Project description:Bulk RNA-Seq datasets were generated for the roots and leaves of Pistia stratiotes in order to compare expression of nutrient transporters between the tissues
Project description:<p>Gene expression is a biological process regulated at different molecular levels, including chromatin accessibility, transcription, and RNA maturation and transport. In addition, these regulatory mechanisms have strong links with cellular metabolism. Here we present a multi-omics dataset that captures different aspects of this multi-layered process in yeast. We obtained RNA-seq, metabolomics, and H4K12Ac ChIP-seq data for wild-type and mip6delta strains during a heat-shock time course. Mip6 is an RNA-binding protein that contributes to RNA export during environmental stress and is informative of the contribution of post-transcriptional regulation to control cellular adaptations to environmental changes. The experiment was performed in quadruplicate, and the different omics measurements were obtained from the same biological samples, which facilitates the integration and analysis of data using covariance-based methods. We validate our dataset by showing that ChIP-seq, RNA-seq and metabolomics signals recapitulate existing knowledge about the response of ribosomal genes and the contribution of trehalose metabolism to heat stress.</p>
Project description:An updated representation of S. meliloti metabolism that was manually-curated and encompasses information from 240 literature sources, which includes transposon-sequencing (Tn-seq) data and Phenotype MicroArray data for wild-type and mutant strains.
Project description:The first GSSM of V. vinifera was reconstructed (MODEL2408120001). Tissue-specific models for stem, leaf, and berry of the Cabernet Sauvignon cultivar were generated from the original model, through the integration of RNA-Seq data. These models have been merged into diel multi-tissue models to study the interactions between tissues at light and dark phases.
Project description:Scaffold Attachment Factor B (SAFB) is a conserved RNA Binding Protein (RBP) that is essential for early mammalian development. However, the RNAs that associate with SAFB in mouse embryonic stem cells have not been characterized. Here, we addressed this unknown using RNA-seq and SAFB RNA immunoprecipitation followed by RNA-seq (RIP-seq) in wild-type mouse embryonic stem cells (ESCs) and in ESCs in which SAFB and SAFB2 were knocked out. The transcript most enriched in SAFB association was the lncRNA Malat1, which contains a series of purine-rich motifs in its 5 end. Beyond Malat1, SAFB predominantly associated with introns of protein-coding genes also through purine-rich motifs. Knockout of SAFB/2 led to down- and upregulation of genes in multiple biological pathways. The nascent transcripts of many downregulated genes associated with high levels of SAFB in wild-type cells, implying that SAFB binding promotes the expression of these genes. Reintroduction of SAFB into double-knockout cells restored gene expression towards wild-type levels, an effect that was again observable at the level of nascent transcripts. Proteomic analyses indicate an enrichment of nuclear speckle-associated, SR proteins in FLAG-tagged SAFB immunoprecipitated samples. Comparison to immunoprecipitates made from FLAG-tagging of another nuclear-enriched RNA-binding protein called HNRNPU (also known as SAF-A) identified both similarities and differences. Perhaps most notably, we observed a stronger enrichment for speckle-associated proteins in SAFB immunoprecipitations and a strong enrichment for paraspeckle-associated proteins in HNRNPU immunoprecipitations. Our findings suggest that among other potential functions in mouse embryonic stem cells, SAFB directly promotes the expression of a subset of genes through its ability to bind purine regions in nascent RNA.
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.