An atlas of healthy and injured cell states and niches in the human kidney [Slide-seq2]
Ontology highlight
ABSTRACT: Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
Project description:Spatially resolved transcriptomics technologies allow for the measurement of gene expression in situ. We applied direct RNA hybridization-based in situ sequencing (ISS, Cartana) to compare male and female healthy mouse kidneys and the male kidneys injury and repair timecourse of ischemic reperfusion injury (IRI). A pre-selected panel of 200 genes were used to identify the dynamics of cell states and their spatial distributions during injury and repair. We developed a new computational pipeline, CellScopes, for the rapid analysis, multi-omic integration and visualization of spatially resolved transcriptomic datasets. The resulting atlas allowed us to resolve distinct kidney niches, dynamic alterations in cell state over the course of injury and repair and cell-cell interactions between leukocytes and kidney parenchyma. Projection of snRNA-seq dataset from the same injury and repair samples allowed us to impute the spatial localization of genes not directly measured by Cartana.
Project description:Spatially resolved transcriptomics technologies allow for the measurement of gene expression in situ. We applied direct RNA hybridization-based in situ sequencing (ISS, Cartana) to compare male and female healthy mouse kidneys and the male kidneys injury and repair timecourse of ischemic reperfusion injury (IRI). A pre-selected panel of 200 genes were used to identify the dynamics of cell states and their spatial distributions during injury and repair. We developed a new computational pipeline, CellScopes, for the rapid analysis, multi-omic integration and visualization of spatially resolved transcriptomic datasets. The resulting atlas allowed us to resolve distinct kidney niches, dynamic alterations in cell state over the course of injury and repair and cell-cell interactions between leukocytes and kidney parenchyma. Projection of snRNA-seq dataset from the same injury and repair samples allowed us to impute the spatial localization of genes not directly measured by Cartana.
Project description:Kidneys possess come one of the most intricate three-dimensional cellular structures in the body, yet the spatial molecular principles of kidney health and disease remain inadequately understood. Here we generated high-quality single cell (sc), single nuclear (sn), spatial (sp) RNA expression and sn open chromatin datasets for 79 samples, capturing half a million cells from healthy, diabetic, and hypertensive diseased human kidneys. By combining the sn/sc and sp RNA data, we identify over 100 cell types and states and successfully map them back to their spatial locations. Computational deconvolution of spRNA-seq helps to identifies glomerular, tubular, immune, and fibrotic spatial microenvironments (FMEs). Although injured proximal tubule cells appear to be the nidus of fibrosis, we reveal the complex, heterogenous cellular and spatial organization of human FMEs, including the highly intricate and organized immune environment. We demonstrate the clinical utility of the FME spatial gene signature for the classification of a large number of human kidneys for disease severity and prognosis. We provide a comprehensive spatially-resolved molecular roadmap for the human kidney and the fibrotic process and demonstrate the clinical utility of spatial transcriptomics.
Project description:The kidney contains a population of resident macrophages from birth that expands as it grows and forms a contiguous network throughout the tissue. Kidney resident macrophages (KRMs) are important in homeostasis and the response to acute kidney injury (AKI). While the kidney contains many microenvironments, it is unknown whether KRMs are a heterogeneous population differentiated by function and location. We combined single-cell RNA sequencing (scRNAseq), spatial transcriptomics, flow cytometry, and immunofluorescence imaging to localize, characterize, and validate KRM populations during quiescence and following 19 minutes of bilateral ischemic kidney injury. scRNAseq and spatial transcriptomics revealed seven distinct KRM subpopulations, which are organized into zones corresponding to regions of the nephron. Each subpopulation was identifiable by a unique transcriptomic signature suggesting distinct functions. Specific protein markers were identified for two clusters allowing analysis by flow cytometry or immunofluorescence imaging. Following injury, the original localization of each subpopulation is lost, either from changing locations or transcriptomic signatures. The original spatial distribution of KRMs is not fully restored for at least 28 days post-injury. The change in KRM localization confirms a long hypothesized dysregulation of the local immune system following acute injury and may explain the increased risk for chronic kidney disease.
