SugarPy facilitates the universal, discovery-driven analysis of intact glycopeptides

Protein glycosylation is a complex post-translational modification with crucial cellular functions in all domains of life. Currently, large-scale glycoproteomics approaches rely on glycan database dependent algorithms and are thus unsuitable for discovery-driven analyses of glycoproteomes. Therefore, we devised SugarPy, a glycan database independent Python module, and validated it on the glycoproteome of human breast milk. We further demonstrated its applicability by analyzing glycoproteomes with uncommon glycans stemming from the green algae Chalmydomonas reinhardtii and the archaeon Haloferax volcanii. Finally, SugarPy facilitated the novel characterization of glycoproteins from Cyanidioschyzon merolae.