[Distribution characteristics and results of allergens in patients with allergic rhinitis in Ningxia area]

Objective:To investigate the distribution of allergens in patients with allergic rhinitis （AR） in Ningxia, and provide theoretical data for the prevention and treatment of AR in this region. Methods:A total of 1664 patients diagnosed with AR in the Otorhinolaryngology Head and Neck Surgery Department of Yinchuan First People's Hospital Outpatient Clinic from January 2018 to December 2021 were retrospectively collected. Use the allergen sIgE antibody detection kit （immunoblotting method） to detect inhalation and ingestion allergens in patients.Results: ①Among all AR patients, 1 158 cases were detected positive, resulting in the detection rate was 69.59%; ②The detection rate of inhalation allergen was 65.87%, and the detection rate of ingestion allergen was 19.83%; ③Mugwort was the most sensitive allergen, and 76.32% of the patients having a positive grade ≥3; ④Out of the patients, 294 cases （25.39%） were allergic to only one allergen, 244 cases （21.07%） were allergic to two allergens, and 620 cases （53.54%） were allergic to three or more allergens; ⑤During different seasons, the highest number of positive allergens detected was in the summer, with 968 cases （83.59%）. Mugwort was the main allergen during this season （69.01%）. After the COVID-19 epidemic, the total positive rate of sIgE tests in AR patients decreased compared to before, and the difference was statistically significant （P<0.001）; ⑥Mugwort, dog epithelium, mold combination, egg, peanut, soybean, Marine fish combination and fruit combination all showed statistically significant differences between different gender groups （P<0.05）; ⑦Common ragweed, mugwort, dust mite combination, cockroach, egg, milk, Marine fish combination, shrimp, fruit combination and nut combination all showed statistically significant differences among different age groups （P<0.05）; ⑧There were statistically significant differences in hay dust among different ethnic groups （P<0.05）. Conclusion:Artemisia argyi is the main allergen in Ningxia, and the distribution characteristics of different allergens are influenced by treatment season, the COVID-19 epidemic, gender, age, ethnicity, and other factors, showing certain distribution patterns and rules.

In vitro selection and optimization of high-affinity aptamer for milk allergen α-lactalbumin and its application in dual-mode detection

Milk is one of the most common sources of protein in people’s daily lives, and it is also recognized by the World Health Organization (WHO) as one of the eight categories of food allergies to human beings. α-lactalbumin (α-La) is the main cause of milk allergy. In this study, a single-stranded DNA aptamer with high binding affinity to α-La were selected using systematic evolution of ligands by exponential enrichment (SELEX) method. Compared with the full-length sequence, the binding affinity of the truncated aptamer LA-1t for α-La was increased six times using fluorescence analysis. Circular dichroism (CD) indicated that the secondary structure of LA-1t contained a typical hairpin structure. Through the docking simulation of LA-1t and α-La, these experimental results were further explained theoretically, and the recognition mechanism was explained. Finally, the colorimetric and fluorescence signal of boron nitride quantum dots anchored to porous CeO₂ nanorods (BNQDs/CeO₂) were modulated by FAM-labeled LA-1t to achieve highly selective and sensitive determination of α-La. This dual-mode sensing strategy displayed sensitive recognition for α-La in a linear range of 5–4,000 ng/ml with the LOD was 3.32 ng/ml (colorimetry) and 0.71 ng/ml (fluorescence), respectively. Simultaneously, the colorimetry/fluorescence dual-mode sensing strategy was applied for detecting α-La in spiked real samples and demonstrated good stability and reliability.

