Fluorometric Detection of Salmonella in Water Using a Cell Imprinted Polymer Thin Film-based Microfluidic Sensor

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Most imprinted polymer-based bacterial sensors rely on microparticles as recognition elements, which pose challenges in handling, integration, and consistency in real-world applications. This study introduces a novel fluorometric microfluidic biosensor using cell-imprinted polymer (CIP) thin films for Salmonella detection in water. The CIP was fabricated by mixing Salmonella cells into a pre-polymer solution containing four functional monomers. Non-imprinted polymer (NIP) solution was prepared by eliminating the template bacteria. The CIP and NIP pre-polymers were injected into a pair of laser-cut parallel microchannels, UV‑cured, and washed to form complementary bacterial binding cavities in CIP. A second pair of microchannels with fluid inlets and outlets were bonded orthogonally to the CIP/NIP microchannels, allowing for fluid handling and bacterial exposure (10 1 -10 8 CFU/mL) within the sensor. Exposure to FITC dye post bacteria capture and fluorescence quantification showed an increase in signal intensity proportional to Salmonella concentration. The sensor exhibited a detection limit of 1.47×10 3 CFU/mL and a linear dynamic range from 10 3 to 10 7 CFU/mL. Specificity assays showed that CIP differentiated target bacteria from non-target species at 10 7 CFU/mL, but with moderate selectivity. Competitive binding experiments further confirmed the sensor’s capability to differentiate Salmonella from E. coli and Sarcina at 10 7 CFU/mL. Future optimization of polymer composition and microfluidic design is required to enhance sensitivity and selectivity. Overall, this work shows that combining CIPs with a simple microfluidic fluorescence setup is an effective way to build low-cost, portable sensors for real-time whole-cell bacterial detection.

Article activity feed