Dynamic Python-Based Method Provides Quantitative Analysis of Intercellular Junction Organization During S. pneumoniae Infection of the Respiratory Epithelium.
Dynamic Python-Based Method Provides Quantitative Analysis of Intercellular Junction Organization During S. pneumoniae Infection of the Respiratory Epithelium.
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DOI：
10.3389/fcimb.2022.865528
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发表时间：
2022
影响因子：
5.7
通讯作者：
中科院分区：
文献类型：
--
作者：
许多呼吸道病原体在肺部感染期间通过破坏维持细胞间完整性的细胞间连接（例如粘附连接和紧密连接）而损害上皮屏障功能。这包括肺炎链球菌，肺炎的主要原因，它可以成功地突破上皮屏障，并导致严重的感染，如败血症和脑膜炎。荧光显微镜分析细胞间连接蛋白操纵呼吸道病原体产生了重大进展，我们了解他们的发病机制。不幸的是，缺乏自动化的图像分析工具，可以容忍的样品-样品染色的变化限制了定量评估细胞间连接组织的准确性。我们已经创建了一个开源的自动化Python计算机脚本，称为“细胞间连接组织量化”或IJOQ，可以处理高度的样品-样品染色变异性并稳健地测量细胞间连接的完整性。IJOQ的计算机模拟验证成功分析了包含不同程度模拟细胞间连接破坏的计算机生成图像。使用从体外和体内细菌感染模型生成的图像进一步证实了准确的IJOQ分析。当与先前公开的用于测量细胞间连接组织的半自动化脚本平行比较时，IJOQ证明了本文所述的所有体外和体内实验的上级分析。这些数据表明，IJOQ是一个公正的，易于使用的工具，荧光显微镜分析，并将作为一个有价值的，自动化的资源，以快速量化细胞间连接破坏在不同的实验条件下。
Many respiratory pathogens compromise epithelial barrier function during lung infection by disrupting intercellular junctions, such as adherens junctions and tight junctions, that maintain intercellular integrity. This includes Streptococcus pneumoniae, a leading cause of pneumonia, which can successfully breach the epithelial barrier and cause severe infections such as septicemia and meningitis. Fluorescence microscopy analysis on intercellular junction protein manipulation by respiratory pathogens has yielded major advances in our understanding of their pathogenesis. Unfortunately, a lack of automated image analysis tools that can tolerate variability in sample-sample staining has limited the accuracy in evaluating intercellular junction organization quantitatively. We have created an open source, automated Python computer script called “Intercellular Junction Organization Quantification” or IJOQ that can handle a high degree of sample-sample staining variability and robustly measure intercellular junction integrity. In silico validation of IJOQ was successful in analyzing computer generated images containing varying degrees of simulated intercellular junction disruption. Accurate IJOQ analysis was further confirmed using images generated from in vitro and in vivo bacterial infection models. When compared in parallel to a previously published, semi-automated script used to measure intercellular junction organization, IJOQ demonstrated superior analysis for all in vitro and in vivo experiments described herein. These data indicate that IJOQ is an unbiased, easy-to-use tool for fluorescence microscopy analysis and will serve as a valuable, automated resource to rapidly quantify intercellular junction disruption under diverse experimental conditions.
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影响因子：
56.9
作者：
Coureuil, Mathieu;Mikaty, Guillain;Nassif, Xavier
通讯作者：
Nassif, Xavier
影响因子：
24.3
作者：
Heijink, I. H.;Brandenburg, S. M.;van Oosterhout, A. J. M.
通讯作者：
van Oosterhout, A. J. M.
影响因子：
4.6
作者：
Brückner BR;Janshoff A
通讯作者：
Janshoff A
影响因子：
3.1
作者：
RAYNER, CFJ;JACKSON, AD;WILSON, R
通讯作者：
WILSON, R
影响因子：
4.4
作者：
Adams, Walter;Bhowmick, Rudra;Leong, John M.
通讯作者：
Leong, John M.