Discrimination of cabbage (Brassica rapa ssp. pekinensis) cultivars grown in different geographical areas using 1H NMR-based metabolomics

Metabolomic Insights of Biosurfactant Activity from Bacillus niabensis against Planktonic Cells and Biofilm of Pseudomonas stutzeri Involved in Marine Biofouling

In marine environments, biofilm can cause negative impacts, including the biofouling process. In the search for new non-toxic formulations that inhibit biofilm, biosurfactants (BS) produced by the genus Bacillus have demonstrated considerable potential. To elucidate the changes that BS from B. niabensis promote in growth inhibition and biofilm formation, this research performed a nuclear magnetic resonance (NMR) metabolomic profile analysis to compare the metabolic differences between planktonic cells and biofilms of Pseudomonas stutzeri, a pioneer fouling bacteria. The multivariate analysis showed a clear separation between groups with a higher concentration of metabolites in the biofilm than in planktonic cells of P. stutzeri. When planktonic and biofilm stages were treated with BS, some differences were found among them. In planktonic cells, the addition of BS had a minor effect on growth inhibition, but at a metabolic level, NADP+, trehalose, acetone, glucose, and betaine were up-regulated in response to osmotic stress. When the biofilm was treated with the BS, a clear inhibition was observed and metabolites such as glucose, acetic acid, histidine, lactic acid, phenylalanine, uracil, and NADP+ were also up-regulated, while trehalose and histamine were down-regulated in response to the antibacterial effect of the BS.

Effect of glycinebetaine on metabolite profiles of cold-stored strawberry revealed by 1H NMR-based metabolomics

Glycinebetaine (GB) has long been used as a preservative for refrigerated fruits, but the effect of GB on the global metabolites of cold-stored strawberries is still unclear. In this study, the effects of exogenous application of GB on quality-related metabolites of cold-stored strawberries were investigated by nuclear magnetic resonance (NMR)-based metabolomic analysis. The results showed that the application of GB (especially at the concentration of 10 mM) on cold-stored strawberries effectively stabilized the sugars (d-xylose and d-glucose) and amino acids (tyrosine, leucine, and tryptophan) content, and lowered the acid (acetic acid) content as well. Additionally, the GB content in strawberries also increased. This implies that the appropriate concentration of GB is a natural and safe treatment, which could maintain the quality of cold-stored strawberries by regulating levels of quality-related metabolites, and the ingestion of GB-preserved strawberries may serve as a source of methyl-donor supplementation in our daily diet.

Nuclear magnetic resonance-based metabolomics and cytotoxicity (HT-29 and HCT-116 cell lines) studies insight the potential of less utilized parts of Camellia sinensis (Kangra tea)

Camellia sinensis (tea) is an evergreen plant having bioactive compounds associated with various pharmacological effects, including anti-cancerous activity. These phytochemicals are variedly distributed in plant tissues. A detailed study to understand chemical composition within the economically underutilized tea tissues is required to generate value. Therefore, a comprehensive chemical profiling of underutilized C. sinensis parts [coarse leaves, flowers, fruits (immature);n = 9] was performed by NMR techniques. NMR (1D and 2D) spectroscopy ambiguously identified and quantified fifty-seven metabolites (Coarse leaves: 35, flowers; 42, immature fruits; 45). The statistical analysis showed apparent tissue-specific similarities (26 metabolites) and variations. Further, HPLC-DAD revealed absolute quantification of catechins, caffeine and theanine among the different parts of C. sinensis. Moreover, cytotoxicity studies of tea tissues against colorectal cancer cell lines showed anticancer potentials. This chemical information and anticancer activity of underutilized C. sinensis parts will help to develop value added nutraceutical and cosmeceutical products.

Bean cultivars (Phaseolus vulgaris L.) under the spotlight of NMR metabolomics

The seeds of Phaseolus vulgaris are a rich source of protein consumed around the world and are considered as the most important source of proteins and antioxidants in the Mexican diet. This work reports on the 1H NMR metabolomics profiling of the cultivars Peruano (FPe), Pinto (FPi), Flor de mayo (FM), Negro (FN) and Flor de junio (FJ). Total phenolics, total flavonoids and total protein contents were determined to complement the nutritional facts in seeds and leaves. According to our results, the metabolomics fingerprint of beans seeds and leaves were very similar, showing the presence of 52 metabolites, 46 in seeds and 48 in leaves, including 8 sugars, 17 amino acids, 15 organic acids, 5 nucleosides and 7 miscellaneous compounds. In seeds, free amino acids were detected in higher concentrations than in the leaves, whereas organic acids were more abundant in leaves than in seeds. With multivariate and cluster analysis it was possible to rank the cultivars according to their nutritional properties according to NMR profiling, then a machine learning algorithm was used to reveal the most important differential metabolites which are the key for correct classification. The results coincide in highlighting the FN seeds and FPe leaves for the best nutritional facts. Finally, in terms of cultivars, FN and FM present the best nutritional properties, with high protein and flavonoids content, as well as, a high concentration of amino acids and nucleosides.

NMR Tracing of Food Geographical Origin: The Impact of Seasonality, Cultivar and Production Year on Data Analysis

The traceability of typical foodstuffs is necessary to protect high quality of traditional products. It is well-known that several factors could influence metabolites content in certified foods, but soil composition, altitude, latitude and coded production protocols constitute the territorial conditions responsible for the peculiar organoleptic and nutritional properties of labelled foods. Instead, regardless of origin, seasonality, cultivar, collection year can affect all agricultural products, so it is appropriate to include them in data analysis in order to obtain a correct interpretation of the differences linked to growing areas alone. Therefore, it is useful to use a flexible all-round technique, and NMR spectroscopy coupled with multivariate statistical analysis is considered a powerful means of assessing food authenticity. The purpose of this review is to investigate the relevance of year, cultivar, and seasonal period in the determination of food geographical origin using NMR spectroscopy. The strategy for testing these three factors may differ from author to author, but a preliminary study of cultivar or collection year effects on NMR spectra is the most popular method before starting the geographical characterization of samples. In summary, based on the available literature, the most significant influence is due to cultivar, followed by harvesting year, however seasonality is not considered a source of variability in data analysis.

