Revealing the human mucinome

Abstract

Mucin domains are densely O-glycosylated modular protein domains found in a wide variety of cell surface and secreted proteins. Mucin-domain glycoproteins are key players in a host of human diseases, especially cancer, but the scope of the mucinome remains poorly defined. Recently, we characterized a bacterial mucinase, StcE, and demonstrated that an inactive point mutant retains binding selectivity for mucins. In this work, we leveraged inactive StcE to selectively enrich and identify mucins from complex samples like cell lysate and crude ovarian cancer patient ascites fluid. Our enrichment strategy was further aided by an algorithm to assign confidence to mucin-domain glycoprotein identifications. This mucinomics platform facilitated detection of hundreds of glycopeptides from mucin domains and highly overlapping populations of mucin-domain glycoproteins from ovarian cancer patients. Ultimately, we demonstrate our mucinomics approach can reveal key molecular signatures of cancer from in vitro and ex vivo sources.

Exploring the glycosylation of mucins by use of O-glycodomain reporters recombinantly expressed in glycoengineered HEK293 cells

“…Glycomucinases may offer unique opportunities for use in bottom–up analysis of mucin TRs and other dense O-glycodomains ( 16 , 71 ); however, they may digest TRs into fragments that are challenging to identify and/or challenging to place in sequence context, and detailed knowledge of the cleavage specificities of these enzymes is still limited ( 72 ). StcE is a zinc metalloprotease secreted from the human pathogenic enterohemorrhagic Escherichia coli ( 73 ).…”

Benefits of Chemical Sugar Modifications Introduced by Click Chemistry for Glycoproteomic Analyses

“…10,11 That said, the field of O-glycoproteomics has seen an explosion of technical advances in the last decade. 8,[11][12][13][14][15][16] Generally, glycoproteins are enriched using lectins, antibodies, and/or solid-phase extraction (i.e. hydrophilic interaction chromatography).…”

Glycowork: A Python package for glycan data science and machine learning

“…Until now, technical limitations have directed the focus of researchers to rather short and/or uniform glycans that are amenable to manual analysis, such as N -glycans or short O -glycans. Yet with the addition of more (complex) sequences ( Malaker et al. 2021 ), and the combination of glycans with systems biology data ( Kearney et al.…”