A novel approach based on untargeted lipidomics reveals differences in the lipid pattern among durum and common wheat

1H-NMR Lipidomics, Comparing Fatty Acids and Lipids in Cow, Goat, Almond, Cashew, Soy, and Coconut Milk Using NMR and Mass Spectrometry

Background/Objectives: Lipids are an important component of human nutrition. Conventional milk is obtained from animals, and dairy milk is consumed by many people worldwide. Recently, milk consumers have been increasingly shifting towards plant-based milk options. The aim of the study was the qualitative identification of lipid metabolites in animal- and plant-based milk, the identification and comparison of the fatty acids (FAs) of milk, and the qualitative identification of the lipid groups among the milk varieties. Methods: Milk samples were obtained from local grocery stores. Lipids were extracted using a modified Folch method and analyzed using nuclear magnetic resonance (NMR) metabolomics. Gas and liquid chromatography mass spectrometry methods (GC-MS and LC-MS) were used to identify the FAs and lipid groups. Lipid weights were compared and the NMR profiles of the lipids analyzed by multivariate statistical analysis. Principal component analysis was performed for the milk lipids obtained from the animal, and plant milk varieties. Results: Clustering of NMR data showed two main clusters: cow/almond/cashew and goat/soy/coconut. GC-MS analysis of the methylated fatty acids (FAs) showed the presence of 12:0, 14:0, 16:0, 16:1, 17:0, 18:0, 18:1, 18:2, 20:1, and 20:2 in all milk types, while FAs 19:0 and 20:4 were observed only in the dairy milk. LC-MS data showed common masses that may indicate the presence of mono- and diacyl glycerols and several lysophospholipids among the different types of milk. Conclusions: This study shows the advantage of using NMR, GC-MS, and LC-MS to differentiate the lipids among different milk types and compare them on one platform.

AI-based processing of future prepared foods: Progress and prospects

The prepared foods sector has grown rapidly in recent years, driven by the fast pace of modern living and increasing consumer demand for convenience. Prepared foods are taking an increasingly important role in the modern catering industry due to their ease of storage, transportation, and operation. However, their processing faces several challenges, including labor shortages, inefficient sorting, inadequate cleaning, unsafe cutting processes, and a lack of industry standards. The development of artificial intelligence (AI) will change the processing of prepared foods. This review summarizes the progress and prospects of AI applications in the sorting/classification, cleaning, cutting, preprocessing, and freezing of prepared foods, encompassing techniques such as mathematical modeling, chemometrics, machine learning, fuzzy logic, and adaptive neuro fuzzy inference system. For example, AI-powered sorting systems using computer vision have improved accuracy in ingredient classification, while deep learning models in cleaning processes have enhanced microbial contamination detection with high spectral imaging techniques. Despite challenges like managing large-scale data and complex models, AI has shown significant potential to inspire both industry practice and research. AI applications can enhance the efficiency, accuracy, and consistency of prepared foods processing, while also reducing labor costs, improving hygiene monitoring, minimizing resource waste, and decreasing environmental impact. Furthermore, AI-driven resource optimization has demonstrated its potential in reducing energy consumption and promoting sustainable food production practices. In the future, AI technology is expected to further improve model generalization and operation precision, driving the food processing industry toward smarter, more sustainable development. This study provides valuable insights to encourage further innovation in AI applications within food processing and technological advancement in the food industry.

Foodomics as a Tool for Evaluating Food Authenticity and Safety from Field to Table: A Review

The globalization of the food industry chain and the increasing complexity of the food supply chain present significant challenges for food authenticity and raw material processing. Food authenticity identification now extends beyond mere adulteration recognition to include quality evaluation, label compliance, traceability determination, and other quality-related aspects. Consequently, the development of high-throughput, accurate, and rapid analytical techniques is essential to meet these diversified needs. Foodomics, an innovative technology emerging from advancements in food science, enables both a qualitative judgment and a quantitative analysis of food authenticity and safety. This review also addresses crucial aspects of fully processing food, such as verifying the origin, processing techniques, label authenticity, and detecting adulterants, by summarizing the omics technologies of proteomics, lipidomics, flavoromics, metabolomics, genomics, and their analytical methodologies, recent developments, and limitations. Additionally, we analyze the advantages and application prospects of multi-omics strategies. This review offers a comprehensive perspective on the food chain, food safety, and food processing from field to table through omics approaches, thereby promoting the stable and sustained development of the food industry.