Nontargeted 1 H NMR fingerprinting and multivariate statistical analysis for traceability of Greek PDO Vostizza currants

In this study, non-targeted ¹ H NMR fingerprinting was used in combination with multivariate statistical analyses for the classification of Greek currants based on their geographical origins (Aeghion, Nemea, Kalamata, Zante, and Amaliada). As classification techniques, Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were carried out. To elucidate different components according to PDO (Protected Designation of Origin), products from Aeghion (Vostizza) were statistically compared with each one of the four other regions. PLS-DA plots ensure that currants from Kalamata, Nemea, Zante, and Amaliada are well classified with respect to the PDO currants, according to differences observed in metabolites. Results suggest that composition differences in carbohydrates, amino, and organic acids of currants are sufficient to discriminate them in correlation to their geographical origin. In conclusion, currants metabolites which mostly contribute to classification performance of such discriminant analysis model present a suitable alternative technique for currants traceability. The study results contribute information to the currants' metabolite fingerprinting by NMR spectroscopy and their geographical origin. PRACTICAL APPLICATION: This study presents an analytical approach for a high nutritional value Greek PDO product, Vostizza currant. A further research and implementation of this method in food industry, can be the key to food fraud incidents. Thus, application of this work opens up posibilities to "farm to table" mission.

The dehiscence process in Panax ginseng seeds and the stigmasterol biosynthesis pathway in terms of metabolomics

Background

Ginseng, officially known as Panax ginseng Meyer, has been traditionally used as a medicinal herb, particularly in Asia. Ginseng is propagated from seeds; however, seed germination is challenging, especially in its natural environment on farms. The seeds typically exhibit morphophysiological dormancy and require release from both morphological and physiological dormancy before germination. Although some studies have proposed methods for increasing seed germination rates, the underlying mechanisms of its dormancy release process remain unclear. Here, we investigated metabolic alterations during dehiscence in P. ginseng to determine their potential roles in dormancy release.

Methods

We compared the ginseng seed metabolome before and after dehiscence and the ginsenoside and phytosterol compositions of the seeds in both periods in the presence of related enzymes.

Results

After seed dehiscence, the sugar, amino acid, and squalene concentrations were significantly altered, phytosterols associated with the stigmasterol biosynthesis pathway were increased, while ginsenoside and brassinosteroid levels were not significantly altered. In addition, squalene epoxidase, cycloartenol synthase, 24-methylenesterol C-methyltransferase, and the stigmasterol biosynthesis pathway were activated.

Conclusion

Overall, our findings suggest that morphological activities that facilitate ginseng seed growth are the primary phenomena occurring during the dehiscence process. This study improves the understanding of P. ginseng germination processes and promotes further research of its germination and cultivation.

You Are What You Eat: Application of Metabolomics Approaches to Advance Nutrition Research

A healthy condition is defined by complex human metabolic pathways that only function properly when fully satisfied by nutritional inputs. Poor nutritional intakes are associated with a number of metabolic diseases, such as diabetes, obesity, atherosclerosis, hypertension, and osteoporosis. In recent years, nutrition science has undergone an extraordinary transformation driven by the development of innovative software and analytical platforms. However, the complexity and variety of the chemical components present in different food types, and the diversity of interactions in the biochemical networks and biological systems, makes nutrition research a complicated field. Metabolomics science is an "-omic", joining proteomics, transcriptomics, and genomics in affording a global understanding of biological systems. In this review, we present the main metabolomics approaches, and highlight the applications and the potential for metabolomics approaches in advancing nutritional food research.

A Rapid and Accurate 1HNMR Method for the Identification and Quantification of Major Constituents in Qishen Yiqi Dripping Pills

BACKGROUND

Qishen Yiqi dripping pills (QSYQ), composed of four herbal medicines-Salvia miltiorrhiza, Astragalus membranaceus, Panax notoginseng, and Dalbergiaodorifera-are widely used to treat ischemic cerebrovascular and hemorrhagic cerebrovascular conditions.

OBJECTIVE

In this study, a rapid and accurate proton NMR (1HNMR) spectroscopy method was established to control the quality of QSYQ and ensure their clinical efficacy.

METHOD

Firstly, different types of metabolites were identified based on the proton signal peaks of chemical shifts, coupling constants, and related information provided through two-dimensional NMR spectroscopy. Secondly, a quantitative 1HNMR method was established for the simultaneous determination of major constituents in QSYQ samples. In addition, an HPLC method was performed to verify the results obtained by the quantitative proton NMR (qHNMR)  method.

RESULTS

In the present study, 26 metabolites were identified in the 1HNMR spectra of QSYQ. In addition, a rapid and accruate qHNMR method was established for the simultaneous determination of protocatechualdehyde, rosmarinic acid, danshensu, calycosin-7-O-β-D-glucoside, and ononin in ten batches of QSYQ samples for the first time. Moreover, the proposed qHNMR method and HPLC method were compared using Bland-Altman and plots Passing-Bablok regression, indicating no significant differences and a strong correlation between the two analytical methods.

CONCLUSIONS

This method is an important tool for the identification and quantification of major constituents in QSYQ.

