Introduction into
Flow Cytometry
September 27, 2014
6th EFIS-EJI South East European
Immunology School – SEEIS 2014
Timisoara, Romania
The Principle of Flow Cytometry
• Resuspendend single cells are moved through a
light source (laser).
• In this process cells emit characteristic light signals
depending on the cell type and the preparation of
cells that are detected by appropriate detectors.
Design of a Flow Cytometer
• Fluidic System
Moves and aligns cells in to the laser focus
• Optical System
Excitation Optics
Detection Optics
• Electronical System
Transfers optical signals into electronical signals, digitalizes the electronical signals for the analysis on a computer
The Fluidic System
• Fluidic Cart
– Sheath Fluid
– Waste
– Cleaning Solution
– Shut Down Solution
• Sample Injection Port
• Cuvette
Overview of the Fluidic System
Sheath Fluid Stream Sample Stream
Waste Aspirator
Flow Cell
Laser Fokus
Waste Tank
Reservoir
Fluid Filter
Bubble filter
“Plenum” (internal reservoir)
Sample Injektion
Tube (SIT)
Sample Tube
Hydrodynamic Focusing
• Sample stream is accelerated due
to the reduction of the cross
section inside the cuvette
resulting in the acceleration and
separation of cells (hydrodynamic
Focusing).
• BD FACSCanto™ II:
– Max. event rate of 10.000 events/sec
– Detection of particles ca. 0,2 – 50 µm.
Sheath Fluid
Sample
Laser beam
SIP (Sample Injection Port) BD FACSCanto II
Sample Injection Tube
(SIT)
Support
Arm
Holder for
Tube Rack
Sample
Tube
Cuvette
Waste Line
Intersection Point
SIT
Rinse Line
Sheath Line
Event Rate
Sample
Red laser
Violet laser Blue laser
Sheath fluid
LOW – low sample pressure
Low sample consumption
~12 µl/min
HIGH – high sample pressure
High sample consumption
~120 µl/min
The Optical System
• Excitation optic
– Laser
– Prism and lenses
• Detection optic
– Filter and mirrors
– Detectors
The Lasers
• Lasers emit light of a single wave length
Often used lasers in flow cytometers: – 488 nm (blue Laser)
– 633 nm (red laser)
– 405 nm (violet laser)
• Various available laser types:
Gas laser Diode laser Solid state laser
Transport & Focusing of Laser Beam
Why do we need a laser?
Excitation of fluorochromes in the cuvette that are bound on or inside a
cell/particle
Blue laser Red laser Cuvette
Glas fiber cable
Optical Filters & Dichroic Mirrors
• Separation of cell signals with filters and mirrors
450 550 650 500 550 600
LP 500 BP550/50
Longpass Bandpass
The Detectors
Amplification of the light signal and transfer of an
optical signal into an electronical signal
• Photodiode
• PMT (Photomultiplier Tube)
Detection Optic — Octagon Signals of the blue laser (4–2, 4–2–2 configurations)
564–606 nm
750–810 nm
483–493 nm
> 670 nm
515–545 nm e.g. FITC
SSC
e.g. PE
e.g. PE-Cy7
e.g. PerCP or
PerCP-Cy5.5
Detection Optic — Trigon Signals of the red and violet laser
Signals of the red laser 4–2, 4–2–2 Configurations
Signals of the violet laser 4–2–2 Configuration
425-475
485-535
650-670 750-810 e.g. APC-H7 e.g. APC
e.g. BD Horizon V450
e.g.
