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bioRxiv2018

Designer Sinorhizobium meliloti strains and multi-functional vectors for direct inter-kingdom transfer of high G+C content DNA

Storage and manipulation of large DNA fragments is crucial for synthetic biology applications, yet DNA with high G+C content can be unstable in many host organisms. Here, we report the development of Sinorhizobium meliloti as a new universal host that can store DNA, including high G+C content, and mobilize DNA to Escherichia coli, Saccharomyces cerevisiae, and the eukaryotic microalgae Phaeodactylum tricornutum. We deleted the S. meliloti hsdR restriction-system to enable DNA transformation with up to 1.4 x 105 efficiency. Multi-host and multi-functional shuttle vectors (MHS) were constructed and shown to stably replicate in S. meliloti, E. coli, S. cerevisiae, and P. tricornutum, with a copy-number inducible E. coli origin for isolating plasmid DNA. Crucially, we demonstrated that S. meliloti can act as a universal conjugative donor for MHS plasmids with a cargo of at least 62 kb of G+C rich DNA derived from Deinococcus radiodurans.

synthetic biology↗

bioRxiv2018

Two new plasmid post-segregational killing mechanisms for the implementation of synthetic gene networks in E. coli

Plasmids are the workhorse of both industrial biotechnology and synthetic biology, but ensuring they remain in bacterial cells is a challenge. Antibiotic selection, commonly used in the laboratory, cannot be used to stabilise plasmids in most real-world applications, and inserting dynamical gene networks into the genome is difficult. Plasmids have evolved several mechanisms for stability, one of which, post-segregational killing (PSK), ensures that plasmid-free cells do not grow or survive. Here we demonstrate the plasmid-stabilising capabilities of the axe/txe two component system and the microcin-V system in the probiotic bacteria Escherichia coli Nissle 1917 and show they can outperform the hok/sok system commonly used in biotechnological applications. Using plasmid stability assays, automated flow cytometry analysis, mathematical models and Bayesian statistics we quantified plasmid stability in vitro. Further, we used an in vivo mouse cancer model to demonstrate plasmid stability in a real-world therapeutic setting. These new PSK systems, plus the developed Bayesian methodology, will have wide applicability in clinical and industrial biotechnology.

synthetic biology↗

bioRxiv2017

Uncovering cell-free protein expression dynamics by a promoter library with diverse strengths

Cell-free protein expression systems have been widely used for synthetic biology and metabolic engineering applications in recent years. Yet little is known about protein expression in the cell-free systems. Here we take a systems approach to uncover underlying dynamics of cell-free protein expression. We construct a set of T7 promoter variants to express proteins at different transcription rates in a reconstituted and E. coli extract-based cell-free systems. We find that the maximum expression level and the rate of protein synthesis as responses to the transcription rate change are different in the two cell-free systems, suggesting they are driven by different expression dynamics. We confirm this by constructing a simple mathematical model for each cell-free system, which well reproduce the experimental results and also identify different limiting factors for better protein expression in the two cell-free systems. In particular, they revealed there is a negative feedback effect in the mRNA-protein translation by the PURE system and also identified different limiting factors for better protein expression in the two cell-free systems.

synthetic biology↗

bioRxiv2017

A plasmid-based Escherichia coli gene expression system with cell-to-cell variation below the extrinsic noise limit

Experiments in synthetic biology and microbiology can benefit from protein expression systems with low cell-to-cell variability (noise) and expression levels precisely tunable across a useful dynamic range. Despite advances in understanding the molecular biology of microbial gene regulation, many experiments employ protein-expression systems exhibiting high noise and nearly all-or-none responses to induction. I present an expression system that incorporates elements known to reduce gene expression noise: negative autoregulation and bicistronic transcription. I show by stochastic simulation that while negative autoregulation can produce a more gradual response to induction, bicistronic expression of a repressor and gene of interest can be necessary to reduce noise below the extrinsic limit. I synthesized a plasmid-based system incorporating these principles and studied its properties in Escherichia coli cells, using flow cytometry and fluorescence microscopy to characterize induction dose-response, induction/repression kinetics and gene expression noise. By varying ribosome binding site strengths, expression levels from 55-- 10,740 molecules/cell were achieved with noise below the extrinsic limit. Individual strains are inducible across a dynamic range greater than 20-fold. Experimental comparison of different regulatory networks confirmed that bicistronic autoregulation reduces noise, and revealed unexpectedly high noise for a conventional expression system with a constitutively expressed transcriptional repressor. I suggest a hybrid, low-noise expression system to increase the dynamic range.

synthetic biology↗

bioRxiv2015

Improving fold activation of small transcription activating RNAs (STARs) with rational RNA engineering strategies.

