Advances in ultra-high performance liquid chromatography coupled to tandem mass spectrometry for sensitive detection of several food allergens in complex and processed foodstuffs

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.

In-house validation of an LC-MS method for the multiplexed quantitative determination of total allergenic food in chocolate

Mass spectrometry has been widely accepted as a confirmatory tool for the sensitive detection of undeclared presence of allergenic ingredients. Multiple methods have been developed so far, achieving different levels of sensitivity and robustness, still lacking harmonization of the analytical validation and impairing comparability of results. In this investigation, a quantitative method has been validated in-house for the determination of six allergenic ingredients (cow's milk, hen's egg, peanut, soybean, hazelnut, and almond) in a chocolate-based matrix. The latter has been produced in a food pilot plant to provide a real and well-characterized matrix for proper assessment of method performance characteristics according to official guidelines. In particular, recent considerations issued by the European Committee for Standardization have been followed to guide a rigorous single-laboratory validation and to feature the main method performance, such as selectivity, linearity, and sensitivity. Synthetic surrogates of the peptide markers have been used both in native and labelled forms in matrix-matched calibration curves as external calibrants and internal standards, respectively. A two-order of magnitude range was investigated, focusing on the low concentration range for proper assessment of the detection and quantification limits (LOD and LOQ) by rigorous calibration approach. Conversion factors for all six allergenic ingredients have been determined for the first time to report the final quantitative information as fraction of total allergenic food protein (TAFP) per mass of food (µgTAFP/gfood), since such a reporting unit is exploitable in allergenic risk assessment plans. The method achieved good sensitivity with LOD values ranging between 0.08 and 0.2 µgTAFP/gfood, for all ingredients besides egg and soybean, whose quantitative markers reported a slightly higher limit (1.1 and 1.2 µgTAFP/gfood, respectively). Different samples of chocolate bar incurred at four defined concentration levels close to the currently available threshold doses have been analyzed to test the quantitative performance of the analytical method, with a proper estimate of the measurement uncertainty from different sources of variability. The sensitivity achieved resulted in compliance with the various threshold doses issued or recommended worldwide.

Food allergen detection by mass spectrometry: From common to novel protein ingredients

Food allergens are molecules, mainly proteins, that trigger immune responses in susceptible individuals upon consumption even when they would otherwise be harmless. Symptoms of a food allergy can range from mild to acute; this last effect is a severe and potentially life-threatening reaction. The European Union (EU) has identified 14 common food allergens, but new allergens are likely to emerge with constantly changing food habits. Mass spectrometry (MS) is a promising alternative to traditional antibody-based assays for quantifying multiple allergenic proteins in complex matrices with high sensitivity and selectivity. Here, the main allergenic proteins and the advantages and drawbacks of some MS acquisition protocols, such as multiple reaction monitoring (MRM) and data-dependent analysis (DDA) for identifying and quantifying common allergenic proteins in processed foodstuffs are summarized. Sections dedicated to novel foods like microalgae and insects as new sources of allergenic proteins are included, emphasizing the significance of establishing stable marker peptides and validated methods using database searches. The discussion involves the in-silico digestion of allergenic proteins, providing insights into their potential impact on immunogenicity. Finally, case studies focussing on microalgae highlight the value of MS as an effective analytical tool for ensuring regulatory compliance throughout the food control chain.

Targeted proteomics for rapid and robust peanut allergen quantification

This study improves LC-MS-based trace level peanut allergen quantification in processed food by refining method robustness, total analysis time and method sensitivity. Extraction buffer (six compared) and peptide choice were optimised and found to profoundly affect method robustness. A rapid extraction and in-solution digestion method was developed omitting subsequent reduction, alkylation and sample clean-up steps effectively reducing total analysis time from the previously reported ∼5.5-20 h to ∼2.5 h. For the three best performing peptides, accurate quantification (CVs < 15%) with matrix-matched calibration curves (R² = 0.99-0.97) was achieved for peanut muffin and ice-cream with excellent linearity (0.25-1000 mg kg^-1). The best performing peptide enabled excellent recovery rates in ice-cream (106.0 ± 15.1%) and peanut muffin (72.7 ± 13.4%). Sensitivity (LOD = 0.25-0.5 mg kg^-1; LOQ = 0.5-1.0 mg kg^-1) was 2- to 20-fold improved compared to previous methods depending on the peptide. These methodological improvements contribute to robust peanut detection in food and can be translated to additional food-borne allergens.

