Nodal points and complexity of Notch-Ras signal integration
Ontology highlight
ABSTRACT:
ORGANISM(S): Drosophila melanogaster
PROVIDER: GSE11203 | GEO | 2009/01/06
SECONDARY ACCESSION(S): PRJNA106803
REPOSITORIES: GEO
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Project description:Metazoans utilize a handful of highly conserved signaling pathways to create a signaling backbone that governs all stages of development, by providing spatial and temporal cues that influence gene expression. How these few signals have such a versatile developmental action is of significance to evolution, development, and disease. Their versatility likely depends upon the larger-scale network they form through integration. Such integration is exemplified by cross-talk between the Notch and the Receptor Tyrosine Kinase (RTK) pathways. We examined the transcriptional output of Notch-RTK cross-talk during Drosophila development and present in vivo data that supports a role for selected mutually-regulated genes as potentially important nodal points for signal integration. We find the complex interplay between these pathways involves their mutual regulation of numerous core components of RTK signaling in addition to targets that include components of all the major signalling pathways (TGF-β, Hh, Jak/Stat, Nuclear Receptor and Wnt). Interestingly, Notch-RTK integration did not lead to general antagonism of either pathway, as is commonly believed. Instead, integration had a combinatorial effect on specific cross-regulated targets, which unexpectedly included the majority of Ras-responsive genes, suggesting Notch can specify the response to Ras activation. Experiment Overall Design: To identify nodal points that interlink the Notch and RTK pathways, we examined the transcriptional output of each during Drosophila embryonic development and identified common transcriptional targets. Pathway activation was achieved through ubiquitous GAL4-mediated expression of activated Notch (UAS-NotchICD) or through an activated form of the RTK signal mediator Ras1 (UAS-Ras1V12), either alone or in combination, under the control of the armadillo promoter, which drives GAL4 at moderate physiological levels. Homozygous armadillo-GAL4 virgin females were crossed either to: 1) homozygous UAS-NotchICD males; 2) males homozygous for both UAS-Ras1V12 and UAS-NotchICD; or 3) homozygous UAS-Ras1V12 males. As a control for GAL4 dependent effects, homozygous armadillo-GAL4 virgin females were crossed to w1118 males. Embryos resulting from these crosses were collected on apple juice plates for one hour, incubated at 25°C for 5 hours and 30 minutes for the first time point and 6 hours and 45 minutes for the second time point; dechorionated by treatment with 50% Chlorox bleach at room temperature for 1 minute with agitation, washed with 0.5X PBS, 1% Tween, rinsed with ddH2O. Embryos were then shock frozen and stored in liquid nitrogen at 5:45-6:45 hours After Egg Lay (AEL) for the first time point and 7-8 hours AEL for the second. All collections were performed in parallel sets but staggered to equalize the length of embryo submersion in liquid. Each collection contained approximately 500 embryos. Frozen embryos were ground by pestle in the Trizol reagent (Invitrogen). RNA was extracted via standard methods, with the inclusion of an additional Trizol extraction prior to RNA precipitation to increase RNA purity. Total RNA was prepared from three independent experiments for each described embryonic genotype at each of the two time points. RNA samples were subjected in triplicate to analysis by Affymetrix high-density oligonucleotide arrays using the DrosGenome1 array (Affymetrix) that contains 14,010 probe sets specific to 13,108 Drosophila genes. Probe synthesis and microarray hybridization were performed according to standard Affymetrix protocols. External standards were included to control for hybridization efficiency and sensitivity. Following washing, the chips were scanned with a Hewlett-Packard GeneArray laser scanner. Signal levels were obtained and statistical analysis performed using GC-Robust Multi-Array expression measure (GC-RMA) and LInear Modes for MicroArray (LIMMA) data packages and the affylmGUI graphical user interface in the R programming environment.
2009-01-14 | E-GEOD-11203 | biostudies-arrayexpress
Project description:Background: Interaction between key signaling mechanisms is important to generate the diversity in signaling output required for proper control of cellular differentiation and function, although the molecular manifestations of such cross-talk are only partially understood. Notch signaling and the cellular response to hypoxia intersect at different points in the signaling cascades, and in this report we analyze the consequences of this cross-talk at the transcriptome level. Results: Mouse ES cells were subjected to various combinations of hypoxia and/or activated Notch signaling, and the transcriptome changes could be grouped into different categories, reflecting various modes of hypoxia and Notch signaling integration. Two principal categories of novel Notch- and hypoxia-induced genes were identified: i) a larger set of genes induced by one pathway and not significantly affected by the activity status of the other pathway; and ii) a smaller set of genes co-regulated by Notch and hypoxia. In the latter category, we identified genes that were induced by hypoxia and the expression of which was enhanced by active Notch signaling. In addition, a number of genes were induced by Notch and hypoxia independently, and a final category of genes required simultaneous activation of Notch and hypoxia to be significantly induced. Several of the hypoxia- and Notch-induced genes were found to be upregulated in various forms of cancer. Conclusions: We identify novel Notch and hypoxia downstream genes and genes co-regulated by the two pathways, providing a molecular platform to better understand the intersection between the two signaling cascades in normal development and cancer.
