“Measuring Antigen Specific T- cells using Surface and Intracellular Staining Polychromatic Flow Cytometry” 3 rd Annual CFAR Flow Cytometry Workshop 6-10.

Slides:



Advertisements
Similar presentations
Key Variables in ICS Assays
Advertisements

Building a Panel Select markers Select conjugates Method to build panel performance criteria.
A. a). d). c). f). b).e). g). Figure S1. NAT2 expression in lymphocytes and monocytes from a healthy volunteer. PBMC from a healthy volunteer were simple.
Design and optimization of multicolor panels Holden T. Maecker.
Steps to Success with Multicolor Flow Cytometry
What is Flow Cytometry? Flow Cytometry uic Introduction to Flow Cytometry IGC Workshop Multicolor Flow Cytometry IGC – April 28, 2010 Adapted from Holden.
Issues in Multicolor Flow Cytometry: Beyond 6 Colors
Quality Control in Immunophenotyping Dr. N. Varma Prof. & Head – Hematology Post Graduate Institute of Medical Education & Research (PGIMER), Chandigarh.
Early HIV cohort: Frozen PBMC samples from all 37 HIV-1 infected subjects; (77% of subjects within 6 months of seroconversion) (HIV negative or control.
2013 Duke CFAR Flow Cytometry Workshop Data Analysis.
Assays of Immune Function. Some Definitions BrdU: bromodeoxyuridine (incorporated into DNA during cell division) CBA: cytometric bead array DC: dendritic.
Advancements in FACS analyzers optical design leads to greater functionality and a smaller footprint. INTRODUCTION In the past decade, instrumentation.
Page 1 © J.Paul Robinson, Purdue University BMS 602 LECTURE 9.PPT BMS LECTURE 10x Flow Cytometry: Theory Bindley Bioscience Center Purdue.
Introducing a new instrument to the Cancer Center Flow Cytometry Core Facility: The LSR II by Becton Dickinson.
“Measuring Antigen Specific T-cells using Surface and Intracellular Staining Polychromatic Flow Cytometry” 4th Annual CFAR Flow Cytometry Wet-Workshop.
Basics of Flow Cytometry Holden Maecker. Outline Definitions, what can be measured by flow cytometry Fluidics: Sheath and sample streams, flow cells,
2014 Duke CFAR Flow Cytometry Workshop Data Standards and Annotation.
Intracellular Cytokine Staining (ICS) Flow Cytometry Assay 1 Kent J. Weinhold, Duke CFAR Director November 6th, 2013 CFAR Director’s Meeting Flow Cytometry.
Applications of flow cytometry in basic immunology Generation and characterization of DC Assays for T cell activation –Cell proliferation – Cell division.
2013 Duke CFAR Flow Cytometry Workshop Data Standards and Annotation.
Flow Cytometry at Boston University Medical Campus Introduction to some methods that we offer Yan Deng (X4-5225), Gerald Denis (X4-1371),
Detection of Immune Responses in Mucosal T-cells in Kenya Jackton Indangasi 2, Hannah Cheeseman 1, Onyango J. I. Obila 2, Simon Ogola 2, Robert Langat.
Flow cytometry to evaluate vaccine-induced T cell responses: standardized analysis of large numbers of FCS files Stephen De Rosa, M.D. HVTN Laboratory.
Introduction To Flow Cytometry By Noha Kamel. Flow cytometry is a method of measuring multiple physical and chemical characteristics of particles by optical.
Peripheral T follicular Helper Cells (pTfh)
Laser Flow Cytometry Forward Scatter indicates size Forward Scatter.
Flow Cytometry Basic Training. What Is Flow Cytometry? Flow ~ cells in motion Cyto ~ cell Metry ~ measure Measuring properties of cells while in a fluid.
Potential Applications of Flow Cytometry Cell activation statusCell activation status Cell cycle distributionCell cycle distribution Cell divisionCell.
Multi-parameter Flow Cytometry: available dyes and combined usage Martin R. Goodier Department of Immunology Imperial College London.
Cytometry tutorial: The impact of adjusting PMT voltages on spillover and compensation Thomas Myles Ashhurst1,2,3, Adrian Lloyd Smith3,4 1Viral Immunopathology.