Unraveling the spoilage characteristics of refrigerated pork using high-throughput sequencing coupled with UHPLC-MS/MS-based non-targeted metabolomics

The spoilage of refrigerated pork involves nutrient depletion and the production of spoilage metabolites by spoilage bacteria, yet the microbe-metabolite interactions during this process remain unclear. This study employed 16S rRNA high-throughput sequencing and non-targeted metabolomics based on ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) to reveal the core microbiota and metabolite profiles of pork during refrigeration. A total of 45 potential biomarkers were screened through random forest model analysis. Metabolic pathway analysis indicated that eleven pathways, including biogenic amine metabolism, pentose metabolism, purine metabolism, pyrimidine metabolism, phospholipid metabolism, and fatty acid degradation, were potential mechanisms of pork spoilage. Correlation analysis revealed nine metabolites-histamine, tyramine, tryptamine, D-gluconic acid, UDP-d-glucose, xanthine, glutamine, phosphatidylcholine, and hexadecanoic acid-as spoilage biomarkers, with Pseudomonas, Serratia, and Photobacterium playing significant roles. This study provides new insights into the changes in microbial and metabolic characteristics during the spoilage of refrigerated pork.

Lipidomic Profiling of Common Wheat Flours from 1891-2010

Wheat lipids are a minor constituent of wheat, with an important influence on its processing properties. While breeding aimed to improve the protein composition of wheat flour, its influence on the lipid composition remains unknown. We therefore analyzed the lipidome of 60 different common wheat (Triticum aestivum) flours representing cultivars registered and grown in Germany from 1891 to 2010. Four different extraction techniques were tested before the application of a semiquantitative, untargeted UHPLC-MS/MS method. The measurements included 16 different lipid classes and 102 different lipid species. Based on the lipid profile, discrimination between old (registered between 1891 to 1950) and modern (1951 to 2010) cultivars was possible. While the lipid class composition remained constant, differences were due to variations within the class of triacylglycerols, with modern cultivars containing less unsaturated fatty acids than the older ones. Our results imply that improving the lipid class composition of common wheat is a promising target for further breeding.

Untargeted metabolomics liquid chromatography-high resolution mass spectrometry approach for the geographical origin assessment of Italian dehydrated apples

Geographical provenience is nowadays a relevant aspect of the authenticity and the quality of many food commodities. Dehydrated apple cubes/slices represent an ingredient commonly used by food companies for bakery products. However, this apple-based matrix is not so known and studied from an analytical point of view. In the present work, seven compounds were identified as key molecules to distinguish between Italian and non-Italian samples, through an untargeted ultrahigh-pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) approach. This methodology was merged with multivariate statistical analysis, and the principal features were studied and identified considering several identification steps. Samples from 2020 and 2021 harvesting campaigns, with partial and total dehydration rates, with or without peel, and from different apple varieties were considered for the study, for a total of 91 samples. Afterward, the same analysis protocol was applied to an external set (n = 12 samples), included in the statistical models, searching for the key compounds identified in the training set. Interesting and significant results underlined the potentiality of the UHPLC-HRMS technology as a confirmatory strategy for the geographical origin assessment of dehydrated apple commodities.

Determination of Polar Lipids in Wheat and Oat by a Complementary Approach of Hydrophilic Interaction Liquid Chromatography and Reversed-Phase High-Performance Liquid Chromatography Hyphenated with High-Resolution Mass Spectrometry

