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Mısırlı G. libSBOLj3: a graph-based library for design and data exchange in synthetic biology. Bioinformatics 2023; 39:btad525. [PMID: 37624918 PMCID: PMC10471897 DOI: 10.1093/bioinformatics/btad525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/14/2023] [Accepted: 08/23/2023] [Indexed: 08/27/2023] Open
Abstract
SUMMARY The Synthetic Biology Open Language version 3 data standard provides a graph-based approach to exchange information about biological designs. The new data model has major updates and offers several features for software tools. Here, we present libSBOLj3 to facilitate data exchange and provide interoperability between computer-aided design and automation tools using this standard. The library adopts a graph-based approach. Tool developers can extend these graphs with application-specific information and use detailed validation reports to identify errors and interoperability issues and apply best practice rules. AVAILABILITY AND IMPLEMENTATION The libSBOLj3 library is implemented in Java and can be downloaded or used as a Maven dependency. The open-source project, code examples and documentation about accessing and using the library are available via GitHub at https://github.com/SynBioDex/libSBOLj3.
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Affiliation(s)
- Göksel Mısırlı
- School of Computer Science and Mathematics, Keele University, Keele, Staffordshire, ST5 5BG, United Kingdom
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Mısırlı G, Yang B, James K, Wipat A. Virtual Parts Repository 2: Model-Driven Design of Genetic Regulatory Circuits. ACS Synth Biol 2021; 10:3304-3315. [PMID: 34762797 DOI: 10.1021/acssynbio.1c00157] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Engineering genetic regulatory circuits is key to the creation of biological applications that are responsive to environmental changes. Computational models can assist in understanding especially large and complex circuits for which manual analysis is infeasible, permitting a model-driven design process. However, there are still few tools that offer the ability to simulate the system under design. One of the reasons for this is the lack of accessible model repositories or libraries that cater to the modular composition of models of synthetic systems. Here, we present the second version of the Virtual Parts Repository, a framework to facilitate the model-driven design of genetic regulatory circuits, which provides reusable, modular, and composable models. The new framework is service-oriented, easier to use in computational workflows, and provides several new features and access methods. New features include supporting hierarchical designs via a graph-based repository or compatible remote repositories, enriching existing designs, and using designs provided in Synthetic Biology Open Language documents to derive system-scale and hierarchical Systems Biology Markup Language models. We also present a reaction-based modeling abstraction inspired by rule-based modeling techniques to facilitate scalable and modular modeling of complex and large designs. This modeling abstraction enhances the modeling capability of the framework, for example, to incorporate design patterns such as roadblocking, distributed deployment of genetic circuits using plasmids, and cellular resource dependency. The framework and the modeling abstraction presented in this paper allow computational design tools to take advantage of computational simulations and ultimately help facilitate more predictable applications.
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Affiliation(s)
- Göksel Mısırlı
- School of Computing and Mathematics, Keele University, Keele, ST5 5BG, U.K
| | - Bill Yang
- School of Computing, Newcastle University, Newcastle upon Tyne, NE4 5TG, U.K
| | - Katherine James
- Department of Applied Sciences, Northumbria University, Newcastle upon Tyne, NE1 8ST, U.K
| | - Anil Wipat
- School of Computing, Newcastle University, Newcastle upon Tyne, NE4 5TG, U.K
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Misirli G, Nguyen T, McLaughlin JA, Vaidyanathan P, Jones TS, Densmore D, Myers C, Wipat A. A Computational Workflow for the Automated Generation of Models of Genetic Designs. ACS Synth Biol 2019; 8:1548-1559. [PMID: 29782151 DOI: 10.1021/acssynbio.7b00459] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Computational models are essential to engineer predictable biological 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 standards. This workflow leverages the software tool SBOLDesigner to build structural models that are then enriched by the Virtual Parts Repository API using Systems Biology 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 Biology 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 biological 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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Affiliation(s)
- Göksel Misirli
- School of Computing and Mathematics, Keele University, Staffordshire, U.K
| | - Tramy Nguyen
