Methodology for the Identification of Pesticide Metabolites in Complex Matrices Using UPLC-ToF/MSE and the UNIFI Scientific Information System

Significance of the Topic

Comprehensive identification of pesticide metabolites in environmental and food matrices is crucial for understanding their fate, potential toxicity, and regulatory compliance. High-resolution UPLC-MS E methodologies, combined with advanced informatics, deliver detailed precursor and fragment ion data in a single experiment, enabling rapid and robust assessment of agrochemical metabolism without prior knowledge of analytes.

Objectives and Study Overview

This study aimed to demonstrate an integrated workflow for identifying atrazine and its degradation products in soil extracts. Using spiked samples, the methodology highlighted:

• Efficient sample preparation and chromatographic separation via UPLC
• Simultaneous acquisition of full-scan precursor and product ions using MS E
• Automated data processing and metabolite prioritization within the UNIFI Scientific Information System

Methodology and Instrumentation

Soil samples were extracted with acetonitrile and water, followed by salting out and cleanup before spiking with atrazine and its metabolites. Separation employed an ACQUITY UPLC I-Class system with an HSS T3 column (2.1 × 100 mm, 1.8 μm) at 45 °C, using a gradient of water and acetonitrile with 10 mM ammonium formate, 0.6 mL/min flow rate, and 1 μL injection. Mass analysis used a Xevo G2-XS QTof in positive ESI mode, collecting low (2 eV) and high (17–45 eV) collision energy data across m/z 50–950 with 0.15 s scan time.

Main Results and Discussion

The UNIFI workflow identified key atrazine metabolites, including 2-hydroxyatrazine, desethyl atrazine, desisopropyl atrazine, and desethyl-desisopropyl atrazine, by applying over 100 biotransformation rules. Key features included:

• Binary Compare distinguishing metabolites unique to spiked samples, revealing Cl→OH transformation for 2-hydroxyatrazine
• Metabolite Hierarchy Map visualizing structural relationships around the parent compound
• Transformation Localization pinpointing modified sites via color-coded spectral overlays
• TrendPlot monitoring relative abundance changes for kinetic studies
• Common Fragment Search extracting related compounds sharing diagnostic ions (e.g., m/z 79.005)

Benefits and Practical Applications

This integrated UPLC-MS E and UNIFI approach yields:

• Increased throughput and resolution compared to traditional HPLC methods
• Enhanced confidence in metabolite identification through simultaneous precursor and fragment acquisition
• Automated, customizable workflows reducing manual data review
• Comprehensive reporting tools for regulatory submissions and internal documentation

Future Trends and Applications

Advancements in high-resolution mass spectrometry and informatics are expected to:

• Expand libraries of custom biotransformations and predicted metabolites
• Integrate machine learning for more accurate spectral interpretation and unknown compound discovery
• Enhance in situ and real-time monitoring of environmental samples
• Facilitate large-scale agrochemical screening and non-targeted environmental metabolomics

Conclusion

The presented methodology effectively identified atrazine metabolites in complex soil matrices using UPLC-MS E and the UNIFI platform. The streamlined workflow supports robust metabolite characterization, meets regulatory requirements, and can be adapted to a variety of environmental fate studies for pesticide registration and safety assessment.

References

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