The specific fibrinolytic properties of both high molecular weight (55 kd) and low molecular weight (30 kd) pro-urokinase from a monkey kidney cell culture were evaluated in a plasma clot lysis system and compared with those of human urokinase. The system was composed of a radiolabelled plasma clot immersed in plasma containing the fibrinolytic agent. On unit base, 55 kd pro-urokinase was approximately 1.5 times more effective in lysing the clot than 30 kd pro-urokinase and equally effective as urokinase. In contrast to urokinase, both pro-urokinase forms induced clot lysis without degrading fibrinogen in the surrounding plasma. However, a considerable activation of the fibrinolytic system in the plasma occurred as a large amount of alpha 2-antiplasmin was consumed, indicating that pro-urokinase was not fully fibrin-specific. Quenching antibodies against tissue-type plasminogen activator (t-PA) added to the plasma clot lysis system retarded but did not prevent pro-urokinase-induced clot lysis. This indicated that not only was t-PA in plasma involved in the activation of pro-urokinase (probably via plasmin), but that an additional mechanism also existed.
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Plasma urokinase, a plasminogen activator immunochemically related to urinary urokinase (UK), was removed from human plasma (3.5 ng/ml) by immuno-depletion with antibodies raised against UK. The remaining plasminogen activator activity of the depleted plasma could not be inhibited by anti-UK antibodies and a sensitive ELISA for UK did not detect any UK levels that were higher than the background of the assay (0.1 ng/ml). However, when the depleted plasma was subjected to SDS-PAGE, substantial amounts of protein were found hereafter around 110 and 46 kD which now gave a positive reaction in the ELISA (35-350 ng/ml plasma). From these observations it is concluded that in human plasma two types of UK-related protein occur: Type I, among which the plasma urokinase, has antigenic determinants which are directly accessible to the anti-UK antibodies, Type II has determinants in a latent form. The function of the 110 kD type-II protein is that of a plasminogen activator; that of the 46 kD protein is not yet clear.
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In this article, we present CoPub 5.0, a publicly available text mining system, which uses Medline abstracts to calculate robust statistics for keyword co-occurrences. CoPub was initially developed for the analysis of microarray data, but we broadened the scope by implementing new technology and new thesauri. In CoPub 5.0, we integrated existing CoPub technology with new features, and provided a new advanced interface, which can be used to answer a variety of biological questions. CoPub 5.0 allows searching for keywords of interest and its relations to curated thesauri and provides highlighting and sorting mechanisms, using its statistics, to retrieve the most important abstracts in which the terms co-occur. It also provides a way to search for indirect relations between genes, drugs, pathways and diseases, following an ABC principle, in which A and C have no direct connection but are connected via shared B intermediates. With CoPub 5.0, it is possible to create, annotate and analyze networks using the layout and highlight options of Cytoscape web, allowing for literature based systems biology. Finally, operations of the CoPub 5.0 Web service enable to implement the CoPub technology in bioinformatics workflows. CoPub 5.0 can be accessed through the CoPub portal http://www.copub.org. © 2011 The Author(s).
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Background: Glucocorticoids are potent anti-inflammatory agents used for the treatment of diseases such as rheumatoid arthritis, asthma, inflammatory bowel disease and psoriasis. Unfortunately, usage is limited because of metabolic side-effects, e.g. insulin resistance, glucose intolerance and diabetes. To gain more insight into the mechanisms behind glucocorticoid induced insulin resistance, it is important to understand which genes play a role in the development of insulin resistance and which genes are affected by glucocorticoids. Medline abstracts contain many studies about insulin resistance and the molecular effects of glucocorticoids and thus are a good resource to study these effects. Results: We developed CoPubGene a method to automatically identify gene-disease associations in Medline abstracts. We used this method to create a literature network of genes related to insulin resistance and to evaluate the importance of the genes in this network for glucocorticoid induced metabolic side effects and anti-inflammatory processes. With this approach we found several genes that already are considered markers of GC induced IR, such as phosphoenolpyruvate carboxykinase (PCK) and glucose-6-phosphatase, catalytic subunit (G6PC). In addition, we found genes involved in steroid synthesis that have not yet been recognized as mediators of GC induced IR. Conclusions: With this approach we are able to construct a robust informative literature network of insulin resistance related genes that gave new insights to better understand the mechanisms behind GC induced IR. The method has been set up in a generic way so it can be applied to a wide variety of disease networks. © 2013 Fleuren et al.; licensee BioMed Central Ltd.
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This article describes a relatively straightforward procedure to knock out the gene that encodes the invertase enzyme in baker’s yeast. The SUC2 gene, which encodes for the invertase enzyme, is knocked out by a single-step PCR knock out method. The knockout is subsequently confirmed at the genetic level by PCR and agarose gel electrophoresis. The knockout is confirmed at the biochemical level by measuring the activity of the invertase enzyme using a colorimetric assay. This tips and tools article describes an easily scalable, inexpensive, yet challenging research project helping undergraduate students at the Bachelor level to conceptualize the effect of the deletion of a gene encoding an enzyme.
