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Mechanisms That Enhance Sustainability of p53 Pulses

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  • Jae Kyoung Kim
  • Trachette L Jackson

Abstract

The tumor suppressor p53 protein shows various dynamic responses depending on the types and extent of cellular stresses. In particular, in response to DNA damage induced by γ-irradiation, cells generate a series of p53 pulses. Recent research has shown the importance of sustaining repeated p53 pulses for recovery from DNA damage. However, far too little attention has been paid to understanding how cells can sustain p53 pulses given the complexities of genetic heterogeneity and intrinsic noise. Here, we explore potential molecular mechanisms that enhance the sustainability of p53 pulses by developing a new mathematical model of the p53 regulatory system. This model can reproduce many experimental results that describe the dynamics of p53 pulses. By simulating the model both deterministically and stochastically, we found three potential mechanisms that improve the sustainability of p53 pulses: 1) the recently identified positive feedback loop between p53 and Rorα allows cells to sustain p53 pulses with high amplitude over a wide range of conditions, 2) intrinsic noise can often prevent the dampening of p53 pulses even after mutations, and 3) coupling of p53 pulses in neighboring cells via cytochrome-c significantly reduces the chance of failure in sustaining p53 pulses in the presence of heterogeneity among cells. Finally, in light of these results, we propose testable experiments that can reveal important mechanisms underlying p53 dynamics.

Suggested Citation

  • Jae Kyoung Kim & Trachette L Jackson, 2013. "Mechanisms That Enhance Sustainability of p53 Pulses," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.
  • Handle: RePEc:plo:pone00:0065242
    DOI: 10.1371/journal.pone.0065242
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    References listed on IDEAS

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    1. Bert Vogelstein & David Lane & Arnold J. Levine, 2000. "Surfing the p53 network," Nature, Nature, vol. 408(6810), pages 307-310, November.
    2. N. Barkai & S. Leibler, 1997. "Robustness in simple biochemical networks," Nature, Nature, vol. 387(6636), pages 913-917, June.
    3. U. Alon & M. G. Surette & N. Barkai & S. Leibler, 1999. "Robustness in bacterial chemotaxis," Nature, Nature, vol. 397(6715), pages 168-171, January.
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    Cited by:

    1. Jae Kyoung Kim & Eduardo D Sontag, 2017. "Reduction of multiscale stochastic biochemical reaction networks using exact moment derivation," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-24, June.

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