Efficient coupling of transducin to monomeric rhodopsin in a phospholipid bilayer

G protein-coupled receptors (GPCRs) are seven transmembrane domain proteins that transduce extracellular signals across the plasma membrane and couple to the heterotrimeric family of G proteins. Like most intrinsic membrane proteins, GPCRs are capable of oligomerization, the function of which has only been established for a few different receptor systems. One challenge in understanding the function of oligomers relates to the inability to separate monomeric and oligomeric receptor complexes in membrane environments. Here we report the reconstitution of bovine rhodopsin, a GPCR expressed in the retina, into an apolipoprotein A-I phospholipid particle, derived from high density lipoprotein (HDL). We demonstrate that rhodopsin, when incorporated into these 10 nm reconstituted HDL (rHDL) particles, is monomeric and functional. Rhodopsin.rHDL maintains the appropriate spectral properties with respect to photoactivation and formation of the active form, metarhodopsin II. Additionally, the kinetics of metarhodopsin II decay is similar between rhodopsin in native membranes and rhodopsin in rHDL particles. Photoactivation of monomeric rhodopsin.rHDL also results in the rapid activation of transducin, at a rate that is comparable with that found in native rod outer segments and 20-fold faster than rhodopsin in detergent micelles. These data suggest that monomeric rhodopsin is the minimal functional unit in G protein activation and that oligomerization is not absolutely required for this process.

Bilayer Blind Deconvolution with the Light Field Camera

In this paper we propose a solution to blind deconvolution of a scene with two layers (foreground/background). We show that the reconstruction of the support of these two layers from a single image of a conventional camera is not possible. As a solution we propose to use a light field camera. We demonstrate that a single light field image captured with a Lytro camera can be successfully deblurred. More specifically, we consider the case of space-varying motion blur, where the blur magnitude depends on the depth changes in the scene. Our method employs a layered model that handles occlusions and partial transparencies due to both motion blur and out of focus blur of the plenoptic camera. We reconstruct each layer support, the corresponding sharp textures, and motion blurs via an optimization scheme. The performance of our algorithm is demonstrated on synthetic as well as real light field images.