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Synthetic Biology underpins advances in the bioeconomy

Biological systems - including the simplest cells - exhibit a broad range of functions to thrive in their environment. Research in the Imperial College Centre for Synthetic Biology is focused on the possibility of engineering the underlying biochemical processes to solve many of the challenges facing society, from healthcare to sustainable energy. In particular, we model, analyse, design and build biological and biochemical systems in living cells and/or in cell extracts, both exploring and enhancing the engineering potential of biology. 

As part of our research we develop novel methods to accelerate the celebrated Design-Build-Test-Learn synthetic biology cycle. As such research in the Centre for Synthetic Biology highly multi- and interdisciplinary covering computational modelling and machine learning approaches; automated platform development and genetic circuit engineering ; multi-cellular and multi-organismal interactions, including gene drive and genome engineering; metabolic engineering; in vitro/cell-free synthetic biology; engineered phages and directed evolution; and biomimetics, biomaterials and biological engineering.

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  • Journal article
    Kis Z, Shattock R, Shah N, Kontoravdi Ket al., 2019,

    Emerging technologies for low-cost, rapid vaccine manufacture

    , Biotechnology Journal, Vol: 14, ISSN: 1860-6768

    To stop the spread of future epidemics and meet infant vaccination demands in low‐ and middle‐income countries, flexible, rapid and low‐cost vaccine development and manufacturing technologies are required. Vaccine development platform technologies that can produce a wide range of vaccines are emerging, including: a) humanized, high‐yield yeast recombinant protein vaccines; b) insect cell‐baculovirus ADDomer vaccines; c) Generalized Modules for Membrane Antigens (GMMA) vaccines; d) RNA vaccines. Herein, existing and future platforms are assessed in terms of addressing challenges of scale, cost, and responsiveness. To assess the risk and feasibility of the four emerging platforms, the following six metrics are applied: 1) technology readiness; 2) technological complexity; 3) ease of scale‐up; 4) flexibility for the manufacturing of a wide range of vaccines; 5) thermostability of the vaccine product at tropical ambient temperatures; and 6) speed of response from threat identification to vaccine deployment. The assessment indicated that technologies in the order of increasing feasibility and decreasing risk are the yeast platform, ADDomer platform, followed by RNA and GMMA platforms. The comparative strengths and weaknesses of each technology are discussed in detail, illustrating the associated development and manufacturing needs and priorities.

  • Journal article
    Nash A, Urdaneta Mignini G, Beaghton A, Hoermann A, Papathanos P, Christophides G, Windbichler Net al., 2019,

    Integral Gene Drives for population replacement

    , Biology Open, Vol: 8, ISSN: 2046-6390

    A first generation of CRISPR-based gene drives has now been tested in the laboratory in a number of organisms, including malaria vector mosquitoes. Challenges for their use in the area-wide genetic control of vector-borne disease have been identified, including the development of target site resistance, their long-term efficacy in the field, their molecular complexity, and practical and legal limitations for field testing of both gene drive and coupled anti-pathogen traits. We have evaluated theoretically the concept of integral gene drive (IGD) as an alternative paradigm for population replacement. IGDs incorporate a minimal set of molecular components, including drive and anti-pathogen effector elements directly embedded within endogenous genes – an arrangement that in theory allows targeting functionally conserved coding sequences without disrupting their function. Autonomous and non-autonomous IGD strains could be generated, optimized, regulated and imported independently. We performed quantitative modeling comparing IGDs with classical replacement drives and show that selection for the function of the hijacked host gene can significantly reduce the establishment of resistant alleles in the population, while drive occurring at multiple genomic loci prolongs the duration of transmission blockage in the face of pre-existing target site variation. IGD thus has potential as a more durable and flexible population replacement strategy.

  • Journal article
    Ellis T, 2019,

    Predicting how evolution will beat us

    , MICROBIAL BIOTECHNOLOGY, Vol: 12, Pages: 41-43, ISSN: 1751-7915
  • Journal article
    Blount B, Ellis T, 2019,

    The Synthetic Genome Summer Course

    , Synthetic Biology, Vol: 3, ISSN: 2397-7000

    The Synthetic Genome Summer Course was convened with the aim of teaching a wide range of researchers the theory and practical skills behind recent advances in synthetic biology and synthetic genome science, with a focus on Sc2.0, the synthetic yeast genome project. Through software workshops, tutorials and research talks from leading members of the field, the 30 attendees learnt about relevant principles and techniques that they were then able to implement first-hand in laboratory-based practical sessions. Participants SCRaMbLEd semi-synthetic yeast strains to diversify heterologous pathways, used automation to build combinatorial pathway libraries and used CRISPR to debug fitness defects caused by synthetic chromosome design changes. Societal implications of synthetic chromosomes were explored and industrial stakeholders discussed synthetic biology from a commercial standpoint. Over the 5 days, participants gained valuable insight and acquired skills to aid them in future synthetic genome research.

