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      Salmonella enterica Prophage Sequence Profiles Reflect Genome Diversity and Can Be Used for High Discrimination Subtyping

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          Abstract

          Non-typhoidal Salmonella is a leading cause of foodborne illness worldwide. Prompt and accurate identification of the sources of Salmonella responsible for disease outbreaks is crucial to minimize infections and eliminate ongoing sources of contamination. Current subtyping tools including single nucleotide polymorphism (SNP) typing may be inadequate, in some instances, to provide the required discrimination among epidemiologically unrelated Salmonella strains. Prophage genes represent the majority of the accessory genes in bacteria genomes and have potential to be used as high discrimination markers in Salmonella. In this study, the prophage sequence diversity in different Salmonella serovars and genetically related strains was investigated. Using whole genome sequences of 1,760 isolates of S. enterica representing 151 Salmonella serovars and 66 closely related bacteria, prophage sequences were identified from assembled contigs using PHASTER. We detected 154 different prophages in S. enterica genomes. Prophage sequences were highly variable among S. enterica serovars with a median ± interquartile range (IQR) of 5 ± 3 prophage regions per genome. While some prophage sequences were highly conserved among the strains of specific serovars, few regions were lineage specific. Therefore, strains belonging to each serovar could be clustered separately based on their prophage content. Analysis of S. Enteritidis isolates from seven outbreaks generated distinct prophage profiles for each outbreak. Taken altogether, the diversity of the prophage sequences correlates with genome diversity. Prophage repertoires provide an additional marker for differentiating S. enterica subtypes during foodborne outbreaks.

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          A5-miseq: an updated pipeline to assemble microbial genomes from Illumina MiSeq data.

          Open-source bacterial genome assembly remains inaccessible to many biologists because of its complexity. Few software solutions exist that are capable of automating all steps in the process of de novo genome assembly from Illumina data.
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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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              Comparative genome analysis of Salmonella Enteritidis PT4 and Salmonella Gallinarum 287/91 provides insights into evolutionary and host adaptation pathways.

              We have determined the complete genome sequences of a host-promiscuous Salmonella enterica serovar Enteritidis PT4 isolate P125109 and a chicken-restricted Salmonella enterica serovar Gallinarum isolate 287/91. Genome comparisons between these and other Salmonella isolates indicate that S. Gallinarum 287/91 is a recently evolved descendent of S. Enteritidis. Significantly, the genome of S. Gallinarum has undergone extensive degradation through deletion and pseudogene formation. Comparison of the pseudogenes in S. Gallinarum with those identified previously in other host-adapted bacteria reveals the loss of many common functional traits and provides insights into possible mechanisms of host and tissue adaptation. We propose that experimental analysis in chickens and mice of S. Enteritidis-harboring mutations in functional homologs of the pseudogenes present in S. Gallinarum could provide an experimentally tractable route toward unraveling the genetic basis of host adaptation in S. enterica.
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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
                04 May 2018
                2018
                : 9
                : 836
                Affiliations
                [1] 1Department of Food Science and Agricultural Chemistry, McGill University , Ste Anne de Bellevue, QC, Canada
                [2] 2Department of Microbiology and Immunology, Faculty of Pharmacy, Mansoura University , Mansoura, Egypt
                [3] 3Ottawa Laboratory Fallowfield, Canadian Food Inspection Agency , Ottawa, ON, Canada
                [4] 4Laboratoire de Santé Publique du Québec, Institut National de Santé Publique due Québec , Ste Anne de Bellevue, QC, Canada
                [5] 5Institut de Biologie Intégrative et des Systèmes, Université Laval , Québec City, QC, Canada
                [6] 6Health Canada, Bureau of Microbial Hazards , Ottawa, ON, Canada
                [7] 7Institute of Parasitology, McGill University , Montreal, QC, Canada
                [8] 8Centre for Infectious Disease Control, National Institute for Public Health and the Environment , Bilthoven, Netherlands
                [9] 9National Microbiology Laboratory, Public Health Agency of Canada , Guelph, ON, Canada
                [10] 10Department of Biology, Wilfrid Laurier University , Waterloo, ON, Canada
                [11] 11Department of Microbiology and Immunology, McGill University , Montreal, QC, Canada
                [12] 12Department of Food Science, Cornell University , Ithaca, NY, United States
                [13] 13Département de Microbiologie, Infectiologie et Immunologie, Université de Montréal , Montreal, QC, Canada
                [14] 14Département de Biochimie, de Microbiologie et de Bioinformatique, Université Laval , Québec City, QC, Canada
                Author notes

                Edited by: Ludmila Chistoserdova, University of Washington, United States

                Reviewed by: Francisco Rodriguez-Valera, Universidad Miguel Hernández de Elche, Spain; Eric Altermann, AgResearch, New Zealand

                *Correspondence: Dele Ogunremi dele.ogunremi@ 123456inspection.gc.ca

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

                Article
                10.3389/fmicb.2018.00836
                5945981
                29780368
                3dde9491-0110-40ac-80cd-2957e4d1ee10
                Copyright © 2018 Mottawea, Duceppe, Dupras, Usongo, Jeukens, Freschi, Emond-Rheault, Hamel, Kukavica-Ibrulj, Boyle, Gill, Burnett, Franz, Arya, Weadge, Gruenheid, Wiedmann, Huang, Daigle, Moineau, Bekal, Levesque, Goodridge and Ogunremi.

                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) and the copyright owner 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.

                History
                : 12 December 2017
                : 12 April 2018
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 51, Pages: 13, Words: 8057
                Funding
                Funded by: Genome Canada 10.13039/100008762
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                salmonella,prophage sequence typing,genome diversity,outbreaks,enteritidis
                Microbiology & Virology
                salmonella, prophage sequence typing, genome diversity, outbreaks, enteritidis

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