To Örebro University

Extensive gonococcal surveillance has been performed using molecular typing at global, regional, national and local levels. The three main genotyping schemes for this pathogen, multi-locus sequence typing (MLST), Neisseria gonorrhoeae multi-antigen sequence typing (NG-MAST) and N. gonorrhoeae sequence typing for antimicrobial resistance (NG-STAR), allow inter-laboratory and inter-study comparability and reproducibility and provide an approximation to the gonococcal population structure. With whole-genome sequencing (WGS), we obtain a substantially higher and more accurate discrimination between strains compared to previous molecular typing schemes. However, WGS remains unavailable or not affordable in many laboratories, and thus bioinformatic tools that allow the integration of data among laboratories with and without access to WGS are imperative for a joint effort to increase our understanding of global pathogen threats. Here, we present pyngoST, a command-line Python tool for fast, simultaneous and accurate sequence typing of N. gonorrhoeae from WGS assemblies. pyngoST integrates MLST, NG-MAST and NG-STAR, and can also designate NG-STAR clonal complexes, NG-MAST genogroups and penA mosaicism, facilitating multiple sequence typing from large WGS assembly collections. Exact and closest matches for existing alleles and sequence types are reported. The implementation of a fast multi-pattern searching algorithm allows pyngoST to be rapid and report results on 500 WGS assemblies in under 1 min. The mapping of typing results on a core genome tree of 2375 gonococcal genomes revealed that NG-STAR is the scheme that best represents the population structure of this pathogen, emphasizing the role of antimicrobial use and antimicrobial resistance as a driver of gonococcal evolution. This article contains data hosted by Microreact.