A Proteomic-Based Approach for Detection of Chicken in Meat Mixes

Simultaneous Determination of Animal Products from Ruminant, Pig, Poultry, and Fish in Feedingstuff by Targeted High-Resolution LC-MS/MS

The prohibition of processed animal proteins (PAPs) has been relaxed gradually since 2007. The official control method for PAPs in feedingstuff, a combination of light microscopy (LM) followed by PCR, is no longer sufficient. Thus, a targeted LC-MS/MS method was developed, which enables a tissue-specific distinction between egg and dairy products, gelatine, and PAPs derived from blood or muscle tissue of the species ruminants, pigs, poultry, and fish. Tissue-specific proteins were analyzed after tryptic digestion to peptides with high-resolution ESI-QTOF-MS. A targeted method was developed based on untargeted proteomics approaches and the selection of specific peptides (45 unique peptides in total). Proficiency testing of blank and spiked samples revealed excellent results for trueness and selectivity. Furthermore, sensitivity was achieved at a level of 0.1% (w/w) for assessed peptides. Summing up, the developed method seems to be suitable for routine analysis after verification by ring trials.

Identification of Cross-Species Marker Peptides for the Detection of Mammalian and Poultry Meat in Vegan and Vegetarian Foods

Authentication of vegan and vegetarian foods is important since these increasingly popular food items could be adulterated with cheap meat to increase profit margins. In this study, nine marker peptides for the detection of meat (several species) were identified applying liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). These marker peptides enable the crucial differentiation of beef versus milk and chicken meat versus egg, demonstrated by the investigation of 19 commercial vegetarian meat substitutes containing milk and egg. Extensive experimental testing proved the presence of the cross-species meat marker peptides in 19 food-relevant types of mammals and poultry as well as their absence in more than 136 plant-based ingredients for the production of vegan and vegetarian foods. An authentic vegan sausage matrix based on an actual retail product was produced and spiked with 5.0%, w/w meat to confirm the high signal intensities and the heat stability of the marker peptides.

Droplet digital PCR versus real-time PCR for in-house validation of porcine detection and quantification protocol: An artificial recombinant plasmid approach

Authenticity and traceability are essential for modern food and medicine inspection, and reliable techniques are important for the trade of halal foods, which reach more than 20 percent of the world market. A sensitive and accurate porcine detection method is required to develop a conformity assessment system that includes laboratory testing for porcine-free certification. This study proposes a procedure that could be incorporated into the development of a standardized control and protocol for real-time PCR (qPCR) methods and their traceability using droplet digital PCR (ddPCR). The design used a recombinant pUC57 plasmid as an amplification target to carry the 97 bp fragment of the porcine ATCB gene. The absolute quantification and linearity assessment showed high precision with R2 values of 0.9971 and 0.9998 for qPCR and ddPCR, respectively. In general, both methods showed comparable results in terms of linearity and detection limit. However, both limit of detection assessments showed high sensitivity, although ddPCR showed a slightly higher sensitivity than that of qPCR, especially at low DNA concentrations. Multiple-sample and inter-participatory testing evaluations revealed a high sensitivity, broad applicability, and robustness of the qPCR method. Therefore, we conclude that based on a recombinant plasmid analysis with a low quantity (less than five copy number), the digital PCR method produced more reliable results. These results could provide scientific information for regulatory authorities, especially those in Indonesia, to consider the development and formulation of a well-established qPCR protocol for porcine detection using expected DNA concentrations.

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.

Lateral flow immunoassay-based absolute point-of-care technique for authentication of meat and commercial meat products

Point-of-care (POC) assay is an emerging technique for rapid initial screening of meat fraud incidents in a resource-limited environment. To achieve this goal, a simple extraction protocol is proposed for efficient recovery of meat proteins from raw, heat-processed, and commercial samples as well as meat offals without utilizing sophisticated laboratory settings. A sandwich-format lateral flow immunoassay (LFIA) was developed based on gold nanoparticles as labels and immunoglobulins (IgG and IgY) as biomarkers for meat species identification in raw and cooked meat mixes. The test system showed a sensitivity of 10 ng/mL allowing the detection of as low as 0.063% pork and chicken meat and 0.125% sheep meat (lamb) in meat mixes within 15 min including sample preparation. Reproducibility of the assay was confirmed by the fully consistent intra- and inter-laboratory tests and RT-PCR method. The current study developed a field-deployable extraction technique and highly-specific, sensitive, reproducible, cost-effective, and user-friendly LFIA-based assay for rapid species authentication in raw, cooked, and commercial meat samples and meat offals.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-022-05663-2.