  • Journal article
    Gu Y, Lv X, Liu Y, Li J, Du G, Chen J, Rodrigo L-A, Liu Let al., 2019,

    Synthetic redesign of central carbon and redox metabolism for high yield production of N-acetylglucosamine in Bacillus subtilis

    , Metabolic Engineering, Vol: 51, Pages: 59-69, ISSN: 1096-7176

    One of the primary goals of microbial metabolic engineering is to achieve high titer, yield and productivity (TYP) of engineered strains. This TYP index requires optimized carbon flux toward desired molecule with minimal by-product formation. De novo redesign of central carbon and redox metabolism holds great promise to alleviate pathway bottleneck and improve carbon and energy utilization efficiency. The engineered strain, with the overexpression or deletion of multiple genes, typically can’t meet the TYP index, due to overflow of central carbon and redox metabolism that compromise the final yield, despite a high titer or productivity might be achieved. To solve this challenge, we reprogramed the central carbon and redox metabolism of Bacillus subtilis and achieved high TYP production of N-acetylglucosamine. Specifically, a “push–pull–promote” approach efficiently reduced the overflown acetyl-CoA flux and eliminated byproduct formation. Four synthetic NAD(P)-independent metabolic routes were introduced to rewire the redox metabolism to minimize energy loss. Implementation of these genetic strategies led us to obtain a B. subtilis strain with superior TYP index. GlcNAc titer in shake flask was increased from 6.6 g L−1 to 24.5 g L−1, the yield was improved from 0.115 to 0.468 g GlcNAc g−1 glucose, and the productivity was increased from 0.274 to 0.437 g L−1 h−1. These titer and yield are the highest levels ever reported and, the yield reached 98% of the theoretical pathway yield (0.478 g g−1 glucose). The synthetic redesign of carbon metabolism and redox metabolism represent a novel and general metabolic engineering strategy to improve the performance of microbial cell factories.

  • Journal article
    Weenink T, van der Hilst J, McKiernan R, Ellis Tet al., 2019,

    Design of RNA hairpin modules that predictably tune translation in yeast

    , Synthetic Biology, Vol: 3, ISSN: 2397-7000

    Modular parts for tuning translation are prevalent in prokaryotic synthetic biology but lacking for eukaryotic synthetic biology. Working in Saccharomyces cerevisiae yeast, we here describe how hairpin RNA structures inserted into the 5′ untranslated region (5′UTR) of mRNAs can be used to tune expression levels by 100-fold by inhibiting translation. We determine the relationship between the calculated free energy of folding in the 5′UTR and in vivo protein abundance, and show that this enables rational design of hairpin libraries that give predicted expression outputs. Our approach is modular, working with different promoters and protein coding sequences, and outperforms promoter mutation as a way to predictably generate a library where a protein is induced to express at a range of different levels. With this new tool, computational RNA sequence design can be used to predictably fine-tune protein production for genes expressed in yeast.

  • Conference paper
    Appuswamy R, Lebrigand K, Barbry P, Antonini M, Madderson O, Freemont P, MacDonald J, Heinis Tet al., 2019,

    Oligoarchive: Using DNA in the DBMS storage hierarchy

    © 2019 Conference on Innovative Data Systems Research (CIDR). All rights reserved. The demand for data-driven decision making coupled with need to retain data to meet regulatory compliance requirements has resulted in a rapid increase in the amount of archival data stored by enterprises. As data generation rate far outpaces the rate of improvement in storage density of media like HDD and tape, researchers have started investigating new architectures and media types that can store such “cold”, infrequently accessed data at very low cost. Synthetic DNA is one such storage media that has received some attention recently due to its high density and durability. In this paper, we investigate the problem of integrating DNA in the database storage hierarchy. More specifically, we ask the following two questions: (i) how can database knowledge help optimize DNA encoding and decoding? and (ii) how can biochemical mechanisms used for DNA manipulation be used to perform in-vitro, near-data SQL query processing? In answering these questions, we present OligoArchive, an architecture for using DNA-based storage system as the archival tier of a relational database. We demonstrate that OligoArchive can be realized in practice by building archiving and recovery tools (pg_oligo_dump and pg_oligo_restore) for PostgreSQL that perform schema-aware encoding and decoding of relational data on DNA, and using these tools to archive a 12KB TPC-H database to DNA, perform in-vitro computation, and restore it back again.