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.

Tree Nuts and Peanuts as a Source of Beneficial Compounds and a Threat for Allergic Consumers: Overview on Methods for Their Detection in Complex Food Products

Consumption of tree nuts and peanuts has considerably increased over the last decades due to their nutritional composition and the content of beneficial compounds. On the other hand, such widespread consumption worldwide has also generated a growing incidence of allergy in the sensitive population. Allergy to nuts and peanuts represents a global relevant problem, especially due to the risk of the ingestion of hidden allergens as a result of cross-contamination between production lines at industrial level occurring during food manufacturing. The present review provides insights on peanuts, almonds, and four nut allergens—namely hazelnuts, walnuts, cashew, and pistachios—that are likely to cross-contaminate different food commodities. The paper aims at covering both the biochemical aspect linked to the identified allergenic proteins for each allergen category and the different methodological approaches developed for allergens detection and identification. Attention has been also paid to mass spectrometry methods and to current efforts of the scientific community to identify a harmonized approach for allergens quantification through the detection of allergen markers.

Recent advances in analytical strategies and microsystems for food allergen detection

Food allergies are abnormal immune responses that typically occur within short period after exposure of certain allergenic proteins in food or food-related resources. Currently, the means to treat food allergies is not clearly understood, and the only known prevention method is avoiding the consumption of allergen-containing foods. From the viewpoint of analytical methods, the effective detection of food allergens is hindered by the effects of various treatment processes and food matrices on trace amounts of allergens. The aim of this effort is to provide the reader with a clear and concise view of new advances for the detection of food allergens. Therefore, the present review explored the development status of various biosensors for the real-time, on-site detection of food allergens with high selectivity and sensitivity. The review also described the analytical consideration for the quantification of food allergens, and global development trends and the future availability of these technologies.

Quantification of Soy-Derived Ingredients in Model Bread and Frankfurter Matrices with an Optimized Liquid Chromatography-Tandem Mass Spectrometry External Standard Calibration Workflow

ABSTRACT

The detection and quantification of soy protein is important for food allergen management and identifying the presence of undeclared soy proteins. Heat processing and matrix interactions can affect the accuracy of allergen detection methods. The sensitivity of enzyme-linked immunosorbent assay methods can be compromised if protein epitopes are modified during processing. Therefore, a mass spectrometry (MS)-based method was evaluated for the recovery of total soy protein in incurred matrices. MS-based quantification of total soy protein was assessed by using a combination of external and internal standards. The reproducibility of the standard curves was investigated by comparing within-day and among-day variation. Incurred samples were prepared using bread and frankfurters as model food matrices. Several soy-derived ingredients were used to prepare the matrices with varying levels of soy protein (1, 10, 50, or 100 ppm of total soy protein). A pooled standard curve was used to estimate the total soy protein concentration of the incurred food matrices and the percent total protein recovery. The variation of replicate standard curves between days and among all days was not significant. The differences in slopes obtained from replicate standards run on different days were minimal. The most influential factor on the quantitative protein recovery in incurred samples was the effect of the physical matrix structure on protein extraction. The lowest percent protein recoveries, less than 50%, were calculated for uncooked matrices. The cooked matrices had percentage recoveries between 50 and 150% for all total soy protein levels. Other factors, such as type of ingredient, were determined to be not as impactful on recovery. The MS method described in this study was able to provide sensitive detection and accurate quantification of total soy protein from various soy-derived ingredients present in processed food matrices.

HIGHLIGHTS

High-Throughput Identification of Allergens in a Food System via Hybridization Probe Cluster-Targeted Next-Generation Sequencing

Food allergies (FAs) are a crucial public health problem and a severe food safety issue, resulting in an urgent need for an accurate method to detect all of the hidden allergens that exist in food systems. Current methods for detecting allergens typically utilize ELISA, PCR, or LC-MS, which are suitable for the confirmatory analysis of allergens from ingredients rather than unintended contaminants. In this study, we demonstrate a hybridization probe cluster-targeted next-generation sequencing (HPC-NGS) platform for high-throughput screening of potential allergens in food systems. The HPC-NGS successfully captured target DNA fragments and identified 19 allergenic ingredients in a complex food system. Additionally, the HPC-NGS provided expected allergenic species matching rates of 94.24-100% in single food materials and 99.87-99.98% in processed food products. Thus, HPC-NGS enables the accurate characterization of allergenic ingredients and unintended allergenic contaminants in foods. Our results provide new perspectives on the use of HPC-NGS in the accuracy of high-throughput detection technologies for allergens imposed by the complex matrix effect.

