A Mechanical Model of Collective Cell Movement In Tissues

Ray, Soumyadipta (2026) A Mechanical Model of Collective Cell Movement In Tissues. PhD thesis, Indian Institute of Science Education and Research Kolkata.

Text (PhD thesis of Soumyadipta Ray (19RS003)) 19RS003.pdf - Submitted Version Restricted to Repository staff only Download (26MB)

Abstract

Motion of cell collectives is a fundamental process in development, cancer progression, and wound healing, yet the influence of intercellular forces and local microenvironments remains underexplored. A key question is how the tissue material properties and collective modes of cell migration emerge from the interplay of single cell-level properties and cell-cell interaction forces. In this doctoral work, we develop a two-dimensional computational model of tissues, integrating intercellular force dynamics and cell shape changes. Our model captures a solid-to-liquid transition in near-confluent tissue monolayers upon reducing the intercellular adhesion strength, which leads to spontaneous neighbor exchanges, known as T1 transitions. Near the liquid-solid phase boundary, we observe glassy behavior characterized by subdiffusive dynamics, swirling motion, and non-Gaussian exponential tails in displacement distributions. These exponential tails collapse onto a single master curve, suggesting a universal ‘diffusion length’ in the glassy regime. Notably, we show that structural parameters depending on cell shape cannot always distinguish tissue phases due to huge cell shape fluctuations that are not observed in energy functional based Vertex and Voronoi models. Furthermore, this thesis work also sheds light on chemoattractant-driven long-range collective cell migration through heterogeneous microenvironments. We apply our modeling framework to investigate border cell migration in Drosophila egg chambers, where it successfully replicates in-vivo observations such as rotation of the cell cluster and its tendency to follow a central path through the egg chamber. Our model also predicts alternating acceleration and deceleration phases as the cluster moves through the junctions of other cell types, offering insights into the influence of surrounding tissue topology and perturbations in chemoattractant gradients on migration speed and directionality. By addressing the limitations of earlier models and eliminating some arbitrary features, our approach offers broad applicability to other migration contexts in development and disease, involving interactions among different cell types within complex environments. In essence, this doctoral work contributes a novel, comprehensive computational framework for studying collective cell behavior, offering insights into biological processes that involve cell migration and tissue mechanics.

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