Relative quantification of pork and beef in meat products using global and species-specific peptide markers for the authentication of meat composition

We used global and species-specific peptide markers for a relative quantitative determination of pork and beef in raw and processed meat products made of the two meat species. Four groups of products were prepared (i.e., minced raw meats, sausages, raw and fried burgers) in order to represent products with different extents of food processing. In each group, the products varied in the pork/beef proportions. All products were analysed by multiple reaction monitoring mass spectrometry (MRM-MS) for the presence/concentration of pork- and beef-specific peptide markers, as well as global markers - peptides widely distributed in muscle tissue. The combined MRM-MS analysis of pork-specific peptide HPGDFGADAQGAMSK, beef-specific peptide VLGFHG and global marker LFDLR offered the most reliable validation of declared pork/beef compositions across the whole range of meat products. Our work suggests that a simultaneous analysis of global and species-specific peptide markers can be used for composition authentication in commercial pork/beef products.

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.

Proteomics as a promising biomarker in food authentication, quality and safety: A review

Adulteration and mislabeling have become a very common global malpractice in food industry. Especially foods of animal origin are prepared from plant sources and intentionally mislabeled. This type of mislabeling is an important concern in food safety as the replaced ingredients may cause a food allergy or toxicity to vulnerable consumers. Moreover, foodborne pathogens also pose a major threat to food safety. There is a dire need to develop strong analytical tools to deal with related issues. In this context, proteomics stands out as a promising tool used to report the aforementioned issues. The development in the field of omics has inimitable advantages in enabling the understanding of various biological fields especially in the discipline of food science. In this review, current applications and the role of proteomics in food authenticity, safety, and quality and food traceability are highlighted comprehensively. Additionally, the other components of proteomics have also been comprehensively described. Furthermore, this review will be helpful in the provision of new intuition into the use of proteomics in food analysis. Moreover, the pathogens in food can also be identified based on differences in their protein profiling. Conclusively, proteomics, an indicator of food properties, its origin, the processes applied to food, and its composition are also the limelight of this article.

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.

Proteomic Technologies and their Application for Ensuring Meat Quality, Safety and Authenticity

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Proteomic tools were extensively used to understand the relationship between muscle proteome and conversion of muscle to meat, post-mortem proteolysis, meat texture, and variation in meat color. Developments in proteomic tools have also resulted in their application for addressing the safety and authenticity issues including meat species identification, detection of animal byproducts, non-meat ingredients and tissues in meat products, traceability, identification of genetically modified ingredients, chemical residues and other harmful substances. Proteomic tools are also being used in some of the potential areas like understanding the effect of animal transportation, stunning, slaughter stress, halal authentication and issues related to animal welfare. Emerging advances in proteomic and peptidomic technologies and their application in traceability, meat microbiology, safety and authentication are taking a major stride as an interesting and complementary alternative to DNA-based methods currently in use. Future research in meat science need to be linked to emerging metabolomic, lipidomic and other omic technologies for ensuring integrated meat quality and safety management. In this paper, a comprehensive overview of the use of proteomics for the assessment of quality and safety in the meat value chain and their potential application is discussed.

Identification and quantification of fox meat in meat products by liquid chromatography-tandem mass spectrometry

Over the years, food adulteration has become an important global problem, threatening public health safety and the healthy development of food industry. This study established a liquid chromatography-tandem mass (LC-MS/MS) method for accurate identification and quantitative analysis of fox meat products. High-resolution mass was used for data collection, and Proteome Discoverer was used for data analysis to screen fox-specific peptides. Multivariate statistical analysis was conducted using the data obtained from the label-free analysis of different contents of simulated samples. Samples with different contents were distinguished without interfering with each other, suggesting the feasibility of quantitative analysis of fox meat content. The linear correlation coefficient and recovery rate were calculated to determine the fox peptides that can be used for accurate quantification. The established LC-MS/MS method can be used for the accurate identification and quantification of actual samples. In addition, this method can provide technical support for law enforcement departments.

