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Cytometry

Threshold/Discriminator

Overview of Threshold/Discriminator

  • Definition: A threshold, also known as a discriminator, is a set value that an electronic signal must exceed in order to be recorded as an event by the flow cytometer
  • Purpose in Flow Cytometry:
    • Reduce Noise: To eliminate background noise and low-amplitude signals from being recorded as events
    • Discriminate Events: To selectively record events of interest while ignoring unwanted events
    • Improve Data Quality: By reducing noise and unwanted events, the overall quality of the data is improved
  • Key Concepts:
    • Threshold Level: The specific value that the signal must exceed
    • Trigger Parameter: The parameter that is used to determine whether the threshold is exceeded (e.g., forward scatter, side scatter, fluorescence channel)
    • Event Recording: Only events that exceed the threshold level are recorded and analyzed
    • Data Analysis: The threshold setting can affect the number of events recorded and the overall distribution of data

Types of Thresholds

  • Single Threshold:
    • Definition: A single value that the signal must exceed on a specific parameter
    • Example: A threshold set on forward scatter to exclude debris and small particles
  • Multiple Thresholds:
    • Definition: Multiple values that the signal must exceed on different parameters
    • Example: A threshold set on forward scatter and a threshold set on side scatter to select a specific population of cells
  • Software Thresholds:
    • Definition: Thresholds that are set and adjusted using software controls
    • Advantages: More flexible and easier to adjust than hardware thresholds
  • Hardware Thresholds:
    • Definition: Thresholds that are set using physical components on the flow cytometer
    • Advantages: More stable and less susceptible to software glitches

Setting Thresholds

  • Considerations:
    • Cell Type: The size and complexity of the cells being analyzed
    • Fluorophore Brightness: The intensity of the fluorescence signal
    • Background Noise: The level of background noise in the system
    • Experimental Goals: The specific objectives of the experiment
  • Methods:
    1. Visual Inspection: Examine the data on a scatter plot or histogram to identify the region of interest
    2. Control Samples: Use control samples (e.g., unstained cells) to determine the level of background noise
    3. Titration: Titrate the threshold level to optimize the separation between positive and negative populations
    4. Automated Thresholding: Use software algorithms to automatically set the threshold level based on the data

Trigger Parameter Selection

  • Definition: The parameter that is used to determine whether the threshold is exceeded
  • Common Trigger Parameters:
    • Forward Scatter (FSC): Used to trigger on cells based on size
    • Side Scatter (SSC): Used to trigger on cells based on granularity
    • Fluorescence Channel: Used to trigger on cells based on fluorescence intensity
  • Considerations:
    • Cell Population of Interest: Select a trigger parameter that is expressed by the cell population of interest
    • Background Noise: Avoid trigger parameters with high levels of background noise
    • Experiment Objectives: Select a trigger parameter that is relevant to the specific objectives of the experiment

Impact of Threshold Settings

  • Low Threshold:
    • Advantages:
      • Captures more events
      • Detects rare cell populations
    • Disadvantages:
      • Increases noise
      • Records unwanted events
      • Decreases data quality
  • High Threshold:
    • Advantages:
      • Reduces noise
      • Records fewer unwanted events
      • Improves data quality
    • Disadvantages:
      • Loses events
      • May miss rare cell populations

Optimizing Threshold Settings

  • Objective: To find the optimal balance between capturing events of interest and reducing noise
  • Strategies:
    1. Start with a Low Threshold: Begin with a low threshold to capture all possible events
    2. Gradually Increase the Threshold: Gradually increase the threshold level while monitoring the data
    3. Monitor the Noise Level: Pay close attention to the level of background noise
    4. Optimize Separation: Adjust the threshold to optimize the separation between positive and negative populations
    5. Confirm with Controls: Use control samples to confirm that the threshold setting is appropriate
  • General Considerations:
    • If you are performing immunophenotyping, you will want to trigger on the cells of interest
      • If you are performing immunophenotyping on lymphocytes, trigger on CD45
    • If you are performing rare event analysis, you want to cast a very wide net by setting the threshold low
    • If you want to remove any carryover from the sheath fluid as well as remove debris, you will want to set the threshold on forward scatter (FSC)

Troubleshooting Threshold Issues

  • Low Event Count:
    • Possible Causes:
      • High threshold setting
      • Incorrect trigger parameter
      • Sample preparation issues
    • Troubleshooting Steps:
      • Reduce threshold setting
      • Verify trigger parameter
      • Optimize sample preparation
  • High Background Noise:
    • Possible Causes:
      • Low threshold setting
      • Contaminated samples
      • Incorrect instrument settings
    • Troubleshooting Steps:
      • Increase threshold setting
      • Clean samples
      • Optimize instrument settings
  • Unexpected Event Populations:
    • Possible Causes:
      • Incorrect threshold settings
      • Sample contamination
      • Instrument malfunction
    • Troubleshooting Steps:
      • Verify threshold settings
      • Check for sample contamination
      • Inspect instrument for malfunctions