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

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.

Keywords: Antimicrobial resistance; Epidemiology; Genomics; Neisseria gonorrhoeae; Pathogenwatch; Public health; Surveillance.

Fig. 1

Main workflow in Pathogenwatch. New genomes can be uploaded and combined with public data for contextualisation. The collection view allows data exploration through a combined phylogenetic tree, a map, a timeline and the metadata table, which can be switched to show typing information (multi-locus sequence typing, MLST; N. gonorrhoeae sequence typing for antimicrobial resistance, NG-STAR; and N. gonorrhoeae multi-antigen sequence typing, NG-MAST) as well as known genetic AMR mechanisms for eight antibiotics. Genome reports summarise the metadata, typing and AMR marker results for individual isolates and allow finding other close genomes in Pathogenwatch based on core genome MLST (cgMLST). SNPs: single-nucleotide polymorphisms

Fig. 2

Main display of a Pathogenwatch collection, showing a phylogenetic tree, a map and a table of SNPs associated with AMR of 395 N. gonorrhoeae genomes from a global study [65, 112]. Isolates carrying three mosaic penA marker mutations are marked in red in the tree and the map. The table can be switched to show the metadata, a timeline, typing results (multi-locus sequence typing, MLST; N. gonorrhoeae sequence typing for antimicrobial resistance, NG-STAR and N. gonorrhoeae multi-antigen sequence typing, NG-MAST) and AMR analytics (known genetic mechanisms and genotypic AMR prediction) implemented in the platform. Further detail is shown in Additional file 3: Fig. S1. The contents of and boundaries in the map are the sole responsibility of Pathogenwatch and do not necessarily reflect the views or opinions of WHO or other Public Health Agency

Fig. 3

Distribution of minimum inhibitory concentration (MIC) values (mg/L) for the last-line antibiotics for N. gonorrhoeae azithromycin (a) and ceftriaxone (b) in a collection of 3987 N. gonorrhoeae isolates with different combinations of genetic antimicrobial resistance (AMR) mechanisms. Only combinations observed in at least 5 isolates are shown (see Additional file 3: Fig. S5-S10 for expanded plots for six antibiotics). Dashed horizontal lines on the violin plots mark the EUCAST epidemiological cut-off (ECOFF) for azithromycin and EUCAST clinical breakpoint for ceftriaxone. Point colours inside violins represent the genotypic AMR prediction by Pathogenwatch on each combination of mechanisms (indicated in the grid below by black circles connected vertically; horizontal thick grey lines connect combinations of mechanisms that share an individual determinant). Barplots on the top show the abundance of isolates with each combination of mechanisms. Bar colours represent the differences between the predicted (Pred SIR) and the observed SIR (Obs SIR), i.e. red for a predicted susceptible mechanism when the observed phenotype is resistant). c Radar plots comparing the sensitivity, specificity, positive and negative predictive values (PPV/NPV) for six antibiotics for the test and validation benchmark analyses. AZM = azithromycin, CFM = cefixime, CIP = ciprofloxacin, CRO = ceftriaxone, PEN = benzylpenicillin, TET = tetracycline

Fig. 4

Summary of the geolocalization and collection date of 12,515 public N. gonorrhoeae genomes in Pathogenwatch. Coloured bars represent the genotypic antimicrobial resistance (AMR) prediction based on the mechanisms included in the library. AZM = azithromycin, CFM = cefixime, CIP = ciprofloxacin, CRO = ceftriaxone, PEN = benzylpenicillin, TET = tetracycline

Fig. 5

Predicted antimicrobial resistance (AMR) profiles of the top five multi-locus sequence typing (MLST), N. gonorrhoeae sequence typing for antimicrobial resistance (NG-STAR) and N. gonorrhoeae multi-antigen sequence typing (NG-MAST) types in the N. gonorrhoeae public data in Pathogenwatch. Coloured circles in the grids show the proportion of genomes from each ST which are predicted to have an intermediate (susceptible but increased exposure) or resistant phenotype (in red) versus susceptible genomes (in dark blue) from each sequence type (ST) and antibiotic. Bars on the top show the number of isolates from each ST coloured by the number of antibiotics the genomes are predicted to be resistant to

Fig. 6

N. gonorrhoeae genomes carrying genetic AMR mechanisms associated with azithromycin resistance were selected in Pathogenwatch (n = 1142) and combined with genomes from a global collection [65, 112] (total n = 1528) for background contextualization. a Main layout of the combined collection, with an emerging lineage carrying an N. lactamica-like mtr mosaic (‘mtr_mosaic.2’) spanning the mtrR promoter and mtrD marked in red in the tree and the map. b Timeline of the genomes carrying mtr mosaic 2 (in red) and other public genomes in the database without this genetic AMR mechanism. c Visualisation of the mtr mosaic 2-carrying lineage (n = 520) spreading in the USA and Australia (see legend) using Microreact. The arrow in turquoise colour marks the divergence of the Australian lineage, shown in more detail in d coloured by the presence (in red) or absence (in white) of the porB1b G120K and A121N mutations. The Pathogenwatch project of this case study can be explored in [135]. The contents of and boundaries in the map are the sole responsibility of Pathogenwatch and do not necessarily reflect the views or opinions of WHO or other Public Health Agency