We describe a method combining immunomagnetic beads and fluorescence-activated cell sorting to isolate and analyze defined immune cell subpopulations of peripheral blood mononuclear cells (monocytes, CD4+ T cells, CD8+ T cells, B cells, and natural killer cells). Using this method, magnetic and fluorescently labeled cells can be purified and analyzed.
Infectious mononucleosis (IM) is an acute syndrome mostly associated with primary Epstein–Barr virus (EBV) infection. The main clinical symptoms include irregular fever, lymphadenopathy, and significantly increased lymphocytes in peripheral blood. The pathogenic mechanism of IM is still unclear; there is no effective treatment method for it, with mainly symptomatic therapies being available. The main question in EBV immunobiology is why only a small subset of infected individuals shows severe clinical symptoms and even develop EBV-associated malignancies, whilemost individuals are asymptomatic for life with the virus.
B cells are first involved in IM because EBV receptors are presented on their surface. Natural killer (NK) cells are cytotoxic innate lymphocytes that are important for killing EBV-infected cells. The proportion of CD4+ T cells decreases while that of CD8+ T cells expands dramatically during acute EBV infection, and the persistence of CD8+ T cells is important for lifelong control of IM. Those immune cells play important roles in IM, and their functions need to be identified separately. For this purpose, monocytes are separated first from peripheral blood mononuclear cells (PBMCs) of IM individuals using CD14 microbeads, a column, and a magnetic separator.
The remaining PBMCs are stained with peridinin-chlorophyll-protein (PerCP)/Cyanine 5.5 anti-CD3, allophycocyanin (APC)/Cyanine 7 anti-CD4, phycoerythrin (PE) anti-CD8, fluorescein isothiocyanate (FITC) anti-CD19, APC anti-CD56, and APC anti-CD16 antibodies to sort CD4+ T cells, CD8+ T cells, B cells, and NK cells using a flow cytometer. Furthermore, transcriptome sequencing of five subpopulations was performed to explore their functions and pathogenic mechanisms in IM.
Epstein–Barr virus (EBV), a γ-herpesvirus also known as human herpes virus type 4, is ubiquitous in the human population and establishes lifelong latent infection in more than 90% of the adult population1. Most EBV primary infection occurs during childhood and adolescence, with a fraction of patients manifesting with infectious mononucleosis (IM)2, showing characteristic immunopathology, including an activated immune response with CD8+ T cells in blood and a transient proliferation of EBV-infected B cells in the oropharynx3. The course of IM may last for 2–6 weeks and the majority of the patients recover well4. However, some individuals develop persistent or recurrent IM-like symptoms with high morbidity and mortality, which is classified as chronic active EBV infection (CAEBV)5. In addition, EBV is an important oncogenic virus, which is closely related to a variety of malignancies, including epithelioid and lymphoid malignancies such asnasopharyngeal carcinoma, Burkitt's lymphoma, Hodgkin's lymphoma (HL), and T/NK cell lymphoma6. Although EBV has been studied for over 50 years, its pathogenesis and the mechanism by which it induces the proliferation of lymphocytes have not been fully elucidated.
Several studies have investigated the molecular signatures for the immunopathology of EBV infection by transcriptome sequencing. Zhong et al. analyzed whole-transcriptome profiling of peripheral blood mononuclear cells (PBMCs) from Chinese children with IM or CAEBV to find that CD8+ T cell expansion was predominantly found in the IM group7, suggesting that CD8+ T cells may play a major role in IM. Similarly, another study found lower proportions of EBV-specific cytotoxic T and CD19+ B cells and higher percentages of CD8+ T cells in patients with IM caused by primary EBV infection than in patients with IM caused both by EBV reactivation and other agents8. B cells are first involved in IM because EBV receptors are presented on their surface. Al Tabaa et al. found that B cells were polyclonally activated and differentiated intoplasmablasts (CD19+, CD27+ and CD20−, and CD138− cells) and plasma cells (CD19+, CD27+ and CD20−, and CD138+) during IM9. Moreover, Zhong et al. found that monocyte markers CD14 and CD64 were upregulated in CAEBV, suggesting that monocytes may play an important role in the cellular immune response of CAEBV through antibody-dependent cellular cytotoxicity (ADCC) and hyperactive phagocytosis7. Alka et al. characterized the transcriptome of MACS sorted CD56dim CD16+ NK cells from four patients of IM or HL and found that NK cells from both IM and HL had downregulated innate immunity and chemokine signaling genes, which could be responsible for the hyporesponsiveness of NK cells10. In addition, Greenough et al. analyzed gene expression of sorted CD8+ T cells from 10 PBMCs of individuals with IM. They reported that a large proportion of CD8+ T cells in IM were virus-specific, activated, dividing, and primed to exert effector activities11. Both T cell-mediated, EBV-specific responses, and NK cell-mediated, nonspecific responses play essential roles during primary EBV infection. However, these studies only investigated the transcriptome results of the diverse mixture of immune cells or only a certain subpopulation of lymphocytes, which is not sufficient for the comprehensive comparison of the molecular characteristics and functions of different immune cell subpopulations in children with IM at the same disease state.
