Cell cycle dysregulation is a classic hallmark of cancer and, as such, has been widely studied by researchers hoping to develop effective treatments. It is most commonly monitored by flow cytometry, using fluorescent DNA-binding dyes to determine the distribution of cells in a population based on distinct nuclear phases. Important considerations for cell cycle analysis include the choice of dye and whether to combine DNA staining with detection of additional markers. This article discusses some best practices for analyzing the cell cycle and explains how using image cytometry can enhance flow cytometry data.
Choosing the right dye
Although some of the earliest dyes used for cell cycle analysis—Hoechst, DAPI, propidium iodide (PI)—are still routinely used today, newer dyes offer several advantages. These include narrower emission spectra and lower cytotoxicity, providing researchers with greater flexibility when designing flow cytometry experiments.
“The principle of DNA-binding dyes is that they are stoichiometric,” notes Dr. Saeeda Bobat, senior scientist at Abcam. “This means they will bind proportionally to the amount of DNA present in each cell. Different dye types include single-intercalators such as PI that bind between adjacent base pairs of DNA, bis-intercalators like YOYO that have two intercalating moieties, and minor-groove binding dyes such as DAPI that bind to DNA in a base-dependent manner. Choosing a DNA-binding dye to support your research largely depends on the setup and aims of your experiment.”
Image: Monitoring cell cycle inhibition with flow cytometry. Image provided by Abcam.
Lauren Jachimowicz, application development scientist, flow cytometry at Agilent Technologies, explains that the specificity of a dye for DNA is important, highlighting as an example the use of PI for cell cycle analysis. “Because PI will bind to all nucleic acids, RNase A should be included in staining buffers to degrade any RNA present,” she says. In some instances, dye choice may also be influenced by DNA sequence; for instance, DAPI preferentially binds A-T rich regions.
“Another factor to consider when selecting a DNA-binding dye is the type of fixative,” adds Jachimowicz. “Ethanol fixation is preferred to aldehyde-based fixation for cell cycle analysis since aldehyde-induced cross-linking can impair dye binding to DNA. However, if you intend to stain for additional targets, you should confirm that the antibodies and fluorochromes you plan to use are compatible with ethanol fixation.”
One of the most important advances in DNA staining is the development of dyes that can be used to study live cells. “The advantage of live cell staining is that it enables cell sorting based on DNA content for further downstream processing,” says Bobat. “Although this is currently only possible with next-generation products such as the Vybrant™ DyeCycle™ dyes, being able to perform cell cycle analysis in live cells opens up a multitude of opportunities for longer-term experiments.”
Combining DNA staining with other markers
As already mentioned, performing cell cycle analysis with flow cytometry often involves monitoring other targets besides DNA. “Staining for other parameters is necessary if you are analyzing a heterogeneous population rather than a cell line,” reports Bobat. “For example, during immunophenotyping, where you may want to identify sub-populations of neutrophils, lymphocytes, and macrophages and measure their DNA content individually. Alternatively, you might wish to compare quiescent (G0) and proliferating (G1) cells, which are indistinguishable in terms of their DNA content. This can be achieved by combining DNA analysis with staining for cell cycle markers such as Cyclins D1 and E (which will be negative in quiescent cells), or by using Pyronin Y to monitor RNA levels (quiescent cells downregulate RNA expression).” Another common practice is to stain for phosphorylated Histone H3 to distinguish mitotic cells from cells in G2, since at both these phases of the cell cycle the normal DNA content is doubled.
Best practices
Carefully optimized protocols are essential to the success of any flow cytometry experiment, yet there are certain best practices that are especially critical when it comes to cell cycle analysis using flow cytometry. Many of these are aimed at avoiding doublets, because if two cells in G1 pass through the laser simultaneously, they can be mistaken for a single cell in G2/M. “The probability of doublets increases when analyzing cells with a tendency to stick together or when running at high flow rates,” says Bobat. “Clumps can be removed before staining by filtering cells through a nylon mesh filter, whereas steps to ensure a single-cell suspension include adding EDTA to sample buffers to reduce cell-to-cell adhesion and avoiding any harsh centrifugations.” While slow flow rates inevitably add time to workflows, it is important not to cut corners by being tempted to count fewer cells. Bobat recommends aiming for at least 10,000 events for optimum data analysis.
“Doublets can be gated out by plotting forward scatter height (FSC-H) against forward scatter area (FSC-A),” reports Jachimowicz. “Compared to manual gating analysis, software-based automation provides more accurate interpretation of data here, however it is important to choose the right model. The two main algorithms used in automated analysis are the Watson Pragmatic and the Dean-Jett-Fox (DJF). The Watson Pragmatic model assumes that the G0/G1 and G2/M are normally distributed and fit a Gaussian curve, whereas the DJF model allows for the interpretation of abnormally distributed cell cycle phases. Agilent’s NovoExpress® software offers both and can automatically fit normal and complex S phase distribution alike.”
Image cytometry provides deeper insights
Despite flow cytometry being widely recognized as the gold standard for cell cycle analysis, image cytometry has recently seen huge uptake in this area. According to Søren Kjærulff, Ph.D., head of R&D at ChemoMetec, the main reason for this is that image cytometry enables researchers to combine quantification of cellular DNA content with morphological characterization. Using an image cytometer to visualize DNA and the subcellular localization of multiple markers in parallel, researchers can gain deeper insights without compromising the unique single-cell analysis capabilities of flow.
Image: Quantification of cell cycle phases in U2OS cells is most accurate when performing spot-based image cytometry. Image provided by ChemoMetec. For experimental details see chemometec.com.
“Image cytometry brings together the advantages of optical microscopy and flow cytometry in one platform,” he says. “While optical microscopy is a powerful technique to determine the relative abundance and distribution of markers within a cell, it requires that cells be attached to a solid surface and as such limits the number of cells that can be analyzed. In contrast, flow cytometry allows for analysis of extremely large numbers of cells in suspension, but that spatial context is lost. Using image cytometry for cell cycle analysis, researchers can rapidly interrogate large cell numbers and see morphological confirmation of results. Moreover, since image cytometry captures both brightfield and fluorescent images, it allows for visual verification of fluorescence data.”