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Purely stochastic binary decisions in cell signaling models without underlying deterministic bistabilities.

Maxim N Artyomov¹, Jayajit Das, Mehran Kardar

¹Departments of Chemical Engineering, Chemistry, Biological Engineering, and Physics, Massachusetts Institute of Technology, Cambridge, MA 02139.

Proceedings of the National Academy of Sciences of the United States of America

|November 21, 2007

Summary

Stochastic fluctuations in cell signaling, particularly with balanced feedback loops, can lead to distinct "on" or "off" cellular states, deviating from deterministic predictions. This highlights the role of randomness in enabling binary cell decisions.

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Area of Science:

Cell Biology
Systems Biology
Biophysics

Background:

Cellular responses to extracellular stimuli involve complex signaling networks with positive and negative feedback loops.
Stochastic effects, or random fluctuations, can be significant when cellular responses are triggered by small numbers of molecules.

Purpose of the Study:

To investigate the influence of stochastic fluctuations on a signaling model featuring opposing feedback loops.
To understand how random molecular events impact cellular decision-making processes.

Main Methods:

Development and analysis of a simplified signaling model with coupled positive and negative feedback loops.
Comparison of deterministic (mean-field) predictions with stochastic simulations.

Main Results:

The stochastic model exhibits bimodal distributions for signaling molecules, resulting in distinct "on" or "off" cellular states, unlike the intermediate steady state predicted by deterministic models.
For a large number of molecules, stochastic results converge to deterministic predictions.
Signal output scaling deviates anomalously from mean-field predictions when stochastic effects are prominent.

Conclusions:

Stochastic fluctuations can drive cellular systems into discrete states, enabling binary decisions.
The identified conditions for this phenomenon are common, suggesting broad relevance in cell biology.
Randomness plays a crucial role in cellular information processing and decision-making.