Recently, the Agro-product Processing Quality and Safety Prevention Research Team, Institute of Food Science and Technology (IFST), Chinese Academy of Agricultural Sciences has reported novel data collection strategy based on liquid chromatography coupled with high-resolution mass spectrometry platforms. The proposed strategies have been published in Food Chemistry (IF=9.231, Q1) with the title “Background ions into exclusion list: a new strategy to enhance the efficiency of DDA data collection for high-throughput screening of chemical contaminations in food”.

Background: The frequent irresponsible use of pesticides and veterinary drugs in intensive farming and industrial agriculture leads to their accumulation in the consumed vegetables, fruits and meats, posing potential harm to human health. In addition, mycotoxins are also widely present in foods such as grains, fruits, and vegetables. As these hazardous compounds are prone to undergo modification and degradation inside plant and animals and/or during food processing, more novel toxic chemicals or metabolites are being included since they may contribute to the overall toxicity inside human body. Therefore, the accurate identification of novel chemical hazards in foods has become a challenge in recent years which is expected to remain in the incoming periods in the food safety field.

Scope and approach: Nowadays, Liquid Chromatography tandem High-Resolution Mass Spectrometry (LC-HRMS) has become a popular tool for screening of chemical hazards in food. Data Dependent Acquisition (DDA) is the most adopted HRMS-based acquisition mode, which is suitable for targeted analysis. However, more than 95% of MS/MS spectra obtained in DDA are derived from endogenous compounds in foods, which are useless for screening of potential hazardous materials. And how to acquire more effective MS/MS spectra in DDA is the key approach for high-throughput screening of chemical contaminations in food.

Key findings and conclusions: Herein, a novel data-dependent acquisition (DDA) approach, based on a combination of inclusion list and exclusion list, was proposed to acquire more effective MS/MS spectra. This strategy was successfully applied in a large-scale screening survey to detect 50 mycotoxins in oats, 155 veterinary drugs in dairy milk, and 200 pesticides in tomatoes. Compared with traditional acquisition modes, this new strategy has higher detection rate, particularly at ultra-low concentration by eliminating background influence, thereby generating the MS/MS spectra for more potential hazardous materials instead of matrix interference. Additionally, the obtained MS/MS spectra are simpler and more likely to be traced back than DIA. Moreover, this new strategy would be more comprehensively applied in food safety monitoring with the improvement of HRMS and post-acquisition techniques.

Professor Yi Li and associate professor Shupeng Yang are the co-corresponding authors, and student Haiguang Tan is the first author. This work was supported by the National Science Foundation of China (No.31702296) and the Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2022-IFST).

Link to the paper: https://www.sciencedirect.com/science/article/pii/S0308814622006318

Source: Institute of Food Science and Technology (IFST), CAAS

By Shupeng Yang (yangshupeng@caas.cn)