Polychromatic Flow Cytometry1
1 The National Institutes of Health does not endorse or recommend
any commercial products, processes, or services. The views
and opinions of authors expressed in this manuscript do not necessarily
state or reflect those of the U.S. Government and may not be
used for advertising or product endorsement purposes. The U.S.
Government does not warrant or assume any legal liability or
responsibility for the accuracy, completeness, or usefulness of any
information, apparatus, product, or process disclosed.
The flow cytometer has proven to be one of the most
powerful scientific techniques for the analysis of
immunobiology in the past 35 years. Recent advances
allowing the detection of 14 distinct cell parameters on
each cell have revealed the immense heterogeneity of
the immune system; e.g., the identification of more
than 100 functionally distinct cell phenotypes in the
peripheral blood of humans. In addition, the evolution
in computer technology brings to bear the ability to
analyze very large sample sets using sophisticated
algorithms, increasing the power of analysis of lowfrequency
Current state-of-the-art cytometric evaluation
allows for distinct cell population delineation using
two physical parameters--side scattered light (SSC)
and forward scattered light (FS) - and 12 separate fluorescent
parameters. Each fluorescence parameter can
be used to independently measure the expression of a
protein or function; combined, these measurements
may predict disease progression, vaccine responses, or
other immunological parameters.
Still, the use of high-end multicolor flow cytometry
is in its infancy; many challenges must still be overcome
before this technology will become routinely
available in research laboratories. The most difficult
obstacle at this time is reagent availability; many laboratories
are forced to conjugate fluorochromes not yet
available commercially. Many dyes are now available that can be conjugated easily to antibodies for use in
polychromatic flow cytometry (PFC) to supplement
the commercially available conjugates. With regard to
instrument development, by far the most important
requirement is automation. Instrument setup and calibration
are still far more complex with the use of
multiple lasers and detectors for PFC; computer-aided
validation of instrument performance is necessary.
In addition, automated compensation (fluorescence
spillover) is necessary; however, this is adequately
handled by most contemporary software packages.
Data analysis is by far the most time-consuming
aspect of PFC experiments. The complexity of data is
such that, with current software tools, analysis of individual
samples requires inordinate amounts of time.
There is a considerable demand for tools that can
organize the analyses into databases, as well as assist
in the exploration of the complex data sets. To help
researchers analyze such data, automated multivariate
techniques have been developed by this laboratory.
These algorithms are designed to compare multidimensional
distributions to identify and quantify the
degree of difference between data sets (De Rosa et al.
2001; Roederer and Hardy, 2001). In addition, these
algorithms can rapidly identify regions of multivariate
distributions that differ, thereby providing a mechanism
for identifying those cells that are different
between two samples. Tools such as these help
researchers explore the complex data sets and identify
interesting aspects that no combination of twodimensional
graphs could have revealed. The probability
binning (PB) algorithm can be used to quantify
the degree of similarity or disparity of highly complex
distributions for the purposes of ranking these distributions
(Roederer et al.
, 2001a,b). This may be useful
for quantifying the number of cells that respond to a
particular stimulus (perhaps having responded in
complex multivariate patterns) or for identifying variations
in immunophenotyping patterns that correlate with pathogenic states (Baggerly, 2001). These strategies
allow for the most useful and comprehensive
display of complex data in the field of flow cytometry
This article presents some of the latest techniques
used in our implementation of our 12-color flow cytometric
technology. It discusses the reagents, calibration
and setup, and analysis of the resulting data, including
some of the hurdles and pitfalls encountered. This
guide will aid research laboratories wishing to implement
flow cytometric technology capable of more than
5 or 6 colors.
II. MATERIALS AND
A. Monoclonal Antibodies
Purified monoclonal antibodies are available from
manufacturers as bulk concentrated protein in the absence of any exogenous protein. All conjugations
are performed as detailed (http://www.drmr.com/
abcon/). Large quantities of reactive fluorochromes
are prepared and stored (and are stable for many
months at 4C); the conjugation to antibodies is a fairly
rapid procedure that can then be accomplished in 2-3 h.
