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Journal ArticleDOI

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.

21 Oct 2020-Metabolites (Multidisciplinary Digital Publishing Institute)-Vol. 10, Iss: 10, pp 422
TL;DR: Optimal analytical methods for metabolic profiling in the fruits of three Solanaceae species, reported here for the first time to the authors' knowledge, revealed compounds discriminating the Lycium species were more abundant in Lycium chinense, whereas Lycium barbarum accumulated more lycibarbarphenylpropanoids A-B, coumaric acid, fructose and glucose.
Abstract: 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.
Citations
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Journal ArticleDOI
TL;DR: In this article, the potential value of metabolite profiling comprising the above-mentioned applications of metabolomics in crop improvement, medicinal plants utilization, and, in the prognosis, diagnosis and management of complex diseases is explored.
Abstract: During the past decade metabolomics has emerged as one of the fastest developing branches of "-omics" technologies. Metabolomics involves documentation, identification, and quantification of metabolites through modern analytical platforms in various biological systems. Advanced analytical tools, such as gas chromatography-mass spectrometry (GC/MS), liquid chromatography-mass spectroscopy (LC/MS), and non-destructive nuclear magnetic resonance (NMR) spectroscopy, have facilitated metabolite profiling of complex biological matrices. Metabolomics, along with transcriptomics, has an influential role in discovering connections between genetic regulation, metabolite phenotyping and biomarkers identification. Comprehensive metabolite profiling allows integration of the summarized data towards manipulation of biosynthetic pathways, determination of nutritional quality markers, improvement in crop yield, selection of desired metabolites/genes, and their heritability in modern breeding. Along with that, metabolomics is invaluable in predicting the biological activity of medicinal plants, assisting the bioactivity-guided fractionation process and bioactive leads discovery, as well as serving as a tool for quality control and authentication of commercial plant-derived natural products. Metabolomic analysis of human biofluids is implemented in clinical practice to discriminate between physiological and pathological state in humans, to aid early disease biomarker discovery and predict individual response to drug therapy. Thus, metabolomics could be utilized to preserve human health by improving the nutritional quality of crops and accelerating plant-derived bioactive leads discovery through disease diagnostics, or through increasing the therapeutic efficacy of drugs via more personalized approach. Here, we attempt to explore the potential value of metabolite profiling comprising the above-mentioned applications of metabolomics in crop improvement, medicinal plants utilization, and, in the prognosis, diagnosis and management of complex diseases.

17 citations

Journal ArticleDOI
TL;DR: In this article , five solvents were applied to the extraction of pigments from nine brown algae, followed by their determination and quantification by HPLC-DAD, showing a maximal value of 11.9 mg of total pigments per gram of dry alga obtained from the ethanolic extracts of H. elongata and U. pinnatifida.
Abstract: Brown algae are ubiquitously distributed in the NW coastline of the Iberian Peninsula, where they stand as an underexploited resource. In this study, five solvents were applied to the extraction of pigments from nine brown algae, followed by their determination and quantification by HPLC-DAD. A total of 13 compounds were detected: Six were identified as chlorophylls, six were classified as xanthophylls, and one compound was reported as a carotene. Fucoxanthin was reported in all extracts, which is the most prominent pigment of these algae. Among them, L. saccharina and U. pinnatifida present the highest concentration of fucoxanthin (4.5–4.7 mg∙g−1 dry weight). Ethanol and acetone were revealed as the most efficient solvents for the extraction of pigments, showing a maximal value of 11.9 mg of total pigments per gram of dry alga obtained from the ethanolic extracts of H. elongata, followed by the acetonic extracts of L. ochroleuca. Indeed, ethanol was also revealed as the most efficient solvent according to its high extraction yield along all species evaluated. Our results supply insights into the pigment composition of brown algae, opening new perspectives on their commercial exploitation by food, pharmaceutical, and cosmeceutical industries.