Engineered RNAs have become integral components of the synthetic biology and bioengineering toolbox for controlling gene expression. We recently expanded this toolbox by creating small transcription activating RNAs (STARs) that act by disrupting the formation of a target transcriptional terminator hairpin placed upstream of a gene. While STARs are a promising addition to the repertoire of RNA regulators, much work remains to be done to optimize the fold activation of these systems. Here we apply rational RNA engineering strategies to improve the fold activation of two STAR regulators. We demonstrate that a combination of promoter strength tuning and multiple RNA stabilization strategies can improve fold activation from 5.4-fold to 13.4-fold for a STAR regulator derived from the pbuE riboswitch terminator. We then validate the generality of our approach and show that these same strategies improve fold activation from 2.1-fold to 14.6-fold for an unrelated STAR regulator. We also establish that the optimizations preserve the orthogonality of these STARs between themselves and a set of antisense RNA transcriptional repressors, enabling these optimized STARs to be used in more sophisticated circuits. These optimization strategies open the door for creating a generation of additional STARs to use in a broad array of biotechnologies.

Synthetic Biology↗

bioRxiv2017

Optimization-based synthesis of stochastic biocircuits with statistical specifications

Model-guided design has become a standard approach to engineering biomolecular circuits in current synthetic biology. However, the stochastic nature of biomolecular reactions is often overlooked in the design process. As a result, cell-cell heterogeneity causes unexpected deviation of biocircuit behaviors from model predictions and requires additional iterations of design-build-test cycles. To enhance the design process of stochastic biocircuits, this paper presents a computational framework to systematically specify the level of intrinsic noise using well-defined metrics of statistics and design highly heterogeneous biocircuits based on the specifications. Specifically, we use descriptive statistics of population distributions as an intuitive specification language of stochastic biocircuits and develop an optimization based computational tool that explores parameter configurations satisfying design requirements. Sensitivity analysis methods are also developed to ensure the robustness of a biocircuit design. These design tools are formulated using convex optimization programs to enable efficient and rigorous quantification of the statistics without approximation, and thus, they are amenable to the synthesis of stochastic biocircuits that require high reliability. We demonstrate these features by designing a stochastic negative feedback biocircuit that satisfies multiple statistical constraints. In particular, we use a rigorously quantified parameter map of feasible design space to perform in-depth study of noise propagation and regulation in negative feedback pathways.

synthetic biology↗

bioRxiv2017

Sequence Specific Modeling of E. coli Cell-Free Protein Synthesis

Cell-free protein synthesis (CFPS) is a widely used research tool in systems and synthetic biology. However, if CFPS is to become a mainstream technology for applications such as point of care manufacturing, we must understand the performance limits and costs of these systems. Toward this question, we used sequence specific constraint based modeling to evaluate the performance of E. coli cell-free protein synthesis. A core E. coli metabolic network, describing glycolysis, the pentose phosphate pathway, energy metabolism, amino acid biosynthesis and degradation was augmented with sequence specific descriptions of transcription and translation and effective models of promoter function. Model parameters were largely taken from literature, thus the constraint based approach coupled the transcription and translation of the protein product, and the regulation of gene expression, with the availability of metabolic resources using only a limited number of adjustable model parameters. We tested this approach by simulating the expression of two model proteins: chloramphenicol acetyltransferase and dual emission green fluorescent protein, for which we have training data sets; we then expanded the simulations to a range of additional proteins. Protein expression simulations were consistent with measurements for a variety of cases. The constraint based simulations confirmed that oxidative phosphorylation was active in the CAT cell-free extract, as without it there was no feasible solution within the experimental constraints of the system. We then compared the metabolism of theoretically optimal and experimentally constrained CFPS reactions, and developed parameter free correlations which could be used to estimate productivity as a function of protein length and promoter type. Lastly, global sensitivity analysis identified the key metabolic processes that controlled CFPS productivity and energy efficiency. In summary, sequence specific constraint based modeling of CFPS offered a novel means to a priori estimate the performance of a cell-free system, using only a limited number of adjustable parameters. While we modeled the production of a single protein in this study, the approach could easily be extended to multi-protein synthetic circuits, RNA circuits or the cell free production of small molecule products.

