Complex p53 dynamics regulated by miR-125b in cellular responses to reactive oxidative stress and DNA damage

被引:0
作者
Malik, Md Zubbair [1 ]
Dashti, Mohammed [1 ]
Jangid, Amit [2 ]
Channanath, Arshad [1 ]
John, Sumi Elsa [1 ]
Singh, R. K. Brojen [2 ]
Al-Mulla, Fahd [1 ]
Thanaraj, Thangavel Alphonse [1 ]
机构
[1] Dasman Diabet Inst, Dept Translat Res, Kuwait 15462, Kuwait
[2] Jawaharlal Nehru Univ, Sch Computat & Integrat Sci, New Delhi 110067, India
关键词
cell stress responses; dynamics; miR-125b; p53; ROS; cellular state; PANCREATIC BETA-CELLS; P53-MDM2 FEEDBACK LOOP; TUMOR-SUPPRESSOR; G(1) ARREST; APOPTOSIS; MDM2; METABOLISM; CANCER; ARF; ACTIVATION;
D O I
10.1093/bib/bbae706
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
In response to distinct cellular stresses, the p53 exhibits distinct dynamics. These p53 dynamics subsequently control cell fate. However, different stresses can generate the same p53 dynamics with different cell fate outcomes, suggesting that the integration of dynamic information from other pathways is important for cell fate regulation. The interactions between miRNA-125b, p53, and reactive oxygen species (ROS) are significant in the context of cellular stress responses and apoptosis. However, the regulating mechanism of miR-125b with p53 is not fully studied. The dynamics of p53 and its response to the miR-125b regulation are still open questions. In the present study, we try to answer some of these fundamental questions based on basic model built from available experimental reports. The miR-125b-p53 regulatory network is modeled using a set of 11 molecular species variables. The biochemical network of miR-125b-p53, described by 22 reaction channels, is represented by coupled ordinary differential equations (ODEs) using the mass action law of chemical kinetics. These ODEs are solved numerically using the standard fourth-order Runge-Kutta method to analyze the dynamical behavior of the system. The biochemical network model we designed is based on both experimental and theoretical reported data. The p53 dynamics driven by miR-125b exhibit five distinct dynamical states: first and second stable states, first and second dynamical states, and a sustained oscillation state. These different p53 dynamical states may correspond to various cellular conditions. If the stress induced by miR-125b is weak, the system will be weakly activated, favoring a return to normal functioning. However, if the stress is significantly strong, the system will move to an active state. To sustain this active state, which is far from equilibrium with little scope for returning to normal conditions, the system may transition to an apoptotic state by crossing through other intermediate states, as it is unlikely to regain normal functioning. The p53 dynamical states show a multifractal nature, contributed by both short- and long-range correlations. The networks illustrated from these dynamical states follow hierarchical scale-free features, exhibiting an assortative nature with an absence of the centrality-lethality rule. Furthermore, the active dynamical state is generally closer to hierarchical characteristics and is self-organized. Our research study reveals that significant activity of miR-125b on the p53 regulatory network and its dynamics can only be observed when the system is slightly activated by ROS. However, this process does not necessarily require the direct study of ROS activity. These findings elucidate the mechanisms by which cells integrate signaling pathways with distinct temporal activity patterns to encode stress specificity and direct diverse cell fate decisions.
引用
收藏
页数:17
相关论文
共 85 条
  • [1] Switching p53 states by calcium: dynamics and interaction of stress systems
    Alam, Md. Jahoor
    Devi, Gurumayum Reenaroy
    Ravins
    Ishrat, Romana
    Agarwal, Subhash M.
    Singh, R. K. Brojen
    [J]. MOLECULAR BIOSYSTEMS, 2013, 9 (03) : 508 - 521
  • [2] Statistical mechanics of complex networks
    Albert, R
    Barabási, AL
    [J]. REVIEWS OF MODERN PHYSICS, 2002, 74 (01) : 47 - 97
  • [3] Spermine Metabolism and Anticancer Therapy
    Amendola, R.
    Cervelli, M.
    Fratini, E.
    Polticelli, F.
    Sallustio, D. E.
    Mariottini, P.
    [J]. CURRENT CANCER DRUG TARGETS, 2009, 9 (02) : 118 - 130
  • [4] Generation of oscillations by the p53-Mdm2 feedback loop: A theoretical and experimental study
    Bar-Or, RL
    Maya, R
    Segel, LA
    Alon, U
    Levine, AJ
    Oren, M
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2000, 97 (21) : 11250 - 11255
  • [5] The architecture of complex weighted networks
    Barrat, A
    Barthélemy, M
    Pastor-Satorras, R
    Vespignani, A
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2004, 101 (11) : 3747 - 3752
  • [6] Stimulus-dependent dynamics of p53 in single cells
    Batchelor, Eric
    Loewer, Alexander
    Mock, Caroline
    Lahav, Galit
    [J]. MOLECULAR SYSTEMS BIOLOGY, 2011, 7
  • [7] A novel cellular protein (MTBP) binds to MDM2 and induces a G1 arrest that is suppressed by MDM2
    Boyd, MT
    Vlatkovic, N
    Haines, DS
    [J]. JOURNAL OF BIOLOGICAL CHEMISTRY, 2000, 275 (41) : 31883 - 31890
  • [8] Regeneration of peroxiredoxins by p53-regulated sestrins, homologs of bacterial AhpD
    Budanov, AV
    Sablina, AA
    Feinstein, E
    Koonin, EV
    Chumakov, PM
    [J]. SCIENCE, 2004, 304 (5670) : 596 - 600
  • [9] Chen JD, 1996, MOL CELL BIOL, V16, P2445
  • [10] Power-Law Distributions in Empirical Data
    Clauset, Aaron
    Shalizi, Cosma Rohilla
    Newman, M. E. J.
    [J]. SIAM REVIEW, 2009, 51 (04) : 661 - 703