Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 83,503 bioRxiv papers from 359,889 authors.
Most downloaded bioRxiv papers, all time
in category synthetic biology
765 results found. For more information, click each entry to expand.
358 downloads synthetic biology
We develop a system for implementing "packet-based" intercellular communication in an engineered bacterial population via conjugation. Our system uses gRNA-based identification markers that allow messages to be addressed to specific strains via Cas9-mediated cleavage of messages sent to the wrong recipient, which we show reduces plasmid transfer by four orders of magnitude. Integrase-mediated editing of the address on the message plasmid allows cells to dynamically update the message's recipients in vivo. As a proof-of-concept demonstration of our system, we propose a linear path scheme that would propagate a message sequentially through the strains of a population in a defined order.
356 downloads synthetic biology
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 facilitate 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.
354 downloads synthetic biology
Every year, Enterotoxigenic Escherichia coli (ETEC), the most common form of travelers diarrhea, affects thousands of military personnel deployed overseas. The goal of this research was to engineer non-pathogenic E. coli to sense ETEC, respond to its presence, and package the non- pathogenic E. coli in a cellulose matrix to enable environmental detection of ETEC. Two plasmids were created: sense-respond; and packaging. The sense-respond plasmid detected autoinducer 2 (AI-2), a quorum sensing molecule created by most ETEC strains, by expressing LsrR which switches on the Lsr promoter. Activation of the Lsr promoter expresses superfolder green fluorescent protein (sfGFP), indicating the presence of ETEC. The packaging plasmid expresses a fusion protein consisting of curli fibers and cellulose binding domains. These modified surface proteins permit the bacteria to bind to cellulose, encapsulating the sense-response module. This genetically engineered machine could be deployed in both the internal and external environment to detect ETEC.
353 downloads synthetic biology
In male heterogametic species the Y chromosome is transmitted solely from fathers to sons, and is selected for based only on its impacts on male fitness. This fact can be exploited to develop efficient pest control strategies that use Y-linked editors to disrupt the fitness of female descendants. In simple strategic population models we show that Y-linked editors can be substantially more efficient than other self-limiting strategies and, while not as efficient as gene drive approaches, are expected to have less impact on non-target populations with which there is some gene flow. Efficiency can be further augmented by simultaneously releasing an autosomal X-shredder construct, in either the same or different males. Y-linked editors may be attractive option to consider when efficient control of a species is desired in some locales but not others.
352 downloads synthetic biology
We have identified a synthetic peptide that interrupts discrete aspects of seedling development under red light. Previous reports have demonstrated that plants transformed with random DNA sequences produce synthetic peptides that affect plant biology. In this report one specific peptide is characterized that inhibits discrete aspects of red-light-mediated Arabidopsis thaliana development during photomorphogenesis. Seedlings expressing the PEP6-32 peptide presented longer hypocotyls and diminished cotyledon expansion when grown under red light. Other red-light-mediated seedling processes such as induction of Lhcb (cab) transcripts or loss of vertical growth remained unaffected. Long-term responses to red light in PEP6-32 expressing plants, such as repression of flowering time, did not show defects in red light signaling or integration. A synthesized peptide applied exogenously induced the long-hypocotyl phenotype under red light in non-transformed seedlings. The results indicate that the PEP6-32 peptide causes discrete cell expansion defects during early seedling development in red light, mimicking weak phyB alleles in some aspects of seedling photomorphogenesis. The findings demonstrate that new chemistries derived from random peptide expression can modulate specific facets of plant growth and development.