Comparison of allergen quantification strategies for egg, milk, and peanut in food using targeted LC-MS/MS

Methods for the detection and quantification of food allergens in complex matrices are necessary to ensure compliance with labeling regulations and assess the effectiveness of food allergen preventive controls. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as an orthogonal technique in complement to immunochemical-based assays. However, the absence of established guidelines for MS-based quantification of allergens in food has limited harmonization among the method development community. In this study, different quantification strategies were evaluated using a previously developed multiplexed LC-MS/MS method for the detection of egg, milk, and peanut. Peptide performance criteria (retention time, signal-to-noise ratio, and ion ratio tolerance) were established and quantification approaches using varying calibrants, internal standards, background matrices, and calibration curve preparation schemes were systematically evaluated to refine the previous method for routine laboratory use. A matrix-matched calibration curve using allergen ingredients as calibrants and stable isotope-labeled peptides as internal standards provided the most accurate quantitative results. The strategy was further verified with commercially available reference materials and allowed for the confident detection and quantification of food allergens. This work highlights the need for transparency in calibration strategy and peptide performance requirements for effective evaluation of mass spectrometric methods for the quantification of food allergens.

Labeled Peptide-Free UHPLC-MS/MS Method Used for Simultaneous Determination of Shrimp and Soybean in Sauce Products

Unintentional missing of shrimp and soybean allergen information on precautionary food allergen labeling often occurs in sauce products. To avoid food allergies, sensitive and time-saving analytical methods are urgently needed. However, the currently reported methods usually employed labeled peptides for isotope internal standard quantitation, and the matrix effect caused by protein extraction or digestion can not be corrected. In this study, a labeled peptide-free standard addition method was developed for simultaneous determination of shrimp and soybean in sauce products using ultrahigh-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS). Through the rational selection of stable peptides, satisfying mean recoveries and relative standard deviations of the chosen peptides are achieved. The limit of quantifications of each peptide ranged from 0.25 to 5 μg tropomyosin/g sauce and from 1 to 10 μg Gly m 6/g sauce, respectively. Using the labeled peptide-free UHPLC-MS/MS method, not only ideal experimental results were obtained surpassing those obtained with labeled peptides, but also the reagents were economized and shortening of the sample preparation time was achieved.

Development of a simplified, sensitive, and accurate LC-MS/MS method for peanut quantification in wheat flour-based dry matrices

In this study, an ELISA-based method was observed to overestimate quantification of peanut in three wheat flour-based dry matrices (both raw and cooked). A reliable method using liquid chromatography tandem mass spectrometry (LC-MS/MS) was developed to quantify peanut accurately in these matrices. This method simplified both sample preparation and quantification compared with previous approaches, by digesting peanut proteins without reduction and alkylation and using Ara h 1 to build calibration curves. A significantly increased amount of peanut peptides was detected by heating the extracts. The sensitivity and linearity were superior to most commercial ELISA kits. The limit of quantification (LOQ) was 0.31 mg/kg total peanut in wheat flour and the linear range was between 0.3 and 40 mg/kg. This LC-MS/MS method could be applied as a confirmatory method for peanut allergen management when positive ELISA results raise suspicion of contamination.

Targeted mass spectrometry quantification of total soy protein residues from commercially processed ingredients for food allergen management

Soybean is one of the most commonly allergenic foods in the U.S. However, the variety of commercial soy ingredients used in the food industry makes soybean a challenging allergen to detect and quantify. The processing methods used to produce soy-derived ingredients result in protein modifications that often substantially impact detection and quantification with commonly used antibody-based methods. This study aimed to develop a mass spectrometry (MS)-based method capable of quantifying commercially processed soy ingredients in food matrices. A quantification strategy using external standards with internal calibrants was developed and evaluated, resulting in the ultimate use of a matrix-independent standard curve of non-roasted soy flour with milk proteins as carrier proteins. The method performance was evaluated by quantifying six soy-derived ingredients in incurred food matrices using three quantification strategies. Out of the twelve ingredient-matrix combinations with 10 ppm incurred total soy protein, eight had maximum recoveries between 60 and 120% using the full standard curve strategy. Other quantification strategies may be useful for internal quality control and interlaboratory calibrations. Compared with three commercial ELISA kits, the MS method showed a substantial advantage in quantifying the highly processed soy proteins in food matrices. SIGNIFICANCE: The ability to quantify undeclared soy protein in food products regardless of the soy ingredient source is essential for food allergen management, risk assessment, and regulatory enforcement. The MS-based method described here is able to reliably quantify six different soy-derived ingredients incurred in a model processed food. When compared with existing commercial ELISA methods, the MS method is much less affected by matrices and ingredient types, indicating its wider applicability to a range of soy-derived ingredients and processed products.

