Discrimination between lectins with similar specificities by ratiometric profiling of binding to glycosylated surfaces; a chemical ‘tongue’ approach† †Electronic supplementary information (ESI) is available: This includes protein preparation, surface functionalisation and LDA analysis. See DOI: 10.1039/c5ra08857g Click here for additional data file

Glycan–lectin interactions drive infectious processes, but are characterized by relatively low specificity, especially for monosaccharides. Here we use multiplexed biosensing to discriminate between lectins (including cholera toxin). Carbohydrate–lectin interactions dictate a range of signalling and...

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Bibliographic Details
Published inRSC advances Vol. 5; no. 66; pp. 53172 - 53179
Main Authors Otten, L., Gibson, M. I.
Format Journal Article
LanguageEnglish
Published Royal Society of Chemistry 18.06.2015
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Summary:Glycan–lectin interactions drive infectious processes, but are characterized by relatively low specificity, especially for monosaccharides. Here we use multiplexed biosensing to discriminate between lectins (including cholera toxin). Carbohydrate–lectin interactions dictate a range of signalling and recognition processes in biological systems. The exploitation of these, particularly for diagnostic applications, is complicated by the inherent promiscuity of lectins along with their low affinity for individual glycans which themselves are challenging to access (bio)synthetically. Inspired by how a ‘tongue’ can discriminate between hundreds of flavours using a minimal set of multiplexed sensors and a training algorithm, here individual lectins are ‘profiled’ based on their unique binding profile (barcode) to a range of monosaccharides. By comparing the relative binding of a panel of 5 lectins to 3 monosaccharide-coated surfaces, it was possible to generate a training algorithm that enables correct identification of lectins, even those with similar glycan preferences. This is demonstrated to be useful for discrimination between the cholera and ricin toxin lectins showing the potential of this minimalist approach for exploiting glycan complexity.
ISSN:2046-2069
DOI:10.1039/c5ra08857g