Amin Abedini1,2,3, Yuan O Zhu4, Shatakshee Chatterjee1,2,3, Gabor Halasz4, Kishor Devalaraja-Narashimha4, Rojesh Shrestha1,2,3, Michael S Balzer1,2,3, Jihwan Park1,2,3, Tong Zhou1,2,3, Ziyuan Ma5,2,3, Katie Marie Sullivan1,2,3, Hailong Hu1,2,3, Xin Sheng1,2,3, Hongbo Liu1,2,3, Yi Wei4, Carine M Boustany-Kari6, Uptal Patel7, Salem Almaani8, Matthew Palmer9, Raymond Townsend1, Shira Blady1, Jonathan Hogan1, Lori Morton4, Katalin Susztak5,2,3. 1. Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania. 2. Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania. 3. Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania. 4. Cardiovascular, Renal and Fibrosis Research, Regeneron Pharmaceuticals Inc., Tarrytown, New York. 5. Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania ksusztak@pennmedicine.upenn.edu. 6. Cardiometabolic Disease Research Department, Boehringer Ingelheim, Ridgefield, Connecticut. 7. Inflammation and Respiratory Therapeutics, Gilead Sciences Inc., Foster City, California. 8. Division of Nephrology, The Ohio State University Wexner Medical Center, Columbus, Ohio. 9. Department of Pathology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania.
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.
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.
Authors: Parker C Wilson; Haojia Wu; Yuhei Kirita; Kohei Uchimura; Nicolas Ledru; Helmut G Rennke; Paul A Welling; Sushrut S Waikar; Benjamin D Humphreys Journal: Proc Natl Acad Sci U S A Date: 2019-09-10 Impact factor: 11.205
Authors: Matthew D Cheung; Elise N Erman; Shanrun Liu; Nathaniel B Erdmann; Gelare Ghajar-Rahimi; Kyle H Moore; Jeffrey C Edberg; James F George; Anupam Agarwal Journal: Kidney360 Date: 2021-11-05
Authors: Michael S Balzer; Tomohito Doke; Ya-Wen Yang; Daniel L Aldridge; Hailong Hu; Hung Mai; Dhanunjay Mukhi; Ziyuan Ma; Rojesh Shrestha; Matthew B Palmer; Christopher A Hunter; Katalin Susztak Journal: Nat Commun Date: 2022-07-11 Impact factor: 17.694
Authors: Valerie A Luyckx; Andrew D Rule; Katherine R Tuttle; Pierre Delanaye; Helen Liapis; Afschin Gandjour; Paola Romagnani; Hans-Joachim Anders Journal: Nat Rev Nephrol Date: 2021-12-08 Impact factor: 42.439