Skip to main content
Log in

A second-order positivity preserving central-upwind scheme for chemotaxis and haptotaxis models

  • Published:
Numerische Mathematik Aims and scope Submit manuscript

Abstract

The paper is concerned with development of a new finite-volume method for a class of chemotaxis models and for a closely related haptotaxis model. In its simplest form, the chemotaxis model is described by a system of nonlinear PDEs: a convection-diffusion equation for the cell density coupled with a reaction-diffusion equation for the chemoattractant concentration. The first step in the derivation of the new method is made by adding an equation for the chemoattractant concentration gradient to the original system. We then show that the convective part of the resulting system is typically of a mixed hyperbolic-elliptic type and therefore straightforward numerical methods for the studied system may be unstable. The proposed method is based on the application of the second-order central-upwind scheme, originally developed for hyperbolic systems of conservation laws in Kurganov et al. (SIAM J Sci Comput 21:707–740, 2001), to the extended system of PDEs. We show that the proposed second-order scheme is positivity preserving, which is a very important stability property of the method. The scheme is applied to a number of two-dimensional problems including the most commonly used Keller–Segel chemotaxis model and its modern extensions as well as to a haptotaxis system modeling tumor invasion into surrounding healthy tissue. Our numerical results demonstrate high accuracy, stability, and robustness of the proposed scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Adler J.: Chemotaxis in bacteria. Ann. Rev. Biochem. 44, 341–356 (1975)

    Article  Google Scholar 

  2. Anderson A.R.A.: A hybrid mathematical model of solid tumor invasion: the importance of cell adhesion. Math. Med. Biol. IMA J. 22, 163–186 (2005)

    Article  MATH  Google Scholar 

  3. Ascher U.M., Ruuth S.J., Spiteri R.J.: Implicit-explicit Runge–Kutta methods for time-dependent partial differential equations. Special issue on time integration (Amsterdam, 1996). Appl. Numer. Math. 25, 151–167 (1997)

    MATH  MathSciNet  Google Scholar 

  4. Ascher U.M., Ruuth S.J., Wetton B.T.R.: Implicit-explicit methods for time-dependent partial differential equations. SIAM J. Numer. Anal. 32, 797–823 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  5. Ayati B.P., Webb G.F., Anderson A.R.A.: Computational methods and results for structured multiscale models of tumor invasion. Multiscale Model. Simul. 5, 1–20 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  6. Bonner J.T.: The Cellular Slime Molds, 2nd edn. Princeton University Press, Princeton (1967)

    Google Scholar 

  7. Budrene E.O., Berg H.C.: Complex patterns formed by motile cells of escherichia coli. Nature 349, 630–633 (1991)

    Article  Google Scholar 

  8. Budrene E.O., Berg H.C.: Dynamics of formation of symmetrical patterns by chemotactic bacteria. Nature 376, 49–53 (1995)

    Article  Google Scholar 

  9. Calvez V., Carrillo J.A.: Volume effects in the Keller–Segel model: energy estimates preventing blow-up. J. Math. Pures Appl. 86, 155–175 (2006)

    MATH  MathSciNet  Google Scholar 

  10. Carter S.B.: Principles of cell motility: the direction of cell movement and cancer invasion. Nature 208, 1183–1187 (1965)

    Article  Google Scholar 

  11. Carter S.B.: Haptotaxis and the mechanism of cell motility. Nature 213, 256–260 (1967)

    Article  Google Scholar 

  12. Chertock, A., Kurganov, A., Petrova, G.: Fast explicit operator splitting method for convection-diffusion equations. Int. J. Numer. Methods Fluids (2008, in press)

  13. Childress S., Percus J.K.: Nonlinear aspects of chemotaxis. Math. Biosci. 56, 217–237 (1981)

    Article  MATH  MathSciNet  Google Scholar 

  14. Cohen M.H., Robertson A.: Wave propagation in the early stages of aggregation of cellular slime molds. J. Theor. Biol. 31, 101–118 (1971)

    Article  Google Scholar 

  15. Filbet F.: A finite volume scheme for the Patlak-Keller-Segel chemotaxis model. Numer. Math. 104, 457–488 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  16. Godlewski E., Raviart P.-A.: Numerical Approximation of Hyperbolic Systems of Conservation Laws. Springer, New York (1996)

    MATH  Google Scholar 

  17. Godunov S.K.: A difference method for numerical calculation of discontinuous solutions of the equations of hydrodynamics. Mat. Sb. 47, 271–306 (1959)

    MathSciNet  Google Scholar 

  18. Gottlieb S., Shu C.-W., Tadmor E.: High order time discretization methods with the strong stability property. SIAM Rev. 43, 89–112 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  19. Herrero M.A., Velázquez J.J.L.: A blow-up mechanism for a chemotaxis model. Ann. Sc. Norm. Super. 24, 633–683 (1997)

    MATH  Google Scholar 

  20. Higueras, I., Roldán, T.: Positivity-preserving and entropy-decaying IMEX methods. In: Ninth International Conference Zaragoza-Pau on Applied Mathematics and Statistics. Monogr. Semin. Mat. Garcia Galdeano, vol. 33, pp. 129–136. Prensas University Zaragoza, Zaragoza (2006)

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

    Article  MATH  MathSciNet  Google Scholar 

  22. Horstmann D.: From 1970 until now: the Keller–Segel model in chemotaxis and its consequences I. Jahresber. DMV 105, 103–165 (2003)

