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一种利用自动图像分析在细胞微阵列中进行蛋白质谱分析的高通量策略。

A high-throughput strategy for protein profiling in cell microarrays using automated image analysis.

作者信息

Strömberg Sara, Björklund Marcus Gry, Asplund Caroline, Sköllermo Anna, Persson Anja, Wester Kenneth, Kampf Caroline, Nilsson Peter, Andersson Ann-Catrin, Uhlen Mathias, Kononen Juha, Ponten Fredrik, Asplund Anna

机构信息

Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden.

出版信息

Proteomics. 2007 Jun;7(13):2142-50. doi: 10.1002/pmic.200700199.

Abstract

Advances in antibody production render a growing supply of affinity reagents for immunohistochemistry (IHC), and tissue microarray (TMA) technologies facilitate simultaneous analysis of protein expression in a multitude of tissues. However, collecting validated IHC data remains a bottleneck problem, as the standard method is manual microscopical analysis. Here we present a high-throughput strategy combining IHC on a recently developed cell microarray with a novel, automated image-analysis application (TMAx). The software was evaluated on 200 digital images of IHC-stained cell spots, by comparing TMAx annotation with manual annotation performed by seven human experts. A high concordance between automated and manual annotation of staining intensity and fraction of IHC-positive cells was found. In a limited study, we also investigated the possibility to assess the correlation between mRNA and protein levels, by using TMAx output results for relative protein quantification and quantitative real-time PCR for the quantification of corresponding transcript levels. In conclusion, automated analysis of immunohistochemically stained in vitro-cultured cells in a microarray format can be used for high-throughput protein profiling, and extraction of RNA from the same cell lines provides a basis for comparing transcription and protein expression on a global scale.

摘要

抗体生产技术的进步使得免疫组织化学(IHC)可用的亲和试剂供应不断增加,并且组织微阵列(TMA)技术有助于同时分析多种组织中的蛋白质表达。然而,由于标准方法是手动显微镜分析,收集经过验证的IHC数据仍然是一个瓶颈问题。在此,我们提出了一种高通量策略,将在最近开发的细胞微阵列上进行的免疫组织化学与一种新型自动化图像分析应用程序(TMAx)相结合。通过将TMAx注释与七位人类专家进行的手动注释进行比较,在200张免疫组织化学染色细胞斑点的数字图像上对该软件进行了评估。结果发现,染色强度和免疫组织化学阳性细胞比例的自动注释与手动注释之间具有高度一致性。在一项有限的研究中,我们还研究了通过使用TMAx输出结果进行相对蛋白质定量以及使用定量实时PCR对相应转录水平进行定量来评估mRNA和蛋白质水平之间相关性的可能性。总之,以微阵列形式对免疫组织化学染色的体外培养细胞进行自动分析可用于高通量蛋白质谱分析,并且从同一细胞系中提取RNA为在全球范围内比较转录和蛋白质表达提供了基础。

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