Chen Kai, Zhang Junqing, Huang Youyuan, Tian Xiaodong, Yang Yinmo, Dong Aimei
Department of General Surgery, Peking University First Hospital, Beijing 100034, China.
Department of Endocrinology, Peking University First Hospital, Beijing 100034, China.
iScience. 2022 Oct 14;25(11):105366. doi: 10.1016/j.isci.2022.105366. eCollection 2022 Nov 18.
Single-cell RNA sequencing has paved the way for delineating the pancreatic islet cell atlas and identifying hallmarks of diabetes. However, pathological alterations of type 2 diabetes (T2D) remain unclear. We isolated pancreatic islets from control and T2D mice for single-cell RNA sequencing (scRNA-seq) and retrieved multiple datasets from the open databases. The complete islet cell landscape and robust marker genes and transcription factors of each endocrine cell type were identified. GLRA1 was restricted to beta cells, and beta cells exhibited obvious heterogeneity. The beta subcluster in the T2D mice remarkably decreased the expression of Slc2a2, G6pc2, Mafa, Nkx6-1, Pdx1, and Ucn3 and had higher unfolded protein response (UPR) scores than in the control mice. Moreover, we developed a Web-based interactive tool, creating new opportunities for the data mining of pancreatic islet scRNA-seq datasets. In conclusion, our work provides a valuable resource for a deeper understanding of the pathological mechanism underlying diabetes.
单细胞RNA测序为描绘胰岛细胞图谱和识别糖尿病的特征铺平了道路。然而，2型糖尿病（T2D）的病理改变仍不清楚。我们从对照小鼠和T2D小鼠中分离出胰岛进行单细胞RNA测序（scRNA-seq），并从开放数据库中检索了多个数据集。确定了完整的胰岛细胞图谱以及每种内分泌细胞类型的可靠标记基因和转录因子。GLRA1仅限于β细胞，并且β细胞表现出明显的异质性。T2D小鼠中的β亚群显著降低了Slc2a2、G6pc2、Mafa、Nkx6-1、Pdx1和Ucn3的表达，并且其未折叠蛋白反应（UPR）评分高于对照小鼠。此外，我们开发了一个基于网络的交互式工具，为胰岛scRNA-seq数据集的数据挖掘创造了新机会。总之，我们的工作为更深入了解糖尿病的病理机制提供了宝贵资源。