synthetic biology↗

bioRxiv2018

Characterizing Genetic Circuit Components in E. coli towards a Campylobacter jejuni Biosensor.

Campylobacter jejuni is responsible for most cases of bacterial gastroenteritis (food poisoning) in the United Kingdom. The most common routes of transmission are by contact with raw poultry. Current detection systems for the pathogen are time-consuming, expensive or inaccessible for everyday users. In this article we propose a cheaper and faster system for detection of C. jejuni using a synthetic biology approach. We aimed to detect C. jejuni by the presence of xylulose, an uncommon bacterial capsular saccharide. We characterized two sugar-based regulatory systems that displayed potential to act as tools for detection of xylulose. Using a two-plasmid reporter system in Escherichia coli, we investigated the regulatory protein component (MtlR) of the mannitol operon from Pseudomonas fluorescens. Our findings suggest that the promoter of mtlE is activated by MtlR in the presence of a variety of sugar inducer molecules, and may exhibit cross-activity with a native regulator of E. coli. Additionally, we engineered the L-arabinose transcriptional activator (AraC) of E. coli for altered ligand specificity. We performed site-specific saturation mutagenesis to generate AraC variants with altered effector specificity, with an aim to generate a mutant activated by xylulose. We characterized several mutant AraC variants which have lost the ability to respond specifically to the native L-arabinose effector. We promote this technique as a powerful tool for future iGEM teams to create regulatory circuits activated by novel small molecule ligands.

synthetic biology↗

bioRxiv2018

Creation and multi-omics characterization of a genomically hybrid strain in the nitrogen-fixing symbiotic bacterium Sinorhizobium meliloti

Many bacteria, often associated with eukaryotic hosts and of relevance for biotechnological applications, harbour a multipartite genome composed by more than one replicon. Biotechnologically relevant phenotypes are often encoded by genes residing on the secondary replicons. A synthetic biology approach to developing enhanced strains for biotechnological purposes could therefore involve merging pieces or entire replicons from multiple strains into a single genome. Here we report the creation of a genomic hybrid strain in a model multipartite genome species, the plant-symbiotic bacterium Sinorhizobium meliloti. In particular, we moved the secondary replicon pSymA (accounting for nearly 20% of total genome content) from a donor S. meliloti strain to an acceptor strain. The cis-hybrid strain was screened for a panel of complex phenotypes (carbon/nitrogen utilization phenotypes, intra- and extra-cellular metabolomes, symbiosis, and various microbiological tests). Additionally, metabolic network reconstruction and constraint-based modelling were employed for in silico prediction of metabolic flux reorganization. Phenotypes of the cis-hybrid strain were in good agreement with those of both parental strains. Interestingly, the symbiotic phenotype showed a marked cultivar-specific improvement with the cis-hybrid strains compared to both parental strains. These results provide a proof-of-principle for the feasibility of genome-wide replicon-based remodelling of bacterial strains for improved biotechnological applications in precision agriculture.

synthetic biology↗

bioRxiv2017

Toward a Genome Scale Sequence Specific Dynamic Model of Cell-Free Protein Synthesis in Escherichia coli

