208 research outputs found

    Tocotrienols inhibit human glutathione S-transferase P1-1

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    Tocotrienols inhibit human glutathione S-transferase P1-1. van Haaften RI, Haenen GR, Evelo CT, Bast A. Department of Pharmacology and Toxicology, Faculty of Medicine, Universiteit Maastricht, The Netherlands. [email protected] Tocopherols and tocotrienols are food ingredients that are believed to have a positive effect on health. The most studied property of both groups of compounds is their antioxidant action. Previously, we found that tocopherols and diverse tocopherol derivatives can inhibit the activity of human glutathione S-transferase P1-1 (GST P1-1). In this study we found that GST P1-1 is also inhibited, in a concentration-dependent manner, by alpha- and gamma-tocotrienol. The concentration giving 50% inhibition of GST P1-1 is 1.8 +/- 0.1 microM for alpha-tocotrienol and 0.7 +/- 0.1 microM for gamma-tocotrienol. This inhibition of GST P1-1 is noncompetitive with respect to both substrates CDNB and GSH. We also examined the 3D structure of GST P1-1 for a possible tocopherol/tocotrienol binding site. The enzyme contains a very hydrophobic pit-like structure where the phytyl tail of tocopherols and tocotrienols could fit in. Binding of tocopherol and tocotrienol to this hydrophobic region might lead to bending of the 3D structure. In this way tocopherols and tocotrienols can inhibit the activity of the enzyme; this inhibition can have far-reaching implications for human

    BridgeDb: standardized access to gene, protein and metabolite identifier mapping services

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    Many interesting problems in bioinformatics require integration of data from various sources. For example when combining microarray data with a pathway database, or merging co-citation networks with protein-protein interaction networks. Invariably this leads to an identifier mapping problem, where different datasets are annotated with identifiers that are related, but originate from different databases.

Solutions for the identifier mapping problem exist, such as Biomart, Synergizer, Cronos, PICR, HMS and many more. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. BridgeDb provides such an interface layer, in the form of both a Java and REST API.

Because of the standardized interface layer, BridgeDb is not tied to a specific source of mapping information. You can switch easily between flat files, relational databases and several different web services. Mapping services can be combined to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb isn't just yet another mapping service: it tries to build further on existing work, and integrate multiple partial solutions. The framework is intended for customization and adaptation to any identifier mapping service. 

BridgeDb makes it easy to add an important capability to existing tools. BridgeDb has already been integrated into several popular bioinformatics applications, such as Cytoscape, WikiPathways, PathVisio, Vanted and Taverna. To encourage tool developers to start using BridgeDb, we've created code examples, online documentation, and a mailinglist to ask questions. 

We believe that, to meet the challenges that are encountered in bioinformatics today, the software development process should follow a few essential principles: user friendliness, code reuse, modularity and open source. BridgeDb adheres to these principles, and can serve as a useful model for others to follow. BridgeDb can function to increase user-friendliness of graphical applications. It re-uses work from other projects such as BioMart and MIRIAM. BridgeDb consists of several small modules, integrated through a common interface (API). Components of BridgeDb can be left out or replaced, for maximum flexibility. BridgeDb was open source from the very beginning of the project. The philosophy of open source is closely aligned to academic values, of building on top of the work of giants. 

Many interesting problems in bioinformatics require integration of data from various sources. For example when combining microarray data with a pathway database, or merging co-citation networks with protein-protein interaction networks. Invariably this leads to an identifier mapping problem, where different datasets are annotated with identifiers that are related, but originate from different databases.

Solutions for the identifier mapping problem exist, such as Biomart, Synergizer, Cronos, PICR, HMS and many more. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. BridgeDb provides such an interface layer, in the form of both a Java and REST API.

Because of the standardized interface layer, BridgeDb is not tied to a specific source of mapping information. You can switch easily between flat files, relational databases and several different web services. Mapping services can be combined to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb isn't just yet another mapping service: it tries to build further on existing work, and integrate multiple partial solutions. The framework is intended for customization and adaptation to any identifier mapping service. 

BridgeDb makes it easy to add an important capability to existing tools. BridgeDb has already been integrated into several popular bioinformatics applications, such as Cytoscape, WikiPathways, PathVisio, Vanted and Taverna. To encourage tool developers to start using BridgeDb, we've created code examples, online documentation, and a mailinglist to ask questions. 

We believe that, to meet the challenges that are encountered in bioinformatics today, the software development process should follow a few essential principles: user friendliness, code reuse, modularity and open source. BridgeDb adheres to these principles, and can serve as a useful model for others to follow. BridgeDb can function to increase user-friendliness of graphical applications. It re-uses work from other projects such as BioMart and MIRIAM. BridgeDb consists of several small modules, integrated through a common interface (API). Components of BridgeDb can be left out or replaced, for maximum flexibility. BridgeDb was open source from the very beginning of the project. The philosophy of open source is closely aligned to academic values, of building on top of the work of giants. 

