Enabling the Advanced Bioeconomy through Public Policy Supporting Biofoundries and Engineering Biology

A new era of synthetic biology-microbial community design

Synthetic biology conceptualizes biological complexity as a network of biological parts, devices, and systems with predetermined functionalities and has had a revolutionary impact on fundamental and applied research. With the unprecedented ability to synthesize and transfer any DNA and RNA across organisms, the scope of synthetic biology is expanding and being recreated in previously unimaginable ways. The field has matured to a level where highly complex networks, such as artificial communities of synthetic organisms, can be constructed. In parallel, computational biology became an integral part of biological studies, with computational models aiding the unravelling of the escalating complexity and emerging properties of biological phenomena. However, there is still a vast untapped potential for the complete integration of modelling into the synthetic design process, presenting exciting opportunities for scientific advancements. Here, we first highlight the most recent advances in computer-aided design of microbial communities. Next, we propose that such a design can benefit from an organism-free modular modelling approach that places its emphasis on modules of organismal function towards the design of multispecies communities. We argue for a shift in perspective from single organism-centred approaches to emphasizing the functional contributions of organisms within the community. By assembling synthetic biological systems using modular computational models with mathematical descriptions of parts and circuits, we can tailor organisms to fulfil specific functional roles within the community. This approach aligns with synthetic biology strategies and presents exciting possibilities for the design of artificial communities. Graphical Abstract.

An engineering biology approach to automated workflow and biodesign

The paper addresses the application of engineering biology strategies and techniques to the automation of laboratory workflow-primarily in the context of biofoundries and biodesign applications based on the Design, Build, Test and Learn paradigm. The trend toward greater automation comes with its own set of challenges. On the one hand, automation is associated with higher throughput and higher replicability. On the other hand, the implementation of an automated workflow requires an instruction set that is far more extensive than that required for a manual workflow. Automated tasks must also be conducted in the order specified in the workflow, with the right logic, utilizing suitable biofoundry resources, and at scale-while simultaneously collecting measurements and associated data. The paper describes an approach to an automated workflow that is being trialed at the London Biofoundry at SynbiCITE. The solution represents workflows with directed graphs, uses orchestrators for their execution, and relies on existing standards. The approach is highly flexible and applies to not only workflow automation in single locations but also distributed workflows (e.g. for biomanufacturing). The final section presents an overview of the implementation-using the simple example of an assay based on a dilution, measurement, and data analysis workflow.

The Laboratory Automation Protocol (LAP) Format and Repository: A Platform for Enhancing Workflow Efficiency in Synthetic Biology

Laboratory automation deals with eliminating manual tasks in high-throughput protocols. It therefore plays a crucial role in allowing fast and reliable synthetic biology. However, implementing open-source automation solutions often demands experimental scientists to possess scripting skills, and even when they do, there is no standardized toolkit available for their use. To address this, we present the Laboratory Automation Protocol (LAP) Format and Repository. LAPs adhere to a standardized script-based format, enhancing end-user implementation and simplifying further development. With a modular design, LAPs can be seamlessly combined to create customized, target-specific workflows. Furthermore, all LAPs undergo experimental validation, ensuring their reliability. Detailed information is provided within each repository entry, allowing users to validate the LAPs in their own laboratory settings. We advocate for the adoption of the LAP Format and Repository as a community resource, which will continue to expand, improving the reliability and reproducibility of the automation processes.

Public biofoundries as innovation intermediaries: the integration of translation, sustainability, and responsibility

The emergence and evolution of engineering biology, and its potential to address multiple global challenges is associated with the rise of biofoundries. These innovation intermediaries are facilities that employ advanced automation and computational analytics to accelerate engineering biology applications. Yet, for biofoundries to fully achieve their promise of generating applications that address grand societal challenges, they need to meet three key challenges: translation of research technology and its commercialization, attention to sustainability, and responsible innovation. Using web content analysis and interviews, this paper explores the functions and capabilities undertaken by existing public biofoundries, the extent to which they address these three challenges, and opportunities and models for enhancement. We also probe the roles undertaken by three other contrasting types of innovation intermediaries to identify practices and opportunities for integration and partnering with public biofoundries. We find that public biofoundries exhibit relatively strong capabilities for research translation, whereas efforts toward sustainability and responsibility are generally less prominent. For biofoundry enhancement, we propose an organisational model based on external partnering where public biofoundries are positioned as intermediaries within regional innovation systems. The framework put forward is reproducible and could be used in other contexts for assessing innovation intermediary organisational functions and capabilities toward meeting societal challenges.

