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      Robustness and Plasticity of Metabolic Pathway Flux among Uropathogenic Isolates of Pseudomonas aeruginosa

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          Abstract

          Pseudomonas aeruginosa is a human pathogen that frequently causes urinary tract and catheter-associated urinary tract infections. Here, using 13C-metabolic flux analysis, we conducted quantitative analysis of metabolic fluxes in the model strain P. aeruginosa PAO1 and 17 clinical isolates. All P. aeruginosa strains catabolized glucose through the Entner-Doudoroff pathway with fully respiratory metabolism and no overflow. Together with other NADPH supplying reactions, this high-flux pathway provided by far more NADPH than needed for anabolism: a benefit for the pathogen to counteract oxidative stress imposed by the host. P. aeruginosa recruited the pentose phosphate pathway exclusively for biosynthesis. In contrast to glycolytic metabolism, which was conserved among all isolates, the flux through pyruvate metabolism, the tricarboxylic acid cycle, and the glyoxylate shunt was highly variable, likely caused by adaptive processes in individual strains during infection. This aspect of metabolism was niche-specific with respect to the corresponding flux because strains isolated from the urinary tract clustered separately from those originating from catheter-associated infections. Interestingly, most glucose-grown strains exhibited significant flux through the glyoxylate shunt. Projection into the theoretical flux space, which was computed using elementary flux-mode analysis, indicated that P. aeruginosa metabolism is optimized for efficient growth and exhibits significant potential for increasing NADPH supply to drive oxidative stress response.

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          Pseudomonas aeruginosa: all roads lead to resistance.

          Pseudomonas aeruginosa is often resistant to multiple antibiotics and consequently has joined the ranks of 'superbugs' due to its enormous capacity to engender resistance. It demonstrates decreased susceptibility to most antibiotics due to low outer membrane permeability coupled to adaptive mechanisms and can readily achieve clinical resistance. Newer research, using mutant library screens, microarray technologies and mutation frequency analysis, has identified very large collections of genes (the resistome) that when mutated lead to resistance as well as new forms of adaptive resistance that can be triggered by antibiotics themselves, in in vivo growth conditions or complex adaptations such as biofilm growth or swarming motility. Copyright © 2011 Elsevier Ltd. All rights reserved.
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            A dynamic and intricate regulatory network determines Pseudomonas aeruginosa virulence

            Pseudomonas aeruginosa is a metabolically versatile bacterium that is found in a wide range of biotic and abiotic habitats. It is a major human opportunistic pathogen causing numerous acute and chronic infections. The critical traits contributing to the pathogenic potential of P. aeruginosa are the production of a myriad of virulence factors, formation of biofilms and antibiotic resistance. Expression of these traits is under stringent regulation, and it responds to largely unidentified environmental signals. This review is focused on providing a global picture of virulence gene regulation in P. aeruginosa. In addition to key regulatory pathways that control the transition from acute to chronic infection phenotypes, some regulators have been identified that modulate multiple virulence mechanisms. Despite of a propensity for chaotic behaviour, no chaotic motifs were readily observed in the P. aeruginosa virulence regulatory network. Having a ‘birds-eye’ view of the regulatory cascades provides the forum opportunities to pose questions, formulate hypotheses and evaluate theories in elucidating P. aeruginosa pathogenesis. Understanding the mechanisms involved in making P. aeruginosa a successful pathogen is essential in helping devise control strategies.
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              Persistence of Mycobacterium tuberculosis in macrophages and mice requires the glyoxylate shunt enzyme isocitrate lyase.

              Mycobacterium tuberculosis claims more human lives each year than any other bacterial pathogen. Infection is maintained in spite of acquired immunity and resists eradication by antimicrobials. Despite an urgent need for new therapies targeting persistent bacteria, our knowledge of bacterial metabolism throughout the course of infection remains rudimentary. Here we report that persistence of M. tuberculosis in mice is facilitated by isocitrate lyase (ICL), an enzyme essential for the metabolism of fatty acids. Disruption of the icl gene attenuated bacterial persistence and virulence in immune-competent mice without affecting bacterial growth during the acute phase of infection. A link between the requirement for ICL and the immune status of the host was established by the restored virulence of delta icl bacteria in interferon-gamma knockout mice. This link was apparent at the level of the infected macrophage: Activation of infected macrophages increased expression of ICL, and the delta icl mutant was markedly attenuated for survival in activated but not resting macrophages. These data suggest that the metabolism of M. tuberculosis in vivo is profoundly influenced by the host response to infection, an observation with important implications for the treatment of chronic tuberculosis.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                7 April 2014
                : 9
                : 4
                : e88368
                Affiliations
                [1 ]Institute of Biochemical Engineering, Technische Universität Braunschweig, Braunschweig, Germany
                [2 ]Institute of Microbiology, Technische Universität Braunschweig, Braunschweig, Germany
                [3 ]Institute of Systems Biotechnology, Saarland University, Saarbrücken, Germany
                Virginia Commonwealth University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: CW. Performed the experiments: AB. Analyzed the data: AB JB PT CW. Contributed reagents/materials/analysis tools: KD. Wrote the paper: AB JB DJ CW. Drafted metabolic network and performed in silico pathway analysis: JB. Provided clinical isolates: PT.

                Article
                PONE-D-13-40031
                10.1371/journal.pone.0088368
                3977821
                24709961
                45707e23-1c35-4360-a799-50fd8b02ad8c
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 30 September 2013
                : 6 January 2014
                Page count
                Pages: 14
                Funding
                This work was financially supported by the German Federal Ministry of Eduction and Research ( www.bmbf.de) through grant 315833D in the initiative Medical Infection Genomics. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Carbohydrate Metabolism
                Metabolic Pathways
                Biochemical Simulations
                Computational Biology
                Microbiology
                Bacteriology
                Gram Negative
                Medical Microbiology
                Microbial Pathogens
                Bacterial Pathogens
                Microbial Physiology
                Microbial Metabolism
                Systems Biology
                Computer and Information Sciences
                Network Analysis
                Metabolic Networks

                Uncategorized
                Uncategorized

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