ABSTRACT
The glycosyltransferases (GTs) are an important and functionally diverse family of enzymes involved in glycan and glycoside biosynthesis. Plants have evolved large families of GTs which undertake the array of glycosylation reactions that occur during plant development and growth. Based on the Carbohydrate-Active enZymes (CAZy) database, the genome of the reference plant Arabidopsis thaliana codes for over 450 GTs, while the rice genome (Oryza sativa) contains over 600 members. Collectively, GTs from these reference plants can be classified into over 40 distinct GT families. Although these enzymes are involved in many important plant specific processes such as cell-wall and secondary metabolite biosynthesis, few have been functionally characterized. We have sought to develop a plant GTs clone resource that will enable functional genomic approaches to be undertaken by the plant research community. In total, 403 (88%) of CAZy defined Arabidopsis GTs have been cloned, while 96 (15%) of the GTs coded by rice have been cloned. The collection resulted in the update of a number of Arabidopsis GT gene models. The clones represent full-length coding sequences without termination codons and are Gateway® compatible. To demonstrate the utility of this JBEI GT Collection, a set of efficient particle bombardment plasmids (pBullet) was also constructed with markers for the endomembrane. The utility of the pBullet collection was demonstrated by localizing all members of the Arabidopsis GT14 family to the Golgi apparatus or the endoplasmic reticulum (ER). Updates to these resources are available at the JBEI GT Collection website http://www.addgene.org/.
Subject(s)
Genomics , Glycosyltransferases/metabolism , Arabidopsis/enzymology , Arabidopsis/genetics , Arabidopsis/metabolism , Cell Wall/metabolismABSTRACT
The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about 'legacy' parts, such as plasmids, microbial host strains and Arabidopsis seeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code, a hosting site for community-driven open source projects.
Subject(s)
Registries , Software , Synthetic Biology , Arabidopsis/embryology , Internet , Plasmids , Seeds , Sequence Analysis, DNA , User-Computer InterfaceABSTRACT
Capturing, storing, and sharing biological DNA parts data are integral parts of synthetic biology research. Here, we detail updates to the ICE biological parts registry software platform that enable these processes, describe our implementation of the Web of Registries concept using ICE, and establish Bioparts, a search portal for biological parts available in the public domain. The Web of Registries enables standalone ICE installations to securely connect and form a distributed parts database. This distributed database allows users from one registry to query and access plasmid, strain, (DNA) part, plant seed, and protein entry types in other connected registries. Users can also transfer entries from one ICE registry to another or make them publicly accessible. Bioparts, the new search portal, combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically.
Subject(s)
Software , Synthetic Biology/methods , Computational Biology , Databases, FactualABSTRACT
Biology has changed radically in the past two decades, growing from a purely descriptive science into also a design science. The availability of tools that enable the precise modification of cells, as well as the ability to collect large amounts of multimodal data, open the possibility of sophisticated bioengineering to produce fuels, specialty and commodity chemicals, materials, and other renewable bioproducts. However, despite new tools and exponentially increasing data volumes, synthetic biology cannot yet fulfill its true potential due to our inability to predict the behavior of biological systems. Here, we showcase a set of computational tools that, combined, provide the ability to store, visualize, and leverage multiomics data to predict the outcome of bioengineering efforts. We show how to upload, visualize, and output multiomics data, as well as strain information, into online repositories for several isoprenol-producing strain designs. We then use these data to train machine learning algorithms that recommend new strain designs that are correctly predicted to improve isoprenol production by 23%. This demonstration is done by using synthetic data, as provided by a novel library, that can produce credible multiomics data for testing algorithms and computational tools. In short, this paper provides a step-by-step tutorial to leverage these computational tools to improve production in bioengineered strains.
ABSTRACT
Biological computer-aided design and manufacturing (bioCAD/CAM) tools facilitate the design and build processes of engineering biological systems using iterative design-build-test-learn (DBTL) cycles. In this book chapter, we highlight some of the bioCAD/CAM tools developed and used at the US Department of Energy (DOE) Joint Genome Institute (JGI), Joint BioEnergy Institute (JBEI), and Agile BioFoundry (ABF). We demonstrate the use of these bioCAD/CAM tools on a common workflow for designing and building a multigene pathway in a hierarchical fashion. Each tool presented in this book chapter is specifically tailored to support one or more specific steps in a workflow, can be integrated with the others into design and build workflows, and can be deployed at academic, government, or commercial entities.
Subject(s)
Synthetic Biology/methods , Computer-Aided Design , Software , WorkflowABSTRACT
Research is communicated more effectively and reproducibly when articles depict genetic designs consistently and fully disclose the complete sequences of all reported constructs. ACS Synthetic Biology is now providing authors with updated guidance and piloting a new tool and publication workflow that facilitate compliance with these recommended practices and standards for visual representation and data exchange.
Subject(s)
Genetics/standards , Publishing/standards , Research/standards , Sequence Analysis/standards , Synthetic Biology/standards , Humans , WorkflowABSTRACT
The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. Here we describe the Synthetic Biology Open Language (SBOL), a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-driven, formalized format for exchange between software tools, research groups and commercial 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 standard, SBOL will be updated as synthetic biology evolves to provide specific capabilities for different aspects of the synthetic biology workflow.