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Cell Line Macroarray

机译:细胞系宏阵列

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摘要

In the past decade, tissue microarray (TMA) technology has evolved as an innovative tool for high-throughput proteomics analysis and mainly for biomarker validation. Similarly, enormous amount of data can be obtained from the cell line macroarray (CLMA) technology, which developed from the TMA using formalin-fixed, paraffin-embedded cell pellets. Here, we applied CLMA technology in stem cell research and in particular to identify bona fide neogenerated human induced pluripotent stem cell (hiPSC) clones suitable for down the line differentiation. All hiPSC protocols generate tens of clones, which need to be tested to determine genetically stable cell lines suitable for differentiation. Screening methods generally rely on fluorescence-activated cell sorting isolation and coverslip cell growth followed by immunofluorescence; these techniques could be cumbersome. Here, we show the application of CLMA to identify neogenerated pluripotent cell colonies and neuronal differentiated cell products. We also propose the use of the automated image analyzer, TissueQuest, as a reliable tool to quickly select the best clones, based upon the level of expression of multiple pluripotent biomarkers.
机译:在过去的十年中,组织微阵列(TMA)技术已经发展成为一种用于高通量蛋白质组学分析以及主要用于生物标志物验证的创新工具。同样,可以从细胞系大分子阵列(CLMA)技术获得大量数据,该技术是使用福尔马林固定的石蜡包埋的细胞沉淀物从TMA开发的。在这里,我们将CLMA技术应用到干细胞研究中,尤其是鉴定了真正的新一代人诱导多能干细胞(hiPSC)克隆,这些克隆适用于线下分化。所有hiPSC协议都会生成数十个克隆,需要对其进行测试以确定适合分化的遗传稳定细胞系。筛选方法通常依靠荧光激活的细胞分选分离和盖玻片细胞生长,然后进行免疫荧光。这些技术可能很麻烦。在这里,我们展示了CLMA在鉴定新生多能细胞集落和神经元分化细胞产物中的应用。我们还建议使用自动图像分析仪TissueQuest作为可靠工具,根据多种多能生物标志物的表达水平快速选择最佳克隆。

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