HIGHLIGHTS

Compared with traditional HPLC, the established qHNMR method has the advantages of simple sample preparation, short analysis time, and non-destructive analysis.

Relaxometric learning: a pattern recognition method for T2 relaxation curves based on machine learning supported by an analytical framework

Nuclear magnetic resonance (NMR)-based relaxometry is widely used in various fields of research because of its advantages such as simple sample preparation, easy handling, and relatively low cost compared with metabolomics approaches. However, there have been no reports on the application of the T₂ relaxation curves in metabolomics studies involving the evaluation of metabolic mixtures, such as geographical origin determination and feature extraction by pattern recognition and data mining. In this study, we describe a data mining method for relaxometric data (i.e., relaxometric learning). This method is based on a machine learning algorithm supported by the analytical framework optimized for the relaxation curve analyses. In the analytical framework, we incorporated a variable optimization approach and bootstrap resampling-based matrixing to enhance the classification performance and balance the sample size between groups, respectively. The relaxometric learning enabled the extraction of features related to the physical properties of fish muscle and the determination of the geographical origin of the fish by improving the classification performance. Our results suggest that relaxometric learning is a powerful and versatile alternative to conventional metabolomics approaches for evaluating fleshiness of chemical mixtures in food and for other biological and chemical research requiring a nondestructive, cost-effective, and time-saving method.

Influence of Storage Conditions on the Quality, Metabolites, and Biological Activity of Soursop (Annona muricata. L.) Kombucha

Kombucha is a slightly alcoholic beverage produced using sugared tea via fermentation using the symbiotic culture of bacteria and yeast (SCOBY). This study aimed to optimize the production of soursop kombucha and determine the effects of different storage conditions on the quality, metabolites, and biological activity. The response surface method (RSM) results demonstrated that the optimum production parameters were 300 ml soursop juice, 700 ml black tea, and 150 g sugar and 14 days fermentation at 28°C. The storage conditions showed significant (P < 0.05) effects on the antioxidant activity including the highest antioxidant activity for the sample stored for 14 days at 25°C in light and the highest total phenolic content (TPC) for the sample stored for 7 days at 4°C in the dark. No significant effects were observed on the antimicrobial activity of soursop kombucha toward Escherichia coli and Staphylococcus aureus. The microbial population was reduced from the average of 106 CFU/ml before the storage to 104 CFU/ml after the storage at 4 and 25°C in dark and light conditions. The metabolites profiling demonstrated significant decline for the sucrose, acetic acid, gluconic acid, and ethanol, while glucose was significantly increased. The storage conditions for 21 days at 25°C in the dark reduced 98% of ethanol content. The novel findings of this study revealed that prolonged storage conditions have high potential to improve the quality, metabolites content, biological activity, and the Halal status of soursop kombucha.

1H NMR-based metabolomics for the discrimination of celery (Apium graveolens L. var. dulce) from different geographical origins

Celery (Apium graveolens L. var dulce) is a widely cultivated vegetable which is popularly consumed due to its nutrient content and contains bioactive metabolites with positive effects on human physiology. In this study, ¹H NMR spectroscopy coupled with multivariate statistical analyses was used to distinguish celery stem and leaf samples from different geographical origins. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were employed to investigate the differences between celery extracts from three geographical origins: Australia, Taiwan and China. Sugars, amino acids and organic acids were found to contribute significantly to the differentiation between origins, with mannitol identified as an important discriminating metabolite. It was demonstrated that NMR-based metabolomics is an effective approach for establishing reliable metabolomic fingerprints and profiles, enabling the identification of metabolite biomarkers for the possible discrimination of geographical origin.

Biochar for urban agriculture: Impacts on soil chemical characteristics and on Brassica rapa growth, nutrient content and metabolism over multiple growth cycles

With possible food crises looming in the near future, urban farming, including small-scale community and home gardens for home consumption, presents a promising option to improve food security in cities. These small-scale farms and gardens often use planter boxes and raised beds filled with lightweight soil or potting mixes. While previous studies on biochar focused on its application on large-scale contiguous farmlands, this study aimed to evaluate the suitability of biochar as a partial soil substitute to produce a durable and lightweight soil-biochar mix for small-scale urban farms. The effects of biochar on the chemical properties of the soil-biochar mix, crop yield and, particularly, crop nutrients and metabolic content were assessed. A germination test using pak choi seeds (Brassica rapa L. cultivar group Pak choi, Green-Petioled Form) showed that the biochar contained phytostimulants. Through a nursery pot experiment over four growth cycles, biochar treatments performed better than pure soil at retaining water-soluble NO₃^- and K⁺ ions, but were worse at retaining PO₄^3- ions. Nonetheless, despite its positive effect on soil NO₃^- retention, biochar application did not improve crop yield significantly when the application rate varied from 0% to 60% (v/v). Untargeted metabolomic analyses showed that biochar application may increase the production of carbohydrates and certain flavonoids and glucosinolates. The results of this study showed that biochar can potentially be used to improve pak choi nutritional values and applied in large quantity to obtain a lightweight soil mix for urban farming.

