The effects of intrinsic noise on the behaviour of bistable cell regulatory systems under quasi-steady state conditions

TL;DR

This paper investigates how intrinsic noise influences bistable cell regulatory systems under quasi-steady state conditions, introducing a stochastic quasi-steady state approximation and demonstrating how molecule numbers control bistability.

Contribution

It develops a stochastic generalisation of the quasi-steady state approximation using a semi-classical approach, revealing molecule counts as key parameters in bistability beyond mean-field predictions.

Findings

Number of molecules regulates bistability.

Stochastic effects confirmed by simulations.

Strategies for controlling cell states based on molecule counts.

Abstract

We analyse the effect of intrinsic fluctuations on the properties of bistable stochastic systems with time scale separation operating under1 quasi-steady state conditions. We first formulate a stochastic generalisation of the quasi-steady state approximation based on the semi-classical approximation of the partial differential equation for the generating function associated with the Chemical Master Equation. Such approximation proceeds by optimising an action functional whose associated set of Euler-Lagrange (Hamilton) equations provide the most likely fluctuation path. We show that, under appropriate conditions granting time scale separation, the Hamiltonian can be re-scaled so that the set of Hamilton equations splits up into slow and fast variables, whereby the quasi-steady state approximation can be applied. We analyse two particular examples of systems whose mean-field limit has been shown to exhibit bi-stability: an enzyme-catalysed system of two mutually-inhibitory proteins and a gene regulatory circuit with self-activation. Our theory establishes that the number of molecules of the conserved species are order parameters whose variation regulates bistable behaviour in the associated systems beyond the predictions of the mean-field theory. This prediction is fully confirmed by direct numerical simulations using the stochastic simulation algorithm. This result allows us to propose strategies whereby, by varying the number of molecules of the three conserved chemical species, cell properties associated to bistable behaviour (phenotype, cell-cycle status, etc.) can be controlled.