After completing the perfect staining and cytometry run, the hard work begins – data analysis. To properly identify the cells of interest, it is critical to pull together knowledge of the biology with the controls run in the experiment to properly place the regions of interest that will be dictate the final results. Gating is an all-or-nothing data reduction process. Cells inside the gate move to the next checkpoint, while cells outside the gate – even by a pixel, are excluded.
1. Before beginning, know as much as you can about the populations of interest. While it may sound flip, knowing what cells are the target of the experiment are critical.
How these cells are identified in the literature, or by past experience should guide the experiment. Check this first to ensure the proper stains are being used, and the proper controls are in place to analyze the data.
2. Size isn’t everything. The reliance on forward and side scatter gates as a way to identify lymphocytes from other cells can be rife with peril. Blasting lymphocytes are larger than resting cells, and can be missed if there is a tight forward vs side scatter gate.
It is best to use the scatter gate to remove the debris on the left size of the plot, as well as the small, pyknotic cells that are often FSC small and SSC complex . Or, even better, use a FSC vs. viability dye gate. This will clearly eliminate both dead cells and debris from your analysis.
3. Check the stability of the run. Plot a time vs a scatter plot to see how even the flow was during the run.
Using a plot like this will help eliminate artifacts caused by poor flow. Check out the plot below. The left plot shows good, even flow, while the right plot shows poor flow.
4. Delete the doublets. As shown in the figure below, cell clumps, when they pass through the laser intercept, will take longer than single cells. This in turn, affects the area of the signal. Using a pulse geometry gate (such as FSC-H x FSC-A), doublets can be easily eliminated.
5. Let your controls be your guide. The controls run in for the experiment are critical for ensuring the proper cells are identified. An FMO control, for example, is critical for identifying the proper placement of a gate in a multi-color experiment. The spread of the data due to the fluorochromes in the panel cannot be corrected for using an isotype control (for example). As shown below, the cells in the red circle represent cells that are in this spread region, and thus should be excluded. To fully optimize this panel; however, it would be wise to use a brighter antibody.
Without the FMO control, these cells would have been included in the analysis.
6. Break into the back gate. The back gating tool is one that allows the inspection of the data to determine what cells would fall in the final population, assuming the gate of interest was not used in the gating scheme.
In the third panel, especially, there a lot of cells that would be included in the final gate, assuming the gate was not used. Knowing that those cells are positive for a viability marker (and thus, should be excluded) helps confirm thee placement of the gate.
My other passions include grilling, wine tasting, and real food. To be honest, my biggest passion is flow cytometry, which is something that Carol and I share. My personal mission is to make flow cytometry education accessible, relevant, and fun. I’ve had a long history in the field starting all the way back in graduate school.
Latest posts by Tim Bushnell (see all)
- 3 Advantages FCS Express 6 Has Over Other Flow Cytometry Data Analysis Software Programs - September 6, 2017
- 4 Steps To Validate Flow Cytometry Antibodies And Improve Reproducibility - August 23, 2017
- Why Understanding Fluorochromes Is Important In Flow Cytometry - August 9, 2017