Development of computational methods for exploration of cryo-electron tomograms

低温电子断层成像(CET)以其独特的三维成像能力，使其成为现代结构生物学中重要的成像手段。冷冻水化样品的三维(3-D)密度是根据其投影来近似的，这些投影是使用透射电子显微镜(TEM)从顺序倾斜的样品中获得的。在这里，我们建议开发计算方法，以提高从冷冻电子断层扫描数据得出的三维重建的准确性。首先，我们将实现一种新的算法，将二维(2-D)瞬变电磁图像配准到公共坐标系。特别是，这种方法关注的是样本体积的较小区域，而不是整个成像区域。这种方法可以补偿光束引起的样品改变，这是目前从CET获得高分辨率的最大挑战。由于配准算法不依赖于基准标记，因此对于使用聚焦离子束制备的样品的分析将特别重要，并且它能够进一步实现层析重建的自动化。其次，我们将实现一种新的迭代方法，从配准的二维图像重建三维体。有三个特点表明，该方法将产生比目前使用的方法更准确的重建：(I)非均匀傅立叶变换允许高度精确的内插和使用适当考虑实验几何的度量；(Ii)正则化避免了像CET中那样对低信噪比数据的噪声过度拟合；(Iii)对样本形状的真实空间限制允许部分恢复实验中无法访问的结构数据(缺失的楔形)。第三，我们将把这种重建方法整合到现有的框架中，用于统计分析描绘特定大分子复合体的单拷贝的亚断层图像。亚断层图像分析包括相干对准和平均以获得比单个噪声断层图像高得多的分辨率的平均密度，以及根据所描述的复合体的结构差异对亚断层图像进行分类。具体地说，我们将使用不同的3-D重建进行比对/分类和平均。最后，开发的方法将被广泛记录，并将编写适当的教程，以最大限度地发挥算法在科学界的价值。总而言之，本提案中开发的方法将使人们能够更详细地了解络合物在其原始环境中的结构以及它们的构象变化。

Cryo-electron tomography (CET) has the unique ability to image macromolecular complexes in their native environment in three dimensions, making it an important imaging modality in modern structural biology. The three-dimensional (3-D) density of the frozen-hydrated sample is approximated from its projections, which are acquired from the sequentially tilted specimen using a transmission electron microscope (TEM). Here, we suggest developing computational methods that improve the accuracy of 3-D reconstructions derived from cryo-electron tomographic data. Firstly, we will implement a novel algorithm for registration of the two-dimensional (2-D) TEM images to a common coordinate system. In particular, this approach focuses on smaller areas of the specimen volume rather than the whole imaged area. This approach allows compensation for beam-induced alteration of the sample, currently arguably the biggest challenge for obtaining high-resolution from CET. Since the registration algorithm does not rely on fiducial markers it will be of particular importance for the analysis of samples prepared using a focused ion beam and it enables further automation of tomographic reconstruction. Secondly, we will implement a novel iterative method for reconstruction of the 3-D volume from the registered 2-D images. Three features suggest that the methodology will yield substantially more accurate reconstructions than approaches currently used: (i) nonuniform Fourier transforms allows highly accurate interpolation and the use of a metric that considers the geometry of the experiment appropriately; (ii) regularization avoids overfitting to noise for data with low signal-to-noise ratios as in CET; (iii) real space constraints on the shape of the specimen allow partial restoration of structural data that are inaccessible in the experiment (missing wedge). Thirdly, we will integrate this reconstruction methodology into existing frameworks for the statistical analysis of subtomograms depicting single copies of specific macromolecular complexes. Subtomogram analysis involves coherent alignment and averaging to obtain averaged densities with much higher resolution than the individual noisy tomograms, as well as classification of subtomograms according to structural differences of the depicted complexes. Specifically, we will use distinct 3-D reconstructions for alignment/classification and averaging. Finally, the developed methodology will be extensively documented and suitable tutorials will be compiled to maximize the value of the algorithms in the scientific community. In summary, the methodology developed in this proposal will enable much more detailed insights into the structures of complexes in their native settings as well as their conformational changes.