10 citations

Journal Article
TL;DR: A nontargeted metabolomics approach based on ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to find the differential composition between ZNG and NZNG and showed that two sets of combinative biomarkers to distinguish ZNG from NZNG with good sensitivity and specificity.

3 citations

Journal ArticleDOI
24 Feb 2021
TL;DR: The cultivar Amber Sweet (L. chinense) had fruits of which the similarities between biochemical characteristics of different studies genotypes were the lowest, and a distinctive feature of the other tested genotypes was the yellow colour of the fruit.
Abstract: Fruits of Lycium possess therapeutic properties due to which they are used in traditional and folk medicine and can be used as a kind of functional food. The objective of this study was to evaluate the biochemical characterization of Lycium L. (L. barbarum L., L. chinense Mill. and L. truncatum Y. C. Wang) fruits for 16 cultivars and varieties from the collections in the M. M. Gryshko National Botanical Garden of NAS of Ukraine (Kyiv). This study was aimed at determining the concentration of nutrients in the Lycium fruits. Individual genotypes of three Lycium species: L. barbarum, L.chinense, and L. truncatum, differed in such features as the content of dry matter, sugars, vitamin C, β-carotene, acidity, and tannins in the fruit. Fruits of Lycium spp. are a valuable source of nutrients such as vitamin C (4.38–121.0 mg 100g–1 FW), β-carotene content (1.45–5.52%), and tannin (0.12–1.34%). The sugar content (13.83–20.87%) and acidity of the fruit (0.23–4.62%) meet the consumers' requirements for fresh fruit. The cultivar Amber Sweet (L. chinense) had fruits of which the similarities between biochemical characteristics of different studies genotypes were the lowest. The cv. Amber Sweet was characterized by fruit with high sugar content, very high vitamin C content, average acid content, low tannins and β-carotene content, and the lowest dry matter content. Furthermore, a distinctive feature of the other tested genotypes was the yellow colour of the fruit. The data obtained can be used for further selective work.

2 citations


Cites background from "Multi-Targeted Metabolic Profiling ..."

  • ...Comparison with other studies showed that dry matter content for L. chinense was 11.9% and for L. barbarum 22.7–23.3% (Dumont et al., 2020)....

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References
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Journal ArticleDOI
TL;DR: A level system is proposed, which arose from intense discussions within the department, to ease the communication of identification confidence and form the basis of further discussions on this topic, and specifically covers the new possibilities in HR-MS-based analysis.
Abstract: T increased availability of high resolution mass spectrometry (HR-MS) in chemical analysis has dramatically improved the detection and identification of compounds in environmental (and other) samples. This has opened up new research opportunities in environmental sciences, demonstrated by over 200 research papers per year, increasing strongly (source: SCOPUS keywords “high resolution mass spectromet”, subject “envi”). The elucidation of small molecules such as emerging pollutants and their transformation products using HR-MSbased suspect and nontarget analysis is gaining in relevance, also in other fields (e.g., metabolomics, drug discovery, forensics). However, confidence in these HR-MS-based identifications varies between studies and substances, since it is not always possible or even meaningful to synthesize each substance or confirm them via complementary methods (e.g., nuclear magnetic resonance). These varying levels of confidence are very difficult to communicate to readers concisely and accurately. In Figure 1 we propose a level system, which arose from intense discussions within our department, to ease the communication of identification confidence and form the basis of further discussions on this topic. This level system is not intended to replace guidance documents (e.g., EU Guideline 2002/657/EG), but specifically covers the new possibilities in HR-MS-based analysis. Our discussion started with the levels published by the Metabolomics Standards Initiative (MSI), as we experienced many cases that fitted “in between” their proposed levels. While Jeon et al. first refined these levels, these were tailored to the specific investigation. The levels in Figure 1 reconcile differences in the two proposals, contain additional levels pertinent to screening methods and are clarified in the text below.

