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A new interpretation of the Keller-Segel model based on multiphase modelling

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Abstract.

In this paper an alternative derivation and interpretation are presented of the classical Keller-Segel model of cell migration due to random motion and chemotaxis. A multiphase modelling approach is used to describe how a population of cells moves through a fluid containing a diffusible chemical to which the cells are attracted. The cells and fluid are viewed as distinct components of a two-phase mixture. The principles of mass and momentum balance are applied to each phase, and appropriate constitutive laws imposed to close the resulting equations. A key assumption here is that the stress in the cell phase is influenced by the concentration of the diffusible chemical.

By restricting attention to one-dimensional cartesian geometry we show how the model reduces to a pair of nonlinear coupled partial differential equations for the cell density and the chemical concentration. These equations may be written in the form of the Patlak-Keller-Segel model, naturally including density-dependent nonlinearities in the cell motility coefficients. There is a direct relationship between the random motility and chemotaxis coefficients, both depending in an inter-related manner on the chemical concentration. We suggest that this may explain why many chemicals appear to stimulate both chemotactic and chemokinetic responses in cell populations.

After specialising our model to describe slime mold we then show how the functional form of the chemical potential that drives cell locomotion influences the ability of the system to generate spatial patterns. The paper concludes with a summary of the key results and a discussion of avenues for future research.

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References

  1. Advani, S.G.: Flow and rheology in polymeric composites manufacturing. Elsevier, 1994

  2. Alt, W.: Biased random walk models for chemotaxis and related diffusion approximations. J. Math. Biol 9, 147–177 (1980)

    MathSciNet  MATH  Google Scholar 

  3. Serini, G., Ambrosi, D., Giraudo, E., Gamba, A., Preziosi, L., Bussolini, F.: Modeling the early stages of vascular network assembly. EMBO J. 22, 1771–1779 (2003)

    Article  Google Scholar 

  4. Anderson, A.R.A., Chaplain, M.A.J.: Continuous and discrete mathematical models of tumour-induced angiogenesis. Bull. Math. Biol. 60, 857–899 (1998)

    Article  MATH  Google Scholar 

  5. Barker, M.K., Seedhom, B.B.: Articular cartilage deformation under physiological cycling loading. J. Biomech 30, 377–381 (1997)

    Article  Google Scholar 

  6. Bearon, R.N., Pedley, T.J.: Modelling run-and-tumble chemotaxis in a shear flow. Bull. Math. Biol. 62, 775–791 (2000)

    Article  Google Scholar 

  7. Bennet, N.T., Schultz, G.S.: Growth factors and wound healing: Part II role in normal and chronic wound healing. Am. J. Surgery 166, 74–81 (1993)

    Google Scholar 

  8. Boyden, S.V.: The chemotactic effect of mixtures of antibody and antigen on polymorphonuclear leukocytes. J. Exp. Med. 115, 453–466 (1962)

    Article  Google Scholar 

  9. Bray, D.: Cell movements: from molecules to motility. Garland Publishing, 2001

  10. Breward, C.J.W., Byrne, H.M., Lewis, C.E.: The role of cell-cell interactions in a two-phase of solid tumor growth. J. Math. Biol. 45, 125–152 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  11. Buettner, H.M., Lauffenburger, D.A., Zigmond, S.H.: Measurement of leukocyte motility and chemotaxis parameters with the Millipore filter assay. J. Immunol. Meth. 123, 25–37 (1989)

    Article  Google Scholar 

  12. Byrne, H.M., Cave, G., McElwain, D.L.S.: The effects of chemokinesis on leukocyte locomotion: a new interpretation of experimental results. IMA J. Math. Appl. Med. Biol. 15, 235–256 (1998)

    MATH  Google Scholar 

  13. Byrne, H.M., King, J.R., McElwain, D.L.S., Preziosi, L.: A two-phase model of solid tumor growth. Appl. Math. Lett. 16, 567–573 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  14. Byrne, H.M., Preziosi, L.: Modelling solid tumor growth using the theory of mixtures. IMA J. Math. Appl. Med. Biol. 20, 341–366 (2003)

    MATH  Google Scholar 

  15. Dallon, J.C., Othmer, H.G.: A discrete cell model with adaptive signalling for aggregation of Dictyostelium discoideum. Phil. Trans Roy. Soc. B 352, 391–417 (1997)

    Article  Google Scholar 

  16. Drew, D.A., Segel, L.A.: Averaged equations for two-phase flows. Stud. Appl. Math. 50, 205–231 (1971)

    MATH  Google Scholar 

  17. Early, A., Abe, T., William, J.: Evidence for positional differentiation of prestalk cells and for a morphogenetic gradient in dictyostelium. Cell 83, 91–99 (1995)