350 downloads synthetic biology
Lijin Zou, Youlai Zhang, Ying He, Hui Yu, Jun Chen, Delong Liu, Sixiong Lin, Manman Gao, Gang Zhong, Weicheng Lei, Guangqian Zhou, Xuenong Zou, Kai Li, Yin Yu, Gaofeng Zha, Linxian Li, Yuanlin Zeng, Jianfei Wang, Gang Wang
Organ transplantation is the only curative treatment for patients with terminal organ failure, however, there is a worldwide organ shortage. Genetically modified pig organs and tissues have become an attractive and practical alternative solution for the severe organ shortage, which has been made possible by significant progress in xenotransplantation in recent years. The past several decades witnessed an expanding list of genetically engineered pigs due to technology advancements, however, the necessary combination of genetic modifications in pig for human organ xenotransplantation has not been determined. In the current study, we created a selective germline genome edited pig (SGGEP). The first triple xenoantigens (GGTA, B4GAL, and CAMH) knockout somatic cells were generated to serve as a prototype cells and then human proteins were expressed in the xenoantigen knockout cells, which include human complement system negative regulatory proteins (CD46, CD55, and CD59); human coagulation system negative regulatory proteins thrombomodulin (THBD); tissue factor pathway inhibitor (TFPI); CD39; macrophage negative regulatory proteins (human CD47); and natural killer cell negative regulatory human HLA-E. After the successful establishment of SGGEP by the nuclear tranfer, we engrafted SGGEP skin to NHP, up to 25 days graft survival without immunosuppressive drugs was observed. Because a pig skin graft does not impact the success of a subsequent allograft or autograft or vice versa, thus our SGGEP could have a great potential for clinical value to save severe and large area burn patients and the other human organ failure. Therefore, this combination of specific gene modifications is a major milestone and provides proof of concept to initiate investigator-initiated clinical trials (IITs) in severe burn patients with defined processes and governance measures in place and the other clinical application.
350 downloads synthetic biology
The T7 bacteriophage RNA polymerase (T7 RNAP) serves as a model for understanding RNA synthesis, as a tool for protein expression, and as an actuator for synthetic gene circuit design in bacterial cells and cell-free extract. T7 RNAP is an attractive tool for orthogonal protein expression in bacteria owing to its compact single subunit structure and orthogonal promoter specificity. Understanding the mechanisms underlying T7 RNAP regulation is important to the design of engineered T7-based transcription factors, which can be used in gene circuit design. To explore regulatory mechanisms for T7 RNAP-driven expression, we developed a rapid and cost-effective method to characterize engineered T7-based transcription factors using cell-free protein synthesis and an acoustic liquid handler. Using this method, we investigated the effects of the tetracycline operator's proximity to the T7 promoter on the regulation of T7 RNAP-driven expression. Our results reveal a mechanism for regulation that functions by interfering with the transition of T7 RNAP from initiation to elongation and validates the use of the method described here to engineer future T7-based transcription factors.
350 downloads synthetic biology
Glycosylation plays important roles in cellular function and endows protein therapeutics with beneficial properties. However, constructing biosynthetic pathways to study and engineer protein glycosylation remains a bottleneck. To address this limitation, we describe a modular, versatile cell-free platform for glycosylation pathway assembly by rapid in vitro mixing and expression (GlycoPRIME). In GlycoPRIME, crude cell lysates are enriched with glycosyltransferases by cell-free protein synthesis and then glycosylation pathways are assembled in a mix-and-match fashion to elaborate a single glucose priming handle installed by an N-linked glycosyltransferase. We demonstrate GlycoPRIME by constructing 37 putative protein glycosylation pathways, creating 23 unique glycan motifs. We then use selected pathways to design a one-pot cell-free system to synthesize a vaccine protein with an α-galactose motif and engineered Escherichia coli strains to produce human antibody constant regions with minimal sialic acid motifs. We anticipate that our work will facilitate glycoscience and make possible new glycoengineering applications.
350 downloads synthetic biology
Inside individual cells, protein population counts are subject to molecular noise due to low copy numbers and the inherent probabilistic nature of biochemical processes. Such random fluctuations in the level of a protein critically impact functioning of intracellular biological networks, and not surprisingly, cells encode diverse regulatory mechanisms to buffer noise. We investigate the effectiveness of proportional and derivative-based feedback controllers to suppress protein count fluctuations originating from two noise sources: bursty expression of the protein, and external disturbance in protein synthesis. Designs of biochemical reactions that function as proportional and derivative controllers are discussed, and the corresponding closed-loop system is analyzed for stochastic controller realizations. Our results show that proportional controllers are effective in buffering protein copy number fluctuations from both noise sources, but this noise suppression comes at the cost of reduced static sensitivity of the output to the input signal. Next, we discuss the design of a coupled feedforward-feedback biochemical circuit that approximately functions as a derivate controller. Analysis using both analytical methods and Monte Carlo simulations reveals that this derivative controller effectively buffers output fluctuations from bursty stochastic expression, while maintaining the static input-output sensitivity of the open-loop system. As expected, the derivative controller performs poorly in terms of rejecting external disturbances. In summary, this study provides a systematic stochastic analysis of biochemical controllers, and paves the way for their synthetic design and implementation to minimize deleterious fluctuations in gene product levels.
