Mass spectrometry-based untargeted metabolomics approach for differentiation of beef of different geographic origins

From genes to phenotypes: A review of multilevel omics techniques in beef quality

Beef quality is a crucial factor affecting both consumer preferences and the economic efficiency of the industry. With the rapid advancements in high-throughput technologies, including genomics, transcriptomics, proteomics, and metabolomics, integrated multi-omics analysis has emerged as a new research paradigm for deeply investigating the mechanisms underlying beef quality. This review systematically summarizes recent progress in multi-omics research related to beef quality, encompassing various levels such as genomics, transcriptomics, proteomics, metabolomics, and phenomics. At the genomic level, the use of genome-wide association studies (GWAS) and genomic selection techniques has markedly improved the precision of selecting meat quality traits. Studies in transcriptomics and proteomics have identified key genes involved in muscle growth and fat deposition, along with their expression regulation networks. Metabolomics analyses have highlighted critical metabolites that influence beef flavor and tenderness, as well as their biosynthetic pathways. The integration of multi-omics data has led to the construction of a comprehensive regulatory network linking genotype to phenotype, providing a theoretical foundation for precision breeding and quality control. However, current research faces challenges such as limited sample sizes and the need for more advanced data integration methods. Future research should prioritize: (1) increasing sample sizes and conducting large-scale omics data collection across diverse breeds and environmental conditions; (2) developing sophisticated computational methods for deeper integration of multi-omics data to create more accurate quality prediction models, and (3) enhancing functional validation experiments to elucidate the roles of key genes and metabolites. This review offers a systematic perspective on the molecular mechanisms driving beef quality and is of significant importance for guiding precision breeding and quality control in the beef industry.

Nontargeted screening strategy of chemical residues in animal-derived foods based on endogenous metabolite global annotation and interquartile range filtering by ultrahigh-performance liquid chromatography-high-resolution mass spectrometry

Endogenous components and other experimental background information can interfere with the efficiency of nontargeted screening for unknown chemical residues in complex food matrices. In this study, a new nontargeted screening strategy of chemical residues in animal-derived foods was developed based on endogenous metabolite global annotation and interquartile range (IQR) filtering by ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). First, endogenous metabolite global annotation was employed to eliminate the majority of endogenous components and their related ion peaks in food from the UHPLC-HRMS data. Second, IQR filtering was evaluated across multiple intercept values under different sample sizes and spiking concentrations based on 72 standards of chemical residues. The evaluation results indicated that chemical residues could be rapidly found after background interference was effectively removed when the sum of the third quartile and 20 times the interquartile range was used as intercept values. By integrating endogenous metabolite global annotation information with IQR filtering, this strategy achieved a total background interference filtering performance of >95 %. Finally, this strategy was applied to screen 13 meat samples. Suspected chemical residues in meat samples were successfully found out and identified by endogenous metabolite global annotation and IQR filtering, and the overall capability for filtering background interference reached 93.1 %. The strategy effectively improved the efficiency of nontargeted screening for unknown chemical residues in animal-derived foods, which can provide a powerful tool for routine risk assessment of food safety.

Advanced exploration of metabolite variation and the role of key differential metabolites during the ripening process of PSE pork

Pale, soft, exudative (PSE) meat, marked by pale color, soft texture, and high drip loss, affects over 10 % of pork from modern intensive farming, posing a major industry challenge. Despite extensive research, addressing PSE formation remains difficult due to complex genetic and environmental factors. This study developed a PSE-like pork model by heating normal pork at 36 °C for 4 h and identified differential metabolites using liquid chromatography-mass spectrometry (LC-MS) metabolomics. We detected 141 metabolites differing between normal and PSE-like pork across three post-slaughter storage times. Quinic acid (QA) and Xanthine (Xa) emerged as key factors, with QA enhancing muscle fiber structure and stabilizing pH, while Xa accelerated pH decline and increased fiber disruption. Our findings highlight the significant role of metabolites in meat quality, offering new strategies to mitigate PSE meat.

