A novel strategy integrating gas phase fractionation with staggered mass range and LC-MS/MS molecular network for comprehensive metabolites profiling of Gui Ling Ji in rats

Abstract

Metabolite detection from complex biological samples faces challenges due to interference from endogenous substrates and the inherent limitation of multiple subsequent tandem scanning rates of instruments. Here, a new integrated approach based on gas-phase fractionation with a staggered mass range (sGPF) and a liquid chromatography-tandem mass spectrometry (LC-MS/MS) molecular network was developed to accelerate the data processing of the targeted and untargeted constituents absorbed in rats after oral administration of the traditional Chinese medicine (TCM) prescription Gui Ling Ji (GLJ). Compared with three conventional acquisition methods, sGPF at 3, 5, and 7 mass fractions could enhance MS/MS coverage with an increased MS/MS triggering rate of 29.4–206.2% over data-dependent acquisition (DDA), fast DDA and gas-phase fractionation. A mass range fraction setting of five optimized the performance. Based on the similar diagnostic fragment ions and characteristic neutral loss behaviors in the DDA-MS/MS spectrum, an initial molecular network of GLJ was created with the help of the global natural products social molecular networking (GNPS) platform. Furthermore, to remove the endogenous interference nodes, Cytoscape software was adopted to produce a clean and concise molecular network of prototype compounds and their corresponding metabolites. Using this strategy, a total of 210 compounds, including 59 prototype constituents and 151 metabolites, was unambiguously or tentatively identified in GLJ. This first systematic metabolic study of GLJ in vivo elucidated the potential pharmacodynamic basis of GLJ in clinical treatment. More importantly, this work can serve as a practical example and establish a guide for rapidly identifying TCM metabolites in biological matrices.