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Control Engineering and Systems Biology

  • Burton W. Andrews
  • Pablo A. Iglesias
Chapter
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 367)

Abstract

Engineers use feedback, both positive and negative, to perform a wide array of signaling functions. Biological systems are also faced with many of the same requirements In this tutorial we examine examples from different cellular signaling systems to show how biology also uses feedback paths to perform many of the same tasks.

Keywords

Nerve Growth Factor System Biology Control Engineering Feedback Gain MAPK Cascade 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Hartwell, L.H., Hopfield, J.J., Leibler, S., Murray, A.W.: From molecular to modular cell biology. Nature 402, 47–52 (1999)CrossRefGoogle Scholar
  2. 2.
    Pollard, T.D.: The cytoskeleton, cellular motility and the reductionist agenda. Nature 422, 741–745 (2003)CrossRefGoogle Scholar
  3. 3.
    Ideker, T., Galitski, T., Hood, L.: A new approach to decoding life: Systems biology. Annu. Rev. Genomics Hum. Genet. 2, 343–372 (2001)CrossRefGoogle Scholar
  4. 4.
    Kitano, H.: Systems biology: A brief overview. Science 295, 1662–1664 (2002)CrossRefGoogle Scholar
  5. 5.
    Wiener, N.: Cybernetics or Control and Communication in the Animal and the Machine, 2nd edn. MIT Press, New York (1961)zbMATHGoogle Scholar
  6. 6.
    Wonham, W.M.: Linear Multivariable Control: A Geometric Approach, 3rd edn. Springer, New York (1985)zbMATHGoogle Scholar
  7. 7.
    Venkatesh, K.V., Bhartiya, S., Ruhela, A.: Mulitple feedback loops are key to a robust dynamic performance of tryptophan regulation in Escherichia coli. FEBS Letters 563, 234–240 (2004)CrossRefGoogle Scholar
  8. 8.
    El-Samad, H., Goff, J.P., Khammash, M.: Calcium homeostasis and parturient hypocalcemia: An integral feedback perspective. J. Theor. Biol. 214, 17–29 (2002)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Saunders, P.T., Koeslag, J.H., Wessels, J.A.: Integral rein control in physiology. J. Theor. Biol. 194, 163–173 (1998)CrossRefGoogle Scholar
  10. 10.
    Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., Walter, P.: Molecular Biology of the Cell, 4th edn. Garland Science, New York (2002)Google Scholar
  11. 11.
    Levchenko, A., Bruck, J., Sternberg, P.W.: Scaffold proteins may biphasically affect the levels of mitogen-activated protein kinase signaling and reduce its threshold properties. Proc. Natl. Acad. Sci. USA 97, 5818–5823 (2000)CrossRefGoogle Scholar
  12. 12.
    Huang, C., Ferrell Jr, J.E.: Ultrasensitivity in the mitogen-activated protein kinase cascade. Proc. Natl. Acad. Sci. USA 93, 10078–10083 (1996)CrossRefGoogle Scholar
  13. 13.
    Brightman, F.A., Fell, D.A.: Differential feedback regulation of the MAPK cascade underlies the quantitative differences in EGF and NGF signalling in PC12 cells. FEBS Lett. 482, 169–174 (2000)CrossRefGoogle Scholar
  14. 14.
    Hao, N., Yildirim, N., Wang, Y., Elston, T.C., Dohlman, H.G.: Regulators of G protein signaling and transient activation of signaling: Experimental and computational analysis reveals negative and positive feedback controls on G protein activity. J. Biol. Chem. 278, 46506–46515 (2003)CrossRefGoogle Scholar
  15. 15.
    Vinnicombe, G.: Feedback networks. In: Francis, B.A., Smith, M.C., Willems, J.C. (eds.) Contol of Uncertain Systems: Modelling, Approximation, and Design. LNCIS, pp. 371–387. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  16. 16.
    Thattai, M., van Oudenaarden, A.: Intrinsic noise in gene regulatory networks. Proc. Natl. Acad. Sci. USA 98, 8614–8619 (2001)CrossRefGoogle Scholar
