The NMR added value to the Green Foodomics perspective: advances by machine learning to the holistic view on food and nutrition

Food is a complex matter, literally. From production to functionalization, from nutritional quality engineering to predicting effects on health, the interest in finding an efficient physicochemical characterization of food has boomed in recent years. The sheer complexity of characterizing food and its interaction with the human organism has however made the use of data driven approaches in modelling a necessity. High-throughput techniques, such as Nuclear Magnetic Resonance (NMR) spectroscopy, are well suited for omics data production and, coupled with machine learning, are paving a promising way of modelling food-human interaction. The foodomics approach sets the framework for omic data integration in food studies, in which NMR experiments play a key role. NMR data can be used to assess nutritional qualities of food, helping the design of functional and sustainable sources of nutrients, detect biomarkers of intake and study how they impact the metabolism of different individuals, study the kinetics of compounds in foods or their by-products to detect pathological conditions and improve the efficiency of in-silico models of the metabolic network

NMR-Based Metabolomics for a More Holistic and Sustainable Research in Food Quality Assessment: A Narrative Review

The ability of nuclear magnetic resonance spectroscopy (NMR) to extract chemical information from a complex mixture is invaluable and widely described in literature. Many applications of this technique in the foodomics field have highlighted how NMR could characterize food matrices, and it can be used all along its “life chain”: from farm to fork and from fork to the digestion process. The aim of this review is an attempt to show, firstly, the potential of NMR as a method based on green chemistry in sample preparation, and then in characterizing the nutritional qualities of agri-food products (with particular attention to their by-products) from a sustainable point of view. For instance, the NMR-based metabolomics approach has been used to enhance the nutritional properties of bio-products waste naturally rich in antioxidants and prebiotics. The reintroduction of these products in the food supply chain as functional foods or ingredients answers and satisfies the consumer demand for more food with high nutritional quality and more respect for the environment

Metabolomics as a Powerful Tool for Molecular Quality Assessment of the Fish Sparus aurata

The molecular profiles of perchloric acid solutions extracted from the flesh of Sparus aurata fish specimens, produced according to different aquaculture systems, have been investigated. The 1H-NMR spectra of aqueous extracts are indicative of differences in the metabolite content of fish reared under different conditions that are already distinguishable at their capture, and substantially maintain the same differences in their molecular profiles after sixteen days of storage under ice. The fish metabolic profiles are studied by top-down chemometric analysis. The results of this exploratory investigation show that the fish metabolome accurately reflects the rearing conditions. The level of many metabolites co-vary with the rearing conditions and a few metabolites are quantified including glycogen (stress indicator), histidine, alanine and glycine which all display significant changes dependent on the aquaculture system and on the storage times

Vaginal microbiome and metabolome highlight specific signatures of bacterial vaginosis

In this study, we sought to find novel bacterial and metabolic hallmarks for bacterial vaginosis (BV). We studied the vaginal microbiome and metabolome of vaginal fluids from BV-affected patients (n = 43) and healthy controls (n = 37) by means of an integrated approach based on quantitative polymerase chain reaction (qPCR) and proton nuclear magnetic resonance ((1)H-NMR). The correlations between the clinical condition and vaginal bacterial communities were investigated by principal component analysis (PCA). To define the metabolomics signatures of BV, 100 discriminant analysis by projection on latent structure (PLS-DA) models were calculated. Bacterial signatures distinguishing the health condition and BV were identified by qPCR. Lactobacillus crispatus strongly featured the healthy vagina, while increased concentrations of Prevotella, Atopobium and Mycoplasma hominis specifically marked the infection. (1)H-NMR analysis has led to the identification and quantification of 17 previously unreported molecules. BV was associated with changes in the concentration of metabolites belonging to the families of amines, organic acids, short chain fatty acids, amino acids, nitrogenous bases and monosaccharides. In particular, maltose, kynurenine and NAD(+) primarily characterised the healthy status, while nicotinate, malonate and acetate were the best metabolic hallmarks of BV. This study helps to better understand the role of the vaginal microbiota and metabolome in the development of BV infection. We propose a molecular approach for the diagnosis of BV based on quantitative detection in the vaginal fluids of Atopobium, Prevotella and M. hominis, and nicotinate, malonate and acetate by combining qPCR and (1)H-NMR

Spotting Frozen Curd in PDO Buffalo Mozzarella Cheese Through Insights on Its Supramolecular Structure Acquired by 1H TD-NMR Relaxation Experiments

The addition of frozen curd (FC) during the production process of \u201cMozzarella di Bufala Campana\u201d, an Italian cheese with Protected Designation of Origin (PDO), is a common fraud not involving modifications of the chemical composition in the final product. Its detection cannot thus be easily obtained by common analytical methods, which are targeted at changes in concentrations of diagnostic chemical species. In this work, the possibility of spotting this fraud by focusing on the modifications of the supramolecular structure of the food matrix, detected by time domain nuclear magnetic resonance (TD-NMR) experiments, was investigated. Cheese samples were manufactured in triplicate, according to the PDO disciplinary of production, except for using variable amounts of FC (i.e., 0, 15, 30, and 50% w/w). Relaxation data were analysed through different approaches: (i) Discrete multi-exponential fitting, (ii) continuous Laplace inverse fitting, and (iii) chemometrics approach. The strategy that lead to best detection results was the chemometrics analysis of raw Carr-Purcell-Meiboom-Gill (CPMG) decays, allowing to discriminate between compliant and adulterated samples, with as low as 15% of FC addition. The strategy is based on the use of machine learning for projection on latent structures of raw CPMG data and classification tasks for fraud detection, using quadratic discriminant analysis. By coupling TD-NMR raw decays with machine learning, this work opens the way to set up a system for detecting common food frauds modifying the matrix structure, for which no official authentication methods are yet availabl

