Dual-recognition surface-enhanced Raman scattering(SERS)biosensor for pathogenic bacteria detection by using vancomycin-SERS tags and aptamer-Fe3O4@Au
Autor: | Nan Wan, Zhiwei Sun, Shengqi Wang, Rui Xiao, Luoluo Shi, Yuanfeng Pang, Chongwen Wang |
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Rok vydání: | 2019 |
Předmět: |
Detection limit
Chromatography biology Chemistry Aptamer 010401 analytical chemistry Pathogenic bacteria 02 engineering and technology 021001 nanoscience & nanotechnology biology.organism_classification medicine.disease_cause 01 natural sciences Biochemistry Bacterial cell structure 0104 chemical sciences Analytical Chemistry Linear range medicine Environmental Chemistry Magnetic nanoparticles 0210 nano-technology Biosensor Spectroscopy Bacteria |
Zdroj: | Analytica Chimica Acta. 1077:288-296 |
ISSN: | 0003-2670 |
DOI: | 10.1016/j.aca.2019.05.059 |
Popis: | Rapid and reliable detection of pathogenic bacteria is vital to prevent and control bacterial diseases. In this study, we present a magnetically assisted surface-enhanced Raman scattering (SERS) biosensor based on the dual-recognition of bacterial cell by aptamer and antibiotic molecules. Aptamer-Fe3O4@Au magnetic nanoparticles (AuMNPs) were synthesized as magnetic and SERS activated substrate for specific bacteria enrichment, vancomycin-SERS tags (Au@MBA) were prepared for the sensitive quantification of pathogenic bacteria. Due to the Au-shell based dual-SERS enhancement and aptamer/vancomycin based dual-recognition ability, a detection limit of 3 cells/mL with a wide dynamic linear range from 10 to 107 cells/mL can be achieved within 50 min without other non-target bacteria interference. When applied in real samples, the approach shows recoveries from 95.0% to 106.4% with relative standard derivation (RSD) less than 5.3%. The SERS strategy could be used to detect a broad range of bacteria by using different aptamers, moreover, the simple operation and precise quantification ability empower this assay great potential in the application of food safety and infectious disease point-of-care diagnosis. |
Databáze: | OpenAIRE |
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