    Article  Google Scholar 

  18. Farina, A., Preziosi, L.: Deformable porous media and composites manufacturing. In: Heterogeneous Media: Micromechanics, Modelling, Methods and Simulations, Markov, M., Preziosi, L. (eds.), Birkhäuser, 2000

  19. Folkman, J., Brem, H.: Angiogenesis and inflammation. In: Inflammation: Basic Principles and Clinical Correlates, Second Edition. Gallin, J.I., Goldstein, I.M. and Dnyderman, R. (eds.), New York, Raven Press, 1992

  20. Fowler, A.C.: Mathematical models in the applied sciences. Cambridge University Press, Cambridge, 1997

  21. Franks, S.J.: Mathematical modelling of tumour growth and stability. PhD thesis, University of Nottingham, England, 2001

  22. Franks, S.J., King, J.R.: Interactions between a uniformly proliferating tumour and its surroundings: uniform material properties. IMA J. Math. Med. Biol., 2003 (submitted)

  23. Fung, Y.C.: Biomechanics: motion, flow, stress and growth. Spinger-Verlag, New York, 1990

  24. Gamba, A., Ambrosi, D., Coniglio, A., de Candia, A., di Talia, S., Giraudo, E., Serini, G., Preziosi, L., Bussolini, F.: Percolation, morphogenesis, and Burgers dynamics in blood vessel formation. Phys. Rev. Lett. 90 (11), 118101 (2003)

    Article  Google Scholar 

  25. Haddox, J.L., Pfister, R.R., Sommers, C.I.: A visual assay for quantitating neutrophil chemotaxis in a collagen gel matrix. J. Immunol. Meth. 141, 41–52 (1991)

    Article  Google Scholar 

  26. Hader, D.P.: Polarotaxis, gravitaxis and vertical phototaxis in the green flagellate, Euglena-gracilis. Arch. Microbiol. 147, 179–183 (1987)

    Article  Google Scholar 

  27. Hill, N.A., Plumpton, L.A.: Control strategies for the polarotactic orientation of the microorganism Euglena gracilis. J. Theor. Biol. 203, 357–365 (2000)

    Article  Google Scholar 

  28. Hillen, T., Painter, K.: Global existence for a parabolic chemotaxis model with prevention of overcrowding. Adv. Appl. Math. 26, 280–301 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  29. Horstmann, D.: Lyapunov functions and Lp-estimates for a class of reaction-diffusion systems. Coll. Math. 87, 113–127 (2001)

    MathSciNet  MATH  Google Scholar 

  30. Hou, J.S., Holmes, M.H., Lai, W.M., Mow, V.C.: Boundary conditions at the cartilage-synovial fluid interface for joint lubrication and theoretical verifications. J. Biomech. Eng. 111, 78–87 (1989)

    Google Scholar 

  31. Jackson, T.J., Byrne, H.M.: A mathematical model of tumour encapsulation. Math. Biosci. 180, 307–328 (2002)

    MathSciNet  MATH  Google Scholar 

  32. Keller, E.F., Segel, L.A.: Initiation of slime mold aggregation viewed as an instability. J. Theor. Biol. 26, 399–415 (1970)

    Google Scholar 

  33. Keller, E.F., Segel, L.A.: Model for chemotaxis. J. Theor. Biol. 30, 225–234 (1971a)

    Google Scholar 

  34. Keller, E.F., Segel, L.A.: Travelling bands of chemotactic bacteria: a theoretical analysis J. Theor. Biol. 30, 235–248 (1971b)

    Google Scholar 

  35. Keller, E.F.: Assessing the Keller-Segel model: how has it fared? In: Biological growth and spread, Jager, W., Rost, H. and Tautu, P. (eds.), Lecture Notes in Biomathematics, 38, Berlin, Springer-Verlag, 1980, pp. 379–387

  36. King, J.R., Franks, S.J.: Mathematical analysis of some multi-dimensional tissue growth models. Eur. J. Appl. Maths., 2003 (in press)

  37. Lai, W.M., Hou, J.S., Mow, V.C.: A triphasic theory for the swelling and deformation behaviours of articular cartilage. J. Biomech. Eng. 113, 245–258 (1991)

    Google Scholar 

  38. Landman, K., Please, C.P.: Tumor dynamics and necrosis: Surface tension and stability. IMA J. Maths. Appl. Med. Biol. 18, 131–158 (2001)

