90a46c29-4ef0-43b5-9aa4-5f4ae95e8535 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001010907 | EGA |
REPOSITORIES: EGA
Similar Datasets
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:Human data for chromatin accessibility (scATAC-Seq) in CD34+ B cell precursors.
| EGAD00001010910 | EGA
Project description:Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by repetitive alveolar injuries with excessive deposition of extracellular matrix (ECM) proteins. A crucial need in understanding IPF pathogenesis is identifying cell types associated with histopathological regions, particularly local fibrosis centers known as fibroblast foci. To address this, we integrated published spatial transcriptomics and single-cell RNA sequencing (scRNA-seq) transcriptomics and adopted the Query method and the Overlap method to determine cell type enrichments in histopathological regions. Distinct fibroblast cell types are highly associated with fibroblast foci, and transitional alveolar type 2 and aberrant KRT5-/KRT17+ epithelial cells are associated with morphologically normal alveoli in human IPF lungs. Furthermore, we employed laser capture microdissection directed mass spectrometry to profile proteins. By comparing with another published similar dataset, common differentially expressed proteins and enriched pathways related to ECM structure organization and collagen processing were identified in fibroblast foci. Importantly, cell type enrichment results from innovative spatial proteomics and scRNA-seq data integration accord with those from spatial transcriptomics and scRNA-seq data integration, supporting the capability and versatility of the entire approach. In summary, we integrated spatial multi-omics with scRNA-seq data to identify disease-associated cell types and potential targets for novel therapies in IPF intervention. The approach can be further applied to other disease areas characterized by spatial heterogeneity.
2025-01-27 | PXD058805 | Pride
Project description:A variety of newly developed next-generation sequencing technologies are making their way rapidly into the research and clinical applications, for which accuracy and cross-lab reproducibility are critical, and reference standards are much needed. However, there is still a lack of well-characterized reference materials which include epigenomic and proteomic data. Our previous multicenter studies under the SEQC-2 umbrella using a breast cancer cell line with paired B-cell line have produced large amount different genomic data including whole genome sequencing (Illumina, PacBio, Nanopore), HiC, and scRNA-seq with detailed analyses on somatic mutations, single-nucleotide variations (SNVs), and structure variations (SVs). Here we further performed ATAC-seq, Methyl-seq, RNA-seq, and proteomic analyses and provided a comprehensive catalog of epigenomic landscape, which overlapped with the transcriptomes and proteomes for the two cell lines. We identified >7,700 peptide isoforms, where the majority (95%) of the genes had a single peptide isoform and found that the protein expression levels of the transcripts overlapping CGIs were much higher than the protein expression levels of the non-CGI transcripts in both cell lines. We observed that open chromatin regions had low methylation while closed chromatin regions had high methylation, which were largely regulated by CG density, where CG-rich regions had more accessible chromatin, low methylation, and higher gene and protein expressions. The CG-poor regions had higher repressive epigenetic regulations (less open chromatin and higher DNA methylation), resulting in a cell line specific methylation and gene expression patterns. Our studies provide well-defined reference materials consisting of two cell lines with genomic, epigenomic, transcriptomic, scRNA-seq and proteomic characterizations which can serve as standards for validating and benchmarking not only on various omics assays, but also on bioinformatics methods. It will be a valuable resource for both research and clinical communities.
