CTFFIND5 provides improved insight into quality, tilt, and thickness of TEM samples

Images taken by transmission electron microscopes are usually affected by lens aberrations and image defocus, among other factors. These distortions can be modeled in reciprocal space using the contrast transfer function (CTF). Accurate estimation and correction of the CTF is essential for restoring the high-resolution signal in cryogenic electron microscopy (cryoEM). Previously, we described the implementation of algorithms for this task in the cis TEM software package (Grant et al., 2018). Here we show that taking sample characteristics, such as thickness and tilt, into account can improve CTF estimation. This is particularly important when imaging cellular samples, where measurement of sample thickness and geometry derived from accurate modeling of the Thon ring pattern helps judging the quality of the sample. This improved CTF estimation has been implemented in CTFFIND5, a new version of the cis TEM program CTFFIND. We evaluated the accuracy of these estimates using images of tilted aquaporin crystals and eukaryotic cells thinned by focused ion beam milling. We estimate that with micrographs of sufficient quality CTFFIND5 can measure sample tilt with an accuracy of 3° and sample thickness with an accuracy of 5 nm.

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Publication Details

Journal
eLife
Published
2024-12-20
DOI
https://doi.org/10.7554/elife.97227.3
Citations
1
Primary Topic
Advanced Electron Microscopy Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.52

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article

CTFFIND5 provides improved insight into quality, tilt, and thickness of TEM samples

Nikolaus Grigorieff, Johannes Elferich, Lingli Kong, Ximena Zottig
1 citations
eLife
Advanced Electron Microscopy Techniques and Applications
0.52
article

CTFFIND5 provides improved insight into quality, tilt, and thickness of TEM samples

Nikolaus Grigorieff, Johannes Elferich, Lingli Kong, Ximena Zottig
article en
1 citations

Abstract

Images taken by transmission electron microscopes are usually affected by lens aberrations and image defocus, among other factors. These distortions can be modeled in reciprocal space using the contrast transfer function (CTF). Accurate estimation and correction of the CTF is essential for restoring the high-resolution signal in cryogenic electron microscopy (cryoEM). Previously, we described the implementation of algorithms for this task in the cis TEM software package (Grant et al., 2018). Here we show that taking sample characteristics, such as thickness and tilt, into account can improve CTF estimation. This is particularly important when imaging cellular samples, where measurement of sample thickness and geometry derived from accurate modeling of the Thon ring pattern helps judging the quality of the sample. This improved CTF estimation has been implemented in CTFFIND5, a new version of the cis TEM program CTFFIND. We evaluated the accuracy of these estimates using images of tilted aquaporin crystals and eukaryotic cells thinned by focused ion beam milling. We estimate that with micrographs of sufficient quality CTFFIND5 can measure sample tilt with an accuracy of 3° and sample thickness with an accuracy of 5 nm.

eLifeVol. 13
Howard Hughes Medical Institute (US), University of Massachusetts Chan Medical School (US)
Howard Hughes Medical Institute, Chan Zuckerberg Initiative
Openalex Percentile: Top 18%
Advanced Electron Microscopy Techniques and Applications
0.52
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