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Results for “Synthetic Biology”

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bioRxiv2018

Intrinsic limitations in mainstream methods of identifying network motifs in biology

Network motifs are connectivity structures that occur with significantly higher frequency than chance, and are thought to play important roles in complex biological networks, for example in gene regulation, interactomes, and metabolomes. Network motifs may also become pivotal in the rational design and engineering of complex biological systems underpinning the field of synthetic biology. Distinguishing true motifs from arbitrary substructures, however, remains a challenge. Here we demonstrate both theoretically and empirically that implicit assumptions present in mainstream methods for motif identification do not necessarily hold, with the ramification that motif studies using these mainstream methods are less able to effectively differentiate between spurious results and events of true statistical significance than is often presented. We show that these difficulties cannot be overcome without revising the methods of statistical analysis used to identify motifs. The implications of these findings are therefore far-reaching across diverse areas of biology.

systems biology↗

bioRxiv2015

Layering genetic circuits to build a single cell, bacterial half adder

Gene regulation in biological systems is impacted by the cellular and genetic context-dependent effects of the biological parts which comprise the circuit. Here, we have sought to elucidate the limitations of engineering biology from an architectural point of view, with the aim of compiling a set of engineering solutions for overcoming failure modes during the development of complex, synthetic genetic circuits. Using a synthetic biology approach that is supported by computational modelling and rigorous characterisation, AND, OR and NOT biological logic gates were layered in both parallel and serial arrangements to generate a repertoire of Boolean operations that include NIMPLY, XOR, half adder and half subtractor logics in single cell. Subsequent evaluation of these near-digital biological systems revealed critical design pitfalls that triggered genetic context dependent effects, including 5 UTR interference and uncontrolled switch-on behaviour of {sigma}54 promoter. Importantly, this work provides a representative case study to the debugging of genetic context dependent effects through principles elucidated herein, thereby providing a rational design framework to program single prokaryotic cell with diversified digital operations.

Synthetic Biology↗

bioRxiv2018

CRISPR-interference based modulation of mobile genetic elements in bacteria

Spontaneous mutagenesis of synthetic genetic constructs by mobile genetic elements frequently results in the rapid loss of advantageous functions. Previous efforts to minimize such mutations required the exceedingly time-consuming manipulation of bacterial chromosomes and the complete removal of insertional sequences (ISes). To this aim, we developed a single plasmid-based system (pCRIS) that applies CRISPR-interference to inhibit the transposition of bacterial ISes. pCRIS expresses multiple guide RNAs to direct inactivated Cas9 (dCas9) to simultaneously silence IS1, IS3, IS5, and IS150 at up to 38 chromosomal loci in Escherichia coli, in vivo. As a result, the transposition rate of all four targeted ISes dropped to negligible levels at both chromosomal and episomal targets, increasing the half-life of exogenous protein expression. Most notably, pCRIS, while requiring only a single plasmid delivery performed within a single day, provided a reduction of IS-mobility comparable to that seen in genome-scale chromosome engineering projects. Global transcriptomics analysis revealed nevertheless only minute alterations in the expression of untargeted genes. Finally, the transposition-silencing effect of pCRIS was easily transferable across multiple E. coli strains. The plasticity and robustness of our IS-silencing system make it a promising tool to stabilize bacterial genomes for synthetic biology and industrial biotechnology applications.

