Flow Cytometry Gating: A Comprehensive Guide

Flow cytometry gating is a critical step for isolating and analyzing specific cell populations based on size, granularity, and fluorescence. Proper gating strategies enhance data accuracy by excluding irrelevant or compromised events such as doublets, dead cells, and debris, ensuring that the analysis focuses on relevant, viable cells.

Gating is the process of setting criteria to identify cell populations of interest based on specific parameters in flow cytometry. Gating helps:

• Exclude unwanted events: Filters out dead cells, debris, and doublets.
• Focus on single cells: Isolates single, viable cells for precise data analysis.
• Identify specific cell populations: Differentiates based on fluorescence markers, size, and granularity.

Forward Scatter (FSC) and Side Scatter (SSC) are used to analyze cell size and granularity, respectively.

1. FSC: Measures cell size based on light scattered forward. Larger cells produce higher FSC values.
2. SSC: Measures internal complexity or granularity. Cells with high granularity, like granulocytes, produce higher SSC values.

Setting the FSC vs. SSC Gate

• Plot FSC-A (area) vs. SSC-A: Draw a region to capture your primary cell population. This first gate will exclude debris, as debris has lower FSC and SSC values.

Doublets and clumps can resemble larger single cells, introducing variability in measurements. Doublet discrimination ensures that the analysis focuses on single cells.

• FSC-A (Area): Reflects total signal area; larger values can indicate clumps.
• FSC-H (Height): Measures the signal’s peak height, generally lower in doublets.

Plot FSC-A vs. FSC-H

• Single cells typically appear along a linear, diagonal line, while doublets deviate from this line.
• Gate along the linear population in FSC-A vs. FSC-H to exclude doublets.

• FSC-W (Width): Measures pulse width, typically wider for doublets.
• Plot FSC-W vs. FSC-H: Exclude events with high FSC-W, indicative of doublets.

Dead cells can nonspecifically bind antibodies, causing non-specific fluorescence. Use a viability dye to stain dead cells and exclude them.

• 7-AAD (7-Aminoactinomycin D): Enters only dead cells, showing fluorescence in dead cell populations.
• Propidium Iodide (PI): Intercalates with DNA of compromised cells, emitting fluorescence in dead cells.
• Live/Dead stains: Available in various fluorescent colors, useful in multicolor panels.

Plotting Viability

Using fluorescence-conjugated antibodies, flow cytometry can differentiate cell populations based on the expression of specific markers.

• Select non-overlapping fluorophores to minimize spectral overlap.
• Compensation controls are essential to correct for spectral overlap in multicolor experiments.

For T cell analysis, specific markers like CD3 for T cells, CD4 for helper T cells, and CD8 for cytotoxic T cells are commonly used.

Step-by-Step Gating

1. Set Primary FSC-A vs. SSC-A Gate: Exclude debris.
2. Apply Single-Cell Gate: Use FSC-H vs. FSC-A to include single cells.
3. Dead Cell Exclusion: Gate out dead cells stained with viability dyes.
4. Population-Specific Gating:
• CD3+ Gate: Identify T cells.
• cells (CD8+).

FMO controls are critical in multicolor flow cytometry to set accurate gates, as they show fluorescence spillover from other channels without the specific marker in question. Use FMO controls to:

• Determine where to set boundaries between positive and negative populations.
• Avoid false positives due to spillover in overlapping fluorescence channels.

• Adjust gates for each experiment: Cell populations can vary by sample, so adjust gates accordingly.
• Run controls: Include positive and negative controls to accurately identify populations.
• Use sequential gating: Move from broad gating (debris exclusion) to more specific gating (population markers).
• Optimize compensation: Use single-stain controls to set compensation correctly in multicolor
  experiments.

By following these gating strategies and using controls, you can achieve precise identification and quantification of cell populations in flow cytometry, ensuring reliable and interpretable data.