Similar Datasets
Project description:The effect of CD151 expression onto the kinome of Jurkat T cells was assessed using kinome analysis. CD151 was expressed in Jurkat T cells by retroviral transduction based on a pMSCV vector. Entrez Gene: 977 UniProtKB: P48509 Jurkat T cells were transduced with the MSCV-CD151 vector and successfully transduced cells were selected using puromycin. For the kinome array experiments 3 independent samples of Jurkat cells and three independent samples of J-CD151 cells were collected. To minimize unspecific background signals, lysates from Jurkat and J-CD151 T cells harvested at different growth stages, which were then pooled to provide one sample prior to loading on the Kinexus antibody microarrays.
2017-09-30 | E-MTAB-5978 | biostudies-arrayexpress
Project description:Current differentiation protocols for human pluripotent stem cells produce a heterogeneous population of cardiomyocytes (CMs). Here, we identified CD151 as a marker of ventricular CMs (VCMs) and atrial CMs (ACMs) from 212 different cell surface markers. In the VCM induction, CD151high CMs were a homogeneous population of mature VCMs, including binuclear VCMs, and showed enriched cell cycle-related genes based on RNA-seq analysis. As for the ACM induction, CD151low CMs expressed high levels of atrial-related genes and exhibited atrial-type electrophysiological properties. According to RNA-seq analysis, CD151high CMs from the ACM induction had molecular signatures for cell-cell interactions and NOTCH signaling. When treated with a NOTCH signal inhibitor, the same cells showed mature electrophysiological properties consistent of ACMs with an increasing expression of atrial-related genes. Altogether, we found that CD151 is an indicator of subtype specification with distinct mechanisms between VCM and ACM differentiation and that NOTCH signaling inhibition enhances atrial specification.
2024-01-29 | GSE179769 | GEO
Project description:Primary human T cells from healthy donors were sorted using a FACSAria II to obtain CD3+CD4+CD151+ and CD3+CD4+CD151- populations. To perform kinome analysis using Kinex™ microarrays, 50 µg of lysate protein from each sample were labeled with a proprietary fluorescent dye according to the manufacturers instructions (Kinexus, Canada). The utilized KAM-850 chips were spotted in duplicates with over 850 antibodies: 510 pan-specific antibodies used in the chip allows for the detection of 189 protein kinases, 31 protein phosphatases and 142 regulatory subunits of these enzymes and other cell signaling proteins. 340 phospho-specific antibodies tracked the unique phosphorylation of 128 sites in protein kinases, 4 sites in protein phosphatases and 155 sites in other cell signaling proteins. The background-corrected raw intensity data were logarithmically transformed with base 2. Z scores were calculated by subtracting the overall average intensity of all spots within a sample from the raw intensity for each spot, and Z score ratios were calculated by dividing Z scores by the standard deviations (SD) of all of the measured intensities within each sample. To minimize unspecific background signals, lysates from cells from 5 different donors were sorted and the corresponding populations were pooled to provide one sample prior to loading on the Kinexus antibody microarrays. 16JN20-KAM880 Kit-K012003211-19123.txt contains the original data for the CD4+CD151- T cell population at baseline. 16JN20-KAM880 Kit-K012003211-19124.txt contains the original data for the CD4+CD151- T cell population following stimulation with 30 U/ml IL-2 for 24 hours. 16JN21-KAM880 Kit-K012003229-19125.txt contains the original data for the CD4+CD151+ T cell population at baseline. 16JN21-KAM880 Kit-K012003229-19126.txt ontains the original data for the CD4+CD151+ T cell population following stimulation with 30 U/ml IL-2 for 24 hours.
2017-09-30 | E-MTAB-5977 | biostudies-arrayexpress
Project description:The first GSSM of V. vinifera was reconstructed (MODEL2408120001). Tissue-specific models for stem, leaf, and berry of the Cabernet Sauvignon cultivar were generated from the original model, through the integration of RNA-Seq data. These models have been merged into diel multi-tissue models to study the interactions between tissues at light and dark phases.
