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bioRxiv2017

A semi-synthetic strategy for derivatization of the violacein natural product scaffold

Natural products and their analogues are often challenging to synthesise due to their complex scaffolds and embedded functional groups. Solely relying on engineering the biosynthesis of natural products may lead to limited compound diversity. Integrating synthetic biology with synthetic chemistry allows rapid access to much more diverse portfolios of xenobiotic compounds which may accelerate the discovery of new therapeutics. As a proof-of-concept, by supplementing an Escherichia coli strain expressing the violacein biosynthesis pathway with 5-bromo-tryptophan in vitro or tryptophan 7-halogenase RebH in vivo, 6 halogenated analogues of violacein or deoxyviolacein were generated, demonstrating promiscuity of the violacein biosynthesis pathway. Furthermore, 20 new derivatives were generated from 5-brominated violacein analogues via Suzuki-Miyaura cross-coupling reaction directly using the crude extract without prior purification. Herein, we demonstrate a flexible and rapid approach to access diverse chemical space that can be applied to a wide range of natural product scaffolds.

synthetic biology↗

bioRxiv2017

RetroPath2.0: A retrosynthesis workflow for metabolic engineers

Synthetic biology applied to industrial biotechnology is transforming the way we produce chemicals. However, despite advances in the scale and scope of metabolic engineering, the bioproduction process still remains costly. In order to expand the chemical repertoire for the production of next generation compounds, a major engineering biology effort is required in the development of novel design tools that target chemical diversity through rapid and predictable protocols. Addressing that goal involves retrosynthesis approaches that explore the chemical biosynthetic space. However, the complexity associated with the large combinatorial retrosynthesis design space has often been recognized as the main challenge hindering the approach. Here, we provide RetroPath2.0, an automated open source workflow for retrosynthesis based on generalized reaction rules that perform the retrosynthesis search from chassis to target through an efficient and well-controlled protocol. Its easiness of use and the versatility of its applications make of this tool a valuable addition into the biological engineer bench desk. We show through several examples the application of the workflow to biotechnological relevant problems, including the identification of alternative biosynthetic routes through enzyme promiscuity; or the development of biosensors. We demonstrate in that way the ability of the workflow to streamline retrosynthesis pathway design and its major role in reshaping the design, build, test and learn pipeline by driving the process toward the objective of optimizing bioproduction. The RetroPath2.0 workflow is built using tools developed by the bioinformatics and cheminformatics community, because it is open source we anticipate community contributions will likely expand further the features of the workflow.\n\nHighlightsO_LIState-of-the-art Computer-Aided Design retrosynthesis solutions lack open source and ease of use\nC_LIO_LIWe propose RetroPath2.0 a modular and open-source workflow to perform retrosynthesis\nC_LIO_LIRetroPath2.0 computes reaction network between Source and Sink sets of compounds\nC_LIO_LIRetroPath2.0 is distributed as a KNIME workflow for desktop computers\nC_LIO_LIRetroPath2.0 is ready-for-use and distributed with reaction rules\nC_LI\n\nFundingThis work was supported by the French National Research Agency [ANR-15-CE1-0008], the Biotechnology and Biological Sciences Research Council, Centre for synthetic biology of fine and speciality chemicals [BB/M017702/1]; Synthetic Biology Applications for Protective Materials [EP/N025504/1], and GIP Genopole.

systems biology↗

bioRxiv2018

Stochasticity of cellular growth: sources, propagation and consequences

Cellular growth impacts a range of phenotypic responses. Identifying the sources of fluctuations in growth and how they propagate across the cellular machinery can unravel mechanisms that underpin cell decisions. We present a stochastic cell model linking gene expression, metabolism and replication to predict growth dynamics in single bacterial cells. In addition to several population-averaged data, the model quantitatively recovers how growth fluctuations in single cells change across nutrient conditions. We develop a framework to analyse stochastic chemical reactions coupled with cell divisions and use it to identify sources of growth heterogeneity. By visualising cross-correlations we then determine how such initial fluctuations propagate to growth rate and affect other cell processes. We further study antibiotic responses and find that complex drug-nutrient interactions can both enhance and suppress heterogeneity. Our results provide a predictive framework to integrate single-cell and bulk data and draw testable predictions with implications for antibiotic tolerance, evolutionary biology and synthetic biology.