Typicality Assessment of Onions (Allium cepa) from Different Geographical Regions Based on the Volatile Signature and Chemometric Tools

Onion (Allium cepa L.) is one of the main agricultural commodities produced and consumed around the world. In the present work, for the first time, the volatile signature of onions from different geographical regions of Madeira Island (Caniço, Santa Cruz, Ribeira Brava, and Porto Moniz) was tested with headspace solid-phase microextraction (HS-SPME/GC-qMS) and chemometric tools, showing that the volatile signature was affected by the geographical region of cultivation. Sulfur compounds, furanic compounds, and aldehydes are the most dominant chemical groups. Some of the identified volatile organic metabolites (VOMs) were detected only in onions cultivated in specific regions; 17 VOMs were only identified in onions cultivated at Caniço, eight in Porto Moniz, two in Santa Cruz, two in Ribeira Brava, while 12 VOMs are common to all samples from the four regions. Moreover, some VOMs belonging to sulfur compounds (dipropyl disulfide, 3-(acetylthio)-2-methylfuran), furanic compounds (dimethylmethoxyfuranone, ethyl furanone, acetyloxy-dimethylfuranone), and lactones (whiskey lactone isomer), could be applied as potential geographical markers of onions, providing a useful tool to authenticate onions by farming regions where the influence of latitude seems to be an important factor for yielding the chemical profile and may contribute to geographical protection of food and simultaneously benefiting both consumers and farmers.

Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles

Soybean (Glycine max) is a major crop cultivated in various regions and consumed globally. The formation of volatile compounds in soybeans is influenced by the cultivar as well as environmental factors, such as the climate and soil in the cultivation areas. This study used gas chromatography-mass spectrometry (GC-MS) combined by headspace solid-phase microextraction (HS-SPME) to analyze the volatile compounds of soybeans cultivated in Korea, China, and North America. The multivariate data analysis of partial least square-discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA) were then applied to GC-MS data sets. The soybeans could be clearly discriminated according to their geographical origins on the PLS-DA score plot. In particular, 25 volatile compounds, including terpenes (limonene, myrcene), esters (ethyl hexanoate, butyl butanoate, butyl prop-2-enoate, butyl acetate, butyl propanoate), aldehydes (nonanal, heptanal, (E)-hex-2-enal, (E)-hept-2-enal, acetaldehyde) were main contributors to the discrimination of soybeans cultivated in China from those cultivated in other regions in the PLS-DA score plot. On the other hand, 15 volatile compounds, such as 2-ethylhexan-1-ol, 2,5-dimethylhexan-2-ol, octanal, and heptanal, were related to Korean soybeans located on the negative PLS 2 axis, whereas 12 volatile compounds, such as oct-1-en-3-ol, heptan-4-ol, butyl butanoate, and butyl acetate, were responsible for North American soybeans. However, the multivariate statistical analysis (PLS-DA) was not able to clearly distinguish soybeans cultivated in Korea, except for those from the Gyeonggi and Kyeongsangbuk provinces.

Analysis of Primary Metabolites in Cabbage (Brassica oleracea var. capitata) Varieties Correlated with Antioxidant Activity and Taste Attributes by Metabolic Profiling

Brassica vegetables, such as cabbage, have many health benefits arising from their antioxidant and anticancer properties. These properties are endowed by the metabolite composition of the plant, and it is therefore important to elucidate the metabolic profile and associated activities in this genus. This study objectively evaluated the characteristics of cabbage varieties using metabolic profiling to identify the primary metabolic components that correlate with antioxidant activity and taste attributes. GC-MS analysis was used to identify the primary metabolites. Antioxidant activity was measured by oxygen radical absorbance capacity (ORAC) and 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) scavenging assays, and an electronic tongue was used to quantitate nine taste attributes. Orthogonal projections to latent structures (OPLS) using SIMCA 14 correlated the metabolite components with the taste and antioxidant characteristics. We identified 4-aminobutyric acid, fructose 1-phosphate, adipic acid, 5-oxoproline, N-acetylglycine, O-phosphoethanolamine, and homovanillic acid as important determinants of DPPH scavenging activity and umami, sourness, acidic bitterness, irritant and saltiness, bitterness, astringency, and richness, respectively. These metabolites represent markers indicating breed differences and contribute to differential cabbage functionality. These studies could be extended to measure additional metabolites, as well as to understand the role of growth conditions on the metabolic profile and health benefits of plants.

Influence of drought stress on bioactive compounds, antioxidant enzymes and glucosinolate contents of Chinese cabbage (Brassica rapa)

This study investigated the effects of drought stress on Chinese cabbage (Chcab) by measuring plant growth responses, total antioxidant enzyme activities, the contents of bioactive compounds including glucosinolates (GLS, aliphatic and indolic), and binding with human serum albumin (HSA). Forty-day-old Chinese cabbage (Brassica rapa L. ssp. pekinensis) seedlings were transplanted into pots and maintained for three weeks at 10% (drought-treated, D-T) and 30% (control, C) soil water. The total leaf number, leaf area, and fresh and dry weights were significantly lower in D-T Chcab than in controls. Total GLSs and catalase activities were found to be significantly higher in D-T Chcab than in controls. Indolic GLSs were significantly higher than aliphatic GLSs in D-T Chcab. These results show that D-T Chcab reduced growth parameters and binding properties with HSA and influenced total contents of GLSs, polyphenols, flavonoids, total antioxidant enzyme activities, catalase and peroxidase.

Highly geographical specificity of metabolomic traits among Korean domestic soybeans (Glycine max)

Classification and characterization of agricultural products at molecular levels are important but often impractical with genotyping, particularly for soybeans that have numerous types of variety and landraces. Alternatively, metabolic signature, a determinant for nutritional value, can be the good molecular indicator, which reflects cultivation region-dependent factors such as climate and soil. Accordingly, we analyzed the integrative metabolic profiles of Korean soybeans cultivated in 7 different provinces (representative production areas), and explored the potential association with geographic traits. A total of 210 primary and secondary metabolites were profiled using gas-chromatography time-of-flight mass spectrometry (GC-TOF MS) and liquid-chromatography Orbitrap mass spectrometry (LC-Orbitrap MS). Despite the partial heterogeneity of the soybean varieties, the metabolomic phenotypic analysis based on multivariate statistics inferred the chemical compositional characteristics was primarily governed by the regional specificity. The OPLS-DA model proposed biomarker cluster re-composed with 5 metabolites (tryptophan, malonylgenistin, malonyldaidzin, N-acetylornithine, and allysine) (AUCs = 0.870-1.0). The most distinctive metabolic profiles were identified with the soybeans of Gunsan (middle-western coast) and Daegu (east-southern inland area), which were best characterized by the highest contents of isoflavones and amino acids, respectively. Further interrogation on geographic data suggested the combinatorial association of region-specific metabolic features with general soil texture and climate traits (total rainfall and average annual temperature).