Advances in High-Resolution Mass Spectrometry-Based Metabolomics: Applications in Food Analysis and Biomarker Discovery

Consumer concerns regarding food nutrition and quality are becoming increasingly prevalent. High-resolution mass spectrometry (HRMS)-based metabolomics stands as a cutting-edge and widely embraced technique in the realm of food component analysis and detection. It boasts the capability to identify character metabolites at exceedingly low abundances, which remain undetectable by conventional platforms. It can also enable real-time monitoring of the flux of targeted compounds in metabolic synthesis and decomposition. With the emergence of artificial intelligence and machine learning, it has become more convenient to process the vast data sets of metabolomics and identify biomarkers. The review summarizes the latest applications of HRMS-based metabolomics platforms in traditional foods, novel foods, and pharmaceutical-food homologous matrices. It compares the suitability of HRMS to nuclear magnetic resonance (NMR) in metabolomics across three dimensions and discusses the principles and application scenarios of various mass spectrometry technologies.

Untargeted Metabolomics Reveals the Metabolic Characteristics and Biomarkers of Antioxidant Properties of Gardeniae Fructus from Different Geographical Origins in China

Background/Objectives: Gardeniae Fructus (GF) has been widely used as both food and medicinal purposes for thousands of years, but their antioxidant properties and potential metabolite biomarkers remain unclear. Methods: The purposes of this study were to examine antioxidant activities of 21 GF varieties from different geographical origins in China and identify potential biomarkers of antioxidant properties using an untargeted LC-MS-based metabolomics approach. Results: The results demonstrate that metabolomics had the ability to trace the geographical origins of GF. We found that antioxidant activities varied with different varieties of GF, which was dependent on their chemical compositions. The key chemical categories were obtained as the primary contributors of the antioxidant activity, including prenol lipids, flavonoids, coumarins and derivatives, as well as steroids and steroid derivatives. In addition, adouetine Y, coagulin R 3-glucoside and epicatechin 3-glucoside were identified as potential biomarkers for the antioxidant activity of GF. Conclusions: Therefore, our study sheds light on the metabolic characteristics and biomarkers of the antioxidant properties of GF, contributing to the selection and cultivation of a high antioxidant variety.

Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review

Food authentication and contamination are significant concerns, especially for consumers with unique nutritional, cultural, lifestyle, and religious needs. Food authenticity involves identifying food contamination for many purposes, such as adherence to religious beliefs, safeguarding health, and consuming sanitary and organic food products. This review article examines the issues related to food authentication and food fraud in recent periods. Furthermore, the development and innovations in analytical techniques employed to authenticate various food products are comprehensively focused. Food products derived from animals are susceptible to deceptive practices, which can undermine customer confidence and pose potential health hazards due to the transmission of diseases from animals to humans. Therefore, it is necessary to employ suitable and robust analytical techniques for complex and high-risk animal-derived goods, in which molecular biomarker-based (genomics, proteomics, and metabolomics) techniques are covered. Various analytical methods have been employed to ascertain the geographical provenance of food items that exhibit rapid response times, low cost, nondestructiveness, and condensability.

Authentication of aged beef in terms of aging time and aging type by 1H NMR spectroscopy

Meat authenticity addresses parameters such as species, breed, sex, housing system and postmortem treatment. Seventy-four beef backs from two breeds ('Fleckvieh' and 'Schwarzbunt') and three cattle types (heifer, cow, young bull) were dry-aged and wet-aged up to 28 days and analyzed by 1H NMR spectroscopy. Statistical models based on partial least squares regression and discriminant analysis were performed to classify the beef samples by breed, cattle type, aging time, and aging type based on their 1H NMR spectra. The aging time of beef samples can be predicted with an error ± 2.28 days. The cattle type model has an accuracy of cross-validation of 99.2 %, the breed models of 100 % and the aging type model for 28-days aged samples of 99.6 %. These models allow the authentication of beef samples in terms of breed, cattle type, aging time, and aging type with a single 1H NMR measurement.

