Membrane protein structure determination using cryo-electron tomography and 3D image averaging

Abstract

The vast majority of membrane protein complexes of biological interest cannot be purified to homogeneity, or removed from a physiologically relevant context without loss of function. It is therefore not possible to easily determine the 3D structures of these protein complexes using X-ray crystallography or conventional cryo-electron microscopy. Newly emerging methods that combine cryo-electron tomography with 3D image classification and averaging are, however, beginning to provide unique opportunities for in situ determination of the structures of membrane protein assemblies in intact cells and nonsymmetric viruses. Here we review recent progress in this field and assess the potential of these methods to describe the conformation of membrane proteins in their native environment.

Figure 1

Representative examples 3D architectures of membrane associated proteins determined using cryo-electron tomography combined with image averaging. (A) Nuclear pore complex [18], (B) Treponema primitia flagellar motor [20], (C) Cadherins in native epidermal desmosomes fitted with coordinates of cadherin molecules obtained by X-ray crystallography [17], (D) Bacterial chemoreceptor for serine (Tsr) fitted with coordinates for the cytoplasmic and ligand-binding domains obtained by X-ray crystallography and the HAMP domain obtained by NMR spectroscopy [19]. (E-H) Four conflicting density maps reported for the SIV/HIV-1 envelope glycoproteins from the work of Zhu et al (E, F) [22,30], Zanetti et al (G) [21] and Liu et al (H) [23].

Figure 2

Identification of two distinct receptor conformations of a membrane protein. Projection image of a whole E.coli cell engineered to overproduce the bacterial chemoreceptor for serine. Small patches of the receptor which are present in the cytoplasmic membrane are evident in the electron microscopic image recorded under low-dose illumination. From tomograms of cells such as the one shown, subvolumes corresponding to individual receptor trimers were extracted and classified to obtain two distinct receptor conformations (inset). The relative occupancy of the two states is modulated by changes in the level of serine or the extent of receptor methylation, which have opposing functional effects [24].

Figure 3

Structural heterogeneity of HIV-1 envelope glycoprotein spikes studied by image classification. (A) Tomographic slice showing Env spikes on the surface of individual HIV-1 viruses [23]. (B) Segmented rendering of a single virion highlighting the viral membrane, core and spikes; the yellow box represents the subvolume corresponding to a single spike extracted for further analysis. (C) Two-dimensional factor map representation of the three sets of spikes that were combined, shuffled and subjected to classification into 3 groups. Class 1 (green) contained 89% of volumes corresponding to unliganded Env, Class 2 (red) contained 88% of volumes corresponding to b12-bound spikes, and Class 3 (blue) contained 97% of volumes corresponding to 17b-CD4 bound spikes. (D) Corresponding class averages demonstrating the ability of image classification to successfully separate the different conformations of the HIV-1 Env trimer in this experiment (color code as before).