350 downloads synthetic biology
Wound healing is a complicated biological process consisting of many types of cellular dy- namics and functions regulated by chemical and molecular signals. Recent advances in synthetic biology have made it possible to predictably design and build closed-loop controllers that can function appropriately alongside biological species. In this paper we develop a simple dynamical population model mimicking the sequential relay-like dynamics of cellular populations involved in the wound healing process. Our model consists of four nodes and five signals whose pa- rameters we can tune to simulate various chronic healing conditions. We also develop a set of regulator functions based on type-1 incoherent feed forward loops (IFFL) that can sense the change from acute healing to incomplete chronic wounds, improving the system in a timely manner. Both the wound healing and type-1 IFFL controller architectures are compatible with available synthetic biology experimental tools for potential applications.
349 downloads synthetic biology
Background: Gene knockout has been used to improve the conversion ratio of strains for some chemical products. Based on mixed integer bi-level linear programming (MIBLP) and cell network models, there have been several algorithms to predict the target for deletion to improve the productivity of chemicals. At present, the cell models on which these algorithms based have changed from metabolic network to metabolic-regulatory integrated network, for integrated network is more comprehensive in describing the behavior of cells. Metabolic-regulatory integrated network is better than metabolic network in flux prediction, but will introduce integer variables in the inner of MIBLP. How to solve the intractable MIBLP, however, is not explicated clearly as in mathematical literatures, especially for MIBLP with integer variables in the inner problem (named as MIBLP-2) where integer variables are introduced by the flux balance analysis (FBA) for integrated network. Dual theory was still be used to transform MIBLP-2 to a single level with ignoring integer variables in the inner problem. Intelligent computation is another choice for solving MIBLP, but it usually was used to solve the single level nonlinear programming (NLP) which was the transformation from MIBLP by using joint objective of upper/lower level, while the equivalence between this MIBLP and this NLP was not be proved in mathematics. Methods: In this study, we develop a new target predicting algorithm for gene knockouts, named RegKnock. The cell model on which we base is metabolic-regulatory integrated network as well. When solving the MIBLP-2, RegKnock uses Parallel Genetic Algorithm (PGA), but not use joint objective. GA was used to generate control variables of the upper, indicating which genes should be deleted, while the fitness function is to maximize the objective product calculated from the inner FBA of the integrated network. FBA of the inner problem, a mixed integer programming, could be solved by existing optimization softwares. Parallel computation aims to accelerate finding the optimal solution and thus decreases the time of computation. Results and Conclusions: With comparing with OptORF and OptFlux, two published target predicting algorithm for gene knockouts which also aiming at integrated network, two merits have been shown for RegKnock, i.e. absolutely accuracy and not a long time of computation. So RegKnock is a nice algorithm for predicting algorithm for gene deletions as for integrated network.
