Single-cell RNA sequencing reveals the transcriptomic landscape of kidneys in patients with ischemic acute kidney injury

Author:

Tang Rong12,Jin Peng3,Shen Chanjuan4,Lin Wei25,Yu Leilin16,Hu Xueling1,Meng Ting12,Zhang Linlin1,Peng Ling1,Xiao Xiangcheng12,Eggenhuizen Peter7,Ooi Joshua D.17,Wu Xueqin8,Ding Xiang3,Zhong Yong129

Affiliation:

1. Department of Nephrology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China

2. Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China

3. Department of Organ Transplantation, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China

4. Department of Hematology, The Affiliated Zhuzhou Hospital Xiangya Medical College, Central South University, Zhuzhou, Hunan 412007, China

5. Department of Pathology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China

6. Department of Nephrology, Jiujiang Hospital of Traditional Chinese Medicine, Jiujiang, Jiangxi 332099, China

7. Department of Medicine, Centre for Inflammatory Diseases, Monash Medical Centre, Monash University, Clayton, VIC 3168, Australia

8. Department of Nephrology, The Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, China

9. National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.

Abstract

Abstract Background: Ischemic acute kidney injury (AKI) is a common syndrome associated with considerable mortality and healthcare costs. Up to now, the underlying pathogenesis of ischemic AKI remains incompletely understood, and specific strategies for early diagnosis and treatment of ischemic AKI are still lacking. Here, this study aimed to define the transcriptomic landscape of AKI patients through single-cell RNA sequencing (scRNA-seq) analysis in kidneys. Methods: In this study, scRNA-seq technology was applied to kidneys from two ischemic AKI patients, and three human public scRNA-seq datasets were collected as controls. Differentially expressed genes (DEGs) and cell clusters of kidneys were determined. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, as well as the ligand–receptor interaction between cells, were performed. We also validated several DEGs expression in kidneys from human ischemic AKI and ischemia/reperfusion (I/R) injury induced AKI mice through immunohistochemistry staining. Results: 15 distinct cell clusters were determined in kidney from subjects of ischemic AKI and control. The injured proximal tubules (PT) displayed a proapoptotic and proinflammatory phenotype. PT cells of ischemic AKI had up-regulation of novel pro-apoptotic genes including USP47, RASSF4, EBAG9, IER3, SASH1, SEPTIN7, and NUB1, which have not been reported in ischemic AKI previously. Several hub genes were validated in kidneys from human AKI and renal I/R injury mice, respectively. Furthermore, PT highly expressed DEGs enriched in endoplasmic reticulum stress, autophagy, and retinoic acid-inducible gene I (RIG-I) signaling. DEGs overexpressed in other tubular cells were primarily enriched in nucleotide-binding and oligomerization domain (NOD)-like receptor signaling, estrogen signaling, interleukin (IL)-12 signaling, and IL-17 signaling. Overexpressed genes in kidney-resident immune cells including macrophages, natural killer T (NKT) cells, monocytes, and dendritic cells were associated with leukocyte activation, chemotaxis, cell adhesion, and complement activation. In addition, the ligand–receptor interactions analysis revealed prominent communications between macrophages and monocytes with other cells in the process of ischemic AKI. Conclusion: Together, this study reveals distinct cell-specific transcriptomic atlas of kidney in ischemic AKI patients, altered signaling pathways, and potential cell–cell crosstalk in the development of AKI. These data reveal new insights into the pathogenesis and potential therapeutic strategies in ischemic AKI.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine,General Medicine

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