Mixture distributions in a stochastic gene expression model with delayed feedback: a WKB approximation approach

J Math Biol. 2020 Jul;81(1):343-367. doi: 10.1007/s00285-020-01512-y. Epub 2020 Jun 24.

Abstract

Noise in gene expression can be substantively affected by the presence of production delay. Here we consider a mathematical model with bursty production of protein, a one-step production delay (the passage of which activates the protein), and feedback in the frequency of bursts. We specifically focus on examining the steady-state behaviour of the model in the slow-activation (i.e. large-delay) regime. Using a formal asymptotic approach, we derive an autonomous ordinary differential equation for the inactive protein that applies in the slow-activation regime. If the differential equation is monostable, the steady-state distribution of the inactive (active) protein is approximated by a single Gaussian (Poisson) mode located at the globally stable fixed point of the differential equation. If the differential equation is bistable (due to cooperative positive feedback), the steady-state distribution of the inactive (active) protein is approximated by a mixture of Gaussian (Poisson) modes located at the stable fixed points; the weights of the modes are determined from a WKB approximation to the stationary distribution. The asymptotic results are compared to numerical solutions of the chemical master equation.

Keywords: Bursting; Exponential asymptotics; Large deviations; Production delay; Stochastic gene expression; WKB approximation.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Biochemical Phenomena
  • Feedback, Physiological*
  • Gene Expression*
  • Models, Genetic*
  • Normal Distribution
  • Stochastic Processes