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IB, NF-B Regulation Model: Simulation Analysis of Small Number of Molecules

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Abstract

The regulation of IB, NF-B is of foremost interest in biology as the transcription factor NF-B has multiple target genes. We have modeled a previously published model by Hoffmann et al. (2002) of IB, NF-B mathematically as discrete reaction systems. We have used stochastic algorithm to compare the results when there are large and small numbers of molecules available in a finite volume for each protein. Our results for small number of molecules show that with continuous presence of stimulation, nuclear NF-B oscillates continuously in every individual cell rather than damping, which was observed in cell population results. This characteristic of the system is missed when averaged behavior is studied.

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References

  1. 1.

    Ghosh S, May MJ, Kopp EB:NF-B and rel proteins: evolutionary conserved mediators of immune responses. Annual Review of Immunology 1998, 16: 225-260. 10.1146/annurev.immunol.16.1.225

  2. 2.

    Gonzalez-Crespo S, Levine M:Related target enhancers for dorsal and NF-B signaling pathways. Science 1994, 264(5156):255-258. 10.1126/science.8146656

  3. 3.

    Malek S, Huxford T, Ghosh G:IB functions through direct contacts with the nuclear localization signals and the DNA binding sequences of NF-B. Journal of Biological Chemistry 1998, 273(39):25427-25435. 10.1074/jbc.273.39.25427

  4. 4.

    Hoffmann A, Levchenko A, Scott ML, Baltimore D:The IB-NF-B signaling module: temporal control and selective gene activation. Science 2002, 298(5596):1241-1245. 10.1126/science.1071914

  5. 5.

    Nelson DE, Ihewaba AEC, Elliott M, et al.:Oscillations in NF-B signaling control the dynamics of gene expresion. Science 2004, 306(5696):704-708. 10.1126/science.1099962

  6. 6.

    Barken D, Wang CJ, Kearns J, Cheong R, Hoffmann A, Levchenko A:Comment on oscillations in NF-B signaling control the dynamics of the gene expression. Science 2005, 308(5718):52. 10.1126/science.1107904

  7. 7.

    Nelson DE, Horton CA, See V, et al.:Response to comment on oscillations in NF-B signaling control the dynamics of the gene expression. Science 2005, 308(5718):52. 10.1126/science.1107904

  8. 8.

    Lauffenburger DA: Receptors: Models for Binding, Trafficking and Signaling. Oxford University Press, Oxford, UK; 1993.

  9. 9.

    Bhalla US, Iyengar R: Emergent properties of networks of biological signaling pathways. Science 1999, 283(5400):381-387. 10.1126/science.283.5400.381

  10. 10.

    Kholodenko BN: Negative feedbacka dn ultrasensitivity can bring about oscillationsin the mitogen-activated protein kinase cascades. European Journal of Biochemistry 2000, 267(6):1583-1588.

  11. 11.

    Bentele M, Lavrik I, Ulrich M, et al.: Mathematical modeling reveals threshold mechanism in CD95-induced apoptosis. Journal of Cell Biology 2004, 166(6):839-851. 10.1083/jcb.200404158

  12. 12.

    [http://physiome.org]

  13. 13.

    [http://www.nrcam.uchc.edu/login/login.html]

  14. 14.

    Luby-Phelps K, Weisiger RA: Role of cytoarchitecture in cytoplasmic transport. Comparative Biochemistry and Physiology B 1996, 115(3):295-306. 10.1016/S0305-0491(96)00176-9

  15. 15.

    Goodsell DS: Inside a living cell. Trends in Biochemical Sciences 1991, 16(6):203-206.

  16. 16.

    Berg OG: The influence of macromolecular crowding on thermodynamic activity: solubility and dimerization constants for spherical and dumbbell-shaped molecules in a hard-sphere mixture. Biopolymers 1990, 30(11-12):1027-1037. 10.1002/bip.360301104

  17. 17.

    Han J, Herzfeld J: Macromolecular diffusion in crowded solutions. Biophysical Journal 1993, 65(3):1155-1161. 10.1016/S0006-3495(93)81145-7

  18. 18.

