Developing genome typing strategies for the emerging zoonotic pathogen Streptococcus parasuis

The reported human infections with the emerging zoonotic pathogen Streptococcus parasuis are steadily rising. Rapid and standardized genotyping tools specific to S. parasuis are critically needed for epidemiological surveillance and identification of strains with zoonotic potential. This study developed a whole-genome sequence (WGS)-based typing strategy, encompassing average nucleotide identity, a minimum core genome (MCG) typing scheme, and a multilocus sequence typing (MLST) scheme using 255 S. parasuis genomes isolated from eight countries between the 1980s and 2024. The S. parasuis population was categorized into 12 MCG clusters based on 72,172 SNPs in non-recombining regions distributed across an MCG comprising 607 genes, forming two distinct lineages. The rapid MCG typing program accurately assigned 92.5% of S. parasuis genomes to their corresponding MCG clusters by identifying 4,509 cluster/subcluster-specific SNPs. To elucidate the clonal relationships among S. parasuis genomes, an MLST scheme was developed, defining 161 sequence types (STs) based on the allelic profiles of seven housekeeping loci (aroA, cpn60, gki, mutS, sdhA, recA, and thrA). Thirty-two STs that shared identical alleles at 6 loci were assigned to 10 complex clones, whereas 100 STs that shared identical alleles at 4 or more loci were grouped into 9 ST clades. The MCG typing scheme and the MLST scheme demonstrated sufficient discriminatory power, with Simpson's diversity index values of 0.8864 and 0.9821, respectively. This study characterized the S. parasuis population and provided a rapid, reproducible, and expandable WGS-based typing strategy for taxonomic identification, epidemiological surveillance, and evaluation of the zoonotic potential of S. parasuis.IMPORTANCEOur study provides valuable insights for developing effective prevention and control strategies for Streptococcus parasuis infections, by revealing the structural characteristics and phylogenetic relationship of S. parasuis population, by developing a whole-genome sequence-based typing strategy applicable for epidemiological surveillance, transmission investigation, and zoonotic potential evaluation.