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.

Omics-Based Analytical Approaches for Assessing Chicken Species and Breeds in Food Authentication

Chicken is known to be the most common meat type involved in food mislabeling and adulteration. Establishing a method to authenticate chicken content precisely and identifying chicken breeds as declared in processed food is crucial for protecting consumers' rights. Categorizing the authentication method into their respective omics disciplines, such as genomics, transcriptomics, proteomics, lipidomics, metabolomics, and glycomics, and the implementation of bioinformatics or chemometrics in data analysis can assist the researcher in improving the currently available techniques. Designing a vast range of instruments and analytical methods at the molecular level is vital for overcoming the technical drawback in discriminating chicken from other species and even within its breed. This review aims to provide insight and highlight previous and current approaches suitable for countering different circumstances in chicken authentication.

Development of a two-level control system for the analysis of the composition of meat products

Because of the increased demand for processed meat, there is an urgent need to introduce specific identification methods. Strategies such as molecular genetics and the physical condition of meat are used to quickly explore multi-component products. However, a single methodology does not always unambiguously classify a product as counterfeit. In laboratory practice, as a rule, screening techniques are rarely used in the first stage, followed by arbitration. This work aimed to study individual methodologies using artificially falsified meat samples as examples and to identify their composition based on muscle tissue. For the experiments, the three most common types of raw meat were selected: pork, beef, and chicken. The calculation of the content of muscle tissue was carried out according to the BEFFE method. The study of muscle protein was carried out by ICA, ELISA, PCR, microstructural analysis, and mass spectrometric identification. In this connection, we proposed a multilevel control system for multicomponent meat products. Both classical methodologies, such as calculation by prescription bookmarks (BEFFE) and microstructural analysis, and approaches of highly sensitive methodologies, such as identification of muscle tissue by marker peptides (LC/MS-MRM) and semi-quantitative PCR analysis, were evaluated.

A quantitative method for detecting meat contamination based on specific polypeptides

OBJECTIVE

This study was aimed to establish a quantitative detection method for meat contamination based on specific polypeptides.

METHODS

Thermally stable peptides with good responses were screened by high resolution liquid chromatography tandem mass spectrometry. Standard curves of specific polypeptide were established by triple quadrupole mass spectrometry. Finally, the adulteration of commercial samples was detected according to the standard curve.

RESULTS

Fifteen thermally stable peptides with good responses were screened. The selected specific peptides can be detected stably in raw meat and deep processed meat with the detection limit up to 1% and have a good linear relationship with the corresponding muscle composition.

CONCLUSION

This method can be effectively used for quantitative analysis of commercial samples.

Diving Deep into the Data: A Review of Deep Learning Approaches and Potential Applications in Foodomics

Deep learning is a trending field in bioinformatics; so far, mostly known for image processing and speech recognition, but it also shows promising possibilities for data processing in food analysis, especially, foodomics. Thus, more and more deep learning approaches are used. This review presents an introduction into deep learning in the context of metabolomics and proteomics, focusing on the prediction of shelf-life, food authenticity, and food quality. Apart from the direct food-related applications, this review summarizes deep learning for peptide sequencing and its context to food analysis. The review’s focus further lays on MS (mass spectrometry)-based approaches. As a result of the constant development and improvement of analytical devices, as well as more complex holistic research questions, especially with the diverse and complex matrix food, there is a need for more effective methods for data processing. Deep learning might offer meeting this need and gives prospect to deal with the vast amount and complexity of data.

Mass spectrometry-based protein and peptide profiling for food frauds, traceability and authenticity assessment

The ever-growing use of mass spectrometry (MS) methodologies in food authentication and traceability originates from their unrivalled specificity, accuracy and sensitivity. Such features are crucial for setting up analytical strategies for detecting food frauds and adulterations by monitoring selected components within food matrices. Among MS approaches, protein and peptide profiling has become increasingly consolidated. This review explores the current knowledge on recent MS techniques using protein and peptide biomarkers for assessing food traceability and authenticity, with a specific focus on their use for unmasking potential frauds and adulterations. We provide a survey of the current state-of-the-art instrumentation including the most reliable and sensitive acquisition modes highlighting advantages and limitations. Finally, we summarize the recent applications of MS to protein/peptide analyses in food matrices and examine their potential in ensuring the quality of agro-food products.

