Deep Sequencing of Complex Proteoglycans: A Novel Strategy for High Coverage and Site-specific Identification of Glycosaminoglycan-linked Peptides

Proteoglycans are distributed in all animal tissues and play critical, multifaceted, physiological roles. Expressed in a spatially and temporally regulated manner, these molecules regulate interactions among growth factors and cell surface receptors and play key roles in basement membranes and other extracellular matrices. Because of the high degree of glycosylation by glycosaminoglycan (GAG), N-glycan and mucin-type O-glycan classes, the peptide sequence coverage of complex proteoglycans is revealed poorly by standard mass spectrometry-based proteomics methods. As a result, there is little information concerning how proteoglycan site specific glycosylation changes during normal and pathological processes. Here, we developed a workflow to improve sequence coverage and identification of glycosylated peptides in proteoglycans. We applied this workflow to the small leucine-rich proteoglycan decorin and three hyalectan proteoglycans: neurocan, brevican, and aggrecan. We characterized glycosylation of these proteoglycans using LC-MS methods easily implemented on instruments widely used in proteomics laboratories. For decorin, we assigned the linker-glycosite and three N-glycosylation sites. For neurocan and brevican, we identified densely glycosylated mucin-like regions in the extended domains. For aggrecan, we identified 50 linker-glycosites and mucin-type O-glycosites in the extended region and N-glycosites in the globular domains, many of which are novel and have not been observed previously. Most importantly, we demonstrate an LC-MS and bioinformatics approach that will enable routine analysis of proteoglycan glycosylation from biological samples to assess their role in pathophysiology.