Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1210001 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31986049_1.fastq.gz | Fastqsanger.gz | |||
| SRR31986049_2.fastq.gz | Fastqsanger.gz | |||
| SRR31986050_1.fastq.gz | Fastqsanger.gz | |||
| SRR31986050_2.fastq.gz | Fastqsanger.gz | |||
| SRR31986051_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 12 |
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:During mononuclear phagocyte system evolution, monocytes differentiate into pro-tumorigenic TAMs. We used single cell RNA sequencing (scRNA-seq) to analyze the characteristics of mononuclear phagocyte in colorectal cancer
2023-07-01 | GSE217774 | GEO
Project description:We performed single-cell transcriptome analysis with the 10X Genomic Chromium platform of CD4+ T cells infiltrating human primary and metastatic colorectal cancer (CRC) and non-small-cell lung cancer (NSCLC). Datasets derive from fresh samples collected and immediately processed by cell sorting and single-cell isolation 10X protocol. A total number of 10000 cells per sample was analyzed by scRNA-seq.
2021-04-28 | E-MTAB-7006 | biostudies-arrayexpress
Project description:Single cell genome, DNA methylome, and transcriptome sequencing has been achieved separately. However, to analyze the regulation of RNA expression by genetic and epigenetic factors within an individual cell, it is necessary to analyze these omics simultaneously from the same single cell. Here we developed a single cell triple omics sequencing technique- scTrio-seq, to analyze the genome, DNA methylome, and transcriptome concurrently of a mammalian cell. 6 single human HepG2 cell line cells were sequenced using the newly developed scTrio-seq, other 2 HepG2 cells were sequenced using scRNA-seq and other 2 HepG2 cells were sequenced using scRRBS as technique control. 6 single mouse embryonic stem cells (mESCs) were sequenced using the newly developted scTrio-seq. Meanwhile, two scRNA-seq and two scRRBS were also completed using two mESCs separately. 26 single cells from hepatocellular carcinoma were sequenced using scTrio-seq to analyze the regulation relations between three omics of cancer cells.
2016-03-01 | E-GEOD-65364 | biostudies-arrayexpress
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:Intra-tumor heterogeneity of tumor-initiating cell (TIC) activity drives colorectal cancer (CRC) progression and therapy resistance. Here, we used single-cell mRNA-sequencing (scRNA-seq) of patient-derived CRC models to decipher distinct cell subpopulations based on their transcriptional profiles. Cell type-specific expression modules of stem-like, transit amplifying-like, and differentiated CRC cells resemble differentiation states of normal intestinal epithelial cells. Strikingly, identified subpopulations differ in proliferative activity and metabolic state. In summary, we here show at single-cell resolution that transcriptional heterogeneity identifies functional states during TIC differentiation. Targeting transcriptional states associated to cancer cell differentiation might unravel vulnerabilities in human CRC.
2021-05-07 | PXD018230 | Pride
Project description:To gain a comprehensive understanding of the alterations in the tumor microenvironment following FOXM1 depletion in breast cancer cells, we employed single-cell RNA sequencing (scRNA-seq) on tumor samples from control and FOXM1 knockout groups.
2025-03-04 | GSE266617 | GEO
Project description:Understanding cellular processes underlying colorectal cancer (CRC) development is needed to devise intervention strategies. Here, we performed single-cell RNA sequencing (scRNA-seq) of human treatment-naive colorectal cancer.
2026-06-15 | GSE330797 | GEO
Project description:we employed single-cell RNA sequencing (scRNA-seq) to analyze the cellular activities and transcriptional changes of corneal limbal epithelial cells at different stages after wound healing in cynomolgus monkeys
2024-09-20 | GSE276184 | GEO
Project description:<p>Metabolic and inflammatory diseases often coexist, and become important challenges facing global health, and obesity has shown to be a susceptibility factor for osteoarthritis (OA). As a metabolic regulatory drug for lowering blood sugar and body weight, semaglutide has shown additional therapeutic effects in OA, but the underlying mechanism requires further investigation. Here we employed cross-tissue single-cell RNA sequencing (scRNA-seq) analysis, and found that semaglutide significantly improved metabolic disorders in muscle tissue under high-fat diet (HFD) and OA conditions in mice. The results of scRNA-seq and mitochondrial proteomics indicated that semaglutide targeted muscle mitochondria to regulate glutamate metabolism during OA. Intriguingly, intramuscular injection of semaglutide pre-stimulated mitochondria from muscle stem cell could significantly alleviate OA inflammation and pain symptoms. These findings reveal the mitochondrial regulatory mechanism in the muscle-OA axis, and provide a new perspective for the application of semaglutide in OA treatment.</p>
2026-05-06 | MTBLS14059 | MetaboLights