Development of fluorescence microscopic image analyzing system for rapid detection of bacterial cells

为了预防传染病的流行，维护制药和食品工业中微生物的安全，我们开发了一种简便、快速的微生物检测系统。我们优化了荧光染色直接计数法、荧光抗体法和荧光原位杂交法在荧光显微镜下检测特定细菌。检测生理活性细菌采用CTC和DAPI双染色。该系统可用于具有生理活性的大肠杆菌O157的特异性检测。首先用CTC染色O157，并与FITC标记的抗O157抗体反应，然后进行生理活性O157的特异性检测。用Cy3标记的基因探针和FITC标记的抗O157抗体双染色对O157抗原的大肠杆菌进行特异性检测。为了在实际场景中常规应用该系统，自动化是必不可少的。我们开发了软件来分析由冷却CCD相机获得的图像。通过图像分析、平滑处理、二次差分锉削和边缘检测，自动区分细菌细胞和其他颗粒。利用该系统可同时获得单个细胞的细菌数量、形态特征和荧光强度。建立了一个用户界面，使软件作为一个全面的系统，易于在日常分析中使用。

In order to prevent epidemics of infectious diseases and to maintain microbiological safety in pharmaceutical and food industry, we developed a system to detect microbes easily and rapidly. We optimized a direct count method with fluorescent staining, a fluorescent antibody method and a fluorescent in situ hybridization method to detect specific bacteria under fluorescent microscopy For the detection of physiologically active bacteria, double staining by CTC and DAPI were used.This system was applied to specific detection of Escherichia coli O157 with physiological activity. Staining O157 first by CTC and have it reacted with anti O157 antibody labeled with FITC next allowed specific detection of physiologically active O157. E.coli with O157 antigen were also specifically detected by double staining with Cy3 labeled gene probe and with anti O157 antibody labeled with FITC.In order to apply the system routinely in the practical scenes, automation is essential. We developed software to analyze images acquired by a cooled CCD camera. Bacterial cells were automatically discriminated from other particles by image analysis with smoothing, secondary differential filing and edge detection. Bacterial number, morphological character, and fluorescent intensity of individual cells were obtained at the same time using this system. A user interface to enable the software to function as a comprehensive system easily used in everyday analysis was established.