High-performance liquid chromatography coupled to mass spectrometry methodology for analyzing site-specific N-glycosylation patterns.

Analysis of protein glycosylation is a major challenge in biochemistry, here we present a nano-UHPLC-MS(MS) based methodology, which is suitable to determine site-specific N-glycosylation patterns. A few pmol glycoprotein is sufficient to determine glycosylation patterns (which opens the way for biomedical applications) and requires at least two separate chromatographic runs. One is using tandem mass spectrometry (for structure identification); the other single stage MS mode (for semi-quantitation). Analysis relies heavily on data processing. The previously developed GlycoMiner algorithm and software was used to identify glycopeptides in MS/MS spectra. We have developed a new algorithm and software (GlycoPattern), which evaluates single stage mass spectra, both in terms of glycopeptide identification (for minor glycoforms) and semi-quantitation. Identification of glycopeptide structures based on MS/MS analysis has a false positive rate of 1%. Minor glycoforms (when sensitivity is insufficient to obtain an MS/MS spectrum) can be identified in single stage MS using GlycoPattern; but in such a case the false positive rate is increased to 5%. Glycosylation is studied at the glycopeptide level (i.e. following proteolytic digestion). This way the sugar chains can be unequivocally assigned to a given glycosylation site (site-specific glycosylation pattern). Glycopeptide analysis has the further advantage that protein-specific glycosylation patterns can be identified in complex mixtures and not only in purified samples. This opens the way for medium high throughput analysis of glycosylation. Specific examples of site-specific glycosylation patterns of alpha-1-acid glycoprotein, haptoglobin and on a therapeutic monoclonal antibody, Infliximab are also discussed.