Improved Sensitivity of Allergen Detection by Immunoaffinity LC-MS/MS Using Ovalbumin as a Case Study

Food allergies are caused by severe hypersensitivity to specific food allergens such as the egg protein ovalbumin. It is therefore important to test food products for the presence of allergens to protect allergic people from accidental ingestion. For egg detection, ELISA is the only reasonable commercially available test format, although the recognition of target allergens can be affected by food processing, which may lead to false negative results. Current mass spectrometry-based detection methods may overcome this issue, but these approaches are often less sensitive. Here we combined the advantages of antibody-based and MS-based methods by developing an immunoaffinity LC-MS/MS technique to detect the common egg allergen Gal d 2. We investigated the principal functionality of this method with incurred cookie material containing whole egg powder. We found that the new method matched easily the sensitivity of egg specific ELISA tests. Further western blot experiments indicated that this strategy may be unaffected by food processing, providing an important alternative strategy for the detection and quantification of allergens in food.

Development of Multiplex PCR Coupled DNA Chip Technology for Assessment of Endogenous and Exogenous Allergens in GM Soybean

Allergenicity assessment of transgenic plants and foods is important for food safety, labeling regulations, and health protection. The aim of this study was to develop an effective multi-allergen diagnostic approach for transgenic soybean assessment. For this purpose, multiplex polymerase chain reaction (PCR) coupled with DNA chip technology was employed. The study was focused on the herbicide-resistant Roundup Ready soya (RRS) using a set of certified reference materials consisting of 0, 0.1%, 0.5%, and 10% RRS. Technically, the procedure included design of PCR primers and probes; genomic DNA extraction; development of uniplex and multiplex PCR systems; DNA analysis by agarose gel electrophoresis; microarray development, hybridization, and scanning. The use of the asymmetric multiplex PCR method is shown to be very efficient for DNA hybridization with biochip probes. We demonstrate that newly developed fourplex PCR methods coupled with DNA-biochips enable simultaneous identification of three major endogenous allergens, namely, Gly m Bd 28K, Gly m Bd 30K, and lectin, as well as exogenous 5-enolppyruvyl shikimate-phosphate synthase (epsps) expressed in herbicide-resistant roundup ready GMOs. The approach developed in this study can be used for accurate, cheap, and fast testing of food allergens.

Electroanalytical Overview: Electrochemical Sensing Platforms for Food and Drink Safety

Robust, reliable, and affordable analytical techniques are essential for screening and monitoring food and water safety from contaminants, pathogens, and allergens that might be harmful upon consumption. Recent advances in decentralised, miniaturised, and rapid tests for health and environmental monitoring can provide an alternative solution to the classic laboratory-based analytical techniques currently utilised. Electrochemical biosensors offer a promising option as portable sensing platforms to expedite the transition from laboratory benchtop to on-site analysis. A plethora of electroanalytical sensor platforms have been produced for the detection of small molecules, proteins, and microorganisms vital to ensuring food and drink safety. These utilise various recognition systems, from direct electrochemical redox processes to biological recognition elements such as antibodies, enzymes, and aptamers; however, further exploration needs to be carried out, with many systems requiring validation against standard benchtop laboratory-based techniques to offer increased confidence in the sensing platforms. This short review demonstrates that electroanalytical biosensors already offer a sensitive, fast, and low-cost sensor platform for food and drink safety monitoring. With continued research into the development of these sensors, increased confidence in the safety of food and drink products for manufacturers, policy makers, and end users will result.

A Proteomic- and Bioinformatic-Based Identification of Specific Allergens from Edible Insects: Probes for Future Detection as Food Ingredients

The increasing development of edible insect flours as alternative sources of proteins added to food and feed products for improving their nutritional value, necessitates an accurate evaluation of their possible adverse side-effects, especially for individuals suffering from food allergies. Using a proteomic- and bioinformatic-based approach, the diversity of proteins occurring in currently consumed edible insects such as silkworm (Bombyx mori), cricket (Acheta domesticus), African migratory locust (Locusta migratoria), yellow mealworm (Tenebrio molitor), red palm weevil (Rhynchophorus ferrugineus), and giant milworm beetle (Zophobas atratus), was investigated. Most of them consist of phylogenetically-related protein allergens widely distributed in the different groups of arthropods (mites, insects, crustaceans) and mollusks. However, a few proteins belonging to discrete protein families including the chemosensory protein, hexamerin, and the odorant-binding protein, emerged as proteins highly specific for edible insects. To a lesser extent, other proteins such as apolipophorin III, the larval cuticle protein, and the receptor for activated protein kinase, also exhibited a rather good specificity for edible insects. These proteins, that are apparently missing or much less represented in other groups of arthropods, mollusks and nematods, share well conserved amino acid sequences and very similar three-dimensional structures. Owing to their ability to trigger allergic responses in sensitized people, they should be used as probes for the specific detection of insect proteins as food ingredients in various food products and thus, to assess their food safety, especially for people allergic to edible insects.