systems biology↗

bioRxiv2017

Population regulation in microbial consortia using dual feedback control

An ongoing area of study in synthetic biology has been the design and construction of synthetic circuits that maintain homeostasis at the population level. Here, we are interested in designing a synthetic control circuit that regulates the total cell population and the relative ratio between cell strains in a culture containing two different cell strains. We have developed a dual feedback control strategy that uses two separate control loops to achieve the two functions respectively. By combining both of these control loops, we have created a population regulation circuit where both the total population size and relative cell type ratio can be set by reference signals. The dynamics of the regulation circuit show robustness and adaptation to perturbations in cell growth rate and changes in cell numbers. The control architecture is general and could apply to any organism for which synthetic biology tools for quorum sensing, comparison between outputs, and growth control are available.

synthetic biology↗

bioRxiv2016

A new improved and extended version of the multicell bacterial simulator gro

gro is a cell programming language developed in Klavins Lab for simulating colony growth and cell-cell communication. It is used as a synthetic biology prototyping tool for simulating multicellular biocircuits. In this work, we present several extensions made to gro that improve the performance of the simulator, make it easier to use and provide new functionalities. The new version of gro is between one and two orders of magnitude faster than the original version. It is able to grow microbial colonies with up to 105 cells in less than 20 minutes. A new library, CellEngine, accelerates the resolution of spatial physical interactions between growing and dividing cells by implementing a new shoving algorithm. A genetic library, CellPro, based on Probabilistic Timed Automata, simulates gene expression dynamics using simplified and easy to compute digital proteins. We also propose a more convenient language specification layer, ProSpec, based on the idea that proteins drive cell behavior. CellNutrient, another library, implements Monod-based growth and nutrient uptake functionalities. The intercellular signaling management was improved and extended in a library called CellSignals. Finally, bacterial conjugation, another local cell-cell communication process, was added to the simulator. To show the versatility and potential outreach of this version of gro, we provide studies and novel examples ranging from synthetic biology to evolutionary microbiology. We believe that the upgrades implemented for gro have made it into a powerful and fast prototyping tool capable of simulating a large variety of systems and synthetic biology designs.

synthetic biology↗

bioRxiv2017

Rapid and scalable preparation of bacterial lysates for cell-free gene expression

Cell-free gene expression systems are emerging as an important platform for a diverse range of synthetic biology and biotechnology applications, including production of robust field-ready biosensors. Here, we combine programmed cellular autolysis with a freeze-thaw or freeze-dry cycle to create a practical, reproducible, and a labor- and cost-effective approach for rapid production of bacterial lysates for cell-free gene expression. Using this method, ro-bust and highly active bacterial cell lysates can be produced without specialized equipment at a wide range of scales, making cell-free gene expression easily and broadly accessible. More-over, live autolysis strain can be freeze-dried directly and subsequently lysed upon rehydration to produce active lysate. We demonstrate the utility of autolysates for synthetic biology by reg-ulating protein production and degradation, implementing quorum sensing, and showing quan-titative protection of linear DNA templates by GamS protein. To allow versatile and sensitive {beta}-galactosidase (LacZ) based readout we produce autolysates with no detectable background LacZ activity and use them to produce sensitive mercury(II) biosensors with LacZ-mediated colorimetric and fluorescent outputs. The autolysis approach can facilitate wider adoption of cell-free technology for cell-free gene expression as well as other synthetic biology and biotechnology applications, such as metabolic engineering, natural product biosynthesis, or proteomics.

synthetic biology↗

bioRxiv2018

CyanoGate: A Golden Gate modular cloning suite for engineering cyanobacteria based on the plant MoClo syntax