  • Conference paper
    Appuswamy R, Lebrigand K, Barbry P, Antonini M, Madderson O, Freemont P, MacDonald J, Heinis Tet al., 2019,

    Oligoarchive: Using DNA in the DBMS storage hierarchy

    © 2019 Conference on Innovative Data Systems Research (CIDR). All rights reserved. The demand for data-driven decision making coupled with need to retain data to meet regulatory compliance requirements has resulted in a rapid increase in the amount of archival data stored by enterprises. As data generation rate far outpaces the rate of improvement in storage density of media like HDD and tape, researchers have started investigating new architectures and media types that can store such “cold”, infrequently accessed data at very low cost. Synthetic DNA is one such storage media that has received some attention recently due to its high density and durability. In this paper, we investigate the problem of integrating DNA in the database storage hierarchy. More specifically, we ask the following two questions: (i) how can database knowledge help optimize DNA encoding and decoding? and (ii) how can biochemical mechanisms used for DNA manipulation be used to perform in-vitro, near-data SQL query processing? In answering these questions, we present OligoArchive, an architecture for using DNA-based storage system as the archival tier of a relational database. We demonstrate that OligoArchive can be realized in practice by building archiving and recovery tools (pg_oligo_dump and pg_oligo_restore) for PostgreSQL that perform schema-aware encoding and decoding of relational data on DNA, and using these tools to archive a 12KB TPC-H database to DNA, perform in-vitro computation, and restore it back again.

  • Conference paper
    Webb AJ, Landeryou T, Kelwick R, Allan F, Emery A, Jensen K, Templeton M, Freemont PSet al., 2019,

    SPECIFIC NUCLEIC ACIDS LIGATION FOR DETECTION OF SCHISTOSOMES: SNAILS

    , 68th Annual Meeting of the American-Society-for-Tropical-Medicine-and-Hygiene (ASTMH), Publisher: AMER SOC TROP MED & HYGIENE, Pages: 182-182, ISSN: 0002-9637
  • Conference paper
    Tuza ZA, Stan G-B, 2019,

    An Automatic Sparse Model Estimation Method Guided by Constraints That Encode System Properties

    , 18th European Control Conference (ECC), Publisher: IEEE, Pages: 2171-2176
  • Journal article
    Lawrence J, Chang S, Rodriguez LC, Ouldridge Tet al., 2019,

    Students go through the gears at the iGEM competition for engineering biology

    , Biochemist, Vol: 41, Pages: 58-61, ISSN: 0954-982X

    © 2019 Biochemical Society. The annual International Genetically Engineered Machine (iGEM) competition, represents an exciting opportunity for students to experience first-hand the potential of synthetic biology approaches to solve real-world problems. In this article, an iGEM team based at Imperial College London share some of the highlights from their participation in the 2018 iGEM event, including sharing their work at the annual Jamboree in Boston, Massachusetts.

  • Journal article
    Eyerich K, Brown S, Perez White B, Tanaka RJ, Bissonette R, Dhar S, Bieber T, Hijnen DJ, Guttman-Yassky E, Irvine A, Thyssen JP, Vestergaard C, Werfel T, Wollenberg A, Paller A, Reynolds NJet al., 2019,

    Human and computational models of atopic dermatitis: A review and perspectives by an expert panel of the International Eczema Council

    , Journal of Allergy and Clinical Immunology, Vol: 143, Pages: 36-45, ISSN: 0091-6749

    Atopic dermatitis (AD) is a prevalent disease worldwide and is associated with systemic comorbidities representing a significant burden on patients, their families, and society. Therapeutic options for AD remain limited, in part because of a lack of well-characterized animal models. There has been increasing interest in developing experimental approaches to study the pathogenesis of human AD in vivo, in vitro, and in silico to better define pathophysiologic mechanisms and identify novel therapeutic targets and biomarkers that predict therapeutic response. This review critically appraises a range of models, including genetic mutations relevant to AD, experimental challenge of human skin in vivo, tissue culture models, integration of “omics” data sets, and development of predictive computational models. Although no one individual model recapitulates the complex AD pathophysiology, our review highlights insights gained into key elements of cutaneous biology, molecular pathways, and therapeutic target identification through each approach. Recent developments in computational analysis, including application of machine learning and a systems approach to data integration and predictive modeling, highlight the applicability of these methods to AD subclassification (endotyping), therapy development, and precision medicine. Such predictive modeling will highlight knowledge gaps, further inform refinement of biological models, and support new experimental and systems approaches to AD.

