The power of synthetic biology for bioproduction, remediation and pollution control: The UN's Sustainable Development Goals will inevitably require the application of molecular biology and biotechnology on a global scale

Application of Cyanobacteria as Chassis Cells in Synthetic Biology

Synthetic biology is an exciting new area of research that combines science and engineering to design and build new biological functions and systems. Predictably, with the development of synthetic biology, more efficient and economical photosynthetic microalgae chassis will be successfully constructed, making it possible to break through laboratory research into large-scale industrial applications. The synthesis of a range of biochemicals has been demonstrated in cyanobacteria; however, low product titers are the biggest barrier to the commercialization of cyanobacterial biotechnology. This review summarizes the applied improvement strategies from the perspectives of cyanobacteria chassis cells and synthetic biology. The harvest advantages of cyanobacterial products and the latest progress in improving production strategies are discussed according to the product status. As cyanobacteria synthetic biology is still in its infancy, apart from the achievements made, the difficulties and challenges in the application and development of cyanobacteria genetic tool kits in biochemical synthesis, environmental monitoring, and remediation were assessed.

Navigating the 'moral hazard' argument in synthetic biology's application

Synthetic biology has immense potential to ameliorate widespread environmental damage. The promise of such technology could, however, be argued to potentially risk the public, industry or governments not curtailing their environmentally damaging behavior or even worse exploit the possibility of this technology to do further damage. In such cases, there is the risk of a worse outcome than if the technology was not deployed. This risk is often couched as an objection to new technologies, that the technology produces a moral hazard. This paper describes how to navigate a moral hazard argument and mitigate the possibility of a moral hazard. Navigating moral hazard arguments and mitigating the possibility of a moral hazard will improve the public and environmental impact of synthetic biology.

Building Synthetic Cells─From the Technology Infrastructure to Cellular Entities

The de novo construction of a living organism is a compelling vision. Despite the astonishing technologies developed to modify living cells, building a functioning cell "from scratch" has yet to be accomplished. The pursuit of this goal alone has─and will─yield scientific insights affecting fields as diverse as cell biology, biotechnology, medicine, and astrobiology. Multiple approaches have aimed to create biochemical systems manifesting common characteristics of life, such as compartmentalization, metabolism, and replication and the derived features, evolution, responsiveness to stimuli, and directed movement. Significant achievements in synthesizing each of these criteria have been made, individually and in limited combinations. Here, we review these efforts, distinguish different approaches, and highlight bottlenecks in the current research. We look ahead at what work remains to be accomplished and propose a "roadmap" with key milestones to achieve the vision of building cells from molecular parts.

Synthetic Gene Circuits Combining CRISPR Interference and CRISPR Activation in E. coli: Importance of Equal Guide RNA Binding Affinities to Avoid Context-Dependent Effects

Gene expression control based on clustered regularly interspaced short palindromic repeats (CRISPR) has emerged as a powerful approach for constructing synthetic gene circuits. While the use of CRISPR interference (CRISPRi) is already well-established in prokaryotic circuits, CRISPR activation (CRISPRa) is less mature, and a combination of the two in the same circuits is only just emerging. Here, we report that combining CRISPRi with SoxS-based CRISPRa in Escherichia coli can lead to context-dependent effects due to different affinities in the formation of CRISPRa and CRISPRi complexes, resulting in loss of predictable behavior. We show that this effect can be avoided by using the same scaffold guide RNA structure for both complexes.

Biodiversity: the overlooked source of human health

Biodiversity is the measure of the variation of lifeforms in a given ecological system. Biodiversity provides ecosystems with the robustness, stability, and resilience that sustains them. This is ultimately essential for our survival because we depend on the services that natural ecosystems provide (food, fresh water, air, climate, and medicine). Despite this, human activity is driving an unprecedented rate of biodiversity decline, which may jeopardize the life-support systems of the planet if no urgent action is taken. In this article we show why biodiversity is essential for human health. We raise our case and focus on the biomedicine services that are enabled by biodiversity, and we present known and novel approaches to promote biodiversity conservation.

