1
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Ba F, Zhang Y, Ji X, Liu WQ, Ling S, Li J. Expanding the toolbox of probiotic Escherichia coli Nissle 1917 for synthetic biology. Biotechnol J 2024; 19:e2300327. [PMID: 37800393 DOI: 10.1002/biot.202300327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/11/2023] [Accepted: 09/27/2023] [Indexed: 10/07/2023]
Abstract
Escherichia coli Nissle 1917 (EcN) is a probiotic microbe that has the potential to be developed as a promising chassis for synthetic biology applications. However, the molecular tools and techniques for utilizing EcN remain to be further explored. To address this opportunity, the EcN-based toolbox was systematically expanded, enabling EcN as a powerful platform for more applications. First, two EcN cryptic plasmids and other compatible plasmids were genetically engineered to enrich the manipulable plasmid toolbox for multiple gene coexpression. Next, two EcN-based technologies were developed, including the conjugation strategy for DNA transfer, and quantification of protein expression capability. Finally, the EcN-based applications were further expanded by developing EcN native integrase-mediated genetic engineering and establishing an in vitro cell-free protein synthesis (CFPS) system. Overall, this study expanded the toolbox for manipulating and making full use of EcN as a commonly used probiotic chassis, providing several simplified, dependable, and predictable strategies for researchers working in synthetic biology fields.
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Affiliation(s)
- Fang Ba
- School of Physical Science and Technology, ShanghaiTech University, Shanghai, China
| | - Yufei Zhang
- School of Physical Science and Technology, ShanghaiTech University, Shanghai, China
| | - Xiangyang Ji
- School of Physical Science and Technology, ShanghaiTech University, Shanghai, China
| | - Wan-Qiu Liu
- School of Physical Science and Technology, ShanghaiTech University, Shanghai, China
| | - Shengjie Ling
- School of Physical Science and Technology, ShanghaiTech University, Shanghai, China
| | - Jian Li
- School of Physical Science and Technology, ShanghaiTech University, Shanghai, China
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2
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Chaudhari VR, Hanson MR. GoldBricks: an improved cloning strategy that combines features of Golden Gate and BioBricks for better efficiency and usability. Synth Biol (Oxf) 2021; 6:ysab032. [PMID: 34778568 PMCID: PMC8578713 DOI: 10.1093/synbio/ysab032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 09/17/2021] [Accepted: 11/08/2021] [Indexed: 12/02/2022] Open
Abstract
With increasing complexity of expression studies and the repertoire of characterized sequences, combinatorial cloning has become a common necessity. Techniques like BioBricks and Golden Gate aim to standardize and speed up the process of cloning large constructs while enabling sharing of resources. The BioBricks format provides a simplified and flexible approach to endless assembly with a compact library and useful intermediates but is a slow process, joining only two parts in a cycle. Golden Gate improves upon the speed with use of Type IIS enzymes and joins several parts in a cycle but requires a larger library of parts and logistical inefficiencies scale up significantly in the multigene format. We present here a method that provides improvement over these techniques by combining their features. By using Type IIS enzymes in a format like BioBricks, we have enabled a faster and efficient assembly with reduced scarring, which performs at a similarly fast pace as Golden Gate, but significantly reduces library size and user input. Additionally, this method enables faster assembly of operon-style constructs, a feature requiring extensive workaround in Golden Gate. Our format allows such inclusions resulting in faster and more efficient assembly.
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Affiliation(s)
| | - Maureen R Hanson
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
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3
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Wang B, Yang H, Sun J, Dou C, Huang J, Guo FB. BioMaster: An Integrated Database and Analytic Platform to Provide Comprehensive Information About BioBrick Parts. Front Microbiol 2021; 12:593979. [PMID: 33552037 PMCID: PMC7858672 DOI: 10.3389/fmicb.2021.593979] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 01/04/2021] [Indexed: 01/25/2023] Open
Abstract
Synthetic biology seeks to create new biological parts, devices, and systems, and to reconfigure existing natural biological systems for custom-designed purposes. The standardized BioBrick parts are the foundation of synthetic biology. The incomplete and flawed metadata of BioBrick parts, however, are a major obstacle for designing genetic circuit easily, quickly, and accurately. Here, a database termed BioMaster http://www.biomaster-uestc.cn was developed to extensively complement information about BioBrick parts, which includes 47,934 items of BioBrick parts from the international Genetically Engineered Machine (iGEM) Registry with more comprehensive information integrated from 10 databases, providing corresponding information about functions, activities, interactions, and related literature. Moreover, BioMaster is also a user-friendly platform for retrieval and analyses of relevant information on BioBrick parts.