Dotplots CD3 CD4 Allow for visualizing relationship between two different parameters that is not apparent by histogram analysis.
Cytometry tutorial: The impact of adjusting PMT voltages on spillover and compensation Thomas Myles Ashhurst1,2,3, Adrian Lloyd Smith3,4 1Viral Immunopathology.
SSC -A SLAN CD16 CD14 CD3-CD19-CD56 CD123 HLA-DR CD33
C. 24-well whole blood (HIV+)
Greg Finak, Ph.D., Senior Staff Scientist Marylou Ingram ISAC Scholar
Flow Cytometry Halima Moncrieffe, University College London, UK IL-17
Supplementary Figure 3 Antigen-specific responses are enhanced by stimulation in an in vitro stimulation (IVS) assay, as well as with stimulation using.
A. B. EXP #1: 3 donors EXP #2: 3 donors EXP #3: 6 donors EXP #4:
Forensic Flow Cytometry
Volume 66, Issue 6, Pages (June 2013)
Figure e-1A.
WT1-specific T-cell responses in high-risk multiple myeloma patients undergoing allogeneic T cell–depleted hematopoietic stem cell transplantation and.
COMPENSATION + FITC - PE - + PE - FITC - FITC detector FITC PE
AAV-1–mediated gene transfer to skeletal muscle in humans results in dose-dependent activation of capsid-specific T cells by Federico Mingozzi, Janneke.
Engineering Human Peripheral Blood Stem Cell Grafts that Are Depleted of Naïve T Cells and Retain Functional Pathogen-Specific Memory T Cells  Marie Bleakley,
Selective expansion of polyfunctional pathogen-specific CD4+ T cells in HIV-1–infected patients with immune reconstitution inflammatory syndrome by Yolanda.
Reduced TH1/TH17 CD4 T-cell numbers are associated with impaired purified protein derivative–specific cytokine responses in patients with HIV-1 infection 
Functionally Active HIV-Specific T Cells that Target Gag and Nef Can Be Expanded from Virus-Naïve Donors and Target a Range of Viral Epitopes: Implications.
Measurement of Cell Surface Receptors
by Jason M. Brenchley, Mirko Paiardini, Kenneth S. Knox, Ava I
Volume 27, Issue 4, Pages (October 2007)
Improving T-cell expansion and function for adoptive T-cell therapy using ex vivo treatment with PI3Kδ inhibitors and VIP antagonists by Christopher T.
Skin-Resident Effector Memory CD8+CD28– T Cells Exhibit a Profibrotic Phenotype in Patients with Systemic Sclerosis  Gang Li, Adriana T. Larregina, Robyn.
by Vladia Monsurrò, Ena Wang, Yoshisha Yamano, Stephen A
Jelle de Wit, PhD, Maarten E. Emmelot, BSc, Martien C. M
Functional leukemia-associated antigen-specific memory CD8+ T cells exist in healthy individuals and in patients with chronic myelogenous leukemia before.
Reconstitution of Natural Killer Cells in HLA-Matched HSCT after Reduced-Intensity Conditioning: Impact on Clinical Outcome  Caroline Pical-Izard, Roberto.
J. Joseph Melenhorst, Phillip Scheinberg, Ann Williams, David R
Human dendritic cell subset 4 (DC4) correlates to a subset of CD14dim/−CD16++ monocytes  Federica Calzetti, BS, Nicola Tamassia, PhD, Alessandra Micheletti,
The Art of Flow Cytometry
Volume 19, Issue 11, Pages (November 2011)
Flow cytometry analysis of TNF-β- and IL-10-producing CD33+ cells.
Volume 28, Issue 6, Pages (June 2008)
Volume 11, Issue 11, Pages (June 2015)
Volume 36, Issue 1, Pages (January 2012)
Theoretical Immunology: Aging
High-dimensional analysis of effector CD4 T cell function following γHV68 infection in B6 and IL-10KO mice. High-dimensional analysis of effector CD4 T.
IL-33, IL-25, and TSLP induce a distinct phenotypic and activation profile in human type 2 innate lymphoid cells by Ana Camelo, Guglielmo Rosignoli, Yoichiro.
Ex vivo depletion of alloreactive cells based on CFSE dye dilution, activation antigen selection, and dendritic cell stimulation by Wayne R. Godfrey, Mark.
Intracellular TNF-α and IL-4 expression in gated CD33+ monocytes by three-color flow cytometry. Intracellular TNF-α and IL-4 expression in gated CD33+
Presentation transcript:

