994 resultados para Signal de transduction


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Bystander activation of T cells, i.e. the stimulation of unrelated (heterologous) T cells by cytokines during an Ag-specific T-cell response, has been best described for CD8(+) T cells. In the CD8(+) compartment, the release of IFN and IFN-inducers leads to the production of IL-15, which mediates the proliferation of CD8(+) T cells, notably memory-phenotype CD8(+) T cells. CD4(+) T cells also undergo bystander activation, however, the signals inducing this Ag-nonspecific stimulation of CD4(+) T cells are less well known. A study in this issue of the European Journal of Immunology sheds light on this aspect, suggesting that common gamma-chain cytokines including IL-2 might be involved in bystander activation of CD4(+) T cells.

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Transforming growth factor-beta (TGF-beta) and its related proteins regulate broad aspects of body development, including cell proliferation, differentiation, apoptosis and gene expression, in various organisms. Deregulated TGF-beta function has been causally implicated in the generation of human fibrotic disorders and in tumor progression. Nevertheless, the molecular mechanisms of TGF-beta action remained essentially unknown until recently. Here, we discuss recent progress in our understanding of the mechanism of TGF-beta signal transduction with respect to the regulation of gene expression, the control of cell phenotype and the potential usage of TGF-beta for the treatment of human diseases.

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Escherichia coli-based bioreporters for arsenic detection are typically based on the natural feedback loop that controls ars operon transcription. Feedback loops are known to show a wide range linear response to the detriment of the overall amplification of the incoming signal. While being a favourable feature in controlling arsenic detoxification for the cell, a feedback loop is not necessarily the most optimal for obtaining highest sensitivity and response in a designed cellular reporter for arsenic detection. Here we systematically explore the effects of uncoupling the topology of arsenic sensing circuitry on the developed reporter signal as a function of arsenite concentration input. A model was developed to describe relative ArsR and GFP levels in feedback and uncoupled circuitry, which was used to explore new ArsR-based synthetic circuits. The expression of arsR was then placed under the control of a series of constitutive promoters, which differed in promoter strength, and which could be further modulated by TetR repression. Expression of the reporter gene was maintained under the ArsR-controlled Pars promoter. ArsR expression in the systems was measured by using ArsR-mCherry fusion proteins. We find that stronger constitutive ArsR production decreases arsenite-dependent EGFP output from Pars and vice versa. This leads to a tunable series of arsenite-dependent EGFP outputs in a variety of systematically characterized circuitries. The higher expression levels and sensitivities of the response curves in the uncoupled circuits may be useful for improving field-test assays using arsenic bioreporters.

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Nanomotors are nanoscale devices capable of converting energy into movement and forces. Among them, self-propelled nanomotors offer considerable promise for developing new and novel bioanalytical and biosensing strategies based on the direct isolation of target biomolecules or changes in their movement in the presence of target analytes. The mainachievements of this project consists on the development of receptor-functionalized nanomotors that offer direct and rapid target detection, isolation and transport from raw biological samples without preparatory and washing steps. For example, microtube engines functionalized with aptamer, antibody, lectin and enzymes receptors were used for the direct isolation of analytes of biomedical interest, including proteins and whole cells, among others. A target protein was also isolated from a complex sample by using an antigen-functionalized microengine navigating into the reservoirs of a lab-on-a-chip device. The new nanomotorbased target biomarkers detection strategy not only offers highly sensitive, rapid, simple and low cost alternative for the isolation and transport of target molecules, but also represents a new dimension of analytical information based on motion. The recognition events can be easily visualized by optical microscope (without any sophisticated analytical instrument) to reveal the target presence and concentration. The use of artificial nanomachines has shown not only to be useful for (bio)recognition and (bio)transport but also for detection of environmental contamination and remediation. In this context, micromotors modified with superhydrophobic layer demonstrated that effectively interacted, captured, transported and removed oil droplets from oil contaminated samples. Finally, a unique micromotor-based strategy for water-quality testing, that mimics live-fish water-quality testing, based on changes in the propulsion behavior of artificial biocatalytic microswimmers in the presence of aquatic pollutants was also developed. The attractive features of the new micromachine-based target isolation and signal transduction protocols developed in this project offer numerous potential applications in biomedical diagnostics, environmental monitoring, and forensic analysis.

