Metabolomics approach based on utra-performance liquid chromatography coupled to mass spectrometry with chemometrics methods for high-throughput analysis of metabolite biomarkers to explore the abnormal metabolic pathways associated with myocardial dysfunction

Comprehensive Evaluation of Lipopolysaccharide-Induced Changes in Rats Based on Metabolomics

Purpose

Substantial evidence indicates that lipopolysaccharide (LPS) exposure can lead to systemic inflammatory response syndrome (SIRS) and multiple organ failure. Previous metabolomic studies have mainly focused on LPS-induced depression or hepatic and renal effects. However, no comprehensive metabolomics-based analysis of the serum, liver, kidney, hippocampus, and heart following exposure to LPS has been undertaken to date.

Material and Methods

Male Sprague-Dawley rats were randomly allocated to a control and a LPS-treated group (n=8). LPS for 2 weeks (0.5 mg/kg every other day) was given via intraperitoneal injection. Gas chromatography-mass spectrometry (GC-MS) was used for metabolite determination, while multivariate statistical analysis was performed to identify differentially expressed metabolites between the two groups.

Results

Our study revealed that 24, 13, 12, 7, and 12 metabolites were differentially expressed between the LPS treatment group and the control group in the serum, liver, kidney, hippocampus, and heart, respectively. We further identified that these metabolic changes were mainly involved with aminoacyl-tRNA biosynthesis; glutathione metabolism; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; arginine biosynthesis; bile acid biosynthesis; and glycerolipid metabolism.

Conclusion

We have systematically elucidated the metabolic changes underlying LPS-induced SIRS, thereby providing insight into the mechanisms associated with these alterations.

High-Throughput Metabolomics Discovers Metabolic Biomarkers and Pathways to Evaluating the Efficacy and Exploring Potential Mechanisms of Osthole Against Osteoporosis Based on UPLC/Q-TOF-MS Coupled With Multivariate Data Analysis

Postmenopausal osteoporosis (PMOP) is the most common metabolic bone illness among the elderly especially in postmenopausal women resulting from a reduction in bone mineral density, but there is no effective drug at present. The study was aimed at evaluating efficacy of osthole against osteoporosis using high-throughput metabolomics method. The blood samples for illustrating the pathological mechanism of PMOP and exploring the efficacy of osthole treatment (ST) were collected to perform metabolites and metabolic profiles and pathways analysis using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) and pattern recognition methods. In addition, backbone weight, the bone density, and some vital biochemical indexes were also detected. A total of 28 metabolites were identified as biomarkers for ovariectomized-osteoporosis model, and ST could significantly regulate 19 of them including lysine, linoleic acid, 3-hydroxybutyric acid, prostaglandin F2a, taurocholic acid, LysoPC(15:0), l-carnitine, glucose, arginine, citric acid, corticosterone, ornithine, tryptophan, arachidonic acid, Cer(d18:0/18:0), glutamine, uric acid, 8-HETE, estriol, which mainly related with 13 metabolic pathways, such as linoleic acid metabolism, starch, and sucrose metabolism, arachidonic acid metabolism, alanine, aspartate and glutamate metabolism, arginine and proline metabolism, citrate cycle (TCA cycle), and arginine biosynthesis. The ovariectomized model (OVX) rats display a significant decrease bone density, TGF-β1, NO, and NOS level, and a significant increase bone weight, IL-6, TNF-α, and Ca 2+ level. These parameters in the ST rats were evidently improved as compared to the OVX group. ST effectively mitigated ovariectomy-induced osteoporosis in rats by affecting endogenous metabolite-related metabolic mechanism and showed the natural alternative with potential for the treatment of PMOP.