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Affiliation(s)
- Beibei Wang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Centre for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huayi Yang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jianan Sun
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chuhao Dou
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jian Huang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Centre for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng-Biao Guo
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Centre for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China
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4
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Whitford CM, Dymek S, Kerkhoff D, März C, Schmidt O, Edich M, Droste J, Pucker B, Rückert C, Kalinowski J. Auxotrophy to Xeno-DNA: an exploration of combinatorial mechanisms for a high-fidelity biosafety system for synthetic biology applications. J Biol Eng 2018; 12:13. [PMID: 30123321 PMCID: PMC6090650 DOI: 10.1186/s13036-018-0105-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Accepted: 06/25/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Biosafety is a key aspect in the international Genetically Engineered Machine (iGEM) competition, which offers student teams an amazing opportunity to pursue their own research projects in the field of Synthetic Biology. iGEM projects often involve the creation of genetically engineered bacterial strains. To minimize the risks associated with bacterial release, a variety of biosafety systems were constructed, either to prevent survival of bacteria outside the lab or to hinder horizontal or vertical gene transfer. MAIN BODY Physical containment methods such as bioreactors or microencapsulation are considered the first safety level. Additionally, various systems involving auxotrophies for both natural and synthetic compounds have been utilized by iGEM teams in recent years. Combinatorial systems comprising multiple auxotrophies have been shown to reduced escape frequencies below the detection limit. Furthermore, a number of natural toxin-antitoxin systems can be deployed to kill cells under certain conditions. Additionally, parts of naturally occurring toxin-antitoxin systems can be used for the construction of 'kill switches' controlled by synthetic regulatory modules, allowing control of cell survival. Kill switches prevent cell survival but do not completely degrade nucleic acids. To avoid horizontal gene transfer, multiple mechanisms to cleave nucleic acids can be employed, resulting in 'self-destruction' of cells. Changes in light or temperature conditions are powerful regulators of gene expression and could serve as triggers for kill switches or self-destruction systems. Xenobiology-based containment uses applications of Xeno-DNA, recoded codons and non-canonical amino acids to nullify the genetic information of constructed cells for wild type organisms. A 'minimal genome' approach brings the opportunity to reduce the genome of a cell to only genes necessary for survival under lab conditions. Such cells are unlikely to survive in the natural environment and are thus considered safe hosts. If suitable for the desired application, a shift to cell-free systems based on Xeno-DNA may represent the ultimate biosafety system. CONCLUSION Here we describe different containment approaches in synthetic biology, ranging from auxotrophies to minimal genomes, which can be combined to significantly improve reliability. Since the iGEM competition greatly increases the number of people involved in synthetic biology, we will focus especially on biosafety systems developed and applied in the context of the iGEM competition.
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Affiliation(s)
| | - Saskia Dymek
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
| | - Denise Kerkhoff
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
| | - Camilla März
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
| | - Olga Schmidt
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
| | - Maximilian Edich
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
| | - Julian Droste
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
- Faculty of Biology, Bielefeld University, Bielefeld, Germany
| | - Boas Pucker
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
- Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Present address: Evolution and Diversity, Department of Plant Sciences, University of Cambridge, Cambridge, UK
| | - Christian Rückert
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
- Faculty of Biology, Bielefeld University, Bielefeld, Germany
| | - Jörn Kalinowski
- Center for Biotechnology, Bielefeld University, 33615 Bielefeld, Germany
- Faculty of Biology, Bielefeld University, Bielefeld, Germany
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5
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Fang G, Zhang S, Dong Y. Optimizing DNA assembly based on statistical language modelling. Nucleic Acids Res 2017; 45:e182. [PMID: 29036490 PMCID: PMC5727464 DOI: 10.1093/nar/gkx859] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Accepted: 09/16/2017] [Indexed: 11/13/2022] Open
Abstract
By successively assembling genetic parts such as BioBrick according to grammatical models, complex genetic constructs composed of dozens of functional blocks can be built. However, usually every category of genetic parts includes a few or many parts. With increasing quantity of genetic parts, the process of assembling more than a few sets of these parts can be expensive, time consuming and error prone. At the last step of assembling it is somewhat difficult to decide which part should be selected. Based on statistical language model, which is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence, the most commonly used parts will be selected. Then, a dynamic programming algorithm was designed to figure out the solution of maximum probability. The algorithm optimizes the results of a genetic design based on a grammatical model and finds an optimal solution. In this way, redundant operations can be reduced and the time and cost required for conducting biological experiments can be minimized.
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Affiliation(s)
- Gang Fang
- Institute of Advanced Cyberspace Technology, Guangzhou University, Guangzhou 510006, China.,Genetic Engineering Laboratory, School of Biological and Environmental Engineering, Xi'an University, Xi'an 710065, China
| | - Shemin Zhang
- School of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong 723001, China
| | - Yafei Dong
- College of life sciences, Shaanxi Normal University, Xi'an 710119, China
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6
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Shi P, Wu T, Li P, Guo B, Fang G, Dong Y. Use of processed data to design an orderly logic gate to construct plasmids in GenoCAD. IET Syst Biol 2017; 11:65-68. [PMID: 28476974 DOI: 10.1049/iet-syb.2016.0043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Rapid developments have been made in synthetic biology within the past two decades, particularly in combination with chemistry, computer science, and other disciplines. Genetic components and internal features have been a main focus of research for synthetic biologists. Logic gates can be applied in various disciplines, but have not yet been used for plasmid design. GenoCAD is a computer-aided design software programme for synthetic biology that can be used to design complex structures. Thus, in this study, the authors analysed a large, commonly used data set containing over 70,000 feature sequences and eventually obtained comprehensive information for a complete data set without redundancy. By analysing the internal feature sequences, the authors input the most representative data in the GenoCAD platform, along with design rules and grammar for constructing high-quality practical parts. Additionally, the orderly logic gate for building biological parts designed in this study may be useful for professionals and non-professionals and may have applications in the design of a new biological computer. Finally, the authors compared the constructed plasmid with other successful examples in BLAST and PlasMapper software to demonstrate the rationality of the orderly logic gate.
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Affiliation(s)
- Pei Shi
- Department of Computer Sciences, Shaanxi Normal University, Xi'an, Shaanxi, People's Republic of China
| | - Tao Wu
- Department of Computer Sciences, Shaanxi Normal University, Xi'an, Shaanxi, People's Republic of China
| | - Panpan Li
- Department of Computer Sciences, Shaanxi Normal University, Xi'an, Shaanxi, People's Republic of China
| | - Bingjie Guo
- Department of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, People's Republic of China
| | - Gang Fang
- School of Biological and Environmental Engineering, Xi'an University, Xi'an, Shaanxi, People's Republic of China
| | - Yafei Dong
- Department of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, People's Republic of China.
