Assessment of peanut allergen Ara h1 in processed foods using a SWCNTs-based nanobiosensor

Effects of the covalent conjugation between caffeic acid and peanut allergen protein Ara h1 on the antigenicity and structure of Ara h1

Ara h1 was the highest content of peanut allergen protein, identified as a biomarker of peanut allergen. In this study, Ara h1 was covalently complexed with caffeic acid (CA) to research the effects of covalent conjugation on the antigenicity and protein structural properties of Ara h1. After the covalent complexing of Ara h1 and CA, the IgG-binding capacity of Ara h1 was reduced compared with that of control Ara h1. Moreover, the structure of Ara h1 changed from ordered to disordered, the number of intermolecular hydrogen bonds decreased, and some hydrophobic groups were exposed or hydrophobic peptides were released. The carboxyl group in CA reacted with the amino group in Ara h1. The digestibility of Ara h1-CA was increased. The antigenicity of Ara h1-CA was undetectable after 30 min of digestion in vitro. These findings can serve as a reference for further research on hypoallergenic peanut products.

Microfluidic paper-based analysis device applying black phosphorus nanosheets@MWCNTs-COOH: A portable and efficient strategy for detection of β-Lactoglobulin in dairy products

This study prepared a novel, portable and cost-effective microfluidic paper-based electrochemical analysis device (μ-PAD) using black phosphorus nanosheets@carboxylated multi-walled carbon nanotubes (BPNSs@MWCNTs-COOH) nanocomposites for β-lactoglobulin (β-LG) detection. At the appreciate ratio, the synthesized BPNSs@MWCNTs-COOH was demonstrated to not only serve as a high-quality substrate for the specific aptamer immobilization, but also improve the electron transfer capability of the sensing interface. The μ-PADs, utilizing BPNSs@MWCNTs-COOH and aptamer recognition, exhibited a wider detection range (10-1000 ng mL-1) and lower detection limit (LOD: 0.12 ng mL-1) for β-LG, and demonstrated enhanced specificity, satisfactory anti-interference ability and stability. When applied to the β-LG determination in dairy samples, the μ-PAD yielded β-LG concentrations highly correlated with those obtained using the HPLC method (R2: 0.9982). These results emphasized the reliable performance of the developed μ-PADs in β-LG allergen quantification, highlighting their potential as an efficient platform for the rapid screening of β-LG allergens.

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.

Paper-based microfluidic device for selective detection of peanut allergen Ara h1 applying black phosphorus-Au nanocomposites for signal amplification

This paper developed a portable microfluidic paper-based analysis device (μ-PAD) combined with the electrochemical technique for efficient and sensitive detection of peanut allergen Ara h1. The proposed μ-PAD works based on the variation of differential pulse voltammetry (DPV) response current induced by peanut allergen Ara h1. Black phosphorus (BP)-Au nanocomposites were introduced both to improve the electron transfer rate at the electrode interface for signal amplification, and to immobilize the specific Ara h1 aptamers through Au-S bonding to recognize the target in food matrices. This μ-PAD had good specificity and detection stability for Ara h1 allergen and could complete the entire analysis process within 20 min, achieving a wide linear response range (25-800 ng mL-1) and a low detection limit (LOD, 11.8 ng mL-1). In the Ara h1 allergen detection applied to real peanut products (cookies, milk, and bread), the constructed μ-PAD obtained acceptable recoveries (93.50%-101.86%) with relative standard deviations (RSDs) of 0.36-2.97% (n = 3), with a good correlation with the ELISA results (R2 = 0.9956). Therefore, the portable μ-PAD based on BP-Au nanocomposites was demonstrated to provide an effective strategy for rapid analysis and screening of Ara h1 allergen in food, which has broad application prospects.

Carbon Nanotube-Based Biosensors Using Fusion Technologies with Biologicals & Chemicals for Food Assessment

High-sensitivity sensors applied in various diagnostic systems are considered to be a promising technology in the era of the fourth industrial revolution. Biosensors that can quickly detect the presence and concentration of specific biomaterials are receiving research attention owing to the breakthroughs in detection technology. In particular, the latest technologies involving the miniaturization of biosensors using nanomaterials, such as nanowires, carbon nanotubes, and nanometals, have been widely studied. Nano-sized biosensors applied in food assessment and in in vivo measurements have the advantages of rapid diagnosis, high sensitivity and selectivity. Nanomaterial-based biosensors are inexpensive and can be applied to various fields. In the present society, where people are paying attention to health and wellness, high-technology food assessment is becoming essential as the consumer demand for healthy food increases. Thus, biosensor technology is required in the food and medical fields. Carbon nanotubes (CNTs) are widely studied for use in electrochemical biosensors. The sensitive electrical characteristics of CNTs allow them to act as electron transfer mediators in electrochemical biosensors. CNT-based biosensors require novel technologies for immobilizing CNTs on electrodes, such as silicon wafers, to use as biosensor templates. CNT-based electrochemical biosensors that serve as field-effect transistors (FET) increase sensitivity. In this review, we critically discuss the recent advances in CNT-based electrochemical biosensors applied with various receptors (antibodies, DNA fragments, and other nanomaterials) for food evaluation, including pathogens, food allergens, and other food-based substances.

