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Updated: Jan 31, 2026

Extraction of Aqueous Metabolites from Cultured Adherent Cells for Metabolomic Analysis by Capillary Electrophoresis-Mass Spectrometry
Published on: June 9, 2019
A comprehensive strategy for studying protein-metabolite interactions by metabolomics and native mass spectrometry
Qian Qin1, Bohong Wang1, Jiayue Wang2
1CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Abstract:
Protein-metabolite interactions play important roles in many cellular and physiological processes in biological systems. However, the lack of effective research approaches impedes the understanding of the protein-metabolite interactions. In this study, a novel comprehensive strategy by combining metabolomics platform with native mass spectrometry was developed for investigating the protein-metabolite interactions. Peroxisome proliferator-activated receptors gamma (PPARγ) is a lipid-binding nuclear receptors that plays a key role in regulating fatty-acid oxidation and lipid metabolism, which was selected as the model protein. Seven metabolites including lyso-phosphatidylcholine (LPC) 16:0, LPC18:0, LPC18:1, arachidonic acid, oleic acid, linoleic acid and palmitoleic acid (p < 0.05) were found to have the possible interactions with the PPARγ, these LPCs were discovered as candidate ligands for the first time by using untargeted metabolomics method. Native mass spectrometry based on 15 T Fourier transform ion cyclotron resonance mass spectrometer was employed to directly detect the PPARγ-LPCs complexes to obtain their stoichiometry and kinetic constants. Isothermal titration calorimetry, circular dichroism spectrum and molecular modeling were further utilized to investigate the thermodynamics, conformation and binding mechanism of the interaction between PPARγ and LPCs. It was found that the PPARγ-LPC interaction was an endothermic process, and these LPCs have similar binding constants with stoichiometric number of 1:1. The novel strategy can provide a very useful approach for mapping and identifying unknown protein-metabolite interactions in biological systems.
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