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.

Environmental Galenics: large-scale fortification of extant microbiomes with engineered bioremediation agents

Contemporary synthetic biology-based biotechnologies are generating tools and strategies for reprogramming genomes for specific purposes, including improvement and/or creation of microbial processes for tackling climate change. While such activities typically work well at a laboratory or bioreactor scale, the challenge of their extensive delivery to multiple spatio-temporal dimensions has hardly been tackled thus far. This state of affairs creates a research niche for what could be called Environmental Galenics (EG), i.e. the science and technology of releasing designed biological agents into deteriorated ecosystems for the sake of their safe and effective recovery. Such endeavour asks not just for an optimal performance of the biological activity at stake, but also the material form and formulation of the agents, their propagation and their interplay with the physico-chemical scenario where they are expected to perform. EG also encompasses adopting available physical carriers of microorganisms and channels of horizontal gene transfer as potential paths for spreading beneficial activities through environmental microbiomes. While some of these propositions may sound unsettling to anti-genetically modified organisms sensitivities, they may also fall under the tag of TINA (there is no alternative) technologies in the cases where a mere reduction of emissions will not help the revitalization of irreversibly lost ecosystems.

This article is part of the theme issue ‘Ecological complexity and the biosphere: the next 30 years’.

Emerging landscape of molecular interaction networks: Opportunities, challenges and prospects

Network biology finds application in interpreting molecular interaction networks and providing insightful inferences using graph theoretical analysis of biological systems. The integration of computational bio-modelling approaches with different hybrid network-based techniques provides additional information about the behaviour of complex systems. With increasing advances in high-throughput technologies in biological research, attempts have been made to incorporate this information into network structures, which has led to a continuous update of network biology approaches over time. The newly minted centrality measures accommodate the details of omics data and regulatory network structure information. The unification of graph network properties with classical mathematical and computational modelling approaches and technologically advanced approaches like machine-learning- and artificial intelligence-based algorithms leverages the potential application of these techniques. These computational advances prove beneficial and serve various applications such as essential gene prediction, identification of drug–disease interaction and gene prioritization. Hence, in this review, we have provided a comprehensive overview of the emerging landscape of molecular interaction networks using graph theoretical approaches. With the aim to provide information on the wide range of applications of network biology approaches in understanding the interaction and regulation of genes, proteins, enzymes and metabolites at different molecular levels, we have reviewed the methods that utilize network topological properties, emerging hybrid network-based approaches and applications that integrate machine learning techniques to analyse molecular interaction networks. Further, we have discussed the applications of these approaches in biomedical research with a note on future prospects.

Biologically engineered microbes for bioremediation of electronic waste: Wayposts, challenges and future directions

In the face of a burgeoning stream of e-waste globally, e-waste recycling becomes increasingly imperative, not only to mitigate the environmental and health risks it poses but also as an urban mining strategy for resource recovery of precious metals, rare Earth elements, and even plastics. As part of the continual efforts to develop greener alternatives to conventional approaches of e-waste recycling, biologically assisted degradation of e-waste offers a promising recourse by capitalising on certain microorganisms' innate ability to interact with metals or degrade plastics. By harnessing emerging genetic tools in synthetic biology, the evolution of novel or enhanced capabilities needed to advance bioremediation and resource recovery could be potentially accelerated by improving enzyme catalytic abilities, modifying substrate specificities, and increasing toxicity tolerance. Yet, the management of e-waste presents formidable challenges due to its massive volume, high component complexity, and associated toxicity. Several limitations will need to be addressed before nascent laboratory-scale achievements in bioremediation can be translated to viable industrial applications. Nonetheless, vested groups, involving both start-up and established companies, have taken visionary steps towards deploying microbes for commercial implementation in e-waste recycling.

