Polychromatic Flow Cytometry and Flow Applications

Basic Concepts

Kevin P. Weller

Technical Applications Specialist

T Cellζ ζ

TCR

recognition

signaling

CD3 CD3

ITAM FYN

CD45CD4/CD8

Lck

α βε εδ γ

CD28

T Cellζ ζ

FYN

CD45CD4/CD8

Zap 70

α βε εδ γ

APC

MHC Class IICD28

Lck

Co-stimulation LAT

Gads

SO

S

Grb2

PLCg1

Ras

MAPKCytoskeletal Changes

promotorJun Fos

NF-AT, PKC,Ras

IL-2

Polychromatic Flow CytometryPolychromatic Flow Cytometry

• What Do We Need For PFC?– Chemistry – the fluorescent dyes

• Must be bright (S/N)• Minimal spectral overlap• Straightforward conjugation to antibodies

– Instrumentation• More Light Sources: Multi-laser (2- 4 or more)• More Detectors: 6 to 16 or more parameters• More Efficient Optical Pathway: Higher sensitivity• Higher resolution & fast complex data handling :Digital

Electronics & New Graphical User Interface

Polychromatic Flow CytometryPolychromatic Flow Cytometry

• Experimental design: – Make “Good” Fluorochrome/Antigen Density Choices/Matches

• Implementing multicolor panels is principally empirical and requires many iterations (time)

– Optimize Instrument Setup• Photomultiplier Voltages• Compensation/Spillover

– Add necessary controls • Fluorescence Minus One (FMO)• Autofluorescence Controls• Optimized Isotypic Controls

• Hardware– Digital Electronics: Eliminate Analog Artifacts

• Software:– Automate compensation– Enhance graphical user interface

Practical Considerations: Improving Resolution

““Bright” = good resolution Bright” = good resolution sensitivitysensitivity

WD(SI)Index Stain

W2

W1

D

Various fluorochromes-stain Various fluorochromes-stain indexindex

Reagent Clone Filter Stain Index

PE RPA-T4 585/40 356.3

Alexa 647 RPA-T4 660/20 313.1

APC RPA-T4 660/20 279.2

PE-Cy7 RPA-T4 780/60 278.5

PE-Cy5 RPA-T4 695/40 222.1

PerCP-Cy5.5 Leu-3a 695/40 92.7

PE-Alexa 610 RPA-T4 610/20 80.4

Alexa 488 RPA-T4 530/30 75.4

FITC RPA-T4 530/30 68.9

PerCP Leu-3a 695/40 64.4

APC-Cy7 RPA-T4 7801/60 42.2

Alexa 700 RPA-T4 720/45 39.9

Pacific Blue RPA-T4 440/40 22.5

AmCyan RPA-T4 525/50 20.2

6-color 8-color 10-color Additional

FITC or Alexa 488 FITC or Alexa 488 FITC or Alexa 488 FITC or Alexa 488

PE PE PE PE

PE-Texas Red or PE-Alexa 610

PE-Texas Red or PE-Alexa 610

PerCP-Cy5.5 PerCP-Cy5.5 PerCP-Cy5.5 PerCP-Cy5.5

PE-Cy7 PE-Cy7 PE-Cy7 PE-Cy7

APC or Alexa 647 APC or Alexa 647 APC or Alexa 647 APC or Alexa 647

Alexa 680 or 700 Alexa 680 or 700

APC-Cy7 APC-Cy7 APC-Cy7 APC-Cy7

AmCyan AmCyan AmCyan

Pacific Blue Pacific Blue Pacific Blue

Q-dot 655, 705…

Best color Combinations…Best color Combinations…

Building An PCF Assay: Building An PCF Assay: Relative Antigen DensitiesRelative Antigen Densities

• Approximate Relative Antigen Densities from Technical Data Sheets

• Match The Lowest Density Antigen To The Brightest Fluorochrome, etc………….– Limited by conjugate availability– New cheaper custom conjugates

available– Consider potential spectral

overlap

Building An PCF Assay:Building An PCF Assay:Laser ChoicesLaser Choices

Optimize Your PCF Assay By:• Using Multiple Laser Lines• Don’t “Pack” A Laser Line• Choose “Optimal” Laser/Fluorochrome

Combinations:– To Minimize Spillover Background– To Optimize Signal :Noise

• Optimize Filter Choices to Minimize Spillover– Use JAVA Applet on BD Website

Building An PCF Assay:Building An PCF Assay:Effect of Spillover on Double Stained CellsEffect of Spillover on Double Stained Cells

