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access icon free Architecture-dependent robustness in a class of multiple positive feedback loops

  • Author(s): Changhong Shi 1 ; Han-xiong Li 2 ; Tianshou Zhou 1
    • View affiliations
    • Affiliations: 1: School of Mathematics and Computational Science and Guangdong Province Key Laboratory of Computational Science, Sun Yat-Sen University, Guangzhou 510275, People's Republic China;
      2: Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong, People's Republic China
  • Source: Volume 7, Issue 1, February 2013, p. 1 – 10
    DOI:  10.1049/iet-syb.2011.0090 , Print ISSN 1751-8849, Online ISSN 1751-8857
© The Institution of Engineering and Technology
Received 13/12/2011, Accepted 13/09/2012, Revised 20/07/2012, Published

Many types of multiple positive feedbacks with each having potentials to generate bistability exist extensively in natural, raising the question of why a particular architecture is present in a cell. In this study, the authors investigate multiple positive feedback loops across three classes: one-loop class, two-loop class and three-loop class, where each class is composed of double positive feedback loop (DPFL) or double negative feedback loop (DNFL) or both. Through large-scale sampling and robustness analysis, the authors find that for a given class, the homogeneous DPFL circuit (i.e. the coupled circuit that is composed of only DPFLs) is more robust than all the other circuits in generating bistable behaviour. In addition, stochastic simulation shows that the low stable state is more robust than the high stable state in homogeneous DPFL whereas the high-stable state is more robust than the low-stable state in homogeneous DNFL circuits. It was argued that this investigation provides insight into the relationship between robustness and network architecture.

Inspec keywords: sampling methods; feedback; cellular biophysics; stochastic processes

Other keywords: stochastic simulation; network architecture; one-loop class; architecture-dependent robustness; double negative feedback loop; low stable state; large-scale sampling; cell architecture; bistability; robustness analysis; two-loop class; multiple positive feedback loops; bistable behaviour; three-loop class; DNFL; double positive feedback loop; homogeneous DPFL circuit

Subjects: Cellular biophysics; Probability theory, stochastic processes, and statistics

