P53 activity results in DNA replication fork processivity
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE87668 | GEO | 2016/10/06
SECONDARY ACCESSION(S): PRJNA345510
REPOSITORIES: GEO
Similar Datasets
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: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: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:Its a mathematial model studying steady state and oscialltions in p53-MDM2 network triggered by IR induced DNA Damage.
2024-09-02 | BIOMD0000001006 | BioModels
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
Project description:The tumor suppressor p53 plays a critical role in the cellular response to various stresses, including DNA damage, hypoxia, nutrition starvation, and oncogene activation. However, wild-type p53 function was largely impaired in cancer cells, one of the reasons is the inhibition by p53 negative regulating proteins (iASPP, MDM2 etc.). To globally evaluate the transcriptome inhibited by iASPP and the potent synergy of co-inhibiting MDM2, we performed RNAseq analysis in colon cancer cell line HCT116 upon p53 or iASPP knockdown with or without Nutlin-3 treatment.
2022-10-29 | GSE139546 | GEO
Project description:After DNA damage, cells activate p53, a tumor suppressor gene, and select a cell fate (e.g., DNA repair, cell cycle arrest, or apoptosis). Recently, a p53 oscillatory behavior was observed following DNA damage. However, the relationship between this p53 oscillation and cell-fate selection is unclear. Here, we present a novel model of the DNA damage signaling pathway that includes p53 and whole cell cycle regulation and explore the relationship between p53 oscillation and cell fate selection. The simulation run without DNA damage qualitatively realized experimentally observed data from several cell cycle regulators, indicating that our model was biologically appropriate. Moreover, the comprehensive sensitivity analysis for the proposed model was implemented by changing the values of all kinetic parameters, which revealed that the cell cycle regulation system based on the proposed model has robustness on a fluctuation of reaction rate in each process. Simulations run with four different intensities of DNA damage, i.e. Low-damage, Medium-damage, High-damage, and Excess-damage, realized cell cycle arrest in all cases. Low-damage, Medium-damage, High-damage, and Excess-damage corresponded to the DNA damage caused by 100, 200, 400, and 800 J/m(2) doses of UV-irradiation, respectively, based on expression of p21, which plays a crucial role in cell cycle arrest. In simulations run with High-damage and Excess-damage, the length of the cell cycle arrest was shortened despite the severe DNA damage, and p53 began to oscillate. Cells initiated apoptosis and were killed at 400 and 800 J/m(2) doses of UV-irradiation, corresponding to High-damage and Excess-damage, respectively. Therefore, our model indicated that the oscillatory mode of p53 profoundly affects cell fate selection.
2024-09-02 | BIOMD0000000939 | BioModels
Project description:The MDM2 oncoprotein is an essential component of the p53 pathway. Although MDM2 has been widely described as a major negative regulator of the p53 tumor suppressor, growing evidences support the notion that Mdm2 functions are also mediated through p53 independent mechanisms. We found that MDM2 is recruited on chromatin. By ChIP-Seq (using MDM2 antibody) of H1299 cells exhibiting MDM2 recruitment on chromatin, we identified at the whole genome level MDM2 binding sites. Both input and IPped-DNA were exhaustively sequenced and mapped on human genome
2016-06-09 | GSE64439 | GEO
Project description:This a model from the article:
Stress-specific response of the p53-Mdm2 feedback loop
Alexander Hunziker, Mogens H Jensen and Sandeep Krishna
BMC Systems Biology 2010, Jul 12;4(1):94
20624280,
Abstract:
ABSTRACT: BACKGROUND: The p53 signalling pathway has hundreds of inputs and outputs. It can trigger cellular senescence, cell-cycle arrest and apoptosis in response to diverse stress conditions, including DNA damage, hypoxia and nutrient deprivation. Signals from all these inputs are channeled through a single node, the transcription factor p53. Yet, the pathway is flexible enough to produce different downstream gene expression patterns in response to different stresses. RESULTS: We construct a mathematical model of the negative feedback loop involving p53 and its inhibitor, Mdm2, at the core of this pathway, and use it to examine the effect of different stresses that trigger p53. In response to DNA damage, hypoxia, etc., the model exhibits a wide variety of specific output behaviour -- steady states with low or high levels of p53 and Mdm2, as well as spiky oscillations with low or high average p53 levels. CONCLUSIONS: We show that even a simple negative feedback loop is capable of exhibiting the kind of flexible stress-specific response observed in the p53 system. Further, our model provides a framework for predicting the differences in p53 response to different stresses and single nucleotide polymorphisms.
The parameters of the model corresponds to the resting state, with delta = 11hr-1, gamma = 0.2hr-1, kt = 0.03nM-1hr-1 and kf = 5000nM-1hr-1.
To simulate different stress conditions as in figure 2A (also look at the curation figure of this model) of the reference publication, the above parameter should be changed. The parameter values corresponding to different stress conditions are shown in the following table.
Stress Condition/Parameter
delta
gamma
kt
kf
Nutlin
11hr-1
0.2hr-1
0.03nM-1hr-1
500nM-1hr-1
Oncogene
2hr-1
0.2hr-1
0.03nM-1hr-1
5000nM-1hr-1
DNA damage
2hr-1
0.5hr-1
0.03nM-1hr-1
2500nM-1hr-1
Hypoxia
2hr-1
0.2hr-1
0.01nM-1hr-1
5000nM-1hr-1
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2011 The BioModels.net Team.For more information see the terms of use.To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2024-09-02 | BIOMD0000000252 | 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