Project description:Biofilms are surface-adhered bacterial communities encased in an extracellular matrix composed of polysaccharides, proteins, and extracelluar (e)DNA, with eDNA being required for the formation and integrity of biofilms. Here we demonstrate that the spatial and temporal release of eDNA is regulated by BfmR, a regulator essential for Pseudomonas aeruginosa biofilm development. The expression of bfmR coincided with localized cell death and DNA release, with high eDNA concentrations localized to the outer part of microcolonies in the form of a ring and as a cap on small clusters. Additionally, eDNA release and cell lysis increased significantly following bfmR inactivation. Genome-wide transcriptional profiling indicated that bfmR was required for repression of genes associated with bacteriophage assembly and bacteriophage-mediated lysis. In order to determine which of these genes were directly regulated by BfmR, we utilized chromatin immunoprecipitation (ChIP) analysis to identify the promoter of PA0691, termed here phdA, encoding a previously undescribed homologue of the prevent-host-death (Phd) family of proteins. Lack of phdA expression coincided with impaired biofilm development, increased cell death and bacteriophage release, a phenotype comparable to ΔbfmR. Expression of phdA in ΔbfmR biofilms restored eDNA release, cell lysis, release of bacteriophages, and biofilm formation to wild type levels. Moreover, overexpression of phdA rendered P. aeruginosa resistant to lysis mediated by superinfective bacteriophage Pf4 which was only detected in biofilms. The expression of bfmR was stimulated by conditions resulting in membrane perturbation and cell lysis. Thus, we propose that BfmR regulates biofilm development by controlling bacteriophage-mediated lysis and thus, cell death and eDNA release, via PhdA. For biofilm growth experiments, three independent replicates of P. aeruginosa strains PAO1 and ΔbfmR were grown as biofilms in a flow-through system using a once-through continuous flow tube reactor system for biofilm sample collection and in flow cells (BioSurface Technologies) for the analysis of biofilm architecture as previously described (Sauer et al., 2002, Sauer et al., 2004, Petrova & Sauer, 2009). Cells were treated with RNAprotect (Qiagen), and total RNA was extracted using an RNeasy mini purification kit (Qiagen) per the manufacturer’s instructions. RNA quality and the presence of residual DNA were checked on an Agilent Bioanalyzer 2100 electrophoretic system pre- and post-DNase treatment. Ten micrograms of total RNA was used for cDNA synthesis, fragmentation, and labeling according to the Affymetrix GeneChip P. aeruginosa genome array expression analysis protocol. Sauer, K., A. K. Camper, G. D. Ehrlich, J. W. Costerton & D. G. Davies, (2002) Pseudomonas aeruginosa displays multiple phenotypes during development as a biofilm. J. Bacteriol. 184: 1140-1154. Sauer, K., M. C. Cullen, A. H. Rickard, L. A. H. Zeef, D. G. Davies & P. Gilbert, (2004) Characterization of nutrient-induced dispersion in Pseudomonas aeruginosa PAO1 biofilm. J. Bacteriol. 186: 7312-7326. Petrova, O. E. & K. Sauer, (2009) A novel signaling network essential for regulating Pseudomonas aeruginosa biofilm development. PLoS Pathogens 5: e1000668.

Project description:Oberhardt2008 - Genome-scale metabolic network of Pseudomonas aeruginosa (iMO1056) This model is described in the article: Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1. Oberhardt MA, Puchałka J, Fryer KE, Martins dos Santos VA, Papin JA. J. Bacteriol. 2008 Apr; 190(8): 2790-2803 Abstract: Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen. This model is hosted on BioModels Database and identified by: MODEL1507180020. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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