Meat, the metabolites: an integrated metabolite profiling and lipidomics approach for the detection of the adulteration of beef with pork

Untargeted metabolomics using liquid chromatography-high resolution mass spectrometry and chemometrics for analysis of non-halal meats adulteration in beef meat

OBJECTIVE

The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach.

METHODS

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr.

RESULTS

The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R2>0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w).

CONCLUSION

A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

A current review of U.S. beef flavor I: Measuring beef flavor

Historically, consumer acceptance of beef was determined by tenderness. Developments in genetics and management over the last couple of decades have improved tenderness to the point that it is secondary to other factors in beef's taste. Flavor, however, is an extraordinarily complex taste attribute dependent on biological sensors in the mouth, sinus cavity, and jaws. The culinary industry has recently focused on innovative ways to give consumers new products satisfying their curiosity about different foods, especially proteins. Competition from plant-based, cell-based, and even other animal-based proteins provides diversity in consumers' ability to select a protein that satisfies their desire to include unique products in their diet. Consequently, the beef industry has focused on flavor for the last 10 to 15 years to determine whether it can provide the guardrails for beef consumption in the future. The U.S. beef industry formed a Flavor Working Group in 2012 composed of the authors listed here to investigate new and innovative ways to manage and measure beef flavor. The results of this working group have resulted in dozens of papers, presentations, abstracts, and symposia. The objective of this manuscript is to summarize the research developed by this working group and by others worldwide that have investigated methodologies that measure beef flavor. This paper will describe the strengths of the research in beef flavor measurement and point out future needs that might be identified as technology advances.

Exploration of the shelf-life difference between chilled beef and pork with similar initial levels of bacterial contamination

This study compared the shelf-life of beef and pork longissimus lumborum muscles (loins) that had the same initial bacterial loads and were held under the same chilled storage conditions. To identify the underlying pathways, comparisons were conducted from the perspective of the spoilage indicators; protease/lipase activity, and the volatile organic compounds (VOC) generated over 28 d of chilled storage. The initial total viable microbial count (TVC) on Day 0 for both type of meat was 4.3 log10 CFU/g. It was found that the TVC of beef and pork did not differ throughout the total chilled storage period and both ultimately exceeded 7 log10 CFU/g after 28 d. Based on total volatile basic nitrogen (TVB-N) guidelines, pork was spoilt after 21 d of chilled storage and therefore 7 d earlier than beef. Changes in the concentration of VOC spoilage biomarkers, including 1-octen-3-ol, 1-octanol, nonanal, and others, confirmed that pork had a shorter shelf-life than beef. An important reason for the difference in shelf-life between the two types of meat was that pork had a higher protease activity, although the beef had higher levels of total lipase activity. These findings help us understand the differences in the spoilage process of raw meat from different species and explore specific measures to control the spoilage of beef or pork.

Analysis of dog meat adulteration in beef meatballs using non-targeted UHPLC-Orbitrap HRMS metabolomics and chemometrics for halal authentication study

Due to the different price and high quality, halal meat such as beef can be adulterated with non-halal meat with low price to get an economical price. The objective of this research was to develop an analytical method for halal authentication testing of beef meatballs (BM) from dog meat (DM) using a non-targeted metabolomics approach employing liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics. The differentiation of authentic BM from that adulterated with DM was successfully performed using partial least square-discriminant analysis (PLS-DA) with high accuracy (R2X = 0.980, and R2Y = 0.980) and good predictivity (Q2 = 0.517). In addition, partial least square (PLS) and orthogonal PLS (OPLS) were successfully used to predict the DM added (% w/w) in BM with high accuracy (R2 > 0.990). A number of metabolites, potential for biomarker candidates, were identified to differentiate BM and that adulterated with DM. It showed that the combination of a non-targeted LC-HRMS Orbitrap metabolomics and chemometrics could detect up to 0.1% w/w of DM adulteration. The developed method was successfully applied for analysis of commercial meatball samples (n = 28). Moreover, pathway analysis revealed that beta-alanine, histidine, and ether lipid metabolism were significantly affected by dog meat adulteration. In summary, this developed method has great potential to be developed and used as an alternative method for analysis of non-halal meats in halal meat products.

