Detection Of Food Allergens Research Articles

Detection and Quantification of Allergens in Foods and Minimum Eliciting Doses in Food-Allergic Individuals (ThRAll)

Abstract Risk-based approaches to managing allergens in foods are being developed by the food industry and regulatory authorities to support food-allergic consumers to avoid ingestion of their problem food, especially in relation to the traces of unintended allergens. The application of such approaches requires access to good quality data from clinical studies to support identification of levels of allergens in foods that are generally safe for most food-allergic consumers as well as analytical tools that are able to quantify allergenic food protein. The ThRAll project aims to support the application of risk-based approaches to food-allergen management in two ways. First, a harmonized quantitative MS-based prototype reference method will be developed for the detection of multiple food allergens in standardized incurred food matrices. This will be undertaken for cow’s milk, hen’s egg, peanut, soybean, hazelnut, and almond incurred into two highly processed food matrices, chocolate and broth powder. This activity is complemented by a second objective to support the development and curation of data on oral food challenges, which are used to define thresholds and minimum eliciting doses. This will be achieved through the development of common protocols for collection and curation of data that will be applied to allergenic foods for which there are currently data gaps.

Selection of Tree Nut Allergen Peptide Markers: A Need for Improved Protein Sequence Databases

Abstract Background: To effectively safeguard the food-allergic population and support compliance with food-labeling regulations, the food industry and regulatory agencies require reliable methods for food allergen detection and quantification. MS-based detection of food allergens relies on the systematic identification of robust and selective target peptide markers. The selection of proteotypic peptide markers, however, relies on the availability of high-quality protein sequence information, a bottleneck for the analysis of many plant-based proteomes. Method: In this work, data were compiled for reference tree nut ingredients and evaluated using a parsimony-driven global proteomics workflow. Results: The utility of supplementing existing incomplete protein sequence databases with translated genomic sequencing data was evaluated for English walnut and provided enhanced selection of candidate peptide markers and differentiation between closely related species. Highlights: Future improvements of protein databases and release of genomics-derived sequences are expected to facilitate the development of robust and harmonized LC–tandem MS-based methods for food allergen detection.

Screening of Nanobody Specific for Peanut Major Allergen Ara h 3 by Phage Display.

Peanut allergy is a major health problem worldwide. Detection of food allergens is a critical aspect of food safety. The VHH domain of single chain antibody from camelids, also known as nanobody (Nb), showed its advantages in the development of biosensors because of its high stability, small molecular size, and ease of production. However, no nanobody specific to peanut allergens has been developed. In this study, we constructed a library with random triplets (NNK) in its CDR regions of a camel nanobody backbone. We screened the library with peanut allergy Ara h 3 and obtained several candidate nanobodies. One of the promising nanobodies, Nb16 was further biochemical characterization by gel filtration, isothermal titration calorimetry (ITC), cocrystallization, and Western blot in terms of its interaction with Ara h 3. Nb16 specifically binds to peanut major allergen Ara h 3 with a dissociation constant of 400 nM. Furthermore, we obtained the Ara h 3-Nb16 complex crystals. Structure analysis shows the packing mode is completely different between the Ara h 3-Nb16 complex crystal and the native Ara h 3 crystal. Structural determination of Ara h 3-Nb16 will provide the necessary information to understand the allergenicity of this important peanut allergen. The nanobody Nb16 may have application in the development of biosensors for peanut allergen detection.

Smartphone-based biosensors for portable food evaluation

Rapid and accurate analysis of food draws considerable attention in the modern pace of the world due to the close relationship between human health and food safety. Traditional detection technologies for food evaluation are often restricted by high cost, lengthy time, bulky instruments and trained personnel. The marriage of biosensors with smartphones enables the development of powerful analysis platforms for food evaluation including detection of food contaminants, toxins, pathogens, allergens and nutrition. Here, we provide an overview of recent developments on smartphone-based biosensors for portable food evaluation. Owing to operability, connectivity, portability and built-in sensors, smartphones have become ideal control, interaction and analysis tools in the on-site sensing systems. Fusion of smartphones with different kinds of sensitive and selective biosensors enables to develop portable and user-friendly analytical devices. In addition to introducing technical principles, detection methods and selected applications in food science, challenges and future perspectives for smartphone-based biosensors are also discussed.

