Molecularly imprinted polymer as a synthetic antibody for the biorecognition of hazelnut Cor a 14-allergen

Artificial receptors that mimic their natural biological counterparts have several advantages, such as lower production costs and increased shelf-life stability/versatility, while overcoming the ethical issues related to raising antibodies in animals. In this work, the proposed tailor-made molecularly imprinted polymer (MIP)-allergen receptors aimed at substituting or even transcending the performance of biological antibodies. For this purpose, a MIP was proposed as an artificial antibody for the recognition of hazelnut Cor a 14-allergen. The target protein was grafted onto the conducting polypyrrole receptor film using gold screen-printed electrodes (Au-SPE). The electrochemical assessment presented a linear response for the dynamic range of 100 fg mL^-1-1 μg mL^-1 and a LOD of 24.5 fg mL^-1, as determined by square wave voltammetry from the calibration curves prepared with standards diluted in phosphate buffer. Surface plasmon resonance (SPR) was used as a secondary transducer to evaluate the performance of the Cor a 14-MIP sensor, enabling a linear dynamic range of 100 fg mL^-1- 0.1 μg mL^-1 and a LOD of 18.1 fg mL^-1. The selectivity of the tailored-made Cor a 14-MIP was tested against potentially cross-reactive plant/animal species based on the rebinding affinity (Freundlich isotherm-K_F) of homologues/similar proteins, being further compared with custom-made polyclonal anti-Cor a 14 IgG immunosensor. Results evidenced that the MIP mimics the biorecognition of biological antibodies, presenting higher selectivity (only minor cross-reactivity towards walnut and Brazil nut 2S albumins) than the Cor a 14/anti-Cor a 14 IgG immunosensor. The application of electrochemical Cor a 14-MIP sensor to model mixtures of hazelnut in pasta enabled quantifying hazelnut down to 1 mg kg^-1 (corresponding to 0.16 mg kg^-1 of hazelnut protein in the matrix). To the best of our knowledge, Cor a 14-MIP is the first sensor based on an artificial/synthetic biorecognition platform for the specific detection of hazelnut allergens, while presenting high-performance parameters with demonstrated application in food safety management.