Discovery and validation of biomarkers for Zhongning goji berries using liquid chromatography mass spectrometry

Fast and accurate discrimination analysis of Angelicae Pubescentis Radix using non-targeted analytical profiles images and two-dimensional convolution neural network

This study developed an effective approach for discriminating geographical origins of Duhuo samples using non-targeted UPLC chromatograms and UV-Vis spectrogram images combined with a two-dimensional convolution neural network (2D-CNN). For comparison, four machine learning methods-extreme gradient boosting (XGBoost), random forest (RF), partial least squares discriminant analysis (PLS-DA), and support vector machine (SVM) were applied to analyze UPLC, UV-Vis data matrix, and concentrations of seven target compounds. Enhanced by data augmentation, 2D-CNN demonstrated superior accuracy, with 98.28% accuracy for UV-Vis images and 100% for UPLC images, while traditional machine learning models showed considerable variation across datasets. These results demonstrate the integration of 2D-CNN with UPLC and UV-Vis images enable robustness, accurate and non-destructive analysis for the efficient discrimination of TCM samples. Specifically, UV-Vis spectroscopy provides a convenient method for quick detection. Overall, the employed approach offers a powerful tool for the precise and reliable analysis of herbal medicines.

A comparative UHPLC-QTOF-MS/MS-based metabolomics approach reveals the metabolite profiling of wolfberry sourced from different geographical origins

Wolfberry, known as Goji berry, is the fruit of Lycium barbarum L. (LB). As a famous functional food and TCM, the cost and efficacy of LB are closely linked to its geographical origin. The present study aimed to establish an effective method for distinguishing LB from different geographical origins. By employing UHPLC-QTOF-MS/MS combined with multivariate analysis, the metabolite profiling of LB (199 batches) obtained from Ningxia, Gansu, Qinghai, and Xinjiang, was evaluated. The results demonstrated that the method effectively distinguished LB from the four regions, with a total of 148 different metabolites being detected. Subsequent assessment using heat maps, Venn analysis, receiver operating characteristics curves and dot plots revealed 21 of these metabolites exhibited exceptional sensitivity and specificity, with under-curve values approaching 1, thus indicating their potential as biomarkers for LB. These findings strongly support the suitability of UHPLC-QTOF-MS/MS-based metabolomics as an effective approach to identify the source of LB.

Genomic Analysis of Romanian Lycium Genotypes: Exploring BODYGUARD Genes for Stress Resistance Breeding

Goji berries, long valued in Traditional Chinese Medicine and Asian cuisine for their wide range of medicinal benefits, are now considered a 'superfruit' and functional food worldwide. Because of growing demand, Europe and North America are increasing their goji berry production, using goji berry varieties that are not originally from these regions. European breeding programs are focusing on producing Lycium varieties adapted to local conditions and market demands. By 2023, seven varieties of goji berries were successfully registered in Romania, developed using germplasm that originated from sources outside the country. A broader project focused on goji berry breeding was initiated in 2014 at USAMV Bucharest. In the present research, five cultivated and three wild L. barbarum genotypes were compared to analyse genetic variation at the whole genome level. In addition, a case study presents the differences in the genomic coding sequences of BODYGUARD (BDG) 3 and 4 genes from chromosomes 4, 8, and 9, which are involved in cuticle-related resistance. All three BDG genes show distinctive differences between the cultivated and wild-type genotypes at the SNP level. In the BDG 4 gene located on chromosome 8, 69% of SNPs differentiate the wild from the cultivated genotypes, while in BDG 3 on chromosome 4, 64% of SNPs could tell the difference between the wild and cultivated goji berry. The research also uncovered significant SNP and InDel differences between cultivated and wild genotypes, in the entire genome, providing crucial insights for goji berry breeders to support the development of goji berry cultivation in Romania.

Authenticating the geographic origins of Atractylodes lancea rhizome chemotypes in China through metabolite marker identification

Introduction

Atractylodes lancea is widely distributed in East Asia, ranging from Amur to south-central China. The rhizome of A. lancea is commonly used in traditional Chinese medicine, however, the quality of products varies across different regions with different geochemical characteristics.

Method

This study aimed to identify the chemotypes of A. lancea from different areas and screen for chemical markers by quantifying volatile organic compounds (VOCs) using a targeted metabolomics approach based on GC-MS/MS.

Results

The A. lancea distributed in Hubei, Anhui, Shaanxi, and a region west of Henan province was classified as the Hubei Chemotype (HBA). HBA is characterized by high content of β-eudesmol and hinesol with lower levels of atractylodin and atractylon. In contrast, the Maoshan Chemotype (MA) from Jiangsu, Shandong, Shanxi, Hebei, Inner Mongolia, and other northern regions, exhibited high levels of atractylodin and atractylon. A total of 15 categories of VOCs metabolites were detected and identified, revealing significant differences in the profiles of terpenoid, heterocyclic compound, ester, and ketone among different areas. Multivariate statistics indicated that 6 compounds and 455 metabolites could serve as candidate markers for differentiating A. lancea obtained from the southern, northern, and Maoshan areas.

