Identification and absolute quantification of animal blood products by peptide markers using an UPLC–MS/MS method

Absolute quantification of targeted rabbit liver- and meat tissue-specific peptide markers in highly processed food products

A highly sensitive and selective method for the simultaneous absolute quantification of peptides unique to rabbit meat- and liver-specific tissue was developed using liquid chromatography - triple quadrupole mass spectrometry. Two rabbit skeletal muscle-specific peptides (SSVFVADPK and PHSHPALTPEQK), three rabbit liver tissue-specific peptides (FNLEALVTHTLPFEK, AILNYVANK, and TELAEPTSTR) and one peptide specific to both rabbit offal and skeletal muscle tissue (AFFGHYLYEVAR) were monitored. Analyses were performed using peptides labelled with stable isotopes (13C and 15N) as internal standards. Fifteen food samples containing rabbit meat and/or liver were analysed to verify compliance of the rabbit meat and liver composition with product labelling. One sample was adulterated with undeclared rabbit liver. The limit of detection and limit of quantification for the selected peptides of interest were in the range of 0.17 to 0.35 ng/mg and 0.57 to 1.17 ng/mg, respectively. The method may be useful for the determination of rabbit meat and liver tissue in highly processed food samples.

Heat-stable peptide markers specific to rabbit and chicken liver tissue for meat product authentication testing

A three-step analysis was used to detect and identify heat-stable peptide markers specific to liver tissue from rabbit and chicken. It involved peptide discovery by liquid chromatography coupled to high resolution mass spectrometer (LC-HRMS), followed by protein identification using Spectrum Mill software and multiple reaction monitoring (MRM) based confirmation of the discovered peptides using a liquid chromatography coupled to triple quadrupole mass spectrometer (LC-TQ). We identified 50 and 91 heat-stable peptide markers unique to chicken and rabbit liver, respectively. The markers were validated in commercial food samples with declared liver tissue contents ranging from 5% to 30%. The best candidate peptides for distinguishing liver tissue from skeletal muscle were selected and then confirmed using MRM-based approach. Limit of detection of liver was found to be in the range of 0.13 to 2.13% (w/w) for chicken liver-specific peptide markers, and from 0.04 to 0.6% (w/w) for rabbit liver-specific peptide markers.

Burden levels of polychlorinated dibenzo-p-dioxins, dibenzofurans, and polychlorinated biphenyls in typical edible meat animals

The concentrations and distributions of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and polychlorinated biphenyls (PCBs) in the whole blood and meat of eight typical edible animals (chicken, donkey, horse, cattle, rabbit, sheep, duck, and pig) were illustrated. Total concentrations of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and PCBs (on a basis of liquid volume) in animal bloods were 142-484 pg/L and 46-62 ng/L, respectively. Total concentrations of PCDD/Fs and PCBs (on a basis of dry weight (dw) and lipid weight (lw)) in animal meat samples were 0.47-1090 pg/g dw (0.47-4513 pg/g lw) and 7.2-23 ng/g dw (10-776 ng/g lw), respectively. TEQs for both PCDD/Fs and PCBs in animal blood and meat samples were (67 ± 27) pg/L and (5.3 ± 14) pg/g dw (24 ± 56 pg/g lw), respectively. Besides, the dietary intakes of PCDD/Fs and PCBs were also estimated. Chicken and pig contributed more TEQs than other animals. Chicken contributed the most (95%) with high toxicity, followed by pig (3.4%) with high consumption. The dietary intake of chicken might pose risks to consumers who prefer to eat chicken products, who should comprehensively consider the essential nutrients and contaminants in food during dietary intake.

A critical review on slaughterhouse waste management and framing sustainable practices in managing slaughterhouse waste in India

Global meat consumption is on a rise with around 253 million metric tons of meat produced globally in the year 2020. Because of the rise in population and change in food preferences, meat consumption trend is likely to continue. Meat production by animal slaughtering increases the slaughterhouse wastes in the form of both solid and liquid wastes. Although various technologies for slaughterhouse waste management are available in developed countries, the effective utilization of slaughterhouse waste management is still missing in developing countries like India. India plays an active role in the meat export business globally and stood 2nd in the world with a total export valuation of 2.89 billion US $ in the year 2020. In this context, this study presents a critical overview of the current technological advancements in the global slaughterhouse waste management including utilization of by-products and further, the prevailing slaughterhouse waste management of India is discussed. Finally, a sustainable slaughterhouse waste management strategy emphasizing circular economy and regulations improvements have been suggested for India to compete in this sector at global scale.

