Fitness and entropy production in a cell population dynamics with epigenetic phenotype switching

Abstract

Motivated by recent understandings in the stochastic natures of gene expression, biochemical signaling, and spontaneous reversible epigenetic switchings, we study a simple deterministic cell population dynamics in which subpopulations grow with different rates and individual cells can bi-directionally switch between a small number of different epigenetic phenotypes. Two theories in the past, the population dynamics and thermodynamics of master equations, separatedly defined two important concepts in mathematical terms: the {\em fitness} in the former and the (non-adiabatic) {\em entropy production} in the latter. Both play important roles in the evolution of the cell population dynamics. The switching sustains the variations among the subpopulation growth thus continuous natural selection. As a form of Price's equation, the fitness increases with ($i$) natural selection through variations and $(ii)$ a positive covariance between the per capita growth and switching, which represents a Lamarchian-like behavior. A negative covariance balances the natural selection in a fitness steady state | "the red queen" scenario. At the same time the growth keeps the proportions of subpopulations away from the "intrinsic" switching equilibrium of individual cells, thus leads to a continous entropy production. A covariance, between the per capita growth rate and the "chemical potential" of subpopulation, counter-acts the entropy production. Analytical results are obtained for the limiting cases of growth dominating switching and vice versa.

16 pages

References in corpus (1)

• Stochastic Dynamical Structure (SDS) of Nonequilibrium Processes in the Absence of Detailed Balance. IV: Emerging of Stochastic Dynamical Equalities and Steady State Thermodynamics from Darwinian Dynamics

Cited by in corpus (4)

• Stochastic phenotype transition of a single cell in an intermediate region of gene-state switching
• Fluctuation Relations of Fitness and Information in Population Dynamics
• Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology
• Stochastic and Information-thermodynamic Structures of Population Dynamics in Fluctuating Environment