EcoSP

EcoSP provides a comprehensive repository of Escherichia coli surface polysaccharide antigen data, covering O-antigen and K-antigen serotypes, coding-region sequences, glycosyltransferases, structural compositions, and biosynthetic pathways to support analyses of SP diversity and biosynthesis.

Key Features:

• Extensive data collection: Derived from a systematic analysis of 7,741 Escherichia coli genomic sequences to capture SP diversity.
• Monosaccharide composition analysis: Reports predominance of D-hexopyranose and that 70–80% of strains have polysaccharides composed primarily of the five most common hexoses or their combinations.
• Glycosidic linkage insights: Quantifies linkage prevalence, noting α-1,3 and β-1,3 bonds at 23.15% and 20.49%, respectively.
• Role of UDP: Documents that uridine diphosphate (UDP) activates over 50% of monosaccharides for glycosyltransferase reactions involved in SP biosynthesis.
• Structural and pathway annotations: Includes structural information and detailed biosynthetic pathway data for O-antigens and K-antigens.
• Polysaccharide and GT analysis: Summarizes and analyzes polysaccharide antigen properties and glycosyltransferases (GTs) across strains.
• Integration into chassis cells: Identifies common pathways and structures to facilitate integration of SP biosynthetic pathways into chassis cells for enhanced glycan biosynthesis.
• Serotype analysis and GT annotation: Provides capability for serotype analysis and glycosyltransferase annotation of known and novel E. coli sequences.

Scientific Applications:

• Diagnostics and typing: Supports serotype-based diagnostics and typing of Escherichia coli through serotype analysis and GT annotation.
• Vaccine design: Informs design of glycan-based vaccines by providing antigen structural and compositional data.
• Synthetic glycobiology: Enables selection of pathways and GTs for engineering glycan biosynthesis in chassis cells.
• Pathogenesis research: Facilitates study of bacterial pathogenic mechanisms by linking SP structures and biosynthetic genes to strain variation.

Methodology:

Built via a systematic data-mining analysis of 7,741 E. coli genomic sequences to identify common monosaccharides, glycosidic linkages, glycosyltransferases, and biosynthetic pathways.