Navigating the maze of mass spectra: a machine-learning guide to identifying diagnostic ions in O-glycan analysis.

Structural details of oligosaccharides, or glycans, often carry biological relevance, which is why they are typically elucidated using tandem mass spectrometry. Common approaches to distinguish isomers rely on diagnostic glycan fragments for annotating topologies or linkages. Diagnostic fragments are often only known informally among practitioners or stem from individual studies, with unclear validity or generalizability, causing annotation heterogeneity and hampering new analysts.

Protocol for constructing glycan biosynthetic networks using glycowork.

Glycans, present across all domains of life, comprise a wide range of monosaccharides assembled into complex, branching structures. Here, we present an in silico protocol to construct biosynthetic networks from a list of observed glycans using the Python package glycowork. We describe steps for data preparation, network construction, feature analysis, and data export.

GlycoDraw: a python implementation for generating high-quality glycan figures.

Glycans are essential to all scales of biology, with their intricate structures being crucial for their biological functions. The structural complexity of glycans is communicated through simplified and unified visual representations according to the Symbol Nomenclature for Glycans (SNFGs) guidelines adopted by the community. Here, we introduce GlycoDraw, a Python-native implementation for high-throughput generation of high-quality, SNFG-compliant glycan figures with flexible display options.

Mammalian milk glycomes: Connecting the dots between evolutionary conservation and biosynthetic pathways.

Milk oligosaccharides (MOs) are among the most abundant constituents of breast milk and are essential for health and development. Biosynthesized from monosaccharides into complex sequences, MOs differ considerably between taxonomic groups. Even human MO biosynthesis is insufficiently understood, hampering evolutionary and functional analyses.

The Role of Fucose-Containing Glycan Motifs Across Taxonomic Kingdoms.

The extraordinary diversity of glycans leads to large differences in the glycomes of different kingdoms of life. Yet, while most monosaccharides are solely found in certain taxonomic groups, there is a small set of monosaccharides with widespread distribution across nearly all domains of life. These general monosaccharides are particularly relevant for glycan motifs, as they can readily be used by commensals and pathogens to mimic host glycans or hijack existing glycan recognition systems.

Glycowork: A Python package for glycan data science and machine learning.

While glycans are crucial for biological processes, existing analysis modalities make it difficult for researchers with limited computational background to include these diverse carbohydrates into workflows. Here, we present glycowork, an open-source Python package designed for glycan-related data science and machine learning by end users. Glycowork includes functions to, for instance, automatically annotate glycan motifs and analyze their distributions via heatmaps and statistical enrichment.

Mosaic Evolution of the Phosphopantothenate Biosynthesis Pathway in Bacteria and Archaea.

Phosphopantothenate is a precursor to synthesis of coenzyme A, a molecule essential to many metabolic pathways. Organisms of the archaeal phyla were shown to utilize a different phosphopantothenate biosynthetic pathway from the eukaryotic and bacterial one. In this study, we report that symbiotic bacteria from the group Candidatus poribacteria present enzymes of the archaeal pathway, namely pantoate kinase and phosphopantothenate synthetase, mirroring what was demonstrated for Picrophilus torridus, an archaea partially utilizing the bacterial pathway.