Prediction of Pasteurella multocida serotypes based on whole genomic sequences

Area of Science:

• Microbiology
• Genomics
• Bacterial Pathogenesis

Background:

• Pasteurella multocida is a significant bacterial pathogen with diverse serotypes impacting animal and human health.
• Accurate serotyping is crucial for epidemiological surveillance and understanding disease transmission.
• Traditional serotyping methods can be laborious and may lack precision for certain bacterial species.

Purpose of the Study:

• To develop and validate a whole genomic sequencing (WGS)-based method for predicting Pasteurella multocida serotypes.
• To identify specific target genes within capsular and lipopolysaccharide (LPS) regions for accurate typing.
• To establish a publicly accessible database (BIGSdb) for WGS-based bacterial isolate genome sequencing.

Main Methods:

• Whole genome sequencing of 56 Pasteurella multocida strains.
• Inclusion of publicly available assembled genomes from NCBI for comparative analysis.
• Installation of BIGSdb on a Linux server to define and target specific gene sequences for capsular types (A, B, D, E, F) and LPS groups (1-8).

Main Results:

• WGS predictions showed 87% correspondence with classical phenotypic typing for capsular types.
• WGS predictions demonstrated 82% correspondence with phenotypic typing for LPS groups.
• High success rates for WGS-based typing: 93% for capsular types and 94% for LPS groups.

Conclusions:

• Whole genomic sequencing provides a robust and accurate method for Pasteurella multocida serotyping.
• The defined WGS targets and BIGSdb server offer a valuable resource for bacterial isolate characterization.
• This WGS approach enhances epidemiological surveillance and diagnostic capabilities for Pasteurella multocida infections.