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Author Spotlight: Advancing Protein Glycosylation Research Using a Fully Automated System
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Automated, high-throughput serum glycoprofiling platform.

H Stöckmann1, R O'Flaherty, B Adamczyk

  • 1NIBRT GlycoScience Group, NIBRT - The National Institute for Bioprocessing Research and Training, Fosters Avenue, Mount Merrion, Blackrock, Co.Dublin, Ireland. pauline.rudd@nibrt.ie.

Integrative Biology : Quantitative Biosciences From Nano to Macro
|July 21, 2015
PubMed
Summary
This summary is machine-generated.

Automated N-glycan sample preparation accelerates biomarker discovery. This high-throughput platform enables rapid glycoprofiling of serum samples, facilitating the identification of clinical glycobiomarkers.

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Area of Science:

  • Glycomics
  • Biomarker Discovery
  • Analytical Chemistry

Background:

  • Complex carbohydrates (glycans) show high sensitivity to pathological changes, making them promising biomarker candidates.
  • Clinical glycobiomarker discovery is hindered by the lack of high-throughput glycoanalytical workflows for large sample sets.

Purpose of the Study:

  • To develop a robotized platform for rapid, high-throughput serum-based N-glycan sample preparation.
  • To enable quantitative glycomics data generation for efficient biomarker discovery.

Main Methods:

  • Automated glycoprotein denaturation, enzymatic N-glycan release, and solid-supported hydrazide purification.
  • Fluorescent labeling of glycans for accurate quantitation using ultra-high performance liquid chromatography (UPLC).
  • Automation on an eight-channel liquid handling workstation for processing nearly 100 samples in 14 hours.

Main Results:

  • The developed platform provides a fully automated workflow for serum N-glycan sample preparation.
  • Excellent reproducibility was achieved in sample preparation.
  • The workflow significantly enhances the speed of glycoprofiling for large clinical sample sets.

Conclusions:

  • The robotized platform greatly facilitates serum-based glycobiomarker discovery.
  • High-throughput glycoprofiling is now feasible for large-scale clinical studies.
  • This advancement addresses the bottleneck in identifying novel clinical glycobiomarkers.