Toward Full-Stack In Silico Synthetic Biology: Integrating Model Specification, Simulation, Verification, and Biological Compilation

This article references 80 other publications.

1. 1

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   Next generation gene synthesis: From microarrays to genomes

   Kuhn, Phillip; Wagner, Katrin; Heil, Korbinian; Liss, Michael; Netuschil, Nikolai

   Engineering in Life Sciences (2017), 17 (1), 6-13CODEN: ELSNAE; ISSN:1618-2863. (Wiley-Blackwell)

   Similar to the incredible advances in DNA sequencing, the de novo synthesis of DNA is subject to innovations and fast progress in terms of synthesis speed and cost. We will discuss novel techniques that are expected to enable high-throughput synthesis of oligonucleotides on microarrays and the subsequent assembly into longer fragments, up to whole genomes. Esp., the inherent disadvantages of microarray-derived oligonucleotide pools for gene synthesis will be discussed in detail, and also the different approaches to still render these oligonucleotides useful for gene assembly. These so-called next-generation techniques will lead to a significant cost redn. of gene synthesis and to the possibility of much larger projects, such as whole genome synthesis. This article is protected by copyright. All rights reserved.

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   Hsu, P. D., Lander, E. S., and Zhang, F. (2014) Development and applications of CRISPR-Cas9 for genome engineering. Cell 157, 1262– 1278,  DOI: 10.1016/j.cell.2014.05.010

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   Development and applications of CRISPR-Cas9 for genome engineering

   Hsu, Patrick D.; Lander, Eric S.; Zhang, Feng

   Cell (Cambridge, MA, United States) (2014), 157 (6), 1262-1278CODEN: CELLB5; ISSN:0092-8674. (Cell Press)

   A review. Recent advances in genome engineering technologies based on the CRISPR-assocd. RNA-guided endonuclease Cas9 are enabling the systematic interrogation of mammalian genome function. Analogous to the search function in modern word processors, Cas9 can be guided to specific locations within complex genomes by a short RNA search string. Using this system, DNA sequences within the endogenous genome and their functional outputs are now easily edited or modulated in virtually any organism of choice. Cas9-mediated genetic perturbation is simple and scalable, empowering researchers to elucidate the functional organization of the genome at the systems level and establish causal linkages between genetic variations and biol. phenotypes. In this Review, we describe the development and applications of Cas9 for a variety of research or translational applications while highlighting challenges as well as future directions. Derived from a remarkable microbial defense system, Cas9 is driving innovative applications from basic biol. to biotechnol. and medicine.

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   Price, M., Cruz, R., Baxter, S., Escalettes, F., and Rosser, S. (2019) CRISPR-Cas9 In Situ engineering of subtilisin E in Bacillus subtilis. PLoS One 14, e0210121,  DOI: 10.1371/journal.pone.0210121

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   CRISPR-Cas9 In Situ engineering of subtilisin E in Bacillus subtilis

   Price, Marcus A.; Cruz, Rita; Baxter, Scott; Escalettes, Franck; Rosser, Susan J.

   PLoS One (2019), 14 (1), e0210121CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)

   CRISPR-Cas systems have become widely used across all fields of biol. as a genome engineering tool. With its recent demonstration in the Gram pos. industrial workhorse Bacillus subtilis, this tool has become an attractive option for rapid, markerless strain engineering of industrial prodn. hosts. Previously described strategies for CRISPR-Cas9 genome editing in B. subtilis have involved chromosomal integrations of Cas9 and single guide RNA expression cassettes, or construction of large plasmids for simultaneous transformation of both single guide RNA and donor DNA. Here we use a flexible, co-transformation approach where the single guide RNA is inserted in a plasmid for Cas9 co-expression, and the donor DNA is supplied as a linear PCR product observing an editing efficiency of 76%. This allowed multiple, rapid rounds of in situ editing of the subtilisin E gene to incorporate a salt bridge triad present in the Bacillus clausii thermotolerant homolog, M-protease. A novel subtilisin E variant was obtained with increased thermotolerance and activity.

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   Keating, K. W. and Young, E. M. (2019) Synthetic biology for bio-derived structural materials. Curr. Opin. Chem. Eng. 24, 107– 114,  DOI: 10.1016/j.coche.2019.03.002

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   Materials engineering: bioderived/bioinspired materials. Separations Engineering: advances in adsorption.

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   Nguyen, P. Q. (2017) Synthetic biology engineering of biofilms as nanomaterials factories. Biochem. Soc. Trans. 45, 585– 597,  DOI: 10.1042/BST20160348

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   Synthetic biology engineering of biofilms as nanomaterials factories

   Nguyen, Peter Q.

   Biochemical Society Transactions (2017), 45 (3), 585-597CODEN: BCSTB5; ISSN:0300-5127. (Portland Press Ltd.)

   Bottom-up fabrication of nanoscale materials has been a significant focus in materials science for expanding our technol. frontiers. This assembly concept, however, is old news to biol. - all living organisms fabricate themselves using bottom-up principles through a vast self-organizing system of incredibly complex biomols., a marvelous dynamic that we are still attempting to unravel. Can we use what we have gleaned from biol. thus far to illuminate alternative strategies for designer nanomaterial manufg. In the present review article, new synthetic biol. efforts toward using bacterial biofilms as platforms for the synthesis and secretion of programmable nanomaterials are described. Particular focus is given to self-assembling functional amyloids found in bacterial biofilms as re-engineerable modular nanomol. components. Potential applications and existing challenges for this technol. are also explored. This novel approach for repurposing biofilm systems will enable future technologies for using engineered living systems to grow artificial nanomaterials.

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   Gilbert, C. and Ellis, T. (2019) Biological Engineered Living Materials: Growing Functional Materials with Genetically Programmable Properties. ACS Synth. Biol. 8, 1– 15,  DOI: 10.1021/acssynbio.8b00423

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   Biological Engineered Living Materials: Growing Functional Materials with Genetically Programmable Properties

   Gilbert, Charlie; Ellis, Tom

   ACS Synthetic Biology (2019), 8 (1), 1-15CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

   A review. Natural biol. materials exhibit remarkable properties: self-assembly from simple raw materials, precise control of morphol., diverse phys. and chem. properties, self-repair, and the ability to sense-and-respond to environmental stimuli. Despite having found numerous uses in human industry and society, the utility of natural biol. materials is limited. But, could it be possible to genetically program microbes to create entirely new and useful biol. materials. At the intersection between microbiol., material science, and synthetic biol., the emerging field of biol. engineered living materials (ELMs) aims to answer this question. Here we review recent efforts to program cells to produce living materials with novel functional properties, focusing on microbial systems that can be engineered to grow materials and on new genetic circuits for pattern formation that could be used to produce the more complex systems of the future.

