Ciliberto2005 - Steady states and oscillations in the p53/Mdm2 network
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ABSTRACT:
SUBMITTER: 
Krishna Kumar Tiwari
PROVIDER: BIOMD0000001006 | BioModels | 2024-09-02
REPOSITORIES: BioModels
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Steady states and oscillations in the p53/Mdm2 network.
Ciliberto Andrea A Novak Béla B Tyson John J JJ
Cell cycle (Georgetown, Tex.) 20050318 3
p53 is activated in response to events compromising the genetic integrity of a cell. Recent data show that p53 activity does not increase steadily with genetic damage but rather fluctuates in an oscillatory fashion. Theoretical studies suggest that oscillations can arise from a combination of positive and negative feedbacks or from a long negative feedback loop alone. Both negative and positive feedbacks are present in the p53/Mdm2 network, but it is not known what roles they play in the oscilla ...[more]
Similar Datasets
Project description:Recent observations show that the single-cell response of p53 to ionizing radiation (IR) is “digital” in that it is the number of oscillations rather than the amplitude of p53 that shows dependence on the radiation dose. We present a model of this phenomenon. In our model, double-strand break (DSB) sites induced by IR interact with a limiting pool of DNA repair proteins, forming DSB–protein complexes at DNA damage foci. The persisting complexes are sensed by ataxia telangiectasia mutated (ATM), a protein kinase that activates p53 once it is phosphorylated by DNA damage. The ATM-sensing module switches on or off the downstream p53 oscillator, consisting of a feedback loop formed by p53 and its negative regulator, Mdm2. In agreement with experiments, our simulations show that by assuming stochasticity in the initial number of DSBs and the DNA repair process, p53 and Mdm2 exhibit a coordinated oscillatory dynamics upon IR stimulation in single cells, with a stochastic number of oscillations whose mean increases with IR dose. The damped oscillations previously observed in cell populations can be explained as the aggregate behavior of single cell
2020-05-13 | MODEL2005130001 | BioModels
Project description:Proctor2008 - p53/Mdm2 circuit - p53 stabilisation by ATM
This model is described in the article:
Explaining oscillations and
variability in the p53-Mdm2 system.
Proctor CJ, Gray DA.
BMC Syst Biol 2008; 2: 75
Abstract:
BACKGROUND: In individual living cells p53 has been found to
be expressed in a series of discrete pulses after DNA damage.
Its negative regulator Mdm2 also demonstrates oscillatory
behaviour. Attempts have been made recently to explain this
behaviour by mathematical models but these have not addressed
explicit molecular mechanisms. We describe two stochastic
mechanistic models of the p53/Mdm2 circuit and show that
sustained oscillations result directly from the key biological
features, without assuming complicated mathematical functions
or requiring more than one feedback loop. Each model examines a
different mechanism for providing a negative feedback loop
which results in p53 activation after DNA damage. The first
model (ARF model) looks at the mechanism of p14ARF which
sequesters Mdm2 and leads to stabilisation of p53. The second
model (ATM model) examines the mechanism of ATM activation
which leads to phosphorylation of both p53 and Mdm2 and
increased degradation of Mdm2, which again results in p53
stabilisation. The models can readily be modified as further
information becomes available, and linked to other models of
cellular ageing. RESULTS: The ARF model is robust to changes in
its parameters and predicts undamped oscillations after DNA
damage so long as the signal persists. It also predicts that if
there is a gradual accumulation of DNA damage, such as may
occur in ageing, oscillations break out once a threshold level
of damage is acquired. The ATM model requires an additional
step for p53 synthesis for sustained oscillations to develop.
The ATM model shows much more variability in the oscillatory
behaviour and this variability is observed over a wide range of
parameter values. This may account for the large variability
seen in the experimental data which so far has examined ARF
negative cells. CONCLUSION: The models predict more regular
oscillations if ARF is present and suggest the need for further
experiments in ARF positive cells to test these predictions.
Our work illustrates the importance of systems biology
approaches to understanding the complex role of p53 in both
ageing and cancer.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000188.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000188 | BioModels
Project description:Proctor2008 - p53/Mdm2 circuit - p53 stabilisation by p14ARF
This model is described in the article:
Explaining oscillations and
variability in the p53-Mdm2 system.
