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使用延时显微镜信号处理对诱导凋亡的化学物质进行无标记高通量筛选。

Label free high throughput screening for apoptosis inducing chemicals using time-lapse microscopy signal processing.

作者信息

Aftab Obaid, Nazir Madiha, Fryknäs Mårten, Hammerling Ulf, Larsson Rolf, Gustafsson Mats G

机构信息

Department of Medical Sciences, Cancer Pharmacology and Computational Medicine, Uppsala Academic Hospital, Uppsala University, 751 85, Uppsala, Sweden.

出版信息

Apoptosis. 2014 Sep;19(9):1411-8. doi: 10.1007/s10495-014-1009-9.

Abstract

Label free time-lapse microscopy has opened a new avenue to the study of time evolving events in living cells. When combined with automated image analysis it provides a powerful tool that enables automated large-scale spatiotemporal quantification at the cell population level. Very few attempts, however, have been reported regarding the design of image analysis algorithms dedicated to the detection of apoptotic cells in such time-lapse microscopy images. In particular, none of the reported attempts is based on sufficiently fast signal processing algorithms to enable large-scale detection of apoptosis within hours/days without access to high-end computers. Here we show that it is indeed possible to successfully detect chemically induced apoptosis by applying a two-dimensional linear matched filter tailored to the detection of objects with the typical features of an apoptotic cell in phase-contrast images. First a set of recorded computational detections of apoptosis was validated by comparison with apoptosis specific caspase activity readouts obtained via a fluorescence based assay. Then a large screen encompassing 2,866 drug like compounds was performed using the human colorectal carcinoma cell line HCT116. In addition to many well known inducers (positive controls) the screening resulted in the detection of two compounds here reported for the first time to induce apoptosis.

摘要

无标记延时显微镜为研究活细胞中的时间演化事件开辟了一条新途径。当与自动图像分析相结合时,它提供了一个强大的工具,能够在细胞群体水平上进行自动的大规模时空定量分析。然而,关于设计专门用于在此类延时显微镜图像中检测凋亡细胞的图像分析算法的报道却很少。特别是,所报道的尝试均未基于足够快速的信号处理算法,以在不使用高端计算机的情况下,在数小时/数天内实现大规模的凋亡检测。在此我们表明,通过应用一种二维线性匹配滤波器,确实有可能成功检测化学诱导的凋亡,该滤波器专门用于检测相差图像中具有凋亡细胞典型特征的物体。首先,通过与基于荧光测定法获得的凋亡特异性半胱天冬酶活性读数进行比较,验证了一组记录的凋亡计算检测结果。然后,使用人结肠癌细胞系HCT116对包含2866种类药物化合物进行了大规模筛选。除了许多众所周知的诱导剂(阳性对照)外,该筛选还首次检测到两种诱导凋亡的化合物。

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