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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
    Kitney R, Adeogun M, Fujishima Y, Goni-Moreno A, Johnson R, Maxon M, Steedman S, Ward S, Winickoff D, Philp Jet al., 2019,

    Enabling the Advanced Bioeconomy through Public Policy Supporting Biofoundries and Engineering Biology

    , TRENDS IN BIOTECHNOLOGY, Vol: 37, Pages: 917-920, ISSN: 0167-7799
  • Conference paper
    Hurault G, Tanaka RJ, 2019,

    A Bayesian machine learning model to identify patient-specific dynamic responses to eczema treatments

    , 49th Annual Meeting of the European-Society-for-Dermatological-Research (ESDR), Publisher: ELSEVIER SCIENCE INC, Pages: S239-S239, ISSN: 0022-202X
  • Journal article
    Deng J, Chen C, Gu Y, Lv X, Liu Y, Li J, Ledesma-Amaro R, Du G, Liu Let al., 2019,

    Creating an in vivo bifunctional gene expression circuit through an aptamer-based regulatory mechanism for dynamic metabolic engineering in Bacillus subtilis.

    , Metabolic Engineering, Vol: 55, Pages: 179-190, ISSN: 1096-7176

    Aptamer-based regulatory biosensors can dynamically regulate the expression of target genes in response to ligands and could be used in dynamic metabolic engineering for pathway optimization. However, the existing aptamer-ligand biosensors can only function with non-complementary DNA elements that cannot replicate in growing cells. Here, we construct an aptamer-based synthetic regulatory circuit that can dynamically upregulate and downregulate the expression of target genes in response to the ligand thrombin at transcriptional and translational levels, respectively, and further used this system to dynamically engineer the synthesis of 2'-fucosyllactose (2'-FL) in Bacillus subtilis. First, we demonstrated the binding of ligand molecule thrombin with the aptamer can induce the unwinding of fully complementary double-stranded DNA. Based on this finding, we constructed a bifunctional gene expression regulatory circuit using ligand thrombin-bound aptamers. The expression of the reporter gene ranged from 0.084- to 48.1-fold. Finally, by using the bifunctional regulatory circuit, we dynamically upregulated the expression of key genes fkp and futC and downregulated the expression of gene purR, resulting in the significant increase of 2'-FL titer from 24.7 to 674 mg/L. Compared with the other pathway-specific dynamic engineering systems, here the constructed aptamer-based regulatory circuit is independent of pathways, and can be generally used to fine-tune gene expression in other microbes.

  • 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
    Bruder S, Moldenhauer EJ, Lemke RD, Ledesma-Amaro R, Kabisch Jet al., 2019,

    Drop-in biofuel production using fatty acid photodecarboxylase from Chlorella variabilis in the oleaginous yeast Yarrowia lipolytica.

    , Biotechnol Biofuels, Vol: 12, Pages: 1-13, ISSN: 1754-6834

    Background: Oleaginous yeasts are potent hosts for the renewable production of lipids and harbor great potential for derived products, such as biofuels. Several promising processes have been described that produce hydrocarbon drop-in biofuels based on fatty acid decarboxylation and fatty aldehyde decarbonylation. Unfortunately, besides fatty aldehyde toxicity and high reactivity, the most investigated enzyme, aldehyde-deformylating oxygenase, shows unfavorable catalytic properties which hindered high yields in previous metabolic engineering approaches. Results: To demonstrate an alternative alkane production pathway for oleaginous yeasts, we describe the production of diesel-like, odd-chain alkanes and alkenes, by heterologously expressing a recently discovered light-driven oxidase from Chlorella variabilis (CvFAP) in Yarrowia lipolytica. Initial experiments showed that only strains engineered to have an increased pool of free fatty acids were susceptible to sufficient decarboxylation. Providing these strains with glucose and light in a synthetic medium resulted in titers of 10.9 mg/L of hydrocarbons. Using custom 3D printed labware for lighting bioreactors, and an automated pulsed glycerol fed-batch strategy, intracellular titers of 58.7 mg/L were achieved. The production of odd-numbered alkanes and alkenes with a length of 17 and 15 carbons shown in previous studies could be confirmed. Conclusions: Oleaginous yeasts such as Yarrowia lipolytica can transform renewable resources such as glycerol into fatty acids and lipids. By heterologously expressing a fatty acid photodecarboxylase from the algae Chlorella variabilis hydrocarbons were produced in several scales from microwell plate to 400 mL bioreactors. The lighting turned out to be a crucial factor in terms of growth and hydrocarbon production, therefore, the evaluation of different conditions was an important step towards a tailor-made process. In general, the developed bioprocess shows a route t

