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6 Areas Of Consideration For Flow Cytometry Cell Cycle Analysis

Written by Tim Bushnell, PhD

As discussed previously, cell cycle assays require optimization of fixation and dye concentrations, but that is just the beginning. There are important considerations when performing the assay to ensure high-quality data. Cell cycle experiments are judged by the CV of the G0/G1 peak, and the best way to get a good peak is to run the experiment as slow as possible. Likewise, since the cell cycle assay is run with linear amplification, the PMTs must be monitored and their linearity measured.

Even with those 2 aspects on the machine mastered, there are additional details (like synchronizing the cell culture) that need to be considered. Even more so is the fact that the cell cycle assay lends itself to multiplexing, allowing for more information to be extracted from each sample. Those add-ons to the basic protocol need to explored and optimized as well.

Thus, here are 6 areas of consideration for cell cycle analysis covering these important topics.

1. Run cell cycle analysis low and slow

Acquisition of cell cycle data is not like phenotyping. First, data is acquired with linear amplification, rather than logarithmic amplification. Unlike the expression of surface markers (where there can be a wide range of expression), with cell cycle data, the range of expression is much more restricted. If the G0/G1 peak is set at 10,000, the G2/M peak would be around 20,000. Second, the quality of the data is assessed by the spread of the G0/G1 peak, so running the samples at a low flow rate is critical. The consequences of high flow rates are shown in Figure 1.

Figure 1: Impact of flow speed on data quality. The blue peaks show the results of data acquired at low flow rate. The red peaks show data acquired at high flow rate. At high flow rate, the peaks broaden and shift, both of which compromise the quality of the data.

2. Check PMT linearity

Another important component of acquiring cell cycle data is that the detectors, the PMTs, need to be linear. One way to check this is to use a standard, like Chicken Erythrocyte Nuclei (CEN), as shown in Figure 2. After setting the voltage, gate on each of the populations and take the mode value (most common value in the gate). The ratio of the peaks 1 to 2, or 1 to 3, should be 2 or 3. The closer this is to linear, the better the quality of data.

Figure 2: CEN stained with 50 μl/ml PI staining buffer containing RNase.

In an ideal world, the cell cycle data would look like the theoretical plot shown in Figure 3, left plot. In this case, the G0/G1 is a peak in a single channel, and the G2/M is a peak in a single channel with twice the fluorescence intensity of the G0/G1. The line connecting the 2 peaks represents the S-phase. The red line in the left plot represents a common control used in cell cycle analysis — in this case, trout nuclei.

The reality of the data is shown on the right, and the spread of the data comes from the sample preparation and instrument.

Figure 3: Ideal cell cycle data (left) and the reality (right).

3. Controls are critical

One very useful control to add to cell cycle analysis is a DNA standard control. The most common controls are either chicken or trout nuclei (CEN and TEN). Using one or both of these controls can help consistently establish proper voltages, as well as help sort out how different populations may be changing. In this example from Darzynkiewicz et al., (2017) (Figure 4), the breast cancer cells were stained and CEN and TEN were used to help establish the position of the diploid (D) and aneuploid (A) cells.

Figure 4: Use of CEN and TEN as a control for cell cycle analysis. From Darzynkiewicz et al., (2017).

These controls are especially important when studying aneuploid cells, and for longitudinal studies. CEN, for example, have a DNA content that is 35% that of human DNA, while TEN have 80% of human DNA, which makes them ideal controls (Vindelov et al. 1983). By staining these 2 controls, establishing voltages and calculating ploidy is a breeze.

4. The Sub-G0 peak is not just apoptotic cells

As cells die and undergo apoptosis, DNA fragmentation occurs. This can manifest itself in the cell cycle histograms as a population to the left of the G1 peak. Compare these 2 figures from Darzynkeicwicz et al., (2010):

Figure 5: Appearance of sub-G1 peaks on cell cycle profiles. From Figure 2 Darzynkeicwicz et al., (2010).

The inclination of some investigators is to put a region around this area and call that the percentage of apoptotic cells. However, what is really in that population? If we use plates as an analogy for cells, the issues with subG1 analysis become clear. In Figure 6, we have a hypothetical DNA histogram with a G1 peak and sub-G1 peak. The plates represent whole cells and are in the G1 phase. Now, the sub-G1 peak represents cells undergoing apoptosis, or being “broken”. Based on the picture above, how many plates are broken?

