کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
2029694 | 1070947 | 2014 | 10 صفحه PDF | دانلود رایگان |
• AC3D is a powerful method for classification of cryoelectron subtomograms
• A near-perfect classification result is achieved for realistic simulations
• AC3D recovers known structural heterogeneity of ribosomes in experimental data
• AC3D detects structurally distinct protein translocon populations
SummaryClassification of subtomograms obtained by cryoelectron tomography (cryo-ET) is a powerful approach to study the conformational landscapes of macromolecular complexes in situ. Major challenges in subtomogram classification are the low signal-to-noise ratio (SNR) of cryo-tomograms, their incomplete angular sampling, the unknown number of classes and the typically unbalanced abundances of structurally distinct complexes. Here, we propose a clustering algorithm named AC3D that is based on a similarity measure, which automatically focuses on the areas of major structural discrepancy between respective subtomogram class averages. Furthermore, we incorporate a spherical-harmonics-based fast subtomogram alignment algorithm, which provides a significant speedup. Assessment of our approach on simulated data sets indicates substantially increased classification accuracy of the presented method compared to two state-of-the-art approaches. Application to experimental subtomograms depicting endoplasmic-reticulum-associated ribosomal particles shows that AC3D is well suited to deconvolute the compositional heterogeneity of macromolecular complexes in situ.
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Journal: - Volume 22, Issue 10, 7 October 2014, Pages 1528–1537