Figure 1 shows the common fluorochromes currently
used in our laboratory, which can all be directly
conjugated to monoclonal antibodies. Also shown are
the excitation and emission spectra and suggested
bandpass filters for each fluorochrome. Ideally, each
fluorochrome should be conjugated to a wide variety
of monoclonal specificities in order to provide a wide
range of possible panels; of course, this requires a
fairly substantial investment of both fluorochromes
and monoclonal antibodies. New fluorochromes are
becoming available that are more photo stable and
easier to conjugate, such as the Alexa family of fluorochomes
(i.e., Alexa, 488, 532, 660, 633, 647, and 680).
Commercial manufacturers currently offer only a
limited range of fluorochromes conjugated to specific monoclonal antibodies. Table I shows that only 7 of the
12 fluorochromes used in our laboratory are available
commercially; this range is currently increasing but is
still a limiting factor. In addition, newer conjugates
have far more limited reagent combinations available
until manufacturers can build up a significant inventory.
Hence, it is likely that researchers who wish to
perform more than 6-color flow cytometry will likely
need to invest in the ability to manufacture reagents
in-house. In general, this is incorporated most efficiently
into a core facility that can supply reagents to
multiple research laboratories.
B. Qualification of Fluorescently Conjugated
Monoclonal Antibodies (mAbs)
|FIGURE 1 Conjugate spectrum chart of excitation and emission curves for common fluorochomes used
in PFC. Laser lines show which conjugates are excited by the individual laser lines and the selected bandpass
filters used to measure the specific emission.
Regardless of the conjugate used (i.e., commercial
or in-house), all mAbs require titration against a target
cell population to determine the optimal concentration
for staining. Note that staining conditions (temperature, time, and volume) impact the titration; thus,
qualification should be performed under the same
conditions as experimental staining. By plotting the
median of the positive cell population against the
serial dilution of the mAb as illustrated in Fig. 2, the
lowest concentration at which the maximum separation
can be discerned; in general, this is the optimal
concentration to use (in this example, 10btg/ml).
Lower concentrations of mAb result in loss of resolution
(note, however, that for some mAbs the separation
is still highly adequate at very low concentrations,
allowing the use of the reagent at a more economical
rate). It cannot be overemphasized that proper titration
and selection of mAb concentration are paramount for
successful multicolor analysis. Adding too much antibody
conjugate can have as much effect on sample
analysis as the addition of too little antibody conjugate.
In this situation, backgrounds increase due to
nonspecific binding of the antibody conjugate, thus
reducing the signal-to-background ratio dramatically.
|FIGURE 2 Serial dilution of anti-CD4-FITC-labeled PBMCs and the median value of the positive signal
(black line). (A) The point on the titration curve (10µg/ml) yielding the greatest separation (highest median
value with the lower auto fluorescence) as compared to poor separation (B) at a lower titer (<2µg/ml).
Samples are acquired on a modified FACSDiVa flow
cytometer (BDIS, San Jose, CA), which measures 12
fluorescent parameters and 2 physical parameters (FS
and SSC). Figure 3 illustrates the optical configuration
and filter selection of this instrument. The geometry of
this instrument is based on the traditional collection
optics and is far more complex than more recent
instrumentation using optical fibers such as the LSR II
(BDIS). In these instruments, photons of light from the
laser-excited conjugates are transmitted through
optical fibers and measured in unique optical arrays.
Figure 4 shows an example of an argon laser array
containing eight detectors called an Octagon. The
advantage of these systems includes increased efficiency
of photon transfer, thus lower-energy lasers can
be used with good signal reproducibility as compared
to higher-end systems equipped with powerful lasers.
Figure 5 shows the laser configuration of older traditional
high-end systems as compared to newer instruments
using low-powered diode lasers (5-10mW).