Recent advances in synthetic biology research have been underpinned by an exponential increase in available genomic information and a proliferation of advanced DNA assembly tools. The adoption of plasmid vector assembly standards and parts libraries has greatly enhanced the reproducibility of research and exchange of parts between different labs and biological systems. However, a standardised Modular Cloning (MoClo) system is not yet available for cyanobacteria, which lag behind other prokaryotes in synthetic biology despite their huge potential in biotechnological applications. By building on the assembly library and syntax of the Plant Golden Gate MoClo kit, we have developed a versatile system called CyanoGate that unites cyanobacteria with plant and algal systems. We have generated a suite of parts and acceptor vectors for making i) marked/unmarked knock-outs or integrations using an integrative acceptor vector, and ii) transient multigene expression and repression systems using known and novel replicative vectors. We have tested and compared the CyanoGate system in the established model cyanobacterium Synechocystis sp. PCC 6803 and the more recently described fast-growing strain Synechococcus elongatus UTEX 2973. The system is publicly available and can be readily expanded to accommodate other standardised MoClo parts.

synthetic biology↗

bioRxiv2017

Expressing Biologically Active Membrane Proteins in a Cell-Free Transcription-Translation Platform

Cell-free transcription-translation platforms have been widely utilized to express soluble proteins in basic synthetic biological circuit prototyping. From a synthetic biology point of view, it is critical to express membrane proteins in cell-free transcription-translation systems, and use them directly in biocircuits, considering the fact that histidine kinases, G-protein coupled receptors (GPCRs) and other important biosensors are all membrane proteins. Previous studies have expressed membrane proteins in cell-free systems with the help of detergents, liposomes or nanodiscs, but have not demonstrated the ability to prototype circuit behavior for the purpose of testing more complex circuit functions involving membrane-bound proteins. Built on previous efforts, in this work we demonstrated that we could co-translationally express solubilized and active membrane proteins in our cell-free TX-TL platform with membrane-like materials. We first tested the expression of several constructs with {beta}1 and {beta}2 adrenergic receptors in TX-TL and observed significant insoluble membrane protein production. The addition of nanodiscs to the cell free expression system enabled solubilization of membrane proteins. Nanodisc is lipoprotein-based membrane-like material. The activity of {beta}2 adrenergic receptor was tested with both fluorescence and Surface Plasmon Resonance (SPR) binding assays by monitoring the specific binding response of small-molecule binders, carazolol and norepinephrine. Our results suggest that it is promising to use cell-free expression systems to prototype synthetic biocircuits involving single chain membrane proteins without extra procedures. This data made us one step closer to testing complex membrane protein circuits in cell-free environment.

bioengineering↗

bioRxiv2018

Linear-double-stranded DNA (ldsDNA) based AND logic computation in mammalian cells

Synthetic biology employs engineering principles to redesign biological system for clinical or industrial purposes. The development and application of novel genetic devices for genetic circuits construction will facilitate the rapid development of synthetic biology. Here we demonstrate that mammalian cells could perform two- and three-input linear-double-stranded DNA (ldsDNA) based Boolean AND logic computation. Through hydrodynamic ldsDNA delivery, two-input ldsDNA-base AND-gate computation could be achieved in vivo. Inhibition of DNA-PKcs expression, a key enzyme in non-homologous end joining (NHEJ), could significantly downregulate the intensity of output signals from ldsDNA-based AND-gate. We further reveal that in mammalian cells ldsDNAs could undergo end processing and then perform AND-gate calculation to generate in-frame output proteins. Moreover, we show that ldsDNAs or plasmids with identical overlapping sequences could also serve as inputs of AND-gate computation. Our work establishes novel genetic devices and principles for genetic circuits construction, thus may open a new gate for the development of new disease targeting strategies and new protein genesis methodologies.

synthetic biology↗

bioRxiv2017

Native and engineered clifednamide biosynthesis in multiple Streptomyces spp.

