1,185 research outputs found

    Structure Analysis of Ice-Embedded Single Particles

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    The conventional negative-stain preparation method for electron microscopy, in which biological macromolecules are contrasted using heavy metal salts (such as uranyl-acetate), is a simple and fast technique which has helped visualize hundreds of different molecular structures. Computer analysis of such negatively stained images of individual (i.e., non-crystalline) macromolecules using statistical pattern-recognition techniques has revealed considerable new structural information. Negative staining, however, has some disadvantages: the specimens are often severely flattened (as much as 25%-75%), they often exhibit strong preferential attachment of the molecules to the supporting carbon foil, and the molecular images may be difficult to interpret due to the relatively complex nature of the interaction between molecules and stain. Embedding biological macromolecules in a layer of vitreous ice (actually: vitreous water ) represents an attractive alternative preparation method which mimics the natural environment of these molecules. The processing of ice-images often requires special computational approaches such as: multivariate statistical classification of aligned images or of invariant functions derived from the unaligned images; alignment of images belonging to a specific class of images, determination of the spatial orientations of the projection images relative to each other ( angular reconstitution ). In this paper, we discuss our own overall single-particle structure analysis approach and highlight some new methodological developments in this context

    RELION: Implementation of a Bayesian approach to cryo-EM structure determination

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    AbstractRELION, for REgularized LIkelihood OptimizatioN, is an open-source computer program for the refinement of macromolecular structures by single-particle analysis of electron cryo-microscopy (cryo-EM) data. Whereas alternative approaches often rely on user expertise for the tuning of parameters, RELION uses a Bayesian approach to infer parameters of a statistical model from the data. This paper describes developments that reduce the computational costs of the underlying maximum a posteriori (MAP) algorithm, as well as statistical considerations that yield new insights into the accuracy with which the relative orientations of individual particles may be determined. A so-called gold-standard Fourier shell correlation (FSC) procedure to prevent overfitting is also described. The resulting implementation yields high-quality reconstructions and reliable resolution estimates with minimal user intervention and at acceptable computational costs

    Validação de heterogeneidade estrutural em dados de Crio-ME por comitês de agrupadores

