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Project description:single-cell RNA-seq for indicated genotypes
2022-11-18 | GSE200556 | GEO
Project description:Interferon regulation of neonatal hematopoiesis
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Project description:RNA-seq of Human Embryonic Stem Cell derived pancreas progenitor differentiation, Day 13 of wildtype, HES1-/-, NEUROG3-/- and HES1-/-NEUROG3-/- genotypes
2025-01-23 | E-MTAB-7185 | ExpressionAtlas
Project description:Type I interferon (IFN-1) regulates gene expression and hematopoiesis both during development and in response to inflammatory stress. We previously showed that during development in mice, hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) induce IFN-1 target genes shortly before birth. This coincides with the onset of a transition to adult hematopoiesis, and it drives the expression of genes associated with antigen presentation. However, it is not clear whether perinatal IFN-1 modulates hematopoietic output, as has been observed in contexts of inflammation. We have characterized hematopoiesis at several different stages of blood formation, from HSCs to mature blood cells, and found that loss of the IFN-1 receptor (IFNAR1) leads to depletion of several phenotypic HSC and MPP subpopulations in neonatal and juvenile mice. Committed lymphoid and myeloid progenitor populations expand simultaneously. These changes had a surprisingly little effect on the production of more differentiated blood cells. Cellular indexing of transcriptomes and epitopes by sequencing resolved the discrepancy between the extensive changes in progenitor numbers and modest changes in hematopoiesis, revealing stability in most MPP populations in Ifnar1-deficient neonates when the populations were identified based on gene expression rather than surface marker phenotype. Thus, basal IFN-1 signaling has only modest effects on hematopoiesis. Discordance between transcriptionally and phenotypically defined MPP populations may affect interpretations of how IFN-1 shapes hematopoiesis in other contexts, such as aging or inflammation.
| S-EPMC10250919 | biostudies-literature
Project description:RNA-seq of human neuroblastoma cell lines
2025-01-23 | E-MTAB-2690 | ExpressionAtlas
Project description:Single cell RNA-seq indicated that putrescine inhibited B-cell differentiation in vitro
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Project description:RNA-seq upon PAX8 knockdown in Renal Cell Carcinoma cell lines
2025-01-23 | E-MTAB-7808 | ExpressionAtlas
Project description:RNA-seq of two Trifolium pratense genotypes, Tripo and Lasang, from early to late developmental stages of flower development
2018-01-05 | E-MTAB-5117 | ExpressionAtlas
Project description:Single cell RNA-seq indicated that putrescine inhibited B-cell differentiation in Peyer's patches
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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