CD45-FITCDim CD4-PE

Compensated analog data:

CD45 FITC makes

dim CD4 difficult to measure

due to FITC spillover into

PE and resultant “spread”

CD45- PerCPDim CD4-PE

Compensated analog data:

CD45 PerCP allows

same dim CD4 cells to be

separated from bkg. – little

spillover into PE

Top 4 Sources of ProblemsIn Multi-Color Analyses

Top 4 Sources of ProblemsIn Multi-Color Analyses

1.) Compensation

2.) Compensation

3.) Compensation

4.) Compensation

1.) Compensation

2.) Compensation

3.) Compensation

4.) Compensation

Basic Principles of Compensation Basic Principles of Compensation - The Problem- The Problem

FITC

PE

450 500 550 600 650

Remember the basic assumption of flow analysis: The signal in FL1= the signal from FITC and only FITC and the signal in FL2= the signal from PE and only PE.

Remember the basic assumption of flow analysis: The signal in FL1= the signal from FITC and only FITC and the signal in FL2= the signal from PE and only PE.

This is NOT TRUE for the raw data! The process by which each fluorescence channel is “corrected” for this spectral overlap is termed Fluorescence Compensation

This is NOT TRUE for the raw data! The process by which each fluorescence channel is “corrected” for this spectral overlap is termed Fluorescence Compensation

FL1 = FITC + x% PEFL1 = FITC + x% PE

FL2 = PE + y% FITCFL2 = PE + y% FITC

Compensation - Too Little; Too Compensation - Too Little; Too MuchMuch

Compensation- Too Dim, Too Bright Compensation- Too Dim, Too Bright Compensation ControlsCompensation Controls

Small errors in compensation of a dim control (A) can result in large compensation errors with bright reagents (B & C).

Building An PCF Assay:Building An PCF Assay: Spillover increases background

http://www.bdbiosciences.com/spectra/

Building An PCF Assay:Building An PCF Assay:FMO (Fluorescence Minus One)FMO (Fluorescence Minus One)

• Compensated data exhibits spread• Bright single positives may change threshold

levels between dim and background in other dimensions

• Use where autofluorescence and/or isotypic controls are NOT useful for determining threshold over background

• The best control is one stained with all reagents except the one of interest

Building An PCF Assay:Building An PCF Assay:FMO (Fluorescence Minus One)FMO (Fluorescence Minus One)

100 101 102 103 104100

101

102

103

104

105

100 101 102 103 104 100 101 102 103 104

Unstained Control FMO Control Fully Stained

PE

FITC

FITCPE

Cy5PECy7PE

ĞĞĞĞ

CD3Ğ

CD8CD45RO

CD3CD4CD8

CD45RO

Isotype BoundsFMO Bounds

PBMC were stained as shown in a 4-color experiment. Compensation was properly set for all spillovers

Courtesy Mario Roederer

Setting Up For A PCF Assay: Setting Up For A PCF Assay: Compensation: BDCompensation: BDTMTM CompBeads CompBeads

• Three Specificities– Anti-mouse Ig, kappa– Anti-rat Ig, kappa– Anti-rat/hamster Ig, kappa

• Negative Control Bead• Supplied in sets: Positive & Negative Bead• Stain with reagents used for PCF Assay

– Optimal Spillover Control– 50% positive/50% negative Control

Setting Up For A PCF Assay: Setting Up For A PCF Assay: Compensation: BDCompensation: BDTMTM CompBeads CompBeads

Method:For Each Conjugate:1. Add 1 drop (60 ul) of positive bead and 1

drop of negative bead to 100 ul of staining buffer in a tube or well

2. Add optimally titered antibody 3. Incubate 15-30 minutes RT4. Wash with staining buffer5. Resuspend pellet in staining buffer6. Run according to instructions for automated

spillover algorithm

Setting Up For A PCF Assay: Setting Up For A PCF Assay: Compensation: BDCompensation: BDTMTM CompBeads CompBeads

2010

57981

10

Spillover coefficient = slope

FITC Spillover calculationAutoCompensation methodMatrix algebra (PE = 0.83%)

2010

57981

1025150

10798152010

12

12

. k

)()(k

1

1

21

12

00209.100832.0

25203.000209.1

0.10083.0

2515.00.1

1

1

kPEPE

k

k

kk

comp

1.

2.

3.

4.

±183.8

±33.7

Setting Up For A PCF Assay: Setting Up For A PCF Assay: Compensation: CD20 BDCompensation: CD20 BDTMTM CompBeads CompBeads

Populations are alignedIn dye space

PEc = PE x 1.00209 +

FITC x -0.25203

Not a subtraction, rather a correction because we use matrix algebra and compensation coefficients.

±133.6±33.6

Setting Up For A PCF Assay:Setting Up For A PCF Assay:Compensation: TandemsCompensation: Tandems

0 hours

2 hours

22.5 hours

PE(FL2)

CD8 CD3PE-Cy5PE-Cy7 Time Sample

Left in Light

Logicle: Compensated Biexponential Logicle: Compensated Biexponential DisplayDisplay

Log at the upper end, linear at the low, and symmetrical about zero.Biexponential transform where data zero is shown by the crosshairs in the plot

• This FlowJo example shows the value of a mostly logarithmic scale on the upper end, and a lower linear region occupies a reasonable plot area compared to that in the blended scale. – Compensated single pos are

continuous– All populations are visible0 100 1000 10000 1x105

<FITC-A>

0

100

1000

10000

1x105

<PE

-A>

PCF: Questions of T Cell DifferentiationPCF: Questions of T Cell Differentiation

Questions of T Cell Differentiation that can be Addressed with Polychromatic Flow Cytometry

– What is the CD45RA/CD27/CD28 phenotype of antigen-specific CD4 and CD8 T cells?

• In IFN+ versus IL-2+ cells?• In CMV- versus HIV-specific cells?• In CMV-specific cells of HIV- versus HIV+

donors?

8-color antigen-specific immunophenotyping8-color antigen-specific immunophenotyping

Ab Conjugate Laser

CD28 PerCP-Cy5.5 488

CD45RA PE-Cy7 488

CD27 APC 633 Surface

CD8 APC-Cy7 633 staining

CD3 Pacific Blue 405

CD4 AmCyan 405

Anti-IFN FITC 488 Intracellular

Anti-IL-2 PE 488 staining

8 Color Compensation (LSR II)8 Color Compensation (LSR II)

CD4 FITC

CD4 PE

CD28 PerCP-Cy5.5

CD45RA PE-Cy7

CD3 Pacific Blue

CD4 AmCyan

CD27 APC

CD8 APC-Cy7

FITC PEPerCP-Cy5.5

PE-Cy7

APCAPC-Cy7

Pacific Blue

Am Cyan

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:

Auto-comp

Spillover Matrix

Hierarchal Gating StrategyHierarchal Gating Strategy

Phenotype of CMV-responsive CD4 Phenotype of CMV-responsive CD4 T cellsT cells

CD27

IFN Response IL-2 Response

CD

28C

D45

RA

0 1

78 20

1 1

69 29

64 20

14 1

68 29

3 0

Phenotype of CMV-responsive CD8 Phenotype of CMV-responsive CD8 T cellsT cells

IFN Response IL-2 Response

CD27

CD

28C

D45

RA

8 3

30 58

1 1

20 78

3 21

36 40

7 52

15 26

CFC Staining Protocol - Key StepsCFC Staining Protocol - Key Steps

Stimulate and Harvest Cells

Stain Cell Surface Antigens

Fix and Permeabilize Cells

Stain Intracellular Cytokines

Intracellular Staining Controls

Analyze by Flow Cytometry

Block Fc Receptors

T Cell Immunology Tool KitT Cell Immunology Tool Kit

Traditional Cytokine Flow Cytometry

IL-2

Ph

yco

eryt

hri

n

CD4 FITC

CFC & ProliferationCFC & Proliferation

Measures cellular incorporation of BrdU with gentle fixation and permeablization at neutral pH which allows the concomitant detection of other cellular determinants.

