High-throughput screening tools for a reinforced chemical safety surveillance of food – SENTINEL
SENTINEL: High-throughput screening tools for a reinforced chemical safety surveillance of food
The European Parliament has called on Member States to strengthen their food safety control mechanisms by 2019. In July 2018, the French government has launched the SCA platform to strengthen the coverage and the efficiency of the surveillance. To reach this objective, it is necessary for both food safety authorities and industry to get high-throughput and cost-effective screening methods to monitor priority hazards throughout the food chain.
Three additional options for the rapid and cost-effective detection of chemical contaminants
To overcome the limitations and strengthen the existing monitoring system, INRAE is developing with other national players (IFIP, CNRS, CEA, ONIRIS, INRIA, University of Perpignan) three additional options for the rapid and cost-effective detection of chemical contaminants (objective 1): 1) The “sample pooling” option. It is a question of compensating for the cost and cumbersomeness of the methods for quantifying contaminants by no longer using them on an individual sample but on a mixture of n samples. 2) The “biosensor” option. Coupled with ad hoc extraction methods, they replace conventional control methods with field technologies. 3) The “exposure markers” option. Rather than the contaminant, it is a question of detecting exposure markers that are more easily detectable and therefore accessible to fast and less expensive sensors (e.g. electronic nose). Each of the three options is the subject of a multi-criteria and multi-stakeholder cost-benefit analysis to assess their relevance (objective 2).
Taking the monitoring of polychlorinated biphenyls (PCBs) in meat as a model, the first objective of SENTINEL is to develop a panel of 3 complementary tools. Recent advances in analytical sciences enable to meet this challenge in SENTINEL via three options: Tool N°1 ) coupling highly-sensitive mass spectrometry-based methods with novel sample pooling strategies, Tool N°2 ) coupling up-to-date contaminant-targeted biosensors with quick, efficient and cheap extraction methods, and Tool N°3) designing sensors targeted on the detection of markers of animal exposure to contaminants discovered by omic approaches.
In order to improve the technological transfer from research to industry and to food safety authorities (objective 2), the project will experiment an original two-stage methodology. First, the conditions of SENTINEL tool implementation will be defined on the basis of the most probable evolutions of the French meat supply chain. Second, the cost-benefit analysis (economic, regulatory, social and public health impacts) of these implementation scenarios will be assessed to support future decisions for food chain chemical safety surveillance.
The first 18 months of the project have already made it possible to show the interest of the sample pooling strategy (tool 1) based on a dual approach aimed on the one hand at showing the technical feasibility of carrying out reproducible homogeneous mixtures of 2 to 200 samples and on the other hand to study by numerical simulation the gains corresponding to the dimensioning of the pooling (n) in terms of number of analyses. They also enabled the consortium to validate the feasibility of producing and evaluating the most promising PCB aptasensors (tool 2) proposed by the literature. Finally, an animal experiment made it possible to produce samples of animal tissues and fluids contaminated by different types of PCBs (DL or NDL) at different doses. The volatolome and the proteome of the animal liver could be analyzed by GC-MS and LC-MS/MS, respectively, with a view to searching for markers of exposure to PCBs. In parallel with this work on the tools, an analysis of the current state of the French pig sector and of the health monitoring system was carried out. Six scenarios for the future of the sector have been proposed with a view to an upcoming cost-benefit analysis of the implementation of the 3 tools proposed by the project.
The next few months should make it possible to quickly refine and develop the «sample pooling« proof of concept and extend its scope to other contaminants / food pairs within the framework of the H2020 SAFFI project. They should also lead to further development of PCB aptasensors, taking into account their compatibility with the procedures that can be envisaged to allow their extraction from the meat matrix. The coming months will also allow i) to broaden the scope of marker research to new omics techniques (metabolomics by NMR), to new matrices (plasma, caeca) and to an in vitro framework (culture of chicken hepatocytes), ii) integrating all the results using multi-table statistical approaches and bioinformatics approaches, and iii) developing and/or validating sensor technologies (notably electronic noses) to measure these markers. Finally, the next few months will also make it possible to select the two most plausible scenarios for the future of the pork sector in order to carry out a multi-actor cost-benefit analysis of the implementation of the 3 tools proposed by the project.
