Multilaboratory Collaborative Study of a Nontarget Data Acquisition for Target Analysis (nDATA) Workflow Using Liquid Chromatography-High-Resolution Accurate Mass Spectrometry for Pesticide Screening in Fruits and Vegetables

Jon W. Wong (1) , Jian Wang (2) , James S. Chang (3, 4) , Willis Chow (2) , Roland Carlson (5) , Łukasz Rajski (6) , Amadeo Fernández-Alba (6) , Randy Self (7) , William Cooke (7) , Christopher Lock (7) , Gregory Mercer (7) , Katerina Mastovska (8) , John Schmitz (8) , Lukas Vaclavik (8) , Lingyun Li (9) , Deepika Panawennage (9) , Guo-Fang Pang (10) , Heng Zhou (11) , Shui Miao (11) , Clare Ho (12) , Tony Chong-Ho Lam (12) , Yim-Bun Sze To (12) , Paul Zomer (13) , Yu-Ching Hung (14) , Shu-Wei Lin , Chia-Ding Liao , Danny Culberson (15) , Tameka Taylor (16) , Yuansheng Wu (17) , Dingyi Yu , Poh Leong Lim , Qiong Wu , Jean-Paul Schirlé-Keller (18) , Sheldon Williams , Yoko Johnson , Sara Nason (19) , Michael Ammirata (19) , Brian Eitzer (19) , Michelle Willis (20) , Shane Wyatt , Soyoung Kwon (21, 22) , Nayane Udawatte (22) , Kandalama Priyasantha (22) , Ping Wan (22) , Michael Filigenzi (23) , Erica Bakota (1) , Mark Sumarah (24) , Justin Renaud (24) , Julien Parinet (25) , Ronel Biré (25) , Vincent Hort (25) , Shristi Prakash (26) , Michael Conway , James Pyke (27) , Dan-Hui Dorothy Yang (27) , Wei Jia (28) , Kai Zhang (1) , Douglas Hayward (1)

1 FDA - U.S. Food and Drug Administration
2 CFIA - Canadian Food Inspection Agency
3 NTU - National Taiwan University [Taiwan]
4 ThermoFisher Scientific
5 CDFA - California Department of Food and Agriculture
6 University of Almeria
7 PNNL - Pacific Northwest National Laboratory
8 Eurofins Scientific Group
9 New York State Department of Health [Albany]
10 CAIQ - Chinese Academy of Inspection And Quarantine
11 Shanghai Institute for Food and Drug Control
12 Government Laboratory
13 WUR - Wageningen University and Research [Wageningen]
14 Taiwan Food and Drug Administration
15 NCAGR - North Carolina Department of Agriculture and Consumer Services
16 EPA - US Environmental Protection Agency
17 SFA - Singapore Food Agency
18 MDA - Minnesota Department of Agriculture
19 CAES - The Connecticut Agricultural Experiment Station [New Haven]
20 DGS Virginia - Virginia Division of Consolidated Laboratory Services
21 OISC - Office of Indiana State Chemist
22 Purdue University [West Lafayette]
23 CAHFS - California Animal Health and Food Safety Laboratory System [UC Davis]
24 Agriculture and Agri-Food Canada (London, Ontario)
25 LSAl - Laboratoire de sécurité des aliments de Maisons-Alfort
26 OMIC USA Inc.
27 Agilent Technology [Santa Clara]
28 Shaanxi University of Science and Technology

Nontarget data acquisition for target analysis (nDATA) workflows using liquid chromatography-high-resolution accurate mass (LC-HRAM) spectrometry, spectral screening software, and a compound database have generated interest because of their potential for screening of pesticides in foods. However, these procedures and particularly the instrument processing software need to be thoroughly evaluated before implementation in routine analysis. In this work, 25 laboratories participated in a collaborative study to evaluate an nDATA workflow on high moisture produce (apple, banana, broccoli, carrot, grape, lettuce, orange, potato, strawberry, and tomato). Samples were extracted in each laboratory by quick, easy, cheap, effective, rugged, and safe (QuEChERS), and data were acquired by ultrahigh-performance liquid chromatography (UHPLC) coupled to a high-resolution quadrupole Orbitrap (QOrbitrap) or quadrupole time-of-flight (QTOF) mass spectrometer operating in full-scan mass spectrometry (MS) data-independent tandem mass spectrometry (LC-FS MS/DIA MS/MS) acquisition mode. The nDATA workflow was evaluated using a restricted compound database with 51 pesticides and vendor processing software. Pesticide identifications were determined by retention time (tR, ±0.5 min relative to the reference retention times used in the compound database) and mass errors (δM) of the precursor (RTP, δM ≤ ±5 ppm) and product ions (RTPI, δM ≤ ±10 ppm). The elution profiles of all 51 pesticides were within ±0.5 min among 24 of the participating laboratories. Successful screening was determined by false positive and false negative rates of <5% in unfortified (pesticide-free) and fortified (10 and 100 μg/kg) produce matrices. Pesticide responses were dependent on the pesticide, matrix, and instrument. The false negative rates were 0.7 and 0.1% at 10 and 100 μg/kg, respectively, and the false positive rate was 1.1% from results of the participating LC-HRAM platforms. Further evaluation was achieved by providing produce samples spiked with pesticides at concentrations blinded to the laboratories. Twenty-two of the 25 laboratories were successful in identifying all fortified pesticides (0-7 pesticides ranging from 5 to 50 μg/kg) for each produce sample (99.7% detection rate). These studies provide convincing evidence that the nDATA comprehensive approach broadens the screening capabilities of pesticide analyses and provide a platform with the potential to be easily extended to a larger number of other chemical residues and contaminants in foods.

Mots clés: data-independent acquisition (DIA); liquid chromatography-high-resolution accurate mass (LC-HRAM) spectrometry; nontarget data acquisition for target analysis (nDATA); pesticides; quadrupole Orbitrap (QOrbitrap); quadrupole time-of-flight (QTOF); quick; easy; cheap; effective; rugged; and safe (QuEChERS)

Domaines: Alimentation et Nutrition

Jon W. Wong, Jian Wang, James S. Chang, Willis Chow, Roland Carlson, et al.. Multilaboratory Collaborative Study of a Nontarget Data Acquisition for Target Analysis (nDATA) Workflow Using Liquid Chromatography-High-Resolution Accurate Mass Spectrometry for Pesticide Screening in Fruits and Vegetables. Journal of Agricultural and Food Chemistry, 2021, 69 (44), pp.13200-13216. ⟨10.1021/acs.jafc.1c04437⟩. ⟨anses-03722038⟩