Proteomics with Enhanced In-Source Fragmentation/Annotation: Applying XCMS-EISA Informatics and Q-MRM High-Sensitivity Quantification
- 11 October 2021
- journal article
- research article
- Published by American Chemical Society (ACS) in Journal of the American Society for Mass Spectrometry
- Vol. 32 (11), 2644-2654
- https://doi.org/10.1021/jasms.1c00188
Abstract
Enhanced in-source fragmentation/annotation (EISA) has recently been shown to produce fragment ions that match tandem mass spectrometry data across a wide range of small molecules. EISA has been developed to facilitate data-dependent acquisition (DDA), data-independent acquisiton (DIA), and multiple-reaction monitoring (MRM), enabling molecular identifications in untargeted metabolomics and targeted quantitative single-quadrupole MRM (Q-MRM) analyses. Here, EISA has been applied to peptide-based proteomic analysis using optimized in-source fragmentation to generate fragmentation patterns for a mixture of 38 peptides, which were comparable to the b- and y-type fragment ions typically observed in tandem MS experiments. The optimal in-source fragmentation conditions at which high-abundance peptide fragments and precursor ions coexist were compared with automated data-dependent acquisition (DDA) in the same quadrupole time-of-flight (QTOF–MS) mass spectrometer, generating a significantly higher fragment percentage of peptides from both singly and doubly charged b- and y-type fragment (b+, y+, b2+, and y2+) ions. Higher fragment percentages were also observed for these fragment ion series over linear ion trap instrumentation. An XCMS-EISA annotation/deconvolution program was developed, making use of the retention time and peak shape continuity between precursor fragment ions, to perform automated proteomic data analysis on the enhanced in-source fragments. Post-translational modification (PTM) characterization on peptides was demonstrated with EISA, producing fragment ions corresponding to a neutral loss of phosphoric acid with greater intensity than observed with DDA on a QTOF–MS. Moreover, Q-MRM demonstrated the ability to use EISA for peptide quantification. The availability of more sophisticated in-source fragmentation informatics, beyond XCMS-EISA, will further enable EISA for sensitive autonomous identification and Q-MRM quantitative analyses in proteomics.Keywords
Funding Information
- National Cancer Institute (U01 CA235493)
- National Institute on Drug Abuse (P01 DA026146)
- National Institute of Mental Health (P30 MH062261)
- National Institute of General Medical Sciences (R35 GM130385)
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