10 research outputs found

    Regulatorische und metabolische Anpassung von Pseudomonas aeruginosa an Änderungen des Sauerstoffpartialdruckes und der Wachstumsphase

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    Anaerobic growth and persistence are major prerequisites for a successful infection by the opportunistic pathogen P. aeruginosa. Central regulatory strategies of Pseudomonas aeruginosa were investigated at the gene regulatory and metabolic level. Transcriptome analyses of the P. aeruginosa wild type and a narL mutant defective in the nitrate response regulator required for anaerobic growth identified 42 genes as members of the NarL regulon. Importantly, NarL induces expression of the nitrate reductase operon narK1K2GHJI and of genes involved in the biosynthesis of enzymatic cofactors and represses transcription of the rhl quorum sensing genes indicating an interaction of these two regulatory networks both associated with pathogenicity. Additionally, northern blot analysis and promoter lacZ reporter gene studies confirmed NarL mediated repression of the arginine fermentation operon arcDABC. Thus NarXL coordinates the anaerobic energy metabolism via induction of nitrate respiration and repression of less efficient arginine fermentation. Promoter lacZ reporter gene studies of the Anr-dependent arcD and Dnr-dependent nirS promoter clearly demonstrated that the downstream region of the Anr binding site consisting of the - 10 region mediates Anr and Dnr specific gene regulation and that Dnr specificity further requires the Anr binding site upstream region indicating an involvement of additional regulators. Metabolome and transcriptome analyses of the P. aeruginosa wild type revealed several pathways affected by changes in growth phase and showed overall downregulation of the carbohydrate and amino acid metabolism in stationary phase at both levels. Interestingly, GC-MS analyses identified various new cellular responses not found with microarrays, e. g. production of the polyamine cadaverine related to pathogenicity.Anaerobes Wachstum und Persitenz sind wichtige Vorraussetzungen für eine erfolgreiche Infektion des opportunistischen Pathogens P. aeruginosa. Zentrale regulatorische Strategien von P. aeruginosa wurden auf regulatorischer und metabolischer Ebene untersucht. Transkriptom Analysen des P. aeruginosa Wildtyps und einer narL Mutante mit defektem Nitrat detektierenden Antwortregulator identifizierten 42 Gene als Mitglieder des NarL Regulons. NarL induziert die Expression des Nitratreduktase Operons narK1K2GHJI und von Genen, welche in die Biosynthese enzymatischer Kofaktoren involviert sind und reprimiert die Transkription der rhl Quorum Sensing Gene, was wiederum eine Interaktion dieser beiden regulatorischen Netzwerke andeutet. Zudem bestätigten Northern Blot Analysen und Promotor-lacZ Reportergen Studien die durch NarL vermittelte Repression des Arginin Fermentation Operons arcDABC. Folglich koordiniert NarXL den anaeroben Energie Metabolismus durch Induktion der Nitrat Respiration und Repression der Arginin Fermentation. Promotor-lacZ Reportergen Studien des Anr abhängigen arcD und des Dnr abhängigen nirS Promotors zeigten, dass die der Anr Bindestelle stromabwärts gelegene Region, welche die – 10 Region enthält, die Anr und Dnr spezifische Genregulation vermittelt und dass die Dnr Spezifität zudem durch die der Anr Bindestelle stromaufwärts gelegene Region beeinflusst wird, was auf eine Beteiligung zusätzlicher Regulatoren hinweist. Metabolom und Transkriptom Analysen des P. aeruginosa Wildtyps identifizierten verschiedene Stoffwechselwege, welche durch Änderungen der Wachstumsphase affektiert wurden und zeigten sowohl auf Metabolom- als auch auf Transkriptomebene einen weniger aktiven Kohlenhydrat- und Aminosäure-Metabolismus in der Stationärphase. Interessanterweise konnten durch GC-MS Analysen neue zelluläre Antworten, wie z. B. die Produktion des Polyamins Cadaverin, beschrieben werden, welche anhand der Mikroarray Analysen nicht erkennbar waren

