Validation of the Orthogonal Tilt Reconstruction Method with a Biological Test Sample

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Validation of the Orthogonal Tilt Reconstruction Method with a Biological Test Sample

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Title: Validation of the Orthogonal Tilt Reconstruction Method with a Biological Test Sample
Author: Chandramouli, Preethi; Hernandez-Lopez, Rogelio Antonio; Wang, Hong-Wei; Leschziner, Andres

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Citation: Chandramouli, Preethi, Rogelio A. Hernandez-Lopez, Hong-Wei Wang, and Andres E. Leschziner. 2011. Validation of the orthogonal tilt reconstruction method with a biological test sample. Journal of Structural Biology 175(1): 85-96.
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Abstract: Electron microscopy of frozen-hydrated samples (cryo-EM) can yield high resolution structures of macromolecular complexes by accurately determining the orientation of large numbers of experimental views of the sample relative to an existing 3D model. The “initial model problem”, the challenge of obtaining these orientations ab initio, remains a major bottleneck in determining the structure of novel macromolecules, chiefly those lacking internal symmetry. We previously proposed a method for the generation of initial models – orthogonal tilt reconstruction (OTR) – that bypasses limitations inherent to the other two existing methods, random conical tilt (RCT) and angular reconstitution (AR). Here we present a validation of OTR with a biological test sample whose structure was previously solved by RCT: the complex between the yeast exosome and the subunit Rrp44. We show that, as originally demonstrated with synthetic data, OTR generates initial models that do not exhibit the “missing cone” artifacts associated with RCT and show an isotropic distribution of information when compared with the known structure. This eliminates the need for further user intervention to solve these artifacts and makes OTR ideal for automation and the analysis of heterogeneous samples. With the former in mind, we propose a set of simple quantitative criteria that can be used, in combination, to select from a large set of initial reconstructions a subset that can be used as reliable references for refinement to higher resolution.
Published Version: doi:10.1016/j.jsb.2011.04.012
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