Jia Fu1,2, Kemal M Akat3, Zeguo Sun1, Weijia Zhang1, Detlef Schlondorff1, Zhihong Liu2, Thomas Tuschl3, Kyung Lee4, John Cijiang He4,5. 1. Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York. 2. National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China. 3. Laboratory of RNA Molecular Biology, The Rockefeller University, New York, New York; and. 4. Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York; cijiang.he@mssm.edu kim.lee@mssm.edu. 5. Renal Program, James J Peters VA Medical Center at Bronx, New York, New York.
Abstract
BACKGROUND: Recent single-cell RNA sequencing (scRNA-seq) analyses have offered much insight into cell-specific gene expression profiles in normal kidneys. However, in diseased kidneys, understanding of changes in specific cells, particularly glomerular cells, remains limited. METHODS: To elucidate the glomerular cell-specific gene expression changes in diabetic kidney disease, we performed scRNA-seq analysis of isolated glomerular cells from streptozotocin-induced diabetic endothelial nitric oxide synthase (eNOS)-deficient (eNOS-/-) mice and control eNOS-/- mice. RESULTS: We identified five distinct cell populations, including glomerular endothelial cells, mesangial cells, podocytes, immune cells, and tubular cells. Using scRNA-seq analysis, we confirmed the expression of glomerular cell-specific markers and also identified several new potential markers of glomerular cells. The number of immune cells was significantly higher in diabetic glomeruli compared with control glomeruli, and further cluster analysis showed that these immune cells were predominantly macrophages. Analysis of differential gene expression in endothelial and mesangial cells of diabetic and control mice showed dynamic changes in the pattern of expressed genes, many of which are known to be involved in diabetic kidney disease. Moreover, gene expression analysis showed variable responses of individual cells to diabetic injury. CONCLUSIONS: Our findings demonstrate the ability of scRNA-seq analysis in isolated glomerular cells from diabetic and control mice to reveal dynamic changes in gene expression in diabetic kidneys, with variable responses of individual cells. Such changes, which might not be apparent in bulk transcriptomic analysis of glomerular cells, may help identify important pathophysiologic factors contributing to the progression of diabetic kidney disease.
BACKGROUND: Recent single-cell RNA sequencing (scRNA-seq) analyses have offered much insight into cell-specific gene expression profiles in normal kidneys. However, in diseased kidneys, understanding of changes in specific cells, particularly glomerular cells, remains limited. METHODS: To elucidate the glomerular cell-specific gene expression changes in diabetic kidney disease, we performed scRNA-seq analysis of isolated glomerular cells from streptozotocin-induced diabeticendothelial nitric oxide synthase (eNOS)-deficient (eNOS-/-) mice and control eNOS-/- mice. RESULTS: We identified five distinct cell populations, including glomerular endothelial cells, mesangial cells, podocytes, immune cells, and tubular cells. Using scRNA-seq analysis, we confirmed the expression of glomerular cell-specific markers and also identified several new potential markers of glomerular cells. The number of immune cells was significantly higher in diabetic glomeruli compared with control glomeruli, and further cluster analysis showed that these immune cells were predominantly macrophages. Analysis of differential gene expression in endothelial and mesangial cells of diabetic and control mice showed dynamic changes in the pattern of expressed genes, many of which are known to be involved in diabetic kidney disease. Moreover, gene expression analysis showed variable responses of individual cells to diabetic injury. CONCLUSIONS: Our findings demonstrate the ability of scRNA-seq analysis in isolated glomerular cells from diabetic and control mice to reveal dynamic changes in gene expression in diabetic kidneys, with variable responses of individual cells. Such changes, which might not be apparent in bulk transcriptomic analysis of glomerular cells, may help identify important pathophysiologic factors contributing to the progression of diabetic kidney disease.
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