“Measuring Antigen Specific T-cells using Surface and Intracellular Staining Polychromatic Flow Cytometry” 3 rd Annual CFAR Flow Cytometry Workshop 6-10 May, 2013 Janet Staats Flow Cytometry Core Facility Center for AIDS Research Duke University Medical Center E-mail: [email protected]
“ Measuring Antigen Specific T-cells using Surface and Intracellular Staining Polychromatic Flow Cytometry ” 3 rd Annual CFAR Flow Cytometry Workshop 6-10 May, 2013 Janet Staats Flow Cytometry Core Facility Center for AIDS Research Duke University Medical Center E-mail: [email protected]. - PowerPoint PPT Presentation
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“Measuring Antigen Specific T-cells using Surface and
Simplified Presentation of Incredibly Complex Evaluations
Dr. Mario RoedererImmunotechnology SectionVRC / NIAID / NIH
Duke University Medical Center
Part 2 of 3
PFC Challenges
Duke University Medical Center
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!)
Duke University Medical Center
Consistency across batchesCD38 vs HLA-DR Staining on Ctrl 5L
28Feb085L CD8+
04Marb085L CD8+
11Mar085L CD8+
06Mar085L CD8+
Duke University Medical Center
uncompensated
compensationFSC/SSC settings
PMT settings
highlow
Difficulties in doing Automated Analysis related to Instrument Settings
CD4
CD
3
IFNg
CD
69
CD4
SSC
FSC
SSC
optimal optimal
Duke University Medical Center
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!)
Duke University Medical Center
Optimization using Spillover Assessments: Using Titration Files to Assess Spreading Error
Violet G- CD3 AmCyan
<Blu
e B
-A>
<Vio
let H
-A>
<Red
C-A
>
<Red
B-A
>
Red
A-A
<Gre
en E
-A>
<Gre
en D
-A>
<Gre
en C
-A>
<Gre
en B
-A>
<Gre
en 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
<Blu
e 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
SSC
CD3AmCyan
9.8e-4Unstained
SSC
0.047
Blue B
Unstained
66.3
4.58
0.13
CD57 FITC
CD3AmCyan
20.5
Duke University Medical Center
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…
• Instrument - optical configuration, optimization, standardization, and calibration
• Reagent - optimization and standardization
• Sample processing• Staining protocols• Data Analysis - compensation &
gating• Volume of data (death-by-excel!) Duke University Medical Center
9-Color Activation/Maturation Using Cryo-preserved PBMC
Duke University Medical Center
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
Duke University Medical Center
Challenges…
• Instrument - optical configuration, optimization, standardization, and calibration
• Reagent - optimization and standardization
• Sample processing• Staining protocols• Data Analysis - compensation &
gating• Operator• Volume of data (death-by-excel!)
Duke University Medical Center
How would you gate?
Markers:CD3CD4CD8IL-2+IFNg(FSC)(SSC)
Duke University Medical Center
N CM EM TE E
Pre-Vaccination
33%
21%
27%
2%
17%
Post-Vaccination
8%
48%25%
2%
17%
Duke University Medical Center
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 Panel110 labs participated and there were 110 different approaches to gating
BeforeBackgate
AfterBackgate
IFNgBackgate
CD3 AmCyan
Excl
usio
n
0.38 5.74
CD4 Gated CD8 Gated
5.230.27
IFNg PE-Cy7
CD
4 Pe
rCP-
Cy5
.5
CD
8 A
PC-C
y7
BeforeBackgate
AfterBackgate
A
B
BACKGATING: purity & recovery
Duke University Medical Center
Gating bias in proficiency panel results
CD4 FITC
IL2+
IFNg
PE
Unstim CEF CMV pp65
0.02%
0.01%
0.16%
0.03%
0.02%
0.17%
0.02%
0.03%
0.21%
Duke University Medical Center
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
-g +
IL-2
PE
Expert GatingManual
Cluster GatingAutomated
Duke University Medical Center
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%? Outside
Normal RangeRCV?
Duke University Medical Center
Challenges…
• Instrument - optical configuration, optimization, standardization, and calibration
• Reagent - optimization and standardization
• Sample processing• Staining protocols• Data Analysis - compensation &
gating• Operator• Volume of data (death-by-excel!)
Duke University Medical Center
Assay Complexity
Duke University Medical Center
Endpoints for 11-Color Maturation/Function Panel DEATH BY EXCEL ……..
Basic (3) Maturation (5) Function Boolean (16)CD4+ CD8-
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+
CFS
E lo
w
LaboratoryDuke University Medical Center
History of Flow-based Proficiency/Standardization Efforts
Duke University Medical Center
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
Duke University Medical Center
DAIDS ICS Proficiency:Round 6, 26Jun09 (CMVpp65)
CD4-CD8+ CD4+CD8-
IFNg
+ IL-
2 PE
CD3 APC-Cy7
Rep #1
Rep #2
Rep #3
Duke University Medical Center
Acknowledgements
Duke University Medical Center
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