Cereals contain lipids that fulfill important physiological roles and are associated with stress in the plant. However, many of the specific biological roles of lipids are yet unknown. Comprehensive analysis of these polar lipid categories in whole grain wheat and oat, cereals highly relevant also in nutrition, was performed. Hydrophilic interaction liquid chromatography (HILIC) and reversed-phase high-performance liquid chromatography (RP-HPLC) coupled with high-resolution mass spectrometry using electrospray ionization in both positive and negative ionization mode was used. Exploiting the different separation mechanisms, HILIC was used as a screening method for straightforward lipid class assignment and enabled differentiation of isomeric lipid classes, like phosphatidylethanolamine and lyso-N-acylphosphatidylethanolamine, while RP-HPLC facilitated separation of constitutional isomers. In combination with data-dependent MS/MS experiments, 67 lipid species belonging to nine polar lipid classes could be identified. Furthermore, with both ionization modes, fatty acyl chains directly connected to the lipid headgroups could be assigned. This work focused on the four lipid classes N-acylphosphatidylethanolamines, acyl-monogalactosyldiacylglycerols, digalactosyldiacylglycerols, and monogalactosyldiacylglycerols as they were less studied in detail in the past. Applying the complementary approach, the relative lipid species compositions in these lipid classes was investigated in detail.

New insights into the search of meat quality biomarkers assisted by Orbitrap Tribrid untargeted metabolite analysis and chemometrics

Metabolite profiles of normal and defective dry, firm and dark (DFD) meat extracts with known ultimate pH (pHu) values were determined by Orbitrap Tribrid ID-X untargeted analysis coupled to chemometrics. An intelligent MS³ AcquireX^TM workflow firstly approached the unambiguous characterization of detected features that were subsequently quantified by a complementary MS¹ study of biological replicates. Chemometric research revealed how threonylphenylalanine (overexpressed in normal meats) together to tetradecadienoyl- and hydroxydodecanoyl-carnitines (both overexpressed in DFD meats) appropriately grouped meat groups assayed. Robustness of such biomarkers was confirmed through a time-delayed study of a blind set of samples (unknown pHu) and evidenced limitations of pHu as an isolated parameter for accurate meat quality differentiation. Other acyl-carnitines also characterized DFD samples, suggesting interferences induced by pre-slaughter stress (PSS) on lipid catabolism that would explain accumulation of such intermediate metabolites. Results achieved can ease understanding of biochemical mechanisms underlying meat quality defects.

Lipidomics reveals alterations of lipid composition and molecular nutrition in irradiated marble beef

Electron beam irradiation can effectively inhibit microbial growth, but the changes of lipid during irradiation have not been comprehensively analyzed in marble beef. Here, UHPLC-MS/MS was used to detect lipids changes of irradiated marble beef. A total of 1032 lipids were identified and classified into 3 lipid classes and 8 subclasses in irradiated marble beef. 9 lipid biomarkers were screened with increasing irradiation dose. 122 differential lipids were generated and involved in 4 metabolic pathways included Glycerophospholipid metabolism, Linoleic acid metabolism, alpha-Linolenic acid metabolism and Arachidonic acid metabolism though PC(18:0/14:0), PE(16:0/16:0) and PE(18:0/16:0) in irradiated. Our results showed that irradiation had effect on the lipid of marbled beef, but the increase of irradiation dose from 2.5 kGy to 4.5 kGy had little effect on lipids. These results help us to understand the dynamic changes of irradiated meat lipids and lay a foundation for the application of irradiation in meat preservation.

Mutations in Rht-B1 Locus May Negatively Affect Frost Tolerance in Bread Wheat

The wheat semi-dwarfing genes Rht (Reduced height) are widely distributed among the contemporary wheat varieties. These genes also exert pleiotropic effects on plant tolerance towards various abiotic stressors. In this work, frost tolerance was studied in three near-isogenic lines of the facultative variety ‘April Bearded’ (AB), carrying the wild type allele Rht-B1a (tall phenotype), and the mutant alleles Rht-B1b (semi-dwarf) and Rht-B1c (dwarf), and was further compared with the tolerance of a typical winter type variety, ‘Mv Beres’. The level of freezing tolerance was decreasing in the order ‘Mv Beres’ > AB Rht-B1a > AB Rht-B1b > AB Rht-B1c. To explain the observed differences, cold acclimation-related processes were studied: the expression of six cold-related genes, the phenylpropanoid pathway, carbohydrates, amino acids, polyamines and compounds in the tricarboxylic acid cycle. To achieve this, a comprehensive approach was applied, involving targeted analyses and untargeted metabolomics screening with the help of gas chromatography/liquid chromatography—mass spectrometry setups. Several cold-related processes exhibited similar changes in these genotypes; indeed, the accumulation of eight putrescine and agmatine derivatives, 17 flavones and numerous oligosaccharides (max. degree of polymerization 18) was associated with the level of freezing tolerance in the ‘April Bearded’ lines. In summary, the mutant Rht alleles may further decrease the generally low frost tolerance of the Rht-B1a, and, based on the metabolomics study, the mechanisms of frost tolerance may differ for a typical winter variety and a facultative variety. Present results point to the complex nature of frost resistance.