344 downloads synthetic biology
Genetic circuit design requires characterisation of the dynamics of synthetic gene expression. This is a difficult problem since gene expression varies in complex ways over time and across different contexts. Here we present a novel method for characterising the dynamics of gene expression with a few parameters that account for changes in cellular context (host cell physiology) and compositional context (adjacent genes). The dynamics of gene circuits were characterised by a trajectory through a multi-dimensional phase space parameterised by the expression levels of each of their constituent transcriptional units (TU). These trajectories followed piecewise linear dynamics, with each dynamical regime corresponding to different growth regimes, or cellular contexts. Thus relative expression rates were changed by transitions between growth regimes, but were constant in each regime. We present a plausible two-factor mathematical model for this behaviour based on resource consumption. By analyzing different combinations of TUs, we then showed that relative expression rates were significantly affected by the neighboring TU (compositional context), but maintained piecewise linear dynamics across cellular and compositional contexts. Taken together these results show that TU expression dynamics can be predicted by a reference TU up to a context dependent scaling factor. This model provides a framework for design of genetic circuits composed of TUs. A common sharable reference TU may be chosen and measured in the cellular contexts of interest. The output of each TU in the circuit may then be predicted by the output of the reference TU in the given cellular context scaled by a characteristic parameter. This will aid in genetic circuit design by providing simple models for the dynamics of gene circuits and their constituent TUs.
341 downloads synthetic biology
Second messenger signaling networks allow cells to sense and adapt to changing environmental conditions. In bacteria, the nearly ubiquitous second messenger molecule cyclic di-GMP coordinates diverse processes such as motility, biofilm formation, and virulence. In bacterial pathogens, these signaling networks allow the bacteria to survive changing environment conditions that are experienced during infection of a mammalian host. While studies have examined the effects of cyclic di-GMP levels on virulence in these pathogens, it has previously not been possible to visualize cyclic di-GMP levels in real time during the stages of host infection. Towards this goal, we generate the first ratiometric, chemiluminescent biosensor scaffold that selectively responds to c-di-GMP. By engineering the biosensor scaffold, a suite of Venus-YcgR-NLuc (VYN) biosensors is generated that provide extremely high sensitivity (KD < 300 pM) and large BRET signal changes (up to 109%). As a proof-of-concept that VYN biosensors can image cyclic di-GMP during host infection, we show that the VYN biosensors function in the context of a tissue phantom model, with only ~103-104 biosensor-expressing cells required for the measurement. Furthermore, the stable BRET signal suggests that the sensors could be used for long-term imaging of cyclic di-GMP dynamics during host infection. The VYN sensors developed here can serve as robust in vitro diagnostic tools for high throughput screening, as well as genetically encodable tools for monitoring the dynamics of c-di-GMP in live cells, and lay the groundwork for live cell imaging of c-di-GMP dynamics in bacteria during host infection, and other complex environments.
340 downloads synthetic biology
Alice Checcucci, George C diCenzo, Veronica Ghini, Marco Bazzicalupo, Anke Becker, Francesca Decorosi, Johannes Döhlemann, Camilla Fagorzi, Turlough M. Finan, Marco Fondi, Claudio Luchinat, Paola Turano, Tiziano Vignolini, Carlo Viti, Alessio Mengoni
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.
340 downloads synthetic biology
Lanthipeptides have extensive therapeutic and industrial applications; however, since many are bactericidal, traditional in vivo platforms are limited in their capacity to discover and mass produce novel lanthipeptides as bacterial organisms are often critical components in these systems. We developed a cell-free protein synthesis (CFPS) platform that enables rapid genome mining, screening and guiding overproduction of lanthipeptides in vivo. For proof-of-concept studies, the type I lanthipeptide, nisin, was selected. Four novel lanthipeptides with anti-bacterial activity were identified among all nisin analogs in the NCBI database in a single day. Further, we coupled the CFPS platform with a screening assay for gram-negative bacterial growth and identified a potent nisin mutant, M5. The titer of nisin and nisin analogs significantly improved with CFPS platform guidance. Owing to the similarities in biosynthesis, our CFPS platform is broadly applicable to other lanthipeptides, provides a universal method for lanthipeptides discovery and overproduction.
339 downloads synthetic biology
Primary processing of painful stimulation occurs in the dorsal horn of the spinal cord. In this article, we introduce mathematical models of the neural circuitry in the dorsal horn responsible for processing nerve fiber inputs from noxious stimulation of peripheral tissues and generating the resultant pain signal. The differential equation models describe the average firing rates of excitatory and inhibitory interneuron populations, as well as the wide dynamic range (WDR) neurons whose output correlates with the pain signal. The temporal profile of inputs on the different afferent nerve fibers that signal noxious and innocuous stimulation and the excitability properties of the included neuronal populations are constrained by experimental results. We consider models for the spinal cord circuit in isolation and when top-down inputs from higher brain areas that modulate pain processing are included. We validate the models by replicating experimentally observed phenomena of A fiber inhibition of pain and wind-up. We then use the models to investigate mechanisms for the observed phase shift in circadian rhythmicity of pain that occurs with neuropathic pain conditions. Our results suggest that changes in neuropathic pain rhythmicity can occur through dysregulation of inhibition within the dorsal horn circuit.
