19
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A community-driven resource for genomic epidemiology and antimicrobial resistance prediction of Neisseria gonorrhoeae at Pathogenwatch

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Antimicrobial-resistant (AMR) Neisseria gonorrhoeae is an urgent threat to public health, as strains resistant to at least one of the two last-line antibiotics used in empiric therapy of gonorrhoea, ceftriaxone and azithromycin, have spread internationally. Whole genome sequencing (WGS) data can be used to identify new AMR clones and transmission networks and inform the development of point-of-care tests for antimicrobial susceptibility, novel antimicrobials and vaccines. Community-driven tools that provide an easy access to and analysis of genomic and epidemiological data is the way forward for public health surveillance.

          Methods

          Here we present a public health-focussed scheme for genomic epidemiology of N. gonorrhoeae at Pathogenwatch ( https://pathogen.watch/ngonorrhoeae). An international advisory group of experts in epidemiology, public health, genetics and genomics of N. gonorrhoeae was convened to inform on the utility of current and future analytics in the platform. We implement backwards compatibility with MLST, NG-MAST and NG-STAR typing schemes as well as an exhaustive library of genetic AMR determinants linked to a genotypic prediction of resistance to eight antibiotics. A collection of over 12,000 N. gonorrhoeae genome sequences from public archives has been quality-checked, assembled and made public together with available metadata for contextualization.

          Results

          AMR prediction from genome data revealed specificity values over 99% for azithromycin, ciprofloxacin and ceftriaxone and sensitivity values around 99% for benzylpenicillin and tetracycline. A case study using the Pathogenwatch collection of N. gonorrhoeae public genomes showed the global expansion of an azithromycin-resistant lineage carrying a mosaic mtr over at least the last 10 years, emphasising the power of Pathogenwatch to explore and evaluate genomic epidemiology questions of public health concern.

          Conclusions

          The N. gonorrhoeae scheme in Pathogenwatch provides customised bioinformatic pipelines guided by expert opinion that can be adapted to public health agencies and departments with little expertise in bioinformatics and lower-resourced settings with internet connection but limited computational infrastructure. The advisory group will assess and identify ongoing public health needs in the field of gonorrhoea, particularly regarding gonococcal AMR, in order to further enhance utility with modified or new analytic methods.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13073-021-00858-2.

          Related collections

          Most cited references104

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              FLASH: fast length adjustment of short reads to improve genome assemblies.

              Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome. We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds. The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash. t.magoc@gmail.com.
                Bookmark

                Author and article information

                Contributors
                leo.sanchez-buso@cgps.group , sanchez_leobus@gva.es
                david.aanensen@cgps.group
                Journal
                Genome Med
                Genome Med
                Genome Medicine
                BioMed Central (London )
                1756-994X
                19 April 2021
                19 April 2021
                2021
                : 13
                : 61
                Affiliations
                [1 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, , University of Oxford, ; Oxford, Oxfordshire UK
                [2 ]GRID grid.428862.2, Genomics and Health Area, Foundation for the Promotion of Health and Biomedical Research in the Valencian Community (FISABIO-Public Health), ; Valencia, Spain
                [3 ]GRID grid.10306.34, ISNI 0000 0004 0606 5382, Centre for Genomic Pathogen Surveillance, , Wellcome Sanger Institute, Wellcome Genome Campus, ; Cambridge, Cambridgeshire UK
                [4 ]GRID grid.4709.a, ISNI 0000 0004 0495 846X, European Molecular Biology Lab, ; Heidelberg, Baden-Wuerttemberg Germany
                [5 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Immunology and Infectious Diseases, , Harvard T. H. Chan School of Public Health, ; Boston, MA USA
                [6 ]GRID grid.15895.30, ISNI 0000 0001 0738 8966, World Health Organization Collaborating Centre for Gonorrhoea and Other STIs, Department of Laboratory Medicine, Faculty of Medicine and Health, , Örebro University, ; Örebro, Sweden
                [7 ]GRID grid.271308.f, ISNI 0000 0004 5909 016X, National Infection Service, , Public Health England, ; London, UK
                [8 ]GRID grid.38142.3c, ISNI 000000041936754X, Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, , Harvard Medical School, ; Boston, MA USA
                [9 ]GRID grid.415368.d, ISNI 0000 0001 0805 4386, National Microbiology Laboratory, , Public Health Agency of Canada, ; Winnipeg, Manitoba Canada
                [10 ]GRID grid.416738.f, ISNI 0000 0001 2163 0069, Division of STD prevention, National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, , Centers for Disease Control and Prevention, ; Atlanta, GA USA
                [11 ]GRID grid.189967.8, ISNI 0000 0001 0941 6502, Department of Microbiology and Immunology and Emory Antibiotic Resistance Center, , Emory University School of Medicine, ; Atlanta, GA USA
                [12 ]GRID grid.414026.5, ISNI 0000 0004 0419 4084, Laboratories of Bacterial Pathogenesis, , Veterans Affairs Medical Center, ; Decatur, GA USA
                [13 ]GRID grid.3575.4, ISNI 0000000121633745, Department of the Global HIV, Hepatitis and STI Programmes, , World Health Organization, ; Geneva, Switzerland
                [14 ]Microbiotica, Biodata Innovation Centre, Cambridge, Cambridgeshire UK
                Author information
                http://orcid.org/0000-0002-4162-0228
                Article
                858
                10.1186/s13073-021-00858-2
                8054416
                33875000
                56dc6dd0-1a0f-4ffe-a63a-a6642f20ebcd
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 3 July 2020
                : 22 February 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Funded by: FundRef http://dx.doi.org/10.13039/100007421, Li Ka Shing Foundation;
                Funded by: FundRef http://dx.doi.org/10.13039/501100000272, National Institute for Health Research;
                Award ID: 16_136_111
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: R01 AI132606
                Award ID: 1 F32 AI145157-01
                Award ID: R01 AI153521
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: DGE1745303
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: R37 AI-021150
                Award ID: R01 AI-147609
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000805, European Centre for Disease Prevention and Control;
                Funded by: FundRef http://dx.doi.org/10.13039/100004423, World Health Organization;
                Funded by: FundRef http://dx.doi.org/10.13039/501100011597, Conselleria de Sanitat Universal i Salut Pública;
                Award ID: Plan GenT CDEI-06/20-B
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Molecular medicine
                neisseria gonorrhoeae,pathogenwatch,public health,genomics,epidemiology,surveillance,antimicrobial resistance

                Comments

                Comment on this article