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Updated: May 16, 2026

Mouse Kidney Transplantation: Models of Allograft Rejection
Published on: October 11, 2014
Urinary single-cell transcriptomics in kidney transplantation: Elucidation of donor-recipient cellular dynamics and
Thangamani Muthukumar1, Aziz Belkadi2, Carol Li3
1Division of Nephrology and Hypertension, Department of Medicine, Weill Cornell Medical College, New York, New York, USA; Department of Transplantation Medicine, NewYork Presbyterian Hospital-Weill Cornell Medical College, New York, New York, USA.
Abstract:
Urinary single-cell RNA sequencing (scRNA-seq) provides a noninvasive and mechanistically informative approach for studying kidney allograft biology. We established a high-quality urinary scRNA-seq workflow and applied it to 12 kidney recipients with various clinical states. Benchmarking genotype-based deconvolution against published tissue data sets confirmed accurate assignment of donor and recipient cell origins in urine, despite the low-input challenges. Analysis showed that most urinary cells were recipient-derived, indicating that urine primarily reflects the host immune environment rather than the graft parenchyma. Integration with nontransplant reference data sets revealed conserved epithelial programs but enrichment of immune and proliferative subsets in transplant urine, consistent with active immune surveillance and repair. Urinary podocytes exhibited epithelial-to-mesenchymal transition signatures linked to fibrogenic stress. Recipient T cells displayed activated cytotoxic states, whereas rare donor T cells retained quiescent, tissue-associated characteristics. Donor-derived macrophages exhibited antigen-presenting and chemotactic signatures, suggesting that persistent graft-resident macrophages maintain functional activity and can be detected in urine. Collectively, these results validate urinary scRNA-seq as a robust and reproducible platform for capturing the mechanistic processes underlying epithelial injury, immune activation, and graft adaptation. This noninvasive approach extends molecular monitoring beyond biopsy, providing a scalable tool for the dynamic, mechanistically informed assessment of kidney allograft health.
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