Phenolic variation among Chamaecrista nictitans subspecies and varieties revealed through UPLC-ESI(-)-MS/MS chemical fingerprinting

INTRODUCTION

Comparative analysis of metabolic features of plants has a high potential for determination of quality control of active ingredients, ecological or chemotaxonomic purposes. Specifically, the development of efficient and rapid analytical tools that allow the differentiation among species, subspecies and varieties of plants is a relevant issue. Here we describe a multivariate model based on LC-MS/MS fingerprinting capable of discriminating between subspecies and varieties of the medicinal plant Chamaecrista nictitans, a rare distributed species in Costa Rica.

METHODS

Determination of the chemical fingerprint was carried out on a LC-MS (ESI-QTOF) in negative ionization mode, main detected and putatively identified compounds included proanthocyanidin oligomers, several flavonoid C- and O-glycosides, and flavonoid acetates. Principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA) and cluster analysis of chemical profiles were performed.

RESULTS

Our method showed a clear discrimination between the subspecies and varieties of Chamaecrista nictitans, separating the samples into four fair differentiated groups: M1 = C. nictitans ssp. patellaria; M2 = C. nictitans ssp. disadena; M3 = C. nictitans ssp. nictitans var. jaliscensis and M4 = C. nictitans ssp. disadena var. pilosa. LC-MS/MS fingerprint data was validated using both morphological characters and DNA barcoding with ITS2 region. The comparison of the morphological characters against the chemical profiles and DNA barcoding shows a 63% coincidence, evidencing the morphological similarity in C. nictitans. On the other hand, genetic data and chemical profiles grouped all samples in a similar pattern, validating the functionality of our metabolomic approach.

CONCLUSION

The metabolomic method described in this study allows a reliably differentiation between subspecies and varieties of C. nictitans using a straightforward protocol that lacks extensive purification steps.

Nuclear Magnetic Resonance (NMR) Spectroscopy in Food Science: A Comprehensive Review

Nuclear magnetic resonance (NMR) spectroscopy is a robust method, which can rapidly analyze mixtures at the molecular level without requiring separation and/or purification steps, making it ideal for applications in food science. Despite its increasing popularity among food scientists, NMR is still an underutilized methodology in this area, mainly due to its high cost, relatively low sensitivity, and the lack of NMR expertise by many food scientists. The aim of this review is to help bridge the knowledge gap that may exist when attempting to apply NMR methodologies to the field of food science. We begin by covering the basic principles required to apply NMR to the study of foods and nutrients. A description of the discipline of chemometrics is provided, as the combination of NMR with multivariate statistical analysis is a powerful approach for addressing modern challenges in food science. Furthermore, a comprehensive overview of recent and key applications in the areas of compositional analysis, food authentication, quality control, and human nutrition is provided. In addition to standard NMR techniques, more sophisticated NMR applications are also presented, although limitations, gaps, and potentials are discussed. We hope this review will help scientists gain some of the knowledge required to apply the powerful methodology of NMR to the rich and diverse field of food science.

Food fingerprints - A valuable tool to monitor food authenticity and safety

In recent years, food frauds and adulterations have increased significantly. This practice is motivated by fast economical gains and has an enormous impact on public health, representing an important issue in food science. In this context, this review has been designed to be a useful guide of potential biomarkers of food authenticity and safety. In terms of food authenticity, we focused our attention on biomarkers reported to specify different botanical or geographical origins, genetic diversity or production systems, while at the food safety level, molecular evidences of food adulteration or spoilage will be highlighted. This report is the first to combine results from recent studies in a format that allows a ready overview of metabolites (<1200 Da) and potentially molecular routes to monitor food authentication and safety. This review has therefore the potential to unveil important aspects in food adulteration and safety, contributing to improve the current regulatory frameworks.

1H NMR-based metabolomics profiling of ten new races from Capsicum annuum cv. serrano produced in Mexico

Herein we report on the ¹H NMR-based metabolomics profiling of ten new races of Capsicum annuum cv. serrano, cultivated in Mexico. Forty eight metabolites (including sugars, amino acids, organic acids, polyphenolic acids and alcohols) were identified and quantified by 2D NMR and qNMR, respectively. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) separated the ten races into two clusters, from which citric acid, formic acid, fumaric acid, malic acid, glucose, fructose, sucrose and galactose were found as differential metabolites. This is the first study describing the chemical profiling of ten new races of Capsicum annuum cv. serrano and the spectrometric method used presently is characterized by great simplicity, robustness and reproducibility. Thus, this technique can be used for establishing reliable metabolomic fingerprints of different races of Capsicum annuum cv. serrano.