Comparative database search engine analysis on massive tandem mass spectra of pork-based food products for halal proteomics

Mass spectrometry-based proteomics relies on dedicated software for peptide and protein identification. These software include open-source or commercial-based search engines; wherein, they employ different algorithms to establish their scoring and identified proteins. Although previous comparative studies have differentiated the proteomics results from different software, there are still yet studies specifically been conducted to compare and evaluate the search engine in the field of halal analysis. This is important because the halal analysis is often using commercial meat samples that have been subjected to various processing, further complicating its analysis. Thus, this study aimed to assess three open-source search engines (Comet, X! Tandem, and ProteinProspector) and a commercial-based search engine (ProteinPilot™) against 135 raw tandem mass spectrometry data files from 15 types of pork-based food products for halal analysis. Each database search engine contained high false-discovery rate (FDR); however, a post-searching algorithm called PeptideProphet managed to reduce the FDR, except for ProteinProspector and ProteinPilot™. From this study, the combined database search engine (executed by iProphet) reveals a thorough protein list for pork-based food products; wherein the most abundant proteins are myofibrillar proteins. Thus, this proteomics study will aid the identification of potential peptide and protein biomarkers for future precision halal analysis. SIGNIFICANCE: A critical challenge of halal proteomics is the availability of a database to confirm the inferential peptides as well as proteins. Currently, the established database such as UniProtKB is related to animal proteome; however, the halal proteomics is related to the highly processed meat-based food products. This study highlights the use of different database search engines (Comet, X! Tandem, ProteinProspector, and ProteinPilot™) and their respective algorithms to analyse 135 raw tandem mass spectrometry data files from 15 types of pork-based food products. This is the first attempt that has compared different database search engines in the context of halal proteomics to ensure the effectiveness of controlling the FDR. Previous studies were just focused on the advantages of a certain algorithm over another. Moreover, other previous studies also have mainly reported the use of mass spectrometry-based shotgun proteomics for meat authentication (the most similar field to halal analysis), but none of the studies were reported on halal aspects that used samples originated from highly processed food products. Hence, a systematic comparative study is duly needed for a more comprehensive and thorough proteomics analysis for such samples. In this study, our combinatorial approach for halal proteomics results from the different search engines used (Comet, X! Tandem, and ProteinProspector) has successfully generated a comprehensive spectral library for the pork-based meat products. This combined spectral library is freely available at https://data.mendeley.com/datasets/6dmm8659rm/3. Thus far, this is the first and new attempt at establishing a spectral library for halal proteomics. We also believe this study is a pioneer for halal proteomics that aimed at non-conventional and non-model organism proteomics, protein analytics, protein bioinformatics, and potential biomarker discovery.

Rapid Analysis and Authentication of Meat Using the MasSpec Pen Technology

Food authenticity and safety are major public concerns due to the increasing number of food fraud cases. Meat fraud is an economically motivated practice of covertly replacing one type of meat with a cheaper alternative raising health, safety, and ethical concerns for consumers. In this study, we implement the MasSpec Pen technology for rapid and direct meat analysis and authentication. The MasSpec Pen is an easy-to-use handheld device connected to a mass spectrometer that employs a solvent droplet for gentle chemical analysis of samples. Here, MasSpec Pen analysis was performed directly on several meat and fish types including grain-fed beef, grass-fed beef, venison, cod, halibut, Atlantic salmon, sockeye salmon, and steelhead trout, with a total analysis time of 15 s per sample. Statistical models developed with the Lasso method using a training set of samples yielded per-sample accuracies of 95% for the beef model, 100% for the beef versus venison model, and 84% for the multiclass fish model. Predictors of meat type selected included several molecules previously reported in the skeletal muscles of animals, including carnosine, anserine, succinic acid, xanthine, and taurine. When testing the models on independent test sets of samples, per-sample accuracies of 100% were achieved for all models, demonstrating the robustness of our method for unadulterated meat authentication. MasSpec Pen feasibility testing for classifying venison and grass-fed beef samples adulterated with grain-fed beef achieved per-sample prediction accuracies of 100% for both classifiers using test sets of samples. Altogether, the results obtained in this study provide compelling evidence that the MasSpec Pen technology is a powerful alternative analytical method for meat analysis and investigation of meat fraud.

