Project description:To further determine the origin of the increased virulence of Pseudomonas aeruginosa PA14 compared to Pseudomonas aeruginosa PAO1, we report a transcriptomic approach through RNA sequencing. Next-generation sequencing (NGS) has revolutioned sistems-based analsis of transcriptomic pathways. The goals of this study are to compare the transcriptomic profile of all 5263 orthologous genes of these nearly two strains of Pseudomonas aeruginosa.
Project description:Individuals with cystic fibrosis are susceptible to co-infection by Aspergillus fumigatus and Pseudomonas aeruginosa, however P. aeruginosa eventually predominates as the primary pathogen. Several factors are likely to facilitate P. aeruginosa colonization in the airways, including alterations to the microbial environment. In this study, significant growth proliferation was observed in P. aeruginosa when the bacteria were exposed to culture filtrates produced by A. fumigatus in a nitrate-rich, nutrient-poor liquid broth, Czapek-Dox. Proteomic analysis of the A. fumigatus culture filtrate identified a significant number of environment-altering proteases and peptidases, which may contribute to the growth promoting effect observed when P. aeruginosa is exposed to this culture filtrate. These findings offer insights into the determinants that contribute to P. aeruginosa proliferation in the presence of A. fumigatus.
Project description:We report RNA-seq data of Pseudomonas aeruginosa PA14 (UCBPP-PA14) and an isogenic rpoS-STOP mutant generated using CRISPR/Cas9 base editing. Transcriptomic profiling during exponential growth in rich medium highlights the regulatory influence of RpoS. These data enable exploration of RpoS-dependent responses in the virulent PA14 strain.
Project description:We aim to compare global transcriptomic analysis of wt and delta-nrdRmutant in Pseudomonas aeruginosa PAO1 during aerobic and anaerobic conditions.
Project description:This model, iPau21, updates and extends the genome-scale metabolic model of the harmful pathogen Pseudomonas aeruginosa UCBPP-PA14, initially published by Bartell et al. (2017). This new model incorporates new information and extensive annotation additions based on manual literature curation. The model was validated using MEMOTE to demonstrate its ability to grow on known carbon sources for this organism, gene essentiality, and additional capabilities. The model was contextualized with transcriptomic data that demonstrate its growth capabilities and differential utilization of fumarate metabolism while also revealing an increased utilization of propionate metabolism upon MUC5B exposure.
Project description:ErfA is a transcription factor of Pseudomonas aeruginosa. We here define the genome-wide binding sites of ErfA by DAP-seq in Pseudomonas aeruginosa PAO1 and IHMA87, Pseudomonas chlororaphis PA23, Pseudomonas protegens CHA0 and Pseudomonas putida KT2440.
Project description:Pseudomonas aeruginosa is a common bacterium in the terminal plumbing system of buildings and it is from this niche that a substantial fraction of infections are acquired. To better understand P. aeruginosa biology in this environment, we examined the transcriptomes in tap water and pond water.
Project description:PsrA, a transcription factor belonging to the TetR family, is known to participate in the regulation of fatty acid metabolism, type III secretion system, and quinolone signaling in Pseudomonas aeruginosa. Using a psrA overexpression strain, this study conducted a transcriptomic analysis to examine the role of PsrA in P. aeruginosa PAO1.
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.
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