Poster Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

Glycoproteomic measurement of site-specific polysialylation (#777)

Ruby Pelingon 1 , Cassandra Pegg 1 , Lucia Zacchi 1 , Toan Phung 1 , Christopher Howard 1 , Matthew Hardy 2 , Catherine Owczarek 2 , Ben Schulz 1
  1. Univeristy of Queensland, Brisbane, QUEENSLAND, Australia
  2. CSL Limited, Melbourne, Victoria, Australia

Polysialylation is the enzymatic addition of a negatively charged sialic acid polymer (>8 residues) at the terminal end of glycans. Polysialylation plays important roles through embryonic development, and is involved in neurological diseases, neural tissue regeneration, and cancer. Polysialic acid (PSA) is also researched as a potential biodegradable and non-immunogenic biomolecule conjugated to therapeutic drugs to improve their pharmacokinetics. PSA chains can vary in length, composition, and linkages. In addition, the site of polysialylation and the abundance of this modification are important determinants of protein function. PSA is difficult to analyse by mass spectrometry due to the biochemical properties of the molecule (negative charge and size). Most analytical tools available focus on determining degree of polymerization and composition, but do not address the key question of site specificity and abundance. We developed a high-throughput LC-ESI-MS/MS glycoproteomic method to measure site-specific polysialylation of glycoproteins. This method combines enzymatic (endosialidase EndoNF) and chemical (mild acid hydrolysis) elimination of PSA and sialic acids, leaving the glycan backbone intact to provide site-specificity. As proof of principle, we tested this method in polysialylated recombinant human neural cell adhesion molecule (rHuNCAM) and non-polysialylated serum purified human IgG glycoproteins (as negative control). Control untreated glycopeptides (mono/polysialylated) and desialylated glycopeptides were analysed by LC-ESI-MS/MS, and data was processed using Proteome Discoverer (v2.0.0.802, Thermo Fisher Scientific), Byonic (v2.13.17, Protein Metrics), and in-house designed scripts to identify glycopeptides and calculate relative abundance of glycoforms. This new methodology allows for the detailed comparison between polysialylated and non-polysialylated versions of glycoproteins, and it is an effective analytical method to facilitate studies of biological polysialylation and for quality control of polysialylated therapeutic proteins.