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.

Mass spectrometry detection of protein allergenic additives in emulsion-type pork sausages

The application of various functional protein additives in the meat industry is still increasing. Soy, milk and egg white proteins are applied to various types of meat product to improve their structural properties or as good substitutes for meat and fat components. It is common practice to add these preparations to reduce production costs. New methods are needed for reliable detection of small amounts of these additives in complex and processed food matrices regarding the potential for food adulteration and allergen detection. In this work, a mass spectrometry method was implemented for the detection of soy (Glycine max), milk (Bos taurus) and egg white (Gallus gallus) in smoked and cooked pork sausages. Specific peptide markers for glycinin and β-conglycinin, α-S1-casein, β-lactoglobulin, ovotransferrin and lysozyme C were monitored in the sausage samples. The proteins were detectable at the low concentration of 0.53% (w/w) of a given additive, which corresponds to a limit of detection of 0.14% for milk proteins and 0.45% for soy and egg white proteins in the final meat product. The results were validated by the use of synthetic peptides labelled with stable isotopes. Considering the universal nature of the presented peptide markers, the method has the potential to be implemented for other complex and processed foodstuffs for authenticity purposes.

Development of simple and rapid food allergen detection method and its use for on-site analysis

Development of simple and rapid food allergen detection method and its use for on-site analysis

German Government Official Methods Board Points the Way Forward: Launch of a New Working Group for Mass Spectrometry for Protein Analysis to Detect Food Fraud and Food Allergens.

The detection of food fraud and undeclared food allergens is one of the major challenges for competent authorities. Because adulterations are continuously adapted to the methods used to uncover them, the accomplishment of this task has become increasingly difficult over time. In recent years, various new promising methods for the detection of multiple food adulterants and multiple food allergens have been developed. Some of them utilize LC-MS to identify specific marker peptides. However, these methods have yet to be validated and standardized. For this reason, the German officials have established a working group with the objective of validating methods through multilaboratory validation studies. The experts of the working group also aim for the first time to standardize validated methods and to develop general validation criteria. This manuscript will highlight the current work of the group. For this purpose, an overview is given on the principles and applications of the new mass spectrometric methods. Moreover, requirements and the present work of other institutions regarding method validation are described.

Detection and Quantification of Allergens in Foods and Minimum Eliciting Doses in Food-Allergic Individuals (ThRAll).

Risk-based approaches to managing allergens in foods are being developed by the food industry and regulatory authorities to support food-allergic consumers to avoid ingestion of their problem food, especially in relation to the traces of unintended allergens. The application of such approaches requires access to good quality data from clinical studies to support identification of levels of allergens in foods that are generally safe for most food-allergic consumers as well as analytical tools that are able to quantify allergenic food protein. The ThRAll project aims to support the application of risk-based approaches to food-allergen management in two ways. First, a harmonized quantitative MS-based prototype reference method will be developed for the detection of multiple food allergens in standardized incurred food matrices. This will be undertaken for cow's milk, hen's egg, peanut, soybean, hazelnut, and almond incurred into two highly processed food matrices, chocolate and broth powder. This activity is complemented by a second objective to support the development and curation of data on oral food challenges, which are used to define thresholds and minimum eliciting doses. This will be achieved through the development of common protocols for collection and curation of data that will be applied to allergenic foods for which there are currently data gaps.

Selection of Tree Nut Allergen Peptide Markers: A Need for Improved Protein Sequence Databases.

Background: To effectively safeguard the food-allergic population and support compliance with food-labeling regulations, the food industry and regulatory agencies require reliable methods for food allergen detection and quantification. MS-based detection of food allergens relies on the systematic identification of robust and selective target peptide markers. The selection of proteotypic peptide markers, however, relies on the availability of high-quality protein sequence information, a bottleneck for the analysis of many plant-based proteomes. Method: In this work, data were compiled for reference tree nut ingredients and evaluated using a parsimony-driven global proteomics workflow. Results: The utility of supplementing existing incomplete protein sequence databases with translated genomic sequencing data was evaluated for English walnut and provided enhanced selection of candidate peptide markers and differentiation between closely related species. Highlights: Future improvements of protein databases and release of genomics-derived sequences are expected to facilitate the development of robust and harmonized LC-tandem MS-based methods for food allergen detection.

