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Abstract
Over half of all cellular proteins are modified by post translational addition of oligosaccharides. Proper glycosylation plays a critical role in cell-cell communication and changes in pH, nutrient availability, and cell status results in altered cellular glycosylation profiles which have been reported in a broad range of diseases including cancer, autoimmune diseases, and type II diabetes. Vaccination development relies heavily on differential recognition of glycan variability by the immune system and they are potential biomarkers for early detection of cancer. In addition, glycans play important roles in therapeutic applications, including both treatments and diagnostics. Comprehensive characterization of the glycans on glycoproteins has become an essential element for drug development, quality control, and basic biomedical research. Manual interpretation of mass spectrometry datasets constitutes the core of most glycomics technology currently in use. However, interpretation of up to 2000 mass spectra per biological sample consumes significant expert personnel time and reduces the number of samples that can be analyzed. This bottleneck is a major impediment blocking the expansion of glycomic analysis to a broad range of basic biomedical investigations. Progress in the field has been severely restricted by the absence of appropriate computational software tools that facilitate automated structural assignment and high throughput data analysis.We have combined efforts of computer scientists, experimentalists, and mass spectrometrists in an effort to provide a semi-automated high throughput workflow aimed to fulfill this critical need.