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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
    Irmisch P, Ouldridge TE, Seidel R, 2020,

    Modelling DNA-strand displacement reactions in the presence of base-pair mismatches

    , Journal of the American Chemical Society, Vol: 142, Pages: 11451-11463, ISSN: 0002-7863

    Toehold-mediated strand displacement is the most abundantly used method to achieve dynamic switching in DNA-based nanotechnology. An ‘invader’ strand binds to the ‘toehold’ overhang of a target strand and replaces a target-bound ’incumbent’ strand. Hereby, complementarity of the invader to the single-stranded toehold provides the energetic bias of the reaction. Despite the widespread use of strand displacement reactions for realizing dynamic DNA nanostructures, variants on the basic motif have not been completely characterized. Here we introduce a simple thermodynamic model, which is capable of quantitatively describing the kinetics of strand displacement reactions in the presence of mismatches, using a minimal set of parameters. Furthermore, our model highlights that base pair fraying and internal loop formation are important mechanisms when involving mismatches in the displacement process. Our model should provide a helpful tool for the rational design of strand-displacement reaction networks.

  • Journal article
    Ouldridge T, Turberfield A, Mullor Ruiz I, Louis A, Bath J, Haley N, Geraldini Aet al., 2020,

    Design of hidden thermodynamic driving for non-equilibrium systems via mismatch elimination during DNA strand displacement

    , Nature Communications, Vol: 11, ISSN: 2041-1723

    Recent years have seen great advances in the development of synthetic self-assembling molecular systems. Designing out-of-equilibrium architectures, however, requires a more subtle control over the thermodynamics and kinetics of reactions. We propose a mechanism for enhancing the thermodynamic drive of DNA strand-displacement reactions whilst barely perturbing forward reaction rates: the introduction of mismatches within the initial duplex. Through a combination of experiment and simulation, we demonstrate that displacement rates are strongly sensitive to mismatch location and can be tuned by rational design. By placing mismatches away from duplex ends, the thermodynamic drive for a strand-displacement reaction can be varied without significantly affecting the forward reaction rate. This hidden thermodynamic driving motif is ideal for the engineering of non-equilibrium systems that rely on catalytic control and must be robust to leak reactions.

  • Journal article
    Arpino JAJ, Polizzi KM, 2020,

    A modular method for directing protein self-assembly

    , ACS Synthetic Biology, Vol: 9, Pages: 993-1002, ISSN: 2161-5063

    Proteins are versatile macromolecules with diverse structure, charge, and function. They are ideal building blocks for biomaterials for drug delivery, biosensing, or tissue engineering applications. Simultaneously, the need to develop green alternatives to chemical processes has led to renewed interest in multienzyme biocatalytic routes to fine, specialty, and commodity chemicals. Therefore, a method to reliably assemble protein complexes using protein-protein interactions would facilitate the rapid production of new materials. Here we show a method for modular assembly of protein materials using a supercharged protein as a scaffolding "hub" onto which target proteins bearing oppositely charged domains have been self-assembled. The physical properties of the material can be tuned through blending and heating and disassembly triggered using changes in pH or salt concentration. The system can be extended to the synthesis of living materials. Our modular method can be used to reliably direct the self-assembly of proteins using small charged tag domains that can be easily encoded in a fusion protein.

  • Journal article
    Riangrungroj P, Polizzi KM, 2020,

    BeQuIK (Biosensor Engineered Quorum Induced Killing): designer bacteria for destroying recalcitrant biofilms.

    , Microbial Biotechnology, Vol: 13, Pages: 311-314, ISSN: 1751-7915

    This opinion piece describes a new design for the remediation of recalcitrant biofilms. It builds on previous work to develop engineered E. coli that recognize quorum sensing signals from pathogens in a biofilm and secrete toxins in response. To solve the challenge of dilute signalling molecules, we propose to use nanobodies and enzymes displayed on the surface of the cells to localize them to the biofilm and degrade the extracellular polymeric substances, thus creating a solution with better 'seek and destroy' capabilities.