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BACKGROUND: In many genomics projects, numerous lists containing biological identifiers are produced. Often it is useful to see the overlap between different lists, enabling researchers to quickly observe similarities and differences between the data sets they are analyzing. One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram: a diagram consisting of two or more circles in which each circle corresponds to a data set, and the overlap between the circles corresponds to the overlap between the data sets. Venn diagrams are especially useful when they are 'area-proportional' i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. Currently there are no programs available that can create area-proportional Venn diagrams connected to a wide range of biological databases.RESULTS: We designed a web application named BioVenn to summarize the overlap between two or three lists of identifiers, using area-proportional Venn diagrams. The user only needs to input these lists of identifiers in the textboxes and push the submit button. Parameters like colors and text size can be adjusted easily through the web interface. The position of the text can be adjusted by 'drag-and-drop' principle. The output Venn diagram can be shown as an SVG or PNG image embedded in the web application, or as a standalone SVG or PNG image. The latter option is useful for batch queries. Besides the Venn diagram, BioVenn outputs lists of identifiers for each of the resulting subsets. If an identifier is recognized as belonging to one of the supported biological databases, the output is linked to that database. Finally, BioVenn can map Affymetrix and EntrezGene identifiers to Ensembl genes.CONCLUSION: BioVenn is an easy-to-use web application to generate area-proportional Venn diagrams from lists of biological identifiers. It supports a wide range of identifiers from the most used biological databases currently available. Its implementation on the World Wide Web makes it available for use on any computer with internet connection, independent of operating system and without the need to install programs locally. BioVenn is freely accessible at http://www.cmbi.ru.nl/cdd/biovenn/.
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BACKGROUND: T lymphocytes are orchestrators of adaptive immunity. Naïve T cells may differentiate into Th1, Th2, Th17 or iTreg phenotypes, depending on environmental co-stimulatory signals. To identify genes and pathways involved in differentiation of Jurkat T cells towards Th1 and Th2 subtypes we performed comprehensive transcriptome analyses of Jurkat T cells stimulated with various stimuli and pathway inhibitors. Results from these experiments were validated in a human experimental setting using whole blood and purified CD4+ Tcells.RESULTS: Calcium-dependent activation of T cells using CD3/CD28 and PMA/CD3 stimulation induced a Th1 expression profile reflected by increased expression of T-bet, RUNX3, IL-2, and IFNγ, whereas calcium-independent activation via PMA/CD28 induced a Th2 expression profile which included GATA3, RXRA, CCL1 and Itk. Knock down with siRNA and gene expression profiling in the presence of selective kinase inhibitors showed that proximal kinases Lck and PKCθ are crucial signaling hubs during T helper cell activation, revealing a clear role for Lck in Th1 development and for PKCθ in both Th1 and Th2 development. Medial signaling via MAPkinases appeared to be less important in these pathways, since specific inhibitors of these kinases displayed a minor effect on gene expression. Translation towards a primary, whole blood setting and purified human CD4+ T cells revealed that PMA/CD3 stimulation induced a more pronounced Th1 specific, Lck and PKCθ dependent IFNγ production, whereas PMA/CD28 induced Th2 specific IL-5 and IL-13 production, independent of Lck activation. PMA/CD3-mediated skewing towards a Th1 phenotype was also reflected in mRNA expression of the master transcription factor Tbet, whereas PMA/CD28-mediated stimulation enhanced GATA3 mRNA expression in primary human CD4+ Tcells.CONCLUSIONS: This study identifies stimulatory pathways and gene expression profiles for in vitro skewing of T helper cell activation. PMA/CD3 stimulation enhances a Th1-like response in an Lck and PKCθ dependent fashion, whereas PMA/CD28 stimulation results in a Th2-like phenotype independent of the proximal TCR-tyrosine kinase Lck. This approach offers a robust and fast translational in vitro system for skewed T helper cell responses in Jurkat T cells, primary human CD4+ Tcells and in a more complex matrix such as human whole blood.
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BACKGROUND: Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinformatics by making its use and extension more simple through more and better application of high-level languages commonly used in bioinformatics, such as Python.RESULTS: The novel application pyPaSWAS presents the parallel SW sequence alignment code fully packed in Python. It is a generic SW implementation running on several hardware platforms with multi-core systems and/or GPUs that provides accurate sequence alignments that also can be inspected for alignment details. Additionally, pyPaSWAS support the affine gap penalty. Python libraries are used for automated system configuration, I/O and logging. This way, the Python environment will stimulate further extension and use of pyPaSWAS.CONCLUSIONS: pyPaSWAS presents an easy Python-based environment for accurate and retrievable parallel SW sequence alignments on GPUs and multi-core systems. The strategy of integrating Python with high-performance parallel compute languages to create a developer- and user-friendly environment should be considered for other computationally intensive bioinformatics algorithms.
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Using an optimized transformation protocol we have studied the possible interactions between transforming plasmid DNA and the Hansenula polymorpha genome. Plasmids consisting only of a pBR322 replicon, an antibiotic resistance marker for Escherichia coli and the Saccharomyces cerevisiae LEU2 gene were shown to replicate autonomously in the yeast at an approximate copy number of 6 (copies per genome equivalent). This autonomous behaviour is probably due to an H. polymorpha replicon-like sequence present on the S. cerevisiae LEU2 gene fragment. Plasmids replicated as multimers consisting of monomers connected in a head-to-tail configuration. Two out of nine transformants analysed appeared to contain plasmid multimers in which one of the monomers contained a deletion. Plasmids containing internal or flanking regions of the genomic alcohol oxidase gene were shown to integrate by homologous single or double cross-over recombination. Both single- and multi-copy (two or three) tandem integrations were observed. Targeted integration occurred in 1-22% of the cases and was only observed with plasmids linearized within the genomic sequences, indicating that homologous linear ends are recombinogenic in H. polymorpha. In the cases in which no targeted integration occurred, double-strand breaks were efficiently repaired in a homology-independent way. Repair of double-strand breaks was precise in 50-68% of the cases. Linearization within homologous as well as nonhomologous plasmid regions stimulated transformation frequencies up to 15-fold.
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