TY - JOUR
T1 - Automation of random conical tilt and orthogonal tilt data collection using feature-based correlation
AU - Yoshioka, Craig
AU - Pulokas, James
AU - Fellmann, Denis
AU - Potter, Clinton S.
AU - Milligan, Ronald A.
AU - Carragher, Bridget
N1 - Funding Information:
Funding for the work was provided by NIH Grant RR23093. This research was conducted at the National Resource for Automated Molecular Microscopy that is supported by the NIH through the National Center for Research Resources P41 program (RR17573). We thank Scott Stagg, Joel Quispe, and Elizabeth Wilson-Kubalek for providing grids of the COPII, GroEL, and NSF samples, respectively, and Michael Radermacher for discussion on the collection of RCT data.
PY - 2007/9
Y1 - 2007/9
N2 - Visualization by electron microscopy has provided many insights into the composition, quaternary structure, and mechanism of macromolecular assemblies. By preserving samples in stain or vitreous ice it is possible to image them as discrete particles, and from these images generate three-dimensional structures. This 'single-particle' approach suffers from two major shortcomings; it requires an initial model to reconstitute 2D data into a 3D volume, and it often fails when faced with conformational variability. Random conical tilt (RCT) and orthogonal tilt (OTR) are methods developed to overcome these problems, but the data collection required, particularly for vitreous ice specimens, is difficult and tedious. In this paper, we present an automated approach to RCT/OTR data collection that removes the burden of manual collection and offers higher quality and throughput than is otherwise possible. We show example datasets collected under stain and cryo conditions and provide statistics related to the efficiency and robustness of the process. Furthermore, we describe the new algorithms that make this method possible, which include new calibrations, improved targeting and feature-based tracking.
AB - Visualization by electron microscopy has provided many insights into the composition, quaternary structure, and mechanism of macromolecular assemblies. By preserving samples in stain or vitreous ice it is possible to image them as discrete particles, and from these images generate three-dimensional structures. This 'single-particle' approach suffers from two major shortcomings; it requires an initial model to reconstitute 2D data into a 3D volume, and it often fails when faced with conformational variability. Random conical tilt (RCT) and orthogonal tilt (OTR) are methods developed to overcome these problems, but the data collection required, particularly for vitreous ice specimens, is difficult and tedious. In this paper, we present an automated approach to RCT/OTR data collection that removes the burden of manual collection and offers higher quality and throughput than is otherwise possible. We show example datasets collected under stain and cryo conditions and provide statistics related to the efficiency and robustness of the process. Furthermore, we describe the new algorithms that make this method possible, which include new calibrations, improved targeting and feature-based tracking.
KW - Automation
KW - Cryo-electron microscopy
KW - Electron microscopy
KW - Orthogonal tilt reconstruction
KW - Random conical tilt
KW - TEM
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U2 - 10.1016/j.jsb.2007.03.005
DO - 10.1016/j.jsb.2007.03.005
M3 - Article
C2 - 17524663
AN - SCOPUS:34548309353
SN - 1047-8477
VL - 159
SP - 335
EP - 346
JO - Journal of Structural Biology
JF - Journal of Structural Biology
IS - 3
ER -