Integrative deep learning framework predicts lipidomics-based investigation of preservatives on meat nutritional biomarkers and metabolic pathways

Preservatives are added as antimicrobial agents to extend the shelf life of meat. Adding preservatives to meat products can affect their flavor and nutrition. This review clarifies the effects of preservatives on metabolic pathways and network molecular transformations in meat products based on lipidomics, metabolomics and proteomics analyses. Preservatives change the nutrient content of meat products via altering ionic strength and pH to influence enzyme activity. Ionic strength in salt triggers muscle triglyceride hydrolysis by causing phosphorylation and lipid droplet splitting in adipose tissue hormone-sensitive lipase and triglyceride lipase. DisoLipPred exploiting deep recurrent networks and transfer learning can predict the lipid binding trend of each amino acid in the disordered region of input protein sequences, which could provide omics analyses of biomarkers metabolic pathways in meat products. While conventional meat quality assessment tools are unable to elucidate the intrinsic mechanisms and pathways of variables in the influences of preservatives on the quality of meat products, the promising application of omics techniques in food analysis and discovery through multimodal learning prediction algorithms of neural networks (e.g., deep neural network, convolutional neural network, artificial neural network) will drive the meat industry to develop new strategies for food spoilage prevention and control.

Mass spectrometry-based techniques for identification of compounds in milk and meat matrix

Food including milk and meat is often viewed as the mixture of different components such as fat, protein, carbohydrates, moisture and ash, which are estimated using well-established protocols and techniques. However, with the advent of metabolomics, low-molecular weight substances, also known as metabolites, have been recognized as one of the major factors influencing the production, quality and processing. Therefore, different separation and detection techniques have been developed for the rapid, robust and reproducible separation and identification of compounds for efficient control in milk and meat production and supply chain. Mass-spectrometry based techniques such as GC-MS and LC-MS and nuclear magnetic resonance spectroscopy techniques have been proven successful in the detailed food component analysis owing to their associated benefits. Different metabolites extraction protocols, derivatization, spectra generated, data processing followed by data interpretation are the major sequential steps for these analytical techniques. This chapter deals with not only the detailed discussion of these analytical techniques but also sheds light on various applications of these analytical techniques in milk and meat products.

Integrative metabolomic and transcriptomic analysis reveals difference in glucose and lipid metabolism in the longissimus muscle of Luchuan and Duroc pigs

Luchuan pig, an obese indigenous Chinese porcine breed, has a desirable meat quality and reproductive capacity. Duroc, a traditional western breed, shows a faster growth rate, high feed efficiency and high lean meat rate. Given the unique features these two porcine breeds have, it is of interest to investigate the underlying molecular mechanisms behind their distinctive nature. In this study, the metabolic and transcriptomic profiles of longissimus dorsi muscle from Duroc and Luchuan pigs were compared. A total of 609 metabolites were identified, 77 of which were significantly decreased in Luchuan compared to Duroc, and 71 of which were significantly elevated. Most differentially accumulated metabolites (DAMs) upregulated in Luchuan were glycerophospholipids, fatty acids, oxidized lipids, alcohols, and amines, while metabolites downregulated in Luchuan were mostly amino acids, organic acids and nucleic acids, bile acids and hormones. From our RNA-sequencing (RNA-seq) data we identified a total of 3638 differentially expressed genes (DEGs), 1802 upregulated and 1836 downregulated in Luchuan skeletal muscle compared to Duroc. Combined multivariate and pathway enrichment analyses of metabolome and transcriptome results revealed that many of the DEGs and DAMs are associated with critical energy metabolic pathways, especially those related to glucose and lipid metabolism. We examined the expression of important DEGs in two pathways, AMP-activated protein kinase (AMPK) signaling pathway and fructose and mannose metabolism, using Real-Time Quantitative Reverse Transcription PCR (qRT-PCR). Genes related to glucose uptake, glycolysis, glycogen synthesis, fatty acid synthesis (PFKFB1, PFKFB4, MPI, TPI1, GYS1, SLC2A4, FASN, IRS1, ULK1) are more activated in Luchuan, while genes related to fatty acid oxidation, cholesterol synthesis (CPT1A, HMGCR, FOXO3) are more suppressed. Energy utilization can be a decisive factor to the distinctive metabolic, physiological and nutritional characteristics in skeletal muscle of the two breeds we studied. Our research may facilitate future porcine breeding projects and can be used to reveal the potential molecular basis of differences in complex traits between various breeds.

Comparative chemical characters of Pseudostellaria heterophylla from geographical origins of China

Objective

Pseudostellaria heterophylla has been paid more attention in recent years, mainly as a medicine food homology plant. The content determination of P. heterophylla is not specified in the Chinese Pharmacopoeia (version 2020). The environmental conditions in different production areas could exert an influence on the quality of P. heterophylla. The purpose of this study is to discriminate P. heterophylla collected from different geographical origins of China.

