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      Clinical utilization of genomics data produced by the international Pseudomonas aeruginosa consortium

      1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 2 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 1 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 8 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 16 , 25 , 9 , 26 , 18 , 8 , 27 , 8 , 12 , 28 , 18 , 29 , 30 , 31 , 32 , 12 , 33 , 34 , 23 , 19 , 18 , 8 , 17 , 18 , 3 , 35 , 22 , 2 , 1

      Frontiers in Microbiology

      Frontiers Media S.A.

      Pseudomonas aeruginosa, next-generation sequencing, bacterial genome, phylogeny, database, cystic fibrosis, antibiotic resistance, clinical microbiology

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          Abstract

          The International Pseudomonas aeruginosa Consortium is sequencing over 1000 genomes and building an analysis pipeline for the study of Pseudomonas genome evolution, antibiotic resistance and virulence genes. Metadata, including genomic and phenotypic data for each isolate of the collection, are available through the International Pseudomonas Consortium Database ( http://ipcd.ibis.ulaval.ca/). Here, we present our strategy and the results that emerged from the analysis of the first 389 genomes. With as yet unmatched resolution, our results confirm that P. aeruginosa strains can be divided into three major groups that are further divided into subgroups, some not previously reported in the literature. We also provide the first snapshot of P. aeruginosa strain diversity with respect to antibiotic resistance. Our approach will allow us to draw potential links between environmental strains and those implicated in human and animal infections, understand how patients become infected and how the infection evolves over time as well as identify prognostic markers for better evidence-based decisions on patient care.

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          Most cited references 36

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          The comprehensive antibiotic resistance database.

          The field of antibiotic drug discovery and the monitoring of new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. Despite the fact that the first genomes sequenced of free living organisms were those of bacteria, there have been few specialized bioinformatic tools developed to mine the growing amount of genomic data associated with pathogens. In particular, there are few tools to study the genetics and genomics of antibiotic resistance and how it impacts bacterial populations, ecology, and the clinic. We have initiated development of such tools in the form of the Comprehensive Antibiotic Research Database (CARD; http://arpcard.mcmaster.ca). The CARD integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in new unannotated genome sequences. This unique platform provides an informatic tool that bridges antibiotic resistance concerns in health care, agriculture, and the environment.
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            Sampling the antibiotic resistome.

            Microbial resistance to antibiotics currently spans all known classes of natural and synthetic compounds. It has not only hindered our treatment of infections but also dramatically reshaped drug discovery, yet its origins have not been systematically studied. Soil-dwelling bacteria produce and encounter a myriad of antibiotics, evolving corresponding sensing and evading strategies. They are a reservoir of resistance determinants that can be mobilized into the microbial community. Study of this reservoir could provide an early warning system for future clinically relevant antibiotic resistance mechanisms.
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              An Integrated Pipeline for de Novo Assembly of Microbial Genomes