A UHPLC-MS/MS Method for the Detection of Meat Substitution by Nine Legume Species in Emulsion-Type Sausages

Meat substitution by legume proteins in various types of meat products is a common practice. A reliable detection and quantification of these additives is required to control food specifications, especially regarding food fraud. Consequently, a UHPLC-MS/MS method for the simultaneous detection of alfalfa (Medicago sativa), broad bean (Vicia faba), chickpea (Cicer arietinum), lentil (Lens culinaris), lupine (Lupinus albus and Lupinus angustifolius), pea (Pisum sativum), peanut (Arachis hypogaea), and soy (Glycine max) proteins in meat products was developed. After protein extraction and tryptic digestion, three marker peptides for each legume species were measured by multiple reaction monitoring (MRM) using an optimized extraction protocol. To the best of our knowledge, the marker peptides for alfalfa, broad bean, chickpea, and lentil have not been reported previously. Emulsion-type sausages with 0.1, 0.4, 0.7, 1.0, 1.3, 1.6, 1.9, 2.2, and 2.5% meat substitution by each legume species, representing the concentration range between inadvertently transferred cross-contaminations and the conscious use for meat substitution, were produced for matrix calibration. No false-positive results were recorded in blank samples. In the quantification of alfalfa, broad bean, chickpea, lentil, pea, peanut, and soy, 673 of 756 measuring data of the recovery rate in unknown sausages were in the accepted range of 80–120%.

Discovery based high resolution MS/MS analysis for selection of allergen markers in chocolate and broth powder matrices

Peptide marker identification is an important step in development of a mass spectrometry method for multiple allergen detection, since specificity, robustness and sensitivity of the overall analytical method will depend on the reliability of the proteotypic peptides. As part of the development of a multi-analyte reference method, discovery analysis of two incurred food matrices has been undertaken to select the most reliable peptide markers. Six allergenic ingredients (milk, egg, peanut, soybean, hazelnut, and almond) were incurred into either chocolate or broth powder matrix. Different conditions of protein extraction and purification were tested and the tryptic peptide pools were analysed by untargeted high resolution tandem mass spectrometry and the resulting fragmentation spectra were processed via a commercial software for sequence identification. The analysis performed on incurred foods provides both a prototype effective and straightforward sample preparation protocol and delivers reliable peptides to be included in a standardized selected reaction monitoring method.

Validation of a MS Based Proteomics Method for Milk and Egg Quantification in Cookies at the Lowest VITAL Levels: An Alternative to the Use of Precautionary Labeling

The prevalence of food allergy has increased over the last decades and consequently the food labeling policies have improved over the time in different countries to regulate allergen presence in foods. In particular, Reg 1169 in EU mandates the labelling of 14 allergens whenever intentionally added to foods, but the inadvertent contamination by allergens still remains an uncovered topic. In order to warn consumers on the risk of cross-contamination occurring in certain categories of foods, a precautionary allergen labelling system has been put in place by food industries on a voluntary basis. In order to reduce the overuse of precautionary allergen labelling (PAL), reference doses and action limits have been proposed by the Voluntary Incidental Trace Allergen Labelling VITAL project representing a guide in this jeopardizing scenario. Development of sensitive and reliable mass spectrometry methods are therefore of paramount importance in this regard to check the contamination levels in foods. In this paper we describe the development of a time-managed multiple reaction monitoring (MRM) method based on a triple quadrupole platform for milk and egg quantification in processed food. The method was in house validated and allowed to achieve levels of proteins lower than 0.2 mg of total milk and egg proteins, respectively, in cookies, challenging the doses recommended by VITAL. The method was finally applied to cookies labeled as milk and egg-free. This method could represent, in perspective, a promising tool to be implemented along the food chain to detect even tiny amounts of allergens contaminating food commodities.

