SBOLDesigner 2: An Intuitive Tool for Structural Genetic Design

GOLDBAR: A Framework for Combinatorial Biological Design

With the rise of new DNA part libraries and technologies for assembling DNA, synthetic biologists are increasingly constructing and screening combinatorial libraries to optimize their biological designs. As combinatorial libraries are used to generate data on design performance, new rules for composing biological designs will emerge. Most formal frameworks for combinatorial design, however, do not yet support formal comparison of design composition, which is needed to facilitate automated analysis and machine learning in massive biological design spaces. To address this need, we introduce a combinatorial design framework called GOLDBAR. Compared with existing frameworks, GOLDBAR enables synthetic biologists to intersect and merge the rules for entire classes of biological designs to extract common design motifs and infer new ones. Here, we demonstrate the application of GOLDBAR to refine/validate design spaces for TetR-homologue transcriptional logic circuits, verify the assembly of a partial nif gene cluster, and infer novel gene clusters for the biosynthesis of rebeccamycin. We also discuss how GOLDBAR could be used to facilitate grammar-based machine learning in synthetic biology.

pyBrick-DNA: A Python-Based Environment for Automated Genetic Component Assembly

Genetic component assembly is key in the simulation and implementation of genetic circuits. Automating this process, thus accelerating prototyping, is a necessity. We present pyBrick-DNA, a software written in Python, that assembles components for the construction of genetic circuits. pyBrick-DNA (colab.pyBrick.com) is a user-friendly environment where scientists can select genetic sequences or input custom sequences to build genetic assemblies. All components are modularly fused to generate a ready-to-go single DNA fragment. It includes Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and plant gene-editing components. Hence, pyBrick-DNA can generate a functional CRISPR construct composed of a single-guided RNA integrated with Cas9, promoters, and terminator elements. The outcome is a DNA sequence, along with a graphical representation, composed of user-selected genetic parts, ready to be synthesized and cloned in vivo. Moreover, the sequence can be exported as a GenBank file allowing its use with other synthetic biology tools.

SynBio2Easy-a biologist-friendly tool for batch operations on SBOL designs with Excel inputs

Practical delivery of Findable, Accessible, Reusable and Interoperable principles for research data management requires expertise, time resource, (meta)data standards and formats, software tools and public repositories. The Synthetic Biology Open Language (SBOL2) metadata standard enables FAIR sharing of the designs of synthetic biology constructs, notably in the repository of the SynBioHub platform. Large libraries of such constructs are increasingly easy to produce in practice, for example, in DNA foundries. However, manual curation of the equivalent libraries of designs remains cumbersome for a typical lab researcher, creating a barrier to data sharing. Here, we present a simple tool SynBio2Easy, which streamlines and automates operations on multiple Synthetic Biology Open Language (SBOL) designs using Microsoft Excel® tables as metadata inputs. The tool provides several utilities for manipulation of SBOL documents and interaction with SynBioHub: for example, generation of a library of plasmids based on an original design template, bulk deposition into SynBioHub, or annotation of existing SBOL component definitions with notes and authorship information. The tool was used to generate and deposit a collection of 3661 cyanobacterium Synechocystis plasmids into the public SynBioHub repository. In the process of developing the software and uploading these data, we evaluated some aspects of the SynBioHub platform and SBOL ecosystem, and we discuss proposals for improvement that could benefit the user community. With software such as SynBio2Easy, we aim to deliver a user-driven tooling to make FAIR a reality at all stages of the project lifecycle in synthetic biology research. Graphical Abstract.