BD Horizon V500
Example: Fluorochrome combination on
Canto II (4–2–2 Configuration)
Laser Fluorochromes Alternatives
405 nm (violet) BV421 BD Horizon V450, PacificBlue
BV510 BD Horizon V500, AmCyan, DAPI
488 nm (blue) FITC GFP, Alexa Fluor® 488
PE PI
PerCP-Cy5.5 PerCP, PE-Cy5.5, 7-AAD, PI
PE-Cy7
633 nm (red) APC Alexa Fluor® 647
APC-H7 APC-Cy7
The Optical System
Violet Laser (405 nm)
Blue Laser (488 nm)
Red Laser (633 nm)
Glas fiber cable
Prisms Fokus lense
Steering disk
Flow cell
564–606 nm
750–810 nm
> 670 nm
SSC
515–545 nm
The Electronic System
• Digital data processing
– Tasks:
• Converts analog signals into digital signals
• Determins Area and Height of each impuls
• Calculates the Width of the signal
• Does the compensation
• Communication (data transfer) between workstation and flow cytometer
The Electronic System
Laser
Laser
Laser
Time V
olta
ge
Time
Vo
lta
ge
Time
Vo
lta
ge
Quantification of pulse
Time
Pulse Area
(Area)
Puls
e H
eig
ht
( H
eig
ht)
Pulse Width
(Width)
0
The Results
39,271 39,271
Event 2
Event 3
0 60 120 90
10 160 65
30 650 160
FCS-Data
185
PE-A
Exportable as FCS File 1900
2,688
3100
3,189
1900
90
185 3100
PE-A
FIT
C-A
1900
90
FIT
C-A
185 3100
39,271 0 60 120 90
10 160 65
30 650 160
PE-A
FIT
C-A
39,271 0 60 120 90
10 65
30 650 160
PE-A
FIT
C-A
39,271 0 60 120 90
10 65
30 650 160
PE-A
1900
90
FIT
C-A
FIT
C-A
39,271 0 60 90
10 65
30 650 160
PE-A PE-A
1900
90
FIT
C-A
FIT
C-A
39,271 0 60 90
65
30 160
PE-A
FIT
C-A
Time
PE-A
FIT
C-A
1900
90
FIT
C-A
PE-A
FIT
C-A
Event 1
PE-A
1900
90
FIT
C-A
PE-A
FIT
C-A
PE FITC SSC FSC
PE-A
1900
90
FIT
C-A
PE-A
FIT
C-A
Flow Cytometry Software
BD FACSCantoTM Software BD FACSDivaTM Software
- Automatic QC Setup
- Automatic analysis of predefined kits
for clinical applications (e.g. BD
Multitest)
- Acquisition and analysis of
individual applications
The Electronic System
Time
Time
Time
Time
Time
Data
Processing
PE
FITC
SS
C
FSC
AP
C
PerCP-Cy5.5
Time
What can you measure?
Algae
Blood
cells
DNA/RNA
Protozoa
Applications used in Flow Cytometry
Which Parameters can be Analyzed?
• Relative Size (Forward Scatter-FSC)
• Relative granularity or internal complexity (Side Scatter-
SSC)
• Relative fluorescence intensity
What can a flow cytometer perform?
• Simultaneous quantification of multiple optical parameters
• With a high flow rate.
The Scatter Parameters: FSC & SSC
• Forward Scatter (FSC) – defracted light
– Proportional to cell surface (cell size)
– Detected along the incident light in forward direction (1-10°)
• Side Scatter (SSC) - reflected and refracted light
– Related to cell granularity and complexity
– Detected in a 90° angle from the laser beam
Forward Scatter Light (488 nm): Cell Surface Area
Light Source (Laser Beam)
Side Scatter Light (488 nm): Cell Complexity/Granularity
Light Source (Laser Beam)
Example:
FSC & SSC of Lysed Whole Blood
Neutrophilic
Granulocytes
Lymphocytes
FSC
0 50 100 150 200 250
Monocytes
*1000
*1000
0
50
10
0
15
0
20
0
250
Debris S
SC
Basophilic
Granulocyte
Lymphocyte
Eosinophilic
Granulocyte Neutrophilic
Granulocyte
Monocyte Thrombocyte
Erythrocyte
What is Fluorescence ?
