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.

High methanol-to-formate ratios induce butanol production in Eubacterium limosum

Unlike gaseous C₁ feedstocks for acetogenic bacteria, there has been less attention on liquid C₁ feedstocks, despite benefits in terms of energy efficiency, mass transfer and integration within existing fermentation infrastructure. Here, we present growth of Eubacterium limosum ATCC8486 using methanol and formate as substrates, finding evidence for the first time of native butanol production. We varied ratios of methanol‐to‐formate in batch serum bottle fermentations, showing butyrate is the major product (maximum specific rate 220 ± 23 mmol‐C gDCW^‐1day^‐1). Increasing this ratio showed methanol is the key feedstock driving the product spectrum towards more reduced products, such as butanol (maximum titre 2.0 ± 1.1 mM‐C). However, both substrates are required for a high growth rate (maximum 0.19 ± 0.011 h^‐1) and cell density (maximum 1.2 ± 0.043 gDCW l^‐1), with formate being the preferred substrate. In fact, formate and methanol are consumed in two distinct growth phases – growth phase 1, on predominately formate and growth phase 2 on methanol, which must balance. Because the second growth varied according to the first growth on formate, this suggests butanol production is due to overflow metabolism, similar to 2,3‐butanediol production in other acetogens. However, further research is required to confirm the butanol production pathway in E. limosum, particularly given, unlike other substrates, methanol likely results in mostly NADH generation, not reduced ferredoxin.

Identifying toggle genes from transcriptome-wide scatter: A new perspective for biological regulation

The study of gene expression variability, especially for cancer and cell differentiation studies, has become important. Here, we investigate transcriptome-wide scatter of 23 cell types and conditions across different levels of biological complexity. We focused on genes that act like toggle switches between pairwise replicates of the same cell type, i.e. genes expressed in one replicate and not expressed in the other, sometimes also referred as ON/OFF genes. The proportion of these toggle genes dramatically increases from unicellular to multicellular organization, especially for development and cancer cells. A relevant portion of toggle switches are non-coding genes: in unicellular systems the most represented classes are tRNA and rRNA, while multicellular systems more frequently show lncRNA, sncRNA and pseudogenes. Notably, disease associated microRNAs (miRNAs), pseudogenes and numerous uncharacterized transcripts are present in both development and cancer cells. On top of the known intrinsic and extrinsic factors, our work indicates toggle genes as a novel collective component creating transcriptome-wide variability. This requires further investigation for elucidating both evolutionary and disease processes.

GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis

Gene expression profiling techniques, such as DNA microarray and RNA-Sequencing, have provided significant impact on our understanding of biological systems. They contribute to almost all aspects of biomedical research, including studying developmental biology, host-parasite relationships, disease progression and drug effects. However, the high-throughput data generations present challenges for many wet experimentalists to analyze and take full advantage of such rich and complex data. Here we present GeneCloudOmics, an easy-to-use web server for high-throughput gene expression analysis that extends the functionality of our previous ABioTrans with several new tools, including protein datasets analysis, and a web interface. GeneCloudOmics allows both microarray and RNA-Seq data analysis with a comprehensive range of data analytics tools in one package that no other current standalone software or web-based tool can do. In total, GeneCloudOmics provides the user access to 23 different data analytical and bioinformatics tasks including reads normalization, scatter plots, linear/non-linear correlations, PCA, clustering (hierarchical, k-means, t-SNE, SOM), differential expression analyses, pathway enrichments, evolutionary analyses, pathological analyses, and protein-protein interaction (PPI) identifications. Furthermore, GeneCloudOmics allows the direct import of gene expression data from the NCBI Gene Expression Omnibus database. The user can perform all tasks rapidly through an intuitive graphical user interface that overcomes the hassle of coding, installing tools/packages/libraries and dealing with operating systems compatibility and version issues, complications that make data analysis tasks challenging for biologists. Thus, GeneCloudOmics is a one-stop open-source tool for gene expression data analysis and visualization. It is freely available at http://combio-sifbi.org/GeneCloudOmics.

Mathematical model reveals that heterogeneity in the number of ion transporters regulates the fraction of mouse sperm capacitation

Capacitation is a complex maturation process mammalian sperm must undergo in the female genital tract to be able to fertilize an egg. This process involves, amongst others, physiological changes in flagellar beating pattern, membrane potential, intracellular ion concentrations and protein phosphorylation. Typically, in a capacitation medium, only a fraction of sperm achieve this state. The cause for this heterogeneous response is still not well understood and remains an open question. Here, one of our principal results is to develop a discrete regulatory network, with mostly deterministic dynamics in conjunction with some stochastic elements, for the main biochemical and biophysical processes involved in the early events of capacitation. The model criterion for capacitation requires the convergence of specific levels of a select set of nodes. Besides reproducing several experimental results and providing some insight on the network interrelations, the main contribution of the model is the suggestion that the degree of variability in the total amount and individual number of ion transporters among spermatozoa regulates the fraction of capacitated spermatozoa. This conclusion is consistent with recently reported experimental results. Based on this mathematical analysis, experimental clues are proposed for the control of capacitation levels. Furthermore, cooperative and interference traits that become apparent in the modelling among some components also call for future theoretical and experimental studies.

Screening of Gas Substrate and Medium Effects on 2,3-Butanediol Production with C. ljungdahlii and C. autoethanogenum Aided by Improved Autotrophic Cultivation Technique

Gas fermentation by acetogens of the genus Clostridium is an attractive technology since it affords the production of biochemicals and biofuels from industrial waste gases while contributing to mitigate the carbon cycle alterations. The acetogenic model organisms C. ljungdahlii and C. autoethanogenum have already been used in large scale industrial fermentations. Among the natural products, ethanol production has already attained industrial scale. However, some acetogens are also natural producers of 2,3-butanediol (2,3-BDO), a platform chemical of relevant industrial interest. Here, we have developed a lab-scale screening campaign with the aim of enhancing 2,3-BDO production. Our study generated comparable data on growth and 2,3-BDO production of several batch gas fermentations using C. ljungdahlii and C. autoethanogenum grown on different gas substrates of primary applicative interest (CO2 · H2, CO · CO2, syngas) and on different media featuring different compositions as regards trace metals, mineral elements and vitamins. CO · CO2 fermentation was found to be preferable for the production of 2,3-BDO, and a fair comparison of the strains cultivated in comparable conditions revealed that C. ljungdahlii produced 3.43-fold higher titer of 2,3-BDO compared to C. autoethanogenum. Screening of different medium compositions revealed that mineral elements, Zinc and Iron exert a major positive influence on 2,3-BDO titer and productivity. Moreover, the CO2 influence on CO fermentation was explored by characterizing C. ljungdahlii response with respect to different gas ratios in the CO · CO2 gas mixtures. The screening strategies undertaken in this study led to the production of 2.03 ± 0.05 g/L of 2,3-BDO, which is unprecedented in serum bottle experiments.

