Project description:We performed RNA-Seq transcriptome profiling on 29 immune cell types consituting peripheral blood mononuclear cells (PBMCs) sorted from 4 Singaporean-Chinese individuals (S4 cohort). We also performed RNA-Seq and microarray transcriptome profiling of PBMCs from an extended cohort of 13 individuals (S13 cohort). The data was used first to characterize the transcriptomic signatures and relationships among the 29 immune cell types. Then we explored the difference in mRNA composition in terms of transcripts proportions and abundance. Lastly, we performed deep deconvolution for both microarray and RNA-Seq technologies.
Project description:We performed RNA-Seq transcriptome profiling on 29 immune cell types consituting peripheral blood mononuclear cells (PBMCs) sorted from 4 Singaporean-Chinese individuals (S4 cohort). We also performed RNA-Seq and microarray transcriptome profiling of PBMCs from an extended cohort of 13 individuals (S13 cohort). The data was used first to characterize the transcriptomic signatures and relationships among the 29 immune cell types. Then we explored the difference in mRNA composition in terms of transcripts proportions and abundance. Lastly, we performed deep deconvolution for both microarray and RNA-Seq technologies.
Project description:Systems biology is an approach to comprehensively study complex interactions within a biological system. Most published systems vaccinology studies have utilized whole blood or peripheral blood mononuclear cells (PBMC) to monitor the immune response after vaccination. Because human blood is comprised of multiple hematopoietic cell types, the potential for masking responses of under-represented cell populations is increased when analyzing whole blood or PBMC. To investigate the contribution of individual cell types to the immune response after vaccination, we established a rapid and efficient method to purify human T and B cells, natural killer (NK) cells, myeloid dendritic cells (mDC), monocytes, and neutrophils from fresh venous blood. Purified cells were fractionated and processed in a single day. RNA-Seq and quantitative shotgun proteomics were performed to determine expression profiles for each cell type prior to and after inactivated seasonal influenza vaccination. Our results show that transcriptomic and proteomic profiles generated from purified immune cells differ significantly from PBMC. Differential expression analysis for each immune cell type also shows unique transcriptomic and proteomic expression profiles as well as changing biological networks at early time points after vaccination. This cell type-specific information provides a more comprehensive approach to monitor vaccine responses.
2015-01-08 | PXD001657 | Pride
Project description:Circular RNA-seq of peripheral blood mononuclear cell
Project description:To investigate a non-invasive strategy for immune monitoring the peripheral blood by flow cytometry, to address the critical need to itdentify predictive immunological biomarkers that correlate with treatment response Peripheral blood mononuclear cells (PBMCs) from 19 non–small-cell lung cancer (NSCLC) patients before and after ICI treatment and four healthy human donors were evaluated, utilizing spectral flow to monitor 24 immune cell markers simultaneously over the course of treatment. We performed immune cell profiling analysis using data obtained from RNA-seq of 19 different patients before and after immunotherapy, to validate the multi-color flow based immune profiling
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.
Project description:Single-cell RNA-seq analysis of murine bone marrow and peripheral blood mononuclear cells (PBMCs) immune populations isolated from B-ALL recipient animals and two healthy littermate controls.