Narayan Pritika J, Kim Sue-Ling, Lill Claire, Feng Sheryl, Faull Richard L M, Curtis Maurice A, Dragunow Michael
Gravida, National Centre for Growth and Development, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland, New Zealand; Centre for Brain Research, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland, New Zealand; Biomedical Imaging Research Unit, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland, New Zealand.
Centre for Brain Research, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag 92019, Auckland, New Zealand.
J Neurosci Methods. 2015 May 30;247:41-9. doi: 10.1016/j.jneumeth.2015.03.017. Epub 2015 Mar 23.
Tissue microarrays are commonly used to evaluate disease pathology however methods to automate and quantify pathological changes are limited.
This article demonstrates the utility of the VSlide scanner (MetaSystems) for automated image acquisition from immunolabelled tissue microarray slides, and subsequent automated image analysis with MetaXpress (Molecular Devices) software to obtain objective, efficient and reproducible data from immunolabelled tissue microarray sections.
Significant increases in fibrinogen immunolabelling were observed in 29 Alzheimer's disease cases compared to 28 control cases analysed from a single tissue microarray slide. Western blot analysis also demonstrated significant increases in fibrinogen immunolabelling in 6 Alzheimer's cases compared to 6 control cases. The observed changes were also validated with gold standard blinded manual H-scoring.
VSlide Metafer software offers a 'tissue microarray acquisition' plugin for easy mapping of tissue cores with their original position on the tissue microarray map. High resolution VSlide images are compatible with MetaXpress image analysis software. This article details the coupling of these two technologies to accurately and reproducibly analyse immunolabelled tissue microarrays within minutes, compared to the gold standard method of manual counting using H-scores which is significantly slower and prone to inter-observer variation.
Here, we couple brain tissue microarray technology with high-content screening and automated image analysis as a powerful way to address bottle necks in data generation and improve throughput, as well as sensitivity to study biological/pathological changes in brain disease.
组织微阵列常用于评估疾病病理学,然而自动化和量化病理变化的方法有限。
本文展示了VSlide扫描仪(MetaSystems公司)用于从免疫标记的组织微阵列载玻片自动采集图像,以及随后使用MetaXpress(Molecular Devices公司)软件进行自动图像分析,以便从免疫标记的组织微阵列切片获得客观、高效且可重复的数据。
与从单个组织微阵列载玻片分析的28例对照病例相比,在29例阿尔茨海默病病例中观察到纤维蛋白原免疫标记显著增加。蛋白质印迹分析也显示,与6例对照病例相比,6例阿尔茨海默病病例中纤维蛋白原免疫标记显著增加。观察到的变化也通过金标准盲法手动H评分得到验证。
VSlide Metafer软件提供了一个“组织微阵列采集”插件,便于在组织微阵列图上轻松定位组织芯与其原始位置。高分辨率的VSlide图像与MetaXpress图像分析软件兼容。本文详细介绍了这两种技术的结合,与使用H评分的金标准手动计数方法相比,该方法能在几分钟内准确且可重复地分析免疫标记的组织微阵列,而手动计数方法明显更慢且容易出现观察者间差异。
在此,我们将脑组织微阵列技术与高内涵筛选和自动图像分析相结合,作为解决数据生成瓶颈、提高通量以及研究脑部疾病生物/病理变化敏感性的有力方法。