Utilizing graph machine learning within drug discovery and development

Graph machine learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types. Herein, we present a multidisciplinary academic-industrial review of the topic within the context of drug discovery and development. After introducing key terms and modelling approaches, we move chronologically through the drug development pipeline to identify and summarize work incorporating: target identification, design of small molecules and biologics, and drug repurposing. Whilst the field is still emerging, key milestones including repurposed drugs entering in vivo studies, suggest GML will become a modelling framework of choice within biomedical machine learning.

Waste-to-nutrition: a review of current and emerging conversion pathways

Residual biomass is acknowledged as a key sustainable feedstock for the transition towards circular and low fossil carbon economies to supply whether energy, chemical, material and food products or services. The latter is receiving increasing attention, in particular in the perspective of decoupling nutrition from arable land demand. In order to provide a comprehensive overview of the technical possibilities to convert residual biomasses into edible ingredients, we reviewed over 950 scientific and industrial records documenting existing and emerging waste-to-nutrition pathways, involving over 150 different feedstocks here grouped under 10 umbrella categories: (i) wood-related residual biomass, (ii) primary crop residues, (iii) manure, (iv) food waste, (v) sludge and wastewater, (vi) green residual biomass, (vii) slaughterhouse by-products, (viii) agrifood co-products, (ix) C₁ gases and (x) others. The review includes a detailed description of these pathways, as well as the processes they involve. As a result, we proposed four generic building blocks to systematize waste-to-nutrition conversion sequence patterns, namely enhancement, cracking, extraction and bioconversion. We further introduce a multidimensional representation of the biomasses suitability as potential as nutritional sources according to (i) their content in anti-nutritional compounds, (ii) their degree of structural complexity and (iii) their concentration of macro- and micronutrients. Finally, we suggest that the different pathways can be grouped into eight large families of approaches: (i) insect biorefinery, (ii) green biorefinery, (iii) lignocellulosic biorefinery, (iv) non-soluble protein recovery, (v) gas-intermediate biorefinery, (vi) liquid substrate alternative, (vii) solid-substrate fermentation and (viii) more-out-of-slaughterhouse by-products. The proposed framework aims to support future research in waste recovery and valorization within food systems, along with stimulating reflections on the improvement of resources' cascading use.

Collagen- and hyaluronic acid-based hydrogels and their biomedical applications

Hydrogels have been widely investigated in biomedical fields due to their similar physical and biochemical properties to the extracellular matrix (ECM). Collagen and hyaluronic acid (HA) are the main components of the ECM in many tissues. As a result, hydrogels prepared from collagen and HA hold inherent advantages in mimicking the structure and function of the native ECM. Numerous studies have focused on the development of collagen and HA hydrogels and their biomedical applications. In this extensive review, we provide a summary and analysis of the sources, features, and modifications of collagen and HA. Specifically, we highlight the fabrication, properties, and potential biomedical applications as well as promising commercialization of hydrogels based on these two natural polymers.

Improving the politics of biotechnological innovations in food security and other sustainable development goals

The unwarranted interference of some environmental non-governmental organisations (ENGOs) in decision-making over genetically modified (GM) crops has prompted calls for politics to be removed from the regulatory governance of these products. However, regulatory systems are inevitably political because their purpose is to decide whether the use of particular products will help or hinder the delivery of public policy objectives. ENGOs are most able to interfere in regulatory decision-making when policy objectives and decision-making criteria are vague, making the process vulnerable to disruption by organisations that have a distinct agenda. Making regulatory decision-making about GM crops and other green biotechnology more resistant to interference therefore requires better politics not the removal of politics. Better politics begins with political leadership making a case for green biotechnology in achieving food security and other sustainable development goals. Such a policy must involve making political choices and cannot be outsourced to science. Other aspects of better politics include regulatory reform to set policy aims and decision-making criteria that encourage innovation as well as control risk, and engagement with civil society that discusses the values behind attitudes to the application of green biotechnology. In short, green biotechnology for sustainable development needs better politics to counter well-organised opposition, to encourage innovation, and to build the trust of civil society for these policies. Removing politics from regulatory governance would be a gift to ENGOs that are opposed to the use of biotechnology.

Nature-Based Biomaterials and Their Application in Biomedicine

Natural polymers, based on proteins or polysaccharides, have attracted increasing interest in recent years due to their broad potential uses in biomedicine. The chemical stability, structural versatility, biocompatibility and high availability of these materials lend them to diverse applications in areas such as tissue engineering, drug delivery and wound healing. Biomaterials purified from animal or plant sources have also been engineered to improve their structural properties or promote interactions with surrounding cells and tissues for improved in vivo performance, leading to novel applications as implantable devices, in controlled drug release and as surface coatings. This review describes biomaterials derived from and inspired by natural proteins and polysaccharides and highlights their promise across diverse biomedical fields. We outline current therapeutic applications of these nature-based materials and consider expected future developments in identifying and utilising innovative biomaterials in new biomedical applications.

Multi-Objective Sustainability Optimization of Biomass Residues to Ethanol via Gasification and Syngas Fermentation: Trade-Offs between Profitability, Energy Efficiency, and Carbon Emissions

This work presents a strategy for optimizing the production process of ethanol via integrated gasification and syngas fermentation, a conversion platform of growing interest for its contribution to carbon recycling. The objective functions (minimum ethanol selling price (MESP), energy efficiency, and carbon footprint) were evaluated for the combinations of different input variables in models of biomass gasification, energy production from syngas, fermentation, and ethanol distillation, and a multi-objective genetic algorithm was employed for the optimization of the integrated process. Two types of waste feedstocks were considered, wood residues and sugarcane bagasse, with the former leading to lower MESP and a carbon footprint of 0.93 USD/L and 3 g CO2eq/MJ compared to 1.00 USD/L and 10 g CO2eq/MJ for sugarcane bagasse. The energy efficiency was found to be 32% in both cases. An uncertainty analysis was conducted to determine critical decision variables, which were found to be the gasification zone temperature, the split fraction of the unreformed syngas sent to the combustion chamber, the dilution rate, and the gas residence time in the bioreactor. Apart from the abovementioned objectives, other aspects such as water footprint, ethanol yield, and energy self-sufficiency were also discussed.