  • Journal article
    Spice AJ, Aw R, Bracewell DG, Polizzi KMet al., 2020,

    Synthesis and assembly of Hepatitis B virus-like particles in a Pichia pastoris cell-free system

    , Frontiers in Bioengineering and Biotechnology, Vol: 8, ISSN: 2296-4185

    Virus-like particles (VLPs) are supramolecular protein assemblies with the potential for unique and exciting applications in synthetic biology and medicine. Despite the attention VLPs have gained thus far, considerable limitations still persist in their production. Poorly scalable manufacturing technologies and inconsistent product architectures continue to restrict the full potential of VLPs. Cell-free protein synthesis (CFPS) offers an alternative approach to VLP production and has already proven to be successful, albeit using extracts from a limited number of organisms. Using a recently developed Pichia pastoris-based CFPS system, we have demonstrated the production of the model Hepatitis B core antigen VLP as a proof-of-concept. The VLPs produced in the CFPS system were found to have comparable characteristics to those previously produced in vivo and in vitro. Additionally, we have developed a facile and rapid synthesis, assembly and purification methodology that could be applied as a rapid prototyping platform for vaccine development or synthetic biology applications. Overall the CFPS methodology allows far greater throughput, which will expedite the screening of optimal assembly conditions for more robust and stable VLPs. This approach could therefore support the characterization of larger sample sets to improve vaccine development efficiency.

  • Journal article
    Scholes N, Schnoerr D, Isalan M, Stumpf Met al., 2019,

    A comprehensive network atlas reveals that Turing patterns are common but not robust

    , Cell Systems, Vol: 9, Pages: 243-257.e4, ISSN: 2405-4712

    Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question and to distill design rules. We exhaustively analyze 2- and 3-node biological candidate Turing systems, amounting to 7,625 networks and more than 3 × 10^11 analyzed scenarios. We find that network structure alone neither implies nor guarantees emergent TPs. A large fraction (>61%) of network design space can produce TPs, but these are sensitive to even subtle changes in parameters, network structure, and regulatory mechanisms. This implies that TP networks are more common than previously thought, and evolution might regularly encounter prototypic solutions. We deduce compositional rules for TP systems that are almost necessary and sufficient (96% of TP networks contain them, and 92% of networks implementing them produce TPs). This comprehensive network atlas provides the blueprints for identifying natural TPs and for engineering synthetic systems.

  • Journal article
    Kuntz J, Thomas P, Stan G-B, Barahona Met al., 2019,

    Stationary distributions of continuous-time Markov chains: a review of theory and truncation-based approximations

    Computing the stationary distributions of a continuous-time Markov chaininvolves solving a set of linear equations. In most cases of interest, thenumber of equations is infinite or too large, and cannot be solved analyticallyor numerically. Several approximation schemes overcome this issue by truncatingthe state space to a manageable size. In this review, we first give acomprehensive theoretical account of the stationary distributions and theirrelation to the long-term behaviour of the Markov chain, which is readilyaccessible to non-experts and free of irreducibility assumptions made instandard texts. We then review truncation-based approximation schemes payingparticular attention to their convergence and to the errors they introduce, andwe illustrate their performance with an example of a stochastic reactionnetwork of relevance in biology and chemistry. We conclude by elaborating oncomputational trade-offs associated with error control and some open questions.

  • Journal article
    Kelwick RJR, Ricci L, Chee SM, Bell D, Webb A, Freemont Pet al., 2019,

    Cell-free prototyping strategies for enhancing the sustainable production of polyhydroxyalkanoates bioplastics

