protein amounts. The dynamic range of four codon-optimized reporter genes (gfp, mKate2, lacZ and luc+) was evaluated with inducible promoters. Moreover, the suitability of GFP and mKate2 as protein tags was verified by N- and C-terminal protein fusions that were analyzed by fluorescence microscopy. Finally, the BacillusBioBrick Box also provides five widely used epitope tags (FLAG-, His10-, cMyc, HA-, Strep-), which can be translationally fused N- or C-terminally to any gene of choice. Three reporter genes (gfp, mKate2, and lacZ) and the tags are provided in BioBrick (RFC10) and Freiburg (RFC25) standard, to allow the construction of transcriptional and N-/C-terminal translational fusions. For N-terminal fusions, these parts are provided with optimized ribosome-binding sites. We believe that our well-document and carefully evaluated BacillusBioBrick Box represents a very useful genetic tool kit, for iGEM and beyond.

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Alkanes are the major constituents of gasoline and jet fuel and the demand for alkanes as biofuels is ever increasing. However, the conventional alkane production process based on expensive raw materials (coal, hydrogen and cobalt) increases the overall cost of alkanes. To meet the growing demand for alkanes, efforts have been made to engineer microbial systems for the economical production of alkanes. Nevertheless, the microbial productions of alkanes are far below our satisfaction. To screen and select the high alkane-producing strains with rational engineering and/or directed evolution, a high-throughput strain selection method is needed. Here, we construct an artificial circuit for the selection of high alkane-producing strains. An alkane sensor plasmid (pALK) was constructed, which consists of an alkane responsive promoter, PalkB, a transcriptional regulator of Alcanivorax borkumensis, AlkS, and a green fluorescence protein, GFP as a reporter. In the presence of alkanes, the circuit is turned on by the release of AlkS from the regulatory region of the PalkB promoter. To observe the response of the PalkB promoter to alkanes, Escherichia coli harboring pALK were supplemented with various kinds of alkanes (e.g., C13, C15, and C17) with concentrations ranging from 10 to 100 ppm. The fluorescent intensities increased accordingly with increasing alkane concentration, which means that the alkane sensitive promoter responded in a concentration-dependent manner. For the detection of alkanes produced by engineered strains, the pALK was co-transformed with alkane-producing plasmid (pET-acr-adc) in E. coli. With our artificial circuit, high alkane-producing strains could be screened successfully. Our results suggest that pALK could be used as a reliable tool for the rapid screening of high alkane-producing hosts and to facilitate the process of rapid strain development.

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The ability to engineer biological circuits and organisms for biomedical and technological applications is one of the key goals of synthetic biology. Constructing synthetic biological systems via genome engineering requires efficient and precise tools for manipulating genetic information and regulation. The currently available genome editing systems – designer zinc fingers, transcription activator-like effectors, and homing meganucleases – each have made enormous progress towards this end yet have unique limitations; there remains a need for tools that are easy to assemble, affordable, and amenable to multiplexed gene editing. The type II CRISPR (clustered regularly interspaced short palindromic repeats) loci found in bacteria function as an adaptive immune system that uses a pair of non-coding RNAs, crRNA and tracrRNA, to guide the Cas9 nuclease for site-specific DNA cleavage, presenting a simple, RNA-programmable system that can be harnessed to mediate genome editing in mammalian cells. We engineered two type II CRISPR systems from Streptococcus pyogenes SF370 and S. thermophilus LMD-9 through heterologous expression of the key protein and RNA components in mouse and human cells. We show that Cas9 nucleases can be guided by custom RNAs to introduce double stranded break (DSB) at multiple endogenous loci with high efficiency (up to 59%). Furthermore, we have engineered Cas9 into a nicking enzyme to minimize mutagenic DNA repair processes while maintaining the ability to facilitate template-directed homologous recombination for gene insertion or modification. Finally, we have encoded a pair of guide sequences into a single CRISPR array to direct simultaneous editing of multiple sites within the human genome. This technology will enable applications across basic science, biotechnology, and medicine, as well as allow scalable and iterative optimization of designer, multi-component biological systems.

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Thermophilic microorganisms have many advantages for bioprocessing, however tools for their genetic manipulation remain under-developed. We employed a synthetic biology approach to the production and characterisation of promoters and other biological parts in order to expand the genetic tool kit for Geobacillus themoglucosidans. This will allow future rational engineering of the organism for improved biofuel and chemical production from renewable cellulosic feedstocks. Several constitutive and inducible promoters were characterised and a constitutive promoter library was produced. Thermophilic fluorescent reporters were investigated to enable rapid characterisation. With this toolkit we aim to make Geobacillus the premier chassis choice for thermophilic synthetic biology.

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Conceptually, clinical chemistry progressively transformed from mainly an analytical science, through inputs from information technology and now through the emerging synthetic biology with its strong engineering character. Metabolomics is a biotechnology that may contribute to these developments. Its relationship with synthetic biology is still in its infancy (Oldham et al. 2012, PLoS ONE, 7 (e34368), 1-15), but it is clearly a growing relationship (Ellis and Goodacre 2012, Current Opinion in Biotechnology, 23, 22-28). Here we present our views on the implications for synthetic biology of knowledge that we generated through metabolomics investigations of inherited metabolic diseases (Reinecke et al. Metabolomics, 8, 264-283) and their treatment through interventions (Dercksen et al. Metabolomics – In press DOI 10.1007/s11306-013-0501-5). Our investigation included a new bio-statistical application of concurrent class analysis which disclosed different metabolic patterns encapsulated within the data sets that would not have been revealed by using only the conventional modes of multivariate analysis. Moreover, the investigation was done on patients carrying the same homozygous c.367 G>A nucleotide change in exon 4 of the gene for isovaleryl-CoA dehydrogenase. These individuals, however, showed clear phenotype diversity, including diversity in response to treatment. The detection of informative metabolites of even very low concentrations in the patient group highlights the potential advantage of the holistic mode of analysis of diseases through a metabolomics approach. This knowledge is not peripheral to potential applications of synthetic biology in health and disease. A prerequisite of any design process envisaged to produce beneficial artifacts aimed at improved personalized medicine should conspicuously take the complex genotype-phenotype relation into account, as indicated by this illustrative investigation, informing also on the societal and ethical debate affecting the application of synthetic biology and related bio-technologies (Jochemsen and Reinecke, 2011, In: From technological transfer to intercultural development, ISBN 978-1-920383-28-2, p. 51-65).

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The quantitative movement and binding properties of genetically engineered systems of proteins are difficult to predict. Thus, it is difficult to choose parameters such as binding constants and attachment geometries in creating high-level design specifications for a synthetic-biological system. To address this issue, we have developed a constrained Brownian dynamics simulation framework that operates on simplified models of protein systems, with the goal of performing long time scale simulations. The behavior of a simulated protein system is determined by integrating Newton’s equations of motion in time without inertia, with Brownian forces and fluid drag, and subject to constraints on excluded volume, relative positions and protein-protein binding interactions. Proteins are abstracted as rigid spheres, with binding surfaces defined radially within them. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20kD proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. These specific results have implications for the design of targeted fusion proteins. More broadly, the simulation framework described here can be extended to include more detailed system features such as non-spherical protein shapes, electrostatics, etc., without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.

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The rational design of cellular factories for industrial biotechnology aims to create optimized organisms for the production of bulk chemicals, pharmaceuticals, food ingredients and enzymes, among others. Metabolic engineering (ME) plays a key role in this process, supported by the latest advances in genetic engineering in combination with computational tools to define targets for strain improvement. OptFlux is an open-source reference computational platform for the optimization of cellular factories by the application of in silico ME methods, designed for non-computational experts by providing a user-friendly interface. It allows to load genome-scale models from several sources to be used in the prediction of cellular behavior and identification of metabolic targets for genetic engineering. Its latest version, OptFlux3, allows to perform the simulation of wild type and mutant strains (allowing the simulation of gene/ reaction deletion and over/under expression). Regarding strain optimization, the new architecture opts for a multi-objective framework, allowing users to easily add different goals as optimization targets in a flexible way. Specialized multi-objective algorithms, co-exist with traditional single objectives algorithms to be applied for each case. Also, OptFlux3 includes a new visualization framework for metabolic models and phenotype simulations and a new plug-in management interface that allows to install and remove plug-ins in execution time. Currently available plug-ins include the calculation and visualization of elementary modes, topological analysis and the ability to add reactions/ pathways to existing models. OptFlux is made freely available for all major operating systems, together with suitable documentation in www.optflux.org.

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A novel method for the development of industrial strains targeted at the production of chemical compounds is presented. This method consists on the rewiring of transcriptional regulatory networks through node addition to explore novel regulatory landscape architectures. A library of transcriptional regulatory components was created to randomly combine promoters and ORFs and installed over existing regulatory networks. New strains that are more adapted to the stress imposed by a heterologous pathway are isolated, resulting in improved phenotypes. The modified networks of improved strains are examined at the transcriptional level in order to better understand how the rewiring events produced the desired phenotype. This strategy was implemented in a Pichia pastoris strain producing the red pigment lycopene through the expression of the P. ananatis crtB, crtI and crtE genes. This pathway allows for simple screening procedures to be used, is a precursor to a number of medically and industrially relevant carotenoids and is itself relevant in the food, cosmetics and nutritional supplement markets. 67 promoters and 43 open reading frames of were combined using Gibson assembly to generate a library consisting of 2881 novel nodes. This library was then screened for increased production of lycopene after genomic integration. Validation of targets’ production levels and copy-number normalisation is ongoing and will be followed by scale up to confirm validity of the method for industrial application. Further use of this method across species and metabolic product classes should inform future rational engineering of strains and expand our knowledge of regulatory network evolution.

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As engineering foundations such as standards and abstraction begin to mature within synthetic biology, one limiting factor for the design of more complex genetic networks will be the availability and effectiveness of genetic design automation (GDA) software tools. Ideally, a synthetic biologist could design genetic networks at a fairly high level of abstraction, focusing on a desired behavior rather than the DNA components used to implement said behavior. Such a synthetic biologist would use GDA tools to automatically map behavioral descriptions to standardized sets of DNA components, thereby decreasing the expert knowledge and time required during the design process. To this end, we have developed a genetic technology mapping algorithm to map from a model of a genetic network written in the Systems Biology Markup Language (SBML) to a parts library of SBML models that are annotated with DNA components written in the Synthetic Biology Open Language (SBOL). Our algorithm builds on directed acyclic graph-based (DAG-based) mapping techniques originally used to map electronic circuits and can be divided into three steps. First, the algorithm constructs regulatory graph representations of the given genetic network and parts library and partitions them into rooted DAGs. Second, the algorithm converts these DAGs to a canonical form and matches the library DAGs to each node in the network DAG. Lastly, matches are selected via dynamic programming and recursive backtracking to obtain the solution set of DNA components with the fewest base pairs. Backtracking is necessary since each selected match can lead to a non-minimal solution by precluding subsequent selection of minimal matches that also introduce genetic cross-talk. As backtracking can be computationally expensive, we will continue to explore heuristics for reducing average computation time such as bounding solution size with the best solution size found so far.

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The re-design and controlled self-assembly of natural systems into non-natural functional products is a quickly developing area of Synthetic Biology. Specifically, the manipulation of existing and the introduction of new protein-protein interactions will allow great advances in bionanotechnology. In nature protein-protein assemblies mediate many cellular processes and exhibit complex and efficient functions. It is thus rational to assume human guided biomolecular assemblies could house equally complex functionality designed to address our current needs, including such devices as molecular diagnostic tools and therapeutic drug delivery systems. The goal of our project is the design and production of a capsid-like protein cage of dodecahedral symmetry and diameter of 15 nm or 32 nm, with an internal cargo-holding space, by the de novo design of a protein-protein interface between subunits. Firstly we used scaffolding molecules to tether our protein into the correct proximity for dodecahedral assembly. A combination of current computational methods was then used to suggest mutations which reduced the G of interaction across the interface. These designs were then experimentally characterised and the simulations optimised. These methods should be appropriate for generic application to the design of self-assembling protein systems. The dodecahedral particle is assembled from Cholera Toxin B-subunit, a natural homopentamer with an inbuilt cell targeting and endocytic triggering mechanism. Future applications could therefore use our capsid as a drug delivery vehicle to transport protected therapeutic agents to targeted cell types.

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In the last few years, new types of structures and roles for RNA molecules have been constantly discovered: sRNAs, microRNAs, siRNA are just a few amongst an ever growing catalogue of RNA types, with the latest addition to the collection being circular RNAs (circRNA). There is therefore an urgent need for reliable and robust methods for in vivo visualisation and quantification of this type of molecule. Our team has recently created an RNA design software based on first principles, RNAdes, which uses in silico evolution to automatically design small RNAs capable of allosteric interactions with other RNAs in vivo. Using this software, we are designing and implementing various small sensors. By using fluorophore binding aptamers such as the malachite green aptamer within these designs, we have created artificial scaffolds which stabilise these fluorescent aptamers, allowing in vivo visualisation of RNA. We are developing methods to automatically design allosteric RNA sensors using these fluorescent RNAs and/or genetically encoded reporters. These will expand the toolbox for researchers in RNA biology, as well as aid in the construction of more advanced synthetic RNA circuits.

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Pichia pastoris is a commonly used expression host for heterologous protein production, predominantly because it is amenable to genetic manipulation and can grow to high cell densities in cheap culture media. While considerable yields can be achieved in this way, the specific productivity is relatively low. Consequently, the full impact of this host on industrial biotechnology has not yet been realised. Previous studies to increase productivity have focused on bioengineering, such as targeting gene and strain characteristics, and fermentation conditions. Whereas the latter has been subject to systematic multivariate optimisations, the former has not. The majority of bioengineering studies have targeted one factor in isolation, and despite comparable strategies have variable outcomes. Here, an integrated experimental and computational modelling approach has been taken to understand how the factors interact and develop a global optimisation strategy. A deterministic single cell model of protein production in P. pastoris has been devised including the essential aspects of transcription, translation and folding in the endoplasmic reticulum (ER). Additionally, as heterologous protein production can induce stress responses, the unfolded protein response (UPR) and ER associated degradation pathway (ERAD) have been accounted for. Results from preliminary simulations highlighted key regulators of production capacity. To understand how yield arises from a balance of these, the regulators were characterised in strains which express a heterologous protein to different degrees. Consequently, two single chain antibody fragments were cloned into P. pastoris and a high and a low secretor of each identified. These strains were characterised with RT Q-PCR and LC-MS/MS and the results integrated into the model. Knowledge of the upper and lower bounds for parameters from the low and high secreting strains allowed for the optimal value to be predicted for the highest yield. This constitutes an integrated modelling and experimental approach to improving productivity in P. pastoris.

