“Measuring Antigen Specific T- cells using Surface and Intracellular Staining Polychromatic Flow...

“Measuring Antigen Specific T-cells using Surface and

Intracellular Staining Polychromatic Flow Cytometry”

3rd Annual CFAR Flow Cytometry Workshop6-10 May, 2013

Janet StaatsFlow Cytometry Core Facility

Center for AIDS ResearchDuke University Medical Center

E-mail: [email protected]

Part 1 of 3

Overview of PFC Assay

Duke University Medical Center

IL-4IL-2

TNFaIFNg

APC-T cellinteractions

Cytokine/Chemokineexpression

Rantes

Apoptosis

Proliferation/Death

Memory CD4 T Cell Response to Ag

From H. MaeckerDuke University Medical Center

CD4+

T cellcytokines

CD8+

CTL

APC MHCII

CD4

CD8 cytokines

Ag

peptide

MHC I

T, B,or APC

MHC I

Wholeprotein

Optimalpeptide

Duke University Medical CenterFrom H. Maecker

Response to CMV pp65 Peptide Mix

0.19% 2.03%

pp65 protein peptide mix A2 peptide

1.14%

CMV lysate

0.87%

CD8

7.41%0.27% 0.04%0.27%

CD4

Duke University Medical CenterFrom H. Maecker

Peptide Mixes15 a.a.

11 a.a.

CMV pp65: pool of 138 peptidesHIV p55: pool of 120 peptides


Sampson Clinical Trial:11-Color Maturation/Function Panel

Basic Subset Markers:• CD3 (T-cells)• CD4 (T-Helper Subset)• CD8 (T-Suppressor Subset)

Exclusion Markers:• CD14 (Monocytes)• CD19 (B-cells)• vAmine (Dead cell marker)

Maturational Markers:• CD45RO• CD27• CD57

Functional Markers:• CD107• IFN-• TNF• IL-2


Wash

5. Permeabilize

Wash

6. IC Stain7. Acquisition

8. Analysis

Overview of 11-Color Assay

4. Lyse/Fix

BrefeldinMonensin

3. Surface Stain2. Stimulate

Wash

lymphocyteerythrocyte

cytokine

6 hrs

AmineCD14 CD3CD4CD8

CD45ROCD27CD57

IFNIL2TNF

1. Thaw

Rest

CD1076 h

CostimSEB

CMVpp65

Wash

CD107 PE-Cy5

CD8+ CM Response

7+g+M+g+M+

M+

Monday Tuesday WednesdayThursday - Friday


FSC-W

FS

C-H

88.3

<V705-A>: CD8 Q705

<G

710-

A>

: CD

4 C

Y55

PE

57.8

36.3

0.79

FSC-A

SS

C-A

99.3

<Violet G-A>: CD3 Amcyan

<V

iole

t H-A

>: v

Am

ine

CD

14P

B C

D19

PB

41.4

Gating Strategy for 11-Color Maturation/Function Panel: 1 of 3

CD

4 P

erC

P-C

y5.5

SS

C-A

Exc

lusi

on

(V

iole

t H

)

FS

C-H

FSC-ACD3 AmCyanFSC-W

CD8 Alexa700

Ungated Singlets CD3+ Exclusion-

Scatter

Basic Gates:

CD4+CD8-

CD8+CD4-

CD4+CD8+

- 3 total


<G

660-

A>

: C

D27

CY

5PE

43 54.1

2.580.33

<G

660-

A>

: C

D27

CY

5PE

56.4 28.6

8.466.55

<V

545-

A>

: C

D57

Q54

5

0.12 1.07

55.942.9

<V

545-

A>

: C

D57

Q54

5

5.67 13.2

24.256.9

Gating Strategy for Sampson 11-Color Maturation/Function Panel: 2 of 3

<G

660-

A>

: C

D27

CY

5PE

22 62.5

11.73.98

<V

545-

A>

: C

D57

Q54

5

3.98 22.9

51.721.5

CD

57

FIT

C

CD

57

FIT

C

CD

57

FIT

CCD

27

AP

C-A

lex

a75

0

CD

27

AP

C-A

lex

a75

0

CD

27

AP

C-A

lex

a75

0

CD45RO ECD

N

N

N

CM

CM

CMEM

EM

EM

TE

TE

TE

E

E

E

Maturational Gates:

CD4+CD8-

CD8+CD4-

CD4+CD8+

CD45RO ECD

CD45RO ECD

NaiveCentral Memory

EffectorMemory

Terminal Effector

Effector

NaiveCentral Memory

EffectorMemory

Terminal Effector

Effector

NaiveCentral Memory

EffectorMemory

Terminal Effector

Effector

- 5 per basic subset


<R710-A>: CD107a AX680

2.59CD107

Gating Strategy for Sampson 11-Color Maturation/Function Panel: 3 of 3

Functional & Boolean Gates: - 4 functional gates per maturational subset - 16 boolean gates per maturational subset

