SBOL Visual: A Graphical Language for Genetic Designs

A tuneable genetic switch for tight control of tac promoters in Escherichia coli boosts expression of synthetic injectisomes

Biosafety of engineered bacteria as living therapeutics requires a tight regulation to control the specific delivery of protein effectors, maintaining minimum leakiness in the uninduced (OFF) state and efficient expression in the induced (ON) state. Here, we report a three repressors (3R) genetic circuit that tightly regulates the expression of multiple tac promoters (Ptac) integrated in the chromosome of E. coli and drives the expression of a complex type III secretion system injectisome for therapeutic protein delivery. The 3R genetic switch is based on the tetracycline repressor (TetR), the non-inducible lambda repressor cI (ind-) and a mutant lac repressor (LacIW220F ) with higher activity. The 3R switch was optimized with different protein translation and degradation signals that control the levels of LacIW220F . We demonstrate the ability of an optimized switch to fully repress the strong leakiness of the Ptac promoters in the OFF state while triggering their efficient activation in the ON state with anhydrotetracycline (aTc), an inducer suitable for in vivo use. The implementation of the optimized 3R switch in the engineered synthetic injector E. coli (SIEC) strain boosts expression of injectisomes upon aTc induction, while maintaining a silent OFF state that preserves normal growth in the absence of the inducer. Since Ptac is a commonly used promoter, the 3R switch may have multiple applications for tight control of protein expression in E. coli. In addition, the modularity of the 3R switch may enable its tuning for the control of Ptac promoters with different inducers.

Automated Platform for the Plasmid Construction Process

There is a growing need for applications capable of handling large synthesis biology experiments. At the core of synthetic biology is the process of cloning and manipulating DNA as plasmids. Here, we report the development of an application named DNAda capable of writing automation instructions for any given DNA construct design generated by the J5 DNA assembly program. We also describe the automation pipeline and several useful features. The pipeline is particularly useful for the construction of combinatorial DNA assemblies. Furthermore, we demonstrate the platform by constructing a library of polyketide synthase parts, which includes 120 plasmids ranging in size from 7 to 14 kb from 4 to 7 DNA fragments.

Optimization of CRISPR-Cas system for clinical cancer therapy

Cancer is a genetic disease caused by alterations in genome and epigenome and is one of the leading causes for death worldwide. The exploration of disease development and therapeutic strategies at the genetic level have become the key to the treatment of cancer and other genetic diseases. The functional analysis of genes and mutations has been slow and laborious. Therefore, there is an urgent need for alternative approaches to improve the current status of cancer research. Gene editing technologies provide technical support for efficient gene disruption and modification in vivo and in vitro, in particular the use of clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems. Currently, the applications of CRISPR-Cas systems in cancer rely on different Cas effector proteins and the design of guide RNAs. Furthermore, effective vector delivery must be met for the CRISPR-Cas systems to enter human clinical trials. In this review article, we describe the mechanism of the CRISPR-Cas systems and highlight the applications of class II Cas effector proteins. We also propose a synthetic biology approach to modify the CRISPR-Cas systems, and summarize various delivery approaches facilitating the clinical application of the CRISPR-Cas systems. By modifying the CRISPR-Cas system and optimizing its in vivo delivery, promising and effective treatments for cancers using the CRISPR-Cas system are emerging.

Engineering genetic circuits: advancements in genetic design automation tools and standards for synthetic biology

Synthetic biology (SynBio) is a field at the intersection of biology and engineering. Inspired by engineering principles, researchers use defined parts to build functionally defined biological circuits. Genetic design automation (GDA) allows scientists to design, model, and analyze their genetic circuits in silico before building them in the lab, saving time, and resources in the process. Establishing SynBio's future is dependent on GDA, since the computational approach opens the field to a broad, interdisciplinary community. However, challenges with part libraries, standards, and software tools are currently stalling progress in the field. This review first covers recent advancements in GDA, followed by an assessment of the challenges ahead, and a proposed automated genetic design workflow for the future.

