Abstract
The rapid and accurate detection of food pathogens plays a critical role in the early prevention of foodborne epidemics. Current bacteria identification practices, including colony counting, polymerase chain reaction (PCR) and immunological methods, are time consuming and labour intensive; they are not ideal for achieving the required immediate diagnosis. Different SERS substrates have been studied for the detection of foodborne microbes. The majority of the approaches are either based on costly patterning techniques on silicon or glass wafers or on methods which have not been tested in large scale fabrication. We demonstrate the feasibility of analyte specific sensing using mass-produced, polymer-based low-cost SERS substrate in analysing the chosen model microbe with biological recognition. The use of this novel roll-to-roll fabricated SERS substrate was combined with optimised gold nanoparticles to increase the detection sensitivity. Distinctive SERS spectral bands were recorded for Listeria innocua ATCC 33090 using an in-house build (785 nm) near infra red (NIR) Raman system. Results were compared to both those found in the literature and the results obtained from a commercial time-gated Raman system with a 532 nm wavelength laser excitation. The effect of the SERS enhancer metal and the excitation wavelength on the detected spectra was found to be negligible. The hypothesis that disagreements within the literature regarding bacterial spectra results from conditions present during the detection process has not been supported. The sensitivity of our SERS detection was improved through optimization of the concentration of the sample inside the hydrophobic polydimethylsiloxane (PDMS) wells. Immunomagnetic separation (IMS) beads were used to assist the accumulation of bacteria into the path of the beam of the excitation laser. With this combination we have detected Listeria with gold enhanced SERS in a label free manner from such low sample concentrations as 104 CFU ml-1.
Original language | English |
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Pages (from-to) | 62981-62989 |
Number of pages | 9 |
Journal | RSC advances |
Volume | 6 |
Issue number | 67 |
Early online date | 22 Jun 2016 |
DOIs | |
Publication status | Published - 2016 |