Clearly another advantage of lower-power lasers and
optical fibers is the smaller footprint, yielding a more
compact system with the measurement capability of a
high-end research instrument.
|FIGURE 3 Digital Vantage optical configuration used to detect 12 colors using three lasers: 488-nm
argon, 408-nm krypton, and 595-nm dye lasers. Each section of detectors is outlined (black boxes) to
indicate the laser associated with the emission. Also illustrated are the dichroic mirrors and bandpass
filter combinations for each PMT.
|FIGURE 4 LSR II optical configuration of detectors for only the 488-nm diode laser. This configuration
shows the light path with the typical dichroic mirrors and bandpass filters used to detect six
different conjugates excited by this laser plus side scattered light.
D. Alignment and Calibration Beads
|FIGURE 5 Comparison between the Digital Vantage and the LSR II laser configuration system. Due
to the use of the low-powered diode laser in the LSR II system, this instrument can be very compact
and inexpensive to operate.
Alignment beads containing a single peak bead
(single peak Rainbow beads) are from Spherotech Inc.
(Rainbow beads, Cat. No. RFP-30-5A). Calibration
beads containing eight separate peaks (eight peak Rainbow beads) are from Spherotech Inc. (Rainbow
beads, Cat. No. RFP-30-5A) and Blank Beads are from
Becton Dickinson Immunocytometry Systems (Cat.
No. RFP-30-5A). All beads are diluted by the addition
of one drop (approximately 20µl) per milliliter of
phosphate-buffered saline (PBS) containing 1% HIFCS
(Quality BiologicalmPAA labs, Cat. No. 110-001-101)
and 1 mg/ml of sodium azide (Sigma Chemical, Cat.
E. Monoclonal Antibody Selection
A laboratory Web-based database containing all of
the antibody conjugate reagents is used to select the
antibody conjugate combinations. This database lists
the correct mAb concentration (determined from a
titration curve; see the titration procedure in Section
III) and displays the concentration, specificity, lot
number, and location on a laboratory worksheet. Such
databases become necessarymlaboratories doing 6-12
color flow cytometry will inevitably have a very large
storehouse of reagents; it is necessary to have a centralized
repository of the qualification and validation
data for each reagent in an easily accessible location.
Researchers planning experiments need access to this
information in order to know how much of each
reagent to use, as well as some idea of the quality of
the staining that can be expected with that reagent.
F. Compensation Beads
Latex beads coated with anti-mouse κ antibody are
from Becton Dickinson Immunocytometry Systems
(Cat. No. 557640). After incubating with mAb conjugate,
beads are fixed in a final concentration of 0.5%
paraformaldehyde (PFA). These "capture" beads are
used with each antibody conjugate tested to set up the
A. Alignment and Instrument Calibration
All flow cytometers, regardless of engineered
advances in alignment techniques, require alignment
and calibration quality control to determine reproducibility
and sensitivity. For this purpose, alignment
beads and calibration standards must be stable and
reproducible from day to day. It is important to point
out that such quality control measurements are not a
substitute for proper cell controls as outlined in this article to assure testing quality. Alignment beads are
used to determine good instrument performance and,
if successful, should determine proper light collection
in all detectors as measured by fluorescence intensity
and fluorescence CV at a consistent voltage. Once the
instrument lasers are aligned properly, calibration
beads can be used to determine the correct tolerance
range of fluorescent intensity by adjusting the detector
sensitivity (e.g., photomultiplier voltage). These tolerance
ranges are determined by unstained cell analysis
set to a predetermined value. In addition, calibration
standards determine the signal-to-background ratio,
which must remain consistent within at most a 5%
- Place diluted single peak Rainbow beads onto
the sample insertion tube and adjust the sample pressure
to approximately 600 beads per second.
- While observing dual-parameter histograms of
FS vs SSC and all other fluorescence parameter combinations,
adjust instrument to achieve the narrowest
CV and highest intensity possible according to the manufacturer's instructions. Figure 6 shows the incorrect
(A) and the correct (B) display for two fluorescence
parameters. It is important to note that while slight
misalignments may have only a small impact on the
measurement of any given single parameter, they can
have a serious impact on the visualization of data after
compensation (Roederer, 2001a,b). This is because the
spread in compensated data is directly related to the
efficiency of light collection; larger CVs, as illustrated
in Fig. 6, result from decreased light efficiency and
result in much poorer data quality after compensation.
