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2.2.3.1 SIV Use Case

2.2.3.2 SIV gating SOP
3.2.3 SIV Results
4.2.3 SIV Discussion

Simian Immunodeficiency Virus (SIV) is commonly studied as a mechanism to learn more about HIV and AIDS. This study is looking at whether immunization with a peptide will increase cytokine response in vitro. IFN, IL-2, & TNF were tracked in CD4+ and CD8+ populations, for six populations of interest.

SIV Use Case Experiment Description using MiFlowCyt Standard

1. Experiment Overview

1.1. Purpose & Hypothesis: Detection of T-cell responses following administration of an AIDS vaccine to rhesus monkeys.
1.2. Keywords: SIV, Cytokine T-cells
1.3. Experiment Variables:  Timecourse of 6 timepoints x 3 primates x 3 treatments x 6 target populations/fcs file = 54 FCS files & 324 target pops for the Experiment.
variables

1.4. Organization: Dr. Joern Schmitz Lab, Beth Israel Deaconess Medical Center, Inc.
1.5. Primary Contacts: Dr. Joern Schmitz, Michelle Lifton
1.6. Date: Experiment conducted from 2/15/2007 through 9/19/2007
1.7. Conclusions - All primates had elevated IL-2 in CD4 and CD8 T-cells at time-point 2.
1.8. Quality Control Measures - Unstimulated and PMA positive controls were run.
2. Flow Sample/Specimen Details
2.1. Sample/Specimen Material Description - PBMCs from primate species Rhesus macaque were immunized with CS peptide over a timecourse.
2.2. Sample Treatment(s) Description - Samples were stimulated with PMA or CS_peptide or left unstimulated.
2.3. Fluorescence Reagent(s) Description -
FITC-A TNF
ECD-A CD8
PERCP-CY55-A CD4
PE-CY7-A IFN
APC-A IL-2
ALEXA700-A CD3 

3. Instrument Details - BD LSRII, BD FACSDiva
4. Data Analysis Details
4.1. List-mode Data File - FCS 3.0 files provided
4.2. Compensation Details acquisition defined or software defined and matrix name
Run 1 = 15-FEB-2007 - software computed compensation
Run 2 = 29-MAR-2007 - acquisition defined (and has compensation samples to allow software computed compensation)
Run 3 = 09-MAY-2007 - acquisition defined (and has compensation samples to allow software computed compensation)
Run 4 = 21-JUN-2007 - acquisition defined (and has compensation samples to allow software computed compensation)
Run 5 = 08-AUG-2007 - software computed compensation
Run 6 = 19-SEP-2007 - acquisition defined (and has compensation samples to allow software computed compensation)


4.3. Gating (Data Filtering) Details - Describe the rationale behind the gate placements and structure and tree. Why use PE for the gating of CD3 cells? How do you decide the cut-off point for cytokine positive events?

  1. Target populations
    1. Lymphocytes
      1. CD3+ Lymphocytes (T-cells)
        1. i. CD4+ T-cells (activated T-cells)
          1. CD4+ IFN subset
          2. CD4+ IL2 subset
          3. CD4+ TNF subset
        2. ii. CD8+ T-cells (antigen specific T-cells)
          1. CD8+ IFN subset
          2. CD8+ IL2 subset
          3. CD8+ TNF subset
Graphs below illustrated the process of defining the six targets.
The first gate below is the scatter gate to isolate particles the size of lymphocytes.
The second gate compares area vs. height of the Forward Scatter signal to remove doublets.
The third gate includes the CD3+ T-cells.
The fourth graph shows two gates, selecting CD8+ (top) and CD4+ (right) T-cells
Graphs 5 and 6 are representative of the six populations of interest. Graph 5 shows the CD4 cells expression of IL2, and Graph 6 shows the CD8 cells expression of TNF

gating

Additionally, the gated populations need to have more data analysis done as described in the SIV Data Analysis Document

Goals from conversations with Dr. Schmitz and Michelle Lifton
1) MiFlowCyt Experiment Description: gate placement decisions and biological analysis outcome. 

2) Is the gating SOP descriptive and correct? 

3) Get their analysis for all 6 runs. Currently only have Run 2 


Challenges:

  1. Contributing lab's workspaces are .jo files. Modified to only contain uniquely named target population. MichellesHIVRun2_forGateathon.jo
  2. There are 4 comp matrices in the .jo original file, when opening in 7.5.5, comp matrices are not correctly assigned to the samples. should use 03-29-07 crucell. Adam stated in Engineering meeting on 10/5/2009 that we should just export all the populations (and presumably stats) from .jo workspaces and not expect Java version of FlowJo to read in the .jo workspaces for now.
  3. 7.5.5 does not open the groups appropriately to contain the 9 test samples in the 03-29-07 group
  4. the target populations do not contain the same # of events when opened in 7.5.5 compared to 8.8.6. So it is not the same populations.
  5. The number of events in each FCS files has prevented the analysis of match ratio in spreadsheet programs. FJ7.5 can only calc. match ratio of .wsp within 7.5, not from 8.8.6 for magnetic gating or probability bin clustering. Magnetic gating is now available as of 8/10/09 in FJv7.6.
  6. 7.6 match ratio calc. does not allow for designation of which .wsp to include in the consensus sequence vs. which to exclude. (Calculate Match Ratio function in Debug menu)
  7. 7.6 population comparison platform requires all populations to be contained within one workspace and only will report match ratio on the one target population at a time.
  8. the fcs files are named exactly the same for runs 2-6 and just kept in different file folders.
  9. Match Ratio Calculation has been problematic due to the large number of events in each file.
  10. Too large for Excel,
  11. Match Ratio Calculation in FlowJo will only create a consensus from opened workspaces and compare each .wsp file to the consensus. Won't allow comparison of an intern to the consensus of experts.
  12. Population comparison platform is time consuming if you want to compare 6 target populations and 14 manual gaters in all possible combinations.
  13. One solution is the utility that Aaron Hart is writing
  14. Solution is a repository of datafiles and a utility to compare in many ways