CURRENT PROJECTS
FOOD SAFETY
Considering the structural diversity of food contaminants and the many potential interactions with food components, we have proposed an approach based on liquid chromatography coupled to hybrid quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS) as a new tool to profile contaminants in food matrices. The MS-based non-targeted approach relies on three major consecutive analytical steps: sample preparation, followed by LC-QTOF-MS and concluding with data processing. Our research therefore aims to develop novel non-targeted tools to characterize contaminant mixtures in complex matrices and estimate dietary exposure for consumers.
Examples of current projects:
Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Program (PI): Development of a mass spectrometry-based foodomics approach to characterize the fate of selected antibiotic residues during food processing and storage. 2017-2023.
Canadian Institutes of Health Research (CIHR): Environments and Health: Intersectoral Prevention Research (Agri-Food) (co-investigator): Endocrine Disrupting Chemicals: Towards Responsible Replacements. 2016-2023 - PI: Dr. B. Hales (McGill); co-investigators: 20 other researchers.
FOOD
AUTHENTICITY
Food fraud (including substitution, adulteration or mislabeling) is often synonymous with economic impacts on the buyers (consumers and food industry), but may also result in adverse health effects for the consumers. While conventional food authenticity testing has relied on a limited suite of markers, fingerprinting based on thousands of signals has now emerged as a more effective & robust approach to track food fraud. Indeed, fingerprinting has the potential to investigate a wider range of quality attributes simultaneously; and chemical fingerprints are virtually impossible to imitate for fraudsters due to their complexity.
Examples of recent projects:
Natural Sciences and Engineering Research Council of Canada (NSERC) Engage Program (PI): Non-targeted screening of maple syrup based on LC-HRMS and FTIR: a proof-of-concept. 2018-2019.
Natural Sciences and Engineering Research Council of Canada (NSERC) Alliance Program (PI): Development of a standard food authenticity testing workflow for honey using non-targeted LC/MS analysis. 2022-2024.
POLLUTION&
AGRIFOOD SYSTEMs
Thousands of environmental pollutants are estimated to contaminate our water and food. At the moment, most testing laboratories run targeted analyses, i.e. they analyse and record data for only a limited suite of target contaminants in each sample. This conventional approach has provided significant data. However, such conventional monitoring and assessment on an individual compound level is largely inefficient to understand the overall potential impact of thousands of pollutants. Recently, the chemical risk assessment community has highlighted the need for innovative tools. Through key case studies, we demonstrated how non-targeted analysis can be used to detect and track unknown or unexpected pollutants in aquatic and soil systems.
Examples of recent projects:
Natural Sciences and Engineering Research Council of Canada (NSERC) CREATE (co-investigator): Advanced Technological Training network on the risk and remediation of Pollution in URban Environments (PURE CREATE). 2019-2025 - PI: Dr. K. Wilkinson (U. de Montreal); co-investigators: 8 other researchers.
Projet structurant (MAPAQ). Utilisation des matières résiduelles fertilisantes (MRF) en agriculture. 2021-2024. PI: Dr. L. Khiari; co-investigators: Drs. J. Whalen, D. Potvin: S. Bayen, S. Sauvé, R. Legros, A. Karam, S. Hamoudi, C. Kallenbach, G. Clark.
Fonds de recherche du Québec, Programme AUDACE (PI). Cartographie de l’exposition aux perturbateurs endocriniens dans l’air extérieur urbain. 2021-2022. co-investigators: Drs. G. Delbes, P. Apparicio.
DATA
TREATMENT
Non-targeted fingerprinting is promising but results are not always replicable due to the different approaches in sample preparation, data acquisition, analysis and processing being used, thus limiting this technique to be fully deployed in a routine setting. The key reasons found by research in our laboratory why results differ in NTA fingerprinting is largely due to 1) lack of standard protocol in performing NTA in sample preparation and instrument analysis and 2) lack of standardization & protocol in data processing of large datasets. We are studying the impact of conventional and emerging algorithms on the outcome of the chemical analysis.
Examples of recent projects:
Canada Foundation for Innovation, John R. Evans Leaders Fund (PI): A novel foodomics approach to chemical food safety: application to fish and seafood. 2016-2021.
Agilent Thought Leader Award (PI): Development of a standard food authenticity testing workflow for honey using non-targeted LC/MS analysis. 2021-24
