High-resolution magic angle spinning nuclear magnetic resonance in foodstuff analysis

1H NMR spectroscopy as a tool to probe potential biomarkers of the drying-salting process: A proof-of-concept study with the Amazon fish pirarucu

Dry-salted pirarucu (Arapaima gigas) plays an important cultural role in the Amazon region - South America. In this study, we explored the changes in the chemical composition of pirarucu meat following the drying-salting process via 1H NMR spectroscopy. Combining multivariate and univariate statistical analyses yielded a robust differentiation of metabolites involved in the process. VIP score (>1), p-value (<0.05), and AUC (>0.7) were considered to selecting compounds that had significant fluctuations in their contents along the process. Our results pointed out acetate, lactate, succinate, and creatinine as metabolites undergoing significant changes during the drying-salting process. Creatinine was not detected in fresh samples. The investigation of multiple components delves deeper into the molecular nuances of the salting-drying process's impact on fish meat, providing a more comprehensive understanding of the possible chemical transformations and how the matrix's quality control and nutritional aspects should be addressed.

1H HR-MAS NMR chemical profile and chemometric analysis as a tool for quality control of different cultivars of green tea (Camellia sinensis)

Green tea is a product obtained from the processing of fresh leaves of Camellia sinensis (L.) O. Kuntze species. In this study, the influence of climatic parameters on the chemical composition of green tea cultivars ('Yabukita' and 'Yutakamidori') over the harvest was evaluated using HR-MAS NMR. 'Yabukita' showed higher concentrations of epicatechin while higher amounts of theanine and caffeine were found in 'Yutakamidori'. The decline of theanine was associated with high average maximum temperature and solar radiation index, this latter also seemed to be responsible for relevant changes in epicatechin concentrations. It was not possible to associate any trend between climatic parameters and caffeine concentration. Fluctuations in linolenic acid concentration were monitored during the harvest period and were associated with the plant's defense mechanism. Monitoring of green tea over seasons and correlating the fluctuations of compounds to climatic parameters might become an efficient strategy for establishing quality standards for green teas.

Covalent Organic Frameworks-Based Electrochemical Sensors for Food Safety Analysis

Food safety is a key issue in promoting human health and sustaining life. Food analysis is essential to prevent food components or contaminants causing foodborne-related illnesses to consumers. Electrochemical sensors have become a desirable method for food safety analysis due to their simple, accurate and rapid response. The low sensitivity and poor selectivity of electrochemical sensors working in complex food sample matrices can be overcome by coupling them with covalent organic frameworks (COFs). COFs are a kind of novel porous organic polymer formed by light elements, such as C, H, N and B, via covalent bonds. This review focuses on the recent progress in COF-based electrochemical sensors for food safety analysis. Firstly, the synthesis methods of COFs are summarized. Then, a discussion of the strategies is given to improve the electrochemistry performance of COFs. There follows a summary of the recently developed COF-based electrochemical sensors for the determination of food contaminants, including bisphenols, antibiotics, pesticides, heavy metal ions, fungal toxin and bacterium. Finally, the challenges and the future directions in this field are discussed.

Introducing comprehensive multiphase NMR for the analysis of food: Understanding the hydrothermal treatment of starch-based foods

Cooking is essential for preparing starch-based food, however thermal treatment promotes the complexation of biopolymers, impacting their final properties. Comprehensive Multiphase (CMP) NMR allows all phases (liquids, gels, and solids) to be differentiated and monitored within intact samples. This study acts as a proof-of-principle to introduce CMP-NMR to food research and demonstrate its application to monitor the various phases in spaghetti, black turtle beans, and white long-grain rice, and how they change during the cooking process. When uncooked, only a small fraction of lipids and structurally bound water show any molecular mobility. Once cooked, little "crystalline solid" material is left, and all components exhibit increased molecular dynamics. Upon cooking, the solid-like components in spaghetti contains signals consistent with cellulose that were buried beneath the starches in the uncooked product. Thus, CMP-NMR holds potential for the study of food and related processes involving phase changes such as growth, manufacturing, and composting.

NMR-Based Approaches in the Study of Foods

In this review, the three different NMR-based approaches usually used to study foodstuffs are described, reporting specific examples. The first approach starts with the food of interest that can be investigated using different complementary NMR methodologies to obtain a comprehensive picture of food composition and structure; another approach starts with the specific problem related to a given food (frauds, safety, traceability, geographical and botanical origin, farming methods, food processing, maturation and ageing, etc.) that can be addressed by choosing the most suitable NMR methodology; finally, it is possible to start from a single NMR methodology, developing a broad range of applications to tackle common food-related challenges and different aspects related to foods.

