Label-Free Detection of Bacteria Using Surface-Enhanced Raman Scattering and Principal Component Analysis

被引:10
|
作者
Cozar, Ionut Bogdan [1 ]
Colnita, Alia [1 ]
Szoke-Nagy, Tiberiu [1 ,2 ,3 ]
Gherman, Ana Maria Raluca [1 ,4 ]
Dina, Nicoleta Elena [1 ]
机构
[1] Natl Inst Res & Dev Isotop & Mol Technol, Dept Mol & Biomol Phys, Donat 67-103, Cluj Napoca 400293, Romania
[2] Babes Bolyai Univ, Fac Biol & Geol, Cluj Napoca, Romania
[3] Branch Natl Inst Res & Dev Biol Sci Bucharest, Inst Biol Res Cluj Napoca, Cluj Napoca, Romania
[4] Babes Bolyai Univ, Fac Phys, Cluj Napoca, Romania
关键词
Bacteria; label-free detection; principal component analysis (PCA); single-cell; surface-enhanced Raman scattering (SERS) mapping; SINGLE-CELL ANALYSIS; BACILLUS-CEREUS; SILVER NANOPARTICLES; ESCHERICHIA-COLI; RAPID DETECTION; SERS DETECTION; SPECTROSCOPY; IDENTIFICATION; INFORMATION; DISCRIMINATION;
D O I
10.1080/00032719.2018.1445747
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Recently, the possibility of creating surface-enhanced Raman scattering (SERS)-based biosensors for rapid detection of bacteria has been widely explored. For this purpose, we used ultrasensitive SERS spectroscopy to detect and identify common bacteria's spectral profiles in different experimental conditions: using in situ-synthesized silver colloids (Bacteria@AgNPs) and incubation of the biomass in silver colloids. Moreover, a label-free SERS-based detection protocol was optimized and the influences of taxonomic affiliation and time-dependent effects of incubation in silver colloid were monitored. Label-free detection and identification at single-cell level of common pathogens (Escherichia coli, Aeromonas hydrophila, and Bacillus cereus) were assessed using SERS mapping under the optimized experimental conditions. High-accuracy principal component analysis (PCA) was used for discrimination at strain level of the tested bacterial species. The reduced volume of sample required (3 mu L), rapid spectral acquisition (within minutes), and the use of SERS mapping at single-cell level provide an ideal candidate for developing SERS-based biosensors for food safety, water research, and health care real-life applications.
引用
收藏
页码:177 / 189
页数:13
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