The antimicrobial resistance landscape of Neisseria gonorrhoeae in New Zealand from November 2018 to March 2019 and the role of sexual orientation in transmission

Abstract

The increasing use of culture independent diagnostic testing for the diagnosis of Neisseria gonorrhoeae infection has led to gaps in surveillance of antimicrobial resistance (AMR) rates due to limited availability of cultures. Our study reports the findings of a second national survey of N. gonorrhoeae in New Zealand, utilizing whole-genome sequencing (WGS) to study the population structure, prevalence of AMR, epidemiology and transmission of gonorrhoea isolates. We analysed 314 isolates and found a strong correlation between carriage of acquired resistance genes or chromosomal point mutations and phenotypic susceptibility testing results. Overall, the New Zealand rates of azithromycin resistance and decreased susceptibility to ceftriaxone remain lower than in most countries, which are part of the World Health Organization (WHO) Global Gonococcal Antimicrobial Surveillance Programme (GASP). The phylogeny provides evidence of a diverse population significantly associated with sexual behaviour groups. Transmission clustering with a ten single nucleotide polymorphism (SNP) cut-off identified 49 clusters, of which ten were solely associated with men who have sex with men (MSM), whereas remaining clusters included heterosexual patients, as well as MSM, suggesting that bridging of sexual networks is occurring. Utilizing pairwise SNP differences between isolates of the same sequence types we determined genetic variation for the three typing schemes used in this study [Multi locus sequence typing (MLST), multi-antigen sequence typing (NG-MAST), and sequence typing for antimicrobial resistance (NG-STAR)]. A median of 0.0 to 52.5 pairwise SNP differences within a single NG-STAR sequence type underlines previous findings of the superiority of the NG-STAR typing scheme in terms of genomic inherency. With our analysis incorporating epidemiological and genomic data, we were able to show a comprehensive overview of the N. gonorrhoeae population circulating in New Zealand, focussing on AMR and transmission within sexual networks. Regular surveillance studies to understand the origin, evolution and spread of AMR for gonorrhoea remain necessary to make informed decisions about public health guidelines, as the internationally rising rates of ceftriaxone and azithromycin resistance have already led to adaptation of current treatment guidelines in the UK and the USA, highlighting the importance of regular surveillance in individual countries.

Keywords: Gonorrhoea; MSM; clustering; population genomics; single nucleotide polymorphisms; typing.

Fig. 1.

Population structure of N. gonorrhoeae circulating in New Zealand in 2018–2019. The maximum-likelihood phylogeny is based on 314 N . gonorrhoeae isolates and the reference strain FA1090. The ML tree was built using iqtree and is based on a recombinant-free core genome alignment of 5,059 sites. The inner ring represents the sex of the patient, the outer ring illustrates the first level of clustering for Bayesian analysis of population structure (BAPS).

Fig. 2.

Maximum-likelihood phylogeny for the combined dataset from both national surveys. In total, 314 isolates from this dataset were combined with 401 isolates from the 2014/2015 study [23]. ML phylogeny was built based on a core-genome alignment of 4813 sites with 3269 informative sites. All samples from the 2014/2015 survey are highlighted in yellow and the isolates from 2018/2019 are illustrated in blue (inner ring). The outer ring illustrates the seven mixed transmission clusters, with isolates from 2014/2015 and 2018/2019.

Fig. 3.

Transmission cluster analysis based on pairwise SNP-distances and a cut-off threshold of ten SNPs. (a) Highlighting clusters with>=9 isolates. (b) Cluster composition of patients sexual orientation. Cluster composition of patients sexual orientation. (c)Age range of patients whose isolates were assigned to cluster and sexual orientation highlighted. Age range of patients whose isolates were assigned to cluster and sexual orientation highlighted.

Fig. 4.

Pairwise SNP distance identified within MLST, NGSTAR and NGMAST sequence types. From each calculated pairwise SNP distance, both isolates had to be of the same type (MLST, NGSTAR or NGMAST) to be grouped. Only sequence types with n>1 are displayed.