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Flow cytometry is a technique that was developed to analyze multiple parameters on single particles at a rate of several thousand of events per second1. Examples of specimens analyzed by flow cytometry include, but are not limited to, cells, beads, bacteria, vesicles and chromosomes. A fluidic system directs particles at the interrogation point where each particle intersects its path with one or more lasers, and multiple parameters are recorded for further analysis. Forward and side scatters, generated by scattering of the pure laser light, are used to identify the target population and retrieve information about the relative size and internal complexity/granularity of particles, respectively. All the other parameters, that account for most of data in a flow cytometric analysis, are derived by fluorochrome-labeled probes that recognize and bind to specific targets on the particles of interest.
Flow cytometry is a primary tool for immunological studies to identify and characterize cell populations. To dissect the complexity of the immune system, multicolor panels are constantly evolving to expand the number of markers simultaneously recorded for deep immunophenotyping of cell populations1. This is leading to the development of more capable instruments and fluorochromes, with recent high-end flow cytometers exceeding 20 fluorescent parameters. This results in complex study design due to fluorochrome spectral overlap and in higher costs associated with custom antibody labelling and skilled operators. In several instances, complexity and costs are reduced by using separate panels of markers for different cell populations. This approach, however, is error prone, reduces the information in each panel, and can be difficult to apply to samples with limited number of cells. Moreover, increasing the number of markers precludes deep immunophenotyping on instruments with fewer fluorescent parameters. We previously developed a staining protocol to identify major human immune populations (CD4+ and CD8+ T cells, γδ T cells, B cells, NK cells and monocytes) in peripheral blood mononuclear cells (PBMCs) by combining seven lineage markers using only two fluorochromes instead of the seven required using the traditional "one fluorochrome-one marker" approach (www.hcdm.org)2,3. Our initial report explored and validated the notion of combining seven markers in two fluorochromes for deep immunophenotyping. In this report, we present a step-by step protocol to isolate and stain peripheral blood cells, focusing on the practical aspect and troubleshooting steps to achieve a successful staining.
This protocol is based on the observation that lineage markers have a constant expression on the cell surface and that each cell population has an exclusive combination of lineage markers. In PBMCs, CD3 expression subdivides immune cells into two main categories: CD3-positive T lymphocytes and CD3-negative cells. Within the CD3 positive subgroup, CD4+, CD8+ and γδ T cells can be separated using antibodies that solely target CD4, CD8 and the γδ receptor. In a comparable way, within the CD3 negative subgroup, B cells, NK cells and monocytes can be uniquely identified using antibodies against CD19, CD56 and CD14, respectively. In a standard one fluorochrome-one marker approach, anti-CD3, -CD4, -CD8, -CD14, -CD19, -CD56 and -TCR γδ antibodies are detected with seven different fluorochromes. Our approach combines anti-CD3, -CD56, and -TCR γδ antibodies in one fluorochrome (labeled for convenience fluorochrome A) and anti-CD4, -CD8, -CD14 and -CD19 antibodies in a different fluorochrome (fluorochrome B). This is possible by a combination of antibody titration and differential antigen expression. Both CD4+ and CD8+ T cells are positive for the anti-CD3 antibody in fluorochrome A, but they can be separated in fluorochrome B maximizing the expression of the CD8 signal while placing, with an ad hoc titration, the CD4 signal in between the CD8 and the CD3 positive-CD4/CD8 double negative cells. γδ T cells expresses higher level of CD3 than CD4 and CD8, and therefore they can be identified as CD3 high4. This signal is further boosted by labeling γδ T cells in fluorochrome A with an anti-TCR γδ antibodies, thus improving separation between CD3 low T cells and CD3 high γδ T cells. B cells can be identified as CD3- in fluorochrome A and CD19+ in fluorochrome B. To separate CD3 negative NK cells from B cells, an anti-CD56 antibody was used in fluorochrome A as the anti-CD3. This is possible because CD56 expressed on NK cell at a much lower level than CD3 on T cells5. Finally, monocytes can be identified via a combination of forward-side scatter properties and expression of CD14 in fluorochrome B.
The idea of combining up to four markers using two fluorochromes has been already successfully attempted before6,7,8, and has been used in a clinical protocol to identify malignant lymphocytic populations9. A previous report also combined seven markers (with different specificity from the markers than we used in our protocol) using two fluorochromes, but this approach relied on a complex labelling of each antibody with varying amount of fluorochrome10. This is in contrast to our method which uses commercially available antibodies and can be adapted to the instrument configuration and can take advantage of the new generation of polymer fluorochromes.
The overall goal of this methodology is to expand the optical limits of most flow cytometers allowing for the recording of five additional markers to interrogate complex cell populations. As a consequence, advanced immunological analysis can be performed on affordable 6-10 fluorochrome flow cytometers, and 2-3 fluorochrome field instruments can achieve remarkable results in areas with limited resources. High-end instruments can also benefit from this approach by using extra fluorochromes to accomplish deeper flow cytometry analysis and to create modular flow cytometric panels targeting several lineages at the same time11. This can potentially reduce the number of panels used in modular immunophenotyping flow cytometry and reduce costs, errors and handling time. This approach is also very well suited in the case of clinical samples with limited number of cells.