Olive oil industry by-products. Effects of a polyphenol-rich extract on the metabolome and response to inflammation in cultured intestinal cell

Over the past years, researchers and food manufacturers have become increasingly interested in olive polyphenols due to the recognition of their biological properties and probable role in the prevention of various diseases such as inflammatory bowel disease. Olive pomace, one of the main by-products of olive oil production, is a potential low-cost, phenol-rich ingredient for the formulation of functional food. In this study, the aqueous extract of olive pomace was characterized and used to supplement human intestinal cell in culture (Caco-2). The effect on the cell metabolome and the anti-inflammatory potential were then evaluated. Modification in the metabolome induced by supplementation clearly evidenced a metabolic shift toward a “glucose saving/accumulation” strategy that could have a role in maintaining anorexigenic hormone secretion and could explain the reported appetite-suppressing effect of the administration of polyphenol-rich food. In both basal and inflamed condition, supplementation significantly reduced the secretion of the main pro-inflammatory cytokine, IL-8. Thus, our data confirm the therapeutic potential of polyphenols, and specifically of olive pomace in intestinal bowel diseases. Although intervention studies are needed to confirm the clinical significance of our findings, the herein reported results pave the road for exploitation of olive pomace in the formulation of new, value-added foods. In addition, the application of a foodomics approach allowed observing a not hypothesized modulation of glucose metabolism

Investigation of the Defatted Colostrum 1H-NMR Metabolomics Profile of Gilts and Multiparous Sows and Its Relationship with Litter Performance

The aim of the study was to characterize the soluble metabolomics profile of defatted colostrum of sows at different parity number (PA) and to correlate the metabolomics profile with the Brix percentage estimate of colostrum immunoglobulin G (IgG) and sow productive traits. A total of 96 Meidam (crossbreed Large White 7 Meishan) sows of PA from 1-4 (PA1: 28; PA2:26; PA3:12; PA4:26) were included, and their productive traits were recorded at 10 days post-farrowing. Colostrum IgG was quantified using a Brix refractometer, and metabolomics profile was assessed using 1H-NMR spectroscopy. Sows' PA slightly influenced the metabolomics profile of colostrum. lactose and glycine were higher in PA1 compared with PA4 (p 0.05) and N-acetylglucosamine (GlcNAc) tended to be higher in PA2 than PA3 and PA4 (p < 0.10). The Brix percentage of IgG was negatively associated with lactose and positively with creatine, myo-inositol, and O-phosphocholine (p < 0.05). Taurine was positively related to litter weight at birth. GlcNAc and myo-inositol were linked to piglet mortality at day 10 with a negative and positive trend, respectively. In conclusion, colostrum of gilts and multiparous sows had a similar metabolomics profile. Specific metabolites contributed to explanation of the variability in colostrum Brix percentage estimate of IgG concentration and the sows' productive performance

Characterization of Flavor Profile of "Nanx Wudl" Sour Meat Fermented from Goose and Pork Using Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) Combined with Electronic Nose and Tongue

Sour meat is a highly appreciated traditional fermented product, mainly from the Guizhou, Yunnan, and Hunan provinces. The flavor profiles of sour meat from goose and pork were evaluated using gas chromatography-ion mobility spectrometry (GC-IMS) combined with an electronic nose (E-nose) and tongue (E-tongue). A total of 94 volatile compounds were characterized in fermented sour meat from both pork and goose using GC-IMS. A data-mining protocol based on univariate and multivariate analyses revealed that the source of the raw meat plays a crucial role in the formation of flavor compounds during the fermentation process. In detail, sour meat from pork contained higher levels of hexyl acetate, sotolon, heptyl acetate, butyl propanoate, hexanal, and 2-acetylpyrrole than sour goose meat. In parallel, sour meat from goose showed higher levels of 4-methyl-3-penten-2-one, n-butyl lactate, 2-butanol, (E)-2-nonenal, and decalin than sour pork. In terms of the odor and taste response values obtained by the E-nose and E-tongue, a robust principal component model (RPCA) could effectively differentiate sour meat from the two sources. The present work could provide references to investigate the flavor profiles of traditional sour meat products fermented from different raw meats and offer opportunities for a rapid identification method based on flavor profiles

Effect of Sprouting on Biomolecular and Antioxidant Features of Common Buckwheat (Fagopyrum esculentum)

Buckwheat is a pseudo-cereal widely grown and consumed throughout the world. Buckwheat is recognized as a good source of nutrients and, in combination with other health-promoting components, is receiving increasing attention as a potential functional food. Despite the high nutritional value of buckwheat, a variety of anti-nutritional features makes it difficult to exploit its full potential. In this framework, sprouting (or germination) may represent a process capable of improving the macromolecular profile, including reducing anti-nutritional factors and/or synthesizing or releasing bioactives. This study addressed changes in the biomolecular profile and composition of buckwheat that was sprouted for 48 and 72 h. Sprouting increased the content of peptides and free-phenolic compounds and the antioxidant activity, caused a marked decline in the concentration of several anti-nutritional components, and affected the metabolomic profile with an overall improvement in the nutritional characteristics. These results further confirm sprouting as a process suitable for improving the compositional traits of cereals and pseudo-cereals, and are further steps towards the exploitation of sprouted buckwheat as a high-quality ingredient in innovative products of industrial interest