UHPLC-HRMS/MS on untargeted metabolomics: a case study with Copaifera (Fabaceae)

Metabolomics-based profiling of five Salvia L. (Lamiaceae) species using untargeted data analysis workflow

INTRODUCTION

The genus Salvia L., a member of the family Lamiaceae, is a keystone genus with a wide range of medicinal properties. It possesses a rich metabolite source that has long been used to treat different disorders.

OBJECTIVES

Due to a deficiency of untargeted metabolomic profiling in the genus Salvia, this work attempts to investigate a comprehensive mass spectral library matching, computational data annotations, exclusive biomarkers, specific chemotypes, intraspecific metabolite profile variation, and metabolite enrichment by a case study of five medicinal species of Salvia.

MATERIAL AND METHODS

Aerial parts of each species were subjected to QTRAP liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis workflow based on untargeted metabolites. A comprehensive and multivariate analysis was acquired on the metabolite dataset utilizing MetaboAnalyst 6.0 and the Global Natural Products Social Molecular Networking (GNPS) Web Platform.

RESULTS

The untargeted approach empowered the identification of 117 metabolites by library matching and 92 nodes annotated by automated matching. A machine learning algorithm as substructural topic modeling, MS2LDA, was further implemented to explore the metabolite substructures, resulting in four Mass2Motifs. The automated library newly discovered a total of 23 metabolites. In addition, 87 verified biomarkers of library matching, 58 biomarkers of GNPS annotations, and 11 specific chemotypes were screened.

CONCLUSION

Integrative spectral library matching and automated annotation by the GNPS platform provide comprehensive metabolite profiling through a workflow. In addition, QTRAP LC-MS/MS with multivariate analysis unveiled reliable information about inter and intraspecific levels of differentiation. The rigorous investigation of metabolite profiling presents a large-scale overview and new insights for chemotaxonomy and pharmaceutical studies.

Exploring quality evaluation markers of Fructus Psoraleae based on chemometric analysis integrated with network pharmacology

INTRODUCTION

Fructus Psoraleae (FP) is a well-known traditional Chinese medicine for the treatment of osteoporosis. However, major quality differences were witnessed owing to its various origins, thus influencing its safety and efficacy.

OBJECTIVES

The study aimed to evaluate the quality of FP from different origins and predict its quality evaluation markers.

METHODS

Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry was employed for tentative characterisation of the constituents in 10 batches of FP, followed by the utilisation of multivariate statistical analysis methods including principal component analysis and orthogonal partial least squares discriminant analysis for quality evaluation. Network pharmacology approaches were utilised to explore the underlying mechanism of the screened chemotaxonomic markers in treating osteoporosis.

RESULTS

Forty-one components in FP including, chalcones, coumarins, coumestans, flavonoids, iso-flavonoids, and phenolics, were characterised based on their fragmentation pathways. Ten batches of FP were basically divided into three categories, and eight chemotaxonomic markers including isopsoralen, calamenene, bakuchiol, psoralen, bavachinin, isoneobavaisoflavone, corylifol C, and neobavaisoflavone were screened. Network pharmacology revealed that the chemotaxonomic markers can act on targets such as AKT1, HSP90AA1, and EGFR and possess effects mainly through glycolysis and wnt/β-catenin signalling to alleviate osteoporosis. Molecular docking and molecular dynamic simulation confirmed the good binding affinity and stability between proteins and selected markers. So, eight chemotaxonomic markers were all preferentially recommended as quality evaluation markers.

CONCLUSION

The study not only provides a reference for the improvement of quality control of FP but also offers a theoretical basis for its further in-depth research in osteoporosis.

Untargeted metabolomics study and identification of potential biomarkers in the six sections of the genus Stachys L. (Lamiaceae) using HPLC-MQ-API-MS/MS

INTRODUCTION

The genus Stachys L., belonging to the family Lamiaceae, is one of the largest genera with remarkable medicinal properties. Plants of this genus produce a broad range of secondary metabolites.