Discussion

This comprehensive analysis provides a chemical fingerprint of selected A. lancea. Our results highlight the potential of metabolite profiling combined with chemometrics for authenticating the geographical origin of A. lancea.

Widely Targeted Metabolomics Reveals the Effects of Soil on the Metabolites in Dioscorea opposita Thunb

Chinese yam (Dioscorea opposita Thunb. cv. Tiegun), a type of homologous medicinal plant, mainly grows in sandy soil (SCY) and loessial soil (LCY). However, the effects of the soil on the metabolites in SCY and LCY remain unclear. Herein, this study aims to comprehensively elucidate the metabolites in SCY and LCY. A UPLC-MS/MS-based, widely targeted metabolomics approach was adapted to compare the chemical composition of SCY and LCY. A total of 988 metabolites were detected, including 443 primary metabolites, 510 secondary metabolites, and 35 other compounds. Notably, 177 differential metabolites (classified into 12 categories) were identified between SCY and LCY; among them, 85.9% (152 differential metabolites) were upregulated in LCY. LCY significantly increased the contents of primary metabolites such as 38 lipids and 6 nucleotides and derivatives, as well as some secondary metabolites such as 36 flavonoids, 28 phenolic acids, 13 alkaloids, and 6 tannins. The results indicate that loessial soil can improve the nutritional and medicinal value of D. opposita.

Study on phenolic acids of Lonicerae japonicae Flos based on ultra high performance liquid chromatography-tandem mass spectrometry combined with multivariate statistical analysis

Lonicerae japonicae Flos, a traditional Chinese medicine, has the function of evacuating heat and detoxifying. To promote the optimization of Lonicerae japonicae Flos germplasms and improve the quality of medicinal materials, fifty-five batches of five Lonicerae japonicae Flos germplasms with the same origin were collected during different periods, a UHPLC-TOF-MS method was established, and twenty-two kinds of phenolic acids were found and qualitatively analysed. Seventeen phenolic acids were selected for quantitative analysis by UHPLC-QqQ-MS/MS, and the quantitative results were analysed by principal component analysis, orthogonal partial least squares-discriminant analysis, and partial least squares discriminant analysis. The contents of phenolic acids in periods S1∼S6 were found to be significantly different. There were also significant differences in the accumulation of phenolic acids in Lonicerae japonicae Flos during different growth periods. Ferulic acid, 5-O-caffeoylquinic acid, and caffeic acid were determined to be important components to distinguish the different growth periods of Lonicerae japonicae Flos. There were significant differences in the phenolic acid content of different germplasms of Lonicerae japonicae Flos, and the total amount of seventeen phenolic acids and total acids (chlorogenic acid, 3,5-di-O-caffeoylquinic acid, and 4,5-di-O-caffeoylquinic acid) in "Hua Jin No. 6" was highest, so the quality of "Hua Jin No. 6" was better than that of the four other germplasms. In addition, chlorogenic acid methyl ester and caffeic acid were the markers smallest in combination to distinguish the five germplasms of Lonicerae japonicae Flos. This article is protected by copyright. All rights reserved.

Chemical profiling and quality evaluation of Pogostemon cablin Benth by liquid chromatography tandem mass spectrometry combined with multivariate statistical analysis

Pogostemon cablin Benth (PCB) is a well-known traditional Chinese medicine that has been used for treatment of many ailments for several centuries. In presently, the chemical profiling and quality control study of PCB has mainly concentrated on the volatile fractions. However, the non-volatile chemical profile of PCB was still unclear. In this study, 73 non-volatile constituents (i.e., 33 flavonoids, 21 organic acids, 9 phenylpropanoids, 4 sesquiterpenes, 3 alkaloids, and 3 other types of compounds) were identified and characterized in PCB using high performance liquid chromatography coupled with quadruple time-of-flight tandem mass spectrometry (HPLC-Q-TOF-MS). Meanwhile, to assess PCB samples, an established HPLC-Q-TOF-MS fingerprint was combined with multivariate statistical analysis that included similarity analysis (SA), hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA). The PCB samples could be classified into two groups (herbal decoction pieces and processed medicinal materials), and acteoside, isoacteoside, 4',6-Dihydroxy-5,7-dimethoxyflavone, pachypodol and pogostone were screened as the potential chemical markers that attributed classification. In addition, nine representative components (pachypodol, vicenin-2, apigenin, rhamnocitrin, acteoside, isoacteoside, chlorogenic acid, azelaic acid and pogostone) in PCB were simultaneously determined by using an ultra-high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UPLC-QQQ-MS/MS). This study is the first to describe the chemical profile of PCB using liquid chromatography tandem mass spectrometry, which would improve our understanding of the substance basis of PCB and is helpful to the PCB further quality evaluation.

