Optimization of Electrochemical Aptamer-Based Sensors via Optimization of Probe Packing Density and Surface Chemistry
- 9 August 2008
- journal article
- research article
- Published by American Chemical Society (ACS) in Langmuir
- Vol. 24 (18), 10513-10518
- https://doi.org/10.1021/la800801v
Abstract
Electrochemical, aptamer-based (E-AB) sensors, which are comprised of an electrode modified with surface immobilized, redox-tagged DNA aptamers, have emerged as a promising new biosensor platform. In order to further improve this technology we have systematically studied the effects of probe (aptamer) packing density, the AC frequency used to interrogate the sensor, and the nature of the self-assembled monolayer (SAM) used to passivate the electrode on the performance of representative E-AB sensors directed against the small molecule cocaine and the protein thrombin. We find that, by controlling the concentration of aptamer employed during sensor fabrication, we can control the density of probe DNA molecules on the electrode surface over an order of magnitude range. Over this range, the gain of the cocaine sensor varies from 60% to 200%, with maximum gain observed near the lowest probe densities. In contrast, over a similar range, the signal change of the thrombin sensor varies from 16% to 42% and optimal signaling is observed at intermediate densities. Above cut-offs at low hertz frequencies, neither sensor displays any significant dependence on the frequency of the alternating potential employed in their interrogation. Finally, we find that E-AB signal gain is sensitive to the nature of the alkanethiol SAM employed to passivate the interrogating electrode; while thinner SAMs lead to higher absolute sensor currents, reducing the length of the SAM from 6-carbons to 2-carbons reduces the observed signal gain of our cocaine sensor 10-fold. We demonstrate that fabrication and operational parameters can be varied to achieve optimal sensor performance and that these can serve as a basic outline for future sensor fabrication.Keywords
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