228 research outputs found

    Two New Plasmid Post-segregational Killing Mechanisms for the Implementation of Synthetic Gene Networks in Escherichia coli

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    Plasmids are the workhorse of both industrial biotechnology and synthetic biology, but ensuring they remain in bacterial cells is a challenge. Antibiotic selection cannot be used to stabilize plasmids in most real-world applications, and inserting dynamical gene networks into the genome remains challenging. Plasmids have evolved several mechanisms for stability, one of which, post-segregational killing (PSK), ensures that plasmid-free cells do not survive. Here we demonstrate the plasmid-stabilizing capabilities of the axe/txe toxin-antitoxin system and the microcin-V bacteriocin system in the probiotic bacteria Escherichia coli Nissle 1917 and show that they can outperform the commonly used hok/sok. Using plasmid stability assays, automated flow cytometry analysis, mathematical models, and Bayesian statistics we quantified plasmid stability in vitro. Furthermore, 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

    Multibudded tubules formed by COPII on artificial liposomes

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    COPII-coated vesicles form at the endoplasmic reticulum for cargo transport to the Golgi apparatus. We used in vitro reconstitution to examine the roles of the COPII scaffold in remodeling the shape of a lipid bilayer. Giant Unilamellar Vesicles were examined using fast confocal fluorescence and cryo-electron microscopy in order to avoid separation steps and minimize mechanical manipulation. COPII showed a preference for high curvature structures, but also sufficient flexibility for binding to low curvatures. The COPII proteins induced beads-on-a-string-like constricted tubules, similar to those previously observed in cells. We speculate about a mechanical pathway for vesicle fission from these multibudded COPII-coated tubules, considering the possibility that withdrawal of the Sar1 amphipathic helix upon GTP hydrolysis leads to lipid bilayer destabilization resulting in fission

    The study of expanded tri-lobed flap in a rabbit model: possible flap model in ear reconstruction?

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    BACKGROUND: Local flaps are widely used in reconstructive surgery. Tri-lobed skin flap is a relatively new flap and there has been no experimental model of this flap. This flap can be used for repair of full thickness defects in the face, ears and alar region. Based on the size of ears in a rabbit, we designed a model of ear reconstruction using expanded tri-lobed flap. Local flaps are more advantageous in that they provide excellent color and texture matching up with those of the face, adequately restore ear contour, place scars in a favorable location and ideally accomplish these goals in a single stage with minimal donor site morbidity. METHODS: Eight adult New Zealand rabbits were divided into two groups. 50 ml round tissue expander were implanted to four rabbits. After completion of the expansion, a superiorly based tri-lobed flap was elevated and a new ear was created from the superior dorsal skin of each rabbit. Scintigraphy with Technetium-99m pertecnetate was performed to evaluate flap viability. RESULTS: Subtotal flap necrosis was seen in all animals in non-expanded group. New ear in dimensions of the original ear was created in expanded group without complication. Perfusion and viability of the flaps were proved by Technetium-99m pertecnetate scintigraphy. CONCLUSION: According to our knowledge this study is the first to demonstrate animal model in tri-lobed flap. Also, our technique is the first application of the trilobed flap to the possible ear reconstruction. We speculated that this flap may be used mastoid based without hair, in human. Also, tri-lobed flap may be an alternative in reconstruction of cylindrical organs such as penis or finger

    In-Silico Patterning of Vascular Mesenchymal Cells in Three Dimensions

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    Cells organize in complex three-dimensional patterns by interacting with proteins along with the surrounding extracellular matrix. This organization provides the mechanical and chemical cues that ultimately influence a cell's differentiation and function. Here, we computationally investigate the pattern formation process of vascular mesenchymal cells arising from their interaction with Bone Morphogenic Protein-2 (BMP-2) and its inhibitor, Matrix Gla Protein (MGP). Using a first-principles approach, we derive a reaction-diffusion model based on the biochemical interactions of BMP-2, MGP and cells. Simulations of the model exhibit a wide variety of three-dimensional patterns not observed in a two-dimensional analysis. We demonstrate the emergence of three types of patterns: spheres, tubes, and sheets, and show that the patterns can be tuned by modifying parameters in the model such as the degradation rates of proteins and chemotactic coefficient of cells. Our model may be useful for improved engineering of three-dimensional tissue structures as well as for understanding three dimensional microenvironments in developmental processes.National Institutes of Health (U.S.) (GM69811)United States. Dept. of Energy (DOE CSGF fellowship

    Comparative genomic analysis reveals independent expansion of a lineage-specific gene family in vertebrates: The class II cytokine receptors and their ligands in mammals and fish