Lipidomics reveals lipid changes in the intramuscular fat of geese at different growth stages

The quality (color, tenderness, juiciness, protein content, and fat content) of poultry meat is closely linked to age, with older birds typically exhibiting increased intramuscular fat (IMF) deposition. However, specific lipid metabolic pathways involved in IMF deposition remain unknown. To elucidate the mechanisms underlying lipid changes, we conducted a study using meat geese at 2 distinct growth stages (70 and 300 d). Our findings regarding the approximate composition of the meat revealed that as the geese aged 300 d, their meat acquired a chewier texture and displayed higher levels of IMF. Liquid chromatography-mass spectrometry (LC-MS) was employed for lipid profiling of the IMF. Using a lipid database, we identified 849 lipids in the pectoralis muscle of geese. Principal component analysis and orthogonal partial least squares discriminant analysis were used to distinguish between the 2 age groups and identify differential lipid metabolites. As expected, we observed significant changes in 107 lipids, including triglycerides, diglycerides, phosphatidylethanolamine, alkyl-glycerophosphoethanolamine, alkenyl-glycerophosphoethanolamine, phosphatidylcholine, phosphatidylinositol, lysophosphatidylserine, ceramide-AP, ceramide-AS, free fatty acids, cholesterol lipids, and N-acyl-lysophosphatidylethanolamine. Among these, the glyceride molecules exhibited the most pronounced changes and played a pivotal role in IMF deposition. Additionally, increased concentration of phospholipid molecules was observed in breast muscle at 70 d. Unsaturated fatty acids attached to lipid side chain sites enrich the nutritional value of goose meat. Notably, C16:0 and C18:0 were particularly abundant in the 70-day-old goose meat. Pathway analysis demonstrated that glycerophospholipid and glyceride metabolism were the pathways most significantly associated with lipid changes during goose growth, underscoring their crucial role in lipid metabolism in goose meat. In conclusion, this work provides an up-to-date study on the lipid composition and metabolic pathways of goose meat and may provide a theoretical basis for elucidating the nutritional value of goose meat at different growth stages.

Amplification-Based CRISPR/Cas12a Biosensor Targeting the COX1 Gene for Specific Detection of Porcine DNA

We propose a CRISPR/Cas12a-mediated recombinase polymerase amplification (RPA) detection method that combines RPA with Cas12a cleavage for the detection of halal food adulteration, which is of global concern, particularly for Muslim consumers. We optimized the reagent concentrations for the Cas12a cleavage steps and designed and screened gRNA targeting a conserved area of the mitochondrial cytochrome C oxidase subunit I (COX1) gene. This procedure successfully detected the presence of porcine components as low as 5 pg/μL in the linear range of 5-1000 pg/μL. The assay's detection limit was 500 times lower than CRISPR-based approaches that exclude a preamplification step, allowing the detection of trace porcine DNA in food samples. The assay additionally showed no cross-reaction with nontarget species. Therefore, this detection platform shows tremendous potential as a method for the quick, sensitive, and specific detection of porcine-derived components.

A Critical Overview of HPLC-MS-Based Lipidomics in Determining Triacylglycerol and Phospholipid in Foods

With the current advancement in mass spectrometry (MS)-based lipidomics, the knowledge of lipidomes and their diverse roles has greatly increased, enabling a deeper understanding of the action of bioactive lipid molecules in plant- and animal-based foods. This review provides in-depth information on the practical use of MS techniques in lipidomics, including lipid extraction, adduct formation, MS analysis, data processing, statistical analysis, and bioinformatics. Moreover, this contribution demonstrates the effectiveness of MS-based lipidomics for identifying and quantifying diverse lipid species, especially triacylglycerols and phospholipids, in foods. Further, it summarizes the wide applications of MS-based lipidomics in food science, such as for assessing food processing methods, detecting food adulteration, and measuring lipid oxidation in foods. Thus, MS-based lipidomics may be a useful method for identifying the action of individual lipid species in foods.

