In Silico Typing and Identification Confirmation of Isolates.

Abstract

Streptococcus suis is an important zoonotic pathogen causing severe infections in pigs and humans. Serotyping of S. suis strains is crucial for epidemiological surveillance, outbreak investigations, and understanding the pathogenesis of this bacterium. Here, we describe a step-by-step approach that enhances a previously developed pipeline by utilizing a computational script for efficient and accurate typing of S. suis strains. The pipeline is implemented in Perl programming language and leverages the Short Read Sequence Typing for Bacterial Pathogens (SRST2) tool. It integrates various bioinformatics techniques and utilizes multiple databases, including a serotype database, cpsH confirmation database, multi-locus sequence typing (MLST) database, recN species-specific gene database, and virulence gene database. These databases contain comprehensive information on S. suis serotypes, genetic markers, and virulence factors. The script can utilize paired-end or single-end fastq files as input and first confirms the species by sequence read data aligning to the recN gene, ensuring the accurate identification of S. suis strains. The pipeline next performs MLST typing and virulence factor identification using SRST2 while in a parallel processes it performs in silico serotyping of the strains. The pipeline offers a streamlined and semiautomated approach to serotyping S. suis strains, facilitating large-scale studies and reducing the manual effort required for data analysis.