Methods

In this study, the content of polysaccharide in 28 batches of P. heterophylla was determined using phenol-sulfuric acid. HPLC fingerprints were established under optimised HPLC-PDA methods. Subsequently, the similarity analysis (SA) and the quantification of heterophyllin B were analyzed. The metabolites of P. heterophylla were identified and evaluated using UHPLC-Q Exactive HF orbitrap MS system. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), hierarchical cluster analysis (HCA) and orthogonal PLS-DA (OPLS-DA) were performed based on all peak areas.

Results

The polysaccharide content in Guizhou and Jiangsu was higher than that of other production areas, which varied significant from different origins. While the content of heterophyllin B in Anhui and Jiangsu was high. The correlation coefficients of HPLC fingerprints for 28 batches samples ranged from 0.877 to 0.990, and the characteristic map can be used to identify and evaluate the quality of P. heterophylla. The samples from Fujian, Guizhou, Jiangsu provinces can be relatively separated using multivariate statistical analysis including PCA, PLS-DA, HCA, OPLS-DA, indicating that their metabolic compositions were significantly different. Ultimately, a total of 15 metabolites which were filtrated by a VIP-value > 1 and a P-value < 0.05 associated with the separation of different origins were identified.

Conclusion

HPLC fingerprint was established to evaluate the quality and authenticity of P. heterophylla. The present work showed that the difference of geographic distributions had an influence on the internal chemical compositions. A sensitive and rapid untargeted metabolomics approach by UHPLC-Q Exactive HF orbitrap MS was utilized to evaluate P. heterophylla from different origins in China for the first time. Overall, this study provides insights to metabolomics of P. heterophylla and supplies important reference values for the development of functional foods.

Pseudotargeted Metabolomics Approach Enabling the Classification-Induced Ginsenoside Characterization and Differentiation of Ginseng and Its Compound Formulation Products

The use of diversified ginseng extracts in health-promoting foods is difficult to differentiate, as they share bioactive ginsenosides among different Panax species (e.g., P. ginseng, P. quinquefolius, P. notoginseng, and P. japonicus) and different parts (e.g., root, leaf, and flower). This work was designed to develop a pseudo-targeted metabolomics approach to discover ginsenoside markers facilitating the precise authentication of ginseng and its use in compound formulation products (CFPs). Versatile mass spectrometry experiments on the QTrap mass spectrometer achieved classified characterization of the neutral, malonyl, and oleanolic acid-type ginsenosides, with 567 components characterized. A pseudo-targeted metabolomics approach by multiple reaction monitoring (MRM) of 262 ion pairs could assist to establish key identification points for 12 ginseng species. The simultaneous detection of 14 markers enabled the identification of ginseng from 15 ginseng-containing CFPs. The pseudo-targeted metabolomics strategy enabled better performance in differentiating among multiple ginseng, compared with the full-scan high-resolution mass spectrometry approach.

Nutritional lipidomics for the characterization of lipids in food

Lipids represent one out of three major macronutrient classes in the human diet. It is estimated to account for about 15-20% of the total dietary intake. Triacylglycerides comprise the majority of them, estimated 90-95%. Other lipid classes include free fatty acids, phospholipids, cholesterol, and plant sterols as minor components. Various methods are used for the characterization of nutritional lipids, however, lipidomics approaches become increasingly attractive for this purpose due to their wide coverage, comprehensiveness and holistic view on composition. In this chapter, analytical methodologies and workflows utilized for lipidomics profiling of food samples are outlined with focus on mass spectrometry-based assays. The chapter describes common lipid extraction protocols, the distinct instrumental mass-spectrometry based analytical platforms for data acquisition, chromatographic and ion-mobility spectrometry methods for lipid separation, briefly mentions alternative methods such as gas chromatography for fatty acid profiling and mass spectrometry imaging. Critical issues of important steps of lipidomics workflows such as structural annotation and identification, quantification and quality assurance are discussed as well. Applications reported over the period of the last 5years are summarized covering the discovery of new lipids in foodstuff, differential profiling approaches for comparing samples from different origin, species, varieties, cultivars and breeds, and for food processing quality control. Lipidomics as a powerful tool for personalized nutrition and nutritional intervention studies is briefly discussed as well. It is expected that this field is significantly growing in the near future and this chapter gives a short insight into the power of nutritional lipidomics approaches.