A toolbox for digitally enhanced teaching in synthetic biology

The global pandemic of COVID-19 has forced educational provision to suddenly shift to a digital environment all around the globe. During these extraordinary times of teaching and learning both the challenges and the opportunities of embedding technologically enhanced education permanently became evident. Even though reinforced by constraints due to the pandemic, teaching through digital tools increases the portfolio of approaches to reach learning outcomes in general. In order to reap the full benefits, this Minireview displays various initiatives and tools for distance education in the area of Synthetic Biology in higher education while taking into account specific constraints of teaching Synthetic Biology from a distance, such as collaboration, laboratory and practical experiences. The displayed teaching resources can benefit current and future educators and raise awareness about a diversified inventory of teaching formats as a starting point to reflect upon one's own teaching and its further advancement.

The beauty of biocatalysis: sustainable synthesis of ingredients in cosmetics

Covering: 2015 up to July 2021The market for cosmetics is consumer driven and the desire for green, sustainable and natural ingredients is increasing. The use of isolated enzymes and whole-cell organisms to synthesise these products is congruent with these values, especially when combined with the use of renewable, recyclable or waste feedstocks. The literature of biocatalysis for the synthesis of ingredients in cosmetics in the past five years is herein reviewed.

Recent trends in microbial nanoparticle synthesis and potential application in environmental technology: a comprehensive review

Microbial technology comprising environment in various aspects of pollution monitoring, treatment of pollutants, and energy generation has been put forth by the researchers worldwide in an eco-friendly manner. During the past few decades, this revolution has pronounced microbial cells in green nanotechnology, extending the scope, efficiency, and investment capita at research institutes, industries, and global markets. In the present review, initially, the source for the microbial synthesis of nanoparticles will be discussed involving bacteria, fungi, actinomycetes, microalgae, and viruses. Further, the mechanism and bio-components of microbial cells such as enzymes, proteins, peptides, amino-acids, exopolysaccharides, and others involved in the bio-reduction of metal ions to corresponding metal nanoparticles will be emphasized. The biosynthesized nanoparticles physicochemical properties and bio-reduction methods' advantages compared with synthetic methods will be detailed. To understand the suitability of biosynthesized nanoparticles in a wide range of applications, an overview of its blend of medicine, agriculture, and electronics will be discussed. This will be geared up with its applications specific to environmental aspects such as bioremediation, wastewater treatment, green-energy production, and pollution monitoring. Towards the end of the review, nano-waste management and limitations, i.e., void gaps that tend to impede the application of biosynthesized nanoparticles and microbial-based nanoparticles' prospects, will be deliberated. Thus, the review would claim to be worthy of unwrapping microorganisms sustainability in the emerging field of green nanotechnology.

From Biogas and Hydrogen to Microbial Protein Through Co-Cultivation of Methane and Hydrogen Oxidizing Bacteria

Increasing efforts are directed towards the development of sustainable alternative protein sources among which microbial protein (MP) is one of the most promising. Especially when waste streams are used as substrates, the case for MP could become environmentally favorable. The risks of using organic waste streams for MP production-the presence of pathogens or toxicants-can be mitigated by their anaerobic digestion and subsequent aerobic assimilation of the (filter-sterilized) biogas. Even though methane and hydrogen oxidizing bacteria (MOB and HOB) have been intensively studied for MP production, the potential benefits of their co-cultivation remain elusive. Here, we isolated a diverse group of novel HOB (that were capable of autotrophic metabolism), and co-cultured them with a defined set of MOB, which could be grown on a mixture of biogas and H2/O2. The combination of MOB and HOB, apart from the CH4 and CO2 contained in biogas, can also enable the valorization of the CO2 that results from the oxidation of methane by the MOB. Different MOB and HOB combinations were grown in serum vials to identify the best-performing ones. We observed synergistic effects on growth for several combinations, and in all combinations a co-culture consisting out of both HOB and MOB could be maintained during five days of cultivation. Relative to the axenic growth, five out of the ten co-cultures exhibited 1.1-3.8 times higher protein concentration and two combinations presented 2.4-6.1 times higher essential amino acid content. The MP produced in this study generally contained lower amounts of the essential amino acids histidine, lysine and threonine, compared to tofu and fishmeal. The most promising combination in terms of protein concentration and essential amino acid profile was Methyloparacoccus murrelli LMG 27482 with Cupriavidus necator LMG 1201. Microbial protein from M. murrelli and C. necator requires 27-67% less quantity than chicken, whole egg and tofu, while it only requires 15% more quantity than the amino acid-dense soybean to cover the needs of an average adult. In conclusion, while limitations still exist, the co-cultivation of MOB and HOB creates an alternative route for MP production leveraging safe and sustainably-produced gaseous substrates.

CytokineLink: A Cytokine Communication Map to Analyse Immune Responses-Case Studies in Inflammatory Bowel Disease and COVID-19

Intercellular communication mediated by cytokines is critical to the development of immune responses, particularly in the context of infectious and inflammatory diseases. By releasing these small molecular weight peptides, the source cells can influence numerous intracellular processes in the target cells, including the secretion of other cytokines downstream. However, there are no readily available bioinformatic resources that can model cytokine-cytokine interactions. In this effort, we built a communication map between major tissues and blood cells that reveals how cytokine-mediated intercellular networks form during homeostatic conditions. We collated the most prevalent cytokines from the literature and assigned the proteins and their corresponding receptors to source tissue and blood cell types based on enriched consensus RNA-Seq data from the Human Protein Atlas database. To assign more confidence to the interactions, we integrated the literature information on cell-cytokine interactions from two systems of immunology databases, immuneXpresso and ImmunoGlobe. From the collated information, we defined two metanetworks: a cell-cell communication network connected by cytokines; and a cytokine-cytokine interaction network depicting the potential ways in which cytokines can affect the activity of each other. Using expression data from disease states, we then applied this resource to reveal perturbations in cytokine-mediated intercellular signalling in inflammatory and infectious diseases (ulcerative colitis and COVID-19, respectively). For ulcerative colitis, with CytokineLink, we demonstrated a significant rewiring of cytokine-mediated intercellular communication between non-inflamed and inflamed colonic tissues. For COVID-19, we were able to identify cell types and cytokine interactions following SARS-CoV-2 infection, highlighting important cytokine interactions that might contribute to severe illness in a subgroup of patients. Such findings have the potential to inform the development of novel, cytokine-targeted therapeutic strategies. CytokineLink is freely available for the scientific community through the NDEx platform and the project github repository.

