日本語
 
Help Privacy Policy ポリシー/免責事項
  詳細検索ブラウズ

アイテム詳細

  Bayesian analysis of individual electron microscopy images: towards structures of dynamic and heterogeneous biomolecular assemblies

Cossio, P., & Hummer, G. (2013). Bayesian analysis of individual electron microscopy images: towards structures of dynamic and heterogeneous biomolecular assemblies. Journal of Structural Biology, 184(3), 427-437. doi:10.1016/j.jsb.2013.10.006.

Item is

基本情報

表示: 非表示:
アイテムのパーマリンク: https://hdl.handle.net/21.11116/0000-0007-0927-4 版のパーマリンク: https://hdl.handle.net/21.11116/0000-0007-0928-3
資料種別: 学術論文

ファイル

表示: ファイル

関連URL

表示:

作成者

表示:
非表示:
 作成者:
Cossio, Pilar1, 2, 著者           
Hummer, Gerhard1, 2, 著者           
所属:
1Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society, ou_2068292              
2Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, USA, ou_persistent22              

内容説明

表示:
非表示:
キーワード: Bayes Theorem, Bayesian inference, Chaperonin 60, Cryo-EM, Cryoelectron Microscopy, Crystallography, X-Ray, Disorder, Electron microscopy, Ensemble refinement, ESCRT, GroEL, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Likelihood Functions, Microscopy, Electron, Validation
 要旨: We develop a method to extract structural information from electron microscopy (EM) images of dynamic and heterogeneous molecular assemblies. To overcome the challenge of disorder in the imaged structures, we analyze each image individually, avoiding information loss through clustering or averaging. The Bayesian inference of EM (BioEM) method uses a likelihood-based probabilistic measure to quantify the consistency between each EM image and given structural models. The likelihood function accounts for uncertainties in the molecular position and orientation, variations in the relative intensities and noise in the experimental images. The BioEM formalism is physically intuitive and mathematically simple. We show that for experimental GroEL images, BioEM correctly identifies structures according to the functional state. The top-ranked structure is the corresponding X-ray crystal structure, followed by an EM structure generated previously from a superset of the EM images used here. To analyze EM images of highly flexible molecules, we propose an ensemble refinement procedure, and validate it with synthetic EM maps of the ESCRT-I-II supercomplex. Both the size of the ensemble and its structural members are identified correctly. BioEM offers an alternative to 3D-reconstruction methods, extracting accurate population distributions for highly flexible structures and their assemblies. We discuss limitations of the method, and possible applications beyond ensemble refinement, including the cross-validation and unbiased post-assessment of model structures, and the structural characterization of systems where traditional approaches fail. Overall, our results suggest that the BioEM framework can be used to analyze EM images of both ordered and disordered molecular systems.

資料詳細

表示:
非表示:
言語: eng - English
 日付: 2013-10-052013-05-022013-10-092013-10-242013-12
 出版の状態: 出版
 ページ: 11
 出版情報: -
 目次: -
 査読: 査読あり
 識別子(DOI, ISBNなど): DOI: 10.1016/j.jsb.2013.10.006
BibTex参照ID: cossio_bayesian_2013
 学位: -

関連イベント

表示:

訴訟

表示:

Project information

表示:

出版物 1

表示:
非表示:
出版物名: Journal of Structural Biology
  省略形 : J. Struct. Biol.
種別: 学術雑誌
 著者・編者:
所属:
出版社, 出版地: San Diego, CA : Elsevier
ページ: - 巻号: 184 (3) 通巻号: - 開始・終了ページ: 427 - 437 識別子(ISBN, ISSN, DOIなど): ISSN: 1047-8477
CoNE: https://pure.mpg.de/cone/journals/resource/954922650160