Structure Sorting of Multiple Macromolecular States in Heterogeneous Cryo-EM Samples by 3D Multivariate Statistical AnalysisReport as inadecuate




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Heterogeneity of biological samples is usually considered a major obstacle for three-dimensional 3D structure determination of macromolecular complexes. Heterogeneity may occur at the level of composition or conformational variability of complexes and affects most 3D structure determination methods that rely on signal averaging. Here, an approach is described that allows sorting structural states based on a 3D statistical approach, the 3D sampling and classification 3D-SC of 3D structures derived from single particles imaged by cryo electron microscopy cryo-EM. The method is based on jackknifing & bootstrapping of 3D sub-ensembles and 3D multivariate statistical analysis followed by 3D classification. The robustness of the statistical sorting procedure is corroborated using model data from an RNA polymerase structure and experimental data from a ribosome complex. It allows resolving multiple states within heterogeneous complexes that thus become amendable for a structural analysis despite of their highly flexible nature. The method has important implications for high-resolution structural studies and allows describing structure ensembles to provide insights into the dynamics of multi-component macromolecular assemblies.

KEYWORDS

Heterogeneity, Structural Biology, Cryo Electron Microscopy, Particle Sorting, Multiple States, Macromolecular Complexes, Resampling, Jackknifing, Bootstrapping, Multivariate Statistical Analysis, 3D MSA, 3D-SC, Ribosome, RNA Polymerase

Cite this paper

Klaholz, B. 2015 Structure Sorting of Multiple Macromolecular States in Heterogeneous Cryo-EM Samples by 3D Multivariate Statistical Analysis. Open Journal of Statistics, 5, 820-836. doi: 10.4236-ojs.2015.57081.





Author: Bruno P. Klaholz1,2,3,4

Source: http://www.scirp.org/



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