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7. 7

   Lorenzo, V., Prather, K. L., Chen, G.-Q., O'Day, E., Kameke, C., Oyarzun, D. A, Hosta-Rigau, L., Alsafar, H., Cao, C., Ji, W., Okano, H., Roberts, R. J, Ronaghi, M., Yeung, K., Zhang, F., and Lee, S. Y. (2018) The power of synthetic biology for bioproduction, remediation and pollution control. EMBO Rep. 19, e45658,  DOI: 10.15252/embr.201745658

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   Gleizer, S., Ben-Nissan, R., Bar-On, Y. M., Antonovsky, N., Noor, E., Zohar, Y., Jona, G., Krieger, E., Shamshoum, M., Bar-Even, A., and Milo, R. (2019) Conversion of Escherichia coli to Generate All Biomass Carbon from CO₂. Cell 179, 1255– 1263,  DOI: 10.1016/j.cell.2019.11.009

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   Conversion of Escherichia coli to generate all biomass carbon from CO2

   Gleizer, Shmuel; Ben-Nissan, Roee; Bar-On, Yinon M.; Antonovsky, Niv; Noor, Elad; Zohar, Yehudit; Jona, Ghil; Krieger, Eyal; Shamshoum, Melina; Bar-Even, Arren; Milo, Ron

   Cell (Cambridge, MA, United States) (2019), 179 (6), 1255-1263.e12CODEN: CELLB5; ISSN:0092-8674. (Cell Press)

   The living world is largely divided into autotrophs that convert CO2 into biomass and heterotrophs that consume org. compds. In spite of widespread interest in renewable energy storage and more sustainable food prodn., the engineering of industrially relevant heterotrophic model organisms to use CO2 as their sole carbon source has so far remained an outstanding challenge. Here, we report the achievement of this transformation on lab. timescales. We constructed and evolved Escherichia coli to produce all its biomass carbon from CO2. Reducing power and energy, but not carbon, are supplied via the one-carbon mol. formate, which can be produced electrochem. Rubisco and phosphoribulokinase were co-expressed with formate dehydrogenase to enable CO2 fixation and redn. via the Calvin-Benson-Bassham cycle. Autotrophic growth was achieved following several months of continuous lab. evolution in a chemostat under intensifying org. carbon limitation and confirmed via isotopic labeling.

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9. 9

   Kylilis, N., Riangrungroj, P., Lai, H.-E., Salema, V., Fernández, L. A., Stan, G.-B. V., Freemont, P. S., and Polizzi, K. M. (2019) Whole-Cell Biosensor with Tunable Limit of Detection Enables Low-Cost Agglutination Assays for Medical Diagnostic Applications. ACS Sensors 4, 370– 378,  DOI: 10.1021/acssensors.8b01163

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   Whole-Cell Biosensor with Tunable Limit of Detection Enables Low-Cost Agglutination Assays for Medical Diagnostic Applications

   Kylilis, Nicolas; Riangrungroj, Pinpunya; Lai, Hung-En; Salema, Valencio; Fernandez, Luis Angel; Stan, Guy-Bart V.; Freemont, Paul S.; Polizzi, Karen M.

   ACS Sensors (2019), 4 (2), 370-378CODEN: ASCEFJ; ISSN:2379-3694. (American Chemical Society)

   Whole-cell biosensors can form the basis of affordable, easy-to-use diagnostic tests that can be readily deployed for point-of-care (POC) testing, but to date the detection of analytes such as proteins that cannot easily diffuse across the cell membrane has been challenging. Here we developed a novel biosensing platform based on cell agglutination using an E. coli whole-cell biosensor surface-displaying nanobodies which bind selectively to a target protein analyte. As a proof-of-concept, we show the feasibility of this design to detect a model analyte at nanomolar concns. Moreover, we show that the design architecture is flexible by building assays optimized to detect a range of model analyte concns. using straightforward design rules and a math. model. Finally, we re-engineer our whole-cell biosensor for the detection of a medically relevant biomarker by the display of two different nanobodies against human fibrinogen and demonstrate a detection limit as low as 10 pM in dild. human plasma. Overall, we demonstrate that our agglutination technol. fulfills the requirement of POC testing by combining low-cost nanobody prodn., customizable detection range and low detection limits. This technol. has the potential to produce affordable diagnostics for field-testing in the developing world, emergency or disaster relief sites, as well as routine medical testing and personalized medicine.

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10. 10

    Sheth, R. U. and Wang, H. H. (2018) DNA-based memory devices for recording cellular events. Nat. Rev. Genet. 19, 718– 732,  DOI: 10.1038/s41576-018-0052-8

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    DNA-based memory devices for recording cellular events

    Sheth, Ravi U.; Wang, Harris H.

    Nature Reviews Genetics (2018), 19 (11), 718-732CODEN: NRGAAM; ISSN:1471-0056. (Nature Research)

    A review. Measuring biol. data across time and space is crit. for understanding complex biol. processes and for various biosurveillance applications. However, such data are often inaccessible or difficult to directly obtain. Less invasive, more robust and higher-throughput biol. recording tools are needed to profile cells and their environments. DNA-based cellular recording is an emerging and powerful framework for tracking intracellular and extracellular biol. events over time across living cells and populations. Here, we review and assess DNA recorders that utilize CRISPR nucleases, integrases and base-editing strategies, as well as recombinase and polymerase-based methods. Quant. characterization, modeling and evaluation of these DNA-recording modalities can guide their design and implementation for specific application areas.

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    Karr, J., Sanghvi, J., Macklin, D., Gutschow, M., Jacobs, J., Bolival, B., Assad-Garcia, N., Glass, J., and Covert, M. (2012) A Whole-Cell Computational Model Predicts Phenotype from Genotype. Cell 150, 389– 401,  DOI: 10.1016/j.cell.2012.05.044

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    A Whole-Cell Computational Model Predicts Phenotype from Genotype

    Karr, Jonathan R.; Sanghvi, Jayodita C.; Macklin, Derek N.; Gutschow, Miriam V.; Jacobs, Jared M.; Bolival, Benjamin; Assad-Garcia, Nacyra; Glass, John I.; Covert, Markus W.

    Cell (Cambridge, MA, United States) (2012), 150 (2), 389-401CODEN: CELLB5; ISSN:0092-8674. (Cell Press)

    Understanding how complex phenotypes arise from individual mols. and their interactions is a primary challenge in biol. that computational approaches are poised to tackle. We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its mol. components and their interactions. An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and exptl. measurements. Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data. The model provides insights into many previously unobserved cellular behaviors, including in vivo rates of protein-DNA assocn. and an inverse relationship between the durations of DNA replication initiation and replication. In addn., exptl. anal. directed by model predictions identified previously undetected kinetic parameters and biol. functions. We conclude that comprehensive whole-cell models can be used to facilitate biol. discovery.

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    Naylor, J., Fellermann, H., Ding, Y., Mohammed, W. K., Jakubovics, N. S., Mukherjee, J., Biggs, C. A., Wright, P. C., and Krasnogor, N. (2017) Simbiotics: A Multiscale Integrative Platform for 3D Modeling of Bacterial Populations. ACS Synth. Biol. 6, 1194– 1210,  DOI: 10.1021/acssynbio.6b00315

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    Simbiotics: A Multiscale Integrative Platform for 3D Modeling of Bacterial Populations

    Naylor, Jonathan; Fellermann, Harold; Ding, Yuchun; Mohammed, Waleed K.; Jakubovics, Nicholas S.; Mukherjee, Joy; Biggs, Catherine A.; Wright, Phillip C.; Krasnogor, Natalio

    ACS Synthetic Biology (2017), 6 (7), 1194-1210CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    Simbiotics is a spatially explicit multiscale modeling platform for the design, simulation and anal. of bacterial populations. Systems ranging from planktonic cells and colonies, to biofilm formation and development may be modeled. Representation of biol. systems in Simbiotics is flexible, and user-defined processes may be in a variety of forms depending on desired model abstraction. Simbiotics provides a library of modules such as cell geometries, phys. force dynamics, genetic circuits, metabolic pathways, chem. diffusion and cell interactions. Model defined processes are integrated and scheduled for parallel multithread and multi-CPU execution. A virtual lab provides the modeler with anal. modules and some simulated lab equipment, enabling automation of sample interaction and data collection. An extendable and modular framework allows for the platform to be updated as novel models of bacteria are developed, coupled with an intuitive user interface to allow for model definitions with minimal programming experience. Simbiotics can integrate existing stds. such as SBML, and process microscopy images to initialize the 3D spatial configuration of bacteria consortia. Two case studies, used to illustrate the platform flexibility, focus on the phys. properties of the biosystems modeled. These pilot case studies demonstrate Simbiotics versatility in modeling and anal. of natural systems and as a CAD tool for synthetic biol.

