Metabolic Profiling with Gas Chromatography-Mass Spectrometry and Capillary Electrophoresis-Mass Spectrometry Reveals the Carbon-Nitrogen Status of Tobacco Leaves Across Different Planting Areas

Metabolic and oxidative stress response of sea cucumber Apostichopus japonicus exposed to acute high concentration of bisphenol AF

Bisphenols are known as endocrine disruptor that affect the development, and growth of marine creatures, including human. There were plenty of manuscripts evaluated the toxicology of bisphenol A (BPA) and its analogues such as bisphenol F (BPF), bisphenol AF (BPAF), and bisphenol S (BPS), but limits of them studied the effects of bisphenol analogues on echinoderms. In this study, we used metabolomics to investigate the metabolic response of sea cucumber (Apostichopus japonicus) exposed to BPAF, and the activities of glutathione (GSH), catalase (CAT), and superoxide dismutase (SOD) were determined. The results demonstrated alterations in lipid metabolism, glycerophospholipid metabolism, and biosynthesis of amino acids following BPAF treatment. Sea cucumbers upregulated the glycerophospholipid metabolism to repair the destruction of intestine cellular homeostasis. Six metabolites were selected as the potential biomarkers for the exposure of BPAF. This study revealed the metabolic response and oxidative response of sea cucumber arising from BPAF exposure, and provided theoretical support for the risk assessment of bisphenol analogues on economically important echinoderms, such as A. japonicus.

Analysis of metabolite differences between South Korean and Chinese yellow goosefish (Lophius litulon) using capillary electrophoresis time-of-flight mass spectrometry

The yellow goosefish is a benthic fish that belongs to the family Lophiidae and order Lophiiformes and is distributed in the Yellow and East China Seas. This study aimed to distinguish between yellow goosefish from different geographical origins by analyzing their metabolites. Capillary electrophoresis time-of-flight mass spectrometry was used to analyze metabolite profiles in the muscle tissues of yellow goosefish to distinguish between Korean and Chinese yellow goosefish. In total, 271 putative metabolites were extracted using 50% acetonitrile in water. Principal component analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to distinguish different geographical origins using the metabolite profiles obtained. The R2 and Q2 values of the OPLS-DA model were 0.856 and 0.695, respectively, indicating that the model was well-fitted and had good predictability. The heat map revealed that nucleic acid and amino compounds differed between the Korean and Chinese fish, and the variable importance in the projection scores obtained from OPLS-DA showed that there were geographical differences in the primary metabolites (5'-methylthioadenosine, adenosine, uridine 5-diphosphate, guanosine 5-diphosphate, urea, homocarnosine, O-acetylcarnitine, cycloleucine, cycloleucine S-adenosylmethionine, S-adenosylhomocysteine, ethanolamine, myo-inositol 1-phosphate), which were identified as potential candidate biomarkers.

Antioxidant-Activity-Guided Purification and Separation of Octocrylene from Saussurea heteromalla

Plants have been a source of medicine since ancient times, and such traditional medications are widely practiced nowadays. Saussurea heteromalla is widely used in traditional medicine in the Himalayan region for the treatment of different ailments. However, despite its traditional uses, it is not widely explored for its free radical scavenging abilities and other biological activities. Thus, the current study is aimed at exploring the free radical scavenging ability of S. heteromalla extracts, along with the isolation and evaluation of its compound through bioassay-guided purification. From different solvent fractions, an n-hexane extract of a whole plant is found to be most active; thus, it is processed for large-scale extraction and column chromatography. Further, the purification of an active fraction is performed using HPLC–DAD, which led to the isolation of an active peak, identified by GC/MS, as 2-ethylhexyl 2-cyano-3, 3-diphenylprop-2-enoate. This compound, commonly known as octocrylene, is widely recommended for UV-B filter, to be used in the cosmetic industry as photoprotection products. The presence of free radical scavenging activity enhances the sun protection factor of octocrylene. The present study presents the first report on the isolation of this compound from the family Asteraceae. The compound has good free radical scavenging activity and is widely used in the cosmetic industry as a sun protectant and is much less reported from botanical sources.