- Adjust the voltages for each PMT to result in predetermined
intensity levels for the bead population.
Such levels are defined previously as optimal for the
particular types of samples that are being analyzed;
this calibration procedure ensures that the instrument
sensitivity is comparable across experiments, allowing
for the best comparison of data. As an example, for the
analysis of lymphocytes, we typically analyze completely
unstained lymphocytes and adjust the PMT
voltages such that the upper end of the unstained cells
is at the top of the first (of four) decades of fluorescence.
Then the beads are reanalyzed at those voltages and the intensities are recorded for future target settings.
These same voltage settings are used for sample
acquisition and instrument calibration.
- Place diluted eight peak Rainbow beads onto the
sample insertion tube and adjust the sample pressure
to approximately 600 beads per second.
- Collect and save all single parameter histograms
for future analysis.
- Place diluted Blank beads onto the sample insertion
tube and adjust the sample pressure to approximately
600 beads per second.
- Collect and save all single parameter histograms
for future analysis.
- From data collected on the single peak beads,
chart voltage versus time. Correct tolerances for each
PMT should be ±5% variance.
- Data collected on the eight peak beads (median
channel of the eight peak) divided by the median
channel of the blank bead yield the signal-to-background
ratio (see Fig. 7). Each PMT will have a characteristic
S/B ratio; however, the correct tolerance
plotted against time should produce a range of ±10%.
|FIGURE 6 Rainbow beads with incorrect (A) and correct (B) alignment of two fluorescent parameters.
Tolerance ranges for the coefficient of variance and fluorescent intensity are established for all
instrument parameters. Setting quality control of all parameters within these tolerance ranges can
avoid incorrect alignment and compensation error.
|FIGURE 7 An overlay of eight peak rainbow beads with blank
beads of I of the 12 parameters. The signal/background ratio is calculated
using the median channel of the eighth peak bead and dividing
by the median channel of the blank bead.
Compensation and analysis of samples can be done
either online or after data collection with appropriate
software. In general, if cell samples are sorted, the user
must perform compensation online; however, in most
cases, sample compensation and analysis are performed
off-line. Regardless of when compensation is
performed, the same rules apply to correctly compensate
the sample. It is important to note that each experiment
must have matching compensation controls.
These controls must produce signals, which are of as
high or higher fluorescence intensity than the test
sample. In many cases the use of compensation beads
will satisfy this condition; however, if any of the experimental
samples are more than severalfold brighter
than the beads, then single-stained cells of the appropriate
reagents must be used as compensation controls.
In addition to matched compensation controls, a
negative (unstained beads) must be collected. This
control and individually labeled compensation tubes
are used in the compensation algorithm to calculate
compensation. Finally, to verify cell autofluoresence
relative to the unstained bead location, an unstained
cell sample control must be collected. Online compensation for the FACSDiVa is described later. Figure 8
shows an example of compensation beads labeled with
anti-CD8 APC. Figure 8A shows the location of
unstained beads as compared to the stained beads in
Fig. 8B. As expected, the degree of spillover for the
excitation of APC from the argon into the Cy5PE channel is negligible (Fig. 8C). However, the dye laser
(595 nm) excites APC and the spillover is seen in the
Cy55APC channel. This will require compensation correction
of the Cy55APC channels due to the spillover
of APC (Fig. 8D). As shown in Fig. 9, the degree of
compensation (percentage of spillover) or light contamination
can be considerable, and the complexity of
this issue is only magnified by the addition of multiple
parameters. A detailed explanation of compensation
and controls is beyond the scope of this article;
however, additional information can be found at
|FIGURE 8 Fluorescent intensity of unstained (A) compensation beads (anti-mouse κ) and stained
beads with anti-CD8 APC (B). (C and D) The effect of contaminated light from the excitation of CD8-
APC. In C, no ompensation is required because no contaminating light or spillover occurs into the
Cy5PE channel. However, D shows that compensation correction is required because of the large
spillover of contaminating light into the Cy55APC channel. After applying compensation correction,
D will appear like C.
