Tricks for analyzing PBMC populations by flow cytometry

Flow cytometry allows assessment of protein expression on a single cell level.  Because of the diversity of populations comprising peripheral blood mononuclear cells (PBMC), flow cytometry represents the best method for studying the functional and phenotypic properties of these cell subsets.  There have been a number of publications that present multiparametric flow cytometry staining panels for assessing PBMC populations, and as an easy first step into these assays, these panels can be referenced (see a few examples below).

However, use of these established panels may not suit further exploratory questions, and thus an understanding of the best methods for designing flow cytometry panels is needed.  Because of the many identified populations and the upper limits of markers that can be simultaneously used in flow cytometry, a lot of thought must go into planning these assays.

Flow cytometry utilizes fluorophore-conjugated antibodies targeting antigens of interest.  Antigenic markers uniquely present on PBMC population subsets have been actively sought after by the immunology community. The upper limit of the number of markers that can be simultaneously assessed depends on several parameters.  Most obviously, this depends on the specs of the flow cytometer instrument available.  I presently use a modified version of the BD LSR Fortessa, with five lasers, and allowing detection of up to 17 parameters plus forward and side scatter.

Unfortunately, because of overlap in the excitation and emission spectrums of available fluorophores, this doesn’t mean that I am able to successfully co-analyze 17 PBMC markers.  The fluorescence emitted from a given fluorophore may be detected or “spill over” into the range of detectors optimized for other fluorophores.  Although flow cytometry software is capable of calculating the percent spillover from this spectral overlap and subtracting this estimated fluorescence from the affected channels by a process known as compensation, this is not a perfect science. Due to spectral overlap, there are a few points to consider when designing an antibody “staining panel” for your immunological assessments.

First, select the fluorophores you hope to use in your panel.  To do this, determine the laser and detector configurations of your cytometer.  This will tell you for which fluorophores the excitation and emission spectrums are optimal on your instrument.

Next, choose detection channels to try first based on minimal excitation and emissions overlap.  Alternatively, consult previously published panels to see which fluorophore combinations have been recommended.  As an example, for my instrument’s 561nm laser, there are 5 detectors, so if I had to choose 3 of these, it would simply be every-other one based on the detector’s spectral range.  However, fluorophores can overlap in not only their emission but also their excitation spectrums.  Thus, it is important to look across the detectors for different lasers.  For instance on my instrument, there is a 780/60BP detector on the 561nm laser for detection of PE-Cy7, and the same detector on the 640nm laser for detection of APC-Cy7.   Thus the use of these channels together may be complicated if the fluorophores have a wide excitation range.  BD Biosciences has an awesome fluorescence spectrum viewer for envisioning the spill-over between parameters based on your cytometer configurations.  Other companies such as Life Technologies, eBioscience, and Biolegend also have similar tools to reference for fluorophores not sold by BD Biosciences.

It is important to mention that fluorophores are improving all the time.  Newer chemistries have led to development of product lines such as the Brilliant Violet dye series and Q-Dots with highly improved excitation and emissions spectrums for minimal spill-over.  Thus, for each channel, there could be several fluorophores that fit the optimal excitation and emission properties but select the one with optimal qualities of not only brightness but also their excitation and emission spectrums.

Once you have selected a likely handful of combinable fluorophores, it is time to figure out which cellular markers to target with which fluorophores.  To do this, first determine which markers of interest in your staining panel are co-expressed.  If there is no co-expression of your selected markers, it becomes easier to utilize antibodies tagged with spectrally overlapping fluorophores.  For instance, Pacific Blue and V500 have an approximately 10-20% spillover into the other’s channel on my LSR Fortessa’s configurations.  However, when not co-expressed, for instance CD4 and CD8, the fluorescent spill-over and hence compensation issues between these fluorophores are minimized, i.e. if there is no expression of Pacific Blue, then there is nothing to subtract from the V500 channel and vice versa.  However, if markers are co-expressed, such as CD4 and CD45RA, then issues with compensation between these parameters may lead to over or under-subtraction of fluorescence values in CD4+CD45RA+ populations compared with single positive populations.  But if your objective is only to gate these populations for analysis of other markers or to determine population percentages, then markers such as these may be successfully utilized together if these populations are visually discernible on cytometry data plots.  Another key thing to mention is for the lower expressing antigens, choose the brightest fluorophores.

But we’re not finished yet.  Next, determine for which markers your objective is to gain information about fluorescence intensity.  Now take the example from above but imagine that your question involved the magnitude of CD45RA expression on the CD4 versus CD8 population of PBMC T cells.  I have not done this example directly, but I can imagine that having high levels of compensation between one but not another parameter (in this case between CD4 and CD45RA but not between CD8 and CD45RA), may lead to inaccuracies in the relative fluorescence intensities.   Thus, in this example, if CD45RA is the marker for which expression intensity is the question, then the overlapping spectral fluorophores Pacific Blue and V500 would be best suited for identifying CD4 and CD8, while a fluorophore with minimal compensation issues with these channels, such as PE, would be best for CD45RA.  Thus, for markers in which determining fluorescence intensity is your objective, choose fluorophores with the least spectral overlap with all of the others in your panel.

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Finally here’s another trick:  you can use two exclusively expressed markers in the same channel, as long as there is a third marker to differentiate these populations.  For example, I have very successfully used CD4-PerCP-Cy5.5 (CD4+ T cells) together with CD20-PerCP-Cy5.5 (B cells) along with CD3-V450 to differentiate the T cells from B cells in human PBMC.  In this case, CD4+ T cells will be double positive in V450 and PerCP-Cy5.5 channels, while CD20+ B cells will be PerCP-Cy5.5+ but V450, and CD8+ T cells will be PerCP-Cy5.5 and V450+.

In summary, multiparametric flow cytometry analysis of PBMCs can be tricky, but with these and other tricks up your sleeve it becomes much easier to successfully design panels optimal for the questions you are asking and to maximize the number of parameters in your flow cytometry staining panels.



Examples of established multiparametric flow cytometry panels:

Standardizing immunophenotyping for the Human Immunology Project.  Maecker HT, McCoy JP, Nussenblatt R.  Nat Rev Immunol. 2012 Feb 17;12(3):191-200.

Multiparameter flow cytometry monitoring of T cell responses.  Maecker HT.  Methods Mol Biol. 2009;485:375-91.

11-color, 13-parameter flow cytometry: identification of human naive T cells by phenotype, function, and T-cell receptor diversity.  De Rosa SC, Herzenberg LA, Herzenberg LA, Roederer M. Nat Med. 2001 Feb;7(2):245-8.

Nine-color flow cytometry for accurate measurement of T cell subsets and cytokine responses. Part I: Panel design by an empiric approach. McLaughlin BE, Baumgarth N, Bigos M, Roederer M, De Rosa SC, Altman JD, Nixon DF, Ottinger J, Oxford C, Evans TG, Asmuth DM. Cytometry A. 2008 May;73(5):400-10.


BD Bioscience’s Fluorescence Spectrum Viewer: