Highly-automated, high-throughput replication of yeast-based logic circuit design assessments.

We describe an experimental campaign that replicated the performance assessment of logic gates engineered into cells of Saccharomyces cerevisiae by Gander et al. Our experimental campaign used a novel high-throughput experimentation framework developed under Defense Advanced Research Projects Agency's Synergistic Discovery and Design program: a remote robotic lab at Strateos executed a parameterized experimental protocol. Using this protocol and robotic execution, we generated two orders of magnitude more flow cytometry data than the original experiments. We discuss our results, which largely, but not completely, agree with the original report and make some remarks about lessons learned. Graphical Abstract.

Synthetic biology open language visual (SBOL Visual) version 2.3.

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.3 of SBOL Visual, which builds on the prior SBOL Visual 2.2 in several ways. First, the specification now includes higher-level "interactions with interactions," such as an inducer molecule stimulating a repression interaction. Second, binding with a nucleic acid backbone can be shown by overlapping glyphs, as with other molecular complexes. Finally, a new "unspecified interaction" glyph is added for visualizing interactions whose nature is unknown, the "insulator" glyph is deprecated in favor of a new "inert DNA spacer" glyph, and the polypeptide region glyph is recommended for showing 2A sequences.

Synthetic biology open language visual (SBOL visual) version 2.2.

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.2 of SBOL Visual, which builds on the prior SBOL Visual 2.1 in several ways. First, the grounding of molecular species glyphs is changed from BioPAX to SBO, aligning with the use of SBO terms for interaction glyphs. Second, new glyphs are added for proteins, introns, and polypeptide regions (e. g., protein domains), the prior recommended macromolecule glyph is deprecated in favor of its alternative, and small polygons are introduced as alternative glyphs for simple chemicals.

Extending SynBioHub's Functionality with Plugins.

SynBioHub is a repository for synthetic genetic designs represented in the Synthetic Biology Open Language (SBOL). To integrate SynBioHub into more synthetic biology workflows, its data processing capabilities need to be expanded. To this end, a plugin interface has been developed. Plugins can be developed for data submission, visualization, and download. This framework was tested by the development of three example plugins, one of each type as follows: one allowing the submission of SnapGene files, one visualizing the course of different genetic parts, and one preparing plasmid maps for download.

SBOLExplorer: Data Infrastructure and Data Mining for Genetic Design Repositories.

This paper describes SBOLExplorer, a system that is used to provide intuitive searching within the SynBioHub genetic design repository. SynBioHub stores genetic constructs encoded in the SBOL data format. These constructs can represent genetic parts, circuits, and sequences. These constructs are often numerous, exist in various states of completeness and documentation, and do not lend themselves to simple searching and discovery. In particular, this paper focuses on improving the search capabilities of SynBioHub. Inspiration is drawn from the techniques used to organize and search over the World Wide Web, a linked data set with many of the same properties of the SBOL data in SynBioHub. SBOLExplorer integrates these methods into SynBioHub's data representation and search, providing significant improvement over the previous search implementation based on pattern-matching.

Communicating Structure and Function in Synthetic Biology Diagrams.

Biological engineers often find it useful to communicate using diagrams. These diagrams can include information both about the structure of the nucleic acid sequences they are engineering and about the functional relationships between features of these sequences and/or other molecular species. A number of conventions and practices have begun to emerge within synthetic biology for creating such diagrams, and the Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard to organize, systematize, and extend such conventions in order to produce a coherent visual language. Here, we describe SBOL Visual version 2, which expands previous diagram standards to include new functional interactions, categories of molecular species, support for families of glyph variants, and the ability to indicate modular structure and mappings between elements of a system. SBOL Visual 2 also clarifies a number of requirements and best practices, significantly expands the collection of glyphs available to describe genetic features, and can be readily applied using a wide variety of software tools, both general and bespoke.

Specifying Combinatorial Designs with the Synthetic Biology Open Language (SBOL).

As improvements in DNA synthesis technology and assembly methods make combinatorial assembly of genetic constructs increasingly accessible, methods for representing genetic constructs likewise need to improve to handle the exponential growth of combinatorial design space. To this end, we present a community accepted extension of the SBOL data standard that allows for the efficient and flexible encoding of combinatorial designs. This extension includes data structures for representing genetic designs with "variable" components that can be implemented by choosing one of many linked designs for existing genetic parts or constructs. We demonstrate the representational power of the SBOL combinatorial design extension through case studies on metabolic pathway design and genetic circuit design, and we report the expansion of the SBOLDesigner software tool to support users in creating and modifying combinatorial designs in SBOL.

Synthetic Biology Open Language Visual (SBOL Visual) Version 2.1.

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species . Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.1 of SBOL Visual, which builds on the prior SBOL Visual 2.0 standard by expanding diagram syntax to include methods for showing modular structure and mappings between elements of a system, interactions arrows that can split or join (with the glyph at the split or join indicating either superposition or a chemical process), and adding new glyphs for indicating genomic context (e.g., integration into a plasmid or genome) and for stop codons.