= 488 nm (blue)
Energy of laser
light (excitation)
Energy of emitted
fluorescence
519 nm (green) Antibody
Step 1: Fluorochrome absorbs the energy of laser light
Step 2: Fluorochrome releases absorbed energy as:
a) Vibration and heat
b) Emission of photons with longer wave length
(= lower energy)
Stoke´s- Shift: Wave length difference between absorbtion and emission
Fluorescein
Isothiocyanate
(FITC)
HO
N
O O
O
HO
C
S
Fluorescence Intensity
Relative Fluorescence Intensity
No.
of events
FITC
100 101 102 103 104
FIT
C
FITC
FIT
C
FITC
FIT
C
FITC
FIT
C
FITC
FIT
C
The emitted fluorescence is proportional to the
amount of bound fluorochromes.
Emission Spectra of common
Fluorochromes
blue
Laser
red
Laser
violet
Laser
The Compensation
Spectral Overlap
FITC PE PerCP-Cy5.5 PE-Cy7
650nm 700nm
PerCP-Cy5.5
670 LP
500nm 600nm
FITC
530/30
Rela
tive
In
ten
sity
Wave length (nm)
550nm
PE
585/42
PE-Cy7
780/60
750nm 800nm
The Principle of Compensation
Correction of spectral overlap
• Depends on:
- Used fluorochromes
- Amp gains of detectors
- But not on: used material
• Sample material:
- Unmarked cells as negative control
- Single marked samples to calculate
compensation
The Correct Compensation Settings
Correct Compensation:
The median of the FITC-positive
population is on the same level than
the median of the unstained
population.
Not compensated Correctly compensated
Missing compensation:
The single FITC-stained population
seems to be double-positive due to the
spectral overlap of FITC into the PE
channel.
Example: Spectral Overlap of FITC
650nm 700nm
PerCP-Cy5.5
670 LP
500nm 600nm
FITC
530/30
Re
lative
In
ten
sity
Wave length (nm)
550nm
PE
585/42
750nm 800nm
Before Compensation
650nm 700nm
PerCP-Cy5.5
670 LP
500nm 600nm
FITC
530/30
Rela
tive
In
ten
sity
Wave length (nm)
550nm
PE
585/42
Increase values
After Compensation
650nm 700nm
PerCP-Cy5.5
670 LP
500nm 600nm
FITC
530/30
Rela
tive
In
ten
sity
Wave length (nm)
550nm
PE
585/42
Increase value to move population down
Influence of the Voltage on Compensation
• FITC PMT Voltage constant (575 V)
• PE PMT Voltage changes from 500 to 600 Volt
Spectral overlap
of FITC into PE
channel varies
from
17% (500 V) to
71% (600 V)
8-Color Panel & the Resulting
Compensation Matrix
CD4 FITC
CD4 PE
CD28 PerCP-Cy5.5
CD45RA PE-Cy7
CD3 Pacific Blue
CD4 AmCyan
CD27 APC
CD8 APC-Cy7
FL1 FL2 FL3 FL4 FL5 FL6 FL7 FL8
FITC 100.0 23.5 2.1 0.7 0.0 0.0 0.0 3.0
PE 1.6 100.0 12.3 2.7 0.0 0.0 0.0 0.0
PerCP- Cy5.5
0.2 0.1 100.0 43.0 2.5 5.6 0.0 0.0
PE- Cy7
0.0 0.6 0.1 100.0 0.0 3.6 0.0 0.0
APC 0.1 0.0 0.3 0.2 100.0 2.7 0.0 0.0
APC- Cy7
0.0 0.0 0.1 3.9 19.9 100.0 0.0 0.1
Pacific Blue
0.1 0.0 0.0 0.1 0.0 0.0 100.0 18.1
Am Cyan
38.1 7.0 1.1 0.6 1.5 0.0 17.1 100.0
Single-stained controls:
DET
Auto
matic
Com
pensation
Automatic Compensation
Samples
• Unmarked cells/particles to set the PMTV
• Single stained samples of every used fluorochrome
• Tandem conjugates: single stained samples of each
lot# of the individual tandem conjugates
Why so many Colors?
