Hall Richard J, Patwardhan Ardan
Department of Biological Sciences, Imperial College London, London SW7 2AY, UK.
J Struct Biol. 2004 Jan-Feb;145(1-2):19-28. doi: 10.1016/j.jsb.2003.10.024.
Over recent years advances in cryo-electron microscopy for the study of macromolecular structure have resulted in resolutions in the range 10-15 A becoming routine. With this drive for increased resolution comes the need to collect larger datasets, commonly >10,000 particle images. Manual selection of particles from micrographs is often difficult and with such large numbers of particles now involved it is also laborious and a common bottleneck. Automated methods do exist but are normally restricted to specific samples or data, i.e., spherical particles, no aggregation, high contrast, and low noise. A two step approach has been developed that remains general and can be applied to low contrast, high noise micrographs of small molecules. Specifically, application of the approach is presented using micrographs of Escherichia coli RNA polymerase, which due to low contrast and the relatively small size of the molecule prove difficult to pick manually. To test the automated approach, independent reconstructions of RNA polymerase were carried out using manual and automatically picked data. The two reconstructions are shown to be comparable and the reconstruction from the automatically picked dataset is at a higher resolution, due to an increase in the number of particles picked.
近年来，用于研究大分子结构的冷冻电子显微镜技术取得了进展，使得10 - 15埃范围内的分辨率变得常规化。随着对更高分辨率的追求，需要收集更大的数据集，通常是>10,000个粒子图像。从显微照片中手动选择粒子往往很困难，而且涉及如此大量的粒子时也很费力，这是一个常见的瓶颈。虽然存在自动化方法，但通常仅限于特定的样本或数据，即球形粒子、无聚集、高对比度和低噪声。已经开发出一种两步法，该方法具有通用性，可应用于小分子的低对比度、高噪声显微照片。具体而言，本文展示了该方法在大肠杆菌RNA聚合酶显微照片中的应用，由于对比度低且分子相对较小，手动挑选这些粒子很困难。为了测试这种自动化方法，使用手动挑选的数据和自动挑选的数据对RNA聚合酶进行了独立重建。结果表明，这两种重建结果具有可比性，并且由于自动挑选的数据集中粒子数量增加，从该数据集中重建得到的分辨率更高。
