Fig 1.
Overall schematic for flow cytometry optimization and standardization across clinical study sites.
Schematic outlining the strategy used to improve the resolution of targeted populations of interest via flow cytometry.
Table 1.
Standardization actions taken and purpose for the identification and collection of cell populations in flow cytometry.
Fig 2.
Gating strategy used to differentiate immune cell populations based on cell surface markers.
A) Cell surface marker combinations used to identify CD4+ T cell subset populations. B) The final optimized flow panel for separation of cell populations across different sites noting which reagents were in the lyophilized antibody cocktail, added to the antibody cocktail, or stained separately. C) Fluorescence Minus One (FMO) design and addition of antibodies after reconstituting the FMO lyophilized cocktail. D) Gating strategy illustrating strategy for separation of cell populations. Note, in some plots, can’t see the gates because the blue color blends in with the populations; could consider changing the color of the gate for all plots.
Fig 3.
Testing of flow panels for optimal resolution of T cell subset identification due to variations in cytometer specifications between different study sites.
A) Differences in cytometer laser/filter set combinations by site for the finalized panel. Red text denotes lasers/filters that differ between sites. B) Two variations of the flow panel that were tested to optimize population separation based on differences between cytometers, noting which reagents were in the lyophilized antibody cocktail, added to the antibody cocktail, or stained separately. Red text indicates fluorochromes that differ between the two panels. C) Side by side comparison of T cell subset identification by panel 1 or 2.
Table 2.
MFI values for each detector channel.
Fig 4.
Comparison of human PBMC sample analysis between institutions after standardization.
PBMCs from different human subjects were isolated, stained, and run on the flow cytometer at each study site. Shown are cell populations after gating on singlets, live/dead, lymphocytes each by FSC/SSC, and CD3+ cells. T cell subsets identified by the analysis include T effector, Th17.1, Th17, Th1, and Treg.
Fig 5.
Cell number and RNA quantity obtained after cell sorting.
CD4+ T cell subsets were flow sorted from PBMCs at each site using the final flow panel shown in Fig 3. Sorted populations were lysed to preserve RNA and shipped to the central laboratory where total RNA was isolated. A) Number of cells sorted in each subset by each site from one sample. There was only one sample per test, thus no error bars are added. B) Total RNA mass obtained after extractions based on number of cells sorted per site per subset.