Research
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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.
Publications
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Conference paperSchumacher J, Waite C, 2018,
In vivo absolute and relative Nif protein abundances of Klebsiella oxytoca
, 13th European Nitrogen Fixation Conference -
Conference paperHurault G, Roekevisch E, Szegedi K, et al., 2018,
Development of computational tools to convert severity scores of atopic dermatitis for a probabilistic classification of symptom severity
, Annual Meeting of the British-Society-for-Investigative-Dermatology, Publisher: WILEY, Pages: E429-E429, ISSN: 0007-0963 -
Journal articlePan W, Yuan Y, Ljung L, et al., 2018,
Identification of nonlinear state-space systems from heterogeneous datasets
, IEEE Transactions on Control of Network Systems, Vol: 5, Pages: 737-747, ISSN: 2325-5870This paper proposes a new method to identify nonlinear state-space systems from heterogeneous datasets. The method is described in the context of identifying biochemical/gene networks (i.e., identifying both reaction dynamics and kinetic parameters) from experimental data. Simultaneous integration of various datasets has the potential to yield better performance for system identification. Data collected experimentally typically vary depending on the specific experimental setup and conditions. Typically, heterogeneous data are obtained experimentally through 1) replicate measurements from the same biological system or 2) application of different experimental conditions such as changes/perturbations in biological inductions, temperature, gene knock-out, gene over-expression, etc. We formulate here the identification problem using a Bayesian learning framework that makes use of “sparse group” priors to allow inference of the sparsest model that can explain the whole set of observed heterogeneous data. To enable scale up to large number of features, the resulting nonconvex optimization problem is relaxed to a reweighted Group Lasso problem using a convex–concave procedure. As an illustrative example of the effectiveness of our method, we use it to identify a genetic oscillator (generalized eight species repressilator). Through this example we show that our algorithm outperforms Group Lasso when the number of experiments is increased, even when each single time-series dataset is short. We additionally assess the robustness of our algorithm against noise by varying the intensity of process noise and measurement noise.
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Journal articleCritchley B, Isalan M, Mielcarek M, 2018,
Neuro-Cardio mechanisms in Huntington’s disease and other neurodegenerative disorders
, Frontiers in Physiology, Vol: 9, ISSN: 1664-042XAlthough Huntington’s disease is generally considered to be aneurological disorder, there is mounting evidence that heart malfunction plays an important role in disease progression. This is perhaps not unexpected since both cardiovascular and nervous systems are strongly connected—both development ally and subsequently inhealth and disease. This connection occurs through a systemof central and peripheral neurons that control cardiovascular performance, while in return the cardiovascular system worksas a sensor for the nervous system to react to physiological events. Hence, given their permanent interconnectivity, any pathological events occurring in one system might affect the second. In addition, some pathological signals fromHuntington’s disease might occur simultaneously in both the cardiovascular and nervous systems, since mutant Huntingtin protein is expressedin both. Here we aim to review the source of HD-related cardiomyopathy in the light of recently-published studies, and to identify similarities between HD-related cardiomyopathy andother neuro-cardio disorders.
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Journal articleKreula SM, Kaewphan S, Ginter F, et al., 2018,
Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining
, PeerJ, Vol: 6, ISSN: 2167-8359The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm (filter) was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already 'known', and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and filter to (i) discover novel candidate associations between different genes or proteins in the network, and (ii) rapidly evaluate the potential role of any one particular gene or protein. The full network is provided as an open-source resource.
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Journal articleBlount B, Gowers G, Ho JCH, et al., 2018,
Rapid host strain improvement by in vivo rearrangement of a synthetic yeast chromosome
, Nature Communications, Vol: 9, ISSN: 2041-1723Synthetic biology tools, such as modular parts and combinatorial DNA assembly, are routinely used to optimise the productivity of heterologous metabolic pathways for biosynthesis or substrate utilisation, yet, it is well established that host strain background is just as important for determining productivity. Here we report that in vivo combinatorial genomic rearrangement of Saccharomyces cerevisiae yeast with a synthetic chromosome V can rapidly generate new, improved host strains with genetic backgrounds favourable to diverse heterologous pathways, including those for violacein and penicillin biosynthesis and for xylose utilisation. We show how the modular rearrangement of synthetic chromosomes by SCRaMbLE can be easily determined using long-read nanopore sequencing and we explore experimental conditions that optimise diversification and screening. This new synthetic genome approach to metabolic engineering provides productivity improvements in a fast, simple and accessible way, making it a valuable addition to existing strain improvement techniques.
