Flow cytometry is a laboratory technique that allows for the analysis of individual cells within a sample. This method measures various characteristics of cells as they pass in a single file through a laser beam. The data generated from this analysis can be complex, often involving thousands to millions of cellular events, making it challenging to interpret without further processing. To isolate specific cell types, a process known as “gating” is employed.
What Are Flow Cytometry Gates?
Flow cytometry gates are user-defined boundaries drawn on data plots that allow researchers to select and analyze specific subsets of cells from a larger population. This process involves creating a graphical boundary around a cluster of data points, where each point represents an individual cell. Cells within these boundaries are included for further investigation, while those outside are excluded.
A gate isolates a specific group of cellular events based on their measured characteristics, such as size, internal complexity (granularity), or the presence and intensity of fluorescent markers. Like sifting through beads to pull out only the red, spherical ones, gating performs a similar selective function for cells. This step in data analysis helps to focus on cells of interest and remove unwanted particles or debris that might obscure meaningful results.
The Purpose Behind Gating
Gating allows for the accurate identification, quantification, and characterization of specific cell populations within a heterogeneous sample. Without gating, the sheer volume of data from different cell types and non-cellular events would be overwhelming and difficult to interpret. It enables researchers to accurately distinguish between various cell types, even within a complex mixture like blood, where numerous cell lineages coexist.
A primary purpose of gating is to isolate specific cell types, allowing researchers to focus on the cells relevant to their study. It also excludes unwanted events, such as dead cells, cellular debris, or cell aggregates (clumps of cells), which can lead to inaccurate measurements and skewed results. Removing these confounding factors improves the accuracy and precision of flow cytometry data analysis, ensuring that the insights gained are reliable and biologically relevant.
Visualizing Gating
Flow cytometry data is displayed on scatter plots or histograms, which provide a visual representation of cell characteristics. Common plot types include forward scatter (FSC) versus side scatter (SSC) plots, estimating cell size and internal granularity. Other plots display the intensity of different fluorescent markers, indicating the presence or absence of specific proteins on or within cells.
Researchers apply gates by drawing shapes like rectangles, ovals, or polygons around clusters of cells with similar characteristics on these plots. For instance, on an FSC vs. SSC plot, lymphocytes, monocytes, and granulocytes often form distinct clusters based on their unique size and granularity, allowing for separation by drawing specific gates around each population. Cells whose measured properties fall within a gate’s boundaries are selected for subsequent analysis.
Insights from Gated Data
Once cell populations have been gated, quantitative and qualitative information can be derived. Gating enables the precise quantification of specific cell types within the original sample. For example, after gating on T cells, researchers can determine the percentage of helper T cells (CD4+) or cytotoxic T cells (CD8+) within that isolated population.
Beyond percentages, gating allows for the assessment of cell population purity, ensuring that subsequent analyses are performed on a relatively homogeneous group of cells. It also facilitates the analysis of marker expression levels on isolated cell subsets, providing insights into their functional state or differentiation. This information contributes to understanding various biological processes, including disease progression, immune responses, and cellular function.