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Synthetic biology has proved useful in both elucidating existing cellular regulatory mechanisms and constructing simple novel systems from them. A clear next step is to apply this approach to multicellular organisation. However, multicellularity is the result of a complex interplay of generative and regulatory mechanisms (cell growth, division, signaling, and genetic regulation) that are difficult to decouple. Such complexity suggests the use of simple, abstracted model systems in which each of these effects can be isolated, both for understanding them and engineering their interaction. Using layers of bacterial cells, that exhibit little or no molecular coordination of growth, we were able to effectively isolate the effects of cell shape, growth and division on the development of fluorescence-labeled cellular domains. Combining confocal microscopy, a cell-shape mutant, and computational modeling, we show that individual cell shape can cause mechanical instabilities that give rise to tissue-wide fractal patterns. We also created a simple mechanism for genetic symmetry-breaking that utilizes this effect to spontaneously generate spatial pattern – illustrating the potential for engineering.

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Top-down approaches to functional genomics traditionally rely on the targeted deletion of individual genes. However, the necessity to tailor the recombination sequences of knock-out constructs to each target poses an obstacle for automation and high-throughput experimentation. In order to rapidly streamline the genome of the biotechnologically important gram-negative bacterium Pseudomonas putida, we developed a recyclable three-step deletion method capable of excising large genomic segments.

The method combines random insertions of selectable mini-Tn5 transposons with the site-specific Flp-FRT recombination system to generate successive random deletions in a single strain in which parts of the genome are excised via the action of the cognate flippase.  These mini-Tn5 transposons carry different selectable markers and each has an FRT (Flippase Recognition Target) site. Upon induction, both FRT sites are recognized by the flippase, resulting in the deletion of the intervening genomic segment along with the transposon backbones without the inheritance of any marker genes.

A cyclical application of the method generated four double-deletion mutants of which a maximum of ~ 7.4% of the chromosome (~ 6.9% of the gene count) was excised. Comparative Phenotype Microarray analysis between the deletion mutants and their ancestors analysis revealed an unexpected increase in respiratory capacity when utilizing a number of sugars and organic acids as carbon sources, and a decreased capacity to metabolize certain amino acids.

This procedure demonstrates a new approach to streamlining bacterial genomes and generating large libraries of deletion mutants. Combined with high-throughput ~omics analyses, the application of this method will lead to a better understanding of the metabolic and regulatory interactions relevant to design and optimization of heterologous metabolic pathways – and eventually result in a streamlined bacterial chassis for the sustainable production of chemicals.

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While the biosphere is replete with solar energy, the primary challenge is to channel it into molecules usable with current infrastructure, such as liquid fuels and polymers. In addition to traditional genetic engineering techniques, “coercing” cells to produce chemicals of interest requires ability to manipulate naturally evolved regulation and development of tools to enable directed control. Compartmentalization is a powerful strategy for metabolic control used widely in eukaryotes. Our work shows that carefully designed RNA strands expressed genetically can be used as intracellular scaffolds for metabolic enzymes, enhancing pathway fluxes in E coli and Cyanobacteria. These RNA are in-vivo assembled by base-pair interactions and are designed to form precise structures that offer multiple binding sites to specific enzymes. By spatially insulating metabolic reaction centers, the scaffolds can mimic organellar compartmentalization. We are implementing three different kinds of pathways involving alkane fuel synthesis, succinic acid synthesis and carbon dioxide fixation by RubsiCo. This poster presents the various synthetic parts built, the chasses developed, the mechanism and characterization of increase in pathway flux by various scaffold designs. This is also the first example for use of scaffolds to channel metabolic pathway fluxes in cyanobacteria. We believe that this research sets the stage for a creative merger of the nucleic acid nanotechnology field with that of metabolic engineering.

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The formation of well defined synthetic membrane model systems is commonly used in the field of biophysics to study basic biological processes in a less complex environment than a viable cell. However, the functionality of membrane proteins not only depends on their incorporation into a lipid bilayer, but also e.g. on subsequent posttranslational modification. The integration of these biological processes into synthetic systems is rather challenging. However, due to the fact that membrane proteins are naturally low abundant in living cells, common over-expression systems often reach their limits caused by cytotoxic effects or aggregation of membrane proteins. Thus, the reduction of the biological protein production machinery to a viable cell independent system is favourable. Our eukaryotic cell-free system based on insect cell lysates provides endoplasmic reticulum derived vesicles, so called microsomes, which enable co-translational translocation as well as posttranslational modifications as glycosylation or lipid modification. These microsomes, serving as micro-containers, enable us to integrate the membrane protein of interest into giant unilamellar vesicles (GUVs) using the electroswelling process [1]. Additionally, with this method we are able to simultaneously modify microsomes containing membrane proteins with synthetic lipids to gain so called hybrid-GUVs. Thus, techniques for functionalization and immobilization are applicable to embed membrane systems into technical processes or incorporate proteins in synthetically modified biological membranes. Ongoing research is focusing on mild formation methods, such as agarose-supported swelling to gain translocationally active GUVs for direct expression of active membrane proteins. Taken together, these methods now enable the engineering of biomimetic vesicles and the development of novel functional assays based on cell-free systems. [1] “Towards an artificial cell: Protein incorporation in giant unilamellar vesicles under physiological conditions”, Paige M. Shaklee, Stefan Semrau, Maurits Malkus, Stefan Kubick, Marileen Dogterom,Thomas Schmidt, ChemBioChem (2010)

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Synthetic biology has vast potential in many fields of application, but has so far failed to live up to its promise. The main reason for this is that current design and modelling strategies are greatly lacking. The design paradigms of electronic engineering, and even of network motifs, do not fully account for the complexity and inherent stochasticity of biological systems, and current modelling techniques are inefficient. As we attempt to design more and more complex systems, these difficulties are compounded exponentially, leading to synthetic designs that do not possess the robustness they require to perform and a great deal of trial and error. A more holistic approach to design is the use of Bayesian model selection, a form of in silico evolution, where a prior set of high-dimensional design space is tested and selected for using a desired outcome. ABC-SysBio is used to infer ‘designs’ for a robust genetic oscillator system from all possible 3 node systems. With this technique the design space can be limited by practical considerations, such as the immutable characteristics of available genes, and can also infer kinetic parameters of the system on top of node connectivity. The leading candidates are compared computationally and experimentally to a previously characterised synthetic oscillator that was consciously designed.

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Non-coding small RNAs (sRNAs) are involved in post-transcriptional gene regulation and controls cellular processes. Until now, many natural sRNAs has been identified and characterized in Escherichia coli. These sRNAs base-pair with the 5-untranslated region and/or the translation initiation region of the mRNA, thereby modulating the mRNA stability or the translational efficiency resulting in the activation or repression of the gene expression. The trans-encoded sRNAs, which are encoded separately from the mRNA, commonly binds to Hfq, an RNA chaperone protein. Hfq binds to a single-stranded AU-rich sequence of sRNA that is not within the antisense region, which hybridizes with the mRNA. This Hfq-binding promotes sRNA-mRNA hybridization and also enhances the stability by protecting sRNAs from ribonuclease degradation. Since artificial sRNAs can be designed based on the complementary sequence of the target mRNA, sRNAs are valuable to control the expression of various target genes. In this research, we engineered the Hfq binding sequence based on natural sRNAs to further improve their gene regulation ability. We selected four different E. coli-derived, Hfq-dependent sRNAs and focused on their Hfq binding sequence. The engineered Hfq binding sequences were designed by stabilizing the secondary structure and/or by introducing sequence that has high affinity against Hfq. We introduced these engineered Hfq binding sequence into the natural sRNA by substituting its natural Hfq binding sequence with the engineered one or directly fused the engineered Hfq binding sequence to the antisense sequence of the artificial sRNA. As a result, we were able to improve the gene regulation of both natural and artificial sRNAs in E. coli. We believe our engineered Hfq binding sequence would be applicable to other sRNAs to improve its regulatory activity and engineering Hfq binding sequence would be a valuable strategy to engineer sRNAs that strongly regulate the expression of their target gene.

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Bacteriophage M13 has become one of the leading nano-particle chassis in synthetic biology. The shape, ruggedness and genetic flexibility make it ideal for cycles of design and test required to reliably develop nano devices. In this work we explore a unique application of M13 in pathogen detection. Detection and identification of pathogens remains a major challenge for science. Over the last 100 years a large number of different approaches have been trialled to provide a detection system that is rapid and specific while remaining cheap, simple and generic. The relative lack of progress towards this goal can be gauged from the continued reliance of clinical microbiology laboratories on microbial culture methods to detect and identify pathogens. In the study presented here we show the utility of a completely new approach to pathogen detection based on an engineer M13 bacteriophage. We have taken the hydrodynamic behaviour of the filamentous virus, M13 as inspiration for this new approach. The exquisite (semi liquid crystalline) structure of this virus endows it with exceptional rigidity compared to other biological filaments of similar dimensions. We have exploited this alignment and combined it with a novel form of spectroscopy, linear dichroism, that specifically probes systems with high levels of alignment. By selectively modifying the structure of the bacteriophage to add additional functionalities (e.g. pathogen binding) we have generated a reagent that forms the basis of a rapid simple test for the human pathogen E. coli O157 (See www.youtube.com/watch?v=XO5bFYOJotc for a description of the method). Our goal for the future is to extend the application of this approach to a wider range of targets using ever more advanced M13 particles.

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For decades, bacterial luciferase operon has brought light into the molecular biology labs, serving as a sensitive tool for numerous sensor applications. Traditionally the light producing multienzyme complex has been exploited in an orthogonal manner, independent from the host metabolism. The complex can be divided into two functional parts, an aldehyde producing unit LuxCDE, and a fatty acid and light producing unit LuxAB. In our study, these functional units were exploited independently and integrated to the metabolism of an optimal cellular framework, enabling the construction of novel screening tools and synthesis pathways for metabolic engineering applications. The integration of the light producing unit allows detection of endogenous long chain aldehyde formation, and vice versa, the integration of the aldehyde producing unit provides intermediates for the production of customized long chain hydrocarbons. As long-chain aldehydes represent an intermediate in the wax ester synthesis route, LuxAB was exploited in developing a tool for monitoring bacterial wax ester production in Acinetobacter baylyi ADP1 wild type strain. The monitoring system showed correlation between wax ester synthesis pattern and luminescent signal. The system holds potential for real-time screening purposes and studies on bacterial hydrocarbon production. Furthermore, a reverse monitoring system was constructed for studying the kinetics and potential for bacterial degradation of long chain hydrocarbons such as petrodiesel, alkanes, and other pollutants in contaminated soil and water environments, applicable in the field of environmental biotechnology. Finally, the wax ester synthesis route of A. baylyi ADP1 was reconstructed by replacing part of the natural production pathway with LuxCDE, resulting in recircuited production of modified wax esters.

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Synthetic Biology has recently arrived to Plant Science, representing an emergent discipline. Following the work previously done in bacteria and yeast, Plant Synthetic Biology (PSB) aims to design and construct new biological parts or systems and redesign existing ones to carry out novel tasks. The design of plants with new characters requires the existence of a versatile and efficient modular assembly system that makes affordable the combination of complex genetic structures involving multiple transcriptional units. GoldenBraid (GB) [1] was created to overcome the existing limitations and to facilitate multigene engineering. GB is an iterative cloning system for the standardized and modular assembly of reusable genetic modules. It is based on a very efficient digestion/ligation method [2,3] that turns into a routine the assembly of combinatorial constructs. GB consists of a set of eight destination plasmids (pDGBs) designed to host scar-benign multipartite composites that can be binarily combined to create complex multigene constructs. GB makes possible the assembly of 15-19 kb constructs comprising 4-5 transcription units made of individual standardized GBparts in a few days work. A new version of GoldenBraid, named GB2.0, has recently been released, , which improves the simplicity and versatility of the previous version and provides a pre-defined grammar for transcriptional unit composition. The incorporation of new DNAparts to the collection has been standardized by using the Universal Part Domesticator Vector (pUPD). The GB2.0 includes a complete kit for PSB. Most new GBparts have been generated and tested by transient transformation of N.benthamiana leaves or by stable transformation of A.thaliana. Different vector backbones, constitutive and inducible promoters, reporters, tags, resistance genes, silencing tools (amiRNA, tasiRNA, hpRNA) and other elements of interest compose this collection that aims to serve as a reference for Plant Synthetic Biologists. 1. Sarrion-Perdigones et al.(2011).PLoSOne6: e21622. 2. Engler et al.(2008).PLoSOne3: e3647. 3. Engler et al.(2009).PLoSOne4: e5553.

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Natural biological processes like development and self-organization of populations (ex: biofilm formation), require cells to respond to the distribution of a diffusing molecule. Synthetic biology has adapted acyl homoserine lactone (AHL)-based quorum-sensing systems to rationally engineer intercellular communication, chemotaxis, and pattern formation in bacterial populations. A key component for engineering reliable cell-cell interaction via AHL molecules is to exercise control over the size, shape, and stability of the AHL distribution. We used engineered C6-AHL receiver cells in order to ratiometrically characterize the rate of AHL diffusion in a bacterial lawn with different AHL sources. Using mathematical modeling based on experimental characterization of enzyme-catalyzed degradation of C6-AHL by aiiA (an AHL lactonase), we show that aiiA can be used to control the shape and size of the AHL diffusion in a bacterial lawn.

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A grand challenge in synthetic biology is the development of engineered biological functions that operate robustly in multiple cell types and under a variety of conditions. Plasmid-based approaches to engineering microbes are convenient and widely-used, but in multi-plasmid systems, cell-to-cell variability in plasmid copy number and plasmid identity can generate heterogeneous phenotypes between different cells within a population. Moreover, such heterogeneity varies with both method of copy number regulation and regime of cell growth, which is tied to growth substrate utilized. Although these effects are known to exist and potentially complicate the engineering of complex synthetic functions, we lack a quantitative understanding and framework for incorporating these effects into the design and analysis of engineered cellular functions. To meet this need, we present a novel agent-based computational framework for describing and predicting the dynamics of heterogeneous plasmid ensembles within individual cells in a bacterial population. This model was calibrated against both bulk and single-cell experimental measures of cell count, plasmid content, and genome replication under various growth regimes. Our agent-based simulation provides the first computational tool for investigating plasmid ensemble dynamics at the individual cell level in a manner that explicitly incorporates mechanisms of cell growth and plasmid replication and regulation. This approach should facilitate analysis and design of improved plasmid-based synthetic functions. Because our modeling framework is mechanistically driven, this approach can be extended to incorporate and investigate other phenomena that are of both fundamental biological interest and may represent potential tools for synthetic biology, such as exchange of mobile genetic elements via bacteriophage and conjugation and plasmid coupling via toxin-antitoxin interactions.

