SummaryThe anaerobic metabolism of the opportunistic pathogen Pseudomonas aeruginosa is important for growth and biofilm formation during persistent infections. The two Fnr-type transcription factors Anr and Dnr regulate different parts of the underlying network in response to oxygen tension and NO. Little is known about all members of the Anr and Dnr regulons and the mediated immediate response to oxygen depletion. Comprehensive transcriptome and bioinformatics analyses in combination with a limited proteome analyses were used for the investigation of the P. aeruginosa response to an immediate oxygen depletion and for definition of the corresponding Anr and Dnr regulons. We observed at first the activation of fermentative pathways for immediate energy generation followed by induction of alternative respiratory chains. A solid position weight matrix model was deduced from the experimentally identified Anr boxes and used for identification of 170 putative Anr boxes in potential P. aeruginosa promoter regions. The combination with the experimental data unambiguously identified 130 new members for the Anr and Dnr regulons. The basis for the understanding of two regulons of P. aeruginosa central to biofilm formation and infection is now defined.

In Pseudomonas aeruginosa, the narK 1 K 2 GHJI operon encodes two nitrate/nitrite transporters and the dissimilatory nitrate reductase. The narK 1 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 finetuned genetic response of P. aeruginosa to anaerobic growth conditions in the presence of nitrate was deduced.The most efficient way for the gram-negative bacterium Pseudomonas aeruginosa to generate energy in the absence of oxygen is through denitrification. During this process, molecular oxygen is replaced by nitrate as the terminal electron acceptor. Nitrate (NO 3 Ϫ ) is reduced in four consecutive steps, via nitrite (NO 2 Ϫ ), nitric oxide (NO), and nitrous oxide (N 2 O) to dinitrogen (N 2 ). This process is vital for growth and survival under microaerobic and anaerobic conditions as found in biofilms and microcolonies of infectious P. aeruginosa (1, 25a). The majority of earlier investigations focused on the enzymology and regulation of nitrite (NO 2 Ϫ )-to-dinitrogen (N 2 ) conversion (27). Here, the regulatory network for the onset of nitrate respiration under oxygen-limiting conditions was elucidated using reporter gene fusions, strains carrying mutated regulatory genes, and site-directed mutagenesis of potential regulator binding sites.Importance of narGHJI, narXL, anr, and dnr for anaerobic growth of P. aeruginosa. In order to confirm the importance of the nitrate reductase genes narGHJI and the regulatory genes anr, dnr, and narXL for the anaerobic growth of P. aeruginosa, knockout mutants were characterized concerning their growth behavior. P. aeruginosa Anr is the oxygen-sensing regulatory protein homologue to Escherichia coli Fnr (19,26). Dnr of P. aeruginosa belongs to the Crp-Fnr superfamily of transcriptional regulators and was reported to activate transcription of the genes nir, nor, and nos (6, 9). In Pseudomonas stutzeri, DnrD was shown to detect NO (13,22). NarXL is a nitrateresponding two-component regulatory system (14). All investigated P. aeruginosa mutant strains failed to grow under anaerobic nitrate respiratory conditions (data not shown). They did not reveal any growth phenotype when tested under aerobic conditions (data not shown). These experiments identify narL, anr, dnr, and narG as key players in the anaerobic growth of P. aeruginosa.Transcriptional control of the nar locus is mediated by the narXL-narK 1 intergenic region. In E. coli and P. stutzeri, Fnrand NarXL-dependent transcription of the narGHJI operon is mediated by the narG ups...

Denitrification and arginine fermentation are major parts of the anaerobic metabolism of Pseudomonas aeruginosa, which is important for biofilm formation and infection. The twocomponent regulatory system NarX-NarL is part of the underlying network and is required for denitrifying growth. All target promoters identified so far are activated by NarL. In this study the effect of NarL on arginine fermentation was investigated using proteome, Northern blot and lacZ reporter gene analyses. NarL-dependent repression of the arcDABC operon was observed and the corresponding NarL-binding site in the arcD promoter region was functionally localized at "60 bp upstream of the transcriptional start site using site-directed promoter mutagenesis and reporter gene fusion experiments. The results clearly show that in the presence of nitrate NarL represses the arginine-dependent activation of the arcDABC operon mediated by ArgR. It does not influence the oxygen-tension-dependent activation via Anr. Thus, the anaerobic energy metabolism of P. aeruginosa is coordinated via NarX-NarL activity. In the presence of nitrate the highly efficient denitrification is preferred over the less attractive arginine fermentation. INTRODUCTIONIn Pseudomonas aeruginosa anaerobic metabolism is important for biofilm growth and for the infection of the cystic fibrosis lung involving biofilm-like P. aeruginosa microcolonies (Barraud et al., 2006;Filiatrault et al., 2006;Hassett et al., 2002;Palmer et al., 2007;Platt et al., 2008;Sauer et al., 2002;Van Alst et al., 2007;Worlitzsch et al., 2002;Xu et al., 1998). In the absence of oxygen P. aeruginosa grows either by denitrification or by arginine fermentation (Carlson & Ingraham, 1983;Vander Wauven et al., 1984;Zumft, 1997). The expression of genes which encode enzymes for denitrification in P. aeruginosa are controlled by the regulatory proteins Anr and Dnr, as well as the nitrate-responsive two-component system NarXNarL (Arai et al., 1997;Schreiber et al., 2007;Ye et al., 1995). Enzymes required for arginine fermentation are encoded by genes which are organized in the operon arcDABC (Luthi et al., 1990). Anaerobic expression of arcDABC has been shown to be Anr-dependent and further stimulated by the arginine-responsive regulator ArgR (Lu et al., 1999). The global oxygen-sensing regulator Anr is an Escherichia coli Fnr homologue and is essential for fermentative and denitrifying growth in the absence of oxygen (Ye et al., 1995). Moreover, Anr controls the expression of dnr, which encodes the nitrogen-oxidesensing regulator Dnr (Arai et al., 1997). Dnr finally induces expression of the genes encoding the nitrite, nitric oxide and nitrous oxide reductases required for denitrification (Arai et al., 1999(Arai et al., , 2003. Mutant and gene expression studies in P. aeruginosa and Pseudomonas stutzeri showed that the two-component system NarXNarL is additionally required for denitrifying growth (Härtig et al., 1999;Schreiber et al., 2007). The P. aeruginosa NarX protein is a sensor kinase and shares 38 % and 3...

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 .

Modern high-throughput techniques allow for the identification and quantification of hundreds of metabolites of a biological system which cover central parts of the metabolome. Due to the amount and complexity of obtained data there is an increasing need for the development of appropriate computational interpretation methods.A novel data analysis pipeline designed for high-throughput determined metabolomic data is presented. The combination of principal component analysis (PCA) with emergent self-organizing maps (ESOM) and hierarchical cluster analysis (HCA) algorithms is used to unravel the structure underlying metabolomic data sets, including the detection of outliers. Observed differences between various analyzed metabolomes are automatically mapped and visualized using KEGG metabolic pathway maps. This way typical metabolic biomarker for data sets from various analyzed growth conditions and genetic backgrounds become visible. In order to validate the described methods we analyzed time resolved metabolomic datasets obtained for Corynebacterium glutamicum cells grown on various carbon sources consisting of 126 different metabolic patterns.The analysis pipeline was implemented in the user-friendly Java software eSOMet. The software was successfully used for the clustering of the metabolome data mentioned above. Metabolic biomarkers typical for the utilized carbon sources and analyzed growth phases were identified.