CM: CD8+CD4-

Boolean Gates

Polyfunctional (1: ++++)

Polyfunctional (4: +++)

Bifunctional (6: ++)

Monofunctional (4: +)

Nonfunctional (1: ----)

Key:7 = CD107g = IFN-2 = IL-2T = TNF-

1.14

IL-2

TNF-

IFN-

0.31

4.19


Visualizing PFC Data:CMVpp65-specific Polyfunctional Response in CD8+ Central Memory Subset Increases

Post-Vaccination

Betts, (2006) Blood 107, 4781-4789.Makedonas, (2006) Springer Semin. Immunopathol. 28, 209-219.

Simplified Presentation of Incredibly Complex Evaluations

Dr. Mario RoedererImmunotechnology SectionVRC / NIAID / NIH


Part 2 of 3

PFC Challenges


Challenges…

• Instrument - optical configuration, optimization, standardization, and calibration

• Reagent - optimization and standardization

• Sample processing• Staining protocols• Data Analysis - compensation &

gating• Operators• Volume of data (death-by-excel!)


Consistency across batchesCD38 vs HLA-DR Staining on Ctrl 5L

28Feb085L CD8+

04Marb085L CD8+

11Mar085L CD8+

06Mar085L CD8+


uncompensated

compensationFSC/SSC settings

PMT settings

highlow

Difficulties in doing Automated Analysis related to Instrument Settings

CD4

CD

3

IFNg

CD

69

CD4

SS

C

FSC

SS

C

optimal optimal


Challenges…




gating• Operators• Volume of data (death-by-excel!)


Optimization using Spillover Assessments: Using Titration Files to Assess Spreading Error

Violet G- CD3 AmCyan

<B

lue

B-A

><

Vio

let

H-A

><

Red

C-A

>

<R

ed B

-A>

Red

A-A

<G

reen

E-A

>

<G

reen

D-A

>

<G

reen

C-A

>

<G

reen

B-A

>

<G

reen

A-A

>

CD3AC (5ug/ml) Spillover assessment:

• After compensation CD3AC showed spilllover into Blue-B detector (FITC channel)

Blue Laser

Violet Laser

Red Laser

Green Laser

<B

lue

A-A

>

• Ottinger, et. al., Poster #28, 23rd Annual Clinical Cytometry Meeting (2008)• Mahnke, et. al. Clin Lab Med. 2007 September; 27(3): 469-v.• Lamoreaux, et. al., Nature Protocols 1, 1507-1516 (2006) on line 9 November 2006Duke University Medical Center

Spillover Assessments:CD3 AmCyan (5µg/mL) Spillover into CD27 (0.32µg/mL)

& CD57 FITC (1.8µg/mL)

• Spillover from CD3AC interferes with detection of dim CD27 pos cells

• Spillover from CD3AC does not

interfere with detection of CD57

• Spillover is acceptable if it does not interfere with proper classification of events

• mAb concentration may be varied to reduce spillover as long as frequency is unaffected

CD27 FITC

Blue B

SS

C

CD3AmCyan

9.8e-4Unstained

SS

C

0.047

Blue B

Unstained

66.3

4.58

0.13

CD57 FITC

CD3AmCyan

20.5


Is this positive???

CMV pp65 stimulated sample

Maecker, et. al.Duke University Medical Center

Tandems Degrade!

• Ice• Dark• Fix• Controls• 6 hours

Maecker, et. al.Duke University Medical Center

Challenges…




gating• Volume of data (death-by-excel!) Duke University Medical Center

9-Color Activation/Maturation Using Cryo-preserved PBMC


Batch Processing ErrorCD38 vs HLA-DR Staining on Ctrl 5L

28Feb085L CD8+Lot 05262

04Marb085L CD8+Lot 05262

11Mar085L CD8+Lot 05262

06Mar085L CD8+Lot 05262

26Feb085L CD8+Lot 05262


Challenges…




gating• Operator• Volume of data (death-by-excel!)


How would you gate?

Markers:CD3CD4CD8IL-2+IFNg(FSC)(SSC)


N CM EM TE E

Pre-Vaccination

33%

21%

27%

2%

17%

Post-Vaccination

8%

48%25%

2%

17%


Reproducible analysis allows us to measure an expansion of CD4+ CM cells post vaccination with

some degree of confidence

ICS Standardization Conclusions

• ICS assays can be performed by multiple laboratories using a common protocol with good inter-laboratory precision (<20% C.V.), that improves as the frequency of responding cells increases.

• Gating is a significant source of variability, and can be reduced by centralized analysis and/or use of standardized gating.

• Cryopreserved PBMC may yield slightly more consistent results than shipped whole blood.

• Use of pre-aliquoted lyophilized reagents for stimulation and staining can reduce variability.