Comparative metabolomics of Japanese Black cattle beef and other meats using gas chromatography-mass spectrometry

Progress in metabolomic analysis now allows the evaluation of food quality. This study aims to identify the metabolites in meat from livestock using a metabolomic approach. Using gas chromatography-mass spectrometry (GC/MS), many metabolites were reproducibly detected in meats, and distinct differences between livestock species (cattle, pigs, and chickens) were indicated. A comparison of metabolites between tissues types (muscle, intramuscular fat, and intermuscular fat) in marbled beef of Japanese Black cattle revealed that most metabolites are abundant in the muscle tissue. Several metabolites (medium-chain fatty acids, etc.) involved in triacylglycerol synthesis were uniquely detected in fat tissue. Additionally, the results of multivariate analysis suggest that GC/MS analysis of metabolites can distinguish between cattle breeds. These results provide useful information for the analysis of meat quality using GC/MS-based metabolomic analysis.ABBREVIATIONS: GC/MS: gas chromatography-mass spectrometry; NMR: nuclear magnetic resonance; MS: mass spectrometry; IS: 2-isopropylmalic acid; MSTFA: N-Methyl-N-trimethylsilyltrifluoroacetamide; CV: coefficient of variation; TBS: Tris-buffered saline; MHC: myosin fast type; PCA: principal component analysis; OPLS-DA: orthogonal partial least-squares discriminant analysis; O2PLS: two-way orthogonal partial least-squares.

Identification of redox imbalance as a prominent metabolic response elicited by rapeseed feeding in swine metabolome

Rapeseed (RS) is an abundant and inexpensive source of energy and AA in diets for monogastrics and a sustainable alternative to soybean meal. It also contains diverse bioactive phytochemicals that could have antinutritional effects at high dose. When the RS-derived feed ingredients (RSF) are used in swine diets, the uptake of these nutrients and phytochemicals is expected to affect the metabolic system. In this study, 2 groups of young pigs (17.8 ± 2.7 kg initial BW) were equally fed a soybean meal-based control diet and an RSF-based diet, respectively, for 3 wk. Digesta, liver, and serum samples from these pigs were examined by liquid chromatography-mass spectrometry-based metabolomic analysis to determine the metabolic effects of the 2 diets. Analyses of digesta samples revealed that sinapine, sinapic acid, and gluconapin were robust exposure markers of RS. The distribution of free AA along the intestine of RSF pigs was consistent with the reduced apparent ileal digestibility of AA observed in these pigs. Despite its higher fiber content, the RSF diet did not affect microbial metabolites in the digesta, including short-chain fatty acids and secondary bile acids. Analyses of the liver and serum samples revealed that RSF altered the levels of AA metabolites involved in the urea cycle and 1-carbon metabolism. More importantly, RSF increased the levels of multiple oxidized metabolites and aldehydes while decreased the levels of ascorbic acid and docosahexaenoic acid-containing lipids in the liver and serum, suggesting that RSF could disrupt redox balance in young pigs. Overall, the results indicated that RSF elicited diverse metabolic events in young pigs through its influences on nutrient and antioxidant metabolism, which might affect the performance and health in long-term feeding and also provide the venues for nutritional and processing interventions to improve the utilization of RSF in pigs.

Metabolite characterization of different palm date varieties and the correlation with their NO inhibitory activity, texture and sweetness

The aim of this study was to examine the variation in metabolite constituents of five commercial varieties of date fruits; Ajwa, Safawi and Ambar which originated from Madinah, the Iranian Bam and Tunisian Deglet Noor. The differences of metabolome were investigated using proton nuclear magnetic resonance (1H NMR) spectroscopy combined with multivariate data analysis (MVDA). Principal Component Analysis (PCA) revealed clear separation between the date varieties. The Tunisian Deglet Noor demonstrated distinct cluster from the rest of the palm date samples based on the metabolite composition as shown by the pattern observed in Hierarchical Clustering Analysis (HCA) and PCA. Deglet Noor exhibited a significant higher level of sucrose (δ 5.40) and fructose (δ 4.16) in comparison with the other four varieties which can be associated with the distinctive sweet taste of this variety. Dates originated from Madinah and Tunisia exhibited a contrast manner in the amount of xylose and moisture content. These two aspects may contribute towards the soft texture of Tunisian dates. All Madinah dates were found to contain phenolic compounds which were well established as great antioxidant and anti-inflammatory agent. Ajwa dates exerted greater effect in inhibiting the generation of nitric oxide (NO) from the stimulated RAW264.7 cells at 95.37% inhibition. Succinic acid was suggested to have the most significant correlation with the trend of NO inhibitory shown by the selected date palm varieties.

Environmental metabolomics with data science for investigating ecosystem homeostasis

A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems, understanding what benefits humans receive by facilitating the maintenance of environmental homeostasis is important. This review describes recent applications of several NMR approaches to the evaluation of environmental homeostasis by metabolic profiling and data science. The basic NMR strategy used to evaluate homeostasis using big data collection is similar to that used in human health studies. Sophisticated metabolomic approaches (metabolic profiling) are widely reported in the literature. Further challenges include the analysis of complex macromolecular structures, and of the compositions and interactions of plant biomass, soil humic substances, and aqueous particulate organic matter. To support the study of these topics, we also discuss sample preparation techniques and solid-state NMR approaches. Because NMR approaches can produce a number of data with high reproducibility and inter-institution compatibility, further analysis of such data using machine learning approaches is often worthwhile. We also describe methods for data pretreatment in solid-state NMR and for environmental feature extraction from heterogeneously-measured spectroscopic data by machine learning approaches.

