71 resultados para POSITIVE INTERACTIONS


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Background: Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment andinnate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Results:Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection arefrequent on genes that are known to be at bifurcation points, and that are identified as beingin key position by a network-level analysis such as MGAT3 and GCS1.Conclusions: These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.

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Placental malaria is a special form of malaria that causes up to 200,000 maternal and infant deaths every year. Previous studies show that two receptor molecules, hyaluronic acid and chondroitin sulphate A, are mediating the adhesion of parasite-infected erythrocytes in the placenta of patients, which is believed to be a key step in the pathogenesis of the disease. In this study, we aimed at identifying sites of malaria-induced adaptation by scanning for signatures of natural selection in 24 genes in the complete biosynthesis pathway of these two receptor molecules. We analyzed a total of 24 Mb of publicly available polymorphism data from the International HapMap project for three human populations with European, Asian and African ancestry, with the African population from a region of presently and historically high malaria prevalence. Using the methods based on allele frequency distributions, genetic differentiation between populations, and on long-range haplotype structure, we found only limited evidence for malaria-induced genetic adaptation in this set of genes in the African population; however, we identified one candidate gene with clear evidence of selection in the Asian population. Although historical exposure to malaria in this population cannot be ruled out, we speculate that it might be caused by other pathogens, as there is growing evidence that these molecules are important receptors in a variety of host-pathogen interactions. We propose to use the present methods in a systematic way to help identify candidate regions under positive selection as a consequence of malaria.

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Background: The human FOXI1 gene codes for a transcription factor involved in the physiology of the inner ear, testis, and kidney. Using three interspecies comparisons, it has been suggested that this may be a gene underhuman-specific selection. We sought to confirm this finding by using an extended set of orthologous sequences.Additionally, we explored for signals of natural selection within humans by sequencing the gene in 20 Europeans,20 East Asians and 20 Yorubas and by analysing SNP variation in a 2 Mb region centered on FOXI1 in 39worldwide human populations from the HGDP-CEPH diversity panel.Results: The genome sequences recently available from other primate and non-primate species showed that FOXI1divergence patterns are compatible with neutral evolution. Sequence-based neutrality tests were not significant inEuropeans, East Asians or Yorubas. However, the Long Range Haplotype (LRH) test, as well as the iHS and XP-Rsbstatistics revealed significantly extended tracks of homozygosity around FOXI1 in Africa, suggesting a recentepisode of positive selection acting on this gene. A functionally relevant SNP, as well as several SNPs either on theputatively selected core haplotypes or with significant iHS or XP-Rsb values, displayed allele frequencies stronglycorrelated with the absolute geographical latitude of the populations sampled.Conclusions: We present evidence for recent positive selection in the FOXI1 gene region in Africa. Climate mightbe related to this recent adaptive event in humans. Of the multiple functions of FOXI1, its role in kidney-mediatedwater-electrolyte homeostasis is the most obvious candidate for explaining a climate-related adaptation.

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Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characterize cancer, but validating their results can be a laborious task. Computational approaches are used to prioritize between genes putatively involved in cancer, usually based on further analyzing experimental data. Results: We implemented a systematic method using the PIANA software that predicts cancer involvement of genes by integrating heterogeneous datasets. Specifically, we produced lists of genes likely to be involved in cancer by relying on: (i) protein-protein interactions; (ii) differential expression data; and (iii) structural and functional properties of cancer genes. The integrative approach that combines multiple sources of data obtained positive predictive values ranging from 23% (on a list of 811 genes) to 73% (on a list of 22 genes), outperforming the use of any of the data sources alone. We analyze a list of 20 cancer gene predictions, finding that most of them have been recently linked to cancer in literature. Conclusion: Our approach to identifying and prioritizing candidate cancer genes can be used to produce lists of genes likely to be involved in cancer. Our results suggest that differential expression studies yielding high numbers of candidate cancer genes can be filtered using protein interaction networks.

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Background: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. Results: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. Conclusion: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.

