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Find video protocols related to scientific articles indexed in Pubmed.
Genome sequence of the model sulfate reducer Desulfovibrio gigas: a comparative analysis within the Desulfovibrio genus.
Microbiologyopen
PUBLISHED: 03-20-2014
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Desulfovibrio gigas is a model organism of sulfate-reducing bacteria of which energy metabolism and stress response have been extensively studied. The complete genomic context of this organism was however, not yet available. The sequencing of the D. gigas genome provides insights into the integrated network of energy conserving complexes and structures present in this bacterium. Comparison with genomes of other Desulfovibrio spp. reveals the presence of two different CRISPR/Cas systems in D. gigas. Phylogenetic analysis using conserved protein sequences (encoded by rpoB and gyrB) indicates two main groups of Desulfovibrio spp, being D. gigas more closely related to D. vulgaris and D. desulfuricans strains. Gene duplications were found such as those encoding fumarate reductase, formate dehydrogenase, and superoxide dismutase. Complexes not yet described within Desulfovibrio genus were identified: Mnh complex, a v-type ATP-synthase as well as genes encoding the MinCDE system that could be responsible for the larger size of D. gigas when compared to other members of the genus. A low number of hydrogenases and the absence of the codh/acs and pfl genes, both present in D. vulgaris strains, indicate that intermediate cycling mechanisms may contribute substantially less to the energy gain in D. gigas compared to other Desulfovibrio spp. This might be compensated by the presence of other unique genomic arrangements of complexes such as the Rnf and the Hdr/Flox, or by the presence of NAD(P)H related complexes, like the Nuo, NfnAB or Mnh.
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Shotgun proteomics to unravel the complexity of the Leishmania infantum exoproteome and the relative abundance of its constituents.
Mol. Biochem. Parasitol.
PUBLISHED: 01-27-2014
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The exoproteome of some Leishmania species has revealed important insights into host-parasite interaction, paving the way for the proposal of novel disease-oriented interventions. The focus of the present investigation constituted the molecular profile of the L. infantum exoproteome revealed by a shotgun proteomic approach. Promastigotes under logarithmic phase of growth were obtained and harvested by centrifugation at different time points. Cell integrity was evaluated through the counting of viable parasites using propidium iodide labeling, followed by flow cytometry analysis. The 6h culture supernatant, operationally defined here as exoproteome, was then conditioned to in solution digestion and the resulting peptides submitted to mass spectrometry. A total of 102 proteins were identified and categorized according to their cellular function. Their relative abundance index (emPAI) allowed inference that the L. infantum exoproteome is a complex mixture dominated by molecules particularly involved in nucleotide metabolism and antioxidant activity. Bioinformatic analyses support that approximately 60% of the identified proteins are secreted, of which, 85% possibly reach the extracellular milieu by means of non-classic pathways. At last, sera from naturally infected animals, carriers of differing clinical forms of Canine Visceral Leishmaniasis (CVL), were used to test the immunogenicity associated to the L. infantum exoproteome. Western blotting experiments revealed that this sub-proteome was useful at discriminating symptomatic animals from those exhibiting other clinical forms of the disease. Collectively, the molecular characterization of the L. infantum exoproteome and the preliminary immunoproteomic assays opened up new research avenues related to treatment, prognosis and diagnosis of CVL.
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Molecular diagnosis of canine visceral leishmaniasis: a comparative study of three methods using skin and spleen from dogs with natural Leishmania infantum infection.
Vet. Parasitol.
PUBLISHED: 03-23-2013
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Polymerase chain reaction (PCR) and its variations represent highly sensitive and specific methods for Leishmania DNA detection and subsequent canine visceral leishmaniasis (CVL) diagnosis. The aim of this work was to compare three different molecular diagnosis techniques (conventional PCR [cPCR], seminested PCR [snPCR], and quantitative PCR [qPCR]) in samples of skin and spleen from 60 seropositive dogs by immunofluorescence antibody test and enzyme-linked immunosorbent assay. Parasitological analysis was conducted by culture of bone marrow aspirate and optical microscopic assessment of ear skin and spleen samples stained with Giemsa, the standard tests for CVL diagnosis. The primers L150/L152 and LINR4/LIN17/LIN19 were used to amplify the conserved region of the Leishmania kDNA minicircle in the cPCR, and snPCR and qPCR were performed using the DNA polymerase gene (DNA pol ?) primers from Leishmania infantum. The parasitological analysis revealed parasites in 61.7% of the samples. Sensitivities were 89.2%, 86.5%, and 97.3% in the skin and 81.1%, 94.6%, and 100.0% in spleen samples used for cPCR, snPCR, and qPCR, respectively. We demonstrated that the qPCR method was the best technique to detect L. infantum in both skin and spleen samples. However, we recommend the use of skin due to the high sensitivity and sampling being less invasive.
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Evidence for reductive genome evolution and lateral acquisition of virulence functions in two Corynebacterium pseudotuberculosis strains.
PLoS ONE
PUBLISHED: 03-11-2011
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Corynebacterium pseudotuberculosis, a gram-positive, facultative intracellular pathogen, is the etiologic agent of the disease known as caseous lymphadenitis (CL). CL mainly affects small ruminants, such as goats and sheep; it also causes infections in humans, though rarely. This species is distributed worldwide, but it has the most serious economic impact in Oceania, Africa and South America. Although C. pseudotuberculosis causes major health and productivity problems for livestock, little is known about the molecular basis of its pathogenicity.
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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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An assessment on epitope prediction methods for protozoa genomes.
BMC Bioinformatics
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Epitope prediction using computational methods represents one of the most promising approaches to vaccine development. Reduction of time, cost, and the availability of completely sequenced genomes are key points and highly motivating regarding the use of reverse vaccinology. Parasites of genus Leishmania are widely spread and they are the etiologic agents of leishmaniasis. Currently, there is no efficient vaccine against this pathogen and the drug treatment is highly toxic. The lack of sufficiently large datasets of experimentally validated parasites epitopes represents a serious limitation, especially for trypanomatids genomes. In this work we highlight the predictive performances of several algorithms that were evaluated through the development of a MySQL database built with the purpose of: a) evaluating individual algorithms prediction performances and their combination for CD8+ T cell epitopes, B-cell epitopes and subcellular localization by means of AUC (Area Under Curve) performance and a threshold dependent method that employs a confusion matrix; b) integrating data from experimentally validated and in silico predicted epitopes; and c) integrating the subcellular localization predictions and experimental data. NetCTL, NetMHC, BepiPred, BCPred12, and AAP12 algorithms were used for in silico epitope prediction and WoLF PSORT, Sigcleave and TargetP for in silico subcellular localization prediction against trypanosomatid genomes.
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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.