Versioning biological cells for trustworthy cell engineering

“Full-stack” biotechnology platforms for cell line (re)programming are on the horizon, thanks mostly to (a) advances in gene synthesis and editing techniques as well as (b) the growing integration of life science research with informatics, the internet of things and automation. These emerging platforms will accelerate the production and consumption of biological products. Hence, traceability, transparency, and—ultimately—trustworthiness is required from cradle to grave for engineered cell lines and their engineering processes. Here we report a cloud-based version control system for biotechnology that (a) keeps track and organizes the digital data produced during cell engineering and (b) molecularly links that data to the associated living samples. Barcoding protocols, based on standard genetic engineering methods, to molecularly link to the cloud-based version control system six species, including gram-negative and gram-positive bacteria as well as eukaryote cells, are shown. We argue that version control for cell engineering marks a significant step toward more open, reproducible, easier to trace and share, and more trustworthy engineering biology.

Full traceability and transparency are important to establish trust in engineered cell lines. Here the authors argue that version control for cell engineering marks a significant step toward more open, reproducible, traceable and ultimately more trustworthy engineering biology.

Insect pest management in the age of synthetic biology

Arthropod crop pests are responsible for 20% of global annual crop losses, a figure predicted to increase in a changing climate where the ranges of numerous species are projected to expand. At the same time, many insect species are beneficial, acting as pollinators and predators of pest species. For thousands of years, humans have used increasingly sophisticated chemical formulations to control insect pests but, as the scale of agriculture expanded to meet the needs of the global population, concerns about the negative impacts of agricultural practices on biodiversity have grown. While biological solutions, such as biological control agents and pheromones, have previously had relatively minor roles in pest management, biotechnology has opened the door to numerous new approaches for controlling insect pests. In this review, we look at how advances in synthetic biology and biotechnology are providing new options for pest control. We discuss emerging technologies for engineering resistant crops and insect populations and examine advances in biomanufacturing that are enabling the production of new products for pest control.

Intelligent host engineering for metabolic flux optimisation in biotechnology

Optimising the function of a protein of length N amino acids by directed evolution involves navigating a 'search space' of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is 'making such biology predictable'. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.

Engineering gene overlaps to sustain genetic constructs in vivo

Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, reducing the evolutionary potential of the system and thus increasing its stability over time.

Genomes are translated by triplets of nucleotides on two different strands, allowing for six different reading frames. This permits the existence of gene overlaps, often observed in microbial genomes, where two different proteins are encoded on the same piece of DNA, but in different reading frames. Gene overlaps are classically considered an obstacle for both evolution and genetic engineering, as mutations in overlapping regions likely have pleitrotropic effects on several genes. In 2013, we identified specific evolutionary scenarios where the decrease in evolutionary potential caused by gene overlaps could instead be advantageous and selected for. In this work, we demonstrate the use of gene overlaps in another context where reducing evolutionary potential can be useful: preventing evolution from inactivating synthetic circuits. We show that gene overlaps can be engineered to increase the evolutionary stability of genes that are costly to their hosts, by entangling these costly genes with essential genes.

Toward Full-Stack In Silico Synthetic Biology: Integrating Model Specification, Simulation, Verification, and Biological Compilation

We present the Infobiotics Workbench (IBW), a user-friendly, scalable, and integrated computational environment for the computer-aided design of synthetic biological systems. It supports an iterative workflow that begins with specification of the desired synthetic system, followed by simulation and verification of the system in high-performance environments and ending with the eventual compilation of the system specification into suitable genetic constructs. IBW integrates modeling, simulation, verification, and biocompilation features into a single software suite. This integration is achieved through a new domain-specific biological programming language, the Infobiotics Language (IBL), which tightly combines these different aspects of in silico synthetic biology into a full-stack integrated development environment. Unlike existing synthetic biology modeling or specification languages, IBL uniquely blends modeling, verification, and biocompilation statements into a single file. This allows biologists to incorporate design constraints within the specification file rather than using decoupled and independent formalisms for different in silico analyses. This novel approach offers seamless interoperability across different tools as well as compatibility with SBOL and SBML frameworks and removes the burden of doing manual translations for standalone applications. We demonstrate the features, usability, and effectiveness of IBW and IBL using well-established synthetic biological circuits.

