Evaluation of methods for DNA extraction from Clostridium tyrobutyricum spores and its detection by qPCR

Clostridium tyrobutyricum is the major agent that causes the blowing defect in cheese due to the germination of its dormant spores during the ripening stage. As a result, many of the affected cheeses show cavities and cracks, which cause the product loss in most cases. Nowadays, there is not a fast method capable of detecting milk contaminated with C. tyrobutyricum spores. The aim of this study has been to develop a fast and reliable method based on real time PCR (qPCR) to detect C. tyrobutyricum spores in raw milk. One of the main limitations has been to find a good procedure for the spore disruption to extract the DNA due to its high resistance. For this reason, different disruption methods have been tested, including chemical agents, bead beating, enzymatic and microwave treatment. Furthermore, an enzymatic treatment with subtilisin was applied for milk clarification and recovery of spores. The comparison of the assayed methods has been made using sterile milk spiked with C. tyrobutyricum spores, obtained in solid or liquid medium. The results showed that microwave treatment followed by a standard DNA purification step was found to be the best disruption method. The Ct values obtained for spores were higher than those found for vegetative cells by qPCR, for the same quantity of DNA. This difference could be due to the action of the Small Acid Soluble Proteins (SASP) in the DNA packaging of spores. Moreover, spores obtained in agar plate were found more resistant to disruption than those obtained in liquid medium. Subtilisin and microwave treatments were found to be successful for DNA extraction from C. tyrobutyricum spores in milk and subsequent identification by qPCR. However, the differences observed between the amplification of DNA from spores obtained in different media and from vegetative cells have to be taken into account to optimize a method for C. tyrobutyricum detection

Development and validation of sensitive and rapid immunoassays to detect minute amounts of hazelnut in processed food and working surfaces

Hazelnut (Corylus avellana L.) represents one of the most allergenic nuts and it can be found as a hidden allergen in processed food due to cross contamination. Therefore, sensitive and specific analytical techniques are in high demand to be used in allergen risk management plans at food industry. In this study, sandwich ELISA and Lateral Flow Immunoassay (LFIA) to detect hazelnut have been developed based on the determination of Cor a 9, one of the most abundant and allergenic proteins of hazelnut. Results showed that cross-reactivity was only found with walnut and Pecan nut, which was lower than 0.1%. When analyzing food spiked with a hazelnut extract or blended with hazelnut flour, ELISA and LFIA were able to detect 0.1 ppm and 0.5 ppm of hazelnut protein with a recovery from 82 to 110%. ELISA and LFIA could also detect 0.15 and 0.6 ppm of hazelnut protein in baked cookies incurred with ground hazelnut, respectively. Furthermore, LFIA could detect 1.25 μg of hazelnut protein in working surfaces of stainless steel and melamine. The sandwich ELISA was in-house validated, showing acceptable results of precision. Likewise, ELISA and LFIA showed to be robust tests. The combined use of both assays could improve the allergen risk management plans in food industry to monitor the presence of hazelnut traces in raw ingredients, processed food and working surfaces

Development of sandwich ELISA and lateral flow immunoassay to detect almond in processed food

Almond (Prunus dulcis) represents a potential allergenic hazard that should be included in Allergen Control Plans. In this study, sandwich ELISA and lateral flow immunoassay (LFIA), using amandin (Pru du 6) as the target protein, were developed to detect almond in processed food and validated according to international guides. ELISA could detect 2 ng/mL and LFIA 30 ng/mL of pure amandin. No cross-reactivity was found on a panel of 50 food commodities with the exception of Pecan nut, Brazil nut and chestnut for which the cross-reactivity was lower than 0.02%. Furthermore, ELISA and LFIA were able to detect 0.12 and 0.70 ppm of almond protein in foods spiked with almond extract whereas 0.20 and 2.0 ppm could be detected in baked cookies incurred with almond, respectively. Both techniques could be applied for food manufacturers and control agencies for monitoring the presence of almond traces in food and working surfaces. © 2021 The Author(s