A four-dimensional separation approach by offline 2D-LC/IM-TOF-MS in combination with database-driven computational peak annotation facilitating the in-depth characterization of the multicomponents from Atractylodis Macrocephalae Rhizoma (Atractylodes macrocephala)

Plant metabolites represent complex chemical system, which renders it difficult to clarify the chemical composition by conventional liquid chromatography/mass spectrometry (LC/MS) due to the limited selectivity and peak capacity. The rhizomes of Atractylodes macrocephala have been utilized as a traditional Chinese medicine Atractylodis Macrocephalae Rhizoma (Bai-Zhu), and have been reported containing multiple categories of plant metabolites. Targeting the multicomponents from A. macrocephala , an integral approach by offline two-dimensional liquid chromatography/ion mobility quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS) was established and validated. By configuring an XBridge Amide column of Hydrophilic Interaction Chromatography and an Atlantis Premier BEH C18AX column of mixed ion exchange and reversed-phase modes, the established 2D-LC/IM-QTOF-MS system showed high orthogonality up to 0.91. Dimension-enhanced, data-independent high-definition MS E (HDMS E ) in the positive ESI mode was conducted on a Vion IM-QTOF mass spectrometer, and its hyphenation to offline 2D-LC could enable the four-dimensional separation (each dimension in 2D-LC, IM, and MS). Particularly, HDMS E facilitated the acquisition of high-definition MS 1 and MS 2 spectra. In-house library-driven computational peak annotation by the bioinformatics platform UNIFI could efficiently process and annotate the HDMS E data for the structural elucidation. By integrating reference compounds comparison, we could identify or tentatively characterize 251 components from A. macrocephala (including 115 sesquiterpenoids, 90 polyacetylenes, 11 flavonoids, 9 benzoquinones, 12 coumarins, and 14 others), which indicated large improvement in identifying those minor plant components, compared with the conventional LC/MS approach. Conclusively, offline 2D-LC/IM-QTOF-HDMS E in combination with computational data interpretation proves to be powerful facilitating the in-depth multicomponent characterization of herbal medicine.