Post-translational regulation enables robust p53 regulation

BMC Systems Biology

Xiling Shen²  Brandon Hencey³  Ali H Sayed¹  Kai-Yuan Chen²  Yong-Jun Shin² 

[1] Department of Electrical Engineering, University of California, Los Angeles, CA 90095-1594, USA;School of Electrical and Computer Engineering, 402 Phillips Hall, Cornell University, Ithaca, NY 14853, USA;School of Mechanical and Aerospace Engineering, 214 Upson Hall, Cornell University, Ithaca, NY 14853, USA

关键词: Disturbance rejection;    Robustness;    p53-Mdm2 feedback loop;    Feedback control theory;   

Others  :  1142341
DOI  :  10.1186/1752-0509-7-83

 received in 2012-08-24, accepted in 2013-08-23,  发布年份 2013

【 摘 要 】

Background

The tumor suppressor protein p53 plays important roles in DNA damage repair, cell cycle arrest and apoptosis. Due to its critical functions, the level of p53 is tightly regulated by a negative feedback mechanism to increase its tolerance towards fluctuations and disturbances. Interestingly, the p53 level is controlled by post-translational regulation rather than transcriptional regulation in this feedback mechanism.

Results

We analyzed the dynamics of this feedback to understand whether post-translational regulation provides any advantages over transcriptional regulation in regard to disturbance rejection. When a disturbance happens, even though negative feedback reduces the steady-state error, it can cause a system to become less stable and transiently overshoots, which may erroneously trigger downstream reactions. Therefore, the system needs to balance the trade-off between steady-state and transient errors. Feedback control and adaptive estimation theories revealed that post-translational regulation achieves a better trade-off than transcriptional regulation, contributing to a more steady level of p53 under the influence of noise and disturbances. Furthermore, post-translational regulation enables cells to respond more promptly to stress conditions with consistent amplitude. However, for better disturbance rejection, the p53- Mdm2 negative feedback has to pay a price of higher stochastic noise.

Conclusions

Our analyses suggest that the p53-Mdm2 feedback favors regulatory mechanisms that provide the optimal trade-offs for dynamic control.