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7
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Shih SCC, Goyal G, Kim PW, Koutsoubelis N, Keasling JD, Adams PD, Hillson NJ, Singh AK. A Versatile Microfluidic Device for Automating Synthetic Biology. ACS Synth Biol 2015; 4:1151-64. [PMID: 26075958 DOI: 10.1021/acssynbio.5b00062] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
New microbes are being engineered that contain the genetic circuitry, metabolic pathways, and other cellular functions required for a wide range of applications such as producing biofuels, biobased chemicals, and pharmaceuticals. Although currently available tools are useful in improving the synthetic biology process, further improvements in physical automation would help to lower the barrier of entry into this field. We present an innovative microfluidic platform for assembling DNA fragments with 10× lower volumes (compared to that of current microfluidic platforms) and with integrated region-specific temperature control and on-chip transformation. Integration of these steps minimizes the loss of reagents and products compared to that with conventional methods, which require multiple pipetting steps. For assembling DNA fragments, we implemented three commonly used DNA assembly protocols on our microfluidic device: Golden Gate assembly, Gibson assembly, and yeast assembly (i.e., TAR cloning, DNA Assembler). We demonstrate the utility of these methods by assembling two combinatorial libraries of 16 plasmids each. Each DNA plasmid is transformed into Escherichia coli or Saccharomyces cerevisiae using on-chip electroporation and further sequenced to verify the assembly. We anticipate that this platform will enable new research that can integrate this automated microfluidic platform to generate large combinatorial libraries of plasmids and will help to expedite the overall synthetic biology process.
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Affiliation(s)
- Steve C. C. Shih
- Sandia National Laboratories, 7011 East Avenue, Livermore, California 94550, United States
| | - Garima Goyal
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road, Berkeley, California 94720, United States
| | - Peter W. Kim
- Sandia National Laboratories, 7011 East Avenue, Livermore, California 94550, United States
| | - Nicolas Koutsoubelis
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road, Berkeley, California 94720, United States
| | - Jay D. Keasling
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road, Berkeley, California 94720, United States
- Department of Chemical & Biomolecular Engineering, Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Paul D. Adams
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road, Berkeley, California 94720, United States
| | - Nathan J. Hillson
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road, Berkeley, California 94720, United States
| | - Anup K. Singh
- Sandia National Laboratories, 7011 East Avenue, Livermore, California 94550, United States
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8
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Basso-Blandin A, Delaplace F. Towards a behavioral-matching based compilation of synthetic biology functions. Acta Biotheor 2015; 63:325-39. [PMID: 26141968 PMCID: PMC4531147 DOI: 10.1007/s10441-015-9265-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Accepted: 06/24/2015] [Indexed: 11/27/2022]
Abstract
The field of synthetic biology is looking forward engineering framework for safely designing reliable de-novo biological functions. In this undertaking, Computer-Aided-Design (CAD) environments should play a central role for facilitating the design. Although, CAD environment is widely used to engineer artificial systems the application in synthetic biology is still in its infancy. In this article we address the problem of the design of a high level language which at the core of CAD environment. More specifically the Gubs (Genomic Unified Behavioural Specification) language is a specification language used to describe the observations of the expected behaviour. The compiler appropriately selects components such that the observation of the synthetic biological function resulting to their assembly complies to the programmed behaviour.
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9
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Roehner N, Zhang Z, Nguyen T, Myers CJ. Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language. ACS Synth Biol 2015; 4:873-9. [PMID: 25822671 DOI: 10.1021/sb5003289] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).
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Affiliation(s)
- Nicholas Roehner
- Department
of Bioengineering, University of Utah, Salt Lake City, Utah 84112, United States
| | - Zhen Zhang
- Department
of Electrical and Computer Engineering, University of Utah, Salt Lake
City, Utah 84112, United States
| | - Tramy Nguyen
- Department
of Electrical and Computer Engineering, University of Utah, Salt Lake
City, Utah 84112, United States
| | - Chris J. Myers
- Department
of Electrical and Computer Engineering, University of Utah, Salt Lake
City, Utah 84112, United States
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10
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Kelwick R, Bowater L, Yeoman KH, Bowater RP. Promoting microbiology education through the iGEM synthetic biology competition. FEMS Microbiol Lett 2015; 362:fnv129. [DOI: 10.1093/femsle/fnv129] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2015] [Indexed: 12/14/2022] Open
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11
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Coll A, Wilson ML, Gruden K, Peccoud J. Rule-Based Design of Plant Expression Vectors Using GenoCAD. PLoS One 2015; 10:e0132502. [PMID: 26148190 PMCID: PMC4492961 DOI: 10.1371/journal.pone.0132502] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2015] [Accepted: 06/15/2015] [Indexed: 01/28/2023] Open
Abstract
Plant synthetic biology requires software tools to assist on the design of complex multi-genic expression plasmids. Here a vector design strategy to express genes in plants is formalized and implemented as a grammar in GenoCAD, a Computer-Aided Design software for synthetic biology. It includes a library of plant biological parts organized in structural categories and a set of rules describing how to assemble these parts into large constructs. Rules developed here are organized and divided into three main subsections according to the aim of the final construct: protein localization studies, promoter analysis and protein-protein interaction experiments. The GenoCAD plant grammar guides the user through the design while allowing users to customize vectors according to their needs. Therefore the plant grammar implemented in GenoCAD will help plant biologists take advantage of methods from synthetic biology to design expression vectors supporting their research projects.
