999 resultados para Predicting Signal Peptides
Resumo:
Fas is a cell surface death receptor that signals apoptosis. Several proteins have been identified that bind to the cytoplasmic death domain of Fas. Fas-associated death domain (FADD), which couples Fas to procaspase-8, and Daxx, which couples Fas to the Jun NH(2)-terminal kinase pathway, bind independently to the Fas death domain. We have identified a 130-kD kinase designated Fas-interacting serine/threonine kinase/homeodomain-interacting protein kinase (FIST/HIPK3) as a novel Fas-interacting protein. Binding to Fas is mediated by a conserved sequence in the COOH terminus of the protein. FIST/HIPK3 is widely expressed in mammalian tissues and is localized both in the nucleus and in the cytoplasm. In transfected cell lines, FIST/HIPK3 causes FADD phosphorylation, thereby promoting FIST/HIPK3-FADD-Fas interaction. Although Fas ligand-induced activation of Jun NH(2)-terminal kinase is impaired by overexpressed active FIST/HIPK3, cell death is not affected. These results suggest that Fas-associated FIST/HIPK3 modulates one of the two major signaling pathways of Fas.
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T lymphocytes recognize antigen in the form of peptides that associate with specific alleles of class I or class II major histocompatibility (MHC) molecules. By contrast with the clear MHC allele-specific binding of peptides to purified class II molecules purified solubilized class I molecules either bind relatively poorly or show degenerate specificity. Using photo-affinity labelling, we demonstrate here the specific interaction of peptides with cell-associated MHC class I molecules and show that this involves metabolically active processes.
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Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.
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The double spin-echo point resolved spectroscopy sequence (PRESS) is a widely used method and standard in clinical MR spectroscopy. Existence of important J-modulations at constant echo times, depending on the temporal delays between the rf-pulses, have been demonstrated recently for strongly coupled spin systems and were exploited for difference editing, removing singlets from the spectrum (strong-coupling PRESS, S-PRESS). A drawback of this method for in vivo applications is that large signal modulations needed for difference editing occur only at relatively long echo times. In this work we demonstrate that, by simply adding a third refocusing pulse (3S-PRESS), difference editing becomes possible at substantially shorter echo times while, as applied to citrate, more favorable lineshapes can be obtained. For the example of an AB system an analytical description of the MR signal, obtained with this triple refocusing sequence (3S-PRESS), is provided.
Resumo:
As an approved vaccine adjuvant for use in humans, alum has vast health implications, but, as it is a crystal, questions remain regarding its mechanism. Furthermore, little is known about the target cells, receptors, and signaling pathways engaged by alum. Here we report that, independent of inflammasome and membrane proteins, alum binds dendritic cell (DC) plasma membrane lipids with substantial force. Subsequent lipid sorting activates an abortive phagocytic response that leads to antigen uptake. Such activated DCs, without further association with alum, show high affinity and stable binding with CD4(+) T cells via the adhesion molecules intercellular adhesion molecule-1 (ICAM-1) and lymphocyte function-associated antigen-1 (LFA-1). We propose that alum triggers DC responses by altering membrane lipid structures. This study therefore suggests an unexpected mechanism for how this crystalline structure interacts with the immune system and how the DC plasma membrane may behave as a general sensor for solid structures.
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We designed a trap system to isolate different amino acid sequences which could target proteins to the cell surface via GPI anchor transfer. This selection procedure is based on the insertion of various sequences which regenerate a functional GPI anchor signal sequence and therefore provoke re-expression at the surface of a reporter molecule. Using this trap for cell surface targeting sequences, we could show the importance of the defined elements essential for GPI anchor addition. Such a system could be used for an exhaustive analysis of the carboxyl terminus structural requirements for GPI membrane anchoring.
