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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
    Rivadeneira PS, Moog CH, Stan G-B, Costanza V, Brunet C, Raffi F, Ferre V, Mhawej M-J, Biafore F, Ouattara DA, Ernst D, Fonteneau R, Xia Xet al., 2014,

    Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Clinical Research Study

    , AIDS RESEARCH AND HUMAN RETROVIRUSES, Vol: 30, Pages: 831-834, ISSN: 0889-2229
  • Journal article
    Casini A, Christodoulou G, Freemont PS, Baldwin GS, Ellis T, MacDonald JTet al., 2014,

    R2oDNA Designer: Computational Design of Biologically Neutral Synthetic DNA Sequences

    , ACS SYNTHETIC BIOLOGY, Vol: 3, Pages: 525-528, ISSN: 2161-5063
  • Journal article
    Galdzicki M, Clancy KP, Oberortner E, Pocock M, Quinn JY, Rodriguez CA, Roehner N, Wilson ML, Adam L, Anderson JC, Bartley BA, Beal J, Chandran D, Chen J, Densmore D, Endy D, Gruenberg R, Hallinan J, Hillson NJ, Johnson JD, Kuchinsky A, Lux M, Misirli G, Peccoud J, Plahar HA, Sirin E, Stan G-B, Villalobos A, Wipat A, Gennari JH, Myers CJ, Sauro HMet al., 2014,

    The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology

    , NATURE BIOTECHNOLOGY, Vol: 32, Pages: 545-550, ISSN: 1087-0156
  • Journal article
    Oyarzun DA, Lugagne J-B, Stan G-B, 2014,

    Noise propagation in synthetic gene circuits for metabolic control

    , ACS Synthetic Biology, Vol: 4, Pages: 116-125, ISSN: 2161-5063

    Dynamic control of enzyme expression can be an effective strategy to engineer robust metabolic pathways. It allows a synthetic pathway to self-regulate in response to changes in bioreactor conditions or the metabolic state of the host. The implementation of this regulatory strategy requires gene circuits that couple metabolic signals with the genetic machinery, which is known to be noisy and one of the main sources of cell-to-cell variability. One of the unexplored design aspects of these circuits is the propagation of biochemical noise between enzyme expression and pathway activity. In this article, we quantify the impact of a synthetic feedback circuit on the noise in a metabolic product in order to propose design criteria to reduce cell-to-cell variability. We consider a stochastic model of a catalytic reaction under negative feedback from the product to enzyme expression. On the basis of stochastic simulations and analysis, we show that, depending on the repression strength and promoter strength, transcriptional repression of enzyme expression can amplify or attenuate the noise in the number of product molecules. We obtain analytic estimates for the metabolic noise as a function of the model parameters and show that noise amplification/attenuation is a structural property of the model. We derive an analytic condition on the parameters that lead to attenuation of metabolic noise, suggesting that a higher promoter sensitivity enlarges the parameter design space. In the theoretical case of a switch-like promoter, our analysis reveals that the ability of the circuit to attenuate noise is subject to a trade-off between the repression strength and promoter strength.

  • Journal article
    Pothoulakis G, Ceroni F, Reeve B, Ellis Tet al., 2014,

    The spinach RNA aptamer as a characterization tool for synthetic biology

    , ACS Synthetic Biology, Vol: 3, Pages: 182-187, ISSN: 2161-5063

    Characterization of genetic control elements is essential for the predictable engineering of synthetic biology systems. The current standard for in vivo characterization of control elements is through the use of fluorescent reporter proteins such as green fluorescent protein (GFP). Gene expression, however, involves not only protein production but also the production of mRNA. Here, we present the use of the Spinach aptamer sequence, an RNA mimic of GFP, as a tool to characterize mRNA expression in Escherichia coli. We show how the aptamer can be incorporated into gene expression cassettes and how co-expressing it with a red fluorescent protein (mRFP1) allows, for the first time, simultaneous measurement of mRNA and protein levels from engineered constructs. Using flow cytometry, we apply this tool here to evaluate ribosome binding site sequences and promoters and use it to highlight the differences in the temporal behavior of transcription and translation.