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    Sanassy, D., Widera, P., and Krasnogor, N. (2015) Meta-Stochastic Simulation of Biochemical Models for Systems and Synthetic Biology. ACS Synth. Biol. 4, 39– 47,  DOI: 10.1021/sb5001406

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    13

    Meta-Stochastic Simulation of Biochemical Models for Systems and Synthetic Biology

    Sanassy, Daven; Widera, Pawel; Krasnogor, Natalio

    ACS Synthetic Biology (2015), 4 (1), 39-47CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    Stochastic simulation algorithms (SSAs) are used to trace realistic trajectories of biochem. systems at low species concns. As the complexity of modeled biosystems increases, it is important to select the best performing SSA. Numerous improvements to SSAs have been introduced but they each only tend to apply to a certain class of models. This makes it difficult for a systems or synthetic biologist to decide which algorithm to employ when confronted with a new model that requires simulation. In this paper, we demonstrate that it is possible to det. which algorithm is best suited to simulate a particular model and that this can be predicted a priori to algorithm execution. We present a Web based tool ssapredict that allows scientists to upload a biochem. model and obtain a prediction of the best performing SSA. Furthermore, ssapredict gives the user the option to download our high performance simulator ngss preconfigured to perform the simulation of the queried biochem. model with the predicted fastest algorithm as the simulation engine. The ssapredict Web application is available at http://ssapredict.ico2s.org. It is free software and its source code is distributed under the terms of the GNU Affero General Public License.

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14. 14

    Gorochowski, T. E., Hauert, S., Kreft, J.-U., Marucci, L., Stillman, N. R., Tang, T.-Y. D., Bandiera, L., Bartoli, V., Dixon, D. O. R., Fedorec, A. J. H., Fellermann, H., Fletcher, A. G., Foster, T., Giuggioli, L., Matyjaszkiewicz, A., McCormick, S., Montes Olivas, S., Naylor, J., Rubio Denniss, A., and Ward, D. (2020) Toward Engineering Biosystems With Emergent Collective Functions. Front. Bioeng. Biotechnol. 8, 705,  DOI: 10.3389/fbioe.2020.00705

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    14

    Toward Engineering Biosystems With Emergent Collective Functions

    Gorochowski Thomas E; Ward Daniel; Hauert Sabine; Marucci Lucia; Stillman Namid R; Bartoli Vittorio; Giuggioli Luca; McCormick Scott; Montes Olivas Sandra; Rubio Denniss Ana; Kreft Jan-Ulrich; Foster Tim; Tang T-Y Dora; Tang T-Y Dora; Bandiera Lucia; Dixon Daniel O R; Fedorec Alex J H; Fellermann Harold; Naylor Jonathan; Fletcher Alexander G; Matyjaszkiewicz Antoni

    Frontiers in bioengineering and biotechnology (2020), 8 (), 705 ISSN:2296-4185.

    Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales.

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    Jiang, S., Wang, Y., Kaiser, M., and Krasnogor, N. (2020) NIHBA: a network interdiction approach for metabolic engineering design. Bioinformatics 36, 3482– 3492,  DOI: 10.1093/bioinformatics/btaa163

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    15

    NIHBA: a network interdiction approach for metabolic engineering design

    Jiang, Shouyong; Wang, Yong; Kaiser, Marcus; Krasnogor, Natalio

    Bioinformatics (2020), 36 (11), 3482-3492CODEN: BOINFP; ISSN:1367-4811. (Oxford University Press)

    Motivation: Flux balance anal. (FBA) based bilevel optimization has been a great success in redesigning metabolic networks for biochem. overprodn. To date, many computational approaches have been developed to solve the resulting bilevel optimization problems. However, most of them are of limited use due to biased optimality principle, poor scalability with the size of metabolic networks, potential numeric issues or low quantity of design solns. in a single run. Results: Here, we have employed a network interdiction model free of growth optimality assumptions, a special case of bilevel optimization, for computational strain design and have developed a hybrid Benders algorithm (HBA) that deals with complicating binary variables in the model, thereby achieving high efficiency without numeric issues in search of best design strategies. More importantly, HBA can list solns. that meet users' prodn. requirements during the search, making it possible to obtain numerous design strategies at a small runtime overhead (typically ~ 1 h, e.g. studied in this article).

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    Misirli, G., Nguyen, T., McLaughlin, J. A., Vaidyanathan, P., Jones, T. S., Densmore, D., Myers, C., and Wipat, A. (2019) A Computational Workflow for the Automated Generation of Models of Genetic Designs. ACS Synth. Biol. 8, 1548– 1559,  DOI: 10.1021/acssynbio.7b00459

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    16

    A Computational Workflow for the Automated Generation of Models of Genetic Designs

    Misirli, Goksel; Nguyen, Tramy; McLaughlin, James Alastair; Vaidyanathan, Prashant; Jones, Timothy S.; Densmore, Douglas; Myers, Chris; Wipat, Anil

    ACS Synthetic Biology (2019), 8 (7), 1548-1559CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    Computational models are essential to engineer predictable biol. systems and to scale up this process for complex systems. Computational modeling often requires expert knowledge and data to build models. Clearly, manual creation of models is not scalable for large designs. Despite several automated model construction approaches, computational methodologies to bridge knowledge in design repositories and the process of creating computational models have still not been established. This paper describes a workflow for automatic generation of computational models of genetic circuits from data stored in design repositories using existing stds. This workflow leverages the software tool SBOLDesigner to build structural models that are then enriched by the Virtual Parts Repository API using Systems Biol. Open Language (SBOL) data fetched from the SynBioHub design repository. The iBioSim software tool is then utilized to convert this SBOL description into a computational model encoded using the Systems Biol. Markup Language (SBML). Finally, this SBML model can be simulated using a variety of methods. This workflow provides synthetic biologists with easy to use tools to create predictable biol. systems, hiding away the complexity of building computational models. This approach can further be incorporated into other computational workflows for design automation.

