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
Author Information
Leonor Sánchez-Busó: Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK. leo.sanchez-buso@cgps.group. ORCID
Corin A Yeats: Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK.
Benjamin Taylor: Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK.
Richard J Goater: Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK.
Anthony Underwood: Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK.
Khalil Abudahab: Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK.
Silvia Argimón: Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK.
Kevin C Ma: Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Tatum D Mortimer: Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Daniel Golparian: World Health Organization Collaborating Centre for Gonorrhoea and Other STIs, Department of Laboratory Medicine, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
Michelle J Cole: National Infection Service, Public Health England, London, UK.
Yonatan H Grad: Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Irene Martin: National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada.
Brian H Raphael: Division of STD prevention, National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA.
William M Shafer: Department of Microbiology and Immunology and Emory Antibiotic Resistance Center, Emory University School of Medicine, Atlanta, GA, USA.
Katy Town: Division of STD prevention, National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Teodora Wi: Department of the Global HIV, Hepatitis and STI Programmes, World Health Organization, Geneva, Switzerland.
Simon R Harris: Microbiotica, Biodata Innovation Centre, Cambridge, Cambridgeshire, UK.
Magnus Unemo: World Health Organization Collaborating Centre for Gonorrhoea and Other STIs, Department of Laboratory Medicine, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
David M Aanensen: Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK. david.aanensen@cgps.group.
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.