BMC Immunology 2005, 6:13 http://www.biomedcentral.com/1471-2172/6/13 Duke University Medical Center

CIC ICS Gating Panel

110 labs participated and there were 110 different approaches to gating

BeforeBackgate

AfterBackgate

IFNgBackgate

CD3 AmCyan

Exc

lusi

on

0.38 5.74

CD4 Gated CD8 Gated

5.230.27

IFNg PE-Cy7

CD

4 P

erC

P-C

y5.5

CD

8 A

PC

-Cy7

BeforeBackgate

AfterBackgate

A

B

BACKGATING: purity & recovery


Gating bias in proficiency panel results

CD4 FITC

IL2+

IFN P

E

Unstim CEF CMV pp65

0.02%

0.01%

0.16%

0.03%

0.02%

0.17%

0.02%

0.03%

0.21%


We NEED better analysis tools!!!Manual (Expert) vs. Automated Analysis of

4-Color ICS Data File (CMVpp65)

0.21%0.18%

CD4 FITC

1.9%1.65%

CD8 PerCP-Cy5.5

IFN

- +

IL-2

PE

Expert GatingManual

Cluster GatingAutomated


Would you know a positive if you saw one?

Roederer. Cytometry Part A, 73A:384-385 (2008)Horton et. al. J Immuno Methods, 323:39-54 (2007)Maecker et. al. Cytometry Part A, 69A:1037-1042 (2006)Comin-Anduix et. al. Clin Cancer Res, 12(1):107-116 (2006)

2xSD?>0.05%?

OutsideNormal Range

RCV?


Challenges…




gating• Operator• Volume of data (death-by-excel!)


Assay Complexity


Endpoints for 11-Color Maturation/Function Panel DEATH BY EXCEL ……..

Basic (3) Maturation (5) Function Boolean (16)

CD4+ CD8-

CD4+ CD8+

CD4- CD8+

NaïveCentral MemoryEffector MemoryEffectorTerminal Effector

CD107IFN-IL-2TNF-

Basic (3) Maturation (5) Boolean (16)X X 240/stim=X 3 Stimulations/Sample (CoStim, SEB, CMVpp65) = 720 Endpoints/Sample

720 Endpoints/Sample x 200 Samples (192 Participants + 8 Controls) = 144,000 Endpoints/Trial

Note 1: Frequency of parent only, reporting units of #cells/µL doubles the total EP/trialDuke University Medical Center

Data Annotation - for all 143,280 data points!

Study IDMethodAssay NameBatch #OperatorSample IDVisit IDAccession #% Viable (Flow)% Viable (Guava)RecoveryCD4 countCD8 countGate Name (Parameter Names)Tube NameFile NameError Code (1-11)

Checking:X1 - for electronic dataX3 - for manual entry

Requires STRONG statistical support:• Quickly exceeds limits of excel• Format data for statistical analysis

• FJ: column (gates) vs row (file)• CSV: column (identifiers) vs row (single value)

• Check data• Manual check: 8sec/value x 143280 = 49 days!!!


Part 3 of 3

Why does this matter??Why are you here???


Why is Reproducibility Important?

CFSE Standardization Results (13 EXPERT IM Labs):- Very high inter-laboratory variability.- High background in some laboratories.- Responses to Gag and Nef peptide pools were

detected in HIV negative (control) donors!

Example Gag stimulationHIV negative donor

Example CMVpp65 stimulationCMV positive donor

% C

D8

+ C

FS

E lo

w

LaboratoryDuke University Medical Center

History of Flow-based Proficiency/Standardization Efforts


The number of measurements outside the optimal range established by the GS was determined for each laboratory. Each laboratory performed a total of 54 measurements (27 for CD4+ cells and 27 for CD8+ cells). The red line represents 50% (=27) of the total measurements. Laboratories above this line had over 50% of their measurements outside the optimal range. The green line represents 20% of total measurements. The laboratories below this line had over 80% of their measurements within the optimal range.

ICS Proficiency Testing Results: March 2007


DAIDS ICS Proficiency:Round 6, 26Jun09 (CMVpp65)

CD4-CD8+ CD4+CD8-

IFN

g +

IL-2

PE

CD3 APC-Cy7

Rep #1

Rep #2

Rep #3


Acknowledgements


Duke CFARKent WeinholdJennifer EnzorTwan WeaverJianling ShiCliburn Chan

Patricia D’Souza (DAIDS) CFSE Standardization:

Claire Laundry (NIML)

EQAPOL

Duke Tisch Brain Tumor CenterGary ArcherDuane MitchellJohn Sampson

CHAVI

VRCSteve PerfettoLaurie LamoureauxMario Roederer

CVCSylvia Janetski

Duke DTRIScottie Sparks (Roche)

“Measuring Antigen Specific T- cells using Surface and Intracellular Staining Polychromatic Flow...

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