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Enhancing Chimeric Fragmentation Spectra Deconvolution Using Direct Infusion-Tandem Mass Spectrometry Across
Arina Ivanova1, Wei Tang2, Carsten Simon1
1Department of Biogeochemical Processes, Max Planck Institute for Biogeochemistry, Jena, Germany.
Rationale:
Direct infusion mass spectrometry (DI-MS) is a rapid analytical technique widely used in omics research and other fields. However, the complexity of DI-MS spectra frequently leads to co-fragmentation of analytes with similar m/z, resulting in chimeric fragmentation spectra that complicate compound identification. A DI-based tandem mass spectrometric method (DI-MS2), which modulates the intensity of precursors and fragments by the stepwise movement of the quadrupole isolation window, has been shown to successfully deconvolute chimeric fragmentation spectra. Yet, its applicability to different instruments and optimisation has not been evaluated.
Method:
We evaluate the performance of DI-MS2 on two high-resolution instruments: a linear ion trap-Orbitrap (LIT-Orbitrap) and a quadrupole-Orbitrap (Q-Orbitrap). We examined the impact of six instrumental settings, including mass resolving power, isolation window width, step size between MS2 scans, number of microscans, collision energy and automatic gain control (AGC) target, on the analysis of isobaric mixtures with varying m/z differences.
Results:
The LIT-Orbitrap consistently achieved high-quality chimeric spectra deconvolution with an average similarity score of 0.98 despite unexpected intensity modulation patterns. The Q-Orbitrap provided four times faster measurements but showed more variable results: It achieved a similarity score of 0.96 for isobars with a m/z difference larger than 0.02, but only 0.56 for m/z differences of 0.006.
Conclusions:
These findings indicate that the DI-MS2 is a robust and flexible method applicable across different MS platforms, though the Q-Orbitrap may be less suited for highly complex samples with multiple peaks per nominal mass. This highlights the potential of the DI-MS2 for structural elucidation of complex biological mixtures. Additionally, we provide initial setting optimisation guidelines to improve spectra deconvolution and measurement speed.
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