– Bromodeoxyuridine (BrdU) is a thymidine analog – Allows measurement of cell proliferation and cell

cycle status– May be used in vitro and in vivo– BrdU is incorporated into the DNA of cycling cells– Incorporated BrdU is detected with anti-BrdU mAb

– Prolonged exposure identifies cycling cells– Pulse labeling allows determination of cell-cycle

kinetics

BrdU Flow Kit

CFC & ProliferationCFC & Proliferation

Allows the correlation of:

• Phenotype

•Cytokine expression

•Cell Cycle

•Proliferation

T Cell Immunology Tool KitT Cell Immunology Tool Kit

Antigen Specific Cytokine Flow Cytometry

CD

69 P

E

anti-TNF FITC

Antigen Specific Cytokine Flow Antigen Specific Cytokine Flow CytometryCytometry

• Simultaneous single cell detection of cell surface and intracellular events (e.g. cytokines, activation antigens, proliferation, phenotypic markers)

• Whole blood (physiological conditions)

• Rapid method (<6 h)

• Compatible with variety of stimuli including antigen

CD4+ T cell cytokine response to HIV-1 antigen CD4+ T cell cytokine response to HIV-1 antigen following 3 immunizations with Remmunefollowing 3 immunizations with Remmune

CD4+ T cell cytokine response to HIV-1 antigen CD4+ T cell cytokine response to HIV-1 antigen following 3 immunizations with Remmunefollowing 3 immunizations with Remmune

anti-IFN FITC

CD

69-P

E

Viral load: <400CD4: 1147

What is a Cytometric Bead Array What is a Cytometric Bead Array (CBA)(CBA)

ELISA

=

Bead-based ImmunoassaysBead-based Immunoassays

+

+

Analyte of Interest Fluorescent Detector Ab

Capture BeadCapture Ab

Beads and Flow Cytometry –Beads and Flow Cytometry –A Powerful ToolA Powerful Tool

+

IL-8

IL-6

100

100

101

101

102

102

103

103

104

104

Bea

d In

ten s

ityF

L3

(6

70

LP

)

Detector Ab IntensityFL2 (585/42BP)

New CBA Flex BeadsNew CBA Flex Beads

• Single Size:– Forward/Side Scatter: 7um size, 99% singlets

• Maintain PE Reporter system with excitationoff 488 or 532 source– Indexing options

• Systems with 2 channels off 635nm– BD FACSArray– BD FACSAria– BD FACSCanto– BD LSRII

• Systems with 1 channel on 635nm– BD FACSCalibur

ABCDEFGHI

1 2 3 45 6 7 8 9

Plex definition: clustering Plex definition: clustering

Double clickor drag to assign

9-Plex for Measuring T Cell 9-Plex for Measuring T Cell ActivationActivation

1

2 3 4 5

6

7

89

1. Itk (Y511)

2. ERK (T202/Y204)

3. JNK (T183/Y185)

4. P38 (T180/Y182)

5. PLC (Y783)

6. ZAP70 (Y319)

7. LAT (Y171)

8. c-Jun (S63)

9. RSK (S380)

Phagocytosis: Fluorescent BeadsPhagocytosis: Fluorescent Beads

Quantitative Phagocytosis

using fluorescent

beads

Activation: Calcium FluxActivation: Calcium Flux

390 nm/ 495 nm

Ratio Of Ca++Bound Indo-1at 390 nm to Free Indo-1at 495 nm

Cytotoxicity: NK MediatedCytotoxicity: NK Mediated

http://sci.cancerresearchuk.org/axp/facs/davies/ISACXXI.pdf

PKH-26 Labeled NK Sensitive YAC-1 Lymphoma Cell Line

NK Effector Cells

To-Pro-3 DNA Dye

P-Glycoprotein: Drug ResistanceP-Glycoprotein: Drug Resistance

P-glycoprotein is a transmembrane protein that acts as an ATP-dependent efflux pump. This efflux activity has been suggested to lead to resistance to the drugs used in chemotherapy

pH: pH Dependent GFPpH: pH Dependent GFP

Changes in Mitochondrial-Matrix

pH Induced by Ultraviolet Radiation

Signal Transduction:Signal Transduction:Fluorescence Resonance EnergyTransferFluorescence Resonance EnergyTransfer

Interaction between Fas and FADD death Domains visualized by FRET

Fas CFP Plasmids were cotransfected withYFP expression vector YFP-C1 (Clontech) orA vector encoding FADD (DD)-YFP

The upper right quadrants indicate the % of CFP positive cells exhibiting FRET

Cell Division: CSFECell Division: CSFE

5-(and-6)-carboxyfluorescein diacetate, succinimidyl ester

is a lipophilic dye which incorporates into the cell

membrane

The amount of dye in the cell Membrane of proliferating cells

halves with each successive division

Übersicht ApoptoseÜbersicht Apoptose

Apoptosis: Apoptosis: Mitochondrial Membrane PotentialMitochondrial Membrane Potential

