Enhanced N-Glycosylation Site Analysis of Sialoglycopeptides by Strong Cation Exchange Prefractionation Applied to Platelet Plasma Membranes

Abstract

Elucidation of post-translational modifications to proteins, such as glycosylations or phosphorylations, is one of the major issues concerning ongoing proteomics studies. To reduce general sample complexity, a necessary prerequisite is specific enrichment of peptide subsets prior to mass spectrometric sequencing. Regarding analysis of overall N-glycosylation sites in the past, this has been achieved by several approaches proving to be more or less complicated and specific. Here we present a novel strategy to target N-glycosylation sites with application to platelet membrane proteins. Initial aqueous two-phase partitioning for membrane enrichment and single step strong cation exchange-based purification of glycopeptides resulted in identification of 148 glycosylation sites on 79 different protein species. Although 69% of these sites were not annotated in the Swiss-Prot database before, a high number of 75% plasma membrane-localized proteins were analyzed. Furthermore miniaturizations and relative quantification are comprised in the developed method suggesting further use in other proteome projects.

What Can Proteomics Tell Us About Platelets?

“…Based on the literature, >2500 phosphorylation sites and >1000 other PTM have been identified in platelets. 42,99,[116][117][118]120,148 However, this information has not been coupled to the quantitative proteome. To date, there is limited evidence that the platelet protein composition may vary with age and in patients with cardiovascular or other diseases.…”

“…Yet, glycosylation patterns may dramatically influence processes such as platelet biogenesis 146 and activation. 147 To date, only few dedicated glycoproteomics studies have been conducted on human platelets, 117,118,148 identifying several hundreds of N-glycosylation sites mainly on membrane proteins. However, the advent of more sensitive and robust protocols for the enrichment and quantitative analysis of glycopeptides is promising for the future.…”

“…115 Owing to the enrichment provided by specific probes, activity-based protein profiling 116-121 B, These studies are mainly (40%) based on 2-dimensional gel electrophoresis (2-DE)/ difference gel electrophoresis (DIGE), 46,52,53,80,82,83,85,87,88,90,91,[93][94][95][96]98,102,106,110,112,113 whereas gelfree methods (23%) are still under-represented. 21,42,89,97,[114][115][116][117][118]121 Combination refers to studies using 2-DE/DIGE in combination with other approaches. COFRADIC indicates combined fractional diagonal chromatography; and MudPIT, multidimensional protein identification technology.…”

An Application of Electrostatic Repulsion Hydrophilic Interaction Chromatography in Phospho- and Glycoproteome Profiling of Epicardial Adipose Tissue in Obesity Mouse

“…So far, for protein fractionation to reduce sample complexity and increase the sensitivity, strong cation exchange (SCX) 8,9 and anion-exchange (AEX) chromatography 10 are the two most common types of chromatography. Recently, a novel mode of chromatography termed electrostatic repulsion hydrophilic interaction chromatography (ERLIC) was first introduced by Alpert for separation of biomolecules and phosphopeptide enrichment.…”

Application of proteomics to hematology: the revolution is starting

“…Although GPIbβ was already known to be regulated by protein kinase A and G (PKA/PKG; negative regulation of von Willebrand factor "Besides the brute-force search for disease biomarkers, proteomics has already delivered some important contributions to the field of blood-related diseases." [12], study of phosphorylation [24] and glycosylation [25,26]. However, as highlighted by several authors, assembling a list of proteins, even together with their list of post-translational modifications, is just the beginning of the search for the knowledge of the mechanisms of red blood cell or platelet physiology [27,28]; the next task is to aggregate these data and build functional models of metabolism, signaling or activation networks.…”