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

Mass Spectrometry-Based Method for Multiple Allergens Control: Application to Bakery Goods

In recent years, mass spectrometry has played a key role as a confirmatory method to unequivocally identify multiple allergens, increasing the level of protection of allergic consumers. Despite advances made in methods of development, food processing still represents a critical issue in terms of the detection and accurate quantification of allergens due to chemical/structural modifications that can occur on the protein moiety or interferences of matrix compounds that might impair their final detection. Based on the multi-allergen MS/MS method devised within the ThrAll project, in this paper, we investigated the applicability of the developed method for the detection of traces of allergenic ingredients including egg, milk, soy, almond, hazelnut, peanuts, and sesame in two different kind of food matrices, namely cookies and rusks. The products were produced at laboratory scale in a food pilot plant that underwent different technological and thermal treatments. The challenge was to validate, in these extensively processed foods, the selected proteotypic peptide-markers capable of tracing the culprit ingredients in baked goods despite the processing the foods had undergone for their production. To accomplish this goal, the multi-target method developed on a low-resolution MS platform was transferred to a high-resolution MS system, and the pre-identified markers were also checked and validated on the new platform in order to be considered robust markers able to be indistinctly used on both types of platforms. Finally, the sensitivity of the method in terms of the Limit of Detection (LOD) and Limit of Quantification (LOQ) was calculated and the effect of the processing conditions on allergens detection in both baked goods was also investigated.

Selection of signature peptide biomarkers for the sesame allergens in commercial food based on LC-MS/MS

Sesame is a commonly used food ingredient, yet it is one of the eight major allergens. As sesame is often consumed in various processed forms, it is important to establish methods for detecting sesame allergens in processed foods. Liquid chromatography-tandem mass spectrometry (LC-MS/MS), using characteristic peptides as biomarkers, detects multiple allergenic proteins simultaneously with high sensitivity and accuracy. Choosing robust biomarkers is beneficial for developing a specific, universal, and sensitive method. To obtain excellent peptides of sesame allergens, sixteen commercial products were used as test materials. Proteins from these materials were extracted, digested, and analyzed. Peptides were screened based on several criteria, including specificity and amino acid composition. Only peptides showing process robustness were retained. Ultimately, nine peptides were selected as the best biomarkers. Based on the above peptides, it is possible to achieve precise and high-sensitivity detection of sesame allergens in processed products.

Quantifying allergenic proteins using antibody-based methods or liquid chromatography-mass spectrometry/mass spectrometry: A review about the influence of food matrix, extraction, and sample preparation

Accurate quantification of allergens in food is crucial for ensuring consumer safety. Pretreatment steps directly affect accuracy and efficiency of allergen quantification. We systematically reviewed the latest advances in pretreatment steps for antibody-based methods and liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) protein quantification methods in food. For antibody-based methods, the effects induced by food matrix like decreased allergen solubility, epitope masking, and nonspecific binding are of the upmost importance. To mitigate interference from the matrix, effective and proper extraction can be used to obtain the target allergens with a high protein concentration and necessary epitope exposure. Removal of interfering substances, extraction systems (buffers and additives), assistive technologies, and commercial kits were discussed. About LC-MS/MS quantification, the preparation of the target peptides is the crucial step that significantly affects the efficiency and results obtained from the MS detector. The advantages and limitations of each method for pre-purification, enzymatic digestion, and peptide desalting were compared. Additionally, the application characteristics of microfluidic-based pretreatment devices were illustrated to improve the convenience and efficiency of quantification. A promising research direction is the targeted development of pretreatment methods for complex food matrices, such as lipid-based and carbohydrate-based matrices.

Improved multi-food allergen analysis of processed foods using HRAM-LC-MS/MS with an ELISA-validated extraction solution and MS sample prep kit

Food allergens in processed foods are affected by heating, processing, and the food matrix. To conduct highly reliable tests, extracting allergens into test solutions is necessary for appropriate detection. In addition to the commonly used enzyme-linked immunosorbent assay (ELISA), liquid chromatography-mass spectrometry (LC-MS), which has the advantage of simultaneously detecting multiple allergens in foods, is being increasingly used. When managing food allergens at food manufacturing sites, obtaining the same measured values is desirable, regardless of the analytical method used. Therefore, in this study, we focused on the importance of pretreatment steps for LC-MS when examining food allergens in processed foods, which can be difficult to analyze. The ELISA method uses food extracts optimized for analyzing allergens in processed foods. We developed a high-resolution accurate mass spectrometry (HRAM)-LC-MS/MS method using the same food extract used in the ELISA method and an MS sample preparation kit. Multiple food allergen analysis was performed using 1, 5, 10, and 20 ppm of allergen-incurred processed foods. Overall, a strong correlation was observed between the measured values of HRAM-LC-MS/MS and ELISA, demonstrating the applicability of multi-allergen analysis using LC-MS.