  17. 17.
    Paulsson, J.: Summing up the noise in gene networks. Nature 427, 415–418 (2004)CrossRefGoogle Scholar
  18. 18.
    Morishita, Y., Kobayashi, T.J., Aihara, K.: Evaluation of the performance of mechanisms for noise attenuation in a single-gene expression. J. Theor. Biol. 235, 241–264 (2005)CrossRefMathSciNetGoogle Scholar
  19. 19.
    El-Samad, H., Khammash, M.: Regulated degradation is a mechanism for suppressing stochastic fluctuations in gene regulatory networks. Biophys. J. 90, 3749–3761 (2006)CrossRefGoogle Scholar
  20. 20.
    Alon, U., Surette, M.G., Barkai, N., Leibler, S.: Robustness in bacterial chemotaxis. Nature 397, 168–171 (1999)CrossRefGoogle Scholar
  21. 21.
    von Dassow, G., Meir, E., Munro, E.M., Odell, G.M.: The segment polarity network is a robust developmental module. Nature 406, 188–192 (2000)CrossRefGoogle Scholar
  22. 22.
    Eldar, A., Dorfman, R., Weiss, D., Ashe, H., Shilo, B.-Z., Barkai, N.: Robustness of the BMP morphogen gradient in Drosophila embryonic patterning. Nature 419, 304–308 (2002)CrossRefGoogle Scholar
  23. 23.
    Yi, T.M., Huang, Y., Simon, M.I., Doyle, J.: Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proc. Natl. Acad. Sci. USA 97, 4649–4653 (2000)CrossRefGoogle Scholar
  24. 24.
    Yang, L., Iglesias, P.A.: Positive feedback may cause the biphasic response observed in the chemoattractant-induced response of Dictyostelium cells. Systems & Control Letters 55, 329–337 (2006)zbMATHCrossRefMathSciNetGoogle Scholar
  25. 25.
    Barkai, N., Leibler, S.: Robustness in simple biochemical networks. Nature 387, 913–917 (1997)CrossRefGoogle Scholar
  26. 26.
    Iglesias, P.A., Levchenko, A.: A general framework for achieving integral control in chemotactic biological signaling mechanisms. In: Proc. Conf. Decision and Control, Orlando, FL, pp. 843–848 (2001)Google Scholar
  27. 27.
    Keener, J.P., Sneyd, J.: Mathematical Physiology. Springer, New York (1998)zbMATHGoogle Scholar
  28. 28.
    Bennett, S.: A History of Control Engineering, pp. 1800–1930. Peter Peregrinus, Stevenage (1979)Google Scholar
  29. 29.
    Shvartsman, S.Y., Hagan, M.P., Yacoub, A., Dent, P., Wiley, H.S., Lauffenburger, D.A.: Autocrine loops with positive feedback enable context-dependent cell signaling. Amer. J. Phys. Cell Phys. 282, 545–559 (2002)Google Scholar
  30. 30.
    Chaves, M., Sontag, E., Dinerstein, R.J.: Optimal length and signal amplification in weakly activated signal transduction cascades. J. Phys. Chem. B 108, 15311–15320 (2004)CrossRefGoogle Scholar
  31. 31.
    Mayawala, K., Gelmi, C.A., Edwards, J.S.: MAPK cascade possesses decoupled controllability of signal amplification and duration. Biophys. J. 87, L01–2 (2004)CrossRefGoogle Scholar
  32. 32.
    Sedra, A., Smith, K.: Microelectronic Circuits, 5th edn. Oxford University Press, New York (2004)Google Scholar
  33. 33.
    Angeli, D., Ferrell Jr., J.E., Sontag, E.D.: Detection of multistability, bifurcations, and hysteresis in a large class of biological positive-feedback systems. Proc. Natl. Acad. Sci. USA 101, 1822–1827 (2004)CrossRefGoogle Scholar
  34. 34.
    Pomerening, J.R., Sontag, E.D., Ferrell Jr., J.E.: Building a cell cycle oscillator: Hysteresis and bistability in the activation of Cdc2. Nature Cell Biology 5, 346–351 (2003)CrossRefGoogle Scholar
  35. 35.
    Xiong, W., Ferrell Jr., J.E.: A positive-feedback-based bistable ‘memory module’ that governs a cell fate decision. Nature 426, 460–465 (2003)CrossRefGoogle Scholar
  36. 36.
