Seed storage allergens tackled via next-generation research assistant

Abstract

The expanding consumption of plant proteins in the diet to overcome the environmental issues associated with animal proteins is increasing the incidence of food-induced allergic reactions. One of the 21st-century research drivers in agriculture sciences is the development and validation of concrete approaches for modulating the expression of allergenic proteins in crops before harvesting. The increasing incidence of plant food allergies is primarily induced by seed storage proteins that clinicians are experiencing recently because of the more predominant use of plant-derived proteins in the food industry. Increased availability of high-throughput technologies has generated an ever-growing number of omics data, allowing us to have better structural knowledge of SSPs and molecular properties that can inform the allergenicity assessment. The recent systems for targeted genome engineering, without double-strand DNA breaks, allow the introduction of precise modifications directly into commercial plant species. Artificial intelligence is significantly transforming scientific research across every stage, assisting scientists, processing large-scale data, making predictions, automating tasks. During this epochal change, marked by the encounter between artificial intelligence and synthetic biology, a next-generation research assistant (NGA) is coming alive. Here, we propose a new conceptual vision to facilitate and speed up the editing of cross-reactivity sites to obtain hypoallergenic cultivars and avoid pleiotropic effects. Finally, we discuss the potential applications of this new way to conceive the research. NGA may be undoubtedly capable of managing the evolution of SPP allergies through the prediction of novel epitopes, as well as the prediction of immunological response mechanisms.