An in-source multiple collision-neutral loss filtering based nontargeted metabolomics approach for the comprehensive analysis of malonyl-ginsenosides from Panax ginseng, P. quinquefolius, and P. notoginseng

Abstract

The simultaneous identification and quantification of target metabolites from herbal medicines are difficult to implement by the full-scan MS based nontargeted metabolomics approaches. Here an in-source multiple collision-neutral loss filtering (IMC-NLF) based nontargeted metabolomics approach is developed and applied to identify and quantify the variations of malonyl-ginsenosides, a common group of acyl saponins with potential anti-diabetic activity, among Panax ginseng, P. quinquefolius, and P. notoginseng. The key steps of the IMC-NLF strategy are the acquisition of specific high-resolution neutral loss data and the efficient filtering of target precursor ions from the full-scan spectra. Using a hybrid LTQ-Orbitrap mass spectrometer after UHPLC separation, abundant in-source product ions, [M-H-CO2]- (due to the vulnerability of the carboxyl group) and [M-H-Mal.]-, were generated at the energies of 70 V and 90 V, respectively. After spectral deconvolution, the generated peak list was screened by dual NLF using a Neutral Loss MS Finder software (NL of 43.9898 Da for CO2 and 86.0004 Da for the malonyl substituent). By combining the precursor ions list-triggered HCD-MS/MS and basic hydrolysis, a total of 101 malonyl-ginsenosides (including 69 from P. ginseng, 52 from P. quinquefolius, and 44 from P. notoginseng) were identified or tentatively characterized. The variations of 81 characterized malonyl-ginsenosides among 45 batches of Ginseng samples were statistically analyzed disclosing ten potential markers. It is the first systematic analysis of malonyl-ginsenosides. The IMC-NLF approach by a single analytical platform is promising in targeted analyses of modification-specific metabolites in metabolomics and drug metabolism.