“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

Part 1 of 3 Overview of PFC Assay Duke University Medical Center

IL-4IL-2 TNF  IFN  APC-T cell interactions Cytokine/Chemokine expression Rantes Apoptosis Proliferation/ Death Memory CD4 T Cell Response to Ag From H. Maecker Duke University Medical Center

CD4 + T cell cytokines CD8 + CTL APC MHC II CD4 CD8 cytokines Ag peptide MHC I T, B, or APC MHC I Whole protein Optimal peptide Duke University Medical Center From H. Maecker

Response to CMV pp65 Peptide Mix 0.19%2.03% pp65 proteinpeptide mixA2 peptide 1.14% CMV lysate 0.87% CD8 7.41%0.27%0.04%0.27% CD4 Duke University Medical Center From H. Maecker

Peptide Mixes 15 a.a. 11 a.a. CMV pp65: pool of 138 peptides HIV p55: pool of 120 peptides Duke University Medical Center

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 Duke University Medical Center

Wash 5. Permeabilize Wash 6. IC Stain 7. Acquisition 8. Analysis Overview of 11-Color Assay 4. Lyse/Fix Brefeldin Monensin 3. Surface Stain 2. Stimulate Wash lymphocyte erythrocyte cytokine 6 hrs Amine CD14 CD3 CD4 CD8 CD45RO CD27 CD57 IFN  IL2 TNF 1. Thaw Rest CD107 6 h Costim SEB CMVpp65 Wash CD107 PE-Cy5 CD8 + CM Response 7+g+M+ g+M+ M+ MondayTuesdayWednesday Thursday - Friday Duke University Medical Center

FSC-W FSC-H 88.3 : CD8 Q705 : CD4 CY55PE FSC-A SSC-A 99.3 : CD3 Amcyan : vAmine CD14PB CD19 PB 41.4 Gating Strategy for 11-Color Maturation/Function Panel: 1 of 3 CD4 PerCP-Cy5.5 SSC-A Exclusion (Violet H) FSC-H FSC-ACD3 AmCyanFSC-W CD8 Alexa700 UngatedSingletsCD3+ Exclusion- Scatter Basic Gates: CD4 + CD8 - CD8 + CD4 - CD4 + CD total Duke University Medical Center

: CD27 CY5PE : CD27 CY5PE : CD57 Q : CD57 Q Gating Strategy for Sampson 11-Color Maturation/Function Panel: 2 of 3 : CD27 CY5PE : CD57 Q CD57 FITC CD27 APC-Alexa750 CD45RO ECD N N N CM EM TE E E E Maturational Gates: CD4 + CD8 - CD8 + CD4 - CD4 + CD8 + CD45RO ECD Naive Central Memory Effector Memory Terminal Effector Effector Naive Central Memory Effector Memory Terminal Effector Effector Naive Central Memory Effector Memory Terminal Effector Effector - 5 per basic subset Duke University Medical Center

: CD107a AX CD107 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 = CD107 g = IFN-  2 = IL-2 T = TNF-  1.14 IL-2 TNF-  IFN-  Duke University Medical Center

