A community-driven resource for genomic surveillance of Neisseria gonorrhoeae at Pathogenwatch

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. With new treatment options not yet available, this has prompted a call for collaborative action on global surveillance for this sexually transmitted pathogen. Whole genome sequencing (WGS) data can be used to identify new AMR clones, outbreaks, 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 using Pathogenwatch (https://pathogen.watch/ngonorrhoeae), which enables the processing of raw or assembled genomic data. We implement backwards compatibility with MLST, NG-MAST and NG-STAR typing schemes as well as an exhaustive library of genetic AMR determinants associated with 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 An international advisory group of experts in epidemiology, public health, genetics and genomics of N. gonorrhoeae was convened to identify public health needs in the field and inform on the utility of current and future analytics in the platform, including a customised library of genetic AMR determinants. After uploading genome data, this platform automatically provides typing information, detects genetic determinants of AMR for eight antibiotics including azithromycin and the extended-spectrum cephalosporins ceftriaxone and cefixime, and infers resistance based on the specific combination of mechanisms. Furthermore, genomes are contextualised with globally available genomic data to aid epidemiological investigation. Conclusions The N. gonorrhoeae scheme in Pathogenwatch provides customized 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. This advisory group will assess and identify ongoing public health needs in the field of gonococcal AMR in order to further enhance utility with modified or new analytic methods.