Confirmative Structural Annotation for Metabolites of (R)-7,3′-Dihydroxy-4′-methoxy-8-methylflavane, A Natural Sweet Taste Modulator, by Liquid Chromatography–Three-Dimensional Mass Spectrometry

Abstract

Flavonoids occupy the largest family of natural products and possess a broad spectrum of health benefits. Their metabolites are sometimes the truly effective molecules in vivo. It is still challenging, however, to unambiguously identify flavonoid metabolites using conventional LC–MS/MS. Herein, we aimed to pursue auxiliary structural clues to m/z values in both MS1 and MS2 spectra through LC coupled to three-dimensional MS (LC–3D MS). MS1, as the first dimension, was in charge of suggesting theoretical molecular formulas, MS2, the as second dimension, was responsible for offering substructures, and exactly, online energy-resolved MS (ER-MS), as the third dimension, provided optimal collision energies (OCEs) that reflected the linkage manners among the substructures. Metabolic characterization of a natural sweet taste modulator, namely, (R)-7,3′-dihydroxy-4′-methoxy-8-methylflavane (DHMMF), was conducted as a proof-of-concept. Extensive efforts, such as full MS1 and MS2 scans on IT-TOF-MS and predictive selected-reaction monitoring mode on Qtrap-MS, were made for in-depth metabolite mining. Seventeen metabolites (M1–M17) were captured from DHMMF-treated biological samples, including 17 (M1–M17), 10 (M4–M9, M11, M13, M14, and M16), and 2 (M5 and M10) metabolites from urine, plasma, and feces, respectively. Their structures were configured by integrating MS1, MS2, and OCE information. Except M10, all metabolites were new compounds. LC–MS/MS-guided chromatographic purification yielded three glucuronyl-conjugated metabolites (M5, M8, and M11), and NMR spectroscopic assays consolidated the structures transmitted from LC–3D MS. Demethylation, glucuronidation, and sulfation occurred as the primary metabolic pathways of DHMMF. Above all, LC–3D MS bridged LC–MS/MS from putatively structural annotation toward confidence-enhanced identification, beyond the metabolite characterization of flavonoids.

Full Collision Energy Ramp-MS2 Spectrum in Structural Analysis Relying on MS/MS

“…Some reports focusing on the correlations between RII and structures are available now. , Because RII is dependent on collision energy (CE), RII value at a single CE level, however, might cause spectral interpretation misleading risks. The breakdown graph is termed as the ion intensity as a function of CE and as the acme, optimal CE (OCE) is able to partially denote CID thermodynamic patterns and further to provide important information regarding the linkage fashion among substructures. − To extract as much information as possible from the MS 2 spectral pattern, herein, we conceptually propose a full CE ramp-MS 2 (FCER-MS 2 ) spectrum. MS 2 spectra at high and low CE levels are first recorded using LC–Q-Exactive-MS to comprehensively capture fragment ion species.…”

“…MS 2 spectra at high and low CE levels are first recorded using LC–Q-Exactive-MS to comprehensively capture fragment ion species. Online energy-resolved MS (ER-MS) is subsequently programmed on an LC–Qtrap-MS platform to acquire a breakdown graph for each obvious MS 2 spectral signal. − After data normalization through defining the greatest value amongst all regressive apices as 100%, the breakdown graphs are assembled to produce an FCER-MS 2 spectrum for each compound. The MS 2 spectrum at any CE level can be extracted from the FCER-MS 2 spectrum and moreover, OCE along with RII max , which is termed as RII at OCE, is obviously available for each fragment ion.…”