Analysis of Pork in Beef Sausages Using LC-Orbitrap HRMS Untargeted Metabolomics Combined with Chemometrics for Halal Authentication Study

Beef sausage (BS) is one of the most favored meat products due to its nutrition and good taste. However, for economic purposes, BS is often adulterated with pork by unethical players. Pork consumption is strictly prohibited for religions including Islam and Judaism. Therefore, advanced detection methods are highly required to warrant the halal authenticity of BS. This research aimed to develop a liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method to determine the halal authenticity of BS using an untargeted metabolomics approach. LC-HRMS was capable of detecting various metabolites in BS and BS containing pork. The presence of pork in BS could be differentiated using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) with high accuracy. PLS-DA perfectly classified authentic BS and BS containing pork in all concentration levels of pork with R2X = (0.821), R2Y(= 0.984), and Q2 = (0.795). The level of pork in BS was successfully predicted through partial least squares (PLS) and orthogonal PLS (OPLS) chemometrics. Both models gave high R2 (>0.99) actual and predicted values as well as few errors, indicating good accuracy and precision. Identification of discriminating metabolites' potential as biomarker candidates through variable importance for projections (VIP) value revealed metabolites of 2-arachidonyl-sn-glycero-3-phosphoethanolamine, 3-hydroxyoctanoylcarnitine, 8Z,11Z,14Z-eicosatrienoic acid, D-(+)-galactose, oleamide, 3-hydroxyhexadecanoylcarnitine, arachidonic acid, and α-eleostearic acid as good indicators to detect pork. It can be concluded that LC-HRMS metabolomics combined with PCA, PLS-DA, PLS, and OPLS was successfully used to detect pork adulteration in beef sausages. The results imply that LC-HRMS untargeted metabolomics in combination with chemometrics is a promising alternative as an analytical technique to detect pork in sausage products. Further analysis of larger samples is required to warrant the reproducibility.

A study of the lipid profile of Coix seeds from four areas based on untargeted lipidomics combined with multivariate algorithms to enable tracing of their origin

The geographical traceability of food products is seen as a distinctive feature of the future of food which is increasingly becoming a concern for consumers. In this research, differences in the lipid composition of Coix seed samples from four major Chinese origins were investigated using non-targeted lipidomics. By multivariate statistical analysis, unsupervised PCA and OPLS-DA based differentiation between the four origins of Coix seed samples could be achieved. The OPLS-DA VIP > 1 screened 72 lipids out of 1211 lipids as potential markers to distinguish Coix seeds from different origins. In addition, the potential markers (SPH(d16:0), Cer(d18:2/20:0 + O) and PC(8:0e/8:0) were combined with statistical analysis algorithms to construct a discriminant function for rapid differentiation of Coix seed samples from different origins and a specific function for different origins with 100% discrimination accuracy. In general, a rapid and accurate method combining multivariate chemometrics and algorithms was developed based on untargeted lipidomics to determine the geographical origin of Coix seed samples, which can also be applied to other agricultural products.

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.

Microbial spoilage mechanisms of vacuum-packed lamb meat: A review

Lamb meat is an important export commodity, however chilled vacuum-packed (VP) lamb has approximately half the shelf-life of beef under the same storage conditions. This makes the industry more vulnerable to financial losses due to long shipping times and unexpected spoilage. Understanding the spoilage mechanisms of chilled VP lamb in relation to VP beef is important for developing effective strategies to extend the shelf-life of lamb. This review has discussed various key factors (i.e., pH, fat, and presence of bone) that have effects on microbial spoilage of VP lamb contributing to its shorter shelf-life relative to VP beef. A range of bacterial organisms and their metabolisms in relevance to lamb spoilage are also discussed. The data gap in the literature regarding the potential mechanisms of spoilage in VP red meat is highlighted. This review has provided the current understanding of key factors affecting the shelf-life of VP lamb relative to VP beef. It has also identified key areas of research to further understand the spoilage mechanisms of VP lamb. These include investigating the potential influence of fat and bone (including bone marrow) on the shelf-life, as well as assessing changes in the meat metabolome as the spoilage microbial community is developing using an integrated approach. Such new knowledge would aid the development of effective approaches to extend the shelf-life of VP lamb.