Virtual Parts Repository 2: Model-Driven Design of Genetic Regulatory Circuits

Engineering genetic regulatory circuits is key to the creation of biological applications that are responsive to environmental changes. Computational models can assist in understanding especially large and complex circuits for which manual analysis is infeasible, permitting a model-driven design process. However, there are still few tools that offer the ability to simulate the system under design. One of the reasons for this is the lack of accessible model repositories or libraries that cater to the modular composition of models of synthetic systems. Here, we present the second version of the Virtual Parts Repository, a framework to facilitate the model-driven design of genetic regulatory circuits, which provides reusable, modular, and composable models. The new framework is service-oriented, easier to use in computational workflows, and provides several new features and access methods. New features include supporting hierarchical designs via a graph-based repository or compatible remote repositories, enriching existing designs, and using designs provided in Synthetic Biology Open Language documents to derive system-scale and hierarchical Systems Biology Markup Language models. We also present a reaction-based modeling abstraction inspired by rule-based modeling techniques to facilitate scalable and modular modeling of complex and large designs. This modeling abstraction enhances the modeling capability of the framework, for example, to incorporate design patterns such as roadblocking, distributed deployment of genetic circuits using plasmids, and cellular resource dependency. The framework and the modeling abstraction presented in this paper allow computational design tools to take advantage of computational simulations and ultimately help facilitate more predictable applications.

Synthetic Biology Curation Tools (SYNBICT)

Much progress has been made in developing tools to generate component-based design representations of biological systems from standard libraries of parts. Most biological designs, however, are still specified at the sequence level. Consequently, there exists a need for a tool that can be used to automatically infer component-based design representations from sequences, particularly in cases when those sequences have minimal levels of annotation. Such a tool would assist computational synthetic biologists in bridging the gap between the outputs of sequence editors and the inputs to more sophisticated design tools, and it would facilitate their development of automated workflows for design curation and quality control. Accordingly, we introduce Synthetic Biology Curation Tools (SYNBICT), a Python tool suite for automation-assisted annotation, curation, and functional inference for genetic designs. We have validated SYNBICT by applying it to genetic designs in the DARPA Synergistic Discovery & Design (SD2) program and the International Genetically Engineered Machines (iGEM) 2018 distribution. Most notably, SYNBICT is more automated and parallelizable than manual design editors, and it can be applied to interpret existing designs instead of only generating new ones.

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.

paraSBOLv: a foundation for standard-compliant genetic design visualization tools

Diagrams constructed from standardized glyphs are central to communicating complex design information in many engineering fields. For example, circuit diagrams are commonplace in electronics and allow for a suitable abstraction of the physical system that helps support the design process. With the development of the Synthetic Biology Open Language Visual (SBOLv), bioengineers are now positioned to better describe and share their biological designs visually. However, the development of computational tools to support the creation of these diagrams is currently hampered by an excessive burden in maintenance due to the large and expanding number of glyphs present in the standard. Here, we present a Python package called paraSBOLv that enables access to the full suite of SBOLv glyphs through the use of machine-readable parametric glyph definitions. These greatly simplify the rendering process while allowing extensive customization of the resulting diagrams. We demonstrate how the adoption of paraSBOLv can accelerate the development of highly specialized biodesign visualization tools or even form the basis for more complex software by removing the burden of maintaining glyph-specific rendering code. Looking forward, we suggest that incorporation of machine-readable parametric glyph definitions into the SBOLv standard could further simplify the development of tools to produce standard-compliant diagrams and the integration of visual standards across fields.

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.

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.

Flapjack: Data Management and Analysis for Genetic Circuit Characterization

Characterization is fundamental to the design, build, test, learn (DBTL) cycle for engineering synthetic genetic circuits. Components must be described in such a way as to account for their behavior in a range of contexts. Measurements and associated metadata, including part composition, constitute the test phase of the DBTL cycle. These data may consist of measurements of thousands of circuits, measured in hundreds of conditions, in multiple assays potentially performed in different laboratories and using different techniques. In order to inform the learn phase this large volume of data must be filtered, collated, and analyzed. Characterization consists of using this data to parametrize models of component function in different contexts, and combining them to predict behaviors of novel circuits. Tools to store, organize, share, and analyze large volumes of measurement and metadata are therefore essential to linking the test phase to the build and learn phases, closing the loop of the DBTL cycle. Here we present such a system, implemented as a web app with a backend data registry and analysis engine. An interactive frontend provides powerful querying, plotting, and analysis tools, and we provide a REST API and Python package for full integration with external build and learn software. All measurements are associated with circuit part composition via SBOL (Synthetic Biology Open Language). We demonstrate our tool by characterizing a range of genetic components and circuits according to composition and context.