【 授权许可】

   
2013 Shin et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Kaern M, Elston TC, Blake WJ, Collins JJ: Stochasticity in gene expression: From theories to phenotypes. Nat Rev Genet 2005, 6:451-464.
• [2]Raj A, van Oudenaarden A: Nature, nurture, or chance: Stochastic gene expression and its consequences. Cell 2008, 135:216-226.
• [3]Rosenfeld N, Young JW, Alon U, Swain PS, Elowitz MB: Gene regulation at the single-cell level. Science 2005, 307:1962-1965.
• [4]Dunlop MJ, Cox RS, Levine JH, Murray RM, Elowitz MB: Regulatory activity revealed by dynamic correlations in gene expression noise. Nat Genet 2008, 40:1493-1498.
• [5]Jen E: Robust design : Repertoire of biological, ecological, and engineering case studies. New York: Oxford University Press; 2005.
• [6]Cosentino C, Bates D: Feedback control in systems biology. Boca Raton, Florida: CRC Press; 2012.
• [7]Åström KJ, Murray RM: Feedback systems: An introduction for scientists and engineers. Princeton: Princeton University Press; 2008.
• [8]Becskei A, Serrano L: Engineering stability in gene networks by autoregulation. Nature 2000, 405:590-593.
• [9]Simpson ML, Cox CD, Sayler GS: Frequency domain analysis of noise in autoregulated gene circuits. Proc Natl Acad Sci U S A 2003, 100:4551-4556.
• [10]Dublanche Y, Michalodimitrakis K, Kummerer N, Foglierini M, Serrano L: Noise in transcription negative feedback loops: Simulation and experimental analysis. Mol Syst Biol 2006, 2:41.
• [11]Piette J, Neel H, Marechal V: Mdm2: Keeping p53 under control. Oncogene 1997, 15:1001-1010.
• [12]Vogelstein B, Lane D, Levine AJ: Surfing the p53 network. Nature 2000, 408:307-310.
• [13]Levine AJ, Oren M: The first 30 years of p53: Growing ever more complex. Nat Rev Cancer 2009, 9:749-758.
• [14]Kaina B: DNA damage-triggered apoptosis: Critical role of DNA repair, double-strand breaks, cell proliferation and signaling. Biochem Pharmacol 2003, 66:1547-1554.
• [15]Roos WP, Kaina B: DNA damage-induced cell death by apoptosis. Trends Mol Med 2006, 12:440-450.
• [16]Shin YJ, Hencey B, Lipkin SM, Shen X: Frequency domain analysis reveals external periodic fluctuations can generate sustained p53 oscillation. PLoS One 2011, 6:e22852.
• [17]Maltzman W, Czyzyk L: UV irradiation stimulates levels of p53 cellular tumor antigen in nontransformed mouse cells. Mol Cell Biol 1984, 4:1689-94.
• [18]Price BD, Calderwood SK: Increased sequence-specific p53-DNA binding activity after DNA damage is attenuated by phorbol esters. BASINGSTOKE: ONCOGENE; 1993. 8: 3055
• [19]Kastan MB, Zhan Q, El-Deiry WS, Carrier F, Jacks T, et al.: A mammalian cell cycle checkpoint pathway utilizing p53 and GADD45 is defective in ataxia-telangiectasia. Cell 1992, 71:587-597.
• [20]Gannon HS, Woda BA, Jones SN: ATM phosphorylation of Mdm2 Ser394 regulates the amplitude and duration of the DNA damage response in mice. Cancer Cell 2012, 21:668-679.
• [21]Geva-Zatorsky N, Rosenfeld N, Itzkovitz S, Milo R, Sigal A, et al.: Oscillations and variability in the p53 system. Mol Syst Biol 2006, 2:2006.0033.
• [22]Chandra FA, Buzi G, Doyle JC: Glycolytic oscillations and limits on robust efficiency. Science Science 2011, 333:187-192.
• [23]Geva-Zatorsky N, Dekel E, Batchelor E, Lahav G, Alon U: Fourier analysis and systems identification of the p53 feedback loop. Proc Natl Acad Sci U S A 2010, 107:13550-13555.
• [24]Shin YJ, Bleris L: Linear control theory for gene network modeling. PLoS One 2010, 5:e12785.
• [25]Stommel JM, Wahl GM: Accelerated MDM2 auto-degradation induced by DNA-damage kinases is required for p53 activation. EMBO J 2004, 23:1547-56.
• [26]Ju J, Schmitz JC, Song B, Kudo K, Chu E: Regulation of p53 expression in response to 5-fluorouracil in human cancer RKO cells. Clin Cancer Res 2007, 13:4245-4251.
• [27]Shin YJ, Sayed AH, Shen X: Adaptive models for gene networks. PloS one 2012, 7:e31657.
• [28]Sayed AH: Adaptive Filters. New Jersey: Willey; 2008.
• [29]Franklin GF, Powell JD: Digital control of dynamic systems. Reading, Mass.: Addison-Wesley Pub. Co.; 1980.
• [30]Cheng Q, Cross B, Li B, Chen L, Li Z, et al.: Regulation of MDM2 E3 ligase activity by phosphorylation after DNA damage. Mol Cell Biol 2011, 31:4951-4963.
• [31]Xu L, Qu Z: Roles of protein ubiquitination and degradation kinetics in biological oscillations. PloS one 2012, 7(4):e34616.
• [32]O'Keefe K, Li H, Zhang Y: Nucleocytoplasmic shuttling of p53 is essential for MDM2-mediated cytoplasmic degradation but not ubiquitination. Mol Cell Biol 2003, 23:6396-405.
• [33]Tao W, Levine AJ: Nucleocytoplasmic shuttling of oncoprotein Hdm2 is required for Hdm2-mediated degradation of p53. Proc Natl Acad Sci 1999, 96:3077-3080.
• [34]Ashcroft M, Kubbutat MH, Vousden KH: Regulation of p53 function and stability by phosphorylation. Mol Cell Biol 1999, 19:1751-8.
• [35]Kazuyasu S, Herrera JE, Shin’ichi S, Toru M, Michael B, Alex V, Anderson CW, Anderson CW, Ettore A: DNA damage activates p53 through a phosphorylation–acetylation cascade. Genes Dev 1998, 12(18):2831-2841.
• [36]Alenzi FQ, Ahmad SY, Alenazi BQ, Salem ML, Al-Jabri AA, et al.: The haemopoietic stem cell: Between apoptosis and self renewal. Yale J Biol Med 2009, 82:7-18.