Multiple and Optimal Screening Subset: a method selecting global characteristic congeners for robust foodomics analysis.

Metabolomics and foodomics shed light on the molecular processes within living organisms and the complex food composition by leveraging sophisticated analytical techniques to systematically analyze the vast array of molecular features. The traditional feature-picking method often results in arbitrary selections of the model, feature ranking, and cut-off, which may lead to suboptimal results. Thus, a Multiple and Optimal Screening Subset (MOSS) approach was developed in this study to achieve a balance between a minimal number of predictors and high predictive accuracy during statistical model setup. The MOSS approach compares five commonly used models in the context of food matrix analysis, specifically bourbons. These models include Student's t-test, receiver operating characteristic curve, partial least squares-discriminant analysis (PLS-DA), random forests, and support vector machines. The approach employs cross-validation to identify promising subset feature candidates that contribute to food characteristic classification. It then determines the optimal subset size by comparing it to the corresponding top-ranked features. Finally, it selects the optimal feature subset by traversing all possible feature candidate combinations. By utilizing MOSS approach to analyze 1406 mass spectral features from a collection of 122 bourbon samples, we were able to generate a subset of features for bourbon age prediction with 88% accuracy. Additionally, MOSS increased the area under the curve performance of sweetness prediction to 0.898 with only four predictors compared with the top-ranked four features at 0.681 based on the PLS-DA model. Overall, we demonstrated that MOSS provides an efficient and effective approach for selecting optimal features compared with other frequently utilized methods.

Multi Omics Applications in Biological Systems.

Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

Capillary electromigration methods for food analysis and Foodomics: Advances and applications in the period March 2021 to March 2023.

This work presents a revision of the main applications of capillary electromigration (CE) methods in food analysis and Foodomics. Papers that were published during the period March 2021 to March 2023 are included. The work shows the multiple CE methods that have been developed and applied to analyze different types of molecules in foods and beverages. Namely, CE methods have been applied to analyze amino acids, biogenic amines, heterocyclic amines, peptides, proteins, phenols, polyphenols, pigments, lipids, carbohydrates, vitamins, DNAs, contaminants, toxins, pesticides, additives, residues, small organic and inorganic compounds, and other minor compounds. In addition, new CE procedures to perform chiral separation and for evaluating the effects of food processing as well as the last developments of microchip CE and new applications in Foodomics will be also discussed. The new procedures of CE to investigate food quality and safety, nutritional value, storage, and bioactivity are also included in the present review work.

Postprandial Plasma and Whole Blood Amino Acids Are Largely Indicative of Dietary Amino Acids in Adult Dogs Consuming Diets with Increasing Whole Pulse Ingredient Inclusion.

BACKGROUND: Pulse ingredients often replace grains in grain-free dog diets owing to their high-protein content. However, research to ascertain the benefit of this modification is limited. OBJECTIVES: This study aimed to correlate food compounds in 1 corn-inclusive control diet and 3 grain-free diets with increasing inclusions of whole pulses (≤45%; Pulse15, Pulse30, and Pulse45), formulated to meet similar macronutrient and micronutrient targets with postprandial amino acids (AAs) in healthy dogs >20 wk. METHODS: Diets were analyzed for biochemical compounds using tandem mass spectrometry. Twenty-eight outdoor-housed, healthy, adult Siberian Huskies were allocated to diet, and meal responses were analyzed at baseline and weeks 2, 4, 8, 16, and 20 with samples collected at fasted and 15, 30, 60, 90, 120, and 180 min after meal presentation. Blood AAs were analyzed by ultra performance liquid chromatography and differences across week, treatment, and time postmeal were analyzed in SAS Studio. Partial least squares regression was performed in SAS Studio using biochemical compounds in the diet as predictor variables and blood AAs as response variables. RESULTS: In plasma, Pulse45 had ∼32% greater postprandial Asn than Pulse15, and the control diet had ∼34% greater postprandial Leu and ∼35% greater Pro than Pulse15 (P < 0.05). In whole blood, Pulse30 had ∼23% greater postprandial Lys than the control diet, and the control diet had ∼21% greater postprandial Met and ∼18% greater Pro than Pulse45 and Pulse30, respectively (P < 0.05). Several phospholipids were correlated with postprandial AAs. Compounds in the urea cycle and glycine and serine metabolism were more enriched (P < 0.05) in plasma and whole blood, respectively. CONCLUSIONS: In macronutrient-balanced and micronutrient-balanced canine diets that differ in their inclusion of corn-derived compared with pulse-derived ingredients, postprandial changes in circulating AAs are largely indicative of the dietary AAs. This helps further our understanding of AA metabolism in healthy dogs fed grain-free diets.

