Gating and the “Art” of Flow Cytometry
Posted on: Nov 14, 2017
Flow cytometry gating can often seem like a daunting task. While there is no single solution, experienced cytometrists can recommend several tips beyond “praying for good data”. Here we define gating, explore gating methodologies, and provide some useful tips for properly gating your cells.
- Forward/Side Scatter Gating
- Single Parameter Gating
- Multiparamter Gating
- General Recommendations
- Gating Strategies
Gating is simply a fancy term for grouping cell populations based on common characteristics. However, distinguishing cell populations in samples with multiple cell types of similar sizes can be somewhat subjective. This is where the “art” of flow cytometry comes in.
Flow cytometry data is typically displayed as a dot plot, density plot or contour map. Modern analysis software allows researchers to group cell populations by simply drawing polygons (gates) around cell groups within the plot. These gated groups can then be further investigated and quantified during data analysis.
Forward/Side Scatter Gating
The main parameters for grouping cell populations are forward scatter (FSC), side scatter (SSC) and marker expression. Forward and side scatter measurements give an estimation of the size and granularity of the cells, and are most useful to find viable, single cell events.
Due to their smaller size, dead cells and cellular debris typically have a lower level of forward scatter and are therefore found at the bottom left corner of the density plot. Researchers can increase the forward scatter threshold to avoid collecting these events, or simply exclude them from their positive gates if a small amount of debris is still detected. However viability dyes are recommended to ensure proper identification of living cells.
After identifying the populations of interest using FSC and SSC, researchers can perform further analysis on the expression of markers within these cells.
Gating Single Parameters
Measuring a single parameter (marker) will produce a univariate histogram, typically with multiple peaks due to population mixing. Researchers must therefore use appropriate controls including FMO and unstained controls to accurately identify their positive dataset. They can then analyze the positive cell populations with measurements including the number/percentage of cells within the gate, or the mean/median fluorescence intensity.
Gating Multiple Parameters
Measuring two markers produces a two-parameter density plot, with one parameter on the x-axis and the other on the y-axis. These can include FCS, SSC or fluorescent markers. Grouping these populations produces a bivariate histogram, which divides the plot in four quadrants for the four possible combinations: double positive, double negative, and two single positives. It is up to the individual researcher to set the threshold for each of these groups.
This basic gating principle can be applied multiple times to further investigate the expression patterns on each cell type.
Backgating is used to confirm a staining pattern or gating method by analyzing cells on dot plots with different parameters. This allows cells in the final gate to be visualized at a higher level to ensure the gate was placed properly. It is most useful if you are unsure of your marker expression levels, suspect non-specific binding or are in doubt about your gating strategy and need additional information to identify your populations.
Flow cytometry gating can be greatly simplified by asking yourself these questions:
- What are your populations of interest? – Check the literature for information on defining your populations
- What size are your cells? – Consider all living types in your sample and whether they may change size under different conditions. Be sure to exclude doublets/clumped cells via pulse gating or dead cells/debris via viability dye and FCC gating.
- Which markers are expressed? – Consider disease state and other conditions that can affect expression levels.
- Am I using the proper controls? – These typically include viability dyes as well as FMO, Internal negative, unstimulated, and isotype controls.
- Do I have an appropriate Analysis Software? – There are many commercially available analysis software options optimized for different hardware or specific types of analysis. Find a complete list on our analysis software page.
Common Gating Strategies
Flow Stability — Gating based on the flow stream stabilization is useful to eliminate the effects of clogging, back-pressure, etc.
Pulse Geometry — Gating based on pulse area is useful to identify/exclude doublets from the dataset.
Forward & Side Scatter — Gating based on FSC/SSC (described above) is useful to remove dead cells/debris based on size or granularity.
Subset gating — Gating based on one or more marker expression parameters (described above) is the most important data analysis method for flow cytometry.
Backgating — Visualizing cells on dot plots with different parameters (described above) is useful to determine if any cells have been missed by the current gating strategies.