Department of Biomedical Engineering, School of Biological Sciences and Medical Engineering, Southeast University.
Department of Biomedical Engineering, School of Biological Sciences and Medical Engineering, Southeast University;
J Vis Exp. 2024 May 10(207). doi: 10.3791/64845.
Efficient methods for the extraction of features of interest remain one of the biggest challenges for the interpretation of cryo-electron tomograms. Various automated approaches have been proposed, many of which work well for high-contrast datasets where the features of interest can be easily detected and are clearly separated from one another. Our inner ear stereocilia cryo-electron tomographic datasets are characterized by a dense array of hexagonally packed actin filaments that are frequently cross-connected. These features make automated segmentation very challenging, further aggravated by the high-noise environment of cryo-electron tomograms and the high complexity of the densely packed features. Using prior knowledge about the actin bundle organization, we have placed layers of a highly simplified ball-and-stick actin model to first obtain a global fit to the density map, followed by regional and local adjustments of the model. We show that volumetric model building not only allows us to deal with the high complexity, but also provides precise measurements and statistics about the actin bundle. Volumetric models also serve as anchoring points for local segmentation, such as in the case of the actin-actin cross connectors. Volumetric model building, particularly when further augmented by computer-based automated fitting approaches, can be a powerful alternative when conventional automated segmentation approaches are not successful.
对于冷冻电子断层图像的解释，提取感兴趣特征的有效方法仍然是最大的挑战之一。已经提出了各种自动化方法，其中许多方法适用于高对比度数据集，在这些数据集中，可以轻松检测到感兴趣的特征，并且它们彼此之间清晰分开。我们内耳静纤毛的冷冻电子断层图像数据集的特征是排列紧密的六方排列的肌动蛋白丝，这些肌动蛋白丝经常相互交联。这些特征使得自动分割变得非常具有挑战性，冷冻电子断层图像的高噪声环境和密集排列特征的高度复杂性进一步加剧了这种情况。利用关于肌动蛋白束组织的先验知识，我们将一层高度简化的球棍肌动蛋白模型放置到位，首先对密度图进行全局拟合，然后对模型进行区域和局部调整。我们表明，体积模型构建不仅使我们能够处理高复杂性，还提供了关于肌动蛋白束的精确测量和统计信息。体积模型还可以作为局部分割的锚定点，例如在肌动蛋白-肌动蛋白连接点的情况下。当传统的自动分割方法不成功时，体积模型构建，特别是当进一步增强基于计算机的自动拟合方法时，可以成为一种强大的替代方法。