Advantages
• More colors improve efficiency in:
– time consumption
– use of reagents
– preserving sample material
1 tube with a 6 color labeling can replace up to 15 tubes with a two color
labeling
2 colors BD Simultest™
• CD45/CD14
• IgG1/IgG2a
• CD3/CD4
• CD3/CD8
• CD3/CD19
• CD3/CD16+56
3 colors BD Tritest™
• CD3/CD4/CD45
• CD3/CD8/CD45
• CD3/CD19/CD45
• CD3/CD16+56/CD45
6
4 colors BD Multitest™
• CD3/CD4/CD8/CD45
• CD3/CD19/CD16+56/CD45
6 colors BD Multitest™
• CD3/CD4/CD8/CD19/ CD16+56
/CD45
2 1
Advantage - Multicolor Reagents
4
Why so many Colors?
Advantages
• More colors improve efficiency in:
– time consumption
– use of reagents
– preserving sample material
1 tube with a 6 color labeling can replace up to 15 tubes with a two color
labeling
• Exponental increase of information
More Colors, Higher Resolution =
More Details/Information
The higher the resolution, the more you know about your cells and
small differences are being discovered.
Why so many Colors?
Advantages
• More colors improve efficiency in:
– time consumption
– use of reagents
– preserving sample material
1 tube with a 6 color labeling can replace up to 15 tubes with a two color
labeling
• Exponental increase of information
• Identification of rare/new cells (< 0,05%)
A successful multicolor Application
A successful multicolor application depends on:
A. Sample preparation and quality of sample
B. Careful reagent selection
– New fluorochromes: more colors, more choices that improve
population discrimination in multicolor flow cytometry
C. Proper cytometer performance, setup, and data
collection
D. Proper data analysis
Panel Design Issues
• Some antigens are expressed at high levels, some at low levels, some over a range (continuum).
• Some fluorochromes are bright, others are dim.
• Emission spillover from bright markers can degrade the sensitivity of dim markers being measured in an adjacent detector.
• Some antigen markers are only available with certain fluorophores.
• Tandem dyes may be unstable.
• Complexity of the assay/panel increases the likelihood of errors.
Panel Design Principles I
• Know your cytometer.
– Know what lasers, filters, and how many PMT per laser
Instrument Configuration &
Fluorochrome Combinations
BD Accuri™ C6 BD FACSVerse™
BD FACSCanto™ II
BD FACSVerse™
BD FACSCanto™ II
BD LSR™ Fortessa
BD LSR Fortessa X-20
BD LSR™ Fortessa
BD LSR Fortessa X-20
2 laser
4 colors 2 laser
6 colors
3 laser
8 colors
4 laser
14 colors
5 laser
18 colors
355 nm BUV395
BUV737
BUV395
BUV737
405 nm
BV421 / V450
BV510 / V500 BV421 / V450
BV510 / V500
BV605
BV650
BV711
BV786
BV421 / V450
BV510 / V500
BV605
BV650
BV711
BV786
488 nm
BB515 / FITC / AF488
PE
PerCP / PerCP-Cy5.5
BB515 / FITC / AF488
PE
PerCP / PerCP-Cy5.5
PE-Cy7
BB515 / FITC / AF488
PE
PerCP / PerCP-Cy5.5
PE-Cy7
BB515 / FITC / AF488
PE
PE-CF594
PerCP / PerCP-Cy5.5
PE-Cy7
BB515 / FITC / AF488
PerCP / PerCP-Cy5.5
561 nm
PE
PE-CF594
PE-Cy5
PE-Cy7
640 nm APC / AF647
APC-Cy7 / APC-H7
APC / AF647
APC-Cy7 / APC-H7
APC / AF647
APC-Cy7 / APC-H7 APC / AF647
AF700
APC-H7 / APC-Cy7
APC / AF647
AF700
APC-H7 / APC-Cy7
Panel Design Principles I
• Know your cytometer.
– Know what lasers, filters, and how many PMT per laser
• Availability of certain fluorophores
• Match brighter fluorochromes with lower-expressed
antigens (and vice-versa).