This paper describes a method that combines immunomagnetic beads and fluorescence-activated cell sorting (FACS) to isolate and analyze defined immune cell subpopulations of PBMCs (monocytes, CD4+ T cells, CD8+ T cells, B cells, and NK cells). Using this method, magnetic and fluorescently labeled cells can be purified using a magnetic separator and FACS or analyzed by flow cytometry. RNA can be extracted from the purified cells for transcriptome sequencing. This method will enable the characterization and gene expression of different immune cells in the same states of disease of individuals with IM, which will expand our understanding of the immunopathology of EBV infection.
Blood samples were obtained from patients with IM (n = 3), healthy EBV carriers (n = 3), and EBV-uninfected children (n = 3). Volunteers were recruited from Beijing Children's Hospital, Capital Medical University, and all studies were ethically approved. Ethical approval was obtained by the Ethics Committee of Beijing Children's Hospital, Capital Medical University (Approval Number: [2021]-E-056-Y). Informed consent of patients was waived as the study only used the remaining samples for clinical testing. All data were fully deidentified and anonymized to protect patient privacy.
1. Isolation of PBMCs from peripheral blood
2. Isolation of CD14 + monocytes from PBMCs using CD14 microbeads
3. Separation of lymphocyte populations from PBMCs by fluorescently labeled antibody staining and FACS
4. Flow cytometry parameter setting
5. Cell sorting and collecting data via flow cytometry
Reference of the gating strategy
The gating strategy used to sort the four lymphocyte subpopulations is shown in Figure 1. Briefly, lymphocytes are selected (P1) on a dot plot showing the granulosity (SSC-A) versus size (FSC-A). Then, single cells are selected (P2) on a dot plot showing the size (FSC-A) versus forward scatter (FSC-H), while doublet cells are excluded. CD3+ T cells (P3) and CD19+ B cells (Figure 1B) are selected separately on a dot plot showing the CD3 PerCP-Cy5.5-A versus CD19 FITC-A. CD8+ T cells and CD4+ T cells are selected separately on a dot plot showing CD8 PE-A versus CD4 APC-Cy7-A from P3. CD16+/CD56+ NK cells are selected on a dot plot showing CD56/CD16 APC-A versus SSC-A from P4 (Figure 1C).
The representative results of four cell subpopulations sorted from the samples of patients with IM by the described method are shown in Figure 2A. We also performed cell sorting on samples from healthy EBV carriers and EBV-uninfected children as control groups to confirm the feasibility of this experiment. The representative results of cell subpopulations separated from a healthy EBV carrier's sample are shown in Figure 2B. The representative result of cell subpopulations sorted from the sample of EBV-uninfected children is shown in Figure 2C. As shown in Figure 2, P1 was gated to identify lymphocytes and doublet cells were excluded through P2; P3 was gated to select CD3+ T cells and P5 was gated to select CD19+ B cells; CD3+ CD8+ T cells (P6) and CD3+ CD4+ T cells (P7) were selected separately from P3; CD16+/CD56+ NK cells (P8) were selected from P4. Each of these subpopulations can be individually sorted and collected for downstream experiments. This system was used to analyze gene expression through RNA extraction and transcriptome sequencing.
