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Microplastics pollution is major threat to ecosystems and is impacting abiotic and biotic components. Microplastics are diverse and highly complex contaminants that transport other contaminants and microbes. Current methods to remove microplastics include biodegradation, incineration, landfilling, and recycling. Here we review microplastics with focus on sources, toxicity, and biodegradation. We discuss the role of algae, fungi, bacteria in the biodegradation, and we present biotechnological methods to enhance degradation, e.g., gene editing tools and bioinformatics.

Synthetic biology is a rapidly evolving interdisciplinary field that combines principles from biology, bioengineering, biochemistry, and computational sciences to design and engineer new biological systems for various applications. This thesis focuses on addressing the challenges in engineering large and complex biological circuits. We develop modular modeling frameworks, formal theory, and computer-assisted design (CAD) tools for design and analysis of biological systems at a larger scale. This thesis introduces a new problem of robustness in structured model reduction of dynamical systems and provides bounds on a robustness distance metric for linear and nonlinear systems. With this theory, we show the discrimination and quantification of different mathematical models, considering resource loading effects in biological circuits. Using our proposed model reduction robustness theory and its associated software development, we build a modeling, analysis, and parameter identification pipeline. This pipeline is demonstrated through the characterization of DNA recombination enzymes in a cell-free protein expression system. This pipeline is a general approach to systematically develop mathematical models, infer parameters from experimental data, and guide experimental design choices. Identification of parameters in detailed mathematical models is a major challenge in synthetic biology where only sparse data is available. This prevents the application of our detail-driven modeling approach to larger biological systems. Hence, to address this limitation, we present a formal methods-based approach for specifying and synthesizing implementations for the design of biological circuits. We present a contract-based design framework for synthetic biology. We write formal description of design objectives at a higher level of abstraction without modeling the details of each component. This design framework facilitates the design and prediction of complex synthetic biological circuits at scale. Overall, this thesis contributes to the advancement of synthetic biology by providing novel modeling frameworks, analysis methods, and design approaches. These contributions aim to enable the design and analysis of complex biological systems and foster the systematic engineering of biological circuits.

Synthetic biology seeks to probe fundamental aspects of biological form and function by construction [i.e., (re)synthesis] rather than deconstruction (analysis). In this sense, biological sciences now follow the lead given by the chemical sciences. Synthesis can complement analytic studies but also allows novel approaches to answering fundamental biological questions and opens up vast opportunities for the exploitation of biological processes to provide solutions for global problems. In this review, we explore aspects of this synthesis paradigm as applied to the chemistry and function of nucleic acids in biological systems and beyond, specifically, in genome resynthesis, synthetic genetics (i.e., the expansion of the genetic alphabet, of the genetic code, and of the chemical make-up of genetic systems), and the elaboration of orthogonal biosystems and components.

Synthetic biology seeks to probe fundamental aspects of biological form and function by construction [i.e., (re)synthesis] rather than deconstruction (analysis). In this sense, biological sciences now follow the lead given by the chemical sciences. Synthesis can complement analytic studies but also allows novel approaches to answering fundamental biological questions and opens up vast opportunities for the exploitation of biological processes to provide solutions for global problems. In this review, we explore aspects of this synthesis paradigm as applied to the chemistry and function of nucleic acids in biological systems and beyond, specifically, in genome resynthesis, synthetic genetics (i.e., the expansion of the genetic alphabet, of the genetic code, and of the chemical make-up of genetic systems), and the elaboration of orthogonal biosystems and components.

Cooperativity (homotropic allostery) is the primary mechanism by which evolution steepens the binding curves of biomolecular receptors to produce more responsive input–output behavior in biomolecular systems. Motivated by the ubiquity with which nature employs this effect, over the past 15 years we, together with other groups, have engineered this mechanism into several otherwise noncooperative receptors. These efforts largely aimed to improve the utility of such receptors in artificial biotechnologies, such as synthetic biology and biosensors, but they have also provided the first quantitative, experimental tests of longstanding ideas about the mechanisms underlying cooperativity. In this article, we review the literature on the design of this effect, paying particular attention to the design strategies involved, the extent to which each can be rationally applied to (and optimized for) new receptors, and what each teaches us about the origins and optimization of this important phenomenon.

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.

Recombinant adeno-associated viruses (rAAV) are important gene delivery vehicles for gene therapy applications. Their production relies on plasmid transfection or virus infection of producer cells, which pose a challenge in process scale-up. Here, we describe a template for a transfection-free, helper virus-free rAAV producer cell line using a synthetic biology approach. Three modules were integrated into HEK293 cells including an rAAV genome and multiple inducible promoters controlling the expression of AAV Rep, Cap, and helper coding sequences. The synthetic cell line generated infectious rAAV vectors upon induction. Independent control over replication and packaging activities allowed for manipulation of the fraction of capsid particles containing viral genomes, affirming the feasibility of tuning gene expression profiles in a synthetic cell line for enhancing the quality of the viral vector produced. The synthetic biology approach for rAAV production presented in this study can be exploited for scalable biomanufacturing.

Global warming and climate instability have spurred interest in using renewable carbon resources for the sustainable production of chemicals. Cyanobacteria are ideal cellular factories for carbon-negative production of chemicals owing to their great potentials for directly utilizing light and CO

During the last decades, we have witnessed unprecedented advances in biological engineering and synthetic biology. These disciplines aim to take advantage of gene pathway regulation and gene expression in different organisms, to enable cells to perform desired functions. Yeast has been widely utilized as a model for the study of eukaryotic protein expression while bacteriophage T7RNAP and its promoter constitute the preferred system for prokaryotic protein expression (such as pET-based expression systems). The ability to integrate a T7RNAP-based expression system in yeast could allow for a better understanding of gene regulation in eukaryotic cells, and potentially increase the efficiency and processivity of yeast as an expression system. However, the attempts for the creation of such a system have been unsuccessful to date. This review aims to: (i) summarize the efforts that, for many years, have been devoted to the creation of a T7RNAP-based yeast expression system and ii) provide an overview of the latest advances in knowledge of eukaryotic transcription and translation that could lead to the construction of a successful T7RNAP expression system in yeast. The completion of this new expression system would allow to further expand the toolkit of yeast in synthetic biology and ultimately contribute to boost yeast usage as a key cell factory in sustainable biorefinery and circular economy., The work was supported by the Fundacao para a Ciencia e a Tecnologia [UIDB/04469/2020]; Fundacao para a Ciencia e a Tecnologia [UI/BD/151411/2021]., info:eu-repo/semantics/publishedVersion

