Rohou Alexis, Grigorieff Nikolaus
Department of Biochemistry, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA 02454, USA; Janelia Farm Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
Department of Biochemistry, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA 02454, USA; Janelia Farm Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
J Struct Biol. 2014 May;186(2):234-44. doi: 10.1016/j.jsb.2014.03.012. Epub 2014 Mar 20.
The structures of many helical protein filaments can be derived from electron micrographs of their suspensions in thin films of vitrified aqueous solutions. The most successful and generally-applicable approach treats short segments of these filaments as independent "single particles", yielding near-atomic resolution for rigid and well-ordered filaments. The single-particle approach can also accommodate filament deformations, yielding sub-nanometer resolution for more flexible filaments. However, in the case of thin and flexible filaments, such as some amyloid-β (Aβ) fibrils, the single-particle approach may fail because helical segments can be curved or otherwise distorted and their alignment can be inaccurate due to low contrast in the micrographs. We developed new software called Frealix that allows the use of arbitrarily short filament segments during alignment to approximate even high curvatures. All segments in a filament are aligned simultaneously with constraints that ensure that they connect to each other in space to form a continuous helical structure. In this paper, we describe the algorithm and benchmark it against datasets of Aβ(1-40) fibrils and tobacco mosaic virus (TMV), both analyzed in earlier work. In the case of TMV, our algorithm achieves similar results to single-particle analysis. In the case of Aβ(1-40) fibrils, we match the previously-obtained resolution but we are also able to obtain reliable alignments and ∼8-Å reconstructions from curved filaments. Our algorithm also offers a detailed characterization of filament deformations in three dimensions and enables a critical evaluation of the worm-like chain model for biological filaments.
许多螺旋状蛋白质细丝的结构可从其在玻璃化水溶液薄膜中的悬浮液的电子显微照片中推导出来。最成功且普遍适用的方法是将这些细丝的短片段视为独立的“单颗粒”,对于刚性且有序排列的细丝可实现近原子分辨率。单颗粒方法也能适应细丝的变形,对于更灵活的细丝可实现亚纳米分辨率。然而,对于细且灵活的细丝,如某些淀粉样β(Aβ)原纤维,单颗粒方法可能会失败,因为螺旋片段可能会弯曲或以其他方式扭曲,并且由于显微照片中的低对比度,它们的排列可能不准确。我们开发了名为Frealix的新软件,该软件允许在排列过程中使用任意短的细丝片段来近似甚至高曲率。细丝中的所有片段同时进行排列,并受到约束,以确保它们在空间中相互连接形成连续的螺旋结构。在本文中,我们描述了该算法,并针对Aβ(1 - 40)原纤维和烟草花叶病毒(TMV)的数据集对其进行基准测试,这两个数据集在早期工作中都已进行过分析。对于TMV,我们的算法取得了与单颗粒分析相似的结果。对于Aβ(1 - 40)原纤维,我们达到了先前获得的分辨率,但我们还能够从弯曲的细丝中获得可靠的排列和约8埃的重建。我们的算法还提供了细丝三维变形的详细表征,并能够对生物细丝的蠕虫状链模型进行关键评估。