De novo glycan annotation of mass spectrometry data

Carbohydrates are fundamental molecules of life and are involved in virtually all biological processes. The chemical diversity of glycans – carbohydrate chains – enables these diverse functions, but also challenges analytics. Mass spectrometry (MS) is a powerful approach to resolve and identify glycan structures. Annotation of glycans in MS data relies heavily on experimental databases or manual calculations, hindering the discovery of novel glycan compositions and structures. Here, we introduce Glyco- Annotate - a package in the open-source programming language R - for de novo annotation of glycan compositions in MS data. GlycoAnnotateR calculates all possible monomer and modification combinations, filtered against a defined set of chemical rules to provide biologically relevant compositions. The ‘glycoPredict’ function can return compositions for oligosaccharides ranging from 1-22 monomers in length while accounting for four different modifications in under ten minutes with less than 4 Gb of random-access memory (RAM). Three case studies demonstrate the efficacy and versatility of GlycoAnnotateR: (1) Analysis of commercial and synthetic mono- and oligosaccharide standards across multiple MS platforms, revealing accurate annotations of intact molecules, and fragmentation product identification; (2) On-the-fly analysis of LC-MS data guided the design of a targeted LC-MS/MS experiment that identified sulfated fucan oligosaccharides obtained by enzymatic digestion of fucoidan, a complex algal glycan; (3) Re-analysis of a published mouse lung MALDI-MS imaging dataset, reproducing and expanding annotations compared to those from a database, thereby annotating a new distribution pattern of tri-sulfated glycans. GlycoAnnotateR provides rapid, accurate annotations and com- plements existing R packages for MS data processing. This combinatorial approach enhances glycan annotation capabilities, gener- ating hypotheses and facilitating the exploration of glycan chemical diversity.