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

    The polyhydroxyalkanoates (PHAs) are microbially-produced biopolymers that could potentially be used as sustainable alternatives to oil-derived plastics. However, PHAs are currently more expensive to produce than oil-derived plastics. Therefore, more efficient production processes would be desirable. Cell-free metabolic engineering strategies have already been used to optimise several biosynthetic pathways and we envisioned that cell-free strategies could be used for optimising PHAs biosynthetic pathways. To this end, we developed several Escherichia coli cell-free systems for in vitro prototyping PHAs biosynthetic operons, and also for screening relevant metabolite recycling enzymes. Furthermore, we customised our cell-free reactions through the addition of whey permeate, an industrial waste that has been previously used to optimise in vivo PHAs production. We found that the inclusion of an optimal concentration of whey permeate enhanced relative cell-free GFPmut3b production by ∼50%. In cell-free transcription-translation prototyping reactions, GC-MS quantification of cell-free 3-hydroxybutyrate (3HB) production revealed differences between the activities of the Native ΔPhaC_C319A (1.18 ±0.39 µM), C104 ΔPhaC_C319A (4.62 ±1.31 µM) and C101 ΔPhaC_C319A (2.65 ±1.27 µM) phaCAB operons that were tested. Interestingly, the most active operon, C104 produced higher levels of PHAs (or PHAs monomers) than the Native phaCAB operon in both in vitro and in vivo assays. Coupled cell-free biotransformation/transcription-translation reactions produced greater yields of 3HB (32.87 ±6.58 µM) and these reactions were also used to characterise a Clostridium propionicum Acetyl-CoA recycling enzyme. Together, these data demonstrate that cell-free approaches complement in vivo workflows for identifying additional strategies for optimising PHAs production.

  • Journal article
    Bartasun P, Prandi N, Storch M, Aknin Y, Bennett M, Palma A, Baldwin G, Sakuragi Y, Jones PR, Rowland Jet al., 2019,

    The effect of modulating the quantity of enzymes in a model ethanol pathway on metabolic flux in Synechocystis sp. PCC 6803

    , PEERJ, Vol: 7, ISSN: 2167-8359

    Synthetic metabolism allows new metabolic capabilities to be introduced into strains for biotechnology applications. Such engineered metabolic pathways are unlikely to function optimally as initially designed and native metabolism may not efficiently support the introduced pathway without further intervention. To develop our understanding of optimal metabolic engineering strategies, a two-enzyme ethanol pathway consisting of pyruvate decarboxylase and acetaldehyde reductase was introduced into Synechocystis sp. PCC 6803. We characteriseda new set of ribosome binding site sequences in Synechocystis sp. PCC 6803 providing a range of translation strengths for different genes under test. The effect of ribosome-bindingsite sequence, operon design and modifications to native metabolism on pathway flux was analysed by HPLC. The accumulation of all introduced proteins was also quantified using selected reaction monitoring mass spectrometry. Pathway productivity was more strongly dependent on the accumulation of pyruvate decarboxylase than acetaldehyde reductase. In fact, abolishment of reductase over-expression resulted in the greatest ethanol productivity, most likely because strains harbouringsingle-gene constructs accumulated more pyruvate decarboxylase than strains carrying any of the multi-gene constructs. Overall, several lessons were learned. Firstly, the expression level of the first gene in anyoperon influenced the expression level of subsequent genes, demonstrating that translational coupling can also occur in cyanobacteria. Longer operons resulted in lower protein abundance for proximally-encoded cistrons. And, implementation of metabolic engineering strategies that have previously been shown to enhance the growth or yield of pyruvate dependent products, through co-expression with pyruvate kinase and/or fructose-1,6-bisphosphatase/sedoheptulose-1,7-bisphosphatase, indicated that other factors had greater control over growth and metabolic flux under the tested con

  • Journal article
    Brödel A, Rodrigues R, Jaramillo A, Isalan Met al., 2019,

    Engineering the smallest transcription factor: accelerated evolution of a 63-amino acid peptide dual activator-repressor

    , bioRxiv

    Transcription factors control gene expression in all life. This raises the question of what is the smallest protein that can support such activity. In nature, Cro from bacteriophage λ is the smallest known repressor (66 amino acids; a.a.) but activators are typically much larger (e.g. λ cI, 237 a.a.). Indeed, previous efforts to engineer a minimal activator from Cro resulted in no activity in vivo . In this study, we show that directed evolution results in a new Cro activator-repressor that functions as efficiently as λ cI, in vivo . To achieve this, we develop Phagemid-Assisted Continuous Evolution: PACEmid. We find that a peptide as small as 63-a.a. functions efficiently as an activator and/or repressor. To our knowledge, this is the smallest protein gene regulator reported to date, highlighting the capacity of transcription factors to evolve from very short peptide sequences.

