E-GEOD-46109
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA196711PRJNA197280PRJNA196710
PROVIDER: E-GEOD-46109 | ExpressionAtlas | 2015-07-13
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-46109-analysis-methods.tsv | Tabular | |||
| E-GEOD-46109-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-46109-configuration.xml | Xml | |||
| E-GEOD-46109-percentile-ranks.tsv | Tabular | |||
| E-GEOD-46109.condensed-sdrf.tsv | Tabular |
Items per page: 5 1 - 5 of 206 |
Similar Datasets
Project description:Dynamic Gene Expression Response to TGF-β Stimulation in Multipotent Progenitors and Common Dendritic Cell Progenitors
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Project description:Multipotent progenitors (MPP) and common dendritic cell progenitors (CDP) were obtained from mouse bone marrow, followed by in vitro culture with a specific cytokine cocktail and FACS sorting (Felker et al., 2010; Sere et al., 2012). Cells were treated with 10 ng/ml recombinant human TGF-b1 (R&D Systems, Minneapolis, USA) for 2, 4, 8, 12 and 24 h as described (Felker et al., 2010) or left untreated. Untreated multipotent progenitor (MPP) - MPP_0h_1 - MPP_0h_2 - MPP_0h_3 TGF-beta1 treated (2 hours) MPP - MPP_2h_1 - MPP_2h_2 - MPP_2h_3 TGF-beta1 treated (4 hours) MPP - MPP_4h_1 - MPP_4h_2 - MPP_4h_3 TGF-beta1 treated (8 hours) MPP - MPP_8h_1 - MPP_8h_2 - MPP_8h_3 TGF-beta1 treated (12 hours) MPP - MPP_12h_1 - MPP_12h_2 - MPP_12h_3 TGF-beta1 treated (24 hours) MPP - MPP_24h_1 - MPP_24h_2 - MPP_24h_3 Untreated common dendritic cell progenitor (CDP) - CDP_0h_1 - CDP_0h_2 - CDP_0h_3 TGF-beta1 treated (2 hours) CDP - CDP_2h_1 - CDP_2h_2 - CDP_2h_3 TGF-beta1 treated (4 hours) CDP - CDP_4h_1 - CDP_4h_2 - CDP_4h_3 TGF-beta1 treated (8 hours) CDP - CDP_8h_1 - CDP_8h_2 - CDP_8h_3 TGF-beta1 treated (12 hours) CDP - CDP_12h_1 - CDP_12h_2 - CDP_12h_3 TGF-beta1 treated (24 hours) CDP - CDP_24h_1 - CDP_24h_2 - CDP_24h_3
2014-04-15 | E-GEOD-46109 | biostudies-arrayexpress
Project description:Dendritic cells (DCs) in lymphoid tissue comprise conventional DCs (cDCs) and plasmacytoid DCs (pDCs) that develop from common DC progenitors (CDPs). CDPs are Flt3+c-kitintM-CSFR+ and reside in bone marrow. Here we describe a two-step culture system that recapitulates DC development from c-kithiFlt3-/lo multipotent progenitors (MPPs) into CDPs and further into cDC and pDC subsets. MPPs and CDPs are amplified in vitro with Flt3 ligand, stem cell factor, hyper-IL-6 and insulin- like growth factor-1. The four-factor cocktail readily induces self-renewal of MPPs and their progression into CDPs and has no self-renewal activity on CDPs. The amplified CDPs respond to all known DC poietins and generate all lymphoid tissue DCs in vivo and in vitro. Additionally, in vitro CDPs recapitulate the cell surface marker and gene expression profile of in vivo CDPs and possess a DC-primed transcription profile. Transforming growth factor-β1 (TGF-β1) impacts on CDPs and directs their differentiation towards cDCs. Genome-wide gene expression profiling of TGF-β1-induced genes identified transcription factors, such as interferon regulatory factor-4 (IRF-4) and RelB, that are implicated as instructive factors for cDC subset specification. TGF-β1 also induced the transcription factor inhibitor of differentiation/DNA binding 2 (Id2) that suppresses pDC development. Thus, TGF-β1 directs CDP differentiation into cDC by inducing both cDC instructive factors and pDC inhibitory factors. 