As reported in Table 3, an increase in CD3+ CD8+ T cells was observed in patients with IM compared to both healthy EBV carriers and EBV-uninfected children (46.5 ± 4.0 vs. 27.0 ± 0.1 and 46.5 ± 4.0 vs. 24.7 ± 2.9, % CD3+ CD8+ T cells per total lymphocytes); Decreased proportions of CD3+ CD4+ T cells and CD19+ B cells were observed in patients with IM compared with healthy EBV carriers and EBV-uninfected children (13.4 ± 1.5 vs. 19.3 ± 1.5 and 13.4 ± 1.5 vs. 23.6 ± 3.2, % CD3+ CD4+ T cells per total lymphocytes; 1.4 ± 0.3 vs. 7.6 ± 0.7 and 1.4 ± 0.3 vs. 9.0 ± 1.5, % CD19+ B cells per total lymphocytes). Decreased proportions of CD16+/CD56+ NK cells were observed in patients with IM compared with EBV-uninfected children (7.5 ± 0.5 vs. 10.7 ± 0.4, % CD16+/CD56+ NK cells per total lymphocytes). These results validated the effectiveness of this sorting protocol and demonstrated that the proportions of lymphocyte subsets are different in patients with IM and EBV-uninfected children.
Figure 1: Overall gating strategy used to sort immune cell subpopulations from PBMCs. (A) The PerCP-Cy5.5 filter was used to separate CD3+ T cells. CD8+ T cells and CD4+ T cells were selected separately on a dot plot showing CD8 PE-A versus CD4 APC-Cy7-A from P3. (B) The FITC filter was used to identify CD19+ B cells. (C) The APC filter was used to separate CD16+/CD56+ NK cells from P4. Abbreviations: PBMCs= peripheral blood mononuclear cells; FSC-A = forward scattering-area; SSC-A = side scattering-area; FSC-H = forward scattering-height; PerCP = peridinin-chrorophyll-protein; PE = phycoerythrin; APC = allophycocyanin; FITC = fluorescein isothiocyanate. Please click here to view a larger version of this figure.
Figure 2: Representative results of four cell subpopulations successfully isolated by the described method. (A) Representative cell sorting figures from the peripheral blood sample of patient with IM. (B) Representative cell sorting figures from the peripheral blood sample of healthy EBV carrier. (C) Representative cell sorting figures from the peripheral blood sample of EBV-uninfected children. P1, dot plot gate to identify lymphocytes; P2, dot plot gate to select single cells; P3, dot plot gate to select CD3+ T cells; P4, dot plot gate to identify CD3– CD19– lymphocytes; P5, dot plot gate to select CD19+ B cells; P6, dot plot gate to select CD3+ CD8+ T cells from P3; P7, dot plot gate to select CD3+ CD4+ T cells from P3; P8, dot plot gate to select CD16+/CD56+ NK cells from P4. Abbreviations: EBV = Epstein–Barr virus; IM = infectious mononucleosis; FSC-A = forward scattering-area; SSC-A = side scattering-area; FSC-H = forward scattering-height; PerCP = peridinin-chrorophyll-protein; PE = phycoerythrin; APC = allophycocyanin; FITC = fluorescein isothiocyanate. Please click here to view a larger version of this figure.
Antibody Target | Conjugated Fluorophore | Dosage | Clone | Isotype |
CD3 | PerCP/Cyanine5.5 | 2 µL | SK7 | Mouse IgG1, κ |
CD4 | APC/Cyanine7 | 2 µL | SK3 | Mouse IgG1, κ |
CD8 | PE | 2 µL | SK1 | Mouse IgG1, κ |
CD19 | FITC | 2 µL | HIB19 | Mouse IgG1, κ |
CD56 | APC | 2 µL | 5.1H11 | Mouse IgG1, κ |
CD16 | APC | 2 µL | 3G8 | Mouse IgG1, κ |
Table 1: Antibodies used for flow cytometry. Abbreviations: PerCP = peridinin-chrorophyll-protein; PE = phycoerythrin; APC = allophycocyanin; FITC = fluorescein isothiocyanate.