Multi-omics analyses reveal new insights into nutritional quality changes of alfalfa leaves during the flowering period

High-quality alfalfa is an indispensable resource for animal husbandry and sustainable development. Its nutritional quality changes dramatically during its life cycle and, at present, no molecular mechanisms for nutrient metabolic variation in alfalfa leaves at different growth stages have been clearly reported. We have used correlation and network analyses of the alfalfa leaf metabolome, proteome, and transcriptome to explore chlorophyll, flavonoid, and amino acid content at two development stages: budding stage (BS) and full-bloom stage (FBS). A high correlation between the expression of biosynthetic genes and their metabolites revealed significant reductions in metabolite content as the plant matured from BS to FBS. l-Glutamate, the first molecule of chlorophyll biosynthesis, decreased, and the expression of HemA, which controls the transformation of glutamyl-tRNA to glutamate 1-semialdehyde, was down-regulated, leading to a reduction in leaf chlorophyll content. Flavonoids also decreased, driven at least in part by increased expression of the gene encoding CYP75B1: flavonoid 3'-monooxygenase, which catalyzes the hydroxylation of dihydroflavonols and flavonols, resulting in degradation of flavonoids. Expression of NITRILASE 2 (NIT2) and Methyltransferase B (metB), which regulate amino acid metabolism and influence the expression of genes of the glycolysis-TCA pathway, were down-regulated, causing amino acid content in alfalfa leaves to decrease at FBS. This study provides new insights into the complex regulatory network governing the content and decrease of chlorophyll, amino acids, flavonoids, and other nutrients in alfalfa leaves during maturation. These results further provide a theoretical basis for the generation of alfalfa varieties exhibiting higher nutritional quality, high-yield cultivation, and a timely harvest.

Analysis of metabolites of red seabream (Pagrus major) from different geographical origins by capillary electrophoresis time-of-flight mass spectrometry

Red seabream (Pagrus major), a migratory fish, is characterized by high protein levels in the muscle. South Korean and Japanese red seabreams have a general distribution pattern; however, distinguishing them based on their geographical origin is difficult. In this study, we used capillary electrophoresis time-of-flight mass spectrometry (CE-TOF/MS) to analyze the red seabream muscle metabolome to investigate how can distinguish the origin of the fish. The metabolites were extracted using 50% acetonitrile in water. Chromatographic separation was successfully used to classify the metabolite profiles of Japanese and South Korean red seabream. Principal component analysis and hierarchical cluster analysis showed good ability to categorize the samples according to their origin. Amino acids showed the greatest quantitative difference in South Korean and Japanese muscle samples. Specifically, the L-alanine, L-glutamic acid, L-isoleucine, dimethylglycine, and L-valine levels in Japanese red seabream samples were significantly higher than those in South Korean samples. In contrast, the levels of trimethylamine N-oxide and inosine monophosphate in South Korean muscle samples were significantly higher than those in Japanese red muscle samples. The monitored metabolite profiles suggest that South Korean and Japanese red seabreams can be identified on the basis of amino acid levels.

Amino acids profiling and transcriptomic data integration demonstrates the dynamic regulation of amino acids synthesis in the leaves of Cyclocarya paliurus

Background

Cyclocarya paliurus is a tree well known for its edible and medicinal leaves. Amino acids are essential nutritional components that are present in foods and closely related to the flavor and quality of tea. However, the abundance of amino acids and the regulation of amino acid biosynthesis in the leaves of C. paliurus have not been investigated across different developmental stages.

Methods

A combined metabolomic and transcriptomic analysis was employed to investigate the changes in the amino acid profile over several developmental stages (S1, the smallest fully expanded leaf; S3, full leaf enlargement and full leaf thickness; and S2, an intermediate developmental stage between S1 and S3) and the molecular mechanism was elucidated.

