3D bio-printing-based vascular-microtissue electrochemical biosensor for fish parvalbumin detection

A novel 3D bio-printing vascular microtissue biosensor was developed to detect fish parvalbumin quickly. The graphite rod electrode was modified with gold and copper organic framework (Cu-MOF) to improve the sensor properties. Polydopamine-modified multi-wall carbon nanotubes (PDA-MWCNT) were mixed with gelatin methacryloyl (GelMA) to prepare a conductive hydrogel. The conductive hydrogel was mixed with mast cells and endothelial cells to produce a bio-ink for 3D bioprinting. High throughput and standardized preparation of vascular microtissue was performed by stereolithography 3D bioprinting. The vascular microtissue was immobilized on the modified electrode to construct the microtissue sensor. The biosensor's peak current was positively correlated with the fish parvalbumin concentration, and the detection linear concentration range was 0.1 ∼ 2.5 μg/mL. The standard curve equation was IDPV(μA) = 31.30 + 5.46 CPV(μg/mL), the correlation coefficient R2 was 0.990 (n = 5), and the detection limit was 0.065 μg/mL. These indicated a biomimetic microtissue sensor detecting fish parvalbumin has been successfully constructed.

Standardization of a Mass Spectrometry-Based Workflow for Food Allergen Quantification

In this chapter, the analytical workflow typically used for the development and validation of an analytical method tailored to food allergen detection and quantification is presented. The main steps defining the workflow are herein described and commented with specific notes about the critical issues that can be faced and common solutions to be adopted. References to guidelines and/or recommendation available from official bodies, as well as main papers from international consortia operating on the specific research field, are also reported, whenever possible. As such, this chapter may represent a practical guide to drive method development in the standardization of analytical methods for food allergen detection.

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.

A reference method for determining the total allergenic protein content in a processed food: the case of milk in cookies as proof of concept

The establishment of a reference method for the determination of the allergen protein content in a processed food material has been explored. An analytical approach was developed to enable the comparability of food allergen measurement results expressed in a decision-relevant manner. A proof of concept is here presented, resulting in quantity values for the common measurand, namely ‘mass of total allergen protein per mass of food’. The quantities are determined with SI traceability to enable the comparability of reported results. A method for the quantification of total milk protein content in an incurred baked food at a concentration level clinically relevant is presented. The strategy on how to obtain the final analytical result is outlined. Challenges associated with this method are discussed, in particular the optimal extraction of the marker proteins, the complete digestion and release of the peptides in an equimolar fashion, the use of conversion factors to translate the amount of measured proteins into total milk protein and the estimation of the uncertainty contributions as well as of the combined uncertainty of the final result. The implementation of such a reference method for the determination of the total allergen content in a processed food is an important step, which will provide comparable measurement data of relevance to risk assessors.