Proctor CJ, Gray DA.
BMC Syst Biol 2008; 2: 75
Abstract:
BACKGROUND: In individual living cells p53 has been found to
be expressed in a series of discrete pulses after DNA damage.
Its negative regulator Mdm2 also demonstrates oscillatory
behaviour. Attempts have been made recently to explain this
behaviour by mathematical models but these have not addressed
explicit molecular mechanisms. We describe two stochastic
mechanistic models of the p53/Mdm2 circuit and show that
sustained oscillations result directly from the key biological
features, without assuming complicated mathematical functions
or requiring more than one feedback loop. Each model examines a
different mechanism for providing a negative feedback loop
which results in p53 activation after DNA damage. The first
model (ARF model) looks at the mechanism of p14ARF which
sequesters Mdm2 and leads to stabilisation of p53. The second
model (ATM model) examines the mechanism of ATM activation
which leads to phosphorylation of both p53 and Mdm2 and
increased degradation of Mdm2, which again results in p53
stabilisation. The models can readily be modified as further
information becomes available, and linked to other models of
cellular ageing. RESULTS: The ARF model is robust to changes in
its parameters and predicts undamped oscillations after DNA
damage so long as the signal persists. It also predicts that if
there is a gradual accumulation of DNA damage, such as may
occur in ageing, oscillations break out once a threshold level
of damage is acquired. The ATM model requires an additional
step for p53 synthesis for sustained oscillations to develop.
The ATM model shows much more variability in the oscillatory
behaviour and this variability is observed over a wide range of
parameter values. This may account for the large variability
seen in the experimental data which so far has examined ARF
negative cells. CONCLUSION: The models predict more regular
oscillations if ARF is present and suggest the need for further
experiments in ARF positive cells to test these predictions.
Our work illustrates the importance of systems biology
approaches to understanding the complex role of p53 in both
ageing and cancer.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000188.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000189 | BioModels
Project description:Circular RNAs (circRNAs) are a class of noncoding RNAs produced by a non-canonical form of alternative splicing called back-splicing. To investigate a potential role of circRNAs in the p53 pathway, we analyzed RNA-seq data from colorectal cancer cell lines (HCT116, RKO and SW48) in the presence or absence of DNA damage. Surprisingly, unlike the strong p53-dependent induction of hundreds of p53-induced mRNAs, only a few circRNAs were induced from the p53-induced genes. Circ-MDM2, an annotated circRNA from the MDM2 locus, was one of the handful of circRNAs that originated from a p53-induced gene. Given the central role of MDM2 in suppressing p53 protein levels and p53 activity, we investigated the function of circ-MDM2. Knocking down circ-MDM2 with siRNAs that targeted the circ-MDM2 junction and had no effect on linear MDM2 mRNA, resulted in increased basal p53 levels and growth defects in vitro and in vivo. Consistent with these results, transcriptome profiling showed increased expression of several direct p53 targets, reduced Rb phosphorylation and defects in G1-S progression upon silencing circ-MDM2. Our results reveal the role of a novel circRNA by which the MDM2 locus suppresses p53 levels and cell cycle progression.
2020-03-04 | GSE138016 | GEO
Project description:Integrated-systems model of oxidative stress connecting NRF2 and p53 signaling pathways. Additional crosstalk linking oxidative stress to p53 inhibition, p53 to NRF2 through p21, and NRF2 to MDM2 was incorporated in this model. The NRF2 pathway was encoded as first- and second-order rate equations for KEAP1 oxidation and NRF2 stabilization; NRF2-mediated transcription of antioxidant enzymes was modeled as a Hill function. The p53 pathway was reconstructed from a delay differential equation model of p53 signaling in response to DNA damage. To adapt the p53 DNA-damage model to respond to oxidative stress, we used a first-order oxidation reaction of ATM/CHEK2 by intracellular H2O2.
The integrated base model of NRF2–p53 oxidative-stress signaling contains 42 reactions and 22 ordinary differential equations (ODEs).
2021-10-29 | MODEL2110270001 | BioModels
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Project description:TRAF6 -/- thymi display defects in IR-induced p53 target gene expression and attenuate further enhancement of apoptosis upon IR treatment. TRAF6-mediated K63-linked ubiquitination of p53 at K24
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