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Journal articleBolognesi G, Friddin MS, Salehi-Reyhani S, et al., 2018,
Sculpting and fusing biomimetic vesicle networks using optical tweezers
, Nature Communications, Vol: 9, Pages: 1-11, ISSN: 2041-1723Constructing higher-order vesicle assemblies has discipline-spanning potential from responsive soft-matter materials to artificial cell networks in synthetic biology. This potential is ultimately derived from the ability to compartmentalise and order chemical species in space. To unlock such applications, spatial organisation of vesicles in relation to one another must be controlled, and techniques to deliver cargo to compartments developed. Herein, we use optical tweezers to assemble, reconfigure and dismantle networks of cell-sized vesicles that, in different experimental scenarios, we engineer to exhibit several interesting properties. Vesicles are connected through double-bilayer junctions formed via electrostatically controlled adhesion. Chemically distinct vesicles are linked across length scales, from several nanometres to hundreds of micrometres, by axon-like tethers. In the former regime, patterning membranes with proteins and nanoparticles facilitates material exchange between compartments and enables laser-triggered vesicle merging. This allows us to mix and dilute content, and to initiate protein expression by delivering biomolecular reaction components.
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Journal articleKaramdad K, Hindley J, Friddin MS, et al., 2018,
Engineering thermoresponsive phase separated vesicles formed via emulsion phase transfer as a content-release platform
, Chemical Science, Vol: 9, Pages: 4851-4858, ISSN: 2041-6520Giant unilamellar vesicles (GUVs) are a well-established tool for the study of membrane biophysics and are increasingly used as artificial cell models and functional units in biotechnology. This trend is driven by the development of emulsion-based generation methods such as Emulsion Phase Transfer (EPT), which facilitates the encapsulation of almost any water-soluble compounds (including biomolecules) regardless of size or charge, is compatible with droplet microfluidics, and allows GUVs with asymmetric bilayers to be assembled. However, the ability to control the composition of membranes formed via EPT remains an open question; this is key as composition gives rise to an array of biophysical phenomena which can be used to add functionality to membranes. Here, we evaluate the use of GUVs constructed via this method as a platform for phase behaviour studies and take advantage of composition-dependent features to engineer thermally-responsive GUVs. For the first time, we generate ternary GUVs (DOPC/DPPC/cholesterol) using EPT, and by compensating for the lower cholesterol incorporation efficiencies, show that these possess the full range of phase behaviour displayed by electroformed GUVs. As a demonstration of the fine control afforded by this approach, we demonstrate release of dye and peptide cargo when ternary GUVs are heated through the immiscibility transition temperature, and show that release temperature can be tuned by changing vesicle composition. We show that GUVs can be individually addressed and release triggered using a laser beam. Our findings validate EPT as a suitable method for generating phase separated vesicles and provide a valuable proof-of-concept for engineering content release functionality into individually addressable vesicles, which could have a host of applications in the development of smart synthetic biosystems.
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Journal articleHenrich O, Gutiérrez Fosado YA, Curk T, et al., 2018,
Coarse-grained simulation of DNA using LAMMPS : an implementation of the oxDNA model and its applications
, European Physical Journal E. Soft Matter, Vol: 41, Pages: 57-57, ISSN: 1292-8941During the last decade coarse-grained nucleotide models have emerged that allow us to study DNA and RNA on unprecedented time and length scales. Among them is oxDNA, a coarse-grained, sequence-specific model that captures the hybridisation transition of DNA and many structural properties of single- and double-stranded DNA. oxDNA was previously only available as standalone software, but has now been implemented into the popular LAMMPS molecular dynamics code. This article describes the new implementation and analyses its parallel performance. Practical applications are presented that focus on single-stranded DNA, an area of research which has been so far under-investigated. The LAMMPS implementation of oxDNA lowers the entry barrier for using the oxDNA model significantly, facilitates future code development and interfacing with existing LAMMPS functionality as well as other coarse-grained and atomistic DNA models.
