Title of presentation:
Comprehensive glycopeptide profiling in blood plasma for clinical applications
Dr. Hans Wessels specializes in translational clinical proteomics driving further development of emerging technologies contributing to healthcare. His professional career started as proteomics specialist at the Radboud University Medical Center in 2003 working on inborn errors of metabolism and biochemistry of novel microorganisms. In this time, he was key to establish the core proteomics facility of the Radboudumc. From 2010-2015, he performed his PhD research at the Nijmegen Center for Mitochondrial Disorders where he conceived and applied novel methods to study mitochondrial complexomes. Since then, he is building his own line of research on the importance of proteoforms in disease pathology at the Radboudumc Proteomics Center. Novel innovative projects include the development and implementation of Top-Down proteomics and Glycoproteomics for translational research and patient care. His track record includes over thirty publications in peer-reviewed journals, two book chapters, and he has been a speaker at various international conferences and seminars.
The vast majority of proteins in blood plasma are glycosylated. Protein glycosylation is a non-template driven multi-enzyme process that is known to be changed in many human diseases. Detailed site-specific information on the glycosylation status of glycoproteins is therefore highly desired in translational clinical research and patientcare. Comprehensive glycopeptide profiling in complex samples is however challenging with respect to sensitivity and required high-throughput identification of both glycan- and peptide-moieties. We here present an innovative glycopeptide profiling approach that overcomes many of the technological challenges. Following extensive method development we demonstrate the robustness of this approach by analyzing a cohort of healthy individuals and patients with congenital disorders of glycosylation (CDG type II). Multivariate analysis unambiguously differentiated disease subtypes and allowed for glycopeptide biomarker identification. Global glycosylation profiles and individual glycoprotein data were compared with released N-glycan and intact Transferrin LC-MS data for validation.