Dynamic cluster field modeling of collective chemotaxis

TL;DR

This paper introduces Dynamic cluster field modeling (DCF), a new computational approach that simulates collective chemotaxis of thousands of cells with high-resolution chemoattractant dynamics, matching experimental results and enabling studies of complex biological processes.

Contribution

The paper presents DCF, a novel computational method that allows high-fidelity simulation of large-scale collective cell migration with detailed chemoattractant transport modeling.

Findings

DCF accurately reproduces experimental chemotaxis scenarios.

The model can simulate thousands of cells with detailed extracellular dynamics.

It opens new research avenues in neuroscience, immunology, and oncology.

Abstract

Collective migration of eukaryotic cells is often guided by chemotaxis, and is critical in several biological processes, such as cancer metastasis, wound healing, and embryogenesis. Understanding collective chemotaxis has challenged experimental, theoretical and computational scientists because cells can sense very small chemoattractant gradients that are tightly controlled by cell-cell interactions and the regulation of the chemoattractant distribution by the cells. Computational models of collective cell migration that offer a high-fidelity resolution of the cell motion and chemoattractant dynamics in the extracellular space have been limited to a small number of cells. Here, we present Dynamic cluster field modeling (DCF), a novel computational method that enables simulations of collective chemotaxis of cellular systems with O(1000) cells and high-resolution transport dynamics of the chemoattractant in the time-evolving extracellular space. We illustrate the efficiency and predictive capabilities of our approach by comparing our numerical simulations with experiments in multiple scenarios that involve chemoattractant secretion and uptake by the migrating cells, regulation of the attractant distribution by cell motion, and interactions of the chemoattractant with an enzyme. The proposed algorithm opens new opportunities to address outstanding problems that involve collective cell migration in the central nervous system, immune response and cancer metastasis.