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Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
Published on: April 27, 2021
Time-dependent information transmission in a model regulatory circuit.
F Mancini1, C H Wiggins, M Marsili
1International School for Advanced Studies (SISSA), Trieste, Italy.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 17, 2013
Summary
Biological systems with signal processing delays have limited information transmission. Network structure and dynamic states, like absorbing states, optimize information flow in stress response circuits.
Area of Science:
- Systems biology
- Information theory
- Physiology
Background:
- Biological regulatory systems often exhibit physiological delays in signal processing.
- Understanding these delays is crucial for modeling biological information transmission.
Purpose of the Study:
- To model how physiological delays affect information transmission in biological regulatory systems.
- To identify network topologies that maximize information transfer.
- To explore the role of dynamic states in optimal information transmission.
Main Methods:
- Development of a simple regulatory model incorporating physiological delays.
- Analysis of information transmission limits based on input and output dynamic timescales.
- Identification of network topologies associated with maximally informative circuits.
Main Results:
- Information transmission in delayed systems is constrained by both input and output dynamics.
- Maximally informative network topologies resemble known biological circuits, particularly those in stress response.
- Circuits operating outside steady state can leverage absorbing states for optimal information transmission.
Conclusions:
- Physiological delays fundamentally limit information transmission in biological networks.
- Network structure and dynamic operating points are key determinants of information processing efficiency.
- Biological circuits, especially stress response pathways, may have evolved to exploit these principles for optimal function.
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