All cells govern their reproduction according to the mysterious rules—still being unearthed by scientists—of the cell cycle. When the cell cycle gets out of whack, the consequences can include cancer as well as Alzheimer’s and Parkinson’s diseases. Researchers study cell cycle dysregulation using cell cycle analysis (CCA), in which a population of cells is examined to ascertain how many cells are in which stages of the cell cycle (e.g., G1, G2, S, and M phases). CCA has long been performed as a flow cytometry assay, even being used clinically to analyze tumor cells in the hopes of gaining information about a patient’s cancer aggressiveness. Today CCA can also be performed using imaging cytometry instead of flow cytometry.
At its core, a CCA assay (whether by flow or imaging cytometry) is straightforward: a cytometer detects fluorescent DNA dye with a cell population, and analysis software constructs a histogram of the data, with peaks indicating the relative proportion of cells in different cell cycle phases. Narrower, sharper, well-separated histogram peaks are the goal because they give the clearest results, but obtaining high-quality histograms is not always easy. This article will address the benefits of flow vs. imaging cytometry, and discuss ways to optimize CCA assays so that histograms are as clear as possible.
Flow vs. imaging cytometry
If you simply want to know what percentage of cells are in different phases of the cell cycle, traditional flow cytometry is fast, accurate, and well-optimized for doing that. But according to Dmitry Kuksin, head of reagent development and commercialization at Nexcelom Bioscience, the power of image cytometry lies in the fact that scientists love having pictures of their cells. “They love having a cell cycle histogram and being able to relate it to a picture of a population that they can see and understand— do the nuclei look plump and round, or shriveled?” says Kuksin.
When Nexcelom performed side-by-side CCA experiments using an image cytometer and a traditional flow cytometer, they got identical results. “It was exciting to be able to communicate to other scientists that image cytometry is another tool that you can use in parallel to traditional flow cytometry,” says Kuksin. In the publishing world, academic reviewers are beginning to view image cytometry as an orthogonal technique that can bolster your original results obtained by traditional flow cytometry. “It’s a complementary, not a competitive, tool,” says Kuksin.
At Nexcelom, there are two main ways to perform CCA using an image cytometer—with cells in suspension (as in flow cytometry, which means trypsinizing adherent cells), or with adherent cells on plates (without trypsin; not an option in flow cytometry). With the latter method, “you can fix your cells right onto the plate, wash off the fixative, stain with your cell cycle reagent, and image cells right on the plate,” says Kuksin.
Imaging cytometry also produces subcellular localization information of labeled proteins. “Additionally, you get locations of different molecules that you might be interested in, such as proteins involved in the cell cycle,” says Sherree Friend, product portfolio manager of imaging flow cytometry at Luminex. “Imaging cytometry allows you to analyze those related proteins too, including how much and where those proteins are located within cells at different phases of the cell cycle.”
Luminex offers three traditional flow cytometry instruments, and two imaging cytometry instruments, each with varying features and levels of complexity to suit their customers’ needs. Their newest release is the Cellstream, a traditional flow cytometry system that is highly flexible with respect to configuring different lasers. It can measure up to 20 fluorophore colors, and is extremely sensitive, owing in part to detection via a CCD camera (rather than PMTs). Luminex also offers the FlowSight (20X) and the higher-resolution ImageStream (60X) imaging cytometry systems.
Optimizing sample preparation
One of the most important, though sometimes overlooked, ways to optimize CCA histograms lies in sample prep. Optimizing sample preparation for flow versus imaging cytometry is generally similar.
Buffers. “One exception is that for imaging cytometry, you should use reagents designed to maintain cell integrity,” says Friend. Luminex sells reagent kits for imaging cytometry containing optimized assay and fixation buffers, as well as an optimized protocol. “With traditional flow cytometry, because you can’t see your cells, they might be damaged and you can’t tell—you could have apoptotic or necrotic cells and not realize it, because all you detect is the intensity of the DNA stain,” notes Friend. “With imaging cytometry, you can actually see apoptosis by the condensation and breaking apart of the chromosomes, and we have algorithms that can measure that and eliminate apoptotic cells from your analysis.”
