Cellular Frustration: A New Conceptual Framework for Understanding Cell-Mediated Immune Responses

  • F. Vistulo de Abreu
  • E. N. M. Nolte‘Hoen
  • C. R. Almeida
  • D. M. Davis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4163)


Here we propose that frustration within dynamic interactions between cells can provide the basis for a functional immune system. Cellular frustration arises when cells in the immune system interact through exchanges of potentially conflicting and diverse signals. This results in dynamic changes in the configuration of cells that interact. If a response such as cellular activation, apoptosis or proliferation only takes place when two cells interact for a sufficiently long and characteristic time, then tolerance can be understood as the state in which no cells reach this stage and an immune response can result from a disruption of the frustrated state. Within this framework, high specificity in immune reactions is a result of a generalized kinetic proofreading mechanism that takes place at the intercellular level. An immune reaction could be directed against any cell, but this is still compatible with maintaining perfect specific tolerance against self.


self-nonself discrimination tolerance homeostasis cellular frustration generalized kinetic proofreading 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Casal, A., Sumen, C., Reddy, T.E., Alber, M.S., Lee, P.P.: Agent-based modeling of the context dependency in T cell recognition. Journal of Theoretical Biology 236(4), 376–391 (2005)CrossRefGoogle Scholar
  2. 2.
    Leon, K., Lage, A., Carneiro, J.: Tolerance and immunity in a mathematical model of T-cell mediated suppression. Journal of Theoretical Biology 225(1), 107–126 (2003)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Chan, C., Stark, J., George, A.J.T.: The impact of multiple T cell-APC encounters and the role of anergy. J. Comp. App. Mathematics 184(1), 101–120 (2005)zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Leon, K., Perez, R., Lage, A., Carneiro, J.: Three-cell interactions in T cell-mediated suppression? A mathematical analysis of its quantitative implications. Journal of Immunology 166(9), 5356–5365 (2001)Google Scholar
  5. 5.
    Leon, K., Perez, R., Lage, A., Carneiro, J.: Modelling T-cell-mediated suppression dependent on interactions in multicellular conjugates. Journal of Theoretical Biology 207(2), 231–254 (2000)CrossRefGoogle Scholar
  6. 6.
    Perelson, A.S., Weisbuch, G.: Immunology for physicists. Reviews of Modern Physics 69(4), 1219–1267 (1997)CrossRefGoogle Scholar
  7. 7.
    Varela, F.J., Coutinho, A.: 2nd Generation Immune Networks. Immunology Today 12(5), 159–166 (1991)Google Scholar
  8. 8.
    Chao, D.L., Davenport, M.P., Forrest, S., Perelson, A.S.: A stochastic model of cytotoxic T cell responses. Journal of Theoretical Biology 228(2), 227–240 (2004)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Scherer, A., Noest, A., de Boer, R.J.: Activation-threshold tuning in an affinity model for the T-cell repertoire. Proc. Roy. Soc. B 271(1539), 609–616 (2004)CrossRefGoogle Scholar
  10. 10.
    Van Den Berg, H.A., Rand, D.A., Burroughs, N.J.: A reliable and safe T cell repertoire based on low-affinity T cell receptors. Journal of Theoretical Biology 209(4), 465–486 (2001)CrossRefGoogle Scholar
  11. 11.
    McKeithan, T.W.: Kinetic Proofreading in T-Cell Receptor Signal-Transduction. Proceedings of the National Academy of Sciences of the United States of America 92(11), 5042–5046 (1995)CrossRefGoogle Scholar
  12. 12.
    Chan, C., George, A.J.T., Stark, J.: T cell sensitivity and specificity - Kinetic proofreading revisited. Discrete and Continuous Dynamical Systems-Series B 3(3), 343–360 (2003)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Ji, Z., Dasgupta, D.: Real-Valued Negative Selection Algorithm with Variable-Sized Detectors. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 287–298. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  14. 14.
    Bersini, H., Calenbuhr, V.: Frustrated chaos in biological networks. Journal of Theoretical Biology 188(2), 187–200 (1997)CrossRefGoogle Scholar
  15. 15.
