953 resultados para Sequence Trap Method
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The signal sequence trap technique was applied to identify genes coding for secreted and membrane bound proteins from Echinococcus granulosus, the etiologic agent of cystic hydatid disease. An E. granulosus protoscolex cDNA library was constructed in the AP-PST vector such that randomly primed cDNAs were fused with a placental alkaline phosphatase reporter gene lacking its endogenous signal peptide. E. granulosus cDNAs encoding a functional signal peptide were selected by their ability to rescue secretion of alkaline phosphatase by COS-7 cells that had been transfected with the cDNA library. Eighteen positive clones were identified and sequenced. Their deduced amino acid sequences showed significant similarity with amino acid transporters, Krebs cycle intermediates transporters, presenilins and vacuolar protein sorter proteins. Other cDNAs encoded secreted proteins without homologues. Three sequences were transcribed antisense to E. granulosus expressed sequence tags. All the mRNAs were expressed in protoscoleces and adult worms, but some of them were not found in oncospheres. The putative E. granulosus secreted and membrane bound proteins identified are likely to play important roles in the metabolism, development and survival in the host and represent potential targets for diagnosis, drugs and vaccines against E. granulosus. (c) 2005 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.
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Proteins secreted by and anchored on the surfaces of parasites are in intimate contact with host tissues. The transcriptome of infective cercariae of the blood fluke, Schistosoma mansoni, was screened using signal sequence trap to isolate cDNAs encoding predicted proteins with an N-terminal signal peptide. Twenty cDNA fragments were identified, most of which contained predicted signal peptides or transmembrane regions, including a novel putative seven-transmembrane receptor and a membrane-associated mitogen-activated protein kinase. The developmental expression pattern within different life-cycle stages ranged from ubiquitous to a transcript that was highly upregulated in the cercaria. A bioinformatics-based comparison of 100 signal peptides from each of schistosomes, humans, a parasitic nematode and Escherichia coli showed that differences in the sequence composition of signal peptides, notably the residues flanking the predicted cleavage site, might account for the negative bias exhibited in the processing of schistosome signal peptides in mammalian cells. (c) 2005 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.
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Dissertação de Mestrado, Qualidade em Análises, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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Bioinformatics, in the last few decades, has played a fundamental role to give sense to the huge amount of data produced. Obtained the complete sequence of a genome, the major problem of knowing as much as possible of its coding regions, is crucial. Protein sequence annotation is challenging and, due to the size of the problem, only computational approaches can provide a feasible solution. As it has been recently pointed out by the Critical Assessment of Function Annotations (CAFA), most accurate methods are those based on the transfer-by-homology approach and the most incisive contribution is given by cross-genome comparisons. In the present thesis it is described a non-hierarchical sequence clustering method for protein automatic large-scale annotation, called “The Bologna Annotation Resource Plus” (BAR+). The method is based on an all-against-all alignment of more than 13 millions protein sequences characterized by a very stringent metric. BAR+ can safely transfer functional features (Gene Ontology and Pfam terms) inside clusters by means of a statistical validation, even in the case of multi-domain proteins. Within BAR+ clusters it is also possible to transfer the three dimensional structure (when a template is available). This is possible by the way of cluster-specific HMM profiles that can be used to calculate reliable template-to-target alignments even in the case of distantly related proteins (sequence identity < 30%). Other BAR+ based applications have been developed during my doctorate including the prediction of Magnesium binding sites in human proteins, the ABC transporters superfamily classification and the functional prediction (GO terms) of the CAFA targets. Remarkably, in the CAFA assessment, BAR+ placed among the ten most accurate methods. At present, as a web server for the functional and structural protein sequence annotation, BAR+ is freely available at http://bar.biocomp.unibo.it/bar2.0.
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An isolated wind power generation scheme using slip ring induction machine (SRIM) is proposed. The proposed scheme maintains constant load voltage and frequency irrespective of the wind speed or load variation. The power circuit consists of two back-to-back connected inverters with a common dc link, where one inverter is directly connected to the rotor side of SRIM and the other inverter is connected to the stator side of the SRIM through LC filter. Developing a negative sequence compensation method to ensure that, even under the presence of unbalanced load, the generator experiences almost balanced three-phase current and most of the unbalanced current is directed through the stator side converter is the focus here. The SRIM controller varies the speed of the generator with variation in the wind speed to extract maximum power. The difference of the generated power and the load power is either stored in or extracted from a battery bank, which is interfaced to the common dc link through a multiphase bidirectional fly-back dc-dc converter. The SRIM control scheme, maximum power point extraction algorithm and the fly-back converter topology are incorporated from available literature. The proposed scheme is both simulated and experimentally verified.
