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<p>Bacterial genomics is increasingly used for infectious diseases surveillance, outbreak detection and prediction of antibiotic resistance. With expanding availability of rapid whole-genome sequencing, bacterial genomics data could become a valuable tool for clinicians managing bacterial infections, driving precision medicine strategies. Here, we present a clinician-driven bacterial genomics framework that applies within-patient evolutionary analysis to identify in real-time microbial genetic changes that have an impact on treatment outcomes of severe <i>Staphylococcus aureus</i> infections, a strategy that is increasingly used in cancer genomics. Our approach uses a combination of bacterial genomics and antibiotic susceptibility testing to identify and track bacterial adaptive mutations that underlie microbiologically documented treatment failure (i.e. ongoing positive cultures [persistent infection] or new positive cultures after initial response [recurrent infection]). We show the potential added value of our approach to clinicians and propose a roadmap for the use of bacterial genomics to advance the management of severe bacterial infections.</p>

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A multi-hospital, clinician-initiated bacterial genomics programme to investigate treatment failure in severe Staphylococcus aureus infections

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月26日

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  • Stefano G. Giulieri,
  • Marcel Leroi,
  • Diane Daniel,
  • Roy Chean,
  • Katherine Bond,
  • Harry Walker,
  • Natasha E. Holmes,
  • Nomvuyo Mothobi,
  • Adrian Alexander,
  • Adam Jenney,
  • Carolyn Beckett,
  • Andrew Mahony,
  • Kerrie Stevens,
  • Norelle L. Sherry,
  • Benjamin P. Howden

摘要

Bacterial genomics is increasingly used for infectious diseases surveillance, outbreak detection and prediction of antibiotic resistance. With expanding availability of rapid whole-genome sequencing, bacterial genomics data could become a valuable tool for clinicians managing bacterial infections, driving precision medicine strategies. Here, we present a clinician-driven bacterial genomics framework that applies within-patient evolutionary analysis to identify in real-time microbial genetic changes that have an impact on treatment outcomes of severe Staphylococcus aureus infections, a strategy that is increasingly used in cancer genomics. Our approach uses a combination of bacterial genomics and antibiotic susceptibility testing to identify and track bacterial adaptive mutations that underlie microbiologically documented treatment failure (i.e. ongoing positive cultures [persistent infection] or new positive cultures after initial response [recurrent infection]). We show the potential added value of our approach to clinicians and propose a roadmap for the use of bacterial genomics to advance the management of severe bacterial infections.