– Determine the antigens and classify expression
– Determine a fluorochrome set and classify brightness
– Match antigens with fluorochromes
Antigen Density
• Level of antigen
expression on a cell
– Can vary due to cell
activation level and
functional differences
– Can be a range
(eg. smeared population)
– Depends on cell type
• Classify antigens as
high, intermediate and
low expressed
Density of Common Human Surface Antigens
www.bdbiosciences.com/documents/Human-Antigen-Density-Chart.pdf
Comparison of Fluorochrome Brightness
Laser very bright bright moderate dim
355 nm BD Horizon™ BUV737 BD Horizon™ BUV395
405 nm
BD Horizon™ BV421 BD Horizon™ BV605 BD Horizon™ BV510 BD Horizon™ V500
BD Horizon™ BV650 BD Horizon™ V450
BD Horizon™ BV711
BD Horizon™ BV786
488 nm
BD Horizon™ PE-CF594 BD Horizon™ BB515 FITC, AlexaFluor®488
PE
PE-Cy7 PerCP, PerCP-Cy5.5
561 nm
PE
PE-Cy7
BD Horizon™ PE-CF594
640 nm APC-R700 APC AlexaFluor® 647 APC-H7, APC-Cy7
Importance of Fluorochrome Choice
V450 BV510 BV421 BV605
CD4
CD
3
• Match reagents with Antigens classified as high, intermediate
and low expressed
• Bright dyes are important when looking at dim antigens
• Choice of fluorochrome helps understand more about the
biology of the experiment
Panel Design Principles II
• Avoid significant spectral overlap between markers
on the same population.
Impact of Spillover Background & Resolution
Population resolution is decreased by increased spread due to spillover
from other fluorochromes.
• Maximal resolution & sensitivity of a given subpopulation
• Minimimal fluorescence spillover into the detector that defines that
population
Spread of the
populations due
to spillover
Spread Resolution
Minimize Impact of Fluorescence
Spillover and Maximize Resolution
Understanding the impact of
fluorescence spillover on spread
is the key to good panel design
Use a fluor for CD3
with less spillover into
the CD56 detector
SD
MFI
Negative of Width
Brightness SI Resolution
CD
56
CD3
CD3
CD
56
How can we improve the
resolution of this double
positive population? Use a brighter
fluor for CD56
CD3
CD
56
1
1
2
2
Strategies to Minimize Spillover Issues
• Multiple antigens co-expressed on the same cell
=> spread them across as many lasers as possible
• Combining fluorochromes with high spillover
=> spread across different cell types
• Use optimal compensation controls
=> Treat the compensation controls the same way as cells (i.e. fixation)
=> Use bright and clear expressed markers
Panel Design Principles II
• Avoid significant spectral overlap between markers
on the same population.
• Prefer red-laser fluorochromes for markers on highly
autofluorescent cells.
• Always check for tandem-dye issues.
Tandem Dyes
• Chemical coupling of small organic dyes (e.g. Cy7)
with a fluorescent protein (e.g. PE)
Cyanine 7 (Cy7) photo-active center
of PE
Tandem Dyes Advantages, Challenges & Solutions
• Advantages
– Increasing number of fluorescent dyes
– Bright fluorochromes with a high stain index
• Challenges
– Degradation
– Lot to lot variances
– Antibody-specific variances
• Solutions
− Protect from light & avoid fixation
− Lot-specific compensation
− Label-specific compensation
• Automated on all digital flow
cytometers from BD Biosciences
Summary - Optimizing an Assay Panel Design Process Workflow
Spillovers of fluorochromes
Ranking of fluorochrome brightness / Match antigen specificities to fluorochrome brightness / resolution (high to low) Spillover
Ranking of antigen density (high to low)
Classify as Primary, Secondary, Tertiary Markers
Co-expression of markers on populations of interest Antigens
What Reagents are available? Fluorochrome
Define the Assay; Purpose / Goal
Cell type; biological function (e.g. cytokines); species
Definition of Sub-populations, CD Markers & “critical” populations Biology
Optical Configuration (laser, filter, PMT)
Gain (PMT voltage) optimization Instrument
Optimize Panel Design using the above information
Maximize resolution of critical populations Optimization