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Apoptosis detection via automated algorithms to analyze biomarker translocation in reporter cells

机译:通过自动化算法进行凋亡检测,分析报告细胞中的生物标志物易位

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摘要

Rapid, efficient, and robust quantitative analyses of dynamic apoptotic events are essential in a high-throughput screening workflow. Currently used methods have several bottlenecks, specifically, limitations in available fluorophores for downstream assays and misinterpretation of statistical image data analysis. In this study, we developed cytochrome-C (Cyt-C) and caspase-3/-8 reporter cell lines using lung (PC9) and breast (T47D) cancer cells, and characterized them from the response to apoptotic stimuli. In these two reporter cell lines, the spatial fluorescent signal translocation patterns served as reporters of activations of apoptotic events, such as Cyt-C release and caspase-3/-8 activation. We also developed a vision-based, tunable, automated algorithm in MATLAB to implement the robust and accurate analysis of signal translocation in single or multiple cells. Construction of the reporter cell lines allows live monitoring of apoptotic events without the need for any other dyes or fixatives. Our algorithmic implementation forgoes the use of simple image statistics for more robust analytics. Our optimized algorithm can achieve a precision greater than 90% and a sensitivity higher than 85%. Combining our automated algorithm with reporter cells bearing a single-color dye/fluorophore, we expect our approach to become an integral component in the high-throughput drug screening workflow.
机译:动态凋亡事件的快速,高效和稳健的定量分析在高吞吐量筛选工作流程中是必不可少的。目前使用的方法具有几个瓶颈,具体地,用于下游测定的可用荧光团的限制和统计图像数据分析的误解。在该研究中,我们使用肺(PC9)和乳腺(T47D)癌细胞产生细胞色素-C(CYT-C)和Caspase-3 / -8报告细胞系,并从对凋亡刺激的反应表征它们。在这两种报告细胞系中,空间荧光信号易位模式作为凋亡事件的激活的报道,例如Cyt-C释放和Caspase-3 / -8激活。我们还开发了MATLAB的基于视觉,可调,自动化的算法,实现了单个或多个单元格中的信号易位的稳健和准确分析。记者细胞系的构建允许在不需要任何其他染料或固定剂的情况下进行凋亡事件的实际监测。我们的算法实现,用于使用简单的图像统计数据以获取更强大的分析。我们的优化算法可以实现大于90%的精度,灵敏度高于85%。将我们的自动化算法与带有单色染料/荧光团的记者细胞结合,我们预计我们的方法是在高通量药物筛选工作流程中成为一个整体组成部分。

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