Plant Biosystems Design Research Roadmap 1.0

Human life intimately depends on plants for food, biomaterials, health, energy, and a sustainable environment. Various plants have been genetically improved mostly through breeding, along with limited modification via genetic engineering, yet they are still not able to meet the ever-increasing needs, in terms of both quantity and quality, resulting from the rapid increase in world population and expected standards of living. A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches. This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems. Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes. From this perspective, we present a comprehensive roadmap of plant biosystems design covering theories, principles, and technical methods, along with potential applications in basic and applied plant biology research. We highlight current challenges, future opportunities, and research priorities, along with a framework for international collaboration, towards rapid advancement of this emerging interdisciplinary area of research. Finally, we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception, trust, and acceptance.

Enhanced production of taxadiene in Saccharomyces cerevisiae

Background

Cost-effective production of the highly effective anti-cancer drug, paclitaxel (Taxol^®), remains limited despite growing global demands. Low yields of the critical taxadiene precursor remains a key bottleneck in microbial production. In this study, the key challenge of poor taxadiene synthase (TASY) solubility in S. cerevisiae was revealed, and the strains were strategically engineered to relieve this bottleneck.

Results

Multi-copy chromosomal integration of TASY harbouring a selection of fusion solubility tags improved taxadiene titres 22-fold, up to 57 ± 3 mg/L at 30 °C at microscale, compared to expressing a single episomal copy of TASY. The scalability of the process was highlighted through achieving similar titres during scale up to 25 mL and 250 mL in shake flask and bioreactor cultivations, respectively at 20 and 30 °C. Maximum taxadiene titres of 129 ± 15 mg/L and 127 mg/L were achieved through shake flask and bioreactor cultivations, respectively, of the optimal strain at a reduced temperature of 20 °C.

Conclusions

The results of this study highlight the benefit of employing a combination of molecular biology and bioprocess tools during synthetic pathway development, with which TASY activity was successfully improved by 6.5-fold compared to the highest literature titre in S. cerevisiae cell factories.

Genetic Circuit Dynamics: Hazard and Glitch Analysis

Multiple input changes can cause unwanted switching variations, or glitches, in the output of genetic combinational circuits. These glitches can have drastic effects if the output of the circuit causes irreversible changes within or with other cells such as a cascade of responses, apoptosis, or the release of a pharmaceutical in an off-target tissue. Therefore, avoiding unwanted variation of a circuit's output can be crucial for the safe operation of a genetic circuit. This paper investigates what causes unwanted switching variations in combinational genetic circuits using hazard analysis and a new dynamic model generator. The analysis is done in previously built and modeled genetic circuits with known glitching behavior. The dynamic models generated not only predict the same steady states as previous models but can also predict the unwanted switching variations that have been observed experimentally. Multiple input changes may cause glitches due to propagation delays within the circuit. Modifying the circuit's layout to alter these delays may change the likelihood of certain glitches, but it cannot eliminate the possibility that the glitch may occur. In other words, function hazards cannot be eliminated. Instead, they must be avoided by restricting the allowed input changes to the system. Logic hazards, on the other hand, can be avoided using hazard-free logic synthesis. This paper demonstrates this by showing how a circuit designed using a popular genetic design automation tool can be redesigned to eliminate logic hazards.

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.

Data-driven rational biosynthesis design: from molecules to cell factories

A proliferation of chemical, reaction and enzyme databases, new computational methods and software tools for data-driven rational biosynthesis design have emerged in recent years. With the coming of the era of big data, particularly in the bio-medical field, data-driven rational biosynthesis design could potentially be useful to construct target-oriented chassis organisms. Engineering the complicated metabolic systems of chassis organisms to biosynthesize target molecules from inexpensive biomass is the main goal of cell factory design. The process of data-driven cell factory design could be divided into several parts: (1) target molecule selection; (2) metabolic reaction and pathway design; (3) prediction of novel enzymes based on protein domain and structure transformation of biosynthetic reactions; (4) construction of large-scale DNA for metabolic pathways; and (5) DNA assembly methods and visualization tools. The construction of a one-stop cell factory system could achieve automated design from the molecule level to the chassis level. In this article, we outline data-driven rational biosynthesis design steps and provide an overview of related tools in individual steps.

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.