The potential of proteomics in the study of processed meat products

Proteomics is a field that has grown rapidly since its emergence in the mid-1990s, reaching many disciplines such as food technology. The application of proteomic techniques in the study of complex biological samples such as foods, specifically meat products, allows scientists to decipher the underlying cellular mechanisms behind different quality traits. Lately, much emphasis has been placed on the discovery of biomarkers that facilitate the prediction of biochemical transformations of the product and provide key information on parameters associated with traceability and food safety. This review study focuses on the contribution of proteomics in the improvement of processed meat products. Different techniques and strategies have recently been successfully carried out in the study of the proteome of these products that can help the development of foods with a higher sensory quality, while ensuring consumer safety through early detection of microbiological contamination and fraud. SIGNIFICANCE: The food industry and the academic world work together with the aim of responding to market demands, always seeking excellence. In particular, the meat industry has to face a series of challenges such as, achieving sensory attributes in accordance with the standards required by the consumer and maintaining a high level of safety and transparency, avoiding deliver adulterated and/or contaminated products. This review work exposes how the aforementioned challenges are attempted to be solved through proteomic technology, discussing the latest and most outstanding research in this regard, which undoubtedly contribute to improving the quality, in all the extension of the word, of meat products, providing relevant knowledge in the field of proteomic research.

Authentication of duck blood tofu binary and ternary adulterated with cow and pig blood-based gel using Fourier transform near-infrared coupled with fast chemometrics

This work aims to investigate a feasible and practical technique for the authentication of edible animal blood food (EABF) using Fourier transform near-infrared (FT-NIR) coupled with fast chemometrics. A total of 540 samples were used, including raw duck blood tofu (DBT), cow blood-based gel (CBG), pig blood-based gel (PBG), and DBT binary and ternary adulterated with CBG and PBG. The protein, fat, total sugar, and 16 kinds of amino acids were measured to validate the difference in basic organic matters among EABFs according to species. Fisher linear discriminate analysis (Fisher LDA) and extreme learning machine (ELM) were implemented comparatively to identify the adulterated EABF. To predict adulteration levels, four extreme learning machine regression (ELMR) models were constructed and optimized. Results showed that, by analyzing 27 crucial spectral variables, the ELM model provides higher accuracy of 93.89% than Fisher LDA for the independent samples. All the correlation coefficients of the optimized ELMR models' training and prediction sets were better than 0.94, the root mean square errors were all less than 3.5%, and the residual prediction deviation and the range error ratios were all higher than 4.0 and 12.0, respectively. In conclusion, the FT-NIR paired with ELM have great potential in authenticating the EABF. This work presents amino acids content in EABFs for the first time and built tracing models for rapid authentication of DBT, which can be used to manage the EABF market, thereby preventing illegal adulteration and unfair competition.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

Machine-learning assisted modelling of multiple elements for authenticating edible animal blood food

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The critical elements for identifying species of the animal blood food were selected.

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Elemental fingerprint coupled with ELM were proposed for species identification of the animal blood food.

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The optimal ELM model for identifying the species of the animal blood food was constructed.

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The absolute and relative content of 25 elements in animal blood food were reported for the first time.

Elemental fingerprint coupled with machine learning modelling was proposed for species authentication of the edible animal blood gel (EABG). A total of 25 elements were determined by inductively coupled plasma mass spectrometry (ICP-MS) and atomic absorption spectroscopy (AAS) in 150 EABG samples prepared from five species of animals, namely duck, chicken, bovine, pig, and sheep. Extreme learning machine (ELM) models were constructed and optimized. Principal component analysis and Fisher linear discriminant analysis were comparatively utilized for dimension reduction of the crucial input elements selected via stepwise discriminant analysis and one-way ANOVA. The optimal ELM model was obtained with the crucial elements selected by one-way ANOVA from the relative content of the measured elements, which afforded accuracies of 98.0% and 96.0% for the training and test set, respectively. All findings suggest that elemental fingerprint accompanied by ELM have great potential in authenticating the edible animal blood food.

Screening of specific quantitative peptides of beef by LC-MS/MS coupled with OPLS-DA

A rapid, simple, and efficient analysis methodology for screening specific quantitative peptides of beef was established based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) coupled with orthogonal partial least squares-discriminant analysis (OPLS-DA). The OPLS-DA model was built to select species-specific peptides that make a significant contribution to classification. Peptides with statistical significance were selected based on the variable importance in the projection (VIP) values and univariate P values. After the workflow of the statistical process, three specific quantitative peptides were identified by using homemade products with different beef contents. A quantification method for selected specific quantitative peptides was established by using LC-MS/MS. The quantitative results were applied to commercialized beef products. The developed method has high sensitivity, specificity, and repeatability. The results of this study proved that the integration of LC-MS/MS coupled with OPLS-DA is an efficient method for screening specific quantitative peptides and identification of the authenticity of meat products.

