Development of a sandwich ELISA-type system for the detection and quantification of hazelnut in model chocolates

Development and validation of sensitive and rapid CRISPR/Cas12-based PCR method to detect hazelnut in unlabeled products

Hazelnut, one of the most popular tree nuts, is widely found in processed food and even very small amounts can trigger severe allergic reactions in susceptible people. Herein, we developed a sensitive and rapid method based on CRISPR and qPCR capable of detecting low-abundance hazelnut in processed food. The assay, known as CRISPR-based nucleic acid test method (Crinac) can detect 1 % of hazelnut in a mixture and allows the species to be identified in a complex processed sample. The detection process can be completed within 60 min. Contributed to amplification via PCR and CRISPR/Cas12a, enables end-fluorescence measurement for the quantification of hazelnut, thus reducing assay time and eliminating the need for costly real-time fluorescence PCR instruments. The assay based on CRISPR/Cas12 and PCR has potential as a sensitive and reliable analytical tool for the detection of food authenticity.

1D-, 2D-Gel Electrophoresis, Immunoblotting, and Enzyme-Linked Immunosorbent Assay (ELISA) for the Study of Food Allergens

Protein-based methods have been fundamental for the study of food allergens, not only from a mechanistic and diagnostic point of view, but especially with respect to allergen management and food safety. In this chapter, four individual protocols are suggested, relying on one-dimensional, two-dimensional gel electrophoresis, immunoblotting, and enzyme-linked immunosorbent assay (ELISA). The particularities of the proposed protocols are focused on previous research targeting specific allergenic foods, with cow's milk proteins as case studies. Data on the importance of protein extraction and the use of different animal-raised antibodies and/or sera of food-allergic patients are also critically discussed within method development and optimization. The protocols herein described are successful examples applied to the study of cow's milk allergens in complex matrices, although they can be easily developed and optimized for any food allergen or allergenic food.

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.

Molecularly imprinted polymer as a synthetic antibody for the biorecognition of hazelnut Cor a 14-allergen

Artificial receptors that mimic their natural biological counterparts have several advantages, such as lower production costs and increased shelf-life stability/versatility, while overcoming the ethical issues related to raising antibodies in animals. In this work, the proposed tailor-made molecularly imprinted polymer (MIP)-allergen receptors aimed at substituting or even transcending the performance of biological antibodies. For this purpose, a MIP was proposed as an artificial antibody for the recognition of hazelnut Cor a 14-allergen. The target protein was grafted onto the conducting polypyrrole receptor film using gold screen-printed electrodes (Au-SPE). The electrochemical assessment presented a linear response for the dynamic range of 100 fg mL^-1-1 μg mL^-1 and a LOD of 24.5 fg mL^-1, as determined by square wave voltammetry from the calibration curves prepared with standards diluted in phosphate buffer. Surface plasmon resonance (SPR) was used as a secondary transducer to evaluate the performance of the Cor a 14-MIP sensor, enabling a linear dynamic range of 100 fg mL^-1- 0.1 μg mL^-1 and a LOD of 18.1 fg mL^-1. The selectivity of the tailored-made Cor a 14-MIP was tested against potentially cross-reactive plant/animal species based on the rebinding affinity (Freundlich isotherm-K_F) of homologues/similar proteins, being further compared with custom-made polyclonal anti-Cor a 14 IgG immunosensor. Results evidenced that the MIP mimics the biorecognition of biological antibodies, presenting higher selectivity (only minor cross-reactivity towards walnut and Brazil nut 2S albumins) than the Cor a 14/anti-Cor a 14 IgG immunosensor. The application of electrochemical Cor a 14-MIP sensor to model mixtures of hazelnut in pasta enabled quantifying hazelnut down to 1 mg kg^-1 (corresponding to 0.16 mg kg^-1 of hazelnut protein in the matrix). To the best of our knowledge, Cor a 14-MIP is the first sensor based on an artificial/synthetic biorecognition platform for the specific detection of hazelnut allergens, while presenting high-performance parameters with demonstrated application in food safety management.