Cell-free protein expression systems have become widely used in systems and synthetic biology. In this study, we developed an ensemble of dynamic E. coli cell-free protein synthesis (CFPS) models. Model parameters were estimated from a training dataset for the cell-free production of a protein product, chloramphenicol acetyltransferase (CAT). The dataset consisted of measurements of glucose, organic acids, energy species, amino acids, and CAT. The ensemble accurately predicted these measurements, especially those of the central carbon metabolism. We then used the trained model to evaluate the optimality of protein production. CAT was produced with an energy efficiency of 12%, suggesting that the process could be further optimized. Reaction group knockouts showed that protein productivity and the metabolism as a whole depend most on oxidative phosphorylation and glycolysis and gluco-neogenesis. Amino acid biosynthesis is also important for productivity, while the overflow metabolism and TCA cycle affect the overall system state. In addition, the translation rate is shown to be more important to productivity than the transcription rate. Finally, CAT production was robust to allosteric control, as was most of the network, with the exception of the organic acids in central carbon metabolism. This study is the first to use kinetic modeling to predict dynamic protein production in a cell-free E. coli system, and should provide a foundation for genome scale, dynamic modeling of cell-free E. coli protein synthesis.

synthetic biology↗

bioRxiv2017

Scalable composition frameworks for multicellular logic

A major goal of synthetic biology is to reprogram living organisms to solve pressing challenges in manufacturing, environmental remediation, or healthcare. While many types of genetic logic gates have been engineered, their scalability remains limited. Previous work demonstrated that Distributed Multicellular Computation (DMC) enables the implementation of complex logic within cellular consortia. However, current DMC systems require spatial separation of cellular subpopulation to be scalable to N-inputs, and need cell-cell communication channels to operate. Here we present scalable composition frameworks for the systematic design of multicellular consortia performing recombinase-based Boolean or history-dependent logic, and integrating an arbitrary number of inputs. The theoretical designs for both Boolean and history-dependent logic are based on reduced sets of computational modules implemented into specific cellular subpopulations which can then be combined in various manners to implement all logic functions. Our systems mark a departure from previous DMC architectures as they do not require either cell-cell communication nor spatial separation, greatly facilitating their implementation and making them fully autonomous. Due to their scalability and composability, we anticipate that the design strategies presented here will help researchers and engineers to reprogram cellular behavior for various applications in a streamlined manner. We provide an online tool for automated design of DNA architectures allowing the implementation of multicellular N-inputs logic functions at: http://synbio.cbs.cnrs.fr/calin.

synthetic biology↗

bioRxiv2018

Optimization of Golden Gate assembly through application of ligation sequence-dependent fidelity and bias profiling

Modern synthetic biology depends on the manufacture of large DNA constructs from libraries of genes, regulatory elements or other genetic parts. Type IIS restriction enzyme-dependent DNA assembly methods (e.g., Golden Gate) enable rapid one-pot, ordered, multi-fragment DNA assembly, facilitating the generation of high-complexity constructs. The order of assembly of genetic parts is determined by the ligation of flanking Watson-Crick base-paired overhangs. The ligation of mismatched overhangs leads to erroneous assembly, and the need to avoid such pairings has typically been accomplished by using small sets of empirically vetted junction pairs, limiting the number of parts that can be joined in a single reaction. Here, we report the use of a comprehensive method for profiling end-joining ligation fidelity and bias to predict highly accurate sets of connections for ligation-based DNA assembly methods. This data set allows quantification of sequence-dependent ligation efficiency and identification of mismatch-prone pairings. The ligation profile accurately predicted junction fidelity in ten-fragment Golden Gate assembly reactions, and enabled efficient assembly of a lac cassette from up to 24-fragments in a single reaction. Application of the ligation fidelity profile to inform choice of junctions thus enables highly flexible assembly design, with >20 fragments in a single reaction.

synthetic biology↗

bioRxiv2018

Coiled Coil-Mediated Assembly of an Icosahedral Protein Cage with Extremely High Thermal and Chemical Stability

