首页 | 本学科首页   官方微博 | 高级检索  
     


Detection and differentiation of Salmonella serotypes using surface enhanced Raman scattering (SERS) technique
Authors:Jaya Sundaram  Bosoon Park  Arthur Hinton Jr  Kurt C Lawrence  Yongkuk Kwon
Affiliation:1. USDA, ARS, Russell Research Center, 950 College Station Road, Athens, GA, 30605, USA
2. Animal, Plant and Fisheries Quarantine & Inspection Agency, Anyang, Korea
Abstract:This research was conducted to prove that developed silver biopolymer nanoparticle substrate for surface enhanced Raman scattering (SERS) technique could detect and differentiate three different serotypes of Salmonella. Nanoparticle was prepared by adding 100 mg of silver nitrate to a 2 % polyvinyl alcohol solution, then adding 1 % trisodium citrate to reduce silver nitrate and produce silver encapsulated biopolymer nanoparticles. Then, nanoparticle was deposited on a stainless steel plate and used as SERS substrate. Fresh cultures of Salmonella typhimurium, Salmonella enteritidis and Salmonella infantis were washed and suspended in 10 mL of sterile deionized water. Approximately 5 μl of the bacterial suspensions were placed on the substrate individually and exposed to 785 nm laser excitation. SERS spectral data were recorded between 400 and 1,800 cm?1. SERS signals were collected from 15 different spots on the substrate for each sample. PCA model was developed to classify Salmonella serotypes. PC1 identified 92 % of the variation between the Salmonella serotypes, and PC2 identified 6 % and in total 98 % between the serotypes. Soft independent modeling of class analogies of validation set gave an average correct classification of 92 %. Comparison of the SERS spectra of Salmonella serotypes indicated that both isolates have similar cell walls and cell membrane structures which were identified by spectral regions between 520 and 1,050 cm?1. However, major differences were detected in cellular genetic material and proteins between 1,200 and 1,700 cm?1. SERS with silver biopolymer nanoparticle substrate could be a promising tool in pathogen detection and it would potentially be used to classify them.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号