Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, United States.
Howard Hughes Medical Institute, RNA Therapeutics Institute, The University of Massachusetts Medical School, Worcester, United States.
Elife. 2021 Jun 11;10:e68946. doi: 10.7554/eLife.68946.
For a more complete understanding of molecular mechanisms, it is important to study macromolecules and their assemblies in the broader context of the cell. This context can be visualized at nanometer resolution in three dimensions (3D) using electron cryo-tomography, which requires tilt series to be recorded and computationally aligned, currently limiting throughput. Additionally, the high-resolution signal preserved in the raw tomograms is currently limited by a number of technical difficulties, leading to an increased false-positive detection rate when using 3D template matching to find molecular complexes in tomograms. We have recently described a 2D template matching approach that addresses these issues by including high-resolution signal preserved in single-tilt images. A current limitation of this approach is the high computational cost that limits throughput. We describe here a GPU-accelerated implementation of 2D template matching in the image processing software TEM that allows for easy scaling and improves the accessibility of this approach. We apply 2D template matching to identify ribosomes in images of frozen-hydrated cells with high precision and sensitivity, demonstrating that this is a versatile tool for in situ visual proteomics and in situ structure determination. We benchmark the results with 3D template matching of tomograms acquired on identical sample locations and identify strengths and weaknesses of both techniques, which offer complementary information about target localization and identity.
为了更全面地了解分子机制,研究大分子及其在细胞更广泛环境中的组装情况非常重要。电子 cryo-tomography 可在纳米分辨率下对其进行三维可视化,该技术需要记录和计算倾斜系列,目前限制了通量。此外,原始断层扫描中保留的高分辨率信号目前受到许多技术难题的限制,这导致在使用 3D 模板匹配在断层扫描中查找分子复合物时,错误阳性检测率增加。我们最近描述了一种 2D 模板匹配方法,通过包括在单倾斜图像中保留的高分辨率信号来解决这些问题。该方法目前的一个限制是计算成本高,限制了通量。我们在这里描述了图像处理软件 TEM 中 2D 模板匹配的 GPU 加速实现,这使得该方法易于扩展并提高了其可访问性。我们将 2D 模板匹配应用于冷冻水合细胞图像中的核糖体识别,具有高精度和灵敏度,证明这是原位可视化蛋白质组学和原位结构测定的多功能工具。我们将结果与在相同样本位置获取的断层扫描的 3D 模板匹配进行基准测试,并确定两种技术的优缺点,这两种技术提供了关于目标定位和身份的互补信息。