Sialoglycan microarray encoding reveals differential sialoglycan binding of phylogenetically-related bacterial AB5 toxin B subunits

Vertebrate sialic acids (Sias) display much diversity in modifications, linkages and underlying glycans. Slide microarrays allow high-throughput analysis of sialoglycan-protein interactions. The preceding paper used ~150 structurally-defined sialyltrisaccharides with various Sias and modified forms at non-reducing ends, to compare pentameric sialoglycan-recognizing bacterial toxin B subunits. Unlike the poor correlation between B subunits and species phylogeny, there is stronger correlation with Sia types prominently expressed in susceptible species. Further supporting this pattern we report a B subunit(YenB) from Yersinia enterocolitica (broad host range) recognizing almost all sialoglycans in the microarray, including 4-O-acetylated-Sias not recognized by a Y.pestis orthologue(YpeB). Differential Sia-binding patterns were also observed with phylogenetically-related B subunits from Escherichia coli(SubB), Salmonella Typhi(PltB), S. Typhimurium(ArtB), extra-intestinal E.coli(EcPltB), Vibrio cholera(CtxB), and cholera family homologue of E. coli(EcxB). Given library size, data sorting and analysis posed a challenge. We devised a 9-digit code for trisaccharides with terminal Sias and underlying two monosaccharides assigned from the non-reducing end, with three digits assigning a monosaccharide, its modifications, and linkage. This code allows logical sorting, motif searching of results, and optimizes printing. While we developed the system for the >113,000 possible linear sialyltrisaccharides, we note that a biantennary N-glycan with two terminal sialoglycan tri saccharides could have >1010 potential combinations and a triantennary N-glycan with three terminal sequences, >1015 potential combinations. While all possibilities likely do not exist in nature, sialoglycans encode enormous diversity. Thus, while glycomic approaches address these challenges, naturally-occurring toxin B subunits are simpler tools to track the dynamic sialome in biological systems.

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