Evaluating whole-genome sequencing quality metrics for enteric pathogen outbreaks

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Whole genome sequencing (WGS) is vital for tracking enteric bacterial outbreaks.
• WGS data quality directly impacts the accuracy of single nucleotide polymorphism (SNP) analysis and genome assembly.
• Key quality metrics include PHRED score, read length, insert size, and ambiguous nucleotide composition.

Purpose of the Study:

• To assess the impact of WGS data quality metrics on bacterial outbreak analysis.
• To compare the effectiveness of various read-healing pipelines in improving WGS data quality for SNP analysis and genome assembly.
• To identify optimal strategies for enhancing WGS data for enteric pathogen surveillance.

Main Methods:

• Characterized WGS reads from *Escherichia coli*, *Salmonella enterica*, and *Shigella sonnei* outbreak clusters for four quality metrics.
• Evaluated the correlation between PHRED scores and SNP analysis outcomes.
• Compared seven read-healing pipelines for their ability to improve quality metrics and downstream analysis results (SNP and assembly).

Main Results:

• PHRED scores strongly correlated with improved SNP analysis for *E. coli* and *S. enterica*.
• Assembly quality showed moderate correlation with PHRED scores and insert size, primarily for *Salmonella*.
• Quality-based or fixed-width trimming pipelines most effectively improved SNP analyses; SPAdes improved *E. coli* assembly, while Skesa showed no significant improvement on healed reads.

Conclusions:

• PHRED scores remain a critical WGS quality metric, with variable impact across different analyses and bacterial species.
• Trimming-based read healing is effective for SNP analysis, but distinct approaches may be necessary for genome assembly and novel WGS methodologies.
• Optimizing WGS data quality through appropriate read healing is essential for accurate enteric pathogen outbreak investigations.