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Affiliation(s)
- Anna Coll
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Mandy L. Wilson
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Kristina Gruden
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Jean Peccoud
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
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12
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Adames NR, Wilson ML, Fang G, Lux MW, Glick BS, Peccoud J. GenoLIB: a database of biological parts derived from a library of common plasmid features. Nucleic Acids Res 2015; 43:4823-32. [PMID: 25925571 PMCID: PMC4446419 DOI: 10.1093/nar/gkv272] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2014] [Accepted: 03/18/2015] [Indexed: 11/12/2022] Open
Abstract
Synthetic biologists rely on databases of biological parts to design genetic devices and systems. The sequences and descriptions of genetic parts are often derived from features of previously described plasmids using ad hoc, error-prone and time-consuming curation processes because existing databases of plasmids and features are loosely organized. These databases often lack consistency in the way they identify and describe sequences. Furthermore, legacy bioinformatics file formats like GenBank do not provide enough information about the purpose of features. We have analyzed the annotations of a library of ∼2000 widely used plasmids to build a non-redundant database of plasmid features. We looked at the variability of plasmid features, their usage statistics and their distributions by feature type. We segmented the plasmid features by expression hosts. We derived a library of biological parts from the database of plasmid features. The library was formatted using the Synthetic Biology Open Language, an emerging standard developed to better organize libraries of genetic parts to facilitate synthetic biology workflows. As proof, the library was converted into GenoCAD grammar files to allow users to import and customize the library based on the needs of their research projects.
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Affiliation(s)
- Neil R Adames
- Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, VA 24061, USA
| | - Mandy L Wilson
- Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, VA 24061, USA
| | - Gang Fang
- Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, VA 24061, USA School of Biological Technology, Xi'an University of Arts and Science, Xi'an, Shaanxi Province 710065, China
| | - Matthew W Lux
- Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, VA 24061, USA Biosciences Division, Edgewood Chemical Biological Center, 5183 Blackhawk Rd Aberdeen Proving Grounds MD 21010, USA
| | - Benjamin S Glick
- Molecular Genetics & Cell Biology, University of Chicago, 920 E. 58th St., Chicago, IL 60637, USA GSL Biotech LLC, 5211 S. Kenwood Ave., Chicago, IL 60615, USA
| | - Jean Peccoud
- Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, VA 24061, USA
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13
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Roehner N, Oberortner E, Pocock M, Beal J, Clancy K, Madsen C, Misirli G, Wipat A, Sauro H, Myers CJ. Proposed data model for the next version of the synthetic biology open language. ACS Synth Biol 2015; 4:57-71. [PMID: 24896221 DOI: 10.1021/sb500176h] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
While the first version of the Synthetic Biology Open Language (SBOL) has been adopted by several academic and commercial genetic design automation (GDA) software tools, it only covers a limited number of the requirements for a standardized exchange format for synthetic biology. In particular, SBOL Version 1.1 is capable of representing DNA components and their hierarchical composition via sequence annotations. This proposal revises SBOL Version 1.1, enabling the representation of a wider range of components with and without sequences, including RNA components, protein components, small molecules, and molecular complexes. It also introduces modules to instantiate groups of components on the basis of their shared function and assert molecular interactions between components. By increasing the range of structural and functional descriptions in SBOL and allowing for their composition, the proposed improvements enable SBOL to represent and facilitate the exchange of a broader class of genetic designs.
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Affiliation(s)
- Nicholas Roehner
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States
| | - Ernst Oberortner
- Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts, United States
| | - Matthew Pocock
- School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Jacob Beal
- Raytheon BBN Technologies, Cambridge, Massachusetts, United States
| | - Kevin Clancy
- Life Technologies, Carlsbad, California, United States
| | - Curtis Madsen
- School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Goksel Misirli
- School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Anil Wipat
- School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Herbert Sauro
- Department of Bioengineering, University of Washington, Seattle, Washington, United States
| | - Chris J. Myers
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah, United States
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14
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Li M, Borodina I. Application of synthetic biology for production of chemicals in yeast Saccharomyces cerevisiae. FEMS Yeast Res 2015; 15:1-12. [PMID: 25238571 DOI: 10.1111/1567-1364.12213] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 05/13/2014] [Accepted: 09/15/2014] [Indexed: 11/29/2022] Open
Abstract
Synthetic biology and metabolic engineering enable generation of novel cell factories that efficiently convert renewable feedstocks into biofuels, bulk, and fine chemicals, thus creating the basis for biosustainable economy independent on fossil resources. While over a hundred proof-of-concept chemicals have been made in yeast, only a very small fraction of those has reached commercial-scale production so far. The limiting factor is the high research cost associated with the development of a robust cell factory that can produce the desired chemical at high titer, rate, and yield. Synthetic biology has the potential to bring down this cost by improving our ability to predictably engineer biological systems. This review highlights synthetic biology applications for design, assembly, and optimization of non-native biochemical pathways in baker's yeast Saccharomyces cerevisiae We describe computational tools for the prediction of biochemical pathways, molecular biology methods for assembly of DNA parts into pathways, and for introducing the pathways into the host, and finally approaches for optimizing performance of the introduced pathways.
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Affiliation(s)
- Mingji Li
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark
| | - Irina Borodina
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark
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15
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Huang H, Densmore D. Integration of microfluidics into the synthetic biology design flow. LAB ON A CHIP 2014; 14:3459-74. [PMID: 25012162 DOI: 10.1039/c4lc00509k] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
One goal of synthetic biology is to design and build genetic circuits in living cells for a range of applications. Major challenges in these efforts include increasing the scalability and robustness of engineered biological systems and streamlining and automating the synthetic biology workflow of specification-design-assembly-verification. We present here a summary of the advances in microfluidic technology, particularly microfluidic large scale integration, that can be used to address the challenges facing each step of the synthetic biology workflow. Microfluidic technologies allow precise control over the flow of biological content within microscale devices, and thus may provide more reliable and scalable construction of synthetic biological systems. The integration of microfluidics and synthetic biology has the capability to produce rapid prototyping platforms for characterization of genetic devices, testing of biotherapeutics, and development of biosensors.