Cell-free synthesis of industrial chemicals and biofuels from carbon feedstocks

The power of biological systems can be harnessed with higher efficiency when biosynthetic reactions are decoupled from cellular physiology. This can be achieved by cell-free synthesis, which relies on the in vitro use of cellular machinery under optimized reaction conditions. As exemplified by the recent development of mRNA vaccines and therapeutics, the cell-free synthesis of biomolecules is fast, efficient and flexible. Cell-free synthesis of industrial chemicals and biofuels is drawing considerable attention as a promising alternative to microbial fermentation processes, which currently show low conversion yields and toxicity to host cells. Here, we provide a brief overview of the history of cell-free synthesis systems and the state-of-the-art cell-free technologies used to produce diverse chemicals and biofuels. We also discuss the future directions of cell-free synthesis that can fully harness the synthetic power of biological systems.

Characterizing and Improving Reaction Times for E. coli-Based Cell-Free Protein Synthesis

Cell-free protein synthesis (CFPS) is a platform biotechnology that has enabled the on-demand synthesis of proteins for a variety of applications. Numerous advances have improved the productivity of the CFPS platform to result in high-yielding reactions; however, many applications remain limited due to long reaction times. To overcome this limitation, we first established the benchmarks reaction times for CFPS across in-house E. coli extracts and commercial kits. We then set out to fine-tune our in-house extract systems to improve reaction times. Through the optimization of reaction composition and titration of low-cost additives, we have identified formulations that reduce reaction times by 30-50% to obtain high protein titers for biomanufacturing applications, and reduce times by more than 50% to reach the sfGFP detection limit for applications in education and diagnostics. Under optimum conditions, we report the visible observation of sfGFP signal in less than 10 min. Altogether, these advances enhance the utility of CFPS as a rapid, user-defined platform.

Spiers Memorial Lecture: CO2 utilization: why, why now, and how?

This introduction to the Faraday Discussion on carbon dioxide utilization (CDU) provides a framework to lay out the need for CDU, the opportunities, boundary conditions, potential pitfalls, and critical needs to advance the required technologies in the time needed. CDU as a mainstream climate-relevant solution is gaining rapid traction as measured by the increase in the number of related publications, the investment activity, and the political action taken in various countries.

Natural-Based Biomaterial for Skin Wound Healing (Gelatin vs. Collagen): Expert Review

Collagen (Col) and gelatin are most extensively used in various fields, particularly in pharmaceuticals and therapeutics. Numerous researchers have proven that they are highly biocompatible to human tissues, exhibit low antigenicity and are easy to degrade. Despite their different sources both Col and gelatin have almost the same effects when it comes to wound healing mechanisms. Considering this, the bioactivity and biological effects of both Col and gelatin have been, and are being, constantly investigated through in vitro and in vivo assays to obtain maximum outcomes in the future. With regard to their proven nutritional values as sources of protein, Col and gelatin products exert various possible biological activities on cells in the extracellular matrix (ECM). In addition, a vast number of novel Col and gelatin applications have been discovered. This review compared Col and gelatin in terms of their structures, sources of derivatives, physicochemical properties, results of in vitro and in vivo studies, their roles in wound healing and the current challenges in wound healing. Thus, this review provides the current insights and the latest discoveries on both Col and gelatin in their wound healing mechanisms.

Does transcriptional heterogeneity facilitate the development of genetic drug resistance?

Non-genetic forms of antimicrobial (drug) resistance can result from cell-to-cell variability that is not encoded in the genetic material. Data from recent studies also suggest that non-genetic mechanisms can facilitate the development of genetic drug resistance. We speculate on how the interplay between non-genetic and genetic mechanisms may affect microbial adaptation and evolution during drug treatment. We argue that cellular heterogeneity arising from fluctuations in gene expression, epigenetic modifications, as well as genetic changes contribute to drug resistance at different timescales, and that the interplay between these mechanisms enhance pathogen resistance. Accordingly, developing a better understanding of the role of non-genetic mechanisms in drug resistance and how they interact with genetic mechanisms will enhance our ability to combat antimicrobial resistance. Also see the video abstract here: https://youtu.be/aefGpdh-bgU.

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.

Comparative analysis of three studies measuring fluorescence from engineered bacterial genetic constructs

Reproducibility is a key challenge of synthetic biology, but the foundation of reproducibility is only as solid as the reference materials it is built upon. Here we focus on the reproducibility of fluorescence measurements from bacteria transformed with engineered genetic constructs. This comparative analysis comprises three large interlaboratory studies using flow cytometry and plate readers, identical genetic constructs, and compatible unit calibration protocols. Across all three studies, we find similarly high precision in the calibrants used for plate readers. We also find that fluorescence measurements agree closely across the flow cytometry results and two years of plate reader results, with an average standard deviation of 1.52-fold, while the third year of plate reader results are consistently shifted by more than an order of magnitude, with an average shift of 28.9-fold. Analyzing possible sources of error indicates this shift is due to incorrect preparation of the fluorescein calibrant. These findings suggest that measuring fluorescence from engineered constructs is highly reproducible, but also that there is a critical need for access to quality controlled fluorescent calibrants for plate readers.

