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Glycopeptide Capture for Cell Surface Proteomics
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Published on: May 9, 2014

Serial affinity chromatography as a selection tool in glycoproteomics.

Kwanyoung Jung1, Wonryeon Cho

  • 1Department of Chemistry, Seoul Science High School, Jongno-gu, Seoul, Republic of Korea.

Analytical Chemistry
|June 14, 2013
PubMed
Summary

Serial affinity chromatography (SAC) effectively reveals glycan diversity in glycoproteins by using sequential columns. Varying the column order helps identify if specific glycan structures appear alone or with others on the same protein.

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Area of Science:

  • Biochemistry
  • Analytical Chemistry
  • Glycomics

Background:

  • Glycan-targeting affinity chromatography is crucial for glycoprotein purification and identification.
  • Single-column methods struggle to reveal glycan diversity within captured glycoproteins.
  • Understanding glycan heterogeneity is vital for glycoproteomics.

Purpose of the Study:

  • To evaluate the utility of serial affinity columns (SAC) for determining glycan diversity in glycoproteins.
  • To investigate if specific glycan structures occur independently or co-occur with others on the same glycoprotein.
  • To assess the impact of column order in SAC on glycan analysis.

Main Methods:

  • Utilized four types of affinity columns in two distinct serial arrangements.
  • Analyzed protein capture patterns across different SAC series.
  • Compared results from varying the order of lectin and antibody affinity columns.

Main Results:

  • Different column orders in SAC yielded distinct protein capture patterns.
  • SAC successfully identified two types of glycan diversity: independent occurrence and co-residence of features.
  • The method demonstrated the ability to distinguish between single and multiple co-resident glycans.

Conclusions:

  • Serial affinity chromatography (SAC) is a valuable tool for recognizing protein glycosylation diversity.
  • Varying the order of affinity columns in SAC enhances the analysis of glycan heterogeneity.
  • This approach integrates well with existing glycoproteomics workflows.