Deep Learning-Based Method for Compound Identification in NMR Spectra of Mixtures

Nuclear magnetic resonance (NMR) spectroscopy is highly unbiased and reproducible, which provides us a powerful tool to analyze mixtures consisting of small molecules. However, the compound identification in NMR spectra of mixtures is highly challenging because of chemical shift variations of the same compound in different mixtures and peak overlapping among molecules. Here, we present a pseudo-Siamese convolutional neural network method (pSCNN) to identify compounds in mixtures for NMR spectroscopy. A data augmentation method was implemented for the superposition of several NMR spectra sampled from a spectral database with random noises. The augmented dataset was split and used to train, validate and test the pSCNN model. Two experimental NMR datasets (flavor mixtures and additional flavor mixture) were acquired to benchmark its performance in real applications. The results show that the proposed method can achieve good performances in the augmented test set (ACC = 99.80%, TPR = 99.70% and FPR = 0.10%), the flavor mixtures dataset (ACC = 97.62%, TPR = 96.44% and FPR = 2.29%) and the additional flavor mixture dataset (ACC = 91.67%, TPR = 100.00% and FPR = 10.53%). We have demonstrated that the translational invariance of convolutional neural networks can solve the chemical shift variation problem in NMR spectra. In summary, pSCNN is an off-the-shelf method to identify compounds in mixtures for NMR spectroscopy because of its accuracy in compound identification and robustness to chemical shift variation.

Metabolic Changes in Serum Metabolome of Beagle Dogs Fed Black Ginseng

The effects of black ginseng, which has many kinds of biological activities, on dogs was investigated. Serum samples of beagle dogs, which were fed with black ginseng for 8 weeks, were measured using high-resolution magic angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectrometry. Acquired NMR data from the serum of dogs fed for 0, 4, and 8 weeks were analyzed by metabolic profiling and multivariate statistical analysis. In statistical analysis and biomarker analysis results of metabolite profiles, formate, glutamine, histidine, isoleucine, leucine, proline, and valine had variable importance in projection (VIP) scores above 1.0 and excellent area under the curve (AUC) values of receiver operating characteristic (ROC) curves above 0.9. In the result of multivariate statistical analysis, the score plot showed the discrimination between before and after feeding of black ginseng. These differences in metabolic profiles are considered to be due to the involvement of metabolic processes following black ginseng administration, such as enhancing immunity and energy metabolism. Through metabolomics analysis, we confirmed the biological efficacy of black ginseng in dogs and also confirmed that metabolomics can be applied to the pet health industry.

High-Resolution Magic Angle Spinning (HR-MAS) NMR-Based Fingerprints Determination in the Medicinal Plant Berberis laurina

Berberis laurina (Berberidaceae) is a well-known medicinal plant used in traditional medicine since ancient times; however, it is scarcely studied to a large-scale fingerprint. This work presents a broad-range fingerprints determination through high-resolution magical angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy, a well-established flexible analytical method and one of most powerful "omics" platforms. It had been intended to describe a large range of chemical compositions in all plant parts. Beyond that, HR-MAS NMR allowed the direct investigation of botanical material (leaves, stems, and roots) in their natural, unaltered states, preventing molecular changes. The study revealed 17 metabolites, including caffeic acid, and berberine, a remarkable alkaloid from the genus Berberis L. The metabolic pattern changes of the leaves in the course of time were found to be seasonally dependent, probably due to the variability of seasonal and environmental trends. This metabolites overview is of great importance in understanding plant (bio)chemistry and mediating plant survival and is influenceable by interacting environmental means. Moreover, the study will be helpful in medicinal purposes, health sciences, crop evaluations, and genetic and biotechnological research.

High-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) as a tool in the determination of biomarkers of Passiflora-based herbal medicines

High-resolution magic-angle spinning nuclear magnetic resonance spectroscopy (HR-MAS NMR) for the identification of the metabolic profile of plants under conditions very close to that in which the compounds are present in the matrix, the herbal medicines in this case. This enables selectivity in the determination of the active principle and other biomarkers present in the complex matrix, avoiding degradation products, which may occur in the extractive processes required in several analytical methods. In this study, HR-MAS analysis was applied in the quality control of seven Passiflora-based herbal medicines, using metabolic fingerprinting to confirm plant species and identify biomarkers. Vitexin and isovitexin were identified as major compounds in three of these herbal medicines (0.17 to 0.55%), while salicin was the majority in two others. On the other hand, no significant flavonoid contents were observed in the remaining two. In addition, it was possible to detect ethanol, a non-target compound, in all herbal medicines in concentrations varying between 0.009 and 0.342%. In this way, combined with chemometrics ¹H HR-MAS NMR proved to be suitable for the qualitative and quantitative study of Passiflora biomarkers, using a minimal pre-treatment of the sample.

