Microbiome Engineering: Synthetic Biology of Plant-Associated Microbiomes in Sustainable Agriculture.

To support an ever-increasing population, modern agriculture faces numerous challenges that pose major threats to global food and energy security. Plant-associated microbes, with their many plant growth-promoting (PGP) traits, have enormous potential in helping to solve these challenges. However, the results of their use in agriculture have been variable, probably because of poor colonization. Phytomicrobiome engineering is an emerging field of synthetic biology that may offer ways to alleviate this limitation. This review highlights recent advances in both bottom-up and top-down approaches to engineering non-model bacteria and microbiomes to promote beneficial plant-microbe interactions, as well as advances in strategies to evaluate these interactions. Biosafety, biosecurity, and biocontainment strategies to address the environmental concerns associated with field use of synthetic microbes are also discussed.

Genetic Safeguards for Safety-by-design: So Close Yet So Far.

Safety-by-design (SbD) is paramount for risk management in synthetic biology, with genetic safeguards being a key technology for its implementation. While attractive in theory, the integration of genetic safeguards into SbD strategies is rarely exercised in practice, despite technological advances. Here we question why and what might be done about it.

Developing synthetic biology for industrial biotechnology applications.

Since the beginning of the 21st Century, synthetic biology has established itself as an effective technological approach to design and engineer biological systems. Whilst research and investment continues to develop the understanding, control and engineering infrastructural platforms necessary to tackle ever more challenging systems - and to increase the precision, robustness, speed and affordability of existing solutions - hundreds of start-up companies, predominantly in the US and UK, are already translating learnings and potential applications into commercially viable tools, services and products. Start-ups and SMEs have been the predominant channel for synthetic biology commercialisation to date, facilitating rapid response to changing societal interests and market pull arising from increasing awareness of health and global sustainability issues. Private investment in start-ups across the US and UK is increasing rapidly and now totals over $12bn. Health-related biotechnology applications have dominated the commercialisation of products to date, but significant opportunities for the production of bio-derived materials and chemicals, including consumer products, are now being developed. Synthetic biology start-ups developing tools and services account for between 10% (in the UK) and ∼25% (in the US) of private investment activity. Around 20% of synthetic biology start-ups address industrial biotechnology targets, but currently, only attract ∼11% private investment. Adopting a more networked approach - linking specialists, infrastructure and ongoing research to de-risk the economic challenges of scale-up and supported by an effective long-term funding strategy - is set to transform the impact of synthetic biology and industrial biotechnology in the bioeconomy.

Hands-On Introduction to Synthetic Biology for Security Professionals.

The rapid pace of life sciences innovations and a growing list of nontraditional actors engaging in biological research make it challenging to develop appropriate policies to protect sensitive infrastructures. To address this challenge, we developed a five-day awareness program for security professionals, including laboratory work, site visits, and lectures.

[The eradication of infectious viral diseases endangered by advances in synthetic biology]. / L'éradication des maladies infectieuses virales mise en danger par les avancées de la biologie synthétique.

The eradication of infectious diseases is one of the oldest dreams of mankind. It has been materialized only once in History with smallpox in 1980. Considerable efforts are being developed against poliomyelitis viruses since 1988, but the ultimate goal of eradication is not yet achieved. Paradoxically, while the objective of having eradicated these two viral diseases is approaching, synthetic biology multiplies the prowesses of virus "neosynthesis", imperiling at least virtually the durability of these advances. This article emphasizes the potential of a new biology on one side, and the difficult reality of the fight against infections on the other.

Time to Get Serious about Measurement in Synthetic Biology.

For synthetic biology to mature, composition of devices into functional systems must become routine. This requires widespread adoption of comparable and replicable units of measurement. Interlaboratory studies organized through the International Genetically Engineered Machine (iGEM) competition show that fluorescence can be calibrated with simple, low-cost protocols, so fluorescence should no longer be published without units.

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.

Synthetic Biology Open Language (SBOL) Version 2.2.0.

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

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2017.

Standards are essential to the advancement of Systems and Synthetic Biology. COMBINE provides a formal body and a centralised platform to help develop and disseminate relevant standards and related resources. The regular special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards by providing unified, easily citable access. This paper provides an overview of existing COMBINE standards and presents developments of the last year.

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

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

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.

Blueprints for green biotech: development and application of standards for plant synthetic biology.

Synthetic biology aims to apply engineering principles to the design and modification of biological systems and to the construction of biological parts and devices. The ability to programme cells by providing new instructions written in DNA is a foundational technology of the field. Large-scale de novo DNA synthesis has accelerated synthetic biology by offering custom-made molecules at ever decreasing costs. However, for large fragments and for experiments in which libraries of DNA sequences are assembled in different combinations, assembly in the laboratory is still desirable. Biological assembly standards allow DNA parts, even those from multiple laboratories and experiments, to be assembled together using the same reagents and protocols. The adoption of such standards for plant synthetic biology has been cohesive for the plant science community, facilitating the application of genome editing technologies to plant systems and streamlining progress in large-scale, multi-laboratory bioengineering projects.

Improving Synthetic Biology Communication: Recommended Practices for Visual Depiction and Digital Submission of Genetic Designs.

Research is communicated more effectively and reproducibly when articles depict genetic designs consistently and fully disclose the complete sequences of all reported constructs. ACS Synthetic Biology is now providing authors with updated guidance and piloting a new tool and publication workflow that facilitate compliance with these recommended practices and standards for visual representation and data exchange.

Scientific Opinion on Risk Assessment of Synthetic Biology.

In 2013, three Scientific Committees of the European Commission (EC) drafted Scientific Opinions on synthetic biology that provide an operational definition and address risk assessment methodology, safety aspects, environmental risks, knowledge gaps, and research priorities. These Opinions contribute to the international discussions on the risk governance for synthetic biology developments.

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways.

Sharing Structure and Function in Biological Design with SBOL 2.0.

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

Toward the First Data Acquisition Standard in Synthetic Biology.

This paper describes the development of a new data acquisition standard for synthetic biology. This comprises the creation of a methodology that is designed to capture all the data, metadata, and protocol information associated with biopart characterization experiments. The new standard, called DICOM-SB, is based on the highly successful Digital Imaging and Communications in Medicine (DICOM) standard in medicine. A data model is described which has been specifically developed for synthetic biology. The model is a modular, extensible data model for the experimental process, which can optimize data storage for large amounts of data. DICOM-SB also includes services orientated toward the automatic exchange of data and information between modalities and repositories. DICOM-SB has been developed in the context of systematic design in synthetic biology, which is based on the engineering principles of modularity, standardization, and characterization. The systematic design approach utilizes the design, build, test, and learn design cycle paradigm. DICOM-SB has been designed to be compatible with and complementary to other standards in synthetic biology, including SBOL. In this regard, the software provides effective interoperability. The new standard has been tested by experiments and data exchange between Nanyang Technological University in Singapore and Imperial College London.