A Novel Activated Biochar-Based Immunosensor for Rapid Detection of E. coli O157:H7

E. coli O157:H7, one of the major foodborne pathogens, can cause a significant threat to the safety of foods. The aim of this research is to develop an activated biochar-based immunosensor that can rapidly detect E. coli O157:H7 cells without incubation in pure culture. Biochar was developed from corn stalks using proprietary reactors and then activated using steam-activation treatment. The developed activated biochar presented an enhanced surface area of 830.78 m²/g. To develop the biosensor, the gold electrode of the sensor was first coated with activated biochar and then functionalized with streptavidin as a linker and further immobilized with biotin-labeled anti-E. coli polyclonal antibodies (pAbs). The optimum concentration of activated biochar for sensor development was determined to be 20 mg/mL. Binding of anti-E. coli pAbs with E. coli O157:H7 resulted in a significant increase in impedance amplitude from 3.5 to 8.5 kΩ when compared to an only activated biochar-coated electrode. The developed immunosensor was able to detect E. coli O157:H7 cells with a limit of detection of 4 log CFU/mL without incubation. Successful binding of E. coli O157:H7 onto an activated biochar-based immunosensor was observed on the microelectrode surface in scanning electron microscopy (SEM) images.

Sensors Based on the Carbon Nanotube Field-Effect Transistors for Chemical and Biological Analyses

Nano biochemical sensors play an important role in detecting the biomarkers related to human diseases, and carbon nanotubes (CNTs) have become an important factor in promoting the vigorous development of this field due to their special structure and excellent electronic properties. This paper focuses on applying carbon nanotube field-effect transistor (CNT-FET) biochemical sensors to detect biomarkers. Firstly, the preparation method, physical and electronic properties and functional modification of CNTs are introduced. Then, the configuration and sensing mechanism of CNT-FETs are introduced. Finally, the latest progress in detecting nucleic acids, proteins, cells, gases and ions based on CNT-FET sensors is summarized.

Development of GO/Co/Chitosan-Based Nano-Biosensor for Real-Time Detection of D-Glucose

Electrochemical nano-biosensor systems are popular in the industrial field, along with evaluations of medical, agricultural, environmental and sports analysis, because they can simultaneously perform qualitative and quantitative analyses with high sensitivity. However, real-time detection using an electrochemical nano-biosensor is greatly affected by the surrounding environment with the performance of the electron transport materials. Therefore, many researchers are trying to find good factors for real-time detection. In this work, it was found that a composite composed of graphite oxide/cobalt/chitosan had strong stability and electron transfer capability and was applied to a bioelectrochemical nano-biosensor with high sensitivity and stability. As a mediator-modified electrode, the GO/Co/chitosan composite was electrically deposited onto an Au film electrode by covalent boding, while glucose oxidase as a receptor was immobilized on the end of the GO/Co/chitosan composite. It was confirmed that the electron transfer ability of the GO/Co/chitosan composite was excellent, as shown with power density analysis. In addition, the real-time detection of D-glucose could be successfully performed by the developed nano-biosensor with a high range of detected concentrations from 1.0 to 15.0 mM. Furthermore, the slope value composed of the current, per the concentration of D-glucose as a detection response, was significantly maintained even after 14 days.

Recent advances in analytical strategies and microsystems for food allergen detection

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

Food Allergies: Immunosensors and Management

Food allergies (FA) are commonly depicted as immune responses. The mechanism of allergic reactions involves immunoglobulin E (IgE) and non-immunoglobulin E (non-IgE)-related responses caused by contact with specific foods. FAs can be fatal, have negative effects and have become the subject of fanaticism in recent years. In terms of food safety, allergic compounds have become a problem. The immune response to allergens is different to that from food intolerance, pharmacological reactions, and poisoning. The most important allergenic foods are soybeans, milk, eggs, groundnuts, shellfishes, tree nuts, cereals and fish, which together are known as the “Big Eight”. This review will introduce and discuss FAs in milk, peanuts, nuts, shellfishes, eggs and wheat and their detections and potential treatments will also be provided. We believe that this review may provide important information regarding food-induced allergies for children who have allergic reactions and help them avoid the allergenic food in the future.

An Ultrasensitive Silicon-Based Electrolyte-Gated Transistor for the Detection of Peanut Allergens

The highly sensitive detection of peanut allergens (PAs) using silicon-based electrolyte-gated transistors (Si-EGTs) was demonstrated. The Si-EGT was made using a top-down technique. The fabricated Si-EGT showed excellent intrinsic electrical characteristics, including a low threshold voltage of 0.7 V, low subthreshold swing of <70 mV/dec, and low gate leakage of <10 pA. Surface functionalization and immobilization of antibodies were performed for the selective detection of PAs. The voltage-related sensitivity (S_V) showed a constant behavior from the subthreshold regime to the linear regime. The current-related sensitivity (S_I) was high in the subthreshold regime and then significantly decreased as the drain current increased. The limit of detection (LOD) was calculated to be as low as 25 pg/mL based on S_I characteristics, which is the lowest value reported to date in the literature for various sensor methodologies. The Si-EGT showed selective detection of PA through a non-specific control test. These results confirm that Si-EGT is a high-sensitivity and low-power biosensor for PA detection.