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    Orientadores: Fernando José Von Zuben, Rodrigo Villares PortugalDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Análise de Partículas Isoladas é uma técnica que permite o estudo da estrutura tridimensional de proteínas e outros complexos macromoleculares de interesse biológico. Seus dados primários consistem em imagens de microscopia eletrônica de transmissão de múltiplas cópias da molécula em orientações aleatórias. Tais imagens são bastante ruidosas devido à baixa dose de elétrons utilizada. Reconstruções 3D podem ser obtidas combinando-se muitas imagens de partículas em orientações similares e estimando seus ângulos relativos. Entretanto, estados conformacionais heterogêneos frequentemente coexistem na amostra, porque os complexos moleculares podem ser flexíveis e também interagir com outras partículas. Heterogeneidade representa um desafio na reconstrução de modelos 3D confiáveis e degrada a resolução dos mesmos. Entre os algoritmos mais populares usados para classificação estrutural estão o agrupamento por k-médias, agrupamento hierárquico, mapas autoorganizáveis e estimadores de máxima verossimilhança. Tais abordagens estão geralmente entrelaçadas à reconstrução dos modelos 3D. No entanto, trabalhos recentes indicam ser possível inferir informações a respeito da estrutura das moléculas diretamente do conjunto de projeções 2D. Dentre estas descobertas, está a relação entre a variabilidade estrutural e manifolds em um espaço de atributos multidimensional. Esta dissertação investiga se um comitê de algoritmos de não-supervisionados é capaz de separar tais "manifolds conformacionais". Métodos de "consenso" tendem a fornecer classificação mais precisa e podem alcançar performance satisfatória em uma ampla gama de conjuntos de dados, se comparados a algoritmos individuais. Nós investigamos o comportamento de seis algoritmos de agrupamento, tanto individualmente quanto combinados em comitês, para a tarefa de classificação de heterogeneidade conformacional. A abordagem proposta foi testada em conjuntos sintéticos e reais contendo misturas de imagens de projeção da proteína Mm-cpn nos estados "aberto" e "fechado". Demonstra-se que comitês de agrupadores podem fornecer informações úteis na validação de particionamentos estruturais independetemente de algoritmos de reconstrução 3DAbstract: Single Particle Analysis is a technique that allows the study of the three-dimensional structure of proteins and other macromolecular assemblies of biological interest. Its primary data consists of transmission electron microscopy images from multiple copies of the molecule in random orientations. Such images are very noisy due to the low electron dose employed. Reconstruction of the macromolecule can be obtained by averaging many images of particles in similar orientations and estimating their relative angles. However, heterogeneous conformational states often co-exist in the sample, because the molecular complexes can be flexible and may also interact with other particles. Heterogeneity poses a challenge to the reconstruction of reliable 3D models and degrades their resolution. Among the most popular algorithms used for structural classification are k-means clustering, hierarchical clustering, self-organizing maps and maximum-likelihood estimators. Such approaches are usually interlaced with the reconstructions of the 3D models. Nevertheless, recent works indicate that it is possible to infer information about the structure of the molecules directly from the dataset of 2D projections. Among these findings is the relationship between structural variability and manifolds in a multidimensional feature space. This dissertation investigates whether an ensemble of unsupervised classification algorithms is able to separate these "conformational manifolds". Ensemble or "consensus" methods tend to provide more accurate classification and may achieve satisfactory performance across a wide range of datasets, when compared with individual algorithms. We investigate the behavior of six clustering algorithms both individually and combined in ensembles for the task of structural heterogeneity classification. The approach was tested on synthetic and real datasets containing a mixture of images from the Mm-cpn chaperonin in the "open" and "closed" states. It is shown that cluster ensembles can provide useful information in validating the structural partitionings independently of 3D reconstruction methodsMestradoEngenharia de ComputaçãoMestre em Engenharia Elétric

    Alignment, Classification, and Three-Dimensional Reconstruction of Single Particles Embedded in Ice

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    Cryo-electron microscopy of single biological particles poses new challenges to digital image processing due to the low signal-to-noise ratio of the data. New tools have been devised to deal with important aspects of 3-D reconstruction following the random-conical data collection scheme: (a) a new shift-invariant function has been derived, which promises to facilitate alignment and classification of single particle projections; (b) a new method of orientation search is proposed, which makes it possible to relate random-conical data sets to one another prior to reconstruction; and (c) the foundation is laid for a 3-D variance estimation which utilizes the oversampling of 3-D angular space by projections in the random-conical reconstruction scheme

    Cryo-electron tomography of Kaposi\u27s sarcoma-associated herpesvirus capsids reveals dynamic scaffolding structures essential to capsid assembly and maturation.

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    Kaposi\u27s sarcoma-associated herpesvirus (KSHV) is a recently discovered DNA tumor virus that belongs to the gamma-herpesvirus subfamily. Though numerous studies on KSHV and other herpesviruses, in general, have revealed much about their multilayered organization and capsid structure, the herpesvirus capsid assembly and maturation pathway remains poorly understood. Structural variability or irregularity of the capsid internal scaffolding core and the lack of adequate tools to study such structures have presented major hurdles to earlier investigations employing more traditional cryo-electron microscopy (cryoEM) single particle reconstruction. In this study, we used cryo-electron tomography (cryoET) to obtain 3D reconstructions of individual KSHV capsids, allowing direct visualization of the capsid internal structures and systematic comparison of the scaffolding cores for the first time. We show that B-capsids are not a structurally homogenous group; rather, they represent an ensemble of B-capsid-like particles whose inner scaffolding is highly variable, possibly representing different intermediates existing during the KSHV capsid assembly and maturation. This information, taken together with previous observations, has allowed us to propose a detailed pathway of herpesvirus capsid assembly and maturation

    Unique structures in a tumor herpesvirus revealed by cryo-electron tomography and microscopy.

