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dc.contributor.authorLin, Chi-Hungen_US
dc.contributor.authorKrisp, Christophen_US
dc.contributor.authorPacker, Nicolleen_US
dc.contributor.authorMolloy, Marken_US
dc.date.accessioned2019-05-29T12:36:41Z
dc.date.available2019-05-29T12:36:41Z
dc.date.issued2018en_US
dc.identifier.issn1874-3919en_US
dc.identifier.doi10.1016/j.jprot.2017.10.011en_US
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.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherElsevieren_US
dc.publisher.placeNetherlandsen_US
dc.relation.ispartofpagefrom68en_US
dc.relation.ispartofpageto75en_US
dc.relation.ispartofjournalJournal of Proteomicsen_US
dc.relation.ispartofvolume172en_US
dc.subject.fieldofresearchBiochemistry and Cell Biology not elsewhere classifieden_US
dc.subject.fieldofresearchBiochemistry and Cell Biologyen_US
dc.subject.fieldofresearchcode060199en_US
dc.subject.fieldofresearchcode0601en_US
dc.titleDevelopment of a data independent acquisition mass spectrometry workflow to enable glycopeptide analysis without predefined glycan compositional knowledgeen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dc.type.codeC - Journal Articlesen_US
gro.facultyOffice of the Snr Dep Vice Chancellor, Institute for Glycomicsen_US
gro.hasfulltextNo Full Text


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