Phenotyping EBV-Infected Cell Lines Using Flow Cytometry
JoVE Encyclopedia of Experiments
Microbiology
0 views • 3:14 min • June 30th, 2026
Take lymphoid cell lines established from Epstein–Barr virus (EBV)-infected patients.
These cells express oncogenic viral proteins that activate signaling pathways, promoting immortalization and a chronically activated state marked by HLA-DR expression, a molecule involved in antigen presentation.
Centrifuge the tubes and wash the cells with a buffer.
Add serum to block non-specific binding sites. Centrifuge the cells, and add the buffer.
Divide each suspension into tubes, then centrifuge.
To each tube, add a unique pair of fluorescently labeled antibodies, one tagged with a green fluorophore and the other with a red, each targeting specific surface markers.
Centrifuge the tubes, add the buffer to wash the cells, and resuspend them.
Use flow cytometry to detect fluorescence from the markers.
Both lines express HLA-DR, indicating EBV-driven immune activation, but differ in lineage-specific markers that confirm one as a T cell and the other as an NK cell line.
When the cells have expanded, collect one times ten to the sixth cells to determine the phenotypes of the cell lines. Centrifuge them at 240 times g for five minutes at room temperature to precipitate the NKNT cells.
After that, discard the supernatant, wash the precipitation by adding 7 milliliters of PBS. Centrifuge it for five minutes at 240 times g at room temperature. Repeat the procedure once more. Then, add 200 microliters of human serum to each tube, mix well, and incubate for 10 minutes at room temperature. Centrifuge the cells at 240 times g for five minutes at room temperature.
Discard the supernatant and resuspend the cells at one times ten to the sixth cells per milliliter with cold PBSA. Subsequently, divide the cells into five tubes, each containing two times ten to the fifth cells. After that, centrifuge the cells at 240 times g for five minutes at four degrees Celsius. Discard the supernatant and resuspend the cells with PBSA buffer or PBSA containing 10 microliters of PE and 10 microliters of FITC-labeled antibodies to stain cell receptors of T or NK cells on ice.
Cells suspended with PBSA buffer are used as a negative control. Next, incubate the cells with antibodies for 20 to 30 minutes on ice in the dark. Wash the cells twice with cold PBSA and resuspend the cells with 300 microliters of cold PBSA before the analysis with the flow cytometer.
Overview
This article presents a straightforward and efficient protocol for establishing and phenotyping NK and T cell lines from patients with chronic active Epstein-Barr virus (EBV) infection. The method utilizes flow cytometry to distinguish between T-cell and NK-cell populations based on lineage-specific surface markers, providing a reliable approach for characterizing EBV-infected lymphoid cell lines.
Key Study Components
Area of Science
- Immunology
- Cell Biology
- Virology
Background
- EBV infection can lead to the immortalization and chronic activation of lymphoid cells.
- These cells express oncogenic viral proteins and activation markers such as HLA-DR.
- Accurate identification of T and NK cell lineages is essential for studying EBV-associated diseases.
- Flow cytometry enables detailed phenotyping of immune cell populations using fluorescently labeled antibodies.
Purpose of Study
- To establish a simple and efficient method for generating NK and T cell lines from EBV-infected patients.
- To demonstrate a protocol for phenotyping these cell lines using flow cytometry.
- To confirm the identity of T and NK cell lines based on surface marker expression.
Methods Used
- Expansion of EBV-infected lymphoid cell lines in culture.
- Cell washing and blocking of non-specific binding with human serum.
- Staining with pairs of fluorescently labeled antibodies (PE and FITC) targeting lineage-specific surface markers.
- Use of negative controls with buffer only.
- Incubation on ice and in the dark to preserve fluorescence.
- Flow cytometric analysis to detect and quantify marker expression.
Main Results
- Both T and NK cell lines express HLA-DR, indicating EBV-driven immune activation.
- Distinct lineage-specific markers allow clear differentiation between T-cell and NK-cell populations.
- The protocol reliably confirms the identity of each cell line.
- Negative controls validate the specificity of antibody staining.
Conclusions
- This method provides a robust and reproducible approach for establishing and phenotyping EBV-infected NK and T cell lines.
- Flow cytometry with fluorescent antibodies is effective for distinguishing immune cell lineages.
- The protocol supports further research into EBV-associated lymphoproliferative disorders.
Frequently Asked Questions
Executive Industry Relevance
Reliable phenotyping of EBV-infected T and NK cell lines using flow cytometry enables precise target validation and mechanistic de-risking in immunology-focused discovery pipelines. Quantitative identification of lineage-specific markers supports predictive confidence in disease-relevant model systems and informs portfolio triage for EBV-associated research programs. This approach strengthens translational continuity from early discovery through preclinical evaluation of immune cell function.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables rigorous interrogation of immune cell lineage in EBV-driven disease models.
- Supports functional target validation by confirming T and NK cell identities via surface marker expression.
- Facilitates mechanistic de-risking by distinguishing chronic activation states through HLA-DR detection.
- Improves predictive confidence for downstream immune modulation studies.
Screening & Assay Development
- Prepares validated T and NK cell lines for standardized compound screening workflows.
- Delivers reproducible, quantitative marker profiles essential for assay development.
- Enables robust negative controls to ensure specificity and reliability of readouts.
- Supports scalable phenotyping for high-throughput immune cell analysis.
Translational & Preclinical Research
- Aligns phenotypic outputs with disease-relevant immune activation markers such as HLA-DR.
- Provides continuity from cell line establishment to preclinical immune function studies.
- Reduces biological ambiguity in translational models of EBV-associated disorders.
- Enables risk-adjusted advancement of immune-targeted therapeutic hypotheses.
Pipeline & Workflow Integration
This phenotyping protocol integrates at the interface of early discovery and preclinical research, supporting lead identification and mechanistic studies in EBV-related immune models.
- Discovery Biology: Confirms immune cell lineage and activation state, supporting hypothesis testing and pathway clarification.
- Screening: Provides standardized, quantitative marker data for assay readiness and reproducibility.
- Analytics: Delivers fluorescence-based measurements to compare lineage-specific marker expression across conditions.
- Translational Research: Aligns cell phenotypes with disease-relevant biomarkers for preclinical continuity.
- Enterprise Reuse: Establishes a reusable phenotyping workflow for diverse EBV-infected lymphoid cell lines.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in immune cell research.
- Operational Value: Standardizes phenotyping, ensuring reproducibility and scalability across studies.
- Strategic Value: Informs go/no-go decisions and enhances capital efficiency in immune-targeted portfolios.
- Portfolio Impact: Supports risk-adjusted prioritization of EBV-related discovery and preclinical programs.
Implementation Considerations
- Requires expertise in flow cytometry and immunophenotyping protocols.
- Needs access to fluorescent antibody panels and cytometric instrumentation.
- Demands rigorous cross-team standardization of staining and analysis procedures.
- Adaptation may be needed for other lymphoid or disease-relevant cell models.
- Dependent on validated negative controls to ensure specificity of marker detection.
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Last updated: 29 August 2026