Research
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.
Publications
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Journal articleFreemont P, 2019,
Synthetic biology industry - Data-driven design is creating new opportunities in biotechnology.
, Emerging Topics in Life Sciences, Vol: 3, Pages: 651-657, ISSN: 2397-8554Synthetic biology is a rapidly emerging interdisciplinary research field that is primarily built upon foundational advances in molecular biology combined with engineering design. The field considers living systems as programmable at the genetic level and has been defined by the development of new platform technologies. This has spurned a rapid growth in start-up companies and the new synthetic biology industry is growing rapidly, with start-up companies receiving ~$6.1B investment since 2015 and a global synthetic biology market value estimated to be $14B by 2026. Many of the new start-upscan be grouped within a multi-layer ‘technology stack’. The ‘stack’ comprises a number of technology layers which together can be applied to a diversity of new biotechnology applications like consumer biotechnology products and living therapies. The ‘stack’ also enables new commercial opportunities and value chains similar to the software design and manufacturing revolution of the 20th century. However, synthetic biology industry is at a crucial point, as it now requires recognisable commercial successes in order for the industry to expand and scale, in terms of investment and companies. However, such expansion may directly challenge the ethos of synthetic biology, in terms of open technology sharing and democratisation, which could by accident lead to multi-national corporations and technology monopolies similar to the existing biotechnology/biopharma industry.
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Journal articleWood TE, Howard SA, Forster A, et al., 2019,
The Pseudomonas aeruginosa T6SS delivers a periplasmic toxin that disrupts bacterial cell morphology
, Cell Reports, Vol: 29, Pages: 187-201.e7, ISSN: 2211-1247The type VI secretion system (T6SS) is crucialin interbacterial competition and is avirulence determinant ofmany Gram-negative bacteria. Several T6SS effectorsarecovalently fused to secreted T6SS structural components such asthe VgrG spike for delivery into target cells.In Pseudomonas aeruginosa, theVgrG2b effector waspreviously proposedto mediatebacterial internalisation into eukaryotic cells. In this work, wefind that the VgrG2b C-terminal domain(VgrG2bC-ter) elicits toxicity in the bacterial periplasm, counteracted by a cognate immunity protein.We resolve thestructure of VgrG2bC-ter and confirm it is a member ofthezinc-metallopeptidasefamily of enzymes. We show that this effector causesmembrane blebbing atmidcell, whichsuggests a distincttype of T6SS-mediated growthinhibition through interference with cell division, mimicking the impact of β-lactam antibiotics. Ourstudyintroduces a further effector family to the T6SS arsenaland demonstrates that VgrG2b can target both prokaryotic and eukaryotic cells.
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Journal articleMeccariello A, Salvemini M, Primo P, et al., 2019,
Maleness-on-the-Y (MoY) orchestrates male sex determination in major agricultural fruit fly pests
, Sciecnce, Vol: 365, Pages: 1457-1460, ISSN: 0036-8075In insects, rapidly evolving primary sex-determining signals are transduced by a conserved regulatory module controlling sexual differentiation. In the agricultural pest Ceratitis capitata (Mediterranean fruit fly, or Medfly), we identified a Y-linked gene, Maleness-on-the-Y (MoY), encoding a small protein that is necessary and sufficient for male development. Silencing or disruption of MoY in XY embryos causes feminization, whereas overexpression of MoY in XX embryos induces masculinization. Crosses between transformed XY females and XX males give rise to males and females, indicating that a Y chromosome can be transmitted by XY females. MoY is Y-linked and functionally conserved in other species of the Tephritidae family, highlighting its potential to serve as a tool for developing more effective control strategies against these major agricultural insect pests.
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Journal articleScholes N, Schnoerr D, Isalan M, et al., 2019,
A comprehensive network atlas reveals that Turing patterns are common but not robust
, Cell Systems, Vol: 9, Pages: 243-257.e4, ISSN: 2405-4712Turing 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.
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Journal articleKelwick RJR, Ricci L, Chee SM, et al., 2019,
Cell-free prototyping strategies for enhancing the sustainable production of polyhydroxyalkanoates bioplastics
, Synthetic Biology, Vol: 3, ISSN: 2397-7000The 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.
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Conference paperHurault 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 articleKitney R, Adeogun M, Fujishima Y, et 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- Author Web Link
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- Citations: 16
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Journal articleDeng J, Chen C, Gu Y, et 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: 1096-7176Aptamer-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.
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Journal articleBartasun P, Prandi N, Storch M, et 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: 2167-8359Synthetic 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
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Journal articleBruder S, Moldenhauer EJ, Lemke RD, et 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: 1754-6834Background: 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
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Journal articleHindley JW, Zheleva DG, Elani Y, et 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: 0027-8424To 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.
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Journal articleCui S, Lv X, Wu Y, et 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: 2161-5063Quorum 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.
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Journal articleHarrison RM, Romano F, Ouldridge TE, et 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: 1549-9618DNA 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.
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Journal articlePerin G, Yunus IS, Valton M, et al., 2019,
Sunlight-driven recycling to increase nutrient use-efficiency in agriculture
, Algal Research, Vol: 41, ISSN: 2211-9264Humans 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.
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Journal articleKuntz Nussio J, Thomas P, Stan GB, et al., 2019,
Bounding the stationary distributions of the chemical master equation via mathematical programming
, Journal of Chemical Physics, Vol: 151, ISSN: 0021-9606The 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.
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Journal articleHillson N, Caddick M, Cai Y, et al., 2019,
Building a global alliance of biofoundries (vol 10, 2040, 2019)
, Nature Communications, Vol: 10, Pages: 1-2, ISSN: 2041-1723 -
Journal articleHaines M, Storch M, Oyarzun D, et al., 2019,
Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)
, Synthetic Biology, Vol: 4, Pages: 1-10, ISSN: 2397-7000In 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.
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Journal articleCiechonska M, Sturrock M, Grob A, et 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>
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Journal articleWalker K, Goosens V, Das A, et al., 2019,
Engineered cell-to-cell signalling within growing bacterial cellulose pellicles
, Microbial Biotechnology, Vol: 12, Pages: 611-619, ISSN: 1751-7915Bacterial 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.
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Journal articleKotidis P, Jedrzejewski P, Sou SN, et al., 2019,
Model-based optimization of antibody galactosylation in CHO cell culture
, Biotechnology and Bioengineering, Vol: 116, Pages: 1612-1626, ISSN: 0006-3592Exerting 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.
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