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Affiliation(s)
- Haiyao Huang
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA.
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Advances and computational tools towards predictable design in biological engineering. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2014; 2014:369681. [PMID: 25161694 PMCID: PMC4137594 DOI: 10.1155/2014/369681] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Accepted: 06/09/2014] [Indexed: 11/21/2022]
Abstract
The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated.
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Wilson ML, Okumoto S, Adam L, Peccoud J. Development of a domain-specific genetic language to design Chlamydomonas reinhardtii expression vectors. ACTA ACUST UNITED AC 2013; 30:251-7. [PMID: 24215020 DOI: 10.1093/bioinformatics/btt646] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
MOTIVATION Expression vectors used in different biotechnology applications are designed with domain-specific rules. For instance, promoters, origins of replication or homologous recombination sites are host-specific. Similarly, chromosomal integration or viral delivery of an expression cassette imposes specific structural constraints. As de novo gene synthesis and synthetic biology methods permeate many biotechnology specialties, the design of application-specific expression vectors becomes the new norm. In this context, it is desirable to formalize vector design strategies applicable in different domains. RESULTS Using the design of constructs to express genes in the chloroplast of Chlamydomonas reinhardtii as an example, we show that a vector design strategy can be formalized as a domain-specific language. We have developed a graphical editor of context-free grammars usable by biologists without prior exposure to language theory. This environment makes it possible for biologists to iteratively improve their design strategies throughout the course of a project. It is also possible to ensure that vectors designed with early iterations of the language are consistent with the latest iteration of the language. AVAILABILITY AND IMPLEMENTATION The context-free grammar editor is part of the GenoCAD application. A public instance of GenoCAD is available at http://www.genocad.org. GenoCAD source code is available from SourceForge and licensed under the Apache v2.0 open source license.
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Affiliation(s)
- Mandy L Wilson
- Virginia Bioinformatics Institute, Department of Plant Pathology, Physiology, and Weed Science and ICTAS Center for Systems Biology of Engineered Tissues, MC 0193, Virginia Tech, Blacksburg, VA 24061, USA
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Linshiz G, Stawski N, Poust S, Bi C, Keasling JD, Hillson NJ. PaR-PaR laboratory automation platform. ACS Synth Biol 2013; 2:216-22. [PMID: 23654257 DOI: 10.1021/sb300075t] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Labor-intensive multistep biological tasks, such as the construction and cloning of DNA molecules, are prime candidates for laboratory automation. Flexible and biology-friendly operation of robotic equipment is key to its successful integration in biological laboratories, and the efforts required to operate a robot must be much smaller than the alternative manual lab work. To achieve these goals, a simple high-level biology-friendly robot programming language is needed. We have developed and experimentally validated such a language: Programming a Robot (PaR-PaR). The syntax and compiler for the language are based on computer science principles and a deep understanding of biological workflows. PaR-PaR allows researchers to use liquid-handling robots effectively, enabling experiments that would not have been considered previously. After minimal training, a biologist can independently write complicated protocols for a robot within an hour. Adoption of PaR-PaR as a standard cross-platform language would enable hand-written or software-generated robotic protocols to be shared across laboratories.
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Affiliation(s)
- Gregory Linshiz
- Fuels Synthesis
Division, Joint BioEnergy Institute, Emeryville,
California 94608,
United States
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road Mail Stop 978R4121, Berkeley, California 94720, United States
| | - Nina Stawski
- Fuels Synthesis
Division, Joint BioEnergy Institute, Emeryville,
California 94608,
United States
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road Mail Stop 978R4121, Berkeley, California 94720, United States
| | - Sean Poust
- Department of Chemical & Biomolecular Engineering, Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Changhao Bi
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road Mail Stop 978R4121, Berkeley, California 94720, United States
| | - Jay D. Keasling
- Fuels Synthesis
Division, Joint BioEnergy Institute, Emeryville,
California 94608,
United States
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road Mail Stop 978R4121, Berkeley, California 94720, United States
- Department of Chemical & Biomolecular Engineering, Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Nathan J. Hillson
- Fuels Synthesis
Division, Joint BioEnergy Institute, Emeryville,
California 94608,
United States
- Physical
Bioscience Division, Lawrence Berkeley National Laboratory, 1 Cyclotron
Road Mail Stop 978R4121, Berkeley, California 94720, United States
- DOE Joint Genome Institute, Walnut Creek, California 94598, United States
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Platforms for Genetic Design Automation. METHODS IN MICROBIOLOGY 2013. [DOI: 10.1016/b978-0-12-417029-2.00007-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register]
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20
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Maguire E, Rocca-Serra P, Sansone SA, Davies J, Chen M. Taxonomy-Based Glyph Design—with a Case Study on Visualizing Workflows of Biological Experiments. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2012; 18:2603-2612. [PMID: 26357169 DOI: 10.1109/tvcg.2012.271] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Glyph-based visualization can offer elegant and concise presentation of multivariate information while enhancing speed and ease in visual search experienced by users. As with icon designs, glyphs are usually created based on the designers' experience and intuition, often in a spontaneous manner. Such a process does not scale well with the requirements of applications where a large number of concepts are to be encoded using glyphs. To alleviate such limitations, we propose a new systematic process for glyph design by exploring the parallel between the hierarchy of concept categorization and the ordering of discriminative capacity of visual channels. We examine the feasibility of this approach in an application where there is a pressing need for an efficient and effective means to visualize workflows of biological experiments. By processing thousands of workflow records in a public archive of biological experiments, we demonstrate that a cost-effective glyph design can be obtained by following a process of formulating a taxonomy with the aid of computation, identifying visual channels hierarchically, and defining application-specific abstraction and metaphors.
