Project description:We report the application of single cell RNA-seq for transcript profiling in bladder tissue from Interstitial cystitis/bladder pain syndrome (IC/BPS) with Hunner lesions and without Hunner lesions and normal tissue.
Project description:To investigate whether the bladder assembloids recapitulate cell compositions, in addition to the gene expression patterns of each cell type in the adult bladder, we performed single-cell RNA-seq of bladder assembloids and mouse adult bladders, and compared the transcriptional profiles between them at the single-cell level.
Project description:Bladder Ewing sarcoma/primitive neuroectodermal tumor (bladder ES/PNET) is a rare and highly malignant tumor associated with a poor prognosis, yet its underlying mechanisms remain poorly understood. This study employed a combination of single-cell RNA sequencing (scRNA-seq) analyses to delve into the pathogenesis of bladder ES/PNET. The investigation revealed the presence of specialized types of epithelial cells (referred to as bladder ES-Epi) and mast cells (referred to as bladder ES-Mast) within bladder ES/PNET in comparison to urothelial carcinoma. Notably, TNFRSF12A exhibited significant upregulation in bladder ES/PNET. Furthermore, mast cells possessed the ability to activate epithelial cells through the TNFSF12-TNFRSF12A ligand-receptor signaling pattern. This activation mechanism appears to contribute to the progression of bladder ES/PNET.
Project description:The gene activity during human urinary bladder development is largely unknown. Our aim is to provide gene expression data to identify active genes during development and to facilitate future candidate gene identification for bladder malformations. Here, we make the first step to provide RNA-Seq of time-series bladder tissues between week 5 to 10. Fetal lung is used as reference sample.
Project description:<p>Droplet-based single-cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While these approaches offer the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective, reliable, and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we have developed a microfluidic control instrument that can be easily assembled from 3D printed parts and commercially available components costing approximately $575. We adapted this instrument for massively parallel scRNA-seq and deployed it in a clinical environment to perform single-cell transcriptome profiling of disaggregated synovial tissue from 5 rheumatoid arthritis patients. We sequenced 20,387 single cells from synovectomies, revealing 13 transcriptomically distinct clusters. These encompass a comprehensive and unbiased characterization of the autoimmune infiltrate, including inflammatory T and NK subsets that contribute to disease biology. Additionally, we identified fibroblast subpopulations that are demarcated via THY1 (CD90) and CD55 expression. Further experiments confirm that these represent synovial fibroblasts residing within the synovial intimal lining and subintimal lining, respectively, each under the influence of differing microenvironments. We envision that this instrument will have broad utility in basic and clinical settings, enabling low-cost and routine application of microfluidic techniques, and in particular single-cell transcriptome profiling.</p> <p>Reprinted from [Stephenson et al., Nature Communications, 2018], with permission from the Nature Publishing Group.</p>
Project description:Single cell RNA sequencing of human thymic cells is dependent on isolation of highly pure and viable cell populations. This protocol describes the isolation of CD34+ progenitor and more differentiated CD34- fractions from post-natal thymic tissue to study thymopoiesis. CD34+ cells represent <1% of thymic cells, so this protocol uses magnetic- followed by fluorescence-activated cell separation to isolate highly enriched CD34+ cells. For complete details on the use and execution of this protocol, please refer to Le et al. (2020).