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Analysis of metabolic disturbances attributable to sepsis-induced myocardial dysfunction using metabolomics and transcriptomics techniques - PubMed

  • ️Sat Jan 01 2022

Analysis of metabolic disturbances attributable to sepsis-induced myocardial dysfunction using metabolomics and transcriptomics techniques

Xiaonan Jia et al. Front Mol Biosci. 2022.

Abstract

Background: Sepsis-induced myocardial dysfunction (SIMD) is the most common and severe sepsis-related organ dysfunction. We aimed to investigate the metabolic changes occurring in the hearts of patients suffering from SIMD. Methods: An animal SIMD model was constructed by injecting lipopolysaccharide (LPS) into mice intraperitoneally. Metabolites and transcripts present in the cardiac tissues of mice in the experimental and control groups were extracted, and the samples were studied following the untargeted metabolomics-transcriptomics high-throughput sequencing method. SIMD-related metabolites were screened following univariate and multi-dimensional analyses methods. Additionally, differential analysis of gene expression was performed using the DESeq package. Finally, metabolites and their associated transcripts were mapped to the relevant metabolic pathways after extracting transcripts corresponding to relevant enzymes. The process was conducted based on the metabolite information present in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results: One hundred and eighteen significant differentially expressed metabolites (DEMs) (58 under the cationic mode and 60 under the anionic mode) were identified by studying the SIMD and control groups. Additionally, 3,081 significantly differentially expressed genes (DEGs) (1,364 were down-regulated and 1717 were up-regulated DEGs) were identified in the transcriptomes. The comparison was made between the two groups. The metabolomics-transcriptomics combination analysis of metabolites and their associated transcripts helped identify five metabolites (d-mannose, d-glucosamine 6-phosphate, maltose, alpha-linolenic acid, and adenosine 5'-diphosphate). Moreover, irregular and unusual events were observed during the processes of mannose metabolism, amino sugar metabolism, starch metabolism, unsaturated fatty acid biosynthesis, platelet activation, and purine metabolism. The AMP-activated protein kinase (AMPK) signaling pathways were also accompanied by aberrant events. Conclusion: Severe metabolic disturbances occur in the cardiac tissues of model mice with SIMD. This can potentially help in developing the SIMD treatment methods.

Keywords: SIMD; metabolic; myocardial dysfunction; sepsis; transcriptomics.

Copyright © 2022 Jia, Peng, Ma, Liu, Yu and Wang.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1

The cardiac function of SIMD mice decreased significantly. (A) Representative images of mice heart examined by echocardiography. (B)EF%, FS% and LVESd (n = 6, p < 0.001) (C)Tn-I in serum were measured by ELISA assays (n = 6, p < 0.01).

FIGURE 2
FIGURE 2

The multidimensional results in positive and negative ionization modes are shown in this figure. (A,B) OPLS-DA score plot and OPLS-DA validation plot intercepts in positive ionization modes: the Treated group vs. the Control group. R2Y = (0.0, 0.9638), Q2 = (0.0,−0.139). (C,D) OPLS-DA score plot and OPLS-DA validation plot intercepts in negative ionization modes: the Treated group vs. the Control group. R2Y = (0.0, 0.8281), Q2 = (0.0,−0.2474).

FIGURE 3
FIGURE 3

In two ionization modes, one-dimensional, and multi-dimensional analysis results of differential metabolites. (A)significant differences in metabolite expression in positive ionization modes. (B)significant differences in metabolite expression in negative ionization modes.

FIGURE 4
FIGURE 4

Bioinformatics analysis of RNA-seq data. (A) Sample correlation test. (B)PCA of mRNAs. (C) Volcano plot of mRNAs. C-group the control group (n = 6). T-group the SIMD group (n = 6).

FIGURE 5
FIGURE 5

Differential expression of metabolites and related transcripts. (A)Differential expression of metabolites and related transcripts in positive ionization modes. (B) Differential expression of metabolites and related transcripts in negative ionization modes.

FIGURE 6
FIGURE 6

Metabolites with significant differences between the two groups.

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