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Ultramicroscopy. 2013 Mar;126:33-9. doi: 10.1016/j.ultramic.2012.12.009. Epub 2012 Dec 20.

Single particle and molecular assembly analysis of polyribosomes by single- and double-tilt cryo electron tomography.

Author information

1
IGBMC (Institute of Genetics and of Molecular and Cellular Biology), Department of Integrative Structural Biology, Centre National de la Recherche Scientifique (CNRS) UMR 7104/ Institut National de la Santé de la Recherche Médicale (INSERM) U964/ Université de Strasbourg, 1 rue Laurent Fries, 67404 Illkirch, France.

Abstract

Cryo electron tomography (cryo-ET) can provide cellular and molecular structural information on various biological samples. However, the detailed interpretation of tomograms reconstructed from single-tilt data tends to suffer from low signal-to-noise ratio and artefacts caused by some systematically missing angular views. While these can be overcome by sub-tomogram averaging, they remain limiting for the analysis of unique structures. Double-tilt ET can improve the tomogram quality by acquiring a second tilt series after an in-plane rotation, but its usage is not widespread yet because it is considered technically demanding and it is rarely used under cryo conditions. Here we show that double-tilt cryo-ET improves the quality of 3D reconstructions so significantly that even single particle analysis can be envisaged despite of the intrinsically low image contrast obtained from frozen-hydrated specimens. This is illustrated by the analysis of eukaryotic polyribosomes in which individual ribosomes were reconstructed using single-tilt, partial and full double-tilt geometries. The improved tomograms favour the faster convergence of iterative sub-tomogram averaging and allow a better 3D classification using multivariate statistical analysis. Our study of single particles and molecular assemblies within polysomes illustrates that the dual-axis approach is particularly useful for cryo applications of ET, both for unique objects and for structures that can be classified and averaged.

PMID:
23376404
DOI:
10.1016/j.ultramic.2012.12.009
[Indexed for MEDLINE]

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