Quantitative Bioreactor Monitoring of Intracellular Bacterial Metabolites in Clostridium autoethanogenum Using Liquid Chromatography-Isotope Dilution Mass Spectrometry

We report a liquid chromatography-isotope dilution mass spectrometry method for the simultaneous quantification of 131 intracellular bacterial metabolites of Clostridium autoethanogenum. A comprehensive mixture of uniformly ¹³C-labeled internal standards (U-¹³C IS) was biosynthesized from the closely related bacterium Clostridium pasteurianum using 4% ¹³C-glucose as a carbon source. The U-¹³C IS mixture combined with ¹²C authentic standards was used to validate the linearity, precision, accuracy, repeatability, limits of detection, and quantification for each metabolite. A robust-fitting algorithm was employed to reduce the weight of the outliers on the quantification data. The metabolite calibration curves were linear with R ² ≥ 0.99, limits of detection were ≤1.0 μM, limits of quantification were ≤10 μM, and precision/accuracy was within RSDs of 15% for all metabolites. The method was subsequently applied for the daily monitoring of the intracellular metabolites of C. autoethanogenum during a CO gas fermentation over 40 days as part of a study to optimize biofuel production. The concentrations of the metabolites were estimated at steady states of different pH levels using the robust-fitting mathematical approach, and we demonstrate improved accuracy of results compared to conventional regression. Metabolic pathway analysis showed that reactions of the incomplete (branched) tricarboxylic acid "cycle" were the most affected pathways associated with the pH shift in the bioreactor fermentation of C. autoethanogenum and the concomitant changes in ethanol production.

Host Systems for the Production of Recombinant Spider Silk

Spider silk is renowned for its impressive mechanical properties. It is one of the strongest known biomaterials, possessing mechanical properties that outmatch both steel and Kevlar. However, the farming of spiders for their silk is unfeasible. Consequently, production of recombinant spider silk proteins (spidroins) in more amenable hosts is an exciting field of research. For large-scale production to be viable, a heterologous silk production system that is both highly efficient and cost effective is essential. Genes encoding recombinant spidroin have been expressed in bacterial, yeast, insect, and mammalian cells, in addition to many other platforms. This review discusses the recent advances in exploiting an increasingly diverse range of host platforms in the heterologous production of recombinant spidroins.

Bayesian inference of gene expression states from single-cell RNA-seq data

Despite substantial progress in single-cell RNA-seq (scRNA-seq) data analysis methods, there is still little agreement on how to best normalize such data. Starting from the basic requirements that inferred expression states should correct for both biological and measurement sampling noise and that changes in expression should be measured in terms of fold changes, we here derive a Bayesian normalization procedure called Sanity (SAmpling-Noise-corrected Inference of Transcription activitY) from first principles. Sanity estimates expression values and associated error bars directly from raw unique molecular identifier (UMI) counts without any tunable parameters. Using simulated and real scRNA-seq datasets, we show that Sanity outperforms other normalization methods on downstream tasks, such as finding nearest-neighbor cells and clustering cells into subtypes. Moreover, we show that by systematically overestimating the expression variability of genes with low expression and by introducing spurious correlations through mapping the data to a lower-dimensional representation, other methods yield severely distorted pictures of the data.

Mimicking the Hierarchical Organization of Natural Collagen: Toward the Development of Ideal Scaffolding Material for Tissue Regeneration

Biological materials found in living organisms, many of which are proteins, feature a complex hierarchical organization. Type I collagen, a fibrous structural protein ubiquitous in the mammalian body, provides a striking example of such a hierarchical material, with peculiar architectural features ranging from the amino acid sequence at the nanoscale (primary structure) up to the assembly of fibrils (quaternary structure) and fibers, with lengths of the order of microns. Collagen plays a dominant role in maintaining the biological and structural integrity of various tissues and organs, such as bone, skin, tendons, blood vessels, and cartilage. Thus, "artificial" collagen-based fibrous assemblies, endowed with appropriate structural properties, represent ideal substrates for the development of devices for tissue engineering applications. In recent years, with the ultimate goal of developing three-dimensional scaffolds with optimal bioactivity able to promote both regeneration and functional recovery of a damaged tissue, numerous studies focused on the capability to finely modulate the scaffold architecture at the microscale and the nanoscale in order to closely mimic the hierarchical features of the extracellular matrix and, in particular, the natural patterning of collagen. All of these studies clearly show that the accurate characterization of the collagen structure at the submolecular and supramolecular levels is pivotal to the understanding of the relationships between the nanostructural/microstructural properties of the fabricated scaffold and its macroscopic performance. Several studies also demonstrate that the selected processing, including any crosslinking and/or sterilization treatments, can strongly affect the architecture of collagen at various length scales. The aim of this review is to highlight the most recent findings on the development of collagen-based scaffolds with optimized properties for tissue engineering. The optimization of the scaffolds is particularly related to the modulation of the collagen architecture, which, in turn, impacts on the achieved bioactivity.

Stepping on the Gas to a Circular Economy: Accelerating Development of Carbon-Negative Chemical Production from Gas Fermentation

Owing to rising levels of greenhouse gases in our atmosphere and oceans, climate change poses significant environmental, economic, and social challenges globally. Technologies that enable carbon capture and conversion of greenhouse gases into useful products will help mitigate climate change by enabling a new circular carbon economy. Gas fermentation usingcarbon-fixing microorganisms offers an economically viable and scalable solution with unique feedstock and product flexibility that has been commercialized recently. We review the state of the art of gas fermentation and discuss opportunities to accelerate future development and rollout. We discuss the current commercial process for conversion of waste gases to ethanol, including the underlying biology, challenges in process scale-up, and progress on genetic tool development and metabolic engineering to expand the product spectrum. We emphasize key enabling technologies to accelerate strain development for acetogens and other nonmodel organisms.

Quasi-robust control of biochemical reaction networks via stochastic morphing

One of the main objectives of synthetic biology is the development of molecular controllers that can manipulate the dynamics of a given biochemical network that is at most partially known. When integrated into smaller compartments, such as living or synthetic cells, controllers have to be calibrated to factor in the intrinsic noise. In this context, biochemical controllers put forward in the literature have focused on manipulating the mean (first moment) and reducing the variance (second moment) of the target molecular species. However, many critical biochemical processes are realized via higher-order moments, particularly the number and configuration of the probability distribution modes (maxima). To bridge the gap, we put forward the stochastic morpher controller that can, under suitable timescale separations, morph the probability distribution of the target molecular species into a predefined form. The morphing can be performed at a lower-resolution, allowing one to achieve desired multi-modality/multi-stability, and at a higher-resolution, allowing one to achieve arbitrary probability distributions. Properties of the controller, such as robustness and convergence, are rigorously established, and demonstrated on various examples. Also proposed is a blueprint for an experimental implementation of stochastic morpher.

Defense Advanced Research Projects Agency: Comment on ‘Engineering biology and the grand challenges: Do we need a new R&D&I model?’

