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 articleEyerich K, Brown S, Perez White B, et 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.
Journal articleGu Y, Lv X, Liu Y, et 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 articleWeenink T, van der Hilst J, McKiernan R, et al., 2019,
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 paperAppuswamy R, Lebrigand K, Barbry P, et al., 2019,
Oligoarchive: Using DNA in the DBMS storage hierarchy
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 paperAppuswamy R, Lebrigand K, Barbry P, et 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 paperWebb AJ, Landeryou T, Kelwick R, et 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 paperTuza 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 articleLawrence J, Chang S, Rodriguez LC, et al., 2019,
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.
Book chapterOuldridge 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
Book chapterStopnitzky E, Still S, Ouldridge TE, et 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
Journal articleSilhan J, Zhao Q, Boura E, et 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.
SoftwareBrittain 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 articleLarroude M, Rossignol T, Nicaud J-M, et al., 2018,
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.
Journal articleKontoravdi K, Jimenez Del Val I, 2018,
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 paperToczek M, Zielonka D, Zukowska P, et al., 2018,
Conference paperWebb AJ, Allan F, Kelwick R, et al., 2018,
Journal articleKyrou K, Hammond AM, Galizi R, et al., 2018,
A CRISPR-Cas9 gene drive targeting doublesex causes complete population suppression in caged Anopheles gambiae mosquitoes, Nature Biotechnology, Vol: 36, Pages: 1062-1066, ISSN: 1087-0156
In the human malaria vector Anopheles gambiae, the gene doublesex (Agdsx) encodes two alternatively spliced transcripts, dsx-female (AgdsxF) and dsx-male (AgdsxM), that control differentiation of the two sexes. The female transcript, unlike the male, contains an exon (exon 5) whose sequence is highly conserved in all Anopheles mosquitoes so far analyzed. We found that CRISPR–Cas9-targeted disruption of the intron 4–exon 5 boundary aimed at blocking the formation of functional AgdsxF did not affect male development or fertility, whereas females homozygous for the disrupted allele showed an intersex phenotype and complete sterility. A CRISPR–Cas9 gene drive construct targeting this same sequence spread rapidly in caged mosquitoes, reaching 100% prevalence within 7–11 generations while progressively reducing egg production to the point of total population collapse. Owing to functional constraint of the target sequence, no selection of alleles resistant to the gene drive occurred in these laboratory experiments. Cas9-resistant variants arose in each generation at the target site but did not block the spread of the drive.
Journal articleGirvan P, Teng X, Brooks NJ, et al., 2018,
Journal articleLedesma-Amaro R, Jiménez A, Revuelta JL, 2018,
Pathway Grafting for Polyunsaturated Fatty Acids Production in Ashbya gossypii through Golden Gate Rapid Assembly., ACS Synthetic Biology, Vol: 7, Pages: 2340-2347, ISSN: 2161-5063
Here we present a Golden Gate assembly system adapted for the rapid genomic engineering of the industrial fungus Ashbya gossypii. This biocatalyst is an excellent biotechnological chassis for synthetic biology applications and is currently used for the industrial production of riboflavin. Other bioprocesses such as the production of folic acid, nucleosides, amino acids and biolipids have been recently reported in A. gossypii. In this work, an efficient assembly system for the expression of heterologous complex pathways has been designed. The expression platform comprises interchangeable DNA modules, which provides flexibility for the use of different loci for integration, selection markers and regulatory sequences. The functionality of the system has been applied to engineer strains able to synthesize polyunsaturated fatty acids (up to 35% of total fatty acids). The production of the industrially relevant arachidonic, eicosapentanoic and docosahexanoic acids remarks the potential of A. gossypii to produce these functional lipids.
Journal articleHurault G, Schram M, Roekevisch E, et al., 2018,
Relationship and probabilistic stratification of EASI and oSCORAD severity scores for atopic dermatitis, British Journal of Dermatology, Vol: 179, Pages: 1003-1005, ISSN: 1365-2133
The Harmonizing Outcome Measures for Eczema (HOME) recommended the Eczema Area and Severity Index (EASI) as the core outcome instrument for measuring the clinical signs of atopic dermatitis (AD). However, EASI may not have been used in previous clinical trials, and other scores, e.g. SCORAD (SCORing Atopic Dermatitis), the objective component of SCORAD (oSCORAD) and the Investigator Global Assessment (IGA), remain widely used. It is useful to establish a method to convert these scores into EASI to compare the results from different studies effectively. Indeed, EASI and oSCORAD have been found to be strongly correlated (rSpearman=0.92)7, suggesting a possibility to find a relationship between the two scores.
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