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17. 17

    Tellechea-Luzardo, J., Winterhalter, C., Widera, P., Kozyra, J., de Lorenzo, V., and Krasnogor, N. (2020) Linking Engineered Cells to Their Digital Twins: A Version Control System for Strain Engineering. ACS Synth. Biol. 9, 536– 545,  DOI: 10.1021/acssynbio.9b00400

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    17

    Linking Engineered Cells to Their Digital Twins: A Version Control System for Strain Engineering

    Tellechea-Luzardo, Jonathan; Winterhalter, Charles; Widera, Pawel; Kozyra, Jerzy; de Lorenzo, Victor; Krasnogor, Natalio

    ACS Synthetic Biology (2020), 9 (3), 536-545CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    As DNA sequencing and synthesis become cheaper and more easily accessible, the scale and complexity of biol. engineering projects is set to grow. Yet, although there is an accelerating convergence between biotechnol. and digital technol., a deficit in software and lab. techniques diminishes the ability to make biotechnol. more agile, reproducible and transparent while, at the same time, limiting the security and safety of synthetic biol. constructs. To partially address some of these problems, this paper presents an approach for phys. linking engineered cells to their digital footprint-we called it digital twinning. This enables the tracking of the entire engineering history of a cell line in a specialized version control system for collaborative strain engineering via simple barcoding protocols.

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    Watanabe, L., Nguyen, T., Zhang, M., Zundel, Z., Zhang, Z., Madsen, C., Roehner, N., and Myers, C. (2019) iBioSim 3: A Tool for Model-Based Genetic Circuit Design. ACS Synth. Biol. 8, 1560,  DOI: 10.1021/acssynbio.8b00078

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    18

    iBioSim 3: A Tool for Model-Based Genetic Circuit Design

    Watanabe, Leandro; Nguyen, Tramy; Zhang, Michael; Zundel, Zach; Zhang, Zhen; Madsen, Curtis; Roehner, Nicholas; Myers, Chris

    ACS Synthetic Biology (2019), 8 (7), 1560-1563CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    The iBioSim tool has been developed to facilitate the design of genetic circuits via a model-based design strategy. This paper illustrates the new features incorporated into the tool for DNA circuit design, design anal., and design synthesis, all of which can be used in a workflow for the systematic construction of new genetic circuits.

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19. 19

    Nielsen, A. A. K., Der, B. S., Shin, J., Vaidyanathan, P., Paralanov, V., Strychalski, E. A., Ross, D., Densmore, D., and Voigt, C. A. (2016) Genetic circuit design automation. Science 352, aac7341,  DOI: 10.1126/science.aac7341

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20. 20

    Gutiérrez, M., Gregorio-Godoy, P., Pérez del Pulgar, G., Muñoz, L. E., Sáez, S., and Rodríguez-Patón, A. (2017) A New Improved and Extended Version of the Multicell Bacterial Simulator GRO. ACS Synth. Biol. 6, 1496– 1508,  DOI: 10.1021/acssynbio.7b00003

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    20

    A New Improved and Extended Version of the Multicell Bacterial Simulator gro

    Gutierrez, Martin; Gregorio-Godoy, Paula; Perez del Pulgar, Guillermo; Munoz, Luis E.; Saez, Sandra; Rodriguez-Paton, Alfonso

    ACS Synthetic Biology (2017), 6 (8), 1496-1508CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    Gro is a cell programming language developed in Klavins Lab for simulating colony growth and cell-cell communication. It is used as a synthetic biol. prototyping tool for simulating multicellular biocircuits and microbial consortia. The authors present several extensions made to gro that improve the performance of the simulator, make it easier to use, and provide new functionalities. The new version of gro is 1-2 orders of magnitude faster than the original version. It is able to grow microbial colonies with up to 105 cells in <10 min. A new library, CellEngine, accelerates the resoln. of spatial phys. interactions between growing and dividing cells by implementing a new shoving algorithm. A genetic library, CellPro, based on Probabilistic Timed Automata, simulates gene expression dynamics using simplified and easy to compute digital proteins. The authors also propose a more convenient language specification layer, ProSpec, based on the idea that proteins drive cell behavior. CellNutrient, another library, implements Monod-based growth and nutrient uptake functionalities. The intercellular signaling management was improved and extended in a library called CellSignals. Finally, bacterial conjugation, another local cell-cell communication process, was added to the simulator. To show the versatility and potential outreach of this version of gro, the authors provide studies and novel examples ranging from synthetic biol. to evolutionary microbiol. The authors believe that the upgrades implemented for gro have made it into a powerful and fast prototyping tool capable of simulating a large variety of systems and synthetic biol. designs.

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21. 21

    Chandran, D. and Sauro, H. M. (2012) Hierarchical modeling for synthetic biology. ACS Synth. Biol. 1, 353– 364,  DOI: 10.1021/sb300033q

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    21

    Hierarchical Modeling for Synthetic Biology

    Chandran, Deepak; Sauro, Herbert M.

    ACS Synthetic Biology (2012), 1 (8), 353-364CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    One of the characteristics of synthetic biol. is that it often combines math. modeling with exptl. work. The link between modeling and expts. is carried out by human researchers who have a conceptual understanding of the underlying biol. system. At present, there is no method for representing a conceptual description that can be used to connect math. models and exptl. data, esp. sequence annotations, pertaining to the same underlying biol. system. One reason for this limitation is that there can exist different math. models of the same biol. system. In such cases, the same annotation in a DNA sequence would map differently to different models of the same system. In order to enable software support for synthetic biol., a software framework is needed such that it is able to capture a conceptual description of a biol. system, including quant. values, without confining itself to one math. model. The novel use of hierarchical modeling inside TinkerCell provides one potential software soln. for representing a "conceptual diagram" of a biol. system. The conceptual diagram does not assume any underlying model. Rather, the diagram is mapped automatically to one of several models. The diagram can then contain information relevant for both modeling and exptl. work. Computer-aided design (CAD) can be very useful to synthetic biol. CAD allows engineers to spend more effort at the design stage and less at the construction stage by automatically performing many tasks that are currently performed by human researchers. The ability to automatically link models and exptl. results will be one step in the development of practical CAD systems for synthetic biol.

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22. 22

    Bilitchenko, L., Liu, A., Cheung, S., Weeding, E., Xia, B., Leguia, M., Anderson, J. C., and Densmore, D. (2011) EUGENE - A domain specific language for specifying and constraining synthetic biological parts, devices, and systems. PLoS One 6, e18882,  DOI: 10.1371/journal.pone.0018882

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    22

    Eugene - a domain specific language for specifying and constraining synthetic biological parts, devices, and systems

    Bilitchenko, Lesia; Liu, Adam; Cheung, Sherine; Weeding, Emma; Xia, Bing; Leguia, Mariana; Anderson, J. Christopher; Densmore, Douglas

    PLoS One (2011), 6 (4), e18882CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)

    Background: Synthetic biol. systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their compn. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biol. designs based on biol. parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts. Results: We illustrate Eugene's capabilities in three different areas: Device specification, design space exploration, and assembly and simulation integration. These results highlight Eugene's ability to create combinatorial design spaces and prune these spaces for simulation or phys. assembly. Eugene creates functional designs quickly and cost-effectively. Conclusions: Eugene is intended for forward engineering of DNA-based devices, and through its data types and execution semantics, reflects the desired ion hierarchy in synthetic biol. Eugene provides a powerful constraint system which can be used to drive the creation of new devices at runtime. It accomplishes all of this while being part of a larger tool chain which includes support for design, simulation, and phys. device assembly.

