Dataset Information

Deconstruction of O-glycosylation--GalNAc-T isoforms direct distinct subsets of the O-glycoproteome.

ABSTRACT: GalNAc-type O-glycosylation is found on most proteins trafficking through the secretory pathway in metazoan cells. The O-glycoproteome is regulated by up to 20 polypeptide GalNAc-Ts and the contributions and biological functions of individual GalNAc-Ts are poorly understood. Here, we used a zinc-finger nuclease (ZFN)-directed knockout strategy to probe the contributions of the major GalNAc-Ts (GalNAc-T1 and GalNAc-T2) in liver cells and explore how the GalNAc-T repertoire quantitatively affects the O-glycoproteome. We demonstrate that the majority of the O-glycoproteome is covered by redundancy, whereas distinct subsets of substrates are modified by non-redundant functions of GalNAc-T1 and GalNAc-T2. The non-redundant O-glycoproteome subsets and specific transcriptional responses for each isoform are related to different cellular processes; for the GalNAc-T2 isoform, these support a role in lipid metabolism. The results demonstrate that GalNAc-Ts have different non-redundant glycosylation functions, which may affect distinct cellular processes. The data serves as a comprehensive resource for unique GalNAc-T substrates. Our study provides a new view of the differential regulation of the O-glycoproteome, suggesting that the plurality of GalNAc-Ts arose to regulate distinct protein functions and cellular processes.

SUBMITTER: Schjoldager KT

PROVIDER: S-EPMC4693523 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Deconstruction of O-glycosylation--GalNAc-T isoforms direct distinct subsets of the O-glycoproteome.

Schjoldager Katrine T KT Joshi Hiren J HJ Kong Yun Y Goth Christoffer K CK King Sarah Louise SL Wandall Hans H HH Bennett Eric P EP Vakhrushev Sergey Y SY Clausen Henrik H

EMBO reports 20151113 12

GalNAc-type O-glycosylation is found on most proteins trafficking through the secretory pathway in metazoan cells. The O-glycoproteome is regulated by up to 20 polypeptide GalNAc-Ts and the contributions and biological functions of individual GalNAc-Ts are poorly understood. Here, we used a zinc-finger nuclease (ZFN)-directed knockout strategy to probe the contributions of the major GalNAc-Ts (GalNAc-T1 and GalNAc-T2) in liver cells and explore how the GalNAc-T repertoire quantitatively affects ...[more]

PMID: 26566661

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Project description:Characterizing protein GalNAc-type O-glycosylation has long been a major challenge, and as a result, our understanding of this glycoproteome is particularly poor. Recently, we presented a novel strategy for high throughput identification of O-GalNAc glycosites using zinc finger nuclease gene-engineered "SimpleCell" lines producing homogeneous truncated O-glycosylation. Total lysates of cells were trypsinized and subjected to lectin affinity chromatography enrichment, followed by identification of GalNAc O-glycopeptides by nLC-MS/MS, with electron transfer dissociation employed to specify sites of O-glycosylation. Here, we demonstrate a substantial improvement in the SimpleCell strategy by including an additional stage of lectin affinity chromatography on secreted glycoproteins from culture media (secretome) and by incorporating pre-fractionation of affinity-enriched glycopeptides via IEF before nLC-MS/MS. We applied these improvements to three human SimpleCells studied previously, and each yielded a substantial increase in the number of O-glycoproteins and O-glycosites identified. We found that analysis of the secretome was an important independent factor for increasing identifications, suggesting that further substantial improvements can also be sought through analysis of subcellular organelle fractions. In addition, we uncovered a substantial nonoverlapping set of O-glycoproteins and O-glycosites using an alternative protease digestion (chymotrypsin). In total, the improvements led to identification of 259 glycoproteins, of which 152 (59%) were novel compared with our previous strategy using the same three cell lines. With respect to individual glycosites, we identified a total of 856 sites, of which 508 (59%) were novel compared with our previous strategy; this includes four new identifications of O-GalNAc attached to tyrosine. Furthermore, we uncovered ≈ 220 O-glycosites wherein the peptides were clearly identified, but the glycosites could not be unambiguously assigned to specific positions. The improved strategy should greatly facilitate high throughput characterization of the human GalNAc-type O-glycoproteome as well as be applicable to analysis of other O-glycoproteomes.

Project description:Acetylgalactosamine (GalNAc)-type O-glycosylation is an essential posttranslational modification (PTM) that plays fundamental roles in biology. Malfunction of this PTM is exemplified by the presence of truncated O-glycans in cancer. For instance, the glycoprotein MUC1 is overexpressed in many tumor tissues and tends to carry simple oligosaccharides that allow for the presentation of different tumor-associated antigens, such as the Tn or sTn antigens (GalNAc-α-1-O-Thr/Ser and Neu5Acα2-6GalNAcα1-O-Ser/Thr, respectively). In other cases, such as tumoral calcinosis associated with O-glycosylation of the fibroblast growth factor 23, O-glycans are absent or less abundant. Significant progress has been made in determining the three-dimensional structures of biomolecules that recognize GalNAc, such as antibodies, lectins, mucinases, GalNAc-transferases, and other glycosyltransferases. Analysis of the complexes between these entities and GalNAc-containing glycopeptides, in most cases derived from crystallographic or NMR analysis, provides an understanding of the key structural elements that control molecular recognition of these glycopeptides. Here, we describe and compare the binding sites of these proteins in detail, focusing on how the GalNAc moieties interact selectively with them. We also summarize the differences and similarities in GalNAc recognition. In general, the recognition of GalNAc-containing glycopeptides is determined by hydrogen bonds between hydroxyl groups and the N-acetyl group of GalNAc with proteins, as well as CH-π contacts in which the hydrophobic α-face of the sugar and the methyl group of NHAc can be involved. The latter interaction usually provides the basis for selectivity. It is worth noting that binding of these glycopeptides depends primarily on recognition of the sugar moiety, with some exceptions such as a few anti-MUC1 antibodies that primarily recognize the peptide backbone and use the sugar to facilitate shape complementarity or to establish a limited number of interactions with the protein. Focusing specifically on the GalNAc moiety, we can observe that there is some degeneracy of interactions within the same protein families, likely due to substrate flexibility. However, when all studied proteins are considered together, despite the commonalities within each protein family, no pattern can be discerned between the different families, apart from the presence of common residues such as Tyr, His, or Asp, which are responsible for hydrogen bonds. The lack of a pattern can be anticipated, given the diverse functions of mucinases, glycosyltransferases, antibodies, and lectins. Finally, it is important to point out that the conformational differences observed in solution in glycopeptides bearing GalNAc-α-1-O-Ser or GalNAc-α-1-O-Thr also can be found in the bound state. This unique characteristic is exploited, for instance, by the enzyme C1GalT1 to broadly glycosylate both acceptor substrates. The findings summarized in this review may contribute to the rational structure-guided development of therapeutic vaccines, novel diagnostic tools for early cancer detection, and new cancer treatments for cancer with tailored anti-Tn or anti-STn antibodies or new drugs to inhibit GalNAc-T isoenzymes.

Dataset Information

Deconstruction of O-glycosylation--GalNAc-T isoforms direct distinct subsets of the O-glycoproteome.

Publications

Deconstruction of O-glycosylation--GalNAc-T isoforms direct distinct subsets of the O-glycoproteome.

Similar Datasets

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