Using Porcine Jejunum Ex Vivo to Study Absorption and Biotransformation of Natural Products in Plant Extracts: Pueraria lobata as a Case Study.
Joelle HourietYvonne E ArnoldLéonie PellissierYogeshvar N KaliaJean-Luc WolfenderPublished in: Metabolites (2021)
Herbal preparations (HPs) used in folk medicine are complex mixtures of natural products (NPs). Their efficacy in vivo after ingestion depends on the uptake of the active ingredient, and, in some cases, their metabolites, in the gastrointestinal tract. Thus, correlating bioactivities measured in vitro and efficacy in vivo is a challenge. An extract of Pueraria lobata rich in different types of isoflavones was used to evaluate the capacity of viable porcine small intestine ex vivo to elucidate the absorption of HP constituents, and, in some cases, their metabolites. The identification and transport of permeants across the jejunum was monitored by liquid chromatography-mass spectrometry (LC-MS), combining targeted and untargeted metabolite profiling approaches. It was observed that the C-glycoside isoflavones were stable and crossed the intestinal membrane, while various O-glycoside isoflavones were metabolized into their corresponding aglycones, which were then absorbed. These results are consistent with human data, highlighting the potential of using this approach. A thorough investigation of the impact of absorption and biotransformation was obtained without in vivo studies. The combination of qualitative untargeted and quantitative targeted LC-MS methods effectively monitored a large number of NPs and their metabolites, which is essential for research on HPs.
Keyphrases
- liquid chromatography
- mass spectrometry
- high resolution mass spectrometry
- ms ms
- tandem mass spectrometry
- gas chromatography
- high resolution
- endothelial cells
- high performance liquid chromatography
- cancer therapy
- capillary electrophoresis
- simultaneous determination
- electronic health record
- solid phase extraction
- systematic review
- big data
- risk assessment
- oxide nanoparticles
- climate change
- artificial intelligence
- human health
- machine learning
- anti inflammatory
- bioinformatics analysis