Application of UPLC-QTOF-MS in Analysis of Non-targeted Urine Metabolomics in Rats with Yunaconitine Poisoning / 法医学杂志

OBJECTIVES@#To explore the possible mechanism of Yunaconitine poisoning by studying the changes of urine metabolic profile in rats chronically poisoned by Yunaconitine via non-targeted metabolomics.@*METHODS@#A rat model of Yunaconitine poisoning was established, and a metabolomics method based on UPLC-QTOF-MS technology was used to obtain the urine metabolic profile. Principal component analysis (PCA), orthogonal projections to latent structures-discriminant analysis (OPLS-DA), variable importance in projection (VIP) value greater than 1, fold change (FC) value greater than 3 or less than 0.33 and P value less than 0.05 were used to screen potential biomarkers related to the toxicity of Yunaconitine. The metabolic pathway analysis was performed through the MetaboAnalyst website and pathological changes of related tissues were observed.@*RESULTS@#Sixteen potential biomarkers including L-isoleucine were screened, which mainly involved six metabolic pathways including the biosynthesis and degradation of valine, leucine and isoleucine, pentose and glucuronate interconversions, and propanoate metabolism, alanine, aspartate and glutamate metabolism, tyrosine metabolism. Pathological studies showed that rat toxic change in nervous system, liver and cardiac caused by Yunaconitine.@*CONCLUSIONS@#Yunaconitine may cause neurotoxicity, hepatotoxicity and cardiotoxicity by affecting amino acid and glucose metabolism.

Serum metabonomics in mice infected with mycoplasma pneumoniae by UPLC-Q-TOF-MS / 中国中药杂志

Ultra high performance liquid chromatography coupled with tandem quadrupole time of flight mass spectrometry(UPLC-Q-TOF-MS) was applied to metabonomics study in BALB/c mice infected with mycoplasma pneumoniae(MP) to analyze the changes in serum endogenous metabolites, identify potential biomarkers associated with mycoplasma pneumoniae pneumonia(MPP), analyze the metabolic pathway and explore the pathogenic mechanism of MPP. The BALB/c mice were inoculated with MP by repeated intranasal infectious routes to establish MPP models, and the results of the lung tissue biopsy, IgM and mycoplasma nucleic acid content determination showed that the models of MP in BALB/c mice were successfully established. UPLC-Q-TOF-MS was used to analyze the serum metabolic profiling of BALB/c mice infected with MP, and then principal component analysis(PCA) was combined with orthogonal partial least squares discriminant analysis(OPLS-DA) for data processing. The results showed that there were significant differences in serum metabolic profile between the MP infected mice and the normal mice. Forty-seven potential biomarkers such as ornithine, cortisol, vitamin A and tryptophan were screened out by database searching and MS information matching. These potential biomarkers related to 17 metabolic pathways including retinol metabolism, arginine and proline metabolism, steroid hormone synthesis and so on. The metabonomic research method for serum of mice infected with mycoplasma pneumoniae based on UPLC-Q-TOF-MS was established in this study. The metabolic changes of endogenous small molecules in mice infected with MP were reflected in the overall level, laying the foundation for the selection and evaluation of MPP drugs.

Metabolic fingerprint analysis of RAW264.7 inflammatory cell model by using UPLC-Q-TOF/MS / 中国中药杂志

In order to reveal the properties of polar metabolome in inflammatory cells, we selected LPS-induced RAW264.7 inflammatory cell models as the carrier for the research of metabolic fingerprint analysis. In this study, an ultra performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS)-based metabolomics protocol was optimized for the extraction of polar metabolites from RAW264.7 cell line. Then orthogonal partial least squares discriminant analysis (OPLS-DA) was used to process the metabolic data, and finally, a total of 17 metabolites were selected and identified. The results showed that MeOH-CHCl3-H2O (8∶1∶1) was chosen as the optimal extraction solvent to achieve higher number of chromatographic peaks, with the best relative extraction efficiency and stability. Comparing with the normal cells, the inflammatory cells presented an abnormal metabolism in protein, carbohydrate, nucleotide and phospholipids. In this study, a UPLC-Q-TOF/MS-based metabolomics protocol for the polar metabolites from RAW264.7 cell line was developed, which may provide important information for the study of mechanism of inflammation and the anti-inflammatory drugs.