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Affiliation(s)
- E Maguire
- Oxford e-Research Centre and Department of Computer Science, University of Oxford, UK.
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21
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Madsen C, Myers CJ, Patterson T, Roehner N, Stevens JT, Winstead C. 06 2012 C1 C1 6327710 10.1109/MDT.2012.2211731 http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6327710 ${\tt iBioSim}$iBioSim. ACTA ACUST UNITED AC 2012. [DOI: 10.1109/mdt.2012.2187875] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Copeland WB, Bartley BA, Chandran D, Galdzicki M, Kim KH, Sleight SC, Maranas CD, Sauro HM. Computational tools for metabolic engineering. Metab Eng 2012; 14:270-80. [PMID: 22629572 PMCID: PMC3361690 DOI: 10.1016/j.ymben.2012.03.001] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
A great variety of software applications are now employed in the metabolic engineering field. These applications have been created to support a wide range of experimental and analysis techniques. Computational tools are utilized throughout the metabolic engineering workflow to extract and interpret relevant information from large data sets, to present complex models in a more manageable form, and to propose efficient network design strategies. In this review, we present a number of tools that can assist in modifying and understanding cellular metabolic networks. The review covers seven areas of relevance to metabolic engineers. These include metabolic reconstruction efforts, network visualization, nucleic acid and protein engineering, metabolic flux analysis, pathway prospecting, post-structural network analysis and culture optimization. The list of available tools is extensive and we can only highlight a small, representative portion of the tools from each area.
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Affiliation(s)
- Wilbert B Copeland
- Department of Bioengineering, University of Washington, Seattle, WA 98195-5061, USA.
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23
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Abstract
Background Biological Computer Aided Design (bioCAD) assists the de novo design and selection of existing genetic components to achieve a desired biological activity, as part of an integrated design-build-test cycle. To meet the emerging needs of Synthetic Biology, bioCAD tools must address the increasing prevalence of combinatorial library design, design rule specification, and scar-less multi-part DNA assembly. Results We report the development and deployment of web-based bioCAD software, DeviceEditor, which provides a graphical design environment that mimics the intuitive visual whiteboard design process practiced in biological laboratories. The key innovations of DeviceEditor include visual combinatorial library design, direct integration with scar-less multi-part DNA assembly design automation, and a graphical user interface for the creation and modification of design specification rules. We demonstrate how biological designs are rendered on the DeviceEditor canvas, and we present effective visualizations of genetic component ordering and combinatorial variations within complex designs. Conclusions DeviceEditor liberates researchers from DNA base-pair manipulation, and enables users to create successful prototypes using standardized, functional, and visual abstractions. Open and documented software interfaces support further integration of DeviceEditor with other bioCAD tools and software platforms. DeviceEditor saves researcher time and institutional resources through correct-by-construction design, the automation of tedious tasks, design reuse, and the minimization of DNA assembly costs.
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Bower AG, McClintock MK, Fong SS. Synthetic biology: a foundation for multi-scale molecular biology. Bioeng Bugs 2012; 1:309-12. [PMID: 21326830 DOI: 10.4161/bbug.1.5.12391] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2010] [Revised: 05/17/2010] [Accepted: 05/18/2010] [Indexed: 11/19/2022] Open
Abstract
The field of synthetic biology has made rapid progress in a number of areas including method development, novel applications and community building. In seeking to make biology "engineerable," synthetic biology is increasing the accessibility of biological research to researchers of all experience levels and backgrounds. One of the underlying strengths of synthetic biology is that it may establish the framework for a rigorous bottom-up approach to studying biology starting at the DNA level. Building upon the existing framework established largely by the Registry of Standard Biological Parts, careful consideration of future goals may lead to integrated multi- scale approaches to biology. Here we describe some of the current challenges that need to be addressed or considered in detail to continue the development of synthetic biology. Specifically, discussion on the areas of elucidating biological principles, computational methods and experimental construction methodologies are presented.
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Affiliation(s)
- Adam G Bower
- Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, USA
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25
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Lux MW, Bramlett BW, Ball DA, Peccoud J. Genetic design automation: engineering fantasy or scientific renewal? Trends Biotechnol 2011; 30:120-6. [PMID: 22001068 DOI: 10.1016/j.tibtech.2011.09.001] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2011] [Revised: 09/06/2011] [Accepted: 09/06/2011] [Indexed: 01/19/2023]
Abstract
The aim of synthetic biology is to make genetic systems more amenable to engineering, which has naturally led to the development of computer-aided design (CAD) tools. Experimentalists still primarily rely on project-specific ad hoc workflows instead of domain-specific tools, which suggests that CAD tools are lagging behind the front line of the field. Here, we discuss the scientific hurdles that have limited the productivity gains anticipated from existing tools. We argue that the real value of efforts to develop CAD tools is the formalization of genetic design rules that determine the complex relationships between genotype and phenotype.
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Affiliation(s)
- Matthew W Lux
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA
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Wilson ML, Hertzberg R, Adam L, Peccoud J. A step-by-step introduction to rule-based design of synthetic genetic constructs using GenoCAD. Methods Enzymol 2011; 498:173-88. [PMID: 21601678 DOI: 10.1016/b978-0-12-385120-8.00008-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
GenoCAD is an open source web-based system that provides a streamlined, rule-driven process for designing genetic sequences. GenoCAD provides a graphical interface that allows users to design sequences consistent with formalized design strategies specific to a domain, organization, or project. Design strategies include limited sets of user-defined parts and rules indicating how these parts are to be combined in genetic constructs. In addition to reducing design time to minutes, GenoCAD improves the quality and reliability of the finished sequence by ensuring that the designs follow established rules of sequence construction. GenoCAD.org is a publicly available instance of GenoCAD that can be found at www.genocad.org. The source code and latest build are available from SourceForge to allow advanced users to install and customize GenoCAD for their unique needs. This chapter focuses primarily on how the GenoCAD tools can be used to organize genetic parts into customized personal libraries, then how these libraries can be used to design sequences. In addition, GenoCAD's parts management system and search capabilities are described in detail. Instructions are provided for installing a local instance of GenoCAD on a server. Some of the future enhancements of this rapidly evolving suite of applications are briefly described.
