Maximizing Glycoproteomics Results through an Integrated Parallel Accumulation Serial Fragmentation Workflow.
Publication year
2024Source
Analytical Chemistry, 96, 22, (2024), pp. 8956-8964ISSN
Publication type
Article / Letter to editor
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Organization
Neurology
Human Genetics
Analytical Chemistry
Journal title
Analytical Chemistry
Volume
vol. 96
Issue
iss. 22
Page start
p. 8956
Page end
p. 8964
Subject
Analytical Chemistry; Human Genetics - Radboud University Medical Center; Human Genetics - Radboud University Medical Center - DCMN; Neurology - Radboud University Medical Center - DCMNAbstract
Glycoproteins play important roles in numerous physiological processes and are often implicated in disease. Analysis of site-specific protein glycobiology through glycoproteomics has evolved rapidly in recent years thanks to hardware and software innovations. Particularly, the introduction of parallel accumulation serial fragmentation (PASEF) on hybrid trapped ion mobility time-of-flight mass spectrometry instruments combined deep proteome sequencing with separation of (near-)isobaric precursor ions or converging isotope envelopes through ion mobility separation. However, the reported use of PASEF in integrated glycoproteomics workflows to comprehensively capture the glycoproteome is still limited. To this end, we developed an integrated methodology using timsTOF Pro 2 to enhance N-glycopeptide identifications in complex mixtures. We systematically optimized the ion optics tuning, collision energies, mobility isolation width, and the use of dopant-enriched nitrogen gas (DEN). Thus, we obtained a marked increase in unique glycopeptide identification rates compared to standard proteomics settings, showcasing our results on a large set of glycopeptides. With short liquid chromatography gradients of 30 min, we increased the number of unique N-glycopeptide identifications in human plasma samples from around 100 identifications under standard proteomics conditions to up to 1500 with our optimized glycoproteomics approach, highlighting the need for tailored optimizations to obtain comprehensive data.
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- Academic publications [244127]
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- Faculty of Medical Sciences [92874]
- Faculty of Science [37029]
- Open Access publications [105172]
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