Bioeconomy and net-zero carbon: lessons from Trends in Biotechnology, volume 1, issue 1

Many biotechnology applications tend to be for low production volumes and relatively high-value products such as insulin and vaccines. More difficult to perfect at scale are bioprocesses for high-volume products with lower value, especially if the target product is a reduced chemical such as a solvent or a plastic. Historically, industrial microbiology succeeded under special circumstances when fossil feedstocks were either unavailable or expensive. Inevitably, as these circumstances relaxed, bioprocesses struggled to compete with petrochemistry. Why try to compete? Fossil resources will be phased out in the coming decades in the struggle with climate change. To reach net-zero carbon by 2050 will require all sectors to transition, not only energy and transportation. This may herald a new opportunity for industrial bioprocesses with much better tools.

A Network Approach to Genetic Circuit Designs

As genetic circuits become more sophisticated, the size and complexity of data about their designs increase. The data captured goes beyond genetic sequences alone; information about circuit modularity and functional details improves comprehension, performance analysis, and design automation techniques. However, new data types expose new challenges around the accessibility, visualization, and usability of design data (and metadata). Here, we present a method to transform circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into subnetworks of relevant information based on requirements such as the hierarchy of biological parts or interactions between entities. A significant advantage of a network approach is the ability to scale abstraction, providing an automatic sliding level of detail that further tailors the visualization to a given situation. Additionally, several visual changes can be applied, such as coloring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. We advocate using networks to structure, access, and improve synthetic biology information.

Removing the Bottleneck: Introducing cMatch - A Lightweight Tool for Construct-Matching in Synthetic Biology

We present a software tool, called cMatch, to reconstruct and identify synthetic genetic constructs from their sequences, or a set of sub-sequences—based on two practical pieces of information: their modular structure, and libraries of components. Although developed for combinatorial pathway engineering problems and addressing their quality control (QC) bottleneck, cMatch is not restricted to these applications. QC takes place post assembly, transformation and growth. It has a simple goal, to verify that the genetic material contained in a cell matches what was intended to be built - and when it is not the case, to locate the discrepancies and estimate their severity. In terms of reproducibility/reliability, the QC step is crucial. Failure at this step requires repetition of the construction and/or sequencing steps. When performed manually or semi-manually QC is an extremely time-consuming, error prone process, which scales very poorly with the number of constructs and their complexity. To make QC frictionless and more reliable, cMatch performs an operation we have called “construct-matching” and automates it. Construct-matching is more thorough than simple sequence-matching, as it matches at the functional level-and quantifies the matching at the individual component level and across the whole construct. Two algorithms (called CM_1 and CM_2) are presented. They differ according to the nature of their inputs. CM_1 is the core algorithm for construct-matching and is to be used when input sequences are long enough to cover constructs in their entirety (e.g., obtained with methods such as next generation sequencing). CM_2 is an extension designed to deal with shorter data (e.g., obtained with Sanger sequencing), and that need recombining. Both algorithms are shown to yield accurate construct-matching in a few minutes (even on hardware with limited processing power), together with a set of metrics that can be used to improve the robustness of the decision-making process. To ensure reliability and reproducibility, cMatch builds on the highly validated pairwise-matching Smith-Waterman algorithm. All the tests presented have been conducted on synthetic data for challenging, yet realistic constructs - and on real data gathered during studies on a metabolic engineering example (lycopene production).

