Improved bounds on entropy production in living systems

TL;DR

This paper introduces an optimization-based method to better estimate the entropy production rate in living systems from partial data, revealing non-zero heat dissipation even under apparent equilibrium conditions.

Contribution

It provides a novel, provably optimal framework for inferring entropy production bounds from limited measurements in biological systems.

Findings

Improved bounds on entropy production in bacterial flagella motors

Enhanced estimates for microtubule growth processes

Detection of heat dissipation in calcium oscillations

Abstract

Living systems maintain or increase local order by working against the Second Law of Thermodynamics. Thermodynamic consistency is restored as they dissipate heat, thereby increasing the net entropy of their environment. Recently introduced estimators for the entropy production rate have provided major insights into the thermal efficiency of important cellular processes. In experiments, however, many degrees of freedom typically remain hidden to the observer, and in these cases, existing methods are not optimal. Here, by reformulating the problem within an optimization framework, we are able to infer improved bounds on the rate of entropy production from partial measurements of biological systems. Our approach yields provably optimal estimates given certain measurable transition statistics. In particular, it can reveal non-zero heat production rates even when non-equilibrium processes appear time symmetric and so may pretend to obey detailed balance. We demonstrate the broad applicability of this framework by providing improved bounds on the entropy production rate in a diverse range of biological systems including bacterial flagella motors, growing microtubules, and calcium oscillations within human embryonic kidney cells.