Authentication of berries and berry-based food products

Berries represent one of the most important and high-valued group of modern-day health-beneficial "superfoods" whose dietary consumption has been recognized to be beneficial for human health for a long time. In addition to being delicious, berries are rich in nutrients, vitamins, and several bioactive compounds, including carotenoids, flavonoids, phenolic acids, and hydrolysable tannins. However, due to their high value, berries and berry-based products are often subject to fraudulent adulteration, commonly for economical gain, but also unintentionally due to misidentification of species. Deliberate adulteration often comprises the substitution of high-value berries with lower value counterparts and mislabeling of product contents. As adulteration is deceptive toward customers and presents a risk for public health, food authentication through different methods is applied as a countermeasure. Although many authentication methods have been developed in terms of fast, sensitive, reliable, and low-cost analysis and have been applied in the authentication of a myriad of food products and species, their application on berries and berry-based products is still limited. The present review provides an overview of the development and application of analytical chemistry methods, such as isotope ratio analysis, liquid and gas chromatography, spectroscopy, as well as DNA-based methods and electronic sensors, for the authentication of berries and berry-based food products. We provide an overview of the earlier use and recent advances of these methods, as well as discuss the advances and drawbacks related to their application.

Comprehensive characterization of the chemical constituents in Yiganmingmu oral liquid and the absorbed prototypes in cynomolgus monkey plasma after oral administration by UPLC-Q-TOF-MS based on the self built components database

BACKGROUND

Yiganmingmu oral liquid (YGMM), a well known over-the-counter (OTC) drug in China, is composed of 12 types of valuable herbal medicines and has been widely used in clinical for the treatment of soreness and weakness of waist and knees, dizziness, memory loss, and fatigue. However, the chemical compositions of YGMM and its absorbed compounds in plasma remain unclear.

METHODS

Since chemical investigation is the first important step to reveal effects and action mechanisms of traditional Chinese medicine (TCM), in this study, based on the self built components database, systematic characterization of the chemical profile of YGMM in vitro was carried out by using a reliable UPLC-Q-TOF-MS method. Moreover, to obtain better understanding of the absorbed prototypes in plasma, serum pharmacochemistry analysis of YGMM after oral administration was conducted by using cynomolgus monkeys as animal model.

RESULTS

A total of 667 constituents from the 12 single herbal medicines were collected in the self built components database by searching the reported literatures, and 415 of them were initially screened as candidate compounds in YGMM by comparison of their experimental accurate mass measurements with those theoretical values. After that, 117 compounds including 17 phenolic acids, 25 flavonoids, 4 alkaloids, 10 phthalides, 5 monoterpenes, 8 triterpenoid saponins, 9 anthraquinones, and 39 other compounds, were unambiguously identified or tentatively characterized by analysing their MS/MS fragmentation patterns, and also by comparison with reference standards and those data reported in the literatures. 61 prototypes absorbed in plasma of cynomolgus monkey, including 13 phenolic acids, 21 flavonoids, 8 phthalides, 3 monoterpenes, 4 triterpenoid saponins, and 12 other compounds were tentatively assigned by serum pharmacochemistry analysis after oral administration.

CONCLUSION

It was the first comprehensive analysis of chemical constituents of YGMM and prototypes in plasma, and the data analysis strategy developed in this study showed high efficiency in the structural elucidations. The results might provide scientific evidence for further research on material basis of YGMM.

Multi-Targeted Metabolic Profiling of Carotenoids, Phenolic Compounds and Primary Metabolites in Goji (Lycium spp.) Berry and Tomato (Solanum lycopersicum) Reveals Inter and Intra Genus Biomarkers

Metabolic profile is a key component of fruit quality, which is a challenge to study due to great compound diversity, especially in species with high nutritional value. This study presents optimized analytical methods for metabolic profiling in the fruits of three Solanaceae species: Lycium barbarum, Lycium chinense and Solanumlycopersicum. It includes the most important chemical classes involved in nutrition and taste, i.e., carotenoids, phenolic compounds and primary compounds. Emphasis has been placed on the systematic achievement of good extraction yields, sample stability, and high response linearity using common LC-ESI-TQ-MS and GC-EI-MS apparatuses. A set of 13 carotenoids, 46 phenolic compounds and 67 primary compounds were profiled in fruit samples. Chemometrics revealed metabolic markers discriminating Lycium and Solanum fruits but also Lycium barbarum and Lycium chinense fruits and the effect of the crop environment. Typical tomato markers were found to be lycopene, carotene, glutamate and GABA, while lycibarbarphenylpropanoids and zeaxanthin esters characterized goji (Lycium spp.) fruits. Among the compounds discriminating the Lycium species, reported here for the first time to our knowledge, chlorogenic acids, asparagine and quinic acid were more abundant in Lycium chinense, whereas Lycium barbarum accumulated more lycibarbarphenylpropanoids A-B, coumaric acid, fructose and glucose.