synthetic biology↗

bioRxiv2017

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

The advent of easy-to-use open source microcontrollers, off-the-shelf electronics and customizable manufacturing technologies has facilitated the development of inexpensive scientific devices and laboratory equipment. In this study, we describe an imaging system that integrates low-cost and open-source hardware, software and genetic resources. The multi-fluorescence imaging system consists of readily available 470 nm LEDs, a Raspberry Pi camera and a set of filters made with low cost acrylics. This device allows imaging in scales ranging from single colonies to entire plates. We developed a set of genetic components (e.g. promoters, coding sequences, terminators) and vectors following the standard framework of Golden Gate, which allowed the fabrication of genetic constructs in a combinatorial, low cost and robust manner. In order to provide simultaneous imaging of multiple wavelength signals, we screened a series of long stokes shift fluorescent proteins that could be combined with cyan/green fluorescent proteins. We found CyOFP1, mBeRFP and sfGFP to be the most compatible set for 3-channel fluorescent imaging. We developed open source Python code to operate the hardware to run time-lapse experiments with automated control of illumination and camera and a Python module to analyze data and extract meaningful biological information. To demonstrate the potential application of this integral system, we tested its performance on a diverse range of imaging assays often used in disciplines such as microbial ecology, microbiology and synthetic biology. We also assessed its potential for STEM teaching in a high school environment, using it to teach biology, hardware design, optics, and programming. Together, these results demonstrate the successful integration of open source hardware, software, genetic resources and customizable manufacturing to obtain a powerful, low cost and robust system for STEM education, scientific research and bioengineering. All the resources developed here are available under open source licenses.

synthetic biology↗

bioRxiv2017

Data-Driven Prediction of CRISPR-Based Transcription Regulation for Programmable Control of Metabolic Flux

Multiplex and multi-directional control of metabolic pathways is crucial for metabolic engineering to improve product yield of fuels, chemicals, and pharmaceuticals. To achieve this goal, artificial transcriptional regulators such as CRISPR-based transcription regulators have been developed to specifically activate or repress genes of interest. Here, we found that by deploying guide RNAs to target on DNA sites at different locations of genetic cassettes, we could use just one synthetic CRISPR-based transcriptional regulator to simultaneously activate and repress gene expressions. By using the pairwise datasets of guide RNAs and gene expressions, we developed a data-driven predictive model to rationally design this system for fine-tuning expression of target genes. We demonstrated that this system could achieve programmable control of metabolic fluxes when using yeast to produce versatile chemicals. We anticipate that this master CRISPR-based transcription regulator will be a valuable addition to the synthetic biology toolkit for metabolic engineering, speeding up the \"design-build-test\" cycle in industrial biomanufacturing as well as generating new biological insights on the fates of eukaryotic cells.

synthetic biology↗

bioRxiv2016

Achieving large dynamic range control of gene expression with a compact RNA transcription-translation regulator

RNA transcriptional regulators are emerging as versatile components for genetic circuit construction. However, RNA transcriptional regulators suffer from incomplete repression, making their dynamic range less than that of their protein counterparts. This incomplete repression can cause expression leak, which impedes the construction of larger RNA synthetic regulatory networks. Here we demonstrate how naturally derived antisense RNA-mediated transcriptional regulators can be configured to regulate both transcription and translation in a single compact RNA mechanism that functions in Escherichia coli. Using in vivo gene expression assays, we show that a combination of transcriptional termination and RBS sequestration increases repression from 85% to 98% and activation from 10 fold to over 900 fold in response to cognate antisense RNAs. We also show that orthogonal versions of this mechanism can be created through engineering minimal antisense RNAs. Finally, to demonstrate the utility of this dual control mechanism, we use it to reduce circuit leak in an RNA-only transcriptional cascade that activates gene expression as a function of a small molecule input. We anticipate these regulators will find broad use as synthetic biology moves beyond parts engineering to the design and construction of larger and more sophisticated circuits.

Synthetic Biology↗

bioRxiv2017

A genetically encoded adhesin toolbox for programming multicellular morphologies and patterns

Synthetic multicellular systems hold promise for understanding natural development of biofilms and higher organisms1,2, as well as for engineering complex multi-component metabolic pathways2,3 and materials4. However, such efforts will require tools to adhere cells into defined morphologies and patterns, and these tools are currently lacking1,5,6. Here we report the first 100% genetically encoded synthetic platform for modular cell-cell adhesion in Escherichia coli, which provides control over multicellular self-assembly. Adhesive selectivity is provided by a library of outer membrane-displayed nanobody7,8 and antigen peptides with orthogonal intra-library specificities, while affinity is controlled by intrinsic adhesin affinity, competitive inhibition, and inducible expression. We demonstrate the resulting capabilities for rational design of well-defined morphologies and patterns through homophilic and heterophilic interactions, lattice-like self-assembly, phase separation, differential adhesion, and sequential layering. This adhesion toolbox, compatible with synthetic biology standards9, will enable construction of high-level multicellular designs and shed light on the evolutionary transition to multicellularity6,10.

synthetic biology↗

bioRxiv2013

Resource usage and gene circuit performance characterization in a cell-free ?breadboard?