  • Journal article
    Pan W, Sootla A, Stan G-B, 2014,

    Distributed Reconstruction of Nonlinear Networks: An ADMM Approach

    , IFAC PAPERSONLINE, Vol: 47, Pages: 3208-3213, ISSN: 2405-8963
  • Journal article
    Casini A, MacDonald JT, De Jonghe J, Christodoulou G, Freemont PS, Baldwin GS, Ellis Tet al., 2013,

    One-pot DNA construction for synthetic biology: the Modular Overlap-Directed Assembly with Linkers (MODAL) strategy

    , Nucleic Acids Research, Vol: 42, ISSN: 1362-4962

    Overlap-directed DNA assembly methods allowmultiple DNA parts to be assembled together inone reaction. These methods, which rely onsequence homology between the ends of DNAparts, have become widely adopted in syntheticbiology, despite being incompatible with a key principleof engineering: modularity. To answer this, wepresent MODAL: a Modular Overlap-DirectedAssembly with Linkers strategy that brings modularityto overlap-directed methods, allowing assemblyof an initial set of DNA parts into a variety ofarrangements in one-pot reactions. MODAL isaccompanied by a custom software tool thatdesigns overlap linkers to guide assembly,allowing parts to be assembled in any specifiedorder and orientation. The in silico design of syntheticorthogonal overlapping junctions allows formuch greater efficiency in DNA assembly for avariety of different methods compared with usingnon-designed sequence. In tests with three differentassembly technologies, the MODAL strategy givesassembly of both yeast and bacterial plasmids,composed of up to five DNA parts in the kilobaserange with efficiencies of between 75 and 100%.It also seamlessly allows mutagenesis to beperformed on any specified DNA parts duringthe process, allowing the one-step creation of constructlibraries valuable for synthetic biologyapplications.

  • Journal article
    O'Clery N, Yuan Y, Stan G-B, Barahona Met al., 2013,

    Observability and coarse graining of consensus dynamics through the external equitable partition

    , PHYSICAL REVIEW E, Vol: 88, ISSN: 1539-3755
  • Journal article
    Wright O, Stan G-B, Ellis T, 2013,

    Building-in biosafety for synthetic biology

    , MICROBIOLOGY-SGM, Vol: 159, Pages: 1221-1235, ISSN: 1350-0872
  • Journal article
    Arpino JAJ, Hancock EJ, Anderson J, Barahona M, Stan G-BV, Papachristodoulou A, Polizzi Ket al., 2013,

    Tuning the dials of Synthetic Biology

    , Microbiology-Sgm, Vol: 159, Pages: 1236-1253, ISSN: 1465-2080
  • Journal article
    Yuan Y, Stan G-B, Shi L, Barahona M, Goncalves Jet al., 2013,

    Decentralised minimum-time consensus

    , AUTOMATICA, Vol: 49, Pages: 1227-1235, ISSN: 0005-1098
  • Journal article
    Papadimitriou KI, Stan G-B, Drakakis EM, 2013,

    Systematic computation of non-linear cellular and molecular dynamics with low-power cytomimetic circuits: A simulation study