Sensory and metabolite migration from tilapia skin to soup during the boiling process: fast and then slow

This study mainly studied sensory and metabolite migration from the skin to the soup in the boiling process of tilapia skin using content analysis, electronic nose technique, electronic tongue technique, and metabolomics technique based on ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry and gas chromatography-time-of-flight-mass spectrometry. The content changes, flavor changes, taste changes, metabolite numbers and differential metabolite numbers for both tilapia skin and soup mainly occurred in the initial 30 min. Moreover, the initial 10 min was the key period for the metabolite changes in the boiling process. Further, the differential metabolites in these three periods (0–10, 10–30, and 30–60 min) were identified to show the metabolites migration process. Six (adenine, gingerol, terephthalic acid, vanillin, pentanenitrile, and 2-pyrrolidinonede) and seven (butyramide, lysope(0:0/20:4(5z,8z,11z,14z)), lysope(22:6(4z,7z,10z,13z,16z,19z)/0:0), linoleic acid, N-acetylneuraminic acid, L-threose, and benzoin) chemicals were screened out in the differential metabolites of tilapia skin and soup, respectively, with Variable Importance in the Projection of >1 and p value of <0.05. This work would be beneficial to understand the sensory and metabolite migration in the preparation process of fish soup and provided a metabolomic analysis route to analyze metabolites migration in food.

Effects of ultrasound-assisted thawing on lamb meat quality and oxidative stability during refrigerated storage using non-targeted metabolomics

The aim of this study was to evaluate the changes of ultrasound-assisted thawing on lamb meat quality and differential metabolite profiles during refrigerated storage. Compared with flow water thawing (FW), pH, a*, C*, and sulfhydryl content of lamb were significantly increased, while L*, drip loss and cooking loss were significantly decreased after ultrasound-assisted thawing (UT). On day 1 (UT1 and FW1) and day 7 (UT7 and FW7) in the UT and FW groups, principal component analysis explained 42.22% and 39.25% of the total variance. In this study, 44 (UT1 and FW1) and 47 (UT7 and FW7) differentially expressed metabolites were identified, including amino acids, carbohydrates and their conjugates, nucleic acids, carbonyl compounds and others. The results of this study provide data to clarify the differences between UT and FW, and lay a foundation for the application of ultrasound-assisted thawing in the meat industry.

Advanced Lipidomics in the Modern Meat Industry: Quality Traceability, Processing Requirement, and Health Concerns

Over the latest decade, lipidomics has been extensively developed to give robust strength to the qualitative and quantitative information of lipid molecules derived from physiological animal tissues and edible muscle foods. The main lipidomics analytical platforms include mass spectrometry (MS) and nuclear magnetic resonance (NMR), where MS-based approaches [e.g., "shotgun lipidomics," ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF-MS)] have been widely used due to their good sensitivity, high availability, and accuracy in identification/quantification of basal lipid profiles in complex biological point of view. However, each method has limitations for lipid-species [e.g., fatty acids, triglycerides (TGs), and phospholipids (PLs)] analysis, and necessitating the extension of effective chemometric-resolved modeling and novel bioinformatic strategies toward molecular insights into alterations in the metabolic pathway. This review summarized the latest research advances regarding the application of advanced lipidomics in muscle origin and meat processing. We concisely highlighted and presented how the biosynthesis and decomposition of muscle-derived lipid molecules can be tailored by intrinsic characteristics during meat production (i.e., muscle type, breed, feeding, and freshness). Meanwhile, the consequences of some crucial hurdle techniques from both thermal/non-thermal perspectives were also discussed, as well as the role of salting/fermentation behaviors in postmortem lipid biotransformation. Finally, we proposed the inter-relationship between potential/putative lipid biomarkers in representative physiological muscles and processed meats, their metabolism accessibility, general nutritional uptake, and potency on human health.

