Oral Presentation 26th Annual Lorne Proteomics Symposium 2021

GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis (#22)

Toan K. Phung 1 , Cassandra L. Pegg 1 , Ben L. Schulz 1 2
  1. School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, Australia
  2. ARC Training Centre for Biopharmaceutical Innovation, The University of Queensland, Brisbane, Queensland, Australia

Mass spectrometry glycoproteomics is rapidly maturing, allowing unprecedented insights into the diversity and functions of protein glycosylation. However, quantitative glycoproteomics remains challenging. We developed GlypNirO, an automated software pipeline which integrates the complementary outputs of Byonic and Proteome Discoverer to allow high-throughput automated
quantitative glycoproteomic data analysis. The output of GlypNirO is clearly structured, allowing manual interrogation, and is also appropriate for input into diverse statistical workflows. We used GlypNirO to analyse a published plasma glycoproteome dataset and identified changes in site-specific N- and O-glycosylation occupancy and structure associated with hepatocellular carcinoma as
putative biomarkers of disease.