DANGO: An MS data annotation tool for glycolipidomics

Glycosphingolipids are essential components of all eukaryotic cells and play a major role in a broad range of cellular and biological processes, including growth, cell signaling, survival, differentiation, and disease. Glycosphingolipid structural diversity arises from heterogeneity in both the glycan and lipid moieties. Most currently available computational tools for annotating mass spectrometry data for glycosphingolipids primarily focus on glycan structure analysis, although a tool for annotating intact glycosphingolipids has recently been reported. Developing tools that integrate both glycan-centric analytical approaches and dynamic lipid composition changes, which influence functional membrane characteristics, would be highly beneficial. We have developed a glycosphingolipid computational tool, named DANGO (Data ANnotation system for GlycolipidOmics), for the automated annotation of glycolipidomic datasets. DANGO supports processing and annotation of mass spectrometry data to characterize both the glycan and lipid (ceramide) moieties (http://www.ms-dango.org/). DANGO annotates MS datasets using a glycosphingolipid database, which is created from a curated or user-defined glycan and ceramide collection, and proposes candidate structures to the user that match the experimental data. DANGO is implemented as an extension of GRITS Toolbox (http://www.grits-toolbox.org), employing functionalities such as display routines for post-processing and organized annotation of data and relevant metadata. Implementation of a novel filter algorithm in DANGO reduces false-positive identifications, resulting in enhanced reliability and shortened computational time for acquiring glycosphingolipid structural annotation. The labor-intensive manual annotation of mass spectrometry datasets has been the only approach to confident assignment of glycosphingolipid structural identity. DANGO provides intuitive workflows for enhancing the annotation of glycosphingolipidomic data.