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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.

SUBMITTER: Bartesaghi A

PROVIDER: S-EPMC2752674 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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

Bartesaghi Alberto A Subramaniam Sriram S

Current opinion in structural biology 20090729 4

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 opportu ...[more]

PMID: 19646859

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Project description:Since its discovery nearly 30 years ago, more than 60 million people have been infected with the human immunodeficiency virus (HIV) (www.usaid.gov). The virus infects and destroys CD4+ T-cells thereby crippling the immune system, and causing an acquired immunodeficiency syndrome (AIDS) (2). Infection begins when the HIV Envelope glycoprotein "spike" makes contact with the CD4 receptor on the surface of the CD4+ T-cell. This interaction induces a conformational change in the spike, which promotes interaction with a second cell surface co-receptor (5,9). The significance of these protein interactions in the HIV infection pathway makes them of profound importance in fundamental HIV research, and in the pursuit of an HIV vaccine. The need to better understand the molecular-scale interactions of HIV cell contact and neutralization motivated the development of a technique to determine the structures of the HIV spike interacting with cell surface receptor proteins and molecules that block infection. Using cryo-electron tomography and 3D image processing, we recently demonstrated the ability to determine such structures on the surface of native virus, at ˜20 Å resolution (9,14). This approach is not limited to resolving HIV Envelope structures, and can be extended to other viral membrane proteins and proteins reconstituted on a liposome. In this protocol, we describe how to obtain structures of HIV envelope glycoproteins starting from purified HIV virions and proceeding stepwise through preparing vitrified samples, collecting, cryo-electron microscopy data, reconstituting and processing 3D data volumes, averaging and classifying 3D protein subvolumes, and interpreting results to produce a protein model. The computational aspects of our approach were adapted into modules that can be accessed and executed remotely using the Biowulf GNU/Linux parallel processing cluster at the NIH (http://biowulf.nih.gov). This remote access, combined with low-cost computer hardware and high-speed network access, has made possible the involvement of researchers and students working from school or home.

Dataset Information

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

Publications

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

Similar Datasets

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