pyngoST: fast, simultaneous and accurate multiple sequence typing of Neisseria gonorrhoeae genome collections

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 high-throughput whole-genome sequencing (WGS), we obtain a substantially higher and more accurate discrimination between strains, i.e., compared to previous molecular typing schemes where isolates with the same sequence type often have a different genomic background. However, WGS remains unavailable or not affordable in many laboratories, accordingly, bioinformatic tools that allow the integration of data among laboratories with and without access to WGS is imperative for a joint effort to increase our understanding of global pathogen threats. Here, we present pyngoST, a command-line Python tool for a fast, simultaneous and accurate sequence typing of the WHO priority pathogen N. gonorrhoeae, from WGS assemblies. pyngoST integrates MLST, NG-MAST and NG-STAR, and can also designate NG-STAR clonal complexes and NG-MAST genogroups, facilitating multiple sequence typing from large WGS assembly collections. Exact matches for existing alleles and STs are reported, but also closest matches of new alleles and STs. The implementation of a fast multi-pattern searching algorithm allows pyngoST to be rapid and report results on 500 WGS assemblies in under 1 minute. The mapping of typing results on a core genome tree of 2,375 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 (AMR) as a driver of gonococcal evolution. IMPACT STATEMENT Molecular typing has been key for N. gonorrhoeae epidemiological and AMR surveillance, and WGS has revolutionized this typing. The most frequently used molecular typing schemes include MLST, NG-MAST and NG-STAR, and modifications of those. These schemes can be extracted from WGS assemblies for comparability and reproducibility of results with laboratories that do not have access to WGS technologies. pyngoST is a unique command-line Python tool that integrates all these common typing schemes under the same framework and performs rapid simultaneous user-defined multiple typing of large number of gonococcal genomes through a fast multi-pattern searching algorithm. Typing results on 2,375 gonococcal genomes revealed that NG-STAR best represents the genomic population structure of N. gonorrhoeae, highlighting the importance of antimicrobial use and AMR on the evolution of this pathogen. DATA SUMMARY pyngoST is written in Python 3 and is available from Github under the GPL-3.0 License (https://github.com/leosanbu/pyngoST). The script can be installed via the Python ‘pip’ package. Genome assemblies used in this study are from the Euro-GASP 2018 WGS survey and are available from Pathogenwatch: https://pathogen.watch/collection/eurogasp2018 (1,2). Pairwise single nucleotide polymorphism (SNP) distances among isolates from this dataset are also available from the same link. Results from running pyngoST on the Euro-GASP 2018 WGS dataset can be explored from Microreact: https://microreact.org/project/wYpBzCs9A6Uf7HEMA6zmmY-eurogasp2018-pyngost.