Tyto: A Python Tool Enabling Better Annotation Practices for Synthetic Biology Data-Sharing

As synthetic biology becomes increasingly automated and data-driven, tools that help researchers implement FAIR (findable-accessible-interoperable-reusable) data management practices are needed. Crucially, in order to support machine processing and reusability of data, it is important that data artifacts are appropriately annotated with metadata drawn from controlled vocabularies. Unfortunately, adopting standardized annotation practices is difficult for many research groups to adopt, given the set of specialized database science skills usually required to interface with ontologies. In response to this need, Take Your Terms from Ontologies (Tyto) is a lightweight Python tool that supports the use of controlled vocabularies in everyday scripting practice. While Tyto has been developed for synthetic biology applications, its utility may extend to users working in other areas of bioinformatics research as well. Tyto is available as a Python package distribution or available as source at https://github.com/SynBioDex/tyto.

EMMA-CAD: Design Automation for Synthetic Mammalian Constructs

Computational design tools are the cornerstone of synthetic biology and have underpinned its rapid development over the past two decades. As the field has matured, the scale of biological investigation has expanded dramatically, and researchers often must rely on computational tools to operate in the high-throughput investigational space. This is especially apparent in the modular design of DNA expression circuits, where complexity is accumulated rapidly. Alongside our automated pipeline for the high-throughput construction of Extensible Modular Mammalian Assembly (EMMA) expression vectors, we recognized the need for an integrated software solution for EMMA vector design. Here we present EMMA-CAD (https://emma.cailab.org), a powerful web-based computer-aided design tool for the rapid design of bespoke mammalian expression vectors. EMMA-CAD features a variety of functionalities, including a user-friendly design interface, automated connector selection underpinned by rigorous computer optimization algorithms, customization of part libraries, and personalized design spaces. Capable of translating vector assembly designs into human- and machine-readable protocols for vector construction, EMMA-CAD integrates seamlessly into our automated EMMA pipeline, hence completing an end-to-end design to production workflow.

Stochastic Hazard Analysis of Genetic Circuits in iBioSim and STAMINA

In synthetic biology, combinational circuits are used to program cells for various new applications like biosensors, drug delivery systems, and biofuels. Similar to asynchronous electronic circuits, some combinational genetic circuits may show unwanted switching variations (glitches) caused by multiple input changes. Depending on the biological circuit, glitches can cause irreversible effects and jeopardize the circuit's functionality. This paper presents a stochastic analysis to predict glitch propensities for three implementations of a genetic circuit with known glitching behavior. The analysis uses STochastic Approximate Model-checker for INfinite-state Analysis (STAMINA), a tool for stochastic verification. The STAMINA results were validated by comparison to stochastic simulation in iBioSim resulting in further improvements of STAMINA. This paper demonstrates that stochastic verification can be utilized by genetic designers to evaluate design choices and input restrictions to achieve a desired reliability of operation.

BioParts-A Biological Parts Search Portal and Updates to the ICE Parts Registry Software Platform

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.

Data sharing policies: share well and you shall be rewarded

Sharing research data is an integral part of the scientific publishing process. By sharing data, authors enable their readers to use their results in a way that the textual description of the results does not allow by itself. In order to achieve this objective, data should be shared in a way that makes it as easy as possible for readers to import them in computer software where they can be viewed, manipulated and analyzed. Many authors and reviewers seem to misunderstand the purpose of the data sharing policies developed by journals. Rather than being an administrative burden that authors should comply with to get published, the objective of these policies is to help authors maximize the impact of their work by allowing other members of the scientific community to build upon it. Authors and reviewers need to understand the purpose of data sharing policies to assist editors and publishers in their efforts to ensure that every article published complies with them.

