LC–MS/MS Identification of the O‑Glycosylation and Hydroxylation of Amino Acid Residues of Collagen α‑1 (II) chain from Bovine Cartilage

O-Glycosylation of collagen is a unique type of posttranslational modifications (PTMs) involving the attachment of galactose (Gal) or glucose-galactose (Glc-Gal) moieties to hydroxylysine (HyK). Also, hydroxyproline (HyP) result from the posttranslational hydroxylation of some proline residues in collagen. Here, LC–MS/MS was effectively employed to identify 23 O-glycosylation sites and a large number of HyP residues associated with bovine type II collagen α-1 chain (CO2A1). The modifications of the 23 O-glycosylation sites varied qualitatively and quantitatively. Both Gal and Glc-Gal moieties occupied 22 of the identified glycosylation sites, while K773 was observed as unmodified. A large number of HyP residues at Yaa positions of Gly-Xaa-Yaa motif were detected. HyP residues at Xaa positions of Gly-HyP-HyP, Gly-HyP-Ala, and Gly-HyP-Val motifs were also observed. Notably, HyP residue of Gly-HyP-Gln motif was detected, which has not been previously reported. Moreover, the deamidation of 8 Asn residues was identified, of which 2 Asp residues were observed at different retention times because of isomerization (Asp vs isoAsp). Partial macroheterogeneities of some CO2A1 glycosylation sites were revealed by LC–MS/MS analysis. ETD experiments revealed partial macroheterogeneities associated with K299–K308, K452–K464, K464–K470, and K857–K884 glycosylation sites. Semiquantitative data suggest that the glycosylation of hydroxylysine residues is site-specific

LC–MS/MS Identification of the O‑Glycosylation and Hydroxylation of Amino Acid Residues of Collagen α‑1 (II) chain from Bovine Cartilage

O-Glycosylation of collagen is a unique type of posttranslational modifications (PTMs) involving the attachment of galactose (Gal) or glucose-galactose (Glc-Gal) moieties to hydroxylysine (HyK). Also, hydroxyproline (HyP) result from the posttranslational hydroxylation of some proline residues in collagen. Here, LC–MS/MS was effectively employed to identify 23 O-glycosylation sites and a large number of HyP residues associated with bovine type II collagen α-1 chain (CO2A1). The modifications of the 23 O-glycosylation sites varied qualitatively and quantitatively. Both Gal and Glc-Gal moieties occupied 22 of the identified glycosylation sites, while K773 was observed as unmodified. A large number of HyP residues at Yaa positions of Gly-Xaa-Yaa motif were detected. HyP residues at Xaa positions of Gly-HyP-HyP, Gly-HyP-Ala, and Gly-HyP-Val motifs were also observed. Notably, HyP residue of Gly-HyP-Gln motif was detected, which has not been previously reported. Moreover, the deamidation of 8 Asn residues was identified, of which 2 Asp residues were observed at different retention times because of isomerization (Asp vs isoAsp). Partial macroheterogeneities of some CO2A1 glycosylation sites were revealed by LC–MS/MS analysis. ETD experiments revealed partial macroheterogeneities associated with K299–K308, K452–K464, K464–K470, and K857–K884 glycosylation sites. Semiquantitative data suggest that the glycosylation of hydroxylysine residues is site-specific

LC–MS/MS Identification of the O‑Glycosylation and Hydroxylation of Amino Acid Residues of Collagen α‑1 (II) chain from Bovine Cartilage

O-Glycosylation of collagen is a unique type of posttranslational modifications (PTMs) involving the attachment of galactose (Gal) or glucose-galactose (Glc-Gal) moieties to hydroxylysine (HyK). Also, hydroxyproline (HyP) result from the posttranslational hydroxylation of some proline residues in collagen. Here, LC–MS/MS was effectively employed to identify 23 O-glycosylation sites and a large number of HyP residues associated with bovine type II collagen α-1 chain (CO2A1). The modifications of the 23 O-glycosylation sites varied qualitatively and quantitatively. Both Gal and Glc-Gal moieties occupied 22 of the identified glycosylation sites, while K773 was observed as unmodified. A large number of HyP residues at Yaa positions of Gly-Xaa-Yaa motif were detected. HyP residues at Xaa positions of Gly-HyP-HyP, Gly-HyP-Ala, and Gly-HyP-Val motifs were also observed. Notably, HyP residue of Gly-HyP-Gln motif was detected, which has not been previously reported. Moreover, the deamidation of 8 Asn residues was identified, of which 2 Asp residues were observed at different retention times because of isomerization (Asp vs isoAsp). Partial macroheterogeneities of some CO2A1 glycosylation sites were revealed by LC–MS/MS analysis. ETD experiments revealed partial macroheterogeneities associated with K299–K308, K452–K464, K464–K470, and K857–K884 glycosylation sites. Semiquantitative data suggest that the glycosylation of hydroxylysine residues is site-specific