Assessing food authenticity through protein and metabolic markers

This chapter aims to address an issue of ancient origins, but more and more topical in a globalized world in which consumers and stakeholders are increasingly aware: the authenticity of food. Foods are systems that can also be very complex, and verifying the correspondence between what is declared and the actual characteristics of the product is often a challenging issue. The complexity of the question we want to answer (is the food authentic?) means that the answer is equally articulated and makes use of many different analytical techniques. This chapter will consider the chemical analyses of foods aimed at guaranteeing their authenticity and will focus on frontier methods that have been developed in recent years to address the need to respond to ever-increasing guarantees of authenticity. Targeted and non-targeted approaches will be considered for verifying the authenticity of foods, through the study of different classes of constituents (proteins, metabolites, lipids, flavors). The numerous approaches available (proteomics, metabolomics, lipidomics) and the related analytical techniques (LC-MS, GC-MS, NMR) are first described from a more general point of view, after which their specific application for the purposes of authentication of food is addressed.

Integration of lipidomics and metabolomics for the authentication of camellia oil by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry coupled with chemometrics

The integration of lipidomics and metabolomics approaches, based on UPLC-QTOF-MS technology coupled with chemometrics, was established to authenticate camellia oil adulterated with rapeseed oil, peanut oil, and soybean oil. Lipidomics revealed that the glyceride profile provides a prospective authentication of camellia oil, but no characteristic markers were available. Sixteen characteristic markers were identified by metabolomics. For camellia oil, all six markers were sapogenins of oleanane-type triterpene saponins. Lariciresinol, sinapic acid, doxercalciferol, and an unknown compound were identified as markers for rapeseed oil. Characteristic markers in peanut oil were formononetin, sativanone, and medicarpin. In the case of soybean oil, the characteristic markers were dimethoxyflavone, daidzein, and genistein. The established OPLS-DA and OPLS prediction models were highly accurate in the qualitative and quantitative analyses of camellia oil adulterated with 5% other oils. These results indicate that the integration of lipidomics and metabolomics approaches has great potential for the authentication of edible oils.

A molecular insight into the lipid changes of pig Longissimus thoracis muscle following dietary supplementation with functional ingredients

In this work, the Longissimus thoracis pig skeletal muscle was used as a model to investigate the impact of two different diets, supplemented with n-3 polyunsaturated fatty acids from extruded linseed (L) and polyphenols from grape skin and oregano extracts (L+P), on the lipidomic profile of meat. A standard diet for growing-finishing pigs (CTRL) was used as a control. Changes in lipids profile were investigated through an untargeted lipidomics and transcriptomics combined investigation. The lipidomics identified 1507 compounds, with 195 compounds fitting with the MS/MS spectra of LipidBlast database. When compared with the CTRL group, the L+P diet significantly increased 15 glycerophospholipids and 8 sphingolipids, while the L diet determined a marked up-accumulation of glycerolipids. According to the correlations outlined between discriminant lipids and genes, the L diet may act preventing adipogenesis and the related inflammation processes, while the L+P diet promoted the expression of genes involved in lipids' biosynthesis and adipogenic extracellular matrix formation and functioning.

Lipid profile migration during the tilapia muscle steaming process revealed by a transactional analysis between MS data and lipidomics data