    SYSTOMONAS — an integrated database for systems biology analysis of Pseudomonas

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    To provide an integrated bioinformatics platform for a systems biology approach to the biology of pseudomonads in infection and biotechnology the database SYSTOMONAS (SYSTems biology of pseudOMONAS) was established. Besides our own experimental metabolome, proteome and transcriptome data, various additional predictions of cellular processes, such as gene-regulatory networks were stored. Reconstruction of metabolic networks in SYSTOMONAS was achieved via comparative genomics. Broad data integration is realized using SOAP interfaces for the well established databases BRENDA, KEGG and PRODORIC. Several tools for the analysis of stored data and for the visualization of the corresponding results are provided, enabling a quick understanding of metabolic pathways, genomic arrangements or promoter structures of interest. The focus of SYSTOMONAS is on pseudomonads and in particular Pseudomonas aeruginosa, an opportunistic human pathogen. With this database we would like to encourage the Pseudomonas community to elucidate cellular processes of interest using an integrated systems biology strategy. The database is accessible at

    The Anaerobic Regulatory Network Required for Pseudomonas aeruginosa Nitrate Respirationâ–¿

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    In Pseudomonas aeruginosa, the narK1K2GHJI operon encodes two nitrate/nitrite transporters and the dissimilatory nitrate reductase. The narK1 promoter is anaerobically induced in the presence of nitrate by the dual activity of the oxygen regulator Anr and the N-oxide regulator Dnr in cooperation with the nitrate-responsive two-component regulatory system NarXL. The DNA bending protein IHF is essential for this process. Similarly, narXL gene transcription is enhanced under anaerobic conditions by Anr and Dnr. Furthermore, Anr and NarXL induce expression of the N-oxide regulator gene dnr. Finally, NarXL in cooperation with Dnr is required for anaerobic nitrite reductase regulatory gene nirQ transcription. A cascade regulatory model for the fine-tuned genetic response of P. aeruginosa to anaerobic growth conditions in the presence of nitrate was deduced

    The visualization of metabolic pathways from KEGG in SYSTOMONAS is based on GraphViz using the dot layout

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    <p><b>Copyright information:</b></p><p>Taken from "SYSTOMONAS — an integrated database for systems biology analysis of "</p><p>Nucleic Acids Research 2007;35(Database issue):D533-D537.</p><p>Published online Jan 2007</p><p>PMCID:PMC1899106.</p><p>© 2006 The Author(s)</p> All known metabolic reactions are depicted here for the ‘Urea cycle and metabolism of amino groups’ pathway. Rectangles depict metabolic reactions, ellipses represent metabolites whose names are abbreviated with an asterisk * when the length exceeds 10 letters. Both types of nodes are clickable. Different colours for rectangles specify distinct species, which catalyse the corresponding reaction. These pathways can be obtained from metabolic pathway entries. An abbreviation code for the species is provided with the visualization output (AO1 = PAO1, A14 = PA14, P = KT2440, Pf-5 = F5, F01 = PfO-1, ST = pv tomato, SP = pv , SS = pv

    Semi-quantitative scatter plot for the comparison of metabolic profiles measured for PAO1 grown under aerobic conditions

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    <p><b>Copyright information:</b></p><p>Taken from "SYSTOMONAS — an integrated database for systems biology analysis of "</p><p>Nucleic Acids Research 2007;35(Database issue):D533-D537.</p><p>Published online Jan 2007</p><p>PMCID:PMC1899106.</p><p>© 2006 The Author(s)</p> Metabolites were analysed by GC/MS. Mean peak areas and standard deviations for the metabolites were calculated and plotted on a logarithmic scale using gnuplot (). Metabolites measured from samples of exponentially growing cells under aerobic conditions are plotted along the -axis against metabolites from samples of resting cells along the -axis. The metabolite name for every data point is shown as tooltip while moving the mouse over the point (e.g. for the data point ‘Lactate’) and linked back to the corresponding database entry. If the metabolic profile during one experimental condition is similar to the condition compared, data points will arrange closely to the diagonal line
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