Lipid analysis of meat from Bactrian camel (Camelus bacterianus), beef, and tails of fat-tailed sheep using UPLC-Q-TOF/MS based lipidomics

Introduction

As a source of low-cost and high-quality meat for human beings, the consumption of camel meat was increasing, and beef has similar texture and nutritional characteristics with camel meat. Camel hump and fatty-tails are important parts of fat storage for camels and fat-tailed lambs, respectively, which were to adapt and endure harsh environments. Considering their similar physiological functions, their fat composition might be similar. Lipidomics is a system-level analysis of lipids method, which play an important role in the determination and quantification of individual lipid molecular specie, food adulteration and labeling.

Methods

A GC/MS was used to analyze fatty acids composition of Xinjiang Bactrian camel meat, hump, beef, and fatty-tails. UPLC-Q-TOF/MS based on lipidomics approach was used to analyze lipid composition, characterize and examine the lipid differences in Xinjiang Bactrian camel meat, hump, beef, and fatty-tails.

Results and discussion

The major fatty acids of the four samples were C16:0, C18:0, and C18:1cis, and camel meat had a significant low SFA content and high MUFA content. A total of 342 lipid species were detected, 192, 64, and 79 distinguishing lipids were found in the groups camel hump compared to camel meat, camel meat compared to beef, and camel hump compared to fatty-tails, respectively. Lipid metabolisms of ether lipid, glycerophospholipid, glycerolipid, and sphingolipid were the most influential pathways revealed by KEGG analysis. The results contributed to enrich the lipid information of Bactrian camel meat, and indicated that UPLC-Q-TOF/MS based on lipidomics was an alternative method to distinguish meat samples.

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.

Adulteration detection technologies used for halal/kosher food products: an overview

In the Islamic and Jewish religions, there are various restrictions that should be followed in order for food products to be acceptable. Some food items like pork or dog meat are banned to be consumed by the followers of the mentioned religions. However, illegally, some food producers in various countries use either the meat or the fat of the banned animals during food production without being mentioned in the label on the final products, and this considers as food adulteration. Nowadays, halal or kosher labeled food products have a high economic value, therefore deceiving the consumers by producing adulterated food is an illegal business that could make large gains. On the other hand, there is an insistent need from the consumers for getting reliable products that comply with their conditions. One of the main challenges is that the detection of food adulteration and the presence of any of the banned ingredients is usually unnoticeable and cannot be determined by the naked eye. As a result, scientists strove to develop very sensitive and precise analytical techniques. The most widely utilized techniques for the detection and determination of halal/kosher food adulterations can be listed as High-Pressure Liquid Chromatography (HPLC), Capillary Electrophoresis (CE), Gas Chromatography (GC), Electronic Nose (EN), Polymerase Chain Reaction (PCR), Enzyme-linked Immuno Sorbent Assay (ELISA), Differential Scanning Calorimetry (DSC), Nuclear Magnetic Resonance (NMR), Near-infrared (NIR) Spectroscopy, Laser-induced Breakdown Spectroscopy (LIBS), Fluorescent Light Spectroscopy, Fourier Transform Infrared (FTIR) Spectroscopy and Raman Spectroscopy (RS). All of the above-mentioned techniques were evaluated in terms of their detection capabilities, equipment and analysis costs, accuracy, mobility, and needed sample volume. As a result, the main purposes of the present review are to identify the most often used detection approaches and to get a better knowledge of the existing halal/kosher detection methods from a literature perspective.

Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication

Adulteration of high-quality meat products using lower-priced meats, such as pork, is a crucial issue that could harm consumers. The consumption of pork is strictly forbidden in certain religions, such as Islam and Judaism. Therefore, the objective of this research was to develop untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with chemometrics for analysis of pork in beef meatballs for halal authentication. We investigated the use of non-targeted LC-HRMS as a method to detect such food adulteration. As a proof of concept using six technical replicates of pooled samples from beef and pork meat, we could show that metabolomics using LC-HRMS could be used for high-throughput screening of metabolites in meatballs made from beef and pork. Chemometrics of principal component analysis (PCA) was successfully used to differentiate beef meatballs and pork meatball samples. Partial least square-discriminant analysis (PLS-DA) clearly discriminated between halal and non-halal beef meatball samples with 100% accuracy. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) perfectly discriminated and classified meatballs made from beef, pork, and a mixture of beef-pork with a good level of fitness (R²X = 0.88, R²Y = 0.71) and good predictivity (Q² = 0.55). Partial least square (PLS) and orthogonal PLS (OPLS) were successfully applied to predict the concentration of pork present in beef meatballs with high accuracy (R² = 0.99) and high precision. Thirty-five potential metabolite markers were identified through VIP (variable important for projections) analysis. Metabolites of 1-(1Z-hexadecenyl)-sn-glycero-3-phosphocholine, acetyl-l-carnitine, dl-carnitine, anserine, hypoxanthine, linoleic acid, and prolylleucine had important roles for predicting pork in beef meatballs through S-line plot analysis. It can be concluded that a combination of untargeted metabolomics using LC-HRMS and chemometrics is promising to be developed as a standard analytical method for halal authentication of highly processed meat products.

1H NMR Metabolic Profiling and Meat Quality in Three Beef Cattle Breeds from Northeastern Thailand

The increasing need for effective analytical tools to evaluate beef quality has prompted the development of new procedures to improve the animal sector's performance. In this study, three beef breeds-Thai native (TN), crossbred Brahman × Thai native (BT), and crossbred Charolais × Brahman (CB)-were compared in terms of their physicochemical and metabolic profiles. The findings demonstrated that TN beef was lighter and tougher than other beef. Beef odor was stronger in BT. In addition, CB beef was the most tender and had the highest intramuscular fat content. Twenty-one different metabolites were found overall through NMR and chemometric approaches. The primary factors contributing to the difference in OPLS-DA loading plots were acetylcholine, valine, adenine, leucine, phosphocreatine, β-hydroxypyruvate, ethanol, adenosine diphosphate, creatine, acetylcholine, and lactate. The multivariate analysis indicated that these metabolites in beef cattle breeds could be distinguished using NMR spectroscopy. The results of this study provide valuable information on the quality and meat metabolites of different breeds. This could help in the development of a more accurate assessment of the quality of beef in future research.

iPSC Technology: An Innovative Tool for Developing Clean Meat, Livestock, and Frozen Ark

Induced pluripotent stem cell (iPSC) technology is an emerging technique to reprogram somatic cells into iPSCs that have revolutionary benefits in the fields of drug discovery, cellular therapy, and personalized medicine. However, these applications are just the tip of an iceberg. Recently, iPSC technology has been shown to be useful in not only conserving the endangered species, but also the revival of extinct species. With increasing consumer reliance on animal products, combined with an ever-growing population, there is a necessity to develop alternative approaches to conventional farming practices. One such approach involves the development of domestic farm animal iPSCs. This approach provides several benefits in the form of reduced animal death, pasture degradation, water consumption, and greenhouse gas emissions. Hence, it is essentially an environmentally-friendly alternative to conventional farming. Additionally, this approach ensures decreased zoonotic outbreaks and a constant food supply. Here, we discuss the iPSC technology in the form of a "Frozen Ark", along with its potential impact on spreading awareness of factory farming, foodborne disease, and the ecological footprint of the meat industry.

Identification of Four Chicken Breeds by Hyperspectral Imaging Combined with Chemometrics

The current study aims to explore the potential of the combination of hyperspectral imaging and chemometrics in the rapid identification of four chicken breeds. The hyperspectral data of four chicken breeds were collected in the range of 400–900 nm. Five pretreatment methods were used to pretreat the original spectra. The important characteristic wavelength variables were extracted by random frog (RF), successive projection algorithm (SPA), and competitive adaptive reweighted sampling (CARS) algorithms. The classification models were established by using support vector machine (SVM), k-nearest neighbor (KNN), and partial least squares-discriminant analysis (PLS-DA). The results showed that the mean normalization pretreatment method was preferable, and overall classification accuracy of SVM-based models was higher than that of KNN-based and PLS-DA-based models. The correct classification rate (CCR) of the full-spectrum SVM model (Full-SVM) could reach 96.25%. The SPA method extracted 13 important wavelengths, and the SVM model based on SPA (SPA-SVM) achieved 90% CCR. This study can provide a theoretical reference for the discriminant analysis of chicken breeds.

