Literature DB >> 27371817

Metabolomic analysis of glycerophospholipid signatures of inflammation treated with non-steroidal anti-inflammatory drugs-induced-RAW264.7 cells using (1)H NMR and U-HPLC/Q-TOF-MS.

Xia Wu1, Han Cao1, Lifang Zhao1, Jianao Song1, Yuqi She1, Yifan Feng2.   

Abstract

Non-destructive proton nuclear magnetic resonance ((1)H NMR) spectroscopy and highly sensitive ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (U-HPLC/Q-TOF-MS) coupled to data processing methods were applied to analyze the metabolic profiling changes of glycerophospholipids (GPLs) in RAW264.7 cells from inflammation to prognosis. Analysis of (1)H NMR was shown that the models were grouped successfully, illustrating that all of them had significant differences. Based on the highly simple, accurate, non-targeted and non-destructively advantages of (1)H NMR, it could be used as a new screening tool of anti-inflammatory drugs in the metabolic profiling of GPLs. 58 GPLs were identified by U-HPLC/Q-TOF-MS, and 19 components were firstly identified in this study compared with our previous results. In addition, ten potential biomarkers were proved, of which phosphatidylcholine (PC) (16:0/18:1) and (18:0/18:1) changed consistently in three drug-induced groups and might be the important biomarkers. Compared with (1)H NMR, U-HPLC/Q-TOF-MS showed higher sensitivity and specificity and was more suitable for the determination of biomarkers apart from the deficiency of time-consuming sample preparation steps and unambiguous metabolite identification. Therefore, it is feasible to analyze the changes of GPLs during inflammation by combining (1)H NMR spectroscopy with U-HPLC/Q-TOF-MS. The metabolic profiling of GPLs provides valuable evidence for inflammation diagnosis and prognosis, and might unravel the mechanisms involved in inflammation progression.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  (1)H NMR; Biomarkers; Chemometrics; Glycerolphospholipids; RAW264.7 cells; U-HPLC/Q-TOF-MS

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Year:  2016        PMID: 27371817     DOI: 10.1016/j.jchromb.2016.06.032

Source DB:  PubMed          Journal:  J Chromatogr B Analyt Technol Biomed Life Sci        ISSN: 1570-0232            Impact factor:   3.205


  2 in total

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  2 in total

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