FcεR1-expressing nociceptors trigger allergic airway inflammation

BACKGROUND

Lung nociceptor neurons amplify immune cell activity and mucus metaplasia in response to an inhaled allergen challenge in sensitized mice.

OBJECTIVE

We sought to identify the cellular mechanisms by which these sensory neurons are activated subsequent to allergen exposure.

METHODS

We used calcium microscopy and electrophysiologic recording to assess whether vagal neurons directly respond to the model allergen ovalbumin (OVA). Next, we generated the first nociceptor-specific FcεR1γ knockdown (TRPV1^Cre::FcεR1γ^fl/fl) mice to assess whether this targeted invalidation would affect the severity of allergic inflammation in response to allergen challenges.

RESULTS

Lung-innervating jugular nodose complex ganglion neurons express the high-affinity IgE receptor FcεR1, the levels of which increase in OVA-sensitized mice. FcεR1γ-expressing vagal nociceptor neurons respond directly to OVA complexed with IgE with depolarization, action potential firing, calcium influx, and neuropeptide release. Activation of vagal neurons by IgE-allergen immune complexes, through the release of substance P from their peripheral terminals, directly amplifies T_H2 cell influx and polarization in the airways. Allergic airway inflammation is decreased in TRPV1^Cre::FcεR1γ^fl/fl mice and in FcεR1α^-/- mice into which bone marrow has been transplanted. Finally, increased in vivo circulating levels of IgE following allergen sensitization enhances the responsiveness of FcεR1 to immune complexes in both mouse jugular nodose complex ganglion neurons and human induced pluripotent stem cell-derived nociceptors.

CONCLUSIONS

Allergen sensitization triggers a feedforward inflammatory loop between IgE-producing plasma cells, FcεR1-expressing vagal sensory neurons, and T_H2 cells, which helps to both initiate and amplify allergic airway inflammation. These data highlight a novel target for reducing allergy, namely, FcεR1γ expressed by nociceptors.

LAMP-LFD Based on Isothermal Amplification of Multicopy Gene ORF160b: Applicability for Highly Sensitive Low-Tech Screening of Allergenic Soybean (Glycine max) in Food

Soybean (Glycine max) allergy can be life threatening. A lack of causative immunotherapy of soybean allergy makes soybean avoidance indispensable. Detection methods are essential to verify allergen labeling and unintentional allergen cross contact during food manufacture. Here, we aimed at evaluating our previously described primers for loop-mediated isothermal amplification (LAMP) of multicopy gene ORF160b, combined with a lateral flow dipstick (LFD)-like detection, for their performance of soybean detection in complex food matrices. The results were compared with those obtained using quantitative real-time Polymerase Chain Reaction (qPCR) as the current standard of DNA-based allergen detection, and antibody-based commercial lateral flow device (LFD) as the current reference of protein-based rapid allergen detection. LAMP-LFD allowed unequivocal and reproducible detection of 10 mg/kg soybean incurred in three representative matrices (boiled sausage, chocolate, instant tomato soup), while clear visibility of positive test lines of two commercial LFD tests was between 10 and 10² mg/kg and depending on the matrix. Sensitivity of soybean detection in incurred food matrices, commercial retail samples, as well as various processed soybean products was comparable between LAMP-LFD and qPCR. The DNA-based LAMP-LFD proved to be a simple and low-technology soybean detection tool, showing sensitivity and specificity that is comparable or superior to the investigated commercial protein-based LFD.