A Divergent Selection on Breast Meat Ultimate pH, a Key Factor for Chicken Meat Quality, is Associated With Different Circulating Lipid Profiles

Background: Chicken meat has become a major source of protein for human consumption. However, the quality of the meat is not yet under control, especially since pH values that are too low or too high are often observed. In an attempt to get a better understanding of the genetic and biochemical determinants of the ultimate pH, two genetic lines of broilers were divergently selected for low (pHu−) or high (pHu+) breast meat pHu. In this study, the serum lipidome of 17-day-old broilers from both lines was screened for pHu markers using liquid-chromatography coupled with mass spectrometry (LC-HRMS).

Results: A total of 185 lipids belonging to 4 groups (glycerolipids, glycerophospholipids, sterols, sphingolipids) were identified in the sera of 268 broilers from the pHu lines by targeted lipidomics. The glycerolipids, which are involved in energy storage, were in higher concentration in the blood of pHu− birds. The glycerophospholipids (phosphatidylcholines, phosphatidylethanolamines) with long and polyunsaturated acyl chains were more abundant in pHu+ than in pHu− while the lysophosphatidylcholines and lysophosphatidylethanolamines, known to be associated with starch, were observed in higher quantity in the serum of the pHu− line. Finally, the concentration of the sterols and the ceramides, belonging to the sphingolipids class, were higher in the pHu+ and pHu−, respectively. Furthermore, orthogonal partial least-squares analyses highlighted a set of 68 lipids explaining 77% of the differences between the two broilers lines (R²Y = 0.77, Q² = 0.67). Among these lipids, a subset of 40 predictors of the pHu value was identified with a Root Mean Squared Error of Estimation of 0.18 pH unit (R²Y = 0.69 and Q² = 0.62). The predictive model of the pHu value was externally validated on 68 birds with a Root Mean Squared Error of Prediction of 0.25 pH unit.

Conclusion: The sets of molecules identified will be useful for a better understanding of relationship between serum lipid profile and meat quality, and will contribute to define easily accessible pHu biomarkers on live birds that could be useful in genetic selection.

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.

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.

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.

Investigation of the characteristics of different shrimps by species and habitat using gas chromatography/mass spectrometry based metabolomics

Approximately 6.5 million tons of shrimp are consumed annually worldwide. The price of shrimp is greatly influenced by species and habitat (e.g., farmed vs wild-caught). In recent years, false labeling has become a problem in the shrimp industry. False labeling can include species, habitat (whether farmed or wild-caught). This problem is motivated by the potential for economic benefit, and significantly reduces the consumer reliability of food. As a first step in establishing a detection method, we took a metabolomics approach to elucidate phenotypic diversity by assessing genetic differences and environmental factors. Metabolites identified by gas chromatography/mass spectrometry (GC/MS) analysis were subjected to multivariate analysis to identify metabolites that correlated with shrimp species and habitat. The characteristics based on species and habitat were observed respectively. For species, the classification approximately tended to be based on taxonomy. It suggests that species different have strong effect on metabolite profiles. In particular, the difference between Panaediae and Pandalidae was significantly observed, and some fatty acids such as palmitoleic acid and elaidic acid are abundant in Pandalidae. Among Pandalidae, Japanese tiger shrimp was characterized by metabolites related to purine metabolism. For habitat, farmed shrimp had a high amino acid content, and wild caught shrimp had a high fatty acid content. Habitat-based separation was observed in Indonesian black tiger shrimp samples, indicating that metabolites such as glycolic acid, phosphate, and pentadecanoic acid are characteristic components of natural black tiger shrimp.

