Summers Huw D, Wills John W, Brown M Rowan, Rees Paul
Systems and Process Engineering Centre, College of Engineering, Swansea University, Singleton Park, Swansea, SA2 8PP, United Kingdom.
Cytometry A. 2015 May;87(5):385-92. doi: 10.1002/cyto.a.22620. Epub 2015 Jan 8.
A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture.
本文介绍了一种评估细胞增殖动力学的方案。该方案基于对细胞分裂事件的测量,并使用泊松概率统计对其进行后续分析。在时间序列分析中,对异质群体中的增殖动力学进行详细分析需要单细胞分辨率,因此在技术上实施起来要求很高。在这里,我们表明,通过关注细胞进行分裂的事件,而不是直接关注细胞本身,可以遵循一种简化的图像采集和分析方案,该方案保持单细胞分辨率并报告细胞增殖的关键指标。使用具有1.3μm空间分辨率的显微镜对A549和BEAS-2B细胞系中的有丝分裂事件进行了长达48小时的跟踪,展示了该技术。使用ImageJ软件工具包中的标准算法对明场图像进行自动图像处理,对有丝分裂事件系列的手动识别的时间和空间位置的记录准确率达到87%。对事件间隔时间(即视野中观察到的有丝分裂之间的时间)的统计分析表明,细胞分裂符合非齐次泊松过程,其中有丝分裂事件的发生率λ随时间呈指数增加,A549细胞的平均有丝分裂间隔时间为21.1±1.2小时,BEAS-2B细胞为25.0±1.1小时。将BEAS-2B细胞系的有丝分裂事件系列与随机泊松统计预测的结果进行比较,表明细胞分裂过程在70%的群体中发生了时间同步,通过对细胞培养进行血清饥饿处理,这一比例可以提高到85%。