A Practical Bioinformatics Workflow for Routine Analysis of Bacterial WGS Data.

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Whole-genome sequencing (WGS) adoption for bacterial characterization has surged due to high throughput and reduced costs.
• WGS significantly impacts pathogen surveillance and outbreak investigations but faces hurdles in data analysis, management, and standardization for routine use.

Purpose of the Study:

• To develop and present a standardized bioinformatics workflow for bacterial characterization using Illumina WGS data.
• To address the limitations hindering the routine integration of WGS in microbiology.

Main Methods:

• A comprehensive bioinformatics workflow was developed for bacterial characterization.
• The workflow includes genome annotation, species identification, serotype and antimicrobial resistance prediction, virulence gene detection, and phylogenetic analysis.
• It was validated using 22 in-house *Salmonella enterica* isolates and 182 public *Salmonella* genomes.

Main Results:

• The workflow successfully analyzed all tested *Salmonella* genomes without errors.
• It provides a standardized approach for multiple WGS-based bacterial characterization tasks.
• The workflow is adaptable for other bacterial pathogens.

Conclusions:

• The presented bioinformatics workflow enhances the utility of WGS for bacterial characterization.
• It offers a standardized, robust, and adaptable solution for pathogen surveillance and outbreak investigations.
• The workflow is freely available on the Galaxy platform for academic and non-profit use.