ShortBOL: A Language for Scripting Designs for Engineered Biological Systems Using Synthetic Biology Open Language (SBOL)

The Synthetic Biology Open Language (SBOL) is an emerging synthetic biology data exchange standard, designed primarily for unambiguous and efficient machine-to-machine communication. However, manual editing of SBOL is generally difficult for nontrivial designs. Here, we describe ShortBOL, a lightweight SBOL scripting language that bridges the gap between manual editing, visual design tools, and direct programming. ShortBOL is a shorthand textual language developed to enable users to create SBOL designs quickly and easily, without requiring strong programming skills or visual design tools.

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.

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.

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.

Better research by efficient sharing: evaluation of free management platforms for synthetic biology designs

Synthetic biology aims to introduce engineering principles into biology, for example, the construction of biological devices by assembling previously-characterized, functional parts. This approach demands new resources for cataloging and sharing biological components and designs, in order to accelerate the design-build-test-learn cycle. We evaluated two free, open source software platforms for managing synthetic biology data: Joint Bioenergy Institute-Inventory of Composable Elements (JBEI-ICE) and SynBioHub. We analyzed the systems from the perspective of experimental biology research groups in academia, which seek to incorporate the repositories into their synthetic biology workflow. Here, we define the minimal requirements for a repository in this context and develop three usage scenarios, where we then examine the two platforms: (i) supporting the synthetic biology design-build-test-learn cycle, (ii) batch deposit of existing designs into the repository and (iii) discovery and reuse of designs from the repository. Our evaluation of JBEI-ICE and SynBioHub provides an insight into the current state of synthetic biology resources, might encourage their wider adoption and should guide future development to better meet the needs of this user group.

Opening options for material transfer

The Open Material Transfer Agreement is a material-transfer agreement that enables broader sharing and use of biological materials by biotechnology practitioners working within the practical realities of technology transfer.

An Automated Induction Microfluidics System for Synthetic Biology

The expression of a recombinant gene in a host organism through induction can be an extensively manual and labor-intensive procedure. Several methods have been developed to simplify the protocol, but none has fully replaced the traditional IPTG-based induction. To simplify this process, we describe the development of an autoinduction platform based on digital microfluidics. This system consists of a 600 nm LED and a light sensor to enable the real-time monitoring of  the optical density (OD) samples coordinated with the semicontinuous mixing of a bacterial culture. A hand-held device was designed as a microbioreactor to culture cells and to measure the OD of the bacterial culture. In addition, it serves as a platform for the analysis of regulated protein expression in E. coli without the requirement of standardized well-plates or pipetting-based platforms. Here, we report for the first time, a system that offers great convenience without the user to physically monitor the culture or to manually add inducer at specific times. We characterized our system by looking at several parameters (electrode designs, gap height, and growth rates) required for an autoinducible system. As a first step, we carried out an automated induction optimization assay using a RFP reporter gene to identify conditions suitable for our system. Next, we used our system to identify active thermophilic β-glucosidase enzymes that may be suitable candidates for biomass hydrolysis. Overall, we believe that this platform may be useful for synthetic biology applications that require regulating and analyzing expression of heterologous genes for strain optimization.

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.

Standardization in synthetic biology: an engineering discipline coming of age

BACKGROUND

Leaping DNA read-and-write technologies, and extensive automation and miniaturization are radically transforming the field of biological experimentation by providing the tools that enable the cost-effective high-throughput required to address the enormous complexity of biological systems. However, standardization of the synthetic biology workflow has not kept abreast with dwindling technical and resource constraints, leading, for example, to the collection of multi-level and multi-omics large data sets that end up disconnected or remain under- or even unexploited.

PURPOSE

In this contribution, we critically evaluate the various efforts, and the (limited) success thereof, in order to introduce standards for defining, designing, assembling, characterizing, and sharing synthetic biology parts. The causes for this success or the lack thereof, as well as possible solutions to overcome these, are discussed.

CONCLUSION

Akin to other engineering disciplines, extensive standardization will undoubtedly speed-up and reduce the cost of bioprocess development. In this respect, further implementation of synthetic biology standards will be crucial for the field in order to redeem its promise, i.e. to enable predictable forward engineering.