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A Diffuse Interface Framework for Modeling the Evolution of Multi-cell Aggregates as a Soft Packing Problem Driven by the Growth and Division of Cells

  • Special Issue: Multiscale Modeling of Tissue Growth and Shape
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Abstract

We present a model for cell growth, division and packing under soft constraints that arise from the deformability of the cells as well as of a membrane that encloses them. Our treatment falls within the framework of diffuse interface methods, under which each cell is represented by a scalar phase field and the zero level set of the phase field represents the cell membrane. One crucial element in the treatment is the definition of a free energy density function that penalizes cell overlap, thus giving rise to a simple model of cell–cell contact. In order to properly represent cell packing and the associated free energy, we include a simplified representation of the anisotropic mechanical response of the underlying cytoskeleton and cell membrane through penalization of the cell shape change. Numerical examples demonstrate the evolution of multi-cell clusters and of the total free energy of the clusters as a consequence of growth, division and packing.

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Notes

  1. In some simulations, a buffer zone, \(\Omega ^{'}\), is needed around the simulation domain to inhibit unrealistic cell shapes resulting from the enforcement of \(\kappa {\varvec{\nabla }} c_k \cdot {\varvec{n}}= 0\) on \(\partial \Omega \). In addition, this buffer zone also acts as a membrane around the cell cluster. In the buffer zone, an additional term of the form \(\sum _{k=1}^{N}\lambda c_k^2\) is added to the free energy density to penalize the movement of any cells from the active simulation domain (\(\Omega \)) to the buffer zone (\(\Omega ^{'}\)).

  2. In this initial boundary value problem, \(\partial \Omega \) is composed of only a Neumann (flux) boundary (\(\partial \Omega ^{h} = \partial \Omega \)) and hence the Dirichlet boundary is a null set (\(\partial \Omega ^{g} = \varnothing \)).

References

  • Allen SM, Cahn JW (1979) A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening. Acta Metall 27(6):1085–1095

    Article  Google Scholar 

  • Alt S, Ganguly P, Salbreux G (2017) Vertex models: from cell mechanics to tissue morphogenesis. Philos Trans R Soc Lond B Biol Sci 372(1720):20150520

    Article  Google Scholar 

  • Bangerth W, Hartmann R, Kanschat G (2007) deal. II—a general purpose object oriented finite element library. ACM Trans Math Softw 33(4):24/1–24/27

    Article  MathSciNet  MATH  Google Scholar 

  • Brezzi F, Fortin M (1991) Mixed and hybrid finite element methods. Springer, Berlin

    Book  MATH  Google Scholar 

  • Brodland GW (2004) Computational modeling of cell sorting, tissue engulfment, and related phenomena: a review. Appl Mech Rev 57:47–76

    Article  Google Scholar 

  • Cahn JW, Hilliard JE (1958) Free energy of a nonuniform system. I. Interfacial free energy. J Chem Phys 28(2):258–267

    Article  Google Scholar 

  • Fletcher A, Osterfield M, Baker RE, Shvartsman SY (2014) Vertex models of epithelial morphogenesis. Biophys J 106(11):2291–2304

    Article  Google Scholar 

  • Gilbert SF (2000) Developmental biology, 6th edn. Sinauer Associates, Sunderland

    Google Scholar 

  • Glazier JA, Graner F (1993) Simulation of the differential adhesion driven rearrangement of biological cells. Phys Rev E 47:2128–2154

    Article  Google Scholar 

  • Goel NS, Rogers G (1978) Computer simulation of engulfment and other movements of embryonic tissues. J Theor Biol 71(1):103–140

    Article  Google Scholar 

  • Goel N, Campbell RD, Gordon R, Rosen R, Martinez H, Yaas M (1970) Self-sorting of isotropic cells. J Theor Biol 28(3):423–468

    Article  Google Scholar 

  • Graner F (1993) Can surface adhesion drive cell-rearrangement? Part I: biological cell-sorting. J Theor Biol 164(4):455–476

    Article  Google Scholar 

  • Graner F, Glazier JA (1992) Simulation of biological cell sorting using a two-dimensional extended Potts model. Phys Rev Lett 69:2013–2016

    Article  Google Scholar 

  • Heroux M, Bartlett R, Hoekstra VHR, Hu J, Kolda T, Lehoucq R, Long K, Pawlowski R, Phipps E, Salinger A, Thornquist H, Tuminaro R, Willenbring J, Williams A (2003) An overview of Trilinos. Technical report SAND2003-2927, Sandia National Laboratories