Results

The results showed that leaves at the S1 stage had the highest content, while those at the S3 stage had the lowest content of amino acids; fourteen differentially expressed genes were involved in the glycolysis pathway, the tricarboxylic acid cycle and the pentose phosphate pathway, which indicated that the reduced abundance of amino acids in the leaves of C. paliurus (mature leaves) may be attributable to reduced gene expression related to carbohydrate metabolism. Four basic leucine zipper transcription factors might play important roles in the regulation of the biosynthesis of amino acids in the leaves of C. paliurus.

Conclusions

Leaves at the S1 stage are recommended for high quality tea production because of their high content of amino acids, while leaves at the S2 stage are recommended for generous tea production because of their high levels of sweet flavor amino acids (alanine) and essential amino acids (methionine, phenylalanine, threonine, and tryptophan).

Metabolomics Analysis of Morchella sp. From Different Geographical Origins of China Using UPLC-Q-TOF-MS

The morel mushroom (Morchella sp.) is reputed as one of the most highly-prized edible fungi with mounting cultivated area as well as commercial popularity in China. To date, optimized methods specific for quality evaluation and constituent analysis of Morchella sp. are still non-available, impeding the healthy and sustainable development of this industry. Herein, an untargeted UPLC-Q-TOF-MS-based metabolomics approach was performed to characterize the metabolite profiles of morel samples from four distinct geographical origins of China, viz. Gansu, Guizhou, Liaoning, and Henan province. A total of 32 significantly different metabolites assigned to lipids (19), organic acids (9), amino acids (3), and ketones (1) were identified to distinguish the geographic-segregation samples amenable to multivariate analysis. These metabolites may serve as molecular markers indicative of specific regions. More importantly, the lipid, protein and amino acid metabolism were responsible for geographic differences as revealed by KEGG pathway enrichment analysis. Collectively, this study not only pioneered high-throughput methodology to evaluate quality of Morchella sp. and distinguish geographical origins in a sensitive, rapid and efficient manner, but also shed light on the potential link between physiochemical variation and geological origins from a metabolic perspective, which may be conducive to the advancement of edible fungi industry and establishment of food traceability system.

Metabolomics analysis provides new insights into the medicinal value of flavonoids in tobacco leaves

Tobacco is a traditional Chinese medicine containing a variety of biologically active substances. In addition to being used to make cigarettes, tobacco is also a vastly underdeveloped medicinal resource. In order to identify and clarify the biological activities and medicinal value of tobacco leaves, the metabolomes of tobacco leaves were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) based on multiple reaction monitoring (MRM). In total, 1169 metabolites were identified and quantified. The results showed that the metabolic profiles of the tobacco cultivars K326 and Yun87 are similar to each other but different from that of Hongda. Moreover, the curing process affects the metabolic profiles of tobacco leaves. Flavonoids are the largest class of metabolites in tobacco leaves. Flavonoids have multiple biological functions; for example, they can promote or inhibit inflammation. We found that quercetin provides anti-inflammatory activity by inhibiting the il-1β mRNA expression, while glycitin and neohesperidin can promote il-1β and il-6 production. Our results provide in-depth insights into the medical uses and biological mechanisms of tobacco leaves.

Discrimination of the Geographical Origin of Soybeans Using NMR-Based Metabolomics

With the increase in soybean trade between countries, the intentional mislabeling of the origin of soybeans has become a serious problem worldwide. In this study, metabolic profiling of soybeans from the Republic of Korea and China was performed by nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to predict the geographical origin of soybeans. The optimal orthogonal partial least squares-discriminant analysis (OPLS-DA) model was obtained using total area normalization and unit variance (UV) scaling, without applying the variable influences on projection (VIP) cut-off value, resulting in 96.9% sensitivity, 94.4% specificity, and 95.6% accuracy in the leave-one-out cross validation (LOO-CV) test for discriminating between Korean and Chinese soybeans. Soybeans from the northeastern, middle, and southern regions of China were successfully differentiated by standardized area normalization and UV scaling with a VIP cut-off value of 1.0, resulting in 100% sensitivity, 91.7%–100% specificity, and 94.4%–100% accuracy in a LOO-CV test. The methods employed in this study can be used to obtain essential information for the authentication of soybean samples from diverse geographical locations in future studies.

Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of Nicotiana tabacum L. Leaves

Nicotiana tabacum L. (NTL) is an important agricultural and economical crop. Its maturity is one of the key factors affecting its quality. Traditionally, maturity is discriminated visually by humans, which is subjective and empirical. In this study, we concentrated on detecting as many compounds as possible in NTL leaves from different maturity grades using ultra-performance liquid chromatography ion trap time-of-flight mass spectrometry (UPLC-IT-TOF/MS). Then, the low-dimensional embedding of LC-MS dataset by t-distributed stochastic neighbor embedding (t-SNE) clearly showed the separation of the leaves from different maturity grades. The discriminant models between different maturity grades were established using orthogonal partial least squares discriminant analysis (OPLS-DA). The quality metrics of the models are R2Y = 0.939 and Q2 = 0.742 (unripe and ripe), R2Y = 0.900 and Q2 = 0.847 (overripe and ripe), and R2Y = 0.972 and Q2 = 0.930 (overripe and unripe). The differential metabolites were screened by their variable importance in projection (VIP) and p-Values. The existing tandem mass spectrometry library of plant metabolites, the user-defined library of structures, and MS-FINDER were combined to identify these metabolites. A total of 49 compounds were identified, including 12 amines, 14 lipids, 10 phenols, and 13 others. The results can be used to discriminate the maturity grades of the leaves and ensure their quality.

Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry

Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.

Recent development in mass spectrometry and its hyphenated techniques for the analysis of medicinal plants

INTRODUCTION

Medicinal plants are gaining increasing attention worldwide due to their empirical therapeutic efficacy and being a huge natural compound pool for new drug discovery and development. The efficacy, safety and quality of medicinal plants are the main concerns, which are highly dependent on the comprehensive analysis of chemical components in the medicinal plants. With the advances in mass spectrometry (MS) techniques, comprehensive analysis and fast identification of complex phytochemical components have become feasible, and may meet the needs, for the analysis of medicinal plants.

OBJECTIVE

Our aim is to provide an overview on the latest developments in MS and its hyphenated technique and their applications for the comprehensive analysis of medicinal plants.

METHODOLOGY

Application of various MS and its hyphenated techniques for the analysis of medicinal plants, including but not limited to one-dimensional chromatography, multiple-dimensional chromatography coupled to MS, ambient ionisation MS, and mass spectral database, have been reviewed and compared in this work.

RESULTS

Recent advancs in MS and its hyphenated techniques have made MS one of the most powerful tools for the analysis of complex extracts from medicinal plants due to its excellent separation and identification ability, high sensitivity and resolution, and wide detection dynamic range.

CONCLUSION

To achieve high-throughput or multi-dimensional analysis of medicinal plants, the state-of-the-art MS and its hyphenated techniques have played, and will continue to play a great role in being the major platform for their further research in order to obtain insight into both their empirical therapeutic efficacy and quality control.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

Metabolic profiles of Cuibi-1 and Zhongyan-100 flue-cured tobacco leaves in different growing regions by gas chromatography/mass spectrometry

The metabolic profiles of tobacco leaves of two differential Chinese cultivars from different growing regions were analysed using gas chromatography-mass spectrometry (GC-MS). The results of principal component analysis, partial least-squares discriminant analysis and hierarchical cluster analysis showed significant differences in metabolome among three groups, identified 24 differential metabolites, and analysed the metabolic pathway in which the metabolites were involved. Among them, 13 metabolites were associated with geographical regions, including seven organic and fatty acids, four carbohydrates and two secondary metabolites. Four amino acids and two monosaccharides were associated with cultivars and the remaining five metabolites were associated with both. The relationships among the differential metabolites and the distinct characteristics of environment and cultivar were further discussed. In addition, correlation analysis indicated that most of the differential carbohydrates were negatively correlated with the differential amino acids and organic acids. Taken together, this study demonstrates the metabolite differences between two cultivars in different regions, and highlights the effect of environment and cultivar on tobacco leaf metabolism.

