Predicting Sialic Acid Content of N-Linked Glycans Using the Isotopic Pattern of Chlorine

Sialic acids play several roles in both physiologicaland pathologicalprocesses; however, due to their labile nature, they are difficultto analyze using mass spectrometry. Previous work has shown that infraredmatrix-assisted laser desorption electrospray ionization (IR-MALDESI)is able to detect intact sialylated N-linked glycanswithout the use of chemical derivatization. In this work, we describea new rule that can predict the number of sialic acids on a glycan.Formalin-fixed paraffin-embedded human kidney tissue was preparedusing previously established methods and analyzed using IR-MALDESIin negative-ion mode mass spectrometry. Using the experimental isotopicdistribution of a detected glycan, we can predict the number of sialicacids on the glycan; #sialic acids is equal to the charge state minusthe number of chlorine adducts, or z - #Cl-. This new rule grants confident glycan annotationsand compositions beyond accurate mass measurements, thereby furtherimproving the capability of IR-MALDESI to study sialylated N-linked glycans within biological tissues.

Automated summary

This study presents a new rule that can predict the number of sialic acids on a glycan. By utilizing infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) in negative-ion mode mass spectrometry, the number of sialic acids on the glycan can be predicted based on the experimental isotopic distribution of a detected glycan. This new rule improves the capability of IR-MALDESI to analyze sialylated N-linked glycans within biological tissues, providing confident glycan annotations and compositions.