Abstract
Over the past three decades, cryogenic electron microscopy (cryo-EM) and single-particle reconstruction (SPR) techniques have evolved into a powerful toolbox for determining biological macromolecular structures. In its original form, the SPR requires a homogeneous sample, i.e., all the projection images represent identical copies of the macromolecules (Frank, Three-dimensional electron microscopy of macromolecular assemblies: visualization of biological molecules in their native state, Oxford University Press, Oxford, 2006). Recent developments in computational classification methods have made it possible to determine multiple conformations/structures of the macromolecules from cryo-EM data obtained from a single biological sample (Agirrezabala et al., Proc Natl Acad Sci 109:6094–6099, 2012; Fischer et al., Nature 466:329–333, 2010; Scheres, J Struct Biol 180:519–530, 2012). However, the existing classification methods involve different amounts of arbitrary decisions, which may lead to ambiguities of the classification results. In this work, we propose a quantitative way of analyzing the results obtained with iterative classification of cryo-EM data. Based on the logs of iterative particle classification, this analysis can provide quantitative criteria for determining the iteration of convergence and the number of distinguishable conformations/structures in a heterogeneous cryo-EM data set. To show its applicability, we tailored this analysis to the classification results of the program RELION (Scheres, Methods Enzymol 482:295–320, 2010; Scheres, J Mol Biol 415:406–418, 2011) using both benchmark and experimental data sets of ribosomes.
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Acknowledgements
The authors are grateful to Sjors Scheres, Ming Sun, and Amy Jobe for valuable comments. The authors also would like to thank Nam Ho and Melissa Thomas for their help on figure illustrations and Bob Grassucci for aid with data collection. This work is supported by the Howard Hughes Medical Institute and the National Institute of Health Grant R01 G M55440.
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Shen, B., Chen, B., Liao, H., Frank, J. (2014). Quantitative Analysis in Iterative Classification Schemes for Cryo-EM Application. In: Herman, G., Frank, J. (eds) Computational Methods for Three-Dimensional Microscopy Reconstruction. Applied and Numerical Harmonic Analysis. Birkhäuser, New York, NY. https://doi.org/10.1007/978-1-4614-9521-5_4
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DOI: https://doi.org/10.1007/978-1-4614-9521-5_4
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