An immunochromatographic assay utilizing magnetic nanoparticles to detect major peanut allergen Ara h 1 in processed foods

This study describes an immunomagnetic nanoparticle (IMNP)-based lateral flow assay (LFA) for detecting the major peanut allergen Ara h 1. We developed a clearly specific method in identifying peanut from ten other seeds and nuts, and a good visual limit of detection (vLOD) of 0.01 μg/mL Ara h 1 in PBS. PBS that contains 1 M NaCl and 2% Tween 20 was determined to be the optimal extraction buffer for isolating Ara h 1 from cookie, milk and chocolate with vLOD values of 0.5 μg/g, 0.5 μg/mL, and 1 μg/g, respectively. Forty two processed foods were simultaneously analyzed using this method and an AOAC-approved ELISA kit. The specificity and sensitivity of this assay were thus determined to be 100 and 95%, respectively. This new IMNP-based LFA has potential as a rapid tool for screening processed foods for Ara h 1 residues.

Novel monoclonal antibody-sandwich immunochromatographic assay based on Fe3O4/Au nanoparticles for rapid detection of fish allergen parvalbumin

In this study, a rapid sandwich immunochromatographic assay (ICA) was developed to detect parvalbumin (PV). Firstly, two optimum primary monoclonal antibody (mAb) against PV had been screened out: mAb1 was used as the capture antibody, and mAb2 conjugated to Fe₃O₄/Au nanoparticles (Fe₃O₄/AuNPs) that served as a detection reagent. Using this pair of mAbs, a sandwich ICA strip based on Fe₃O₄/AuNPs was developed. The results showed that the color intensity of test line positively correlated with the PV concentration in the standard or spiked sample. The limit of detection for qualitative (LOD) and quantitative detection (LOQ) were 2 ng/mL and 0.691 ng/mL, respectively. Besides, the detection time of this ICA strip was within 15 min. The recovery rates ranged from 104.0% to 117.4%, within an acceptable level (80-120%). Moreover, the developed assay also showed high cross reaction in different fish species. These results demonstrated that the established test strip has the potential to be used as a rapid screening tool for large scale determination of PV in foodstuffs.

Highly Sensitive Detection of Bovine β-Lactoglobulin with Wide Linear Dynamic Range Based on Platinum Nanoparticles Probe

Cow's milk allergy is one of the most frequent and severe IgE-induced food allergies for children, demanding sensitive analytical methods, and β-lactoglobulin (BLG) can be as an important biomarker for detection of milk protein. In this study, a highly sensitive sandwich enzyme-linked immunosorbent assay (sELISA) based on a specific polyclonal antibody against human IgE linear epitopes of BLG and an anti-BLG polyclonal antibody-platinum nanoparticles probe was described for detection of BLG. This sELISA exhibited an ultrawide linear range of 0.49-1.6 × 10⁴ ng/mL, covering more than four orders of magnitude. The limit of detection was 0.12 ng/mL, which was 16-fold lower than that using traditional sELISA with the same antibodies. Furthermore, the proposed approach showed high recoveries (93.53%-111.95%) and low coefficient of variation (1.49%-12.50%) after analysis of samples fortified with BLG. The presence of allergenic BLG residues also could be detected in partially hydrolyzed infant formulas. These results, in comparison with conventional and commercial BLG detection sELISAs, highlight that this proposed sELISA could be a reliable and user-friendly tool to monitor trace amounts of BLG and its potentially allergenic residues in foods.

Colour-encoded lateral flow immunoassay for the simultaneous detection of aflatoxin B1 and type-B fumonisins in a single Test line

A multiplex Lateral Flow Immunoassay was developed based on the use of a single Test line and multicolour gold nanoparticles (GNPs) as signal reporters. Red and blue GNPs were linked to antibodies directed towards two different analytes and included in a typical lateral flow immunoassay configuration, in which the Test line was formed by the mixture of two antigens. As a result of the immunoreactions occurring at the Test zone, diverse combinations of red and blue GNPs labels were captured. Therefore, the Test line assumed different colours depending on which - and how much - analyte is present in the sample. The multiplexing capability of the 'colour-encoded assay' is illustrated by the simultaneous detection of aflatoxin B1 (AFB1) and type-B fumonisins (FMs) in wheat and food products that made with wheat. Reproducible detection of AFB1 and FMs contamination in raw and processed food was achieved with visual cut-off levels at 1 ng mL^-1 and 50 ng mL^-1, respectively. The contaminant was identified based on the colour of the label according with a specific colour code. Furthermore, strips images were acquired by means of a common smartphone and analysed through RGB data analysis providing semi-quantitative detection of the two mycotoxins.

