Development and application of lectin affinity selection for monitoring changes in glycoproteins with disease state
The major focus of the work in this thesis was to develop quantitative proteomic methods for the analysis of post translational modifications using a bottom-up approach including the optimization lectin selection of glycopeptides for proteomic applications. This thesis evaluated diagonal chromatography as a method for the identification of peptides containing post translational modifications such as phosphorylation and N-linked glycosylation. With a well chosen ion pairing agent, diagonal chromatography was able to differentiate between phosphorylated and non-phosphorylated peptides. However, diagonal chromatography proved to be unable to adequately identify glycopeptides therefore lectin affinity targeting was explored in this thesis. The optimal parameters for lectin selection of glycopeptides from a proteomic sample were determined including immobilization procedure, divalent cation concentration, and binding and elution buffer conditions. A serial lectin affinity selection was applied to a human pooled serum sample to determine the relative fucose content of serum proteins. Finally, lectin affinity selection for glycopeptides was applied to a canine model of arthritis to quantify changes in glycoproteins in sera that are potentially disease-associated. Inter-individual differences in protein concentration of serum proteins from two healthy individuals were compared to the differences between a healthy and arthritic individual. The healthy individuals showed relatively small changes in protein concentration between the two patients whereas; the arthritic individual demonstrated a large change in concentration of several cytokines.
Regnier, Purdue University.
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