Excretion of Dietary Cow's Milk Derived Peptides Into Breast Milk.

Nanoflow-HPLC-tandem mass spectrometry (MS/MS) was used to analyze the peptide fraction of breast milk samples collected from a single non-atopic donor on different days (10 samples) after receiving an oral load of cow's milk (by drinking 200 mL of bovine milk). In addition, breast milk was sampled from the same lactating mother over a 6-h period at five time points after drinking cow's milk. We aimed to trace the intra-individual variability and to define a time profile of the excretion of dietary peptides into breast milk. Overall, 21 peptides exclusively originating from both bovine caseins and whey proteins with no match within the human milk proteome were identified in the breast milk samples. These peptides were missing in the breast milk obtained from the mother after a prolonged milk- and dairy-free diet (three samples). The time course of cow's milk-derived β-Lg f(125–135) and β-casein f(81–92) in breast milk was determined from the MS ion intensity of the peptide signals. No intact cow's milk gene products were detected by HPLC-MS/MS analysis and Western blotting with anti-β-Lg antibody, but dot-blot analysis confirmed the occurrence of β-Lg fragments in the enriched peptide fraction of breast milk. These data suggest shifting the analytical perspective for the detection of dietary food allergens in breast milk from intact proteins to digested peptide fragments. The possible sensitization and elicitation potential or the tolerogenic properties of such low amounts of dietary peptides for the breastfed newborns remain to be explored.

A novel electrochemical mast cell-based paper biosensor for the rapid detection of milk allergen casein

Developing low-cost, portable and simple analysis tools is of vital importance for food safety point-of-care testing. Therefore, herein, a new low-cost, simple to fabricate, disposable, electrochemical mast cell-based paper sensor is proposed and developed to sensitively determine the major milk allergen casein. Then, a graphene (GN)/carbon nanofiber (CN)/ Gelatin methacryloyl (GelMA) composite material with high conductivity and good biocompatibility was modified on the cell-based paper sensor to improve the electrical conductivity and provide a sensing recognition interface for the immobilization of rat basophilic leukemia (RBL-2H3) mast cells. The cyclic voltammetry and differential pulse voltammetry measurement of the mast cells in the paper sensor revealed an irreversible anodic peak, whose peak current is proportional to the number of cells in the range from 1 × 102 to 1 × 108 cells/mL. For the milk allergen detection tests, mast cells exposed to the casein caused a significant reduction in the current signal, displaying an inverse dose-dependent relationship. The developed cell sensor exhibited a range of linearity between 1 × 10−7 and 1 × 10−6 g/mL of casein with a detection limit of 3.2 × 10−8 g/mL and a great reproducibility and selectivity. The electrochemical responses obtained using the cell-based paper sensor were well consistent with the conventional detection assay, with good stability and reproducibility. Therefore, a simple and novel electrochemical method for food allergens detection was developed, demonstrating its potential application in the food safety determination and evaluation.

Single-Laboratory Validation of the Multiplex xMAP Food Allergen Detection Assay with Incurred Food Samples.

An xMAP Food Allergen Detection Assay (xMAP FADA) was developed to meet analytical needs when responding to complaints by individuals with multiple food allergies and to address potential ambiguities associated with cross-reactive proteins. A single-laboratory validation (SLV) was conducted to examine the reliability of the xMAP FADA to detect 15 analytes individually or as part of a mixture at more than six concentrations in four foods. The xMAP FADA reliably detected the analytes despite the incurred dark chocolate and incurred baked muffins displaying recoveries of 10-20% and <60%, respectively. The high reliability for recoveries less than 60% in part reflects the statistical strength of the design of the xMAP FADA. Only crustacean, egg, and milk incurred in dark chocolate were not reliably detected using the PBST-buffered-detergent protocol. Following the reduced-denatured protocol, no problems were encountered in the detection of milk, although egg did not display a dynamic response in dark chocolate. The ruggedness of the xMAP FADA was ascertained by the ability of novice analysts to detect food allergens in baked rice cookies. Despite one analyst losing >80% of the beads and the count for one bead set dropping to seven, the assay displayed only a decrease in precision (increased standard deviations) and a change in the ratios between complementary antibody pairs.