Synthetic Biology Open Language (SBOL) Version 2.3.

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems is to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.3.0 of SBOL, which builds upon version 2.2.0 published in last year's JIB Standards in Systems Biology special issue. In particular, SBOL 2.3.0 includes means of succinctly representing sequence modifications, such as insertion, deletion, and replacement, an extension to support organization and attachment of experimental data derived from designs, and an extension for describing numerical parameters of design elements. The new version also includes specifying types of synthetic biology activities, unambiguous locations for sequences with multiple encodings, refinement of a number of validation rules, improved figures and examples, and clarification on a number of issues related to the use of external ontology terms.

pySBOL: A Python Package for Genetic Design Automation and Standardization.

This paper presents pySBOL, a software library for computer-aided design of synthetic biological systems in the Python scripting language. This library provides an easy-to-use, object-oriented, application programming interface (API) with low barrier of entry for synthetic biology application developers. The pySBOL library enables reuse of genetic parts and designs through standardized data exchange with biological parts repositories and software tools that communicate using the Synthetic Biology Open Language (SBOL). In addition, pySBOL supports data management of design-build-test-learn workflows for individual laboratories as well as large, distributed teams of synthetic biologists. PySBOL also lets users add custom data to SBOL files to support the specific data requirements of their research. This extensibility helps users integrate software tool chains and develop workflows for new applications. These features and others make the pySBOL library a valuable tool for supporting engineering practices in synthetic biology. Documentation and installation instructions can be found at pysbol2.readthedocs.io .

sboljs: Bringing the Synthetic Biology Open Language to the Web Browser.

The Synthetic Biology Open Language (SBOL) is a data standard for the representation of engineered biological systems. SBOL is implemented in the form of software libraries which can be used to add SBOL support to both new and existing software tools. While existing libraries allow for software to be developed that runs on a server or is installed locally, they lack the capability to create SBOL software that runs directly in a Web browser. Here, we address this issue by presenting sboljs, a JavaScript software library for SBOL that is capable of being used both on the server and in the Web browser.

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

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 analysis, and design synthesis, all of which can be used in a workflow for the systematic construction of new genetic circuits.

Synthetic Biology Open Language (SBOL) Version 2.2.0.

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year's JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.

Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0.

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.0 of SBOL Visual, which builds on the prior SBOL Visual 1.0 standard by expanding diagram syntax to include functional interactions and molecular species, making the relationship between diagrams and the SBOL data model explicit, supporting families of symbol variants, clarifying a number of requirements and best practices, and significantly expanding the collection of diagram glyphs.

SynBioHub: A Standards-Enabled Design Repository for Synthetic Biology.

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.

A standard-enabled workflow for synthetic biology.

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications.

A Validator and Converter for the Synthetic Biology Open Language.

This paper presents a new validation and conversion utility for the Synthetic Biology Open Language (SBOL). This utility can be accessed directly in software using the libSBOLj library, through a web interface, or using a web service via RESTful API calls. The validator checks all required and best practice rules set forth in the SBOL specification document, and it reports back to the user the location within the document of any errors found. The converter is capable of translating from/to SBOL 1, GenBank, and FASTA formats to/from SBOL 2. The SBOL Validator/Converter utility is released freely and open source under the Apache 2.0 license. The online version of the validator/converter utility can be found here: http://www.async.ece.utah.edu/sbol-validator/ . The source code for the validator/converter can be found here: http://github.com/SynBioDex/SBOL-Validator/ .

Sharing Structure and Function in Biological Design with SBOL 2.0.

The Synthetic Biology Open Language (SBOL) is a standard that enables collaborative engineering of biological systems across different institutions and tools. SBOL is developed through careful consideration of recent synthetic biology trends, real use cases, and consensus among leading researchers in the field and members of commercial biotechnology enterprises. We demonstrate and discuss how a set of SBOL-enabled software tools can form an integrated, cross-organizational workflow to recapitulate the design of one of the largest published genetic circuits to date, a 4-input AND sensor. This design encompasses the structural components of the system, such as its DNA, RNA, small molecules, and proteins, as well as the interactions between these components that determine the system's behavior/function. The demonstrated workflow and resulting circuit design illustrate the utility of SBOL 2.0 in automating the exchange of structural and functional specifications for genetic parts, devices, and the biological systems in which they operate.

Synthetic Biology Open Language (SBOL) Version 2.1.0.

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.1 of SBOL that builds upon version 2.0 published in last year’s JIB special issue. In particular, SBOL 2.1 includes improved rules for what constitutes a valid SBOL document, new role fields to simplify the expression of sequence features and how components are used in context, and new best practices descriptions to improve the exchange of basic sequence topology information and the description of genetic design provenance, as well as miscellaneous other minor improvements.

A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.

Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.