Validating allergen coding genes (Cor a 1, Cor a 8, Cor a 14) as target sequences for hazelnut detection via Real-Time PCR

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.

Detection of Hazelnut and Almond Adulteration in Olive Oil: An Approach by qPCR

Virgin olive oil (VOO), characterized by its unique aroma, flavor, and health benefits, is subject to adulteration with the addition of oils obtained from other edible species. The consumption of adulterated olive oil with nut species, such as hazelnut or almond, leads to health and safety issues for consumers, due to their high allergenic potential. To detect almond and hazelnut in olive oil, several amplification systems have been analyzed by qPCR assay with a SYBR Green post-PCR melting curve analysis. The systems selected were Cora1F2/R2 and Madl, targeting the genes coding the allergenic protein Cor a 1 (hazelnut) and Pru av 1 (almond), respectively. These primers revealed adequate specificity for each of the targeted species. In addition, the result obtained demonstrated that this methodology can be used to detect olive oil adulteration with up to 5% of hazelnut or almond oil by a single qPCR assay, and with a level as low as 2.5% by a nested-qPCR assay. Thus, the present research has shown that the SYBR-based qPCR assay can be a rapid, precise, and accurate method to detect adulteration in olive oil.

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.

Detection of allergen coding sequences of kiwi, peach, and apple in processed food by qPCR

BACKGROUND

Food traceability becomes lifesaving for persons suffering severe allergy or intolerance, and therefore need a complete avoidance of the immune-trigger food. This paper describes how to fingerprint the presence of some allergenic species (kiwi, peach, and apple) in foods by quantitative real-time PCR (qPCR).

RESULTS

Five DNA extraction procedures were tested on fruits and foods. The results were statistically evaluated, and discussed. Analysis by qPCR with SYBR Green was developed to detect traces of these allergenic species in foods. Plasmids containing the target sequences of kiwi, peach and apple were employed as internal reference standard. Analysis of spiked food samples showed a limit of detection of 25 mg kg^-1 for kiwi, 20 mg kg^-1 for peach and 50 mg kg^-1 for apple.

CONCLUSION

The qPCR method here developed, combined with the use of internal plasmid reference standard, represents a specific system for the quick detection of allergenic species in complex food matrices, with a limit of detection comparable with those reported using more time-consuming methods. © 2017 Society of Chemical Industry.

Detection of almond allergen coding sequences in processed foods by real time PCR

The aim of this work was to develop and analytically validate a quantitative RT-PCR method, using novel primer sets designed on Pru du 1, Pru du 3, Pru du 4, and Pru du 6 allergen-coding sequences, and contrast the sensitivity and specificity of these probes. The temperature and/or pressure processing influence on the ability to detect these almond allergen targets was also analyzed. All primers allowed a specific and accurate amplification of these sequences. The specificity was assessed by amplifying DNA from almond, different Prunus species and other common plant food ingredients. The detection limit was 1 ppm in unprocessed almond kernels. The method's robustness and sensitivity were confirmed using spiked samples. Thermal treatment under pressure (autoclave) reduced yield and amplificability of almond DNA; however, high-hydrostatic pressure treatments did not produced such effects. Compared with ELISA assay outcomes, this RT-PCR showed higher sensitivity to detect almond traces in commercial foodstuffs.

Single-tube nested real-time PCR as a new highly sensitive approach to trace hazelnut

Hazelnut is one of the most commonly consumed tree nuts, being largely used by the food industry in a wide variety of processed foods. However, it is a source of allergens capable of inducing mild to severe allergic reactions in sensitized individuals. Hence, the development of highly sensitive methodologies for hazelnut traceability is essential. In this work, we developed a novel technique for hazelnut detection based on a single-tube nested real-time PCR system. The system presents high specificity and sensitivity, enabling a relative limit of detection of 50 mg/kg of hazelnut in wheat material and an absolute limit of detection of 0.5 pg of hazelnut DNA (1 DNA copy). Its application to processed food samples was successfully achieved, detecting trace amounts of hazelnut in chocolate down to 60 mg/kg. These results highlight the adequacy of the technique for the specific detection and semiquantitation of hazelnut as potential hidden allergens in foods.