Ontology highlight
ABSTRACT:
PROVIDER: PRJNA673166 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12961080_1.fastq.gz | Fastqsanger.gz | |||
| SRR12961081_1.fastq.gz | Fastqsanger.gz | |||
| SRR12961082_1.fastq.gz | Fastqsanger.gz | |||
| SRR12961083_1.fastq.gz | Fastqsanger.gz | |||
| SRR12961084_1.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:Protein post-translational modifications transmit signals in part by creating binding sites for effector molecules. This is especially true in epigenetic pathways where histone tails are heavily modified, resulting in the recruitment of molecules that can affect transcription. One such molecule, plant homeodomain finger protein 20 (PHF20), uses a Tudor domain to read dimethyl-lysine residues and is a known component of the MOF histone acetyltransferase protein complex, suggesting it plays a role in the crosstalk between lysine methylation and histone acetylation. We sought to investigate the biological role of PHF20 by generating a knockout mouse. Without PHF20, mice die shortly after birth and display a wide variety of phenotypes within the skeletal and hematopoietic systems. Mechanistically, PHF20 is not required for maintaining the global H4K16 acetylation levels, but instead works downstream in transcriptional regulation of MOF target genes. ChIP sequencing of H4K16ace ChIP DNA from PHF20 knockout and wild type cells using Illumina Solexa Genome Analyzer II single end sequencing protocol.
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Project description:Here we adapt native elongating transcript sequencing (NET-seq) to develop transcription elongation factor associated nascent elongating transcript sequencing (TEF-seq). In this the RNA polymerase II (Pol2) transcription elongation complex (TEC) is immunoprecipitated via associated transcription elongation factors (TEFs). Sequencing from the 3' end of the Pol2-associated nascent transcript shows the position of the final incorporated nucleotide giving strand-specific, single nucleotide resolution maps of the level of TEF association with Pol2 during transcription.
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Project description:During maturation, eukaryotic precursor RNAs undergo processing events including intron splicing, 3’-end cleavage, and polyadenylation. Here, we describe nanopore analysis of CO-transcriptional Processing (nano-COP), a method for probing the timing and patterns of RNA processing. An extension of native elongating transcript sequencing (NET-seq), which quantifies transcription genome-wide through short-read sequencing of nascent RNA 3’ ends, nano-COP uses long-read nascent RNA sequencing to observe global patterns of RNA processing. First, nascent RNA is stringently purified through a combination of 4-thiouridine metabolic labeling and cellular fractionation. In contrast to cDNA or short-read–based approaches relying on reverse transcription or amplification, the sample is sequenced directly through nanopores to reveal the native context of nascent RNA. nano-COP identifies both active transcription sites and splice isoforms of single RNA molecules during synthesis, providing insight into patterns of intron removal and the physical coupling between transcription and splicing. The nano-COP protocol yields data within 3 days.
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Project description:We have genetically ablated the neural crest by simultaneously knocking out tfap2a and tfap2c in developing zebrafish embryos. We have collected 10 single embryos at the 15 somites stage from all nine possible genotypic combinations which can be found when heterozygous parent carriers of tfap2a and tfap2c are crossed. Embryos were prepped in singular, barcoded and RNA-Seq libraries were created using True-Seq stranded RNA-Seq LT kit. Libraries were paired end sequenced at 75bp on an Illumina Hi-Seq 2500.
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Project description:In this study, based on Nanopore direct RNA-seq where native RNAs are sequenced directly as near full-length transcripts in the 3' to 5' direction, transcription units of the phytopathogen Dickeya dadantii 3937 were validated and transcriptional termination sites were determined. Briefly, D. dadantii cultures were grown in M63 medium supplemented with 0.2% glucose and 0.2% PGA, until the early exponential phase (A600nm = 0.2, condition 1), or the early stationary phase (A600nm = 1.8, condition 2). RNAs were extracted using a frozen acid-phenol method, as previously described (Hommais et al. 2008), and treated successively with Roche and Biolabs DNases. Two samples were prepared: 50 µg of RNAs from each condition were pulled into one sample (sample 1), whereas the other one contained 100 µg of RNAs from condition 2 (sample 2). Both samples were then supplied to Vertis Biotechnologie AG for Nanopore native RNA-seq: total RNA preparations were first examined by capillary electrophoresis. For sample 1, ribosomal RNA molecules were depleted using an in-house developed protocol (recovery rate = 84%), whereas no ribodepletion was performed for sample 2. 3' ends of RNA were then poly(A)-tailed using poly(A) polymerase, and the Direct RNA sequencing kit (SQK-RNA002) was used to prepare the library for 1D sequencing on the Oxford Nanopore sequencing device. The direct RNA libraries were sequenced on a MinION device (MIN-101B) using standard settings. Basecalling of the fast5 files was performed using Guppy (version 3.6.1) with the following settings: --flowcell FLO-MIN106 --kit SQK-RNA002 --cpu_threads_per_caller 12--compress_fastq --reverse_sequence true --trim_strategy rna. Reads smaller than 50 nt were removed. 466 393 and 556 850 reads were generated for sample 1 and 2, respectively.
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