Novel HILIC-MS strategies for retention prediction and quantitative analysis of glycomic and glycoproteomic analytes
Mize, Emily Mavreen
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Liquid chromatography mass spectrometry (LC-MS) is a powerful method for glycomic and glycoproteomic research. Many recent advances in research have served to raise awareness that the ability to ascertain more refined linkage and position information is of vital importance, as structure is proving to be of critical importance to the function of a glycan. Even the smallest of changes in linkage can produce a significant change in function, therefore it is essential that analytical methods be able to reliably characterize glycans and glycoproteins. Hydrophilic interaction liquid chromatography (HILIC) is a relatively recent addition to LC methods, but has already begun to gain favor for glycan and glycoprotein analysis owing to the improvement in effective separation, particularly for isomeric and isobaric analytes. The purpose of this work is to improve analytical procedures for glycans and glycoproteins, and to that end explores several aspects of LC-MS analysis in order to enhance current methodologies. One project describes the impact degrees of sialylation has on adduct formation and the influence this has on relative and absolute quantitation via HILIC-MS analysis, demonstrating a significant increase in ammonium adduct formation in particular as the number of sialic acids increased. Quantitation via HILIC-MS with and without the use of an 15N isotopically labeled internal standard is another project detailed herein, which showed a significantly improved correlation to expected trends when the internal standard was used. The ability to partially analyze samples by way of an internal standard without compromising results was also explored, as were the consequences of incomplete analysis when an internal standard was not utilized. The development of a HILIC retention prediction model for released and procainamide labeled N-linked glycans is detailed in depth, and is shown to be capable of accurately predicting retention and differentiating between isomeric and isobaric structures. An additional retention prediction model developed for intact glycopeptides is also described, which is capable of accurate retention predictions for isomeric and isobaric glycoforms. These models demonstrated high correlation coefficients between experimental and calculated values, and were proven effective with changes to instruments and experimental parameters.