Gas chromatography–mass spectrometry based metabolic profiling for the identification of discrimination markers of Angelicae Radix and its application to gas chromatography–flame ionization detector system

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Gas chromatography (GC)-based metabolomics technologies were applied for quality control of Angelicae Radix, an herbal medicine commonly used in Japan and China. Since Angelica roots are priced and graded differently based on their species and cultivation area, there is a need for a simple and reproducible method to discriminate Angelica roots. Here, we used GC–MS profiling data to construct a discrimination method for species and cultivation area of A. Radix. Seventy-six primary metabolites were identified. The quality factors of A. Radix were successfully classified using metabolic profiling and the orthogonal projections to latent structures-discriminant analysis (OPLS-DA) technique. Sorbitol and a glucose/4-aminobutyric acid combination were chosen as bio-markers from S-plot of OPLS-DA. Application of these selected bio-markers to a more practical and cost-efficient system, namely gas chromatography–flame ionization detector (GC–FID) system were also assessed. As a result, the same separations of sorbitol, glucose and 4-aminobutyric acid in box plots were obtained from GC–FID data. Our results demonstrate that GC-based metabolic markers can be readily applied for the establishment of a practical quality control method for A. Radix.

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Samples

All the samples of A. Radix were provided from Tochimoto Tenkaido Co. Ltd. (Osaka, Japan). Species identifications of the samples were performed by description of a crude drug and microscopic identification by trained specialists prior to analysis of this study. Sample details are shown in Table 1. Nara, Hokkaido and Gansu are known as main cultivation areas of A. acutiloba, A. acutiloba Kitagawa var. sugiyamae Hikino (1) and A. sinensis (19), respectively. The specimens were first sliced or

GC–MS analysis

GC–MS was used to identify and quantify low-molecular-weight hydrophilic compounds in A. Radix samples. After performing data processing and peak determination as described in Materials and Methods, we were able to identify seventy-six compounds in these samples (Table S1). The total number of identified compounds was much higher than 22 metabolites in our previous study (14), mostly due to the operation of AI output, a newly developed GC–MS peak annotation system (20).

Principal component analysis

Principal component

Acknowledgments

We would like to thank T. Mae of Maechu Co. Ltd. (Nara, Japan) and S. Sakamoto of Sakamotoshige shop for the sample information.

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