An Automatic Analysis System for High-Throughput Clostridium Difficile Toxin Activity Screening
An Automatic Analysis System for High-Throughput Clostridium Difficile Toxin Activity Screening
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DOI：
10.3390/app8091512
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发表时间：
2018-09-01
影响因子：
2.7
通讯作者：
Sienczyk, Marcin
中科院分区：
文献类型：
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作者：
Garland, Megan;Jaworek-Korjakowska, Joanna;Sienczyk, Marcin
艰难梭菌感染（CDI）是一种日益严重的全球健康威胁，也是全球医院获得性腹泻的主要原因。开发有效治疗这种细菌病原体的新疗法是一种未满足的临床需求。在这里，我们描述了一种图像处理和分类算法，自动识别毒素诱导的细胞毒性宿主细胞的特征形态学变化的基础上。该算法可用于筛选新型抗毒素类C.艰难梭菌的主要毒力因子TcdA和TcdB，并包含以下步骤：图像增强，细胞分割和分类。我们在504张图像（包含5096个细胞）上测试了该算法，并实现了93%的灵敏度和91%的特异性，这表明所提出的计算方法正确地分类了大多数细胞，并为有效的筛选平台提供了可靠的信息。与现有的细胞计数和分析程序相比，该算法实现了更高的分类结果，准确率为92.6%。与研究人员的目视检查相比，该算法显着减少了分类时间，并以无偏的方式识别了毒素诱导的细胞毒性。可用性：示例可在home.agh.edu.pl/jaworek/CDI上获得。
Clostridium difficile infection (CDI) is an increasing global health threat and major worldwide cause of hospital-acquired diarrhea. The development of novel therapies to effectively treat this bacterial pathogen is an unmet clinical need. Here, we describe an image processing and classification algorithm that automatically identifies toxin-induced cytotoxicity to host cells based on characteristic morphological changes. This efficient and automatic algorithm can be incorporated into a screening platform to identify novel anti-toxin inhibitors of the C. difficile major virulence factors TcdA and TcdB, and contains the following steps: image enhancement, cell segmentation, and classification. We tested the algorithm on 504 images (containing 5096 cells) and achieved 93% sensitivity and 91% specificity, indicating that the proposed computational approach correctly classified most of the cells and provided reliable information for an effective screening platform. This algorithm achieved higher classification results compared to existing cell counter and analysis programs, scoring 92.6% accuracy. Compared to visual examination by a researcher, the algorithm significantly decreased classification time and identified toxin-induced cytotoxicity in an unbiased manner. Availability: Examples are available at home.agh.edu.pl/jaworek/CDI.