Detection of peptide markers of soy, milk and egg white allergenic proteins in poultry products by LC-Q-TOF-MS/MS

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.

Simultaneous Mass Spectrometric Detection of Proteins of Ten Oilseed Species in Meat Products

Food fraud is a common issue in the modern food industry. The undeclared use of foreign proteins in meat products is a major concern in this context. Oilseeds are ideal for this purpose due to their high protein content and since huge amounts of oil meal are obtained as a by-product of oil production. Therefore, a UHPLC-MS/MS method was developed for the simultaneous detection of chia, coconut, flaxseed, hemp, peanut, pumpkin, rapeseed, sesame, soy, and sunflower proteins in meat products. Potential tryptic peptide markers were identified by high-resolution mass spectrometry. The final twenty peptide markers selected, which are specific for one of the ten species targeted, were each measured by multiple reaction monitoring. To the best of our knowledge, twelve new heat-stable marker peptides for chia, coconut, flaxseed, pumpkin, rapeseed, sesame and sunflower have not been reported previously. Emulsion-type sausages with 0.01, 0.25, 0.50, 0.75 and 1.00% protein addition by each oilseed species were produced for matrix calibration. No false-positive results were recorded. In the quantification of the ten oilseed species, 466 of 480 measuring data points of the recovery rate in unknown sausages (0.15 and 0.85% protein addition by each oilseed species) were in the accepted range of 80–120%.

A new paradigm to search for allergenic proteins in novel foods by integrating proteomics analysis and in silico sequence homology prediction: Focus on spirulina and chlorella microalgae

Since novel nutrient sources with high protein content, such as yeast, fungi, bacteria, algae, and insects, are increasingly introduced in the consumer market, safety evaluation studies on their potentially allergenic proteins are required. A pipeline for in silico establishing the sequence-based homology between proteins of spirulina (Arthrospira platensis) and chlorella (Chlorella vulgaris) micro-algae and those included in the AllergenOnline (AO) database (AllergenOnline.org) is described. The extracted proteins were first identified through tryptic peptides analysis by reversed-phase liquid chromatography and high resolution/accuracy Fourier-transform tandem mass spectrometry (RPLC-ESI-FTMS/MS), followed by a quest on the UniProt database. The AO database was subsequently interrogated to assess sequence similarity between identified microalgal proteins and known allergens, based on criteria established by the World Health Organization (WHO) and Food and Agriculture Organization (FAO). A direct search for microalgal proteins already included in allergen databases was also performed using the Allergome database. Six proteins exhibiting a significant homology with food allergens were identified in spirulina extracts. Five of them, i.e., two thioredoxins (D4ZSU6, K1VP15), a superoxide dismutase (C3V3P3), a glyceraldehyde-3-phosphate dehydrogenase (K1W168), and a triosephosphate isomerase (D5A635), resulted from the search on AO. The sixth protein, C-phycocyanin beta subunit (P72508), was directly obtained after examining the Allergome database. Two proteins exhibiting significant sequence homology with food allergens were retrieved in chlorella extracts, viz. calmodulin (A0A2P6TFR8), which is related to troponin c (D7F1Q2), and fructose-bisphosphate aldolase (A0A2P6TDD0). Specific serum screenings based on immunochemical tests should be undertaken to confirm or rule out the allergenicity of the identified proteins.

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.

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.

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.

LC-HRMS/MS for the simultaneous determination of four allergens in fish and swine food products

The inclusion on the label of packed foods of any ingredient or technological adjuvant causing allergies is required by EU food legislation. In this study a targeted proteomics method for detecting four allergens in animal-derived food matrices was developed. Liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) was used to select marker peptides from four allergens and develop a quantitative method able to simultaneously detect the presence of milk, egg, crustaceans and soy. The method was validated on fish or swine processed food products contaminated at 5 μg g^-1 for milk and egg and 10 μg g^-1 for soy and crustaceans. The method was tested by analyzing commercial food products with high protein content and was compared to the ELISA technique. Our results indicated the presence of soy not reported on the food label of some products, pointing out the need for efficient controls to protect allergic consumers.

Effect of soybean oligopeptide on the growth and metabolism of Lactobacillus acidophilus JCM 1132

Soybean protein (Pro) and soybean oligopeptide (Pep) were subjected to simulated digestion in vitro to study the effect of Pep on the growth and metabolism of Lactobacillus acidophilus JCM 1132. First, the molecular weight distribution differences of samples before and after digestion were compared, and the samples were used to replace the nitrogen source components in the culture media. Then, the viable cell numbers, lactic acid and acetic acid content, differential metabolites, and metabolic pathways during the culturing process were measured. Results showed that the digested soybean oligopeptide (dPep) was less efficient than MRS medium in promoting the growth, but by increasing the content of the intermediates during the tricarboxylic acid (TCA) cycle, its metabolic capacity was significantly improved. Besides, due to the low molecular weight of dPep, it can be better transported and utilized. And dPep significantly strengthened the amino acid metabolism and weakened the glycerol phospholipid metabolism, so the ability of dPep in promoting the growth and metabolism of Lactobacillus acidophilus JCM 1132 is higher than the digested soybean protein (dPro).