  • Book chapter
    Stopnitzky E, Still S, Ouldridge TE, Altenberg Let al., 2018,

    Physical Limitations of Work Extraction from Temporal Correlations

    , The Interplay of Thermodynamics and Computation in Both Natural and Artificial Systems, Publisher: SFI Press
  • Book chapter
    Ouldridge TE, Brittain R, ten Wolde PR, 2018,

    The power of being explicit: demystifying work, heat, and free energy in the physics of computation

    , The Interplay of Thermodynamics and Computation in Both Natural and Artificial Systems
  • Journal article
    Silhan J, Zhao Q, Boura E, Thomson H, Förster A, Tang CM, Freemont PS, Baldwin GSet al., 2018,

    Structural basis for recognition and repair of the 3'-phosphate by NExo, a base excision DNA repair nuclease from Neisseria meningitidis

    , Nucleic Acids Research, Vol: 46, Pages: 11980-11989, ISSN: 0305-1048

    NExo is an enzyme from Neisseria meningitidis that is specialized in the removal of the 3'-phosphate and other 3'-lesions, which are potential blocks for DNA repair. NExo is a highly active DNA 3'-phosphatase, and although it is from the class II AP family it lacks AP endonuclease activity. In contrast, the NExo homologue NApe, lacks 3'-phosphatase activity but is an efficient AP endonuclease. These enzymes act together to protect the meningococcus from DNA damage arising mainly from oxidative stress and spontaneous base loss. In this work, we present crystal structures of the specialized 3'-phosphatase NExo bound to DNA in the presence and absence of a 3'-phosphate lesion. We have outlined the reaction mechanism of NExo, and using point mutations we bring mechanistic insights into the specificity of the 3'-phosphatase activity of NExo. Our data provide further insight into the molecular origins of plasticity in substrate recognition for this class of enzymes. From this we hypothesize that these specialized enzymes lead to enhanced efficiency and accuracy of DNA repair and that this is important for the biological niche occupied by this bacterium.

  • Software
    Brittain R, Jones N, Ouldridge T, 2018,

    Biochemical Szilard engine for memory limited inference

    Code and data for figures in 'Biochemical Szilard engine for memory limited inference'

  • Journal article
    Kontoravdi K, Jimenez Del Val I, 2018,

    Computational tools for predicting and controlling the glycosylation of biopharmaceuticals

    , Current Opinion in Chemical Engineering, Vol: 22, Pages: 89-97, ISSN: 2211-3398

    Glycosylation is a critical quality attribute of biopharmaceuticals because it is a major source of structural variability that influences the in vivo safety and therapeutic efficacy of these products. Manufacturing process conditions are known to influence the monosaccharide composition and relative abundance of the complex carbohydrates bound to therapeutic proteins. Multiple computational tools have been developed to describe these process/product quality relationships in order to control and optimise the glycosylation of biopharmaceuticals. This review will provide a summary highlighting the strengths and weaknesses of each modelling strategy in their application towards cellular glycoengineering or bioprocess design and control. To conclude, potential unified glycosylation modelling approaches for biopharmaceutical quality assurance are proposed.

  • Conference paper
    Toczek M, Zielonka D, Zukowska P, Marcinkowski JT, Kutryb-Zajac B, Slominska E, Isalan M, Mielcarek M, Smolenski RTet al., 2018,

    An altered nucleotide metabolism as a novel mechanism leading to Huntington disease related cardiomyopathy

    , Purines 2018 Basic and Translational Science on Purinergic Signaling and its Components for a Healthy and Better World, Publisher: Springer Verlag, Pages: S53-S53, ISSN: 1573-9538
  • Journal article
    Larroude M, Rossignol T, Nicaud J-M, Ledesma Amaro Ret al., 2018,

    Synthetic biology tools for engineering Yarrowia lipolytica

    , Biotechnology Advances, Vol: 36, Pages: 2150-2164, ISSN: 0734-9750

    The non-conventional oleaginous yeast Yarrowia lipolytica shows great industrial promise. It naturally produces certain compounds of interest but can also artificially generate non-native metabolites, thanks to an engineering process made possible by the significant expansion of a dedicated genetic toolbox. In this review, we present recently developed synthetic biology tools that facilitate the manipulation of Y. lipolytica, including 1) DNA assembly techniques, 2) DNA parts for constructing expression cassettes, 3) genome-editing techniques, and 4) computational tools.

  • Conference paper
    Webb AJ, Allan F, Kelwick R, Jensen K, Templeton MR, Freemont Pet al., 2018,

    Protease-based bioreporters for the detection of schistosome cercariae

    , American Society of Tropical Medicine and Hygiene (ASTMH) 67th Annual Meeting, New Orleans, Louisiana, USA

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