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Related Experiment Video

Updated: Jul 3, 2025

A Quantitative Glycomics and Proteomics Combined Purification Strategy

A Quantitative Glycomics and Proteomics Combined Purification Strategy

Published on: March 8, 2016

SSSMuG: Same Sample Sequential Multi-Glycomics.

Edward S X Moh¹, Sagar Dalal¹, Nicholas J DeBono¹

¹ARC Centre of Excellence in Synthetic Biology, School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, North Ryde, Sydney, New South Wales 2109, Australia.

Analytical Chemistry

|February 12, 2024

Summary

This summary is machine-generated.

We developed Same Sample Sequential Multi-Glycomics (SSSMuG) for analyzing multiple glycan classes from a single sample. This multiglycomics approach enhances glycan and protein identification for systems glycobiology.

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Area of Science:

Glycomics
Systems Biology
Analytical Chemistry

Background:

The mammalian glycome is highly complex, comprising diverse glycan classes like N- and O-linked glycans, GAGs, and GSLs.
Current analytical methods require sample prefractionation for individual glycan class analysis, limiting comprehensive glycome understanding.
There is a need for integrated approaches to study relationships between different glycan components within a biological system.

Purpose of the Study:

To develop a novel workflow for simultaneous analysis of multiple conjugated glycan classes from a single biological sample.
To enable a comprehensive understanding of the mammalian glycome by analyzing its interconnected components.
To establish a foundation for multiglycomics and systems glycobiology research.

Main Methods:

Developed Same Sample Sequential Multi-Glycomics (SSSMuG), a sequential release workflow for glycan analysis.
Utilized enzymatic or chemical release of five glycan classes (PolySia, GAGs, GSL glycans, N-glycans, O-glycans) from a single immobilized sample.
Analyzed released glycans using High-Performance Liquid Chromatography (HPLC) and Mass Spectrometry (MS).

Main Results:

SSSMuG successfully characterized multiple glycan classes and proteins from a single tissue lysate.
Compared to traditional methods, SSSMuG identified more glycans and proteins with increased analytical peak intensity.
The workflow provided improved comparative normalization of diverse glycan classes within the complex glycome.

Conclusions:

SSSMuG facilitates the simultaneous analysis of multiple glycan classes, offering a more holistic view of the glycome.
This technology represents a significant advancement in glycoanalytics, moving towards multiglycomics and systems glycobiology.
SSSMuG enables a deeper understanding of glycan structures and their biological roles by analyzing them in concert.