LIQUID CHROMATOGRAPHY-MASS SPECTROMETRY BOTTOM-UP PROTEOMIC METHODS IN ANIMAL SPECIES ANALYSIS OF PROCESSED MEAT FOR FOOD AUTHENTICATION AND THE DETECTION OF ADULTERATIONS

This review offers an overview of the current status and the most recent advances in liquid chromatography-mass spectrometry (LC-MS) techniques with both high-resolution and low-resolution tandem mass analyzers applied to the identification and detection of heat-stable species-specific peptide markers of meat in highly processed food products. We present sets of myofibrillar and sarcoplasmic proteins, which turned out to be the source of 105 heat-stable peptides, detectable in processed meat using LC-MS/MS. A list of heat-stable species-specific peptides was compiled for eleven types of white and red meat including chicken, duck, goose, turkey, pork, beef, lamb, rabbit, buffalo, deer, and horse meat, which can be used as markers for meat authentication. Among the 105 peptides, 57 were verified by multiple reaction monitoring, enabling identification of each species with high specificity and selectivity. The most described and monitored species by LC-MS/MS so far are chicken and pork with 26 confirmed heat-stable peptide markers for each meat. In thermally processed samples, myosin, myoglobin, hemoglobin, l-lactase dehydrogenase A and β-enolase are the main protein sources of heat-stable markers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Peptide markers for distinguishing guinea fowl meat from that of other species using liquid chromatography-mass spectrometry

The inability to easily identify the animal species in highly processed meat products makes them highly susceptible to adulterations. Reliable methods for detecting the species origin of meat used in processed food are required to ensure adequate labelling and minimize food fraud and allergenic potential. Liquid chromatography high resolution mass spectrometry was employed to identify new heat-stable guinea-fowl-specific peptide markers that can differentiate guinea fowl meat from other commonly consumed animal species, including closely related poultry species, in highly processed food products. We identified 26 unique guinea-fowl-specific markers. The high stability of guinea-fowl-specific peptides was confirmed by analysing food products with guinea fowl meat content ranging from 4% to 100%. The findings indicate that sensitive and reliable LC-MS/MS methods can be developed for the targeted detection and quantification of guinea fowl meat in highly processed meat 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.

A straightforward gel-free proteomics pipeline assisted by liquid isoelectric focusing (OFFGEL) and mass spectrometry analysis to study bovine meat proteome

Bovine sarcoplasmic sub-proteome was studied through a straightforward gel-free pipeline supported by liquid isoelectric focusing (OFFGEL) protein fractionation coupled to liquid chromatography-mass spectrometry (LC-MS) analysis. Full-MS and data-dependent MS/MS analyses were simultaneously performed by a conventional three-dimensional ion-trap addressing targeted quantitative and untargeted qualitative research, respectively. There were unambiguously identified 47 proteins distributed along 12 OFFGEL fractions assayed. Regarding intermediate- and high-abundant peptides, bulky quantitative data processing performed by MZmine 2 freeware yielded a satisfactory linearity and coefficient of variation with r2 in the 0.95–0.99 range and about 25%, respectively. Up to 41 peptides from 20 identified proteins were relatively quantified throughout OFFGEL fractions. This reliable, flexible and affordable gel-free proteomic approach could be readily implemented by industry to improve quality assessment of protein-based food products.

Measuring quantitative proteomic distance between Spanish beef breeds

Estimates of quantitative proteomic distance between populations have not been reported to date. Here, quantitative proteomic distances between three Spanish bovine breeds (Asturiana de los Valles, AV; Retinta, RE; and Rubia Gallega, RG) were estimated from two-dimensional electrophoresis profiles of meat samples of longissimus thoracis muscle at 2 h post-mortem. Statistically significant distances were detected between AV/RG and the most genetically different RE breed, using the novel QD measure of quantitative proteomic distance. In total, 18 differentially abundant myofibrillar and sarcoplasmic proteins/isoforms contributing to proteomic distances between breeds were confidently identified by tandem mass spectrometry. The fast skeletal myosin regulatory light chain 2 followed by other five interacting proteins exhibited the most pronounced relative change between breeds. In addition, most differentially represented proteins could be associated with variations in meat tenderness. Therefore, they could be candidate biomarkers for molecular breeding programs and authentication of the three Spanish beef breeds.

