Escherichia coli
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1057330 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To investigate the effect of chr21amp on cell differentiation, we performed droplet-based, high-throughput single-cell RNA-seq on Lin-CD34+ cells and total mononuclear cells.
2025-03-27 | GSE292030 | GEO
Project description:Cell atlas projects and high-throughput perturbation screens require single-cell sequencing at a scale that is challenging with current technology. To enable cost-effective single-cell sequencing for millions of individual cells, we developed “single-cell combinatorial fluidic indexing” (scifi). The scifi-RNA-seq assay combines one-step combinatorial pre-indexing of entire transcriptomes inside permeabilized cells with subsequent single-cell RNA-seq using microfluidics. Pre-indexing allows us to load multiple cells per droplet and bioinformatically demultiplex their individual expression profiles. Thereby, scifi-RNA-seq massively increases the throughput of droplet-based single-cell RNA-seq, and it provides a straightforward way of multiplexing thousands of samples in a single experiment. Compared to multi-round combinatorial indexing, scifi-RNA-seq provides an easier, faster, and more efficient workflow. In contrast to cell hashing methods, which flag and discard droplets containing more than one cell, scifi-RNA-seq resolves and retains individual transcriptomes from overloaded droplets.
2021-03-11 | GSE168620 | GEO
Project description:Single-cell RNA sequencing in principle offers unique opportunities to improve the efficacy of contemporary T-cell based immunotherapy against cancer. The use of high-quality single-cell data will aid our incomplete understanding of molecular programs determining the differentiation and functional heterogeneity of cytotoxic T lymphocytes (CTLs) allowing for optimal therapeutic design. So far a major obstacle to high depth single-cell analysis of CTLs is the minute amount of RNA available leading to low capturing efficacy. To overcome this we tailor a droplet-based approach for high-throughput analysis (tDrop-seq) and a plate-based method for high-performance in-depth CTL analysis (tSCRB-seq). The latter gives on average a 15-fold higher number of captured transcripts per gene compared to droplet-based technologies. The improved dynamic range of gene detection gives tSCRB-seq an edge in resolution sensitive downstream applications such as graded high confidence gene expression measurements and cluster characterization. We demonstrate the power of tSCRB-seq by revealing the subpopulation-specific expression of co-inhibitory and co-stimulatory receptor targets of key importance for immunotherapy.
2020-12-13 | GSE163089 | GEO
Project description:We performed a high-throughput mapping of the 5’ end transcriptome of the pAA plasmid of the clinical Escherichia coli O104:H4 (E. coli O104:H4) isolate LB226692. We employed differential RNA-sequencing (dRNA-seq), a terminator exonuclease (TEX)-based RNA-seq approach allowing for the discrimination of primary and processed transcripts. This method has proven to be a powerful tool for the mapping of transcription start sites (TSS) and detection of non-coding RNAs (ncRNAs) in bacteria. We catalogued pAA-associated TSS and processing sites on a plasmid-wide scale and performed a detailed analysis of the primary transcriptome focusing on pAA virulence gene expression.
2016-10-19 | GSE78041 | GEO
Project description:PAT-seq - a high-throughput polyadenylation assay for the Illumina platform
2019-05-14 | E-MTAB-2456 | ExpressionAtlas
Project description:To generate a gene expression atlas of early adrenogonadal development, we performed single-cell transcriptome profiling using a high throughput droplet-based system (10X Genomics).
2023-02-27 | GSE156176 | GEO
Project description:A bead supsension and a solution of ERCC spike-ins at a concentration of ~100,000 molecules per droplet was used in Drop-Seq, a novel technology for high-throughput single cell mRNAseq An estimated 84 beads were selected for amplification.
2015-05-20 | E-GEOD-66694 | biostudies-arrayexpress
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:Droplet based MDA DNA sequencing
| PRJNA312675 | ENA
Project description:Droplet-based bisulfite sequencing for high-throughput profiling of single-cell DNA methylomes
| PRJNA841973 | ENA