Mechanochemical Coupling and Junctional Forces during Collective Cell Migration

Bui, Justin C.; Conway, Daniel E.; Heise, Rebecca L.; Weinberg, Seth H.

doi:10.1016/j.bpj.2019.05.020

Cited by 27 publications

(33 citation statements)

References 57 publications

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“…To mimic the initial migratory stimulus through the presence of the cell-free region to which the leading cells (i.e., the first row of cells) are exposed, when the barrier is lifted, we assign an initial polarity to the leading cells to trigger their motility. This accords with the earlier studies showing that the motile force production is initiated at the first few rows of the leading edge and travels backwards into the monolayer 19,20,46 with a stable profile along the edge 47 .…”

Section: Intra-cellular Dynamicssupporting

confidence: 93%

“…Such bistable behavior has been experimentally observed in 48,49 . Thus, following the experiments 19,20,46,47 , at the onset of migration, when the barrier is removed, we set the polarity of the leading cells equal to the steady state value; see Table 1. We set the maximum motile force F max = 1000, at which according to the single cell simulations the cell velocity starts to saturate; see Fig.…”

Section: Intra-cellular Dynamicsmentioning

confidence: 99%

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Multiscale modelling of motility wave propagation in cell migration

Khataee

Neufeld

Czirók

2020

Preprint

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The collective motion of cell monolayers within a tissue is a fundamental biological process that occurs during tissue formation, wound healing, cancerous invasion, and viral infection. Experiments have shown that at the onset of migration, the motility is self-generated as a polarization wave starting from the leading edge of the monolayer and progressively propagates into the bulk. However, it is unclear how the propagation of this motility wave is influenced by cellular properties. Here, we investigate this using a computational model based on the Potts model coupled to the dynamics of intracellular polarization. The model captures the propagation of the polarization wave initiated at the leading edge and suggests that the cells cortex can regulate the migration modes: strongly contractile cells may depolarize the monolayer, whereas less contractile cells can form swirling movement. Cortical contractility is further found to limit the cells motility, which (i) decelerates the wave speed and the leading edge progression, and (ii) destabilises the leading edge into migration fingers. Together, our model describes how different cellular properties can contribute to the regulation of collective cell migration.

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Section: Intra-cellular Dynamicssupporting

confidence: 93%

Section: Intra-cellular Dynamicsmentioning

confidence: 99%

Multiscale modelling of motility wave propagation in cell migration

Khataee

Neufeld

Czirók

2020

Preprint

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“…Furthermore, a (C C C) is chosen to reflect the fact that RhoA promotes cell contraction [12,33]. We first set D 1 = D 2 = 1, and then vary the diffusivity to explore how this affects the tissue-level dynamics.…”

Section: Case Study 1: Rac-rho Pathwaymentioning

confidence: 99%

“…Rho GTPase models [12,33]. We note that the source terms in Equations (38)-(40) can be applied to a single, spatially-uniform cell to explore how the stability of the equilibria depend on model parameters [12].…”

Section: The Mechanobiological Coupling and Intracellular Signalling mentioning

confidence: 99%

“…To investigate mechanobiological coupling within epithelial tissues, the modelling framework is applied in two different case studies. The first case study involves the Rac-Rho pathway where diffusible chemicals called Rho GTPases regulate mechanical cell properties [12,[33][34][35][36][37][38]. We explicitly consider how the coupling between diffusible chemical signals and mechanical properties lead to different tissue-level outcomes, including oscillatory and non-oscillatory tissue dynamics.…”

Section: Introductionmentioning

confidence: 99%

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A free boundary mechanobiological model of epithelial tissues

Tambyah

Murphy

Buenzli

et al. 2020

Preprint

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AbstractIn this study, we couple intracellular signalling and cell–based mechanical properties to develop a novel free boundary mechanobiological model of epithelial tissue dynamics. Mechanobiological coupling is introduced at the cell level in a discrete modelling framework, and new reaction–diffusion equations are derived to describe tissue–level outcomes. The free boundary evolves as a result of the underlying biological mechanisms included in the discrete model. To demonstrate the accuracy of the continuum model, we compare numerical solutions of the discrete and continuum models for two different signalling pathways. First, we study the Rac–Rho pathway where cell- and tissue–level mechanics are directly related to intracellular signalling. Second, we study an activator–inhibitor system which gives rise to spatial and temporal patterning related to Turing patterns. In all cases, the continuum model and free boundary condition accurately reflect the cell–level processes included in the discrete model.

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Multicellular mechanochemical hybrid cellular Potts model of tissue formation during epithelial‐mesenchymal transition

2021

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Epithelial-mesenchymal transition (EMT) is the transdifferentiation of epithelial cells to a mesenchymal phenotype, in which cells lose epithelial-like cell-cell adhesions and gain mesenchymal-like enhanced contractility and mobility. EMT is crucial for tissue regeneration and is also implicated in pathological conditions, such as cancer metastasis. Prior work has shown that transforming growth factor-β1 (TGF-β1) is a potent inducer of this biological process. In this study, we develop a computational model coupling mechanical and biochemical signaling in a multicellular tissue undergoing EMT. Specifically, we utilize a recently developed formulation that integrates a multicellular cellular Potts model (CPM), a lattice-based stochastic model governing cell movement; a first moment of area model, governing cellular traction and junctional forces; a finite element model, which defines extracellular matrix (ECM) substrate strains; an intracellular signaling TGF-β1-mediated EMT model that governs cellular phenotype; and an extracellular signaling component governing ECM and TGF-β1 signaling. In this study, we modeled the spatial cellular patterns that occur in tissue and the ECM during EMT. Our model predicts that EMT often initially occurs at a tissue boundary due to mechanochemical coupling, which results in transdifferentiation to progress inwards toward the center. Variation in model parameters demonstrated conditions enhancing and suppressing EMT, especially to drive EMT in the absence of TGF-β1 and inhibit EMT in the presence of TGF-β1. Specifically, enhancing the mechanochemical feedback typically promoted EMT, whereas greater assembled ECM degradation suppressed EMT. Simulated scratch test experiments illustrate that ECM composition can impact closure directly through EMT signaling. In conclusion, we integrated mechanical, biochemical, and extracellular signaling networks in a novel hybrid computational model to reproduce tissue formation dynamics of EMT.

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Mechanochemical Coupling and Junctional Forces during Collective Cell Migration

Cited by 27 publications

References 57 publications

Multiscale modelling of motility wave propagation in cell migration

Multiscale modelling of motility wave propagation in cell migration

A free boundary mechanobiological model of epithelial tissues

Multicellular mechanochemical hybrid cellular Potts model of tissue formation during epithelial‐mesenchymal transition

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