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Journal articleFreemont PS, Moore S, MacDonald J, et al., 2018,
Rapid acquisition and model-based analysis of cell-free transcription-translation reactions from non-model bacteria
, Proceedings of the National Academy of Sciences, Vol: 115, Pages: E4340-E4349, ISSN: 0027-8424Native cell-free transcription–translation systems offer a rapid route to characterize the regulatory elements (promoters, transcription factors) for gene expression from nonmodel microbial hosts, which can be difficult to assess through traditional in vivo approaches. One such host, Bacillus megaterium, is a giant Gram-positive bacterium with potential biotechnology applications, although many of its regulatory elements remain uncharacterized. Here, we have developed a rapid automated platform for measuring and modeling in vitro cell-free reactions and have applied this to B. megaterium to quantify a range of ribosome binding site variants and previously uncharacterized endogenous constitutive and inducible promoters. To provide quantitative models for cell-free systems, we have also applied a Bayesian approach to infer ordinary differential equation model parameters by simultaneously using time-course data from multiple experimental conditions. Using this modeling framework, we were able to infer previously unknown transcription factor binding affinities and quantify the sharing of cell-free transcription–translation resources (energy, ribosomes, RNA polymerases, nucleotides, and amino acids) using a promoter competition experiment. This allows insights into resource limiting-factors in batch cell-free synthesis mode. Our combined automated and modeling platform allows for the rapid acquisition and model-based analysis of cell-free transcription–translation data from uncharacterized microbial cell hosts, as well as resource competition within cell-free systems, which potentially can be applied to a range of cell-free synthetic biology and biotechnology applications.
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Journal articleKogenaru M, Isalan M, 2018,
Drug-inducible control of lethality genes: a low background destabilizing domain architecture applied to the Gal4-UAS system in Drosophila
, ACS Synthetic Biology, Vol: 7, Pages: 1496-1506, ISSN: 2161-5063Destabilizing domains (DDs) are genetic tags that conditionally control the level of abundance of proteins-of-interest (POI) with specific stabilizing small-molecule drugs, rapidly and reversibly, in a wide variety of organisms. The amount of the DD-tagged fusion protein directly impacts its molecular function. Hence, it is important that the background levels be tightly regulated in the absence of any drug. This is especially true for classes of proteins that function at extremely low levels, such as lethality genes involved in tissue development and certain transcriptional activator proteins. Here, we establish the uninduced background and induction levels for two widely used DDs (FKBP and DHFR) by developing an accurate quantification method. We show that both DDs exhibit functional background levels in the absence of a drug, but each to a different degree. To overcome this limitation, we systematically test a double architecture for these DDs (DD-POI-DD) that completely suppresses the protein’s function in an uninduced state, while allowing tunable functional levels upon adding a drug. As an example, we generate a drug-stabilizable Gal4 transcriptional activator with extremely low background levels. We show that this functions in vivo in the widely used Gal4-UAS bipartite expression system in Drosophila melanogaster. By regulating a cell death gene, we demonstrate that only the low background double architecture enables tight regulation of the lethal phenotype in vivo. These improved tools will enable applications requiring exceptionally tight control of protein function in living cells and organisms.
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Journal articleCeroni F, Boo A, Furini S, et al., 2018,
Burden-driven feedback control of gene expression
, Nature Methods, Vol: 15, Pages: 387-393, ISSN: 1548-7091Cells use feedback regulation to ensure robust growth despite fluctuating demands for resources and differing environmental conditions. However, the expression of foreign proteins from engineered constructs is an unnatural burden that cells are not adapted for. Here we combined RNA-seq with an in vivo assay to identify the major transcriptional changes that occur in Escherichia coli when inducible synthetic constructs are expressed. We observed that native promoters related to the heat-shock response activated expression rapidly in response to synthetic expression, regardless of the construct. Using these promoters, we built a dCas9-based feedback-regulation system that automatically adjusts the expression of a synthetic construct in response to burden. Cells equipped with this general-use controller maintained their capacity for native gene expression to ensure robust growth and thus outperformed unregulated cells in terms of protein yield in batch production. This engineered feedback is to our knowledge the first example of a universal, burden-based biomolecular control system and is modular, tunable and portable.
