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      Essential genome of Pseudomonas aeruginosa in cystic fibrosis sputum.

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          Abstract

          Defining the essential genome of bacterial pathogens is central to developing an understanding of the biological processes controlling disease. This has proven elusive for Pseudomonas aeruginosa during chronic infection of the cystic fibrosis (CF) lung. In this paper, using a Monte Carlo simulation-based method to analyze high-throughput transposon sequencing data, we establish the P. aeruginosa essential genome with statistical precision in laboratory media and CF sputum. Reconstruction of the global requirements for growth in CF sputum compared with defined growth conditions shows that the latter requires several cofactors including biotin, riboflavin, and pantothenate. Comparison of P. aeruginosa strains PAO1 and PA14 demonstrates that essential genes are primarily restricted to the core genome; however, some orthologous genes in these strains exhibit differential essentiality. These results indicate that genes with similar molecular functions may have distinct genetic roles in different P. aeruginosa strains during growth in CF sputum. We also show that growth in a defined growth medium developed to mimic CF sputum yielded virtually identical fitness requirements to CF sputum, providing support for this medium as a relevant in vitro model for CF microbiology studies.

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          Most cited references41

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          Differential expression analysis for sequence count data

          High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.
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            Tn-seq; high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms

            Biological pathways are structured in complex networks of interacting genes. Solving the architecture of such networks may provide valuable information, such as how microorganisms cause disease. Here we present a method (Tn-seq) for accurately determining quantitative genetic interactions on a genome-wide scale in microorganisms. Tn-seq is based on the assembly of a saturated Mariner transposon insertion library. After library selection, changes in frequency of each insertion mutant are determined by sequencing of the flanking regions en masse. These changes are used to calculate each mutant’s fitness. Fitness was determined for each gene of the gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis. A genome-wide screen for genetic interactions identified both alleviating and aggravating interactions that could be further divided into seven distinct categories. Due to the wide activity of the Mariner transposon, Tn-seq has the potential to contribute to the exploration of complex pathways across many different species.
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              Identifying genetic determinants needed to establish a human gut symbiont in its habitat.

              The human gut microbiota is a metabolic organ whose cellular composition is determined by a dynamic process of selection and competition. To identify microbial genes required for establishment of human symbionts in the gut, we developed an approach (insertion sequencing, or INSeq) based on a mutagenic transposon that allows capture of adjacent chromosomal DNA to define its genomic location. We used massively parallel sequencing to monitor the relative abundance of tens of thousands of transposon mutants of a saccharolytic human gut bacterium, Bacteroides thetaiotaomicron, as they established themselves in wild-type and immunodeficient gnotobiotic mice, in the presence or absence of other human gut commensals. In vivo selection transforms this population, revealing functions necessary for survival in the gut: we show how this selection is influenced by community composition and competition for nutrients (vitamin B(12)). INSeq provides a broadly applicable platform to explore microbial adaptation to the gut and other ecosystems.
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                Author and article information

                Journal
                Proc. Natl. Acad. Sci. U.S.A.
                Proceedings of the National Academy of Sciences of the United States of America
                1091-6490
                0027-8424
                Mar 31 2015
                : 112
                : 13
                Affiliations
                [1 ] Department of Molecular Biosciences, Institute of Cellular and Molecular Biology, Center for Infectious Disease, The University of Texas at Austin, Austin, TX 78712.
                [2 ] Department of Molecular Biosciences, Institute of Cellular and Molecular Biology, Center for Infectious Disease, The University of Texas at Austin, Austin, TX 78712 mwhiteley@austin.utexas.edu.
                Article
                1419677112
                10.1073/pnas.1419677112
                25775563
                a4959261-f479-41da-8ac8-cccaef08aa7a
                History

                Pseudomonas aeruginosa,Tn-seq,cystic fibrosis,essential genes,sputum

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