|FIGURE 9 Compensation percentage of contaminated light,
which must be subtracted from all of the other detectors for accurate
analysis. The x axis shows the signal, and the y axis indicates
the percentage of contaminated light removed from the signal. In
general the largest contamination occurs within the same laser
C. Sample Acquisition for
Steps and Considerations
- Into a 12 × 75 test tube add 40 µl of compensation
beads (mouse anti-κ beads) and the volume of a previously tittered antibody conjugate. Dilute volume to
100µl with PBS containing 1 mg/ml of sodium azide
and 1% fetal calf serum (FCS). Note that each antibody
conjugate tested will have a single stained tube for the
compensation control used in the experiment. Each
compensation control tube will be used to set the compensation
- Incubate in the dark for 15min at room
- Wash once in PBS containing 1 mg/ml of sodium
azide and 1% FCS.
- Remove supernatant and resuspend in 250µl of
PBS containing 1 mg/ml of sodium azide and 1% FCS.
- Vortex and add 250µl of 0.5% PFA.
- Acquire each compensation control tube and the
unstained bead control on the flow cytometer using
previously defined voltage settings.
- Set automated compensation matrix either on the
instrument or by off-line software. Once completed,
the test sample is correctly compensated and is ready
- Compensation should be checked frequently by
acquiring cell samples stained with combinations of
antibody conjugates. After applying the compensation
matrix, median values of the unstained cells should
match the median values of the positive cells.
D. Sample Analysis
Steps and Considerations
- Altering sample pressure and sheath velocity
should be avoided. When possible, cells should be analyzed
at low sheath pressure to ensure greatest sensitivity;
increasing sample pressure increases the CV of
the measurement, thus affecting alignment and compensation
negatively. Therefore, it is recommended to
maintain the lowest useful sample pressure and sheath
- Collecting enough events for statistical analysis
is key. However, the number of events needed for 12-
color analysis is no different than for 2-color analysis.
What is important is the size of the population of cells
of interest. For example, if the subset of interest represents
0.1% of the input population, then collecting 1
million events yields 1000 events of the subset of interest.
In general, 1000 events is more than enough for
phenotypic analysis; for quantitative enumeration,
a count of 1000 has an associated precision of 3%
(i.e., the square root of 1000 divided by 1000). If a 1%
precision was required, then 10 million events of the
original sample need to be acquired.
- Particle size and cell aggregates should be considered
before sample collection. In addition to sample
clogging the macro-sort tip, small changes in alignment
can alter fluorescent intensity, compensation, and
forward scatter detection. In general, if the particle size
is greater than one-fourth the size of the macro-sort tip,
the user should consider a larger macro-sort tip. Alternatively,
cell aggregates can be avoided by prefiltering
samples through a 100-µm filter cap tube prior to
- Fluorescence minus one (FMO) control refers
to a staining strategy, which uses all mAbs in the
staining mix as in the test sample except for one
mAb. This method allows for the correct determination
of gate selection and verification of cell percentages.
Figure 10 shows an example of the FMO
strategy. In this example, cells were stained with four
colors: anti-CD3-FITC, anti-CD4-PE, anti-CD8-Cy5PE,
and anti-CD45RO-Cy7PE. The FMO control lacked
anti-CD4-PE. In Fig. 10A, the sample is compensated
correctly and shows that the FMO control is a better
indicator of negative cell control cursor position than
the unstained control sample (compare line 1 and line
2). Figure 10B demonstrates that even poorly
compensated samples can benefit from the FMO
control sample (compare line 1 and line 2). After
setting the positive gate cutoff the test sample percentages
can be determined more accurately. Thus this
control reduces false negatives (best specificity) and
better identifies positive cell populations (lower sensitivity).
