Cell dynamics in microfluidic devices under heterogeneous chemotaxis and growth conditions: a mathematical study

TL;DR

This paper develops an analytical framework to understand cell movement driven by complex chemotactic gradients in microfluidic devices, capturing dynamic behaviors like oscillations and spatial variations.

Contribution

It introduces a novel analytical approach for approximating cell densities and velocities in heterogeneous chemotactic fields, extending beyond traditional translationally invariant wave models.

Findings

Analytical solutions reveal diverse cell motility patterns in complex chemoattractant fields.

Framework enables rapid evaluation of model predictions and experimental data.

Application to models with full chemoattractant dynamics enhances understanding of microdevice control.

Abstract

As motivated by studies of cellular motility driven by spatiotemporal chemotactic gradients in microdevices, we develop a framework for constructing approximate analytical solutions for the location, speed and cellular densities for cell chemotaxis waves in heterogeneous fields of chemoattractant from the underlying partial differential equation models. In particular, such chemotactic waves are not in general translationally invariant travelling waves, but possess a spatial variation that evolves in time, and may even may oscillate back and forth in time, according to the details of the chemotactic gradients. The analytical framework exploits the observation that unbiased cellular diffusive flux is typically small compared to chemotactic fluxes and is first developed and validated for a range of exemplar scenarios. The framework is subsequently applied to more complex models considering the full dynamics of the chemoattractant and how this may be driven and controlled within a microdevice by considering a range of boundary conditions. In particular, even though solutions cannot be constructed in all cases, a wide variety of scenarios can be considered analytically, firstly providing global insight into the important mechanisms and features of cell motility in complex spatiotemporal fields of chemoattractant. Such analytical solutions also provide a means of rapid evaluation of model predictions, with the prospect of application in computationally demanding investigations relating theoretical models and experimental observation, such as Bayesian parameter estimation.