The use of synthetic biological circuits to deal with numerous biological challenges has been proposed in several studies, but its implementation is still remote. A major problem encountered is the complexity of the cellular engineering needed to achieve complex biological circuits and the lack of general-purpose biological systems. The generation of re-programmable circuits can increase circuit flexibility and the scalability of complex cell-based computing devices. Here we present a new architecture to produce reprogrammable biological circuits that allow the development of a variety of different functions with minimal cell engineering. We demonstrate the feasibility of creating several circuits using only a small set of engineered cells, which can be externally reprogrammed to implement simple logics in response to specific inputs. In this regard, depending on the computation needs, a device composed of a number of defined cells can generate a variety of circuits without the need of further cell engineering or rearrangements. In addition, the inclusion of a memory module in the circuits strongly improved the digital response of the devices. The reprogrammability of biological circuits is an intrinsic capacity that is not provided in electronics and it may be used as a tool to solve complex biological problems. The laboratories of F.P. and E.dN. are supported by a coordinated grant from the Ministry of Science, Innovation, and Universities [PID2021-124723NB-C21/C22 and FEDER, TED2021-131562B-100]; Government of Catalonia [2017 SGR 799, AEI-PID2020-119538RB-I00 to J.M.]; Fundació La Marató de TV3 [332/C/2016]; Office of Naval Research ONR and AFOSR [N62909-18-1-2065 NCE]; F.P. and E.dN. are recipients of an ICREA Acadèmia (Government of Catalonia); Ministry of Science, Innovation and Universities through the Centres of Excellence Severo Ochoa Award, and from the CERCA Programme of the Government of Catalonia and the Unidad de Excelencia María de Maeztu, funded by the AEI [CEX2018-000792-M]. Funding for open access charge: IRB core funding of the group.

The application of synthetic biology approaches to study development opens the possibility to build and manipulate developmental processes to understand them better. Researchers have reconstituted fundamental developmental processes, such as cell patterning and sorting, by engineering gene circuits in vitro. Moreover, new tools have been created that allow for the control of developmental processes in more complex organoids and embryos. Synthetic approaches allow testing of which components are sufficient to reproduce a developmental process and under which conditions as well as what effect perturbations have on other processes. We envision that the future of synthetic developmental biology requires an increase in the diversity of available tools and further efforts to combine multiple developmental processes into one system.

Protein condensates are distinct structures assembled in living cells that concentrate molecules via phase separation in a confined subcellular compartment. In the past decade, remarkable advances have been made to discover the fundamental roles of the condensates in spatiotemporal control of cellular metabolism and physiology and to reveal the molecular principles, components and driving forces that underlie their formation. Here we review the unique properties of the condensates, the promise and hurdles for harnessing them toward purposeful design and manipulation of biological functions in living cells. In particular, we highlight recent advances in mining and understanding the proteinaceous components for creating designer condensates, along with the engineering approaches to manipulate their material properties and biological functions. With these advances, a greater variety of complex organelle-like structures can be built for diverse applications, with unprecedented effects on synthetic biology.

Recent studies have shown that the reconstituted cell-free DNA replisome and in vitro transcription and translation systems from Escherichia coli are highly important in applied and synthetic biology. To date, no attempt has been made to combine those two systems. Here, we study the performance of the mixed two separately exploited systems commercially available as RCR and PURE systems. Regarding the genetic information flow from DNA to proteins, mixtures with various ratios of RCR/PURE gave low protein expression, possibly due to the well-known conflict between replication and transcription or inappropriate buffer conditions. To further increase the compatibility of the two systems, rationally designed reaction buffers with a lower concentration of nucleoside triphosphates in 50 mM HEPES (pH7.6) were evaluated, showing increased performance from RCR/PURE (85%/15%) in a time-dependent manner. The compatibility was also validated in compartmentalized cell-sized droplets encapsulating the same RCR/PURE soup. Our findings can help to better fine-tune the reaction conditions of RCR-PURE systems and provide new avenues for rewiring the central dogma of molecular biology as self-sustaining systems in synthetic cell models. KEY POINTS: • Commercial reconstituted DNA amplification (RCR) and transcription and translation (PURE) systems hamper each other upon mixing. • A newly optimized buffer with a low bias for PURE was formulated in the RCR-PURE mixture. • The performance and dynamics of RCR-PURE were investigated in either bulk or compartmentalized droplets.

One important direction of synthetic biology is to establish desired spatial structures from microbial populations. Underlying this structural development process are different driving factors, among which bacterial motility and chemotaxis serve as a major force. Here, we present an individual-based, biophysical computational framework for mechanistic and multiscale simulation of the spatiotemporal dynamics of motile and chemotactic microbial populations. The framework integrates cellular movement with spatial population growth, mechanical and chemical cellular interactions, and intracellular molecular kinetics. It is validated by a statistical comparison of single-cell chemotaxis simulations with reported experiments. The framework successfully captures colony range expansion of growing isogenic populations and also reveals chemotaxis-modulated, spatial patterns of a two-species amensal community. Partial differential equation-based models subsequently validate these simulation findings. This study provides a versatile computational tool to uncover the fundamentals of microbial spatial ecology as well as to facilitate the design of synthetic consortia for desired spatial patterns.

Formate is a promising, water-soluble C1 feedstock for biotechnology that can be efficiently produced from CO2—but formatotrophy has been engineered in only a few industrially-relevant microbial hosts. We addressed the challenge of expanding the feedstock range of bacterial hosts by adopting Pseudomonas putida as a robust platform for synthetic formate assimilation. Here, the metabolism of a genome-reduced variant of P. putida was radically rewired to establish synthetic auxotrophies that could be functionally complemented by expressing components of the reductive glycine (rGly) pathway. We adopted a modular engineering approach, dividing C1 assimilation in segments composed of both heterologous activities (sourced from Methylobacterium extorquens) and native biochemical reactions. Modular expression of rGly pathway elements enabled growth on formate as carbon source and acetate (predominantly for energy supply), and adaptive laboratory evolution of two lineages of engineered P. putida formatotrophs lead to doubling times of ca. 15 h. We likewise identified emergent metabolic features for assimilation of C1 units in these evolved P. putida populations. Taken together, our results consolidate the landscape of useful microbial platforms that can be implemented for C1-based biotechnological production towards a formate bioeconomy.

