Rapid Detection of Fish Major Allergen Parvalbumin by Surface Plasmon Resonance Biosensor

Seafood product safety: A hybrid graphene/gold-based electrochemical immunosensor for fish allergen analysis

Seafood product labels with accurate allergen contents can avoid and/or minimize allergic reactions. Therefore, an electrochemical immunosensor for the analysis of β-parvalbumin (β-PV, a major fish allergen) was developed. Screen-printed carbon electrodes were nanostructured with reduced graphene oxide and gold nanoparticles. The platform was characterized by scanning electron microscopy and elemental analysis. In a sandwich-type assay (∼75 min), the antigen-antibody interaction was detected by chronoamperometry using horseradish peroxidase and TMB-H2O2. A linear range of 25-3000 ng/mL, a sensitivity of 2.99 µA.mL/ng, and a limit of detection of 9.9 ng/mL (corresponding to 0.40 ng in the analysed aliquot) were obtained. The selectivity and possible interferences were assessed by analysing several other food allergens and a marine toxin. The sensor was applied to the analysis of 17 commercial foods and the effect of culinary processing (e.g., grilled, canned, smoked) on the β-PV concentration was assessed. Traces of β-PV were successfully quantified and ELISA was used to assess the results.

Parvalbumin: A Major Fish Allergen and a Forensically Relevant Marker

Parvalbumins (PVALBs) are low molecular weight calcium-binding proteins. In addition to their role in many biological processes, PVALBs play an important role in regulating Ca2+ switching in muscles with fast-twitch fibres in addition to their role in many biological processes. The PVALB gene family is divided into two gene types, alpha (α) and beta (β), with the β gene further divided into two gene types, beta1 (β1) and beta2 (β2), carrying traces of whole genome duplication. A large variety of commonly consumed fish species contain PVALB proteins which are known to cause fish allergies. More than 95% of all fish-induced food allergies are caused by PVALB proteins. The authentication of fish species has become increasingly important as the seafood industry continues to grow and the growth brings with it many cases of food fraud. Since the PVALB gene plays an important role in the initiation of allergic reactions, it has been used for decades to develop alternate assays for fish identification. A brief review of the significance of the fish PVALB genes is presented in this article, which covers evolutionary diversity, allergic properties, and potential use as a forensic marker.

DNA, protein and aptamer-based methods for seafood allergens detection: Principles, comparisons and updated applications

The increasing number of people with seafood allergy has caused a series of problems for practitioners and consumers in the seafood industry year by year. Thereby, development of efficient, convenient and low-cost allergen detection methods is urgently needed. This review introduces three important existing seafood allergen detection methods associated with DNA-based, protein-based and aptamer-based. Their principles and biological characteristics are firstly presented. The core of these three methods are DNA amplification techniques, specific binding of antigens and antibodies, and specific binding of aptamers and ligands, respectively. Among them, DNA-based detection method is an indirect analysis, which takes the gene of allergen as the detection object and is characterized by good stability and high sensitivity. Protein-based and aptamer-based, methods employ indirect analysis for allergen detection. The difference is that the latter uses an easily synthesized and highly efficient aptamer as the detection probe, showing great promising potentials. The advantages and disadvantages of the three mentioned detection methods are also discussed. In the future, as more efficient and reliable detection methods for seafood allergens come into practice, the possibility of seafood allergy patients eating seafood products by mistake will be greatly reduced, which will ensure the food safety and the health of allergy patients.

New applications of advanced instrumental techniques for the characterization of food allergenic proteins

Current approaches based on electrophoretic, chromatographic or immunochemical principles have allowed characterizing multiple allergens, mapping their epitopes, studying their mechanisms of action, developing detection and diagnostic methods and therapeutic strategies for the food and pharmaceutical industry. However, some of the common structural features related to the allergenic potential of food proteins remain unknown, or the pathological mechanism of food allergy is not yet fully understood. In addition, it is also necessary to evaluate new allergens from novel protein sources that may pose a new risk for consumers. Technological development has allowed the expansion of advanced technologies for which their whole potential has not been entirely exploited and could provide novel contributions to still unexplored molecular traits underlying both the structure of food allergens and the mechanisms through which they sensitize or elicit adverse responses in human subjects, as well as improving analytical techniques for their detection. This review presents cutting-edge instrumental techniques recently applied when studying structural and functional aspects of proteins, mechanism of action and interaction between biomolecules. We also exemplify their role in the food allergy research and discuss their new possible applications in several areas of the food allergy field.