Microfluidic origami nano-aptasensor for peanut allergen Ara h1 detection

In this study, an origami microfluidic electrochemical nano-aptasensor was developed for the rapid detection of the peanut allergen Ara h1. Specifically, the microfluidic aptasensor was fabricated through sequential folding of a piece of chromatography paper substrate patterned with microchannel and screen-printed electrodes. Aptamer-decorated black phosphorus nanosheets (BPNSs) were electrodeposited onto the paper-based electrode surface as sensing probes for enhanced electrochemical detection and high specificity and selectivity. Critical design parameters (the concentration of probe, time for self-assembly of aptamer and reaction time) were investigated to optimize the aptasensor performance. The prepared aptasensor was able to complete detection within 20 min and demonstrated a linear range from 50 ~ 1000 ng/mL with a detection limit of 21.6 ng/mL. The aptasensor was successfully used to detect the Ara h1 spiked cookie dough sample. The proposed method reduces the gap between complex lab testing and food allergen analysis at the point of need.

Visible on-site detection of Ara h 1 by the switchable-linker-mediated precipitation of gold nanoparticles

Biosensors have been widely applied in tests for allergens, but on-site detection remains a challenge. Herein, we proposed a detection procedure for peanut Ara h 1 as a representative allergen, which was extracted from a cookie, thereby minimising the need for any complex pretreatment that was difficult to perform, and enabling the visual detection of the target without the use of analytical equipment. The extraction procedure was performed in less than 30 min using a syringe and filter (0.45 μm). The detection method for Ara h 1 was based on the aggregation of switchable linkers (SL) and gold nanoparticles (AuNP), and the presence of 0.19 mg peanut protein per 30 g of cookie could be confirmed within 30 min based on the AuNP/SL concentration ratio by the precipitation. This proposed procedure could be successfully applied to the detection of a wide range of food allergens.

A Systematic Review of Food Allergy: Nanobiosensor and Food Allergen Detection

Several individuals will experience accidental exposure to an allergen. In this sense, the industry has invested in the processes of removing allergenic compounds in food. However, accidental exposure to allergenic proteins can result from allergenic substances not specified on labels. Analysis of allergenic foods is involved in methods based on immunological, genetic, and mass spectrometry. The traditional methods have some limitations, such as high cost. In recent years, biosensor and nanoparticles combined have emerged as sensitive, selective, low-cost, and time-consuming techniques that can replace classic techniques. Nevertheless, each nanomaterial has shown a different potential to specific allergens or classes. This review used Preferred Reporting Items for Systematic Reviews and the Meta-Analysis guidelines (PRISMA) to approach these issues. A total of 104 articles were retrieved from a standardized search on three databases (PubMed, Scopus and Web of Science). The systematic review article is organized by the category of allergen detection and nanoparticle detection. This review addresses the relevant biosensors and nanoparticles as gold, carbon, graphene, quantum dots to allergen protein detection. Among the selected articles it was possible to notice a greater potential application on the allergic proteins Ah, in peanuts and gold nanoparticle-base as a biosensor. We envision that in our review, the association between biosensor and nanoparticles has shown promise in the analysis of allergenic proteins present in different food samples.

Significant Effect of Sample Pretreatment on Ara h1 Extraction and Improved Sensitive SWCNT-Based Detection through Optimization

Single-walled carbon nanotube (SWCNT)-based nanobiosensors have received increasing attention from food researchers as a future instrument of food safety due to their high sensitivity. However, the pretreatment process of the sample applying to SWCNT-based nanobiosensor is required to be more delicate compared to other analyses. In this study, the pretreatment process of Ara h1 protein from its retained complex food matrix was optimized using various buffer compounds and the pretreated allergenic Ara h1 obtained for the optimized process was detected by SWCNT-based nanobiosensor. In the pretreatment process, the buffer extraction method with tris buffer (Tris-HNO3, pH 8.4) was developed and used to extract native peanut allergens from foods. The extraction procedure for Ara h1 from peanut butter foods was performed by varying the temperature, extraction time, and additives (NaCl and skim milk powder). The results of these tests using our SWCNT-based biosensor were analyzed to evaluate the allergenic nature of the extracts. The peak level of Ara h1 extraction was achieved as 84.60 ± 7.50 ng/mL at 21 °C/60 min with the mixture of Tris-HNO3 and 1 M NaCl. In addition, other significant Ara h1 extractions were found to be 29.59 ± 2.57 at 21 °C/15 min and 27.74 ± 1.33 ng/mL at 60 °C/15 min. This study emphasizes the importance of adjusting the extraction time and temperature with respect to the target allergen and food matrix components. After the optimization of the sample pretreatment, the precision of SWCNT-based nanobiosensor by the resistance difference (ΔR) of the SWCNT-based biosensor via linear sweep voltammetry in a potentiostat was identified using the pretreated Ara h1 sample from the processed food compared with the indirect enzyme-linked immunosorbent assay (ELISA) results.