Project description:Fibroblasts are present in every organ. While the role fibroblasts in chronic diseases such as fibrosis or tumor expression has been extensively explored, little is known about their physiological role. The kidney possesses a unique capacity to recover from even severe acute injury. We study molecular mechanisms of this intrinsic repair capacity in the mouse model of ischemia-reperfusion (IR). In this model, the renal artery and vein are clamped for 45 min, leading to acute kidney injury. The kidney spontaneously recovers from such IR injury within 14 days. IR kidney injury is associated with a transient accumulation of fibroblasts in the diseased tissue. We hypothesized that fibroblasts aid the repair of acute IR injury in the kidney. To elucidate how FSP1+ fibroblasts may contribute to the repair of kidney injury, we undertook a global unbiased approach to compare gene expression profiles of fibroblasts isolated from kidneys post-IRI and from control kidneys by FACS sorting. To investigate the role fibroblasts may play in the repair of kidney inhury, we performed ischemia reperfusion injury surgery on transgenic mice in which the FSP-1 promoter drives EGFP expression. Kidney injury peaks at day 3 post-IRI, followed by spontaneous regeration that restores nearly perfect kidney architecture and health by day 10. Fibroblasts are thought to possibly play a role in this process, as they are normally rare in the healthy kidney, acute kidney injury is associated with a transient accumulation of interstitial fibroblasts, but whether they may help repair the acute kidney injury or in fact could contribute to the damage is not known. To compare the gene expression profiles of normal fibroblasts and those from post-ischemic kidneys, we sacrificed control FSP1-GFP mice and the FSP1-GFP mice three days post-IRI. We generated single-cell suspensions from both the post-IRI and control kidneys, and then isolated FSP1-GFP+ cells by FACS sorting that, when cultured on plastic, displayed typical fibroblast morphology. Total RNA was immediately extracted from the sorted cells and amplified to produce enough for a array. We biotinylated five of the samples from post-ischemic kidneys and three of the control (non-ischemic) kidneys and used Affymetrix 3' Arrays to examine differences in gene expression profiles between the two groups that may she some light on what role, if any, fibroblasts play in the spontaneous healing of the kidney after acute kidney injury. We performed ischemia reperfusion surgery in FSP1-GFP mice, and at day 3, we sacrificed the mice, isolated FSP1-GFP positive cells from both IR and normal control kidneys by FACS sorting, extracted total RNA from the isolated FSP1-GFP cells and used Affymetrix Mouse Expression Array 430 2.0 microarrays to perform gene expression profiling of the samples. All told, we performed the FACS Sorting, RNA extration, and hybridization with 5 ischemic kidneys and 3 normal kidneys. Fibroblasts, acute kidney injury, repair, comparative gene expression profiling, microarrays, FACS sorting, role in healing
Project description:T cells are important in the pathogenesis of acute kidney injury (AKI), and TCR+CD4-CD8- (double negative-DN) are T cells that have a regulatory role. However, little is understood about these cells in comparison to traditional CD4+ and CD8+ cells. To elucidate the molecular and spatial dynamics of DN T cells during AKI, we performed single-cell RNA sequencing (scRNA-seq) on sorted murine DN, CD4+, and CD8+ cells, combined with spatial transcriptomic profiling of normal and post-AKI mouse kidneys. scRNA-seq revealed distinct transcriptional profiles for DN, CD4+, and CD8+ T cells of mouse kidneys, with enrichment of Kcnq5, Klrb1c, Fcer1g, and Klre1 expression in DN T cells compared to CD4+ and CD8+ T cells in normal kidney tissue. We validated the expression of these genes in mouse and human kidney DN, CD4+ and CD8+ T cells using RT-PCR and in the NIH kidney precision medicine project (KPMP). Spatial transcriptomics in normal and ischemic mouse kidney tissue showed a localized cluster of T cells in the outer medulla expressing DN T cell genes including Fcer1g. These results provide a template for future studies in DN T as well as CD4+ and CD8+ cells in the normal and diseased kidney.