Exploring the effect of soybean oligopeptide on the growth and metabolism of Lactobacillus acidophilus JCM 1132 by metabolomics.

Nano-Biosensing Platforms for Detection of Cow's Milk Allergens: An Overview

Among prevalent food allergies, cow milk allergy (CMA) is most common and may persist throughout the life. The allergic individuals are exposed to a constant threat due to milk proteins' presence in uncounted food products like yogurt, cheese, and bakery items. The problem can be more severe due to cross-reactivity of the milk allergens in the food products due to homologous milk proteins of diverse species. This problem can be overcome by proper and reliable food labeling in order to ensure the life quality of allergic persons. Therefore, highly sensitive and accurate analytical techniques should be developed to detect the food allergens. Here, significant research advances in biosensors (specifically immunosensors and aptasensors) are reviewed for detection of the milk allergens. Different allergic proteins of cow milk are described here along with the analytical standard methods for their detection. Additionally, the commercial status of biosensors is also discussed in comparison to conventional techniques like enzyme-linked immunosorbent assay (ELISA). The development of novel biosensing mechanisms/kits for milk allergens detection is imperative from the perspective of enforcement of labeling regulations and directives keeping in view the sensitive individuals.

Critical review on proteotypic peptide marker tracing for six allergenic ingredients in incurred foods by mass spectrometry

Peptide marker identification is one of the most important steps in the development of a mass spectrometry (MS) based method for allergen detection, since the robustness and sensitivity of the overall analytical method will strictly depend on the reliability of the proteotypic peptides tracing for each allergen. The European legislation in place issues the mandatory labelling of fourteen allergenic ingredients whenever used in different food formulations. Among these, six allergenic ingredients, namely milk, egg, peanut, soybean, hazelnut and almond, can be prioritized in light of their higher occurrence in food recalls for undeclared presence with serious risk decision. In this work, we described the results of a comprehensive evaluation of the current literature on MS-based allergen detection aiming at collecting all available information about proteins and peptide markers validated in independent studies for the six allergenic ingredients of interest. The main features of the targeted proteins were commented reviewing all details available about known isoforms and sequence homology particularly in plant-derived allergens. Several critical aspects affecting peptide markers reliability were discussed and according to this evaluation a final short-list of candidate markers was compiled likely to be standardized and implemented in MS methods for allergen analysis.

Effect of Marination Time on the Antioxidant Properties of Peptides Extracted from Organic Dry-Fermented Beef

In this study, we evaluated the effect of marination time on changes in the antioxidant properties of peptides extracted from bovine semimembranosus muscle. We measured antiradical scavenging capacity and reducing power of the peptides using a spectrophotometric decolorization method; inhibition of lipid oxidation was also assessed by estimating the level of malondialdehyde formed. According to our results, there was no benefit from the doubling of marinating time (from 24 to 48 h) as part of the preprocessing of beef. Samples from S1 batch (24 h marination) showed better antioxidant properties than those from S2 batch. We also tested various color parameters as a reflection of the inhibition of oxidative processes, in which case, the most favorable parameters from the consumer point of view were found to be lightness and redness. The effect of marination time on the degree of proteolytic changes was estimated using peptidomic approach. The degradation of myoglobin, hemoglobin, creatine kinase-type M, and beta-enolase-as the most sensitive proteins to proteolytic degradation-was observed during the 62 days of processing. It seems that the prolongation of marination time as a preprocessing step intensifies the hydrolytic degradation of proteins and peptides during the processing step. This results in the loss (or it has no effect) of antioxidative properties in organic dry-fermented beef.

Addressing Complex Matrix Interference Improves Multiplex Food Allergen Detection by Targeted LC-MS/MS

The frequent use of precautionary food allergen labeling (PAL) such as "may contain" frustrates allergic individuals who rely on such labeling to determine whether a food is safe to consume. One technique to study whether foods contain allergens is targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) employing scheduled multiple reaction monitoring (MRM). However, the applicability of a single MRM method to many commercial foods is unknown as complex and heterogeneous interferences derived from the unique composition of each food matrix can hinder quantification of trace amounts of allergen contamination. We developed a freely available, open source software package MAtrix-Dependent Interference Correction (MADIC) to identify interference and applied it with a method targeting 14 allergens. Among 84 unique food products, we found patterns of allergen contamination such as wheat in grains, milk in chocolate-containing products, and soy in breads and corn flours. We also found additional instances of contamination in products with and without PAL as well as highly variable soy content in foods containing only soybean oil and/or soy lecithin. These results demonstrate the feasibility of applying LC-MS/MS to a variety of food products with sensitive detection of multiple allergens in spite of variable matrix interference.