Polycyclic tetramate macrolactam (PTM) natural products are produced by actinomycetes and other bacteria. PTMs are often bioactive, and the simplicity of their biosynthetic clusters make them attractive for bioengineering. Clifednamide-type PTMs from Streptomyces sp. JV178 contain a distinctive ketone group, suggesting the existence of a novel PTM oxidizing enzyme. Here, we report the new cytochrome P450 enzyme (CftA) is required for clifednamide production. Genome mining was used to identify several new clifednamide producers, some having improved clifednamide yields. Using a parallel synthetic biology approach, CftA isozymes were used to engineer the ikarugamycin pathway of Streptomyces sp. NRRL F-2890 to yield clifednamides. Further, we observed that strong CftA expression leads to the production of a new PTM, clifednamide C. We demonstrate the utility of both genome mining and synthetic biology to rapidly increase clifednamide production and identify a PTM tailoring enzyme for rational molecule design.

synthetic biology↗

bioRxiv2016

Tellurium: A Python Based Modeling and Reproducibility Platform for Systems Biology

In this article, we present Tellurium, a powerful Python-based integrated environment designed for model building, analysis, simulation and reproducibility in systems and synthetic biology. Tellurium is a modular, cross-platform, and open-source integrated development environment (IDE) composed of multiple libraries, plugins, and specialized modules and methods. Tellurium ensures exchangeability and reproducibility of computational models by supporting SBML (Systems Biology Markup Language), SED-ML (Simulation Experiment Description Markup Language), the COMBINE archive, and SBOL (Synthetic Biology Open Language). Tellurium is a self-contained modeling platform which comes with a fully configured Python distribution independent of other local Python installations on the target machine. The main interface is based on the Spyder IDE which has a highly accessible user interface akin to MATLAB (https://www.mathworks.com/). Tellurium uses libRoadRunner as the default SBML simulation engine due to its superior performance, scalability and ease of integration. libRoadRunner supports deterministic simulations, stochastic simulations and steady state analyses. Tellurium also includes Antimony, a human-readable model definition language which can be converted to and from SBML. Other standard Python scientific libraries such as NumPy, SciPy, and matplotlib are included by default. Additionally, we include several user-friendly plugins and advanced modules for a wide-variety of applications, ranging from visualization tools to complex algorithms for bifurcation analysis and multi-dimensional parameter scanning. By combining multiple libraries, plugins, and modules into a single package, Tellurium provides a unified but extensible solution for biological modeling and simulation.

Systems Biology↗

bioRxiv2017

Selenzyme: Enzyme selection tool for pathway design

Synthetic biology applies the principles of engineering to biology in order to create biological functionalities not seen before in nature. One of the most exciting applications of synthetic biology is the design of new organisms with the ability to produce valuable chemicals including pharmaceuticals and biomaterials in a greener; sustainable fashion. Selecting the right enzymes to catalyze each reaction step in order to produce a desired target compound is, however, not trivial. Here, we present Selenzyme, a free online enzyme selection tool for metabolic pathway design. The user is guided through several decision steps in order to shortlist the best candidates for a given pathway step. The tool graphically presents key information about enzymes based on existing databases and tools such as: similarity of sequences and of catalyzed reactions; phylogenetic distance between source organism and intended host species; multiple alignment highlighting conserved regions, predicted catalytic site, and active regions; and relevant properties such as predicted solubility and transmembrane regions. Selenzyme provides bespoke sequence selection for automated workflows in biofoundries. The tool is integrated as part of the pathway design stage into the design-build-test-learn SYNBIOCHEM pipeline. The Selenzyme web server is available at http://selenzyme.synbiochem.co.uk.

