Dataset Information

Comprehensive Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis

ABSTRACT: Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condi-tion with high morbidity and mortality among emergency patients, and it poses a sig-nificant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnostic biomarkers or treatment targets. In this study, we established an SA-AKI mouse model using LPS and performed proteomics and metabolomics analyses. A variety of bioinformatic analyses, including Gene Set En-richment Analysis (GSEA), Weighted Gene Co-expression Network Analysis (WGCNA), protein and protein interactions (PPI), and MetaboAnalyst analysis, were conducted to investigate the key molecules of SA-AKI. Proteomics and metabolomics analyses re-vealed that sepsis led to impaired renal mitochondrial function and metabolic disorders. Immune-related pathways were found to be activated in kidneys upon septic infection. The catabolic products of polyamines accumulated in septic kidneys. Overall, our study provides a more comprehensive understanding of SA-AKI and identifies potential pathways for this condition.

INSTRUMENT(S): Q Exactive HF-X

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Kidney

SUBMITTER: Jiatong Xu

LAB HEAD: Huadong Zhu

PROVIDER: PXD044371 | Pride | 2023-10-24

REPOSITORIES: Pride

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Publications

Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis.

Xu Jiatong J Li Jiaying J Li Yan Y Shi Xiaoxiao X Zhu Huadong H Chen Limeng L

Biomolecules 20230830 9

Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condition with high morbidity and mortality among emergency patients, and it poses a significant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnostic biomarkers or treatment targets. In this study, we established an SA-AKI mouse model using lipopolysaccharide (LPS) and performed proteomics and metabolomics analyses. A variety of bioinformatic ana ...[more]

PMID: 37759729

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Project description:# Background Acute kidney injury (AKI) in sepsis patients increases patient mortality. Endothelial cells are important players in the pathophysiology of sepsis-associated AKI (SA-AKI), yet knowledge regarding their spatiotemporal involvement in coagulation disbalance and leukocyte recruitment is lacking. This study investigated the identity and kinetics of responses of different microvascular compartments in kidney cortex in response to SA-AKI. # Methods Laser microdissected arterioles, glomeruli, peritubular capillaries, and postcapillary venules from kidneys of mice subjected to cecal ligation and puncture (CLP) were analyzed using RNA sequencing. Differential expression and pathway enrichment analyses identified genes involved in coagulation and inflammation. A selection of these genes was evaluated by RT-qPCR in microvascular compartments of renal biopsies from patients with SA-AKI. The role of two identified genes in lipopolysaccharide-induced endothelial coagulation and inflammatory activation were determined in vitro in HUVEC using siRNA-based gene silencing. # Results CLP-sepsis in mice induced altered expression of approximately 400 genes in the renal microvasculature, with microvascular compartments exhibiting unique spatiotemporal responses. In mice, changes in gene expression related to coagulation and inflammation were most extensive in glomeruli at early and intermediate time points, with high induction of Plat, Serpine1, Thbd, Icam1, Stat3, and Ifitm3. In human SA-AKI, PROCR and STAT3 were induced in postcapillary venules, while SERPINE1 expression was diminished. IFITM3 was increased in arterioles and glomeruli. In vitro studies revealed that STAT3 and IFITM3 partly control endothelial coagulation and inflammatory activation. # Conclusion Renal microvascular compartments in mice and humans exhibited heterogeneous changes in coagulation- and inflammation-related gene expression in response to SA-AKI. Additional research should aim at understanding the functional consequences of the here described heterogeneous microvascular responses to establish the usefulness of identified genes as therapeutic targets in SA-AKI.

Project description:Microarray analysis of human kidneys with acute kidney injury (AKI) has been limited because such kidneys are seldom biopsied. However, all kidney transplants experience AKI, and early kidney transplants without rejection are an excellent model for human AKI: they are screened to exclude chronic kidney disease, frequently biopsied, and have extensive follow-up. We used histopathology and microarrays to compare indication biopsies from 28 transplants with AKI to 11 pristine protocol biopsies of stable transplants. Kidneys with AKI showed increased expression of 394 injury-repair response associated transcripts, including many known epithelial injury molecules (e.g. ITGB6, LCN2), tissue remodeling molecules (e.g. VCAN), and inflammation molecules (S100A8, ITGB3). Many other genes also predict the phenotype, depending on statistical filtering rules, including AKI biomarkers as HAVCR1 and IL18. Most mouse orthologs of the top injury-repair transcripts were increased in published mouse AKI models. Pathway analysis of the injury-repair transcripts revealed similarities to cancer, development, and cell movement. The injury-repair transcript score AKI kidneys correlated with reduced function, future recovery, brain death, and need for dialysis, but not future graft loss. In contrast, histologic features of "acute tubular injury" did not correlate with function or with the molecular changes. Thus the injury-repair associated transcripts represent a massive coordinate injury-repair response of kidney parenchyma to AKI, similar to mouse AKI models, and provide an objective measure for assessing the severity of AKI in kidney biopsies and validation for the use of many AKI biomarkers. AKI biopsies sample names and CEL files are from GSE21374. All consenting renal transplant patients undergoing biopsies for cause as standard of care between 09/2004 and 10/2007 at the university of Alberta or between 11/2006 and 02/2007 at the University of Illinois were included in the analysis. In addition to the cores required for standard histopathology, we collected one core for gene expression studies. the relationship between gene expression in the biopsy and subsequent graft loss was analyzed. This dataset is part of the TransQST collection.

Dataset Information

Comprehensive Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis

Publications

Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis.

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