Recurrent Initiation: A Mechanism for Triggering p53 Pulses in Response to DNA Damage

Batchelor, Eric; Mock, Caroline S.; Bhan, Irun; Loewer, Alexander; Lahav, Galit

doi:10.1016/j.molcel.2008.03.016

Cited by 379 publications

(577 citation statements)

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“…These mod-els were the first to make the important distinction between nuclear and cytoplasmic concentrations. Some models have taken stochastic effects into account (Puszyński et al 2008;Proctor and Gray 2008;Ouattara et al 2010) while others have used time delays (Mihalas et al 2006;Ma et al 2005;Batchelor et al 2008), in a manner similar to that discussed for the Hes1 system previously. An attempt was made to model the spatial aspect of the system by Gordon (Gordon et al 2009), but this model also relied on time delays to produce oscillations.…”

Section: The P53-mdm2 Systemmentioning

confidence: 99%

Spatio-temporal modelling of the Hes1 and p53-Mdm2 intracellular signalling pathways

Sturrock

Terry

Xirodimas

et al. 2011

Journal of Theoretical Biology

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The correct localisation of transcription factors is vitally important for the proper functioning of many intracellular signalling pathways. Experimental data has shown that many pathways exhibit oscillations in concentrations of the substances involved, both temporally and spatially. Negative feedback loops are important components of these oscillations, providing fine regulation for the factors involved. In this paper we consider mathematical models of two such pathways -Hes1 and p53-Mdm2.Building on previous mathematical modelling approaches, we derive systems of partial differential equations to capture the evolution in space and time of the variables in the Hes1 and p53-Mdm2 systems. Through computational simulations we show that our reaction-diffusion models are able to produce sustained oscillations both spatially and temporally, accurately reflecting experimental evidence and advancing previous models. The simulations of our models also allow us to calculate a diffusion coefficient range for the variables in each mRNA and protein system, as well as ranges for other key parameters of the models, where sustained oscillations are observed. Finally, by exploiting the explicitly spatial nature of the partial differential equations, we are also able to manipulate mathematically the spatial location of the ribosomes, thus controlling where the proteins are synthesized within the cytoplasm. The results of these simulations predict an optimal distance outside the nucleus where protein synthesis should take place in order to generate sustained oscillations. Preprint submitted to Journal of Theoretical BiologyDecember 8, 2010 Using partial differential equation models, new information can be gained about the precise spatio-temporal dynamics of mRNA and proteins. The ability to determine spatial localisation of proteins within the cell is likely to yield fresh insight into a range of cellular diseases such as diabetes and cancer.

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Section: The P53-mdm2 Systemmentioning

confidence: 99%

Spatio-temporal modelling of the Hes1 and p53-Mdm2 intracellular signalling pathways

Sturrock

Terry

Xirodimas

et al. 2011

Journal of Theoretical Biology

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“…In biomolecular regulatory networks, oscillatory systems control many vital functions, including circadian rhythms (Zhang and Kay 2010), glycolysis (Chandra et al 2011), DNA damage response (Batchelor et al 2008), among others (Tiana et al 2007). Given this ubiquitousness, it is no surprise that oscillatory systems have been extensively studied for a long time ).…”

Section: Introductionmentioning

confidence: 99%

Design principles for robust oscillatory behavior

2015

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Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.

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“…When the DNA damage is not properly repaired, it can ultimately lead to cancer. Due to the relevance in cancer research, this pathway has been investigated in great detail, which includes modeling studies with the stressor γ-irradiation [25,[83][84][85][86][87][88][89][90][91][92][93][94][95][96][97].…”

Section: Dna Damage Response Pathwaymentioning

confidence: 99%

“…Batchelor et al [85] therefore proposed a model in which ATM and Chk2 activate p53 which subsequently activates (besides Mdm2) wild-type p53-induced phosphatase 1 (Wip1). Wip1 provides negative feedback in the pathway by inhibiting ATM and Chk2.…”

Section: Modelingmentioning

confidence: 99%

“…Wip1 provides negative feedback in the pathway by inhibiting ATM and Chk2. The origin of the pulsation of both ATM and Chk2 is ongoing DNA damage, which keeps reactivating ATM and Chk2 after deactivation by p53 [85]. In a follow-up study, Batchelor et al [84] showed that UV light instead of γ-irradiation also triggers p53 but is then regulated by different upstream targets: Whereas γ-irradiation triggers ATM and ATM triggers Chk2, UV light triggers ataxia telangiectasia and Rad3-related protein (ATR) and ATR triggers Chk1.…”

Section: Modelingmentioning

confidence: 99%

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Unraveling cellular pathways contributing to drug-induced liver injury by dynamical modeling

Kuijper

Yang

Water

et al. 2016

Expert Opinion on Drug Metabolism & Toxicology

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Introduction: Drug-induced liver injury (DILI) is a significant threat to human health and a major problem in drug development. It is hard to predict due to its idiosyncratic nature and which does not show up in animal trials. Hepatic adaptive stress response pathway activation is generally observed in drug-induced liver injury. Dynamical pathway modeling has the potential to foresee adverse effects of drugs before they go in trial. Ordinary differential equation modeling can offer mechanistic insight, and allows us to study the dynamical behavior of stress pathways involved in DILI. Areas covered: This review provides an overview on the progress of the dynamical modeling of stress and death pathways pertinent to DILI, i.e. pathways relevant for oxidative stress, inflammatory stress, DNA damage, unfolded proteins, heat shock and apoptosis. We also discuss the required steps for applying such modeling to the liver. Expert opinion: Despite the strong progress made since the turn of the century, models of stress pathways have only rarely been specifically applied to describe pathway dynamics for DILI. We argue that with minor changes, in some cases only to parameter values, many of these models can be repurposed for application in DILI research. Combining both dynamical models with in vitro testing might offer novel screening methods for the harmful side-effects of drugs. ARTICLE HISTORY

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Recurrent Initiation: A Mechanism for Triggering p53 Pulses in Response to DNA Damage

Cited by 379 publications

References 50 publications

Spatio-temporal modelling of the Hes1 and p53-Mdm2 intracellular signalling pathways

Spatio-temporal modelling of the Hes1 and p53-Mdm2 intracellular signalling pathways

Design principles for robust oscillatory behavior

Unraveling cellular pathways contributing to drug-induced liver injury by dynamical modeling

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