    Calenbuhr, V., Bersini, H., Stewart, J., Varela, F.J.: Natural tolerance in a simple immune network. Journal of Theoretical Biology 177 (3), 199–213 (1995)CrossRefGoogle Scholar
  16. 16.
    Almeida, C.R., de Abreu, F.V.: Dynamical instabilities lead to sympatric speciation. Evolutionary Ecology Research 5(5), 739–757 (2003)Google Scholar
  17. 17.
    Cederbom, L., Hall, H., Ivars, F.: CD4(+)CD25(+) regulatory T cells down-regulate co-stimulatory molecules on antigen-presenting cells. European Journal of Immunology 30(6), 1538–1543 (2000)CrossRefGoogle Scholar
  18. 18.
    Wykes, M., Pombo, A., Jenkins, C., MacPherson, G.G.: Dendritic cells interact directly with naive B lymphocytes to transfer antigen and initiate class switching in a primary T-dependent response. Journal of Immunology 161(3), 1313–1319 (1998)Google Scholar
  19. 19.
    Knight, S.C., Iqball, S., Roberts, M.S., Macatonia, S., Bedford, P.A.: Transfer of antigen between dendritic cells in the stimulation of primary T cell proliferation. European Journal of Immunology 28(5), 1636–1644 (1998)CrossRefGoogle Scholar
  20. 20.
    van Gisbergen, K.P., Sanchez-Hernandez, M., Geijtenbeek, T.B.H., van Kooyk, Y.: Neutrophils mediate immune modulation of dendritic cells through glycosylation-dependent interactions between Mac-1 and DC-SIGN. Journal of Experimental Medicine 201(8), 1281–1292 (2005)CrossRefGoogle Scholar
  21. 21.
    Ferlazzo, G.: Natural killer and dendritic cell liaison: recent insights and open questions. Immunology Letters 101(1), 12–17 (2005)CrossRefGoogle Scholar
  22. 22.
    Zhang, M., et al.: Splenic stroma drives mature dendritic cells to differentiate into regulatory dendritic cells. Nature Immunology 5(11), 1124–1133 (2004)CrossRefGoogle Scholar
  23. 23.
    Hanna, J., et al.: Novel APC-like properties of human NK cells directly regulate T cell activation. Journal of Clinical Investigation 114(11), 1612–1623 (2004)MathSciNetGoogle Scholar
  24. 24.
    Mekori, Y.A., Metcalfe, D.D.: Mast cell-T cell interactions. Journal of Allergy and Clinical Immunology 104(3 Pt 1), 517–523 (1999)CrossRefGoogle Scholar
  25. 25.
    Flugel, A., et al.: Neuronal FasL induces cell death of encephalitogenic T lymphocytes. Brain Pathology 10(3), 353–364 (2000)CrossRefGoogle Scholar
  26. 26.
    Thornton, A.M., Shevach, M.E.: CD4(+)CD25(+) immunoregulatory T cells suppress polyclonal T cell activation in vitro by inhibiting interleukin 2 production. Journal of Experimental Medicine 188(2), 287–296 (1998)CrossRefGoogle Scholar
  27. 27.
    Taams, L.S., et al.: Modulation of monocyte/macrophage function by human CD4+CD25+ regulatory T cells. Human Immunology 66(3), 222–230 (2005)CrossRefGoogle Scholar
  28. 28.
    Nolte-’t Hoen, E.N., et al.: Uptake of membrane molecules from T cells endows antigen-presenting cells with novel functional properties. European Journal of Immunology 34(11), 3115–3125 (2004)CrossRefGoogle Scholar
  29. 29.
    Taams, L.S., et al.: Anergic T cells actively suppress T cell responses via the antigen-presenting cell. European Journal of Immunology 28(9), 2902–2912 (1998)CrossRefGoogle Scholar
  30. 30.
    Huang, J.F., et al.: TCR-Mediated internalization of peptide-MHC complexes acquired by T cells. Science 286(5441), 952–954 (1999)CrossRefGoogle Scholar
  31. 31.
