Scholarlink

<p>Antibiotic resistance is a growing global health threat. To improve our understanding of the mechanisms driving antibiotic resistance, suitable infection models are needed that also capture relevant drug dynamics. Here, we present a microfluidic hollow-fiber infection model that enables pharmacokinetic/pharmacodynamic studies under physiologically relevant conditions. The system simulates temporally antibiotic concentration gradients (pharmacokinetic module) and enables the long-term, high-resolution imaging of bacterial cells within a tissue-like hydrogel matrix in a flat growth chamber (pharmacodynamic module) with minimum sample and drug consumption. Using <i>Escherichia coli</i> quality control strains exposed to amoxicillin and amoxicillin-clavulanic acid, we show that treatment efficacy is not determined solely by the fraction of time above the minimum inhibitory concentration. Instead, dosing intervals and recovery phases between doses critically shape bacterial survival and killing. Prolonged dosing phases (&gt;6 h) or shortened recovery periods enhance bacterial clearance, while specific dynamic regimens induce distinct phenotypic responses, including filamentous growth. In addition, the system supports analysis of clinical isolates via inline staining. By combining dynamic PK control, tissue-like hydrogel environments, and sustained high-resolution imaging, the µHFIM enables in vivo-like investigation of bacterial responses to antibiotic treatment. This system provides mechanistic insight into how dosing schedules govern efficacy and adaptation, which may help to optimize antibiotic treatment strategies in the future (bench to bedside translation).</p><p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A microfluidic hollow-fiber infection model (µHFIM): monitoring bacterial response to dynamic drug treatment with single-cell resolution

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月9日

查看全文
  • Friederike-Leonie Born,
  • Raphael Dezauzier,
  • Annelies S. Zinkernagel,
  • Petra S. Dittrich

摘要

Antibiotic resistance is a growing global health threat. To improve our understanding of the mechanisms driving antibiotic resistance, suitable infection models are needed that also capture relevant drug dynamics. Here, we present a microfluidic hollow-fiber infection model that enables pharmacokinetic/pharmacodynamic studies under physiologically relevant conditions. The system simulates temporally antibiotic concentration gradients (pharmacokinetic module) and enables the long-term, high-resolution imaging of bacterial cells within a tissue-like hydrogel matrix in a flat growth chamber (pharmacodynamic module) with minimum sample and drug consumption. Using Escherichia coli quality control strains exposed to amoxicillin and amoxicillin-clavulanic acid, we show that treatment efficacy is not determined solely by the fraction of time above the minimum inhibitory concentration. Instead, dosing intervals and recovery phases between doses critically shape bacterial survival and killing. Prolonged dosing phases (>6 h) or shortened recovery periods enhance bacterial clearance, while specific dynamic regimens induce distinct phenotypic responses, including filamentous growth. In addition, the system supports analysis of clinical isolates via inline staining. By combining dynamic PK control, tissue-like hydrogel environments, and sustained high-resolution imaging, the µHFIM enables in vivo-like investigation of bacterial responses to antibiotic treatment. This system provides mechanistic insight into how dosing schedules govern efficacy and adaptation, which may help to optimize antibiotic treatment strategies in the future (bench to bedside translation).