A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice
January 5th, 2021
Clonal expansion is a key feature of antigen-specific T cell response. However, the cell cycle of antigen-responding T cells has been poorly investigated, partly because of technical limitations. We describe a flow cytometric method to analyze clonally expanding antigen-specific CD8 T cells in spleen and lymph nodes of vaccinated mice.
Our protocol provides a practical approach by which mouse spleen and lymph nodes can be used to reflect the dynamic of T cell response greater than providing a steady-state phenotypic snapshot. Our technique sensitively detects antigen-specific CD8 T cells that are engaged in an ongoing the response. Proliferating CD8 T cells are measured without the possibly confounding effects of in vivo drug treatment or cell transfer.
Our technique can provide a window in immune dynamics in several settings. For example, in relation to response to vaccination and infections, autoimmune diseases, and cancer immunotherapy. Prepare fresh 1x permeabilization wash buffer by diluting 10x permeabilization buffer with distilled water and filter it through a 0.45 micrometer filter to eliminate aggregates.
Dilute monoclonal antibody Ki67 FITC in 1x permeabilization wash buffer as determined with a titration experiment for a final volume of 100 microliters per sample. Add 3 milliliters of the 1x permeabilization wash buffer to each tube with cells and centrifuge at 400 G for five minutes at room temperature. Discard the supernatant.
Again, add the 1x permeabilization wash buffer and centrifuge to pellet the cells. Then, discard the supernatant. Add 100 microliters of diluted monoclonal antibody Ki67 FITC to the pellet, then vortex and incubate for 30 minutes in the dark.
After the incubation, wash the cells twice with 4 milliliters of 1x permeabilization buffer, centrifuging after each wash, and discard the supernatant. Add 350 microliters of PBS to the cell pellet for samples to be acquired directly at the flow cytometer and 250 microliters of PBS to the cell pellet for samples to be incubated with Hoechst for DNA staining. Prepare Hoechst and PBS solution and add it to each sample so that the final concentration is two micrograms per milliliter.
Vortex and incubate the samples for 15 minutes in the dark. Then, centrifuge the samples for five minutes and add 350 microliters of PBS to the cell pellet. Open the software and create different groups corresponding to the different organs to be analyzed by clicking Create Group"in the workspace ribbon section.
Open the modified group window by double clicking on the group name and synchronize the newly created groups by inserting a check mark on the function synchronized. Drag each FCS file to its corresponding group, then create a gating strategy starting with a-LN group. Open the graph window by double-clicking on the fully stained sample to display the ungated events acquired for the sample in a dot plot.
Note that the x-and y-axis are labeled as in the FCS files, as indicated in table two of the flow cytometer settings file of this manuscript. Check that a sufficient number of events is displayed for appropriate visualization. If necessary, open preferences by clicking on the heart icon in the workspace ribbon, select Graphs, then Dot Plot"as graph type, and check that the number of dots drawn in the corresponding box is correct or change it.
Display the ungated events in the graph window in a dot plot with DNA-A on the x-axis and DNA-W on the y-axis. Use linear scale for both axes. If necessary change scale from logarithmic to linear by clicking on the box indicated with a T close to each axis in the graph window.
Select a single cell population by clicking on rectangle in the gating tool section then double-click in the center of the rectangular gate to display single cells in a dot plot with FSC-A parameter on the x-axis and dead cell die on the y-axis. Click on the polygon to select the live cell population, which are negative for dead cell die. Double-click in the center of the polygon gate to display the cells in a dot plot with the FSC-A parameter on the x-axis and the SSC-A parameter on the y-axis.
Click on rectangle and create a relaxed gate to include all single live cells in that graph. Double click in the center of the relaxed gate to display the cells in a dot plot with CD3 on the x-axis and CD8 on the y-axis. Use the appropriate access scale for visualization in the graph window.
If necessary, modify the x and y scale by clicking on the box, indicated with a T close to each axis, choose Customize Access Function, and modify extra neg decades with bases and positive decades as necessary. Select the CD3+CD8+cells by clicking on polygon. Double-click in the center of the CD3+CD8+gate to display the cells in a dot plot with Tetr-gag on the x-axis and Pent-gag on the y-axis.