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Postsynaptic density-95/disks large/zonula occludens-1 (PDZ) domains are relatively small (80-120 residues) protein binding modules central in the organization of receptor clusters and in the association of cellular proteins. Their main function is to bind C-terminals of selected proteins that are recognized through specific amino acids in their carboxyl end. Binding is associated with a deformation of the PDZ native structure and is responsible for dynamical changes in regions not in direct contact with the target. We investigate how this deformation is related to the harmonic dynamics of the PDZ structure and show that one low-frequency collective normal mode, characterized by the concerted movements of different secondary structures, is involved in the binding process. Our results suggest that even minimal structural changes are responsible for communication between distant regions of the protein, in agreement with recent NMR experiments. Thus, PDZ domains are a very clear example of how collective normal modes are able to characterize the relation between function and dynamics of proteins, and to provide indications on the precursors of binding/unbinding events.

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Plants possess an interrelated family of potent fatty acid-derived regulators-the jasmonates. These compounds, which play roles in both defense and development, are derived from tri-unsaturated fatty acids [alpha-linolenic acid (18:3) or 7Z,10Z,13Z-hexadecatrienoic acid (16:3)]. The lipoxygenase-catalyzed addition of molecular oxygen to alpha-linolenic acid initiates jasmonate synthesis by providing a 13-hydroperoxide substrate for the formation of an unstable allene oxide that is then subject to enzyme-guided cyclization to produce 12-oxo-phytodienoic acid (OPDA). OPDA has several fates, including esterification into plastid lipids or transformation into the 12-carbon co-regulator jasmonic acid (JA). JA, the best-characterized member of the family, regulates both male and female fertility (depending on the plant species) and is an important mediator of defense gene expression. JA is itself a substrate for further diverse modifications. Genetic dissection of the pathway is revealing how the different jasmonates modulate different physiological processes. Each new family member that is discovered provides another key to understanding the fine control of gene expression in immune responses, in the initiation and maintenance of long-distance signal transfer in response to wounding, in the regulation of fertility, and in the turnover, inactivation, and sequestration of jasmonates, among other processes. The Jasmonate Biochemical Pathway provides an overview of the growing jasmonate family, and new members will be included in future versions of the Connections Map.

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Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

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Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

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A central feature of drugs of abuse is to induce gene expression in discrete brain structures that are critically involved in behavioral responses related to addictive processes. Although extracellular signal-regulated kinase (ERK) has been implicated in several neurobiological processes, including neuronal plasticity, its role in drug addiction remains poorly understood. This study was designed to analyze the activation of ERK by cocaine, its involvement in cocaine-induced early and long-term behavioral effects, as well as in gene expression. We show, by immunocytochemistry, that acute cocaine administration activates ERK throughout the striatum, rapidly but transiently. This activation was blocked when SCH 23390 [a specific dopamine (DA)-D1 antagonist] but not raclopride (a DA-D2 antagonist) was injected before cocaine. Glutamate receptors of NMDA subtypes also participated in ERK activation, as shown after injection of the NMDA receptor antagonist MK 801. The systemic injection of SL327, a selective inhibitor of the ERK kinase MEK, before cocaine, abolished the cocaine-induced ERK activation and decreased cocaine-induced hyperlocomotion, indicating a role of this pathway in events underlying early behavioral responses. Moreover, the rewarding effects of cocaine were abolished by SL327 in the place-conditioning paradigm. Because SL327 antagonized cocaine-induced c-fos expression and Elk-1 hyperphosphorylation, we suggest that the ERK intracellular signaling cascade is also involved in the prime burst of gene expression underlying long-term behavioral changes induced by cocaine. Altogether, these results reveal a new mechanism to explain behavioral responses of cocaine related to its addictive properties.

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FANCM binds and remodels replication fork structures in vitro. We report that in vivo, FANCM controls DNA chain elongation in an ATPase-dependent manner. In the presence of replication inhibitors that do not damage DNA, FANCM counteracts fork movement, possibly by remodelling fork structures. Conversely, through damaged DNA, FANCM promotes replication and recovers stalled forks. Hence, the impact of FANCM on fork progression depends on the underlying hindrance. We further report that signalling through the checkpoint effector kinase Chk1 prevents FANCM from degradation by the proteasome after exposure to DNA damage. FANCM also acts in a feedback loop to stabilize Chk1. We propose that FANCM is a ringmaster in the response to replication stress by physically altering replication fork structures and by providing a tight link to S-phase checkpoint signalling.