Hi-C metagenomics facilitate comparative genome analysis of bacteria and yeast from spontaneous beer and cider.

Sequence-based analysis of fermented foods and beverages' microbiomes offers insights into their impact on taste and consumer health. High-throughput metagenomics provide detailed taxonomic and functional community profiling, but bacterial and yeast genome reconstruction and mobile genetic elements tracking are to be improved. We established a pipeline for exploring fermented foods microbiomes using metagenomics coupled with chromosome conformation capture (Hi-C metagenomics). The approach was applied to analyze a collection of spontaneously fermented beers and ciders (n = 12). The Hi-C reads were used to reconstruct the metagenome-assembled genomes (MAGs) of bacteria and yeasts facilitating subsequent comparative genomic analysis, assembly scaffolding and exploration of "plasmid-bacteria" links. For a subset of beverages, yeasts were isolated and characterized phenotypically. The reconstructed Hi-C MAGs primarily belonged to the Lactobacillaceae family in beers, along with Acetobacteraceae and Enterobacteriaceae in ciders, exhibiting improved quality compared to conventional metagenomic MAGs. Comparative genomic analysis of Lactobacillaceae Hi-C MAGs revealed clustering by niche and suggested genetic determinants of survival and probiotic potential. For Pediococcus damnosus, Hi-C-based networks of contigs enabled linking bacteria with plasmids. Analyzing phylogeny and accessory genes in the context of known reference genomes offered insights into the niche specialization of beer lactobacilli. The subspecies-level diversity of cider Tatumella spp. was disentangled using a Hi-C-based graph. We obtained highly complete yeast Hi-C MAGs primarily represented by Brettanomyces and Saccharomyces, with Hi-C-facilitated chromosome-level genome assembly for the former. Utilizing Hi-C metagenomics to unravel the genomic content of individual species can provide a deeper understanding of the ecological interactions within the food microbiome, aid in bioprospecting beneficial microorganisms, improving quality control and improving innovative fermented products.

'Nine Steaming Nine Sun-drying' processing enhanced properties of Polygonatum kingianum against inflammation, oxidative stress and hyperglycemia.

BACKGROUND: Polygonatum kingianum Coll. & Hemsl (PK), a prominent medicine and food homology plant, has been consumed as a decoction from boiling water for thousands of years. 'Nine Steaming Nine Sun-drying' processing has been considered an effective method for enriching tonic properties, but studies investigating such impacts on PK and underlying mechanisms are extremely rare. RESULTS: We first demonstrated substantial improvements in the anti-oxidative, anti-inflammatory and anti-hyperglycemia effects of the Nine Steaming Nine Sun-drying processed PK water extracts compared with crude PK in cell models (i.e., HepG2 and Raw 264.7 cells). We then integrated foodomics and network pharmacology analysis to uncover the key compounds responsible for the improved benefits. A total of 551 metabolites of PK extracts were identified, including polyphenols, flavonoids, alkaloids, and organic acids. During processing, 204 metabolites were enhanced, and 32 metabolites were recognized as key constituents of processed PK responsible for the improved health-promoting activities, which may affect PI3K-Akt-, MAPK-, and HIF-1 pathways. We further confirmed the high affinity between identified key constituents of processed PK and their predicted acting targets using molecular docking. CONCLUSION: Our results provide novel insights into bioactive compounds of processed PK, elaborating the rationality of processing from the perspective of tonic effects. Consuming processed PK could be an efficacious strategy to combat the high prevalence of metabolic diseases that currently affect millions of people worldwide. © 2023 Society of Chemical Industry.

