Drug-induced cholestasis is a leading cause of drug withdrawal. However, the use of primary human hepatocytes (PHHs), the gold standard for predicting cholestasis in vitro, is limited by their high cost and batch-to-batch variability. Mature hepatocyte characteristics have been observed in human induced hepatocytes (hiHeps) derived from human fibroblast transdifferentiation. Here, we evaluated whether hiHeps could biosynthesize and excrete bile acids (BAs) and their potential as PHH alternatives for cholestasis investigations. Quantitative real-time PCR (qRT-PCR) and western blotting indicated that hiHeps highly expressed BA synthases and functional transporters. Liquid chromatography tandem mass spectrometry (LC-MS/MS) showed that hiHeps produced normal intercellular unconjugated BAs but fewer conjugated BAs than human hepatocytes. When incubated with representative cholestatic agents, hiHeps exhibited sensitive drug-induced bile salt export pump (BSEP) dysfunction, and their response to cholestatic agent-mediated cytotoxicity correlated well with that of PHHs (r2 = 0.8032). Deoxycholic acid (DCA)-induced hepatotoxicity in hiHeps was verified by elevated aspartate aminotransferase (AST) and γ-glutamyl-transferase (γ-GT) levels. Mitochondrial damage and cell death suggested DCA-induced toxicity in hiHeps, which were attenuated by hepatoprotective drugs, as in PHHs. For the first time, hiHeps were reported to biosynthesize and excrete BAs, which could facilitate predicting cholestatic hepatotoxicity and screening potential therapeutic drugs against cholestasis.

Metabolite profiling plays a crucial role in drug discovery and development, and HPLC-Q-TOF has evolved into a powerful and effective high-resolution analytical tool for metabolite detection. However, traditional empirical identification is laborious and incomplete. This paper presents a systematic and comprehensive strategy for elucidating metabolite structures using software-assisted HPLC-Q-TOF that takes full advantage of data acquisition, data processing, and data mining technologies, especially for high-throughput metabolite screening. This strategy has been successfully applied in the study of magnoflorine metabolism based on our previous report of its poor bioavailability and drug-drug interactions. In this report, 23 metabolites of magnoflorine were tentatively identified with detailed fragmentation pathways in rat biological samples (urine, feces, plasma, and various organs) after i.p. or i.g. administration, and for most of these metabolites, the metabolic sites were determined. The phase I biotransformations of magnoflorine (M1-M7, M10-M14) consist of demethylation, dehydrogenation, hydroxylation, methylene to ketone transformation, N-ring opening, and dehydroxylation. The phase II biotransformations (M8, M9, and M15-M23) consist of methylation, acetylation, glucuronidation, and N-acetylcysteine conjugation. The results indicate that the extensive metabolism and wide tissue distribution of magnoflorine and its metabolites may partly contribute to its poor bioavailability and drug-drug interaction, and i.p. administration should thus be a suitable approach for isolating magnoflorine metabolites. In summary, this strategy could provide an efficient, rapid, and reliable method for the structural characterization of drug metabolites and may be applicable for general Q-TOF users.