Select the antigen specific CD8 T cells by clicking on polygon. Double click in the center of the gag-specific gate to display the cells in a dot plot with DNA-A on the x-axis and Ki67 on the y-axis. Select the cells in the different cell cycle phases by clicking on Quad"in the gating tool section of the graph window.
Copy the gating strategy created in one sample to the corresponding group to apply the gates to all the samples of the group. Then copy gating strategies for the b-spleen and CBM groups, as described in the text manuscript. Verify that all gates are appropriate for each sample of the three groups.
If necessary, desynchronize the group and modify gates as described in the manuscript. Display the BM cells of the relaxed gate in a dot plot with DNA-A on the x-axis and Ki67 on the y-axis. Visualize the results by clicking on Layout Editor"in the workspace ribbon section.
Drag each gate of the gating strategy in the sample pane to the layout editor and place the plots according to the sequence of the gating. If necessary, change the graph type by double clicking on the corresponding plot in the layout and selecting the appropriate type in the graph definition window. Click on the group and iterate by functions on the layout ribbon to visualize the results obtained in antigen-specific CD8 T cells from each organ and compare different samples.
Visualize results of bone marrow cells representing a positive control. A typical example of cell cycle analysis of bone marrow cells is shown here. The protocol yielded a low coefficient of variation of G0 to G1 and G2 to M DNA peaks, indicating excellent quality of the DNA staining.
A five step gating strategy was employed to identify antigen specific CD8 cells. Two multimers were used to improve the sensitivity of gag-specific CD8 T cell detection in vaccinated mice without increasing the staining background in untreated mice. Gag-specific CD8 T cells in the draining lymph nodes and in the spleen contain a high proportion of cells in the S-G2/M phases at day three post boost.
Furthermore, gag-specific CD8 T cells in the S-G2/M phases had high FSC-A and SSC-A when overlaid onto the total CD8 T cells from the same organ. Offset histograms showed that CD62L expression by gag-specific CD8 T cells was low, as expected for activated T cells, except for a few cells in G0 in the lymph nodes. This method is designed for T-cells to achieve an excellent quality of DNA staining together with the membrane and Ki67 staining.
Flow cytometry data analysis is a key point. Make sure to use appropriate control for gate positioning. Using this method, we discovered T-cells in S-G2/M phases of cell cycle in mouse and human peripheral blood.
This technique was useful in immuno-monitoring studies in type 1 diabetes, infectious mononucleosis, and COVID-19.
Overview
This study presents a flow cytometric method to analyze clonally expanding antigen-specific CD8 T cells in the spleen and lymph nodes of vaccinated mice. The technique allows for the detection of T cell responses without the confounding effects of in vivo drug treatment or cell transfer.
Key Study Components
Area of Science
- Immunology
- Flow Cytometry
- T Cell Biology
Background
- Clonal expansion is crucial for antigen-specific T cell responses.
- The cell cycle of responding T cells has been underexplored due to technical challenges.
- Understanding T cell dynamics is essential for insights into immune responses.
- This study addresses the need for a method to analyze T cell responses in real-time.
Purpose of Study
- To develop a method for analyzing antigen-specific CD8 T cells in vivo.
- To provide insights into T cell proliferation during immune responses.
- To facilitate the study of T cell dynamics in various immunological contexts.
Methods Used
- Preparation of fresh permeabilization wash buffer for cell staining.
- Use of monoclonal antibody Ki67 FITC to detect proliferating T cells.
- Flow cytometric analysis to assess T cell populations and their activation states.
- Gating strategies to isolate antigen-specific CD8 T cells from mixed populations.
Main Results
- The method successfully detects antigen-specific CD8 T cells engaged in active responses.
- Proliferation of CD8 T cells can be measured accurately without confounding variables.
- The technique reveals insights into T cell dynamics during vaccination and infection.
- Results demonstrate the utility of this method in studying autoimmune diseases and cancer immunotherapy.
Conclusions
- The developed flow cytometric method is effective for analyzing T cell responses.