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23. 23

    Beal, J., Lu, T., and Weiss, R. (2011) Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks. PLoS One 6, e22490,  DOI: 10.1371/journal.pone.0022490

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    23

    Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks

    Beal, Jacob; Lu, Ting; Weiss, Ron

    PLoS One (2011), 6 (8), e22490CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)

    Background: The field of synthetic biol. promises to revolutionize our ability to engineer biol. systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biol. itself and the lag in our ability to design and optimize sophisticated biol. circuitry. Methodol./Principal Findings: To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biol.-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biol. system design with our platform, and show that our compiler optimizations can yield significant redns. in the no. of genes (∼50) and latency of the optimized engineered gene networks. Conclusions/Significance: Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biol. systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biol. relevant compiler optimizations, providing an important foundation for the development of sophisticated biol. systems.

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24. 24

    Villalobos, A., Ness, J. E., Gustafsson, C., Minshull, J., and Govindarajan, S. (2006) Gene Designer: a synthetic biology tool for constructing artificial DNA segments. BMC Bioinf. 7, 285,  DOI: 10.1186/1471-2105-7-285

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    24

    Gene Designer: a synthetic biology tool for constructing artificial DNA segments

    Villalobos Alan; Ness Jon E; Gustafsson Claes; Minshull Jeremy; Govindarajan Sridhar

    BMC bioinformatics (2006), 7 (), 285 ISSN:.

    BACKGROUND: Direct synthesis of genes is rapidly becoming the most efficient way to make functional genetic constructs and enables applications such as codon optimization, RNAi resistant genes and protein engineering. Here we introduce a software tool that drastically facilitates the design of synthetic genes. RESULTS: Gene Designer is a stand-alone software for fast and easy design of synthetic DNA segments. Users can easily add, edit and combine genetic elements such as promoters, open reading frames and tags through an intuitive drag-and-drop graphic interface and a hierarchical DNA/Protein object map. Using advanced optimization algorithms, open reading frames within the DNA construct can readily be codon optimized for protein expression in any host organism. Gene Designer also includes features such as a real-time sliding calculator of oligonucleotide annealing temperatures, sequencing primer generator, tools for avoidance or inclusion of restriction sites, and options to maximize or minimize sequence identity to a reference. CONCLUSION: Gene Designer is an expandable Synthetic Biology workbench suitable for molecular biologists interested in the de novo creation of genetic constructs.

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25. 25

    Gaspar, P., Oliveira, J. L., Frommlet, J., Santos, M., and Moura, G. (2012) EuGene: maximizing synthetic gene design for heterologous expression. Bioinformatics 28, 2683,  DOI: 10.1093/bioinformatics/bts465

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    25

    EuGene: maximizing synthetic gene design for heterologous expression

    Gaspar, Paulo; Oliveira, Jose Luis; Frommlet, Joerg; Santos, Manuel A. S.; Moura, Gabriela

    Bioinformatics (2012), 28 (20), 2683-2684CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)

    Numerous software applications exist to deal with synthetic gene design, granting the field of heterologous expression a significant support. However, their dispersion requires the access to different tools and online services in order to complete one single project. Analyzing codon usage, calcg. codon adaptation index (CAI), aligning orthologs and optimizing genes are just a few examples. A software application, EuGene, was developed for the optimization of multiple gene synthetic design algorithms. In a seamless automatic form, EuGene calcs. or retrieves genome data on codon usage (relative synonymous codon usage and CAI), codon context (CPS and codon pair bias), GC content, hidden stop codons, repetitions, deleterious sites, protein primary, secondary and tertiary structures, gene orthologs, species housekeeping genes, performs alignments and identifies genes and genomes. The main function of EuGene is analyzing and redesigning gene sequences using multi-objective optimization techniques that maximize the coding features of the resulting sequence.

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26. 26

    Czar, M. J., Cai, Y., and Peccoud, J. (2009) Writing DNA with GenoCAD. Nucleic Acids Res. 37, W40– W47,  DOI: 10.1093/nar/gkp361

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    26

    Writing DNA with GenoCAD

    Czar, Michael J.; Cai, Yizhi; Peccoud, Jean

    Nucleic Acids Research (2009), 37 (Web Server), W40-W47CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)

    Chem. synthesis of custom DNA made to order calls for software streamlining the design of synthetic DNA sequences. GenoCAD (www.genocad.org) is a free web-based application to design protein expression vectors, artificial gene networks and other genetic constructs composed of multiple functional blocks called genetic parts. By capturing design strategies in grammatical models of DNA sequences, GenoCAD guides the user through the design process. By successively clicking on icons representing structural features or actual genetic parts, complex constructs composed of dozens of functional blocks can be designed in a matter of minutes. GenoCAD automatically derives the construct sequence from its comprehensive libraries of genetic parts. Upon completion of the design process, users can download the sequence for synthesis or further anal. Users who elect to create a personal account on the system can customize their workspace by creating their own parts libraries, adding new parts to the libraries, or reusing designs to quickly generate sets of related constructs.

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27. 27

    Pedersen, M. and Phillips, A. (2009) Towards programming languages for genetic engineering of living cells. J. R. Soc., Interface 6, S437– S450,  DOI: 10.1098/rsif.2008.0516.focus

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    27

    Towards programming languages for genetic engineering of living cells

    Pedersen, Michael; Phillips, Andrew

    Journal of the Royal Society, Interface (2009), 6 (Suppl. 4), S437-S450CODEN: JRSICU; ISSN:1742-5689. (Royal Society)

    Synthetic biol. aims at producing novel biol. systems to carry out some desired and well-defined functions. An ultimate dream is to design these systems at a high level of abstraction using engineering-based tools and programming languages, press a button, and have the design translated to DNA sequences that can be synthesized and put to work in living cells. We introduce such a programming language, which allows logical interactions between potentially undetd. proteins and genes to be expressed in a modular manner. Programs can be translated by a compiler into sequences of std. biol. parts, a process that relies on logic programming and prototype databases that contain known biol. parts and protein interactions. Programs can also be translated to reactions, allowing simulations to be carried out. While current limitations on available data prevent full use of the language in practical applications, the language can be used to develop formal models of synthetic systems, which are otherwise often presented by informal notations. The language can also serve as a concrete proposal on which future language designs can be discussed, and can help to guide the emerging std. of biol. parts which so far has focused on biol., rather than logical, properties of parts.