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Fungal infections represent a serious threat, particularly in immunocompromised patients. Interleukin-1beta (IL-1beta) is a key pro-inflammatory factor in innate antifungal immunity. The mechanism by which the mammalian immune system regulates IL-1beta production after fungal recognition is unclear. Two signals are generally required for IL-1beta production: an NF-kappaB-dependent signal that induces the synthesis of pro-IL-1beta (p35), and a second signal that triggers proteolytic pro-IL-1beta processing to produce bioactive IL-1beta (p17) via Caspase-1-containing multiprotein complexes called inflammasomes. Here we demonstrate that the tyrosine kinase Syk, operating downstream of several immunoreceptor tyrosine-based activation motif (ITAM)-coupled fungal pattern recognition receptors, controls both pro-IL-1beta synthesis and inflammasome activation after cell stimulation with Candida albicans. Whereas Syk signalling for pro-IL-1beta synthesis selectively uses the Card9 pathway, inflammasome activation by the fungus involves reactive oxygen species production and potassium efflux. Genetic deletion or pharmalogical inhibition of Syk selectively abrogated inflammasome activation by C. albicans but not by inflammasome activators such as Salmonella typhimurium or the bacterial toxin nigericin. Nlrp3 (also known as NALP3) was identified as the critical NOD-like receptor family member that transduces the fungal recognition signal to the inflammasome adaptor Asc (Pycard) for Caspase-1 (Casp1) activation and pro-IL-1beta processing. Consistent with an essential role for Nlrp3 inflammasomes in antifungal immunity, we show that Nlrp3-deficient mice are hypersusceptible to Candida albicans infection. Thus, our results demonstrate the molecular basis for IL-1beta production after fungal infection and identify a crucial function for the Nlrp3 inflammasome in mammalian host defence in vivo.
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Communication is an indispensable component of animal societies, yet many open questions remain regarding the factors affecting the evolution and reliability of signalling systems. A potentially important factor is the level of genetic relatedness between signallers and receivers. To quantitatively explore the role of relatedness in the evolution of reliable signals, we conducted artificial evolution over 500 generations in a system of foraging robots that can emit and perceive light signals. By devising a quantitative measure of signal reliability, and comparing independently evolving populations differing in within-group relatedness, we show a strong positive correlation between relatedness and reliability. Unrelated robots produced unreliable signals, whereas highly related robots produced signals that reliably indicated the location of the food source and thereby increased performance. Comparisons across populations also revealed that the frequency for signal production-which is often used as a proxy of signal reliability in empirical studies on animal communication-is a poor predictor of signal reliability and, accordingly, is not consistently correlated with group performance. This has important implications for our understanding of signal evolution and the empirical tools that are used to investigate communication.
Resumo:
Presented here is a cell-suspension model for positive selection using thymocytes from alphabeta-TCR (H-2Db-restricted) transgenic mice specific to the lymphocytic choriomeningitis virus (LCMV) on a nonselecting MHC background (H-2d or TAP-1 -/-), cocultured with freshly isolated adult thymus stromal cells of the selecting MHC type. The thymic stromal cells alone induced positive selection of functional CD4- CD8+ cells whose kinetics and efficiency were enhanced by nominal peptide. Fibroblasts expressing the selecting MHC alone did not induce positive selection; however, together with nonselecting stroma and nominal peptide, there was inefficient positive. These results suggest multiple signaling in positive selection with selection events able to occur on multiple-cell types. The ease with which this model can be manipulated should greatly facilitate the resolution of the mechanisms of positive selection in normal and pathological states.
Resumo:
Until recently, most research efforts aimed at developing anti-cancer tools were focusing on small molecules. Alternative compounds are now being increasingly assessed for their potential anti-cancer properties, including peptides and their derivatives. One earlier limitation to the use of peptides was their limited capacity to cross membranes but this limitation was alleviated with the characterization of cell-permeable sequences. Additionally, means are designed to target peptides to their malignant targets. Most anti-cancer peptidic compounds induce apoptosis of tumor cells by modulating the activity of Bcl-2 family members that control the release of death factors from the mitochondria or by inhibiting negative regulators of caspases, the proteases that mediate the apoptotic response in cells. Some of these peptides have been shown to inhibit the growth of tumors in mouse models. Hopefully, pro-apoptotic anti-tumor peptides will soon be tested for their efficacy in patients with cancers.
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Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realised properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate assemblage properties. Here, we propose to unify the two approaches in a single 'spatially-explicit species assemblage modelling' (SESAM) framework. This framework uses relevant species source pool designations, macroecological factors, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.