The Magnitude and Impact of Food Allergens and the Potential of AI-Based Non-Destructive Testing Methods in Their Detection and Quantification

Reaction to food allergens is on the increase and so is the attending cost on consumers, the food industry, and society at large. According to FDA, the "big-eight" allergens found in foods include wheat (gluten), peanuts, egg, shellfish, milk, tree nuts, fish, and soybeans. Sesame was added to the list in 2023, making the target allergen list nine instead of eight. These allergenic foods are major ingredients in many food products that can cause severe reactions in those allergic to them if found at a dose that can elicit a reaction. Defining the level of contamination that can elicit sensitivity is a work in progress. The first step in preventing an allergic reaction is reliable detection, then an effective quantification method. These are critical steps in keeping contaminated foods out of the supply chain of foods with allergen-free labels. The conventional methods of chemical assay, DNA-PCR, and enzyme protocols like enzyme-linked immunosorbent assay are effective in allergen detection but slow in providing a response. Most of these methods are incapable of quantifying the level of allergen contamination. There are emerging non-destructive methods that combine the power of sensors and machine learning to provide reliable detection and quantification. This review paper highlights some of the critical information on the types of prevalent food allergens, the mechanism of an allergic reaction in humans, the measure of allergenic sensitivity and eliciting doses, and the conventional and emerging AI-based methods of detection and quantification-the merits and downsides of each type.

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.

Standardization of a Mass Spectrometry-Based Workflow for Food Allergen Quantification

In this chapter, the analytical workflow typically used for the development and validation of an analytical method tailored to food allergen detection and quantification is presented. The main steps defining the workflow are herein described and commented with specific notes about the critical issues that can be faced and common solutions to be adopted. References to guidelines and/or recommendation available from official bodies, as well as main papers from international consortia operating on the specific research field, are also reported, whenever possible. As such, this chapter may represent a practical guide to drive method development in the standardization of analytical methods for food allergen detection.

Discovery, verification, and validation of walnut protein marker peptides using LC-MS approaches

A key requirement of liquid chromatography-mass spectrometry (LC-MS)-based allergenic food protein analysis methods is to use protein marker peptides with good analytical performances in LC-MS analysis of commercial processed foods. In this study, we developed a multi-stage walnut protein marker peptide selection strategy involving marker peptide discovery and verification and LC-MS validation of chemically equivalent stable isotope-labeled peptides. This strategy proposed three walnut protein marker peptides, including two new marker peptides. Our LC-MS-based walnut protein analysis method using the three stable isotope-labeled peptides showed acceptable linearity (R2 >0.99), matrix effects (coefficient of variation <±15%), sensitivity (limit of detection >0.3 pg/μL, limit of quantification >0.8 pg/μL), recovery (85.1-103.4%), accuracy, and precision (coefficient of variation <10%). In conclusion, our multi-stage marker peptide selection strategy effectively selects specific protein marker peptides for sensitive detection and absolute quantification of walnut proteins in LC-MS analysis of commercial processed foods.

Food allergen analysis: A review of current gaps and the potential to fill them by matrix-assisted laser desorption/ionization

Food allergy remains a public health, business, and regulatory challenge. Risk analysis (RA) and risk management (RM) of food allergens are of great importance and analysis for food allergens is necessary for both. The current workhorse techniques for allergen analysis (enzyme linked immunosorbent assay [ELISA] and real-time polymerase chain reaction) exhibit recognized challenges including variable and antibody specific responses and detection of species DNA rather than allergen protein, respectively. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) enables protein identification, with potential for multiplex analysis and traceability to the System of International units (SI), aiding global measurement standardization. In this review, recent literature has been systematically reviewed to assess progress in LC-MS/MS and define the potential and benefits of matrix-assisted laser desorption/ionization-time-of-flight MS (MALDI-ToF-MS) technology for allergen analysis. MALDI-ToF-MS of initially intact protein is already applied to verify in silico-derived peptide sequences for LC-MS/MS analysis. We describe the origins of MALDI and its future perspectives, including affinity bead-assisted assays coupled to MALDI. Based on the proliferation of reliable and reproducible MALDI-based clinical applications, the technique should emulate the detection capability (sensitivity) of established allergen detection techniques, whilst reducing technical support and having equivalent multiplexing potential to competing techniques, for example, LC-MS/MS and ELISA. Although unlikely to offer inherent SI traceability, MALDI-based allergen analysis will complement existing MS approaches for allergens. Affinity bead-MALDI appears capable of higher throughput at lower cost per sample than almost any existing technique, enabling repeated sub-sampling as a way to reduce representative sampling issues.

Development of a simple and reliable LC-MS/MS method to simultaneously detect walnut and almond as specified in food allergen labelling regulations in processed foods

We developed a simple and reliable analytical method using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) to simultaneously detect walnut and almond as specified in regulations for food allergen labelling in processed foods. Five specific target peptides derived from walnut 2S albumin and 7S globulin and three target peptides from almond 11S globulin were selected by analysing several varieties of walnut and almond, eight kinds of other nuts, and ten kinds of major allergen ingredients or cereals. The limit of detection for the walnut 2S albumin peptide GEEMEEMVQSAR (m/z 698.3 [precursor] > 316.1 [product]) was 0.22 ± 0.02 μg/g, and that for almond 11S globulin peptide GNLDFVQPPR (m/z 571.8 [precursor] > 369.2 [product]) was 0.08 ± 0.02 μg/g when extracted walnut and almond protein were spiked into butter cookie chocolate ice cream. These peptides had good linearity (R2 > 0.999) for each calibration curve with a range of 0.1-50 μg/mL protein concentration in the sample solutions, and sufficient recovery rates (90.4-101.5%) from the spiked samples. The developed analytical approach is applicable to a wide variety of processed foods for food allergen labelling.

