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Multicolor Flow Cytometry Workshop. Holden Maecker, PhD. Learning Objectives. Explain the critical aspects of digital and multicolor flow cytometry that make it different from traditional analog flow cytometry with 1 – 4 colors

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Multicolor Flow Cytometry Workshop

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learning objectives
Learning Objectives
  • Explain the critical aspects of digital and multicolor flow cytometry that make it different from traditional analog flow cytometry with 1–4 colors
  • Describe the role of instrument configuration in the performance of multicolor flow cytometry
  • Perform instrument QC using BDTM Cytometer Setup and Tracking beads, and understand the use of baseline and application settings in BD FACSDivaTM software
  • Design a robust multicolor reagent panel, understanding the role of spillover, tandem dyes, and antibody titration
  • Create appropriate controls for a multicolor experiment, and be able to find and correct potential problems in multicolor data
schedule day 1
Schedule: Day 1

9:00–10:30 I. Introduction, review of basic concepts

10:30–10:45 Break

10:45–11:45 II. Digital and multicolor flow cytometry

Exercise 1: Adjusting biexponential displays

12:00–1:00 Lunch

1:00–2:00 III. Instrument setup, optimization, and QC

Exercise 2: Determining stain index and spill index

2:00–4:00 Acquisition of data:

  • Instrument characterization using CS&T
  • Baseline and application settings determination
  • Compensation using BD™ CompBeads
  • 8-color stained PBMCs
schedule day 2
Schedule: Day 2

9:00–10:00IV. Design and optimization of multicolor panels:

  • Selection of fluorochromes
  • Matching fluorochromes with antibody specificities
  • Determining application-specific settings

Demonstration: Visualizing data on a virtual cytometer

10:00–12:00 Data analysis in BD FACSDiva software

12:00–1:00 Lunch

1:00–2:30 V. Controls and Data QC

Exercise 3: Finding and correcting a spillover problem

2:30–2:45 Break

2:45–4:00 Review and summary, discussion of participant issues

  • Definitions, what can be measured by flow cytometry
  • Fluidics: Sheath and sample streams, flow cells, sorting
  • Optics: Lasers, filters
  • Electronics: PMTs, signal processing
  • Fluorochromes: Spectra, spillover
  • Data analysis: FCS files, gating, statistics
  • Flow cytometry: The study of cells as they move in fluid suspension, allowing multiple measurements to be made for each cell.
  • FACSTM: Fluorescence-activated cell sorting
what measurements can be made
What Measurements Can Be Made?
  • Forward scatter (FSC): Proportional to cell size
  • Side scatter (SSC): Proportional to cell granularity
  • Fluorescence:
    • Binding of fluorescent-labeled antibodies
    • Ca++-sensitive dyes within cells
    • Fluorescent proteins expressed by cells
    • Binding of DNA dyes
scatter profile of lysed whole blood

Largestand most granular population





Side Scatter




Smallestand least granular population









Forward Scatter

Scatter Profile of Lysed Whole Blood
fluorescence data display
Fluorescence Data Display

Negative control histogram


Number of Events

FITC Fluorescent Intensity 


major components of a flow cytometer
Major Components of a Flow Cytometer
  • Sample injection port
  • Sheath and waste reservoirs
  • Flow cell
  • Laser(s)
  • Optical filters
  • Photomultiplier tubes ( PMTs ) or photodiodes
  • Signal processor
cytometer fluidics create laminar flow
Cytometer Fluidics Create Laminar Flow

Sample stream

Flow cell

Sheath stream

Laser beam


multicolor experiment cytometer configuration
MulticolorExperiment Cytometer Configuration

Longpass filter

Bandpass filter


background and autofluorescence
Background and Autofluorescence

All cells have a certain level of background fluorescence due to:

  • Autofluorescence from pigments and fluorescent moieties on cellular proteins
  • Non-specifically bound antibodies and free antibody in the sample stream

The level of autofluorescence varies with the wavelength of excitation and collection:

  • Highest in FITC, PE detectors
  • Lowest in far red (APC, Cy™7) detectors
fluorescence sensitivity
Fluorescence Sensitivity

Detection Efficiency (Q): The number of photoelectrons generated per molecule of fluorophore

  • Dependent upon fluorophore, laser, filters, PMT sensitivity, voltage gain setting, etc.