This comment paper refers to the article published by Gauvreau et al. in Engineering Biology in 2018. Gauvreau et al. discussed various civilian models in the private and public sectors that could boost R&D plus Innovation (R&D&I) progress in the environmental sphere. The authors concluded that there is no tried-and-tested R&D&I model for engineering biology that is suited to help solve the problems of many grand and interacting challenges, and further, that the required model will not work without the private sector, so governments must collaborate to develop such a model. However, the authors have not mentioned one of the most famous classic Research & Development (R&D) models used in the creation of disruptive technologies-a unique model of the Defense Advanced Research Projects Agency (DARPA) of the US Department of Defense. The present commentary poses questions about the models currently used in innovative research, known as DARPA-like R&D agencies, and the innovative ecosystems around them.

Responsible innovation: Its role in an era of technological and regulatory transformation

In the development of innovative technology products, companies of all sizes are being encouraged to innovate responsibly and regulators are encouraged to adapt their regulatory systems to be smarter, more proportionate and adaptive to the needs of innovative technologies. The British Standards Institution Responsible Innovation (RI) Guide (Publicly Available Specification [PAS] 440) is an industry-wide standard relevant to both these policy trends. It supports companies by providing a framework to demonstrate the balance between the potential benefits and harms and, if necessary, to take action to maximise the benefits and/or minimise the harms. It includes guidance on engagement with stakeholders and will codify what stakeholders can expect from companies undertaking responsible innovation, paving the way to more harmonious relationships among stakeholders with differing interests and values. A cross-sectoral survey of innovative companies showed that 90% favoured the development of such a standard. PAS 440 was also trialled in two early-stage biotechnology companies and its expected benefits included contributing to coordinated responsible behaviour along a supply chain; better company and stakeholder understanding of the product properties; supporting decision-making on whether or not to start a company; considering the risks of not developing the product and avoiding reputational risks. Benefits were expected to be increasingly significant as the RI standard becomes widely adopted.

Enhanced Collagen-like Protein for Facile Biomaterial Fabrication

We present a collagen-mimetic protein of bacterial origin based upon a modified subdomain of the collagen-like Sc12 protein from Streptococcus pyogenes, as an alternative collagen-like biomaterial platform that is highly soluble, forms stable, homogeneous, fluid-like solutions at elevated concentrations, and that can be efficiently fabricated into hydrogel materials over a broad range of pH conditions. This extended bacterial collagen-like (eBCL) protein is expressed in a bacterial host and purified as a trimeric assembly exhibiting a triple helical secondary structure in its collagen-like subdomain that is stable near physiological solution conditions (neutral pH and 37 °C), as well as over a broad range of pH conditions. We also show how this sequence can be modified to include biofunctional attributes, in particular, the Arg-Gly-Asp (RGD) sequence to elicit integrin-specific cell binding, without loss of structural function. Furthermore, through the use of EDC-NHS chemistry, we demonstrate that members of this eBCL protein system can be covalently cross-linked to fabricate transparent hydrogels with high protein concentrations (at least to 20% w/w). These hydrogels are shown to possess material properties and resistance to enzymatic degradation that are comparable or superior to a type I collagen control. Moreover, such hydrogels containing the constructs with the RGD integrin-binding sequence are shown to promote the adhesion, spreading, and proliferation of C2C12 and 3T3 cells in vitro. Due to its enhanced solubility, structural stability, fluidity at elevated concentrations, ease of modification, and facility of cross-linking, this eBCL collagen-mimetic system has potential for numerous biomedical material applications, where the ease of processing and fabrication and the facility to tailor the sequence for specific biological functionality are desired.

Genetic and metabolic engineering challenges of C1-gas fermenting acetogenic chassis organisms

Unabated mining and utilisation of petroleum and petroleum resources and their conversion to essential fuels and chemicals have drastic environmental consequences, contributing to global warming and climate change. In addition, fossil fuels are finite resources, with a fast-approaching shortage. Accordingly, research efforts are increasingly focusing on developing sustainable alternatives for chemicals and fuels production. In this context, bioprocesses, relying on microorganisms, have gained particular interest. For example, acetogens use the Wood-Ljungdahl pathway to grow on single carbon C1-gases (CO2 and CO) as their sole carbon source and produce valuable products such as acetate or ethanol. These autotrophs can, therefore, be exploited for large-scale fermentation processes to produce industrially relevant chemicals from abundant greenhouse gases. In addition, genetic tools have recently been developed to improve these chassis organisms through synthetic biology approaches. This review will focus on the challenges of genetically and metabolically modifying acetogens. It will first discuss the physical and biochemical obstacles complicating successful DNA transfer in these organisms. Current genetic tools developed for several acetogens, crucial for strain engineering to consolidate and expand their catalogue of products, will then be described. Recent tool applications for metabolic engineering purposes to allow redirection of metabolic fluxes or production of non-native compounds will lastly be covered.

Future trends in synthetic biology in Asia

Synthetic biology research and technology translation has garnered increasing interest from the governments and private investors in Asia, where the technology has great potential in driving a sustainable bio-based economy. This Perspective reviews the latest developments in the key enabling technologies of synthetic biology and its application in bio-manufacturing, medicine, food and agriculture in Asia. Asia-centric strengths in synthetic biology to grow the bio-based economy, such as advances in genome editing and the presence of biofoundries combined with the availability of natural resources and vast markets, are also highlighted. The potential barriers to the sustainable development of the field, including inadequate infrastructure and policies, with suggestions to overcome these by building public-private partnerships, more effective multi-lateral collaborations and well-developed governance framework, are presented. Finally, the roles of technology, education and regulation in mitigating potential biosecurity risks are examined. Through these discussions, stakeholders from different groups, including academia, industry and government, are expectantly better positioned to contribute towards the establishment of innovation and bio-economy hubs in Asia.

Molecular and phenotypic analysis of rodent models reveals conserved and species-specific modulators of human sarcopenia

Sarcopenia, the age-related loss of skeletal muscle mass and function, affects 5-13% of individuals aged over 60 years. While rodents are widely-used model organisms, which aspects of sarcopenia are recapitulated in different animal models is unknown. Here we generated a time series of phenotypic measurements and RNA sequencing data in mouse gastrocnemius muscle and analyzed them alongside analogous data from rats and humans. We found that rodents recapitulate mitochondrial changes observed in human sarcopenia, while inflammatory responses are conserved at pathway but not gene level. Perturbations in the extracellular matrix are shared by rats, while mice recapitulate changes in RNA processing and autophagy. We inferred transcription regulators of early and late transcriptome changes, which could be targeted therapeutically. Our study demonstrates that phenotypic measurements, such as muscle mass, are better indicators of muscle health than chronological age and should be considered when analyzing aging-related molecular data.

