Glycoproteomics

Bagdonaite, Ieva; Malaker, Stacy A.; Polasky, Daniel A.; Riley, Nicholas M.; Schjoldager, Katrine T.-B. G.; Vakhrushev, Sergey Y.; Halim, Adnan; Aoki‐Kinoshita, Kiyoko F.; Nesvizhskii, Alexey I.; Bertozzi, Carolyn R.; Wandall, Hans H.; Parker, Benjamin L.; Thaysen‐Andersen, Morten; Scott, Nichollas E.

doi:10.1038/s43586-022-00128-4

Cited by 112 publications

(140 citation statements)

References 420 publications

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“…[1][2][3] Dedicated efforts to improve mass spectrometry (MS)-based glycoproteomics methodology have significantly increased our ability to analyze intact glycopeptides, which can provide site-specific characterization of glycoproteins to capture macro-and microheterogeneity across the glycoproteome. [4][5][6][7][8][9] Thanks, in part, to the presence of a consensus N-glycosylation sequence motif, location of N-glycosites in regions accessible by canonical proteases, effective endoglycosidases (i.e., PNGaseF), and favorable gas-phase fragmentation behavior in ubiquitous tandem MS approaches that use collision-based dissociation, thousands of N-glycopeptides and N-glycosites can now be profiled in a single experiment. [10][11][12][13][14][15][16] Conversely, O-glycoproteins enjoy none of these analytical benefits, making O-glycosite characterization a significantly more challenging task that requires new and innovative tools.…”

Section: Introductionmentioning

confidence: 99%

Deciphering O-glycoprotease substrate preferences with O-Pair Search

Riley

Bertozzi

2022

Mol. Omics

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Section: Introductionmentioning

confidence: 99%

Deciphering O-glycoprotease substrate preferences with O-Pair Search

Riley

Bertozzi

2022

Mol. Omics

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“…It is meaningful that during investigations on protein O-GlcNAcylation, the S-GlcNAcylated structures have also been discovered (Maynard et al 2016;Xiao and Wu 2017). Accordingly, it deems reasonable to include research on S-glycosylation in well-developed workflows of mass spectrometry-based glycoproteomics (Bagdonaite et al 2022;Darula and Medzihradszky 2018;Riley et al 2021b), e.g., in the manner sketched in Fig. 2.…”

Section: Discussionmentioning

confidence: 99%

Protein cysteine S-glycosylation: oxidative hydrolysis of protein S-glycosidic bonds in aqueous alkaline environments

Buchowiecka

2022

Amino Acids

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Some glycoproteins contain carbohydrates S-linked to cysteine (Cys) residues. However, relatively few S-glycosylated proteins have been detected, due to the lack of an effective research methodology. This work outlines a general concept for the detection of S-glycosylation sites in proteins. The approach was verified by exploratory experiments on a model mixture of β-S-glucosylated polypeptides obtained by the chemical transformation of lysozyme P00698. The model underwent two processes: (1) oxidative hydrolysis of S-glycosidic bonds under alkaline conditions to expose the thiol group of Cys residues; (2) thiol S-alkylation leading to thiol S-adduct formation at the former S-glycosylation sites. Oxidative hydrolysis was conducted in aqueous urea, dimethyl sulfoxide, or trifluoroethanol, with silver nitrate as the reaction promoter, in the presence of triethylamine and/or pyridine. The concurrent formation of stable protein silver thiolates, gluconic acid, and silver nanoclusters was observed. The essential de-metalation of protein silver thiolates using dithiothreitol preceded the S-labeling of Cys residues with 4-vinyl pyridine or a fluorescent reagent. The S-labeled model was sequenced by tandem mass spectrometry to obtain data on the modifications and their distribution over the protein chains. This enabled the efficiency of both S-glycosidic bonds hydrolysis and S-glycosylation site labeling to be evaluated. Suggestions are also given for testing this novel strategy on real proteomic samples.

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“…[1][2][3] Dedicated efforts to improve glycoproteomics methodology have significantly increased our ability to analyze intact glycopeptides, which can provide sitespecific characterization of glycoproteins to capture macro-and microheterogeneity across the glycoproteome. [4][5][6][7][8][9] Thanks, in part, to the presence of a consensus N-glycosylation sequence motif, location of N-glycosites in regions accessible by canonical proteases, effective endoglycosidases (i.e., PNGaseF), and favorable gas-phase fragmentation behavior in ubiquitous collision-based dissociation approaches, thousands of N-glycopeptides and N-glycosites can now be profiled in a single experiment. [10][11][12][13][14][15][16] Conversely, O-glycoproteins enjoy none of these benefits, making O-glycosite characterization a significantly more challenging task that requires new and innovative tools.…”

Section: Introductionmentioning

confidence: 99%

Deciphering O-glycoprotease substrate preferences with O-Pair Search

Riley

Bertozzi

2022

Preprint

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O-glycoproteases are an emerging class of enzymes that selectively digest glycoproteins at positions decorated with specific O-linked glycans. O-glycoprotease substrates range from any O-glycoprotein (albeit with specific O-glycan modifications) to only glycoproteins harboring specific O-glycosylated sequence motifs, such as those found in mucin domains. Their utility for multiple glycoproteomic applications is driving the search to both discover new O-glycoproteases and to understand how structural features of characterized O-glycoproteases influence their substrate specificities. One challenge of defining O-glycoprotease specificity restraints is the need to characterize O-glycopeptides with site-specific analysis of O-glycosites. Here, we demonstrate how O-Pair Search, a recently developed O-glycopeptide-centric identification platform that enables rapid searches and confident O-glycosite localization, can be used to determine substrate specificities of various O-glycoproteases de novo from LC-MS/MS data of O-glycopeptides. Using secreted protease of C1 esterase inhibitor (StcE) from enterohemorrhagic Escherichia coli and O-endoprotease OgpA from Akkermansia mucinophila, we explore numerous settings that effect O-glycopeptide identification and show how non-specific and semi-tryptic searches of O-glycopeptide data can produce candidate cleavage motifs that can be used to define new protease cleavage settings that lower search times and improve O-glycopeptide identifications. We use this platform to generate a consensus motif for the recently characterized immunomodulating metalloprotease (IMPa) from Pseudomonas aeruginosa and show that IMPa is a favorable O-glycoprotease for characterizing densely O-glycosylated mucin-domain glycoproteins.

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Glycoproteomics

Cited by 112 publications

References 420 publications

Deciphering O-glycoprotease substrate preferences with O-Pair Search

Deciphering O-glycoprotease substrate preferences with O-Pair Search

Protein cysteine S-glycosylation: oxidative hydrolysis of protein S-glycosidic bonds in aqueous alkaline environments

Deciphering O-glycoprotease substrate preferences with O-Pair Search

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