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      Emergence of novel strains of Shigella flexneri associated with sexual transmission in adult men in England, 2019–2020

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          Abstract

          National surveillance of shigellosis in England revealed an increase in sexually transmitted Shigella flexneri in adult males in 2019 that persisted throughout 2020. We observed a resurgence of azithromycin-resistant S. flexneri serotype 3a, and the emergence of two novel multidrug-resistant clades of S. flexneri 2a and S. flexneri 1b.

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          Most cited references22

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

              Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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                Author and article information

                Journal
                J Med Microbiol
                J Med Microbiol
                jmm
                jmm
                Journal of Medical Microbiology
                Microbiology Society
                0022-2615
                1473-5644
                2021
                19 October 2021
                19 October 2021
                : 70
                : 10
                : 001437
                Affiliations
                [ 1] departmentNational Infection Service , Public Health England, 61 Colindale Avenue , London, UK
                Author notes
                *Correspondence: Claire Jenkins, Claire.Jenkins1@ 123456phe.gov.uk

                FASTQ reads from all sequences in this study can be found at the PHE Bioproject PRJNA315192.

                Author information
                https://orcid.org/0000-0002-3229-6198
                https://orcid.org/0000-0002-0497-8976
                https://orcid.org/0000-0001-8596-0649
                https://orcid.org/0000-0003-2090-7702
                https://orcid.org/0000-0002-5846-8517
                https://orcid.org/0000-0001-8600-9169
                Article
                001437
                10.1099/jmm.0.001437
                8604172
                34665107
                7fe88cc2-11fe-4afd-a4c4-8210cf753a7c
                © 2021 The Authors

                This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.

                History
                : 21 May 2021
                : 08 September 2021
                Funding
                Funded by: National Institute for Health Research Health Protection Research Unit
                Award Recipient : ClaireJenkins
                Categories
                Molecular and Microbial Epidemiology
                Custom metadata
                0

                Microbiology & Virology
                shigellosis,sexual transmission,surveillance,multidrug resistance
                Microbiology & Virology
                shigellosis, sexual transmission, surveillance, multidrug resistance

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