FMT datasets
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB47909 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR9697727_1.fastq.gz | Fastqsanger.gz | |||
| ERR9697727_2.fastq.gz | Fastqsanger.gz | |||
| ERR9707210_1.fastq.gz | Fastqsanger.gz | |||
| ERR9707210_2.fastq.gz | Fastqsanger.gz | |||
| ERR9709070_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 230 |
Similar Datasets
Project description:Faecal microbiota transplant as treatment for recurrent Clostridioides difficile infection
| PRJEB30298 | ENA
Project description:The intestines house a diverse microbiota that must compete for nutrients to survive, but the specific limiting nutrients that control pathogen colonization are not clearly defined. Clostridioides difficile colonization typically requires prior disruption of the microbiota, suggesting that outcompeting commensals for resources is key in establishing C. difficile infection (CDI). The immune protein calprotectin (CP) is released into the gut lumen during CDI to chelate zinc (Zn) and other essential nutrient metals. Yet, the impact of Zn limitation on C. difficile colonization is unknown. To define C. difficile responses to Zn limitation, we performed RNA sequencing on C. difficile exposed to CP. In media with CP, C. difficile upregulated genes involved in metal homeostasis and amino acid metabolism.
2019-10-24 | GSE135912 | GEO
Project description:Background: Clostridioides difficile (C. difficile) is a global threat and has significant implications for individuals and health care systems. Little is known about host molecular mechanisms and transcriptional changes in peripheral immune cells. This is the first gene expression study in whole blood of patients with C. difficile infection. Methods: We took blood and stool samples from patients with toxigenic C. difficile infection (CDI), non-toxigenic C. difficile infection (GDH), inflammatory bowel disease (IBD), diarrhoea from other causes (DC) and healthy controls (HC). We performed transcriptome-wide RNA profiling on peripheral blood to identify diarrhoea common and CDI unique gene sets. Results: Diarrhoea groups upregulated innate immune responses with neutrophils at the epicentre. The common signature associated with diarrhoea was non-specific and shared by various other inflammatory conditions. CDI had a unique 45-gene set reflecting downregulation of humoral and T cell memory functions. Dysregulation of immunometabolic genes was also abundant and linked to immune cell fate during differentiation. Conclusions: Whole transcriptome analysis of white cells in blood from patients with toxigenic C. difficile infection showed that there is an impairment of adaptive immunity and immunometabolism.
2024-11-24 | GSE276395 | GEO
Project description:WGS data from FMT trial for the treatment of recurrent Clostridium difficile infection
| PRJEB23524 | ENA
Project description:16S data from FMT trial for the treatment of recurrent Clostridium difficile infection
| PRJEB23489 | ENA
Project description:Treatment of recurrent Clostridioides difficile infection with Fecal Microbiota Transplantation
| PRJEB39023 | ENA
Project description:Successful Fecal Microbiota Transplants in Post-antibiotic Treated Recurrent Clostridioides difficile Patients Induce Acylcarnitine and Sphingolipid Lipidomic Shifts.
| MSV000099241 | GNPS
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