    Lahav G, Rosenfeld N, Sigal A, et al.: Dynamcis of the p53-Mdm2 feedback loop in individual cells. Nature Genetics 2004, 36(2):147-150. 10.1038/ng1293

  19. 19.

    Vilar JMG, Kueh HY, Barkai N, Leibler S: Mechanisms of noise-resistance in genetic oscillators. Proceedings of the National Academy of Sciences of the United States of America 2002, 99(9):5988-5992. 10.1073/pnas.092133899

  20. 20.

    Sachs K, Perez O, Pe'er D, Lauffenburger DA, Nolan GP: Causal protein-signaling networks derived from multiparameter single-cell data. Science 2005, 308(5721):523-529. 10.1126/science.1105809

  21. 21.

    Mcadams HH, Arkin A: Stochastic mechanisms in gene expression. Proceedings of the National Academy of Sciences of the United States of America 1997, 94(3):814-819. 10.1073/pnas.94.3.814

  22. 22.

    McAdams H, Arkin H: It's noisy business! Genetic regulation at the nanomolecular scale. Trends Genetics 1999, 15(2):65-69. 10.1016/S0168-9525(98)01659-X

  23. 23.

    Gonze D, Halloy J, Goldbeter A: Robustness of circadian rhythms with respect to molecular noise. Proceedings of the National Academy of Sciences of the United States of America 2002, 99(2):673-678. 10.1073/pnas.022628299

  24. 24.

    Srivastava R, You L, Summers J, Yin J: Stochastic vs deterministic modeling of intracellular viral kinetics. Journal of Theoretical Biology 2002, 218(3):309-321. 10.1006/jtbi.2002.3078

  25. 25.

    Bhalla US: Signaling in small subcellular volumes. I. Stochastic and diffusion effects on individual pathways. Biophysical Journal 2004, 87(2):733-744. 10.1529/biophysj.104.040469

  26. 26.

    Bhalla US: Signaling in small subcellular volumes. II. Stochastic and diffusion effects on synaptic network properties. Biophysical Journal 2004, 87(2):745-753. 10.1529/biophysj.104.040501

  27. 27.

    [http://www.cellsystems.org/teams/modeling/projects/sigtran/index.html]

  28. 28.

    Morton-Firth CJ, Bray D: Predicting temporal fluctuations in an intracellular signalling pathway. Journal of Theoretical Biology 1998, 192(1):117-128. 10.1006/jtbi.1997.0651

  29. 29.

    Gillepsie DT: A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. Journal of Computational Physics 1976, 22(4):403-434. 10.1016/0021-9991(76)90041-3

  30. 30.

    Gibson MA, Bruck J: Efficient exact stochastic simulation of chemical systems with many species and many channels. Journal of Physical Chemistry A 2000, 104(9):1876-1889. 10.1021/jp993732q

  31. 31.

    Gillespie DT: Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry 1977, 81(25):2340-2361. 10.1021/j100540a008

  32. 32.

    Elliott DF: Handbook of Digital Signal Processing: Engineering Applications. Academic Press, New York, NY, USA; 1987.

  33. 33.

    Grenander U, Szego G: Toeplitz Forms and Their Applications. Chelsea, New York, NY, USA; 1984.

  34. 34.

    [http://www.mathworks.com]

  35. 35.

    Perkins ND, Gilmore TD:Good cop, badcop: the different faces of NF-B. Cell Death and Differentiation 2006, 13: 759-772. 10.1038/sj.cdd.4401838

  36. 36.

    Rayet B, Gélinas C: Aberrant rel/nfkb genes and activity in human cancer. Oncogene 1999, 18(49):6938-6947. 10.1038/sj.onc.1203221

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Correspondence to Anamika Sarkar.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Sarkar, A., Meila, M. & Franza, R.B. IB, NF-B Regulation Model: Simulation Analysis of Small Number of Molecules. J Bioinform Sys Biology 2007, 25250 (2008) doi:10.1155/2007/25250

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Keywords

  • Transcription Factor
  • Target Gene
  • Cell Population
  • Reaction System
  • Individual Cell