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Peroxiredoxins are known to interact with hydrogen peroxide (H2O2) and to participate in oxidant scavenging, redox signal transduction, and heat-shock responses. The two-cysteine peroxiredoxin Tpx1 of Schizosaccharomyces pombe has been characterized as the H2O2 sensor that transduces the redox signal to the transcription factor Pap1. Here, we show that Tpx1 is essential for aerobic, but not anaerobic, growth. We demonstrate that Tpx1 has an exquisite sensitivity for its substrate, which explains its participation in maintaining low steady-state levels of H2O2. We also show in vitro and in vivo that inactivation of Tpx1 by oxidation of its catalytic cysteine to a sulfinic acid is always preceded by a sulfinic acid form in a covalently linked dimer, which may be important for understanding the kinetics of Tpx1 inactivation. Furthermore, we provide evidence that a strain expressing Tpx1.C169S, lacking the resolving cysteine, can sustain aerobic growth, and we show that small reductants can modulate the activity of the mutant protein in vitro, probably by supplying a thiol group to substitute for cysteine 169.

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MyD88 has a modular organization, an N-terminal death domain (DD) related to the cytoplasmic signaling domains found in many members of the tumor necrosis factor receptor (TNF-R) superfamily, and a C-terminal Toll domain similar to that found in the expanding family of Toll/interleukin-1-like receptors (IL-1R). This dual domain structure, together with the following observations, supports a role for MyD88 as an adapter in IL-1 signal transduction; MyD88 forms homodimers in vivo through DD-DD and Toll-Toll interactions. Overexpression of MyD88 induces activation of the c-Jun N-terminal kinase (JNK) and the transcription factor NF-kappaB through its DD. A point mutation in MyD88, MyD88-lpr (F56N), which prevents dimerization of the DD, also blocks induction of these activities. MyD88-induced NF-kappaB activation is inhibited by the dominant negative versions of TRAF6 and IRAK, which also inhibit IL-1-induced NF-kappaB activation. Overexpression of MyD88-lpr or MyD88-Toll (expressing only the Toll domain) acted to inhibit IL-1-induced NF-kappaB and JNK activation in a 293 cell line overexpressing the IL-1RI. MyD88 coimmunoprecipitates with the IL-1R signaling complex in an IL-1-dependent manner.

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Previous microarray studies on breast cancer identified multiple tumour classes, of which the most prominent, named luminal and basal, differ in expression of the oestrogen receptor alpha gene (ER). We report here the identification of a group of breast tumours with increased androgen signalling and a 'molecular apocrine' gene expression profile. Tumour samples from 49 patients with large operable or locally advanced breast cancers were tested on Affymetrix U133A gene expression microarrays. Principal components analysis and hierarchical clustering split the tumours into three groups: basal, luminal and a group we call molecular apocrine. All of the molecular apocrine tumours have strong apocrine features on histological examination (P=0.0002). The molecular apocrine group is androgen receptor (AR) positive and contains all of the ER-negative tumours outside the basal group. Kolmogorov-Smirnov testing indicates that oestrogen signalling is most active in the luminal group, and androgen signalling is most active in the molecular apocrine group. ERBB2 amplification is commoner in the molecular apocrine than the other groups. Genes that best split the three groups were identified by Wilcoxon test. Correlation of the average expression profile of these genes in our data with the expression profile of individual tumours in four published breast cancer studies suggest that molecular apocrine tumours represent 8-14% of tumours in these studies. Our data show that it is possible with microarray data to divide mammary tumour cells into three groups based on steroid receptor activity: luminal (ER+ AR+), basal (ER- AR-) and molecular apocrine (ER- AR+).

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Expressions relating spectral efficiency, power, and Doppler spectrum, are derived for Rayleigh-faded wireless channels with Gaussian signal transmission. No side information on the state of the channel is assumed at the receiver. Rather, periodic reference signals are postulated in accordance with the functioning of most wireless systems. The analysis relies on a well-established lower bound, generally tight and asymptotically exact at low SNR. In contrast with most previous studies, which relied on block-fading channel models, a continuous-fading model is adopted. This embeds the Doppler spectrum directly in the derived expressions, imbuing them with practical significance. Closed-form relationships are obtained for the popular Clarke-Jakes spectrum and informative expansions, valid for arbitrary spectra, are found for the low- and high-power regimes. While the paper focuses on scalar channels, the extension to multiantenna settings is also discussed.

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This paper formulates power allocation policies that maximize the region of mutual informationsachievable in multiuser downlink OFDM channels. Arbitrary partitioning ofthe available tones among users and arbitrary modulation formats, possibly different forevery user, are considered. Two distinct policies are derived, respectively for slow fadingchannels tracked instantaneously by the transmitter and for fast fading channels knownonly statistically thereby. With instantaneous channel tracking, the solution adopts theform of a multiuser mercury/waterfilling procedure that generalizes the single-user mercury/waterfilling introduced in [1, 2]. With only statistical channel information, in contrast,the mercury/waterfilling interpretation is lost. For both policies, a number of limitingregimes are explored and illustrative examples are provided.