bioRxivBiophysicsPreprint
Direct information estimation from cryo-EM Movies with CARYON
K. Ramlaul, A. Burt, N. de Martin Garrido, J. MacDonald, C. Palmer, A. Jakobi, C. H. S. Aylett
Abstract
While cryo-EM with modern direct electron detectors has proven incredibly powerful, becoming a dominant technique in structural biology, the analysis of cryo-EM images is significantly complicated by their exceptionally low signal-to-noise ratio, limiting the accuracy of the parameterisation of the physical models required for successful classification and reconstruction. Micrographs from modern direct electron detectors are typically collected as dose-fractionated multi-frame movies to allow the recording of separated individual electron impacts. These detectors improve electron detection and allow for both inter-frame motion correction, and dose-dependent image filtering, lessening the overall impact of effects deleterious to the recovery of high-resolution information. In this study we measured the information content at each spatial frequency in cryo-EM movies as it accrues during the course of an exposure. We show that, as well as correction for motion and radiation damage, the use of the information within movies allows substantially improved direct estimation of the remaining key image parameters required for accurate 3D reconstruction: the image CTF and spectral SNR. We are developing "CARYON" {insert contrived acronym here}, as a LAFTER-family filter for cryo-EM movies based upon such measurements. CARYON is intended to provide the best parameter estimation and filtration possible for a single complete, or large sub-section from a, movie micrograph without the use of a previously refined density. We demonstrate its utility in both single-particle and tomographic cryo-EM data processing.
- assay: cryo-EM
- research focus: protein structure prediction
- research focus: dimensionality reduction
- research focus: benchmarking
- research focus: software / tool
- approach: deep learning
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A particle-filter framework for robust cryoEM 3D reconstruction
Mingxu Hu, Hongkun Yu, … Xueming Li·bioRxiv·May 23, 2018
- CryoEM single particle reconstruction with a complex-valued particle stack
R. Bromberg, Y. Guo, … Z. Otwinowski·bioRxiv·Jul 28, 2022
- Topaz-Denoise: general deep denoising models for cryoEM and cryoET
Tristan Bepler, Kotaro Kelley, … Bonnie Berger·Nature CommunicationsPeer-reviewed·Oct 15, 2020
- Noise-Transfer2Clean: Denoising cryo-EM images based on noise modeling and transfer
Hongjia Li, Hui Zhang, … Fa Zhang·BioinformaticsPeer-reviewed·Jan 28, 2022
- The impact of data reduction and lossy image formats on electron microscope images
Edward T. Eng, Mykhailo Kopylov, … Clinton S. Potter·bioRxiv·Oct 24, 2018
- Toward single particle reconstruction without particle picking: Breaking the detection limit
Tamir Bendory, Nicolas Boumal, … Amit Singer·SIAM Journal on Imaging SciencesPeer-reviewed·Jun 6, 2023