LC–MS/MS Quantitation of Esophagus Disease Blood Serum Glycoproteins by Enrichment with Hydrazide Chemistry and Lectin Affinity Chromatography

Changes in glycosylation have been shown to have a profound correlation with development/malignancy in many cancer types. Currently, two major enrichment techniques have been widely applied in glycoproteomics, namely, lectin affinity chromatography (LAC)-based and hydrazide chemistry (HC)-based enrichments. Here we report the LC–MS/MS quantitative analyses of human blood serum glycoproteins and glycopeptides associated with esophageal diseases by LAC- and HC-based enrichment. The separate and complementary qualitative and quantitative data analyses of protein glycosylation were performed using both enrichment techniques. Chemometric and statistical evaluations, PCA plots, or ANOVA test, respectively, were employed to determine and confirm candidate cancer-associated glycoprotein/glycopeptide biomarkers. Out of 139, 59 common glycoproteins (42% overlap) were observed in both enrichment techniques. This overlap is very similar to previously published studies. The quantitation and evaluation of significantly changed glycoproteins/glycopeptides are complementary between LAC and HC enrichments. LC–ESI–MS/MS analyses indicated that 7 glycoproteins enriched by LAC and 11 glycoproteins enriched by HC showed significantly different abundances between disease-free and disease cohorts. Multiple reaction monitoring quantitation resulted in 13 glycopeptides by LAC enrichment and 10 glycosylation sites by HC enrichment to be statistically different among disease cohorts

Glycoproteomics: Identifying the Glycosylation of Prostate Specific Antigen at Normal and High Isoelectric Points by LC–MS/MS

Prostate specific antigen (PSA) is currently used as a biomarker to diagnose prostate cancer. PSA testing has been widely used to detect and screen prostate cancer. However, in the diagnostic gray zone, the PSA test does not clearly distinguish between benign prostate hypertrophy and prostate cancer due to their overlap. To develop more specific and sensitive candidate biomarkers for prostate cancer, an in-depth understanding of the biochemical characteristics of PSA (such as glycosylation) is needed. PSA has a single glycosylation site at Asn69, with glycans constituting approximately 8% of the protein by weight. Here, we report the comprehensive identification and quantitation of N-glycans from two PSA isoforms using LC–MS/MS. There were 56 N-glycans associated with PSA, whereas 57 N-glycans were observed in the case of the PSA-high isoelectric point (pI) isoform (PSAH). Three sulfated/phosphorylated glycopeptides were detected, the identification of which was supported by tandem MS data. One of these sulfated/phosphorylated N-glycans, HexNAc5Hex4dHex1s/p1 was identified in both PSA and PSAH at relative intensities of 0.52 and 0.28%, respectively. Quantitatively, the variations were monitored between these two isoforms. Because we were one of the laboratories participating in the 2012 ABRF Glycoprotein Research Group (gPRG) study, those results were compared to that presented in this study. Our qualitative and quantitative results summarized here were comparable to those that were summarized in the interlaboratory study

Characterization of the Glycosylation Site of Human PSA Prompted by Missense Mutation using LC–MS/MS

Prostate specific antigen (PSA) is currently used as a diagnostic biomarker for prostate cancer. It is a glycoprotein possessing a single glycosylation site at N69. During our previous study of PSA N69 glycosylation, additional glycopeptides were observed in the PSA sample that were not previously reported and did not match glycopeptides of impure glycoproteins existing in the sample. This extra glycosylation site of PSA is associated with a mutation in KLK3 genes. Among single nucleotide polymorphisms (SNPs) of KLKs families, the rs61752561 in KLK3 genes is an unusual missense mutation resulting in the conversion of D102 to N in PSA amino acid sequence. Accordingly, a new N-linked glycosylation site is created with an N102MS motif. Here we report the first qualitative and quantitative glycoproteomic study of PSA N102 glycosylation site by LC–MS/MS. We successfully applied tandem MS to verify the amino acid sequence possessing N102 glycosylation site and associated glycoforms of PSA samples acquired from different suppliers. Among the three PSA samples, HexNAc2Hex5 was the predominant glycoform at N102, while Hex­NAc4­Hex5­Fuc1­Neu­Ac1 or Hex­NAc4­Hex5­Fuc1­Neu­Ac2 was the primary glycoforms at N69. D102 is the first amino acid of “kallikrein loop”, which is close to a zinc-binding site and catalytic triad. The different glycosylation of N102 relative to N69 might be influenced by the close vicinity of N102 to these functional sites and steric hindrance

Computational Framework for Identification of Intact Glycopeptides in Complex Samples

