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Find video protocols related to scientific articles indexed in Pubmed.
Genome Sequence of Corynebacterium pseudotuberculosis MB20 bv. equi Isolated from a Pectoral Abscess of an Oldenburg Horse in California.
Genome Announc
PUBLISHED: 11-15-2014
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The genome of Corynebacterium pseudotuberculosis MB20 bv. equi was sequenced using the Ion Personal Genome Machine (PGM) platform, and showed a size of 2,363,089 bp, with 2,365 coding sequences and a GC content of 52.1%. These results will serve as a basis for further studies on the pathogenicity of C. pseudotuberculosis bv. equi.
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C. pseudotuberculosis Phop confers virulence and may be targeted by natural compounds.
Integr Biol (Camb)
PUBLISHED: 09-13-2014
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The bacterial two-component system (TCS) regulates genes that are crucial for virulence in several pathogens. One of such TCS, the PhoPR system, consisting of a transmembrane sensory histidine kinase protein (PhoR) and an intracellular response regulator protein (PhoP), has been reported to have a major role in mycobacterial pathogenesis. We knocked out the phoP in C. pseudotuberculosis, the causal organism of caseous lymphadenitis (CLA), and using a combination of in vitro and in vivo mouse system, we showed for the first time, that the PhoP of C. pseudotuberculosis plays an important role in the virulence and pathogenicity of this bacterium. Furthermore, we modeled the PhoP of C. pseudotuberculosis and our docking results showed that several natural compounds including Rhein, an anthraquinone from Rheum undulatum, and some drug-like molecules may target PhoP to inhibit the TCS of C. pseudotuberculosis, and therefore may facilitate a remarkable attenuation of bacterial pathogenicity being the CLA. Experiments are currently underway to validate these in silico docking results.
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An improved interolog mapping-based computational prediction of protein-protein interactions with increased network coverage.
Integr Biol (Camb)
PUBLISHED: 09-12-2014
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Automated and efficient methods that map ortholog interactions from several organisms and public databases (pDB) are needed to identify new interactions in an organism of interest (interolog mapping). When computational methods are applied to predict interactions, it is important that these methods be validated and their efficiency proven. In this study, we compare six Blast+ metrics over three datasets to identify the best metric for protein-protein interaction predictions. Using Blast+ to align the protein pairs, the ortholog interactions from DIP were mapped to String, Intact and Psibase pDBs. For each interaction mapped to each pDBs, we retrieved the alignment score, e-value, bitscore, similarity, identity and coverage. We evaluated these Blast+ values, and combinations thereof, with the Receiver Operating Characteristic (ROC) curves and computed the Area Under Curve (AUC). To validate these predictions, we used a subset of the Database of Interacting Proteins (DIP) composed of experimental interactions curated by the International Molecular Exchange (IMEx). The cut-off point for each metric/pDB was computed aiming to identify the best one that separates the true and false predicted interactions. In contrast to other methods that only compute the first Blast hit, we considered the first 20 hits, thus increasing the number of predicted interaction pairs. In addition, we identified the contribution of each individual pDB, as well as their combined contribution to the prediction. The best metric had an AUC of 0.96 for a single pDB and AUC of 0.93 for combined pDBs. Compared to other studies, with a cut-off point of 0.70 representing a specificity of 0.95 and a sensitivity of 0.90 for individual pDB, our method efficiently predicts protein-protein interactions.
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Segtor: rapid annotation of genomic coordinates and single nucleotide variations using segment trees.
PLoS ONE
PUBLISHED: 04-15-2011
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Various research projects often involve determining the relative position of genomic coordinates, intervals, single nucleotide variations (SNVs), insertions, deletions and translocations with respect to genes and their potential impact on protein translation. Due to the tremendous increase in throughput brought by the use of next-generation sequencing, investigators are routinely faced with the need to annotate very large datasets. We present Segtor, a tool to annotate large sets of genomic coordinates, intervals, SNVs, indels and translocations. Our tool uses segment trees built using the start and end coordinates of the genomic features the user wishes to use instead of storing them in a database management system. The software also produces annotation statistics to allow users to visualize how many coordinates were found within various portions of genes. Our system currently can be made to work with any species available on the UCSC Genome Browser. Segtor is a suitable tool for groups, especially those with limited access to programmers or with interest to analyze large amounts of individual genomes, who wish to determine the relative position of very large sets of mapped reads and subsequently annotate observed mutations between the reads and the reference. Segtor (http://lbbc.inca.gov.br/segtor/) is an open-source tool that can be freely downloaded for non-profit use. We also provide a web interface for testing purposes.
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Computational prediction of protein-protein interactions in Leishmania predicted proteomes.
PLoS ONE
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The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI) study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping) and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks received some degree of functional annotation which represents an important contribution since approximately 60% of Leishmania predicted proteomes has no predicted function.
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Molecular characterization of the hexose transporter gene in benznidazole resistant and susceptible populations of Trypanosoma cruzi.
Parasit Vectors
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Hexose transporters (HT) are membrane proteins involved in the uptake of energy-supplying glucose and other hexoses into the cell. Previous studies employing the Differential Display technique have shown that the transcription level of the HT gene from T. cruzi (TcrHT) is higher in an in vitro-induced benznidazole (BZ)-resistant population of the parasite (17 LER) than in its susceptible counterpart (17 WTS).
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SpliceProt: a protein sequence repository of predicted human splice variants.
Proteomics
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The mechanism of alternative splicing in the transcriptome may increase the proteome diversity in eukaryotes. In proteomics, several studies aim to use protein sequence repositories to annotate mass spectrometry experiments or to detect differentially expressed proteins. However, the available protein sequence repositories are not designed to fully detect protein isoforms derived from mRNA splice variants. To foster knowledge for the field, here we introduce SpliceProt, a new protein sequence repository of transcriptome experimental data used to investigate for putative splice variants to investigate for putative splice variants in human proteomes. Current version of SpliceProt contains 159,719 non-redundant putative polypeptide sequences. The assessment of the potential of SpliceProt in detecting new protein isoforms resulting from alternative splicing was performed by using publicly available proteomics data. We detected 173 peptides hypothetically derived from splice variants, which 54 of them are not present in UniprotKB/TrEMBL sequence repository. In comparison to other protein sequence repositories, SpliceProt contains a greater number of unique peptides and is able to detect more splice variants. Therefore, SpliceProt provides a solution for the annotation of proteomics experiments regarding splice isofoms. The repository files containing the translated sequences of the predicted splice variants and a visualization tool are freely available at http://lbbc.inca.gov.br/spliceprot. This article is protected by copyright. All rights reserved.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.