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      The Serum Resistome of a Globally Disseminated Multidrug Resistant Uropathogenic Escherichia coli Clone

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          Abstract

          Escherichia coli ST131 is a globally disseminated, multidrug resistant clone responsible for a high proportion of urinary tract and bloodstream infections. The rapid emergence and successful spread of E. coli ST131 is strongly associated with antibiotic resistance; however, this phenotype alone is unlikely to explain its dominance amongst multidrug resistant uropathogens circulating worldwide in hospitals and the community. Thus, a greater understanding of the molecular mechanisms that underpin the fitness of E. coli ST131 is required. In this study, we employed hyper-saturated transposon mutagenesis in combination with multiplexed transposon directed insertion-site sequencing to define the essential genes required for in vitro growth and the serum resistome (i.e. genes required for resistance to human serum) of E. coli EC958, a representative of the predominant E. coli ST131 clonal lineage. We identified 315 essential genes in E. coli EC958, 231 (73%) of which were also essential in E. coli K-12. The serum resistome comprised 56 genes, the majority of which encode membrane proteins or factors involved in lipopolysaccharide (LPS) biosynthesis. Targeted mutagenesis confirmed a role in serum resistance for 46 (82%) of these genes. The murein lipoprotein Lpp, along with two lipid A-core biosynthesis enzymes WaaP and WaaG, were most strongly associated with serum resistance. While LPS was the main resistance mechanism defined for E. coli EC958 in serum, the enterobacterial common antigen and colanic acid also impacted on this phenotype. Our analysis also identified a novel function for two genes, hyxA and hyxR, as minor regulators of O-antigen chain length. This study offers novel insight into the genetic make-up of E. coli ST131, and provides a framework for future research on E. coli and other Gram-negative pathogens to define their essential gene repertoire and to dissect the molecular mechanisms that enable them to survive in the bloodstream and cause disease.

          Author Summary

          The emergence and rapid dissemination of new bacterial pathogens presents multiple challenges to healthcare systems, including the need for rapid detection, precise diagnostics, effective transmission control and effective treatment. E. coli ST131 is an example of a recently emerged multidrug resistant pathogen that is capable of causing urinary tract and bloodstream infections with limited available treatment options. In order to increase our molecular understanding of E. coli ST131, we developed a high-throughput transposon mutagenesis system in combination with next generation sequencing to test every gene for its essential role in growth and for its contribution to serum resistance. We identified 315 essential genes, 270 of which were conserved among all currently available complete E. coli genomes. Fifty-six genes that define the serum resistome of E. coli ST131 were identified, including genes encoding membrane proteins, proteins involved in LPS biosynthesis, regulators and several novel proteins with previously unknown function. This study therefore provides an inventory of essential and serum resistance genes that could form a framework for the future development of targeted therapeutics to prevent disease caused by multidrug-resistant E. coli ST131 strains.

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          Small-sample estimation of negative binomial dispersion, with applications to SAGE data.

          We derive a quantile-adjusted conditional maximum likelihood estimator for the dispersion parameter of the negative binomial distribution and compare its performance, in terms of bias, to various other methods. Our estimation scheme outperforms all other methods in very small samples, typical of those from serial analysis of gene expression studies, the motivating data for this study. The impact of dispersion estimation on hypothesis testing is studied. We derive an "exact" test that outperforms the standard approximate asymptotic tests.
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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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              Moderated statistical tests for assessing differences in tag abundance.

              Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene expression on a genomic scale, without the need for prior knowledge of the genome sequence. As the cost of sequencing DNA decreases, the number of DGE datasets is expected to grow dramatically. Various tests of differential expression have been proposed for replicated DGE data using binomial, Poisson, negative binomial or pseudo-likelihood (PL) models for the counts, but none of the these are usable when the number of replicates is very small. We develop tests using the negative binomial distribution to model overdispersion relative to the Poisson, and use conditional weighted likelihood to moderate the level of overdispersion across genes. Not only is our strategy applicable even with the smallest number of libraries, but it also proves to be more powerful than previous strategies when more libraries are available. The methodology is equally applicable to other counting technologies, such as proteomic spectral counts. An R package can be accessed from http://bioinf.wehi.edu.au/resources/
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                October 2013
                October 2013
                3 October 2013
                : 9
                : 10
                : e1003834
                Affiliations
                [1 ]Australian Infectious Diseases Research Centre, The University of Queensland, Brisbane, Queensland, Australia
                [2 ]School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia
                [3 ]Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
                [4 ]Faculty of Medicine and Dentistry, University of Plymouth, Plymouth, United Kingdom
                MicroTrek Incorporated, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MDP SS MT SAB MAS. Performed the experiments: MDP KMP SS SWL LPA MESA VMM. Analyzed the data: MDP DGM SAB MAS. Contributed reagents/materials/analysis tools: VMM MU SAB. Wrote the paper: MDP SS DGM MT MU SAB MAS.

                [¤]

                Current address: Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland.

                Article
                PGENETICS-D-13-00963
                10.1371/journal.pgen.1003834
                3789825
                24098145
                a9878890-9f8b-4f4a-870c-415dff520c19
                Copyright @ 2013

                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
                : 11 April 2013
                : 12 August 2013
                Page count
                Pages: 18
                Funding
                This work was supported by a grant from the Australian National Health and Medical Research Council [APP1012076]. MAS was supported by an Australian Research Council (ARC) Future Fellowship [FT100100662]. SAB was supported by an ARC Australian Research Fellowship [DP0881347]. MT was supported by an ARC Discovery Early Career Researcher Award [DE130101169]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article

                Genetics
                Genetics

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