The BridgeDb library is available at "http://www.bridgedb.org":http://www.bridgedb.org.
A paper about BridgeDb was published in BMC _Bioinformatics_, 2010 Jan 4;11(1):5.

BridgeDb blog: "http://www.helixsoft.nl/blog/?tag=bridgedb":http://www.helixsoft.nl/blog/?tag=bridged

    An integrated bioinformatics approach to improve two-color microarray quality-control: impact on biological conclusions

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    Omics technology used for large-scale measurements of gene expression is rapidly evolving. This work pointed out the need of an extensive bioinformatics analyses for array quality assessment before and after gene expression clustering and pathway analysis. A study focused on the effect of red wine polyphenols on rat colon mucosa was used to test the impact of quality control and normalisation steps on the biological conclusions. The integration of data visualization, pathway analysis and clustering revealed an artifact problem that was solved with an adapted normalisation. We propose a possible point to point standard analysis procedure, based on a combination of clustering and data visualization for the analysis of microarray data

    Identification of novel ER-alpha target genes in breast cancer cells: Gene- and cell-selective co-regulator recruitment at target promoters determines the response to 17beta-estradiol and tamoxifen

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    International audienceTamoxifen and 17β-estradiol are capable of up-regulating the expression of some genes and down-regulate the expression of others simultaneously in the same cell. In addition, tamoxifen shows distinct transcriptional activities in different target tissues.To elucidate whether these events are determined by differences in the recruitment of co-regulators by activated estrogen receptor-α (ER-α) at target promoters, we applied chromatin-immunoprecipitation (ChIP) with promoter microarray hybridisation in breast cancer T47D cells and identified 904 ER-α targets genome-wide. On a selection of newly identified targets, we show that 17β-estradiol and tamoxifen stimulated up- or down-regulation of transcription correlates with the selective recruitment of co-activators or co-repressors, respectively. This is shown for both breast (T47D) and endometrial carcinoma cells (ECC1). Moreover, differential co-regulator recruitment also explains that tamoxifen regulates a number of genes in opposite direction in breast and endometrial cancer cells. Over-expression of co-activator SRC-1 or co-repressor SMRT is sufficient to alter the transcriptional action of tamoxifen on a number of targets. Our findings support the notion that recruitment of co-regulator at target gene promoters and their expression levels determine the effect of ER-α on gene expression to a large extent

    Bioinformatic interrogation of expression array data to identify nutritionally regulated genes potentially modulated by DNA methylation

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    DNA methylation occurs at CpG dinucleotide sites within the genome and is recognised as one of the mechanisms involved in regulation of gene expression. CpG sites are relatively underrepresented in the mammalian genome, but occur densely in regions called CpG islands (CGIs). CGIs located in the promoters of genes inhibit transcription when methylated by impeding transcription factor binding. Due to the malleable nature of DNA methylation, environmental factors are able to influence promoter CGI methylation patterns and thus influence gene expression. Recent studies have provided evidence that nutrition (and other environmental exposures) can cause altered CGI methylation but, with a few exceptions, the genes influenced by these exposures remain largely unknown. Here we describe a novel bioinformatics approach for the analysis of gene expression microarray data designed to identify regulatory sites within promoters of differentially expressed genes that may be influenced by changes in DNA methylation

    Reduction of colonic inflammation in HLA-B27 transgenic rats by feeding Marie Ménard apples, rich in polyphenols

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    Inflammatory bowel diseases (IBD) are immunomediated ailments affecting millions of individuals. Although diet is regarded as an important factor influencing IBD, there are no accepted dietary recommendations presently available. We administered 7.6 % lyophilised apples obtained from two cultivars (Golden Delicious and Marie Ménard, low and high in polyphenols, respectively) to HLA-B27 transgenic rats which develop spontaneous IBD. After 3 months feeding, rats fed Marie Ménard apples had reduced myeloperoxidase activity (3.6 (sem 0.3) v. 2.2 (sem 0.2) U/g tissue; P <0.05) and reduced cyclo-oxygenase-2 (P <0.05) and inducible NO synthase gene expression (P <0.01) in the colon mucosa and significantly less diarrhoea (P <0.05), compared with control rats. Cell proliferation in the colon mucosa was reduced significantly by feeding Golden Delicious apples, with a borderline effect of Marie Ménard apples. Gene expression profiling of the colon mucosa, analysed using the Whole Rat Genome 4 x 44 K Agilent Arrays, revealed a down-regulation of the pathways of PG synthesis, mitogen-activated protein kinase (MAPK) signalling and TNFalpha-NF-kappaB in Marie Ménard-fed rats. In the stools of the animals of this group we also measured a significant reduction of bacteria of the Bacteriodes fragilis group. In conclusion, the administration of Marie Ménard apples, rich in polyphenols and used at present only in the manufacturing of cider, ameliorates colon inflammation in transgenic rats developing spontaneous intestinal inflammation, suggesting the possible use of these and other apple varieties to control inflammation in IBD patient

