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dc.contributor.authorLin, Chi-Hung
dc.contributor.authorKrisp, Christoph
dc.contributor.authorPacker, Nicolle H
dc.contributor.authorMolloy, Mark P
dc.date.accessioned2019-05-29T12:36:41Z
dc.date.available2019-05-29T12:36:41Z
dc.date.issued2018
dc.identifier.issn1874-3919
dc.identifier.doi10.1016/j.jprot.2017.10.011
dc.identifier.urihttp://hdl.handle.net/10072/380546
dc.description.abstractGlycoproteomics investigates glycan moieties in a site specific manner to reveal the functional roles of protein glycosylation. Identification of glycopeptides from data-dependent acquisition (DDA) relies on high quality MS/MS spectra of glycopeptide precursors and often requires manual validation to ensure confident assignments. In this study, we investigated pseudo-MRM (MRM-HR) and data-independent acquisition (DIA) as alternative acquisition strategies for glycopeptide analysis. These approaches allow data acquisition over the full MS/MS scan range allowing data re-analysis post-acquisition, without data re-acquisition. The advantage of MRM-HR over DDA for N-glycopeptide detection was demonstrated from targeted analysis of bovine fetuin where all three N-glycosylation sites were detected, which was not the case with DDA. To overcome the duty cycle limitation of MRM-HR acquisition needed for analysis of complex samples such as plasma we trialed DIA. This allowed development of a targeted DIA method to identify N-glycopeptides without pre-defined knowledge of the glycan composition, thus providing the potential to identify N-glycopeptides with unexpected structures. This workflow was demonstrated by detection of 59 N-glycosylation sites from 41 glycoproteins from a HILIC enriched human plasma tryptic digest. 21 glycoforms of IgG1 glycopeptides were identified including two truncated structures that are rarely reported. Significance: We developed a data-independent mass spectrometry workflow to identify specific glycopeptides from complex biological mixtures. The novelty is that this approach does not require glycan composition to be pre-defined, thereby allowing glycopeptides carrying unexpected glycans to be identified. This is demonstrated through the analysis of immunoglobulins in human plasma where we detected two IgG1 glycoforms that are rarely observed.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherElsevier
dc.publisher.placeNetherlands
dc.relation.ispartofpagefrom68
dc.relation.ispartofpageto75
dc.relation.ispartofjournalJournal of Proteomics
dc.relation.ispartofvolume172
dc.subject.fieldofresearchBiochemistry and Cell Biology not elsewhere classified
dc.subject.fieldofresearchBiochemistry and Cell Biology
dc.subject.fieldofresearchPlant Biology
dc.subject.fieldofresearchcode060199
dc.subject.fieldofresearchcode0601
dc.subject.fieldofresearchcode0607
dc.titleDevelopment of a data independent acquisition mass spectrometry workflow to enable glycopeptide analysis without predefined glycan compositional knowledge
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyOffice of the Snr Dep Vice Chancellor, Institute for Glycomics
gro.hasfulltextNo Full Text
gro.griffith.authorLin, Chi-Hung
gro.griffith.authorPacker, Nicki


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