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Related Experiment Videos

Estimating lymphocyte division and death rates from CFSE data.

Rob J De Boer1, Vitaly V Ganusov, Dejan Milutinović

  • 1Theoretical Biology, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands. r.j.deboer@bio.uu.nl

Bulletin of Mathematical Biology
|July 13, 2006
PubMed
Summary

Carboxyfluorescein diacetate succinimidyl ester (CFSE) analysis of T cells reveals that cell death rates depend on completed divisions. This study refines mathematical models for immune cell division history and IL-2 concentration effects.

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Area of Science:

  • Immunology
  • Computational Biology
  • Mathematical Modeling

Background:

  • Carboxyfluorescein diacetate succinimidyl ester (CFSE) is a key dye for tracking immune cell division history.
  • Quantitative analysis of CFSE data, pioneered by Gett and Hodgkin, is crucial for understanding immune responses.
  • Interleukin-2 (IL-2) concentration significantly impacts T cell proliferation and survival.

Purpose of the Study:

  • To confirm and extend existing mathematical models for analyzing CFSE data.
  • To estimate key cell division parameters like time to first division, recruitment fraction, cell cycle time, and death rate.
  • To investigate the influence of IL-2 concentration on these parameters and T cell death dynamics.

Main Methods:

  • Utilized an extended Gett and Hodgkin method for CFSE data analysis.

Related Experiment Videos

  • Developed and applied a reformulated Deenick et al. mathematical model.
  • Employed non-linear fitting procedures to estimate parameter values and confidence intervals.
  • Assessed the impact of IL-2 concentration on T cell division and death parameters.

    • Main Results:

    • Successfully estimated time to first division, recruitment fraction, cell cycle time, and average death rate from CFSE data.
    • Identified parameters influenced by varying IL-2 concentrations.
    • Achieved a significantly better data fit by incorporating a T cell death rate dependent on the number of completed divisions.

    Conclusions:

    • The T cell death rate is demonstrably dependent on the number of divisions cells have undergone.
    • Mathematical modeling provides robust insights into immune cell division dynamics and responses to stimuli like IL-2.
    • Future work will extend current models to include arbitrary probability distributions for cell death and division.