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Non-genetic heterogeneity, criticality and cell differentiation
Mainak Pal1, Sayantari Ghosh, Indrani Bose
1Department of Physics, Bose Institute 93/1, Acharya Prafulla Chandra Road, Kolkata-700009, India.
Physical Biology
|November 28, 2014
Summary
This study models cell differentiation using a two-gene system where transcription factors repress each other. Deterministic and stochastic processes combine to explain how progenitor cells become distinct cell types.
Area of Science:
- Systems Biology
- Molecular Biology
- Genetics
Background:
- Cell differentiation is crucial for forming distinct cell types from multipotent progenitors.
- A two-gene regulatory motif, where genes repress each other and autoactivate, is key in cell differentiation.
- Existing theoretical models explore this motif, but a simplified approach is needed.
Purpose of the Study:
- To investigate a simplified model of cell differentiation without cooperativity in gene expression.
- To understand the combined roles of deterministic and stochastic processes in cell differentiation.
- To provide a physical understanding of experimental observations in cell differentiation.
Main Methods:
- Developed a simple mathematical model of cell differentiation based on a two-gene motif.
- Analyzed deterministic dynamics, identifying a supercritical pitchfork bifurcation.
- Studied stochastic dynamics using Langevin equations and linear noise approximation.
Main Results:
- The model's deterministic dynamics predict a bifurcation from one stable state to two.
- Stochastic simulations reveal how noise influences the differentiation process.
- Simulation results offer a new physical interpretation of experimental findings.
Conclusions:
- Deterministic and stochastic factors are essential for cell differentiation.
- Protein fluctuation variance and autocorrelation can serve as early indicators of bifurcation in cell differentiation.
- The study provides a foundational understanding of gene regulatory networks in cell fate determination.
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