Integration of Quartz Crystal Microbalance-Dissipation and Reflection-Mode Localized Surface Plasmon Resonance Sensors for Biomacromolecular Interaction Analysis
November 25, 2016
The combination of label-free, surface-sensitive measurement techniques based on different physical principles enables detailed characterization of biomacromolecular interactions at solid-liquid interfaces. To date, most combined measurement systems have involved experimental techniques with similar probing volumes, while the potential of utilizing techniques with different surface sensitivities remains largely unexplored, especially for data interpretation. Herein, we report a combined measurement approach that integrates a conventional quartz crystal microbalance-dissipation (QCM-D) setup with a reflection-mode localized surface plasmon (LSPR) sensor. Using this platform, we investigate vesicle adsorption on a titanium oxide-coated sensing substrate along with the amphipathic, α-helical (AH) peptide-induced structural transformation of surface-adsorbed lipid vesicles into a supported lipid bilayer (SLB) as a model biomacromolecular interaction. While the QCM-D and LSPR signals both detected mass uptake arising from vesicle adsorption, tracking the AH peptide-induced structural transformation revealed more complex measurement responses based on the different surface sensitivities of the two techniques. In particular, the LSPR signal recorded an increase in optical mass near the sensor surface which indicated SLB formation, whereas the QCM-D signals detected a significant loss in net acoustic mass due to excess lipid and coupled solvent leaving the probing volume. Importantly, these measurement capabilities allowed us to temporally distinguish the process of SLB formation at the sensor surface from the overall structural transformation process. Looking forward, these label-free measurement capabilities to simultaneously probe adsorbates at multiple length scales will provide new insights into complex biomacromolecular interactions.
Abdul Rahim Ferhan, Joshua A Jackman, and Nam-Joon Cho
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