Phase-Field Modeling of Individual and Collective Cell Migration

Moure, Adrian; Gómez, Héctor

doi:10.1007/s11831-019-09377-1

Cited by 49 publications

(37 citation statements)

References 199 publications

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“…Different approaches to cell motility, as for active gel theory coupled to the classical theory of thin elastic shells, are also widely used [85], but are not discussed in this work. The framework described herein, including myosin dynamics, phase transformations between G-actin and F-actin, has been depicted in a set of publications by the group of H. Gomez [36,86]. The flow of the F-actin network was treated as a Newtonian fluid and directed by its velocity.…”

Section: Multiscale Scenario Of Cell Viscoelasticitymentioning

confidence: 99%

Modeling cells spreading, motility, and receptors dynamics: a general framework

et al. 2021

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The response of cells during spreading and motility is dictated by several multi-physics events, which are triggered by extracellular cues and occur at different time-scales. For this sake, it is not completely appropriate to provide a cell with classical notions of the mechanics of materials, as for “rheology” or “mechanical response”. Rather, a cell is an alive system with constituents that show a reproducible response, as for the contractility for single stress fibers or for the mechanical response of a biopolymer actin network, but that reorganize in response to external cues in a non-exactly-predictable and reproducible way. Aware of such complexity, in this note we aim at formulating a multi-physics framework for modeling cells spreading and motility, accounting for the relocation of proteins on advecting lipid membranes. Graphic Abstract We study the mechanical response under compression/extension of an assembly composed of 8 helical rods, pin-jointed and arranged in pairs with opposite chirality. In compression we find that, whereas a single rod buckles (a), the rods of the assembly deform as stable helical shapes (b). We investigate the effect of different boundary conditions and elastic properties on the mechanical response, and find that the deformed geometries exhibit a common central region where rods remain circular helices. Our findings highlight the key role of mutual interactions in the ensemble response and shed some light on the reasons why tubular helical assemblies are so common and persistent.

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Section: Multiscale Scenario Of Cell Viscoelasticitymentioning

confidence: 99%

Modeling cells spreading, motility, and receptors dynamics: a general framework

et al. 2021

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“…Furtheron, in view of the viscoelastic flow behavior of monolayers migrating around an obstacle [22], a generalization of the approach to different viscoelastic models [49] would be highly interesting. We also envision extending our approach to multicellular situations in which single cell resolution is required, by using different phase fields for different cells [30,[74][75][76][77]. The approach could be generalized to three dimensions, to model e.g.…”

Section: Discussionmentioning

confidence: 99%

Reversible elastic phase field approach and application to cell monolayers

2020

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Abstract. Motion and generation of forces by single cells and cell collectives are essential elements of many biological processes, including development, wound healing and cancer cell migration. Quantitative wound healing assays have demonstrated that cell monolayers can be both dynamic and elastic at the same time. However, it is very challenging to model this combination with conventional approaches. Here we introduce an elastic phase field approach that allows us to predict the dynamics of elastic sheets under the action of active stresses and localized forces, e.g. from leader cells. Our method ensures elastic reversibility after release of forces. We demonstrate its potential by studying several paradigmatic situations and geometries relevant for single cells and cell monolayers, including elastic bars, contractile discs and expanding monolayers with leader cells. Graphical abstract

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“…Alternatively, the product δ φ c restricts it to the narrow region around the interphase. Thus, the evolution of a species that is found in the cytoplasm is governed by

\frac{\partial ((), φ c_{cyt})}{\partial t} = \nabla \cdot ((), D_{cyt} φ \nabla c_{cyt}) + f_{cyt},

where f cyt includes all the relevant reactions (Moure & Gomez, 2019). For a function found only on the membrane, the term φ in this equation would be replaced by δ φ .…”

Section: Simulation Methodsmentioning

confidence: 99%

Tools for computational analysis of moving boundary problems in cellular mechanobiology

DiNapoli¹,

Robinson²,

Iglesias

2020

WIREs Mechanisms of Disease

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A cell's ability to change shape is one of the most fundamental biological processes and is essential for maintaining healthy organisms. When the ability to control shape goes awry, it often results in a diseased system. As such, it is important to understand the mechanisms that allow a cell to sense and respond to its environment so as to maintain cellular shape homeostasis. Because of the inherent complexity of the system, computational models that are based on sound theoretical understanding of the biochemistry and biomechanics and that use experimentally measured parameters are an essential tool. These models involve an inherent feedback, whereby shape is determined by the action of regulatory signals whose spatial distribution depends on the shape. To carry out computational simulations of these moving boundary problems requires special computational techniques. A variety of alternative approaches, depending on the type and scale of question being asked, have been used to simulate various biological processes, including cell motility, division, mechanosensation, and cell engulfment. In general, these models consider the forces that act on the system (both internally generated, or externally imposed) and the mechanical properties of the cell that resist these forces. Moving forward, making these techniques more accessible to the non‐expert will help improve interdisciplinary research thereby providing new insight into important biological processes that affect human health.This article is categorized under: Cancer > Computational Models Cancer > Molecular and Cellular Physiology

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Phase-Field Modeling of Individual and Collective Cell Migration

Cited by 49 publications

References 199 publications

Modeling cells spreading, motility, and receptors dynamics: a general framework

Modeling cells spreading, motility, and receptors dynamics: a general framework

Reversible elastic phase field approach and application to cell monolayers

Tools for computational analysis of moving boundary problems in cellular mechanobiology

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