  • Journal article
    Kuntz Nussio J, Thomas P, Stan GB, Barahona Met al., 2019,

    Bounding the stationary distributions of the chemical master equation via mathematical programming

    , Journal of Chemical Physics, Vol: 151, ISSN: 0021-9606

    The stochastic dynamics of biochemical networks are usually modelled with the chemical master equation (CME). The stationary distributions of CMEs are seldom solvable analytically, and numerical methods typically produce estimates with uncontrolled errors. Here, we introduce mathematical programming approaches that yield approximations of these distributions with computable error bounds which enable the verification of their accuracy. First, we use semidefinite programming to compute increasingly tighter upper and lower bounds on the moments of the stationary distributions for networks with rational propensities. Second, we use these moment bounds to formulate linear programs that yield convergent upper and lower bounds on the stationary distributions themselves, their marginals and stationary averages. The bounds obtained also provide a computational test for the uniqueness of the distribution. In the unique case, the bounds form an approximation of the stationary distribution with a computable bound on its error. In the non unique case, our approach yields converging approximations of the ergodic distributions. We illustrate our methodology through several biochemical examples taken from the literature: Schl¨ogl’s model for a chemical bifurcation, a two-dimensional toggle switch, a model for bursty gene expression, and a dimerisation model with multiple stationary distributions.

  • Journal article
    Haines M, Storch M, Oyarzun D, Stan G, Baldwin Get al., 2019,

    Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)

    , Synthetic Biology, Vol: 4, Pages: 1-10, ISSN: 2397-7000

    In vitro selection of ligand-responsive ribozymes can identify rare, functional sequences from large libraries. While powerful, key caveats of this approach include lengthy and demanding experimental workflows; unpredictable experimental outcomes and unknown functionality of enriched sequences in vivo. To address the first of these limitations we developed Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR). LigASERR is scalable, amenable to automation and requires less time to implement compared to alternative methods. To improve the predictability of experiments, we modelled the underlying selection process, predicting experimental outcomes based on sequence and population parameters. We applied this new methodology and model to the enrichment of a known, in vitro-selected sequence from a bespoke library. Prior to implementing selection, conditions were optimised and target sequence dynamics accurately predicted for the majority of the experiment. In addition to enriching the target sequence, we identified two new, theophylline-activated ribozymes. Notably, all three sequences yielded riboswitches functional in Escherichia coli, suggesting LigASERR and similar in vitro selection methods can be utilised for generating functional riboswitches in this organism.

  • Journal article
    Moya-Ramirez I, Kontoravdi K, Polizzi K, 2019,

    Low-cost and user-friendly biosensor to test the integrity of mRNA molecules suitable for field applications

    , Biosensors and Bioelectronics, Vol: 137, Pages: 199-206, ISSN: 0956-5663

    The use of mRNA in biotechnology has expanded with novel applications such as vaccines and therapeutic mRNA delivery recently demonstrated. For mRNA to be used in patients, quality control assays will need to be routinely established. Currently, there is a gap between the highly sophisticated RNA integrity tests available and broader application of mRNA-based products by non-specialist users, e.g. in mass vaccination campaigns. Therefore, the aim of this work was to develop a low-cost biosensor able to test the integrity of a mRNA molecule with low technological requirements and easy end-user application. The biosensor is based on a bi-functional fusion protein, composed by the λN peptide that recognizes its cognate aptamer encoded on the 5’ end of the RNA under study and β-lactamase, which is able to produce a colorimetric response through a simple test. We propose two different mechanisms for signal processing adapted to two levels of technological sophistication, one based on spectrophotometric measurements and other on visual inspection. We show that the proposed λN-βLac chimeric protein specifically targets its cognate RNA aptamer, boxB, using both gel shift and biolayer interferometry assays. More importantly, the results presented confirm the biosensor performs reliably, with a wide dynamic range and a proportional response at different percentages of full-length RNA, even when gene-sized mRNAs were used. Thus, the features of the proposed biosensor would allow to end-users of products such as mRNA vaccines to test the integrity of the product before its application in a low-cost fashion, enabling a more reliable application of these products.

