153 research outputs found

    Chemotaxis: a feedback-based computational model robustly predicts multiple aspects of real cell behaviour

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    The mechanism of eukaryotic chemotaxis remains unclear despite intensive study. The most frequently described mechanism acts through attractants causing actin polymerization, in turn leading to pseudopod formation and cell movement. We recently proposed an alternative mechanism, supported by several lines of data, in which pseudopods are made by a self-generated cycle. If chemoattractants are present, they modulate the cycle rather than directly causing actin polymerization. The aim of this work is to test the explanatory and predictive powers of such pseudopod-based models to predict the complex behaviour of cells in chemotaxis. We have now tested the effectiveness of this mechanism using a computational model of cell movement and chemotaxis based on pseudopod autocatalysis. The model reproduces a surprisingly wide range of existing data about cell movement and chemotaxis. It simulates cell polarization and persistence without stimuli and selection of accurate pseudopods when chemoattractant gradients are present. It predicts both bias of pseudopod position in low chemoattractant gradients and-unexpectedly-lateral pseudopod initiation in high gradients. To test the predictive ability of the model, we looked for untested and novel predictions. One prediction from the model is that the angle between successive pseudopods at the front of the cell will increase in proportion to the difference between the cell's direction and the direction of the gradient. We measured the angles between pseudopods in chemotaxing Dictyostelium cells under different conditions and found the results agreed with the model extremely well. Our model and data together suggest that in rapidly moving cells like Dictyostelium and neutrophils an intrinsic pseudopod cycle lies at the heart of cell motility. This implies that the mechanism behind chemotaxis relies on modification of intrinsic pseudopod behaviour, more than generation of new pseudopods or actin polymerization by chemoattractant

    Circular RNAs Are the Predominant Transcript Isoform from Hundreds of Human Genes in Diverse Cell Types

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    Most human pre-mRNAs are spliced into linear molecules that retain the exon order defined by the genomic sequence. By deep sequencing of RNA from a variety of normal and malignant human cells, we found RNA transcripts from many human genes in which the exons were arranged in a non-canonical order. Statistical estimates and biochemical assays provided strong evidence that a substantial fraction of the spliced transcripts from hundreds of genes are circular RNAs. Our results suggest that a non-canonical mode of RNA splicing, resulting in a circular RNA isoform, is a general feature of the gene expression program in human cells

    An Experimental and Computational Study of the Effect of ActA Polarity on the Speed of Listeria monocytogenes Actin-based Motility

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    Listeria monocytogenes is a pathogenic bacterium that moves within infected cells and spreads directly between cells by harnessing the cell's dendritic actin machinery. This motility is dependent on expression of a single bacterial surface protein, ActA, a constitutively active Arp2,3 activator, and has been widely studied as a biochemical and biophysical model system for actin-based motility. Dendritic actin network dynamics are important for cell processes including eukaryotic cell motility, cytokinesis, and endocytosis. Here we experimentally altered the degree of ActA polarity on a population of bacteria and made use of an ActA-RFP fusion to determine the relationship between ActA distribution and speed of bacterial motion. We found a positive linear relationship for both ActA intensity and polarity with speed. We explored the underlying mechanisms of this dependence with two distinctly different quantitative models: a detailed agent-based model in which each actin filament and branched network is explicitly simulated, and a three-state continuum model that describes a simplified relationship between bacterial speed and barbed-end actin populations. In silico bacterial motility required a cooperative restraining mechanism to reconstitute our observed speed-polarity relationship, suggesting that kinetic friction between actin filaments and the bacterial surface, a restraining force previously neglected in motility models, is important in determining the effect of ActA polarity on bacterial motility. The continuum model was less restrictive, requiring only a filament number-dependent restraining mechanism to reproduce our experimental observations. However, seemingly rational assumptions in the continuum model, e.g. an average propulsive force per filament, were invalidated by further analysis with the agent-based model. We found that the average contribution to motility from side-interacting filaments was actually a function of the ActA distribution. This ActA-dependence would be difficult to intuit but emerges naturally from the nanoscale interactions in the agent-based representation