Authentication of fish oil (omega-3) supplements using class-oriented chemometrics and comprehensive two-dimensional gas chromatography coupled to mass spectrometry.

Food supplement authentication is an important concern worldwide due to the ascending consumption related to health benefits and its lack of effective regulation in underdeveloped countries, making it a target of fraudulent activities. In this context, this study evaluated fish oil supplements by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) to obtain fingerprints, which were used to build predictive models for automated authentication of the most popular products sold in Brazil. The authentication process relied on a one-class classifier model using data-driven soft independent modeling of class analogy (DD-SIMCA). The output of the model was a binary classifier: certified IFOS fish oils and non-certified ones - regardless of the source of adulteration. The compositional analysis showed a significant variation in the samples, which validated the need for reliable statistical models. The DD-SIMCA algorithm is still incipient in GC×GC studies, but it proved to be an excellent tool for authenticity purposes, achieving a chemometric model with a sensitivity of 100%, specificity of 98.6%, and accuracy of 99.0% for fish oil authentication. Finally, orthogonalized partial least square discriminant analysis (OPLS-DA) was used to identify the features that distinguished the groups, which ascertained the results of the DD-SIMCA model that IFOS-certified oils are positively correlated to omega-3 fatty acids, including eicosapentaenoic acid (EPA, C20:5 n-3) and docosahexaenoic acid (DHA, C22:6 n-3).

Influence of Different Types, Utilization Times, and Volumes of Aging Barrels on the Metabolite Profile of Red Wine Revealed by 1H-NMR Metabolomics Approach.

It is well recognized that the aging process is a critical step in winemaking because it induces substantial chemical changes linked to the organoleptic properties and stability of the finished wines. Therefore, this study aimed to investigate the influence of different types, utilization times, and volumes of aging barrels on the metabolite profile of red wines, produced from Thai-grown Shiraz grapes, using a non-targeted proton nuclear magnetic resonance (1H-NMR) metabolomics approach. As a result, 37 non-volatile polar metabolites including alcohols, amino acids, organic acids, carbohydrates and low-molecular-weight phenolics were identified. Chemometric analysis allowed the discrimination of wine metabolite profiles associated with different types of aging containers (oak barrels vs. stainless-steel tanks), as well as the utilization times (2, 6 and >10 years old) and volumes (225, 500 and 2000 L) of the wooden barrels employed. Significant variations in the concentration of formate, fumarate, pyruvate, succinate, citrate, gallate, acetate, tyrosine, phenylalanine, histidine, γ-aminobutyrate, methionine and choline were statistically suggested as indicators accountable for the discrimination of samples aged under different conditions. These feature biomarkers could be applied to manipulate the use of aging containers to achieve the desired wine maturation profiles.

NMR-Based Metabolite Profiling and the Application of STOCSY toward the Quality and Authentication Assessment of European EVOOs.

Extra virgin olive oil (EVOO) possesses a high-value rank in the food industry, thus making it a common target for adulteration. Hence, several methods have been essentially made available over the years. However, the issue of authentication remains unresolved with national and food safety organizations globally struggling to regulate and control its market. Over the course of this study, the aim was to determine the origin of EVOOs suggesting a high-throughput, state-of-the-art method that could be easily adopted. A rapid, NMR-based untargeted metabolite profiling method was applied and complemented by multivariate analysis (MVA) and statistical total correlation spectroscopy (STOCSY). STOCSY is a valuable statistical tool contributing to the biomarker identification process and was employed for the first time in EVOO analysis. Market samples from three Mediterranean countries of Spain, Italy, and Greece, blended samples from these countries, as well as monocultivar samples from Greece were analyzed. The NMR spectra were collected, with the help of chemometrics acting as "fingerprints" leading to the discovery of certain chemical classes and single biomarkers that were related to the classification of the samples into groups based on their origin.

Omics data reveals the phenolic fingerprint of Brazilian whole wheat flours of different technological qualities.