Compensation reference of flow cytometry (%) | |||||
PE | APC | APC-Cy7 | FITC | PerCP-Cy5.5 | |
PE | 100 | 0 | 0 | 0.8 | 4.1 |
APC | 0 | 100 | 30.1 | 0 | 0.9 |
APC-Cy7 | 0 | 1.8 | 100 | 0 | 0 |
FITC | 0 | 0 | 0 | 100 | 0 |
PerCP-Cy5.5 | 0 | 1.8 | 10 | 0 | 100 |
Table 2: Compensation reference of flow cytometry. Abbreviations: PerCP = peridinin-chrorophyll-protein; PE = phycoerythrin; APC = allophycocyanin; FITC = fluorescein isothiocyanate.
Proportion of lymphocytes of different subpopulations in total sorted lymphocytes (%) | |||
lymphocytes subpopulation | IM | healthy EBV carriers | EBV-uninfected children |
CD3+ T cells | 80.5 ± 1.8 | 70.2 ± 2.3 | 66.1 ± 2.1 |
CD3+ CD8+ T cells | 46.5 ± 4.0 | 27.0 ± 0.1 | 24.7 ± 2.9 |
CD3+ CD4+ T cells | 13.4 ± 1.5 | 19.3 ± 1.5 | 23.6 ± 3.2 |
CD16+/CD56+ NK cells | 7.5 ± 0.5 | 2.2 ± 0.1 | 10.7 ± 0.4 |
CD3– CD19+ B cells | 1.4 ± 0.3 | 7.6 ± 0.7 | 9.0 ± 1.5 |
Table 3: The proportion of sorted lymphocytes of different groups. Abbreviations: EBV = Epstein–Barr virus; IM = infectious mononucleosis; NK = natural killer.
This protocol represents an efficient way to sort peripheral blood immune cell subpopulations. In this study, venous blood samples from patients with IM, healthy EBV carriers, and EBV-uninfected children were selected as the research objective. This work using the peripheral blood of patients of IM mainly focuses on analyzing and determining the proportions of different cell subsets through multi-color flow cytometry. Transcriptome sequencing is mainly used for the detection and analysis of a certain subpopulation of lymphocytes that was insufficient for the comprehensive and specific comparisons of the molecular characteristics and functions of different immune cell subpopulations in children with IM at the same disease state. Therefore, sorting out several types of cells from the peripheral blood and performing transcriptome sequencing to compare the differences in the expression genes and functions of these immune cells could provide significant data for the study of the pathogenesis of IM.
FACS sorting has the additional benefit of being able to process live, fractionated cells for further in vitro or in vivo experiments14. Maintaining the cell viability is vital for subsequent experiments. We have optimized the sorting step to improve cell viability in this protocol-experimental manipulations have been performed on ice or in a 4 °C refrigerator. Proper centrifugation speed and time are also critical for cell isolation. The yield of sorted cells is also the main constraint in this method, and the use of FBS-coated tubes during sorting can greatly reduce the loss of cells that adhere to the tubes. Providing the proper settings for the FACS sorter can improve the overall efficiency of the sorting by avoiding cell blockage or cross-contamination in the collection tube. Through the optimization of experimental steps and settings, this protocol can be extrapolated to the sorting of other immune cells by replacing magnetic or fluorescent labels. However, due to the specificity of the children's samples (low blood collection volume), we only investigated the major populations of immune cells (monocytes, CD4+ T cells, CD8+ T cells, B cells, and NK cells) without proceeding to sort subpopulations due to the restriction of the flow sorting channel. This study demonstrated that peripheral blood samples from immunocompetent children and samples from IM could successfully sort out these five groups of immune cells; however, the blood samples of patients with hematological malignancies (e.g., leukemia, lymphoma), lymphoproliferative disorders (e.g., posttransplant lymphoproliferative disorders, CAEBV), or primary immunodeficiency/acquired immune deficiency syndrome may not be successfully sorted according to this protocol.