Are current analytical methods suitable to verify VITAL® 2.0/3.0 allergen reference doses for EU allergens in foods?

Food allergy affects up to 6% of Europeans. Allergen identification is important for the risk assessment and management of the inadvertent presence of allergens in foods. The VITAL® initiative for voluntary incidental trace allergen labeling suggests protein reference doses, based on clinical reactivity in food challenge studies, at or below which voluntary labelling is unnecessary. Here, we investigated if current analytical methodology could verify the published VITAL® 2.0 doses, that were available during this analysis, in serving sizes between 5 and 500 g. Available data on published and commercial ELISA, PCR and mass spectrometry methods, especially for the detection of peanuts, soy, hazelnut, wheat, cow's milk and hen's egg were reviewed in detail. Limit of detection, quantitative capability, matrix compatibility, and specificity were assessed. Implications by the recently published VITAL® 3.0 doses were also considered. We conclude that available analytical methods are capable of reasonably robust detection of peanut, soy, hazelnut and wheat allergens for levels at or below the VITAL® 2.0 and also 3.0 doses, with some methods even capable of achieving this in a large 500 g serving size. Cow's milk and hen's egg are more problematic, largely due to matrix/processing incompatibility. An unmet need remains for harmonized reporting units, available reference materials, and method ring-trials to enable validation and the provision of comparable measurement results.

Comparative study of concatemer efficiency as an isotope-labelled internal standard for allergen quantification

Mass spectrometry-based methods coupled with stable isotope dilution have become effective and widely used methods for the detection and quantification of food allergens. Current methods target signature peptides resulting from proteolytic digestion of proteins of the allergenic ingredient. The choice of appropriate stable isotope-labelled internal standard is crucial, given the diversity of encountered food matrices which can affect sample preparation and analysis. We propose the use of concatemer, an artificial and stable isotope-labelled protein composed of several concatenated signature peptides as internal standard. With a comparative analysis of three matrices contaminated with four allergens (egg, milk, peanut, and hazelnut), the concatemer approach was found to offer advantages associated with the use of labelled proteins, ideal but unaffordable, and circumvent certain limitations of traditionally used synthetic peptides as internal standards. Although used in the proteomic field for more than a decade, concatemer strategy has not yet been applied for food analysis.

Parallel Reaction Monitoring Mass Spectrometry Method for Detection of Both Casein and Whey Milk Allergens from a Baked Food Matrix

Milk allergy is among the most common food allergies present in early childhood, which in some cases may persist into adulthood as well. Proteins belonging to both casein and whey fractions of milk can trigger an allergic response in susceptible individuals. Milk is present as an ingredient in many foods, and it can also be present as casein- or whey-enriched milk-derived ingredients. As whey proteins are more susceptible to thermal processing than caseins, conventional methods often posed a challenge in accurate detection of whey allergens, particularly from a processed complex food matrix. In this study, a targeted mass spectrometry method has been developed to detect the presence of both casein and whey allergens from thermally processed foods. A pool of 19 candidate peptides representing four casein proteins and two whey proteins was identified using a discovery-driven target selection approach from various milk-derived ingredients. These target peptides were evaluated by parallel reaction monitoring of baked cookie samples containing known amounts of nonfat dry milk (NFDM). The presence of milk could be detected from baked cookies incurred with NFDM at levels as low as 1 ppm using seven peptides representing α-, β-, and κ-casein proteins and three peptides representing a whey protein, β-lactoglobulin, by this consensus PRM method.

Use of IHF-QD Microscopic Analysis for the Detection of Food Allergenic Components: Peanuts and Wheat Protein

