Profiling of the charged metabolites of traditional herbal medicines using capillary electrophoresis time-of-flight mass spectrometry |
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Authors: | Keiko Iino Masahiro Sugimoto Tomoyoshi Soga and Masaru Tomita |
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Institution: | (1) Institute for Advanced Biosciences, Keio University, Tsuruoka Yamagata, 997-0052, Japan;(2) Department of Environment and Information Studies, Keio University, Fujisawa Kanagawa, 252-8520, Japan;(3) Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa Kanagawa, 252-8520, Japan; |
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Abstract: | The quantification of a small number of bioactive components in herbal medicines is often inadequate when attempting to elucidate
a medicine’s biological effects. Despite rapid advances in analytical technologies, obtaining comprehensive metabolomic profiles
of herbal medicines remains difficult, due to the complexity of natural product mixtures. Toki-Shakuyaku-San is a Chinese medicine used widely to treat gynecological and obstetric disorders, such as infertility, dysmenorrhea, toxemia
during pregnancy and neural dysfunction. It consists of Angelica acutiloba Radix (Toki), Cnidium officinale Rhizoma (Senkyu), Paeonia lactiflora Radix (Shakuyaku), Atractylodes lancea Rhizoma (Sojutsu), Alisma orientale Rhizoma (Takusha) and Poria cocos Hoelen (Bukuryo). To elucidate the composition of these herbal medicines individually, we conducted non-targeted profiling analyses
of extracts of these herbs using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), which allows the simultaneous
quantification of hundreds of charged metabolites. In total, 737 ± 183.1 (average ± SD) metabolite-derived features were observed,
and of these, 119 metabolites were identified. Score plots of principal component analysis (PCA) showed a clear cluster including
Shakuyaku, Bukuryo, and Sojutsu, while the other three herbs were distributed over PCA spaces. Loading plots revealed that
amino acids and shikimate-derived alkaloids were the predominant metabolite constituents. Hierarchical clustering analysis
revealed that few clusters overlapped in the herbal medicines tested. This report is the first demonstration of the characterization
of a herbal medicine using large-scale metabolomic analysis, which is complementary to traditional quality control methods. |
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