2009-12-31 | GSE19074 | GEO
Project description:Purpose: analyze ligand and receptor genes regulated at early time points following JAK STAT pathway stimulation During development and homeostasis, cells integrate multiple signals originating either from neighboring cells or systemically. In turn, responding cells can produce signals that act in an autocrine, paracrine, or endocrine manner. Although the nature of the signals and pathways used in cell-cell communication are well characterized, we lack, in most cases, an integrative view of signaling describing the spatial and temporal interactions between pathways (e.g., whether the signals are processed sequentially or concomitantly when two pathways are required for a specific outcome). To address the extent of cross-talk between the major metazoan signaling pathways, we characterized immediate transcriptional responses to either single- or multiple pathway stimulations in homogeneous Drosophila cell lines. Our study, focusing on seven core pathways, epidermal growth factor receptor (EGFR), bone morphogenetic protein (BMP), Jun kinase (JNK), JAK/STAT, Notch, Insulin, and Wnt, revealed that many ligands and receptors are primary targets of signaling pathways, highlighting that transcriptional regulation of genes encoding pathway components is a major level of signaling cross-talk. In addition, we found that ligands and receptors can integrate multiple pathway activities and adjust their transcriptional responses accordingly. RNA-seq data is for JAK STAT pathway only
2018-12-01 | GSE123167 | GEO
Project description:This model is from the article:
PI3K-dependent cross-talk interactions converge with Ras as quantifiable inputs integrated by Erk.
Wang CC, Cirit M, Haugh JM Mol. Syst. Biol.
2009;5:246. 19225459
,
Abstract:
Although it is appreciated that canonical signal-transduction pathways represent dominant modes of regulation embedded in larger interaction networks, relatively little has been done to quantify pathway cross-talk in such networks. Through quantitative measurements that systematically canvas an array of stimulation and molecular perturbation conditions, together with computational modeling and analysis, we have elucidated cross-talk mechanisms in the platelet-derived growth factor (PDGF) receptor signaling network, in which phosphoinositide 3-kinase (PI3K) and Ras/extracellular signal-regulated kinase (Erk) pathways are prominently activated. We show that, while PI3K signaling is insulated from cross-talk, PI3K enhances Erk activation at points both upstream and downstream of Ras. The magnitudes of these effects depend strongly on the stimulation conditions, subject to saturation effects in the respective pathways and negative feedback loops. Motivated by those dynamics, a kinetic model of the network was formulated and used to precisely quantify the relative contributions of PI3K-dependent and -independent modes of Ras/Erk activation.
This model is parameterized with the median of the estimated parameters given in the supplementary material of the original publication's (doi: 10.1038/msb.2009.4
) supplement
on pages 8 and 9.
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2010 The BioModels.net Team.
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.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
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.
2010-01-21 | BIOMD0000000288 | BioModels
Project description:Muscle development and regeneration strongly depends on extracellular cues and growth factors, which are taken up by muscle stem cells and guide them either towards proliferation and fusion or towards quiescence. Here we investigated the effect of bone morphogenetic protein (BMP) signaling on Pax7 positive adult muscle stem cells of the mouse. We discovered a cross talk between the BMP- and NOTCH-signalling pathways, leading to high upregulation upon BMP4/BMP6-stimulation of Hes1 mRNA which is a key component of the NOTCH-siganling pathway.
2023-10-01 | GSE127798 | GEO
Project description:Muscle development and regeneration strongly depends on extracellular cues and growth factors, which are taken up by muscle stem cells and guide them either towards proliferation and fusion or towards quiescence. Here we investigated the effect of bone morphogenetic protein (BMP) signaling on Pax7 positive adult muscle stem cells of the mouse. We discovered a cross talk between the BMP- and NOTCH-signalling pathways, leading to high upregulation upon BMP4/BMP6-stimulation of Hes1 mRNA which is a key component of the NOTCH-siganling pathway.
2023-10-01 | GSE159594 | GEO
Project description:This a model from the article:
Modeling specificity in the yeast MAPK signaling networks
Zou X, Peng T, Pan Z J. Theor. Biol.
(2008);250(1):139-55 17977559
,
Abstract:
Cells sense several kinds of stimuli and trigger corresponding responses through signaling pathways. As a result, cells must process and integrate multiple signals in parallel to maintain specificity and avoid erroneous cross-talk. In this study, we focus our theoretical effort on understanding specificity of a model network system in yeast, Saccharomyces cerevisiae, which contains three mitogen-activated protein kinase (MAPK) signal transduction cascades that share multiple signaling components. The cellular response to the pheromone, the filamentous growth and osmotic pressure stimuli in yeast is described and an integrative mathematical model for the three MAPK cascades is developed using available literature and experimental data. The theoretical framework for analyzing the specificity of signaling networks [Bardwell, L., Zou, X.F., Nie, Q., Komarova, N.L., 2007. Mathematical models of specificity in cell signaling. Biophys. J. 92, 3425-3441] is extended to include multiple interacting pathways with shared components. Simulations are also performed with any one stimulus, with any two simultaneous stimuli, and with the simultaneous application of the three stimuli. The interactions between the three pathways are systematically investigated. Moreover, the specificity and fidelity of this model system are calculated using our newly developed concept under different stimuli or with specific mutants. Our simulated and calculated results demonstrate that the yeast MAPK signaling network can achieve specificity and fidelity by filtering out spurious cross-talk between the relevant pathways through different mechanisms, such as scaffolding, cross-inhibiting, and feedback control. Proof that Pbs2 and Hog1 are essential for the maintenance of signaling specificity is presented. Our studies provide novel insights into integration of relevant signaling pathways in a biological system and the mechanisms conferring specificity in cellular signaling networks.