Advancing Undergraduate Synthetic Biology Education: Insights from a Canadian iGEM Student Perspective

The last two decades have seen vigorous activity in synthetic biology research and ever-increasing applications of its technologies. However, pedagogical research pertaining to teaching synthetic biology is scarce, especially when compared to other science and engineering disciplines. Within Canada there are only three universities that offer synthetic biology programs; two of which are at the undergraduate level. Rather than take place in formal academic settings, many Canadian undergraduate students are introduced to synthetic biology through participation in the annual International Genetically Engineered Machine (iGEM) competition. Although the iGEM competition has had a transformative impact on synthetic biology training in other nations, the impact in Canada has been relatively modest. Consequently, the iGEM competition is still a major setting for synthetic biology education in Canada. To promote further development of synthetic biology education, we surveyed undergraduate students from the Canadian iGEM design teams of 2019. We extracted insights from these data using qualitative analysis to provide recommendations for best teaching practices in synthetic biology undergraduate education, which we describe through our proposed Framework for Transdisciplinary Synthetic Biology Education (FTSBE).

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development

Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the Synechocystis sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.

Reversible thermal regulation for bifunctional dynamic control of gene expression in Escherichia coli

Genetically programmed circuits allowing bifunctional dynamic regulation of enzyme expression have far-reaching significances for various bio-manufactural purposes. However, building a bio-switch with a post log-phase response and reversibility during scale-up bioprocesses is still a challenge in metabolic engineering due to the lack of robustness. Here, we report a robust thermosensitive bio-switch that enables stringent bidirectional control of gene expression over time and levels in living cells. Based on the bio-switch, we obtain tree ring-like colonies with spatially distributed patterns and transformer cells shifting among spherical-, rod- and fiber-shapes of the engineered Escherichia coli. Moreover, fed-batch fermentations of recombinant E. coli are conducted to obtain ordered assembly of tailor-made biopolymers polyhydroxyalkanoates including diblock- and random-copolymer, composed of 3-hydroxybutyrate and 4-hydroxybutyrate with controllable monomer molar fraction. This study demonstrates the possibility of well-organized, chemosynthesis-like block polymerization on a molecular scale by reprogrammed microbes, exemplifying the versatility of thermo-response control for various practical uses.

Natural Products, the Fourth Industrial Revolution, and the Quintuple Helix

The profound interconnectedness of the sciences and technologies embodied in the Fourth Industrial Revolution is discussed in terms of the global role of natural products, and how that interplays with the development of sustainable and climate-conscious practices of cyberecoethnopharmacolomics within the Quintuple Helix for the promotion of a healthier planet and society.

Public Attitudes and Willingness to Pay for Cultured Meat: A Cross-Sectional Experimental Study

Previous research has suggested that the general public is divided over their willingness to consider consuming cultured meat (CM) products. As commercial backing for cultured meat startups increases and the public interest in the US, Europe, and developing countries expands, formally evaluating attitudes to these products will become increasingly important. Willingness to pay (WTP) may provide insight into the level of acceptability of CM products, highlight latent societal preferences, and suggest commercial opportunities. To date, no studies have evaluated the societal WTP for CM products. A cross-sectional internet-based survey was distributed to 300 respondents in the US general population using a survey panel design. The mean age was 30 (range: 18–76), and 47% of respondents were male. We presented respondents with a series of scenarios relating to CM products, framing CM burgers as environmentally friendly vs. as a better alternative to traditional burgers. Prior research has highlighted taste and price as areas of societal concern, but no studies have rigorously evaluated the intersection between these considerations. When CM products were framed as being equivalent in taste to conventional meat, and where their environmental benefits were stressed, respondents were willing to pay significantly more than for a traditional burger ($2.11 vs. $1.00). This WTP jumped to $2.66 when framing the CM burger as the best burger, reflecting a 266% premium that consumers were willing to pay for an appropriately framed CM burger. Framing CM burgers as a better alternative to traditional burgers, rather than focusing on their environmental impact, similarly led to the highest desirability ratings. These preferences were also reflected in a contingent valuation discrete choice experiment examining preferences for paying $1 for a traditional burger vs. $2 for a CM burger. These findings support our hypothesis regarding the existence of what we term the gold-standard bias, a cognitive bias that systematically favors a product or service framed as the best available choice over and above its marginal benefit, and has significant and broad implications for feasibility, pricing, and marketing, suggesting the need for further research in this area.

