Introduction: There is still a shortage of systematic reports on the changes in mitochondrial-related pathways and genes following kidney IRI through multi-omics techniques, and the role of mitochondria in renal IRI needs further exploration. The purpose of this study was to conduct a comprehensive analysis of mitochondrial-related pathway and gene changes after kidney IRI using transcriptomic, metabolomic, proteomic, and single cell transcriptomics approaches, in hopes of finding new therapeutic targets.
Method: A unilateral renal IRI model was established using C57BL/6 mice. Mice were killed 24h after reperfusion, and kidney samples were collected for metabolomic, transcriptomic, and proteomic sequencing. Single-cell transcriptomic data were retrieved from Gene Expression Omnibus (GEO). Common changed mitochondrial-related pathways were identified using these multiple types of omic data. Machine learning algorithms were performed to screen hub Mito-RGs based on transcriptome data and GEO datasets. Kidney IRI animal and cell models were used for the validation of gene expression.
Results: The results of transcriptomic, metabolomic, proteomic, single-cell transcriptomic analyses showed that energy-related mitochondrial pathways were impaired after kidney IRI. The ssGSEA analysis based on multi-omics data also confirmed that mitochondrial pathways were significantly impaired after kidney IRI. Through the comprehensive analysis of GSE43974 dataset and our transcriptomic data by combining bioinformatics analysis and machine learning strategies, we found that PDK4 was hub Mito-RGs in kidney IRI. The expression levels and function of PDK4 were confirmed in kidney IRI models in vivo and in vitro.
Conclusion: Mitochondrial pathways were significantly inhibited after kidney IRI, characterized by impaired energy metabolism. PDK4 is a novel therapeutic target for kidney ischemia reperfusion.