According to statistics, in the 185 countries' 36 types of cancer, the morbidity and mortality of lung cancer take the first place, and non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer (International Agency for Research on Cancer, 2018), (Bray et al., 2018). Significantly in many developing countries, limited medical resources and excess population seriously affect the diagnosis and treatment of alung cancer patients. The 21st century is an era of life medicine, big data, and information technology. Synthetic biology is known as the driving force of natural product innovation and research in this era. Based on the research of NSCLC targeted drugs, through the cross-fusion of synthetic biology and artificial intelligence, using the idea of bioengineering, we construct an artificial intelligence assisted medical system and propose a drug selection framework for the personalized selection of NSCLC patients. Under the premise of ensuring the efficacy, considering the economic cost of targeted drugs as an auxiliary decision-making factor, the system predicts the drug effectiveness-cost then. The experiment shows that our method can rely on the provided clinical data to screen drug treatment programs suitable for the patient's conditions and assist doctors in making an efficient diagnosis.

The bottom-up assembly of biological and chemical components opens exciting opportunities to engineer artificial vesicular systems for applications with previously unmet requirements. The modular combination of scaffolds and functional building blocks enables the engineering of complex systems with biomimetic or new-to-nature functionalities. Inspired by the compartmentalized organization of cells and organelles, lipid or polymer vesicles are widely used as model membrane systems to investigate the translocation of solutes and the transduction of signals by membrane proteins. The bottom-up assembly and functionalization of such artificial compartments enables full control over their composition and can thus provide specifically optimized environments for synthetic biological processes. This review aims to inspire future endeavors by providing a diverse toolbox of molecular modules, engineering methodologies, and different approaches to assemble artificial vesicular systems. Important technical and practical aspects are addressed and selected applications are presented, highlighting particular achievements and limitations of the bottom-up approach. Complementing the cutting-edge technological achievements, fundamental aspects are also discussed to cater to the inherently diverse background of the target audience, which results from the interdisciplinary nature of synthetic biology. The engineering of proteins as functional modules and the use of lipids and block copolymers as scaffold modules for the assembly of functionalized vesicular systems are explored in detail. Particular emphasis is placed on ensuring the controlled assembly of these components into increasingly complex vesicular systems. Finally, all descriptions are presented in the greater context of engineering valuable synthetic biological systems for applications in biocatalysis, biosensing, bioremediation, or targeted drug delivery.

Genetic biosensors are integral to synthetic biology. In particular, ligand-inducible prokaryotic transcription factors are frequently used in high-throughput screening, for dynamic feedback regulation, as multilayer logic gates, and in diagnostic applications. In order to provide a curated source that users can rely on for engineering applications, we have developed GroovDB (available at https://groov.bio), a Web-accessible database of ligand-inducible transcription factors that contains all information necessary to build chemically responsive genetic circuits, including biosensor sequence, ligand, and operator data. Ligand and DNA interaction data have been verified against the literature, while an automated data curation pipeline is used to programmatically fetch metadata, structural information, and references for every entry. A custom tool to visualize the natural genetic context of biosensor entries provides potential insights into alternative ligands and systems biology.

Chemically inducible systems represent valuable synthetic biology tools that enable the external control of biological processes. However, their translation to therapeutic applications has been limited because of unfavorable ligand characteristics or the immunogenicity of xenogeneic protein domains. To address these issues, we present a strategy for engineering inducible split protein regulators (INSPIRE) in which ligand-binding proteins of human origin are split into two fragments that reassemble in the presence of a cognate physiological ligand or clinically approved drug. We show that the INSPIRE platform can be used for dynamic, orthogonal and multiplex control of gene expression in mammalian cells. Furthermore, we demonstrate the functionality of a glucocorticoid-responsive INSPIRE platform in vivo and apply it for perturbing an endogenous regulatory network. INSPIRE presents a generalizable approach toward designing small-molecule responsive systems that can be implemented for the construction of new sensors, regulatory networks and therapeutic applications.

Intestinal probiotics are often used for the in situ treatment of diseases, such as metabolic disorders, tumors, and chronic inflammatory infections. Recently, there has been an increased emphasis on intelligent, customized treatments with a focus on long-term efficacy; however, traditional probiotic therapy has not kept up with this trend. The use of synthetic biology to construct gut-engineered probiotics as live therapeutics is a promising avenue in the treatment of specific diseases, such as phenylketonuria and inflammatory bowel disease. These studies generally involve a series of fundamental design issues: choosing an engineered chassis, improving the colonization ability of engineered probiotics, designing functional gene circuits, and ensuring the safety of engineered probiotics. In this review, we summarize the relevant past research, the progress of current research, and discuss the key issues that restrict the widespread application of intestinal engineered probiotic living therapeutics.

Transposons are mobile genetic elements that can give rise to gene mutation and genome rearrangement. Due to their mobility, transposons have been exploited as genetic tools for modification of plants, animals, and microbes. Although a plethora of reviews have summarized families of transposons, the transposons from fermentation bacteria have not been systematically documented, which thereby constrain the exploitation for metabolic engineering and synthetic biology purposes. In this review, we summarize the transposons from the most used fermentation bacteria including Escherichia coli, Bacillus subtilis, Lactococcus lactis, Corynebacterium glutamicum, Klebsiella pneumoniae, and Zymomonas mobilis by literature retrieval and data mining from GenBank and KEGG. We also outline the state-of-the-art advances in basic research and industrial applications especially when allied with other genetic tools. Overall, this review aims to provide valuable insights for transposon-mediated strain improvement. KEY POINTS: • The transposons from the most-used fermentation bacteria are systematically summarized. • The applications of transposons in strain improvement are comprehensively reviewed.

