Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA130369 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Background: Niemann Pick type C disease (NPC) is a neurovisceral lipid storage disorder, characterized by unesterified cholesterol accumulation in lysosomal/late endosome compartments. The main tissues affected in the disease are the liver and the cerebellum. Although the primary defect in this disease occurs in the liver, the pathological mechanisms involved in hepatocyte damage and death have been poorly explored. Here, we assessed biochemical parameters, liver histology and the mRNA abundance of genes encoding proteins associated to oxidative stress, copper metabolism, fibrosis and inflammation and cholesterol metabolism in livers of WT and NPC mice. Methodology/Principal Findings: We found that the histology of NPC mice livers show signals of inflammation and fibrosis. This was correlated with an increase of carbonylated proteins and reduced glutathione content in the liver, as well as a significantly increment of total content of copper in liver tissue. Finally, we analyzed the liver gene expression pattern by qPCR and microarray assays. We found a correlation between the tissue fibrotic status and a differential hepatic expression of genes related to oxidative stress, fibrosis and inflammation processes in NPC mice. Conclusions/Significance: Our data show that NPC liver disease is evidenced by an increase in fibrosis as well as in oxidative stress status. Concomitantly, there is a correlation with an altered gene expression pattern, mainly of oxidative stress and fibrosis related genes, which could be useful as a potential disease progression biomarkers. We compared three liver samples from NPC mice to a common reference sample made from pooled mRNA of three wild type mice
2010-09-14 | E-GEOD-24013 | biostudies-arrayexpress
Project description:Background: Niemann Pick type C disease (NPC) is a neurovisceral lipid storage disorder, characterized by unesterified cholesterol accumulation in lysosomal/late endosome compartments. The main tissues affected in the disease are the liver and the cerebellum. Although the primary defect in this disease occurs in the liver, the pathological mechanisms involved in hepatocyte damage and death have been poorly explored. Here, we assessed biochemical parameters, liver histology and the mRNA abundance of genes encoding proteins associated to oxidative stress, copper metabolism, fibrosis and inflammation and cholesterol metabolism in livers of WT and NPC mice. Methodology/Principal Findings: We found that the histology of NPC mice livers show signals of inflammation and fibrosis. This was correlated with an increase of carbonylated proteins and reduced glutathione content in the liver, as well as a significantly increment of total content of copper in liver tissue. Finally, we analyzed the liver gene expression pattern by qPCR and microarray assays. We found a correlation between the tissue fibrotic status and a differential hepatic expression of genes related to oxidative stress, fibrosis and inflammation processes in NPC mice. Conclusions/Significance: Our data show that NPC liver disease is evidenced by an increase in fibrosis as well as in oxidative stress status. Concomitantly, there is a correlation with an altered gene expression pattern, mainly of oxidative stress and fibrosis related genes, which could be useful as a potential disease progression biomarkers.
2010-09-14 | GSE24013 | GEO
Project description:We established a comprehensive temporal dynamic response profile of a large set of BAC-GFP HepG2 cell lines representing the following components of stress signaling: i) unfolded protein response (UPR) [ATF4, XBP1, BIP and CHOP]; ii) oxidative stress [NRF2, SRXN1, HMOX1]; iii) DNA damage [P53, P21, BTG2, MDM2]; and iv) NF-κB pathway [A20, ICAM1]. Using logic-based ordinary differential equation (Logic-ODE), we modelled the dynamic profiles of the different stress responses and extracted specific descriptors potentially predicting the progressive outcomes.
Please see the most updated version on GitHub: https://github.com/saezlab/LogicODE_GFP_SR
2022-08-02 | MODEL2206070001 | BioModels
Project description:miRNA profile of duck duodenum mucosa damage caused by oxidative stress
| PRJNA996064 | ENA
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:Study of Oxidative stress Markers (F2 Isoprostanes for lipid peroxidation, Carbonyl groups for protein peroxidation, 3 Nitrotyrosine for damage by nitrogens, and 8-Hydroxyguanosine for RNA peroxidation)in patients with colorectal cancer undergo surgical treatment (preoperatively during the intervention and postoperatively) and controls.
| 2115584 | ecrin-mdr-crc
Project description:This is the model described in the article:
A mathematical model of glutathione metabolism.
Michael C Reed, Rachel L Thomas, Jovana Pavisic, S. Jill James, Cornelia M Ulrich and H. Frederik Nijhout, Theor Biol Med Model 2008,5:8; PubmedID:18442411 ; DOI:10.1186/1742-4682-5-8;
Abstract:
BACKGROUND: Glutathione (GSH) plays an important role in anti-oxidant defense and detoxification reactions. It is primarily synthesized in the liver by the transsulfuration pathway and exported to provide precursors for in situ GSH synthesis by other tissues. Deficits in glutathione have been implicated in aging and a host of diseases including Alzheimer's disease, Parkinson's disease, cardiovascular disease, cancer, Down syndrome and autism.
APPROACH: We explore the properties of glutathione metabolism in the liver by experimenting with a mathematical model of one-carbon metabolism, the transsulfuration pathway, and glutathione synthesis, transport, and breakdown. The model is based on known properties of the enzymes and the regulation of those enzymes by oxidative stress. We explore the half-life of glutathione, the regulation of glutathione synthesis, and its sensitivity to fluctuations in amino acid input. We use the model to simulate the metabolic profiles previously observed in Down syndrome and autism and compare the model results to clinical data.
