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Comparison of Compound Identification Tools Using Data Dependent and Data Independent High-Resolution Mass
Rosalie Nijssen1, Marco H Blokland1, Robin S Wegh1
1Wageningen Food Safety Research, Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands.
Evaluating four high-resolution mass spectrometry (HRMS) identification tools for pesticide and drug metabolite analysis revealed that mzCloud performed best for data-dependent acquisition (DDA) spectra. MSfinder showed the highest success rate for data-independent acquisition (DIA) spectra, though overall identification rates were lower for DIA.
Area of Science:
- Analytical Chemistry
- Environmental Toxicology
- Metabolomics
Background:
- Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is crucial for suspect screening (SS) and non-target screening (NTS).
- Accurate compound identification in SS/NTS, particularly with data-independent acquisition (DIA), remains a significant challenge.
- Evaluating HRMS spectral identification tools is essential for improving analytical accuracy in complex matrices.
Purpose of the Study:
- To assess the performance of four HRMS spectral identification tools.
- To compare identification capabilities for data-dependent acquisition (DDA) and DIA HRMS spectra.
- To evaluate tool performance on pesticides, veterinary drugs, and their metabolites in solvent standards and spiked feed extract.
Main Methods:
- Generated DDA and DIA HRMS spectra for 32 pesticides, veterinary drugs, and metabolites.
- Utilized four identification tools: mzCloud, MSfinder, CFM-ID, and Chemdistiller.
- Evaluated identification success rates in both solvent standards and a complex spiked feed matrix.
Main Results:
- For DDA spectra, mzCloud achieved the highest identification rates (84-88%).
- MSfinder demonstrated the best performance for DIA spectra (72-75%), outperforming other tools.
- Identification success rates were generally lower for DIA compared to DDA, especially with mzCloud and Chemdistiller in the spiked feed extract.
Conclusions:
- While DDA spectra generally yield higher identification success rates, DIA spectra can be effectively used for compound annotation with specific software tools like MSfinder.
- The complexity of DIA spectra presents greater challenges for direct spectral matching compared to DDA.
- The choice of identification tool is critical and depends on the acquisition method (DDA vs. DIA) and sample matrix.
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