Likelihood-Based Heterogeneity Inference Reveals Non-Stationary Effects in Biohybrid Cell-Cargo Transport

TL;DR

This paper introduces a likelihood-based method to analyze heterogeneity in biohybrid cell-cargo transport, revealing that the variability in bead motion driven by active cells is non-stationary over time.

Contribution

The study presents a novel likelihood approach for estimating heterogeneity in biological transport systems, capable of handling limited data and providing uncertainty quantification.

Findings

Heterogeneity in bead dynamics is time-dependent.

The likelihood method effectively estimates heterogeneity from sparse data.

Heterogeneity exhibits non-stationary behavior over time.

Abstract

Variability of motility behavior in populations of microbiological agents is a ubiquitous phenomenon even in the case of genetically identical cells. Accordingly, passive objects introduced into such biological systems and driven by them will also exhibit heterogeneous motion patterns. Here, we study a biohybrid system of passive beads driven by active ameboid cells and use a likelihood approach to estimate the heterogeneity of the bead dynamics from their discretely sampled trajectories. We showcase how this approach can deal with information-scarce situations and provides natural uncertainty bounds for heterogeneity estimates. Using these advantages we particularly uncover that the heterogeneity in the system is time-dependent.