Metabolomic Profiling of Wildtype and Transgenic Giardia lamblia Strains by 1H HR-MAS NMR Spectroscopy

Giardia lamblia, a causative agent of persistent diarrhea in humans, domestic animals, and cattle, is usually treated with nitro compounds. Consequently, enzymes involved in anaerobic nitro reduction have been investigated in detail as potential targets. Their role within the normal metabolic context is, however, not understood. Using ¹H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy, we analyzed the metabolomes of G. lamblia trophozoites overexpressing three nitroreductases (NR1–NR3) and thioredoxin reductase (TrxR), most likely a scavenger of reactive oxygen species, as suggested by the results published in this study. We compared the patterns to convenient controls and to the situation in the nitro drug resistant strain C4 where NR1 is downregulated. We identified 27 metabolites in G. lamblia trophozoites. Excluding metabolites of high variability among different wildtype populations, only trophozoites overexpressing NR1 presented a distinct pattern of nine metabolites, in particular arginine catabolites, differing from the respective controls. This pattern matched a differential pattern between wildtype and strain C4. This suggests that NR1 interferes with arginine and thus energy metabolism. The exact metabolic function of NR1 (and the other nitroreductases) remains to be elucidated.

Metabolic response of soybean plants to Sclerotinia sclerotiorum infection

White mold is a disease caused by the fungus Sclerotinia sclerotiorum, a highly destructive necrotrophic pathogen that infects soybean crops, among others. Usually, the infection triggers the plant defense system to minimize the damages. However, the effects of the infection on soybean plant metabolism are still unclear. In this work, the metabolic profiles of soybean stems and leaves were accessed using 1H HR-MAS NMR spectroscopy to identify metabolic changes as a response to S. sclerotiorum infection. This fungus widely affects the central metabolism of soybean plants, and most of the altered metabolites are involved in carbon metabolism, as suggested by the results. Furthermore, the metabolites of central metabolism can be associated with the production of several polyphenolic metabolites. Changes in metabolic profile of leaves indicate systemic effects.

High-resolution magic angle spinning nuclear magnetic resonance (HR-MAS-NMR) as quick and direct insight of almonds

Almonds are the tasty seeds of Prunus dulcis plants globally appreciated for the pleasant palatability and remarkable nutritional value, therefore it is very spread as snack and as basic ingredient of the confectionery products. The HR-MAS-NMR is a simple spectroscopy able to directly and quickly explore the chemical composition of powdered seed samples dispersed in D₂O. ¹H spectra witness the remarkable presence of triglyceride fatty esters together with sucrose; other minor water soluble metabolites are also detectable. This very rough approach is effectively providing chemical profiles featuring almond samples. In this analysis we were able to statistically distinguish the "Avola" almonds from other marketed products submitted to the same analysis. This is just a first investigation based on the main compounds but it might pave the way toward the quantitative evaluation of many other compounds in the almond therefore implementing the HR-MAS-NMR knowledge of these precious seeds.

Important issues in plant tissues analyses by HR-MAS NMR

INTRODUCTION

High-resolution magic-angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy enables the analysis of the metabolic profile of plant and animal tissues under close to natural conditions, as well as of other heterogeneous natural or synthetic materials. Neither sample pretreatment is required after fragmentation nor powdering of the sample before insertion into the rotor. However, the efficiency of the method depends strongly on the sample preparation, rotor insertion procedure, and analysis conditions.

OBJECTIVE

To identify some of the variables that affect the spectral data and to propose solutions that minimise their impact on the quality of the analyses and results.

METHODS

Dried plant tissues were powdered, weighed, and homogenised in a 50 μL rotor with an optimised volume of deuterated solvent and sample in order to prevent material from escaping during spacer insertion, avoiding variations in magnetic susceptibility. Factors affecting the quality of HR-MAS NMR analysis such as particle size, sample and solvent amounts, solvent polarity, swelling time, rotor manipulation and pulse sequence setting were evaluated.

RESULTS

A strong correlation was observed between the signal area and the particle size of the powdered sample. The spectral profile varied depending on the deuterated solvent used. An incubation period was necessary to achieve adequate swelling of the sample and to ensure good data reproducibility. Proper sealing of the rotor, number of cycles and τ time on cpmgpr1d pulse sequence were found to affect the signal areas.

CONCLUSION

The study highlights the need for standardised sample preparation and instrumental setup protocols in order to achieve high reproducibility and obtain reliable data from HR-MAS NMR analyses.

