journal article·2007-06Open access

Imaging large arrays of supported lipid bilayers with a macroscope

Edward T. Castellana, Paul S. Cremer

Biointerphases· Volume 2· Issue 2

Abstract

Herein, the authors present fluorescence resonance energy transfer (FRET) and two-dimensional protein saturation data acquired from spatially addressed arrays of solid supported lipid bilayers (SLBs). The SLB arrays were imaged with an epifluorescencetotal internal reflection macroscope. The macroscope allowed 1x imaging and had a relatively high numerical aperture (0.4). Such powerful light gathering and large field of view capabilities make it possible to simultaneously image dozens of addressed SLBs. Three experiments have been performed. First, a 9x7 array of supported lipid bilayer was fabricated and imaged in which each bilayer element was individually addressed. Second, a FRET assay was developed between Texas Red-DHPE (1,2-dihexadecanoyl-sn-glycero-3-phosphoethanolamine) and NBD-PE (1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine-n-(7-nitro-2-1,3-benzoxadiazol-4-yl)). The concentration of dye could be varied at each address and the value of the Forster radius (7.3+/-0.6 nm) was easily abstracted. Third, a ligandreceptor recognition assay was designed to show the two-dimensional number density of proteins which can be bound at saturation. It was found for the streptavidinbiotin pair that the protein saturated at the interface above 3 mol % biotin concentration. This corresponded to a two-dimensional footprint of 40 nm(2) for the streptavidin molecule. These results clearly open the door to using individually addressed bilayers for obtaining large amounts of biophysical data at the supported bilayeraqueous interface. Such abilities will be crucial to obtaining sufficient data for determining the interfacial mechanisms for a variety of membraneprotein interactions.
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Research context

OpenAlex topics: Lipid Membrane Structure and Behavior · Force Microscopy Techniques and Applications · Molecular Junctions and Nanostructures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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