Label-Free Detection of Bacteria Using Surface-Enhanced Raman Scattering and Principal Component Analysis
Autor: | Nicoleta Elena Dina, Alia Colniţă, Ana Maria Raluca Gherman, Tiberiu Szöke-Nagy, Ionuţ Bogdan Cozar |
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Rok vydání: | 2018 |
Předmět: |
Clinical Biochemistry
Nanotechnology macromolecular substances 02 engineering and technology 01 natural sciences Biochemistry Rapid detection Analytical Chemistry symbols.namesake Electrochemistry Spectroscopy Label free biology Chemistry 010401 analytical chemistry Biochemistry (medical) technology industry and agriculture 021001 nanoscience & nanotechnology biology.organism_classification 0104 chemical sciences Principal component analysis symbols 0210 nano-technology Biosensor Bacteria Raman scattering |
Zdroj: | Analytical Letters. 52:177-189 |
ISSN: | 1532-236X 0003-2719 |
Popis: | 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 µL), 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. |
Databáze: | OpenAIRE |
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