N-Glycoproteomics – An automated workflow approach

Abstract

Glycan decorations dictate protein functions and thus have crucial importance in life sciences. Previously glycoprotein analysis was mainly focused on the analysis of the liberated glycans allowing detailed structural, but lacking positional information. Analysis of intact glycopeptides required purified glycoproteins and manual interpretation of spectra. We developed an approach where mixtures of native glycopeptides were analyzed with tandem mass spectrometry and the spectra were analyzed with automated in silico workflows. The latter included combination of the original spectra, generation of a human N-glycopeptide library, matching the glycopeptide spectra to the theoretical peptide fragments, scoring the observations, predicting the glycan composition, which were then matched against the observed spectra, statistical validation of the results with target-decoy filtering, and finally the calculation of glycan structures. We verified this approach with the 150 serotransferrin glycopeptide spectra, where we automatically generated 10(5) putative interpretations from >10(9) theoretical glycopeptides. After scoring 62 glycopeptide spectra obtained validated interpretation with concomitant amino acid sequences, glycan compositions, and structures. When applying this method to an unknown mixture of human plasma glycoproteins we identified 80 glycopeptides with their glycan compositions or structures. Instead of weeks and months of interpretation work of mass spectrometry files our automated workflow can be executed in few hours and provide information concomitantly from both the amino acid and glycan moieties of intact glycopeptides in mixtures. No advanced computational skills were needed to use these preformed and tested workflows. In case users want to add complexity to the analysis they are allowed to alter all parameters and rebuild the workflows.