It’s also helpful to be aware of the buffer system being used in the CCA protocol, because some antibodies used in CCA work best in different types of buffer systems. “Being aware of what buffers your antibodies require relative to what your CCA kit comes with is important, and some types of cells can benefit from buffer optimizations,” says Lissette Wilensky, senior scientist at BD Biosciences.
DNA dyes. Common DNA dyes used in CCA assays include propidium iodide (PI) and DAPI. Dyes used for CCA must bind DNA stoichiometrically, so that the fluorescence signal detected from stained DNA is directly proportional to the amount of DNA present. Wilensky recommends ensuring that the instrument’s bandpass filter matches the dye to be used. “Some new dyes fluoresce differently, so it’s a good idea to check.”
A recent innovation in CCA tools is the BrdU- and EdU-based reagents for detecting nuclear DNA. The antibody-based BrdU method is more easily multiplexed, and can be combined with other antibodies for cell cycle probes or intracellular markers. The click-chemistry-based EdU method uses probes that enter the nucleus more easily, but must be performed separately from immunostaining. “The EdU kit needs to be a separate step, because the click chemistry reaction requires copper, which may interfere with antibody conjugates,” says Wilensky.
Choosing cell populations. As in traditional flow cytometry, Kuksin says that it’s important to choose the appropriate population of cells to analyze; for example, a researcher may want to eliminate debris or apoptotic cells by using forward and side scatter. “In image cytometry we do something similar by selecting the cell population based on cell size and then verifying the selected cells by looking at the images,” says Kuksin. “You can change the roundness, aspect ratio, and cell size to obtain the appropriate population for analysis.” After you select the population, the data are automatically exported into flow cytometry software for further analysis.
A common pitfall is that sometimes researchers don’t realize that treating cells with drugs may inevitably damage or alter the cellular DNA. “Therefore you cannot expect that your control cell cycle histogram will be overlaid or will have identical parameters for your drug-treated samples,” says Kuksin. “Remember that your cell cycle histogram for drug-treated samples may be shifted compared to control, due to drug-induced cellular damage” that can be compensated for during analysis.
Cell cycle analysis going forward
CCA is opening new lines of scientific inquiry, especially in immuno-oncology. For example, researchers are using CRISPR/Cas9 technology to create cancer models from cell lines. CCA allows them to test these cancer cell models for growth characteristics, and to see how these cells react to drug therapies. “They treat the model cells in a dose-dependent manner with a single drug or combinational drug therapy, and then over time look at parameters like viability, apoptosis, and CCA,” says Kuksin. Oncology researchers studying solid tumors can now do CCA on adherent cell line models without having to disturb the cell growth by trypsinizing them for traditional flow cytometry. “By using image cytometry they can image and analyze the cells directly in the plate, which more closely mirrors the natural tumor environment,” says Kuksin.
For mitosis researchers, imaging cytometry is especially valuable because different stages of mitosis can be defined by morphology, such as chromosome condensation and spindle formation. “You can also label cell cycle proteins like laminin, and [by taking snapshots in time] see them move to particular locations around the chromosomes, then move out to the daughter cells as cell division starts to happen,” says Friend. “[By looking at different time points], you can see the nuclear envelope breaking down, and you can watch the separation of laminin proteins to the different daughter cells.”
Imaging cytometry is also useful for research on asymmetric cell division, when a cell divides into two daughter cells such that the original cell’s contents are not evenly split. “It’s when you want to look specifically at subsets of mitosis, what’s going on with the locations of proteins around mitotic events, and correlations with cell size, where imaging cytometry has added a lot of benefit to cell cycle analysis,” says Friend.
A scientist fortunate enough to be faced with a choice between using a flow vs. imaging cytometer for CCA assays should consider speed and imaging ability, advises Wilensky. “If you are doing cell cycle analysis on a large number of cells, or on a rare cell subset, then traditional flow cytometry is better,” she says. “But if you want to multiplex cell cycle analysis with other immunostaining within the cells, then an imaging cytometer is definitely needed to quantify that.” Imaging cytometers are not new, and have in fact been around for awhile. “But recently, imaging cytometers have been getting faster, which makes them more valuable as a tool for cell cycle analysis,” says Wilensky.