Nan Cui

Identification of a novel intestinal first pass metabolic pathway: NQO1 mediated quinone reduction and subsequent glucuronidation.

Quinones represent a very important class of compounds found in nature and for the chemically synthesized drugs. The present study was designed to elucidate the intestinal first pass metabolic pathways in vivo and in vitro, of tanshinone IIA (TS), a derivative of phenanthrene-quinone isolated from Salvia miltiorrhiza. Five metabolites, proposed to be TS catechol glucuronides (two position isomers), dehydrotanshinone IIA and its two catechol glucuronides, were identified from the rat intestinal homogenates after oral administration of TS. TS metabolism was further conducted in the subcellular system including cytosol, microsomes, mitochondrial and S9 under both phase I and phase II metabolic conditions. TS underwent negligible metabolism in all of the subcellular systems under phase I metabolic condition using NADPH as the cofactor. However, significant and substantial metabolic elimination of TS was observed in the cytosol and S9 fractions, while not in the microsomes fractions, when both NADPH and UDPGA were added. Two TS catechol glucuronides were identified from such an in vitro metabolic medium. Dicoumarol, a specific inhibitor of the NAD(P)H dependent quinone oxidoreductase (NQO1), significantly inhibited the metabolic elimination of TS in a noncompetitive way, suggesting that NQO1 was responsible for the quinone reduction of TS to form the catechol intermediate. The catechol intermediate failed to be detected directly was proved to be highly unstable and autoxidized back to TS accompanied with hydrogen peroxide generation. Dicoumarol exhibited a significant inhibitory effect on the hydrogen peroxide generation, further supporting that the reduction of TS was catalyzed by NQO1. The absolute bioavailability of TS was significantly enhanced by oral dicoumarol pretreatment. In conclusion, a novel intestinal metabolic pathway for quinones, NQO1 mediated reduction and subsequent glucuronidation, was determined using TS as a model compound. This study should be helpful for the general understanding of quinones absorption and intestinal first pass metabolism.

Chemicalome and Metabolome Matching Approach to Elucidating Biological Metabolic Networks of Complex Mixtures

Global metabolite identification of complex compound mixtures in biological systems is a very challenging task. Herein, we developed and validated a chemicalome to metabolome matching approach by taking herbal medicine as an example to delineate the metabolic networks of complex systems. This approach consists of five steps of data processing including raw data output, endogenous background subtraction, parent compound and metabolite differentiation, chemicalome to metabolome correlation, and the final validation via manual fragment comparison. Chemicalome to metabolome correlation, the core step of this approach, was performed based on matching the accurate mass differences of pseudomolecular ions between them with the accurate mass changes of known metabolic pathways and validating the matches by validation ions. A step-forward approach that confers a gradual identification of metabolites generated from different steps (1-4) and types (degradation, phase I/II, or mixed) of metabolic reactions was further proposed for chemicalome to metabolome matching. This approach was validated to be very useful and powerful for the metabolite identification of a single compound, a homologous compound mixture, and a complex herbal system. Using this approach, all metabolites (162) detected from urine samples of rats treated with Mai-Luo-Ning injection could be linked to their respective parent compounds, and 143 of them were supported by the final validation via manual fragment analysis. In most cases, more than 80% of the automatic matching results could be supported by the manual fragment validations. A complex metabolic network showing all the possible links between precursors and metabolites was successfully constructed. This study provides a generally applicable approach to global metabolite identification of complex compound mixtures in complex matrixes.