Mass spectrometry-driven drug discovery for development of herbal medicine

Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high-throughput technology for advancing drug discovery from HM in the post-genomic era. It is essential to develop an efficient, high-quality, high-throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics-guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high-throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes.

Recent advances in amino acid analysis by capillary electromigration methods: June 2015-May 2017

In the tenth edition of this article focused on recent advances in amino acid analysis using capillary electrophoresis, we describe the most important research articles published on this topic during the period from June 2015 to May 2017. This article follows the format of the previous articles published in Electrophoresis. The new developments in amino acid analysis with CE mainly describe improvements in CE associated with mass spectrometry. Focusing on applications, we mostly describe clinical works, although metabolomics studies are also very important. Finally, works focusing on amino acids in food and agricultural applications are also described.

CE-MS for metabolomics: Developments and applications in the period 2014-2016

CE–MS can be considered a useful analytical technique for the global profiling of (highly) polar and charged metabolites in various samples. Over the past few years, significant advancements have been made in CE–MS approaches for metabolomics studies. In this paper, which is a follow‐up of a previous review paper covering the years 2012–2014 (Electrophoresis 2015, 36, 212–224), recent CE–MS strategies developed for metabolomics covering the literature from July 2014 to June 2016 are outlined. Attention will be paid to new CE–MS approaches for the profiling of anionic metabolites and the potential of SPE coupled to CE–MS is also demonstrated. Representative examples illustrate the applicability of CE–MS in the fields of biomedical, clinical, microbial, plant, and food metabolomics. A complete overview of recent CE–MS‐based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given.

The development of plasma pseudotargeted GC-MS metabolic profiling and its application in bladder cancer

Bladder cancer (BC) is a fatal malignancy with considerable mortality. BC urinary metabolomics has been extensively investigated for biomarker discovery, but few BC blood metabolomic studies have been performed. Hence, a plasma pseudotargeted metabolomic method based on gas chromatography-mass spectrometry with selected ion monitoring (GC-MS-SIM) was developed to study metabolic alterations in BC. The analytical performance of the developed method was compared with that of a nontargeted method. The relative standard deviation (RSD) values of 89 and 70.7 % of the peaks obtained using the pseudotargeted and nontargeted methods, respectively, were less than 20 %. The Pearson correlations of 90.7 and 78.3 % of the peaks obtained using the pseudotargeted and nontargeted methods, respectively, exceeded 0.90 in the linearity evaluation. Compared with the nontargeted method, the signal-to-noise ratios (S/N) of 97.9 and 69.3 % of the peaks increased two- and fivefold, respectively. The developed method was fully validated, with good precision, recovery, and stability of the trimethylsilyl (TMS) derivatives. The method was applied to investigate BC. Significant increases in the contents of metabolites involved in, for example, the pentose phosphate pathway (PPP) and nucleotide and fatty acid synthesis were found in the high-grade (HG) BC group compared to the healthy control (HC) group. These differences imply that the activated PPP may regulate BC cell proliferation by promoting lipid and nucleotide biosynthesis and the detoxification of reactive oxygen species (ROS). These results illustrate that the plasma pseudotargeted method is a powerful tool for metabolic profiling. Graphical abstract The plasma pseudotargeted metabolic profiling suggested the metabolic alterations in bladder cancer (BC) and the significantly differential metabolites for BC discrimination.