Stanford University
United States
Chemical Glycoproteomics
Mucins are densely O-glycosylated proteins with extended regions of clustered Ser/Thr-linked O-glycans, a structural feature that imparts a rigid and extended conformation. Their range of biological functions include physical stiffening of the glycocalyx to modulate cell survival in low adhesion settings, and biochemical interactions with glycan-binding receptors on other cells. Altered mucin expression and glycosylation patterns have been strongly linked to cancer progression. Crude measurements of these changes are currently used for cancer diagnosis but are imperfect due to their lack of molecular-level detail. A detailed map of mucin O-glycan structures and sites has been impossible to obtain, as mucins are recalcitrant to conventional mass spectrometry-based glycoproteomics methods. As a consequence, the cellular pathways underlying aberrant mucin structures are not well defined. We are pursuing these questions with the long-term goal of identifying more accurate cancer biomarkers and new therapeutic targets. During the previous funding period, we developed new mass spectrometry-based glycoproteomics methods and used them in fundamental studies of the enzymes that initiate mucin-type O-glycosylation, the polypeptide GalNAc transferases. Examples of our accomplishments include (i) development of the IsoTaG method for intact glycoproteomics via isotopic recoding and mass-independent glycopeptide discovery; (ii) identification of an optimal tandem mass spectrometry method for O-glycosite discovery; and (iii) development of a bump/hole strategy to identify biological substrates of polypeptide GalNAc transferases that initiate mucin-type Oglycosylation. In preliminary work for this application, we repurposed mucin-specific proteases (“mucinases”) from gut-resident microbes as tools for mapping O-glycosites on mucin domains. In the next funding period, we plan to develop a comprehensive “mucinomics” platform. We will use engineered mucinases as glycoform-sensitive probes of mucin expression on cells and tissues. We will also develop a mucinase-based enrichment strategy for mass spectrometry-based discovery of new mucin domain molecules as well as O-glycosite mapping. Integrated into this workflow will be newly developed ionization methods and search algorithms for O-glycosite identification. Finally, we will use the mucinomics platform to define pathways by which prevalent oncogenes drive altered mucin expression and glycosylation in cancer.