bioinformatics↗

bioRxiv2026

Living electronic transistors with tunable conductivity

Electroactive bacteria, like Shewanella oneidensis, can couple the oxidation of organic electron donors to the reduction of external conductive surfaces, such as minerals and electrodes, by utilizing multiheme cytochromes to carry charge from within the cell to external surfaces. Additionally, multiheme cytochromes facilitate gateable, long-distance (micrometer-scale) redox conduction along the outer membrane and across multiple cells bridging electrodes. While electroactive microbes are being used to develop bioelectrochemical devices, there have been limited efforts to use synthetic biology to exert additional control over microbes serving as device components. Thus, this work implements an optogenetic biofilm patterning gene circuit and a small molecule sensor in S. oneidensis to simultaneously control cell deposition and cytochrome expression. This allows for photolithographic patterning of biofilms possessing tunable electrical properties controlled with small molecules. This system demonstrates tunable electrochemical activity, redox conduction, intrinsic biofilm conductivity, and negative differential transconductance as a function of cytochrome expression. Additionally, temperature-dependent measurements of this tunable biofilm conduction reveal changes in activation energy as a function of cytochrome expression. Through this combination of synthetic biology and electrochemistry, simultaneous control over biofilm geometry and conductivity sheds light on fundamental microbial electron transport processes, and it enables the construction of living electronic devices.

synthetic biology↗

bioRxiv2016

How Cancer Genomics Drives Cancer Biology: Does Synthetic Lethality Explain Mutually Exclusive Oncogenic Mutations?

Large-scale analyses of cancer genomes are revealing patterns of mutations that suggest biologically significant ideas about many aspects of cancer, including carcinogenesis, classification, and preventive and therapeutic strategies. Among those patterns is \"mutual exclusivity\", a phenomenon observed when two or more mutations that are commonly observed in samples of a type of cancer are not found combined in individual tumors. We have been studying a striking example of mutual exclusivity: the absence of co-existing mutations in the KRAS and EGFR proto-oncogenes in human lung adenocarcinomas, despite the high individual frequencies of such mutations in this common type of cancer. Multiple lines of evidence suggest that toxic effects of the joint expression of KRAS and EGFR mutant oncogenes, rather than loss of any selective advantages conferred by a second oncogene that operates through the same signaling pathway, are responsible for the observed mutational pattern. We discuss the potential for understanding the physiological basis of such toxicity, for exploiting it therapeutically, and for extending the studies to other examples of mutual exclusivity.

cancer biology↗

bioRxiv2018

HEx: a heterologous expression platform for the discovery of fungal natural products

For decades, fungi have been a source of FDA-approved natural products such as penicillin, cyclosporine, and the statins. Recent breakthroughs in DNA sequencing suggest that millions of fungal species exist on Earth with each genome encoding pathways capable of generating as many as dozens of natural products. However, the majority of encoded molecules are difficult or impossible to access because the organisms are uncultivable or the genes are transcriptionally silent. To overcome this bottleneck in natural product discovery, we developed the HEx (Heterologous EXpression) synthetic biology platform for rapid, scalable expression of fungal biosynthetic genes and their encoded metabolites in Saccharomyces cerevisiae. We applied this platform to 41 fungal biosynthetic gene clusters from diverse fungal species from around the world, 22 of which produced detectable compounds. These included novel compounds with unexpected biosynthetic origins, particularly from poorly studied species. This result establishes the HEx platform for rapid discovery of natural products from any fungal species, even those that are uncultivable, and opens the door to discovery of the next generation of natural products.\n\nSummaryHere we present the largest scale effort reported to date toward the complete refactoring and heterologous expression of fungal biosynthetic gene clusters utilizing HEx, a novel synthetic biology platform.

synthetic biology↗

bioRxiv2017

Computational Re-Design of Synthetic Genetic Oscillators for Independent Amplitude and Frequency Modulation

Engineering robust and tuneable genetic clocks is a topic of current interest in Systems and Synthetic Biology with wide applications in biotechnology. Synthetic genetic oscillators share a common structure based on a negative feedback loop with a time delay, and generally display only limited tuneability. Recently, the dual-feedback oscillator was demonstrated to be robust and tuneable, to some extent, by the use of chemical inducers. Yet no engineered genetic oscillator currently allows for the independent modulation of amplitude and period. In this work, we demonstrate computationally how recent advances in tuneable synthetic degradation can be used to decouple the frequency and amplitude modulation in synthetic genetic oscillators. We show how the range of tuneability can be increased by connecting additional input dials, e.g. orthogonal transcription factors that respond to chemical, temperature or even light signals. Modelling and numerical simulations predict that our proposed re-designs enable amplitude tuning without period modulation, coupled modulation of both period and amplitude, or period adjustment with near-constant amplitude. We illustrate our work through computational re-designs of both the dual-feedback oscillator and the repressilator, and show that the repressilator is more flexible and can allow for independent amplitude and near-independent period modulation.