CONCLUSION: We show that the glutathione pools in hepatic cells and in the blood are quite insensitive to fluctuations in amino acid input and offer an explanation based on model predictions. In contrast, we show that hepatic glutathione pools are highly sensitive to the level of oxidative stress. The model shows that overexpression of genes on chromosome 21 and an increase in oxidative stress can explain the metabolic profile of Down syndrome. The model also correctly simulates the metabolic profile of autism when oxidative stress is substantially increased and the adenosine concentration is raised. Finally, we discuss how individual variation arises and its consequences for one-carbon and glutathione metabolism.
parameter
orig. article
this model
Vm_CBS
700000
420000
Vm_GNMT
245
260
K_sam_GNMT
32
63
Vr_MTD(mito)
600000
595000
V_CBS
kinetic law
rearranged
V_bmetc
913
913.4
Vm_GR
8925
892.5
This version of the model contains a feeding rhythm as used in figure 5 of the original article. Four parameters, breakfast, lunch
dinner and fasting, describe the relative level of amino acids, described by the parameter aa_input or Aminoacid_input, in the blood. To remove the daily feeding rhythm, either set the parameters for meals and fasting to 1 (or for figure 3 to 0.333), or remove the assignment rule for the Aminoacid_input. For the steady state evaluations for figure 6, the mealtime parameters were set to one, which, while making Copasi complain about explicit time dependency, still gives valid results.
This version of the model differs slightly from the version described in the supplement, in which contains some typos. It was corrected using the version of JWS-online, created using the original matlab files, thankfully provided by the articles authors. Many thanks to Jacky Snoep for his help and support.
In the SBML version of the model the volumes of the mitochondrion, the cytoplasm and the cell were all set to one to obtain the same equations as described in the supplemental materials of the article. The total folate is equally split between the cytosol and the mitochondrion and divided by 3/4 for the cytosol and 1/4 for the mitochondrion, respectively. To obtain an SBML model in which the volumes of the compartments, cytosol and mito, are used, the model needs to be altered as follows:
for the initial distribution of folate the terms 3/4 and 1/4 have to be replaced by volumes of cytosol and mitochondria respectively
in the transport reactions between mitochondrion and cytosol the stoichiometry of the mitochondrial reactants has to be set from 3 to 1 and in the first part of the according rate laws the factor mito/3 should simply be replaced with mito.
the stoichiometries of src and dmg have to be changed to cell/mito for mitchondrial and cell/cytosol for cytosolic reactions involving these two species (for the relative volumes used in the article this would be 4 for mitochondrial reactions and 1.33333 for cytosolic ones).
While the concentrations stay the same after these alteration, the reaction fluxes change by a factor of cytosol and mito for cytosolic and mitchondrial reactions, respectively.
Originally created by libAntimony v1.3 (using libSBML 3.4.1)
2024-09-02 | BIOMD0000000268 | BioModels
Project description:Hepatic injury provoked by cold storage is a major problem affecting liver transplantation, as exposure to cold induces apoptosis in hepatic tissues. Long noncoding RNAs (lncRNAs) are increasingly understood to regulate apoptosis, but the contribution of lncRNAs to cold-induced liver injury remains unknown. Using RNA-seq, we determined the differential lncRNA expression profile in mouse livers after cold storage and found that expression of the lncRNA TUG1 was significantly down-regulated. Over-expression of TUG1 attenuated cold-induced apoptosis in mouse hepatocytes and liver sinusoidal endothelial cells LSECs, in part by blocking mitochondrial apoptosis and ER stress pathways. Moreover, TUG1 attenuated apoptosis, inflammation and oxidative stress in vivo in livers subjected to cold storage. Over-expression of TUG1 also improved hepatocyte function and prolonged hepatic graft survival rates in mice. These results suggest that the lncRNA TUG1 exerts a protective effect against cold-induced liver damage by inhibiting apoptosis in mice, and suggests a potential role for TUG1 as a target for the prevention of cold-induced liver damage in liver transplantation.
2016-01-07 | GSE76609 | GEO
Project description:Oxidative stress and inflammation are closely related, and inter-dependent pathophysiological processes. Oxidative stress plays a key role in the pathophysiology of several chronic inflammatory conditions that causes cellular alterations such as lipid damage, increase of cell permeability, apoptosis/cell death, alteration in growth factors, and signaling pathways.An imbalance between the production of reactive oxygen species (ROS) and their neutralization by the antioxidant system results in the onset of oxidative stress which subsequently leads to the release of chronic inflammatory mediators such as pro-inflammatory cytokines, which causes damages to DNA, proteins, and lipids.LC-MSMS is widely used for non-targeted and non-invasive metabolomics of biological samples including saliva in a variety of conditions such as inflammatory conditions, cancers, diabetes, etc. However, to the best of our knowledge, there are currently no metabolomics-based studies identifying salivary biomarkers associated with inflammation and oxidative stress utilizing HPLC-ESI-QTOF-MS. Therefore, in this study, we aim to discover the biochemical and physiological changes induced by medwak smoking and explore the metabolomics profile of medwak smokers with a focus on the markers of oxidative stress and inflammation in comparison to nonsmokers.
2022-06-20 | ST002211 | MetabolomicsWorkbench
Project description:This SuperSeries is composed of the following subset Series:; GSE12220: Changes in Saccharomyces cerevisiae mRNA abundance following oxidative stress and DNA damage stress; GSE12221: Decay profiles of Saccharomyces cerevisiae mRNAs following oxidative stress and DNA damage Experiment Overall Design: Refer to individual Series
2008-10-26 | E-GEOD-12222 | biostudies-arrayexpress