在体外耐药性预测研究和在体外耐药性相关参数 - 一个打击到领先的前景
Joanna Krajewska1, Stefan Tyski2, Agnieszka E Laudy3
1Department of Environmental Health and Safety, National Institute of Public Health NIH-National Research Institute, 00-791 Warsaw, Poland.
Pharmaceuticals (Basel, Switzerland)
|August 29, 2024
概括
改善体外耐药性预测对于开发新抗生素至关重要. 本综述详细介绍了诸如突变预防度 (MPC) 和适应性实验室进化 (ALE) 等方法,以预测抗生素耐药性潜力.
科学领域:
- 微生物学 微生物学
- 药理学 药理学是指药理学的学科.
- 药物发现 药物发现 药物发现
背景情况:
- 新抗生素的生产线非常低,需要改进的方法来识别候选药物.
- 预测自然环境中抗生素耐药性选择的潜力对于药物开发至关重要.
研究的目的:
- 审查和突出体外预测抗生素耐药性的方法.
- 讨论适应性实验室进化 (ALE) 方法用于比较抗生素候选者的实用性.
- 探索高吞吐量ALE设置和对抗性突变物的健康评估.
主要方法:
- 实验室耐药性参数的表述:自发突变选择的频率 (FSMS),突变预防度 (MPC),主导突变预防度 (MPC-D),劣质突变预防度 (MPC-F) 和最小选择度 (MSC).
- 讨论各种适应性实验室进化 (ALE) 方法,包括串行转移,连续培养和空间时空微环境中的进化.
- 考虑高通量ALE设置,如机器人工作站,DIY连续种植,MEGA板,SAGE板,微流体芯片和微滴技术.
主要成果:
- 可以利用各种体外参数和ALE方法来比较抗生素命中.
- 高通量ALE设置提供了可扩展的解决方案,用于击中到领先的阶段.
- 已有用于评估体外生成的耐药突变物适应性的方法.
结论:
- 加强体外耐药性预测对于新型抗生素的可持续供应至关重要.
- 适应性实验室进化 (ALE) 和相关技术为预测抗性潜力提供了强大的工具.
- 这些方法的进一步开发和应用可以加速发现有效的抗生素候选剂.
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