Single-cell RNA sequencing highlights the roles of C1QB and NKG7 in the pancreatic islet immune microenvironment in type 1 diabetes mellitus
Single-cell RNA sequencing (scRNA-seq) technology is a powerful tool for characterizing individual cells and elucidating biological mechanisms at the cellular level. Using this technology, this study focuses on the mechanism of C1QB and NKG7 in pancreatic islet immune microenvironment in type 1 diabetes mellitus (T1DM). T1DM-related scRNA-seq data were downloaded from GEO database, followed by batch effect removal, cluster analysis, cell annotation and enrichment analysis. Thereafter, T1DM-related Bulk RNA-seq data were downloaded from GEO database. The infiltrating immune cell abundance was estimated and its correlation with the expression of immune cell marker genes was determined. Functional assays were performed in a constructed rat model of T1DM and cultured monocytes and lymphocytes for further validation. A large number of highly variable genes were found in pancreatic islet samples in T1DM. T1DM islet-derived cells may consist of 14 cell types. Macrophages and T lymphocytes were the major cells in pancreatic islet immune microenvironment. C1QB and NKG7 may be the key genes affecting macrophages and T lymphocytes, respectively. Silencing C1QB inhibited the differentiation of monocytes into macrophages and reduced the number of macrophages. Silencing NKG7 prevented T lymphocyte activation and proliferation. In vivo data confirmed that silencing C1QB and NKG7 reduced the number of macrophages and T lymphocytes in the pancreatic islet of T1DM rats, respectively, and alleviated pancreatic islet β-cell damage. Overall, C1QB and NKG7 can increase the number of macrophages and T lymphocytes, respectively, causing pancreatic islet β-cell damage and promoting T1DM in rats. Keywords: C1QB; Immune microenvironment; Macrophages; Monocytes; NKG7; Pancreatic islet cells; T lymphocytes; Type 1 diabetes mellitus.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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