High Resolution in Single Particle Reconstruction

说明(申请人提供)：在这份续展申请中，重点将放在开发健壮的单粒子低温电磁分析方法上，这些方法从一开始就纳入了对结果的统计核实。我们将集中在三个具体的领域：(1)二维图像比对，(2)从头算结构确定，(3)基于数据重采样方法的大分子构象可变性的定量描述。在(1)中，一种新的基于最大似然(ML)范式的二维图像对齐方法将利用期望最大化算法并结合精确的成像模型。该方法的可行性要求极高的计算效率，这将通过在有限集上生成似然函数中的角参数来实现，这与典型电磁数据的性质一致。我们将能够通过在傅立叶调和基中使用滤波来对对齐引起的图像数据模糊进行建模来优化所提出的方法的性能。我们还提出了利用ML得到的对准参数协方差矩阵的特征分析来直接从对准信息中对图像进行分类。在(2)中，我们将通过引入附加的差异项来极大地提高先前开发的基于共线的方法的性能和可靠性，这些差异项源于考虑相交的傅立叶平面之间的二维重叠。与改进的比对算法相结合，这种方法将产生一种稳健的方法来生成初始低温EM结构，该方法将克服由于数据的低信噪比和结构异质性而造成的当前限制。在(3)中，一种新的数据重采样方法旨在克服低温电磁数据集中投影的强各向异性分布带来的限制，将允许三维重建的方差和协方差估计的自动化。通过数据重采样产生的大体积集的特征分析将被用于(直接从图像数据)计算描述大分子组装的构象模式的特征向量。通过这种特征向量分析确定的数据子集计算的结构将提供与分子功能研究相关的更高分辨率的构象模型。我们建议开发的方法不是循序渐进的改进，而是代表了解决目前阻碍单粒子低温电磁进一步发展的具体问题的新方法。为了确保最大的便携性和有效的传播，这些新方法将在目前部署的SPARX图像处理包中实施。与公众健康相关：高分辨率低温电子显微镜(CRYO-EM)已成为确定大分子复合体结构/功能的重要工具。即使在亚纳米分辨率下，冷冻-EM图也提供了丰富的结构信息，最终导致了二级结构的确定，正如我们在核糖体结构上的工作所证明的那样。此外，低温电子显微镜是一种独特的结构技术，因为它能够检测一个样品中可能包含各种构象状态的混合物的大分子组件的构象可变性。我们建议开发专用的数据处理和统计工具，用于确定数据集中的构象数目，并用于研究直接从EM数据获得的结构的构象模式。

DESCRIPTION (provided by applicant): In this renewal application, the focus will be on the development of robust single particle cryo-EM analysis methods that incorporate, from their inception, statistical verification of the results. We will concentrate on three specific areas: (1) 2-D image alignment, (2) ab initio structure determination, and (3) quantitative description of macromolecular conformational variability based on data resampling methodology. In (1), a novel 2-D image alignment approach based on the Maximum Likelihood (ML) paradigm will make use of an Expectation Maximization algorithm and incorporate a precise image formation model. The feasibility of the method requires excellent computational efficiency, which will be achieved by spanning the angular parameters in the likelihood function over a finite set, in agreement with properties of typical EM data. We will be able to optimize performance of the proposed method by using filtration in the Fourier Harmonics basis to model alignment-induced blurring of the image data. We also propose to use the eigenanalysis of the alignment parameter covariance matrix obtained from ML to classify images directly from alignment information. In (2), we will greatly improve the performance and reliability of previously developed common lines-based methodology by introducing additional discrepancy terms that follow from considering 2-D overlap between intersecting Fourier planes. In combination with improved alignment algorithms, this methodology will result in a robust approach for generation of initial cryo-EM structures that will overcome current limitations due to low Signal-to-Noise Ratio and structural heterogeneity of the data. In (3), a novel data resampling approach designed to overcome limitations arising from the strongly anisotropic distribution of projections in cryo-EM data sets will permit automation of variance and covariance estimation for 3-D reconstructions. Eigenanalysis of large volume sets generated through data resampling will be used to calculate (directly from the image data) eigenvectors describing the conformational modes of a macromolecular assembly. Structures calculated from data subsets identified through this eigenvector analysis will provide higher-resolution models of conformations relevant for studies of molecular function. Rather than incremental improvements, the methods we propose to develop represent novel approaches that address specific issues currently hindering further development of single particle cryo-EM. To assure maximum portability and efficient dissemination, these new methods will be implemented within the currently deployed SPARX image processing package. PUBLIC HEALTH RELEVANCE: High-resolution cryo-electron microscopy (cryo-EM) has become an important tool for the structure/function determination of large macromolecular complexes. Even at subnanometer resolution cryo-EM maps provide a wealth of structural information, eventually leading to determination of the secondary structure, as demonstrated by our work on the structure of the ribosome. In addition, cryo-EM is a unique structural technique in its ability to detect conformational variability of large molecular assemblies within one sample that may contain a mixture of complexes in various conformational states. We propose development of dedicated data processing and statistical tools for establishing the number of conformers in the data set, and for studies of conformational modes of the structure, as directly obtained from the EM data.