Specific and sensitive ELISA for measurement of IgE-binding variations of milk allergen β-lactoglobulin in processed foods

Immunochemical detection of food allergens is usually based on the use of polyclonal or monoclonal immunoglobulins G (IgG) antibodies. However, due to differences in epitopes recognition between IgG and IgE, an epitope modification during food processing can potentially alter allergenicity and detection in such different way. For that reason, the use of traditional immunological methods to anticipate or study the protein allergenicity is not recommended.The objective of this work was to develop a standardized competitive ELISA, based on recombinant IgE antibodies to β-lactoglobulin (β-lg), to reveal and to measure changes in β-lg immunoreactivity provoked by technological processes in foods containing this milk protein.As a result, a sensitive immunochemical method (Limit of Detection, LOD < 0.2 μg mL−1) has been developed for β-lg recognition. Also, this technique has been confirmed to detect modifications in β-lg-IgE binding after food processing (thermal treatment) in a similar way to those results obtained with allergic patients in previous works. Consequently, data obtained with this assay could be used as a preliminary test to predict in vitro β-lg allergenic behavior in allergenicity studies in processed foods.

Silver and gold nanoparticles as multi-chromatic lateral flow assay probes for the detection of food allergens.

In this study, we report the simultaneous use of gold and silver nanoparticles to set a multicolor multiplex lateral flow immunoassay (xLFIA). Silver nanoparticles (AgNPs), spherical in shape and characterized by a brilliant yellow color, were obtained by a new viable one-step synthetic protocol. AgNPs were stable over time and acceptably robust to conditions used for fabricating LFIA devices. These AgNPs were employed as a colorimetric probe in combination with two different kinds of gold nanoparticles (AuNPs) to set a visual xLFIA for detecting allergens. Surface plasmon resonance peaks of probes (AgNPs, spherical and desert rose-like AuNPs) were centered at 420, 525, and 620nm, respectively. Therefore, the xLFIA output was easily interpreted through a "yellow magenta cyan (YMC)" color code. The prospect of the YMC xLFIA was demonstrated by simultaneously detecting three major allergens in bakery products. Antibodies directed towards casein, ovalbumin, and hazelnut allergenic proteins were individually adsorbed onto metal nanoparticles to produce three differently colored specific probes. These were inserted in a LFIA comprising three lines, each responsive for one allergen. The trichromatic xLFIA was able to detect allergenic proteins at levels as low as 0.1mg/l and enabled the easy identification of the allergens in commercial biscuits based on the color of the probes. Graphical Abstract.

Development and Validation of a Surface Plasmon Resonance Biosensor for Specific Detection of Porcine Serum Albumin in Food.

Food allergies are a potential food safety and public health concern worldwide. To assure the safety of people who experience allergic reactions, it is necessary to establish effective and reliable methods for rapid detection of food allergens. This paper reports an innovative method for the rapid detection and analysis of porcine serum albumin (PSA), known as a major allergen in pork, based on a surface plasmon resonance (SPR) biosensor. The antibodies known to have a high bioactivity against PSA were verified by competitive indirect-ELISA and then immobilized on the SPR sensor surface, thus allowing them to capture PSA. The developed SPR demonstrated a linear range from 1.0 to 450ng/mL for the measurement of PSA with a detection limit of 19.81ng/mL. Within-day RSD (1.97-4.02%) and between-day RSD (1.88-4.15%) were no more than 5%. The SPR was evaluated for analysis of six commercial food samples and showed almost perfect agreement between the results obtained by ELISA test kits without significant differences (P > 0.05). Therefore, this assay permits accurate, specific, and sensitive detection of PSA in pork and pork products.

