Havener Eye Institute, Department of Ophthalmology and Visual Science, The Ohio State University, Columbus, OH, USA; Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA.
Havener Eye Institute, Department of Ophthalmology and Visual Science, The Ohio State University, Columbus, OH, USA.
Exp Eye Res. 2018 Nov;176:121-129. doi: 10.1016/j.exer.2018.06.028. Epub 2018 Jun 28.
Nuclear co-localization labels are critical to ocular research. Among these, the TUNEL assay has been established as a gold standard of cell death and apoptosis. While several validated computer-based methods exist to quantitate these markers, including ImageJ Retina Analysis (RA) Toolkit and ImagePro, none verify the count with the nuclear counter stain to confirm nuclear co-localization. We established a new ImageJ-based automated multichannel thresholding (MCT) method to quantitate nuclear co-localized labeling. The MCT method was validated by comparing it with the two published TUNEL analysis in TUNEL-positive photoreceptors in an experimental retinal detachment (RD) model. RDs were induced in murine eyes and cross-sectional images of TUNEL and DAPI counter stain were obtained. Images were classified as "typical" or high density "hotspot" TUNEL regions (n = 10/group). Images were analyzed and compared between the MCT method and the published techniques including both "standard" and "high" settings of the RA Toolkit for detecting lower or higher TUNEL densities, respectively. Additional testing of the MCT method with built-in ImageJ thresholding algorithms was performed to produce fully automated measurements. All images were compared with Bland-Altman mean difference plots to assess the difference in counts and linear regression plots to assess correlation. Comparison between the MCT method and the ImagePro method were found to be well correlated (typical: R = 0.8972, hotspot: R = 0.9000) with minor to non-significant differences. The RA Toolkit settings were found to be mostly well correlated as well (standard/typical: R = 0.8036, standard/hotspot: R = 0.4309, high/typical: R = 0.7895, high/hotspot: R = 0.8738) but were often found to have significantly higher counts than the MCT. In conclusion, the MCT method compared favorably with validated computer-based methods of nuclear marker immunofluorescence quantitation and avoids staining artifacts through the incorporation of the nuclear counter stain to confirm positive cells.
核共定位标记对于眼部研究至关重要。其中，TUNEL 检测已被确立为细胞死亡和凋亡的金标准。虽然已经存在几种经过验证的基于计算机的方法来定量这些标记物，包括 ImageJ Retina Analysis（RA）Toolkit 和 ImagePro，但没有一种方法可以通过核计数器染色来验证计数，以确认核共定位。我们建立了一种新的基于 ImageJ 的自动多通道阈值（MCT）方法来定量核共定位标记。通过将 MCT 方法与两种已发表的 TUNEL 分析方法在实验性视网膜脱离（RD）模型中的 TUNEL 阳性光感受器中的应用进行比较，验证了该方法的有效性。在鼠眼诱导 RD 后，获得 TUNEL 和 DAPI 计数器染色的横截面图像。将图像分为“典型”或高密度“热点”TUNEL 区域（每组 n=10）。使用 MCT 方法和已发表的技术（包括 RA Toolkit 的“标准”和“高”设置）对图像进行分析和比较，以分别检测较低或较高的 TUNEL 密度。还使用内置的 ImageJ 阈值算法对 MCT 方法进行了额外的测试，以产生全自动测量。所有图像均与 Bland-Altman 均值差异图进行比较，以评估计数差异，并与线性回归图进行比较，以评估相关性。发现 MCT 方法与 ImagePro 方法之间具有良好的相关性（典型：R=0.8972，热点：R=0.9000），差异较小且无统计学意义。RA Toolkit 设置也具有很好的相关性（标准/典型：R=0.8036，标准/热点：R=0.4309，高/典型：R=0.7895，高/热点：R=0.8738），但通常发现计数明显高于 MCT。总之，MCT 方法与核标记免疫荧光定量的经过验证的基于计算机的方法相比表现良好，并通过纳入核计数器染色来确认阳性细胞，避免了染色伪影。
