A Glycopolymer Sensor Array That Differentiates Lectins and Bacteria.

Abstract

Identification of bacterial lectins offers an attractive route to the development of new diagnostics, but the design of specific sensors is complicated by the low selectivity of carbohydrate-lectin interactions. Here we describe a glycopolymer-based sensor array which can identify a selection of lectins with similar carbohydrate recognition preferences through a pattern-based approach. Receptors were generated using a polymer scaffold functionalized with an environmentally sensitive fluorophore, along with simple carbohydrate motifs. Exposure to lectins induced changes in the emission profiles of the receptors, enabling the discrimination of analytes using linear discriminant analysis. The resultant algorithm was used for lectin identification across a range of concentrations and within complex mixtures of proteins. The sensor array was shown to discriminate different strains of pathogenic bacteria, demonstrating its potential application as a rapid diagnostic tool to characterize bacterial infections and identify bacterial virulence factors such as production of adhesins and antibiotic resistance.