In this work, lipid profile migration from muscle to juice during the tilapia muscle steaming process was revealed by a transactional analysis of data from ultra-high-performance liquid chromatography coupled with Q Exactive (UHPLC-QE) Orbitrap mass spectrometry (MS) and lipidomics. Firstly, the lipids in tilapia muscles and juices at different steaming time points were extracted and examined by UHPLC-QE Orbitrap mass spectrometry. Secondly, a transactional analysis procedure was developed to analyze the data from UHPLC-QE Orbitrap MS and lipidomics. Finally, the corrected lipidomics data and the normalized MS data were used for lipid migration analysis. The results suggested that the transactional analysis procedure was efficient to significantly decrease UHPLC-QE Orbitrap MS workloads and delete the false-positive data (22.4-36.7%) in lipidomics data, which compensated the disadvantages of the current lipidomics method. The lipid changes could be disappearance, full migration into juice, appearance in juice, appearance in muscle, appearance in both muscle and juice, and retention in the muscle. Moreover, the results showed 9 (compared with 52), 5 (compared with 116), and 10 (compared with 178) of lipid class (compared with individual lipid) variables showed significant differences among the different steaming times (0, 10, 30, and 60 min) in all the muscles, juices, and muscle-juice systems, respectively. These results showed significant lipid profile migration from muscle to juice during the tilapia steaming process.

Non-targeted high-resolution mass spectrometry study for evaluation of milk freshness

Milk freshness is an important parameter for both consumers' health and quality of milk-based products. Up to now there have been neither analytical methods nor specific parameters to uniquely define milk freshness from a complete and univocal chemical perspective. In this study, 8 molecules were selected and identified as responsible for milk aging, using a liquid chromatography-high-resolution mass spectrometry approach followed by chemometric data elaboration. For model setup and marker selection, 30 high-quality pasteurized fresh milk samples were collected directly from the production site and analyzed immediately and after storage at 2 to 8°C for 7 d. The markers were then validated by challenging the model with a set of 10 milk samples, not previously analyzed. Our results demonstrated that the markers identified within this study can be successfully used for the correct classification of non-fresh milk samples, complementing and successfully enhancing parallel evaluations obtainable through sensory measures.

Metabolomics as a Tool to Elucidate the Sensory, Nutritional and Safety Quality of Wheat Bread-A Review

Wheat (Triticum aestivum) is one of the most extensively cultivated and used staple crops in human nutrition, while wheat bread is annually consumed in more than nine billion kilograms over the world. Consumers’ purchase decisions on wheat bread are largely influenced by its nutritional and sensorial characteristics. In the last decades, metabolomics is considered an effective tool for elucidating the information on metabolites; however, the deep investigations on metabolites still remain a difficult and longtime action. This review gives emphasis on the achievements in wheat bread metabolomics by highlighting targeted and untargeted analyses used in this field. The metabolomics approaches are discussed in terms of quality, processing and safety of wheat and bread, while the molecular mechanisms involved in the sensorial and nutritional characteristics of wheat bread are pointed out. These aspects are of crucial importance in the context of new consumers’ demands on healthy bakery products rich in bioactive compounds but, equally, with good sensorial acceptance. Moreover, metabolomics is a potential tool for assessing the changes in nutrient composition from breeding to processing, while monitoring and understanding the transformations of metabolites with bioactive properties, as well as the formation of compounds like toxins during wheat storage.

Integration of Untargeted and Pseudotargeted Metabolomics for Authentication of Three Shrimp Species Using UHPLC-Q-Orbitrap

In this work, an untargeted and pseudotargeted metabolomics combination approach was used for authentication of three shrimp species (Litopenaeus vanmamei, Penaeus japonicus, and Penaeus monodon). The monophasic extraction-based untargeted metabolomics approach enabled comprehensive-coverage and high-throughput analysis of shrimp tissue and revealed 26 potential markers. The pseudotargeted metabolomics approach confirmed 21 markers (including 9 key markers), which realized at least putative identification. The 21 confirmed markers, as well as 9 key markers, were used to develop PLS-DA models, correctly classifying 60/60 testing samples. Furthermore, DD-SIMCA and PLS-DA models were integrated based on the 9 key markers, with 59/60 and 20/20 samples of the species that were involved and uninvolved in model training correctly classified. The results demonstrated the potential of this untargeted and pseudotargeted metabolomics combination approach for shrimp species authentication.