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Affiliation(s)
- Mandy L Wilson
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA
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27
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Abstract
The most recent developments in the area of deep DNA sequencing and downstream quantitative and functional analysis are rapidly adding a new dimension to understanding biochemical pathways and metabolic interdependencies. These increasing insights pave the way to designing new strategies that address public needs, including environmental applications and therapeutic inventions, or novel cell factories for sustainable and reconcilable energy or chemicals sources. Adding yet another level is building upon nonnaturally occurring networks and pathways. Recent developments in synthetic biology have created economic and reliable options for designing and synthesizing genes, operons, and eventually complete genomes. Meanwhile, high-throughput design and synthesis of extremely comprehensive DNA sequences have evolved into an enabling technology already indispensable in various life science sectors today. Here, we describe the industrial perspective of modern gene synthesis and its relationship with synthetic biology. Gene synthesis contributed significantly to the emergence of synthetic biology by not only providing the genetic material in high quality and quantity but also enabling its assembly, according to engineering design principles, in a standardized format. Synthetic biology on the other hand, added the need for assembling complex circuits and large complexes, thus fostering the development of appropriate methods and expanding the scope of applications. Synthetic biology has also stimulated interdisciplinary collaboration as well as integration of the broader public by addressing socioeconomic, philosophical, ethical, political, and legal opportunities and concerns. The demand-driven technological achievements of gene synthesis and the implemented processes are exemplified by an industrial setting of large-scale gene synthesis, describing production from order to delivery.
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Affiliation(s)
- Frank Notka
- Life Technologies Inc./GeneArt AG, Regensburg, Germany
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28
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29
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Solomon KV, Prather KLJ. The zero-sum game of pathway optimization: emerging paradigms for tuning gene expression. Biotechnol J 2011; 6:1064-70. [PMID: 21695787 DOI: 10.1002/biot.201100086] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2011] [Revised: 04/30/2011] [Accepted: 05/09/2011] [Indexed: 12/20/2022]
Abstract
With increasing price volatility and growing awareness of the lack of sustainability of traditional chemical synthesis, microbial chemical production has been tapped as a promising renewable alternative for the generation of diverse, stereospecific compounds. Nonetheless, many attempts to generate them are not yet economically viable. Due to the zero-sum nature of microbial resources, traditional strategies of pathway optimization are attaining minimal returns. This result is in part a consequence of the gross changes in host physiology resulting from such efforts and underscores the need for more precise and subtle forms of gene modulation. In this review, we describe alternative strategies and emerging paradigms to address this problem and highlight potential solutions from the emerging field of synthetic biology.
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Affiliation(s)
- Kevin V Solomon
- Department of Chemical Engineering, Synthetic Biology Engineering Research Center (SynBERC), Massachusetts Institute of Technology, Cambridge, MA, USA
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30
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Gendrault Y, Madec M, Lallement C, Pecheux F, Haiech J. Synthetic biology methodology and model refinement based on microelectronic modeling tools and languages. Biotechnol J 2011; 6:796-806. [PMID: 21681965 DOI: 10.1002/biot.201100083] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2011] [Revised: 05/20/2011] [Accepted: 05/30/2011] [Indexed: 01/19/2023]
Abstract
In microelectronics, the design of new systems is based on a proven time-tested design flow. The goal of this paper is to determine to what extend this design flow can be adapted to biosystem design. The presented methodology is based on a top-down approach and consists of starting with a behavioral description of the system to progressively refine it to its final low-level system representation, composed of DNA parts. To preserve accuracy and simplicity, the design flow relies on refined models of biological mechanisms, which can be expressed by the hardware description languages and simulation tools traditionally used in microelectronics. A case study, the complete modeling of a priority encoder, is presented to demonstrate the effectiveness of the method.
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Affiliation(s)
- Yves Gendrault
- Institut d'Electronique du Solide et des Systemes (InESS), UMR 7163-CNRS / UdS, Strasbourg, France
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31
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Galdzicki M, Rodriguez C, Chandran D, Sauro HM, Gennari JH. Standard biological parts knowledgebase. PLoS One 2011; 6:e17005. [PMID: 21390321 PMCID: PMC3044748 DOI: 10.1371/journal.pone.0017005] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2010] [Accepted: 01/19/2011] [Indexed: 11/19/2022] Open
Abstract
We have created the Knowledgebase of Standard Biological Parts (SBPkb) as a publically accessible Semantic Web resource for synthetic biology (sbolstandard.org). The SBPkb allows researchers to query and retrieve standard biological parts for research and use in synthetic biology. Its initial version includes all of the information about parts stored in the Registry of Standard Biological Parts (partsregistry.org). SBPkb transforms this information so that it is computable, using our semantic framework for synthetic biology parts. This framework, known as SBOL-semantic, was built as part of the Synthetic Biology Open Language (SBOL), a project of the Synthetic Biology Data Exchange Group. SBOL-semantic represents commonly used synthetic biology entities, and its purpose is to improve the distribution and exchange of descriptions of biological parts. In this paper, we describe the data, our methods for transformation to SBPkb, and finally, we demonstrate the value of our knowledgebase with a set of sample queries. We use RDF technology and SPARQL queries to retrieve candidate "promoter" parts that are known to be both negatively and positively regulated. This method provides new web based data access to perform searches for parts that are not currently possible.