Background (B): Non-specific signal intrinsic to the system

  • Dependent upon autofluorescence, unbound fluorophore, ambient light, etc.
fluorescence spillover
Fluorescence Spillover

Emission of FITC in the PE channel

compensating for spillover

1,650 – 185

  • 3,540 – 125
Compensating for Spillover



FITC mean fluorescence PE mean fluorescence

---------------------------- ----------------------------

Negative Positive Negative Positive

----------- ---------- ----------- ----------

Uncompensated 125 3,540 185 1,650

Compensated 125 3,560 135135

% Spillover =

X 100

fcs files
FCS Files
  • FCS 2.0 and FCS 3.0 conventions
  • Often referred to as list-mode files
  • Contain all of the measurements (FSC-H, FSC-A, SSC-H, SSC-A, FL1-H…) for each individual cell processed in a given sample
web reference tools
Web Reference Tools
  • BD Spectrum Viewer:

  • Maecker lab weblog:

(protocols, manuscripts, literature updates)

differences from analog instruments
Differences From Analog Instruments
  • Optics: Fiber optics and octagons/trigons
  • Fluidics: Optimized for high flow rates
  • Electronics: Digital signal processing
pmt octagon and trigon
PMT Octagon and Trigon






filter nomenclature conventions
Filter Nomenclature Conventions

Longpass (LP) filter: Allows light above a certain wavelength to pass, reflects shorter wavelengths

  • Example: 505 LP = 505 nm longpass

Bandpass (BP) filter: Allows light within a certain range of wavelengths to pass (above and below a specified midpoint)

  • Example: 530/30 BP = 515–545 nm bandpass
effect of flow rate
Effect of Flow Rate
  • Higher flow rates mean a broader sample stream ( less precise focusing)
  • Less precise focusing means less accurate fluorescence measurement of dim populations ( population spreading)
  • Higher flow rates also increase the frequency of coincident events (can be gated out based on FSC area vs height)
  • In practice, flow rates of 8,000–12,000 events per second are acceptable on the BD™ LSRII (vs 2,000–3,000 events per second on a BD FACSCalibur™ flow cytometer)
digital signal processing
Digital Signal Processing

Generates high resolution fluorescence values that can include negative numbers

  • No compression of populations at the low end of the fluorescence scale
  • More accurate representation of dim populations

Allows compensation to be performed in the software at any time

  • Uncompensated data and any associated compensation matrix are both stored
  • Compensation can be changed at any time

Peak area and peak height can both be recorded for all parameters

biexponential display of digital data
Biexponential Display of Digital Data

Antibody capture beads

stained with 3 levels of

an APC reagent

The transformed display

shows aligned populations

In the APC-Cy7 dimension

APC-Cy7 Area

All populations

align correctly

APC Area

spillover affects resolution sensitivity
Spillover Affects Resolution Sensitivity

Without CD45 AmCyan

With CD45 AmCyan


  • Optical platforms using octagons and trigons result in more efficient light collection and flexibility in the use of detectors and filters
  • BD LSR II fluidics allow running at higher flow rates with minimal compromise to the data
  • Digital signal processing provides more accurate representation of dim populations, and more accurate and flexible compensation—but logarithmic data display may not be appropriate
  • More colors mean more spillover issues, with loss of resolution sensitivity in affected detectors
exercise 1
Exercise 1

Adjusting biexponential displays:

  • Open the FCS file “exercise1.fcs”
  • Gate on small lymphocytes, then on double-positive events for CD45 AmCyan vs CD3 Pacific Blue
  • From this gate, create a plot of CD4 FITC vs CD8 APC-H7
  • Turn on biexponential scaling for the x- and y-axes, and note the changes to the plots
  • Turn on manual biexponential scaling and experiment with various scaling factors for FITC and APC-H7, noting how the plots change