Effect of Instant Controlled Pressure Drop (DIC) Treatment on the Detection of Nut Allergens by Real Time PCR

Tree nuts show nutritional properties and human health benefits. However, they contain allergenic proteins, which make them harmful to the sensitised population. The presence of tree nuts on food labelling is mandatory and, consequently, the development of suitable analytical methodologies to detect nuts in processed foods is advisable. Real-Time PCR allowed a specific and accurate amplification of allergen sequences. Some food processing methods could induce structural and/or conformational changes in proteins by altering their allergenic capacity, as well as produce the fragmentation and/or degradation of genomic DNA. In this work, we analysed by means of Real-Time PCR, the influence of pressure and thermal processing through Instant Controlled Pressure Drop (DIC) on the detectability of hazelnut, pistachio and cashew allergens. The detection of targets in hazelnut, pistachio and cashew (Cor a 9, Pis v 1 and Ana o 1, respectively) is affected by the treatment to different extents depending on the tree nut. Results are compared to those previously obtained by our group in the analysis of different treatments on the amplificability of the same targets. Reduction in amplificability is similar to that reported for some autoclave conditions. Our assays might allow for the detection of up to 1000 mg/kg of hazelnut, pistachio and cashew flours after being submitted to DIC treatment in food matrices.

The Development of Highly Specific and Sensitive Primers for the Detection of Potentially Allergenic Soybean (Glycine max) Using Loop-Mediated Isothermal Amplification Combined with Lateral Flow Dipstick (LAMP-LFD)

The soybean (Glycine max) has been recognized as a frequent elicitor of food allergy worldwide. A lack of causative immunotherapy of soybean allergy makes soybean avoidance essential. Therefore, sensitive and specific methods for soybean detection are needed to allow for soybean verification in foods. Loop-mediated isothermal amplification (LAMP) represents a rapid and simple DNA-based detection method principally suitable for field-like applications or on-site analytical screening for allergens during the manufacturing of foods. This work describes the systematic development and selection of suitable LAMP primers based on soybean multicopy genes. The chemistry applied allows for a versatile detection of amplified DNA, using either gel electrophoresis, fluorescence recording, or a simple Lateral Flow Dipstick (LFD). LAMP based on the ORF160b gene was highly specific for the soybean and may allow for a detection level equivalent to approximately 10 mg soy per kg food. Various soybean cultivars were detectable at a comparable level of sensitivity. LAMP combined with LFD-like detection facilitates a simple, highly specific and sensitive detection of the soybean without the need for expensive analytical equipment. In contrast to the majority of antibody-based methods for soybean detection, all identified primer sequences and optimized protocols are disclosed and broadly available to the community.

The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods when using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods

Food allergens present a significant health risk to the human population, so their presence must be monitored and controlled within food production environments. This is especially important for powdered food, which can contain nearly all known food allergens. Manufacturing is experiencing the fourth industrial revolution (Industry 4.0), which is the use of digital technologies, such as sensors, Internet of Things (IoT), artificial intelligence, and cloud computing, to improve the productivity, efficiency, and safety of manufacturing processes. This work studied the potential of small low-cost sensors and machine learning to identify different powdered foods which naturally contain allergens. The research utilised a near-infrared (NIR) sensor and measurements were performed on over 50 different powdered food materials. This work focussed on several measurement and data processing parameters, which must be determined when using these sensors. These included sensor light intensity, height between sensor and food sample, and the most suitable spectra pre-processing method. It was found that the K-nearest neighbour and linear discriminant analysis machine learning methods had the highest classification prediction accuracy for identifying samples containing allergens of all methods studied. The height between the sensor and the sample had a greater effect than the sensor light intensity and the classification models performed much better when the sensor was positioned closer to the sample with the highest light intensity. The spectra pre-processing methods, which had the largest positive impact on the classification prediction accuracy, were the standard normal variate (SNV) and multiplicative scattering correction (MSC) methods. It was found that with the optimal combination of sensor height, light intensity, and spectra pre-processing, a classification prediction accuracy of 100% could be achieved, making the technique suitable for use within production environments.