    Meinhardt, H.: Orientation of chemotactic cells and growth cones: Models and mechanisms. J. Cell Science 112, 2867–2874 (1999)Google Scholar
  37. 37.
    Narang, A., Subramanian, K.K., Lauffenburger, D.A.: A mathematical model for chemoattractant gradient sensing based on receptor-regulated membrane phospholipid signaling dynamics. Ann. Biomedical Eng. 29, 677–691 (2001)CrossRefGoogle Scholar
  38. 38.
    Postma, M., Van Haastert, P.J.: A diffusion-translocation model for gradient sensing by chemotactic cells. Biophys. J. 81, 1314–1323 (2001)CrossRefGoogle Scholar
  39. 39.
    Goldbeter, A.: Computational approaches to cellular rhythms. Nature 420, 238–245 (2002)CrossRefGoogle Scholar
  40. 40.
    Martiel, J.L., Goldbeter, A.: Autonomous chaotic behaviour of the slime mould Dictyostelium discoideum predicted by a model for cyclic AMP signalling. Nature 313, 590–592 (1985)CrossRefGoogle Scholar
  41. 41.
    Goldbeter, A.: Mechanism for oscillatory synthesis of cyclic AMP in Dictyostelium discoideum. Nature 253, 540–542 (1975)CrossRefGoogle Scholar
  42. 42.
    Hofer, T., Sherratt, J.A., Maini, P.K.: Dictyostelium discoideum: Cellular selforganization in an excitable biological medium. Proc. Biol. Sci. 259, 249–257 (1995)CrossRefGoogle Scholar
  43. 43.
    Levine, H., Aranson, I., Tsimring, L., Truong, T.V.: Positive genetic feedback governs cAMP spiral wave formation in Dictyostelium. Proc. Natl. Acad. Sci. USA 93, 6382–6386 (1996)CrossRefGoogle Scholar
  44. 44.
    Halloy, J., Lauzeral, J., Goldbeter, A.: Modeling oscillations and waves of cAMP in Dictyostelium discoideum cells. Biophys. Chem. 72, 9–19 (1998)CrossRefGoogle Scholar
  45. 45.
    Laub, M.T., Loomis, W.F.: A molecular network that produces spontaneous oscillations in excitable cells of Dictyostelium. Mol. Biol. Cell 9, 3521–3532 (1998)Google Scholar
  46. 46.
    Iglesias, P.A.: Feedback control in intracellular signaling pathways: Regulating chemotaxis in Dictyostelium discoideum. Eur. J. Control 9, 216–225 (2003)Google Scholar
  47. 47.
    Tomchik, K.J., Devreotes, P.N.: Adenosine 3’,5’-monophosphate waves in Dictyostelium discoideum: A demonstration by isotope dilution-fluorography. Science 12, 443–446 (1981)CrossRefGoogle Scholar
  48. 48.
    Kessin, R.H.: Dictyostelium: Evolution, Cell Biology, and the Development of Multicellularity. Cambridge University Press, Cambridge (2001)Google Scholar
  49. 49.
    Ingalls, B.P., Yi, T.-M., Iglesias, P.A.: Using control theory to study biology. In: Szallasi, Z., Stelling, J., Periwal, V. (eds.) System Modeling in Cellular Biology, pp. 243–267. MIT Press, Cambridge (2006)Google Scholar
  50. 50.
    Parent, C.A., Devreotes, P.N.: A cell’s sense of direction. Science, 765–770 (1999)Google Scholar
  51. 51.
    Levchenko, A., Iglesias, P.A.: Models of eukaryotic gradient sensing: Application to chemotaxis of amoebae and neutrophils. Biophys. J. 82, 50–63 (2002)Google Scholar
  52. 52.
    Ma, L., Janetopoulos, C., Yang, L., Devreotes, P.N., Iglesias, P.A.: Two complementary, local excitation, global inhibition mechanisms acting in parallel can explain the chemoattractant-induced regulation of PI(3,4,5)P3 response in Dictyostelium cells. Biophys. J. 87, 3764–3774 (2004)CrossRefGoogle Scholar
  53. 53.
    Manahan, C.L., Iglesias, P.A., Long, Y., Devreotes, P.N.: Chemoattractant signaling in Dictyostelium discoideum. Annu. Rev. Cell Dev. Biol. 20, 223–253 (2004)CrossRefGoogle Scholar
  54. 54.
    Krishnan, J., Iglesias, P.A.: Analysis of the signal transduction properties of a module of spatial sensing in eukaryotic chemotaxis. Bull. Math. Biol. 65, 95–128 (2003)CrossRefGoogle Scholar
  55. 55.