    Gunzer, M., et al.: Antigen presentation in extracellular matrix: interactions of T cells with dendritic cells are dynamic, short lived, and sequential. Immunity 13(3), 323–332 (2000)CrossRefGoogle Scholar
  32. 32.
    Mempel, T.R., Henrickson, S.E., Von Andrian, U.H.: T-cell priming by dendritic cells in lymph nodes occurs in three distinct phases. Nature 427(6970), 154–159 (2004)CrossRefGoogle Scholar
  33. 33.
    Depoil, D., et al.: Immunological synapses are versatile structures enabling selective T cell polarization. Immunity 22(2), 185–194 (2005)CrossRefGoogle Scholar
  34. 34.
    Eissner, G., Kolch, W., Scheurich, P.: Ligands working as receptors: reverse signaling by members of the TNF superfamily enhance the plasticity of the immune system. Cytokine Growth Factor Rev 15, 353–366 (2004)CrossRefGoogle Scholar
  35. 35.
    Lehner, M., et al.: MHC class II antigen signaling induces homotypic and heterotypic cluster formation of human mature monocyte derived dendritic cells in the absence of cell death. Human Immunology 64(8), 762–770 (2003)CrossRefGoogle Scholar
  36. 36.
    Lokshin, A.E., et al.: Differential regulation of maturation and apoptosis of human monocyte-derived dendritic cells mediated by MHC class II. International Immunology 14(9), 1027–1037 (2002)CrossRefGoogle Scholar
  37. 37.
    Walzer, T., et al.: Natural-killer cells and dendritic cells: l’union fait la force. Blood 106(7), 2252–2258 (2005)CrossRefGoogle Scholar
  38. 38.
    Gett, A.V., et al.: T cell fitness determined by signal strength. Nature Immunology 4(4), 355–360 (2003)CrossRefGoogle Scholar
  39. 39.
    Iezzi, G., Karjalainen, K., Lanzavecchia, A.: The duration of antigenic stimulation determines the fate of naive and effector T cells. Immunity 8(1), 89–95 (1998)CrossRefGoogle Scholar
  40. 40.
    Iezzi, G., et al.: The interplay between the duration of TCR and cytokine signaling determines T cell polarization. European Journal Immunology 29(12), 4092–4101 (1999)CrossRefGoogle Scholar
  41. 41.
    Wulfing, C., et al.: Stepwise cytoskeletal polarization as a series of checkpoints in innate but not adaptive cytolytic killing. Proc. Natl. Acad. Sci. U S A 100(13), 7767–7772 (2003)CrossRefGoogle Scholar
  42. 42.
    Davis, D.M.: Assembly of the immunological synapse for T cells and NK cells. Trends in Immunology 23(7), 356–363 (2002)CrossRefGoogle Scholar
  43. 43.
    Davis, D.M., Dustin, M.L.: What is the importance of the immunological synapse? Trends in Immunology 25(6), 323–327 (2004)CrossRefGoogle Scholar
  44. 44.
    Gusfield, D., Irving, R.W.: The stable marriage problem: structure and algorithms. MIT Press, Cambridge (1989)zbMATHGoogle Scholar
  45. 45.
    Mertens, S.: Computational complexity for physicists. Computing in Science and Engineering 4(3), 31–47 (2002)CrossRefGoogle Scholar
  46. 46.
    Hopfield, J.J.: Kinetic proofreading – new mechanism for reducing errors in biosynthetic processes requiring high specificity. Proc. Natl. Acad. Sci. U S A 71(10), 4135–4139 (1974)CrossRefGoogle Scholar
  47. 47.
    Ninio, J.: Kinetic amplification of enzyme discrimination. Biochimie 57(5), 587–595 (1975)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • F. Vistulo de Abreu
    • 1
    • 2
  • E. N. M. Nolte‘Hoen
    • 2
    • 3
  • C. R. Almeida
    • 2
  • D. M. Davis
    • 2
  1. 1.Depto. FísicaUniversidade de AveiroAveiroPortugal
  2. 2.Division of Cell and Molecular BiologyImperial CollegeLondonUK
  3. 3.Department of Biochemistry and Cell BiologyUtrecht UniversityThe Netherlands

Personalised recommendations