Tandem Mass Spectrometry of Sulfated Heparin-Like Glycosaminoglycan Oligosaccharides
- 17 April 2003
- journal article
- research article
- Published by American Chemical Society (ACS) in Analytical Chemistry
- Vol. 75 (10) , 2445-2455
- https://doi.org/10.1021/ac0263418
Abstract
The structural characterization of heparin-like glycosaminoglycans (HLGAGs) is a major challenge in glycobiology. These linear, sulfated oligosaccharides are expressed on animal cell surfaces, in extracellular matrixes, basement membranes, and mast cell granules and bind with varying degrees of specificity to families of proteases, growth factors, chemokines, and blood coagulation proteins. Cell surface HLGAGs bind growth factors and growth factor receptors and serve as coreceptors in these interactions. Understanding of the mechanism and regulation of growth factor−receptor binding requires efficient determination of cell surface HLGAG structures and the variations in their expression in response to the cellular environment. The solution to this problem entails rapid, sensitive structural analysis of these molecules. To date, HLGAG sequencing requires multistep processes that combine chemical and enzymatic degradation with gel-based or mass spectrometry-based detection systems. Although tandem mass spectrometry has revolutionized proteomics, the fragility of sulfate groups has limited its usefulness in the analysis of HLGAGs. This work demonstrates that tandem mass spectrometry can be effectively used to determine HLGAG structures while minimizing losses of SO3. First, collision-induced dissociation (CID) is shown to produce abundant backbone cleavage ions for HLGAG oligosaccharides, provided that most sulfate groups are deprotonated. Fragmentation of different precursor ion charge states produces complementary data on the structure of the HLGAG. Second, calcium ion complexation of HLGAGs stabilizes the sulfate groups, increases the relative abundances of backbone cleavage ions, and decreases the abundances of ions produced from SO3 losses.Keywords
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