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Heterocycles are centerpieces of most natural products and especially in biomolecules like nucleic acids, amino acids, vitamins and alkaloids nitrogen containing rings are overrepresented. This bioactivity is also responsible for N-heterocycles being common backbone elements in the vast majority of small molecule drugs. Hence, they represent ideal precursors for the pharmaceutical industry. However the chemical snytheses of these molecules are hampered by a complex stereochemistry, the dependence on expensive and environmental toxic chemicals as well as low yields. Inspired by the natural biosynthesis of tropane-, piperidine-, pyrrolizidine- and quinolizidine alkaloids, we aim to establish biotechnological production routes resulting in a diverse set of heterocyclic compounds. Although these classes of alkaloids exhibit quite complex and diverse structures, their biosyntheses are initiated with the decarboxylation of only a few amino acids. Using the amino acids arginine, lysine and ornithine different polyamines are generated. They then function as a link between primary and secondary metabolism. The cyclization of these polyamines is a spontaneous reaction, triggered by their oxidation to an aminoaldehyde which will be catalyzed by FAD containing amine oxidases. To gain access to a wide variety of different heterocycles the application and evolution of amine oxidases towards a set of naturally occurring and synthetically modified polyamines is one part of this work. By using methods of directed evolution and rational protein design in combination with high-throughput screening assays based on H2O2 detection, amine oxidase variants and libraries thereof will be created. The assembly of an enzymatic reaction cascade consisting of polyamine modifying enzymes to provide different precursors and the concept of purpose-evolved amine oxidases combined with “tailoring” enzymes for the functionalization of the basic heterocyclic compounds represents a highly flexible approach. Finally the transfer of these enzymes in a living organism will generate artificial pathways for an in vivo production of N-heterocycles.

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By aiming to develop orthogonal biological systems, research on xenobiology attempts to create biological parts, devices, and systems entirely different from the canonical forms in terms of biochemistry, genetic code and metabolism. Since it is early days for xenobiology, most of the research is focused on basic chemical components such as nucleic acids and amino acids. Initial results demonstrating the proof of concept have been achieved recently. Xenobiology offers three main opportunities for science and society: (1) it will help to understand the origins of life, and why biology turned out to have its current form and structure; (2) it will enable the development of more efficient industrial biotechnology by means of enhanced biopolymer engineering and pathogen resistance; and (3) it may be used to develop highly increased biosafety systems featuring an inherently safe genetic firewall. In this talk, the challenges and opportunities of xenobiology will be reviewed. Firstly, the current development in xenobiology will be introduced, focusing on the research of chemical evolution and de novo design genetic materials. Secondly, the challenges and opportunities of xenobiology to the current biosafety regulations will be reviewed. Finally, the plausible roles of xenobiology in making synthetic biology safer will be discussed.

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One of the major bottlenecks in the field of synthetic biology is the assembly of DNA ‘parts’ into larger pathways or genomes. To address this, the Genabler proprietary technology was developed with funding from Scottish Enterprise to enable the next generation of genome engineering by designing and generating combinatorial DNA assemblies on a high throughput scale. We describe a methodology that is capable of assembling in a single reaction as many as ten parts into biological pathways using a specific restriction endonuclease and T4 DNA ligase. Furthermore, the technology allows the combination of any input part in any desired order thanks to unique compatible ends that are designed by Genabler proprietary bioinformatics software. The entire process is ready to be automated offering the generation of large assemblies in a fast, reliable and robust manner. Technical examples of metabolic pathways will be presented and discussed in further detail. Genabler was founded following a three-year research program involving prominent UK and US based companies and academic research groups. As well as being available to UK academics via a straightforward research use license, Genabler works with global partners in the consumer products, energy, agbio, industrial biotech, and biopharmaceuticals industries to develop innovative bioproducts and processes. In sum, Genabler provides reliable and cost effective assemblies to its partners with the ultimate aim being the development of future products that have a smaller environmental impact, improved production economics, or enhanced characteristics.

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With increasing scales of oligonucleotide synthesis comes a concomitant need to rapidly screen complex synthetic libraries and selectively retrieve specific error-free sequences. This is currently a significant bottleneck for the field of synthetic biology. To overcome this limitation we have developed dial-out PCR, a highly parallel method for retrieving accurate DNA molecules for gene and genome synthesis. A complex library of DNA molecules is modified with unique flanking tags before massively parallel sequencing. Tag-directed primers then enable the retrieval of molecules with desired sequences by PCR. Dial-out PCR enables multiplex in vitro clone screening, allows for the normalization of target sequence abundance before multiplex assembly steps, and it has the potential to decrease production costs for high-quality, sequence-verified synthetic DNA by over an order of magnitude. The method also supports clone retrieval from other nucleic acid pools, such as in the screening and recovery of specific mutants from a complex mutagenesis library. Dial-out PCR is a compelling alternative to in vivo cloning and Sanger sequencing for large-scale target verification and retrieval.

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The presence of endocrine disrupting chemicals (EDCs) in surface waters has been linked to a number of adverse effects in aquatic organisms; an increasing body of literature attempts to link EDCs with human endocrine and developmental disorders too. Ethinyl-oestradiol (EE2) is by far the most potent and recalcitrant EDC to date; as the active ingredient of the contraceptive pill it is also highly ubiquitous. The need to improve the removal of EE2 from wastewater in a cost-effective manner has become increasingly important and we believe the solution lies in the construction of a synthetic biodegradation pathway. Hence the focus of this project is to investigate bacterial and fungal enzymatic degradation of EE2 so that these can then be used as parts in a steroid breakdown pathway. Laccases are multi-copper oxidases well known for degrading phenolic and aromatic compounds; however, there are still gaps in the knowledge in terms of the EE2 degradation process. In order to assess the bioremediation potential of laccases our main aim is to elucidate the oestrogenicity and structure of the metabolites produced. Since the nature of the metabolites is unknown, we are employing two bioassays that measure oestrogenic activity. The more relevant of the two, is a new biosensor we developed in collaboration with the Institute of Natural Sciences (Japan) – a mammalian cell host with a fish oestrogen receptor coupled to a luciferase reporter. This biosensor is highly important because the detrimental effect of EE2 exposure to fish populations is very well documented. Here we present our preliminary results on laccases ability to degrade EE2, along with the oestrogenic profile of the metabolites produced. Where possible the chemical structures of major metabolites will be also included.

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Genome engineering technologies such as ZFNs, TALENs, and CRISPR/Cas systems have the potential to revolutionize therapeutic strategies for disease intervention and accelerate the creation of designer genetic systems, with applications ranging from agriculture to neuroscience.

We recently created prototyping pipeline for the rapid design of single and multiplexed CRISPR/Cas systems with target specificities optimized over the entire genome. Results from our lab and others have shown that the specificity of the Streptococcus pyogenes CRISPR/Cas Type II system in mammalian cells varies as a function of the guide RNA sequence used to target the Cas9 nuclease to a specific gene. We constructed large oligo libraries of guide RNAs carrying combinations of mutations to study the sequence dependence of Cas9 programming. Data from these studies were used to develop algorithms for the prediction of CRISPR/Cas off-target activity across the human genome. Our resulting computational platform supports the prediction of specificity for CRISPR/Cas systems from any species.

Additionally, we developed a next-generation deep sequencing (NGS) and data processing pipeline for rapidly assessing the on-target gene editing performance and genome-wide off-target activity of any targeted nuclease technology. We used the Ion Torrent platform to sequence genomic regions flanking target loci and predicted off-target sites across the human genome. We present a library of computational tools for processing NGS sequencing data and detecting indels. The combination of our CRISPR prototyping and NGS sequencing pipeline resources will greatly advance the rational design and precise application of genome engineering technologies.

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In this work, we describe the creation of a set of transcription factors that loosely mimics the action of prokaryotic core polymerase and sigma factors. In prokaryotes, the core polymerase complex contains the majority of enzymatic function required for transcription, and sigma factors contain DNA binding domains that recruit the polymerase complex to promoters. Since core polymerase is usually limiting, sigma factors compete with each other to bind core and direct transcription proportional to their relative concentrations and binding affinity. We have attempted to recreate this system for use in orthogonal, synthetic genetic programs by bisecting a set of orthogonal phage RNA polymerases. Using a new transposon-based method for generating libraries of split proteins, we split T7 RNA polymerase into two subunits that are active when co-expressed: a larger one that contains much of the catalytic core, and a smaller one that contains the promoter recognition loop. After improving the split protein interactions and activity, we were able to apply this split site to four orthogonal T7 RNA polymerase variants, making a system with one shared ‘core’ protein and four variable ‘sigma-like’ proteins. Both fragments are necessary for transcription, and we have shown that multiple ‘sigma-like’ factors expressed in the same cell compete with each other for a limited pool of the ‘core’ fragment. We envision that this system could prove useful in engineering more complex regulation of synthetic genetic programs in bacteria. The level of the ‘core’ fragment sets the number of polymerases available to the synthetic program as a whole while the relative levels of the ‘sigma-like’ fragments allocates these polymerases among different parts of the program. The levels of ‘core’ could therefore be modulated to avoid stressing or killing the chassis organism without changing relative expression levels within the synthetic system.

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Technologies for assembling of multi-Kilobase synthetic DNA constructs are rapidly outpacing technologies for verifying that the final molecules match design specifications to the base pair. Traditional methods of Sanger sequencing become cost prohibitive when assemblies are large. Next-generation sequencing offers the necessary cost reduction, but for state of the art workflows the throughput is too low. To address this, Amyris has undertaken development of a high-throughput next-generation sequencing pipeline for DNA assemblies that relies on the Illumina Nextera sample preparation protocol and a single MiSeq. To match the cost of current QC methods, the Nextera sample preparation reaction volume must be scaled down more than 100-fold and each sequencing reaction should include more than 500 pooled and barcoded plasmid samples. Several steps of the pipeline require significant reengineering to meet the requirements imposed by scale and cost. When operationalized, the pipeline will provide base-pair resolution and automated data analysis for the several thousand assemblies Amyris generates each month.

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Synthesis of active E. coli ribosomes from in vitro-transcribed 23S ribosomal RNA (rRNA) is a key step towards several goals of synthetic biology, such as in vitro evolution of ribosomes, antibiotic discovery and synthesis of a minimal cell (1). Reconstitution analyses showed that active E. coli ribosomes could not be assembled using in vitro-transcribed rRNAs alone, but required one to six post-transcriptional chemical modifications in a 78-nucleotide critical region of the 23S rRNA comprising part of the peptidyl transferase center (2). Recently, five of the six enzymes responsible for these modifications were identified, namely methyltransferases RlmKL, RlmM and RlmN, and pseudouridine synthases RluC and RluE (3). Using a bottom-up approach, we have overexpressed these modification enzymes and reconstituted their reactions in a purified system. Tritium-labeling and primer-extension assays demonstrated that in vitro-transcribed 23S rRNA is a substrate for several of the enzymes, while combined modification reactions showed surprising cooperativity. In addition, we elucidated the crystal structure of modification enzyme RlmM in complex with its cofactor, S-adenysyl methionine (SAM) (4). RlmM is composed of a large N-terminal RNA recognition domain that presumably provides substrate specificity with a conserved, positively-charged patch. As expected, SAM was bound at the catalytic C-terminal methyltransferase domain at a Rossman fold. However, the SAM pocket was surprisingly shallow, suggesting that the site becomes deeper upon RNA binding. This new synthetic biology approach to rRNA modification reactions and ribosome reconstitution should illuminate the functions of these enigmatic modifications while moving us closer to synthesizing a minimal cell. 1. Forster AC, Church GM (2006) Mol Syst Biol 2:45. 2. Green R, Noller HF (1996) RNA 2:1011. 3. Purta E, O’Connor M, Bujnicki JM, Douthwaite S (2009) Mol Microbiol 72:1157. 4. Punekar AS, Shepherd TR, Liljeruhm J, Forster AC, Selmer M (2012) Nucleic Acids Res 40:10507.

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Exponentially decreasing costs in DNA synthesis will lead to increased outsourcing of DNA construction in the future, a situation comparable to the current state of oligonucleotide synthesis and DNA sequencing. As DNA construction is increasingly outsourced, the next generation of scientists and engineers that work with DNA should turn their focus from DNA construction to prototype specification and design and experimental testing of genetic parts and devices. However, there are currently few undergraduate laboratory courses which decouple DNA construction from the other tasks. We present a bioengineering course which outsources DNA synthesis, focusing on giving students experience in prototype specification and design and experimental testing of their own custom genetic parts and devices while simultaneously learning the basic laboratory skills required when working with DNA and living organisms. This course has produced its first successful student-designed genetic parts and devices, and student surveys indicate student improvement in skills taught by the course. Future versions of the course will allow students to work with a wider variety of organisms and will use feedback from student surveys to implement further improvements.

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Amino acids are the building blocks of proteins and are essential in all organisms. L-isoleucine, one of the branched amino acids, cannot be synthesized in humans and must be ingested. It is thus relevant that this amino acid is highly demanded in the industries of dietary supplements, pharmaceuticals and cosmetics. Conventionally, amino acids are industrially produced by bacterial strains developed from rounds of random mutagenesis. However, the metabolism of such strains is difficult to elucidate and growth may not always be efficient. Thus, the present study was aimed at constructing a 100% genetically defined L-isoleucine producing strain. TH20, a genetically defined L-threonine overproducing strain, was used as the starting strain, as L-isoleucine is synthesized from L-threonine after five enzymatic steps in vivo. The thrABC (encoding L-threonine biosynthetic enzymes), engineered ilvA (encoding feedback-resistant threonine dehydratase), engineered ilvIH (encoding feedback-resistant acetohydroxy acid synthase ), and ygaZH (encoding branched-chain amino acid exporter) genes were amplified by plasmid-based overexpression. The ilvCED (encoding L-isoleucine biosynthetic enzymes) and lrp (encoding Lrp, a global regulator) genes were also amplified by chromosomal promoter replacement to further increase the flux toward L-isoleucine. The final engineered E. coli strain was able to produce 9.46g/L of L-isoleucine with a yield of 0.14g/g of glucose by fed-batch culture. [This work was supported by the Technology Development Program to Solve Climate Changes (systems metabolic engineering for biorefineries; NRF-2012-C1AAA001-2012M1A2A2026556) and the Intelligent Synthetic Biology Center of Global Frontier Program (2011-0031963) from the Ministry of Education, Science and Technology (MEST) through the National Research Foundation of Korea.]

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Concerns over the increasing emergence of antibiotic-resistant pathogenic microorganisms due to the overuse of antibiotics and the lack of effective antibiotics for livestock have prompted efforts to develop alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) with a broad-spectrum activity and rapid killing, along with little opportunity for the development of resistance, represent one of the promising novel alternatives. Their high production cost and cytotoxicity, however, limit the use of AMPs as effective antibiotic agents to livestock. To overcome these problems, we developed potent antimicrobial Escherichia coli displaying multimeric AMPs on the cell surface so that the AMP multimers can be converted into active AMP monomers by the pepsin in the stomach of livestock. Buf IIIb, a strong AMP without cytotoxicity, was expressed on the surface of E. coli as Lpp-OmpA-fused tandem multimers with a pepsin substrate residue, leucine, at the C-terminus of each monomer. The AMP multimers were successfully converted into active AMPs upon pepsin cleavage, and the liberated Buf IIIb-L monomers inhibited the growth of two major oral infectious pathogens of livestock, Salmonella enteritidis and Listeria monocytogenes. Live antimicrobial microorganisms developed in this study may represent the most effective means of providing potent AMPs to livestock, and have a great impact on controlling over pathogenic microorganisms in the livestock production.