Figure 6: Why the sub-G1 peak can’t be used to calculate apoptosis. Thanks to Mark Munson for this explanation.

Since the composition of the Sub-G1 peak is a mixture of many cell fragments, it is not a useful marker for determining the percentage of apoptotic cells. It can give you a suggestion that apoptosis is occurring, but use a more robust method like the Annexin-V assay to measure apoptosis.

5. Synchronizing cells when performing drug studies

When performing a drug study to explore the effects of your drug of choice on cell cycle progression, synchronizing of the culture is critical. Since cells are all going through cell cycle at different rates, if the culture is not synchronized, it will be very difficult to determine the impact of the drug unless the cells are synchronized.

There are several popular techniques for synchronizing cells at a specific stage of the cell cycle, which are reviewed by Jackman and O’Connor and are summarized in Figure 7.

Figure 7: Methods for synchronizing cells at specific stages of the cell cycle. From Figure 8.3.1 in Jackman and O’Connor.

Serum starvation is a popular technique for synchronizing a culture. By removing serum from an actively growing culture, within 24 to 48 hours, you can get the cells to stop at the G0/G1 phase. When serum is added, the cells will resume the cell cycle.

Nocodazole disrupts microtubule, so prevents cells from undergoing Mitosis. It is easily reversible, and allows for isolation of cells in M-phase in about 12 to 16 hours.

6. Consider multiplexing for more information

If you are going to the trouble of performing a cell cycle analysis, why not expand the assay a bit and get that much more information about the cells?

  1. BrDU for S-phaseBrDU and the related EdU are thymidine analogs that can be used to better identify the S-phase. The assay is relatively straightforward: by pulsing the culture for some period of time with BrDU, it will get incorporated into the actively synthesizing cells. The BrDU is measured with an antibody, while EdU uses “Click-iT” technology to reveal the labeled cells. The resulting data is shown in Figure 8.Figure 8: Using BrDU to reveal the S-phase of the cell cycle. Figure from Tonbo LiteratureThe BrDU pulls out the S-phase cells, making it easier to identify this phase of the cell cycle.
  2. Ki-67 for proliferationAntibodies against Ki-67 are useful, as they are a marker of proliferation and can be used to differentiate quiescent cells from cycling cells.Figure 9: Separating quiescent cells from cycling cells. From Kim and Sederstrom (2015).
  3. Phospho-H3 for M phase determination Histone H3 is phosphorylated during mitosis at the Ser-10 and Ser-28, thus serves as an excellent tool to separate the G2 from the M phases, as shown in Figure 10.Figure 10: Use of pH3 to separate M phase from G2 phase. Figure from ThermoFisher websiteConsider the possibilities. Using these tools in combination with traditional cell cycle staining can really dissect this important biological process. The caveat when moving into multiplexing cell cycle measurements is that the fixation conditions need to be optimized to ensure good staining of each component. For example, fixation with formaldehyde may be necessary to ensure good antibody staining, but this might need to be followed up with alcohol fixation to improve the cell cycle staining. Optimization is the key here.

Cell cycle seems like such a straightforward assay. At its heart, it is a one-color assay and should be a simple protocol to follow. However, as discussed before, fixation and dye concentrations are critical. Once those are optimized, it becomes important to run the cells low and slow to get the best quality histograms for analysis — the topic of another blog. Adding the critical CEN and TEN controls will help standardize the assay, and ensure consistency and reproducibility between runs, while helping identify non-standard (aneuploid, polyploid) populations from normal ploidy. Trying to isolate and focus on specific components of the cell cycle can be done by addition of specific antibodies, or using thymidine analogs. In the end, cell cycle analysis is a simple assay that has a great deal of potential. With work and optimization, a great deal of information about the life of a cell can be extracted.

To learn more about the 6 Areas Of Consideration For Flow Cytometry Cell Cycle Analysis, and to get access to all of our advanced materials including 20 training videos, presentations, workbooks, and private group membership, get on the Flow Cytometry Mastery Class wait list.

Tim Bushnell, PhD

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