    , PLoS ONE, Vol: 8, ISSN: 1932-6203

    This paper presents a novel method for the systematic implementation of low-power microelectronic circuits aimed at computing nonlinear cellular and molecular dynamics. The method proposed is based on the Nonlinear Bernoulli Cell Formalism (NBCF), an advanced mathematical framework stemming from the Bernoulli Cell Formalism (BCF) originally exploited for the modular synthesis and analysis of linear, time-invariant, high dynamic range, logarithmic filters. Our approach identifies and exploits the striking similarities existing between the NBCF and coupled nonlinear ordinary differential equations (ODEs) typically appearing in models of naturally encountered biochemical systems. The resulting continuous-time, continuous-value, low-power CytoMimetic electronic circuits succeed in simulating fast and with good accuracy cellular and molecular dynamics. The application of the method is illustrated by synthesising for the first time microelectronic CytoMimetic topologies which simulate successfully: 1) a nonlinear intracellular calcium oscillations model for several Hill coefficient values and 2) a gene-protein regulatory system model. The dynamic behaviours generated by the proposed CytoMimetic circuits are compared and found to be in very good agreement with their biological counterparts. The circuits exploit the exponential law codifying the low-power subthreshold operation regime and have been simulated with realistic parameters from a commercially available CMOS process. They occupy an area of a fraction of a square-millimetre, while consuming between 1 and 12 microwatts of power. Simulations of fabrication-related variability results are also presented.

  • Journal article
    Stan G-B, 2013,

    A century of revolution in bioengineering

    , BIOFUTUR, Pages: 38-39, ISSN: 0294-3506
  • Journal article
    Anderson J, Strelkowa N, Stan G-B, Douglas T, Savulescu J, Barahona M, Papachristodoulou Aet al., 2012,

    Engineering and ethical perspectives in synthetic biology

    , EMBO Reports, Vol: 13, Pages: 584-590, ISSN: 1469-221X

    Synthetic biology has emerged as an exciting and promising new research field, garnering significant attention from both the scientific community and the general public. This interest results from a variety of striking features: synthetic biology is a truly interdisciplinary field that engages biologists, mathematicians, physicists and engineers; its research focus is applied; and it has enormous potential to harness the power of biology to provide scientific and engineering solutions to a wide range of problems and challenges that plague humanity. However, the power of synthetic biology to engineer organisms with custom‐made functionality requires that researchers and society use this power safely and responsibly, in particular when it comes to releasing organisms into the environment. This creates new challenges for both the design of such organisms and the regulatory process governing their creation and use.

  • Journal article
    Parker KH, Alastruey J, Stan G-B, 2012,

    Arterial reservoir-excess pressure and ventricular work

    , MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, Vol: 50, Pages: 419-424, ISSN: 0140-0118
  • Journal article
    Yuan Y, Stan G-B, Warnick S, Goncalves Jet al., 2012,

    Minimal realization of the dynamical structure function and its application to network reconstruction

    Network reconstruction, i.e., obtaining network structure from data, is acentral theme in systems biology, economics and engineering. In some previouswork, we introduced dynamical structure functions as a tool for posing andsolving the problem of network reconstruction between measured states. Whilerecovering the network structure between hidden states is not possible sincethey are not measured, in many situations it is important to estimate theminimal number of hidden states in order to understand the complexity of thenetwork under investigation and help identify potential targets formeasurements. Estimating the minimal number of hidden states is also crucial toobtain the simplest state-space model that captures the network structure andis coherent with the measured data. This paper characterizes minimal orderstate-space realizations that are consistent with a given dynamical structurefunction by exploring properties of dynamical structure functions anddeveloping an algorithm to explicitly obtain such a minimal realization.

  • Journal article
    Pan W, Yuan Y, Goncalves J, Stan G-Bet al., 2012,

    Reconstruction of Arbitrary Biochemical Reaction Networks: A Compressive Sensing Approach

    , 2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), Pages: 2334-2339, ISSN: 0743-1546
  • Journal article
    OyarzĂșn DA, Stan GB, 2012,

    Synthetic gene circuits for metabolic control: design tradeoffs and constraints

    , Journal of the Royal Society Interface, Vol: 10
  • Journal article
    Zhang H-T, Chen MZQ, Stan G-B, 2011,

    Fast Consensus Via Predictive Pinning Control

  • Journal article
    Dalchau N, Baek SJ, Briggs HM, Robertson FC, Dodd AN, Gardner MJ, Stancombe MA, Haydon MJ, Stan G-B, Goncalves JM, Webb AARet al., 2011,

    The circadian oscillator gene GIGANTEA mediates a long-term response of the Arabidopsis thaliana circadian clock to sucrose


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