Matrix effect on food allergen detection – A case study of fish parvalbumin

Two fish parvalbumin models were established to study relationships among matrix effect, extractability, and thermostability during in vitro immunodetection using two parvalbumin-specific monoclonal antibodies (3E1 and PARV19). Our results illustrated that matrix-induced thermal instability of parvalbumin was due mainly to physical (hydrophobic effect) and chemical (thiol-disulfide interchange) interactions. The addition of sodium dodecyl sulfate (SDS, surfactant), β-mercaptoethanol (reducing agent) or ethylenediaminetetraacetic acid (EDTA, metal chelator) during sample preparation could not only increase the extractability of parvalbumin but also enhanced its immunodetection. Our findings demonstrated excess EDTA completely chelated Ca2+ in parvalbumin and rendered it undetectable using PARV19 (a Ca2+-dependent antibody). Overall, our resulted showed that matrix effect on in vitro analyte quantification cannot be underestimated. Any false negative or positive results could lead to severe or life-threatening allergic reactions.

Characterization and Detection of Food Allergens Using High-Resolution Mass Spectrometry: Current Status and Future Perspective.

Allergic reactions to food are among the major food safety concerns in industrialized countries, and it is estimated that approximately 5% of the population suffers from immunoglobulin-E-mediated food allergy. High-resolution mass spectrometry has become one of the most important techniques for the molecular characterization of allergens, including structural modification, degradation in the gastrointestinal environment, or identification of suitable marker peptides for the development of novel analytical approaches, in the past decade. This perspective aims to briefly summarize the current situation and discuss future developments.

Cross-reactivity by botanicals used in dietary supplements and spices using the multiplex xMAP food allergen detection assay (xMAP FADA).

Food allergies affect some 15 million Americans. The only treatment for food allergies is a strict avoidance diet. To help ensure the reliability of food labels, analytical methods are employed; the most common being enzyme-linked immunosorbent assays (ELISAs). However, the commonly employed ELISAs are single analyte-specific and cannot distinguish between false positives due to cross-reactive homologous proteins; making the method of questionable utility for regulatory purposes when analyzing for unknown or multiple food allergens. Also, should the need arise to detect additional analytes, extensive research must be undertaken to develop new ELISAs. To address these and other limitations, a multiplex immunoassay, the xMAP® food allergen detection assay (xMAP FADA), was developed using 30 different antibodies against 14 different food allergens plus gluten. Besides incorporating two antibodies for the detection of most analytes, the xMAP FADA also relies on two different extraction protocols; providing multiple confirmatory end-points. Using the xMAP FADA, the cross-reactivities of 45 botanicals used in dietary supplements and spices commercially sold in the USA were assessed. Only a few displayed cross-reactivities with the antibodies in the xMAP FADA at levels exceeding 0.0001%. The utility of the xMAP FADA was exemplified by its ability to detect and distinguish between betel nut, saw palmetto, and acai which are in the same family as coconut. Other botanicals examined included allspice, amchur, anise seed, black pepper, caraway seed, cardamom, cayenne red pepper, sesame seed, poppy seed, white pepper, and wheat grass. The combination of direct antibody detection, multi-antibody profiling, high sensitivity, and a modular design made it possible for the xMAP FADA to distinguish between homologous antigens, provide multiple levels of built-in confirmatory analysis, and optimize the bead set cocktail to address specific needs.

A review of thin layer chromatography methods for determination of authenticity of foods and dietary supplements

This paper reviews advances in qualitative and quantitative thin layer chromatography analytical methods published from 2000–2018 for assessing quality, adulteration, and authenticity of foods, beverages, and dietary supplements. Samples covered include animal and butter fats, oils, spices, flavorings, grains, honeys, soft drinks and juices, tea, sweeteners, wine and other alcoholic beverages, and vegetables, which are analyzed for a wide variety of characteristic analytes. It is suggested that TLC methods of the kind cited will continue to be used to complement the LC-MS/MS based peptide analysis methods that are being developed for food allergen detection and food fraud testing.