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Efforts to replace petroleum derived products include the development of sustainable processes to produce diesel-like fuels. The current biodiesel (fatty acid alkyl ester) production is based mainly on plant oils and has a number of disadvantages, e.g. a low per hectare yield. We are therefore aiming at developing an efficient yeast cell factory for the synthesis of diesel fuels from biomass. The production of fatty acid ethyl esters (FAEEs) has previously been established in S. cerevisiae through introduction of a bacterial wax ester synthase. In this project, we optimized FAEE production in yeast through different strategies: (i) Improvement of wax ester synthase activity. Wax ester synthases from different sources were expressed in yeast to select the one with the highest activity, which was then integrated into the genome in multiple copies. We also developed a screening system to select for wax ester synthases with altered substrate specificity. (ii) Decrease of fatty acid consumption. Pathways competing with FAEE synthesis for the substrate, acyl-CoA, were eliminated. These included the formation of storage lipids and beta-oxidation. (iii) Increase of precursor supply. To increase the amount of acyl-CoA in the cytosol overexpression of a de-regulated version of acetyl-CoA carboxylase was combined with expression of a heterologous glyceraldehyde-3-phosphate dehydrogenase providing NADPH for fatty acid biosynthesis and overexpression of the endogenous acyl-CoA binding protein. In addition, the supply of acetyl-CoA was increased either by enhancing ethanol catabolism or through introduction of the heterologous phosphoketolase pathway. All these strategies proven beneficial when tested separately are now being combined in a single strain to create a platform strain for production of FAEEs and other fatty acid derived fuels and chemicals.

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Synthetic biology is a rapidly changing field that is always on the edge of a new frontier. In 2010, Craig Venter’s team synthesized the entire Mycloplasma mycoides genome and transplanted into another species of bacterium, Mycoplasma capricolum, resulting in the first living organism with a fully synthetic genome. As such advancements are emerging at a swift pace, it crucial to consider not only the scientific challenges that will be faced, but the ethical and policy challenges, as well. Ideally, such consideration takes place in advance of the science, though that is not always possible. Ethical consideration is of particular importance in this field, as many of the new discoveries have ‘dual-uses’, holding potential to both benefit and harm. In 2011, Dymond et al. spearheaded a project similar to Venter’s, but on a larger scale. The Sc2.0 project aims to synthesize the genome of Saccharomyces cerevisiae, and is anticipated to result in the first eukaryotic organism with a fully synthesized genome. This is a massive, collaborative project that involves diverse scientists from multiple academic and commercial institutions from across the globe. The project also includes a group of motivated citizen scientists from the United States. With scientists from such different backgrounds working together on this single project, it is essential that everyone is well informed and conscientious with regard to the ethical considerations related to this project. Here, we propose a set of recommendations and guidelines to govern the Sc2.0 project, and to which all collaborator agree to adhere to as this project moves forward. We believe that this proactive effort to have a unified vision about the goals and expectations of this sort of collaboration can serve as a model for other similarly collaborative, global projects.

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In order to engineer a foundational technology suitable for characterising the plethora of Synthetic Biology’s applications, a robust and high-throughput solution is required. To achieve this we adopt a multidisciplinary approach; combining microfluidics with robotics for the automatic characterisation of DNA constructs within a cell-free environment, all of which feeds into an automated data analysis software suite, providing a versatile and highly sensitive solution to the characterisation problem.

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The type III secretion system (TTSS) is a needle-shaped export machine, which directly delivers proteins from bacterial cytosol to host cytoplasm. The expressions of genes encoding those proteins are tightly regulated temporarily and spatially under physiological conditions. Here, we refactored two major gene clusters, prg-org or inv-spa clusters, encoding the structural components of TTSS to eliminate all native regulation for the expression of system in Salmonella. During the refactoring procedures, non-coding DNAs, non-essential genes, and transcription factors were removed then the codons of essential genes were randomized. These were organized into operons under the control of synthetic ribosomal binding site (RBS) for each gene. For the control of expression of refactored operons, we used inducible orthogonal bacteriophage RNA polymerase systems. Using these regulated refactored operons, we could detect secreted effectors from bacterial culture media as an indicative hallmark of functional TTSS. This work allows us to take advantage of most effective protein export system without limitation by native regulatory complexities through the refactoring procedure for diverse applications in biotechnology.

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We consider the problem of optimal exogenous feedback control of gene regulatory networks. Solutions to this problem are feedback control policies, i.e., functions computing the next optimal control input based on the currently measured system’s output. In our setting, these policies are inferred without using a mathematical model of the system, but directly from the measurements of the system’s response to external control inputs. The direct use of the measurements is beneficial since the modelling of gene regulatory networks is accompanied by a large degree of stochasticity, variability and uncertainty. Our approach to this control problem consists in adapting and further developing an established reinforcement learning algorithm called the fitted-Q iteration. To perform its computations, the fitted-Q iteration algorithm requires data sets consisting of inputs (e.g., a schedule of light pulses of fixed amplitude and wavelength, which affect the expression of certain genes in the gene regulatory network) and consequent outputs (e.g., fluorescence measurements as a proxy for protein concentrations). This data set can either be collected from wet-lab experiments or artificially created by computer simulations of stochastic dynamical models of the system. The developed algorithm is applicable to a wide range of biological systems due to its inherent ability to deal with highly stochastic system dynamics. In order to illustrate the performance of the approach, two benchmark control problems are considered: regulation of the toggle switch system, where the objective is to drive the concentrations of two specific proteins to prescribed constant levels, and reference tracking of the generalised repressilator system, where the objective is to force the system to follow a prescribed reference trajectory. In both cases, the objective is formulated as a trade-off between the minimal time response and the minimal gene expression burden imposed on the host cell.

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A synthetic signaling system has been developed based on engineered viral proteases. The signaling platform mimics the principles of natural signaling systems as signal transducers are formed by artificially autoinhibited proteases which act as molecular switches able to receive, convert, transmit and amplify biomolecular signals. The system is highly engineerable featuring a high degree of orthogonality and modularity as viral proteases with stringent and well-defined substrate specificities are recombined with engineered autoinhibition-domains and other functional elements to create different types of molecular switches in a plug-and-play fashion. Functionality is primarily conferred by structural and functional features in the linker connecting the transducer protease with the autoinhibition-domain. For instance, highly specific protease biosensors for biomedical applications were constructed by incorporating cleavage sites for several clinically important proteases into the linker. In the presence of the target protease, the autoinhibition-domain is then irreversibly separated from the transducer protease causing its activity to increase 150-200-fold. The specificity of the assay could be further improved by affinity targeting of the biosensor to its target protease, either directly through antibody-like fragments or indirectly though monoclonal antibodies effectively adopting the latter as synthetic signaling scaffolds. Using a second autoinhibited transducer protease with substrate specificities orthogonal to the first stage, it subsequently became possible to amplify protease signals through linear amplification cascades and positive feedback loops enhancing sensitivity and shortening response times. Moreover, the components of a basic autoinhibited protease unit could be rapidly repurposed to create protease-based ligand sensors. To this end, an allosteric binding scaffold was incorporated into the linker yielding an allosterically regulated protease whose activity could be modulated 15-fold following addition of the peptide ligand. The ligand sensor could then be readily connected to protease-based amplification motives forming an integrated signal sensing and amplification network.

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A key feature of development is the spatially organized differentiation of cells that underlies morphogenesis. This self-organization is responsible for many of the extraordinary capabilities of natural biological systems and is so far absent from engineered biological systems. Once initially established, boundaries between cellular populations must be maintained in spite of forces that might otherwise disrupt them. Biological systems employ multiple strategies to this end, including physical mechanisms like differential adhesion and genetic mechanisms like those driven by chemical communication. We have recently shown that clonal sectors of bacterial populations form fractal boundaries through a purely physical emergence process (see poster abstract submitted by Tim Rudge to SB6.0). This suggests that construction of synthetic multicellular systems will require not only mechanisms to establish cohorts of cells, but also mechanisms to maintain the separation of those cohorts. I describe here the ongoing development of a system to maintain an orderly boundary between cellular populations which would otherwise form a fractal boundary due to growth. The genetic circuit employs multiple cross-inhibitory signals and bistability to allow dynamic alteration of cell fate for those cells that cross the boundary between populations. Biophysical and genetic modeling using our software CellModeller demonstrates the feasibility and properties of the system. The in vivo genetic circuit in Bacillus subtilis makes novel use of multiple cross-inhibitory types of the agr system of Staphylococcus aureus for intercellular communication.

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Chitin and chitosan, the deacetylated form of chitin, belong to earth’s most abundant biopolymers. For chemical and pharmaceutical industries, chitosan is of increasing interest due to its unique physio-chemical properties and intriguing biological functionalities. However, the term chitosan actually refers to a family of oligo- and polymers differing in their degree of polymerisation (DP), degree of acetylation (DA), as well as their pattern of acetylation (PA), and different chitosans possess different biological activities. Chitin and chitosan modifying enzymes (CCME) provide promising tools for the industrial production of chitosans with defined DP, DA, and PA. We have, therefore, set up powerful knowledge-based and –omics-based discovery projects, i.a. a metagenomic sequencing approach, for the identification of potentially novel CCMEs. Soil with a long history of exposure to chitin and chitosan was used for the extraction of metagenomic DNA. The purified DNA was sequenced on a Genome Sequencer FLX platform from Roche applying Titanium chemistry. Management and analysis of the sequences were performed within the MetaSAMS platform and by using GenDB, an automated genome annotation system for prokaryotic genomes. Bioinformatic analysis of the obtained data revealed a rather large number of genes with homology to different CCME, including chitin synthases, chitin deacetylases, chitinases, and chitosanases. A full-length sequence putatively coding for a bacterial chitinase was selected for further investigation. Its sequence was codon-optimized for E.coli expression, synthesized, cloned into E.coli, and the corresponding recombinant protein was expressed. Chitinase activity was demonstrated by dot activity assays, establishing proof-of-principle that metagenomic sequencing followed by automated genome annotation can be used as a promising source for novel CCMEs.

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As part of the Synthetic Yeast Genome Project (Sc2.0), an inducible evolutionary system (SCRaMbLE) was developed using a synthetic yeast chromosome arm, synIXR, by inserting recombinase target sites in specific regions, according to predefined design principles. By inducing a chemically regulated form of Cre recombinase, cells undergo structural variations (inversions, deletions, duplications) generating potentially complex populations with many distinct derivatives (SCRaMbLEotypes) through in vivo scrambling. By sequencing SCRaMbLEd genomes, it will be possible to elucidate evolutionary trajectories compatible with viability. Identifying and quantifying recombination events and determining the novel genomic sequence generated by scrambling poses challenging computational problems. We performed in-depth sequence evaluation of >70 genomes subjected to SCRaMbLE using a custom analysis pipeline to detect structural variations, quantify copy number variations, and perform sequence reconstruction. The strains had for the most part been selected for loss of function in one of two genes. The pipeline is efficient and scalable for massive sequencing analysis of SCRaMbLEd strains. We identified 491 novel junctions that resulted from scrambling; under the conditions used, scrambled derivatives of synIXR had on average approximately 2 deletions and 1 inversion per synIXR chromosome, along with smaller numbers of duplications and complex rearrangements that are difficult to characterize. Because all strains were selected for loss of one gene, which only occurred via deletion, the data are consistent with equal frequencies of deletion and inversion, as predicted by the theory and confirmed by our statistical model. Our analysis shows that rearrangements occurred only at loxP sites, with no preference. Also, no ectopic rearrangements were observed in synIXR or in the remaining 99% non-synthetic genome. SCRaMbLE is an effective mechanism for generating genome diversity in a predefined genomic region, and is expected to be scalable to a fully synthetic genome designed by the same principles as synIXR.

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Biomolecules in Nature interact with solid materials by producing and degrading, as well as attaching to them. Material binding proteins found in Nature can serve as a basis for the engineering of biointerfaces but an understanding of the molecular origins of biomolecular interactions is often required for their technological use. We have studied and engineered material binding proteins for various applications. Examples include proteins binding to hydrophobic – hydrophilic interfaces (fungal hydrophobins), carbohydrates such as cellulose and chitin (fungal and bacterial carbohydrate binding domains), and biominerals (aspeins from oyster). As these proteins have shown strong binding to technologically relevant materials (carbon nanotubes, graphene, nanocellulosic paper, and calcium carbonate, respectively), they show great promise for use in applications. Furthermore, combinatorial peptide library selection methods can be used to develop solid binding peptides to materials not found in nature. This approach can be challenging as the interactions required are usually not typical in biology. We have generated diamond-like carbon binding peptides by phage display that may find use in water-based lubrication and in interfacing biology with electronics. Utilizing the material specificities of these natural and non-natural biomolecules enables the interlinking of different material components together for example in biomimetic composite materials. Furthermore, these proteins may show use in interfacing engineered biological systems with solid or nanomaterials.

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We have recently engineered a set of polymerases that allow genetic information to be transferred to, and retrieved from, a variety of unnatural nucleic acids with distinct physicochemical properties (XNAs). These synthetic polymers are now accessible for evolutionary exploration. As a proof of principle, we have selected aptamers (functional nucleic acid structures) entirely composed of a nuclease-resistant XNA, anhydrohexitol nucleic acid (HNA), from a pool of random sequences. The evolved aptamers bind their targets, a protein (Hen Egg Lysozyme) and an RNA motif (HIV-TAR), with high affinity (nM) and specificity in several different assays, including when presented on the surface of cells. XNA has the potential to overcome problems associated with the use of RNA and DNA structures in biotechnology and medicine.