A multifactorial approach in characterizing geographical origin of Sicilian cherry tomatoes using 1H-NMR profiling

In this study, metabolomic analysis of chloroform extracts was performed to characterize cherry tomatoes (cv Naomi and Shiren) grown in different Sicilian areas, using ¹H NMR spectroscopy coupled with multivariate statistical analysis. Principal components analysis showed clear discrimination between extracts of cherry tomatoes cultivated in two different seasons (winter and summer) and grown in three areas of Sicily (Gela, Licata, Pachino). In particular, carotenoids and phospholipids mainly were found to be more discriminating metabolites for both cultivars in summer and winter. In the present study, the simple separation only based on production area was found to be inadequate to distinguish the three groups of tomatoes. A clear separation among the different samples groups was obtained using a multifactorial approach not only based on the geographical origin classification, but considering also cultivar, year and seasonality.

Characterization of metabolites in different kiwifruit varieties by NMR and fluorescence spectroscopy

It is known from our previous studies that kiwifruits, which are used in common human diet, have preventive properties of coronary artery disease. This study describes a combination of ¹H NMR spectroscopy, multivariate data analyses and fluorescence measurements in differentiating of some kiwifruit varieties, their quenching and antioxidant properties. A total of 41 metabolites were identified by comparing with literature data Chenomx database and 2D NMR. The binding properties of the extracted polyphenols against HSA showed higher reactivity of studied two cultivars in comparison with the common Hayward. The results showed that the fluorescence of HSA was quenched by Bidan as much as twice than by other fruits. The correlation between the binding properties of polyphenols in the investigated fruits, their relative quantification and suggested metabolic pathway was established. These results can provide possible application of fruit extracts in pharmaceutical industry.

Discrimination and Nitric Oxide Inhibitory Activity Correlation of Ajwa Dates from Different Grades and Origin

This study was aimed at examining the variations in the metabolite constituents of the different Ajwa grades and farm origins. It is also targeted at establishing the correlations between the metabolite contents and the grades and further to the nitric oxide (NO) inhibitory activity. Identification of the metabolites was generated using ¹H-NMR spectroscopy metabolomics analyses utilizing multivariate methods. The NO inhibitory activity was determined using a Griess assay. Multivariate data analysis, for both supervised and unsupervised approaches, showed clusters among different grades of Ajwa dates obtained from different farms. The compounds that contribute towards the observed separation between Ajwa samples were suggested to be phenolic compounds, ascorbic acid and phenylalanine. Ajwa dates were shown to have different metabolite compositions and exhibited a wide range of NO inhibitory activity. It is also revealed that Ajwa Grade 1 from the al-Aliah farm exhibited more than 90% NO inhibitory activity compared to the other grades and origins. Phenolic compounds were among the compounds that played a role towards the greater capacity of NO inhibitory activity shown by Ajwa Grade 1 from the al-Aliah farm.

Discrimination of Polygonatum species and identification of novel markers using (1) H NMR- and UPLC/Q-TOF MS-based metabolite profiling

BACKGROUND

Rhizomes of Polygonatum species are commonly used as herbal supplements in Asia. They have different medicinal effects by species but have been misused and mixed owing to their similar taste and smell. Therefore accurate and reliable analytical methods to discriminate between Polygonatum species are required.

RESULTS

In this study, global and targeted metabolite profiling using (1) H nuclear magnetic resonance ((1) H NMR) spectroscopy and ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS) was applied to discriminate between different Polygonatum species. Partial least squares discriminant analysis (PLS-DA) models were used to classify and predict species of Polygonatum. Cross-validation derived from PLS-DA revealed good predictive accuracy. Polygonatum species were classified into unique patterns based on K-means clustering analysis. 4-Hydrobenzoic acid and trigonelline were identified as novel marker compounds and quantified accurately.

CONCLUSION

The results demonstrate that metabolite profiling approaches coupled with chemometric analysis can be used to classify and discriminate between different species of various herbal medicines. © 2015 Society of Chemical Industry.

A 1H NMR-based metabolomics approach to evaluate the geographical authenticity of herbal medicine and its application in building a model effectively assessing the mixing proportion of intentional admixtures: A case study of Panax ginseng: Metabolomics for the authenticity of herbal medicine

Ginseng, the root of Panax ginseng has long been the subject of adulteration, especially regarding its origins. Here, 60 ginseng samples from Korea and China initially displayed similar genetic makeup when investigated by DNA-based technique with 23 chloroplast intergenic space regions. Hence, (1)H NMR-based metabolomics with orthogonal projections on the latent structure-discrimination analysis (OPLS-DA) were applied and successfully distinguished between samples from two countries using seven primary metabolites as discrimination markers. Furthermore, to recreate adulteration in reality, 21 mixed samples of numerous Korea/China ratios were tested with the newly built OPLS-DA model. The results showed satisfactory separation according to the proportion of mixing. Finally, a procedure for assessing mixing proportion of intentionally blended samples that achieved good predictability (adjusted R(2)=0.8343) was constructed, thus verifying its promising application to quality control of herbal foods by pointing out the possible mixing ratio of falsified samples.

Recent progress in the use of 'omics technologies in brassicaceous vegetables

Continuing advances in 'omics methodologies and instrumentation is enhancing the understanding of how plants cope with the dynamic nature of their growing environment. 'Omics platforms have been only recently extended to cover horticultural crop species. Many of the most widely cultivated vegetable crops belong to the genus Brassica: these include plants grown for their root (turnip, rutabaga/swede), their swollen stem base (kohlrabi), their leaves (cabbage, kale, pak choi) and their inflorescence (cauliflower, broccoli). Characterization at the genome, transcript, protein and metabolite levels has illustrated the complexity of the cellular response to a whole series of environmental stresses, including nutrient deficiency, pathogen attack, heavy metal toxicity, cold acclimation, and excessive and sub-optimal irradiation. This review covers recent applications of 'omics technologies to the brassicaceous vegetables, and discusses future scenarios in achieving improvements in crop end-use quality.