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    Gammaherpesviruses, including the human pathogens Epstein-Barr virus and Kaposi\u27s sarcoma-associated herpesvirus, are causative agents of lymphomas and other malignancies. The structural characterization of these viruses has been limited due to difficulties in obtaining adequate amount of virion particles. Here we report the first three-dimensional structural characterization of a whole gammaherpesvirus virion by an emerging integrated approach of cryo-electron tomography combined with single-particle cryo-electron microscopy, using murine gammaherpesvirus-68 (MHV-68) as a model system. We found that the MHV-68 virion consists of distinctive envelope and tegument compartments, and a highly conserved nucleocapsid. Two layers of tegument are identified: an inner tegument layer tethered to the underlying capsid and an outer, flexible tegument layer conforming to the overlying, pleomorphic envelope, consistent with the sequential viral tegumentation process inside host cells. Surprisingly, comparison of the MHV-68 virion and capsid reconstructions shows that the interactions between the capsid and inner tegument proteins are completely different from those observed in alpha and betaherpesviruses. These observations support the notion that the inner layer tegument across different subfamilies of herpesviruses has evolved significantly to confer specific characteristics related to viral-host interactions, in contrast to a highly conserved capsid for genome encapsidation and protection

    Superresolved Three-Dimensional Analysis of the Spatial Arrangement of the Human Immunodeficiency Virus Type-1 (HIV-1) Envelope Glycoprotein at Sites of Viral Assembly

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    Human Immunodeficiency Virus type 1 (HIV-1) replicates by forcing infected host cells to produce new virus particles, which assemble form protein components on the inner leaflet of the host cell\u27s plasma membrane. This involves incorporation of the essential viral envelope glycoprotein (Env) into a structural lattice of viral Gag proteins. The mechanism of Env recruitment and incorporation is not well understood. To better define this process, we seek to describe the timing of Env-Gag encounters during particle assembly by measuring angular positions of Env proteins about the surfaces of budding particles. Using three-dimensional superresolution microscopy, we show that Env distributions are biased toward the necks of budding particles, indicating incorporation of Env late in the assembly of the lattice. We show that this behavior is dependent on the host cell type and on the long cytoplasmic tail of Env. We propose a model wherein Env incorporation is regulated by opposing mechanisms: Gag lattice trapping of Env cytoplasmic tails, and intracellular sequestering of Env during lattice assembly

    A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0

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    We present a new approach for macromolecular structure determination from multiple particles in electron cryo-tomography (cryo-ET) data sets. Whereas existing subtomogram averaging approaches are based on 3D data models, we propose to optimise a regularised likelihood target that approximates a function of the 2D experimental images. In addition, analogous to Bayesian polishing and contrast transfer function (CTF) refinement in single-particle analysis, we describe the approaches that exploit the increased signal-to-noise ratio in the averaged structure to optimise tilt-series alignments, beam-induced motions of the particles throughout the tilt-series acquisition, defoci of the individual particles, as well as higher-order optical aberrations of the microscope. Implementation of our approaches in the open-source software package RELION aims to facilitate their general use, particularly for those researchers who are already familiar with its single-particle analysis tools. We illustrate for three applications that our approaches allow structure determination from cryo-ET data to resolutions sufficient for de novo atomic modelling.This work was funded by the UK Research and Innovation (UKRI) Medical Research Council (MC_UP_A025_1013 to SHWS; and MC_UP_1201/16 to JAGB), the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC-CoG-2014, grant 648432, MEMBRANEFUSION to JAGB and ERC StG-2019, grant 852915 CRYTOCOP to GZ); the Swiss National Science Foundation (grant 205321_179041/1 to DC-D), the Max Planck Society (to JAGB) and the UKRI Biotechnology and Biological Sciences Research Council (grant BB/T002670/1 to GZ). TAMB is a recipient of a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (202231/Z/16/Z). JZ was partially funded by the European Union’s Horizon 2020 research and innovation program (ERC-ADG-2015, grant 692726, GlobalBioIm to Michael Unser)
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