This application addresses NIGMS PAR-17-045 ?Focused Technology Research and Development (R01)?. This initiative supports projects that focus solely on development of technologies with the potential to enable biomedical research. Dysregulation of the cellular microenvironment occurs in cancers, neurodevelopmental and neuropsychiatric diseases. Known as the matrisome, the set of extracellular matrix and cell surface molecules control the availability of growth factors to cellular receptors and the mechanical-physical properties of the cell microenvironment. Currently, the limited understanding of regulation of matrisome glycosylation hinders understanding of the roles of glycosylation-dependent matrisome networks in the basic mechanisms necessary for targeted intervention of many diseases. Matrisome function depends on networks of interaction among glycosylated proteins and glycan-binding lectins. It is not possible using present proteomics and glycoproteomics methods to compare using rigorous statistics similarities of glycoproteins that differ by disease-related changes in site-specific glycosylation. We propose to develop technologies to meet this need. Present proteomics methods quantify proteins using a few representative peptides per gene product; sequence coverage for most proteins is low. Such low sequence coverage does not suffice to reconstruct the predominant glycosylated proteoforms active in a biological context. We propose to develop technologies to compare glycoprotein similarities among biological sample sets. To do this, we will develop MS acquisition and bioinformatics methods for rapid, sensitive and reproducible mapping of glycoprotein glycosylation to enable statistically rigorous comparison of glycoprotein similarities. By making these technologies available, we will enable a new level of understanding of the roles of matrisome networks in human diseases.
The matrisome consists of glycosylated extracellular matrix and cell surface proteins that surround cells and support normal physiological activity. While it is known that glycosylation changes during disease processes, it has not been possible to quantitatively compare glycoprotein structure among biological samples. We aim to develop technologies to meet this need.
