Abstract
In this article we describe a new class of high-density optical microarrays based on molecularly imprinted microsphere sensors that directly incorporate specific recognition capabilities to detect enrofloxacin (ENRO), an antibiotic widely used for both human and veterinary applications. This approach involves the preparation of highly cross-linked polymer microspheres by thermal precipitation-polymerization in the presence and absence of the target analyte ENRO to generate either molecularly imprinted (MIP) or non-imprinted polymer (NIP) microspheres, respectively. Each polymer type of tailor-made microsphere is fluorescently encoded with either coumarin-30 or tris(4,7-diphenyl-1,10-phenanthroline)ruthenium(ii) dichloride [Ru(dip)3]Cl2 to enable the microspheres to be distinguished. The new MIP-based sensing platform utilizes an optical fiber bundle containing approximately 50 000 individual 3.1 μm diameter fibers that are chemically etched to create microwells in which MIP and NIP microspheres can be deposited and imaged using an epi-fluorescence microscope. The method enables multiplexed detection by independently addressing both types of beads through their separate light channels. The unique response to the presence of ENRO is manifested on the basis of a competitive immunoassay. A red-fluorescent dye-tagged ENRO, labeled with BODIPY® TR Cadaverine, competes with ENRO for specific binding sites. The developed immuno-like assay displayed a limit of detection (LOD) of 0.04 μM (10% binding inhibition) and a dynamic range of 0.29-21.54 μM (20-80% binding inhibition). The selectivity of the assay was evaluated by measuring the cross-reactivity of other fluoroquinolones (ciprofloxacin, norfloxacin, danofloxacin, and flumequine) and non-related antibiotics (penicillin G and doxycycline). This work demonstrates, for the first time, the applicability of MIPs, as an alternative to biomolecule receptors, for the development of multiplexed detection fiber-optic microarrays paving the way for a new generation of biomimetic sensors.