    Kutscher, B., Devreotes, P., Iglesias, P.A.: Local excitation, global inhibition mechanism for gradient sensing: An interactive applet. Sci. STKE, p. PL3 (2004)Google Scholar
  56. 56.
    Janetopoulos, C., Ma, L., Devreotes, P.N., Iglesias, P.A.: Chemoattractant-induced phosphatidylinositol 3,4,5-trisphosphate accumulation is spatially amplified and adapts, independent of the actin cytoskeleton. Proc. Natl. Acad. Sci. USA 101, 8951–8956 (2004)CrossRefGoogle Scholar
  57. 57.
    Krishnan, J., Iglesias, P.A.: A modeling framework describing the enzyme regulation of membrane lipids underlying gradient perception in Dictyostelium cells. J. Theor. Biol. 229, 85–99 (2004)CrossRefMathSciNetGoogle Scholar
  58. 58.
    Krishnan, J., Iglesias, P.A.: A modelling framework describing the enzyme regulation of membrane lipids underlying gradient perception in Dictyostelium cells II: Input-output analysis. J. Theor. Biol. 235, 504–520 (2005)CrossRefMathSciNetGoogle Scholar
  59. 59.
    Amonlirdviman, K., Khare, N.A., Tree, D.R.P., Chen, W.-S., Axelrod, J.D., Tomlin, C.J.: Mathematical modeling of planar cell polarity to understand domineering nonautonomy. Science, 423–426 (2005)Google Scholar
  60. 60.
    El-Samad, H., Kurata, H., Doyle, J.C., Gross, C.A., Khammash, M.: Surviving heat shock: Control strategies for robustness and performance. Proc. Natl. Acad. Sci. USA 102, 2736–2741 (2005)CrossRefGoogle Scholar
  61. 61.
    Iglesias, P.A., Levchenko, A.: Modeling the cell’s guidance system. Sci. STKE, p. RE12 (2002)Google Scholar
  62. 62.
    Effler, J.C., Iglesias, P.A., Robinson, D.N.: Regulating cell shape during cytokinesis. In: Francis, B.A., Smith, M.C., Willems, J.C. (eds.) Contol of Uncertain Systems: Modelling, Approximation, and Design. LNCIS, pp. 203–224. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  63. 63.
    Effler, J.C., Kee, Y.-S., Berk, J.M., Tran, M.N., Iglesias, P.A., Robinson, D.N.: Mitosis-sspecific mechanosensing and contractile-protein redistribution control cell shape. Current Biology 16(19) (2006)Google Scholar
  64. 64.
    Morohashi, M., Winn, A.E., Borisuk, M.T., Bolouri, H., Doyle, J., Kitano, H.: Robustness as a measure of plausibility in models of biochemical networks. J. Theor. Biol. 216, 19–30 (2002)CrossRefMathSciNetGoogle Scholar
  65. 65.
    Ma, L., Iglesias, P.A.: Quantifying robustness of biochemical network models. BMC Bioinformatics, p. 38 (2002)Google Scholar
  66. 66.
    Stelling, J., Gilles, E.D., Doyle 3rd, F.J.: Robustness properties of circadian clock architectures. Proc. Natl. Acad. Sci. USA 101, 13210–13215 (2004)CrossRefGoogle Scholar
  67. 67.
    Prill, R.J., Iglesias, P.A., Levchenko, A.: Dynamic properties of network motifs contribute to biological network organization. PLoS Biol., vol. 3, p. e343 (2005)Google Scholar
  68. 68.
    Kim, J., Bates, D.G., Postlethwaite, I., Ma, L., Iglesias, P.A.: Robustness analysis of biochemical network models. IEEE Proc. Systems Biol. 152, 96–104 (2006)CrossRefGoogle Scholar
  69. 69.
    Angeli, D., Sontag, E.D.: Monotone control systems. IEEE Trans. Automat. Control 48, 1684–1698 (2003)CrossRefMathSciNetGoogle Scholar
  70. 70.
    Angeli, D., Ferrell Jr, J.E., Sontag, E.D.: Detection of multistability, bifurcations, and hysteresis in a large class of biological positive-feedback systems. Proc. Natl. Acad. Sci. USA 101, 1822–1827 (2004)CrossRefGoogle Scholar

Copyright information

© Springer London 2007

Authors and Affiliations

  • Burton W. Andrews
    • 1
  • Pablo A. Iglesias
    • 1
  1. 1.The Johns Hopkins University, Baltimore, MD 21218USA

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