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

Details

• Alternative Title:
  Genome Med
• Personal Author:
  Sánchez-Busó, Leonor ; Yeats, Corin A. ; Taylor, Benjamin ; Goater, Richard J. ; Underwood, Anthony ; Abudahab, Khalil ; Argimón, Silvia ; Ma, Kevin C. ; Mortimer, Tatum D. ; Golparian, Daniel ; Cole, Michelle J. ; Grad, Yonatan H. ; Martin, Irene ; Raphael, Brian H. ; Shafer, William M. ; Town, Katy ; Wi, Teodora ; Harris, Simon R. ; Unemo, Magnus ; Aanensen, David M.
• Description:
  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.
  
  Additional File 2, Results of the GHRU assembly pipeline on 12,192 public N. gonorrhoeae genomes, is attached to this record in Supporting Files below..
  
  
• Subjects:
  Antimicrobial Resistance Epidemiology Genomics Neisseria Gonorrhoeae Pathogenwatch Public Health Research Surveillance
• Source:
  Genome Med. 13
• Pubmed ID:
  33875000
• Pubmed Central ID:
  PMC8054416
• Document Type:
  Journal Article
• Funding:
  R01 AI021150/AI/NIAID NIH HHSUnited States/ ; F32 AI145157/AI/NIAID NIH HHSUnited States/ ; R37 AI021150/AI/NIAID NIH HHSUnited States/ ; 16_136_111/DH_/Department of HealthUnited Kingdom/ ; R01 AI153521/AI/NIAID NIH HHSUnited States/ ; R01 AI147609/AI/NIAID NIH HHSUnited States/ ; R01 AI132606/AI/NIAID NIH HHSUnited States/ ; 001/WHO_/World Health OrganizationInternational/ ; IK6 BX005390/BX/BLRD VAUnited States/ ; F32 AI145157/AI/NIAID NIH HHSUnited States/
• Volume:
  13
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:cf7f09853153cd45d755ca0d52803a19d3e2fc2b68747d5c403a943c451dba7e65e89a3471ba38042fa03c97ac3d9c1a4ea4733614003cb6d5e3676e0e68a4b6
• Download URL:
  https://stacks.cdc.gov/view/cdc/111610/cdc_111610_DS1.pdf
• File Type:
  [PDF - 4.00 MB ]