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This article presents a new method for acquiring three-dimensional (3-D) volumes of ultrasonic axial strain data. The method uses a mechanically-swept probe to sweep out a single volume while applying a continuously varying axial compression. Acquisition of a volume takes 15-20 s. A strain volume is then calculated by comparing frame pairs throughout the sequence. The method uses strain quality estimates to automatically pick out high quality frame pairs, and so does not require careful control of the axial compression. In a series of in vitro and in vivo experiments, we quantify the image quality of the new method and also assess its ease of use. Results are compared with those for the current best alternative, which calculates strain between two complete volumes. The volume pair approach can produce high quality data, but skillful scanning is required to acquire two volumes with appropriate relative strain. In the new method, the automatic quality-weighted selection of image pairs overcomes this difficulty and the method produces superior quality images with a relatively relaxed scanning technique.
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Karwath, A. King, R. Homology induction: the use of machine learning to improve sequence similarity searches. BMC Bioinformatics. 23rd April 2002. 3:11 Additional File Describes the title organims species declaration in one string [http://www.biomedcentral.com/content/supplementary/1471- 2105-3-11-S1.doc] Sponsorship: Andreas Karwath and Ross D. King were supported by the EPSRC grant GR/L62849.
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Despite the development of novel typing methods based on whole genome sequencing, most laboratories still rely on classical molecular methods for outbreak investigation or surveillance. Reference methods for Clostridium difficile include ribotyping and pulsed-field gel electrophoresis, which are band-comparing methods often difficult to establish and which require reference strain collections. Here, we present the double locus sequence typing (DLST) scheme as a tool to analyse C. difficile isolates. Using a collection of clinical C. difficile isolates recovered during a 1-year period, we evaluated the performance of DLST and compared the results to multilocus sequence typing (MLST), a sequence-based method that has been used to study the structure of bacterial populations and highlight major clones. DLST had a higher discriminatory power compared to MLST (Simpson's index of diversity of 0.979 versus 0.965) and successfully identified all isolates of the study (100 % typeability). Previous studies showed that the discriminatory power of ribotyping was comparable to that of MLST; thus, DLST might be more discriminatory than ribotyping. DLST is easy to establish and provides several advantages, including absence of DNA extraction [polymerase chain reaction (PCR) is performed on colonies], no specific instrumentation, low cost and unambiguous definition of types. Moreover, the implementation of a DLST typing scheme on an Internet database, such as that previously done for Staphylococcus aureus and Pseudomonas aeruginosa ( http://www.dlst.org ), will allow users to easily obtain the DLST type by submitting directly sequencing files and will avoid problems associated with multiple databases.
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Although it is generally accepted that osteoclasts breakdown and resorb bone matrix, the possibility that they may also be able to engulf apoptotic osteoblasts/ lining cells and/or osteocytes remains controversial. Apoptosis of osteoblasts/ lining cells and/or osteocytes and interactions between these cells and osteoclasts are extremely rapid events that are difficult to observe in viva. A suitable in viva model for studying these events is the alveolar bone of young rats because it is continuously. Thus, sections of aldehyde fixed alveolar undergoing intense resorption/remodeling bone of young rats were stained by the combined terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) method and the tartrate-resistant acid phosphatase (TRAP) method for the simultaneous visualization of apoptotic cells and osteoclasts in the same section. The combined TUNEL and TRAP reactions, in the same section, greatly facilitated visualization of relationship between osteoclasts and apoptotic bone cells during alveolar bone remodeling. Our results showed that several TRAP-positive osteoclasts exhibited large vacuoles containing TUNEL positive apoptotic structures, probably derived from osteoblasts/lining cells and/or osteocytes. These results support the idea that alveolar bone osteoclasts are able to internalize dying apoptotic bone cells.