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28. 28

    Misirli, G., Hallinan, J. S., Yu, T., Lawson, J. R., Wimalaratne, S. M., Cooling, M. T., and Wipat, A. (2011) Model annotation for synthetic biology: automating model to nucleotide sequence conversion. Bioinformatics 27, 973– 979,  DOI: 10.1093/bioinformatics/btr048

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    28

    Model annotation for synthetic biology: automating model to nucleotide sequence conversion

    Misirli, Goksel; Hallinan, Jennifer S.; Yu, Tommy; Lawson, James R.; Wimalaratne, Sarala M.; Cooling, Michael T.; Wipat, Anil

    Bioinformatics (2011), 27 (7), 973-979CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)

    Motivation: The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biol. projects. Currently, most circuits are designed through the assembly of models of individual parts such as promoters, ribosome binding sites and coding sequences. These low level models are combined to produce a dynamic model of a larger device that exhibits a desired behavior. The larger model then acts as a blueprint for phys. implementation at the DNA level. However, the conversion of models of complex genetic circuits into DNA sequences is a non-trivial undertaking due to the complexity of mapping the model parts to their phys. manifestation. Automating this process is further hampered by the lack of computationally tractable information in most models. Results: We describe a method for automatically generating DNA sequences from dynamic models implemented in CellML and Systems Biol. Markup Language (SBML). We also identify the metadata needed to annotate models to facilitate automated conversion, and propose and demonstrate a method for the markup of these models using RDF. Our algorithm has been implemented in a software tool called MoSeC. Availability: The software is available from the authors' web site http://research.ncl.ac.uk/synthetic_biol./downloads.html. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

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29. 29

    Swainston, N., Dunstan, M., Jervis, A. J., Robinson, C. J., Carbonell, P., Williams, A. R., Faulon, J.-L., Scrutton, N. S., and Kell, D. B. (2018) PartsGenie: an integrated tool for optimizing and sharing synthetic biology parts. Bioinformatics 34, 2327– 2329,  DOI: 10.1093/bioinformatics/bty105

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    29

    PartsGenie: an integrated tool for optimizing and sharing synthetic biology parts

    Swainston, Neil; Dunstan, Mark; Jervis, Adrian J.; Robinson, Christopher J.; Carbonell, Pablo; Williams, Alan R.; Faulon, Jean-Loup; Scrutton, Nigel S.; Kell, Douglas B.

    Bioinformatics (2018), 34 (13), 2327-2329CODEN: BOINFP; ISSN:1367-4811. (Oxford University Press)

    Motivation: Synthetic biol. is typified by developing novel genetic constructs from the assembly of reusable synthetic DNA parts, which contain one or more features such as promoters, ribosome binding sites, coding sequences and terminators. PartsGenie is introduced to facilitate the computational design of such synthetic biol. parts, bridging the gap between optimization tools for the design of novel parts, the representation of such parts in community-developed data stds. such as Synthetic Biol. Open Language, and their sharing in journal-recommended data repositories. Consisting of a drag-and-drop web interface, a no. of DNA optimization algorithms, and an interface to the well-used data repository JBEI ICE, PartsGenie facilitates the design, optimization and dissemination of reusable synthetic biol. parts through an integrated application.

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    Hoops, S., Sahle, S., Gauges, R., Lee, C., Pahle, J., Simus, N., Singhal, M., Xu, L., Mendes, P., and Kummer, U. (2006) COPASI—a COmplex PAthway SImulator. Bioinformatics 22, 3067,  DOI: 10.1093/bioinformatics/btl485

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    30

    COPASI - A COmplex PAthway SImulator

    Hoops, Stefan; Sahle, Sven; Gauges, Ralph; Lee, Christine; Pahle, Juergen; Simus, Natalia; Singhal, Mudita; Xu, Liang; Mendes, Pedro; Kummer, Ursula

    Bioinformatics (2006), 22 (24), 3067-3074CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)

    Motivation: Simulation and modeling is becoming a std. approach to understand complex biochem. processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. Results: Here, we present COPASI, a platform-independent and user-friendly biochem. simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random no. generator numerical resoln. in stochastic simulation.

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31. 31

    Moraru, I., Schaff, J., and Slepchenko, B. (2008) Virtual cell modelling and simulation software environment. IET Syst. Biol. 2, 352,  DOI: 10.1049/iet-syb:20080102

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    Virtual Cell modelling and simulation software environment

    Moraru I I; Schaff J C; Slepchenko B M; Blinov M L; Morgan F; Lakshminarayana A; Gao F; Li Y; Loew L M

    IET systems biology (2008), 2 (5), 352-62 ISSN:1751-8849.

    The Virtual Cell (VCell; http://vcell.org/) is a problem solving environment, built on a central database, for analysis, modelling and simulation of cell biological processes. VCell integrates a growing range of molecular mechanisms, including reaction kinetics, diffusion, flow, membrane transport, lateral membrane diffusion and electrophysiology, and can associate these with geometries derived from experimental microscope images. It has been developed and deployed as a web-based, distributed, client-server system, with more than a thousand world-wide users. VCell provides a separation of layers (core technologies and abstractions) representing biological models, physical mechanisms, geometry, mathematical models and numerical methods. This separation clarifies the impact of modelling decisions, assumptions and approximations. The result is a physically consistent, mathematically rigorous, spatial modelling and simulation framework. Users create biological models and VCell will automatically (i) generate the appropriate mathematical encoding for running a simulation and (ii) generate and compile the appropriate computer code. Both deterministic and stochastic algorithms are supported for describing and running non-spatial simulations; a full partial differential equation solver using the finite volume numerical algorithm is available for reaction-diffusion-advection simulations in complex cell geometries including 3D geometries derived from microscope images. Using the VCell database, models and model components can be reused and updated, as well as privately shared among collaborating groups, or published. Exchange of models with other tools is possible via import/export of SBML, CellML and MatLab formats. Furthermore, curation of models is facilitated by external database binding mechanisms for unique identification of components and by standardised annotations compliant with the MIRIAM standard. VCell is now open source, with its native model encoding language (VCML) being a public specification, which stands as the basis for a new generation of more customised, experiment-centric modelling tools using a new plug-in based platform.

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32. 32

    Galdzicki, M., Clancy, K. P., Oberortner, E., Pocock, M., Quinn, J. Y., Rodriguez, C. A., Nicholas, R., Wilson, M. L., Adam, L., Anderson, J. C. (2014) The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology. Nat. Biotechnol. 32, 545– 550,  DOI: 10.1038/nbt.2891

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    32

    The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology

    Galdzicki, Michal; Clancy, Kevin P.; Oberortner, Ernst; Pocock, Matthew; Quinn, Jacqueline Y.; Rodriguez, Cesar A.; Roehner, Nicholas; Wilson, Mandy L.; Adam, Laura; Anderson, J. Christopher; Bartley, Bryan A.; Beal, Jacob; Chandran, Deepak; Chen, Joanna; Densmore, Douglas; Endy, Drew; Grunberg, Raik; Hallinan, Jennifer; Hillson, Nathan J.; Johnson, Jeffrey D.; Kuchinsky, Allan; Lux, Matthew; Misirli, Goksel; Peccoud, Jean; Plahar, Hector A.; Sirin, Evren; Stan, Guy-Bart; Villalobos, Alan; Wipat, Anil; Gennari, John H.; Myers, Chris J.; Sauro, Herbert M.

    Nature Biotechnology (2014), 32 (6), 545-550CODEN: NABIF9; ISSN:1087-0156. (Nature Publishing Group)

    The re-use of previously validated designs is crit. to the evolution of synthetic biol. from a research discipline to an engineering practice. Here we describe the Synthetic Biol. Open Language (SBOL), a proposed data std. for exchanging designs within the synthetic biol. community. SBOL represents synthetic biol. designs in a community-driven, formalized format for exchange between software tools, research groups and com. service providers. The SBOL Developers Group has implemented SBOL as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. We describe early successes, including a demonstration of the utility of SBOL for information exchange between several different software tools and repositories from both academic and industrial partners. As a community-driven std., SBOL will be updated as synthetic biol. evolves to provide specific capabilities for different aspects of the synthetic biol. workflow.