Bacterial communities form biofilms on various surfaces by synthesizing a cohesive and protective extracellular matrix, and these biofilms protect microorganisms against harsh environmental conditions. Bacillus subtilis is a widely used experimental species, and its biofilms are used as representative models of beneficial biofilms. Specifically, B. subtilis biofilms are known to be rich in extracellular polymeric substances (EPS) and other biopolymers such as DNA and proteins like the amyloid protein TasA and the hydrophobic protein BslA. These materials, which form an interconnected, cohesive, three-dimensional polymer network, provide the mechanical stability of biofilms and mediate their adherence to surfaces among other functional contributions. Here, we explored how genetically-encoded components specifically contribute to regulate the growth status, mechanical properties, and antibiotic resistance of B. subtilis biofilms, thereby establishing a solid empirical basis for understanding how various genetic engineering efforts are likely to affect the structure and function of biofilms. We noted discrete contributions to biofilm morphology, mechanical properties, and survival from major biofilm components such as EPS, TasA and BslA. For example, EPS plays an important role in maintaining the stability of the mechanical properties and the antibiotic resistance of biofilms, whereas BslA has a significant impact on the resolution that can be obtained for printing applications. This work provides a deeper understanding of the internal interactions of biofilm components through systematic genetic manipulations. It thus not only broadens the application prospects of beneficial biofilms, but also serves as the basis of future strategies for targeting and effectively removing harmful biofilms.

This article is part of the theme issue ‘Ecological complexity and the biosphere: the next 30 years’., Ecological systems are facing major diversity losses in this century owing to Anthropogenic effects. Habitat loss, overexploitation of resources, invasion and pollution are rapidly jeopardizing the survival of whole communities. It has been recently suggested that a potential approach to flatten the curve of species extinction and prevent catastrophic shifts would involve the engineering of one selected species within one of these communities. Such possibility has started to become part of potential intervention scenarios to preserve biodiversity. Despite its potential, very little is known about the actual dynamic responses of complex ecological networks to the introduction of a synthetic strains derived from a resident species. In this paper, we address this problem by modelling the response of a community to the addition of a synthetic strain derived from a member of a stable ecosystem. We show that the community interaction matrix largely limits the spread of the engineered strain, thus suggesting that species diversity acts as an ecological firewall. The implications for future scenarios of ecosystem engineering are outlined., This work was supported by the PR01018-EC-H2020-FET-Open MADONNA project, the Spanish Ministry of Economy and Competitiveness, grant no. FIS2016-77447-R MINECO/AEI/FEDER, an AGAUR FI-SDUR 2020 grant, and by the Santa Fe Institute, where most of this work was done.

As modern life science research shifts from an observational field of science to a field of engineering biology, computational techniques are more relevant to every aspect of the field. Artificial intelligence (AI) is emerging as a massive accelerator of biological engineering for its ability to learn the design paradigms of life (DPoL) and understand the genotype-to-phenotype (G2P) relationships of organisms. The reception has been mixed, however, as opportunities across health, energy, environment, agriculture, and industrial materials are confronted with emerging biosecurity risks across novel pathogens of concern and operational knowledge of biological engineering. There is an urgent need for research to be conducted at the intersection of AI security and biosecurity and the establishment of a violet teaming paradigm where research focused on risk is paired with those focused on the opportunity to minimize the downside and maximize the upside provided by AI in the life sciences.

Plasmids are circular double-stranded DNA and have been the workhorse of molecular biology. They can also be adopted by more complex organisms to influence how their cells behave. Importantly, this means they can be leveraged to study intricate molecular networks, and gene-function relationships, and hold promise as therapeutic devices. Thus, the ability to deliver and control their activity will not only advance their utility in research fields such as developmental and molecular biology but also expedite their translation to clinical settings. In this regard, light is a convenient stimulus as it is non-invasive, and its properties and application can be adjusted to minimise cellular damage. However, examples of light-controlled plasmid are limited, with the majority displaying poor light-dependent activation, or necessitating specific sequences that limit their use. This thesis outlines the development of a general strategy to deliver light-activated plasmids. This approach relied on photoblocking groups placed at the promoter, which could be removed in response to UV light. This strategy was used to control two ubiquitous bacterial and mammalian promoters. Cell-free reactions with the T7 promoter could be tightly repressed until the UV stimulus was applied. Likewise, light-regulated transcription and translation from the CMV promoter were also demonstrated in mammalian cells, although the photomodulation efficiency was more modest. However, this strategy failed to work on the tac and Sp6 promoters, which is likely due to the difference in binding interactions between the promoter and their cognate RNA polymerase partner. Thus, although this strategy worked well for the T7 promoter in cell-free reactions, the promoter dependency would mean that optimisation is required when the strategy is adopted to photocage alternative promoters. Furthermore, an outstanding challenge needs to be overcome before plasmids can be used for therapy: the inefficient delivery of large negatively charged molecules into cells. Initial studies in this regard were made, and suggestions to enable plasmid delivery were outlined. Unlike previous examples, this technology has the potential to be sequence agnostic, meaning it could be adaptable to any plasmid, greatly expanding its scope.

The Design-Build-Test-Learn cycle is the main approach of synthetic biology to re-design and create new biological parts and systems, targeting the solution for complex and challenging paramount problems. The applications of the novel designs range from biosensing and bioremediation of water pollutants (e.g. heavy metals) to drug discovery and delivery (e.g. cancer treatment) or biofuel production (e.g. butanol and ethanol), amongst others. Standardisation, predictability and automation are crucial elements for synthetic biology to efficiently attain these objectives. Mathematical modelling is a powerful tool that allows us to understand, predict, and control these systems, as shown in many other disciplines such as particle physics, chemical engineering, epidemiology and economics. Yet, the inherent difficulties of using mathematical models substantially slowed their adoption by the synthetic biology community. Researchers might develop different competing model alternatives in absence of in-depth knowledge of a system, consequently being left with the burden of with having to find the best one. Models also come with unknown and difficult to measure parameters that need to be inferred from experimental data. Moreover, the varying informative content of different experiments hampers the solution of these model selection and parameter identification problems, adding to the scarcity and noisiness of laborious-to-obtain data. The difficulty to solve these non-linear optimisation problems limited the widespread use of advantageous mathematical models in synthetic biology, broadening the gap between computational and experimental scientists. In this work, I present the solutions to the problems of parameter identification, model selection and experimental design, validating them with in vivo data. First, I use Bayesian inference to estimate model parameters, relaxing the traditional noise assumptions associated with this problem. I also apply information-theoretic approaches to evaluate the amount of information extracted from experiments (entropy gain). Next, I define methodologies to quantify the informative content of tentative experiments planned for model selection (distance between predictions of competing models) and parameter inference (model prediction uncertainty). Then, I use the two methods to define efficient platforms for optimal experimental design and use a synthetic gene circuit (the genetic toggle switch) to substantiate the results, computationally and experimentally. I also expand strategies to optimally design experiments for parameter identification to update parameter information and input designs during the execution of these (on-line optimal experimental design) using microfluidics. Finally, I developed an open-source and easy-to-use Julia package, BOMBs.jl, automating all the above functionalities to facilitate their dissemination and use amongst the synthetic biology community.

