Group 30: Sequencing the Glycome
Lead Contributor for Webpage: Tyler Houchin
Lead Contributor for Webpage: Tyler Houchin
Welcome to our project, "Sequencing the Glycome". We are dedicated to advancing the understanding and characterization of glycans, an important class of biomolecules that play central roles in various biological functions and diseases. Glycans can exist as free carbohydrates or attached to a protein (forming a glycoprotein) or lipid (forming a glycolipid), adding additional functionality and complexities to these molecules. Despite their crucial role, rapid and accurate profiling of glycans has always been a challenge. This project aims to address this gap in glycan research by using innovative computational and experimental methods.
Our endeavor is two-fold: developing a computational workflow to analyze lectin sequences and experimentally testing deglycosylation of model lectins.
The computational aspect of our project focuses on analyzing lectin sequences to determine the conservation of N-glycosylation sites. These sites serve as potential points where glycans can be removed from a lectin to reduce self-binding without affecting overall protein integrity.
Simultaneously, we carry out experimental wet lab experiments to fully deglycosylate model lectins, determining if deglycosylation affects binding activity. Together, these approaches aim to guide rationale modification of lectins for optimized use in glycan sequencing.
We summarize our project under two main objectives:
Computational - Addresses which glycans can be removed
Develop a computational workflow that can be used to analyze conservation of lectin sequences
Identify lectins with conserved and non-conserved glycans
Wet Lab - Addresses if lectin binding is dependent on glycans
Optimize methods to deglycosylate N-linked glycans on proteins
Investigate effect of deglycosylation on lectin binding ability
Our work involves extensive computational analysis, database curation, extraction of glycosylation information, and multiple sequence alignment. We also visually represent the physical location of glycosylation sites using Pymol, a Python library for protein structures.
Experimentally, we performed enzymatic deglycosylation of lectins, SDS-PAGE, gel staining for proteins and glycoproteins, and ELISA for functional analysis of lectins.
Our computational pipeline provides a valuable insight into the conservation of specific glycan motifs in lectins. This data guides the studies to probe the importance of individual sites and the consequences of their removal.
Our experimental results confirm that the presence of glycans on lectins, like SNA, is critical for their ability to bind to target glycans. Complete deglycosylation may not be a viable option as it can remove crucial conserved glycans. Therefore, site-specific modifications of non-conserved sites would be a more optimal approach to generate lectins that self-bind less.