2025-10-01 | PXD052353 | Pride
Project description:Pancreatic cancer is a complex disease with a desmoplastic stroma, extreme hypoxia, and inherent resistance to therapy. Understanding the signaling and adaptive response of such an aggressive cancer is key to making advances in therapeutic efficacy and understanding disease progression. Redox factor-1 (Ref-1), a redox signaling protein, regulates the DNA binding activity of several transcription factors, including HIF-1. The conversion of HIF-1 from an oxidized to reduced state leads to enhancement of its DNA binding. In our previously published work, knockdown of Ref-1 under normoxia resulted in altered gene expression patterns on pathways including EIF2, protein kinase A, and mTOR. In this study, single cell RNA sequencing (scRNA-seq) and proteomics were used to explore the effects of Ref-1 on metabolic pathways under hypoxia.Results: We also integrated the scRNA data analysis with the proteomic analysis and found that the differentially expressed genes and pathways identified from the scRNA-seq data are highly consistent to the significant proteins observed in the proteomics data, especially for the upregulated cell cycle and transcription pathways and downregulated metabolic, apoptosis and signaling pathways under hypoxia. Conclusion: The scRNA-seq and proteomics data consistently demonstrated down-regulated central metabolism pathways in APE1/Ref-1 knockdown vs scrambled control under both normoxia and hypoxia conditions. Experimental Methods: scRNA-seq comparing pancreatic cancer cells expressing less than 20% of the Ref-1 protein was analyzed using left truncated mixture Gaussian model. Matched samples were also collected for bulk proteomic analysis of the four conditions. scRNA-seq data was validated using proteomics and qRT-PCR. Ref-1’s role in mitochondrial function was confirmed using mitochondrial function assays and qRT-PCR. Results: We also integrated the scRNA data analysis with the proteomic analysis and found that the differentially expressed genes and pathways identified from the scRNA-seq data are highly consistent to the significant proteins observed in the proteomics data, especially for the upregulated cell cycle and transcription pathways and downregulated metabolic, apoptosis and signaling pathways under hypoxia. Conclusion: The scRNA-seq and proteomics data consistently demonstrated down-regulated central metabolism pathways in APE1/Ref-1 knockdown vs scrambled control under both normoxia and hypoxia conditions.
2021-09-09 | PXD020515 | Pride
Project description:Diminishing potential to replace damaged tissues is a hallmark for aging of somatic stem cells, but the mechanisms leading to aging remain elusive. We performed a proteome-wide analysis of human hematopoietic stem and progenitor cells (CD34+) along with five other cell types that constitute the bone marrow niche, namely, lymphocytes and precursors; monocytes/macrophages and precursors; granulocytic precursors and erythroid precursors, as well as mesenchymal stem/stromal cells. In total, we analyzed 270 samples from 59 human subjects. The data represents a valuable resource for further in-depth mechanistic analyses, and for validation of knowledge gained from animal models.
2018-07-20 | PXD007048 | Pride
Project description:Plasmodium-specific CD4+ T cells from mice infected with Plasmodium chabaudi chabaudi AS parasites were recovered at Days 0, 7, and 28 to undergo processing and generate scRNA-seq dataset. At Day 28, mice were administered with either saline or artesunate (intermittent artesunate therapy - IAT). scRNA-seq dataset was analysed to investigate transcriptome dynamics of CD4+ T cells from effector to memory states.
2020-10-14 | E-MTAB-9317 | biostudies-arrayexpress
Project description:Our study focuses on understanding the early transcriptional changes taking place during the divergence of the adult muscle precursors that give rise to indirect flight muscles and direct flight muscles in Drosophila. We analyzed the heterogenous cell population of the adult muscle precursors by scRNA-seq and build an integrated single-cell reference atlas. We addressed the differences among muscle-type and different cell state during myoblast differentiation. Also, our dataset includes the transcriptional profile of the epithelial cells localized in the presumptive hinge and notum of third instar larval wing discs. In addition we studied the functional relevance of Amalgam in flight muscle development by depleting Ama expression specifically in the adult muscle precursors. We determined the transcriptional changes and perturbations in AMP cell identity upon Ama knockdown.
2020-08-31 | E-MTAB-9444 | biostudies-arrayexpress
Project description:Plasmodium-specific CD4+ T cells from mice infected with Plasmodium chabaudi chabaudi AS parasites were recovered at Days 0, 7, 10, 14, 17, 21, 28 to undergo processing and generate scRNA-seq dataset. From Day 10 onwards, mice were administered with either saline or artesunate (intermittent artesunate therapy - IAT). scRNA-seq dataset was analysed to investigate transcriptome dynamics of CD4+ T cells from effector to memory states.
2020-10-14 | E-MTAB-9403 | biostudies-arrayexpress