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    Hucka, M. (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19, 524,  DOI: 10.1093/bioinformatics/btg015

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    The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models

    Hucka, M.; Finney, A.; Sauro, H. M.; Bolouri, H.; Doyle, J. C.; Kitano, H.; Arkin, A. P.; Bornstein, B. J.; Bray, D.; Cornish-Bowden, A.; Cuellar, A. A.; Dronov, S.; Gilles, E. D.; Ginkel, M.; Gor, V.; Goryanin, I. I.; Hedley, W. J.; Hodgman, T. C.; Hofmeyr, J.-H.; Hunter, P. J.; Juty, N. S.; Kasberger, J. L.; Kremling, A.; Kummer, U.; Le Novere, N.; Loew, L. M.; Lucio, D.; Mendes, P.; Minch, E.; Mjolsness, E. D.; Nakayama, Y.; Nelson, M. R.; Nielsen, P. F.; Sakurada, T.; Schaff, J. C.; Shapiro, B. E.; Shimizu, T. S.; Spence, H. D.; Stelling, J.; Takahashi, K.; Tomita, M.; Wagner, J.; Wang, J.

    Bioinformatics (2003), 19 (4), 524-531CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)

    The Systems Biol. Markup Language (SBML) Level 1 is a free, open, XML-based format for representing biochem. reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biol., including cell signaling pathways, metabolic pathways, gene regulation, and others.

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    Oberortner, E., Densmore, D., and Anderson, J. C. (2012) An interactive pattern story on designing the architecture of Clotho. In Proceedings of the 19th Conference on Pattern Languages of Programs, Association for Computing Machinery.

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    Blakes, J., Twycross, J., Romero-Campero, F. J., and Krasnogor, N. (2011) The Infobiotics Workbench: an integrated in silico modelling platform for Systems and Synthetic Biology. Bioinformatics 27, 3323– 3324,  DOI: 10.1093/bioinformatics/btr571

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    35

    The Infobiotics Workbench: an integrated in silico modelling platform for Systems and Synthetic Biology

    Blakes, Jonathan; Twycross, Jamie; Romero-Campero, Francisco Jose; Krasnogor, Natalio

    Bioinformatics (2011), 27 (23), 3323-3324CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)

    The Infobiotics Workbench is an integrated software suite incorporating model specification, simulation, parameter optimization and model checking for Systems and Synthetic Biol. A modular model specification allows for straightforward creation of large-scale models contg. many compartments and reactions. Models are simulated either using stochastic simulation or numerical integration, and visualized in time and space. Model parameters and structure can be optimized with evolutionary algorithms, and model properties calcd. using probabilistic model checking.

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36. 36

    Mısırlı, G., Taylor, R., Goñi-Moreno, A., McLaughlin, J. A., Myers, C., Gennari, J. H., Lord, P., and Wipat, A. (2019) SBOL-OWL: An Ontological Approach for Formal and Semantic Representation of Synthetic Biology Information. ACS Synth. Biol. 8, 1498– 1514,  DOI: 10.1021/acssynbio.8b00532

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    36

    SBOL-OWL: An Ontological Approach for Formal and Semantic Representation of Synthetic Biology Information

    Misirli, Goksel; Taylor, Renee; Goni-Moreno, Angel; McLaughlin, James Alastair; Myers, Chris; Gennari, John H.; Lord, Phillip; Wipat, Anil

    ACS Synthetic Biology (2019), 8 (7), 1498-1514CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    Std. representation of data is key for the reproducibility of designs in synthetic biol. The Synthetic Biol. Open Language (SBOL) has already emerged as a data std. to represent information about genetic circuits, and it is based on capturing data using graphs. The language provides the syntax using a free text document that is accessible to humans only. This paper describes SBOL-OWL, an ontol. for a machine understandable definition of SBOL. This ontol. acts as a semantic layer for genetic circuit designs. As a result, computational tools can understand the meaning of design entities in addn. to parsing structured SBOL data. SBOL-OWL not only describes how genetic circuits can be constructed computationally, it also facilitates the use of several existing Semantic Web tools for synthetic biol. This paper demonstrates some of these features, for example, to validate designs and check for inconsistencies. Through the use of SBOL-OWL, queries can be simplified and become more intuitive. Moreover, existing reasoners can be used to infer information about genetic circuit designs that cannot be directly retrieved using existing querying mechanisms. This ontol. representation of the SBOL std. provides a new perspective to the verification, representation, and querying of information about genetic circuits and is important to incorporate complex design information via the integration of biol. ontologies.

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    Baker, D., Church, G., Collins, J., Endy, D., Jacobson, J., Keasling, J., Modrich, P., Smolke, C., and Weiss, R. (2006) Engineering life: building a fab for biology. Sci. Am. 294, 44– 51,  DOI: 10.1038/scientificamerican0606-44

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    Engineering life: Building a FAB for biology

    Baker, David; Church, George; Collins, Jim; Endy, Drew; Jacobson, Joseph; Keasling, Jay; Modrich, Paul; Smolke, Christina; Weiss, Ron

    Scientific American (2006), 294 (6), 44-51CODEN: SCAMAC; ISSN:0036-8733. (Scientific American, Inc.)

    A review. Flexible, reliable fabrication technol. along with standardized methods and design libraries gave rise to the semiconductor chip "fab" system. It enabled engineers to create extraordinarily complex and powerful electronic devices with broad applications. A fab approach could similarly empower biol. engineers to conceive and build sophisticated devices from biol. parts. Bio fab technologies and techniques are already being developed and used. Addressing safety issues and encouraging biologists to think more like engineers are ongoing efforts.

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    Roberts, R. J., Vincze, T., Posfai, J., and Macelis, D. (2004) REBASE-restriction enzymes and DNA methyltransferases. Nucleic acids research 33, D230– D232,  DOI: 10.1093/nar/gki029

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    Salis, H. M., Mirsky, E. A., and Voigt, C. A. (2009) Automated design of synthetic ribosome binding sites to control protein expression. Nat. Biotechnol. 27, 946– 950,  DOI: 10.1038/nbt.1568

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    Automated design of synthetic ribosome binding sites to control protein expression

    Salis, Howard M.; Mirsky, Ethan A.; Voigt, Christopher A.

    Nature Biotechnology (2009), 27 (10), 946-950CODEN: NABIF9; ISSN:1087-0156. (Nature Publishing Group)

    Microbial engineering often requires fine control over protein expression-for example, to connect genetic circuits or control flux through a metabolic pathway. To circumvent the need for trial and error optimization, we developed a predictive method for designing synthetic ribosome binding sites, enabling a rational control over the protein expression level. Exptl. validation of >100 predictions in Escherichia coli showed that the method is accurate to within a factor of 2.3 over a range of 100,000-fold. The design method also correctly predicted that reusing identical ribosome binding site sequences in different genetic contexts can result in different protein expression levels. We demonstrate the method's utility by rationally optimizing protein expression to connect a genetic sensor to a synthetic circuit. The proposed forward engineering approach should accelerate the construction and systematic optimization of large genetic systems.

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74. 74

    Hillson, N. J., Rosengarten, R. D., and Keasling, J. D. (2012) j5 DNA assembly design automation software. ACS Synth. Biol. 1, 14– 21,  DOI: 10.1021/sb2000116

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    74

    j5 DNA Assembly Design Automation Software

    Hillson, Nathan J.; Rosengarten, Rafael D.; Keasling, Jay D.

