Related Experiment Video
Updated: May 19, 2026
Quantification of Proliferating Human Antigen-specific CD4+ T Cells using Carboxyfluorescein Succinimidyl Ester
Published on: June 4, 2019
Estimating point and interval frequency of antigen-specific CD4+ T cells based on short in vitro expansion and
Giulia Di Lullo1, Francesca Ieva, Renato Longhi
1Tumor Immunology Unit, San Raffaele Scientific Institute, Milan, Italy.
Insights
A new method quantifies antigen-specific CD4(+) T cell frequencies using simple in vitro culture and statistical analysis. This approach aids in vaccine development and immune response monitoring.
Area of Science:
- Immunology
- Vaccinology
- Computational Biology
Background:
- Accurate quantification of antigen-specific CD4(+) T cells is crucial for vaccine development and immune response monitoring.
- Existing methods often require large cell numbers or complex instrumentation, hindering standardization and clinical application.
Purpose of the Study:
- To develop a simple, standardized method for determining antigen-specific CD4(+) T cell frequencies.
- To provide a tool for monitoring immune responses in clinical settings.
Main Methods:
- Culturing purified CD4(+) T cells with antigen-presenting cells and viral peptide antigens.
- Measuring cytokine release (IFN-γ, IL-5) after stimulation.
- Applying a Poisson distribution-based statistical analysis to calculate cell frequencies.
Main Results:
- A patient-specific threshold for cytokine release was established using unstimulated wells.
- The frequency of antigen-specific CD4(+) T cells was calculated based on stimulated well activity.
- An Excel tool was developed for automated frequency estimation.
Conclusions:
- A straightforward in vitro cell culture and statistical analysis method effectively determines antigen-specific CD4(+) T cell frequencies.
- The developed procedure and accompanying Excel tool offer a valuable resource for clinical immune response monitoring.
Background:
Knowledge of antigen-specific CD4(+) T cells frequencies is pivotal to the choice of the antigen to be used in anti-viral and anti-tumor vaccination procedures and for monitoring of immune responses. Methods that employ small cell numbers from patient samples, are easy to perform and do not require complex techniques/instrumentations and therefore standardization are desirable.
Methodology/Principal Findings:
Purified blood CD4(+) T cells from healthy donors were cultured with autologous antigen presenting cells in several replicate wells in equal numbers in the absence (un-stimulated wells) or in the presence of synthetic peptides corresponding to viral antigens promiscuous HLA-DR epitopes (antigen-stimulated wells). At day 7 of culture low dose IL-2 was added and at day 14 IFN-γ and IL-5 release in the supernatant was measured. A statistical analysis approach, based on Poisson distribution, was then implemented to calculate the frequency of viral-specific CD4(+) T cells. We first determined a patient-specific exceptionality threshold of cytokine release in the un-stimulated wells and then, based on this threshold, we counted the inactive/active wells within the antigen-stimulated wells. This number, along with the number of cells per well, allowed the point and interval estimates of frequencies. A ready-to-use Excel worksheet template with automatic calculations for frequencies estimate was developed and is provided as a supplemental file (Table S9).
Conclusions/Significance:
We report a simple experimental procedure combining short term in vitro cell culture with statistical analysis to calculate the frequency of antigen-specific CD4(+) T cells. The detailed experimental procedure along with the Excel applicative are a valuable tool for monitoring immune responses in the clinical practice.
