Unsupervised analysis of combined cells from all six clusters (three healthy and three rejection) by tSNE resulted in the expected three cell types, indicating that rejection did not fundamentally alter tubular cell identity (Figure 3D, Supplemental Figure 6). monocyte cell subtypes was validated by staining of self-employed transplant biopsy specimens. Assessment of healthy N-Methylcytisine kidney epithelial transcriptomes with biopsy specimen counterparts recognized novel segment-specific proinflammatory reactions in rejection. Endothelial cells created three unique subclusters: resting cells N-Methylcytisine and two triggered endothelial cell organizations. One triggered endothelial cell group indicated Fc receptor pathway activation and Ig internalization genes, consistent with the pathologic analysis of antibody-mediated rejection. We mapped previously defined genes that associate with rejection results to solitary cell types and generated a searchable on-line gene expression database. Conclusions We present the first step toward incorporation of single-cell transcriptomics into kidney biopsy specimen interpretation, describe a heterogeneous immune response in combined rejection, and provide a searchable resource for the scientific community. for 5 minutes, resuspended in inDrops cell suspension buffer (9% Optiprep), and strained through a 40-(CD16) distinguishes monocyte 1 from monocyte 2, whereas is usually expressed in monocyte 2 but not monocyte 1. MSR1 is usually expressed in both clusters. (F) Immunohistochemistry for or on normal, mixed rejected, or pure antibody-mediated rejection (ABMR) transplant kidney biopsies. Distinct monocyte 1 and 2 cell types can be seen. Upper and lower panels are serial sections. Scale bar, 50 (CD16) and was most similar to CD16-positive, proinflammatory, nonclassic monocytes.17 Of note, CD16++ cells are strongly associated with allograft rejection.18,19 Monocyte 2 seems to be a classic or intermediate monocyte population (Determine 2A, Supplemental Table 4). Interestingly, and (Physique 2D). We identified unique marker genes for each monocyte cluster (Physique 2E) and performed immunohistochemistry on impartial transplant biopsies, with histologic diagnoses of no disease, mixed rejection, or ABMR. There was sparse interstitial staining for both the monocyte 1 marker (FCGR3A or CD16) and the monocyte 2 marker (FCN1) in biopsies with no disease. By contrast, there was strong staining for both monocyte subsets in mixed rejection, with lesser infiltration in pure ABMR N-Methylcytisine (Physique 2F, Supplemental Physique 5). Costaining by immunofluorescence analysis confirmed that this monocyte subtypes are individual populations (Physique 2G). The presence N-Methylcytisine of these monocyte subsets in all six impartial biopsies with mixed rejection or ABMR validates the use of scRNA-seq to identify novel cell types associated with kidney rejection. Ligand-receptor analysis revealed expression of 14 receptors (excluding collagens) for which we could detect expression of their cognate ligands (Physique 2B). These ligands were detected in all cell types, emphasizing the integration of signals between multiple kidney and leukocyte cell types. Pericytes, fibroblasts, and myofibroblasts expressed the chemoki and is expressed on mast cells in the biopsy (Physique 2B).25 Stem cell factor promotes mast cell migration, adhesion, proliferation, and survival. Mast cells transcripts correlate strongly with allograft biopsy fibrosis.26 These results suggest the unexpected hypothesis N-Methylcytisine that collecting duct epithelia actively coordinate mast cell infiltration during rejection. Consistent with TIL4 an important role for mast cells in kidney injury, a recent study showed that mast cell ablation in the early phases of renal injury is sufficient to reduce subsequent fibrosis by decreasing the inflammatory response.27,28 Activation of Epithelial, Endothelial, and Stromal Cells in Allograft Rejection We next compared epithelial transcriptomes from the biopsy with their healthy counterparts. Multiple attempts at scRNA-seq of healthy nephrectomy tissue failed to generate libraries; however, we were successful in generating adult human kidney single-nucleus RNA-sequencing (RNA-seq) data. We sequenced 4259 nuclei to a similar depth as the biopsy and identified six.
