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Conference Paper

Automated detection of polysomes in cryoelectron tomography

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons78283

Cuellar,  L. K.
Förster, Friedrich / Modeling of Protein Complexes, Max Planck Institute of Biochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons78500

Pfeffer,  S.
Förster, Friedrich / Modeling of Protein Complexes, Max Planck Institute of Biochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons77858

Chen,  Y.
Förster, Friedrich / Modeling of Protein Complexes, Max Planck Institute of Biochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons77965

Forster,  F.
Förster, Friedrich / Modeling of Protein Complexes, Max Planck Institute of Biochemistry, Max Planck Society;

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Citation

Cuellar, L. K., Pfeffer, S., Chen, Y., & Forster, F. (2014). Automated detection of polysomes in cryoelectron tomography. In Image Processing (ICIP), 2014 IEEE International Conference on (pp. 2085-2089).


Cite as: http://hdl.handle.net/11858/00-001M-0000-0025-76AC-A
Abstract
Ribosomes and messenger RNA assemble to polysomes during protein synthesis. Cryoelectron tomography enables detection and identification of large macromolecular complexes under physiological conditions making the method uniquely suitable to study the supercomplexes that govern translation of mRNA into proteins. Here, we describe a method for automated assignment of polysomes in cryoelectron tomograms using the positions and orientations of ribosomes, as localized by template matching on tomographic data, as input. On the basis of a training dataset of expert-curated polysomes in cryoelectron tomograms, we define the relative 3D arrangements of neighboring ribosomes in polysomes. This prior distribution is used in a probabilistic framework for polysome assignment: the localized ribosomes from a tomogram are represented as a graph of which the edge weights are defined by the prior distribution. A Markov Random Field is embedded on the graph structure, and a message-passing algorithm is used to infer a polysome-label for each ribosome, i.e., to cluster ribosomes into polysomes. The performance of the method is assessed based on simulated tomograms and experimental tomograms indicating that polysome detection is reliable for typical signal-to-noise ratios of cryoelectron tomograms.