Large-Scale Measurement of Absolute Protein Glycosylation Stoichiometry

Protein glycosylation is one of the most important protein modifications. Glycosylation site occupancy alteration has been implicated in human diseases and cancers. However, current glycoproteomic methods focus on the identification and quantification of glycosylated peptides and glycosylation sites but not glycosylation occupancy or glycoform stoichiometry. Here we describe a method for large-scale determination of the absolute glycosylation stoichiometry using three independent relative ratios. Using this method, we determined 117 absolute N-glycosylation occupancies in OVCAR-3 cells. Finally, we investigated the possible functions and the determinants for partial glycosylation

Phylogenetic tree of 103 HAs from H5N1 strains.

<p>Phylogenetic trees are inferred from protein sequences by the Neighbor-Joining method and rooted using A/turkey/England/1991(red text). Estimates of the statistical significance of the phylogenies are calculated by performing 1,000 bootstrap replicates. The lengths of the horizontal line are proportional to the numbers of protein sequence differences, as indicated by the scale bars. Different clades classified by the WHO are shown as grayish-white bars. Virus with glycosylation site 158N deficiency are labeled in red, whereas glycosylation site 169N deficiency are labeled in green, and the dual deficiencies are labeled in purple. Several important mutation strains mentioned in the article are labeled in blue.</p

The amino-acid residues in the RBD of H5N1 HA.

<p>(A) The RBD in H5N1 HA consists of three secondary structure elements, Loop130, Loop220 and Helix190, together with four 100% conserved residues at the bottom (red). The residues with a conservation rate higher than 99% are labeled in yellow. (B) The statistics of the conserved amino-acid residues in the RBD. The predominant amino-acid residues are underlined, and the number of different types of mutations are shown as various blocks. Those with conservation rates lower than 99% are labeled. All of the residue numbers were adopted from the H3 HA numbering system.</p

Sequence alignment of A/Hong Kong/486/97, A/Viet Nam/1203/2004(3GBM), A/Hong Kong/213/2003, A/Cambodia/S1211394/2008, A/Egypt/2321-NAMRU3/2007, A/Anhui/1/2005 and A/chicken/Shanxi/10/2006.

<p>The RBDs are shown in blue lines with the identical amino acids marked with asterisks. The glycosylation site 158N are boxed in red, whereas the four most conserved residues at the bottom of the RBD are boxed in green.</p

The binding energies collected from flexible docking.

<p>The binding energies are calculated from the three lowest energies provided in the largest clusters. A notable tendency is the increasing binding energy accompanying with increasing glycosylation.</p

The influence of vicinal N-glycans on the RBD of HA trimer.

<p>(A) The volumetric topologies of the N-glycans near the RBD during the 5 ns MD simulation. The complex N-glycans on the sites 158N and 169N would swing dramatically. (B) The distances from the weight center of the RBD to the three topological centers of the N-glycans are calculated at 10 ps intervals, three colors represent the corresponding distances in (A).</p

Schematic diagrams for HA and SA receptors models.

<p>(A) Five initial models of HA are represented by 04VN, MG, HM, DS and FG respectively. Only one glycan is added on 158N near the RBD. (B) Four glycans on glycosylated HAs are represented by MG, HM, DS and FG respectively. (C) Eight sialoglycans and one pentaglucose are used for docking assays. The abbreviations for each glycan are as follows: lactosialyltetraoses (LSTa/LSTc), disialyllacto-N-tetraose (3DSLNT/6DSLNT) and bisialyantennas based on two monosaccharides (bisialyantennary mannose, BM3/BM6 and bisialyantennary GlcNAc, BG3/BG6). The sequence of monosaccharides and glycosidic bonds are illustrated using Consortium for Functional Glycomics nomenclature.</p

Precision Characterization of Site-Specific <i>O</i>‑Acetylated Sialic Acids on <i>N</i>‑Glycoproteins

O-Acetylation is a common modification of sialic acid, playing a significant role in glycoprotein stability, immune response, and cell development. Due to the lack of efficient methods for direct analysis of O-acetylated sialoglycopeptides (O-AcSGPs), the majority of identified O-acetylated sialic acids (O-AcSia) until now had no glycosite/glycoprotein information. Herein, we introduced a new workflow for precise interpretation of O-AcSGPs with probability estimation by recognizing the characteristic B and Y ions of O-AcSias. With further optimization of mass spectrometry parameters, the method allowed us to identify a total of 171 unique O-AcSGPs in mouse serum. Although the majority of these O-AcSGPs were at a relatively low abundance compared with their non-O-acetylated states, they were mainly involved in peptidase/endopeptidase inhibitor activities. The method paves the way for large-scale structural and functional analyses of site-specific O-AcSias in various complex samples as well as further identification of many other similar chemical modifications on glycoproteins

Precision Characterization of Site-Specific <i>O</i>‑Acetylated Sialic Acids on <i>N</i>‑Glycoproteins

O-Acetylation is a common modification of sialic acid, playing a significant role in glycoprotein stability, immune response, and cell development. Due to the lack of efficient methods for direct analysis of O-acetylated sialoglycopeptides (O-AcSGPs), the majority of identified O-acetylated sialic acids (O-AcSia) until now had no glycosite/glycoprotein information. Herein, we introduced a new workflow for precise interpretation of O-AcSGPs with probability estimation by recognizing the characteristic B and Y ions of O-AcSias. With further optimization of mass spectrometry parameters, the method allowed us to identify a total of 171 unique O-AcSGPs in mouse serum. Although the majority of these O-AcSGPs were at a relatively low abundance compared with their non-O-acetylated states, they were mainly involved in peptidase/endopeptidase inhibitor activities. The method paves the way for large-scale structural and functional analyses of site-specific O-AcSias in various complex samples as well as further identification of many other similar chemical modifications on glycoproteins

Precision Characterization of Site-Specific <i>O</i>‑Acetylated Sialic Acids on <i>N</i>‑Glycoproteins

O-Acetylation is a common modification of sialic acid, playing a significant role in glycoprotein stability, immune response, and cell development. Due to the lack of efficient methods for direct analysis of O-acetylated sialoglycopeptides (O-AcSGPs), the majority of identified O-acetylated sialic acids (O-AcSia) until now had no glycosite/glycoprotein information. Herein, we introduced a new workflow for precise interpretation of O-AcSGPs with probability estimation by recognizing the characteristic B and Y ions of O-AcSias. With further optimization of mass spectrometry parameters, the method allowed us to identify a total of 171 unique O-AcSGPs in mouse serum. Although the majority of these O-AcSGPs were at a relatively low abundance compared with their non-O-acetylated states, they were mainly involved in peptidase/endopeptidase inhibitor activities. The method paves the way for large-scale structural and functional analyses of site-specific O-AcSias in various complex samples as well as further identification of many other similar chemical modifications on glycoproteins