Common wheat (Triticum aestivum) is one of the most consumed staple foods used for bakery products. Outer layers of grain present a great diversity of bioactive compounds, especially phenolic compounds (PC). Free and bound PC were extracted from eight genotypes of whole wheat flours (WWF) presenting different technological classifications. These extracts were comprehensively characterized through untargeted metabolomics applying ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MSE) and spectrophotometric analyses. Chemical composition and colorimetry were also determined by classical analyses. Thirty-eight PC were tentatively identified by UHPLC-MSE belonging to three classes (phenolic acids, flavonoids, and other polyphenols), some of them identified in all WWF samples. Bound hydroxycinnamic acids were the main PC found in WWF, especially the trans-ferulic acid and its isomer. No difference was found in starch and protein contents, whereas low-quality flours showed a higher ash content than the superior and medium-quality flours. Total phenolic content (TPC) ranged between 124.5 and 171.4 mg GAE/100 g WWF, which bound PC were responsible for 60% of TPC. Omics data and multivariate statistical analyses were successfully applied to discern the phenolic profile of WWF from different genotypes and technological qualities. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-023-05665-8.

Metabolic Responses of "Big Six" Escherichia coli in Wheat Flour to Thermal Treatment Revealed by Nuclear Magnetic Resonance Spectroscopy.

Escherichia coli outbreaks linked to wheat flour consumption have kept emerging in recent years, which necessitated an antimicrobial step being incorporated into the flour production process. The objectives of this in vivo study were to holistically evaluate the sanitizing efficacy of thermal treatment at 60 and 70°C against the "big six" E. coli strains (O26:H11, O45:H2, O103:H11, O111, O121:H19, and O145) in wheat flour and to assess the strain-specific metabolic responses using nuclear magnetic resonance (NMR) spectroscopy. The 70°C treatment temperature indiscriminatingly inactivated all strains by over 4.3-log CFU/g within 20 min, suggesting the high sanitization effectiveness of this treatment temperature, whereas the treatment at 60°C inactivated the strains to various degrees during the 1-h process. The most resistant strains at 60°C, O26 and O45, were characterized by amino acid and sugar depletion, and their high resistance was attributed to the dual effects of activated heat shock protein (HSP) synthesis and promoted glycolysis. O121 also demonstrated these metabolic changes, yet its thermal resistance was largely impaired by the weakened membrane structure and diminished osmotic protection due to phosphorylcholine exhaustion. In contrast, O111, O145, and O103 presented a substantial elevation of metabolites after stress at 60°C; their moderate thermal resistance was mainly explained by the accumulation of amino acids as osmolytes. Overall, the study enhanced our understanding of the metabolic responses of big six E. coli to heat stress and provided a model for conducting NMR-based metabolomic studies in powdered food matrices. IMPORTANCE "Big six" Escherichia coli strains have caused several outbreaks linked to wheat flour consumption in the last decade, revealing the vital importance of adopting an antimicrobial treatment during the flour production process. Therefore, the present study was carried out to evaluate the efficacy of a typical sanitizing approach, thermal treatment, against the big six strains in wheat flour along with the underlying antimicrobial mechanisms. Findings showed that thermal treatment at 60 and 70°C could markedly mitigate the loads of all strains in wheat flour. Moreover, activated heat shock protein synthesis combined with expedited glycolysis and enhanced osmotic protection were identified as two major metabolic alteration patterns in the E. coli strains to cope with the heat stress. With the responses of big six in wheat flour to thermal treatment elucidated, scientific basis for incorporating a thermal inactivation step in wheat flour production was provided.

Capillary electromigration methods for food analysis and Foodomics: Advances and applications in the period February 2019-February 2021.

This work presents a revision of the main applications of capillary electromigration methods in food analysis and Foodomics. Articles that were published during the period February 2019-February 2021 are included. The work shows the multiple CE methods that have been developed and applied to analyze different types of molecules in foods. Namely, CE methods have been applied to analyze amino acids, biogenic amines, carbohydrates, chiral compounds, contaminants, DNAs, food additives, heterocyclic amines, lipids, secondary metabolites, peptides, pesticides, phenols, pigments, polyphenols, proteins, residues, toxins, vitamins, small organic and inorganic compounds, as well as other minor compounds. The last results on the use of CE for monitoring food interactions and food processing, including recent microchips developments and new applications of CE in Foodomics, are discussed too. The new procedures of CE to investigate food quality and safety, nutritional value, storage and bioactivity are also included in the present review work.

