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      An outbreak of a rare Shiga-toxin-producing Escherichia coli serotype (O117:H7) among men who have sex with men

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          Abstract

          Sexually transmissible enteric infections (STEIs) are commonly associated with transmission among men who have sex with men (MSM). In the past decade, the UK has experienced multiple parallel STEI emergences in MSM caused by a range of bacterial species of the genus Shigella, and an outbreak of an uncommon serotype (O117 : H7) of Shiga-toxin-producing Escherichia coli (STEC). Here, we used microbial genomics on 6 outbreak and 30 sporadic STEC O117 : H7 isolates to explore the origins and pathogenic drivers of the STEC O117 : H7 emergence in MSM. Using genomic epidemiology, we found that the STEC O117 : H7 outbreak lineage was potentially imported from Latin America and likely continues to circulate both in the UK MSM population and in Latin America. We found genomic relationships consistent with existing symptomatic evidence for chronic infection with this STEC serotype. Comparative genomic analysis indicated the existence of a novel Shiga toxin 1-encoding prophage in the outbreak isolates, and evidence of horizontal gene exchange among the STEC O117 : H7 outbreak lineage and other enteric pathogens. There was no evidence of increased virulence in the outbreak strains relative to contextual isolates, but the outbreak lineage was associated with azithromycin resistance. Comparing these findings with similar genomic investigations of emerging MSM-associated Shigella in the UK highlighted many parallels, the most striking of which was the importance of the azithromycin phenotype for STEI emergence in this patient group.

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          Toward almost closed genomes with GapFiller

          De novo assembly is a commonly used application of next-generation sequencing experiments. The ultimate goal is to puzzle millions of reads into one complete genome, although draft assemblies usually result in a number of gapped scaffold sequences. In this paper we propose an automated strategy, called GapFiller, to reliably close gaps within scaffolds using paired reads. The method shows good results on both bacterial and eukaryotic datasets, allowing only few errors. As a consequence, the amount of additional wetlab work needed to close a genome is drastically reduced. The software is available at http://www.baseclear.com/bioinformatics-tools/.
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            SNP-sites: rapid efficient extraction of SNPs from multi-FASTA alignments

            Rapidly decreasing genome sequencing costs have led to a proportionate increase in the number of samples used in prokaryotic population studies. Extracting single nucleotide polymorphisms (SNPs) from a large whole genome alignment is now a routine task, but existing tools have failed to scale efficiently with the increased size of studies. These tools are slow, memory inefficient and are installed through non-standard procedures. We present SNP-sites which can rapidly extract SNPs from a multi-FASTA alignment using modest resources and can output results in multiple formats for downstream analysis. SNPs can be extracted from a 8.3 GB alignment file (1842 taxa, 22 618 sites) in 267 seconds using 59 MB of RAM and 1 CPU core, making it feasible to run on modest computers. It is easy to install through the Debian and Homebrew package managers, and has been successfully tested on more than 20 operating systems. SNP-sites is implemented in C and is available under the open source license GNU GPL version 3.
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              Robust high-throughput prokaryote de novo assembly and improvement pipeline for Illumina data

              The rapidly reducing cost of bacterial genome sequencing has lead to its routine use in large-scale microbial analysis. Though mapping approaches can be used to find differences relative to the reference, many bacteria are subject to constant evolutionary pressures resulting in events such as the loss and gain of mobile genetic elements, horizontal gene transfer through recombination and genomic rearrangements. De novo assembly is the reconstruction of the underlying genome sequence, an essential step to understanding bacterial genome diversity. Here we present a high-throughput bacterial assembly and improvement pipeline that has been used to generate nearly 20 000 annotated draft genome assemblies in public databases. We demonstrate its performance on a public data set of 9404 genomes. We find all the genes used in multi-locus sequence typing schema present in 99.6 % of assembled genomes. When tested on low-, neutral- and high-GC organisms, more than 94 % of genes were present and completely intact. The pipeline has been proven to be scalable and robust with a wide variety of datasets without requiring human intervention. All of the software is available on GitHub under the GNU GPL open source license.
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                Author and article information

                Journal
                Microb Genom
                Microb Genom
                mgen
                mgen
                Microbial Genomics
                Microbiology Society
                2057-5858
                July 2018
                21 May 2018
                21 May 2018
                : 4
                : 7
                : e000181
                Affiliations
                [ 1]Institute for Integrative Biology, University of Liverpool , Liverpool, UK
                [ 2]Public Health England , Colindale, London, UK
                [ 3]Wellcome Trust Sanger Institute , Hinxton, UK
                Author notes
                *Correspondence: Kate S. Baker, Kate.Baker@ 123456liverpool.ac.uk
                Article
                mgen000181
                10.1099/mgen.0.000181
                6113874
                29781799
                27cae9ac-0c4f-4660-9c59-96635d61b47e

                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 work is properly cited.

                History
                : 19 December 2017
                : 25 April 2018
                Funding
                Funded by: Wellcome Trust
                Award ID: 106690/A/14/Z
                Categories
                Outbreak Report
                Microbial Evolution and Epidemiology: Communicable Disease Genomics

                stec,msm,antimicrobial resistance,outbreak
                stec, msm, antimicrobial resistance, outbreak

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