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

Leonor Sánchez-Busó*, Corin A. Yeats, Benjamin Taylor, Richard J. Goater, Anthony Underwood, Khalil Abudahab, Silvia Argimón, Kevin C. Ma, Tatum D. Mortimer, Daniel Golparian, Michelle J. Cole, Yonatan H. Grad, Irene Martin, Brian H. Raphael, William M. Shafer, Katy Town, Teodora Wi, Simon R. Harris, Magnus Unemo, David M. Aanensen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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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.

Original languageEnglish
Article number61
Number of pages22
JournalGenome Medicine
Volume13
Issue number1
DOIs
Publication statusPublished - 19 Apr 2021

Bibliographical note

Funding Information: Pathogenwatch is developed with support from Li Ka Shing Foundation (Big Data Institute, University of Oxford) and Wellcome (099202). At the time of preparation of this manuscript, LSB was supported by the Li Ka Shing Foundation (Big Data Institute, University of Oxford) and the Centre for Genomic Pathogen Surveillance (CGPS, https://www.pathogensurveillance.net/ ). At the time of review and publication of this manuscript, LSB is funded by Plan GenT (CDEI-06/20-B), Conselleria de Sanitat Universal i Salut Pública, Generalitat Valenciana (Valencia, Spain). DMA is supported by the Li Ka Shing Foundation (Big Data Institute, University of Oxford) and the Centre for Genomic Pathogen Surveillance (CGPS). DMA and SA are supported by the National Institute for Health Research (UK) Global Health Research Unit on Genomic Surveillance of AMR (16_136_111). The department of MJC receives funding from the European Centre for Disease Prevention and Control and the National Institute for Health Research (Health Protection Research Unit) for gonococcal whole-genome sequencing. YHG is supported by the NIH/NIAID grants R01 AI132606 and R01 AI153521. KCM is supported by the NSF GRFP grant number DGE1745303. TDM is supported by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health [1 F32 AI145157-01]. WMS is a recipient of a Senior Research Career Scientist Award from the Biomedical Laboratory Research and Development Service of the Department of Veterans. Work on antibiotic resistance in his laboratory is supported by NIH grants R37 AI-021150 and R01 AI-147609. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the Department of Veterans Affairs, The National Institutes of Health or the United States Government. The findings and conclusions in this article are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention. The WHO Collaborating Centre for Gonorrhoea and other STIs represented by DG and MU receives funding from the European Centre for Disease Prevention and Control and the World Health Organization. This publication made use of the Neisseria Multi-Locus Sequence Typing website ( https://pubmlst.org/neisseria/ ) sited at the University of Oxford [] and funded by Wellcome and European Union.

Open Access This 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.

Publisher Copyright: © 2021, The Author(s).

Citation: Sánchez-Busó, L., Yeats, C.A., Taylor, B. et al. A community-driven resource for genomic epidemiology and antimicrobial resistance prediction of Neisseria gonorrhoeae at Pathogenwatch. Genome Med 13, 61 (2021).

DOI: https://doi.org/10.1186/s13073-021-00858-2

Keywords

  • Antimicrobial resistance
  • Epidemiology
  • Genomics
  • Neisseria gonorrhoeae
  • Pathogenwatch
  • Public health
  • Surveillance
  • REDUCED SUSCEPTIBILITY
  • POINT MUTATION
  • MTRE EFFLUX PUMP
  • TETRACYCLINE RESISTANCE
  • HIGH-LEVEL RESISTANCE
  • AZITHROMYCIN
  • RIBOSOMAL-RNA
  • IDENTIFICATION
  • EXPANDED-SPECTRUM CEPHALOSPORINS
  • MACROLIDE RESISTANCE

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