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      Reorganization of gene network for degradation of polycyclic aromatic hydrocarbons (PAHs) in Pseudomonas aeruginosa PAO1 under several conditions

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          Abstract

          Although polycyclic aromatic hydrocarbons (PAHs) are harmful to human health, their elimination from the environment is not easy. Biodegradation of PAHs is promising since many bacteria have the ability to use hydrocarbons as their sole carbon and energy sources for growth. Of various microorganisms that can degrade PAHs, Pseudomonas aeruginosa is particularly important, not only because it causes a series of diseases including infection in cystic fibrosis patients, but also because it is a model bacterium in various studies. The genes that are responsible for degrading PAHs have been identified in P. aeruginosa, however, no gene acts alone as various stresses often initiate different metabolic pathways, quorum sensing, biofilm formation, antibiotic tolerance, etc. Therefore, it is important to study how PAH degradation genes behave under different conditions. In this study, we apply network analysis to investigating how 46 PAH degradation genes reorganized among 5549 genes in P. aeruginosa PAO1 under nine different conditions using publicly available gene coexpression data from GEO. The results provide six aspects of novelties: (i) comparing the number of gene clusters before and after stresses, (ii) comparing the membership in each gene cluster before and after stresses, (iii) defining which gene changed its membership together with PAH degradation genes before and after stresses, (iv) classifying membership-changed-genes in terms of category in Pseudomonas Genome Database, (v) postulating unknown gene’s function, and (vi) proposing new mechanisms for genes of interests. This study can shed light on understanding of cooperative mechanisms of PAH degradation from the level of entire genes in an organism, and paves the way to conduct the similar studies on other genes.

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          The online version of this article (doi:10.1007/s13353-017-0402-9) contains supplementary material, which is available to authorized users.

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          Most cited references62

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          Physiological heterogeneity in biofilms.

          Biofilms contain bacterial cells that are in a wide range of physiological states. Within a biofilm population, cells with diverse genotypes and phenotypes that express distinct metabolic pathways, stress responses and other specific biological activities are juxtaposed. The mechanisms that contribute to this genetic and physiological heterogeneity include microscale chemical gradients, adaptation to local environmental conditions, stochastic gene expression and the genotypic variation that occurs through mutation and selection. Here, we discuss the processes that generate chemical gradients in biofilms, the genetic and physiological responses of the bacteria as they adapt to these gradients and the techniques that can be used to visualize and measure the microscale physiological heterogeneities of bacteria in biofilms.
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            Is Open Access

            Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database

            The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches.
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              The hierarchy quorum sensing network in Pseudomonas aeruginosa

              Pseudomonas aeruginosa causes severe and persistent infections in immune compromised individuals and cystic fibrosis sufferers. The infection is hard to eradicate as P. aeruginosa has developed strong resistance to most conventional antibiotics. The problem is further compounded by the ability of the pathogen to form biofilm matrix, which provides bacterial cells a protected environment withstanding various stresses including antibiotics. Quorum sensing (QS), a cell density-based intercellular communication system, which plays a key role in regulation of the bacterial virulence and biofilm formation, could be a promising target for developing new strategies against P. aeruginosa infection. The QS network of P. aeruginosa is organized in a multi-layered hierarchy consisting of at least four interconnected signaling mechanisms. Evidence is accumulating that the QS regulatory network not only responds to bacterial population changes but also could react to environmental stress cues. This plasticity should be taken into consideration during exploration and development of anti-QS therapeutics.
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                Author and article information

                Contributors
                hongguanglishibahao@yahoo.com
                Journal
                J Appl Genet
                J. Appl. Genet
                Journal of Applied Genetics
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1234-1983
                2190-3883
                7 July 2017
                7 July 2017
                2017
                : 58
                : 4
                : 545-563
                Affiliations
                ISNI 0000 0004 1774 8517, GRID grid.418329.5, Bioscience and Technology Research Center, Guangxi Academy of Sciences, ; 98 Daling Road, Nanning, Guangxi 530007 China
                Author notes

                Communicated by: Agnieszka Szalewska-Palasz

                Author information
                http://orcid.org/0000-0003-0775-5759
                Article
                402
                10.1007/s13353-017-0402-9
                5655620
                28685384
                c90e7bf8-f07c-4b73-90f2-dd45221ae019
                © The Author(s) 2017

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 28 November 2016
                : 22 May 2017
                : 6 June 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31560315
                Award ID: 31460296
                Award Recipient :
                Categories
                Microbial Genetics • Original Paper
                Custom metadata
                © Institute of Plant Genetics, Polish Academy of Sciences, Poznan 2017

                Genetics
                bioinformatics,network,polycyclic aromatic hydrocarbon degradation gene,pseudomonas aeruginosa

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