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Stochastic gene expression in switching environments.

Martin J Gander1, Christian Mazza, Hansklaus Rummler

  • 1Section de Mathématiques, University of Geneva, Genève, Switzerland. Martin.Gander@math.unige.ch

Journal of Mathematical Biology
|March 24, 2007
PubMed
Summary

Organisms adapt to uncertain environments through population diversification. Heterogeneous cell populations can exhibit higher net growth rates than homogeneous ones in fluctuating conditions.

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Area of Science:

  • Mathematical Biology
  • Evolutionary Dynamics
  • Population Genetics

Background:

  • Organisms adapt to predictable environmental changes.
  • Irregular environmental fluctuations pose challenges for cellular survival.
  • Population diversification is a potential adaptive strategy.

Purpose of the Study:

  • To mathematically investigate population diversification in stochastic environments.
  • To analyze the dynamics of cell phenotype switching.
  • To determine conditions under which heterogeneous populations outperform homogeneous ones.

Main Methods:

  • Mathematical modeling of cell population dynamics.
  • Analysis of phenotype switching rates.
  • Derivation of steady-state distributions for population structure.
  • Numerical methods for calculating population growth rates.

Main Results:

  • Identified the steady-state distribution (pi) for the proportion of cells with the highest growth rate.
  • Proved convergence of empirical averages to the expected value of this proportion.
  • Developed efficient numerical methods for computation.

Conclusions:

  • Population diversification can be advantageous in uncertain environments.
  • Mathematical analysis confirms the potential for heterogeneous populations to achieve higher net growth rates.
  • The study provides a framework for understanding adaptive strategies in fluctuating environments.