Wheat authentication：An overview on different techniques and chemometric methods

Wheat (Triticum aestivum L.) is one of the most important cereal crops and is consumed as a staple food around the globe. Wheat authentication has become a crucial issue over the last decades. Recently, many techniques have been applied in wheat authentication including the authentication of wheat geographical origin, wheat variety, organic wheat, and wheat flour from other cereals. This paper collected related literature in the last ten years, and attempted to highlight the recent studies on the discrimination and authentication of wheat using different determination techniques and chemometric methods. The stable isotope analysis and elemental profile of wheat are promising tools to obtain information regarding the origin, and variety, and to differentiate organic from conventional farming of wheat. Image analysis, genetic parameters, and omics analysis can provide solutions for wheat variety, organic wheat, and wheat adulteration. Vibrational spectroscopy analyses, such as NIR, FTIR, and HIS, in combination with multivariate data analysis methods, such as PCA, LDA, and PLS-DA, show great potential in wheat authenticity and offer many advantages such as user-friendly, cost-effective, time-saving, and environment friendly. In conclusion, analytical techniques combining with appropriate multivariate analysis are very effective to discriminate geographical origin, cultivar classification, and adulterant detection of wheat.

Fraud Detection of Herbal Medicines Based on Modern Analytical Technologies Combine with Chemometrics Approach: A Review

Fraud in herbal medicines (HMs), commonplace throughout human history, is significantly related to medicinal effects with sometimes lethal consequences. Major HMs fraud events seem to occur with a certain regularity, such as substitution by counterfeits, adulteration by addition of inferior production-own materials, adulteration by chemical compounds, and adulteration by addition of foreign matter. The assessment of HMs fraud is in urgent demand to guarantee consumer protection against the four fraudulent activities. In this review, three analysis platforms (targeted, non-targeted, and the combination of non-targeted and targeted analysis) were introduced and summarized. Furthermore, the integration of analysis technology and chemometrics method (e.g., class-modeling, discrimination, and regression method) have also been discussed. Each integration shows different applicability depending on their advantages, drawbacks, and some factors, such as the explicit objective analysis or the nature of four types of HMs fraud. In an attempt to better solve four typical HMs fraud, appropriate analytical strategies are advised and illustrated with several typical studies. The article provides a general workflow of analysis methods that have been used for detection of HMs fraud. All analysis technologies and chemometrics methods applied can conduce to excellent reference value for further exploration of analysis methods in HMs fraud.

Normal-Phase HPLC-ELSD to Compare Lipid Profiles of Different Wheat Flours

Normal-phase high-performance liquid chromatography (HPLC) is widely used in combination with evaporative light scattering detection (ELSD) for separating and detecting lipids in various food samples. ELSD responses of different lipids were evaluated to elucidate the possibilities and challenges associated with quantification by means of HPLC-ELSD. Not only the number and type of polar functional groups but also the chain length and degree of unsaturation of (free or esterified) fatty acids (FAs) had a significant effect on ELSD responses. Tripalmitin and trilinolein yielded notably different ELSD responses, even if their constituting free FAs produced identical responses. How FA structure impacts ELSD responses of free FAs is thus not predictive for those of triacylglycerols and presumably other lipids containing esterified FAs. Because ELSD responses of lipids depend on the identity of the (esterified) FA(s) which they contain, fully accurate lipid quantification with HPLC-ELSD is challenging and time-consuming. Nonetheless, HPLC-ELSD is a good and fast technique to semi-quantitatively compare the levels of different lipid classes between samples of comparable FA composition. In this way, lipid profiles of different flours from near-isogenic wheat lines could be compared.

Lipid Compositions and Geographical Discrimination of 94 Geographically Authentic Wheat Samples Based on UPLC-MS with Non-Targeted Lipidomic Approach

Wheat is the staple food for the world’s major populations. However, chemical characters of geographically authentic wheat samples, especially for the lipids, have not been deeply studied. The present research aimed to investigate lipid compositions of Chinese wheat samples and clarify the major markers that contribute to the geographical differences. A total of 94 wheat samples from eight main wheat-producing provinces in China were evaluated to differentiate their lipid compositions. Based on the data collected from ultra-high-performance-liquid-chromatography tandem time-of-flight mass spectrometry (UPLC-Q/TOF MS), an optimized non-targeted lipidomic method was utilized for analyses. As the results, 62 lipid compounds, including fatty acids, phospholipids, galactolipids, triglycerides, diglycerides, alkylresorcinol, and ceramide were tentatively identified. Partial least squares discriminant analysis (PLS-DA) demonstrated a more satisfying performance in distinguishing wheat samples from different origins compared with principal component analysis (PCA). Further, the abundances of triglycerides and glycerophospholipids with more unsaturated fatty acids were found greater in wheat samples from northern origins of China, while more glycolipids and unsaturated fatty acids arose in southern original wheat samples. These findings describe the lipid profiles of wheat samples in China and could contribute to the quality and safety control for the wheat flour products.