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Background: The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties.Results: We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php.Conclusions: BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

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This paper studies monetary and fiscal policy interactions in a two country model, where taxes on firms sales are optimally chosen and the monetary policy is set cooperatively.It turns out that in a two country setting non-cooperative fiscal policy makers have an incentive to change taxes on sales depending on shocks realizations in order to reduce output production. Therefore whether the fiscal policy is set cooperatively or not matters for optimal monetary policy decisions. Indeed, as already shown in the literature, the cooperative monetary policy maker implements the flexible price allocation only when special conditions on the value of the distortions underlying the economy are met. However, if non-cooperative fiscal policy makers set the taxes on firms sales depending on shocks realizations, these conditions cannot be satisfied; conversely, when fiscal policy is cooperative, these conditions are fulfilled. We conclude that whether implementing the flexible price allocation is optimal or not depends on the fiscal policy regime.

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This paper reconsiders the empirical evidence on the asymmetricoutput effects of monetary policy. Asymmetric effects is a common feature ofmany theoretical models, and there are many different versions of suchasymmetries. We concentrate on the distinctions between positive andnegative money-supply changes, big and small changes in money-supply, andpossible combinations of the two asymmetries. Earlier research has foundempirical evidence in favor of the former of these in US data. Using M1 asthe monetary variable we find evidence in favor of neutrality of big shocksand non-neutrality of small shocks. The results may, however, be affected bystructual instability of M1 demand. Thus, we substitute M1 with the federalfunds rate. In these data we find that only small negative shocks affectreal aggregate activity. The results are interpreted in terms of menu-costmodels.

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That individuals contribute in social dilemma interactions even when contributing is costly is a well-established observation in the experimental literature. Since a contributor is always strictly worse off than a non-contributor the question is raised if an intrinsic motivation to contribute can survive in an evolutionary setting. Using recent results on deterministic approximation of stochastic evolutionary dynamics we give conditions for equilibria with a positive number of contributors to be selected in the long run.

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This paper presents a tractable dynamic general equilibrium model thatcan explain cross-country empirical regularities in geographical mobility,unemployment and labor market institutions. Rational agents vote overunemployment insurance (UI), taking the dynamic distortionary effects ofinsurance on the performance of the labor market into consideration.Agents with higher cost of moving, i.e., more attached to their currentlocation, prefer more generous UI. The key assumption is that an agent'sattachment to a location increases the longer she has resided there. UIreduces the incentive for labor mobility and increases, therefore, thefraction of attached agents and the political support for UI. The mainresult is that this self-reinforcing mechanism can give rise to multiplesteady-states-one 'European' steady-state featuring high unemployment,low geographical mobility and high unemployment insurance, and one'American' steady-state featuring low unemployment, high mobility andlow unemployment insurance.

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Plants, like humans and other animals, also get sick, exhibit disease symptoms, and die. Plant diseases are caused by environmental stress, genetic or physiological disorders and infectious agents including viroids, viruses, bacteria and fungi. Plant pathology originated from the convergence of microbiology, botany and agronomy; its ultimate goal is the control of plant disease. Microbiologists have been attracted to this field of research because of the need for identification of the agents causing infectious diseases in economically important crops. In 1878—only two years after Pasteur and Koch had shown for the first time that anthrax in animals was caused by a bacteria—Burril, in the USA, discovered that the fire blight disease of apple and pear was also caused by a bacterium (nowadays known as Erwinia amylovora). In 1898, Beijerinck concluded that tobacco mosaic was caused by a “contagium vivum fluidum” which he called a virus. In 1971, Diener proved that a potato disease named potato spindle tuber was caused by infectious RNA which he called viroid

