Ontology highlight
ABSTRACT:
PROVIDER: PRJNA765009 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15997817.fastq.gz | Fastqsanger.gz | |||
| SRR18856553.fastq.gz | Fastqsanger.gz | |||
| SRR18856554.fastq.gz | Fastqsanger.gz | |||
| SRR18856555.fastq.gz | Fastqsanger.gz | |||
| SRR18856556.fastq.gz | Fastqsanger.gz |
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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: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.
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Project description:The experiment aims at characterizing the immune responses elicited by the BNT162b2 vaccine against SARS-CoV-2, initially administered in a two dose regimen (second dose after three weeks followinf the first dose) In particular the transcriptional landscape of circulating T and B lymphocytes has been profiled longitudinnaly by scRNA-seq coupleD with CITE-seq of 19 cell surface markers to better classify T cells subpopulations, LIBRA-seq to assess the Spike-specificity of BCRs and and V(D)J seq to also track T and B cell clones dynamics. Eeach sample was profiled before vaccination (T0), 21 days after the first dose (T1), 2 months after the first dose (1 month after the second dose) (T2). The immune responses were characterized using PBMC from 3 SARS-CoV-2 experienced donors (experiencing SARS-Cov-2 at least 4 months before the first vaccinatin) and 2 SARS-CoV-2 unexperienced donors.
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Project description:Tumor-infiltrating regulatory T cells contribute to an immunosuppressive tumor microenvironment. We applied single-cell RNA sequencing (scRNA-seq) , TCR sequencing combined with cellular indexing of transcriptomes and epitopes (CITE-seq) on CD4 T cells to decipher the heterogeneity of intratumoral Tregs in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL), compared with non-malignant tonsillar tissue.
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Project description:The malaria parasite Plasmodium replicates and differentiates in red blood cells of its host. The erythropoietic niches (spleen and bone marrow) are important but poorly understood reservoirs of asexual replication and sexual development. We aimed to understand how the parasite adapts to its host organ and a host cell level. For this, we performed single-cell RNA-seq (scRNA-seq) analysis on host and parasite cells derived from spleen, blood and bone marrow. Organs were harvested from two infected and one uninfected mice and parasite cells were enriched to about 50% by flow sorting (infected samples only). To identify host cells by surface expression (CITE-seq), cells were stained with barcoded antibodies targeting CD44 and CD71. Droplet-based scRNA-seq of these samples was performed using 10X genomics technology and cDNA was sequenced on Illumina.
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2023-08-25 | E-MTAB-10607 | biostudies-arrayexpress
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