    ACS Synthetic Biology (2012), 1 (1), 14-21CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    Recent advances in Synthetic Biol. have yielded standardized and automatable DNA assembly protocols that enable a broad range of biotechnol. research and development. Unfortunately, the exptl. design required for modern scar-less multipart DNA assembly methods is frequently laborious, time-consuming, and error-prone. Here, we report the development and deployment of a web-based software tool, j5, which automates the design of scar-less multipart DNA assembly protocols including SLIC, Gibson, CPEC, and Golden Gate. The key innovations of the j5 design process include cost optimization, leveraging DNA synthesis when cost-effective to do so, the enforcement of design specification rules, hierarchical assembly strategies to mitigate likely assembly errors, and the instruction of manual or automated construction of scar-less combinatorial DNA libraries. Using a GFP expression testbed, we demonstrate that j5 designs can be executed with the SLIC, Gibson, or CPEC assembly methods, used to build combinatorial libraries with the Golden Gate assembly method, and applied to the prepn. of linear gene deletion cassettes for E. coli. The DNA assembly design algorithms reported here are generally applicable to broad classes of DNA construction methodologies and could be implemented to supplement other DNA assembly design tools. Taken together, these innovations save researchers time and effort, reduce the frequency of user design errors and off-target assembly products, decrease research costs, and enable scar-less multipart and combinatorial DNA construction at scales unfeasible without computer-aided design.

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75. 75

    Crowther, M., Grozinger, L., Pocock, M., Taylor, C. P. D., McLaughlin, J. A., Mısırlı, G., Bartley, B. A., Beal, J., Goñi-Moreno, A., and Wipat, A. (2020) ShortBOL: A Language for Scripting Designs for Engineered Biological Systems Using Synthetic Biology Open Language (SBOL). ACS Synth. Biol. 9, 962– 966,  DOI: 10.1021/acssynbio.9b00470

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    75

    ShortBOL: A Language for Scripting Designs for Engineered Biological Systems Using Synthetic Biology Open Language (SBOL)

    Crowther, Matthew; Grozinger, Lewis; Pocock, Matthew; Taylor, Christopher P. D.; McLaughlin, James A.; Misirli, Goksel; Bartley, Bryan A.; Beal, Jacob; Goni-Moreno, Angel; Wipat, Anil

    ACS Synthetic Biology (2020), 9 (4), 962-966CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    The Synthetic Biol. Open Language (SBOL) is an emerging synthetic biol. data exchange std., designed primarily for unambiguous and efficient machine-to-machine communication. However, manual editing of SBOL is generally difficult for nontrivial designs. Here, we describe ShortBOL, a lightwt. SBOL scripting language that bridges the gap between manual editing, visual design tools, and direct programming. ShortBOL is a shorthand textual language developed to enable users to create SBOL designs quickly and easily, without requiring strong programming skills or visual design tools.

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    Construction of a genetic toggle switch in Escherichia coli

    Gardner, Timothy S.; Cantor, Charles R.; Collins, James J.

    Nature (London) (2000), 403 (6767), 339-342CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)

    It has been proposed that gene-regulatory circuits with virtually any desired property can be constructed from networks of simple regulatory elements. These properties, which include multistability and oscillations, have been found in specialized gene circuits such as the bacteriophage λ switch and the Cyanobacteria circadian oscillator. However, these behaviors have not been demonstrated in networks of non-specialized regulatory components. Here we present the construction of a genetic toggle switch - a synthetic, bistable gene-regulatory network - in Escherichia coli and provide a simple theory that predicts the conditions necessary for bistability. The toggle is constructed from any two repressible promoters arranged in a mutually inhibitory network. It is flipped between stable states using transient chem. or thermal induction and exhibits a nearly ideal switching threshold. As a practical device, the toggle switch forms a synthetic, addressable cellular memory unit and has implications for biotechnol., biocomputing and gene therapy.

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    A synthetic oscillatory network of transcriptional regulators

    Elowitz M B; Leibler S

    Nature (2000), 403 (6767), 335-8 ISSN:0028-0836.

    Networks of interacting biomolecules carry out many essential functions in living cells, but the 'design principles' underlying the functioning of such intracellular networks remain poorly understood, despite intensive efforts including quantitative analysis of relatively simple systems. Here we present a complementary approach to this problem: the design and construction of a synthetic network to implement a particular function. We used three transcriptional repressor systems that are not part of any natural biological clock to build an oscillating network, termed the repressilator, in Escherichia coli. The network periodically induces the synthesis of green fluorescent protein as a readout of its state in individual cells. The resulting oscillations, with typical periods of hours, are slower than the cell-division cycle, so the state of the oscillator has to be transmitted from generation to generation. This artificial clock displays noisy behaviour, possibly because of stochastic fluctuations of its components. Such 'rational network design may lead both to the engineering of new cellular behaviours and to an improved understanding of naturally occurring networks.

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78. 78

    Dockery, J. D. and Keener, J. P. (2001) A Mathematical Model for Quorum Sensing in Pseudomonas aeruginosa. Bull. Math. Biol. 63, 95,  DOI: 10.1006/bulm.2000.0205

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    A mathematical model for quorum sensing in Pseudomonas aeruginosa

    Dockery, Jack D.; Keener, James P.

    Bulletin of Mathematical Biology (2001), 63 (1), 95-116CODEN: BMTBAP; ISSN:0092-8240. (Academic Press)

    The bacteria Pseudomonas aeruginosa use the size and d. of their colonies to regulate the prodn. of a large variety of substances, including toxins. This phenomenon, called quorum sensing, apparently enables colonies to grow to sufficient size undetected by the immune system of the host organism. In this paper, we present a math. model of quorum sensing in P. aeruginosa that is based on the known biochem. of regulation of the autoinducer that is crucial to this signalling mechanism. Using this model we show that quorum sensing works because of a biochem. switch between two stable steady solns., one with low levels of autoinducer and one with high levels of autoinducer. (c) 2001 Society for Mathematical Biology.

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    Myers, C. (2010) Engineering Genetic Circuits, CRC Press.

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    Baig, H. and Madsen, J. (2017) Simulation Approach for Timing Analysis of Genetic Logic Circuits. ACS Synth. Biol. 6, 1169– 1179,  DOI: 10.1021/acssynbio.6b00296

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    80

    Simulation Approach for Timing Analysis of Genetic Logic Circuits

    Baig, Hasan; Madsen, Jan

    ACS Synthetic Biology (2017), 6 (7), 1169-1179CODEN: ASBCD6; ISSN:2161-5063. (American Chemical Society)

    Constructing genetic logic circuits is an application of synthetic biol. in which parts of the DNA of a living cell are engineered to perform a dedicated Boolean function triggered by an appropriate concn. of certain proteins or by different genetic components. These logic circuits work in a manner similar to electronic logic circuits, but they are much more stochastic and hence much harder to characterize. In this article, we introduce an approach to analyze the threshold value and timing of genetic logic circuits. We show how this approach can be used to analyze the timing behavior of single and cascaded genetic logic circuits. We further analyze the timing sensitivity of circuits by varying the degrdn. rates and concns. Our approach can be used not only to characterize the timing behavior but also to analyze the timing constraints of cascaded genetic logic circuits, a capability that we believe will be important for design automation in synthetic biol.

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