Differentially expressed miRNAs in sepsis-induced acute kidney injury target oxidative stress and mitochondrial dysfunction pathways

Abstract

Objective: To identify specific miRNAs involved in sepsis-induced AKI and to explore their targeting pathways.

Methods: The expression profiles of miRNAs in serum from patients with sepsis-induced AKI (n = 6), sepsis-non AKI (n = 6), and healthy volunteers (n = 3) were investigated by microarray assay and validated by quantitative PCR (qPCR). The targets of the differentially expressed miRNAs were predicted by Target Scan, mirbase and Miranda. Then the significant functions and involvement in signaling pathways of gene ontology (GO) and KEGG pathways were analyzed. Furthermore, eight miRNAs were randomly selected out of the differentially expressed miRNAs for further testing by qPCR.

Results: qPCR analysis confirmed that the expressions levels of hsa-miR-23a-3p, hsa-miR-4456, hsa-miR-142-5p, hsa-miR-22-3p and hsa-miR-191-5p were significantly lower in patients with sepsis compared with the healthy volunteers, while hsa-miR-4270, hsa-miR-4321, hsa-miR-3165 were higher in the sepsis patients. Statistically, miR-4321; miR-4270 were significantly upregulated in the sepsis-induced AKI compared with sepsis-non AKI, while only miR-4321 significantly overexpressed in the sepsis groups compared with control groups. GO analysis showed that biological processes regulated by the predicted target genes included diverse terms. They were related to kidney development, regulation of nitrogen compound metabolic process, regulation of cellular metabolic process, cellular response to oxidative stress, mitochondrial outer membrane permeabilization, etc. Pathway analysis showed that several significant pathways of the predicted target genes related to oxidative stress. miR-4321 was involved in regulating AKT1, mTOR and NOX5 expression while miR-4270 was involved in regulating PPARGC1A, AKT3, NOX5, PIK3C3, WNT1 expression. Function and pathway analysis highlighted the possible involvement of miRNA-deregulated mRNAs in oxidative stress and mitochondrial dysfunction.

Conclusion: This study might help to improve understanding of the relationship between serum miRNAs and sepsis-induced AKI, and laid an important foundation for further identification of the potential mechanisms of sepsis-induced AKI and oxidative stress and mitochondrial dysfunction.

Fig 1. Differentially expressed miRNAs between two groups.

Septic AKI (n = 6); Sepsis-non AKI (n = 6). Red color indicated high relative expression and green color denoted low relative expression. miRNA with expression fold change >1.5 and with FDR <0.05 was considered statistically significant.

Fig 2. Differentially expressed miRNAs among the three groups.

Control (n = 3); Septic AKI (n = 6); Sepsis-non AKI (n = 6). Red color indicated high relative expression and green color denoted low relative expression. miRNA with expression fold change >1.5 and with FDR <0.05 was considered statistically significant. MiRNAs marked with arrow were randomly selected for further confirmation by RT-qPCR.

Fig 3

Volcano plot (A) and scatter plot (B) of the miRNA microarray analysis. (A) Volcano plots are useful tool for visualizing differential expression patterns between two different conditions. The vertical lines correspond to 1.5-fold up and down, respectively, and the horizontal line represents a P value of 0.05. So the red point in the plot represents the differentially expressed miRNAs with statistical significance. (B) The scatter plot is a useful visualization for assessing the variation (or reproducibility) between chips. The axes of the scatter plot are the normalized signal values of the samples (the ratio scale).

Fig 4. Confirmation of miRNA level by RT-qPCR.

Relative expression of each miRNA was normalized to hsa-miR-423-5p level. miR-142-5p, miR-22-3p, miR-191-5p, miR-23a-3p and miR-4456 were significantly decreased in both the sepsis-induced AKI and sepsis-non AKI groups compared with the healthy controls. miR-4270, miR-4321 and miR-3165 were obviously increased in the sepsis-induced AKI, and miR-3165 also was obviously increased in sepsis-non AKI group compared with the healthy controls. While statistical significance between the sepsis-induced AKI and sepsis-non AKI groups was shown only on miR-4321 expression. Note: a single asterisk indicates significant difference between the healthy controls (n = 3) and the sepsis-induced AKI group (n = 6), as well as between the healthy controls and the sepsis-non AKI group (n = 6). A pound sign indicates a statistical difference between the sepsis-induced AKI group and the sepsis-non AKI group. P < 0.05 was considered statistically significant.

Fig 5. Bioinformatics GO and pathway analysis based on miRNA target genes.

Enrichment score is equal to -log10 (P-value) that represents the significant level of GOs and pathways. (A) Significant GOs. (B) Significant signaling pathways. KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene ontology. BH-corrected P < 0.05 was considered statistically significant.

Fig 6

The pathways enriched in the FoxO signaling pathway (A), PI3K-Akt signaling pathway(B), Wnt signaling pathway (C) and mTOR signaling pathway.

Fig 7. miRNA-mRNA gene network analysis.

All the miRNAs in the microarray and GOs were integrated by outlining the interactions of miRNA and GO-related genes