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Interactions between yellow-legged Larus cachinnans and Audouin´s Larus audouinii gulls and fisheries operating around the Chafarinas Islands, located 4.5 km off the Moroccan Mediterranean coast, are reviewed. At the Chafarinas archipelago two distinct types of fisheries operate: trawlers and purse seines. Gulls take advantage of both fisheries. They scavenge trawler discards and congregate around shoals of fish attracted to the surface by the purse-seine lamps. When both trawlers and purse-seine boats are in operation, the diet of both gull species is similar, with epipelagic fish accounting for over 60% of the biomass, partially collected in association with the purse-seine fishery. When only trawlers operated yellow-legged gulls, but not Audouin´s gulls, augmented their diet mainly with human waste from refuse dumps, suggesting that competition for food between the two species is mainly limited to the periods when resources made available by fishery activities are abundant. Likewise, when only trawlers operated, there was an increase in the predation pressure on eggs and chicks of Audouin´s gulls. In particular, during the week of celebrations for the holy lamb festival when neither fishery operated, egg losses of Audouin´s gull increased dramatically, suggesting that severe food shortage caused by the cessation of fishing can result in an increased predation pressure by yellow-legged gulls, affecting Audouin´s gull productivity. These results suggest a novel socio-ecological link between gulls, fisheries and local feasts.

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The clathrin assembly lymphoid myeloid leukemia (CALM) gene encodes a putative homologue of the clathrin assembly synaptic protein AP180. Hence the biochemical properties, the subcellular localization, and the role in endocytosis of a CALM protein were studied. In vitro binding and coimmunoprecipitation demonstrated that the clathrin heavy chain is the major binding partner of CALM. The bulk of cellular CALM was associated with the membrane fractions of the cell and localized to clathrin-coated areas of the plasma membrane. In the membrane fraction, CALM was present at near stoichiometric amounts relative to clathrin. To perform structure-function analysis of CALM, we engineered chimeric fusion proteins of CALM and its fragments with the green fluorescent protein (GFP). GFP-CALM was targeted to the plasma membrane-coated pits and also found colocalized with clathrin in the Golgi area. High levels of expression of GFP-CALM or its fragments with clathrin-binding activity inhibited the endocytosis of transferrin and epidermal growth factor receptors and altered the steady-state distribution of the mannose-6-phosphate receptor in the cell. In addition, GFP-CALM overexpression caused the loss of clathrin accumulation in the trans-Golgi network area, whereas the localization of the clathrin adaptor protein complex 1 in the trans-Golgi network remained unaffected. The ability of the GFP-tagged fragments of CALM to affect clathrin-mediated processes correlated with the targeting of the fragments to clathrin-coated areas and their clathrin-binding capacities. Clathrin-CALM interaction seems to be regulated by multiple contact interfaces. The C-terminal part of CALM binds clathrin heavy chain, although the full-length protein exhibited maximal ability for interaction. Altogether, the data suggest that CALM is an important component of coated pit internalization machinery, possibly involved in the regulation of clathrin recruitment to the membrane and/or the formation of the coated pit.

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Ran, the small, predominantly nuclear GTPase, has been implicated in the regulation of a variety of cellular processes including cell cycle progression, nuclear-cytoplasmic trafficking of RNA and protein, nuclear structure, and DNA synthesis. It is not known whether Ran functions directly in each process or whether many of its roles may be secondary to a direct role in only one, for example, nuclear protein import. To identify biochemical links between Ran and its functional target(s), we have generated and examined the properties of a putative Ran effector mutation, T42A-Ran. T42A-Ran binds guanine nucleotides as well as wild-type Ran and responds as well as wild-type Ran to GTP or GDP exchange stimulated by the Ran-specific guanine nucleotide exchange factor, RCC1. T42A-Ran·GDP also retains the ability to bind p10/NTF2, a component of the nuclear import pathway. In contrast to wild-type Ran, T42A-Ran·GTP binds very weakly or not detectably to three proposed Ran effectors, Ran-binding protein 1 (RanBP1), Ran-binding protein 2 (RanBP2, a nucleoporin), and karyopherin ß (a component of the nuclear protein import pathway), and is not stimulated to hydrolyze bound GTP by Ran GTPase-activating protein, RanGAP1. Also in contrast to wild-type Ran, T42A-Ran does not stimulate nuclear protein import in a digitonin permeabilized cell assay and also inhibits wild-type Ran function in this system. However, the T42A mutation does not block the docking of karyophilic substrates at the nuclear pore. These properties of T42A-Ran are consistent with its classification as an effector mutant and define the exposed region of Ran containing the mutation as a probable effector loop.