Improved estimation for energy dissipation in biochemical oscillations

TL;DR

This paper introduces a new method based on stochastic normal form theory to more accurately estimate energy dissipation in biochemical oscillations, revealing the role of sensitivity, noise, and amplitude effects.

Contribution

It develops a tighter estimator for energy dissipation using the Pearson correlation, surpassing conventional thermodynamic uncertainty relations.

Findings

Enhanced sensitivity improves energy dissipation estimation.

Internal noise and amplitude power effects influence oscillation performance.

A trade-off relation between transport efficiency and phase sensitivity is established.

Abstract

Biochemical oscillations, regulating the timing of life processes, need consume energy to achieve good performance on crucial functions, such as high accuracy of phase period and high sensitivity to external signals. However, it is a great challenge to precisely estimate the energy dissipation in such systems. Here, based on the stochastic normal form theory (SNFT), we calculate the Pearson correlation coefficient between the oscillatory amplitude and phase, and a trade-off relation between transport efficiency and phase sensitivity can then be derived, which serves as a tighter form than the estimator resulting from the conventional thermodynamic uncertainty relation (TUR). Our findings demonstrate that a more precise energy dissipation estimation can be obtained by enhancing the sensitivity of the biochemical oscillations. Moreover, the internal noise and amplitude power effects have also been discovered.