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Understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scRNA‐seq datasets
OBJECTIVES: To elaborately decipher the mouse and human bladders at single‐cell levels. MATERIALS AND METHODS: We collected more than 50,000 cells from multiple datasets and created, up to date, the largest integrated bladder datasets. Pseudotime trajectory of urothelium and interstitial cells, as w...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780900/ https://www.ncbi.nlm.nih.gov/pubmed/34951074 http://dx.doi.org/10.1111/cpr.13170 |
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author | Shi, Bowen Wu, Yanyuan Chen, Haojie Ding, Jie Qi, Jun |
author_facet | Shi, Bowen Wu, Yanyuan Chen, Haojie Ding, Jie Qi, Jun |
author_sort | Shi, Bowen |
collection | PubMed |
description | OBJECTIVES: To elaborately decipher the mouse and human bladders at single‐cell levels. MATERIALS AND METHODS: We collected more than 50,000 cells from multiple datasets and created, up to date, the largest integrated bladder datasets. Pseudotime trajectory of urothelium and interstitial cells, as well as dynamic cell‐cell interactions, was investigated. Biological activity scores and different roles of signaling pathways between certain cell clusters were also identified. RESULTS: The glucose score was significantly high in most urothelial cells, while the score of H3 acetylation was roughly equally distributed across all cell types. Several genes via a pseudotime pattern in mouse (Car3, Dkk2, Tnc, etc.) and human (FBLN1, S100A10, etc.) were discovered. S100A6, TMSB4X, and typical uroplakin genes seemed as shared pseudotime genes for urothelial cells in both human and mouse datasets. In combinational mouse (n = 16,688) and human (n = 22,080) bladders, we verified 1,330 and 1,449 interactive ligand‐receptor pairs, respectively. The distinct incoming and outgoing signaling was significantly associated with specific cell types. Collagen was the strongest signal from fibroblasts to urothelial basal cells in mouse, while laminin pathway for urothelial basal cells to smooth muscle cells (SMCs) in human. Fibronectin 1 pathway was intensely sent by myofibroblasts, received by urothelial cells, and almost exclusively mediated by SMCs in mouse bladder. Interestingly, the cell cluster of SMCs 2 was the dominant sender and mediator for Notch signaling in the human bladder, while SMCs 1 was not. The expression of integrin superfamily (the most common communicative pairs) was depicted, and their co‐expression patterns were located in certain cell types (eg, Itgb1 and Itgb4 in mouse and human basal cells). CONCLUSIONS: This study provides a complete interpretation of the normal bladder at single‐cell levels, offering an in‐depth resource and foundation for future research. |
format | Online Article Text |
id | pubmed-8780900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87809002022-02-01 Understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scRNA‐seq datasets Shi, Bowen Wu, Yanyuan Chen, Haojie Ding, Jie Qi, Jun Cell Prolif Original Articles OBJECTIVES: To elaborately decipher the mouse and human bladders at single‐cell levels. MATERIALS AND METHODS: We collected more than 50,000 cells from multiple datasets and created, up to date, the largest integrated bladder datasets. Pseudotime trajectory of urothelium and interstitial cells, as well as dynamic cell‐cell interactions, was investigated. Biological activity scores and different roles of signaling pathways between certain cell clusters were also identified. RESULTS: The glucose score was significantly high in most urothelial cells, while the score of H3 acetylation was roughly equally distributed across all cell types. Several genes via a pseudotime pattern in mouse (Car3, Dkk2, Tnc, etc.) and human (FBLN1, S100A10, etc.) were discovered. S100A6, TMSB4X, and typical uroplakin genes seemed as shared pseudotime genes for urothelial cells in both human and mouse datasets. In combinational mouse (n = 16,688) and human (n = 22,080) bladders, we verified 1,330 and 1,449 interactive ligand‐receptor pairs, respectively. The distinct incoming and outgoing signaling was significantly associated with specific cell types. Collagen was the strongest signal from fibroblasts to urothelial basal cells in mouse, while laminin pathway for urothelial basal cells to smooth muscle cells (SMCs) in human. Fibronectin 1 pathway was intensely sent by myofibroblasts, received by urothelial cells, and almost exclusively mediated by SMCs in mouse bladder. Interestingly, the cell cluster of SMCs 2 was the dominant sender and mediator for Notch signaling in the human bladder, while SMCs 1 was not. The expression of integrin superfamily (the most common communicative pairs) was depicted, and their co‐expression patterns were located in certain cell types (eg, Itgb1 and Itgb4 in mouse and human basal cells). CONCLUSIONS: This study provides a complete interpretation of the normal bladder at single‐cell levels, offering an in‐depth resource and foundation for future research. John Wiley and Sons Inc. 2021-12-23 /pmc/articles/PMC8780900/ /pubmed/34951074 http://dx.doi.org/10.1111/cpr.13170 Text en © 2021 The Authors. Cell Proliferation published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Shi, Bowen Wu, Yanyuan Chen, Haojie Ding, Jie Qi, Jun Understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scRNA‐seq datasets |
title | Understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scRNA‐seq datasets |
title_full | Understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scRNA‐seq datasets |
title_fullStr | Understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scRNA‐seq datasets |
title_full_unstemmed | Understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scRNA‐seq datasets |
title_short | Understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scRNA‐seq datasets |
title_sort | understanding of mouse and human bladder at single‐cell resolution: integrated analysis of trajectory and cell‐cell interactive networks based on multiple scrna‐seq datasets |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780900/ https://www.ncbi.nlm.nih.gov/pubmed/34951074 http://dx.doi.org/10.1111/cpr.13170 |
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