1,962 citations


"Multi-Targeted Metabolic Profiling ..." refers background or methods in this paper

  • ...Thirty-four primary metabolites were identified with a level 1 confidence [26] by comparing their retention time and EI–MS spectra with authentic standards....

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  • ...Twenty-three compounds were identified with a level 1 confidence [26] by comparing their retention time, absorbance spectra and MS/MS data with authentic standards....

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  • ...Thirty-four primary m tabolites were identified with a l vel 1 confidence [26] by comparing their retention tim and EI– MS spectra with authentic standards....

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  • ...Six major carotenoids (compounds 1, 2, 4, 7, 8 and 11 in Table S1) were identified with a level 1 confidence by comparing their retention time, absorbance spectra and MS/MS data with authentic standards [26] (Figure S2)....

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Journal ArticleDOI
TL;DR: MassBank is the first public repository of mass spectra of small chemical compounds for life sciences and provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions.
Abstract: MassBank is the first public repository of mass spectra of small chemical compounds for life sciences (<3000 Da). The database contains 605 electron-ionization mass spectrometry (EI-MS), 137 fast atom bombardment MS and 9276 electrospray ionization (ESI)-MS(n) data of 2337 authentic compounds of metabolites, 11 545 EI-MS and 834 other-MS data of 10,286 volatile natural and synthetic compounds, and 3045 ESI-MS(2) data of 679 synthetic drugs contributed by 16 research groups (January 2010). ESI-MS(2) data were analyzed under nonstandardized, independent experimental conditions. MassBank is a distributed database. Each research group provides data from its own MassBank data servers distributed on the Internet. MassBank users can access either all of the MassBank data or a subset of the data by specifying one or more experimental conditions. In a spectral search to retrieve mass spectra similar to a query mass spectrum, the similarity score is calculated by a weighted cosine correlation in which weighting exponents on peak intensity and the mass-to-charge ratio are optimized to the ESI-MS(2) data. MassBank also provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions. Data merging has significantly improved the precision of the identification of a chemical compound by 21-23% at a similarity score of 0.6. Thus, MassBank is useful for the identification of chemical compounds and the publication of experimental data.

1,689 citations


"Multi-Targeted Metabolic Profiling ..." refers background in this paper

  • ...The composition of goji fruits, especially in secondary metabolites, has been characterized by numerous authors [1,11,19,34,36,38,40]....

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Journal ArticleDOI
TL;DR: An overview of the main functional modules and the general workflow of MetaboAnalyst 4.0 is provided, followed by 12 detailed protocols: © 2019 by John Wiley & Sons, Inc.
Abstract: MetaboAnalyst (https://www.metaboanalyst.ca) is an easy-to-use web-based tool suite for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since its first release in 2009, MetaboAnalyst has evolved significantly to meet the ever-expanding bioinformatics demands from the rapidly growing metabolomics community. In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst supports a wide array of functions for statistical, functional, as well as data visualization tasks. Some of the most widely used approaches include PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), clustering analysis and visualization, MSEA (metabolite set enrichment analysis), MetPA (metabolic pathway analysis), biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. The current version of MetaboAnalyst (4.0) features a complete overhaul of the user interface and significantly expanded underlying knowledge bases (compound database, pathway libraries, and metabolite sets). Three new modules have been added to support pathway activity prediction directly from mass peaks, biomarker meta-analysis, and network-based multi-omics data integration. To enable more transparent and reproducible analysis of metabolomic data, we have released a companion R package (MetaboAnalystR) to complement the web-based application. This article provides an overview of the main functional modules and the general workflow of MetaboAnalyst 4.0, followed by 12 detailed protocols: © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Data uploading, processing, and normalization Basic Protocol 2: Identification of significant variables Basic Protocol 3: Multivariate exploratory data analysis Basic Protocol 4: Functional interpretation of metabolomic data Basic Protocol 5: Biomarker analysis based on receiver operating characteristic (ROC) curves Basic Protocol 6: Time-series and two-factor data analysis Basic Protocol 7: Sample size estimation and power analysis Basic Protocol 8: Joint pathway analysis Basic Protocol 9: MS peaks to pathway activities Basic Protocol 10: Biomarker meta-analysis Basic Protocol 11: Knowledge-based network exploration of multi-omics data Basic Protocol 12: MetaboAnalystR introduction.