OBJECTIVES

Due to the incomplete comprehensive assessment of chemical profiles in Stachys species, we conducted an untargeted metabolomics study and identified potential biomarkers in the six sections of Stachys with chemotaxonomic importance.

MATERIAL AND METHODS

Dried leaves of 17 taxa were utilized for analysis of all the constituents using HPLC-MQ-API-MS. The obtained data were processed and analyzed using multivariate statistical methods, including heatmaps, PLS-DA score plots, functional analysis of metabolic pathways, metabolite set enrichment analysis, and biomarker and network analysis.

RESULTS

Among the 129 metabolites, 111 flavonoids and 18 non-flavonoids were recognized. The most represented flavonoids, including 41 flavones and 20 flavonols, displayed remarkable abundance. In non-flavonoid compounds, a total of six coumarins and six phenolic acids were present at high levels. In terms of approved markers in six sections, 76 chemical compounds, mainly flavonoids, coumarins, quinic acids, and cinnamic acids, were identified as potential biomarkers or chemotaxonomic indicators. Accordingly, the taxonomic complexities of some Stachys species in sections Fragilicaulis, Aucheriana, and Setifolia were properly resolved.

CONCLUSION

An HPLC-MS/MS-based metabolomics approach integrated with multivariate statistical methods was employed to identify (1) valuable markers and analyze metabolic diversity and (2) predict the pharmaceutical properties of Stachys species. The obtained chemical profiles provide a new perspective for investigation of the Stachys genus.

Margaritaria nobilis L.F. (Phyllanthaceae): Ethnopharmacology and Application of Computational Tools in the Annotation of Bioactive Molecules

Margaritaria nobilis is a shrubby species widely distributed in Brazil from the Amazon to the Atlantic Rainforest. Its bark and fruit are used in the Peruvian Amazon for disinfecting abscesses and as a tonic in pregnancy, respectively, and its leaves are used to treat cancer symptoms. From analyses via UHPLC-MS/MS, we sought to determine the chemical profile of the ethanolic extract of M. nobilis leaves by means of putative analyses supported by computational tools and spectral libraries. Thus, it was possible to annotate 44 compounds, of which 12 are phenolic acid derivatives, 16 are O-glycosylated flavonoids and 16 hydrolysable tannins. Among the flavonoids, although they are known, except for kaempferol, which has already been isolated from this species, the other flavonoids (10, 14, 15, 21, 24–26, 28–30, 33–35, 40 and 41) are being reported for the first time in the genus. Among the hydrolysable tannins, six ellagitannins present the HHDP group (6, 19, 22, 31, 38 and 43), one presents the DHHDP group (5), and four contain oxidatively modified congeners (12, 20, 37 and 39). Through the annotation of these compounds, we hope to contribute to the improved chemosystematics knowledge of the genus. Furthermore, supported by a metric review of the literature, we observed that many of the compounds reported here are congeners of authentically bioactive compounds. Thus, we believe that this work may help in understanding future pharmacological activities.

Chemical variability of Copaifera langsdorffii Desf. from environmentally contrasting populations

Copaifera langsdorffii Desf. is recognised as one of most famous medicinal and economic species of Copaiba, occurring in several distinct biomes. An untargeted metabolomic approach was used to evaluate the chemical variability of C. langsdorffii from contrasting climates biomes (Atlantic Rainflorest and the semiarid Cerrado). Metabolomic analysis enabled the identification of 11 compounds, including glycosylated flavonoids and galloylquinic acid derivatives. Multivariate analysis highlighted that Cerrado population had a significantly higher concentrations of galloylquinic acid derivatives in comparison to the rainforest biome. Meanwhile, Atlantic Rainforest populations presented higher content of flavonols. Semiarid biome, reduced the concentration of flavonoids, mainly concerning quercetin and kaempferol derivatives, however, in this biome flavonoids were more diverse. Both chemical classes presented relevance to be used as geographical origin chemical markers by qualitative and quantitative features.