    MATH  Google Scholar 

  39. Lega, J., Passot, T.: Hydrodynamics of bacterial colonies: a model. Phys. Rev. E 67(3), 31906 (2003)

    Article  Google Scholar 

  40. Lubkin, S.R., Jackson, T.: Multiphase mechanics of capsule formation in tumours. J. Biomech. Eng. 124, 237–243 (2002)

    Article  Google Scholar 

  41. Mow, V.C., Lai, W.M.: Mechanics of animal joints. Annu. Rev. Fluid Mech. 11, 247–288 (1979)

    Article  MATH  Google Scholar 

  42. Murray, J.D.: Mathematical Biology. Springer-Verlag, New York, 1989

  43. Nicholson, C.: Diffusion from an injected volume of a substance in brain tissues with arbitrary volume fraction and tortuosity. Brain Res. 333, 325–329 (1985)

    Article  Google Scholar 

  44. Othmer, H.G., Stevens, A.: Aggregation, blowup and collapse: the ABCs of taxis in reinforced random walks. SIAM J. Appl. Math. 57, 1041–1081 (1997)

    Article  Google Scholar 

  45. Owen, M.R., Sherratt, J.A.: Pattern formation and spatiotemporal irregularity in a model for macrophage-tumour interactions. J. Theor. Biol. 189, 63–80 (1997)

    Article  Google Scholar 

  46. Painter, K.J., Hillen, T.: Volume-filling and quorum-sensing in models for chemosensitive movement. Can. App. Math. Quart., 2003 to appear

  47. Patlak, C.: Random walk with persistence and external bias. Bull. Math. Biophys. 15, 311–338 (1953)

    MathSciNet  Google Scholar 

  48. Please, C.P., Pettet, G., McElwain, D.L.S.: A new approach to modelling the formation of necrotic regions in tumors, Appl. Math. Lett. 11, 89–94 (1998)

    Article  MATH  Google Scholar 

  49. Primicerio, M., Zaltzman, B.: A free boundary problem arising in chemotaxis. Adv. Math. Sci. Appl. 12, 685–708 (2002)

    MathSciNet  MATH  Google Scholar 

  50. Primicerio, M., Zaltzman, B.: Free boundary in radial-symmetric chemotaxis Proceedings WASCOM 2001, World Scientific, 2002

  51. Segel, L.A.: A theoretical study of receptor mechanisms in bacterial chemotaxis. SIAM J. Appl. Math. 32, 653–665 (1977)

    MATH  Google Scholar 

  52. Sherratt, J.A., Sage, E.H., Murray, J.D.: Chemical Control of Eukaryotic Cell Movement: A New Model. J. Theor. Biol. 162, 23–40 (1993)

    Article  Google Scholar 

  53. Sleeman, B.D., Levine, H.A.: A system of reaction diffusion equations arising in the theory of reinforced random walks. SIAM J. Appl. Math. 57, 683–730 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  54. Sorek, S., Sideman, S.: A porous medium approach for modelling heart mechanics: Part 1 theory. Math. Biosci. 81, 1–14 (1986)

    Article  MATH  Google Scholar 

  55. Spencer, A.J.M.: Deformations of fibre-reinforced materials. Clarendon Press, 1972

  56. Spencer, A.J.M.: Continuum theory of the mechanics of fibre-reinforced composites. Springer Verlag, 1984

  57. Stevens, A.: The derivation of chemotaxis equations as limit dynamics of moderately interacting stochastic many-particle systems. SIAM J. Appl. Math. 61, 183–212 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  58. Stokes, C.I., Lauffenburger, D.A.: Analysis of the roles of microvessel endothelial cell random motility and chemotaxis in angiogenesis. J. Theor. Biol. 152, 377–403 (1991)

    Google Scholar 

  59. Tyson, R., Lubkin, S.R., Murray, J.D.: Model and analysis of chemotactic bacterial patterns in a liquid medium, J. Math. Biol. 38, 359–375 (1999)

    Article  MATH  Google Scholar 

  60. Turing, A.M.: The chemical basis of morphogenesis. Phil. Trans. Roy. Soc. Lond. B237, 37–72 (1952)

    Google Scholar 

  61. Ward, J.P., King, J.R.: Mathematical modelling of avascular-tumour growth. IMA. J. Math. Appl. Med. 14, 39–69 (1997)

    MATH  Google Scholar 

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Byrne, H., Owen, M. A new interpretation of the Keller-Segel model based on multiphase modelling. J. Math. Biol. 49, 604–626 (2004). https://doi.org/10.1007/s00285-004-0276-4

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  • DOI: https://doi.org/10.1007/s00285-004-0276-4

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