Synthetic Biology in Plants, a Boon for Coming Decades

Recently an enormous expansion of knowledge is seen in various disciplines of science. This surge of information has given rise to concept of interdisciplinary fields, which has resulted in emergence of newer research domains, one of them is 'Synthetic Biology' (SynBio). It captures basics from core biology and integrates it with concepts from the other areas of study such as chemical, electrical, and computational sciences. The essence of synthetic biology is to rewire, re-program, and re-create natural biological pathways, which are carried through genetic circuits. A genetic circuit is a functional assembly of basic biological entities (DNA, RNA, proteins), created using typical design, built, and test cycles. These circuits allow scientists to engineer nearly all biological systems for various useful purposes. The development of sophisticated molecular tools, techniques, genomic programs, and ease of nucleic acid synthesis have further fueled several innovative application of synthetic biology in areas like molecular medicines, pharmaceuticals, biofuels, drug discovery, metabolomics, developing plant biosensors, utilization of prokaryotic systems for metabolite production, and CRISPR/Cas9 in the crop improvement. These applications have largely been dominated by utilization of prokaryotic systems. However, newer researches have indicated positive growth of SynBio for the eukaryotic systems as well. This paper explores advances of synthetic biology in the plant field by elaborating on its core components and potential applications. Here, we have given a comprehensive idea of designing, development, and utilization of synthetic biology in the improvement of the present research state of plant system.

VisBOL2-Improving Web-Based Visualization for Synthetic Biology Designs

VisBOL is a web-based visualization tool used to depict genetic circuit designs. This tool depicts simple DNA circuits adequately, but it has become increasingly outdated as new versions of SBOL Visual were released. This paper introduces VisBOL2, a heavily redesigned version of VisBOL that makes a number of improvements to the original VisBOL, including proper functional interaction rendering, dynamic viewing, a more maintainable code base, and modularity that facilitates compatibility with other software tools. This modularity is demonstrated by incorporating VisBOL2 into a sequence visualization plugin for SynBioHub.

Engineering and standardization of posttranscriptional biocircuitry in Saccharomyces cerevisiae

This short review considers to what extent posttranscriptional steps of gene expression can provide the basis for novel control mechanisms and procedures in synthetic biology and biotechnology. The term biocircuitry is used here to refer to functionally connected components comprising DNA, RNA or proteins. The review begins with an overview of the diversity of devices being developed and then considers the challenges presented by trying to engineer more scaled-up systems. While the engineering of RNA-based and protein-based circuitry poses new challenges, the resulting 'toolsets' of components and novel mechanisms of operation will open up multiple new opportunities for synthetic biology. However, agreed procedures for standardization will need to be placed at the heart of this expanding field if the full potential benefits are to be realized.

SBOLCanvas: A Visual Editor for Genetic Designs

SBOLCanvas is a web-based application that can create and edit genetic constructs using the SBOL data and visual standards. SBOLCanvas allows a user to create a genetic design visually and structurally from start to finish. It also allows users to incorporate existing SBOL data from a SynBioHub repository. By the nature of being a web-based application, SBOLCanvas is readily accessible and easy to use. A live version of the latest release can be found at https://sbolcanvas.org.

Comparative analysis of three studies measuring fluorescence from engineered bacterial genetic constructs

Reproducibility is a key challenge of synthetic biology, but the foundation of reproducibility is only as solid as the reference materials it is built upon. Here we focus on the reproducibility of fluorescence measurements from bacteria transformed with engineered genetic constructs. This comparative analysis comprises three large interlaboratory studies using flow cytometry and plate readers, identical genetic constructs, and compatible unit calibration protocols. Across all three studies, we find similarly high precision in the calibrants used for plate readers. We also find that fluorescence measurements agree closely across the flow cytometry results and two years of plate reader results, with an average standard deviation of 1.52-fold, while the third year of plate reader results are consistently shifted by more than an order of magnitude, with an average shift of 28.9-fold. Analyzing possible sources of error indicates this shift is due to incorrect preparation of the fluorescein calibrant. These findings suggest that measuring fluorescence from engineered constructs is highly reproducible, but also that there is a critical need for access to quality controlled fluorescent calibrants for plate readers.

An Integrated Computer-Aided Design and Manufacturing Workflow for Synthetic Biology

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.

