Flow cytometry is a laboratory technique that measures the physical and chemical characteristics of cells as they flow in a fluid suspension past a laser beam. The process generates a large dataset, where each data point represents a single cell or event. To make sense of this cellular complexity, a process called “gating” is performed, which is the practice of drawing boundaries, or gates, around populations of interest on two-dimensional plots. This systematic isolation of specific cell subsets is a foundational step in flow cytometry analysis, allowing researchers to accurately interpret experimental results.
Data Quality Checks Before Gating
Before any attempt is made to isolate specific cell populations, the raw data must be cleaned to ensure accuracy and prevent artifacts from skewing the results. The initial step involves removing debris, which are non-cellular events identified by their very low signals on scatter plots. These events typically cluster in the bottom-left corner of a plot displaying light scatter characteristics.
Another crucial cleaning step is the exclusion of doublets or cell aggregates. These aggregates can falsely inflate the counts of certain populations or distort fluorescence measurements. Doublet discrimination is typically achieved by plotting the pulse area (A) against the pulse height (H) or width (W) for a given parameter, such as Forward Scatter (FSC). Single cells show a linear relationship on this plot, while doublets appear as outliers that deviate from the diagonal line, allowing them to be excluded.
A final prerequisite for accurate gating, particularly in multi-color experiments, is the application of compensation. Compensation is a mathematical correction that accounts for spectral overlap, where the fluorescence signal from one stain “bleeds” into the detector designated for a different stain. If compensation is not correctly applied, the resulting fluorescence values will not accurately reflect the true marker expression, leading to misidentification of positive and negative populations.
Utilizing Scatter Plots for Initial Population Isolation
The first analytical step in gating utilizes the cell’s intrinsic physical properties, measured by light scatter. Forward Scatter (FSC) measures the amount of light diffracted forward and is generally proportional to the cell’s size. Side Scatter (SSC) measures the light refracted at a 90-degree angle and provides information about the cell’s internal complexity, or granularity.
By plotting FSC against SSC, distinct clusters of cells with similar size and internal structure can be visualized. In a sample of peripheral blood mononuclear cells, for example, this plot allows for the separation of major leukocyte populations. Lymphocytes, being small and agranular, cluster in the lower FSC and SSC region.
Monocytes are typically larger than lymphocytes and possess more internal complexity, placing them in a region of higher FSC and intermediate SSC. Granulocytes, such as neutrophils, are highly granular, resulting in the highest SSC values. Drawing a polygonal gate around one of these broad clusters defines the “parent” population for all subsequent analyses, ensuring that only events with the expected physical characteristics proceed to the next stage.
Defining Specific Cell Types with Fluorescent Markers
Once the broad cell populations are isolated using scatter properties, fluorescently labeled antibodies are used to define specific cell subsets based on protein expression. This process moves from histograms, which display the intensity of a single fluorescent marker, to two-dimensional dot or density plots for analyzing two markers simultaneously. The vast majority of immunophenotyping involves these two-parameter plots.
Quadrant gating is a common technique on these two-parameter plots, where two perpendicular lines are drawn to divide the plot into four sections. This allows for the precise identification of double-positive (top-right), double-negative (bottom-left), and two single-positive populations. For instance, plotting CD4 against CD8 on a previously gated T-cell population allows for the isolation of helper T-cells (CD4-positive, CD8-negative) and cytotoxic T-cells (CD4-negative, CD8-positive).
To accurately determine where to set the boundary between a positive and a negative population, controls are essential. Isotype controls, which are antibodies with no relevant target but the same non-specific binding properties, help gauge background fluorescence. However, Fluorescence Minus One (FMO) controls are often preferred in multi-color panels; these controls include all stains except the one being tested, providing a reliable measure of the background signal spillover into that specific channel.
Hierarchical Analysis and Sequential Gating Strategy
Gating is not a single, isolated action but a sequential process of refinement, known as hierarchical gating. The events selected within one gate automatically become the only events that are displayed and analyzed in the next plot, establishing a “parent-child” relationship between the gates. This systematic narrowing of the population is fundamental for accurately identifying rare or complex cell subsets.
A typical hierarchical strategy begins with the most general cleaning steps and progresses to the most specific marker expression. This sequence might start with excluding debris and doublets, followed by isolating a broad population like lymphocytes using the FSC/SSC plot. The next step would be to identify a defining marker, such as CD3 for T-cells, and then use that gated CD3-positive population to look for subsets like CD4 and CD8 expression.
This logical, ordered strategy ensures that the final analysis of a highly specific population, such as CD4-positive T-cells, is only performed on events confirmed to meet the physical and initial marker characteristics. A flaw or error in an upstream parent gate will inevitably compromise all the downstream analysis, underscoring the importance of a deliberate and systematic gating plan.