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Discrete event modeling of CD4+ memory T cell generation
Martin S Zand1, Benjamin J Briggs, Anirban Bose
1Nephrology Unit, University of Rochester Medical Center, Rochester, NY 14642, USA martin_zand@urmc.rochester.edu.
Journal of Immunology (Baltimore, Md. : 1950)
|September 10, 2004
Summary
A new computer model simulates CD4+ memory T cell generation. It reveals that direct progression to memory cells requires postactivation expansion to match experimental data.
Area of Science:
- Immunology
- Computational Biology
- Systems Biology
Background:
- Quantitative models are lacking for memory T cell differentiation studies.
- In silico hypothesis testing is crucial before in vivo experiments.
Purpose of the Study:
- To create a stochastic computer model for CD4+ memory T cell generation.
- To identify key variables influencing memory T cell pool size.
- To compare two distinct models of CD4+ memory T cell generation.
Main Methods:
- Developed a discrete event computer simulation for lymphocyte tracking (10^1 to 10^8 cells).
- Derived model parameters from in vitro experiments with human naive CD4+ T cells.
- Performed sensitivity analyses by varying critical model parameters.
Main Results:
- Identified cell cycle-dependent apoptosis probability and postactivation mitosis timing as key variables.
- Model I (maturation via effector cells) and Model II (direct progression) were compared.
- Direct progression (Model II) fails to explain memory cell mass without postactivation expansion.
Conclusions:
- Current models of direct naive to memory T cell progression do not account for experimentally measured cohort sizes.
- Postactivation expansion of the memory T cell cohort is necessary for direct progression models.
- The developed model provides a framework for in silico testing of T cell differentiation hypotheses.