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Strategic Applications of Negative-Mode LC-MS/MS Analyses to Expedite Confident Mass Spectrometry-Based Identification of Multiple Glycosylated Peptides

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NIAID Data Ecosystem2026-03-11 收录
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https://figshare.com/articles/dataset/Strategic_Applications_of_Negative-Mode_LC-MS_MS_Analyses_to_Expedite_Confident_Mass_Spectrometry-Based_Identification_of_Multiple_Glycosylated_Peptides/12340772
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Although recent advances in mass spectrometry (MS) have enabled meaningful glycoproteomic undertakings, many technical limitations remain unsolved. Among these, the ability to efficiently sequence the peptide backbone for de novo identification, delineating multiple N- and O-glycosylation sites on single glycopeptides, and deriving more glycan structure information to discriminate isomeric glycoforms are well acknowledged practical problems to be tackled. To address these issues, we explored the use of negative-mode MS2/MS3 fragmentation to supplement current nanoLC-MS2-based sequencing and identification of intact glycopeptides largely performed in positive mode. Consistent with previous reports by others, we found that sulfation and sialylation drastically alter the MS2 fragmentation pattern of glycopeptides in negative mode and the characteristic features identified can be utilized to program the most informative MS3 on the glycan moiety itself. Importantly, direct elimination of one or more O-glycans under negative-mode MS2 affords an easy way to discover additional O-glycosylations on a multiply glycosylated peptide by virtue of enumerating the dehydration scars imprinted on the O-glycosylated sites. Moreover, the characteristic peptide core ion carrying a ring cleavage remnant of the innermost amino sugar residue of an N-glycan can be relied upon to filter out all related N-glycopeptides carrying additional O-glycans defined by specific mass increments. Such enhanced ability to advance from definitive identification of single to multiple site-specific glycosylation on the same peptide backbones is anticipated to have a significant impact on the level of structural and biological insights one can gain in glycoproteomic applications.
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2020-05-08
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