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Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device

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Published on: April 17, 2021

Multicellular sensing at a feedback-induced critical point.

Michael Vennettilli^1,2, Amir Erez^3,4, Andrew Mugler^1,2

¹Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana 47907, USA.

Physical Review. E

|December 17, 2020

Summary

This summary is machine-generated.

This study shows that operating near critical points in biological systems maximizes information gain from chemical signals. However, this comes at the cost of slower responses, impacting information processing rates.

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Area of Science:

Systems biology
Biochemical networks
Cellular signaling

Background:

Cellular behavior can exhibit bifurcations due to feedback in sensory biochemical networks, mimicking thermodynamic critical points.
Biological systems may operate near these critical points, but the functional advantages are not well understood.

Purpose of the Study:

To investigate if operating at criticality offers a functional benefit for sensing stochastic chemical signals.
To explore the role of multicellular communication in enhancing information gain at criticality.

Main Methods:

Development of a simple biochemical model incorporating nonlinear feedback and multicellular communication.
Analysis of mutual information to quantify signal sensing capabilities.
Examination of signal susceptibility and readout noise at criticality.

Main Results:

Mutual information is maximized at criticality for slow signal fluctuations, as increased signal susceptibility outweighs readout noise.
Multicellular communication at criticality induces long-range correlations, enhancing information about the spatially averaged signal.
The information rate, unlike information content, is minimized at criticality due to critical slowing down.

Conclusions:

Feedback-induced criticality offers benefits for multicellular sensing by maximizing information acquisition.
Criticality presents a trade-off between information gain and information processing speed.
Understanding these costs and benefits is crucial for comprehending biological sensing mechanisms.