Abstract
Cell migration in confining physiological environments relies on the concerted dynamics of several cellular components, including protrusions, adhesions with the environment, and the cell nucleus. However, it remains poorly understood how the dynamic interplay of these components and the cell polarity determine the emergent migration behavior at the cellular scale. Here, we combine data-driven inference with a mechanistic bottom-up approach to develop a model for protrusion and polarity dynamics in confined cell migration, revealing how the cellular dynamics adapt to confining geometries. Specifically, we use experimental data of joint protrusion-nucleus migration trajectories of cells on confining micropatterns to systematically determine a mechanistic model linking the stochastic dynamics of cell polarity, protrusions, and nucleus. This model indicates that the cellular dynamics adapt to confining constrictions through a switch in the polarity dynamics from a negative to a positive self-reinforcing feedback loop. Our model further reveals how this feedback loop leads to stereotypical cycles of protrusion-nucleus dynamics that drive the migration of the cell through constrictions. These cycles are disrupted upon perturbation of cytoskeletal components, indicating that the positive feedback is controlled by cellular migration mechanisms. Our data-driven theoretical approach therefore identifies polarity feedback adaptation as a key mechanism in confined cell migration.
15 More- Received 18 May 2022
- Accepted 23 August 2022
DOI:https://doi.org/10.1103/PhysRevX.12.031041
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
Published by the American Physical Society
Physics Subject Headings (PhySH)
Focus
How Cells Move through Narrow Spaces
Published 20 September 2022
Experiments demonstrate that biological cells actively change shape to respond to their surroundings when moving in confined regions.
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Popular Summary
The movement of cells through complex and confining tissues is crucial in many biological processes, ranging from embryo development to cancer metastasis. This process of confined cell migration relies on a complex active-matter system that consumes energy. This system is composed of various cellular components—nucleus, protrusions, polarity—that interact with their environment. However, the coupled dynamics of these components, and how they impact cell migration under confinement, remain poorly understood. We use experimental data of confined migrating cells to infer a model for the coupled dynamics of the nucleus, protrusion, and polarity, which reveals that these dynamics adapt to the geometry of the confinement, allowing cells to overcome narrow constrictions more efficiently.
Biophysical modeling approaches to cell migration typically address such problems either from the bottom up, by postulating mechanisms, or from the top down, through inference from data. We bridge this gap by developing a hybrid data-driven and mechanistic model using experimental data of cell shapes in confined migration. We find that under strong confinement, the cell polarity dynamics switches from a random exploration mode to a self-reinforcing feedback loop, which enhances directed protrusion growth that facilitates cell motion across confining constrictions. Our model successfully predicts the key statistics of cellular behavior in a variety of confinement geometries in terms of a geometry adaptation mechanism of protrusion and polarity dynamics.
Our approach paves the way toward extracting mechanistic insights from complex active-matter systems using data-driven inference. Our findings suggest that adaptation to geometry plays a key role in confined migration and highlights that we should consider adaptation to local structure as an important aspect of active-matter systems.