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Journal articleDe Porcellinis AJ, Norgaard H, Brey LMF, et al., 2018,
Overexpression of bifunctional fructose-1,6-bisphosphatase/sedoheptulose-1,7-bisphosphatase leads to enhanced photosynthesis and global reprogramming of carbon metabolism in Synechococcus sp PCC 7002
, Metabolic Engineering, Vol: 47, Pages: 170-183, ISSN: 1096-7176Cyanobacteria fix atmospheric CO2 to biomass and through metabolic engineering can also act as photosynthetic factories for sustainable productions of fuels and chemicals. The Calvin Benson cycle is the primary pathway for CO2 fixation in cyanobacteria, algae and C3 plants. Previous studies have overexpressed the Calvin Benson cycle enzymes, ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) and bifunctional sedoheptulose-1,7-bisphosphatase/fructose-1,6-bisphosphatase (hereafter BiBPase), in both plants and algae, although their impacts on cyanobacteria have not yet been rigorously studied. Here, we show that overexpression of BiBPase and RuBisCO have distinct impacts on carbon metabolism in the cyanobacterium Synechococcus sp. PCC 7002 through physiological, biochemical, and proteomic analyses. The former enhanced growth, cell size, and photosynthetic O2 evolution, and coordinately upregulated enzymes in the Calvin Benson cycle including RuBisCO and fructose-1,6-bisphosphate aldolase. At the same time it downregulated enzymes in respiratory carbon metabolism (glycolysis and the oxidative pentose phosphate pathway) including glucose-6-phosphate dehydrogenase (G6PDH). The content of glycogen was also significantly reduced while the soluble carbohydrate content increased. These results indicate that overexpression of BiBPase leads to global reprogramming of carbon metabolism in Synechococcus sp. PCC 7002, promoting photosynthetic carbon fixation and carbon partitioning towards non-storage carbohydrates. In contrast, whilst overexpression of RuBisCO had no measurable impact on growth and photosynthetic O2 evolution, it led to coordinated increase in the abundance of proteins involved in pyruvate metabolism and fatty acid biosynthesis. Our results underpin that singular genetic modifications in the Calvin Benson cycle can have far broader cellular impact than previously expected. These features could be exploited to more efficiently direct carbons towards desired
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Journal articlePerez-Carrasco R, Barnes CP, Schaerli Y, et al., 2018,
Combining a toggle switch and a repressilator within the AC-DC circuit generates distinct dynamical behaviors
, Cell Systems, Vol: 6, Pages: 521-530.e3, ISSN: 2405-4712Although the structure of a genetically encoded regulatory circuit is an important determinant of its function, the relationship between circuit topology and the dynamical behaviors it can exhibit is not well understood. Here, we explore the range of behaviors available to the AC-DC circuit. This circuit consists of three genes connected as a combination of a toggle switch and a repressilator. Using dynamical systems theory, we show that the AC-DC circuit exhibits both oscillations and bistability within the same region of parameter space; this generates emergent behaviors not available to either the toggle switch or the repressilator alone. The AC-DC circuit can switch on oscillations via two distinct mechanisms, one of which induces coherence into ensembles of oscillators. In addition, we show that in the presence of noise, the AC-DC circuit can behave as an excitable system capable of spatial signal propagation or coherence resonance. Together, these results demonstrate how combinations of simple motifs can exhibit multiple complex behaviors.
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Journal articleAvalos JL, Toettcher JE, Lalanne J-B, et al., 2018,
Principles of Systems Biology, No. 28
, CELL SYSTEMS, Vol: 6, Pages: 397-399, ISSN: 2405-4712 -
Journal articleTomazou M, Barahona M, Polizzi K, et al., 2018,
Computational re-design of synthetic genetic oscillators for independent amplitude and frequency modulation
, Cell Systems, Vol: 6, Pages: 508-520.e5, ISSN: 2405-4712To perform well in biotechnology applications, synthetic genetic oscillators must be engineered to allow independent modulation of amplitude and period. This need is currently unmet. Here, we demonstrate computationally how two classic genetic oscillators, the dual-feedback oscillator and the repressilator, can be re-designed to provide independent control of amplitude and period and improve tunability—that is, a broad dynamic range of periods and amplitudes accessible through the input “dials.” Our approach decouples frequency and amplitude modulation by incorporating an orthogonal “sink module” where the key molecular species are channeled for enzymatic degradation. This sink module maintains fast oscillation cycles while alleviating the translational coupling between the oscillator's transcription factors and output. We characterize the behavior of our re-designed oscillators over a broad range of physiologically reasonable parameters, explain why this facilitates broader function and control, and provide general design principles for building synthetic genetic oscillators that are more precisely controllable.
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Journal articleKelly CL, Taylor GM, Hitchcock A, et al., 2018,
A Rhamnose-Inducible System for Precise and Temporal Control of Gene Expression in Cyanobacteria.