LC-QTOF-MS identification of rabbit-specific peptides for authenticating the species composition of meat products

Rabbit is a healthy meat, with low allergenicity and excellent nutritional properties. The global popularity of rabbit meat makes it a target for food fraud. We present a LC-QTOF-MS/MS approach for detecting and identifying rabbit-specific peptide-markers from thermally processed meat products to differentiate rabbit from other commonly-consumed animal species. We identified 49 heat-stable specific peptides. We selected the most stable markers for testing complex meat matrices by analysing pâtés-type products with a rabbit meat content ranging from 5% to 85%. Of the 49 heat-stable peptides detected in pure cooked rabbit meat, three were consistently detected in all investigated pâté samples i.e., SSVFVADPK, AFFGHYLYEVAR and PHSHPALTPEQK. Monitoring meat species other than rabbit in the examined pâtés using pork-, lamb- and chicken-specific peptides identified the presence of undeclared chicken in two samples. The results confirm that LC-QTOF-MS/MS is a suitable tool for multi-species detection in processed meat products, particularly for authentication purposes.

Comparison of heat-stable peptides using a multiple-reaction monitoring method to identify beef muscle tissue

Nowadays, proteomics is widely used as an analytical control method. A new method for determining animal tissue species-specificity based on a combination of two effective methods of food analysis, liquid chromatography (LC) and mass spectrometry (MS), was used in this work. Using this approach, it became possible to detect peptides. This work presents a comparison of species-specific, heat-stable peptides for the identification of beef. The objects of the study were native and boiled model mixtures containing beef with concentrations of 8% (w/w) and 16% (w/w). Pork was also added to the recipe to control for false-positive results. A high-performance liquid chromatography technique with mass spectrometric detection (LC-MS/MS) was used. Analysis of finished samples takes 25 minutes and is adapted to detect marker peptides. From the processing of the obtained data, three beef marker peptides were identified that were accepted as the best candidates. Two peptide prototypes, NDMAAQYK and YLEFISDAIIHVLHAK from the myoglobin protein and SNVSDAVAQSAR from the triosephosphate isomerase protein, were selected as potential biomarkers. For all samples, the signal-to-noise ratio (S/N) was set above 10. Temperature was not found to affect the structure and detection of marker peptides in samples with a muscle tissue concentration of 8% (w/w) at p <0.05. This approach is universally applicable for comparing biomarkers of other types of meat and to identify the most suitable candidates.

Application of two-dimensional gel electrophoresis technique for protein profiling of Indian black gram varieties and detection of adulteration in black gram-based food products using comparative proteomics

In the present study, protein fingerprints from six novel Indian black gram varieties were obtained using 2D-GE. The results revealed the presence of thirteen well-resolved protein spots in all six varieties. Analysis of the fingerprints using PD Quest™ revealed differential protein expression. In addition, six proteins were found to be uniquely expressed in varieties PDKV Black Gold and TAU-1. Further, analysis of 2D patterns of black gram and potential adulterants such as refined wheat flour and white pea using PD Quest™ revealed the presence of proteins with MW 15.0 kDa, pI 4.89 (refined flour) and MW 21.5 kDa, pI 5.70 (white pea), which can be considered as biomarkers for their presence in black gram food products. The method was sensitive enough to detect adulteration at 5% level and could successfully detect the potential presence of refined flour in one of the black gram papad samples analysed during the study.

N-Glycan Profile as a Tool in Qualitative and Quantitative Analysis of Meat Adulteration

Adulteration of meat and meat products causes concerns to consumers. It is necessary to develop novel robust and sensitive methods that can authenticate the origin of meat by qualitative and quantitative means to minimize the drawbacks of the existing methods. This study has shown that the protein N-glycosylation profiles of different meats are species specific and thus can be used for meat authentication. Based on the N-glycan pattern, the investigated five meat species (beef, chicken, pork, duck, and mutton) can be distinguished by principal component analysis, and partial least square regression was performed to build a calibration and validation model for the prediction of adulteration ratio. Using this method, beef samples adulterated with a lower-value duck meat could be detected down to the addition ratio as low as 2.2%. The most distinguishing N-glycans from beef and duck were elucidated for the detailed structures.