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Synthetic biology is a new and exciting research field of intense activity, profoundly affecting our perception of the way living organisms work, and the realization of their genetic programs. Synthetic biology encompasses many different methodologies and disciplines, combining approaches from molecular biology, biotechnology and engineering with the objective to design and construct new biological functions and systems which are not found in nature. Our laboratory has developed MultiBac, a technology for producing eukaryotic multi-protein complexes in previously unattainable quantity and quality, catalyzing progress in many areas of the life sciences. MultiBac has become the technology for multi-protein complex production, and already has been distributed close to 500 laboratories world-wide. MultiBac relies on a baculoviral genome from AcMNPV. When developing MultiBac, we engineered this genome by deleting proteolytic and apoptotic activities, applying classical gene-deletion approaches, thus improving the quality of recombinant protein significantly. MultiBac was first mainly to produce high-quality sample for structural biology. More recently, applications of MultiBac emerged that used modular and iterative modification of the genome for wide range of applications including gene therapy or glycoengineering of human therapeutic proteins. Currently, all these applications rely on baculovirus genome (~133 kb) derived from wild-type AcMNPV. This genome has been intensively researched. Genes that are essential for propagation in cell culture and genes which are detrimental for foreign protein production were delineated. beneficial alterations to the genome by classical techniques require currently an excessive effort by specialists. Therefore, it is not possible to fully exploit the vast potential of the baculovirus system to-date. We propose to completely reverse the methodology by using synthetic biology approach. By applying synthetic biology techniques, we aim to completely rewrite, rebuild and improve the baculovirus genome to provide customized engineered surrogates that are tailor-made to fulfill particular needs in academic and industrial R&D.

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Keywords: DIYbio, participative, synthetic biology, publics Over the past five years DIYbiologists, biohackers and alike have been exploring and experimenting with a variety of participative practices. Those include organizing street workshops and holding booths at science festivals; setting up community laboratories, posting online videos and working closely with journalists and artists. Those activities reflect DIYbiologists intentions to make biology and biotechnology available to everyone, and establish what they understand as a truly democratic biotechnology. Meanwhile, struggling between claims and realities, the hope of a distributed and open biotechnology have also been made and defended by the early founders of synthetic biology. More recently researchers in the field of synthetic biology have also engaged in a variety of collaborative and ‘public outreach’ initiatives. These includes ‘classical approaches’ such as the invitation of leading scientists to join public conferences and events, but also more experimental approaches such as the Synthetic Aesthetic initiative; a project where synthetic biologists were invited to collaborate with designers and social scientists to explore the notion of design and nature. Following a three years ethnographic study of the DIYbio and biohacking network this paper compares the participative discourses and practices claimed and actually developed by both the members of the DIYbio network and the researchers in the field of synthetic biology. As the role of the public is becoming more influential on the development of science and technology, this paper’s aim is i) to critically highlight how the participatory initiatives from the DIYbio network and the ones from the synthetic biology community differs and ii) propose practical solutions so that those differences can become part of a productive synergy.

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When looking to design gene regulatory networks, ensuring that the network is robust is a high priority. We have performed an analytic and computational investigation on nonlinear models of gene motifs. There are many competing definitions of robustness that are applicable to synthetic biology (e.g. [1], [2] & [3]). Using a measure of parameter robustness based on the one put forward by Del Vecchio et al. [1], we isolate the effect of changing topology on the robustness and show how moving between different motifs affects robustness. These results are useful for predicting how (for example) knockout experiments will affect the robustness of genetic networks. [1] Ghaemi, R., Sun, J., Iglesias, P. a, & Del Vecchio, D. (2009). A method for determining the robustness of bio-molecular oscillator models. BMC systems biology, 3, 95. doi:10.1186/1752-0509-3-95 [2] Rizk, A., Batt, G., Fages, F., & Soliman, S. (2009). A general computational method for robustness analysis with applications to synthetic gene networks. Bioinformatics (Oxford, England), 25(12), i169–78. doi:10.1093/bioinformatics/btp200 [3] Kitano, H. (2007). Towards a theory of biological robustness. Molecular systems biology, 3(137), 137. doi:10.1038/msb4100179

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Utilising biological light sensors to gain control over transcriptional regulation was realised through years of research on the structural nature of the light-harvesting protein domains, encountered mainly in photosynthetic organisms. The Cph8 chimera introduced by Levskaya et al. (2005), was one of the first examples on how light can provide a non-invasive, cheap and reversible induction scheme. These advantages, absent in chemical inducers, hold promising potentials for developing a framework for gaining temporal and even spatial control over cellular metabolism. Our work is focused on the experimental characterisation and mathematical modelling of the dynamics of light responsive systems and on optimising them for a robust and predictable transcriptional photo-regulation. We worked on coupling such light input modules with existing synthetic genetic devices like the toggle switch and the dual feedback oscillator in order to gain control over the frequency and amplitude of the oscillation through light.

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The success of the artemisinin project from Amyris has demonstrated that microbial biosynthesis of natural product pharmaceuticals is a viable production platform to address global drug needs. Plant secondary metabolites, like artemisinin, are a rich source of established and potential drug candidates. However, our capacity to extend artemisinin’s success to other plant pathways is limited by our ability reliably engineer complex natural product pathways in microbial hosts. Plant pathways are particularly challenging due to the number and types of associated enzymes and in particular, the prevalence of cytochrome P450s. We have focused on engineering Saccharomyces cerevisiae as a microbial production platform for the benzylisoquinoline alkaloids (BIAs), a large class of plant secondary metabolites that exhibit a wide range of pharmacological activities, including anti-HIV, anticancer, and antimicrobial activities. Through engineering BIA biosynthetic pathways in yeast we have sought to (1) create a reliable and scalable source of valuable drugs and drug candidates and (2) gain an understanding of the effects of complex pathway expression on the host system and develop generalizable optimization strategies that will broadly advance the development of microbial production platforms for complex plant natural products. We have engineered strains of Saccharomyces cerevisiae capable of producing various protoberberine and benzophenanthridine alkaloids. In particular, strains that produce the key branch point intermediates reticuline and scoulerine have been developed and used to produce the compounds cheilanthifoline and stylopine through the addition of two sequential cytochrome P450 transformations. The number and types of chemical transformation steps achieved in this work represents one of the most complex examples in the field of metabolic engineering. We have developed a number of pathway optimization strategies for improving pathway flux and functional microbial expression of plant cytochrome P450s including spatial control over pathway enzymes and transport control over intermediate metabolites.

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Large-scale genome engineering represents a broad group of technologies, all of which stand to impact the manufacturing of a range of biological and chemical products. While the power of these methods to increase the production of biologically-driven manufacturing processes has been previously demonstrated, they are often developed and optimized toward a single target, or single methodology. For example Multiplex Automated Genome Engineering, or MAGE has been used to simultaneously engineer all 20 genes in an important isoprenoid pathway in Escherichia coli to produce record lycopene yields. Automating this method required a range of custom instrumentation, not suited to other genome engineering methods or targets without dramatic reconfiguration. Therefore, a platform does not currently exist that enables a broad range of genome engineering methods directed towards a diverse range of biomanufactured products. Advanced Liquid Logic (ALL) has developed a powerful software-programmable liquid handling technology called digital microfluidics. ALL is currently collaborating with a number of lead users to automate a broad range of synthetic biology and genome engineering protocols. These include: gene synthesis using oligonucleotide building blocks, quality assessment of synthetic genes, cell-free gene circuits and targeted genome engineering. Specific features of the ALL platform make it ideal for these applications. Software programmability provides a high degree of application flexibility, allowing users to generate multiple bioassay protocols which can be run on the same instrument and disposable cartridge. In addition, a new software development architecture is under development, allowing real-time monitoring and intervention of each reaction droplet. The platform also provides support for a range of molecular biology processes, including thermocycling, magnetic bead operations and optical detection (including both fluorescence and chemiluminescence). Coupling general molecular biology capabilities, with software-based control over hundreds of reaction droplets provides an automation platform uniquely suited to both synthetic biology and genome engineering.

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Scientists have leveraged similarities between synthetic biology and engineering in order to apply engineering techniques to genome design. One of such techniques, called iterative design, has enabled scientists to generate viable synthetic organisms by conducting iterations of design, prototyping, and evaluation. However, the tools used during evaluation can still lead to uncertainties on how to correct undesirable behavior. The synthetic biology community needs better platforms to debug the mechanics of synthetic organisms both in silico and in vivo in order to avoid wasted effort and resources used during wet lab implementation. In order to address these issues we have constructed a software platform that can perform the first formalized debugging method for synthetic and systems biology. The method allows users to refine their models by translating a model to a biological instruction set and perform debugging techniques similar to that seen in integrated development environments for software engineering. After in vivo implementation of the refined model, expression data can be compared with the expected deviation of multiple stochastic model simulations in order to identify runtime reactions, events or other instructions that did not occur as expected in vivo via simulation breakpoints provided by the debugger. This technique increases the prediction of defects that cause unexpected behavior in synthetic organisms and allows for a much more efficient iterative process. We applied the debugging methodology to a variety of different models to test the methodology’s viability. The models ranged from classic examples of designs in synthetic biology to completely novel systems. In each case we demonstrated the effectiveness of the debugger in identifying runtime defects and demonstrate how useful the methodology can be for improving iterative design of synthetic organisms. Funding for this project provided by the National Science Council (NSC) of Taiwan (NSC 101-2319-B-010-002 and NSC101-3113-P-110-002).

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There is currently immense interest in the development of artificial nucleic acid structures as analogues of natural forms. Until now, examples have been based on organic components, for example PNA and the various other forms of XNAs. As far as metal-based analogues of nucleic acids are concerned, attention has instead been largely focused on replacing nucleobases with metal-binding ligands. In an alternative approach, we have turned our attention to the synthesis of unprecedented metal-based nucleic acids, in which the nucleobases are retained but components of the sugar-phosphate backbone are replaced with metal-containing units. To this end, we recently reported the synthesis of FcNA, or ferrocene nucleic acid (Nguyen et al), that has a structure consisting of repeating iron-containing ferrocene units. Each unit is covalently linked to two nucleobases and connected to one another by a negatively charged phosphodiester group. Oligomers containing up to eight ferrocene units (i.e. 16 nucleobases in total) have been prepared, as well as FcNA-DNA conjugates. This talk will give an overview of our results on this new metal-containing nucleic acid form, involving a description of how the oligomers are made and initial results concerning their physicochemical properties, including their electrochemistry. H. V. Nguyen, Z. Zhao, A. Sallustrau, S. L. Horswell, L. Male, A. Mulas, J. H. R. Tucker, Chem. Commun., 2012, 48, 12165.

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We are going through a stage where Synthetic Biology is gaining relevance and, although there are many available tools for working in the Synthetic Biology field aimed at bacteria, Plant Synthetic Biology is still emerging. To overcome the existing limitations on the design and construction of new genetic combinations, the GoldenBraid assembly system was improved into a new version, GB2.0, which has strengthen its grammar and has created a collection of standard DNA parts and genetic modules. The GB assembly process, though simple, implies multiple steps to build a multigenic module. The first of them is the adaptation of a sequence to the standard; then, different standard parts can be assembled together in a multipartite reaction. Finally, transcriptional units, as well as preformed modules, can be assembled together in a binary reaction. To manage the growing GBcollection it was necessary to create a database that houses all the data in an organized way. Therefore we created the GBdatabase using PostgreSQL, a powerful database management system. GoldenBraid2.0 offers also the Gbtool-kit, a set of three computational tools that guide the user through the GBassembly process. The first of them, named GBDomesticator, adapts the input DNA sequence provided by the user to the GBstandard. The second tool, named GBMultiAssembler, performs the in silico multipartite assembly of GBparts to create a transcriptional unit (TU). Finally, the last tool is named GBinAssembler, and allows the binary assembly of preformed TUs or modules over the GoldenBraid loop to produce multigenic structures. The GBdatabase and the GBtool-kit are presented in a website using Django, a Python web framework that supports rapid design and development of web based applications. The development of this project shows that synthetic biology is an interdisciplinary field that needs from the computational science to exploit all its potential.

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Recent developments demonstrate that the combination of microbiology with micro- and nanoelectronics is a successful approach to develop new miniaturized sensing devices and other biochip technologies. In the last decade, there is a shift from the optimization of the abiotic components, e.g. the chip, to the improvement of the processing capabilities of cells through genetic engineering. The multidisciplinary approach of synthetic biology will not only give rise to systems with new functionalities, but will also improve the robustness and speed of their response towards applied signals. In this project, we aim to illustrate the potential of integrating microbiology with microdevices by the development of a new biological part that allows transfer of information from bacteria to microchips by means of electrical signalling. In order to obtain electrical signalling between bacteria and micro-electronic devices, we exploit the redox cycling behaviour of electron shuttles. In the first stage of this project, pyocyanin, an electron shuttle produced by Pseudomonas aeruginosa, was selected as an appropriate electron signal to establish the electrical connection between bacteria and microchips since it’s possible to detect pyocyanin in bacterial cultures in a quantitative manner with microchip-based detection techniques. By introducing the biosynthesis pathway of pyocyanin in Escherichia coli, bacterial biosensor cells are capable of producing pyocyanin in a dose-response manner when detecting a specific analyte. Although pyocyanin is proven to be an accurate molecule to establish an electrical connection between bacteria and microelectronic devices, the production of pyocyanin by E. coli requires further optimization. Therefore, pyocyanin production is further optimized in this study by tackling the toxicity of pyocyanin through an evolutionary approach. When pyocyanin production by E. coli and pyocyanin detection with the microelectronic system is fully characterized, pyocyanin can be exploited as a new reporter molecule in bacterial biosensors and used to develop novel microchip-based biosensors.

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Cyclic expression of genes (i.e. oscillations) is essential for multicellular life and it is involved in basic processes such as the cell-cycle and the circadian clock. Ultradian oscillations, i.e. with periods much shorter than 24 hours, have been observed also in the major signalling pathways, but their relevance is still unclear. Specifically in myoblasts, ultradian oscillations of the Notch-effector gene Hes1 have been observed but their role is unknown. Differentiated myoblasts, however, do not exhibit any ultradian oscillation. The Notch family of cell surface receptors is involved in contact-mediated cell-to-cell signaling (Artavanis-Tsakonas et al.,1995; Weinmaster,1997). The Notch pathway regulates downstream responses, such as cell-fate specification, progenitor cell maintenance, boundary formation, cell proliferation and apoptosis. Notch signaling also mediates the synchronization of cyclic gene expression of effector genes among cells, an essential process during the somite segmentation of vertebrate embryos. The aim of the project is to understand the physiological significance of Hes1 cyclic gene expression in myoblasts. We will use a synthetic biology approach to investigate the role of Notch-Delta signaling in myotube differentiation, to verify the role of cyclic gene expression in cell proliferation, cell differentiation and in specification of compartment and boundary cells. Whether these oscillators regulate the timing of differentiation system as a clock also remains to be determined. We chose as a model the mouse C2C12 myoblast cells. We first evaluated existing gene expression profiles (Dilusha A. William, Kenro Kusum, 2007) to estimate the endogenous expression level of Notch family and its ligands. We then confirmed the results by quantitative RT-PCR. Our preliminary results show that the Notch pathway is indeed active in C2C12 cells. We will now investigate Hes1 oscillations in single cells during differentiation, and the effect of blocking Hes1 oscillations by constitutively activating or inhibiting Notch signaling.

