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. 2020 Jul 7;117(27):15874-15883.
doi: 10.1073/pnas.2005477117. Epub 2020 Jun 22.

Cell profiling of mouse acute kidney injury reveals conserved cellular responses to injury

Yuhei Kirita  1   2 , Haojia Wu  1 , Kohei Uchimura  1 , Parker C Wilson  3 , Benjamin D Humphreys  4   5
Affiliations

Cell profiling of mouse acute kidney injury reveals conserved cellular responses to injury

Yuhei Kirita et al. Proc Natl Acad Sci U S A. .

Abstract

After acute kidney injury (AKI), patients either recover or alternatively develop fibrosis and chronic kidney disease. Interactions between injured epithelia, stroma, and inflammatory cells determine whether kidneys repair or undergo fibrosis, but the molecular events that drive these processes are poorly understood. Here, we use single nucleus RNA sequencing of a mouse model of AKI to characterize cell states during repair from acute injury. We identify a distinct proinflammatory and profibrotic proximal tubule cell state that fails to repair. Deconvolution of bulk RNA-seq datasets indicates that this failed-repair proximal tubule cell (FR-PTC) state can be detected in other models of kidney injury, increasing during aging in rat kidney and over time in human kidney allografts. We also describe dynamic intercellular communication networks and discern transcriptional pathways driving successful vs. failed repair. Our study provides a detailed description of cellular responses after injury and suggests that the FR-PTC state may represent a therapeutic target to improve repair.

Keywords: AKI; epithelia; injury; transcriptomics.

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Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
Single nucleus RNA-seq atlas of mouse IRI kidney. (A) Summary of experimental strategy. n = 3 mice per group. (B) BUN (mg/dL) after sham and IRI. Data are shown as the mean ± SEM. (C) Table with details of group, replicates, and cell numbers of mouse IRI datasets present in this figure. (D) UMAP plots of all mouse IRI kidney datasets integrated with Harmony. ATL, thin ascending limb of loop of Henle; Bil, bilateral; CNT, connecting tubule; CPC, principle cells of collecting duct in cortex; CTAL, thick ascending limb of loop of Henle in cortex; DCT, distal convoluted tubule; DTL, descending limb of loop of Henle; EC, endothelial cells; Fib, fibroblasts; ICA, type A intercalated cells of collecting duct; ICB, type B intercalated cells of collecting duct; MD, macula densa; Mø, macrophages; MPC, principle cells of collecting duct in medulla; MTAL, thick ascending limb of loop of Henle in medulla; PEC, parietal epithelial cells; Per, pericytes; Pod, podocytes; PT-S1, S1 segment of proximal tubule; PT-S2, S2 segment of proximal tubule; PT-S3, S3 segment of proximal tubule; Uro, urothelium. (E) Dot plot displaying gene expression patterns of cluster-enriched markers, and bar plot displaying composition of clusters by groups.
Fig. 2.
Fig. 2.
Time course analysis of proximal tubular cells revealed new cell state, failed repair proximal tubular cells. (A) UMAP displaying the clustering of proximal tubular cells without Harmony integration and dot plot displaying gene expression patterns of cluster-enriched markers. (B) Bar plot displaying composition of groups by clusters. (C) Representative images of immunofluorescence staining for VCAM1 (red), Kim1 (green), and LTL (white). (Scale bars: 50 μm.) (D) Deconvolution analysis of bulk RNA-seq mouse kidney IRI dataset using gene sets specific for healthy PT, injured PT, and failed repair PT. *P < 0.05; **P < 0.01; ***P < 0.001, one-way ANOVA with post hoc Dunnett’s multiple comparisons test. (E) Monocle2 pseudotime trajectory of proximal tubular cells colored by cluster identity. (F) Gene expression dynamics on the trajectories. The expression dynamics of DEGs were cataloged into three clusters across pseudotime shown as red lines (successful repair) and blue lines (failed repair). Thick lines indicate the average gene expression patterns in each cluster. The top six enriched GO terms for each cluster are shown on the right.
Fig. 3.
Fig. 3.
Gene regulatory network analysis of proximal tubular cells predicts transcription factors for successful repair and failing repair. (A) Heat map depicting the average regulon activity in each cluster of proximal tubular cells. Representative transcription factors are highlighted along with corresponding DNA-binding motifs. Cluster identities are according to Fig. 2. (B) Regulon activity dynamics on the pseudotime trajectory. The regulon activity dynamics were cataloged into three clusters across pseudotime shown as blue lines (successful repair) and red lines (delayed repair). Thick lines indicate the average gene expression patterns in each cluster. Pseudotime trajectories are according to Fig. 2. Transcription factors that have downstream CKD GWAS hit genes are displayed with their target genes expression patterns by dot plots. TF, transcription factor.
Fig. 4.
Fig. 4.
Stromal subtypes are identified including a population with reversible expression of αSMA. (A) UMAP displaying the clustering of all stromal cells with Harmony integration and dot plot displaying gene expression patterns of cluster-enriched markers. SM, smooth muscle; JG, juxtaglomerular; Mes, mesangial. (B) UMAP displaying expression levels of typical myofibroblast markers in each group of the datasets. (C) Box plot displaying percentages (Pct.) of myofibroblast markers expressing cells in mouse fibroblast3 (cortical fibroblast) and fibroblast2 (medullary fibroblast) at each time point. (D) Representative images of immunofluorescence staining for αSMA (red) and Pdgfrb (green). (Scale bars: 50 μm.) (E) Diagram of the fate of fibroblasts after IRI.
Fig. 5.
Fig. 5.
Ligand–receptor (L-R) analysis reveals dynamics of leukocyte (Leu) stimulating signaling networks during AKI-to-CKD transition. TAL, thick ascending limp. (A) UMAP of the integrated datasets with recategorized cell type names for ligand–receptor analysis. (B) Changes in the standardized interaction scores for Ccl2-Ccr2 ligand–receptor pair between injured proximal tubular cells and interstitial cells. (C) UMAP displaying expression levels of Ccl2 and Ccr2 in each group. (D) Heat map displaying sum of the leukocyte chemotaxis relating L-R interaction scores from each cell type to leukocytes.
Fig. 6.
Fig. 6.
Signaling from proximal tubule to interstitial cell types in health and injury. Heat maps displaying scaled ligand–receptor interaction scores between proximal tubular cells and interstitial cells. (A) PT to endothelial cells. (B) PT to fibroblasts. (C) PT to leukocytes.
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