  • Journal article
    Hindley JW, Zheleva DG, Elani Y, Charalambous K, Barter LMC, Booth PJ, Bevan CL, Law RV, Ces Oet al., 2019,

    Building a synthetic mechanosensitive signaling pathway in compartmentalized artificial cells

    , Proceedings of the National Academy of Sciences, Vol: 116, Pages: 16711-16716, ISSN: 0027-8424

    To date reconstitution of one of the fundamental methods of cell communication, the signaling pathway, has been unaddressed in the bottom-up construction of artificial cells (ACs). Such developments are needed to increase the functionality and biomimicry of ACs, accelerating their translation and application in biotechnology. Here we report the construction of a de novo synthetic signaling pathway in microscale nested vesicles. Vesicle cell models respond to external calcium signals through activation of an intracellular interaction between phospholipase A2 and a mechanosensitive channel present in the internal membranes, triggering content mixing between compartments and controlling cell fluorescence. Emulsion-based approaches to AC construction are therefore shown to be ideal for the quick design and testing of new signaling networks and can readily include synthetic molecules difficult to introduce to biological cells. This work represents a foundation for the engineering of multi-compartment-spanning designer pathways that can be utilised to control downstream events inside an artificial cell, leading to the assembly of micromachines capable of sensing and responding to changes in their local environment.

  • Journal article
    Cui S, Lv X, Wu Y, Li J, Du G, Ledesma-Amaro R, Liu Let al., 2019,

    Engineering a bifunctional Phr60-Rap60-Spo0A quorum-sensing molecular switch for dynamic fine-tuning of menaquinone-7 synthesis in bacillus subtilis

    , ACS Synthetic Biology, Vol: 8, Pages: 1826-1837, ISSN: 2161-5063

    Quorum sensing (QS)-based dynamic regulation has been widely used as basic tool for fine-tuning gene expression in response to cell density changes without adding expensive inducers. However, most reported QS systems primarily relied on down-regulation rather than up-regulation of gene expression, significantly limiting its potential as a molecular switch to control metabolic flux. To solve this challenge, we developed a bifunctional and modular Phr60-Rap60-Spo0A QS system, based on two native promoters, P abrB (down-regulation by Spo0A-P) and P spoiiA (up-regulation by Spo0A-P). We constructed a library of promoters with different capacities to implement down-regulation and up-regulation by changing the location, number, and sequences of the binding sites for Spo0A-P. The QS system can dynamically balance the relationship between efficient synthesis of the target product and cell growth. Finally, we validated the usefulness of this strategy by dynamic control of menaquinone-7 (MK-7) synthesis in Bacillus subtilis 168, a model Gram-positive bacterium, with the bifunctional Phr60-Rap60-Spo0A quorum sensing system. Our dynamic pathway regulation led to a 40-fold improvement of MK-7 production from 9 to 360 mg/L in shake flasks and 200 mg/L in 15-L bioreactor. Taken together, our bilayer QS system has been successfully integrated with biocatalytic functions to achieve dynamic pathway regulation in B. subtilis 168, which may be extended for use in other microbes to fine-tune gene expression and improve metabolites production.