SynBiopython: an open-source software library for Synthetic Biology

Advances in hardware automation in synthetic biology laboratories are not yet fully matched by those of their software counterparts. Such automated laboratories, now commonly called biofoundries, require software solutions that would help with many specialized tasks such as batch DNA design, sample and data tracking, and data analysis, among others. Typically, many of the challenges facing biofoundries are shared, yet there is frequent wheel-reinvention where many labs develop similar software solutions in parallel. In this article, we present the first attempt at creating a standardized, open-source Python package. A number of tools will be integrated and developed that we envisage will become the obvious starting point for software development projects within biofoundries globally. Specifically, we describe the current state of available software, present usage scenarios and case studies for common problems, and finally describe plans for future development. SynBiopython is publicly available at the following address: http://synbiopython.org.

The Synthetic Biology Open Language (SBOL) Version 3: Simplified Data Exchange for Bioengineering

The Synthetic Biology Open Language (SBOL) is a community-developed data standard that allows knowledge about biological designs to be captured using a machine-tractable, ontology-backed representation that is built using Semantic Web technologies. While early versions of SBOL focused only on the description of DNA-based components and their sub-components, SBOL can now be used to represent knowledge across multiple scales and throughout the entire synthetic biology workflow, from the specification of a single molecule or DNA fragment through to multicellular systems containing multiple interacting genetic circuits. The third major iteration of the SBOL standard, SBOL3, is an effort to streamline and simplify the underlying data model with a focus on real-world applications, based on experience from the deployment of SBOL in a variety of scientific and industrial settings. Here, we introduce the SBOL3 specification both in comparison to previous versions of SBOL and through practical examples of its use.

Combinatorial-Hierarchical DNA Library Design Using the TeselaGen DESIGN Module with j5

Modern DNA assembly techniques are known for their potential to link multiple large DNA fragments together into even larger constructs in single pot reactions that are easier to automate and work more reliably than traditional cloning methods. The simplicity of the chemistry is in contrast to the increased work needed to design optimal reactions that maximize DNA fragment reuse, minimize cost, and organize thousands of potential chemical reactions. Here we examine available DNA assembly methods and describe through example, the construction of a complex but not atypical combinatorial and hierarchical library using protocols that are generated automatically with the assistance of modern synthetic biology software.

Beyond natural: synthetic expansions of botanical form and function

Powered by developments that enabled genome-scale investigations, systems biology emerged as a field aiming to understand how phenotypes emerge from network functions. These advances fuelled a new engineering discipline focussed on synthetic reconstructions of complex biological systems with the goal of predictable rational design and control. Initially, progress in the nascent field of synthetic biology was slow due to the ad hoc nature of molecular biology methods such as cloning. The application of engineering principles such as standardisation, together with several key technical advances, enabled a revolution in the speed and accuracy of genetic manipulation. Combined with mathematical and statistical modelling, this has improved the predictability of engineering biological systems of which nonlinearity and stochasticity are intrinsic features leading to remarkable achievements in biotechnology as well as novel insights into biological function. In the past decade, there has been slow but steady progress in establishing foundations for synthetic biology in plant systems. Recently, this has enabled model-informed rational design to be successfully applied to the engineering of plant gene regulation and metabolism. Synthetic biology is now poised to transform the potential of plant biotechnology. However, reaching full potential will require conscious adjustments to the skillsets and mind sets of plant scientists.

The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE)

This paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.

SBOL Visual 2 Ontology

Standardizing the visual representation of genetic parts and circuits is essential for unambiguously creating and interpreting genetic designs. To this end, an increasing number of tools are adopting well-defined glyphs from the Synthetic Biology Open Language (SBOL) Visual standard to represent various genetic parts and their relationships. However, the implementation and maintenance of the relationships between biological elements or concepts and their associated glyphs has up to now been left up to tool developers. We address this need with the SBOL Visual 2 Ontology, a machine-accessible resource that provides rules for mapping from genetic parts, molecules, and interactions between them, to agreed SBOL Visual glyphs. This resource, together with a web service, can be used as a library to simplify the development of visualization tools, as a stand-alone resource to computationally search for suitable glyphs, and to help facilitate integration with existing biological ontologies and standards in synthetic biology.

