964 resultados para Models, Biological
Resumo:
Phagocytosis, whether of food particles in protozoa or bacteria and cell remnants in the metazoan immune system, is a conserved process. The particles are taken up into phagosomes, which then undergo complex remodeling of their components, called maturation. By using two-dimensional gel electrophoresis and mass spectrometry combined with genomic data, we identified 179 phagosomal proteins in the amoeba Dictyostelium, including components of signal transduction, membrane traffic, and the cytoskeleton. By carrying out this proteomics analysis over the course of maturation, we obtained time profiles for 1,388 spots and thus generated a dynamic record of phagosomal protein composition. Clustering of the time profiles revealed five clusters and 24 functional groups that were mapped onto a flow chart of maturation. Two heterotrimeric G protein subunits, Galpha4 and Gbeta, appeared at the earliest times. We showed that mutations in the genes encoding these two proteins produce a phagocytic uptake defect in Dictyostelium. This analysis of phagosome protein dynamics provides a reference point for future genetic and functional investigations.
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In the mouse, over the last 20 years, a set of cell-surface markers and activities have been identified, enabling the isolation of bone marrow (BM) populations highly enriched in hematopoietic stem cells (HSCs). These HSCs have the ability to generate multiple lineages and are capable of long-term self-renewal activity such that they are able to reconstitute and maintain a functional hematopoietic system after transplantation into lethally irradiated recipients. Using single-cell reconstitution assays, various marker combinations can be used to achieve a functional HSC purity of almost 50%. Here we have used the differential expression of six of these markers (Sca1, c-Kit, CD135, CD48, CD150, and CD34) on lineage-depleted BM to refine cell hierarchies within the HSC population. At the top of the hierarchy, we propose a dormant HSC population (Lin(-)Sca1(+)c-Kit(+) CD48(-)CD150(+)CD34(-)) that gives rise to an active self-renewing CD34(+) HSC population. HSC dormancy, as well as the balance between self-renewal and differentiation activity, is at least, in part, controlled by the stem cell niches individual HSCs are attached to. Here we review the current knowledge about HSC niches and propose that dormant HSCs are located in niches at the endosteum, whereas activated HSCs are in close contact to sinusoids of the BM microvasculature.
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A new metabolite profiling approach combined with an ultrarapid sample preparation procedure was used to study the temporal and spatial dynamics of the wound-induced accumulation of jasmonic acid (JA) and its oxygenated derivatives in Arabidopsis thaliana. In addition to well known jasmonates, including hydroxyjasmonates (HOJAs), jasmonoyl-isoleucine (JA-Ile), and its 12-hydroxy derivative (12-HOJA-Ile), a new wound-induced dicarboxyjasmonate, 12-carboxyjasmonoyl-l-isoleucine (12-HOOCJA-Ile) was discovered. HOJAs and 12-HOOCJA-Ile were enriched in the midveins of wounded leaves, strongly differentiating them from the other jasmonate metabolites studied. The polarity of these oxylipins at physiological pH correlated with their appearance in midveins. When the time points of accumulation of different jasmonates were determined, JA levels were found to increase within 2-5 min of wounding. Remarkably, these changes occurred throughout the plant and were not restricted to wounded leaves. The speed of the stimulus leading to JA accumulation in leaves distal to a wound is at least 3 cm/min. The data give new insights into the spatial and temporal accumulation of jasmonates and have implications in the understanding of long-distance wound signaling in plants.