Photosynthetic microalgae offer a biotechnological solution to current climate concerns and the growing demand for food, bioproducts and bulk chemicals. As naturally efficient producers of carbohydrates, lipids, proteins and pigments, microalgae are a sustainable platform in which to realise the demand for high-value compounds. Moreover, they are amenable to metabolic engineering to produce other such molecules, including those with medicinal or therapeutic potential. The challenge however is to find solutions to the current bottlenecks, a major one of which is the challenge of microalgal scale-up. This project uses strains of the green microalga *Chlamydomonas reinhardtii*, UVM4 which is cell-wall deficient and RSW2 that has an intact cell wall. Both strains had previously been engineered to produce the diterpenoid, casbene, by introduction of the *Jatropha curcas* gene encoding casbene synthase. Two constructs were used, PM50, where the casbene synthase gene is under the control of the HSP70/RBCS2 promoter and includes a chloroplast transit peptide, and PM51, which in addition includes a thiamine dependent riboswitch (CrTHI4_4N). Casbene-producing *C. reinhardtii* strains were characterised under standard laboratory conditions of 25ºC and 90 μmol s-1 m-2 in Tris-Acetate Phosphate media (TAP) and found to reliably produce casbene when measured by gas-chromatography mass-spectrometry. Casbene production in strains ranged from 0.064 ± 0.074 mg l-1 to 16.7 ± 0.66 mg l-1 with RSW2::PM50#B08 being the best. The results of this work provided a reference against which to compare diterpenoid production in outdoor conditions. Casbene-producing strains RSW2::PM50#B08, UVM4::PM50#B12 and UVM4::PM51#E09 were taken forward for experiments in the outdoor facility located in the Botanic Garden at the University of Cambridge. Strains were inoculated in 10 l hanging bags, and the impact of environmental conditions during Summer and Autumn, the walled versus cell wall deficient phenotype, and the ability of a repressible riboswitch system to regulate diterpenoid production were investigated by measuring a range of abiotic and biotic factors alongside casbene production. During the Summer, casbene titer reached a maximum of 0.17 ± 0.05 mg l-1 compared to 0.061 ± 0.008 mg l-1 in Autumn. Cell walled RSW2::PM50#B08 produced 2.3-fold more casbene than cell wall deficient UVM4::PM50#B12. To prevent any impact on biomass by engineered pathways, a construct was made where casbene synthase was regulated by a thiamine repressible riboswitch. Preliminary experiments showed that the riboswitch worked to turn casbene synthase off, however it was not possible to show casbene production. Observations of microalgal growth and casbene production in natural settings informed further investigations. Temperature, light intensity, media type and algae-bacteria co-cultures were further investigated under controlled laboratory conditions. Increasing temperature improved growth and casbene production, although this decreased when the upper limit of temperature and light thresholds were tested, 38ºC and 200 μmol s-1 m-2, respectively. Casbene titer increased when grown at lower light intensity (45 μmol s-1 m-2) and when grown heterotrophically in TAP in the dark, strain UVM4::PM50#B12 produced 2.3 ± 0.4 mg l-1 of casbene. When grown in High Salt Medium (HSM) under normal laboratory conditions, growth was much slower and casbene production was an order of magnitude lower than in TAP medium. Preliminary investigations of mutualistic microalgae-bacteria co-cultures suggested that bacteria can improve casbene production two-fold, compared to axenic *C. reinhardtii* cultures. The experience of moving through scales of cultivation revealed challenges and solutions for translation and commercialization of algae biotechnology beyond the lab. This work highlighted the success of engineered strains at scale and identified that many abiotic and biotic factors can strongly influence the success or failure of cultures in outdoor settings. This work has provided new insights into microalgae cultivation practices, which are key to developing microalgae as next-generation, low-cost, sustainable, scalable, and high-productivity systems.

Encapsulated cell-based therapies involve the use of genetically-modified cells embedded in a material in order to produce a therapeutic agent in a specific location in the patient’s body. This approach has shown great potential in animal model systems for treating diseases such as type I diabetes or cancer, with selected approaches having been tested in clinical trials. Despite the promise shown by encapsulated cell therapy, though, there are safety concerns yet to be addressed, such as the escape of the engineered cells from the encapsulation material and the resulting production of therapeutic agents at uncontrolled sites of the body. For that reason, there is great interest in the implementation of safety switches that protect from those side effects. Here, we develop a material-genetic interface as safety switch for engineered mammalian cells embedded into hydrogels. Our switch allows the therapeutic cells to sense whether they are embedded in the hydrogel by means of a synthetic receptor and signaling cascade that link transgene expression to the presence of an intact embedding material. The system design is highly modular, allowing its flexible adaptation to other cell types and embedding materials. This autonomously acting switch constitutes an advantage over previously described safety switches, which rely on user-triggered signals to modulate activity or survival of the implanted cells. We envision that the concept developed here will advance the safety of cell therapies and facilitate their translation to clinical evaluation.Graphical abstract

