Validation of a DNA-based method for bread wheat contamination detection in pasta

Abstract

Food quality and safety, including food traceability and authenticity, have become crucial in the last decades. Today, molecular and genetic progress can support the agri-food industry, due to the improvement of new analytical tools. Among the available applications, DNA-based methods can detect the presence of a particular species or variety along the food supply chain, verify the genetic identity of food and feed ingredients and detecting the presence of contaminating organisms, thus becoming an essential tool to study patterns, causes, and risk factors of diseases and outbreaks. As a consequence, genetic analysis has become increasingly popular even among non-specialists and highly beneficial for consumers, agricultural farmers, governments, and the private sector (Reid, O’Donnell, and Downey 2006). In this framework, the research developed in this thesis arises by active collaboration between the private company Barilla G. & R. Fratelli S.p.A., the public research institute CREA-GB (Consiglio per la Ricerca in agricoltura e l'analisi dell Economia Agraria) and Universita Cattolica del Sacro Cuore, to develop a set of DNA-based methods to improve the traceability and authenticity of plant and microbial species and durum wheat varieties applicable from farm to fork. Following these aims, the research developed in this thesis includes: 1. The optimization and validation of qPCR assay for the discrimination of plant species along the pasta production chain through the organization of a ring test involving nine Italian public and private laboratories. The results obtained in this study were published in the Journal of Cereal Science (Chapter 2); 2. The discrimination of durum wheat varieties by selecting SSRs and DarT molecular markers as reliable methods for variety fingerprinting (Chapter 3). The results confirm the sensitivity of the method and the feasibility to 7 protect the food industry from fraud and ensure the consumer a certified pasta quality; 3. The application of the Barcoding technique and the development of qPCR assay for the identification and quantification of field fungi (Fusarium, Alternaria, Michrodochium, Cochliobolus spp.) and saprophytic fungi (Aspergillus, Penicillium, Rhizopus spp) along the wheat chain (Chapter 3). The sensitivity of the method was investigated by inoculating potted durum wheat plants at full anthesis and wheat kernels (pre and postharvest trials). The DNA-based methods demonstrate a key role in pathogen detection and the application in several points of the wheat chain (e.g., for control of both locally and imported grains, for storage lots, to evaluate the environmental risk associated with grain powder for farmers and workers); 4. The optimization of Viability q-PCR (V-qPCR) for the discrimination of dead and alive Bacillus cereus, a spore-forming bacteria (Chapter 4). The results of PMAxx, combined with qPCR, have demonstrated the selective discrimination of B.cereus viable cells, with no false-positive signals determined by dead cells, a peculiar aspect of thermally treated food; 5. The comparison of two DNA extraction kits (FastDNA® SPIN Kit for Soil – MB and NucleoSpin Tissue - Macherey Nagel) by detecting B.cereus spores in basil pesto sauce, selected as a model food matrix. Despite the limit of detection (LOD) achieved (respectively 1.8x102 spores/gr by using Fast DNA TM SPIN and 2.7 x 105 spores/gr by using NucleoSpin®), the principal challenge remains the spores' DNA extraction from the complex matrix. Lastly, the results obtained during the doctoral research project were globally discussed (Chapter 5).