Noise-induced metastability in biochemical networks

TL;DR

This paper demonstrates that biochemical networks exhibit metastable states and multiple timescales due to noise, providing new analytical insights into their complex dynamics, exemplified by the Togashi-Kaneko reaction.

Contribution

It reveals that metastability and diverse timescales are common in autocatalytic biochemical networks and offers an analytical approach to study these phenomena.

Findings

Metastable states are a general feature of autocatalytic reaction networks.

Different timescales emerge naturally from noise in these systems.

Analytical treatment of the Togashi-Kaneko reaction is achieved.

Abstract

Intra-cellular biochemical reactions exhibit a rich dynamical phenomenology which cannot be explained within the framework of mean-field rate equations and additive noise. Here, we show that the presence of metastable states and radically different timescales are general features of a broad class of autocatalyic reaction networks, and moreover, that this fact may be exploited to gain analytical results. The latter point is demonstrated by a treatment of the paradigmatic Togashi-Kaneko reaction, which has resisted theoretical analysis for the last decade.