Cyanobacteria represent a treasure trove of uncovered natural products (NPs) and unbeknown biosynthetic machinery. Currently the exponential rise in genome sequencing of cyanobacteria and other organisms has revealed a wealth of biosynthetic gene clusters, many of which cannot be linked to a NP. This work describes the investigation of cyanobacterial strains for the presence of non-ribosomal peptide synthase (NRPS) and polyketide synthase (PKS) genes screened by PCR and Sanger sequencing. In addition to whole genome sequencing (WGS) using Illumina and Oxford Nanopore was undertaken of selected strains. Bioinformatic tools were used to detect biosynthetic gene clusters (BGCs) and identify regions of interest. Furthermore, publicly available data, in the form of publications and nucleotide data from genome assemblies was gathered to form several datasets to analyse and link cyanobacterial metabolites to their genomes, and to uncover the diversity of cyanobacterial NPs. Recent development has been undergoing to establish heterologous expression tools for cyanobacteria. Currently only a dozen cyanobacterial natural products have been heterologously expressed, this work details the heterologous expression of a ribosomally synthesised and post-translationally modified peptide (RiPP) named viridisamide A from Oscillatoria nigro-viridis PCC 7112 using the DiPaC method. This thesis also describes the use of this method for the cloning of the Fischerazole BGC from Fischerella sp. 9431. Furthermore, the NP cyclomarin A, a marine natural product from an actinomycetes rather than a cyanobacterium, which possesses potent bioactivities against both tuberculosis and malaria was investigated. Here precursor directed biosynthesis of the fermented strain Streptomyces sp. BCC41611 was used to created halogenated cyclomarin variants. In addition, synthetic chemistry methods were used to functionalise the epoxide of the biosynthesised NP by azidolysis and copper(I) catalysed alkyne-azide cycloaddition. Lastly, the halogenase VirX1 from the cyanophage syn10 was studied. This phage infects the marine cyanobacterial genera Synechococcus and Prochlorococcus which are responsible for over a quarter of global photosynthesis. Here, the halogenase was investigated in order to attempt to uncover its natural substrates. "This work was supported by the University of St Andrews (School of Chemistry), IBioIC, MASTS and Xanthella [grant number ACH7-BDTPRG]. Conference attendance was supported by the RSC Researcher Development Grant [D22-5593926529]."--Funding

In this paper, circular cross-section microchannels with 3-D lattice arrangements are designed and fabricated using the Mosquito method in order to construct on-off valves. The 3-D microchannels with on-off valves consist of two types of lines: the flow lines for chemical liquid flow and the control lines to activate the valves. We confirmed that both a circular cross-section and a PDMS with low elastic modulus used as the microchannel material contribute to a valve that can be closed with a lower pressure. Then, we demonstrated liquid flow to evaluate the functionality of the valve. Fluorescein solution was flown into a flow line. We found that the fluorescence intensity decreases at the intersection between the flow and control lines when the flow line is closed by the inflation of the control line, experimentally confirming the functionality of the valve microchannels fabricated via the Mosquito method.

Nadzor imunskih celic T, ki izražajo himerni antigenski receptor (CAR-T celice, angl. Chimeric Antigen Receptor T cells) z uporabo destabilizacijskih domen, je pomembno orodje za natančno in prilagodljivo regulacijo aktivnosti celic CAR-T. Destabilizacijske domene služijo kot varnostna stikala in omogočajo regulacijo aktivnosti celic CAR-T, preko modulacije stabilnosti himernega antigenskega receptorja (CAR) na površini celic z uporabo majhnih molekul. Z njihovo uporabo lahko omejimo stranske učinke in resne zaplete povezane s CAR-T celično terapijo, ki so predvsem posledica njihove prekomerne aktivacije. Do danes že poznamo nekaj nadzornih sistemov na osnovi destabilizacijskih domen (na primer destabilizacijski domeni ecDHFR ali FKBP). Ti sistemi imajo omejeno terapevtsko uporabnost, saj so njihovi ligandi molekule, ki so za človeške celice toksični, ali pa proteinske komponente teh sistemov izvirajo iz drugih organizmov in lahko izzovejo imunski odziv pri človeku. V sklopu magistrske naloge smo se tako osredotočili na razširitev trenutnega nabora destabilizacijskih domen. Uporabili smo destablizacijske domene na osnovi ligand vezavne domene estrogenskega receptorja alfa (ERα), ki se aktivirajo z molekulo 4-OHT, ki je FDA odobreno zdravilo. Pripravljene konstrukte smo vstavili v sesalske celične linije in preverili izražanje receptorja CAR po stimulaciji celic s tarčno majhno molekulo 4-OHT. Destabilizacijskim domenam, ki smo jim dodali CD19 CAR, je prisotnost liganda zagotovila stabilno izražanje receptorja na površini celic. Pričakujemo, da bodo načrtovane destabilizacijske domene pripomogle k razširitvi nabora hitrih, reverzibilnih in prilagodljivih metod za uravnavanje stabilnosti proteinov v živih celicah z uporabo majhnih molekul. The control of immune T cells expressing synthetic chimeric antigen receptors (CAR-T cells) using destabilization domains is an important tool for precise and adaptive regulation of CAR-T cell activity. Destabilization domains serve as safety switches and allow the regulation of CAR-T cell activity by modulating the stability of the CAR receptor on the cell surface using small molecules. Their use could limit the side effects and serious complications associated with CAR-T cell therapy, which are mainly due to their over-activation. To date, several control systems based on destabilization domains are known (e.g. ecDHFR or FKBP destabilization domains), but their number is limited. These systems have limited therapeutic utility because their ligands are molecules that are toxic to human cells, or the protein components of these systems are derived from other organisms and can elicit an immune response in humans. The focus of the MSc thesis was therefore to extend the current set of destabilization domains. We used destabilization domains based on the ligand binding domain of the estrogen receptor α (ERα), which are activated by the FDA approved drug, molecule 4-OHT. The prepared constructs were inserted into mammalian cell lines and the expression of the CAR receptor was verified after stimulation of the cells with the small target molecule 4-OHT. For the destabilization domains to which CD19 CAR was added, the presence of the ligand ensured stable expression of the receptor on the cell surface. We expect that the designed destabilization domains will help to extend the range of rapid, reversible and scalable methods to regulate protein stability in living cells using small molecules.

Z,Z-farnesol (Z,Z-FOH), the all-cis isomer of farnesol, holds enormous potential for application in cosmetics, daily chemicals, and pharmaceuticals. In this study, we aimed to metabolically engineer Escherichia coli to produce Z,Z-FOH. First, we tested five Z,Z-farnesyl diphosphate (Z,Z-FPP) synthases that catalyze neryl diphosphate to form Z,Z-FPP in E. coli. Furthermore, we screened thirteen phosphatases that could facilitate the dephosphorylation of Z,Z-FPP to produce Z,Z-FOH. Finally, through site-directed mutagenesis of cis-prenyltransferase, the optimal mutant strain was able to produce 572.13 mg/L Z,Z-FOH by batch fermentation in a shake flask. This achievement represents the highest reported titer of Z,Z-FOH in microbes to date. Notably, this is the first report on the de novo biosynthesis of Z,Z-FOH in E. coli. This work represents a promising step toward developing synthetic E. coli cell factories for the de novo biosynthesis of Z,Z-FOH and other cis-configuration terpenoids.