Digitalizing heterologous gene expression in Gram-negative bacteria with a portable ON/OFF module

While prokaryotic promoters controlled by signal-responding regulators typically display a range of input/output ratios when exposed to cognate inducers, virtually no naturally occurring cases are known to have an OFF state of zero transcription-as ideally needed for synthetic circuits. To overcome this problem, we have modelled and implemented a simple digitalizer module that completely suppresses the basal level of otherwise strong promoters in such a way that expression in the absence of induction is entirely impeded. The circuit involves the interplay of a translation-inhibitory sRNA with the translational coupling of the gene of interest to a repressor such as LacI. The digitalizer module was validated with the strong inducible promoters Pm (induced by XylS in the presence of benzoate) and PalkB (induced by AlkS/dicyclopropyl ketone) and shown to perform effectively in both Escherichia coli and the soil bacterium Pseudomonas putida. The distinct expression architecture allowed cloning and conditional expression of, e.g. colicin E3, one molecule of which per cell suffices to kill the host bacterium. Revertants that escaped ColE3 killing were not found in hosts devoid of insertion sequences, suggesting that mobile elements are a major source of circuit inactivation in vivo.

Towards a fully automated algorithm driven platform for biosystems design

Large-scale data acquisition and analysis are often required in the successful implementation of the design, build, test, and learn (DBTL) cycle in biosystems design. However, it has long been hindered by experimental cost, variability, biases, and missed insights from traditional analysis methods. Here, we report the application of an integrated robotic system coupled with machine learning algorithms to fully automate the DBTL process for biosystems design. As proof of concept, we have demonstrated its capacity by optimizing the lycopene biosynthetic pathway. This fully-automated robotic platform, BioAutomata, evaluates less than 1% of possible variants while outperforming random screening by 77%. A paired predictive model and Bayesian algorithm select experiments which are performed by Illinois Biological Foundry for Advanced Biomanufacturing (iBioFAB). BioAutomata excels with black-box optimization problems, where experiments are expensive and noisy and the success of the experiment is not dependent on extensive prior knowledge of biological mechanisms.

Existing efforts have been focused on one of the elements in the automation of the design, build, test, and learn (DBTL) cycle for biosystems design. Here, the authors integrate a robotic system with machine learning algorithms to fully automate the DBTL cycle and apply it in optimizing the lycopene biosynthetic pathway.

Contemporary Tools for Regulating Gene Expression in Bacteria

Insights from novel mechanistic paradigms in gene expression control have led to the development of new gene expression systems for bioproduction, control, and sensing applications. Coupled with a greater understanding of synthetic burden and modern creative biodesign approaches, contemporary bacterial gene expression tools and systems are emerging that permit fine-tuning of expression, enabling greater predictability and maximisation of specific productivity, while minimising deleterious effects upon cell viability. These advances have been achieved by using a plethora of regulatory tools, operating at all levels of the so-called 'central dogma' of molecular biology. In this review, we discuss these gene regulation tools in the context of their design, prototyping, integration into expression systems, and biotechnological application.

Industrializing a Bacterial Strain for l-Serine Production through Translation Initiation Optimization

Turning a proof-of-concept synthetic biology design into a robust, high performing cell factory is a major time and money consuming task, which severely limits the growth of the white biotechnology sector. Here, we extend the use of tunable antibiotic resistance markers for synthetic evolution (TARSyn), a workflow for screening translation initiation region (TIR) libraries with antibiotic selection, to generic pathway engineering, and transform a proof-of-concept synbio design into a process that performs at industrially relevant levels. Using a combination of rational design and adaptive evolution, we recently engineered a high-performing bacterial strain for production of the important building block biochemical l-serine, based on two high-copy pET vectors facilitating expression of the serine biosynthetic genes serA, serC, and serB from three independent transcriptional units. Here, we prepare the bacterial strain for industrial scale up by transferring and reconfiguring the three genes into an operon encoded on a single low-copy plasmid. Not surprisingly, this initially reduces production titers considerably. We use TARSyn to screen both experimental and computational optimization designs resulting in high-performing synthetic serine operons and reach industrially relevant production levels of 50 g/L in fed-batch fermentations, the highest reported so far for serine production.

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.

A Computational Workflow for the Automated Generation of Models of Genetic Designs

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.

