Optimization of Surface-Protein Interactions for Next Generation Biosensors

By Brightbill, Eleanor Lyons

Georgia Institute of Technology

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Advisors: Eric Vogel, Ravi Kane, Valeria Milam, Craig Nies, Vladimir Tsukruk

Currently, diagnosis for serological diseases such as Ebola, HIV, and Lyme disease relies on enzyme-linked immunosorbent assays (ELISAs), which require centralized laboratories and several-day timescales to complete. However, emerging technologies such as potentiometric and electrochemical impedance biosensing can be developed into portable, label-free, point-of-care devices that require only hour timescales. Specifically, potentiometric sensing platforms can be miniaturized through cost-effective microfabrication, lend themselves to multiplexed and parallel sensing, and are easily integrated with other electronics. Despite the promise of these new label free technologies, device reliability inhibits commercialization and adoption. This work focuses on improving potentiometric sensing, primarily through understanding erroneous behavior at the sensor-solution interface. During biomolecular sensing, biomolecules in solution interact with the sensor surface. Ideally, protein recognition mechanisms are leveraged to allow only target proteins to attach to the surface, imparting signal selectivity. However, unwanted protein interactions with sensor surfaces cause signal instability and increase false-positive rates. Although commonly used to functionalize the sensing surface, carboxyl-terminated thiol self-assembled monolayers (COOH-SAMs) can have large defect densities, which in turn leads to large non-selective adsorption of proteins to hydrophobic surfaces exposed by these defects. A procedure is developed where the surface of COOH-SAMs is treated before functionalization to improve the reliability and quality of receptor attachment to the sensor surface. In this method, a preblocking protein orthogonal to the immunological system of interest is used to cover hydrophobic, non-selective sites on the sensor surface while still leaving carboxylic acid headgroups available for covalent functionalization. This methodology is advantageous when compared to standard blocking, where the receptor protein must be attached to the sensor prior to the blocking step. With traditional postblocking, non-selective adsorption and degradation of the receptor protein itself can occur, and the storage stability of the receptor must be considered since the sensor cannot be functionalized after blocking. Additionally, COOH-SAMs oxidize when exposed to ambient conditions. The impact of this degradation of sensing, as well as methods to prevent degradation, are explored. Beyond SAM-based sensors, there has been significant interest in biomedical applications of 2D materials, including potentiometric sensing. The inert basal plane of certain 2D materials, such as graphene, could lead to larger biosensing signals due to a decrease in surface pH response. However, there is conflicting literature on to what extent interaction from the substrate are transmitted through a 2D monolayer, and the subsequent effect on biomolecule interactions are unknown. Therefore, the degree to which the substrate influences graphene-protein interactions is explored. Finally, a section is dedicated to non-surface-layer sources of signal unreliability, including presentation of a model for sensor response time. The work presented in this thesis demonstrates initial steps towards reliable control over sensor-solution interfaces. Despite the current challenges facing label-free, portable biosensors, the work presented here provides a step towards reliable biosensing.

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Researchers should cite this work as follows:

  • Brightbill, Eleanor Lyons (2021), "Optimization of Surface-Protein Interactions for Next Generation Biosensors," https://matin.gatech.edu/resources/4139.

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