    Beyond Pathway Analysis: Identification of Active Subnetworks in Rett Syndrome

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    Pathway and network approaches are valuable tools in analysis and interpretation of large complex omics data. Even in the field of rare diseases, like Rett syndrome, omics data are available, and the maximum use of such data requires sophisticated tools for comprehensive analysis and visualization of the results. Pathway analysis with differential gene expression data has proven to be extremely successful in identifying affected processes in disease conditions. In this type of analysis, pathways from different databases like WikiPathways and Reactome are used as separate, independent entities. Here, we show for the first time how these pathway models can be used and integrated into one large network using the WikiPathways RDF containing all human WikiPathways and Reactome pathways, to perform network analysis on transcriptomics data. This network was imported into the network analysis tool Cytoscape to perform active submodule analysis. Using a publicly available Rett syndrome gene expression dataset from frontal and temporal cortex, classical enrichment analysis, including pathway and Gene Ontology analysis, revealed mainly immune response, neuron specific and extracellular matrix processes. Our active module analysis provided a valuable extension of the analysis prominently showing the regulatory mechanism of MECP2, especially on DNA maintenance, cell cycle, transcription, and translation. In conclusion, using pathway models for classical enrichment and more advanced network analysis enables a more comprehensive analysis of gene expression data and provides novel results

    Fasting induces a biphasic adaptive metabolic response in murine small intestine

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    BACKGROUND: The gut is a major energy consumer, but a comprehensive overview of the adaptive response to fasting is lacking. Gene-expression profiling, pathway analysis, and immunohistochemistry were therefore carried out on mouse small intestine after 0, 12, 24, and 72 hours of fasting. RESULTS: Intestinal weight declined to 50% of control, but this loss of tissue mass was distributed proportionally among the gut's structural components, so that the microarrays' tissue base remained unaffected. Unsupervised hierarchical clustering of the microarrays revealed that the successive time points separated into distinct branches. Pathway analysis depicted a pronounced, but transient early response that peaked at 12 hours, and a late response that became progressively more pronounced with continued fasting. Early changes in gene expression were compatible with a cellular deficiency in glutamine, and metabolic adaptations directed at glutamine conservation, inhibition of pyruvate oxidation, stimulation of glutamate catabolism via aspartate and phosphoenolpyruvate to lactate, and enhanced fatty-acid oxidation and ketone-body synthesis. In addition, the expression of key genes involved in cell cycling and apoptosis was suppressed. At 24 hours of fasting, many of the early adaptive changes abated. Major changes upon continued fasting implied the production of glucose rather than lactate from carbohydrate backbones, a downregulation of fatty-acid oxidation and a very strong downregulation of the electron-transport chain. Cell cycling and apoptosis remained suppressed. CONCLUSION: The changes in gene expression indicate that the small intestine rapidly looses mass during fasting to generate lactate or glucose and ketone bodies. Meanwhile, intestinal architecture is maintained by downregulation of cell turnove

    Tolerogenic effects of 1,25-dihydroxyvitamin D on dendritic cells involve induction of fatty acid synthesis

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    The active form of vitamin D, 1,25-dihydroxyvitamin D (1,25D) is a potent regulator of immune function, promoting anti-inflammatory, tolerogenic T cell responses by modulating antigen presentation by dendritic cells (DC). Transcriptomic analyses indicate that DC responses to 1,25D involve changes in glycolysis, oxidative phosphorylation, electron transport and the TCA cycle. To determine the functional impact of 1,25D-mediated metabolic remodelling, human monocyte-derived DC were differentiated to immature (+vehicle, iDC), mature (+LPS, mDC), and immature tolerogenic DC (+1,25D, itolDC) and characterised for metabolic function. In contrast to mDC which showed no change in respiration, itolDC showed increased basal and ATP-linked respiration relative to iDC. Tracer metabolite analyses using (13)C -labeled glucose showed increased lactate and TCA cycle metabolites. Analysis of lipophilic metabolites of (13)C-glucose revealed significant incorporation of label in palmitate and palmitoleate, indicating that 1,25D promotes metabolic fatty acid synthesis in itolDC. Inhibition of fatty acid synthesis in itolDC altered itolDC morphology and suppressed expression of CD14 and IL-10 by these cells. These data indicate that the ability of 1,25D to induce tolerogenic DC involves metabolic remodelling leading to synthesis of fatty acids
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