ViralLink: An integrated workflow to investigate the effect of SARS-CoV-2 on intracellular signalling and regulatory pathways

The SARS-CoV-2 pandemic of 2020 has mobilised scientists around the globe to research all aspects of the coronavirus virus and its infection. For fruitful and rapid investigation of viral pathomechanisms, a collaborative and interdisciplinary approach is required. Therefore, we have developed ViralLink: a systems biology workflow which reconstructs and analyses networks representing the effect of viruses on intracellular signalling. These networks trace the flow of signal from intracellular viral proteins through their human binding proteins and downstream signalling pathways, ending with transcription factors regulating genes differentially expressed upon viral exposure. In this way, the workflow provides a mechanistic insight from previously identified knowledge of virally infected cells. By default, the workflow is set up to analyse the intracellular effects of SARS-CoV-2, requiring only transcriptomics counts data as input from the user: thus, encouraging and enabling rapid multidisciplinary research. However, the wide-ranging applicability and modularity of the workflow facilitates customisation of viral context, a priori interactions and analysis methods. Through a case study of SARS-CoV-2 infected bronchial/tracheal epithelial cells, we evidence the functionality of the workflow and its ability to identify key pathways and proteins in the cellular response to infection. The application of ViralLink to different viral infections in a context specific manner using different available transcriptomics datasets will uncover key mechanisms in viral pathogenesis.

Green Synthesis of Selenium and Tellurium Nanoparticles: Current Trends, Biological Properties and Biomedical Applications

The synthesis and assembly of nanoparticles using green technology has been an excellent option in nanotechnology because they are easy to implement, cost-efficient, eco-friendly, risk-free, and amenable to scaling up. They also do not require sophisticated equipment nor well-trained professionals. Bionanotechnology involves various biological systems as suitable nanofactories, including biomolecules, bacteria, fungi, yeasts, and plants. Biologically inspired nanomaterial fabrication approaches have shown great potential to interconnect microbial or plant extract biotechnology and nanotechnology. The present article extensively reviews the eco-friendly production of metalloid nanoparticles, namely made of selenium (SeNPs) and tellurium (TeNPs), using various microorganisms, such as bacteria and fungi, and plants' extracts. It also discusses the methodologies followed by materials scientists and highlights the impact of the experimental sets on the outcomes and shed light on the underlying mechanisms. Moreover, it features the unique properties displayed by these biogenic nanoparticles for a large range of emerging applications in medicine, agriculture, bioengineering, and bioremediation.

Statistical Design of Experiments for Synthetic Biology

The design and optimization of biological systems is an inherently complex undertaking that requires careful balancing of myriad synergistic and antagonistic variables. However, despite this complexity, much synthetic biology research is predicated on One Factor at A Time (OFAT) experimentation; the genetic and environmental variables affecting the activity of a system of interest are sequentially altered while all other variables are held constant. Beyond being time and resource intensive, OFAT experimentation crucially ignores the effect of interactions between factors. Given the ubiquity of interacting genetic and environmental factors in biology this failure to account for interaction effects in OFAT experimentation can result in the development of suboptimal systems. To address these limitations, an increasing number of studies have turned to Design of Experiments (DoE), a suite of methods that enable efficient, systematic exploration and exploitation of complex design spaces. This review provides an overview of DoE for synthetic biologists. Key concepts and commonly used experimental designs are introduced, and we discuss the advantages of DoE as compared to OFAT experimentation. We dissect the applicability of DoE in the context of synthetic biology and review studies which have successfully employed these methods, illustrating the potential of statistical experimental design to guide the design, characterization, and optimization of biological protocols, pathways, and processes.

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.

Space-time logic of liver gene expression at sub-lobular scale

The mammalian liver is a central hub for systemic metabolic homeostasis. Liver tissue is spatially structured, with hepatocytes operating in repeating lobules, and sub-lobule zones performing distinct functions. The liver is also subject to extensive temporal regulation, orchestrated by the interplay of the circadian clock, systemic signals and feeding rhythms. However, liver zonation has previously been analysed as a static phenomenon, and liver chronobiology has been analysed at tissue-level resolution. Here, we use single-cell RNA-seq to investigate the interplay between gene regulation in space and time. Using mixed-effect models of messenger RNA expression and smFISH validations, we find that many genes in the liver are both zonated and rhythmic, and most of them show multiplicative space-time effects. Such dually regulated genes cover not only key hepatic functions such as lipid, carbohydrate and amino acid metabolism, but also previously unassociated processes involving protein chaperones. Our data also suggest that rhythmic and localized expression of Wnt targets could be explained by rhythmically expressed Wnt ligands from non-parenchymal cells near the central vein. Core circadian clock genes are expressed in a non-zonated manner, indicating that the liver clock is robust to zonation. Together, our scRNA-seq analysis reveals how liver function is compartmentalized spatio-temporally at the sub-lobular scale.

Solar-Powered Carbon Fixation for Food and Feed Production Using Microorganisms-A Comparative Techno-Economic Analysis

This study evaluates the techno-economic feasibility of five solar-powered concepts for the production of autotrophic microorganisms for food and feed production; the main focus is on three concepts based on hydrogen-oxidizing bacteria (HOB), which are further compared to two microalgae-related concepts. Two locations with markedly different solar conditions are considered (Finland and Morocco), in which Morocco was found to be the most economically competitive for the cultivation of microalgae in open ponds and closed systems (1.4 and 1.9 € kg-1, respectively). Biomass production by combined water electrolysis and HOB cultivation results in higher costs for all three considered concepts. Among these, the lowest production cost of 5.3 € kg-1 is associated with grid-assisted electricity use in Finland, while the highest production cost of >9.1 € kg-1 is determined for concepts using solely photovoltaics and/or photoelectrochemical technology for on-site electricity production and solar-energy conversion to H2 by water electrolysis. All assessed concepts are capital intensive. Furthermore, a sensitivity analysis suggests that the production costs of HOB biomass can be lowered down to 2.1 € kg-1 by optimization of the process parameters among which volumetric productivity, electricity strategy, and electricity costs have the highest cost-saving potentials. The study reveals that continuously available electricity and H2 supply are essential for the development of a viable HOB concept due to the capital intensity of the needed technologies. In addition, volumetric productivity is the key parameter that needs to be optimized to increase the economic competitiveness of HOB production.