    MATH  MathSciNet  Google Scholar 

  23. Horstmann D.: From 1970 until now: the Keller–Segel model in chemotaxis and its consequences II. Jahresber. DMV 106, 51–69 (2004)

    MATH  MathSciNet  Google Scholar 

  24. Hundsdorfer W., Verwer J.: Numerical solution of time-dependent advection-diffusion-reaction equations. Springer Series in Computational Mathematics, vol. 33. Springer, Berlin (2003)

    Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  28. Kröner D.: Numerical Schemes for Conservation Laws. Wiley, Chichester (1997)

    MATH  Google Scholar 

  29. Kurganov, A.: Central-upwind schemes for balance laws. Application to the Broadwell model. In: Finite Volumes for Complex Applications, III (Porquerolles, 2002), pp. 351–358. Hermes Sci. Publ., Paris (2002)

  30. Kurganov A., Levy D.: Central-upwind schemes for the Saint–Venant system. M2AN Math. Model. Numer. Anal. 36, 397–425 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  31. Kurganov A., Lin C.-T.: On the reduction of numerical dissipation in central-upwind schemes. Commun. Comput. Phys. 2, 141–163 (2007)

    MathSciNet  MATH  Google Scholar 

  32. Kurganov A., Noelle S., Petrova G.: Semi-discrete central-upwind schemes for hyperbolic conservation laws and Hamilton–Jacobi equations. SIAM J. Sci. Comput. 21, 707–740 (2001)

    Article  MathSciNet  Google Scholar 

  33. Kurganov A., Petrova G.: A second-order well-balanced positivity preserving central-upwind scheme for the Saint-Venant system. Commun. Math. Sci. 5, 133–160 (2007)

    MATH  MathSciNet  Google Scholar 

  34. Kurganov A., Tadmor E.: New high-resolution central schemes for nonlinear conservation laws and convection-diffusion equations. J. Comput. Phys. 160, 241–282 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  35. van Leer B.: Towards the ultimate conservative difference scheme, V. a second order sequel to Godunov’s method. J. Comput. Phys. 32, 101–136 (1979)

    Article  Google Scholar 

  36. LeVeque R.: Finite volume methods for hyperbolic problems. Cambridge Texts in Applied Mathematics. Cambridge University Press, London (2002)

    Google Scholar 

  37. Lie K.-A., Noelle S.: On the artificial compression method for second-order nonoscillatory central difference schemes for systems of conservation laws. SIAM J. Sci. Comput. 24, 1157–1174 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  38. Lin C.-S., Ni W.-M., Takagi I.: Large amplitude stationary solutions to a chemotaxis system. J. Differ. Equ. 72, 1–27 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  39. Manoussaki D.: A mechanochemical model of angiogenesis and vasculogenesis. M2AN Math. Model. Numer. Anal. 37, 581–599 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  40. Marrocco A.: 2D simulation of chemotaxis bacteria aggregation. M2AN Math. Model. Numer. Anal. 37, 617–630 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  41. Nanjundiah V.: Chemotaxis, signal relaying and aggregation morphology. J. Theor. Biol. 42, 63–105 (1973)

    Article  Google Scholar 

  42. Nessyahu H., Tadmor E.: Non-oscillatory central differencing for hyperbolic conservation laws. J. Comput. Phys. 87, 408–463 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  43. Pareschi L., Russo G.: Implicit-Explicit Runge–Kutta schemes and applications to hyperbolic systems with relaxation. J. Sci. Comput. 25, 129–155 (2005)

    MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  45. Perthame, B.: Transport equations in biology. Frontiers in Mathematics. Birkhäuser, Basel (2007)

  46. Prescott L.M., Harley J.P., Klein D.A.: Microbiology, 3rd edn. Wm. C. Brown Publishers, Chicago (1996)

    Google Scholar 

  47. Samarskii A.A., Gulin A.V.: Ustoichivost raznostnykh skhem (Russian) [Stability of difference schemes], 2nd edn. Editorial URSS, Moscow (2004)

    Google Scholar 

  48. Saito N.: Conservative upwind finite-element method for a simplified Keller-Segel system modelling chemotaxis. IMA J. Numer. Anal. 27, 332–365 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  49. Sweby P.K.: High resolution schemes using flux limiters for hyperbolic conservation laws. SIAM J. Numer. Anal. 21, 995–1011 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  50. 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  MathSciNet  Google Scholar 

  51. Tyson R., Lubkin S.R., Murray J.D.: A minimal mechanism for bacterial pattern formation. Proc. Roy. Soc. Lond. B 266, 299–304 (1999)

    Article  Google Scholar 

  52. Tyson R., Stern L.G., LeVeque R.J.: Fractional step methods applied to a chemotaxis model. J. Math. Biol. 41, 455–475 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  53. Walker, C., Webb, G.F.: Global Existence of classical solutions for a haptotaxis model (preprint)

  54. Woodward D., Tyson R., Myerscough M., Murray J., Budrene E., Berg H.: Spatio-temporal patterns generated by S. typhimurium. Biophys. J. 68, 2181–2189 (1995)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alina Chertock.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chertock, A., Kurganov, A. A second-order positivity preserving central-upwind scheme for chemotaxis and haptotaxis models. Numer. Math. 111, 169–205 (2008). https://doi.org/10.1007/s00211-008-0188-0

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00211-008-0188-0

Mathematics Subject Classification (2000)

Navigation