Mass spectrometry-based lipidomics in food science and nutritional health: A comprehensive review

With the advance in science and technology as well as the improvement of living standards, the function of food is no longer just to meet the needs of survival. Food science and its associated nutritional health issues have been increasingly debated. Lipids, as complex metabolites, play a key role both in food and human health. Taking advantages of mass spectrometry (MS) by combining its high sensitivity and accuracy with extensive selective determination of all lipid classes, MS-based lipidomics has been employed to resolve the conundrum of addressing both qualitative and quantitative aspects of high-abundance and low-abundance lipids in complex food matrices. In this review, we systematically summarize current applications of MS-based lipidomics in food field. First, common MS-based lipidomics procedures are described. Second, the applications of MS-based lipidomics in food science, including lipid composition characterization, adulteration, traceability, and other issues, are discussed. Third, the application of MS-based lipidomics for nutritional health covering the influence of food on health and disease is introduced. Finally, future research trends and challenges are proposed. MS-based lipidomics plays an important role in the field of food science, promoting continuous development of food science and integration of food knowledge with other disciplines. New methods of MS-based lipidomics have been developed to improve accuracy and sensitivity of lipid analysis in food samples. These developments offer the possibility to fully characterize lipids in food samples, identify novel functional lipids, and better understand the role of food in promoting healt.

Pulsatilla Decoction Can Treat the Dampness-Heat Diarrhea Rat Model by Regulating Glycerinphospholipid Metabolism Based Lipidomics Approach

Ethnopharmacological Relevance

Diarrhea is a major medical problem in clinical practice. According to the theory of traditional Chinese medicine (TCM), different types of diarrhea should be treated with different TCM formulations based on the targeted medical condition. Dampness-heat diarrhea (DHD) is a serious diarrheal disease and Pulsatilla decoction (PD), a TCM, has been found effective against DHD.

Objective

The aim of this study was to clarify the mechanism of action of PD in DHD using an untargeted lipidomics strategy.

Materials and Methods

Wistar rats were randomized to four groups, including the control group, model group, PD groups and self-healing group. The PD groups were given a daily intragastric gavage of PD at doses of 3.76 g/kg. The rat model of DHD established by such complex factors as high-sugar and high-fat diet, improper diet, high temperature and humidity environment, drinking and intraperitoneal injection of Escherichia coli., which imitated the inducing conditions of DHD. Then the clinical symptoms and signs, blood routine, serum inflammatory cytokines levels and the histopathological changes of main organs were detected and observed to evaluate DHD model and therapeutic effect of PD. Lipid biomarkers of DHD were selected by comparing the control and model groups with the colon lipidomics technology and an ultra-high performance liquid chromatography (UHPLC) coupled with Q Exactive plus mass analyzer. Multivariate statistical analysis and pattern recognition were employed to examine different lipids within the colon of PD-treated rats.

Results

The clinical symptoms and signs of the model rats were consistent with the diagnostic criteria of DHD. After treatment with PD, the clinical symptoms and signs of the rats with DHD were improved; the indexes of blood routine and inflammatory cytokines levels tended to be normal. The lipidomics profile of the model group were evidently disordered when compared to the control group. A total of 42 significantly altered lipids between the model-control groups were identified by multivariate statistical analysis. DHD may result from such lipid disorders which are related to glycerophospholipid metabolism, arachidonic acid (AA) metabolism, and sphingolipid metabolism. After PD treatment, the lipidomic profiles of the disorders tended to recover when compared to the model group. Twenty lipid molecules were identified and some glycerophospholipids and AA levels returned close to the normal level.

Conclusion

Glycerophospholipid metabolism may play an important role in the treatment of dampness-heat induced diarrhea using PD.