The aim of the study was to analytically evaluate quantum dots in immunohistofluorescence (IHF-QD) microscopic imaging as detectors of food allergens—peanut and wheat. The experiment was designed as two in silico experiments or simulations: (a) models of pastry samples were prepared with the addition of allergenic components (peanut and wheat protein components) and without the addition of allergenic components, and (b) positive and negative commercial samples underwent food allergen detection. The samples from both simulations were tested by the ELISA and IHF-QD microscopic methods. The primary antibodies (secondary antibodies to a rabbit Fc fragment with labeled CdSe/ZnS QD) were labelled at 525, 585, and 655 nm emissions. The use of quantum dots (QDs) has expanded to many science areas and they are also finding use in food allergen detection, as shown in the study. The study indicated that differences between the ELISA and IHF-QD microscopic methods were not observable among experimentally produced pastry samples with and without allergenic components, although differences were observed among commercial samples. The important value of the study is certainly the differences found in the application of different QD conjugates (525, 585, and 655). The highest contrast was found in the application of 585 QD conjugates that can serve for the possible quantification of present food allergens—peanuts and wheat. The study clearly emphasized that QD can be used for the qualitative detection of food allergens and can represent a reliable analytical method for food allergen detection in different food matrixes.

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.

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.

Surface plasmon resonance (SPR) biosensors for food allergen detection in food matrices

Food allergies are recognized as a growing public health concern, with an estimated 3% of adults and 6-8% of children affected by food allergy disorders. Hence, food allergen detection, labeling, and management have become significant priorities within the food industry, and there is an urgent requirement for reliable, sensitive, and user-friendly technologies to trace food allergens in food products. In this critical review, we provide a comprehensive overview of the principles and applications of surface plasmon resonance (SPR) biosensors in the identification and quantification of food allergens (milk, egg, peanut, and seafood), including fiber-optic surface plasmon resonance (FOSPR), surface plasmon resonance imaging (SPRI), localized surface plasmon resonance (LSPR), and transmission surface plasmon resonance (TSPR). Moreover, the characteristics and fitness-for-purpose of each reviewed SPR biosensor is discussed, and the potential of newly developed SPR biosensors for multi-allergen real-time detection in a complex food system is highlighted. Such SPR biosensors are also required to facilitate the reliable, high-throughput, and real-time detection of food allergens by the food control industry and food safety control officials to easily monitor cross-contamination during food processing.

A hybridization chain reaction coupled with gold nanoparticles for allergen gene detection in peanut, soybean and sesame DNAs

Food allergy is an abnormal immune response of the immune system to some foods, which has caused great harm to people's health. Therefore, it is particularly important to detect allergens in food. In this article, a hybridization chain reaction (HCR) was coupled with gold nanoparticles (AuNPs) to detect the allergen genes of peanut, soybean and sesame DNAs. Two hairpin probes (H1 and H2) were designed for the allergen target genes of peanut, soybean and sesame DNAs. In the presence of target DNA, the hybridization chain reaction was triggered by it producing long double-stranded DNA (dsDNA) products. In the gold nanoparticle system, long dsDNA couldn't be adsorbed on the surface of AuNPs. When the concentration of salt ions in the solution increased, gold nanoparticles accumulated and led to a decrease of ultraviolet absorption. In the absence of target DNA, no hybridization chain reaction occurred. The hairpin probes could be adsorbed on the surface of AuNPs and no accumulation happened for gold nanoparticles even if the concentration of salt ions in the solution was increased. This method required no enzymes and had a strong specificity, so it was very easy to distinguish target DNA from non-target DNA. The detection limit of three allergens detected by this method was as low as 0.5 nM. The feasibility of this method for the detection of commercial commodities had been demonstrated by the successful detection of the DNAs extracted from commercial commodities, which were treated with extreme thermostable single-stranded binding protein (ET SSB).

Detection of Six Commercially Processed Soy Ingredients in an Incurred Food Matrix Using Parallel Reaction Monitoring

Soybeans are one of the major allergenic foods in many countries. Soybeans are commonly processed into different types of soy ingredients to achieve the desired properties. The processing, however, may affect the protein profiles and protein structure, thus affecting the detection of soy proteins. Mass spectrometry (MS) is a potential alternative to the traditional immunoassays for the detection of soy-derived ingredients in foods. This study aims to develop a liquid chromatography-tandem MS method that uniformly detects different types of soy-derived ingredients. Target peptides applicable to the detection of six commercial soy ingredients were identified based on the results of MS label-free quantification and a set of selection criteria. The results indicated that soy ingredient processing can result in different protein profiles. A total of six soy ingredients were then individually incurred into cookie matrices at different levels. Sample preparation methods were optimized, and a distinct improvement in peptide performance was observed after optimization. Cookies and dough incurred with different soy ingredients at 100 ppm total soy protein showed a similar level of peptide recovery (90% mean signal relative to unroasted soy flour), demonstrating the ability of the MS method to detect processed soy ingredients in a uniform manner.