Changes in the metabolome of lettuce leaves due to exposure to mancozeb pesticide

This paper describes a proton high resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) metabolomic study of lettuce (Lactuca sativa L.) leaves to characterise metabolic adaptations during leaf growth and exposure to mancozeb. Metabolite variations were identified through multivariate analysis and checked through spectral integration. Lettuce growth was accompanied by activation of energetic metabolism, preferential glucose use and changes in amino acids, phospholipids, ascorbate, nucleotides and nicotinate/nicotinamide. Phenylalanine and polyphenolic variations suggested higher oxidative stress at later growth stages. Exposure to mancozeb induced changes in amino acids, fumarate and malate, suggesting Krebs cycle up-regulation. In tandem disturbances in sugar, phospholipid, nucleotide and nicotinate/nicotinamide metabolism were noted. Additional changes in phenylalanine, dehydroascorbate, tartrate and formate were consistent with a higher demand for anti-oxidant defence mechanisms. Overall, lettuce exposure to mancozeb was shown to have a significant impact on plant metabolism, with mature leaves tending to be more extensively affected than younger leaves.

Assessment of constituents in Allium by multivariate data analysis, high-resolution α-glucosidase inhibition assay and HPLC-SPE-NMR

Bulbs and leaves of 35 Allium species and cultivars bought or collected in 2010-2012 were investigated with multivariate data analysis, high-resolution α-glucosidase inhibition assays and HPLC-HRMS-SPE-NMR with the aim of exploring the potential of Allium as a future functional food for management of type 2 diabetes. It was found that 30 out of 106 crude extracts showed more than 80% inhibition of the α-glucosidase enzyme at a concentration of 40mg/mL (dry sample) or 0.4g/mL (fresh sample). High-resolution α-glucosidase biochromatograms of these extracts allowed fast identification of three analytes with α-glucosidase inhibitory activity, and subsequent HPLC-HRMS-SPE-NMR experiments allowed identification of these as N-p-coumaroyloctopamine, N-p-coumaroyltyramine, and quercetin. The distribution of these three compounds was mapped for all samples by HPLC-ESI-HRMS. Unsupervised principal component analysis of samples from 2012 indicated that a major difference between fresh material and dried material is the increased amount of quercetin, a known α-glucosidase inhibitor.

Discrimination of conventional and organic white cabbage from a long-term field trial study using untargeted LC-MS-based metabolomics

The influence of organic and conventional farming practices on the content of single nutrients in plants is disputed in the scientific literature. Here, large-scale untargeted LC-MS-based metabolomics was used to compare the composition of white cabbage from organic and conventional agriculture, measuring 1,600 compounds. Cabbage was sampled in 2 years from one conventional and two organic farming systems in a rigidly controlled long-term field trial in Denmark. Using Orthogonal Projection to Latent Structures–Discriminant Analysis (OPLS-DA), we found that the production system leaves a significant (p = 0.013) imprint in the white cabbage metabolome that is retained between production years. We externally validated this finding by predicting the production system of samples from one year using a classification model built on samples from the other year, with a correct classification in 83 % of cases. Thus, it was concluded that the investigated conventional and organic management practices have a systematic impact on the metabolome of white cabbage. This emphasizes the potential of untargeted metabolomics for authenticity testing of organic plant products.

In vivo and in vitro effects of secondary metabolites against Xanthomonas campestris pv. campestris

Brassica rapa is a crucifer that is grown worldwide, mainly as a vegetable. The quality of B. rapa crops is highly affected by the disease caused by the bacteria Xanthomonas campestris pv. campestris (Xcc). Glucosinolates and phenolic compounds can confer resistance to Brassica crops against pests and diseases, but few works have been done to evaluate their role in Xcc resistance. The objectives of this work were: (1) to evaluate the in vivo and in vitro antibacterial effect of gluconapin, its isothiocyanate and the methanolic extracts of B. rapa against the type 4 of Xcc, and (2) to test if there is induced resistance mediated by glucosinolates or phenolic compounds in two varieties of B. rapa. Gluconapin and its ITC varieties had an antibacterial effect on the development of Xanthomonas and this effect was strongly dependent on the concentration applied. Methanolic extracts from B. rapa, containing glucosinolates and phenolic compounds, inhibited the growth of these bacteria. Concentration of gluconapin is higher in resistant plants than in the susceptible ones and there is an induction of gluconapin, some flavonoids and sinapic acid 48 to 72 h after inoculation. Gluconapin plays a role in the constitutive resistance to Xcc, while gluconapin, some flavonoids and hydroxycinnamic acids are induced by a Xcc infection but it is not clear if this induction confers resistance to this disease.

The use of wavelength dispersive X-ray fluorescence in the identification of the elemental composition of vanilla samples and the determination of the geographic origin by discriminant function analysis

Sixteen elements found in 37 vanilla samples from Madagascar, Uganda, India, Indonesia (all Vanilla planifolia species), and Papa New Guinea (Vanilla tahitensis species) were measured by wavelength dispersive X-ray fluorescence (WDXRF) spectroscopy for the purpose of determining the elemental concentrations to discriminate among the origins. Pellets were prepared of the samples and elemental concentrations were calculated based on calibration curves created using 4 Natl. Inst. of Standards and Technology (NIST) standards. Discriminant analysis was used to successfully classify the vanilla samples by their species and their geographical region. Our method allows for higher throughput in the rapid screening of vanilla samples in less time than analytical methods currently available.

PRACTICAL APPLICATION

Wavelength dispersive X-ray fluorescence spectroscopy and discriminant function analysis were used to classify vanilla from different origins resulting in a model that could potentially serve to rapidly validate these samples before purchasing from a producer.