SBOL-OWL: An Ontological Approach for Formal and Semantic Representation of Synthetic Biology Information

Standard representation of data is key for the reproducibility of designs in synthetic biology. The Synthetic Biology Open Language (SBOL) has already emerged as a data standard to represent information about genetic circuits, and it is based on capturing data using graphs. The language provides the syntax using a free text document that is accessible to humans only. This paper describes SBOL-OWL, an ontology for a machine understandable definition of SBOL. This ontology acts as a semantic layer for genetic circuit designs. As a result, computational tools can understand the meaning of design entities in addition to parsing structured SBOL data. SBOL-OWL not only describes how genetic circuits can be constructed computationally, it also facilitates the use of several existing Semantic Web tools for synthetic biology. This paper demonstrates some of these features, for example, to validate designs and check for inconsistencies. Through the use of SBOL-OWL, queries can be simplified and become more intuitive. Moreover, existing reasoners can be used to infer information about genetic circuit designs that cannot be directly retrieved using existing querying mechanisms. This ontological representation of the SBOL standard provides a new perspective to the verification, representation, and querying of information about genetic circuits and is important to incorporate complex design information via the integration of biological ontologies.

Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)

In vitro selection of ligand-responsive ribozymes can identify rare, functional sequences from large libraries. While powerful, key caveats of this approach include lengthy and demanding experimental workflows; unpredictable experimental outcomes and unknown functionality of enriched sequences in vivo. To address the first of these limitations, we developed Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR). LigASERR is scalable, amenable to automation and requires less time to implement compared to alternative methods. To improve the predictability of experiments, we modeled the underlying selection process, predicting experimental outcomes based on sequence and population parameters. We applied this new methodology and model to the enrichment of a known, in vitro-selected sequence from a bespoke library. Prior to implementing selection, conditions were optimized and target sequence dynamics accurately predicted for the majority of the experiment. In addition to enriching the target sequence, we identified two new, theophylline-activated ribozymes. Notably, all three sequences yielded riboswitches functional in Escherichia coli, suggesting LigASERR and similar in vitro selection methods can be utilized for generating functional riboswitches in this organism.

Lessons from Two Design-Build-Test-Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning

The Design-Build-Test-Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient approach to strain development than historical efforts in biofuels and biobased products. Here, we report on implementation of two DBTL cycles to optimize 1-dodecanol production from glucose using 60 engineered Escherichia coli MG1655 strains. The first DBTL cycle employed a simple strategy to learn efficiently from a relatively small number of strains (36), wherein only the choice of ribosome-binding sites and an acyl-ACP/acyl-CoA reductase were modulated in a single pathway operon including genes encoding a thioesterase (UcFatB1), an acyl-ACP/acyl-CoA reductase (Maqu_2507, Maqu_2220, or Acr1), and an acyl-CoA synthetase (FadD). Measured variables included concentrations of dodecanol and all proteins in the engineered pathway. We used the data produced in the first DBTL cycle to train several machine-learning algorithms and to suggest protein profiles for the second DBTL cycle that would increase production. These strategies resulted in a 21% increase in dodecanol titer in Cycle 2 (up to 0.83 g/L, which is more than 6-fold greater than previously reported batch values for minimal medium). Beyond specific lessons learned about optimizing dodecanol titer in E. coli, this study had findings of broader relevance across synthetic biology applications, such as the importance of sequencing checks on plasmids in production strains as well as in cloning strains, and the critical need for more accurate protein expression predictive tools.

Cellular checkpoint control using programmable sequential logic

Biological processes that require orderly progression, such as growth and differentiation, proceed via regulatory checkpoints where the cell waits for signals before continuing to the next state. Implementing such control would allow genetic engineers to divide complex tasks into stages. We present genetic circuits that encode sequential logic to instruct Escherichia coli to proceed through a linear or cyclical sequence of states. These are built with 11 set-reset latches, designed with repressor-based NOR gates, which can connect to each other and sensors. The performance of circuits with up to three latches and four sensors, including a gated D latch, closely match predictions made by using nonlinear dynamics. Checkpoint control is demonstrated by switching cells between multiple circuit states in response to external signals over days.

