An integrated approach for global profiling of multi-type constituents: Comprehensive chemical characterization of Lonicerae Japonicae Flos as a case study

Pan, Huiqin; Zhou, Heng; Shui, Miao; Cao, Jiayin; Liu, Jiaming; Lan, Lan; Hu, Qing; Mao, Xiuhong; Shen, Ji

doi:10.1016/j.chroma.2019.460674

Cited by 43 publications

(18 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Eventually, a total of 727 special nodes were identified, which were represented as arrow-shaped nodes, and 46 metabolites were successfully identified by their Rt, accurate molecular weight, and MS/MS spectra. The reason for the results was that the parameters of the ion source would be affected by the coexistence of multiple components theoretically, which may influence the MS response and trigger the fragmentation of secondary components [20]. Interestingly, the molecular network contained a large number of proanthocyanidins and some unreported alkaloids.…”

Section: The Annotation Of Metabolites By Fbmnmentioning

confidence: 99%

Comprehensive feature‐based molecular networking and metabolomics approaches to reveal the differences components in Cinnamomum cassia and Cinnamomum verum

Long

et al. 2021

J of Separation Science

View full text Add to dashboard Cite

Cinnamon was been a widely used plant in medicinal and spices for a long time and has spread all over the world. However, the differences in the components of the bark from Cinnamomum cassia and Cinnamomum verum, the two most common types of cinnamon, have not been thoroughly investigated. In the present experiment, ultra-high-performance liquid chromatography LTQ-Orbitrap Velos Pro hybrid mass spectrometer-based metabolomics coupled with chemometrics and feature-based molecular networking were employed to dramatically distinguish and annotate Cinnamomum cassia Bark and Cinnamomum verum bark. As a consequence, principal component analysis, orthogonal projection to latent structures discriminates analysis, and heat map analysis demonstrated clear discrimination between the profiles of metabolites in cinnamon. Besides, as the known compounds, proanthocyanidins (cinnamtannin B1 and procyanidin B2) and alkaloids (norboldine, norisoboldine) with variable importance in the projection scores >6, and an unknown alkaloid (formula C 24 H 33 NO 6 ) were selected as the best markers to discriminate cinnamon. Furthermore, large numbers of proanthocyanidins and alkaloids components were identified through featurebased molecular networking for the first time. Our investigation provides new ideas for the discovery of quality markers and identification of unknown components in natural products.

show abstract

Section: The Annotation Of Metabolites By Fbmnmentioning

confidence: 99%

Comprehensive feature‐based molecular networking and metabolomics approaches to reveal the differences components in Cinnamomum cassia and Cinnamomum verum

Long

et al. 2021

J of Separation Science

View full text Add to dashboard Cite

show abstract

“…To our knowledge, this study is the first to explore the potentialities of FBMN for documenting the detailed composition of a TCM multiherb formula. Molecular networking was previously successfully used to annotate components of interest in single TCM herb extracts (Pan et al, 2019;Wang et al, 2019;Wang et al, 2020b).…”

Section: Feature-based Molecular Network For Multi-herb Formulae Compmentioning

confidence: 99%

“…Furthermore, organizing HRMS/MS data by molecular networking (MN) brought a novel dimension to metabolite annotation (Wang et al, 2016a). As a way of classifying structurally related chemicals, MN is seen as a tool of interest for TCMs chemical investigation (Hou et al, 2019) and has recently begun to be employed in TCM research to annotate single herb extracts (Pan et al, 2019;Wang et al, 2019;Wang et al, 2020b). Data processing step by open-source software, such as MZmine (Pluskal et al, 2010) prior to MN has enabled the generation of so-called feature-based molecular networks (FBMN) (Nothias et al, 2020) (Table 1).…”