    Control of Dendritic Morphogenesis by Trio in Drosophila melanogaster

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    Abl tyrosine kinase and its effectors among the Rho family of GTPases each act to control dendritic morphogenesis in Drosophila. It has not been established, however, which of the many GTPase regulators in the cell link these signaling molecules in the dendrite. In axons, the bifunctional guanine exchange factor, Trio, is an essential link between the Abl tyrosine kinase signaling pathway and Rho GTPases, particularly Rac, allowing these systems to act coordinately to control actin organization. In dendritic morphogenesis, however, Abl and Rac have contrary rather than reinforcing effects, raising the question of whether Trio is involved, and if so, whether it acts through Rac, Rho or both. We now find that Trio is expressed in sensory neurons of the Drosophila embryo and regulates their dendritic arborization. trio mutants display a reduction in dendritic branching and increase in average branch length, whereas over-expression of trio has the opposite effect. We further show that it is the Rac GEF domain of Trio, and not its Rho GEF domain that is primarily responsible for the dendritic function of Trio. Thus, Trio shapes the complexity of dendritic arbors and does so in a way that mimics the effects of its target, Rac

    An Adhesion-Dependent Switch between Mechanisms That Determine Motile Cell Shape

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    Keratocytes are fast-moving cells in which adhesion dynamics are tightly coupled to the actin polymerization motor that drives migration, resulting in highly coordinated cell movement. We have found that modifying the adhesive properties of the underlying substrate has a dramatic effect on keratocyte morphology. Cells crawling at intermediate adhesion strengths resembled stereotypical keratocytes, characterized by a broad, fan-shaped lamellipodium, clearly defined leading and trailing edges, and persistent rates of protrusion and retraction. Cells at low adhesion strength were small and round with highly variable protrusion and retraction rates, and cells at high adhesion strength were large and asymmetrical and, strikingly, exhibited traveling waves of protrusion. To elucidate the mechanisms by which adhesion strength determines cell behavior, we examined the organization of adhesions, myosin II, and the actin network in keratocytes migrating on substrates with different adhesion strengths. On the whole, our results are consistent with a quantitative physical model in which keratocyte shape and migratory behavior emerge from the self-organization of actin, adhesions, and myosin, and quantitative changes in either adhesion strength or myosin contraction can switch keratocytes among qualitatively distinct migration regimes

    Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems

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    Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. © 2014 Hogg et al

    Myceliophthora thermophila M77 utilizes hydrolytic and oxidative mechanisms to deconstruct biomass

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    Biomass is abundant, renewable and useful for biofuel production as well as chemical priming for plastics and composites. Deconstruction of biomass by enzymes is perceived as recalcitrant while an inclusive breakdown mechanism remains to be discovered. Fungi such as Myceliophthora thermophila M77 appear to decompose natural biomass sources quite well. This work reports on this fungus fermentation property while producing cellulolytic enzymes using natural biomass substrates. Little hydrolytic activity was detected, insufficient to explain the large amount of biomass depleted in the process. Furthermore, this work makes a comprehensive account of extracellular proteins and describes how secretomes redirect their qualitative protein content based on the nature and chemistry of the nutritional source. Fungus grown on purified cellulose or on natural biomass produced secretomes constituted by: cellobiohydrolases, cellobiose dehydrogenase, B-1,3 glucanase, B-glucosidases, aldose epimerase, glyoxal oxidase, GH74 xyloglucanase, galactosidase, aldolactonase and polysaccharide monooxygenases. Fungus grown on a mixture of purified hemicellulose fractions (xylans, arabinans and arabinoxylans) produced many enzymes, some of which are listed here: xylosidase, mixed B-1,3(4) glucanase, B-1,3 glucanases, B-glucosidases, B-mannosidase, B-glucosidases, galactosidase, chitinases, polysaccharide lyase, endo B-1,6 galactanase and aldose epimerase. Secretomes produced on natural biomass displayed a comprehensive set of enzymes involved in hydrolysis and oxidation of cellulose, hemicellulose-pectin and lignin. The participation of oxidation reactions coupled to lignin decomposition in the breakdown of natural biomass may explain the discrepancy observed for cellulose decomposition in relation to natural biomass fermentation experiments.Peer reviewedMicrobiology and Molecular GeneticsBiochemistry and Microbiolog
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