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Background <p><i>Staphylococcus aureus</i> is a leading cause of hospital- and community-acquired infections. While Whole Genome Sequencing (WGS) has become the gold standard for surveillance, extracting actionable epidemiological data typically requires assembling fragmented workflows of disparate software tools. We introduce StaphSCAN, a modular, open-source Python tool designed to streamline <i>S. aureus</i> genomic analysis.</p> Results <p>StaphSCAN integrates essential typing methods (MLST, <i>spa</i> typing, SCC<i>mec</i> typing, capsular typing) with the detection of antimicrobial resistance (AMR), virulence, and biofilm-associated genes. It produces a comprehensive, normalized tabular report suitable for immediate interpretation. We validated StaphSCAN using a public dataset of 404 clinical <i>S. aureus</i> genomes collected in 2019 during a study conducted by the StaphNET-SA network. The tool successfully characterized the population structure, replicating the main key findings, demonstrating high throughput and reliability.</p> Conclusions <p>In conclusion, StaphSCAN provides a lightweight framework for <i>S. aureus</i> genomics, facilitating rapid genomic surveillance.</p>

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StaphSCAN: a genomic surveillance framework for Staphylococcus aureus

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月9日

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  • Riccardo Bollini,
  • Valeria Cento

摘要

Background

Staphylococcus aureus is a leading cause of hospital- and community-acquired infections. While Whole Genome Sequencing (WGS) has become the gold standard for surveillance, extracting actionable epidemiological data typically requires assembling fragmented workflows of disparate software tools. We introduce StaphSCAN, a modular, open-source Python tool designed to streamline S. aureus genomic analysis.

Results

StaphSCAN integrates essential typing methods (MLST, spa typing, SCCmec typing, capsular typing) with the detection of antimicrobial resistance (AMR), virulence, and biofilm-associated genes. It produces a comprehensive, normalized tabular report suitable for immediate interpretation. We validated StaphSCAN using a public dataset of 404 clinical S. aureus genomes collected in 2019 during a study conducted by the StaphNET-SA network. The tool successfully characterized the population structure, replicating the main key findings, demonstrating high throughput and reliability.

Conclusions

In conclusion, StaphSCAN provides a lightweight framework for S. aureus genomics, facilitating rapid genomic surveillance.