Opportunities at the Interface of Network Science and Metabolic Modeling

Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimization principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.

Contextual dependencies expand the re-usability of genetic inverters

The implementation of Boolean logic circuits in cells have become a very active field within synthetic biology. Although these are mostly focussed on the genetic components alone, the context in which the circuit performs is crucial for its outcome. We characterise 20 genetic NOT logic gates in up to 7 bacterial-based contexts each, to generate 135 different functions. The contexts we focus on are combinations of four plasmid backbones and three hosts, two Escherichia coli and one Pseudomonas putida strains. Each gate shows seven different dynamic behaviours, depending on the context. That is, gates can be fine-tuned by changing only contextual parameters, thus improving the compatibility between gates. Finally, we analyse portability by measuring, scoring, and comparing gate performance across contexts. Rather than being a limitation, we argue that the effect of the genetic background on synthetic constructs expands functionality, and advocate for considering context as a fundamental design parameter.

Sustainable Chemistry - An Interdisciplinary Matrix Approach

Within the framework of green chemistry, the continuous development of new and advanced tools for sustainable synthesis is essential. For this, multi-facetted underlying demands pose inherent challenges to individual chemical disciplines. As a solution, both interdisciplinary technology screening and research can enhance the possibility for groundbreaking innovation. To illustrate the stages from discovery to the implementing of combined technologies, a SusChem matrix model is proposed inspired by natural product biosynthesis. The model describes a multi-dimensional and dynamic exploratory space where necessary interaction is exclusively provided and guided by sustainable themes.

Concomitant prediction of environmental fate and toxicity of chemical compounds

The environmental fate of many functional molecules that are produced on a large scale as precursors or as additives to specialty goods (plastics, fibers, construction materials, etc.), let alone those synthesized by the pharmaceutical industry, is generally unknown. Assessing their environmental fate is crucial when taking decisions on the manufacturing, handling, usage, and release of these substances, as is the evaluation of their toxicity in humans and other higher organisms. While this data are often hard to come by, the experimental data already available on the biodegradability and toxicity of many unusual compounds (including genuinely xenobiotic molecules) make it possible to develop machine learning systems to predict these features. As such, we have created a predictor of the "risk" associated with the use and release of any chemical. This new system merges computational methods to predict biodegradability with others that assess biological toxicity. The combined platform, named BiodegPred (https://sysbiol.cnb.csic.es/BiodegPred/), provides an informed prognosis of the chance a given molecule can eventually be catabolized in the biosphere, as well as of its eventual toxicity, all available through a simple web interface. While the platform described does not give much information about specific degradation kinetics or particular biodegradation pathways, BiodegPred has been instrumental in anticipating the probable behavior of a large number of new molecules (e.g. antiviral compounds) for which no biodegradation data previously existed.

An overview of anoxygenic phototrophic bacteria and their applications in environmental biotechnology for sustainable Resource recovery

Anoxygenic phototrophic bacteria (APB) are a phylogenetically diverse group of organisms that can harness solar energy for their growth and metabolism. These bacteria vary broadly in terms of their metabolism as well as the composition of their photosynthetic apparatus. Unlike oxygenic phototrophic bacteria such as algae and cyanobacteria, APB can use both organic and inorganic electron donors for light-dependent fixation of carbon dioxide without generating oxygen. Their versatile metabolism, ability to adapt in extreme conditions, low maintenance cost and high biomass yield make APB ideal for wastewater treatment, resource recovery and in the production of high value substances. This review highlights the advantages of APB over algae and cyanobacteria, and their applications in photo-bioelectrochemical systems, production of poly-β-hydroxyalkanoates, single-cell protein, biofertilizers and pigments. The ecology of ABP, their distinguishing factors, various physiochemical parameters governing the production of high-value substances and future directions of APB utilization are also discussed.

