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A community-driven resource for genomic epidemiology and antimicrobial resistance prediction of Neisseria gonorrhoeae at Pathogenwatch
Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK; Genomics and Health Area, Foundation for the Promotion of Health and Biomedical Research in the Valencian Community (FISABIO-Public Health), Valencia, Spain.
Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK.
Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK; Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK.
Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK; European Molecular Biology Lab, Heidelberg, Baden-Wuerttemberg, Germany.
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2021 (English)In: Genome Medicine, E-ISSN 1756-994X, Vol. 13, no 1, article id 61Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
BioMed Central, 2021. Vol. 13, no 1, article id 61
Keywords [en]
Antimicrobial resistance, Epidemiology, Genomics, Neisseria gonorrhoeae, Pathogenwatch, Public health, Surveillance
National Category
Infectious Medicine
Identifiers
URN: urn:nbn:se:oru:diva-91343DOI: 10.1186/s13073-021-00858-2ISI: 000641712700003PubMedID: 33875000Scopus ID: 2-s2.0-85104510157OAI: oai:DiVA.org:oru-91343DiVA, id: diva2:1546189
Funder
Wellcome trust, 099202
Note

Funding Agencies:

Li Ka Shing Foundation (Big Data Institute, University of Oxford) 

Centre for Genomic Pathogen Surveillance (CGPS)  

Plan GenT, Conselleria de Sanitat Universal i Salut Publica, Generalitat Valenciana (Valencia, Spain) CDEI-06/20-B

National Institute for Health Research (UK) Global Health Research Unit on Genomic Surveillance of AMR 16_136_111

European Centre for Disease Prevention and Control  

National Institute for Health Research (Health Protection Research Unit)  

United States Department of Health & Human Services

National Institutes of Health (NIH) - USA

NIH National Institute of Allergy & Infectious Diseases (NIAID) R01 AI132606 R01 AI153521

National Science Foundation (NSF)

NSF - Office of the Director (OD) DGE1745303

United States Department of Health & Human Services

National Institutes of Health (NIH) - USA

NIH National Institute of Allergy & Infectious Diseases (NIAID) 1 F32 AI145157-01

Biomedical Laboratory Research and Development Service of the Department of Veterans  

United States Department of Health & Human Services

National Institutes of Health (NIH) - USA R37 AI-021150

R01 AI-147609

World Health Organization

European Commission

Available from: 2021-04-21 Created: 2021-04-21 Last updated: 2024-07-04Bibliographically approved

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Golparian, DanielUnemo, Magnus

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