Predicting Sialic Acid Content of

Sialic acids play several roles in both physiological and pathological processes; however, due to their labile nature, they are difficult to analyze using mass spectrometry. Previous work has shown that infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is able to detect intact sialylated N-linked glycans without the use of chemical derivatization. In this work, we describe a new rule that can predict the number of sialic acids on a glycan. Formalin-fixed paraffin-embedded human kidney tissue was prepared using previously established methods and analyzed using IR-MALDESI in negative-ion mode mass spectrometry. Using the experimental isotopic distribution of a detected glycan, we can predict the number of sialic acids on the glycan; #sialic acids is equal to the charge state minus the number of chlorine adducts, or z - #Cl-. This new rule grants confident glycan annotations and compositions beyond accurate mass measurements, thereby further improving the capability of IR-MALDESI to study sialylated N-linked glycans within biological tissues.