Nanoplasmonic Sensing Architectures for Decoding Membrane Curvature-Dependent Biomacromolecular Interactions
Nanoplasmonic sensors have emerged as a promising measurement approach to track biomacromolecular interactions involving lipid membrane interfaces. By taking advantage of nanoscale fabrication capabilities, it is possible to design sensing platforms with various architectural configurations. Such capabilities open the door to fabricating lipid membrane-coated nanoplasmonic sensors with varying degrees of membrane curvature in order to understand how biomacromolecular interaction processes are influenced by membrane curvature. Herein, we employed an indirect nanoplasmonic sensing approach to characterize the fabrication of supported lipid bilayers (SLBs) on silica-coated nanowell and nanodisk sensing platforms and to investigate how membrane curvature influences membrane–peptide interactions by evaluating the corresponding measurement responses from different spectral signatures that are sensitive to specific regions of the sensor geometries. SLBs were prepared by the vesicle fusion method, as monitored in real-time by nanoplasmonic sensing measurements and further characterized by fluorescence recovery after photobleaching (FRAP) experiments. By resolving different spectral signatures in the nanoplasmonic sensing measurements, it was determined that peptide binding induces membrane disruption at positively curved membrane regions, while peptide binding without subsequent disruption was observed at planar and negatively curved regions. These findings are consistent with the peptide’s known preference to selectively form pores in positively curved membranes, providing validation to the nanoplasmonic sensing approach and highlighting how the integration of nanoplasmonic sensors with different nanoscale architectures can be utilized to study the influence of membrane curvature on biomacromolecular interaction processes.
Published in: Analytical Chemistry
Authors: Abdul Rahim Ferhan, Joshua A. Jackman, Bita Malekian, Kunli Xiong, Gustav Emilsson, Soohyun Park, Andreas B. Dahlin, and Nam-Joon Cho