Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 12/17/2010
Publication Date: 6/20/2011
Citation: Sundaram, J., Park, B., Hinton Jr, A., Windham, W.R., Yoon, S.C., Lawrence, K.C. 2011. Rapid detection of salmonella using SERS with silver nanosubstrates. Proceedings of SPIE. 8027:B1-11.
Interpretive Summary: Conventional microbiological methods require anywhere from days to week to get results for pathogen detection. Though this method is very accurate, rapid detection of pathogens is very much in need nowadays. Many researchers have proven that Surface Enhanced Raman Scattering (SERS) can detect pathogens rapidly and accurately. In this study, a silver metal surface with biopolymer was used as a substrate. Silver nano particles encapsulated biopolymer was coated over stainless steel plates. This was used as a biopolymer metal substrate for SERS. Salmonella typhimurium, a common food pathogen, was selected for this study and were prepared in different concentrations, varied from 109 to 102 cfu/mL. Multivariate data analysis was used to develop calibration models and predict the unknown concentration.
Technical Abstract: Surface Enhanced Raman Scattering (SERS) can detect pathogens rapidly and accurately. In SERS, weak Raman scattering signals are enhanced by many orders of magnitude. In this study, silver metal with biopolymer was used as a substrate. Silver nano particles encapsulated biopolymer (polyvinyl alcohol) colloid was prepared and deposited on stainless steel plates. This was used as metal-biopolymer substrate for SERS. Salmonella typhimurium, a common food pathogen, was selected for this study. Salmonella typhimurium bacteria cells were prepared in different concentrations, ranged from 109 to 102 cfu/mL. Small amounts of these cells were loaded on to the substrates individually, scanned and spectra were recorded using a confocal Raman microscope. The cells were exposed to a laser diode at 785 nm excitation and a confocal object 50x was used to focus the laser light on the sample. Laser light scattered Raman spectra were acquired in the spectral range from 400 to 2400 cm-1. Multivariate data analysis was used to predict the concentration of unknown samples. Concentration prediction gave an R2 of 0.93 and standard error of prediction of 0.21. The results showed that it is possible to detect the Salmonella cells present in low concentrations using SERS.