References

    1. 1)
      • 21. Zhang, J.J., Yuan, Z.J., Li, H.X., Zhou, T.S.: ‘Architecture-dependent robustness and bistability in a class of genetic circuits’, Biophys. J., 2009, 99, pp. 1034–1042.
    2. 2)
      • 17. Reynolds, A.R., Tischer, C., Verveer, P.J., Rocks, O., Bastiaens, P.I.: ‘EGFR activation coupled to inhibition of tyrosine phosphatases causes lateral signal propagation’, Nat. Cell Biol., 2003, 5, pp. 447.
    3. 3)
      • 5. Veening, J.W., Smits, W.K., Kuipers, O.P.: ‘Bistability, epigenetic, and bet-hedging in bacteria’, Annu. Rev. Microbiol., 2008, 4, pp. 259–271.
    4. 4)
      • 4. Brandman, O., James, E., Ferrell, J., Rong, L., Tobias, M.: ‘Interlinked fast and slow positive feedback loop driven reliable cell decision’, Science, 2005, 310, pp. 496–498.
    5. 5)
      • 6. Wedlich-Soldner, R., Wai, S.C., Schmidt, T., Li, R.: ‘Robust cell polarity is a dynamic state established by coupling transport and GTPase signaling’, J. Cell. Biol., 2004, 166, pp. 889.
    6. 6)
      • 22. Ma, W., Lai, L., Ouyang, Q., Tang, C.: ‘Robustness and modular design of the Drosophila segment polarity network’, Mol. Syst. Biol., 2006, 2, pp. 70.
    7. 7)
      • 32. Shahrezaei, V., Swain, P.S.: ‘Analytical distributions for stochastic gene expression’, Proc. Natl. Acad. Sci. USA, 2008, 105, pp. 17256–17261.
    8. 8)
      • 36. Sudin, B., Qiang, Z., Melvin E., A.: ‘A deterministic map of Waddington's epigenetic landscape for cell fate specification’, BMC Syst. Boil., 2011, 5, pp. 85.
    9. 9)
      • 16. Kanehisa, M., Goto, S., Hattori, M., et al: ‘From genomics to chemical genomics: new developments in KEGG’, Nucleic Acids Res., 2006, 22, pp. D354–D357.
    10. 10)
      • 28. Marc, H., Heinz, K., Martin, H., Andreas, W.: ‘Glocal robustness analysis and model discrimination for circadian oscillators’, PLos Comput. Biol., 2009, 5, pp. e1000534.
    11. 11)
      • 19. Acar, M., Becskei, A., Oudennarden, A.v.: ‘Enhancement of cellular memory by reducing stochastic transitions’, Nature, 2005, 435, pp. 228–232.
    12. 12)
      • 3. Angeli, D., Ferrell, 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, 2004, 97, pp. 2075–2080.
    13. 13)
      • 30. Qiao, L., Robert, B.N., loannis G, K., Stanislav, Y.S.: ‘Bistability and oscillations in the Huang-Ferrell model of MAPK signaling’, PLoS Comput. Biol., 2007, 3, (9), pp. e184.
    14. 14)
      • 24. Hasty, J., Pradines, J., Dolnik, M., Collins, J.J.: ‘Noise-based switches and amplifiers for gene expression’, Proc. Natl. Acad. Sci. USA, 2000, 101, pp. 1822–1827.
    15. 15)
      • 18. Solomon, M.J., Glotzer, M., Lee, T.H., Philippe, M., Kirschner, M.W.: ‘Cyclin activation of p34cdc2’, Cell, 1990, 63, pp. 1013.
    16. 16)
      • 1. Barkai, N., Leibler, S.: ‘Robustness in simple biomedical networks’, Nature, 1997, 387, pp. 913–917.
    17. 17)
      • 31. Iman, R., Davenport, J., Zeigler, D.: ‘Latin hypercube sampling (Program user's guide)’ (Sandia National Laboratories, Albuquerque, 1980).
    18. 18)
      • 40. McDaniel, R., Weiss, R.: ‘Advance in synthetic biology: on the path from prototypes to applications’, Curr. Opin. Biotech., 2005, 15, pp. 476–483.
    19. 19)
      • 29. Najaf, A.S., Casim, A.S.: ‘Robust network topologies for generating switch-like cellular responses’, PLoS Comput. Biol., 2011, 7, (6), pp. e1002085.
    20. 20)
      • 34. Gardner, T.S., Cantor, C.R., Collins, J.J.: ‘Construction of a genetic toggle switch in Escherichia coli’, Nature, 2000, 403, pp. 339–342.
    21. 21)
      • 41. Palani, S., Sarkar, C.: ‘Synthetic conversion of a graded receptor signal into a tunable, reversible switch’, Mol. Syst. Biol., 2011, 7, pp. 480.
    22. 22)
      • 9. Cherry, J., Adler, F.: ‘How to make a biological switch’, J. Theor. Biol., 2000, 203, pp. 117–133.
    23. 23)
      • 12. Sriram, K., Soliman, S., Fages, F.: ‘Dynamics of the interlocked positive feedback loops explaining the robust epigenetic switching in Candida albicans’, J. Theor. Biol., 2010, 258, pp. 71–88.
    24. 24)
      • 7. Singh, H., Medina, K.L., Pongubala, J.M.: ‘Contingent gene regulatory networks and B cell fate specification’, Proc. Natl. Acad. Sci. USA, 2005, 102, pp. 4949.
    25. 25)
      • 10. Ferrell Jr., J.E.: ‘Self-perpetuating states in signal transduction: positive feedback, double-negative feedback and bi-stability’, Curr. Opin. Chem. Biol., 2002, 6, pp. 140–148.
    26. 26)
      • 8. Bhalla, U.S., Ram, P.T., Iyengar, R.: ‘MAP kinase phosphatase as a locus of flexibility in a mitogen-activated protein kinase signaling network’, Science, 2002, 297, pp. 1018.
    27. 27)
      • 14. Kim, J.-R., Yoon, Y., Cho, K.-H.: ‘Coupled feedback loops form dynamic motifs of cellular networks’, Biophys. J., 2008, 94, pp. 359–365.
    28. 28)
      • 26. Smith, H.L.: ‘Monotone dynamic systems: an introduction to the theory of competitive and cooperative systems. 1995: A. Math. Soc., Providence, R1.
    29. 29)
      • 27. Ma, W., Trusina, A., El-Samad, H., et al: ‘Defining network Topologies that can achieve biochemical adaptation’, Cell, 2009, 138, pp. 760–773.
    30. 30)
      • 11. Kim, T.-H., Jung, S.H., Cho, K.-H.: ‘Interlinked mutual inhibitory positive feedbacks induce robust memory effects’, FEBS Lett., 2007, 581, pp. 4899–4909.
    31. 31)
      • 13. Chang, D.-E., Leung, S., Atkinson, M.R., Reifler, A., Forger, D., Ninfa, A.J.: ‘Building biological memory by linking positive feedback loops’, Proc. Natl. Acad. Sci. USA, 2010, 107, (1), pp. 175–180.
    32. 32)
      • 35. Allen, R.J., Warren, P.B., Ten Wolde, P.R.: ‘Sampling rare switching events in biochemical networks’, Phys. Rev. Lett., 2005, 94, (1), pp. 18104.
    33. 33)
      • 37. Stefanie, W., Javier, m., Ricard, S.: ‘Monomeric bistability and the role of autoloops in gene regulation’, PLos One, 2009, 4, (4), pp. e5399.
    34. 34)
      • 38. Yong-Jun, S., Leonidas, B.: ‘Linear control theory for gene network modeling’, PLos One, 2010, 5, (9), pp. e12785.
    35. 35)
      • 2. Waddington, C.: ‘The strategy of the genes’ (George Allen & Unwin Ltd., London, 1957).
    36. 36)
      • 23. Adiel, l., Ofer, B.: ‘Analysis of genetic switch system encoded on plasmids’, Phys. Rev. Lett., 2009, 103, pp. 028101.
    37. 37)
      • 15. Yao, G., Cheemeng West, M., Nevins, J.R., Lingchong, Y.: ‘Origin of bistability underlying mammalian cell cycle entry’, Mol. Syst. Biol., 2011, 7, pp. 485.
    38. 38)
      • 33. Barnes, C.P., Silk, D., Sheng, X., Stumpf, M.P.H.: ‘Bayesian design of synthetic biological systems’, Proc. Natl Acad. Sci. USA, 2011, 108, (37), pp. 15190–15195.
    39. 39)
      • 25. Jun, T., Xianqing, Y., Jun, M., Ya, J.: ‘Noise effect on persistence of memory in a positive-feedback gene regulatory circuit’, Phys. Rev. E., 2009, 80, pp. 011907.
    40. 40)
      • 39. Bescskei, A., Seraphin, B., Serrano, L.: ‘Positive feedback in eukaryotic gene networks: cell differentiation by graded to binary response conversion’, EMBO J., 2011, 20, pp. 2528–2535.
    41. 41)
      • 20. Wang, J., Zhang, J., Yuan, Z., Zhou, T.: ‘Noise-induced switches in network system of the genetic toggle switch’, BMC Syst. Biol., 2007, I, pp. 50.
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