In:
Journal of the American Society of Nephrology, Ovid Technologies (Wolters Kluwer Health), Vol. 32, No. 3 ( 2021-3), p. 614-627
Abstract:
Microscopic analysis of urinary sediment is one of the most fundamental tests in nephrology. Urinary cells, however, have not been characterized in a standardized, unbiased manner. Single-cell transcriptomics of urine, of subjects with diabetic kidney disease and controls, were used to characterize 23,082 urinary cells in an unbiased manner. Combined analysis of urinary, kidney, and bladder cells indicated the technique can detect almost all kidney cell types and a variety of bladder cell types in human urine. This pilot study provides a reference dataset for future urinary single-cell characterization. Background Microscopic analysis of urine sediment is probably the most commonly used diagnostic procedure in nephrology. The urinary cells, however, have not yet undergone careful unbiased characterization. Methods Single-cell transcriptomic analysis was performed on 17 urine samples obtained from five subjects at two different occasions, using both spot and 24-hour urine collection. A pooled urine sample from multiple healthy individuals served as a reference control. In total 23,082 cells were analyzed. Urinary cells were compared with human kidney and human bladder datasets to understand similarities and differences among the observed cell types. Results Almost all kidney cell types can be identified in urine, such as podocyte, proximal tubule, loop of Henle, and collecting duct, in addition to macrophages, lymphocytes, and bladder cells. The urinary cell–type composition was subject specific and reasonably stable using different collection methods and over time. Urinary cells clustered with kidney and bladder cells, such as urinary podocytes with kidney podocytes, and principal cells of the kidney and urine, indicating their similarities in gene expression. Conclusions A reference dataset for cells in human urine was generated. Single-cell transcriptomics enables detection and quantification of almost all types of cells in the kidney and urinary tract.
Type of Medium:
Online Resource
ISSN:
1046-6673
,
1533-3450
DOI:
10.1681/ASN.2020050757
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2021
detail.hit.zdb_id:
2029124-3