20 samples in total. Multipotent progenitor - MPP_1 - MPP_2 Common dendritic cell progenitor - CDP_1 - CDP_2 Plasmacytoid dendritic cell - pDC_1 - pDC_2 Conventional dendritic cell - cDC_1 - cDC_2 In vivo common dendritic cell progenitor - In vivo CDP_1 - In vivo CDP_2 Untreated common dendritic cell progenitor (CDP) - CDP_0h_1 - CDP_0h_2 TGF-beta1 treated (4 hours) CDP - CDP_4h_1 - CDP_4h_2 TGF-beta1 treated (8 hours) CDP - CDP_8h_1 - CDP_8h_2 TGF-beta1 treated (12 hours) CDP - CDP_12h_1 - CDP_12h_2 TGF-beta1 treated (24 hours) CDP - CDP_24h_1 - CDP_24h_2
2010-10-04 | E-GEOD-22432 | biostudies-arrayexpress
Project description:Dendritic cells (DC) develop from hematopoietic stem cells, which is guided by instructive signals through cytokines. DC development progresses from multipotent progenitors (MPP) via common DC progenitors (CDP) into DC. Flt3 ligand (Flt3L) signaling via the Flt3/Stat3 pathway is of pivotal importance for DC development under steady state conditions. Additional factors produced during steady state or inflammation, such as TGF-beta1 or GM-CSF, also influence the differentiation potential of MPP and CDP. Here, we studied how gp130, GM-CSF and TGF-beta1 signaling influence DC lineage commitment from MPP to CDP and further into DC. We observed that activation of gp130 signaling promotes expansion of MPP. Additionally, gp130 signaling inhibited Flt3L-driven DC differentiation, but had little effect on GM-CSF-driven DC development. The inflammatory cytokine GM-CSF induces differentiation of MPP into inflammatory DC and blocks steady state DC development. Global transcriptome analysis revealed a GM-CSF-driven gene expression repertoire that primes MPP for differentiation into inflammatory DC. Finally, TGF-beta1 induces expression of DC-lineage affiliated genes in MPP, including Flt3, Irf-4 and Irf-8. Under inflammatory conditions, however, the effect of TGF- beta1 is altered: Flt3 is not upregulated, indicating that an inflammatory environment inhibits steady state DC development. Altogether, our data indicate that distinct cytokine signals produced during steady state or inflammation have a different outcome on DC lineage commitment and differentiation. 6 samples in total. Multipotent progenitor - GM-MPP_1 - GM-MPP_2 Dendritic cell - GM-DC_1 - GM-DC_2 Dendritic cell plus TNFa - GM-TNFa-DC_1 - GM-TNFa-DC_2
2011-11-13 | E-GEOD-29241 | biostudies-arrayexpress
Project description:Multipotent progenitors (MPP) and common dendritic cell progenitors (CDP) were obtained from mouse bone marrow, followed by in vitro culture with a specific cytokine cocktail and FACS sorting (Felker et al., 2010; Seré et al., 2012). Cells were treated with 10 ng/ml recombinant human TGF-β1 (R&D Systems, Minneapolis, USA) for 2, 4, 8, 12 and 24 h as described (Felker et al., 2010) or left untreated.
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2017-06-01 | GSE99467 | GEO
Project description:The development of dendritic cells (DCs) is regulated by complex transcriptional networks. DCs originate from the multipotent progenitors (MPPs) in the bone marrow, which could further give rise to common lymphoid progenitors (CLPs) and common dendritic cell progenitors (CDPs). Whereas CDPs, which could be further divided into CD115+ and CD115- populations, give rise to both conventional (cDC) and plasmacytoid DCs (pDCs), CLP is an addtional source of pDCs. Transcriptome profiling of wild type and Trim33-/- MPPs, CD115- CDPs, and CLPs revealed a critical role of TRIM33 in the development of DCs.
