Filters
Technology
Platform
Mus musculus
12 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
External stimulations of cells by hormones, growth factors or cytokines activate signal transduction pathways that subsequently induce a rearrangement of cellular gene expression. The representation and analysis of changes in the gene response is complicated, and essentially consists of multiple layered temporal responses. In such situations, matrix factorization techniques may provide efficient tools for the detailed temporal analysis. Related methods applied in bioinformatics intentionally do not take prior knowledge into account. In signal processing, factorization techniques incorporating data properties like second-order spatial and temporal structures have shown a robust performance. However, large-scale biological data rarely imply a natural order that allows the definition of an autocorrelation function. We therefore develop the concept of graph-autocorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways as a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the samples to define an autocorrelation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph decorrelation (GraDe) algorithm. To analyze the alterations in the gene response in IL-6 stimulated primary mouse hepatocytes by GraDe, a time-course microarray experiment was performed. Extracted gene expression profiles show that IL-6 activates genes involved in cell cycle progression and cell division in a time-resolved manner. On the contrary, genes linked to metabolic and apoptotic processes are down-regulated indicating that IL-6 mediated priming rendered hepatocytes more responsive towards cell proliferation and reduces expenses for the energy household.
Publication Title
Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation.
Sample Metadata Fields
Specimen part, Treatment, Time
View Samples- Homo sapiens
- 30 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Type I interferons (IFN) are important components of the innate antiviral response. A key signalling pathway activated by IFNa is the Janus kinase signal transducer and activator of transcription (JAKSTAT) pathway. Major components of the pathway have been identified. However, critical kinetic properties that facilitate accelerated initiation of intracellular antiviral signalling and thereby promote virus elimination remain to be determined. By combining mathematical modelling with experimental analysis, we show that control of dynamic behaviour is not distributed among several pathway components but can be primarily attributed to interferon regulatory factor 9 (IRF9), constituting a positive feedback loop. Model simulations revealed that increasing the initial IRF9 concentration reduced the time to peak, increased the amplitude and enhanced termina- tion of pathway activation. These model predictions were experimentally verified by IRF9 over-expression studies. Furthermore, acceleration of signal processing was linked to more rapid and enhanced expression of IFNa target genes. Thus, the amount of cellular IRF9 is a crucial determinant for amplification of early dynamics of IFNa-mediated signal transduction.
Publication Title
Combining theoretical analysis and experimental data generation reveals IRF9 as a crucial factor for accelerating interferon α-induced early antiviral signalling.
Sample Metadata Fields
Specimen part, Disease, Cell line, Time
View Samples- Homo sapiens
- 13 Downloadable Samples
- Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
TTCA: an R package for the identification of differentially expressed genes in time course microarray data.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 7 Downloadable Samples
- Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for the detection of significant expression dynamics often fail when the expression dynamics show a large heterogeneity, and often cannot cope with irregular and sparse measurements.
Publication Title
TTCA: an R package for the identification of differentially expressed genes in time course microarray data.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for the detection of significant expression dynamics often fail when the expression dynamics show a large heterogeneity, and often cannot cope with irregular and sparse measurements.
Publication Title
TTCA: an R package for the identification of differentially expressed genes in time course microarray data.
Sample Metadata Fields
Cell line, Treatment
View Samples- Mus musculus
- 16 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Activation of the AKT and ERK signaling pathway is a major contributor to cell proliferation. However, the integrated regulation of this multistep process, involving signal processing, cell growth and cell-cycle progression, is poorly understood. Here we study three cell types of hematopoietic origin, in which AKT and ERK signaling is triggered by erythropoietin (Epo). We find that the different cell types exhibit distinct proliferative responses, despite sharing the molecular network for pro-proliferative signaling. Iterating quantitative experiments and mathematical modeling, we show that the cell-type-specific regulation of proliferation emerges from two sources: (1) the protein abundance patterns of signaling components that cause differential flow of signals along the AKT and ERK pathways, and (2) the differential impact of the downstream regulators for protein synthesis and for cell-cycle progression on proliferation. Our integrated mathematical model of Epo-driven proliferation explains cell-type-specific effects of targeted AKT and ERK inhibitors and correctly predicts whether their combined application results in synergy.
Publication Title
Protein abundance of AKT and ERK pathway components governs cell type-specific regulation of proliferation.
Sample Metadata Fields
Sex, Cell line
View Samples
GSE23591- Homo sapiens
- 39 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Primary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin lymphoma (cHL) share a frequent constitutive activation of Janus-activated kinase (JAK) / signal transducer and activator of transcription (STAT) signaling pathway. Due to complex non-linear relations within the pathway, key dynamic properties remained to be identified to predict possible strategies for intervention. To untangle these features, we used dynamic pathway modeling that employs model development and calibration based on extensive quantitative data generation. Quantitative data were collected on JAK/STAT pathway signaling components in two lymphoma-derived cell lines, MedB-1 and L1236, representative of PMBL and cHL, respectively. We showed that the amounts of STAT5 and STAT6 are higher whereas the amount of SHP1 is lower in the two lymphoma cell lines compared to B cells from healthy donors. Distinctively, L1236 cells harbor more JAK2 and less SHP1 molecules per cell than MedB-1 or control cells. In our experimental setting interleukin-13 (IL13) stimulation levels remained constant over time. In MedB-1 cells surface IL13 receptor alpha 2 had a strong IL13-sequestering/decoy function. In both lymphoma cell lines we observed IL13-induced activation of interleukin-4 receptor alpha, JAK2 and STAT5, but not of STAT6, which was highly phosphorylated even without stimulus. Furthermore, the known STAT-inducible negative regulators CISH and SOCS3 were up-regulated within 2 hours in MedB-1 but not in L1236 cells. Global transcription profiling revealed 11 early and 16 sustained common genes up-regulated by IL13 in both lymphoma cell lines. Based on this detailed information we established two individual mathematical models, MedB-1 and L1236 model, which were able to describe the respective experimental data. Sensitivity analysis of the model identified six possible therapeutic targets able to reduce gene expression levels in L1236 cells and three in MedB-1 cells. By inhibition of STAT5 phosphorylation we successfully validated one of the predicted targets demonstrating the potential of the approach in guiding target identification for highly deregulated signaling networks in cancer cells. We established mathematical models of the JAK/STAT pathway in two lymphoma cell types (PMBL and cHL), able to reproduce experimental data and to predict possible therapeutic targets.
Publication Title
Dynamic mathematical modeling of IL13-induced signaling in Hodgkin and primary mediastinal B-cell lymphoma allows prediction of therapeutic targets.
Sample Metadata Fields
Cell line, Time
View Samples- Mus musculus
- 20 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
The goal of the study is a high-throughput evaluation of the effect of TGFb treatment on gene expression.
Publication Title
Resolving the Combinatorial Complexity of Smad Protein Complex Formation and Its Link to Gene Expression.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 4 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
We analysed the genexpression of dental follicle cells (DFCs) after 3 days osteogenic differentiation with BMP2 after transfection with a DLX3 plasmid (pDLX3) and after transfection with an empty plasmid (pEV)
Publication Title
A protein kinase A (PKA)/β-catenin pathway sustains the BMP2/DLX3-induced osteogenic differentiation in dental follicle cells (DFCs).
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 26 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The goal of the experiment: To characterize the dynamic gene expression profile of engineered human skin in vitro and after grafting, and compare with expression profile of uninjured human skin.
Publication Title
Engineered human skin substitutes undergo large-scale genomic reprogramming and normal skin-like maturation after transplantation to athymic mice.
Sample Metadata Fields
Specimen part
View Samples