DNA assembly standards: Setting the low-level programming code for plant biotechnology

Synthetic Biology is defined as the application of engineering principles to biology. It aims to increase the speed, ease and predictability with which desirable changes and novel traits can be conferred to living cells. The initial steps in this process aim to simplify the encoding of new instructions in DNA by establishing low-level programming languages for biology. Together with advances in the laboratory that allow multiple DNA molecules to be efficiently assembled together into a desired order in a single step, this approach has simplified the design and assembly of multigene constructs and has even facilitated the automated construction of synthetic chromosomes. These advances and technologies are now being applied to plants, for which there are a growing number of software and wetware tools for the design, construction and delivery of DNA molecules and for the engineering of endogenous genes. Here we review the efforts of the past decade that have established synthetic biology workflows and tools for plants and discuss the constraints and bottlenecks of this emerging field.

Quantification of bacterial fluorescence using independent calibrants

Fluorescent reporters are commonly used to quantify activities or properties of both natural and engineered cells. Fluorescence is still typically reported only in arbitrary or normalized units, however, rather than in units defined using an independent calibrant, which is problematic for scientific reproducibility and even more so when it comes to effective engineering. In this paper, we report an interlaboratory study showing that simple, low-cost unit calibration protocols can remedy this situation, producing comparable units and dramatic improvements in precision over both arbitrary and normalized units. Participants at 92 institutions around the world measured fluorescence from E. coli transformed with three engineered test plasmids, plus positive and negative controls, using simple, low-cost unit calibration protocols designed for use with a plate reader and/or flow cytometer. In addition to providing comparable units, use of an independent calibrant allows quantitative use of positive and negative controls to identify likely instances of protocol failure. The use of independent calibrants thus allows order of magnitude improvements in precision, narrowing the 95% confidence interval of measurements in our study up to 600-fold compared to normalized units.

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.

Part by Part: Synthetic Biology Parts Used in Solventogenic Clostridia

The solventogenic Clostridia are of interest to the chemical industry because of their natural ability to produce chemicals such as butanol, acetone and ethanol from diverse feedstocks. Their use as whole cell factories presents multiple metabolic engineering targets that could lead to improved sustainability and profitability of Clostridium industrial processes. However, engineering efforts have been held back by the scarcity of genetic and synthetic biology tools. Over the past decade, genetic tools to enable transformation and chromosomal modifications have been developed, but the lack of a broad palette of synthetic biology parts remains one of the last obstacles to the rapid engineered improvement of these species for bioproduction. We have systematically reviewed existing parts that have been used in the modification of solventogenic Clostridia, revealing a narrow range of empirically chosen and nonengineered parts that are in current use. The analysis uncovers elements, such as promoters, transcriptional terminators and ribosome binding sites where increased fundamental knowledge is needed for their reliable use in different applications. Together, the review provides the most comprehensive list of parts used and also presents areas where an improved toolbox is needed for full exploitation of these industrially important bacteria.

Automated Visualization of Genetic Designs Using DNAplotlib

Visualization of complex genetic systems can help efficiently communicate important design features and clearly illustrate overall structures. To aid in the creation of such diagrams, standards such as the Synthetic Biology Open Language Visual (SBOLv) have been established to ensure that specific symbols and shapes convey the same meaning for genetic parts across the field. Here, we describe several ways that the computational tool DNAplotlib can be used to automate the generation of SBOLv standard-compliant diagrams covering simple genetic designs to large libraries of genetic constructs.

Genetic Constructor: An Online DNA Design Platform

Genetic Constructor is a cloud Computer Aided Design (CAD) application developed to support synthetic biologists from design intent through DNA fabrication and experiment iteration. The platform allows users to design, manage, and navigate complex DNA constructs and libraries, using a new visual language that focuses on functional parts abstracted from sequence. Features like combinatorial libraries and automated primer design allow the user to separate design from construction by focusing on functional intent, and design constraints aid iterative refinement of designs. A plugin architecture enables contributions from scientists and coders to leverage existing powerful software and connect to DNA foundries. The software is easily accessible and platform agnostic, free for academics, and available in an open-source community edition. Genetic Constructor seeks to democratize DNA design, manufacture, and access to tools and services from the synthetic biology community.