  • Journal article
    Harrison RM, Romano F, Ouldridge TE, Louis AA, Doye JPKet al., 2019,

    Identifying physical causes of apparent enhanced cyclization of short DNA molecules with a coarse-grained model

    , Journal of Chemical Theory and Computation, Vol: 15, Pages: 4660-4672, ISSN: 1549-9618

    DNA cyclization is a powerful technique to gain insight into the nature of DNA bending. While the worm-like chain model provides a good description of small to moderate bending fluctuations, it is expected to break down for large bending. Recent cyclization experiments on strongly-bent shorter molecules indeed suggest enhanced flexibility over and above that expected from the worm-like chain. Here, we use a coarse-grained model of DNA to investigate the subtle thermodynamics of DNA cyclization for molecules ranging from 30 to 210 base pairs. As the molecules get shorter we find increasing deviations between our computed equilibrium j-factor and the classic worm-like chain predictions of Shimada and Yamakawa for a torsionally aligned looped molecule. These deviations are due to sharp kinking, first at nicks, and only subsequently in the body of the duplex. At the shortest lengths, substantial fraying at the ends of duplex domains is the dominant method of relaxation. We also estimate the dynamic j-factor measured in recent FRET experiments. We find that the dynamic j-factor is systematically larger than its equilibrium counterpart - with the deviation larger for shorter molecules - because not all the stress present in the fully cyclized state is present in the transition state. These observations are important for the interpretation of recent cyclization experiments, suggesting that measured anomalously high j-factors may not necessarily indicate non-WLC behavior in the body of duplexes.

  • Journal article
    Perin G, Yunus IS, Valton M, Alobwede E, Jones PRet al., 2019,

    Sunlight-driven recycling to increase nutrient use-efficiency in agriculture

    , Algal Research, Vol: 41, ISSN: 2211-9264

    Humans unsustainably scavenge massive amounts of nutrients from the environment to feed our agricultural systems, thereby perturbing pre-existing natural re-cycling processes. Only a minor fraction of the nutrients are eventually taken up by crops and converted into food, while the majority runs-off into the environment, causing the release of greenhouse gases (e.g. emission of nitrous and nitrogen oxides from the soil) and threatening water security/biodiversity in several ecosystems. The estimated continued growth in global population in the 21st century is expected to place even greater pressure on nutrient use, with likely consequences for the sustainability of human society. Technologies that are able to balance the requirement for intensification of food production with a mitigation of its impact on the environment will be essential to deploy in the near future. The aim is to substantially increase nutrient use-efficiency in order to lower the pressure on finite resources and lighten the environmental impact of intensive agriculture. In this review, we will discuss one such technology, sunlight-driven prokaryotic and eukaryotic microalgae, as a vehicle for both capture and provision of nutrients leached from and provided to agricultural systems, respectively. This technology has the potential to make a difference, but it remains immature and we need to rapidly enhance our knowledge of its opportunities and challenges in order to exploit it for a sustainable circular nutrient economy.

  • 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
    Hillson N, Caddick M, Cai Y, Carrasco JA, Chang MW, Curach NC, Bell DJ, Le Feuvre R, Friedman DC, Fu X, Gold ND, Herrgard MJ, Holowko MB, Johnson JR, Johnson RA, Keasling JD, Kitney RI, Kondo A, Liu C, Martin VJJ, Menolascina F, Ogino C, Patron NJ, Pavan M, Poh CL, Pretorius IS, Rosser SJ, Scrutton NS, Storch M, Tekotte H, Travnik E, Vickers CE, Yew WS, Yuan Y, Zhao H, Freemont PSet al., 2019,

    Building a global alliance of biofoundries (vol 10, 2040, 2019)

    , Nature Communications, Vol: 10, Pages: 1-2, ISSN: 2041-1723
  • 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
    Ciechonska M, Sturrock M, Grob A, Larrouy-Maumus G, Shahrezaei V, Isalan Met al., 2019,

