RESUMO
We present a model-based parallel algorithm for origin and orientation refinement for 3D reconstruction in cryoTEM. The algorithm is based upon the Projection Theorem of the Fourier Transform. Rather than projecting the current 3D model and searching for the best match between an experimental view and the calculated projections, the algorithm computes the Discrete Fourier Transform (DFT) of each projection and searches for the central section ("cut") of the 3D DFT that best matches the DFT of the projection. Factors that affect the efficiency of a parallel program are first reviewed and then the performance and limitations of the proposed algorithm are discussed. The parallel program that implements this algorithm, called PO(2)R, has been used for the refinement of several virus structures, including those of the 500 Angstroms diameter dengue virus (to 9.5 Angstroms resolution), the 850 Angstroms mammalian reovirus (to better than 7A), and the 1800 Angstroms paramecium bursaria chlorella virus (to 15 Angstroms).
Assuntos
Algoritmos , Microscopia Crioeletrônica/métodos , Imageamento Tridimensional/métodos , Microscopia Eletrônica de Transmissão/métodos , Vírus/ultraestrutura , Vírus da Dengue/ultraestrutura , Análise de Fourier , Modelos Moleculares , Orthoreovirus de Mamíferos/ultraestrutura , Phycodnaviridae/ultraestruturaRESUMO
The 3D reconstruction of virus structures at high resolution using CryoTEM data requires a very accurate rotational and translational alignment of individual views obtained experimentally. We discuss the geometrical foundations and the computational problems raised by rotational and translational alignment. We also outline the basic ideas for CTF correction.
Assuntos
Biologia Computacional/métodos , Processamento de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Vírus/ultraestrutura , Algoritmos , Microscopia Crioeletrônica , Elétrons , Análise de Fourier , Microscopia Eletrônica/métodos , Microscopia Eletrônica de Transmissão , Modelos Estatísticos , Vírus/químicaRESUMO
Reovirus is a useful model for addressing the molecular basis of membrane penetration by one of the larger nonenveloped animal viruses. We now report the structure of the reovirus virion at approximately 7.0 A resolution as obtained by electron cryomicroscopy and three-dimensional image reconstruction. Several features of the myristoylated outer capsid protein mu1, not seen in a previous X-ray crystal structure of the mu1-sigma3 heterohexamer, are evident in the virion. These features appear to be important for stabilizing the outer capsid, regulating the conformational changes in mu1 that accompany perforation of target membranes, and contributing directly to membrane penetration during cell entry.
Assuntos
Proteínas do Capsídeo/química , Proteínas do Capsídeo/ultraestrutura , Microscopia Crioeletrônica , Orthoreovirus/química , Orthoreovirus/ultraestrutura , Vírion/ultraestrutura , Algoritmos , Sequência de Aminoácidos , Animais , Proteínas do Capsídeo/isolamento & purificação , Cristalografia por Raios X , Análise de Fourier , Células L , Camundongos , Modelos Químicos , Modelos Moleculares , Dados de Sequência Molecular , Ácido Mirístico/metabolismo , Orthoreovirus/genética , Conformação Proteica , Estrutura Secundária de Proteína , Homologia de Sequência de Aminoácidos , Vírion/crescimento & desenvolvimentoRESUMO
Three-dimensional reconstruction of large macromolecules like viruses at resolutions below 10 A requires a large set of projection images. Several automatic and semi-automatic particle detection algorithms have been developed along the years. Here we present a general technique designed to automatically identify the projection images of particles. The method is based on Markov random field modelling of the projected images and involves a pre-processing of electron micrographs followed by image segmentation and post-processing. The image is modelled as a coupling of two fields--a Markovian and a non-Markovian. The Markovian field represents the segmented image. The micrograph is the non-Markovian field. The image segmentation step involves an estimation of coupling parameters and the maximum á posteriori estimate of the realization of the Markovian field i.e, segmented image. Unlike most current methods, no bootstrapping with an initial selection of particles is required.
Assuntos
Microscopia Crioeletrônica/métodos , Aumento da Imagem/métodos , Processamento de Imagem Assistida por Computador/métodos , Cadeias de Markov , Algoritmos , Anisotropia , Bacteriófago T4/química , Bacteriófago T4/ultraestrutura , Imageamento Tridimensional , Reconhecimento Automatizado de Padrão , Ross River virus/química , Ross River virus/ultraestrutura , Vírion/química , Vírion/ultraestruturaRESUMO
Structural biology, in particular the structure determination of viruses and other large macromolecular complexes leads to data- and compute-intensive problems that require resources well beyond those available on a single system. Thus, there is an imperative need to develop parallel algorithms and programs for clusters and computational grids. We present one of the most challenging computational problems posed by the three-dimensional structure determination of viruses, the orientation refinement.