1,522 citations

Journal ArticleDOI
TL;DR: Although the method represents a compromise for a wide range of metabolites in terms of extraction, chemical modification and GC-MS analysis, for 25 metabolites analysed in detail the recoveries were found to be within the generally accepted range of 70-140%.
Abstract: A new method is presented in which gas chromatography coupled to mass spectrometry (GC-MS) allows the quantitative and qualitative detection of more than 150 compounds within a potato tuber, in a highly sensitive and specific manner. In contrast to other methods developed for metabolite analysis in plant systems, this method represents an unbiased and open approach that allows the detection of unexpected changes in metabolite levels. Although the method represents a compromise for a wide range of metabolites in terms of extraction, chemical modification and GC-MS analysis, for 25 metabolites analysed in detail the recoveries were found to be within the generally accepted range of 70-140%. Further, the reproducibility of the method was high: the error occurring in the analysis procedures was found to be less than 6% for 30 out of 33 compounds tested. Biological variability exceeded the systematic error of the analysis by a factor of up to 10. The method is also suited for upscaling, potentially allowing the simultaneous analysis of a large number of samples. As a first example this method has been applied to soil- and in vitro-grown tubers. Due to the simultaneous analysis of a wide range of metabolites it was immediately apparent that these systems differ significantly in their metabolism. Furthermore, the parallel insight into many pathways allows some conclusions to be drawn about the underlying physiological differences between both tuber systems. As a second example, transgenic lines modified in sucrose catabolism or starch synthesis were analysed. This example illustrates the power of an unbiased approach to detecting unexpected changes in transgenic lines.

1,119 citations


"Multi-Targeted Metabolic Profiling ..." refers methods in this paper

  • ...Finally, primary metabolites were analyzed with a well-established GC–EI–TOF–MS technique that provides a good coverage of small polar molecules and high reliability in terms of both peak annotation and quantification [16,17]....

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Journal ArticleDOI
TL;DR: In view of the available pharmacological data and the long tradition of use in the traditional Chinese medicine, L. barbarum and L. chinense certainly deserve further investigation, but clinical evidences and rigorous procedures for quality control are indispensable before any recommendation of use can be made for Goji products.
Abstract: Since the beginning of this century, Goji berries and juice are being sold as health food products in western countries and praised in advertisements and in the media for well-being and as an anti-aging remedy. The popularity of Goji products has rapidly grown over the last years thanks to efficient marketing strategies. Goji is a relatively new name given to Lycium barbarum and L. chinense, two close species with a long tradition of use as medicinal and food plants in East Asia, in particular in China. While only L. barbarum is officinal, the fruit (fructus Lycii) and the root bark (cortex Lycii radicis) of both species are used in the folk medicine. We review here the constituents, pharmacology, safety, and uses of L. barbarum and L. chinense with consideration to the different parts of the plant. Investigations of the fruit have focused on proteoglycans, known as " Lycium barbarum polysaccharides", which showed antioxidative properties and some interesting pharmacological activities in the context of age related diseases such as atherosclerosis and diabetes. As to the root bark, several compounds have demonstrated a hepatoprotective action as well as inhibitory effects on the rennin/angiotensin system which may support the traditional use for the treatment of hypertension. While there are no signs of toxicity of this plant, two cases of possible interaction with warfarin point to a potential risk of drug interaction. In view of the available pharmacological data and the long tradition of use in the traditional Chinese medicine, L. barbarum and L. chinense certainly deserve further investigation. However, clinical evidences and rigorous procedures for quality control are indispensable before any recommendation of use can be made for Goji products.

530 citations

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