An enhanced strategy integrating offline two-dimensional separation with data independent acquisition mode and deconvolution: Characterization of metabolites of Uncaria rhynchophylla in rat plasma as a case.

The importance to clarify the drug metabolites is beyond doubt in view of their potential efficacy and safety. However, due to the complex matrix interference, relatively low content and the co-eluting effect, it is of a great challenge to comprehensively and systematically characterize the metabolites in vivo, especially for the traditional Chinese medicines (TCMs) due to the numerous types of components. In the present study, a comprehensive off-line two-dimensional separation system combining with data independent acquisition (DIA) mode and multi-dimensional data deconvolution method was established for chromatographic separation, data acquisition and data procession of indole alkaloids in rat plasma after intragastrically administrated with the extract of Uncaria rhynchophylla at the dose of 1 g/kg. The orthogonality of the off-line 2D separation system consisting of HILIC for first-dimensional separation and the PRLC for second-dimensional separation was valuated with the "asterisk" equations, and the results showed that off-line 2D separation system had passable orthogonality (A = 53.3%). Furthermore, the DIA mode was applied to capture MS/MS spectra in view of its advantage in acquiring MS data, and an effective multi-dimensional deconvolution method integrating the calculation of chemical formula, the extraction of diagnostic ion, the filter of ring double bond (RDB) and the judgement of neutral loss was established to parse the spectra for the complicated DIA data for comprehensive analysis of metabolites in rat plasma. Ultimately, a total of 127 indole alkaloids were tentatively characterized, and the main metabolic pathways were inferred as demethylation, dehydrogenation, hydroxylation and deglycosylation. The off-line two-dimensional separation system was applied for the comprehensive characterization of metabolites in vivo for the first time. This study suggested a new approach to enable the enrichment, separation and analysis of the low content components in vivo.