Rapid LC-MS/MS method for the detection of seven animal species in meat products

The adulteration of meat products has been reported worldwide, and detection of specific peptides through mass spectrometry (MS) is a reliable method for meat species identification. However, the practical application of this method is limited by complicated steps and long reaction time of the traditional sample preparation. Therefore, this paper introduced a convenient and time-saving sample preparation by optimizing the steps of reduction, alkylation, digestion, and purification. With the rapid sample preparation, 35 species-specific peptides for seven species (pig, cattle, sheep, deer, chicken, duck, and turkey) were screened using high-resolution MS, and a rapid LC-MS/MS method was established. The method only takes 3 h from sample receipt to results. The meat species of 20 processed meat products were detected, and three samples were found potentially adulterated. The method is proved to have high sensitivity, specificity, practicability with respect to rapid identification of meat species in meat products.

Multispecies Identification of Oilseed- and Meat-Specific Proteins and Heat-Stable Peptide Markers in Food Products

Consumer demand for both plant products and meat products enriched with plant raw materials is constantly increasing. Therefore, new versatile and reliable methods are needed to find and combat fraudulent practices in processed foods. The objective of this study was to identify oilseed species-specific peptide markers and meat-specific markers that were resistant to processing, for multispecies authentication of different meat and vegan food products using the proteomic LC-MS/MS method. To assess the limit of detection (LOD) for hemp proteins, cooked meatballs consisting of three meat species and hemp cake at a final concentration of up to 7.4% were examined. Hemp addition at a low concentration of below 1% was detected. The LOD for edestin subunits and albumin was 0.9% (w/w), whereas for 7S vicilin-like protein it was 4.2% (w/w). Specific heat-stable peptides unique to hemp seeds, flaxseed, nigella, pumpkin, sesame, and sunflower seeds, as well as guinea fowl, rabbit, pork, and chicken meat, were detected in different meat and vegan foods. Most of the oilseed-specific peptides were identified as processing-resistant markers belonging to 11S globulin subunits, namely conlinin, edestin, helianthinin, pumpkin vicilin-like or late embryogenesis proteins, and sesame legumin-like as well as 2S albumins and oleosin isoforms or selected enzymic proteins.

Peptidomic analysis of antioxidant peptides from porcine liver hydrolysates using SWATH-MS

There is a growing interest in the production and identification of bioactive peptides as health-promoting agents. A relevant method to produce biopeptides is enzymatic hydrolysis from protein-rich meat by-products. Pork liver proved to be a good source of protein (18.54%) with a low-fat content (3.38%). After hydrolysis at different times (4,6,8 and 10 h) with Alcalase, relevant amino acids such as hydrophobic (leucine, valine and isoleucine) and aromatic (tyrosine and phenylalanine) involved in antioxidant capacity were strongly increased. For the peptidomic analysis, a novel technique called sequential window acquisition of all theoretical mass spectra (SWATH-MS) was used. Regarding the effect of hydrolysis time, PCA demonstrated a great differentiation among the peptidomic pattern. Fifty-one peptides were correlated with antioxidant activity measured by DPPH, ABTS, FRAP and ORAC assays. SWATH-MS allowed the identification and quantification of six peptides from trypsinogen, ferritin, keratin, carboxylic ester hydrolase and globin domain-containing protein as potential antioxidant compounds. SIGNIFICANCE: The pork liver tissue contains a substantial amount of proteins whose enzymatic hydrolysis might generate antioxidant peptides. The bioactive peptides from pork liver would contribute to harnessing by-products of the swine industry as well as added-value products will be produced. The antioxidant activity of the mixtures revealed potential antioxidant peptides which could be used in the development of nutraceutical and functional food products.

Assessment of carbonic anhydrase 3 as a marker for meat authenticity and performance of LC-MS/MS for pork content

In recent years, food fraud is a global issue that has raised wide public concern. Mass spectrometry techniques have a significant advantage of qualitatively and quantitatively analyzing food authenticity, especially for highly processed meat products. In this work, a simple and specific, rapid resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for the determination of pork content in processed meat products according to internal standard (ISTD) method. To improve the efficiency of sample preparation, simplified bead-beating and enzymolysis process were investigated. In contrast with different heat-stable and specific porcine-peptides, EPITVSSDQMAK, GGPLTAAYR, HDPSLLPWTASYDPGSAK from Carbonic anhydrase 3 proved to have an excellent quantitative ability, thus obtaining good linear relationship and satisfactory recovery. This method was successfully applied to different types of meat products, thus demonstrating that complex mixtures of pork content can be accurately quantified.