Abstract: FR-OR133
Single Cell Transcriptome Analysis of Human Kidney Allograft
Session Information
- Translational and Transplant Pathology
October 26, 2018 | Location: 6E, San Diego Convention Center
Abstract Time: 04:42 PM - 04:54 PM
Category: Transplantation
- 1802 Transplantation: Clinical
Authors
- Suryawanshi, Hemant, The Rockefeller University, New York, New York, United States
- Yang, Hua, Weill-Cornell , New York, New York, United States
- Lagman, Milagros T., Weill Medical College of Cornell University, New York, New York, United States
- Lubetzky, Michelle L., Division of Nephrology and Hypertension, New York, New York, United States
- Tuschl, Thomas, Howard Hughes Medical Institute, New York, New York, United States
- Suthanthiran, Manikkam, Weill Cornell Medical College, New York, New York, United States
- Muthukumar, Thangamani, Weill Cornell Medicine, New York, New York, United States
Background
Unbiased transcriptome-based clustering analysis of cells within the kidney allograft may help identify cell type-specific injury and has the potential to redefine the current pathology-based classification of allograft rejection/injury.
Methods
Kidney allograft tissue obtained at the time of core needle biopsy (n=2, TK1 and TK2, Figure 1) was digested to generate single cell suspension. Droplet-based 10X Chromium platform (10X Genomics) was used to capture single cells in emulsion, followed by cDNA synthesis, sequencing, and analysis.
Results
We obtained 2,657 (TK1) and 2,207 (TK2) high-quality scRNA-seq profiles and identified 13 and 11 major cell clusters, respectively (Figure 2).
In both biopsies, T cells (27% TK1 and 24% TK2) were abundant despite the differences in histopathology findings. Cell types restricted to TK1 were NK, MZB and SMC, whereas cell types restricted to TK2 were NKT, MC and IC. Only TK2 had fibrosis but we found FB cells in both the samples.
Conclusion
Our single cell expression atlas of human kidney allograft has deciphered the complex cellular environment of kidney allograft and provides a powerful step towards better understanding of the cellular basis of kidney allograft dysfunction.