MRM3-based LC-MS multi-method for the detection and quantification of nut allergens

Food allergies have become a global challenge to food safety in industrialized countries in recent years. With governmental monitoring and legislation moving towards the establishment of threshold allergen doses, there is a need for sensitive and quantitative analytical methods for the determination of allergenic food contaminants. Targeted proteomics employing liquid chromatography-mass spectrometry (LC-MS) has emerged as a promising technique that offers increased specificity and reproducibility compared to antibody and DNA-based technologies. As the detection of trace levels of allergenic food contaminants also demands excellent sensitivity, we aimed to significantly increase the analytical performance of LC-MS by utilizing multiple reaction monitoring cubed (MRM³) technology. Following a bottom-up proteomics approach, including a straightforward sample preparation process, 38 MRM³ experiments specific to 18 proteotypic peptides were developed and optimized. This permitted the highly specific identification of peanut, almond, cashew, hazelnut, pistachio, and walnut. The analytical performance of the method was assessed for three relevant food matrices with different chemical compositions. Limits of detection were around 1 μg/g or below in fortified matrix samples, not accounting for the effects of food processing. Compared to an MRM-based approach, the MRM³-based method showed an increase in sensitivity of up to 30-fold. Regression analysis demonstrated high linearity of the MRM³ signal in spiked matrix samples together with robust intersample reproducibility, confirming that the method is highly applicable for quantitative purposes. To the best of our knowledge, we describe here the most sensitive LC-MS multi-method for food allergen detection thus far. In addition, this is the first study that systematically compares MRM³ with MRM for the analysis of complex foods. Graphical abstract Allergen detection by MRM³.

Bioanalytical methods for food allergy diagnosis, allergen detection and new allergen discovery

For effective monitoring and prevention of the food allergy, one of the emerging health problems nowadays, existing diagnostic procedures and allergen detection techniques are constantly improved. Meanwhile, new methods are also developed, and more and more putative allergens are discovered. This review describes traditional methods and summarizes recent advances in the fast evolving field of the in vitro food allergy diagnosis, allergen detection in food products and discovery of the new allergenic molecules. A special attention is paid to the new diagnostic methods under laboratory development like various immuno- and aptamer-based assays, including immunoaffinity capillary electrophoresis. The latter technique shows the importance of MS application not only for the allergen detection but also for the allergy diagnosis.

Comprehensive peptide marker identification for the detection of multiple nut allergens using a non-targeted LC-HRMS multi-method

Food allergies have emerged as a global problem over the last few decades; therefore, reliable and sensitive analytical methods to ensure food safety for allergic consumers are required. The application of mass spectrometry is of growing interest in this field and several procedures based on low resolution tandem mass spectrometry using single tryptic peptides as analytical targets have recently been described. However, a comprehensive survey of marker peptides for the development of multi-methods is still missing, as is a consensus guide to marker identification. In this study, we therefore report a consistent approach to the development of liquid chromatography-mass spectrometry (LC-MS) multi-screening methods for the detection of allergens in food matrices. Proteotypic peptides were identified by a shotgun proteomics approach and verified through a thorough investigation of specificity and sensitivity. On the basis of this procedure, we identified 44 suitable tryptic marker peptides from six allergenic nut species and developed the first analytical LC-MS method for the detection of trace nut contaminations in processed foods using high resolution mass spectrometry (HRMS). The analysis of spiked matrix samples gave limits of detection (LODs) below 10 μg/g for several nuts; these LODs are comparable with routinely used methods such as ELISA and PCR. Notably, the HRMS approach can be used in an untargeted fashion to identify multiple allergens also retrospectively. In conclusion, we present here the so far largest consensus set of analytical markers from nut allergens and to the best of our knowledge the first multi-allergen method based on LC-HRMS.