Section: Introductionmentioning

confidence: 99%

A Mass Spectrometry Based Metabolite Profiling Workflow for Selecting Abundant Specific Markers and Their Structurally Related Multi-Component Signatures in Traditional Chinese Medicine Multi‐Herb Formulae

et al. 2020

View full text Add to dashboard Cite

In Traditional Chinese Medicine (TCM), herbal preparations often consist of a mixture of herbs. Their quality control is challenging because every single herb contains hundreds of components (secondary metabolites). A typical 10 herb TCM formula was selected to develop an innovative strategy for its comprehensive chemical characterization and to study the specific contribution of each herb to the formula in an exploratory manner. Metabolite profiling of the TCM formula and the extract of each single herb were acquired with liquid chromatography coupled to high-resolution mass spectrometry for qualitative analyses, and to evaporative light scattering detection (ELSD) for semi-quantitative evaluation. The acquired data were organized as a feature-based molecular network (FBMN) which provided a comprehensive view of all types of secondary metabolites and their occurrence in the formula and all single herbs. These features were annotated by combining MS/MS-based in silico spectral match, manual evaluation of the structural consistency in the FBMN clusters, and taxonomy information. ELSD detection was used as a filter to select the most abundant features. At least one marker per herb was highlighted based on its specificity and abundance. A single large-scale fractionation from the enriched formula enabled the isolation and formal identification of most of them. The obtained markers allowed an improved annotation of associated features by manually propagating this information through the FBMN. These data were incorporated in the high-resolution metabolite profiling of the formula, which highlighted specific series of related components to each individual herb markers. These series of components, named multi-component signatures, may serve to improve the traceability of each herb in the formula. Altogether, the strategy provided highly informative compositional data of the TCM formula and detailed visualizations of the contribution of each herb by FBMN, filtered feature maps, and reconstituted chromatogram traces of all components linked to each specific marker. This comprehensive MS-based analytical workflow allowed a generic and unbiased selection of specific and abundant markers and the identification of multiple related sub-markers. This exploratory approach could serve as a starting point to develop more simple and targeted quality control methods with adapted marker specificity selection criteria to given TCM formula.

show abstract

“…In a previous study [16], a predicted metabolites screening method was developed to accomplish the screening of the ginsenosides based on the UNIFI platform, which displayed the advantages for mono‐type components. Global Natural Products Social (GNPS, http://gnps.edu) molecular networking (MN) was proved a powerful tool for MS data processing according to the MS/MS spectral similarity [17, 18]. This approach groups sets of spectra from related molecules even when the spectra themselves are not identified.…”

Section: Introductionmentioning

confidence: 99%

Systematic characterization of chemical constituents in Mahuang decoction by UHPLC tandem linear ion trap‐Orbitrap mass spectrometry coupled with feature‐based molecular networking

Ling

Yao

et al. 2021

J of Separation Science

View full text Add to dashboard Cite

Comprehensive characterization of traditional Chinese medicine prescriptions has long been a hurdle due to the chemical complexity and the lack of analytical tools. Mahuang decoction is a well-known traditional Chinese medicine prescription widely used for sweating and relieving the exterior, relieving cough and asthma, but it was insufficiently chemically scrutinized. In this study, the chemical component information of Mahuang decoction was investigated by ultrahigh-performance liquid chromatography tandem linear ion trap-Orbitrap mass spectrometry. A new data processing tool, feature-based molecular networking, was introduced for grouping and elucidating the compounds. In this way, 156 chemical components were identified or tentatively characterized, including alkaloids, triterpenoid saponins, flavanone-O-glycosides, flavone-Cglycosides, and procyanidins. Thus, this research provides a solid foundation for further development of Mahuang decoction, and the adopted method is expected to be applied to other traditional Chinese medicine prescriptions.

show abstract

An integrated approach for global profiling of multi-type constituents: Comprehensive chemical characterization of Lonicerae Japonicae Flos as a case study

Cited by 43 publications

References 34 publications

Comprehensive feature‐based molecular networking and metabolomics approaches to reveal the differences components in Cinnamomum cassia and Cinnamomum verum

Comprehensive feature‐based molecular networking and metabolomics approaches to reveal the differences components in Cinnamomum cassia and Cinnamomum verum

A Mass Spectrometry Based Metabolite Profiling Workflow for Selecting Abundant Specific Markers and Their Structurally Related Multi-Component Signatures in Traditional Chinese Medicine Multi‐Herb Formulae

Systematic characterization of chemical constituents in Mahuang decoction by UHPLC tandem linear ion trap‐Orbitrap mass spectrometry coupled with feature‐based molecular networking

Contact Info

Product

Resources

About