Control Staurosporine 1m 4hrs

FL1-H FL1-H

FL2

-H

FL2

-H

Apoptosis: Quantitative Analysis of Apoptosis: Quantitative Analysis of Caspase-3 ActivationCaspase-3 Activation

Jurkat cells Treated with Campothecin

Caspase 3 PE

Apoptosis: A Time CourseApoptosis: A Time Course

Annexin

PI

Apoptosis: PARP CleavageApoptosis: PARP Cleavage

Poly-ADP Ribose PolymeraseIs Cleaved By Caspases DuringApoptosis.

HeLa Cells Treated With 4 mCampothecin for 4 hours

Staining with anti-Cleaved PARP FITCIndicates 40% Apoptotic Index

0 Hours 6 Hours

APO-BRDU

Apoptosis: TUNEL AssayApoptosis: TUNEL Assay

Jurkat Cells Treated for 6 hours with IgM Anti Fas Antibody

lysisY Z

Phospho-specific Ab blot

1. Limited opportunity to view variability

2. Limited statistics

3. Requires sorting of subsets to gain access to intracellular antigens (not easily multiplexed)

4. Requires large #s of cells (106)

5. Lysates: not living cells

0.1 1 10 100 1000

Flowcytometry

1

110

1100 4671

115

25 50

7

227

Current methods for assessing phosphorylation

1. Possible to observe heterogeneity

2. Considerably enhanced statistics

3. Can subset via surface markers to gain access to rare cell types

4. Requires fewer cells (103 - 104)

5. Simultaneous detection of multiple post-translational modifications within heterogenic cell populations

11 Color Flow Cytometry Looking at 11 Color Flow Cytometry Looking at Signaling in Subpopulations of Cells Signaling in Subpopulations of Cells

Perez & Nolan, Nature Biotechnology, Vol 20, p155-162 Multi-Dimensional Analysis

Development of Visualization toolsDevelopment of Visualization tools

Nolan et al.

Systems Biology : Signaling Network Systems Biology : Signaling Network MappingMapping

Kinase 1

Kinase 11

Kinase 2

Kinase 6Kinase 3

Kinase 1

Kinase 3

Kinase 1

Kin

ase 1

1

Kin

ase 4

Kin

ase 9

Kin

ase 1

1

Kin

ase 1

1

Su

rface 2

p-p44/42p-p38 CD28 CD27 P-JNK CD45RACD62L CD11ACD8 CD3 CD4

0 0 0 1651 1914 2594 2180 2746 2506 0 0

1443 1382 451 1887 2088 1992 0 2149 1674 1631 1722

1755 0 1575 2311 0 1821 0 2427 1280 1835 1592

1629 1621 1290 2429 0 1008 0 2023 1686 2348 1208

0 1600 0 1767 0 2496 0 2412 939 0 733

1671 0 2409 2203 0 2141 0 1981 1012 2750 2016

0 0 0 0 0 2029 0 2201 2466 2486 1136

0 0 0 0 0 2230 0 2272 2619 2471 1023

2034 0 2439 2021 2397 0 1611 2033 1300 2642 2255

0 2367 0 0 0 2650 2731 1669 0 2166 1252

1750 1373 1780 2253 1441 0 1448 2109 1688 2338 1777

786 1344 0 2168 0 2461 2076 2537 1111 0 1109

0 1056 0 1880 1683 1947 2356 2169 1862 2341 588

1033 2195 0 2282 0 2175 2508 1698 664 1800 666

1560 1355 2193 2253 0 1935 674 1977 2107 2527 0

2031 1649 2020 2794 0 2247 2131 2389 1729 0 2140

2410 2090 2484 2449 2439 2212 2408 1898 1259 2675 2157

0 1360 1555 1996 1409 2147 0 2480 1264 0 1889

raf

p44/

42

mek

PLC

g

PIP

3

PIP

2

jnk

p38

AK

TP

KA

PK

C

MIT Supercomputer

Irish JM, Hovland R, Krutzik PO, Perez OD, Bruserud O, Gjertsen BT, Nolan GP.Single cell profiling of potentiated phospho-protein networks in cancer cells. Cell. 2004 Jul 23;118(2):217-28.

Clustering of Biosignature, Clustering of Biosignature, Clinical SignificanceClinical Significance

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