The ribosome is the core element of the translational apparatus and displays unrivaled fidelity and efficiency in the synthesis of long polymers with defined sequences and diverse compositions. Repurposing ribosomes for the assembly of nonproteinogenic (bio)polymers is an enticing prospect with implications for fundamental science, bioengineering and synthetic biology alike. Here, we review tethered ribosomes, which feature inseparable large and small subunits that can be evolved for novel function without interfering with native translation. Following a tutorial summary of ribosome structure, function, and biogenesis, we introduce design and optimization strategies for the creation of orthogonal and tethered ribosomes. We also highlight studies, in which (rational) engineering efforts of these designer ribosomes enabled the evolution of new functions. Lastly, we discuss future prospects and challenges that remain for the ribosomal synthesis of tailor-made (bio)polymers.

Recent years have seen exciting progress across human embryo research, including new methods for culturing embryos, transcriptional profiling of embryogenesis and gastrulation, mapping lineage trajectories, and experimenting on stem cell-based embryo models. These advances are beginning to define the dynamical principles of development across stages, tissues and organs, enabling a better understanding of human development before birth in health and disease, and potentially leading to improved treatments for infertility and developmental disorders. However, there are still significant roadblocks en route to this goal. Here, we highlight technical challenges to studying early human development and propose ways and means to overcome some of these constraints.

In ethical reflections on new technologies, a specific type of argument often pops up, which criticizes scientists for "playing God" with these new technological possibilities. The first part of this article is an examination of how these arguments have been interpreted in the literature. Subsequently, this article aims to reinterpret these arguments as symbolic arguments: they are grounded not so much in a set of ontological or empirical claims, but concern symbolic classificatory schemes that ground our value judgments in the first place. Invoking symbolic arguments thus refers to how certain new technologies risk undermining our fundamental symbolic distinctions by which we organize and evaluate our interactions with the world and in society. Such symbolic distinctions, moreover, tend to be resilient against logical argumentation, mainly because they themselves form the basis on which we argue in the cultural and ethical sphere in the first place. Therefore, effective strategies to evaluate and counter these arguments require another approach, showing that these technologies either do not challenge these classifications or, if they do, how they can be accompanied by the proper actions to integrate these technologies into our society.

The physical stability of bacterial chromosomes is important for their in vitro manipulation, while genetic stability is important in vivo. However, extracted naked chromosomes in the open circular form are fragile due to nicks and gaps. Using a nick/gap repair and negative supercoiling reaction (named SCR), we first achieved the negative supercoiling of the whole genomes extracted from

9 Pág. Centro de Biotecnología y Genómica de Plantas, The engineering of nitrogen fixation in plants requires assembly of an active prokaryotic nitrogenase complex, which is yet to be achieved. Nitrogenase biogenesis relies on NifB, which catalyzes the formation of the [8Fe-9S-C] metal cluster NifB-co. This is the first committed step in the biosynthesis of the iron-molybdenum cofactor (FeMo-co) found at the nitrogenase active site. The production of NifB in plants is challenging because this protein is often insoluble in eukaryotic cells, and its [Fe-S] clusters are extremely unstable and sensitive to O2. As a first step to address this challenge, we generated transgenic rice plants expressing NifB from the Archaea Methanocaldococcus infernus and Methanothermobacter thermautotrophicus. The recombinant proteins were targeted to the mitochondria to limit exposure to O2 and to have access to essential [4Fe-4S] clusters required for NifB-co biosynthesis. M. infernus and M. thermautotrophicus NifB accumulated as soluble proteins in planta, and the purified proteins were functional in the in vitro FeMo-co synthesis assay. We thus report NifB protein expression and purification from an engineered staple crop, representing a first step in the biosynthesis of a functional NifDK complex, as required for independent biological nitrogen fixation in cereals., This work was supported, in whole or in part, by the Bill and Melinda Gates Foundation Grants OPP1143172 and INV-005889. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. W.H. and C.B. were supported by doctoral fellowships from AGAUR. X.J. was supported by a doctoral fellowship from Universidad Politécnica de Madrid.

Microbial biosensors sense and report exposures to stimuli, thereby facilitating our understanding of environmental processes. Successful design and deployment of biosensors hinge on the persistence of the microbial host of the genetic circuit, termed the chassis. However, model chassis organisms may persist poorly in environmental conditions. In contrast, non-model organisms persist better in environmental conditions but are limited by other challenges, such as genetic intractability and part unavailability. Here we identify ecological, metabolic, and genetic constraints for chassis development and propose a conceptual framework for the systematic selection of environmental biosensor chassis. We identify key challenges with using current model chassis and delineate major points of conflict in choosing the most suitable organisms as chassis for environmental biosensing. This framework provides a way forward in the selection of biosensor chassis for environmental synthetic biology.

Extrachromosomal circular DNA (eccDNA) with exons and whole genes are common features of eukaryotic cells. Work from especially tumours and the yeast Saccharomyces cerevisiae has revealed that eccDNA can provide large selective advantages and disadvantages. Besides the phenotypic effect due to expression of an eccDNA fragment, eccDNA is different from other mutations in that it is released from 1:1 segregation during cell division. This means that eccDNA can quickly change copy number, pickup secondary mutations and reintegrate into a chromosome to establish substantial genetic variation that could not have evolved via canonical mechanisms. We propose a unifying 5-factor model for conceptualizing the eccDNA load of a eukaryotic cell, emphasizing formation, replication, segregation, selection and elimination. We suggest that the magnitude of these sequential events and their interactions determine the copy number of eccDNA in mitotically dividing cells. We believe that our model will provide a coherent framework for eccDNA research, to understand its biology and the factors that can be manipulated to modulate eccDNA load in eukaryotic cells.