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.

Development of incurred chocolate bars and broth powder with six fully characterised food allergens as test materials for food allergen analysis

The design and production of incurred test materials are critical for the development and validation of methods for food allergen analysis. This is because production and processing conditions, together with the food matrix, can modify allergens affecting their structure, extractability and detectability. For the ThRAll project, which aims to develop a mass spectrometry-based reference method for the simultaneous accurate quantification of six allergenic ingredients in two hard to analyse matrices. Two highly processed matrices, chocolate bars and broth powder, were selected to incur with six allergenic ingredients (egg, milk, peanut, soy, hazelnut and almond) at 2, 4, 10 and 40 mg total allergenic protein/kg food matrix using a pilot-scale food manufacturing plant. The allergenic activity of the ingredients incurred was verified using food-allergic patient serum/plasma IgE, the homogeneity of the incurred matrices verified and their stability at 4 °C assessed over at least 30-month storage using appropriate enzyme-linked immunosorbent assays (ELISA). Allergens were found at all levels from the chocolate bar and were homogenously distributed, apart from peanut and soy which could only be determined above 4 mg total allergenic ingredient protein/kg. The homogeneity assessment was restricted to analysis of soy, milk and peanut for the broth powder but nevertheless demonstrated that the allergens were homogeneously distributed. All the allergens tested were found to be stable in the incurred matrices for at least 30 months demonstrating they are suitable for method development.

Selecting processing robust markers using high resolution mass spectrometry for the detection of milk in food products

BACKGROUND

Cow's milk allergy is one of the most reported food allergies in Europe. To help patients suffering from food allergies it is important to be able to detect milk in different foods. An analytical method that is gaining interest in the field of allergen detection is Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry, where the analyte is a target peptide. When these peptide biomarkers are selected the effect of food processing should be taken into account to allow a robust detection method.

OBJECTIVE

This works aims at identifying such processing stable peptide markers for milk for the Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry based detection of food allergens in different food products.

METHODS

Milk-incurred food materials that underwent several processing techniques were produced. This was followed by establishing tryptic peptide profiles from each matrix using Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry .

RESULT

A careful comparison of peptide profiles/intensities and the use of specific exclusion criteria resulted in the selection of 8 peptide biomarkers suitable for application in Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry based milk detection methods. One of these markers is a α-lactalbumin specific peptide, which has been determined to be stable in different incurred materials for the first time.

CONCLUSION

To our knowledge, this is the first systematic and experimentally based approach for the selection of suitable milk peptide biomarkers robust towards multiple, often applied food processing techniques for milk. Ensuring the exact knowledge of the food processing circumstances by starting from well-defined raw material and using fully controlled settings to produce incurred test material allowed the construction of a peptide database with robust markers. These robust markers can be used for the development of a robust detection method for milk in different food matrices.

Food labeling issues for severe food allergic patients

Food allergy carries high importance and responsibility, affecting an estimated 220 million people worldwide. It is a frequent cause of food-induced anaphylaxis, a life-threatening condition requiring a toll of about one death per 50 million people a year worldwide. In order to help patients to identify allergenic foods and thus avoid anaphylactic reactions, 66 countries over the 5 continents require by law that allergenic ingredients must be declared when used in prepackaged foods. Unfortunately, the mandatory allergen list is not uniform, but varies among different countries. The widespread adoption of Precautionary Allergen Labeling (PAL) results in a proliferation of unregulated PALs with different informative statements. In this situation, the need of a scientific consensus on the definition of food allergy and the identification of a tolerable risk with routinely used detection assays, considering not only the eliciting dose but also the food source, is urgent. The aim of this manuscript is: 1) to draw a picture of the global situation in terms of PALs, and 2) to highlight new approaches that could aid in tackling the problem of regulating the labeling of allergens. These include the Voluntary Incidental Trace Allergen Labelling (VITAL) system, which intersects reference doses and labelling decisions, and a direct quantification of trace amounts of allergens at lower limit of detection (LOD) levels in the food itself through proteomics. We here highlight how, although with some limitations, the steady advances in proteomic approaches possess higher sensitivity than the recommended VITAL reference doses, allowing the identification of allergens at much lower LOD levels than VITAL. Considering that each assay used to detect allergen in food products carries method-specific issues, a more comprehensive and harmonized approach implementing both quantitative and qualitative methods could help overcoming the risk stratification approach and the overuse of PALs, offering promise as the field moves forward towards improving consumers' quality of life.