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Studying global dynamics and stability of biological network is of importance in order to understand its function and behavior. In this paper, we consider the p53-Mdm2 oscillator module with PDCD5 as a core part of p53 signaling pathway after the DNA damage, and explore the dynamics and stability of the tumor suppressor p53. The dynamics of p53 may decide the cell fate after the DNA damage, while the oscillation of p53 may induce cell cycle arrest and so promote the repair of DNA, and the high levels of p53 can trigger apoptosis. However, p53 activity may be inhibited by its negative regulator Mdm2 in some cancer cells, as Mdm2 is of overexpression due to the increase in Mdm2 production rate. So we first investigate the effect of Mdm2 production rate on the kinetics of p53 through bifurcation analysis. after the DNA damage. With the increase in Mdm2 production rate, p53 can display a steady state, a stable-limit cycle and the coexistence of a stable-limit cycle and a stable steady state. Furthermore, the potential landscapes for oscillation show that the lower concentration of p53 means a stronger stability, whereas those for bistability of the higher steady state and the oscillatory state illustrate that stability of the higher steady state increases with the increasing Mdm2 production rate. In addition, noise strength can greatly affect the stability of p53 oscillations, so we explore the effect of noise strength on potential landscapes, barrier heights and periods. A smaller noise strength leads to a higher barrier height associated with more stable-limit cycle, and the harmonic oscillation with more uniform period and smaller variance is helpful to have more stable maintainance. Our results may be useful for understanding regulation of p53 signaling pathway after DNA damage.
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Keywords:
- p53 dynamics and stability /
- Mdm2 production rate /
- bifurcation /
- potential landscape
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[1] Kubbutat M H G, Jones S N, Vousden K H 1997 Nature 387 299
[2] Vousden K H, Lane D P 2007 Nat.Rev. Mol. Cell Biol. 8 275
[3] Zhang X P, Liu F, Wang W 2012 Biophys. J. 102 2251
[4] Zhang X P, Liu F, Cheng Z, Wang W 2009 Proc. Natl. Acad. Sci. U.S.A 106 12245
[5] Zhang X P, Liu F, Wang W 2011 Proc. Natl. Acad. Sci. U.S.A 108 8990
[6] Ashcroft M, Vousden K H 1999 Oncogene 18 7637
[7] Tovar C, Rosinski J, Filipovic Z, Higgins B, Kolinsky K, Hilton H, Vassilev L T 2006 Proc. Natl. Acad. Sci. U.S.A 103 1888
[8] Bose I, Ghosh B 2007 J. Biosci. 32 991
[9] Zhang L J, Yan S W, Zhuo Y Z 2007 Acta Phys. Sin. 56 2442 (in Chinese) [张丽娟, 晏世伟, 卓益忠 2007 56 2442]
[10] Xia J F, Jia Y 2010 Chin. Phys. B 19 040506
[11] Geng D Y, Xie H J, Wan X W, Xu G Z 2014 Acta Phys. Sin. 63 018702 (in Chinese) [耿读艳, 谢红娟, 万晓伟, 徐桂芝 2014 63 018702]
[12] Bakkenist C J, Kastan M B 2003 Nature 421 499
[13] Stommel J M, Wahl G M 2004 EMBO J. 23 1547
[14] Yin Y, Stephen C W, Luciani M G, Fahraeus R 2002 Nat. Cell Biol. 4 462
[15] Xu L J, Hu J, Zhao Y B, Hu J, Xiao J, Wang Y M, Ma D, Chen Y Y 2012 Apoptosis 17 1235
[16] Zhuge C J, Sun X J, Chen Y Y, Lei J Z 2015 arXiv:1503.08274v1 [q-bio.MN]
[17] Batchelor E, Mock C S, Bhan I, Loewer A, Lahav G 2008 Mol. Cell 30 277
[18] Frauenfelder H, Sligar S G, Wolynes P G 1991 Science 254 1598
[19] Wang J, Xu L, Wang E K 2008 Proc. Natl. Acad. Sci. U.S.A 105 12271
[20] Wang J, Li C H, Wang E K 2010 Proc. Natl. Acad. Sci. U.S.A 107 8195
[21] Tay S, Hughey J J, Lee T K, Lipniacki T, Quake S R, Covert M W 2010 Nature 466 267
[22] Yan H, Zhao L, Hu L, Wang X D, Wang E K, Wang J 2013 Proc. Natl. Acad. Sci. U.S.A 110 E4185
[23] Cao Z, Wang W D 2015 Prog. Biochem. Biophys. 42 147 (in Chinese) [曹志, 王卫东 2015 生物化学与生物物理进展 42 147]
[24] Rinaldo C, Prodosmo A, Mancini F, Iacovelli S, Sacchi A, Moretti F, Soddu S 2007 Mol. Cell 25 739
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