Literature DB >> 31566965

Retention Time Prediction for Glycopeptides in Reversed-Phase Chromatography for Glycoproteomic Applications.

Evelyn Ang1,2, Haley Neustaeter2, Vic Spicer2, Hélène Perreault1, Oleg Krokhin1,2,3.   

Abstract

The sequence-specific retention calculator algorithm (SSRCalc) [ Krokhin , O. V. Anal. Chem. 2006 , 78 , 7785 ] was adapted for the prediction of retention times of N-glycopeptides separated by reversed-phase high performance liquid chromatography (RPLC). The retention time shifts (dHI = HIglyco - HIdeglyco, where HI is the hydrophobicity index, measured in percent acetonitrile units) used for modeling were measured for 602 glycopeptides versus 123 of their deglycosylated analogues. Our method used a tryptic digest of 12 purified glycoproteins, glycopeptide enrichment, deglycosylation with PNGaseF, and RPLC-MS/MS analysis of combined (deglycosylated and intact) peptide mixtures. On average, glycosylation yields a 0.79% acetonitrile unit decrease in retention, compared with the hydrophobicity indices of their deglycosylated analogues. These values, however, are drastically different for asialo (-1.37% acetonitrile units), monosialylated (-0.47% acetonitrile units), disialylated (+0.61% acetonitrile units), and trisialylated (+1.94% acetonitrile units) glycans. Peptide retention time shifts upon glycosylation (dHI) vary depending on the number of monosaccharide units, the presence or absence of sialic acid, peptide hydrophobicity, and the number of position-dependent features. These features are mostly driven by competing effects of acidic residues (aspartic acid and sialic acid) on ion-pair formation and by nearest-neighbor effects of hydrophilic glycans. The accuracy of the modified prediction model for glycopeptides approaches that of the prediction for nonmodified species (R2 = 0.97 vs 0.98). However, retention time prediction based on the experimental retention values of deglycosylated analogues (HIglyco = HIdeglyco + dHI, R2 = 0.995) is much more accurate, thus providing a solid support for glycopeptide identification in complex samples based on mass and retention time.

Entities:  

Year:  2019        PMID: 31566965     DOI: 10.1021/acs.analchem.9b02584

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  6 in total

1.  Prediction of Intact N-Glycopeptide Retention Time Windows in Hydrophilic Interaction Liquid Chromatography.

Authors:  Petr Kozlik; Katarina Molnarova; Tomas Jecmen; Tomas Krizek; Zuzana Bosakova
Journal:  Molecules       Date:  2022-06-09       Impact factor: 4.927

Review 2.  Measuring change in glycoprotein structure.

Authors:  Mary Rachel Nalehua; Joseph Zaia
Journal:  Curr Opin Struct Biol       Date:  2022-04-19       Impact factor: 7.786

3.  Relative Retention Time Estimation Improves N-Glycopeptide Identifications by LC-MS/MS.

Authors:  Joshua Klein; Joseph Zaia
Journal:  J Proteome Res       Date:  2020-04-10       Impact factor: 4.466

Review 4.  A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts.

Authors:  Joshua A Klein; Joseph Zaia
Journal:  Biochemistry       Date:  2019-12-31       Impact factor: 3.162

Review 5.  Towards structure-focused glycoproteomics.

Authors:  Anastasia Chernykh; Rebeca Kawahara; Morten Thaysen-Andersen
Journal:  Biochem Soc Trans       Date:  2021-02-26       Impact factor: 5.407

Review 6.  MS-based glycomics and glycoproteomics methods enabling isomeric characterization.

Authors:  Wenjing Peng; Cristian D Gutierrez Reyes; Sakshi Gautam; Aiying Yu; Byeong Gwan Cho; Mona Goli; Kaitlyn Donohoo; Stefania Mondello; Firas Kobeissy; Yehia Mechref
Journal:  Mass Spectrom Rev       Date:  2021-06-22       Impact factor: 9.011

  6 in total

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