A dynamical model for receptor-mediated cell adhesion to surfaces

Hammer, Daniel A.; Lauffenburger, Douglas A.

doi:10.1016/s0006-3495(87)83236-8

Cited by 252 publications

(189 citation statements)

References 41 publications

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“…a Ã ¼ ð1 þ zÞðb a o À b aÞ=N is the maximum number of CE bonds in a given node at current time, where b a o ¼ 10 4 is the total number of bonded and free receptors per cell at any time (20,21), b a is the number of bonded receptors in a cell at a given time, and thus b a o À b a is the number of free receptors in the whole cell, with N ¼ 36 nodes per cell. The vertically distributed adhesion nodes on channel walls, with height z > 0, are represented by combining (1 þ z) number of nodes into one node.…”

Section: Cell-ecm Adhesion Dynamicsmentioning

confidence: 99%

Scattering of Cell Clusters in Confinement

Pathak

2016

Biophysical Journal

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Epithelial-to-mesenchymal transition (EMT) enables scattering of cell clusters and disseminates motile cells to distant locations in vivo during embryonic development and cancer metastasis. Both stiffness and topography of the extracellular matrix (ECM) have been shown to influence EMT. In this work, we examine how the integrity of epithelial cell clusters is regulated by subcellular forces, protrusions, and adhesions for varying ECM inputs, such as stiffness, topography, and dimensionality. Our model simulates multicell networks of defined sizes and shapes in ECMs of varied stiffness and geometry. The integrity of cell clusters is dictated by cell-cell junctions, which depend on subcellular forces and adhesion dynamics within each cell of the cluster. Our simulations demonstrate an enhanced dissociation of cell-cell junctions in stiffer and more confined three-dimensional (3D) environments, consistent with experimental findings. In narrow channels, the cell edges parallel to the axis of channels lose their cell-cell junctions more readily than those oriented in the perpendicular direction. The inhibition of protrusive activity and cell polarity disables confinement-dependent cell scattering. Here, cell adhesion and spreading along channel walls is found to be essential for scattering. The model also predicts that two-dimensional (2D) confinement of clusters restricts cell spreading and simultaneously blunts the confinement-sensitive cell scattering. This new, to our knowledge, multiscale model integrates molecular adhesion dynamics, subcellular forces, cellular deformation, and macroscale mechanical properties of the ECM to predict the state of cell clusters of defined shapes and sizes. The predictions made by our model not only match experimental findings from a number of experimental setups, but also provide a new conceptual framework for understanding mechanosensitive cell scattering and EMT.

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Section: Cell-ecm Adhesion Dynamicsmentioning

confidence: 99%

Scattering of Cell Clusters in Confinement

Pathak

2016

Biophysical Journal

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“…In Hammer and Lauffenburger (1987); Hammer and Apte (1992), the leukocyte is modelled as a ligand-coated rigid sphere flowing near a wall. In other works, the ligand-receptor binding follows a chemical kinetic dynamics Bell (1978); Bell et al (1984).…”

Section: Introductionmentioning

confidence: 99%

A 1D model of leukocyte adhesion coupling bond dynamics with blood velocity

Grec

Maury

Meunier

et al. 2018

Journal of Theoretical Biology

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Cell adhesion on the vascular wall is a highly coupled process where blood flow and adhesion dynamics are closely linked. Cell dynamics in the vicinity of the vascular wall is driven mechanically by the competition between the drag force of the blood flow and the force exerted by the bonds created between the cell and the wall. Bonds exert a friction force. Here, we propose a mathematical model of such a competitive system, namely leukocytes whose capacity to create bonds with the vascular wall and transmigratory ability are coupled by integrins and chemokines. The model predicts that this coupling gives rise to a dichotomic cell dynamic, whereby cells switch from rolling to firm arrest, through non linear effects. Cells can then transmigrate through the wall. These predicted dynamic regimes are compared to in-vitro trajectories of leukocytes. We expect that competition between friction and drag force in particle dynamics (such as shear stress-controlled nanoparticle capture) can lead to similar dichotomic mode.

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“…The Bell model only allows for cases where force accelerates dissociation, but it is now known that exceptions exist [6]. The second paper was a simple model of cell capture under shear flow that Doug Lauffenburger and I wrote, in which we could determine whether adhesion was controlled by kinetics (when the reaction rates were too slow) or by mechanics (when the reaction rates were fast) [7]. Finally, Micah Dembo and I, with colleagues, developed a tape peeling model of the dynamics of adhesion, in which the rate of peeling under an applied tension could be calculated from the density, strength and mechano-chemical response of the adhesion molecules [8].…”

Section: Introductionmentioning

confidence: 99%

Adhesive Dynamics

Hammer¹

2014

Journal of Biomechanical Engineering

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Adhesive dynamics (AD) is a method for simulating the dynamic response of biological systems in response to force. Biological bonds are mechanical entities that exert force under strain, and applying forces to biological bonds modulates their rate of dissociation. Since small numbers of events usually control biological interactions, we developed a simple method for sampling probability distributions for the formation or failure of individual bonds. This method allows a simple coupling between force and strain and kinetics, while capturing the stochastic response of biological systems. Biological bonds are dynamically reconfigured in response to applied mechanical stresses, and a detailed spatio-temporal map of molecules and the forces they exert emerges from AD. The shape or motion of materials bearing the molecules is easily calculated from a mechanical energy balance provided the rheology of the material is known. AD was originally used to simulate the dynamics of adhesion of leukocytes under flow, but new advances have allowed the method to be extended to many other applications, including but not limited to the binding of viruses to surface, the clustering of adhesion molecules driven by stiff substrates, and the effect of cell-cell interaction on cell capture and rolling dynamics. The technique has also been applied to applications outside of biology. A particular exciting recent development is the combination of signaling with AD (so-called integrated signaling adhesive dynamics, or ISAD), which allows facile integration of signaling networks with mechanical models of cell adhesion and motility. Potential opportunities in applying AD are summarized.

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A dynamical model for receptor-mediated cell adhesion to surfaces

Cited by 252 publications

References 41 publications

Scattering of Cell Clusters in Confinement

Scattering of Cell Clusters in Confinement

A 1D model of leukocyte adhesion coupling bond dynamics with blood velocity

Adhesive Dynamics

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