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Manipulation and fine-tuning of gene expression is critical for a large number of bioengineering applications aiming at altering a wide range of cellular behaviours. Regulation can be achieved on the transcriptional and the translational level. Transcriptional promoters and regulatory factors can be manipulated and changed, allowing control over how fast (or slow) RNA is synthesized or degraded. Alternatively, at the translational level the copy number of a protein, e.g. influencing the flux through metabolic pathways, can be fine-tuned by altering ribosomal binding sites, initiation factors, and optimizing codon usage. Translation initiation is the most regulated phase during protein biosynthesis and is also the rate-limiting step. It is therefore a promising target for expanding our toolbox of cellular control devices. Viruses and eukaryotic cells have very successfully evolved mechanisms using internal ribosomal entry sites (IRES) to bypass the rate-limiting and highly regulated classical eukaryotic translation initiation machinery. IRESs are able to drive translation with a reduced (or no) set of initiation factors and initiate translation through direct interaction with the ribosome. It would be of significant value for bioengineers to have a tool analogous to the virus IRESs for use in prokaryotes, enabling rational fine-tuning of translation initiation. To this end we have designed standardized translation initiation region (TIR) constructs based on an existing Escherichia coli (E.coli) IRES-like TIR. We have generated a randomized library of TIRs using error-prone PCR and directed evolution. Using an in vitro reconstituted translation system we have assessed the ability of our TIRs to drive protein synthesis in the presence and absence of specific translation factors. The aim of this study is to provide the Registry of Standard Biological Parts with a well characterized TIR library able to efficiently drive protein synthesis in a predictable way using a reduced number of translational factors.

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Quorum Sensing mechanisms have been on the table in the last few years. Auto-inducer mole-cules were used as “chemical wires” to obtain in vivo logic circuits [1]. Also QS was used to synchronize oscillators in [2] and to tune two-step bistable circuits inducing phenotypic diversification in [3]. In this contribution, we use QS to indirectly drive a population of bistable cells to a desired state in a robust way, by using a second mediating population of regulatory cells. On the one hand, the bistable cells carry a genetic circuit containing the LuxI-LuxR-AHL system along with the LuxR-AHL activated promoter, thus implementing a positive feedback loop in a one-step circuit. Regulatory cells, on the other hand, have a regulated circuit that contains a negative feedback loop based also on the LuxI-LuxR-AHL system, but using an engineered LuxR-AHL repressible promoter [4], which can be found as part BBa_R0061 from the Registry of Standard Biological Parts. We rely on the CcaS/CcaR TCSs system [5], and use light as a control knob to drive the regulatory cells to a desired expression level of LuxI. This, in turn leads to set the appropriate level of the auto-inducer signal to broadcast to the bistable cells. This control of the population-ratio of bistable cells in each of both states has broad applications in synthetic biology. References: [1] A. Tamsir, et al. Robust multicellular computing using genetically encoded NOR gates and chemical wires, Nature (2010). [2] T. Danino, et al. A Synchronized Quorum of Genetic Clocks, Nature (2010). [3] R. Sekine, et al. Tunable synthetic phenotypic diversification on Waddington’s landscape through autonomous signaling. PNAS (2011). [4] K. A. Egland, et al. Conversion of the Vibrio fischeri transcriptional activator, LuxR, to a re-pressor, Journal of Bacteriology (2000). [5] J.J. Tabor, et al. Multichromatic control of gene expression in Escherichia coli. J Molecular Biology (2011).

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A biomolecular network is called adaptive if a specific output concentration returns to the original value after a transient response even under a persisting stimulus. Adaptation is an important mechanism to reset cellular sensing systems to a basal level, and serves to have cells react to changes in a stimulus only, but not to specific constant stimulus values. Biochemical networks with adaptation have for example been studied in eukaryotic gradient sensing, bacterial chemotaxis, yeast osmo regulation, and cellular signal transduction via the MAP kinase pathway. From a systems perspective, the conditions for a biochemical network to be adaptive are well known and straightforward to check on a mathematical model of the considered network. These conditions typically imply the existence of an internal feedback or feedforward circuit structure in the network. In this contribution, we look at the design problem for adaptation in biochemical networks. In contrast to the problem of checking whether a given network is adaptive, designing a network for adaptation is more challenging, especially for medium and large-scale networks. We present a systematic approach, based on a linear network approximation and the notion of kinetic perturbations, to design reaction rate modifications that make a biochemical reaction network adaptive. The approach indicates all interactions in the network where a modification can yield adaptation, and provides specific values for such modifications. An advantage of our approach in the context of synthetic biology is that both the stoichiometry as well as the steady state in the unstimulated system are not perturbed by these modifications. Thus, a predesigned network can be tuned to be adaptive without interfering with other core properties of the network. Furthermore, the method covers both parameter and network structure modifications and can be applied to any reaction rate formalism and even to medium-scale or partially unknown models.

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Advances in de novo synthesis of DNA and assembly methodology make construction of synthetic chromosomes a reachable goal. Considering a potential design leads almost certainly to the question what the essential parts of a chromosome are. Investigations on this question have mainly focused on the minimal set of genes needed to allow cells to live. However, chromosomes are more than arrays of genes. Chromosomes need systems to replicate, segregate and organize the encoded genetic information. We explore such chromosome maintenance systems by application of synthetic biology approaches. Our goal is the design and assembly of secondary synthetic chromosomes in Escherichia coli. The natural template is the human pathogen Vibrio cholerae which carries a natural secondary chromosome. Chromosome maintenance systems usually consist of proteins binding to sites with specific chromosomal distributions. The construction of synthetic secondary chromosomes will allow variation of this binding site distribution. Downstream functional characterization should allow deeper understanding of chromosome maintenance. As a proof of principle we designed a set of three secondary synthetic chromosomes with varied distribution of GATC sequences. GATC is the target sequence for MutH, involved in DNA mismatch repair and SeqA, which is involved in chromosome segregation. The synthetic chromosomes are designed to bind only MutH, the dimeric SeqA and MutH or none of the proteins. Analysis of mutation rates should provide insights into a potential functional interplay of mismatch repair and chromosome segregation. Our long term goal is to establish synthetic secondary chromosomes as experimental system to study chromosome maintenance and to provide chromosome construction rules for biotechnology applications.

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Biological systems maintain proper functioning in changing environments by performing complex computations on environmental inputs and determining appropriate responses. These biological computations can be constructed in a bottom-up approach by fundamental additive and subtractive operators. Despite a growing number of examples of synthetic biological devices that execute computational functions, limited effort has been directed toward building subtractive devices. We have designed a genetic operational amplifier (gen-opamp), which serves as a key subtractive component in most circuit systems. This gen-opamp consists of three stages: a differential sensor, an amplifier, and an output stage. The differential sensor contains a molecular transducer, which maps the input levels to mRNA levels, and a RNA sense-antisense subtractor as the core of the differential calculation. The genetic differential signal is amplified by a transcriptional device, which is subsequently used to regulate the expression of protein outputs to reveal the comparison result. The non-feedback configuration of the gen-opamp can function as a comparator, whereas the feedback level-setter can keep the ratio of the input levels by actively re-adjusting one to the other. We implemented this gen-opamp using theophylline and tetracycline as the inputs. The corresponding aptamer-coupled ribozymes are implemented as molecular transducers within the targeted mRNAs, together with a mutual complementary 150-bp sense-antisense pair to achieve subtraction. The amplifier is implemented using a synthetic LexA-based promoter regulating either an activator (caffeine demethylase) or deactivator (theophylline demethylase) to form an enzymatic feedback loop targeting the theophylline input. Preliminary results suggest that each of stages of the gen-opamp exhibit desired activity when characterized individually; further partial assembly of each stage proves their compatibility and functionality as a whole. Building a gen-opamp can be a significant milestone towards designing more sophisticated genetic circuits in synthetic biology and understanding the nature of differential genetic interactions in biological networks.

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Here we report the design and construction of a modular and tunable genetic amplifier in E. coli that can amplify weak transcriptional input signals in linear analogue mode with continuous tunable gain control. The three-terminal transcriptional device comprises orthogonal genetic components (hrpRS, hrpV and PhrpL) from the hrp (hypersensitive response and pathogenicity) gene regulatory network in Pseudomonas syringae. In contrast to other work, our design approach focuses on controlling the amounts of in trans acting protein components to achieve tunable devices. Our results show that the amplifier can linearly amplify 20-fold the transduced transcriptional signal of an arsenic-responsive sensor without observable response delay, thus greatly enhancing the sensitivity and dynamic range of the biosensor. To showcase the flexibility of the device, we generated a set of genetic amplifiers with different gains and input dynamic ranges by varying the expression levels of the underlying activator proteins in the device. Furthermore, we appended a third modular terminal to control the expression of an inhibitor protein for the output transcriptional rate, thus acting as a gain-tuning knob for our amplifier. As a result, the amplifier was able to modulate transcriptional signals with a continuous tunable gain depending on this additional external signal input. The device was demonstrated to be modular since it can amplify the transcriptional inputs from a set of constitutive promoters of different strengths with the same gain as the one measured for the arsenic sensor. To our knowledge, the engineered genetic amplifier is the first analogue device in the field that allows linear transcriptional signal amplification with a tunable high gain and a large dynamic range output. The device could have a wide range of applications for tuning transcriptional signals in gene circuits, e.g. for enhanced biosensing, and in metabolic pathways for improved bioproduction.

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The ribosomal incorporation of single and multiple unnatural amino acids (AAs) for fabrication of redesigned peptides and biological systems is generally limited by low incorporation efficiencies. We used our purified translation system and quench-flow techniques to study the kinetics of translation with unnatural AA-tRNAs prepared via the standard aminoacyl-pdCpA chemoenzymatic ligation method [1,2]. Single incorporation of allyl-glycine (aG) into peptide had a similar rate to Phe [3]. However, the binding affinity of aG-tRNA to EF-Tu was lower [3], indicating that the low incorporation efficiency of aG [4] was caused by inefficient delivery. Furthermore, in kinetic studies of five consecutive incorporations with aG, the processivity was lower than with natural Ala-tRNA(Ala). This is in a line with our earlier observation [4] that the deoxyC introduced to the tRNA body in the chemoenzymatic ligation method decreased the yield. Peptidyl-tRNA hydrolase assays indicated that the lower processivities were caused by drop-off of intermediate-length peptides. Full processivity could not be recovered by increasing EF-Tu concentration, indicating that the delivery of the AA-tRNA was not limiting in the case of multiple adjacent unnatural AA incorporations. We conclude that the incorporation efficiencies of single non-N-alkylated unnatural AAs can be improved by increasing EF-Tu concentration, while incorporations of multiple unnatural AAs might be improved using aminoacyl-pCpA instead of aminoacyl-pdCpA. References: 1. S A Robertson, C J Noren, S J Anthony-Cahill, M C Griffith, P G Schultz (1989) Nucleic Acids Res. 17,9649. 2. M Y Pavlov, R E Watts, Z Tan, V W Cornish, M Ehrenberg, A C Forster (2009) PNAS. 106(1), 50. 3. K-W Ieong, M Y Pavlov, M Kwiatkowski, A C Forster, M Ehrenberg (2012) JACS. 134, 17955. 4. R Gao, A C Forster (2010) FEBS Lett. 584(1), 99.

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Alternative splicing (AS) of mRNA is a major source of biological diversity and regulation in eukaryotes. Despite its rapidity and flexibility as a regulatory mechanism, AS remains under-utilized in synthetic biology devices. The mammalian AS system contains multiple standard regulatory network motifs including positive and negative feedback loops. In many cases, AS functions as a switch modulating critical biological functions, such as cell fate and identity determination during development in multicellular organisms. AS allows cells to respond to environmental cues at the post-transcriptional level, and often more rapidly than through transcriptional regulation alone. Here, we demonstrate a splicing-based circuit in mammalian cells that confers memory of extracellular stimuli based on the autoregulatory feedback loop from the splicing regulation of Sex-Lethal (Sxl), the Drosophila sex determination master gene. We show that the positive feedback loop of Sxl regulating the splicing of its own mRNA is conserved in mammalian cells as in Drosophila. Furthermore, this positive feedback loop has the potential of serving as a device to rapidly retain memory of transient exposure to stimuli in mammalian cells. Our splicing-based memory device explores the potential of AS regulatory networks and will contribute to the study of long term effects of transient stimuli on cells as well as our knowledge of post-transcriptional regulation in biology.

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One of the primary goals of synthetic biology is the application-driven generation of new parts, circuits, and systems to solve problems that as yet have not been adequately addressed. The parasitic infection Schistosomiasis affects over 200 million people worldwide, with estimates suggesting that a further 780 million people are at risk of infection. The causative agents are fluke worms of the Schistosoma genus, and infection only occurs when the cercarial larvae are able to penetrate the skin. To facilitate this, the cercariae secrete an elastase possessing a defined substrate specificity. Our project takes advantage of this property of the cercarial elastase, and has used it to design and create biosensors that are specific in targeting Schistosoma. The design of our biosensor is based on a two-pronged approach, 1) an accurate detection system which is targeted to the cercarial elastase, and 2) an easily measurable output. Using synthetic biology approaches we have engineered the biosensor to be “housed” in two bacterial chassis, Bacillus subtilis and Escherichia coli. The B. subtilis biosensor is a fusion protein that possesses the cell wall binding domain of LytC along with our biosensor component, whilst the E. coli biosensor is composed of the CmpX protein, which traverses the outer membrane, fused with our biosensor component. Both biosensor components are presented to the external environment, and possess the cercarial elastase recognition motif, as well as a streptavidin binding peptide, which can be detected by a streptavidin fluorophore conjugate. Thus when the elastase is present it cleaves the biosensor at the recognition motif site, thereby releasing the detectable component, our streptavidin binding peptide. Here we report and discuss the progress we have made in this exciting and important project.

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Here we show the most recent work towards a minimal degrade-and-fire oscillator in Saccharomyces cerevisiae. This type of oscillator has been shown to work in bacterial chassis, but has not yet been constructed in yeast. Gaining insight in the transition of genetic circuits from one chassis to the next (‘porting’) is important because it expands the applicability and use of work done in one organism to other organisms that have better characteristics in a particular application. The oscillator was chosen as an example circuit because time keeping is one of the basic functions that lie at the foundation of biological computation, along with sensors, switches and memory. The main focus is on the design and characterization of parts. This touches on degradation tags, nuclear localisation tags and promoter repression characteristics in particular. Our mathematical model has shown the need for strong non-linearity in the repression of the promoter as a function of inhibitor concentration. The tetrameric LacI repressor is capable of the intended cooperative effects, however the promoter architecture needs to match this capacity for the intended non-linearity to arise. This imposes specific requirements on the placement of regulatory sequences on the promoter. We show how these design rules resulted in promoter modifications and what the repression characteristics the new promoters have. These characterizations are necessary to determine the most suitable part for the construction of circuits such as a genetic oscillator in yeast, which we are focusing on in particular.

