Urinary Single-Cell Profiling Captures the Cellular Diversity of the Kidney
Amin Abedini, Yuan O Zhu, Shatakshee Chatterjee, Gabor Halasz, Kishor Devalaraja-Narashimha, Rojesh Shrestha, Michael S Balzer, Jihwan Park, Tong Zhou, Ziyuan Ma, Katie Marie Sullivan, Hailong Hu, Xin Sheng, Hongbo Liu, Yi Wei, Carine M Boustany-Kari, Uptal Patel, Salem Almaani, Matthew Palmer, Raymond Townsend, Shira Blady, Jonathan Hogan, Lori Morton, Katalin Susztak, TRIDENT Study Investigators, Katalin Susztak, Raymond Townsend, Shira Blady, Matthew Palmer, Carine Boustany, Richard Urquhart, Paolo Guarnieri, Lea Sarov-Blat, Erding Hu, Lori Morton, Kishor Devalaraja, Uptal Patel, Shawn Badal, John Liles, Jonathan Rosen, Anil Karihaloo, Randy Luciano, Jonathan Hogan, Amy Mottl, Shweta Bansal, Salem Almaani, Christos Argyropoulos, Kirk Campbell, Tamara Isakova, Oliver Lenz, Harold Szerlip, Matthias Kretzler, Pietro Canetta, Jeffery Schelling, Rupali Avasare, Frank Brosius, Michael Ross, Nelson Kopyt, James Tumlin, Julia Scialla, Richard Lafayette, Manisha Singh, Yan Zhong, Amin Abedini, Yuan O Zhu, Shatakshee Chatterjee, Gabor Halasz, Kishor Devalaraja-Narashimha, Rojesh Shrestha, Michael S Balzer, Jihwan Park, Tong Zhou, Ziyuan Ma, Katie Marie Sullivan, Hailong Hu, Xin Sheng, Hongbo Liu, Yi Wei, Carine M Boustany-Kari, Uptal Patel, Salem Almaani, Matthew Palmer, Raymond Townsend, Shira Blady, Jonathan Hogan, Lori Morton, Katalin Susztak, TRIDENT Study Investigators, Katalin Susztak, Raymond Townsend, Shira Blady, Matthew Palmer, Carine Boustany, Richard Urquhart, Paolo Guarnieri, Lea Sarov-Blat, Erding Hu, Lori Morton, Kishor Devalaraja, Uptal Patel, Shawn Badal, John Liles, Jonathan Rosen, Anil Karihaloo, Randy Luciano, Jonathan Hogan, Amy Mottl, Shweta Bansal, Salem Almaani, Christos Argyropoulos, Kirk Campbell, Tamara Isakova, Oliver Lenz, Harold Szerlip, Matthias Kretzler, Pietro Canetta, Jeffery Schelling, Rupali Avasare, Frank Brosius, Michael Ross, Nelson Kopyt, James Tumlin, Julia Scialla, Richard Lafayette, Manisha Singh, Yan Zhong
Abstract
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.
Keywords: RNA sequencing; diabetic kidney disease; single-cell transcriptomics; urine.
Copyright © 2021 by the American Society of Nephrology.
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Source: PubMed