339 downloads synthetic biology
Biological nitrogen fixation is catalyzed by nitrogenase, a complex metalloenzyme found only in prokaryotes. N2 fixation is energetically highly expensive, and an energy generating process such as photosynthesis can meet the energy demand of N2 fixation. However, synthesis and expression of nitrogenase is exquisitely sensitive to oxygen. Thus, engineering nitrogen fixation activity in photosynthetic organisms that produce oxygen is challenging. Cyanobacteria are oxygenic photosynthetic prokaryotes, and some of them also fix N2. Here, we demonstrate a feasible way to engineer nitrogenase activity in the non-diazotrophic cyanobacterium Synechocystis sp. PCC 6803 through the transfer of 35 nitrogen fixation (nif) genes from the diazotrophic cyanobacterium Cyanothece sp. ATCC 51142. In addition, we have identified the minimal nif cluster required for such activity in Synechocystis 6803. Moreover, nitrogenase activity was significantly improved by increasing the expression levels of nif genes. Importantly, the O2 tolerance of nitrogenase was enhanced by introduction of uptake hydrogenase genes, showing this to be a functional way to improve nitrogenase enzyme activity under micro-oxic conditions. To date, our efforts have resulted in engineered Synechocystis 6803 strains that remarkably have more than 30% N2-fixation activity compared to that in Cyanothece 51142, the highest such activity established in any non-diazotrophic oxygenic photosynthetic organism. This study establishes a baseline towards the ultimate goal of engineering nitrogen fixation ability in crop plants.
338 downloads synthetic biology
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.
337 downloads synthetic biology
One challenge with controlling electron flow in cells is the lack of biomolecules that directly couple the sensing of environmental conditions to electron transfer efficiency. To overcome this protein component limitation, we randomly inserted the ligand binding domain (LBD) from the human estrogen receptor (ER) into a thermostable 2Fe-2S ferredoxin (Fd) from Mastigocladus laminosus and used a bacterial selection to identify Fd-LBD fusion proteins that support electron transfer from a Fd-NADP reductase (FNR) to a Fd-dependent sulfite reductase (SIR). Mapping LBD insertion sites onto structure revealed that Fd tolerates domain insertion adjacent to or within the tetracysteine motif that coordinates the 2Fe-2S metallocluster. With both classes of the fusion proteins, cellular ET was enhanced by the ER antagonist 4-hydroxytamoxifen. In addition, one of Fds arising from ER-LBD insertion within the tetracysteine motif acquires an oxygen-tolerant 2Fe-2S cluster, suggesting that ET is regulated through post-translational ligand binding.
336 downloads synthetic biology
Biocompatibility assessment of nanomaterials has been of great interest due to their potential toxicity. However, conventional biocompatibility tests are short of providing a fast toxicity report. We developed a whole cell based biosensor to track biocompatibility of nanomaterials with the aim of providing fast feedback for engineering nanomaterials with lower toxicity levels. We have engineered promoters of four heat shock response proteins. As an initial design a reporter coding gene was cloned to downstream of the promoter regions selected. Initial results indicated that native HSP promoter regions were not very promising to generate signals with low background signals. Introducing riboregulators to native promoters eliminated unwanted background signal almost entirely. Unfortunately, this approach also leads a decrease in expected sensor signal. Thus, a repression based genetic circuit, inspired from HSP mechanism of Mycobacterium tuberculosis was constructed. These genetic circuits can report the toxicity of Quantum Dot nanoparticles in one hour with high precision. Our designed nanoparticle toxicity sensors can provide quick reports which can lower the demand for additional experiments with more complex organisms
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