The organization of protein molecules into higher-order nanoscale architectures is ubiquitous in Nature and represents an important goal in synthetic biology. Here we describe the symmetry-directed design of a hollow protein cage with dimensions similar to those of many icosahedral viruses. The cage was constructed based on icosahedral symmetry by genetically fusing a trimeric protein (TriEst) to a small pentameric de novo-designed coiled coil domain, separated by a flexible oligo-glycine linker sequence. Screening a small library of designs in which the linker length varied from 2 to 12 residues identified a construct containing 8 glycine residues (Ico8) that formed well-defined cages. Characterization by dynamic light scattering, negative stain and cryo EM, and by atomic force and IR-photo-induced force microscopy established that Ico8 assembles into a flexible hollow cage with comprising 60-subunits with overall icosahedral geometry. Unexpectedly, the cages were found to encapsulate DNA, even though neither protein component binds nucleic acids on its own. Notably, the cages formed by Ico8 proved to be extremely stable towards thermal and chemical denaturation: whereas TriEst was unfolded by heating (Tm ~75 {degrees}C) or denatured by 1.5 M guanidine hydrochloride, the Ico8 cages remained folded even at 120 {degrees}C or in 8 M guanidine hydrochloride. The encapsulation of DNA and increased stability of the cages are new properties that emerge from the higher order structure of the protein cage, rather than being intrinsic to the components from which it is constructed.

synthetic biology↗

bioRxiv2018

Deconstructing cell-free extract preparation for in vitro activation of transcriptional genetic circuitry

Recent advances in cell-free gene expression (CFE) systems have enabled their use for a host of synthetic biology applications, particularly for rapid prototyping of genetic circuits designed as biosensors. Despite the proliferation of cell-free protein synthesis platforms, the large number of currently existing protocols for making CFE extracts muddles the collective understanding of how the method by which an extract is prepared affects its functionality. Specifically, a key goal toward developing cell-free biosensors based on native genetic regulators is activating the transcriptional machinery present in bacterial extracts for protein synthesis. However, protein yields from genes transcribed in vitro by the native Escherichia coli RNA polymerase are quite low in conventional crude extracts originally optimized for expression by the bacteriophage transcriptional machinery. Here, we show that cell-free expression of genes under bacterial {sigma}70 promoters is constrained by the rate of transcription in crude extracts and that processing the extract with a ribosomal run-off reaction and subsequent dialysis can alleviate this constraint. Surprisingly, these processing steps only enhance protein synthesis in genes under native regulation, indicating that the translation rate is unaffected. We further investigate the role of other common process variants on extract performance and demonstrate that bacterial transcription is inhibited by including glucose in the growth culture, but is unaffected by flash-freezing the cell pellet prior to lysis. Our final streamlined protocol for preparing extract by sonication generates extract that facilitates expression from a diverse set of sensing modalities including protein and RNA regulators. We anticipate that this work will clarify the methodology for generating CFE extracts that are active for biosensing and will encourage the further proliferation of cell-free gene expression technology for new applications.

synthetic biology↗

bioRxiv2017

A Synthetic Microbial Operational Amplifier

Synthetic biology has created oscillators, latches, logic gates, logarithmically linear circuits, and load drivers that have electronic analogs in living cells. The ubiquitous operational amplifier, which allows circuits to operate robustly and precisely has not been built with bio-molecular parts. As in electronics, a biological operational-amplifier could greatly improve the predictability of circuits despite noise and variability, a problem that all cellular circuits face. Here, we show how to create a synthetic 3-stage inducer-input operational amplifier with a differential transcription-factor stage, a CRISPR-based push-pull stage, and an enzymatic output stage with just 5 proteins including dCas9. Our Bio-OpAmp expands the toolkit of fundamental circuits available to bioengineers or biologists, and may shed insight into biological systems that require robust and precise molecular homeostasis and regulation.\n\nOne Sentence SummaryA synthetic bio-molecular operational amplifier that can enable robust, precise, and programmable homeostasis and regulation in living cells with just 5 protein parts is described.

