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      Neisseria gonorrhoeae clustering to reveal major European whole-genome-sequencing-based genogroups in association with antimicrobial resistance

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          Abstract

          Neisseria gonorrhoeae , the bacterium responsible for the sexually transmitted disease gonorrhoea, has shown an extraordinary ability to develop antimicrobial resistance (AMR) to multiple classes of antimicrobials. With no available vaccine, managing N. gonorrhoeae infections demands effective preventive measures, antibiotic treatment and epidemiological surveillance. The latter two are progressively being supported by the generation of whole-genome sequencing (WGS) data on behalf of national and international surveillance programmes. In this context, this study aims to perform N. gonorrhoeae clustering into genogroups based on WGS data, for enhanced prospective laboratory surveillance. Particularly, it aims to identify the major circulating WGS-genogroups in Europe and to establish a relationship between these and AMR. Ultimately, it enriches public databases by contributing with WGS data from Portuguese isolates spanning 15 years of surveillance. A total of 3791 carefully inspected N. gonorrhoeae genomes from isolates collected across Europe were analysed using a gene-by-gene approach (i.e. using cgMLST). Analysis of cluster composition and stability allowed the classification of isolates into a two-step hierarchical genogroup level determined by two allelic distance thresholds revealing cluster stability. Genogroup clustering in general agreed with available N. gonorrhoeae typing methods [i.e. MLST (multilocus sequence typing), NG-MAST ( N. gonorrhoeae multi-antigen sequence typing) and PubMLST core-genome groups], highlighting the predominant genogroups circulating in Europe, and revealed that the vast majority of the genogroups present a dominant AMR profile. Additionally, a non-static gene-by-gene approach combined with a more discriminatory threshold for potential epidemiological linkage enabled us to match data with previous reports on outbreaks or transmission chains. In conclusion, this genogroup assignment allows a comprehensive analysis of N. gonorrhoeae genetic diversity and the identification of the WGS-based genogroups circulating in Europe, while facilitating the assessment (and continuous monitoring) of their frequency, geographical dispersion and potential association with specific AMR signatures. This strategy may benefit public-health actions through the prioritization of genogroups to be controlled, the identification of emerging resistance carriage, and the potential facilitation of data sharing and communication.

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          Most cited references75

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

            The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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              Pilon: An Integrated Tool for Comprehensive Microbial Variant Detection and Genome Assembly Improvement

              Advances in modern sequencing technologies allow us to generate sufficient data to analyze hundreds of bacterial genomes from a single machine in a single day. This potential for sequencing massive numbers of genomes calls for fully automated methods to produce high-quality assemblies and variant calls. We introduce Pilon, a fully automated, all-in-one tool for correcting draft assemblies and calling sequence variants of multiple sizes, including very large insertions and deletions. Pilon works with many types of sequence data, but is particularly strong when supplied with paired end data from two Illumina libraries with small e.g., 180 bp and large e.g., 3–5 Kb inserts. Pilon significantly improves draft genome assemblies by correcting bases, fixing mis-assemblies and filling gaps. For both haploid and diploid genomes, Pilon produces more contiguous genomes with fewer errors, enabling identification of more biologically relevant genes. Furthermore, Pilon identifies small variants with high accuracy as compared to state-of-the-art tools and is unique in its ability to accurately identify large sequence variants including duplications and resolve large insertions. Pilon is being used to improve the assemblies of thousands of new genomes and to identify variants from thousands of clinically relevant bacterial strains. Pilon is freely available as open source software.
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                Author and article information

                Journal
                Microb Genom
                Microb Genom
                mgen
                mgen
                Microbial Genomics
                Microbiology Society
                2057-5858
                February 2021
                27 November 2020
                27 November 2020
                : 7
                : 2
                : 000481
                Affiliations
                [ 1] departmentBioinformatics Unit , Department of Infectious Diseases, National Institute of Health , 1649-016 Lisbon, Portugal
                [ 2] departmentLaboratory of Microbiology , Department of Infectious Diseases, National Institute of Health , 1649-016 Lisbon, Portugal
                [ 3] departmentTechnology and Innovation Unit , Department of Human Genetics, National Institute of Health , Lisbon, Portugal
                [ 4] departmentCentre for Toxicogenomics and Human Health (ToxOmics) , Genetics, Oncology and Human Toxicology, Nova Medical School/Faculty of Medical Sciences, New University of Lisbon , Lisbon, Portugal
                [ 5] departmentReference Laboratory of Bacterial Sexually Transmitted Infections , Department of Infectious Diseases, National Institute of Health , 1649-016 Lisbon, Portugal
                Author notes
                *Correspondence: João Paulo Gomes, j.paulo.gomes@ 123456insa.min-saude.pt
                Author information
                https://orcid.org/0000-0001-6370-3051
                https://orcid.org/0000-0003-3767-2209
                https://orcid.org/0000-0002-8529-9878
                https://orcid.org/0000-0003-4118-7062
                https://orcid.org/0000-0002-8604-8800
                https://orcid.org/0000-0002-2697-2399
                Article
                000481
                10.1099/mgen.0.000481
                8208699
                33245688
                3ea48855-5fe0-4be0-a1cd-e104441f6257
                © 2021 The Authors

                This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License.

                History
                : 17 July 2020
                : 04 November 2020
                Funding
                Funded by: Fundação para a Ciência e a Tecnologia
                Award ID: POCI-01-0145-FEDER-022184
                Funded by: Fundação para a Ciência e a Tecnologia
                Award ID: SFRH/BD/109264/2015
                Categories
                Research Article
                Microbial evolution and epidemiology: Population Genomics
                Custom metadata
                0

                antimicrobial resistance,molecular epidemiology,neisseria gonorrhoeae,whole-genome sequencing

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