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Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis

BACKGROUNDS: Gentiana rhodantha, a rich source of iridoids and polyphenols, is a traditional ethnomedicine widely used in China. Metabolic fingerprinting based on a LC-UV-MS/MS method was applied to explore the chemical markers for discrimination of G. rhodantha from different geographical origins....

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Autores principales: Pan, Yu, Zhang, Ji, Shen, Tao, Zhao, Yan-Li, Wang, Yuan-Zhong, Li, Wan-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390080/
https://www.ncbi.nlm.nih.gov/pubmed/25880482
http://dx.doi.org/10.1186/s12858-015-0038-5
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author Pan, Yu
Zhang, Ji
Shen, Tao
Zhao, Yan-Li
Wang, Yuan-Zhong
Li, Wan-Yi
author_facet Pan, Yu
Zhang, Ji
Shen, Tao
Zhao, Yan-Li
Wang, Yuan-Zhong
Li, Wan-Yi
author_sort Pan, Yu
collection PubMed
description BACKGROUNDS: Gentiana rhodantha, a rich source of iridoids and polyphenols, is a traditional ethnomedicine widely used in China. Metabolic fingerprinting based on a LC-UV-MS/MS method was applied to explore the chemical markers for discrimination of G. rhodantha from different geographical origins. RESULTS: Targeted compounds were separated on a Shim-pack XR-ODS III (150 × 2.0 mm, 2.2 μm), with a mobile phase consisted of acetonitrile and 0.1% formic acid in water, under gradient elution. In quantitative analysis, all of the calibration curves showed good linear regression (R(2) < less than 0.9991) within the tested ranges, and accuracy ranged from 97.8% to 104.2% and the %RSD of precision (less than 3%) were all within the required limits. The most abundant mangiferin (82.21 mg/g) found in sample from Zunyi, Guizhou province. Furthermore, 64 samples according to their geographical origins, could be classified by partial least-squares discriminate analysis (PLS-DA) and nine compounds including two new compounds identified by mass spectrometry could be regarded as characteristic compounds for discriminating samples from different geographical origins. CONCLUSIONS: The developed method appears to be a useful tool for analysis of G. rhodantha, which could provide potential indicators for differentiation of different geographical origins. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12858-015-0038-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-43900802015-04-09 Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis Pan, Yu Zhang, Ji Shen, Tao Zhao, Yan-Li Wang, Yuan-Zhong Li, Wan-Yi BMC Biochem Methodology Article BACKGROUNDS: Gentiana rhodantha, a rich source of iridoids and polyphenols, is a traditional ethnomedicine widely used in China. Metabolic fingerprinting based on a LC-UV-MS/MS method was applied to explore the chemical markers for discrimination of G. rhodantha from different geographical origins. RESULTS: Targeted compounds were separated on a Shim-pack XR-ODS III (150 × 2.0 mm, 2.2 μm), with a mobile phase consisted of acetonitrile and 0.1% formic acid in water, under gradient elution. In quantitative analysis, all of the calibration curves showed good linear regression (R(2) < less than 0.9991) within the tested ranges, and accuracy ranged from 97.8% to 104.2% and the %RSD of precision (less than 3%) were all within the required limits. The most abundant mangiferin (82.21 mg/g) found in sample from Zunyi, Guizhou province. Furthermore, 64 samples according to their geographical origins, could be classified by partial least-squares discriminate analysis (PLS-DA) and nine compounds including two new compounds identified by mass spectrometry could be regarded as characteristic compounds for discriminating samples from different geographical origins. CONCLUSIONS: The developed method appears to be a useful tool for analysis of G. rhodantha, which could provide potential indicators for differentiation of different geographical origins. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12858-015-0038-5) contains supplementary material, which is available to authorized users. BioMed Central 2015-03-28 /pmc/articles/PMC4390080/ /pubmed/25880482 http://dx.doi.org/10.1186/s12858-015-0038-5 Text en © Pan et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Pan, Yu
Zhang, Ji
Shen, Tao
Zhao, Yan-Li
Wang, Yuan-Zhong
Li, Wan-Yi
Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis
title Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis
title_full Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis
title_fullStr Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis
title_full_unstemmed Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis
title_short Comparative metabolic fingerprinting of Gentiana rhodantha from different geographical origins using LC-UV-MS/MS and multivariate statistical analysis
title_sort comparative metabolic fingerprinting of gentiana rhodantha from different geographical origins using lc-uv-ms/ms and multivariate statistical analysis
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390080/
https://www.ncbi.nlm.nih.gov/pubmed/25880482
http://dx.doi.org/10.1186/s12858-015-0038-5
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