Determining Streptococcus suis serotype from short-read whole-genome sequencing data.

Area of Science:

• Veterinary Microbiology
• Bioinformatics
• Genomics

Background:

• Streptococcus suis is classified into 29 serotypes based on capsular polysaccharide (CPS) serological reactions.
• Current multiplex PCR methods struggle to differentiate specific serotype pairs (1/14 and 2/1/2).

Purpose of the Study:

• To develop an in silico pipeline for accurate Streptococcus suis serotyping using whole-genome sequencing (WGS) data.
• To resolve ambiguities in differentiating S. suis serotypes 1/14 and 2/1/2.

Main Methods:

• Development of an automated bioinformatics pipeline utilizing WGS short-read data.
• Differential alignment of sequencing reads to a custom S. suis cps loci database.
• Identification of missense mutations in the cpsK gene for differentiating specific serotype pairs.

Main Results:

• The pipeline successfully identified all 29 S. suis serotypes.
• Differentiation between serotypes 1 and 14, and between 2 and 1/2 was achieved via cpsK gene mutation analysis.
• High concordance (99%) with coagglutination serotyping and 92% with external WGS data.

Conclusions:

• The developed pipeline offers rapid and accurate S. suis serotyping directly from WGS data.
• This approach resolves a 30-year-old challenge in S. suis serotype differentiation.
• The pipeline also provides insights into virulence markers and multilocus sequence typing.