Which dataset
would you like to
analyze in BBrowser?

Species: human
Number of cells: 27203
Study size: 910MB

Immunology 

Spatiotemporal immune zonation of the human kidney (fetal)

Stewart, Benjamin J and Ferdinand, John R and Young, Matthew D and Mitchell, Thomas J and Loudon, Kevin W and Riding, Alexandra M and Richoz, Nathan and Frazer, Gordon L and Staniforth, Joy UL and Braga, Felipe A Vieira and others

Tissue-resident immune cells are important for organ homeostasis and defense. The epithelium may contribute to these functions directly or by cross-talk with immune cells. We used single-cell RNA sequencing to resolve the spatiotemporal immune topology of the human kidney. We reveal anatomically defined expression patterns of immune genes within the epithelial compartment, with antimicrobial peptide transcripts evident in pelvic epithelium in the mature, but not fetal, kidney. A network of tissue-resident myeloid and lymphoid immune cells was evident in both fetal and mature kidney, with postnatal acquisition of transcriptional programs that promote infection-defense capabilities. Epithelial-immune cross-talk orchestrated localization of antibacterial macrophages and neutrophils to the regions of the kidney most susceptible to infection. Overall, our study provides a global overview of how the immune landscape of the human kidney is zonated to counter the dominant immunological challenge.

Download bbrowser to analyze now

Species: human
Number of cells: 40268
Study size: 571MB

Immunology 

Spatiotemporal immune zonation of the human kidney (mature)

Stewart, Benjamin J and Ferdinand, John R and Young, Matthew D and Mitchell, Thomas J and Loudon, Kevin W and Riding, Alexandra M and Richoz, Nathan and Frazer, Gordon L and Staniforth, Joy UL and Braga, Felipe A Vieira and others

Tissue-resident immune cells are important for organ homeostasis and defense. The epithelium may contribute to these functions directly or by cross-talk with immune cells. We used single-cell RNA sequencing to resolve the spatiotemporal immune topology of the human kidney. We reveal anatomically defined expression patterns of immune genes within the epithelial compartment, with antimicrobial peptide transcripts evident in pelvic epithelium in the mature, but not fetal, kidney. A network of tissue-resident myeloid and lymphoid immune cells was evident in both fetal and mature kidney, with postnatal acquisition of transcriptional programs that promote infection-defense capabilities. Epithelial-immune cross-talk orchestrated localization of antibacterial macrophages and neutrophils to the regions of the kidney most susceptible to infection. Overall, our study provides a global overview of how the immune landscape of the human kidney is zonated to counter the dominant immunological challenge.

Download bbrowser to analyze now

Species: human
Number of cells: 23369
Study size: 234MB

kidney 

Single-cell RNA sequencing of human kidney

Jinling Liao, Zhenyuan Yu, Yang Chen, Mengying Bao, Chunlin Zou, Haiying Zhang, Deyun Liu, Tianyu Li, Qingyun Zhang, Jiaping Li, Jiwen Cheng & Zengnan Mo

A comprehensive cellular anatomy of normal human kidney is crucial to address the cellular origins of renal disease and renal cancer. Some kidney diseases may be cell type-specific, especially renal tubular cells. To investigate the classification and transcriptomic information of the human kidney, we rapidly obtained a single-cell suspension of the kidney and conducted single-cell RNA sequencing (scRNA-seq). Here, we present the scRNA-seq data of 23,366 high-quality cells from the kidneys of three human donors. In this dataset, we show 10 clusters of normal human renal cells. Due to the high quality of single-cell transcriptomic information, proximal tubule (PT) cells were classified into three subtypes and collecting ducts cells into two subtypes. Collectively, our data provide a reliable reference for studies on renal cell biology and kidney disease.

Download bbrowser to analyze now

Species: human
Number of cells: 4487
Study size: 84MB

kidney 

Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response

Haojia Wu, Andrew F. Malone, Erinn L. Donnelly, Yuhei Kirita, Kohei Uchimura, Sai M. Ramakrishnan, Joseph P. Gaut, Benjamin D. Humphreys

ackground: Single-cell genomics techniques are revolutionizing our ability to characterize complex tissues. By contrast, the techniques used to analyze renal biopsy specimens have changed little over several decades. We tested the hypothesis that single-cell RNA-sequencing can comprehensively describe cell types and states in a human kidney biopsy specimen. Methods: We generated 8746 single-cell transcriptomes from a healthy adult kidney and a single kidney transplant biopsy core by single-cell RNA-sequencing. Unsupervised clustering analysis of the biopsy specimen was performed to identify 16 distinct cell types, including all of the major immune cell types and most native kidney cell types, in this biopsy specimen, for which the histologic read was mixed rejection. Results: Monocytes formed two subclusters representing a nonclassical CD16+ group and a classic CD16− group expressing dendritic cell maturation markers. The presence of both monocyte cell subtypes was validated by staining of independent transplant biopsy specimens. Comparison of healthy kidney epithelial transcriptomes with biopsy specimen counterparts identified novel segment-specific proinflammatory responses in rejection. Endothelial cells formed three distinct subclusters: resting cells and two activated endothelial cell groups. One activated endothelial cell group expressed Fc receptor pathway activation and Ig internalization genes, consistent with the pathologic diagnosis of antibody-mediated rejection. We mapped previously defined genes that associate with rejection outcomes to single cell types and generated a searchable online 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 mixed rejection, and provide a searchable resource for the scientific community.

Download bbrowser to analyze now

Species: human
Number of cells: 4297
Study size: 97MB

Immunology 
epithelium 

Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response (healthy)

Haojia Wu, Andrew F. Malone, Erinn L. Donnelly, Yuhei Kirita, Kohei Uchimura, Sai M. Ramakrishnan, Joseph P. Gaut, Benjamin D. Humphreys

Background: Single-cell genomics techniques are revolutionizing our ability to characterize complex tissues. By contrast, the techniques used to analyze renal biopsy specimens have changed little over several decades. We tested the hypothesis that single-cell RNA-sequencing can comprehensively describe cell types and states in a human kidney biopsy specimen. Methods: We generated 8746 single-cell transcriptomes from a healthy adult kidney and a single kidney transplant biopsy core by single-cell RNA-sequencing. Unsupervised clustering analysis of the biopsy specimen was performed to identify 16 distinct cell types, including all of the major immune cell types and most native kidney cell types, in this biopsy specimen, for which the histologic read was mixed rejection. Results: Monocytes formed two subclusters representing a nonclassical CD16+ group and a classic CD16− group expressing dendritic cell maturation markers. The presence of both monocyte cell subtypes was validated by staining of independent transplant biopsy specimens. Comparison of healthy kidney epithelial transcriptomes with biopsy specimen counterparts identified novel segment-specific proinflammatory responses in rejection. Endothelial cells formed three distinct subclusters: resting cells and two activated endothelial cell groups. One activated endothelial cell group expressed Fc receptor pathway activation and Ig internalization genes, consistent with the pathologic diagnosis of antibody-mediated rejection. We mapped previously defined genes that associate with rejection outcomes to single cell types and generated a searchable online 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 mixed rejection, and provide a searchable resource for the scientific community.

Download bbrowser to analyze now

About 5 datasets