  • Would gating be affected by biexponential scaling?
  • Is it important to use the same scaling for all samples in an experiment?
  • Configure your instrument
  • Characterize your instrument
  • Design your panel
  • Optimize settings for your panel
  • Run appropriate controls
  • QC your data
  • Configure your instrument
      • Number and type of lasers
      • Number of PMTs per laser
      • Choice of filters and dichroic mirrors

These choices will determine:

      • What fluorochromes you can use effectively
      • How well certain fluorochrome combinations will perform
how do we measure performance



How Do We Measure Performance?

Resolution Sensitivity


Stain Index = D / W

Where D = difference between positive and negative peak medians

W = 2 x rSD (robust standard deviation)

an example green vs blue lasers

CD127 PE




25 mW green laser (532 nm)


100 mW blue laser (488 nm)

Stain index


25 mW blue laser (488 nm)










PMT voltage

An Example: Green vs Blue Lasers
  • Green laser is more efficient for PE and PE tandems
  • Blue laser is more efficient for FITC, PerCP, and GFP
  • Characterize your instrument
      • Obtain minimum baseline PMT settings
      • Track performance over time

This allows you to:

      • Run the instrument where it is most sensitive
      • Be alert to changes in the instrument that might affect performance
automated baseline pmt voltage determination using bd cs t
Automated Baseline PMT Voltage Determination Using BD CS&T

Baseline PMTV is set by placing the dim bead MFI to equal 10X SDEN

460 V

SDEN = 20

MFI= 200

performance tracking

FITC Channel (Blue laser)




PMT Voltage














Performance Tracking

A variety of parameters can be tracked:

  • Linearity, CVs, laser alignment
  • PMT voltages must hit target values

Data can be visualized in Levey-Jennings plots:

exercise 2
Exercise 2

Calculating stain index and spill index:

  • Open the FCS file “exercise2.fcs” (AmCyan Compbeads)
  • Calculate the stain index in the primary detector (AmCyan) by determining:

[Median (positive peak)] - [Median (neg peak)]

2 x rSD (neg peak)

  • Calculate the spill index in FITC by determining the FITC stain index as above, then calculating:

[Stain index (FITC) / Stain index (AmCyan)]


  • What is an acceptable stain index?
  • How high can the spill index be before it is problematic?
antibody cocktail for data acquisition
Antibody Cocktail for Data Acquisition
  • CD4 FITC
  • CD127 PE
  • HLA-DR PerCP-Cy™5.5
  • CD45RA PE-Cy7
  • CD25 APC
  • CD8 APC-H7
  • CD3 V450
  • CD45 AmCyan
schedule day 21
Schedule: Day 2

9:00–10:00IV. Design and optimization of multicolor panels:

  • Selection of fluorochromes
  • Matching fluorochromes with antibody specificities
  • Determining application-specific settings

Demonstration: Visualizing data on a virtual cytometer

10:00–12:00 Data analysis in BD FACSDiva software

12:00–1:00 Lunch

1:00–2:30 V. Controls and Data QC

Exercise 3: Finding and correcting a spillover problem

2:30–2:45 Break

2:45–4:00 Review and summary, discussion of participant issues

  • Design your panel
      • Reserve the brightest fluorochromes for the dimmest markers and vice versa
      • Avoid spillover from bright populations into detectors requiring high sensitivity
      • Beware of tandem dye issues
      • Titrate antibodies for best separation

This allows you to:

      • Maintain resolution sensitivity where you need it most
      • Avoid artifacts of tandem dye degradation
spillover affects resolution sensitivity1
Spillover Affects Resolution Sensitivity

Without CD45 AmCyan

With CD45 AmCyan


Note that this is only an issue when the two markers (CD45 and CD19) are co-expressed on the same cell population.

special requirements for tandem dyes
Special Requirements for Tandem Dyes

Compensation requirements for tandem dye conjugates can vary, even between two experiments with the same antibody

  • Degrade with exposure to light, temperature, and fixation
  • Stained cells are most vulnerable