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah 84112, United States
| | | | - Prashant Vaidyanathan
- Department of Electrical and Computer Engineering Boston University, Boston, Massachusetts 02215, United States
| | - Timothy S. Jones
- Department of Electrical and Computer Engineering Boston University, Boston, Massachusetts 02215, United States
| | - Douglas Densmore
- Department of Electrical and Computer Engineering Boston University, Boston, Massachusetts 02215, United States
| | - Chris Myers
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah 84112, United States
| | - Anil Wipat
- ICOS, School of Computing, Newcastle University, Newcastle upon Tyne, U.K
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Hallinan JS, Wipat A, Kitney R, Woods S, Taylor K, Goñi‐Moreno A. Future‐proofing synthetic biology: educating the next generation. ENGINEERING BIOLOGY 2019. [DOI: 10.1049/enb.2019.0001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Affiliation(s)
| | - Anil Wipat
- School of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Richard Kitney
- Department of BioengineeringImperial College LondonLondonUK
| | - Simon Woods
- Policy, Ethics and Life Sciences (PEALS) Research CentreNewcastle UniversityNewcastle upon TyneUK
| | - Ken Taylor
- Policy, Ethics and Life Sciences (PEALS) Research CentreNewcastle UniversityNewcastle upon TyneUK
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Scher E, Cohen SB, Sanguinetti G. PartCrafter: find, generate and analyze BioParts. Synth Biol (Oxf) 2019; 4:ysz014. [PMID: 32995539 PMCID: PMC7445878 DOI: 10.1093/synbio/ysz014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Revised: 05/14/2019] [Accepted: 05/22/2019] [Indexed: 06/11/2023] Open
Abstract
The field of Synthetic Biology is both practically and philosophically reliant on the idea of BioParts-concrete DNA sequences meant to represent discrete functionalities. While there are a number of software tools which allow users to design complex DNA sequences by stitching together BioParts or genetic features into genetic devices, there is a lack of tools assisting Synthetic Biologists in finding BioParts and in generating new ones. In practice, researchers often find BioParts in an ad hoc way. We present PartCrafter, a tool which extracts and aggregates genomic feature data in order to facilitate the search for new BioParts with specific functionalities. PartCrafter can also turn a genomic feature into a BioPart by packaging it according to any manufacturing standard, codon optimizing it for a new host, and removing forbidden sites. PartCrafter is available at partcrafter.com.
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Affiliation(s)
- Emily Scher
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | - Shay B Cohen
- School of Informatics, University of Edinburgh, Edinburgh, UK
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McLaughlin JA, Myers CJ, Zundel Z, Mısırlı G, Zhang M, Ofiteru ID, Goñi-Moreno A, Wipat A. SynBioHub: A Standards-Enabled Design Repository for Synthetic Biology. ACS Synth Biol 2018; 7:682-688. [PMID: 29316788 DOI: 10.1021/acssynbio.7b00403] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The SynBioHub repository ( https://synbiohub.org ) is an open-source software project that facilitates the sharing of information about engineered biological systems. SynBioHub provides computational access for software and data integration, and a graphical user interface that enables users to search for and share designs in a Web browser. By connecting to relevant repositories (e.g., the iGEM repository, JBEI ICE, and other instances of SynBioHub), the software allows users to browse, upload, and download data in various standard formats, regardless of their location or representation. SynBioHub also provides a central reference point for other resources to link to, delivering design information in a standardized format using the Synthetic Biology Open Language (SBOL). The adoption and use of SynBioHub, a community-driven effort, has the potential to overcome the reproducibility challenge across laboratories by helping to address the current lack of information about published designs.
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Affiliation(s)
| | - Chris J. Myers
- Department
of Electrical and Computer Engineering, University of Utah, Salt Lake
City, Utah 84112, United States
| | - Zach Zundel
- Department
of Electrical and Computer Engineering, University of Utah, Salt Lake
City, Utah 84112, United States
| | - Göksel Mısırlı
- School
of Computing and Mathematics, Keele University, Newcastle, ST5 5BG, U.K
| | - Michael Zhang
- Department
of Electrical and Computer Engineering, University of Utah, Salt Lake
City, Utah 84112, United States
| | - Irina Dana Ofiteru
- School
of Engineering, Newcastle University, Newcastle upon Tyne, NE1
7RU, U.K
| | - Angel Goñi-Moreno
- School
of Computing, Newcastle University, Newcastle upon Tyne, NE1
7RU, U.K
| | - Anil Wipat
- School
of Computing, Newcastle University, Newcastle upon Tyne, NE1
7RU, U.K
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