Fluctuations in first passage times and utility of resetting protocol in biochemical systems with two-state toggling

TL;DR

This paper investigates the fluctuations in first passage times in three two-state toggling biochemical systems, revealing non-monotonic behavior and the effects of stochastic resetting, including a re-entrant transition in protocol efficacy.

Contribution

It provides the first detailed analysis of first passage time fluctuations and resetting protocols in three distinct two-state biochemical models, confirming analytical predictions with simulations.

Findings

First passage time fluctuations are non-monotonic with bias strength.

Stochastic resetting can expedite first passage in these systems.

Efficacy of resetting exhibits a re-entrant transition as bias varies.

Abstract

Interesting theoretical problems of target search or threshold crossing, formally known as {\it first passage}, often arise in both diffusive transport problems as well as problems of chemical reaction kinetics. We study three systems following different chemical kinetics, and are special as they {\it toggle between two states}: (i) a population dynamics of cells with auto-catalytic birth and intermittent toxic chemical-induced forced death, (ii) a bond cluster model representing membrane adhesion to extracellular matrix under a fluctuating load, and (iii) a model of gene transcription with a regulated promoter switching between active and inactive states. Each of these systems has a target state to attain, which defines a first passage problem -- namely, population becoming extinct, complete membrane detachment, or mRNA count crossing a threshold. We study the fluctuations in first passage time and show that it is interestingly {\it non-monotonic} in all these cases, with increasing strength of bias towards the target. We also study suitable {\it stochastic resetting} protocols to expedite first passage for these systems, and show that there is a re-entrant transition of the efficacy of this protocol in all the three cases, as a function of the bias. The exact analytical condition for these transitions predicted in earlier literature is verified here through simulations.