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In order to enable the engineering of cellular function in living organisms, it is necessary to develop tools that are both genetically encoded and capable of regulating endogenous protein levels in response to user-specified molecular signals. The goal of this project is to engineer a set of microRNA regulatory networks with integrated modular ligand sensors for the reversible arrest of living mammalian cell populations in G0/1, S, G2, and M. Unlike currently available small molecule inhibitors of the cell cycle that broadly disrupt cell function, a switchable microRNA platform allows inducible cell cycle arrest through regulation of specific endogenous gene targets with potentially any small molecule effector by modular replacement of the microRNA targeting sequence or aptamer-based sensing region. We have identified promising RNAi targets for G0/1 arrest in a human cell line, measuring over 76% knockdown of mRNA levels by qRT-PCR and accumulation of over 92% of cells in G0/1 by flow cytometry. By creating cell lines with stably integrated microRNA regulatory networks, we have quantitatively measured mature microRNA and target mRNA levels by qRT-PCR, as well as target protein levels and cell cycle distribution by flow cytometry, providing a detailed picture of the changes in gene expression that lead to a measurable phenotypic change. The creation of a model cell line that can be easily and reversibly paused at specific cell cycle phases has potential applications for increasing heterologous protein production, better control of signal processing in the self-renewal versus differentiation decision, and increasing the reliability of mammalian genetic integration techniques. More broadly, these ligand-responsive microRNAs represent a general class of synthetic biology tools that can be adapted for sophisticated control of complex cellular processes in higher organisms.

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Microbial biofilms are cell communities that coordinate behaviour and gene expression at the population level. Due to the production of a defensive extracellular matrix, biofilms are extremely difficult to disperse with antimicrobial agents and subsequently pose a major challenge in healthcare and industrial settings. Rapid detection of this bacterial phenotype could assist greatly in treating and eradicating biofilm colonisations. An in vitro biosensor has been developed which targets biofilm signalling molecules by expressing a detection module within a cell-free transcription and translation context. Our current efforts aim to detect the early-stage biofilm signalling molecule cyclic diguanylate (c-di-GMP) using this system. The Vibrio cholerae transcription factor VpsT can upregulate the expression of a reporter module in the presence of c-di-GMP. Previous work focused on the detection of the quorum-sensing molecules acyl homoserine lactones (AHL), which also play a key role in pathogenic biofilms. By expanding the number of detection targets for biofilm formation, this approach shows the adaptability of the in vitro biosensor platform. Furthermore, it can potentially increase the specificity of detection to differentiate between stages of biofilm formation and virulence.

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The gut microbiota is integral to many facets of human biology, including pathogen susceptibility, immune disorders, diabetes and obesity. Gut-resident microbes are highly adapted to perceive and respond to conditions within the gut and can be considered platforms for diagnostic applications, therapeutic production and delivery, and for probing intestinal biology. The gut serves as an interface that is highly evolved and receptive to symbiotic interaction with microbes and represents a promising target for microbially produced therapeutics. Recent microbiota-focused mechanistic studies have elucidated a number of potential avenues for manipulating gut community composition and host response, but require the development of cell-based engineering tools for human-associated microbes. Here we apply synthetic biology principles proven in E. coli to improve the engineering of a model intestinal symbiont Bacteroides thetaiotaomicron (Bt). Our improvements in symbiont engineering include (i) redesigning Bt integration vectors to allow rapid assembly, via Golden Gate (ii) creating and characterizing expression machinery, including promoters stronger than previously available, and (iii) implementing strategies for reduced context dependence of expression machinery to provide reliable control of protein expression in Bt. Synthetic biology offers a powerful approach to study the gut microbiota, providing tools to help bridge the gap between sequencing complex gut microbial communities and defining molecular mechanisms. Applying the principles of synthetic biology to host-associated microbes represents a frontier in biomedicine.

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We have generated a synthetic sex distortion system in the human malaria mosquito. By expressing, during spermatogenesis of Anopheles gambiae, a highly specific endonuclease that recognizes sequences present only on the X chromosome we bias the production of functional sperm towards Y chromosome bearing spermatozoa. As a result transgenic males generate offspring consisting largely of males. As the first system of its kind, it bypasses the sex determination mechanism of the mosquito and functions by biasing the transmission of the sex chromosomes. It has been suggested by W.D. Hamilton and others that inducing extreme sex ratios represents a potential strategy for suppressing natural pest populations and thus our finding has direct implications for malaria vector control.

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Pichia pastoris is a useful heterologous protein expression system capable of complex post-translational modifications like glycosylation, disulfide bond formation, phosphorylation and proteolytic processing. However, heterologous protein expression presents a highly unnatural cellular state that invokes a number of responses that adversely affect product quality and quantity. Miss-folded protein can invoke unfolded protein stress response reducing production, while hyperglycosylation gives unfavorable by-products. Induction of many of these deleterious processes is governed transcriptionally. Reprogramming the host transcriptome is a potentially useful way to circumvent or repurpose these events to improve productivity. We have rewired the yeast transcriptome combining promoters open reading frames (ORFs) in a library to assess the influence of ~2800 unique networks on protein production. These are created using 67 promoters and 43 ORFs from transcriptional regulators involved in stress, protein transport and translation. The ability of regulatory rewirings to influence protein productivity was assessed using different heterologous proteins, a membrane bound opoid receptor, human insulin, a large repetitive spider silk protein and an immunotoxin fusion protein. Thus, we were able to probe the library for solutions to problems that currently limit protein production in this system. Our results indicate network rewiring can improve yields up to 8-fold in some cases. Library screening revealed enrichment for artificial rewired networks across all and selected subsets of heterologous protein types. This suggests that rewired networks can lead to general improvement in protein production as well as production improvement for proteins with specific physical characteristics such as large size or highly repetitive sequence. We will present how this network creation technique can lead to elegant expression improvement solutions such as negative feed back loop enforcement, which are not easily achievable using classical network perturbation methods.

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Metabolic engineers seek to direct endogenous metabolic fluxes toward valuable or interesting products. Evolution tends to redistribute these same fluxes in ways that maximize host fitness. To what extent can these two conflicting forces be reconciled? How much can a flux profile be perturbed before host growth begins to suffer? Can we predict how a chassis organism will respond to a perturbed and suboptimal (from an evolutionary perspective) central metabolism? Our work builds on widely used MFA models that treat metabolism as a problem of optimization under constraint. Metabolic reaction rates are constrained to obey thermodynamics and the conservation of mass. Natural selection may work within these constraints to optimize metabolism for some objective, for example fast growth. Yet because of redundancies in the metabolic network, many different flux profiles can be equally optimal for a given objective. Here we formulate a mathematical objective function that accounts for this degenerate optimality. In our model, some fluxes may assume a wide range of values while still allowing near-optimal growth. These same fluxes are shown to be more variable in sets of enzymatic and transcription factor deletion mutants. We suggest that metabolic regulation may tolerate significant fitness-neutral variation. This variation may be exploited to expand the limits of fitness-neutral metabolic engineering, and to better predict host responses to altered metabolism in general.

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Translational processes play a role in regulating genome-wide protein expression levels. While the translational initiation step and codon usage have received much attention, we focus on another aspect, namely tRNA availability. This factor conditionally influences translational speed along a transcript and has been linked to co-translational processes like protein folding. Recent studies have shown that tRNA pools can significantly vary under different growth and stress conditions. Due to tRNAs acting as a shared resource and the ability for synonymous codons to code the same amino acid, modulating tRNA concentrations offers the cell a way to precisely adapt translational dynamics across the genome. With the aim of understanding how such a mechanism is used, we developed a generalized computational workflow that estimates the translational speed of codons along a given transcript and generated speed profiles. We show data for all coding sequences in the E.coli genome. Unlike previous studies that assumed fixed tRNA concentrations, we investigated the sensitivity of these profiles to large shifts in tRNA availability, as experimentally measured during amino acid starvation and for differing growth rates. Visualization of profiles across the entire genome highlighted key gene clusters that were either particularly sensitive or insensitive to tRNA level change, and surprising temporal responses with links to genes that are known to use translational control to alter protein expression level. In addition to analyzing how tRNA availability might be used by E.coli as such, we also consider applications as a control mechanism for synthetic biology. We show how our developed workflow can be applied to: (i) forward-engineering of new protein parts where translational dynamics will respond in a specific way to known changes in tRNA pools; and (ii) help in the design of circuits to artificially modulate tRNA availability to control translational dynamics of endogenous genes across the genome.

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Over the past decade, both academia and industry have increasingly turned to the use of microbes for the synthesis of value-added chemicals. Microbial biosynthesis is advantageous for it affords green, complex chemical reactions at a lower cost. Successful examples include the production of plant-derived malaria drug, artemisinin, in yeast, production scale biosynthesis of cholesterol-lowering drug, Zocor, and synthesis of several biofuels through modified enzyme pathways. Biosynthetic engineering of metabolic pathways have provided new and effective methods for the synthesis of value-added chemicals, drug compounds and biofuels. One of the few major chain-elongation enzymatic families is the polyketide synthases (PKSs), which produces stereochemically and structurally complex drug compounds, such as lovastatin, erythromycin and rifamycin. PKSs are often utilized in biosynthetic applications as they use simple carbon building blocks as feedstock, have a modular assembly-line design and can perform a rich repertoire of chemical reactions. Characterization of novel PKS biosynthetic pathways is a promising line of research for it could lead to the development of new chemical scaffolds for drug development and the discovery of new reaction domains for biotechnological applications.However, many difficulties still exist in manipulation of these gene families. For example, these genes are often very large, making genetic engineering a challenging task even with current technologies. As a result, the journey from PKS discovery to production and then to manipulation is a long process. To overcome this, we will develop a common scaffold on which novel enzymatic domains can be rapidly evaluated for activity. This platform will allow for rapid search and verification of novel enzymatic domains for applications in metabolic engineering and to discover new active biosynthetic clusters.

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As applications of synthetic biology move from the realms of ideas and laboratory-confined research towards real-world implementation, concerns over biosafety are being raised. Re-engineered, self-replicating cells may produce undesired consequences if they escape or overwhelm their intended environment, or if the synthetic information they contain (often plasmid-borne) is utilised by indigenous organisms. To address these biosafety issues, multiple mechanisms for constraining microbial replication and horizontal gene transfer have been proposed. These include the use of host-construct dependencies such as toxin-antitoxin pairs, conditional plasmid replication, or auxotrophies. While refactoring of the existing genetic code or tailoring of orthogonal systems offer future promise of more stringent ‘firewalls’ between natural and synthetic cells, here we focus on what level of biosafety can be achieved currently using the approaches cited above. To maximise system redundancy, such devices are utilised in parallel. An in vivo screen with a high selection coefficient for horizontal gene transfer is introduced, and subsequently used to assess overall efficacy of the systems for biocontainment. Comparison of these results with the theoretical levels desired for maximal biosafety is also made.

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This report is the first describing a simple, low-cost, and extremely sensitive reporter-gene assay system (EPTH system; Enhanced Plant Two Hybrid system) for the comprehensive analysis of agonistic and antagonistic activities of human steroid hormones and related chemicals using transgenic Arabidopsis thaliana. Genes introduced into plant to make biosensors were constructed by fusing DNA fragments (genetic parts) obtained from various organisms containing human, bacteria, viruses, and plant. We succeeded in making six plant biosensors that can detect and determine estrogen, progesterone, glucocorticoid hormone, mineralocorticoid hormone, thyroid hormone, and PPAR ligand specifically by introducing three chimeric genes into each plant. Two effector genes controlled by P35S, a strong constitutive promoter, are overexpressed constitutively in the transgenic plants. Both effector proteins contain nuclear localization signal (NLS) to retain them in the nucleus. Ligand binding to a ligand-binding domain of nuclear receptor from human of the chimeric hormone receptor (effector 1) permits interaction with a nuclear receptor interacting domain of transcriptional co-activator from human of the chimeric co-activator (effector 2). Through this interaction, the transcriptional activation signal of acidic transactivation domain of VP16 (VP16 AD) can stimulate transcription of a -glucuronidase (GUS) reporter gene in the EPTH system. Development of the system opened the way to find chemicals with human steroid hormone activity and anti-steroid hormone activity efficiently not only from purified chemical library but also from extracts of medicinal herbs (50 species) and common foods (80 species) prepared by simple homogenization and centrifugation with no manipulation for aseptic treatment. We will show the lists of chemicals and extracts those with activities described above.

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Polylactic acid (PLA) has been considered an environmentally good alternative to petroleum-based plastic because it possesses several desirable properties such as biocompatibility, biodegradability, and non-toxic to human. PLA is a promising biomass-derived polymer, but is currently synthesized by a two-step process: fermentative production of lactic acid followed by chemical polymerization. Here we reported the production of PLA and its copolymer, poly(3-hydroxybutyrate-co-lactate), by direct fermentation of metabolically engineered E. coli. In this study, the metabolic pathways of E. coli were further engineered based on in silico genome-scale metabolic flux analysis. By using this engineered strain, PLA homopolymer and P(3HB-co-LA) copolymers containing up to 70mol% lactate could be produced up to 11wt% and 46wt% from glucose, respectively. Thus, the strategy of combined systems-level metabolic engineering and enzyme engineering allowed efficient bio-based one-step production of PLA and its copolymers. [This work was supported by the Technology Development Program to Solve Climate Changes (systems metabolic engineering for biorefineries) from the Ministry of Education, Science and Technology (MEST) through the National Research Foundation of Korea (NRF-2012-C1AAA001-2012M1A2A2026556).]

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An extension of directed evolution strategies to genome-wide variations increases the chance of obtaining metabolite-overproducing microbes. However, there is no general high-throughput screening platform to isolate improved strain from tremendous library. Among the various screening methods available currently, selection by the physiology associated with the growth is known to be the most efficient since high producer can be easily enriched simply by a serial culture. However, metabolite overproduction is usually not beneficial features for microbe and consequently, tedious screening process should be used for isolating improved strain from generated library. In this study, to expedite the evolution of metabolite-producing microbes, we utilize synthetic RNA devices comprising a riboswitch and a selection module that specifically sense inconspicuous metabolites. L-lysine-producing Escherichia coli, as a model system, we demonstrate that this RNA device could enrich pathway-optimized strains to up to 75% of the total population diversifying phosphoenolpyruvate carboxylase expression level using randomized promoter sequences after four rounds of enrichment cycles from library. When used in conjunction with combinatorial mutagenesis for metabolite overproduction, our synthetic RNA device strategy should facilitate strain improvement.