synthetic biology↗

bioRxiv2018

Optimally designed vs intuition-driven inputs: the study case of promoter activity modelling

Synthetic biology is an emerging engineering discipline that aims at synthesising logical circuits into cells to accomplish new functions. Despite a thriving community and some notable successes, the basic task of assembling predictable gene circuits is still a key challenge. Mathematical models are uniquely suited to help solve this issue. Yet in biology they are perceived as expensive and laborious to obtain because low-information experiments have often been used to infer model parameters. How much additional information can be gained using optimally designed experiments? To tackle this question we consider a building block in Synthetic Biology, an inducible promoter in yeast S. cerevisiae. Using in vivo data we re-fit a mathematical model for such a system; we then compare in silico the quality of the parameter estimates when model calibration is done using typical (e.g. step inputs) and optimally designed experiments. We find that Optimal Experimental Design leads to ~70% improvement in the predictive ability of the inferred models. We conclude providing suggestions on how optimally designed experiments can be implemented in vivo.

bioengineering↗

bioRxiv2017

dRNA-seq implicates sulfide as master regulator of S(0) metabolism in Chlorobaculum tepidum and other green sulfur bacteria

The green sulfur bacteria (Chlorobiaceae) are anaerobes that use electrons from reduced sulfur compounds (sulfide, S(0), and thiosulfate) as electron donors for photoautotrophic growth. Chlorobaculum tepidum, the model system for the Chlorobiaceae, both produces and consumes extracellular S(0) globules depending on the availability of sulfide in the environment. These physiological changes imply significant changes in gene regulation, which has been observed when sulfide is added to Cba. tepidum growing on thiosulfate. However, the underlying mechanisms driving these gene expression changes, i.e. specific regulators and promoter elements involved, have not yet been defined. Here, differential RNA-seq (dRNA-seq) was used to globally identify transcript start sites (TSS) that were present during growth on sulfide, biogenic S(0), and thiosulfate as sole electron donors. TSS positions were used in combination with RNA-seq data from cultures growing on these same electron donors to identify both basal promoter elements and motifs associated with electron donor dependent transcriptional regulation. These motifs were conserved across homologous Chlorobiaceae promoters. Two lines of evidence suggest that sulfide mediated repression is the dominant regulatory mode in Cba. tepidum. First, motifs associated with genes regulated by sulfide overlap key basal promoter elements. Second, deletion of the gene CT1277, encoding a putative regulatory protein, leads to constitutive over-expression of the sulfide:quinone oxidoreductase CT1087 in the absence of sulfide. The results suggest that sulfide is the master regulator of sulfur metabolism in Cba. tepidum and the Chlorobiaceae. Finally, the identification of basal promoter elements with differing strengths will further the development of synthetic biology in Cba. tepidum and perhaps other Chlorobiaceae.\n\nImportanceElemental sulfur is a key intermediate in biogeochemical sulfur cycling. The photoautotrophic green sulfur bacterium Chlorobaculum tepidum both produces and consumes elemental sulfur depending on the availability of sulfide in the environment. Our results reveal transcriptional dynamics of Chlorobaculum tepidum on elemental sulfur, and increase our understanding of the mechanisms of transcriptional regulation governing growth on different reduced sulfur compounds. This study identifies new genes and sequence motifs that likely play significant roles in the production and consumption of elemental sulfur. Beyond this focused impact, this study paves the way for the development of synthetic biology in Chlorobaculum tepidum and other Chlorobiaceae by providing a comprehensive identification of promoter elements to control gene expression, a key element of strain engineering.

microbiology↗