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Synthetic biology roadmap to set research agenda for next 10 years, published by EBRS

Synthetic biology is the application of science, technology and engineering to facilitate and accelerate the design, manufacture and/or modification of genetic materials in living organisms, as defined by the European Commission. It envisions the redesign of natural biological systems for greater efficiency, as well as create new organisms as well as molecules with desired bio-attributes. Among the potential applications of this new field is the creation of bioengineered microorganisms (and possibly other life forms) that can produce pharmaceuticals, detect toxic chemicals, break down pollutants, repair defective genes, destroy cancer cells, and generate hydrogen for the post petroleum economy.


To date, achievements in the field include creating engineered trees for fire resistant timber, yeast which can produce biofuel, and synthetic gut microbes that could be used to detect the early signs of disease.


The latest roadmap, published by the US Engineering Biology Research Consortium (EBRC), is a consensus of more than 80 scientists and engineers from a range of disciplines, representing more than 30 universities around the world and 12 companies.


Professor Paul Freemont, Head of the Section of Structural Biology in the Department of Medicine at Imperial, member of EBRC and co-author of the roadmap, said: “We believe this roadmap will firmly set the research strategy for the whole synthetic biology field for at least the next 10 years. It is a major achievement.”


“The roadmap has several audiences,” Howard Salis, associate professor of biological engineering and chemical engineering at Penn State said. “Federal agencies looking to fund the most important areas of biotech research; industrial, medical and agricultural biotech companies who wish to anticipate future developments; and emerging faculty looking to prioritize their research.”


The roadmap will serve to guide these investments not only to improve our food supply, public health and environment, but to fuel the economy and maintain America’s leadership in synthetic biology. It stresses the importance of coordinated efforts among researchers, funding agencies, policymakers, government organizations and other stakeholders to fully realize the field’s potential.

Synthetic Biology Roadmap

The roadmap is, in part, highly technical, having “Technical Themes” as one of its two main sections. However, the other main roadmap section, “Application Sectors,” urges investment in synthetic biology by all federal government agencies, such as the Department of Energy, Department of Defense, National Institutes of Health, and the National Science Foundation.


Gene Editing, Synthesis, and Assembly

Fundamentally, an organism’s sensing, metabolic, and decision-making capabilities are all encoded within their genome, a very long double-stranded DNA molecule. By changing an organism’s genome sequence, we have the ability to rationally alter these cellular functions, and thereby engineer them to address a myriad of societal challenges. The ability to rationally alter DNA sequences, combining gene editing, DNA synthesis, and DNA assembly, are therefore considered a cornerstone capability of engineering biology, enabling us to construct engineered genetic systems to reprogram organisms with targeted functions. Advances in gene editing, synthesis, and assembly have significant transformative impacts on all sectors impacted by engineering biology by broadening the complexity and breadth of functionality that can be introduced into an engineered organism.


Gene Editing, Synthesis, and Assembly highlights several technological routes to achieving the overall goal of manufacturing mega-base length DNA molecules, and designing genes and genomes with desired functionalities.


This theme focuses on the development and advancement of tools to enable the production of chromosomal DNA and the engineering of entire genomes. Advancements are needed in the design and construction of functional genetic systems though the synthesis of long oligonucleotides, assembly of multiple fragments, and precision editing with high specificity.



At the molecular level, the functional richness, complexity, and diversity of biology can be localized predominantly to large “macro”-molecules (nucleic acids and proteins) and secondary metabolites. If researchers are able to efficiently design, generate, synthesize, assemble, and regulate biomolecules in ways that rival the functional complexity of natural counterparts, but with user-defined functions, then all areas of bioengineering and synthetic biology should benefit.


The roadmap for Biomolecule, Pathway, and Circuit Engineering addresses the engineering of individual biomolecules to have expanded or new functions and the combination of biomolecular parts into macromolecular assemblies, pathways, and circuits that carry out a larger function, both in vivo, in cell culture systems, and in vitro, in cell-free and/or purified settings. The roadmap operates from the definition that 1) biomolecules are made by natural or engineered biological systems; 2) biomolecules are made from natural simple building blocks or engineered variants of those building blocks; and 3) the production of biomolecules can predominantly be genetically encoded.


Successful progress would be demonstrated by production of functional macromolecules on demand from both natural and non-natural building blocks, targeted design of complex circuits and pathways, and control over the dynamics of regulatory systems.



Engineering biology has delivered new tools to engineer microorganisms, plants, and animal cell lines. There are now entirely new ways to construct hosts to perform tasks that nature cannot accomplish. While many of these efforts have focused on ‘traditional’ hosts represented by model microbes like E. coli and S. cerevisiae, there is a wealth of potential if the unique capabilities of a broader range of microbes can be harnessed for useful purposes. These might include microbes that are photosynthetic, such as cyanobacteria1, that can utilize non-sugar feedstocks such as methane or lignocellulose2, or that can be engineered to produce and secrete complex macromolecules more efficiently than model hosts.


Host and Consortia Engineering spans the development of cell-free systems, synthetic cells, single-cell organisms, multicellular tissues and whole organisms, and microbial consortia and biomes. Development of robust cell-free systems capable of diverse reactions, domestication and use of many single-cell hosts, targeted modification of multicellular organisms, and manipulation of microbial consortia.




Applications of engineering biology have grown beyond chemical production to include the generation of biosensor organisms for the lab, animal, and field, modification of agricultural organisms for nutrition and pest/environmental resilience, production of organisms for bioremediation, and live cell and gene/viral therapies. The rapid expansion of the field has resulted in new tools and new approaches; however, we are still challenged by the need for novel and more robust computational tools and models for engineering biology. For example, improved models of synthetic systems and of their interaction with their host organisms will facilitate more successful engineering and broader application.


The foundation of a viable design and manufacturing process for, or using, engineering biology is automation, which requires a complete description of a biological system’s components, data to describe the system’s function and interconnections, and computational models to predict the impact of environmental parameters on the system’s behavior. For each stage and interface of the design-build-test-learn framework, we need to specify the new data and algorithms that drive experimental design, clarify the assay frameworks that allow computational diagnosis of outcomes, assure that metrology is high quality and comparable across sites, integrate frameworks that allow algorithmic prediction of process and performance improvements, and build interfaces to drive both automated and human-in-the-loop design improvements.


Data Integration, Modeling, and Automation proposes a roadmap towards efficiently scaling engineering biology applications from the design, build, test, and learn cycle to the efficient and reproducible creation of individual biological components, to intracellular systems, multicellular systems, and their operation in diverse environments.


Data Integration, Modeling, and Automation focuses on robust, systematic use of the design, build, test, learn methodology to create complex systems. Progress requires a purpose-built computational infrastructure that supports DBTL biological processes, the ability to predict design outcomes, and optimize manufacturing processes at scale


The roadmap also keeps in mind that genetically engineered organisms can be a controversial issue, and stresses that the scientific community is committed to engaging with the public before their introduction. This includes addressing any potential ethical, legal and societal implications of consumer-facing products and technologies, along with discussing large-scale benefits.





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