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Growing experimental evidence indicates that, in addition to the physical virion components, the non-structural proteins of hepatitis C virus (HCV) are intimately involved in orchestrating morphogenesis. Since it is dispensable for HCV RNA replication, the non-structural viral protein NS2 is suggested to play a central role in HCV particle assembly. However, despite genetic evidences, we have almost no understanding about NS2 protein-protein interactions and their role in the production of infectious particles. Here, we used co-immunoprecipitation and/or fluorescence resonance energy transfer with fluorescence lifetime imaging microscopy analyses to study the interactions between NS2 and the viroporin p7 and the HCV glycoprotein E2. In addition, we used alanine scanning insertion mutagenesis as well as other mutations in the context of an infectious virus to investigate the functional role of NS2 in HCV assembly. Finally, the subcellular localization of NS2 and several mutants was analyzed by confocal microscopy. Our data demonstrate molecular interactions between NS2 and p7 and E2. Furthermore, we show that, in the context of an infectious virus, NS2 accumulates over time in endoplasmic reticulum-derived dotted structures and colocalizes with both the envelope glycoproteins and components of the replication complex in close proximity to the HCV core protein and lipid droplets, a location that has been shown to be essential for virus assembly. We show that NS2 transmembrane region is crucial for both E2 interaction and subcellular localization. Moreover, specific mutations in core, envelope proteins, p7 and NS5A reported to abolish viral assembly changed the subcellular localization of NS2 protein. Together, these observations indicate that NS2 protein attracts the envelope proteins at the assembly site and it crosstalks with non-structural proteins for virus assembly.
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BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.
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Individuals carrying BRCA2 mutations are predisposed to breast and ovarian cancers. Here, we show that BRCA2 plays a dual role in regulating the actions of RAD51, a protein essential for homologous recombination and DNA repair. First, interactions between RAD51 and the BRC3 or BRC4 regions of BRCA2 block nucleoprotein filament formation by RAD51. Alterations to the BRC3 region that mimic cancer-associated BRCA2 mutations fail to exhibit this effect. Second, transport of RAD51 to the nucleus is defective in cells carrying a cancer-associated BRCA2 truncation. Thus, BRCA2 regulates both the intracellular localization and DNA binding ability of RAD51. Loss of these controls following BRCA2 inactivation may be a key event leading to genomic instability and tumorigenesis.
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High-throughput technologies are now used to generate more than one type of data from the same biological samples. To properly integrate such data, we propose using co-modules, which describe coherent patterns across paired data sets, and conceive several modular methods for their identification. We first test these methods using in silico data, demonstrating that the integrative scheme of our Ping-Pong Algorithm uncovers drug-gene associations more accurately when considering noisy or complex data. Second, we provide an extensive comparative study using the gene-expression and drug-response data from the NCI-60 cell lines. Using information from the DrugBank and the Connectivity Map databases we show that the Ping-Pong Algorithm predicts drug-gene associations significantly better than other methods. Co-modules provide insights into possible mechanisms of action for a wide range of drugs and suggest new targets for therapy
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It is estimated that one third of the world population is latently infected by Mycobacterium tuberculosis and thus at risk of reactivation. Latent tuberculosis (TB) impact in Switzerland is often overlooked. Diagnosis and prophylaxis are insufficiently undertaken, especially for people at higher risk of reactivation due to immunosuppression. Interferon-gamma release assays replace tuberculosis skin tests for diagnosis of latent infection in adults. It is still recommended to treat prophylactically a case of latent TB infection with 9 months of isoniazid; however therapy with rifampicin for 4 months, currently an alternative option, is linked to improved adherence and favorable cost-benefit ratio.
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Real-time imaging of stromal and immune cells in tumors is an emerging field that will greatly help us to understand the role of these non-malignant tumor components in tumor progression and therapy.
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During the last several years, the mechanism of IFN gamma-dependent signal transduction has been the focus of intense investigation. This research has recently culminated in the elucidation of a comprehensive molecular understanding of the events that underlie IFN gamma-induced cellular responses. The structure and function of the IFN gamma receptor have been defined. The mechanism of IFN gamma signal transduction has been largely elucidated, and the physiologic relevance of this process validated. Most recently, the molecular events that link receptor ligation to signal transduction have been established. Together these insights have produced a model of IFN gamma signaling that is nearly complete and that serves as a paradigm for signaling by other members of the cytokine receptor superfamily.
