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

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

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

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 zur Publikation

FachzeitschriftBioinformatics
Jahrgang / Bandnr. / Volume36
Ausgabe / Heftnr. / Issue22-23
Seitenbereich5330-5336
StatusVeröffentlicht
Veröffentlichungsjahr2020
Sprache, in der die Publikation verfasst istEnglisch
DOI10.1093/bioinformatics/btaa1042

Autor*innen der Universität Münster

Mormann, Michael
Institut für Hygiene