Absolute Quantification of Allergen Glb33 in Rice by Liquid Chromatography-Mass Spectrometry using Two Isotope-Labeled Standard Peptides

Allergen Glb33 is an important allergen in rice that can cause allergic reactions such as asthma and atopic dermatitis. However, knowledge of the content in rice is sparse. In the present work, an absolute protein quantification method was established for allergen Glb33 in rice samples using liquid chromatography-tandem mass spectrometry. After extraction of allergen Glb33 from rice grains using salt solution, the isotope-labeled peptide internal standard was added to the extract, followed by enzymatic digestion with trypsin. The signature peptide and its isotope-labeled analogue from the tryptic hydrolysates of allergen Glb33 and the internal standard were detected by liquid chromatography-tandem mass spectrometry. The quantitative bias caused by tryptic efficiency and matrix effect was corrected by using two isotope-labeled standard peptides. The method exhibited good linearity in the range of 1-200 nM, with coefficients of determination of R² > 0.998. A high sensitivity was observed, with a limit of quantification of 0.97 nM. Mean recoveries obtained from different rice matrices ranged from 82.7%-98.1% with precision <8.5% in intraday trials ( n = 6), while mean recoveries were from 75.1%-107.4% with precision <14.6% in interday trials ( n = 14). The developed method was successfully applied to the analysis of allergen Glb33 in 24 different rice cultivars.

Absolute quantification of targeted meat and allergenic protein additive peptide markers in meat products

We present an implementation of the absolute quantification (AQUA) method for monitoring of peptide abundance in complex mixtures of processed proteins. Specific peptide markers from meats (chicken, duck, goose, pork and beef) and common protein allergenic additives (soy, milk and egg white preparations) were chosen and synthesised with stable isotopes (13C and 15N) for use as internal standards. A wide range of food samples, from cooked or raw meat to sterilised pâté, was analysed by a triggered multiple reaction monitoring mode experiment and triple quadrupole mass spectrometry for the direct measure of tryptic peptides representing the amounts of specific proteins. Considerable differences among the abundances of meat and non-meat proteins were observed, and illegal addition and replacement of ingredients were discovered, i.e. undeclared addition of pork and egg white proteins, and illegal substitution of veal, goose and duck meat with cheaper pork.

LC⁻Q⁻TOF⁻MS/MS Identification of Specific Non-Meat Proteins and Peptides in Beef Burgers

Beef burgers are a popular food choice, due to their taste and convenience. The extensive range of beef burgers with different flavours currently offered on the market is adding to their growing consumption. This study detected and identified specific non-meat proteins and peptide markers originating from functional preparations, i.e., powdered mixes of protein additives and spices, used as meat substitutes in the production of ready-to-cook beef burgers. Twenty-eight soy proteins, including isoforms (nine milk-, three pea- and one beetroot-specific protein) were found concurrently with a set of peptide markers unique to soy glycinin and β-conglycinin, pea vicilin and provicilin, milk α_S1-casein, β-lactoglobulin, as well as beetroot elongation factor 2. Soy and beetroot proteins and peptides were observed in all burgers containing additives. Milk and pea proteins were included in powdered mixes but were not detected in burgers, indicating that their content was below the limit of detection. The study demonstrates that the proposed method can be implemented to analyse protein additives in cooked burgers; however, the presence of low amounts of additives, below 1–2%, should be further confirmed by using a more sensitive triple quadrupole instrument.

Detection of allergenic additives in processed meat products

Allergic responses to food components are an increasing problem all over the world. It is therefore important to protect people who are vulnerable to food allergens against accidental and unintended consumption of products containing allergic ingredients. The meat industry commonly uses various allergic additives in the production of processed products, such as legumes (soy, peas, beans), milk and egg preparations, cereals containing gluten (wheat, rye, barley and oats), and spices (celery and mustard). These meat additives have specific technological properties, which help to create a texture or flavor profile, or affect the nutritional value, although some of them, such as soy, mustard, milk and egg white proteins, can cause severe allergic reactions. The aim of this paper is to discuss the application of various recently established methods of detection of allergenic additives in processed meat products - for instance cold cuts and sausages. The new methods are based mainly on protein, DNA, and isoflavones or phytic acid analysis. The article also characterizes the latest trends in the development of research on methods that would enable quick and reliable identification of targeted allergens in meat products. © 2018 Society of Chemical Industry.

Development of a strategy for the quantification of food allergens in several food products by mass spectrometry in a routine laboratory

Worldwide, mass spectrometry is widely used to detect and quantify food allergens, especially in complex and processed food products. Yet, the absence of a regulatory framework for the developed methods has led to a lack of harmonization between laboratories. In this study, ten allergens were analyzed in eight food products by UHPLC-MS/MS, in order to establish criteria for the retention time, variation tolerance, the ion ratio deviation, and the signal-to-noise ratio for allergen detection. The set of criteria should help laboratories to compare results and avoid false positives and negatives. Furthermore, a strategy combining standard addition and labeled peptide correction was used to quantify milk, soy, peanut, and egg allergens in eight food products. This strategy is particularly interesting for routine laboratories, which receive hundreds of samples and cannot use an external calibration curve for each sample.