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Updated: May 14, 2026
09:18
Identification of Intracellular Signaling Events Induced in Viable Cells by Interaction with Neighboring Cells Undergoing Apoptotic Cell Death
Published on: December 27, 2016
Modeling cell-to-cell stochastic variability in intrinsic apoptosis pathway.
1Department of Bioengineering, University of Texas at Dallas, Richardson, TX 75080, USA.
Summary
Cellular apoptosis exhibits variability due to intrinsic noise and protein concentration changes. Extrinsic factors, not intrinsic noise, are the primary cause of cell-to-cell differences in apoptosis timing.
Area of Science:
- Cell Biology
- Systems Biology
- Biophysics
Background:
- Apoptosis, or programmed cell death, is crucial for metazoan development and tissue homeostasis.
- Apoptosis can be triggered via intrinsic or extrinsic pathways, with previous models focusing on deterministic intrinsic pathway dynamics.
- Observed cell-to-cell variability in apoptosis suggests the influence of stochastic processes.
Purpose of the Study:
- To investigate the impact of intrinsic stochastic fluctuations and extrinsic protein variations on the intrinsic apoptosis network.
- To determine the origins of cell-to-cell variability in apoptosis response.
Main Methods:
- Implementation of the Gillespie Stochastic Simulation Algorithm (SSA) to model intrinsic noise.
- Analysis of steady-state output histograms to assess bistability regions.
- Modeling of extrinsic fluctuations through variations in key protein concentrations.
Main Results:
- Intrinsic noise broadens the bistability region of the intrinsic apoptosis network.
- Intrinsic noise alone is insufficient to explain significant stochastic variations at physiological molecular numbers.
- Extrinsic fluctuations, specifically variations in protein concentrations, quantitatively explain experimentally observed cell-to-cell variability in apoptosis timing.
Conclusions:
- Cellular heterogeneity in apoptosis response is primarily driven by extrinsic factors rather than intrinsic stochasticity.
- Understanding these fluctuations is key to deciphering cell fate decisions and developing targeted therapies.
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