Modelling co-translational dimerization for programmable nonlinearity in synthetic biology

Nonlinearity plays a fundamental role in the performance of both natural and synthetic biological networks. Key functional motifs in living microbial systems, such as the emergence of bistability or oscillations, rely on nonlinear molecular dynamics. Despite its core importance, the rational design of nonlinearity remains an unmet challenge. This is largely due to a lack of mathematical modelling that accounts for the mechanistic basis of nonlinearity. We introduce a model for gene regulatory circuits that explicitly simulates protein dimerization-a well-known source of nonlinear dynamics. Specifically, our approach focuses on modelling co-translational dimerization: the formation of protein dimers during-and not after-translation. This is in contrast to the prevailing assumption that dimer generation is only viable between freely diffusing monomers (i.e. post-translational dimerization). We provide a method for fine-tuning nonlinearity on demand by balancing the impact of co- versus post-translational dimerization. Furthermore, we suggest design rules, such as protein length or physical separation between genes, that may be used to adjust dimerization dynamics in vivo. The design, build and test of genetic circuits with on-demand nonlinear dynamics will greatly improve the programmability of synthetic biological systems.

Developing a population-state decision system for intelligently reprogramming extracellular electron transfer in Shewanella oneidensis

The unique extracellular electron transfer (EET) ability has positioned electroactive bacteria (EAB) as a major class of cellular chassis for genetic engineering aimed at favorable environmental, energy, and geoscience applications. However, previous efforts to genetically enhance EET ability have often impaired the basal metabolism and cellular growth due to the competition for the limited cellular resource. Here, we design a quorum sensing-based population-state decision (PSD) system for intelligently reprogramming the EET regulation system, which allows the rebalanced allocation of the cellular resource upon the bacterial growth state. We demonstrate that the electron output from Shewanella oneidensis MR-1 could be greatly enhanced by the PSD system via shifting the dominant metabolic flux from initial bacterial growth to subsequent EET enhancement (i.e., after reaching a certain population-state threshold). The strain engineered with this system achieved up to 4.8-fold EET enhancement and exhibited a substantially improved pollutant reduction ability, increasing the reduction efficiencies of methyl orange and hexavalent chromium by 18.8- and 5.5-fold, respectively. Moreover, the PSD system outcompeted the constant expression system in managing EET enhancement, resulting in considerably enhanced electron output and pollutant bioreduction capability. The PSD system provides a powerful tool for intelligently managing extracellular electron transfer and may inspire the development of new-generation smart bioelectrical devices for various applications.

RES transformation for biosynthesis and detoxification

The reactive electrophilic species (RES), typically the molecules bearing α,β-unsaturated carbonyl group, are widespread in living organisms and notoriously known for their damaging effects. Many of the mycotoxins released from phytopathogenic fungi are RES and their contamination to cereals threatens food safety worldwide. However, due to their high reactivity, RES are also used by host organisms to synthesize specific metabolites. The evolutionary conserved glyoxalase (GLX) system scavenges the cytotoxic α-oxoaldehydes that bear RES groups, which cause host disorders and diseases. In cotton, a specialized enzyme derived from glyoxalase I (GLXI) through gene duplications and named as specialized GLXI (SPG), acts as a distinct type of aromatase in the gossypol pathway to transform the RES intermediates into the phenolic products. In this review, we briefly introduce the research progress in understanding the RES, especially the RES-type mycotoxins, the GLX system and SPG, and discuss their application potential in detoxification and synthetic biology.