Biotechnologies to Bridge the Schism in the Bioeconomy

Schism is the new normal for the bioeconomy concept. Since its proliferation in governments, the concept has been adapted to fit national or regional exigencies. Earlier this century the knowledge-based bioeconomy (KBBE) in Europe was seen as a technical and knowledge fix in the evolving sustainability landscape. At the OECD, the concept was further honed by imagining a future where biotechnologies contribute significantly to economic growth and development. Countries started to make national bioeconomy strategies. Some countries have diverged and made the bioeconomy both much larger and more general, involving a wide variety of sectors, such as industry, energy, healthcare, agriculture, aquaculture, forestry and fishing. Whatever the approach, what seems to be consistent is the need to reconcile environmental, social and economic sustainability. This paper attempts to establish one schism that could have ramifications for the future development of the bioeconomy. Some countries, including some of the largest economies but not exclusively so, are clearly following a biotechnology model, whereas others are clearly not. In the wake of the COVID-19 pandemic, biotechnologies offer outstanding potential in healthcare, although this sector is by no means included in all bioeconomy strategies. The paper also attempts to clarify how biotechnologies can address the grand challenges and the United Nations Sustainable Development Goals. The communities of scientists seem to have no difficulty with this, but citizens and governments find it more difficult. In fact, some biotechnologies are already well established, whereas others are emerging and more controversial.

Building the UK's industrial base in engineering biology

The paper describes the strategy and components that have been put in place to build the UK's research and industrial base in Engineering Biology. The initial section of the paper provides a brief historical overview of the development of the field in the United Kingdom. This comprised, principally, a major report by the Royal Academy of Engineering and a strategic roadmap for synthetic biology, together with the establishment of six new synthetic biology research centres, a national centre for the industrial translation of synthetic biology and five biofoundries. The next section of the paper describes the UK government's policy for the field. Important elements of the implementation of the policy comprises people, Infrastructure, Business Environment and place. In this context, a number of important areas are addressed-including industrial translation; building an expert workforce and nucleating, incubating and accelerating a new engineering biology industry in the United Kingdom. The final portion of the paper addresses the author's view of the way forward. This comprises placing the development of the field, both nationally and internationally, in the context of the development of the Bioeconomy and Climate Change. The final section of the text addresses a specific strategic approach and the implications for the United Kingdom in relation to the development of its industrial base in Engineering Biology.

Addressing the post‐COVID era through engineering biology

Currently, the world is faced with two fundamental issues of great importance, namely climate change and the coronavirus pandemic. These are intimately involved with the need to control climate change and the need to switch from high carbon, unsustainable economies to low carbon economies. Inherent in this approach are the concepts of the bioeconomy and the Green Industrial Revolution. The article addresses both issues, but it, principally, focusses on the development of the bioeconomy. It considers how nations are divided in relation to the use of biotechnology and synthetic biology in terms of their bioeconomy strategies. The article addresses, as a central theme, the nature and role of engineering biology in these developments. Engineering biology is addressed in terms of BioDesign, coupled with high levels of automation (including AI and machine learning) to increase reproducibility and reliability to meet industrial standards. This lends itself to distributed manufacturing of products in a range of fields. Engineering biology is a platform technology that can be applied in a range of sectors. The bioeconomy, as an engine for economic growth is addressed—in terms of moving from oil‐based economies to bio‐based economies—using biomass, for example, using selected lignocellulosic waste as a feedstock.

Build a Sustainable Vaccines Industry with Synthetic Biology

The vaccines industry has not changed appreciably in decades regarding technology, and has struggled to remain viable, with large companies withdrawing from production. Meanwhile, there has been no let-up in outbreaks of viral disease, at a time when the biopharmaceuticals industry is discussing downsizing. The distributed manufacturing model aligns well with this, and the advent of synthetic biology promises much in terms of vaccine design. Biofoundries separate design from manufacturing, a hallmark of modern engineering. Once designed in a biofoundry, digital code can be transferred to a small-scale manufacturing facility close to the point of care, rather than physically transferring cold-chain-dependent vaccine. Thus, biofoundries and distributed manufacturing have the potential to open up a new era of biomanufacturing, one based on digital biology and information systems. This seems a better model for tackling future outbreaks and pandemics.