Glycosylation is an important protein modification that involves enzymatic attachment of sugars to amino acid residues. Understanding the structure of these sugars and the effects of glycosylation are vital for developing indicators of disease development and progression. Although computational methods based on mass spectrometric data have proven to be effective in monitoring changes in the glycome, developing such methods for the glycoproteome are challenging, largely due to the inherent complexity in simultaneously studying glycan structures with their corresponding glycosylation sites. This paper introduces a computational framework for identifying intact N-linked glycopeptides, i.e. glycopeptides with N-linked glycans attached to their glycosylation sites, in complex proteome samples. Scoring algorithms are presented for tandem mass spectra of glycopeptides resulting from collision-induced dissociation (CID), higher-energy C-trap dissociation (HCD), and electron transfer dissociation (ETD) fragmentation modes. An empirical false-discovery rate estimation method, based on a target-decoy search approach, is derived for assigning confidence. The power of our method is further enhanced when multiple data sets are pooled together to increase identification confidence. Using this framework, 103 highly confident N-linked glycopeptides from 53 sites across 33 glycoproteins were identified in complex human serum proteome samples using conventional proteomic platforms with standard depletion of the 7-most abundant proteins. These results indicate that our method is ready to be used for characterizing site-specific protein glycosylation in complex samples

Label-Free Glycopeptide Quantification for Biomarker Discovery in Human Sera

Glycan moieties of glycoproteins modulate many biological processes in mammals, such as immune response, inflammation, and cell signaling. Numerous studies show that many human diseases are correlated with quantitative alteration of protein glycosylation. In some cases, these changes can occur for certain types of glycans over specific sites in a glycoprotein rather than on the global abundance of the glycoprotein. Conventional analytical techniques that analyze the abundance of glycans cleaved from glycoproteins cannot reveal these subtle effects. Here we present a novel statistical method to quantify the site-specific glycosylation of glycoproteins in complex samples using label-free mass spectrometric techniques. Abundance variations between sites of a glycoprotein as well as different glycoforms, that is, glycopeptides with different glycans attached to the same site, can be detected using these techniques. We applied our method to an esophageal cancer study based on blood serum samples from cancer patients in an attempt to detect potential biomarkers of site-specific N-linked glycosylation. A few glycoproteins, including vitronectin, showed significantly different site-specific glycosylations within cancer/control samples, indicating that our method is ready to be used for the discovery of glycosylated biomarkers

HILIC and ERLIC Enrichment of Glycopeptides Derived from Breast and Brain Cancer Cells

Aberrant glycosylation has been linked to many different cancer types. The blood–brain barrier (BBB) is a region of the brain that regulates the entrance of ions, diseases, toxins, and so on. However, in breast cancer metastasis, the BBB fails to prevent the crossing of the cancer cells into the brain. Here we present a study of identifying and quantifying the glycosylation of six breast and brain cancer cell lines using hydrophilic interaction liquid chromatography (HILIC) and electrostatic repulsion liquid chromatography (ERLIC) enrichments and LC–MS/MS analysis. Qualitative and quantitative analyses of N-linked glycosylation were performed by both enrichment techniques for individual and complementary comparison. Potential cancer glycopeptide biomarkers were identified and confirmed by chemometric and statistical evaluations. A total of 497 glycopeptides were characterized, of which 401 were common glycopeptides (80.6% overlap) identified from both enrichment techniques. HILIC enrichment yielded 320 statistically significant glycopeptides in 231BR relative to the other cell lines out of 494 unique glycopeptides, and sequential HILIC-ERLIC enrichment yielded 214 statistically significant glycopeptides in 231BR compared with the other cell lines out of 404 unique glycopeptides. The results provide the first comprehensive glycopeptide listing for these six cell lines

Automated Glycan Sequencing from Tandem Mass Spectra of N‑Linked Glycopeptides

Mass spectrometry has become a routine experimental tool for proteomic biomarker analysis of human blood samples, partly due to the large availability of informatics tools. As one of the most common protein post-translational modifications (PTMs) in mammals, protein glycosylation has been observed to alter in multiple human diseases and thus may potentially be candidate markers of disease progression. While mass spectrometry instrumentation has seen advancements in capabilities, discovering glycosylation-related markers using existing software is currently not straightforward. Complete characterization of protein glycosylation requires the identification of intact glycopeptides in samples, including identification of the modification site as well as the structure of the attached glycans. In this paper, we present GlycoSeq, an open-source software tool that implements a heuristic iterated glycan sequencing algorithm coupled with prior knowledge for automated elucidation of the glycan structure within a glycopeptide from its collision-induced dissociation tandem mass spectrum. GlycoSeq employs rules of glycosidic linkage as defined by glycan synthetic pathways to eliminate improbable glycan structures and build reasonable glycan trees. We tested the tool on two sets of tandem mass spectra of N-linked glycopeptides cell lines acquired from breast cancer patients. After employing enzymatic specificity within the N-linked glycan synthetic pathway, the sequencing results of GlycoSeq were highly consistent with the manually curated glycan structures. Hence, GlycoSeq is ready to be used for the characterization of glycan structures in glycopeptides from MS/MS analysis. GlycoSeq is released as open source software at https://github.com/chpaul/GlycoSeq/