Journal
ELIFE
Volume 11, Issue -, Pages -Publisher
eLIFE SCIENCES PUBL LTD
DOI: 10.7554/eLife.83724
Keywords
maximum likelihood; electron tomography; subtomogram averaging; S; cerevisiae
Categories
Funding
- UK Research and Innovation [MC_UP_A025_1013, MC_UP_1201/16]
- European Research Council [648432, 852915, 692726]
- Swiss National Science Foundation [205321 _179041/1]
- UK Research and Innovation BBSRC [BB/T002670/1]
- Swiss National Science Foundation (SNF) [205321_179041] Funding Source: Swiss National Science Foundation (SNF)
- European Research Council (ERC) [648432, 852915] Funding Source: European Research Council (ERC)
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We propose a new approach for determining macromolecular structures from cryo-ET data. Unlike existing methods, our approach optimizes a regularized likelihood target that approximates a function of the 2D experimental images. Additionally, we optimize tilt-series alignments, beam-induced motions, defoci, and higher-order optical aberrations using the increased signal-to-noise ratio in the averaged structure.
We present a new approach for macromolecular structure determination from multiple particles in electron cryo-tomography (cryo-ET) data sets. Whereas existing subtomogram averaging approaches are based on 3D data models, we propose to optimise a regularised likelihood target that approximates a function of the 2D experimental images. In addition, analogous to Bayesian polishing and contrast transfer function (CTF) refinement in single-particle analysis, we describe the approaches that exploit the increased signal-to-noise ratio in the averaged structure to optimise tilt-series alignments, beam-induced motions of the particles throughout the tilt-series acquisition, defoci of the individual particles, as well as higher-order optical aberrations of the microscope. Implementation of our approaches in the open-source software package RELION aims to facilitate their general use, particularly for those researchers who are already familiar with its single-particle analysis tools. We illustrate for three applications that our approaches allow structure determination from cryo-ET data to resolutions sufficient for de novo atomic modelling.
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