Visualizing PFC Data: CMVpp65-specific Polyfunctional Response in CD8 + Central Memory Subset Increases Post-Vaccination Betts, (2006) Blood 107, Makedonas, (2006) Springer Semin. Immunopathol. 28, Simplified Presentation of Incredibly Complex Evaluations Dr. Mario Roederer Immunotechnology Section VRC / 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 batches CD38 vs HLA-DR Staining on Ctrl 5L 28Feb08 5L CD8+ 04Marb08 5L CD8+ 11Mar08 5L CD8+ 06Mar08 5L CD8+ Duke University Medical Center

uncompensated compensation FSC/SSC settings PMT settings highlow Difficulties in doing Automated Analysis related to Instrument Settings CD4 CD3 IFN  CD69 CD4 SSC FSC SSC 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 Red 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 Ottinger, et. al., Poster #28, 23rd Annual Clinical Cytometry Meeting (2008) Mahnke, et. al. Clin Lab Med September; 27(3): 469-v. Lamoreaux, et. al., Nature Protocols 1, (2006) on line 9 November 2006 Duke 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 CD3 AmCyan 9.8e-4 Unstained SSC Blue B Unstained CD57 FITC CD3 AmCyan 20.5 Duke University Medical Center

Is this positive??? CMV pp65 stimulated sample Maecker, et. al. Duke University Medical Center

Tandems Degrade! Ice Ice Dark Dark Fix Fix Controls Controls 6 hours 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 Error CD38 vs HLA-DR Staining on Ctrl 5L 28Feb08 5L CD8+ Lot Marb08 5L CD8+ Lot Mar08 5L CD8+ Lot Mar08 5L CD8+ Lot Feb08 5L CD8+ Lot 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

NCMEMTEE 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, 6:13http:// Duke University Medical Center

CIC ICS Gating Panel 110 labs participate d and there were 110 different approache s to gating

Before Backgate After Backgate IFNg Backgate CD3 AmCyan Exclusion CD4 GatedCD8 Gated IFNg PE-Cy7 CD4 PerCP-Cy5.5 CD8 APC-Cy7 Before Backgate After Backgate A B BACKGATING: purity & recovery Duke University Medical Center

Gating bias in proficiency panel results CD4 FITC IL2+IFN  PE UnstimCEFCMV pp % 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!!! 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 Gating Manual Cluster Gating Automated Duke University Medical Center

Would you know a positive if you saw one? Roederer. Cytometry Part A, 73A: (2008) Horton et. al. J Immuno Methods, 323:39-54 (2007) Maecker et. al. Cytometry Part A, 69A: (2006) Comin-Anduix et. al. Clin Cancer Res, 12(1): (2006) 2xSD? >0.05%? Outside Normal Range RCV? 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)FunctionBoolean (16) CD4 + CD8 - CD4 + CD8 + CD4 - CD8 + Naïve Central Memory Effector Memory Effector Terminal Effector CD107 IFN-  IL-2 TNF-  Basic (3)Maturation (5)Boolean (16) XX 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/trial Duke University Medical Center

Data Annotation - for all 143,280 data points! Study ID Method Assay Name Batch # Operator Sample ID Visit ID Accession # % Viable (Flow) % Viable (Guava) Recovery CD4 count CD8 count Gate Name (Parameter Names) Tube Name File Name Error Code (1-11) Checking: X1 - for electronic data X3 - 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 = 49 days!!! Duke University Medical Center

Part 3 of 3 Why does this matter?? Why are you here??? Duke University Medical Center

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 stimulation HIV negative donor Example CMVpp65 stimulation CMV positive donor % CD8+ CFSE low Laboratory Duke 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- IFN  + IL-2 PE CD3 APC-Cy7 Rep #1 Rep #2 Rep #3 Duke University Medical Center

Acknowledgements Duke CFAR Kent Weinhold Jennifer Enzor Twan Weaver Jianling Shi Cliburn Chan Patricia D’Souza (DAIDS) CFSE Standardization: Claire Laundry (NIML) EQAPOL Duke Tisch Brain Tumor Center Gary Archer Duane Mitchell John Sampson CHAVI VRC Steve Perfetto Laurie Lamoureaux Mario Roederer CVC Sylvia Janetski Duke DTRI Scottie Sparks (Roche)