Comparative lipid profile of four edible shellfishes by UPLC-Triple TOF-MS/MS

An ultra performance liquid chromatography-Triple time of flight mass spectrometry (UPLC-Triple TOF-MS/MS) method were established to characterize the lipid profiles in four shellfish species. More than 600 lipid molecular species belonging to 14 classes were detected. Phospholipids (PLs) were predominant in Chlamys farreri (54.9%) and glycerolipids (GLs) were dominant in Ostrea gigas (51.6%). PLs that contained polyunsaturated fatty acids (PUFAs) such as PC (16:0/20:5), PC (16:0/22:6) and PE (18:0/22:6) were the main molecular species. Especially, the percentage of sphingolipids (SLs) in four shellfishes is considerable (18.8-38.6%), the characterization of their special long-chain base (LCB) structure (mainly d19:3) and N-acyl group (mainly 16:0) was realized. Several SL subclasses with low abundance in four shellfish species, such as ceramide 2-aminoethylphosphonate (CAEP) and deoxy-ceramide (DeoxyCer), were also detected. These active lipids identified by this method have potential value in revealing the nutritional value of shellfishes and serving as biomarkers for distinguishing different shellfishes.

Differential Physiological Responses Elicited by Ancient and Heritage Wheat Cultivars Compared to Modern Ones

Although ancient, heritage, and modern wheat varieties appear rather similar from a nutritional point of view, having a similar gluten content and a comparable toxicity linked to their undigested gluten peptide, whenever the role of ancient end heritage wheat grains has been investigated in animal studies or in clinical trials, more anti-inflammatory effects have been associated with the older wheat varieties. This review provides a critical overview of existing data on the differential physiological responses that could be elicited in the human body by ancient and heritage grains compared to modern ones. The methodology used was that of analyzing the results of relevant studies conducted from 2010 through PubMed search, by using as keywords “ancient or heritage wheat”, “immune wheat” (protein or peptides), and immune gluten (protein or peptides). Our conclusion is that, even if we do not know exactly which molecular mechanisms are involved, ancient and heritage wheat varieties have different anti-inflammatory and antioxidant proprieties with respect to modern cultivars. It is, therefore, reasonable to assume that the health proprieties attributed to older cultivars could be related to wheat components which have positive roles in the modulation of intestinal inflammation and/or permeability.

Metabolomics Provides Valuable Insight for the Study of Durum Wheat: A Review

Metabolomics is increasingly being applied in various fields offering a highly informative tool for high-throughput diagnostics. However, in plant sciences, metabolomics is underused, even though plant studies are relatively easy and cheap when compared to those on humans and animals. Despite their importance for human nutrition, cereals, and especially wheat, remain understudied from a metabolomics point of view. The metabolomics of durum wheat has been essentially neglected, although its genetic structure allows the inference of common mechanisms that can be extended to other wheat and cereal species. This review covers the present achievements in durum wheat metabolomics highlighting the connections with the metabolomics of other cereal species (especially bread wheat). We discuss the metabolomics data from various studies and their relationships to other "-omics" sciences, in terms of wheat genetics, abiotic and biotic stresses, beneficial microbes, and the characterization and use of durum wheat as feed, food, and food ingredient.

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.

Egg product freshness evaluation: A metabolomic approach

Egg products' freshness is a crucial issue for the production of safe and high-quality commodities. Up to now, this parameter is assessed with the quantification of few compounds, but the possibility to evaluate more molecules simultaneously could help to provide robust results. In this study, 31 compounds responsible of freshness and not freshness of egg products were selected with a metabolomic approach. After an ultrahigh-pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) analysis, different chemometric models were created to select gradually the most significant features that were finally extracted and identified through HRMS data. Sample lots were collected directly from their arrival at the production plant sites, extracted immediately after, then left at room temperature, and extracted again after 24 and 48 hours (first day and second day, respectively). A total amount of 79 samples was used for the model creation. Furthermore, the same compounds were detected in seven new egg products sample lots not used for the model creation and treated with the same experimental design (total amount of samples, 21). The results obtained clearly demonstrate that these 31 molecules can be considered real freshness or not freshness chemical markers. Furthermore, this UHPLC-HRMS metabolomic approach allows for the detection of a larger set of metabolites clearly related to possible microbial growth over time, which is a relevant point for also ensuring food safety.