- This approach enhances understanding of immune dynamics in various settings.
- Future studies can leverage this technique to explore T cell behavior in health and disease.
Frequently Asked Questions
Executive Industry Relevance
This method enables precise quantification of antigen-specific CD8 T cell proliferation in vivo, addressing a critical gap in immuno-monitoring for vaccine and immunotherapy development. By distinguishing G0, G1, and S-G2/M phases without reliance on nucleotide analogs or dye dilution, it provides a mechanistic snapshot of clonal expansion dynamics. This supports target validation and lead identification by linking antigen engagement to functional proliferative states in preclinical models.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Scientific Value: Enables interrogation of therapeutic hypotheses by correlating antigen specificity with cell cycle progression in responding T cells.
- Operational Value: Provides a reproducible flow cytometry readout for functional target validation independent of BrdU or CFSE limitations.
- Predictive Value: Supports mechanistic de-risking by quantifying the proportion of antigen-specific T cells committed to mitosis versus those in G1 or G0.
Screening & Assay Development
- Assay Readiness: Generates standardized, quantitative outputs (DNA-A vs Ki67) suitable for high-throughput screening of vaccine candidates or immunomodulators.
- Reproducibility: Uses Hoechst 33342 for high-resolution DNA peak discrimination, ensuring consistent G0/G1 and G2/M separation across samples.
- Scalability: Compatible with multi-organ analysis (spleen, lymph nodes, bone marrow) and adaptable to preclinical species for cross-study comparison.
Translational & Preclinical Research
- Disease Relevance: Applicable to vaccine efficacy studies, as demonstrated in HIV-gag vector-vaccinated mice showing S-G2/M enrichment in antigen-specific CD8 T cells.
- Translational Continuity: Bridges discovery and preclinical phases by providing a kinetically resolved measure of T cell expansion predictive of immune response magnitude.
- Risk-Adjusted Decisions: Enables go/no-go criteria based on proliferative kinetics of antigen-specific clones, reducing reliance on endpoint phenotypic markers alone.
Pipeline & Workflow Integration
The assay fits within the discovery-to-preclinical continuum, enabling early assessment of T cell proliferative capacity post-immunization and informing lead optimization through functional immune profiling.
- Discovery Biology: Supports hypothesis testing by linking antigen recognition (via MHC-multimer) to cell cycle status, clarifying whether engagement drives proliferation or anergy.
- Screening: Delivers assay-ready, quantitative cell cycle distribution data for comparing vaccine platforms or adjuvant effects on T cell expansion.
- Analytics: Generates multiparametric readouts (DNA content, Ki67, scatter, antigen specificity) enabling statistical comparison of proliferative indices across conditions.
- Translational Research: Connects to preclinical validation by identifying activated, cycling T cell subsets that correlate with protective immunity in infection and cancer models.
- Enterprise Reuse: Establishes a reusable immuno-monitoring platform for longitudinal studies in autoimmune, infectious disease, and immuno-oncology pipelines.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence in target validation by resolving proliferative heterogeneity within antigen-specific T cell populations.
- Operational Value: Delivers standardization through fixed gating strategy and Hoechst-based DNA staining, minimizing inter-assay variability.
- Strategic Value: Improves capital efficiency by enabling early de-risking of immunomodulatory candidates based on functional T cell kinetics.
- Portfolio Impact: Informs risk-adjusted advancement by quantifying the proliferative fraction of antigen-specific T cells as a biomarker of response quality.
Implementation Considerations
- Requires expertise in multicolor flow cytometry, including compensation controls for FITC-Ki67 and Hoechst signals.
- Necessitates access to a flow cytometer capable of UV excitation for Hoechst 33342 detection and appropriate filter sets.
- Demands standardized permeabilization and washing protocols to preserve epitope integrity for Ki67, multimer, and surface markers.
- Involves optimization of Hoechst concentration (2 µg/mL) and incubation time to avoid cytotoxicity while achieving optimal DNA peak resolution.
- Depends on proper gating hierarchy, starting with singlet and live-cell exclusion, to ensure accurate antigen-specific T cell identification.