  • Minimize exposure to above agents
  • Use BD stabilizing fixative if a final fix is necessary
  • Run label-specific compensation
false positives due to tandem degradation
False Positives Due to Tandem Degradation


With CD8 APC-Cy7 and CD4 PE-Cy7:

Gating scheme

CD8 APC-Cy7+ cells

CD4 PE-Cy7+ cells

False positives in

APC channel reduced

in absence of APC-Cy7

False positives

in PE channel



Without CD8 APC-Cy7:

new tandems can be more stable





New Tandems Can Be More Stable

APC-H7 as a replacement for APC-Cy7:

Comparison of Sample Stability

(in BD Stabilizing Fixative at RT)




% Spillover












Hours of light exposure

antibody titration basics
Antibody Titration Basics

For most purposes, the main objective is to maximize the signal-to-noise ratio (pos/neg separation)

  • This may occur at less than saturating antibody concentrations
  • This may or may not be the manufacturer’s recommended titer, depending on the application

Titer is affected by:

  • Staining volume (eg, 100 mL)
  • Number of cells (not critical up to ~5 x 106)
  • Staining time and temperature (eg, 30 min at RT)
  • Type of sample (whole blood, PBMCs, etc)
  • Optimize settings for your panel
      • Derive experiment-specific PMT settings
      • Run compensation controls for each experiment

This allows you to:

      • Use the most appropriate settings for your panel
      • Avoid gross errors of compensation
application settings for a new panel i
Application Settings for a New Panel (I)

Balancing detectors and checking spillover:

  • Start with the current baseline CS&T settings
  • Run single-stained BDTM CompBeads to see if all populations are on scale
    • Decrease voltage if positives are off-scale
    • Increase voltage if the negative mean is below zero
  • Verify that each positive bead is at least 2x brighter in its primary detector vs other detectors (use the unstained control worksheet)
    • If not, increase voltage in the primary detector
    • Spill indexes for all combinations should be <0.8
application settings for a new panel ii
Application Settings for a New Panel (II)

Optimizing voltages for cells of interest:

  • Run fully-stained cells and:
    • Decrease voltages for any detectors where events are off-scale
    • Increase voltages for any detectors where low-end resolution is poor (SDNEG PEAK should be 5–10x SDEN)
  • Save application settings
  • Run single-stained BD CompBeads and calculate compensation
  • Run samples
application settings for an existing panel
Application Settings foran Existing Panel
  • Start with the current CS&T settings
  • Apply previously saved application settings
  • Run single-stained BD CompBeads and calculate compensation
  • Run samples

Visualizing data using a virtual cytometer:

  • Demonstration of data display as PMT voltages change
  • Note the percentage of variance due to electronic noise at different voltages


  • What percentage of the variance contributed by electronic noise is acceptable?
  • Do you need to calculate this for all detectors and all panels?
  • Is there such a thing as too high a voltage?
  • Run appropriate controls
      • Instrument setup controls (eg, voltage and compensation determination)
      • Gating controls (eg, FMO)
      • Biological controls (eg, unstimulated samples, healthy donors)

This allows you to:

      • Obtain consistent setup and compensation
      • Gate problem markers reproducibly
      • Make appropriate biological comparisons and conclusions
bd compbeads as single color controls
BD CompBeads as Single-Color Controls
  • BD CompBeads provide a convenient way to create single-color compensation controls:
  • Using the same antibodies as in the experimental samples
  • Creating a (usually) bright and uniform positive fluorescent peak
  • Without using additional cells
frequent compensation questions
Frequent Compensation Questions

Do I need to use the same antibody for compensation as I use in the experiment?

  • Yes, for certain tandem dyes (eg, PE-Cy7, APC-Cy7)

Are capture beads better than cells for compensation?

  • Usually, as long as the antibody binds to the bead and is as bright or brighter than stained cells

Should compensation controls be treated the same as experimental samples (eg, fixed and permeabilized)?

