Differentiation of Ficus deltoidea varieties and chemical marker determination by UHPLC-TOFMS metabolomics for establishing quality control criteria of this popular Malaysian medicinal herb

Afzan, Adlin; Kasim, Nawal; Ismail, Nor Hadiani; Azmi, Norfaizura; Ali, Abdul Manaf; Mat, Nashriyah; Wolfender, Jean‐Luc

doi:10.1007/s11306-019-1489-2

Cited by 24 publications

(22 citation statements)

References 22 publications

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“…Because of the particularly high performances in both mass spectrometry (MS) and tandem MS (MS/MS) modes, the combination of ultra-performance liquid chromatography (UPLC) separation and quadrupole time-of-flight mass spectrometry (QTOF-MS) detection has shown absolute superiority in qualitative and quantitative compound analysis (Taamalli et al, 2014;Wolfender et al, 2008;Da Silva et al, 2017). Coupled with multivariate statistical methods, UPLC-QTOF-MS is an optimized compound characterization approach that has been used to analyze ginseng, Ficus deltoidea, Garcinia oblongifolia, and many traditional Chinese medicinal herbs (Zhu et al, 2019;Afzan et al, 2019;Ning et al, 2013;Yu et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Chemotype classification and biomarker screening of male Eucommia ulmoides Oliv. flower core collections using UPLC-QTOF/MS-based non-targeted metabolomics

Liu

Wang

et al. 2020

PeerJ

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Background In the Chinese health care industry, male Eucommia ulmoides Oliv. flowers are newly approved as a raw material of functional food. Core collections have been constructed from conserved germplasm resources based on phenotypic traits and molecular markers. However, little is known about these collections’ phytochemical properties. This study explored the chemical composition of male E. ulmoides flowers, in order to provide guidance in the quality control, sustainable cultivation, and directional breeding of this tree species. Methods We assessed the male flowers from 22 core collections using ultra-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) non-targeted metabolomics, and analyzed them using multivariate statistical methods including principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS-DA). Results We annotated a total of 451 and 325 metabolites in ESI+ and ESI− modes, respectively, by aligning the mass fragments of the secondary mass spectra with those in the database. Four chemotypes were well established using the ESI+ metabolomics data. Of the 29 screened biomarkers, 21, 6, 19, and 5 markers corresponded to chemotypes I, II, III, and IV, respectively. More than half of the markers belonged to flavonoid and amino acid derivative classes. Conclusion Non-targeted metabolomics is a suitable approach to the chemotype classification and biomarker screening of male E. ulmoides flower core collections. We first evaluated the metabolite profiles and compositional variations of male E. ulmoides flowers in representative core collections before establishing possible chemotypes and significant biomarkers denoting the variations. We used genetic variations to infer the metabolite compositional variations of male E. ulmoides flower core collections instead of using the geographical origins of the germplasm resources. The newly proposed biomarkers sufficiently classified the chemotypes to be applied for germplasm resource evaluation.

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Section: Introductionmentioning

confidence: 99%

Chemotype classification and biomarker screening of male Eucommia ulmoides Oliv. flower core collections using UPLC-QTOF/MS-based non-targeted metabolomics

Liu

Wang

et al. 2020

PeerJ

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“…The technique is also able to assess bioavailability, metabolism, safety and toxicity of herbal medicines in human body [13]. The combination of NMR- or MS- based metabolomics with supervised multivariate data analysis methods has been successfully applied in NPs research: For example, OPLS-DA has been used to identify discriminant markers in the 1 H-NMR and UHPLC-MS metabolic profiles of the closely related species Pelargonium sidoides and P. reniforme [18]; partial least squares discriminant analysis (PLS-DA) of UHPLC-TOF-MS data has been applied for the identification of chemical quality markers for different Ficus deltoidea varieties [19]. Correlating bioactivity data with metabolomic data has been successfully used to predict bioactive plant constituents which contribute to the activity of herbal extracts: For example, PLS-DA was used to predict the bioactive principles from 1 H-NMR metabolomic data of Galphimia glauca accessions with distinct in vivo sedative and anxiolytic activities [20]; recently, compounds with anti-biofilm activity were identified by correlating the LC-MS profiles of six marine Streptomyces strains with bioactivity data by means of PLS-DA [21].…”