The many successes of synthetic biology have come in a manner largely different from those in other engineering disciplines; in particular, without well-characterized and simplified prototyping environments to play a role analogous to wind-tunnels in aerodynamics and breadboards in electrical engineering. However, as the complexity of synthetic circuits increases, the benefits--in cost savings and design cycle time--of a more traditional engineering approach can be significant. We have recently developed an in vitro breadboard prototyping platform based on E. coli cell extract that allows biocircuits to operate in an environment considerably simpler than but functionally similar to in vivo. The simplicity of this system makes it a promising tool for rapid biocircuit design and testing, as well as for probing fundamental aspects of gene circuit operation normally masked by cellular complexity. In this work we characterize the cell-free breadboard using real-time and simultaneous measurements of transcriptional and translational activities of a small set of reporter genes and a transcriptional activation cascade. We determine the effects of promoter strength, gene concentration, and nucleoside triphosphate concentration on biocircuit properties, and we isolate the specific contributions of essential biomolecular resources--core RNA polymerase and ribosomes--to overall performance. Importantly, we show how limits on resources, particularly those involved in translation, are manifested as reduced expression in the presence of orthogonal genes that serve as additional loads on the system.

Synthetic Biology↗

bioRxiv2018

Codon usage influences fitness through RNA toxicity

Many organisms are subject to selective pressure that gives rise to unequal usage of synonymous codons, known as codon bias. To experimentally dissect the mechanisms of selection on synonymous sites, we expressed several hundred synonymous variants of the GFP gene in Escherichia coli, and used quantitative growth and viability assays to estimate bacterial fitness. Unexpectedly, we found many synonymous variants whose expression was toxic to E. coli. Unlike previously studied effects of synonymous mutations, the effect that we discovered is independent of translation, but it depends on the production of toxic mRNA molecules. We identified RNA sequence determinants of toxicity, and evolved suppressor strains that can tolerate the expression of toxic GFP variants. Genome sequencing of these suppressor strains revealed a cluster of promoter mutations that prevented toxicity by reducing mRNA levels. We conclude that translation-independent RNA toxicity is a previously unrecognized obstacle in bacterial gene expression.\n\nSignificance statementSynonymous mutations in genes do not change protein sequence, but they may affect gene expression and cellular function. Here we describe an unexpected toxic effect of synonymous mutations in Escherichia coli, with potentially large implications for bacterial physiology and evolution. Unlike previously studied effects of synonymous mutations, the effect that we discovered is independent of translation, but it depends on the production of toxic mRNA molecules. We hypothesize that the mechanism we identified influences the evolution of endogenous genes in bacteria, by imposing selective constraints on synonymous mutations that arise in the genome. Of interest for biotechnology and synthetic biology, we identify bacterial strains and growth conditions that alleviate RNA toxicity, thus allowing efficient overexpression of heterologous proteins.

synthetic biology↗

bioRxiv2018

Multiplex transcriptional characterizations across diverse and hybrid bacterial cell-free expression systems

Cell-free expression systems enable rapid prototyping of genetic programs in vitro. However, current throughput of cell-free measurements is often limited by the use of single-channel reporter assays. Here, we describe DNA Regulatory element Analysis by cell-Free Transcription and Sequencing (DRAFTS), a rapid and robust in vitro approach for multiplexed measurement of transcriptional activities from thousands of regulatory sequences in a single reaction. We employed this method in active cell lysates developed from ten diverse bacterial species. Interspecies analysis of transcriptional profiles from >1,000 diverse regulatory sequences revealed functional differences in gene expression that could be predictively modeled. Finally, we constructed and examined the transcriptional capacities of dual-species \"hybrid\" cell lysates that can simultaneously harness gene expression properties of multiple organisms. We expect that this cell-free multiplex transcriptional measurement approach will improve genetic circuit prototyping in new bacterial chassis for synthetic biology.