The first highlights of the project are being published with an article submitted on scenario building, several conferences at national (2) and international (3) congresses, popularization actions (30).
The European Parliament has called on Member States to strengthen their food safety control mechanisms by 2019. In July 2018, the French government has launched a platform to strengthen the coverage and the efficiency of the surveillance. To reach this objective, it is necessary for both food safety authorities and industry to get high-throughput and cost effective screening methods to monitor priority hazards throughout the food chain. Over the past few years, there has been substantial progress in microbiological safety and fast and cheap PCR-based methods are now currently used by regulatory authorities for inspection and by manufacturers for self-monitoring. On the chemical safety side, technical and societal transition is lagging behind. The current French system is reliant on : 1/ Surveillance and inspection plans which are used to detect non-conformities i.e. above the maximum level (ML) for a given contaminant /food couple and 2/ National total diet studies which are implemented every 5 years to assess the risk related to the global chronic dietary exposure of consumers to sub-ML doses of contaminants. Due to the very low ML of most priority contaminants, both approaches revolves mainly around very sensitive reference methods which are often expensive and low-throughput, thus limiting frequency and scope of surveillance by food safety authorities and dissuading routine preventive monitoring by the industry.
Starting with the surveillance of PCBs in meat as a model issue, SENTINEL's primary objective is to develop a panel of three complementary high-throughput, sensitive, cost-effective screening tools 1/ for strengthening the detection of non-conformities, but also 2/ for monitoring these contaminants at relevant sub-ML levels. When non-conformities (>ML) are detected, confirmatory analyses by approved laboratories will be requested prior to corrective action whereas detection above targeted sub-ML levels will lead to preventive actions carried on the food chain. With the final aim to better control consumer dietary exposure to these contaminants, the implementation of these novel tools should thus boost the screening of positive samples by food safety authorities (top-down approach) and permit sample self-monitoring by the agri-food industry (bottom-up approach). Recent advances in analytical sciences enable to meet this challenge in SENTINEL via three options: i) coupling highly-sensitive mass spectrometry-based methods with novel sample pooling strategies ii) coupling up-to-date contaminant-targeted biosensors with quick, efficient and cheap extraction methods and iii) designing sensors targeted on the detection of markers of animal exposure to contaminants discovered by omic approaches.
The second objective is to determine several practical and plausible implementation scenarios for the new tools, and to anticipate the main costs and benefits of their meat sector implantation. The project will experiment an original two-stage methodology, in order to improve the technological transfer from research to industry and to food safety authorities. First, the conditions of SENTINEL tool implementation will be defined on the basis of the most probable evolutions of the French meat supply chain. Second, the cost-benefit analysis (economic, regulatory, social, public health impacts) of these implementation scenarios will be performed to support future decisions for strengthening the surveillance of food chain chemical safety.
SENTINEL is a multidisciplinary collaborative research project that will prompt developments in the fields of residue chemistry, biosensors, e-nose, omics, chemometrics, bioinformatics, social and consumer sciences, risk assessment and knowledge engineering. SENTINEL involves 11 partners from 4 scientific institutes (INRA, INRIA, IRSTEA, CNRS), 2 educational and research institutions (Perpignan University, ONIRIS) and 1 technical institute (IFIP).
Monsieur Erwan Engel (Qualité des Produits Animaux)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
IFIP IFIP- INSTITUT DU PORC
INRIA GraphIK UMR IATE - Equipe GraphIK
MIA INRA UMR0518 MIA Mathématiques et Informatique Appliquées
BOA Biologie des Oiseaux et Aviculture
SyMMES Systèmes Moléculaires et nano Matériaux pour l'Energie et la Santé (SyMMES)
StatSC Oniris, Unité de Statistique Sensométrie et Chimiométrie
Alimentation et Sciences Sociales
IRSTEA Institut National de Recherche en Sciences et Technologies pour l'Environnement et l'AgricultureS AGRICOLES
QuaPA Qualité des Produits Animaux
INRA TOXALIM - AXIOM Institut National de la Recherche Agronomique Centre Toulouse - Occitanie
Help of the ANR 596,874 euros
Beginning and duration of the scientific project: March 2020 - 48 Months