Foodborne pathogens in the omics era.

Outbreaks and deaths related to Foodborne Diseases (FBD) occur constantly in the world, as a result of the consumption of contaminated foodstuffs with pathogens such as Listeria monocytogenes, Escherichia coli, Staphylococcus aureus, Salmonella spp, Clostridium spp. and Campylobacter spp. The purpose of this review is to discuss the main omic techniques applied in foodborne pathogen and to demonstrate their functionalities through the food chain and to guarantee the food safety. The main techniques presented are genomic, transcriptomic, secretomic, proteomic, and metabolomic, which together, in the field of food and nutrition, are known as "Foodomics." This review had highlighted the potential of omics to integrate variables that contribute to food safety and to enable us to understand their application on foodborne diseases. The appropriate use of these techniques had driven the definition of critical parameters to achieve successful results in the improvement of consumers health, costs and to obtain safe and high-quality products.

Milk metabolome reveals pyrimidine and its degradation products as the discriminant markers of different corn silage-based nutritional strategies.

The purpose of this study was to evaluate the effect of 6 different feeding systems (based on corn silage as the main ingredient) on the chemical composition of milk and to highlight the potential of untargeted metabolomics to find discriminant marker compounds of different nutritional strategies. Interestingly, the multivariate statistical analysis discriminated milk samples mainly according to the high-moisture ear corn (HMC) included in the diet formulation. Overall, the most discriminant compounds, identified as a function of the HMC, belonged to AA (10 compounds), peptides (71 compounds), pyrimidines (38 compounds), purines (15 compounds), and pyridines (14 compounds). The discriminant milk metabolites were found to significantly explain the metabolic pathways of pyrimidines and vitamin B6. Interestingly, pathway analyses revealed that the inclusion of HMC in the diet formulation strongly affected the pyrimidine metabolism in milk, determining a significant up-accumulation of pyrimidine degradation products, such as 3-ureidopropionic acid, 3-ureidoisobutyric acid, and 3-aminoisobutyric acid. Also, some pyrimidine intermediates (such as l-aspartic acid, N-carbamoyl-l-aspartic acid, and orotic acid) were found to possess a high discrimination degree. Additionally, our findings suggested that the inclusion of alfalfa silage in the diet formulation was potentially correlated with the vitamin B6 metabolism in milk, being 4-pyridoxic acid (a pyridoxal phosphate degradation product) the most significant and up-accumulated compound. Taken together, the accumulation trends of different marker compounds revealed that both pyrimidine intermediates and degradation products are potential marker compounds of HMC-based diets, likely involving a complex metabolism of microbial nitrogen based on total splanchnic fluxes from the rumen to mammary gland in dairy cows. Also, our findings highlight the potential of untargeted metabolomics in both foodomics and foodomics-based studies involving dairy products.

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 modeling 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 modeling 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.

A Review on the Foodomics Based on Liquid Chromatography Mass Spectrometry.

Due to the globalization of food production and distribution, the food chain has become increasingly complex, making it more difficult to evaluate unexpected food changes. Therefore, establishing sensitive, robust, and cost-effective analytical platforms to efficiently extract and analyze the food-chemicals in complex food matrices is essential, however, challenging. LC/MS-based metabolomics is the key to obtain a broad overview of human metabolism and understand novel food science. Various metabolomics approaches (e.g., targeted and/or untargeted) and sample preparation techniques in food analysis have their own advantages and limitations. Selecting an analytical platform that matches the characteristics of the analytes is important for food analysis. This review highlighted the recent trends and applications of metabolomics based on "foodomics" by LC-MS and provides the perspectives and insights into the methodology and various sample preparation techniques in food analysis.

Effects of Hydrothermal Processing on Volatile and Fatty Acids Profile of Cowpeas (Vigna unguiculata), Chickpeas (Cicer arietinum) and Kidney Beans (Phaseolus vulgaris).