2024-09-02 | MODEL2408160001 | BioModels
Project description:Analysis of glomerular gene expression levels was performed in 3- to 4-week-old FVB/N Cd151-/- mice and wild type controls. Identification of the glomerular gene expression profile at this early stage of disease progression in FVB/N Cd151-/- mice provides insight into the molecular mechanisms associated with glomerular disease development, including thickening and splitting of the glomerular basement membrane
2017-11-30 | GSE104624 | GEO
Project description:The high degree of genetic aberrations characteristic of high-grade serous ovarian cancer (HGSC) makes identification of the molecular features that drive tumor progression difficult. Here, we perform genome-wide RNAi screens and comprehensive expression analysis of cell surface markers in a panel of HGSC cell lines to identify genes that are critical to their survival. We report that the tetraspanin CD151 contributes to survival of a subset of HGSC cell lines associated with a ZEB transcriptional program and supports the growth of HGSC tumors. Moreover, we show that high CD151 expression is prognostic of poor clinical outcome. This study reveals cell-surface vulnerabilities associated with HGSC, provides a framework for identifying therapeutic targets, and reports a role for CD151 in HGSC.
2017-02-03 | GSE94304 | GEO
Project description:The miRNA profile between different pancreatic adenocarcinoma cells (A818.4, Capan-1) and different colorectal carcinoma cells (SW948, HT-29). The impact of a knockdown (kd) of function-relevant cancer stem cell markers (CD44v6, Tspan8, CD151, claudin7) on the miRNA profile. The kd cell miRNA profiles were compared with the wt cell as well as between the different kd miRNA profiles.
2018-08-25 | GSE119032 | GEO
Project description:Kilian2024 - Immune cell dynamics in Cue-Induced Extended Human Colitis Model
Single-cell technologies such as scRNA-seq and flow cytometry provide critical insights into immune cell behavior in inflammatory bowel disease (IBD). However, integrating these datasets into computational models for dynamic analysis remains challenging. Here, Kilian et al., (2024) developed a deterministic ODE-based model that incorporates these technologies to study immune cell population changes in murine colitis. The model parameters were optimized to fit experimental data, ensuring an accurate representation of immune cell behavior over time. It was then validated by comparing simulations with experimental data using Pearson’s correlation and further tested on independent datasets to confirm its robustness. Additionally, the model was applied to clinical bulk RNA-seq data from human IBD patients, providing valuable insights into immune system dynamics and potential therapeutic strategies.
Figure 4c, obtained from the simulation of human colitis model is highlighted here.
This model is described in the article:
Kilian, C., Ulrich, H., Zouboulis, V.A. et al. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. npj Syst Biol Appl 10, 69 (2024). https://doi.org/10.1038/s41540-024-00395-9
Abstract:
Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.
2025-03-07 | MODEL2502180001 | BioModels
Project description:Comparison of gene expressions between the lungs of CD9KO and CD151KO mice A microarray study identified an enrichment of genes involved in connective tissue disorders in the lungs of CD151 KO mice, but not in CD9 KO mice.
2020-10-20 | GSE159236 | GEO
Project description:<p>Gene expression is a biological process regulated at different molecular levels, including chromatin accessibility, transcription, and RNA maturation and transport. In addition, these regulatory mechanisms have strong links with cellular metabolism. Here we present a multi-omics dataset that captures different aspects of this multi-layered process in yeast. We obtained RNA-seq, metabolomics, and H4K12Ac ChIP-seq data for wild-type and mip6delta strains during a heat-shock time course. Mip6 is an RNA-binding protein that contributes to RNA export during environmental stress and is informative of the contribution of post-transcriptional regulation to control cellular adaptations to environmental changes. The experiment was performed in quadruplicate, and the different omics measurements were obtained from the same biological samples, which facilitates the integration and analysis of data using covariance-based methods. We validate our dataset by showing that ChIP-seq, RNA-seq and metabolomics signals recapitulate existing knowledge about the response of ribosomal genes and the contribution of trehalose metabolism to heat stress.</p>
2020-02-14 | MTBLS1320 | MetaboLights