The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research

Covering: up to 2018With contributions from the global natural product (NP) research community, and continuing the Raw Data Initiative, this review collects a comprehensive demonstration of the immense scientific value of disseminating raw nuclear magnetic resonance (NMR) data, independently of, and in parallel with, classical publishing outlets. A comprehensive compilation of historic to present-day cases as well as contemporary and future applications show that addressing the urgent need for a repository of publicly accessible raw NMR data has the potential to transform natural products (NPs) and associated fields of chemical and biomedical research. The call for advancing open sharing mechanisms for raw data is intended to enhance the transparency of experimental protocols, augment the reproducibility of reported outcomes, including biological studies, become a regular component of responsible research, and thereby enrich the integrity of NP research and related fields.

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.

1H HR-MAS NMR spectroscopy to study the metabolome of the protozoan parasite Giardia lamblia

Knowledge of the metabolic profile and exchange processes in the protozoan parasite Giardia lamblia is of importance for a better understanding of the biochemical processes and for the development of drugs to control diseases caused by G. lamblia. In the current paper, ¹H High Resolution Magic Angle Spinning (HR-MAS) NMR spectroscopy was directly applied to G. lamblia trophozoite suspensions to analyze the detectable small metabolites with a minimum of intervention. Thirty-one components were identified with main contributions from amino acids such as alanine and ornithine. The reproducibility, variability, and stability of the metabolites were investigated. Citrulline was found to be formed as an intermediate and citrulline levels depended on the stage of cell growth. Glucose-1-phosphate was found to be formed in relatively high amounts after cell harvesting if enzymes were not inactivated. In addition, the metabolic footprint of Giardia trophozoites, i.e. changes in the culture medium induced by G. lamblia, was investigated by liquid state NMR spectroscopy of culture media before and after inoculation. A quantitative comparison of the NMR spectra revealed component changes in the culture media during growth. The results suggested that not glucose but rather arginine serves as main energy supply. Biochemical functions of intracellular components and their metabolic exchange with the culture medium are discussed. The results provide an important basis for the design of HR-MAS NMR based metabolomic studies of G. lamblia in particular and any protozoan parasite samples in general.

Integrating High-Resolution and Solid-State Magic Angle Spinning NMR Spectroscopy and a Transcriptomic Analysis of Soybean Tissues in Response to Water Deficiency

INTRODUCTION

Solid-state NMR (SSNMR) spectroscopy methods provide chemical environment and ultrastructural details that are not easily accessible by other non-destructive, high-resolution spectral techniques. High-resolution magic angle spinning (HR-MAS) has been widely used to obtain the metabolic profile of a heterogeneous sample, combining the resolution enhancement provided by MAS in SSNMR with the shimming and locking procedures in liquid-state NMR.

OBJECTIVE

In this work, we explored the feasibility of using the HR-MAS and SSNMR techniques to identify metabolic changes in soybean leaves subjected to water-deficient conditions.

METHODOLOGY

Control and water-deficient soybean leaves were analysed using one-dimensional (1D) HR-MAS and SSNMR. Total RNA was extracted from the leaves for the transcriptomic analysis.

RESULTS

The 1 H HR-MAS and CP-MAS 13 C{1 H} spectra of soybean leaves grown with and without water deficiency stress revealed striking differences in metabolites. A total of 30 metabolites were identified, and the impact of water deficiency on the metabolite profile of soybean leaves was to induce amino acid synthesis. High expression levels of genes required for amino acid biosynthesis were highly correlated with the compounds identified by 1 H HR-MAS.

CONCLUSIONS

The integration of the 1 H HR-MAS and SSNMR spectra with the transcriptomic data provided a complete picture of the major changes in the metabolic profile of soybeans in response to water deficiency. Copyright © 2017 John Wiley & Sons, Ltd.

1H HR-MAS NMR-based metabolomics study of different persimmon cultivars (Diospyros kaki) during fruit development

¹H HR-MAS NMR spectroscopy was used to track the metabolic changes throughout the whole development of astringent ('Giombo') and non-astringent ('Fuyu') cultivars of persimmon (Diospyros kaki). The NMR data revealed the low concentration of amino acids (threonine, alanine, citrulline and GABA) and organic acids (malic acid). In addition, the signals of carbohydrates (sucrose, glucose and fructose) seemed to play the most important role in the fruit development. In both cultivars, the growth was characterized by fluctuating sucrose concentration along with a constant increase in both glucose and fructose. In the initial growth stage, the polyphenol composition was quite different between the cultivars. Gallic acid was detected throughout the growth of 'Giombo', while for 'Fuyu', signals of polyphenols disappeared over time. Additional multivariate analysis suggested that these cultivars share many metabolic similarities during development. These findings might help the comprehension of fruit development, which in turn, impacts the quality of the fruits.