Research on Screening Methods of Pesticides and Their Transformation Products Based on Omics，Machine Learning and Biotransformation Technology

FENG Chao; LU Da-sheng; WANG Guo-quan; XU Qian; QIU Xin-lei; JIN Yu-e; CHEN Yu-hang

doi:10.19969/j.fxcsxb.23062702

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Research on Screening Methods of Pesticides and Their Transformation Products Based on Omics，Machine Learning and Biotransformation Technology

Scientific Papers | 更新时间：2023-10-18

- Research on Screening Methods of Pesticides and Their Transformation Products Based on Omics，Machine Learning and Biotransformation Technology
- Journal of Instrumental Analysis Vol. 42, Issue 10, Pages: 1211-1220(2023)
- 作者机构：
  
  上海市疾病预防控制中心，国家环境保护新型污染物环境健康影响评价重点实验室，上海 200336
- 作者简介：
- 基金信息：
- DOI：10.19969/j.fxcsxb.23062702
  CLC：
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冯超,卢大胜,汪国权等.基于组学、机器学习和生物转化技术的农药及其转化物筛查方法研究[J].分析测试学报,2023,42(10):1211-1220.

FENG Chao,LU Da-sheng,WANG Guo-quan,et al.Research on Screening Methods of Pesticides and Their Transformation Products Based on Omics，Machine Learning and Biotransformation Technology[J].Journal of Instrumental Analysis,2023,42(10):1211-1220.
冯超,卢大胜,汪国权等.基于组学、机器学习和生物转化技术的农药及其转化物筛查方法研究[J].分析测试学报,2023,42(10):1211-1220. DOI： 10.19969/j.fxcsxb.23062702.

FENG Chao,LU Da-sheng,WANG Guo-quan,et al.Research on Screening Methods of Pesticides and Their Transformation Products Based on Omics，Machine Learning and Biotransformation Technology[J].Journal of Instrumental Analysis,2023,42(10):1211-1220. DOI： 10.19969/j.fxcsxb.23062702.

摘要

该研究基于液相色谱-高分辨质谱联用技术，针对不同食品基质，通过标准化的样品提取方法，低歧视的仪器采集方法，以及组学、机器学习和生物转化等技术的融合，建立了各类农药及其转化物的靶向和拟靶向数据筛查方法。实验结果表明，不同农药在多种基质中的回收率为80%~120%。样本中农药的MS,2,特征能在基于特定列表（Inclusion list）的数据依赖性扫描（DDA）方式下兼顾检出率和特异性。靶向方法基于数据库的保留时间（RT）、MS,1,（,m,/,z,偏差、同位素轮廓、加合形态、源内裂解）和MS,2,（二级碎片）等多元参数匹配，可以高置信度地鉴定阳性物质。同时，拟靶向方法在人工智能（AI）预测模型的帮助下，在菊花茶中发现8种疑似的农药转化物，这些特征在MS,1,匹配的基础上进行MS,2,的预测和RT的过滤，并通过体外肝微粒生物合成获得无商业化标准品的农药转化物的质谱特征，确证疑似结果。该方法实现了农药及其转化物的高通量和高特异性的筛查，适用于各类食品基质的快速筛查。

Abstract

Based on liquid chromatography-high resolution mass spectrometry，this study established target and suspect screening methods of various pesticides and their transformation products for different food matrices through standardized sample extraction methods，low discrimination instrument analysis methods，and the integration of technologies such as omics，machine learning and biotransformation. The experimental results show that the recoveries of different pesticides in various matrices ranged from 80% to 120%. The MS,2, of pesticides in samples can balance both detection rate and specificity in data-dependent scanning（DDA） mode with inclusion list. The target screening method is based on the matching of multiple parameters such as retention time（RT），MS,1,（,m,/,z, deviation，isotope profile，addition form，in-source cleavage） and MS,2,（secondary fragment） in the database，which can identify positive substances with high confidence. Meanwhile，with the help of artificial intelligence（AI） prediction model，eight suspected pesticide transformants were found in chrysanthemum tea. Based on the MS,1, matching，these suspected features are further filtered by predicted MS,2, and RT. The MS,2, characteristics of these transformation products without commercial standard were obtained by in vitro liver microsomes biosynthesis，which confirmed the suspected results. The method realized high throughput and high specificity screening of pesticides and their transformation products，which was suitable for rapid screening of various food substrates.

关键词

农药农药转化物拟靶向筛查机器学习生物转化

Keywords

pesticidepesticide transformation productsuspect screeningmachine learningbiotransformation

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