Comparative Metabolomics Study of Chaenomeles speciosa (Sweet) Nakai from Different Geographical Regions

Chaenomeles speciosa (Sweet) Nakai (C. speciosa) is not only a Chinese herbal medicine but also a functional food widely planted in China. Its fruits are used to treat many diseases or can be processed into food products. This study aims to find key metabolic components, distinguish the differences between geographical regions and find more medicinal and edible values of C. speciosa fruits. We used ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) and widely targeted metabolomics analysis to reveal key and differential metabolites. We identified 974 metabolites and screened 548 differential metabolites from 8 regions. We selected significantly high-content differential metabolites to visualize a regional biomarker map. Comparative analysis showed Yunnan had the highest content of total flavonoids, the highest amounts of compounds related to disease resistance and drug targets and the most significant difference from the other regions according to the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database, a unique platform for studying the systematic pharmacology of Chinese herbal medicine and capturing the relationship between drugs, targets and diseases. We used oral bioavailability (OB) ≥ 30% and drug likeness (DL) ≥ 0.18 as the selection criteria and found 101 key active metabolites, which suggests that C. speciosa fruits were rich in healthy metabolites. These results provide valuable information for the development of C. speciosa.

Metabolites Analysis on Water-Holding Capacity in Beef Longissimus lumborum Muscle during Postmortem Aging

Currently, the metabolomic research on water-holding capacity (WHC) of beef during postmortem aging is still insufficient. In this paper, the kit method was adopted for energy metabolites testing, the ultra-high-performance liquid chromatography (UHPLC) system was used for sample separation, and the mass spectrometer was applied to collect the primary and secondary spectra of the samples. The results showed that lactic acid reached saturation at day 2 postmortem, while energy metabolites changed significantly within day 2 postmortem (p < 0.05). Based on these findings, it was suggested that the energy metabolism qualities of the beef had already achieved a largely stable state at around day 2 postmortem. Then, through metabolomic analysis, 25 compounds were differentially abundant at days 0, 0.5, 1, and 2 during postmortem aging. Within the period of day 0−2 postmortem, the purine metabolism in beef was relatively active until 0.5 d postmortem, while glycolysis metabolism remained active until day 2 postmortem. The functions of the identified metabolites contribute to a more detailed molecular view of the processes behind WHC and are a valuable resource for future investigations into the flavor of postmortem beef.

Comparative metabolite fingerprinting of chia, flax and sesame seeds using LC-MS untargeted metabolomics

Chia, flax, and sesame seeds are well known for their nutritional quality and are commonly included in bakery products. So far, the development of methods to verify their presence and authenticity in foods is a requisite and a raised need. In this work we applied untargeted metabolomics to propose authenticity markers. Seeds were analyzed by HPLC-MS/MS and 9938 features in negative mode and 9044 in positive mode were obtained by Mzmine. After isotopes grouping, alignment, gap-filling, filtering adducts, and normalization, PCA was applied to explore the dataset and recognize pre-existent classification patterns. OPLS-DA analysis and S-Plots were used as supervised methods. Twenty-five molecules (12 in negative mode and 13 in positive mode) were selected as discriminant for the three seeds, polyphenols and lignans were identified among them. To the best of our knowledge, this is the first approach using non-target HPLC-MS/MS for the authentication of chia, flax and sesame seeds.

Current State of Metabolomics Research in Meat Quality Analysis and Authentication

In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.

Muscle and Serum Metabolomics for Different Chicken Breeds under Commercial Conditions by GC-MS

Globally, village chicken is popular and is known as a premium meat with a higher price. Food fraud can occur by selling other chicken breeds at a premium price in local markets. This study aimed to distinguish local village chicken from other chicken breeds available in the market, namely, colored broiler (Hubbard), broiler (Cobb), and spent laying hen (Dekalb) in pectoralis major and serum under commercial conditions using an untargeted metabolomics approach. Both pectoralis major and serum were analyzed using gas chromatography-mass spectrometry (GC-MS). The principal component analysis (PCA) results distinguished four different chicken breeds into three main groups for pectoralis major and serum. A total of 30 and 40 characteristic metabolites were identified for pectoralis major and serum, respectively. The four chicken breeds were characterized by the abundance of metabolites such as amino acids (L-glutamic acid, L-threonine, L-serine, L-leucine), organic acids (L-lactic acid, succinic acid, 3-hydroxybutyric acid), sugars (D-allose, D-glucose), sugar alcohols (myo-inositol), and fatty acids (linoleic acid). Our results suggest that an untargeted metabolomics approach using GC-MS and PCA could discriminate chicken breeds for pectoralis major and serum under commercial conditions. In this study, village chicken could only be distinguished from colored broiler (Hubbard) by serum samples.

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.