Selective Discrimination of Key Enzymes of Pathogenic and Nonpathogenic Bacteria on Autonomously Reporting Shape-Encoded Hydrogel Patterns.

This work reports on a new approach to rapidly and selectively detect and discriminate enzymes of pathogenic from those of nonpathogenic bacteria using a patterned autonomously reporting hydrogel on a transparent support, in which the selectivity has been encoded by the pattern shape to enable facile detection by a color change at one single wavelength. In particular, enzyme-responsive chitosan hydrogel layers that report the presence of the enzymes β-glucuronidase (β-Gus) and β-galactosidase (β-Gal), produced by the nonvirulent Escherichia coli K12 and the food-borne biosafety level 3 pathogen enterohemorrhagic E. coli, respectively, via the blue color of an indigo dye were patterned by two complementary strategies. The comparison of the functionalization of patterned chitosan patches on a solid support with two chromogenic substrates on one hand and the area-selective conjugation of the substrates on the other hand showed that the two characteristic enzymes could indeed be rapidly and selectively discriminated. The limits of detection of the highly stable sensing layers for an observation time of 60 min using a spectrophotometer correspond to enzyme concentrations of β-Gus and β-Gal of ≤5 and ≤3 nM, respectively, and to ≤62 and ≤33 nM for bare eye detection in nonoptimized sensor patches. These results confirm the applicability of this approach, which is compatible with the simple measurement of optical density at one single wavelength only as well as with parallel, multiplexed detection, to differentiate the enzymes secreted by a highly pathogenic E. coli from a nonpathogenic E. coli on the basis of specifically secreted enzymes. Hence, a general approach for the rapid and selective detection of enzymes of different bacterial species for potential applications in food safety as well as point-of-care microbiological diagnostics is described.