A novel method based on infrared spectroscopic inception-resnet networks for the detection of the major fish allergen parvalbumin

We have developed a novel approach that involves inception-resnet network (IRN) modeling based on infrared spectroscopy (IR) for rapid and specific detection of the fish allergen parvalbumin. SDS-PAGE and ELISA were used to validate the new method. Through training and learning with parvalbumin IR spectra from 16 fish species, IRN, support vector machine (SVM), and random forest (RF) models were successfully established and compared. The IRN model extracted highly representative features from the IR spectra, leading to high accuracy in recognizing parvalbumin (up to 97.3%) in a variety of seafood matrices. The proposed infrared spectroscopic IRN (IR-IRN) method was rapid (~20 min, cf. ELISA ~4 h) and required minimal expert knowledge for application. Thus, it could be extended for large-scale field screening and identification of parvalbumin or other potential allergens in complex food matrices.

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.

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.

Surface plasmon resonance (SPR) biosensors for food allergen detection in food matrices

Food allergies are recognized as a growing public health concern, with an estimated 3% of adults and 6-8% of children affected by food allergy disorders. Hence, food allergen detection, labeling, and management have become significant priorities within the food industry, and there is an urgent requirement for reliable, sensitive, and user-friendly technologies to trace food allergens in food products. In this critical review, we provide a comprehensive overview of the principles and applications of surface plasmon resonance (SPR) biosensors in the identification and quantification of food allergens (milk, egg, peanut, and seafood), including fiber-optic surface plasmon resonance (FOSPR), surface plasmon resonance imaging (SPRI), localized surface plasmon resonance (LSPR), and transmission surface plasmon resonance (TSPR). Moreover, the characteristics and fitness-for-purpose of each reviewed SPR biosensor is discussed, and the potential of newly developed SPR biosensors for multi-allergen real-time detection in a complex food system is highlighted. Such SPR biosensors are also required to facilitate the reliable, high-throughput, and real-time detection of food allergens by the food control industry and food safety control officials to easily monitor cross-contamination during food processing.

Detection of allergenic additives in processed meat products

Allergic responses to food components are an increasing problem all over the world. It is therefore important to protect people who are vulnerable to food allergens against accidental and unintended consumption of products containing allergic ingredients. The meat industry commonly uses various allergic additives in the production of processed products, such as legumes (soy, peas, beans), milk and egg preparations, cereals containing gluten (wheat, rye, barley and oats), and spices (celery and mustard). These meat additives have specific technological properties, which help to create a texture or flavor profile, or affect the nutritional value, although some of them, such as soy, mustard, milk and egg white proteins, can cause severe allergic reactions. The aim of this paper is to discuss the application of various recently established methods of detection of allergenic additives in processed meat products - for instance cold cuts and sausages. The new methods are based mainly on protein, DNA, and isoflavones or phytic acid analysis. The article also characterizes the latest trends in the development of research on methods that would enable quick and reliable identification of targeted allergens in meat products. © 2018 Society of Chemical Industry.

Electrochemical Affinity Biosensors Based on Disposable Screen-Printed Electrodes for Detection of Food Allergens

Food allergens are proteins from nuts and tree nuts, fish, shellfish, wheat, soy, eggs or milk which trigger severe adverse reactions in the human body, involving IgE-type antibodies. Sensitive detection of allergens in a large variety of food matrices has become increasingly important considering the emergence of functional foods and new food manufacturing technologies. For example, proteins such as casein from milk or lysozyme and ovalbumin from eggs are sometimes used as fining agents in the wine industry. Nonetheless, allergen detection in processed foods is a challenging endeavor, as allergen proteins are degraded during food processing steps involving heating or fermentation. Detection of food allergens was primarily achieved via Enzyme-Linked Immuno Assay (ELISA) or by chromatographic methods. With the advent of biosensors, electrochemical affinity-based biosensors such as those incorporating antibodies and aptamers as biorecognition elements were also reported in the literature. In this review paper, we highlight the success achieved in the design of electrochemical affinity biosensors based on disposable screen-printed electrodes towards detection of protein allergens. We will discuss the analytical figures of merit for various disposable screen-printed affinity sensors in relation to methodologies employed for immobilization of bioreceptors on transducer surface.

Survey of the year 2004 commercial optical biosensor literature

The year 2004 represents a milestone for the biosensor research community: in this year, over 1000 articles were published describing experiments performed using commercially available systems. The 1038 papers we found represent an approximately 10% increase over the past year and demonstrate that the implementation of biosensors continues to expand at a healthy pace. We evaluated the data presented in each paper and compiled a 'top 10' list. These 10 articles, which we recommend every biosensor user reads, describe well-performed kinetic, equilibrium and qualitative/screening studies, provide comparisons between binding parameters obtained from different biosensor users, as well as from biosensor- and solution-based interaction analyses, and summarize the cutting-edge applications of the technology. We also re-iterate some of the experimental pitfalls that lead to sub-optimal data and over-interpreted results. We are hopeful that the biosensor community, by applying the hints we outline, will obtain data on a par with that presented in the 10 spotlighted articles. This will ensure that the scientific community at large can be confident in the data we report from optical biosensors.