Section: Introductionmentioning

confidence: 99%

Identification of Constituents Affecting the Secretion of Pro-Inflammatory Cytokines in LPS-Induced U937 Cells by UHPLC-HRMS-Based Metabolic Profiling of the Traditional Chinese Medicine Formulation Huangqi Jianzhong Tang

et al. 2019

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Within non-communicable diseases, chronic inflammatory conditions represent one of the biggest challenges for modern medicine. Traditional Chinese Medicine (TCM) has been practiced over centuries and has accumulated tremendous empirical knowledge on the treatment of such diseases. Huangqi Jianzhong Tang (HQJZT) is a famous TCM herbal formula composed of Radix Astragali, Ramulus Cinnamomi, Radix et Rhizoma Glycyrrhizae Praeparata cum Melle, Radix Paeoniae Alba, Rhizoma Zingiberis Recens, Fructus Jujubae and Saccharum Granorum (maltose), which has been used for the treatment of various chronic inflammatory gastrointestinal diseases. However, there is insufficient knowledge about its active constituents and the mechanisms responsible for its effects. The present study aimed at identifying constituents contributing to the bioactivity of HQJZT by combining in vitro cytokine production assays and LC-MS metabolomics techniques. From the HQJZT decoction as well as from its single herbal components, extracts of different polarities were prepared. Phytochemical composition of the extracts was analyzed by means of UPLC-QTOF-MS/MS. The inhibitory effects of the extracts on TNF-α, IL-1β and IFN-γ production were studied in U937 cells. Phytochemical and pharmacological bioactivity data were correlated by orthogonal projection to latent structures discriminant analysis (OPLS-DA) in order to identify those HQJZT constituents which may be relevant for the observed pharmacological activities. The investigations resulted in the identification of 16 HQJZT constituents, which are likely to contribute to the activities observed in U937 cells. Seven of them, namely calycosin, formononetin, astragaloside I, liquiritigenin, 18β-glycyrrhetinic acid, paeoniflorin and albiflorin were unambiguously identified. The predicted results were verified by testing these compounds in the same pharmacological assays as for the extracts. In conclusion, the anti-inflammatory activity of HQJZT could be substantiated by in vitro pharmacological screening, and the predicted activities of the OPLS-DA hits could be partially verified. Moreover, the benefits and limitations of MVDA for prediction pharmacologically active compounds contributing to the activity of a TCM mixture could be detected.

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“…Rhoifolin is the most widespread of the studied metabolites. It has been identied in barley, wheat, soybeans, Ficus, and B. distachyon, which is phylogenetically close to barley and wheat (Afzan et al (2019), Piasecka et al (2017), Onda et al (2015), Sawada et al (2016)). Preclinical studies have shown that rhoifolin possesses a variety of signicant biological activities in- cluding antioxidant, anti-inammatory, antimicrobial, hepatoprotective and anticancer eects; see Refaat et al (2018).…”

Section: Methodsmentioning

confidence: 99%

Meta-analysis of flavonoids with antiviral potential against coronavirus

Sawikowska

2020

Biometrical Letters

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SummaryPreliminary studies which may be of significance for research against coronaviruses, including SARS-CoV-2, which has caused an epidemic in China, are presented. An analysis was made of publicly available data that contain information about important metabolites neutralizing coronaviruses. Preliminary studies show that especially Ficus, barley, thistle and sundew should be additionally tested with the aim of producing medicines for coronavirus.

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Differentiation of Ficus deltoidea varieties and chemical marker determination by UHPLC-TOFMS metabolomics for establishing quality control criteria of this popular Malaysian medicinal herb

Cited by 24 publications

References 22 publications

Chemotype classification and biomarker screening of male Eucommia ulmoides Oliv. flower core collections using UPLC-QTOF/MS-based non-targeted metabolomics

Chemotype classification and biomarker screening of male Eucommia ulmoides Oliv. flower core collections using UPLC-QTOF/MS-based non-targeted metabolomics

Identification of Constituents Affecting the Secretion of Pro-Inflammatory Cytokines in LPS-Induced U937 Cells by UHPLC-HRMS-Based Metabolic Profiling of the Traditional Chinese Medicine Formulation Huangqi Jianzhong Tang

Meta-analysis of flavonoids with antiviral potential against coronavirus

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