Institute of Physical and Theoretical Chemistry, University of Bonn, Bonn, Germany.
Institute for Pharmaceutical Microbiology, University Hospital Bonn, University of Bonn, Bonn, Germany.
Methods Mol Biol. 2023;2601:231-257. doi: 10.1007/978-1-0716-2855-3_12.
Microscopy is a powerful method to evaluate the direct effects of antibiotic action on the single cell level. As with other methodologies, microscopy data is obtained through sufficient biological and technical replicate experiments, where evaluation of the sample is generally followed over time. Even if a single antibiotic is tested for a defined time, the most certain outcome is large amounts of raw data that requires systematic analysis. Although microscopy is a helpful qualitative method, the recorded information is stored as defined quantifiable units, the pixels. When this information is transferred to diverse bioinformatic tools, it is possible to analyze the microscopy data while avoiding the inherent bias associated to manual quantification. Here, we briefly describe methods for the analysis of microscopy images using open-source programs, with a special focus on bacteria exposed to antibiotics.
显微镜是一种评估抗生素在单细胞水平上直接作用的有力方法。与其他方法一样，显微镜数据是通过足够的生物学和技术重复实验获得的，通常随着时间的推移对样本进行评估。即使只测试一种抗生素一段时间，最确定的结果也是大量需要系统分析的原始数据。虽然显微镜是一种有用的定性方法，但所记录的信息以定义的可量化单位（像素）存储。当将此信息传输到各种生物信息学工具时，可以分析显微镜数据，同时避免与手动量化相关的固有偏差。在这里，我们简要描述了使用开源程序分析显微镜图像的方法，特别关注暴露于抗生素的细菌。