GB3.0: a platform for plant bio-design that connects functional DNA elements with associated biological data

Modular DNA assembly simplifies multigene engineering in Plant Synthetic Biology. Furthermore, the recent adoption of a common syntax to facilitate the exchange of plant DNA parts (phytobricks) is a promising strategy to speed up genetic engineering. Following this lead, here, we present a platform for plant biodesign that incorporates functional descriptions of phytobricks obtained under pre-defined experimental conditions, and systematically registers the resulting information as metadata for documentation. To facilitate the handling of functional descriptions, we developed a new version (v3.0) of the GoldenBraid (GB) webtool that integrates the experimental data and displays it in the form of datasheets. We report the use of the Luciferase/Renilla (Luc/Ren) transient agroinfiltration assay in Nicotiana benthamiana as a standard to estimate relative transcriptional activities conferred by regulatory phytobricks, and show the consistency and reproducibility of this method in the characterization of a synthetic phytobrick based on the CaMV35S promoter. Furthermore, we illustrate the potential for combinatorial optimization and incremental innovation of the GB3.0 platform in two separate examples, (i) the development of a collection of orthogonal transcriptional regulators based on phiC31 integrase and (ii) the design of a small genetic circuit that connects a glucocorticoid switch to a MYB/bHLH transcriptional activation module.

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.

GeneMill: A 21st century platform for innovation

GeneMill officially launched on 4th February 2016 and is an open access academic facility located at The University of Liverpool that has been established for the high-throughput construction and testing of synthetic DNA constructs. GeneMill provides end-to-end design, construction and phenotypic characterization of small to large gene constructs or genetic circuits/pathways for academic and industrial applications. Thus, GeneMill is equipping the scientific community with easy access to the validated tools required to explore the possibilities of Synthetic Biology.

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 (e.g., 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 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/ .

DNAplotlib: Programmable Visualization of Genetic Designs and Associated Data

DNAplotlib ( www.dnaplotlib.org ) is a computational toolkit for the programmable visualization of highly customizable, standards-compliant genetic designs. Functions are provided to aid with both visualization tasks and to extract and overlay associated experimental data. High-quality output is produced in the form of vector-based PDFs, rasterized images, and animated movies. All aspects of the rendering process can be easily customized or extended by the user to cover new forms of genetic part or regulation. DNAplotlib supports improved communication of genetic design information and offers new avenues for static, interactive and dynamic visualizations that map and explore the links between the structure and function of genetic parts, devices and systems; including metabolic pathways and genetic circuits. DNAplotlib is cross-platform software developed using Python.

SBOLDesigner 2: An Intuitive Tool for Structural Genetic Design

As the Synthetic Biology Open Language (SBOL) data and visual standards gain acceptance for describing genetic designs in a detailed and reproducible way, there is an increasing need for an intuitive sequence editor tool that biologists can use that supports these standards. This paper describes SBOLDesigner 2, a genetic design automation (GDA) tool that natively supports both the SBOL data model (Version 2) and SBOL Visual (Version 1). This software is enabled to fetch and store parts and designs from SBOL repositories, such as SynBioHub. It can also import and export data about parts and designs in FASTA, GenBank, and SBOL 1 data format. Finally, it possesses a simple and intuitive user interface. This paper describes the design process using SBOLDesigner 2, highlighting new features over the earlier prototype versions. SBOLDesigner 2 is released freely and open source under the Apache 2.0 license.

Synthetic Biology: Engineering Living Systems from Biophysical Principles

Synthetic biology was founded as a biophysical discipline that sought explanations for the origins of life from chemical and physical first principles. Modern synthetic biology has been reinvented as an engineering discipline to design new organisms as well as to better understand fundamental biological mechanisms. However, success is still largely limited to the laboratory and transformative applications of synthetic biology are still in their infancy. Here, we review six principles of living systems and how they compare and contrast with engineered systems. We cite specific examples from the synthetic biology literature that illustrate these principles and speculate on their implications for further study. To fully realize the promise of synthetic biology, we must be aware of life's unique properties.