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dc.contributor.authorAshwood, Christopher
dc.contributor.authorPratt, Brian
dc.contributor.authorMacLean, Brendan X
dc.contributor.authorGundry, Rebekah L
dc.contributor.authorPacker, Nicolle H
dc.date.accessioned2021-06-08T00:46:59Z
dc.date.available2021-06-08T00:46:59Z
dc.date.issued2019
dc.identifier.issn0003-2654
dc.identifier.doi10.1039/c9an00486f
dc.identifier.urihttp://hdl.handle.net/10072/404972
dc.description.abstractPorous graphitized carbon (PGC) based chromatography achieves high-resolution separation of glycan structures released from glycoproteins. This approach is especially valuable when resolving structurally similar isomers and for discovery of novel and/or sample-specific glycan structures. However, the implementation of PGC-based separations in glycomics studies has been limited because system-independent retention values have not been established to normalize technical variation. To address this limitation, this study combined the use of hydrolyzed dextran as an internal standard and Skyline software for post-acquisition normalization to reduce retention time and peak area technical variation in PGC-based glycan analyses. This approach allowed assignment of system-independent retention values that are applicable to typical PGC-based glycan separations and supported the construction of a library containing >300 PGC-separated glycan structures with normalized glucose unit (GU) retention values. To enable the automation of this normalization method, a spectral MS/MS library was developed of the dextran ladder, achieving confident discrimination against isomeric glycans. The utility of this approach is demonstrated in two ways. First, to inform the search space for bioinformatically predicted but unobserved glycan structures, predictive models for two structural modifications, core-fucosylation and bisecting GlcNAc, were developed based on the GU library. Second, the applicability of this method for the analysis of complex biological samples is evidenced by the ability to discriminate between cell culture and tissue sample types by the normalized intensity of N-glycan structures alone. Overall, the methods and data described here are expected to support the future development of more automated approaches to glycan identification and quantitation.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherRoyal Society of Chemistry
dc.relation.ispartofpagefrom3601
dc.relation.ispartofpageto3612
dc.relation.ispartofissue11
dc.relation.ispartofjournalAnalyst
dc.relation.ispartofvolume144
dc.subject.fieldofresearchAnalytical chemistry
dc.subject.fieldofresearchOther chemical sciences
dc.subject.fieldofresearchcode3401
dc.subject.fieldofresearchcode3499
dc.subject.keywordsScience & Technology
dc.subject.keywordsPhysical Sciences
dc.subject.keywordsChemistry
dc.subject.keywordsMASS-SPECTROMETRY
dc.titleStandardization of PGC-LC-MS-based glycomics for sample specific glycotyping
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationAshwood, C; Pratt, B; MacLean, BX; Gundry, RL; Packer, NH, Standardization of PGC-LC-MS-based glycomics for sample specific glycotyping, Analyst, 2019, 144 (11), pp. 3601-3612
dc.date.updated2021-06-08T00:43:37Z
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2019 Royal Society of Chemistry. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal website for access to the definitive, published version.
gro.hasfulltextFull Text
gro.griffith.authorPacker, Nicki


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