  • Honda H (1978) Description of cellular patterns by Dirichlet domains: the two-dimensional case. J Theor Biol 72(3):523–543

    Article  MathSciNet  Google Scholar 

  • Honda H (1983) Geometrical models for cells in tissues. Int Rev Cytol 81:191–248

    Article  Google Scholar 

  • Honda H, Yamanaka H, Eguchi G (1986) Transformation of a polygonal cellular pattern during sexual maturation of the avian oviduct epithelium: computer simulation. Development 98(1):1–19

    Google Scholar 

  • Itskovitz-Eldor J, Schuldiner M, Karsenti D, Eden A, Yanuka O, Amit M, Soreq H, Benvenisty N (2000) Differentiation of human embryonic stem cells into embryoid bodies compromising the three embryonic germ layers. Mol Med 6(2):88

    Article  Google Scholar 

  • Kamrin K, Rycroft CH, Nave JC (2012) Reference map technique for finite-strain elasticity and fluid–solid interaction. J Mech Phys Solids 60(11):1952–1969

    Article  MathSciNet  Google Scholar 

  • Li XS (2005) An overview of SuperLU: algorithms, implementation, and user interface. ACM Trans Math Softw 31(3):302–325

    Article  MathSciNet  MATH  Google Scholar 

  • Mills KL, Kemkemer R, Rudraraju S, Garikipati K (2014) Elastic free energy drives the shape of prevascular solid tumors. PloS ONE 9(7):e103245

    Article  Google Scholar 

  • Mirams GR, Arthurs CJ, Bernabeu MO, Bordas R, Cooper J, Corrias A, Davit Y, Dunn S-J, Fletcher AG, Harvey DG et al (2013) Chaste: an open source C++ library for computational physiology and biology. PLoS Comput Biol 9(3):e1002970

    Article  MathSciNet  Google Scholar 

  • Mochizuki A, Wada N, Ide H, Iwasa Y (1998) Cell-cell adhesion in limb formation, estimated from photographs of cell sorting experiments based on a spatial stochastic model. Dev Dyn 211(3):204–214

    Article  Google Scholar 

  • Mosaffa P, Asadipour N, Millán D, Rodríguez-Ferran A, Muñoz JJ (2015) Cell-centred model for the simulation of curved cellular monolayers. Comput Part Mech 2(4):359–370

    Article  Google Scholar 

  • Mosaffa P, Rodríguez-Ferran A, Muñoz JJ (2017) Hybrid cell-centred/vertex model for multicellular systems with equilibrium preserving remodelling. Int J Numer Methods Biomed Eng 34(3):e2928

    Article  MathSciNet  Google Scholar 

  • Nonomura M (2012) Study on multicellular systems using a phase field model. PLOS ONE 7(4):1–904

    Article  Google Scholar 

  • Reya T, Morrison SJ, Clarke MF, Weissman IL (2001) Stem cells, cancer, and cancer stem cells. Nature 414(6859):105

    Article  Google Scholar 

  • Rudraraju S, Mills KL, Kemkemer R, Garikipati K (2013) Multiphysics modeling of reactions, mass transport and mechanics of tumor growth. In: Holzapfel G, Kuhl E (eds) Computer models in biomechanics. Springer, Dordrecht, pp 293–303

    Chapter  Google Scholar 

  • Schierenberg E (2006) Embryological variation during nematode development (2 Jan 2006), WormBook, ed. The C. elegans Research Community, WormBook

  • Swat MH, Thomas GL, Belmonte JM, Shirinifard A, Hmeljak D, Glazier JA (2012) Multi-scale modeling of tissues using compucell3d. In: Asthagiri AR, Arkin AP (eds) Methods in cell biology, vol 110. Elsevier, Amsterdam, pp 325–366

    Chapter  Google Scholar 

  • Vedantam S, Patnaik BSV (2006) Efficient numerical algorithm for multiphase field simulations. Phys Rev E 73(1):016703

    Article  Google Scholar 

  • Verner SN, Garikipati K (2018) A computational study of the mechanisms growth-driven folding patterns on shells, with application to the developing brain. Extreme Mech Lett 18:58–69

    Article  Google Scholar 

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Jiang, J., Garikipati, K. & Rudraraju, S. A Diffuse Interface Framework for Modeling the Evolution of Multi-cell Aggregates as a Soft Packing Problem Driven by the Growth and Division of Cells. Bull Math Biol 81, 3282–3300 (2019). https://doi.org/10.1007/s11538-019-00577-1

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