Synthetic biology, engineering biology, market expectation

'Engineering biology' is being increasingly adopted as a term by organisations that seek to deliver benefits from 'synthetic biology'. However, are 'engineering biology' and 'synthetic biology' different words with the same meaning or do they signal important differences? By observing how these two terms are currently being described and applied in practice, it is possible to differentiate the two whilst also acknowledging significant overlaps and complementarity. Increasing adoption of the term 'engineering biology' reflects the maturing of synthetic biology since the early years of this century from a research concept to a technological platform that is facilitating the delivery of commercial products and services. The term 'synthetic biology' retains a strong association with its original goal to help make biology engineerable, a challenge that will inevitably continue to stimulate research for decades to come as ever more complex and demanding systems are tackled. In comparison, the term 'engineering biology' relates more commonly to the utilisation of the synthetic biology platform alongside other related technologies to deliver effective solutions in response to increasing market challenges and expectations.

Optimizing enzymatic catalysts for rapid turnover of substrates with low enzyme sequestration

Enzymes are central to both metabolism and information processing in cells. In both cases, an enzyme's ability to accelerate a reaction without being consumed in the reaction is crucial. Nevertheless, enzymes are transiently sequestered when they bind to their substrates; this sequestration limits activity and potentially compromises information processing and signal transduction. In this article, we analyse the mechanism of enzyme-substrate catalysis from the perspective of minimizing the load on the enzymes through sequestration, while maintaining at least a minimum reaction flux. In particular, we ask: which binding free energies of the enzyme-substrate and enzyme-product reaction intermediates minimize the fraction of enzymes sequestered in complexes, while sustaining a certain minimal flux? Under reasonable biophysical assumptions, we find that the optimal design will saturate the bound on the minimal flux and reflects a basic trade-off in catalytic operation. If both binding free energies are too high, there is low sequestration, but the effective progress of the reaction is hampered. If both binding free energies are too low, there is high sequestration, and the reaction flux may also be suppressed in extreme cases. The optimal binding free energies are therefore neither too high nor too low, but in fact moderate. Moreover, the optimal difference in substrate and product binding free energies, which contributes to the thermodynamic driving force of the reaction, is in general strongly constrained by the intrinsic free-energy difference between products and reactants. Both the strategies of using a negative binding free-energy difference to drive the catalyst-bound reaction forward and of using a positive binding free-energy difference to enhance detachment of the product are limited in their efficacy.

A mechanistic model of the BLADE platform predicts performance characteristics of 256 different synthetic DNA recombination circuits

Boolean logic and arithmetic through DNA excision (BLADE) is a recently developed platform for implementing inducible and logical control over gene expression in mammalian cells, which has the potential to revolutionise cell engineering for therapeutic applications. This 2-input 2-output platform can implement 256 different logical circuits that exploit the specificity and stability of DNA recombination. Here, we develop the first mechanistic mathematical model of the 2-input BLADE platform based on Cre- and Flp-mediated DNA excision. After calibrating the model on experimental data from two circuits, we demonstrate close agreement between model outputs and data on the other 111 circuits that have so far been experimentally constructed using the 2-input BLADE platform. Model simulations of the remaining 143 circuits that have yet to be tested experimentally predict excellent performance of the 2-input BLADE platform across the range of possible circuits. Circuits from both the tested and untested subsets that perform less well consist of a disproportionally high number of STOP sequences. Model predictions suggested that circuit performance declines with a decrease in recombinase expression and new experimental data was generated that confirms this relationship.

Precise determination of input-output mapping for multimodal gene circuits using data from transient transfection

The mapping of molecular inputs to their molecular outputs (input/output, I/O mapping) is an important characteristic of gene circuits, both natural and synthetic. Experimental determination of such mappings for synthetic circuits is best performed using stably integrated genetic constructs. In mammalian cells, stable integration of complex circuits is a time-consuming process that hampers rapid characterization of multiple circuit variants. On the other hand, transient transfection is quick. However, it is an extremely noisy process and it is unclear whether the obtained data have any relevance to the input/output mapping of a circuit obtained in the case of a stable integration. Here we describe a data processing workflow, Peakfinder algorithm for flow cytometry data (PFAFF), that allows extracting precise input/output mapping from single-cell protein expression data gathered by flow cytometry after a transient transfection. The workflow builds on the numerically-proven observation that the multivariate modes of input and output expression of multi-channel flow cytometry datasets, pre-binned by the expression level of an independent transfection reporter gene, harbor cells with circuit gene copy numbers distributions that depend deterministically on the properties of a bin. We validate our method by simulating flow cytometry data for seven multi-node circuit architectures, including a complex bi-modal circuit, under stable integration and transient transfection scenarios. The workflow applied to the simulated transient transfection data results in similar conclusions to those reached with simulated stable integration data. This indicates that the input/output mapping derived from transient transfection data using our method is an excellent approximation of the ground truth. Thus, the method allows to determine input/output mapping of complex gene network using noisy transient transfection data.

One of the key features of a gene circuit is its input/output behavior. A few earlier publications attempted to develop methods to extract this behavior using transient transfection of circuit components in mammalian cells. However, the hitherto developed methods are only suitable for circuit with monomodal output distribution. Moreover, the relationship between the extracted I/O mapping and the "ground truth" that would have obtained with stably-integrated circuits, has not been addressed. Here we explore cell populations easily identifiable in flow cytometry data, namely, the peaks of fluorescent readout distribution in cells binned by the common expression value of the transfection reporter, or marker, gene. Using numerical simulations, we find that the distribution of circuit copy number in these cells deterministically depends on marker fluorescence in the noise-dependent manner. Moreover, we find that this is true also in the case of bi-modal output distribution. Using the peaks of input and output distributions, we are able to reconstruct the I/O mapping of the circuit and relate it to the I/O mapping of the stably-integrated circuit. The reconstruction is enabled by a new computational method we call PFAFF. The method is extensively validated with forward-simulated flow cytometry data from stable and transient transfections, with up to seven different circuits. The results show excellent correlation between the I/O behavior extracted by PFAFF from simulated transient transfection data, and the data simulated for stably integrated circuit.