  • Journal article
    Walker K, Goosens V, Das A, Graham A, Ellis Tet al., 2019,

    Engineered cell-to-cell signalling within growing bacterial cellulose pellicles

    , Microbial Biotechnology, Vol: 12, Pages: 611-619, ISSN: 1751-7915

    Bacterial cellulose is a strong and flexible biomaterial produced at high yields by Acetobacter species and has applications in health care, biotechnology and electronics. Naturally, bacterial cellulose grows as a large unstructured polymer network around the bacteria that produce it, and tools to enable these bacteria to respond to different locations are required to grow more complex structured materials. Here, we introduce engineered cell‐to‐cell communication into a bacterial cellulose‐producing strain of Komagataeibacter rhaeticus to enable different cells to detect their proximity within growing material and trigger differential gene expression in response. Using synthetic biology tools, we engineer Sender and Receiver strains of K. rhaeticus to produce and respond to the diffusible signalling molecule, acyl‐homoserine lactone. We demonstrate that communication can occur both within and between growing pellicles and use this in a boundary detection experiment, where spliced and joined pellicles sense and reveal their original boundary. This work sets the basis for synthetic cell‐to‐cell communication within bacterial cellulose and is an important step forward for pattern formation within engineered living materials.

  • Journal article
    Brittain R, Jones N, Ouldridge T, 2019,

    Biochemical Szilard engines for memory-limited inference

    , New Journal of Physics, Vol: 21, ISSN: 1367-2630

    By designing and leveraging an explicit molecular realisation of a measurement-and-feedback-powered Szilard engine, we investigate the extraction of work from complex environments by minimal machines with finite capacity for memory and decision-making. Living systems perform inference to exploit complex structure, or correlations, in their environment, but the physical limits and underlying cost/benefit trade-offs involved in doing so remain unclear. To probe these questions, we consider a minimal model for a structured environment—a correlated sequence of molecules—and explore mechanisms based on extended Szilard engines for extracting the work stored in these non-equilibrium correlations. We consider systems limited to a single bit of memory making binary 'choices' at each step. We demonstrate that increasingly complex environments allow increasingly sophisticated inference strategies to extract more free energy than simpler alternatives, and argue that optimal design of such machines should also consider the free energy reserves required to ensure robustness against fluctuations due to mistakes.

  • Journal article
    Kuntz J, Thomas P, Stan G-B, Barahona Met al., 2019,

    Approximations of countably-infinite linear programs over bounded measure spaces

    We study a class of countably-infinite-dimensional linear programs (CILPs)whose feasible sets are bounded subsets of appropriately defined weightedspaces of measures. We show how to approximate the optimal value, optimalpoints, and minimal points of these CILPs by solving finite-dimensional linearprograms. The errors of our approximations converge to zero as the size of thefinite-dimensional program approaches that of the original problem and are easyto bound in practice. We discuss the use of our methods in the computation ofthe stationary distributions, occupation measures, and exit distributions ofMarkov~chains.

