Non-Markovian non-equilibrium modeling of experimental cell-motion trajectories reveals dependence of propulsion-force correlations on solvent viscosity

TL;DR

This study introduces a non-equilibrium model for cell motility that captures propulsion-force correlations influenced by solvent viscosity, revealing how cells adapt their propulsion in different fluid environments and predicting their power output.

Contribution

We develop a data-driven non-Markovian model based on the generalized Langevin equation that accounts for hydrodynamic effects and correlated propulsion forces in cell motility.

Findings

Propulsion-force correlations are multi-exponential and depend on solvent viscosity.

Cells adapt their propulsion characteristics according to solvent viscosity.

The model predicts cell diffusivities and power outputs beyond experimental timescales.

Abstract

Cell motility underlies many biological processes, including cancer metastasis, bacterial infection, and evolutionary adaptation. We introduce a non-equilibrium single-cell motility model inspired by the generalized Langevin equation, which accounts for hydrodynamic friction and correlated propulsion force. From video microscopy of Chlamydomonas reinhardtii algae and Salmonella typhimurium bacteria we extract the propulsion-force dynamics on the single-cell level, which we find to exhibit multi-exponential correlations, not captured by literature non-equilibrium cell-motility models. Based on our data-driven model, we predict the effective cell diffusivities beyond experimentally resolved timescales and demonstrate a diffusivity maximum at intermediate solvent viscosity for both cell types. This means that cells adapt their propulsion-force characteristics according to the solvent viscosity. In addition, our model predicts the power output of single cells, which is on the order of aW for the salmonella and fW for the algae.