synthetic biology↗

bioRxiv2014

Synthesis and patterning of tunable multiscale materials with engineered cells

A major challenge in materials science is to create self-assembling, functional, and environmentally responsive materials which can be patterned across multiple length scales. Natural biological systems, such as biofilms, shells, and skeletal tissues, implement dynamic regulatory programs to assemble complex multiscale materials comprised of living and non-living components1-9. Such systems can provide inspiration for the design of heterogeneous functional systems which integrate biotic and abiotic materials via hierarchical self-assembly. Here, we present a synthetic-biology platform for synthesizing and patterning self-assembled functional amyloid materials across multiple length scales with bacterial biofilms. We engineered Escherichia coli curli amyloid production under the tight control of synthetic regulatory circuits and interfaced amyloids with inorganic materials to create a biofilm-based electrical switch whose conductance can be selectively toggled by specific environmental signals. Furthermore, we externally tuned synthetic biofilms to build nanoscale amyloid biomaterials with different structure and composition through the controlled expression of their constituent subunits with artificial gene circuits. By using synthetic cell-cell communication, our engineered biofilms can also autonomously manufacture dynamic materials whose structure and composition change with time. In addition, we show that by combining subunit-level protein engineering, controlled genetic expression of self-assembling subunit proteins, and macroscale spatial gradients, synthetic biofilms can pattern protein biomaterials across multiple length scales. This work lays a foundation for synthesizing, patterning, and controlling composite materials with engineered biological systems. We envision that this approach can be expanded to other cellular and biomaterials contexts for the construction of self-organizing, environmentally responsive, and tunable multiscale composite materials with heterogeneous functionalities.

Synthetic Biology↗

bioRxiv2015

Engineering Modular Viral Scaffolds for Targeted Bacterial Population Editing

Bacteria are central to human health and disease, but the tools available for modulating and editing bacterial communities are limited. New technologies for tuning microbial populations would facilitate the targeted manipulation of the human microbiome and treatment of bacterial infections. For example, antibiotics are often broad spectrum in nature and cannot be used to accurately manipulate bacterial communities. Bacteriophages can provide highly specific targeting of bacteria, but relying solely on natural phage isolation strategies to assemble well-defined and uniform phage cocktails that are amenable to engineering can be a time-consuming and labor-intensive process. Here, we present a synthetic-biology strategy to modulate phage host ranges by manipulating phage genomes in Saccharomyces cerevisiae. We used this technology to swap multiple modular phage tail components and demonstrated that Escherichia coli phage scaffolds can be redirected to target pathogenic Yersinia and Klebsiella bacteria, and conversely, Klebsiella phage scaffolds can be redirected to target E. coli. The synthetic phages achieved multiple orders-of-magnitude killing of their new target bacteria and were used to selectively remove specific bacteria from multi-species bacterial communities. We envision that this approach will accelerate the study of phage biology, facilitate the tuning of phage host ranges, and enable new tools for microbiome engineering and the treatment of infectious diseases.

Synthetic Biology↗

bioRxiv2016

Multiplex shRNA Screening of Germ Cell Development by in vivo Transfection of Mouse Testis

Spermatozoa are one of the few mammalian cells types that cannot be fully derived in vitro, severely limiting the application of modern genomic techniques to study germ cell biology. The current gold standard approach of characterizing single gene knockout mice is slow as generation of each mutant line can take 6-9 months. Here, we describe an in vivo approach to rapid functional screening of germline genes based on a new non-surgical, non-viral in vivo transfection method to deliver nucleic acids into testicular germ cells. By coupling multiplex transfection of short hairpin RNA constructs with pooled amplicon sequencing as a readout, we were able to screen many genes for spermatogenesis function in a quick and inexpensive experiment. We transfected nine mouse testes with a pilot pool of RNAi against well-characterized genes to show that this system is highly reproducible and accurate. With a false negative rate of 18% and a false positive rate of 12%, this method has similar performance as other RNAi screens in the well-described Drosophila model system. In a separate experiment, we screened 26 uncharacterized genes computationally predicted to be essential for spermatogenesis and found numerous candidates for follow up studies. Further, by characterizing the effect of both libraries on neuronal N2a cells, we show that our screening results from testis are tissue-specific. Our calculations indicate that the current implementation of this approach could be used to screen thousands of protein-coding genes simultaneously in a single mouse testis. The experimental protocols and analysis scripts provided will enable other groups to use this procedure to study diverse aspects of germ cell biology ranging from epigenetics to cell physiology. This approach also has great promise as an applied tool for validating diagnoses made from medical genome sequencing, or designing synthetic biological sequences that act as potent and highly specific male contraceptives.

Genomics↗