UHPLC-Q-Orbitrap HRMS-based quantitative lipidomics reveals the chemical changes of phospholipids during thermal processing methods of Tan sheep meat

Thermal processing affects the lipid compositions of meat products. The study determined the effects of boiled, steamed and roasted processing methods on the lipidomics profiles of Tan sheep meat with a validated UPLC-Q-Orbitrap HRMS combined lipid screening strategy method. Combined with sphingolipid metabolism, the boiled approach was the suitable choice for atherosclerosis patients for more losses of sphingomyelin than ceramide in meat. The similarly less losses of phosphatidylcholine and lysophosphatidylcholine showed in glycerophospholipid metabolism implied that steamed Tan sheep meat was more suitable for the populations of elderly and infants. Furthermore, a total of 90 lipids with significant difference (VIP > 1) in 6 lipid subclasses (sphingomyelin, ceramide, lysophosphatidylcholine, phosphatidylcholine, phosphatidylethanolamines, triacylglycerol,) were quantified among raw and three types of thermal processed Tan sheep meat, further providing useful information for identification of meat products with different thermal processing methods (LOD with 0.14-0.31 μg kg^-1, LOQ with 0.39-0.90 μg kg^-1).

Analysis of lipidomics profile of rice and changes during storage by UPLC-Q-extractive orbitrap mass spectrometry

Rice is one of major staple food worldwide; however, lipid profile of rice and changes during storage remain unclear. Herein, an UPLC-Q-Exactive Orbitrap/MS method was applied for comprehensive lipidomics analysis of rice during storage. A total of 21 subclasses of 277 lipids including fatty acid (36 species), (O-acyl)-1-hydroxy fatty acid (6 species), diglyceride (16 species), triglyceride (89 species), lysophosphatidylcholine (4 species), phosphatidylcholine (14 species), phosphatidylethanolamine (28 species), phosphatidylglycerol (6 species), phosphatidylinositol (11species), cardiolipin (4 species), ceramide (8 species), hexosylceramide (20 species), dihexosylceramide (2 species), trihexosylceramide (1 species), sitosterol ester (1species), acyl hexosyl campesterol ester (5 species), acyl hexosyl sitosterol ester (6 species), digalactosyldiacylglycerol (6 species), monogalactosyldiacylglycerol (9 species), monogalactosylmonoacylglycerol (2 species), and sulfoquinovosyldiacylglycerol (3 species), were first identified in rice during storage. In addition, ceramide, fatty acid, (O-acyl)-1-hydroxy fatty acid, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, lysophosphatidylcholine, and diglyceride were quantified. Furthermore, statistical analysis of all lipids was performed based on MetaboAnalyst software. The results showed that 22 lipids were significantly different between fresh and stored (360 and 540 days storage) rice demonstrating that lipid composition changed during storage. These different lipids involved 11 metabolic pathways, of which linoleic acid metabolism, glycerophospholipid metabolism, and cutin, suberine and wax biosynthesis were the most relevant. Our study provides useful information for lipidomics profile of rice during storage.

Development of an optimized sample preparation method for quantification of free fatty acids in food using liquid chromatography-mass spectrometry

Accurate and precise determination of free fatty acid (FFA) contents is essential for quality control and assurance in food production. Herein, a mass spectrometric study was performed to develop a sample preparation protocol that can minimize exogenous FFA contamination during the quantification of FFA in food. The quantities of exogenous FFAs were measured using various combinations of seven pretreatment methods for a sample tube, three extraction methods, and four types of sample tubes. Methanol washing could effectively reduce exogenous palmitic acid (PA) and stearic acid (SA) by 73 and 64%, respectively, in contrast to furnace baking resulting in a decrease in the amount of PA and SA contaminants by 50 and 37%, respectively. A lower amount of FFA contaminants was extracted from glass tubes during comparative analysis of the four different sample tubes studied. A combination of a methanol-washed glass tube and chloroform extraction solvent was determined to be the optimal method for minimizing the error in FFA quantification. The optimized sample preparation protocol used for FFA quantification can lower the amount of foreign palmitic acid and stearic acid to the sub-nanomolar level in the analysis of FFAs in skimmed milk.

Use of Rapid Evaporative Ionisation Mass Spectrometry fingerprinting to determine the metabolic changes to dry-aged lean beef due to different ageing regimes

Rapid Evaporative Ionisation Mass Spectrometry (REIMS) was used to determine the impact of in-bag ageing regimes (stepwise-ageing at different air velocities and straight-dry-ageing) and trimming on the metabolic profile of dry-aged lean beef. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) models based on 1705 tentatively identified m/z features were found for ageing methods (Q² = 0.85), ageing time (0 vs. 21 days, Q² = 0.95) and sampling locations (surface meat vs. trimmings, Q² = 0.94). No significant (P > 0.05) difference in metabolites due to air velocities. Small metabolites such as dipeptides and amino acids were more abundant, especially on the surface of untrimmed lean beef, following 21 days of straight-dry-ageing. Stepwise-ageing produced different metabolic profiles from straight-dry-ageing, suggesting that the two methods may differ in dry-aged meat quality and flavour. This work demonstrates REIMS's potential for real time differentiation of meat on processing parameters.

Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry and Rapid Evaporative Ionization Mass Spectrometry Were Used to Develop a Lamb Authentication Method: A Preliminary Study

A untargeted metabolomics approach was proposed in this study based on ultra-high performance liquid chromatography quadrupole time-of-flight (UHPLC-QTOF) and rapid evaporative ionization mass spectrometry (REIMS) to discriminate lamb and mutton meat and investigate their subtle metabolic differences, considering the higher popularity of lamb meat than mutton in the market. Multivariate statistical analysis was performed for data processing in order to distinguish between the two sample types. A total of 42 potential metabolites (20 in positive and 22 in negative ion mode) were defined for UHPLC-QTOF analysis, which provided references for discriminating the two kinds of meat. Furthermore, three potential markers were tentatively identified using LC/MS data against chemical databases. In addition, 14 potential metabolites were putatively identified in negative ion mode using the LipidMaps database. Meanwhile, the data-driven soft independent modeling of class analogy (DD-SIMCA) model was established, which could rapidly differentiate non-pretreated lamb meat and mutton with 92% specificity, rendering REIMS a promising technique for meat identification.

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.

Comparison of Targeted (HPLC) and Nontargeted (GC-MS and NMR) Approaches for the Detection of Undeclared Addition of Protein Hydrolysates in Turkey Breast Muscle

The adulteration of fresh turkey meat by the undeclared addition of protein hydrolysates is of interest for fraudsters due to the increase of the economic gain by substituting meat with low cost ingredients. The aim of this study was to compare the suitability of three different analytical techniques such as GC-MS and ¹H-NMR with HPLC-UV/VIS as a targeted method, for the detection of with protein hydrolysates adulterated turkey meat. For this, turkey breast muscles were treated with different plant- (e.g., wheat) and animal-based (e.g., gelatin, casein) protein hydrolysates with different hydrolyzation degrees (15–53%: partial; 100%: total), which were produced by enzymatic and acidic hydrolysis. A water- and a nontreated sample (REF) served as controls. The data analyses revealed that the hydrolysate-treated samples had significantly higher levels of amino acids (e.g., leucine, phenylalanine, lysine) compared with REF observed with all three techniques concordantly. Furthermore, the nontargeted metabolic profiling (GC-MS and NMR) showed that sugars (glucose, maltose) and/or by-products (build and released during acidic hydrolyses, e.g., levulinic acid) could be used for the differentiation between control and hydrolysates (type, degrees). The combination of amino acid profiling and additional compounds gives stronger evidence for the detection and classification of adulteration in turkey breast meat.

Comparative review and the recent progress in detection technologies of meat product adulteration

Meat adulteration, mainly for the purpose of economic pursuit, is widespread and leads to serious public health risks, religious violations, and moral loss. Rapid, effective, accurate, and reliable detection technologies are keys to effectively supervising meat adulteration. Considering the importance and rapid advances in meat adulteration detection technologies, a comprehensive review to summarize the recent progress in this area and to suggest directions for future progress is beneficial. In this review, destructive meat adulteration technologies based on DNA, protein, and metabolite analyses and nondestructive technologies based on spectroscopy were comparatively analyzed. The advantages and disadvantages, application situations of these technologies were discussed. In the future, determining suitable indicators or markers is particularly important for destructive methods. To improve sensitivity and save time, new interdisciplinary technologies, such as biochips and biosensors, are promising for application in the future. For nondestructive techniques, convenient and effective chemometric models are crucial, and the development of portable devices based on these technologies for onsite monitoring is a future trend. Moreover, omics technologies, especially proteomics, are important methods in laboratory detection because they enable multispecies detection and unknown target screening by using mass spectrometry databases.