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Project description:TGF-β1 Accelerates Dendritic Cell Differentiation from Common Dendritic Cell Progenitors (CDPs) and Directs Subset Specification Towards Conventional Dendritic Cells
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Project description:This model is from the article:
Quantitative analysis of transient and sustained transforming growth factor-β signaling dynamics.
Zhike Zi, Zipei Feng, Douglas A Chapnick, Markus Dahl, Difan Deng, Edda Klipp, Aristidis Moustakas & Xuedong Liu Molecular Systems Biology
2011 May 24;7:492. 21613981
,
Abstract:
Mammalian cells can decode the concentration of extracellular transforming growth factor-β (TGF-β) and transduce this cue into appropriate cell fate decisions. How variable TGF-β ligand doses quantitatively control intracellular signaling dynamics and how continuous ligand doses are translated into discontinuous cellular fate decisions remain poorly understood. Using a combined experimental and mathematical modeling approach, we discovered that cells respond differently to continuous and pulsating TGF-β stimulation. The TGF-β pathway elicits a transient signaling response to a single pulse of TGF-β stimulation, whereas it is capable of integrating repeated pulses of ligand stimulation at short time interval, resulting in sustained phospho-Smad2 and transcriptional responses. Additionally, the TGF-β pathway displays different sensitivities to ligand doses at different time scales. While ligand-induced short-term Smad2 phosphorylation is graded, long-term Smad2 phosphorylation is switch-like to a small change in TGF-β levels. Correspondingly, the short-term Smad7 gene expression is graded, while long-term PAI-1 gene expression is switch-like, as is the long-term growth inhibitory response. Our results suggest that long-term switch-like signaling responses in the TGF-β pathway might be critical for cell fate determination.
Note:
Developer of the model: Zhike Zi
Reference: Zi Z. et al., Quantitative Analysis of Transient and Sustained Transforming Growth Factor-beta Signaling Dynamics, Molecular Systems Biology, 2011
1. The global parameter that set the type of stimulation
(a) for sustained TGF-beta stimulation: set stimulation_type = 1.
(b) for single pulse of TGF-beta stimulation: set stimulation_type = 2.
parameter "single_pulse_duration" is for the duration of stimulation, for example,
single_pulse_duration = 0.5, for 0.5 min (30 seconds) of TGF-beta stimulation.
*Note: make sure that the time course cover the time point when the event is triggered.
(c) for single pulse of TGF-beta stimulation in COPASI
change the trigger of event "single_pulse_TGF_beta_washout"
from
"and(eq(stimulation_type, 2), eq(time, single_pulse_duration))" (for SBML-SAT)
to
"and(eq(stimulation_type, 2), gt(time, single_pulse_duration))" (for COPASI)
2. Notes for TGF-beta dose in terms of molecules per cell
(a) The following equation applies for conversion of TGF-beta dose in molecules per cell
TGF_beta_dose_mol_per_cell = initial TGF_beta_ex*1e-9*Vmed*6e23
(b) for standard experimental setup 1e6 cells in 2 mL medium
0.001 nM initial TGF_beta_ex is approximately equal to the dose of 1200 TGF-beta molecules/cell
0.050 nM initial TGF_beta_ex is approximately equal to the dose of 60000 TGF-beta molecules/cell
(c) For 1e6 cells in 10 mL medium, please change the initial compartment size of Vmed and the corresponding assignment rule for Vmed.
initial Vmed = 1e-8 (1e6 cells in 10 mL medium)
Vmed = 0.010/(1e6*exp(log(1.45)*time/1440)) (1e6 cells in 10 mL medium)
3. Please note that this model contains events and the medium compartment size is varied.
4. For the model simulation in SBML-SAT, please remove initialAssignments and save it as SBML Level 2 Verion 1 file.
2024-09-02 | BIOMD0000000342 | BioModels