, ACS Synth Biol, Vol: 7, Pages: 1056-1066Cyanobacteria are important for fundamental studies of photosynthesis and have great biotechnological potential. In order to better study and fully exploit these organisms, the limited repertoire of genetic tools and parts must be expanded. A small number of inducible promoters have been used in cyanobacteria, allowing dynamic external control of gene expression through the addition of specific inducer molecules. However, the inducible promoters used to date suffer from various drawbacks including toxicity of inducers, leaky expression in the absence of inducer and inducer photolability, the latter being particularly relevant to cyanobacteria, which, as photoautotrophs, are grown under light. Here we introduce the rhamnose-inducible rhaBAD promoter of Escherichia coli into the model freshwater cyanobacterium Synechocystis sp. PCC 6803 and demonstrate it has superior properties to previously reported cyanobacterial inducible promoter systems, such as a non-toxic, photostable, non-metabolizable inducer, a linear response to inducer concentration and crucially no basal transcription in the absence of inducer.
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Journal articleBorkowski O, Bricio C, Murgiano M, et al., 2018,
Cell-free prediction of protein expression costs for growing cells
, Nature Communications, Vol: 9, Pages: 1-11, ISSN: 2041-1723Translating heterologous proteins places significant burden on host cells, consuming expression resources leading to slower cell growth and productivity. Yet predicting the cost of protein production for any given gene is a major challenge, as multiple processes and factors combine to determine translation efficiency. To enable prediction of the cost of gene expression in bacteria, we describe here a standard cell-free lysate assay that provides a relative measure of resource consumption when a protein coding sequence is expressed. These lysate measurements can then be used with a computational model of translation to predict the in vivo burden placed on growing E. coli cells for a variety of proteins of different functions and lengths. Using this approach, we can predict the burden of expressing multigene operons of different designs and differentiate between the fraction of burden related to gene expression compared to action of a metabolic pathway.
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Journal articleFonseca P, Romano F, Schreck JS, et al., 2018,
Multi-scale coarse-graining for the study of assembly pathways in DNA-brick self assembly
, Journal of Chemical Physics, Vol: 148, ISSN: 0021-9606Inspired by recent successes using single-stranded DNA tiles to producecomplex structures, we develop a two-step coarse-graining approach that usesdetailed thermodynamic calculations with oxDNA, a nucleotide-based model ofDNA, to parametrize a coarser kinetic model that can reach the time and lengthscales needed to study the assembly mechanisms of these structures. We test themodel by performing a detailed study of the assembly pathways for atwo-dimensional target structure made up of 334 unique strands each of whichare 42 nucleotides long. Without adjustable parameters, the model reproduces acritical temperature for the formation of the assembly that is close to thetemperature at which assembly first occurs in experiments. Furthermore, themodel allows us to investigate in detail the nucleation barriers and thedistribution of critical nucleus shapes for the assembly of a single targetstructure. The assembly intermediates are compact and highly connected(although not maximally so) and classical nucleation theory provides a good fitto the height and shape of the nucleation barrier at temperatures close towhere assembly first occurs.
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Journal articleGrob A, Marbiah MM, Isalan M, 2018,
Functional insulator scanning of CpG islands to identify regulatory regions of promoters using CRISPR
, Methods in Molecular Biology, Vol: 1766, Pages: 285-301, ISSN: 1940-6029The ability to mutate a promoter in situ is potentially a very useful approach for gaining insights into endogenous gene regulation mechanisms. The advent of CRISPR/Cas systems has provided simple, efficient, and targeted genetic manipulation in eukaryotes, which can be applied to studying genome structure and function.The basic CRISPR toolkit comprises an endonuclease, Cas9, and a short DNA-targeting sequence, made up of a single guide RNA (sgRNA). The catalytic domains of Cas9 are rendered active upon dimerization of Cas9 with sgRNA, resulting in targeted double stranded DNA breaks. Among other applications, this method of DNA cleavage can be coupled to endogenous homology-directed repair (HDR) mechanisms for the generation of site-specific editing or knockin mutations, at both promoter regulatory and gene coding sequences.A well-characterized regulatory feature of promoter regions is the high abundance of CpGs. These CpG islands tend to be unmethylated, ensuring a euchromatic environment that promotes gene transcription. Here, we demonstrate CRISPR-mediated editing of two CpG islands located within the promoter region of the MDR1 gene (Multi Drug Resistance 1). Cas9 is used to generate double stranded breaks across multiple target sites, which are then repaired while inserting the beta globin (β-globin) insulator, 5′HS5. Thus, we are screening through promoter regulatory sequences with a chromatin barrier element to identify functional regions via “insulator scanning.” Transcriptional and functional assessment of MDR1 expression provides evidence of genome engineering. Overall, this method allows the scanning of CpG islands to identify their promoter functions.
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