IM is considered a self-limiting disease, and immune cells such as γδ T cells, NKT cells, and NK cells play a significant role in the antiviral immune response15. EBV-specific CD8+ T cells are largely differentiated toward an effector phenotype10,16, and there is contraction of late effector memory and effector cells from IM to convalescence17. Meanwhile, NK cells in IM appear to be functionally defective, including lack of cell activation10, loss of activating receptor signaling, and degranulation18. Some studies have found that CD4+ T cells can not only assist CD8+ T cells to kill and eliminate EBV-infected B cells but also inhibit the proliferation of B cells by secreting cytokines and even directly play a killing role during EBV infection19,20. As shown in this study, an increased proportion of CD3+ CD8+ T cells was observed in patients with IM compared to both healthy EBV carriers and EBV-uninfected children. In contrast, decreased proportions of CD3+ CD4+ T cells, CD19+ B cells, and CD16+/CD56+ NK cells were observed in patients with IM compared with EBV-uninfected children. However, the function and gene expression of these different subtypes of immune cells in the same disease state of IM remain unclear. Further analysis of the gene expression profiles of specific immune cell subsets in IM can help to gain insight into the pathogenic mechanism of IM.
We provide a strategy that combines immunomagnetic bead sorting and FACS to isolate and analyze defined immune cell subpopulations in PBMCs. Monocytes are separated first using CD14 microbeads, and the remaining PBMCs are stained with corresponding fluorescently labeled antibodies to sort CD4+ T cells, CD8+ T cells, B cells, and NK cells through FACS. We further used these sorted cells for RNA extraction and transcriptome sequencing to characterize the function and gene expression of different immune cells in the immunopathology of IM. The purity and yield of the sorted cells was generally sufficient to conduct gene expression studies (data not shown). Therefore, the sorting method of separate immune cell subpopulations can be used to further explore EBV-associated lymphoproliferative disorders such as CAEBV, post-transplant lymphoproliferative disorder to detect pathogenic genes, pathogenic proteins, and potential therapeutic targets.
The authors have nothing to disclose.
This work was supported by the National Natural Science Foundation of China (82002130), Beijing Natural Science Foundation (7222059) and the CAMS Innovation Fund for Medical Sciences (2019-I2M-5-026).
APC anti-human CD16 | Biolegend | 302012 | Fluorescent antibody |
APC anti-human CD56 (NCAM) | Biolegend | 362504 | Fluorescent antibody |
APC/Cyanine7 anti-human CD4 | Biolegend | 344616 | Fluorescent antibody |
Automated cell counter | BIO RAD | TC20 | Cell count |
BD FACSAria fluorescence-activated flow cell sorter-cytometer (BD FACSAria II) | Becton, Dickinson and Company | 644832 | Cell sort |
CD14 MicroBeads, human | Miltenyi Biotec | 130-050-201 | microbeads |
Cell ctng slides | BIO RAD | 1450016 | Cell count |
Centrifuge tubes | Falcon | 35209715 | 15 mL centrifuge tube |
EDTA (≥99%, BioPremium) | Beyotime | ST1303 | EDTA |
Ethylene diamine tetra acetic acid (EDTA) anticoagulant tubes | Becton, Dickinson and Company | 367862 | EDTA anticoagulant tubes |
FITC anti-human CD19 | Biolegend | 302206 | Fluorescent antibody |
Gibco Fetal Bovine Serum | Thermo Fisher Scientific | 16000-044 | Fetal Bovine Serum |
High-speed centrifuge | Sigma | 3K15 | Cell centrifugation for 15 mL centrifuge tube |
High-speed centrifuge | Eppendorf | 5424R | Cell centrifugation for 1.5 mL Eppendorf (EP) tube |
Human lymphocyte separation medium | Dakewe | DKW-KLSH-0100 | Ficoll-Paque |
LS Separation columns | Miltenyi Biotec | 130-042-401 | Separation columns |
Microcentrifuge tubes | Axygen | MCT-150-C | 1.5 mL microcentrifuge tube |
MidiMACS Separator | Miltenyi Biotec | 130-042-302 | Magnetic bead separator |
PE anti-human CD8 | Biolegend | 344706 | Fluorescent antibody |
PerCP/Cyanine5.5 anti-human CD3 | Biolegend | 344808 | Fluorescent antibody |
Phosphate Buffered Saline (PBS) | BI | 02-024-1ACS | PBS |
Polystyrene round bottom tubes | Falcon | 352235 | 5 mL tube for FACS flow cytometer |
TRIzol reagent | Ambion | 15596024 | Lyse cells for RNA extraction |
Trypan Blue Staining Cell Viability Assay Kit | Beyotime | C0011 | Trypan Blue Staining |