As a new interdisciplinary field, synthetic biology has led to valuable innovations in the fields of medicine, chemistry, agriculture, energy and environment. In this paper, we systematically review the development status of global synthetic biology in the past six years, and make an in-depth benchmarking analysis of the field in China. With the aid of Scopus and SciVal, we analyze the scholarly output of synthetic biology in the world and individual countries, including publication distribution, popular journals and eminent institutions. Furthermore, the research focus and concepts, citation impact and collaborations are also examined using numerical index methods such as the field-weighted citation impact (FWCI) and relative activity index (RAI), showing the differences between data more intuitively. This study aims to offer a comprehensive understanding of the research status of synthetic biology in China and the world, offering a benchmarked overview of the results as a reference to guide the development of this field in the future.

Promoter is a key DNA element located near the transcription start site, which regulates gene transcription by binding RNA polymerase. Thus, the identification of promoters is an important research field in synthetic biology. Nannochloropsis is an important unicellular industrial oleaginous microalgae, and at present, some studies have identified some promoters with specific functions by biological methods in Nannochloropsis, whereas few studies used computational methods. Here, we propose a method called DNPPro (DenseNet-Predict-Promoter) based on densely connected convolutional neural networks to predict the promoter of Nannochloropsis. First, we collected promoter sequences from six Nannochloropsis strains and removed 80% similarity using CD-HIT for each strain to yield a reliable set of positive datasets. Then, in order to construct a robust classifier, within-group scrambling method was used to generate negative dataset which overcomes the limitation of randomly selecting a non-promoter region from the same genome as a negative sample. Finally, we constructed a densely connected convolutional neural network, with the sequence one-hot encoding as the input. Compared with commonly used sequence processing methods, DNPPro can extract long sequence features to a greater extent. The cross-strain experiment on independent dataset verifies the generalization of our method. At the same time, T-SNE visualization analysis shows that our method can effectively distinguish promoters from non-promoters.

While the installation of complex genetic circuits in microorganisms is relatively routine, the synthetic biology toolbox is severely limited in plants. Of particular concern is the absence of combinatorial analysis of regulatory elements, the long design-build-test cycles associated with transgenic plant analysis, and a lack of naming standardization for cloning parts. Here, we use previously described plant regulatory elements to design, build, and test 91 transgene cassettes for relative expression strength. Constructs were transiently transfected into

Modeling in synthetic biology constitutes a powerful means in our continuous search for improved performance with a rational Design-Build-Test-Learn approach. Particularly, kinetic models unravel system dynamics and enable system analysis for guiding experimental design. However, a systematic yet modular pipeline that allows one to identify the appropriate model and guide the experimental designs while tracing the entire model development and analysis is still lacking. Here, we develop BMSS2, a unified tool that streamlines and automates model selection by combining information criterion ranking with upstream and parallel analysis algorithms. These include Bayesian parameter inference

Terpenes are a large class of secondary metabolites with diverse structures and functions that are commonly used as valuable raw materials in food, cosmetics, and medicine. With the development of metabolic engineering and emerging synthetic biology tools, these important terpene compounds can be sustainably produced using different microbial chassis. Currently, yeasts such as

Rapid and flexible plasmid construct generation at scale is one of the most limiting first steps in drug discovery projects. These hurdles can partly be overcome by adopting modular DNA design principles, automated sequence fragmentation, and plasmid assembly. To this end we have designed a robust, multimodule

To constantly supply functional feed resources (FFRs) toward meeting the rapidly growing meat demand, an efficient process alternative to traditional farming is required. Fermentation of synthetic microorganisms serves as an emerging solution, necessitating the coordination of (i) microorganism customization, (ii) product processing, and (iii) effect evaluation using animal experiments.

Concerns regarding food security arise from population growth, global warming, and reduction in arable land. With advances in synthetic biology, food production by microbes is considered to be a promising alternative that would allow rapid food production in an environmentally friendly manner. Moreover, synthetic biology can be adopted to the production of healthier or specifically designed food ingredients (e.g., high-value proteins, lipids, and vitamins) and broaden the utilization of feedstocks (e.g., methanol and CO

Mitigating unintended interferences between circuits and host cells is key to realize applications of synthetic regulatory systems both for bacteria and mammalian cells. Here, we demonstrated that growth burden and circuit dysregulation occurred in a concentration-dependent manner for specific transcription factors (CymR*/CymR) in

Publisher Copyright: © 2022 American Chemical Society. All rights reserved. The rapid-growing and genetically tractable methanogen Methanococcus maripaludis is a promising host organism for the biotechnological conversion of carbon dioxide and renewable hydrogen to fuels and value-Added products. Expansion of its product scope through metabolic engineering necessitates reliable and efficient genetic tools, particularly for genome edits that affect the primary metabolism and cell growth. Here, we have designed a genome-editing toolbox by utilizing Cas12a from Lachnospiraceae bacterium ND2006 (LbCas12a) in combination with the homology-directed repair machinery endogenously present in M. maripaludis. This toolbox can delete target genes with a success rate of up to 95%, despite the hyperpolyploidy of M. maripaludis. For the purpose of demonstrating a large deletion, the M. maripaludis flagellum operon (â 8.9 kbp) was replaced by the Escherichia coli β-glucuronidase gene. To facilitate metabolic engineering and flux balancing in M. maripaludis, the relative strength of 15 different promoters was quantified in the presence of two common growth substrates, either formate or carbon dioxide and hydrogen. This CRISPR/LbCas12a toolbox can be regarded as a reliable and quick method for genome editing in a methanogen.

Metabolite biosensors based on metabolite-responsive transcription factors are key synthetic biology components for sensing and precisely controlling cellular metabolism. Biosensors are often designed under laboratory conditions but are deployed in applications where cellular growth rate differs drastically from its initial characterization. Here we asked how growth rate impacts the minimum and maximum biosensor outputs and the dynamic range, which are key metrics of biosensor performance. Using LacI, TetR, and FadR-based biosensors in Escherichia coli as models, we find that the dynamic range of different biosensors have different growth rate dependencies. We developed a kinetic model to explore how tuning biosensor parameters impact the dynamic range growth rate dependence. Our modeling and experimental results revealed that the effects to dynamic range and its growth rate dependence are often coupled, and the metabolite transport mechanisms shape the dynamic range-growth rate response. This work provides systematic understanding on biosensor’s performance under different growth rates, which will be useful for predicting biosensor’s behavior in broad synthetic biology and metabolic engineering applications.