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Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot
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Phenoxyalkanoic acid degradation is well studied in Beta- and Gammaproteobacteria, but the genetic background has not been elucidated so far in Alphaproteobacteria. We report the isolation of several genes involved in dichlor- and mecoprop degradation from the alphaproteobacterium Sphingomonas herbicidovorans MH and propose that the degradation proceeds analogously to that previously reported for 2,4-dichlorophenoxyacetic acid (2,4-D). Two genes for alpha-ketoglutarate-dependent dioxygenases, sdpA(MH) and rdpA(MH), were found, both of which were adjacent to sequences with potential insertion elements. Furthermore, a gene for a dichlorophenol hydroxylase (tfdB), a putative regulatory gene (cadR), two genes for dichlorocatechol 1,2-dioxygenases (dccA(I/II)), two for dienelactone hydrolases (dccD(I/II)), part of a gene for maleylacetate reductase (dccE), and one gene for a potential phenoxyalkanoic acid permease were isolated. In contrast to other 2,4-D degraders, the sdp, rdp, and dcc genes were scattered over the genome and their expression was not tightly regulated. No coherent pattern was derived on the possible origin of the sdp, rdp, and dcc pathway genes. rdpA(MH) was 99% identical to rdpA(MC1), an (R)-dichlorprop/alpha-ketoglutarate dioxygenase from Delftia acidovorans MC1, which is evidence for a recent gene exchange between Alpha- and Betaproteobacteria. Conversely, DccA(I) and DccA(II) did not group within the known chlorocatechol 1,2-dioxygenases, but formed a separate branch in clustering analysis. This suggests a different reservoir and reduced transfer for the genes of the modified ortho-cleavage pathway in Alphaproteobacteria compared with the ones in Beta- and Gammaproteobacteria.
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Current levels of endangerment and historical trends of species and habitats are the main criteria used to direct conservation efforts globally. Estimates of future declines, which might indicate different priorities than past declines, have been limited by the lack of appropriate data and models. Given that much of conservation is about anticipating and responding to future threats, our inability to look forward at a global scale has been a major constraint on effective action. Here, we assess the geography and extent of projected future changes in suitable habitat for terrestrial mammals within their present ranges. We used a global earth-system model, IMAGE, coupled with fine-scale habitat suitability models and parametrized according to four global scenarios of human development. We identified the most affected countries by 2050 for each scenario, assuming that no additional conservation actions other than those described in the scenarios take place. We found that, with some exceptions, most of the countries with the largest predicted losses of suitable habitat for mammals are in Africa and the Americas. African and North American countries were also predicted to host the most species with large proportional global declines. Most of the countries we identified as future hotspots of terrestrial mammal loss have little or no overlap with the present global conservation priorities, thus confirming the need for forward-looking analyses in conservation priority setting. The expected growth in human populations and consumption in hotspots of future mammal loss mean that local conservation actions such as protected areas might not be sufficient to mitigate losses. Other policies, directed towards the root causes of biodiversity loss, are required, both in Africa and other parts of the world.
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The concept of ideal geometric configurations was recently applied to the classification and characterization of various knots. Different knots in their ideal form (i.e., the one requiring the shortest length of a constant-diameter tube to form a given knot) were shown to have an overall compactness proportional to the time-averaged compactness of thermally agitated knotted polymers forming corresponding knots. This was useful for predicting the relative speed of electrophoretic migration of different DNA knots. Here we characterize the ideal geometric configurations of catenanes (called links by mathematicians), i.e., closed curves in space that are topologically linked to each other. We demonstrate that the ideal configurations of different catenanes show interrelations very similar to those observed in the ideal configurations of knots. By analyzing literature data on electrophoretic separations of the torus-type of DNA catenanes with increasing complexity, we observed that their electrophoretic migration is roughly proportional to the overall compactness of ideal representations of the corresponding catenanes. This correlation does not apply, however, to electrophoretic migration of certain replication intermediates, believed up to now to represent the simplest torus-type catenanes. We propose, therefore, that freshly replicated circular DNA molecules, in addition to forming regular catenanes, may also form hemicatenanes.