Species-Specific Discrimination of Insect Meals for Aquafeeds by Direct Comparison of Tandem Mass Spectra

Insect protein has the potential to become a sustainable feed ingredient for the rapidly growing aquaculture industry. In the European Union, insect derived protein is placed under the same legislation as processed animal proteins (PAP). It is therefore of interest to develop methods for regulatory use, which unambiguously identify the species origin of insect-based ingredients. We performed (i) total protein quantification of insect samples using the traditional nitrogen-to-protein conversion factor of 6.25 and the sum of anhydrous amino acids, (ii) quantitative amino acid profiling and (iii) high-throughput tandem mass spectrometry to describe and differentiate 18 different commercial-grade insect meal samples derived from Hermetia illucens (8), Tenebrio molitor (5), Alphitobius diaperinus (3) and Acheta domesticus (2). In addition, we investigated and compared different protein extraction and digestion protocols for proteomic analysis. We found that irrespective of sample preparation, shotgun proteomics in combination with direct spectral comparison were able to differentiate insect meal according to their taxonomic classification. The insect specific spectral libraries created in the present work can in future be used to develop more sensitive targeted methods of insect PAP identification and quantification in commercial feed mixtures.

El Gueddid, a traditional Algerian dried salted meat: Physicochemical, microbiological characteristics and proteolysis intensity during its manufacturing process and ripening

El Gueddid is a traditional salted and dried meat with high popularity in Algeria. It is used as an ingredient in various dishes. In this study, different samples of El Gueddid were analyzed at different processing times to follow up their microbiological and physicochemical properties. Changes in the protein profile were also demonstrated by electrophoretic study of myofibrillar proteins. Microbiological determinations included the total viable count, coliforms, Staphylococci, lactic acid bacteria, yeasts, and molds, whereas physicochemical properties were characterized by pH, moisture, salt content and water activity. The results showed that microbial profiles were elevated for all the studied micro-organisms. Staphylococci and lactic acid bacteria were the most abundant micro-organisms in the product. Total coliforms were found in low numbers in fresh meat, being eliminated at the post salting stage of process. The physicochemical characteristics showed that the moisture content decreased in the product during the drying period. The pH also decreased during the drying period, then remained almost unchanged during the rest of the ripening period. Moreover, El Gueddid showed low water activity and high salt content. One of the most important changes in the profile of myofibrillar proteins was a reduction in the myosin heavy chain content.

Species-specific peptide-based liquid chromatography-mass spectrometry monitoring of three poultry species in processed meat products

The detection of adulteration and mislabeling of food products, including intensively processed meat, is a challenge which needs urgent solutions to protect consumers' rights. The aim of the study was to demonstrate the feasibility of species-specific peptide-based LC-MS methods for monitoring duck, goose and chicken in processed meat products. Food commodities of various compositions, subjected to various treatments, including homogenization, cooking, roasting, drying, and sterilization during production, were examined to ensure that MS-based methods are resistant to matrix composition changes. A qualitative LC-QQQ multiple reaction monitoring (MRM) method was developed which allows high-confidence monitoring of duck, goose and chicken meat (ten specific peptides), simultaneously with beef and pork (seven peptides), in the presence of turkey meat, in highly processed food. The developed LC-MS methods can be used for food authentication, monitoring of the food composition conformity with label statements and detection of adulteration of poultry-containing food products.

Determination of food allergens by LC-MS: Impacts of sample preparation, food matrix, and thermal processing on peptide detectability and quantification

Food allergies are a growing worldwide concern and the contamination of products with food allergens represents a significant health risk to allergic consumers. With the introduction of reference doses, quantitative methods are needed for the monitoring of allergen levels, and the potential of LC-MS/MS is of hugely growing interest. In this study, we demonstrate that relevant food matrices (bakery products and chocolates) and thermal food processing substantially influence the quantification of 18 marker peptides from various nut and peanut allergens via targeted proteomics. In addition, we characterize the individual release kinetics of marker peptides and provide examples for metastable marker peptide candidates. Matrix recovery rates overall ranged between 15 and 250% with the observed variation being linked to the individual peptide structure as well as to specific matrix interferences. In contrast, thermal processing considerably influences the detectability of allergens on the protein level as different marker peptides from the identical parent allergen are similarly affected, leading to a loss in signal of up to 83% in extreme cases after a 45-min simulated baking. Provided data are finally used for evaluation of different calibrators as well as the overall potential and challenges of LC-MS for the absolute quantification of food allergens. SIGNIFICANCE: With the scientific discussion moving towards a risk-based management of food allergens, including the establishment of threshold doses, robust methods for the absolute quantification of allergens in food samples are urgently needed. Because the currently used antibody- and DNA-based technologies show severe limitations in terms of specificity and reproducibility, LC-MS has emerged as a promising alternative. Its application to absolute quantification, however, first requires an understanding of the various impacts that affect quantification results, including different food matrices, sample preparation, and thermal processing of foodstuffs. Knowledge of these factors, which are assessed as part of a comprehensive survey in this study, is also an important prerequisite to evaluate means of calibration for an LC-MS-based quantification of food allergens.

