Characterize Immune Cell Identity and Purity

eBioscience Essential Phenotyping antibody panels and PureQuant qPCR-based assays

(See a list of the products featured in this article.)

One of the many challenges in immunology, cell therapy, and related fields is the accurate estimation of T cell identity and purity within heterogeneous immune cell populations due to the diverse cell types, rare subsets, source material variability, and lack of available validated techniques [1]. Currently, the primary means of characterizing heterogeneous cell populations is by flow cytometry [2]. Although there are commonly used antibody markers for immunophenotyping, few validated panels are commercially available. Other technologies used to assess immune cell populations include next-generation sequencing, ELISAs, qPCR assays, and array-based assays, but these methods are typically low-throughput, time-consuming, and costly.

Invitrogen eBioscience Essential Phenotyping Kits and Applied Biosystems PureQuant Assays provide two different but complementary methods for characterizing immune cells. Each method allows researchers to characterize cytotoxic T (CD8⁺) cells, regulatory T (Treg) cells, and T helper 17 (Th17) cells. The eBioscience Essential Phenotyping Kits are antibody panels that enable the identification of a large number of markers and cell types using flow cytometry. The PureQuant Assays are qPCR-based methylation assays that are rapid and potentially more accurate than antibody panels, depending on the workflow. Throughout the development of these methods, we compared their performance on the same cell populations, allowing us to see the benefits and drawbacks of each assay. In each case, these methods were designed to provide a flexible and efficient system for determining the identity and purity of immune cell subtypes.

eBioscience Essential Phenotyping antibody panels

Despite the fact that flow cytometry is a highly utilized characterization tool, many antibody panels lack validation and standardized analysis strategies. The eBioscience Essential Human T Cell, Treg, and Th1/Th17 Phenotyping Kits were designed for easy and consistent identity testing of T cells using flow cytometry instruments with a standard three-laser configuration. They include high-quality Invitrogen eBioscience antibodies and optional isotype controls, as well as a ready-to-use protocol for experimental setup, gating strategy, and analysis.

The three panels detect and quantify both cell-surface and intracellular markers for T cells, Treg cells, and Th1/Th17 populations. After analysis using the appropriate gating strategy (Figure 1), each panel determines the percentage of multiple cell types within the population. The eBioscience Essential Human T cell panel includes antibodies that identify pan T cells (CD3⁺), helper T cells (CD4⁺), cytotoxic T cells (CD8⁺), and both naive T cells (CD8⁺ CD62L⁺ CCR7⁺) and effector T cells (CD8⁺ CD62L^– CCR7^–). The eBioscience Essential Human Treg panel identifies Treg cells (CD4⁺ CD25⁺ CD127^– FOXP3⁺). The eBioscience Essential Human Th1/Th17 panel identifies both Th1 cells (CD4⁺ IFN-γ⁺) and Th17 cells (CD4⁺ IL-17A⁺). These cell types play critical roles in the immune system. Effector cells will quickly kill tumor cells and die, while naive T cells will persist significantly longer. In contrast, Treg cells are important for peripheral immune tolerance and quell hyperactive inflammatory responses. Inflammatory immune cells such as Th17 cells are responsible for recruiting neutrophils and macrophages to protect against extracellular bacterial infection; however, Th17 cells also play a major role in autoimmune disorders. Ultimately, these panels provide a validated turnkey method for researchers to identify and monitor T cell subtypes.

PureQuant methylation assays

The PureQuant CD8⁺ T Cell, Treg, and Th17 Assays provide another highly standardized method for determining T cell subtypes that offers flexibility with regard to both workflow and source material (fresh or frozen cells, or isolated genomic DNA). These assays utilize cell type–specific genomic DNA methylation patterns to identify and quantify specific immune cell subtypes in a heterogeneous cell population using a qPCR-based method. In this assay (Figure 2), ammonium bisulfite converts unmethylated cytosine to uracil indiscriminately throughout the entire genome. Primer pairs are specifically designed to anneal within target genes and the newly converted uracil bases. A sequence with methylated cytosine will not bind these primers and consequently will not be amplified during the qPCR reaction. All necessary controls such as calibrator (to correct for variation in bisulfite conversion efficiency), reference (to check assay performance), and standards are provided to create standard curves to derive copy number, which is normalized to total copy number (GAPDH) to determine the percentage of the cell type of interest.

Side-by-side comparisons

In order to evaluate these two methods, we tested three different donor samples using the eBioscience Essential Human T Cell Phenotyping Kit and the PureQuant CD8⁺ T Cell Assay. When compared side by side, the two methods yielded consistent results for the measurement of the CD8⁺ population (Figure 3). For this characterization of donor samples, the antibody panel workflow required less time because all antibody targets are surface-bound receptors and therefore the cells do not require fixation or multiple rounds of staining.

Next, we characterized three different samples of purified Treg cells using both the eBioscience Essential Human Treg Phenotyping Kit and the PureQuant Treg Assay (Figure 4). Purified Treg cells were used because these cells are in very low abundance, even within pan T cell populations. Once again, results were very consistent between methods. Because the eBioscience Essential Phenotyping antibody panels stain for the intracellular marker FOXP3, which requires cell fixation and permeabilization, the length of each workflow was comparable.

Lastly, we compared the eBioscience Essential Human Th1/Th17 Phenotyping Kit and the PureQuant Th17 Assay. To identify Th17 cells in a T cell population using an IL-17A antibody and flow cytometry, cells first need to be stimulated with PMA and ionomycin to increase the normally low expression of IL-17A, the marker used to identify Th17 cells. Additionally, a protein transport inhibitor is required to prevent secretion of IL-17A by Th17 cells. As a control, cells were treated with the protein transport inhibitor but not with PMA and ionomycin. The qPCR-based methylation assay does not require this stimulation step, but for this comparison, the control and stimulated T cells were used with both the phenotyping panel (see gating strategy in Figures 1C and 1D) and the qPCR-based methylation assay. As seen in Figure 5, results based on methylation signatures are much higher and closer to the expected result than those achieved with the antibody panel. It is possible that the artificial stimulation needed for the antibody-based flow cytometry assay is not an optimally effective method for detecting transient analytes, at least when compared with detection of genomic methylation signatures. In addition to the extended time needed for the stimulation workflow, the eBioscience Essential Phenotyping antibody panels require live cells for the flow cytometry analysis, whereas the PureQuant assays can be used with fresh or frozen cells or with isolated genomic DNA.

Learn more about immune cell characterization

The eBioscience Essential Phenotyping Kits and the PureQuant Assays provide orthogonal methods to measure the identity and purity of heterogeneous immune cell populations. Whereas the phenotyping panels allow quantitation of more cell types and provide a faster workflow for surface-marker identification, the qPCR-based methylation assays offer an improvement in the workflow and accuracy with regard to Th17 identification. Both methods have significant benefits and, when used together, provide a robust means for determining the identity and purity of mixed immune cell populations.

References

1. Carmen J, Burger SR, McCaman M et al. (2012) Regen Med 7:85–100. 
2. Rayment EA, Williams DJ (2010) Stem Cells 28:996–1004.