Determination of site-specific glycan heterogeneity on glycoproteins

Kolarich, Daniel; Jensen, Pia; Altmann, Friedrich; Packer, Nicolle H.

doi:10.1038/nprot.2012.062

Cited by 173 publications

(156 citation statements)

References 44 publications

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“…Unlike eukaryotic glycosylation where robust and high-throughput technologies now exist to enrich (20 -22) and characterize both the glycan and peptide component of glycopeptides (23)(24)(25), the diversity (glycan composition and linkage) within bacterial glycosylation systems makes few technologies broadly applicable to all bacterial glycoproteins. Because of this challenge a deeper understanding of the glycan diversity and substrates of glycosylation has been largely unachievable for the majority of known bacterial glycosylation systems.…”

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confidence: 99%

Diversity Within the O-linked Protein Glycosylation Systems of Acinetobacter Species

Scott

Kinsella

Edwards

et al. 2014

Molecular & Cellular Proteomics

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The opportunistic human pathogen Acinetobacter baumannii is a concern to health care systems worldwide because of its persistence in clinical settings and the growing frequency of multiple drug resistant infections. To combat this threat, it is necessary to understand factors associated with disease and environmental persistence of A. baumannii. Recently, it was shown that a single biosynthetic pathway was responsible for the generation of capsule polysaccharide and O-linked protein glycosylation. Because of the requirement of these carbohydrates for virulence and the non-template driven nature of glycan biogenesis we investigated the composition, diversity, and properties of the Acinetobacter glycoproteome. Utilizing global and targeted mass spectrometry methods, we examined 15 strains and found extensive glycan diversity in the O-linked glycoproteome of Acinetobacter. Comparison of the 26 glycoproteins identified revealed that different A. baumannii strains target similar protein substrates, both in characteristics of the sites of O-glycosylation and protein identity. Surprisingly, glycan micro-heterogeneity was also observed within nearly all isolates examined demonstrating glycan heterogeneity is a widespread phenomena in Acinetobacter O-linked glycosylation. By comparing the 11 main glycoforms and over 20 alternative glycoforms characterized within the 15 strains, trends within the glycan utilized for O-linked glycosylation could be observed. These trends reveal Acinetobacter O-linked glycosylation favors short (three to five residue) glycans with limited branching containing negatively charged sugars such as GlcNAc3NAcA4OAc or legionaminic/pseudaminic acid derivatives. These observations suggest that although highly diverse, the capsule/O-linked glycan biosynthetic pathways generate glycans with similar characteristics across all A. baumannii. Molecular & Cellular

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confidence: 99%

Diversity Within the O-linked Protein Glycosylation Systems of Acinetobacter Species

Scott

Kinsella

Edwards

et al. 2014

Molecular & Cellular Proteomics

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“…A list of 2325 unique precursors was generated, which were classified as glycopeptides by GRAEZ, and targeted in two subsequent LC-MS runs. Data were acquired with similar instrumental parameters, except the normalized collision energy was 29 and the AGC was set for 3e 6 for MS 1 and 1e 5 for MS 2 scans. All MS 2 spectra from the retrospective experiment were searched for the presence of two marker ions, the TMT reporter ion at 126.1277 daltons or the diagnostic Hex 1 HexNac 1 oxonium ion at 366.1395.…”

Section: Methodsmentioning

confidence: 99%

“…A 60-min linear gradient from 5 to 35% ACN was used. Normalized collision energy was 30, and the AGC was set for 1e 6 for MS 1 and 5e 4 for MS 2 scans. In addition to the retrospective GRAEZ evaluation, prospective GRAEZ testing was also performed.…”

Section: Methodsmentioning

confidence: 99%

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A Classifier Based on Accurate Mass Measurements to Aid Large Scale, Unbiased Glycoproteomics

Froehlich

Dodds

Wilhelm

et al. 2013

Molecular & Cellular Proteomics

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Determining which glycan moieties occupy specific N-glycosylation sites is a highly challenging analytical task. Arguably, the most common approach involves LC-MS and LC-MS/MS analysis of glycopeptides generated by proteases with high cleavage site specificity; however, the depth achieved by this approach is modest. Nonglycosylated peptides are a major challenge to glycoproteomics, as they are preferentially selected for data-dependent MS/MS due to higher ionization efficiencies and higher stoichiometric levels in moderately complex samples. With the goal of improving glycopeptide coverage, a mass defect classifier was developed that discriminates between peptides and glycopeptides in complex mixtures based on accurate mass measurements of precursor peaks. By using the classifier, glycopeptides that were not fragmented in an initial data-dependent acquisition run may be targeted in a subsequent analysis without any prior knowledge of the glycan or protein species present in the mixture. Additionally, from probable glycopeptides that were poorly fragmented, tandem mass spectra may be reacquired using optimal glycopeptide settings. We demonstrate high sensitivity (0.892) and specificity (0.947) based on an in silico dataset spanning >100,000 tryptic entries. Comparable results were obtained using chymotryptic species. Further validation using published data and a fractionated tryptic digest of human urinary proteins was performed, yielding a sensitivity of 0.90 and a specificity of 0.93. Lists of glycopeptides may be generated from an initial proteomics experiment, and we show they may be efficiently targeted using the classifier. Considering the growing availability of high accuracy mass analyzers, this approach represents a simple and broadly applicable means of increasing the depth of MS/MS-based glycoproteomic analyses. Molecular &

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“…Changes in glycosylation have been associated with a wide variety of conditions including inherited disease, cancer and infection [7,[16][17][18][19][20]. However, relatively specialized sample preparation, detection methods and data analysis outside the scope of many studies are often required for detailed glycosylation analysis [21,22]. In these cases, the N-glycosylation status of components of a sample is generally ignored.…”

Section: Introductionmentioning

confidence: 99%

Deglycosylation systematically improves N-glycoprotein identification in liquid chromatography–tandem mass spectrometry proteomics for analysis of cell wall stress responses in Saccharomyces cerevisiae lacking Alg3p

Bailey

Schulz

2013

Journal of Chromatography B

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Post-translational modification of proteins with glycosylation is of key importance in many biological systems in eukaryotes, influencing fundamental biological processes and regulating protein function. Changes in glycosylation are therefore of interest in understanding these processes and are also useful as clinical biomarkers of disease. The presence of glycosylation can also inhibit protease digestion and lower the quality and confidence of protein identification by mass spectrometry. While deglycosylation can improve the efficiency of subsequent protease digest and increase protein coverage, this step is often excluded from proteomic workflows. Here, we performed a systematic analysis that showed that deglycosylation with peptide-N-glycosidase F (PNGase F) prior to protease digestion with AspN or trypsin improved the quality of identification of the yeast cell wall proteome. The improvement in the confidence of identification of glycoproteins following PNGase F deglycosylation correlated with a higher density of glycosylation

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Determination of site-specific glycan heterogeneity on glycoproteins

Cited by 173 publications

References 44 publications

Diversity Within the O-linked Protein Glycosylation Systems of Acinetobacter Species

Diversity Within the O-linked Protein Glycosylation Systems of Acinetobacter Species

A Classifier Based on Accurate Mass Measurements to Aid Large Scale, Unbiased Glycoproteomics

Deglycosylation systematically improves N-glycoprotein identification in liquid chromatography–tandem mass spectrometry proteomics for analysis of cell wall stress responses in Saccharomyces cerevisiae lacking Alg3p

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