Choudhry Priya
Department of Chemistry, California Institute of Technology, Pasadena, California, United States of America.
PLoS One. 2016 Feb 5;11(2):e0148469. doi: 10.1371/journal.pone.0148469. eCollection 2016.
Counting cells and colonies is an integral part of high-throughput screens and quantitative cellular assays. Due to its subjective and time-intensive nature, manual counting has hindered the adoption of cellular assays such as tumor spheroid formation in high-throughput screens. The objective of this study was to develop an automated method for quick and reliable counting of cells and colonies from digital images. For this purpose, I developed an ImageJ macro Cell Colony Edge and a CellProfiler Pipeline Cell Colony Counting, and compared them to other open-source digital methods and manual counts. The ImageJ macro Cell Colony Edge is valuable in counting cells and colonies, and measuring their area, volume, morphology, and intensity. In this study, I demonstrate that Cell Colony Edge is superior to other open-source methods, in speed, accuracy and applicability to diverse cellular assays. It can fulfill the need to automate colony/cell counting in high-throughput screens, colony forming assays, and cellular assays.
细胞和集落计数是高通量筛选和定量细胞分析不可或缺的一部分。由于其主观性和耗时性,手动计数阻碍了诸如高通量筛选中肿瘤球形成等细胞分析方法的应用。本研究的目的是开发一种自动方法,用于从数字图像中快速可靠地计数细胞和集落。为此,我开发了一个ImageJ宏“细胞集落边缘”和一个CellProfiler管道“细胞集落计数”,并将它们与其他开源数字方法和手动计数进行了比较。ImageJ宏“细胞集落边缘”在细胞和集落计数以及测量它们的面积、体积、形态和强度方面很有价值。在本研究中,我证明“细胞集落边缘”在速度、准确性和对各种细胞分析的适用性方面优于其他开源方法。它可以满足高通量筛选、集落形成分析和细胞分析中集落/细胞计数自动化的需求。