Legumes are an economical source of protein, starch, dietary fibre, fatty acids, vitamins and minerals. However, they are not as fully utilised, due to volatile compounds contributing to their undesirable odour. The purpose of this work was to understand the processing time's effect on the legumes' volatile profile. Hence, this study investigated the effects of hydrothermal processing times on the volatile and fatty acids profiles of cowpeas, chickpeas and kidney beans. All legumes were pre-soaked (16 h) and then hydrothermally processed at 95 °C for 15 to 120 min, using an open system to approximate standard household cooking practices and a closed system to represent industrial processing. Alcohol, aldehyde, acid and ester volatile compounds showed decreasing trends during processing, which can be associated with enzyme inactivation and process-induced degradation. This work showed that processing at 95 °C for 30 min significantly reduced the number of compounds commonly associated with undesirable odour, but showed no significant change in the fatty acid profile. Other volatiles, such as furanic compounds, pyrans and sulphur compounds, showed an increasing trend during processing, which can be related to the Maillard reactions. This observation contributes to the growing knowledge of legume processing and its impact on volatile flavour. It can advise consumers and the industry on selecting processing intensity to maximise legume utilisation.

The Potential Neuroprotective Effect of Cyperus esculentus L. Extract in Scopolamine-Induced Cognitive Impairment in Rats: Extensive Biological and Metabolomics Approaches.

The aim of the present study is to investigate the phytochemical composition of tiger nut (TN) (Cyperus esculentus L.) and its neuroprotective potential in scopolamine (Scop)-induced cognitive impairment in rats. The UHPLC-ESI-QTOF-MS analysis enabled the putative annotation of 88 metabolites, such as saccharides, amino acids, organic acids, fatty acids, phenolic compounds and flavonoids. Treatment with TN extract restored Scop-induced learning and memory impairments. In parallel, TN extract succeeded in lowering amyloid beta, ß-secretase protein expression and acetylcholine esterase (AChE) activity in the hippocampus of rats. TN extract decreased malondialdehyde levels, restored antioxidant levels and reduced proinflammatory cytokines as well as the Bax/Bcl2 ratio. Histopathological analysis demonstrated marked neuroprotection in TN-treated groups. In conclusion, the present study reveals that TN extract attenuates Scop-induced memory impairments by diminishing amyloid beta aggregates, as well as its anti-inflammatory, antioxidant, anti-apoptotic and anti-AChE activities.

Capillary Electromigration Techniques Coupled to Mass Spectrometry: Applications to Food Analysis.

Analysis of food is essential for safety, quality control, government regulations, and recommendations to answer basic research questions. Capillary electrophoresis-mass spectrometry (CE-MS) is a powerful hyphenated technique in food, beverages, and foodomics for analytes ranging from small organic ions and biochemical compounds to macromolecules. Advantages of CE-MS for food analysis include high efficiency, high resolution, low cost of reagent consumption, fast and green approach in various food research areas. This review offers a comprehensive evaluation of CE-MS application for food analysis published in the open literature in the last decade (July 2010-October 2020). The principles of various CE-MS modes, CE-inductively coupled plasma mass spectrometry, ionization interfaces, and sample preparation methods for multiple types of liquid and solid food analysis are compiled. The latest advances and potential trends are outlined in several food analysis areas where CE-MS could be beneficial.

The Role of Chromatographic and Electromigration Techniques in Foodomics.

Foodomics is the discipline aimed at studying the prevention of diseases by food, identifying chemical, biological and biochemical food contaminants, determining changes in genetically modified foods, identifying biomarkers able to confirm the authenticity and quality of foods or studying the safety, quality and traceability of foods, among other issues. It is mainly based on the use of genomic, transcriptomic, proteomic and metabolomic tools, among others, in order to understand the effect of food on animals and humans at the level of genes, messenger ribonucleic acid, proteins and metabolites. Since the first definition of Foodomics, a reasonable number of works have shown the extremely high possibilities of this discipline, which is highly based on the use of advanced analytical hyphenated techniques - especially for proteomics and metabolomics. This book chapter aims at providing a general description of the role of chromatographic and electromigration techniques that are currently being applied to achieve the main objectives of Foodomics, particularly in the proteomic and metabolomic fields, since most published works have been focused on these approaches, and to highlight relevant applications.