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<p><i>Staphylococcus aureus</i>, particularly methicillin-resistant <i>S. aureus</i> (MRSA), poses a persistent global health challenge. Genomic surveillance is essential but often hindered by the bioinformatics complexity of integrating multiple, disparate analysis tools. To address this, we developed StaphScope, a specialized computational pipeline for the comprehensive genotyping of <i>S. aureus</i>. Distributed as a single-install Conda package, StaphScope integrates six core analyses—Multi-Locus Sequence typing (MLST), staphylococcal protein A (<i>spa)</i> typing, staphylococcal cassette chromosome <i>mec</i> (SCC<i>mec</i>) characterization, antimicrobial resistance (AMR) profiling, virulence factor screening, and plasmid detection—within a unified workflow. It features intelligent resource management via the Python psutil library for efficient parallel execution. Validation using reference strains showed complete concordance with established types. Analysis of 24 <i>S. aureus</i> genomes identified prevalent lineages (e.g., ST5, ST9), diverse resistance mechanisms, and key virulence determinants, with the pipeline completing all analyses in estimated 10–14&#xa0;min on a system with 16 CPU cores and 16 GB RAM. StaphScope generates consolidated, interactive HTML reports alongside structured data files (TSV, JSON). By streamlining access to integrated genomic analysis, it supports enhanced surveillance and outbreak response. The tool is available at: https://github.com/bbeckley-hub/staphscope-typing-tool.</p>

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StaphScope: a species-optimized computational pipeline for rapid and accessible Staphylococcus aureus genotyping and surveillance

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月6日

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  • Brown Beckley,
  • Vincent Amarh

摘要

Staphylococcus aureus, particularly methicillin-resistant S. aureus (MRSA), poses a persistent global health challenge. Genomic surveillance is essential but often hindered by the bioinformatics complexity of integrating multiple, disparate analysis tools. To address this, we developed StaphScope, a specialized computational pipeline for the comprehensive genotyping of S. aureus. Distributed as a single-install Conda package, StaphScope integrates six core analyses—Multi-Locus Sequence typing (MLST), staphylococcal protein A (spa) typing, staphylococcal cassette chromosome mec (SCCmec) characterization, antimicrobial resistance (AMR) profiling, virulence factor screening, and plasmid detection—within a unified workflow. It features intelligent resource management via the Python psutil library for efficient parallel execution. Validation using reference strains showed complete concordance with established types. Analysis of 24 S. aureus genomes identified prevalent lineages (e.g., ST5, ST9), diverse resistance mechanisms, and key virulence determinants, with the pipeline completing all analyses in estimated 10–14 min on a system with 16 CPU cores and 16 GB RAM. StaphScope generates consolidated, interactive HTML reports alongside structured data files (TSV, JSON). By streamlining access to integrated genomic analysis, it supports enhanced surveillance and outbreak response. The tool is available at: https://github.com/bbeckley-hub/staphscope-typing-tool.