RetroRules: a database of reaction rules for engineering biology

RetroRules is a database of reaction rules for metabolic engineering (https://retrorules.org). Reaction rules are generic descriptions of chemical reactions that can be used in retrosynthesis workflows in order to enumerate all possible biosynthetic routes connecting a target molecule to its precursors. The use of such rules is becoming increasingly important in the context of synthetic biology applied to de novo pathway discovery and in systems biology to discover underground metabolism due to enzyme promiscuity. Here, we provide for the first time a complete set containing >400 000 stereochemistry-aware reaction rules extracted from public databases and expressed in the community-standard SMARTS (SMIRKS) format, augmented by a rule representation at different levels of specificity (the atomic environment around the reaction center). Such numerous representations of reactions expand natural chemical diversity by predicting de novo reactions of promiscuous enzymes.

Towards engineering and production of artificial spider silk using tools of synthetic biology

Spider silk is one of the strongest biomaterials available in nature. Its mechanical properties make it a good candidate for applications in various fields ranging from protective armour to bandages for wound dressing to coatings for medical implants. Spider silk is formed by an intricate arrangement of spidroins, which are extremely large proteins containing long stretches of repeating segments rich in alanine and glycine. A large amount of research has been directed towards harnessing the spectacular potential of spider silks and using them for different applications. The interdisciplinary approach of synthetic biology is an ideal tool to study these spider silk proteins and work towards the engineering and production of synthetic spider silk. This review aims to highlight the recent progress that has been made in the study of spider silk proteins using different branches of synthetic biology. Here, the authors discuss the different computational approaches, directed evolution techniques and various expression platforms that have been tested for the successful production of spider silk. Future challenges facing the field and possible solutions offered by synthetic biology are also discussed.

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.

Tackling Achilles' Heel in Synthetic Biology: Pairing Intracellular Synthesis of Noncanonical Amino Acids with Genetic-Code Expansion to Foster Biotechnological Applications

For the last two decades, synthetic biologists have been able to unlock and expand the genetic code, generating proteins with unique properties through the incorporation of noncanonical amino acids (ncAAs). These evolved biomaterials have shown great potential for applications in industrial biocatalysis, therapeutics, bioremediation, bioconjugation, and other areas. Our ability to continue developing such technologies depends on having relatively easy access to ncAAs. However, the synthesis of enantiomerically pure ncAAs in practical quantitates for large-scale processes remains a challenge. Biocatalytic ncAA production has emerged as an excellent alternative to traditional organic synthesis in terms of cost, enantioselectivity, and sustainability. Moreover, biocatalytic synthesis offers the opportunity of coupling the intracellular generation of ncAAs with genetic-code expansion to overcome the limitations of an external supply of amino acid. In this minireview, we examine some of the most relevant achievements of this approach and its implications for improving technological applications derived from synthetic biology.

Integrating Enzyme and Metabolic Engineering Tools for Enhanced α-Ionone Production

Metabolic engineering aims to balance intracellular pathways and increase the precursor supply. However, some heterologous enzymes are not evolved to support high flux. To remove the limitation, the catalytic properties of rate-limiting enzymes must be enhanced. Here, we engineered carotenoid cleavage dioxygenase 1 (CCD1), whose intrinsic promiscuity and low activity limited the production of α-ionone in Escherichia coli. Site-directed mutagenesis was carried out to mutate three structural elements of CCD1: an active site loop, η-helices, and α-helices. Furthermore, mutated CCD1 was fused with lycopene ε-cyclase to facilitate substrate channelling. Collectively, these methods improved the α-ionone concentration by >2.5-fold compared to our previously optimized strain. Lastly, the engineered enzyme was used in conjunction with the metabolic engineering strategy to further boost the α-ionone concentration by another 20%. This work deepens our understanding of CCD1 catalytic properties and proves that integrating enzyme and metabolic engineering can be synergistic for a higher microbial production yield.

Revolutionizing agriculture with synthetic biology

Synthetic biology is here to stay and will transform agriculture if given the chance. The huge challenges facing food, fuel and chemical production make it vital to give synthetic biology that chance-notwithstanding the shifts in mindset, training and infrastructure investment this demands. Here, we assess opportunities for agricultural synthetic biology and ways to remove barriers to their realization.

