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

Schulze S, Oltmanns A, Fufezan C, Kraegenbring J, Mormann M, Pohlschroeder M, Hippler M

Research article (journal) | Peer reviewed

Abstract

Motivation: 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. Results: 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 alga Chlamydomonas reinhardtii and the archaeon Haloferax volcanii. SugarPy also facilitated the novel characterization of glycoproteins from the red alga Cyanidioschyzon merolae.

Details about the publication

JournalBioinformatics
Volume36
Issue22-23
Page range5330-5336
StatusPublished
Release year2020
Language in which the publication is writtenEnglish
DOI10.1093/bioinformatics/btaa1042

Authors from the University of Münster

Mormann, Michael
Institute of Hygiene