Rapid identification of bacteria and yeast using surface-enhanced Raman scattering


Culha M., Kahraman M., Cam D., Sayin I., Keseroglu K.

SURFACE AND INTERFACE ANALYSIS, cilt.42, ss.462-465, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 42
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1002/sia.3256
  • Dergi Adı: SURFACE AND INTERFACE ANALYSIS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.462-465
  • İnönü Üniversitesi Adresli: Hayır

Özet

Surface-enhanced Raman scattering (SERS) is a powerful technique used for obtaining chemical information about the molecules and molecular structures in the vicinity of surfaces of noble metal nanostructures. The chemical information acquired through SERS can be used for not only characterization but also detection and identification. In a clinical setting, rapid and accurate identification of micro-organisms is critical. The biochemical information collected through the SERS spectra can be used for quick identification of micro-organisms. The concentrated silver colloidal nanoparticles (AgNPs) are simply mixed with micro-organisms after culturing, and their SERS spectra acquired. Since the nanoparticles are in contact with the cell wall of the micro-organism, the biochemical information obtained is mostly assumed as originating from the cell wall which the AgNPs are in contact with, and is considered as the 'fingerprint' of the micro-organism, which can be used for the identification. Since a SERS spectrum can be acquired only in seconds, the obtained spectrum can be used for fast micro-organism identification. The reproducibility of the spectra obtained frommicro-organisms is first tested, and then the obtained spectra are used for the goal. The identification of micro-organisms in mixtures is also attempted in model mixtures. It is demonstrated that the SERS can be used for fast and accurate identification of micro-organisms such as bacteria and yeast, even in their mixtures. Four bacteria, i.e. Shigella sonnei, Erwinia amylovara, Proteus vulgaris and DH5 alpha (E. coli strain), and three yeast cells, i.e. Hyphopichia burtonii, Candida parapsilosis and Filobasidiella neoformans are used as model micro-organisms in the study. Copyright (C) 2010 John Wiley & Sons, Ltd.