GIPS-Mix for Accurate Identification of Isomeric Components in Glycan Mixtures Using Intelligent Group-Opting Strategy

Accurate identification of glycan structures is highly
desirable
as they are intimately linked to their different functions. However,
glycan samples generally exist as mixtures with multiple isomeric
structures, making assignment of individual glycan components very
challenging, even with the aid of multistage mass spectrometry (MSn). Here, we present an approach, GIPS-mix, for assignment
of isomeric glycans within a mixture using an intelligent group-opting
strategy. Our approach enumerates all possible combinations (groupings)
of candidate glycans and opts in the best-matched glycan group(s)
based on the similarity between the simulated spectra of each glycan
group and the acquired experimental spectra of the mixture. In the
case that a single group could not be elected, a tie break is performed
by additional MSn scanning using intelligently selected
precursors. With 11 standard mixtures and 6 human milk oligosaccharide
fractions, we demonstrate the application of GIPS-mix in assignment
of individual glycans in mixtures with high accuracy and efficiency.