Ontology highlight
ABSTRACT:
PROVIDER: PRJNA356964 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5097240.fastq.gz | Fastqsanger.gz | |||
| SRR5097241.fastq.gz | Fastqsanger.gz | |||
| SRR5097242.fastq.gz | Fastqsanger.gz | |||
| SRR5097233.fastq.gz | Fastqsanger.gz | |||
| SRR5097243.fastq.gz | Fastqsanger.gz |
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Project description:All mammalian cells need oxygen. Inadequate oxygen (hypoxia) triggers cellular responses for survival and the maintenance of homeostasis. A transcription factor, hypoxia-inducible factor (HIF), plays a central role in the hypoxia response; its activity is regulated by the oxygen-dependent degradation of the HIF-1a protein. Despite the ubiquity and importance of hypoxia responses, very little is known about the variation in the global transcriptional response to hypoxia among different cell types and its links to tissue and cell-specific diseases. We analyzed the temporal changes in global transcript levels in response to hypoxia in primary renal proximal tubule epithelial cells (RPTECs), breast epithelial cells, smooth muscle (SMs), and endothelial cells (ECs) with DNA microarrays. The extent of the transcriptional response to hypoxia was greatest in the renal tubule cells. This exaggerated response was associated with a uniquely high level of HIF-1a RNA in renal cells and could be diminished by reducing HIF-1a expression via RNA interference (RNAi). A gene-expression signature of the hypoxia response, derived from our studies of cultured mammary and renal tubular epithelial cells, showed coordinated variation in several human cancers, and was a strong predictor of clinical outcomes in both breast and ovarian cancers. In an analysis of a large, published gene-expression dataset from breast cancers, we found that the prognostic information in the hypoxia signature was virtually independent of that provided by the previously reported wound signature and more predictive of outcomes than any of the clinical parameters in current use. A stimulus or stress experiment design type is where that tests response of an organism(s) to stress/stimulus. e.g. osmotic stress, behavioral treatment Using regression correlation
2010-07-01 | E-GEOD-3537 | biostudies-arrayexpress
Project description:All mammalian cells need oxygen. Inadequate oxygen (hypoxia) triggers cellular responses for survival and the maintenance of homeostasis. A transcription factor, hypoxia-inducible factor (HIF), plays a central role in the hypoxia response; its activity is regulated by the oxygen-dependent degradation of the HIF-1a protein. Despite the ubiquity and importance of hypoxia responses, very little is known about the variation in the global transcriptional response to hypoxia among different cell types and its links to tissue and cell-specific diseases. We analyzed the temporal changes in global transcript levels in response to hypoxia in primary renal proximal tubule epithelial cells (RPTECs), breast epithelial cells, smooth muscle (SMs), and endothelial cells (ECs) with DNA microarrays. The extent of the transcriptional response to hypoxia was greatest in the renal tubule cells. This exaggerated response was associated with a uniquely high level of HIF-1a RNA in renal cells and could be diminished by reducing HIF-1a expression via RNA interference (RNAi). A gene-expression signature of the hypoxia response, derived from our studies of cultured mammary and renal tubular epithelial cells, showed coordinated variation in several human cancers, and was a strong predictor of clinical outcomes in both breast and ovarian cancers. In an analysis of a large, published gene-expression dataset from breast cancers, we found that the prognostic information in the hypoxia signature was virtually independent of that provided by the previously reported wound signature and more predictive of outcomes than any of the clinical parameters in current use. A stimulus or stress experiment design type is where that tests response of an organism(s) to stress/stimulus. e.g. osmotic stress, behavioral treatment Keywords: stimulus_or_stress_design
2006-01-24 | GSE3537 | GEO
Project description:This dataset includes 60 BAM files from HF2354, HF3016 glioblastoma cell lines subjected to continuous stress (hypoxia, 3-day and 9-day), stress followed by recovery (irradiation, 4-day stress exposure and 5-day recovery), and no stress/normoxia controls and profiled using reduced-representation bisulfite sequencing.
| EGAD00001007770 | EGA
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:To understand how microRNAs are involved in stress response, we examined their expression changes in C. elegans animals that were exposed to stress conditions, including heat shock, oxidation, hypoxia and starvation.
