Transcriptomics combined with metabolomics analysis of the mechanism of agmatine in the treatment of septic liver injury

Abstract

Background: Acute liver injury can occur at any stage of sepsis and is an important sign of multiple organ dysfunction syndrome (MODS). Studies have shown that agmatine (AGM) can effectively improve liver injury caused by sepsis. However, due to the numerous metabolites and metabolic pathways of AGM in the human body, its mechanism in treating septic liver injury is unclear.Methods: In this study, a liver injury model of septic Sprague-Dawley rats was established by cecal ligation and perforation (CLP). After AGM treatment, transcriptomics combined with metabolomics was employed to analyze the gene expression levels and metabolite changes. Results:The results showed that AGM decreased the expression levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), procalcitonin (PCT), and inflammatory factors [interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β)] in the serum of septic rats. It also reduced liver inflammatory cell infiltration and abnormal lipid metabolism, and promoted the survival rate of septic rats. In addition, 17 differentially-expressed genes were identified by transcriptomics, mainly in arginine and proline metabolism, the arachidonic acid metabolism pathway, as well as the nuclear factor kappa B (NF-κB) and AMP-activated protein kinase (AMPK)-peroxisome proliferator-activated receptor α (PPARα) signal transduction pathways. Metabolomics analysis was carried out to study the potential liver metabolism spectrum changes induced by AGM treatment. The results showed significant changes in 26 metabolites in the rat liver samples, mainly involved in arginine and proline metabolism, arachidonic acid metabolism, linoleic acid metabolism, and fatty acid metabolism. Conclusions:The integrated transcriptomics and metabolomics analysis demonstrated that AGM improved septic liver injury by regulating lipid metabolism, and reduced the inflammatory reaction by affecting fatty acid metabolism, amino acid metabolism, and the arachidonic acid metabolism pathway. The integration of transcriptomics and metabolomics provides an effective means to elucidate AGM's therapeutic pathways and biomarkers.

LncRNA 220: A Novel Long Non-Coding RNA Regulates Autophagy and Apoptosis in Kupffer Cells via the miR-5101/PI3K/AKT/mTOR Axis in LPS-Induced Endotoxemic Liver Injury in Mice

“…These results suggested that lncRNAs were primarily expressed during the 8 h period. Prior research has established that ALI may manifest at any point during sepsis, indicating its potential significance as a marker for MODS [ 58 ]. Collectively, a duration of 8 h of LPS treatment may serve as the intervention condition in the present investigation.…”

Integration of multiomics analysis to reveal the major pathways of vitamin A deficiency aggravates acute respiratory distress syndrome in neonatal rats

“…The reference genome and gene annotation files were downloaded from genome website. The filtered reads were mapping to the reference genome using HISAT2 v2.0.5.Then, the quality of the library was evaluated by an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, United States).After RNA extraction, purification, and library construction of the samples, next-generation sequencing technology was used to perform paired-end (PE) testing on these libraries using the Illumina sequencing platform (NEB, United States) 14 . Then difference expression of genes was analyzed by DESeq (1.30.0) with screened conditions as follows: expression difference multiple |log2FoldChange| > 1, significant P-value < 0.05.…”

“…Then difference expression of genes was analyzed by DESeq (1.30.0) with screened conditions as follows: expression difference multiple |log2FoldChange| > 1, significant P-value < 0.05. At the same time, We used R language Pheatmap(1.0.8) software package to perform bi-directional clustering analysis of all different genes of samples 14 . On the basis of the existing reference genome, using the software StringTie ( http://ccb.jhu.edu/software/stringtie/ ) to assemble the mapped reads.…”