Knowledge Representation in Synthetic Biology

PhD ThesisSynthetic biology, or SynBio, is a relatively new and exciting field concerning the formalisation of genetic engineering into a design, build, test, learn lifecycle common to other engineering disciplines. This lifecycle can be used to systematically develop biological systems, such as synthetic genetic circuits — where transcriptional machinery is repurposed to construct familiar electronic circuit concepts such as logic gates — and other engineered devices such as biosensors or drug production factories. Synthetic biological systems are typically designed by repurposing existing natural and synthetic biological parts. This design process is made possible by knowledge about part structure and function, which can be experimentally derived or predicted using bioinformatics methodologies. However, the process of gathering such knowledge is arduous, as it is often computationally intractable, distributed across multiple disparate databases with semantic and syntactic heterogeneity, or even not recorded at all. The research question motivating this work is how the machine-tractability of knowledge can be improved in order to make the synthetic biology design process more efficient. There are both short-term and long-term approaches. The short-term approach is to improve the ease of access and machine-tractability of existing knowledge relevant to SynBio design. The long-term approach is to establish the software and data infrastructure necessary to enable knowledge about future designs to be documented in a standardized manner. This work investigates both approaches with research into data standards, significantly furthering the development of the Synthetic Biology Open Language (SBOL) to improve the machine-tractability of design knowledge; the research and development of novel technology for data integration to make existing information easier to access; conversion of an existing dataset, the iGEM Registry, into an enriched SBOL representation; the development of SynBioHub, a repository for the sharing and dissemination of future SynBio designs; and SynBioCAD, a visual tool enabling synthetic biologists to capture their designs using data standards

Capturing Multicellular System Designs Using Synthetic Biology Open Language (SBOL)

8 Pág.Synthetic biology aims to develop novel biological systems and increase their reproducibility using engineering principles such as standardization and modularization. It is important that these systems can be represented and shared in a standard way to ensure they can be easily understood, reproduced, and utilized by other researchers. The Synthetic Biology Open Language (SBOL) is a data standard for sharing biological designs and information about their implementation and characterization. Previously, this standard has only been used to represent designs in systems where the same design is implemented in every cell; however, there is also much interest in multicellular systems, in which designs involve a mixture of different types of cells with differing genotype and phenotype. Here, we show how the SBOL standard can be used to represent multicellular systems, and, hence, how researchers can better share designs with the community and reliably document intended system functionality.This work was supported in part by NSF Expeditions in Computing Program Award No. 1522074 as part of the Living Computing Project and by the Defense Advanced Research Projects Agency under Contract No. W911NF-17-2-0098. The views, opinions, and/or findings expressed are of the author(s) and should not be interpreted as representing official views or policies of the Department of Defense or the U.S. Government. A.G.-M. was supported by the SynBio3D project of the UK Engineering and Physical Sciences Research Council (No.EP/R019002/1) and the European CSA on biological standardization BIOROBOOST (EU Grant No. 820699)Peer reviewe

Synthetic biology open language (SBOL) version 3.0.0

Synthetic biology builds upon genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. When designing a synthetic system, synthetic biologists need to exchange information about multiple types of molecules, the intended behavior of the system, and actual experimental measurements. 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, following an open community process involving both wet bench scientists and dry scientific modelers and software developers, across academia, industry, and other institutions. This document describes SBOL 3.0.0, which condenses and simplifies previous versions of SBOL based on experiences in deployment across a variety of scientific and industrial settings. In particular, SBOL 3.0.0, (1) separates sequence features from part/sub-part relationships, (2) renames Component Definition/Component to Component/Sub-Component, (3) merges Component and Module classes, (4) ensures consistency between data model and ontology terms, (5) extends the means to define and reference Sub-Components, (6) refines requirements on object URIs, (7) enables graph-based serialization, (8) moves Systems Biology Ontology (SBO) for Component types, (9) makes all sequence associations explicit, (10) makes interfaces explicit, (11) generalizes Sequence Constraints into a general structural Constraint class, and (12) expands the set of allowed constraints

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

SBOL Visual: A Graphical Language for Genetic Designs

Synthetic Biology Open Language (SBOL) Visual is a graphical standard for genetic engineering. It consists of symbols representing DNA subsequences, including regulatory elements and DNA assembly features. These symbols can be used to draw illustrations for communication and instruction, and as image assets for computer-aided design. SBOL Visual is a community standard, freely available for personal, academic, and commercial use (Creative Commons CC0 license). We provide prototypical symbol images that have been used in scientific publications and software tools. We encourage users to use and modify them freely, and to join the SBOL Visual community: http://www.sbolstandard.org/visual

Data integration and mining for synthetic biology design

One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterised parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterise biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread amongst these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single dataset, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modelling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.12 page(s

A Visual Language for Protein Design

As protein engineering becomes more sophisticated, practitioners increasingly need to share diagrams for communicating protein designs. To this end, we present a draft visual language, Protein Language, that describes the high-level architecture of an engineered protein with easy-to-draw glyphs, intended to be compatible with other biological diagram languages such as SBOL Visual and SBGN. Protein Language consists of glyphs for representing important features (<i>e.g.</i>, globular domains, recognition and localization sequences, sites of covalent modification, cleavage and catalysis), rules for composing these glyphs to represent complex architectures, and rules constraining the scaling and styling of diagrams. To support Protein Language we have implemented an extensible web-based software diagram tool, Protein Designer, that uses Protein Language in a “drag and drop” interface for visualization and computer-aided-design of engineered proteins, as well as conversion of annotated protein sequences to Protein Language diagrams and figure export. Protein Designer can be accessed at http://biocad.ncl.ac.uk/protein-designer/

A Visual Language for Protein Design

As protein engineering becomes more sophisticated, practitioners increasingly need to share diagrams for communicating protein designs. To this end, we present a draft visual language, Protein Language, that describes the high-level architecture of an engineered protein with easy-to-draw glyphs, intended to be compatible with other biological diagram languages such as SBOL Visual and SBGN. Protein Language consists of glyphs for representing important features (<i>e.g.</i>, globular domains, recognition and localization sequences, sites of covalent modification, cleavage and catalysis), rules for composing these glyphs to represent complex architectures, and rules constraining the scaling and styling of diagrams. To support Protein Language we have implemented an extensible web-based software diagram tool, Protein Designer, that uses Protein Language in a “drag and drop” interface for visualization and computer-aided-design of engineered proteins, as well as conversion of annotated protein sequences to Protein Language diagrams and figure export. Protein Designer can be accessed at http://biocad.ncl.ac.uk/protein-designer/