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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Automated local bright feature image analysis of nuclear protein distribution identifies changes in tissue phenotype
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Automated local bright feature image analysis of nuclear protein distribution identifies changes in tissue phenotype

机译：核蛋白分布的自动局部亮特征图像分析可识别组织表型的变化

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摘要

The organization of nuclear proteins is linked to cell and tissue phenotypes. When cells arrest proliferation, undergo apoptosis, or differentiate, distribution of nuclear proteins changes. Conversely, forced alteration of the distribution of nuclear proteins modifies cell phenotype. Immunostaining and fluorescence microscopy have been critical for such findings. However, there is increasing need for quantitative analysis of nuclear protein distribution to decipher epigenetic relationships between nuclear structure and cell phenotype and to unravel the mechanisms linking nuclear structure and function. We have developed imaging methods to quantify the distribution of fluorescently stained nuclear protein NuMA in different mammary phenotypes obtained using 3D cell culture. Automated image segmentation of DAPI-stained nuclei was generated to isolate thousands of nuclei from 3D confocal images. Prominent features of fluorescently stained NuMA were detected by using a previously undescribed local bright feature analysis technique, and their normalized spatial density was calculated as a function of the distance from the nuclear perimeter to its center. The results revealed marked changes in the distribution of the density of NuMA bright features when nonneoplastic cells underwent phenotypically normal acinar morphogenesis. Conversely, we did not detect any reorganization of NuMA during formation of tumor nodules by malignant cells. Importantly, the analysis also discriminated proliferating nonneoplastic from proliferating malignant cells, suggesting that these imaging methods are capable of identifying alterations linked not only to the proliferation status but also to the malignant character of cells. We believe that this quantitative analysis will have additional applications for classifying normal and pathological tissues.
机译：核蛋白的组织与细胞和组织表型有关。当细胞阻止增殖，经历凋亡或分化时，核蛋白的分布就会改变。相反，强迫改变核蛋白的分布会改变细胞表型。免疫染色和荧光显微镜对于这种发现至关重要。但是，越来越需要对核蛋白分布进行定量分析，以破译核结构与细胞表型之间的表观遗传关系，并阐明连接核结构与功能的机制。我们已经开发了成像方法以量化使用3D细胞培养获得的不同乳腺表型中荧光染色的核蛋白NuMA的分布。生成了DAPI染色核的自动图像分割，以从3D共聚焦图像中分离出数千个核。通过使用先前未描述的局部亮特征分析技术检测荧光染色的NuMA的突出特征，并根据从核周界到其中心的距离来计算归一化的空间密度。结果表明，当非肿瘤细胞进行表型正常腺泡形态发生时，NuMA亮特征的密度分布发生了明显变化。相反，我们在恶性细胞形成的肿瘤结节期间未检测到NuMA的任何重组。重要的是，该分析还将增殖性非肿瘤细胞与增殖性恶性肿瘤区分开来，表明这些成像方法能够识别不仅与增殖状态有关而且与细胞的恶性特征有关的改变。我们相信，这种定量分析将在分类正常组织和病理组织方面有更多应用。

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