The role of incurred materials in method development and validation to account for food processing effects in food allergen analysis

The issue of undeclared allergens represents a matter of great concern, being the subject of many alert notifications by the Rapid Alert System for Food and Feed portal of the European Commission, often leading to food recalls. The availability of reliable analytical approaches able to detect and quantify hidden allergens in processed foods is increasingly requested by the food industry, food safety authorities and regulatory bodies to protect sensitive consumers' health. The present review discusses the fundamental role of incurred materials for method development and analytical performance assessment in a metrology perspective on testing for undeclared allergens in processed foodstuffs. Due to the nature of the analytes and their susceptibility to various processing effects, reliability and comparability of results have posed a great challenge. In this context, the use of incurred samples as reference materials permits simulation of the effects of food processing on target analyte structure affecting analyte extractability and detectability. Graphical abstract ᅟ.

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.

In house validation of a high resolution mass spectrometry Orbitrap-based method for multiple allergen detection in a processed model food

In recent years, mass spectrometry (MS) has been establishing its role in the development of analytical methods for multiple allergen detection, but most analyses are being carried out on low-resolution mass spectrometers such as triple quadrupole or ion traps. In this investigation, performance provided by a high resolution (HR) hybrid quadrupole-Orbitrap™ MS platform for the multiple allergens detection in processed food matrix is presented. In particular, three different acquisition modes were compared: full-MS, targeted-selected ion monitoring with data-dependent fragmentation (t-SIM/dd2), and parallel reaction monitoring. In order to challenge the HR-MS platform, the sample preparation was kept as simple as possible, limited to a 30-min ultrasound-aided protein extraction followed by clean-up with disposable size exclusion cartridges. Selected peptide markers tracing for five allergenic ingredients namely skim milk, whole egg, soy flour, ground hazelnut, and ground peanut were monitored in home-made cookies chosen as model processed matrix. Timed t-SIM/dd2 was found the best choice as a good compromise between sensitivity and accuracy, accomplishing the detection of 17 peptides originating from the five allergens in the same run. The optimized method was validated in-house through the evaluation of matrix and processing effects, recoveries, and precision. The selected quantitative markers for each allergenic ingredient provided quantification of 60-100 μg_ingred/g allergenic ingredient/matrix in incurred cookies.

A mass spectrometry method for sensitive, specific and simultaneous detection of bovine blood meal, blood products and milk products in compound feed

Feed sustainability is one of the biggest challenges for the next few years. Solutions have to be found that take feed quality and safety into account. Animal by-products are one valuable source of proteins. However, since the bovine spongiform encephalopathy (BSE) crisis, their use has been strictly regulated. The objective of this study was to propose a routine, sensitive and specific method using ultra-high performance liquid chromatography coupled to tandem mass spectrometry for the detection of blood-derived products and milk powder in feed. Contaminated aquafeeds were analysed in order to evaluate the sensitivity and specificity of the method. This new method meets both selectivity and sensitivity (0.1% (w/w)) requirements imposed by the European Commission for animal proteins detection methods. It offers an innovative and complementary solution for the simultaneously identification of authorised and unauthorised animal by-products such as processed animal proteins (PAPs).

Liquid chromatography coupled to tandem mass spectrometry for detecting ten allergens in complex and incurred foodstuffs

Food allergy is a considerable heath problem, as undesirable contaminations by allergens during food production are still widespread and may be dangerous for human health. To protect the population, laboratories need to develop reliable analytical methods in order to detect allergens in various food products. Currently, a large majority of allergen-related food recalls concern bakery products. It is therefore essential to detect allergens in unprocessed and processed foodstuffs. In this study, we developed a method for detecting ten allergens in complex (chocolate, ice cream) and processed (cookie, sauce) foodstuffs, based on ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS). Using a single protocol and considering a signal-to-noise ratio higher than 10 for the most abundant multiple reaction monitoring (MRM) transition, we were able to detect target allergens at 0.5mg/kg for milk proteins, 2.5mg/kg for peanut, hazelnut, pistachio, and cashew proteins, 3mg/kg for egg proteins, and 5mg/kg for soy, almond, walnut, and pecan proteins. The ability of the method to detect 10 allergens with a single protocol in complex and incurred food products makes it an attractive alternative to the ELISA method for routine laboratories.