  • Yes, although with optimal fix/perm protocols this may not make much difference
gating controls
Gating Controls

Isotype control: Non-specific antibody of same isotype as the test antibody. For example :

  • IgG1 FITC + IgG2a PE + IgG1 APC

Fluorescence-minus-one (FMO) control: All test antibodies except the one of interest. For example :

  • CD3 FITC + CD4 APC (no PE)

Combined control: All test antibodies except the one of interest, which is replaced by an isotype control. For example :

  • CD3 FITC + IgG2a PE + CD4 PE

Biological controls can sometimes be used as gating controls.

gating controls continued
Gating Controls (continued)
  • Isotype controls don’t take spillover into account
  • FMO controls don’t take background staining into account
  • Combined controls take both into account, but still may not accurately represent the background staining of the test antibody
consider using lyophilized reagents
Consider Using Lyophilized Reagents
  • Lyophilization provides increased stability, even at room temperature or 37°C
  • One batch of reagents can be used for an entire longitudinal study
  • Pre-configured plates (BD Lyoplate™ plates) can avoid errors of reagent addition
  • Complex experiments (multiple stimuli, multiple polychromatic staining cocktails) become easier
  • Lyophilized cell controls can provide run-to-run standardization
  • QC your data
      • Visually inspect compensation
      • Visually inspect gating
      • Set sample acceptance criteria

This allows you to:

      • Avoid classification errors and false conclusions due to improper compensation and/or gating, or sample artifacts
visually inspect compensation
Visually Inspect Compensation
  • Create a template containing dot plots of each color combination in your experiment, then examine a fully stained sample for possible compensation problems
  • Yikes!
compensation problems can have cascading effects
Compensation Problems Can Have Cascading Effects

Compensation at 110%

Compensation at 15%

visually inspect gating



Visually Inspect Gating
  • Check gating across all samples in the experiment.
  • Gates may need to be adjusted across donors and/or experimental runs. Dynamic (eg, snap-to) gates may help in some cases.
types of sample acceptance criteria
Types of Sample Acceptance Criteria
  • Minimum viability and recovery for cryopreserved PBMCs
  • Minimum number of events collected in an appropriate gate (eg, lymphocytes)
  • Minimum number of events within a region of interest, to calculate an accurate percentage
exercise 3
Exercise 3

Finding and correcting a spillover problem:

  • Open the FCS file “exercise3.fcs”
  • Gate on small lymphcytes, then use the provided worksheet to look at all color combinations
  • Using biexponential display, change compensation for FITC - % AmCyan and note the changes in the plots
  • Find the compensation that aligns the FITC means of the AmCyan positive and negative populations


  • What could cause the discrepancy between calculated compensation by AutoComp and visually appropriate compensation on cells?
  • How might this problem, if uncorrected, affect your results?
outline review
Outline: Review
  • Configure your instrument
  • Characterize your instrument
  • Design your panel
  • Optimize settings for your panel
  • Run appropriate controls
  • QC your data
a question for you to answer
A Question for You to Answer

How many colors can you combine and still have robust results? This depends on:

-The experimental question

-The instrument used

-The markers to be combined

  • Maecker HT,Frey T,Nomura,LE,Trotter J.Selecting fluorochrome conjugates for maximum sensitivity. Cytometry A. 2004;62:169-173.
  • Maecker HT,TrotterJ.Flow cytometry controls, instrument setup, and the determination of positivity. Cytometry A. 2006;69:1037-1042.
  • RoedererM.How many events is enough? Are you positive? Cytometry A. 2008;73:384-385.
  • McLaughlin BE,Baumgarth N,BigosM,et al.Nine-color flow cytometry for accurate measurement of T cell subsets and cytokine responses. Part I: Panel design by an empiric approach. Cytometry A. 2008;73:400-410.
Laurel Nomura

Margaret Inokuma

Maria Suni

Maria Jaimes, M.D.

Smita Ghanekar, Ph.D.

Jack Dunne, Ph.D.

Skip Maino, Ph.D.

Joe Trotter, Ph.D.

Dennis Sasaki

Marina Gever