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    BACKGROUND: The high degree of sequence conservation between coding regions in fish and mammals can be exploited to identify genes in mammalian genomes by comparison with the sequence of similar genes in fish. Conversely, experimentally characterized mammalian genes may be used to annotate fish genomes. However, gene families that escape this principle include the rapidly diverging cytokines that regulate the immune system, and their receptors. A classic example is the class II helical cytokines (HCII) including type I, type II and lambda interferons, IL10 related cytokines (IL10, IL19, IL20, IL22, IL24 and IL26) and their receptors (HCRII). Despite the report of a near complete pufferfish (Takifugu rubripes) genome sequence, these genes remain undescribed in fish. RESULTS: We have used an original strategy based both on conserved amino acid sequence and gene structure to identify HCII and HCRII in the genome of another pufferfish, Tetraodon nigroviridis that is amenable to laboratory experiments. The 15 genes that were identified are highly divergent and include a single interferon molecule, three IL10 related cytokines and their potential receptors together with two Tissue Factor (TF). Some of these genes form tandem clusters on the Tetraodon genome. Their expression pattern was determined in different tissues. Most importantly, Tetraodon interferon was identified and we show that the recombinant protein can induce antiviral MX gene expression in Tetraodon primary kidney cells. Similar results were obtained in Zebrafish which has 7 MX genes. CONCLUSION: We propose a scheme for the evolution of HCII and their receptors during the radiation of bony vertebrates and suggest that the diversification that played an important role in the fine-tuning of the ancestral mechanism for host defense against infections probably followed different pathways in amniotes and fish

    Modular Composition of Gene Transcription Networks

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    Predicting the dynamic behavior of a large network from that of the composing modules is a central problem in systems and synthetic biology. Yet, this predictive ability is still largely missing because modules display context-dependent behavior. One cause of context-dependence is retroactivity, a phenomenon similar to loading that influences in non-trivial ways the dynamic performance of a module upon connection to other modules. Here, we establish an analysis framework for gene transcription networks that explicitly accounts for retroactivity. Specifically, a module's key properties are encoded by three retroactivity matrices: internal, scaling, and mixing retroactivity. All of them have a physical interpretation and can be computed from macroscopic parameters (dissociation constants and promoter concentrations) and from the modules' topology. The internal retroactivity quantifies the effect of intramodular connections on an isolated module's dynamics. The scaling and mixing retroactivity establish how intermodular connections change the dynamics of connected modules. Based on these matrices and on the dynamics of modules in isolation, we can accurately predict how loading will affect the behavior of an arbitrary interconnection of modules. We illustrate implications of internal, scaling, and mixing retroactivity on the performance of recurrent network motifs, including negative autoregulation, combinatorial regulation, two-gene clocks, the toggle switch, and the single-input motif. We further provide a quantitative metric that determines how robust the dynamic behavior of a module is to interconnection with other modules. This metric can be employed both to evaluate the extent of modularity of natural networks and to establish concrete design guidelines to minimize retroactivity between modules in synthetic systems.United States. Air Force Office of Scientific Research (FA9550-12-1-0129

    Prediction by Promoter Logic in Bacterial Quorum Sensing

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    Quorum-sensing systems mediate chemical communication between bacterial cells, coordinating cell-density-dependent processes like biofilm formation and virulence-factor expression. In the proteobacterial LuxI/LuxR quorum sensing paradigm, a signaling molecule generated by an enzyme (LuxI) diffuses between cells and allosterically stimulates a transcriptional regulator (LuxR) to activate its cognate promoter (pR). By expressing either LuxI or LuxR in positive feedback from pR, these versatile systems can generate smooth (monostable) or abrupt (bistable) density-dependent responses to suit the ecological context. Here we combine theory and experiment to demonstrate that the promoter logic of pR – its measured activity as a function of LuxI and LuxR levels – contains all the biochemical information required to quantitatively predict the responses of such feedback loops. The interplay of promoter logic with feedback topology underlies the versatility of the LuxI/LuxR paradigm: LuxR and LuxI positive-feedback systems show dramatically different responses, while a dual positive/negative-feedback system displays synchronized oscillations. These results highlight the dual utility of promoter logic: to probe microscopic parameters and predict macroscopic phenotype

    Self-Organizing Circuit Assembly through Spatiotemporally Coordinated Neuronal Migration within Geometric Constraints

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    Neurons are dynamically coupled with each other through neurite-mediated adhesion during development. Understanding the collective behavior of neurons in circuits is important for understanding neural development. While a number of genetic and activity-dependent factors regulating neuronal migration have been discovered on single cell level, systematic study of collective neuronal migration has been lacking. Various biological systems are shown to be self-organized, and it is not known if neural circuit assembly is self-organized. Besides, many of the molecular factors take effect through spatial patterns, and coupled biological systems exhibit emergent property in response to geometric constraints. How geometric constraints of the patterns regulate neuronal migration and circuit assembly of neurons within the patterns remains unexplored.We established a two-dimensional model for studying collective neuronal migration of a circuit, with hippocampal neurons from embryonic rats on Matrigel-coated self-assembled monolayers (SAMs). When the neural circuit is subject to geometric constraints of a critical scale, we found that the collective behavior of neuronal migration is spatiotemporally coordinated. Neuronal somata that are evenly distributed upon adhesion tend to aggregate at the geometric center of the circuit, forming mono-clusters. Clustering formation is geometry-dependent, within a critical scale from 200 µm to approximately 500 µm. Finally, somata clustering is neuron-type specific, and glutamatergic and GABAergic neurons tend to aggregate homo-philically.We demonstrate self-organization of neural circuits in response to geometric constraints through spatiotemporally coordinated neuronal migration, possibly via mechanical coupling. We found that such collective neuronal migration leads to somata clustering, and mono-cluster appears when the geometric constraints fall within a critical scale. The discovery of geometry-dependent collective neuronal migration and the formation of somata clustering in vitro shed light on neural development in vivo
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