Dataset Information

Single-Cell Transcriptome Profiling of the Kidney Glomerulus Identifies Key Cell Types and Reactions to Injury.

ABSTRACT:

Background

The glomerulus is a specialized capillary bed that is involved in urine production and BP control. Glomerular injury is a major cause of CKD, which is epidemic and without therapeutic options. Single-cell transcriptomics has radically improved our ability to characterize complex organs, such as the kidney. Cells of the glomerulus, however, have been largely underrepresented in previous single-cell kidney studies due to their paucity and intractability.

Methods

Single-cell RNA sequencing comprehensively characterized the types of cells in the glomerulus from healthy mice and from four different disease models (nephrotoxic serum nephritis, diabetes, doxorubicin toxicity, and CD2AP deficiency).

Results

All cell types in the glomerulus were identified using unsupervised clustering analysis. Novel marker genes and gene signatures of mesangial cells, vascular smooth muscle cells of the afferent and efferent arterioles, parietal epithelial cells, and three types of endothelial cells were identified. Analysis of the disease models revealed cell type-specific and injury type-specific responses in the glomerulus, including acute activation of the Hippo pathway in podocytes after nephrotoxic immune injury. Conditional deletion of YAP or TAZ resulted in more severe and prolonged proteinuria in response to injury, as well as worse glomerulosclerosis.

Conclusions

Generation of comprehensive high-resolution, single-cell transcriptomic profiles of the glomerulus from healthy and injured mice provides resources to identify novel disease-related genes and pathways.

SUBMITTER: Chung JJ

PROVIDER: S-EPMC7609001 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND: The comprehensive analysis of human kidney glomerulus we previously performed using highly purified glomeruli, provided a dataset of 6,686 unique proteins representing 2,966 distinct genes. This dataset, however, contained considerable redundancy resulting from identification criteria under which all the proteins matched with the same set of peptides and its subset were reported as identified proteins. In this study we reanalyzed the raw data using the Mascot search engine and highly stringent criteria in order to select proteins with the highest scores matching peptides with scores exceeding the "Identity Threshold" and one or more unique peptides. This enabled us to exclude proteins with lower scores which only matched the same set of peptides or its subset. This approach provided a high-confidence, non-redundant dataset of identified proteins for extensive profiling, annotation, and comparison with other proteome datasets that can provide biologically relevant knowledge of glomerulus proteome. RESULTS: Protein identification using the Mascot search engine under highly stringent, computational strategy generated a non-redundant dataset of 1,817 proteins representing 1,478 genes. These proteins were represented by 2-D protein array specifying observed molecular weight and isoelectric point range of identified proteins to demonstrate differences in the observed and calculated physicochemical properties. Characteristics of glomerulus proteome could be illustrated by GO analysis and protein classification. The depth of proteomic analysis was well documented via comparison of the dynamic range of identified proteins with other proteomic analyses of human glomerulus, as well as a high coverage of biologically important pathways. Comparison of glomerulus proteome with human plasma and urine proteomes, provided by comprehensive analysis, suggested the extent and characteristics of proteins contaminated from plasma and excreted into urine, respectively. Among the latter proteins, several were demonstrated to be highly or specifically localized in the glomerulus by cross-reference analysis with the Human Protein Atlas database, and could be biomarker candidates for glomerular injury. Furthermore, comparison of ortholog proteins identified in human and mouse glomeruli suggest some biologically significant differences in glomerulus proteomes between the two species. CONCLUSIONS: A high-confidence, non-redundant dataset of proteins created by comprehensive proteomic analysis could provide a more extensive understanding of human glomerulus proteome and could be useful as a resource for the discovery of biomarkers and disease-relevant proteins.