In addition, the FMO control can help identify
compensation issues within the test sample. Therefore,
FMO controls should be used whenever accurate discrimination
is essential or when antigen expression is
relatively low. While theoretically there could be as
many FMO controls for each staining combination as there are colors, in reality most of these are not necessary.
For example, in many cases (e.g., CD3 or CD8
staining), the distinction of positive and negative cells
is made easily enough based on visual inspection.
In no case, however, is a completely unstained (or
completely isotype-stained) sample the appropriate
control for setting discriminatory gates.
- Use only titered antibody conjugates prior to use
in combinations as described earlier.
|FIGURE 10 Use of the FMO control (fluorescence minus one) stained with all mAbs except for anti-CD4-
PE. (A and B) The unstained control, the FMO control, and the fully stained cell sample (anti-CD3-FITC, anti-
CD4-PE, anti-CD8-Cy5PE, and anti-CD45RO-Cy7PE) are compared. (A) The sample is compensated correctly
and shows that the FMO control is a better indicator of negative cell control cursor position than the unstained
control sample (compare line 1 and line 2). (B) Even samples that are poorly compensated can benefit from
the FMO control sample (compare line 1 and line 2).
A. Sample Viability
Dead cells will bind many antibody conjugates nonspecifically
and erroneously count these as a positively
labeled cell. Therefore, gating strategies must be employed to properly gate out these cells. Intercalating
dyes such as ethidium monoazide (EMA) or propidium
iodide (PI) can be useful in gating out these
nonspecifically labeled cells. One advantage of the use
of PI over EMA is the ability to use the same channel
(Cy5PE channel) for both PI and another mAb stained
with Cy5PE. This can be done due to the high
intensity of PI over most mAbs sharing this channel.
Figure 11 shows an example of EMA used as a dead
cell discriminator. In this example, unfixed cells were
stained with 0.5 µg/ml of EMA (Molecular Probes Inc,
Cat. No. E1374) for 10min on ice covered with aluminum
foil followed by 15 min under a bright fluorescent
light. Samples can be fixed with 2% PFA and run
within the same day. Dead cells are labeled positive
with EMA, as seen in Fig. 11B, and can be removed
from the gated live cells (live cell gate, B). Without the
use of EMA, Fig. 11A shows the total number of dead
cells and live cells combined. Cells within a standard light scatter gate could contain dead cells as shown in
Fig. 11A; however, after the dead cells were gated out
using the live cell gate in Fig. 11B, the dead cells were
removed from the analysis (Fig. 11C).
B. Antibody Aggregation
|FIGURE 11 Use of ethidium monazide (EMA) as a method to discriminate live cells from dead cells. Dead
cells are labeled positive with EMA as seen in B and can be removed from gated live cells (live cell gate).
Without the use of EMA, A shows the total number of dead cells and live cells combined. Cells within a standard
light scatter gate could contain dead cells as shown in A; however, after the dead cells were gated out
using the live cell gate in B, dead cells were removed from the analysis (C).
Cyanine conjugates can potentially form immune
complexes or aggregates during storage. Typically,
cyanine tandem dyes form these aggregates and must
be removed before using in the staining procedure.
Ultracentrifugation of the antibody conjugate mixture
for 3 min will remove these aggregates.
Routine polychromatic flow cytometry is now
closer to reality than ever before. Recent advances in
instrumentation, computer technology, and biochemistry
will prove to be the ingredients necessary to successfully
understand the human immune system
(Eckstein et al.
, 2001; Roederer et al.
, 1997). As engineering
goals meet science objectives, the last frontier
to cross will be analysis and comprehension of data
never seen before or not very well understood. It will
be this area where intense effort is needed to understand
the massive amount of information collected and
interpreted. Nonetheless, significant hurdles remain to
be crossed by all laboratories wishing to implement
this technology, and significant education of all immunologists
regarding the interpretation of data generated by this technology is crucial to the understanding
of its vagaries.
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