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Formaldehyde is an important organic precursor to many materials and chemical compounds. Despite its widespread use, exposure to formaldehyde is a significant consideration for human health due to its toxicity and volatility. Methanol dehydrogenase (MDH) is an NAD+-dependent oxidoreductase that catalyzes formaldehyde to methanol reversibly. Reduction activity of MDH is noticeable in two aspects of the elimination of toxic formaldehyde and the production of methanol as an energy source. Herein, we screened improved mutants of Bacillus methanolicus MDH in Esehcichia coli that reduce formaldehyde to methanol effectively with directed evolution and Phichia-based biological methanol sensor system. To examine the resistance to formaldehyde, E. coli strains expressing each mutant were cultured in 3mM formaldehyde, toxic concentration for E. coli. In the best mutant, three phenylalanine residues were substituted to leucine, valine and serine respectively and all the three substitutions were required to increase reduction activity for formaldehyde. Purified mutant converted formaldehyde to methanol approximately 5 times more than wild type. Based on these results, mutant MDH carry out the elimination of formaldehyde efficiently, therefore it could help solve environmental problem such as sick house syndrome.

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Precise and predictable gene expression is fundamental for creating new synthetic circuits inside cells. Since gene expression is mainly controlled by the promoter sequences, being able to quickly design promoters with minimal experimental workload is desired. Existing promoter libraries provide a design starting point but the final promoter sequence will vary with experimental conditions, additional binding sites, and other design elements. Here, we present a simple algorithm for tuning the negative autoregulatory transcription network motif using differential in vivo RNA- based computations. The algorithm comprises two stages: sensitivity to perturbations is minimized first and the steady state level of the gene product is set second. Tuning is achieved by adjusting spacings between the consensus sequences in the -10/-35 and transcription factor binding site promoter regions. Differential RNA- based computations are proposed to minimize measurement sensitivity to external noise. Computations are realized by hybridization reactions between modified 3′- UTRs and 5′-UTRs of mRNA transcribed from different promoter designs. Convergence of the algorithm to the desired design irrespective of the binding kinetics is shown analytically. Accuracy of the method in measuring differences in gene expression from different promoter sequences is shown in silico. The feasibility of the approach and the underlying sequential tuning protocol are demonstrated in vivo. Gene expression is measured using both the described RT-qPCR measurements and fluorescence measurements for comparison. Several time- saving protocol innovations are introduced.

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We explore the possibilities of synthetic biology in Streptomyces bacteria, targetting their most important ability: producing a large variety of secondary metabolites, diverse in both chemical structure and bioactivity. The biosynthesis gene clusters are modular, thus an ideal system to apply synthetic biology and engineer new and diverse bioactive molecules (1,2). As a first step towards re-engineering antibiotic biosynthesis, we studied the regulatory circuitry controlling antibiotic production in Streptomyces coelicolor A3(2), using experimentation and computational modelling. In this species antibiotic production is regulated by -butyrolactones are known to be the signalling molecules (or bacterial hormones) that regulate. We could show that the two major players of the butyrolactone signalling system, -butyrolactone synthase and the -butyrolactone receptor, exert a concerted regulation (3) set up to create a bistable switch. We also show how antibiotic biosynthesis is additionally regulated at the translational level involving ncRNA. Now that we have a detailed understanding of the circuitry regulating antibiotic biosynthesis, we can start to re-engineer the bacterial genomes to awaken cryptic antibiotic clusters, 20–50 of which are typically found in each genome (4). For this purpose, we are exploiting computational constraint-based modelling of bacterial metabolism to automatically identify suitable overproduction hosts and pinpoint biosynthetic bottlenecks that will be target for further cellular engineering (5). We have also developed a high-throughput, in vivo reporter system to aid in creating a library of orthogonal promoters. 1. Medema MH, Breitling R, Bovenberg RAL, Takano E. Nature Rev Microbiol (2011) 9:131–137. 2. Medema MH, van Raaphorst R, Takano E, Breitling R. Nature Rev Microbiol (2012) 10:191-202. 3. Gottelt M, Gomez-Escribano JP, Bibb M, Takano E. Microbiology (2010) 156:2343–2353. 4. Medema MH, Trefzer A, …, Takano E. Genome Biology and Evolution (2010) 2:212–224. 5. Zakrzewski P, … Breitling R, Takano E. PLoS ONE. in press.

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Like Cro-Magnon architects limited by the rocks and sticks available around their camp, synthetic biologists are currently limited by the catalytic proteins (enzymes) and metabolic pathways available from natural organisms. Civilization only emerged once humanity developed new tools unavailable in our natural environment but well suited to our needs. Likewise, our ability to design cell factories to produce the fuels, chemicals and drugs our industrial world needs will certainly require the “recombination” not only of existing but also designer enzymes into novel pathways. Unfortunately, our ability to rationally engineer synthetic enzymes catalyzing the chemical reactions we care about is nowhere as advanced as our ability to construct synthetic genes! Here we will present the technology developed by our team that enabled for the first time the computational de novo design of synthetic enzymes with entirely new catalytic sites. Using a combination of dedicated high-performance computing and computational structural biology algorithms, around 100 new enzymes were computationally designed and experimentally proven to catalyze a novel retro-aldol reaction, a Kemp elimination reaction and a bimolecular, stereo-selective Diels-Alder reaction. We will also present subsequent case studies of successful applications of this technology to industrial biotechnology challenges. Much more than an incremental improvement over rational protein engineering (which typically involves an expert deciding on a small number of ‘tweaks’ – mutations – to alter an existing enzymatic activity), this new technique allows the automated reconfiguring of existing proteins to impart them with completely novel catalytic activities. We will discuss how this new technology can be integrated with existing synthetic biology tools (such as large-scale DNA synthesis and CAD software) to design novel pathways and cell-factories.

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Biological modules that can implement information processing and storage are a major long-term goal in Synthetic Biology. Large serine phage integrases are ideally suited for the production of bio-computing and memory modules. These integrase proteins carry out directional cut-and-splice reactions on DNA by recognizing sequences known as attP and attB, cutting them at their centres and rejoining them to form two new sites, attL and attR which do not recombine further. However, in the present of recombination directionality factor (RDF), this directionality is reversed so that attL and attR recombine to re-create attP and attB. If two att sites are placed in inverted repeat, recombination flips the orientation of the intervening sequence, and the two orientations can be thought of as representing a single binary digit (0 or 1 / OFF or ON) heritably stored in the DNA. The state of the DNA can be easily detected by physical means or can drive the expression of a reporter gene such as GFP. We are using phage integrases to build modules for a binary counter that function in living cells. A synthetic circuit has been constructed in E. coli and proper expression levels of Integrase and RDF have been established. By first expressing the integrase on its own, and then the integrase and the RDF together, the binary counter module switches repeatedly from 0 to 1, and then from 1 to 0 each time it receives an external signal. By chaining N units together, each using a different phage integrase, a ripple counter can be made that can count to 2^N. Binary genetic counters could be used to record the number of times the cell has been exposed to a specific environmental event, or to step through a programmed cycle of gene expression patterns.

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Synthetic biologists have engineered biological circuits to perturb increasingly complex systems such as eukaryotic cells. To better understand these processes, it is necessary to visualize the spatial distributions of many proteins with high resolution. Super-resolution microscopy techniques such as STORM have enabled structures smaller than 20nm to be resolved. However, these techniques are inherently limited by the number of targets that can be visualized in one sample. Currently, no immunofluorescent super-resolution approach has been able to image more than six protein targets because of signal loss associated with cross-talk between spectrally similar fluorophores. Here, we demonstrate a cost-effective technique to overcome this limitation in fixed cells by encoding many protein targets with temporal DNA-based barcodes. These barcodes use dynamic DNA complexes. We can selectively label and remove fluorescent signals by utilizing programmable sequence-specific strand displacement reactions. These reactions occur between target-bound DNA-conjugated primary antibodies and STORM dye pair-conjugated DNA complexes. Then, we re-iteratively localize each individual target molecule with a permuted fluorescent signal in sequential imaging rounds. By doing so, we are able to encode each target with a color-based temporal barcode. Importantly, the number of targets that can be imaged using this technique scales polynomially (the number of fluorescent channels to the power of the number of imaging rounds). Here, we show that DNA-based temporal barcodes can be used to image ten or more immunofluorescent targets at super-resolution.

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One of the main problems connected with the assembly of genetic circuits from simple genetic parts is the unpredictability of the behaviour of the whole system, given the input/output behaviour of the single modules that compose it. Within this frame, it is essential to trace the linearity working boundaries of engineered biological systems to rationally design gene networks. In this study, the nonlinear and saturation effects due to copy number variation were examined using in vivo and in silico methodologies. First, a BioBrick-compatible integrative vector for Escherichia coli was designed, constructed and validated. This tool supports both site specific and homologous recombination and has been successfully used to target two different loci of the E. coli chromosome. This tool allows the construction of gene networks present in a single copy in the bacterial genome. Commonly used plasmids present in the Registry were also used. They enable a 40-fold copy number variation (from 5 to about 200 copies per cell). Quantitative analysis of the activity of different constitutive promoters was measured in the genomic and plasmid contexts. Secondly, a simple inducible device in four different copy number contexts (from 1 to about 200 copies per cell) was quantitatively characterized. An empiric mathematical model was used to fully characterize the device in all the investigated conditions. Finally, a mechanistic model of the inducible device, based on the mass action law, has been proposed and used to study the effects of copy number variation of both promoter and transcription factor, individually and in concert. Taken together, these results show how fundamental the copy number tuning is in regulating gene networks. Biological and computational tools to study these phenomena have been developed and tested and an important step has been done in the process of defining the linear working boundaries of synthetic biological devices.

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We follow a pioneering synergistic research line at the cross-section between plant and mammalian synthetic biology aimed at developing a wide array of building blocks necessary for the design, construction and further assembly of the resulting modules into synthetic signalling networks and biosensors. This integrative approach allows for the study of plant metabolisms and signalling pathways in an orthogonal system preventing undesirable crosstalk with endogenous components. For instance, plant-light signalling pathways were partially reconstituted in mammalian cells shedding light into key functional aspects of the systems. Moreover, we also successfully applied this principle to the development of plant metabolite biosensors that were further used to study plant biomolecular circuits and pathways. In addition, we have used plant molecular tools for the construction of orthogonal modules with novel capabilities. Based on this platform we engineered optogenetic and chemical switches for the de novo design of signalling networks to control gene expression, metabolism and development in mammalian cell systems. In particular, we further seek to integrate green and red synthetic biology approaches with a focus on valorising results on fundamental research to the de novo design of genetic systems and robust metabolisms with novel functionalities and biotechnological applications.

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Although methods in the design-build-test life cycle of the synthetic biology field have grown rapidly, the expansion has been non-uniform. The design and build stages in development have seen innovations in the form of biological CAD and more efficient means for building DNA, RNA, and other biological constructs. The testing phase of the cycle remains in need of innovation. Presented will be both a theoretical abstraction of biological measurement and a practical demonstration of a microfluidics-based platform for characterizing synthetic biological phenomena. Such a platform demonstrates a design of additive manufacturing (3D printing) for construction of a microbial fuel cell (MFC) to be used in experiments carried out in space. First, the biocompatibility of the polypropylene chassis will be demonstrated. The novel MFCs will be cheaper, and faster to make and iterate through designs. The novel design will contain a manifold switching/distribution system and an integrated in-chip set of reagent reservoirs fabricated via 3D printing. The automated nature of the 3D printing yields itself to higher resolution switching valves and leads to smaller sized payloads, lower cost, reduced power and a standardized platform for synthetic biology unit tests on Earth and in space. It will be demonstrated that the application of unit testing in synthetic biology will lead to the automatic construction and validation of desired constructs. Unit testing methodologies offer benefits of preemptive problem identification, change of facility, simplicity of integration, ease of documentation, and separation of interface from implementation, and automated design.

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Bacterial spores have gained attention as attractive candidates for use in biotechnology in recent years, with notable progression in research that utilizes spores as vehicles for whole cell biosensors, surface display systems and vehicles for vaccines and therapeutic agents. Spores of Bacillus subtilis that exit from dormancy generate quick, unique responses characteristic of germination that can be easily detected. However, the exploitation of spore germination in biosensing has remained limited to the use of spores as vehicles for cellular functions or dependent on existing germination pathways and inputs. Here, we describe a novel ligand responsive spore detection system through engineering of new ‘germination’ receptors. This technology is able to rapidly detect peptide agonists, small molecules and protein interactions, and is amenable to high-throughput setups. Exploiting spores for biosensing in this way may serve as a useful platform for engineering new ligand specificities and detecting small molecule modulators of protein:protein interactions, with direct application in drug discovery and aiding of metabolic engineering design.

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Complex cellular behaviors are orchestrated by networks of signal transduction pathways that process sensory information to execute specific physiological functions. Tyrosine kinase (TyrK) signaling is an example of a recently evolved signaling system that has become an essential part of modern metazoan cell biology. Phosphotyrosine (pTyr) signaling circuits mediate cell-to-cell communication responsible for controlling cell migration, differentiation, hormone response and immune defense. Its underlying architecture is a combination of three components: the writer (Tyrosine kinase, TyrK), the reader (SH2 domain, specifically binds phosphotyrosine peptides) and the eraser (protein tyrosine phosphatase, PTP). This modular, versatile design has enabled cells to develop vast set of complex signaling networks and provides us with a rich toolkit with which to engineer novel signaling circuits to artificially control cellular behavior.

In order to study the design principles of pTyr signaling circuits in a naive cellular environment, we are introducing pTyr signaling to the budding yeast Saccharomyces cerevisiae, which lacks endogenous TyrK or SH2 domain containing proteins. We are developing artificial phosphorylation cascades using designed TyrK and SH2 substrates towards building novel signal transduction circuits with interesting properties. Through a combination of proteomics, cell biology and in vitro biochemistry we have uncovered the mechanistic basis for growth defects resulting from Src TyrK expression in yeast. Our results highlight the engineering challenges of developing an orthogonal signaling system in a naive host as well as provide insights into the emergence of a novel signaling currency in eukaryotic evolution.

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My PhD project aims to investigate the use of cell-free systems as an alternative chassis for synthetic biology. Two applications have been explored, firstly for the characterisation of DNA regulatory elements and secondly for the development of in vitro biosensors. Both aspects of my project are explained below. Current approaches to characterise DNA regulatory elements are mostly tied to living systems and are inherently time-consuming and low-throughput. I have developed a completely in vitro assay to assemble and characterise libraries of regulatory DNA regulatory regions that is significantly quicker than current in vivo approaches. First a PCR coupled to a USER-ligase reaction is used to generate libraries of DNA regulatory regions within 2-3 hours, omitting the need for transformation into e.coli. These DNA templates are then expressed in a cell-free system for 2-3 hours and characterisation performed. I have demonstrated a correlation for the data collect in cell-free systems to that of living systems for the most frequently used DNA regulatory regions.  The second part of the project is to developed an in vitro biosensor to detect the presence of pathogenic bacterial biofilms. It is based upon a DNA template being expressed within the context of a cell-free systems. This DNA biosensor once expressed is able to detect biomarkers that have been shown to be both essential and present in pathogenic biofilms, and give a detectable output. Currently, a proof of principle has been shown for detection of the formation and presence of Pseudomonas aeruginosa biofilms.

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