  • Journal article
    Madsen C, Goni Moreno A, Palchick Z P U, Roehner N, Bartley B, Bhatia S, Bhakta S, Bissell M, Clancy K, Cox RS, Gorochowski T, Grunberg R, Luna A, McLaughlin J, Nguyen T, Le Novere N, Pocock M, Sauro H, Scott-Brown J, Sexton JT, Stan G-B, Tabor JJ, Voigt CA, Zundel Z, Myers C, Beal J, Wipat Aet al., 2019,

    Synthetic Biology Open Language Visual (SBOL Visual) version 2.1

    , Journal of Integrative Bioinformatics, Vol: 16, Pages: 1-78, ISSN: 1613-4516

    People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species . Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.1 of SBOL Visual, which builds on the prior SBOL Visual 2.0 standard by expanding diagram syntax to include methods for showing modular structure and mappings between elements of a system, interactions arrows that can split or join (with the glyph at the split or join indicating either superposition or a chemical process), and adding new glyphs for indicating genomic context (e.g., integration into a plasmid or genome) and for stop codons.

  • Journal article
    Rajakumar PD, Gower G, Suckling L, Kitney R, McClymont D, Freemont Pet al., 2019,

    Rapid prototyping platform for Saccharomyces cerevisiae using computer-aided genetic design enabled by parallel software and workcell platform development

    , Slas Technology, Vol: 24, Pages: 291-297, ISSN: 2472-6303

    Biofoundries have enabled the ability to automate the construction of genetic constructs using computer-aided design. In this study, we have developed the methodology required to abstract and automate the construction of yeast-compatible designs. We demonstrate the use of our in-house software tool, AMOS, to coordinate with design software, JMP, and robotic liquid handling platforms to successfully manage the construction of a library of 88 yeast expression plasmids. In this proof-of-principle study, we used three fluorescent genes as proxy for three enzyme coding sequences. Our platform has been designed to quickly iterate around a design cycle of four protein coding sequences per plasmid, with larger numbers possible with multiplexed genome integrations in Saccharomyces cerevisiae. This work highlights how developing scalable new biotechnology applications requires a close integration between software development, liquid handling robotics, and protocol development.

  • Journal article
    Shaw W, Yamauchi H, Mead J, Gowers G, Bell D, Oling D, Larsson N, Wigglesworth M, Ladds G, Ellis Tet al., 2019,

    Engineering a model cell for rational tuning of GPCR signaling

    , Cell, Vol: 177, Pages: 782-796.e27, ISSN: 0092-8674

    G protein-coupled receptor (GPCR) signaling is the primary method eukaryotes use to respond tospecific cues in their environment. However, the relationship between stimulus and response for eachGPCR is difficult to predict due to diversity in natural signal transduction architecture and expression.Using genome engineering in yeast, we here constructed an insulated, modular GPCR signaltransduction system to study how the response to stimuli can be predictably tuned using synthetictools. We delineated the contributions of a minimal set of key components via computational andexperimental refactoring, identifying simple design principles for rationally tuning the dose-response.Using five different GPCRs, we demonstrate how this enables cells and consortia to be engineeredto respond to desired concentrations of peptides, metabolites, and hormones relevant to humanhealth. This work enables rational tuning of cell sensing, while providing a framework to guidereprogramming of GPCR-based signaling in other systems.

  • Journal article
    McCarty NS, Shaw WM, Ellis T, Ledesma-Amaro Ret al., 2019,

    Rapid assembly of gRNA arrays via modular cloning in yeast

    , ACS Synthetic Biology, Vol: 8, Pages: 906-910, ISSN: 2161-5063

    CRISPR is a versatile technology for genomic editing and regulation, but the expression of multiple gRNAs in S. cerevisiae has thus far been limited. We present here a simple extension to the Yeast MoClo Toolkit, which enables the rapid assembly of gRNA arrays using a minimal set of parts. Using a dual-PCR, Type IIs restriction enzyme Golden Gate assembly approach, at least 12 gRNAs can be assembled and expressed from a single transcriptional unit. We demonstrate that these gRNA arrays can stably regulate gene expression in a synergistic manner via dCas9-mediated repression. This approach expands the number of gRNAs that can be expressed in this model organism and may enable the versatile editing or transcriptional regulation of a greater number of genes in vivo.

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