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Biomimetic Bacterial Identification Platform Based on Thermal Wave Transport Analysis (TWTA) through Surface-Imprinted Polymers
[Image: see text] This paper introduces a novel bacterial identification assay based on thermal wave analysis through surface-imprinted polymers (SIPs). Aluminum chips are coated with SIPs, serving as synthetic cell receptors that have been combined previously with the heat-transfer method (HTM) for...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5432958/ https://www.ncbi.nlm.nih.gov/pubmed/28388095 http://dx.doi.org/10.1021/acsinfecdis.7b00037 |
Sumario: | [Image: see text] This paper introduces a novel bacterial identification assay based on thermal wave analysis through surface-imprinted polymers (SIPs). Aluminum chips are coated with SIPs, serving as synthetic cell receptors that have been combined previously with the heat-transfer method (HTM) for the selective detection of bacteria. In this work, the concept of bacterial identification is extended toward the detection of nine different bacterial species. In addition, a novel sensing approach, thermal wave transport analysis (TWTA), is introduced, which analyzes the propagation of a thermal wave through a functional interface. The results presented here demonstrate that bacterial rebinding to the SIP layer resulted in a measurable phase shift in the propagated wave, which is most pronounced at a frequency of 0.03 Hz. In this way, the sensor is able to selectively distinguish between the different bacterial species used in this study. Furthermore, a dose–response curve was constructed to determine a limit of detection of 1 × 10(4) CFU mL(–1), indicating that TWTA is advantageous over HTM in terms of sensitivity and response time. Additionally, the limit of selectivity of the sensor was tested in a mixed bacterial solution, containing the target species in the presence of a 99-fold excess of competitor species. Finally, a first application for the sensor in terms of infection diagnosis is presented, revealing that the platform is able to detect bacteria in clinically relevant concentrations as low as 3 × 10(4) CFU mL(–1) in spiked urine samples. |
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