synthetic biology↗

bioRxiv2018

Direct preparation of Cas9 ribonucleoprotein from E. coli for PCR-free seamless DNA assembly

CRISPR-Cas9 is a versatile and powerful genome engineering tool. Recently, Cas9 ribonucleoprotein (RNP) complexes have been used as promising biological tools with plenty of in vivo and in vitro applications, but there are by far no efficient methods to produce Cas9 RNP at large scale and low cost. Here, we describe a simple and effective approach for direct preparation of Cas9 RNP from E. coli by co-expressing Cas9 and target specific single guided RNAs. The purified RNP showed in vivo genome editing ability, as well as in vitro endonuclease activity that combines with an unexpected superior stability to enable routine uses in molecular cloning instead of restriction enzymes. We further develop a RNP-based PCR-free method termed Cas-Brick in a one-step or cyclic way for seamless assembly of multiple DNA fragments with high fidelity up to 99%. Altogether, our findings provide a general strategy to prepare Cas9 RNP and supply a convenient and cost-effective DNA assembly method as an invaluable addition to synthetic biological toolboxes.

synthetic biology↗

bioRxiv2026

Harnessing Escherichia coli motility to engineer bacterial Voronoi patterns

Cell motility drives spatial pattern formation across diverse biological systems. Here, we engineer Escherichia coli motility in semi-solid agar to control Voronoi patterns in two and three dimensions, partitioning space into regions closest to their respective inoculation seeds. Consistent with our reaction-diffusion model, we observed that collisions between expansion fronts generate either biomass depletion (''gaps'') or accumulation (''anti-gaps''), governed by the relative diffusion rates of bacteria and nutrients. By engineering strains with distinct expansion rates and tuneable motility, and by integrating these experimental data into a dynamic Voronoi model, we achieved precise control over pattern geometry. This enabled the generation of gaps with varying widths, curved boundaries, asymmetric structures, seedless regions, and complex composite patterns. Together, these findings establish bacterial Voronoi patterns as a programmable platform for engineering multicellular spatial organization, with potential applications in synthetic biology and materials science.

synthetic biology↗

bioRxiv2018

A broad-host-range event detector: expanding and quantifying performance across bacterial species

Modern microbial biodesign relies on the principle that well-characterized genetic parts can be reused and reconfigured for different functions. However, this paradigm has only been successful in a limited set of hosts, mostly comprised from common lab strains of Escherichia coli. It is clear that new applications - such as chemical sensing and event logging in complex environments - will benefit from new host chassis. This study quantitatively compared how a chemical event logger performed across multiple microbial species. An integrase-based sensor and memory device was operated by two representative soil Pseudomonads - Pseudomonas fluorescens SBW25 and Pseudomonas putida DSM 291. Quantitative comparisons were made between these two non-traditional hosts and two bench-mark Escherichia coli chassis including the probiotic Nissle 1917 and common cloning strain DH5. The performance of sensor and memory components changed according to each host, such that a clear chassis effect was observed and quantified. These results were obtained via fluorescence from reporter proteins that were transcriptionally fused to the integrase and down-stream recombinant region and via data-driven kinetic models. The Pseudomonads proved to be acceptable chassis for the operation of this event logger, which outperformed the common E. coli DH5 in many ways. This study advances an emerging frontier in synthetic biology that aims to build broad-host-range devices and understand the context by which different species can execute programmable genetic operations.

synthetic biology↗

bioRxiv2017

Demonstration of de novo chemotaxis in E. coli using a real-time, quantitative, and digital-like approach

