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William R. Alley
Assistant Professor

Office Phone: (210) 458-5459
Office: BSE 1.104H
E-Mail: william.alley@utsa.edu

Areas of Specialization
• Bioanalytical Chemistry
• Glycomics
• Glycoproteomics/Proteomics
• Analytical Glycobiology
• Mass Spectrometry
• Separation Science

Research Interests

Our group is interested in the macromolecular physiological changes associated with disease conditions, with an emphasis on different types of cancer.  We pay particular attention to those alterations associated with various glycoconjugates (i.e. carbohydrates (commonly referred to as glycans), glycoproteins, and glycopeptides).  To study these biomolecules, we employ highly sensitive bioanalytical techniques, with liquid-chromatographic separations and mass spectrometry (MS) along with its tandem MS modes being the foundation of our methodologies.  We are actively pursuing several different research areas, including developing new techniques to improve the overall fragmentation efficiency of glycopeptides by electron-transfer dissociation (ETD).  We are also working on highly-sensitive methods to selectively enrich glycosylated molecules featuring specific monosaccharides.  We are particularly interested in sialylated structures. We are then applying these methods to investigate in more detail complex biological mixtures.  In one current study, we are building upon previous work which demonstrated that a number of fucosylated and/or sialylated glycans attached to serum proteins are significantly elevated in their abundance levels in pathological samples.  Presently, the proteins bearing these carbohydrates remain tentatively documented, at best.  We are therefore working to a) identify these proteins; b) locate their sites of glycosylation; and c) determine the influence of the disease condition on the site microheterogeneity.  Our ultimate goal is perform detailed structural investigations of cancer cell lines and tissues to identify the key cell-surface glycoproteins, quantitate their abundance levels, and compare their glycosylation patterns to control samples, as these molecules may function as more reliable biomarkers.

Selected Publications











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