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

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.

Lipidomes of Icelandic bryophytes and screening of high contents of polyunsaturated fatty acids by using lipidomics approach

Bryophytes (mosses, liverworts, and hornworts) have interested researchers because of their high chemical diversity and their potential uses in pharmaceutical, food, and cosmetic industries. Specifically, long-chain polyunsaturated fatty acids (l-PUFA) such as arachidonic acid (AA) and eicosapentaenoic acid (EPA) are commonly found in bryophytes, but not in vascular plants. Bryophytes accumulate PUFAs in cold or even freezing temperature to keep the cell fluidity. Iceland has a long history of bryophyte vegetation. These bryophytes are highly adapted to the harsh environment in Iceland and therefore are expected to produce high amounts of PUFAs. However, despite the fact that hundreds of mosses and liverworts have been found in Iceland, their lipid profiles largely remain unknown. In this study, we performed untargeted lipidomics by using UPLC-ESI-QTOF-MS as a rapid screening strategy to examine the lipid compositions of 39 local bryophyte species in Iceland and aimed to find high AA and EPA producers. A total of 280 lipid molecular species from 15 lipid classes were quantified with isotope-labeled internal standards. AA and EPA were abundantly distributed in the phospholipids (mainly PC and PE) and glycerolipids (MGDG and DGDG) in six moss species, namely Racomotrium lanuginosum, R. ericoides, Bryum psedotriquetrium, Plagiomnium ellipticum, Hylocomium splendens, and Rhytidiadelphus triquetrus. Two of the six species (B. psedotriquetrium and H. splendens) also accumulated high concentrations of PUFA-containing-triacylglycerols.

Analysis of chemotypes and their markers in leaves of core collections of Eucommia ulmoides using metabolomics

The leaves of Eucommia ulmoides contain various active compunds and nutritional components, and have successively been included as raw materials in the Chinese Pharmacopoeia, the Health Food Raw Material Catalogue, and the Feed Raw Material Catalogue. Core collections of E. ulmoides had been constructed from the conserved germplasm resources basing on molecular markers and morphological traits, however, the metabolite diversity and variation in this core population were little understood. Metabolite profiles of E. ulmoides leaves of 193 core collections were comprehensively characterized by GC-MS and LC-MS/MS based non-targeted metabolomics in present study. Totally 1,100 metabolites were identified and that belonged to 18 categories, and contained 120 active ingredients for traditional Chinese medicine (TCM) and 85 disease-resistant metabolites. Four leaf chemotypes of the core collections were established by integrated uses of unsupervised self-organizing map (SOM), supervised orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF) statistical methods, 30, 23, 43, and 23 chemomarkers were screened corresponding to the four chemotypes, respectively. The morphological markers for the chemotypes were obtained by weighted gene co-expression network analysis (WGCNA) between the chenomarkers and the morphological traits, with leaf length (LL), chlorophyll reference value (CRV), leaf dentate height (LDH), and leaf thickness (LT) corresponding to chemotypes I, II, III, and IV, respectively. Contents of quercetin-3-O-pentosidine, isoquercitrin were closely correlated to LL, leaf area (LA), and leaf perimeter (LP), suggesting the quercetin derivatives might influence the growth and development of E. ulmoides leaf shape.

Study on enhanced extraction and seasonal variation of secondary metabolites in Eucommia ulmoides leaves using deep eutectic solvents

It has been considered as a crucial field for the extraction of active ingredients from herbal medicine to use a green and efficient method in the medicinal and food industries. In recent years, deep eutectic solvents (DESs) have been obtaining increase attention in green chemistry area since its sustainability, safety and biodegradability. In this study, an efficient DES composed of choline chloride and L-(+)-ascorbic acid with a molar ratio of 2:1 performed higher efficacy on the extraction of target compounds (including iridoids, phenolic acids and flavonoids) in Eucommia ulmoides leaves than 50% methanol solution. Considering the extraction efficacy and time consumption, microwave-assisted extraction (MAE) was selected and the operational conditions, including power of microwave, liquid/solid ratio and irradiation time were optimized by response surface methodology (RSM). Water was used as anti-solvent to recover ten target analytes from DES with recovery yields of 97.59%, 94.91%, 96.09%, 90.66%, 95.16%, 87.33%, 86.57%, 82.15%, 89.28% and 80.75% for eucommiol (EU), aucubin (AU), geniposidic acid (GA), chlorogenic acid (CA), asperuloside (AP), rutin (RU), kaempferol-3-O-sambubioside (KS), isoquercitrin (IQ), kaempferol-3-O-rutinoside (KR) and astragaline (AS), respectively. By combining the DES-based MAE and quantitative analysis of multi-components by single mark (QAMS) methods, the contents of ten compounds in the leaves of Eucommia ulmoides were determined to clarify the relationship between the accumulation of secondary metabolites and the harvest period. It was found that the contents of main ingredients reached the highest during May to October. The period appears to be the best harvest period for Eucommia ulmoides leaves. This study provides a novel strategy for the harvesting, processing, and quality control of the raw materials from Eucommia ulmoides leaves.