The Sustainable Path to a Circular Bioeconomy

Circular bioeconomy is gaining prominence in academic, policy, and industry contexts, linking circular economy and bioeconomy agendas in service of sustainability. However, it is at risk of developing in narrow, unsustainable ways. A sustainable path to circular bioeconomies must embrace diverse expert and stakeholder input, multiple solutions, and noneconomic value.

Automation in the Life Science Research Laboratory

Protocols in the academic life science laboratory are heavily reliant on the manual manipulation of tools, reagents and instruments by a host of research staff and students. In contrast to industrial and clinical laboratory environments, the usage of automation to augment or replace manual tasks is limited. Causes of this 'automation gap' are unique to academic research, with rigid short-term funding structures, high levels of protocol variability and a benevolent culture of investment in people over equipment. Automation, however, can bestow multiple benefits through improvements in reproducibility, researcher efficiency, clinical translation, and safety. Less immediately obvious are the accompanying limitations, including obsolescence and an inhibitory effect on the freedom to innovate. Growing the range of automation options suitable for research laboratories will require more flexible, modular and cheaper designs. Academic and commercial developers of automation will increasingly need to design with an environmental awareness and an understanding that large high-tech robotic solutions may not be appropriate for laboratories with constrained financial and spatial resources. To fully exploit the potential of laboratory automation, future generations of scientists will require both engineering and biology skills. Automation in the research laboratory is likely to be an increasingly critical component of future research programs and will continue the trend of combining engineering and science expertise together to answer novel research questions.

In silico design and automated learning to boost next-generation smart biomanufacturing

The increasing demand for bio-based compounds produced from waste or sustainable sources is driving biofoundries to deliver a new generation of prototyping biomanufacturing platforms. Integration and automation of the design, build, test and learn (DBTL) steps in centers like SYNBIOCHEM in Manchester and across the globe (Global Biofoundries Alliance) are helping to reduce the delivery time from initial strain screening and prototyping towards industrial production. Notably, a portfolio of producer strains for a suite of material monomers was recently developed, some approaching industrial titers, in a tour de force by the Manchester Centre that was achieved in less than 90 days. New in silico design tools are providing significant contributions to the front end of the DBTL pipelines. At the same time, the far-reaching initiatives of modern biofoundries are generating a large amount of high-dimensional data and knowledge that can be integrated through automated learning to expedite the DBTL cycle. In this Perspective, the new design tools and the role of the learning component as an enabling technology for the next generation of automated biofoundries are discussed. Future biofoundries will operate under completely automated DBTL cycles driven by in silico optimal experimental planning, full biomanufacturing devices connectivity, virtualization platforms and cloud-based design. The automated generation of robotic build worklists and the integration of machine-learning algorithms will collectively allow high levels of adaptability and rapid design changes toward fully automated smart biomanufacturing.

Engineering Microbes for Remediation of Oil Sands Tailings

Synthetic biology and adaptive laboratory evolution are key tools for developing biotechnology platforms for the remediation of oil sands tailings. However, field deployment and subsequent regulation of engineered and/or evolved strains is rife with uncertainties and risks. Here, we detail an innovation strategy to derisk and deploy engineered bioremediation platforms.

Growing a circular economy with fungal biotechnology: a white paper

Fungi have the ability to transform organic materials into a rich and diverse set of useful products and provide distinct opportunities for tackling the urgent challenges before all humans. Fungal biotechnology can advance the transition from our petroleum-based economy into a bio-based circular economy and has the ability to sustainably produce resilient sources of food, feed, chemicals, fuels, textiles, and materials for construction, automotive and transportation industries, for furniture and beyond. Fungal biotechnology offers solutions for securing, stabilizing and enhancing the food supply for a growing human population, while simultaneously lowering greenhouse gas emissions. Fungal biotechnology has, thus, the potential to make a significant contribution to climate change mitigation and meeting the United Nation’s sustainable development goals through the rational improvement of new and established fungal cell factories. The White Paper presented here is the result of the 2nd Think Tank meeting held by the EUROFUNG consortium in Berlin in October 2019. This paper highlights discussions on current opportunities and research challenges in fungal biotechnology and aims to inform scientists, educators, the general public, industrial stakeholders and policymakers about the current fungal biotech revolution.