ARTICLE https://doi.org/10.1038/s41467-021-22368-w OPEN Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney Yoshiharu Muto 1,7, Parker C. Wilson 2,7, Nicolas Ledru 1, Haojia Wu1, Henrik Dimke 3,4, ✉ Sushrut S. Waikar 5 & Benjamin D. Humphreys 1,6 1234567890():,; The integration of single cell transcriptome and chromatin accessibility datasets enables a deeper understanding of cell heterogeneity. We performed single nucleus ATAC (snATAC- seq) and RNA (snRNA-seq) sequencing to generate paired, cell-type-specific chromatin accessibility and transcriptional profiles of the adult human kidney. We demonstrate that snATAC-seq is comparable to snRNA-seq in the assignment of cell identity and can further refine our understanding of functional heterogeneity in the nephron. The majority of differ- entially accessible chromatin regions are localized to promoters and a significant proportion are closely associated with differentially expressed genes. Cell-type-specific enrichment of transcription factor binding motifs implicates the activation of NF-κB that promotes VCAM1 expression and drives transition between a subpopulation of proximal tubule epithelial cells. Our multi-omics approach improves the ability to detect unique cell states within the kidney and redefines cellular heterogeneity in the proximal tubule and thick ascending limb. 1 Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA. 2 Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA. 3 Department of Cardiovascular and Renal Research, Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark. 4 Department of Nephrology, Odense University Hospital, Odense, Denmark. 5 Section of Nephrology, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA. 6 Department of Developmental Biology, Washington ✉ University in St. Louis, St. Louis, MO, USA. 7These authors contributed equally: Yoshiharu Muto, Parker C. Wilson. email: [email protected] NATURE COMMUNICATIONS | (2021) 12:2190 | https://doi.org/10.1038/s41467-021-22368-w | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22368-w he kidney is composed of diverse cell types with distinct Results subpopulations and single-cell sequencing can dissect Single-cell transcriptional and chromatin accessibility profiling T 1 cellular heterogeneity at high resolution . For example, a in the adult human kidney. snRNA-seq and snATAC-seq were small subset of cells within the proximal tubule and Bowman’s performed on five healthy adult kidney samples (Fig. 1a). Selected capsule express vimentin, CD24, and CD1332,3. These cells have patients ranged in age from 50 to 62 years and included men a distinct morphology and expression profile and undergo (n = 3) and women (n = 2). All patients had preserved kidney expansion after acute kidney injury3. Furthermore, they have function (mean sCr = 1.07 mg/dl, eGFR = 64.4 ± 4.7 ml/min/ reported potential for tubular and podocyte regeneration4–7 and 1.73 m2). Histologic review showed no significant glomerulo- have been implicated in the development of renal cell sclerosis or interstitial fibrosis and tubular atrophy (Supplemen- carcinoma8. However, the sparsity of these cells has hampered tary Table 1). We processed these samples at different timepoints. further characterization. Another example of cellular hetero- Batch correction was performed with the R package “Harmony” geneity is seen in the thick ascending limb. Studies in mouse and for both snATAC-seq and snRNA-seq datasets. We used Seurat human suggest that there are structural and functional differ- to determine the cellular composition of our snRNA-seq samples, ences between medullary and cortical thick ascending limb, annotate cells based on their transcriptional profiles, and inform however, the signaling pathways that drive these differences are our snATAC-seq analysis (Fig. 1a). snRNA-seq identified all not well defined9. major cell types within the kidney cortex (Fig. 1b, Supplementary Single-cell or nucleus RNA sequencing (scRNA-seq or snRNA- Fig. 1a) based on the expression of lineage-specific markers seq) has fostered a greater understanding of the genes and (Fig. 1c, Supplementary Fig. 1b). We detected proximal tubule pathways that define cell identity in the kidney1. Multiple scRNA- (PT), parietal epithelial cells (PEC), thick ascending limb (TAL), seq atlases of mature human10–13 and mouse kidney14,15 have distal tubule (DCT1, DCT2), connecting tubule (CNT), collecting established how transcription contributes to cell-type specificity. duct (PC, ICA, ICB), endothelial cells (ENDO), glomerular cell Recent methods have expanded this approach to single-cell pro- types (MES, PODO), fibroblasts (FIB), and a small population of filing of chromatin accessibility16–18. Single nucleus assay for leukocytes (LEUK) (Supplementary Table 2, Supplementary transposase-accessible chromatin using sequencing (snATAC- Data 1). Notably, there was a subpopulation of proximal tubule seq) is an extension of bulk ATAC-seq19 that employs hyper- that had increased expression of VCAM1 (PT_VCAM1). This active Tn5 transposase to measure chromatin accessibility in subpopulation also expressed HAVCR1 (kidney injury molecule- thousands of individual cells17. Chromatin accessibility is a 1), which is a gene upregulated in the proximal tubule after acute dynamic process that drives nephron development and nephron injury and a predictor of long-term renal outcomes25. progenitors have distinct chromatin accessibility profiles that change as they differentiate18. The role of chromatin accessibility in the promotion or inhibition of kidney repair and regeneration Integration of single nucleus RNA and ATAC datasets for has important implications for designing therapies for acute and prediction and validation of ATAC cell-type assignments. chronic kidney disease and may help to improve directed dif- snATAC-seq captures the chromatin accessibility profile of ferentiation of kidney organoids20. Joint profiling by scRNA-seq individual cells17. Relatively less is known about cell-type-specific and snATAC-seq in the adult mouse kidney has provided a fra- chromatin accessibility profiles; so we leveraged our annotated mework for understanding how chromatin accessibility regulates snRNA-seq dataset to predict snATAC-seq cell types with Seurat transcription16; however, the single-cell epigenomic landscape of using label transfer21. Label transfer was performed by creating a the human kidney has not been described. gene-activity matrix from the snATAC-seq data, which is a Integration and analysis of multimodal single-cell datasets is an measure of chromatin accessibility within the gene body and emerging field with enormous potential for accelerating our promoter of protein-coding genes. Transfer anchors were iden- understanding of kidney disease and development21. Bioinfor- tified between the “reference” snRNA-seq dataset and “query” matics tools can extract unique information from snATAC-seq gene activity matrix followed by the assignment of predicted cell datasets that is otherwise unavailable by scRNA-seq. Prediction of types. The distribution of snATAC-seq prediction scores showed cell-type-specific cis-regulatory DNA interactions22 and tran- that the vast majority of cells had a high prediction score and scription factor activity23 are two methods that complement the were confidently assigned to a single-cell type (Supplementary transcriptional information obtained by scRNA-seq. Long-range Fig. 2). The snATAC-seq dataset was filtered using a 97% con- chromatin-chromatin interactions play an important role in fidence threshold for cell-type assignment to remove heterotypic transcriptional regulation and are influenced by transcription doublets. Comparison between snATAC-seq cell-type predictions factor binding24. Chromatin accessibility profiling will help to obtained by label transfer (Fig. 1d) and curated annotations of identify distant regulatory regions that influence transcription via unsupervised clusters (Fig. 1e, f, Supplementary Fig. 1c, d and long-range interactions. Supplementary Table 3) indicates that all major cell types were We have performed snATAC-seq and snRNA-seq to examine present in both datasets and that snATAC-seq is comparable to how chromatin accessibility can refine our understanding of cell snRNA-seq in the detection and assignment of cell identities state and function in the mature human kidney. We generated (Supplementary Fig. 3). We performed downstream analyses with an interactive multimodal atlas encompassing both tran- gene-activity-based cell-type assignments, which were obtained scriptomic and epigenomic data (http://humphreyslab.com/ by unsupervised clustering of the snATAC-seq dataset. Interest- SingleCell/). Data tracks for the cis-coaccessibility networks ingly, snATAC-seq was able to detect two subpopulations within and cell-specificdifferentiallyaccessiblechromatinareavailable the proximal tubule cluster, which likely represent the proximal for download and viewing with the UCSC genome browser convoluted tubule (Fig. 1e, PCT) and the proximal straight tubule (https://genome.ucsc.edu/s/parkercwilson/control_celltype_cr). (Fig. 1e, PST). PCT showed greater chromatin accessibility in Combined snRNA-seq and snATAC-seq analysis improved our SLC5A2, which encodes sodium glucose cotransporter