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Field-Based Thermal Physiology Assay: Cold Shock Recovery under Ambient Conditions
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Optimal phenotypic adaptation in fluctuating environments.

Jason T George1

  • 1Department of Biomedical Engineering, Texas A&M University, College Station, Texas; Engineering Medicine Program, Texas A&M University, Houston, Texas; Center for Theoretical Biological Physics, Rice University, Houston, Texas.

Biophysical Journal
|October 25, 2023
PubMed
Summary
This summary is machine-generated.

Cellular systems use memory to adapt to changing environments. This memory influences adaptation speed and accuracy, with observed growth changes being a result of optimal decision-making strategies.

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Area of Science:

  • Biology
  • Ecology
  • Mathematical Modeling

Background:

  • Phenotypic adaptation is crucial for organisms in variable environments.
  • Cellular memory plays a role in decision-making under nutrient uncertainty.
  • Fluctuating conditions can lead to distinct growth phenotypes.

Purpose of the Study:

  • To model memory-driven cellular adaptation in dynamic environments.
  • To understand how memory influences the trade-off between adaptation speed and accuracy.
  • To explain growth reductions observed in fluctuating conditions.

Main Methods:

  • Development of a simple stochastic mathematical model.
  • Analysis of adaptive population dynamics in uncertain environments.
  • Inference of future environmental variations from past states.

Main Results:

  • Memory capacity dictates a trade-off between adaptation speed and accuracy.
  • Observed growth reductions are linked to optimal decision-making (bet hedging).
  • Phenotypic-environmental mismatch contributes to growth changes.

Conclusions:

  • Mathematical modeling provides insights into memory-driven phenotypic adaptation.
  • The framework can inform strategies for therapies targeting adaptive systems.
  • Optimal decision-making in fluctuating environments involves trade-offs and potential mismatches.