The moving boundary node method: A level set-based, finite volume algorithm with applications to cell motility

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

Eukaryotic cell crawling is a highly complex biophysical and biochemical process, where deformation and motion of a cell are driven by internal, biochemical regulation of a poroelastic cytoskeleton. One challenge to built quantitative models that describe crawling cells is solving the reaction-diffusion-advection dynamics for the biochemical and cytoskeletal components of the cell inside its moving and deforming geometry. Here we develop an algorithm that uses the level set method to move the cell boundary and uses information stored in the distance map to construct a finite volume representation of the cell. Our method preserves Cartesian connectivity of nodes in the finite volume representation while resolving the distorted cell geometry. Derivatives approximated using a Taylor series expansion at finite volume interfaces lead to second order accuracy even on highly distorted quadrilateral elements. A modified, Laplacian-based interpolation scheme is developed that conserves mass while interpolating values onto nodes that join the cell interior as the boundary moves. An implicit time stepping algorithm is used to maintain stability. We use the algorithm to simulate two simple models for cellular crawling. The first model uses depolymerization of the cytoskeleton to drive cell motility and suggests that the shape of a steady crawling cell is strongly dependent on the adhesion between the cell and the substrate. In the second model, we use a model for chemical signalling during chemotaxis to determine the shape of a crawling cell in a constant gradient and to show cellular response upon gradient reversal.

Original languageEnglish (US)
Pages (from-to)7287-7308
Number of pages22
JournalJournal of Computational Physics
Volume229
Issue number19
DOIs
StatePublished - Sep 2010
Externally publishedYes

Fingerprint

locomotion
cells
Depolymerization
Taylor series
Geometry
Information use
Advection
Interpolation
Adhesion
Derivatives
depolymerization
Substrates
gradients
geometry
advection
series expansion
interpolation
adhesion

Keywords

  • Cell motility
  • Diffusion
  • Finite volume
  • Level set
  • Moving boundaries
  • Numeric method

ASJC Scopus subject areas

  • Computer Science Applications
  • Physics and Astronomy (miscellaneous)

Cite this

The moving boundary node method : A level set-based, finite volume algorithm with applications to cell motility. / Wolgemuth, Charles William; Zajac, Mark.

In: Journal of Computational Physics, Vol. 229, No. 19, 09.2010, p. 7287-7308.

Research output: Contribution to journalArticle

@article{8106224d4e9e408e917124a74861c3ac,
title = "The moving boundary node method: A level set-based, finite volume algorithm with applications to cell motility",
abstract = "Eukaryotic cell crawling is a highly complex biophysical and biochemical process, where deformation and motion of a cell are driven by internal, biochemical regulation of a poroelastic cytoskeleton. One challenge to built quantitative models that describe crawling cells is solving the reaction-diffusion-advection dynamics for the biochemical and cytoskeletal components of the cell inside its moving and deforming geometry. Here we develop an algorithm that uses the level set method to move the cell boundary and uses information stored in the distance map to construct a finite volume representation of the cell. Our method preserves Cartesian connectivity of nodes in the finite volume representation while resolving the distorted cell geometry. Derivatives approximated using a Taylor series expansion at finite volume interfaces lead to second order accuracy even on highly distorted quadrilateral elements. A modified, Laplacian-based interpolation scheme is developed that conserves mass while interpolating values onto nodes that join the cell interior as the boundary moves. An implicit time stepping algorithm is used to maintain stability. We use the algorithm to simulate two simple models for cellular crawling. The first model uses depolymerization of the cytoskeleton to drive cell motility and suggests that the shape of a steady crawling cell is strongly dependent on the adhesion between the cell and the substrate. In the second model, we use a model for chemical signalling during chemotaxis to determine the shape of a crawling cell in a constant gradient and to show cellular response upon gradient reversal.",
keywords = "Cell motility, Diffusion, Finite volume, Level set, Moving boundaries, Numeric method",
author = "Wolgemuth, {Charles William} and Mark Zajac",
year = "2010",
month = "9",
doi = "10.1016/j.jcp.2010.06.014",
language = "English (US)",
volume = "229",
pages = "7287--7308",
journal = "Journal of Computational Physics",
issn = "0021-9991",
publisher = "Academic Press Inc.",
number = "19",

}

TY - JOUR

T1 - The moving boundary node method

T2 - A level set-based, finite volume algorithm with applications to cell motility

AU - Wolgemuth, Charles William

AU - Zajac, Mark

PY - 2010/9

Y1 - 2010/9

N2 - Eukaryotic cell crawling is a highly complex biophysical and biochemical process, where deformation and motion of a cell are driven by internal, biochemical regulation of a poroelastic cytoskeleton. One challenge to built quantitative models that describe crawling cells is solving the reaction-diffusion-advection dynamics for the biochemical and cytoskeletal components of the cell inside its moving and deforming geometry. Here we develop an algorithm that uses the level set method to move the cell boundary and uses information stored in the distance map to construct a finite volume representation of the cell. Our method preserves Cartesian connectivity of nodes in the finite volume representation while resolving the distorted cell geometry. Derivatives approximated using a Taylor series expansion at finite volume interfaces lead to second order accuracy even on highly distorted quadrilateral elements. A modified, Laplacian-based interpolation scheme is developed that conserves mass while interpolating values onto nodes that join the cell interior as the boundary moves. An implicit time stepping algorithm is used to maintain stability. We use the algorithm to simulate two simple models for cellular crawling. The first model uses depolymerization of the cytoskeleton to drive cell motility and suggests that the shape of a steady crawling cell is strongly dependent on the adhesion between the cell and the substrate. In the second model, we use a model for chemical signalling during chemotaxis to determine the shape of a crawling cell in a constant gradient and to show cellular response upon gradient reversal.

AB - Eukaryotic cell crawling is a highly complex biophysical and biochemical process, where deformation and motion of a cell are driven by internal, biochemical regulation of a poroelastic cytoskeleton. One challenge to built quantitative models that describe crawling cells is solving the reaction-diffusion-advection dynamics for the biochemical and cytoskeletal components of the cell inside its moving and deforming geometry. Here we develop an algorithm that uses the level set method to move the cell boundary and uses information stored in the distance map to construct a finite volume representation of the cell. Our method preserves Cartesian connectivity of nodes in the finite volume representation while resolving the distorted cell geometry. Derivatives approximated using a Taylor series expansion at finite volume interfaces lead to second order accuracy even on highly distorted quadrilateral elements. A modified, Laplacian-based interpolation scheme is developed that conserves mass while interpolating values onto nodes that join the cell interior as the boundary moves. An implicit time stepping algorithm is used to maintain stability. We use the algorithm to simulate two simple models for cellular crawling. The first model uses depolymerization of the cytoskeleton to drive cell motility and suggests that the shape of a steady crawling cell is strongly dependent on the adhesion between the cell and the substrate. In the second model, we use a model for chemical signalling during chemotaxis to determine the shape of a crawling cell in a constant gradient and to show cellular response upon gradient reversal.

KW - Cell motility

KW - Diffusion

KW - Finite volume

KW - Level set

KW - Moving boundaries

KW - Numeric method

UR - http://www.scopus.com/inward/record.url?scp=77955267573&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77955267573&partnerID=8YFLogxK

U2 - 10.1016/j.jcp.2010.06.014

DO - 10.1016/j.jcp.2010.06.014

M3 - Article

AN - SCOPUS:77955267573

VL - 229

SP - 7287

EP - 7308

JO - Journal of Computational Physics

JF - Journal of Computational Physics

SN - 0021-9991

IS - 19

ER -