Use of liquid isoelectric focusing (OFFGEL) on the discovery of meat tenderness biomarkers

Protein biomarkers of meat tenderness are known to be of primary importance for the prediction of meat quality, and hence, industry profitability. Proteome analysis was performed on meat from 8 Main Anjou beef cattle, previously classified as tender or tough meats by Warner Bratzler shear force measurements. Myofibrillar fraction of Longissimus thoracis muscle was separated by a novel fractionation approach based on liquid isoelectric focusing (OFFGEL) and further analyzed by SDS-PAGE and liquid chromatography coupled to tandem mass spectrometry. Obtained OFFGEL fraction profiles were reproducible allowing the comparison of both meat qualities and revealing 7 protein bands capable to discriminate between tender and tough samples. The proteins present in these bands were troponin T, Heat Shock protein beta-1, creatine kinase, actin, troponin C, myosins 1 and 2 and myozenin-1. The latter protein has not been previously reported as a marker of meat tenderness.

SIGNIFICANCE

This study introduces an innovative proteomic approach for the study of muscle proteome. The fact of obtaining fractions in liquid state after OFFGEL fractionation allows for a faster analysis of proteins by mass spectrometry, being an interesting alternative to more classical proteomic approaches based on two dimensional gel electrophoresis (2-DE).

Simultaneous determination of heat stable peptides for eight animal and plant species in meat products using UPLC-MS/MS method

Food adulteration and fraud is driven by economic interests; it is thus necessary to establish a high-through method that allows quantitative identification of familiar animal and plant proteins for global use. In this study, a sensitive mass spectrometric approach for the detection of eight species, including pork, beef, lamb, chicken, duck, soy, peanut, and pea, is presented and the heat stability and specificity of screened peptides are verified. To improve screening efficiency of specific peptides, several key data searching parameters, including peptides, sequence lengths, sequence coverage, and unique peptides, are investigated. Using this approach, it is possible to detect a 0.5% contamination of any of the eight species. The method is proven to have high sensitivity, specificity, repeatability, and a low quantitative detection limit with respect to adulteration of diverse types of meat products.

In-gel and OFFGEL-based proteomic approach for authentication of meat species from minced meat and meat products

BACKGROUND

Fraudulent mislabelling of processed meat products on a global scale that cannot be detected using conventional techniques necessitates sensitive, robust and accurate methods of meat authentication to ensure food safety and public health. In the present study, we developed an in-gel (two-dimensional gel electrophoresis, 2DE) and OFFGEL-based proteomic method for authenticating raw and cooked water buffalo (Bubalus bubalis), sheep (Ovis aries) and goat (Caprus hircus) meat and their mixes.

RESULTS

The matrix-assisted liquid desorption/ionization time-of-flight mass spectrometric analysis of proteins separated using 2DE or OFFGEL electrophoresis delineated species-specific peptide biomarkers derived from myosin light chain 1 and 2 (MLC1 and MLC2) of buffalo-sheep-goat meat mix in definite proportions at 98:1:1, 99:0.5:0.5 and 99.8:0.1:0.1 that were found stable to resist thermal processing. In-gel and OFFGEL-based proteomic approaches are efficient in authenticating meat mixes spiked at minimum 1.0% and 0.1% levels, respectively, in triple meat mix for both raw and cooked samples.

CONCLUSIONS

The study demonstrated that authentication of meat from a complex mix of three closely related species requires identification of more than one species-specific peptide due to close similarity between their amino acid sequences. © 2017 Society of Chemical Industry.