    Ohm’s Law for increasing fitness gene expression with selection pressure

    <jats:title>Abstract</jats:title><jats:p>Natural selection relies on genotypic and phenotypic adaptation in response to fluctuating environmental conditions and is the key to predicting and preventing drug resistance. Whereas classic persistence is all-or-nothing, here we show for the first time that an antibiotic resistance gene displays linear dose-responsive selection for increased expression in proportion to rising antibiotic concentration in <jats:italic>E. coli</jats:italic>. Furthermore, we observe the general nature of an instantaneous phenotypic selection process upon bactericidal and bacteriostatic antibiotic treatment, as well as an amino acid synthesis pathway enzyme under a range of auxotrophic conditions. To explain this phenomenon, we propose an analogy to Ohm’s law in electricity (V=IR) where fitness pressure acts similarly to voltage (V), gene expression to current (I), and resistance (R) to cellular machinery constraints. Lastly, mathematical modelling approaches reveal that the emergent gene expression mechanism requires variation in mRNA and protein production within an isogenic population, and cell ‘memory’ from positive feedbacks between growth and expression of any fitness-inducing gene.</jats:p>

  • 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
    Kotidis P, Jedrzejewski P, Sou SN, Sellick C, Polizzi K, Del Val IJ, Kontoravdi Cet al., 2019,

    Model-based optimization of antibody galactosylation in CHO cell culture

    , Biotechnology and Bioengineering, Vol: 116, Pages: 1612-1626, ISSN: 0006-3592

    Exerting control over the glycan moieties of antibody therapeutics is highly desirable from a product safety and batch-to-batch consistency perspective. Strategies to improve antibody productivity may compromise quality, while interventions for improving glycoform distribution can adversely affect cell growth and productivity. Process design therefore needs to consider the trade-off between preserving cellular health and productivity while enhancing antibody quality. In this work, we present a modeling platform that quantifies the impact of glycosylation precursor feeding - specifically that of galactose and uridine - on cellular growth, metabolism as well as antibody productivity and glycoform distribution. The platform has been parameterized using an initial training data set yielding an accuracy of ±5% with respect to glycoform distribution. It was then used to design an optimized feeding strategy that enhances the final concentration of galactosylated antibody in the supernatant by over 90% compared with the control without compromising the integral of viable cell density or final antibody titer. This work supports the implementation of Quality by Design towards higher-performing bioprocesses.

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

    Correction: Emerging technologies for low‐cost, rapid vaccine manufacture

    , Biotechnology Journal, Vol: 14, Pages: 1-2, ISSN: 1860-6768
  • Journal article
    Kis Z, Papathanasiou M, CalvoSerrano R, Kontoravdi C, Shah Net al., 2019,

    A model‐based quantification of the impact of new manufacturing technologies on developing country vaccine supply chain performance: A Kenyan case study

    , Journal of Advanced Manufacturing and Processing, Vol: 1, ISSN: 2637-403X
  • Journal article
    Nikolados E, Weisse A, Ceroni F, Oyarzun Det al., 2019,

    Growth defects and loss-of-function in synthetic gene circuits

    , ACS Synthetic Biology, Vol: 8, Pages: 1231-1240, ISSN: 2161-5063

    Synthetic gene circuits perturb the physiology of their cellular host. The extra load on endogenous processes shifts the equilibrium of resource allocation in the host, leading to slow growth and reduced biosynthesis. Here we built integrated host-circuit models to quantify growth defects caused by synthetic gene circuits. Simulations reveal a complex relation between circuit output and cellular capacity for gene expression. For weak induction of heterologous genes, protein output can be increased at the expense of growth defects. Yet for stronger induction, cellular capacity reaches a tipping point, beyond which both gene expression and growth rate drop sharply. Extensive simulations across various growth conditions and large regions of the design space suggest that the critical capacity is a result of ribosomal scarcity. We studied the impact of growth defects on various gene circuits and transcriptional logic gates, which highlights the extent to which cellular burden can limit, shape, and even break down circuit function. Our approach offers a comprehensive framework to assess the impact of host-circuit interactions in silico, with wide-ranging implications for the design and optimization of bacterial gene circuits.

  • 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.

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