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.

Synthetic biology uses cells as its computing substrate, often based on the genetic circuit concept. In this Perspective, the authors argue that existing synthetic biology approaches based on classical models of computation limit the potential of biocomputing, and propose that living organisms have under-exploited capabilities.

Regulating, Measuring, and Modeling the Viscoelasticity of Bacterial Biofilms

Biofilms occur in a broad range of environments under heterogeneous physicochemical conditions, such as in bioremediation plants, on surfaces of biomedical implants, and in the lungs of cystic fibrosis patients. In these scenarios, biofilms are subjected to shear forces, but the mechanical integrity of these aggregates often prevents their disruption or dispersal. Biofilms' physical robustness is the result of the multiple biopolymers secreted by constituent microbial cells which are also responsible for numerous biological functions. A better understanding of the role of these biopolymers and their response to dynamic forces is therefore crucial for understanding the interplay between biofilm structure and function. In this paper, we review experimental techniques in rheology, which help quantify the viscoelasticity of biofilms, and modeling approaches from soft matter physics that can assist our understanding of the rheological properties. We describe how these methods could be combined with synthetic biology approaches to control and investigate the effects of secreted polymers on the physical properties of biofilms. We argue that without an integrated approach of the three disciplines, the links between genetics, composition, and interaction of matrix biopolymers and the viscoelastic properties of biofilms will be much harder to uncover.

Biochemistry, genetics and biotechnology of glycerol utilization in Pseudomonas species

The use of renewable waste feedstocks is an environment‐friendly choice contributing to the reduction of waste treatment costs and increasing the economic value of industrial by‐products. Glycerol (1,2,3‐propanetriol), a simple polyol compound widely distributed in biological systems, constitutes a prime example of a relatively cheap and readily available substrate to be used in bioprocesses. Extensively exploited as an ingredient in the food and pharmaceutical industries, glycerol is also the main by‐product of biodiesel production, which has resulted in a progressive drop in substrate price over the years. Consequently, glycerol has become an attractive substrate in biotechnology, and several chemical commodities currently produced from petroleum have been shown to be obtained from this polyol using whole‐cell biocatalysts with both wild‐type and engineered bacterial strains. Pseudomonas species, endowed with a versatile and rich metabolism, have been adopted for the conversion of glycerol into value‐added products (ranging from simple molecules to structurally complex biopolymers, e.g. polyhydroxyalkanoates), and a number of metabolic engineering strategies have been deployed to increase the number of applications of glycerol as a cost‐effective substrate. The unique genetic and metabolic features of glycerol‐grown Pseudomonas are presented in this review, along with relevant examples of bioprocesses based on this substrate – and the synthetic biology and metabolic engineering strategies implemented in bacteria of this genus aimed at glycerol valorization.

Synthetic biology toolkits and applications in Saccharomyces cerevisiae

Synthetic biologists construct biological components and systems to look into biological phenomena and drive a myriad of practical applications that aim to tackle current global challenges in energy, healthcare and the environment. While most tools have been established in bacteria, particularly Escherichia coli, recent years have seen parallel developments in the model yeast strain Saccharomyces cerevisiae, one of the most well-understood eukaryotic biological system. Here, we outline the latest advances in yeast synthetic biology tools based on a framework of abstraction hierarchies of parts, circuits and genomes. In brief, the creation and characterization of biological parts are explored at the transcriptional, translational and post-translational levels. Using characterized parts as building block units, the designing of functional circuits is elaborated with examples. In addition, the status and potential applications of synthetic genomes as a genome level platform for biological system construction are also discussed. In addition to the development of a toolkit, we describe how those tools have been applied in the areas of drug production and screening, study of disease mechanisms, pollutant sensing and bioremediation. Finally, we provide a future outlook of yeast as a workhorse of eukaryotic genetics and a chosen chassis in this field.