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Motivation: Conformational flexibility is essential to the function of many proteins, e.g. catalytic activity. To assist efforts in determining and exploring the functional properties of a protein, it is desirable to automatically identify regions that are prone to undergo conformational changes. It was recently shown that a probabilistic predictor of continuum secondary structure is more accurate than categorical predictors for structurally ambivalent sequence regions, suggesting that such models are suited to characterize protein flexibility. Results: We develop a computational method for identifying regions that are prone to conformational change directly from the amino acid sequence. The method uses the entropy of the probabilistic output of an 8-class continuum secondary structure predictor. Results for 171 unique amino acid sequences with well-characterized variable structure (identified in the 'Macromolecular movements database') indicate that the method is highly sensitive at identifying flexible protein regions, but false positives remain a problem. The method can be used to explore conformational flexibility of proteins (including hypothetical or synthetic ones) whose structure is yet to be determined experimentally.
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The twin arginine translocation (TAT) system ferries folded proteins across the bacterial membrane. Proteins are directed into this system by the TAT signal peptide present at the amino terminus of the precursor protein, which contains the twin arginine residues that give the system its name. There are currently only two computational methods for the prediction of TAT translocated proteins from sequence. Both methods have limitations that make the creation of a new algorithm for TAT-translocated protein prediction desirable. We have developed TATPred, a new sequence-model method, based on a Nave-Bayesian network, for the prediction of TAT signal peptides. In this approach, a comprehensive range of models was tested to identify the most reliable and robust predictor. The best model comprised 12 residues: three residues prior to the twin arginines and the seven residues that follow them. We found a prediction sensitivity of 0.979 and a specificity of 0.942.
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We present a method to guess the realization of an arbitrarily varying source. Let TU be the type of the unknown state sequence. Our method results in a guessing moment that is within Kn (TU) + O(log n=n) of the minimum attainable guessing moment with full knowledge of source statistics, i.e., with knowledge of the sequence of states sn. The quantity Kn (TU) + O(log n=n) can be interpreted as the penalty one pays for not knowing the sequence of states sn of the source. Kn (TU) by itself is the penalty one pays for guessing with the additional knowledge that the state sequence belongs to type TU. Conversely, given any guessing strategy, for every type TU, there is a state sequence belonging to this type whose corresponding source forces a guessing moment penalty of at least Kn (TU) ¡ O(log n=n).
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Human listeners seem to be remarkably able to recognise acoustic sound sources based on timbre cues. Here we describe a psychophysical paradigm to estimate the time it takes to recognise a set of complex sounds differing only in timbre cues: both in terms of the minimum duration of the sounds and the inferred neural processing time. Listeners had to respond to the human voice while ignoring a set of distractors. All sounds were recorded from natural sources over the same pitch range and equalised to the same duration and power. In a first experiment, stimuli were gated in time with a raised-cosine window of variable duration and random onset time. A voice/non-voice (yes/no) task was used. Performance, as measured by d', remained above chance for the shortest sounds tested (2 ms); d's above 1 were observed for durations longer than or equal to 8 ms. Then, we constructed sequences of short sounds presented in rapid succession. Listeners were asked to report the presence of a single voice token that could occur at a random position within the sequence. This method is analogous to the "rapid sequential visual presentation" paradigm (RSVP), which has been used to evaluate neural processing time for images. For 500-ms sequences made of 32-ms and 16-ms sounds, d' remained above chance for presentation rates of up to 30 sounds per second. There was no effect of the pitch relation between successive sounds: identical for all sounds in the sequence or random for each sound. This implies that the task was not determined by streaming or forward masking, as both phenomena would predict better performance for the random pitch condition. Overall, the recognition of familiar sound categories such as the voice seems to be surprisingly fast, both in terms of the acoustic duration required and of the underlying neural time constants.
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Photoionization cross section calculations on the halogen-like ions; Kr + and Xe + have been performed for a photon energy range from each ion threshold to 15 eV, using large-scale close-coupling calculations within the Dirac--Coulomb R -matrix approximation. The results from our theoretical work are compared with recent measurements made at the ASTRID merged-beam set-up at the University of Aarhus in Denmark and from the Fourier transform ion cyclotron resonance trap method at the SOLEIL synchrotron radiation facility in Saint-Aubin, France Bizau et al (2011 J. Phys. B: At. Mol. Opt. Phys. 44 055205) and the advanced light source M{ü}ller (2012 private communication), Aguliar et al (2012 J. Phys.: Conf. Ser . at press). For each of these complex ions our theoretical cross section results over the photon energy range investigated are seen to be in excellent agreement with experiment. Resonance energy positions and quantum defects of the prominent Rydberg resonances series identified in the spectra are compared with experiment for these complex halogen-like ions.