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
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.
2005-01-01 | MODEL7519354389 | BioModels
Project description:Background: Signaling by receptor tyrosine kinases (RTK) is frequently dysregulated in gliomas. Inter-individual variability in the causes for dysregulated RTK signaling may have hampered the efficacy of targeted therapies. Using gene expression modules around key regulators in the RAS-RAF-MEK-MAPK cascade and in the phosphatidylinositol 3-kinase-AKT pathways, we developed a âRMPAâ clustering scheme to distinguish gliomas with varying extents of RTK signaling. Results: We identified gene modules consistently co-expressed with NF1 (NF1-M), Sprouty (SPRY-M) and PTEN (PTEN-M) in gliomas. Their signatures enabled robust clustering of adult diffuse gliomas of WHO grades II-IV into RMPAhigh and RMPAlow phenotypes in a morphology-independent manner. In five independent data sets from three continents containing more than 1500 adult diffuse gliomas, RMPAhigh gliomas were associated with poor prognosis while RMPAlow gliomas were not. The RMPAhigh and RMPAlow glioma subtypes showed distinct levels of the activities of RAS-RAF-MEK-MAPK cascade and PI3K-AKT pathway and harbored unique sets of genomic alterations in the RTK signaling-related genes. The RMPAhigh gliomas contained large numbers of immature vessel cells and tumor associated macrophages and both cell types expressed high levels of pro-angiogenic RTKs including MET, VEGFR1, KDR, EPHB4 and NRP1. Conclusion: Inter-glioma variability in RTK signaling activities can be defined using the RMPA clustering scheme. The combined signatures of NF1-M, SPRY-M and PTEN-M reflect RTK signaling activity both in the glioma cells and in the glioma microenvironment. Our data show that RTK signaling in the glioma microenvironment may play a pivotal role in glioma progression. Transcriptome data from 22 fresh gliomas (2 astrocytoma II, 1 oligodendrocytoma II, 7 oligoastrocytoma II, 4 anaplastic oligoastrocytoma III and 8 GBM) were obtained using Affymetrix Human Gene 1.0 ST Array. Unsupervised hierarchical clustering of the expression data for the SPRY-M, NF1-M and PTEN-M was performed on these transcriptome data to identify samples with RMPAhigh or RMPAlow signature.
2015-10-30 | E-GEOD-74462 | biostudies-arrayexpress
Project description:Background: Signaling by receptor tyrosine kinases (RTK) is frequently dysregulated in gliomas. Inter-individual variability in the causes for dysregulated RTK signaling may have hampered the efficacy of targeted therapies. Using gene expression modules around key regulators in the RAS-RAF-MEK-MAPK cascade and in the phosphatidylinositol 3-kinase-AKT pathways, we developed a “RMPA” clustering scheme to distinguish gliomas with varying extents of RTK signaling. Results: We identified gene modules consistently co-expressed with NF1 (NF1-M), Sprouty (SPRY-M) and PTEN (PTEN-M) in gliomas. Their signatures enabled robust clustering of adult diffuse gliomas of WHO grades II-IV into RMPAhigh and RMPAlow phenotypes in a morphology-independent manner. In five independent data sets from three continents containing more than 1500 adult diffuse gliomas, RMPAhigh gliomas were associated with poor prognosis while RMPAlow gliomas were not. The RMPAhigh and RMPAlow glioma subtypes showed distinct levels of the activities of RAS-RAF-MEK-MAPK cascade and PI3K-AKT pathway and harbored unique sets of genomic alterations in the RTK signaling-related genes. The RMPAhigh gliomas contained large numbers of immature vessel cells and tumor associated macrophages and both cell types expressed high levels of pro-angiogenic RTKs including MET, VEGFR1, KDR, EPHB4 and NRP1. Conclusion: Inter-glioma variability in RTK signaling activities can be defined using the RMPA clustering scheme. The combined signatures of NF1-M, SPRY-M and PTEN-M reflect RTK signaling activity both in the glioma cells and in the glioma microenvironment. Our data show that RTK signaling in the glioma microenvironment may play a pivotal role in glioma progression.
2015-10-30 | GSE74462 | GEO
Project description:Nodal points and complexity of Notch-Ras signal integration
| PRJNA106803 | ENA