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Estimation of Structural Sensitivity of Intrinsically Disordered Regions in Response to Hyperosmotic Stress in Living Cells Using FRET
Published on: January 12, 2024
Decoding molecular distributional codes through collective instabilities
Arxiv
|August 1, 2026
Summary
Cells use physical instabilities like phase separation as efficient sensors to decode molecular information. These collective phenomena capture distribution shapes beyond simple averages, offering a compact sensing mechanism.
Area of Science:
- Biophysics
- Systems Biology
- Molecular Biology
Background:
- Biological information is encoded in molecular variants, like phosphorylation or ubiquitination.
- Conventional sensors struggle to read this information due to the need for numerous distinct sensors.
Purpose of the Study:
- To investigate how collective physical instabilities can naturally integrate and read information from molecular distributions.
- To derive a geometric condition for effective molecular information decoding.
Main Methods:
- Information-theoretic matching conditions were used to derive a geometric condition for decoders.
- Mean-field theory and lattice Monte Carlo simulations were employed.
- Phase separation, percolation, and membrane curvature instabilities were analyzed.
Main Results:
- Phase separation robustly captures distribution variance and skewness, unlike mass-action binding which only detects the mean.
- Physical instabilities, particularly near phase boundaries, efficiently capture molecular population information.
- Finite valency introduces discriminatory power beyond mean-field predictions.
Conclusions:
- Collective physical instabilities serve as natural, compact, and near-optimal sensors for decoding molecular distributional codes.
- Cells can leverage these instabilities for efficient biological information processing.
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