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.

Simplified Tracking of a Soy Allergen in Processed Food Using a Monoclonal Antibody-Based Sandwich ELISA Targeting the Soybean 2S Albumin Gly m 8

Soybean allergens in food samples are currently detected in most cases using enzyme-linked immunosorbent assays (ELISAs) based on antibodies raised against bulk soybean proteins or specifically targeting soybean trypsin inhibitor, conglycinin, or glycinin. The various commercial ELISAs lack standardized reference material, and the results are often inaccurate because the antibodies cross-react with proteins from other legumes. Furthermore, the isolation of allergenic proteins involves laborious denaturing extraction conditions. To tackle these challenges, we have developed a novel sandwich ELISA based on monoclonal antibodies raised against the soybean 2S albumin Gly m 8 and a recombinant Gly m 8 reference protein with native-analogous characteristics. The antibodies do not cross-react with other legume proteins, and the extraordinary stability and solubility of Gly m 8 allows it to be extracted even from complex matrices after processing. The Gly m 8 ELISA therefore achieves greater specificity and reproducibility than current ELISA tests.

Development of a DNA Barcoding-Like Approach to Detect Mustard Allergens in Wheat Flours

The spread of food allergens is a topic of global importance due to its impact on public health. National and International regulations ask food producers and manufacturers to declare product compositions on the label, especially in case of processed raw materials. Wheat flour (Triticum aestivum) can be contaminated by a wide range of species belonging to the Brassicaceae in the field or during grain harvests, storage, and processing. Among them, mustards (Brassica nigra, Brassica juncea and Sinapis alba) are well known allergenic species. Often, food quality laboratories adopt an ELISA approach to detect the presence of mustard species. However, this approach shows cross-reactivity with other non-allergenic species such as Brassica napus (rapeseed). In the last few years, DNA barcoding was proposed as a valid identification method, and it is now commonly used in the authentication of food products. This study aims to set up an easy and rapid DNA-based tool to detect mustard allergenic species. DNA barcoding (matK and ITS2) and chromosome markers (A6, B, C1 genome regions) were selected, and specific primers were validated on incurred reference food matrices. The developed test was proven to be able to distinguish mustard from rapeseed and wheat, overcoming cross-reactivity with Brassica napus.

Application of real-time PCR for tree nut allergen detection in processed foods

Currently, food allergies are an important health concern worldwide. The presence of undeclared allergenic ingredients or the presence of traces of allergens due to accidental contamination during food processing poses a great health risk to sensitized individuals. Therefore, reliable analytical methods are required to detect and identify allergenic ingredients in food products. Real-time PCR allowed a specific and accurate amplification of allergen sequences. Some processing methods could induce the fragmentation and/or degradation of genomic DNA and some studies have been performed to analyze the effect of processing on the detection of different targets, as thermal treatment, with and without applying pressure. In this review, we give an updated overview of the applications of real-time PCR for the detection of allergens of tree nut in processed food products. The different variables that contribute to the performance of PCR methodology for allergen detection are also review and discussed.

Protein or No Protein? Opportunities for DNA-Based Detection of Allergenic Foods

In food allergy, a common immunological disease with a potentially severe outcome, a causative cure is not available. Correct ingredient labeling and risk assessment of unlabeled allergen cross-contact is a prerequisite for effective allergen avoidance. Specific and sensitive analytical methods, which allow for unequivocal identification and accurate quantification of allergenic components, are important tools in allergen risk management. Both protein- and DNA-based methods are in place and reveal pros and cons depending upon the application and individual analytical question. This perspective highlights relevant molecular aspects and discusses, especially, opportunities for the application of DNA-based methods for the detection of allergenic foods.