2012-02-04 | GSE35529 | GEO
Project description:The cellular microenvironment shapes stem cell identity and differentiation capacity. Mammalian early embryos are exposed to hypoxia in vivo and benefit from hypoxic culture in vitro. Yet, how different components of the hypoxia response impact stem cell transcriptional networks and lineage choices remains unclear. Here we investigated the effect of acute and prolonged hypoxia on stem cell states and differentiation efficiencies of embryonic and extraembryonic cells. We show that prolonged hypoxia enhances differentiation of embryonic stem (ES) cells towards the mesendoderm lineage by transcriptionally priming cells with a primitive streak signature including Wnt3 and T expression. Exposure to hypoxia in ES culture or during formation of gastrulation-mimicking organoids (gastruloids) moderates T expression and enhances structural complexity. Hypoxic gastruloids generated without exogenous Wnt induction can spontaneously elongate and self-organize. Direct gene regulation by Hif1a, combined with DNA demethylation and metabolic rewiring modulate the transcriptional response and phenotypic outcome. Our findings highlight the influence of the microenvironment on stem cell function and provide a rationale supportive of applying physiological conditions in synthetic embryo models.
2022-09-05 | PXD026641 | Pride
Project description:The hypoxia frequently occurs in natural aquatic systems and aquaculture environment due to the natural reasons and human factors such as extreme climate, high density farming, environmental pollution and global warming, which have gradually become a huge threat to aquatic ecosystem functions and aquatic organism survival, causing serious ecological damage and enormous economic losses. Rainbow trout (Oncorhynchus mykiss), as a hypoxia-sensitive fish species, is a good model to study hypoxia stress. The molecular regulation and oxidative stress of rainbow trout still remains unknown in response to environmental hypoxia and reoxygenation stress. In this study, the transcriptome and biochemical indexes of rainbow trout liver in response to hypoxia for different durations were analyzed to highlight the changes in the molecular regulation and oxidative stress.
2021-02-25 | GSE167386 | GEO
Project description:Physiological shear stress, produced by blood flow, homeostatically regulates the phenotype of pulmonary endothelial cells exerting anti-inflammatory and anti-thrombotic actions and maintaining normal barrier function. In the pulmonary circulation hypoxia, due to high altitude or diseases such as COPD, causes vasoconstriction, increased vascular resistance and pulmonary hypertension. Hypoxia-induced changes in endothelial function play a central role in the development of this pulmonary hypertension. However, the direct interactive effects of hypoxia and shear stress on the pulmonary endothelial phenotype have not been extensively studied. We cultured human pulmonary microvascular endothelial cells (HPMEC) in normoxia or hypoxia while subjected to physiological shear stress or in static conditions. Unbiased proteomics was used to identify hypoxia-induced changes in protein expression. Using publicly available single cell RNA-seq datasets, differences in gene expression between the alveolar endothelial cells from COPD and healthy lungs were identified. 60 proteins were identified in HPMEC lysates whose expression changed in response to hypoxia in sheared but not in static conditions. mRNA for five of these (ERG, MCRIP1, EIF4A2, HSP90AA1 and DNAJA1) showed similar changes in the endothelial cells of COPD compared to healthy lungs. These data show that the proteomic responses of the pulmonary microvascular endothelium to hypoxia are significantly altered by shear stress and suggest that these differences are important in the development of hypoxic pulmonary vascular disease.
2023-02-17 | PXD036260 | Pride
Project description:Hypoxia response of human cancer cells
| PRJNA543430 | ENA
Project description:We profile the expression pattern of human pulmonary microvascular endothelial cells (HPMECs) at different time points of hypoxic stress. Through mRNA-seq, we identify functional waves of minor gene up-regulation at 8 and 24h hypoxia exposure followed by a massive wave of transcriptional activation after 48 hours. By weighted gene co-expression network analysis, we identify hub genes that likely play central roles in hypoxia transcription program. Strikingly, these hub genes included a prominent group of lincRNAs, suggesting non-coding RNAs may also have pivotal roles in the hypoxia regulatory circuit. HPMECs share a core hypoxia signature profile, but with some notably differences, indicating a portion of HPMECs hypoxia response is cell-specific. Collectively, our study comprehensive surveys the hypoxia transcriptome, and provides insight into the temporal dynamics of hypoxia transcriptional response. Time-course expression profiling of HPMECs exposed to hypoxia
2015-12-31 | E-GEOD-53510 | biostudies-arrayexpress