Abstract
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. © 2015 The Authors. Published by Wiley Periodicals, Inc.
Highlights
A protocol for the assessment of cell proliferation dynamics is presented
Two aspects of the division process can be seen in this image: (i) the interevent times are to some degree random in length and (ii) there is an overall trend to an increasing rate of event occurrence with time
Poisson statistics describe the probability of events within a stochastic series, providing estimates of their spacing in time under the assumption of independence of any given event from previous instances
Summary
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. At the other end of the spectrum, time lapse microscopy, and computational image processing provides full quantification of individual cells in space and time; it is expensive to implement and requires a high level of experience and expertise [6] Between these extremes lies a collection of flow cytometry techniques which provide cell cycle or generational information through measurement of fluorescent molecular reporters [7,8,9,10]. The technique provides single cell resolution and mapping of spatiotemporal events but in a simplified implementation where image processing is made relatively straightforward by the single requirement to recognize mitotic cells; that is, cells only need to be identified when in a high image-contrast mode as they lift off the growth surface and become spherical, prior to a division event It is the measurement of an event sequence that is of primary importance here, as this provides data on the occurrence rate, k of events and the intervals, Dt, Dx, and Dy between them. This is more than sufficient to detect mitotic cells and our results demonstrate how the low-level demands of the Poisson analysis on the optics of the instrument allow a robust and detailed assessment of cell population proliferation dynamics
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