Theoretical Analysis of Fas Ligand-Induced Apoptosis with an Ordinary Differential Equation Model

Zhimin Shi1, Yan Li1, Zhihai Liu1

  • 1State Key Laboratory of Bioorganic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, P. R. China tel: 86-21-54925128.

Molecular Informatics
|August 2, 2016
PubMed

Insights

This study develops a mathematical model to quantitatively interpret cell sensitivity and apoptosis pathways. The model reveals key factors in Fas ligand-induced cell death and predicts pathway transitions.

Area of Science:

  • Cellular biology
  • Systems biology
  • Mathematical modeling

Background:

  • Fas ligand (FasL) triggers diverse apoptotic mechanisms across cell types.
  • Apoptosis pathways are regulated by complex biological networks.
  • Quantitative interpretation of these pathways is crucial for understanding cell sensitivity.

Purpose of the Study:

  • To develop a quantitative ordinary differential equation (ODE) model of Fas receptor-mediated apoptosis.
  • To analyze the role of kinetic parameters and protein concentrations in cell sensitivity to FasL.
  • To investigate the transition between type-I and type-II apoptotic pathways.

Main Methods:

  • Developed a 29-equation ODE model incorporating major apoptosis pathway components.
  • Calibrated model parameters using nonlinear fitting to experimental protein concentrations (caspase-3, -8, -9, Bid) in Jurkat T-cells.
  • Analyzed model predictions regarding FasL-induced apoptosis.

Main Results:

  • The model accurately interprets kinetic parameters and protein concentrations influencing cell sensitivity to FasL.
  • Identified potential reasons for the switch between type-I and type-II apoptosis pathways.
  • Predicted a more significant role for Fas compared to Bax and suggested a feedback mechanism between pathway types.

Conclusions:

  • The ODE model provides quantitative insights into Fas-mediated apoptosis.
  • The model highlights the critical influence of specific proteins and parameters on cell death.
  • Further refinement is needed for predicting apoptosis in diverse cell lines like NCI-60 cells based on gene expression.

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