Kevin Clancy

Characterization of 582 natural and synthetic terminators and quantification of their design constraints

Large genetic engineering projects require more cistrons and consequently more strong and reliable transcriptional terminators. We have measured the strengths of a library of terminators, including 227 that are annotated in Escherichia coli—90 of which we also tested in the reverse orientation—and 265 synthetic terminators. Within this library we found 39 strong terminators, yielding >50-fold reduction in downstream expression, that have sufficient sequence diversity to reduce homologous recombination when used together in a design. We used these data to determine how the terminator sequence contributes to its strength. The dominant parameters were incorporated into a biophysical model that considers the role of the hairpin in the displacement of the U-tract from the DNA. The availability of many terminators of varying strength, as well as an understanding of the sequence dependence of their properties, will extend their usability in the forward design of synthetic cistrons.

Genomic mining of prokaryotic repressors for orthogonal logic gates

Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply “part mining” to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and do not interact with other promoters. Each repressor:promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOR gates, there are >1054 circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.

The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology

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.

Design of orthogonal genetic switches based on a crosstalk map of σs, anti‐σs, and promoters

Cells react to their environment through gene regulatory networks. Network integrity requires minimization of undesired crosstalk between their biomolecules. Similar constraints also limit the use of regulators when building synthetic circuits for engineering applications. Here, we mapped the promoter specificities of extracytoplasmic function (ECF) σs as well as the specificity of their interaction with anti‐σs. DNA synthesis was used to build 86 ECF σs (two from every subgroup), their promoters, and 62 anti‐σs identified from the genomes of diverse bacteria. A subset of 20 σs and promoters were found to be highly orthogonal to each other. This set can be increased by combining the −35 and −10 binding domains from different subgroups to build chimeras that target sequences unrepresented in any subgroup. The orthogonal σs, anti‐σs, and promoters were used to build synthetic genetic switches in Escherichia coli. This represents a genome‐scale resource of the properties of ECF σs and a resource for synthetic biology, where this set of well‐characterized regulatory parts will enable the construction of sophisticated gene expression programs.

Programming cells: towards an automated 'Genetic Compiler'.

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.

Synthetic Biology Open Language (SBOL) Version 2.0.0.

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 2.0 of SBOL, introducing a standardized format for the electronic exchange of information on the structural and functional aspects of biological designs. The standard has been designed to support the explicit and unambiguous description of biological designs by means of a well defined data model. The standard also includes rules and best practices on how to use this data model and populate it with relevant design details. The publication of this specification is intended to make these capabilities more widely accessible to potential developers and users in the synthetic biology community and beyond.

The Ontology for Biomedical Investigations

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

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.

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 systems 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.

Systematic transfer of prokaryotic sensors and circuits to mammalian cells.

Prokaryotic regulatory proteins respond to diverse signals and represent a rich resource for building synthetic sensors and circuits. The TetR family contains >105 members that use a simple mechanism to respond to stimuli and bind distinct DNA operators. We present a platform that enables the transfer of these regulators to mammalian cells, which is demonstrated using human embryonic kidney (HEK293) and Chinese hamster ovary (CHO) cells. The repressors are modified to include nuclear localization signals (NLS) and responsive promoters are built by incorporating multiple operators. Activators are also constructed by modifying the protein to include a VP16 domain. Together, this approach yields 15 new regulators that demonstrate 19- to 551-fold induction and retain both the low levels of crosstalk in DNA binding specificity observed between the parent regulators in Escherichia coli, as well as their dynamic range of activity. By taking advantage of the DAPG small molecule sensing mediated by the PhlF repressor, we introduce a new inducible system with 50-fold induction and a threshold of 0.9 μM DAPG, which is comparable to the classic Dox-induced TetR system. A set of NOT gates is constructed from the new repressors and their response function quantified. Finally, the Dox- and DAPG- inducible systems and two new activators are used to build a synthetic enhancer (fuzzy AND gate), requiring the coordination of 5 transcription factors organized into two layers. This work introduces a generic approach for the development of mammalian genetic sensors and circuits to populate a toolbox that can be applied to diverse applications from biomanufacturing to living therapeutics.