              Remarkable advances in DNA sequencing technology have created a need for de novo genome assembly methods tailored to work with the new sequencing data types. Many such methods have been published in recent years, but assembling raw sequence data to obtain a draft genome has remained a complex, multi-step process, involving several stages of sequence data cleaning, error correction, assembly, and quality control. Successful application of these steps usually requires intimate knowledge of a diverse set of algorithms and software. We present an assembly pipeline called A5 (Andrew And Aaron's Awesome Assembly pipeline) that simplifies the entire genome assembly process by automating these stages, by integrating several previously published algorithms with new algorithms for quality control and automated assembly parameter selection. We demonstrate that A5 can produce assemblies of quality comparable to a leading assembly algorithm, SOAPdenovo, without any prior knowledge of the particular genome being assembled and without the extensive parameter tuning required by the other assembly algorithm. In particular, the assemblies produced by A5 exhibit 50% or more reduction in broken protein coding sequences relative to SOAPdenovo assemblies. The A5 pipeline can also assemble Illumina sequence data from libraries constructed by the Nextera (transposon-catalyzed) protocol, which have markedly different characteristics to mechanically sheared libraries. Finally, A5 has modest compute requirements, and can assemble a typical bacterial genome on current desktop or laptop computer hardware in under two hours, depending on depth of coverage.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                29 September 2015
                2015
                : 6
                Affiliations
                1Institute for Integrative and Systems Biology, Université Laval Quebec, QC, Canada
                2Institute of Infection and Global Health, University of Liverpool Liverpool, UK
                3Department of Molecular Biology and Biochemistry, Simon Fraser University Vancouver, BC, Canada
                4Ottawa Hospital Research Institute Ottawa, ON, Canada
                5Faculté de Médecine Dentaire, Université de Montréal Montréal, QC, Canada
                6QIMR Berghofer Medical Research Institute Brisbane, QLD, Australia
                7Seattle Children's Research Institute, University of Washington School of Medicine Seattle, WA, USA
                8School of Life Sciences, University of Nottingham Nottingham, UK
                9Département de Médecine, Université de Sherbrooke Sherbrooke, QC, Canada
                10Centre de Recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec Quebec, QC, Canada
                11Département de Biochimie, de Microbiologie et de Bio-informatique, Faculté des Sciences et de Génie, Université Laval Quebec, QC, Canada
                12Department of Human Genetics, McGill University Montreal, QC, Canada
                13INRS Institut Armand Frappier Laval, QC, Canada
                14School of Medicine, Griffith University Gold Coast, QLD, Australia
                15Department of Microbiology and Immunology, University of British Columbia Vancouver, BC, Canada
                16Biological Sciences, University of Calgary Calgary, AB, Canada
                17Department of Systems Biology, Technical University of Denmark Lyngby, Denmark
                18M.G. DeGroote Institute for Infectious Disease Research, McMaster University Hamilton, ON, Canada
                19Antimicrobial Resistance and Healthcare Associated Infections Reference Unit, Public Health England London, UK
                20Child Health Research Centre, The University of Queensland Brisbane, QLD, Australia
                21Centre for Infection and Immunity, Queen's University Belfast Belfast, UK
                22Klinische Forschergruppe, Medizinische Hochschule Hannover, Germany
                23Department of Molecular and Cellular Biology, University of Guelph Guelph, ON, Canada
                24Department of Biochemistry, University of Otago Dunedin, New Zealand
                25Institute for Microbiology and Infection, University of Birmingham Birmingham, UK
                26Department of Infectious Diseases and Immunology, The University of Sydney Sydney, NSW, Australia
                27Department of Pneumology, Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval Quebec, QC, Canada
                28Department of Microbiology and Immunology and Department of Experimental Medicine, McGill University Montreal, QC, Canada
                29Department of Biology, Bard College, Annandale-On-Hudson NY, USA
                30Laboratory for Molecular and Cellular Technology, Queen Astrid Military Hospital Brussels, Belgium
                31New Zealand Institute for Advanced Study, Massey University Albany, New Zealand
                32Max Planck Institute for Evolutionary Biology Plön, Germany
                33Department of Biology, University of Minho Braga, Portugal
                34St. Michael's Hospital Toronto, ON, Canada
                35Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde Glasgow, UK
                Author notes

                Edited by: John R. Battista, Louisiana State University, USA

                Reviewed by: Awdhesh Kalia, University of Texas MD Anderson Cancer Center, USA; Suleyman Yildirim, Istanbu Medipol University International School of Medicine, Turkey

                *Correspondence: Roger C. Levesque, Institute for Integrative and Systems Biology, Université Laval, 1030 Avenue de la Médecine, Quebec, QC G1E 7A9, Canada rclevesq@ 123456ibis.ulaval.ca

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                †These authors have contributed equally to this work.

                Article
                10.3389/fmicb.2015.01036
                4586430
                Copyright © 2015 Freschi, Jeukens, Kukavica-Ibrulj, Boyle, Dupont, Laroche, Larose, Maaroufi, Fothergill, Moore, Winsor, Aaron, Barbeau, Bell, Burns, Camara, Cantin, Charette, Dewar, Déziel, Grimwood, Hancock, Harrison, Heeb, Jelsbak, Jia, Kenna, Kidd, Klockgether, Lam, Lamont, Lewenza, Loman, Malouin, Manos, McArthur, McKeown, Milot, Naghra, Nguyen, Pereira, Perron, Pirnay, Rainey, Rousseau, Santos, Stephenson, Taylor, Turton, Waglechner, Williams, Thrane, Wright, Brinkman, Tucker, Tümmler, Winstanley and Levesque.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 43, Pages: 8, Words: 5854
                Funding
                Funded by: Cystic Fibrosis Canada 10.13039/501100000082
                Award ID: Grant ID number 2610
                Categories
                Microbiology
                Perspective

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