A multidimensional chromatography/high-resolution mass spectrometry approach for the in-depth metabolites characterization of two Astragalus species

Two Multidimensional Chromatography/High-Resolution Mass Spectrometry Approaches Enabling the In-Depth Metabolite Characterization Simultaneously from Three Glycyrrhiza Species: Method Development, Comparison, and Integration

“…Different types of silica gel cores were utilized, each with a unique bonding technique and bonding group (Table S3). Primarily, principal component analysis (PCA) modeling was used to intuitively reflect the overall separation difference on various licorice components among the 20 tested columns, taking the relative retention time ([retention time – dead time]/[effective elution time – dead time]) of 68 components as the index. , As shown in Figure A, 14 columns were gathered near the core point. However, the other six columns (including Cosmocore C18, CSH Cyano, HSS C18 SB, CSH Fluoro-Phenyl, XCharge C18, and Atlantis Premier BEH C18AX) exhibited significant separation differences on the licorice components with those 14 ones.…”

“…Structure identification primarily relied on the comparison with 33 standard compounds (Figure ), fragmentation pathway interpretation, and searching of an in-house library of licorice (recording 207 flavonoids, 70 triterpenoids, and 81 other compounds ever isolated from various Glycyrrhiza species). Notably, the data analysis and structural characterization based on the 6550 QTOF mass spectrometer were conducted in the manual mode . while more intelligent automatic peak annotation workflows were available by using the UNIFI software to process the data acquired on the Vion IM-QTOF mass spectrometer. , Ultimately, we could characterize 618 (Table S11) and 668 (Table S12) compounds from three Glycyrrhiza species by methods 1 and 2 , respectively.…”

An efficient approach addressing the chemical complexity of Jiawei Fangji Huangqi decoction by integrating ultra‐high‐performance liquid chromatography/ion mobility‐quadrupole time‐of‐flight mass spectrometry and intelligent data processing workflows

“…In total, 134 flavonoids (comprising 31.16% of the total number of compounds) were provisionally identified in the JFH decoction. Flavonoids are known to be one of the main classes of active ingredients in AR [17], GRR [18], PS [19], and DSLS [16]. The negative fragmentation pathways of the flavonoids, regardless of the subclass, involved typical neutral loss (NL) of the sugar moiety to generate a deprotonated aglycone moiety ([A − H] − ); the preferred NL of CO 2 (43.98 Da), CO (27.99 Da), H 2 O (18.01 Da), or CH 2 O (30.01 Da); the radical cleavage of •CH 3 (for compounds containing –OCH 3 ); and retro ‐Diels–Alder (RDA) reactions [20].…”

“…The Waters bioinformatics platform UNIFI efficiently perform data correction, peak extraction, and peak annotation [16]. In this work, the multiple components in the JFH decoction were identified using the intelligent data processing workflows available in the UNIFI software in combination with an in-house chemical library containing the chemical information of 1250 known compounds (Table S3).…”

“…In total, 134 flavonoids (comprising 31.16% of the total number of compounds) were provisionally identified in the JFH decoction. Flavonoids are known to be one of the main classes of active ingredients in AR [17], GRR [18], PS [19], and DSLS [16] ). Accordingly, compound 215# was identified as a formononetin isomer [21].…”