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Affiliation(s)
- Michal Galdzicki
- Biomedical & Health Informatics, University of Washington, Seattle, Washington, United States of America
| | - Cesar Rodriguez
- BIOFAB, University of California, Berkeley, California, United States of America
| | - Deepak Chandran
- Bioengineering, University of Washington, Seattle, Washington, United States of America
| | - Herbert M. Sauro
- Bioengineering, University of Washington, Seattle, Washington, United States of America
| | - John H. Gennari
- Biomedical & Health Informatics, University of Washington, Seattle, Washington, United States of America
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Weber E, Engler C, Gruetzner R, Werner S, Marillonnet S. A modular cloning system for standardized assembly of multigene constructs. PLoS One 2011; 6:e16765. [PMID: 21364738 PMCID: PMC3041749 DOI: 10.1371/journal.pone.0016765] [Citation(s) in RCA: 731] [Impact Index Per Article: 56.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2010] [Accepted: 01/03/2011] [Indexed: 11/19/2022] Open
Abstract
The field of synthetic biology promises to revolutionize biotechnology through the design of organisms with novel phenotypes useful for medicine, agriculture and industry. However, a limiting factor is the ability of current methods to assemble complex DNA molecules encoding multiple genetic elements in various predefined arrangements. We present here a hierarchical modular cloning system that allows the creation at will and with high efficiency of any eukaryotic multigene construct, starting from libraries of defined and validated basic modules containing regulatory and coding sequences. This system is based on the ability of type IIS restriction enzymes to assemble multiple DNA fragments in a defined linear order. We constructed a 33 kb DNA molecule containing 11 transcription units made from 44 individual basic modules in only three successive cloning steps. This modular cloning (MoClo) system can be readily automated and will be extremely useful for applications such as gene stacking and metabolic engineering.
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33
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Weber E, Engler C, Gruetzner R, Werner S, Marillonnet S. A modular cloning system for standardized assembly of multigene constructs. PLoS One 2011. [PMID: 21364738 DOI: 10.1371/journal.pone.016765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023] Open
Abstract
The field of synthetic biology promises to revolutionize biotechnology through the design of organisms with novel phenotypes useful for medicine, agriculture and industry. However, a limiting factor is the ability of current methods to assemble complex DNA molecules encoding multiple genetic elements in various predefined arrangements. We present here a hierarchical modular cloning system that allows the creation at will and with high efficiency of any eukaryotic multigene construct, starting from libraries of defined and validated basic modules containing regulatory and coding sequences. This system is based on the ability of type IIS restriction enzymes to assemble multiple DNA fragments in a defined linear order. We constructed a 33 kb DNA molecule containing 11 transcription units made from 44 individual basic modules in only three successive cloning steps. This modular cloning (MoClo) system can be readily automated and will be extremely useful for applications such as gene stacking and metabolic engineering.
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Clancy K, Voigt CA. Programming cells: towards an automated 'Genetic Compiler'. Curr Opin Biotechnol 2010; 21:572-81. [PMID: 20702081 PMCID: PMC2950163 DOI: 10.1016/j.copbio.2010.07.005] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2010] [Accepted: 07/08/2010] [Indexed: 10/19/2022]
Abstract
One of the visions of synthetic biology is to be able to program cells using a language that is similar to that used to program computers or robotics. For large genetic programs, keeping track of the DNA on the level of nucleotides becomes tedious and error prone, requiring a new generation of computer-aided design (CAD) software. To push the size of projects, it is important to abstract the designer from the process of part selection and optimization. The vision is to specify genetic programs in a higher-level language, which a genetic compiler could automatically convert into a DNA sequence. Steps towards this goal include: defining the semantics of the higher-level language, algorithms to select and assemble parts, and biophysical methods to link DNA sequence to function. These will be coupled to graphic design interfaces and simulation packages to aid in the prediction of program dynamics, optimize genes, and scan projects for errors.
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Affiliation(s)
- Kevin Clancy
- Life Technologies, 5791 Van Allen Way, Carlsbad, CA, 90028
| | - Christopher A. Voigt
- Department of Pharmaceutical Chemistry, University of California-San Francisco, MC 2540, Room 408C, 1700 4 Street, San Francisco, CA 94158
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Rialle S, Felicori L, Dias-Lopes C, Pérès S, El Atia S, Thierry AR, Amar P, Molina F. BioNetCAD: design, simulation and experimental validation of synthetic biochemical networks. ACTA ACUST UNITED AC 2010; 26:2298-304. [PMID: 20628073 PMCID: PMC2935418 DOI: 10.1093/bioinformatics/btq409] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
MOTIVATION Synthetic biology studies how to design and construct biological systems with functions that do not exist in nature. Biochemical networks, although easier to control, have been used less frequently than genetic networks as a base to build a synthetic system. To date, no clear engineering principles exist to design such cell-free biochemical networks. RESULTS We describe a methodology for the construction of synthetic biochemical networks based on three main steps: design, simulation and experimental validation. We developed BioNetCAD to help users to go through these steps. BioNetCAD allows designing abstract networks that can be implemented thanks to CompuBioTicDB, a database of parts for synthetic biology. BioNetCAD enables also simulations with the HSim software and the classical Ordinary Differential Equations (ODE). We demonstrate with a case study that BioNetCAD can rationalize and reduce further experimental validation during the construction of a biochemical network. AVAILABILITY AND IMPLEMENTATION BioNetCAD is freely available at http://www.sysdiag.cnrs.fr/BioNetCAD. It is implemented in Java and supported on MS Windows. CompuBioTicDB is freely accessible at http://compubiotic.sysdiag.cnrs.fr/.
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Affiliation(s)
- Stéphanie Rialle
- SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France.
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