Chemotaxis is the movement of an organism in response to an external chemical stimulus. This system enables bacteria to sense their immediate environment and adapt to changes in its chemical composition. Bacterial chemotaxis is mediated by chemoreceptors, membrane proteins that bind an effector and transduce the signal to the downstream proteins. From a synthetic biology perspective, the natural chemotactic repertoire is of little use since bacterial chemoreceptors have evolved to sense specific ligands that either benefit or harm the cell. Here we demonstrate that using a combined computational design approach together with a quantitative, real-time, and digital detection approach, we can rapidly design, manufacture, and characterize a synthetic chemoreceptor in E. coli for histamine (a ligand for which there are no known chemoreceptors). First, we employed a computational protocol that uses the Rosetta bioinformatics software together with high threshold filters to design mutational variants to the native Tar ligand binding domain that target histamine. Second, we tested different ligand-chemoreceptors pairs with a novel chemotaxis assay, based on optical reflectance interferometry of porous silicon (PSi) optical transducers, enabling label-free quantification of chemotaxis by monitoring real-time changes in the optical readout (expressed as the effective optical thickness, EOT). We found that different ligands can be characterized by an individual set of fingerprints in our assay. Namely, a binary, digital-like response in EOT change (i.e. positive or negative) that differentiates between attractants and repellants, the amplitude of change of EOT response, and the rate by which steady state in EOT change is reached. Using this assay, we were able to positively identify and characterize a single mutational chemoreceptor variant for histamine that mediated chemotaxis comparably to the natural Tar-aspartate system. Our results demonstrate the possibility of not only expanding the natural chemotaxis repertoire, but also provide a new quantitative assay by which to characterize the efficacy of the chemotactic response.

synthetic biology↗

bioRxiv2013

Design and implementation of a synthetic biomolecular concentration tracker

As a field, synthetic biology strives to engineer increasingly complex artificial systems in living cells. Active feedback in closed loop systems offers a dynamic and adaptive way to ensure constant relative activity independent of intrinsic and extrinsic noise. In this work, we design, model, and implement a biomolecular concentration tracker, in which an output protein tracks the concentration of an input protein. Synthetic modular protein scaffold domains are used to colocalize a two-component system, and a single negative feedback loop modulates the production of the output protein. Using a combination of model and experimental work, we show that the circuit achieves real-time protein concentration tracking in Escherichia coli and that steady state outputs can be tuned.

Synthetic Biology↗

bioRxiv2016

Measurements of translation initiation from all 64 codons in E. coli

Our understanding of translation is one cornerstone of molecular biology that underpins our capacity to engineer living matter. The canonical start codon (AUG) and a few near-cognates (GUG, UUG) are typically considered as the \"start codons\" for translation initiation in Escherichia coli (E. coli). Translation is typically not thought to initiate from the 61 remaining codons. Here, we systematically quantified translation initiation in E. coli from all 64 triplet codons. We detected protein synthesis above background initiating from at least 46 codons. Translation initiated from these non-canonical start codons at levels ranging from 0.01% to 2% relative to AUG. Translation initiation from non-canonical start codons may contribute to the synthesis of peptides in both natural and synthetic biological systems

Synthetic Biology↗

bioRxiv2018

Engineered cell-to-cell signalling within growing bacterial cellulose pellicles

Bacterial cellulose is a strong and flexible biomaterial produced at high yields by Acetobacter species and has applications in healthcare, biotechnology and electronics. Naturally, bacterial cellulose grows as a large unstructured polymer network around the bacteria that produce it, and tools to enable these bacteria to respond to different locations are required to grow more complex structured materials. Here, we introduce engineered cell-to-cell communication into a bacterial cellulose-producing strain of Komagataeibacter rhaeticus to enable different cells to detect their proximity within growing material and trigger differential gene expression in response. Using synthetic biology tools, we engineer Sender and Receiver strains of K. rhaeticus to produce and respond to the diffusible signalling molecule, acyl-homoserine lactone (AHL). We demonstrate that communication can occur both within and between growing pellicles and use this in a boundary detection experiment, where spliced and joined pellicles sense and reveal their original boundary. This work sets the basis for synthetic cell-to-cell communication within bacterial cellulose and is an important step forward for pattern formation within engineered living materials.

synthetic biology↗

bioRxiv2017

A systematic comparison of error correction enzymes by next-generation sequencing

Gene synthesis, the process of assembling gene-length fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality, and cost of gene synthesis is limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment and throughput. Here we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in a model gene assembly and systematically compared six different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G [->] G/C transversions whereas T7 Endonuclease I preferentially corrects A/T [->] T/A transversions. More generally, this experimental and computational pipeline is a fast, scalable, and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.

synthetic biology↗