University of Oulu

S. Uusitalo, M. Kögler, A.-L. Välimaa, A. Popov, Yu. Ryabchikov, V. Kontturi, S. Siitonen, J. Petäjä, T. Virtanen, R. Laitinen, M. Kinnunen, I. Meglinski, A. Kabashin, A. Bunker, T. Viitala and J. Hiltunen, RSC Adv., 2016, 6, 62981 DOI: 10.1039/C6RA08313G

Detection of Listeria innocua on roll-to-roll produced SERS substrates with gold nanoparticles

Saved in:
Author: Uusitalo, S.1; Kögler, M.2,3; Välimaa, A.-L.4;
Organizations: 1VTT Technical Research Centre of Finland, Kaitoväylä 1, 90590 Oulu, Finland
2Centre for Drug Research, Division of Pharmaceutical Biosciences, Faculty of Pharmacy of the University of Helsinki, Finland
3Laboratory of Bioprocess Engineering, Institute of Biotechnology, Technische Universität Berlin, Ackerstr. 71-76, D-13355 Berlin, Germany
4National Resources Institute Finland (LUKE), Bio-based Business and Industry, University of Oulu, P. O. Box 413 (Paavo Havaksen Tie 3), Finland
5Optoelectronics and Measurement Techniques, Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland
6Laboratoire Lasers, Plasmas Procédés Photoniques, Aix-Marseille University (AMU), 163 Avenue de Luminy, Case 917, 13288 Marseille Cedex 09, France
7P. N. Lebedev Physical Institute of Russian Academy of Sciences, 53 Leninskii Prospekt, Moscow, Russia
8Nanocomp Oy Ltd, Ensolantie 6, 80710 Lehmo, Finland
9Lappeenranta University of Technology, School of Engineering Science, Research Group of Membrane Technology, P. O. Box 20, FI-53851 Lappeenranta, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
Persistent link:
Language: English
Published: Royal Society of Chemistry, 2016
Publish Date: 2017-07-04


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, polymerbased 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.

see all

Series: RSC advances
ISSN: 2046-2069
ISSN-E: 2046-2069
ISSN-L: 2046-2069
Volume: 6
Issue: 67
Pages: 62981 - 62989
DOI: 10.1039/C6RA08313G
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This project was funded by TEKES (the Finnish Funding Agency for Technology and Innovation) through FMA project and University of Oulu Graduate School through Infotech Oulu Doctoral Program and by Academy of Finland through FOUL- SENS (Grant No. 292253), M-SPEC (Grant No. 284907) and multi Diagnostics (Grant No. 290596). The financial support of the aforementioned institutes is gratefully acknowledged. Yury Ryabchikov acknowledges a support from COST project (ECOST-STSM-BM1205-120416-072252) for performing experiments.
Academy of Finland Grant Number: 284907
Detailed Information: 284907 (Academy of Finland Funding decision)
Copyright information: This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.