Resumo:
PURPOSE: To evaluate the effect of XG-102 (formerly D-JNKI1), a TAT-coupled dextrogyre peptide that selectively inhibits the c-Jun N-terminal kinase, in the treatment of endotoxin-induced uveitis (EIU). METHODS: EIU was induced in Lewis rats by LPS injection. XG-102 was administered at the time of LPS challenge. The ocular biodistribution of XG-102 was evaluated using immunodetection at 24 hours after either 20 microg/kg IV (IV) or 0.2 microg/injection intravitreous (IVT) administrations in healthy or uveitic eyes. The effect of XG-102 on EIU was evaluated using clinical scoring, infiltration cell quantification, inducible nitric oxide synthase (iNOS) expression and immunohistochemistry, and cytokines and chemokines kinetics at 6, 24, and 48 hours using multiplex analysis on ocular media. Control EIU eyes received vehicle injection IV or IVT. The effect of XG-102 on c-Jun phosphorylation in EIU was evaluated by Western blot in eye tissues. RESULTS: After IVT injection, XG-102 was internalized in epithelial cells from iris/ciliary body and retina and in glial and microglial cells in both healthy and uveitic eyes. After IV injection, XG-102 was concentrated primarily in inflammatory cells of uveitic eyes. Using both routes of administration, XG-102 significantly inhibited clinical signs of EIU, intraocular cell infiltration, and iNOS expression together with reduced phosphorylation of c-Jun. The anti-inflammatory effect of XG-102 was mediated by iNOS, IFN-gamma, IL-2, and IL-13. CONCLUSIONS: This is the first evidence that interfering with the JNK pathway can reduce intraocular inflammation. Local administration of XG-102, a clinically evaluated peptide, may have potential for treating uveitis.
Resumo:
The CD8 coreceptor plays a crucial role in both T cell development in the thymus and in the activation of mature T cells in response to Ag-specific stimulation. In this study we used soluble peptides-MHC class I (pMHC) multimeric complexes bearing mutations in the CD8 binding site that impair their binding to the MHC, together with altered peptide ligands, to assess the impact of CD8 on pMHC binding to the TCR. Our data support a model in which CD8 promotes the binding of TCR to pMHC. However, once the pMHC/TCR complex is formed, the TCR dominates the pMHC/TCR dissociation rates. As a consequence of these molecular interactions, under physiologic conditions CD8 plays a key role in complex formation, resulting in the enhancement of CD8 T cell functions whose specificity, however, is determined by the TCR.
Resumo:
One of the standard tools used to understand the processes shaping trait evolution along the branches of a phylogenetic tree is the reconstruction of ancestral states (Pagel 1999). The purpose is to estimate the values of the trait of interest for every internal node of a phylogenetic tree based on the trait values of the extant species, a topology and, depending on the method used, branch lengths and a model of trait evolution (Ronquist 2004). This approach has been used in a variety of contexts such as biogeography (e.g., Nepokroeff et al. 2003, Blackburn 2008), ecological niche evolution (e.g., Smith and Beaulieu 2009, Evans et al. 2009) and metabolic pathway evolution (e.g., Gabaldón 2003, Christin et al. 2008). Investigations of the factors affecting the accuracy with which ancestral character states can be reconstructed have focused in particular on the choice of statistical framework (Ekman et al. 2008) and the selection of the best model of evolution (Cunningham et al. 1998, Mooers et al. 1999). However, other potential biases affecting these methods, such as the effect of tree shape (Mooers 2004), taxon sampling (Salisbury and Kim 2001) as well as reconstructing traits involved in species diversification (Goldberg and Igić 2008), have also received specific attention. Most of these studies conclude that ancestral character states reconstruction is still not perfect, and that further developments are necessary to improve its accuracy (e.g., Christin et al. 2010). Here, we examine how different estimations of branch lengths affect the accuracy of ancestral character state reconstruction. In particular, we tested the effect of using time-calibrated versus molecular branch lengths and provide guidelines to select the most appropriate branch lengths to reconstruct the ancestral state of a trait.