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Single-cell profiling reveals various types of interstitial cells in the bladder.

ABSTRACT: Clarifying the locations, molecular markers, functions and roles of bladder interstitial cells is crucial for comprehending the pathophysiology of the bladder. This research utilized human, rat and mouse bladder single-cell sequencing, bioinformatics analysis and experimental validation. The main cell types found in human, rat and mouse bladder tissues include epithelial cells, smooth muscle cells, endothelial cells, fibroblasts, myofibroblasts, neurons and various immune cells. Our study identified two significant types of interstitial cells (PTN⁺ IGFBP6⁺ PI16 (CD364)⁺ CD34⁺ ) and myofibroblasts (STC1⁺ PLAT⁺ TNC⁺ ). These two types of interstitial cells are mainly located in the subepithelial lamina propria, between muscles and between muscle bundles. In the CYP (cyclophosphamide)-induced bladder injury mouse model, the interaction types and signals (MK, MIF, GDF and CXCL) of fibroblasts and myofibroblasts significantly increased compared with the normal group. However, in the aging mouse model, the signals CD34, LAMININ, GALECTIN, MK, SELPLG, ncWNT, HSPG, ICAM and ITGAL-ITGB2 of fibroblasts and myofibroblasts disappeared, but the signals PTN and SEMA3 significantly increased. Our findings identified two crucial types of interstitial cells in bladder tissue, fibroblasts and myofibroblasts, which play a significant role in normal bladder physiology, CYP-induced bladder injury and aging bladder development.

SUBMITTER: Zhao J

PROVIDER: S-EPMC10472517 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Single-cell profiling reveals various types of interstitial cells in the bladder.

Zhao Jiang J Yang Chengfei C Liang Bo B Gao Ye Y Luo Jing J Zheng Ji J Song Bo B Shen Wenhao W Dong Xingyou X Dai ShuangShuang S Yang Zhenxing Z

Cell proliferation 20230223 9

Clarifying the locations, molecular markers, functions and roles of bladder interstitial cells is crucial for comprehending the pathophysiology of the bladder. This research utilized human, rat and mouse bladder single-cell sequencing, bioinformatics analysis and experimental validation. The main cell types found in human, rat and mouse bladder tissues include epithelial cells, smooth muscle cells, endothelial cells, fibroblasts, myofibroblasts, neurons and various immune cells. Our study identi ...[more]

PMID: 36824020

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Project description:Single-cell analysis has the potential to provide us with a host of new knowledge about biological systems, but it comes with the challenge of correctly interpreting the biological information. While emerging techniques have made it possible to measure inter-cellular variability at the transcriptome level, no consensus yet exists on the most appropriate method of data analysis of such single cell data. Methods for analysis of transcriptional data at the population level are well established but are not well suited to single cell analysis due to their dependence on population averages. In order to address this question, we have systematically tested combinations of methods for primary data analysis on single cell transcription data generated from two types of primary immune cells, neutrophils and T lymphocytes. Cells were obtained from healthy individuals, and single cell transcript expression data was obtained by a combination of single cell sorting and nanoscale quantitative real time PCR (qRT-PCR) for markers of cell type, intracellular signaling, and immune functionality. Gene expression analysis was focused on hierarchical clustering to determine the existence of cellular subgroups within the populations. Nine combinations of criteria for data exclusion and normalization were tested and evaluated. Bimodality in gene expression indicated the presence of cellular subgroups which were also revealed by data clustering. We observed evidence for two clearly defined cellular subtypes in the neutrophil populations and at least two in the T lymphocyte populations. When normalizing the data by different methods, we observed varying outcomes with corresponding interpretations of the biological characteristics of the cell populations. Normalization of the data by linear standardization taking into account technical effects such as plate effects, resulted in interpretations that most closely matched biological expectations. Single cell transcription profiling provides evidence of cellular subclasses in neutrophils and leukocytes that may be independent of traditional classifications based on cell surface markers. The choice of primary data analysis method had a substantial effect on the interpretation of the data. Adjustment for technical effects is critical to prevent misinterpretation of single cell transcript data.

Dataset Information

Single-cell profiling reveals various types of interstitial cells in the bladder.

Publications

Single-cell profiling reveals various types of interstitial cells in the bladder.

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